From c3b2a8cb2755c1456746c03c9935a38970ad1503 Mon Sep 17 00:00:00 2001
From: Kent Keirsey <31807370+hipsterusername@users.noreply.github.com>
Date: Thu, 8 Feb 2024 22:37:52 -0500
Subject: [PATCH 001/411] Quick Seamless Fixes

---
 invokeai/backend/model_management/seamless.py | 87 ++++++++-----------
 1 file changed, 34 insertions(+), 53 deletions(-)

diff --git a/invokeai/backend/model_management/seamless.py b/invokeai/backend/model_management/seamless.py
index bfdf9e0c53..3ab2db1d90 100644
--- a/invokeai/backend/model_management/seamless.py
+++ b/invokeai/backend/model_management/seamless.py
@@ -28,68 +28,49 @@ def _conv_forward_asymmetric(self, input, weight, bias):
 def set_seamless(model: Union[UNet2DConditionModel, AutoencoderKL], seamless_axes: List[str]):
     try:
         to_restore = []
+        skipped_layers = 0
+        skip_second_resnet = True
+        skip_conv2 = True
 
         for m_name, m in model.named_modules():
-            if isinstance(model, UNet2DConditionModel):
-                if ".attentions." in m_name:
+            if not isinstance(m, (nn.Conv2d, nn.ConvTranspose2d)):
+                continue
+
+            if isinstance(model, UNet2DConditionModel) and m_name.startswith("down_blocks.") and ".resnets." in m_name:
+                # down_blocks.1.resnets.1.conv1
+                _, block_num, _, resnet_num, submodule_name = m_name.split(".")
+                block_num = int(block_num)
+                resnet_num = int(resnet_num)
+
+                # if block_num >= seamless_down_blocks:
+                if block_num >= len(model.down_blocks) - skipped_layers:
                     continue
 
-                if ".resnets." in m_name:
-                    if ".conv2" in m_name:
-                        continue
-                    if ".conv_shortcut" in m_name:
-                        continue
-
-            """
-            if isinstance(model, UNet2DConditionModel):
-                if False and ".upsamplers." in m_name:
+                if resnet_num > 0 and skip_second_resnet:
                     continue
 
-                if False and ".downsamplers." in m_name:
+                if submodule_name == "conv2" and skip_conv2:
                     continue
 
-                if True and ".resnets." in m_name:
-                    if True and ".conv1" in m_name:
-                        if False and "down_blocks" in m_name:
-                            continue
-                        if False and "mid_block" in m_name:
-                            continue
-                        if False and "up_blocks" in m_name:
-                            continue
+            m.asymmetric_padding_mode = {}
+            m.asymmetric_padding = {}
+            m.asymmetric_padding_mode["x"] = "circular" if ("x" in seamless_axes) else "constant"
+            m.asymmetric_padding["x"] = (
+                m._reversed_padding_repeated_twice[0],
+                m._reversed_padding_repeated_twice[1],
+                0,
+                0,
+            )
+            m.asymmetric_padding_mode["y"] = "circular" if ("y" in seamless_axes) else "constant"
+            m.asymmetric_padding["y"] = (
+                0,
+                0,
+                m._reversed_padding_repeated_twice[2],
+                m._reversed_padding_repeated_twice[3],
+            )
 
-                    if True and ".conv2" in m_name:
-                        continue
-
-                    if True and ".conv_shortcut" in m_name:
-                        continue
-
-                if True and ".attentions." in m_name:
-                    continue
-
-                if False and m_name in ["conv_in", "conv_out"]:
-                    continue
-            """
-
-            if isinstance(m, (nn.Conv2d, nn.ConvTranspose2d)):
-                m.asymmetric_padding_mode = {}
-                m.asymmetric_padding = {}
-                m.asymmetric_padding_mode["x"] = "circular" if ("x" in seamless_axes) else "constant"
-                m.asymmetric_padding["x"] = (
-                    m._reversed_padding_repeated_twice[0],
-                    m._reversed_padding_repeated_twice[1],
-                    0,
-                    0,
-                )
-                m.asymmetric_padding_mode["y"] = "circular" if ("y" in seamless_axes) else "constant"
-                m.asymmetric_padding["y"] = (
-                    0,
-                    0,
-                    m._reversed_padding_repeated_twice[2],
-                    m._reversed_padding_repeated_twice[3],
-                )
-
-                to_restore.append((m, m._conv_forward))
-                m._conv_forward = _conv_forward_asymmetric.__get__(m, nn.Conv2d)
+            to_restore.append((m, m._conv_forward))
+            m._conv_forward = _conv_forward_asymmetric.__get__(m, nn.Conv2d)
 
         yield
 

From 3339ad4df80f250c0f19779fdb8561f0353c5fc4 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 13 Feb 2024 13:34:06 +1100
Subject: [PATCH 002/411] feat(nodes): seamless.py minor cleanup

---
 invokeai/backend/model_management/seamless.py | 22 +++++++++----------
 1 file changed, 11 insertions(+), 11 deletions(-)

diff --git a/invokeai/backend/model_management/seamless.py b/invokeai/backend/model_management/seamless.py
index 3ab2db1d90..e145c6f481 100644
--- a/invokeai/backend/model_management/seamless.py
+++ b/invokeai/backend/model_management/seamless.py
@@ -1,10 +1,11 @@
 from __future__ import annotations
 
 from contextlib import contextmanager
-from typing import List, Union
+from typing import Callable, List, Union
 
 import torch.nn as nn
-from diffusers.models import AutoencoderKL, UNet2DConditionModel
+from diffusers.models.autoencoders.autoencoder_kl import AutoencoderKL
+from diffusers.models.unets.unet_2d_condition import UNet2DConditionModel
 
 
 def _conv_forward_asymmetric(self, input, weight, bias):
@@ -26,12 +27,9 @@ def _conv_forward_asymmetric(self, input, weight, bias):
 
 @contextmanager
 def set_seamless(model: Union[UNet2DConditionModel, AutoencoderKL], seamless_axes: List[str]):
+    # Callable: (input: Tensor, weight: Tensor, bias: Optional[Tensor]) -> Tensor
+    to_restore: list[tuple[nn.Conv2d | nn.ConvTranspose2d, Callable]] = []
     try:
-        to_restore = []
-        skipped_layers = 0
-        skip_second_resnet = True
-        skip_conv2 = True
-
         for m_name, m in model.named_modules():
             if not isinstance(m, (nn.Conv2d, nn.ConvTranspose2d)):
                 continue
@@ -42,14 +40,16 @@ def set_seamless(model: Union[UNet2DConditionModel, AutoencoderKL], seamless_axe
                 block_num = int(block_num)
                 resnet_num = int(resnet_num)
 
-                # if block_num >= seamless_down_blocks:
-                if block_num >= len(model.down_blocks) - skipped_layers:
+                # Could be configurable to allow skipping arbitrary numbers of down blocks
+                if block_num >= len(model.down_blocks):
                     continue
 
-                if resnet_num > 0 and skip_second_resnet:
+                # Skip the second resnet (could be configurable)
+                if resnet_num > 0:
                     continue
 
-                if submodule_name == "conv2" and skip_conv2:
+                # Skip Conv2d layers (could be configurable)
+                if submodule_name == "conv2":
                     continue
 
             m.asymmetric_padding_mode = {}

From 8a147bd6e6ccb336ca5eeecf5a70c8b667724d4b Mon Sep 17 00:00:00 2001
From: Jennifer Player <chainchompa@gmail.com>
Date: Tue, 13 Feb 2024 11:53:49 -0500
Subject: [PATCH 003/411] added sortable to linear view, not saving yet

---
 invokeai/frontend/web/package.json            |  1 +
 invokeai/frontend/web/pnpm-lock.yaml          | 15 +++++++
 .../features/dnd/components/AppDndContext.tsx |  2 +
 .../web/src/features/dnd/types/index.ts       | 14 ++++++-
 .../Invocation/fields/LinearViewField.tsx     | 13 +++++++
 .../sidePanel/workflow/WorkflowLinearTab.tsx  | 39 +++++++++++++------
 .../src/features/nodes/store/workflowSlice.ts |  7 ++++
 7 files changed, 78 insertions(+), 13 deletions(-)

diff --git a/invokeai/frontend/web/package.json b/invokeai/frontend/web/package.json
index e583169af7..cd95183c7a 100644
--- a/invokeai/frontend/web/package.json
+++ b/invokeai/frontend/web/package.json
@@ -52,6 +52,7 @@
     "@chakra-ui/react-use-size": "^2.1.0",
     "@dagrejs/graphlib": "^2.1.13",
     "@dnd-kit/core": "^6.1.0",
+    "@dnd-kit/sortable": "^8.0.0",
     "@dnd-kit/utilities": "^3.2.2",
     "@fontsource-variable/inter": "^5.0.16",
     "@invoke-ai/ui-library": "^0.0.18",
diff --git a/invokeai/frontend/web/pnpm-lock.yaml b/invokeai/frontend/web/pnpm-lock.yaml
index ba76a61275..1d9083d1b4 100644
--- a/invokeai/frontend/web/pnpm-lock.yaml
+++ b/invokeai/frontend/web/pnpm-lock.yaml
@@ -22,6 +22,9 @@ dependencies:
   '@dnd-kit/core':
     specifier: ^6.1.0
     version: 6.1.0(react-dom@18.2.0)(react@18.2.0)
+  '@dnd-kit/sortable':
+    specifier: ^8.0.0
+    version: 8.0.0(@dnd-kit/core@6.1.0)(react@18.2.0)
   '@dnd-kit/utilities':
     specifier: ^3.2.2
     version: 3.2.2(react@18.2.0)
@@ -2884,6 +2887,18 @@ packages:
       tslib: 2.6.2
     dev: false
 
+  /@dnd-kit/sortable@8.0.0(@dnd-kit/core@6.1.0)(react@18.2.0):
+    resolution: {integrity: sha512-U3jk5ebVXe1Lr7c2wU7SBZjcWdQP+j7peHJfCspnA81enlu88Mgd7CC8Q+pub9ubP7eKVETzJW+IBAhsqbSu/g==}
+    peerDependencies:
+      '@dnd-kit/core': ^6.1.0
+      react: '>=16.8.0'
+    dependencies:
+      '@dnd-kit/core': 6.1.0(react-dom@18.2.0)(react@18.2.0)
+      '@dnd-kit/utilities': 3.2.2(react@18.2.0)
+      react: 18.2.0
+      tslib: 2.6.2
+    dev: false
+
   /@dnd-kit/utilities@3.2.2(react@18.2.0):
     resolution: {integrity: sha512-+MKAJEOfaBe5SmV6t34p80MMKhjvUz0vRrvVJbPT0WElzaOJ/1xs+D+KDv+tD/NE5ujfrChEcshd4fLn0wpiqg==}
     peerDependencies:
diff --git a/invokeai/frontend/web/src/features/dnd/components/AppDndContext.tsx b/invokeai/frontend/web/src/features/dnd/components/AppDndContext.tsx
index f800e5c869..a28b865366 100644
--- a/invokeai/frontend/web/src/features/dnd/components/AppDndContext.tsx
+++ b/invokeai/frontend/web/src/features/dnd/components/AppDndContext.tsx
@@ -19,6 +19,7 @@ const AppDndContext = (props: PropsWithChildren) => {
 
   const handleDragStart = useCallback(
     (event: DragStartEvent) => {
+      console.log('handling drag start', event.active.data.current);
       log.trace({ dragData: parseify(event.active.data.current) }, 'Drag started');
       const activeData = event.active.data.current;
       if (!activeData) {
@@ -31,6 +32,7 @@ const AppDndContext = (props: PropsWithChildren) => {
 
   const handleDragEnd = useCallback(
     (event: DragEndEvent) => {
+      console.log('handling drag end', event.active.data.current);
       log.trace({ dragData: parseify(event.active.data.current) }, 'Drag ended');
       const overData = event.over?.data.current;
       if (!activeDragData || !overData) {
diff --git a/invokeai/frontend/web/src/features/dnd/types/index.ts b/invokeai/frontend/web/src/features/dnd/types/index.ts
index 6e680b4ba9..d4dc59de98 100644
--- a/invokeai/frontend/web/src/features/dnd/types/index.ts
+++ b/invokeai/frontend/web/src/features/dnd/types/index.ts
@@ -80,6 +80,14 @@ export type NodeFieldDraggableData = BaseDragData & {
   };
 };
 
+export type LinearViewFieldDraggableData = BaseDragData & {
+  payloadType: 'LINEAR_VIEW_FIELD';
+  payload: {
+    nodeId: string;
+    fieldName: string;
+  };
+};
+
 export type ImageDraggableData = BaseDragData & {
   payloadType: 'IMAGE_DTO';
   payload: { imageDTO: ImageDTO };
@@ -90,7 +98,11 @@ export type GallerySelectionDraggableData = BaseDragData & {
   payload: { boardId: BoardId };
 };
 
-export type TypesafeDraggableData = NodeFieldDraggableData | ImageDraggableData | GallerySelectionDraggableData;
+export type TypesafeDraggableData =
+  | NodeFieldDraggableData
+  | LinearViewFieldDraggableData
+  | ImageDraggableData
+  | GallerySelectionDraggableData;
 
 export interface UseDroppableTypesafeArguments extends Omit<UseDroppableArguments, 'data'> {
   data?: TypesafeDroppableData;
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx
index 3ec4ab1b42..49a676008a 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx
@@ -1,3 +1,5 @@
+import { useSortable } from '@dnd-kit/sortable';
+import { CSS } from '@dnd-kit/utilities';
 import { Flex, Icon, IconButton, Spacer, Tooltip } from '@invoke-ai/ui-library';
 import { useAppDispatch } from 'app/store/storeHooks';
 import NodeSelectionOverlay from 'common/components/NodeSelectionOverlay';
@@ -25,6 +27,13 @@ const LinearViewField = ({ nodeId, fieldName }: Props) => {
     dispatch(workflowExposedFieldRemoved({ nodeId, fieldName }));
   }, [dispatch, fieldName, nodeId]);
 
+  const { attributes, listeners, setNodeRef, transform, transition } = useSortable({ id: nodeId });
+
+  const style = {
+    transform: CSS.Transform.toString(transform),
+    transition,
+  };
+
   return (
     <Flex
       onMouseEnter={handleMouseOver}
@@ -35,6 +44,10 @@ const LinearViewField = ({ nodeId, fieldName }: Props) => {
       w="full"
       p={4}
       flexDir="column"
+      ref={setNodeRef}
+      style={style}
+      {...attributes}
+      {...listeners}
     >
       <Flex>
         <EditableFieldTitle nodeId={nodeId} fieldName={fieldName} kind="input" />
diff --git a/invokeai/frontend/web/src/features/nodes/components/sidePanel/workflow/WorkflowLinearTab.tsx b/invokeai/frontend/web/src/features/nodes/components/sidePanel/workflow/WorkflowLinearTab.tsx
index 375b271c66..fa6bfff41d 100644
--- a/invokeai/frontend/web/src/features/nodes/components/sidePanel/workflow/WorkflowLinearTab.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/sidePanel/workflow/WorkflowLinearTab.tsx
@@ -1,11 +1,15 @@
+
+import { SortableContext, verticalListSortingStrategy } from '@dnd-kit/sortable';
 import { Box, Flex } from '@invoke-ai/ui-library';
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppSelector } from 'app/store/storeHooks';
+import IAIDroppable from 'common/components/IAIDroppable';
 import { IAINoContentFallback } from 'common/components/IAIImageFallback';
 import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
+import type { TypesafeDroppableData } from 'features/dnd/types';
 import LinearViewField from 'features/nodes/components/flow/nodes/Invocation/fields/LinearViewField';
 import { selectWorkflowSlice } from 'features/nodes/store/workflowSlice';
-import { memo } from 'react';
+import { memo, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
 import { useGetOpenAPISchemaQuery } from 'services/api/endpoints/appInfo';
 
@@ -16,20 +20,31 @@ const WorkflowLinearTab = () => {
   const { isLoading } = useGetOpenAPISchemaQuery();
   const { t } = useTranslation();
 
+  const droppableData = useMemo<TypesafeDroppableData | undefined>(
+    () => ({
+      id: 'current-image',
+      actionType: 'SET_CURRENT_IMAGE',
+    }),
+    []
+  );
+
   return (
     <Box position="relative" w="full" h="full">
+      <IAIDroppable data={droppableData} disabled={false} dropLabel="drop label" />
       <ScrollableContent>
-        <Flex position="relative" flexDir="column" alignItems="flex-start" p={1} gap={2} h="full" w="full">
-          {isLoading ? (
-            <IAINoContentFallback label={t('nodes.loadingNodes')} icon={null} />
-          ) : fields.length ? (
-            fields.map(({ nodeId, fieldName }) => (
-              <LinearViewField key={`${nodeId}.${fieldName}`} nodeId={nodeId} fieldName={fieldName} />
-            ))
-          ) : (
-            <IAINoContentFallback label={t('nodes.noFieldsLinearview')} icon={null} />
-          )}
-        </Flex>
+        <SortableContext items={fields.map((field) => field.nodeId)} strategy={verticalListSortingStrategy}>
+          <Flex position="relative" flexDir="column" alignItems="flex-start" p={1} gap={2} h="full" w="full">
+            {isLoading ? (
+              <IAINoContentFallback label={t('nodes.loadingNodes')} icon={null} />
+            ) : fields.length ? (
+              fields.map(({ nodeId, fieldName }) => (
+                <LinearViewField key={`${nodeId}.${fieldName}`} nodeId={nodeId} fieldName={fieldName} />
+              ))
+            ) : (
+              <IAINoContentFallback label={t('nodes.noFieldsLinearview')} icon={null} />
+            )}
+          </Flex>
+        </SortableContext>
       </ScrollableContent>
     </Box>
   );
diff --git a/invokeai/frontend/web/src/features/nodes/store/workflowSlice.ts b/invokeai/frontend/web/src/features/nodes/store/workflowSlice.ts
index 73802da54e..2418f65ceb 100644
--- a/invokeai/frontend/web/src/features/nodes/store/workflowSlice.ts
+++ b/invokeai/frontend/web/src/features/nodes/store/workflowSlice.ts
@@ -42,6 +42,13 @@ export const workflowSlice = createSlice({
       state.exposedFields = state.exposedFields.filter((field) => !isEqual(field, action.payload));
       state.isTouched = true;
     },
+    workflowExposedFieldsReordered: (state, action: PayloadAction<string>) => {
+      state.exposedFields = action.payload.split(',').map((id) => {
+        const [nodeId, fieldName] = id.split('.');
+        return { nodeId, fieldName };
+      });
+      state.isTouched = true;
+    },
     workflowNameChanged: (state, action: PayloadAction<string>) => {
       state.name = action.payload;
       state.isTouched = true;

From 3726293258b5c4e062e3c2bef9d2e0304a3ffdae Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 5 Feb 2024 18:27:31 +1100
Subject: [PATCH 004/411] feat(nodes): improve types in graph.py

Methods `get_node` and `complete` were typed as returning a dynamically created unions `InvocationsUnion` and `InvocationOutputsUnion`, respectively.

Static type analysers cannot work with dynamic objects, so these methods end up as effectively un-annotated, returning `Unknown`.

They now return `BaseInvocation` and `BaseInvocationOutput`, respectively, which are the superclasses of all members of each union. This gives us the best type annotation that is possible.

Note: the return types of these methods are never introspected, so it doesn't really matter what they are at runtime.
---
 invokeai/app/services/shared/graph.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/invokeai/app/services/shared/graph.py b/invokeai/app/services/shared/graph.py
index 80f56b49d3..1acf165aba 100644
--- a/invokeai/app/services/shared/graph.py
+++ b/invokeai/app/services/shared/graph.py
@@ -540,7 +540,7 @@ class Graph(BaseModel):
         except NodeNotFoundError:
             return False
 
-    def get_node(self, node_path: str) -> InvocationsUnion:
+    def get_node(self, node_path: str) -> BaseInvocation:
         """Gets a node from the graph using a node path."""
         # Materialized graphs may have nodes at the top level
         graph, node_id = self._get_graph_and_node(node_path)
@@ -891,7 +891,7 @@ class GraphExecutionState(BaseModel):
         # If next is still none, there's no next node, return None
         return next_node
 
-    def complete(self, node_id: str, output: InvocationOutputsUnion):
+    def complete(self, node_id: str, output: BaseInvocationOutput) -> None:
         """Marks a node as complete"""
 
         if node_id not in self.execution_graph.nodes:

From 85bbf65967d14bc270dfbbfd2a18e929007c1d30 Mon Sep 17 00:00:00 2001
From: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Date: Tue, 13 Feb 2024 12:29:38 -0500
Subject: [PATCH 005/411] only refetch intermediates on modal open if it is
 enabled

---
 .../system/components/SettingsModal/SettingsModal.tsx       | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/invokeai/frontend/web/src/features/system/components/SettingsModal/SettingsModal.tsx b/invokeai/frontend/web/src/features/system/components/SettingsModal/SettingsModal.tsx
index cc937170a3..b7232ae33f 100644
--- a/invokeai/frontend/web/src/features/system/components/SettingsModal/SettingsModal.tsx
+++ b/invokeai/frontend/web/src/features/system/components/SettingsModal/SettingsModal.tsx
@@ -101,9 +101,11 @@ const SettingsModal = ({ children, config }: SettingsModalProps) => {
   const clearStorage = useClearStorage();
 
   const handleOpenSettingsModel = useCallback(() => {
-    refetchIntermediatesCount();
+    if (shouldShowClearIntermediates) {
+      refetchIntermediatesCount();
+    }
     _onSettingsModalOpen();
-  }, [_onSettingsModalOpen, refetchIntermediatesCount]);
+  }, [_onSettingsModalOpen, refetchIntermediatesCount, shouldShowClearIntermediates]);
 
   const handleClickResetWebUI = useCallback(() => {
     clearStorage();

From 9d6e4ff1fb7ee55024d70e9b11cdca1408d30e60 Mon Sep 17 00:00:00 2001
From: Mary Hipp Rogers <maryhipp@gmail.com>
Date: Wed, 14 Feb 2024 09:02:07 -0500
Subject: [PATCH 006/411] workflow tab (#5680)

* new workflow tab UI - still using shared state with workflow editor tab

* polish workflow details

* remove workflow tab, add edit/view mode to workflow slice and get that working to switch between within editor tab

* UI updates for view/edit mode

* cleanup

* add warning to view mode

* lint

* start with isTouched false

* working on styling mode toggle

* more UX iteration

* lint

* cleanup

* save original field values to state, add indicator if they have been changed and give user choice to reset

* lint

* fix import and commit translation

* dont switch to view mode when loading a workflow

* warns before clearing editor

* use folder icon

* fix(ui): track do not erase value when resetting field value

- When adding an exposed field, we need to add it to originalExposedFieldValues
- When removing an exposed field, we need to remove it from originalExposedFieldValues
- add `useFieldValue` and `useOriginalFieldValue` hooks to encapsulate related logic

* feat(ui): use IconButton for workflow view/edit button

* feat(ui): change icon for new workflow

It was the same as the workflow tab icon, confusing bc you think it's going to somehow take you to the tab.

* feat(ui): use render props for NewWorkflowConfirmationAlertDialog

There was a lot of potentially sensitive logic shared between the new workflow button and menu items. Also, two instances of ConfirmationAlertDialog.

Using a render prop deduplicates the logic & components

* fix(ui): do not mark workflow touched when loading workflow

This was occurring because the `nodesChanged` action is called by reactflow when loading a workflow. Specifically, it calculates and sets the node dimensions as it loads.

The existing logic set `isTouched` whenever this action was called.

The changes reactflow emits have types, and we can use the change types and data to determine if a change should result in the workflow being marked as touched.

* chore(ui): lint

* chore(ui): lint

* delete empty file

---------

Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Co-authored-by: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
---
 invokeai/frontend/web/public/locales/en.json  |  4 +
 .../listeners/workflowLoadRequested.ts        |  2 -
 .../fields/FieldLinearViewToggle.tsx          |  7 +-
 .../Invocation/fields/LinearViewField.tsx     | 15 +++-
 .../flow/panels/TopPanel/TopPanel.tsx         | 14 ++-
 .../panels/TopPanel/UpdateNodesButton.tsx     |  1 +
 .../flow/panels/TopPanel/WorkflowName.tsx     | 15 ----
 .../panels/TopRightPanel/TopRightPanel.tsx    | 15 ----
 .../nodes/components/sidePanel/ModeToggle.tsx | 43 +++++++++
 .../sidePanel/NodeEditorPanelGroup.tsx        | 58 ++++++++----
 .../components/sidePanel/WorkflowMenu.tsx     | 26 ++++++
 .../components/sidePanel/WorkflowName.tsx     | 37 ++++++++
 .../sidePanel/viewMode/WorkflowField.tsx      | 53 +++++++++++
 .../viewMode/WorkflowInfoTooltipContent.tsx   | 68 ++++++++++++++
 .../sidePanel/viewMode/WorkflowViewMode.tsx   | 39 ++++++++
 .../sidePanel/viewMode/WorkflowWarning.tsx    | 21 +++++
 .../viewMode/WorkflowWarningTooltip.tsx       | 20 +++++
 .../sidePanel/workflow/WorkflowPanel.tsx      |  6 +-
 .../nodes/hooks/useFieldOriginalValue.ts      | 28 ++++++
 .../src/features/nodes/hooks/useFieldValue.ts | 23 +++++
 .../src/features/nodes/store/nodesSlice.ts    |  7 +-
 .../web/src/features/nodes/store/types.ts     |  9 +-
 .../src/features/nodes/store/workflowSlice.ts | 88 ++++++++++++++++---
 .../features/ui/components/tabs/NodesTab.tsx  | 25 ++++--
 .../components/NewWorkflowButton.tsx          | 26 ++++++
 .../NewWorkflowConfirmationAlertDialog.tsx    | 63 +++++++++++++
 .../components/WorkflowLibraryButton.tsx      |  4 +-
 .../NewWorkflowMenuItem.tsx                   | 64 +++-----------
 .../WorkflowLibraryMenu.tsx                   |  2 +-
 29 files changed, 649 insertions(+), 134 deletions(-)
 delete mode 100644 invokeai/frontend/web/src/features/nodes/components/flow/panels/TopPanel/WorkflowName.tsx
 delete mode 100644 invokeai/frontend/web/src/features/nodes/components/flow/panels/TopRightPanel/TopRightPanel.tsx
 create mode 100644 invokeai/frontend/web/src/features/nodes/components/sidePanel/ModeToggle.tsx
 create mode 100644 invokeai/frontend/web/src/features/nodes/components/sidePanel/WorkflowMenu.tsx
 create mode 100644 invokeai/frontend/web/src/features/nodes/components/sidePanel/WorkflowName.tsx
 create mode 100644 invokeai/frontend/web/src/features/nodes/components/sidePanel/viewMode/WorkflowField.tsx
 create mode 100644 invokeai/frontend/web/src/features/nodes/components/sidePanel/viewMode/WorkflowInfoTooltipContent.tsx
 create mode 100644 invokeai/frontend/web/src/features/nodes/components/sidePanel/viewMode/WorkflowViewMode.tsx
 create mode 100644 invokeai/frontend/web/src/features/nodes/components/sidePanel/viewMode/WorkflowWarning.tsx
 create mode 100644 invokeai/frontend/web/src/features/nodes/components/sidePanel/viewMode/WorkflowWarningTooltip.tsx
 create mode 100644 invokeai/frontend/web/src/features/nodes/hooks/useFieldOriginalValue.ts
 create mode 100644 invokeai/frontend/web/src/features/nodes/hooks/useFieldValue.ts
 create mode 100644 invokeai/frontend/web/src/features/workflowLibrary/components/NewWorkflowButton.tsx
 create mode 100644 invokeai/frontend/web/src/features/workflowLibrary/components/NewWorkflowConfirmationAlertDialog.tsx

diff --git a/invokeai/frontend/web/public/locales/en.json b/invokeai/frontend/web/public/locales/en.json
index 0fe833db39..f991714c24 100644
--- a/invokeai/frontend/web/public/locales/en.json
+++ b/invokeai/frontend/web/public/locales/en.json
@@ -175,6 +175,7 @@
         "statusUpscaling": "Upscaling",
         "statusUpscalingESRGAN": "Upscaling (ESRGAN)",
         "template": "Template",
+        "toResolve": "To resolve",
         "training": "Training",
         "trainingDesc1": "A dedicated workflow for training your own embeddings and checkpoints using Textual Inversion and Dreambooth from the web interface.",
         "trainingDesc2": "InvokeAI already supports training custom embeddourings using Textual Inversion using the main script.",
@@ -900,6 +901,7 @@
         "doesNotExist": "does not exist",
         "downloadWorkflow": "Download Workflow JSON",
         "edge": "Edge",
+        "editMode": "Edit in Workflow Editor",
         "enum": "Enum",
         "enumDescription": "Enums are values that may be one of a number of options.",
         "executionStateCompleted": "Completed",
@@ -995,6 +997,7 @@
         "problemReadingMetadata": "Problem reading metadata from image",
         "problemReadingWorkflow": "Problem reading workflow from image",
         "problemSettingTitle": "Problem Setting Title",
+        "resetToDefaultValue": "Reset to default value",
         "reloadNodeTemplates": "Reload Node Templates",
         "removeLinearView": "Remove from Linear View",
         "newWorkflow": "New Workflow",
@@ -1067,6 +1070,7 @@
         "vaeModelFieldDescription": "TODO",
         "validateConnections": "Validate Connections and Graph",
         "validateConnectionsHelp": "Prevent invalid connections from being made, and invalid graphs from being invoked",
+        "viewMode": "Use in Linear View",
         "unableToGetWorkflowVersion": "Unable to get workflow schema version",
         "unrecognizedWorkflowVersion": "Unrecognized workflow schema version {{version}}",
         "version": "Version",
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/workflowLoadRequested.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/workflowLoadRequested.ts
index 0b37271be7..9307031e6d 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/workflowLoadRequested.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/workflowLoadRequested.ts
@@ -6,7 +6,6 @@ import { WorkflowMigrationError, WorkflowVersionError } from 'features/nodes/typ
 import { validateWorkflow } from 'features/nodes/util/workflow/validateWorkflow';
 import { addToast } from 'features/system/store/systemSlice';
 import { makeToast } from 'features/system/util/makeToast';
-import { setActiveTab } from 'features/ui/store/uiSlice';
 import { t } from 'i18next';
 import { z } from 'zod';
 import { fromZodError } from 'zod-validation-error';
@@ -53,7 +52,6 @@ export const addWorkflowLoadRequestedListener = () => {
           });
         }
 
-        dispatch(setActiveTab('nodes'));
         requestAnimationFrame(() => {
           $flow.get()?.fitView();
         });
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/FieldLinearViewToggle.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/FieldLinearViewToggle.tsx
index cb1bcba1fe..ff59e02916 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/FieldLinearViewToggle.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/FieldLinearViewToggle.tsx
@@ -1,6 +1,7 @@
 import { IconButton } from '@invoke-ai/ui-library';
 import { createSelector } from '@reduxjs/toolkit';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { useFieldValue } from 'features/nodes/hooks/useFieldValue';
 import {
   selectWorkflowSlice,
   workflowExposedFieldAdded,
@@ -18,7 +19,7 @@ type Props = {
 const FieldLinearViewToggle = ({ nodeId, fieldName }: Props) => {
   const dispatch = useAppDispatch();
   const { t } = useTranslation();
-
+  const value = useFieldValue(nodeId, fieldName);
   const selectIsExposed = useMemo(
     () =>
       createSelector(selectWorkflowSlice, (workflow) => {
@@ -30,8 +31,8 @@ const FieldLinearViewToggle = ({ nodeId, fieldName }: Props) => {
   const isExposed = useAppSelector(selectIsExposed);
 
   const handleExposeField = useCallback(() => {
-    dispatch(workflowExposedFieldAdded({ nodeId, fieldName }));
-  }, [dispatch, fieldName, nodeId]);
+    dispatch(workflowExposedFieldAdded({ nodeId, fieldName, value }));
+  }, [dispatch, fieldName, nodeId, value]);
 
   const handleUnexposeField = useCallback(() => {
     dispatch(workflowExposedFieldRemoved({ nodeId, fieldName }));
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx
index 3ec4ab1b42..b3c563b1d3 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx
@@ -1,12 +1,13 @@
 import { Flex, Icon, IconButton, Spacer, Tooltip } from '@invoke-ai/ui-library';
 import { useAppDispatch } from 'app/store/storeHooks';
 import NodeSelectionOverlay from 'common/components/NodeSelectionOverlay';
+import { useFieldOriginalValue } from 'features/nodes/hooks/useFieldOriginalValue';
 import { useMouseOverNode } from 'features/nodes/hooks/useMouseOverNode';
 import { workflowExposedFieldRemoved } from 'features/nodes/store/workflowSlice';
 import { HANDLE_TOOLTIP_OPEN_DELAY } from 'features/nodes/types/constants';
 import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
-import { PiInfoBold, PiTrashSimpleBold } from 'react-icons/pi';
+import { PiArrowCounterClockwiseBold, PiInfoBold, PiTrashSimpleBold } from 'react-icons/pi';
 
 import EditableFieldTitle from './EditableFieldTitle';
 import FieldTooltipContent from './FieldTooltipContent';
@@ -19,8 +20,10 @@ type Props = {
 
 const LinearViewField = ({ nodeId, fieldName }: Props) => {
   const dispatch = useAppDispatch();
+  const { isValueChanged, onReset } = useFieldOriginalValue(nodeId, fieldName);
   const { isMouseOverNode, handleMouseOut, handleMouseOver } = useMouseOverNode(nodeId);
   const { t } = useTranslation();
+
   const handleRemoveField = useCallback(() => {
     dispatch(workflowExposedFieldRemoved({ nodeId, fieldName }));
   }, [dispatch, fieldName, nodeId]);
@@ -39,6 +42,16 @@ const LinearViewField = ({ nodeId, fieldName }: Props) => {
       <Flex>
         <EditableFieldTitle nodeId={nodeId} fieldName={fieldName} kind="input" />
         <Spacer />
+        {isValueChanged && (
+          <IconButton
+            aria-label={t('nodes.resetToDefaultValue')}
+            tooltip={t('nodes.resetToDefaultValue')}
+            variant="ghost"
+            size="sm"
+            onClick={onReset}
+            icon={<PiArrowCounterClockwiseBold />}
+          />
+        )}
         <Tooltip
           label={<FieldTooltipContent nodeId={nodeId} fieldName={fieldName} kind="input" />}
           openDelay={HANDLE_TOOLTIP_OPEN_DELAY}
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/panels/TopPanel/TopPanel.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/panels/TopPanel/TopPanel.tsx
index c87af124bf..a78024074c 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/panels/TopPanel/TopPanel.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/panels/TopPanel/TopPanel.tsx
@@ -1,25 +1,23 @@
 import { Flex, Spacer } from '@invoke-ai/ui-library';
+import { useAppSelector } from 'app/store/storeHooks';
 import AddNodeButton from 'features/nodes/components/flow/panels/TopPanel/AddNodeButton';
 import ClearFlowButton from 'features/nodes/components/flow/panels/TopPanel/ClearFlowButton';
 import SaveWorkflowButton from 'features/nodes/components/flow/panels/TopPanel/SaveWorkflowButton';
 import UpdateNodesButton from 'features/nodes/components/flow/panels/TopPanel/UpdateNodesButton';
-import WorkflowName from 'features/nodes/components/flow/panels/TopPanel/WorkflowName';
-import WorkflowLibraryButton from 'features/workflowLibrary/components/WorkflowLibraryButton';
+import { WorkflowName } from 'features/nodes/components/sidePanel/WorkflowName';
 import WorkflowLibraryMenu from 'features/workflowLibrary/components/WorkflowLibraryMenu/WorkflowLibraryMenu';
 import { memo } from 'react';
 
 const TopCenterPanel = () => {
+  const name = useAppSelector((s) => s.workflow.name);
   return (
     <Flex gap={2} top={2} left={2} right={2} position="absolute" alignItems="flex-start" pointerEvents="none">
-      <Flex flexDir="column" gap="2">
-        <Flex gap="2">
-          <AddNodeButton />
-          <WorkflowLibraryButton />
-        </Flex>
+      <Flex gap="2">
+        <AddNodeButton />
         <UpdateNodesButton />
       </Flex>
       <Spacer />
-      <WorkflowName />
+      {!!name.length && <WorkflowName />}
       <Spacer />
       <ClearFlowButton />
       <SaveWorkflowButton />
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/panels/TopPanel/UpdateNodesButton.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/panels/TopPanel/UpdateNodesButton.tsx
index d356eaa4e1..9fa710bfb5 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/panels/TopPanel/UpdateNodesButton.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/panels/TopPanel/UpdateNodesButton.tsx
@@ -25,6 +25,7 @@ const UpdateNodesButton = () => {
       icon={<PiWarningBold />}
       onClick={handleClickUpdateNodes}
       pointerEvents="auto"
+      colorScheme="warning"
     />
   );
 };
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/panels/TopPanel/WorkflowName.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/panels/TopPanel/WorkflowName.tsx
deleted file mode 100644
index 527147c67d..0000000000
--- a/invokeai/frontend/web/src/features/nodes/components/flow/panels/TopPanel/WorkflowName.tsx
+++ /dev/null
@@ -1,15 +0,0 @@
-import { Text } from '@invoke-ai/ui-library';
-import { useAppSelector } from 'app/store/storeHooks';
-import { memo } from 'react';
-
-const TopCenterPanel = () => {
-  const name = useAppSelector((s) => s.workflow.name);
-
-  return (
-    <Text m={2} fontSize="lg" userSelect="none" noOfLines={1} wordBreak="break-all" fontWeight="semibold" opacity={0.8}>
-      {name}
-    </Text>
-  );
-};
-
-export default memo(TopCenterPanel);
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/panels/TopRightPanel/TopRightPanel.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/panels/TopRightPanel/TopRightPanel.tsx
deleted file mode 100644
index be939f35bd..0000000000
--- a/invokeai/frontend/web/src/features/nodes/components/flow/panels/TopRightPanel/TopRightPanel.tsx
+++ /dev/null
@@ -1,15 +0,0 @@
-import { Flex } from '@invoke-ai/ui-library';
-import WorkflowLibraryButton from 'features/workflowLibrary/components/WorkflowLibraryButton';
-import WorkflowLibraryMenu from 'features/workflowLibrary/components/WorkflowLibraryMenu/WorkflowLibraryMenu';
-import { memo } from 'react';
-
-const TopRightPanel = () => {
-  return (
-    <Flex gap={2} position="absolute" top={2} insetInlineEnd={2}>
-      <WorkflowLibraryButton />
-      <WorkflowLibraryMenu />
-    </Flex>
-  );
-};
-
-export default memo(TopRightPanel);
diff --git a/invokeai/frontend/web/src/features/nodes/components/sidePanel/ModeToggle.tsx b/invokeai/frontend/web/src/features/nodes/components/sidePanel/ModeToggle.tsx
new file mode 100644
index 0000000000..555070d673
--- /dev/null
+++ b/invokeai/frontend/web/src/features/nodes/components/sidePanel/ModeToggle.tsx
@@ -0,0 +1,43 @@
+import { Flex, IconButton } from '@invoke-ai/ui-library';
+import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { workflowModeChanged } from 'features/nodes/store/workflowSlice';
+import { useCallback } from 'react';
+import { useTranslation } from 'react-i18next';
+import { PiEyeBold, PiPencilBold } from 'react-icons/pi';
+
+export const ModeToggle = () => {
+  const dispatch = useAppDispatch();
+  const mode = useAppSelector((s) => s.workflow.mode);
+  const { t } = useTranslation();
+
+  const onClickEdit = useCallback(() => {
+    dispatch(workflowModeChanged('edit'));
+  }, [dispatch]);
+
+  const onClickView = useCallback(() => {
+    dispatch(workflowModeChanged('view'));
+  }, [dispatch]);
+
+  return (
+    <Flex justifyContent="flex-end">
+      {mode === 'view' && (
+        <IconButton
+          aria-label={t('nodes.editMode')}
+          tooltip={t('nodes.editMode')}
+          onClick={onClickEdit}
+          icon={<PiPencilBold />}
+          colorScheme="invokeBlue"
+        />
+      )}
+      {mode === 'edit' && (
+        <IconButton
+          aria-label={t('nodes.viewMode')}
+          tooltip={t('nodes.viewMode')}
+          onClick={onClickView}
+          icon={<PiEyeBold />}
+          colorScheme="invokeBlue"
+        />
+      )}
+    </Flex>
+  );
+};
diff --git a/invokeai/frontend/web/src/features/nodes/components/sidePanel/NodeEditorPanelGroup.tsx b/invokeai/frontend/web/src/features/nodes/components/sidePanel/NodeEditorPanelGroup.tsx
index c145003c95..abd3d707d7 100644
--- a/invokeai/frontend/web/src/features/nodes/components/sidePanel/NodeEditorPanelGroup.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/sidePanel/NodeEditorPanelGroup.tsx
@@ -1,22 +1,37 @@
 import 'reactflow/dist/style.css';
 
 import { Flex } from '@invoke-ai/ui-library';
+import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
+import { useAppSelector } from 'app/store/storeHooks';
+import { selectWorkflowSlice } from 'features/nodes/store/workflowSlice';
 import QueueControls from 'features/queue/components/QueueControls';
 import ResizeHandle from 'features/ui/components/tabs/ResizeHandle';
 import { usePanelStorage } from 'features/ui/hooks/usePanelStorage';
+import WorkflowLibraryButton from 'features/workflowLibrary/components/WorkflowLibraryButton';
 import type { CSSProperties } from 'react';
 import { memo, useCallback, useRef } from 'react';
 import type { ImperativePanelGroupHandle } from 'react-resizable-panels';
 import { Panel, PanelGroup } from 'react-resizable-panels';
 
 import InspectorPanel from './inspector/InspectorPanel';
+import { WorkflowViewMode } from './viewMode/WorkflowViewMode';
 import WorkflowPanel from './workflow/WorkflowPanel';
+import { WorkflowMenu } from './WorkflowMenu';
+import { WorkflowName } from './WorkflowName';
 
 const panelGroupStyles: CSSProperties = { height: '100%', width: '100%' };
 
+const selector = createMemoizedSelector(selectWorkflowSlice, (workflow) => {
+  return {
+    mode: workflow.mode,
+  };
+});
+
 const NodeEditorPanelGroup = () => {
+  const { mode } = useAppSelector(selector);
   const panelGroupRef = useRef<ImperativePanelGroupHandle>(null);
   const panelStorage = usePanelStorage();
+
   const handleDoubleClickHandle = useCallback(() => {
     if (!panelGroupRef.current) {
       return;
@@ -27,22 +42,33 @@ const NodeEditorPanelGroup = () => {
   return (
     <Flex w="full" h="full" gap={2} flexDir="column">
       <QueueControls />
-      <PanelGroup
-        ref={panelGroupRef}
-        id="workflow-panel-group"
-        autoSaveId="workflow-panel-group"
-        direction="vertical"
-        style={panelGroupStyles}
-        storage={panelStorage}
-      >
-        <Panel id="workflow" collapsible minSize={25}>
-          <WorkflowPanel />
-        </Panel>
-        <ResizeHandle orientation="horizontal" onDoubleClick={handleDoubleClickHandle} />
-        <Panel id="inspector" collapsible minSize={25}>
-          <InspectorPanel />
-        </Panel>
-      </PanelGroup>
+      <Flex w="full" justifyContent="space-between" alignItems="center" gap="4" padding={1}>
+        <Flex justifyContent="space-between" alignItems="center" gap="4">
+          <WorkflowLibraryButton />
+          <WorkflowName />
+        </Flex>
+        <WorkflowMenu />
+      </Flex>
+
+      {mode === 'view' && <WorkflowViewMode />}
+      {mode === 'edit' && (
+        <PanelGroup
+          ref={panelGroupRef}
+          id="workflow-panel-group"
+          autoSaveId="workflow-panel-group"
+          direction="vertical"
+          style={panelGroupStyles}
+          storage={panelStorage}
+        >
+          <Panel id="workflow" collapsible minSize={25}>
+            <WorkflowPanel />
+          </Panel>
+          <ResizeHandle orientation="horizontal" onDoubleClick={handleDoubleClickHandle} />
+          <Panel id="inspector" collapsible minSize={25}>
+            <InspectorPanel />
+          </Panel>
+        </PanelGroup>
+      )}
     </Flex>
   );
 };
diff --git a/invokeai/frontend/web/src/features/nodes/components/sidePanel/WorkflowMenu.tsx b/invokeai/frontend/web/src/features/nodes/components/sidePanel/WorkflowMenu.tsx
new file mode 100644
index 0000000000..33dd5dc83f
--- /dev/null
+++ b/invokeai/frontend/web/src/features/nodes/components/sidePanel/WorkflowMenu.tsx
@@ -0,0 +1,26 @@
+import { Flex } from '@invoke-ai/ui-library';
+import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
+import { useAppSelector } from 'app/store/storeHooks';
+import SaveWorkflowButton from 'features/nodes/components/flow/panels/TopPanel/SaveWorkflowButton';
+import { selectWorkflowSlice } from 'features/nodes/store/workflowSlice';
+import { NewWorkflowButton } from 'features/workflowLibrary/components/NewWorkflowButton';
+
+import { ModeToggle } from './ModeToggle';
+
+const selector = createMemoizedSelector(selectWorkflowSlice, (workflow) => {
+  return {
+    mode: workflow.mode,
+  };
+});
+
+export const WorkflowMenu = () => {
+  const { mode } = useAppSelector(selector);
+
+  return (
+    <Flex gap="2" alignItems="center">
+      {mode === 'edit' && <SaveWorkflowButton />}
+      <NewWorkflowButton />
+      <ModeToggle />
+    </Flex>
+  );
+};
diff --git a/invokeai/frontend/web/src/features/nodes/components/sidePanel/WorkflowName.tsx b/invokeai/frontend/web/src/features/nodes/components/sidePanel/WorkflowName.tsx
new file mode 100644
index 0000000000..14852945ab
--- /dev/null
+++ b/invokeai/frontend/web/src/features/nodes/components/sidePanel/WorkflowName.tsx
@@ -0,0 +1,37 @@
+import { Flex, Icon, Text, Tooltip } from '@invoke-ai/ui-library';
+import { useAppSelector } from 'app/store/storeHooks';
+import { useTranslation } from 'react-i18next';
+import { PiDotOutlineFill } from 'react-icons/pi';
+
+import WorkflowInfoTooltipContent from './viewMode/WorkflowInfoTooltipContent';
+import { WorkflowWarning } from './viewMode/WorkflowWarning';
+
+export const WorkflowName = () => {
+  const { name, isTouched, mode } = useAppSelector((s) => s.workflow);
+  const { t } = useTranslation();
+
+  return (
+    <Flex gap="1" alignItems="center">
+      {name.length ? (
+        <Tooltip label={<WorkflowInfoTooltipContent />} placement="top">
+          <Text fontSize="lg" userSelect="none" noOfLines={1} wordBreak="break-all" fontWeight="semibold">
+            {name}
+          </Text>
+        </Tooltip>
+      ) : (
+        <Text fontSize="lg" fontStyle="italic" fontWeight="semibold">
+          {t('workflows.unnamedWorkflow')}
+        </Text>
+      )}
+
+      {isTouched && mode === 'edit' && (
+        <Tooltip label="Workflow has unsaved changes">
+          <Flex>
+            <Icon as={PiDotOutlineFill} boxSize="20px" sx={{ color: 'invokeYellow.500' }} />
+          </Flex>
+        </Tooltip>
+      )}
+      <WorkflowWarning />
+    </Flex>
+  );
+};
diff --git a/invokeai/frontend/web/src/features/nodes/components/sidePanel/viewMode/WorkflowField.tsx b/invokeai/frontend/web/src/features/nodes/components/sidePanel/viewMode/WorkflowField.tsx
new file mode 100644
index 0000000000..0e5857933a
--- /dev/null
+++ b/invokeai/frontend/web/src/features/nodes/components/sidePanel/viewMode/WorkflowField.tsx
@@ -0,0 +1,53 @@
+import { Flex, FormLabel, Icon, IconButton, Spacer, Tooltip } from '@invoke-ai/ui-library';
+import FieldTooltipContent from 'features/nodes/components/flow/nodes/Invocation/fields/FieldTooltipContent';
+import InputFieldRenderer from 'features/nodes/components/flow/nodes/Invocation/fields/InputFieldRenderer';
+import { useFieldLabel } from 'features/nodes/hooks/useFieldLabel';
+import { useFieldOriginalValue } from 'features/nodes/hooks/useFieldOriginalValue';
+import { useFieldTemplateTitle } from 'features/nodes/hooks/useFieldTemplateTitle';
+import { HANDLE_TOOLTIP_OPEN_DELAY } from 'features/nodes/types/constants';
+import { t } from 'i18next';
+import { memo } from 'react';
+import { PiArrowCounterClockwiseBold, PiInfoBold } from 'react-icons/pi';
+
+type Props = {
+  nodeId: string;
+  fieldName: string;
+};
+
+const WorkflowField = ({ nodeId, fieldName }: Props) => {
+  const label = useFieldLabel(nodeId, fieldName);
+  const fieldTemplateTitle = useFieldTemplateTitle(nodeId, fieldName, 'input');
+  const { isValueChanged, onReset } = useFieldOriginalValue(nodeId, fieldName);
+
+  return (
+    <Flex layerStyle="second" position="relative" borderRadius="base" w="full" p={4} gap="2" flexDir="column">
+      <Flex alignItems="center">
+        <FormLabel fontSize="sm">{label || fieldTemplateTitle}</FormLabel>
+
+        <Spacer />
+        {isValueChanged && (
+          <IconButton
+            aria-label={t('nodes.resetToDefaultValue')}
+            tooltip={t('nodes.resetToDefaultValue')}
+            variant="ghost"
+            size="sm"
+            onClick={onReset}
+            icon={<PiArrowCounterClockwiseBold />}
+          />
+        )}
+        <Tooltip
+          label={<FieldTooltipContent nodeId={nodeId} fieldName={fieldName} kind="input" />}
+          openDelay={HANDLE_TOOLTIP_OPEN_DELAY}
+          placement="top"
+        >
+          <Flex h="24px" alignItems="center">
+            <Icon fontSize="md" color="base.300" as={PiInfoBold} />
+          </Flex>
+        </Tooltip>
+      </Flex>
+      <InputFieldRenderer nodeId={nodeId} fieldName={fieldName} />
+    </Flex>
+  );
+};
+
+export default memo(WorkflowField);
diff --git a/invokeai/frontend/web/src/features/nodes/components/sidePanel/viewMode/WorkflowInfoTooltipContent.tsx b/invokeai/frontend/web/src/features/nodes/components/sidePanel/viewMode/WorkflowInfoTooltipContent.tsx
new file mode 100644
index 0000000000..1145af032e
--- /dev/null
+++ b/invokeai/frontend/web/src/features/nodes/components/sidePanel/viewMode/WorkflowInfoTooltipContent.tsx
@@ -0,0 +1,68 @@
+import { Box, Flex, Text } from '@invoke-ai/ui-library';
+import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
+import { useAppSelector } from 'app/store/storeHooks';
+import { selectWorkflowSlice } from 'features/nodes/store/workflowSlice';
+import { memo } from 'react';
+import { useTranslation } from 'react-i18next';
+
+const selector = createMemoizedSelector(selectWorkflowSlice, (workflow) => {
+  return {
+    name: workflow.name,
+    description: workflow.description,
+    notes: workflow.notes,
+    author: workflow.author,
+    tags: workflow.tags,
+  };
+});
+
+const WorkflowInfoTooltipContent = () => {
+  const { name, description, notes, author, tags } = useAppSelector(selector);
+  const { t } = useTranslation();
+
+  return (
+    <Flex flexDir="column" gap="2">
+      {!!name.length && (
+        <Box>
+          <Text fontWeight="semibold">{t('nodes.workflowName')}</Text>
+          <Text opacity={0.7} fontStyle="oblique 5deg">
+            {name}
+          </Text>
+        </Box>
+      )}
+      {!!author.length && (
+        <Box>
+          <Text fontWeight="semibold">{t('nodes.workflowAuthor')}</Text>
+          <Text opacity={0.7} fontStyle="oblique 5deg">
+            {author}
+          </Text>
+        </Box>
+      )}
+      {!!tags.length && (
+        <Box>
+          <Text fontWeight="semibold">{t('nodes.workflowTags')}</Text>
+          <Text opacity={0.7} fontStyle="oblique 5deg">
+            {tags}
+          </Text>
+        </Box>
+      )}
+      {!!description.length && (
+        <Box>
+          <Text fontWeight="semibold">{t('nodes.workflowDescription')}</Text>
+          <Text opacity={0.7} fontStyle="oblique 5deg">
+            {description}
+          </Text>
+        </Box>
+      )}
+      {!!notes.length && (
+        <Box>
+          <Text fontWeight="semibold">{t('nodes.workflowNotes')}</Text>
+          <Text opacity={0.7} fontStyle="oblique 5deg">
+            {notes}
+          </Text>
+        </Box>
+      )}
+    </Flex>
+  );
+};
+
+export default memo(WorkflowInfoTooltipContent);
diff --git a/invokeai/frontend/web/src/features/nodes/components/sidePanel/viewMode/WorkflowViewMode.tsx b/invokeai/frontend/web/src/features/nodes/components/sidePanel/viewMode/WorkflowViewMode.tsx
new file mode 100644
index 0000000000..7bfe256702
--- /dev/null
+++ b/invokeai/frontend/web/src/features/nodes/components/sidePanel/viewMode/WorkflowViewMode.tsx
@@ -0,0 +1,39 @@
+import { Box, Flex } from '@invoke-ai/ui-library';
+import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
+import { useAppSelector } from 'app/store/storeHooks';
+import { IAINoContentFallback } from 'common/components/IAIImageFallback';
+import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
+import { selectWorkflowSlice } from 'features/nodes/store/workflowSlice';
+import { t } from 'i18next';
+import { useGetOpenAPISchemaQuery } from 'services/api/endpoints/appInfo';
+
+import WorkflowField from './WorkflowField';
+
+const selector = createMemoizedSelector(selectWorkflowSlice, (workflow) => {
+  return {
+    fields: workflow.exposedFields,
+    name: workflow.name,
+  };
+});
+
+export const WorkflowViewMode = () => {
+  const { isLoading } = useGetOpenAPISchemaQuery();
+  const { fields } = useAppSelector(selector);
+  return (
+    <Box position="relative" w="full" h="full">
+      <ScrollableContent>
+        <Flex position="relative" flexDir="column" alignItems="flex-start" p={1} gap={2} h="full" w="full">
+          {isLoading ? (
+            <IAINoContentFallback label={t('nodes.loadingNodes')} icon={null} />
+          ) : fields.length ? (
+            fields.map(({ nodeId, fieldName }) => (
+              <WorkflowField key={`${nodeId}.${fieldName}`} nodeId={nodeId} fieldName={fieldName} />
+            ))
+          ) : (
+            <IAINoContentFallback label={t('nodes.noFieldsLinearview')} icon={null} />
+          )}
+        </Flex>
+      </ScrollableContent>
+    </Box>
+  );
+};
diff --git a/invokeai/frontend/web/src/features/nodes/components/sidePanel/viewMode/WorkflowWarning.tsx b/invokeai/frontend/web/src/features/nodes/components/sidePanel/viewMode/WorkflowWarning.tsx
new file mode 100644
index 0000000000..d5182ddd62
--- /dev/null
+++ b/invokeai/frontend/web/src/features/nodes/components/sidePanel/viewMode/WorkflowWarning.tsx
@@ -0,0 +1,21 @@
+import { Flex, Icon, Tooltip } from '@invoke-ai/ui-library';
+import { useGetNodesNeedUpdate } from 'features/nodes/hooks/useGetNodesNeedUpdate';
+import { PiWarningBold } from 'react-icons/pi';
+
+import { WorkflowWarningTooltip } from './WorkflowWarningTooltip';
+
+export const WorkflowWarning = () => {
+  const nodesNeedUpdate = useGetNodesNeedUpdate();
+
+  if (!nodesNeedUpdate) {
+    return <></>;
+  }
+
+  return (
+    <Tooltip label={<WorkflowWarningTooltip />}>
+      <Flex h="full" alignItems="center" gap="2">
+        <Icon color="warning.400" as={PiWarningBold} />
+      </Flex>
+    </Tooltip>
+  );
+};
diff --git a/invokeai/frontend/web/src/features/nodes/components/sidePanel/viewMode/WorkflowWarningTooltip.tsx b/invokeai/frontend/web/src/features/nodes/components/sidePanel/viewMode/WorkflowWarningTooltip.tsx
new file mode 100644
index 0000000000..7f66d60622
--- /dev/null
+++ b/invokeai/frontend/web/src/features/nodes/components/sidePanel/viewMode/WorkflowWarningTooltip.tsx
@@ -0,0 +1,20 @@
+import { Flex, Text } from '@invoke-ai/ui-library';
+import { useTranslation } from 'react-i18next';
+
+export const WorkflowWarningTooltip = () => {
+  const { t } = useTranslation();
+
+  return (
+    <Flex flexDir="column" gap="2">
+      <Flex flexDir="column" gap="2">
+        <Text fontWeight="semibold">{t('toast.loadedWithWarnings')}</Text>
+        <Flex flexDir="column">
+          <Text>{t('common.toResolve')}:</Text>
+          <Text>
+            {t('nodes.editMode')} &gt;&gt; {t('nodes.updateAllNodes')} &gt;&gt; {t('common.save')}
+          </Text>
+        </Flex>
+      </Flex>
+    </Flex>
+  );
+};
diff --git a/invokeai/frontend/web/src/features/nodes/components/sidePanel/workflow/WorkflowPanel.tsx b/invokeai/frontend/web/src/features/nodes/components/sidePanel/workflow/WorkflowPanel.tsx
index bdc384d40d..cb4a110a89 100644
--- a/invokeai/frontend/web/src/features/nodes/components/sidePanel/workflow/WorkflowPanel.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/sidePanel/workflow/WorkflowPanel.tsx
@@ -12,17 +12,17 @@ const WorkflowPanel = () => {
     <Flex layerStyle="first" flexDir="column" w="full" h="full" borderRadius="base" p={2} gap={2}>
       <Tabs variant="line" display="flex" w="full" h="full" flexDir="column">
         <TabList>
-          <Tab>{t('common.linear')}</Tab>
           <Tab>{t('common.details')}</Tab>
+          <Tab>{t('common.linear')}</Tab>
           <Tab>JSON</Tab>
         </TabList>
 
         <TabPanels>
           <TabPanel>
-            <WorkflowLinearTab />
+            <WorkflowGeneralTab />
           </TabPanel>
           <TabPanel>
-            <WorkflowGeneralTab />
+            <WorkflowLinearTab />
           </TabPanel>
           <TabPanel>
             <WorkflowJSONTab />
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useFieldOriginalValue.ts b/invokeai/frontend/web/src/features/nodes/hooks/useFieldOriginalValue.ts
new file mode 100644
index 0000000000..a9ebc991e2
--- /dev/null
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useFieldOriginalValue.ts
@@ -0,0 +1,28 @@
+import { createSelector } from '@reduxjs/toolkit';
+import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { useFieldValue } from 'features/nodes/hooks/useFieldValue';
+import { fieldValueReset } from 'features/nodes/store/nodesSlice';
+import { selectWorkflowSlice } from 'features/nodes/store/workflowSlice';
+import { isEqual } from 'lodash-es';
+import { useCallback, useMemo } from 'react';
+
+export const useFieldOriginalValue = (nodeId: string, fieldName: string) => {
+  const dispatch = useAppDispatch();
+  const selectOriginalExposedFieldValues = useMemo(
+    () =>
+      createSelector(
+        selectWorkflowSlice,
+        (workflow) =>
+          workflow.originalExposedFieldValues.find((v) => v.nodeId === nodeId && v.fieldName === fieldName)?.value
+      ),
+    [nodeId, fieldName]
+  );
+  const originalValue = useAppSelector(selectOriginalExposedFieldValues);
+  const value = useFieldValue(nodeId, fieldName);
+  const isValueChanged = useMemo(() => !isEqual(value, originalValue), [value, originalValue]);
+  const onReset = useCallback(() => {
+    dispatch(fieldValueReset({ nodeId, fieldName, value: originalValue }));
+  }, [dispatch, fieldName, nodeId, originalValue]);
+
+  return { originalValue, isValueChanged, onReset };
+};
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useFieldValue.ts b/invokeai/frontend/web/src/features/nodes/hooks/useFieldValue.ts
new file mode 100644
index 0000000000..5b58a7a345
--- /dev/null
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useFieldValue.ts
@@ -0,0 +1,23 @@
+import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
+import { useAppSelector } from 'app/store/storeHooks';
+import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
+import { isInvocationNode } from 'features/nodes/types/invocation';
+import { useMemo } from 'react';
+
+export const useFieldValue = (nodeId: string, fieldName: string) => {
+  const selector = useMemo(
+    () =>
+      createMemoizedSelector(selectNodesSlice, (nodes) => {
+        const node = nodes.nodes.find((node) => node.id === nodeId);
+        if (!isInvocationNode(node)) {
+          return;
+        }
+        return node?.data.inputs[fieldName]?.value;
+      }),
+    [fieldName, nodeId]
+  );
+
+  const value = useAppSelector(selector);
+
+  return value;
+};
diff --git a/invokeai/frontend/web/src/features/nodes/store/nodesSlice.ts b/invokeai/frontend/web/src/features/nodes/store/nodesSlice.ts
index 761b273f54..aee01b381b 100644
--- a/invokeai/frontend/web/src/features/nodes/store/nodesSlice.ts
+++ b/invokeai/frontend/web/src/features/nodes/store/nodesSlice.ts
@@ -18,6 +18,7 @@ import type {
   MainModelFieldValue,
   SchedulerFieldValue,
   SDXLRefinerModelFieldValue,
+  StatefulFieldValue,
   StringFieldValue,
   T2IAdapterModelFieldValue,
   VAEModelFieldValue,
@@ -36,6 +37,7 @@ import {
   zMainModelFieldValue,
   zSchedulerFieldValue,
   zSDXLRefinerModelFieldValue,
+  zStatefulFieldValue,
   zStringFieldValue,
   zT2IAdapterModelFieldValue,
   zVAEModelFieldValue,
@@ -478,6 +480,9 @@ export const nodesSlice = createSlice({
     selectedEdgesChanged: (state, action: PayloadAction<string[]>) => {
       state.selectedEdges = action.payload;
     },
+    fieldValueReset: (state, action: FieldValueAction<StatefulFieldValue>) => {
+      fieldValueReducer(state, action, zStatefulFieldValue);
+    },
     fieldStringValueChanged: (state, action: FieldValueAction<StringFieldValue>) => {
       fieldValueReducer(state, action, zStringFieldValue);
     },
@@ -760,6 +765,7 @@ export const {
   edgesChanged,
   edgesDeleted,
   edgeUpdated,
+  fieldValueReset,
   fieldBoardValueChanged,
   fieldBooleanValueChanged,
   fieldColorValueChanged,
@@ -834,7 +840,6 @@ export const isAnyNodeOrEdgeMutation = isAnyOf(
   nodeIsOpenChanged,
   nodeLabelChanged,
   nodeNotesChanged,
-  nodesChanged,
   nodesDeleted,
   nodeUseCacheChanged,
   notesNodeValueChanged,
diff --git a/invokeai/frontend/web/src/features/nodes/store/types.ts b/invokeai/frontend/web/src/features/nodes/store/types.ts
index c4a50647b5..8b0de447e4 100644
--- a/invokeai/frontend/web/src/features/nodes/store/types.ts
+++ b/invokeai/frontend/web/src/features/nodes/store/types.ts
@@ -1,4 +1,4 @@
-import type { FieldType } from 'features/nodes/types/field';
+import type { FieldIdentifier, FieldType, StatefulFieldValue } from 'features/nodes/types/field';
 import type {
   AnyNode,
   InvocationNodeEdge,
@@ -33,9 +33,16 @@ export type NodesState = {
   selectionMode: SelectionMode;
 };
 
+export type WorkflowMode = 'edit' | 'view';
+export type FieldIdentifierWithValue = FieldIdentifier & {
+  value: StatefulFieldValue;
+};
+
 export type WorkflowsState = Omit<WorkflowV2, 'nodes' | 'edges'> & {
   _version: 1;
   isTouched: boolean;
+  mode: WorkflowMode;
+  originalExposedFieldValues: FieldIdentifierWithValue[];
 };
 
 export type NodeTemplatesState = {
diff --git a/invokeai/frontend/web/src/features/nodes/store/workflowSlice.ts b/invokeai/frontend/web/src/features/nodes/store/workflowSlice.ts
index 73802da54e..807025032d 100644
--- a/invokeai/frontend/web/src/features/nodes/store/workflowSlice.ts
+++ b/invokeai/frontend/web/src/features/nodes/store/workflowSlice.ts
@@ -2,11 +2,16 @@ import type { PayloadAction } from '@reduxjs/toolkit';
 import { createSlice } from '@reduxjs/toolkit';
 import type { PersistConfig, RootState } from 'app/store/store';
 import { workflowLoaded } from 'features/nodes/store/actions';
-import { isAnyNodeOrEdgeMutation, nodeEditorReset, nodesDeleted } from 'features/nodes/store/nodesSlice';
-import type { WorkflowsState as WorkflowState } from 'features/nodes/store/types';
+import { isAnyNodeOrEdgeMutation, nodeEditorReset, nodesChanged, nodesDeleted } from 'features/nodes/store/nodesSlice';
+import type {
+  FieldIdentifierWithValue,
+  WorkflowMode,
+  WorkflowsState as WorkflowState,
+} from 'features/nodes/store/types';
 import type { FieldIdentifier } from 'features/nodes/types/field';
+import { isInvocationNode } from 'features/nodes/types/invocation';
 import type { WorkflowCategory, WorkflowV2 } from 'features/nodes/types/workflow';
-import { cloneDeep, isEqual, uniqBy } from 'lodash-es';
+import { cloneDeep, isEqual, omit, uniqBy } from 'lodash-es';
 
 export const blankWorkflow: Omit<WorkflowV2, 'nodes' | 'edges'> = {
   name: '',
@@ -23,7 +28,9 @@ export const blankWorkflow: Omit<WorkflowV2, 'nodes' | 'edges'> = {
 
 export const initialWorkflowState: WorkflowState = {
   _version: 1,
-  isTouched: true,
+  isTouched: false,
+  mode: 'view',
+  originalExposedFieldValues: [],
   ...blankWorkflow,
 };
 
@@ -31,15 +38,25 @@ export const workflowSlice = createSlice({
   name: 'workflow',
   initialState: initialWorkflowState,
   reducers: {
-    workflowExposedFieldAdded: (state, action: PayloadAction<FieldIdentifier>) => {
+    workflowModeChanged: (state, action: PayloadAction<WorkflowMode>) => {
+      state.mode = action.payload;
+    },
+    workflowExposedFieldAdded: (state, action: PayloadAction<FieldIdentifierWithValue>) => {
       state.exposedFields = uniqBy(
-        state.exposedFields.concat(action.payload),
+        state.exposedFields.concat(omit(action.payload, 'value')),
+        (field) => `${field.nodeId}-${field.fieldName}`
+      );
+      state.originalExposedFieldValues = uniqBy(
+        state.originalExposedFieldValues.concat(action.payload),
         (field) => `${field.nodeId}-${field.fieldName}`
       );
       state.isTouched = true;
     },
     workflowExposedFieldRemoved: (state, action: PayloadAction<FieldIdentifier>) => {
       state.exposedFields = state.exposedFields.filter((field) => !isEqual(field, action.payload));
+      state.originalExposedFieldValues = state.originalExposedFieldValues.filter(
+        (field) => !isEqual(omit(field, 'value'), action.payload)
+      );
       state.isTouched = true;
     },
     workflowNameChanged: (state, action: PayloadAction<string>) => {
@@ -78,15 +95,43 @@ export const workflowSlice = createSlice({
     workflowIDChanged: (state, action: PayloadAction<string>) => {
       state.id = action.payload;
     },
-    workflowReset: () => cloneDeep(initialWorkflowState),
     workflowSaved: (state) => {
       state.isTouched = false;
     },
   },
   extraReducers: (builder) => {
     builder.addCase(workflowLoaded, (state, action) => {
-      const { nodes: _nodes, edges: _edges, ...workflowExtra } = action.payload;
-      return { ...initialWorkflowState, ...cloneDeep(workflowExtra) };
+      const { nodes, edges: _edges, ...workflowExtra } = action.payload;
+
+      const originalExposedFieldValues: FieldIdentifierWithValue[] = [];
+
+      workflowExtra.exposedFields.forEach((field) => {
+        const node = nodes.find((n) => n.id === field.nodeId);
+
+        if (!isInvocationNode(node)) {
+          return;
+        }
+
+        const input = node.data.inputs[field.fieldName];
+
+        if (!input) {
+          return;
+        }
+
+        const originalExposedFieldValue = {
+          nodeId: field.nodeId,
+          fieldName: field.fieldName,
+          value: input.value,
+        };
+        originalExposedFieldValues.push(originalExposedFieldValue);
+      });
+
+      return {
+        ...cloneDeep(initialWorkflowState),
+        ...cloneDeep(workflowExtra),
+        originalExposedFieldValues,
+        mode: state.mode,
+      };
     });
 
     builder.addCase(nodesDeleted, (state, action) => {
@@ -97,6 +142,29 @@ export const workflowSlice = createSlice({
 
     builder.addCase(nodeEditorReset, () => cloneDeep(initialWorkflowState));
 
+    builder.addCase(nodesChanged, (state, action) => {
+      // Not all changes to nodes should result in the workflow being marked touched
+      const filteredChanges = action.payload.filter((change) => {
+        // We always want to mark the workflow as touched if a node is added, removed, or reset
+        if (['add', 'remove', 'reset'].includes(change.type)) {
+          return true;
+        }
+
+        // Position changes can change the position and the dragging status of the node - ignore if the change doesn't
+        // affect the position
+        if (change.type === 'position' && (change.position || change.positionAbsolute)) {
+          return true;
+        }
+
+        // This change isn't relevant
+        return false;
+      });
+
+      if (filteredChanges.length > 0) {
+        state.isTouched = true;
+      }
+    });
+
     builder.addMatcher(isAnyNodeOrEdgeMutation, (state) => {
       state.isTouched = true;
     });
@@ -104,6 +172,7 @@ export const workflowSlice = createSlice({
 });
 
 export const {
+  workflowModeChanged,
   workflowExposedFieldAdded,
   workflowExposedFieldRemoved,
   workflowNameChanged,
@@ -115,7 +184,6 @@ export const {
   workflowVersionChanged,
   workflowContactChanged,
   workflowIDChanged,
-  workflowReset,
   workflowSaved,
 } = workflowSlice.actions;
 
diff --git a/invokeai/frontend/web/src/features/ui/components/tabs/NodesTab.tsx b/invokeai/frontend/web/src/features/ui/components/tabs/NodesTab.tsx
index 2e2b07f24b..a707327d5d 100644
--- a/invokeai/frontend/web/src/features/ui/components/tabs/NodesTab.tsx
+++ b/invokeai/frontend/web/src/features/ui/components/tabs/NodesTab.tsx
@@ -1,13 +1,28 @@
+import { Box, Flex } from '@invoke-ai/ui-library';
+import { useAppSelector } from 'app/store/storeHooks';
+import CurrentImageDisplay from 'features/gallery/components/CurrentImage/CurrentImageDisplay';
 import NodeEditor from 'features/nodes/components/NodeEditor';
 import { memo } from 'react';
 import { ReactFlowProvider } from 'reactflow';
 
 const NodesTab = () => {
-  return (
-    <ReactFlowProvider>
-      <NodeEditor />
-    </ReactFlowProvider>
-  );
+  const mode = useAppSelector((s) => s.workflow.mode);
+
+  if (mode === 'edit') {
+    return (
+      <ReactFlowProvider>
+        <NodeEditor />
+      </ReactFlowProvider>
+    );
+  } else {
+    return (
+      <Box layerStyle="first" position="relative" w="full" h="full" p={2} borderRadius="base">
+        <Flex w="full" h="full">
+          <CurrentImageDisplay />
+        </Flex>
+      </Box>
+    );
+  }
 };
 
 export default memo(NodesTab);
diff --git a/invokeai/frontend/web/src/features/workflowLibrary/components/NewWorkflowButton.tsx b/invokeai/frontend/web/src/features/workflowLibrary/components/NewWorkflowButton.tsx
new file mode 100644
index 0000000000..c1211f9e2b
--- /dev/null
+++ b/invokeai/frontend/web/src/features/workflowLibrary/components/NewWorkflowButton.tsx
@@ -0,0 +1,26 @@
+import { IconButton } from '@invoke-ai/ui-library';
+import { NewWorkflowConfirmationAlertDialog } from 'features/workflowLibrary/components/NewWorkflowConfirmationAlertDialog';
+import { memo, useCallback } from 'react';
+import { useTranslation } from 'react-i18next';
+import { PiFilePlusBold } from 'react-icons/pi';
+
+export const NewWorkflowButton = memo(() => {
+  const { t } = useTranslation();
+
+  const renderButton = useCallback(
+    (onClick: () => void) => (
+      <IconButton
+        aria-label={t('nodes.newWorkflow')}
+        tooltip={t('nodes.newWorkflow')}
+        icon={<PiFilePlusBold />}
+        onClick={onClick}
+        pointerEvents="auto"
+      />
+    ),
+    [t]
+  );
+
+  return <NewWorkflowConfirmationAlertDialog renderButton={renderButton} />;
+});
+
+NewWorkflowButton.displayName = 'NewWorkflowButton';
diff --git a/invokeai/frontend/web/src/features/workflowLibrary/components/NewWorkflowConfirmationAlertDialog.tsx b/invokeai/frontend/web/src/features/workflowLibrary/components/NewWorkflowConfirmationAlertDialog.tsx
new file mode 100644
index 0000000000..b01d259da7
--- /dev/null
+++ b/invokeai/frontend/web/src/features/workflowLibrary/components/NewWorkflowConfirmationAlertDialog.tsx
@@ -0,0 +1,63 @@
+import { ConfirmationAlertDialog, Flex, Text, useDisclosure } from '@invoke-ai/ui-library';
+import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { nodeEditorReset } from 'features/nodes/store/nodesSlice';
+import { workflowModeChanged } from 'features/nodes/store/workflowSlice';
+import { addToast } from 'features/system/store/systemSlice';
+import { makeToast } from 'features/system/util/makeToast';
+import { memo, useCallback } from 'react';
+import { useTranslation } from 'react-i18next';
+
+type Props = {
+  renderButton: (onClick: () => void) => JSX.Element;
+};
+
+export const NewWorkflowConfirmationAlertDialog = memo((props: Props) => {
+  const { t } = useTranslation();
+  const dispatch = useAppDispatch();
+  const { isOpen, onOpen, onClose } = useDisclosure();
+  const isTouched = useAppSelector((s) => s.workflow.isTouched);
+
+  const handleNewWorkflow = useCallback(() => {
+    dispatch(nodeEditorReset());
+    dispatch(workflowModeChanged('edit'));
+
+    dispatch(
+      addToast(
+        makeToast({
+          title: t('workflows.newWorkflowCreated'),
+          status: 'success',
+        })
+      )
+    );
+
+    onClose();
+  }, [dispatch, onClose, t]);
+
+  const onClick = useCallback(() => {
+    if (!isTouched) {
+      handleNewWorkflow();
+      return;
+    }
+    onOpen();
+  }, [handleNewWorkflow, isTouched, onOpen]);
+
+  return (
+    <>
+      {props.renderButton(onClick)}
+
+      <ConfirmationAlertDialog
+        isOpen={isOpen}
+        onClose={onClose}
+        title={t('nodes.newWorkflow')}
+        acceptCallback={handleNewWorkflow}
+      >
+        <Flex flexDir="column" gap={2}>
+          <Text>{t('nodes.newWorkflowDesc')}</Text>
+          <Text variant="subtext">{t('nodes.newWorkflowDesc2')}</Text>
+        </Flex>
+      </ConfirmationAlertDialog>
+    </>
+  );
+});
+
+NewWorkflowConfirmationAlertDialog.displayName = 'NewWorkflowConfirmationAlertDialog';
diff --git a/invokeai/frontend/web/src/features/workflowLibrary/components/WorkflowLibraryButton.tsx b/invokeai/frontend/web/src/features/workflowLibrary/components/WorkflowLibraryButton.tsx
index 33c3cee2bb..09a484f1e5 100644
--- a/invokeai/frontend/web/src/features/workflowLibrary/components/WorkflowLibraryButton.tsx
+++ b/invokeai/frontend/web/src/features/workflowLibrary/components/WorkflowLibraryButton.tsx
@@ -2,7 +2,7 @@ import { IconButton, useDisclosure } from '@invoke-ai/ui-library';
 import { WorkflowLibraryModalContext } from 'features/workflowLibrary/context/WorkflowLibraryModalContext';
 import { memo } from 'react';
 import { useTranslation } from 'react-i18next';
-import { PiBooksBold } from 'react-icons/pi';
+import { PiFolderOpenBold } from 'react-icons/pi';
 
 import WorkflowLibraryModal from './WorkflowLibraryModal';
 
@@ -15,7 +15,7 @@ const WorkflowLibraryButton = () => {
       <IconButton
         aria-label={t('workflows.workflowLibrary')}
         tooltip={t('workflows.workflowLibrary')}
-        icon={<PiBooksBold />}
+        icon={<PiFolderOpenBold />}
         onClick={disclosure.onOpen}
         pointerEvents="auto"
       />
diff --git a/invokeai/frontend/web/src/features/workflowLibrary/components/WorkflowLibraryMenu/NewWorkflowMenuItem.tsx b/invokeai/frontend/web/src/features/workflowLibrary/components/WorkflowLibraryMenu/NewWorkflowMenuItem.tsx
index 8a41efc1b8..6c5baa584f 100644
--- a/invokeai/frontend/web/src/features/workflowLibrary/components/WorkflowLibraryMenu/NewWorkflowMenuItem.tsx
+++ b/invokeai/frontend/web/src/features/workflowLibrary/components/WorkflowLibraryMenu/NewWorkflowMenuItem.tsx
@@ -1,60 +1,22 @@
-import { ConfirmationAlertDialog, Flex, MenuItem, Text, useDisclosure } from '@invoke-ai/ui-library';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import { nodeEditorReset } from 'features/nodes/store/nodesSlice';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
+import { MenuItem } from '@invoke-ai/ui-library';
+import { NewWorkflowConfirmationAlertDialog } from 'features/workflowLibrary/components/NewWorkflowConfirmationAlertDialog';
 import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
-import { PiFlowArrowBold } from 'react-icons/pi';
+import { PiFilePlusBold } from 'react-icons/pi';
 
-const NewWorkflowMenuItem = () => {
+export const NewWorkflowMenuItem = memo(() => {
   const { t } = useTranslation();
-  const dispatch = useAppDispatch();
-  const { isOpen, onOpen, onClose } = useDisclosure();
-  const isTouched = useAppSelector((s) => s.workflow.isTouched);
 
-  const handleNewWorkflow = useCallback(() => {
-    dispatch(nodeEditorReset());
-
-    dispatch(
-      addToast(
-        makeToast({
-          title: t('workflows.newWorkflowCreated'),
-          status: 'success',
-        })
-      )
-    );
-
-    onClose();
-  }, [dispatch, onClose, t]);
-
-  const onClick = useCallback(() => {
-    if (!isTouched) {
-      handleNewWorkflow();
-      return;
-    }
-    onOpen();
-  }, [handleNewWorkflow, isTouched, onOpen]);
-
-  return (
-    <>
-      <MenuItem as="button" icon={<PiFlowArrowBold />} onClick={onClick}>
+  const renderButton = useCallback(
+    (onClick: () => void) => (
+      <MenuItem as="button" icon={<PiFilePlusBold />} onClick={onClick}>
         {t('nodes.newWorkflow')}
       </MenuItem>
-
-      <ConfirmationAlertDialog
-        isOpen={isOpen}
-        onClose={onClose}
-        title={t('nodes.newWorkflow')}
-        acceptCallback={handleNewWorkflow}
-      >
-        <Flex flexDir="column" gap={2}>
-          <Text>{t('nodes.newWorkflowDesc')}</Text>
-          <Text variant="subtext">{t('nodes.newWorkflowDesc2')}</Text>
-        </Flex>
-      </ConfirmationAlertDialog>
-    </>
+    ),
+    [t]
   );
-};
 
-export default memo(NewWorkflowMenuItem);
+  return <NewWorkflowConfirmationAlertDialog renderButton={renderButton} />;
+});
+
+NewWorkflowMenuItem.displayName = 'NewWorkflowMenuItem';
diff --git a/invokeai/frontend/web/src/features/workflowLibrary/components/WorkflowLibraryMenu/WorkflowLibraryMenu.tsx b/invokeai/frontend/web/src/features/workflowLibrary/components/WorkflowLibraryMenu/WorkflowLibraryMenu.tsx
index 73d0249d3d..55d8ac2626 100644
--- a/invokeai/frontend/web/src/features/workflowLibrary/components/WorkflowLibraryMenu/WorkflowLibraryMenu.tsx
+++ b/invokeai/frontend/web/src/features/workflowLibrary/components/WorkflowLibraryMenu/WorkflowLibraryMenu.tsx
@@ -8,7 +8,7 @@ import {
   useGlobalMenuClose,
 } from '@invoke-ai/ui-library';
 import DownloadWorkflowMenuItem from 'features/workflowLibrary/components/WorkflowLibraryMenu/DownloadWorkflowMenuItem';
-import NewWorkflowMenuItem from 'features/workflowLibrary/components/WorkflowLibraryMenu/NewWorkflowMenuItem';
+import { NewWorkflowMenuItem } from 'features/workflowLibrary/components/WorkflowLibraryMenu/NewWorkflowMenuItem';
 import SaveWorkflowAsMenuItem from 'features/workflowLibrary/components/WorkflowLibraryMenu/SaveWorkflowAsMenuItem';
 import SaveWorkflowMenuItem from 'features/workflowLibrary/components/WorkflowLibraryMenu/SaveWorkflowMenuItem';
 import SettingsMenuItem from 'features/workflowLibrary/components/WorkflowLibraryMenu/SettingsMenuItem';

From 34cc26a4ed26665820292933bdbbec4e29820074 Mon Sep 17 00:00:00 2001
From: Mary Hipp Rogers <maryhipp@gmail.com>
Date: Wed, 14 Feb 2024 10:04:12 -0500
Subject: [PATCH 007/411] revert to using fetch, add token if needed (#5720)

Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
---
 .../web/src/common/hooks/useDownloadImage.ts   | 18 ++++++++++++------
 1 file changed, 12 insertions(+), 6 deletions(-)

diff --git a/invokeai/frontend/web/src/common/hooks/useDownloadImage.ts b/invokeai/frontend/web/src/common/hooks/useDownloadImage.ts
index 3195426da3..26a17e1d0c 100644
--- a/invokeai/frontend/web/src/common/hooks/useDownloadImage.ts
+++ b/invokeai/frontend/web/src/common/hooks/useDownloadImage.ts
@@ -1,22 +1,28 @@
+import { useStore } from '@nanostores/react';
 import { useAppToaster } from 'app/components/Toaster';
+import { $authToken } from 'app/store/nanostores/authToken';
 import { useAppDispatch } from 'app/store/storeHooks';
 import { imageDownloaded } from 'features/gallery/store/actions';
 import { useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 
-import { useImageUrlToBlob } from './useImageUrlToBlob';
-
 export const useDownloadImage = () => {
   const toaster = useAppToaster();
   const { t } = useTranslation();
-  const imageUrlToBlob = useImageUrlToBlob();
   const dispatch = useAppDispatch();
+  const authToken = useStore($authToken);
 
   const downloadImage = useCallback(
     async (image_url: string, image_name: string) => {
       try {
-        const blob = await imageUrlToBlob(image_url);
-
+        const requestOpts = authToken
+          ? {
+              headers: {
+                Authorization: `Bearer ${authToken}`,
+              },
+            }
+          : {};
+        const blob = await fetch(image_url, requestOpts).then((resp) => resp.blob());
         if (!blob) {
           throw new Error('Unable to create Blob');
         }
@@ -40,7 +46,7 @@ export const useDownloadImage = () => {
         });
       }
     },
-    [t, toaster, imageUrlToBlob, dispatch]
+    [t, toaster, dispatch, authToken]
   );
 
   return { downloadImage };

From b77f6bd0ad5e8eb65e7854a063d6c2d540ae42ac Mon Sep 17 00:00:00 2001
From: Wubbbi <clari.skyrim63@gmail.com>
Date: Wed, 14 Feb 2024 09:04:55 +0100
Subject: [PATCH 008/411] Update accelerate 0.26.1 -> 0.27.0

---
 pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index a9a2157d8b..61bb9e7fa2 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -33,7 +33,7 @@ classifiers = [
 ]
 dependencies = [
   # Core generation dependencies, pinned for reproducible builds.
-  "accelerate==0.26.1",
+  "accelerate==0.27.0",
   "clip_anytorch==2.5.2",       # replacing "clip @ https://github.com/openai/CLIP/archive/eaa22acb90a5876642d0507623e859909230a52d.zip",
   "compel==2.0.2",
   "controlnet-aux==0.0.7",

From 5ed2f6e6c19ff14eba0142a5e3eee2d8dd141458 Mon Sep 17 00:00:00 2001
From: Wubbbi <clari.skyrim63@gmail.com>
Date: Wed, 14 Feb 2024 10:10:32 +0100
Subject: [PATCH 009/411] bump

---
 pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index 61bb9e7fa2..7f4b0d77f2 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -33,7 +33,7 @@ classifiers = [
 ]
 dependencies = [
   # Core generation dependencies, pinned for reproducible builds.
-  "accelerate==0.27.0",
+  "accelerate==0.27.2",
   "clip_anytorch==2.5.2",       # replacing "clip @ https://github.com/openai/CLIP/archive/eaa22acb90a5876642d0507623e859909230a52d.zip",
   "compel==2.0.2",
   "controlnet-aux==0.0.7",

From 2071972a8cc988200c5aacb38bc04bc60ed9c6c5 Mon Sep 17 00:00:00 2001
From: Jennifer Player <chainchompa@gmail.com>
Date: Wed, 14 Feb 2024 14:20:08 -0500
Subject: [PATCH 010/411] refactored to just use a new dnd context, got
 reordering working and fixed flicker

---
 .../src/common/components/IAISortableItem.tsx | 45 ++++++++++++
 .../Invocation/fields/LinearViewField.tsx     |  3 +-
 .../sidePanel/workflow/WorkflowLinearTab.tsx  | 68 +++++++++++--------
 .../src/features/nodes/store/workflowSlice.ts |  8 +--
 4 files changed, 91 insertions(+), 33 deletions(-)
 create mode 100644 invokeai/frontend/web/src/common/components/IAISortableItem.tsx

diff --git a/invokeai/frontend/web/src/common/components/IAISortableItem.tsx b/invokeai/frontend/web/src/common/components/IAISortableItem.tsx
new file mode 100644
index 0000000000..fd390b6f1d
--- /dev/null
+++ b/invokeai/frontend/web/src/common/components/IAISortableItem.tsx
@@ -0,0 +1,45 @@
+import { Box } from '@invoke-ai/ui-library';
+import { useDroppableTypesafe } from 'features/dnd/hooks/typesafeHooks';
+import type { TypesafeDroppableData } from 'features/dnd/types';
+import { isValidDrop } from 'features/dnd/util/isValidDrop';
+import { AnimatePresence } from 'framer-motion';
+import type { ReactNode } from 'react';
+import { memo, useRef } from 'react';
+import { v4 as uuidv4 } from 'uuid';
+
+import IAIDropOverlay from './IAIDropOverlay';
+
+type IAISortableItemProps = {
+  dropLabel?: ReactNode;
+  disabled?: boolean;
+  data?: TypesafeDroppableData;
+};
+
+const IAISortableItem = (props: IAISortableItemProps) => {
+  const { dropLabel, data, disabled } = props;
+  const dndId = useRef(uuidv4());
+
+  const { isOver, setNodeRef, active } = useDroppableTypesafe({
+    id: dndId.current,
+    disabled,
+    data,
+  });
+
+  return (
+    <Box
+      ref={setNodeRef}
+      position="absolute"
+      top={0}
+      insetInlineStart={0}
+      w="full"
+      h="full"
+      pointerEvents={active ? 'auto' : 'none'}
+    >
+      <AnimatePresence>
+        {isValidDrop(data, active) && <IAIDropOverlay isOver={isOver} label={dropLabel} />}
+      </AnimatePresence>
+    </Box>
+  );
+};
+
+export default memo(IAISortableItem);
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx
index 49a676008a..c4fbbb2cd7 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx
@@ -23,11 +23,12 @@ const LinearViewField = ({ nodeId, fieldName }: Props) => {
   const dispatch = useAppDispatch();
   const { isMouseOverNode, handleMouseOut, handleMouseOver } = useMouseOverNode(nodeId);
   const { t } = useTranslation();
+
   const handleRemoveField = useCallback(() => {
     dispatch(workflowExposedFieldRemoved({ nodeId, fieldName }));
   }, [dispatch, fieldName, nodeId]);
 
-  const { attributes, listeners, setNodeRef, transform, transition } = useSortable({ id: nodeId });
+  const { attributes, listeners, setNodeRef, transform, transition } = useSortable({ id: `${nodeId}.${fieldName}` });
 
   const style = {
     transform: CSS.Transform.toString(transform),
diff --git a/invokeai/frontend/web/src/features/nodes/components/sidePanel/workflow/WorkflowLinearTab.tsx b/invokeai/frontend/web/src/features/nodes/components/sidePanel/workflow/WorkflowLinearTab.tsx
index fa6bfff41d..3c7dae463c 100644
--- a/invokeai/frontend/web/src/features/nodes/components/sidePanel/workflow/WorkflowLinearTab.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/sidePanel/workflow/WorkflowLinearTab.tsx
@@ -1,15 +1,15 @@
-
-import { SortableContext, verticalListSortingStrategy } from '@dnd-kit/sortable';
+import { DndContext } from '@dnd-kit/core';
+import { arrayMove, SortableContext } from '@dnd-kit/sortable';
 import { Box, Flex } from '@invoke-ai/ui-library';
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
-import { useAppSelector } from 'app/store/storeHooks';
-import IAIDroppable from 'common/components/IAIDroppable';
+import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { IAINoContentFallback } from 'common/components/IAIImageFallback';
 import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
-import type { TypesafeDroppableData } from 'features/dnd/types';
+import type { DragEndEvent } from 'features/dnd/types';
 import LinearViewField from 'features/nodes/components/flow/nodes/Invocation/fields/LinearViewField';
-import { selectWorkflowSlice } from 'features/nodes/store/workflowSlice';
-import { memo, useMemo } from 'react';
+import { selectWorkflowSlice, workflowExposedFieldsReordered } from 'features/nodes/store/workflowSlice';
+import { FieldIdentifier } from 'features/nodes/types/field';
+import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 import { useGetOpenAPISchemaQuery } from 'services/api/endpoints/appInfo';
 
@@ -19,32 +19,46 @@ const WorkflowLinearTab = () => {
   const fields = useAppSelector(selector);
   const { isLoading } = useGetOpenAPISchemaQuery();
   const { t } = useTranslation();
+  const dispatch = useAppDispatch();
 
-  const droppableData = useMemo<TypesafeDroppableData | undefined>(
-    () => ({
-      id: 'current-image',
-      actionType: 'SET_CURRENT_IMAGE',
-    }),
-    []
+  const handleDragEnd = useCallback(
+    (event: DragEndEvent) => {
+      const { active, over } = event;
+      console.log({ active, over });
+      const fieldsStrings = fields.map((field) => `${field.nodeId}.${field.fieldName}`);
+
+      if (over && active.id !== over.id) {
+        const oldIndex = fieldsStrings.indexOf(active.id as string);
+        const newIndex = fieldsStrings.indexOf(over.id as string);
+
+        const newFields = arrayMove(fieldsStrings, oldIndex, newIndex)
+          .map((field) => fields.find((obj) => `${obj.nodeId}.${obj.fieldName}` === field))
+          .filter((field) => field) as FieldIdentifier[];
+
+        dispatch(workflowExposedFieldsReordered(newFields));
+      }
+    },
+    [dispatch, fields]
   );
 
   return (
     <Box position="relative" w="full" h="full">
-      <IAIDroppable data={droppableData} disabled={false} dropLabel="drop label" />
       <ScrollableContent>
-        <SortableContext items={fields.map((field) => field.nodeId)} strategy={verticalListSortingStrategy}>
-          <Flex position="relative" flexDir="column" alignItems="flex-start" p={1} gap={2} h="full" w="full">
-            {isLoading ? (
-              <IAINoContentFallback label={t('nodes.loadingNodes')} icon={null} />
-            ) : fields.length ? (
-              fields.map(({ nodeId, fieldName }) => (
-                <LinearViewField key={`${nodeId}.${fieldName}`} nodeId={nodeId} fieldName={fieldName} />
-              ))
-            ) : (
-              <IAINoContentFallback label={t('nodes.noFieldsLinearview')} icon={null} />
-            )}
-          </Flex>
-        </SortableContext>
+        <DndContext onDragEnd={handleDragEnd}>
+          <SortableContext items={fields.map((field) => `${field.nodeId}.${field.fieldName}`)}>
+            <Flex position="relative" flexDir="column" alignItems="flex-start" p={1} gap={2} h="full" w="full">
+              {isLoading ? (
+                <IAINoContentFallback label={t('nodes.loadingNodes')} icon={null} />
+              ) : fields.length ? (
+                fields.map(({ nodeId, fieldName }) => (
+                  <LinearViewField key={`${nodeId}.${fieldName}`} nodeId={nodeId} fieldName={fieldName} />
+                ))
+              ) : (
+                <IAINoContentFallback label={t('nodes.noFieldsLinearview')} icon={null} />
+              )}
+            </Flex>
+          </SortableContext>
+        </DndContext>
       </ScrollableContent>
     </Box>
   );
diff --git a/invokeai/frontend/web/src/features/nodes/store/workflowSlice.ts b/invokeai/frontend/web/src/features/nodes/store/workflowSlice.ts
index 2418f65ceb..f4dad3f668 100644
--- a/invokeai/frontend/web/src/features/nodes/store/workflowSlice.ts
+++ b/invokeai/frontend/web/src/features/nodes/store/workflowSlice.ts
@@ -42,11 +42,8 @@ export const workflowSlice = createSlice({
       state.exposedFields = state.exposedFields.filter((field) => !isEqual(field, action.payload));
       state.isTouched = true;
     },
-    workflowExposedFieldsReordered: (state, action: PayloadAction<string>) => {
-      state.exposedFields = action.payload.split(',').map((id) => {
-        const [nodeId, fieldName] = id.split('.');
-        return { nodeId, fieldName };
-      });
+    workflowExposedFieldsReordered: (state, action: PayloadAction<FieldIdentifier[]>) => {
+      state.exposedFields = action.payload;
       state.isTouched = true;
     },
     workflowNameChanged: (state, action: PayloadAction<string>) => {
@@ -113,6 +110,7 @@ export const workflowSlice = createSlice({
 export const {
   workflowExposedFieldAdded,
   workflowExposedFieldRemoved,
+  workflowExposedFieldsReordered,
   workflowNameChanged,
   workflowCategoryChanged,
   workflowDescriptionChanged,

From a948bd131075c555fa2ab0abecff6ae92111de9e Mon Sep 17 00:00:00 2001
From: Jennifer Player <chainchompa@gmail.com>
Date: Wed, 14 Feb 2024 14:47:28 -0500
Subject: [PATCH 011/411] refactored dndsortable to be its own component

---
 .../features/dnd/components/AppDndContext.tsx |  1 -
 .../features/dnd/components/DndSortable.tsx   | 32 +++++++++++++++++
 .../Invocation/fields/LinearViewField.tsx     |  2 +-
 .../sidePanel/workflow/WorkflowLinearTab.tsx  | 35 +++++++++----------
 4 files changed, 49 insertions(+), 21 deletions(-)
 create mode 100644 invokeai/frontend/web/src/features/dnd/components/DndSortable.tsx

diff --git a/invokeai/frontend/web/src/features/dnd/components/AppDndContext.tsx b/invokeai/frontend/web/src/features/dnd/components/AppDndContext.tsx
index a28b865366..799fa7135c 100644
--- a/invokeai/frontend/web/src/features/dnd/components/AppDndContext.tsx
+++ b/invokeai/frontend/web/src/features/dnd/components/AppDndContext.tsx
@@ -32,7 +32,6 @@ const AppDndContext = (props: PropsWithChildren) => {
 
   const handleDragEnd = useCallback(
     (event: DragEndEvent) => {
-      console.log('handling drag end', event.active.data.current);
       log.trace({ dragData: parseify(event.active.data.current) }, 'Drag ended');
       const overData = event.over?.data.current;
       if (!activeDragData || !overData) {
diff --git a/invokeai/frontend/web/src/features/dnd/components/DndSortable.tsx b/invokeai/frontend/web/src/features/dnd/components/DndSortable.tsx
new file mode 100644
index 0000000000..0e2f5d537a
--- /dev/null
+++ b/invokeai/frontend/web/src/features/dnd/components/DndSortable.tsx
@@ -0,0 +1,32 @@
+import type { DragEndEvent } from '@dnd-kit/core';
+import { MouseSensor, TouchSensor, useSensor, useSensors } from '@dnd-kit/core';
+import { SortableContext } from '@dnd-kit/sortable';
+import type { PropsWithChildren } from 'react';
+import { memo } from 'react';
+
+import { DndContextTypesafe } from './DndContextTypesafe';
+
+type Props = PropsWithChildren & {
+  items: string[];
+  onDragEnd(event: DragEndEvent): void;
+};
+
+const DndSortable = (props: Props) => {
+  const mouseSensor = useSensor(MouseSensor, {
+    activationConstraint: { distance: 10 },
+  });
+
+  const touchSensor = useSensor(TouchSensor, {
+    activationConstraint: { distance: 10 },
+  });
+
+  const sensors = useSensors(mouseSensor, touchSensor);
+
+  return (
+    <DndContextTypesafe sensors={sensors}>
+      <SortableContext items={props.items}>{props.children}</SortableContext>
+    </DndContextTypesafe>
+  );
+};
+
+export default memo(DndSortable);
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx
index c4fbbb2cd7..2aad446ddf 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx
@@ -31,7 +31,7 @@ const LinearViewField = ({ nodeId, fieldName }: Props) => {
   const { attributes, listeners, setNodeRef, transform, transition } = useSortable({ id: `${nodeId}.${fieldName}` });
 
   const style = {
-    transform: CSS.Transform.toString(transform),
+    transform: CSS.Translate.toString(transform),
     transition,
   };
 
diff --git a/invokeai/frontend/web/src/features/nodes/components/sidePanel/workflow/WorkflowLinearTab.tsx b/invokeai/frontend/web/src/features/nodes/components/sidePanel/workflow/WorkflowLinearTab.tsx
index 3c7dae463c..fa1767138e 100644
--- a/invokeai/frontend/web/src/features/nodes/components/sidePanel/workflow/WorkflowLinearTab.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/sidePanel/workflow/WorkflowLinearTab.tsx
@@ -1,14 +1,14 @@
-import { DndContext } from '@dnd-kit/core';
-import { arrayMove, SortableContext } from '@dnd-kit/sortable';
+import { arrayMove } from '@dnd-kit/sortable';
 import { Box, Flex } from '@invoke-ai/ui-library';
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { IAINoContentFallback } from 'common/components/IAIImageFallback';
 import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
+import DndSortable from 'features/dnd/components/DndSortable';
 import type { DragEndEvent } from 'features/dnd/types';
 import LinearViewField from 'features/nodes/components/flow/nodes/Invocation/fields/LinearViewField';
 import { selectWorkflowSlice, workflowExposedFieldsReordered } from 'features/nodes/store/workflowSlice';
-import { FieldIdentifier } from 'features/nodes/types/field';
+import type { FieldIdentifier } from 'features/nodes/types/field';
 import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 import { useGetOpenAPISchemaQuery } from 'services/api/endpoints/appInfo';
@@ -24,7 +24,6 @@ const WorkflowLinearTab = () => {
   const handleDragEnd = useCallback(
     (event: DragEndEvent) => {
       const { active, over } = event;
-      console.log({ active, over });
       const fieldsStrings = fields.map((field) => `${field.nodeId}.${field.fieldName}`);
 
       if (over && active.id !== over.id) {
@@ -44,21 +43,19 @@ const WorkflowLinearTab = () => {
   return (
     <Box position="relative" w="full" h="full">
       <ScrollableContent>
-        <DndContext onDragEnd={handleDragEnd}>
-          <SortableContext items={fields.map((field) => `${field.nodeId}.${field.fieldName}`)}>
-            <Flex position="relative" flexDir="column" alignItems="flex-start" p={1} gap={2} h="full" w="full">
-              {isLoading ? (
-                <IAINoContentFallback label={t('nodes.loadingNodes')} icon={null} />
-              ) : fields.length ? (
-                fields.map(({ nodeId, fieldName }) => (
-                  <LinearViewField key={`${nodeId}.${fieldName}`} nodeId={nodeId} fieldName={fieldName} />
-                ))
-              ) : (
-                <IAINoContentFallback label={t('nodes.noFieldsLinearview')} icon={null} />
-              )}
-            </Flex>
-          </SortableContext>
-        </DndContext>
+        <DndSortable onDragEnd={handleDragEnd} items={fields.map((field) => `${field.nodeId}.${field.fieldName}`)}>
+          <Flex position="relative" flexDir="column" alignItems="flex-start" p={1} gap={2} h="full" w="full">
+            {isLoading ? (
+              <IAINoContentFallback label={t('nodes.loadingNodes')} icon={null} />
+            ) : fields.length ? (
+              fields.map(({ nodeId, fieldName }) => (
+                <LinearViewField key={`${nodeId}.${fieldName}`} nodeId={nodeId} fieldName={fieldName} />
+              ))
+            ) : (
+              <IAINoContentFallback label={t('nodes.noFieldsLinearview')} icon={null} />
+            )}
+          </Flex>
+        </DndSortable>
       </ScrollableContent>
     </Box>
   );

From 21ba3c63de6384e8be88956ef4c56b7217e19b60 Mon Sep 17 00:00:00 2001
From: Jennifer Player <chainchompa@gmail.com>
Date: Wed, 14 Feb 2024 14:52:48 -0500
Subject: [PATCH 012/411] cleanup

---
 .../src/common/components/IAISortableItem.tsx | 45 -------------------
 .../features/dnd/components/AppDndContext.tsx |  1 -
 .../features/dnd/components/DndSortable.tsx   |  2 +-
 .../web/src/features/dnd/types/index.ts       |  9 ----
 .../Invocation/fields/LinearViewField.tsx     |  2 +-
 5 files changed, 2 insertions(+), 57 deletions(-)
 delete mode 100644 invokeai/frontend/web/src/common/components/IAISortableItem.tsx

diff --git a/invokeai/frontend/web/src/common/components/IAISortableItem.tsx b/invokeai/frontend/web/src/common/components/IAISortableItem.tsx
deleted file mode 100644
index fd390b6f1d..0000000000
--- a/invokeai/frontend/web/src/common/components/IAISortableItem.tsx
+++ /dev/null
@@ -1,45 +0,0 @@
-import { Box } from '@invoke-ai/ui-library';
-import { useDroppableTypesafe } from 'features/dnd/hooks/typesafeHooks';
-import type { TypesafeDroppableData } from 'features/dnd/types';
-import { isValidDrop } from 'features/dnd/util/isValidDrop';
-import { AnimatePresence } from 'framer-motion';
-import type { ReactNode } from 'react';
-import { memo, useRef } from 'react';
-import { v4 as uuidv4 } from 'uuid';
-
-import IAIDropOverlay from './IAIDropOverlay';
-
-type IAISortableItemProps = {
-  dropLabel?: ReactNode;
-  disabled?: boolean;
-  data?: TypesafeDroppableData;
-};
-
-const IAISortableItem = (props: IAISortableItemProps) => {
-  const { dropLabel, data, disabled } = props;
-  const dndId = useRef(uuidv4());
-
-  const { isOver, setNodeRef, active } = useDroppableTypesafe({
-    id: dndId.current,
-    disabled,
-    data,
-  });
-
-  return (
-    <Box
-      ref={setNodeRef}
-      position="absolute"
-      top={0}
-      insetInlineStart={0}
-      w="full"
-      h="full"
-      pointerEvents={active ? 'auto' : 'none'}
-    >
-      <AnimatePresence>
-        {isValidDrop(data, active) && <IAIDropOverlay isOver={isOver} label={dropLabel} />}
-      </AnimatePresence>
-    </Box>
-  );
-};
-
-export default memo(IAISortableItem);
diff --git a/invokeai/frontend/web/src/features/dnd/components/AppDndContext.tsx b/invokeai/frontend/web/src/features/dnd/components/AppDndContext.tsx
index 799fa7135c..f800e5c869 100644
--- a/invokeai/frontend/web/src/features/dnd/components/AppDndContext.tsx
+++ b/invokeai/frontend/web/src/features/dnd/components/AppDndContext.tsx
@@ -19,7 +19,6 @@ const AppDndContext = (props: PropsWithChildren) => {
 
   const handleDragStart = useCallback(
     (event: DragStartEvent) => {
-      console.log('handling drag start', event.active.data.current);
       log.trace({ dragData: parseify(event.active.data.current) }, 'Drag started');
       const activeData = event.active.data.current;
       if (!activeData) {
diff --git a/invokeai/frontend/web/src/features/dnd/components/DndSortable.tsx b/invokeai/frontend/web/src/features/dnd/components/DndSortable.tsx
index 0e2f5d537a..de82af796f 100644
--- a/invokeai/frontend/web/src/features/dnd/components/DndSortable.tsx
+++ b/invokeai/frontend/web/src/features/dnd/components/DndSortable.tsx
@@ -23,7 +23,7 @@ const DndSortable = (props: Props) => {
   const sensors = useSensors(mouseSensor, touchSensor);
 
   return (
-    <DndContextTypesafe sensors={sensors}>
+    <DndContextTypesafe onDragEnd={props.onDragEnd} sensors={sensors}>
       <SortableContext items={props.items}>{props.children}</SortableContext>
     </DndContextTypesafe>
   );
diff --git a/invokeai/frontend/web/src/features/dnd/types/index.ts b/invokeai/frontend/web/src/features/dnd/types/index.ts
index d4dc59de98..a13ac821fe 100644
--- a/invokeai/frontend/web/src/features/dnd/types/index.ts
+++ b/invokeai/frontend/web/src/features/dnd/types/index.ts
@@ -80,14 +80,6 @@ export type NodeFieldDraggableData = BaseDragData & {
   };
 };
 
-export type LinearViewFieldDraggableData = BaseDragData & {
-  payloadType: 'LINEAR_VIEW_FIELD';
-  payload: {
-    nodeId: string;
-    fieldName: string;
-  };
-};
-
 export type ImageDraggableData = BaseDragData & {
   payloadType: 'IMAGE_DTO';
   payload: { imageDTO: ImageDTO };
@@ -100,7 +92,6 @@ export type GallerySelectionDraggableData = BaseDragData & {
 
 export type TypesafeDraggableData =
   | NodeFieldDraggableData
-  | LinearViewFieldDraggableData
   | ImageDraggableData
   | GallerySelectionDraggableData;
 
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx
index 2aad446ddf..106e307889 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx
@@ -23,7 +23,7 @@ const LinearViewField = ({ nodeId, fieldName }: Props) => {
   const dispatch = useAppDispatch();
   const { isMouseOverNode, handleMouseOut, handleMouseOver } = useMouseOverNode(nodeId);
   const { t } = useTranslation();
-
+  
   const handleRemoveField = useCallback(() => {
     dispatch(workflowExposedFieldRemoved({ nodeId, fieldName }));
   }, [dispatch, fieldName, nodeId]);

From de832f68621a6c9aea4449ed0bc029e6b334877b Mon Sep 17 00:00:00 2001
From: Jennifer Player <chainchompa@gmail.com>
Date: Wed, 14 Feb 2024 15:00:18 -0500
Subject: [PATCH 013/411] formatting

---
 invokeai/frontend/web/src/features/dnd/types/index.ts | 5 +----
 1 file changed, 1 insertion(+), 4 deletions(-)

diff --git a/invokeai/frontend/web/src/features/dnd/types/index.ts b/invokeai/frontend/web/src/features/dnd/types/index.ts
index a13ac821fe..6e680b4ba9 100644
--- a/invokeai/frontend/web/src/features/dnd/types/index.ts
+++ b/invokeai/frontend/web/src/features/dnd/types/index.ts
@@ -90,10 +90,7 @@ export type GallerySelectionDraggableData = BaseDragData & {
   payload: { boardId: BoardId };
 };
 
-export type TypesafeDraggableData =
-  | NodeFieldDraggableData
-  | ImageDraggableData
-  | GallerySelectionDraggableData;
+export type TypesafeDraggableData = NodeFieldDraggableData | ImageDraggableData | GallerySelectionDraggableData;
 
 export interface UseDroppableTypesafeArguments extends Omit<UseDroppableArguments, 'data'> {
   data?: TypesafeDroppableData;

From 30dae0f5aac4ed9cdf8b36c038ead15dd8f8093a Mon Sep 17 00:00:00 2001
From: Kent Keirsey <31807370+hipsterusername@users.noreply.github.com>
Date: Tue, 13 Feb 2024 21:49:42 -0500
Subject: [PATCH 014/411] adding back skipped layer

---
 invokeai/backend/model_management/seamless.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/invokeai/backend/model_management/seamless.py b/invokeai/backend/model_management/seamless.py
index e145c6f481..eb04770a06 100644
--- a/invokeai/backend/model_management/seamless.py
+++ b/invokeai/backend/model_management/seamless.py
@@ -30,6 +30,8 @@ def set_seamless(model: Union[UNet2DConditionModel, AutoencoderKL], seamless_axe
     # Callable: (input: Tensor, weight: Tensor, bias: Optional[Tensor]) -> Tensor
     to_restore: list[tuple[nn.Conv2d | nn.ConvTranspose2d, Callable]] = []
     try:
+        # Hard coded to skip down block layers, allowing for seamless tiling at the expense of prompt adherence 
+        skipped_layers = 1
         for m_name, m in model.named_modules():
             if not isinstance(m, (nn.Conv2d, nn.ConvTranspose2d)):
                 continue
@@ -40,8 +42,7 @@ def set_seamless(model: Union[UNet2DConditionModel, AutoencoderKL], seamless_axe
                 block_num = int(block_num)
                 resnet_num = int(resnet_num)
 
-                # Could be configurable to allow skipping arbitrary numbers of down blocks
-                if block_num >= len(model.down_blocks):
+                if block_num >= len(model.down_blocks)  - skipped_layers:
                     continue
 
                 # Skip the second resnet (could be configurable)

From 17d5f7bebd9b2effd8367dca66e4462da7bba380 Mon Sep 17 00:00:00 2001
From: Kent Keirsey <31807370+hipsterusername@users.noreply.github.com>
Date: Tue, 13 Feb 2024 22:11:48 -0500
Subject: [PATCH 015/411] Critical Space Removal

---
 invokeai/backend/model_management/seamless.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/invokeai/backend/model_management/seamless.py b/invokeai/backend/model_management/seamless.py
index eb04770a06..1fe7d54089 100644
--- a/invokeai/backend/model_management/seamless.py
+++ b/invokeai/backend/model_management/seamless.py
@@ -42,7 +42,7 @@ def set_seamless(model: Union[UNet2DConditionModel, AutoencoderKL], seamless_axe
                 block_num = int(block_num)
                 resnet_num = int(resnet_num)
 
-                if block_num >= len(model.down_blocks)  - skipped_layers:
+                if block_num >= len(model.down_blocks) - skipped_layers:
                     continue
 
                 # Skip the second resnet (could be configurable)

From ff9bd040cc334f8ffcba13c159a5b3099403217a Mon Sep 17 00:00:00 2001
From: blessedcoolant <54517381+blessedcoolant@users.noreply.github.com>
Date: Wed, 14 Feb 2024 23:01:49 +0530
Subject: [PATCH 016/411] possible fix: Seamless not working with Custom VAE's

---
 invokeai/backend/model_management/seamless.py |  2 +-
 .../nodes/util/graph/addHrfToGraph.ts         | 11 +++++-----
 .../util/graph/addSeamlessToLinearGraph.ts    | 15 +++++++++++--
 .../nodes/util/graph/addVAEToGraph.ts         | 22 ++++++++++---------
 4 files changed, 32 insertions(+), 18 deletions(-)

diff --git a/invokeai/backend/model_management/seamless.py b/invokeai/backend/model_management/seamless.py
index 1fe7d54089..fb9112b56d 100644
--- a/invokeai/backend/model_management/seamless.py
+++ b/invokeai/backend/model_management/seamless.py
@@ -30,7 +30,7 @@ def set_seamless(model: Union[UNet2DConditionModel, AutoencoderKL], seamless_axe
     # Callable: (input: Tensor, weight: Tensor, bias: Optional[Tensor]) -> Tensor
     to_restore: list[tuple[nn.Conv2d | nn.ConvTranspose2d, Callable]] = []
     try:
-        # Hard coded to skip down block layers, allowing for seamless tiling at the expense of prompt adherence 
+        # Hard coded to skip down block layers, allowing for seamless tiling at the expense of prompt adherence
         skipped_layers = 1
         for m_name, m in model.named_modules():
             if not isinstance(m, (nn.Conv2d, nn.ConvTranspose2d)):
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/addHrfToGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/addHrfToGraph.ts
index daa214364d..3020934e3b 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/addHrfToGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/addHrfToGraph.ts
@@ -23,6 +23,7 @@ import {
   NOISE,
   NOISE_HRF,
   RESIZE_HRF,
+  SEAMLESS,
   VAE_LOADER,
 } from './constants';
 import { setMetadataReceivingNode, upsertMetadata } from './metadata';
@@ -30,7 +31,6 @@ import { setMetadataReceivingNode, upsertMetadata } from './metadata';
 // Copy certain connections from previous DENOISE_LATENTS to new DENOISE_LATENTS_HRF.
 function copyConnectionsToDenoiseLatentsHrf(graph: NonNullableGraph): void {
   const destinationFields = [
-    'vae',
     'control',
     'ip_adapter',
     'metadata',
@@ -107,9 +107,10 @@ export const addHrfToGraph = (state: RootState, graph: NonNullableGraph): void =
   }
   const log = logger('txt2img');
 
-  const { vae } = state.generation;
+  const { vae, seamlessXAxis, seamlessYAxis } = state.generation;
   const { hrfStrength, hrfEnabled, hrfMethod } = state.hrf;
   const isAutoVae = !vae;
+  const isSeamlessEnabled = seamlessXAxis || seamlessYAxis;
   const width = state.generation.width;
   const height = state.generation.height;
   const optimalDimension = selectOptimalDimension(state);
@@ -158,7 +159,7 @@ export const addHrfToGraph = (state: RootState, graph: NonNullableGraph): void =
     },
     {
       source: {
-        node_id: isAutoVae ? MAIN_MODEL_LOADER : VAE_LOADER,
+        node_id: isAutoVae ? MAIN_MODEL_LOADER : isSeamlessEnabled ? SEAMLESS : VAE_LOADER,
         field: 'vae',
       },
       destination: {
@@ -259,7 +260,7 @@ export const addHrfToGraph = (state: RootState, graph: NonNullableGraph): void =
   graph.edges.push(
     {
       source: {
-        node_id: isAutoVae ? MAIN_MODEL_LOADER : VAE_LOADER,
+        node_id: isAutoVae ? MAIN_MODEL_LOADER : isSeamlessEnabled ? SEAMLESS : VAE_LOADER,
         field: 'vae',
       },
       destination: {
@@ -322,7 +323,7 @@ export const addHrfToGraph = (state: RootState, graph: NonNullableGraph): void =
   graph.edges.push(
     {
       source: {
-        node_id: isAutoVae ? MAIN_MODEL_LOADER : VAE_LOADER,
+        node_id: isAutoVae ? MAIN_MODEL_LOADER : isSeamlessEnabled ? SEAMLESS : VAE_LOADER,
         field: 'vae',
       },
       destination: {
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/addSeamlessToLinearGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/addSeamlessToLinearGraph.ts
index 850b2a65bd..803437e968 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/addSeamlessToLinearGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/addSeamlessToLinearGraph.ts
@@ -14,6 +14,7 @@ import {
   SDXL_IMAGE_TO_IMAGE_GRAPH,
   SDXL_TEXT_TO_IMAGE_GRAPH,
   SEAMLESS,
+  VAE_LOADER,
 } from './constants';
 import { upsertMetadata } from './metadata';
 
@@ -23,7 +24,8 @@ export const addSeamlessToLinearGraph = (
   modelLoaderNodeId: string
 ): void => {
   // Remove Existing UNet Connections
-  const { seamlessXAxis, seamlessYAxis } = state.generation;
+  const { seamlessXAxis, seamlessYAxis, vae } = state.generation;
+  const isAutoVae = !vae;
 
   graph.nodes[SEAMLESS] = {
     id: SEAMLESS,
@@ -32,6 +34,15 @@ export const addSeamlessToLinearGraph = (
     seamless_y: seamlessYAxis,
   } as SeamlessModeInvocation;
 
+  if (!isAutoVae) {
+    graph.nodes[VAE_LOADER] = {
+      type: 'vae_loader',
+      id: VAE_LOADER,
+      is_intermediate: true,
+      vae_model: vae,
+    };
+  }
+
   if (seamlessXAxis) {
     upsertMetadata(graph, {
       seamless_x: seamlessXAxis,
@@ -75,7 +86,7 @@ export const addSeamlessToLinearGraph = (
     },
     {
       source: {
-        node_id: modelLoaderNodeId,
+        node_id: isAutoVae ? modelLoaderNodeId : VAE_LOADER,
         field: 'vae',
       },
       destination: {
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/addVAEToGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/addVAEToGraph.ts
index b886c9b7d5..40d943b796 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/addVAEToGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/addVAEToGraph.ts
@@ -21,6 +21,7 @@ import {
   SDXL_IMAGE_TO_IMAGE_GRAPH,
   SDXL_REFINER_INPAINT_CREATE_MASK,
   SDXL_TEXT_TO_IMAGE_GRAPH,
+  SEAMLESS,
   TEXT_TO_IMAGE_GRAPH,
   VAE_LOADER,
 } from './constants';
@@ -31,15 +32,16 @@ export const addVAEToGraph = (
   graph: NonNullableGraph,
   modelLoaderNodeId: string = MAIN_MODEL_LOADER
 ): void => {
-  const { vae, canvasCoherenceMode } = state.generation;
+  const { vae, canvasCoherenceMode, seamlessXAxis, seamlessYAxis } = state.generation;
   const { boundingBoxScaleMethod } = state.canvas;
   const { refinerModel } = state.sdxl;
 
   const isUsingScaledDimensions = ['auto', 'manual'].includes(boundingBoxScaleMethod);
 
   const isAutoVae = !vae;
+  const isSeamlessEnabled = seamlessXAxis || seamlessYAxis;
 
-  if (!isAutoVae) {
+  if (!isAutoVae && !isSeamlessEnabled) {
     graph.nodes[VAE_LOADER] = {
       type: 'vae_loader',
       id: VAE_LOADER,
@@ -56,7 +58,7 @@ export const addVAEToGraph = (
   ) {
     graph.edges.push({
       source: {
-        node_id: isAutoVae ? modelLoaderNodeId : VAE_LOADER,
+        node_id: isAutoVae ? modelLoaderNodeId : isSeamlessEnabled ? SEAMLESS : VAE_LOADER,
         field: 'vae',
       },
       destination: {
@@ -74,7 +76,7 @@ export const addVAEToGraph = (
   ) {
     graph.edges.push({
       source: {
-        node_id: isAutoVae ? modelLoaderNodeId : VAE_LOADER,
+        node_id: isAutoVae ? modelLoaderNodeId : isSeamlessEnabled ? SEAMLESS : VAE_LOADER,
         field: 'vae',
       },
       destination: {
@@ -92,7 +94,7 @@ export const addVAEToGraph = (
   ) {
     graph.edges.push({
       source: {
-        node_id: isAutoVae ? modelLoaderNodeId : VAE_LOADER,
+        node_id: isAutoVae ? modelLoaderNodeId : isSeamlessEnabled ? SEAMLESS : VAE_LOADER,
         field: 'vae',
       },
       destination: {
@@ -111,7 +113,7 @@ export const addVAEToGraph = (
     graph.edges.push(
       {
         source: {
-          node_id: isAutoVae ? modelLoaderNodeId : VAE_LOADER,
+          node_id: isAutoVae ? modelLoaderNodeId : isSeamlessEnabled ? SEAMLESS : VAE_LOADER,
           field: 'vae',
         },
         destination: {
@@ -121,7 +123,7 @@ export const addVAEToGraph = (
       },
       {
         source: {
-          node_id: isAutoVae ? modelLoaderNodeId : VAE_LOADER,
+          node_id: isAutoVae ? modelLoaderNodeId : isSeamlessEnabled ? SEAMLESS : VAE_LOADER,
           field: 'vae',
         },
         destination: {
@@ -131,7 +133,7 @@ export const addVAEToGraph = (
       },
       {
         source: {
-          node_id: isAutoVae ? modelLoaderNodeId : VAE_LOADER,
+          node_id: isAutoVae ? modelLoaderNodeId : isSeamlessEnabled ? SEAMLESS : VAE_LOADER,
           field: 'vae',
         },
         destination: {
@@ -145,7 +147,7 @@ export const addVAEToGraph = (
     if (canvasCoherenceMode !== 'unmasked') {
       graph.edges.push({
         source: {
-          node_id: isAutoVae ? modelLoaderNodeId : VAE_LOADER,
+          node_id: isAutoVae ? modelLoaderNodeId : isSeamlessEnabled ? SEAMLESS : VAE_LOADER,
           field: 'vae',
         },
         destination: {
@@ -160,7 +162,7 @@ export const addVAEToGraph = (
     if (graph.id === SDXL_CANVAS_INPAINT_GRAPH || graph.id === SDXL_CANVAS_OUTPAINT_GRAPH) {
       graph.edges.push({
         source: {
-          node_id: isAutoVae ? modelLoaderNodeId : VAE_LOADER,
+          node_id: isAutoVae ? modelLoaderNodeId : isSeamlessEnabled ? SEAMLESS : VAE_LOADER,
           field: 'vae',
         },
         destination: {

From d7f6af1f070764ece52fc936b72ec625d465a3cc Mon Sep 17 00:00:00 2001
From: blessedcoolant <54517381+blessedcoolant@users.noreply.github.com>
Date: Thu, 15 Feb 2024 02:15:55 +0530
Subject: [PATCH 017/411] possible fix: seamless not being seamless with baked

---
 .../features/nodes/util/graph/addHrfToGraph.ts   |  6 +++---
 .../features/nodes/util/graph/addVAEToGraph.ts   | 16 ++++++++--------
 2 files changed, 11 insertions(+), 11 deletions(-)

diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/addHrfToGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/addHrfToGraph.ts
index 3020934e3b..7413302fa5 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/addHrfToGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/addHrfToGraph.ts
@@ -159,7 +159,7 @@ export const addHrfToGraph = (state: RootState, graph: NonNullableGraph): void =
     },
     {
       source: {
-        node_id: isAutoVae ? MAIN_MODEL_LOADER : isSeamlessEnabled ? SEAMLESS : VAE_LOADER,
+        node_id: isSeamlessEnabled ? SEAMLESS : isAutoVae ? MAIN_MODEL_LOADER : VAE_LOADER,
         field: 'vae',
       },
       destination: {
@@ -260,7 +260,7 @@ export const addHrfToGraph = (state: RootState, graph: NonNullableGraph): void =
   graph.edges.push(
     {
       source: {
-        node_id: isAutoVae ? MAIN_MODEL_LOADER : isSeamlessEnabled ? SEAMLESS : VAE_LOADER,
+        node_id: isSeamlessEnabled ? SEAMLESS : isAutoVae ? MAIN_MODEL_LOADER : VAE_LOADER,
         field: 'vae',
       },
       destination: {
@@ -323,7 +323,7 @@ export const addHrfToGraph = (state: RootState, graph: NonNullableGraph): void =
   graph.edges.push(
     {
       source: {
-        node_id: isAutoVae ? MAIN_MODEL_LOADER : isSeamlessEnabled ? SEAMLESS : VAE_LOADER,
+        node_id: isSeamlessEnabled ? SEAMLESS : isAutoVae ? MAIN_MODEL_LOADER : VAE_LOADER,
         field: 'vae',
       },
       destination: {
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/addVAEToGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/addVAEToGraph.ts
index 40d943b796..95781d08e7 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/addVAEToGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/addVAEToGraph.ts
@@ -58,7 +58,7 @@ export const addVAEToGraph = (
   ) {
     graph.edges.push({
       source: {
-        node_id: isAutoVae ? modelLoaderNodeId : isSeamlessEnabled ? SEAMLESS : VAE_LOADER,
+        node_id: isSeamlessEnabled ? SEAMLESS : isAutoVae ? modelLoaderNodeId : VAE_LOADER,
         field: 'vae',
       },
       destination: {
@@ -76,7 +76,7 @@ export const addVAEToGraph = (
   ) {
     graph.edges.push({
       source: {
-        node_id: isAutoVae ? modelLoaderNodeId : isSeamlessEnabled ? SEAMLESS : VAE_LOADER,
+        node_id: isSeamlessEnabled ? SEAMLESS : isAutoVae ? modelLoaderNodeId : VAE_LOADER,
         field: 'vae',
       },
       destination: {
@@ -94,7 +94,7 @@ export const addVAEToGraph = (
   ) {
     graph.edges.push({
       source: {
-        node_id: isAutoVae ? modelLoaderNodeId : isSeamlessEnabled ? SEAMLESS : VAE_LOADER,
+        node_id: isSeamlessEnabled ? SEAMLESS : isAutoVae ? modelLoaderNodeId : VAE_LOADER,
         field: 'vae',
       },
       destination: {
@@ -113,7 +113,7 @@ export const addVAEToGraph = (
     graph.edges.push(
       {
         source: {
-          node_id: isAutoVae ? modelLoaderNodeId : isSeamlessEnabled ? SEAMLESS : VAE_LOADER,
+          node_id: isSeamlessEnabled ? SEAMLESS : isAutoVae ? modelLoaderNodeId : VAE_LOADER,
           field: 'vae',
         },
         destination: {
@@ -123,7 +123,7 @@ export const addVAEToGraph = (
       },
       {
         source: {
-          node_id: isAutoVae ? modelLoaderNodeId : isSeamlessEnabled ? SEAMLESS : VAE_LOADER,
+          node_id: isSeamlessEnabled ? SEAMLESS : isAutoVae ? modelLoaderNodeId : VAE_LOADER,
           field: 'vae',
         },
         destination: {
@@ -133,7 +133,7 @@ export const addVAEToGraph = (
       },
       {
         source: {
-          node_id: isAutoVae ? modelLoaderNodeId : isSeamlessEnabled ? SEAMLESS : VAE_LOADER,
+          node_id: isSeamlessEnabled ? SEAMLESS : isAutoVae ? modelLoaderNodeId : VAE_LOADER,
           field: 'vae',
         },
         destination: {
@@ -147,7 +147,7 @@ export const addVAEToGraph = (
     if (canvasCoherenceMode !== 'unmasked') {
       graph.edges.push({
         source: {
-          node_id: isAutoVae ? modelLoaderNodeId : isSeamlessEnabled ? SEAMLESS : VAE_LOADER,
+          node_id: isSeamlessEnabled ? SEAMLESS : isAutoVae ? modelLoaderNodeId : VAE_LOADER,
           field: 'vae',
         },
         destination: {
@@ -162,7 +162,7 @@ export const addVAEToGraph = (
     if (graph.id === SDXL_CANVAS_INPAINT_GRAPH || graph.id === SDXL_CANVAS_OUTPAINT_GRAPH) {
       graph.edges.push({
         source: {
-          node_id: isAutoVae ? modelLoaderNodeId : isSeamlessEnabled ? SEAMLESS : VAE_LOADER,
+          node_id: isSeamlessEnabled ? SEAMLESS : isAutoVae ? modelLoaderNodeId : VAE_LOADER,
           field: 'vae',
         },
         destination: {

From fc278c5cb17c6ad98824b6a67a1c5e71aa9f0bfc Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 14 Feb 2024 16:52:48 +1100
Subject: [PATCH 018/411] fix(images_default): correct get_metadata error
 message

The error was misleading, indicating an issue with getting the image DTO, when it was actually an issue with getting metadata.
---
 invokeai/app/services/images/images_default.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/invokeai/app/services/images/images_default.py b/invokeai/app/services/images/images_default.py
index 74aeeccca5..ff21731a50 100644
--- a/invokeai/app/services/images/images_default.py
+++ b/invokeai/app/services/images/images_default.py
@@ -154,7 +154,7 @@ class ImageService(ImageServiceABC):
             self.__invoker.services.logger.error("Image record not found")
             raise
         except Exception as e:
-            self.__invoker.services.logger.error("Problem getting image DTO")
+            self.__invoker.services.logger.error("Problem getting image metadata")
             raise e
 
     def get_workflow(self, image_name: str) -> Optional[WorkflowWithoutID]:

From 792131be0129edc06c8bc9697542703bdfb5fb43 Mon Sep 17 00:00:00 2001
From: Jennifer Player <chainchompa@gmail.com>
Date: Wed, 14 Feb 2024 17:27:21 -0500
Subject: [PATCH 019/411] added drag icon, added vertical strategy for smoother
 scrolling

---
 .../assets/images/popoverImages/image-2.png   | Bin 0 -> 664217 bytes
 .../assets/images/popoverImages/image.png     | Bin 0 -> 591843 bytes
 invokeai/frontend/web/public/locales/en.json  |   1 +
 .../features/dnd/components/DndSortable.tsx   |   6 +-
 .../Invocation/fields/LinearViewField.tsx     |  64 ++++++++++--------
 5 files changed, 42 insertions(+), 29 deletions(-)
 create mode 100644 invokeai/frontend/web/public/assets/images/popoverImages/image-2.png
 create mode 100644 invokeai/frontend/web/public/assets/images/popoverImages/image.png

diff --git a/invokeai/frontend/web/public/assets/images/popoverImages/image-2.png b/invokeai/frontend/web/public/assets/images/popoverImages/image-2.png
new file mode 100644
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literal 0
HcmV?d00001

diff --git a/invokeai/frontend/web/public/locales/en.json b/invokeai/frontend/web/public/locales/en.json
index 0fe833db39..40e43eb73e 100644
--- a/invokeai/frontend/web/public/locales/en.json
+++ b/invokeai/frontend/web/public/locales/en.json
@@ -997,6 +997,7 @@
         "problemSettingTitle": "Problem Setting Title",
         "reloadNodeTemplates": "Reload Node Templates",
         "removeLinearView": "Remove from Linear View",
+        "reorderLinearView": "Reorder Linear View",
         "newWorkflow": "New Workflow",
         "newWorkflowDesc": "Create a new workflow?",
         "newWorkflowDesc2": "Your current workflow has unsaved changes.",
diff --git a/invokeai/frontend/web/src/features/dnd/components/DndSortable.tsx b/invokeai/frontend/web/src/features/dnd/components/DndSortable.tsx
index de82af796f..b04980f6cf 100644
--- a/invokeai/frontend/web/src/features/dnd/components/DndSortable.tsx
+++ b/invokeai/frontend/web/src/features/dnd/components/DndSortable.tsx
@@ -1,6 +1,6 @@
 import type { DragEndEvent } from '@dnd-kit/core';
 import { MouseSensor, TouchSensor, useSensor, useSensors } from '@dnd-kit/core';
-import { SortableContext } from '@dnd-kit/sortable';
+import { SortableContext, verticalListSortingStrategy } from '@dnd-kit/sortable';
 import type { PropsWithChildren } from 'react';
 import { memo } from 'react';
 
@@ -24,7 +24,9 @@ const DndSortable = (props: Props) => {
 
   return (
     <DndContextTypesafe onDragEnd={props.onDragEnd} sensors={sensors}>
-      <SortableContext items={props.items}>{props.children}</SortableContext>
+      <SortableContext items={props.items} strategy={verticalListSortingStrategy}>
+        {props.children}
+      </SortableContext>
     </DndContextTypesafe>
   );
 };
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx
index 106e307889..b6187aa532 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx
@@ -8,7 +8,7 @@ import { workflowExposedFieldRemoved } from 'features/nodes/store/workflowSlice'
 import { HANDLE_TOOLTIP_OPEN_DELAY } from 'features/nodes/types/constants';
 import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
-import { PiInfoBold, PiTrashSimpleBold } from 'react-icons/pi';
+import { PiInfoBold, PiTrashSimpleBold, PiDotsSixVerticalBold } from 'react-icons/pi';
 
 import EditableFieldTitle from './EditableFieldTitle';
 import FieldTooltipContent from './FieldTooltipContent';
@@ -23,7 +23,7 @@ const LinearViewField = ({ nodeId, fieldName }: Props) => {
   const dispatch = useAppDispatch();
   const { isMouseOverNode, handleMouseOut, handleMouseOver } = useMouseOverNode(nodeId);
   const { t } = useTranslation();
-  
+
   const handleRemoveField = useCallback(() => {
     dispatch(workflowExposedFieldRemoved({ nodeId, fieldName }));
   }, [dispatch, fieldName, nodeId]);
@@ -40,39 +40,49 @@ const LinearViewField = ({ nodeId, fieldName }: Props) => {
       onMouseEnter={handleMouseOver}
       onMouseLeave={handleMouseOut}
       layerStyle="second"
+      alignItems="center"
       position="relative"
       borderRadius="base"
       w="full"
       p={4}
-      flexDir="column"
+      paddingLeft={0}
       ref={setNodeRef}
       style={style}
-      {...attributes}
-      {...listeners}
     >
-      <Flex>
-        <EditableFieldTitle nodeId={nodeId} fieldName={fieldName} kind="input" />
-        <Spacer />
-        <Tooltip
-          label={<FieldTooltipContent nodeId={nodeId} fieldName={fieldName} kind="input" />}
-          openDelay={HANDLE_TOOLTIP_OPEN_DELAY}
-          placement="top"
-        >
-          <Flex h="full" alignItems="center">
-            <Icon fontSize="sm" color="base.300" as={PiInfoBold} />
-          </Flex>
-        </Tooltip>
-        <IconButton
-          aria-label={t('nodes.removeLinearView')}
-          tooltip={t('nodes.removeLinearView')}
-          variant="ghost"
-          size="sm"
-          onClick={handleRemoveField}
-          icon={<PiTrashSimpleBold />}
-        />
+      <IconButton
+        aria-label={t('nodes.reorderLinearView')}
+        variant="ghost"
+        icon={<PiDotsSixVerticalBold />}
+        {...listeners}
+        {...attributes}
+        mx={2}
+        height="full"
+      />
+      <Flex flexDir="column" w="full">
+        <Flex alignItems="center">
+          <EditableFieldTitle nodeId={nodeId} fieldName={fieldName} kind="input" />
+          <Spacer />
+          <Tooltip
+            label={<FieldTooltipContent nodeId={nodeId} fieldName={fieldName} kind="input" />}
+            openDelay={HANDLE_TOOLTIP_OPEN_DELAY}
+            placement="top"
+          >
+            <Flex h="full" alignItems="center">
+              <Icon fontSize="sm" color="base.300" as={PiInfoBold} />
+            </Flex>
+          </Tooltip>
+          <IconButton
+            aria-label={t('nodes.removeLinearView')}
+            tooltip={t('nodes.removeLinearView')}
+            variant="ghost"
+            size="sm"
+            onClick={handleRemoveField}
+            icon={<PiTrashSimpleBold />}
+          />
+        </Flex>
+        <InputFieldRenderer nodeId={nodeId} fieldName={fieldName} />
+        <NodeSelectionOverlay isSelected={false} isHovered={isMouseOverNode} />
       </Flex>
-      <InputFieldRenderer nodeId={nodeId} fieldName={fieldName} />
-      <NodeSelectionOverlay isSelected={false} isHovered={isMouseOverNode} />
     </Flex>
   );
 };

From e0f2404c0005ef8a9da4949eedda883e6fafc8be Mon Sep 17 00:00:00 2001
From: Jennifer Player <chainchompa@gmail.com>
Date: Wed, 14 Feb 2024 18:07:15 -0500
Subject: [PATCH 020/411] added reset to default back in, removed unneeded
 activation constraints

---
 .../assets/images/popoverImages/image-2.png    | Bin 664217 -> 0 bytes
 .../assets/images/popoverImages/image.png      | Bin 591843 -> 0 bytes
 .../features/dnd/components/DndSortable.tsx    |  13 +------------
 .../Invocation/fields/LinearViewField.tsx      |  14 +++++++++++++-
 4 files changed, 14 insertions(+), 13 deletions(-)
 delete mode 100644 invokeai/frontend/web/public/assets/images/popoverImages/image-2.png
 delete mode 100644 invokeai/frontend/web/public/assets/images/popoverImages/image.png

diff --git a/invokeai/frontend/web/public/assets/images/popoverImages/image-2.png b/invokeai/frontend/web/public/assets/images/popoverImages/image-2.png
deleted file mode 100644
index 8db14cde13ce82356266a136b609d56165e1328b..0000000000000000000000000000000000000000
GIT binary patch
literal 0
HcmV?d00001

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diff --git a/invokeai/frontend/web/src/features/dnd/components/DndSortable.tsx b/invokeai/frontend/web/src/features/dnd/components/DndSortable.tsx
index b04980f6cf..786e1ce9c2 100644
--- a/invokeai/frontend/web/src/features/dnd/components/DndSortable.tsx
+++ b/invokeai/frontend/web/src/features/dnd/components/DndSortable.tsx
@@ -1,5 +1,4 @@
 import type { DragEndEvent } from '@dnd-kit/core';
-import { MouseSensor, TouchSensor, useSensor, useSensors } from '@dnd-kit/core';
 import { SortableContext, verticalListSortingStrategy } from '@dnd-kit/sortable';
 import type { PropsWithChildren } from 'react';
 import { memo } from 'react';
@@ -12,18 +11,8 @@ type Props = PropsWithChildren & {
 };
 
 const DndSortable = (props: Props) => {
-  const mouseSensor = useSensor(MouseSensor, {
-    activationConstraint: { distance: 10 },
-  });
-
-  const touchSensor = useSensor(TouchSensor, {
-    activationConstraint: { distance: 10 },
-  });
-
-  const sensors = useSensors(mouseSensor, touchSensor);
-
   return (
-    <DndContextTypesafe onDragEnd={props.onDragEnd} sensors={sensors}>
+    <DndContextTypesafe onDragEnd={props.onDragEnd}>
       <SortableContext items={props.items} strategy={verticalListSortingStrategy}>
         {props.children}
       </SortableContext>
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx
index afd64ca0bd..d0a30ecc3c 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx
@@ -3,12 +3,13 @@ import { CSS } from '@dnd-kit/utilities';
 import { Flex, Icon, IconButton, Spacer, Tooltip } from '@invoke-ai/ui-library';
 import { useAppDispatch } from 'app/store/storeHooks';
 import NodeSelectionOverlay from 'common/components/NodeSelectionOverlay';
+import { useFieldOriginalValue } from 'features/nodes/hooks/useFieldOriginalValue';
 import { useMouseOverNode } from 'features/nodes/hooks/useMouseOverNode';
 import { workflowExposedFieldRemoved } from 'features/nodes/store/workflowSlice';
 import { HANDLE_TOOLTIP_OPEN_DELAY } from 'features/nodes/types/constants';
 import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
-import { PiDotsSixVerticalBold, PiInfoBold, PiTrashSimpleBold } from 'react-icons/pi';
+import { PiArrowCounterClockwiseBold, PiDotsSixVerticalBold, PiInfoBold, PiTrashSimpleBold } from 'react-icons/pi';
 
 import EditableFieldTitle from './EditableFieldTitle';
 import FieldTooltipContent from './FieldTooltipContent';
@@ -21,6 +22,7 @@ type Props = {
 
 const LinearViewField = ({ nodeId, fieldName }: Props) => {
   const dispatch = useAppDispatch();
+  const { isValueChanged, onReset } = useFieldOriginalValue(nodeId, fieldName);
   const { isMouseOverNode, handleMouseOut, handleMouseOver } = useMouseOverNode(nodeId);
   const { t } = useTranslation();
 
@@ -62,6 +64,16 @@ const LinearViewField = ({ nodeId, fieldName }: Props) => {
         <Flex alignItems="center">
           <EditableFieldTitle nodeId={nodeId} fieldName={fieldName} kind="input" />
           <Spacer />
+          {isValueChanged && (
+            <IconButton
+              aria-label={t('nodes.resetToDefaultValue')}
+              tooltip={t('nodes.resetToDefaultValue')}
+              variant="ghost"
+              size="sm"
+              onClick={onReset}
+              icon={<PiArrowCounterClockwiseBold />}
+            />
+          )}
           <Tooltip
             label={<FieldTooltipContent nodeId={nodeId} fieldName={fieldName} kind="input" />}
             openDelay={HANDLE_TOOLTIP_OPEN_DELAY}

From c5aeb36230f9af7a1e842d4c45007720fe958be1 Mon Sep 17 00:00:00 2001
From: Copper Phosphate <cu3po42@gmail.com>
Date: Tue, 13 Feb 2024 22:01:30 +0100
Subject: [PATCH 021/411] fix: repair Dockerfile for ROCm

With these changes, the Docker image can be built and executed
successfully on hosts with AMD devices with ROCm acceleration.
Previously, a ROCm-enabled version of torch would be installed, but
later removed during installation of InvokeAI itself. This was caused by
InvokeAI needing a newer torch version than was previously installed.

The fix consists of multiple components:
* Update the hardcoded versions of torch and torchvision to the versions
  currently used in pyproject.toml, so that a new version need not be
  installed during installation of InvokeAI.
* Specify --extra-index-url on installation of InvokeAI so that even if
  a verison mismatch occurs, the correct torch version should still be
  installed. This also necessitates changing --index-url to
  --extra-index-url for the Torch repo. Otherwise non-torch dependencies
  would not be found.
* In run.sh, build the image for the selected service.
---
 docker/Dockerfile | 8 ++++----
 docker/run.sh     | 2 +-
 2 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/docker/Dockerfile b/docker/Dockerfile
index c89a5773f7..2de4d0ffce 100644
--- a/docker/Dockerfile
+++ b/docker/Dockerfile
@@ -18,8 +18,8 @@ ENV INVOKEAI_SRC=/opt/invokeai
 ENV VIRTUAL_ENV=/opt/venv/invokeai
 
 ENV PATH="$VIRTUAL_ENV/bin:$PATH"
-ARG TORCH_VERSION=2.1.0
-ARG TORCHVISION_VERSION=0.16
+ARG TORCH_VERSION=2.1.2
+ARG TORCHVISION_VERSION=0.16.2
 ARG GPU_DRIVER=cuda
 ARG TARGETPLATFORM="linux/amd64"
 # unused but available
@@ -35,7 +35,7 @@ RUN --mount=type=cache,target=/root/.cache/pip \
     if [ "$TARGETPLATFORM" = "linux/arm64" ] || [ "$GPU_DRIVER" = "cpu" ]; then \
         extra_index_url_arg="--extra-index-url https://download.pytorch.org/whl/cpu"; \
     elif [ "$GPU_DRIVER" = "rocm" ]; then \
-        extra_index_url_arg="--index-url https://download.pytorch.org/whl/rocm5.6"; \
+        extra_index_url_arg="--extra-index-url https://download.pytorch.org/whl/rocm5.6"; \
     else \
         extra_index_url_arg="--extra-index-url https://download.pytorch.org/whl/cu121"; \
     fi &&\
@@ -54,7 +54,7 @@ RUN --mount=type=cache,target=/root/.cache/pip \
     if [ "$GPU_DRIVER" = "cuda" ] && [ "$TARGETPLATFORM" = "linux/amd64" ]; then \
         pip install -e ".[xformers]"; \
     else \
-        pip install -e "."; \
+        pip install $extra_index_url_arg -e "."; \
     fi
 
 # #### Build the Web UI ------------------------------------
diff --git a/docker/run.sh b/docker/run.sh
index 409df508dd..d413e53453 100755
--- a/docker/run.sh
+++ b/docker/run.sh
@@ -21,7 +21,7 @@ run() {
     printf "%s\n" "$build_args"
   fi
 
-  docker compose build $build_args
+  docker compose build $build_args $service_name
   unset build_args
 
   printf "%s\n" "starting service $service_name"

From 163b22a7b30de0eb88b238738418990caae55ed7 Mon Sep 17 00:00:00 2001
From: Millun Atluri <millun.atluri@gmail.com>
Date: Thu, 15 Feb 2024 07:34:31 -0700
Subject: [PATCH 022/411] {release} 3.7.0

---
 invokeai/version/invokeai_version.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/invokeai/version/invokeai_version.py b/invokeai/version/invokeai_version.py
index 6a45bf596d..46f67e7f8d 100644
--- a/invokeai/version/invokeai_version.py
+++ b/invokeai/version/invokeai_version.py
@@ -1 +1 @@
-__version__ = "3.6.3"
+__version__ = "3.7.0"

From f36b5990ed3bedd352cdb966b2196c46305e5c03 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Thu, 15 Feb 2024 12:57:30 +1100
Subject: [PATCH 023/411] fix(ui): do not provide auth headers for openapi.json

---
 .../frontend/web/src/services/api/index.ts    | 24 +++++++++++--------
 1 file changed, 14 insertions(+), 10 deletions(-)

diff --git a/invokeai/frontend/web/src/services/api/index.ts b/invokeai/frontend/web/src/services/api/index.ts
index 8cb9aa8618..6a342bb72d 100644
--- a/invokeai/frontend/web/src/services/api/index.ts
+++ b/invokeai/frontend/web/src/services/api/index.ts
@@ -52,10 +52,22 @@ const dynamicBaseQuery: BaseQueryFn<string | FetchArgs, unknown, FetchBaseQueryE
   const baseUrl = $baseUrl.get();
   const authToken = $authToken.get();
   const projectId = $projectId.get();
+  const isOpenAPIRequest =
+    (args instanceof Object && args.url.includes('openapi.json')) ||
+    (typeof args === 'string' && args.includes('openapi.json'));
 
   const fetchBaseQueryArgs: FetchBaseQueryArgs = {
     baseUrl: baseUrl ? `${baseUrl}/api/v1` : `${window.location.href.replace(/\/$/, '')}/api/v1`,
-    prepareHeaders: (headers) => {
+  };
+
+  // When fetching the openapi.json, we need to remove circular references from the JSON.
+  if (isOpenAPIRequest) {
+    fetchBaseQueryArgs.jsonReplacer = getCircularReplacer();
+  }
+
+  // openapi.json isn't protected by authorization, but all other requests need to include the auth token and project id.
+  if (!isOpenAPIRequest) {
+    fetchBaseQueryArgs.prepareHeaders = (headers) => {
       if (authToken) {
         headers.set('Authorization', `Bearer ${authToken}`);
       }
@@ -64,15 +76,7 @@ const dynamicBaseQuery: BaseQueryFn<string | FetchArgs, unknown, FetchBaseQueryE
       }
 
       return headers;
-    },
-  };
-
-  // When fetching the openapi.json, we need to remove circular references from the JSON.
-  if (
-    (args instanceof Object && args.url.includes('openapi.json')) ||
-    (typeof args === 'string' && args.includes('openapi.json'))
-  ) {
-    fetchBaseQueryArgs.jsonReplacer = getCircularReplacer();
+    };
   }
 
   const rawBaseQuery = fetchBaseQuery(fetchBaseQueryArgs);

From d43b843c23db99ca743c2eed00dde5990c6c007a Mon Sep 17 00:00:00 2001
From: B N <berndnieschalk@gmail.com>
Date: Sat, 17 Feb 2024 13:02:07 +0100
Subject: [PATCH 024/411] translationBot(ui): update translation (German)

Currently translated at 80.2% (1143 of 1424 strings)

Co-authored-by: B N <berndnieschalk@gmail.com>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/de/
Translation: InvokeAI/Web UI
---
 invokeai/frontend/web/public/locales/de.json | 91 ++++++++++++--------
 1 file changed, 57 insertions(+), 34 deletions(-)

diff --git a/invokeai/frontend/web/public/locales/de.json b/invokeai/frontend/web/public/locales/de.json
index 3dca1267dc..44ae981b02 100644
--- a/invokeai/frontend/web/public/locales/de.json
+++ b/invokeai/frontend/web/public/locales/de.json
@@ -81,7 +81,7 @@
         "outputs": "Ausgabe",
         "data": "Daten",
         "safetensors": "Safe-Tensors",
-        "outpaint": "Ausmalen",
+        "outpaint": "Outpaint (Außen ausmalen)",
         "details": "Details",
         "format": "Format",
         "unknown": "Unbekannt",
@@ -110,17 +110,17 @@
         "nextPage": "Nächste Seite",
         "unknownError": "Unbekannter Fehler",
         "unsaved": "Nicht gespeichert",
-        "aboutDesc": "Verwenden Sie Invoke für die Arbeit? Dann siehe hier:",
+        "aboutDesc": "Verwenden Sie Invoke für die Arbeit? Siehe hier:",
         "localSystem": "Lokales System",
         "orderBy": "Ordnen nach",
-        "saveAs": "Speicher als",
+        "saveAs": "Speichern als",
         "updated": "Aktualisiert",
         "copy": "Kopieren",
         "aboutHeading": "Nutzen Sie Ihre kreative Energie"
     },
     "gallery": {
         "generations": "Erzeugungen",
-        "showGenerations": "Zeige Erzeugnisse",
+        "showGenerations": "Zeige Ergebnisse",
         "uploads": "Uploads",
         "showUploads": "Zeige Uploads",
         "galleryImageSize": "Bildgröße",
@@ -150,9 +150,9 @@
         "problemDeletingImagesDesc": "Ein oder mehrere Bilder konnten nicht gelöscht werden",
         "starImage": "Bild markieren",
         "assets": "Ressourcen",
-        "unstarImage": "Markierung Entfernen",
+        "unstarImage": "Markierung entfernen",
         "image": "Bild",
-        "deleteSelection": "Lösche markierte",
+        "deleteSelection": "Lösche Auswahl",
         "dropToUpload": "$t(gallery.drop) zum hochladen",
         "dropOrUpload": "$t(gallery.drop) oder hochladen",
         "drop": "Ablegen",
@@ -590,7 +590,15 @@
         "general": "Allgemein",
         "hiresStrength": "High Res Stärke",
         "hidePreview": "Verstecke Vorschau",
-        "showPreview": "Zeige Vorschau"
+        "showPreview": "Zeige Vorschau",
+        "aspect": "Seitenverhältnis",
+        "aspectRatio": "Seitenverhältnis",
+        "scheduler": "Planer",
+        "aspectRatioFree": "Frei",
+        "setToOptimalSizeTooLarge": "$t(parameters.setToOptimalSize) (kann zu groß sein)",
+        "lockAspectRatio": "Seitenverhältnis sperren",
+        "swapDimensions": "Seitenverhältnis umkehren",
+        "setToOptimalSize": "Optimiere Größe für Modell"
     },
     "settings": {
         "displayInProgress": "Bilder in Bearbeitung anzeigen",
@@ -606,7 +614,9 @@
         "useSlidersForAll": "Schieberegler für alle Optionen verwenden",
         "showAdvancedOptions": "Erweiterte Optionen anzeigen",
         "alternateCanvasLayout": "Alternatives Leinwand-Layout",
-        "clearIntermediatesDesc1": "Das Löschen der Zwischenprodukte setzt Leinwand und ControlNet zurück."
+        "clearIntermediatesDesc1": "Das Löschen der Zwischenprodukte setzt Leinwand und ControlNet zurück.",
+        "favoriteSchedulers": "Lieblings-Planer",
+        "favoriteSchedulersPlaceholder": "Keine Planer favorisiert"
     },
     "toast": {
         "tempFoldersEmptied": "Temp-Ordner geleert",
@@ -733,23 +743,23 @@
     "accessibility": {
         "modelSelect": "Modell-Auswahl",
         "uploadImage": "Bild hochladen",
-        "previousImage": "Voriges Bild",
+        "previousImage": "Vorheriges Bild",
         "useThisParameter": "Benutze diesen Parameter",
-        "copyMetadataJson": "Kopiere Metadaten JSON",
+        "copyMetadataJson": "Kopiere JSON-Metadaten",
         "zoomIn": "Vergrößern",
         "rotateClockwise": "Im Uhrzeigersinn drehen",
         "flipHorizontally": "Horizontal drehen",
         "flipVertically": "Vertikal drehen",
         "modifyConfig": "Optionen einstellen",
         "toggleAutoscroll": "Auroscroll ein/ausschalten",
-        "toggleLogViewer": "Log Betrachter ein/ausschalten",
+        "toggleLogViewer": "Log-Betrachter ein/ausschalten",
         "showOptionsPanel": "Seitenpanel anzeigen",
         "reset": "Zurücksetzten",
         "nextImage": "Nächstes Bild",
         "zoomOut": "Verkleinern",
         "rotateCounterClockwise": "Gegen den Uhrzeigersinn drehen",
-        "showGalleryPanel": "Galeriefenster anzeigen",
-        "exitViewer": "Betrachten beenden",
+        "showGalleryPanel": "Galerie-Panel anzeigen",
+        "exitViewer": "Betrachter beenden",
         "menu": "Menü",
         "loadMore": "Mehr laden",
         "invokeProgressBar": "Invoke Fortschrittsanzeige",
@@ -759,7 +769,7 @@
         "about": "Über"
     },
     "boards": {
-        "autoAddBoard": "Automatisches Hinzufügen zum Ordner",
+        "autoAddBoard": "Automatisches Hinzufügen zum Board",
         "topMessage": "Dieser Ordner enthält Bilder die in den folgenden Funktionen verwendet werden:",
         "move": "Bewegen",
         "menuItemAutoAdd": "Auto-Hinzufügen zu diesem Ordner",
@@ -768,13 +778,13 @@
         "noMatching": "Keine passenden Ordner",
         "selectBoard": "Ordner aussuchen",
         "cancel": "Abbrechen",
-        "addBoard": "Ordner hinzufügen",
+        "addBoard": "Board hinzufügen",
         "uncategorized": "Ohne Kategorie",
         "downloadBoard": "Ordner runterladen",
         "changeBoard": "Ordner wechseln",
         "loading": "Laden...",
         "clearSearch": "Suche leeren",
-        "bottomMessage": "Durch das Löschen dieses Ordners und seiner Bilder werden alle Funktionen zurückgesetzt, die sie derzeit verwenden.",
+        "bottomMessage": "Löschen des Boards und seiner Bilder setzt alle Funktionen zurück, die sie gerade verwenden.",
         "deleteBoardOnly": "Nur Ordner löschen",
         "deleteBoard": "Löschen Ordner",
         "deleteBoardAndImages": "Löschen Ordner und Bilder",
@@ -865,11 +875,11 @@
         "maxFaces": "Maximale Anzahl Gesichter",
         "resizeSimple": "Größe ändern (einfach)",
         "large": "Groß",
-        "modelSize": "Modell Größe",
+        "modelSize": "Modellgröße",
         "small": "Klein",
         "base": "Basis",
-        "depthAnything": "Depth Anything / \"Tiefe irgendwas\"",
-        "depthAnythingDescription": "Erstellung einer Tiefenkarte mit der Depth Anything-Technik"
+        "depthAnything": "Depth Anything",
+        "depthAnythingDescription": "Erstellung einer Tiefenkarte mit der Depth-Anything-Technik"
     },
     "queue": {
         "status": "Status",
@@ -904,7 +914,7 @@
         "batchValues": "Stapel Werte",
         "queueCountPrediction": "{{promptsCount}} Prompts × {{iterations}} Iterationen -> {{count}} Generationen",
         "queuedCount": "{{pending}} wartenden Elemente",
-        "clearQueueAlertDialog": "Die Warteschlange leeren, stoppt den aktuellen Prozess und leert die Warteschlange komplett.",
+        "clearQueueAlertDialog": "\"Die Warteschlange leeren\" stoppt den aktuellen Prozess und leert die Warteschlange komplett.",
         "completedIn": "Fertig in",
         "cancelBatchSucceeded": "Stapel abgebrochen",
         "cancelBatch": "Stapel stoppen",
@@ -913,20 +923,20 @@
         "cancelBatchFailed": "Problem beim Abbruch vom Stapel",
         "clearQueueAlertDialog2": "Warteschlange wirklich leeren?",
         "pruneSucceeded": "{{item_count}} abgeschlossene Elemente aus der Warteschlange entfernt",
-        "pauseSucceeded": "Prozessor angehalten",
+        "pauseSucceeded": "Prozess angehalten",
         "cancelFailed": "Problem beim Stornieren des Auftrags",
-        "pauseFailed": "Problem beim Anhalten des Prozessors",
+        "pauseFailed": "Problem beim Anhalten des Prozesses",
         "front": "Vorne",
         "pruneTooltip": "Bereinigen Sie {{item_count}} abgeschlossene Aufträge",
-        "resumeFailed": "Problem beim wieder aufnehmen von Prozessor",
+        "resumeFailed": "Problem beim Fortsetzen des Prozesses",
         "pruneFailed": "Problem beim leeren der Warteschlange",
-        "pauseTooltip": "Pause von Prozessor",
+        "pauseTooltip": "Prozess anhalten",
         "back": "Hinten",
-        "resumeSucceeded": "Prozessor wieder aufgenommen",
-        "resumeTooltip": "Prozessor wieder aufnehmen",
+        "resumeSucceeded": "Prozess wird fortgesetzt",
+        "resumeTooltip": "Prozess wieder aufnehmen",
         "time": "Zeit",
-        "batchQueuedDesc_one": "{{count}} Eintrag ans {{direction}} der Wartschlange hinzugefügt",
-        "batchQueuedDesc_other": "{{count}} Einträge ans {{direction}} der Wartschlange hinzugefügt",
+        "batchQueuedDesc_one": "{{count}} Eintrag an {{direction}} der Wartschlange hinzugefügt",
+        "batchQueuedDesc_other": "{{count}} Einträge an {{direction}} der Wartschlange hinzugefügt",
         "openQueue": "Warteschlange öffnen",
         "batchFailedToQueue": "Fehler beim Einreihen in die Stapelverarbeitung",
         "batchFieldValues": "Stapelverarbeitungswerte",
@@ -965,7 +975,7 @@
     },
     "popovers": {
         "noiseUseCPU": {
-            "heading": "Nutze Prozessor rauschen",
+            "heading": "Nutze CPU-Rauschen",
             "paragraphs": [
                 "Entscheidet, ob auf der CPU oder GPU Rauschen erzeugt wird.",
                 "Mit aktiviertem CPU-Rauschen wird ein bestimmter Seedwert das gleiche Bild auf jeder Maschine erzeugen.",
@@ -1084,12 +1094,18 @@
                 "Wie stark wird das ControlNet das generierte Bild beeinflussen wird."
             ],
             "heading": "Einfluss"
+        },
+        "paramScheduler": {
+            "paragraphs": [
+                "\"Planer\" definiert, wie iterativ Rauschen zu einem Bild hinzugefügt wird, oder wie ein Sample bei der Ausgabe eines Modells aktualisiert wird."
+            ],
+            "heading": "Planer"
         }
     },
     "ui": {
         "lockRatio": "Verhältnis sperren",
-        "hideProgressImages": "Verstecke Prozess Bild",
-        "showProgressImages": "Zeige Prozess Bild",
+        "hideProgressImages": "Fortschrittsbilder verbergen",
+        "showProgressImages": "Fortschrittsbilder anzeigen",
         "swapSizes": "Tausche Größen"
     },
     "invocationCache": {
@@ -1336,12 +1352,12 @@
         },
         "control": {
             "title": "Kontrolle",
-            "controlAdaptersTab": "Kontroll Adapter",
-            "ipTab": "Bild Beschreibung"
+            "controlAdaptersTab": "Kontroll-Adapter",
+            "ipTab": "Bild-Prompts"
         },
         "compositing": {
             "coherenceTab": "Kohärenzpass",
-            "infillTab": "Füllung",
+            "infillTab": "Füllung / Infill",
             "title": "Compositing"
         }
     },
@@ -1379,5 +1395,12 @@
     },
     "app": {
         "storeNotInitialized": "App-Store ist nicht initialisiert"
+    },
+    "sdxl": {
+        "concatPromptStyle": "Verknüpfen von Prompt & Stil",
+        "scheduler": "Planer"
+    },
+    "dynamicPrompts": {
+        "showDynamicPrompts": "Dynamische Prompts anzeigen"
     }
 }

From 716b584f03952636eee49469296f9fd493eb4a6b Mon Sep 17 00:00:00 2001
From: Riccardo Giovanetti <riccardo.giovanetti@gmail.com>
Date: Sun, 18 Feb 2024 15:02:01 +0100
Subject: [PATCH 025/411] translationBot(ui): update translation (Italian)

Currently translated at 97.1% (1384 of 1424 strings)

Co-authored-by: Riccardo Giovanetti <riccardo.giovanetti@gmail.com>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/it/
Translation: InvokeAI/Web UI
---
 invokeai/frontend/web/public/locales/it.json | 12 ++++++++++--
 1 file changed, 10 insertions(+), 2 deletions(-)

diff --git a/invokeai/frontend/web/public/locales/it.json b/invokeai/frontend/web/public/locales/it.json
index 590e9ee28f..8a427482dc 100644
--- a/invokeai/frontend/web/public/locales/it.json
+++ b/invokeai/frontend/web/public/locales/it.json
@@ -1138,7 +1138,11 @@
         "unsupportedAnyOfLength": "unione di troppi elementi ({{count}})",
         "clearWorkflowDesc": "Cancellare questo flusso di lavoro e avviarne uno nuovo?",
         "clearWorkflow": "Cancella il flusso di lavoro",
-        "clearWorkflowDesc2": "Il tuo flusso di lavoro attuale presenta modifiche non salvate."
+        "clearWorkflowDesc2": "Il tuo flusso di lavoro attuale presenta modifiche non salvate.",
+        "viewMode": "Utilizzare nella vista lineare",
+        "reorderLinearView": "Riordina la vista lineare",
+        "editMode": "Modifica nell'editor del flusso di lavoro",
+        "resetToDefaultValue": "Ripristina il valore predefinito"
     },
     "boards": {
         "autoAddBoard": "Aggiungi automaticamente bacheca",
@@ -1241,7 +1245,11 @@
         "large": "Grande",
         "small": "Piccolo",
         "depthAnythingDescription": "Generazione di mappe di profondità utilizzando la tecnica Depth Anything",
-        "modelSize": "Dimensioni del modello"
+        "modelSize": "Dimensioni del modello",
+        "dwOpenposeDescription": "Stima della posa umana utilizzando DW Openpose",
+        "face": "Viso",
+        "body": "Corpo",
+        "hands": "Mani"
     },
     "queue": {
         "queueFront": "Aggiungi all'inizio della coda",

From 3e48edda6f7bb7e64fa2e7e1ca77a22a44f82c97 Mon Sep 17 00:00:00 2001
From: gogurtenjoyer <36354352+gogurtenjoyer@users.noreply.github.com>
Date: Mon, 19 Feb 2024 11:53:35 -0500
Subject: [PATCH 026/411] add latent-upscale to communityNodes.md (#5728)

Adds the 'latent upscale' community node
---
 docs/nodes/communityNodes.md | 8 ++++++++
 1 file changed, 8 insertions(+)

diff --git a/docs/nodes/communityNodes.md b/docs/nodes/communityNodes.md
index 906111f45b..33dddad162 100644
--- a/docs/nodes/communityNodes.md
+++ b/docs/nodes/communityNodes.md
@@ -32,6 +32,7 @@ To use a community workflow, download the the `.json` node graph file and load i
     + [Image to Character Art Image Nodes](#image-to-character-art-image-nodes)
     + [Image Picker](#image-picker)
     + [Image Resize Plus](#image-resize-plus)
+    + [Latent Upscale](#latent-upscale)
     + [Load Video Frame](#load-video-frame)
     + [Make 3D](#make-3d)
     + [Mask Operations](#mask-operations)
@@ -290,6 +291,13 @@ View:
 </br><img src="https://raw.githubusercontent.com/VeyDlin/image-resize-plus-node/master/.readme/node.png" width="500" />
 
 
+--------------------------------
+### Latent Upscale
+
+**Description:** This node uses a small (~2.4mb) model to upscale the latents used in a Stable Diffusion 1.5 or Stable Diffusion XL image generation, rather than the typical interpolation method, avoiding the traditional downsides of the latent upscale technique.
+
+**Node Link:** [https://github.com/gogurtenjoyer/latent-upscale](https://github.com/gogurtenjoyer/latent-upscale)
+
 --------------------------------
 ### Load Video Frame
 

From f0d4c7196082de4bf65fa5ef486e176171e700f9 Mon Sep 17 00:00:00 2001
From: Jennifer Player <chainchompa@gmail.com>
Date: Mon, 19 Feb 2024 12:50:11 -0500
Subject: [PATCH 027/411] updated tooltip popovers

---
 .../InformationalPopover/constants.ts         | 105 +++++++++++++++++-
 .../ParamControlAdapterBeginEnd.tsx           |  11 +-
 .../ParamControlAdapterProcessorSelect.tsx    |   5 +-
 .../hrf/components/ParamHrfMethod.tsx         |   5 +-
 .../hrf/components/ParamHrfStrength.tsx       |   5 +-
 .../hrf/components/ParamHrfToggle.tsx         |   5 +-
 .../src/features/lora/components/LoRACard.tsx |  49 ++++----
 .../features/lora/components/LoRASelect.tsx   |   5 +-
 .../ParamInfillPatchmatchDownscaleSize.tsx    |   5 +-
 .../components/Core/ParamHeight.tsx           |   5 +-
 .../parameters/components/Core/ParamWidth.tsx |   5 +-
 .../ImageSize/AspectRatioSelect.tsx           |   5 +-
 .../ImageToImage/ImageToImageFit.tsx          |   5 +-
 .../MainModel/ParamMainModelSelect.tsx        |  29 +++--
 .../Seamless/ParamSeamlessXAxis.tsx           |   5 +-
 .../Seamless/ParamSeamlessYAxis.tsx           |   5 +-
 .../SDXLRefiner/ParamSDXLRefinerCFGScale.tsx  |   5 +-
 .../ParamSDXLRefinerModelSelect.tsx           |   5 +-
 ...ParamSDXLRefinerNegativeAestheticScore.tsx |   5 +-
 ...ParamSDXLRefinerPositiveAestheticScore.tsx |   5 +-
 .../SDXLRefiner/ParamSDXLRefinerScheduler.tsx |   5 +-
 .../SDXLRefiner/ParamSDXLRefinerStart.tsx     |   5 +-
 .../SDXLRefiner/ParamSDXLRefinerSteps.tsx     |   5 +-
 23 files changed, 224 insertions(+), 65 deletions(-)

diff --git a/invokeai/frontend/web/src/common/components/InformationalPopover/constants.ts b/invokeai/frontend/web/src/common/components/InformationalPopover/constants.ts
index bdcd1ca9a4..2e88c28df6 100644
--- a/invokeai/frontend/web/src/common/components/InformationalPopover/constants.ts
+++ b/invokeai/frontend/web/src/common/components/InformationalPopover/constants.ts
@@ -13,28 +13,46 @@ export type Feature =
   | 'compositingCoherenceSteps'
   | 'compositingStrength'
   | 'compositingMaskAdjustments'
+  | 'controlNet'
   | 'controlNetBeginEnd'
   | 'controlNetControlMode'
+  | 'controlNetProcessor'
   | 'controlNetResizeMode'
-  | 'controlNet'
   | 'controlNetWeight'
   | 'dynamicPrompts'
   | 'dynamicPromptsMaxPrompts'
   | 'dynamicPromptsSeedBehaviour'
+  | 'imageFit'
   | 'infillMethod'
   | 'lora'
+  | 'loraWeight'
   | 'noiseUseCPU'
+  | 'paramAspect'
   | 'paramCFGScale'
   | 'paramCFGRescaleMultiplier'
   | 'paramDenoisingStrength'
+  | 'paramHeight'
+  | 'paramHrf'
   | 'paramIterations'
   | 'paramModel'
   | 'paramRatio'
   | 'paramSeed'
   | 'paramSteps'
+  | 'paramUpscaleMethod'
   | 'paramVAE'
   | 'paramVAEPrecision'
-  | 'scaleBeforeProcessing';
+  | 'paramWidth'
+  | 'patchmatchDownScaleSize'
+  | 'refinerModel'
+  | 'refinerNegativeAestheticScore'
+  | 'refinerPositiveAestheticScore'
+  | 'refinerScheduler'
+  | 'refinerStart'
+  | 'refinerSteps'
+  | 'refinerCfgScale'
+  | 'scaleBeforeProcessing'
+  | 'seamlessTilingXAxis'
+  | 'seamlessTilingYAxis';
 
 export type PopoverData = PopoverProps & {
   image?: string;
@@ -46,21 +64,57 @@ export const POPOVER_DATA: { [key in Feature]?: PopoverData } = {
   paramNegativeConditioning: {
     placement: 'right',
   },
+  clipSkip: {
+    href: 'https://support.invoke.ai/support/solutions/articles/151000178161-advanced-settings',
+  },
   controlNet: {
     href: 'https://support.invoke.ai/support/solutions/articles/151000105880',
   },
+  controlNetBeginEnd: {
+    href: 'https://support.invoke.ai/support/solutions/articles/151000178148',
+  },
+  controlNetWeight: {
+    href: 'https://support.invoke.ai/support/solutions/articles/151000178148',
+  },
   lora: {
     href: 'https://support.invoke.ai/support/solutions/articles/151000159072',
   },
+  loraWeight: {
+    href: 'https://support.invoke.ai/support/solutions/articles/151000159072-concepts-low-rank-adaptations-loras-',
+  },
+  compositingBlur: {
+    href: 'https://support.invoke.ai/support/solutions/articles/151000158838-compositing-settings',
+  },
+  compositingBlurMethod: {
+    href: 'https://support.invoke.ai/support/solutions/articles/151000158838-compositing-settings',
+  },
   compositingCoherenceMode: {
-    href: 'https://support.invoke.ai/support/solutions/articles/151000158838',
+    href: 'https://support.invoke.ai/support/solutions/articles/151000158838-compositing-settings',
+  },
+  compositingCoherenceSteps: {
+    href: 'https://support.invoke.ai/support/solutions/articles/151000158838-compositing-settings',
+  },
+  compositingStrength: {
+    href: 'https://support.invoke.ai/support/solutions/articles/151000158838-compositing-settings',
   },
   infillMethod: {
-    href: 'https://support.invoke.ai/support/solutions/articles/151000158841',
+    href: 'https://support.invoke.ai/support/solutions/articles/151000158841-infill-and-scaling',
   },
   scaleBeforeProcessing: {
     href: 'https://support.invoke.ai/support/solutions/articles/151000158841',
   },
+  paramCFGScale: {
+    href: 'https://www.youtube.com/watch?v=1OeHEJrsTpI',
+  },
+  paramCFGRescaleMultiplier: {
+    href: 'https://support.invoke.ai/support/solutions/articles/151000178161-advanced-settings',
+  },
+  paramDenoisingStrength: {
+    href: 'https://support.invoke.ai/support/solutions/articles/151000094998-image-to-image',
+  },
+  paramHrf: {
+    href: 'https://support.invoke.ai/support/solutions/articles/151000096700-how-can-i-get-larger-images-what-does-upscaling-do-',
+  },
   paramIterations: {
     href: 'https://support.invoke.ai/support/solutions/articles/151000159073',
   },
@@ -70,7 +124,10 @@ export const POPOVER_DATA: { [key in Feature]?: PopoverData } = {
   },
   paramScheduler: {
     placement: 'right',
-    href: 'https://support.invoke.ai/support/solutions/articles/151000159073',
+    href: 'https://www.youtube.com/watch?v=1OeHEJrsTpI',
+  },
+  paramSeed: {
+    href: 'https://support.invoke.ai/support/solutions/articles/151000096684-what-is-a-seed-how-do-i-use-it-to-recreate-the-same-image-',
   },
   paramModel: {
     placement: 'right',
@@ -81,15 +138,53 @@ export const POPOVER_DATA: { [key in Feature]?: PopoverData } = {
   },
   controlNetControlMode: {
     placement: 'right',
+    href: 'https://support.invoke.ai/support/solutions/articles/151000178148',
+  },
+  controlNetProcessor: {
+    placement: 'right',
+    href: 'https://support.invoke.ai/support/solutions/articles/151000105880-using-controlnet',
   },
   controlNetResizeMode: {
     placement: 'right',
+    href: 'https://support.invoke.ai/support/solutions/articles/151000178148',
   },
   paramVAE: {
     placement: 'right',
+    href: 'https://support.invoke.ai/support/solutions/articles/151000178161-advanced-settings',
   },
   paramVAEPrecision: {
     placement: 'right',
+    href: 'https://support.invoke.ai/support/solutions/articles/151000178161-advanced-settings',
+  },
+  paramUpscaleMethod: {
+    href: 'https://support.invoke.ai/support/solutions/articles/151000096700-how-can-i-get-larger-images-what-does-upscaling-do-',
+  },
+  refinerModel: {
+    href: 'https://support.invoke.ai/support/solutions/articles/151000178333-using-the-refiner',
+  },
+  refinerNegativeAestheticScore: {
+    href: 'https://support.invoke.ai/support/solutions/articles/151000178333-using-the-refiner',
+  },
+  refinerPositiveAestheticScore: {
+    href: 'https://support.invoke.ai/support/solutions/articles/151000178333-using-the-refiner',
+  },
+  refinerScheduler: {
+    href: 'https://support.invoke.ai/support/solutions/articles/151000178333-using-the-refiner',
+  },
+  refinerStart: {
+    href: 'https://support.invoke.ai/support/solutions/articles/151000178333-using-the-refiner',
+  },
+  refinerSteps: {
+    href: 'https://support.invoke.ai/support/solutions/articles/151000178333-using-the-refiner',
+  },
+  refinerCfgScale: {
+    href: 'https://support.invoke.ai/support/solutions/articles/151000178333-using-the-refiner',
+  },
+  seamlessTilingXAxis: {
+    href: 'https://support.invoke.ai/support/solutions/articles/151000178161-advanced-settings',
+  },
+  seamlessTilingYAxis: {
+    href: 'https://support.invoke.ai/support/solutions/articles/151000178161-advanced-settings',
   },
 } as const;
 
diff --git a/invokeai/frontend/web/src/features/controlAdapters/components/parameters/ParamControlAdapterBeginEnd.tsx b/invokeai/frontend/web/src/features/controlAdapters/components/parameters/ParamControlAdapterBeginEnd.tsx
index a62f7e7d8a..245c182b9f 100644
--- a/invokeai/frontend/web/src/features/controlAdapters/components/parameters/ParamControlAdapterBeginEnd.tsx
+++ b/invokeai/frontend/web/src/features/controlAdapters/components/parameters/ParamControlAdapterBeginEnd.tsx
@@ -1,5 +1,6 @@
 import { CompositeRangeSlider, FormControl, FormLabel } from '@invoke-ai/ui-library';
 import { useAppDispatch } from 'app/store/storeHooks';
+import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { useControlAdapterBeginEndStepPct } from 'features/controlAdapters/hooks/useControlAdapterBeginEndStepPct';
 import { useControlAdapterIsEnabled } from 'features/controlAdapters/hooks/useControlAdapterIsEnabled';
 import {
@@ -61,12 +62,10 @@ export const ParamControlAdapterBeginEnd = memo(({ id }: Props) => {
   }
 
   return (
-    <FormControl
-      isDisabled={!isEnabled}
-      // feature="controlNetBeginEnd"
-      orientation="vertical"
-    >
-      <FormLabel>{t('controlnet.beginEndStepPercent')}</FormLabel>
+    <FormControl isDisabled={!isEnabled} orientation="vertical">
+      <InformationalPopover feature="controlNetBeginEnd">
+        <FormLabel>{t('controlnet.beginEndStepPercent')}</FormLabel>
+      </InformationalPopover>
       <CompositeRangeSlider
         aria-label={ariaLabel}
         value={value}
diff --git a/invokeai/frontend/web/src/features/controlAdapters/components/parameters/ParamControlAdapterProcessorSelect.tsx b/invokeai/frontend/web/src/features/controlAdapters/components/parameters/ParamControlAdapterProcessorSelect.tsx
index 326dcc412a..5257a47128 100644
--- a/invokeai/frontend/web/src/features/controlAdapters/components/parameters/ParamControlAdapterProcessorSelect.tsx
+++ b/invokeai/frontend/web/src/features/controlAdapters/components/parameters/ParamControlAdapterProcessorSelect.tsx
@@ -2,6 +2,7 @@ import type { ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
 import { Combobox, FormControl, FormLabel } from '@invoke-ai/ui-library';
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { useControlAdapterIsEnabled } from 'features/controlAdapters/hooks/useControlAdapterIsEnabled';
 import { useControlAdapterProcessorNode } from 'features/controlAdapters/hooks/useControlAdapterProcessorNode';
 import { CONTROLNET_PROCESSORS } from 'features/controlAdapters/store/constants';
@@ -58,7 +59,9 @@ const ParamControlAdapterProcessorSelect = ({ id }: Props) => {
   }
   return (
     <FormControl isDisabled={!isEnabled}>
-      <FormLabel>{t('controlnet.processor')}</FormLabel>
+      <InformationalPopover feature="controlNetProcessor">
+        <FormLabel>{t('controlnet.processor')}</FormLabel>
+      </InformationalPopover>
       <Combobox value={value} options={options} onChange={onChange} />
     </FormControl>
   );
diff --git a/invokeai/frontend/web/src/features/hrf/components/ParamHrfMethod.tsx b/invokeai/frontend/web/src/features/hrf/components/ParamHrfMethod.tsx
index 8a94544233..65f65240fc 100644
--- a/invokeai/frontend/web/src/features/hrf/components/ParamHrfMethod.tsx
+++ b/invokeai/frontend/web/src/features/hrf/components/ParamHrfMethod.tsx
@@ -1,6 +1,7 @@
 import type { ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
 import { Combobox, FormControl, FormLabel } from '@invoke-ai/ui-library';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { setHrfMethod } from 'features/hrf/store/hrfSlice';
 import { isParameterHRFMethod } from 'features/parameters/types/parameterSchemas';
 import { memo, useCallback, useMemo } from 'react';
@@ -30,7 +31,9 @@ const ParamHrfMethodSelect = () => {
 
   return (
     <FormControl>
-      <FormLabel>{t('hrf.upscaleMethod')}</FormLabel>
+      <InformationalPopover feature="paramUpscaleMethod">
+        <FormLabel>{t('hrf.upscaleMethod')}</FormLabel>
+      </InformationalPopover>
       <Combobox value={value} options={options} onChange={onChange} />
     </FormControl>
   );
diff --git a/invokeai/frontend/web/src/features/hrf/components/ParamHrfStrength.tsx b/invokeai/frontend/web/src/features/hrf/components/ParamHrfStrength.tsx
index c663989b08..3cb9f7e528 100644
--- a/invokeai/frontend/web/src/features/hrf/components/ParamHrfStrength.tsx
+++ b/invokeai/frontend/web/src/features/hrf/components/ParamHrfStrength.tsx
@@ -1,5 +1,6 @@
 import { CompositeNumberInput, CompositeSlider, FormControl, FormLabel } from '@invoke-ai/ui-library';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { setHrfStrength } from 'features/hrf/store/hrfSlice';
 import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
@@ -25,7 +26,9 @@ const ParamHrfStrength = () => {
 
   return (
     <FormControl>
-      <FormLabel>{t('parameters.denoisingStrength')}</FormLabel>
+      <InformationalPopover feature="paramDenoisingStrength">
+        <FormLabel>{`${t('parameters.denoisingStrength')}`}</FormLabel>
+      </InformationalPopover>
       <CompositeSlider
         min={sliderMin}
         max={sliderMax}
diff --git a/invokeai/frontend/web/src/features/hrf/components/ParamHrfToggle.tsx b/invokeai/frontend/web/src/features/hrf/components/ParamHrfToggle.tsx
index fdd2c97e9f..243c2dc59d 100644
--- a/invokeai/frontend/web/src/features/hrf/components/ParamHrfToggle.tsx
+++ b/invokeai/frontend/web/src/features/hrf/components/ParamHrfToggle.tsx
@@ -1,5 +1,6 @@
 import { FormControl, FormLabel, Switch } from '@invoke-ai/ui-library';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { setHrfEnabled } from 'features/hrf/store/hrfSlice';
 import type { ChangeEvent } from 'react';
 import { memo, useCallback } from 'react';
@@ -18,7 +19,9 @@ const ParamHrfToggle = () => {
 
   return (
     <FormControl w="full">
-      <FormLabel flexGrow={1}>{t('hrf.enableHrf')}</FormLabel>
+      <InformationalPopover feature="paramHrf">
+        <FormLabel flexGrow={1}>{t('hrf.enableHrf')}</FormLabel>
+      </InformationalPopover>
       <Switch isChecked={hrfEnabled} onChange={handleHrfEnabled} />
     </FormControl>
   );
diff --git a/invokeai/frontend/web/src/features/lora/components/LoRACard.tsx b/invokeai/frontend/web/src/features/lora/components/LoRACard.tsx
index caedde875a..28bd8afe95 100644
--- a/invokeai/frontend/web/src/features/lora/components/LoRACard.tsx
+++ b/invokeai/frontend/web/src/features/lora/components/LoRACard.tsx
@@ -10,6 +10,7 @@ import {
   Text,
 } from '@invoke-ai/ui-library';
 import { useAppDispatch } from 'app/store/storeHooks';
+import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import type { LoRA } from 'features/lora/store/loraSlice';
 import { loraIsEnabledChanged, loraRemoved, loraWeightChanged } from 'features/lora/store/loraSlice';
 import { memo, useCallback } from 'react';
@@ -57,29 +58,31 @@ export const LoRACard = memo((props: LoRACardProps) => {
           </Flex>
         </Flex>
       </CardHeader>
-      <CardBody>
-        <CompositeSlider
-          value={lora.weight}
-          onChange={handleChange}
-          min={-1}
-          max={2}
-          step={0.01}
-          marks={marks}
-          defaultValue={0.75}
-          isDisabled={!lora.isEnabled}
-        />
-        <CompositeNumberInput
-          value={lora.weight}
-          onChange={handleChange}
-          min={-5}
-          max={5}
-          step={0.01}
-          w={20}
-          flexShrink={0}
-          defaultValue={0.75}
-          isDisabled={!lora.isEnabled}
-        />
-      </CardBody>
+      <InformationalPopover feature="loraWeight">
+        <CardBody>
+          <CompositeSlider
+            value={lora.weight}
+            onChange={handleChange}
+            min={-1}
+            max={2}
+            step={0.01}
+            marks={marks}
+            defaultValue={0.75}
+            isDisabled={!lora.isEnabled}
+          />
+          <CompositeNumberInput
+            value={lora.weight}
+            onChange={handleChange}
+            min={-5}
+            max={5}
+            step={0.01}
+            w={20}
+            flexShrink={0}
+            defaultValue={0.75}
+            isDisabled={!lora.isEnabled}
+          />
+        </CardBody>
+      </InformationalPopover>
     </Card>
   );
 });
diff --git a/invokeai/frontend/web/src/features/lora/components/LoRASelect.tsx b/invokeai/frontend/web/src/features/lora/components/LoRASelect.tsx
index 30ef99d2f7..ed70a4d44a 100644
--- a/invokeai/frontend/web/src/features/lora/components/LoRASelect.tsx
+++ b/invokeai/frontend/web/src/features/lora/components/LoRASelect.tsx
@@ -2,6 +2,7 @@ import type { ChakraProps } from '@invoke-ai/ui-library';
 import { Combobox, FormControl, FormLabel } from '@invoke-ai/ui-library';
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { useGroupedModelCombobox } from 'common/hooks/useGroupedModelCombobox';
 import { loraAdded, selectLoraSlice } from 'features/lora/store/loraSlice';
 import { memo, useCallback, useMemo } from 'react';
@@ -57,7 +58,9 @@ const LoRASelect = () => {
 
   return (
     <FormControl isDisabled={!options.length}>
-      <FormLabel>{t('models.lora')} </FormLabel>
+      <InformationalPopover feature="lora">
+        <FormLabel>{t('models.lora')} </FormLabel>
+      </InformationalPopover>
       <Combobox
         placeholder={placeholder}
         value={null}
diff --git a/invokeai/frontend/web/src/features/parameters/components/Canvas/InfillAndScaling/ParamInfillPatchmatchDownscaleSize.tsx b/invokeai/frontend/web/src/features/parameters/components/Canvas/InfillAndScaling/ParamInfillPatchmatchDownscaleSize.tsx
index 98fa05b3ac..fbeed1a1be 100644
--- a/invokeai/frontend/web/src/features/parameters/components/Canvas/InfillAndScaling/ParamInfillPatchmatchDownscaleSize.tsx
+++ b/invokeai/frontend/web/src/features/parameters/components/Canvas/InfillAndScaling/ParamInfillPatchmatchDownscaleSize.tsx
@@ -1,5 +1,6 @@
 import { CompositeNumberInput, CompositeSlider, FormControl, FormLabel } from '@invoke-ai/ui-library';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { setInfillPatchmatchDownscaleSize } from 'features/parameters/store/generationSlice';
 import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
@@ -27,7 +28,9 @@ const ParamInfillPatchmatchDownscaleSize = () => {
 
   return (
     <FormControl isDisabled={infillMethod !== 'patchmatch'}>
-      <FormLabel>{t('parameters.patchmatchDownScaleSize')}</FormLabel>
+      <InformationalPopover feature="patchmatchDownScaleSize">
+        <FormLabel>{t('parameters.patchmatchDownScaleSize')}</FormLabel>
+      </InformationalPopover>
       <CompositeSlider
         min={sliderMin}
         max={sliderMax}
diff --git a/invokeai/frontend/web/src/features/parameters/components/Core/ParamHeight.tsx b/invokeai/frontend/web/src/features/parameters/components/Core/ParamHeight.tsx
index dc74697a1a..09f051719f 100644
--- a/invokeai/frontend/web/src/features/parameters/components/Core/ParamHeight.tsx
+++ b/invokeai/frontend/web/src/features/parameters/components/Core/ParamHeight.tsx
@@ -1,5 +1,6 @@
 import { CompositeNumberInput, CompositeSlider, FormControl, FormLabel } from '@invoke-ai/ui-library';
 import { useAppSelector } from 'app/store/storeHooks';
+import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { useImageSizeContext } from 'features/parameters/components/ImageSize/ImageSizeContext';
 import { selectOptimalDimension } from 'features/parameters/store/generationSlice';
 import { memo, useCallback, useMemo } from 'react';
@@ -27,7 +28,9 @@ export const ParamHeight = memo(() => {
 
   return (
     <FormControl>
-      <FormLabel>{t('parameters.height')}</FormLabel>
+      <InformationalPopover feature="paramHeight">
+        <FormLabel>{t('parameters.height')}</FormLabel>
+      </InformationalPopover>
       <CompositeSlider
         value={ctx.height}
         defaultValue={optimalDimension}
diff --git a/invokeai/frontend/web/src/features/parameters/components/Core/ParamWidth.tsx b/invokeai/frontend/web/src/features/parameters/components/Core/ParamWidth.tsx
index 6f9e996d4c..2de6da2220 100644
--- a/invokeai/frontend/web/src/features/parameters/components/Core/ParamWidth.tsx
+++ b/invokeai/frontend/web/src/features/parameters/components/Core/ParamWidth.tsx
@@ -1,5 +1,6 @@
 import { CompositeNumberInput, CompositeSlider, FormControl, FormLabel } from '@invoke-ai/ui-library';
 import { useAppSelector } from 'app/store/storeHooks';
+import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { useImageSizeContext } from 'features/parameters/components/ImageSize/ImageSizeContext';
 import { selectOptimalDimension } from 'features/parameters/store/generationSlice';
 import { memo, useCallback, useMemo } from 'react';
@@ -27,7 +28,9 @@ export const ParamWidth = memo(() => {
 
   return (
     <FormControl>
-      <FormLabel>{t('parameters.width')}</FormLabel>
+      <InformationalPopover feature="paramWidth">
+        <FormLabel>{t('parameters.width')}</FormLabel>
+      </InformationalPopover>
       <CompositeSlider
         value={ctx.width}
         onChange={onChange}
diff --git a/invokeai/frontend/web/src/features/parameters/components/ImageSize/AspectRatioSelect.tsx b/invokeai/frontend/web/src/features/parameters/components/ImageSize/AspectRatioSelect.tsx
index 1ab2fc6945..211cdba500 100644
--- a/invokeai/frontend/web/src/features/parameters/components/ImageSize/AspectRatioSelect.tsx
+++ b/invokeai/frontend/web/src/features/parameters/components/ImageSize/AspectRatioSelect.tsx
@@ -1,6 +1,7 @@
 import type { ComboboxOption, SystemStyleObject } from '@invoke-ai/ui-library';
 import { Combobox, FormControl, FormLabel } from '@invoke-ai/ui-library';
 import type { SingleValue } from 'chakra-react-select';
+import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { ASPECT_RATIO_OPTIONS } from 'features/parameters/components/ImageSize/constants';
 import { useImageSizeContext } from 'features/parameters/components/ImageSize/ImageSizeContext';
 import { isAspectRatioID } from 'features/parameters/components/ImageSize/types';
@@ -28,7 +29,9 @@ export const AspectRatioSelect = memo(() => {
 
   return (
     <FormControl>
-      <FormLabel>{t('parameters.aspect')}</FormLabel>
+      <InformationalPopover feature="paramAspect">
+        <FormLabel>{t('parameters.aspect')}</FormLabel>
+      </InformationalPopover>
       <Combobox value={value} onChange={onChange} options={ASPECT_RATIO_OPTIONS} sx={selectStyles} />
     </FormControl>
   );
diff --git a/invokeai/frontend/web/src/features/parameters/components/ImageToImage/ImageToImageFit.tsx b/invokeai/frontend/web/src/features/parameters/components/ImageToImage/ImageToImageFit.tsx
index 9c41b2d56c..a772daa177 100644
--- a/invokeai/frontend/web/src/features/parameters/components/ImageToImage/ImageToImageFit.tsx
+++ b/invokeai/frontend/web/src/features/parameters/components/ImageToImage/ImageToImageFit.tsx
@@ -1,6 +1,7 @@
 import { FormControl, FormLabel, Switch } from '@invoke-ai/ui-library';
 import type { RootState } from 'app/store/store';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { setShouldFitToWidthHeight } from 'features/parameters/store/generationSlice';
 import type { ChangeEvent } from 'react';
 import { memo, useCallback } from 'react';
@@ -22,7 +23,9 @@ const ImageToImageFit = () => {
 
   return (
     <FormControl w="full">
-      <FormLabel flexGrow={1}>{t('parameters.imageFit')}</FormLabel>
+      <InformationalPopover feature="imageFit">
+        <FormLabel flexGrow={1}>{t('parameters.imageFit')}</FormLabel>
+      </InformationalPopover>
       <Switch isChecked={shouldFitToWidthHeight} onChange={handleChangeFit} />
     </FormControl>
   );
diff --git a/invokeai/frontend/web/src/features/parameters/components/MainModel/ParamMainModelSelect.tsx b/invokeai/frontend/web/src/features/parameters/components/MainModel/ParamMainModelSelect.tsx
index 13e03962b4..c6c77b5fe9 100644
--- a/invokeai/frontend/web/src/features/parameters/components/MainModel/ParamMainModelSelect.tsx
+++ b/invokeai/frontend/web/src/features/parameters/components/MainModel/ParamMainModelSelect.tsx
@@ -1,6 +1,7 @@
-import { Combobox, FormControl, FormLabel, Tooltip } from '@invoke-ai/ui-library';
+import { Box, Combobox, FormControl, FormLabel, Tooltip } from '@invoke-ai/ui-library';
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { useGroupedModelCombobox } from 'common/hooks/useGroupedModelCombobox';
 import { modelSelected } from 'features/parameters/store/actions';
 import { selectGenerationSlice } from 'features/parameters/store/generationSlice';
@@ -41,18 +42,22 @@ const ParamMainModelSelect = () => {
   });
 
   return (
-    <Tooltip label={tooltipLabel}>
-      <FormControl isDisabled={!options.length} isInvalid={!options.length}>
+    <FormControl isDisabled={!options.length} isInvalid={!options.length}>
+      <InformationalPopover feature="paramModel">
         <FormLabel>{t('modelManager.model')}</FormLabel>
-        <Combobox
-          value={value}
-          placeholder={placeholder}
-          options={options}
-          onChange={onChange}
-          noOptionsMessage={noOptionsMessage}
-        />
-      </FormControl>
-    </Tooltip>
+      </InformationalPopover>
+      <Tooltip label={tooltipLabel}>
+        <Box w="full">
+          <Combobox
+            value={value}
+            placeholder={placeholder}
+            options={options}
+            onChange={onChange}
+            noOptionsMessage={noOptionsMessage}
+          />
+        </Box>
+      </Tooltip>
+    </FormControl>
   );
 };
 
diff --git a/invokeai/frontend/web/src/features/parameters/components/Seamless/ParamSeamlessXAxis.tsx b/invokeai/frontend/web/src/features/parameters/components/Seamless/ParamSeamlessXAxis.tsx
index b66293580a..739cf7d83f 100644
--- a/invokeai/frontend/web/src/features/parameters/components/Seamless/ParamSeamlessXAxis.tsx
+++ b/invokeai/frontend/web/src/features/parameters/components/Seamless/ParamSeamlessXAxis.tsx
@@ -1,5 +1,6 @@
 import { FormControl, FormLabel, Switch } from '@invoke-ai/ui-library';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { setSeamlessXAxis } from 'features/parameters/store/generationSlice';
 import type { ChangeEvent } from 'react';
 import { memo, useCallback } from 'react';
@@ -20,7 +21,9 @@ const ParamSeamlessXAxis = () => {
 
   return (
     <FormControl>
-      <FormLabel>{t('parameters.seamlessXAxis')}</FormLabel>
+      <InformationalPopover feature="seamlessTilingXAxis">
+        <FormLabel>{t('parameters.seamlessXAxis')}</FormLabel>
+      </InformationalPopover>
       <Switch isChecked={seamlessXAxis} onChange={handleChange} />
     </FormControl>
   );
diff --git a/invokeai/frontend/web/src/features/parameters/components/Seamless/ParamSeamlessYAxis.tsx b/invokeai/frontend/web/src/features/parameters/components/Seamless/ParamSeamlessYAxis.tsx
index e983565476..455e50b90f 100644
--- a/invokeai/frontend/web/src/features/parameters/components/Seamless/ParamSeamlessYAxis.tsx
+++ b/invokeai/frontend/web/src/features/parameters/components/Seamless/ParamSeamlessYAxis.tsx
@@ -1,5 +1,6 @@
 import { FormControl, FormLabel, Switch } from '@invoke-ai/ui-library';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { setSeamlessYAxis } from 'features/parameters/store/generationSlice';
 import type { ChangeEvent } from 'react';
 import { memo, useCallback } from 'react';
@@ -18,7 +19,9 @@ const ParamSeamlessYAxis = () => {
 
   return (
     <FormControl>
-      <FormLabel>{t('parameters.seamlessYAxis')}</FormLabel>
+      <InformationalPopover feature="seamlessTilingYAxis">
+        <FormLabel>{t('parameters.seamlessYAxis')}</FormLabel>
+      </InformationalPopover>
       <Switch isChecked={seamlessYAxis} onChange={handleChange} />
     </FormControl>
   );
diff --git a/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerCFGScale.tsx b/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerCFGScale.tsx
index 9f3bf33848..a4409955cc 100644
--- a/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerCFGScale.tsx
+++ b/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerCFGScale.tsx
@@ -1,5 +1,6 @@
 import { CompositeNumberInput, CompositeSlider, FormControl, FormLabel } from '@invoke-ai/ui-library';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { setRefinerCFGScale } from 'features/sdxl/store/sdxlSlice';
 import { memo, useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
@@ -21,7 +22,9 @@ const ParamSDXLRefinerCFGScale = () => {
 
   return (
     <FormControl>
-      <FormLabel>{t('sdxl.cfgScale')}</FormLabel>
+      <InformationalPopover feature="refinerCfgScale">
+        <FormLabel>{t('sdxl.cfgScale')}</FormLabel>
+      </InformationalPopover>
       <CompositeSlider
         value={refinerCFGScale}
         defaultValue={initial}
diff --git a/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerModelSelect.tsx b/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerModelSelect.tsx
index c19dc10fb5..5559ec76b7 100644
--- a/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerModelSelect.tsx
+++ b/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerModelSelect.tsx
@@ -1,6 +1,7 @@
 import { Combobox, FormControl, FormLabel } from '@invoke-ai/ui-library';
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { useModelCombobox } from 'common/hooks/useModelCombobox';
 import { refinerModelChanged, selectSdxlSlice } from 'features/sdxl/store/sdxlSlice';
 import { memo, useCallback } from 'react';
@@ -43,7 +44,9 @@ const ParamSDXLRefinerModelSelect = () => {
   });
   return (
     <FormControl isDisabled={!options.length} isInvalid={!options.length}>
-      <FormLabel>{t('sdxl.refinermodel')}</FormLabel>
+      <InformationalPopover feature="refinerModel">
+        <FormLabel>{t('sdxl.refinermodel')}</FormLabel>
+      </InformationalPopover>
       <Combobox
         value={value}
         placeholder={placeholder}
diff --git a/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerNegativeAestheticScore.tsx b/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerNegativeAestheticScore.tsx
index 933043f843..8da7253863 100644
--- a/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerNegativeAestheticScore.tsx
+++ b/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerNegativeAestheticScore.tsx
@@ -1,5 +1,6 @@
 import { CompositeNumberInput, CompositeSlider, FormControl, FormLabel } from '@invoke-ai/ui-library';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { setRefinerNegativeAestheticScore } from 'features/sdxl/store/sdxlSlice';
 import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
@@ -14,7 +15,9 @@ const ParamSDXLRefinerNegativeAestheticScore = () => {
 
   return (
     <FormControl>
-      <FormLabel>{t('sdxl.negAestheticScore')}</FormLabel>
+      <InformationalPopover feature="refinerNegativeAestheticScore">
+        <FormLabel>{t('sdxl.negAestheticScore')}</FormLabel>
+      </InformationalPopover>
       <CompositeSlider
         min={1}
         max={10}
diff --git a/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerPositiveAestheticScore.tsx b/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerPositiveAestheticScore.tsx
index a170b1afb4..f872929c0e 100644
--- a/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerPositiveAestheticScore.tsx
+++ b/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerPositiveAestheticScore.tsx
@@ -1,5 +1,6 @@
 import { CompositeNumberInput, CompositeSlider, FormControl, FormLabel } from '@invoke-ai/ui-library';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { setRefinerPositiveAestheticScore } from 'features/sdxl/store/sdxlSlice';
 import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
@@ -13,7 +14,9 @@ const ParamSDXLRefinerPositiveAestheticScore = () => {
 
   return (
     <FormControl>
-      <FormLabel>{t('sdxl.posAestheticScore')}</FormLabel>
+      <InformationalPopover feature="refinerPositiveAestheticScore">
+        <FormLabel>{t('sdxl.posAestheticScore')}</FormLabel>
+      </InformationalPopover>
       <CompositeSlider
         step={0.5}
         min={1}
diff --git a/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerScheduler.tsx b/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerScheduler.tsx
index 196c4d3dfb..d0aab11038 100644
--- a/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerScheduler.tsx
+++ b/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerScheduler.tsx
@@ -1,6 +1,7 @@
 import type { ComboboxOnChange } from '@invoke-ai/ui-library';
 import { Combobox, FormControl, FormLabel } from '@invoke-ai/ui-library';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { SCHEDULER_OPTIONS } from 'features/parameters/types/constants';
 import { isParameterScheduler } from 'features/parameters/types/parameterSchemas';
 import { setRefinerScheduler } from 'features/sdxl/store/sdxlSlice';
@@ -26,7 +27,9 @@ const ParamSDXLRefinerScheduler = () => {
 
   return (
     <FormControl>
-      <FormLabel>{t('sdxl.scheduler')}</FormLabel>
+      <InformationalPopover feature="refinerScheduler">
+        <FormLabel>{t('sdxl.scheduler')}</FormLabel>
+      </InformationalPopover>
       <Combobox value={value} options={SCHEDULER_OPTIONS} onChange={onChange} />
     </FormControl>
   );
diff --git a/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerStart.tsx b/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerStart.tsx
index c2eea5d925..fd7b1f89cf 100644
--- a/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerStart.tsx
+++ b/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerStart.tsx
@@ -1,5 +1,6 @@
 import { CompositeNumberInput, CompositeSlider, FormControl, FormLabel } from '@invoke-ai/ui-library';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { setRefinerStart } from 'features/sdxl/store/sdxlSlice';
 import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
@@ -12,7 +13,9 @@ const ParamSDXLRefinerStart = () => {
 
   return (
     <FormControl>
-      <FormLabel>{t('sdxl.refinerStart')}</FormLabel>
+      <InformationalPopover feature="refinerStart">
+        <FormLabel>{t('sdxl.refinerStart')}</FormLabel>
+      </InformationalPopover>
       <CompositeSlider
         step={0.01}
         min={0}
diff --git a/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerSteps.tsx b/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerSteps.tsx
index 5c4a885ecd..a18edc8cf4 100644
--- a/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerSteps.tsx
+++ b/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerSteps.tsx
@@ -1,5 +1,6 @@
 import { CompositeNumberInput, CompositeSlider, FormControl, FormLabel } from '@invoke-ai/ui-library';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { setRefinerSteps } from 'features/sdxl/store/sdxlSlice';
 import { memo, useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
@@ -27,7 +28,9 @@ const ParamSDXLRefinerSteps = () => {
 
   return (
     <FormControl>
-      <FormLabel>{t('sdxl.steps')}</FormLabel>
+      <InformationalPopover feature="refinerSteps">
+        <FormLabel>{t('sdxl.steps')}</FormLabel>
+      </InformationalPopover>
       <CompositeSlider
         value={refinerSteps}
         defaultValue={initial}

From 115d92b1ae4df7dc100c5e34f49172dd77ebc388 Mon Sep 17 00:00:00 2001
From: Jennifer Player <chainchompa@gmail.com>
Date: Mon, 19 Feb 2024 12:50:35 -0500
Subject: [PATCH 028/411] updated copy

---
 invokeai/frontend/web/public/locales/en.json | 179 +++++++++++++++----
 1 file changed, 143 insertions(+), 36 deletions(-)

diff --git a/invokeai/frontend/web/public/locales/en.json b/invokeai/frontend/web/public/locales/en.json
index d4f00a5970..32c707f908 100644
--- a/invokeai/frontend/web/public/locales/en.json
+++ b/invokeai/frontend/web/public/locales/en.json
@@ -1424,9 +1424,8 @@
         "clipSkip": {
             "heading": "CLIP Skip",
             "paragraphs": [
-                "Choose how many layers of the CLIP model to skip.",
-                "Some models work better with certain CLIP Skip settings.",
-                "A higher value typically results in a less detailed image."
+                "How many layers of the CLIP model to skip.",
+                "Certain models are better suited to be used with CLIP Skip."
             ]
         },
         "paramNegativeConditioning": {
@@ -1446,7 +1445,8 @@
         "paramScheduler": {
             "heading": "Scheduler",
             "paragraphs": [
-                "Scheduler defines how to iteratively add noise to an image or how to update a sample based on a model's output."
+                "Scheduler used during the generation process.",
+                "Each scheduler defines how to iteratively add noise to an image or how to update a sample based on a model's output."
             ]
         },
         "compositingBlur": {
@@ -1463,47 +1463,52 @@
         },
         "compositingCoherenceMode": {
             "heading": "Mode",
-            "paragraphs": ["The mode of the Coherence Pass."]
+            "paragraphs": ["Method used to create a coherent image with the newly generated masked area."]
         },
         "compositingCoherenceSteps": {
             "heading": "Steps",
-            "paragraphs": ["Number of denoising steps used in the Coherence Pass.", "Same as the main Steps parameter."]
+            "paragraphs": ["Number of steps in the Coherence Pass.", "Similar to Generation Steps."]
         },
         "compositingStrength": {
             "heading": "Strength",
-            "paragraphs": [
-                "Denoising strength for the Coherence Pass.",
-                "Same as the Image to Image Denoising Strength parameter."
-            ]
+            "paragraphs": ["Amount of noise added for the Coherence Pass.", "Similar to Denoising Strength."]
         },
         "compositingMaskAdjustments": {
             "heading": "Mask Adjustments",
             "paragraphs": ["Adjust the mask."]
         },
-        "controlNetBeginEnd": {
-            "heading": "Begin / End Step Percentage",
-            "paragraphs": [
-                "Which steps of the denoising process will have the ControlNet applied.",
-                "ControlNets applied at the beginning of the process guide composition, and ControlNets applied at the end guide details."
-            ]
-        },
-        "controlNetControlMode": {
-            "heading": "Control Mode",
-            "paragraphs": ["Lends more weight to either the prompt or ControlNet."]
-        },
-        "controlNetResizeMode": {
-            "heading": "Resize Mode",
-            "paragraphs": ["How the ControlNet image will be fit to the image output size."]
-        },
         "controlNet": {
             "heading": "ControlNet",
             "paragraphs": [
                 "ControlNets provide guidance to the generation process, helping create images with controlled composition, structure, or style, depending on the model selected."
             ]
         },
+        "controlNetBeginEnd": {
+            "heading": "Begin / End Step Percentage",
+            "paragraphs": [
+                "The part of the of the denoising process that will have the Control Adapter applied.",
+                "Generally, Control Adapters applied at the start of the process guide composition, and Control Adapters applied at the end guide details."
+            ]
+        },
+        "controlNetControlMode": {
+            "heading": "Control Mode",
+            "paragraphs": ["Lend more weight to either the prompt or ControlNet."]
+        },
+        "controlNetProcessor": {
+            "heading": "Processor",
+            "paragraphs": [
+                "Method of processing the input image to guide the generation process. Different processors will providedifferent effects or styles in your generated images."
+            ]
+        },
+        "controlNetResizeMode": {
+            "heading": "Resize Mode",
+            "paragraphs": ["Method to fit Control Adapter's input image size to the output generation size."]
+        },
         "controlNetWeight": {
             "heading": "Weight",
-            "paragraphs": ["How strongly the ControlNet will impact the generated image."]
+            "paragraphs": [
+                "Weight of the Control Adapter. Higher weight will lead to larger impacts on the final image."
+            ]
         },
         "dynamicPrompts": {
             "heading": "Dynamic Prompts",
@@ -1526,13 +1531,23 @@
                 "Per Image will use a unique seed for each image. This provides more variation."
             ]
         },
+        "imageFit": {
+            "heading": "Fit Initial Image to Output Size",
+            "paragraphs": [
+                "Resizes the initial image to the width and height of the output image. Recommended to enable."
+            ]
+        },
         "infillMethod": {
             "heading": "Infill Method",
-            "paragraphs": ["Method to infill the selected area."]
+            "paragraphs": ["Method of infilling during the Outpainting or Inpainting process."]
         },
         "lora": {
-            "heading": "LoRA Weight",
-            "paragraphs": ["Higher LoRA weight will lead to larger impacts on the final image."]
+            "heading": "LoRA",
+            "paragraphs": ["Lightweight models that are used in conjunction with base models."]
+        },
+        "loraWeight": {
+            "heading": "Weight",
+            "paragraphs": ["Weight of the LoRA. Higher weight will lead to larger impacts on the final image."]
         },
         "noiseUseCPU": {
             "heading": "Use CPU Noise",
@@ -1542,14 +1557,25 @@
                 "There is no performance impact to enabling CPU Noise."
             ]
         },
+        "paramAspect": {
+            "heading": "Aspect",
+            "paragraphs": [
+                "Aspect ratio of the generated image. Changing the ratio will update the Width and Height accordingly.",
+                "“Optimize” will set the Width and Height to optimal dimensions for the chosen model."
+            ]
+        },
         "paramCFGScale": {
             "heading": "CFG Scale",
-            "paragraphs": ["Controls how much your prompt influences the generation process."]
+            "paragraphs": [
+                "Controls how much the prompt influences the generation process.",
+                "High CFG Scale values can result in over-saturation and distorted generation results. "
+            ]
         },
         "paramCFGRescaleMultiplier": {
             "heading": "CFG Rescale Multiplier",
             "paragraphs": [
-                "Rescale multiplier for CFG guidance, used for models trained using zero-terminal SNR (ztsnr). Suggested value 0.7."
+                "Rescale multiplier for CFG guidance, used for models trained using zero-terminal SNR (ztsnr).",
+                "Suggested value of 0.7 for these models."
             ]
         },
         "paramDenoisingStrength": {
@@ -1559,6 +1585,16 @@
                 "0 will result in an identical image, while 1 will result in a completely new image."
             ]
         },
+        "paramHeight": {
+            "heading": "Height",
+            "paragraphs": ["Height of the generated image. Must be a multiple of 8."]
+        },
+        "paramHrf": {
+            "heading": "Enable High Resolution Fix",
+            "paragraphs": [
+                "Generate high quality images at a larger resolution than optimal for the model. Generally used to prevent duplication in the generated image."
+            ]
+        },
         "paramIterations": {
             "heading": "Iterations",
             "paragraphs": [
@@ -1569,8 +1605,7 @@
         "paramModel": {
             "heading": "Model",
             "paragraphs": [
-                "Model used for the denoising steps.",
-                "Different models are typically trained to specialize in producing particular aesthetic results and content."
+                "Model used for generation. Different models are trained to specialize in producing different aesthetic results and content."
             ]
         },
         "paramRatio": {
@@ -1584,7 +1619,7 @@
             "heading": "Seed",
             "paragraphs": [
                 "Controls the starting noise used for generation.",
-                "Disable “Random Seed” to produce identical results with the same generation settings."
+                "Disable the “Random” option to produce identical results with the same generation settings."
             ]
         },
         "paramSteps": {
@@ -1594,6 +1629,10 @@
                 "Higher step counts will typically create better images but will require more generation time."
             ]
         },
+        "paramUpscaleMethod": {
+            "heading": "Upscale Method",
+            "paragraphs": ["Method used to upscale the image for High Resolution Fix."]
+        },
         "paramVAE": {
             "heading": "VAE",
             "paragraphs": ["Model used for translating AI output into the final image."]
@@ -1601,14 +1640,82 @@
         "paramVAEPrecision": {
             "heading": "VAE Precision",
             "paragraphs": [
-                "The precision used during VAE encoding and decoding. FP16/half precision is more efficient, at the expense of minor image variations."
+                "The precision used during VAE encoding and decoding.",
+                "Fp16/Half precision is more efficient, at the expense of minor image variations."
+            ]
+        },
+        "paramWidth": {
+            "heading": "Width",
+            "paragraphs": ["Width of the generated image. Must be a multiple of 8."]
+        },
+        "patchmatchDownScaleSize": {
+            "heading": "Downscale",
+            "paragraphs": [
+                "How much downscaling occurs before infilling.",
+                "Higher downscaling will improve performance and reduce quality."
+            ]
+        },
+        "refinerModel": {
+            "heading": "Refiner Model",
+            "paragraphs": [
+                "Model used during the refiner portion of the generation process.",
+                "Similar to the Generation Model."
+            ]
+        },
+        "refinerPositiveAestheticScore": {
+            "heading": "Positive Aesthetic Score",
+            "paragraphs": [
+                "Weight generations to be more similar to images with a high aesthetic score, based on the training data."
+            ]
+        },
+        "refinerNegativeAestheticScore": {
+            "heading": "Negative Aesthetic Score",
+            "paragraphs": [
+                "Weight generations to be more similar to images with a low aesthetic score, based on the training data."
+            ]
+        },
+        "refinerScheduler": {
+            "heading": "Scheduler",
+            "paragraphs": [
+                "Scheduler used during the refiner portion of the generation process.",
+                "Similar to the Generation Scheduler."
+            ]
+        },
+        "refinerStart": {
+            "heading": "Refiner Start",
+            "paragraphs": [
+                "Where in the generation process the refiner will start to be used.",
+                "0 means the refiner will be used for the entire generation process, 0.8 means the refiner will be used for the last 20% of the generation process."
+            ]
+        },
+        "refinerSteps": {
+            "heading": "Steps",
+            "paragraphs": [
+                "Number of steps that will be performed during the refiner portion of the generation process.",
+                "Similar to the Generation Steps."
+            ]
+        },
+        "refinerCfgScale": {
+            "heading": "CFG Scale",
+            "paragraphs": [
+                "Controls how much the prompt influences the generation process.",
+                "Similar to the Generation CFG Scale."
             ]
         },
         "scaleBeforeProcessing": {
             "heading": "Scale Before Processing",
             "paragraphs": [
-                "Scales the selected area to the size best suited for the model before the image generation process."
+                "“Auto” scales the selected area to the size best suited for the model before the image generation process.",
+                "“Manual” allows you to choose the width and height the selected area will be scaled to before the image generation process."
             ]
+        },
+        "seamlessTilingXAxis": {
+            "heading": "Seamless Tiling X Axis",
+            "paragraphs": ["Seamlessly tile an image along the horizontal axis."]
+        },
+        "seamlessTilingYAxis": {
+            "heading": "Seamless Tiling Y Axis",
+            "paragraphs": ["Seamlessly tile an image along the vertical axis."]
         }
     },
     "ui": {

From e01769294f57930ae57ca1d51781a701f9fadf06 Mon Sep 17 00:00:00 2001
From: Hosted Weblate <hosted@weblate.org>
Date: Mon, 19 Feb 2024 19:12:51 +0100
Subject: [PATCH 029/411] translationBot(ui): update translation files

Updated by "Cleanup translation files" hook in Weblate.

Co-authored-by: Hosted Weblate <hosted@weblate.org>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/
Translation: InvokeAI/Web UI
---
 invokeai/frontend/web/public/locales/de.json    | 3 +--
 invokeai/frontend/web/public/locales/it.json    | 6 ++----
 invokeai/frontend/web/public/locales/nl.json    | 6 ++----
 invokeai/frontend/web/public/locales/ru.json    | 6 ++----
 invokeai/frontend/web/public/locales/zh_CN.json | 6 ++----
 5 files changed, 9 insertions(+), 18 deletions(-)

diff --git a/invokeai/frontend/web/public/locales/de.json b/invokeai/frontend/web/public/locales/de.json
index 44ae981b02..ae3da48518 100644
--- a/invokeai/frontend/web/public/locales/de.json
+++ b/invokeai/frontend/web/public/locales/de.json
@@ -985,8 +985,7 @@
         "paramModel": {
             "heading": "Modell",
             "paragraphs": [
-                "Modell für die Entrauschungsschritte.",
-                "Verschiedene Modelle werden in der Regel so trainiert, dass sie sich auf die Erzeugung bestimmter Ästhetik und/oder Inhalte spezialisiert."
+                "Modell für die Entrauschungsschritte."
             ]
         },
         "paramIterations": {
diff --git a/invokeai/frontend/web/public/locales/it.json b/invokeai/frontend/web/public/locales/it.json
index 8a427482dc..3d8fc79390 100644
--- a/invokeai/frontend/web/public/locales/it.json
+++ b/invokeai/frontend/web/public/locales/it.json
@@ -1411,8 +1411,7 @@
         "clipSkip": {
             "paragraphs": [
                 "Scegli quanti livelli del modello CLIP saltare.",
-                "Alcuni modelli funzionano meglio con determinate impostazioni di CLIP Skip.",
-                "Un valore più alto in genere produce un'immagine meno dettagliata."
+                "Alcuni modelli funzionano meglio con determinate impostazioni di CLIP Skip."
             ]
         },
         "compositingCoherencePass": {
@@ -1528,8 +1527,7 @@
         "paramModel": {
             "heading": "Modello",
             "paragraphs": [
-                "Modello utilizzato per i passaggi di riduzione del rumore.",
-                "Diversi modelli sono generalmente addestrati per specializzarsi nella produzione di particolari risultati e contenuti estetici."
+                "Modello utilizzato per i passaggi di riduzione del rumore."
             ]
         },
         "paramDenoisingStrength": {
diff --git a/invokeai/frontend/web/public/locales/nl.json b/invokeai/frontend/web/public/locales/nl.json
index aaf836604f..c23030bf54 100644
--- a/invokeai/frontend/web/public/locales/nl.json
+++ b/invokeai/frontend/web/public/locales/nl.json
@@ -1217,16 +1217,14 @@
         "clipSkip": {
             "paragraphs": [
                 "Kies hoeveel CLIP-modellagen je wilt overslaan.",
-                "Bepaalde modellen werken beter met bepaalde Overslaan CLIP-instellingen.",
-                "Een hogere waarde geeft meestal een minder gedetailleerde afbeelding."
+                "Bepaalde modellen werken beter met bepaalde Overslaan CLIP-instellingen."
             ],
             "heading": "Overslaan CLIP"
         },
         "paramModel": {
             "heading": "Model",
             "paragraphs": [
-                "Model gebruikt voor de ontruisingsstappen.",
-                "Verschillende modellen zijn meestal getraind om zich te specialiseren in het maken van bepaalde esthetische resultaten en materiaal."
+                "Model gebruikt voor de ontruisingsstappen."
             ]
         },
         "compositingCoherencePass": {
diff --git a/invokeai/frontend/web/public/locales/ru.json b/invokeai/frontend/web/public/locales/ru.json
index 18bfad7f02..af640e538a 100644
--- a/invokeai/frontend/web/public/locales/ru.json
+++ b/invokeai/frontend/web/public/locales/ru.json
@@ -1353,16 +1353,14 @@
         "clipSkip": {
             "paragraphs": [
                 "Выберите, сколько слоев модели CLIP нужно пропустить.",
-                "Некоторые модели работают лучше с определенными настройками пропуска CLIP.",
-                "Более высокое значение обычно приводит к менее детализированному изображению."
+                "Некоторые модели работают лучше с определенными настройками пропуска CLIP."
             ],
             "heading": "CLIP пропуск"
         },
         "paramModel": {
             "heading": "Модель",
             "paragraphs": [
-                "Модель, используемая для шагов шумоподавления.",
-                "Различные модели обычно обучаются, чтобы специализироваться на достижении определенных эстетических результатов и содержания."
+                "Модель, используемая для шагов шумоподавления."
             ]
         },
         "compositingCoherencePass": {
diff --git a/invokeai/frontend/web/public/locales/zh_CN.json b/invokeai/frontend/web/public/locales/zh_CN.json
index 65ebc7f01a..3e4319fef8 100644
--- a/invokeai/frontend/web/public/locales/zh_CN.json
+++ b/invokeai/frontend/web/public/locales/zh_CN.json
@@ -1444,16 +1444,14 @@
         "clipSkip": {
             "paragraphs": [
                 "选择要跳过 CLIP 模型多少层。",
-                "部分模型跳过特定数值的层时效果会更好。",
-                "较高的数值通常会导致图像细节更少。"
+                "部分模型跳过特定数值的层时效果会更好。"
             ],
             "heading": "CLIP 跳过层"
         },
         "paramModel": {
             "heading": "模型",
             "paragraphs": [
-                "用于去噪过程的模型。",
-                "不同的模型一般会通过接受训练来专门产生特定的美学内容和结果。"
+                "用于去噪过程的模型。"
             ]
         },
         "paramIterations": {

From 01a6378dc113927877157f867ec5151b734dc2b4 Mon Sep 17 00:00:00 2001
From: B N <berndnieschalk@gmail.com>
Date: Thu, 22 Feb 2024 19:02:03 +0100
Subject: [PATCH 030/411] translationBot(ui): update translation (German)

Currently translated at 78.8% (1159 of 1470 strings)

Co-authored-by: B N <berndnieschalk@gmail.com>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/de/
Translation: InvokeAI/Web UI
---
 invokeai/frontend/web/public/locales/de.json | 40 +++++++++++++++++---
 1 file changed, 35 insertions(+), 5 deletions(-)

diff --git a/invokeai/frontend/web/public/locales/de.json b/invokeai/frontend/web/public/locales/de.json
index ae3da48518..789cedfda8 100644
--- a/invokeai/frontend/web/public/locales/de.json
+++ b/invokeai/frontend/web/public/locales/de.json
@@ -601,7 +601,7 @@
         "setToOptimalSize": "Optimiere Größe für Modell"
     },
     "settings": {
-        "displayInProgress": "Bilder in Bearbeitung anzeigen",
+        "displayInProgress": "Zwischenbilder anzeigen",
         "saveSteps": "Speichern der Bilder alle n Schritte",
         "confirmOnDelete": "Bestätigen beim Löschen",
         "displayHelpIcons": "Hilfesymbole anzeigen",
@@ -614,9 +614,34 @@
         "useSlidersForAll": "Schieberegler für alle Optionen verwenden",
         "showAdvancedOptions": "Erweiterte Optionen anzeigen",
         "alternateCanvasLayout": "Alternatives Leinwand-Layout",
-        "clearIntermediatesDesc1": "Das Löschen der Zwischenprodukte setzt Leinwand und ControlNet zurück.",
+        "clearIntermediatesDesc1": "Das Löschen der Zwischenbilder setzt Leinwand und ControlNet zurück.",
         "favoriteSchedulers": "Lieblings-Planer",
-        "favoriteSchedulersPlaceholder": "Keine Planer favorisiert"
+        "favoriteSchedulersPlaceholder": "Keine Planer favorisiert",
+        "generation": "Erzeugung",
+        "enableInformationalPopovers": "Info-Popouts anzeigen",
+        "shouldLogToConsole": "Konsole loggen",
+        "showProgressInViewer": "Zwischenbilder im Viewer anzeigen",
+        "clearIntermediatesDesc3": "Ihre Bilder werden nicht gelöscht.",
+        "clearIntermediatesWithCount_one": "Lösche {{count}} Zwischenbilder",
+        "clearIntermediatesWithCount_other": "Lösche {{count}} Zwischenbilder",
+        "reloadingIn": "Neuladen in",
+        "enableNodesEditor": "Nodes Editor aktivieren",
+        "autoChangeDimensions": "Breite/Höhe auf Modellstandard setzen",
+        "experimental": "Experimentell",
+        "intermediatesCleared_one": "{{count}} Zwischenbilder gelöscht",
+        "intermediatesCleared_other": "{{count}} Zwischenbilder gelöscht",
+        "enableInvisibleWatermark": "Unsichtbares Wasserzeichen aktivieren",
+        "general": "Allgemein",
+        "consoleLogLevel": "Protokollierungsstufe",
+        "clearIntermediatesDisabled": "Warteschlange muss leer sein, um Zwischenbilder zu löschen",
+        "developer": "Entwickler",
+        "antialiasProgressImages": "Zwischenbilder mit Anti-Alias",
+        "beta": "Beta",
+        "ui": "Benutzeroberfläche",
+        "clearIntermediatesDesc2": "Zwischenbilder sind Nebenprodukte der Erstellung. Sie zu löschen macht Festplattenspeicher frei.",
+        "clearIntermediates": "Zwischenbilder löschen",
+        "intermediatesClearedFailed": "Problem beim Löschen der Zwischenbilder",
+        "enableNSFWChecker": "Auf unangemessene Inhalte prüfen"
     },
     "toast": {
         "tempFoldersEmptied": "Temp-Ordner geleert",
@@ -661,7 +686,9 @@
         "problemCopyingCanvas": "Problem beim Kopieren der Leinwand",
         "problemCopyingCanvasDesc": "Kann Basis-Layer nicht exportieren",
         "problemDownloadingCanvas": "Problem beim Herunterladen der Leinwand",
-        "setAsCanvasInitialImage": "Als Ausgangsbild gesetzt"
+        "setAsCanvasInitialImage": "Als Ausgangsbild gesetzt",
+        "addedToBoard": "Dem Board hinzugefügt",
+        "loadedWithWarnings": "Workflow mit Warnungen geladen"
     },
     "tooltip": {
         "feature": {
@@ -1397,7 +1424,10 @@
     },
     "sdxl": {
         "concatPromptStyle": "Verknüpfen von Prompt & Stil",
-        "scheduler": "Planer"
+        "scheduler": "Planer",
+        "steps": "Schritte",
+        "useRefiner": "Refiner verwenden",
+        "selectAModel": "Modell auswählen"
     },
     "dynamicPrompts": {
         "showDynamicPrompts": "Dynamische Prompts anzeigen"

From 228f1d7f629bab0d041adf3c2f9eba2982623f3d Mon Sep 17 00:00:00 2001
From: Riccardo Giovanetti <riccardo.giovanetti@gmail.com>
Date: Thu, 22 Feb 2024 19:02:03 +0100
Subject: [PATCH 031/411] translationBot(ui): update translation (Italian)

Currently translated at 95.6% (1406 of 1470 strings)

translationBot(ui): update translation (Italian)

Currently translated at 93.9% (1381 of 1470 strings)

Co-authored-by: Riccardo Giovanetti <riccardo.giovanetti@gmail.com>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/it/
Translation: InvokeAI/Web UI
---
 invokeai/frontend/web/public/locales/it.json | 100 +++++++++++++++----
 1 file changed, 80 insertions(+), 20 deletions(-)

diff --git a/invokeai/frontend/web/public/locales/it.json b/invokeai/frontend/web/public/locales/it.json
index 3d8fc79390..406b16cf49 100644
--- a/invokeai/frontend/web/public/locales/it.json
+++ b/invokeai/frontend/web/public/locales/it.json
@@ -1379,7 +1379,8 @@
     "popovers": {
         "paramScheduler": {
             "paragraphs": [
-                "Il campionatore definisce come aggiungere in modo iterativo il rumore a un'immagine o come aggiornare un campione in base all'output di un modello."
+                "Il campionatore utilizzato durante il processo di generazione.",
+                "Ciascun campionatore definisce come aggiungere in modo iterativo il rumore a un'immagine o come aggiornare un campione in base all'output di un modello."
             ],
             "heading": "Campionatore"
         },
@@ -1392,8 +1393,8 @@
         "compositingCoherenceSteps": {
             "heading": "Passi",
             "paragraphs": [
-                "Numero di passi di riduzione del rumore utilizzati nel Passaggio di Coerenza.",
-                "Uguale al parametro principale Passi."
+                "Numero di passi utilizzati nel Passaggio di Coerenza.",
+                "Simile ai passi di generazione."
             ]
         },
         "compositingBlur": {
@@ -1405,7 +1406,7 @@
         "compositingCoherenceMode": {
             "heading": "Modalità",
             "paragraphs": [
-                "La modalità del Passaggio di Coerenza."
+                "Metodo utilizzato per creare un'immagine coerente con l'area mascherata appena generata."
             ]
         },
         "clipSkip": {
@@ -1423,8 +1424,8 @@
         "compositingStrength": {
             "heading": "Forza",
             "paragraphs": [
-                "Intensità di riduzione del rumore per il passaggio di coerenza.",
-                "Uguale al parametro intensità di riduzione del rumore da immagine a immagine."
+                "Quantità di rumore aggiunta per il Passaggio di Coerenza.",
+                "Simile alla forza di riduzione del rumore."
             ]
         },
         "paramNegativeConditioning": {
@@ -1450,8 +1451,8 @@
         "controlNetBeginEnd": {
             "heading": "Percentuale passi Inizio / Fine",
             "paragraphs": [
-                "A quali passi del processo di rimozione del rumore verrà applicato ControlNet.",
-                "I ControlNet applicati all'inizio del processo guidano la composizione, mentre i ControlNet applicati alla fine guidano i dettagli."
+                "La parte del processo di rimozione del rumore in cui verrà applicato l'adattatore di controllo.",
+                "In genere, gli adattatori di controllo applicati all'inizio del processo guidano la composizione, mentre quelli applicati alla fine guidano i dettagli."
             ]
         },
         "noiseUseCPU": {
@@ -1464,7 +1465,7 @@
         },
         "scaleBeforeProcessing": {
             "paragraphs": [
-                "Ridimensiona l'area selezionata alla dimensione più adatta al modello prima del processo di generazione dell'immagine."
+                "\"Auto\" ridimensiona l'area selezionata alla dimensione più adatta al modello prima del processo di generazione dell'immagine."
             ],
             "heading": "Scala prima dell'elaborazione"
         },
@@ -1499,20 +1500,21 @@
         "paramVAEPrecision": {
             "heading": "Precisione VAE",
             "paragraphs": [
-                "La precisione utilizzata durante la codifica e decodifica VAE. FP16/mezza precisione è più efficiente, a scapito di minori variazioni dell'immagine."
+                "La precisione utilizzata durante la codifica e decodifica VAE.",
+                "Fp16/Mezza precisione è più efficiente, a scapito di minori variazioni dell'immagine."
             ]
         },
         "paramSeed": {
             "paragraphs": [
                 "Controlla il rumore iniziale utilizzato per la generazione.",
-                "Disabilita seme \"Casuale\" per produrre risultati identici con le stesse impostazioni di generazione."
+                "Disabilita l'opzione \"Casuale\" per produrre risultati identici con le stesse impostazioni di generazione."
             ],
             "heading": "Seme"
         },
         "controlNetResizeMode": {
             "heading": "Modalità ridimensionamento",
             "paragraphs": [
-                "Come l'immagine ControlNet verrà adattata alle dimensioni di output dell'immagine."
+                "Metodo per adattare le dimensioni dell'immagine in ingresso dell'adattatore di controllo alle dimensioni della generazione di output."
             ]
         },
         "dynamicPromptsSeedBehaviour": {
@@ -1527,7 +1529,7 @@
         "paramModel": {
             "heading": "Modello",
             "paragraphs": [
-                "Modello utilizzato per i passaggi di riduzione del rumore."
+                "Modello utilizzato per la generazione. Diversi modelli vengono addestrati per specializzarsi nella produzione di risultati e contenuti estetici diversi."
             ]
         },
         "paramDenoisingStrength": {
@@ -1545,25 +1547,26 @@
         },
         "infillMethod": {
             "paragraphs": [
-                "Metodo per riempire l'area selezionata."
+                "Metodo di riempimento durante il processo di Outpainting o Inpainting."
             ],
             "heading": "Metodo di riempimento"
         },
         "controlNetWeight": {
             "heading": "Peso",
             "paragraphs": [
-                "Quanto forte sarà l'impatto di ControlNet sull'immagine generata."
+                "Peso dell'adattatore di controllo. Un peso maggiore porterà a impatti maggiori sull'immagine finale."
             ]
         },
         "paramCFGScale": {
             "heading": "Scala CFG",
             "paragraphs": [
-                "Controlla quanto il tuo prompt influenza il processo di generazione."
+                "Controlla quanto il prompt influenza il processo di generazione.",
+                "Valori elevati della scala CFG possono provocare una saturazione eccessiva e distorsioni nei risultati della generazione. "
             ]
         },
         "controlNetControlMode": {
             "paragraphs": [
-                "Attribuisce più peso al prompt o a ControlNet."
+                "Attribuisce più peso al prompt oppure a ControlNet."
             ],
             "heading": "Modalità di controllo"
         },
@@ -1575,9 +1578,9 @@
             ]
         },
         "lora": {
-            "heading": "Peso LoRA",
+            "heading": "LoRA",
             "paragraphs": [
-                "Un peso LoRA più elevato porterà a impatti maggiori sull'immagine finale."
+                "Modelli leggeri utilizzati insieme ai modelli base."
             ]
         },
         "controlNet": {
@@ -1589,8 +1592,65 @@
         "paramCFGRescaleMultiplier": {
             "heading": "Moltiplicatore di riscala CFG",
             "paragraphs": [
-                "Moltiplicatore di riscala per la guida CFG, utilizzato per modelli addestrati utilizzando SNR a terminale zero (ztsnr). Valore suggerito 0.7."
+                "Moltiplicatore di riscala per la guida CFG, utilizzato per modelli addestrati utilizzando SNR a terminale zero (ztsnr).",
+                "Valore suggerito di 0.7 per questi modelli."
             ]
+        },
+        "controlNetProcessor": {
+            "heading": "Processore",
+            "paragraphs": [
+                "Metodo di elaborazione dell'immagine di input per guidare il processo di generazione. Processori diversi forniranno effetti o stili diversi nelle immagini generate."
+            ]
+        },
+        "imageFit": {
+            "heading": "Adatta l'immagine iniziale alle dimensioni di output",
+            "paragraphs": [
+                "Ridimensiona l'immagine iniziale in base alla larghezza e all'altezza dell'immagine di output. Si consiglia di abilitarlo."
+            ]
+        },
+        "loraWeight": {
+            "heading": "Peso",
+            "paragraphs": [
+                "Peso del LoRA. Un peso maggiore comporterà un impatto maggiore sull'immagine finale."
+            ]
+        },
+        "paramAspect": {
+            "heading": "Aspetto",
+            "paragraphs": [
+                "Proporzioni dell'immagine generata. La modifica del rapporto aggiornerà di conseguenza la larghezza e l'altezza.",
+                "\"Ottimizza\" imposterà la larghezza e l'altezza alle dimensioni ottimali per il modello scelto."
+            ]
+        },
+        "paramHeight": {
+            "heading": "Altezza",
+            "paragraphs": [
+                "Altezza dell'immagine generata. Deve essere un multiplo di 8."
+            ]
+        },
+        "paramHrf": {
+            "heading": "Abilita correzione alta risoluzione",
+            "paragraphs": [
+                "Genera immagini di alta qualità con una risoluzione maggiore di quella ottimale per il modello. Generalmente utilizzato per impedire la duplicazione nell'immagine generata."
+            ]
+        },
+        "paramUpscaleMethod": {
+            "heading": "Metodo di ampliamento",
+            "paragraphs": [
+                "Metodo utilizzato per eseguire l'ampliamento dell'immagine per la correzione ad alta risoluzione."
+            ]
+        },
+        "patchmatchDownScaleSize": {
+            "heading": "Ridimensiona",
+            "paragraphs": [
+                "Quanto ridimensionamento avviene prima del riempimento.",
+                "Un ridimensionamento più elevato migliorerà le prestazioni e ridurrà la qualità."
+            ]
+        },
+        "paramWidth": {
+            "paragraphs": [
+                "Larghezza dell'immagine generata. Deve essere un multiplo di 8."
+            ],
+            "heading": "Larghezza"
         }
     },
     "sdxl": {

From 9986fce1a6e735fd28df6b0d56edc89cce040006 Mon Sep 17 00:00:00 2001
From: Alexander Eichhorn <pfannkuchensack@einfach-doof.de>
Date: Thu, 22 Feb 2024 19:02:03 +0100
Subject: [PATCH 032/411] translationBot(ui): update translation (German)

Currently translated at 80.0% (1176 of 1470 strings)

Co-authored-by: Alexander Eichhorn <pfannkuchensack@einfach-doof.de>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/de/
Translation: InvokeAI/Web UI
---
 invokeai/frontend/web/public/locales/de.json | 23 +++++++++++++++++---
 1 file changed, 20 insertions(+), 3 deletions(-)

diff --git a/invokeai/frontend/web/public/locales/de.json b/invokeai/frontend/web/public/locales/de.json
index 789cedfda8..3b44c4c62f 100644
--- a/invokeai/frontend/web/public/locales/de.json
+++ b/invokeai/frontend/web/public/locales/de.json
@@ -116,7 +116,8 @@
         "saveAs": "Speichern als",
         "updated": "Aktualisiert",
         "copy": "Kopieren",
-        "aboutHeading": "Nutzen Sie Ihre kreative Energie"
+        "aboutHeading": "Nutzen Sie Ihre kreative Energie",
+        "toResolve": "Lösen"
     },
     "gallery": {
         "generations": "Erzeugungen",
@@ -906,7 +907,11 @@
         "small": "Klein",
         "base": "Basis",
         "depthAnything": "Depth Anything",
-        "depthAnythingDescription": "Erstellung einer Tiefenkarte mit der Depth-Anything-Technik"
+        "depthAnythingDescription": "Erstellung einer Tiefenkarte mit der Depth-Anything-Technik",
+        "face": "Gesicht",
+        "body": "Körper",
+        "hands": "Hände",
+        "dwOpenpose": "DW Openpose"
     },
     "queue": {
         "status": "Status",
@@ -1329,7 +1334,19 @@
         "vaeFieldDescription": "VAE Submodell.",
         "unknownInput": "Unbekannte Eingabe: {{name}}",
         "unknownNodeType": "Unbekannter Knotentyp",
-        "float": "Kommazahlen"
+        "float": "Kommazahlen",
+        "latentsPolymorphic": "Latents Polymorph",
+        "integerPolymorphicDescription": "Eine Sammlung von ganzen Zahlen.",
+        "integerPolymorphic": "Ganze Zahl Polymorph",
+        "ipAdapterPolymorphic": "IP-Adapter Polymorph",
+        "floatPolymorphic": "Fließkommazahl Polymorph",
+        "enumDescription": "Aufzählungen sind Werte, die eine von mehreren Optionen sein können.",
+        "floatCollection": "Fließkommazahl Sammlung",
+        "enum": "Aufzählung",
+        "floatPolymorphicDescription": "Eine Sammlung von Fließkommazahlen",
+        "fullyContainNodes": "Vollständig ausgewählte Nodes auswählen",
+        "editMode": "Im Workflow-Editor bearbeiten",
+        "floatCollectionDescription": "Eine Sammlung von Fließkommazahlen"
     },
     "hrf": {
         "enableHrf": "Korrektur für hohe Auflösungen",

From 34b0ea20dc7741012a32d72d1b9f1c577d705081 Mon Sep 17 00:00:00 2001
From: B N <berndnieschalk@gmail.com>
Date: Sun, 25 Feb 2024 12:01:59 +0100
Subject: [PATCH 033/411] translationBot(ui): update translation (German)

Currently translated at 80.3% (1181 of 1470 strings)

translationBot(ui): update translation (German)

Currently translated at 80.1% (1178 of 1470 strings)

Co-authored-by: B N <berndnieschalk@gmail.com>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/de/
Translation: InvokeAI/Web UI
---
 invokeai/frontend/web/public/locales/de.json | 17 +++++++++++++----
 1 file changed, 13 insertions(+), 4 deletions(-)

diff --git a/invokeai/frontend/web/public/locales/de.json b/invokeai/frontend/web/public/locales/de.json
index 3b44c4c62f..b0a3f799b3 100644
--- a/invokeai/frontend/web/public/locales/de.json
+++ b/invokeai/frontend/web/public/locales/de.json
@@ -599,7 +599,10 @@
         "setToOptimalSizeTooLarge": "$t(parameters.setToOptimalSize) (kann zu groß sein)",
         "lockAspectRatio": "Seitenverhältnis sperren",
         "swapDimensions": "Seitenverhältnis umkehren",
-        "setToOptimalSize": "Optimiere Größe für Modell"
+        "setToOptimalSize": "Optimiere Größe für Modell",
+        "useSize": "Maße übernehmen",
+        "remixImage": "Remix des Bilds erstellen",
+        "imageActions": "Weitere Bildaktionen"
     },
     "settings": {
         "displayInProgress": "Zwischenbilder anzeigen",
@@ -858,7 +861,7 @@
         "colorMap": "Farbe",
         "lowThreshold": "Niedrige Schwelle",
         "highThreshold": "Hohe Schwelle",
-        "toggleControlNet": "Schalten ControlNet um",
+        "toggleControlNet": "Dieses ControlNet ein- oder ausschalten",
         "delete": "Löschen",
         "controlAdapter_one": "Control Adapter",
         "controlAdapter_other": "Control Adapter",
@@ -911,14 +914,15 @@
         "face": "Gesicht",
         "body": "Körper",
         "hands": "Hände",
-        "dwOpenpose": "DW Openpose"
+        "dwOpenpose": "DW Openpose",
+        "dwOpenposeDescription": "Posenschätzung mit DW Openpose"
     },
     "queue": {
         "status": "Status",
         "cancelTooltip": "Aktuellen Aufgabe abbrechen",
         "queueEmpty": "Warteschlange leer",
         "in_progress": "In Arbeit",
-        "queueFront": "An den Anfang der Warteschlange tun",
+        "queueFront": "Am Anfang der Warteschlange einreihen",
         "completed": "Fertig",
         "queueBack": "In die Warteschlange",
         "clearFailed": "Probleme beim leeren der Warteschlange",
@@ -1131,6 +1135,11 @@
                 "\"Planer\" definiert, wie iterativ Rauschen zu einem Bild hinzugefügt wird, oder wie ein Sample bei der Ausgabe eines Modells aktualisiert wird."
             ],
             "heading": "Planer"
+        },
+        "imageFit": {
+            "paragraphs": [
+                "Reduziert das Ausgangsbild auf die Breite und Höhe des Ausgangsbildes. Empfohlen zu aktivieren."
+            ]
         }
     },
     "ui": {

From 2ec6b51d8b680b341df180908ed43818032c5cd3 Mon Sep 17 00:00:00 2001
From: Riccardo Giovanetti <riccardo.giovanetti@gmail.com>
Date: Sun, 25 Feb 2024 12:01:59 +0100
Subject: [PATCH 034/411] translationBot(ui): update translation (Italian)

Currently translated at 97.2% (1430 of 1470 strings)

Co-authored-by: Riccardo Giovanetti <riccardo.giovanetti@gmail.com>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/it/
Translation: InvokeAI/Web UI
---
 invokeai/frontend/web/public/locales/it.json | 66 +++++++++++++++++++-
 1 file changed, 63 insertions(+), 3 deletions(-)

diff --git a/invokeai/frontend/web/public/locales/it.json b/invokeai/frontend/web/public/locales/it.json
index 406b16cf49..9cd46874c1 100644
--- a/invokeai/frontend/web/public/locales/it.json
+++ b/invokeai/frontend/web/public/locales/it.json
@@ -934,7 +934,7 @@
         "executionStateCompleted": "Completato",
         "boardFieldDescription": "Una bacheca della galleria",
         "addNodeToolTip": "Aggiungi nodo (Shift+A, Space)",
-        "sDXLRefinerModelField": "Modello Refiner",
+        "sDXLRefinerModelField": "Modello Affinatore",
         "problemReadingMetadata": "Problema durante la lettura dei metadati dall'immagine",
         "colorCodeEdgesHelp": "Bordi con codice colore in base ai campi collegati",
         "animatedEdges": "Bordi animati",
@@ -1329,7 +1329,7 @@
         "noModelsAvailable": "Nessun modello disponibile",
         "selectModel": "Seleziona un modello",
         "selectLoRA": "Seleziona un LoRA",
-        "noRefinerModelsInstalled": "Nessun modello SDXL Refiner installato",
+        "noRefinerModelsInstalled": "Nessun modello affinatore SDXL installato",
         "noLoRAsInstalled": "Nessun LoRA installato",
         "esrganModel": "Modello ESRGAN",
         "addLora": "Aggiungi LoRA",
@@ -1465,7 +1465,8 @@
         },
         "scaleBeforeProcessing": {
             "paragraphs": [
-                "\"Auto\" ridimensiona l'area selezionata alla dimensione più adatta al modello prima del processo di generazione dell'immagine."
+                "\"Auto\" ridimensiona l'area selezionata alla dimensione più adatta al modello prima del processo di generazione dell'immagine.",
+                "\"Manuale\" consente di scegliere la larghezza e l'altezza a cui verrà ridimensionata l'area selezionata prima del processo di generazione dell'immagine."
             ],
             "heading": "Scala prima dell'elaborazione"
         },
@@ -1651,6 +1652,65 @@
                 "Larghezza dell'immagine generata. Deve essere un multiplo di 8."
             ],
             "heading": "Larghezza"
+        },
+        "refinerModel": {
+            "heading": "Modello Affinatore",
+            "paragraphs": [
+                "Modello utilizzato durante la parte di affinamento del processo di generazione.",
+                "Simile al modello di generazione."
+            ]
+        },
+        "refinerNegativeAestheticScore": {
+            "paragraphs": [
+                "Valuta le generazioni in modo che siano più simili alle immagini con un punteggio estetico basso, in base ai dati di addestramento."
+            ],
+            "heading": "Punteggio estetico negativo"
+        },
+        "refinerScheduler": {
+            "paragraphs": [
+                "Campionatore utilizzato durante la parte di affinamento del processo di generazione.",
+                "Simile al campionatore di generazione."
+            ],
+            "heading": "Campionatore"
+        },
+        "refinerStart": {
+            "heading": "Inizio affinamento",
+            "paragraphs": [
+                "A che punto nel processo di generazione inizierà ad essere utilizzato l'affinatore.",
+                "0 significa che l'affinatore verrà utilizzato per l'intero processo di generazione, 0.8 significa che l'affinatore verrà utilizzato per l'ultimo 20% del processo di generazione."
+            ]
+        },
+        "refinerSteps": {
+            "heading": "Passi",
+            "paragraphs": [
+                "Numero di passi che verranno eseguiti durante la parte di affinamento del processo di generazione.",
+                "Simile ai passi di generazione."
+            ]
+        },
+        "refinerCfgScale": {
+            "heading": "Scala CFG",
+            "paragraphs": [
+                "Controlla quanto il prompt influenza il processo di generazione.",
+                "Simile alla scala CFG di generazione."
+            ]
+        },
+        "seamlessTilingXAxis": {
+            "heading": "Asse X di piastrellatura senza cuciture",
+            "paragraphs": [
+                "Affianca senza soluzione di continuità un'immagine lungo l'asse orizzontale."
+            ]
+        },
+        "seamlessTilingYAxis": {
+            "heading": "Asse Y di piastrellatura senza cuciture",
+            "paragraphs": [
+                "Affianca senza soluzione di continuità un'immagine lungo l'asse verticale."
+            ]
+        },
+        "refinerPositiveAestheticScore": {
+            "heading": "Punteggio estetico positivo",
+            "paragraphs": [
+                "Valuta le generazioni in modo che siano più simili alle immagini con un punteggio estetico elevato, in base ai dati di addestramento."
+            ]
         }
     },
     "sdxl": {

From 3a09bceea42c161a64272c246976840989cf0fc3 Mon Sep 17 00:00:00 2001
From: skunkworxdark <neil_hodgson@hotmail.com>
Date: Mon, 26 Feb 2024 18:42:25 +0000
Subject: [PATCH 035/411] Update communityNodes.md

Updated description of metadata nodes
---
 docs/nodes/communityNodes.md | 21 +++++++++++++++------
 1 file changed, 15 insertions(+), 6 deletions(-)

diff --git a/docs/nodes/communityNodes.md b/docs/nodes/communityNodes.md
index 33dddad162..296fbb7ee6 100644
--- a/docs/nodes/communityNodes.md
+++ b/docs/nodes/communityNodes.md
@@ -354,12 +354,21 @@ See full docs here: https://github.com/skunkworxdark/Prompt-tools-nodes/edit/mai
 
 **Description:** A set of nodes for Metadata. Collect Metadata from within an `iterate` node & extract metadata from an image.
 
-- `Metadata Item Linked` - Allows collecting of metadata while within an iterate node with no need for a collect node or conversion to metadata node.
-- `Metadata From Image` - Provides Metadata from an image.
-- `Metadata To String` - Extracts a String value of a label from metadata.
-- `Metadata To Integer` - Extracts an Integer value of a label from metadata.
-- `Metadata To Float` - Extracts a Float value of a label from metadata.
-- `Metadata To Scheduler` - Extracts a Scheduler value of a label from metadata.
+- `Metadata Item Linked` - Allows collecting of metadata while within an iterate node with no need for a collect node or conversion to metadata node
+- `Metadata From Image` - Provides Metadata from an image
+- `Metadata To String` - Extracts a String value of a label from metadata
+- `Metadata To Integer` - Extracts an Integer value of a label from metadata
+- `Metadata To Float` - Extracts a Float value of a label from metadata
+- `Metadata To Scheduler` - Extracts a Scheduler value of a label from metadata
+- `Metadata To Bool` - Extracts Bool types from metadata
+- `Metadata To Model` - Extracts model types from metadata
+- `Metadata To SDXL Model` - Extracts SDXL model types from metadata
+- `Metadata To LoRAs` - Extracts Loras from metadata. 
+- `Metadata To SDXL LoRAs` - Extracts SDXL Loras from metadata
+- `Metadata To ControlNets` - Extracts ControNets from metadata
+- `Metadata To IP-Adapters` - Extracts IP-Adapters from metadata
+- `Metadata To T2I-Adapters` - Extracts T2I-Adapters from metadata
+- `Denoise Latents + Metadata` - This is an inherited version of the existing `Denoise Latents` node but with a metadata input and output. 
 
 **Node Link:** https://github.com/skunkworxdark/metadata-linked-nodes
 

From 1a3ffb6e94c0c399492a070fa22e0ffc1f8c79d4 Mon Sep 17 00:00:00 2001
From: Alexander Eichhorn <pfannkuchensack@einfach-doof.de>
Date: Wed, 28 Feb 2024 16:02:04 +0100
Subject: [PATCH 036/411] translationBot(ui): update translation (German)

Currently translated at 80.4% (1183 of 1470 strings)

Co-authored-by: Alexander Eichhorn <pfannkuchensack@einfach-doof.de>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/de/
Translation: InvokeAI/Web UI
---
 invokeai/frontend/web/public/locales/de.json | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/invokeai/frontend/web/public/locales/de.json b/invokeai/frontend/web/public/locales/de.json
index b0a3f799b3..65aa7b2a7a 100644
--- a/invokeai/frontend/web/public/locales/de.json
+++ b/invokeai/frontend/web/public/locales/de.json
@@ -1007,7 +1007,8 @@
         "workflow": "Workflow",
         "scheduler": "Planer",
         "noRecallParameters": "Es wurden keine Parameter zum Abrufen gefunden",
-        "recallParameters": "Parameter wiederherstellen"
+        "recallParameters": "Parameter wiederherstellen",
+        "cfgRescaleMultiplier": "$t(parameters.cfgRescaleMultiplier)"
     },
     "popovers": {
         "noiseUseCPU": {

From 9a8a9c5848834f808b3fe8dc3e28bb950eb6c169 Mon Sep 17 00:00:00 2001
From: Samantha Morello <tildsart@gmail.com>
Date: Wed, 28 Feb 2024 16:02:06 +0100
Subject: [PATCH 037/411] translationBot(ui): update translation (Italian)

Currently translated at 98.0% (1441 of 1470 strings)

Co-authored-by: Samantha Morello <tildsart@gmail.com>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/it/
Translation: InvokeAI/Web UI
---
 invokeai/frontend/web/public/locales/it.json | 25 ++++++++++++++------
 1 file changed, 18 insertions(+), 7 deletions(-)

diff --git a/invokeai/frontend/web/public/locales/it.json b/invokeai/frontend/web/public/locales/it.json
index 9cd46874c1..1a55f967f7 100644
--- a/invokeai/frontend/web/public/locales/it.json
+++ b/invokeai/frontend/web/public/locales/it.json
@@ -47,7 +47,7 @@
         "statusModelConverted": "Modello Convertito",
         "statusConvertingModel": "Conversione Modello",
         "loading": "Caricamento in corso",
-        "loadingInvokeAI": "Caricamento Invoke AI",
+        "loadingInvokeAI": "Caricamento di Invoke AI",
         "postprocessing": "Post Elaborazione",
         "txt2img": "Testo a Immagine",
         "accept": "Accetta",
@@ -61,7 +61,7 @@
         "imagePrompt": "Prompt Immagine",
         "darkMode": "Modalità scura",
         "batch": "Gestione Lotto",
-        "modelManager": "Gestore modello",
+        "modelManager": "Gestore Modelli",
         "communityLabel": "Comunità",
         "nodeEditor": "Editor dei nodi",
         "statusProcessing": "Elaborazione in corso",
@@ -81,7 +81,7 @@
         "error": "Errore",
         "installed": "Installato",
         "template": "Schema",
-        "outputs": "Uscite",
+        "outputs": "Risultati",
         "data": "Dati",
         "somethingWentWrong": "Qualcosa è andato storto",
         "copyError": "$t(gallery.copy) Errore",
@@ -93,7 +93,7 @@
         "created": "Creato",
         "prevPage": "Pagina precedente",
         "delete": "Elimina",
-        "orderBy": "Ordinato per",
+        "orderBy": "Ordina per",
         "nextPage": "Pagina successiva",
         "saveAs": "Salva come",
         "unsaved": "Non salvato",
@@ -109,7 +109,12 @@
         "green": "Verde",
         "blue": "Blu",
         "alpha": "Alfa",
-        "copy": "Copia"
+        "copy": "Copia",
+        "on": "Attivato",
+        "checkpoint": "Checkpoint",
+        "safetensors": "Safetensors",
+        "ai": "ia",
+        "file": "File"
     },
     "gallery": {
         "generations": "Generazioni",
@@ -1249,7 +1254,12 @@
         "dwOpenposeDescription": "Stima della posa umana utilizzando DW Openpose",
         "face": "Viso",
         "body": "Corpo",
-        "hands": "Mani"
+        "hands": "Mani",
+        "lineartAnime": "Linea Anime",
+        "base": "Base",
+        "lineart": "Linea",
+        "controlnet": "$t(controlnet.controlAdapter_one) #{{number}} ($t(common.controlNet))",
+        "mediapipeFace": "Mediapipe Volto"
     },
     "queue": {
         "queueFront": "Aggiungi all'inizio della coda",
@@ -1758,7 +1768,8 @@
         "steps": "Passi",
         "scheduler": "Campionatore",
         "recallParameters": "Richiama i parametri",
-        "noRecallParameters": "Nessun parametro da richiamare trovato"
+        "noRecallParameters": "Nessun parametro da richiamare trovato",
+        "cfgRescaleMultiplier": "$t(parameters.cfgRescaleMultiplier)"
     },
     "hrf": {
         "enableHrf": "Abilita Correzione Alta Risoluzione",

From 63ab5ff5a29e5b46664e2642e636ca34b26a6192 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=D0=92=D0=B0=D1=81=D1=8F=D0=BD=D0=B0=D1=82=D0=BE=D1=80?=
 <ilabulanov339@gmail.com>
Date: Wed, 28 Feb 2024 16:02:07 +0100
Subject: [PATCH 038/411] translationBot(ui): update translation (Russian)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Currently translated at 98.3% (1398 of 1422 strings)

Co-authored-by: Васянатор <ilabulanov339@gmail.com>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/ru/
Translation: InvokeAI/Web UI
---
 invokeai/frontend/web/public/locales/ru.json | 93 +++++++++++++++-----
 1 file changed, 71 insertions(+), 22 deletions(-)

diff --git a/invokeai/frontend/web/public/locales/ru.json b/invokeai/frontend/web/public/locales/ru.json
index af640e538a..8468554bab 100644
--- a/invokeai/frontend/web/public/locales/ru.json
+++ b/invokeai/frontend/web/public/locales/ru.json
@@ -108,7 +108,16 @@
         "preferencesLabel": "Предпочтения",
         "or": "или",
         "advancedOptions": "Расширенные настройки",
-        "free": "Свободно"
+        "free": "Свободно",
+        "aboutHeading": "Владей своей творческой силой",
+        "red": "Красный",
+        "green": "Зеленый",
+        "blue": "Синий",
+        "alpha": "Альфа",
+        "toResolve": "Чтоб решить",
+        "copy": "Копировать",
+        "localSystem": "Локальная система",
+        "aboutDesc": "Используя Invoke для работы? Проверьте это:"
     },
     "gallery": {
         "generations": "Генерации",
@@ -152,17 +161,17 @@
     },
     "hotkeys": {
         "keyboardShortcuts": "Горячие клавиши",
-        "appHotkeys": "Горячие клавиши приложения",
-        "generalHotkeys": "Общие горячие клавиши",
-        "galleryHotkeys": "Горячие клавиши галереи",
-        "unifiedCanvasHotkeys": "Горячие клавиши Единого холста",
+        "appHotkeys": "Приложение",
+        "generalHotkeys": "Общее",
+        "galleryHotkeys": "Галлерея",
+        "unifiedCanvasHotkeys": "Единый холст",
         "invoke": {
             "title": "Invoke",
             "desc": "Сгенерировать изображение"
         },
         "cancel": {
             "title": "Отменить",
-            "desc": "Отменить генерацию изображения"
+            "desc": "Отменить текущий элемент"
         },
         "focusPrompt": {
             "title": "Переключиться на ввод запроса",
@@ -352,7 +361,7 @@
             "desc": "Открывает меню добавления узла",
             "title": "Добавление узлов"
         },
-        "nodesHotkeys": "Горячие клавиши узлов",
+        "nodesHotkeys": "Узлы",
         "cancelAndClear": {
             "desc": "Отмена текущего элемента очереди и очистка всех ожидающих элементов",
             "title": "Отменить и очистить"
@@ -367,7 +376,11 @@
             "desc": "Открытие и закрытие панели опций и галереи",
             "title": "Переключить опции и галерею"
         },
-        "clearSearch": "Очистить поиск"
+        "clearSearch": "Очистить поиск",
+        "remixImage": {
+            "desc": "Используйте все параметры, кроме сида из текущего изображения",
+            "title": "Ремикс изображения"
+        }
     },
     "modelManager": {
         "modelManager": "Менеджер моделей",
@@ -512,7 +525,8 @@
         "modelType": "Тип модели",
         "customConfigFileLocation": "Расположение пользовательского файла конфигурации",
         "vaePrecision": "Точность VAE",
-        "noModelSelected": "Модель не выбрана"
+        "noModelSelected": "Модель не выбрана",
+        "configFile": "Файл конфигурации"
     },
     "parameters": {
         "images": "Изображения",
@@ -583,8 +597,8 @@
         "copyImage": "Скопировать изображение",
         "showPreview": "Показать предпросмотр",
         "noiseSettings": "Шум",
-        "seamlessXAxis": "Горизонтальная",
-        "seamlessYAxis": "Вертикальная",
+        "seamlessXAxis": "Бесшовность по оси X",
+        "seamlessYAxis": "Бесшовность по оси Y",
         "scheduler": "Планировщик",
         "boundingBoxWidth": "Ширина ограничивающей рамки",
         "boundingBoxHeight": "Высота ограничивающей рамки",
@@ -612,7 +626,7 @@
             "noControlImageForControlAdapter": "Адаптер контроля #{{number}} не имеет изображения",
             "noModelForControlAdapter": "Не выбрана модель адаптера контроля #{{number}}.",
             "unableToInvoke": "Невозможно вызвать",
-            "incompatibleBaseModelForControlAdapter": "Модель контрольного адаптера №{{number}} недействительна для основной модели.",
+            "incompatibleBaseModelForControlAdapter": "Адаптер контроля №{{number}} несовместим с основной моделью.",
             "systemDisconnected": "Система отключена",
             "missingNodeTemplate": "Отсутствует шаблон узла",
             "readyToInvoke": "Готово к вызову",
@@ -653,7 +667,10 @@
         "setToOptimalSize": "Установить оптимальный для модели размер",
         "setToOptimalSizeTooSmall": "$t(parameters.setToOptimalSize) (может быть слишком маленьким)",
         "setToOptimalSizeTooLarge": "$t(parameters.setToOptimalSize) (может быть слишком большим)",
-        "lockAspectRatio": "Заблокировать соотношение"
+        "lockAspectRatio": "Заблокировать соотношение",
+        "boxBlur": "Размытие прямоугольника",
+        "gaussianBlur": "Размытие по Гауссу",
+        "remixImage": "Ремикс изображения"
     },
     "settings": {
         "models": "Модели",
@@ -787,7 +804,10 @@
         "canvasSavedGallery": "Холст сохранен в галерею",
         "imageUploadFailed": "Не удалось загрузить изображение",
         "modelAdded": "Добавлена модель: {{modelName}}",
-        "problemImportingMask": "Проблема с импортом маски"
+        "problemImportingMask": "Проблема с импортом маски",
+        "problemDownloadingImage": "Не удается скачать изображение",
+        "uploadInitialImage": "Загрузить начальное изображение",
+        "resetInitialImage": "Сбросить начальное изображение"
     },
     "tooltip": {
         "feature": {
@@ -892,7 +912,8 @@
         "mode": "Режим",
         "loadMore": "Загрузить больше",
         "resetUI": "$t(accessibility.reset) интерфейс",
-        "createIssue": "Сообщить о проблеме"
+        "createIssue": "Сообщить о проблеме",
+        "about": "Об этом"
     },
     "ui": {
         "showProgressImages": "Показывать промежуточный итог",
@@ -1117,7 +1138,18 @@
         "unableToParseEdge": "Невозможно разобрать край",
         "unknownInput": "Неизвестный вход: {{name}}",
         "oNNXModelFieldDescription": "Поле модели ONNX.",
-        "imageCollection": "Коллекция изображений"
+        "imageCollection": "Коллекция изображений",
+        "newWorkflow": "Новый рабочий процесс",
+        "newWorkflowDesc": "Создать новый рабочий процесс?",
+        "clearWorkflow": "Очистить рабочий процесс",
+        "newWorkflowDesc2": "Текущий рабочий процесс имеет несохраненные изменения.",
+        "latentsCollection": "Коллекция латентов",
+        "clearWorkflowDesc": "Очистить этот рабочий процесс и создать новый?",
+        "clearWorkflowDesc2": "Текущий рабочий процесс имеет несохраненные измерения.",
+        "reorderLinearView": "Изменить порядок линейного просмотра",
+        "viewMode": "Использовать в линейном представлении",
+        "editMode": "Открыть в редакторе узлов",
+        "resetToDefaultValue": "Сбросить к стандартному значкнию"
     },
     "controlnet": {
         "amult": "a_mult",
@@ -1198,7 +1230,18 @@
         "enableIPAdapter": "Включить IP Adapter",
         "maxFaces": "Макс Лица",
         "mlsdDescription": "Минималистичный детектор отрезков линии",
-        "resizeSimple": "Изменить размер (простой)"
+        "resizeSimple": "Изменить размер (простой)",
+        "megaControl": "Mega контроль",
+        "base": "Базовый",
+        "depthAnything": "Глубина всего",
+        "depthAnythingDescription": "Создание карты глубины с использованием метода Depth Anything",
+        "face": "Лицо",
+        "dwOpenposeDescription": "Оценка позы человека с помощью DW Openpose",
+        "large": "Большой",
+        "modelSize": "Размер модели",
+        "small": "Маленький",
+        "body": "Тело",
+        "hands": "Руки"
     },
     "boards": {
         "autoAddBoard": "Авто добавление Доски",
@@ -1281,7 +1324,7 @@
         "compositingCoherenceSteps": {
             "heading": "Шаги",
             "paragraphs": [
-                null,
+                "Количество шагов снижения шума, используемых при прохождении когерентности.",
                 "То же, что и основной параметр «Шаги»."
             ]
         },
@@ -1319,7 +1362,10 @@
             ]
         },
         "compositingCoherenceMode": {
-            "heading": "Режим"
+            "heading": "Режим",
+            "paragraphs": [
+                "Режим прохождения когерентности."
+            ]
         },
         "paramSeed": {
             "paragraphs": [
@@ -1599,7 +1645,7 @@
         "openWorkflow": "Открытый рабочий процесс",
         "clearWorkflowSearchFilter": "Очистить фильтр поиска рабочих процессов",
         "workflowLibrary": "Библиотека",
-        "downloadWorkflow": "Скачать рабочий процесс",
+        "downloadWorkflow": "Сохранить в файл",
         "noRecentWorkflows": "Нет недавних рабочих процессов",
         "workflowSaved": "Рабочий процесс сохранен",
         "workflowIsOpen": "Рабочий процесс открыт",
@@ -1612,9 +1658,12 @@
         "deleteWorkflow": "Удалить рабочий процесс",
         "workflows": "Рабочие процессы",
         "noDescription": "Без описания",
-        "uploadWorkflow": "Загрузить рабочий процесс",
+        "uploadWorkflow": "Загрузить из файла",
         "userWorkflows": "Мои рабочие процессы",
-        "newWorkflowCreated": "Создан новый рабочий процесс"
+        "newWorkflowCreated": "Создан новый рабочий процесс",
+        "saveWorkflowToProject": "Сохранить рабочий процесс в проект",
+        "workflowCleared": "Рабочий процесс очищен",
+        "noWorkflows": "Нет рабочих процессов"
     },
     "embedding": {
         "noEmbeddingsLoaded": "встраивания не загружены",

From 992b02aa65ac9ae1e7554ef80f51d18a17d569f9 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 13 Jan 2024 15:23:06 +1100
Subject: [PATCH 039/411] tidy(nodes): move all field things to fields.py

Unfortunately, this is necessary to prevent circular imports at runtime.
---
 invokeai/app/api/routers/images.py            |   2 +-
 invokeai/app/api_app.py                       |   3 +-
 invokeai/app/invocations/baseinvocation.py    | 453 +---------------
 invokeai/app/invocations/collections.py       |   3 +-
 invokeai/app/invocations/compel.py            |   6 +-
 .../controlnet_image_processors.py            |   6 +-
 invokeai/app/invocations/cv.py                |   3 +-
 invokeai/app/invocations/facetools.py         |   4 +-
 invokeai/app/invocations/fields.py            | 501 ++++++++++++++++++
 invokeai/app/invocations/image.py             |   5 +-
 invokeai/app/invocations/infill.py            |   3 +-
 invokeai/app/invocations/ip_adapter.py        |   5 +-
 invokeai/app/invocations/latent.py            |   7 +-
 invokeai/app/invocations/math.py              |   4 +-
 invokeai/app/invocations/metadata.py          |   6 +-
 invokeai/app/invocations/model.py             |   5 +-
 invokeai/app/invocations/noise.py             |   4 +-
 invokeai/app/invocations/onnx.py              |  16 +-
 invokeai/app/invocations/param_easing.py      |   3 +-
 invokeai/app/invocations/primitives.py        |   6 +-
 invokeai/app/invocations/prompt.py            |   3 +-
 invokeai/app/invocations/sdxl.py              |   6 +-
 invokeai/app/invocations/strings.py           |   4 +-
 invokeai/app/invocations/t2i_adapter.py       |   5 +-
 invokeai/app/invocations/tiles.py             |   5 +-
 invokeai/app/invocations/upscale.py           |   3 +-
 .../services/image_files/image_files_base.py  |   2 +-
 .../services/image_files/image_files_disk.py  |   2 +-
 .../image_records/image_records_base.py       |   2 +-
 .../image_records/image_records_sqlite.py     |   2 +-
 invokeai/app/services/images/images_base.py   |   2 +-
 .../app/services/images/images_default.py     |   2 +-
 invokeai/app/services/shared/graph.py         |   5 +-
 invokeai/app/shared/fields.py                 |  67 ---
 invokeai/app/shared/models.py                 |   2 +-
 tests/aa_nodes/test_nodes.py                  |   3 +-
 36 files changed, 552 insertions(+), 608 deletions(-)
 create mode 100644 invokeai/app/invocations/fields.py
 delete mode 100644 invokeai/app/shared/fields.py

diff --git a/invokeai/app/api/routers/images.py b/invokeai/app/api/routers/images.py
index 125896b8d3..cc60ad1be8 100644
--- a/invokeai/app/api/routers/images.py
+++ b/invokeai/app/api/routers/images.py
@@ -8,7 +8,7 @@ from fastapi.routing import APIRouter
 from PIL import Image
 from pydantic import BaseModel, Field, ValidationError
 
-from invokeai.app.invocations.baseinvocation import MetadataField, MetadataFieldValidator
+from invokeai.app.invocations.fields import MetadataField, MetadataFieldValidator
 from invokeai.app.services.image_records.image_records_common import ImageCategory, ImageRecordChanges, ResourceOrigin
 from invokeai.app.services.images.images_common import ImageDTO, ImageUrlsDTO
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
diff --git a/invokeai/app/api_app.py b/invokeai/app/api_app.py
index 6294083d0e..f48074de7c 100644
--- a/invokeai/app/api_app.py
+++ b/invokeai/app/api_app.py
@@ -6,6 +6,7 @@ import sys
 from invokeai.app.api.no_cache_staticfiles import NoCacheStaticFiles
 from invokeai.version.invokeai_version import __version__
 
+from .invocations.fields import InputFieldJSONSchemaExtra, OutputFieldJSONSchemaExtra
 from .services.config import InvokeAIAppConfig
 
 app_config = InvokeAIAppConfig.get_config()
@@ -57,8 +58,6 @@ if True:  # hack to make flake8 happy with imports coming after setting up the c
     from .api.sockets import SocketIO
     from .invocations.baseinvocation import (
         BaseInvocation,
-        InputFieldJSONSchemaExtra,
-        OutputFieldJSONSchemaExtra,
         UIConfigBase,
     )
 
diff --git a/invokeai/app/invocations/baseinvocation.py b/invokeai/app/invocations/baseinvocation.py
index d9e0c7ba0d..395d5e9870 100644
--- a/invokeai/app/invocations/baseinvocation.py
+++ b/invokeai/app/invocations/baseinvocation.py
@@ -12,10 +12,11 @@ from types import UnionType
 from typing import TYPE_CHECKING, Any, Callable, ClassVar, Iterable, Literal, Optional, Type, TypeVar, Union, cast
 
 import semver
-from pydantic import BaseModel, ConfigDict, Field, RootModel, TypeAdapter, create_model
-from pydantic.fields import FieldInfo, _Unset
+from pydantic import BaseModel, ConfigDict, Field, create_model
+from pydantic.fields import FieldInfo
 from pydantic_core import PydanticUndefined
 
+from invokeai.app.invocations.fields import FieldKind, Input
 from invokeai.app.services.config.config_default import InvokeAIAppConfig
 from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID
 from invokeai.app.shared.fields import FieldDescriptions
@@ -52,393 +53,6 @@ class Classification(str, Enum, metaclass=MetaEnum):
     Prototype = "prototype"
 
 
-class Input(str, Enum, metaclass=MetaEnum):
-    """
-    The type of input a field accepts.
-    - `Input.Direct`: The field must have its value provided directly, when the invocation and field \
-      are instantiated.
-    - `Input.Connection`: The field must have its value provided by a connection.
-    - `Input.Any`: The field may have its value provided either directly or by a connection.
-    """
-
-    Connection = "connection"
-    Direct = "direct"
-    Any = "any"
-
-
-class FieldKind(str, Enum, metaclass=MetaEnum):
-    """
-    The kind of field.
-    - `Input`: An input field on a node.
-    - `Output`: An output field on a node.
-    - `Internal`: A field which is treated as an input, but cannot be used in node definitions. Metadata is
-    one example. It is provided to nodes via the WithMetadata class, and we want to reserve the field name
-    "metadata" for this on all nodes. `FieldKind` is used to short-circuit the field name validation logic,
-    allowing "metadata" for that field.
-    - `NodeAttribute`: The field is a node attribute. These are fields which are not inputs or outputs,
-    but which are used to store information about the node. For example, the `id` and `type` fields are node
-    attributes.
-
-    The presence of this in `json_schema_extra["field_kind"]` is used when initializing node schemas on app
-    startup, and when generating the OpenAPI schema for the workflow editor.
-    """
-
-    Input = "input"
-    Output = "output"
-    Internal = "internal"
-    NodeAttribute = "node_attribute"
-
-
-class UIType(str, Enum, metaclass=MetaEnum):
-    """
-    Type hints for the UI for situations in which the field type is not enough to infer the correct UI type.
-
-    - Model Fields
-    The most common node-author-facing use will be for model fields. Internally, there is no difference
-    between SD-1, SD-2 and SDXL model fields - they all use the class `MainModelField`. To ensure the
-    base-model-specific UI is rendered, use e.g. `ui_type=UIType.SDXLMainModelField` to indicate that
-    the field is an SDXL main model field.
-
-    - Any Field
-    We cannot infer the usage of `typing.Any` via schema parsing, so you *must* use `ui_type=UIType.Any` to
-    indicate that the field accepts any type. Use with caution. This cannot be used on outputs.
-
-    - Scheduler Field
-    Special handling in the UI is needed for this field, which otherwise would be parsed as a plain enum field.
-
-    - Internal Fields
-    Similar to the Any Field, the `collect` and `iterate` nodes make use of `typing.Any`. To facilitate
-    handling these types in the client, we use `UIType._Collection` and `UIType._CollectionItem`. These
-    should not be used by node authors.
-
-    - DEPRECATED Fields
-    These types are deprecated and should not be used by node authors. A warning will be logged if one is
-    used, and the type will be ignored. They are included here for backwards compatibility.
-    """
-
-    # region Model Field Types
-    SDXLMainModel = "SDXLMainModelField"
-    SDXLRefinerModel = "SDXLRefinerModelField"
-    ONNXModel = "ONNXModelField"
-    VaeModel = "VAEModelField"
-    LoRAModel = "LoRAModelField"
-    ControlNetModel = "ControlNetModelField"
-    IPAdapterModel = "IPAdapterModelField"
-    # endregion
-
-    # region Misc Field Types
-    Scheduler = "SchedulerField"
-    Any = "AnyField"
-    # endregion
-
-    # region Internal Field Types
-    _Collection = "CollectionField"
-    _CollectionItem = "CollectionItemField"
-    # endregion
-
-    # region DEPRECATED
-    Boolean = "DEPRECATED_Boolean"
-    Color = "DEPRECATED_Color"
-    Conditioning = "DEPRECATED_Conditioning"
-    Control = "DEPRECATED_Control"
-    Float = "DEPRECATED_Float"
-    Image = "DEPRECATED_Image"
-    Integer = "DEPRECATED_Integer"
-    Latents = "DEPRECATED_Latents"
-    String = "DEPRECATED_String"
-    BooleanCollection = "DEPRECATED_BooleanCollection"
-    ColorCollection = "DEPRECATED_ColorCollection"
-    ConditioningCollection = "DEPRECATED_ConditioningCollection"
-    ControlCollection = "DEPRECATED_ControlCollection"
-    FloatCollection = "DEPRECATED_FloatCollection"
-    ImageCollection = "DEPRECATED_ImageCollection"
-    IntegerCollection = "DEPRECATED_IntegerCollection"
-    LatentsCollection = "DEPRECATED_LatentsCollection"
-    StringCollection = "DEPRECATED_StringCollection"
-    BooleanPolymorphic = "DEPRECATED_BooleanPolymorphic"
-    ColorPolymorphic = "DEPRECATED_ColorPolymorphic"
-    ConditioningPolymorphic = "DEPRECATED_ConditioningPolymorphic"
-    ControlPolymorphic = "DEPRECATED_ControlPolymorphic"
-    FloatPolymorphic = "DEPRECATED_FloatPolymorphic"
-    ImagePolymorphic = "DEPRECATED_ImagePolymorphic"
-    IntegerPolymorphic = "DEPRECATED_IntegerPolymorphic"
-    LatentsPolymorphic = "DEPRECATED_LatentsPolymorphic"
-    StringPolymorphic = "DEPRECATED_StringPolymorphic"
-    MainModel = "DEPRECATED_MainModel"
-    UNet = "DEPRECATED_UNet"
-    Vae = "DEPRECATED_Vae"
-    CLIP = "DEPRECATED_CLIP"
-    Collection = "DEPRECATED_Collection"
-    CollectionItem = "DEPRECATED_CollectionItem"
-    Enum = "DEPRECATED_Enum"
-    WorkflowField = "DEPRECATED_WorkflowField"
-    IsIntermediate = "DEPRECATED_IsIntermediate"
-    BoardField = "DEPRECATED_BoardField"
-    MetadataItem = "DEPRECATED_MetadataItem"
-    MetadataItemCollection = "DEPRECATED_MetadataItemCollection"
-    MetadataItemPolymorphic = "DEPRECATED_MetadataItemPolymorphic"
-    MetadataDict = "DEPRECATED_MetadataDict"
-    # endregion
-
-
-class UIComponent(str, Enum, metaclass=MetaEnum):
-    """
-    The type of UI component to use for a field, used to override the default components, which are
-    inferred from the field type.
-    """
-
-    None_ = "none"
-    Textarea = "textarea"
-    Slider = "slider"
-
-
-class InputFieldJSONSchemaExtra(BaseModel):
-    """
-    Extra attributes to be added to input fields and their OpenAPI schema. Used during graph execution,
-    and by the workflow editor during schema parsing and UI rendering.
-    """
-
-    input: Input
-    orig_required: bool
-    field_kind: FieldKind
-    default: Optional[Any] = None
-    orig_default: Optional[Any] = None
-    ui_hidden: bool = False
-    ui_type: Optional[UIType] = None
-    ui_component: Optional[UIComponent] = None
-    ui_order: Optional[int] = None
-    ui_choice_labels: Optional[dict[str, str]] = None
-
-    model_config = ConfigDict(
-        validate_assignment=True,
-        json_schema_serialization_defaults_required=True,
-    )
-
-
-class OutputFieldJSONSchemaExtra(BaseModel):
-    """
-    Extra attributes to be added to input fields and their OpenAPI schema. Used by the workflow editor
-    during schema parsing and UI rendering.
-    """
-
-    field_kind: FieldKind
-    ui_hidden: bool
-    ui_type: Optional[UIType]
-    ui_order: Optional[int]
-
-    model_config = ConfigDict(
-        validate_assignment=True,
-        json_schema_serialization_defaults_required=True,
-    )
-
-
-def InputField(
-    # copied from pydantic's Field
-    # TODO: Can we support default_factory?
-    default: Any = _Unset,
-    default_factory: Callable[[], Any] | None = _Unset,
-    title: str | None = _Unset,
-    description: str | None = _Unset,
-    pattern: str | None = _Unset,
-    strict: bool | None = _Unset,
-    gt: float | None = _Unset,
-    ge: float | None = _Unset,
-    lt: float | None = _Unset,
-    le: float | None = _Unset,
-    multiple_of: float | None = _Unset,
-    allow_inf_nan: bool | None = _Unset,
-    max_digits: int | None = _Unset,
-    decimal_places: int | None = _Unset,
-    min_length: int | None = _Unset,
-    max_length: int | None = _Unset,
-    # custom
-    input: Input = Input.Any,
-    ui_type: Optional[UIType] = None,
-    ui_component: Optional[UIComponent] = None,
-    ui_hidden: bool = False,
-    ui_order: Optional[int] = None,
-    ui_choice_labels: Optional[dict[str, str]] = None,
-) -> Any:
-    """
-    Creates an input field for an invocation.
-
-    This is a wrapper for Pydantic's [Field](https://docs.pydantic.dev/latest/api/fields/#pydantic.fields.Field) \
-    that adds a few extra parameters to support graph execution and the node editor UI.
-
-    :param Input input: [Input.Any] The kind of input this field requires. \
-      `Input.Direct` means a value must be provided on instantiation. \
-      `Input.Connection` means the value must be provided by a connection. \
-      `Input.Any` means either will do.
-
-    :param UIType ui_type: [None] Optionally provides an extra type hint for the UI. \
-      In some situations, the field's type is not enough to infer the correct UI type. \
-      For example, model selection fields should render a dropdown UI component to select a model. \
-      Internally, there is no difference between SD-1, SD-2 and SDXL model fields, they all use \
-      `MainModelField`. So to ensure the base-model-specific UI is rendered, you can use \
-      `UIType.SDXLMainModelField` to indicate that the field is an SDXL main model field.
-
-    :param UIComponent ui_component: [None] Optionally specifies a specific component to use in the UI. \
-      The UI will always render a suitable component, but sometimes you want something different than the default. \
-      For example, a `string` field will default to a single-line input, but you may want a multi-line textarea instead. \
-      For this case, you could provide `UIComponent.Textarea`.
-
-    :param bool ui_hidden: [False] Specifies whether or not this field should be hidden in the UI.
-
-    :param int ui_order: [None] Specifies the order in which this field should be rendered in the UI.
-
-    :param dict[str, str] ui_choice_labels: [None] Specifies the labels to use for the choices in an enum field.
-    """
-
-    json_schema_extra_ = InputFieldJSONSchemaExtra(
-        input=input,
-        ui_type=ui_type,
-        ui_component=ui_component,
-        ui_hidden=ui_hidden,
-        ui_order=ui_order,
-        ui_choice_labels=ui_choice_labels,
-        field_kind=FieldKind.Input,
-        orig_required=True,
-    )
-
-    """
-    There is a conflict between the typing of invocation definitions and the typing of an invocation's
-    `invoke()` function.
-
-    On instantiation of a node, the invocation definition is used to create the python class. At this time,
-    any number of fields may be optional, because they may be provided by connections.
-
-    On calling of `invoke()`, however, those fields may be required.
-
-    For example, consider an ResizeImageInvocation with an `image: ImageField` field.
-
-    `image` is required during the call to `invoke()`, but when the python class is instantiated,
-    the field may not be present. This is fine, because that image field will be provided by a
-    connection from an ancestor node, which outputs an image.
-
-    This means we want to type the `image` field as optional for the node class definition, but required
-    for the `invoke()` function.
-
-    If we use `typing.Optional` in the node class definition, the field will be typed as optional in the
-    `invoke()` method, and we'll have to do a lot of runtime checks to ensure the field is present - or
-    any static type analysis tools will complain.
-
-    To get around this, in node class definitions, we type all fields correctly for the `invoke()` function,
-    but secretly make them optional in `InputField()`. We also store the original required bool and/or default
-    value. When we call `invoke()`, we use this stored information to do an additional check on the class.
-    """
-
-    if default_factory is not _Unset and default_factory is not None:
-        default = default_factory()
-        logger.warn('"default_factory" is not supported, calling it now to set "default"')
-
-    # These are the args we may wish pass to the pydantic `Field()` function
-    field_args = {
-        "default": default,
-        "title": title,
-        "description": description,
-        "pattern": pattern,
-        "strict": strict,
-        "gt": gt,
-        "ge": ge,
-        "lt": lt,
-        "le": le,
-        "multiple_of": multiple_of,
-        "allow_inf_nan": allow_inf_nan,
-        "max_digits": max_digits,
-        "decimal_places": decimal_places,
-        "min_length": min_length,
-        "max_length": max_length,
-    }
-
-    # We only want to pass the args that were provided, otherwise the `Field()`` function won't work as expected
-    provided_args = {k: v for (k, v) in field_args.items() if v is not PydanticUndefined}
-
-    # Because we are manually making fields optional, we need to store the original required bool for reference later
-    json_schema_extra_.orig_required = default is PydanticUndefined
-
-    # Make Input.Any and Input.Connection fields optional, providing None as a default if the field doesn't already have one
-    if input is Input.Any or input is Input.Connection:
-        default_ = None if default is PydanticUndefined else default
-        provided_args.update({"default": default_})
-        if default is not PydanticUndefined:
-            # Before invoking, we'll check for the original default value and set it on the field if the field has no value
-            json_schema_extra_.default = default
-            json_schema_extra_.orig_default = default
-    elif default is not PydanticUndefined:
-        default_ = default
-        provided_args.update({"default": default_})
-        json_schema_extra_.orig_default = default_
-
-    return Field(
-        **provided_args,
-        json_schema_extra=json_schema_extra_.model_dump(exclude_none=True),
-    )
-
-
-def OutputField(
-    # copied from pydantic's Field
-    default: Any = _Unset,
-    title: str | None = _Unset,
-    description: str | None = _Unset,
-    pattern: str | None = _Unset,
-    strict: bool | None = _Unset,
-    gt: float | None = _Unset,
-    ge: float | None = _Unset,
-    lt: float | None = _Unset,
-    le: float | None = _Unset,
-    multiple_of: float | None = _Unset,
-    allow_inf_nan: bool | None = _Unset,
-    max_digits: int | None = _Unset,
-    decimal_places: int | None = _Unset,
-    min_length: int | None = _Unset,
-    max_length: int | None = _Unset,
-    # custom
-    ui_type: Optional[UIType] = None,
-    ui_hidden: bool = False,
-    ui_order: Optional[int] = None,
-) -> Any:
-    """
-    Creates an output field for an invocation output.
-
-    This is a wrapper for Pydantic's [Field](https://docs.pydantic.dev/1.10/usage/schema/#field-customization) \
-    that adds a few extra parameters to support graph execution and the node editor UI.
-
-    :param UIType ui_type: [None] Optionally provides an extra type hint for the UI. \
-      In some situations, the field's type is not enough to infer the correct UI type. \
-      For example, model selection fields should render a dropdown UI component to select a model. \
-      Internally, there is no difference between SD-1, SD-2 and SDXL model fields, they all use \
-      `MainModelField`. So to ensure the base-model-specific UI is rendered, you can use \
-      `UIType.SDXLMainModelField` to indicate that the field is an SDXL main model field.
-
-    :param bool ui_hidden: [False] Specifies whether or not this field should be hidden in the UI. \
-
-    :param int ui_order: [None] Specifies the order in which this field should be rendered in the UI. \
-    """
-    return Field(
-        default=default,
-        title=title,
-        description=description,
-        pattern=pattern,
-        strict=strict,
-        gt=gt,
-        ge=ge,
-        lt=lt,
-        le=le,
-        multiple_of=multiple_of,
-        allow_inf_nan=allow_inf_nan,
-        max_digits=max_digits,
-        decimal_places=decimal_places,
-        min_length=min_length,
-        max_length=max_length,
-        json_schema_extra=OutputFieldJSONSchemaExtra(
-            ui_type=ui_type,
-            ui_hidden=ui_hidden,
-            ui_order=ui_order,
-            field_kind=FieldKind.Output,
-        ).model_dump(exclude_none=True),
-    )
-
-
 class UIConfigBase(BaseModel):
     """
     Provides additional node configuration to the UI.
@@ -460,33 +74,6 @@ class UIConfigBase(BaseModel):
     )
 
 
-class InvocationContext:
-    """Initialized and provided to on execution of invocations."""
-
-    services: InvocationServices
-    graph_execution_state_id: str
-    queue_id: str
-    queue_item_id: int
-    queue_batch_id: str
-    workflow: Optional[WorkflowWithoutID]
-
-    def __init__(
-        self,
-        services: InvocationServices,
-        queue_id: str,
-        queue_item_id: int,
-        queue_batch_id: str,
-        graph_execution_state_id: str,
-        workflow: Optional[WorkflowWithoutID],
-    ):
-        self.services = services
-        self.graph_execution_state_id = graph_execution_state_id
-        self.queue_id = queue_id
-        self.queue_item_id = queue_item_id
-        self.queue_batch_id = queue_batch_id
-        self.workflow = workflow
-
-
 class BaseInvocationOutput(BaseModel):
     """
     Base class for all invocation outputs.
@@ -926,37 +513,3 @@ def invocation_output(
         return cls
 
     return wrapper
-
-
-class MetadataField(RootModel):
-    """
-    Pydantic model for metadata with custom root of type dict[str, Any].
-    Metadata is stored without a strict schema.
-    """
-
-    root: dict[str, Any] = Field(description="The metadata")
-
-
-MetadataFieldValidator = TypeAdapter(MetadataField)
-
-
-class WithMetadata(BaseModel):
-    metadata: Optional[MetadataField] = Field(
-        default=None,
-        description=FieldDescriptions.metadata,
-        json_schema_extra=InputFieldJSONSchemaExtra(
-            field_kind=FieldKind.Internal,
-            input=Input.Connection,
-            orig_required=False,
-        ).model_dump(exclude_none=True),
-    )
-
-
-class WithWorkflow:
-    workflow = None
-
-    def __init_subclass__(cls) -> None:
-        logger.warn(
-            f"{cls.__module__.split('.')[0]}.{cls.__name__}: WithWorkflow is deprecated. Use `context.workflow` to access the workflow."
-        )
-        super().__init_subclass__()
diff --git a/invokeai/app/invocations/collections.py b/invokeai/app/invocations/collections.py
index 4c7b6f94cd..d35a9d79c7 100644
--- a/invokeai/app/invocations/collections.py
+++ b/invokeai/app/invocations/collections.py
@@ -7,7 +7,8 @@ from pydantic import ValidationInfo, field_validator
 from invokeai.app.invocations.primitives import IntegerCollectionOutput
 from invokeai.app.util.misc import SEED_MAX
 
-from .baseinvocation import BaseInvocation, InputField, InvocationContext, invocation
+from .baseinvocation import BaseInvocation, InvocationContext, invocation
+from .fields import InputField
 
 
 @invocation(
diff --git a/invokeai/app/invocations/compel.py b/invokeai/app/invocations/compel.py
index 49c62cff56..b386aef2cb 100644
--- a/invokeai/app/invocations/compel.py
+++ b/invokeai/app/invocations/compel.py
@@ -5,8 +5,8 @@ import torch
 from compel import Compel, ReturnedEmbeddingsType
 from compel.prompt_parser import Blend, Conjunction, CrossAttentionControlSubstitute, FlattenedPrompt, Fragment
 
+from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField, UIComponent
 from invokeai.app.invocations.primitives import ConditioningField, ConditioningOutput
-from invokeai.app.shared.fields import FieldDescriptions
 from invokeai.backend.stable_diffusion.diffusion.conditioning_data import (
     BasicConditioningInfo,
     ExtraConditioningInfo,
@@ -20,11 +20,7 @@ from ..util.ti_utils import extract_ti_triggers_from_prompt
 from .baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
-    Input,
-    InputField,
     InvocationContext,
-    OutputField,
-    UIComponent,
     invocation,
     invocation_output,
 )
diff --git a/invokeai/app/invocations/controlnet_image_processors.py b/invokeai/app/invocations/controlnet_image_processors.py
index 1f9342985a..9b652b8eee 100644
--- a/invokeai/app/invocations/controlnet_image_processors.py
+++ b/invokeai/app/invocations/controlnet_image_processors.py
@@ -25,10 +25,10 @@ from controlnet_aux.util import HWC3, ade_palette
 from PIL import Image
 from pydantic import BaseModel, ConfigDict, Field, field_validator, model_validator
 
+from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField, WithMetadata
 from invokeai.app.invocations.primitives import ImageField, ImageOutput
 from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
 from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
-from invokeai.app.shared.fields import FieldDescriptions
 from invokeai.backend.image_util.depth_anything import DepthAnythingDetector
 from invokeai.backend.image_util.dw_openpose import DWOpenposeDetector
 
@@ -36,11 +36,7 @@ from ...backend.model_management import BaseModelType
 from .baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
-    Input,
-    InputField,
     InvocationContext,
-    OutputField,
-    WithMetadata,
     invocation,
     invocation_output,
 )
diff --git a/invokeai/app/invocations/cv.py b/invokeai/app/invocations/cv.py
index cb6828d21a..5865338e19 100644
--- a/invokeai/app/invocations/cv.py
+++ b/invokeai/app/invocations/cv.py
@@ -8,7 +8,8 @@ from PIL import Image, ImageOps
 from invokeai.app.invocations.primitives import ImageField, ImageOutput
 from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
 
-from .baseinvocation import BaseInvocation, InputField, InvocationContext, WithMetadata, invocation
+from .baseinvocation import BaseInvocation, InvocationContext, invocation
+from .fields import InputField, WithMetadata
 
 
 @invocation("cv_inpaint", title="OpenCV Inpaint", tags=["opencv", "inpaint"], category="inpaint", version="1.2.0")
diff --git a/invokeai/app/invocations/facetools.py b/invokeai/app/invocations/facetools.py
index e0c89b4de5..13f1066ec3 100644
--- a/invokeai/app/invocations/facetools.py
+++ b/invokeai/app/invocations/facetools.py
@@ -13,13 +13,11 @@ from pydantic import field_validator
 import invokeai.assets.fonts as font_assets
 from invokeai.app.invocations.baseinvocation import (
     BaseInvocation,
-    InputField,
     InvocationContext,
-    OutputField,
-    WithMetadata,
     invocation,
     invocation_output,
 )
+from invokeai.app.invocations.fields import InputField, OutputField, WithMetadata
 from invokeai.app.invocations.primitives import ImageField, ImageOutput
 from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
 
diff --git a/invokeai/app/invocations/fields.py b/invokeai/app/invocations/fields.py
new file mode 100644
index 0000000000..0cce8e3c6b
--- /dev/null
+++ b/invokeai/app/invocations/fields.py
@@ -0,0 +1,501 @@
+from enum import Enum
+from typing import Any, Callable, Optional
+
+from pydantic import BaseModel, ConfigDict, Field, RootModel, TypeAdapter
+from pydantic.fields import _Unset
+from pydantic_core import PydanticUndefined
+
+from invokeai.app.util.metaenum import MetaEnum
+from invokeai.backend.util.logging import InvokeAILogger
+
+logger = InvokeAILogger.get_logger()
+
+
+class UIType(str, Enum, metaclass=MetaEnum):
+    """
+    Type hints for the UI for situations in which the field type is not enough to infer the correct UI type.
+
+    - Model Fields
+    The most common node-author-facing use will be for model fields. Internally, there is no difference
+    between SD-1, SD-2 and SDXL model fields - they all use the class `MainModelField`. To ensure the
+    base-model-specific UI is rendered, use e.g. `ui_type=UIType.SDXLMainModelField` to indicate that
+    the field is an SDXL main model field.
+
+    - Any Field
+    We cannot infer the usage of `typing.Any` via schema parsing, so you *must* use `ui_type=UIType.Any` to
+    indicate that the field accepts any type. Use with caution. This cannot be used on outputs.
+
+    - Scheduler Field
+    Special handling in the UI is needed for this field, which otherwise would be parsed as a plain enum field.
+
+    - Internal Fields
+    Similar to the Any Field, the `collect` and `iterate` nodes make use of `typing.Any`. To facilitate
+    handling these types in the client, we use `UIType._Collection` and `UIType._CollectionItem`. These
+    should not be used by node authors.
+
+    - DEPRECATED Fields
+    These types are deprecated and should not be used by node authors. A warning will be logged if one is
+    used, and the type will be ignored. They are included here for backwards compatibility.
+    """
+
+    # region Model Field Types
+    SDXLMainModel = "SDXLMainModelField"
+    SDXLRefinerModel = "SDXLRefinerModelField"
+    ONNXModel = "ONNXModelField"
+    VaeModel = "VAEModelField"
+    LoRAModel = "LoRAModelField"
+    ControlNetModel = "ControlNetModelField"
+    IPAdapterModel = "IPAdapterModelField"
+    # endregion
+
+    # region Misc Field Types
+    Scheduler = "SchedulerField"
+    Any = "AnyField"
+    # endregion
+
+    # region Internal Field Types
+    _Collection = "CollectionField"
+    _CollectionItem = "CollectionItemField"
+    # endregion
+
+    # region DEPRECATED
+    Boolean = "DEPRECATED_Boolean"
+    Color = "DEPRECATED_Color"
+    Conditioning = "DEPRECATED_Conditioning"
+    Control = "DEPRECATED_Control"
+    Float = "DEPRECATED_Float"
+    Image = "DEPRECATED_Image"
+    Integer = "DEPRECATED_Integer"
+    Latents = "DEPRECATED_Latents"
+    String = "DEPRECATED_String"
+    BooleanCollection = "DEPRECATED_BooleanCollection"
+    ColorCollection = "DEPRECATED_ColorCollection"
+    ConditioningCollection = "DEPRECATED_ConditioningCollection"
+    ControlCollection = "DEPRECATED_ControlCollection"
+    FloatCollection = "DEPRECATED_FloatCollection"
+    ImageCollection = "DEPRECATED_ImageCollection"
+    IntegerCollection = "DEPRECATED_IntegerCollection"
+    LatentsCollection = "DEPRECATED_LatentsCollection"
+    StringCollection = "DEPRECATED_StringCollection"
+    BooleanPolymorphic = "DEPRECATED_BooleanPolymorphic"
+    ColorPolymorphic = "DEPRECATED_ColorPolymorphic"
+    ConditioningPolymorphic = "DEPRECATED_ConditioningPolymorphic"
+    ControlPolymorphic = "DEPRECATED_ControlPolymorphic"
+    FloatPolymorphic = "DEPRECATED_FloatPolymorphic"
+    ImagePolymorphic = "DEPRECATED_ImagePolymorphic"
+    IntegerPolymorphic = "DEPRECATED_IntegerPolymorphic"
+    LatentsPolymorphic = "DEPRECATED_LatentsPolymorphic"
+    StringPolymorphic = "DEPRECATED_StringPolymorphic"
+    MainModel = "DEPRECATED_MainModel"
+    UNet = "DEPRECATED_UNet"
+    Vae = "DEPRECATED_Vae"
+    CLIP = "DEPRECATED_CLIP"
+    Collection = "DEPRECATED_Collection"
+    CollectionItem = "DEPRECATED_CollectionItem"
+    Enum = "DEPRECATED_Enum"
+    WorkflowField = "DEPRECATED_WorkflowField"
+    IsIntermediate = "DEPRECATED_IsIntermediate"
+    BoardField = "DEPRECATED_BoardField"
+    MetadataItem = "DEPRECATED_MetadataItem"
+    MetadataItemCollection = "DEPRECATED_MetadataItemCollection"
+    MetadataItemPolymorphic = "DEPRECATED_MetadataItemPolymorphic"
+    MetadataDict = "DEPRECATED_MetadataDict"
+
+
+class UIComponent(str, Enum, metaclass=MetaEnum):
+    """
+    The type of UI component to use for a field, used to override the default components, which are
+    inferred from the field type.
+    """
+
+    None_ = "none"
+    Textarea = "textarea"
+    Slider = "slider"
+
+
+class FieldDescriptions:
+    denoising_start = "When to start denoising, expressed a percentage of total steps"
+    denoising_end = "When to stop denoising, expressed a percentage of total steps"
+    cfg_scale = "Classifier-Free Guidance scale"
+    cfg_rescale_multiplier = "Rescale multiplier for CFG guidance, used for models trained with zero-terminal SNR"
+    scheduler = "Scheduler to use during inference"
+    positive_cond = "Positive conditioning tensor"
+    negative_cond = "Negative conditioning tensor"
+    noise = "Noise tensor"
+    clip = "CLIP (tokenizer, text encoder, LoRAs) and skipped layer count"
+    unet = "UNet (scheduler, LoRAs)"
+    vae = "VAE"
+    cond = "Conditioning tensor"
+    controlnet_model = "ControlNet model to load"
+    vae_model = "VAE model to load"
+    lora_model = "LoRA model to load"
+    main_model = "Main model (UNet, VAE, CLIP) to load"
+    sdxl_main_model = "SDXL Main model (UNet, VAE, CLIP1, CLIP2) to load"
+    sdxl_refiner_model = "SDXL Refiner Main Modde (UNet, VAE, CLIP2) to load"
+    onnx_main_model = "ONNX Main model (UNet, VAE, CLIP) to load"
+    lora_weight = "The weight at which the LoRA is applied to each model"
+    compel_prompt = "Prompt to be parsed by Compel to create a conditioning tensor"
+    raw_prompt = "Raw prompt text (no parsing)"
+    sdxl_aesthetic = "The aesthetic score to apply to the conditioning tensor"
+    skipped_layers = "Number of layers to skip in text encoder"
+    seed = "Seed for random number generation"
+    steps = "Number of steps to run"
+    width = "Width of output (px)"
+    height = "Height of output (px)"
+    control = "ControlNet(s) to apply"
+    ip_adapter = "IP-Adapter to apply"
+    t2i_adapter = "T2I-Adapter(s) to apply"
+    denoised_latents = "Denoised latents tensor"
+    latents = "Latents tensor"
+    strength = "Strength of denoising (proportional to steps)"
+    metadata = "Optional metadata to be saved with the image"
+    metadata_collection = "Collection of Metadata"
+    metadata_item_polymorphic = "A single metadata item or collection of metadata items"
+    metadata_item_label = "Label for this metadata item"
+    metadata_item_value = "The value for this metadata item (may be any type)"
+    workflow = "Optional workflow to be saved with the image"
+    interp_mode = "Interpolation mode"
+    torch_antialias = "Whether or not to apply antialiasing (bilinear or bicubic only)"
+    fp32 = "Whether or not to use full float32 precision"
+    precision = "Precision to use"
+    tiled = "Processing using overlapping tiles (reduce memory consumption)"
+    detect_res = "Pixel resolution for detection"
+    image_res = "Pixel resolution for output image"
+    safe_mode = "Whether or not to use safe mode"
+    scribble_mode = "Whether or not to use scribble mode"
+    scale_factor = "The factor by which to scale"
+    blend_alpha = (
+        "Blending factor. 0.0 = use input A only, 1.0 = use input B only, 0.5 = 50% mix of input A and input B."
+    )
+    num_1 = "The first number"
+    num_2 = "The second number"
+    mask = "The mask to use for the operation"
+    board = "The board to save the image to"
+    image = "The image to process"
+    tile_size = "Tile size"
+    inclusive_low = "The inclusive low value"
+    exclusive_high = "The exclusive high value"
+    decimal_places = "The number of decimal places to round to"
+    freeu_s1 = 'Scaling factor for stage 1 to attenuate the contributions of the skip features. This is done to mitigate the "oversmoothing effect" in the enhanced denoising process.'
+    freeu_s2 = 'Scaling factor for stage 2 to attenuate the contributions of the skip features. This is done to mitigate the "oversmoothing effect" in the enhanced denoising process.'
+    freeu_b1 = "Scaling factor for stage 1 to amplify the contributions of backbone features."
+    freeu_b2 = "Scaling factor for stage 2 to amplify the contributions of backbone features."
+
+
+class MetadataField(RootModel):
+    """
+    Pydantic model for metadata with custom root of type dict[str, Any].
+    Metadata is stored without a strict schema.
+    """
+
+    root: dict[str, Any] = Field(description="The metadata")
+
+
+MetadataFieldValidator = TypeAdapter(MetadataField)
+
+
+class Input(str, Enum, metaclass=MetaEnum):
+    """
+    The type of input a field accepts.
+    - `Input.Direct`: The field must have its value provided directly, when the invocation and field \
+      are instantiated.
+    - `Input.Connection`: The field must have its value provided by a connection.
+    - `Input.Any`: The field may have its value provided either directly or by a connection.
+    """
+
+    Connection = "connection"
+    Direct = "direct"
+    Any = "any"
+
+
+class FieldKind(str, Enum, metaclass=MetaEnum):
+    """
+    The kind of field.
+    - `Input`: An input field on a node.
+    - `Output`: An output field on a node.
+    - `Internal`: A field which is treated as an input, but cannot be used in node definitions. Metadata is
+    one example. It is provided to nodes via the WithMetadata class, and we want to reserve the field name
+    "metadata" for this on all nodes. `FieldKind` is used to short-circuit the field name validation logic,
+    allowing "metadata" for that field.
+    - `NodeAttribute`: The field is a node attribute. These are fields which are not inputs or outputs,
+    but which are used to store information about the node. For example, the `id` and `type` fields are node
+    attributes.
+
+    The presence of this in `json_schema_extra["field_kind"]` is used when initializing node schemas on app
+    startup, and when generating the OpenAPI schema for the workflow editor.
+    """
+
+    Input = "input"
+    Output = "output"
+    Internal = "internal"
+    NodeAttribute = "node_attribute"
+
+
+class InputFieldJSONSchemaExtra(BaseModel):
+    """
+    Extra attributes to be added to input fields and their OpenAPI schema. Used during graph execution,
+    and by the workflow editor during schema parsing and UI rendering.
+    """
+
+    input: Input
+    orig_required: bool
+    field_kind: FieldKind
+    default: Optional[Any] = None
+    orig_default: Optional[Any] = None
+    ui_hidden: bool = False
+    ui_type: Optional[UIType] = None
+    ui_component: Optional[UIComponent] = None
+    ui_order: Optional[int] = None
+    ui_choice_labels: Optional[dict[str, str]] = None
+
+    model_config = ConfigDict(
+        validate_assignment=True,
+        json_schema_serialization_defaults_required=True,
+    )
+
+
+class WithMetadata(BaseModel):
+    metadata: Optional[MetadataField] = Field(
+        default=None,
+        description=FieldDescriptions.metadata,
+        json_schema_extra=InputFieldJSONSchemaExtra(
+            field_kind=FieldKind.Internal,
+            input=Input.Connection,
+            orig_required=False,
+        ).model_dump(exclude_none=True),
+    )
+
+
+class WithWorkflow:
+    workflow = None
+
+    def __init_subclass__(cls) -> None:
+        logger.warn(
+            f"{cls.__module__.split('.')[0]}.{cls.__name__}: WithWorkflow is deprecated. Use `context.workflow` to access the workflow."
+        )
+        super().__init_subclass__()
+
+
+class OutputFieldJSONSchemaExtra(BaseModel):
+    """
+    Extra attributes to be added to input fields and their OpenAPI schema. Used by the workflow editor
+    during schema parsing and UI rendering.
+    """
+
+    field_kind: FieldKind
+    ui_hidden: bool
+    ui_type: Optional[UIType]
+    ui_order: Optional[int]
+
+    model_config = ConfigDict(
+        validate_assignment=True,
+        json_schema_serialization_defaults_required=True,
+    )
+
+
+def InputField(
+    # copied from pydantic's Field
+    # TODO: Can we support default_factory?
+    default: Any = _Unset,
+    default_factory: Callable[[], Any] | None = _Unset,
+    title: str | None = _Unset,
+    description: str | None = _Unset,
+    pattern: str | None = _Unset,
+    strict: bool | None = _Unset,
+    gt: float | None = _Unset,
+    ge: float | None = _Unset,
+    lt: float | None = _Unset,
+    le: float | None = _Unset,
+    multiple_of: float | None = _Unset,
+    allow_inf_nan: bool | None = _Unset,
+    max_digits: int | None = _Unset,
+    decimal_places: int | None = _Unset,
+    min_length: int | None = _Unset,
+    max_length: int | None = _Unset,
+    # custom
+    input: Input = Input.Any,
+    ui_type: Optional[UIType] = None,
+    ui_component: Optional[UIComponent] = None,
+    ui_hidden: bool = False,
+    ui_order: Optional[int] = None,
+    ui_choice_labels: Optional[dict[str, str]] = None,
+) -> Any:
+    """
+    Creates an input field for an invocation.
+
+    This is a wrapper for Pydantic's [Field](https://docs.pydantic.dev/latest/api/fields/#pydantic.fields.Field) \
+    that adds a few extra parameters to support graph execution and the node editor UI.
+
+    :param Input input: [Input.Any] The kind of input this field requires. \
+      `Input.Direct` means a value must be provided on instantiation. \
+      `Input.Connection` means the value must be provided by a connection. \
+      `Input.Any` means either will do.
+
+    :param UIType ui_type: [None] Optionally provides an extra type hint for the UI. \
+      In some situations, the field's type is not enough to infer the correct UI type. \
+      For example, model selection fields should render a dropdown UI component to select a model. \
+      Internally, there is no difference between SD-1, SD-2 and SDXL model fields, they all use \
+      `MainModelField`. So to ensure the base-model-specific UI is rendered, you can use \
+      `UIType.SDXLMainModelField` to indicate that the field is an SDXL main model field.
+
+    :param UIComponent ui_component: [None] Optionally specifies a specific component to use in the UI. \
+      The UI will always render a suitable component, but sometimes you want something different than the default. \
+      For example, a `string` field will default to a single-line input, but you may want a multi-line textarea instead. \
+      For this case, you could provide `UIComponent.Textarea`.
+
+    :param bool ui_hidden: [False] Specifies whether or not this field should be hidden in the UI.
+
+    :param int ui_order: [None] Specifies the order in which this field should be rendered in the UI.
+
+    :param dict[str, str] ui_choice_labels: [None] Specifies the labels to use for the choices in an enum field.
+    """
+
+    json_schema_extra_ = InputFieldJSONSchemaExtra(
+        input=input,
+        ui_type=ui_type,
+        ui_component=ui_component,
+        ui_hidden=ui_hidden,
+        ui_order=ui_order,
+        ui_choice_labels=ui_choice_labels,
+        field_kind=FieldKind.Input,
+        orig_required=True,
+    )
+
+    """
+    There is a conflict between the typing of invocation definitions and the typing of an invocation's
+    `invoke()` function.
+
+    On instantiation of a node, the invocation definition is used to create the python class. At this time,
+    any number of fields may be optional, because they may be provided by connections.
+
+    On calling of `invoke()`, however, those fields may be required.
+
+    For example, consider an ResizeImageInvocation with an `image: ImageField` field.
+
+    `image` is required during the call to `invoke()`, but when the python class is instantiated,
+    the field may not be present. This is fine, because that image field will be provided by a
+    connection from an ancestor node, which outputs an image.
+
+    This means we want to type the `image` field as optional for the node class definition, but required
+    for the `invoke()` function.
+
+    If we use `typing.Optional` in the node class definition, the field will be typed as optional in the
+    `invoke()` method, and we'll have to do a lot of runtime checks to ensure the field is present - or
+    any static type analysis tools will complain.
+
+    To get around this, in node class definitions, we type all fields correctly for the `invoke()` function,
+    but secretly make them optional in `InputField()`. We also store the original required bool and/or default
+    value. When we call `invoke()`, we use this stored information to do an additional check on the class.
+    """
+
+    if default_factory is not _Unset and default_factory is not None:
+        default = default_factory()
+        logger.warn('"default_factory" is not supported, calling it now to set "default"')
+
+    # These are the args we may wish pass to the pydantic `Field()` function
+    field_args = {
+        "default": default,
+        "title": title,
+        "description": description,
+        "pattern": pattern,
+        "strict": strict,
+        "gt": gt,
+        "ge": ge,
+        "lt": lt,
+        "le": le,
+        "multiple_of": multiple_of,
+        "allow_inf_nan": allow_inf_nan,
+        "max_digits": max_digits,
+        "decimal_places": decimal_places,
+        "min_length": min_length,
+        "max_length": max_length,
+    }
+
+    # We only want to pass the args that were provided, otherwise the `Field()`` function won't work as expected
+    provided_args = {k: v for (k, v) in field_args.items() if v is not PydanticUndefined}
+
+    # Because we are manually making fields optional, we need to store the original required bool for reference later
+    json_schema_extra_.orig_required = default is PydanticUndefined
+
+    # Make Input.Any and Input.Connection fields optional, providing None as a default if the field doesn't already have one
+    if input is Input.Any or input is Input.Connection:
+        default_ = None if default is PydanticUndefined else default
+        provided_args.update({"default": default_})
+        if default is not PydanticUndefined:
+            # Before invoking, we'll check for the original default value and set it on the field if the field has no value
+            json_schema_extra_.default = default
+            json_schema_extra_.orig_default = default
+    elif default is not PydanticUndefined:
+        default_ = default
+        provided_args.update({"default": default_})
+        json_schema_extra_.orig_default = default_
+
+    return Field(
+        **provided_args,
+        json_schema_extra=json_schema_extra_.model_dump(exclude_none=True),
+    )
+
+
+def OutputField(
+    # copied from pydantic's Field
+    default: Any = _Unset,
+    title: str | None = _Unset,
+    description: str | None = _Unset,
+    pattern: str | None = _Unset,
+    strict: bool | None = _Unset,
+    gt: float | None = _Unset,
+    ge: float | None = _Unset,
+    lt: float | None = _Unset,
+    le: float | None = _Unset,
+    multiple_of: float | None = _Unset,
+    allow_inf_nan: bool | None = _Unset,
+    max_digits: int | None = _Unset,
+    decimal_places: int | None = _Unset,
+    min_length: int | None = _Unset,
+    max_length: int | None = _Unset,
+    # custom
+    ui_type: Optional[UIType] = None,
+    ui_hidden: bool = False,
+    ui_order: Optional[int] = None,
+) -> Any:
+    """
+    Creates an output field for an invocation output.
+
+    This is a wrapper for Pydantic's [Field](https://docs.pydantic.dev/1.10/usage/schema/#field-customization) \
+    that adds a few extra parameters to support graph execution and the node editor UI.
+
+    :param UIType ui_type: [None] Optionally provides an extra type hint for the UI. \
+      In some situations, the field's type is not enough to infer the correct UI type. \
+      For example, model selection fields should render a dropdown UI component to select a model. \
+      Internally, there is no difference between SD-1, SD-2 and SDXL model fields, they all use \
+      `MainModelField`. So to ensure the base-model-specific UI is rendered, you can use \
+      `UIType.SDXLMainModelField` to indicate that the field is an SDXL main model field.
+
+    :param bool ui_hidden: [False] Specifies whether or not this field should be hidden in the UI. \
+
+    :param int ui_order: [None] Specifies the order in which this field should be rendered in the UI. \
+    """
+    return Field(
+        default=default,
+        title=title,
+        description=description,
+        pattern=pattern,
+        strict=strict,
+        gt=gt,
+        ge=ge,
+        lt=lt,
+        le=le,
+        multiple_of=multiple_of,
+        allow_inf_nan=allow_inf_nan,
+        max_digits=max_digits,
+        decimal_places=decimal_places,
+        min_length=min_length,
+        max_length=max_length,
+        json_schema_extra=OutputFieldJSONSchemaExtra(
+            ui_type=ui_type,
+            ui_hidden=ui_hidden,
+            ui_order=ui_order,
+            field_kind=FieldKind.Output,
+        ).model_dump(exclude_none=True),
+    )
+    # endregion
diff --git a/invokeai/app/invocations/image.py b/invokeai/app/invocations/image.py
index f729d60cdd..16d0f33dda 100644
--- a/invokeai/app/invocations/image.py
+++ b/invokeai/app/invocations/image.py
@@ -7,19 +7,16 @@ import cv2
 import numpy
 from PIL import Image, ImageChops, ImageFilter, ImageOps
 
+from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, WithMetadata
 from invokeai.app.invocations.primitives import BoardField, ColorField, ImageField, ImageOutput
 from invokeai.app.services.image_records.image_records_common import ImageCategory, ImageRecordChanges, ResourceOrigin
-from invokeai.app.shared.fields import FieldDescriptions
 from invokeai.backend.image_util.invisible_watermark import InvisibleWatermark
 from invokeai.backend.image_util.safety_checker import SafetyChecker
 
 from .baseinvocation import (
     BaseInvocation,
     Classification,
-    Input,
-    InputField,
     InvocationContext,
-    WithMetadata,
     invocation,
 )
 
diff --git a/invokeai/app/invocations/infill.py b/invokeai/app/invocations/infill.py
index c3d00bb133..d4d3d5bea4 100644
--- a/invokeai/app/invocations/infill.py
+++ b/invokeai/app/invocations/infill.py
@@ -13,7 +13,8 @@ from invokeai.backend.image_util.cv2_inpaint import cv2_inpaint
 from invokeai.backend.image_util.lama import LaMA
 from invokeai.backend.image_util.patchmatch import PatchMatch
 
-from .baseinvocation import BaseInvocation, InputField, InvocationContext, WithMetadata, invocation
+from .baseinvocation import BaseInvocation, InvocationContext, invocation
+from .fields import InputField, WithMetadata
 from .image import PIL_RESAMPLING_MAP, PIL_RESAMPLING_MODES
 
 
diff --git a/invokeai/app/invocations/ip_adapter.py b/invokeai/app/invocations/ip_adapter.py
index 6bd2889624..c01e0ed0fb 100644
--- a/invokeai/app/invocations/ip_adapter.py
+++ b/invokeai/app/invocations/ip_adapter.py
@@ -7,16 +7,13 @@ from pydantic import BaseModel, ConfigDict, Field, field_validator, model_valida
 from invokeai.app.invocations.baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
-    Input,
-    InputField,
     InvocationContext,
-    OutputField,
     invocation,
     invocation_output,
 )
+from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField
 from invokeai.app.invocations.primitives import ImageField
 from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
-from invokeai.app.shared.fields import FieldDescriptions
 from invokeai.backend.model_management.models.base import BaseModelType, ModelType
 from invokeai.backend.model_management.models.ip_adapter import get_ip_adapter_image_encoder_model_id
 
diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py
index b77363ceb8..909c307481 100644
--- a/invokeai/app/invocations/latent.py
+++ b/invokeai/app/invocations/latent.py
@@ -23,6 +23,7 @@ from diffusers.schedulers import SchedulerMixin as Scheduler
 from pydantic import field_validator
 from torchvision.transforms.functional import resize as tv_resize
 
+from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField, UIType, WithMetadata
 from invokeai.app.invocations.ip_adapter import IPAdapterField
 from invokeai.app.invocations.primitives import (
     DenoiseMaskField,
@@ -35,7 +36,6 @@ from invokeai.app.invocations.primitives import (
 )
 from invokeai.app.invocations.t2i_adapter import T2IAdapterField
 from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
-from invokeai.app.shared.fields import FieldDescriptions
 from invokeai.app.util.controlnet_utils import prepare_control_image
 from invokeai.app.util.step_callback import stable_diffusion_step_callback
 from invokeai.backend.ip_adapter.ip_adapter import IPAdapter, IPAdapterPlus
@@ -59,12 +59,7 @@ from ...backend.util.devices import choose_precision, choose_torch_device
 from .baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
-    Input,
-    InputField,
     InvocationContext,
-    OutputField,
-    UIType,
-    WithMetadata,
     invocation,
     invocation_output,
 )
diff --git a/invokeai/app/invocations/math.py b/invokeai/app/invocations/math.py
index defc61275f..6ca53011f0 100644
--- a/invokeai/app/invocations/math.py
+++ b/invokeai/app/invocations/math.py
@@ -5,10 +5,10 @@ from typing import Literal
 import numpy as np
 from pydantic import ValidationInfo, field_validator
 
+from invokeai.app.invocations.fields import FieldDescriptions, InputField
 from invokeai.app.invocations.primitives import FloatOutput, IntegerOutput
-from invokeai.app.shared.fields import FieldDescriptions
 
-from .baseinvocation import BaseInvocation, InputField, InvocationContext, invocation
+from .baseinvocation import BaseInvocation, InvocationContext, invocation
 
 
 @invocation("add", title="Add Integers", tags=["math", "add"], category="math", version="1.0.0")
diff --git a/invokeai/app/invocations/metadata.py b/invokeai/app/invocations/metadata.py
index 14d66f8ef6..399e217dc1 100644
--- a/invokeai/app/invocations/metadata.py
+++ b/invokeai/app/invocations/metadata.py
@@ -5,20 +5,16 @@ from pydantic import BaseModel, ConfigDict, Field
 from invokeai.app.invocations.baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
-    InputField,
     InvocationContext,
-    MetadataField,
-    OutputField,
-    UIType,
     invocation,
     invocation_output,
 )
 from invokeai.app.invocations.controlnet_image_processors import ControlField
+from invokeai.app.invocations.fields import FieldDescriptions, InputField, MetadataField, OutputField, UIType
 from invokeai.app.invocations.ip_adapter import IPAdapterModelField
 from invokeai.app.invocations.model import LoRAModelField, MainModelField, VAEModelField
 from invokeai.app.invocations.primitives import ImageField
 from invokeai.app.invocations.t2i_adapter import T2IAdapterField
-from invokeai.app.shared.fields import FieldDescriptions
 
 from ...version import __version__
 
diff --git a/invokeai/app/invocations/model.py b/invokeai/app/invocations/model.py
index 99dcc72999..c710c9761b 100644
--- a/invokeai/app/invocations/model.py
+++ b/invokeai/app/invocations/model.py
@@ -3,17 +3,14 @@ from typing import List, Optional
 
 from pydantic import BaseModel, ConfigDict, Field
 
-from invokeai.app.shared.fields import FieldDescriptions
+from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField
 from invokeai.app.shared.models import FreeUConfig
 
 from ...backend.model_management import BaseModelType, ModelType, SubModelType
 from .baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
-    Input,
-    InputField,
     InvocationContext,
-    OutputField,
     invocation,
     invocation_output,
 )
diff --git a/invokeai/app/invocations/noise.py b/invokeai/app/invocations/noise.py
index b1ee91e1cd..2e717ac561 100644
--- a/invokeai/app/invocations/noise.py
+++ b/invokeai/app/invocations/noise.py
@@ -4,17 +4,15 @@
 import torch
 from pydantic import field_validator
 
+from invokeai.app.invocations.fields import FieldDescriptions, InputField, OutputField
 from invokeai.app.invocations.latent import LatentsField
-from invokeai.app.shared.fields import FieldDescriptions
 from invokeai.app.util.misc import SEED_MAX
 
 from ...backend.util.devices import choose_torch_device, torch_dtype
 from .baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
-    InputField,
     InvocationContext,
-    OutputField,
     invocation,
     invocation_output,
 )
diff --git a/invokeai/app/invocations/onnx.py b/invokeai/app/invocations/onnx.py
index 759cfde700..b43d7eaef2 100644
--- a/invokeai/app/invocations/onnx.py
+++ b/invokeai/app/invocations/onnx.py
@@ -11,9 +11,17 @@ from diffusers.image_processor import VaeImageProcessor
 from pydantic import BaseModel, ConfigDict, Field, field_validator
 from tqdm import tqdm
 
+from invokeai.app.invocations.fields import (
+    FieldDescriptions,
+    Input,
+    InputField,
+    OutputField,
+    UIComponent,
+    UIType,
+    WithMetadata,
+)
 from invokeai.app.invocations.primitives import ConditioningField, ConditioningOutput, ImageField, ImageOutput
 from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
-from invokeai.app.shared.fields import FieldDescriptions
 from invokeai.app.util.step_callback import stable_diffusion_step_callback
 from invokeai.backend import BaseModelType, ModelType, SubModelType
 
@@ -24,13 +32,7 @@ from ..util.ti_utils import extract_ti_triggers_from_prompt
 from .baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
-    Input,
-    InputField,
     InvocationContext,
-    OutputField,
-    UIComponent,
-    UIType,
-    WithMetadata,
     invocation,
     invocation_output,
 )
diff --git a/invokeai/app/invocations/param_easing.py b/invokeai/app/invocations/param_easing.py
index dccd18f754..dab9c3dc0f 100644
--- a/invokeai/app/invocations/param_easing.py
+++ b/invokeai/app/invocations/param_easing.py
@@ -41,7 +41,8 @@ from matplotlib.ticker import MaxNLocator
 
 from invokeai.app.invocations.primitives import FloatCollectionOutput
 
-from .baseinvocation import BaseInvocation, InputField, InvocationContext, invocation
+from .baseinvocation import BaseInvocation, InvocationContext, invocation
+from .fields import InputField
 
 
 @invocation(
diff --git a/invokeai/app/invocations/primitives.py b/invokeai/app/invocations/primitives.py
index afe8ff06d9..22f03454a5 100644
--- a/invokeai/app/invocations/primitives.py
+++ b/invokeai/app/invocations/primitives.py
@@ -5,16 +5,12 @@ from typing import Optional, Tuple
 import torch
 from pydantic import BaseModel, Field
 
-from invokeai.app.shared.fields import FieldDescriptions
+from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField, UIComponent
 
 from .baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
-    Input,
-    InputField,
     InvocationContext,
-    OutputField,
-    UIComponent,
     invocation,
     invocation_output,
 )
diff --git a/invokeai/app/invocations/prompt.py b/invokeai/app/invocations/prompt.py
index 4778d98077..94b4a217ae 100644
--- a/invokeai/app/invocations/prompt.py
+++ b/invokeai/app/invocations/prompt.py
@@ -7,7 +7,8 @@ from pydantic import field_validator
 
 from invokeai.app.invocations.primitives import StringCollectionOutput
 
-from .baseinvocation import BaseInvocation, InputField, InvocationContext, UIComponent, invocation
+from .baseinvocation import BaseInvocation, InvocationContext, invocation
+from .fields import InputField, UIComponent
 
 
 @invocation(
diff --git a/invokeai/app/invocations/sdxl.py b/invokeai/app/invocations/sdxl.py
index 68076fdfeb..62df5bc804 100644
--- a/invokeai/app/invocations/sdxl.py
+++ b/invokeai/app/invocations/sdxl.py
@@ -1,14 +1,10 @@
-from invokeai.app.shared.fields import FieldDescriptions
+from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField, UIType
 
 from ...backend.model_management import ModelType, SubModelType
 from .baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
-    Input,
-    InputField,
     InvocationContext,
-    OutputField,
-    UIType,
     invocation,
     invocation_output,
 )
diff --git a/invokeai/app/invocations/strings.py b/invokeai/app/invocations/strings.py
index 3466206b37..ccbc2f6d92 100644
--- a/invokeai/app/invocations/strings.py
+++ b/invokeai/app/invocations/strings.py
@@ -5,13 +5,11 @@ import re
 from .baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
-    InputField,
     InvocationContext,
-    OutputField,
-    UIComponent,
     invocation,
     invocation_output,
 )
+from .fields import InputField, OutputField, UIComponent
 from .primitives import StringOutput
 
 
diff --git a/invokeai/app/invocations/t2i_adapter.py b/invokeai/app/invocations/t2i_adapter.py
index e055d23903..66ac87c37b 100644
--- a/invokeai/app/invocations/t2i_adapter.py
+++ b/invokeai/app/invocations/t2i_adapter.py
@@ -5,17 +5,14 @@ from pydantic import BaseModel, ConfigDict, Field, field_validator, model_valida
 from invokeai.app.invocations.baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
-    Input,
-    InputField,
     InvocationContext,
-    OutputField,
     invocation,
     invocation_output,
 )
 from invokeai.app.invocations.controlnet_image_processors import CONTROLNET_RESIZE_VALUES
+from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField
 from invokeai.app.invocations.primitives import ImageField
 from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
-from invokeai.app.shared.fields import FieldDescriptions
 from invokeai.backend.model_management.models.base import BaseModelType
 
 
diff --git a/invokeai/app/invocations/tiles.py b/invokeai/app/invocations/tiles.py
index e51f891a8d..bdc23ef6ed 100644
--- a/invokeai/app/invocations/tiles.py
+++ b/invokeai/app/invocations/tiles.py
@@ -8,14 +8,11 @@ from invokeai.app.invocations.baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
     Classification,
-    Input,
-    InputField,
     InvocationContext,
-    OutputField,
-    WithMetadata,
     invocation,
     invocation_output,
 )
+from invokeai.app.invocations.fields import Input, InputField, OutputField, WithMetadata
 from invokeai.app.invocations.primitives import ImageField, ImageOutput
 from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
 from invokeai.backend.tiles.tiles import (
diff --git a/invokeai/app/invocations/upscale.py b/invokeai/app/invocations/upscale.py
index 5f715c1a7e..2cab279a9f 100644
--- a/invokeai/app/invocations/upscale.py
+++ b/invokeai/app/invocations/upscale.py
@@ -14,7 +14,8 @@ from invokeai.backend.image_util.basicsr.rrdbnet_arch import RRDBNet
 from invokeai.backend.image_util.realesrgan.realesrgan import RealESRGAN
 from invokeai.backend.util.devices import choose_torch_device
 
-from .baseinvocation import BaseInvocation, InputField, InvocationContext, WithMetadata, invocation
+from .baseinvocation import BaseInvocation, InvocationContext, invocation
+from .fields import InputField, WithMetadata
 
 # TODO: Populate this from disk?
 # TODO: Use model manager to load?
diff --git a/invokeai/app/services/image_files/image_files_base.py b/invokeai/app/services/image_files/image_files_base.py
index 27dd67531f..f4036277b7 100644
--- a/invokeai/app/services/image_files/image_files_base.py
+++ b/invokeai/app/services/image_files/image_files_base.py
@@ -4,7 +4,7 @@ from typing import Optional
 
 from PIL.Image import Image as PILImageType
 
-from invokeai.app.invocations.baseinvocation import MetadataField
+from invokeai.app.invocations.fields import MetadataField
 from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID
 
 
diff --git a/invokeai/app/services/image_files/image_files_disk.py b/invokeai/app/services/image_files/image_files_disk.py
index 0844821672..fb687973ba 100644
--- a/invokeai/app/services/image_files/image_files_disk.py
+++ b/invokeai/app/services/image_files/image_files_disk.py
@@ -7,7 +7,7 @@ from PIL import Image, PngImagePlugin
 from PIL.Image import Image as PILImageType
 from send2trash import send2trash
 
-from invokeai.app.invocations.baseinvocation import MetadataField
+from invokeai.app.invocations.fields import MetadataField
 from invokeai.app.services.invoker import Invoker
 from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID
 from invokeai.app.util.thumbnails import get_thumbnail_name, make_thumbnail
diff --git a/invokeai/app/services/image_records/image_records_base.py b/invokeai/app/services/image_records/image_records_base.py
index 727f4977fb..7b7b261eca 100644
--- a/invokeai/app/services/image_records/image_records_base.py
+++ b/invokeai/app/services/image_records/image_records_base.py
@@ -2,7 +2,7 @@ from abc import ABC, abstractmethod
 from datetime import datetime
 from typing import Optional
 
-from invokeai.app.invocations.metadata import MetadataField
+from invokeai.app.invocations.fields import MetadataField
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
 
 from .image_records_common import ImageCategory, ImageRecord, ImageRecordChanges, ResourceOrigin
diff --git a/invokeai/app/services/image_records/image_records_sqlite.py b/invokeai/app/services/image_records/image_records_sqlite.py
index 74f82e7d84..5b37913c8f 100644
--- a/invokeai/app/services/image_records/image_records_sqlite.py
+++ b/invokeai/app/services/image_records/image_records_sqlite.py
@@ -3,7 +3,7 @@ import threading
 from datetime import datetime
 from typing import Optional, Union, cast
 
-from invokeai.app.invocations.baseinvocation import MetadataField, MetadataFieldValidator
+from invokeai.app.invocations.fields import MetadataField, MetadataFieldValidator
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
 from invokeai.app.services.shared.sqlite.sqlite_database import SqliteDatabase
 
diff --git a/invokeai/app/services/images/images_base.py b/invokeai/app/services/images/images_base.py
index df71dadb5b..42c4266774 100644
--- a/invokeai/app/services/images/images_base.py
+++ b/invokeai/app/services/images/images_base.py
@@ -3,7 +3,7 @@ from typing import Callable, Optional
 
 from PIL.Image import Image as PILImageType
 
-from invokeai.app.invocations.baseinvocation import MetadataField
+from invokeai.app.invocations.fields import MetadataField
 from invokeai.app.services.image_records.image_records_common import (
     ImageCategory,
     ImageRecord,
diff --git a/invokeai/app/services/images/images_default.py b/invokeai/app/services/images/images_default.py
index ff21731a50..adeed73811 100644
--- a/invokeai/app/services/images/images_default.py
+++ b/invokeai/app/services/images/images_default.py
@@ -2,7 +2,7 @@ from typing import Optional
 
 from PIL.Image import Image as PILImageType
 
-from invokeai.app.invocations.baseinvocation import MetadataField
+from invokeai.app.invocations.fields import MetadataField
 from invokeai.app.services.invoker import Invoker
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
 from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID
diff --git a/invokeai/app/services/shared/graph.py b/invokeai/app/services/shared/graph.py
index 1acf165aba..ba05b050c5 100644
--- a/invokeai/app/services/shared/graph.py
+++ b/invokeai/app/services/shared/graph.py
@@ -13,14 +13,11 @@ from invokeai.app.invocations import *  # noqa: F401 F403
 from invokeai.app.invocations.baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
-    Input,
-    InputField,
     InvocationContext,
-    OutputField,
-    UIType,
     invocation,
     invocation_output,
 )
+from invokeai.app.invocations.fields import Input, InputField, OutputField, UIType
 from invokeai.app.util.misc import uuid_string
 
 # in 3.10 this would be "from types import NoneType"
diff --git a/invokeai/app/shared/fields.py b/invokeai/app/shared/fields.py
deleted file mode 100644
index 3e841ffbf2..0000000000
--- a/invokeai/app/shared/fields.py
+++ /dev/null
@@ -1,67 +0,0 @@
-class FieldDescriptions:
-    denoising_start = "When to start denoising, expressed a percentage of total steps"
-    denoising_end = "When to stop denoising, expressed a percentage of total steps"
-    cfg_scale = "Classifier-Free Guidance scale"
-    cfg_rescale_multiplier = "Rescale multiplier for CFG guidance, used for models trained with zero-terminal SNR"
-    scheduler = "Scheduler to use during inference"
-    positive_cond = "Positive conditioning tensor"
-    negative_cond = "Negative conditioning tensor"
-    noise = "Noise tensor"
-    clip = "CLIP (tokenizer, text encoder, LoRAs) and skipped layer count"
-    unet = "UNet (scheduler, LoRAs)"
-    vae = "VAE"
-    cond = "Conditioning tensor"
-    controlnet_model = "ControlNet model to load"
-    vae_model = "VAE model to load"
-    lora_model = "LoRA model to load"
-    main_model = "Main model (UNet, VAE, CLIP) to load"
-    sdxl_main_model = "SDXL Main model (UNet, VAE, CLIP1, CLIP2) to load"
-    sdxl_refiner_model = "SDXL Refiner Main Modde (UNet, VAE, CLIP2) to load"
-    onnx_main_model = "ONNX Main model (UNet, VAE, CLIP) to load"
-    lora_weight = "The weight at which the LoRA is applied to each model"
-    compel_prompt = "Prompt to be parsed by Compel to create a conditioning tensor"
-    raw_prompt = "Raw prompt text (no parsing)"
-    sdxl_aesthetic = "The aesthetic score to apply to the conditioning tensor"
-    skipped_layers = "Number of layers to skip in text encoder"
-    seed = "Seed for random number generation"
-    steps = "Number of steps to run"
-    width = "Width of output (px)"
-    height = "Height of output (px)"
-    control = "ControlNet(s) to apply"
-    ip_adapter = "IP-Adapter to apply"
-    t2i_adapter = "T2I-Adapter(s) to apply"
-    denoised_latents = "Denoised latents tensor"
-    latents = "Latents tensor"
-    strength = "Strength of denoising (proportional to steps)"
-    metadata = "Optional metadata to be saved with the image"
-    metadata_collection = "Collection of Metadata"
-    metadata_item_polymorphic = "A single metadata item or collection of metadata items"
-    metadata_item_label = "Label for this metadata item"
-    metadata_item_value = "The value for this metadata item (may be any type)"
-    workflow = "Optional workflow to be saved with the image"
-    interp_mode = "Interpolation mode"
-    torch_antialias = "Whether or not to apply antialiasing (bilinear or bicubic only)"
-    fp32 = "Whether or not to use full float32 precision"
-    precision = "Precision to use"
-    tiled = "Processing using overlapping tiles (reduce memory consumption)"
-    detect_res = "Pixel resolution for detection"
-    image_res = "Pixel resolution for output image"
-    safe_mode = "Whether or not to use safe mode"
-    scribble_mode = "Whether or not to use scribble mode"
-    scale_factor = "The factor by which to scale"
-    blend_alpha = (
-        "Blending factor. 0.0 = use input A only, 1.0 = use input B only, 0.5 = 50% mix of input A and input B."
-    )
-    num_1 = "The first number"
-    num_2 = "The second number"
-    mask = "The mask to use for the operation"
-    board = "The board to save the image to"
-    image = "The image to process"
-    tile_size = "Tile size"
-    inclusive_low = "The inclusive low value"
-    exclusive_high = "The exclusive high value"
-    decimal_places = "The number of decimal places to round to"
-    freeu_s1 = 'Scaling factor for stage 1 to attenuate the contributions of the skip features. This is done to mitigate the "oversmoothing effect" in the enhanced denoising process.'
-    freeu_s2 = 'Scaling factor for stage 2 to attenuate the contributions of the skip features. This is done to mitigate the "oversmoothing effect" in the enhanced denoising process.'
-    freeu_b1 = "Scaling factor for stage 1 to amplify the contributions of backbone features."
-    freeu_b2 = "Scaling factor for stage 2 to amplify the contributions of backbone features."
diff --git a/invokeai/app/shared/models.py b/invokeai/app/shared/models.py
index ed68cb287e..1a11b480cc 100644
--- a/invokeai/app/shared/models.py
+++ b/invokeai/app/shared/models.py
@@ -1,6 +1,6 @@
 from pydantic import BaseModel, Field
 
-from invokeai.app.shared.fields import FieldDescriptions
+from invokeai.app.invocations.fields import FieldDescriptions
 
 
 class FreeUConfig(BaseModel):
diff --git a/tests/aa_nodes/test_nodes.py b/tests/aa_nodes/test_nodes.py
index bca4e1011f..e71daad3f3 100644
--- a/tests/aa_nodes/test_nodes.py
+++ b/tests/aa_nodes/test_nodes.py
@@ -3,12 +3,11 @@ from typing import Any, Callable, Union
 from invokeai.app.invocations.baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
-    InputField,
     InvocationContext,
-    OutputField,
     invocation,
     invocation_output,
 )
+from invokeai.app.invocations.fields import InputField, OutputField
 from invokeai.app.invocations.image import ImageField
 
 

From 3d98446d5d79828c4048a932877a4e1298d860a0 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 13 Jan 2024 18:02:58 +1100
Subject: [PATCH 040/411] feat(nodes): restricts invocation context power

Creates a low-power `InvocationContext` with simplified methods and data.

See `invocation_context.py` for detailed comments.
---
 .../app/services/shared/invocation_context.py | 408 ++++++++++++++++++
 invokeai/app/util/step_callback.py            |  39 +-
 2 files changed, 434 insertions(+), 13 deletions(-)
 create mode 100644 invokeai/app/services/shared/invocation_context.py

diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
new file mode 100644
index 0000000000..c0aaac54f8
--- /dev/null
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -0,0 +1,408 @@
+from dataclasses import dataclass
+from enum import Enum
+from typing import TYPE_CHECKING, Optional
+
+from PIL.Image import Image
+from pydantic import ConfigDict
+from torch import Tensor
+
+from invokeai.app.invocations.compel import ConditioningFieldData
+from invokeai.app.invocations.fields import MetadataField, WithMetadata
+from invokeai.app.services.config.config_default import InvokeAIAppConfig
+from invokeai.app.services.image_records.image_records_common import ImageCategory, ImageRecordChanges, ResourceOrigin
+from invokeai.app.services.images.images_common import ImageDTO
+from invokeai.app.services.invocation_services import InvocationServices
+from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID
+from invokeai.app.util.misc import uuid_string
+from invokeai.app.util.step_callback import stable_diffusion_step_callback
+from invokeai.backend.model_management.model_manager import ModelInfo
+from invokeai.backend.model_management.models.base import BaseModelType, ModelType, SubModelType
+from invokeai.backend.stable_diffusion.diffusers_pipeline import PipelineIntermediateState
+
+if TYPE_CHECKING:
+    from invokeai.app.invocations.baseinvocation import BaseInvocation
+
+"""
+The InvocationContext provides access to various services and data about the current invocation.
+
+We do not provide the invocation services directly, as their methods are both dangerous and
+inconvenient to use.
+
+For example:
+- The `images` service allows nodes to delete or unsafely modify existing images.
+- The `configuration` service allows nodes to change the app's config at runtime.
+- The `events` service allows nodes to emit arbitrary events.
+
+Wrapping these services provides a simpler and safer interface for nodes to use.
+
+When a node executes, a fresh `InvocationContext` is built for it, ensuring nodes cannot interfere
+with each other.
+
+Note: The docstrings are in weird places, but that's where they must be to get IDEs to see them.
+"""
+
+
+@dataclass(frozen=True)
+class InvocationContextData:
+    invocation: "BaseInvocation"
+    session_id: str
+    queue_id: str
+    source_node_id: str
+    queue_item_id: int
+    batch_id: str
+    workflow: Optional[WorkflowWithoutID] = None
+
+
+class LoggerInterface:
+    def __init__(self, services: InvocationServices) -> None:
+        def debug(message: str) -> None:
+            """
+            Logs a debug message.
+
+            :param message: The message to log.
+            """
+            services.logger.debug(message)
+
+        def info(message: str) -> None:
+            """
+            Logs an info message.
+
+            :param message: The message to log.
+            """
+            services.logger.info(message)
+
+        def warning(message: str) -> None:
+            """
+            Logs a warning message.
+
+            :param message: The message to log.
+            """
+            services.logger.warning(message)
+
+        def error(message: str) -> None:
+            """
+            Logs an error message.
+
+            :param message: The message to log.
+            """
+            services.logger.error(message)
+
+        self.debug = debug
+        self.info = info
+        self.warning = warning
+        self.error = error
+
+
+class ImagesInterface:
+    def __init__(self, services: InvocationServices, context_data: InvocationContextData) -> None:
+        def save(
+            image: Image,
+            board_id: Optional[str] = None,
+            image_category: ImageCategory = ImageCategory.GENERAL,
+            metadata: Optional[MetadataField] = None,
+        ) -> ImageDTO:
+            """
+            Saves an image, returning its DTO.
+
+            If the current queue item has a workflow, it is automatically saved with the image.
+
+            :param image: The image to save, as a PIL image.
+            :param board_id: The board ID to add the image to, if it should be added.
+            :param image_category: The category of the image. Only the GENERAL category is added to the gallery.
+            :param metadata: The metadata to save with the image, if it should have any. If the invocation inherits \
+                from `WithMetadata`, that metadata will be used automatically. Provide this only if you want to \
+                override or provide metadata manually.
+            """
+
+            # If the invocation inherits metadata, use that. Else, use the metadata passed in.
+            metadata_ = (
+                context_data.invocation.metadata if isinstance(context_data.invocation, WithMetadata) else metadata
+            )
+
+            return services.images.create(
+                image=image,
+                is_intermediate=context_data.invocation.is_intermediate,
+                image_category=image_category,
+                board_id=board_id,
+                metadata=metadata_,
+                image_origin=ResourceOrigin.INTERNAL,
+                workflow=context_data.workflow,
+                session_id=context_data.session_id,
+                node_id=context_data.invocation.id,
+            )
+
+        def get_pil(image_name: str) -> Image:
+            """
+            Gets an image as a PIL Image object.
+
+            :param image_name: The name of the image to get.
+            """
+            return services.images.get_pil_image(image_name)
+
+        def get_metadata(image_name: str) -> Optional[MetadataField]:
+            """
+            Gets an image's metadata, if it has any.
+
+            :param image_name: The name of the image to get the metadata for.
+            """
+            return services.images.get_metadata(image_name)
+
+        def get_dto(image_name: str) -> ImageDTO:
+            """
+            Gets an image as an ImageDTO object.
+
+            :param image_name: The name of the image to get.
+            """
+            return services.images.get_dto(image_name)
+
+        def update(
+            image_name: str,
+            board_id: Optional[str] = None,
+            is_intermediate: Optional[bool] = False,
+        ) -> ImageDTO:
+            """
+            Updates an image, returning its updated DTO.
+
+            It is not suggested to update images saved by earlier nodes, as this can cause confusion for users.
+
+            If you use this method, you *must* return the image as an :class:`ImageOutput` for the gallery to
+            get the updated image.
+
+            :param image_name: The name of the image to update.
+            :param board_id: The board ID to add the image to, if it should be added.
+            :param is_intermediate: Whether the image is an intermediate. Intermediate images aren't added to the gallery.
+            """
+            if is_intermediate is not None:
+                services.images.update(image_name, ImageRecordChanges(is_intermediate=is_intermediate))
+            if board_id is None:
+                services.board_images.remove_image_from_board(image_name)
+            else:
+                services.board_images.add_image_to_board(image_name, board_id)
+            return services.images.get_dto(image_name)
+
+        self.save = save
+        self.get_pil = get_pil
+        self.get_metadata = get_metadata
+        self.get_dto = get_dto
+        self.update = update
+
+
+class LatentsKind(str, Enum):
+    IMAGE = "image"
+    NOISE = "noise"
+    MASK = "mask"
+    MASKED_IMAGE = "masked_image"
+    OTHER = "other"
+
+
+class LatentsInterface:
+    def __init__(
+        self,
+        services: InvocationServices,
+        context_data: InvocationContextData,
+    ) -> None:
+        def save(tensor: Tensor) -> str:
+            """
+            Saves a latents tensor, returning its name.
+
+            :param tensor: The latents tensor to save.
+            """
+            name = f"{context_data.session_id}__{context_data.invocation.id}__{uuid_string()[:7]}"
+            services.latents.save(
+                name=name,
+                data=tensor,
+            )
+            return name
+
+        def get(latents_name: str) -> Tensor:
+            """
+            Gets a latents tensor by name.
+
+            :param latents_name: The name of the latents tensor to get.
+            """
+            return services.latents.get(latents_name)
+
+        self.save = save
+        self.get = get
+
+
+class ConditioningInterface:
+    def __init__(
+        self,
+        services: InvocationServices,
+        context_data: InvocationContextData,
+    ) -> None:
+        def save(conditioning_data: ConditioningFieldData) -> str:
+            """
+            Saves a conditioning data object, returning its name.
+
+            :param conditioning_data: The conditioning data to save.
+            """
+            name = f"{context_data.session_id}__{context_data.invocation.id}__{uuid_string()[:7]}__conditioning"
+            services.latents.save(
+                name=name,
+                data=conditioning_data,  # type: ignore [arg-type]
+            )
+            return name
+
+        def get(conditioning_name: str) -> Tensor:
+            """
+            Gets conditioning data by name.
+
+            :param conditioning_name: The name of the conditioning data to get.
+            """
+            return services.latents.get(conditioning_name)
+
+        self.save = save
+        self.get = get
+
+
+class ModelsInterface:
+    def __init__(self, services: InvocationServices, context_data: InvocationContextData) -> None:
+        def exists(model_name: str, base_model: BaseModelType, model_type: ModelType) -> bool:
+            """
+            Checks if a model exists.
+
+            :param model_name: The name of the model to check.
+            :param base_model: The base model of the model to check.
+            :param model_type: The type of the model to check.
+            """
+            return services.model_manager.model_exists(model_name, base_model, model_type)
+
+        def load(
+            model_name: str, base_model: BaseModelType, model_type: ModelType, submodel: Optional[SubModelType] = None
+        ) -> ModelInfo:
+            """
+            Loads a model, returning its `ModelInfo` object.
+
+            :param model_name: The name of the model to get.
+            :param base_model: The base model of the model to get.
+            :param model_type: The type of the model to get.
+            :param submodel: The submodel of the model to get.
+            """
+            return services.model_manager.get_model(
+                model_name, base_model, model_type, submodel, context_data=context_data
+            )
+
+        def get_info(model_name: str, base_model: BaseModelType, model_type: ModelType) -> dict:
+            """
+            Gets a model's info, an dict-like object.
+
+            :param model_name: The name of the model to get.
+            :param base_model: The base model of the model to get.
+            :param model_type: The type of the model to get.
+            """
+            return services.model_manager.model_info(model_name, base_model, model_type)
+
+        self.exists = exists
+        self.load = load
+        self.get_info = get_info
+
+
+class ConfigInterface:
+    def __init__(self, services: InvocationServices) -> None:
+        def get() -> InvokeAIAppConfig:
+            """
+            Gets the app's config.
+            """
+            # The config can be changed at runtime. We don't want nodes doing this, so we make a
+            # frozen copy..
+            config = services.configuration.get_config()
+            frozen_config = config.model_copy(update={"model_config": ConfigDict(frozen=True)})
+            return frozen_config
+
+        self.get = get
+
+
+class UtilInterface:
+    def __init__(self, services: InvocationServices, context_data: InvocationContextData) -> None:
+        def sd_step_callback(
+            intermediate_state: PipelineIntermediateState,
+            base_model: BaseModelType,
+        ) -> None:
+            """
+            The step callback emits a progress event with the current step, the total number of
+            steps, a preview image, and some other internal metadata.
+
+            This should be called after each step of the diffusion process.
+
+            :param intermediate_state: The intermediate state of the diffusion pipeline.
+            :param base_model: The base model for the current denoising step.
+            """
+            stable_diffusion_step_callback(
+                context_data=context_data,
+                intermediate_state=intermediate_state,
+                base_model=base_model,
+                invocation_queue=services.queue,
+                events=services.events,
+            )
+
+        self.sd_step_callback = sd_step_callback
+
+
+class InvocationContext:
+    """
+    The invocation context provides access to various services and data about the current invocation.
+    """
+
+    def __init__(
+        self,
+        images: ImagesInterface,
+        latents: LatentsInterface,
+        models: ModelsInterface,
+        config: ConfigInterface,
+        logger: LoggerInterface,
+        data: InvocationContextData,
+        util: UtilInterface,
+        conditioning: ConditioningInterface,
+    ) -> None:
+        self.images = images
+        "Provides methods to save, get and update images and their metadata."
+        self.logger = logger
+        "Provides access to the app logger."
+        self.latents = latents
+        "Provides methods to save and get latents tensors, including image, noise, masks, and masked images."
+        self.conditioning = conditioning
+        "Provides methods to save and get conditioning data."
+        self.models = models
+        "Provides methods to check if a model exists, get a model, and get a model's info."
+        self.config = config
+        "Provides access to the app's config."
+        self.data = data
+        "Provides data about the current queue item and invocation."
+        self.util = util
+        "Provides utility methods."
+
+
+def build_invocation_context(
+    services: InvocationServices,
+    context_data: InvocationContextData,
+) -> InvocationContext:
+    """
+    Builds the invocation context. This is a wrapper around the invocation services that provides
+    a more convenient (and less dangerous) interface for nodes to use.
+
+    :param invocation_services: The invocation services to wrap.
+    :param invocation_context_data: The invocation context data.
+    """
+
+    logger = LoggerInterface(services=services)
+    images = ImagesInterface(services=services, context_data=context_data)
+    latents = LatentsInterface(services=services, context_data=context_data)
+    models = ModelsInterface(services=services, context_data=context_data)
+    config = ConfigInterface(services=services)
+    util = UtilInterface(services=services, context_data=context_data)
+    conditioning = ConditioningInterface(services=services, context_data=context_data)
+
+    ctx = InvocationContext(
+        images=images,
+        logger=logger,
+        config=config,
+        latents=latents,
+        models=models,
+        data=context_data,
+        util=util,
+        conditioning=conditioning,
+    )
+
+    return ctx
diff --git a/invokeai/app/util/step_callback.py b/invokeai/app/util/step_callback.py
index f166206d52..5cc3caa9ba 100644
--- a/invokeai/app/util/step_callback.py
+++ b/invokeai/app/util/step_callback.py
@@ -1,12 +1,25 @@
+from typing import Protocol
+
 import torch
 from PIL import Image
 
+from invokeai.app.services.events.events_base import EventServiceBase
 from invokeai.app.services.invocation_processor.invocation_processor_common import CanceledException, ProgressImage
+from invokeai.app.services.invocation_queue.invocation_queue_base import InvocationQueueABC
+from invokeai.app.services.shared.invocation_context import InvocationContextData
 
 from ...backend.model_management.models import BaseModelType
 from ...backend.stable_diffusion import PipelineIntermediateState
 from ...backend.util.util import image_to_dataURL
-from ..invocations.baseinvocation import InvocationContext
+
+
+class StepCallback(Protocol):
+    def __call__(
+        self,
+        intermediate_state: PipelineIntermediateState,
+        base_model: BaseModelType,
+    ) -> None:
+        ...
 
 
 def sample_to_lowres_estimated_image(samples, latent_rgb_factors, smooth_matrix=None):
@@ -25,13 +38,13 @@ def sample_to_lowres_estimated_image(samples, latent_rgb_factors, smooth_matrix=
 
 
 def stable_diffusion_step_callback(
-    context: InvocationContext,
+    context_data: InvocationContextData,
     intermediate_state: PipelineIntermediateState,
-    node: dict,
-    source_node_id: str,
     base_model: BaseModelType,
-):
-    if context.services.queue.is_canceled(context.graph_execution_state_id):
+    invocation_queue: InvocationQueueABC,
+    events: EventServiceBase,
+) -> None:
+    if invocation_queue.is_canceled(context_data.session_id):
         raise CanceledException
 
     # Some schedulers report not only the noisy latents at the current timestep,
@@ -108,13 +121,13 @@ def stable_diffusion_step_callback(
 
     dataURL = image_to_dataURL(image, image_format="JPEG")
 
-    context.services.events.emit_generator_progress(
-        queue_id=context.queue_id,
-        queue_item_id=context.queue_item_id,
-        queue_batch_id=context.queue_batch_id,
-        graph_execution_state_id=context.graph_execution_state_id,
-        node=node,
-        source_node_id=source_node_id,
+    events.emit_generator_progress(
+        queue_id=context_data.queue_id,
+        queue_item_id=context_data.queue_item_id,
+        queue_batch_id=context_data.batch_id,
+        graph_execution_state_id=context_data.session_id,
+        node_id=context_data.invocation.id,
+        source_node_id=context_data.source_node_id,
         progress_image=ProgressImage(width=width, height=height, dataURL=dataURL),
         step=intermediate_state.step,
         order=intermediate_state.order,

From 9bc2d0988989a92a5736e8f78d21cca13cdc4646 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 13 Jan 2024 23:23:01 +1100
Subject: [PATCH 041/411] feat: add pyright config

I was having issues with mypy bother over- and under-reporting certain problems. I've added a pyright config.
---
 pyproject.toml | 16 ++++++++++++++++
 1 file changed, 16 insertions(+)

diff --git a/pyproject.toml b/pyproject.toml
index 7f4b0d77f2..d063f1ad0e 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -280,3 +280,19 @@ module = [
   "invokeai.frontend.install.model_install",
 ]
 #=== End: MyPy
+
+[tool.pyright]
+include = [
+  "invokeai/app/invocations/"
+]
+exclude = [
+  "**/node_modules",
+  "**/__pycache__",
+  "invokeai/app/invocations/onnx.py",
+  "invokeai/app/api/routers/models.py",
+  "invokeai/app/services/invocation_stats/invocation_stats_default.py",
+  "invokeai/app/services/model_manager/model_manager_base.py",
+  "invokeai/app/services/model_manager/model_manager_default.py",
+  "invokeai/app/services/model_records/model_records_sql.py",
+  "invokeai/app/util/controlnet_utils.py",
+]

From 8637c40661617de2a792eae5c1495821205587a3 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 13 Jan 2024 23:23:16 +1100
Subject: [PATCH 042/411] feat(nodes): update all invocations to use new
 invocation context

Update all invocations to use the new context. The changes are all fairly simple, but there are a lot of them.

Supporting minor changes:
- Patch bump for all nodes that use the context
- Update invocation processor to provide new context
- Minor change to `EventServiceBase` to accept a node's ID instead of the dict version of a node
- Minor change to `ModelManagerService` to support the new wrapped context
- Fanagling of imports to avoid circular dependencies
---
 invokeai/app/invocations/baseinvocation.py    |  54 +-
 invokeai/app/invocations/collections.py       |   8 +-
 invokeai/app/invocations/compel.py            | 105 ++--
 .../controlnet_image_processors.py            |  56 +-
 invokeai/app/invocations/cv.py                |  30 +-
 invokeai/app/invocations/facetools.py         | 129 ++--
 invokeai/app/invocations/fields.py            |  57 +-
 invokeai/app/invocations/image.py             | 586 +++++-------------
 invokeai/app/invocations/infill.py            | 123 +---
 invokeai/app/invocations/ip_adapter.py        |   9 +-
 invokeai/app/invocations/latent.py            | 238 +++----
 invokeai/app/invocations/math.py              |  22 +-
 invokeai/app/invocations/metadata.py          |  19 +-
 invokeai/app/invocations/model.py             |  29 +-
 invokeai/app/invocations/noise.py             |  25 +-
 invokeai/app/invocations/onnx.py              |  10 +-
 invokeai/app/invocations/param_easing.py      |  44 +-
 invokeai/app/invocations/primitives.py        | 136 ++--
 invokeai/app/invocations/prompt.py            |   6 +-
 invokeai/app/invocations/sdxl.py              |  13 +-
 invokeai/app/invocations/strings.py           |  11 +-
 invokeai/app/invocations/t2i_adapter.py       |   6 +-
 invokeai/app/invocations/tiles.py             |  38 +-
 invokeai/app/invocations/upscale.py           |  33 +-
 invokeai/app/services/events/events_base.py   |   4 +-
 .../invocation_processor_default.py           |  24 +-
 .../model_manager/model_manager_base.py       |   9 +-
 .../model_manager/model_manager_common.py     |   0
 .../model_manager/model_manager_default.py    |  44 +-
 invokeai/app/services/shared/graph.py         |   7 +-
 .../app/services/shared/invocation_context.py |   9 +-
 invokeai/app/util/step_callback.py            |  23 +-
 32 files changed, 716 insertions(+), 1191 deletions(-)
 create mode 100644 invokeai/app/services/model_manager/model_manager_common.py

diff --git a/invokeai/app/invocations/baseinvocation.py b/invokeai/app/invocations/baseinvocation.py
index 395d5e9870..c4aed1fac5 100644
--- a/invokeai/app/invocations/baseinvocation.py
+++ b/invokeai/app/invocations/baseinvocation.py
@@ -16,10 +16,16 @@ from pydantic import BaseModel, ConfigDict, Field, create_model
 from pydantic.fields import FieldInfo
 from pydantic_core import PydanticUndefined
 
-from invokeai.app.invocations.fields import FieldKind, Input
+from invokeai.app.invocations.fields import (
+    FieldDescriptions,
+    FieldKind,
+    Input,
+    InputFieldJSONSchemaExtra,
+    MetadataField,
+    logger,
+)
 from invokeai.app.services.config.config_default import InvokeAIAppConfig
-from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID
-from invokeai.app.shared.fields import FieldDescriptions
+from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.app.util.metaenum import MetaEnum
 from invokeai.app.util.misc import uuid_string
 from invokeai.backend.util.logging import InvokeAILogger
@@ -219,7 +225,7 @@ class BaseInvocation(ABC, BaseModel):
         """Invoke with provided context and return outputs."""
         pass
 
-    def invoke_internal(self, context: InvocationContext) -> BaseInvocationOutput:
+    def invoke_internal(self, context: InvocationContext, services: "InvocationServices") -> BaseInvocationOutput:
         """
         Internal invoke method, calls `invoke()` after some prep.
         Handles optional fields that are required to call `invoke()` and invocation cache.
@@ -244,23 +250,23 @@ class BaseInvocation(ABC, BaseModel):
                     raise MissingInputException(self.model_fields["type"].default, field_name)
 
         # skip node cache codepath if it's disabled
-        if context.services.configuration.node_cache_size == 0:
+        if services.configuration.node_cache_size == 0:
             return self.invoke(context)
 
         output: BaseInvocationOutput
         if self.use_cache:
-            key = context.services.invocation_cache.create_key(self)
-            cached_value = context.services.invocation_cache.get(key)
+            key = services.invocation_cache.create_key(self)
+            cached_value = services.invocation_cache.get(key)
             if cached_value is None:
-                context.services.logger.debug(f'Invocation cache miss for type "{self.get_type()}": {self.id}')
+                services.logger.debug(f'Invocation cache miss for type "{self.get_type()}": {self.id}')
                 output = self.invoke(context)
-                context.services.invocation_cache.save(key, output)
+                services.invocation_cache.save(key, output)
                 return output
             else:
-                context.services.logger.debug(f'Invocation cache hit for type "{self.get_type()}": {self.id}')
+                services.logger.debug(f'Invocation cache hit for type "{self.get_type()}": {self.id}')
                 return cached_value
         else:
-            context.services.logger.debug(f'Skipping invocation cache for "{self.get_type()}": {self.id}')
+            services.logger.debug(f'Skipping invocation cache for "{self.get_type()}": {self.id}')
             return self.invoke(context)
 
     id: str = Field(
@@ -513,3 +519,29 @@ def invocation_output(
         return cls
 
     return wrapper
+
+
+class WithMetadata(BaseModel):
+    """
+    Inherit from this class if your node needs a metadata input field.
+    """
+
+    metadata: Optional[MetadataField] = Field(
+        default=None,
+        description=FieldDescriptions.metadata,
+        json_schema_extra=InputFieldJSONSchemaExtra(
+            field_kind=FieldKind.Internal,
+            input=Input.Connection,
+            orig_required=False,
+        ).model_dump(exclude_none=True),
+    )
+
+
+class WithWorkflow:
+    workflow = None
+
+    def __init_subclass__(cls) -> None:
+        logger.warn(
+            f"{cls.__module__.split('.')[0]}.{cls.__name__}: WithWorkflow is deprecated. Use `context.workflow` to access the workflow."
+        )
+        super().__init_subclass__()
diff --git a/invokeai/app/invocations/collections.py b/invokeai/app/invocations/collections.py
index d35a9d79c7..f5709b4ba3 100644
--- a/invokeai/app/invocations/collections.py
+++ b/invokeai/app/invocations/collections.py
@@ -7,7 +7,7 @@ from pydantic import ValidationInfo, field_validator
 from invokeai.app.invocations.primitives import IntegerCollectionOutput
 from invokeai.app.util.misc import SEED_MAX
 
-from .baseinvocation import BaseInvocation, InvocationContext, invocation
+from .baseinvocation import BaseInvocation, invocation
 from .fields import InputField
 
 
@@ -27,7 +27,7 @@ class RangeInvocation(BaseInvocation):
             raise ValueError("stop must be greater than start")
         return v
 
-    def invoke(self, context: InvocationContext) -> IntegerCollectionOutput:
+    def invoke(self, context) -> IntegerCollectionOutput:
         return IntegerCollectionOutput(collection=list(range(self.start, self.stop, self.step)))
 
 
@@ -45,7 +45,7 @@ class RangeOfSizeInvocation(BaseInvocation):
     size: int = InputField(default=1, gt=0, description="The number of values")
     step: int = InputField(default=1, description="The step of the range")
 
-    def invoke(self, context: InvocationContext) -> IntegerCollectionOutput:
+    def invoke(self, context) -> IntegerCollectionOutput:
         return IntegerCollectionOutput(
             collection=list(range(self.start, self.start + (self.step * self.size), self.step))
         )
@@ -72,6 +72,6 @@ class RandomRangeInvocation(BaseInvocation):
         description="The seed for the RNG (omit for random)",
     )
 
-    def invoke(self, context: InvocationContext) -> IntegerCollectionOutput:
+    def invoke(self, context) -> IntegerCollectionOutput:
         rng = np.random.default_rng(self.seed)
         return IntegerCollectionOutput(collection=list(rng.integers(low=self.low, high=self.high, size=self.size)))
diff --git a/invokeai/app/invocations/compel.py b/invokeai/app/invocations/compel.py
index b386aef2cb..b4496031bc 100644
--- a/invokeai/app/invocations/compel.py
+++ b/invokeai/app/invocations/compel.py
@@ -1,12 +1,18 @@
-from dataclasses import dataclass
-from typing import List, Optional, Union
+from typing import TYPE_CHECKING, List, Optional, Union
 
 import torch
 from compel import Compel, ReturnedEmbeddingsType
 from compel.prompt_parser import Blend, Conjunction, CrossAttentionControlSubstitute, FlattenedPrompt, Fragment
 
-from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField, UIComponent
-from invokeai.app.invocations.primitives import ConditioningField, ConditioningOutput
+from invokeai.app.invocations.fields import (
+    ConditioningFieldData,
+    FieldDescriptions,
+    Input,
+    InputField,
+    OutputField,
+    UIComponent,
+)
+from invokeai.app.invocations.primitives import ConditioningOutput
 from invokeai.backend.stable_diffusion.diffusion.conditioning_data import (
     BasicConditioningInfo,
     ExtraConditioningInfo,
@@ -20,16 +26,14 @@ from ..util.ti_utils import extract_ti_triggers_from_prompt
 from .baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
-    InvocationContext,
     invocation,
     invocation_output,
 )
 from .model import ClipField
 
+if TYPE_CHECKING:
+    from invokeai.app.services.shared.invocation_context import InvocationContext
 
-@dataclass
-class ConditioningFieldData:
-    conditionings: List[BasicConditioningInfo]
     # unconditioned: Optional[torch.Tensor]
 
 
@@ -44,7 +48,7 @@ class ConditioningFieldData:
     title="Prompt",
     tags=["prompt", "compel"],
     category="conditioning",
-    version="1.0.0",
+    version="1.0.1",
 )
 class CompelInvocation(BaseInvocation):
     """Parse prompt using compel package to conditioning."""
@@ -61,26 +65,18 @@ class CompelInvocation(BaseInvocation):
     )
 
     @torch.no_grad()
-    def invoke(self, context: InvocationContext) -> ConditioningOutput:
-        tokenizer_info = context.services.model_manager.get_model(
-            **self.clip.tokenizer.model_dump(),
-            context=context,
-        )
-        text_encoder_info = context.services.model_manager.get_model(
-            **self.clip.text_encoder.model_dump(),
-            context=context,
-        )
+    def invoke(self, context) -> ConditioningOutput:
+        tokenizer_info = context.models.load(**self.clip.tokenizer.model_dump())
+        text_encoder_info = context.models.load(**self.clip.text_encoder.model_dump())
 
         def _lora_loader():
             for lora in self.clip.loras:
-                lora_info = context.services.model_manager.get_model(
-                    **lora.model_dump(exclude={"weight"}), context=context
-                )
+                lora_info = context.models.load(**lora.model_dump(exclude={"weight"}))
                 yield (lora_info.context.model, lora.weight)
                 del lora_info
             return
 
-        # loras = [(context.services.model_manager.get_model(**lora.dict(exclude={"weight"})).context.model, lora.weight) for lora in self.clip.loras]
+        # loras = [(context.models.get(**lora.dict(exclude={"weight"})).context.model, lora.weight) for lora in self.clip.loras]
 
         ti_list = []
         for trigger in extract_ti_triggers_from_prompt(self.prompt):
@@ -89,11 +85,10 @@ class CompelInvocation(BaseInvocation):
                 ti_list.append(
                     (
                         name,
-                        context.services.model_manager.get_model(
+                        context.models.load(
                             model_name=name,
                             base_model=self.clip.text_encoder.base_model,
                             model_type=ModelType.TextualInversion,
-                            context=context,
                         ).context.model,
                     )
                 )
@@ -124,7 +119,7 @@ class CompelInvocation(BaseInvocation):
 
             conjunction = Compel.parse_prompt_string(self.prompt)
 
-            if context.services.configuration.log_tokenization:
+            if context.config.get().log_tokenization:
                 log_tokenization_for_conjunction(conjunction, tokenizer)
 
             c, options = compel.build_conditioning_tensor_for_conjunction(conjunction)
@@ -145,34 +140,23 @@ class CompelInvocation(BaseInvocation):
             ]
         )
 
-        conditioning_name = f"{context.graph_execution_state_id}_{self.id}_conditioning"
-        context.services.latents.save(conditioning_name, conditioning_data)
+        conditioning_name = context.conditioning.save(conditioning_data)
 
-        return ConditioningOutput(
-            conditioning=ConditioningField(
-                conditioning_name=conditioning_name,
-            ),
-        )
+        return ConditioningOutput.build(conditioning_name)
 
 
 class SDXLPromptInvocationBase:
     def run_clip_compel(
         self,
-        context: InvocationContext,
+        context: "InvocationContext",
         clip_field: ClipField,
         prompt: str,
         get_pooled: bool,
         lora_prefix: str,
         zero_on_empty: bool,
     ):
-        tokenizer_info = context.services.model_manager.get_model(
-            **clip_field.tokenizer.model_dump(),
-            context=context,
-        )
-        text_encoder_info = context.services.model_manager.get_model(
-            **clip_field.text_encoder.model_dump(),
-            context=context,
-        )
+        tokenizer_info = context.models.load(**clip_field.tokenizer.model_dump())
+        text_encoder_info = context.models.load(**clip_field.text_encoder.model_dump())
 
         # return zero on empty
         if prompt == "" and zero_on_empty:
@@ -196,14 +180,12 @@ class SDXLPromptInvocationBase:
 
         def _lora_loader():
             for lora in clip_field.loras:
-                lora_info = context.services.model_manager.get_model(
-                    **lora.model_dump(exclude={"weight"}), context=context
-                )
+                lora_info = context.models.load(**lora.model_dump(exclude={"weight"}))
                 yield (lora_info.context.model, lora.weight)
                 del lora_info
             return
 
-        # loras = [(context.services.model_manager.get_model(**lora.dict(exclude={"weight"})).context.model, lora.weight) for lora in self.clip.loras]
+        # loras = [(context.models.get(**lora.dict(exclude={"weight"})).context.model, lora.weight) for lora in self.clip.loras]
 
         ti_list = []
         for trigger in extract_ti_triggers_from_prompt(prompt):
@@ -212,11 +194,10 @@ class SDXLPromptInvocationBase:
                 ti_list.append(
                     (
                         name,
-                        context.services.model_manager.get_model(
+                        context.models.load(
                             model_name=name,
                             base_model=clip_field.text_encoder.base_model,
                             model_type=ModelType.TextualInversion,
-                            context=context,
                         ).context.model,
                     )
                 )
@@ -249,7 +230,7 @@ class SDXLPromptInvocationBase:
 
             conjunction = Compel.parse_prompt_string(prompt)
 
-            if context.services.configuration.log_tokenization:
+            if context.config.get().log_tokenization:
                 # TODO: better logging for and syntax
                 log_tokenization_for_conjunction(conjunction, tokenizer)
 
@@ -282,7 +263,7 @@ class SDXLPromptInvocationBase:
     title="SDXL Prompt",
     tags=["sdxl", "compel", "prompt"],
     category="conditioning",
-    version="1.0.0",
+    version="1.0.1",
 )
 class SDXLCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase):
     """Parse prompt using compel package to conditioning."""
@@ -307,7 +288,7 @@ class SDXLCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase):
     clip2: ClipField = InputField(description=FieldDescriptions.clip, input=Input.Connection, title="CLIP 2")
 
     @torch.no_grad()
-    def invoke(self, context: InvocationContext) -> ConditioningOutput:
+    def invoke(self, context) -> ConditioningOutput:
         c1, c1_pooled, ec1 = self.run_clip_compel(
             context, self.clip, self.prompt, False, "lora_te1_", zero_on_empty=True
         )
@@ -364,14 +345,9 @@ class SDXLCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase):
             ]
         )
 
-        conditioning_name = f"{context.graph_execution_state_id}_{self.id}_conditioning"
-        context.services.latents.save(conditioning_name, conditioning_data)
+        conditioning_name = context.conditioning.save(conditioning_data)
 
-        return ConditioningOutput(
-            conditioning=ConditioningField(
-                conditioning_name=conditioning_name,
-            ),
-        )
+        return ConditioningOutput.build(conditioning_name)
 
 
 @invocation(
@@ -379,7 +355,7 @@ class SDXLCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase):
     title="SDXL Refiner Prompt",
     tags=["sdxl", "compel", "prompt"],
     category="conditioning",
-    version="1.0.0",
+    version="1.0.1",
 )
 class SDXLRefinerCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase):
     """Parse prompt using compel package to conditioning."""
@@ -397,7 +373,7 @@ class SDXLRefinerCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase
     clip2: ClipField = InputField(description=FieldDescriptions.clip, input=Input.Connection)
 
     @torch.no_grad()
-    def invoke(self, context: InvocationContext) -> ConditioningOutput:
+    def invoke(self, context) -> ConditioningOutput:
         # TODO: if there will appear lora for refiner - write proper prefix
         c2, c2_pooled, ec2 = self.run_clip_compel(context, self.clip2, self.style, True, "<NONE>", zero_on_empty=False)
 
@@ -417,14 +393,9 @@ class SDXLRefinerCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase
             ]
         )
 
-        conditioning_name = f"{context.graph_execution_state_id}_{self.id}_conditioning"
-        context.services.latents.save(conditioning_name, conditioning_data)
+        conditioning_name = context.conditioning.save(conditioning_data)
 
-        return ConditioningOutput(
-            conditioning=ConditioningField(
-                conditioning_name=conditioning_name,
-            ),
-        )
+        return ConditioningOutput.build(conditioning_name)
 
 
 @invocation_output("clip_skip_output")
@@ -447,7 +418,7 @@ class ClipSkipInvocation(BaseInvocation):
     clip: ClipField = InputField(description=FieldDescriptions.clip, input=Input.Connection, title="CLIP")
     skipped_layers: int = InputField(default=0, description=FieldDescriptions.skipped_layers)
 
-    def invoke(self, context: InvocationContext) -> ClipSkipInvocationOutput:
+    def invoke(self, context) -> ClipSkipInvocationOutput:
         self.clip.skipped_layers += self.skipped_layers
         return ClipSkipInvocationOutput(
             clip=self.clip,
diff --git a/invokeai/app/invocations/controlnet_image_processors.py b/invokeai/app/invocations/controlnet_image_processors.py
index 9b652b8eee..3797722c93 100644
--- a/invokeai/app/invocations/controlnet_image_processors.py
+++ b/invokeai/app/invocations/controlnet_image_processors.py
@@ -25,18 +25,17 @@ from controlnet_aux.util import HWC3, ade_palette
 from PIL import Image
 from pydantic import BaseModel, ConfigDict, Field, field_validator, model_validator
 
-from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField, WithMetadata
-from invokeai.app.invocations.primitives import ImageField, ImageOutput
+from invokeai.app.invocations.baseinvocation import WithMetadata
+from invokeai.app.invocations.fields import FieldDescriptions, ImageField, Input, InputField, OutputField
+from invokeai.app.invocations.primitives import ImageOutput
 from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
-from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
 from invokeai.backend.image_util.depth_anything import DepthAnythingDetector
 from invokeai.backend.image_util.dw_openpose import DWOpenposeDetector
+from invokeai.backend.model_management.models.base import BaseModelType
 
-from ...backend.model_management import BaseModelType
 from .baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
-    InvocationContext,
     invocation,
     invocation_output,
 )
@@ -121,7 +120,7 @@ class ControlNetInvocation(BaseInvocation):
         validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
         return self
 
-    def invoke(self, context: InvocationContext) -> ControlOutput:
+    def invoke(self, context) -> ControlOutput:
         return ControlOutput(
             control=ControlField(
                 image=self.image,
@@ -145,23 +144,14 @@ class ImageProcessorInvocation(BaseInvocation, WithMetadata):
         # superclass just passes through image without processing
         return image
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        raw_image = context.services.images.get_pil_image(self.image.image_name)
+    def invoke(self, context) -> ImageOutput:
+        raw_image = context.images.get_pil(self.image.image_name)
         # image type should be PIL.PngImagePlugin.PngImageFile ?
         processed_image = self.run_processor(raw_image)
 
         # currently can't see processed image in node UI without a showImage node,
         #    so for now setting image_type to RESULT instead of INTERMEDIATE so will get saved in gallery
-        image_dto = context.services.images.create(
-            image=processed_image,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.CONTROL,
-            session_id=context.graph_execution_state_id,
-            node_id=self.id,
-            is_intermediate=self.is_intermediate,
-            metadata=self.metadata,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=processed_image)
 
         """Builds an ImageOutput and its ImageField"""
         processed_image_field = ImageField(image_name=image_dto.image_name)
@@ -180,7 +170,7 @@ class ImageProcessorInvocation(BaseInvocation, WithMetadata):
     title="Canny Processor",
     tags=["controlnet", "canny"],
     category="controlnet",
-    version="1.2.0",
+    version="1.2.1",
 )
 class CannyImageProcessorInvocation(ImageProcessorInvocation):
     """Canny edge detection for ControlNet"""
@@ -203,7 +193,7 @@ class CannyImageProcessorInvocation(ImageProcessorInvocation):
     title="HED (softedge) Processor",
     tags=["controlnet", "hed", "softedge"],
     category="controlnet",
-    version="1.2.0",
+    version="1.2.1",
 )
 class HedImageProcessorInvocation(ImageProcessorInvocation):
     """Applies HED edge detection to image"""
@@ -232,7 +222,7 @@ class HedImageProcessorInvocation(ImageProcessorInvocation):
     title="Lineart Processor",
     tags=["controlnet", "lineart"],
     category="controlnet",
-    version="1.2.0",
+    version="1.2.1",
 )
 class LineartImageProcessorInvocation(ImageProcessorInvocation):
     """Applies line art processing to image"""
@@ -254,7 +244,7 @@ class LineartImageProcessorInvocation(ImageProcessorInvocation):
     title="Lineart Anime Processor",
     tags=["controlnet", "lineart", "anime"],
     category="controlnet",
-    version="1.2.0",
+    version="1.2.1",
 )
 class LineartAnimeImageProcessorInvocation(ImageProcessorInvocation):
     """Applies line art anime processing to image"""
@@ -277,7 +267,7 @@ class LineartAnimeImageProcessorInvocation(ImageProcessorInvocation):
     title="Midas Depth Processor",
     tags=["controlnet", "midas"],
     category="controlnet",
-    version="1.2.0",
+    version="1.2.1",
 )
 class MidasDepthImageProcessorInvocation(ImageProcessorInvocation):
     """Applies Midas depth processing to image"""
@@ -304,7 +294,7 @@ class MidasDepthImageProcessorInvocation(ImageProcessorInvocation):
     title="Normal BAE Processor",
     tags=["controlnet"],
     category="controlnet",
-    version="1.2.0",
+    version="1.2.1",
 )
 class NormalbaeImageProcessorInvocation(ImageProcessorInvocation):
     """Applies NormalBae processing to image"""
@@ -321,7 +311,7 @@ class NormalbaeImageProcessorInvocation(ImageProcessorInvocation):
 
 
 @invocation(
-    "mlsd_image_processor", title="MLSD Processor", tags=["controlnet", "mlsd"], category="controlnet", version="1.2.0"
+    "mlsd_image_processor", title="MLSD Processor", tags=["controlnet", "mlsd"], category="controlnet", version="1.2.1"
 )
 class MlsdImageProcessorInvocation(ImageProcessorInvocation):
     """Applies MLSD processing to image"""
@@ -344,7 +334,7 @@ class MlsdImageProcessorInvocation(ImageProcessorInvocation):
 
 
 @invocation(
-    "pidi_image_processor", title="PIDI Processor", tags=["controlnet", "pidi"], category="controlnet", version="1.2.0"
+    "pidi_image_processor", title="PIDI Processor", tags=["controlnet", "pidi"], category="controlnet", version="1.2.1"
 )
 class PidiImageProcessorInvocation(ImageProcessorInvocation):
     """Applies PIDI processing to image"""
@@ -371,7 +361,7 @@ class PidiImageProcessorInvocation(ImageProcessorInvocation):
     title="Content Shuffle Processor",
     tags=["controlnet", "contentshuffle"],
     category="controlnet",
-    version="1.2.0",
+    version="1.2.1",
 )
 class ContentShuffleImageProcessorInvocation(ImageProcessorInvocation):
     """Applies content shuffle processing to image"""
@@ -401,7 +391,7 @@ class ContentShuffleImageProcessorInvocation(ImageProcessorInvocation):
     title="Zoe (Depth) Processor",
     tags=["controlnet", "zoe", "depth"],
     category="controlnet",
-    version="1.2.0",
+    version="1.2.1",
 )
 class ZoeDepthImageProcessorInvocation(ImageProcessorInvocation):
     """Applies Zoe depth processing to image"""
@@ -417,7 +407,7 @@ class ZoeDepthImageProcessorInvocation(ImageProcessorInvocation):
     title="Mediapipe Face Processor",
     tags=["controlnet", "mediapipe", "face"],
     category="controlnet",
-    version="1.2.0",
+    version="1.2.1",
 )
 class MediapipeFaceProcessorInvocation(ImageProcessorInvocation):
     """Applies mediapipe face processing to image"""
@@ -440,7 +430,7 @@ class MediapipeFaceProcessorInvocation(ImageProcessorInvocation):
     title="Leres (Depth) Processor",
     tags=["controlnet", "leres", "depth"],
     category="controlnet",
-    version="1.2.0",
+    version="1.2.1",
 )
 class LeresImageProcessorInvocation(ImageProcessorInvocation):
     """Applies leres processing to image"""
@@ -469,7 +459,7 @@ class LeresImageProcessorInvocation(ImageProcessorInvocation):
     title="Tile Resample Processor",
     tags=["controlnet", "tile"],
     category="controlnet",
-    version="1.2.0",
+    version="1.2.1",
 )
 class TileResamplerProcessorInvocation(ImageProcessorInvocation):
     """Tile resampler processor"""
@@ -509,7 +499,7 @@ class TileResamplerProcessorInvocation(ImageProcessorInvocation):
     title="Segment Anything Processor",
     tags=["controlnet", "segmentanything"],
     category="controlnet",
-    version="1.2.0",
+    version="1.2.1",
 )
 class SegmentAnythingProcessorInvocation(ImageProcessorInvocation):
     """Applies segment anything processing to image"""
@@ -551,7 +541,7 @@ class SamDetectorReproducibleColors(SamDetector):
     title="Color Map Processor",
     tags=["controlnet"],
     category="controlnet",
-    version="1.2.0",
+    version="1.2.1",
 )
 class ColorMapImageProcessorInvocation(ImageProcessorInvocation):
     """Generates a color map from the provided image"""
diff --git a/invokeai/app/invocations/cv.py b/invokeai/app/invocations/cv.py
index 5865338e19..375b18f9c5 100644
--- a/invokeai/app/invocations/cv.py
+++ b/invokeai/app/invocations/cv.py
@@ -5,23 +5,23 @@ import cv2 as cv
 import numpy
 from PIL import Image, ImageOps
 
-from invokeai.app.invocations.primitives import ImageField, ImageOutput
-from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
+from invokeai.app.invocations.fields import ImageField
+from invokeai.app.invocations.primitives import ImageOutput
 
-from .baseinvocation import BaseInvocation, InvocationContext, invocation
+from .baseinvocation import BaseInvocation, invocation
 from .fields import InputField, WithMetadata
 
 
-@invocation("cv_inpaint", title="OpenCV Inpaint", tags=["opencv", "inpaint"], category="inpaint", version="1.2.0")
+@invocation("cv_inpaint", title="OpenCV Inpaint", tags=["opencv", "inpaint"], category="inpaint", version="1.2.1")
 class CvInpaintInvocation(BaseInvocation, WithMetadata):
     """Simple inpaint using opencv."""
 
     image: ImageField = InputField(description="The image to inpaint")
     mask: ImageField = InputField(description="The mask to use when inpainting")
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(self.image.image_name)
-        mask = context.services.images.get_pil_image(self.mask.image_name)
+    def invoke(self, context) -> ImageOutput:
+        image = context.images.get_pil(self.image.image_name)
+        mask = context.images.get_pil(self.mask.image_name)
 
         # Convert to cv image/mask
         # TODO: consider making these utility functions
@@ -35,18 +35,6 @@ class CvInpaintInvocation(BaseInvocation, WithMetadata):
         # TODO: consider making a utility function
         image_inpainted = Image.fromarray(cv.cvtColor(cv_inpainted, cv.COLOR_BGR2RGB))
 
-        image_dto = context.services.images.create(
-            image=image_inpainted,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=image_inpainted)
 
-        return ImageOutput(
-            image=ImageField(image_name=image_dto.image_name),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
+        return ImageOutput.build(image_dto)
diff --git a/invokeai/app/invocations/facetools.py b/invokeai/app/invocations/facetools.py
index 13f1066ec3..2c92e28cfe 100644
--- a/invokeai/app/invocations/facetools.py
+++ b/invokeai/app/invocations/facetools.py
@@ -1,7 +1,7 @@
 import math
 import re
 from pathlib import Path
-from typing import Optional, TypedDict
+from typing import TYPE_CHECKING, Optional, TypedDict
 
 import cv2
 import numpy as np
@@ -13,13 +13,16 @@ from pydantic import field_validator
 import invokeai.assets.fonts as font_assets
 from invokeai.app.invocations.baseinvocation import (
     BaseInvocation,
-    InvocationContext,
+    WithMetadata,
     invocation,
     invocation_output,
 )
-from invokeai.app.invocations.fields import InputField, OutputField, WithMetadata
-from invokeai.app.invocations.primitives import ImageField, ImageOutput
-from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
+from invokeai.app.invocations.fields import ImageField, InputField, OutputField
+from invokeai.app.invocations.primitives import ImageOutput
+from invokeai.app.services.image_records.image_records_common import ImageCategory
+
+if TYPE_CHECKING:
+    from invokeai.app.services.shared.invocation_context import InvocationContext
 
 
 @invocation_output("face_mask_output")
@@ -174,7 +177,7 @@ def prepare_faces_list(
 
 
 def generate_face_box_mask(
-    context: InvocationContext,
+    context: "InvocationContext",
     minimum_confidence: float,
     x_offset: float,
     y_offset: float,
@@ -273,7 +276,7 @@ def generate_face_box_mask(
 
 
 def extract_face(
-    context: InvocationContext,
+    context: "InvocationContext",
     image: ImageType,
     face: FaceResultData,
     padding: int,
@@ -304,37 +307,37 @@ def extract_face(
 
     # Adjust the crop boundaries to stay within the original image's dimensions
     if x_min < 0:
-        context.services.logger.warning("FaceTools --> -X-axis padding reached image edge.")
+        context.logger.warning("FaceTools --> -X-axis padding reached image edge.")
         x_max -= x_min
         x_min = 0
     elif x_max > mask.width:
-        context.services.logger.warning("FaceTools --> +X-axis padding reached image edge.")
+        context.logger.warning("FaceTools --> +X-axis padding reached image edge.")
         x_min -= x_max - mask.width
         x_max = mask.width
 
     if y_min < 0:
-        context.services.logger.warning("FaceTools --> +Y-axis padding reached image edge.")
+        context.logger.warning("FaceTools --> +Y-axis padding reached image edge.")
         y_max -= y_min
         y_min = 0
     elif y_max > mask.height:
-        context.services.logger.warning("FaceTools --> -Y-axis padding reached image edge.")
+        context.logger.warning("FaceTools --> -Y-axis padding reached image edge.")
         y_min -= y_max - mask.height
         y_max = mask.height
 
     # Ensure the crop is square and adjust the boundaries if needed
     if x_max - x_min != crop_size:
-        context.services.logger.warning("FaceTools --> Limiting x-axis padding to constrain bounding box to a square.")
+        context.logger.warning("FaceTools --> Limiting x-axis padding to constrain bounding box to a square.")
         diff = crop_size - (x_max - x_min)
         x_min -= diff // 2
         x_max += diff - diff // 2
 
     if y_max - y_min != crop_size:
-        context.services.logger.warning("FaceTools --> Limiting y-axis padding to constrain bounding box to a square.")
+        context.logger.warning("FaceTools --> Limiting y-axis padding to constrain bounding box to a square.")
         diff = crop_size - (y_max - y_min)
         y_min -= diff // 2
         y_max += diff - diff // 2
 
-    context.services.logger.info(f"FaceTools --> Calculated bounding box (8 multiple): {crop_size}")
+    context.logger.info(f"FaceTools --> Calculated bounding box (8 multiple): {crop_size}")
 
     # Crop the output image to the specified size with the center of the face mesh as the center.
     mask = mask.crop((x_min, y_min, x_max, y_max))
@@ -354,7 +357,7 @@ def extract_face(
 
 
 def get_faces_list(
-    context: InvocationContext,
+    context: "InvocationContext",
     image: ImageType,
     should_chunk: bool,
     minimum_confidence: float,
@@ -366,7 +369,7 @@ def get_faces_list(
 
     # Generate the face box mask and get the center of the face.
     if not should_chunk:
-        context.services.logger.info("FaceTools --> Attempting full image face detection.")
+        context.logger.info("FaceTools --> Attempting full image face detection.")
         result = generate_face_box_mask(
             context=context,
             minimum_confidence=minimum_confidence,
@@ -378,7 +381,7 @@ def get_faces_list(
             draw_mesh=draw_mesh,
         )
     if should_chunk or len(result) == 0:
-        context.services.logger.info("FaceTools --> Chunking image (chunk toggled on, or no face found in full image).")
+        context.logger.info("FaceTools --> Chunking image (chunk toggled on, or no face found in full image).")
         width, height = image.size
         image_chunks = []
         x_offsets = []
@@ -397,7 +400,7 @@ def get_faces_list(
                 x_offsets.append(x)
                 y_offsets.append(0)
                 fx += increment
-                context.services.logger.info(f"FaceTools --> Chunk starting at x = {x}")
+                context.logger.info(f"FaceTools --> Chunk starting at x = {x}")
         elif height > width:
             # Portrait - slice the image vertically
             fy = 0.0
@@ -409,10 +412,10 @@ def get_faces_list(
                 x_offsets.append(0)
                 y_offsets.append(y)
                 fy += increment
-                context.services.logger.info(f"FaceTools --> Chunk starting at y = {y}")
+                context.logger.info(f"FaceTools --> Chunk starting at y = {y}")
 
         for idx in range(len(image_chunks)):
-            context.services.logger.info(f"FaceTools --> Evaluating faces in chunk {idx}")
+            context.logger.info(f"FaceTools --> Evaluating faces in chunk {idx}")
             result = result + generate_face_box_mask(
                 context=context,
                 minimum_confidence=minimum_confidence,
@@ -426,7 +429,7 @@ def get_faces_list(
 
         if len(result) == 0:
             # Give up
-            context.services.logger.warning(
+            context.logger.warning(
                 "FaceTools --> No face detected in chunked input image. Passing through original image."
             )
 
@@ -435,7 +438,7 @@ def get_faces_list(
     return all_faces
 
 
-@invocation("face_off", title="FaceOff", tags=["image", "faceoff", "face", "mask"], category="image", version="1.2.0")
+@invocation("face_off", title="FaceOff", tags=["image", "faceoff", "face", "mask"], category="image", version="1.2.1")
 class FaceOffInvocation(BaseInvocation, WithMetadata):
     """Bound, extract, and mask a face from an image using MediaPipe detection"""
 
@@ -456,7 +459,7 @@ class FaceOffInvocation(BaseInvocation, WithMetadata):
         description="Whether to bypass full image face detection and default to image chunking. Chunking will occur if no faces are found in the full image.",
     )
 
-    def faceoff(self, context: InvocationContext, image: ImageType) -> Optional[ExtractFaceData]:
+    def faceoff(self, context: "InvocationContext", image: ImageType) -> Optional[ExtractFaceData]:
         all_faces = get_faces_list(
             context=context,
             image=image,
@@ -468,11 +471,11 @@ class FaceOffInvocation(BaseInvocation, WithMetadata):
         )
 
         if len(all_faces) == 0:
-            context.services.logger.warning("FaceOff --> No faces detected. Passing through original image.")
+            context.logger.warning("FaceOff --> No faces detected. Passing through original image.")
             return None
 
         if self.face_id > len(all_faces) - 1:
-            context.services.logger.warning(
+            context.logger.warning(
                 f"FaceOff --> Face ID {self.face_id} is outside of the number of faces detected ({len(all_faces)}). Passing through original image."
             )
             return None
@@ -483,8 +486,8 @@ class FaceOffInvocation(BaseInvocation, WithMetadata):
 
         return face_data
 
-    def invoke(self, context: InvocationContext) -> FaceOffOutput:
-        image = context.services.images.get_pil_image(self.image.image_name)
+    def invoke(self, context) -> FaceOffOutput:
+        image = context.images.get_pil(self.image.image_name)
         result = self.faceoff(context=context, image=image)
 
         if result is None:
@@ -498,24 +501,9 @@ class FaceOffInvocation(BaseInvocation, WithMetadata):
             x = result["x_min"]
             y = result["y_min"]
 
-        image_dto = context.services.images.create(
-            image=result_image,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=result_image)
 
-        mask_dto = context.services.images.create(
-            image=result_mask,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.MASK,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-        )
+        mask_dto = context.images.save(image=result_mask, image_category=ImageCategory.MASK)
 
         output = FaceOffOutput(
             image=ImageField(image_name=image_dto.image_name),
@@ -529,7 +517,7 @@ class FaceOffInvocation(BaseInvocation, WithMetadata):
         return output
 
 
-@invocation("face_mask_detection", title="FaceMask", tags=["image", "face", "mask"], category="image", version="1.2.0")
+@invocation("face_mask_detection", title="FaceMask", tags=["image", "face", "mask"], category="image", version="1.2.1")
 class FaceMaskInvocation(BaseInvocation, WithMetadata):
     """Face mask creation using mediapipe face detection"""
 
@@ -556,7 +544,7 @@ class FaceMaskInvocation(BaseInvocation, WithMetadata):
             raise ValueError('Face IDs must be a comma-separated list of integers (e.g. "1,2,3")')
         return v
 
-    def facemask(self, context: InvocationContext, image: ImageType) -> FaceMaskResult:
+    def facemask(self, context: "InvocationContext", image: ImageType) -> FaceMaskResult:
         all_faces = get_faces_list(
             context=context,
             image=image,
@@ -578,7 +566,7 @@ class FaceMaskInvocation(BaseInvocation, WithMetadata):
 
             if len(intersected_face_ids) == 0:
                 id_range_str = ",".join([str(id) for id in id_range])
-                context.services.logger.warning(
+                context.logger.warning(
                     f"Face IDs must be in range of detected faces - requested {self.face_ids}, detected {id_range_str}. Passing through original image."
                 )
                 return FaceMaskResult(
@@ -613,28 +601,13 @@ class FaceMaskInvocation(BaseInvocation, WithMetadata):
             mask=mask_pil,
         )
 
-    def invoke(self, context: InvocationContext) -> FaceMaskOutput:
-        image = context.services.images.get_pil_image(self.image.image_name)
+    def invoke(self, context) -> FaceMaskOutput:
+        image = context.images.get_pil(self.image.image_name)
         result = self.facemask(context=context, image=image)
 
-        image_dto = context.services.images.create(
-            image=result["image"],
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=result["image"])
 
-        mask_dto = context.services.images.create(
-            image=result["mask"],
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.MASK,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-        )
+        mask_dto = context.images.save(image=result["mask"], image_category=ImageCategory.MASK)
 
         output = FaceMaskOutput(
             image=ImageField(image_name=image_dto.image_name),
@@ -647,7 +620,7 @@ class FaceMaskInvocation(BaseInvocation, WithMetadata):
 
 
 @invocation(
-    "face_identifier", title="FaceIdentifier", tags=["image", "face", "identifier"], category="image", version="1.2.0"
+    "face_identifier", title="FaceIdentifier", tags=["image", "face", "identifier"], category="image", version="1.2.1"
 )
 class FaceIdentifierInvocation(BaseInvocation, WithMetadata):
     """Outputs an image with detected face IDs printed on each face. For use with other FaceTools."""
@@ -661,7 +634,7 @@ class FaceIdentifierInvocation(BaseInvocation, WithMetadata):
         description="Whether to bypass full image face detection and default to image chunking. Chunking will occur if no faces are found in the full image.",
     )
 
-    def faceidentifier(self, context: InvocationContext, image: ImageType) -> ImageType:
+    def faceidentifier(self, context: "InvocationContext", image: ImageType) -> ImageType:
         image = image.copy()
 
         all_faces = get_faces_list(
@@ -702,22 +675,10 @@ class FaceIdentifierInvocation(BaseInvocation, WithMetadata):
 
         return image
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(self.image.image_name)
+    def invoke(self, context) -> ImageOutput:
+        image = context.images.get_pil(self.image.image_name)
         result_image = self.faceidentifier(context=context, image=image)
 
-        image_dto = context.services.images.create(
-            image=result_image,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=result_image)
 
-        return ImageOutput(
-            image=ImageField(image_name=image_dto.image_name),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
+        return ImageOutput.build(image_dto)
diff --git a/invokeai/app/invocations/fields.py b/invokeai/app/invocations/fields.py
index 0cce8e3c6b..566babbb6b 100644
--- a/invokeai/app/invocations/fields.py
+++ b/invokeai/app/invocations/fields.py
@@ -1,11 +1,13 @@
+from dataclasses import dataclass
 from enum import Enum
-from typing import Any, Callable, Optional
+from typing import Any, Callable, List, Optional, Tuple
 
 from pydantic import BaseModel, ConfigDict, Field, RootModel, TypeAdapter
 from pydantic.fields import _Unset
 from pydantic_core import PydanticUndefined
 
 from invokeai.app.util.metaenum import MetaEnum
+from invokeai.backend.stable_diffusion.diffusion.conditioning_data import BasicConditioningInfo
 from invokeai.backend.util.logging import InvokeAILogger
 
 logger = InvokeAILogger.get_logger()
@@ -255,6 +257,10 @@ class InputFieldJSONSchemaExtra(BaseModel):
 
 
 class WithMetadata(BaseModel):
+    """
+    Inherit from this class if your node needs a metadata input field.
+    """
+
     metadata: Optional[MetadataField] = Field(
         default=None,
         description=FieldDescriptions.metadata,
@@ -498,4 +504,53 @@ def OutputField(
             field_kind=FieldKind.Output,
         ).model_dump(exclude_none=True),
     )
+
+
+class ImageField(BaseModel):
+    """An image primitive field"""
+
+    image_name: str = Field(description="The name of the image")
+
+
+class BoardField(BaseModel):
+    """A board primitive field"""
+
+    board_id: str = Field(description="The id of the board")
+
+
+class DenoiseMaskField(BaseModel):
+    """An inpaint mask field"""
+
+    mask_name: str = Field(description="The name of the mask image")
+    masked_latents_name: Optional[str] = Field(default=None, description="The name of the masked image latents")
+
+
+class LatentsField(BaseModel):
+    """A latents tensor primitive field"""
+
+    latents_name: str = Field(description="The name of the latents")
+    seed: Optional[int] = Field(default=None, description="Seed used to generate this latents")
+
+
+class ColorField(BaseModel):
+    """A color primitive field"""
+
+    r: int = Field(ge=0, le=255, description="The red component")
+    g: int = Field(ge=0, le=255, description="The green component")
+    b: int = Field(ge=0, le=255, description="The blue component")
+    a: int = Field(ge=0, le=255, description="The alpha component")
+
+    def tuple(self) -> Tuple[int, int, int, int]:
+        return (self.r, self.g, self.b, self.a)
+
+
+@dataclass
+class ConditioningFieldData:
+    conditionings: List[BasicConditioningInfo]
+
+
+class ConditioningField(BaseModel):
+    """A conditioning tensor primitive value"""
+
+    conditioning_name: str = Field(description="The name of conditioning tensor")
     # endregion
diff --git a/invokeai/app/invocations/image.py b/invokeai/app/invocations/image.py
index 16d0f33dda..10ebd97ace 100644
--- a/invokeai/app/invocations/image.py
+++ b/invokeai/app/invocations/image.py
@@ -7,30 +7,36 @@ import cv2
 import numpy
 from PIL import Image, ImageChops, ImageFilter, ImageOps
 
-from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, WithMetadata
-from invokeai.app.invocations.primitives import BoardField, ColorField, ImageField, ImageOutput
-from invokeai.app.services.image_records.image_records_common import ImageCategory, ImageRecordChanges, ResourceOrigin
+from invokeai.app.invocations.baseinvocation import WithMetadata
+from invokeai.app.invocations.fields import (
+    BoardField,
+    ColorField,
+    FieldDescriptions,
+    ImageField,
+    Input,
+    InputField,
+)
+from invokeai.app.invocations.primitives import ImageOutput
+from invokeai.app.services.image_records.image_records_common import ImageCategory
 from invokeai.backend.image_util.invisible_watermark import InvisibleWatermark
 from invokeai.backend.image_util.safety_checker import SafetyChecker
 
 from .baseinvocation import (
     BaseInvocation,
     Classification,
-    InvocationContext,
     invocation,
 )
 
 
-@invocation("show_image", title="Show Image", tags=["image"], category="image", version="1.0.0")
+@invocation("show_image", title="Show Image", tags=["image"], category="image", version="1.0.1")
 class ShowImageInvocation(BaseInvocation):
     """Displays a provided image using the OS image viewer, and passes it forward in the pipeline."""
 
     image: ImageField = InputField(description="The image to show")
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(self.image.image_name)
-        if image:
-            image.show()
+    def invoke(self, context) -> ImageOutput:
+        image = context.images.get_pil(self.image.image_name)
+        image.show()
 
         # TODO: how to handle failure?
 
@@ -46,7 +52,7 @@ class ShowImageInvocation(BaseInvocation):
     title="Blank Image",
     tags=["image"],
     category="image",
-    version="1.2.0",
+    version="1.2.1",
 )
 class BlankImageInvocation(BaseInvocation, WithMetadata):
     """Creates a blank image and forwards it to the pipeline"""
@@ -56,25 +62,12 @@ class BlankImageInvocation(BaseInvocation, WithMetadata):
     mode: Literal["RGB", "RGBA"] = InputField(default="RGB", description="The mode of the image")
     color: ColorField = InputField(default=ColorField(r=0, g=0, b=0, a=255), description="The color of the image")
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
+    def invoke(self, context) -> ImageOutput:
         image = Image.new(mode=self.mode, size=(self.width, self.height), color=self.color.tuple())
 
-        image_dto = context.services.images.create(
-            image=image,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-            metadata=self.metadata,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=image)
 
-        return ImageOutput(
-            image=ImageField(image_name=image_dto.image_name),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
+        return ImageOutput.build(image_dto)
 
 
 @invocation(
@@ -82,7 +75,7 @@ class BlankImageInvocation(BaseInvocation, WithMetadata):
     title="Crop Image",
     tags=["image", "crop"],
     category="image",
-    version="1.2.0",
+    version="1.2.1",
 )
 class ImageCropInvocation(BaseInvocation, WithMetadata):
     """Crops an image to a specified box. The box can be outside of the image."""
@@ -93,28 +86,15 @@ class ImageCropInvocation(BaseInvocation, WithMetadata):
     width: int = InputField(default=512, gt=0, description="The width of the crop rectangle")
     height: int = InputField(default=512, gt=0, description="The height of the crop rectangle")
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(self.image.image_name)
+    def invoke(self, context) -> ImageOutput:
+        image = context.images.get_pil(self.image.image_name)
 
         image_crop = Image.new(mode="RGBA", size=(self.width, self.height), color=(0, 0, 0, 0))
         image_crop.paste(image, (-self.x, -self.y))
 
-        image_dto = context.services.images.create(
-            image=image_crop,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-            metadata=self.metadata,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=image_crop)
 
-        return ImageOutput(
-            image=ImageField(image_name=image_dto.image_name),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
+        return ImageOutput.build(image_dto)
 
 
 @invocation(
@@ -145,8 +125,8 @@ class CenterPadCropInvocation(BaseInvocation):
         description="Number of pixels to pad/crop from the bottom (negative values crop inwards, positive values pad outwards)",
     )
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(self.image.image_name)
+    def invoke(self, context) -> ImageOutput:
+        image = context.images.get_pil(self.image.image_name)
 
         # Calculate and create new image dimensions
         new_width = image.width + self.right + self.left
@@ -156,20 +136,9 @@ class CenterPadCropInvocation(BaseInvocation):
         # Paste new image onto input
         image_crop.paste(image, (self.left, self.top))
 
-        image_dto = context.services.images.create(
-            image=image_crop,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-        )
+        image_dto = context.images.save(image=image_crop)
 
-        return ImageOutput(
-            image=ImageField(image_name=image_dto.image_name),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
+        return ImageOutput.build(image_dto)
 
 
 @invocation(
@@ -177,7 +146,7 @@ class CenterPadCropInvocation(BaseInvocation):
     title="Paste Image",
     tags=["image", "paste"],
     category="image",
-    version="1.2.0",
+    version="1.2.1",
 )
 class ImagePasteInvocation(BaseInvocation, WithMetadata):
     """Pastes an image into another image."""
@@ -192,12 +161,12 @@ class ImagePasteInvocation(BaseInvocation, WithMetadata):
     y: int = InputField(default=0, description="The top y coordinate at which to paste the image")
     crop: bool = InputField(default=False, description="Crop to base image dimensions")
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        base_image = context.services.images.get_pil_image(self.base_image.image_name)
-        image = context.services.images.get_pil_image(self.image.image_name)
+    def invoke(self, context) -> ImageOutput:
+        base_image = context.images.get_pil(self.base_image.image_name)
+        image = context.images.get_pil(self.image.image_name)
         mask = None
         if self.mask is not None:
-            mask = context.services.images.get_pil_image(self.mask.image_name)
+            mask = context.images.get_pil(self.mask.image_name)
             mask = ImageOps.invert(mask.convert("L"))
         # TODO: probably shouldn't invert mask here... should user be required to do it?
 
@@ -214,22 +183,9 @@ class ImagePasteInvocation(BaseInvocation, WithMetadata):
             base_w, base_h = base_image.size
             new_image = new_image.crop((abs(min_x), abs(min_y), abs(min_x) + base_w, abs(min_y) + base_h))
 
-        image_dto = context.services.images.create(
-            image=new_image,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-            metadata=self.metadata,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=new_image)
 
-        return ImageOutput(
-            image=ImageField(image_name=image_dto.image_name),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
+        return ImageOutput.build(image_dto)
 
 
 @invocation(
@@ -237,7 +193,7 @@ class ImagePasteInvocation(BaseInvocation, WithMetadata):
     title="Mask from Alpha",
     tags=["image", "mask"],
     category="image",
-    version="1.2.0",
+    version="1.2.1",
 )
 class MaskFromAlphaInvocation(BaseInvocation, WithMetadata):
     """Extracts the alpha channel of an image as a mask."""
@@ -245,29 +201,16 @@ class MaskFromAlphaInvocation(BaseInvocation, WithMetadata):
     image: ImageField = InputField(description="The image to create the mask from")
     invert: bool = InputField(default=False, description="Whether or not to invert the mask")
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(self.image.image_name)
+    def invoke(self, context) -> ImageOutput:
+        image = context.images.get_pil(self.image.image_name)
 
         image_mask = image.split()[-1]
         if self.invert:
             image_mask = ImageOps.invert(image_mask)
 
-        image_dto = context.services.images.create(
-            image=image_mask,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.MASK,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-            metadata=self.metadata,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=image_mask, image_category=ImageCategory.MASK)
 
-        return ImageOutput(
-            image=ImageField(image_name=image_dto.image_name),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
+        return ImageOutput.build(image_dto)
 
 
 @invocation(
@@ -275,7 +218,7 @@ class MaskFromAlphaInvocation(BaseInvocation, WithMetadata):
     title="Multiply Images",
     tags=["image", "multiply"],
     category="image",
-    version="1.2.0",
+    version="1.2.1",
 )
 class ImageMultiplyInvocation(BaseInvocation, WithMetadata):
     """Multiplies two images together using `PIL.ImageChops.multiply()`."""
@@ -283,28 +226,15 @@ class ImageMultiplyInvocation(BaseInvocation, WithMetadata):
     image1: ImageField = InputField(description="The first image to multiply")
     image2: ImageField = InputField(description="The second image to multiply")
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        image1 = context.services.images.get_pil_image(self.image1.image_name)
-        image2 = context.services.images.get_pil_image(self.image2.image_name)
+    def invoke(self, context) -> ImageOutput:
+        image1 = context.images.get_pil(self.image1.image_name)
+        image2 = context.images.get_pil(self.image2.image_name)
 
         multiply_image = ImageChops.multiply(image1, image2)
 
-        image_dto = context.services.images.create(
-            image=multiply_image,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-            metadata=self.metadata,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=multiply_image)
 
-        return ImageOutput(
-            image=ImageField(image_name=image_dto.image_name),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
+        return ImageOutput.build(image_dto)
 
 
 IMAGE_CHANNELS = Literal["A", "R", "G", "B"]
@@ -315,7 +245,7 @@ IMAGE_CHANNELS = Literal["A", "R", "G", "B"]
     title="Extract Image Channel",
     tags=["image", "channel"],
     category="image",
-    version="1.2.0",
+    version="1.2.1",
 )
 class ImageChannelInvocation(BaseInvocation, WithMetadata):
     """Gets a channel from an image."""
@@ -323,27 +253,14 @@ class ImageChannelInvocation(BaseInvocation, WithMetadata):
     image: ImageField = InputField(description="The image to get the channel from")
     channel: IMAGE_CHANNELS = InputField(default="A", description="The channel to get")
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(self.image.image_name)
+    def invoke(self, context) -> ImageOutput:
+        image = context.images.get_pil(self.image.image_name)
 
         channel_image = image.getchannel(self.channel)
 
-        image_dto = context.services.images.create(
-            image=channel_image,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-            metadata=self.metadata,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=channel_image)
 
-        return ImageOutput(
-            image=ImageField(image_name=image_dto.image_name),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
+        return ImageOutput.build(image_dto)
 
 
 IMAGE_MODES = Literal["L", "RGB", "RGBA", "CMYK", "YCbCr", "LAB", "HSV", "I", "F"]
@@ -354,7 +271,7 @@ IMAGE_MODES = Literal["L", "RGB", "RGBA", "CMYK", "YCbCr", "LAB", "HSV", "I", "F
     title="Convert Image Mode",
     tags=["image", "convert"],
     category="image",
-    version="1.2.0",
+    version="1.2.1",
 )
 class ImageConvertInvocation(BaseInvocation, WithMetadata):
     """Converts an image to a different mode."""
@@ -362,27 +279,14 @@ class ImageConvertInvocation(BaseInvocation, WithMetadata):
     image: ImageField = InputField(description="The image to convert")
     mode: IMAGE_MODES = InputField(default="L", description="The mode to convert to")
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(self.image.image_name)
+    def invoke(self, context) -> ImageOutput:
+        image = context.images.get_pil(self.image.image_name)
 
         converted_image = image.convert(self.mode)
 
-        image_dto = context.services.images.create(
-            image=converted_image,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-            metadata=self.metadata,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=converted_image)
 
-        return ImageOutput(
-            image=ImageField(image_name=image_dto.image_name),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
+        return ImageOutput.build(image_dto)
 
 
 @invocation(
@@ -390,7 +294,7 @@ class ImageConvertInvocation(BaseInvocation, WithMetadata):
     title="Blur Image",
     tags=["image", "blur"],
     category="image",
-    version="1.2.0",
+    version="1.2.1",
 )
 class ImageBlurInvocation(BaseInvocation, WithMetadata):
     """Blurs an image"""
@@ -400,30 +304,17 @@ class ImageBlurInvocation(BaseInvocation, WithMetadata):
     # Metadata
     blur_type: Literal["gaussian", "box"] = InputField(default="gaussian", description="The type of blur")
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(self.image.image_name)
+    def invoke(self, context) -> ImageOutput:
+        image = context.images.get_pil(self.image.image_name)
 
         blur = (
             ImageFilter.GaussianBlur(self.radius) if self.blur_type == "gaussian" else ImageFilter.BoxBlur(self.radius)
         )
         blur_image = image.filter(blur)
 
-        image_dto = context.services.images.create(
-            image=blur_image,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-            metadata=self.metadata,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=blur_image)
 
-        return ImageOutput(
-            image=ImageField(image_name=image_dto.image_name),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
+        return ImageOutput.build(image_dto)
 
 
 @invocation(
@@ -431,7 +322,7 @@ class ImageBlurInvocation(BaseInvocation, WithMetadata):
     title="Unsharp Mask",
     tags=["image", "unsharp_mask"],
     category="image",
-    version="1.2.0",
+    version="1.2.1",
     classification=Classification.Beta,
 )
 class UnsharpMaskInvocation(BaseInvocation, WithMetadata):
@@ -447,8 +338,8 @@ class UnsharpMaskInvocation(BaseInvocation, WithMetadata):
     def array_from_pil(self, img):
         return numpy.array(img) / 255
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(self.image.image_name)
+    def invoke(self, context) -> ImageOutput:
+        image = context.images.get_pil(self.image.image_name)
         mode = image.mode
 
         alpha_channel = image.getchannel("A") if mode == "RGBA" else None
@@ -466,16 +357,7 @@ class UnsharpMaskInvocation(BaseInvocation, WithMetadata):
         if alpha_channel is not None:
             image.putalpha(alpha_channel)
 
-        image_dto = context.services.images.create(
-            image=image,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-            metadata=self.metadata,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=image)
 
         return ImageOutput(
             image=ImageField(image_name=image_dto.image_name),
@@ -509,7 +391,7 @@ PIL_RESAMPLING_MAP = {
     title="Resize Image",
     tags=["image", "resize"],
     category="image",
-    version="1.2.0",
+    version="1.2.1",
 )
 class ImageResizeInvocation(BaseInvocation, WithMetadata):
     """Resizes an image to specific dimensions"""
@@ -519,8 +401,8 @@ class ImageResizeInvocation(BaseInvocation, WithMetadata):
     height: int = InputField(default=512, gt=0, description="The height to resize to (px)")
     resample_mode: PIL_RESAMPLING_MODES = InputField(default="bicubic", description="The resampling mode")
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(self.image.image_name)
+    def invoke(self, context) -> ImageOutput:
+        image = context.images.get_pil(self.image.image_name)
 
         resample_mode = PIL_RESAMPLING_MAP[self.resample_mode]
 
@@ -529,22 +411,9 @@ class ImageResizeInvocation(BaseInvocation, WithMetadata):
             resample=resample_mode,
         )
 
-        image_dto = context.services.images.create(
-            image=resize_image,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-            metadata=self.metadata,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=resize_image)
 
-        return ImageOutput(
-            image=ImageField(image_name=image_dto.image_name),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
+        return ImageOutput.build(image_dto)
 
 
 @invocation(
@@ -552,7 +421,7 @@ class ImageResizeInvocation(BaseInvocation, WithMetadata):
     title="Scale Image",
     tags=["image", "scale"],
     category="image",
-    version="1.2.0",
+    version="1.2.1",
 )
 class ImageScaleInvocation(BaseInvocation, WithMetadata):
     """Scales an image by a factor"""
@@ -565,8 +434,8 @@ class ImageScaleInvocation(BaseInvocation, WithMetadata):
     )
     resample_mode: PIL_RESAMPLING_MODES = InputField(default="bicubic", description="The resampling mode")
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(self.image.image_name)
+    def invoke(self, context) -> ImageOutput:
+        image = context.images.get_pil(self.image.image_name)
 
         resample_mode = PIL_RESAMPLING_MAP[self.resample_mode]
         width = int(image.width * self.scale_factor)
@@ -577,22 +446,9 @@ class ImageScaleInvocation(BaseInvocation, WithMetadata):
             resample=resample_mode,
         )
 
-        image_dto = context.services.images.create(
-            image=resize_image,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-            metadata=self.metadata,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=resize_image)
 
-        return ImageOutput(
-            image=ImageField(image_name=image_dto.image_name),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
+        return ImageOutput.build(image_dto)
 
 
 @invocation(
@@ -600,7 +456,7 @@ class ImageScaleInvocation(BaseInvocation, WithMetadata):
     title="Lerp Image",
     tags=["image", "lerp"],
     category="image",
-    version="1.2.0",
+    version="1.2.1",
 )
 class ImageLerpInvocation(BaseInvocation, WithMetadata):
     """Linear interpolation of all pixels of an image"""
@@ -609,30 +465,17 @@ class ImageLerpInvocation(BaseInvocation, WithMetadata):
     min: int = InputField(default=0, ge=0, le=255, description="The minimum output value")
     max: int = InputField(default=255, ge=0, le=255, description="The maximum output value")
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(self.image.image_name)
+    def invoke(self, context) -> ImageOutput:
+        image = context.images.get_pil(self.image.image_name)
 
         image_arr = numpy.asarray(image, dtype=numpy.float32) / 255
         image_arr = image_arr * (self.max - self.min) + self.min
 
         lerp_image = Image.fromarray(numpy.uint8(image_arr))
 
-        image_dto = context.services.images.create(
-            image=lerp_image,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-            metadata=self.metadata,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=lerp_image)
 
-        return ImageOutput(
-            image=ImageField(image_name=image_dto.image_name),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
+        return ImageOutput.build(image_dto)
 
 
 @invocation(
@@ -640,7 +483,7 @@ class ImageLerpInvocation(BaseInvocation, WithMetadata):
     title="Inverse Lerp Image",
     tags=["image", "ilerp"],
     category="image",
-    version="1.2.0",
+    version="1.2.1",
 )
 class ImageInverseLerpInvocation(BaseInvocation, WithMetadata):
     """Inverse linear interpolation of all pixels of an image"""
@@ -649,30 +492,17 @@ class ImageInverseLerpInvocation(BaseInvocation, WithMetadata):
     min: int = InputField(default=0, ge=0, le=255, description="The minimum input value")
     max: int = InputField(default=255, ge=0, le=255, description="The maximum input value")
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(self.image.image_name)
+    def invoke(self, context) -> ImageOutput:
+        image = context.images.get_pil(self.image.image_name)
 
         image_arr = numpy.asarray(image, dtype=numpy.float32)
         image_arr = numpy.minimum(numpy.maximum(image_arr - self.min, 0) / float(self.max - self.min), 1) * 255  # type: ignore [assignment]
 
         ilerp_image = Image.fromarray(numpy.uint8(image_arr))
 
-        image_dto = context.services.images.create(
-            image=ilerp_image,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-            metadata=self.metadata,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=ilerp_image)
 
-        return ImageOutput(
-            image=ImageField(image_name=image_dto.image_name),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
+        return ImageOutput.build(image_dto)
 
 
 @invocation(
@@ -680,17 +510,17 @@ class ImageInverseLerpInvocation(BaseInvocation, WithMetadata):
     title="Blur NSFW Image",
     tags=["image", "nsfw"],
     category="image",
-    version="1.2.0",
+    version="1.2.1",
 )
 class ImageNSFWBlurInvocation(BaseInvocation, WithMetadata):
     """Add blur to NSFW-flagged images"""
 
     image: ImageField = InputField(description="The image to check")
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(self.image.image_name)
+    def invoke(self, context) -> ImageOutput:
+        image = context.images.get_pil(self.image.image_name)
 
-        logger = context.services.logger
+        logger = context.logger
         logger.debug("Running NSFW checker")
         if SafetyChecker.has_nsfw_concept(image):
             logger.info("A potentially NSFW image has been detected. Image will be blurred.")
@@ -699,22 +529,9 @@ class ImageNSFWBlurInvocation(BaseInvocation, WithMetadata):
             blurry_image.paste(caution, (0, 0), caution)
             image = blurry_image
 
-        image_dto = context.services.images.create(
-            image=image,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-            metadata=self.metadata,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=image)
 
-        return ImageOutput(
-            image=ImageField(image_name=image_dto.image_name),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
+        return ImageOutput.build(image_dto)
 
     def _get_caution_img(self) -> Image.Image:
         import invokeai.app.assets.images as image_assets
@@ -728,7 +545,7 @@ class ImageNSFWBlurInvocation(BaseInvocation, WithMetadata):
     title="Add Invisible Watermark",
     tags=["image", "watermark"],
     category="image",
-    version="1.2.0",
+    version="1.2.1",
 )
 class ImageWatermarkInvocation(BaseInvocation, WithMetadata):
     """Add an invisible watermark to an image"""
@@ -736,25 +553,12 @@ class ImageWatermarkInvocation(BaseInvocation, WithMetadata):
     image: ImageField = InputField(description="The image to check")
     text: str = InputField(default="InvokeAI", description="Watermark text")
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(self.image.image_name)
+    def invoke(self, context) -> ImageOutput:
+        image = context.images.get_pil(self.image.image_name)
         new_image = InvisibleWatermark.add_watermark(image, self.text)
-        image_dto = context.services.images.create(
-            image=new_image,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-            metadata=self.metadata,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=new_image)
 
-        return ImageOutput(
-            image=ImageField(image_name=image_dto.image_name),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
+        return ImageOutput.build(image_dto)
 
 
 @invocation(
@@ -762,7 +566,7 @@ class ImageWatermarkInvocation(BaseInvocation, WithMetadata):
     title="Mask Edge",
     tags=["image", "mask", "inpaint"],
     category="image",
-    version="1.2.0",
+    version="1.2.1",
 )
 class MaskEdgeInvocation(BaseInvocation, WithMetadata):
     """Applies an edge mask to an image"""
@@ -775,8 +579,8 @@ class MaskEdgeInvocation(BaseInvocation, WithMetadata):
         description="Second threshold for the hysteresis procedure in Canny edge detection"
     )
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        mask = context.services.images.get_pil_image(self.image.image_name).convert("L")
+    def invoke(self, context) -> ImageOutput:
+        mask = context.images.get_pil(self.image.image_name).convert("L")
 
         npimg = numpy.asarray(mask, dtype=numpy.uint8)
         npgradient = numpy.uint8(255 * (1.0 - numpy.floor(numpy.abs(0.5 - numpy.float32(npimg) / 255.0) * 2.0)))
@@ -791,22 +595,9 @@ class MaskEdgeInvocation(BaseInvocation, WithMetadata):
 
         new_mask = ImageOps.invert(new_mask)
 
-        image_dto = context.services.images.create(
-            image=new_mask,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.MASK,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-            metadata=self.metadata,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=new_mask, image_category=ImageCategory.MASK)
 
-        return ImageOutput(
-            image=ImageField(image_name=image_dto.image_name),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
+        return ImageOutput.build(image_dto)
 
 
 @invocation(
@@ -814,7 +605,7 @@ class MaskEdgeInvocation(BaseInvocation, WithMetadata):
     title="Combine Masks",
     tags=["image", "mask", "multiply"],
     category="image",
-    version="1.2.0",
+    version="1.2.1",
 )
 class MaskCombineInvocation(BaseInvocation, WithMetadata):
     """Combine two masks together by multiplying them using `PIL.ImageChops.multiply()`."""
@@ -822,28 +613,15 @@ class MaskCombineInvocation(BaseInvocation, WithMetadata):
     mask1: ImageField = InputField(description="The first mask to combine")
     mask2: ImageField = InputField(description="The second image to combine")
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        mask1 = context.services.images.get_pil_image(self.mask1.image_name).convert("L")
-        mask2 = context.services.images.get_pil_image(self.mask2.image_name).convert("L")
+    def invoke(self, context) -> ImageOutput:
+        mask1 = context.images.get_pil(self.mask1.image_name).convert("L")
+        mask2 = context.images.get_pil(self.mask2.image_name).convert("L")
 
         combined_mask = ImageChops.multiply(mask1, mask2)
 
-        image_dto = context.services.images.create(
-            image=combined_mask,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-            metadata=self.metadata,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=combined_mask, image_category=ImageCategory.MASK)
 
-        return ImageOutput(
-            image=ImageField(image_name=image_dto.image_name),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
+        return ImageOutput.build(image_dto)
 
 
 @invocation(
@@ -851,7 +629,7 @@ class MaskCombineInvocation(BaseInvocation, WithMetadata):
     title="Color Correct",
     tags=["image", "color"],
     category="image",
-    version="1.2.0",
+    version="1.2.1",
 )
 class ColorCorrectInvocation(BaseInvocation, WithMetadata):
     """
@@ -864,14 +642,14 @@ class ColorCorrectInvocation(BaseInvocation, WithMetadata):
     mask: Optional[ImageField] = InputField(default=None, description="Mask to use when applying color-correction")
     mask_blur_radius: float = InputField(default=8, description="Mask blur radius")
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
+    def invoke(self, context) -> ImageOutput:
         pil_init_mask = None
         if self.mask is not None:
-            pil_init_mask = context.services.images.get_pil_image(self.mask.image_name).convert("L")
+            pil_init_mask = context.images.get_pil(self.mask.image_name).convert("L")
 
-        init_image = context.services.images.get_pil_image(self.reference.image_name)
+        init_image = context.images.get_pil(self.reference.image_name)
 
-        result = context.services.images.get_pil_image(self.image.image_name).convert("RGBA")
+        result = context.images.get_pil(self.image.image_name).convert("RGBA")
 
         # if init_image is None or init_mask is None:
         #    return result
@@ -945,22 +723,9 @@ class ColorCorrectInvocation(BaseInvocation, WithMetadata):
         # Paste original on color-corrected generation (using blurred mask)
         matched_result.paste(init_image, (0, 0), mask=multiplied_blurred_init_mask)
 
-        image_dto = context.services.images.create(
-            image=matched_result,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-            metadata=self.metadata,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=matched_result)
 
-        return ImageOutput(
-            image=ImageField(image_name=image_dto.image_name),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
+        return ImageOutput.build(image_dto)
 
 
 @invocation(
@@ -968,7 +733,7 @@ class ColorCorrectInvocation(BaseInvocation, WithMetadata):
     title="Adjust Image Hue",
     tags=["image", "hue"],
     category="image",
-    version="1.2.0",
+    version="1.2.1",
 )
 class ImageHueAdjustmentInvocation(BaseInvocation, WithMetadata):
     """Adjusts the Hue of an image."""
@@ -976,8 +741,8 @@ class ImageHueAdjustmentInvocation(BaseInvocation, WithMetadata):
     image: ImageField = InputField(description="The image to adjust")
     hue: int = InputField(default=0, description="The degrees by which to rotate the hue, 0-360")
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        pil_image = context.services.images.get_pil_image(self.image.image_name)
+    def invoke(self, context) -> ImageOutput:
+        pil_image = context.images.get_pil(self.image.image_name)
 
         # Convert image to HSV color space
         hsv_image = numpy.array(pil_image.convert("HSV"))
@@ -991,24 +756,9 @@ class ImageHueAdjustmentInvocation(BaseInvocation, WithMetadata):
         # Convert back to PIL format and to original color mode
         pil_image = Image.fromarray(hsv_image, mode="HSV").convert("RGBA")
 
-        image_dto = context.services.images.create(
-            image=pil_image,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            is_intermediate=self.is_intermediate,
-            session_id=context.graph_execution_state_id,
-            metadata=self.metadata,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=pil_image)
 
-        return ImageOutput(
-            image=ImageField(
-                image_name=image_dto.image_name,
-            ),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
+        return ImageOutput.build(image_dto)
 
 
 COLOR_CHANNELS = Literal[
@@ -1072,7 +822,7 @@ CHANNEL_FORMATS = {
         "value",
     ],
     category="image",
-    version="1.2.0",
+    version="1.2.1",
 )
 class ImageChannelOffsetInvocation(BaseInvocation, WithMetadata):
     """Add or subtract a value from a specific color channel of an image."""
@@ -1081,8 +831,8 @@ class ImageChannelOffsetInvocation(BaseInvocation, WithMetadata):
     channel: COLOR_CHANNELS = InputField(description="Which channel to adjust")
     offset: int = InputField(default=0, ge=-255, le=255, description="The amount to adjust the channel by")
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        pil_image = context.services.images.get_pil_image(self.image.image_name)
+    def invoke(self, context) -> ImageOutput:
+        pil_image = context.images.get_pil(self.image.image_name)
 
         # extract the channel and mode from the input and reference tuple
         mode = CHANNEL_FORMATS[self.channel][0]
@@ -1101,24 +851,9 @@ class ImageChannelOffsetInvocation(BaseInvocation, WithMetadata):
         # Convert back to RGBA format and output
         pil_image = Image.fromarray(converted_image.astype(numpy.uint8), mode=mode).convert("RGBA")
 
-        image_dto = context.services.images.create(
-            image=pil_image,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            is_intermediate=self.is_intermediate,
-            session_id=context.graph_execution_state_id,
-            metadata=self.metadata,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=pil_image)
 
-        return ImageOutput(
-            image=ImageField(
-                image_name=image_dto.image_name,
-            ),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
+        return ImageOutput.build(image_dto)
 
 
 @invocation(
@@ -1143,7 +878,7 @@ class ImageChannelOffsetInvocation(BaseInvocation, WithMetadata):
         "value",
     ],
     category="image",
-    version="1.2.0",
+    version="1.2.1",
 )
 class ImageChannelMultiplyInvocation(BaseInvocation, WithMetadata):
     """Scale a specific color channel of an image."""
@@ -1153,8 +888,8 @@ class ImageChannelMultiplyInvocation(BaseInvocation, WithMetadata):
     scale: float = InputField(default=1.0, ge=0.0, description="The amount to scale the channel by.")
     invert_channel: bool = InputField(default=False, description="Invert the channel after scaling")
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        pil_image = context.services.images.get_pil_image(self.image.image_name)
+    def invoke(self, context) -> ImageOutput:
+        pil_image = context.images.get_pil(self.image.image_name)
 
         # extract the channel and mode from the input and reference tuple
         mode = CHANNEL_FORMATS[self.channel][0]
@@ -1177,24 +912,9 @@ class ImageChannelMultiplyInvocation(BaseInvocation, WithMetadata):
         # Convert back to RGBA format and output
         pil_image = Image.fromarray(converted_image.astype(numpy.uint8), mode=mode).convert("RGBA")
 
-        image_dto = context.services.images.create(
-            image=pil_image,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            is_intermediate=self.is_intermediate,
-            session_id=context.graph_execution_state_id,
-            workflow=context.workflow,
-            metadata=self.metadata,
-        )
+        image_dto = context.images.save(image=pil_image)
 
-        return ImageOutput(
-            image=ImageField(
-                image_name=image_dto.image_name,
-            ),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
+        return ImageOutput.build(image_dto)
 
 
 @invocation(
@@ -1202,7 +922,7 @@ class ImageChannelMultiplyInvocation(BaseInvocation, WithMetadata):
     title="Save Image",
     tags=["primitives", "image"],
     category="primitives",
-    version="1.2.0",
+    version="1.2.1",
     use_cache=False,
 )
 class SaveImageInvocation(BaseInvocation, WithMetadata):
@@ -1211,26 +931,12 @@ class SaveImageInvocation(BaseInvocation, WithMetadata):
     image: ImageField = InputField(description=FieldDescriptions.image)
     board: BoardField = InputField(default=None, description=FieldDescriptions.board, input=Input.Direct)
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(self.image.image_name)
+    def invoke(self, context) -> ImageOutput:
+        image = context.images.get_pil(self.image.image_name)
 
-        image_dto = context.services.images.create(
-            image=image,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            board_id=self.board.board_id if self.board else None,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-            metadata=self.metadata,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=image, board_id=self.board.board_id if self.board else None)
 
-        return ImageOutput(
-            image=ImageField(image_name=image_dto.image_name),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
+        return ImageOutput.build(image_dto)
 
 
 @invocation(
@@ -1238,7 +944,7 @@ class SaveImageInvocation(BaseInvocation, WithMetadata):
     title="Linear UI Image Output",
     tags=["primitives", "image"],
     category="primitives",
-    version="1.0.1",
+    version="1.0.2",
     use_cache=False,
 )
 class LinearUIOutputInvocation(BaseInvocation, WithMetadata):
@@ -1247,19 +953,13 @@ class LinearUIOutputInvocation(BaseInvocation, WithMetadata):
     image: ImageField = InputField(description=FieldDescriptions.image)
     board: Optional[BoardField] = InputField(default=None, description=FieldDescriptions.board, input=Input.Direct)
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        image_dto = context.services.images.get_dto(self.image.image_name)
+    def invoke(self, context) -> ImageOutput:
+        image_dto = context.images.get_dto(self.image.image_name)
 
-        if self.board:
-            context.services.board_images.add_image_to_board(self.board.board_id, self.image.image_name)
-
-        if image_dto.is_intermediate != self.is_intermediate:
-            context.services.images.update(
-                self.image.image_name, changes=ImageRecordChanges(is_intermediate=self.is_intermediate)
-            )
-
-        return ImageOutput(
-            image=ImageField(image_name=self.image.image_name),
-            width=image_dto.width,
-            height=image_dto.height,
+        image_dto = context.images.update(
+            image_name=self.image.image_name,
+            board_id=self.board.board_id if self.board else None,
+            is_intermediate=self.is_intermediate,
         )
+
+        return ImageOutput.build(image_dto)
diff --git a/invokeai/app/invocations/infill.py b/invokeai/app/invocations/infill.py
index d4d3d5bea4..be51c8312f 100644
--- a/invokeai/app/invocations/infill.py
+++ b/invokeai/app/invocations/infill.py
@@ -6,15 +6,15 @@ from typing import Literal, Optional, get_args
 import numpy as np
 from PIL import Image, ImageOps
 
-from invokeai.app.invocations.primitives import ColorField, ImageField, ImageOutput
-from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
+from invokeai.app.invocations.fields import ColorField, ImageField
+from invokeai.app.invocations.primitives import ImageOutput
 from invokeai.app.util.misc import SEED_MAX
 from invokeai.backend.image_util.cv2_inpaint import cv2_inpaint
 from invokeai.backend.image_util.lama import LaMA
 from invokeai.backend.image_util.patchmatch import PatchMatch
 
-from .baseinvocation import BaseInvocation, InvocationContext, invocation
-from .fields import InputField, WithMetadata
+from .baseinvocation import BaseInvocation, WithMetadata, invocation
+from .fields import InputField
 from .image import PIL_RESAMPLING_MAP, PIL_RESAMPLING_MODES
 
 
@@ -119,7 +119,7 @@ def tile_fill_missing(im: Image.Image, tile_size: int = 16, seed: Optional[int]
     return si
 
 
-@invocation("infill_rgba", title="Solid Color Infill", tags=["image", "inpaint"], category="inpaint", version="1.2.0")
+@invocation("infill_rgba", title="Solid Color Infill", tags=["image", "inpaint"], category="inpaint", version="1.2.1")
 class InfillColorInvocation(BaseInvocation, WithMetadata):
     """Infills transparent areas of an image with a solid color"""
 
@@ -129,33 +129,20 @@ class InfillColorInvocation(BaseInvocation, WithMetadata):
         description="The color to use to infill",
     )
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(self.image.image_name)
+    def invoke(self, context) -> ImageOutput:
+        image = context.images.get_pil(self.image.image_name)
 
         solid_bg = Image.new("RGBA", image.size, self.color.tuple())
         infilled = Image.alpha_composite(solid_bg, image.convert("RGBA"))
 
         infilled.paste(image, (0, 0), image.split()[-1])
 
-        image_dto = context.services.images.create(
-            image=infilled,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-            metadata=self.metadata,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=infilled)
 
-        return ImageOutput(
-            image=ImageField(image_name=image_dto.image_name),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
+        return ImageOutput.build(image_dto)
 
 
-@invocation("infill_tile", title="Tile Infill", tags=["image", "inpaint"], category="inpaint", version="1.2.1")
+@invocation("infill_tile", title="Tile Infill", tags=["image", "inpaint"], category="inpaint", version="1.2.2")
 class InfillTileInvocation(BaseInvocation, WithMetadata):
     """Infills transparent areas of an image with tiles of the image"""
 
@@ -168,32 +155,19 @@ class InfillTileInvocation(BaseInvocation, WithMetadata):
         description="The seed to use for tile generation (omit for random)",
     )
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(self.image.image_name)
+    def invoke(self, context) -> ImageOutput:
+        image = context.images.get_pil(self.image.image_name)
 
         infilled = tile_fill_missing(image.copy(), seed=self.seed, tile_size=self.tile_size)
         infilled.paste(image, (0, 0), image.split()[-1])
 
-        image_dto = context.services.images.create(
-            image=infilled,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-            metadata=self.metadata,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=infilled)
 
-        return ImageOutput(
-            image=ImageField(image_name=image_dto.image_name),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
+        return ImageOutput.build(image_dto)
 
 
 @invocation(
-    "infill_patchmatch", title="PatchMatch Infill", tags=["image", "inpaint"], category="inpaint", version="1.2.0"
+    "infill_patchmatch", title="PatchMatch Infill", tags=["image", "inpaint"], category="inpaint", version="1.2.1"
 )
 class InfillPatchMatchInvocation(BaseInvocation, WithMetadata):
     """Infills transparent areas of an image using the PatchMatch algorithm"""
@@ -202,8 +176,8 @@ class InfillPatchMatchInvocation(BaseInvocation, WithMetadata):
     downscale: float = InputField(default=2.0, gt=0, description="Run patchmatch on downscaled image to speedup infill")
     resample_mode: PIL_RESAMPLING_MODES = InputField(default="bicubic", description="The resampling mode")
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(self.image.image_name).convert("RGBA")
+    def invoke(self, context) -> ImageOutput:
+        image = context.images.get_pil(self.image.image_name).convert("RGBA")
 
         resample_mode = PIL_RESAMPLING_MAP[self.resample_mode]
 
@@ -228,77 +202,38 @@ class InfillPatchMatchInvocation(BaseInvocation, WithMetadata):
         infilled.paste(image, (0, 0), mask=image.split()[-1])
         # image.paste(infilled, (0, 0), mask=image.split()[-1])
 
-        image_dto = context.services.images.create(
-            image=infilled,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-            metadata=self.metadata,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=infilled)
 
-        return ImageOutput(
-            image=ImageField(image_name=image_dto.image_name),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
+        return ImageOutput.build(image_dto)
 
 
-@invocation("infill_lama", title="LaMa Infill", tags=["image", "inpaint"], category="inpaint", version="1.2.0")
+@invocation("infill_lama", title="LaMa Infill", tags=["image", "inpaint"], category="inpaint", version="1.2.1")
 class LaMaInfillInvocation(BaseInvocation, WithMetadata):
     """Infills transparent areas of an image using the LaMa model"""
 
     image: ImageField = InputField(description="The image to infill")
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(self.image.image_name)
+    def invoke(self, context) -> ImageOutput:
+        image = context.images.get_pil(self.image.image_name)
 
         infilled = infill_lama(image.copy())
 
-        image_dto = context.services.images.create(
-            image=infilled,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-            metadata=self.metadata,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=infilled)
 
-        return ImageOutput(
-            image=ImageField(image_name=image_dto.image_name),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
+        return ImageOutput.build(image_dto)
 
 
-@invocation("infill_cv2", title="CV2 Infill", tags=["image", "inpaint"], category="inpaint", version="1.2.0")
+@invocation("infill_cv2", title="CV2 Infill", tags=["image", "inpaint"], category="inpaint", version="1.2.1")
 class CV2InfillInvocation(BaseInvocation, WithMetadata):
     """Infills transparent areas of an image using OpenCV Inpainting"""
 
     image: ImageField = InputField(description="The image to infill")
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(self.image.image_name)
+    def invoke(self, context) -> ImageOutput:
+        image = context.images.get_pil(self.image.image_name)
 
         infilled = infill_cv2(image.copy())
 
-        image_dto = context.services.images.create(
-            image=infilled,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-            metadata=self.metadata,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=infilled)
 
-        return ImageOutput(
-            image=ImageField(image_name=image_dto.image_name),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
+        return ImageOutput.build(image_dto)
diff --git a/invokeai/app/invocations/ip_adapter.py b/invokeai/app/invocations/ip_adapter.py
index c01e0ed0fb..b836be04b5 100644
--- a/invokeai/app/invocations/ip_adapter.py
+++ b/invokeai/app/invocations/ip_adapter.py
@@ -7,7 +7,6 @@ from pydantic import BaseModel, ConfigDict, Field, field_validator, model_valida
 from invokeai.app.invocations.baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
-    InvocationContext,
     invocation,
     invocation_output,
 )
@@ -62,7 +61,7 @@ class IPAdapterOutput(BaseInvocationOutput):
     ip_adapter: IPAdapterField = OutputField(description=FieldDescriptions.ip_adapter, title="IP-Adapter")
 
 
-@invocation("ip_adapter", title="IP-Adapter", tags=["ip_adapter", "control"], category="ip_adapter", version="1.1.1")
+@invocation("ip_adapter", title="IP-Adapter", tags=["ip_adapter", "control"], category="ip_adapter", version="1.1.2")
 class IPAdapterInvocation(BaseInvocation):
     """Collects IP-Adapter info to pass to other nodes."""
 
@@ -93,9 +92,9 @@ class IPAdapterInvocation(BaseInvocation):
         validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
         return self
 
-    def invoke(self, context: InvocationContext) -> IPAdapterOutput:
+    def invoke(self, context) -> IPAdapterOutput:
         # Lookup the CLIP Vision encoder that is intended to be used with the IP-Adapter model.
-        ip_adapter_info = context.services.model_manager.model_info(
+        ip_adapter_info = context.models.get_info(
             self.ip_adapter_model.model_name, self.ip_adapter_model.base_model, ModelType.IPAdapter
         )
         # HACK(ryand): This is bad for a couple of reasons: 1) we are bypassing the model manager to read the model
@@ -104,7 +103,7 @@ class IPAdapterInvocation(BaseInvocation):
         # is currently messy due to differences between how the model info is generated when installing a model from
         # disk vs. downloading the model.
         image_encoder_model_id = get_ip_adapter_image_encoder_model_id(
-            os.path.join(context.services.configuration.get_config().models_path, ip_adapter_info["path"])
+            os.path.join(context.config.get().models_path, ip_adapter_info["path"])
         )
         image_encoder_model_name = image_encoder_model_id.split("/")[-1].strip()
         image_encoder_model = CLIPVisionModelField(
diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py
index 909c307481..0127a6521e 100644
--- a/invokeai/app/invocations/latent.py
+++ b/invokeai/app/invocations/latent.py
@@ -3,7 +3,7 @@
 import math
 from contextlib import ExitStack
 from functools import singledispatchmethod
-from typing import List, Literal, Optional, Union
+from typing import TYPE_CHECKING, List, Literal, Optional, Union
 
 import einops
 import numpy as np
@@ -23,21 +23,26 @@ from diffusers.schedulers import SchedulerMixin as Scheduler
 from pydantic import field_validator
 from torchvision.transforms.functional import resize as tv_resize
 
-from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField, UIType, WithMetadata
+from invokeai.app.invocations.fields import (
+    ConditioningField,
+    DenoiseMaskField,
+    FieldDescriptions,
+    ImageField,
+    Input,
+    InputField,
+    LatentsField,
+    OutputField,
+    UIType,
+    WithMetadata,
+)
 from invokeai.app.invocations.ip_adapter import IPAdapterField
 from invokeai.app.invocations.primitives import (
-    DenoiseMaskField,
     DenoiseMaskOutput,
-    ImageField,
     ImageOutput,
-    LatentsField,
     LatentsOutput,
-    build_latents_output,
 )
 from invokeai.app.invocations.t2i_adapter import T2IAdapterField
-from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
 from invokeai.app.util.controlnet_utils import prepare_control_image
-from invokeai.app.util.step_callback import stable_diffusion_step_callback
 from invokeai.backend.ip_adapter.ip_adapter import IPAdapter, IPAdapterPlus
 from invokeai.backend.model_management.models import ModelType, SilenceWarnings
 from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ConditioningData, IPAdapterConditioningInfo
@@ -59,14 +64,15 @@ from ...backend.util.devices import choose_precision, choose_torch_device
 from .baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
-    InvocationContext,
     invocation,
     invocation_output,
 )
-from .compel import ConditioningField
 from .controlnet_image_processors import ControlField
 from .model import ModelInfo, UNetField, VaeField
 
+if TYPE_CHECKING:
+    from invokeai.app.services.shared.invocation_context import InvocationContext
+
 if choose_torch_device() == torch.device("mps"):
     from torch import mps
 
@@ -102,7 +108,7 @@ class SchedulerInvocation(BaseInvocation):
         ui_type=UIType.Scheduler,
     )
 
-    def invoke(self, context: InvocationContext) -> SchedulerOutput:
+    def invoke(self, context) -> SchedulerOutput:
         return SchedulerOutput(scheduler=self.scheduler)
 
 
@@ -111,7 +117,7 @@ class SchedulerInvocation(BaseInvocation):
     title="Create Denoise Mask",
     tags=["mask", "denoise"],
     category="latents",
-    version="1.0.0",
+    version="1.0.1",
 )
 class CreateDenoiseMaskInvocation(BaseInvocation):
     """Creates mask for denoising model run."""
@@ -137,9 +143,9 @@ class CreateDenoiseMaskInvocation(BaseInvocation):
         return mask_tensor
 
     @torch.no_grad()
-    def invoke(self, context: InvocationContext) -> DenoiseMaskOutput:
+    def invoke(self, context) -> DenoiseMaskOutput:
         if self.image is not None:
-            image = context.services.images.get_pil_image(self.image.image_name)
+            image = context.images.get_pil(self.image.image_name)
             image = image_resized_to_grid_as_tensor(image.convert("RGB"))
             if image.dim() == 3:
                 image = image.unsqueeze(0)
@@ -147,47 +153,37 @@ class CreateDenoiseMaskInvocation(BaseInvocation):
             image = None
 
         mask = self.prep_mask_tensor(
-            context.services.images.get_pil_image(self.mask.image_name),
+            context.images.get_pil(self.mask.image_name),
         )
 
         if image is not None:
-            vae_info = context.services.model_manager.get_model(
-                **self.vae.vae.model_dump(),
-                context=context,
-            )
+            vae_info = context.models.load(**self.vae.vae.model_dump())
 
             img_mask = tv_resize(mask, image.shape[-2:], T.InterpolationMode.BILINEAR, antialias=False)
             masked_image = image * torch.where(img_mask < 0.5, 0.0, 1.0)
             # TODO:
             masked_latents = ImageToLatentsInvocation.vae_encode(vae_info, self.fp32, self.tiled, masked_image.clone())
 
-            masked_latents_name = f"{context.graph_execution_state_id}__{self.id}_masked_latents"
-            context.services.latents.save(masked_latents_name, masked_latents)
+            masked_latents_name = context.latents.save(tensor=masked_latents)
         else:
             masked_latents_name = None
 
-        mask_name = f"{context.graph_execution_state_id}__{self.id}_mask"
-        context.services.latents.save(mask_name, mask)
+        mask_name = context.latents.save(tensor=mask)
 
-        return DenoiseMaskOutput(
-            denoise_mask=DenoiseMaskField(
-                mask_name=mask_name,
-                masked_latents_name=masked_latents_name,
-            ),
+        return DenoiseMaskOutput.build(
+            mask_name=mask_name,
+            masked_latents_name=masked_latents_name,
         )
 
 
 def get_scheduler(
-    context: InvocationContext,
+    context: "InvocationContext",
     scheduler_info: ModelInfo,
     scheduler_name: str,
     seed: int,
 ) -> Scheduler:
     scheduler_class, scheduler_extra_config = SCHEDULER_MAP.get(scheduler_name, SCHEDULER_MAP["ddim"])
-    orig_scheduler_info = context.services.model_manager.get_model(
-        **scheduler_info.model_dump(),
-        context=context,
-    )
+    orig_scheduler_info = context.models.load(**scheduler_info.model_dump())
     with orig_scheduler_info as orig_scheduler:
         scheduler_config = orig_scheduler.config
 
@@ -216,7 +212,7 @@ def get_scheduler(
     title="Denoise Latents",
     tags=["latents", "denoise", "txt2img", "t2i", "t2l", "img2img", "i2i", "l2l"],
     category="latents",
-    version="1.5.1",
+    version="1.5.2",
 )
 class DenoiseLatentsInvocation(BaseInvocation):
     """Denoises noisy latents to decodable images"""
@@ -302,34 +298,18 @@ class DenoiseLatentsInvocation(BaseInvocation):
                 raise ValueError("cfg_scale must be greater than 1")
         return v
 
-    # TODO: pass this an emitter method or something? or a session for dispatching?
-    def dispatch_progress(
-        self,
-        context: InvocationContext,
-        source_node_id: str,
-        intermediate_state: PipelineIntermediateState,
-        base_model: BaseModelType,
-    ) -> None:
-        stable_diffusion_step_callback(
-            context=context,
-            intermediate_state=intermediate_state,
-            node=self.model_dump(),
-            source_node_id=source_node_id,
-            base_model=base_model,
-        )
-
     def get_conditioning_data(
         self,
-        context: InvocationContext,
+        context: "InvocationContext",
         scheduler,
         unet,
         seed,
     ) -> ConditioningData:
-        positive_cond_data = context.services.latents.get(self.positive_conditioning.conditioning_name)
+        positive_cond_data = context.conditioning.get(self.positive_conditioning.conditioning_name)
         c = positive_cond_data.conditionings[0].to(device=unet.device, dtype=unet.dtype)
         extra_conditioning_info = c.extra_conditioning
 
-        negative_cond_data = context.services.latents.get(self.negative_conditioning.conditioning_name)
+        negative_cond_data = context.conditioning.get(self.negative_conditioning.conditioning_name)
         uc = negative_cond_data.conditionings[0].to(device=unet.device, dtype=unet.dtype)
 
         conditioning_data = ConditioningData(
@@ -389,7 +369,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
 
     def prep_control_data(
         self,
-        context: InvocationContext,
+        context: "InvocationContext",
         control_input: Union[ControlField, List[ControlField]],
         latents_shape: List[int],
         exit_stack: ExitStack,
@@ -417,17 +397,16 @@ class DenoiseLatentsInvocation(BaseInvocation):
         controlnet_data = []
         for control_info in control_list:
             control_model = exit_stack.enter_context(
-                context.services.model_manager.get_model(
+                context.models.load(
                     model_name=control_info.control_model.model_name,
                     model_type=ModelType.ControlNet,
                     base_model=control_info.control_model.base_model,
-                    context=context,
                 )
             )
 
             # control_models.append(control_model)
             control_image_field = control_info.image
-            input_image = context.services.images.get_pil_image(control_image_field.image_name)
+            input_image = context.images.get_pil(control_image_field.image_name)
             # self.image.image_type, self.image.image_name
             # FIXME: still need to test with different widths, heights, devices, dtypes
             #        and add in batch_size, num_images_per_prompt?
@@ -463,7 +442,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
 
     def prep_ip_adapter_data(
         self,
-        context: InvocationContext,
+        context: "InvocationContext",
         ip_adapter: Optional[Union[IPAdapterField, list[IPAdapterField]]],
         conditioning_data: ConditioningData,
         exit_stack: ExitStack,
@@ -485,19 +464,17 @@ class DenoiseLatentsInvocation(BaseInvocation):
         conditioning_data.ip_adapter_conditioning = []
         for single_ip_adapter in ip_adapter:
             ip_adapter_model: Union[IPAdapter, IPAdapterPlus] = exit_stack.enter_context(
-                context.services.model_manager.get_model(
+                context.models.load(
                     model_name=single_ip_adapter.ip_adapter_model.model_name,
                     model_type=ModelType.IPAdapter,
                     base_model=single_ip_adapter.ip_adapter_model.base_model,
-                    context=context,
                 )
             )
 
-            image_encoder_model_info = context.services.model_manager.get_model(
+            image_encoder_model_info = context.models.load(
                 model_name=single_ip_adapter.image_encoder_model.model_name,
                 model_type=ModelType.CLIPVision,
                 base_model=single_ip_adapter.image_encoder_model.base_model,
-                context=context,
             )
 
             # `single_ip_adapter.image` could be a list or a single ImageField. Normalize to a list here.
@@ -505,7 +482,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
             if not isinstance(single_ipa_images, list):
                 single_ipa_images = [single_ipa_images]
 
-            single_ipa_images = [context.services.images.get_pil_image(image.image_name) for image in single_ipa_images]
+            single_ipa_images = [context.images.get_pil(image.image_name) for image in single_ipa_images]
 
             # TODO(ryand): With some effort, the step of running the CLIP Vision encoder could be done before any other
             # models are needed in memory. This would help to reduce peak memory utilization in low-memory environments.
@@ -532,7 +509,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
 
     def run_t2i_adapters(
         self,
-        context: InvocationContext,
+        context: "InvocationContext",
         t2i_adapter: Optional[Union[T2IAdapterField, list[T2IAdapterField]]],
         latents_shape: list[int],
         do_classifier_free_guidance: bool,
@@ -549,13 +526,12 @@ class DenoiseLatentsInvocation(BaseInvocation):
 
         t2i_adapter_data = []
         for t2i_adapter_field in t2i_adapter:
-            t2i_adapter_model_info = context.services.model_manager.get_model(
+            t2i_adapter_model_info = context.models.load(
                 model_name=t2i_adapter_field.t2i_adapter_model.model_name,
                 model_type=ModelType.T2IAdapter,
                 base_model=t2i_adapter_field.t2i_adapter_model.base_model,
-                context=context,
             )
-            image = context.services.images.get_pil_image(t2i_adapter_field.image.image_name)
+            image = context.images.get_pil(t2i_adapter_field.image.image_name)
 
             # The max_unet_downscale is the maximum amount that the UNet model downscales the latent image internally.
             if t2i_adapter_field.t2i_adapter_model.base_model == BaseModelType.StableDiffusion1:
@@ -642,30 +618,30 @@ class DenoiseLatentsInvocation(BaseInvocation):
 
         return num_inference_steps, timesteps, init_timestep
 
-    def prep_inpaint_mask(self, context, latents):
+    def prep_inpaint_mask(self, context: "InvocationContext", latents):
         if self.denoise_mask is None:
             return None, None
 
-        mask = context.services.latents.get(self.denoise_mask.mask_name)
+        mask = context.latents.get(self.denoise_mask.mask_name)
         mask = tv_resize(mask, latents.shape[-2:], T.InterpolationMode.BILINEAR, antialias=False)
         if self.denoise_mask.masked_latents_name is not None:
-            masked_latents = context.services.latents.get(self.denoise_mask.masked_latents_name)
+            masked_latents = context.latents.get(self.denoise_mask.masked_latents_name)
         else:
             masked_latents = None
 
         return 1 - mask, masked_latents
 
     @torch.no_grad()
-    def invoke(self, context: InvocationContext) -> LatentsOutput:
+    def invoke(self, context) -> LatentsOutput:
         with SilenceWarnings():  # this quenches NSFW nag from diffusers
             seed = None
             noise = None
             if self.noise is not None:
-                noise = context.services.latents.get(self.noise.latents_name)
+                noise = context.latents.get(self.noise.latents_name)
                 seed = self.noise.seed
 
             if self.latents is not None:
-                latents = context.services.latents.get(self.latents.latents_name)
+                latents = context.latents.get(self.latents.latents_name)
                 if seed is None:
                     seed = self.latents.seed
 
@@ -691,27 +667,17 @@ class DenoiseLatentsInvocation(BaseInvocation):
                 do_classifier_free_guidance=True,
             )
 
-            # Get the source node id (we are invoking the prepared node)
-            graph_execution_state = context.services.graph_execution_manager.get(context.graph_execution_state_id)
-            source_node_id = graph_execution_state.prepared_source_mapping[self.id]
-
             def step_callback(state: PipelineIntermediateState):
-                self.dispatch_progress(context, source_node_id, state, self.unet.unet.base_model)
+                context.util.sd_step_callback(state, self.unet.unet.base_model)
 
             def _lora_loader():
                 for lora in self.unet.loras:
-                    lora_info = context.services.model_manager.get_model(
-                        **lora.model_dump(exclude={"weight"}),
-                        context=context,
-                    )
+                    lora_info = context.models.load(**lora.model_dump(exclude={"weight"}))
                     yield (lora_info.context.model, lora.weight)
                     del lora_info
                 return
 
-            unet_info = context.services.model_manager.get_model(
-                **self.unet.unet.model_dump(),
-                context=context,
-            )
+            unet_info = context.models.load(**self.unet.unet.model_dump())
             with (
                 ExitStack() as exit_stack,
                 ModelPatcher.apply_freeu(unet_info.context.model, self.unet.freeu_config),
@@ -787,9 +753,8 @@ class DenoiseLatentsInvocation(BaseInvocation):
             if choose_torch_device() == torch.device("mps"):
                 mps.empty_cache()
 
-            name = f"{context.graph_execution_state_id}__{self.id}"
-            context.services.latents.save(name, result_latents)
-        return build_latents_output(latents_name=name, latents=result_latents, seed=seed)
+            name = context.latents.save(tensor=result_latents)
+        return LatentsOutput.build(latents_name=name, latents=result_latents, seed=seed)
 
 
 @invocation(
@@ -797,7 +762,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
     title="Latents to Image",
     tags=["latents", "image", "vae", "l2i"],
     category="latents",
-    version="1.2.0",
+    version="1.2.1",
 )
 class LatentsToImageInvocation(BaseInvocation, WithMetadata):
     """Generates an image from latents."""
@@ -814,13 +779,10 @@ class LatentsToImageInvocation(BaseInvocation, WithMetadata):
     fp32: bool = InputField(default=DEFAULT_PRECISION == "float32", description=FieldDescriptions.fp32)
 
     @torch.no_grad()
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        latents = context.services.latents.get(self.latents.latents_name)
+    def invoke(self, context) -> ImageOutput:
+        latents = context.latents.get(self.latents.latents_name)
 
-        vae_info = context.services.model_manager.get_model(
-            **self.vae.vae.model_dump(),
-            context=context,
-        )
+        vae_info = context.models.load(**self.vae.vae.model_dump())
 
         with set_seamless(vae_info.context.model, self.vae.seamless_axes), vae_info as vae:
             latents = latents.to(vae.device)
@@ -849,7 +811,7 @@ class LatentsToImageInvocation(BaseInvocation, WithMetadata):
                 vae.to(dtype=torch.float16)
                 latents = latents.half()
 
-            if self.tiled or context.services.configuration.tiled_decode:
+            if self.tiled or context.config.get().tiled_decode:
                 vae.enable_tiling()
             else:
                 vae.disable_tiling()
@@ -873,22 +835,9 @@ class LatentsToImageInvocation(BaseInvocation, WithMetadata):
         if choose_torch_device() == torch.device("mps"):
             mps.empty_cache()
 
-        image_dto = context.services.images.create(
-            image=image,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-            metadata=self.metadata,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=image)
 
-        return ImageOutput(
-            image=ImageField(image_name=image_dto.image_name),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
+        return ImageOutput.build(image_dto)
 
 
 LATENTS_INTERPOLATION_MODE = Literal["nearest", "linear", "bilinear", "bicubic", "trilinear", "area", "nearest-exact"]
@@ -899,7 +848,7 @@ LATENTS_INTERPOLATION_MODE = Literal["nearest", "linear", "bilinear", "bicubic",
     title="Resize Latents",
     tags=["latents", "resize"],
     category="latents",
-    version="1.0.0",
+    version="1.0.1",
 )
 class ResizeLatentsInvocation(BaseInvocation):
     """Resizes latents to explicit width/height (in pixels). Provided dimensions are floor-divided by 8."""
@@ -921,8 +870,8 @@ class ResizeLatentsInvocation(BaseInvocation):
     mode: LATENTS_INTERPOLATION_MODE = InputField(default="bilinear", description=FieldDescriptions.interp_mode)
     antialias: bool = InputField(default=False, description=FieldDescriptions.torch_antialias)
 
-    def invoke(self, context: InvocationContext) -> LatentsOutput:
-        latents = context.services.latents.get(self.latents.latents_name)
+    def invoke(self, context) -> LatentsOutput:
+        latents = context.latents.get(self.latents.latents_name)
 
         # TODO:
         device = choose_torch_device()
@@ -940,10 +889,8 @@ class ResizeLatentsInvocation(BaseInvocation):
         if device == torch.device("mps"):
             mps.empty_cache()
 
-        name = f"{context.graph_execution_state_id}__{self.id}"
-        # context.services.latents.set(name, resized_latents)
-        context.services.latents.save(name, resized_latents)
-        return build_latents_output(latents_name=name, latents=resized_latents, seed=self.latents.seed)
+        name = context.latents.save(tensor=resized_latents)
+        return LatentsOutput.build(latents_name=name, latents=resized_latents, seed=self.latents.seed)
 
 
 @invocation(
@@ -951,7 +898,7 @@ class ResizeLatentsInvocation(BaseInvocation):
     title="Scale Latents",
     tags=["latents", "resize"],
     category="latents",
-    version="1.0.0",
+    version="1.0.1",
 )
 class ScaleLatentsInvocation(BaseInvocation):
     """Scales latents by a given factor."""
@@ -964,8 +911,8 @@ class ScaleLatentsInvocation(BaseInvocation):
     mode: LATENTS_INTERPOLATION_MODE = InputField(default="bilinear", description=FieldDescriptions.interp_mode)
     antialias: bool = InputField(default=False, description=FieldDescriptions.torch_antialias)
 
-    def invoke(self, context: InvocationContext) -> LatentsOutput:
-        latents = context.services.latents.get(self.latents.latents_name)
+    def invoke(self, context) -> LatentsOutput:
+        latents = context.latents.get(self.latents.latents_name)
 
         # TODO:
         device = choose_torch_device()
@@ -984,10 +931,8 @@ class ScaleLatentsInvocation(BaseInvocation):
         if device == torch.device("mps"):
             mps.empty_cache()
 
-        name = f"{context.graph_execution_state_id}__{self.id}"
-        # context.services.latents.set(name, resized_latents)
-        context.services.latents.save(name, resized_latents)
-        return build_latents_output(latents_name=name, latents=resized_latents, seed=self.latents.seed)
+        name = context.latents.save(tensor=resized_latents)
+        return LatentsOutput.build(latents_name=name, latents=resized_latents, seed=self.latents.seed)
 
 
 @invocation(
@@ -995,7 +940,7 @@ class ScaleLatentsInvocation(BaseInvocation):
     title="Image to Latents",
     tags=["latents", "image", "vae", "i2l"],
     category="latents",
-    version="1.0.0",
+    version="1.0.1",
 )
 class ImageToLatentsInvocation(BaseInvocation):
     """Encodes an image into latents."""
@@ -1055,13 +1000,10 @@ class ImageToLatentsInvocation(BaseInvocation):
         return latents
 
     @torch.no_grad()
-    def invoke(self, context: InvocationContext) -> LatentsOutput:
-        image = context.services.images.get_pil_image(self.image.image_name)
+    def invoke(self, context) -> LatentsOutput:
+        image = context.images.get_pil(self.image.image_name)
 
-        vae_info = context.services.model_manager.get_model(
-            **self.vae.vae.model_dump(),
-            context=context,
-        )
+        vae_info = context.models.load(**self.vae.vae.model_dump())
 
         image_tensor = image_resized_to_grid_as_tensor(image.convert("RGB"))
         if image_tensor.dim() == 3:
@@ -1069,10 +1011,9 @@ class ImageToLatentsInvocation(BaseInvocation):
 
         latents = self.vae_encode(vae_info, self.fp32, self.tiled, image_tensor)
 
-        name = f"{context.graph_execution_state_id}__{self.id}"
         latents = latents.to("cpu")
-        context.services.latents.save(name, latents)
-        return build_latents_output(latents_name=name, latents=latents, seed=None)
+        name = context.latents.save(tensor=latents)
+        return LatentsOutput.build(latents_name=name, latents=latents, seed=None)
 
     @singledispatchmethod
     @staticmethod
@@ -1092,7 +1033,7 @@ class ImageToLatentsInvocation(BaseInvocation):
     title="Blend Latents",
     tags=["latents", "blend"],
     category="latents",
-    version="1.0.0",
+    version="1.0.1",
 )
 class BlendLatentsInvocation(BaseInvocation):
     """Blend two latents using a given alpha. Latents must have same size."""
@@ -1107,9 +1048,9 @@ class BlendLatentsInvocation(BaseInvocation):
     )
     alpha: float = InputField(default=0.5, description=FieldDescriptions.blend_alpha)
 
-    def invoke(self, context: InvocationContext) -> LatentsOutput:
-        latents_a = context.services.latents.get(self.latents_a.latents_name)
-        latents_b = context.services.latents.get(self.latents_b.latents_name)
+    def invoke(self, context) -> LatentsOutput:
+        latents_a = context.latents.get(self.latents_a.latents_name)
+        latents_b = context.latents.get(self.latents_b.latents_name)
 
         if latents_a.shape != latents_b.shape:
             raise Exception("Latents to blend must be the same size.")
@@ -1163,10 +1104,8 @@ class BlendLatentsInvocation(BaseInvocation):
         if device == torch.device("mps"):
             mps.empty_cache()
 
-        name = f"{context.graph_execution_state_id}__{self.id}"
-        # context.services.latents.set(name, resized_latents)
-        context.services.latents.save(name, blended_latents)
-        return build_latents_output(latents_name=name, latents=blended_latents)
+        name = context.latents.save(tensor=blended_latents)
+        return LatentsOutput.build(latents_name=name, latents=blended_latents)
 
 
 # The Crop Latents node was copied from @skunkworxdark's implementation here:
@@ -1176,7 +1115,7 @@ class BlendLatentsInvocation(BaseInvocation):
     title="Crop Latents",
     tags=["latents", "crop"],
     category="latents",
-    version="1.0.0",
+    version="1.0.1",
 )
 # TODO(ryand): Named `CropLatentsCoreInvocation` to prevent a conflict with custom node `CropLatentsInvocation`.
 # Currently, if the class names conflict then 'GET /openapi.json' fails.
@@ -1210,8 +1149,8 @@ class CropLatentsCoreInvocation(BaseInvocation):
         description="The height (in px) of the crop rectangle in image space. This value will be converted to a dimension in latent space.",
     )
 
-    def invoke(self, context: InvocationContext) -> LatentsOutput:
-        latents = context.services.latents.get(self.latents.latents_name)
+    def invoke(self, context) -> LatentsOutput:
+        latents = context.latents.get(self.latents.latents_name)
 
         x1 = self.x // LATENT_SCALE_FACTOR
         y1 = self.y // LATENT_SCALE_FACTOR
@@ -1220,10 +1159,9 @@ class CropLatentsCoreInvocation(BaseInvocation):
 
         cropped_latents = latents[..., y1:y2, x1:x2]
 
-        name = f"{context.graph_execution_state_id}__{self.id}"
-        context.services.latents.save(name, cropped_latents)
+        name = context.latents.save(tensor=cropped_latents)
 
-        return build_latents_output(latents_name=name, latents=cropped_latents)
+        return LatentsOutput.build(latents_name=name, latents=cropped_latents)
 
 
 @invocation_output("ideal_size_output")
diff --git a/invokeai/app/invocations/math.py b/invokeai/app/invocations/math.py
index 6ca53011f0..d2dbf04981 100644
--- a/invokeai/app/invocations/math.py
+++ b/invokeai/app/invocations/math.py
@@ -8,7 +8,7 @@ from pydantic import ValidationInfo, field_validator
 from invokeai.app.invocations.fields import FieldDescriptions, InputField
 from invokeai.app.invocations.primitives import FloatOutput, IntegerOutput
 
-from .baseinvocation import BaseInvocation, InvocationContext, invocation
+from .baseinvocation import BaseInvocation, invocation
 
 
 @invocation("add", title="Add Integers", tags=["math", "add"], category="math", version="1.0.0")
@@ -18,7 +18,7 @@ class AddInvocation(BaseInvocation):
     a: int = InputField(default=0, description=FieldDescriptions.num_1)
     b: int = InputField(default=0, description=FieldDescriptions.num_2)
 
-    def invoke(self, context: InvocationContext) -> IntegerOutput:
+    def invoke(self, context) -> IntegerOutput:
         return IntegerOutput(value=self.a + self.b)
 
 
@@ -29,7 +29,7 @@ class SubtractInvocation(BaseInvocation):
     a: int = InputField(default=0, description=FieldDescriptions.num_1)
     b: int = InputField(default=0, description=FieldDescriptions.num_2)
 
-    def invoke(self, context: InvocationContext) -> IntegerOutput:
+    def invoke(self, context) -> IntegerOutput:
         return IntegerOutput(value=self.a - self.b)
 
 
@@ -40,7 +40,7 @@ class MultiplyInvocation(BaseInvocation):
     a: int = InputField(default=0, description=FieldDescriptions.num_1)
     b: int = InputField(default=0, description=FieldDescriptions.num_2)
 
-    def invoke(self, context: InvocationContext) -> IntegerOutput:
+    def invoke(self, context) -> IntegerOutput:
         return IntegerOutput(value=self.a * self.b)
 
 
@@ -51,7 +51,7 @@ class DivideInvocation(BaseInvocation):
     a: int = InputField(default=0, description=FieldDescriptions.num_1)
     b: int = InputField(default=0, description=FieldDescriptions.num_2)
 
-    def invoke(self, context: InvocationContext) -> IntegerOutput:
+    def invoke(self, context) -> IntegerOutput:
         return IntegerOutput(value=int(self.a / self.b))
 
 
@@ -69,7 +69,7 @@ class RandomIntInvocation(BaseInvocation):
     low: int = InputField(default=0, description=FieldDescriptions.inclusive_low)
     high: int = InputField(default=np.iinfo(np.int32).max, description=FieldDescriptions.exclusive_high)
 
-    def invoke(self, context: InvocationContext) -> IntegerOutput:
+    def invoke(self, context) -> IntegerOutput:
         return IntegerOutput(value=np.random.randint(self.low, self.high))
 
 
@@ -88,7 +88,7 @@ class RandomFloatInvocation(BaseInvocation):
     high: float = InputField(default=1.0, description=FieldDescriptions.exclusive_high)
     decimals: int = InputField(default=2, description=FieldDescriptions.decimal_places)
 
-    def invoke(self, context: InvocationContext) -> FloatOutput:
+    def invoke(self, context) -> FloatOutput:
         random_float = np.random.uniform(self.low, self.high)
         rounded_float = round(random_float, self.decimals)
         return FloatOutput(value=rounded_float)
@@ -110,7 +110,7 @@ class FloatToIntegerInvocation(BaseInvocation):
         default="Nearest", description="The method to use for rounding"
     )
 
-    def invoke(self, context: InvocationContext) -> IntegerOutput:
+    def invoke(self, context) -> IntegerOutput:
         if self.method == "Nearest":
             return IntegerOutput(value=round(self.value / self.multiple) * self.multiple)
         elif self.method == "Floor":
@@ -128,7 +128,7 @@ class RoundInvocation(BaseInvocation):
     value: float = InputField(default=0, description="The float value")
     decimals: int = InputField(default=0, description="The number of decimal places")
 
-    def invoke(self, context: InvocationContext) -> FloatOutput:
+    def invoke(self, context) -> FloatOutput:
         return FloatOutput(value=round(self.value, self.decimals))
 
 
@@ -196,7 +196,7 @@ class IntegerMathInvocation(BaseInvocation):
             raise ValueError("Result of exponentiation is not an integer")
         return v
 
-    def invoke(self, context: InvocationContext) -> IntegerOutput:
+    def invoke(self, context) -> IntegerOutput:
         # Python doesn't support switch statements until 3.10, but InvokeAI supports back to 3.9
         if self.operation == "ADD":
             return IntegerOutput(value=self.a + self.b)
@@ -270,7 +270,7 @@ class FloatMathInvocation(BaseInvocation):
             raise ValueError("Root operation resulted in a complex number")
         return v
 
-    def invoke(self, context: InvocationContext) -> FloatOutput:
+    def invoke(self, context) -> FloatOutput:
         # Python doesn't support switch statements until 3.10, but InvokeAI supports back to 3.9
         if self.operation == "ADD":
             return FloatOutput(value=self.a + self.b)
diff --git a/invokeai/app/invocations/metadata.py b/invokeai/app/invocations/metadata.py
index 399e217dc1..9d74abd8c1 100644
--- a/invokeai/app/invocations/metadata.py
+++ b/invokeai/app/invocations/metadata.py
@@ -5,15 +5,20 @@ from pydantic import BaseModel, ConfigDict, Field
 from invokeai.app.invocations.baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
-    InvocationContext,
     invocation,
     invocation_output,
 )
 from invokeai.app.invocations.controlnet_image_processors import ControlField
-from invokeai.app.invocations.fields import FieldDescriptions, InputField, MetadataField, OutputField, UIType
+from invokeai.app.invocations.fields import (
+    FieldDescriptions,
+    ImageField,
+    InputField,
+    MetadataField,
+    OutputField,
+    UIType,
+)
 from invokeai.app.invocations.ip_adapter import IPAdapterModelField
 from invokeai.app.invocations.model import LoRAModelField, MainModelField, VAEModelField
-from invokeai.app.invocations.primitives import ImageField
 from invokeai.app.invocations.t2i_adapter import T2IAdapterField
 
 from ...version import __version__
@@ -59,7 +64,7 @@ class MetadataItemInvocation(BaseInvocation):
     label: str = InputField(description=FieldDescriptions.metadata_item_label)
     value: Any = InputField(description=FieldDescriptions.metadata_item_value, ui_type=UIType.Any)
 
-    def invoke(self, context: InvocationContext) -> MetadataItemOutput:
+    def invoke(self, context) -> MetadataItemOutput:
         return MetadataItemOutput(item=MetadataItemField(label=self.label, value=self.value))
 
 
@@ -76,7 +81,7 @@ class MetadataInvocation(BaseInvocation):
         description=FieldDescriptions.metadata_item_polymorphic
     )
 
-    def invoke(self, context: InvocationContext) -> MetadataOutput:
+    def invoke(self, context) -> MetadataOutput:
         if isinstance(self.items, MetadataItemField):
             # single metadata item
             data = {self.items.label: self.items.value}
@@ -95,7 +100,7 @@ class MergeMetadataInvocation(BaseInvocation):
 
     collection: list[MetadataField] = InputField(description=FieldDescriptions.metadata_collection)
 
-    def invoke(self, context: InvocationContext) -> MetadataOutput:
+    def invoke(self, context) -> MetadataOutput:
         data = {}
         for item in self.collection:
             data.update(item.model_dump())
@@ -213,7 +218,7 @@ class CoreMetadataInvocation(BaseInvocation):
         description="The start value used for refiner denoising",
     )
 
-    def invoke(self, context: InvocationContext) -> MetadataOutput:
+    def invoke(self, context) -> MetadataOutput:
         """Collects and outputs a CoreMetadata object"""
 
         return MetadataOutput(
diff --git a/invokeai/app/invocations/model.py b/invokeai/app/invocations/model.py
index c710c9761b..f81e559e44 100644
--- a/invokeai/app/invocations/model.py
+++ b/invokeai/app/invocations/model.py
@@ -10,7 +10,6 @@ from ...backend.model_management import BaseModelType, ModelType, SubModelType
 from .baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
-    InvocationContext,
     invocation,
     invocation_output,
 )
@@ -102,7 +101,7 @@ class LoRAModelField(BaseModel):
     title="Main Model",
     tags=["model"],
     category="model",
-    version="1.0.0",
+    version="1.0.1",
 )
 class MainModelLoaderInvocation(BaseInvocation):
     """Loads a main model, outputting its submodels."""
@@ -110,13 +109,13 @@ class MainModelLoaderInvocation(BaseInvocation):
     model: MainModelField = InputField(description=FieldDescriptions.main_model, input=Input.Direct)
     # TODO: precision?
 
-    def invoke(self, context: InvocationContext) -> ModelLoaderOutput:
+    def invoke(self, context) -> ModelLoaderOutput:
         base_model = self.model.base_model
         model_name = self.model.model_name
         model_type = ModelType.Main
 
         # TODO: not found exceptions
-        if not context.services.model_manager.model_exists(
+        if not context.models.exists(
             model_name=model_name,
             base_model=base_model,
             model_type=model_type,
@@ -203,7 +202,7 @@ class LoraLoaderOutput(BaseInvocationOutput):
     clip: Optional[ClipField] = OutputField(default=None, description=FieldDescriptions.clip, title="CLIP")
 
 
-@invocation("lora_loader", title="LoRA", tags=["model"], category="model", version="1.0.0")
+@invocation("lora_loader", title="LoRA", tags=["model"], category="model", version="1.0.1")
 class LoraLoaderInvocation(BaseInvocation):
     """Apply selected lora to unet and text_encoder."""
 
@@ -222,14 +221,14 @@ class LoraLoaderInvocation(BaseInvocation):
         title="CLIP",
     )
 
-    def invoke(self, context: InvocationContext) -> LoraLoaderOutput:
+    def invoke(self, context) -> LoraLoaderOutput:
         if self.lora is None:
             raise Exception("No LoRA provided")
 
         base_model = self.lora.base_model
         lora_name = self.lora.model_name
 
-        if not context.services.model_manager.model_exists(
+        if not context.models.exists(
             base_model=base_model,
             model_name=lora_name,
             model_type=ModelType.Lora,
@@ -285,7 +284,7 @@ class SDXLLoraLoaderOutput(BaseInvocationOutput):
     title="SDXL LoRA",
     tags=["lora", "model"],
     category="model",
-    version="1.0.0",
+    version="1.0.1",
 )
 class SDXLLoraLoaderInvocation(BaseInvocation):
     """Apply selected lora to unet and text_encoder."""
@@ -311,14 +310,14 @@ class SDXLLoraLoaderInvocation(BaseInvocation):
         title="CLIP 2",
     )
 
-    def invoke(self, context: InvocationContext) -> SDXLLoraLoaderOutput:
+    def invoke(self, context) -> SDXLLoraLoaderOutput:
         if self.lora is None:
             raise Exception("No LoRA provided")
 
         base_model = self.lora.base_model
         lora_name = self.lora.model_name
 
-        if not context.services.model_manager.model_exists(
+        if not context.models.exists(
             base_model=base_model,
             model_name=lora_name,
             model_type=ModelType.Lora,
@@ -384,7 +383,7 @@ class VAEModelField(BaseModel):
     model_config = ConfigDict(protected_namespaces=())
 
 
-@invocation("vae_loader", title="VAE", tags=["vae", "model"], category="model", version="1.0.0")
+@invocation("vae_loader", title="VAE", tags=["vae", "model"], category="model", version="1.0.1")
 class VaeLoaderInvocation(BaseInvocation):
     """Loads a VAE model, outputting a VaeLoaderOutput"""
 
@@ -394,12 +393,12 @@ class VaeLoaderInvocation(BaseInvocation):
         title="VAE",
     )
 
-    def invoke(self, context: InvocationContext) -> VAEOutput:
+    def invoke(self, context) -> VAEOutput:
         base_model = self.vae_model.base_model
         model_name = self.vae_model.model_name
         model_type = ModelType.Vae
 
-        if not context.services.model_manager.model_exists(
+        if not context.models.exists(
             base_model=base_model,
             model_name=model_name,
             model_type=model_type,
@@ -449,7 +448,7 @@ class SeamlessModeInvocation(BaseInvocation):
     seamless_y: bool = InputField(default=True, input=Input.Any, description="Specify whether Y axis is seamless")
     seamless_x: bool = InputField(default=True, input=Input.Any, description="Specify whether X axis is seamless")
 
-    def invoke(self, context: InvocationContext) -> SeamlessModeOutput:
+    def invoke(self, context) -> SeamlessModeOutput:
         # Conditionally append 'x' and 'y' based on seamless_x and seamless_y
         unet = copy.deepcopy(self.unet)
         vae = copy.deepcopy(self.vae)
@@ -485,6 +484,6 @@ class FreeUInvocation(BaseInvocation):
     s1: float = InputField(default=0.9, ge=-1, le=3, description=FieldDescriptions.freeu_s1)
     s2: float = InputField(default=0.2, ge=-1, le=3, description=FieldDescriptions.freeu_s2)
 
-    def invoke(self, context: InvocationContext) -> UNetOutput:
+    def invoke(self, context) -> UNetOutput:
         self.unet.freeu_config = FreeUConfig(s1=self.s1, s2=self.s2, b1=self.b1, b2=self.b2)
         return UNetOutput(unet=self.unet)
diff --git a/invokeai/app/invocations/noise.py b/invokeai/app/invocations/noise.py
index 2e717ac561..41641152f0 100644
--- a/invokeai/app/invocations/noise.py
+++ b/invokeai/app/invocations/noise.py
@@ -4,15 +4,13 @@
 import torch
 from pydantic import field_validator
 
-from invokeai.app.invocations.fields import FieldDescriptions, InputField, OutputField
-from invokeai.app.invocations.latent import LatentsField
+from invokeai.app.invocations.fields import FieldDescriptions, InputField, LatentsField, OutputField
 from invokeai.app.util.misc import SEED_MAX
 
 from ...backend.util.devices import choose_torch_device, torch_dtype
 from .baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
-    InvocationContext,
     invocation,
     invocation_output,
 )
@@ -67,13 +65,13 @@ class NoiseOutput(BaseInvocationOutput):
     width: int = OutputField(description=FieldDescriptions.width)
     height: int = OutputField(description=FieldDescriptions.height)
 
-
-def build_noise_output(latents_name: str, latents: torch.Tensor, seed: int):
-    return NoiseOutput(
-        noise=LatentsField(latents_name=latents_name, seed=seed),
-        width=latents.size()[3] * 8,
-        height=latents.size()[2] * 8,
-    )
+    @classmethod
+    def build(cls, latents_name: str, latents: torch.Tensor, seed: int) -> "NoiseOutput":
+        return cls(
+            noise=LatentsField(latents_name=latents_name, seed=seed),
+            width=latents.size()[3] * 8,
+            height=latents.size()[2] * 8,
+        )
 
 
 @invocation(
@@ -114,7 +112,7 @@ class NoiseInvocation(BaseInvocation):
         """Returns the seed modulo (SEED_MAX + 1) to ensure it is within the valid range."""
         return v % (SEED_MAX + 1)
 
-    def invoke(self, context: InvocationContext) -> NoiseOutput:
+    def invoke(self, context) -> NoiseOutput:
         noise = get_noise(
             width=self.width,
             height=self.height,
@@ -122,6 +120,5 @@ class NoiseInvocation(BaseInvocation):
             seed=self.seed,
             use_cpu=self.use_cpu,
         )
-        name = f"{context.graph_execution_state_id}__{self.id}"
-        context.services.latents.save(name, noise)
-        return build_noise_output(latents_name=name, latents=noise, seed=self.seed)
+        name = context.latents.save(tensor=noise)
+        return NoiseOutput.build(latents_name=name, latents=noise, seed=self.seed)
diff --git a/invokeai/app/invocations/onnx.py b/invokeai/app/invocations/onnx.py
index b43d7eaef2..3f8e6669ab 100644
--- a/invokeai/app/invocations/onnx.py
+++ b/invokeai/app/invocations/onnx.py
@@ -37,7 +37,7 @@ from .baseinvocation import (
     invocation_output,
 )
 from .controlnet_image_processors import ControlField
-from .latent import SAMPLER_NAME_VALUES, LatentsField, LatentsOutput, build_latents_output, get_scheduler
+from .latent import SAMPLER_NAME_VALUES, LatentsField, LatentsOutput, get_scheduler
 from .model import ClipField, ModelInfo, UNetField, VaeField
 
 ORT_TO_NP_TYPE = {
@@ -63,7 +63,7 @@ class ONNXPromptInvocation(BaseInvocation):
     prompt: str = InputField(default="", description=FieldDescriptions.raw_prompt, ui_component=UIComponent.Textarea)
     clip: ClipField = InputField(description=FieldDescriptions.clip, input=Input.Connection)
 
-    def invoke(self, context: InvocationContext) -> ConditioningOutput:
+    def invoke(self, context) -> ConditioningOutput:
         tokenizer_info = context.services.model_manager.get_model(
             **self.clip.tokenizer.model_dump(),
         )
@@ -201,7 +201,7 @@ class ONNXTextToLatentsInvocation(BaseInvocation):
 
     # based on
     # https://github.com/huggingface/diffusers/blob/3ebbaf7c96801271f9e6c21400033b6aa5ffcf29/src/diffusers/pipelines/stable_diffusion/pipeline_onnx_stable_diffusion.py#L375
-    def invoke(self, context: InvocationContext) -> LatentsOutput:
+    def invoke(self, context) -> LatentsOutput:
         c, _ = context.services.latents.get(self.positive_conditioning.conditioning_name)
         uc, _ = context.services.latents.get(self.negative_conditioning.conditioning_name)
         graph_execution_state = context.services.graph_execution_manager.get(context.graph_execution_state_id)
@@ -342,7 +342,7 @@ class ONNXLatentsToImageInvocation(BaseInvocation, WithMetadata):
     )
     # tiled: bool = InputField(default=False, description="Decode latents by overlaping tiles(less memory consumption)")
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
+    def invoke(self, context) -> ImageOutput:
         latents = context.services.latents.get(self.latents.latents_name)
 
         if self.vae.vae.submodel != SubModelType.VaeDecoder:
@@ -417,7 +417,7 @@ class OnnxModelLoaderInvocation(BaseInvocation):
         description=FieldDescriptions.onnx_main_model, input=Input.Direct, ui_type=UIType.ONNXModel
     )
 
-    def invoke(self, context: InvocationContext) -> ONNXModelLoaderOutput:
+    def invoke(self, context) -> ONNXModelLoaderOutput:
         base_model = self.model.base_model
         model_name = self.model.model_name
         model_type = ModelType.ONNX
diff --git a/invokeai/app/invocations/param_easing.py b/invokeai/app/invocations/param_easing.py
index dab9c3dc0f..bf59e87d27 100644
--- a/invokeai/app/invocations/param_easing.py
+++ b/invokeai/app/invocations/param_easing.py
@@ -41,7 +41,7 @@ from matplotlib.ticker import MaxNLocator
 
 from invokeai.app.invocations.primitives import FloatCollectionOutput
 
-from .baseinvocation import BaseInvocation, InvocationContext, invocation
+from .baseinvocation import BaseInvocation, invocation
 from .fields import InputField
 
 
@@ -62,7 +62,7 @@ class FloatLinearRangeInvocation(BaseInvocation):
         description="number of values to interpolate over (including start and stop)",
     )
 
-    def invoke(self, context: InvocationContext) -> FloatCollectionOutput:
+    def invoke(self, context) -> FloatCollectionOutput:
         param_list = list(np.linspace(self.start, self.stop, self.steps))
         return FloatCollectionOutput(collection=param_list)
 
@@ -110,7 +110,7 @@ EASING_FUNCTION_KEYS = Literal[tuple(EASING_FUNCTIONS_MAP.keys())]
     title="Step Param Easing",
     tags=["step", "easing"],
     category="step",
-    version="1.0.0",
+    version="1.0.1",
 )
 class StepParamEasingInvocation(BaseInvocation):
     """Experimental per-step parameter easing for denoising steps"""
@@ -130,7 +130,7 @@ class StepParamEasingInvocation(BaseInvocation):
     # alt_mirror: bool = InputField(default=False, description="alternative mirroring by dual easing")
     show_easing_plot: bool = InputField(default=False, description="show easing plot")
 
-    def invoke(self, context: InvocationContext) -> FloatCollectionOutput:
+    def invoke(self, context) -> FloatCollectionOutput:
         log_diagnostics = False
         # convert from start_step_percent to nearest step <= (steps * start_step_percent)
         # start_step = int(np.floor(self.num_steps * self.start_step_percent))
@@ -149,19 +149,19 @@ class StepParamEasingInvocation(BaseInvocation):
         postlist = list(num_poststeps * [self.post_end_value])
 
         if log_diagnostics:
-            context.services.logger.debug("start_step: " + str(start_step))
-            context.services.logger.debug("end_step: " + str(end_step))
-            context.services.logger.debug("num_easing_steps: " + str(num_easing_steps))
-            context.services.logger.debug("num_presteps: " + str(num_presteps))
-            context.services.logger.debug("num_poststeps: " + str(num_poststeps))
-            context.services.logger.debug("prelist size: " + str(len(prelist)))
-            context.services.logger.debug("postlist size: " + str(len(postlist)))
-            context.services.logger.debug("prelist: " + str(prelist))
-            context.services.logger.debug("postlist: " + str(postlist))
+            context.logger.debug("start_step: " + str(start_step))
+            context.logger.debug("end_step: " + str(end_step))
+            context.logger.debug("num_easing_steps: " + str(num_easing_steps))
+            context.logger.debug("num_presteps: " + str(num_presteps))
+            context.logger.debug("num_poststeps: " + str(num_poststeps))
+            context.logger.debug("prelist size: " + str(len(prelist)))
+            context.logger.debug("postlist size: " + str(len(postlist)))
+            context.logger.debug("prelist: " + str(prelist))
+            context.logger.debug("postlist: " + str(postlist))
 
         easing_class = EASING_FUNCTIONS_MAP[self.easing]
         if log_diagnostics:
-            context.services.logger.debug("easing class: " + str(easing_class))
+            context.logger.debug("easing class: " + str(easing_class))
         easing_list = []
         if self.mirror:  # "expected" mirroring
             # if number of steps is even, squeeze duration down to (number_of_steps)/2
@@ -172,7 +172,7 @@ class StepParamEasingInvocation(BaseInvocation):
 
             base_easing_duration = int(np.ceil(num_easing_steps / 2.0))
             if log_diagnostics:
-                context.services.logger.debug("base easing duration: " + str(base_easing_duration))
+                context.logger.debug("base easing duration: " + str(base_easing_duration))
             even_num_steps = num_easing_steps % 2 == 0  # even number of steps
             easing_function = easing_class(
                 start=self.start_value,
@@ -184,14 +184,14 @@ class StepParamEasingInvocation(BaseInvocation):
                 easing_val = easing_function.ease(step_index)
                 base_easing_vals.append(easing_val)
                 if log_diagnostics:
-                    context.services.logger.debug("step_index: " + str(step_index) + ", easing_val: " + str(easing_val))
+                    context.logger.debug("step_index: " + str(step_index) + ", easing_val: " + str(easing_val))
             if even_num_steps:
                 mirror_easing_vals = list(reversed(base_easing_vals))
             else:
                 mirror_easing_vals = list(reversed(base_easing_vals[0:-1]))
             if log_diagnostics:
-                context.services.logger.debug("base easing vals: " + str(base_easing_vals))
-                context.services.logger.debug("mirror easing vals: " + str(mirror_easing_vals))
+                context.logger.debug("base easing vals: " + str(base_easing_vals))
+                context.logger.debug("mirror easing vals: " + str(mirror_easing_vals))
             easing_list = base_easing_vals + mirror_easing_vals
 
         # FIXME: add alt_mirror option (alternative to default or mirror), or remove entirely
@@ -226,12 +226,12 @@ class StepParamEasingInvocation(BaseInvocation):
                 step_val = easing_function.ease(step_index)
                 easing_list.append(step_val)
                 if log_diagnostics:
-                    context.services.logger.debug("step_index: " + str(step_index) + ", easing_val: " + str(step_val))
+                    context.logger.debug("step_index: " + str(step_index) + ", easing_val: " + str(step_val))
 
         if log_diagnostics:
-            context.services.logger.debug("prelist size: " + str(len(prelist)))
-            context.services.logger.debug("easing_list size: " + str(len(easing_list)))
-            context.services.logger.debug("postlist size: " + str(len(postlist)))
+            context.logger.debug("prelist size: " + str(len(prelist)))
+            context.logger.debug("easing_list size: " + str(len(easing_list)))
+            context.logger.debug("postlist size: " + str(len(postlist)))
 
         param_list = prelist + easing_list + postlist
 
diff --git a/invokeai/app/invocations/primitives.py b/invokeai/app/invocations/primitives.py
index 22f03454a5..ee04345eed 100644
--- a/invokeai/app/invocations/primitives.py
+++ b/invokeai/app/invocations/primitives.py
@@ -1,16 +1,26 @@
 # Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
 
-from typing import Optional, Tuple
+from typing import Optional
 
 import torch
-from pydantic import BaseModel, Field
 
-from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField, UIComponent
+from invokeai.app.invocations.fields import (
+    ColorField,
+    ConditioningField,
+    DenoiseMaskField,
+    FieldDescriptions,
+    ImageField,
+    Input,
+    InputField,
+    LatentsField,
+    OutputField,
+    UIComponent,
+)
+from invokeai.app.services.images.images_common import ImageDTO
 
 from .baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
-    InvocationContext,
     invocation,
     invocation_output,
 )
@@ -49,7 +59,7 @@ class BooleanInvocation(BaseInvocation):
 
     value: bool = InputField(default=False, description="The boolean value")
 
-    def invoke(self, context: InvocationContext) -> BooleanOutput:
+    def invoke(self, context) -> BooleanOutput:
         return BooleanOutput(value=self.value)
 
 
@@ -65,7 +75,7 @@ class BooleanCollectionInvocation(BaseInvocation):
 
     collection: list[bool] = InputField(default=[], description="The collection of boolean values")
 
-    def invoke(self, context: InvocationContext) -> BooleanCollectionOutput:
+    def invoke(self, context) -> BooleanCollectionOutput:
         return BooleanCollectionOutput(collection=self.collection)
 
 
@@ -98,7 +108,7 @@ class IntegerInvocation(BaseInvocation):
 
     value: int = InputField(default=0, description="The integer value")
 
-    def invoke(self, context: InvocationContext) -> IntegerOutput:
+    def invoke(self, context) -> IntegerOutput:
         return IntegerOutput(value=self.value)
 
 
@@ -114,7 +124,7 @@ class IntegerCollectionInvocation(BaseInvocation):
 
     collection: list[int] = InputField(default=[], description="The collection of integer values")
 
-    def invoke(self, context: InvocationContext) -> IntegerCollectionOutput:
+    def invoke(self, context) -> IntegerCollectionOutput:
         return IntegerCollectionOutput(collection=self.collection)
 
 
@@ -145,7 +155,7 @@ class FloatInvocation(BaseInvocation):
 
     value: float = InputField(default=0.0, description="The float value")
 
-    def invoke(self, context: InvocationContext) -> FloatOutput:
+    def invoke(self, context) -> FloatOutput:
         return FloatOutput(value=self.value)
 
 
@@ -161,7 +171,7 @@ class FloatCollectionInvocation(BaseInvocation):
 
     collection: list[float] = InputField(default=[], description="The collection of float values")
 
-    def invoke(self, context: InvocationContext) -> FloatCollectionOutput:
+    def invoke(self, context) -> FloatCollectionOutput:
         return FloatCollectionOutput(collection=self.collection)
 
 
@@ -192,7 +202,7 @@ class StringInvocation(BaseInvocation):
 
     value: str = InputField(default="", description="The string value", ui_component=UIComponent.Textarea)
 
-    def invoke(self, context: InvocationContext) -> StringOutput:
+    def invoke(self, context) -> StringOutput:
         return StringOutput(value=self.value)
 
 
@@ -208,7 +218,7 @@ class StringCollectionInvocation(BaseInvocation):
 
     collection: list[str] = InputField(default=[], description="The collection of string values")
 
-    def invoke(self, context: InvocationContext) -> StringCollectionOutput:
+    def invoke(self, context) -> StringCollectionOutput:
         return StringCollectionOutput(collection=self.collection)
 
 
@@ -217,18 +227,6 @@ class StringCollectionInvocation(BaseInvocation):
 # region Image
 
 
-class ImageField(BaseModel):
-    """An image primitive field"""
-
-    image_name: str = Field(description="The name of the image")
-
-
-class BoardField(BaseModel):
-    """A board primitive field"""
-
-    board_id: str = Field(description="The id of the board")
-
-
 @invocation_output("image_output")
 class ImageOutput(BaseInvocationOutput):
     """Base class for nodes that output a single image"""
@@ -237,6 +235,14 @@ class ImageOutput(BaseInvocationOutput):
     width: int = OutputField(description="The width of the image in pixels")
     height: int = OutputField(description="The height of the image in pixels")
 
+    @classmethod
+    def build(cls, image_dto: ImageDTO) -> "ImageOutput":
+        return cls(
+            image=ImageField(image_name=image_dto.image_name),
+            width=image_dto.width,
+            height=image_dto.height,
+        )
+
 
 @invocation_output("image_collection_output")
 class ImageCollectionOutput(BaseInvocationOutput):
@@ -247,7 +253,7 @@ class ImageCollectionOutput(BaseInvocationOutput):
     )
 
 
-@invocation("image", title="Image Primitive", tags=["primitives", "image"], category="primitives", version="1.0.0")
+@invocation("image", title="Image Primitive", tags=["primitives", "image"], category="primitives", version="1.0.1")
 class ImageInvocation(
     BaseInvocation,
 ):
@@ -255,8 +261,8 @@ class ImageInvocation(
 
     image: ImageField = InputField(description="The image to load")
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(self.image.image_name)
+    def invoke(self, context) -> ImageOutput:
+        image = context.images.get_pil(self.image.image_name)
 
         return ImageOutput(
             image=ImageField(image_name=self.image.image_name),
@@ -277,7 +283,7 @@ class ImageCollectionInvocation(BaseInvocation):
 
     collection: list[ImageField] = InputField(description="The collection of image values")
 
-    def invoke(self, context: InvocationContext) -> ImageCollectionOutput:
+    def invoke(self, context) -> ImageCollectionOutput:
         return ImageCollectionOutput(collection=self.collection)
 
 
@@ -286,32 +292,24 @@ class ImageCollectionInvocation(BaseInvocation):
 # region DenoiseMask
 
 
-class DenoiseMaskField(BaseModel):
-    """An inpaint mask field"""
-
-    mask_name: str = Field(description="The name of the mask image")
-    masked_latents_name: Optional[str] = Field(default=None, description="The name of the masked image latents")
-
-
 @invocation_output("denoise_mask_output")
 class DenoiseMaskOutput(BaseInvocationOutput):
     """Base class for nodes that output a single image"""
 
     denoise_mask: DenoiseMaskField = OutputField(description="Mask for denoise model run")
 
+    @classmethod
+    def build(cls, mask_name: str, masked_latents_name: Optional[str] = None) -> "DenoiseMaskOutput":
+        return cls(
+            denoise_mask=DenoiseMaskField(mask_name=mask_name, masked_latents_name=masked_latents_name),
+        )
+
 
 # endregion
 
 # region Latents
 
 
-class LatentsField(BaseModel):
-    """A latents tensor primitive field"""
-
-    latents_name: str = Field(description="The name of the latents")
-    seed: Optional[int] = Field(default=None, description="Seed used to generate this latents")
-
-
 @invocation_output("latents_output")
 class LatentsOutput(BaseInvocationOutput):
     """Base class for nodes that output a single latents tensor"""
@@ -322,6 +320,14 @@ class LatentsOutput(BaseInvocationOutput):
     width: int = OutputField(description=FieldDescriptions.width)
     height: int = OutputField(description=FieldDescriptions.height)
 
+    @classmethod
+    def build(cls, latents_name: str, latents: torch.Tensor, seed: Optional[int] = None) -> "LatentsOutput":
+        return cls(
+            latents=LatentsField(latents_name=latents_name, seed=seed),
+            width=latents.size()[3] * 8,
+            height=latents.size()[2] * 8,
+        )
+
 
 @invocation_output("latents_collection_output")
 class LatentsCollectionOutput(BaseInvocationOutput):
@@ -333,17 +339,17 @@ class LatentsCollectionOutput(BaseInvocationOutput):
 
 
 @invocation(
-    "latents", title="Latents Primitive", tags=["primitives", "latents"], category="primitives", version="1.0.0"
+    "latents", title="Latents Primitive", tags=["primitives", "latents"], category="primitives", version="1.0.1"
 )
 class LatentsInvocation(BaseInvocation):
     """A latents tensor primitive value"""
 
     latents: LatentsField = InputField(description="The latents tensor", input=Input.Connection)
 
-    def invoke(self, context: InvocationContext) -> LatentsOutput:
-        latents = context.services.latents.get(self.latents.latents_name)
+    def invoke(self, context) -> LatentsOutput:
+        latents = context.latents.get(self.latents.latents_name)
 
-        return build_latents_output(self.latents.latents_name, latents)
+        return LatentsOutput.build(self.latents.latents_name, latents)
 
 
 @invocation(
@@ -360,35 +366,15 @@ class LatentsCollectionInvocation(BaseInvocation):
         description="The collection of latents tensors",
     )
 
-    def invoke(self, context: InvocationContext) -> LatentsCollectionOutput:
+    def invoke(self, context) -> LatentsCollectionOutput:
         return LatentsCollectionOutput(collection=self.collection)
 
 
-def build_latents_output(latents_name: str, latents: torch.Tensor, seed: Optional[int] = None):
-    return LatentsOutput(
-        latents=LatentsField(latents_name=latents_name, seed=seed),
-        width=latents.size()[3] * 8,
-        height=latents.size()[2] * 8,
-    )
-
-
 # endregion
 
 # region Color
 
 
-class ColorField(BaseModel):
-    """A color primitive field"""
-
-    r: int = Field(ge=0, le=255, description="The red component")
-    g: int = Field(ge=0, le=255, description="The green component")
-    b: int = Field(ge=0, le=255, description="The blue component")
-    a: int = Field(ge=0, le=255, description="The alpha component")
-
-    def tuple(self) -> Tuple[int, int, int, int]:
-        return (self.r, self.g, self.b, self.a)
-
-
 @invocation_output("color_output")
 class ColorOutput(BaseInvocationOutput):
     """Base class for nodes that output a single color"""
@@ -411,7 +397,7 @@ class ColorInvocation(BaseInvocation):
 
     color: ColorField = InputField(default=ColorField(r=0, g=0, b=0, a=255), description="The color value")
 
-    def invoke(self, context: InvocationContext) -> ColorOutput:
+    def invoke(self, context) -> ColorOutput:
         return ColorOutput(color=self.color)
 
 
@@ -420,18 +406,16 @@ class ColorInvocation(BaseInvocation):
 # region Conditioning
 
 
-class ConditioningField(BaseModel):
-    """A conditioning tensor primitive value"""
-
-    conditioning_name: str = Field(description="The name of conditioning tensor")
-
-
 @invocation_output("conditioning_output")
 class ConditioningOutput(BaseInvocationOutput):
     """Base class for nodes that output a single conditioning tensor"""
 
     conditioning: ConditioningField = OutputField(description=FieldDescriptions.cond)
 
+    @classmethod
+    def build(cls, conditioning_name: str) -> "ConditioningOutput":
+        return cls(conditioning=ConditioningField(conditioning_name=conditioning_name))
+
 
 @invocation_output("conditioning_collection_output")
 class ConditioningCollectionOutput(BaseInvocationOutput):
@@ -454,7 +438,7 @@ class ConditioningInvocation(BaseInvocation):
 
     conditioning: ConditioningField = InputField(description=FieldDescriptions.cond, input=Input.Connection)
 
-    def invoke(self, context: InvocationContext) -> ConditioningOutput:
+    def invoke(self, context) -> ConditioningOutput:
         return ConditioningOutput(conditioning=self.conditioning)
 
 
@@ -473,7 +457,7 @@ class ConditioningCollectionInvocation(BaseInvocation):
         description="The collection of conditioning tensors",
     )
 
-    def invoke(self, context: InvocationContext) -> ConditioningCollectionOutput:
+    def invoke(self, context) -> ConditioningCollectionOutput:
         return ConditioningCollectionOutput(collection=self.collection)
 
 
diff --git a/invokeai/app/invocations/prompt.py b/invokeai/app/invocations/prompt.py
index 94b4a217ae..4f5ef43a56 100644
--- a/invokeai/app/invocations/prompt.py
+++ b/invokeai/app/invocations/prompt.py
@@ -7,7 +7,7 @@ from pydantic import field_validator
 
 from invokeai.app.invocations.primitives import StringCollectionOutput
 
-from .baseinvocation import BaseInvocation, InvocationContext, invocation
+from .baseinvocation import BaseInvocation, invocation
 from .fields import InputField, UIComponent
 
 
@@ -29,7 +29,7 @@ class DynamicPromptInvocation(BaseInvocation):
     max_prompts: int = InputField(default=1, description="The number of prompts to generate")
     combinatorial: bool = InputField(default=False, description="Whether to use the combinatorial generator")
 
-    def invoke(self, context: InvocationContext) -> StringCollectionOutput:
+    def invoke(self, context) -> StringCollectionOutput:
         if self.combinatorial:
             generator = CombinatorialPromptGenerator()
             prompts = generator.generate(self.prompt, max_prompts=self.max_prompts)
@@ -91,7 +91,7 @@ class PromptsFromFileInvocation(BaseInvocation):
                     break
         return prompts
 
-    def invoke(self, context: InvocationContext) -> StringCollectionOutput:
+    def invoke(self, context) -> StringCollectionOutput:
         prompts = self.promptsFromFile(
             self.file_path,
             self.pre_prompt,
diff --git a/invokeai/app/invocations/sdxl.py b/invokeai/app/invocations/sdxl.py
index 62df5bc804..75a526cfff 100644
--- a/invokeai/app/invocations/sdxl.py
+++ b/invokeai/app/invocations/sdxl.py
@@ -4,7 +4,6 @@ from ...backend.model_management import ModelType, SubModelType
 from .baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
-    InvocationContext,
     invocation,
     invocation_output,
 )
@@ -30,7 +29,7 @@ class SDXLRefinerModelLoaderOutput(BaseInvocationOutput):
     vae: VaeField = OutputField(description=FieldDescriptions.vae, title="VAE")
 
 
-@invocation("sdxl_model_loader", title="SDXL Main Model", tags=["model", "sdxl"], category="model", version="1.0.0")
+@invocation("sdxl_model_loader", title="SDXL Main Model", tags=["model", "sdxl"], category="model", version="1.0.1")
 class SDXLModelLoaderInvocation(BaseInvocation):
     """Loads an sdxl base model, outputting its submodels."""
 
@@ -39,13 +38,13 @@ class SDXLModelLoaderInvocation(BaseInvocation):
     )
     # TODO: precision?
 
-    def invoke(self, context: InvocationContext) -> SDXLModelLoaderOutput:
+    def invoke(self, context) -> SDXLModelLoaderOutput:
         base_model = self.model.base_model
         model_name = self.model.model_name
         model_type = ModelType.Main
 
         # TODO: not found exceptions
-        if not context.services.model_manager.model_exists(
+        if not context.models.exists(
             model_name=model_name,
             base_model=base_model,
             model_type=model_type,
@@ -116,7 +115,7 @@ class SDXLModelLoaderInvocation(BaseInvocation):
     title="SDXL Refiner Model",
     tags=["model", "sdxl", "refiner"],
     category="model",
-    version="1.0.0",
+    version="1.0.1",
 )
 class SDXLRefinerModelLoaderInvocation(BaseInvocation):
     """Loads an sdxl refiner model, outputting its submodels."""
@@ -128,13 +127,13 @@ class SDXLRefinerModelLoaderInvocation(BaseInvocation):
     )
     # TODO: precision?
 
-    def invoke(self, context: InvocationContext) -> SDXLRefinerModelLoaderOutput:
+    def invoke(self, context) -> SDXLRefinerModelLoaderOutput:
         base_model = self.model.base_model
         model_name = self.model.model_name
         model_type = ModelType.Main
 
         # TODO: not found exceptions
-        if not context.services.model_manager.model_exists(
+        if not context.models.exists(
             model_name=model_name,
             base_model=base_model,
             model_type=model_type,
diff --git a/invokeai/app/invocations/strings.py b/invokeai/app/invocations/strings.py
index ccbc2f6d92..a4c92d9de5 100644
--- a/invokeai/app/invocations/strings.py
+++ b/invokeai/app/invocations/strings.py
@@ -5,7 +5,6 @@ import re
 from .baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
-    InvocationContext,
     invocation,
     invocation_output,
 )
@@ -33,7 +32,7 @@ class StringSplitNegInvocation(BaseInvocation):
 
     string: str = InputField(default="", description="String to split", ui_component=UIComponent.Textarea)
 
-    def invoke(self, context: InvocationContext) -> StringPosNegOutput:
+    def invoke(self, context) -> StringPosNegOutput:
         p_string = ""
         n_string = ""
         brackets_depth = 0
@@ -77,7 +76,7 @@ class StringSplitInvocation(BaseInvocation):
         default="", description="Delimiter to spilt with. blank will split on the first whitespace"
     )
 
-    def invoke(self, context: InvocationContext) -> String2Output:
+    def invoke(self, context) -> String2Output:
         result = self.string.split(self.delimiter, 1)
         if len(result) == 2:
             part1, part2 = result
@@ -95,7 +94,7 @@ class StringJoinInvocation(BaseInvocation):
     string_left: str = InputField(default="", description="String Left", ui_component=UIComponent.Textarea)
     string_right: str = InputField(default="", description="String Right", ui_component=UIComponent.Textarea)
 
-    def invoke(self, context: InvocationContext) -> StringOutput:
+    def invoke(self, context) -> StringOutput:
         return StringOutput(value=((self.string_left or "") + (self.string_right or "")))
 
 
@@ -107,7 +106,7 @@ class StringJoinThreeInvocation(BaseInvocation):
     string_middle: str = InputField(default="", description="String Middle", ui_component=UIComponent.Textarea)
     string_right: str = InputField(default="", description="String Right", ui_component=UIComponent.Textarea)
 
-    def invoke(self, context: InvocationContext) -> StringOutput:
+    def invoke(self, context) -> StringOutput:
         return StringOutput(value=((self.string_left or "") + (self.string_middle or "") + (self.string_right or "")))
 
 
@@ -126,7 +125,7 @@ class StringReplaceInvocation(BaseInvocation):
         default=False, description="Use search string as a regex expression (non regex is case insensitive)"
     )
 
-    def invoke(self, context: InvocationContext) -> StringOutput:
+    def invoke(self, context) -> StringOutput:
         pattern = self.search_string or ""
         new_string = self.string or ""
         if len(pattern) > 0:
diff --git a/invokeai/app/invocations/t2i_adapter.py b/invokeai/app/invocations/t2i_adapter.py
index 66ac87c37b..74a098a501 100644
--- a/invokeai/app/invocations/t2i_adapter.py
+++ b/invokeai/app/invocations/t2i_adapter.py
@@ -5,13 +5,11 @@ from pydantic import BaseModel, ConfigDict, Field, field_validator, model_valida
 from invokeai.app.invocations.baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
-    InvocationContext,
     invocation,
     invocation_output,
 )
 from invokeai.app.invocations.controlnet_image_processors import CONTROLNET_RESIZE_VALUES
-from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField
-from invokeai.app.invocations.primitives import ImageField
+from invokeai.app.invocations.fields import FieldDescriptions, ImageField, Input, InputField, OutputField
 from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
 from invokeai.backend.model_management.models.base import BaseModelType
 
@@ -91,7 +89,7 @@ class T2IAdapterInvocation(BaseInvocation):
         validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
         return self
 
-    def invoke(self, context: InvocationContext) -> T2IAdapterOutput:
+    def invoke(self, context) -> T2IAdapterOutput:
         return T2IAdapterOutput(
             t2i_adapter=T2IAdapterField(
                 image=self.image,
diff --git a/invokeai/app/invocations/tiles.py b/invokeai/app/invocations/tiles.py
index bdc23ef6ed..dd34c3dc09 100644
--- a/invokeai/app/invocations/tiles.py
+++ b/invokeai/app/invocations/tiles.py
@@ -8,13 +8,12 @@ from invokeai.app.invocations.baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
     Classification,
-    InvocationContext,
+    WithMetadata,
     invocation,
     invocation_output,
 )
-from invokeai.app.invocations.fields import Input, InputField, OutputField, WithMetadata
-from invokeai.app.invocations.primitives import ImageField, ImageOutput
-from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
+from invokeai.app.invocations.fields import ImageField, Input, InputField, OutputField
+from invokeai.app.invocations.primitives import ImageOutput
 from invokeai.backend.tiles.tiles import (
     calc_tiles_even_split,
     calc_tiles_min_overlap,
@@ -58,7 +57,7 @@ class CalculateImageTilesInvocation(BaseInvocation):
         description="The target overlap, in pixels, between adjacent tiles. Adjacent tiles will overlap by at least this amount",
     )
 
-    def invoke(self, context: InvocationContext) -> CalculateImageTilesOutput:
+    def invoke(self, context) -> CalculateImageTilesOutput:
         tiles = calc_tiles_with_overlap(
             image_height=self.image_height,
             image_width=self.image_width,
@@ -101,7 +100,7 @@ class CalculateImageTilesEvenSplitInvocation(BaseInvocation):
         description="The overlap, in pixels, between adjacent tiles.",
     )
 
-    def invoke(self, context: InvocationContext) -> CalculateImageTilesOutput:
+    def invoke(self, context) -> CalculateImageTilesOutput:
         tiles = calc_tiles_even_split(
             image_height=self.image_height,
             image_width=self.image_width,
@@ -131,7 +130,7 @@ class CalculateImageTilesMinimumOverlapInvocation(BaseInvocation):
     tile_height: int = InputField(ge=1, default=576, description="The tile height, in pixels.")
     min_overlap: int = InputField(default=128, ge=0, description="Minimum overlap between adjacent tiles, in pixels.")
 
-    def invoke(self, context: InvocationContext) -> CalculateImageTilesOutput:
+    def invoke(self, context) -> CalculateImageTilesOutput:
         tiles = calc_tiles_min_overlap(
             image_height=self.image_height,
             image_width=self.image_width,
@@ -176,7 +175,7 @@ class TileToPropertiesInvocation(BaseInvocation):
 
     tile: Tile = InputField(description="The tile to split into properties.")
 
-    def invoke(self, context: InvocationContext) -> TileToPropertiesOutput:
+    def invoke(self, context) -> TileToPropertiesOutput:
         return TileToPropertiesOutput(
             coords_left=self.tile.coords.left,
             coords_right=self.tile.coords.right,
@@ -213,7 +212,7 @@ class PairTileImageInvocation(BaseInvocation):
     image: ImageField = InputField(description="The tile image.")
     tile: Tile = InputField(description="The tile properties.")
 
-    def invoke(self, context: InvocationContext) -> PairTileImageOutput:
+    def invoke(self, context) -> PairTileImageOutput:
         return PairTileImageOutput(
             tile_with_image=TileWithImage(
                 tile=self.tile,
@@ -249,7 +248,7 @@ class MergeTilesToImageInvocation(BaseInvocation, WithMetadata):
         description="The amount to blend adjacent tiles in pixels. Must be <= the amount of overlap between adjacent tiles.",
     )
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
+    def invoke(self, context) -> ImageOutput:
         images = [twi.image for twi in self.tiles_with_images]
         tiles = [twi.tile for twi in self.tiles_with_images]
 
@@ -265,7 +264,7 @@ class MergeTilesToImageInvocation(BaseInvocation, WithMetadata):
         # existed in memory at an earlier point in the graph.
         tile_np_images: list[np.ndarray] = []
         for image in images:
-            pil_image = context.services.images.get_pil_image(image.image_name)
+            pil_image = context.images.get_pil(image.image_name)
             pil_image = pil_image.convert("RGB")
             tile_np_images.append(np.array(pil_image))
 
@@ -288,18 +287,5 @@ class MergeTilesToImageInvocation(BaseInvocation, WithMetadata):
         # Convert into a PIL image and save
         pil_image = Image.fromarray(np_image)
 
-        image_dto = context.services.images.create(
-            image=pil_image,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-            metadata=self.metadata,
-            workflow=context.workflow,
-        )
-        return ImageOutput(
-            image=ImageField(image_name=image_dto.image_name),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
+        image_dto = context.images.save(image=pil_image)
+        return ImageOutput.build(image_dto)
diff --git a/invokeai/app/invocations/upscale.py b/invokeai/app/invocations/upscale.py
index 2cab279a9f..ef17480986 100644
--- a/invokeai/app/invocations/upscale.py
+++ b/invokeai/app/invocations/upscale.py
@@ -8,13 +8,13 @@ import torch
 from PIL import Image
 from pydantic import ConfigDict
 
-from invokeai.app.invocations.primitives import ImageField, ImageOutput
-from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
+from invokeai.app.invocations.fields import ImageField
+from invokeai.app.invocations.primitives import ImageOutput
 from invokeai.backend.image_util.basicsr.rrdbnet_arch import RRDBNet
 from invokeai.backend.image_util.realesrgan.realesrgan import RealESRGAN
 from invokeai.backend.util.devices import choose_torch_device
 
-from .baseinvocation import BaseInvocation, InvocationContext, invocation
+from .baseinvocation import BaseInvocation, invocation
 from .fields import InputField, WithMetadata
 
 # TODO: Populate this from disk?
@@ -30,7 +30,7 @@ if choose_torch_device() == torch.device("mps"):
     from torch import mps
 
 
-@invocation("esrgan", title="Upscale (RealESRGAN)", tags=["esrgan", "upscale"], category="esrgan", version="1.3.0")
+@invocation("esrgan", title="Upscale (RealESRGAN)", tags=["esrgan", "upscale"], category="esrgan", version="1.3.1")
 class ESRGANInvocation(BaseInvocation, WithMetadata):
     """Upscales an image using RealESRGAN."""
 
@@ -42,9 +42,9 @@ class ESRGANInvocation(BaseInvocation, WithMetadata):
 
     model_config = ConfigDict(protected_namespaces=())
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(self.image.image_name)
-        models_path = context.services.configuration.models_path
+    def invoke(self, context) -> ImageOutput:
+        image = context.images.get_pil(self.image.image_name)
+        models_path = context.config.get().models_path
 
         rrdbnet_model = None
         netscale = None
@@ -88,7 +88,7 @@ class ESRGANInvocation(BaseInvocation, WithMetadata):
             netscale = 2
         else:
             msg = f"Invalid RealESRGAN model: {self.model_name}"
-            context.services.logger.error(msg)
+            context.logger.error(msg)
             raise ValueError(msg)
 
         esrgan_model_path = Path(f"core/upscaling/realesrgan/{self.model_name}")
@@ -111,19 +111,6 @@ class ESRGANInvocation(BaseInvocation, WithMetadata):
         if choose_torch_device() == torch.device("mps"):
             mps.empty_cache()
 
-        image_dto = context.services.images.create(
-            image=pil_image,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-            metadata=self.metadata,
-            workflow=context.workflow,
-        )
+        image_dto = context.images.save(image=pil_image)
 
-        return ImageOutput(
-            image=ImageField(image_name=image_dto.image_name),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
+        return ImageOutput.build(image_dto)
diff --git a/invokeai/app/services/events/events_base.py b/invokeai/app/services/events/events_base.py
index e9365f3349..ad08ae0395 100644
--- a/invokeai/app/services/events/events_base.py
+++ b/invokeai/app/services/events/events_base.py
@@ -55,7 +55,7 @@ class EventServiceBase:
         queue_item_id: int,
         queue_batch_id: str,
         graph_execution_state_id: str,
-        node: dict,
+        node_id: str,
         source_node_id: str,
         progress_image: Optional[ProgressImage],
         step: int,
@@ -70,7 +70,7 @@ class EventServiceBase:
                 "queue_item_id": queue_item_id,
                 "queue_batch_id": queue_batch_id,
                 "graph_execution_state_id": graph_execution_state_id,
-                "node_id": node.get("id"),
+                "node_id": node_id,
                 "source_node_id": source_node_id,
                 "progress_image": progress_image.model_dump() if progress_image is not None else None,
                 "step": step,
diff --git a/invokeai/app/services/invocation_processor/invocation_processor_default.py b/invokeai/app/services/invocation_processor/invocation_processor_default.py
index 54342c0da1..d2ebe235e6 100644
--- a/invokeai/app/services/invocation_processor/invocation_processor_default.py
+++ b/invokeai/app/services/invocation_processor/invocation_processor_default.py
@@ -5,11 +5,11 @@ from threading import BoundedSemaphore, Event, Thread
 from typing import Optional
 
 import invokeai.backend.util.logging as logger
-from invokeai.app.invocations.baseinvocation import InvocationContext
 from invokeai.app.services.invocation_queue.invocation_queue_common import InvocationQueueItem
 from invokeai.app.services.invocation_stats.invocation_stats_common import (
     GESStatsNotFoundError,
 )
+from invokeai.app.services.shared.invocation_context import InvocationContextData, build_invocation_context
 from invokeai.app.util.profiler import Profiler
 
 from ..invoker import Invoker
@@ -131,16 +131,20 @@ class DefaultInvocationProcessor(InvocationProcessorABC):
                         # which handles a few things:
                         # - nodes that require a value, but get it only from a connection
                         # - referencing the invocation cache instead of executing the node
-                        outputs = invocation.invoke_internal(
-                            InvocationContext(
-                                services=self.__invoker.services,
-                                graph_execution_state_id=graph_execution_state.id,
-                                queue_item_id=queue_item.session_queue_item_id,
-                                queue_id=queue_item.session_queue_id,
-                                queue_batch_id=queue_item.session_queue_batch_id,
-                                workflow=queue_item.workflow,
-                            )
+                        context_data = InvocationContextData(
+                            invocation=invocation,
+                            session_id=graph_id,
+                            workflow=queue_item.workflow,
+                            source_node_id=source_node_id,
+                            queue_id=queue_item.session_queue_id,
+                            queue_item_id=queue_item.session_queue_item_id,
+                            batch_id=queue_item.session_queue_batch_id,
                         )
+                        context = build_invocation_context(
+                            services=self.__invoker.services,
+                            context_data=context_data,
+                        )
+                        outputs = invocation.invoke_internal(context=context, services=self.__invoker.services)
 
                         # Check queue to see if this is canceled, and skip if so
                         if self.__invoker.services.queue.is_canceled(graph_execution_state.id):
diff --git a/invokeai/app/services/model_manager/model_manager_base.py b/invokeai/app/services/model_manager/model_manager_base.py
index 4c2fc4c085..a9b53ae224 100644
--- a/invokeai/app/services/model_manager/model_manager_base.py
+++ b/invokeai/app/services/model_manager/model_manager_base.py
@@ -5,11 +5,12 @@ from __future__ import annotations
 from abc import ABC, abstractmethod
 from logging import Logger
 from pathlib import Path
-from typing import TYPE_CHECKING, Callable, List, Literal, Optional, Tuple, Union
+from typing import Callable, List, Literal, Optional, Tuple, Union
 
 from pydantic import Field
 
 from invokeai.app.services.config.config_default import InvokeAIAppConfig
+from invokeai.app.services.shared.invocation_context import InvocationContextData
 from invokeai.backend.model_management import (
     AddModelResult,
     BaseModelType,
@@ -21,9 +22,6 @@ from invokeai.backend.model_management import (
 )
 from invokeai.backend.model_management.model_cache import CacheStats
 
-if TYPE_CHECKING:
-    from invokeai.app.invocations.baseinvocation import BaseInvocation, InvocationContext
-
 
 class ModelManagerServiceBase(ABC):
     """Responsible for managing models on disk and in memory"""
@@ -49,8 +47,7 @@ class ModelManagerServiceBase(ABC):
         base_model: BaseModelType,
         model_type: ModelType,
         submodel: Optional[SubModelType] = None,
-        node: Optional[BaseInvocation] = None,
-        context: Optional[InvocationContext] = None,
+        context_data: Optional[InvocationContextData] = None,
     ) -> ModelInfo:
         """Retrieve the indicated model with name and type.
         submodel can be used to get a part (such as the vae)
diff --git a/invokeai/app/services/model_manager/model_manager_common.py b/invokeai/app/services/model_manager/model_manager_common.py
new file mode 100644
index 0000000000..e69de29bb2
diff --git a/invokeai/app/services/model_manager/model_manager_default.py b/invokeai/app/services/model_manager/model_manager_default.py
index cdb3e59a91..b641dd3f1e 100644
--- a/invokeai/app/services/model_manager/model_manager_default.py
+++ b/invokeai/app/services/model_manager/model_manager_default.py
@@ -11,6 +11,8 @@ from pydantic import Field
 
 from invokeai.app.services.config.config_default import InvokeAIAppConfig
 from invokeai.app.services.invocation_processor.invocation_processor_common import CanceledException
+from invokeai.app.services.invoker import Invoker
+from invokeai.app.services.shared.invocation_context import InvocationContextData
 from invokeai.backend.model_management import (
     AddModelResult,
     BaseModelType,
@@ -30,7 +32,7 @@ from invokeai.backend.util import choose_precision, choose_torch_device
 from .model_manager_base import ModelManagerServiceBase
 
 if TYPE_CHECKING:
-    from invokeai.app.invocations.baseinvocation import InvocationContext
+    pass
 
 
 # simple implementation
@@ -86,13 +88,16 @@ class ModelManagerService(ModelManagerServiceBase):
         )
         logger.info("Model manager service initialized")
 
+    def start(self, invoker: Invoker) -> None:
+        self._invoker: Optional[Invoker] = invoker
+
     def get_model(
         self,
         model_name: str,
         base_model: BaseModelType,
         model_type: ModelType,
         submodel: Optional[SubModelType] = None,
-        context: Optional[InvocationContext] = None,
+        context_data: Optional[InvocationContextData] = None,
     ) -> ModelInfo:
         """
         Retrieve the indicated model. submodel can be used to get a
@@ -100,9 +105,9 @@ class ModelManagerService(ModelManagerServiceBase):
         """
 
         # we can emit model loading events if we are executing with access to the invocation context
-        if context:
+        if context_data is not None:
             self._emit_load_event(
-                context=context,
+                context_data=context_data,
                 model_name=model_name,
                 base_model=base_model,
                 model_type=model_type,
@@ -116,9 +121,9 @@ class ModelManagerService(ModelManagerServiceBase):
             submodel,
         )
 
-        if context:
+        if context_data is not None:
             self._emit_load_event(
-                context=context,
+                context_data=context_data,
                 model_name=model_name,
                 base_model=base_model,
                 model_type=model_type,
@@ -263,22 +268,25 @@ class ModelManagerService(ModelManagerServiceBase):
 
     def _emit_load_event(
         self,
-        context: InvocationContext,
+        context_data: InvocationContextData,
         model_name: str,
         base_model: BaseModelType,
         model_type: ModelType,
         submodel: Optional[SubModelType] = None,
         model_info: Optional[ModelInfo] = None,
     ):
-        if context.services.queue.is_canceled(context.graph_execution_state_id):
+        if self._invoker is None:
+            return
+
+        if self._invoker.services.queue.is_canceled(context_data.session_id):
             raise CanceledException()
 
         if model_info:
-            context.services.events.emit_model_load_completed(
-                queue_id=context.queue_id,
-                queue_item_id=context.queue_item_id,
-                queue_batch_id=context.queue_batch_id,
-                graph_execution_state_id=context.graph_execution_state_id,
+            self._invoker.services.events.emit_model_load_completed(
+                queue_id=context_data.queue_id,
+                queue_item_id=context_data.queue_item_id,
+                queue_batch_id=context_data.batch_id,
+                graph_execution_state_id=context_data.session_id,
                 model_name=model_name,
                 base_model=base_model,
                 model_type=model_type,
@@ -286,11 +294,11 @@ class ModelManagerService(ModelManagerServiceBase):
                 model_info=model_info,
             )
         else:
-            context.services.events.emit_model_load_started(
-                queue_id=context.queue_id,
-                queue_item_id=context.queue_item_id,
-                queue_batch_id=context.queue_batch_id,
-                graph_execution_state_id=context.graph_execution_state_id,
+            self._invoker.services.events.emit_model_load_started(
+                queue_id=context_data.queue_id,
+                queue_item_id=context_data.queue_item_id,
+                queue_batch_id=context_data.batch_id,
+                graph_execution_state_id=context_data.session_id,
                 model_name=model_name,
                 base_model=base_model,
                 model_type=model_type,
diff --git a/invokeai/app/services/shared/graph.py b/invokeai/app/services/shared/graph.py
index ba05b050c5..c0699eb96b 100644
--- a/invokeai/app/services/shared/graph.py
+++ b/invokeai/app/services/shared/graph.py
@@ -13,7 +13,6 @@ from invokeai.app.invocations import *  # noqa: F401 F403
 from invokeai.app.invocations.baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
-    InvocationContext,
     invocation,
     invocation_output,
 )
@@ -202,7 +201,7 @@ class GraphInvocation(BaseInvocation):
     # TODO: figure out how to create a default here
     graph: "Graph" = InputField(description="The graph to run", default=None)
 
-    def invoke(self, context: InvocationContext) -> GraphInvocationOutput:
+    def invoke(self, context) -> GraphInvocationOutput:
         """Invoke with provided services and return outputs."""
         return GraphInvocationOutput()
 
@@ -228,7 +227,7 @@ class IterateInvocation(BaseInvocation):
     )
     index: int = InputField(description="The index, will be provided on executed iterators", default=0, ui_hidden=True)
 
-    def invoke(self, context: InvocationContext) -> IterateInvocationOutput:
+    def invoke(self, context) -> IterateInvocationOutput:
         """Produces the outputs as values"""
         return IterateInvocationOutput(item=self.collection[self.index], index=self.index, total=len(self.collection))
 
@@ -255,7 +254,7 @@ class CollectInvocation(BaseInvocation):
         description="The collection, will be provided on execution", default=[], ui_hidden=True
     )
 
-    def invoke(self, context: InvocationContext) -> CollectInvocationOutput:
+    def invoke(self, context) -> CollectInvocationOutput:
         """Invoke with provided services and return outputs."""
         return CollectInvocationOutput(collection=copy.copy(self.collection))
 
diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index c0aaac54f8..b68e521c73 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -6,8 +6,7 @@ from PIL.Image import Image
 from pydantic import ConfigDict
 from torch import Tensor
 
-from invokeai.app.invocations.compel import ConditioningFieldData
-from invokeai.app.invocations.fields import MetadataField, WithMetadata
+from invokeai.app.invocations.fields import ConditioningFieldData, MetadataField, WithMetadata
 from invokeai.app.services.config.config_default import InvokeAIAppConfig
 from invokeai.app.services.image_records.image_records_common import ImageCategory, ImageRecordChanges, ResourceOrigin
 from invokeai.app.services.images.images_common import ImageDTO
@@ -245,13 +244,15 @@ class ConditioningInterface:
             )
             return name
 
-        def get(conditioning_name: str) -> Tensor:
+        def get(conditioning_name: str) -> ConditioningFieldData:
             """
             Gets conditioning data by name.
 
             :param conditioning_name: The name of the conditioning data to get.
             """
-            return services.latents.get(conditioning_name)
+            # TODO(sm): We are (ab)using the latents storage service as a general pickle storage
+            # service, but it is typed as returning tensors, so we need to ignore the type here.
+            return services.latents.get(conditioning_name) # type: ignore [return-value]
 
         self.save = save
         self.get = get
diff --git a/invokeai/app/util/step_callback.py b/invokeai/app/util/step_callback.py
index 5cc3caa9ba..d83b380d95 100644
--- a/invokeai/app/util/step_callback.py
+++ b/invokeai/app/util/step_callback.py
@@ -1,25 +1,18 @@
-from typing import Protocol
+from typing import TYPE_CHECKING
 
 import torch
 from PIL import Image
 
-from invokeai.app.services.events.events_base import EventServiceBase
 from invokeai.app.services.invocation_processor.invocation_processor_common import CanceledException, ProgressImage
-from invokeai.app.services.invocation_queue.invocation_queue_base import InvocationQueueABC
-from invokeai.app.services.shared.invocation_context import InvocationContextData
 
 from ...backend.model_management.models import BaseModelType
 from ...backend.stable_diffusion import PipelineIntermediateState
 from ...backend.util.util import image_to_dataURL
 
-
-class StepCallback(Protocol):
-    def __call__(
-        self,
-        intermediate_state: PipelineIntermediateState,
-        base_model: BaseModelType,
-    ) -> None:
-        ...
+if TYPE_CHECKING:
+    from invokeai.app.services.events.events_base import EventServiceBase
+    from invokeai.app.services.invocation_queue.invocation_queue_base import InvocationQueueABC
+    from invokeai.app.services.shared.invocation_context import InvocationContextData
 
 
 def sample_to_lowres_estimated_image(samples, latent_rgb_factors, smooth_matrix=None):
@@ -38,11 +31,11 @@ def sample_to_lowres_estimated_image(samples, latent_rgb_factors, smooth_matrix=
 
 
 def stable_diffusion_step_callback(
-    context_data: InvocationContextData,
+    context_data: "InvocationContextData",
     intermediate_state: PipelineIntermediateState,
     base_model: BaseModelType,
-    invocation_queue: InvocationQueueABC,
-    events: EventServiceBase,
+    invocation_queue: "InvocationQueueABC",
+    events: "EventServiceBase",
 ) -> None:
     if invocation_queue.is_canceled(context_data.session_id):
         raise CanceledException

From a79a450e9df089c0591037a7ca3696c7945f3e34 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 13 Jan 2024 23:23:27 +1100
Subject: [PATCH 043/411] docs: update INVOCATIONS.md

---
 docs/contributing/INVOCATIONS.md | 95 ++++++++++++--------------------
 1 file changed, 35 insertions(+), 60 deletions(-)

diff --git a/docs/contributing/INVOCATIONS.md b/docs/contributing/INVOCATIONS.md
index 124589f44c..5d9a3690ba 100644
--- a/docs/contributing/INVOCATIONS.md
+++ b/docs/contributing/INVOCATIONS.md
@@ -9,11 +9,15 @@ complex functionality.
 
 ## Invocations Directory
 
-InvokeAI Nodes can be found in the `invokeai/app/invocations` directory. These can be used as examples to create your own nodes.
+InvokeAI Nodes can be found in the `invokeai/app/invocations` directory. These
+can be used as examples to create your own nodes.
 
-New nodes should be added to a subfolder in `nodes` direction found at the root level of the InvokeAI installation location. Nodes added to this folder will be able to be used upon application startup. 
+New nodes should be added to a subfolder in `nodes` direction found at the root
+level of the InvokeAI installation location. Nodes added to this folder will be
+able to be used upon application startup.
+
+Example `nodes` subfolder structure:
 
-Example `nodes`  subfolder structure:
 ```py
 ├── __init__.py # Invoke-managed custom node loader
 │
@@ -30,14 +34,14 @@ Example `nodes`  subfolder structure:
         └── fancy_node.py
 ```
 
-Each node folder must have an `__init__.py` file that imports its nodes. Only nodes imported in the `__init__.py` file are loaded.
- See the README in the nodes folder for more examples: 
+Each node folder must have an `__init__.py` file that imports its nodes. Only
+nodes imported in the `__init__.py` file are loaded. See the README in the nodes
+folder for more examples:
 
 ```py
 from .cool_node import CoolInvocation
 ```
 
-
 ## Creating A New Invocation
 
 In order to understand the process of creating a new Invocation, let us actually
@@ -131,7 +135,6 @@ from invokeai.app.invocations.primitives import ImageField
 class ResizeInvocation(BaseInvocation):
     '''Resizes an image'''
 
-    # Inputs
     image: ImageField = InputField(description="The input image")
     width: int = InputField(default=512, ge=64, le=2048, description="Width of the new image")
     height: int = InputField(default=512, ge=64, le=2048, description="Height of the new image")
@@ -167,12 +170,11 @@ from invokeai.app.invocations.primitives import ImageField
 class ResizeInvocation(BaseInvocation):
     '''Resizes an image'''
 
-    # Inputs
     image: ImageField = InputField(description="The input image")
     width: int = InputField(default=512, ge=64, le=2048, description="Width of the new image")
     height: int = InputField(default=512, ge=64, le=2048, description="Height of the new image")
 
-    def invoke(self, context: InvocationContext):
+    def invoke(self, context):
         pass
 ```
 
@@ -197,12 +199,11 @@ from invokeai.app.invocations.image import ImageOutput
 class ResizeInvocation(BaseInvocation):
     '''Resizes an image'''
 
-    # Inputs
     image: ImageField = InputField(description="The input image")
     width: int = InputField(default=512, ge=64, le=2048, description="Width of the new image")
     height: int = InputField(default=512, ge=64, le=2048, description="Height of the new image")
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
+    def invoke(self, context) -> ImageOutput:
         pass
 ```
 
@@ -228,31 +229,18 @@ class ResizeInvocation(BaseInvocation):
     width: int = InputField(default=512, ge=64, le=2048, description="Width of the new image")
     height: int = InputField(default=512, ge=64, le=2048, description="Height of the new image")
 
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        # Load the image using InvokeAI's predefined Image Service. Returns the PIL image.
-        image = context.services.images.get_pil_image(self.image.image_name)
+    def invoke(self, context) -> ImageOutput:
+        # Load the input image as a PIL image
+        image = context.images.get_pil(self.image.image_name)
 
-        # Resizing the image
+        # Resize the image
         resized_image = image.resize((self.width, self.height))
 
-        # Save the image using InvokeAI's predefined Image Service. Returns the prepared PIL image.
-        output_image = context.services.images.create(
-            image=resized_image,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-        )
+        # Save the image
+        image_dto = context.images.save(image=resized_image)
 
-        # Returning the Image
-        return ImageOutput(
-            image=ImageField(
-                image_name=output_image.image_name,
-            ),
-            width=output_image.width,
-            height=output_image.height,
-        )
+        # Return an ImageOutput
+        return ImageOutput.build(image_dto)
 ```
 
 **Note:** Do not be overwhelmed by the `ImageOutput` process. InvokeAI has a
@@ -343,27 +331,25 @@ class ImageColorStringOutput(BaseInvocationOutput):
 
 That's all there is to it.
 
-<!-- TODO: DANGER - we probably do not want people to create their own field types, because this requires a lot of work on the frontend to accomodate.
-
 ### Custom Input Fields
 
 Now that you know how to create your own Invocations, let us dive into slightly
 more advanced topics.
 
 While creating your own Invocations, you might run into a scenario where the
-existing input types in InvokeAI do not meet your requirements. In such cases,
-you can create your own input types.
+existing fields in InvokeAI do not meet your requirements. In such cases, you
+can create your own fields.
 
 Let us create one as an example. Let us say we want to create a color input
 field that represents a color code. But before we start on that here are some
 general good practices to keep in mind.
 
-**Good Practices**
+### Best Practices
 
 - There is no naming convention for input fields but we highly recommend that
   you name it something appropriate like `ColorField`.
 - It is not mandatory but it is heavily recommended to add a relevant
-  `docstring` to describe your input field.
+  `docstring` to describe your field.
 - Keep your field in the same file as the Invocation that it is made for or in
   another file where it is relevant.
 
@@ -378,10 +364,13 @@ class ColorField(BaseModel):
     pass
 ```
 
-Perfect. Now let us create our custom inputs for our field. This is exactly
-similar how you created input fields for your Invocation. All the same rules
-apply. Let us create four fields representing the _red(r)_, _blue(b)_,
-_green(g)_ and _alpha(a)_ channel of the color.
+Perfect. Now let us create the properties for our field. This is similar to how
+you created input fields for your Invocation. All the same rules apply. Let us
+create four fields representing the _red(r)_, _blue(b)_, _green(g)_ and
+_alpha(a)_ channel of the color.
+
+> Technically, the properties are _also_ called fields - but in this case, it
+> refers to a `pydantic` field.
 
 ```python
 class ColorField(BaseModel):
@@ -396,25 +385,11 @@ That's it. We now have a new input field type that we can use in our Invocations
 like this.
 
 ```python
-color: ColorField = Field(default=ColorField(r=0, g=0, b=0, a=0), description='Background color of an image')
+color: ColorField = InputField(default=ColorField(r=0, g=0, b=0, a=0), description='Background color of an image')
 ```
 
-### Custom Components For Frontend
+### Using the custom field
 
-Every backend input type should have a corresponding frontend component so the
-UI knows what to render when you use a particular field type.
+When you start the UI, your custom field will be automatically recognized.
 
-If you are using existing field types, we already have components for those. So
-you don't have to worry about creating anything new. But this might not always
-be the case. Sometimes you might want to create new field types and have the
-frontend UI deal with it in a different way.
-
-This is where we venture into the world of React and Javascript and create our
-own new components for our Invocations. Do not fear the world of JS. It's
-actually pretty straightforward.
-
-Let us create a new component for our custom color field we created above. When
-we use a color field, let us say we want the UI to display a color picker for
-the user to pick from rather than entering values. That is what we will build
-now.
--->
+Custom fields only support connection inputs in the Workflow Editor.

From ef2728356937574db1de80a9a2c8b27208ffd3ce Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 13 Jan 2024 23:23:38 +1100
Subject: [PATCH 044/411] tests: fix tests for new invocation context

---
 tests/aa_nodes/test_graph_execution_state.py |  8 +-------
 tests/aa_nodes/test_nodes.py                 | 17 ++++++++---------
 2 files changed, 9 insertions(+), 16 deletions(-)

diff --git a/tests/aa_nodes/test_graph_execution_state.py b/tests/aa_nodes/test_graph_execution_state.py
index fab1fa4598..9cc30e43e1 100644
--- a/tests/aa_nodes/test_graph_execution_state.py
+++ b/tests/aa_nodes/test_graph_execution_state.py
@@ -21,7 +21,6 @@ from invokeai.app.services.invocation_processor.invocation_processor_default imp
 from invokeai.app.services.invocation_queue.invocation_queue_memory import MemoryInvocationQueue
 from invokeai.app.services.invocation_services import InvocationServices
 from invokeai.app.services.invocation_stats.invocation_stats_default import InvocationStatsService
-from invokeai.app.services.session_queue.session_queue_common import DEFAULT_QUEUE_ID
 from invokeai.app.services.shared.graph import (
     CollectInvocation,
     Graph,
@@ -86,12 +85,7 @@ def invoke_next(g: GraphExecutionState, services: InvocationServices) -> tuple[B
     print(f"invoking {n.id}: {type(n)}")
     o = n.invoke(
         InvocationContext(
-            queue_batch_id="1",
-            queue_item_id=1,
-            queue_id=DEFAULT_QUEUE_ID,
-            services=services,
-            graph_execution_state_id="1",
-            workflow=None,
+            conditioning=None, config=None, data=None, images=None, latents=None, logger=None, models=None, util=None
         )
     )
     g.complete(n.id, o)
diff --git a/tests/aa_nodes/test_nodes.py b/tests/aa_nodes/test_nodes.py
index e71daad3f3..559457c0e1 100644
--- a/tests/aa_nodes/test_nodes.py
+++ b/tests/aa_nodes/test_nodes.py
@@ -3,7 +3,6 @@ from typing import Any, Callable, Union
 from invokeai.app.invocations.baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
-    InvocationContext,
     invocation,
     invocation_output,
 )
@@ -21,7 +20,7 @@ class ListPassThroughInvocationOutput(BaseInvocationOutput):
 class ListPassThroughInvocation(BaseInvocation):
     collection: list[ImageField] = InputField(default=[])
 
-    def invoke(self, context: InvocationContext) -> ListPassThroughInvocationOutput:
+    def invoke(self, context) -> ListPassThroughInvocationOutput:
         return ListPassThroughInvocationOutput(collection=self.collection)
 
 
@@ -34,13 +33,13 @@ class PromptTestInvocationOutput(BaseInvocationOutput):
 class PromptTestInvocation(BaseInvocation):
     prompt: str = InputField(default="")
 
-    def invoke(self, context: InvocationContext) -> PromptTestInvocationOutput:
+    def invoke(self, context) -> PromptTestInvocationOutput:
         return PromptTestInvocationOutput(prompt=self.prompt)
 
 
 @invocation("test_error", version="1.0.0")
 class ErrorInvocation(BaseInvocation):
-    def invoke(self, context: InvocationContext) -> PromptTestInvocationOutput:
+    def invoke(self, context) -> PromptTestInvocationOutput:
         raise Exception("This invocation is supposed to fail")
 
 
@@ -54,7 +53,7 @@ class TextToImageTestInvocation(BaseInvocation):
     prompt: str = InputField(default="")
     prompt2: str = InputField(default="")
 
-    def invoke(self, context: InvocationContext) -> ImageTestInvocationOutput:
+    def invoke(self, context) -> ImageTestInvocationOutput:
         return ImageTestInvocationOutput(image=ImageField(image_name=self.id))
 
 
@@ -63,7 +62,7 @@ class ImageToImageTestInvocation(BaseInvocation):
     prompt: str = InputField(default="")
     image: Union[ImageField, None] = InputField(default=None)
 
-    def invoke(self, context: InvocationContext) -> ImageTestInvocationOutput:
+    def invoke(self, context) -> ImageTestInvocationOutput:
         return ImageTestInvocationOutput(image=ImageField(image_name=self.id))
 
 
@@ -76,7 +75,7 @@ class PromptCollectionTestInvocationOutput(BaseInvocationOutput):
 class PromptCollectionTestInvocation(BaseInvocation):
     collection: list[str] = InputField()
 
-    def invoke(self, context: InvocationContext) -> PromptCollectionTestInvocationOutput:
+    def invoke(self, context) -> PromptCollectionTestInvocationOutput:
         return PromptCollectionTestInvocationOutput(collection=self.collection.copy())
 
 
@@ -89,7 +88,7 @@ class AnyTypeTestInvocationOutput(BaseInvocationOutput):
 class AnyTypeTestInvocation(BaseInvocation):
     value: Any = InputField(default=None)
 
-    def invoke(self, context: InvocationContext) -> AnyTypeTestInvocationOutput:
+    def invoke(self, context) -> AnyTypeTestInvocationOutput:
         return AnyTypeTestInvocationOutput(value=self.value)
 
 
@@ -97,7 +96,7 @@ class AnyTypeTestInvocation(BaseInvocation):
 class PolymorphicStringTestInvocation(BaseInvocation):
     value: Union[str, list[str]] = InputField(default="")
 
-    def invoke(self, context: InvocationContext) -> PromptCollectionTestInvocationOutput:
+    def invoke(self, context) -> PromptCollectionTestInvocationOutput:
         if isinstance(self.value, str):
             return PromptCollectionTestInvocationOutput(collection=[self.value])
         return PromptCollectionTestInvocationOutput(collection=self.value)

From 1616974b482bc7f68e648604035792b80fae0c28 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sun, 14 Jan 2024 00:05:15 +1100
Subject: [PATCH 045/411] feat(nodes): tidy `invocation_context.py`, improve
 comments

---
 .../app/services/shared/invocation_context.py | 119 ++++++++++++------
 1 file changed, 82 insertions(+), 37 deletions(-)

diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index b68e521c73..7961c011af 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -1,5 +1,4 @@
 from dataclasses import dataclass
-from enum import Enum
 from typing import TYPE_CHECKING, Optional
 
 from PIL.Image import Image
@@ -37,6 +36,9 @@ Wrapping these services provides a simpler and safer interface for nodes to use.
 When a node executes, a fresh `InvocationContext` is built for it, ensuring nodes cannot interfere
 with each other.
 
+Many of the wrappers have the same signature as the methods they wrap. This allows us to write
+user-facing docstrings and not need to go and update the internal services to match.
+
 Note: The docstrings are in weird places, but that's where they must be to get IDEs to see them.
 """
 
@@ -44,12 +46,19 @@ Note: The docstrings are in weird places, but that's where they must be to get I
 @dataclass(frozen=True)
 class InvocationContextData:
     invocation: "BaseInvocation"
+    """The invocation that is being executed."""
     session_id: str
+    """The session that is being executed."""
     queue_id: str
+    """The queue in which the session is being executed."""
     source_node_id: str
+    """The ID of the node from which the currently executing invocation was prepared."""
     queue_item_id: int
+    """The ID of the queue item that is being executed."""
     batch_id: str
+    """The ID of the batch that is being executed."""
     workflow: Optional[WorkflowWithoutID] = None
+    """The workflow associated with this queue item, if any."""
 
 
 class LoggerInterface:
@@ -103,14 +112,15 @@ class ImagesInterface:
             """
             Saves an image, returning its DTO.
 
-            If the current queue item has a workflow, it is automatically saved with the image.
+            If the current queue item has a workflow or metadata, it is automatically saved with the image.
 
             :param image: The image to save, as a PIL image.
             :param board_id: The board ID to add the image to, if it should be added.
-            :param image_category: The category of the image. Only the GENERAL category is added to the gallery.
-            :param metadata: The metadata to save with the image, if it should have any. If the invocation inherits \
-                from `WithMetadata`, that metadata will be used automatically. Provide this only if you want to \
-                override or provide metadata manually.
+            :param image_category: The category of the image. Only the GENERAL category is added \
+                to the gallery.
+            :param metadata: The metadata to save with the image, if it should have any. If the \
+                invocation inherits from `WithMetadata`, that metadata will be used automatically. \
+                **Use this only if you want to override or provide metadata manually!**
             """
 
             # If the invocation inherits metadata, use that. Else, use the metadata passed in.
@@ -186,14 +196,6 @@ class ImagesInterface:
         self.update = update
 
 
-class LatentsKind(str, Enum):
-    IMAGE = "image"
-    NOISE = "noise"
-    MASK = "mask"
-    MASKED_IMAGE = "masked_image"
-    OTHER = "other"
-
-
 class LatentsInterface:
     def __init__(
         self,
@@ -206,6 +208,22 @@ class LatentsInterface:
 
             :param tensor: The latents tensor to save.
             """
+
+            # Previously, we added a suffix indicating the type of Tensor we were saving, e.g.
+            # "mask", "noise", "masked_latents", etc.
+            #
+            # Retaining that capability in this wrapper would require either many different methods
+            # to save latents, or extra args for this method. Instead of complicating the API, we
+            # will use the same naming scheme for all latents.
+            #
+            # This has a very minor impact as we don't use them after a session completes.
+
+            # Previously, invocations chose the name for their latents. This is a bit risky, so we
+            # will generate a name for them instead. We use a uuid to ensure the name is unique.
+            #
+            # Because the name of the latents file will includes the session and invocation IDs,
+            # we don't need to worry about collisions. A truncated UUIDv4 is fine.
+
             name = f"{context_data.session_id}__{context_data.invocation.id}__{uuid_string()[:7]}"
             services.latents.save(
                 name=name,
@@ -231,12 +249,21 @@ class ConditioningInterface:
         services: InvocationServices,
         context_data: InvocationContextData,
     ) -> None:
+        # TODO(psyche): We are (ab)using the latents storage service as a general pickle storage
+        # service, but it is typed to work with Tensors only. We have to fudge the types here.
+
         def save(conditioning_data: ConditioningFieldData) -> str:
             """
             Saves a conditioning data object, returning its name.
 
             :param conditioning_data: The conditioning data to save.
             """
+
+            # Conditioning data is *not* a Tensor, so we will suffix it to indicate this.
+            #
+            # See comment for `LatentsInterface.save` for more info about this method (it's very
+            # similar).
+
             name = f"{context_data.session_id}__{context_data.invocation.id}__{uuid_string()[:7]}__conditioning"
             services.latents.save(
                 name=name,
@@ -250,9 +277,8 @@ class ConditioningInterface:
 
             :param conditioning_name: The name of the conditioning data to get.
             """
-            # TODO(sm): We are (ab)using the latents storage service as a general pickle storage
-            # service, but it is typed as returning tensors, so we need to ignore the type here.
-            return services.latents.get(conditioning_name) # type: ignore [return-value]
+
+            return services.latents.get(conditioning_name)  # type: ignore [return-value]
 
         self.save = save
         self.get = get
@@ -281,6 +307,17 @@ class ModelsInterface:
             :param model_type: The type of the model to get.
             :param submodel: The submodel of the model to get.
             """
+
+            # During this call, the model manager emits events with model loading status. The model
+            # manager itself has access to the events services, but does not have access to the
+            # required metadata for the events.
+            #
+            # For example, it needs access to the node's ID so that the events can be associated
+            # with the execution of a specific node.
+            #
+            # While this is available within the node, it's tedious to need to pass it in on every
+            # call. We can avoid that by wrapping the method here.
+
             return services.model_manager.get_model(
                 model_name, base_model, model_type, submodel, context_data=context_data
             )
@@ -306,8 +343,11 @@ class ConfigInterface:
             """
             Gets the app's config.
             """
-            # The config can be changed at runtime. We don't want nodes doing this, so we make a
-            # frozen copy..
+
+            # The config can be changed at runtime.
+            #
+            # We don't want nodes doing this, so we make a frozen copy.
+
             config = services.configuration.get_config()
             frozen_config = config.model_copy(update={"model_config": ConfigDict(frozen=True)})
             return frozen_config
@@ -330,6 +370,12 @@ class UtilInterface:
             :param intermediate_state: The intermediate state of the diffusion pipeline.
             :param base_model: The base model for the current denoising step.
             """
+
+            # The step callback needs access to the events and the invocation queue services, but this
+            # represents a dangerous level of access.
+            #
+            # We wrap the step callback so that nodes do not have direct access to these services.
+
             stable_diffusion_step_callback(
                 context_data=context_data,
                 intermediate_state=intermediate_state,
@@ -343,36 +389,36 @@ class UtilInterface:
 
 class InvocationContext:
     """
-    The invocation context provides access to various services and data about the current invocation.
+    The `InvocationContext` provides access to various services and data for the current invocation.
     """
 
     def __init__(
         self,
         images: ImagesInterface,
         latents: LatentsInterface,
-        models: ModelsInterface,
-        config: ConfigInterface,
-        logger: LoggerInterface,
-        data: InvocationContextData,
-        util: UtilInterface,
         conditioning: ConditioningInterface,
+        models: ModelsInterface,
+        logger: LoggerInterface,
+        config: ConfigInterface,
+        util: UtilInterface,
+        data: InvocationContextData,
     ) -> None:
         self.images = images
-        "Provides methods to save, get and update images and their metadata."
-        self.logger = logger
-        "Provides access to the app logger."
+        """Provides methods to save, get and update images and their metadata."""
         self.latents = latents
-        "Provides methods to save and get latents tensors, including image, noise, masks, and masked images."
+        """Provides methods to save and get latents tensors, including image, noise, masks, and masked images."""
         self.conditioning = conditioning
-        "Provides methods to save and get conditioning data."
+        """Provides methods to save and get conditioning data."""
         self.models = models
-        "Provides methods to check if a model exists, get a model, and get a model's info."
+        """Provides methods to check if a model exists, get a model, and get a model's info."""
+        self.logger = logger
+        """Provides access to the app logger."""
         self.config = config
-        "Provides access to the app's config."
-        self.data = data
-        "Provides data about the current queue item and invocation."
+        """Provides access to the app's config."""
         self.util = util
-        "Provides utility methods."
+        """Provides utility methods."""
+        self.data = data
+        """Provides data about the current queue item and invocation."""
 
 
 def build_invocation_context(
@@ -380,8 +426,7 @@ def build_invocation_context(
     context_data: InvocationContextData,
 ) -> InvocationContext:
     """
-    Builds the invocation context. This is a wrapper around the invocation services that provides
-    a more convenient (and less dangerous) interface for nodes to use.
+    Builds the invocation context for a specific invocation execution.
 
     :param invocation_services: The invocation services to wrap.
     :param invocation_context_data: The invocation context data.

From 9af05536522b131a82b0b4e3a5ca4f9bfb8709c7 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sun, 14 Jan 2024 00:34:56 +1100
Subject: [PATCH 046/411] chore: ruff

---
 invokeai/app/invocations/baseinvocation.py | 1 -
 invokeai/app/invocations/onnx.py           | 2 +-
 2 files changed, 1 insertion(+), 2 deletions(-)

diff --git a/invokeai/app/invocations/baseinvocation.py b/invokeai/app/invocations/baseinvocation.py
index c4aed1fac5..df0596c9a1 100644
--- a/invokeai/app/invocations/baseinvocation.py
+++ b/invokeai/app/invocations/baseinvocation.py
@@ -22,7 +22,6 @@ from invokeai.app.invocations.fields import (
     Input,
     InputFieldJSONSchemaExtra,
     MetadataField,
-    logger,
 )
 from invokeai.app.services.config.config_default import InvokeAIAppConfig
 from invokeai.app.services.shared.invocation_context import InvocationContext
diff --git a/invokeai/app/invocations/onnx.py b/invokeai/app/invocations/onnx.py
index 3f8e6669ab..a1e318a380 100644
--- a/invokeai/app/invocations/onnx.py
+++ b/invokeai/app/invocations/onnx.py
@@ -318,7 +318,7 @@ class ONNXTextToLatentsInvocation(BaseInvocation):
 
         name = f"{context.graph_execution_state_id}__{self.id}"
         context.services.latents.save(name, latents)
-        return build_latents_output(latents_name=name, latents=torch.from_numpy(latents))
+        # return build_latents_output(latents_name=name, latents=torch.from_numpy(latents))
 
 
 # Latent to image

From f612a96afdc9ddcbf32c67edeb63513a45648678 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sun, 14 Jan 2024 20:16:51 +1100
Subject: [PATCH 047/411] feat(nodes): restore previous invocation context
 methods with deprecation warnings

---
 .../app/services/shared/invocation_context.py | 117 +++++++++++++++++-
 pyproject.toml                                |   1 +
 2 files changed, 117 insertions(+), 1 deletion(-)

diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index 7961c011af..023274d49f 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -1,6 +1,7 @@
 from dataclasses import dataclass
 from typing import TYPE_CHECKING, Optional
 
+from deprecated import deprecated
 from PIL.Image import Image
 from pydantic import ConfigDict
 from torch import Tensor
@@ -365,7 +366,7 @@ class UtilInterface:
             The step callback emits a progress event with the current step, the total number of
             steps, a preview image, and some other internal metadata.
 
-            This should be called after each step of the diffusion process.
+            This should be called after each denoising step.
 
             :param intermediate_state: The intermediate state of the diffusion pipeline.
             :param base_model: The base model for the current denoising step.
@@ -387,6 +388,30 @@ class UtilInterface:
         self.sd_step_callback = sd_step_callback
 
 
+deprecation_version = "3.7.0"
+removed_version = "3.8.0"
+
+
+def get_deprecation_reason(property_name: str, alternative: Optional[str] = None) -> str:
+    msg = f"{property_name} is deprecated as of v{deprecation_version}. It will be removed in v{removed_version}."
+    if alternative is not None:
+        msg += f" Use {alternative} instead."
+    msg += " See PLACEHOLDER_URL for details."
+    return msg
+
+
+# Deprecation docstrings template. I don't think we can implement these programmatically with
+# __doc__ because the IDE won't see them.
+
+"""
+**DEPRECATED as of v3.7.0**
+
+PROPERTY_NAME will be removed in v3.8.0. Use ALTERNATIVE instead. See PLACEHOLDER_URL for details.
+
+OG_DOCSTRING
+"""
+
+
 class InvocationContext:
     """
     The `InvocationContext` provides access to various services and data for the current invocation.
@@ -402,6 +427,7 @@ class InvocationContext:
         config: ConfigInterface,
         util: UtilInterface,
         data: InvocationContextData,
+        services: InvocationServices,
     ) -> None:
         self.images = images
         """Provides methods to save, get and update images and their metadata."""
@@ -419,6 +445,94 @@ class InvocationContext:
         """Provides utility methods."""
         self.data = data
         """Provides data about the current queue item and invocation."""
+        self.__services = services
+
+    @property
+    @deprecated(version=deprecation_version, reason=get_deprecation_reason("`context.services`"))
+    def services(self) -> InvocationServices:
+        """
+        **DEPRECATED as of v3.7.0**
+
+        `context.services` will be removed in v3.8.0. See PLACEHOLDER_URL for details.
+
+        The invocation services.
+        """
+        return self.__services
+
+    @property
+    @deprecated(
+        version=deprecation_version,
+        reason=get_deprecation_reason("`context.graph_execution_state_api`", "`context.data.session_id`"),
+    )
+    def graph_execution_state_id(self) -> str:
+        """
+        **DEPRECATED as of v3.7.0**
+
+        `context.graph_execution_state_api` will be removed in v3.8.0. Use `context.data.session_id` instead. See PLACEHOLDER_URL for details.
+
+        The ID of the session (aka graph execution state).
+        """
+        return self.data.session_id
+
+    @property
+    @deprecated(
+        version=deprecation_version,
+        reason=get_deprecation_reason("`context.queue_id`", "`context.data.queue_id`"),
+    )
+    def queue_id(self) -> str:
+        """
+        **DEPRECATED as of v3.7.0**
+
+        `context.queue_id` will be removed in v3.8.0. Use `context.data.queue_id` instead. See PLACEHOLDER_URL for details.
+
+        The ID of the queue.
+        """
+        return self.data.queue_id
+
+    @property
+    @deprecated(
+        version=deprecation_version,
+        reason=get_deprecation_reason("`context.queue_item_id`", "`context.data.queue_item_id`"),
+    )
+    def queue_item_id(self) -> int:
+        """
+        **DEPRECATED as of v3.7.0**
+
+        `context.queue_item_id` will be removed in v3.8.0. Use `context.data.queue_item_id` instead. See PLACEHOLDER_URL for details.
+
+        The ID of the queue item.
+        """
+        return self.data.queue_item_id
+
+    @property
+    @deprecated(
+        version=deprecation_version,
+        reason=get_deprecation_reason("`context.queue_batch_id`", "`context.data.batch_id`"),
+    )
+    def queue_batch_id(self) -> str:
+        """
+        **DEPRECATED as of v3.7.0**
+
+        `context.queue_batch_id` will be removed in v3.8.0. Use `context.data.batch_id` instead. See PLACEHOLDER_URL for details.
+
+        The ID of the batch.
+        """
+        return self.data.batch_id
+
+    @property
+    @deprecated(
+        version=deprecation_version,
+        reason=get_deprecation_reason("`context.workflow`", "`context.data.workflow`"),
+    )
+    def workflow(self) -> Optional[WorkflowWithoutID]:
+        """
+        **DEPRECATED as of v3.7.0**
+
+        `context.workflow` will be removed in v3.8.0. Use `context.data.workflow` instead. See PLACEHOLDER_URL for details.
+
+        The workflow associated with this queue item, if any.
+        """
+        return self.data.workflow
 
 
 def build_invocation_context(
@@ -449,6 +563,7 @@ def build_invocation_context(
         data=context_data,
         util=util,
         conditioning=conditioning,
+        services=services,
     )
 
     return ctx
diff --git a/pyproject.toml b/pyproject.toml
index d063f1ad0e..8d25ed2091 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -66,6 +66,7 @@ dependencies = [
   "albumentations",
   "click",
   "datasets",
+  "Deprecated",
   "dnspython~=2.4.0",
   "dynamicprompts",
   "easing-functions",

From 6452c706e1269ca40100e2216c39a9ca2b5371c3 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 15 Jan 2024 09:37:05 +1100
Subject: [PATCH 048/411] tests: fix missing arg for InvocationContext

---
 tests/aa_nodes/test_graph_execution_state.py | 10 +++++++++-
 1 file changed, 9 insertions(+), 1 deletion(-)

diff --git a/tests/aa_nodes/test_graph_execution_state.py b/tests/aa_nodes/test_graph_execution_state.py
index 9cc30e43e1..3577a78ae2 100644
--- a/tests/aa_nodes/test_graph_execution_state.py
+++ b/tests/aa_nodes/test_graph_execution_state.py
@@ -85,7 +85,15 @@ def invoke_next(g: GraphExecutionState, services: InvocationServices) -> tuple[B
     print(f"invoking {n.id}: {type(n)}")
     o = n.invoke(
         InvocationContext(
-            conditioning=None, config=None, data=None, images=None, latents=None, logger=None, models=None, util=None
+            conditioning=None,
+            config=None,
+            data=None,
+            images=None,
+            latents=None,
+            logger=None,
+            models=None,
+            util=None,
+            services=None,
         )
     )
     g.complete(n.id, o)

From 05fb485d33dca9df114fbc35aa33170918ea619a Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 15 Jan 2024 10:41:25 +1100
Subject: [PATCH 049/411] feat(nodes): move `ConditioningFieldData` to
 `conditioning_data.py`

---
 invokeai/app/invocations/compel.py                       | 2 +-
 invokeai/app/invocations/fields.py                       | 9 +--------
 invokeai/app/services/shared/invocation_context.py       | 3 ++-
 .../stable_diffusion/diffusion/conditioning_data.py      | 5 +++++
 4 files changed, 9 insertions(+), 10 deletions(-)

diff --git a/invokeai/app/invocations/compel.py b/invokeai/app/invocations/compel.py
index b4496031bc..94caf4128d 100644
--- a/invokeai/app/invocations/compel.py
+++ b/invokeai/app/invocations/compel.py
@@ -5,7 +5,6 @@ from compel import Compel, ReturnedEmbeddingsType
 from compel.prompt_parser import Blend, Conjunction, CrossAttentionControlSubstitute, FlattenedPrompt, Fragment
 
 from invokeai.app.invocations.fields import (
-    ConditioningFieldData,
     FieldDescriptions,
     Input,
     InputField,
@@ -15,6 +14,7 @@ from invokeai.app.invocations.fields import (
 from invokeai.app.invocations.primitives import ConditioningOutput
 from invokeai.backend.stable_diffusion.diffusion.conditioning_data import (
     BasicConditioningInfo,
+    ConditioningFieldData,
     ExtraConditioningInfo,
     SDXLConditioningInfo,
 )
diff --git a/invokeai/app/invocations/fields.py b/invokeai/app/invocations/fields.py
index 566babbb6b..8879f76077 100644
--- a/invokeai/app/invocations/fields.py
+++ b/invokeai/app/invocations/fields.py
@@ -1,13 +1,11 @@
-from dataclasses import dataclass
 from enum import Enum
-from typing import Any, Callable, List, Optional, Tuple
+from typing import Any, Callable, Optional, Tuple
 
 from pydantic import BaseModel, ConfigDict, Field, RootModel, TypeAdapter
 from pydantic.fields import _Unset
 from pydantic_core import PydanticUndefined
 
 from invokeai.app.util.metaenum import MetaEnum
-from invokeai.backend.stable_diffusion.diffusion.conditioning_data import BasicConditioningInfo
 from invokeai.backend.util.logging import InvokeAILogger
 
 logger = InvokeAILogger.get_logger()
@@ -544,11 +542,6 @@ class ColorField(BaseModel):
         return (self.r, self.g, self.b, self.a)
 
 
-@dataclass
-class ConditioningFieldData:
-    conditionings: List[BasicConditioningInfo]
-
-
 class ConditioningField(BaseModel):
     """A conditioning tensor primitive value"""
 
diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index 023274d49f..3cf3952de0 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -6,7 +6,7 @@ from PIL.Image import Image
 from pydantic import ConfigDict
 from torch import Tensor
 
-from invokeai.app.invocations.fields import ConditioningFieldData, MetadataField, WithMetadata
+from invokeai.app.invocations.fields import MetadataField, WithMetadata
 from invokeai.app.services.config.config_default import InvokeAIAppConfig
 from invokeai.app.services.image_records.image_records_common import ImageCategory, ImageRecordChanges, ResourceOrigin
 from invokeai.app.services.images.images_common import ImageDTO
@@ -17,6 +17,7 @@ from invokeai.app.util.step_callback import stable_diffusion_step_callback
 from invokeai.backend.model_management.model_manager import ModelInfo
 from invokeai.backend.model_management.models.base import BaseModelType, ModelType, SubModelType
 from invokeai.backend.stable_diffusion.diffusers_pipeline import PipelineIntermediateState
+from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ConditioningFieldData
 
 if TYPE_CHECKING:
     from invokeai.app.invocations.baseinvocation import BaseInvocation
diff --git a/invokeai/backend/stable_diffusion/diffusion/conditioning_data.py b/invokeai/backend/stable_diffusion/diffusion/conditioning_data.py
index 3e38f9f78d..0676555f7a 100644
--- a/invokeai/backend/stable_diffusion/diffusion/conditioning_data.py
+++ b/invokeai/backend/stable_diffusion/diffusion/conditioning_data.py
@@ -32,6 +32,11 @@ class BasicConditioningInfo:
         return self
 
 
+@dataclass
+class ConditioningFieldData:
+    conditionings: List[BasicConditioningInfo]
+
+
 @dataclass
 class SDXLConditioningInfo(BasicConditioningInfo):
     pooled_embeds: torch.Tensor

From a466f7a94b7ecf41e0a41c862ab34b72ccf5076c Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 15 Jan 2024 10:48:33 +1100
Subject: [PATCH 050/411] feat(nodes): create invocation_api.py

This is the public API for invocations.

Everything a custom node might need should be re-exported from this file.
---
 .../controlnet_image_processors.py            |   3 +-
 invokeai/app/invocations/facetools.py         |   3 +-
 invokeai/app/invocations/image.py             |   2 +-
 invokeai/app/invocations/infill.py            |   4 +-
 invokeai/app/invocations/tiles.py             |   3 +-
 invokeai/invocation_api/__init__.py           | 109 ++++++++++++++++++
 pyproject.toml                                |   1 +
 7 files changed, 116 insertions(+), 9 deletions(-)
 create mode 100644 invokeai/invocation_api/__init__.py

diff --git a/invokeai/app/invocations/controlnet_image_processors.py b/invokeai/app/invocations/controlnet_image_processors.py
index 3797722c93..e993ceffde 100644
--- a/invokeai/app/invocations/controlnet_image_processors.py
+++ b/invokeai/app/invocations/controlnet_image_processors.py
@@ -25,8 +25,7 @@ from controlnet_aux.util import HWC3, ade_palette
 from PIL import Image
 from pydantic import BaseModel, ConfigDict, Field, field_validator, model_validator
 
-from invokeai.app.invocations.baseinvocation import WithMetadata
-from invokeai.app.invocations.fields import FieldDescriptions, ImageField, Input, InputField, OutputField
+from invokeai.app.invocations.fields import FieldDescriptions, ImageField, Input, InputField, OutputField, WithMetadata
 from invokeai.app.invocations.primitives import ImageOutput
 from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
 from invokeai.backend.image_util.depth_anything import DepthAnythingDetector
diff --git a/invokeai/app/invocations/facetools.py b/invokeai/app/invocations/facetools.py
index 2c92e28cfe..dad6308981 100644
--- a/invokeai/app/invocations/facetools.py
+++ b/invokeai/app/invocations/facetools.py
@@ -13,11 +13,10 @@ from pydantic import field_validator
 import invokeai.assets.fonts as font_assets
 from invokeai.app.invocations.baseinvocation import (
     BaseInvocation,
-    WithMetadata,
     invocation,
     invocation_output,
 )
-from invokeai.app.invocations.fields import ImageField, InputField, OutputField
+from invokeai.app.invocations.fields import ImageField, InputField, OutputField, WithMetadata
 from invokeai.app.invocations.primitives import ImageOutput
 from invokeai.app.services.image_records.image_records_common import ImageCategory
 
diff --git a/invokeai/app/invocations/image.py b/invokeai/app/invocations/image.py
index 10ebd97ace..3b8b0b4b80 100644
--- a/invokeai/app/invocations/image.py
+++ b/invokeai/app/invocations/image.py
@@ -7,7 +7,6 @@ import cv2
 import numpy
 from PIL import Image, ImageChops, ImageFilter, ImageOps
 
-from invokeai.app.invocations.baseinvocation import WithMetadata
 from invokeai.app.invocations.fields import (
     BoardField,
     ColorField,
@@ -15,6 +14,7 @@ from invokeai.app.invocations.fields import (
     ImageField,
     Input,
     InputField,
+    WithMetadata,
 )
 from invokeai.app.invocations.primitives import ImageOutput
 from invokeai.app.services.image_records.image_records_common import ImageCategory
diff --git a/invokeai/app/invocations/infill.py b/invokeai/app/invocations/infill.py
index be51c8312f..159bdb5f7a 100644
--- a/invokeai/app/invocations/infill.py
+++ b/invokeai/app/invocations/infill.py
@@ -13,8 +13,8 @@ from invokeai.backend.image_util.cv2_inpaint import cv2_inpaint
 from invokeai.backend.image_util.lama import LaMA
 from invokeai.backend.image_util.patchmatch import PatchMatch
 
-from .baseinvocation import BaseInvocation, WithMetadata, invocation
-from .fields import InputField
+from .baseinvocation import BaseInvocation, invocation
+from .fields import InputField, WithMetadata
 from .image import PIL_RESAMPLING_MAP, PIL_RESAMPLING_MODES
 
 
diff --git a/invokeai/app/invocations/tiles.py b/invokeai/app/invocations/tiles.py
index dd34c3dc09..0b4c472696 100644
--- a/invokeai/app/invocations/tiles.py
+++ b/invokeai/app/invocations/tiles.py
@@ -8,11 +8,10 @@ from invokeai.app.invocations.baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
     Classification,
-    WithMetadata,
     invocation,
     invocation_output,
 )
-from invokeai.app.invocations.fields import ImageField, Input, InputField, OutputField
+from invokeai.app.invocations.fields import ImageField, Input, InputField, OutputField, WithMetadata
 from invokeai.app.invocations.primitives import ImageOutput
 from invokeai.backend.tiles.tiles import (
     calc_tiles_even_split,
diff --git a/invokeai/invocation_api/__init__.py b/invokeai/invocation_api/__init__.py
new file mode 100644
index 0000000000..e867ec3cc4
--- /dev/null
+++ b/invokeai/invocation_api/__init__.py
@@ -0,0 +1,109 @@
+"""
+This file re-exports all the public API for invocations. This is the only file that should be imported by custom nodes.
+
+TODO(psyche): Do we want to dogfood this?
+"""
+
+from invokeai.app.invocations.baseinvocation import (
+    BaseInvocation,
+    BaseInvocationOutput,
+    invocation,
+    invocation_output,
+)
+from invokeai.app.invocations.fields import (
+    BoardField,
+    ColorField,
+    ConditioningField,
+    DenoiseMaskField,
+    FieldDescriptions,
+    FieldKind,
+    ImageField,
+    Input,
+    InputField,
+    LatentsField,
+    MetadataField,
+    OutputField,
+    UIComponent,
+    UIType,
+    WithMetadata,
+    WithWorkflow,
+)
+from invokeai.app.invocations.primitives import (
+    BooleanCollectionOutput,
+    BooleanOutput,
+    ColorCollectionOutput,
+    ColorOutput,
+    ConditioningCollectionOutput,
+    ConditioningOutput,
+    DenoiseMaskOutput,
+    FloatCollectionOutput,
+    FloatOutput,
+    ImageCollectionOutput,
+    ImageOutput,
+    IntegerCollectionOutput,
+    IntegerOutput,
+    LatentsCollectionOutput,
+    LatentsOutput,
+    StringCollectionOutput,
+    StringOutput,
+)
+from invokeai.app.services.image_records.image_records_common import ImageCategory
+from invokeai.app.services.shared.invocation_context import InvocationContext
+from invokeai.backend.stable_diffusion.diffusion.conditioning_data import (
+    BasicConditioningInfo,
+    ConditioningFieldData,
+    ExtraConditioningInfo,
+    SDXLConditioningInfo,
+)
+
+__all__ = [
+    # invokeai.app.invocations.baseinvocation
+    "BaseInvocation",
+    "BaseInvocationOutput",
+    "invocation",
+    "invocation_output",
+    # invokeai.app.services.shared.invocation_context
+    "InvocationContext",
+    # invokeai.app.invocations.fields
+    "BoardField",
+    "ColorField",
+    "ConditioningField",
+    "DenoiseMaskField",
+    "FieldDescriptions",
+    "FieldKind",
+    "ImageField",
+    "Input",
+    "InputField",
+    "LatentsField",
+    "MetadataField",
+    "OutputField",
+    "UIComponent",
+    "UIType",
+    "WithMetadata",
+    "WithWorkflow",
+    # invokeai.app.invocations.primitives
+    "BooleanCollectionOutput",
+    "BooleanOutput",
+    "ColorCollectionOutput",
+    "ColorOutput",
+    "ConditioningCollectionOutput",
+    "ConditioningOutput",
+    "DenoiseMaskOutput",
+    "FloatCollectionOutput",
+    "FloatOutput",
+    "ImageCollectionOutput",
+    "ImageOutput",
+    "IntegerCollectionOutput",
+    "IntegerOutput",
+    "LatentsCollectionOutput",
+    "LatentsOutput",
+    "StringCollectionOutput",
+    "StringOutput",
+    # invokeai.app.services.image_records.image_records_common
+    "ImageCategory",
+    # invokeai.backend.stable_diffusion.diffusion.conditioning_data
+    "BasicConditioningInfo",
+    "ConditioningFieldData",
+    "ExtraConditioningInfo",
+    "SDXLConditioningInfo",
+]
diff --git a/pyproject.toml b/pyproject.toml
index 8d25ed2091..69958064c6 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -170,6 +170,7 @@ version = { attr = "invokeai.version.__version__" }
   "invokeai.frontend.web.static*",
   "invokeai.configs*",
   "invokeai.app*",
+  "invokeai.invocation_api*",
 ]
 
 [tool.setuptools.package-data]

From 282b483d14192a8b031eb07b8ce6da40dc75fde3 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 16 Jan 2024 19:19:49 +1100
Subject: [PATCH 051/411] feat: tweak pyright config

---
 pyproject.toml | 47 +++++++++++++++++++++++++++++++++--------------
 1 file changed, 33 insertions(+), 14 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 69958064c6..8b28375e29 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -284,17 +284,36 @@ module = [
 #=== End: MyPy
 
 [tool.pyright]
-include = [
-  "invokeai/app/invocations/"
-]
-exclude = [
-  "**/node_modules",
-  "**/__pycache__",
-  "invokeai/app/invocations/onnx.py",
-  "invokeai/app/api/routers/models.py",
-  "invokeai/app/services/invocation_stats/invocation_stats_default.py",
-  "invokeai/app/services/model_manager/model_manager_base.py",
-  "invokeai/app/services/model_manager/model_manager_default.py",
-  "invokeai/app/services/model_records/model_records_sql.py",
-  "invokeai/app/util/controlnet_utils.py",
-]
+# Start from strict mode
+typeCheckingMode = "strict"
+# This errors whenever an import is missing a type stub file - way too noisy
+reportMissingTypeStubs = "none"
+# These are the rest of the rules enabled by strict mode - enable them @ warning
+reportConstantRedefinition = "warning"
+reportDeprecated = "warning"
+reportDuplicateImport = "warning"
+reportIncompleteStub = "warning"
+reportInconsistentConstructor = "warning"
+reportInvalidStubStatement = "warning"
+reportMatchNotExhaustive = "warning"
+reportMissingParameterType = "warning"
+reportMissingTypeArgument = "warning"
+reportPrivateUsage = "warning"
+reportTypeCommentUsage = "warning"
+reportUnknownArgumentType = "warning"
+reportUnknownLambdaType = "warning"
+reportUnknownMemberType = "warning"
+reportUnknownParameterType = "warning"
+reportUnknownVariableType = "warning"
+reportUnnecessaryCast = "warning"
+reportUnnecessaryComparison = "warning"
+reportUnnecessaryContains = "warning"
+reportUnnecessaryIsInstance = "warning"
+reportUnusedClass = "warning"
+reportUnusedImport = "warning"
+reportUnusedFunction = "warning"
+reportUnusedVariable = "warning"
+reportUntypedBaseClass = "warning"
+reportUntypedClassDecorator = "warning"
+reportUntypedFunctionDecorator = "warning"
+reportUntypedNamedTuple = "warning"

From 281c3345311114e5e0cf2daef5ef1f3b86394f67 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 16 Jan 2024 20:02:38 +1100
Subject: [PATCH 052/411] feat(nodes): do not freeze InvocationContextData,
 prevents it from being subclassesd

---
 invokeai/app/services/shared/invocation_context.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index 3cf3952de0..a849d6b17a 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -45,7 +45,7 @@ Note: The docstrings are in weird places, but that's where they must be to get I
 """
 
 
-@dataclass(frozen=True)
+@dataclass
 class InvocationContextData:
     invocation: "BaseInvocation"
     """The invocation that is being executed."""

From 4ce21087d3c28e0a0d45e5077e7766a871c1a6fa Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 5 Feb 2024 17:16:35 +1100
Subject: [PATCH 053/411] fix(nodes): restore type annotations for
 `InvocationContext`

---
 docs/contributing/INVOCATIONS.md              |  6 +--
 invokeai/app/invocations/collections.py       |  7 +--
 invokeai/app/invocations/compel.py            | 18 +++----
 .../controlnet_image_processors.py            |  5 +-
 invokeai/app/invocations/cv.py                |  3 +-
 invokeai/app/invocations/facetools.py         | 24 ++++-----
 invokeai/app/invocations/image.py             | 51 ++++++++++---------
 invokeai/app/invocations/infill.py            | 11 ++--
 invokeai/app/invocations/ip_adapter.py        |  3 +-
 invokeai/app/invocations/latent.py            | 18 +++----
 invokeai/app/invocations/math.py              | 21 ++++----
 invokeai/app/invocations/metadata.py          |  9 ++--
 invokeai/app/invocations/model.py             | 13 ++---
 invokeai/app/invocations/noise.py             |  3 +-
 invokeai/app/invocations/onnx.py              |  8 +--
 invokeai/app/invocations/param_easing.py      |  5 +-
 invokeai/app/invocations/primitives.py        | 31 +++++------
 invokeai/app/invocations/prompt.py            |  5 +-
 invokeai/app/invocations/sdxl.py              |  5 +-
 invokeai/app/invocations/strings.py           | 12 +++--
 invokeai/app/invocations/t2i_adapter.py       |  3 +-
 invokeai/app/invocations/tiles.py             | 13 ++---
 invokeai/app/invocations/upscale.py           |  3 +-
 invokeai/app/services/shared/graph.py         |  7 +--
 tests/aa_nodes/test_nodes.py                  | 17 ++++---
 25 files changed, 158 insertions(+), 143 deletions(-)

diff --git a/docs/contributing/INVOCATIONS.md b/docs/contributing/INVOCATIONS.md
index 5d9a3690ba..ce1ee9e808 100644
--- a/docs/contributing/INVOCATIONS.md
+++ b/docs/contributing/INVOCATIONS.md
@@ -174,7 +174,7 @@ class ResizeInvocation(BaseInvocation):
     width: int = InputField(default=512, ge=64, le=2048, description="Width of the new image")
     height: int = InputField(default=512, ge=64, le=2048, description="Height of the new image")
 
-    def invoke(self, context):
+    def invoke(self, context: InvocationContext):
         pass
 ```
 
@@ -203,7 +203,7 @@ class ResizeInvocation(BaseInvocation):
     width: int = InputField(default=512, ge=64, le=2048, description="Width of the new image")
     height: int = InputField(default=512, ge=64, le=2048, description="Height of the new image")
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         pass
 ```
 
@@ -229,7 +229,7 @@ class ResizeInvocation(BaseInvocation):
     width: int = InputField(default=512, ge=64, le=2048, description="Width of the new image")
     height: int = InputField(default=512, ge=64, le=2048, description="Height of the new image")
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         # Load the input image as a PIL image
         image = context.images.get_pil(self.image.image_name)
 
diff --git a/invokeai/app/invocations/collections.py b/invokeai/app/invocations/collections.py
index f5709b4ba3..e02291980f 100644
--- a/invokeai/app/invocations/collections.py
+++ b/invokeai/app/invocations/collections.py
@@ -5,6 +5,7 @@ import numpy as np
 from pydantic import ValidationInfo, field_validator
 
 from invokeai.app.invocations.primitives import IntegerCollectionOutput
+from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.app.util.misc import SEED_MAX
 
 from .baseinvocation import BaseInvocation, invocation
@@ -27,7 +28,7 @@ class RangeInvocation(BaseInvocation):
             raise ValueError("stop must be greater than start")
         return v
 
-    def invoke(self, context) -> IntegerCollectionOutput:
+    def invoke(self, context: InvocationContext) -> IntegerCollectionOutput:
         return IntegerCollectionOutput(collection=list(range(self.start, self.stop, self.step)))
 
 
@@ -45,7 +46,7 @@ class RangeOfSizeInvocation(BaseInvocation):
     size: int = InputField(default=1, gt=0, description="The number of values")
     step: int = InputField(default=1, description="The step of the range")
 
-    def invoke(self, context) -> IntegerCollectionOutput:
+    def invoke(self, context: InvocationContext) -> IntegerCollectionOutput:
         return IntegerCollectionOutput(
             collection=list(range(self.start, self.start + (self.step * self.size), self.step))
         )
@@ -72,6 +73,6 @@ class RandomRangeInvocation(BaseInvocation):
         description="The seed for the RNG (omit for random)",
     )
 
-    def invoke(self, context) -> IntegerCollectionOutput:
+    def invoke(self, context: InvocationContext) -> IntegerCollectionOutput:
         rng = np.random.default_rng(self.seed)
         return IntegerCollectionOutput(collection=list(rng.integers(low=self.low, high=self.high, size=self.size)))
diff --git a/invokeai/app/invocations/compel.py b/invokeai/app/invocations/compel.py
index 94caf4128d..978c6dcb17 100644
--- a/invokeai/app/invocations/compel.py
+++ b/invokeai/app/invocations/compel.py
@@ -1,4 +1,4 @@
-from typing import TYPE_CHECKING, List, Optional, Union
+from typing import List, Optional, Union
 
 import torch
 from compel import Compel, ReturnedEmbeddingsType
@@ -12,6 +12,7 @@ from invokeai.app.invocations.fields import (
     UIComponent,
 )
 from invokeai.app.invocations.primitives import ConditioningOutput
+from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.backend.stable_diffusion.diffusion.conditioning_data import (
     BasicConditioningInfo,
     ConditioningFieldData,
@@ -31,10 +32,7 @@ from .baseinvocation import (
 )
 from .model import ClipField
 
-if TYPE_CHECKING:
-    from invokeai.app.services.shared.invocation_context import InvocationContext
-
-    # unconditioned: Optional[torch.Tensor]
+# unconditioned: Optional[torch.Tensor]
 
 
 # class ConditioningAlgo(str, Enum):
@@ -65,7 +63,7 @@ class CompelInvocation(BaseInvocation):
     )
 
     @torch.no_grad()
-    def invoke(self, context) -> ConditioningOutput:
+    def invoke(self, context: InvocationContext) -> ConditioningOutput:
         tokenizer_info = context.models.load(**self.clip.tokenizer.model_dump())
         text_encoder_info = context.models.load(**self.clip.text_encoder.model_dump())
 
@@ -148,7 +146,7 @@ class CompelInvocation(BaseInvocation):
 class SDXLPromptInvocationBase:
     def run_clip_compel(
         self,
-        context: "InvocationContext",
+        context: InvocationContext,
         clip_field: ClipField,
         prompt: str,
         get_pooled: bool,
@@ -288,7 +286,7 @@ class SDXLCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase):
     clip2: ClipField = InputField(description=FieldDescriptions.clip, input=Input.Connection, title="CLIP 2")
 
     @torch.no_grad()
-    def invoke(self, context) -> ConditioningOutput:
+    def invoke(self, context: InvocationContext) -> ConditioningOutput:
         c1, c1_pooled, ec1 = self.run_clip_compel(
             context, self.clip, self.prompt, False, "lora_te1_", zero_on_empty=True
         )
@@ -373,7 +371,7 @@ class SDXLRefinerCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase
     clip2: ClipField = InputField(description=FieldDescriptions.clip, input=Input.Connection)
 
     @torch.no_grad()
-    def invoke(self, context) -> ConditioningOutput:
+    def invoke(self, context: InvocationContext) -> ConditioningOutput:
         # TODO: if there will appear lora for refiner - write proper prefix
         c2, c2_pooled, ec2 = self.run_clip_compel(context, self.clip2, self.style, True, "<NONE>", zero_on_empty=False)
 
@@ -418,7 +416,7 @@ class ClipSkipInvocation(BaseInvocation):
     clip: ClipField = InputField(description=FieldDescriptions.clip, input=Input.Connection, title="CLIP")
     skipped_layers: int = InputField(default=0, description=FieldDescriptions.skipped_layers)
 
-    def invoke(self, context) -> ClipSkipInvocationOutput:
+    def invoke(self, context: InvocationContext) -> ClipSkipInvocationOutput:
         self.clip.skipped_layers += self.skipped_layers
         return ClipSkipInvocationOutput(
             clip=self.clip,
diff --git a/invokeai/app/invocations/controlnet_image_processors.py b/invokeai/app/invocations/controlnet_image_processors.py
index e993ceffde..f8bdf14117 100644
--- a/invokeai/app/invocations/controlnet_image_processors.py
+++ b/invokeai/app/invocations/controlnet_image_processors.py
@@ -28,6 +28,7 @@ from pydantic import BaseModel, ConfigDict, Field, field_validator, model_valida
 from invokeai.app.invocations.fields import FieldDescriptions, ImageField, Input, InputField, OutputField, WithMetadata
 from invokeai.app.invocations.primitives import ImageOutput
 from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
+from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.backend.image_util.depth_anything import DepthAnythingDetector
 from invokeai.backend.image_util.dw_openpose import DWOpenposeDetector
 from invokeai.backend.model_management.models.base import BaseModelType
@@ -119,7 +120,7 @@ class ControlNetInvocation(BaseInvocation):
         validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
         return self
 
-    def invoke(self, context) -> ControlOutput:
+    def invoke(self, context: InvocationContext) -> ControlOutput:
         return ControlOutput(
             control=ControlField(
                 image=self.image,
@@ -143,7 +144,7 @@ class ImageProcessorInvocation(BaseInvocation, WithMetadata):
         # superclass just passes through image without processing
         return image
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         raw_image = context.images.get_pil(self.image.image_name)
         # image type should be PIL.PngImagePlugin.PngImageFile ?
         processed_image = self.run_processor(raw_image)
diff --git a/invokeai/app/invocations/cv.py b/invokeai/app/invocations/cv.py
index 375b18f9c5..1ebabf5e06 100644
--- a/invokeai/app/invocations/cv.py
+++ b/invokeai/app/invocations/cv.py
@@ -7,6 +7,7 @@ from PIL import Image, ImageOps
 
 from invokeai.app.invocations.fields import ImageField
 from invokeai.app.invocations.primitives import ImageOutput
+from invokeai.app.services.shared.invocation_context import InvocationContext
 
 from .baseinvocation import BaseInvocation, invocation
 from .fields import InputField, WithMetadata
@@ -19,7 +20,7 @@ class CvInpaintInvocation(BaseInvocation, WithMetadata):
     image: ImageField = InputField(description="The image to inpaint")
     mask: ImageField = InputField(description="The mask to use when inpainting")
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.images.get_pil(self.image.image_name)
         mask = context.images.get_pil(self.mask.image_name)
 
diff --git a/invokeai/app/invocations/facetools.py b/invokeai/app/invocations/facetools.py
index dad6308981..a1702d6517 100644
--- a/invokeai/app/invocations/facetools.py
+++ b/invokeai/app/invocations/facetools.py
@@ -1,7 +1,7 @@
 import math
 import re
 from pathlib import Path
-from typing import TYPE_CHECKING, Optional, TypedDict
+from typing import Optional, TypedDict
 
 import cv2
 import numpy as np
@@ -19,9 +19,7 @@ from invokeai.app.invocations.baseinvocation import (
 from invokeai.app.invocations.fields import ImageField, InputField, OutputField, WithMetadata
 from invokeai.app.invocations.primitives import ImageOutput
 from invokeai.app.services.image_records.image_records_common import ImageCategory
-
-if TYPE_CHECKING:
-    from invokeai.app.services.shared.invocation_context import InvocationContext
+from invokeai.app.services.shared.invocation_context import InvocationContext
 
 
 @invocation_output("face_mask_output")
@@ -176,7 +174,7 @@ def prepare_faces_list(
 
 
 def generate_face_box_mask(
-    context: "InvocationContext",
+    context: InvocationContext,
     minimum_confidence: float,
     x_offset: float,
     y_offset: float,
@@ -275,7 +273,7 @@ def generate_face_box_mask(
 
 
 def extract_face(
-    context: "InvocationContext",
+    context: InvocationContext,
     image: ImageType,
     face: FaceResultData,
     padding: int,
@@ -356,7 +354,7 @@ def extract_face(
 
 
 def get_faces_list(
-    context: "InvocationContext",
+    context: InvocationContext,
     image: ImageType,
     should_chunk: bool,
     minimum_confidence: float,
@@ -458,7 +456,7 @@ class FaceOffInvocation(BaseInvocation, WithMetadata):
         description="Whether to bypass full image face detection and default to image chunking. Chunking will occur if no faces are found in the full image.",
     )
 
-    def faceoff(self, context: "InvocationContext", image: ImageType) -> Optional[ExtractFaceData]:
+    def faceoff(self, context: InvocationContext, image: ImageType) -> Optional[ExtractFaceData]:
         all_faces = get_faces_list(
             context=context,
             image=image,
@@ -485,7 +483,7 @@ class FaceOffInvocation(BaseInvocation, WithMetadata):
 
         return face_data
 
-    def invoke(self, context) -> FaceOffOutput:
+    def invoke(self, context: InvocationContext) -> FaceOffOutput:
         image = context.images.get_pil(self.image.image_name)
         result = self.faceoff(context=context, image=image)
 
@@ -543,7 +541,7 @@ class FaceMaskInvocation(BaseInvocation, WithMetadata):
             raise ValueError('Face IDs must be a comma-separated list of integers (e.g. "1,2,3")')
         return v
 
-    def facemask(self, context: "InvocationContext", image: ImageType) -> FaceMaskResult:
+    def facemask(self, context: InvocationContext, image: ImageType) -> FaceMaskResult:
         all_faces = get_faces_list(
             context=context,
             image=image,
@@ -600,7 +598,7 @@ class FaceMaskInvocation(BaseInvocation, WithMetadata):
             mask=mask_pil,
         )
 
-    def invoke(self, context) -> FaceMaskOutput:
+    def invoke(self, context: InvocationContext) -> FaceMaskOutput:
         image = context.images.get_pil(self.image.image_name)
         result = self.facemask(context=context, image=image)
 
@@ -633,7 +631,7 @@ class FaceIdentifierInvocation(BaseInvocation, WithMetadata):
         description="Whether to bypass full image face detection and default to image chunking. Chunking will occur if no faces are found in the full image.",
     )
 
-    def faceidentifier(self, context: "InvocationContext", image: ImageType) -> ImageType:
+    def faceidentifier(self, context: InvocationContext, image: ImageType) -> ImageType:
         image = image.copy()
 
         all_faces = get_faces_list(
@@ -674,7 +672,7 @@ class FaceIdentifierInvocation(BaseInvocation, WithMetadata):
 
         return image
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.images.get_pil(self.image.image_name)
         result_image = self.faceidentifier(context=context, image=image)
 
diff --git a/invokeai/app/invocations/image.py b/invokeai/app/invocations/image.py
index 3b8b0b4b80..7b74e4d96d 100644
--- a/invokeai/app/invocations/image.py
+++ b/invokeai/app/invocations/image.py
@@ -18,6 +18,7 @@ from invokeai.app.invocations.fields import (
 )
 from invokeai.app.invocations.primitives import ImageOutput
 from invokeai.app.services.image_records.image_records_common import ImageCategory
+from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.backend.image_util.invisible_watermark import InvisibleWatermark
 from invokeai.backend.image_util.safety_checker import SafetyChecker
 
@@ -34,7 +35,7 @@ class ShowImageInvocation(BaseInvocation):
 
     image: ImageField = InputField(description="The image to show")
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.images.get_pil(self.image.image_name)
         image.show()
 
@@ -62,7 +63,7 @@ class BlankImageInvocation(BaseInvocation, WithMetadata):
     mode: Literal["RGB", "RGBA"] = InputField(default="RGB", description="The mode of the image")
     color: ColorField = InputField(default=ColorField(r=0, g=0, b=0, a=255), description="The color of the image")
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         image = Image.new(mode=self.mode, size=(self.width, self.height), color=self.color.tuple())
 
         image_dto = context.images.save(image=image)
@@ -86,7 +87,7 @@ class ImageCropInvocation(BaseInvocation, WithMetadata):
     width: int = InputField(default=512, gt=0, description="The width of the crop rectangle")
     height: int = InputField(default=512, gt=0, description="The height of the crop rectangle")
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.images.get_pil(self.image.image_name)
 
         image_crop = Image.new(mode="RGBA", size=(self.width, self.height), color=(0, 0, 0, 0))
@@ -125,7 +126,7 @@ class CenterPadCropInvocation(BaseInvocation):
         description="Number of pixels to pad/crop from the bottom (negative values crop inwards, positive values pad outwards)",
     )
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.images.get_pil(self.image.image_name)
 
         # Calculate and create new image dimensions
@@ -161,7 +162,7 @@ class ImagePasteInvocation(BaseInvocation, WithMetadata):
     y: int = InputField(default=0, description="The top y coordinate at which to paste the image")
     crop: bool = InputField(default=False, description="Crop to base image dimensions")
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         base_image = context.images.get_pil(self.base_image.image_name)
         image = context.images.get_pil(self.image.image_name)
         mask = None
@@ -201,7 +202,7 @@ class MaskFromAlphaInvocation(BaseInvocation, WithMetadata):
     image: ImageField = InputField(description="The image to create the mask from")
     invert: bool = InputField(default=False, description="Whether or not to invert the mask")
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.images.get_pil(self.image.image_name)
 
         image_mask = image.split()[-1]
@@ -226,7 +227,7 @@ class ImageMultiplyInvocation(BaseInvocation, WithMetadata):
     image1: ImageField = InputField(description="The first image to multiply")
     image2: ImageField = InputField(description="The second image to multiply")
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         image1 = context.images.get_pil(self.image1.image_name)
         image2 = context.images.get_pil(self.image2.image_name)
 
@@ -253,7 +254,7 @@ class ImageChannelInvocation(BaseInvocation, WithMetadata):
     image: ImageField = InputField(description="The image to get the channel from")
     channel: IMAGE_CHANNELS = InputField(default="A", description="The channel to get")
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.images.get_pil(self.image.image_name)
 
         channel_image = image.getchannel(self.channel)
@@ -279,7 +280,7 @@ class ImageConvertInvocation(BaseInvocation, WithMetadata):
     image: ImageField = InputField(description="The image to convert")
     mode: IMAGE_MODES = InputField(default="L", description="The mode to convert to")
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.images.get_pil(self.image.image_name)
 
         converted_image = image.convert(self.mode)
@@ -304,7 +305,7 @@ class ImageBlurInvocation(BaseInvocation, WithMetadata):
     # Metadata
     blur_type: Literal["gaussian", "box"] = InputField(default="gaussian", description="The type of blur")
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.images.get_pil(self.image.image_name)
 
         blur = (
@@ -338,7 +339,7 @@ class UnsharpMaskInvocation(BaseInvocation, WithMetadata):
     def array_from_pil(self, img):
         return numpy.array(img) / 255
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.images.get_pil(self.image.image_name)
         mode = image.mode
 
@@ -401,7 +402,7 @@ class ImageResizeInvocation(BaseInvocation, WithMetadata):
     height: int = InputField(default=512, gt=0, description="The height to resize to (px)")
     resample_mode: PIL_RESAMPLING_MODES = InputField(default="bicubic", description="The resampling mode")
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.images.get_pil(self.image.image_name)
 
         resample_mode = PIL_RESAMPLING_MAP[self.resample_mode]
@@ -434,7 +435,7 @@ class ImageScaleInvocation(BaseInvocation, WithMetadata):
     )
     resample_mode: PIL_RESAMPLING_MODES = InputField(default="bicubic", description="The resampling mode")
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.images.get_pil(self.image.image_name)
 
         resample_mode = PIL_RESAMPLING_MAP[self.resample_mode]
@@ -465,7 +466,7 @@ class ImageLerpInvocation(BaseInvocation, WithMetadata):
     min: int = InputField(default=0, ge=0, le=255, description="The minimum output value")
     max: int = InputField(default=255, ge=0, le=255, description="The maximum output value")
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.images.get_pil(self.image.image_name)
 
         image_arr = numpy.asarray(image, dtype=numpy.float32) / 255
@@ -492,7 +493,7 @@ class ImageInverseLerpInvocation(BaseInvocation, WithMetadata):
     min: int = InputField(default=0, ge=0, le=255, description="The minimum input value")
     max: int = InputField(default=255, ge=0, le=255, description="The maximum input value")
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.images.get_pil(self.image.image_name)
 
         image_arr = numpy.asarray(image, dtype=numpy.float32)
@@ -517,7 +518,7 @@ class ImageNSFWBlurInvocation(BaseInvocation, WithMetadata):
 
     image: ImageField = InputField(description="The image to check")
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.images.get_pil(self.image.image_name)
 
         logger = context.logger
@@ -553,7 +554,7 @@ class ImageWatermarkInvocation(BaseInvocation, WithMetadata):
     image: ImageField = InputField(description="The image to check")
     text: str = InputField(default="InvokeAI", description="Watermark text")
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.images.get_pil(self.image.image_name)
         new_image = InvisibleWatermark.add_watermark(image, self.text)
         image_dto = context.images.save(image=new_image)
@@ -579,7 +580,7 @@ class MaskEdgeInvocation(BaseInvocation, WithMetadata):
         description="Second threshold for the hysteresis procedure in Canny edge detection"
     )
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         mask = context.images.get_pil(self.image.image_name).convert("L")
 
         npimg = numpy.asarray(mask, dtype=numpy.uint8)
@@ -613,7 +614,7 @@ class MaskCombineInvocation(BaseInvocation, WithMetadata):
     mask1: ImageField = InputField(description="The first mask to combine")
     mask2: ImageField = InputField(description="The second image to combine")
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         mask1 = context.images.get_pil(self.mask1.image_name).convert("L")
         mask2 = context.images.get_pil(self.mask2.image_name).convert("L")
 
@@ -642,7 +643,7 @@ class ColorCorrectInvocation(BaseInvocation, WithMetadata):
     mask: Optional[ImageField] = InputField(default=None, description="Mask to use when applying color-correction")
     mask_blur_radius: float = InputField(default=8, description="Mask blur radius")
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         pil_init_mask = None
         if self.mask is not None:
             pil_init_mask = context.images.get_pil(self.mask.image_name).convert("L")
@@ -741,7 +742,7 @@ class ImageHueAdjustmentInvocation(BaseInvocation, WithMetadata):
     image: ImageField = InputField(description="The image to adjust")
     hue: int = InputField(default=0, description="The degrees by which to rotate the hue, 0-360")
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         pil_image = context.images.get_pil(self.image.image_name)
 
         # Convert image to HSV color space
@@ -831,7 +832,7 @@ class ImageChannelOffsetInvocation(BaseInvocation, WithMetadata):
     channel: COLOR_CHANNELS = InputField(description="Which channel to adjust")
     offset: int = InputField(default=0, ge=-255, le=255, description="The amount to adjust the channel by")
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         pil_image = context.images.get_pil(self.image.image_name)
 
         # extract the channel and mode from the input and reference tuple
@@ -888,7 +889,7 @@ class ImageChannelMultiplyInvocation(BaseInvocation, WithMetadata):
     scale: float = InputField(default=1.0, ge=0.0, description="The amount to scale the channel by.")
     invert_channel: bool = InputField(default=False, description="Invert the channel after scaling")
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         pil_image = context.images.get_pil(self.image.image_name)
 
         # extract the channel and mode from the input and reference tuple
@@ -931,7 +932,7 @@ class SaveImageInvocation(BaseInvocation, WithMetadata):
     image: ImageField = InputField(description=FieldDescriptions.image)
     board: BoardField = InputField(default=None, description=FieldDescriptions.board, input=Input.Direct)
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.images.get_pil(self.image.image_name)
 
         image_dto = context.images.save(image=image, board_id=self.board.board_id if self.board else None)
@@ -953,7 +954,7 @@ class LinearUIOutputInvocation(BaseInvocation, WithMetadata):
     image: ImageField = InputField(description=FieldDescriptions.image)
     board: Optional[BoardField] = InputField(default=None, description=FieldDescriptions.board, input=Input.Direct)
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         image_dto = context.images.get_dto(self.image.image_name)
 
         image_dto = context.images.update(
diff --git a/invokeai/app/invocations/infill.py b/invokeai/app/invocations/infill.py
index 159bdb5f7a..b007edd9e4 100644
--- a/invokeai/app/invocations/infill.py
+++ b/invokeai/app/invocations/infill.py
@@ -8,6 +8,7 @@ from PIL import Image, ImageOps
 
 from invokeai.app.invocations.fields import ColorField, ImageField
 from invokeai.app.invocations.primitives import ImageOutput
+from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.app.util.misc import SEED_MAX
 from invokeai.backend.image_util.cv2_inpaint import cv2_inpaint
 from invokeai.backend.image_util.lama import LaMA
@@ -129,7 +130,7 @@ class InfillColorInvocation(BaseInvocation, WithMetadata):
         description="The color to use to infill",
     )
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.images.get_pil(self.image.image_name)
 
         solid_bg = Image.new("RGBA", image.size, self.color.tuple())
@@ -155,7 +156,7 @@ class InfillTileInvocation(BaseInvocation, WithMetadata):
         description="The seed to use for tile generation (omit for random)",
     )
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.images.get_pil(self.image.image_name)
 
         infilled = tile_fill_missing(image.copy(), seed=self.seed, tile_size=self.tile_size)
@@ -176,7 +177,7 @@ class InfillPatchMatchInvocation(BaseInvocation, WithMetadata):
     downscale: float = InputField(default=2.0, gt=0, description="Run patchmatch on downscaled image to speedup infill")
     resample_mode: PIL_RESAMPLING_MODES = InputField(default="bicubic", description="The resampling mode")
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.images.get_pil(self.image.image_name).convert("RGBA")
 
         resample_mode = PIL_RESAMPLING_MAP[self.resample_mode]
@@ -213,7 +214,7 @@ class LaMaInfillInvocation(BaseInvocation, WithMetadata):
 
     image: ImageField = InputField(description="The image to infill")
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.images.get_pil(self.image.image_name)
 
         infilled = infill_lama(image.copy())
@@ -229,7 +230,7 @@ class CV2InfillInvocation(BaseInvocation, WithMetadata):
 
     image: ImageField = InputField(description="The image to infill")
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.images.get_pil(self.image.image_name)
 
         infilled = infill_cv2(image.copy())
diff --git a/invokeai/app/invocations/ip_adapter.py b/invokeai/app/invocations/ip_adapter.py
index b836be04b5..845fcfa284 100644
--- a/invokeai/app/invocations/ip_adapter.py
+++ b/invokeai/app/invocations/ip_adapter.py
@@ -13,6 +13,7 @@ from invokeai.app.invocations.baseinvocation import (
 from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField
 from invokeai.app.invocations.primitives import ImageField
 from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
+from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.backend.model_management.models.base import BaseModelType, ModelType
 from invokeai.backend.model_management.models.ip_adapter import get_ip_adapter_image_encoder_model_id
 
@@ -92,7 +93,7 @@ class IPAdapterInvocation(BaseInvocation):
         validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
         return self
 
-    def invoke(self, context) -> IPAdapterOutput:
+    def invoke(self, context: InvocationContext) -> IPAdapterOutput:
         # Lookup the CLIP Vision encoder that is intended to be used with the IP-Adapter model.
         ip_adapter_info = context.models.get_info(
             self.ip_adapter_model.model_name, self.ip_adapter_model.base_model, ModelType.IPAdapter
diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py
index 0127a6521e..2cc84f80a7 100644
--- a/invokeai/app/invocations/latent.py
+++ b/invokeai/app/invocations/latent.py
@@ -3,7 +3,7 @@
 import math
 from contextlib import ExitStack
 from functools import singledispatchmethod
-from typing import TYPE_CHECKING, List, Literal, Optional, Union
+from typing import List, Literal, Optional, Union
 
 import einops
 import numpy as np
@@ -42,6 +42,7 @@ from invokeai.app.invocations.primitives import (
     LatentsOutput,
 )
 from invokeai.app.invocations.t2i_adapter import T2IAdapterField
+from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.app.util.controlnet_utils import prepare_control_image
 from invokeai.backend.ip_adapter.ip_adapter import IPAdapter, IPAdapterPlus
 from invokeai.backend.model_management.models import ModelType, SilenceWarnings
@@ -70,9 +71,6 @@ from .baseinvocation import (
 from .controlnet_image_processors import ControlField
 from .model import ModelInfo, UNetField, VaeField
 
-if TYPE_CHECKING:
-    from invokeai.app.services.shared.invocation_context import InvocationContext
-
 if choose_torch_device() == torch.device("mps"):
     from torch import mps
 
@@ -177,7 +175,7 @@ class CreateDenoiseMaskInvocation(BaseInvocation):
 
 
 def get_scheduler(
-    context: "InvocationContext",
+    context: InvocationContext,
     scheduler_info: ModelInfo,
     scheduler_name: str,
     seed: int,
@@ -300,7 +298,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
 
     def get_conditioning_data(
         self,
-        context: "InvocationContext",
+        context: InvocationContext,
         scheduler,
         unet,
         seed,
@@ -369,7 +367,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
 
     def prep_control_data(
         self,
-        context: "InvocationContext",
+        context: InvocationContext,
         control_input: Union[ControlField, List[ControlField]],
         latents_shape: List[int],
         exit_stack: ExitStack,
@@ -442,7 +440,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
 
     def prep_ip_adapter_data(
         self,
-        context: "InvocationContext",
+        context: InvocationContext,
         ip_adapter: Optional[Union[IPAdapterField, list[IPAdapterField]]],
         conditioning_data: ConditioningData,
         exit_stack: ExitStack,
@@ -509,7 +507,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
 
     def run_t2i_adapters(
         self,
-        context: "InvocationContext",
+        context: InvocationContext,
         t2i_adapter: Optional[Union[T2IAdapterField, list[T2IAdapterField]]],
         latents_shape: list[int],
         do_classifier_free_guidance: bool,
@@ -618,7 +616,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
 
         return num_inference_steps, timesteps, init_timestep
 
-    def prep_inpaint_mask(self, context: "InvocationContext", latents):
+    def prep_inpaint_mask(self, context: InvocationContext, latents):
         if self.denoise_mask is None:
             return None, None
 
diff --git a/invokeai/app/invocations/math.py b/invokeai/app/invocations/math.py
index d2dbf04981..83a092be69 100644
--- a/invokeai/app/invocations/math.py
+++ b/invokeai/app/invocations/math.py
@@ -7,6 +7,7 @@ from pydantic import ValidationInfo, field_validator
 
 from invokeai.app.invocations.fields import FieldDescriptions, InputField
 from invokeai.app.invocations.primitives import FloatOutput, IntegerOutput
+from invokeai.app.services.shared.invocation_context import InvocationContext
 
 from .baseinvocation import BaseInvocation, invocation
 
@@ -18,7 +19,7 @@ class AddInvocation(BaseInvocation):
     a: int = InputField(default=0, description=FieldDescriptions.num_1)
     b: int = InputField(default=0, description=FieldDescriptions.num_2)
 
-    def invoke(self, context) -> IntegerOutput:
+    def invoke(self, context: InvocationContext) -> IntegerOutput:
         return IntegerOutput(value=self.a + self.b)
 
 
@@ -29,7 +30,7 @@ class SubtractInvocation(BaseInvocation):
     a: int = InputField(default=0, description=FieldDescriptions.num_1)
     b: int = InputField(default=0, description=FieldDescriptions.num_2)
 
-    def invoke(self, context) -> IntegerOutput:
+    def invoke(self, context: InvocationContext) -> IntegerOutput:
         return IntegerOutput(value=self.a - self.b)
 
 
@@ -40,7 +41,7 @@ class MultiplyInvocation(BaseInvocation):
     a: int = InputField(default=0, description=FieldDescriptions.num_1)
     b: int = InputField(default=0, description=FieldDescriptions.num_2)
 
-    def invoke(self, context) -> IntegerOutput:
+    def invoke(self, context: InvocationContext) -> IntegerOutput:
         return IntegerOutput(value=self.a * self.b)
 
 
@@ -51,7 +52,7 @@ class DivideInvocation(BaseInvocation):
     a: int = InputField(default=0, description=FieldDescriptions.num_1)
     b: int = InputField(default=0, description=FieldDescriptions.num_2)
 
-    def invoke(self, context) -> IntegerOutput:
+    def invoke(self, context: InvocationContext) -> IntegerOutput:
         return IntegerOutput(value=int(self.a / self.b))
 
 
@@ -69,7 +70,7 @@ class RandomIntInvocation(BaseInvocation):
     low: int = InputField(default=0, description=FieldDescriptions.inclusive_low)
     high: int = InputField(default=np.iinfo(np.int32).max, description=FieldDescriptions.exclusive_high)
 
-    def invoke(self, context) -> IntegerOutput:
+    def invoke(self, context: InvocationContext) -> IntegerOutput:
         return IntegerOutput(value=np.random.randint(self.low, self.high))
 
 
@@ -88,7 +89,7 @@ class RandomFloatInvocation(BaseInvocation):
     high: float = InputField(default=1.0, description=FieldDescriptions.exclusive_high)
     decimals: int = InputField(default=2, description=FieldDescriptions.decimal_places)
 
-    def invoke(self, context) -> FloatOutput:
+    def invoke(self, context: InvocationContext) -> FloatOutput:
         random_float = np.random.uniform(self.low, self.high)
         rounded_float = round(random_float, self.decimals)
         return FloatOutput(value=rounded_float)
@@ -110,7 +111,7 @@ class FloatToIntegerInvocation(BaseInvocation):
         default="Nearest", description="The method to use for rounding"
     )
 
-    def invoke(self, context) -> IntegerOutput:
+    def invoke(self, context: InvocationContext) -> IntegerOutput:
         if self.method == "Nearest":
             return IntegerOutput(value=round(self.value / self.multiple) * self.multiple)
         elif self.method == "Floor":
@@ -128,7 +129,7 @@ class RoundInvocation(BaseInvocation):
     value: float = InputField(default=0, description="The float value")
     decimals: int = InputField(default=0, description="The number of decimal places")
 
-    def invoke(self, context) -> FloatOutput:
+    def invoke(self, context: InvocationContext) -> FloatOutput:
         return FloatOutput(value=round(self.value, self.decimals))
 
 
@@ -196,7 +197,7 @@ class IntegerMathInvocation(BaseInvocation):
             raise ValueError("Result of exponentiation is not an integer")
         return v
 
-    def invoke(self, context) -> IntegerOutput:
+    def invoke(self, context: InvocationContext) -> IntegerOutput:
         # Python doesn't support switch statements until 3.10, but InvokeAI supports back to 3.9
         if self.operation == "ADD":
             return IntegerOutput(value=self.a + self.b)
@@ -270,7 +271,7 @@ class FloatMathInvocation(BaseInvocation):
             raise ValueError("Root operation resulted in a complex number")
         return v
 
-    def invoke(self, context) -> FloatOutput:
+    def invoke(self, context: InvocationContext) -> FloatOutput:
         # Python doesn't support switch statements until 3.10, but InvokeAI supports back to 3.9
         if self.operation == "ADD":
             return FloatOutput(value=self.a + self.b)
diff --git a/invokeai/app/invocations/metadata.py b/invokeai/app/invocations/metadata.py
index 9d74abd8c1..58edfab711 100644
--- a/invokeai/app/invocations/metadata.py
+++ b/invokeai/app/invocations/metadata.py
@@ -20,6 +20,7 @@ from invokeai.app.invocations.fields import (
 from invokeai.app.invocations.ip_adapter import IPAdapterModelField
 from invokeai.app.invocations.model import LoRAModelField, MainModelField, VAEModelField
 from invokeai.app.invocations.t2i_adapter import T2IAdapterField
+from invokeai.app.services.shared.invocation_context import InvocationContext
 
 from ...version import __version__
 
@@ -64,7 +65,7 @@ class MetadataItemInvocation(BaseInvocation):
     label: str = InputField(description=FieldDescriptions.metadata_item_label)
     value: Any = InputField(description=FieldDescriptions.metadata_item_value, ui_type=UIType.Any)
 
-    def invoke(self, context) -> MetadataItemOutput:
+    def invoke(self, context: InvocationContext) -> MetadataItemOutput:
         return MetadataItemOutput(item=MetadataItemField(label=self.label, value=self.value))
 
 
@@ -81,7 +82,7 @@ class MetadataInvocation(BaseInvocation):
         description=FieldDescriptions.metadata_item_polymorphic
     )
 
-    def invoke(self, context) -> MetadataOutput:
+    def invoke(self, context: InvocationContext) -> MetadataOutput:
         if isinstance(self.items, MetadataItemField):
             # single metadata item
             data = {self.items.label: self.items.value}
@@ -100,7 +101,7 @@ class MergeMetadataInvocation(BaseInvocation):
 
     collection: list[MetadataField] = InputField(description=FieldDescriptions.metadata_collection)
 
-    def invoke(self, context) -> MetadataOutput:
+    def invoke(self, context: InvocationContext) -> MetadataOutput:
         data = {}
         for item in self.collection:
             data.update(item.model_dump())
@@ -218,7 +219,7 @@ class CoreMetadataInvocation(BaseInvocation):
         description="The start value used for refiner denoising",
     )
 
-    def invoke(self, context) -> MetadataOutput:
+    def invoke(self, context: InvocationContext) -> MetadataOutput:
         """Collects and outputs a CoreMetadata object"""
 
         return MetadataOutput(
diff --git a/invokeai/app/invocations/model.py b/invokeai/app/invocations/model.py
index f81e559e44..6a1fd6d36b 100644
--- a/invokeai/app/invocations/model.py
+++ b/invokeai/app/invocations/model.py
@@ -4,6 +4,7 @@ from typing import List, Optional
 from pydantic import BaseModel, ConfigDict, Field
 
 from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField
+from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.app.shared.models import FreeUConfig
 
 from ...backend.model_management import BaseModelType, ModelType, SubModelType
@@ -109,7 +110,7 @@ class MainModelLoaderInvocation(BaseInvocation):
     model: MainModelField = InputField(description=FieldDescriptions.main_model, input=Input.Direct)
     # TODO: precision?
 
-    def invoke(self, context) -> ModelLoaderOutput:
+    def invoke(self, context: InvocationContext) -> ModelLoaderOutput:
         base_model = self.model.base_model
         model_name = self.model.model_name
         model_type = ModelType.Main
@@ -221,7 +222,7 @@ class LoraLoaderInvocation(BaseInvocation):
         title="CLIP",
     )
 
-    def invoke(self, context) -> LoraLoaderOutput:
+    def invoke(self, context: InvocationContext) -> LoraLoaderOutput:
         if self.lora is None:
             raise Exception("No LoRA provided")
 
@@ -310,7 +311,7 @@ class SDXLLoraLoaderInvocation(BaseInvocation):
         title="CLIP 2",
     )
 
-    def invoke(self, context) -> SDXLLoraLoaderOutput:
+    def invoke(self, context: InvocationContext) -> SDXLLoraLoaderOutput:
         if self.lora is None:
             raise Exception("No LoRA provided")
 
@@ -393,7 +394,7 @@ class VaeLoaderInvocation(BaseInvocation):
         title="VAE",
     )
 
-    def invoke(self, context) -> VAEOutput:
+    def invoke(self, context: InvocationContext) -> VAEOutput:
         base_model = self.vae_model.base_model
         model_name = self.vae_model.model_name
         model_type = ModelType.Vae
@@ -448,7 +449,7 @@ class SeamlessModeInvocation(BaseInvocation):
     seamless_y: bool = InputField(default=True, input=Input.Any, description="Specify whether Y axis is seamless")
     seamless_x: bool = InputField(default=True, input=Input.Any, description="Specify whether X axis is seamless")
 
-    def invoke(self, context) -> SeamlessModeOutput:
+    def invoke(self, context: InvocationContext) -> SeamlessModeOutput:
         # Conditionally append 'x' and 'y' based on seamless_x and seamless_y
         unet = copy.deepcopy(self.unet)
         vae = copy.deepcopy(self.vae)
@@ -484,6 +485,6 @@ class FreeUInvocation(BaseInvocation):
     s1: float = InputField(default=0.9, ge=-1, le=3, description=FieldDescriptions.freeu_s1)
     s2: float = InputField(default=0.2, ge=-1, le=3, description=FieldDescriptions.freeu_s2)
 
-    def invoke(self, context) -> UNetOutput:
+    def invoke(self, context: InvocationContext) -> UNetOutput:
         self.unet.freeu_config = FreeUConfig(s1=self.s1, s2=self.s2, b1=self.b1, b2=self.b2)
         return UNetOutput(unet=self.unet)
diff --git a/invokeai/app/invocations/noise.py b/invokeai/app/invocations/noise.py
index 41641152f0..78f13cc52d 100644
--- a/invokeai/app/invocations/noise.py
+++ b/invokeai/app/invocations/noise.py
@@ -5,6 +5,7 @@ import torch
 from pydantic import field_validator
 
 from invokeai.app.invocations.fields import FieldDescriptions, InputField, LatentsField, OutputField
+from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.app.util.misc import SEED_MAX
 
 from ...backend.util.devices import choose_torch_device, torch_dtype
@@ -112,7 +113,7 @@ class NoiseInvocation(BaseInvocation):
         """Returns the seed modulo (SEED_MAX + 1) to ensure it is within the valid range."""
         return v % (SEED_MAX + 1)
 
-    def invoke(self, context) -> NoiseOutput:
+    def invoke(self, context: InvocationContext) -> NoiseOutput:
         noise = get_noise(
             width=self.width,
             height=self.height,
diff --git a/invokeai/app/invocations/onnx.py b/invokeai/app/invocations/onnx.py
index a1e318a380..e7b4d3d9fc 100644
--- a/invokeai/app/invocations/onnx.py
+++ b/invokeai/app/invocations/onnx.py
@@ -63,7 +63,7 @@ class ONNXPromptInvocation(BaseInvocation):
     prompt: str = InputField(default="", description=FieldDescriptions.raw_prompt, ui_component=UIComponent.Textarea)
     clip: ClipField = InputField(description=FieldDescriptions.clip, input=Input.Connection)
 
-    def invoke(self, context) -> ConditioningOutput:
+    def invoke(self, context: InvocationContext) -> ConditioningOutput:
         tokenizer_info = context.services.model_manager.get_model(
             **self.clip.tokenizer.model_dump(),
         )
@@ -201,7 +201,7 @@ class ONNXTextToLatentsInvocation(BaseInvocation):
 
     # based on
     # https://github.com/huggingface/diffusers/blob/3ebbaf7c96801271f9e6c21400033b6aa5ffcf29/src/diffusers/pipelines/stable_diffusion/pipeline_onnx_stable_diffusion.py#L375
-    def invoke(self, context) -> LatentsOutput:
+    def invoke(self, context: InvocationContext) -> LatentsOutput:
         c, _ = context.services.latents.get(self.positive_conditioning.conditioning_name)
         uc, _ = context.services.latents.get(self.negative_conditioning.conditioning_name)
         graph_execution_state = context.services.graph_execution_manager.get(context.graph_execution_state_id)
@@ -342,7 +342,7 @@ class ONNXLatentsToImageInvocation(BaseInvocation, WithMetadata):
     )
     # tiled: bool = InputField(default=False, description="Decode latents by overlaping tiles(less memory consumption)")
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         latents = context.services.latents.get(self.latents.latents_name)
 
         if self.vae.vae.submodel != SubModelType.VaeDecoder:
@@ -417,7 +417,7 @@ class OnnxModelLoaderInvocation(BaseInvocation):
         description=FieldDescriptions.onnx_main_model, input=Input.Direct, ui_type=UIType.ONNXModel
     )
 
-    def invoke(self, context) -> ONNXModelLoaderOutput:
+    def invoke(self, context: InvocationContext) -> ONNXModelLoaderOutput:
         base_model = self.model.base_model
         model_name = self.model.model_name
         model_type = ModelType.ONNX
diff --git a/invokeai/app/invocations/param_easing.py b/invokeai/app/invocations/param_easing.py
index bf59e87d27..6845637de9 100644
--- a/invokeai/app/invocations/param_easing.py
+++ b/invokeai/app/invocations/param_easing.py
@@ -40,6 +40,7 @@ from easing_functions import (
 from matplotlib.ticker import MaxNLocator
 
 from invokeai.app.invocations.primitives import FloatCollectionOutput
+from invokeai.app.services.shared.invocation_context import InvocationContext
 
 from .baseinvocation import BaseInvocation, invocation
 from .fields import InputField
@@ -62,7 +63,7 @@ class FloatLinearRangeInvocation(BaseInvocation):
         description="number of values to interpolate over (including start and stop)",
     )
 
-    def invoke(self, context) -> FloatCollectionOutput:
+    def invoke(self, context: InvocationContext) -> FloatCollectionOutput:
         param_list = list(np.linspace(self.start, self.stop, self.steps))
         return FloatCollectionOutput(collection=param_list)
 
@@ -130,7 +131,7 @@ class StepParamEasingInvocation(BaseInvocation):
     # alt_mirror: bool = InputField(default=False, description="alternative mirroring by dual easing")
     show_easing_plot: bool = InputField(default=False, description="show easing plot")
 
-    def invoke(self, context) -> FloatCollectionOutput:
+    def invoke(self, context: InvocationContext) -> FloatCollectionOutput:
         log_diagnostics = False
         # convert from start_step_percent to nearest step <= (steps * start_step_percent)
         # start_step = int(np.floor(self.num_steps * self.start_step_percent))
diff --git a/invokeai/app/invocations/primitives.py b/invokeai/app/invocations/primitives.py
index ee04345eed..c90d3230b2 100644
--- a/invokeai/app/invocations/primitives.py
+++ b/invokeai/app/invocations/primitives.py
@@ -17,6 +17,7 @@ from invokeai.app.invocations.fields import (
     UIComponent,
 )
 from invokeai.app.services.images.images_common import ImageDTO
+from invokeai.app.services.shared.invocation_context import InvocationContext
 
 from .baseinvocation import (
     BaseInvocation,
@@ -59,7 +60,7 @@ class BooleanInvocation(BaseInvocation):
 
     value: bool = InputField(default=False, description="The boolean value")
 
-    def invoke(self, context) -> BooleanOutput:
+    def invoke(self, context: InvocationContext) -> BooleanOutput:
         return BooleanOutput(value=self.value)
 
 
@@ -75,7 +76,7 @@ class BooleanCollectionInvocation(BaseInvocation):
 
     collection: list[bool] = InputField(default=[], description="The collection of boolean values")
 
-    def invoke(self, context) -> BooleanCollectionOutput:
+    def invoke(self, context: InvocationContext) -> BooleanCollectionOutput:
         return BooleanCollectionOutput(collection=self.collection)
 
 
@@ -108,7 +109,7 @@ class IntegerInvocation(BaseInvocation):
 
     value: int = InputField(default=0, description="The integer value")
 
-    def invoke(self, context) -> IntegerOutput:
+    def invoke(self, context: InvocationContext) -> IntegerOutput:
         return IntegerOutput(value=self.value)
 
 
@@ -124,7 +125,7 @@ class IntegerCollectionInvocation(BaseInvocation):
 
     collection: list[int] = InputField(default=[], description="The collection of integer values")
 
-    def invoke(self, context) -> IntegerCollectionOutput:
+    def invoke(self, context: InvocationContext) -> IntegerCollectionOutput:
         return IntegerCollectionOutput(collection=self.collection)
 
 
@@ -155,7 +156,7 @@ class FloatInvocation(BaseInvocation):
 
     value: float = InputField(default=0.0, description="The float value")
 
-    def invoke(self, context) -> FloatOutput:
+    def invoke(self, context: InvocationContext) -> FloatOutput:
         return FloatOutput(value=self.value)
 
 
@@ -171,7 +172,7 @@ class FloatCollectionInvocation(BaseInvocation):
 
     collection: list[float] = InputField(default=[], description="The collection of float values")
 
-    def invoke(self, context) -> FloatCollectionOutput:
+    def invoke(self, context: InvocationContext) -> FloatCollectionOutput:
         return FloatCollectionOutput(collection=self.collection)
 
 
@@ -202,7 +203,7 @@ class StringInvocation(BaseInvocation):
 
     value: str = InputField(default="", description="The string value", ui_component=UIComponent.Textarea)
 
-    def invoke(self, context) -> StringOutput:
+    def invoke(self, context: InvocationContext) -> StringOutput:
         return StringOutput(value=self.value)
 
 
@@ -218,7 +219,7 @@ class StringCollectionInvocation(BaseInvocation):
 
     collection: list[str] = InputField(default=[], description="The collection of string values")
 
-    def invoke(self, context) -> StringCollectionOutput:
+    def invoke(self, context: InvocationContext) -> StringCollectionOutput:
         return StringCollectionOutput(collection=self.collection)
 
 
@@ -261,7 +262,7 @@ class ImageInvocation(
 
     image: ImageField = InputField(description="The image to load")
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.images.get_pil(self.image.image_name)
 
         return ImageOutput(
@@ -283,7 +284,7 @@ class ImageCollectionInvocation(BaseInvocation):
 
     collection: list[ImageField] = InputField(description="The collection of image values")
 
-    def invoke(self, context) -> ImageCollectionOutput:
+    def invoke(self, context: InvocationContext) -> ImageCollectionOutput:
         return ImageCollectionOutput(collection=self.collection)
 
 
@@ -346,7 +347,7 @@ class LatentsInvocation(BaseInvocation):
 
     latents: LatentsField = InputField(description="The latents tensor", input=Input.Connection)
 
-    def invoke(self, context) -> LatentsOutput:
+    def invoke(self, context: InvocationContext) -> LatentsOutput:
         latents = context.latents.get(self.latents.latents_name)
 
         return LatentsOutput.build(self.latents.latents_name, latents)
@@ -366,7 +367,7 @@ class LatentsCollectionInvocation(BaseInvocation):
         description="The collection of latents tensors",
     )
 
-    def invoke(self, context) -> LatentsCollectionOutput:
+    def invoke(self, context: InvocationContext) -> LatentsCollectionOutput:
         return LatentsCollectionOutput(collection=self.collection)
 
 
@@ -397,7 +398,7 @@ class ColorInvocation(BaseInvocation):
 
     color: ColorField = InputField(default=ColorField(r=0, g=0, b=0, a=255), description="The color value")
 
-    def invoke(self, context) -> ColorOutput:
+    def invoke(self, context: InvocationContext) -> ColorOutput:
         return ColorOutput(color=self.color)
 
 
@@ -438,7 +439,7 @@ class ConditioningInvocation(BaseInvocation):
 
     conditioning: ConditioningField = InputField(description=FieldDescriptions.cond, input=Input.Connection)
 
-    def invoke(self, context) -> ConditioningOutput:
+    def invoke(self, context: InvocationContext) -> ConditioningOutput:
         return ConditioningOutput(conditioning=self.conditioning)
 
 
@@ -457,7 +458,7 @@ class ConditioningCollectionInvocation(BaseInvocation):
         description="The collection of conditioning tensors",
     )
 
-    def invoke(self, context) -> ConditioningCollectionOutput:
+    def invoke(self, context: InvocationContext) -> ConditioningCollectionOutput:
         return ConditioningCollectionOutput(collection=self.collection)
 
 
diff --git a/invokeai/app/invocations/prompt.py b/invokeai/app/invocations/prompt.py
index 4f5ef43a56..234743a003 100644
--- a/invokeai/app/invocations/prompt.py
+++ b/invokeai/app/invocations/prompt.py
@@ -6,6 +6,7 @@ from dynamicprompts.generators import CombinatorialPromptGenerator, RandomPrompt
 from pydantic import field_validator
 
 from invokeai.app.invocations.primitives import StringCollectionOutput
+from invokeai.app.services.shared.invocation_context import InvocationContext
 
 from .baseinvocation import BaseInvocation, invocation
 from .fields import InputField, UIComponent
@@ -29,7 +30,7 @@ class DynamicPromptInvocation(BaseInvocation):
     max_prompts: int = InputField(default=1, description="The number of prompts to generate")
     combinatorial: bool = InputField(default=False, description="Whether to use the combinatorial generator")
 
-    def invoke(self, context) -> StringCollectionOutput:
+    def invoke(self, context: InvocationContext) -> StringCollectionOutput:
         if self.combinatorial:
             generator = CombinatorialPromptGenerator()
             prompts = generator.generate(self.prompt, max_prompts=self.max_prompts)
@@ -91,7 +92,7 @@ class PromptsFromFileInvocation(BaseInvocation):
                     break
         return prompts
 
-    def invoke(self, context) -> StringCollectionOutput:
+    def invoke(self, context: InvocationContext) -> StringCollectionOutput:
         prompts = self.promptsFromFile(
             self.file_path,
             self.pre_prompt,
diff --git a/invokeai/app/invocations/sdxl.py b/invokeai/app/invocations/sdxl.py
index 75a526cfff..8d51674a04 100644
--- a/invokeai/app/invocations/sdxl.py
+++ b/invokeai/app/invocations/sdxl.py
@@ -1,4 +1,5 @@
 from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField, UIType
+from invokeai.app.services.shared.invocation_context import InvocationContext
 
 from ...backend.model_management import ModelType, SubModelType
 from .baseinvocation import (
@@ -38,7 +39,7 @@ class SDXLModelLoaderInvocation(BaseInvocation):
     )
     # TODO: precision?
 
-    def invoke(self, context) -> SDXLModelLoaderOutput:
+    def invoke(self, context: InvocationContext) -> SDXLModelLoaderOutput:
         base_model = self.model.base_model
         model_name = self.model.model_name
         model_type = ModelType.Main
@@ -127,7 +128,7 @@ class SDXLRefinerModelLoaderInvocation(BaseInvocation):
     )
     # TODO: precision?
 
-    def invoke(self, context) -> SDXLRefinerModelLoaderOutput:
+    def invoke(self, context: InvocationContext) -> SDXLRefinerModelLoaderOutput:
         base_model = self.model.base_model
         model_name = self.model.model_name
         model_type = ModelType.Main
diff --git a/invokeai/app/invocations/strings.py b/invokeai/app/invocations/strings.py
index a4c92d9de5..182c976cd7 100644
--- a/invokeai/app/invocations/strings.py
+++ b/invokeai/app/invocations/strings.py
@@ -2,6 +2,8 @@
 
 import re
 
+from invokeai.app.services.shared.invocation_context import InvocationContext
+
 from .baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
@@ -32,7 +34,7 @@ class StringSplitNegInvocation(BaseInvocation):
 
     string: str = InputField(default="", description="String to split", ui_component=UIComponent.Textarea)
 
-    def invoke(self, context) -> StringPosNegOutput:
+    def invoke(self, context: InvocationContext) -> StringPosNegOutput:
         p_string = ""
         n_string = ""
         brackets_depth = 0
@@ -76,7 +78,7 @@ class StringSplitInvocation(BaseInvocation):
         default="", description="Delimiter to spilt with. blank will split on the first whitespace"
     )
 
-    def invoke(self, context) -> String2Output:
+    def invoke(self, context: InvocationContext) -> String2Output:
         result = self.string.split(self.delimiter, 1)
         if len(result) == 2:
             part1, part2 = result
@@ -94,7 +96,7 @@ class StringJoinInvocation(BaseInvocation):
     string_left: str = InputField(default="", description="String Left", ui_component=UIComponent.Textarea)
     string_right: str = InputField(default="", description="String Right", ui_component=UIComponent.Textarea)
 
-    def invoke(self, context) -> StringOutput:
+    def invoke(self, context: InvocationContext) -> StringOutput:
         return StringOutput(value=((self.string_left or "") + (self.string_right or "")))
 
 
@@ -106,7 +108,7 @@ class StringJoinThreeInvocation(BaseInvocation):
     string_middle: str = InputField(default="", description="String Middle", ui_component=UIComponent.Textarea)
     string_right: str = InputField(default="", description="String Right", ui_component=UIComponent.Textarea)
 
-    def invoke(self, context) -> StringOutput:
+    def invoke(self, context: InvocationContext) -> StringOutput:
         return StringOutput(value=((self.string_left or "") + (self.string_middle or "") + (self.string_right or "")))
 
 
@@ -125,7 +127,7 @@ class StringReplaceInvocation(BaseInvocation):
         default=False, description="Use search string as a regex expression (non regex is case insensitive)"
     )
 
-    def invoke(self, context) -> StringOutput:
+    def invoke(self, context: InvocationContext) -> StringOutput:
         pattern = self.search_string or ""
         new_string = self.string or ""
         if len(pattern) > 0:
diff --git a/invokeai/app/invocations/t2i_adapter.py b/invokeai/app/invocations/t2i_adapter.py
index 74a098a501..0f4fe66ada 100644
--- a/invokeai/app/invocations/t2i_adapter.py
+++ b/invokeai/app/invocations/t2i_adapter.py
@@ -11,6 +11,7 @@ from invokeai.app.invocations.baseinvocation import (
 from invokeai.app.invocations.controlnet_image_processors import CONTROLNET_RESIZE_VALUES
 from invokeai.app.invocations.fields import FieldDescriptions, ImageField, Input, InputField, OutputField
 from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
+from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.backend.model_management.models.base import BaseModelType
 
 
@@ -89,7 +90,7 @@ class T2IAdapterInvocation(BaseInvocation):
         validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
         return self
 
-    def invoke(self, context) -> T2IAdapterOutput:
+    def invoke(self, context: InvocationContext) -> T2IAdapterOutput:
         return T2IAdapterOutput(
             t2i_adapter=T2IAdapterField(
                 image=self.image,
diff --git a/invokeai/app/invocations/tiles.py b/invokeai/app/invocations/tiles.py
index 0b4c472696..19ece42376 100644
--- a/invokeai/app/invocations/tiles.py
+++ b/invokeai/app/invocations/tiles.py
@@ -13,6 +13,7 @@ from invokeai.app.invocations.baseinvocation import (
 )
 from invokeai.app.invocations.fields import ImageField, Input, InputField, OutputField, WithMetadata
 from invokeai.app.invocations.primitives import ImageOutput
+from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.backend.tiles.tiles import (
     calc_tiles_even_split,
     calc_tiles_min_overlap,
@@ -56,7 +57,7 @@ class CalculateImageTilesInvocation(BaseInvocation):
         description="The target overlap, in pixels, between adjacent tiles. Adjacent tiles will overlap by at least this amount",
     )
 
-    def invoke(self, context) -> CalculateImageTilesOutput:
+    def invoke(self, context: InvocationContext) -> CalculateImageTilesOutput:
         tiles = calc_tiles_with_overlap(
             image_height=self.image_height,
             image_width=self.image_width,
@@ -99,7 +100,7 @@ class CalculateImageTilesEvenSplitInvocation(BaseInvocation):
         description="The overlap, in pixels, between adjacent tiles.",
     )
 
-    def invoke(self, context) -> CalculateImageTilesOutput:
+    def invoke(self, context: InvocationContext) -> CalculateImageTilesOutput:
         tiles = calc_tiles_even_split(
             image_height=self.image_height,
             image_width=self.image_width,
@@ -129,7 +130,7 @@ class CalculateImageTilesMinimumOverlapInvocation(BaseInvocation):
     tile_height: int = InputField(ge=1, default=576, description="The tile height, in pixels.")
     min_overlap: int = InputField(default=128, ge=0, description="Minimum overlap between adjacent tiles, in pixels.")
 
-    def invoke(self, context) -> CalculateImageTilesOutput:
+    def invoke(self, context: InvocationContext) -> CalculateImageTilesOutput:
         tiles = calc_tiles_min_overlap(
             image_height=self.image_height,
             image_width=self.image_width,
@@ -174,7 +175,7 @@ class TileToPropertiesInvocation(BaseInvocation):
 
     tile: Tile = InputField(description="The tile to split into properties.")
 
-    def invoke(self, context) -> TileToPropertiesOutput:
+    def invoke(self, context: InvocationContext) -> TileToPropertiesOutput:
         return TileToPropertiesOutput(
             coords_left=self.tile.coords.left,
             coords_right=self.tile.coords.right,
@@ -211,7 +212,7 @@ class PairTileImageInvocation(BaseInvocation):
     image: ImageField = InputField(description="The tile image.")
     tile: Tile = InputField(description="The tile properties.")
 
-    def invoke(self, context) -> PairTileImageOutput:
+    def invoke(self, context: InvocationContext) -> PairTileImageOutput:
         return PairTileImageOutput(
             tile_with_image=TileWithImage(
                 tile=self.tile,
@@ -247,7 +248,7 @@ class MergeTilesToImageInvocation(BaseInvocation, WithMetadata):
         description="The amount to blend adjacent tiles in pixels. Must be <= the amount of overlap between adjacent tiles.",
     )
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         images = [twi.image for twi in self.tiles_with_images]
         tiles = [twi.tile for twi in self.tiles_with_images]
 
diff --git a/invokeai/app/invocations/upscale.py b/invokeai/app/invocations/upscale.py
index ef17480986..71ef7ca3aa 100644
--- a/invokeai/app/invocations/upscale.py
+++ b/invokeai/app/invocations/upscale.py
@@ -10,6 +10,7 @@ from pydantic import ConfigDict
 
 from invokeai.app.invocations.fields import ImageField
 from invokeai.app.invocations.primitives import ImageOutput
+from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.backend.image_util.basicsr.rrdbnet_arch import RRDBNet
 from invokeai.backend.image_util.realesrgan.realesrgan import RealESRGAN
 from invokeai.backend.util.devices import choose_torch_device
@@ -42,7 +43,7 @@ class ESRGANInvocation(BaseInvocation, WithMetadata):
 
     model_config = ConfigDict(protected_namespaces=())
 
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.images.get_pil(self.image.image_name)
         models_path = context.config.get().models_path
 
diff --git a/invokeai/app/services/shared/graph.py b/invokeai/app/services/shared/graph.py
index c0699eb96b..3df230f5ee 100644
--- a/invokeai/app/services/shared/graph.py
+++ b/invokeai/app/services/shared/graph.py
@@ -17,6 +17,7 @@ from invokeai.app.invocations.baseinvocation import (
     invocation_output,
 )
 from invokeai.app.invocations.fields import Input, InputField, OutputField, UIType
+from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.app.util.misc import uuid_string
 
 # in 3.10 this would be "from types import NoneType"
@@ -201,7 +202,7 @@ class GraphInvocation(BaseInvocation):
     # TODO: figure out how to create a default here
     graph: "Graph" = InputField(description="The graph to run", default=None)
 
-    def invoke(self, context) -> GraphInvocationOutput:
+    def invoke(self, context: InvocationContext) -> GraphInvocationOutput:
         """Invoke with provided services and return outputs."""
         return GraphInvocationOutput()
 
@@ -227,7 +228,7 @@ class IterateInvocation(BaseInvocation):
     )
     index: int = InputField(description="The index, will be provided on executed iterators", default=0, ui_hidden=True)
 
-    def invoke(self, context) -> IterateInvocationOutput:
+    def invoke(self, context: InvocationContext) -> IterateInvocationOutput:
         """Produces the outputs as values"""
         return IterateInvocationOutput(item=self.collection[self.index], index=self.index, total=len(self.collection))
 
@@ -254,7 +255,7 @@ class CollectInvocation(BaseInvocation):
         description="The collection, will be provided on execution", default=[], ui_hidden=True
     )
 
-    def invoke(self, context) -> CollectInvocationOutput:
+    def invoke(self, context: InvocationContext) -> CollectInvocationOutput:
         """Invoke with provided services and return outputs."""
         return CollectInvocationOutput(collection=copy.copy(self.collection))
 
diff --git a/tests/aa_nodes/test_nodes.py b/tests/aa_nodes/test_nodes.py
index 559457c0e1..aab3d9c7b4 100644
--- a/tests/aa_nodes/test_nodes.py
+++ b/tests/aa_nodes/test_nodes.py
@@ -8,6 +8,7 @@ from invokeai.app.invocations.baseinvocation import (
 )
 from invokeai.app.invocations.fields import InputField, OutputField
 from invokeai.app.invocations.image import ImageField
+from invokeai.app.services.shared.invocation_context import InvocationContext
 
 
 # Define test invocations before importing anything that uses invocations
@@ -20,7 +21,7 @@ class ListPassThroughInvocationOutput(BaseInvocationOutput):
 class ListPassThroughInvocation(BaseInvocation):
     collection: list[ImageField] = InputField(default=[])
 
-    def invoke(self, context) -> ListPassThroughInvocationOutput:
+    def invoke(self, context: InvocationContext) -> ListPassThroughInvocationOutput:
         return ListPassThroughInvocationOutput(collection=self.collection)
 
 
@@ -33,13 +34,13 @@ class PromptTestInvocationOutput(BaseInvocationOutput):
 class PromptTestInvocation(BaseInvocation):
     prompt: str = InputField(default="")
 
-    def invoke(self, context) -> PromptTestInvocationOutput:
+    def invoke(self, context: InvocationContext) -> PromptTestInvocationOutput:
         return PromptTestInvocationOutput(prompt=self.prompt)
 
 
 @invocation("test_error", version="1.0.0")
 class ErrorInvocation(BaseInvocation):
-    def invoke(self, context) -> PromptTestInvocationOutput:
+    def invoke(self, context: InvocationContext) -> PromptTestInvocationOutput:
         raise Exception("This invocation is supposed to fail")
 
 
@@ -53,7 +54,7 @@ class TextToImageTestInvocation(BaseInvocation):
     prompt: str = InputField(default="")
     prompt2: str = InputField(default="")
 
-    def invoke(self, context) -> ImageTestInvocationOutput:
+    def invoke(self, context: InvocationContext) -> ImageTestInvocationOutput:
         return ImageTestInvocationOutput(image=ImageField(image_name=self.id))
 
 
@@ -62,7 +63,7 @@ class ImageToImageTestInvocation(BaseInvocation):
     prompt: str = InputField(default="")
     image: Union[ImageField, None] = InputField(default=None)
 
-    def invoke(self, context) -> ImageTestInvocationOutput:
+    def invoke(self, context: InvocationContext) -> ImageTestInvocationOutput:
         return ImageTestInvocationOutput(image=ImageField(image_name=self.id))
 
 
@@ -75,7 +76,7 @@ class PromptCollectionTestInvocationOutput(BaseInvocationOutput):
 class PromptCollectionTestInvocation(BaseInvocation):
     collection: list[str] = InputField()
 
-    def invoke(self, context) -> PromptCollectionTestInvocationOutput:
+    def invoke(self, context: InvocationContext) -> PromptCollectionTestInvocationOutput:
         return PromptCollectionTestInvocationOutput(collection=self.collection.copy())
 
 
@@ -88,7 +89,7 @@ class AnyTypeTestInvocationOutput(BaseInvocationOutput):
 class AnyTypeTestInvocation(BaseInvocation):
     value: Any = InputField(default=None)
 
-    def invoke(self, context) -> AnyTypeTestInvocationOutput:
+    def invoke(self, context: InvocationContext) -> AnyTypeTestInvocationOutput:
         return AnyTypeTestInvocationOutput(value=self.value)
 
 
@@ -96,7 +97,7 @@ class AnyTypeTestInvocation(BaseInvocation):
 class PolymorphicStringTestInvocation(BaseInvocation):
     value: Union[str, list[str]] = InputField(default="")
 
-    def invoke(self, context) -> PromptCollectionTestInvocationOutput:
+    def invoke(self, context: InvocationContext) -> PromptCollectionTestInvocationOutput:
         if isinstance(self.value, str):
             return PromptCollectionTestInvocationOutput(collection=[self.value])
         return PromptCollectionTestInvocationOutput(collection=self.value)

From 95dd5aad16287cc92b8503e6c321fc178361833e Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 5 Feb 2024 17:40:49 +1100
Subject: [PATCH 054/411] feat(nodes): add boards interface to invocation
 context

---
 .../app/services/shared/invocation_context.py | 54 +++++++++++++++++++
 1 file changed, 54 insertions(+)

diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index a849d6b17a..cbcaa6a548 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -7,6 +7,7 @@ from pydantic import ConfigDict
 from torch import Tensor
 
 from invokeai.app.invocations.fields import MetadataField, WithMetadata
+from invokeai.app.services.boards.boards_common import BoardDTO
 from invokeai.app.services.config.config_default import InvokeAIAppConfig
 from invokeai.app.services.image_records.image_records_common import ImageCategory, ImageRecordChanges, ResourceOrigin
 from invokeai.app.services.images.images_common import ImageDTO
@@ -63,6 +64,54 @@ class InvocationContextData:
     """The workflow associated with this queue item, if any."""
 
 
+class BoardsInterface:
+    def __init__(self, services: InvocationServices) -> None:
+        def create(board_name: str) -> BoardDTO:
+            """
+            Creates a board.
+
+            :param board_name: The name of the board to create.
+            """
+            return services.boards.create(board_name)
+
+        def get_dto(board_id: str) -> BoardDTO:
+            """
+            Gets a board DTO.
+
+            :param board_id: The ID of the board to get.
+            """
+            return services.boards.get_dto(board_id)
+
+        def get_all() -> list[BoardDTO]:
+            """
+            Gets all boards.
+            """
+            return services.boards.get_all()
+
+        def add_image_to_board(board_id: str, image_name: str) -> None:
+            """
+            Adds an image to a board.
+
+            :param board_id: The ID of the board to add the image to.
+            :param image_name: The name of the image to add to the board.
+            """
+            services.board_images.add_image_to_board(board_id, image_name)
+
+        def get_all_image_names_for_board(board_id: str) -> list[str]:
+            """
+            Gets all image names for a board.
+
+            :param board_id: The ID of the board to get the image names for.
+            """
+            return services.board_images.get_all_board_image_names_for_board(board_id)
+
+        self.create = create
+        self.get_dto = get_dto
+        self.get_all = get_all
+        self.add_image_to_board = add_image_to_board
+        self.get_all_image_names_for_board = get_all_image_names_for_board
+
+
 class LoggerInterface:
     def __init__(self, services: InvocationServices) -> None:
         def debug(message: str) -> None:
@@ -427,6 +476,7 @@ class InvocationContext:
         logger: LoggerInterface,
         config: ConfigInterface,
         util: UtilInterface,
+        boards: BoardsInterface,
         data: InvocationContextData,
         services: InvocationServices,
     ) -> None:
@@ -444,6 +494,8 @@ class InvocationContext:
         """Provides access to the app's config."""
         self.util = util
         """Provides utility methods."""
+        self.boards = boards
+        """Provides methods to interact with boards."""
         self.data = data
         """Provides data about the current queue item and invocation."""
         self.__services = services
@@ -554,6 +606,7 @@ def build_invocation_context(
     config = ConfigInterface(services=services)
     util = UtilInterface(services=services, context_data=context_data)
     conditioning = ConditioningInterface(services=services, context_data=context_data)
+    boards = BoardsInterface(services=services)
 
     ctx = InvocationContext(
         images=images,
@@ -565,6 +618,7 @@ def build_invocation_context(
         util=util,
         conditioning=conditioning,
         services=services,
+        boards=boards,
     )
 
     return ctx

From e11af7de9b665f70a334758f25c1013371ad603a Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 5 Feb 2024 17:48:32 +1100
Subject: [PATCH 055/411] feat(nodes): export more things from `invocation_api"

---
 invokeai/invocation_api/__init__.py | 20 ++++++++++++++++++++
 1 file changed, 20 insertions(+)

diff --git a/invokeai/invocation_api/__init__.py b/invokeai/invocation_api/__init__.py
index e867ec3cc4..e80bc26a00 100644
--- a/invokeai/invocation_api/__init__.py
+++ b/invokeai/invocation_api/__init__.py
@@ -47,8 +47,14 @@ from invokeai.app.invocations.primitives import (
     StringCollectionOutput,
     StringOutput,
 )
+from invokeai.app.services.boards.boards_common import BoardDTO
+from invokeai.app.services.config.config_default import InvokeAIAppConfig
 from invokeai.app.services.image_records.image_records_common import ImageCategory
 from invokeai.app.services.shared.invocation_context import InvocationContext
+from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID
+from invokeai.backend.model_management.model_manager import ModelInfo
+from invokeai.backend.model_management.models.base import BaseModelType, ModelType, SubModelType
+from invokeai.backend.stable_diffusion.diffusers_pipeline import PipelineIntermediateState
 from invokeai.backend.stable_diffusion.diffusion.conditioning_data import (
     BasicConditioningInfo,
     ConditioningFieldData,
@@ -101,9 +107,23 @@ __all__ = [
     "StringOutput",
     # invokeai.app.services.image_records.image_records_common
     "ImageCategory",
+    # invokeai.app.services.boards.boards_common
+    "BoardDTO",
     # invokeai.backend.stable_diffusion.diffusion.conditioning_data
     "BasicConditioningInfo",
     "ConditioningFieldData",
     "ExtraConditioningInfo",
     "SDXLConditioningInfo",
+    # invokeai.backend.stable_diffusion.diffusers_pipeline
+    "PipelineIntermediateState",
+    # invokeai.app.services.workflow_records.workflow_records_common
+    "WorkflowWithoutID",
+    # invokeai.app.services.config.config_default
+    "InvokeAIAppConfig",
+    # invokeai.backend.model_management.model_manager
+    "ModelInfo",
+    # invokeai.backend.model_management.models.base
+    "BaseModelType",
+    "ModelType",
+    "SubModelType",
 ]

From cbf22d8a804fc6aa7685b7a041cce9db72fbe631 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 5 Feb 2024 18:06:01 +1100
Subject: [PATCH 056/411] chore(nodes): add comments for ConfigInterface

---
 invokeai/app/services/shared/invocation_context.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index cbcaa6a548..cb989cb15e 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -392,7 +392,7 @@ class ConfigInterface:
     def __init__(self, services: InvocationServices) -> None:
         def get() -> InvokeAIAppConfig:
             """
-            Gets the app's config.
+            Gets the app's config. The config is read-only; attempts to mutate it will raise an error.
             """
 
             # The config can be changed at runtime.
@@ -400,6 +400,7 @@ class ConfigInterface:
             # We don't want nodes doing this, so we make a frozen copy.
 
             config = services.configuration.get_config()
+            # TODO(psyche): If config cannot be changed at runtime, should we cache this?
             frozen_config = config.model_copy(update={"model_config": ConfigDict(frozen=True)})
             return frozen_config
 

From 59c77832d8e557f3c111e35e02a3426bffee1bac Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 6 Feb 2024 00:37:18 +1100
Subject: [PATCH 057/411] tests(nodes): fix mock InvocationContext

---
 tests/aa_nodes/test_graph_execution_state.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/tests/aa_nodes/test_graph_execution_state.py b/tests/aa_nodes/test_graph_execution_state.py
index 3577a78ae2..1612cbe719 100644
--- a/tests/aa_nodes/test_graph_execution_state.py
+++ b/tests/aa_nodes/test_graph_execution_state.py
@@ -93,6 +93,7 @@ def invoke_next(g: GraphExecutionState, services: InvocationServices) -> tuple[B
             logger=None,
             models=None,
             util=None,
+            boards=None,
             services=None,
         )
     )

From cc8d713c57e4486496024d4d71942e772bd7628f Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 6 Feb 2024 10:22:58 +1100
Subject: [PATCH 058/411] fix(nodes): restore missing context type annotations

---
 invokeai/app/invocations/latent.py | 18 +++++++++---------
 1 file changed, 9 insertions(+), 9 deletions(-)

diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py
index 2cc84f80a7..5e36e73ec8 100644
--- a/invokeai/app/invocations/latent.py
+++ b/invokeai/app/invocations/latent.py
@@ -106,7 +106,7 @@ class SchedulerInvocation(BaseInvocation):
         ui_type=UIType.Scheduler,
     )
 
-    def invoke(self, context) -> SchedulerOutput:
+    def invoke(self, context: InvocationContext) -> SchedulerOutput:
         return SchedulerOutput(scheduler=self.scheduler)
 
 
@@ -141,7 +141,7 @@ class CreateDenoiseMaskInvocation(BaseInvocation):
         return mask_tensor
 
     @torch.no_grad()
-    def invoke(self, context) -> DenoiseMaskOutput:
+    def invoke(self, context: InvocationContext) -> DenoiseMaskOutput:
         if self.image is not None:
             image = context.images.get_pil(self.image.image_name)
             image = image_resized_to_grid_as_tensor(image.convert("RGB"))
@@ -630,7 +630,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
         return 1 - mask, masked_latents
 
     @torch.no_grad()
-    def invoke(self, context) -> LatentsOutput:
+    def invoke(self, context: InvocationContext) -> LatentsOutput:
         with SilenceWarnings():  # this quenches NSFW nag from diffusers
             seed = None
             noise = None
@@ -777,7 +777,7 @@ class LatentsToImageInvocation(BaseInvocation, WithMetadata):
     fp32: bool = InputField(default=DEFAULT_PRECISION == "float32", description=FieldDescriptions.fp32)
 
     @torch.no_grad()
-    def invoke(self, context) -> ImageOutput:
+    def invoke(self, context: InvocationContext) -> ImageOutput:
         latents = context.latents.get(self.latents.latents_name)
 
         vae_info = context.models.load(**self.vae.vae.model_dump())
@@ -868,7 +868,7 @@ class ResizeLatentsInvocation(BaseInvocation):
     mode: LATENTS_INTERPOLATION_MODE = InputField(default="bilinear", description=FieldDescriptions.interp_mode)
     antialias: bool = InputField(default=False, description=FieldDescriptions.torch_antialias)
 
-    def invoke(self, context) -> LatentsOutput:
+    def invoke(self, context: InvocationContext) -> LatentsOutput:
         latents = context.latents.get(self.latents.latents_name)
 
         # TODO:
@@ -909,7 +909,7 @@ class ScaleLatentsInvocation(BaseInvocation):
     mode: LATENTS_INTERPOLATION_MODE = InputField(default="bilinear", description=FieldDescriptions.interp_mode)
     antialias: bool = InputField(default=False, description=FieldDescriptions.torch_antialias)
 
-    def invoke(self, context) -> LatentsOutput:
+    def invoke(self, context: InvocationContext) -> LatentsOutput:
         latents = context.latents.get(self.latents.latents_name)
 
         # TODO:
@@ -998,7 +998,7 @@ class ImageToLatentsInvocation(BaseInvocation):
         return latents
 
     @torch.no_grad()
-    def invoke(self, context) -> LatentsOutput:
+    def invoke(self, context: InvocationContext) -> LatentsOutput:
         image = context.images.get_pil(self.image.image_name)
 
         vae_info = context.models.load(**self.vae.vae.model_dump())
@@ -1046,7 +1046,7 @@ class BlendLatentsInvocation(BaseInvocation):
     )
     alpha: float = InputField(default=0.5, description=FieldDescriptions.blend_alpha)
 
-    def invoke(self, context) -> LatentsOutput:
+    def invoke(self, context: InvocationContext) -> LatentsOutput:
         latents_a = context.latents.get(self.latents_a.latents_name)
         latents_b = context.latents.get(self.latents_b.latents_name)
 
@@ -1147,7 +1147,7 @@ class CropLatentsCoreInvocation(BaseInvocation):
         description="The height (in px) of the crop rectangle in image space. This value will be converted to a dimension in latent space.",
     )
 
-    def invoke(self, context) -> LatentsOutput:
+    def invoke(self, context: InvocationContext) -> LatentsOutput:
         latents = context.latents.get(self.latents.latents_name)
 
         x1 = self.x // LATENT_SCALE_FACTOR

From dcafbb998890548b24a40a8a415f582dd572fd58 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 7 Feb 2024 14:24:05 +1100
Subject: [PATCH 059/411] feat(nodes): do not hide `services` in invocation
 context interfaces

---
 .../app/services/shared/invocation_context.py | 637 ++++++++----------
 1 file changed, 298 insertions(+), 339 deletions(-)

diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index cb989cb15e..54c50bcf76 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -64,379 +64,338 @@ class InvocationContextData:
     """The workflow associated with this queue item, if any."""
 
 
-class BoardsInterface:
-    def __init__(self, services: InvocationServices) -> None:
-        def create(board_name: str) -> BoardDTO:
-            """
-            Creates a board.
-
-            :param board_name: The name of the board to create.
-            """
-            return services.boards.create(board_name)
-
-        def get_dto(board_id: str) -> BoardDTO:
-            """
-            Gets a board DTO.
-
-            :param board_id: The ID of the board to get.
-            """
-            return services.boards.get_dto(board_id)
-
-        def get_all() -> list[BoardDTO]:
-            """
-            Gets all boards.
-            """
-            return services.boards.get_all()
-
-        def add_image_to_board(board_id: str, image_name: str) -> None:
-            """
-            Adds an image to a board.
-
-            :param board_id: The ID of the board to add the image to.
-            :param image_name: The name of the image to add to the board.
-            """
-            services.board_images.add_image_to_board(board_id, image_name)
-
-        def get_all_image_names_for_board(board_id: str) -> list[str]:
-            """
-            Gets all image names for a board.
-
-            :param board_id: The ID of the board to get the image names for.
-            """
-            return services.board_images.get_all_board_image_names_for_board(board_id)
-
-        self.create = create
-        self.get_dto = get_dto
-        self.get_all = get_all
-        self.add_image_to_board = add_image_to_board
-        self.get_all_image_names_for_board = get_all_image_names_for_board
-
-
-class LoggerInterface:
-    def __init__(self, services: InvocationServices) -> None:
-        def debug(message: str) -> None:
-            """
-            Logs a debug message.
-
-            :param message: The message to log.
-            """
-            services.logger.debug(message)
-
-        def info(message: str) -> None:
-            """
-            Logs an info message.
-
-            :param message: The message to log.
-            """
-            services.logger.info(message)
-
-        def warning(message: str) -> None:
-            """
-            Logs a warning message.
-
-            :param message: The message to log.
-            """
-            services.logger.warning(message)
-
-        def error(message: str) -> None:
-            """
-            Logs an error message.
-
-            :param message: The message to log.
-            """
-            services.logger.error(message)
-
-        self.debug = debug
-        self.info = info
-        self.warning = warning
-        self.error = error
-
-
-class ImagesInterface:
+class InvocationContextInterface:
     def __init__(self, services: InvocationServices, context_data: InvocationContextData) -> None:
-        def save(
-            image: Image,
-            board_id: Optional[str] = None,
-            image_category: ImageCategory = ImageCategory.GENERAL,
-            metadata: Optional[MetadataField] = None,
-        ) -> ImageDTO:
-            """
-            Saves an image, returning its DTO.
-
-            If the current queue item has a workflow or metadata, it is automatically saved with the image.
-
-            :param image: The image to save, as a PIL image.
-            :param board_id: The board ID to add the image to, if it should be added.
-            :param image_category: The category of the image. Only the GENERAL category is added \
-                to the gallery.
-            :param metadata: The metadata to save with the image, if it should have any. If the \
-                invocation inherits from `WithMetadata`, that metadata will be used automatically. \
-                **Use this only if you want to override or provide metadata manually!**
-            """
-
-            # If the invocation inherits metadata, use that. Else, use the metadata passed in.
-            metadata_ = (
-                context_data.invocation.metadata if isinstance(context_data.invocation, WithMetadata) else metadata
-            )
-
-            return services.images.create(
-                image=image,
-                is_intermediate=context_data.invocation.is_intermediate,
-                image_category=image_category,
-                board_id=board_id,
-                metadata=metadata_,
-                image_origin=ResourceOrigin.INTERNAL,
-                workflow=context_data.workflow,
-                session_id=context_data.session_id,
-                node_id=context_data.invocation.id,
-            )
-
-        def get_pil(image_name: str) -> Image:
-            """
-            Gets an image as a PIL Image object.
-
-            :param image_name: The name of the image to get.
-            """
-            return services.images.get_pil_image(image_name)
-
-        def get_metadata(image_name: str) -> Optional[MetadataField]:
-            """
-            Gets an image's metadata, if it has any.
-
-            :param image_name: The name of the image to get the metadata for.
-            """
-            return services.images.get_metadata(image_name)
-
-        def get_dto(image_name: str) -> ImageDTO:
-            """
-            Gets an image as an ImageDTO object.
-
-            :param image_name: The name of the image to get.
-            """
-            return services.images.get_dto(image_name)
-
-        def update(
-            image_name: str,
-            board_id: Optional[str] = None,
-            is_intermediate: Optional[bool] = False,
-        ) -> ImageDTO:
-            """
-            Updates an image, returning its updated DTO.
-
-            It is not suggested to update images saved by earlier nodes, as this can cause confusion for users.
-
-            If you use this method, you *must* return the image as an :class:`ImageOutput` for the gallery to
-            get the updated image.
-
-            :param image_name: The name of the image to update.
-            :param board_id: The board ID to add the image to, if it should be added.
-            :param is_intermediate: Whether the image is an intermediate. Intermediate images aren't added to the gallery.
-            """
-            if is_intermediate is not None:
-                services.images.update(image_name, ImageRecordChanges(is_intermediate=is_intermediate))
-            if board_id is None:
-                services.board_images.remove_image_from_board(image_name)
-            else:
-                services.board_images.add_image_to_board(image_name, board_id)
-            return services.images.get_dto(image_name)
-
-        self.save = save
-        self.get_pil = get_pil
-        self.get_metadata = get_metadata
-        self.get_dto = get_dto
-        self.update = update
+        self._services = services
+        self._context_data = context_data
 
 
-class LatentsInterface:
-    def __init__(
+class BoardsInterface(InvocationContextInterface):
+    def create(self, board_name: str) -> BoardDTO:
+        """
+        Creates a board.
+
+        :param board_name: The name of the board to create.
+        """
+        return self._services.boards.create(board_name)
+
+    def get_dto(self, board_id: str) -> BoardDTO:
+        """
+        Gets a board DTO.
+
+        :param board_id: The ID of the board to get.
+        """
+        return self._services.boards.get_dto(board_id)
+
+    def get_all(self) -> list[BoardDTO]:
+        """
+        Gets all boards.
+        """
+        return self._services.boards.get_all()
+
+    def add_image_to_board(self, board_id: str, image_name: str) -> None:
+        """
+        Adds an image to a board.
+
+        :param board_id: The ID of the board to add the image to.
+        :param image_name: The name of the image to add to the board.
+        """
+        return self._services.board_images.add_image_to_board(board_id, image_name)
+
+    def get_all_image_names_for_board(self, board_id: str) -> list[str]:
+        """
+        Gets all image names for a board.
+
+        :param board_id: The ID of the board to get the image names for.
+        """
+        return self._services.board_images.get_all_board_image_names_for_board(board_id)
+
+
+class LoggerInterface(InvocationContextInterface):
+    def debug(self, message: str) -> None:
+        """
+        Logs a debug message.
+
+        :param message: The message to log.
+        """
+        self._services.logger.debug(message)
+
+    def info(self, message: str) -> None:
+        """
+        Logs an info message.
+
+        :param message: The message to log.
+        """
+        self._services.logger.info(message)
+
+    def warning(self, message: str) -> None:
+        """
+        Logs a warning message.
+
+        :param message: The message to log.
+        """
+        self._services.logger.warning(message)
+
+    def error(self, message: str) -> None:
+        """
+        Logs an error message.
+
+        :param message: The message to log.
+        """
+        self._services.logger.error(message)
+
+
+class ImagesInterface(InvocationContextInterface):
+    def save(
         self,
-        services: InvocationServices,
-        context_data: InvocationContextData,
-    ) -> None:
-        def save(tensor: Tensor) -> str:
-            """
-            Saves a latents tensor, returning its name.
+        image: Image,
+        board_id: Optional[str] = None,
+        image_category: ImageCategory = ImageCategory.GENERAL,
+        metadata: Optional[MetadataField] = None,
+    ) -> ImageDTO:
+        """
+        Saves an image, returning its DTO.
 
-            :param tensor: The latents tensor to save.
-            """
+        If the current queue item has a workflow or metadata, it is automatically saved with the image.
 
-            # Previously, we added a suffix indicating the type of Tensor we were saving, e.g.
-            # "mask", "noise", "masked_latents", etc.
-            #
-            # Retaining that capability in this wrapper would require either many different methods
-            # to save latents, or extra args for this method. Instead of complicating the API, we
-            # will use the same naming scheme for all latents.
-            #
-            # This has a very minor impact as we don't use them after a session completes.
+        :param image: The image to save, as a PIL image.
+        :param board_id: The board ID to add the image to, if it should be added.
+        :param image_category: The category of the image. Only the GENERAL category is added \
+            to the gallery.
+        :param metadata: The metadata to save with the image, if it should have any. If the \
+            invocation inherits from `WithMetadata`, that metadata will be used automatically. \
+            **Use this only if you want to override or provide metadata manually!**
+        """
 
-            # Previously, invocations chose the name for their latents. This is a bit risky, so we
-            # will generate a name for them instead. We use a uuid to ensure the name is unique.
-            #
-            # Because the name of the latents file will includes the session and invocation IDs,
-            # we don't need to worry about collisions. A truncated UUIDv4 is fine.
+        # If the invocation inherits metadata, use that. Else, use the metadata passed in.
+        metadata_ = (
+            self._context_data.invocation.metadata
+            if isinstance(self._context_data.invocation, WithMetadata)
+            else metadata
+        )
 
-            name = f"{context_data.session_id}__{context_data.invocation.id}__{uuid_string()[:7]}"
-            services.latents.save(
-                name=name,
-                data=tensor,
-            )
-            return name
+        return self._services.images.create(
+            image=image,
+            is_intermediate=self._context_data.invocation.is_intermediate,
+            image_category=image_category,
+            board_id=board_id,
+            metadata=metadata_,
+            image_origin=ResourceOrigin.INTERNAL,
+            workflow=self._context_data.workflow,
+            session_id=self._context_data.session_id,
+            node_id=self._context_data.invocation.id,
+        )
 
-        def get(latents_name: str) -> Tensor:
-            """
-            Gets a latents tensor by name.
+    def get_pil(self, image_name: str) -> Image:
+        """
+        Gets an image as a PIL Image object.
 
-            :param latents_name: The name of the latents tensor to get.
-            """
-            return services.latents.get(latents_name)
+        :param image_name: The name of the image to get.
+        """
+        return self._services.images.get_pil_image(image_name)
 
-        self.save = save
-        self.get = get
+    def get_metadata(self, image_name: str) -> Optional[MetadataField]:
+        """
+        Gets an image's metadata, if it has any.
 
+        :param image_name: The name of the image to get the metadata for.
+        """
+        return self._services.images.get_metadata(image_name)
 
-class ConditioningInterface:
-    def __init__(
+    def get_dto(self, image_name: str) -> ImageDTO:
+        """
+        Gets an image as an ImageDTO object.
+
+        :param image_name: The name of the image to get.
+        """
+        return self._services.images.get_dto(image_name)
+
+    def update(
         self,
-        services: InvocationServices,
-        context_data: InvocationContextData,
-    ) -> None:
-        # TODO(psyche): We are (ab)using the latents storage service as a general pickle storage
-        # service, but it is typed to work with Tensors only. We have to fudge the types here.
+        image_name: str,
+        board_id: Optional[str] = None,
+        is_intermediate: Optional[bool] = False,
+    ) -> ImageDTO:
+        """
+        Updates an image, returning its updated DTO.
 
-        def save(conditioning_data: ConditioningFieldData) -> str:
-            """
-            Saves a conditioning data object, returning its name.
+        It is not suggested to update images saved by earlier nodes, as this can cause confusion for users.
 
-            :param conditioning_data: The conditioning data to save.
-            """
+        If you use this method, you *must* return the image as an :class:`ImageOutput` for the gallery to
+        get the updated image.
 
-            # Conditioning data is *not* a Tensor, so we will suffix it to indicate this.
-            #
-            # See comment for `LatentsInterface.save` for more info about this method (it's very
-            # similar).
-
-            name = f"{context_data.session_id}__{context_data.invocation.id}__{uuid_string()[:7]}__conditioning"
-            services.latents.save(
-                name=name,
-                data=conditioning_data,  # type: ignore [arg-type]
-            )
-            return name
-
-        def get(conditioning_name: str) -> ConditioningFieldData:
-            """
-            Gets conditioning data by name.
-
-            :param conditioning_name: The name of the conditioning data to get.
-            """
-
-            return services.latents.get(conditioning_name)  # type: ignore [return-value]
-
-        self.save = save
-        self.get = get
+        :param image_name: The name of the image to update.
+        :param board_id: The board ID to add the image to, if it should be added.
+        :param is_intermediate: Whether the image is an intermediate. Intermediate images aren't added to the gallery.
+        """
+        if is_intermediate is not None:
+            self._services.images.update(image_name, ImageRecordChanges(is_intermediate=is_intermediate))
+        if board_id is None:
+            self._services.board_images.remove_image_from_board(image_name)
+        else:
+            self._services.board_images.add_image_to_board(image_name, board_id)
+        return self._services.images.get_dto(image_name)
 
 
-class ModelsInterface:
-    def __init__(self, services: InvocationServices, context_data: InvocationContextData) -> None:
-        def exists(model_name: str, base_model: BaseModelType, model_type: ModelType) -> bool:
-            """
-            Checks if a model exists.
+class LatentsInterface(InvocationContextInterface):
+    def save(self, tensor: Tensor) -> str:
+        """
+        Saves a latents tensor, returning its name.
 
-            :param model_name: The name of the model to check.
-            :param base_model: The base model of the model to check.
-            :param model_type: The type of the model to check.
-            """
-            return services.model_manager.model_exists(model_name, base_model, model_type)
+        :param tensor: The latents tensor to save.
+        """
 
-        def load(
-            model_name: str, base_model: BaseModelType, model_type: ModelType, submodel: Optional[SubModelType] = None
-        ) -> ModelInfo:
-            """
-            Loads a model, returning its `ModelInfo` object.
+        # Previously, we added a suffix indicating the type of Tensor we were saving, e.g.
+        # "mask", "noise", "masked_latents", etc.
+        #
+        # Retaining that capability in this wrapper would require either many different methods
+        # to save latents, or extra args for this method. Instead of complicating the API, we
+        # will use the same naming scheme for all latents.
+        #
+        # This has a very minor impact as we don't use them after a session completes.
 
-            :param model_name: The name of the model to get.
-            :param base_model: The base model of the model to get.
-            :param model_type: The type of the model to get.
-            :param submodel: The submodel of the model to get.
-            """
+        # Previously, invocations chose the name for their latents. This is a bit risky, so we
+        # will generate a name for them instead. We use a uuid to ensure the name is unique.
+        #
+        # Because the name of the latents file will includes the session and invocation IDs,
+        # we don't need to worry about collisions. A truncated UUIDv4 is fine.
 
-            # During this call, the model manager emits events with model loading status. The model
-            # manager itself has access to the events services, but does not have access to the
-            # required metadata for the events.
-            #
-            # For example, it needs access to the node's ID so that the events can be associated
-            # with the execution of a specific node.
-            #
-            # While this is available within the node, it's tedious to need to pass it in on every
-            # call. We can avoid that by wrapping the method here.
+        name = f"{self._context_data.session_id}__{self._context_data.invocation.id}__{uuid_string()[:7]}"
+        self._services.latents.save(
+            name=name,
+            data=tensor,
+        )
+        return name
 
-            return services.model_manager.get_model(
-                model_name, base_model, model_type, submodel, context_data=context_data
-            )
+    def get(self, latents_name: str) -> Tensor:
+        """
+        Gets a latents tensor by name.
 
-        def get_info(model_name: str, base_model: BaseModelType, model_type: ModelType) -> dict:
-            """
-            Gets a model's info, an dict-like object.
-
-            :param model_name: The name of the model to get.
-            :param base_model: The base model of the model to get.
-            :param model_type: The type of the model to get.
-            """
-            return services.model_manager.model_info(model_name, base_model, model_type)
-
-        self.exists = exists
-        self.load = load
-        self.get_info = get_info
+        :param latents_name: The name of the latents tensor to get.
+        """
+        return self._services.latents.get(latents_name)
 
 
-class ConfigInterface:
-    def __init__(self, services: InvocationServices) -> None:
-        def get() -> InvokeAIAppConfig:
-            """
-            Gets the app's config. The config is read-only; attempts to mutate it will raise an error.
-            """
+class ConditioningInterface(InvocationContextInterface):
+    # TODO(psyche): We are (ab)using the latents storage service as a general pickle storage
+    # service, but it is typed to work with Tensors only. We have to fudge the types here.
+    def save(self, conditioning_data: ConditioningFieldData) -> str:
+        """
+        Saves a conditioning data object, returning its name.
 
-            # The config can be changed at runtime.
-            #
-            # We don't want nodes doing this, so we make a frozen copy.
+        :param conditioning_context_data: The conditioning data to save.
+        """
 
-            config = services.configuration.get_config()
-            # TODO(psyche): If config cannot be changed at runtime, should we cache this?
-            frozen_config = config.model_copy(update={"model_config": ConfigDict(frozen=True)})
-            return frozen_config
+        # Conditioning data is *not* a Tensor, so we will suffix it to indicate this.
+        #
+        # See comment for `LatentsInterface.save` for more info about this method (it's very
+        # similar).
 
-        self.get = get
+        name = f"{self._context_data.session_id}__{self._context_data.invocation.id}__{uuid_string()[:7]}__conditioning"
+        self._services.latents.save(
+            name=name,
+            data=conditioning_data,  # type: ignore [arg-type]
+        )
+        return name
+
+    def get(self, conditioning_name: str) -> ConditioningFieldData:
+        """
+        Gets conditioning data by name.
+
+        :param conditioning_name: The name of the conditioning data to get.
+        """
+
+        return self._services.latents.get(conditioning_name)  # type: ignore [return-value]
 
 
-class UtilInterface:
-    def __init__(self, services: InvocationServices, context_data: InvocationContextData) -> None:
-        def sd_step_callback(
-            intermediate_state: PipelineIntermediateState,
-            base_model: BaseModelType,
-        ) -> None:
-            """
-            The step callback emits a progress event with the current step, the total number of
-            steps, a preview image, and some other internal metadata.
+class ModelsInterface(InvocationContextInterface):
+    def exists(self, model_name: str, base_model: BaseModelType, model_type: ModelType) -> bool:
+        """
+        Checks if a model exists.
 
-            This should be called after each denoising step.
+        :param model_name: The name of the model to check.
+        :param base_model: The base model of the model to check.
+        :param model_type: The type of the model to check.
+        """
+        return self._services.model_manager.model_exists(model_name, base_model, model_type)
 
-            :param intermediate_state: The intermediate state of the diffusion pipeline.
-            :param base_model: The base model for the current denoising step.
-            """
+    def load(
+        self, model_name: str, base_model: BaseModelType, model_type: ModelType, submodel: Optional[SubModelType] = None
+    ) -> ModelInfo:
+        """
+        Loads a model, returning its `ModelInfo` object.
 
-            # The step callback needs access to the events and the invocation queue services, but this
-            # represents a dangerous level of access.
-            #
-            # We wrap the step callback so that nodes do not have direct access to these services.
+        :param model_name: The name of the model to get.
+        :param base_model: The base model of the model to get.
+        :param model_type: The type of the model to get.
+        :param submodel: The submodel of the model to get.
+        """
 
-            stable_diffusion_step_callback(
-                context_data=context_data,
-                intermediate_state=intermediate_state,
-                base_model=base_model,
-                invocation_queue=services.queue,
-                events=services.events,
-            )
+        # During this call, the model manager emits events with model loading status. The model
+        # manager itself has access to the events services, but does not have access to the
+        # required metadata for the events.
+        #
+        # For example, it needs access to the node's ID so that the events can be associated
+        # with the execution of a specific node.
+        #
+        # While this is available within the node, it's tedious to need to pass it in on every
+        # call. We can avoid that by wrapping the method here.
 
-        self.sd_step_callback = sd_step_callback
+        return self._services.model_manager.get_model(
+            model_name, base_model, model_type, submodel, context_data=self._context_data
+        )
+
+    def get_info(self, model_name: str, base_model: BaseModelType, model_type: ModelType) -> dict:
+        """
+        Gets a model's info, an dict-like object.
+
+        :param model_name: The name of the model to get.
+        :param base_model: The base model of the model to get.
+        :param model_type: The type of the model to get.
+        """
+        return self._services.model_manager.model_info(model_name, base_model, model_type)
+
+
+class ConfigInterface(InvocationContextInterface):
+    def get(self) -> InvokeAIAppConfig:
+        """
+        Gets the app's config. The config is read-only; attempts to mutate it will raise an error.
+        """
+
+        # The config can be changed at runtime.
+        #
+        # We don't want nodes doing this, so we make a frozen copy.
+
+        config = self._services.configuration.get_config()
+        # TODO(psyche): If config cannot be changed at runtime, should we cache this?
+        frozen_config = config.model_copy(update={"model_config": ConfigDict(frozen=True)})
+        return frozen_config
+
+
+class UtilInterface(InvocationContextInterface):
+    def sd_step_callback(self, intermediate_state: PipelineIntermediateState, base_model: BaseModelType) -> None:
+        """
+        The step callback emits a progress event with the current step, the total number of
+        steps, a preview image, and some other internal metadata.
+
+        This should be called after each denoising step.
+
+        :param intermediate_state: The intermediate state of the diffusion pipeline.
+        :param base_model: The base model for the current denoising step.
+        """
+
+        # The step callback needs access to the events and the invocation queue services, but this
+        # represents a dangerous level of access.
+        #
+        # We wrap the step callback so that nodes do not have direct access to these services.
+
+        stable_diffusion_step_callback(
+            context_data=self._context_data,
+            intermediate_state=intermediate_state,
+            base_model=base_model,
+            invocation_queue=self._services.queue,
+            events=self._services.events,
+        )
 
 
 deprecation_version = "3.7.0"
@@ -600,14 +559,14 @@ def build_invocation_context(
     :param invocation_context_data: The invocation context data.
     """
 
-    logger = LoggerInterface(services=services)
+    logger = LoggerInterface(services=services, context_data=context_data)
     images = ImagesInterface(services=services, context_data=context_data)
     latents = LatentsInterface(services=services, context_data=context_data)
     models = ModelsInterface(services=services, context_data=context_data)
-    config = ConfigInterface(services=services)
+    config = ConfigInterface(services=services, context_data=context_data)
     util = UtilInterface(services=services, context_data=context_data)
     conditioning = ConditioningInterface(services=services, context_data=context_data)
-    boards = BoardsInterface(services=services)
+    boards = BoardsInterface(services=services, context_data=context_data)
 
     ctx = InvocationContext(
         images=images,

From 60e2eff94d4e9e4e4d889cb49539de696b5de600 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 7 Feb 2024 14:28:29 +1100
Subject: [PATCH 060/411] feat(nodes): cache invocation interface config

---
 .../app/services/shared/invocation_context.py | 19 ++++++++++++-------
 1 file changed, 12 insertions(+), 7 deletions(-)

diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index 54c50bcf76..99e439ad96 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -357,19 +357,24 @@ class ModelsInterface(InvocationContextInterface):
 
 
 class ConfigInterface(InvocationContextInterface):
+    def __init__(self, services: InvocationServices, context_data: InvocationContextData) -> None:
+        super().__init__(services, context_data)
+        # Config cache, only populated at runtime if requested
+        self._frozen_config: Optional[InvokeAIAppConfig] = None
+
     def get(self) -> InvokeAIAppConfig:
         """
         Gets the app's config. The config is read-only; attempts to mutate it will raise an error.
         """
 
-        # The config can be changed at runtime.
-        #
-        # We don't want nodes doing this, so we make a frozen copy.
+        if self._frozen_config is None:
+            # The config is a live pydantic model and can be changed at runtime.
+            # We don't want nodes doing this, so we make a frozen copy.
+            self._frozen_config = self._services.configuration.get_config().model_copy(
+                update={"model_config": ConfigDict(frozen=True)}
+            )
 
-        config = self._services.configuration.get_config()
-        # TODO(psyche): If config cannot be changed at runtime, should we cache this?
-        frozen_config = config.model_copy(update={"model_config": ConfigDict(frozen=True)})
-        return frozen_config
+        return self._frozen_config
 
 
 class UtilInterface(InvocationContextInterface):

From 5730ae9b96021b327888642f872901984ac2d597 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 7 Feb 2024 14:36:42 +1100
Subject: [PATCH 061/411] feat(nodes): context.__services -> context._services

---
 invokeai/app/services/shared/invocation_context.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index 99e439ad96..5da8593167 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -463,7 +463,8 @@ class InvocationContext:
         """Provides methods to interact with boards."""
         self.data = data
         """Provides data about the current queue item and invocation."""
-        self.__services = services
+        self._services = services
+        """Provides access to the full application services. This is an internal API and may change without warning."""
 
     @property
     @deprecated(version=deprecation_version, reason=get_deprecation_reason("`context.services`"))
@@ -475,7 +476,7 @@ class InvocationContext:
 
         The invocation services.
         """
-        return self.__services
+        return self._services
 
     @property
     @deprecated(

From 958b80acddecea011f00514bb5a552e3fe79fa17 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 7 Feb 2024 14:39:26 +1100
Subject: [PATCH 062/411] feat(nodes): context.data -> context._data

---
 .../app/services/shared/invocation_context.py | 38 +++++++++----------
 tests/aa_nodes/test_graph_execution_state.py  |  2 +-
 2 files changed, 20 insertions(+), 20 deletions(-)

diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index 5da8593167..b48a6acc54 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -442,7 +442,7 @@ class InvocationContext:
         config: ConfigInterface,
         util: UtilInterface,
         boards: BoardsInterface,
-        data: InvocationContextData,
+        context_data: InvocationContextData,
         services: InvocationServices,
     ) -> None:
         self.images = images
@@ -461,8 +461,8 @@ class InvocationContext:
         """Provides utility methods."""
         self.boards = boards
         """Provides methods to interact with boards."""
-        self.data = data
-        """Provides data about the current queue item and invocation."""
+        self._data = context_data
+        """Provides data about the current queue item and invocation. This is an internal API and may change without warning."""
         self._services = services
         """Provides access to the full application services. This is an internal API and may change without warning."""
 
@@ -481,77 +481,77 @@ class InvocationContext:
     @property
     @deprecated(
         version=deprecation_version,
-        reason=get_deprecation_reason("`context.graph_execution_state_api`", "`context.data.session_id`"),
+        reason=get_deprecation_reason("`context.graph_execution_state_id", "`context._data.session_id`"),
     )
     def graph_execution_state_id(self) -> str:
         """
         **DEPRECATED as of v3.7.0**
 
-        `context.graph_execution_state_api` will be removed in v3.8.0. Use `context.data.session_id` instead. See PLACEHOLDER_URL for details.
+        `context.graph_execution_state_api` will be removed in v3.8.0. Use `context._data.session_id` instead. See PLACEHOLDER_URL for details.
 
         The ID of the session (aka graph execution state).
         """
-        return self.data.session_id
+        return self._data.session_id
 
     @property
     @deprecated(
         version=deprecation_version,
-        reason=get_deprecation_reason("`context.queue_id`", "`context.data.queue_id`"),
+        reason=get_deprecation_reason("`context.queue_id`", "`context._data.queue_id`"),
     )
     def queue_id(self) -> str:
         """
         **DEPRECATED as of v3.7.0**
 
-        `context.queue_id` will be removed in v3.8.0. Use `context.data.queue_id` instead. See PLACEHOLDER_URL for details.
+        `context.queue_id` will be removed in v3.8.0. Use `context._data.queue_id` instead. See PLACEHOLDER_URL for details.
 
         The ID of the queue.
         """
-        return self.data.queue_id
+        return self._data.queue_id
 
     @property
     @deprecated(
         version=deprecation_version,
-        reason=get_deprecation_reason("`context.queue_item_id`", "`context.data.queue_item_id`"),
+        reason=get_deprecation_reason("`context.queue_item_id`", "`context._data.queue_item_id`"),
     )
     def queue_item_id(self) -> int:
         """
         **DEPRECATED as of v3.7.0**
 
-        `context.queue_item_id` will be removed in v3.8.0. Use `context.data.queue_item_id` instead. See PLACEHOLDER_URL for details.
+        `context.queue_item_id` will be removed in v3.8.0. Use `context._data.queue_item_id` instead. See PLACEHOLDER_URL for details.
 
         The ID of the queue item.
         """
-        return self.data.queue_item_id
+        return self._data.queue_item_id
 
     @property
     @deprecated(
         version=deprecation_version,
-        reason=get_deprecation_reason("`context.queue_batch_id`", "`context.data.batch_id`"),
+        reason=get_deprecation_reason("`context.queue_batch_id`", "`context._data.batch_id`"),
     )
     def queue_batch_id(self) -> str:
         """
         **DEPRECATED as of v3.7.0**
 
-        `context.queue_batch_id` will be removed in v3.8.0. Use `context.data.batch_id` instead. See PLACEHOLDER_URL for details.
+        `context.queue_batch_id` will be removed in v3.8.0. Use `context._data.batch_id` instead. See PLACEHOLDER_URL for details.
 
         The ID of the batch.
         """
-        return self.data.batch_id
+        return self._data.batch_id
 
     @property
     @deprecated(
         version=deprecation_version,
-        reason=get_deprecation_reason("`context.workflow`", "`context.data.workflow`"),
+        reason=get_deprecation_reason("`context.workflow`", "`context._data.workflow`"),
     )
     def workflow(self) -> Optional[WorkflowWithoutID]:
         """
         **DEPRECATED as of v3.7.0**
 
-        `context.workflow` will be removed in v3.8.0. Use `context.data.workflow` instead. See PLACEHOLDER_URL for details.
+        `context.workflow` will be removed in v3.8.0. Use `context._data.workflow` instead. See PLACEHOLDER_URL for details.
 
         The workflow associated with this queue item, if any.
         """
-        return self.data.workflow
+        return self._data.workflow
 
 
 def build_invocation_context(
@@ -580,7 +580,7 @@ def build_invocation_context(
         config=config,
         latents=latents,
         models=models,
-        data=context_data,
+        context_data=context_data,
         util=util,
         conditioning=conditioning,
         services=services,
diff --git a/tests/aa_nodes/test_graph_execution_state.py b/tests/aa_nodes/test_graph_execution_state.py
index 1612cbe719..aba7c5694f 100644
--- a/tests/aa_nodes/test_graph_execution_state.py
+++ b/tests/aa_nodes/test_graph_execution_state.py
@@ -87,7 +87,7 @@ def invoke_next(g: GraphExecutionState, services: InvocationServices) -> tuple[B
         InvocationContext(
             conditioning=None,
             config=None,
-            data=None,
+            context_data=None,
             images=None,
             latents=None,
             logger=None,

From 47d05fdd81010e11bb202db9a98c644539c5e0f4 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 7 Feb 2024 15:58:46 +1100
Subject: [PATCH 063/411] fix(nodes): do not freeze or cache config in context
 wrapper

- The config is already cached by the config class's `get_config()` method.
- The config mutates itself in its `root_path` property getter. Freezing the class makes any attempt to grab a path from the config error. Unfortunately this means we cannot easily freeze the class without fiddling with the inner workings of `InvokeAIAppConfig`, which is outside the scope here.
---
 .../app/services/shared/invocation_context.py  | 18 ++----------------
 1 file changed, 2 insertions(+), 16 deletions(-)

diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index b48a6acc54..cd88ec876d 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -357,24 +357,10 @@ class ModelsInterface(InvocationContextInterface):
 
 
 class ConfigInterface(InvocationContextInterface):
-    def __init__(self, services: InvocationServices, context_data: InvocationContextData) -> None:
-        super().__init__(services, context_data)
-        # Config cache, only populated at runtime if requested
-        self._frozen_config: Optional[InvokeAIAppConfig] = None
-
     def get(self) -> InvokeAIAppConfig:
-        """
-        Gets the app's config. The config is read-only; attempts to mutate it will raise an error.
-        """
+        """Gets the app's config."""
 
-        if self._frozen_config is None:
-            # The config is a live pydantic model and can be changed at runtime.
-            # We don't want nodes doing this, so we make a frozen copy.
-            self._frozen_config = self._services.configuration.get_config().model_copy(
-                update={"model_config": ConfigDict(frozen=True)}
-            )
-
-        return self._frozen_config
+        return self._services.configuration.get_config()
 
 
 class UtilInterface(InvocationContextInterface):

From 5d2f70b3ef37fb1dabfe8186cb417573f9207d35 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 7 Feb 2024 16:14:35 +1100
Subject: [PATCH 064/411] fix(ui): remove original l2i node in HRF graph

---
 .../web/src/features/nodes/util/graph/addHrfToGraph.ts        | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/addHrfToGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/addHrfToGraph.ts
index 7413302fa5..8a4448833c 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/addHrfToGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/addHrfToGraph.ts
@@ -314,6 +314,10 @@ export const addHrfToGraph = (state: RootState, graph: NonNullableGraph): void =
   );
   copyConnectionsToDenoiseLatentsHrf(graph);
 
+  // The original l2i node is unnecessary now, remove it
+  graph.edges = graph.edges.filter((edge) => edge.destination.node_id !== LATENTS_TO_IMAGE);
+  delete graph.nodes[LATENTS_TO_IMAGE];
+
   graph.nodes[LATENTS_TO_IMAGE_HRF_HR] = {
     type: 'l2i',
     id: LATENTS_TO_IMAGE_HRF_HR,

From e137071543c5ac65baf21b444badc44904d87981 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 7 Feb 2024 16:23:57 +1100
Subject: [PATCH 065/411] remove unused configdict import

---
 invokeai/app/services/shared/invocation_context.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index cd88ec876d..8aaa5233af 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -3,7 +3,6 @@ from typing import TYPE_CHECKING, Optional
 
 from deprecated import deprecated
 from PIL.Image import Image
-from pydantic import ConfigDict
 from torch import Tensor
 
 from invokeai.app.invocations.fields import MetadataField, WithMetadata

From 7fbdfbf9e5e504bc8311e307211d1c7064e5a347 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 7 Feb 2024 16:33:55 +1100
Subject: [PATCH 066/411] feat(nodes): add `WithBoard` field helper class

This class works the same way as `WithMetadata` - it simply adds a `board` field to the node. The context wrapper function is able to pull the board id from this. This allows image-outputting nodes to get a board field "for free", and have their outputs automatically saved to it.

This is a breaking change for node authors who may have a field called `board`, because it makes `board` a reserved field name. I'll look into how to avoid this - maybe by naming this invoke-managed field `_board` to avoid collisions?

Supporting changes:
- `WithBoard` is added to all image-outputting nodes, giving them the ability to save to board.
- Unused, duplicate `WithMetadata` and `WithWorkflow` classes are deleted from `baseinvocation.py`. The "real" versions are in `fields.py`.
- Remove `LinearUIOutputInvocation`. Now that all nodes that output images also have a `board` field by default, this node is no longer necessary. See comment here for context: https://github.com/invoke-ai/InvokeAI/pull/5491#discussion_r1480760629
- Without `LinearUIOutputInvocation`, the `ImagesInferface.update` method is no longer needed, and removed.

Note: This commit does not bump all node versions. I will ensure that is done correctly before merging the PR of which this commit is a part.

Note: A followup commit will implement the frontend changes to support this change.
---
 invokeai/app/invocations/baseinvocation.py    | 33 +-------
 .../controlnet_image_processors.py            | 12 ++-
 invokeai/app/invocations/cv.py                |  4 +-
 invokeai/app/invocations/facetools.py         |  4 +-
 invokeai/app/invocations/fields.py            | 16 ++++
 invokeai/app/invocations/image.py             | 76 ++++++-------------
 invokeai/app/invocations/infill.py            | 12 +--
 invokeai/app/invocations/latent.py            |  3 +-
 invokeai/app/invocations/primitives.py        |  4 +-
 invokeai/app/invocations/tiles.py             |  4 +-
 invokeai/app/invocations/upscale.py           |  4 +-
 .../app/services/shared/invocation_context.py | 40 +++-------
 12 files changed, 78 insertions(+), 134 deletions(-)

diff --git a/invokeai/app/invocations/baseinvocation.py b/invokeai/app/invocations/baseinvocation.py
index df0596c9a1..3243714937 100644
--- a/invokeai/app/invocations/baseinvocation.py
+++ b/invokeai/app/invocations/baseinvocation.py
@@ -17,11 +17,8 @@ from pydantic.fields import FieldInfo
 from pydantic_core import PydanticUndefined
 
 from invokeai.app.invocations.fields import (
-    FieldDescriptions,
     FieldKind,
     Input,
-    InputFieldJSONSchemaExtra,
-    MetadataField,
 )
 from invokeai.app.services.config.config_default import InvokeAIAppConfig
 from invokeai.app.services.shared.invocation_context import InvocationContext
@@ -306,9 +303,7 @@ RESERVED_NODE_ATTRIBUTE_FIELD_NAMES = {
     "workflow",
 }
 
-RESERVED_INPUT_FIELD_NAMES = {
-    "metadata",
-}
+RESERVED_INPUT_FIELD_NAMES = {"metadata", "board"}
 
 RESERVED_OUTPUT_FIELD_NAMES = {"type"}
 
@@ -518,29 +513,3 @@ def invocation_output(
         return cls
 
     return wrapper
-
-
-class WithMetadata(BaseModel):
-    """
-    Inherit from this class if your node needs a metadata input field.
-    """
-
-    metadata: Optional[MetadataField] = Field(
-        default=None,
-        description=FieldDescriptions.metadata,
-        json_schema_extra=InputFieldJSONSchemaExtra(
-            field_kind=FieldKind.Internal,
-            input=Input.Connection,
-            orig_required=False,
-        ).model_dump(exclude_none=True),
-    )
-
-
-class WithWorkflow:
-    workflow = None
-
-    def __init_subclass__(cls) -> None:
-        logger.warn(
-            f"{cls.__module__.split('.')[0]}.{cls.__name__}: WithWorkflow is deprecated. Use `context.workflow` to access the workflow."
-        )
-        super().__init_subclass__()
diff --git a/invokeai/app/invocations/controlnet_image_processors.py b/invokeai/app/invocations/controlnet_image_processors.py
index f8bdf14117..37954c1097 100644
--- a/invokeai/app/invocations/controlnet_image_processors.py
+++ b/invokeai/app/invocations/controlnet_image_processors.py
@@ -25,7 +25,15 @@ from controlnet_aux.util import HWC3, ade_palette
 from PIL import Image
 from pydantic import BaseModel, ConfigDict, Field, field_validator, model_validator
 
-from invokeai.app.invocations.fields import FieldDescriptions, ImageField, Input, InputField, OutputField, WithMetadata
+from invokeai.app.invocations.fields import (
+    FieldDescriptions,
+    ImageField,
+    Input,
+    InputField,
+    OutputField,
+    WithBoard,
+    WithMetadata,
+)
 from invokeai.app.invocations.primitives import ImageOutput
 from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
 from invokeai.app.services.shared.invocation_context import InvocationContext
@@ -135,7 +143,7 @@ class ControlNetInvocation(BaseInvocation):
 
 
 # This invocation exists for other invocations to subclass it - do not register with @invocation!
-class ImageProcessorInvocation(BaseInvocation, WithMetadata):
+class ImageProcessorInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Base class for invocations that preprocess images for ControlNet"""
 
     image: ImageField = InputField(description="The image to process")
diff --git a/invokeai/app/invocations/cv.py b/invokeai/app/invocations/cv.py
index 1ebabf5e06..8174f19b64 100644
--- a/invokeai/app/invocations/cv.py
+++ b/invokeai/app/invocations/cv.py
@@ -10,11 +10,11 @@ from invokeai.app.invocations.primitives import ImageOutput
 from invokeai.app.services.shared.invocation_context import InvocationContext
 
 from .baseinvocation import BaseInvocation, invocation
-from .fields import InputField, WithMetadata
+from .fields import InputField, WithBoard, WithMetadata
 
 
 @invocation("cv_inpaint", title="OpenCV Inpaint", tags=["opencv", "inpaint"], category="inpaint", version="1.2.1")
-class CvInpaintInvocation(BaseInvocation, WithMetadata):
+class CvInpaintInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Simple inpaint using opencv."""
 
     image: ImageField = InputField(description="The image to inpaint")
diff --git a/invokeai/app/invocations/facetools.py b/invokeai/app/invocations/facetools.py
index a1702d6517..fed2ed5e4f 100644
--- a/invokeai/app/invocations/facetools.py
+++ b/invokeai/app/invocations/facetools.py
@@ -16,7 +16,7 @@ from invokeai.app.invocations.baseinvocation import (
     invocation,
     invocation_output,
 )
-from invokeai.app.invocations.fields import ImageField, InputField, OutputField, WithMetadata
+from invokeai.app.invocations.fields import ImageField, InputField, OutputField, WithBoard, WithMetadata
 from invokeai.app.invocations.primitives import ImageOutput
 from invokeai.app.services.image_records.image_records_common import ImageCategory
 from invokeai.app.services.shared.invocation_context import InvocationContext
@@ -619,7 +619,7 @@ class FaceMaskInvocation(BaseInvocation, WithMetadata):
 @invocation(
     "face_identifier", title="FaceIdentifier", tags=["image", "face", "identifier"], category="image", version="1.2.1"
 )
-class FaceIdentifierInvocation(BaseInvocation, WithMetadata):
+class FaceIdentifierInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Outputs an image with detected face IDs printed on each face. For use with other FaceTools."""
 
     image: ImageField = InputField(description="Image to face detect")
diff --git a/invokeai/app/invocations/fields.py b/invokeai/app/invocations/fields.py
index 8879f76077..c42d2f8312 100644
--- a/invokeai/app/invocations/fields.py
+++ b/invokeai/app/invocations/fields.py
@@ -280,6 +280,22 @@ class WithWorkflow:
         super().__init_subclass__()
 
 
+class WithBoard(BaseModel):
+    """
+    Inherit from this class if your node needs a board input field.
+    """
+
+    board: Optional["BoardField"] = Field(
+        default=None,
+        description=FieldDescriptions.board,
+        json_schema_extra=InputFieldJSONSchemaExtra(
+            field_kind=FieldKind.Internal,
+            input=Input.Direct,
+            orig_required=False,
+        ).model_dump(exclude_none=True),
+    )
+
+
 class OutputFieldJSONSchemaExtra(BaseModel):
     """
     Extra attributes to be added to input fields and their OpenAPI schema. Used by the workflow editor
diff --git a/invokeai/app/invocations/image.py b/invokeai/app/invocations/image.py
index 7b74e4d96d..f5ad5515a6 100644
--- a/invokeai/app/invocations/image.py
+++ b/invokeai/app/invocations/image.py
@@ -8,12 +8,11 @@ import numpy
 from PIL import Image, ImageChops, ImageFilter, ImageOps
 
 from invokeai.app.invocations.fields import (
-    BoardField,
     ColorField,
     FieldDescriptions,
     ImageField,
-    Input,
     InputField,
+    WithBoard,
     WithMetadata,
 )
 from invokeai.app.invocations.primitives import ImageOutput
@@ -55,7 +54,7 @@ class ShowImageInvocation(BaseInvocation):
     category="image",
     version="1.2.1",
 )
-class BlankImageInvocation(BaseInvocation, WithMetadata):
+class BlankImageInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Creates a blank image and forwards it to the pipeline"""
 
     width: int = InputField(default=512, description="The width of the image")
@@ -78,7 +77,7 @@ class BlankImageInvocation(BaseInvocation, WithMetadata):
     category="image",
     version="1.2.1",
 )
-class ImageCropInvocation(BaseInvocation, WithMetadata):
+class ImageCropInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Crops an image to a specified box. The box can be outside of the image."""
 
     image: ImageField = InputField(description="The image to crop")
@@ -149,7 +148,7 @@ class CenterPadCropInvocation(BaseInvocation):
     category="image",
     version="1.2.1",
 )
-class ImagePasteInvocation(BaseInvocation, WithMetadata):
+class ImagePasteInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Pastes an image into another image."""
 
     base_image: ImageField = InputField(description="The base image")
@@ -196,7 +195,7 @@ class ImagePasteInvocation(BaseInvocation, WithMetadata):
     category="image",
     version="1.2.1",
 )
-class MaskFromAlphaInvocation(BaseInvocation, WithMetadata):
+class MaskFromAlphaInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Extracts the alpha channel of an image as a mask."""
 
     image: ImageField = InputField(description="The image to create the mask from")
@@ -221,7 +220,7 @@ class MaskFromAlphaInvocation(BaseInvocation, WithMetadata):
     category="image",
     version="1.2.1",
 )
-class ImageMultiplyInvocation(BaseInvocation, WithMetadata):
+class ImageMultiplyInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Multiplies two images together using `PIL.ImageChops.multiply()`."""
 
     image1: ImageField = InputField(description="The first image to multiply")
@@ -248,7 +247,7 @@ IMAGE_CHANNELS = Literal["A", "R", "G", "B"]
     category="image",
     version="1.2.1",
 )
-class ImageChannelInvocation(BaseInvocation, WithMetadata):
+class ImageChannelInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Gets a channel from an image."""
 
     image: ImageField = InputField(description="The image to get the channel from")
@@ -274,7 +273,7 @@ IMAGE_MODES = Literal["L", "RGB", "RGBA", "CMYK", "YCbCr", "LAB", "HSV", "I", "F
     category="image",
     version="1.2.1",
 )
-class ImageConvertInvocation(BaseInvocation, WithMetadata):
+class ImageConvertInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Converts an image to a different mode."""
 
     image: ImageField = InputField(description="The image to convert")
@@ -297,7 +296,7 @@ class ImageConvertInvocation(BaseInvocation, WithMetadata):
     category="image",
     version="1.2.1",
 )
-class ImageBlurInvocation(BaseInvocation, WithMetadata):
+class ImageBlurInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Blurs an image"""
 
     image: ImageField = InputField(description="The image to blur")
@@ -326,7 +325,7 @@ class ImageBlurInvocation(BaseInvocation, WithMetadata):
     version="1.2.1",
     classification=Classification.Beta,
 )
-class UnsharpMaskInvocation(BaseInvocation, WithMetadata):
+class UnsharpMaskInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Applies an unsharp mask filter to an image"""
 
     image: ImageField = InputField(description="The image to use")
@@ -394,7 +393,7 @@ PIL_RESAMPLING_MAP = {
     category="image",
     version="1.2.1",
 )
-class ImageResizeInvocation(BaseInvocation, WithMetadata):
+class ImageResizeInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Resizes an image to specific dimensions"""
 
     image: ImageField = InputField(description="The image to resize")
@@ -424,7 +423,7 @@ class ImageResizeInvocation(BaseInvocation, WithMetadata):
     category="image",
     version="1.2.1",
 )
-class ImageScaleInvocation(BaseInvocation, WithMetadata):
+class ImageScaleInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Scales an image by a factor"""
 
     image: ImageField = InputField(description="The image to scale")
@@ -459,7 +458,7 @@ class ImageScaleInvocation(BaseInvocation, WithMetadata):
     category="image",
     version="1.2.1",
 )
-class ImageLerpInvocation(BaseInvocation, WithMetadata):
+class ImageLerpInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Linear interpolation of all pixels of an image"""
 
     image: ImageField = InputField(description="The image to lerp")
@@ -486,7 +485,7 @@ class ImageLerpInvocation(BaseInvocation, WithMetadata):
     category="image",
     version="1.2.1",
 )
-class ImageInverseLerpInvocation(BaseInvocation, WithMetadata):
+class ImageInverseLerpInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Inverse linear interpolation of all pixels of an image"""
 
     image: ImageField = InputField(description="The image to lerp")
@@ -513,7 +512,7 @@ class ImageInverseLerpInvocation(BaseInvocation, WithMetadata):
     category="image",
     version="1.2.1",
 )
-class ImageNSFWBlurInvocation(BaseInvocation, WithMetadata):
+class ImageNSFWBlurInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Add blur to NSFW-flagged images"""
 
     image: ImageField = InputField(description="The image to check")
@@ -548,7 +547,7 @@ class ImageNSFWBlurInvocation(BaseInvocation, WithMetadata):
     category="image",
     version="1.2.1",
 )
-class ImageWatermarkInvocation(BaseInvocation, WithMetadata):
+class ImageWatermarkInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Add an invisible watermark to an image"""
 
     image: ImageField = InputField(description="The image to check")
@@ -569,7 +568,7 @@ class ImageWatermarkInvocation(BaseInvocation, WithMetadata):
     category="image",
     version="1.2.1",
 )
-class MaskEdgeInvocation(BaseInvocation, WithMetadata):
+class MaskEdgeInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Applies an edge mask to an image"""
 
     image: ImageField = InputField(description="The image to apply the mask to")
@@ -608,7 +607,7 @@ class MaskEdgeInvocation(BaseInvocation, WithMetadata):
     category="image",
     version="1.2.1",
 )
-class MaskCombineInvocation(BaseInvocation, WithMetadata):
+class MaskCombineInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Combine two masks together by multiplying them using `PIL.ImageChops.multiply()`."""
 
     mask1: ImageField = InputField(description="The first mask to combine")
@@ -632,7 +631,7 @@ class MaskCombineInvocation(BaseInvocation, WithMetadata):
     category="image",
     version="1.2.1",
 )
-class ColorCorrectInvocation(BaseInvocation, WithMetadata):
+class ColorCorrectInvocation(BaseInvocation, WithMetadata, WithBoard):
     """
     Shifts the colors of a target image to match the reference image, optionally
     using a mask to only color-correct certain regions of the target image.
@@ -736,7 +735,7 @@ class ColorCorrectInvocation(BaseInvocation, WithMetadata):
     category="image",
     version="1.2.1",
 )
-class ImageHueAdjustmentInvocation(BaseInvocation, WithMetadata):
+class ImageHueAdjustmentInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Adjusts the Hue of an image."""
 
     image: ImageField = InputField(description="The image to adjust")
@@ -825,7 +824,7 @@ CHANNEL_FORMATS = {
     category="image",
     version="1.2.1",
 )
-class ImageChannelOffsetInvocation(BaseInvocation, WithMetadata):
+class ImageChannelOffsetInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Add or subtract a value from a specific color channel of an image."""
 
     image: ImageField = InputField(description="The image to adjust")
@@ -881,7 +880,7 @@ class ImageChannelOffsetInvocation(BaseInvocation, WithMetadata):
     category="image",
     version="1.2.1",
 )
-class ImageChannelMultiplyInvocation(BaseInvocation, WithMetadata):
+class ImageChannelMultiplyInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Scale a specific color channel of an image."""
 
     image: ImageField = InputField(description="The image to adjust")
@@ -926,41 +925,14 @@ class ImageChannelMultiplyInvocation(BaseInvocation, WithMetadata):
     version="1.2.1",
     use_cache=False,
 )
-class SaveImageInvocation(BaseInvocation, WithMetadata):
+class SaveImageInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Saves an image. Unlike an image primitive, this invocation stores a copy of the image."""
 
     image: ImageField = InputField(description=FieldDescriptions.image)
-    board: BoardField = InputField(default=None, description=FieldDescriptions.board, input=Input.Direct)
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.images.get_pil(self.image.image_name)
 
-        image_dto = context.images.save(image=image, board_id=self.board.board_id if self.board else None)
-
-        return ImageOutput.build(image_dto)
-
-
-@invocation(
-    "linear_ui_output",
-    title="Linear UI Image Output",
-    tags=["primitives", "image"],
-    category="primitives",
-    version="1.0.2",
-    use_cache=False,
-)
-class LinearUIOutputInvocation(BaseInvocation, WithMetadata):
-    """Handles Linear UI Image Outputting tasks."""
-
-    image: ImageField = InputField(description=FieldDescriptions.image)
-    board: Optional[BoardField] = InputField(default=None, description=FieldDescriptions.board, input=Input.Direct)
-
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        image_dto = context.images.get_dto(self.image.image_name)
-
-        image_dto = context.images.update(
-            image_name=self.image.image_name,
-            board_id=self.board.board_id if self.board else None,
-            is_intermediate=self.is_intermediate,
-        )
+        image_dto = context.images.save(image=image)
 
         return ImageOutput.build(image_dto)
diff --git a/invokeai/app/invocations/infill.py b/invokeai/app/invocations/infill.py
index b007edd9e4..53f6f4732f 100644
--- a/invokeai/app/invocations/infill.py
+++ b/invokeai/app/invocations/infill.py
@@ -15,7 +15,7 @@ from invokeai.backend.image_util.lama import LaMA
 from invokeai.backend.image_util.patchmatch import PatchMatch
 
 from .baseinvocation import BaseInvocation, invocation
-from .fields import InputField, WithMetadata
+from .fields import InputField, WithBoard, WithMetadata
 from .image import PIL_RESAMPLING_MAP, PIL_RESAMPLING_MODES
 
 
@@ -121,7 +121,7 @@ def tile_fill_missing(im: Image.Image, tile_size: int = 16, seed: Optional[int]
 
 
 @invocation("infill_rgba", title="Solid Color Infill", tags=["image", "inpaint"], category="inpaint", version="1.2.1")
-class InfillColorInvocation(BaseInvocation, WithMetadata):
+class InfillColorInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Infills transparent areas of an image with a solid color"""
 
     image: ImageField = InputField(description="The image to infill")
@@ -144,7 +144,7 @@ class InfillColorInvocation(BaseInvocation, WithMetadata):
 
 
 @invocation("infill_tile", title="Tile Infill", tags=["image", "inpaint"], category="inpaint", version="1.2.2")
-class InfillTileInvocation(BaseInvocation, WithMetadata):
+class InfillTileInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Infills transparent areas of an image with tiles of the image"""
 
     image: ImageField = InputField(description="The image to infill")
@@ -170,7 +170,7 @@ class InfillTileInvocation(BaseInvocation, WithMetadata):
 @invocation(
     "infill_patchmatch", title="PatchMatch Infill", tags=["image", "inpaint"], category="inpaint", version="1.2.1"
 )
-class InfillPatchMatchInvocation(BaseInvocation, WithMetadata):
+class InfillPatchMatchInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Infills transparent areas of an image using the PatchMatch algorithm"""
 
     image: ImageField = InputField(description="The image to infill")
@@ -209,7 +209,7 @@ class InfillPatchMatchInvocation(BaseInvocation, WithMetadata):
 
 
 @invocation("infill_lama", title="LaMa Infill", tags=["image", "inpaint"], category="inpaint", version="1.2.1")
-class LaMaInfillInvocation(BaseInvocation, WithMetadata):
+class LaMaInfillInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Infills transparent areas of an image using the LaMa model"""
 
     image: ImageField = InputField(description="The image to infill")
@@ -225,7 +225,7 @@ class LaMaInfillInvocation(BaseInvocation, WithMetadata):
 
 
 @invocation("infill_cv2", title="CV2 Infill", tags=["image", "inpaint"], category="inpaint", version="1.2.1")
-class CV2InfillInvocation(BaseInvocation, WithMetadata):
+class CV2InfillInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Infills transparent areas of an image using OpenCV Inpainting"""
 
     image: ImageField = InputField(description="The image to infill")
diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py
index 5e36e73ec8..5449ec9af7 100644
--- a/invokeai/app/invocations/latent.py
+++ b/invokeai/app/invocations/latent.py
@@ -33,6 +33,7 @@ from invokeai.app.invocations.fields import (
     LatentsField,
     OutputField,
     UIType,
+    WithBoard,
     WithMetadata,
 )
 from invokeai.app.invocations.ip_adapter import IPAdapterField
@@ -762,7 +763,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
     category="latents",
     version="1.2.1",
 )
-class LatentsToImageInvocation(BaseInvocation, WithMetadata):
+class LatentsToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Generates an image from latents."""
 
     latents: LatentsField = InputField(
diff --git a/invokeai/app/invocations/primitives.py b/invokeai/app/invocations/primitives.py
index c90d3230b2..a77939943a 100644
--- a/invokeai/app/invocations/primitives.py
+++ b/invokeai/app/invocations/primitives.py
@@ -255,9 +255,7 @@ class ImageCollectionOutput(BaseInvocationOutput):
 
 
 @invocation("image", title="Image Primitive", tags=["primitives", "image"], category="primitives", version="1.0.1")
-class ImageInvocation(
-    BaseInvocation,
-):
+class ImageInvocation(BaseInvocation):
     """An image primitive value"""
 
     image: ImageField = InputField(description="The image to load")
diff --git a/invokeai/app/invocations/tiles.py b/invokeai/app/invocations/tiles.py
index 19ece42376..cb5373bbf7 100644
--- a/invokeai/app/invocations/tiles.py
+++ b/invokeai/app/invocations/tiles.py
@@ -11,7 +11,7 @@ from invokeai.app.invocations.baseinvocation import (
     invocation,
     invocation_output,
 )
-from invokeai.app.invocations.fields import ImageField, Input, InputField, OutputField, WithMetadata
+from invokeai.app.invocations.fields import ImageField, Input, InputField, OutputField, WithBoard, WithMetadata
 from invokeai.app.invocations.primitives import ImageOutput
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.backend.tiles.tiles import (
@@ -232,7 +232,7 @@ BLEND_MODES = Literal["Linear", "Seam"]
     version="1.1.0",
     classification=Classification.Beta,
 )
-class MergeTilesToImageInvocation(BaseInvocation, WithMetadata):
+class MergeTilesToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Merge multiple tile images into a single image."""
 
     # Inputs
diff --git a/invokeai/app/invocations/upscale.py b/invokeai/app/invocations/upscale.py
index 71ef7ca3aa..2e2a6ce881 100644
--- a/invokeai/app/invocations/upscale.py
+++ b/invokeai/app/invocations/upscale.py
@@ -16,7 +16,7 @@ from invokeai.backend.image_util.realesrgan.realesrgan import RealESRGAN
 from invokeai.backend.util.devices import choose_torch_device
 
 from .baseinvocation import BaseInvocation, invocation
-from .fields import InputField, WithMetadata
+from .fields import InputField, WithBoard, WithMetadata
 
 # TODO: Populate this from disk?
 # TODO: Use model manager to load?
@@ -32,7 +32,7 @@ if choose_torch_device() == torch.device("mps"):
 
 
 @invocation("esrgan", title="Upscale (RealESRGAN)", tags=["esrgan", "upscale"], category="esrgan", version="1.3.1")
-class ESRGANInvocation(BaseInvocation, WithMetadata):
+class ESRGANInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Upscales an image using RealESRGAN."""
 
     image: ImageField = InputField(description="The input image")
diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index 8aaa5233af..97a62246fb 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -5,10 +5,10 @@ from deprecated import deprecated
 from PIL.Image import Image
 from torch import Tensor
 
-from invokeai.app.invocations.fields import MetadataField, WithMetadata
+from invokeai.app.invocations.fields import MetadataField, WithBoard, WithMetadata
 from invokeai.app.services.boards.boards_common import BoardDTO
 from invokeai.app.services.config.config_default import InvokeAIAppConfig
-from invokeai.app.services.image_records.image_records_common import ImageCategory, ImageRecordChanges, ResourceOrigin
+from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
 from invokeai.app.services.images.images_common import ImageDTO
 from invokeai.app.services.invocation_services import InvocationServices
 from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID
@@ -158,7 +158,9 @@ class ImagesInterface(InvocationContextInterface):
         If the current queue item has a workflow or metadata, it is automatically saved with the image.
 
         :param image: The image to save, as a PIL image.
-        :param board_id: The board ID to add the image to, if it should be added.
+        :param board_id: The board ID to add the image to, if it should be added. It the invocation \
+            inherits from `WithBoard`, that board will be used automatically. **Use this only if \
+            you want to override or provide a board manually!**
         :param image_category: The category of the image. Only the GENERAL category is added \
             to the gallery.
         :param metadata: The metadata to save with the image, if it should have any. If the \
@@ -173,11 +175,15 @@ class ImagesInterface(InvocationContextInterface):
             else metadata
         )
 
+        # If the invocation inherits WithBoard, use that. Else, use the board_id passed in.
+        board_ = self._context_data.invocation.board if isinstance(self._context_data.invocation, WithBoard) else None
+        board_id_ = board_.board_id if board_ is not None else board_id
+
         return self._services.images.create(
             image=image,
             is_intermediate=self._context_data.invocation.is_intermediate,
             image_category=image_category,
-            board_id=board_id,
+            board_id=board_id_,
             metadata=metadata_,
             image_origin=ResourceOrigin.INTERNAL,
             workflow=self._context_data.workflow,
@@ -209,32 +215,6 @@ class ImagesInterface(InvocationContextInterface):
         """
         return self._services.images.get_dto(image_name)
 
-    def update(
-        self,
-        image_name: str,
-        board_id: Optional[str] = None,
-        is_intermediate: Optional[bool] = False,
-    ) -> ImageDTO:
-        """
-        Updates an image, returning its updated DTO.
-
-        It is not suggested to update images saved by earlier nodes, as this can cause confusion for users.
-
-        If you use this method, you *must* return the image as an :class:`ImageOutput` for the gallery to
-        get the updated image.
-
-        :param image_name: The name of the image to update.
-        :param board_id: The board ID to add the image to, if it should be added.
-        :param is_intermediate: Whether the image is an intermediate. Intermediate images aren't added to the gallery.
-        """
-        if is_intermediate is not None:
-            self._services.images.update(image_name, ImageRecordChanges(is_intermediate=is_intermediate))
-        if board_id is None:
-            self._services.board_images.remove_image_from_board(image_name)
-        else:
-            self._services.board_images.add_image_to_board(image_name, board_id)
-        return self._services.images.get_dto(image_name)
-
 
 class LatentsInterface(InvocationContextInterface):
     def save(self, tensor: Tensor) -> str:

From d60f1965d11c2529315d85fea9b664adcae9f490 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 7 Feb 2024 16:34:40 +1100
Subject: [PATCH 067/411] chore(ui): regen types

---
 .../frontend/web/src/services/api/schema.ts   | 223 ++++++++----------
 1 file changed, 96 insertions(+), 127 deletions(-)

diff --git a/invokeai/frontend/web/src/services/api/schema.ts b/invokeai/frontend/web/src/services/api/schema.ts
index da036b6d40..45358ed97d 100644
--- a/invokeai/frontend/web/src/services/api/schema.ts
+++ b/invokeai/frontend/web/src/services/api/schema.ts
@@ -968,6 +968,8 @@ export type components = {
      * @description Creates a blank image and forwards it to the pipeline
      */
     BlankImageInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -1860,6 +1862,8 @@ export type components = {
      * @description Infills transparent areas of an image using OpenCV Inpainting
      */
     CV2InfillInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -2095,6 +2099,8 @@ export type components = {
      * @description Canny edge detection for ControlNet
      */
     CannyImageProcessorInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -2482,6 +2488,8 @@ export type components = {
      * using a mask to only color-correct certain regions of the target image.
      */
     ColorCorrectInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -2590,6 +2598,8 @@ export type components = {
      * @description Generates a color map from the provided image
      */
     ColorMapImageProcessorInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -2797,6 +2807,8 @@ export type components = {
      * @description Applies content shuffle processing to image
      */
     ContentShuffleImageProcessorInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -3442,6 +3454,8 @@ export type components = {
      * @description Simple inpaint using opencv.
      */
     CvInpaintInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -3677,6 +3691,8 @@ export type components = {
      * @description Generates a depth map based on the Depth Anything algorithm
      */
     DepthAnythingImageProcessorInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -3910,6 +3926,8 @@ export type components = {
      * @description Upscales an image using RealESRGAN.
      */
     ESRGANInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -4041,6 +4059,8 @@ export type components = {
      * @description Outputs an image with detected face IDs printed on each face. For use with other FaceTools.
      */
     FaceIdentifierInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -4873,6 +4893,8 @@ export type components = {
      * @description Applies HED edge detection to image
      */
     HedImageProcessorInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -5324,6 +5346,8 @@ export type components = {
      * @description Blurs an image
      */
     ImageBlurInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -5382,6 +5406,8 @@ export type components = {
      * @description Gets a channel from an image.
      */
     ImageChannelInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -5422,6 +5448,8 @@ export type components = {
      * @description Scale a specific color channel of an image.
      */
     ImageChannelMultiplyInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -5473,6 +5501,8 @@ export type components = {
      * @description Add or subtract a value from a specific color channel of an image.
      */
     ImageChannelOffsetInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -5640,6 +5670,8 @@ export type components = {
      * @description Converts an image to a different mode.
      */
     ImageConvertInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -5680,6 +5712,8 @@ export type components = {
      * @description Crops an image to a specified box. The box can be outside of the image.
      */
     ImageCropInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -5949,6 +5983,8 @@ export type components = {
      * @description Adjusts the Hue of an image.
      */
     ImageHueAdjustmentInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -5988,6 +6024,8 @@ export type components = {
      * @description Inverse linear interpolation of all pixels of an image
      */
     ImageInverseLerpInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -6064,6 +6102,8 @@ export type components = {
      * @description Linear interpolation of all pixels of an image
      */
     ImageLerpInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -6109,6 +6149,8 @@ export type components = {
      * @description Multiplies two images together using `PIL.ImageChops.multiply()`.
      */
     ImageMultiplyInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -6144,6 +6186,8 @@ export type components = {
      * @description Add blur to NSFW-flagged images
      */
     ImageNSFWBlurInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -6252,6 +6296,8 @@ export type components = {
      * @description Pastes an image into another image.
      */
     ImagePasteInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -6337,6 +6383,8 @@ export type components = {
      * @description Resizes an image to specific dimensions
      */
     ImageResizeInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -6446,6 +6494,8 @@ export type components = {
      * @description Scales an image by a factor
      */
     ImageScaleInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -6621,6 +6671,8 @@ export type components = {
      * @description Add an invisible watermark to an image
      */
     ImageWatermarkInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -6676,6 +6728,8 @@ export type components = {
      * @description Infills transparent areas of an image with a solid color
      */
     InfillColorInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -6719,6 +6773,8 @@ export type components = {
      * @description Infills transparent areas of an image using the PatchMatch algorithm
      */
     InfillPatchMatchInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -6765,6 +6821,8 @@ export type components = {
      * @description Infills transparent areas of an image with tiles of the image
      */
     InfillTileInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -7065,6 +7123,8 @@ export type components = {
      * @description Infills transparent areas of an image using the LaMa model
      */
     LaMaInfillInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -7093,96 +7153,6 @@ export type components = {
        */
       type: "infill_lama";
     };
-    /**
-     * Latent Consistency MonoNode
-     * @description Wrapper node around diffusers LatentConsistencyTxt2ImgPipeline
-     */
-    LatentConsistencyInvocation: {
-      /**
-       * Id
-       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
-       */
-      id: string;
-      /**
-       * Is Intermediate
-       * @description Whether or not this is an intermediate invocation.
-       * @default false
-       */
-      is_intermediate?: boolean;
-      /**
-       * Use Cache
-       * @description Whether or not to use the cache
-       * @default true
-       */
-      use_cache?: boolean;
-      /**
-       * Prompt
-       * @description The prompt to use
-       */
-      prompt?: string;
-      /**
-       * Num Inference Steps
-       * @description The number of inference steps to use, 4-8 recommended
-       * @default 8
-       */
-      num_inference_steps?: number;
-      /**
-       * Guidance Scale
-       * @description The guidance scale to use
-       * @default 8
-       */
-      guidance_scale?: number;
-      /**
-       * Batches
-       * @description The number of batches to use
-       * @default 1
-       */
-      batches?: number;
-      /**
-       * Images Per Batch
-       * @description The number of images per batch to use
-       * @default 1
-       */
-      images_per_batch?: number;
-      /**
-       * Seeds
-       * @description List of noise seeds to use
-       */
-      seeds?: number[];
-      /**
-       * Lcm Origin Steps
-       * @description The lcm origin steps to use
-       * @default 50
-       */
-      lcm_origin_steps?: number;
-      /**
-       * Width
-       * @description The width to use
-       * @default 512
-       */
-      width?: number;
-      /**
-       * Height
-       * @description The height to use
-       * @default 512
-       */
-      height?: number;
-      /**
-       * Precision
-       * @description floating point precision
-       * @default fp16
-       * @enum {string}
-       */
-      precision?: "fp16" | "fp32";
-      /** @description The board to save the image to */
-      board?: components["schemas"]["BoardField"];
-      /**
-       * type
-       * @default latent_consistency_mononode
-       * @constant
-       */
-      type: "latent_consistency_mononode";
-    };
     /**
      * Latents Collection Primitive
      * @description A collection of latents tensor primitive values
@@ -7310,6 +7280,8 @@ export type components = {
      * @description Generates an image from latents.
      */
     LatentsToImageInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -7357,6 +7329,8 @@ export type components = {
      * @description Applies leres processing to image
      */
     LeresImageProcessorInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -7441,46 +7415,13 @@ export type components = {
       /** @description Type of commercial use allowed or 'No' if no commercial use is allowed. */
       AllowCommercialUse?: components["schemas"]["CommercialUsage"];
     };
-    /**
-     * Linear UI Image Output
-     * @description Handles Linear UI Image Outputting tasks.
-     */
-    LinearUIOutputInvocation: {
-      /** @description Optional metadata to be saved with the image */
-      metadata?: components["schemas"]["MetadataField"] | null;
-      /**
-       * Id
-       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
-       */
-      id: string;
-      /**
-       * Is Intermediate
-       * @description Whether or not this is an intermediate invocation.
-       * @default false
-       */
-      is_intermediate?: boolean;
-      /**
-       * Use Cache
-       * @description Whether or not to use the cache
-       * @default false
-       */
-      use_cache?: boolean;
-      /** @description The image to process */
-      image?: components["schemas"]["ImageField"];
-      /** @description The board to save the image to */
-      board?: components["schemas"]["BoardField"] | null;
-      /**
-       * type
-       * @default linear_ui_output
-       * @constant
-       */
-      type: "linear_ui_output";
-    };
     /**
      * Lineart Anime Processor
      * @description Applies line art anime processing to image
      */
     LineartAnimeImageProcessorInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -7526,6 +7467,8 @@ export type components = {
      * @description Applies line art processing to image
      */
     LineartImageProcessorInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -7954,6 +7897,8 @@ export type components = {
      * @description Combine two masks together by multiplying them using `PIL.ImageChops.multiply()`.
      */
     MaskCombineInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -7989,6 +7934,8 @@ export type components = {
      * @description Applies an edge mask to an image
      */
     MaskEdgeInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -8042,6 +7989,8 @@ export type components = {
      * @description Extracts the alpha channel of an image as a mask.
      */
     MaskFromAlphaInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -8122,6 +8071,8 @@ export type components = {
      * @description Applies mediapipe face processing to image
      */
     MediapipeFaceProcessorInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -8238,6 +8189,8 @@ export type components = {
      * @description Merge multiple tile images into a single image.
      */
     MergeTilesToImageInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -8404,6 +8357,8 @@ export type components = {
      * @description Applies Midas depth processing to image
      */
     MidasDepthImageProcessorInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -8449,6 +8404,8 @@ export type components = {
      * @description Applies MLSD processing to image
      */
     MlsdImageProcessorInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -8961,6 +8918,8 @@ export type components = {
      * @description Applies NormalBae processing to image
      */
     NormalbaeImageProcessorInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -9591,6 +9550,8 @@ export type components = {
      * @description Applies PIDI processing to image
      */
     PidiImageProcessorInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -10443,6 +10404,8 @@ export type components = {
      * @description Saves an image. Unlike an image primitive, this invocation stores a copy of the image.
      */
     SaveImageInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -10464,8 +10427,6 @@ export type components = {
       use_cache?: boolean;
       /** @description The image to process */
       image?: components["schemas"]["ImageField"];
-      /** @description The board to save the image to */
-      board?: components["schemas"]["BoardField"];
       /**
        * type
        * @default save_image
@@ -10651,6 +10612,8 @@ export type components = {
      * @description Applies segment anything processing to image
      */
     SegmentAnythingProcessorInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -12189,6 +12152,8 @@ export type components = {
      * @description Tile resampler processor
      */
     TileResamplerProcessorInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -12378,6 +12343,8 @@ export type components = {
      * @description Applies an unsharp mask filter to an image
      */
     UnsharpMaskInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -12846,6 +12813,8 @@ export type components = {
      * @description Applies Zoe depth processing to image
      */
     ZoeDepthImageProcessorInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**

From 70034d26e2e3df971215f35198d98b28511510eb Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 7 Feb 2024 16:41:24 +1100
Subject: [PATCH 068/411] feat(ui): revise graphs to not use
 `LinearUIOutputInvocation`

See this comment for context: https://github.com/invoke-ai/InvokeAI/pull/5491#discussion_r1480760629

- Remove this now-unnecessary node from all graphs
- Update graphs' terminal image-outputting nodes' `is_intermediate` and `board` fields appropriately
- Add util function to prepare the `board` field, tidy the utils
- Update `socketInvocationComplete` listener to work correctly with this change

I've manually tested all graph permutations that were changed (I think this is all...) to ensure images go to the gallery as expected:
- ad-hoc upscaling
- t2i w/ sd1.5
- t2i w/ sd1.5 & hrf
- t2i w/ sdxl
- t2i w/ sdxl + refiner
- i2i w/ sd1.5
- i2i w/ sdxl
- i2i w/ sdxl + refiner
- canvas t2i w/ sd1.5
- canvas t2i w/ sdxl
- canvas t2i w/ sdxl + refiner
- canvas i2i w/ sd1.5
- canvas i2i w/ sdxl
- canvas i2i w/ sdxl + refiner
- canvas inpaint w/ sd1.5
- canvas inpaint w/ sdxl
- canvas inpaint w/ sdxl + refiner
- canvas outpaint w/ sd1.5
- canvas outpaint w/ sdxl
- canvas outpaint w/ sdxl + refiner
---
 .../socketio/socketInvocationComplete.ts      |  9 +--
 .../listeners/upscaleRequested.ts             |  6 +-
 .../nodes/util/graph/addHrfToGraph.ts         |  4 +-
 .../nodes/util/graph/addLinearUIOutputNode.ts | 78 -------------------
 .../nodes/util/graph/addNSFWCheckerToGraph.ts |  4 +-
 .../nodes/util/graph/addSDXLRefinerToGraph.ts |  2 +-
 .../nodes/util/graph/addWatermarkerToGraph.ts |  9 +--
 .../util/graph/buildAdHocUpscaleGraph.ts      | 40 +++-------
 .../graph/buildCanvasImageToImageGraph.ts     | 13 ++--
 .../util/graph/buildCanvasInpaintGraph.ts     |  7 +-
 .../util/graph/buildCanvasOutpaintGraph.ts    |  7 +-
 .../graph/buildCanvasSDXLImageToImageGraph.ts |  8 +-
 .../util/graph/buildCanvasSDXLInpaintGraph.ts |  8 +-
 .../graph/buildCanvasSDXLOutpaintGraph.ts     |  8 +-
 .../graph/buildCanvasSDXLTextToImageGraph.ts  | 11 ++-
 .../util/graph/buildCanvasTextToImageGraph.ts | 10 +--
 .../graph/buildLinearImageToImageGraph.ts     |  7 +-
 .../graph/buildLinearSDXLImageToImageGraph.ts |  8 +-
 .../graph/buildLinearSDXLTextToImageGraph.ts  |  8 +-
 .../util/graph/buildLinearTextToImageGraph.ts |  7 +-
 .../features/nodes/util/graph/constants.ts    |  1 -
 .../nodes/util/graph/getSDXLStylePrompt.ts    | 11 ---
 .../nodes/util/graph/graphBuilderUtils.ts     | 38 +++++++++
 .../frontend/web/src/services/api/types.ts    |  1 -
 24 files changed, 108 insertions(+), 197 deletions(-)
 delete mode 100644 invokeai/frontend/web/src/features/nodes/util/graph/addLinearUIOutputNode.ts
 delete mode 100644 invokeai/frontend/web/src/features/nodes/util/graph/getSDXLStylePrompt.ts
 create mode 100644 invokeai/frontend/web/src/features/nodes/util/graph/graphBuilderUtils.ts

diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationComplete.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationComplete.ts
index d49f35cd2a..75fa9e1094 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationComplete.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationComplete.ts
@@ -4,7 +4,7 @@ import { addImageToStagingArea } from 'features/canvas/store/canvasSlice';
 import { boardIdSelected, galleryViewChanged, imageSelected } from 'features/gallery/store/gallerySlice';
 import { IMAGE_CATEGORIES } from 'features/gallery/store/types';
 import { isImageOutput } from 'features/nodes/types/common';
-import { LINEAR_UI_OUTPUT, nodeIDDenyList } from 'features/nodes/util/graph/constants';
+import { CANVAS_OUTPUT } from 'features/nodes/util/graph/constants';
 import { boardsApi } from 'services/api/endpoints/boards';
 import { imagesApi } from 'services/api/endpoints/images';
 import { imagesAdapter } from 'services/api/util';
@@ -24,10 +24,9 @@ export const addInvocationCompleteEventListener = () => {
       const { data } = action.payload;
       log.debug({ data: parseify(data) }, `Invocation complete (${action.payload.data.node.type})`);
 
-      const { result, node, queue_batch_id, source_node_id } = data;
-
+      const { result, node, queue_batch_id } = data;
       // This complete event has an associated image output
-      if (isImageOutput(result) && !nodeTypeDenylist.includes(node.type) && !nodeIDDenyList.includes(source_node_id)) {
+      if (isImageOutput(result) && !nodeTypeDenylist.includes(node.type)) {
         const { image_name } = result.image;
         const { canvas, gallery } = getState();
 
@@ -42,7 +41,7 @@ export const addInvocationCompleteEventListener = () => {
         imageDTORequest.unsubscribe();
 
         // Add canvas images to the staging area
-        if (canvas.batchIds.includes(queue_batch_id) && [LINEAR_UI_OUTPUT].includes(data.source_node_id)) {
+        if (canvas.batchIds.includes(queue_batch_id) && data.source_node_id === CANVAS_OUTPUT) {
           dispatch(addImageToStagingArea(imageDTO));
         }
 
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/upscaleRequested.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/upscaleRequested.ts
index 46f55ef21f..ab98930179 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/upscaleRequested.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/upscaleRequested.ts
@@ -39,16 +39,12 @@ export const addUpscaleRequestedListener = () => {
         return;
       }
 
-      const { esrganModelName } = state.postprocessing;
-      const { autoAddBoardId } = state.gallery;
-
       const enqueueBatchArg: BatchConfig = {
         prepend: true,
         batch: {
           graph: buildAdHocUpscaleGraph({
             image_name,
-            esrganModelName,
-            autoAddBoardId,
+            state,
           }),
           runs: 1,
         },
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/addHrfToGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/addHrfToGraph.ts
index 8a4448833c..5632cfd112 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/addHrfToGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/addHrfToGraph.ts
@@ -1,6 +1,7 @@
 import { logger } from 'app/logging/logger';
 import type { RootState } from 'app/store/store';
 import { roundToMultiple } from 'common/util/roundDownToMultiple';
+import { getBoardField, getIsIntermediate } from 'features/nodes/util/graph/graphBuilderUtils';
 import { selectOptimalDimension } from 'features/parameters/store/generationSlice';
 import type {
   DenoiseLatentsInvocation,
@@ -322,7 +323,8 @@ export const addHrfToGraph = (state: RootState, graph: NonNullableGraph): void =
     type: 'l2i',
     id: LATENTS_TO_IMAGE_HRF_HR,
     fp32: originalLatentsToImageNode?.fp32,
-    is_intermediate: true,
+    is_intermediate: getIsIntermediate(state),
+    board: getBoardField(state),
   };
   graph.edges.push(
     {
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/addLinearUIOutputNode.ts b/invokeai/frontend/web/src/features/nodes/util/graph/addLinearUIOutputNode.ts
deleted file mode 100644
index 5c78ad804e..0000000000
--- a/invokeai/frontend/web/src/features/nodes/util/graph/addLinearUIOutputNode.ts
+++ /dev/null
@@ -1,78 +0,0 @@
-import type { RootState } from 'app/store/store';
-import { activeTabNameSelector } from 'features/ui/store/uiSelectors';
-import type { LinearUIOutputInvocation, NonNullableGraph } from 'services/api/types';
-
-import {
-  CANVAS_OUTPUT,
-  LATENTS_TO_IMAGE,
-  LATENTS_TO_IMAGE_HRF_HR,
-  LINEAR_UI_OUTPUT,
-  NSFW_CHECKER,
-  WATERMARKER,
-} from './constants';
-
-/**
- * Set the `use_cache` field on the linear/canvas graph's final image output node to False.
- */
-export const addLinearUIOutputNode = (state: RootState, graph: NonNullableGraph): void => {
-  const activeTabName = activeTabNameSelector(state);
-  const is_intermediate = activeTabName === 'unifiedCanvas' ? !state.canvas.shouldAutoSave : false;
-  const { autoAddBoardId } = state.gallery;
-
-  const linearUIOutputNode: LinearUIOutputInvocation = {
-    id: LINEAR_UI_OUTPUT,
-    type: 'linear_ui_output',
-    is_intermediate,
-    use_cache: false,
-    board: autoAddBoardId === 'none' ? undefined : { board_id: autoAddBoardId },
-  };
-
-  graph.nodes[LINEAR_UI_OUTPUT] = linearUIOutputNode;
-
-  const destination = {
-    node_id: LINEAR_UI_OUTPUT,
-    field: 'image',
-  };
-
-  if (WATERMARKER in graph.nodes) {
-    graph.edges.push({
-      source: {
-        node_id: WATERMARKER,
-        field: 'image',
-      },
-      destination,
-    });
-  } else if (NSFW_CHECKER in graph.nodes) {
-    graph.edges.push({
-      source: {
-        node_id: NSFW_CHECKER,
-        field: 'image',
-      },
-      destination,
-    });
-  } else if (CANVAS_OUTPUT in graph.nodes) {
-    graph.edges.push({
-      source: {
-        node_id: CANVAS_OUTPUT,
-        field: 'image',
-      },
-      destination,
-    });
-  } else if (LATENTS_TO_IMAGE_HRF_HR in graph.nodes) {
-    graph.edges.push({
-      source: {
-        node_id: LATENTS_TO_IMAGE_HRF_HR,
-        field: 'image',
-      },
-      destination,
-    });
-  } else if (LATENTS_TO_IMAGE in graph.nodes) {
-    graph.edges.push({
-      source: {
-        node_id: LATENTS_TO_IMAGE,
-        field: 'image',
-      },
-      destination,
-    });
-  }
-};
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/addNSFWCheckerToGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/addNSFWCheckerToGraph.ts
index 4a8e77abfa..35fc324689 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/addNSFWCheckerToGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/addNSFWCheckerToGraph.ts
@@ -2,6 +2,7 @@ import type { RootState } from 'app/store/store';
 import type { ImageNSFWBlurInvocation, LatentsToImageInvocation, NonNullableGraph } from 'services/api/types';
 
 import { LATENTS_TO_IMAGE, NSFW_CHECKER } from './constants';
+import { getBoardField, getIsIntermediate } from './graphBuilderUtils';
 
 export const addNSFWCheckerToGraph = (
   state: RootState,
@@ -21,7 +22,8 @@ export const addNSFWCheckerToGraph = (
   const nsfwCheckerNode: ImageNSFWBlurInvocation = {
     id: NSFW_CHECKER,
     type: 'img_nsfw',
-    is_intermediate: true,
+    is_intermediate: getIsIntermediate(state),
+    board: getBoardField(state),
   };
 
   graph.nodes[NSFW_CHECKER] = nsfwCheckerNode as ImageNSFWBlurInvocation;
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/addSDXLRefinerToGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/addSDXLRefinerToGraph.ts
index 708353e4d6..fc4d998969 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/addSDXLRefinerToGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/addSDXLRefinerToGraph.ts
@@ -24,7 +24,7 @@ import {
   SDXL_REFINER_POSITIVE_CONDITIONING,
   SDXL_REFINER_SEAMLESS,
 } from './constants';
-import { getSDXLStylePrompts } from './getSDXLStylePrompt';
+import { getSDXLStylePrompts } from './graphBuilderUtils';
 import { upsertMetadata } from './metadata';
 
 export const addSDXLRefinerToGraph = (
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/addWatermarkerToGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/addWatermarkerToGraph.ts
index 99c5c07be4..61beb11df4 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/addWatermarkerToGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/addWatermarkerToGraph.ts
@@ -1,5 +1,4 @@
 import type { RootState } from 'app/store/store';
-import { activeTabNameSelector } from 'features/ui/store/uiSelectors';
 import type {
   ImageNSFWBlurInvocation,
   ImageWatermarkInvocation,
@@ -8,16 +7,13 @@ import type {
 } from 'services/api/types';
 
 import { LATENTS_TO_IMAGE, NSFW_CHECKER, WATERMARKER } from './constants';
+import { getBoardField, getIsIntermediate } from './graphBuilderUtils';
 
 export const addWatermarkerToGraph = (
   state: RootState,
   graph: NonNullableGraph,
   nodeIdToAddTo = LATENTS_TO_IMAGE
 ): void => {
-  const activeTabName = activeTabNameSelector(state);
-
-  const is_intermediate = activeTabName === 'unifiedCanvas' ? !state.canvas.shouldAutoSave : false;
-
   const nodeToAddTo = graph.nodes[nodeIdToAddTo] as LatentsToImageInvocation | undefined;
 
   const nsfwCheckerNode = graph.nodes[NSFW_CHECKER] as ImageNSFWBlurInvocation | undefined;
@@ -30,7 +26,8 @@ export const addWatermarkerToGraph = (
   const watermarkerNode: ImageWatermarkInvocation = {
     id: WATERMARKER,
     type: 'img_watermark',
-    is_intermediate,
+    is_intermediate: getIsIntermediate(state),
+    board: getBoardField(state),
   };
 
   graph.nodes[WATERMARKER] = watermarkerNode;
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildAdHocUpscaleGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildAdHocUpscaleGraph.ts
index fa20206d91..52c09b1db0 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildAdHocUpscaleGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildAdHocUpscaleGraph.ts
@@ -1,51 +1,33 @@
-import type { BoardId } from 'features/gallery/store/types';
-import type { ParamESRGANModelName } from 'features/parameters/store/postprocessingSlice';
-import type { ESRGANInvocation, Graph, LinearUIOutputInvocation, NonNullableGraph } from 'services/api/types';
+import type { RootState } from 'app/store/store';
+import { getBoardField, getIsIntermediate } from 'features/nodes/util/graph/graphBuilderUtils';
+import type { ESRGANInvocation, Graph, NonNullableGraph } from 'services/api/types';
 
-import { ESRGAN, LINEAR_UI_OUTPUT } from './constants';
+import { ESRGAN } from './constants';
 import { addCoreMetadataNode, upsertMetadata } from './metadata';
 
 type Arg = {
   image_name: string;
-  esrganModelName: ParamESRGANModelName;
-  autoAddBoardId: BoardId;
+  state: RootState;
 };
 
-export const buildAdHocUpscaleGraph = ({ image_name, esrganModelName, autoAddBoardId }: Arg): Graph => {
+export const buildAdHocUpscaleGraph = ({ image_name, state }: Arg): Graph => {
+  const { esrganModelName } = state.postprocessing;
+
   const realesrganNode: ESRGANInvocation = {
     id: ESRGAN,
     type: 'esrgan',
     image: { image_name },
     model_name: esrganModelName,
-    is_intermediate: true,
-  };
-
-  const linearUIOutputNode: LinearUIOutputInvocation = {
-    id: LINEAR_UI_OUTPUT,
-    type: 'linear_ui_output',
-    use_cache: false,
-    is_intermediate: false,
-    board: autoAddBoardId === 'none' ? undefined : { board_id: autoAddBoardId },
+    is_intermediate: getIsIntermediate(state),
+    board: getBoardField(state),
   };
 
   const graph: NonNullableGraph = {
     id: `adhoc-esrgan-graph`,
     nodes: {
       [ESRGAN]: realesrganNode,
-      [LINEAR_UI_OUTPUT]: linearUIOutputNode,
     },
-    edges: [
-      {
-        source: {
-          node_id: ESRGAN,
-          field: 'image',
-        },
-        destination: {
-          node_id: LINEAR_UI_OUTPUT,
-          field: 'image',
-        },
-      },
-    ],
+    edges: [],
   };
 
   addCoreMetadataNode(graph, {}, ESRGAN);
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasImageToImageGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasImageToImageGraph.ts
index 3002e05441..bc6a83f4fa 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasImageToImageGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasImageToImageGraph.ts
@@ -1,10 +1,10 @@
 import { logger } from 'app/logging/logger';
 import type { RootState } from 'app/store/store';
+import { getBoardField, getIsIntermediate } from 'features/nodes/util/graph/graphBuilderUtils';
 import type { ImageDTO, ImageToLatentsInvocation, NonNullableGraph } from 'services/api/types';
 
 import { addControlNetToLinearGraph } from './addControlNetToLinearGraph';
 import { addIPAdapterToLinearGraph } from './addIPAdapterToLinearGraph';
-import { addLinearUIOutputNode } from './addLinearUIOutputNode';
 import { addLoRAsToGraph } from './addLoRAsToGraph';
 import { addNSFWCheckerToGraph } from './addNSFWCheckerToGraph';
 import { addSeamlessToLinearGraph } from './addSeamlessToLinearGraph';
@@ -132,7 +132,8 @@ export const buildCanvasImageToImageGraph = (state: RootState, initialImage: Ima
       [CANVAS_OUTPUT]: {
         type: 'l2i',
         id: CANVAS_OUTPUT,
-        is_intermediate,
+        is_intermediate: getIsIntermediate(state),
+        board: getBoardField(state),
         use_cache: false,
       },
     },
@@ -242,7 +243,8 @@ export const buildCanvasImageToImageGraph = (state: RootState, initialImage: Ima
     graph.nodes[CANVAS_OUTPUT] = {
       id: CANVAS_OUTPUT,
       type: 'img_resize',
-      is_intermediate,
+      is_intermediate: getIsIntermediate(state),
+      board: getBoardField(state),
       width: width,
       height: height,
       use_cache: false,
@@ -284,7 +286,8 @@ export const buildCanvasImageToImageGraph = (state: RootState, initialImage: Ima
     graph.nodes[CANVAS_OUTPUT] = {
       type: 'l2i',
       id: CANVAS_OUTPUT,
-      is_intermediate,
+      is_intermediate: getIsIntermediate(state),
+      board: getBoardField(state),
       fp32,
       use_cache: false,
     };
@@ -355,7 +358,5 @@ export const buildCanvasImageToImageGraph = (state: RootState, initialImage: Ima
     addWatermarkerToGraph(state, graph, CANVAS_OUTPUT);
   }
 
-  addLinearUIOutputNode(state, graph);
-
   return graph;
 };
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasInpaintGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasInpaintGraph.ts
index bb52a44a8e..d983b9cf4f 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasInpaintGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasInpaintGraph.ts
@@ -1,5 +1,6 @@
 import { logger } from 'app/logging/logger';
 import type { RootState } from 'app/store/store';
+import { getBoardField, getIsIntermediate } from 'features/nodes/util/graph/graphBuilderUtils';
 import type {
   CreateDenoiseMaskInvocation,
   ImageBlurInvocation,
@@ -12,7 +13,6 @@ import type {
 
 import { addControlNetToLinearGraph } from './addControlNetToLinearGraph';
 import { addIPAdapterToLinearGraph } from './addIPAdapterToLinearGraph';
-import { addLinearUIOutputNode } from './addLinearUIOutputNode';
 import { addLoRAsToGraph } from './addLoRAsToGraph';
 import { addNSFWCheckerToGraph } from './addNSFWCheckerToGraph';
 import { addSeamlessToLinearGraph } from './addSeamlessToLinearGraph';
@@ -191,7 +191,8 @@ export const buildCanvasInpaintGraph = (
       [CANVAS_OUTPUT]: {
         type: 'color_correct',
         id: CANVAS_OUTPUT,
-        is_intermediate,
+        is_intermediate: getIsIntermediate(state),
+        board: getBoardField(state),
         reference: canvasInitImage,
         use_cache: false,
       },
@@ -663,7 +664,5 @@ export const buildCanvasInpaintGraph = (
     addWatermarkerToGraph(state, graph, CANVAS_OUTPUT);
   }
 
-  addLinearUIOutputNode(state, graph);
-
   return graph;
 };
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasOutpaintGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasOutpaintGraph.ts
index b82b55cfee..1d02894381 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasOutpaintGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasOutpaintGraph.ts
@@ -1,5 +1,6 @@
 import { logger } from 'app/logging/logger';
 import type { RootState } from 'app/store/store';
+import { getBoardField, getIsIntermediate } from 'features/nodes/util/graph/graphBuilderUtils';
 import type {
   ImageDTO,
   ImageToLatentsInvocation,
@@ -11,7 +12,6 @@ import type {
 
 import { addControlNetToLinearGraph } from './addControlNetToLinearGraph';
 import { addIPAdapterToLinearGraph } from './addIPAdapterToLinearGraph';
-import { addLinearUIOutputNode } from './addLinearUIOutputNode';
 import { addLoRAsToGraph } from './addLoRAsToGraph';
 import { addNSFWCheckerToGraph } from './addNSFWCheckerToGraph';
 import { addSeamlessToLinearGraph } from './addSeamlessToLinearGraph';
@@ -200,7 +200,8 @@ export const buildCanvasOutpaintGraph = (
       [CANVAS_OUTPUT]: {
         type: 'color_correct',
         id: CANVAS_OUTPUT,
-        is_intermediate,
+        is_intermediate: getIsIntermediate(state),
+        board: getBoardField(state),
         use_cache: false,
       },
     },
@@ -769,7 +770,5 @@ export const buildCanvasOutpaintGraph = (
     addWatermarkerToGraph(state, graph, CANVAS_OUTPUT);
   }
 
-  addLinearUIOutputNode(state, graph);
-
   return graph;
 };
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLImageToImageGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLImageToImageGraph.ts
index 1b586371a0..58269afce3 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLImageToImageGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLImageToImageGraph.ts
@@ -4,7 +4,6 @@ import type { ImageDTO, ImageToLatentsInvocation, NonNullableGraph } from 'servi
 
 import { addControlNetToLinearGraph } from './addControlNetToLinearGraph';
 import { addIPAdapterToLinearGraph } from './addIPAdapterToLinearGraph';
-import { addLinearUIOutputNode } from './addLinearUIOutputNode';
 import { addNSFWCheckerToGraph } from './addNSFWCheckerToGraph';
 import { addSDXLLoRAsToGraph } from './addSDXLLoRAstoGraph';
 import { addSDXLRefinerToGraph } from './addSDXLRefinerToGraph';
@@ -26,7 +25,7 @@ import {
   SDXL_REFINER_SEAMLESS,
   SEAMLESS,
 } from './constants';
-import { getSDXLStylePrompts } from './getSDXLStylePrompt';
+import { getBoardField, getIsIntermediate, getSDXLStylePrompts } from './graphBuilderUtils';
 import { addCoreMetadataNode } from './metadata';
 
 /**
@@ -246,7 +245,8 @@ export const buildCanvasSDXLImageToImageGraph = (state: RootState, initialImage:
     graph.nodes[CANVAS_OUTPUT] = {
       id: CANVAS_OUTPUT,
       type: 'img_resize',
-      is_intermediate,
+      is_intermediate: getIsIntermediate(state),
+      board: getBoardField(state),
       width: width,
       height: height,
       use_cache: false,
@@ -368,7 +368,5 @@ export const buildCanvasSDXLImageToImageGraph = (state: RootState, initialImage:
     addWatermarkerToGraph(state, graph, CANVAS_OUTPUT);
   }
 
-  addLinearUIOutputNode(state, graph);
-
   return graph;
 };
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLInpaintGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLInpaintGraph.ts
index 00fea9a37e..5902dee2fc 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLInpaintGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLInpaintGraph.ts
@@ -12,7 +12,6 @@ import type {
 
 import { addControlNetToLinearGraph } from './addControlNetToLinearGraph';
 import { addIPAdapterToLinearGraph } from './addIPAdapterToLinearGraph';
-import { addLinearUIOutputNode } from './addLinearUIOutputNode';
 import { addNSFWCheckerToGraph } from './addNSFWCheckerToGraph';
 import { addSDXLLoRAsToGraph } from './addSDXLLoRAstoGraph';
 import { addSDXLRefinerToGraph } from './addSDXLRefinerToGraph';
@@ -44,7 +43,7 @@ import {
   SDXL_REFINER_SEAMLESS,
   SEAMLESS,
 } from './constants';
-import { getSDXLStylePrompts } from './getSDXLStylePrompt';
+import { getBoardField, getIsIntermediate, getSDXLStylePrompts } from './graphBuilderUtils';
 
 /**
  * Builds the Canvas tab's Inpaint graph.
@@ -190,7 +189,8 @@ export const buildCanvasSDXLInpaintGraph = (
       [CANVAS_OUTPUT]: {
         type: 'color_correct',
         id: CANVAS_OUTPUT,
-        is_intermediate,
+        is_intermediate: getIsIntermediate(state),
+        board: getBoardField(state),
         reference: canvasInitImage,
         use_cache: false,
       },
@@ -687,7 +687,5 @@ export const buildCanvasSDXLInpaintGraph = (
     addWatermarkerToGraph(state, graph, CANVAS_OUTPUT);
   }
 
-  addLinearUIOutputNode(state, graph);
-
   return graph;
 };
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLOutpaintGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLOutpaintGraph.ts
index f85760d8f2..7a78750e8d 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLOutpaintGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLOutpaintGraph.ts
@@ -11,7 +11,6 @@ import type {
 
 import { addControlNetToLinearGraph } from './addControlNetToLinearGraph';
 import { addIPAdapterToLinearGraph } from './addIPAdapterToLinearGraph';
-import { addLinearUIOutputNode } from './addLinearUIOutputNode';
 import { addNSFWCheckerToGraph } from './addNSFWCheckerToGraph';
 import { addSDXLLoRAsToGraph } from './addSDXLLoRAstoGraph';
 import { addSDXLRefinerToGraph } from './addSDXLRefinerToGraph';
@@ -46,7 +45,7 @@ import {
   SDXL_REFINER_SEAMLESS,
   SEAMLESS,
 } from './constants';
-import { getSDXLStylePrompts } from './getSDXLStylePrompt';
+import { getBoardField, getIsIntermediate, getSDXLStylePrompts } from './graphBuilderUtils';
 
 /**
  * Builds the Canvas tab's Outpaint graph.
@@ -199,7 +198,8 @@ export const buildCanvasSDXLOutpaintGraph = (
       [CANVAS_OUTPUT]: {
         type: 'color_correct',
         id: CANVAS_OUTPUT,
-        is_intermediate,
+        is_intermediate: getIsIntermediate(state),
+        board: getBoardField(state),
         use_cache: false,
       },
     },
@@ -786,7 +786,5 @@ export const buildCanvasSDXLOutpaintGraph = (
     addWatermarkerToGraph(state, graph, CANVAS_OUTPUT);
   }
 
-  addLinearUIOutputNode(state, graph);
-
   return graph;
 };
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLTextToImageGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLTextToImageGraph.ts
index 91d9da4cb5..22da39c67d 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLTextToImageGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLTextToImageGraph.ts
@@ -4,7 +4,6 @@ import type { NonNullableGraph } from 'services/api/types';
 
 import { addControlNetToLinearGraph } from './addControlNetToLinearGraph';
 import { addIPAdapterToLinearGraph } from './addIPAdapterToLinearGraph';
-import { addLinearUIOutputNode } from './addLinearUIOutputNode';
 import { addNSFWCheckerToGraph } from './addNSFWCheckerToGraph';
 import { addSDXLLoRAsToGraph } from './addSDXLLoRAstoGraph';
 import { addSDXLRefinerToGraph } from './addSDXLRefinerToGraph';
@@ -24,7 +23,7 @@ import {
   SDXL_REFINER_SEAMLESS,
   SEAMLESS,
 } from './constants';
-import { getSDXLStylePrompts } from './getSDXLStylePrompt';
+import { getBoardField, getIsIntermediate, getSDXLStylePrompts } from './graphBuilderUtils';
 import { addCoreMetadataNode } from './metadata';
 
 /**
@@ -222,7 +221,8 @@ export const buildCanvasSDXLTextToImageGraph = (state: RootState): NonNullableGr
     graph.nodes[CANVAS_OUTPUT] = {
       id: CANVAS_OUTPUT,
       type: 'img_resize',
-      is_intermediate,
+      is_intermediate: getIsIntermediate(state),
+      board: getBoardField(state),
       width: width,
       height: height,
       use_cache: false,
@@ -254,7 +254,8 @@ export const buildCanvasSDXLTextToImageGraph = (state: RootState): NonNullableGr
     graph.nodes[CANVAS_OUTPUT] = {
       type: 'l2i',
       id: CANVAS_OUTPUT,
-      is_intermediate,
+      is_intermediate: getIsIntermediate(state),
+      board: getBoardField(state),
       fp32,
       use_cache: false,
     };
@@ -330,7 +331,5 @@ export const buildCanvasSDXLTextToImageGraph = (state: RootState): NonNullableGr
     addWatermarkerToGraph(state, graph, CANVAS_OUTPUT);
   }
 
-  addLinearUIOutputNode(state, graph);
-
   return graph;
 };
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasTextToImageGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasTextToImageGraph.ts
index 967dd3ff4a..93f0470c7a 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasTextToImageGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasTextToImageGraph.ts
@@ -1,10 +1,10 @@
 import { logger } from 'app/logging/logger';
 import type { RootState } from 'app/store/store';
+import { getBoardField, getIsIntermediate } from 'features/nodes/util/graph/graphBuilderUtils';
 import type { NonNullableGraph } from 'services/api/types';
 
 import { addControlNetToLinearGraph } from './addControlNetToLinearGraph';
 import { addIPAdapterToLinearGraph } from './addIPAdapterToLinearGraph';
-import { addLinearUIOutputNode } from './addLinearUIOutputNode';
 import { addLoRAsToGraph } from './addLoRAsToGraph';
 import { addNSFWCheckerToGraph } from './addNSFWCheckerToGraph';
 import { addSeamlessToLinearGraph } from './addSeamlessToLinearGraph';
@@ -211,7 +211,8 @@ export const buildCanvasTextToImageGraph = (state: RootState): NonNullableGraph
     graph.nodes[CANVAS_OUTPUT] = {
       id: CANVAS_OUTPUT,
       type: 'img_resize',
-      is_intermediate,
+      is_intermediate: getIsIntermediate(state),
+      board: getBoardField(state),
       width: width,
       height: height,
       use_cache: false,
@@ -243,7 +244,8 @@ export const buildCanvasTextToImageGraph = (state: RootState): NonNullableGraph
     graph.nodes[CANVAS_OUTPUT] = {
       type: 'l2i',
       id: CANVAS_OUTPUT,
-      is_intermediate,
+      is_intermediate: getIsIntermediate(state),
+      board: getBoardField(state),
       fp32,
       use_cache: false,
     };
@@ -310,7 +312,5 @@ export const buildCanvasTextToImageGraph = (state: RootState): NonNullableGraph
     addWatermarkerToGraph(state, graph, CANVAS_OUTPUT);
   }
 
-  addLinearUIOutputNode(state, graph);
-
   return graph;
 };
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildLinearImageToImageGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildLinearImageToImageGraph.ts
index c76776d94d..d1f1546b23 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildLinearImageToImageGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildLinearImageToImageGraph.ts
@@ -1,10 +1,10 @@
 import { logger } from 'app/logging/logger';
 import type { RootState } from 'app/store/store';
+import { getBoardField, getIsIntermediate } from 'features/nodes/util/graph/graphBuilderUtils';
 import type { ImageResizeInvocation, ImageToLatentsInvocation, NonNullableGraph } from 'services/api/types';
 
 import { addControlNetToLinearGraph } from './addControlNetToLinearGraph';
 import { addIPAdapterToLinearGraph } from './addIPAdapterToLinearGraph';
-import { addLinearUIOutputNode } from './addLinearUIOutputNode';
 import { addLoRAsToGraph } from './addLoRAsToGraph';
 import { addNSFWCheckerToGraph } from './addNSFWCheckerToGraph';
 import { addSeamlessToLinearGraph } from './addSeamlessToLinearGraph';
@@ -117,7 +117,8 @@ export const buildLinearImageToImageGraph = (state: RootState): NonNullableGraph
         type: 'l2i',
         id: LATENTS_TO_IMAGE,
         fp32,
-        is_intermediate,
+        is_intermediate: getIsIntermediate(state),
+        board: getBoardField(state),
       },
       [DENOISE_LATENTS]: {
         type: 'denoise_latents',
@@ -358,7 +359,5 @@ export const buildLinearImageToImageGraph = (state: RootState): NonNullableGraph
     addWatermarkerToGraph(state, graph);
   }
 
-  addLinearUIOutputNode(state, graph);
-
   return graph;
 };
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildLinearSDXLImageToImageGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildLinearSDXLImageToImageGraph.ts
index 9ae602bcac..de4ad7cece 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildLinearSDXLImageToImageGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildLinearSDXLImageToImageGraph.ts
@@ -4,7 +4,6 @@ import type { ImageResizeInvocation, ImageToLatentsInvocation, NonNullableGraph
 
 import { addControlNetToLinearGraph } from './addControlNetToLinearGraph';
 import { addIPAdapterToLinearGraph } from './addIPAdapterToLinearGraph';
-import { addLinearUIOutputNode } from './addLinearUIOutputNode';
 import { addNSFWCheckerToGraph } from './addNSFWCheckerToGraph';
 import { addSDXLLoRAsToGraph } from './addSDXLLoRAstoGraph';
 import { addSDXLRefinerToGraph } from './addSDXLRefinerToGraph';
@@ -25,7 +24,7 @@ import {
   SDXL_REFINER_SEAMLESS,
   SEAMLESS,
 } from './constants';
-import { getSDXLStylePrompts } from './getSDXLStylePrompt';
+import { getBoardField, getIsIntermediate, getSDXLStylePrompts } from './graphBuilderUtils';
 import { addCoreMetadataNode } from './metadata';
 
 /**
@@ -120,7 +119,8 @@ export const buildLinearSDXLImageToImageGraph = (state: RootState): NonNullableG
         type: 'l2i',
         id: LATENTS_TO_IMAGE,
         fp32,
-        is_intermediate,
+        is_intermediate: getIsIntermediate(state),
+        board: getBoardField(state),
       },
       [SDXL_DENOISE_LATENTS]: {
         type: 'denoise_latents',
@@ -380,7 +380,5 @@ export const buildLinearSDXLImageToImageGraph = (state: RootState): NonNullableG
     addWatermarkerToGraph(state, graph);
   }
 
-  addLinearUIOutputNode(state, graph);
-
   return graph;
 };
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildLinearSDXLTextToImageGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildLinearSDXLTextToImageGraph.ts
index 222dc1a359..58b97b07c7 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildLinearSDXLTextToImageGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildLinearSDXLTextToImageGraph.ts
@@ -4,7 +4,6 @@ import type { NonNullableGraph } from 'services/api/types';
 
 import { addControlNetToLinearGraph } from './addControlNetToLinearGraph';
 import { addIPAdapterToLinearGraph } from './addIPAdapterToLinearGraph';
-import { addLinearUIOutputNode } from './addLinearUIOutputNode';
 import { addNSFWCheckerToGraph } from './addNSFWCheckerToGraph';
 import { addSDXLLoRAsToGraph } from './addSDXLLoRAstoGraph';
 import { addSDXLRefinerToGraph } from './addSDXLRefinerToGraph';
@@ -23,7 +22,7 @@ import {
   SDXL_TEXT_TO_IMAGE_GRAPH,
   SEAMLESS,
 } from './constants';
-import { getSDXLStylePrompts } from './getSDXLStylePrompt';
+import { getBoardField, getIsIntermediate, getSDXLStylePrompts } from './graphBuilderUtils';
 import { addCoreMetadataNode } from './metadata';
 
 export const buildLinearSDXLTextToImageGraph = (state: RootState): NonNullableGraph => {
@@ -120,7 +119,8 @@ export const buildLinearSDXLTextToImageGraph = (state: RootState): NonNullableGr
         type: 'l2i',
         id: LATENTS_TO_IMAGE,
         fp32,
-        is_intermediate,
+        is_intermediate: getIsIntermediate(state),
+        board: getBoardField(state),
         use_cache: false,
       },
     },
@@ -281,7 +281,5 @@ export const buildLinearSDXLTextToImageGraph = (state: RootState): NonNullableGr
     addWatermarkerToGraph(state, graph);
   }
 
-  addLinearUIOutputNode(state, graph);
-
   return graph;
 };
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildLinearTextToImageGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildLinearTextToImageGraph.ts
index 0a45d91deb..b2b84cfdad 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildLinearTextToImageGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildLinearTextToImageGraph.ts
@@ -1,11 +1,11 @@
 import { logger } from 'app/logging/logger';
 import type { RootState } from 'app/store/store';
+import { getBoardField, getIsIntermediate } from 'features/nodes/util/graph/graphBuilderUtils';
 import type { NonNullableGraph } from 'services/api/types';
 
 import { addControlNetToLinearGraph } from './addControlNetToLinearGraph';
 import { addHrfToGraph } from './addHrfToGraph';
 import { addIPAdapterToLinearGraph } from './addIPAdapterToLinearGraph';
-import { addLinearUIOutputNode } from './addLinearUIOutputNode';
 import { addLoRAsToGraph } from './addLoRAsToGraph';
 import { addNSFWCheckerToGraph } from './addNSFWCheckerToGraph';
 import { addSeamlessToLinearGraph } from './addSeamlessToLinearGraph';
@@ -119,7 +119,8 @@ export const buildLinearTextToImageGraph = (state: RootState): NonNullableGraph
         type: 'l2i',
         id: LATENTS_TO_IMAGE,
         fp32,
-        is_intermediate,
+        is_intermediate: getIsIntermediate(state),
+        board: getBoardField(state),
         use_cache: false,
       },
     },
@@ -267,7 +268,5 @@ export const buildLinearTextToImageGraph = (state: RootState): NonNullableGraph
     addWatermarkerToGraph(state, graph);
   }
 
-  addLinearUIOutputNode(state, graph);
-
   return graph;
 };
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/constants.ts b/invokeai/frontend/web/src/features/nodes/util/graph/constants.ts
index 363d319121..767bf25df0 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/constants.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/constants.ts
@@ -9,7 +9,6 @@ export const LATENTS_TO_IMAGE_HRF_LR = 'latents_to_image_hrf_lr';
 export const IMAGE_TO_LATENTS_HRF = 'image_to_latents_hrf';
 export const RESIZE_HRF = 'resize_hrf';
 export const ESRGAN_HRF = 'esrgan_hrf';
-export const LINEAR_UI_OUTPUT = 'linear_ui_output';
 export const NSFW_CHECKER = 'nsfw_checker';
 export const WATERMARKER = 'invisible_watermark';
 export const NOISE = 'noise';
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/getSDXLStylePrompt.ts b/invokeai/frontend/web/src/features/nodes/util/graph/getSDXLStylePrompt.ts
deleted file mode 100644
index e1cd8518fd..0000000000
--- a/invokeai/frontend/web/src/features/nodes/util/graph/getSDXLStylePrompt.ts
+++ /dev/null
@@ -1,11 +0,0 @@
-import type { RootState } from 'app/store/store';
-
-export const getSDXLStylePrompts = (state: RootState): { positiveStylePrompt: string; negativeStylePrompt: string } => {
-  const { positivePrompt, negativePrompt } = state.generation;
-  const { positiveStylePrompt, negativeStylePrompt, shouldConcatSDXLStylePrompt } = state.sdxl;
-
-  return {
-    positiveStylePrompt: shouldConcatSDXLStylePrompt ? positivePrompt : positiveStylePrompt,
-    negativeStylePrompt: shouldConcatSDXLStylePrompt ? negativePrompt : negativeStylePrompt,
-  };
-};
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/graphBuilderUtils.ts b/invokeai/frontend/web/src/features/nodes/util/graph/graphBuilderUtils.ts
new file mode 100644
index 0000000000..cb6fc9acf1
--- /dev/null
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/graphBuilderUtils.ts
@@ -0,0 +1,38 @@
+import type { RootState } from 'app/store/store';
+import type { BoardField } from 'features/nodes/types/common';
+import { activeTabNameSelector } from 'features/ui/store/uiSelectors';
+
+/**
+ * Gets the board field, based on the autoAddBoardId setting.
+ */
+export const getBoardField = (state: RootState): BoardField | undefined => {
+  const { autoAddBoardId } = state.gallery;
+  if (autoAddBoardId === 'none') {
+    return undefined;
+  }
+  return { board_id: autoAddBoardId };
+};
+
+/**
+ * Gets the SDXL style prompts, based on the concat setting.
+ */
+export const getSDXLStylePrompts = (state: RootState): { positiveStylePrompt: string; negativeStylePrompt: string } => {
+  const { positivePrompt, negativePrompt } = state.generation;
+  const { positiveStylePrompt, negativeStylePrompt, shouldConcatSDXLStylePrompt } = state.sdxl;
+
+  return {
+    positiveStylePrompt: shouldConcatSDXLStylePrompt ? positivePrompt : positiveStylePrompt,
+    negativeStylePrompt: shouldConcatSDXLStylePrompt ? negativePrompt : negativeStylePrompt,
+  };
+};
+
+/**
+ * Gets the is_intermediate field, based on the active tab and shouldAutoSave setting.
+ */
+export const getIsIntermediate = (state: RootState) => {
+  const activeTabName = activeTabNameSelector(state);
+  if (activeTabName === 'unifiedCanvas') {
+    return !state.canvas.shouldAutoSave;
+  }
+  return false;
+};
diff --git a/invokeai/frontend/web/src/services/api/types.ts b/invokeai/frontend/web/src/services/api/types.ts
index 1382fbe275..55ff808b40 100644
--- a/invokeai/frontend/web/src/services/api/types.ts
+++ b/invokeai/frontend/web/src/services/api/types.ts
@@ -132,7 +132,6 @@ export type DivideInvocation = s['DivideInvocation'];
 export type ImageNSFWBlurInvocation = s['ImageNSFWBlurInvocation'];
 export type ImageWatermarkInvocation = s['ImageWatermarkInvocation'];
 export type SeamlessModeInvocation = s['SeamlessModeInvocation'];
-export type LinearUIOutputInvocation = s['LinearUIOutputInvocation'];
 export type MetadataInvocation = s['MetadataInvocation'];
 export type CoreMetadataInvocation = s['CoreMetadataInvocation'];
 export type MetadataItemInvocation = s['MetadataItemInvocation'];

From b386b1b8af0c5d0bb790b770ac4e68bb1b8c30c4 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 7 Feb 2024 17:01:39 +1100
Subject: [PATCH 069/411] tidy(nodes): remove unnecessary, shadowing class attr
 declarations

---
 invokeai/app/services/invocation_services.py | 27 --------------------
 1 file changed, 27 deletions(-)

diff --git a/invokeai/app/services/invocation_services.py b/invokeai/app/services/invocation_services.py
index 11a4de99d6..51bfd5d77a 100644
--- a/invokeai/app/services/invocation_services.py
+++ b/invokeai/app/services/invocation_services.py
@@ -36,33 +36,6 @@ if TYPE_CHECKING:
 class InvocationServices:
     """Services that can be used by invocations"""
 
-    # TODO: Just forward-declared everything due to circular dependencies. Fix structure.
-    board_images: "BoardImagesServiceABC"
-    board_image_record_storage: "BoardImageRecordStorageBase"
-    boards: "BoardServiceABC"
-    board_records: "BoardRecordStorageBase"
-    configuration: "InvokeAIAppConfig"
-    events: "EventServiceBase"
-    graph_execution_manager: "ItemStorageABC[GraphExecutionState]"
-    images: "ImageServiceABC"
-    image_records: "ImageRecordStorageBase"
-    image_files: "ImageFileStorageBase"
-    latents: "LatentsStorageBase"
-    logger: "Logger"
-    model_manager: "ModelManagerServiceBase"
-    model_records: "ModelRecordServiceBase"
-    download_queue: "DownloadQueueServiceBase"
-    model_install: "ModelInstallServiceBase"
-    processor: "InvocationProcessorABC"
-    performance_statistics: "InvocationStatsServiceBase"
-    queue: "InvocationQueueABC"
-    session_queue: "SessionQueueBase"
-    session_processor: "SessionProcessorBase"
-    invocation_cache: "InvocationCacheBase"
-    names: "NameServiceBase"
-    urls: "UrlServiceBase"
-    workflow_records: "WorkflowRecordsStorageBase"
-
     def __init__(
         self,
         board_images: "BoardImagesServiceABC",

From 322a60f48fe3c58b2fa5b582a0681f1b7f756fdb Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 7 Feb 2024 17:10:25 +1100
Subject: [PATCH 070/411] fix(nodes): rearrange fields.py to avoid needing
 forward refs

---
 invokeai/app/invocations/fields.py | 92 +++++++++++++++---------------
 1 file changed, 46 insertions(+), 46 deletions(-)

diff --git a/invokeai/app/invocations/fields.py b/invokeai/app/invocations/fields.py
index c42d2f8312..40d403c03d 100644
--- a/invokeai/app/invocations/fields.py
+++ b/invokeai/app/invocations/fields.py
@@ -182,6 +182,51 @@ class FieldDescriptions:
     freeu_b2 = "Scaling factor for stage 2 to amplify the contributions of backbone features."
 
 
+class ImageField(BaseModel):
+    """An image primitive field"""
+
+    image_name: str = Field(description="The name of the image")
+
+
+class BoardField(BaseModel):
+    """A board primitive field"""
+
+    board_id: str = Field(description="The id of the board")
+
+
+class DenoiseMaskField(BaseModel):
+    """An inpaint mask field"""
+
+    mask_name: str = Field(description="The name of the mask image")
+    masked_latents_name: Optional[str] = Field(default=None, description="The name of the masked image latents")
+
+
+class LatentsField(BaseModel):
+    """A latents tensor primitive field"""
+
+    latents_name: str = Field(description="The name of the latents")
+    seed: Optional[int] = Field(default=None, description="Seed used to generate this latents")
+
+
+class ColorField(BaseModel):
+    """A color primitive field"""
+
+    r: int = Field(ge=0, le=255, description="The red component")
+    g: int = Field(ge=0, le=255, description="The green component")
+    b: int = Field(ge=0, le=255, description="The blue component")
+    a: int = Field(ge=0, le=255, description="The alpha component")
+
+    def tuple(self) -> Tuple[int, int, int, int]:
+        return (self.r, self.g, self.b, self.a)
+
+
+class ConditioningField(BaseModel):
+    """A conditioning tensor primitive value"""
+
+    conditioning_name: str = Field(description="The name of conditioning tensor")
+    # endregion
+
+
 class MetadataField(RootModel):
     """
     Pydantic model for metadata with custom root of type dict[str, Any].
@@ -285,7 +330,7 @@ class WithBoard(BaseModel):
     Inherit from this class if your node needs a board input field.
     """
 
-    board: Optional["BoardField"] = Field(
+    board: Optional[BoardField] = Field(
         default=None,
         description=FieldDescriptions.board,
         json_schema_extra=InputFieldJSONSchemaExtra(
@@ -518,48 +563,3 @@ def OutputField(
             field_kind=FieldKind.Output,
         ).model_dump(exclude_none=True),
     )
-
-
-class ImageField(BaseModel):
-    """An image primitive field"""
-
-    image_name: str = Field(description="The name of the image")
-
-
-class BoardField(BaseModel):
-    """A board primitive field"""
-
-    board_id: str = Field(description="The id of the board")
-
-
-class DenoiseMaskField(BaseModel):
-    """An inpaint mask field"""
-
-    mask_name: str = Field(description="The name of the mask image")
-    masked_latents_name: Optional[str] = Field(default=None, description="The name of the masked image latents")
-
-
-class LatentsField(BaseModel):
-    """A latents tensor primitive field"""
-
-    latents_name: str = Field(description="The name of the latents")
-    seed: Optional[int] = Field(default=None, description="Seed used to generate this latents")
-
-
-class ColorField(BaseModel):
-    """A color primitive field"""
-
-    r: int = Field(ge=0, le=255, description="The red component")
-    g: int = Field(ge=0, le=255, description="The green component")
-    b: int = Field(ge=0, le=255, description="The blue component")
-    a: int = Field(ge=0, le=255, description="The alpha component")
-
-    def tuple(self) -> Tuple[int, int, int, int]:
-        return (self.r, self.g, self.b, self.a)
-
-
-class ConditioningField(BaseModel):
-    """A conditioning tensor primitive value"""
-
-    conditioning_name: str = Field(description="The name of conditioning tensor")
-    # endregion

From 31db62ba9975d9d57bb852877231a6ec471d3dd6 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 7 Feb 2024 17:11:22 +1100
Subject: [PATCH 071/411] tidy(nodes): delete onnx.py

It doesn't work and keeping it updated to prevent the app from starting was getting tedious. Deleted.
---
 invokeai/app/invocations/onnx.py | 510 -------------------------------
 1 file changed, 510 deletions(-)
 delete mode 100644 invokeai/app/invocations/onnx.py

diff --git a/invokeai/app/invocations/onnx.py b/invokeai/app/invocations/onnx.py
deleted file mode 100644
index e7b4d3d9fc..0000000000
--- a/invokeai/app/invocations/onnx.py
+++ /dev/null
@@ -1,510 +0,0 @@
-# Copyright (c) 2023 Borisov Sergey (https://github.com/StAlKeR7779)
-
-import inspect
-
-# from contextlib import ExitStack
-from typing import List, Literal, Union
-
-import numpy as np
-import torch
-from diffusers.image_processor import VaeImageProcessor
-from pydantic import BaseModel, ConfigDict, Field, field_validator
-from tqdm import tqdm
-
-from invokeai.app.invocations.fields import (
-    FieldDescriptions,
-    Input,
-    InputField,
-    OutputField,
-    UIComponent,
-    UIType,
-    WithMetadata,
-)
-from invokeai.app.invocations.primitives import ConditioningField, ConditioningOutput, ImageField, ImageOutput
-from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
-from invokeai.app.util.step_callback import stable_diffusion_step_callback
-from invokeai.backend import BaseModelType, ModelType, SubModelType
-
-from ...backend.model_management import ONNXModelPatcher
-from ...backend.stable_diffusion import PipelineIntermediateState
-from ...backend.util import choose_torch_device
-from ..util.ti_utils import extract_ti_triggers_from_prompt
-from .baseinvocation import (
-    BaseInvocation,
-    BaseInvocationOutput,
-    InvocationContext,
-    invocation,
-    invocation_output,
-)
-from .controlnet_image_processors import ControlField
-from .latent import SAMPLER_NAME_VALUES, LatentsField, LatentsOutput, get_scheduler
-from .model import ClipField, ModelInfo, UNetField, VaeField
-
-ORT_TO_NP_TYPE = {
-    "tensor(bool)": np.bool_,
-    "tensor(int8)": np.int8,
-    "tensor(uint8)": np.uint8,
-    "tensor(int16)": np.int16,
-    "tensor(uint16)": np.uint16,
-    "tensor(int32)": np.int32,
-    "tensor(uint32)": np.uint32,
-    "tensor(int64)": np.int64,
-    "tensor(uint64)": np.uint64,
-    "tensor(float16)": np.float16,
-    "tensor(float)": np.float32,
-    "tensor(double)": np.float64,
-}
-
-PRECISION_VALUES = Literal[tuple(ORT_TO_NP_TYPE.keys())]
-
-
-@invocation("prompt_onnx", title="ONNX Prompt (Raw)", tags=["prompt", "onnx"], category="conditioning", version="1.0.0")
-class ONNXPromptInvocation(BaseInvocation):
-    prompt: str = InputField(default="", description=FieldDescriptions.raw_prompt, ui_component=UIComponent.Textarea)
-    clip: ClipField = InputField(description=FieldDescriptions.clip, input=Input.Connection)
-
-    def invoke(self, context: InvocationContext) -> ConditioningOutput:
-        tokenizer_info = context.services.model_manager.get_model(
-            **self.clip.tokenizer.model_dump(),
-        )
-        text_encoder_info = context.services.model_manager.get_model(
-            **self.clip.text_encoder.model_dump(),
-        )
-        with tokenizer_info as orig_tokenizer, text_encoder_info as text_encoder:  # , ExitStack() as stack:
-            loras = [
-                (
-                    context.services.model_manager.get_model(**lora.model_dump(exclude={"weight"})).context.model,
-                    lora.weight,
-                )
-                for lora in self.clip.loras
-            ]
-
-            ti_list = []
-            for trigger in extract_ti_triggers_from_prompt(self.prompt):
-                name = trigger[1:-1]
-                try:
-                    ti_list.append(
-                        (
-                            name,
-                            context.services.model_manager.get_model(
-                                model_name=name,
-                                base_model=self.clip.text_encoder.base_model,
-                                model_type=ModelType.TextualInversion,
-                            ).context.model,
-                        )
-                    )
-                except Exception:
-                    # print(e)
-                    # import traceback
-                    # print(traceback.format_exc())
-                    print(f'Warn: trigger: "{trigger}" not found')
-            if loras or ti_list:
-                text_encoder.release_session()
-            with (
-                ONNXModelPatcher.apply_lora_text_encoder(text_encoder, loras),
-                ONNXModelPatcher.apply_ti(orig_tokenizer, text_encoder, ti_list) as (tokenizer, ti_manager),
-            ):
-                text_encoder.create_session()
-
-                # copy from
-                # https://github.com/huggingface/diffusers/blob/3ebbaf7c96801271f9e6c21400033b6aa5ffcf29/src/diffusers/pipelines/stable_diffusion/pipeline_onnx_stable_diffusion.py#L153
-                text_inputs = tokenizer(
-                    self.prompt,
-                    padding="max_length",
-                    max_length=tokenizer.model_max_length,
-                    truncation=True,
-                    return_tensors="np",
-                )
-                text_input_ids = text_inputs.input_ids
-                """
-                untruncated_ids = tokenizer(prompt, padding="max_length", return_tensors="np").input_ids
-
-                if not np.array_equal(text_input_ids, untruncated_ids):
-                    removed_text = self.tokenizer.batch_decode(
-                        untruncated_ids[:, self.tokenizer.model_max_length - 1 : -1]
-                    )
-                    logger.warning(
-                        "The following part of your input was truncated because CLIP can only handle sequences up to"
-                        f" {self.tokenizer.model_max_length} tokens: {removed_text}"
-                    )
-                """
-
-                prompt_embeds = text_encoder(input_ids=text_input_ids.astype(np.int32))[0]
-
-        conditioning_name = f"{context.graph_execution_state_id}_{self.id}_conditioning"
-
-        # TODO: hacky but works ;D maybe rename latents somehow?
-        context.services.latents.save(conditioning_name, (prompt_embeds, None))
-
-        return ConditioningOutput(
-            conditioning=ConditioningField(
-                conditioning_name=conditioning_name,
-            ),
-        )
-
-
-# Text to image
-@invocation(
-    "t2l_onnx",
-    title="ONNX Text to Latents",
-    tags=["latents", "inference", "txt2img", "onnx"],
-    category="latents",
-    version="1.0.0",
-)
-class ONNXTextToLatentsInvocation(BaseInvocation):
-    """Generates latents from conditionings."""
-
-    positive_conditioning: ConditioningField = InputField(
-        description=FieldDescriptions.positive_cond,
-        input=Input.Connection,
-    )
-    negative_conditioning: ConditioningField = InputField(
-        description=FieldDescriptions.negative_cond,
-        input=Input.Connection,
-    )
-    noise: LatentsField = InputField(
-        description=FieldDescriptions.noise,
-        input=Input.Connection,
-    )
-    steps: int = InputField(default=10, gt=0, description=FieldDescriptions.steps)
-    cfg_scale: Union[float, List[float]] = InputField(
-        default=7.5,
-        ge=1,
-        description=FieldDescriptions.cfg_scale,
-    )
-    scheduler: SAMPLER_NAME_VALUES = InputField(
-        default="euler", description=FieldDescriptions.scheduler, input=Input.Direct, ui_type=UIType.Scheduler
-    )
-    precision: PRECISION_VALUES = InputField(default="tensor(float16)", description=FieldDescriptions.precision)
-    unet: UNetField = InputField(
-        description=FieldDescriptions.unet,
-        input=Input.Connection,
-    )
-    control: Union[ControlField, list[ControlField]] = InputField(
-        default=None,
-        description=FieldDescriptions.control,
-    )
-    # seamless:   bool = InputField(default=False, description="Whether or not to generate an image that can tile without seams", )
-    # seamless_axes: str = InputField(default="", description="The axes to tile the image on, 'x' and/or 'y'")
-
-    @field_validator("cfg_scale")
-    def ge_one(cls, v):
-        """validate that all cfg_scale values are >= 1"""
-        if isinstance(v, list):
-            for i in v:
-                if i < 1:
-                    raise ValueError("cfg_scale must be greater than 1")
-        else:
-            if v < 1:
-                raise ValueError("cfg_scale must be greater than 1")
-        return v
-
-    # based on
-    # https://github.com/huggingface/diffusers/blob/3ebbaf7c96801271f9e6c21400033b6aa5ffcf29/src/diffusers/pipelines/stable_diffusion/pipeline_onnx_stable_diffusion.py#L375
-    def invoke(self, context: InvocationContext) -> LatentsOutput:
-        c, _ = context.services.latents.get(self.positive_conditioning.conditioning_name)
-        uc, _ = context.services.latents.get(self.negative_conditioning.conditioning_name)
-        graph_execution_state = context.services.graph_execution_manager.get(context.graph_execution_state_id)
-        source_node_id = graph_execution_state.prepared_source_mapping[self.id]
-        if isinstance(c, torch.Tensor):
-            c = c.cpu().numpy()
-        if isinstance(uc, torch.Tensor):
-            uc = uc.cpu().numpy()
-        device = torch.device(choose_torch_device())
-        prompt_embeds = np.concatenate([uc, c])
-
-        latents = context.services.latents.get(self.noise.latents_name)
-        if isinstance(latents, torch.Tensor):
-            latents = latents.cpu().numpy()
-
-        # TODO: better execution device handling
-        latents = latents.astype(ORT_TO_NP_TYPE[self.precision])
-
-        # get the initial random noise unless the user supplied it
-        do_classifier_free_guidance = True
-        # latents_dtype = prompt_embeds.dtype
-        # latents_shape = (batch_size * num_images_per_prompt, 4, height // 8, width // 8)
-        # if latents.shape != latents_shape:
-        #    raise ValueError(f"Unexpected latents shape, got {latents.shape}, expected {latents_shape}")
-
-        scheduler = get_scheduler(
-            context=context,
-            scheduler_info=self.unet.scheduler,
-            scheduler_name=self.scheduler,
-            seed=0,  # TODO: refactor this node
-        )
-
-        def torch2numpy(latent: torch.Tensor):
-            return latent.cpu().numpy()
-
-        def numpy2torch(latent, device):
-            return torch.from_numpy(latent).to(device)
-
-        def dispatch_progress(
-            self, context: InvocationContext, source_node_id: str, intermediate_state: PipelineIntermediateState
-        ) -> None:
-            stable_diffusion_step_callback(
-                context=context,
-                intermediate_state=intermediate_state,
-                node=self.model_dump(),
-                source_node_id=source_node_id,
-            )
-
-        scheduler.set_timesteps(self.steps)
-        latents = latents * np.float64(scheduler.init_noise_sigma)
-
-        extra_step_kwargs = {}
-        if "eta" in set(inspect.signature(scheduler.step).parameters.keys()):
-            extra_step_kwargs.update(
-                eta=0.0,
-            )
-
-        unet_info = context.services.model_manager.get_model(**self.unet.unet.model_dump())
-
-        with unet_info as unet:  # , ExitStack() as stack:
-            # loras = [(stack.enter_context(context.services.model_manager.get_model(**lora.dict(exclude={"weight"}))), lora.weight) for lora in self.unet.loras]
-            loras = [
-                (
-                    context.services.model_manager.get_model(**lora.model_dump(exclude={"weight"})).context.model,
-                    lora.weight,
-                )
-                for lora in self.unet.loras
-            ]
-
-            if loras:
-                unet.release_session()
-            with ONNXModelPatcher.apply_lora_unet(unet, loras):
-                # TODO:
-                _, _, h, w = latents.shape
-                unet.create_session(h, w)
-
-                timestep_dtype = next(
-                    (input.type for input in unet.session.get_inputs() if input.name == "timestep"), "tensor(float16)"
-                )
-                timestep_dtype = ORT_TO_NP_TYPE[timestep_dtype]
-                for i in tqdm(range(len(scheduler.timesteps))):
-                    t = scheduler.timesteps[i]
-                    # expand the latents if we are doing classifier free guidance
-                    latent_model_input = np.concatenate([latents] * 2) if do_classifier_free_guidance else latents
-                    latent_model_input = scheduler.scale_model_input(numpy2torch(latent_model_input, device), t)
-                    latent_model_input = latent_model_input.cpu().numpy()
-
-                    # predict the noise residual
-                    timestep = np.array([t], dtype=timestep_dtype)
-                    noise_pred = unet(sample=latent_model_input, timestep=timestep, encoder_hidden_states=prompt_embeds)
-                    noise_pred = noise_pred[0]
-
-                    # perform guidance
-                    if do_classifier_free_guidance:
-                        noise_pred_uncond, noise_pred_text = np.split(noise_pred, 2)
-                        noise_pred = noise_pred_uncond + self.cfg_scale * (noise_pred_text - noise_pred_uncond)
-
-                    # compute the previous noisy sample x_t -> x_t-1
-                    scheduler_output = scheduler.step(
-                        numpy2torch(noise_pred, device), t, numpy2torch(latents, device), **extra_step_kwargs
-                    )
-                    latents = torch2numpy(scheduler_output.prev_sample)
-
-                    state = PipelineIntermediateState(
-                        run_id="test", step=i, timestep=timestep, latents=scheduler_output.prev_sample
-                    )
-                    dispatch_progress(self, context=context, source_node_id=source_node_id, intermediate_state=state)
-
-                    # call the callback, if provided
-                    # if callback is not None and i % callback_steps == 0:
-                    #    callback(i, t, latents)
-
-        torch.cuda.empty_cache()
-
-        name = f"{context.graph_execution_state_id}__{self.id}"
-        context.services.latents.save(name, latents)
-        # return build_latents_output(latents_name=name, latents=torch.from_numpy(latents))
-
-
-# Latent to image
-@invocation(
-    "l2i_onnx",
-    title="ONNX Latents to Image",
-    tags=["latents", "image", "vae", "onnx"],
-    category="image",
-    version="1.2.0",
-)
-class ONNXLatentsToImageInvocation(BaseInvocation, WithMetadata):
-    """Generates an image from latents."""
-
-    latents: LatentsField = InputField(
-        description=FieldDescriptions.denoised_latents,
-        input=Input.Connection,
-    )
-    vae: VaeField = InputField(
-        description=FieldDescriptions.vae,
-        input=Input.Connection,
-    )
-    # tiled: bool = InputField(default=False, description="Decode latents by overlaping tiles(less memory consumption)")
-
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        latents = context.services.latents.get(self.latents.latents_name)
-
-        if self.vae.vae.submodel != SubModelType.VaeDecoder:
-            raise Exception(f"Expected vae_decoder, found: {self.vae.vae.model_type}")
-
-        vae_info = context.services.model_manager.get_model(
-            **self.vae.vae.model_dump(),
-        )
-
-        # clear memory as vae decode can request a lot
-        torch.cuda.empty_cache()
-
-        with vae_info as vae:
-            vae.create_session()
-
-            # copied from
-            # https://github.com/huggingface/diffusers/blob/3ebbaf7c96801271f9e6c21400033b6aa5ffcf29/src/diffusers/pipelines/stable_diffusion/pipeline_onnx_stable_diffusion.py#L427
-            latents = 1 / 0.18215 * latents
-            # image = self.vae_decoder(latent_sample=latents)[0]
-            # it seems likes there is a strange result for using half-precision vae decoder if batchsize>1
-            image = np.concatenate([vae(latent_sample=latents[i : i + 1])[0] for i in range(latents.shape[0])])
-
-            image = np.clip(image / 2 + 0.5, 0, 1)
-            image = image.transpose((0, 2, 3, 1))
-            image = VaeImageProcessor.numpy_to_pil(image)[0]
-
-        torch.cuda.empty_cache()
-
-        image_dto = context.services.images.create(
-            image=image,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-            metadata=self.metadata,
-            workflow=context.workflow,
-        )
-
-        return ImageOutput(
-            image=ImageField(image_name=image_dto.image_name),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
-
-
-@invocation_output("model_loader_output_onnx")
-class ONNXModelLoaderOutput(BaseInvocationOutput):
-    """Model loader output"""
-
-    unet: UNetField = OutputField(default=None, description=FieldDescriptions.unet, title="UNet")
-    clip: ClipField = OutputField(default=None, description=FieldDescriptions.clip, title="CLIP")
-    vae_decoder: VaeField = OutputField(default=None, description=FieldDescriptions.vae, title="VAE Decoder")
-    vae_encoder: VaeField = OutputField(default=None, description=FieldDescriptions.vae, title="VAE Encoder")
-
-
-class OnnxModelField(BaseModel):
-    """Onnx model field"""
-
-    model_name: str = Field(description="Name of the model")
-    base_model: BaseModelType = Field(description="Base model")
-    model_type: ModelType = Field(description="Model Type")
-
-    model_config = ConfigDict(protected_namespaces=())
-
-
-@invocation("onnx_model_loader", title="ONNX Main Model", tags=["onnx", "model"], category="model", version="1.0.0")
-class OnnxModelLoaderInvocation(BaseInvocation):
-    """Loads a main model, outputting its submodels."""
-
-    model: OnnxModelField = InputField(
-        description=FieldDescriptions.onnx_main_model, input=Input.Direct, ui_type=UIType.ONNXModel
-    )
-
-    def invoke(self, context: InvocationContext) -> ONNXModelLoaderOutput:
-        base_model = self.model.base_model
-        model_name = self.model.model_name
-        model_type = ModelType.ONNX
-
-        # TODO: not found exceptions
-        if not context.services.model_manager.model_exists(
-            model_name=model_name,
-            base_model=base_model,
-            model_type=model_type,
-        ):
-            raise Exception(f"Unknown {base_model} {model_type} model: {model_name}")
-
-        """
-        if not context.services.model_manager.model_exists(
-            model_name=self.model_name,
-            model_type=SDModelType.Diffusers,
-            submodel=SDModelType.Tokenizer,
-        ):
-            raise Exception(
-                f"Failed to find tokenizer submodel in {self.model_name}! Check if model corrupted"
-            )
-
-        if not context.services.model_manager.model_exists(
-            model_name=self.model_name,
-            model_type=SDModelType.Diffusers,
-            submodel=SDModelType.TextEncoder,
-        ):
-            raise Exception(
-                f"Failed to find text_encoder submodel in {self.model_name}! Check if model corrupted"
-            )
-
-        if not context.services.model_manager.model_exists(
-            model_name=self.model_name,
-            model_type=SDModelType.Diffusers,
-            submodel=SDModelType.UNet,
-        ):
-            raise Exception(
-                f"Failed to find unet submodel from {self.model_name}! Check if model corrupted"
-            )
-        """
-
-        return ONNXModelLoaderOutput(
-            unet=UNetField(
-                unet=ModelInfo(
-                    model_name=model_name,
-                    base_model=base_model,
-                    model_type=model_type,
-                    submodel=SubModelType.UNet,
-                ),
-                scheduler=ModelInfo(
-                    model_name=model_name,
-                    base_model=base_model,
-                    model_type=model_type,
-                    submodel=SubModelType.Scheduler,
-                ),
-                loras=[],
-            ),
-            clip=ClipField(
-                tokenizer=ModelInfo(
-                    model_name=model_name,
-                    base_model=base_model,
-                    model_type=model_type,
-                    submodel=SubModelType.Tokenizer,
-                ),
-                text_encoder=ModelInfo(
-                    model_name=model_name,
-                    base_model=base_model,
-                    model_type=model_type,
-                    submodel=SubModelType.TextEncoder,
-                ),
-                loras=[],
-                skipped_layers=0,
-            ),
-            vae_decoder=VaeField(
-                vae=ModelInfo(
-                    model_name=model_name,
-                    base_model=base_model,
-                    model_type=model_type,
-                    submodel=SubModelType.VaeDecoder,
-                ),
-            ),
-            vae_encoder=VaeField(
-                vae=ModelInfo(
-                    model_name=model_name,
-                    base_model=base_model,
-                    model_type=model_type,
-                    submodel=SubModelType.VaeEncoder,
-                ),
-            ),
-        )

From 0710fb3fb0486ab901465bb3a6a6ca07cb6e498e Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 7 Feb 2024 17:41:23 +1100
Subject: [PATCH 072/411] feat(nodes): replace latents service with tensors and
 conditioning services

- New generic class `PickleStorageBase`, implements the same API as `LatentsStorageBase`, use for storing non-serializable data via pickling
- Implementation `PickleStorageTorch` uses `torch.save` and `torch.load`, same as `LatentsStorageDisk`
- Add `tensors: PickleStorageBase[torch.Tensor]` to `InvocationServices`
- Add `conditioning: PickleStorageBase[ConditioningFieldData]` to `InvocationServices`
- Remove `latents` service and all `LatentsStorage` classes
- Update `InvocationContext` and all usage of old `latents` service to use the new services/context wrapper methods
---
 invokeai/app/api/dependencies.py              | 18 +++--
 invokeai/app/invocations/latent.py            | 36 +++++-----
 invokeai/app/invocations/noise.py             |  2 +-
 invokeai/app/invocations/primitives.py        |  6 +-
 .../invocation_cache_memory.py                |  3 +-
 invokeai/app/services/invocation_services.py  | 12 +++-
 .../app/services/latents_storage/__init__.py  |  0
 .../latents_storage/latents_storage_disk.py   | 58 ----------------
 .../latents_storage_forward_cache.py          | 68 -------------------
 .../pickle_storage_base.py}                   | 18 ++---
 .../pickle_storage_forward_cache.py           | 58 ++++++++++++++++
 .../pickle_storage/pickle_storage_torch.py    | 62 +++++++++++++++++
 .../app/services/shared/invocation_context.py | 49 ++++++-------
 13 files changed, 197 insertions(+), 193 deletions(-)
 delete mode 100644 invokeai/app/services/latents_storage/__init__.py
 delete mode 100644 invokeai/app/services/latents_storage/latents_storage_disk.py
 delete mode 100644 invokeai/app/services/latents_storage/latents_storage_forward_cache.py
 rename invokeai/app/services/{latents_storage/latents_storage_base.py => pickle_storage/pickle_storage_base.py} (68%)
 create mode 100644 invokeai/app/services/pickle_storage/pickle_storage_forward_cache.py
 create mode 100644 invokeai/app/services/pickle_storage/pickle_storage_torch.py

diff --git a/invokeai/app/api/dependencies.py b/invokeai/app/api/dependencies.py
index c8309e1729..6bb0915cb6 100644
--- a/invokeai/app/api/dependencies.py
+++ b/invokeai/app/api/dependencies.py
@@ -2,9 +2,14 @@
 
 from logging import Logger
 
+import torch
+
 from invokeai.app.services.item_storage.item_storage_memory import ItemStorageMemory
+from invokeai.app.services.pickle_storage.pickle_storage_forward_cache import PickleStorageForwardCache
+from invokeai.app.services.pickle_storage.pickle_storage_torch import PickleStorageTorch
 from invokeai.app.services.shared.sqlite.sqlite_util import init_db
 from invokeai.backend.model_manager.metadata import ModelMetadataStore
+from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ConditioningFieldData
 from invokeai.backend.util.logging import InvokeAILogger
 from invokeai.version.invokeai_version import __version__
 
@@ -23,8 +28,6 @@ from ..services.invocation_queue.invocation_queue_memory import MemoryInvocation
 from ..services.invocation_services import InvocationServices
 from ..services.invocation_stats.invocation_stats_default import InvocationStatsService
 from ..services.invoker import Invoker
-from ..services.latents_storage.latents_storage_disk import DiskLatentsStorage
-from ..services.latents_storage.latents_storage_forward_cache import ForwardCacheLatentsStorage
 from ..services.model_install import ModelInstallService
 from ..services.model_manager.model_manager_default import ModelManagerService
 from ..services.model_records import ModelRecordServiceSQL
@@ -68,6 +71,9 @@ class ApiDependencies:
         logger.debug(f"Internet connectivity is {config.internet_available}")
 
         output_folder = config.output_path
+        if output_folder is None:
+            raise ValueError("Output folder is not set")
+
         image_files = DiskImageFileStorage(f"{output_folder}/images")
 
         db = init_db(config=config, logger=logger, image_files=image_files)
@@ -84,7 +90,10 @@ class ApiDependencies:
         image_records = SqliteImageRecordStorage(db=db)
         images = ImageService()
         invocation_cache = MemoryInvocationCache(max_cache_size=config.node_cache_size)
-        latents = ForwardCacheLatentsStorage(DiskLatentsStorage(f"{output_folder}/latents"))
+        tensors = PickleStorageForwardCache(PickleStorageTorch[torch.Tensor](output_folder / "tensors", "tensor"))
+        conditioning = PickleStorageForwardCache(
+            PickleStorageTorch[ConditioningFieldData](output_folder / "conditioning", "conditioning")
+        )
         model_manager = ModelManagerService(config, logger)
         model_record_service = ModelRecordServiceSQL(db=db)
         download_queue_service = DownloadQueueService(event_bus=events)
@@ -117,7 +126,6 @@ class ApiDependencies:
             image_records=image_records,
             images=images,
             invocation_cache=invocation_cache,
-            latents=latents,
             logger=logger,
             model_manager=model_manager,
             model_records=model_record_service,
@@ -131,6 +139,8 @@ class ApiDependencies:
             session_queue=session_queue,
             urls=urls,
             workflow_records=workflow_records,
+            tensors=tensors,
+            conditioning=conditioning,
         )
 
         ApiDependencies.invoker = Invoker(services)
diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py
index 5449ec9af7..94440d3e2a 100644
--- a/invokeai/app/invocations/latent.py
+++ b/invokeai/app/invocations/latent.py
@@ -163,11 +163,11 @@ class CreateDenoiseMaskInvocation(BaseInvocation):
             # TODO:
             masked_latents = ImageToLatentsInvocation.vae_encode(vae_info, self.fp32, self.tiled, masked_image.clone())
 
-            masked_latents_name = context.latents.save(tensor=masked_latents)
+            masked_latents_name = context.tensors.save(tensor=masked_latents)
         else:
             masked_latents_name = None
 
-        mask_name = context.latents.save(tensor=mask)
+        mask_name = context.tensors.save(tensor=mask)
 
         return DenoiseMaskOutput.build(
             mask_name=mask_name,
@@ -621,10 +621,10 @@ class DenoiseLatentsInvocation(BaseInvocation):
         if self.denoise_mask is None:
             return None, None
 
-        mask = context.latents.get(self.denoise_mask.mask_name)
+        mask = context.tensors.get(self.denoise_mask.mask_name)
         mask = tv_resize(mask, latents.shape[-2:], T.InterpolationMode.BILINEAR, antialias=False)
         if self.denoise_mask.masked_latents_name is not None:
-            masked_latents = context.latents.get(self.denoise_mask.masked_latents_name)
+            masked_latents = context.tensors.get(self.denoise_mask.masked_latents_name)
         else:
             masked_latents = None
 
@@ -636,11 +636,11 @@ class DenoiseLatentsInvocation(BaseInvocation):
             seed = None
             noise = None
             if self.noise is not None:
-                noise = context.latents.get(self.noise.latents_name)
+                noise = context.tensors.get(self.noise.latents_name)
                 seed = self.noise.seed
 
             if self.latents is not None:
-                latents = context.latents.get(self.latents.latents_name)
+                latents = context.tensors.get(self.latents.latents_name)
                 if seed is None:
                     seed = self.latents.seed
 
@@ -752,7 +752,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
             if choose_torch_device() == torch.device("mps"):
                 mps.empty_cache()
 
-            name = context.latents.save(tensor=result_latents)
+            name = context.tensors.save(tensor=result_latents)
         return LatentsOutput.build(latents_name=name, latents=result_latents, seed=seed)
 
 
@@ -779,7 +779,7 @@ class LatentsToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
 
     @torch.no_grad()
     def invoke(self, context: InvocationContext) -> ImageOutput:
-        latents = context.latents.get(self.latents.latents_name)
+        latents = context.tensors.get(self.latents.latents_name)
 
         vae_info = context.models.load(**self.vae.vae.model_dump())
 
@@ -870,7 +870,7 @@ class ResizeLatentsInvocation(BaseInvocation):
     antialias: bool = InputField(default=False, description=FieldDescriptions.torch_antialias)
 
     def invoke(self, context: InvocationContext) -> LatentsOutput:
-        latents = context.latents.get(self.latents.latents_name)
+        latents = context.tensors.get(self.latents.latents_name)
 
         # TODO:
         device = choose_torch_device()
@@ -888,7 +888,7 @@ class ResizeLatentsInvocation(BaseInvocation):
         if device == torch.device("mps"):
             mps.empty_cache()
 
-        name = context.latents.save(tensor=resized_latents)
+        name = context.tensors.save(tensor=resized_latents)
         return LatentsOutput.build(latents_name=name, latents=resized_latents, seed=self.latents.seed)
 
 
@@ -911,7 +911,7 @@ class ScaleLatentsInvocation(BaseInvocation):
     antialias: bool = InputField(default=False, description=FieldDescriptions.torch_antialias)
 
     def invoke(self, context: InvocationContext) -> LatentsOutput:
-        latents = context.latents.get(self.latents.latents_name)
+        latents = context.tensors.get(self.latents.latents_name)
 
         # TODO:
         device = choose_torch_device()
@@ -930,7 +930,7 @@ class ScaleLatentsInvocation(BaseInvocation):
         if device == torch.device("mps"):
             mps.empty_cache()
 
-        name = context.latents.save(tensor=resized_latents)
+        name = context.tensors.save(tensor=resized_latents)
         return LatentsOutput.build(latents_name=name, latents=resized_latents, seed=self.latents.seed)
 
 
@@ -1011,7 +1011,7 @@ class ImageToLatentsInvocation(BaseInvocation):
         latents = self.vae_encode(vae_info, self.fp32, self.tiled, image_tensor)
 
         latents = latents.to("cpu")
-        name = context.latents.save(tensor=latents)
+        name = context.tensors.save(tensor=latents)
         return LatentsOutput.build(latents_name=name, latents=latents, seed=None)
 
     @singledispatchmethod
@@ -1048,8 +1048,8 @@ class BlendLatentsInvocation(BaseInvocation):
     alpha: float = InputField(default=0.5, description=FieldDescriptions.blend_alpha)
 
     def invoke(self, context: InvocationContext) -> LatentsOutput:
-        latents_a = context.latents.get(self.latents_a.latents_name)
-        latents_b = context.latents.get(self.latents_b.latents_name)
+        latents_a = context.tensors.get(self.latents_a.latents_name)
+        latents_b = context.tensors.get(self.latents_b.latents_name)
 
         if latents_a.shape != latents_b.shape:
             raise Exception("Latents to blend must be the same size.")
@@ -1103,7 +1103,7 @@ class BlendLatentsInvocation(BaseInvocation):
         if device == torch.device("mps"):
             mps.empty_cache()
 
-        name = context.latents.save(tensor=blended_latents)
+        name = context.tensors.save(tensor=blended_latents)
         return LatentsOutput.build(latents_name=name, latents=blended_latents)
 
 
@@ -1149,7 +1149,7 @@ class CropLatentsCoreInvocation(BaseInvocation):
     )
 
     def invoke(self, context: InvocationContext) -> LatentsOutput:
-        latents = context.latents.get(self.latents.latents_name)
+        latents = context.tensors.get(self.latents.latents_name)
 
         x1 = self.x // LATENT_SCALE_FACTOR
         y1 = self.y // LATENT_SCALE_FACTOR
@@ -1158,7 +1158,7 @@ class CropLatentsCoreInvocation(BaseInvocation):
 
         cropped_latents = latents[..., y1:y2, x1:x2]
 
-        name = context.latents.save(tensor=cropped_latents)
+        name = context.tensors.save(tensor=cropped_latents)
 
         return LatentsOutput.build(latents_name=name, latents=cropped_latents)
 
diff --git a/invokeai/app/invocations/noise.py b/invokeai/app/invocations/noise.py
index 78f13cc52d..74b3d6e4cb 100644
--- a/invokeai/app/invocations/noise.py
+++ b/invokeai/app/invocations/noise.py
@@ -121,5 +121,5 @@ class NoiseInvocation(BaseInvocation):
             seed=self.seed,
             use_cpu=self.use_cpu,
         )
-        name = context.latents.save(tensor=noise)
+        name = context.tensors.save(tensor=noise)
         return NoiseOutput.build(latents_name=name, latents=noise, seed=self.seed)
diff --git a/invokeai/app/invocations/primitives.py b/invokeai/app/invocations/primitives.py
index a77939943a..082d5432cc 100644
--- a/invokeai/app/invocations/primitives.py
+++ b/invokeai/app/invocations/primitives.py
@@ -313,9 +313,7 @@ class DenoiseMaskOutput(BaseInvocationOutput):
 class LatentsOutput(BaseInvocationOutput):
     """Base class for nodes that output a single latents tensor"""
 
-    latents: LatentsField = OutputField(
-        description=FieldDescriptions.latents,
-    )
+    latents: LatentsField = OutputField(description=FieldDescriptions.latents)
     width: int = OutputField(description=FieldDescriptions.width)
     height: int = OutputField(description=FieldDescriptions.height)
 
@@ -346,7 +344,7 @@ class LatentsInvocation(BaseInvocation):
     latents: LatentsField = InputField(description="The latents tensor", input=Input.Connection)
 
     def invoke(self, context: InvocationContext) -> LatentsOutput:
-        latents = context.latents.get(self.latents.latents_name)
+        latents = context.tensors.get(self.latents.latents_name)
 
         return LatentsOutput.build(self.latents.latents_name, latents)
 
diff --git a/invokeai/app/services/invocation_cache/invocation_cache_memory.py b/invokeai/app/services/invocation_cache/invocation_cache_memory.py
index 4a503b3c6b..c700f81186 100644
--- a/invokeai/app/services/invocation_cache/invocation_cache_memory.py
+++ b/invokeai/app/services/invocation_cache/invocation_cache_memory.py
@@ -37,7 +37,8 @@ class MemoryInvocationCache(InvocationCacheBase):
         if self._max_cache_size == 0:
             return
         self._invoker.services.images.on_deleted(self._delete_by_match)
-        self._invoker.services.latents.on_deleted(self._delete_by_match)
+        self._invoker.services.tensors.on_deleted(self._delete_by_match)
+        self._invoker.services.conditioning.on_deleted(self._delete_by_match)
 
     def get(self, key: Union[int, str]) -> Optional[BaseInvocationOutput]:
         with self._lock:
diff --git a/invokeai/app/services/invocation_services.py b/invokeai/app/services/invocation_services.py
index 51bfd5d77a..81885781ac 100644
--- a/invokeai/app/services/invocation_services.py
+++ b/invokeai/app/services/invocation_services.py
@@ -6,6 +6,10 @@ from typing import TYPE_CHECKING
 if TYPE_CHECKING:
     from logging import Logger
 
+    import torch
+
+    from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ConditioningFieldData
+
     from .board_image_records.board_image_records_base import BoardImageRecordStorageBase
     from .board_images.board_images_base import BoardImagesServiceABC
     from .board_records.board_records_base import BoardRecordStorageBase
@@ -21,11 +25,11 @@ if TYPE_CHECKING:
     from .invocation_queue.invocation_queue_base import InvocationQueueABC
     from .invocation_stats.invocation_stats_base import InvocationStatsServiceBase
     from .item_storage.item_storage_base import ItemStorageABC
-    from .latents_storage.latents_storage_base import LatentsStorageBase
     from .model_install import ModelInstallServiceBase
     from .model_manager.model_manager_base import ModelManagerServiceBase
     from .model_records import ModelRecordServiceBase
     from .names.names_base import NameServiceBase
+    from .pickle_storage.pickle_storage_base import PickleStorageBase
     from .session_processor.session_processor_base import SessionProcessorBase
     from .session_queue.session_queue_base import SessionQueueBase
     from .shared.graph import GraphExecutionState
@@ -48,7 +52,6 @@ class InvocationServices:
         images: "ImageServiceABC",
         image_files: "ImageFileStorageBase",
         image_records: "ImageRecordStorageBase",
-        latents: "LatentsStorageBase",
         logger: "Logger",
         model_manager: "ModelManagerServiceBase",
         model_records: "ModelRecordServiceBase",
@@ -63,6 +66,8 @@ class InvocationServices:
         names: "NameServiceBase",
         urls: "UrlServiceBase",
         workflow_records: "WorkflowRecordsStorageBase",
+        tensors: "PickleStorageBase[torch.Tensor]",
+        conditioning: "PickleStorageBase[ConditioningFieldData]",
     ):
         self.board_images = board_images
         self.board_image_records = board_image_records
@@ -74,7 +79,6 @@ class InvocationServices:
         self.images = images
         self.image_files = image_files
         self.image_records = image_records
-        self.latents = latents
         self.logger = logger
         self.model_manager = model_manager
         self.model_records = model_records
@@ -89,3 +93,5 @@ class InvocationServices:
         self.names = names
         self.urls = urls
         self.workflow_records = workflow_records
+        self.tensors = tensors
+        self.conditioning = conditioning
diff --git a/invokeai/app/services/latents_storage/__init__.py b/invokeai/app/services/latents_storage/__init__.py
deleted file mode 100644
index e69de29bb2..0000000000
diff --git a/invokeai/app/services/latents_storage/latents_storage_disk.py b/invokeai/app/services/latents_storage/latents_storage_disk.py
deleted file mode 100644
index 9192b9147f..0000000000
--- a/invokeai/app/services/latents_storage/latents_storage_disk.py
+++ /dev/null
@@ -1,58 +0,0 @@
-# Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
-
-from pathlib import Path
-from typing import Union
-
-import torch
-
-from invokeai.app.services.invoker import Invoker
-
-from .latents_storage_base import LatentsStorageBase
-
-
-class DiskLatentsStorage(LatentsStorageBase):
-    """Stores latents in a folder on disk without caching"""
-
-    __output_folder: Path
-
-    def __init__(self, output_folder: Union[str, Path]):
-        self.__output_folder = output_folder if isinstance(output_folder, Path) else Path(output_folder)
-        self.__output_folder.mkdir(parents=True, exist_ok=True)
-
-    def start(self, invoker: Invoker) -> None:
-        self._invoker = invoker
-        self._delete_all_latents()
-
-    def get(self, name: str) -> torch.Tensor:
-        latent_path = self.get_path(name)
-        return torch.load(latent_path)
-
-    def save(self, name: str, data: torch.Tensor) -> None:
-        self.__output_folder.mkdir(parents=True, exist_ok=True)
-        latent_path = self.get_path(name)
-        torch.save(data, latent_path)
-
-    def delete(self, name: str) -> None:
-        latent_path = self.get_path(name)
-        latent_path.unlink()
-
-    def get_path(self, name: str) -> Path:
-        return self.__output_folder / name
-
-    def _delete_all_latents(self) -> None:
-        """
-        Deletes all latents from disk.
-        Must be called after we have access to `self._invoker` (e.g. in `start()`).
-        """
-        deleted_latents_count = 0
-        freed_space = 0
-        for latents_file in Path(self.__output_folder).glob("*"):
-            if latents_file.is_file():
-                freed_space += latents_file.stat().st_size
-                deleted_latents_count += 1
-                latents_file.unlink()
-        if deleted_latents_count > 0:
-            freed_space_in_mb = round(freed_space / 1024 / 1024, 2)
-            self._invoker.services.logger.info(
-                f"Deleted {deleted_latents_count} latents files (freed {freed_space_in_mb}MB)"
-            )
diff --git a/invokeai/app/services/latents_storage/latents_storage_forward_cache.py b/invokeai/app/services/latents_storage/latents_storage_forward_cache.py
deleted file mode 100644
index 6232b76a27..0000000000
--- a/invokeai/app/services/latents_storage/latents_storage_forward_cache.py
+++ /dev/null
@@ -1,68 +0,0 @@
-# Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
-
-from queue import Queue
-from typing import Dict, Optional
-
-import torch
-
-from invokeai.app.services.invoker import Invoker
-
-from .latents_storage_base import LatentsStorageBase
-
-
-class ForwardCacheLatentsStorage(LatentsStorageBase):
-    """Caches the latest N latents in memory, writing-thorugh to and reading from underlying storage"""
-
-    __cache: Dict[str, torch.Tensor]
-    __cache_ids: Queue
-    __max_cache_size: int
-    __underlying_storage: LatentsStorageBase
-
-    def __init__(self, underlying_storage: LatentsStorageBase, max_cache_size: int = 20):
-        super().__init__()
-        self.__underlying_storage = underlying_storage
-        self.__cache = {}
-        self.__cache_ids = Queue()
-        self.__max_cache_size = max_cache_size
-
-    def start(self, invoker: Invoker) -> None:
-        self._invoker = invoker
-        start_op = getattr(self.__underlying_storage, "start", None)
-        if callable(start_op):
-            start_op(invoker)
-
-    def stop(self, invoker: Invoker) -> None:
-        self._invoker = invoker
-        stop_op = getattr(self.__underlying_storage, "stop", None)
-        if callable(stop_op):
-            stop_op(invoker)
-
-    def get(self, name: str) -> torch.Tensor:
-        cache_item = self.__get_cache(name)
-        if cache_item is not None:
-            return cache_item
-
-        latent = self.__underlying_storage.get(name)
-        self.__set_cache(name, latent)
-        return latent
-
-    def save(self, name: str, data: torch.Tensor) -> None:
-        self.__underlying_storage.save(name, data)
-        self.__set_cache(name, data)
-        self._on_changed(data)
-
-    def delete(self, name: str) -> None:
-        self.__underlying_storage.delete(name)
-        if name in self.__cache:
-            del self.__cache[name]
-        self._on_deleted(name)
-
-    def __get_cache(self, name: str) -> Optional[torch.Tensor]:
-        return None if name not in self.__cache else self.__cache[name]
-
-    def __set_cache(self, name: str, data: torch.Tensor):
-        if name not in self.__cache:
-            self.__cache[name] = data
-            self.__cache_ids.put(name)
-            if self.__cache_ids.qsize() > self.__max_cache_size:
-                self.__cache.pop(self.__cache_ids.get())
diff --git a/invokeai/app/services/latents_storage/latents_storage_base.py b/invokeai/app/services/pickle_storage/pickle_storage_base.py
similarity index 68%
rename from invokeai/app/services/latents_storage/latents_storage_base.py
rename to invokeai/app/services/pickle_storage/pickle_storage_base.py
index 9fa42b0ae6..558b97c0f1 100644
--- a/invokeai/app/services/latents_storage/latents_storage_base.py
+++ b/invokeai/app/services/pickle_storage/pickle_storage_base.py
@@ -1,15 +1,15 @@
 # Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
 
 from abc import ABC, abstractmethod
-from typing import Callable
+from typing import Callable, Generic, TypeVar
 
-import torch
+T = TypeVar("T")
 
 
-class LatentsStorageBase(ABC):
-    """Responsible for storing and retrieving latents."""
+class PickleStorageBase(ABC, Generic[T]):
+    """Responsible for storing and retrieving non-serializable data using a pickler."""
 
-    _on_changed_callbacks: list[Callable[[torch.Tensor], None]]
+    _on_changed_callbacks: list[Callable[[T], None]]
     _on_deleted_callbacks: list[Callable[[str], None]]
 
     def __init__(self) -> None:
@@ -17,18 +17,18 @@ class LatentsStorageBase(ABC):
         self._on_deleted_callbacks = []
 
     @abstractmethod
-    def get(self, name: str) -> torch.Tensor:
+    def get(self, name: str) -> T:
         pass
 
     @abstractmethod
-    def save(self, name: str, data: torch.Tensor) -> None:
+    def save(self, name: str, data: T) -> None:
         pass
 
     @abstractmethod
     def delete(self, name: str) -> None:
         pass
 
-    def on_changed(self, on_changed: Callable[[torch.Tensor], None]) -> None:
+    def on_changed(self, on_changed: Callable[[T], None]) -> None:
         """Register a callback for when an item is changed"""
         self._on_changed_callbacks.append(on_changed)
 
@@ -36,7 +36,7 @@ class LatentsStorageBase(ABC):
         """Register a callback for when an item is deleted"""
         self._on_deleted_callbacks.append(on_deleted)
 
-    def _on_changed(self, item: torch.Tensor) -> None:
+    def _on_changed(self, item: T) -> None:
         for callback in self._on_changed_callbacks:
             callback(item)
 
diff --git a/invokeai/app/services/pickle_storage/pickle_storage_forward_cache.py b/invokeai/app/services/pickle_storage/pickle_storage_forward_cache.py
new file mode 100644
index 0000000000..3002d9e045
--- /dev/null
+++ b/invokeai/app/services/pickle_storage/pickle_storage_forward_cache.py
@@ -0,0 +1,58 @@
+from queue import Queue
+from typing import Optional, TypeVar
+
+from invokeai.app.services.invoker import Invoker
+from invokeai.app.services.pickle_storage.pickle_storage_base import PickleStorageBase
+
+T = TypeVar("T")
+
+
+class PickleStorageForwardCache(PickleStorageBase[T]):
+    def __init__(self, underlying_storage: PickleStorageBase[T], max_cache_size: int = 20):
+        super().__init__()
+        self._underlying_storage = underlying_storage
+        self._cache: dict[str, T] = {}
+        self._cache_ids = Queue[str]()
+        self._max_cache_size = max_cache_size
+
+    def start(self, invoker: Invoker) -> None:
+        self._invoker = invoker
+        start_op = getattr(self._underlying_storage, "start", None)
+        if callable(start_op):
+            start_op(invoker)
+
+    def stop(self, invoker: Invoker) -> None:
+        self._invoker = invoker
+        stop_op = getattr(self._underlying_storage, "stop", None)
+        if callable(stop_op):
+            stop_op(invoker)
+
+    def get(self, name: str) -> T:
+        cache_item = self._get_cache(name)
+        if cache_item is not None:
+            return cache_item
+
+        latent = self._underlying_storage.get(name)
+        self._set_cache(name, latent)
+        return latent
+
+    def save(self, name: str, data: T) -> None:
+        self._underlying_storage.save(name, data)
+        self._set_cache(name, data)
+        self._on_changed(data)
+
+    def delete(self, name: str) -> None:
+        self._underlying_storage.delete(name)
+        if name in self._cache:
+            del self._cache[name]
+        self._on_deleted(name)
+
+    def _get_cache(self, name: str) -> Optional[T]:
+        return None if name not in self._cache else self._cache[name]
+
+    def _set_cache(self, name: str, data: T):
+        if name not in self._cache:
+            self._cache[name] = data
+            self._cache_ids.put(name)
+            if self._cache_ids.qsize() > self._max_cache_size:
+                self._cache.pop(self._cache_ids.get())
diff --git a/invokeai/app/services/pickle_storage/pickle_storage_torch.py b/invokeai/app/services/pickle_storage/pickle_storage_torch.py
new file mode 100644
index 0000000000..0b3c9af7a3
--- /dev/null
+++ b/invokeai/app/services/pickle_storage/pickle_storage_torch.py
@@ -0,0 +1,62 @@
+# Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
+
+from pathlib import Path
+from typing import TypeVar
+
+import torch
+
+from invokeai.app.services.invoker import Invoker
+from invokeai.app.services.pickle_storage.pickle_storage_base import PickleStorageBase
+
+T = TypeVar("T")
+
+
+class PickleStorageTorch(PickleStorageBase[T]):
+    """Responsible for storing and retrieving non-serializable data using `torch.save` and `torch.load`."""
+
+    def __init__(self, output_folder: Path, item_type_name: "str"):
+        self._output_folder = output_folder
+        self._output_folder.mkdir(parents=True, exist_ok=True)
+        self._item_type_name = item_type_name
+
+    def start(self, invoker: Invoker) -> None:
+        self._invoker = invoker
+        self._delete_all_items()
+
+    def get(self, name: str) -> T:
+        latent_path = self._get_path(name)
+        return torch.load(latent_path)
+
+    def save(self, name: str, data: T) -> None:
+        self._output_folder.mkdir(parents=True, exist_ok=True)
+        latent_path = self._get_path(name)
+        torch.save(data, latent_path)
+
+    def delete(self, name: str) -> None:
+        latent_path = self._get_path(name)
+        latent_path.unlink()
+
+    def _get_path(self, name: str) -> Path:
+        return self._output_folder / name
+
+    def _delete_all_items(self) -> None:
+        """
+        Deletes all pickled items from disk.
+        Must be called after we have access to `self._invoker` (e.g. in `start()`).
+        """
+
+        if not self._invoker:
+            raise ValueError("Invoker is not set. Must call `start()` first.")
+
+        deleted_latents_count = 0
+        freed_space = 0
+        for latents_file in Path(self._output_folder).glob("*"):
+            if latents_file.is_file():
+                freed_space += latents_file.stat().st_size
+                deleted_latents_count += 1
+                latents_file.unlink()
+        if deleted_latents_count > 0:
+            freed_space_in_mb = round(freed_space / 1024 / 1024, 2)
+            self._invoker.services.logger.info(
+                f"Deleted {deleted_latents_count} {self._item_type_name} files (freed {freed_space_in_mb}MB)"
+            )
diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index 97a62246fb..6756b1f5c6 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -216,48 +216,46 @@ class ImagesInterface(InvocationContextInterface):
         return self._services.images.get_dto(image_name)
 
 
-class LatentsInterface(InvocationContextInterface):
+class TensorsInterface(InvocationContextInterface):
     def save(self, tensor: Tensor) -> str:
         """
-        Saves a latents tensor, returning its name.
+        Saves a tensor, returning its name.
 
-        :param tensor: The latents tensor to save.
+        :param tensor: The tensor to save.
         """
 
         # Previously, we added a suffix indicating the type of Tensor we were saving, e.g.
         # "mask", "noise", "masked_latents", etc.
         #
         # Retaining that capability in this wrapper would require either many different methods
-        # to save latents, or extra args for this method. Instead of complicating the API, we
-        # will use the same naming scheme for all latents.
+        # to save tensors, or extra args for this method. Instead of complicating the API, we
+        # will use the same naming scheme for all tensors.
         #
         # This has a very minor impact as we don't use them after a session completes.
 
-        # Previously, invocations chose the name for their latents. This is a bit risky, so we
+        # Previously, invocations chose the name for their tensors. This is a bit risky, so we
         # will generate a name for them instead. We use a uuid to ensure the name is unique.
         #
-        # Because the name of the latents file will includes the session and invocation IDs,
+        # Because the name of the tensors file will includes the session and invocation IDs,
         # we don't need to worry about collisions. A truncated UUIDv4 is fine.
 
         name = f"{self._context_data.session_id}__{self._context_data.invocation.id}__{uuid_string()[:7]}"
-        self._services.latents.save(
+        self._services.tensors.save(
             name=name,
             data=tensor,
         )
         return name
 
-    def get(self, latents_name: str) -> Tensor:
+    def get(self, tensor_name: str) -> Tensor:
         """
-        Gets a latents tensor by name.
+        Gets a tensor by name.
 
-        :param latents_name: The name of the latents tensor to get.
+        :param tensor_name: The name of the tensor to get.
         """
-        return self._services.latents.get(latents_name)
+        return self._services.tensors.get(tensor_name)
 
 
 class ConditioningInterface(InvocationContextInterface):
-    # TODO(psyche): We are (ab)using the latents storage service as a general pickle storage
-    # service, but it is typed to work with Tensors only. We have to fudge the types here.
     def save(self, conditioning_data: ConditioningFieldData) -> str:
         """
         Saves a conditioning data object, returning its name.
@@ -265,15 +263,12 @@ class ConditioningInterface(InvocationContextInterface):
         :param conditioning_context_data: The conditioning data to save.
         """
 
-        # Conditioning data is *not* a Tensor, so we will suffix it to indicate this.
-        #
-        # See comment for `LatentsInterface.save` for more info about this method (it's very
-        # similar).
+        # See comment in TensorsInterface.save for why we generate the name here.
 
-        name = f"{self._context_data.session_id}__{self._context_data.invocation.id}__{uuid_string()[:7]}__conditioning"
-        self._services.latents.save(
+        name = f"{self._context_data.session_id}__{self._context_data.invocation.id}__{uuid_string()[:7]}"
+        self._services.conditioning.save(
             name=name,
-            data=conditioning_data,  # type: ignore [arg-type]
+            data=conditioning_data,
         )
         return name
 
@@ -284,7 +279,7 @@ class ConditioningInterface(InvocationContextInterface):
         :param conditioning_name: The name of the conditioning data to get.
         """
 
-        return self._services.latents.get(conditioning_name)  # type: ignore [return-value]
+        return self._services.conditioning.get(conditioning_name)
 
 
 class ModelsInterface(InvocationContextInterface):
@@ -400,7 +395,7 @@ class InvocationContext:
     def __init__(
         self,
         images: ImagesInterface,
-        latents: LatentsInterface,
+        tensors: TensorsInterface,
         conditioning: ConditioningInterface,
         models: ModelsInterface,
         logger: LoggerInterface,
@@ -412,8 +407,8 @@ class InvocationContext:
     ) -> None:
         self.images = images
         """Provides methods to save, get and update images and their metadata."""
-        self.latents = latents
-        """Provides methods to save and get latents tensors, including image, noise, masks, and masked images."""
+        self.tensors = tensors
+        """Provides methods to save and get tensors, including image, noise, masks, and masked images."""
         self.conditioning = conditioning
         """Provides methods to save and get conditioning data."""
         self.models = models
@@ -532,7 +527,7 @@ def build_invocation_context(
 
     logger = LoggerInterface(services=services, context_data=context_data)
     images = ImagesInterface(services=services, context_data=context_data)
-    latents = LatentsInterface(services=services, context_data=context_data)
+    tensors = TensorsInterface(services=services, context_data=context_data)
     models = ModelsInterface(services=services, context_data=context_data)
     config = ConfigInterface(services=services, context_data=context_data)
     util = UtilInterface(services=services, context_data=context_data)
@@ -543,7 +538,7 @@ def build_invocation_context(
         images=images,
         logger=logger,
         config=config,
-        latents=latents,
+        tensors=tensors,
         models=models,
         context_data=context_data,
         util=util,

From 5dd158a2d404adc3fade0a9916a18eebcc37ff6e Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 7 Feb 2024 18:17:23 +1100
Subject: [PATCH 073/411] tidy(nodes): do not refer to files as latents in
 `PickleStorageTorch`

---
 .../pickle_storage/pickle_storage_torch.py       | 16 ++++++++--------
 1 file changed, 8 insertions(+), 8 deletions(-)

diff --git a/invokeai/app/services/pickle_storage/pickle_storage_torch.py b/invokeai/app/services/pickle_storage/pickle_storage_torch.py
index 0b3c9af7a3..7b18dc0625 100644
--- a/invokeai/app/services/pickle_storage/pickle_storage_torch.py
+++ b/invokeai/app/services/pickle_storage/pickle_storage_torch.py
@@ -48,15 +48,15 @@ class PickleStorageTorch(PickleStorageBase[T]):
         if not self._invoker:
             raise ValueError("Invoker is not set. Must call `start()` first.")
 
-        deleted_latents_count = 0
+        deleted_count = 0
         freed_space = 0
-        for latents_file in Path(self._output_folder).glob("*"):
-            if latents_file.is_file():
-                freed_space += latents_file.stat().st_size
-                deleted_latents_count += 1
-                latents_file.unlink()
-        if deleted_latents_count > 0:
+        for file in Path(self._output_folder).glob("*"):
+            if file.is_file():
+                freed_space += file.stat().st_size
+                deleted_count += 1
+                file.unlink()
+        if deleted_count > 0:
             freed_space_in_mb = round(freed_space / 1024 / 1024, 2)
             self._invoker.services.logger.info(
-                f"Deleted {deleted_latents_count} {self._item_type_name} files (freed {freed_space_in_mb}MB)"
+                f"Deleted {deleted_count} {self._item_type_name} files (freed {freed_space_in_mb}MB)"
             )

From de63e888d6df02b8ac21c0925abb59a2b14e7194 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 7 Feb 2024 18:35:58 +1100
Subject: [PATCH 074/411] fix(nodes): add super init to `PickleStorageTorch`

---
 invokeai/app/services/pickle_storage/pickle_storage_torch.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/invokeai/app/services/pickle_storage/pickle_storage_torch.py b/invokeai/app/services/pickle_storage/pickle_storage_torch.py
index 7b18dc0625..de411bbf47 100644
--- a/invokeai/app/services/pickle_storage/pickle_storage_torch.py
+++ b/invokeai/app/services/pickle_storage/pickle_storage_torch.py
@@ -15,6 +15,7 @@ class PickleStorageTorch(PickleStorageBase[T]):
     """Responsible for storing and retrieving non-serializable data using `torch.save` and `torch.load`."""
 
     def __init__(self, output_folder: Path, item_type_name: "str"):
+        super().__init__()
         self._output_folder = output_folder
         self._output_folder.mkdir(parents=True, exist_ok=True)
         self._item_type_name = item_type_name

From c96f50cc9adde22fcc51c6ad456f607146abb3f7 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 7 Feb 2024 18:43:33 +1100
Subject: [PATCH 075/411] feat(nodes): ItemStorageABC typevar no longer bound
 to pydantic.BaseModel

This bound is totally unnecessary. There's no requirement for any implementation of `ItemStorageABC` to work only on pydantic models.
---
 invokeai/app/services/item_storage/item_storage_base.py | 4 +---
 1 file changed, 1 insertion(+), 3 deletions(-)

diff --git a/invokeai/app/services/item_storage/item_storage_base.py b/invokeai/app/services/item_storage/item_storage_base.py
index c93edf5188..d736679159 100644
--- a/invokeai/app/services/item_storage/item_storage_base.py
+++ b/invokeai/app/services/item_storage/item_storage_base.py
@@ -1,9 +1,7 @@
 from abc import ABC, abstractmethod
 from typing import Callable, Generic, TypeVar
 
-from pydantic import BaseModel
-
-T = TypeVar("T", bound=BaseModel)
+T = TypeVar("T")
 
 
 class ItemStorageABC(ABC, Generic[T]):

From ca09bd63a3184485b539b90519ce191fbc772869 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 7 Feb 2024 18:44:30 +1100
Subject: [PATCH 076/411] tidy(nodes): do not refer to files as latents in
 `PickleStorageTorch` (again)

---
 .../services/pickle_storage/pickle_storage_torch.py  | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/invokeai/app/services/pickle_storage/pickle_storage_torch.py b/invokeai/app/services/pickle_storage/pickle_storage_torch.py
index de411bbf47..16f0d7bb7a 100644
--- a/invokeai/app/services/pickle_storage/pickle_storage_torch.py
+++ b/invokeai/app/services/pickle_storage/pickle_storage_torch.py
@@ -25,17 +25,17 @@ class PickleStorageTorch(PickleStorageBase[T]):
         self._delete_all_items()
 
     def get(self, name: str) -> T:
-        latent_path = self._get_path(name)
-        return torch.load(latent_path)
+        file_path = self._get_path(name)
+        return torch.load(file_path)
 
     def save(self, name: str, data: T) -> None:
         self._output_folder.mkdir(parents=True, exist_ok=True)
-        latent_path = self._get_path(name)
-        torch.save(data, latent_path)
+        file_path = self._get_path(name)
+        torch.save(data, file_path)
 
     def delete(self, name: str) -> None:
-        latent_path = self._get_path(name)
-        latent_path.unlink()
+        file_path = self._get_path(name)
+        file_path.unlink()
 
     def _get_path(self, name: str) -> Path:
         return self._output_folder / name

From a50c7c1cd7b457102f6e31a9fb3321e0f26f3b40 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 7 Feb 2024 19:39:03 +1100
Subject: [PATCH 077/411] feat(nodes): use `ItemStorageABC` for tensors and
 conditioning

Turns out `ItemStorageABC` was almost identical to `PickleStorageBase`. Instead of maintaining separate classes, we can use `ItemStorageABC` for both.

There's only one change needed - the `ItemStorageABC.set` method must return the newly stored item's ID. This allows us to let the service handle the responsibility of naming the item, but still create the requisite output objects during node execution.

The naming implementation is improved here. It extracts the name of the generic and appends a UUID to that string when saving items.
---
 invokeai/app/api/dependencies.py              | 10 +--
 invokeai/app/services/invocation_services.py  |  5 +-
 .../item_storage/item_storage_base.py         |  2 +-
 .../item_storage_ephemeral_disk.py            | 72 +++++++++++++++++++
 .../item_storage_forward_cache.py             | 61 ++++++++++++++++
 .../item_storage/item_storage_memory.py       |  3 +-
 .../pickle_storage/pickle_storage_base.py     | 45 ------------
 .../pickle_storage_forward_cache.py           | 58 ---------------
 .../pickle_storage/pickle_storage_torch.py    | 63 ----------------
 .../app/services/shared/invocation_context.py | 30 +-------
 10 files changed, 145 insertions(+), 204 deletions(-)
 create mode 100644 invokeai/app/services/item_storage/item_storage_ephemeral_disk.py
 create mode 100644 invokeai/app/services/item_storage/item_storage_forward_cache.py
 delete mode 100644 invokeai/app/services/pickle_storage/pickle_storage_base.py
 delete mode 100644 invokeai/app/services/pickle_storage/pickle_storage_forward_cache.py
 delete mode 100644 invokeai/app/services/pickle_storage/pickle_storage_torch.py

diff --git a/invokeai/app/api/dependencies.py b/invokeai/app/api/dependencies.py
index 6bb0915cb6..d6fd970a22 100644
--- a/invokeai/app/api/dependencies.py
+++ b/invokeai/app/api/dependencies.py
@@ -4,9 +4,9 @@ from logging import Logger
 
 import torch
 
+from invokeai.app.services.item_storage.item_storage_ephemeral_disk import ItemStorageEphemeralDisk
+from invokeai.app.services.item_storage.item_storage_forward_cache import ItemStorageForwardCache
 from invokeai.app.services.item_storage.item_storage_memory import ItemStorageMemory
-from invokeai.app.services.pickle_storage.pickle_storage_forward_cache import PickleStorageForwardCache
-from invokeai.app.services.pickle_storage.pickle_storage_torch import PickleStorageTorch
 from invokeai.app.services.shared.sqlite.sqlite_util import init_db
 from invokeai.backend.model_manager.metadata import ModelMetadataStore
 from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ConditioningFieldData
@@ -90,9 +90,9 @@ class ApiDependencies:
         image_records = SqliteImageRecordStorage(db=db)
         images = ImageService()
         invocation_cache = MemoryInvocationCache(max_cache_size=config.node_cache_size)
-        tensors = PickleStorageForwardCache(PickleStorageTorch[torch.Tensor](output_folder / "tensors", "tensor"))
-        conditioning = PickleStorageForwardCache(
-            PickleStorageTorch[ConditioningFieldData](output_folder / "conditioning", "conditioning")
+        tensors = ItemStorageForwardCache(ItemStorageEphemeralDisk[torch.Tensor](output_folder / "tensors"))
+        conditioning = ItemStorageForwardCache(
+            ItemStorageEphemeralDisk[ConditioningFieldData](output_folder / "conditioning")
         )
         model_manager = ModelManagerService(config, logger)
         model_record_service = ModelRecordServiceSQL(db=db)
diff --git a/invokeai/app/services/invocation_services.py b/invokeai/app/services/invocation_services.py
index 81885781ac..69599d83a4 100644
--- a/invokeai/app/services/invocation_services.py
+++ b/invokeai/app/services/invocation_services.py
@@ -29,7 +29,6 @@ if TYPE_CHECKING:
     from .model_manager.model_manager_base import ModelManagerServiceBase
     from .model_records import ModelRecordServiceBase
     from .names.names_base import NameServiceBase
-    from .pickle_storage.pickle_storage_base import PickleStorageBase
     from .session_processor.session_processor_base import SessionProcessorBase
     from .session_queue.session_queue_base import SessionQueueBase
     from .shared.graph import GraphExecutionState
@@ -66,8 +65,8 @@ class InvocationServices:
         names: "NameServiceBase",
         urls: "UrlServiceBase",
         workflow_records: "WorkflowRecordsStorageBase",
-        tensors: "PickleStorageBase[torch.Tensor]",
-        conditioning: "PickleStorageBase[ConditioningFieldData]",
+        tensors: "ItemStorageABC[torch.Tensor]",
+        conditioning: "ItemStorageABC[ConditioningFieldData]",
     ):
         self.board_images = board_images
         self.board_image_records = board_image_records
diff --git a/invokeai/app/services/item_storage/item_storage_base.py b/invokeai/app/services/item_storage/item_storage_base.py
index d736679159..f2d62ea45f 100644
--- a/invokeai/app/services/item_storage/item_storage_base.py
+++ b/invokeai/app/services/item_storage/item_storage_base.py
@@ -26,7 +26,7 @@ class ItemStorageABC(ABC, Generic[T]):
         pass
 
     @abstractmethod
-    def set(self, item: T) -> None:
+    def set(self, item: T) -> str:
         """
         Sets the item. The id will be extracted based on id_field.
         :param item: the item to set
diff --git a/invokeai/app/services/item_storage/item_storage_ephemeral_disk.py b/invokeai/app/services/item_storage/item_storage_ephemeral_disk.py
new file mode 100644
index 0000000000..9843d1e54b
--- /dev/null
+++ b/invokeai/app/services/item_storage/item_storage_ephemeral_disk.py
@@ -0,0 +1,72 @@
+import typing
+from pathlib import Path
+from typing import Optional, TypeVar
+
+import torch
+
+from invokeai.app.services.invoker import Invoker
+from invokeai.app.services.item_storage.item_storage_base import ItemStorageABC
+from invokeai.app.util.misc import uuid_string
+
+T = TypeVar("T")
+
+
+class ItemStorageEphemeralDisk(ItemStorageABC[T]):
+    """Provides arbitrary item storage with a disk-backed ephemeral storage. The storage is cleared at startup."""
+
+    def __init__(self, output_folder: Path):
+        super().__init__()
+        self._output_folder = output_folder
+        self._output_folder.mkdir(parents=True, exist_ok=True)
+        self.__item_class_name: Optional[str] = None
+
+    @property
+    def _item_class_name(self) -> str:
+        if not self.__item_class_name:
+            # `__orig_class__` is not available in the constructor for some technical, undoubtedly very pythonic reason
+            self.__item_class_name = typing.get_args(self.__orig_class__)[0].__name__  # pyright: ignore [reportUnknownMemberType, reportGeneralTypeIssues]
+        return self.__item_class_name
+
+    def start(self, invoker: Invoker) -> None:
+        self._invoker = invoker
+        self._delete_all_items()
+
+    def get(self, item_id: str) -> T:
+        file_path = self._get_path(item_id)
+        return torch.load(file_path)  # pyright: ignore [reportUnknownMemberType]
+
+    def set(self, item: T) -> str:
+        self._output_folder.mkdir(parents=True, exist_ok=True)
+        item_id = f"{self._item_class_name}_{uuid_string()}"
+        file_path = self._get_path(item_id)
+        torch.save(item, file_path)  # pyright: ignore [reportUnknownMemberType]
+        return item_id
+
+    def delete(self, item_id: str) -> None:
+        file_path = self._get_path(item_id)
+        file_path.unlink()
+
+    def _get_path(self, item_id: str) -> Path:
+        return self._output_folder / item_id
+
+    def _delete_all_items(self) -> None:
+        """
+        Deletes all pickled items from disk.
+        Must be called after we have access to `self._invoker` (e.g. in `start()`).
+        """
+
+        if not self._invoker:
+            raise ValueError("Invoker is not set. Must call `start()` first.")
+
+        deleted_count = 0
+        freed_space = 0
+        for file in Path(self._output_folder).glob("*"):
+            if file.is_file():
+                freed_space += file.stat().st_size
+                deleted_count += 1
+                file.unlink()
+        if deleted_count > 0:
+            freed_space_in_mb = round(freed_space / 1024 / 1024, 2)
+            self._invoker.services.logger.info(
+                f"Deleted {deleted_count} {self._item_class_name} files (freed {freed_space_in_mb}MB)"
+            )
diff --git a/invokeai/app/services/item_storage/item_storage_forward_cache.py b/invokeai/app/services/item_storage/item_storage_forward_cache.py
new file mode 100644
index 0000000000..d1fe8e13fa
--- /dev/null
+++ b/invokeai/app/services/item_storage/item_storage_forward_cache.py
@@ -0,0 +1,61 @@
+from queue import Queue
+from typing import Optional, TypeVar
+
+from invokeai.app.services.invoker import Invoker
+from invokeai.app.services.item_storage.item_storage_base import ItemStorageABC
+
+T = TypeVar("T")
+
+
+class ItemStorageForwardCache(ItemStorageABC[T]):
+    """Provides a simple forward cache for an underlying storage. The cache is LRU and has a maximum size."""
+
+    def __init__(self, underlying_storage: ItemStorageABC[T], max_cache_size: int = 20):
+        super().__init__()
+        self._underlying_storage = underlying_storage
+        self._cache: dict[str, T] = {}
+        self._cache_ids = Queue[str]()
+        self._max_cache_size = max_cache_size
+
+    def start(self, invoker: Invoker) -> None:
+        self._invoker = invoker
+        start_op = getattr(self._underlying_storage, "start", None)
+        if callable(start_op):
+            start_op(invoker)
+
+    def stop(self, invoker: Invoker) -> None:
+        self._invoker = invoker
+        stop_op = getattr(self._underlying_storage, "stop", None)
+        if callable(stop_op):
+            stop_op(invoker)
+
+    def get(self, item_id: str) -> T:
+        cache_item = self._get_cache(item_id)
+        if cache_item is not None:
+            return cache_item
+
+        latent = self._underlying_storage.get(item_id)
+        self._set_cache(item_id, latent)
+        return latent
+
+    def set(self, item: T) -> str:
+        item_id = self._underlying_storage.set(item)
+        self._set_cache(item_id, item)
+        self._on_changed(item)
+        return item_id
+
+    def delete(self, item_id: str) -> None:
+        self._underlying_storage.delete(item_id)
+        if item_id in self._cache:
+            del self._cache[item_id]
+        self._on_deleted(item_id)
+
+    def _get_cache(self, item_id: str) -> Optional[T]:
+        return None if item_id not in self._cache else self._cache[item_id]
+
+    def _set_cache(self, item_id: str, data: T):
+        if item_id not in self._cache:
+            self._cache[item_id] = data
+            self._cache_ids.put(item_id)
+            if self._cache_ids.qsize() > self._max_cache_size:
+                self._cache.pop(self._cache_ids.get())
diff --git a/invokeai/app/services/item_storage/item_storage_memory.py b/invokeai/app/services/item_storage/item_storage_memory.py
index d8dd0e0664..6d02874516 100644
--- a/invokeai/app/services/item_storage/item_storage_memory.py
+++ b/invokeai/app/services/item_storage/item_storage_memory.py
@@ -34,7 +34,7 @@ class ItemStorageMemory(ItemStorageABC[T], Generic[T]):
         self._items[item_id] = item
         return item
 
-    def set(self, item: T) -> None:
+    def set(self, item: T) -> str:
         item_id = getattr(item, self._id_field)
         if item_id in self._items:
             # If item already exists, remove it and add it to the end
@@ -44,6 +44,7 @@ class ItemStorageMemory(ItemStorageABC[T], Generic[T]):
             self._items.popitem(last=False)
         self._items[item_id] = item
         self._on_changed(item)
+        return item_id
 
     def delete(self, item_id: str) -> None:
         # This is a no-op if the item doesn't exist.
diff --git a/invokeai/app/services/pickle_storage/pickle_storage_base.py b/invokeai/app/services/pickle_storage/pickle_storage_base.py
deleted file mode 100644
index 558b97c0f1..0000000000
--- a/invokeai/app/services/pickle_storage/pickle_storage_base.py
+++ /dev/null
@@ -1,45 +0,0 @@
-# Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
-
-from abc import ABC, abstractmethod
-from typing import Callable, Generic, TypeVar
-
-T = TypeVar("T")
-
-
-class PickleStorageBase(ABC, Generic[T]):
-    """Responsible for storing and retrieving non-serializable data using a pickler."""
-
-    _on_changed_callbacks: list[Callable[[T], None]]
-    _on_deleted_callbacks: list[Callable[[str], None]]
-
-    def __init__(self) -> None:
-        self._on_changed_callbacks = []
-        self._on_deleted_callbacks = []
-
-    @abstractmethod
-    def get(self, name: str) -> T:
-        pass
-
-    @abstractmethod
-    def save(self, name: str, data: T) -> None:
-        pass
-
-    @abstractmethod
-    def delete(self, name: str) -> None:
-        pass
-
-    def on_changed(self, on_changed: Callable[[T], None]) -> None:
-        """Register a callback for when an item is changed"""
-        self._on_changed_callbacks.append(on_changed)
-
-    def on_deleted(self, on_deleted: Callable[[str], None]) -> None:
-        """Register a callback for when an item is deleted"""
-        self._on_deleted_callbacks.append(on_deleted)
-
-    def _on_changed(self, item: T) -> None:
-        for callback in self._on_changed_callbacks:
-            callback(item)
-
-    def _on_deleted(self, item_id: str) -> None:
-        for callback in self._on_deleted_callbacks:
-            callback(item_id)
diff --git a/invokeai/app/services/pickle_storage/pickle_storage_forward_cache.py b/invokeai/app/services/pickle_storage/pickle_storage_forward_cache.py
deleted file mode 100644
index 3002d9e045..0000000000
--- a/invokeai/app/services/pickle_storage/pickle_storage_forward_cache.py
+++ /dev/null
@@ -1,58 +0,0 @@
-from queue import Queue
-from typing import Optional, TypeVar
-
-from invokeai.app.services.invoker import Invoker
-from invokeai.app.services.pickle_storage.pickle_storage_base import PickleStorageBase
-
-T = TypeVar("T")
-
-
-class PickleStorageForwardCache(PickleStorageBase[T]):
-    def __init__(self, underlying_storage: PickleStorageBase[T], max_cache_size: int = 20):
-        super().__init__()
-        self._underlying_storage = underlying_storage
-        self._cache: dict[str, T] = {}
-        self._cache_ids = Queue[str]()
-        self._max_cache_size = max_cache_size
-
-    def start(self, invoker: Invoker) -> None:
-        self._invoker = invoker
-        start_op = getattr(self._underlying_storage, "start", None)
-        if callable(start_op):
-            start_op(invoker)
-
-    def stop(self, invoker: Invoker) -> None:
-        self._invoker = invoker
-        stop_op = getattr(self._underlying_storage, "stop", None)
-        if callable(stop_op):
-            stop_op(invoker)
-
-    def get(self, name: str) -> T:
-        cache_item = self._get_cache(name)
-        if cache_item is not None:
-            return cache_item
-
-        latent = self._underlying_storage.get(name)
-        self._set_cache(name, latent)
-        return latent
-
-    def save(self, name: str, data: T) -> None:
-        self._underlying_storage.save(name, data)
-        self._set_cache(name, data)
-        self._on_changed(data)
-
-    def delete(self, name: str) -> None:
-        self._underlying_storage.delete(name)
-        if name in self._cache:
-            del self._cache[name]
-        self._on_deleted(name)
-
-    def _get_cache(self, name: str) -> Optional[T]:
-        return None if name not in self._cache else self._cache[name]
-
-    def _set_cache(self, name: str, data: T):
-        if name not in self._cache:
-            self._cache[name] = data
-            self._cache_ids.put(name)
-            if self._cache_ids.qsize() > self._max_cache_size:
-                self._cache.pop(self._cache_ids.get())
diff --git a/invokeai/app/services/pickle_storage/pickle_storage_torch.py b/invokeai/app/services/pickle_storage/pickle_storage_torch.py
deleted file mode 100644
index 16f0d7bb7a..0000000000
--- a/invokeai/app/services/pickle_storage/pickle_storage_torch.py
+++ /dev/null
@@ -1,63 +0,0 @@
-# Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
-
-from pathlib import Path
-from typing import TypeVar
-
-import torch
-
-from invokeai.app.services.invoker import Invoker
-from invokeai.app.services.pickle_storage.pickle_storage_base import PickleStorageBase
-
-T = TypeVar("T")
-
-
-class PickleStorageTorch(PickleStorageBase[T]):
-    """Responsible for storing and retrieving non-serializable data using `torch.save` and `torch.load`."""
-
-    def __init__(self, output_folder: Path, item_type_name: "str"):
-        super().__init__()
-        self._output_folder = output_folder
-        self._output_folder.mkdir(parents=True, exist_ok=True)
-        self._item_type_name = item_type_name
-
-    def start(self, invoker: Invoker) -> None:
-        self._invoker = invoker
-        self._delete_all_items()
-
-    def get(self, name: str) -> T:
-        file_path = self._get_path(name)
-        return torch.load(file_path)
-
-    def save(self, name: str, data: T) -> None:
-        self._output_folder.mkdir(parents=True, exist_ok=True)
-        file_path = self._get_path(name)
-        torch.save(data, file_path)
-
-    def delete(self, name: str) -> None:
-        file_path = self._get_path(name)
-        file_path.unlink()
-
-    def _get_path(self, name: str) -> Path:
-        return self._output_folder / name
-
-    def _delete_all_items(self) -> None:
-        """
-        Deletes all pickled items from disk.
-        Must be called after we have access to `self._invoker` (e.g. in `start()`).
-        """
-
-        if not self._invoker:
-            raise ValueError("Invoker is not set. Must call `start()` first.")
-
-        deleted_count = 0
-        freed_space = 0
-        for file in Path(self._output_folder).glob("*"):
-            if file.is_file():
-                freed_space += file.stat().st_size
-                deleted_count += 1
-                file.unlink()
-        if deleted_count > 0:
-            freed_space_in_mb = round(freed_space / 1024 / 1024, 2)
-            self._invoker.services.logger.info(
-                f"Deleted {deleted_count} {self._item_type_name} files (freed {freed_space_in_mb}MB)"
-            )
diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index 6756b1f5c6..baff47a3df 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -12,7 +12,6 @@ from invokeai.app.services.image_records.image_records_common import ImageCatego
 from invokeai.app.services.images.images_common import ImageDTO
 from invokeai.app.services.invocation_services import InvocationServices
 from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID
-from invokeai.app.util.misc import uuid_string
 from invokeai.app.util.step_callback import stable_diffusion_step_callback
 from invokeai.backend.model_management.model_manager import ModelInfo
 from invokeai.backend.model_management.models.base import BaseModelType, ModelType, SubModelType
@@ -224,26 +223,7 @@ class TensorsInterface(InvocationContextInterface):
         :param tensor: The tensor to save.
         """
 
-        # Previously, we added a suffix indicating the type of Tensor we were saving, e.g.
-        # "mask", "noise", "masked_latents", etc.
-        #
-        # Retaining that capability in this wrapper would require either many different methods
-        # to save tensors, or extra args for this method. Instead of complicating the API, we
-        # will use the same naming scheme for all tensors.
-        #
-        # This has a very minor impact as we don't use them after a session completes.
-
-        # Previously, invocations chose the name for their tensors. This is a bit risky, so we
-        # will generate a name for them instead. We use a uuid to ensure the name is unique.
-        #
-        # Because the name of the tensors file will includes the session and invocation IDs,
-        # we don't need to worry about collisions. A truncated UUIDv4 is fine.
-
-        name = f"{self._context_data.session_id}__{self._context_data.invocation.id}__{uuid_string()[:7]}"
-        self._services.tensors.save(
-            name=name,
-            data=tensor,
-        )
+        name = self._services.tensors.set(item=tensor)
         return name
 
     def get(self, tensor_name: str) -> Tensor:
@@ -263,13 +243,7 @@ class ConditioningInterface(InvocationContextInterface):
         :param conditioning_context_data: The conditioning data to save.
         """
 
-        # See comment in TensorsInterface.save for why we generate the name here.
-
-        name = f"{self._context_data.session_id}__{self._context_data.invocation.id}__{uuid_string()[:7]}"
-        self._services.conditioning.save(
-            name=name,
-            data=conditioning_data,
-        )
+        name = self._services.conditioning.set(item=conditioning_data)
         return name
 
     def get(self, conditioning_name: str) -> ConditioningFieldData:

From 9cda62c2a7a3cf70b539a3e13f6496f5790da144 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 7 Feb 2024 19:50:30 +1100
Subject: [PATCH 078/411] feat(nodes): create helper function to generate the
 item ID

---
 .../app/services/item_storage/item_storage_ephemeral_disk.py | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/invokeai/app/services/item_storage/item_storage_ephemeral_disk.py b/invokeai/app/services/item_storage/item_storage_ephemeral_disk.py
index 9843d1e54b..377c9c39b3 100644
--- a/invokeai/app/services/item_storage/item_storage_ephemeral_disk.py
+++ b/invokeai/app/services/item_storage/item_storage_ephemeral_disk.py
@@ -37,7 +37,7 @@ class ItemStorageEphemeralDisk(ItemStorageABC[T]):
 
     def set(self, item: T) -> str:
         self._output_folder.mkdir(parents=True, exist_ok=True)
-        item_id = f"{self._item_class_name}_{uuid_string()}"
+        item_id = self._new_item_id()
         file_path = self._get_path(item_id)
         torch.save(item, file_path)  # pyright: ignore [reportUnknownMemberType]
         return item_id
@@ -49,6 +49,9 @@ class ItemStorageEphemeralDisk(ItemStorageABC[T]):
     def _get_path(self, item_id: str) -> Path:
         return self._output_folder / item_id
 
+    def _new_item_id(self) -> str:
+        return f"{self._item_class_name}_{uuid_string()}"
+
     def _delete_all_items(self) -> None:
         """
         Deletes all pickled items from disk.

From ab58d34f9bb41a28a3597edc59941be8b4d8caa4 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 7 Feb 2024 19:51:04 +1100
Subject: [PATCH 079/411] feat(nodes): support custom save and load functions
 in `ItemStorageEphemeralDisk`

---
 .../item_storage/item_storage_common.py       | 10 ++++++++
 .../item_storage_ephemeral_disk.py            | 24 +++++++++++++++----
 2 files changed, 30 insertions(+), 4 deletions(-)

diff --git a/invokeai/app/services/item_storage/item_storage_common.py b/invokeai/app/services/item_storage/item_storage_common.py
index 8fd677c71b..7f9bd7bd4e 100644
--- a/invokeai/app/services/item_storage/item_storage_common.py
+++ b/invokeai/app/services/item_storage/item_storage_common.py
@@ -1,5 +1,15 @@
+from pathlib import Path
+from typing import Callable, TypeAlias, TypeVar
+
+
 class ItemNotFoundError(KeyError):
     """Raised when an item is not found in storage"""
 
     def __init__(self, item_id: str) -> None:
         super().__init__(f"Item with id {item_id} not found")
+
+
+T = TypeVar("T")
+
+SaveFunc: TypeAlias = Callable[[T, Path], None]
+LoadFunc: TypeAlias = Callable[[Path], T]
diff --git a/invokeai/app/services/item_storage/item_storage_ephemeral_disk.py b/invokeai/app/services/item_storage/item_storage_ephemeral_disk.py
index 377c9c39b3..4dc67129da 100644
--- a/invokeai/app/services/item_storage/item_storage_ephemeral_disk.py
+++ b/invokeai/app/services/item_storage/item_storage_ephemeral_disk.py
@@ -6,18 +6,31 @@ import torch
 
 from invokeai.app.services.invoker import Invoker
 from invokeai.app.services.item_storage.item_storage_base import ItemStorageABC
+from invokeai.app.services.item_storage.item_storage_common import LoadFunc, SaveFunc
 from invokeai.app.util.misc import uuid_string
 
 T = TypeVar("T")
 
 
 class ItemStorageEphemeralDisk(ItemStorageABC[T]):
-    """Provides arbitrary item storage with a disk-backed ephemeral storage. The storage is cleared at startup."""
+    """Provides a disk-backed ephemeral storage. The storage is cleared at startup.
 
-    def __init__(self, output_folder: Path):
+    :param output_folder: The folder where the items will be stored
+    :param save: The function to use to save the items to disk [torch.save]
+    :param load: The function to use to load the items from disk [torch.load]
+    """
+
+    def __init__(
+        self,
+        output_folder: Path,
+        save: SaveFunc[T] = torch.save,  # pyright: ignore [reportUnknownMemberType]
+        load: LoadFunc[T] = torch.load,  # pyright: ignore [reportUnknownMemberType]
+    ):
         super().__init__()
         self._output_folder = output_folder
         self._output_folder.mkdir(parents=True, exist_ok=True)
+        self._save = save
+        self._load = load
         self.__item_class_name: Optional[str] = None
 
     @property
@@ -33,13 +46,13 @@ class ItemStorageEphemeralDisk(ItemStorageABC[T]):
 
     def get(self, item_id: str) -> T:
         file_path = self._get_path(item_id)
-        return torch.load(file_path)  # pyright: ignore [reportUnknownMemberType]
+        return self._load(file_path)
 
     def set(self, item: T) -> str:
         self._output_folder.mkdir(parents=True, exist_ok=True)
         item_id = self._new_item_id()
         file_path = self._get_path(item_id)
-        torch.save(item, file_path)  # pyright: ignore [reportUnknownMemberType]
+        self._save(item, file_path)
         return item_id
 
     def delete(self, item_id: str) -> None:
@@ -58,6 +71,9 @@ class ItemStorageEphemeralDisk(ItemStorageABC[T]):
         Must be called after we have access to `self._invoker` (e.g. in `start()`).
         """
 
+        # We could try using a temporary directory here, but they aren't cleared in the event of a crash, so we'd have
+        # to manually clear them on startup anyways. This is a bit simpler and more reliable.
+
         if not self._invoker:
             raise ValueError("Invoker is not set. Must call `start()` first.")
 

From 73d871116cc08ed8065e19bcfd1d9a10ed911c6d Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 7 Feb 2024 22:54:52 +1100
Subject: [PATCH 080/411] feat(nodes): support custom exception in ephemeral
 disk storage

---
 .../item_storage/item_storage_ephemeral_disk.py      | 12 +++++++++---
 1 file changed, 9 insertions(+), 3 deletions(-)

diff --git a/invokeai/app/services/item_storage/item_storage_ephemeral_disk.py b/invokeai/app/services/item_storage/item_storage_ephemeral_disk.py
index 4dc67129da..97c767c87d 100644
--- a/invokeai/app/services/item_storage/item_storage_ephemeral_disk.py
+++ b/invokeai/app/services/item_storage/item_storage_ephemeral_disk.py
@@ -1,12 +1,12 @@
 import typing
 from pathlib import Path
-from typing import Optional, TypeVar
+from typing import Optional, Type, TypeVar
 
 import torch
 
 from invokeai.app.services.invoker import Invoker
 from invokeai.app.services.item_storage.item_storage_base import ItemStorageABC
-from invokeai.app.services.item_storage.item_storage_common import LoadFunc, SaveFunc
+from invokeai.app.services.item_storage.item_storage_common import ItemNotFoundError, LoadFunc, SaveFunc
 from invokeai.app.util.misc import uuid_string
 
 T = TypeVar("T")
@@ -18,6 +18,7 @@ class ItemStorageEphemeralDisk(ItemStorageABC[T]):
     :param output_folder: The folder where the items will be stored
     :param save: The function to use to save the items to disk [torch.save]
     :param load: The function to use to load the items from disk [torch.load]
+    :param load_exc: The exception that is raised when an item is not found [FileNotFoundError]
     """
 
     def __init__(
@@ -25,12 +26,14 @@ class ItemStorageEphemeralDisk(ItemStorageABC[T]):
         output_folder: Path,
         save: SaveFunc[T] = torch.save,  # pyright: ignore [reportUnknownMemberType]
         load: LoadFunc[T] = torch.load,  # pyright: ignore [reportUnknownMemberType]
+        load_exc: Type[Exception] = FileNotFoundError,
     ):
         super().__init__()
         self._output_folder = output_folder
         self._output_folder.mkdir(parents=True, exist_ok=True)
         self._save = save
         self._load = load
+        self._load_exc = load_exc
         self.__item_class_name: Optional[str] = None
 
     @property
@@ -46,7 +49,10 @@ class ItemStorageEphemeralDisk(ItemStorageABC[T]):
 
     def get(self, item_id: str) -> T:
         file_path = self._get_path(item_id)
-        return self._load(file_path)
+        try:
+            return self._load(file_path)
+        except self._load_exc as e:
+            raise ItemNotFoundError(item_id) from e
 
     def set(self, item: T) -> str:
         self._output_folder.mkdir(parents=True, exist_ok=True)

From 9f382419dce8a7d950c8f13bd55488a07f96048d Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 7 Feb 2024 23:30:46 +1100
Subject: [PATCH 081/411] revert(nodes): revert making tensors/conditioning use
 item storage

Turns out they are just different enough in purpose that the implementations would be rather unintuitive. I've made a separate ObjectSerializer service to handle tensors and conditioning.

Refined the class a bit too.
---
 invokeai/app/api/dependencies.py              | 10 +-
 invokeai/app/invocations/latent.py            | 24 ++---
 invokeai/app/invocations/primitives.py        |  2 +-
 invokeai/app/services/invocation_services.py  |  6 +-
 .../item_storage/item_storage_base.py         |  8 +-
 .../item_storage/item_storage_common.py       | 10 --
 .../item_storage_ephemeral_disk.py            | 97 -------------------
 .../item_storage_forward_cache.py             | 61 ------------
 .../item_storage/item_storage_memory.py       |  3 +-
 .../object_serializer_base.py                 | 53 ++++++++++
 .../object_serializer_common.py               |  5 +
 .../object_serializer_ephemeral_disk.py       | 84 ++++++++++++++++
 .../object_serializer_forward_cache.py        | 61 ++++++++++++
 .../app/services/shared/invocation_context.py | 24 ++---
 14 files changed, 243 insertions(+), 205 deletions(-)
 delete mode 100644 invokeai/app/services/item_storage/item_storage_ephemeral_disk.py
 delete mode 100644 invokeai/app/services/item_storage/item_storage_forward_cache.py
 create mode 100644 invokeai/app/services/object_serializer/object_serializer_base.py
 create mode 100644 invokeai/app/services/object_serializer/object_serializer_common.py
 create mode 100644 invokeai/app/services/object_serializer/object_serializer_ephemeral_disk.py
 create mode 100644 invokeai/app/services/object_serializer/object_serializer_forward_cache.py

diff --git a/invokeai/app/api/dependencies.py b/invokeai/app/api/dependencies.py
index d6fd970a22..0c80494616 100644
--- a/invokeai/app/api/dependencies.py
+++ b/invokeai/app/api/dependencies.py
@@ -4,9 +4,9 @@ from logging import Logger
 
 import torch
 
-from invokeai.app.services.item_storage.item_storage_ephemeral_disk import ItemStorageEphemeralDisk
-from invokeai.app.services.item_storage.item_storage_forward_cache import ItemStorageForwardCache
 from invokeai.app.services.item_storage.item_storage_memory import ItemStorageMemory
+from invokeai.app.services.object_serializer.object_serializer_ephemeral_disk import ObjectSerializerEphemeralDisk
+from invokeai.app.services.object_serializer.object_serializer_forward_cache import ObjectSerializerForwardCache
 from invokeai.app.services.shared.sqlite.sqlite_util import init_db
 from invokeai.backend.model_manager.metadata import ModelMetadataStore
 from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ConditioningFieldData
@@ -90,9 +90,9 @@ class ApiDependencies:
         image_records = SqliteImageRecordStorage(db=db)
         images = ImageService()
         invocation_cache = MemoryInvocationCache(max_cache_size=config.node_cache_size)
-        tensors = ItemStorageForwardCache(ItemStorageEphemeralDisk[torch.Tensor](output_folder / "tensors"))
-        conditioning = ItemStorageForwardCache(
-            ItemStorageEphemeralDisk[ConditioningFieldData](output_folder / "conditioning")
+        tensors = ObjectSerializerForwardCache(ObjectSerializerEphemeralDisk[torch.Tensor](output_folder / "tensors"))
+        conditioning = ObjectSerializerForwardCache(
+            ObjectSerializerEphemeralDisk[ConditioningFieldData](output_folder / "conditioning")
         )
         model_manager = ModelManagerService(config, logger)
         model_record_service = ModelRecordServiceSQL(db=db)
diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py
index 94440d3e2a..4137ab6e2f 100644
--- a/invokeai/app/invocations/latent.py
+++ b/invokeai/app/invocations/latent.py
@@ -304,11 +304,11 @@ class DenoiseLatentsInvocation(BaseInvocation):
         unet,
         seed,
     ) -> ConditioningData:
-        positive_cond_data = context.conditioning.get(self.positive_conditioning.conditioning_name)
+        positive_cond_data = context.conditioning.load(self.positive_conditioning.conditioning_name)
         c = positive_cond_data.conditionings[0].to(device=unet.device, dtype=unet.dtype)
         extra_conditioning_info = c.extra_conditioning
 
-        negative_cond_data = context.conditioning.get(self.negative_conditioning.conditioning_name)
+        negative_cond_data = context.conditioning.load(self.negative_conditioning.conditioning_name)
         uc = negative_cond_data.conditionings[0].to(device=unet.device, dtype=unet.dtype)
 
         conditioning_data = ConditioningData(
@@ -621,10 +621,10 @@ class DenoiseLatentsInvocation(BaseInvocation):
         if self.denoise_mask is None:
             return None, None
 
-        mask = context.tensors.get(self.denoise_mask.mask_name)
+        mask = context.tensors.load(self.denoise_mask.mask_name)
         mask = tv_resize(mask, latents.shape[-2:], T.InterpolationMode.BILINEAR, antialias=False)
         if self.denoise_mask.masked_latents_name is not None:
-            masked_latents = context.tensors.get(self.denoise_mask.masked_latents_name)
+            masked_latents = context.tensors.load(self.denoise_mask.masked_latents_name)
         else:
             masked_latents = None
 
@@ -636,11 +636,11 @@ class DenoiseLatentsInvocation(BaseInvocation):
             seed = None
             noise = None
             if self.noise is not None:
-                noise = context.tensors.get(self.noise.latents_name)
+                noise = context.tensors.load(self.noise.latents_name)
                 seed = self.noise.seed
 
             if self.latents is not None:
-                latents = context.tensors.get(self.latents.latents_name)
+                latents = context.tensors.load(self.latents.latents_name)
                 if seed is None:
                     seed = self.latents.seed
 
@@ -779,7 +779,7 @@ class LatentsToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
 
     @torch.no_grad()
     def invoke(self, context: InvocationContext) -> ImageOutput:
-        latents = context.tensors.get(self.latents.latents_name)
+        latents = context.tensors.load(self.latents.latents_name)
 
         vae_info = context.models.load(**self.vae.vae.model_dump())
 
@@ -870,7 +870,7 @@ class ResizeLatentsInvocation(BaseInvocation):
     antialias: bool = InputField(default=False, description=FieldDescriptions.torch_antialias)
 
     def invoke(self, context: InvocationContext) -> LatentsOutput:
-        latents = context.tensors.get(self.latents.latents_name)
+        latents = context.tensors.load(self.latents.latents_name)
 
         # TODO:
         device = choose_torch_device()
@@ -911,7 +911,7 @@ class ScaleLatentsInvocation(BaseInvocation):
     antialias: bool = InputField(default=False, description=FieldDescriptions.torch_antialias)
 
     def invoke(self, context: InvocationContext) -> LatentsOutput:
-        latents = context.tensors.get(self.latents.latents_name)
+        latents = context.tensors.load(self.latents.latents_name)
 
         # TODO:
         device = choose_torch_device()
@@ -1048,8 +1048,8 @@ class BlendLatentsInvocation(BaseInvocation):
     alpha: float = InputField(default=0.5, description=FieldDescriptions.blend_alpha)
 
     def invoke(self, context: InvocationContext) -> LatentsOutput:
-        latents_a = context.tensors.get(self.latents_a.latents_name)
-        latents_b = context.tensors.get(self.latents_b.latents_name)
+        latents_a = context.tensors.load(self.latents_a.latents_name)
+        latents_b = context.tensors.load(self.latents_b.latents_name)
 
         if latents_a.shape != latents_b.shape:
             raise Exception("Latents to blend must be the same size.")
@@ -1149,7 +1149,7 @@ class CropLatentsCoreInvocation(BaseInvocation):
     )
 
     def invoke(self, context: InvocationContext) -> LatentsOutput:
-        latents = context.tensors.get(self.latents.latents_name)
+        latents = context.tensors.load(self.latents.latents_name)
 
         x1 = self.x // LATENT_SCALE_FACTOR
         y1 = self.y // LATENT_SCALE_FACTOR
diff --git a/invokeai/app/invocations/primitives.py b/invokeai/app/invocations/primitives.py
index 082d5432cc..d0f95c92d0 100644
--- a/invokeai/app/invocations/primitives.py
+++ b/invokeai/app/invocations/primitives.py
@@ -344,7 +344,7 @@ class LatentsInvocation(BaseInvocation):
     latents: LatentsField = InputField(description="The latents tensor", input=Input.Connection)
 
     def invoke(self, context: InvocationContext) -> LatentsOutput:
-        latents = context.tensors.get(self.latents.latents_name)
+        latents = context.tensors.load(self.latents.latents_name)
 
         return LatentsOutput.build(self.latents.latents_name, latents)
 
diff --git a/invokeai/app/services/invocation_services.py b/invokeai/app/services/invocation_services.py
index 69599d83a4..e893be8763 100644
--- a/invokeai/app/services/invocation_services.py
+++ b/invokeai/app/services/invocation_services.py
@@ -3,6 +3,8 @@ from __future__ import annotations
 
 from typing import TYPE_CHECKING
 
+from invokeai.app.services.object_serializer.object_serializer_base import ObjectSerializerBase
+
 if TYPE_CHECKING:
     from logging import Logger
 
@@ -65,8 +67,8 @@ class InvocationServices:
         names: "NameServiceBase",
         urls: "UrlServiceBase",
         workflow_records: "WorkflowRecordsStorageBase",
-        tensors: "ItemStorageABC[torch.Tensor]",
-        conditioning: "ItemStorageABC[ConditioningFieldData]",
+        tensors: "ObjectSerializerBase[torch.Tensor]",
+        conditioning: "ObjectSerializerBase[ConditioningFieldData]",
     ):
         self.board_images = board_images
         self.board_image_records = board_image_records
diff --git a/invokeai/app/services/item_storage/item_storage_base.py b/invokeai/app/services/item_storage/item_storage_base.py
index f2d62ea45f..ef227ba241 100644
--- a/invokeai/app/services/item_storage/item_storage_base.py
+++ b/invokeai/app/services/item_storage/item_storage_base.py
@@ -1,7 +1,9 @@
 from abc import ABC, abstractmethod
 from typing import Callable, Generic, TypeVar
 
-T = TypeVar("T")
+from pydantic import BaseModel
+
+T = TypeVar("T", bound=BaseModel)
 
 
 class ItemStorageABC(ABC, Generic[T]):
@@ -26,9 +28,9 @@ class ItemStorageABC(ABC, Generic[T]):
         pass
 
     @abstractmethod
-    def set(self, item: T) -> str:
+    def set(self, item: T) -> None:
         """
-        Sets the item. The id will be extracted based on id_field.
+        Sets the item.
         :param item: the item to set
         """
         pass
diff --git a/invokeai/app/services/item_storage/item_storage_common.py b/invokeai/app/services/item_storage/item_storage_common.py
index 7f9bd7bd4e..8fd677c71b 100644
--- a/invokeai/app/services/item_storage/item_storage_common.py
+++ b/invokeai/app/services/item_storage/item_storage_common.py
@@ -1,15 +1,5 @@
-from pathlib import Path
-from typing import Callable, TypeAlias, TypeVar
-
-
 class ItemNotFoundError(KeyError):
     """Raised when an item is not found in storage"""
 
     def __init__(self, item_id: str) -> None:
         super().__init__(f"Item with id {item_id} not found")
-
-
-T = TypeVar("T")
-
-SaveFunc: TypeAlias = Callable[[T, Path], None]
-LoadFunc: TypeAlias = Callable[[Path], T]
diff --git a/invokeai/app/services/item_storage/item_storage_ephemeral_disk.py b/invokeai/app/services/item_storage/item_storage_ephemeral_disk.py
deleted file mode 100644
index 97c767c87d..0000000000
--- a/invokeai/app/services/item_storage/item_storage_ephemeral_disk.py
+++ /dev/null
@@ -1,97 +0,0 @@
-import typing
-from pathlib import Path
-from typing import Optional, Type, TypeVar
-
-import torch
-
-from invokeai.app.services.invoker import Invoker
-from invokeai.app.services.item_storage.item_storage_base import ItemStorageABC
-from invokeai.app.services.item_storage.item_storage_common import ItemNotFoundError, LoadFunc, SaveFunc
-from invokeai.app.util.misc import uuid_string
-
-T = TypeVar("T")
-
-
-class ItemStorageEphemeralDisk(ItemStorageABC[T]):
-    """Provides a disk-backed ephemeral storage. The storage is cleared at startup.
-
-    :param output_folder: The folder where the items will be stored
-    :param save: The function to use to save the items to disk [torch.save]
-    :param load: The function to use to load the items from disk [torch.load]
-    :param load_exc: The exception that is raised when an item is not found [FileNotFoundError]
-    """
-
-    def __init__(
-        self,
-        output_folder: Path,
-        save: SaveFunc[T] = torch.save,  # pyright: ignore [reportUnknownMemberType]
-        load: LoadFunc[T] = torch.load,  # pyright: ignore [reportUnknownMemberType]
-        load_exc: Type[Exception] = FileNotFoundError,
-    ):
-        super().__init__()
-        self._output_folder = output_folder
-        self._output_folder.mkdir(parents=True, exist_ok=True)
-        self._save = save
-        self._load = load
-        self._load_exc = load_exc
-        self.__item_class_name: Optional[str] = None
-
-    @property
-    def _item_class_name(self) -> str:
-        if not self.__item_class_name:
-            # `__orig_class__` is not available in the constructor for some technical, undoubtedly very pythonic reason
-            self.__item_class_name = typing.get_args(self.__orig_class__)[0].__name__  # pyright: ignore [reportUnknownMemberType, reportGeneralTypeIssues]
-        return self.__item_class_name
-
-    def start(self, invoker: Invoker) -> None:
-        self._invoker = invoker
-        self._delete_all_items()
-
-    def get(self, item_id: str) -> T:
-        file_path = self._get_path(item_id)
-        try:
-            return self._load(file_path)
-        except self._load_exc as e:
-            raise ItemNotFoundError(item_id) from e
-
-    def set(self, item: T) -> str:
-        self._output_folder.mkdir(parents=True, exist_ok=True)
-        item_id = self._new_item_id()
-        file_path = self._get_path(item_id)
-        self._save(item, file_path)
-        return item_id
-
-    def delete(self, item_id: str) -> None:
-        file_path = self._get_path(item_id)
-        file_path.unlink()
-
-    def _get_path(self, item_id: str) -> Path:
-        return self._output_folder / item_id
-
-    def _new_item_id(self) -> str:
-        return f"{self._item_class_name}_{uuid_string()}"
-
-    def _delete_all_items(self) -> None:
-        """
-        Deletes all pickled items from disk.
-        Must be called after we have access to `self._invoker` (e.g. in `start()`).
-        """
-
-        # We could try using a temporary directory here, but they aren't cleared in the event of a crash, so we'd have
-        # to manually clear them on startup anyways. This is a bit simpler and more reliable.
-
-        if not self._invoker:
-            raise ValueError("Invoker is not set. Must call `start()` first.")
-
-        deleted_count = 0
-        freed_space = 0
-        for file in Path(self._output_folder).glob("*"):
-            if file.is_file():
-                freed_space += file.stat().st_size
-                deleted_count += 1
-                file.unlink()
-        if deleted_count > 0:
-            freed_space_in_mb = round(freed_space / 1024 / 1024, 2)
-            self._invoker.services.logger.info(
-                f"Deleted {deleted_count} {self._item_class_name} files (freed {freed_space_in_mb}MB)"
-            )
diff --git a/invokeai/app/services/item_storage/item_storage_forward_cache.py b/invokeai/app/services/item_storage/item_storage_forward_cache.py
deleted file mode 100644
index d1fe8e13fa..0000000000
--- a/invokeai/app/services/item_storage/item_storage_forward_cache.py
+++ /dev/null
@@ -1,61 +0,0 @@
-from queue import Queue
-from typing import Optional, TypeVar
-
-from invokeai.app.services.invoker import Invoker
-from invokeai.app.services.item_storage.item_storage_base import ItemStorageABC
-
-T = TypeVar("T")
-
-
-class ItemStorageForwardCache(ItemStorageABC[T]):
-    """Provides a simple forward cache for an underlying storage. The cache is LRU and has a maximum size."""
-
-    def __init__(self, underlying_storage: ItemStorageABC[T], max_cache_size: int = 20):
-        super().__init__()
-        self._underlying_storage = underlying_storage
-        self._cache: dict[str, T] = {}
-        self._cache_ids = Queue[str]()
-        self._max_cache_size = max_cache_size
-
-    def start(self, invoker: Invoker) -> None:
-        self._invoker = invoker
-        start_op = getattr(self._underlying_storage, "start", None)
-        if callable(start_op):
-            start_op(invoker)
-
-    def stop(self, invoker: Invoker) -> None:
-        self._invoker = invoker
-        stop_op = getattr(self._underlying_storage, "stop", None)
-        if callable(stop_op):
-            stop_op(invoker)
-
-    def get(self, item_id: str) -> T:
-        cache_item = self._get_cache(item_id)
-        if cache_item is not None:
-            return cache_item
-
-        latent = self._underlying_storage.get(item_id)
-        self._set_cache(item_id, latent)
-        return latent
-
-    def set(self, item: T) -> str:
-        item_id = self._underlying_storage.set(item)
-        self._set_cache(item_id, item)
-        self._on_changed(item)
-        return item_id
-
-    def delete(self, item_id: str) -> None:
-        self._underlying_storage.delete(item_id)
-        if item_id in self._cache:
-            del self._cache[item_id]
-        self._on_deleted(item_id)
-
-    def _get_cache(self, item_id: str) -> Optional[T]:
-        return None if item_id not in self._cache else self._cache[item_id]
-
-    def _set_cache(self, item_id: str, data: T):
-        if item_id not in self._cache:
-            self._cache[item_id] = data
-            self._cache_ids.put(item_id)
-            if self._cache_ids.qsize() > self._max_cache_size:
-                self._cache.pop(self._cache_ids.get())
diff --git a/invokeai/app/services/item_storage/item_storage_memory.py b/invokeai/app/services/item_storage/item_storage_memory.py
index 6d02874516..d8dd0e0664 100644
--- a/invokeai/app/services/item_storage/item_storage_memory.py
+++ b/invokeai/app/services/item_storage/item_storage_memory.py
@@ -34,7 +34,7 @@ class ItemStorageMemory(ItemStorageABC[T], Generic[T]):
         self._items[item_id] = item
         return item
 
-    def set(self, item: T) -> str:
+    def set(self, item: T) -> None:
         item_id = getattr(item, self._id_field)
         if item_id in self._items:
             # If item already exists, remove it and add it to the end
@@ -44,7 +44,6 @@ class ItemStorageMemory(ItemStorageABC[T], Generic[T]):
             self._items.popitem(last=False)
         self._items[item_id] = item
         self._on_changed(item)
-        return item_id
 
     def delete(self, item_id: str) -> None:
         # This is a no-op if the item doesn't exist.
diff --git a/invokeai/app/services/object_serializer/object_serializer_base.py b/invokeai/app/services/object_serializer/object_serializer_base.py
new file mode 100644
index 0000000000..b01a641d8f
--- /dev/null
+++ b/invokeai/app/services/object_serializer/object_serializer_base.py
@@ -0,0 +1,53 @@
+from abc import ABC, abstractmethod
+from typing import Callable, Generic, TypeVar
+
+T = TypeVar("T")
+
+
+class ObjectSerializerBase(ABC, Generic[T]):
+    """Saves and loads arbitrary python objects."""
+
+    def __init__(self) -> None:
+        self._on_saved_callbacks: list[Callable[[str, T], None]] = []
+        self._on_deleted_callbacks: list[Callable[[str], None]] = []
+
+    @abstractmethod
+    def load(self, name: str) -> T:
+        """
+        Loads the object.
+        :param name: The name of the object to load.
+        :raises ObjectNotFoundError: if the object is not found
+        """
+        pass
+
+    @abstractmethod
+    def save(self, obj: T) -> str:
+        """
+        Saves the object, returning its name.
+        :param obj: The object to save.
+        """
+        pass
+
+    @abstractmethod
+    def delete(self, name: str) -> None:
+        """
+        Deletes the object, if it exists.
+        :param name: The name of the object to delete.
+        """
+        pass
+
+    def on_saved(self, on_saved: Callable[[str, T], None]) -> None:
+        """Register a callback for when an object is saved"""
+        self._on_saved_callbacks.append(on_saved)
+
+    def on_deleted(self, on_deleted: Callable[[str], None]) -> None:
+        """Register a callback for when an object is deleted"""
+        self._on_deleted_callbacks.append(on_deleted)
+
+    def _on_saved(self, name: str, obj: T) -> None:
+        for callback in self._on_saved_callbacks:
+            callback(name, obj)
+
+    def _on_deleted(self, name: str) -> None:
+        for callback in self._on_deleted_callbacks:
+            callback(name)
diff --git a/invokeai/app/services/object_serializer/object_serializer_common.py b/invokeai/app/services/object_serializer/object_serializer_common.py
new file mode 100644
index 0000000000..7057386541
--- /dev/null
+++ b/invokeai/app/services/object_serializer/object_serializer_common.py
@@ -0,0 +1,5 @@
+class ObjectNotFoundError(KeyError):
+    """Raised when an object is not found while loading"""
+
+    def __init__(self, name: str) -> None:
+        super().__init__(f"Object with name {name} not found")
diff --git a/invokeai/app/services/object_serializer/object_serializer_ephemeral_disk.py b/invokeai/app/services/object_serializer/object_serializer_ephemeral_disk.py
new file mode 100644
index 0000000000..afa868b157
--- /dev/null
+++ b/invokeai/app/services/object_serializer/object_serializer_ephemeral_disk.py
@@ -0,0 +1,84 @@
+import typing
+from pathlib import Path
+from typing import Optional, TypeVar
+
+import torch
+
+from invokeai.app.services.invoker import Invoker
+from invokeai.app.services.object_serializer.object_serializer_base import ObjectSerializerBase
+from invokeai.app.services.object_serializer.object_serializer_common import ObjectNotFoundError
+from invokeai.app.util.misc import uuid_string
+
+T = TypeVar("T")
+
+
+class ObjectSerializerEphemeralDisk(ObjectSerializerBase[T]):
+    """Provides a disk-backed ephemeral storage for arbitrary python objects. The storage is cleared at startup.
+
+    :param output_folder: The folder where the objects will be stored
+    """
+
+    def __init__(self, output_dir: Path):
+        super().__init__()
+        self._output_dir = output_dir
+        self._output_dir.mkdir(parents=True, exist_ok=True)
+        self.__obj_class_name: Optional[str] = None
+
+    def start(self, invoker: Invoker) -> None:
+        self._invoker = invoker
+        self._delete_all()
+
+    def load(self, name: str) -> T:
+        file_path = self._get_path(name)
+        try:
+            return torch.load(file_path)  # pyright: ignore [reportUnknownMemberType]
+        except FileNotFoundError as e:
+            raise ObjectNotFoundError(name) from e
+
+    def save(self, obj: T) -> str:
+        name = self._new_name()
+        file_path = self._get_path(name)
+        torch.save(obj, file_path)  # pyright: ignore [reportUnknownMemberType]
+        return name
+
+    def delete(self, name: str) -> None:
+        file_path = self._get_path(name)
+        file_path.unlink()
+
+    @property
+    def _obj_class_name(self) -> str:
+        if not self.__obj_class_name:
+            # `__orig_class__` is not available in the constructor for some technical, undoubtedly very pythonic reason
+            self.__obj_class_name = typing.get_args(self.__orig_class__)[0].__name__  # pyright: ignore [reportUnknownMemberType, reportGeneralTypeIssues]
+        return self.__obj_class_name
+
+    def _get_path(self, name: str) -> Path:
+        return self._output_dir / name
+
+    def _new_name(self) -> str:
+        return f"{self._obj_class_name}_{uuid_string()}"
+
+    def _delete_all(self) -> None:
+        """
+        Deletes all objects from disk.
+        Must be called after we have access to `self._invoker` (e.g. in `start()`).
+        """
+
+        # We could try using a temporary directory here, but they aren't cleared in the event of a crash, so we'd have
+        # to manually clear them on startup anyways. This is a bit simpler and more reliable.
+
+        if not self._invoker:
+            raise ValueError("Invoker is not set. Must call `start()` first.")
+
+        deleted_count = 0
+        freed_space = 0
+        for file in Path(self._output_dir).glob("*"):
+            if file.is_file():
+                freed_space += file.stat().st_size
+                deleted_count += 1
+                file.unlink()
+        if deleted_count > 0:
+            freed_space_in_mb = round(freed_space / 1024 / 1024, 2)
+            self._invoker.services.logger.info(
+                f"Deleted {deleted_count} {self._obj_class_name} files (freed {freed_space_in_mb}MB)"
+            )
diff --git a/invokeai/app/services/object_serializer/object_serializer_forward_cache.py b/invokeai/app/services/object_serializer/object_serializer_forward_cache.py
new file mode 100644
index 0000000000..40e34e6540
--- /dev/null
+++ b/invokeai/app/services/object_serializer/object_serializer_forward_cache.py
@@ -0,0 +1,61 @@
+from queue import Queue
+from typing import Optional, TypeVar
+
+from invokeai.app.services.invoker import Invoker
+from invokeai.app.services.object_serializer.object_serializer_base import ObjectSerializerBase
+
+T = TypeVar("T")
+
+
+class ObjectSerializerForwardCache(ObjectSerializerBase[T]):
+    """Provides a simple forward cache for an underlying storage. The cache is LRU and has a maximum size."""
+
+    def __init__(self, underlying_storage: ObjectSerializerBase[T], max_cache_size: int = 20):
+        super().__init__()
+        self._underlying_storage = underlying_storage
+        self._cache: dict[str, T] = {}
+        self._cache_ids = Queue[str]()
+        self._max_cache_size = max_cache_size
+
+    def start(self, invoker: Invoker) -> None:
+        self._invoker = invoker
+        start_op = getattr(self._underlying_storage, "start", None)
+        if callable(start_op):
+            start_op(invoker)
+
+    def stop(self, invoker: Invoker) -> None:
+        self._invoker = invoker
+        stop_op = getattr(self._underlying_storage, "stop", None)
+        if callable(stop_op):
+            stop_op(invoker)
+
+    def load(self, name: str) -> T:
+        cache_item = self._get_cache(name)
+        if cache_item is not None:
+            return cache_item
+
+        latent = self._underlying_storage.load(name)
+        self._set_cache(name, latent)
+        return latent
+
+    def save(self, obj: T) -> str:
+        name = self._underlying_storage.save(obj)
+        self._set_cache(name, obj)
+        self._on_saved(name, obj)
+        return name
+
+    def delete(self, name: str) -> None:
+        self._underlying_storage.delete(name)
+        if name in self._cache:
+            del self._cache[name]
+        self._on_deleted(name)
+
+    def _get_cache(self, name: str) -> Optional[T]:
+        return None if name not in self._cache else self._cache[name]
+
+    def _set_cache(self, name: str, data: T):
+        if name not in self._cache:
+            self._cache[name] = data
+            self._cache_ids.put(name)
+            if self._cache_ids.qsize() > self._max_cache_size:
+                self._cache.pop(self._cache_ids.get())
diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index baff47a3df..8c5a821fd0 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -223,16 +223,16 @@ class TensorsInterface(InvocationContextInterface):
         :param tensor: The tensor to save.
         """
 
-        name = self._services.tensors.set(item=tensor)
-        return name
+        tensor_id = self._services.tensors.save(obj=tensor)
+        return tensor_id
 
-    def get(self, tensor_name: str) -> Tensor:
+    def load(self, name: str) -> Tensor:
         """
-        Gets a tensor by name.
+        Loads a tensor by name.
 
-        :param tensor_name: The name of the tensor to get.
+        :param name: The name of the tensor to load.
         """
-        return self._services.tensors.get(tensor_name)
+        return self._services.tensors.load(name)
 
 
 class ConditioningInterface(InvocationContextInterface):
@@ -243,17 +243,17 @@ class ConditioningInterface(InvocationContextInterface):
         :param conditioning_context_data: The conditioning data to save.
         """
 
-        name = self._services.conditioning.set(item=conditioning_data)
-        return name
+        conditioning_id = self._services.conditioning.save(obj=conditioning_data)
+        return conditioning_id
 
-    def get(self, conditioning_name: str) -> ConditioningFieldData:
+    def load(self, name: str) -> ConditioningFieldData:
         """
-        Gets conditioning data by name.
+        Loads conditioning data by name.
 
-        :param conditioning_name: The name of the conditioning data to get.
+        :param name: The name of the conditioning data to load.
         """
 
-        return self._services.conditioning.get(conditioning_name)
+        return self._services.conditioning.load(name)
 
 
 class ModelsInterface(InvocationContextInterface):

From 507aeac8a5be9891208569856e56cfc8fe007cdd Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 7 Feb 2024 23:43:22 +1100
Subject: [PATCH 082/411] tidy(nodes): remove object serializer on_saved

It's unused.
---
 .../services/object_serializer/object_serializer_base.py | 9 ---------
 .../object_serializer/object_serializer_forward_cache.py | 1 -
 2 files changed, 10 deletions(-)

diff --git a/invokeai/app/services/object_serializer/object_serializer_base.py b/invokeai/app/services/object_serializer/object_serializer_base.py
index b01a641d8f..ff19b4a039 100644
--- a/invokeai/app/services/object_serializer/object_serializer_base.py
+++ b/invokeai/app/services/object_serializer/object_serializer_base.py
@@ -8,7 +8,6 @@ class ObjectSerializerBase(ABC, Generic[T]):
     """Saves and loads arbitrary python objects."""
 
     def __init__(self) -> None:
-        self._on_saved_callbacks: list[Callable[[str, T], None]] = []
         self._on_deleted_callbacks: list[Callable[[str], None]] = []
 
     @abstractmethod
@@ -36,18 +35,10 @@ class ObjectSerializerBase(ABC, Generic[T]):
         """
         pass
 
-    def on_saved(self, on_saved: Callable[[str, T], None]) -> None:
-        """Register a callback for when an object is saved"""
-        self._on_saved_callbacks.append(on_saved)
-
     def on_deleted(self, on_deleted: Callable[[str], None]) -> None:
         """Register a callback for when an object is deleted"""
         self._on_deleted_callbacks.append(on_deleted)
 
-    def _on_saved(self, name: str, obj: T) -> None:
-        for callback in self._on_saved_callbacks:
-            callback(name, obj)
-
     def _on_deleted(self, name: str) -> None:
         for callback in self._on_deleted_callbacks:
             callback(name)
diff --git a/invokeai/app/services/object_serializer/object_serializer_forward_cache.py b/invokeai/app/services/object_serializer/object_serializer_forward_cache.py
index 40e34e6540..2a4ecdd844 100644
--- a/invokeai/app/services/object_serializer/object_serializer_forward_cache.py
+++ b/invokeai/app/services/object_serializer/object_serializer_forward_cache.py
@@ -41,7 +41,6 @@ class ObjectSerializerForwardCache(ObjectSerializerBase[T]):
     def save(self, obj: T) -> str:
         name = self._underlying_storage.save(obj)
         self._set_cache(name, obj)
-        self._on_saved(name, obj)
         return name
 
     def delete(self, name: str) -> None:

From 23de78ec9f2ba8a700a7574853a7b4c5199ad4d7 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Thu, 8 Feb 2024 00:18:58 +1100
Subject: [PATCH 083/411] feat(nodes): allow `_delete_all` in obj serializer to
 be called at any time

`_delete_all` logged how many items it deleted, and had to be called _after_ service start bc it needed access to logger.

Move the logger call to the startup method and return the the deleted stats from `_delete_all`. This lets `_delete_all` be called at any time.
---
 .../object_serializer_ephemeral_disk.py       | 26 +++++++++++--------
 1 file changed, 15 insertions(+), 11 deletions(-)

diff --git a/invokeai/app/services/object_serializer/object_serializer_ephemeral_disk.py b/invokeai/app/services/object_serializer/object_serializer_ephemeral_disk.py
index afa868b157..9545d1714d 100644
--- a/invokeai/app/services/object_serializer/object_serializer_ephemeral_disk.py
+++ b/invokeai/app/services/object_serializer/object_serializer_ephemeral_disk.py
@@ -1,4 +1,5 @@
 import typing
+from dataclasses import dataclass
 from pathlib import Path
 from typing import Optional, TypeVar
 
@@ -12,6 +13,12 @@ from invokeai.app.util.misc import uuid_string
 T = TypeVar("T")
 
 
+@dataclass
+class DeleteAllResult:
+    deleted_count: int
+    freed_space_bytes: float
+
+
 class ObjectSerializerEphemeralDisk(ObjectSerializerBase[T]):
     """Provides a disk-backed ephemeral storage for arbitrary python objects. The storage is cleared at startup.
 
@@ -26,7 +33,12 @@ class ObjectSerializerEphemeralDisk(ObjectSerializerBase[T]):
 
     def start(self, invoker: Invoker) -> None:
         self._invoker = invoker
-        self._delete_all()
+        delete_all_result = self._delete_all()
+        if delete_all_result.deleted_count > 0:
+            freed_space_in_mb = round(delete_all_result.freed_space_bytes / 1024 / 1024, 2)
+            self._invoker.services.logger.info(
+                f"Deleted {delete_all_result.deleted_count} {self._obj_class_name} files (freed {freed_space_in_mb}MB)"
+            )
 
     def load(self, name: str) -> T:
         file_path = self._get_path(name)
@@ -58,18 +70,14 @@ class ObjectSerializerEphemeralDisk(ObjectSerializerBase[T]):
     def _new_name(self) -> str:
         return f"{self._obj_class_name}_{uuid_string()}"
 
-    def _delete_all(self) -> None:
+    def _delete_all(self) -> DeleteAllResult:
         """
         Deletes all objects from disk.
-        Must be called after we have access to `self._invoker` (e.g. in `start()`).
         """
 
         # We could try using a temporary directory here, but they aren't cleared in the event of a crash, so we'd have
         # to manually clear them on startup anyways. This is a bit simpler and more reliable.
 
-        if not self._invoker:
-            raise ValueError("Invoker is not set. Must call `start()` first.")
-
         deleted_count = 0
         freed_space = 0
         for file in Path(self._output_dir).glob("*"):
@@ -77,8 +85,4 @@ class ObjectSerializerEphemeralDisk(ObjectSerializerBase[T]):
                 freed_space += file.stat().st_size
                 deleted_count += 1
                 file.unlink()
-        if deleted_count > 0:
-            freed_space_in_mb = round(freed_space / 1024 / 1024, 2)
-            self._invoker.services.logger.info(
-                f"Deleted {deleted_count} {self._obj_class_name} files (freed {freed_space_in_mb}MB)"
-            )
+        return DeleteAllResult(deleted_count, freed_space)

From 34d23366f4d61032994d267c6be315c5c75a4b1a Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Thu, 8 Feb 2024 00:20:10 +1100
Subject: [PATCH 084/411] tests: add object serializer tests

These test both object serializer and its forward cache implementation.
---
 .../test_object_serializer_ephemeral_disk.py  | 148 ++++++++++++++++++
 1 file changed, 148 insertions(+)
 create mode 100644 tests/test_object_serializer_ephemeral_disk.py

diff --git a/tests/test_object_serializer_ephemeral_disk.py b/tests/test_object_serializer_ephemeral_disk.py
new file mode 100644
index 0000000000..fffa65304f
--- /dev/null
+++ b/tests/test_object_serializer_ephemeral_disk.py
@@ -0,0 +1,148 @@
+from dataclasses import dataclass
+from pathlib import Path
+
+import pytest
+import torch
+
+from invokeai.app.services.object_serializer.object_serializer_common import ObjectNotFoundError
+from invokeai.app.services.object_serializer.object_serializer_ephemeral_disk import ObjectSerializerEphemeralDisk
+from invokeai.app.services.object_serializer.object_serializer_forward_cache import ObjectSerializerForwardCache
+
+
+@dataclass
+class MockDataclass:
+    foo: str
+
+
+@pytest.fixture
+def obj_serializer(tmp_path: Path):
+    return ObjectSerializerEphemeralDisk[MockDataclass](tmp_path)
+
+
+@pytest.fixture
+def fwd_cache(tmp_path: Path):
+    return ObjectSerializerForwardCache(ObjectSerializerEphemeralDisk[MockDataclass](tmp_path), max_cache_size=2)
+
+
+def test_obj_serializer_ephemeral_disk_initializes(tmp_path: Path):
+    obj_serializer = ObjectSerializerEphemeralDisk[MockDataclass](tmp_path)
+    assert obj_serializer._output_dir == tmp_path
+
+
+def test_obj_serializer_ephemeral_disk_saves(obj_serializer: ObjectSerializerEphemeralDisk[MockDataclass]):
+    obj_1 = MockDataclass(foo="bar")
+    obj_1_name = obj_serializer.save(obj_1)
+    assert Path(obj_serializer._output_dir, obj_1_name).exists()
+
+    obj_2 = MockDataclass(foo="baz")
+    obj_2_name = obj_serializer.save(obj_2)
+    assert Path(obj_serializer._output_dir, obj_2_name).exists()
+
+
+def test_obj_serializer_ephemeral_disk_loads(obj_serializer: ObjectSerializerEphemeralDisk[MockDataclass]):
+    obj_1 = MockDataclass(foo="bar")
+    obj_1_name = obj_serializer.save(obj_1)
+    assert obj_serializer.load(obj_1_name).foo == "bar"
+
+    obj_2 = MockDataclass(foo="baz")
+    obj_2_name = obj_serializer.save(obj_2)
+    assert obj_serializer.load(obj_2_name).foo == "baz"
+
+    with pytest.raises(ObjectNotFoundError):
+        obj_serializer.load("nonexistent_object_name")
+
+
+def test_obj_serializer_ephemeral_disk_deletes(obj_serializer: ObjectSerializerEphemeralDisk[MockDataclass]):
+    obj_1 = MockDataclass(foo="bar")
+    obj_1_name = obj_serializer.save(obj_1)
+
+    obj_2 = MockDataclass(foo="bar")
+    obj_2_name = obj_serializer.save(obj_2)
+
+    obj_serializer.delete(obj_1_name)
+    assert not Path(obj_serializer._output_dir, obj_1_name).exists()
+    assert Path(obj_serializer._output_dir, obj_2_name).exists()
+
+
+def test_obj_serializer_ephemeral_disk_deletes_all(obj_serializer: ObjectSerializerEphemeralDisk[MockDataclass]):
+    obj_1 = MockDataclass(foo="bar")
+    obj_1_name = obj_serializer.save(obj_1)
+
+    obj_2 = MockDataclass(foo="bar")
+    obj_2_name = obj_serializer.save(obj_2)
+
+    delete_all_result = obj_serializer._delete_all()
+
+    assert not Path(obj_serializer._output_dir, obj_1_name).exists()
+    assert not Path(obj_serializer._output_dir, obj_2_name).exists()
+    assert delete_all_result.deleted_count == 2
+
+
+def test_obj_serializer_ephemeral_disk_different_types(tmp_path: Path):
+    obj_serializer = ObjectSerializerEphemeralDisk[MockDataclass](tmp_path)
+
+    obj_1 = MockDataclass(foo="bar")
+    obj_1_name = obj_serializer.save(obj_1)
+    obj_1_loaded = obj_serializer.load(obj_1_name)
+    assert isinstance(obj_1_loaded, MockDataclass)
+    assert obj_1_loaded.foo == "bar"
+    assert obj_1_name.startswith("MockDataclass_")
+
+    obj_serializer = ObjectSerializerEphemeralDisk[int](tmp_path)
+    obj_2_name = obj_serializer.save(9001)
+    assert obj_serializer.load(obj_2_name) == 9001
+    assert obj_2_name.startswith("int_")
+
+    obj_serializer = ObjectSerializerEphemeralDisk[str](tmp_path)
+    obj_3_name = obj_serializer.save("foo")
+    assert obj_serializer.load(obj_3_name) == "foo"
+    assert obj_3_name.startswith("str_")
+
+    obj_serializer = ObjectSerializerEphemeralDisk[torch.Tensor](tmp_path)
+    obj_4_name = obj_serializer.save(torch.tensor([1, 2, 3]))
+    obj_4_loaded = obj_serializer.load(obj_4_name)
+    assert isinstance(obj_4_loaded, torch.Tensor)
+    assert torch.equal(obj_4_loaded, torch.tensor([1, 2, 3]))
+    assert obj_4_name.startswith("Tensor_")
+
+
+def test_obj_serializer_fwd_cache_initializes(obj_serializer: ObjectSerializerEphemeralDisk[MockDataclass]):
+    fwd_cache = ObjectSerializerForwardCache(obj_serializer)
+    assert fwd_cache._underlying_storage == obj_serializer
+
+
+def test_obj_serializer_fwd_cache_saves_and_loads(fwd_cache: ObjectSerializerForwardCache[MockDataclass]):
+    obj = MockDataclass(foo="bar")
+    obj_name = fwd_cache.save(obj)
+    obj_loaded = fwd_cache.load(obj_name)
+    obj_underlying = fwd_cache._underlying_storage.load(obj_name)
+    assert obj_loaded == obj_underlying
+    assert obj_loaded.foo == "bar"
+
+
+def test_obj_serializer_fwd_cache_respects_cache_size(fwd_cache: ObjectSerializerForwardCache[MockDataclass]):
+    obj_1 = MockDataclass(foo="bar")
+    obj_1_name = fwd_cache.save(obj_1)
+    obj_2 = MockDataclass(foo="baz")
+    obj_2_name = fwd_cache.save(obj_2)
+    obj_3 = MockDataclass(foo="qux")
+    obj_3_name = fwd_cache.save(obj_3)
+    assert obj_1_name not in fwd_cache._cache
+    assert obj_2_name in fwd_cache._cache
+    assert obj_3_name in fwd_cache._cache
+    # apparently qsize is "not reliable"?
+    assert fwd_cache._cache_ids.qsize() == 2
+
+
+def test_obj_serializer_fwd_cache_calls_delete_callback(fwd_cache: ObjectSerializerForwardCache[MockDataclass]):
+    called_name = None
+    obj_1 = MockDataclass(foo="bar")
+
+    def on_deleted(name: str):
+        nonlocal called_name
+        called_name = name
+
+    fwd_cache.on_deleted(on_deleted)
+    obj_1_name = fwd_cache.save(obj_1)
+    fwd_cache.delete(obj_1_name)
+    assert called_name == obj_1_name

From aff44c0e58b027eecf1d6e06941f55b95761ee9e Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Thu, 8 Feb 2024 00:23:47 +1100
Subject: [PATCH 085/411] tidy(nodes): minor spelling correction

---
 invokeai/app/services/shared/invocation_context.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index 8c5a821fd0..828d3d8490 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -223,8 +223,8 @@ class TensorsInterface(InvocationContextInterface):
         :param tensor: The tensor to save.
         """
 
-        tensor_id = self._services.tensors.save(obj=tensor)
-        return tensor_id
+        name = self._services.tensors.save(obj=tensor)
+        return name
 
     def load(self, name: str) -> Tensor:
         """
@@ -243,8 +243,8 @@ class ConditioningInterface(InvocationContextInterface):
         :param conditioning_context_data: The conditioning data to save.
         """
 
-        conditioning_id = self._services.conditioning.save(obj=conditioning_data)
-        return conditioning_id
+        name = self._services.conditioning.save(obj=conditioning_data)
+        return name
 
     def load(self, name: str) -> ConditioningFieldData:
         """

From 6d25789705cdb8aa3b095be499e838539b33768b Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Thu, 8 Feb 2024 00:36:53 +1100
Subject: [PATCH 086/411] tests: fix broken tests

---
 .../object_serializer_ephemeral_disk.py                |  9 ++++++---
 .../object_serializer_forward_cache.py                 | 10 ++++++----
 tests/aa_nodes/test_graph_execution_state.py           |  5 +++--
 tests/aa_nodes/test_invoker.py                         |  3 ++-
 4 files changed, 17 insertions(+), 10 deletions(-)

diff --git a/invokeai/app/services/object_serializer/object_serializer_ephemeral_disk.py b/invokeai/app/services/object_serializer/object_serializer_ephemeral_disk.py
index 9545d1714d..880848a142 100644
--- a/invokeai/app/services/object_serializer/object_serializer_ephemeral_disk.py
+++ b/invokeai/app/services/object_serializer/object_serializer_ephemeral_disk.py
@@ -1,15 +1,18 @@
 import typing
 from dataclasses import dataclass
 from pathlib import Path
-from typing import Optional, TypeVar
+from typing import TYPE_CHECKING, Optional, TypeVar
 
 import torch
 
-from invokeai.app.services.invoker import Invoker
 from invokeai.app.services.object_serializer.object_serializer_base import ObjectSerializerBase
 from invokeai.app.services.object_serializer.object_serializer_common import ObjectNotFoundError
 from invokeai.app.util.misc import uuid_string
 
+if TYPE_CHECKING:
+    from invokeai.app.services.invoker import Invoker
+
+
 T = TypeVar("T")
 
 
@@ -31,7 +34,7 @@ class ObjectSerializerEphemeralDisk(ObjectSerializerBase[T]):
         self._output_dir.mkdir(parents=True, exist_ok=True)
         self.__obj_class_name: Optional[str] = None
 
-    def start(self, invoker: Invoker) -> None:
+    def start(self, invoker: "Invoker") -> None:
         self._invoker = invoker
         delete_all_result = self._delete_all()
         if delete_all_result.deleted_count > 0:
diff --git a/invokeai/app/services/object_serializer/object_serializer_forward_cache.py b/invokeai/app/services/object_serializer/object_serializer_forward_cache.py
index 2a4ecdd844..c8ca13982c 100644
--- a/invokeai/app/services/object_serializer/object_serializer_forward_cache.py
+++ b/invokeai/app/services/object_serializer/object_serializer_forward_cache.py
@@ -1,11 +1,13 @@
 from queue import Queue
-from typing import Optional, TypeVar
+from typing import TYPE_CHECKING, Optional, TypeVar
 
-from invokeai.app.services.invoker import Invoker
 from invokeai.app.services.object_serializer.object_serializer_base import ObjectSerializerBase
 
 T = TypeVar("T")
 
+if TYPE_CHECKING:
+    from invokeai.app.services.invoker import Invoker
+
 
 class ObjectSerializerForwardCache(ObjectSerializerBase[T]):
     """Provides a simple forward cache for an underlying storage. The cache is LRU and has a maximum size."""
@@ -17,13 +19,13 @@ class ObjectSerializerForwardCache(ObjectSerializerBase[T]):
         self._cache_ids = Queue[str]()
         self._max_cache_size = max_cache_size
 
-    def start(self, invoker: Invoker) -> None:
+    def start(self, invoker: "Invoker") -> None:
         self._invoker = invoker
         start_op = getattr(self._underlying_storage, "start", None)
         if callable(start_op):
             start_op(invoker)
 
-    def stop(self, invoker: Invoker) -> None:
+    def stop(self, invoker: "Invoker") -> None:
         self._invoker = invoker
         stop_op = getattr(self._underlying_storage, "stop", None)
         if callable(stop_op):
diff --git a/tests/aa_nodes/test_graph_execution_state.py b/tests/aa_nodes/test_graph_execution_state.py
index aba7c5694f..27d2d2230a 100644
--- a/tests/aa_nodes/test_graph_execution_state.py
+++ b/tests/aa_nodes/test_graph_execution_state.py
@@ -60,7 +60,6 @@ def mock_services() -> InvocationServices:
         image_records=None,  # type: ignore
         images=None,  # type: ignore
         invocation_cache=MemoryInvocationCache(max_cache_size=0),
-        latents=None,  # type: ignore
         logger=logging,  # type: ignore
         model_manager=None,  # type: ignore
         model_records=None,  # type: ignore
@@ -74,6 +73,8 @@ def mock_services() -> InvocationServices:
         session_queue=None,  # type: ignore
         urls=None,  # type: ignore
         workflow_records=None,  # type: ignore
+        tensors=None,
+        conditioning=None,
     )
 
 
@@ -89,7 +90,7 @@ def invoke_next(g: GraphExecutionState, services: InvocationServices) -> tuple[B
             config=None,
             context_data=None,
             images=None,
-            latents=None,
+            tensors=None,
             logger=None,
             models=None,
             util=None,
diff --git a/tests/aa_nodes/test_invoker.py b/tests/aa_nodes/test_invoker.py
index 2ae4eab58a..437ea0f00d 100644
--- a/tests/aa_nodes/test_invoker.py
+++ b/tests/aa_nodes/test_invoker.py
@@ -63,7 +63,6 @@ def mock_services() -> InvocationServices:
         image_records=None,  # type: ignore
         images=None,  # type: ignore
         invocation_cache=MemoryInvocationCache(max_cache_size=0),
-        latents=None,  # type: ignore
         logger=logging,  # type: ignore
         model_manager=None,  # type: ignore
         model_records=None,  # type: ignore
@@ -77,6 +76,8 @@ def mock_services() -> InvocationServices:
         session_queue=None,  # type: ignore
         urls=None,  # type: ignore
         workflow_records=None,  # type: ignore
+        tensors=None,
+        conditioning=None,
     )
 
 

From e08f16763b6938f249faf54ed44baf1c89b00265 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Thu, 8 Feb 2024 07:55:36 +1100
Subject: [PATCH 087/411] feat(nodes): use LATENT_SCALE_FACTOR const in tensor
 output builders

---
 invokeai/app/invocations/noise.py      | 5 +++--
 invokeai/app/invocations/primitives.py | 5 +++--
 2 files changed, 6 insertions(+), 4 deletions(-)

diff --git a/invokeai/app/invocations/noise.py b/invokeai/app/invocations/noise.py
index 74b3d6e4cb..4093030388 100644
--- a/invokeai/app/invocations/noise.py
+++ b/invokeai/app/invocations/noise.py
@@ -5,6 +5,7 @@ import torch
 from pydantic import field_validator
 
 from invokeai.app.invocations.fields import FieldDescriptions, InputField, LatentsField, OutputField
+from invokeai.app.invocations.latent import LATENT_SCALE_FACTOR
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.app.util.misc import SEED_MAX
 
@@ -70,8 +71,8 @@ class NoiseOutput(BaseInvocationOutput):
     def build(cls, latents_name: str, latents: torch.Tensor, seed: int) -> "NoiseOutput":
         return cls(
             noise=LatentsField(latents_name=latents_name, seed=seed),
-            width=latents.size()[3] * 8,
-            height=latents.size()[2] * 8,
+            width=latents.size()[3] * LATENT_SCALE_FACTOR,
+            height=latents.size()[2] * LATENT_SCALE_FACTOR,
         )
 
 
diff --git a/invokeai/app/invocations/primitives.py b/invokeai/app/invocations/primitives.py
index d0f95c92d0..2a9cb8cf9b 100644
--- a/invokeai/app/invocations/primitives.py
+++ b/invokeai/app/invocations/primitives.py
@@ -16,6 +16,7 @@ from invokeai.app.invocations.fields import (
     OutputField,
     UIComponent,
 )
+from invokeai.app.invocations.latent import LATENT_SCALE_FACTOR
 from invokeai.app.services.images.images_common import ImageDTO
 from invokeai.app.services.shared.invocation_context import InvocationContext
 
@@ -321,8 +322,8 @@ class LatentsOutput(BaseInvocationOutput):
     def build(cls, latents_name: str, latents: torch.Tensor, seed: Optional[int] = None) -> "LatentsOutput":
         return cls(
             latents=LatentsField(latents_name=latents_name, seed=seed),
-            width=latents.size()[3] * 8,
-            height=latents.size()[2] * 8,
+            width=latents.size()[3] * LATENT_SCALE_FACTOR,
+            height=latents.size()[2] * LATENT_SCALE_FACTOR,
         )
 
 

From 220baae7937063cf61314a7c37c909b8c983bf8b Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Thu, 8 Feb 2024 08:14:04 +1100
Subject: [PATCH 088/411] Revert "feat(nodes): use LATENT_SCALE_FACTOR const in
 tensor output builders"

This reverts commit ef18fc546560277302f3886e456da9a47e8edce0.
---
 invokeai/app/invocations/noise.py      | 5 ++---
 invokeai/app/invocations/primitives.py | 5 ++---
 2 files changed, 4 insertions(+), 6 deletions(-)

diff --git a/invokeai/app/invocations/noise.py b/invokeai/app/invocations/noise.py
index 4093030388..74b3d6e4cb 100644
--- a/invokeai/app/invocations/noise.py
+++ b/invokeai/app/invocations/noise.py
@@ -5,7 +5,6 @@ import torch
 from pydantic import field_validator
 
 from invokeai.app.invocations.fields import FieldDescriptions, InputField, LatentsField, OutputField
-from invokeai.app.invocations.latent import LATENT_SCALE_FACTOR
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.app.util.misc import SEED_MAX
 
@@ -71,8 +70,8 @@ class NoiseOutput(BaseInvocationOutput):
     def build(cls, latents_name: str, latents: torch.Tensor, seed: int) -> "NoiseOutput":
         return cls(
             noise=LatentsField(latents_name=latents_name, seed=seed),
-            width=latents.size()[3] * LATENT_SCALE_FACTOR,
-            height=latents.size()[2] * LATENT_SCALE_FACTOR,
+            width=latents.size()[3] * 8,
+            height=latents.size()[2] * 8,
         )
 
 
diff --git a/invokeai/app/invocations/primitives.py b/invokeai/app/invocations/primitives.py
index 2a9cb8cf9b..d0f95c92d0 100644
--- a/invokeai/app/invocations/primitives.py
+++ b/invokeai/app/invocations/primitives.py
@@ -16,7 +16,6 @@ from invokeai.app.invocations.fields import (
     OutputField,
     UIComponent,
 )
-from invokeai.app.invocations.latent import LATENT_SCALE_FACTOR
 from invokeai.app.services.images.images_common import ImageDTO
 from invokeai.app.services.shared.invocation_context import InvocationContext
 
@@ -322,8 +321,8 @@ class LatentsOutput(BaseInvocationOutput):
     def build(cls, latents_name: str, latents: torch.Tensor, seed: Optional[int] = None) -> "LatentsOutput":
         return cls(
             latents=LatentsField(latents_name=latents_name, seed=seed),
-            width=latents.size()[3] * LATENT_SCALE_FACTOR,
-            height=latents.size()[2] * LATENT_SCALE_FACTOR,
+            width=latents.size()[3] * 8,
+            height=latents.size()[2] * 8,
         )
 
 

From 1655061c968fa2b2d2b566c7dcbf471dca759db6 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Thu, 8 Feb 2024 10:57:01 +1100
Subject: [PATCH 089/411] tidy(nodes): clarify comment

---
 invokeai/app/services/shared/invocation_context.py | 11 ++---------
 1 file changed, 2 insertions(+), 9 deletions(-)

diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index 828d3d8490..3d06cf9272 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -279,15 +279,8 @@ class ModelsInterface(InvocationContextInterface):
         :param submodel: The submodel of the model to get.
         """
 
-        # During this call, the model manager emits events with model loading status. The model
-        # manager itself has access to the events services, but does not have access to the
-        # required metadata for the events.
-        #
-        # For example, it needs access to the node's ID so that the events can be associated
-        # with the execution of a specific node.
-        #
-        # While this is available within the node, it's tedious to need to pass it in on every
-        # call. We can avoid that by wrapping the method here.
+        # The model manager emits events as it loads the model. It needs the context data to build
+        # the event payloads.
 
         return self._services.model_manager.get_model(
             model_name, base_model, model_type, submodel, context_data=self._context_data

From 091f4cb58321001b63969d6af8608ec9f67c38c2 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Thu, 8 Feb 2024 11:05:33 +1100
Subject: [PATCH 090/411] fix(nodes): use `metadata`/`board_id` if provided by
 user, overriding `WithMetadata`/`WithBoard`-provided values

---
 .../app/services/shared/invocation_context.py | 21 +++++++++++--------
 1 file changed, 12 insertions(+), 9 deletions(-)

diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index 3d06cf9272..1ca44b7862 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -167,16 +167,19 @@ class ImagesInterface(InvocationContextInterface):
             **Use this only if you want to override or provide metadata manually!**
         """
 
-        # If the invocation inherits metadata, use that. Else, use the metadata passed in.
-        metadata_ = (
-            self._context_data.invocation.metadata
-            if isinstance(self._context_data.invocation, WithMetadata)
-            else metadata
-        )
+        # If `metadata` is provided directly, use that. Else, use the metadata provided by `WithMetadata`, falling back to None.
+        metadata_ = None
+        if metadata:
+            metadata_ = metadata
+        elif isinstance(self._context_data.invocation, WithMetadata):
+            metadata_ = self._context_data.invocation.metadata
 
-        # If the invocation inherits WithBoard, use that. Else, use the board_id passed in.
-        board_ = self._context_data.invocation.board if isinstance(self._context_data.invocation, WithBoard) else None
-        board_id_ = board_.board_id if board_ is not None else board_id
+        # If `board_id` is provided directly, use that. Else, use the board provided by `WithBoard`, falling back to None.
+        board_id_ = None
+        if board_id:
+            board_id_ = board_id
+        elif isinstance(self._context_data.invocation, WithBoard) and self._context_data.invocation.board:
+            board_id_ = self._context_data.invocation.board.board_id
 
         return self._services.images.create(
             image=image,

From 9edb99564738ceb9cf571610b0fa59ee16a8ba4d Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Thu, 8 Feb 2024 16:09:59 +1100
Subject: [PATCH 091/411] feat(nodes): make delete on startup configurable for
 obj serializer

- The default is to not delete on startup - feels safer.
- The two services using this class _do_ delete on startup.
- The class has "ephemeral" removed from its name.
- Tests & app updated for this change.
---
 invokeai/app/api/dependencies.py              |  8 ++-
 ...eral_disk.py => object_serializer_disk.py} | 22 ++++---
 ...disk.py => test_object_serializer_disk.py} | 64 ++++++++++++++-----
 3 files changed, 67 insertions(+), 27 deletions(-)
 rename invokeai/app/services/object_serializer/{object_serializer_ephemeral_disk.py => object_serializer_disk.py} (77%)
 rename tests/{test_object_serializer_ephemeral_disk.py => test_object_serializer_disk.py} (65%)

diff --git a/invokeai/app/api/dependencies.py b/invokeai/app/api/dependencies.py
index 0c80494616..2acb961aa7 100644
--- a/invokeai/app/api/dependencies.py
+++ b/invokeai/app/api/dependencies.py
@@ -5,7 +5,7 @@ from logging import Logger
 import torch
 
 from invokeai.app.services.item_storage.item_storage_memory import ItemStorageMemory
-from invokeai.app.services.object_serializer.object_serializer_ephemeral_disk import ObjectSerializerEphemeralDisk
+from invokeai.app.services.object_serializer.object_serializer_disk import ObjectSerializerDisk
 from invokeai.app.services.object_serializer.object_serializer_forward_cache import ObjectSerializerForwardCache
 from invokeai.app.services.shared.sqlite.sqlite_util import init_db
 from invokeai.backend.model_manager.metadata import ModelMetadataStore
@@ -90,9 +90,11 @@ class ApiDependencies:
         image_records = SqliteImageRecordStorage(db=db)
         images = ImageService()
         invocation_cache = MemoryInvocationCache(max_cache_size=config.node_cache_size)
-        tensors = ObjectSerializerForwardCache(ObjectSerializerEphemeralDisk[torch.Tensor](output_folder / "tensors"))
+        tensors = ObjectSerializerForwardCache(
+            ObjectSerializerDisk[torch.Tensor](output_folder / "tensors", delete_on_startup=True)
+        )
         conditioning = ObjectSerializerForwardCache(
-            ObjectSerializerEphemeralDisk[ConditioningFieldData](output_folder / "conditioning")
+            ObjectSerializerDisk[ConditioningFieldData](output_folder / "conditioning", delete_on_startup=True)
         )
         model_manager = ModelManagerService(config, logger)
         model_record_service = ModelRecordServiceSQL(db=db)
diff --git a/invokeai/app/services/object_serializer/object_serializer_ephemeral_disk.py b/invokeai/app/services/object_serializer/object_serializer_disk.py
similarity index 77%
rename from invokeai/app/services/object_serializer/object_serializer_ephemeral_disk.py
rename to invokeai/app/services/object_serializer/object_serializer_disk.py
index 880848a142..174ff15192 100644
--- a/invokeai/app/services/object_serializer/object_serializer_ephemeral_disk.py
+++ b/invokeai/app/services/object_serializer/object_serializer_disk.py
@@ -22,26 +22,30 @@ class DeleteAllResult:
     freed_space_bytes: float
 
 
-class ObjectSerializerEphemeralDisk(ObjectSerializerBase[T]):
-    """Provides a disk-backed ephemeral storage for arbitrary python objects. The storage is cleared at startup.
+class ObjectSerializerDisk(ObjectSerializerBase[T]):
+    """Provides a disk-backed storage for arbitrary python objects.
 
     :param output_folder: The folder where the objects will be stored
+    :param delete_on_startup: If True, all objects in the output folder will be deleted on startup
     """
 
-    def __init__(self, output_dir: Path):
+    def __init__(self, output_dir: Path, delete_on_startup: bool = False):
         super().__init__()
         self._output_dir = output_dir
         self._output_dir.mkdir(parents=True, exist_ok=True)
+        self._delete_on_startup = delete_on_startup
         self.__obj_class_name: Optional[str] = None
 
     def start(self, invoker: "Invoker") -> None:
         self._invoker = invoker
-        delete_all_result = self._delete_all()
-        if delete_all_result.deleted_count > 0:
-            freed_space_in_mb = round(delete_all_result.freed_space_bytes / 1024 / 1024, 2)
-            self._invoker.services.logger.info(
-                f"Deleted {delete_all_result.deleted_count} {self._obj_class_name} files (freed {freed_space_in_mb}MB)"
-            )
+
+        if self._delete_on_startup:
+            delete_all_result = self._delete_all()
+            if delete_all_result.deleted_count > 0:
+                freed_space_in_mb = round(delete_all_result.freed_space_bytes / 1024 / 1024, 2)
+                self._invoker.services.logger.info(
+                    f"Deleted {delete_all_result.deleted_count} {self._obj_class_name} files (freed {freed_space_in_mb}MB)"
+                )
 
     def load(self, name: str) -> T:
         file_path = self._get_path(name)
diff --git a/tests/test_object_serializer_ephemeral_disk.py b/tests/test_object_serializer_disk.py
similarity index 65%
rename from tests/test_object_serializer_ephemeral_disk.py
rename to tests/test_object_serializer_disk.py
index fffa65304f..5ce1e57901 100644
--- a/tests/test_object_serializer_ephemeral_disk.py
+++ b/tests/test_object_serializer_disk.py
@@ -1,11 +1,14 @@
 from dataclasses import dataclass
+from logging import Logger
 from pathlib import Path
+from unittest.mock import Mock
 
 import pytest
 import torch
 
+from invokeai.app.services.invoker import Invoker
 from invokeai.app.services.object_serializer.object_serializer_common import ObjectNotFoundError
-from invokeai.app.services.object_serializer.object_serializer_ephemeral_disk import ObjectSerializerEphemeralDisk
+from invokeai.app.services.object_serializer.object_serializer_disk import ObjectSerializerDisk
 from invokeai.app.services.object_serializer.object_serializer_forward_cache import ObjectSerializerForwardCache
 
 
@@ -14,22 +17,31 @@ class MockDataclass:
     foo: str
 
 
+def count_files(path: Path):
+    return len(list(path.iterdir()))
+
+
 @pytest.fixture
 def obj_serializer(tmp_path: Path):
-    return ObjectSerializerEphemeralDisk[MockDataclass](tmp_path)
+    return ObjectSerializerDisk[MockDataclass](tmp_path)
 
 
 @pytest.fixture
 def fwd_cache(tmp_path: Path):
-    return ObjectSerializerForwardCache(ObjectSerializerEphemeralDisk[MockDataclass](tmp_path), max_cache_size=2)
+    return ObjectSerializerForwardCache(ObjectSerializerDisk[MockDataclass](tmp_path), max_cache_size=2)
 
 
-def test_obj_serializer_ephemeral_disk_initializes(tmp_path: Path):
-    obj_serializer = ObjectSerializerEphemeralDisk[MockDataclass](tmp_path)
+@pytest.fixture
+def mock_invoker_with_logger():
+    return Mock(Invoker, services=Mock(logger=Mock(Logger)))
+
+
+def test_obj_serializer_disk_initializes(tmp_path: Path):
+    obj_serializer = ObjectSerializerDisk[MockDataclass](tmp_path)
     assert obj_serializer._output_dir == tmp_path
 
 
-def test_obj_serializer_ephemeral_disk_saves(obj_serializer: ObjectSerializerEphemeralDisk[MockDataclass]):
+def test_obj_serializer_disk_saves(obj_serializer: ObjectSerializerDisk[MockDataclass]):
     obj_1 = MockDataclass(foo="bar")
     obj_1_name = obj_serializer.save(obj_1)
     assert Path(obj_serializer._output_dir, obj_1_name).exists()
@@ -39,7 +51,7 @@ def test_obj_serializer_ephemeral_disk_saves(obj_serializer: ObjectSerializerEph
     assert Path(obj_serializer._output_dir, obj_2_name).exists()
 
 
-def test_obj_serializer_ephemeral_disk_loads(obj_serializer: ObjectSerializerEphemeralDisk[MockDataclass]):
+def test_obj_serializer_disk_loads(obj_serializer: ObjectSerializerDisk[MockDataclass]):
     obj_1 = MockDataclass(foo="bar")
     obj_1_name = obj_serializer.save(obj_1)
     assert obj_serializer.load(obj_1_name).foo == "bar"
@@ -52,7 +64,7 @@ def test_obj_serializer_ephemeral_disk_loads(obj_serializer: ObjectSerializerEph
         obj_serializer.load("nonexistent_object_name")
 
 
-def test_obj_serializer_ephemeral_disk_deletes(obj_serializer: ObjectSerializerEphemeralDisk[MockDataclass]):
+def test_obj_serializer_disk_deletes(obj_serializer: ObjectSerializerDisk[MockDataclass]):
     obj_1 = MockDataclass(foo="bar")
     obj_1_name = obj_serializer.save(obj_1)
 
@@ -64,7 +76,7 @@ def test_obj_serializer_ephemeral_disk_deletes(obj_serializer: ObjectSerializerE
     assert Path(obj_serializer._output_dir, obj_2_name).exists()
 
 
-def test_obj_serializer_ephemeral_disk_deletes_all(obj_serializer: ObjectSerializerEphemeralDisk[MockDataclass]):
+def test_obj_serializer_disk_deletes_all(obj_serializer: ObjectSerializerDisk[MockDataclass]):
     obj_1 = MockDataclass(foo="bar")
     obj_1_name = obj_serializer.save(obj_1)
 
@@ -78,8 +90,30 @@ def test_obj_serializer_ephemeral_disk_deletes_all(obj_serializer: ObjectSeriali
     assert delete_all_result.deleted_count == 2
 
 
-def test_obj_serializer_ephemeral_disk_different_types(tmp_path: Path):
-    obj_serializer = ObjectSerializerEphemeralDisk[MockDataclass](tmp_path)
+def test_obj_serializer_disk_default_no_delete_on_startup(tmp_path: Path, mock_invoker_with_logger: Invoker):
+    obj_serializer = ObjectSerializerDisk[MockDataclass](tmp_path)
+    assert obj_serializer._delete_on_startup is False
+
+    obj_1 = MockDataclass(foo="bar")
+    obj_1_name = obj_serializer.save(obj_1)
+
+    obj_serializer.start(mock_invoker_with_logger)
+    assert Path(tmp_path, obj_1_name).exists()
+
+
+def test_obj_serializer_disk_delete_on_startup(tmp_path: Path, mock_invoker_with_logger: Invoker):
+    obj_serializer = ObjectSerializerDisk[MockDataclass](tmp_path, delete_on_startup=True)
+    assert obj_serializer._delete_on_startup is True
+
+    obj_1 = MockDataclass(foo="bar")
+    obj_1_name = obj_serializer.save(obj_1)
+
+    obj_serializer.start(mock_invoker_with_logger)
+    assert not Path(tmp_path, obj_1_name).exists()
+
+
+def test_obj_serializer_disk_different_types(tmp_path: Path):
+    obj_serializer = ObjectSerializerDisk[MockDataclass](tmp_path)
 
     obj_1 = MockDataclass(foo="bar")
     obj_1_name = obj_serializer.save(obj_1)
@@ -88,17 +122,17 @@ def test_obj_serializer_ephemeral_disk_different_types(tmp_path: Path):
     assert obj_1_loaded.foo == "bar"
     assert obj_1_name.startswith("MockDataclass_")
 
-    obj_serializer = ObjectSerializerEphemeralDisk[int](tmp_path)
+    obj_serializer = ObjectSerializerDisk[int](tmp_path)
     obj_2_name = obj_serializer.save(9001)
     assert obj_serializer.load(obj_2_name) == 9001
     assert obj_2_name.startswith("int_")
 
-    obj_serializer = ObjectSerializerEphemeralDisk[str](tmp_path)
+    obj_serializer = ObjectSerializerDisk[str](tmp_path)
     obj_3_name = obj_serializer.save("foo")
     assert obj_serializer.load(obj_3_name) == "foo"
     assert obj_3_name.startswith("str_")
 
-    obj_serializer = ObjectSerializerEphemeralDisk[torch.Tensor](tmp_path)
+    obj_serializer = ObjectSerializerDisk[torch.Tensor](tmp_path)
     obj_4_name = obj_serializer.save(torch.tensor([1, 2, 3]))
     obj_4_loaded = obj_serializer.load(obj_4_name)
     assert isinstance(obj_4_loaded, torch.Tensor)
@@ -106,7 +140,7 @@ def test_obj_serializer_ephemeral_disk_different_types(tmp_path: Path):
     assert obj_4_name.startswith("Tensor_")
 
 
-def test_obj_serializer_fwd_cache_initializes(obj_serializer: ObjectSerializerEphemeralDisk[MockDataclass]):
+def test_obj_serializer_fwd_cache_initializes(obj_serializer: ObjectSerializerDisk[MockDataclass]):
     fwd_cache = ObjectSerializerForwardCache(obj_serializer)
     assert fwd_cache._underlying_storage == obj_serializer
 

From a9b1aad3d79d0c10a1d655c531b49ea87646d552 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 10 Feb 2024 09:41:23 +1100
Subject: [PATCH 092/411] tidy(nodes): do not store unnecessarily store invoker

---
 .../app/services/object_serializer/object_serializer_disk.py  | 4 +---
 1 file changed, 1 insertion(+), 3 deletions(-)

diff --git a/invokeai/app/services/object_serializer/object_serializer_disk.py b/invokeai/app/services/object_serializer/object_serializer_disk.py
index 174ff15192..b3827e16a9 100644
--- a/invokeai/app/services/object_serializer/object_serializer_disk.py
+++ b/invokeai/app/services/object_serializer/object_serializer_disk.py
@@ -37,13 +37,11 @@ class ObjectSerializerDisk(ObjectSerializerBase[T]):
         self.__obj_class_name: Optional[str] = None
 
     def start(self, invoker: "Invoker") -> None:
-        self._invoker = invoker
-
         if self._delete_on_startup:
             delete_all_result = self._delete_all()
             if delete_all_result.deleted_count > 0:
                 freed_space_in_mb = round(delete_all_result.freed_space_bytes / 1024 / 1024, 2)
-                self._invoker.services.logger.info(
+                invoker.services.logger.info(
                     f"Deleted {delete_all_result.deleted_count} {self._obj_class_name} files (freed {freed_space_in_mb}MB)"
                 )
 

From 6087ace4f10fb85815a398e8a01bb1287634b281 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 10 Feb 2024 10:06:50 +1100
Subject: [PATCH 093/411] tidy(nodes): "latents" -> "obj"

---
 .../object_serializer/object_serializer_forward_cache.py    | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/invokeai/app/services/object_serializer/object_serializer_forward_cache.py b/invokeai/app/services/object_serializer/object_serializer_forward_cache.py
index c8ca13982c..812731f456 100644
--- a/invokeai/app/services/object_serializer/object_serializer_forward_cache.py
+++ b/invokeai/app/services/object_serializer/object_serializer_forward_cache.py
@@ -36,9 +36,9 @@ class ObjectSerializerForwardCache(ObjectSerializerBase[T]):
         if cache_item is not None:
             return cache_item
 
-        latent = self._underlying_storage.load(name)
-        self._set_cache(name, latent)
-        return latent
+        obj = self._underlying_storage.load(name)
+        self._set_cache(name, obj)
+        return obj
 
     def save(self, obj: T) -> str:
         name = self._underlying_storage.save(obj)

From 66d0ec3f6ce770605ff78f848bb5dc9dc55a403f Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 10 Feb 2024 10:10:48 +1100
Subject: [PATCH 094/411] chore(nodes): fix pyright ignore

---
 .../app/services/object_serializer/object_serializer_disk.py    | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/invokeai/app/services/object_serializer/object_serializer_disk.py b/invokeai/app/services/object_serializer/object_serializer_disk.py
index b3827e16a9..06f86aa460 100644
--- a/invokeai/app/services/object_serializer/object_serializer_disk.py
+++ b/invokeai/app/services/object_serializer/object_serializer_disk.py
@@ -66,7 +66,7 @@ class ObjectSerializerDisk(ObjectSerializerBase[T]):
     def _obj_class_name(self) -> str:
         if not self.__obj_class_name:
             # `__orig_class__` is not available in the constructor for some technical, undoubtedly very pythonic reason
-            self.__obj_class_name = typing.get_args(self.__orig_class__)[0].__name__  # pyright: ignore [reportUnknownMemberType, reportGeneralTypeIssues]
+            self.__obj_class_name = typing.get_args(self.__orig_class__)[0].__name__  # pyright: ignore [reportUnknownMemberType, reportAttributeAccessIssue]
         return self.__obj_class_name
 
     def _get_path(self, name: str) -> Path:

From 670f2f75e9afee842f61e591388247d578ab6730 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 10 Feb 2024 10:11:31 +1100
Subject: [PATCH 095/411] chore(nodes): update ObjectSerializerForwardCache
 docstring

---
 .../object_serializer/object_serializer_forward_cache.py     | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/invokeai/app/services/object_serializer/object_serializer_forward_cache.py b/invokeai/app/services/object_serializer/object_serializer_forward_cache.py
index 812731f456..b361259a4b 100644
--- a/invokeai/app/services/object_serializer/object_serializer_forward_cache.py
+++ b/invokeai/app/services/object_serializer/object_serializer_forward_cache.py
@@ -10,7 +10,10 @@ if TYPE_CHECKING:
 
 
 class ObjectSerializerForwardCache(ObjectSerializerBase[T]):
-    """Provides a simple forward cache for an underlying storage. The cache is LRU and has a maximum size."""
+    """
+    Provides a LRU cache for an instance of `ObjectSerializerBase`.
+    Saving an object to the cache always writes through to the underlying storage.
+    """
 
     def __init__(self, underlying_storage: ObjectSerializerBase[T], max_cache_size: int = 20):
         super().__init__()

From 11f64dab38f74e8a6f26d173fcf6f7b5e97c152f Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 10 Feb 2024 18:46:51 +1100
Subject: [PATCH 096/411] tests: test ObjectSerializerDisk class name
 extraction

---
 tests/test_object_serializer_disk.py | 29 +++++++++++++++-------------
 1 file changed, 16 insertions(+), 13 deletions(-)

diff --git a/tests/test_object_serializer_disk.py b/tests/test_object_serializer_disk.py
index 5ce1e57901..2bc7e16937 100644
--- a/tests/test_object_serializer_disk.py
+++ b/tests/test_object_serializer_disk.py
@@ -113,28 +113,31 @@ def test_obj_serializer_disk_delete_on_startup(tmp_path: Path, mock_invoker_with
 
 
 def test_obj_serializer_disk_different_types(tmp_path: Path):
-    obj_serializer = ObjectSerializerDisk[MockDataclass](tmp_path)
-
+    obj_serializer_1 = ObjectSerializerDisk[MockDataclass](tmp_path)
     obj_1 = MockDataclass(foo="bar")
-    obj_1_name = obj_serializer.save(obj_1)
-    obj_1_loaded = obj_serializer.load(obj_1_name)
+    obj_1_name = obj_serializer_1.save(obj_1)
+    obj_1_loaded = obj_serializer_1.load(obj_1_name)
+    assert obj_serializer_1._obj_class_name == "MockDataclass"
     assert isinstance(obj_1_loaded, MockDataclass)
     assert obj_1_loaded.foo == "bar"
     assert obj_1_name.startswith("MockDataclass_")
 
-    obj_serializer = ObjectSerializerDisk[int](tmp_path)
-    obj_2_name = obj_serializer.save(9001)
-    assert obj_serializer.load(obj_2_name) == 9001
+    obj_serializer_2 = ObjectSerializerDisk[int](tmp_path)
+    obj_2_name = obj_serializer_2.save(9001)
+    assert obj_serializer_2._obj_class_name == "int"
+    assert obj_serializer_2.load(obj_2_name) == 9001
     assert obj_2_name.startswith("int_")
 
-    obj_serializer = ObjectSerializerDisk[str](tmp_path)
-    obj_3_name = obj_serializer.save("foo")
-    assert obj_serializer.load(obj_3_name) == "foo"
+    obj_serializer_3 = ObjectSerializerDisk[str](tmp_path)
+    obj_3_name = obj_serializer_3.save("foo")
+    assert obj_serializer_3._obj_class_name == "str"
+    assert obj_serializer_3.load(obj_3_name) == "foo"
     assert obj_3_name.startswith("str_")
 
-    obj_serializer = ObjectSerializerDisk[torch.Tensor](tmp_path)
-    obj_4_name = obj_serializer.save(torch.tensor([1, 2, 3]))
-    obj_4_loaded = obj_serializer.load(obj_4_name)
+    obj_serializer_4 = ObjectSerializerDisk[torch.Tensor](tmp_path)
+    obj_4_name = obj_serializer_4.save(torch.tensor([1, 2, 3]))
+    obj_4_loaded = obj_serializer_4.load(obj_4_name)
+    assert obj_serializer_4._obj_class_name == "Tensor"
     assert isinstance(obj_4_loaded, torch.Tensor)
     assert torch.equal(obj_4_loaded, torch.tensor([1, 2, 3]))
     assert obj_4_name.startswith("Tensor_")

From fece93543862a77a57a5363f46eab3088fb94a89 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 10 Feb 2024 19:11:28 +1100
Subject: [PATCH 097/411] feat(nodes): use TemporaryDirectory to handle
 ephemeral storage in ObjectSerializerDisk

Replace `delete_on_startup: bool` & associated logic with `ephemeral: bool` and `TemporaryDirectory`.

The temp dir is created inside of `output_dir`. For example, if `output_dir` is `invokeai/outputs/tensors/`, then the temp dir might be `invokeai/outputs/tensors/tmpvj35ht7b/`.

The temp dir is cleaned up when the service is stopped, or when it is GC'd if not properly stopped.

In the event of a catastrophic crash where the temp files are not cleaned up, the user can delete the tempdir themselves.

This situation may not occur in normal use, but if you kill the process, python cannot clean up the temp dir itself. This includes running the app in a debugger and killing the debugger process - something I do relatively often.

Tests updated.
---
 invokeai/app/api/dependencies.py              |  4 +-
 .../object_serializer_disk.py                 | 52 +++++++--------
 tests/test_object_serializer_disk.py          | 65 ++++++++-----------
 3 files changed, 50 insertions(+), 71 deletions(-)

diff --git a/invokeai/app/api/dependencies.py b/invokeai/app/api/dependencies.py
index 2acb961aa7..0f2a92b5c8 100644
--- a/invokeai/app/api/dependencies.py
+++ b/invokeai/app/api/dependencies.py
@@ -91,10 +91,10 @@ class ApiDependencies:
         images = ImageService()
         invocation_cache = MemoryInvocationCache(max_cache_size=config.node_cache_size)
         tensors = ObjectSerializerForwardCache(
-            ObjectSerializerDisk[torch.Tensor](output_folder / "tensors", delete_on_startup=True)
+            ObjectSerializerDisk[torch.Tensor](output_folder / "tensors", ephemeral=True)
         )
         conditioning = ObjectSerializerForwardCache(
-            ObjectSerializerDisk[ConditioningFieldData](output_folder / "conditioning", delete_on_startup=True)
+            ObjectSerializerDisk[ConditioningFieldData](output_folder / "conditioning", ephemeral=True)
         )
         model_manager = ModelManagerService(config, logger)
         model_record_service = ModelRecordServiceSQL(db=db)
diff --git a/invokeai/app/services/object_serializer/object_serializer_disk.py b/invokeai/app/services/object_serializer/object_serializer_disk.py
index 06f86aa460..935fec3060 100644
--- a/invokeai/app/services/object_serializer/object_serializer_disk.py
+++ b/invokeai/app/services/object_serializer/object_serializer_disk.py
@@ -1,3 +1,4 @@
+import tempfile
 import typing
 from dataclasses import dataclass
 from pathlib import Path
@@ -23,28 +24,24 @@ class DeleteAllResult:
 
 
 class ObjectSerializerDisk(ObjectSerializerBase[T]):
-    """Provides a disk-backed storage for arbitrary python objects.
+    """Disk-backed storage for arbitrary python objects. Serialization is handled by `torch.save` and `torch.load`.
 
-    :param output_folder: The folder where the objects will be stored
-    :param delete_on_startup: If True, all objects in the output folder will be deleted on startup
+    :param output_dir: The folder where the serialized objects will be stored
+    :param ephemeral: If True, objects will be stored in a temporary directory inside the given output_dir and cleaned up on exit
     """
 
-    def __init__(self, output_dir: Path, delete_on_startup: bool = False):
+    def __init__(self, output_dir: Path, ephemeral: bool = False):
         super().__init__()
-        self._output_dir = output_dir
-        self._output_dir.mkdir(parents=True, exist_ok=True)
-        self._delete_on_startup = delete_on_startup
+        self._ephemeral = ephemeral
+        self._base_output_dir = output_dir
+        self._base_output_dir.mkdir(parents=True, exist_ok=True)
+        # Must specify `ignore_cleanup_errors` to avoid fatal errors during cleanup on Windows
+        self._tempdir = (
+            tempfile.TemporaryDirectory(dir=self._base_output_dir, ignore_cleanup_errors=True) if ephemeral else None
+        )
+        self._output_dir = Path(self._tempdir.name) if self._tempdir else self._base_output_dir
         self.__obj_class_name: Optional[str] = None
 
-    def start(self, invoker: "Invoker") -> None:
-        if self._delete_on_startup:
-            delete_all_result = self._delete_all()
-            if delete_all_result.deleted_count > 0:
-                freed_space_in_mb = round(delete_all_result.freed_space_bytes / 1024 / 1024, 2)
-                invoker.services.logger.info(
-                    f"Deleted {delete_all_result.deleted_count} {self._obj_class_name} files (freed {freed_space_in_mb}MB)"
-                )
-
     def load(self, name: str) -> T:
         file_path = self._get_path(name)
         try:
@@ -75,19 +72,14 @@ class ObjectSerializerDisk(ObjectSerializerBase[T]):
     def _new_name(self) -> str:
         return f"{self._obj_class_name}_{uuid_string()}"
 
-    def _delete_all(self) -> DeleteAllResult:
-        """
-        Deletes all objects from disk.
-        """
+    def _tempdir_cleanup(self) -> None:
+        """Calls `cleanup` on the temporary directory, if it exists."""
+        if self._tempdir:
+            self._tempdir.cleanup()
 
-        # We could try using a temporary directory here, but they aren't cleared in the event of a crash, so we'd have
-        # to manually clear them on startup anyways. This is a bit simpler and more reliable.
+    def __del__(self) -> None:
+        # In case the service is not properly stopped, clean up the temporary directory when the class instance is GC'd.
+        self._tempdir_cleanup()
 
-        deleted_count = 0
-        freed_space = 0
-        for file in Path(self._output_dir).glob("*"):
-            if file.is_file():
-                freed_space += file.stat().st_size
-                deleted_count += 1
-                file.unlink()
-        return DeleteAllResult(deleted_count, freed_space)
+    def stop(self, invoker: "Invoker") -> None:
+        self._tempdir_cleanup()
diff --git a/tests/test_object_serializer_disk.py b/tests/test_object_serializer_disk.py
index 2bc7e16937..125534c500 100644
--- a/tests/test_object_serializer_disk.py
+++ b/tests/test_object_serializer_disk.py
@@ -1,12 +1,10 @@
+import tempfile
 from dataclasses import dataclass
-from logging import Logger
 from pathlib import Path
-from unittest.mock import Mock
 
 import pytest
 import torch
 
-from invokeai.app.services.invoker import Invoker
 from invokeai.app.services.object_serializer.object_serializer_common import ObjectNotFoundError
 from invokeai.app.services.object_serializer.object_serializer_disk import ObjectSerializerDisk
 from invokeai.app.services.object_serializer.object_serializer_forward_cache import ObjectSerializerForwardCache
@@ -31,11 +29,6 @@ def fwd_cache(tmp_path: Path):
     return ObjectSerializerForwardCache(ObjectSerializerDisk[MockDataclass](tmp_path), max_cache_size=2)
 
 
-@pytest.fixture
-def mock_invoker_with_logger():
-    return Mock(Invoker, services=Mock(logger=Mock(Logger)))
-
-
 def test_obj_serializer_disk_initializes(tmp_path: Path):
     obj_serializer = ObjectSerializerDisk[MockDataclass](tmp_path)
     assert obj_serializer._output_dir == tmp_path
@@ -76,39 +69,33 @@ def test_obj_serializer_disk_deletes(obj_serializer: ObjectSerializerDisk[MockDa
     assert Path(obj_serializer._output_dir, obj_2_name).exists()
 
 
-def test_obj_serializer_disk_deletes_all(obj_serializer: ObjectSerializerDisk[MockDataclass]):
+def test_obj_serializer_ephemeral_creates_tempdir(tmp_path: Path):
+    obj_serializer = ObjectSerializerDisk[MockDataclass](tmp_path, ephemeral=True)
+    assert isinstance(obj_serializer._tempdir, tempfile.TemporaryDirectory)
+    assert obj_serializer._base_output_dir == tmp_path
+    assert obj_serializer._output_dir != tmp_path
+    assert obj_serializer._output_dir == Path(obj_serializer._tempdir.name)
+
+
+def test_obj_serializer_ephemeral_deletes_tempdir(tmp_path: Path):
+    obj_serializer = ObjectSerializerDisk[MockDataclass](tmp_path, ephemeral=True)
+    tempdir_path = obj_serializer._output_dir
+    del obj_serializer
+    assert not tempdir_path.exists()
+
+
+def test_obj_serializer_ephemeral_deletes_tempdir_on_stop(tmp_path: Path):
+    obj_serializer = ObjectSerializerDisk[MockDataclass](tmp_path, ephemeral=True)
+    tempdir_path = obj_serializer._output_dir
+    obj_serializer.stop(None)  # pyright: ignore [reportArgumentType]
+    assert not tempdir_path.exists()
+
+
+def test_obj_serializer_ephemeral_writes_to_tempdir(tmp_path: Path):
+    obj_serializer = ObjectSerializerDisk[MockDataclass](tmp_path, ephemeral=True)
     obj_1 = MockDataclass(foo="bar")
     obj_1_name = obj_serializer.save(obj_1)
-
-    obj_2 = MockDataclass(foo="bar")
-    obj_2_name = obj_serializer.save(obj_2)
-
-    delete_all_result = obj_serializer._delete_all()
-
-    assert not Path(obj_serializer._output_dir, obj_1_name).exists()
-    assert not Path(obj_serializer._output_dir, obj_2_name).exists()
-    assert delete_all_result.deleted_count == 2
-
-
-def test_obj_serializer_disk_default_no_delete_on_startup(tmp_path: Path, mock_invoker_with_logger: Invoker):
-    obj_serializer = ObjectSerializerDisk[MockDataclass](tmp_path)
-    assert obj_serializer._delete_on_startup is False
-
-    obj_1 = MockDataclass(foo="bar")
-    obj_1_name = obj_serializer.save(obj_1)
-
-    obj_serializer.start(mock_invoker_with_logger)
-    assert Path(tmp_path, obj_1_name).exists()
-
-
-def test_obj_serializer_disk_delete_on_startup(tmp_path: Path, mock_invoker_with_logger: Invoker):
-    obj_serializer = ObjectSerializerDisk[MockDataclass](tmp_path, delete_on_startup=True)
-    assert obj_serializer._delete_on_startup is True
-
-    obj_1 = MockDataclass(foo="bar")
-    obj_1_name = obj_serializer.save(obj_1)
-
-    obj_serializer.start(mock_invoker_with_logger)
+    assert Path(obj_serializer._output_dir, obj_1_name).exists()
     assert not Path(tmp_path, obj_1_name).exists()
 
 

From e5d8921cf276ea977fa5fe822f40113e01ff88ac Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sun, 11 Feb 2024 08:52:07 +1100
Subject: [PATCH 098/411] feat(nodes): extract LATENT_SCALE_FACTOR to
 constants.py

---
 invokeai/app/invocations/constants.py | 7 +++++++
 invokeai/app/invocations/latent.py    | 7 +------
 invokeai/backend/tiles/tiles.py       | 2 +-
 3 files changed, 9 insertions(+), 7 deletions(-)
 create mode 100644 invokeai/app/invocations/constants.py

diff --git a/invokeai/app/invocations/constants.py b/invokeai/app/invocations/constants.py
new file mode 100644
index 0000000000..95b16f0d05
--- /dev/null
+++ b/invokeai/app/invocations/constants.py
@@ -0,0 +1,7 @@
+LATENT_SCALE_FACTOR = 8
+"""
+HACK: Many nodes are currently hard-coded to use a fixed latent scale factor of 8. This is fragile, and will need to
+be addressed if future models use a different latent scale factor. Also, note that there may be places where the scale
+factor is hard-coded to a literal '8' rather than using this constant.
+The ratio of image:latent dimensions is LATENT_SCALE_FACTOR:1, or 8:1.
+"""
diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py
index 4137ab6e2f..fedfc38402 100644
--- a/invokeai/app/invocations/latent.py
+++ b/invokeai/app/invocations/latent.py
@@ -23,6 +23,7 @@ from diffusers.schedulers import SchedulerMixin as Scheduler
 from pydantic import field_validator
 from torchvision.transforms.functional import resize as tv_resize
 
+from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR
 from invokeai.app.invocations.fields import (
     ConditioningField,
     DenoiseMaskField,
@@ -79,12 +80,6 @@ DEFAULT_PRECISION = choose_precision(choose_torch_device())
 
 SAMPLER_NAME_VALUES = Literal[tuple(SCHEDULER_MAP.keys())]
 
-# HACK: Many nodes are currently hard-coded to use a fixed latent scale factor of 8. This is fragile, and will need to
-# be addressed if future models use a different latent scale factor. Also, note that there may be places where the scale
-# factor is hard-coded to a literal '8' rather than using this constant.
-# The ratio of image:latent dimensions is LATENT_SCALE_FACTOR:1, or 8:1.
-LATENT_SCALE_FACTOR = 8
-
 
 @invocation_output("scheduler_output")
 class SchedulerOutput(BaseInvocationOutput):
diff --git a/invokeai/backend/tiles/tiles.py b/invokeai/backend/tiles/tiles.py
index 3c400fc87c..2757dadba2 100644
--- a/invokeai/backend/tiles/tiles.py
+++ b/invokeai/backend/tiles/tiles.py
@@ -3,7 +3,7 @@ from typing import Union
 
 import numpy as np
 
-from invokeai.app.invocations.latent import LATENT_SCALE_FACTOR
+from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR
 from invokeai.backend.tiles.utils import TBLR, Tile, paste, seam_blend
 
 

From e0694a28563c1ef483984f210ebc6cf7b12feedd Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sun, 11 Feb 2024 08:54:01 +1100
Subject: [PATCH 099/411] feat(nodes): use LATENT_SCALE_FACTOR in
 primitives.py, noise.py

- LatentsOutput.build
- NoiseOutput.build
- Noise.width, Noise.height multiple_of
---
 invokeai/app/invocations/noise.py      | 9 +++++----
 invokeai/app/invocations/primitives.py | 5 +++--
 2 files changed, 8 insertions(+), 6 deletions(-)

diff --git a/invokeai/app/invocations/noise.py b/invokeai/app/invocations/noise.py
index 74b3d6e4cb..335d3df292 100644
--- a/invokeai/app/invocations/noise.py
+++ b/invokeai/app/invocations/noise.py
@@ -4,6 +4,7 @@
 import torch
 from pydantic import field_validator
 
+from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR
 from invokeai.app.invocations.fields import FieldDescriptions, InputField, LatentsField, OutputField
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.app.util.misc import SEED_MAX
@@ -70,8 +71,8 @@ class NoiseOutput(BaseInvocationOutput):
     def build(cls, latents_name: str, latents: torch.Tensor, seed: int) -> "NoiseOutput":
         return cls(
             noise=LatentsField(latents_name=latents_name, seed=seed),
-            width=latents.size()[3] * 8,
-            height=latents.size()[2] * 8,
+            width=latents.size()[3] * LATENT_SCALE_FACTOR,
+            height=latents.size()[2] * LATENT_SCALE_FACTOR,
         )
 
 
@@ -93,13 +94,13 @@ class NoiseInvocation(BaseInvocation):
     )
     width: int = InputField(
         default=512,
-        multiple_of=8,
+        multiple_of=LATENT_SCALE_FACTOR,
         gt=0,
         description=FieldDescriptions.width,
     )
     height: int = InputField(
         default=512,
-        multiple_of=8,
+        multiple_of=LATENT_SCALE_FACTOR,
         gt=0,
         description=FieldDescriptions.height,
     )
diff --git a/invokeai/app/invocations/primitives.py b/invokeai/app/invocations/primitives.py
index d0f95c92d0..4342213482 100644
--- a/invokeai/app/invocations/primitives.py
+++ b/invokeai/app/invocations/primitives.py
@@ -4,6 +4,7 @@ from typing import Optional
 
 import torch
 
+from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR
 from invokeai.app.invocations.fields import (
     ColorField,
     ConditioningField,
@@ -321,8 +322,8 @@ class LatentsOutput(BaseInvocationOutput):
     def build(cls, latents_name: str, latents: torch.Tensor, seed: Optional[int] = None) -> "LatentsOutput":
         return cls(
             latents=LatentsField(latents_name=latents_name, seed=seed),
-            width=latents.size()[3] * 8,
-            height=latents.size()[2] * 8,
+            width=latents.size()[3] * LATENT_SCALE_FACTOR,
+            height=latents.size()[2] * LATENT_SCALE_FACTOR,
         )
 
 

From 0f8af643d153b1f2d13c6d6c888e6fc83664fdd8 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sun, 11 Feb 2024 09:27:57 +1100
Subject: [PATCH 100/411] chore(backend): rename `ModelInfo` ->
 `LoadedModelInfo`

We have two different classes named `ModelInfo` which might need to be used by API consumers. We need to export both but have to deal with this naming collision.

The `ModelInfo` I've renamed here is the one that is returned when a model is loaded. It's the object least likely to be used by API consumers.
---
 invokeai/app/services/events/events_base.py      | 10 +++++-----
 .../services/model_manager/model_manager_base.py |  4 ++--
 .../model_manager/model_manager_default.py       | 16 ++++++++--------
 .../app/services/shared/invocation_context.py    |  7 ++++---
 invokeai/backend/__init__.py                     |  9 ++++++++-
 invokeai/backend/model_management/__init__.py    |  2 +-
 .../backend/model_management/model_manager.py    |  6 +++---
 invokeai/backend/util/test_utils.py              | 10 +++++-----
 invokeai/invocation_api/__init__.py              |  4 ++--
 9 files changed, 38 insertions(+), 30 deletions(-)

diff --git a/invokeai/app/services/events/events_base.py b/invokeai/app/services/events/events_base.py
index ad08ae0395..6b441efc2b 100644
--- a/invokeai/app/services/events/events_base.py
+++ b/invokeai/app/services/events/events_base.py
@@ -11,7 +11,7 @@ from invokeai.app.services.session_queue.session_queue_common import (
     SessionQueueStatus,
 )
 from invokeai.app.util.misc import get_timestamp
-from invokeai.backend.model_management.model_manager import ModelInfo
+from invokeai.backend.model_management.model_manager import LoadedModelInfo
 from invokeai.backend.model_management.models.base import BaseModelType, ModelType, SubModelType
 
 
@@ -201,7 +201,7 @@ class EventServiceBase:
         base_model: BaseModelType,
         model_type: ModelType,
         submodel: SubModelType,
-        model_info: ModelInfo,
+        loaded_model_info: LoadedModelInfo,
     ) -> None:
         """Emitted when a model is correctly loaded (returns model info)"""
         self.__emit_queue_event(
@@ -215,9 +215,9 @@ class EventServiceBase:
                 "base_model": base_model,
                 "model_type": model_type,
                 "submodel": submodel,
-                "hash": model_info.hash,
-                "location": str(model_info.location),
-                "precision": str(model_info.precision),
+                "hash": loaded_model_info.hash,
+                "location": str(loaded_model_info.location),
+                "precision": str(loaded_model_info.precision),
             },
         )
 
diff --git a/invokeai/app/services/model_manager/model_manager_base.py b/invokeai/app/services/model_manager/model_manager_base.py
index a9b53ae224..f888c0ec97 100644
--- a/invokeai/app/services/model_manager/model_manager_base.py
+++ b/invokeai/app/services/model_manager/model_manager_base.py
@@ -14,8 +14,8 @@ from invokeai.app.services.shared.invocation_context import InvocationContextDat
 from invokeai.backend.model_management import (
     AddModelResult,
     BaseModelType,
+    LoadedModelInfo,
     MergeInterpolationMethod,
-    ModelInfo,
     ModelType,
     SchedulerPredictionType,
     SubModelType,
@@ -48,7 +48,7 @@ class ModelManagerServiceBase(ABC):
         model_type: ModelType,
         submodel: Optional[SubModelType] = None,
         context_data: Optional[InvocationContextData] = None,
-    ) -> ModelInfo:
+    ) -> LoadedModelInfo:
         """Retrieve the indicated model with name and type.
         submodel can be used to get a part (such as the vae)
         of a diffusers pipeline."""
diff --git a/invokeai/app/services/model_manager/model_manager_default.py b/invokeai/app/services/model_manager/model_manager_default.py
index b641dd3f1e..c3712abf8e 100644
--- a/invokeai/app/services/model_manager/model_manager_default.py
+++ b/invokeai/app/services/model_manager/model_manager_default.py
@@ -16,8 +16,8 @@ from invokeai.app.services.shared.invocation_context import InvocationContextDat
 from invokeai.backend.model_management import (
     AddModelResult,
     BaseModelType,
+    LoadedModelInfo,
     MergeInterpolationMethod,
-    ModelInfo,
     ModelManager,
     ModelMerger,
     ModelNotFoundException,
@@ -98,7 +98,7 @@ class ModelManagerService(ModelManagerServiceBase):
         model_type: ModelType,
         submodel: Optional[SubModelType] = None,
         context_data: Optional[InvocationContextData] = None,
-    ) -> ModelInfo:
+    ) -> LoadedModelInfo:
         """
         Retrieve the indicated model. submodel can be used to get a
         part (such as the vae) of a diffusers mode.
@@ -114,7 +114,7 @@ class ModelManagerService(ModelManagerServiceBase):
                 submodel=submodel,
             )
 
-        model_info = self.mgr.get_model(
+        loaded_model_info = self.mgr.get_model(
             model_name,
             base_model,
             model_type,
@@ -128,10 +128,10 @@ class ModelManagerService(ModelManagerServiceBase):
                 base_model=base_model,
                 model_type=model_type,
                 submodel=submodel,
-                model_info=model_info,
+                loaded_model_info=loaded_model_info,
             )
 
-        return model_info
+        return loaded_model_info
 
     def model_exists(
         self,
@@ -273,7 +273,7 @@ class ModelManagerService(ModelManagerServiceBase):
         base_model: BaseModelType,
         model_type: ModelType,
         submodel: Optional[SubModelType] = None,
-        model_info: Optional[ModelInfo] = None,
+        loaded_model_info: Optional[LoadedModelInfo] = None,
     ):
         if self._invoker is None:
             return
@@ -281,7 +281,7 @@ class ModelManagerService(ModelManagerServiceBase):
         if self._invoker.services.queue.is_canceled(context_data.session_id):
             raise CanceledException()
 
-        if model_info:
+        if loaded_model_info:
             self._invoker.services.events.emit_model_load_completed(
                 queue_id=context_data.queue_id,
                 queue_item_id=context_data.queue_item_id,
@@ -291,7 +291,7 @@ class ModelManagerService(ModelManagerServiceBase):
                 base_model=base_model,
                 model_type=model_type,
                 submodel=submodel,
-                model_info=model_info,
+                loaded_model_info=loaded_model_info,
             )
         else:
             self._invoker.services.events.emit_model_load_started(
diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index 1ca44b7862..68fb78c143 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -13,7 +13,7 @@ from invokeai.app.services.images.images_common import ImageDTO
 from invokeai.app.services.invocation_services import InvocationServices
 from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID
 from invokeai.app.util.step_callback import stable_diffusion_step_callback
-from invokeai.backend.model_management.model_manager import ModelInfo
+from invokeai.backend.model_management.model_manager import LoadedModelInfo
 from invokeai.backend.model_management.models.base import BaseModelType, ModelType, SubModelType
 from invokeai.backend.stable_diffusion.diffusers_pipeline import PipelineIntermediateState
 from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ConditioningFieldData
@@ -272,14 +272,15 @@ class ModelsInterface(InvocationContextInterface):
 
     def load(
         self, model_name: str, base_model: BaseModelType, model_type: ModelType, submodel: Optional[SubModelType] = None
-    ) -> ModelInfo:
+    ) -> LoadedModelInfo:
         """
-        Loads a model, returning its `ModelInfo` object.
+        Loads a model.
 
         :param model_name: The name of the model to get.
         :param base_model: The base model of the model to get.
         :param model_type: The type of the model to get.
         :param submodel: The submodel of the model to get.
+        :returns: An object representing the loaded model.
         """
 
         # The model manager emits events as it loads the model. It needs the context data to build
diff --git a/invokeai/backend/__init__.py b/invokeai/backend/__init__.py
index ae9a12edbe..54a1843d46 100644
--- a/invokeai/backend/__init__.py
+++ b/invokeai/backend/__init__.py
@@ -1,5 +1,12 @@
 """
 Initialization file for invokeai.backend
 """
-from .model_management import BaseModelType, ModelCache, ModelInfo, ModelManager, ModelType, SubModelType  # noqa: F401
+from .model_management import (  # noqa: F401
+    BaseModelType,
+    LoadedModelInfo,
+    ModelCache,
+    ModelManager,
+    ModelType,
+    SubModelType,
+)
 from .model_management.models import SilenceWarnings  # noqa: F401
diff --git a/invokeai/backend/model_management/__init__.py b/invokeai/backend/model_management/__init__.py
index 03abf58eb4..d523a7a0c8 100644
--- a/invokeai/backend/model_management/__init__.py
+++ b/invokeai/backend/model_management/__init__.py
@@ -3,7 +3,7 @@
 Initialization file for invokeai.backend.model_management
 """
 # This import must be first
-from .model_manager import AddModelResult, ModelInfo, ModelManager, SchedulerPredictionType
+from .model_manager import AddModelResult, LoadedModelInfo, ModelManager, SchedulerPredictionType
 from .lora import ModelPatcher, ONNXModelPatcher
 from .model_cache import ModelCache
 
diff --git a/invokeai/backend/model_management/model_manager.py b/invokeai/backend/model_management/model_manager.py
index 362d8d3ff5..da74ca3fb5 100644
--- a/invokeai/backend/model_management/model_manager.py
+++ b/invokeai/backend/model_management/model_manager.py
@@ -271,7 +271,7 @@ CONFIG_FILE_VERSION = "3.0.0"
 
 
 @dataclass
-class ModelInfo:
+class LoadedModelInfo:
     context: ModelLocker
     name: str
     base_model: BaseModelType
@@ -450,7 +450,7 @@ class ModelManager(object):
         base_model: BaseModelType,
         model_type: ModelType,
         submodel_type: Optional[SubModelType] = None,
-    ) -> ModelInfo:
+    ) -> LoadedModelInfo:
         """Given a model named identified in models.yaml, return
         an ModelInfo object describing it.
         :param model_name: symbolic name of the model in models.yaml
@@ -508,7 +508,7 @@ class ModelManager(object):
 
         model_hash = "<NO_HASH>"  # TODO:
 
-        return ModelInfo(
+        return LoadedModelInfo(
             context=model_context,
             name=model_name,
             base_model=base_model,
diff --git a/invokeai/backend/util/test_utils.py b/invokeai/backend/util/test_utils.py
index 09b9de9e98..685603cedc 100644
--- a/invokeai/backend/util/test_utils.py
+++ b/invokeai/backend/util/test_utils.py
@@ -7,7 +7,7 @@ import torch
 
 from invokeai.app.services.config.config_default import InvokeAIAppConfig
 from invokeai.backend.install.model_install_backend import ModelInstall
-from invokeai.backend.model_management.model_manager import ModelInfo
+from invokeai.backend.model_management.model_manager import LoadedModelInfo
 from invokeai.backend.model_management.models.base import BaseModelType, ModelNotFoundException, ModelType, SubModelType
 
 
@@ -34,8 +34,8 @@ def install_and_load_model(
     base_model: BaseModelType,
     model_type: ModelType,
     submodel_type: Optional[SubModelType] = None,
-) -> ModelInfo:
-    """Install a model if it is not already installed, then get the ModelInfo for that model.
+) -> LoadedModelInfo:
+    """Install a model if it is not already installed, then get the LoadedModelInfo for that model.
 
     This is intended as a utility function for tests.
 
@@ -49,9 +49,9 @@ def install_and_load_model(
         submodel_type (Optional[SubModelType]): The submodel type, forwarded to ModelManager.get_model(...).
 
     Returns:
-        ModelInfo
+        LoadedModelInfo
     """
-    # If the requested model is already installed, return its ModelInfo.
+    # If the requested model is already installed, return its LoadedModelInfo.
     with contextlib.suppress(ModelNotFoundException):
         return model_installer.mgr.get_model(model_name, base_model, model_type, submodel_type)
 
diff --git a/invokeai/invocation_api/__init__.py b/invokeai/invocation_api/__init__.py
index e80bc26a00..2d3ceca11e 100644
--- a/invokeai/invocation_api/__init__.py
+++ b/invokeai/invocation_api/__init__.py
@@ -52,7 +52,7 @@ from invokeai.app.services.config.config_default import InvokeAIAppConfig
 from invokeai.app.services.image_records.image_records_common import ImageCategory
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID
-from invokeai.backend.model_management.model_manager import ModelInfo
+from invokeai.backend.model_management.model_manager import LoadedModelInfo
 from invokeai.backend.model_management.models.base import BaseModelType, ModelType, SubModelType
 from invokeai.backend.stable_diffusion.diffusers_pipeline import PipelineIntermediateState
 from invokeai.backend.stable_diffusion.diffusion.conditioning_data import (
@@ -121,7 +121,7 @@ __all__ = [
     # invokeai.app.services.config.config_default
     "InvokeAIAppConfig",
     # invokeai.backend.model_management.model_manager
-    "ModelInfo",
+    "LoadedModelInfo",
     # invokeai.backend.model_management.models.base
     "BaseModelType",
     "ModelType",

From 6d31bc53269c53506f05341a5c014a6d78681d8f Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sun, 11 Feb 2024 09:39:36 +1100
Subject: [PATCH 101/411] chore(nodes): export model-related objects from
 invocation_api

---
 invokeai/invocation_api/__init__.py | 31 +++++++++++++++++++++++++++++
 1 file changed, 31 insertions(+)

diff --git a/invokeai/invocation_api/__init__.py b/invokeai/invocation_api/__init__.py
index 2d3ceca11e..055dd12757 100644
--- a/invokeai/invocation_api/__init__.py
+++ b/invokeai/invocation_api/__init__.py
@@ -28,6 +28,22 @@ from invokeai.app.invocations.fields import (
     WithMetadata,
     WithWorkflow,
 )
+from invokeai.app.invocations.model import (
+    ClipField,
+    CLIPOutput,
+    LoraInfo,
+    LoraLoaderOutput,
+    LoRAModelField,
+    MainModelField,
+    ModelInfo,
+    ModelLoaderOutput,
+    SDXLLoraLoaderOutput,
+    UNetField,
+    UNetOutput,
+    VaeField,
+    VAEModelField,
+    VAEOutput,
+)
 from invokeai.app.invocations.primitives import (
     BooleanCollectionOutput,
     BooleanOutput,
@@ -87,6 +103,21 @@ __all__ = [
     "UIType",
     "WithMetadata",
     "WithWorkflow",
+    # invokeai.app.invocations.model
+    "ModelInfo",
+    "LoraInfo",
+    "UNetField",
+    "ClipField",
+    "VaeField",
+    "MainModelField",
+    "LoRAModelField",
+    "VAEModelField",
+    "UNetOutput",
+    "VAEOutput",
+    "CLIPOutput",
+    "ModelLoaderOutput",
+    "LoraLoaderOutput",
+    "SDXLLoraLoaderOutput",
     # invokeai.app.invocations.primitives
     "BooleanCollectionOutput",
     "BooleanOutput",

From b845e890d151b4f7652d9131beb82870ff837605 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sun, 11 Feb 2024 09:43:36 +1100
Subject: [PATCH 102/411] chore(nodes): remove deprecation logic for nodes API

---
 .../app/services/shared/invocation_context.py | 112 ------------------
 1 file changed, 112 deletions(-)

diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index 68fb78c143..c68dc1140b 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -1,7 +1,6 @@
 from dataclasses import dataclass
 from typing import TYPE_CHECKING, Optional
 
-from deprecated import deprecated
 from PIL.Image import Image
 from torch import Tensor
 
@@ -334,30 +333,6 @@ class UtilInterface(InvocationContextInterface):
         )
 
 
-deprecation_version = "3.7.0"
-removed_version = "3.8.0"
-
-
-def get_deprecation_reason(property_name: str, alternative: Optional[str] = None) -> str:
-    msg = f"{property_name} is deprecated as of v{deprecation_version}. It will be removed in v{removed_version}."
-    if alternative is not None:
-        msg += f" Use {alternative} instead."
-    msg += " See PLACEHOLDER_URL for details."
-    return msg
-
-
-# Deprecation docstrings template. I don't think we can implement these programmatically with
-# __doc__ because the IDE won't see them.
-
-"""
-**DEPRECATED as of v3.7.0**
-
-PROPERTY_NAME will be removed in v3.8.0. Use ALTERNATIVE instead. See PLACEHOLDER_URL for details.
-
-OG_DOCSTRING
-"""
-
-
 class InvocationContext:
     """
     The `InvocationContext` provides access to various services and data for the current invocation.
@@ -397,93 +372,6 @@ class InvocationContext:
         self._services = services
         """Provides access to the full application services. This is an internal API and may change without warning."""
 
-    @property
-    @deprecated(version=deprecation_version, reason=get_deprecation_reason("`context.services`"))
-    def services(self) -> InvocationServices:
-        """
-        **DEPRECATED as of v3.7.0**
-
-        `context.services` will be removed in v3.8.0. See PLACEHOLDER_URL for details.
-
-        The invocation services.
-        """
-        return self._services
-
-    @property
-    @deprecated(
-        version=deprecation_version,
-        reason=get_deprecation_reason("`context.graph_execution_state_id", "`context._data.session_id`"),
-    )
-    def graph_execution_state_id(self) -> str:
-        """
-        **DEPRECATED as of v3.7.0**
-
-        `context.graph_execution_state_api` will be removed in v3.8.0. Use `context._data.session_id` instead. See PLACEHOLDER_URL for details.
-
-        The ID of the session (aka graph execution state).
-        """
-        return self._data.session_id
-
-    @property
-    @deprecated(
-        version=deprecation_version,
-        reason=get_deprecation_reason("`context.queue_id`", "`context._data.queue_id`"),
-    )
-    def queue_id(self) -> str:
-        """
-        **DEPRECATED as of v3.7.0**
-
-        `context.queue_id` will be removed in v3.8.0. Use `context._data.queue_id` instead. See PLACEHOLDER_URL for details.
-
-        The ID of the queue.
-        """
-        return self._data.queue_id
-
-    @property
-    @deprecated(
-        version=deprecation_version,
-        reason=get_deprecation_reason("`context.queue_item_id`", "`context._data.queue_item_id`"),
-    )
-    def queue_item_id(self) -> int:
-        """
-        **DEPRECATED as of v3.7.0**
-
-        `context.queue_item_id` will be removed in v3.8.0. Use `context._data.queue_item_id` instead. See PLACEHOLDER_URL for details.
-
-        The ID of the queue item.
-        """
-        return self._data.queue_item_id
-
-    @property
-    @deprecated(
-        version=deprecation_version,
-        reason=get_deprecation_reason("`context.queue_batch_id`", "`context._data.batch_id`"),
-    )
-    def queue_batch_id(self) -> str:
-        """
-        **DEPRECATED as of v3.7.0**
-
-        `context.queue_batch_id` will be removed in v3.8.0. Use `context._data.batch_id` instead. See PLACEHOLDER_URL for details.
-
-        The ID of the batch.
-        """
-        return self._data.batch_id
-
-    @property
-    @deprecated(
-        version=deprecation_version,
-        reason=get_deprecation_reason("`context.workflow`", "`context._data.workflow`"),
-    )
-    def workflow(self) -> Optional[WorkflowWithoutID]:
-        """
-        **DEPRECATED as of v3.7.0**
-
-        `context.workflow` will be removed in v3.8.0. Use `context._data.workflow` instead. See PLACEHOLDER_URL for details.
-
-        The workflow associated with this queue item, if any.
-        """
-        return self._data.workflow
-
 
 def build_invocation_context(
     services: InvocationServices,

From 25f64d5b19bbc18c185e7446b48fb40ae4ffce2a Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sun, 11 Feb 2024 09:51:25 +1100
Subject: [PATCH 103/411] chore(nodes): "SAMPLER_NAME_VALUES" ->
 "SCHEDULER_NAME_VALUES"

This was named inaccurately.
---
 invokeai/app/invocations/constants.py |  7 +++++++
 invokeai/app/invocations/latent.py    | 10 ++++------
 2 files changed, 11 insertions(+), 6 deletions(-)

diff --git a/invokeai/app/invocations/constants.py b/invokeai/app/invocations/constants.py
index 95b16f0d05..795e7a3b60 100644
--- a/invokeai/app/invocations/constants.py
+++ b/invokeai/app/invocations/constants.py
@@ -1,3 +1,7 @@
+from typing import Literal
+
+from invokeai.backend.stable_diffusion.schedulers import SCHEDULER_MAP
+
 LATENT_SCALE_FACTOR = 8
 """
 HACK: Many nodes are currently hard-coded to use a fixed latent scale factor of 8. This is fragile, and will need to
@@ -5,3 +9,6 @@ be addressed if future models use a different latent scale factor. Also, note th
 factor is hard-coded to a literal '8' rather than using this constant.
 The ratio of image:latent dimensions is LATENT_SCALE_FACTOR:1, or 8:1.
 """
+
+SCHEDULER_NAME_VALUES = Literal[tuple(SCHEDULER_MAP.keys())]
+"""A literal type representing the valid scheduler names."""
diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py
index fedfc38402..69e3f055ca 100644
--- a/invokeai/app/invocations/latent.py
+++ b/invokeai/app/invocations/latent.py
@@ -23,7 +23,7 @@ from diffusers.schedulers import SchedulerMixin as Scheduler
 from pydantic import field_validator
 from torchvision.transforms.functional import resize as tv_resize
 
-from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR
+from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR, SCHEDULER_NAME_VALUES
 from invokeai.app.invocations.fields import (
     ConditioningField,
     DenoiseMaskField,
@@ -78,12 +78,10 @@ if choose_torch_device() == torch.device("mps"):
 
 DEFAULT_PRECISION = choose_precision(choose_torch_device())
 
-SAMPLER_NAME_VALUES = Literal[tuple(SCHEDULER_MAP.keys())]
-
 
 @invocation_output("scheduler_output")
 class SchedulerOutput(BaseInvocationOutput):
-    scheduler: SAMPLER_NAME_VALUES = OutputField(description=FieldDescriptions.scheduler, ui_type=UIType.Scheduler)
+    scheduler: SCHEDULER_NAME_VALUES = OutputField(description=FieldDescriptions.scheduler, ui_type=UIType.Scheduler)
 
 
 @invocation(
@@ -96,7 +94,7 @@ class SchedulerOutput(BaseInvocationOutput):
 class SchedulerInvocation(BaseInvocation):
     """Selects a scheduler."""
 
-    scheduler: SAMPLER_NAME_VALUES = InputField(
+    scheduler: SCHEDULER_NAME_VALUES = InputField(
         default="euler",
         description=FieldDescriptions.scheduler,
         ui_type=UIType.Scheduler,
@@ -234,7 +232,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
         description=FieldDescriptions.denoising_start,
     )
     denoising_end: float = InputField(default=1.0, ge=0, le=1, description=FieldDescriptions.denoising_end)
-    scheduler: SAMPLER_NAME_VALUES = InputField(
+    scheduler: SCHEDULER_NAME_VALUES = InputField(
         default="euler",
         description=FieldDescriptions.scheduler,
         ui_type=UIType.Scheduler,

From 7a2159beebb25c861f0f499e6a2db5ee2231b27e Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sun, 11 Feb 2024 10:06:53 +1100
Subject: [PATCH 104/411] feat(nodes): add more missing exports to
 invocation_api

Crawled through a few custom nodes to figure out what I had missed.
---
 invokeai/invocation_api/__init__.py | 27 +++++++++++++++++++++++++++
 1 file changed, 27 insertions(+)

diff --git a/invokeai/invocation_api/__init__.py b/invokeai/invocation_api/__init__.py
index 055dd12757..e110b5a2db 100644
--- a/invokeai/invocation_api/__init__.py
+++ b/invokeai/invocation_api/__init__.py
@@ -7,9 +7,11 @@ TODO(psyche): Do we want to dogfood this?
 from invokeai.app.invocations.baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
+    Classification,
     invocation,
     invocation_output,
 )
+from invokeai.app.invocations.constants import SCHEDULER_NAME_VALUES
 from invokeai.app.invocations.fields import (
     BoardField,
     ColorField,
@@ -28,6 +30,8 @@ from invokeai.app.invocations.fields import (
     WithMetadata,
     WithWorkflow,
 )
+from invokeai.app.invocations.latent import SchedulerOutput
+from invokeai.app.invocations.metadata import MetadataItemField, MetadataItemOutput, MetadataOutput
 from invokeai.app.invocations.model import (
     ClipField,
     CLIPOutput,
@@ -68,6 +72,7 @@ from invokeai.app.services.config.config_default import InvokeAIAppConfig
 from invokeai.app.services.image_records.image_records_common import ImageCategory
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID
+from invokeai.app.util.misc import SEED_MAX, get_random_seed
 from invokeai.backend.model_management.model_manager import LoadedModelInfo
 from invokeai.backend.model_management.models.base import BaseModelType, ModelType, SubModelType
 from invokeai.backend.stable_diffusion.diffusers_pipeline import PipelineIntermediateState
@@ -77,11 +82,14 @@ from invokeai.backend.stable_diffusion.diffusion.conditioning_data import (
     ExtraConditioningInfo,
     SDXLConditioningInfo,
 )
+from invokeai.backend.util.devices import CPU_DEVICE, CUDA_DEVICE, MPS_DEVICE, choose_precision, choose_torch_device
+from invokeai.version import __version__
 
 __all__ = [
     # invokeai.app.invocations.baseinvocation
     "BaseInvocation",
     "BaseInvocationOutput",
+    "Classification",
     "invocation",
     "invocation_output",
     # invokeai.app.services.shared.invocation_context
@@ -103,6 +111,12 @@ __all__ = [
     "UIType",
     "WithMetadata",
     "WithWorkflow",
+    # invokeai.app.invocations.latent
+    "SchedulerOutput",
+    # invokeai.app.invocations.metadata
+    "MetadataItemField",
+    "MetadataItemOutput",
+    "MetadataOutput",
     # invokeai.app.invocations.model
     "ModelInfo",
     "LoraInfo",
@@ -157,4 +171,17 @@ __all__ = [
     "BaseModelType",
     "ModelType",
     "SubModelType",
+    # invokeai.app.invocations.constants
+    "SCHEDULER_NAME_VALUES",
+    # invokeai.version
+    "__version__",
+    # invokeai.backend.util.devices
+    "choose_precision",
+    "choose_torch_device",
+    "CPU_DEVICE",
+    "CUDA_DEVICE",
+    "MPS_DEVICE",
+    # invokeai.app.util.misc
+    "SEED_MAX",
+    "get_random_seed",
 ]

From 5fbfed30acf1da1a2870730de9d9d64799c6bfdd Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 13 Feb 2024 15:02:30 +1100
Subject: [PATCH 105/411] chore(ui): regen types

---
 .../frontend/web/src/services/api/schema.ts   | 1802 +----------------
 1 file changed, 22 insertions(+), 1780 deletions(-)

diff --git a/invokeai/frontend/web/src/services/api/schema.ts b/invokeai/frontend/web/src/services/api/schema.ts
index 45358ed97d..1599b310c9 100644
--- a/invokeai/frontend/web/src/services/api/schema.ts
+++ b/invokeai/frontend/web/src/services/api/schema.ts
@@ -680,70 +680,6 @@ export type components = {
        */
       type: "add";
     };
-    /**
-     * Adjust Image Hue Plus
-     * @description Adjusts the Hue of an image by rotating it in the selected color space
-     */
-    AdjustImageHuePlusInvocation: {
-      /** @description Optional metadata to be saved with the image */
-      metadata?: components["schemas"]["MetadataField"] | null;
-      /**
-       * Id
-       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
-       */
-      id: string;
-      /**
-       * Is Intermediate
-       * @description Whether or not this is an intermediate invocation.
-       * @default false
-       */
-      is_intermediate?: boolean;
-      /**
-       * Use Cache
-       * @description Whether or not to use the cache
-       * @default true
-       */
-      use_cache?: boolean;
-      /** @description The image to adjust */
-      image?: components["schemas"]["ImageField"];
-      /**
-       * Space
-       * @description Color space in which to rotate hue by polar coords (*: non-invertible)
-       * @default Okhsl
-       * @enum {string}
-       */
-      space?: "HSV / HSL / RGB" | "Okhsl" | "Okhsv" | "*Oklch / Oklab" | "*LCh / CIELab" | "*UPLab (w/CIELab_to_UPLab.icc)";
-      /**
-       * Degrees
-       * @description Degrees by which to rotate image hue
-       * @default 0
-       */
-      degrees?: number;
-      /**
-       * Preserve Lightness
-       * @description Whether to preserve CIELAB lightness values
-       * @default false
-       */
-      preserve_lightness?: boolean;
-      /**
-       * Ok Adaptive Gamut
-       * @description Higher preserves chroma at the expense of lightness (Oklab)
-       * @default 0.05
-       */
-      ok_adaptive_gamut?: number;
-      /**
-       * Ok High Precision
-       * @description Use more steps in computing gamut (Oklab/Okhsv/Okhsl)
-       * @default true
-       */
-      ok_high_precision?: boolean;
-      /**
-       * type
-       * @default img_hue_adjust_plus
-       * @constant
-       */
-      type: "img_hue_adjust_plus";
-    };
     /**
      * AppConfig
      * @description App Config Response
@@ -1454,39 +1390,6 @@ export type components = {
        */
       type: "boolean_output";
     };
-    /**
-     * BRIA AI Background Removal
-     * @description Uses the new Bria 1.4 model to remove backgrounds from images.
-     */
-    BriaRemoveBackgroundInvocation: {
-      /** @description Optional metadata to be saved with the image */
-      metadata?: components["schemas"]["MetadataField"] | null;
-      /**
-       * Id
-       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
-       */
-      id: string;
-      /**
-       * Is Intermediate
-       * @description Whether or not this is an intermediate invocation.
-       * @default false
-       */
-      is_intermediate?: boolean;
-      /**
-       * Use Cache
-       * @description Whether or not to use the cache
-       * @default true
-       */
-      use_cache?: boolean;
-      /** @description The image to crop */
-      image?: components["schemas"]["ImageField"];
-      /**
-       * type
-       * @default bria_bg_remove
-       * @constant
-       */
-      type: "bria_bg_remove";
-    };
     /**
      * CLIPOutput
      * @description Base class for invocations that output a CLIP field
@@ -1581,282 +1484,6 @@ export type components = {
       /** @description Base model (usually 'Any') */
       base_model: components["schemas"]["invokeai__backend__model_management__models__base__BaseModelType"];
     };
-    /**
-     * CMYK Color Separation
-     * @description Get color images from a base color and two others that subtractively mix to obtain it
-     */
-    CMYKColorSeparationInvocation: {
-      /** @description Optional metadata to be saved with the image */
-      metadata?: components["schemas"]["MetadataField"] | null;
-      /**
-       * Id
-       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
-       */
-      id: string;
-      /**
-       * Is Intermediate
-       * @description Whether or not this is an intermediate invocation.
-       * @default false
-       */
-      is_intermediate?: boolean;
-      /**
-       * Use Cache
-       * @description Whether or not to use the cache
-       * @default true
-       */
-      use_cache?: boolean;
-      /**
-       * Width
-       * @description Desired image width
-       * @default 512
-       */
-      width?: number;
-      /**
-       * Height
-       * @description Desired image height
-       * @default 512
-       */
-      height?: number;
-      /**
-       * C Value
-       * @description Desired final cyan value
-       * @default 0
-       */
-      c_value?: number;
-      /**
-       * M Value
-       * @description Desired final magenta value
-       * @default 25
-       */
-      m_value?: number;
-      /**
-       * Y Value
-       * @description Desired final yellow value
-       * @default 28
-       */
-      y_value?: number;
-      /**
-       * K Value
-       * @description Desired final black value
-       * @default 76
-       */
-      k_value?: number;
-      /**
-       * C Split
-       * @description Desired cyan split point % [0..1.0]
-       * @default 0.5
-       */
-      c_split?: number;
-      /**
-       * M Split
-       * @description Desired magenta split point % [0..1.0]
-       * @default 1
-       */
-      m_split?: number;
-      /**
-       * Y Split
-       * @description Desired yellow split point % [0..1.0]
-       * @default 0
-       */
-      y_split?: number;
-      /**
-       * K Split
-       * @description Desired black split point % [0..1.0]
-       * @default 0.5
-       */
-      k_split?: number;
-      /**
-       * Profile
-       * @description CMYK Color Profile
-       * @default Default
-       * @enum {string}
-       */
-      profile?: "Default" | "PIL";
-      /**
-       * type
-       * @default cmyk_separation
-       * @constant
-       */
-      type: "cmyk_separation";
-    };
-    /**
-     * CMYK Merge
-     * @description Merge subtractive color channels (CMYK+alpha)
-     */
-    CMYKMergeInvocation: {
-      /** @description Optional metadata to be saved with the image */
-      metadata?: components["schemas"]["MetadataField"] | null;
-      /**
-       * Id
-       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
-       */
-      id: string;
-      /**
-       * Is Intermediate
-       * @description Whether or not this is an intermediate invocation.
-       * @default false
-       */
-      is_intermediate?: boolean;
-      /**
-       * Use Cache
-       * @description Whether or not to use the cache
-       * @default true
-       */
-      use_cache?: boolean;
-      /** @description The c channel */
-      c_channel?: components["schemas"]["ImageField"] | null;
-      /** @description The m channel */
-      m_channel?: components["schemas"]["ImageField"] | null;
-      /** @description The y channel */
-      y_channel?: components["schemas"]["ImageField"] | null;
-      /** @description The k channel */
-      k_channel?: components["schemas"]["ImageField"] | null;
-      /** @description The alpha channel */
-      alpha_channel?: components["schemas"]["ImageField"] | null;
-      /**
-       * Profile
-       * @description CMYK Color Profile
-       * @default Default
-       * @enum {string}
-       */
-      profile?: "Default" | "PIL";
-      /**
-       * type
-       * @default cmyk_merge
-       * @constant
-       */
-      type: "cmyk_merge";
-    };
-    /**
-     * CMYKSeparationOutput
-     * @description Base class for invocations that output four L-mode images (C, M, Y, K)
-     */
-    CMYKSeparationOutput: {
-      /** @description Blank image of the specified color */
-      color_image: components["schemas"]["ImageField"];
-      /**
-       * Width
-       * @description The width of the image in pixels
-       */
-      width: number;
-      /**
-       * Height
-       * @description The height of the image in pixels
-       */
-      height: number;
-      /** @description Blank image of the first separated color */
-      part_a: components["schemas"]["ImageField"];
-      /**
-       * Rgb Red A
-       * @description R value of color part A
-       */
-      rgb_red_a: number;
-      /**
-       * Rgb Green A
-       * @description G value of color part A
-       */
-      rgb_green_a: number;
-      /**
-       * Rgb Blue A
-       * @description B value of color part A
-       */
-      rgb_blue_a: number;
-      /** @description Blank image of the second separated color */
-      part_b: components["schemas"]["ImageField"];
-      /**
-       * Rgb Red B
-       * @description R value of color part B
-       */
-      rgb_red_b: number;
-      /**
-       * Rgb Green B
-       * @description G value of color part B
-       */
-      rgb_green_b: number;
-      /**
-       * Rgb Blue B
-       * @description B value of color part B
-       */
-      rgb_blue_b: number;
-      /**
-       * type
-       * @default cmyk_separation_output
-       * @constant
-       */
-      type: "cmyk_separation_output";
-    };
-    /**
-     * CMYK Split
-     * @description Split an image into subtractive color channels (CMYK+alpha)
-     */
-    CMYKSplitInvocation: {
-      /** @description Optional metadata to be saved with the image */
-      metadata?: components["schemas"]["MetadataField"] | null;
-      /**
-       * Id
-       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
-       */
-      id: string;
-      /**
-       * Is Intermediate
-       * @description Whether or not this is an intermediate invocation.
-       * @default false
-       */
-      is_intermediate?: boolean;
-      /**
-       * Use Cache
-       * @description Whether or not to use the cache
-       * @default true
-       */
-      use_cache?: boolean;
-      /** @description The image to halftone */
-      image?: components["schemas"]["ImageField"];
-      /**
-       * Profile
-       * @description CMYK Color Profile
-       * @default Default
-       * @enum {string}
-       */
-      profile?: "Default" | "PIL";
-      /**
-       * type
-       * @default cmyk_split
-       * @constant
-       */
-      type: "cmyk_split";
-    };
-    /**
-     * CMYKSplitOutput
-     * @description Base class for invocations that output four L-mode images (C, M, Y, K)
-     */
-    CMYKSplitOutput: {
-      /** @description Grayscale image of the cyan channel */
-      c_channel: components["schemas"]["ImageField"];
-      /** @description Grayscale image of the magenta channel */
-      m_channel: components["schemas"]["ImageField"];
-      /** @description Grayscale image of the yellow channel */
-      y_channel: components["schemas"]["ImageField"];
-      /** @description Grayscale image of the k channel */
-      k_channel: components["schemas"]["ImageField"];
-      /** @description Grayscale image of the alpha channel */
-      alpha_channel: components["schemas"]["ImageField"];
-      /**
-       * Width
-       * @description The width of the image in pixels
-       */
-      width: number;
-      /**
-       * Height
-       * @description The height of the image in pixels
-       */
-      height: number;
-      /**
-       * type
-       * @default cmyk_split_output
-       * @constant
-       */
-      type: "cmyk_split_output";
-    };
     /**
      * CV2 Infill
      * @description Infills transparent areas of an image using OpenCV Inpainting
@@ -3491,6 +3118,8 @@ export type components = {
      * @description Generates an openpose pose from an image using DWPose
      */
     DWOpenposeImageProcessorInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
       /** @description Optional metadata to be saved with the image */
       metadata?: components["schemas"]["MetadataField"] | null;
       /**
@@ -4014,39 +3643,6 @@ export type components = {
        */
       priority: number;
     };
-    /**
-     * Equivalent Achromatic Lightness
-     * @description Calculate Equivalent Achromatic Lightness from image
-     */
-    EquivalentAchromaticLightnessInvocation: {
-      /** @description Optional metadata to be saved with the image */
-      metadata?: components["schemas"]["MetadataField"] | null;
-      /**
-       * Id
-       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
-       */
-      id: string;
-      /**
-       * Is Intermediate
-       * @description Whether or not this is an intermediate invocation.
-       * @default false
-       */
-      is_intermediate?: boolean;
-      /**
-       * Use Cache
-       * @description Whether or not to use the cache
-       * @default true
-       */
-      use_cache?: boolean;
-      /** @description Image from which to get channel */
-      image?: components["schemas"]["ImageField"];
-      /**
-       * type
-       * @default ealightness
-       * @constant
-       */
-      type: "ealightness";
-    };
     /** ExposedField */
     ExposedField: {
       /** Nodeid */
@@ -4301,39 +3897,6 @@ export type components = {
        */
       y: number;
     };
-    /**
-     * Flatten Histogram (Grayscale)
-     * @description Scales the values of an L-mode image by scaling them to the full range 0..255 in equal proportions
-     */
-    FlattenHistogramMono: {
-      /** @description Optional metadata to be saved with the image */
-      metadata?: components["schemas"]["MetadataField"] | null;
-      /**
-       * Id
-       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
-       */
-      id: string;
-      /**
-       * Is Intermediate
-       * @description Whether or not this is an intermediate invocation.
-       * @default false
-       */
-      is_intermediate?: boolean;
-      /**
-       * Use Cache
-       * @description Whether or not to use the cache
-       * @default true
-       */
-      use_cache?: boolean;
-      /** @description Single-channel image for which to flatten the histogram */
-      image?: components["schemas"]["ImageField"];
-      /**
-       * type
-       * @default flatten_histogram_mono
-       * @constant
-       */
-      type: "flatten_histogram_mono";
-    };
     /**
      * Float Collection Primitive
      * @description A collection of float primitive values
@@ -4683,7 +4246,7 @@ export type components = {
        * @description The nodes in this graph
        */
       nodes?: {
-        [key: string]: components["schemas"]["ImageDilateOrErodeInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["HandDepthMeshGraphormerProcessor"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["TextToMaskClipsegInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["LinearUIOutputInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["OffsetLatentsInvocation"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["CMYKColorSeparationInvocation"] | components["schemas"]["NoiseImage2DInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["EquivalentAchromaticLightnessInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["DepthAnythingImageProcessorInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["ImageBlendInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["ImageRotateInvocation"] | components["schemas"]["ShadowsHighlightsMidtonesMaskInvocation"] | components["schemas"]["ONNXLatentsToImageInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["BriaRemoveBackgroundInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["ImageValueThresholdsInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["ONNXPromptInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["NoiseSpectralInvocation"] | components["schemas"]["TextMaskInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["MaskedBlendLatentsInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["CMYKMergeInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["ColorMapImageProcessorInvocation"] | components["schemas"]["TextToMaskClipsegAdvancedInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["ImageCompositorInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["FlattenHistogramMono"] | components["schemas"]["AdjustImageHuePlusInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["CMYKSplitInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["DWOpenposeImageProcessorInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["ImageEnhanceInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["LatentConsistencyInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["OnnxModelLoaderInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["ImageOffsetInvocation"] | components["schemas"]["GraphInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["ONNXTextToLatentsInvocation"] | components["schemas"]["InfillColorInvocation"];
+        [key: string]: components["schemas"]["ImageCropInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["DepthAnythingImageProcessorInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["DWOpenposeImageProcessorInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["GraphInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["ColorMapImageProcessorInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["IdealSizeInvocation"];
       };
       /**
        * Edges
@@ -4720,7 +4283,7 @@ export type components = {
        * @description The results of node executions
        */
       results: {
-        [key: string]: components["schemas"]["LoraLoaderOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["CMYKSplitOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["LatentsOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["CMYKSeparationOutput"] | components["schemas"]["String2Output"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["MetadataOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["VAEOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["ClipSkipInvocationOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["GraphInvocationOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["SDXLLoraLoaderOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["ONNXModelLoaderOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["HandDepthOutput"] | components["schemas"]["ShadowsHighlightsMidtonesMasksOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["ColorCollectionOutput"];
+        [key: string]: components["schemas"]["MetadataOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["SDXLLoraLoaderOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["VAEOutput"] | components["schemas"]["LoraLoaderOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["GraphInvocationOutput"] | components["schemas"]["String2Output"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["LatentsOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["ClipSkipInvocationOutput"];
       };
       /**
        * Errors
@@ -4811,83 +4374,6 @@ export type components = {
       /** Detail */
       detail?: components["schemas"]["ValidationError"][];
     };
-    /**
-     * Hand Depth w/ MeshGraphormer
-     * @description Generate hand depth maps to inpaint with using ControlNet
-     */
-    HandDepthMeshGraphormerProcessor: {
-      /** @description Optional metadata to be saved with the image */
-      metadata?: components["schemas"]["MetadataField"] | null;
-      /**
-       * Id
-       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
-       */
-      id: string;
-      /**
-       * Is Intermediate
-       * @description Whether or not this is an intermediate invocation.
-       * @default false
-       */
-      is_intermediate?: boolean;
-      /**
-       * Use Cache
-       * @description Whether or not to use the cache
-       * @default true
-       */
-      use_cache?: boolean;
-      /** @description The image to process */
-      image?: components["schemas"]["ImageField"];
-      /**
-       * Resolution
-       * @description Pixel resolution for output image
-       * @default 512
-       */
-      resolution?: number;
-      /**
-       * Mask Padding
-       * @description Amount to pad the hand mask by
-       * @default 30
-       */
-      mask_padding?: number;
-      /**
-       * Offload
-       * @description Offload model after usage
-       * @default false
-       */
-      offload?: boolean;
-      /**
-       * type
-       * @default hand_depth_mesh_graphormer_image_processor
-       * @constant
-       */
-      type: "hand_depth_mesh_graphormer_image_processor";
-    };
-    /**
-     * HandDepthOutput
-     * @description Base class for to output Meshgraphormer results
-     */
-    HandDepthOutput: {
-      /** @description Improved hands depth map */
-      image: components["schemas"]["ImageField"];
-      /** @description Hands area mask */
-      mask: components["schemas"]["ImageField"];
-      /**
-       * Width
-       * @description The width of the depth map in pixels
-       */
-      width: number;
-      /**
-       * Height
-       * @description The height of the depth map in pixels
-       */
-      height: number;
-      /**
-       * type
-       * @default meshgraphormer_output
-       * @constant
-       */
-      type: "meshgraphormer_output";
-    };
     /**
      * HED (softedge) Processor
      * @description Applies HED edge detection to image
@@ -5260,87 +4746,6 @@ export type components = {
        */
       type: "ideal_size_output";
     };
-    /**
-     * Image Layer Blend
-     * @description Blend two images together, with optional opacity, mask, and blend modes
-     */
-    ImageBlendInvocation: {
-      /** @description Optional metadata to be saved with the image */
-      metadata?: components["schemas"]["MetadataField"] | null;
-      /**
-       * Id
-       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
-       */
-      id: string;
-      /**
-       * Is Intermediate
-       * @description Whether or not this is an intermediate invocation.
-       * @default false
-       */
-      is_intermediate?: boolean;
-      /**
-       * Use Cache
-       * @description Whether or not to use the cache
-       * @default true
-       */
-      use_cache?: boolean;
-      /** @description The top image to blend */
-      layer_upper?: components["schemas"]["ImageField"];
-      /**
-       * Blend Mode
-       * @description Available blend modes
-       * @default Normal
-       * @enum {string}
-       */
-      blend_mode?: "Normal" | "Lighten Only" | "Darken Only" | "Lighten Only (EAL)" | "Darken Only (EAL)" | "Hue" | "Saturation" | "Color" | "Luminosity" | "Linear Dodge (Add)" | "Subtract" | "Multiply" | "Divide" | "Screen" | "Overlay" | "Linear Burn" | "Difference" | "Hard Light" | "Soft Light" | "Vivid Light" | "Linear Light" | "Color Burn" | "Color Dodge";
-      /**
-       * Opacity
-       * @description Desired opacity of the upper layer
-       * @default 1
-       */
-      opacity?: number;
-      /** @description Optional mask, used to restrict areas from blending */
-      mask?: components["schemas"]["ImageField"] | null;
-      /**
-       * Fit To Width
-       * @description Scale upper layer to fit base width
-       * @default false
-       */
-      fit_to_width?: boolean;
-      /**
-       * Fit To Height
-       * @description Scale upper layer to fit base height
-       * @default true
-       */
-      fit_to_height?: boolean;
-      /** @description The bottom image to blend */
-      layer_base?: components["schemas"]["ImageField"];
-      /**
-       * Color Space
-       * @description Available color spaces for blend computations
-       * @default Linear RGB
-       * @enum {string}
-       */
-      color_space?: "RGB" | "Linear RGB" | "HSL (RGB)" | "HSV (RGB)" | "Okhsl" | "Okhsv" | "Oklch (Oklab)" | "LCh (CIELab)";
-      /**
-       * Adaptive Gamut
-       * @description Adaptive gamut clipping (0=off). Higher prioritizes chroma over lightness
-       * @default 0
-       */
-      adaptive_gamut?: number;
-      /**
-       * High Precision
-       * @description Use more steps in computing gamut when possible
-       * @default true
-       */
-      high_precision?: boolean;
-      /**
-       * type
-       * @default img_blend
-       * @constant
-       */
-      type: "img_blend";
-    };
     /**
      * Blur Image
      * @description Blurs an image
@@ -5594,77 +4999,6 @@ export type components = {
        */
       type: "image_collection_output";
     };
-    /**
-     * Image Compositor
-     * @description Removes backdrop from subject image then overlays subject on background image
-     */
-    ImageCompositorInvocation: {
-      /** @description Optional metadata to be saved with the image */
-      metadata?: components["schemas"]["MetadataField"] | null;
-      /**
-       * Id
-       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
-       */
-      id: string;
-      /**
-       * Is Intermediate
-       * @description Whether or not this is an intermediate invocation.
-       * @default false
-       */
-      is_intermediate?: boolean;
-      /**
-       * Use Cache
-       * @description Whether or not to use the cache
-       * @default true
-       */
-      use_cache?: boolean;
-      /** @description Image of the subject on a plain monochrome background */
-      image_subject?: components["schemas"]["ImageField"];
-      /** @description Image of a background scene */
-      image_background?: components["schemas"]["ImageField"];
-      /**
-       * Chroma Key
-       * @description Can be empty for corner flood select, or CSS-3 color or tuple
-       * @default
-       */
-      chroma_key?: string;
-      /**
-       * Threshold
-       * @description Subject isolation flood-fill threshold
-       * @default 50
-       */
-      threshold?: number;
-      /**
-       * Fill X
-       * @description Scale base subject image to fit background width
-       * @default false
-       */
-      fill_x?: boolean;
-      /**
-       * Fill Y
-       * @description Scale base subject image to fit background height
-       * @default true
-       */
-      fill_y?: boolean;
-      /**
-       * X Offset
-       * @description x-offset for the subject
-       * @default 0
-       */
-      x_offset?: number;
-      /**
-       * Y Offset
-       * @description y-offset for the subject
-       * @default 0
-       */
-      y_offset?: number;
-      /**
-       * type
-       * @default img_composite
-       * @constant
-       */
-      type: "img_composite";
-    };
     /**
      * Convert Image Mode
      * @description Converts an image to a different mode.
@@ -5846,127 +5180,6 @@ export type components = {
        */
       board_id?: string | null;
     };
-    /**
-     * Image Dilate or Erode
-     * @description Dilate (expand) or erode (contract) an image
-     */
-    ImageDilateOrErodeInvocation: {
-      /** @description Optional metadata to be saved with the image */
-      metadata?: components["schemas"]["MetadataField"] | null;
-      /**
-       * Id
-       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
-       */
-      id: string;
-      /**
-       * Is Intermediate
-       * @description Whether or not this is an intermediate invocation.
-       * @default false
-       */
-      is_intermediate?: boolean;
-      /**
-       * Use Cache
-       * @description Whether or not to use the cache
-       * @default true
-       */
-      use_cache?: boolean;
-      /** @description The image from which to create a mask */
-      image?: components["schemas"]["ImageField"];
-      /**
-       * Lightness Only
-       * @description If true, only applies to image lightness (CIELa*b*)
-       * @default false
-       */
-      lightness_only?: boolean;
-      /**
-       * Radius W
-       * @description Width (in pixels) by which to dilate(expand) or erode (contract) the image
-       * @default 4
-       */
-      radius_w?: number;
-      /**
-       * Radius H
-       * @description Height (in pixels) by which to dilate(expand) or erode (contract) the image
-       * @default 4
-       */
-      radius_h?: number;
-      /**
-       * Mode
-       * @description How to operate on the image
-       * @default Dilate
-       * @enum {string}
-       */
-      mode?: "Dilate" | "Erode";
-      /**
-       * type
-       * @default img_dilate_erode
-       * @constant
-       */
-      type: "img_dilate_erode";
-    };
-    /**
-     * Enhance Image
-     * @description Applies processing from PIL's ImageEnhance module.
-     */
-    ImageEnhanceInvocation: {
-      /** @description Optional metadata to be saved with the image */
-      metadata?: components["schemas"]["MetadataField"] | null;
-      /**
-       * Id
-       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
-       */
-      id: string;
-      /**
-       * Is Intermediate
-       * @description Whether or not this is an intermediate invocation.
-       * @default false
-       */
-      is_intermediate?: boolean;
-      /**
-       * Use Cache
-       * @description Whether or not to use the cache
-       * @default true
-       */
-      use_cache?: boolean;
-      /** @description The image for which to apply processing */
-      image?: components["schemas"]["ImageField"];
-      /**
-       * Invert
-       * @description Whether to invert the image colors
-       * @default false
-       */
-      invert?: boolean;
-      /**
-       * Color
-       * @description Color enhancement factor
-       * @default 1
-       */
-      color?: number;
-      /**
-       * Contrast
-       * @description Contrast enhancement factor
-       * @default 1
-       */
-      contrast?: number;
-      /**
-       * Brightness
-       * @description Brightness enhancement factor
-       * @default 1
-       */
-      brightness?: number;
-      /**
-       * Sharpness
-       * @description Sharpness enhancement factor
-       * @default 1
-       */
-      sharpness?: number;
-      /**
-       * type
-       * @default img_enhance
-       * @constant
-       */
-      type: "img_enhance";
-    };
     /**
      * ImageField
      * @description An image primitive field
@@ -6216,57 +5429,6 @@ export type components = {
        */
       type: "img_nsfw";
     };
-    /**
-     * Offset Image
-     * @description Offsets an image by a given percentage (or pixel amount).
-     */
-    ImageOffsetInvocation: {
-      /** @description Optional metadata to be saved with the image */
-      metadata?: components["schemas"]["MetadataField"] | null;
-      /**
-       * Id
-       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
-       */
-      id: string;
-      /**
-       * Is Intermediate
-       * @description Whether or not this is an intermediate invocation.
-       * @default false
-       */
-      is_intermediate?: boolean;
-      /**
-       * Use Cache
-       * @description Whether or not to use the cache
-       * @default true
-       */
-      use_cache?: boolean;
-      /**
-       * As Pixels
-       * @description Interpret offsets as pixels rather than percentages
-       * @default false
-       */
-      as_pixels?: boolean;
-      /** @description Image to be offset */
-      image?: components["schemas"]["ImageField"];
-      /**
-       * X Offset
-       * @description x-offset for the subject
-       * @default 0.5
-       */
-      x_offset?: number;
-      /**
-       * Y Offset
-       * @description y-offset for the subject
-       * @default 0.5
-       */
-      y_offset?: number;
-      /**
-       * type
-       * @default offset_image
-       * @constant
-       */
-      type: "offset_image";
-    };
     /**
      * ImageOutput
      * @description Base class for nodes that output a single image
@@ -6432,63 +5594,6 @@ export type components = {
        */
       type: "img_resize";
     };
-    /**
-     * Rotate/Flip Image
-     * @description Rotates an image by a given angle (in degrees clockwise).
-     */
-    ImageRotateInvocation: {
-      /** @description Optional metadata to be saved with the image */
-      metadata?: components["schemas"]["MetadataField"] | null;
-      /**
-       * Id
-       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
-       */
-      id: string;
-      /**
-       * Is Intermediate
-       * @description Whether or not this is an intermediate invocation.
-       * @default false
-       */
-      is_intermediate?: boolean;
-      /**
-       * Use Cache
-       * @description Whether or not to use the cache
-       * @default true
-       */
-      use_cache?: boolean;
-      /** @description Image to be rotated clockwise */
-      image?: components["schemas"]["ImageField"];
-      /**
-       * Degrees
-       * @description Angle (in degrees clockwise) by which to rotate
-       * @default 90
-       */
-      degrees?: number;
-      /**
-       * Expand To Fit
-       * @description If true, extends the image boundary to fit the rotated content
-       * @default true
-       */
-      expand_to_fit?: boolean;
-      /**
-       * Flip Horizontal
-       * @description If true, flips the image horizontally
-       * @default false
-       */
-      flip_horizontal?: boolean;
-      /**
-       * Flip Vertical
-       * @description If true, flips the image vertically
-       * @default false
-       */
-      flip_vertical?: boolean;
-      /**
-       * type
-       * @default rotate_image
-       * @constant
-       */
-      type: "rotate_image";
-    };
     /**
      * Scale Image
      * @description Scales an image by a factor
@@ -6603,69 +5708,6 @@ export type components = {
        */
       thumbnail_url: string;
     };
-    /**
-     * Image Value Thresholds
-     * @description Clip image to pure black/white past specified thresholds
-     */
-    ImageValueThresholdsInvocation: {
-      /** @description Optional metadata to be saved with the image */
-      metadata?: components["schemas"]["MetadataField"] | null;
-      /**
-       * Id
-       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
-       */
-      id: string;
-      /**
-       * Is Intermediate
-       * @description Whether or not this is an intermediate invocation.
-       * @default false
-       */
-      is_intermediate?: boolean;
-      /**
-       * Use Cache
-       * @description Whether or not to use the cache
-       * @default true
-       */
-      use_cache?: boolean;
-      /** @description The image from which to create a mask */
-      image?: components["schemas"]["ImageField"];
-      /**
-       * Invert Output
-       * @description Make light areas dark and vice versa
-       * @default false
-       */
-      invert_output?: boolean;
-      /**
-       * Renormalize Values
-       * @description Rescale remaining values from minimum to maximum
-       * @default false
-       */
-      renormalize_values?: boolean;
-      /**
-       * Lightness Only
-       * @description If true, only applies to image lightness (CIELa*b*)
-       * @default false
-       */
-      lightness_only?: boolean;
-      /**
-       * Threshold Upper
-       * @description Threshold above which will be set to full value
-       * @default 0.5
-       */
-      threshold_upper?: number;
-      /**
-       * Threshold Lower
-       * @description Threshold below which will be set to minimum value
-       * @default 0.5
-       */
-      threshold_lower?: number;
-      /**
-       * type
-       * @default img_val_thresholds
-       * @constant
-       */
-      type: "img_val_thresholds";
-    };
     /**
      * Add Invisible Watermark
      * @description Add an invisible watermark to an image
@@ -8025,47 +7067,6 @@ export type components = {
        */
       type: "tomask";
     };
-    /**
-     * Blend Latents/Noise (Masked)
-     * @description Blend two latents using a given alpha and mask. Latents must have same size.
-     */
-    MaskedBlendLatentsInvocation: {
-      /**
-       * Id
-       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
-       */
-      id: string;
-      /**
-       * Is Intermediate
-       * @description Whether or not this is an intermediate invocation.
-       * @default false
-       */
-      is_intermediate?: boolean;
-      /**
-       * Use Cache
-       * @description Whether or not to use the cache
-       * @default true
-       */
-      use_cache?: boolean;
-      /** @description Latents tensor */
-      latents_a?: components["schemas"]["LatentsField"];
-      /** @description Latents tensor */
-      latents_b?: components["schemas"]["LatentsField"];
-      /** @description Mask for blending in latents B */
-      mask?: components["schemas"]["ImageField"];
-      /**
-       * Alpha
-       * @description Blending factor. 0.0 = use input A only, 1.0 = use input B only, 0.5 = 50% mix of input A and input B.
-       * @default 0.5
-       */
-      alpha?: number;
-      /**
-       * type
-       * @default lmblend
-       * @constant
-       */
-      type: "lmblend";
-    };
     /**
      * Mediapipe Face Processor
      * @description Applies mediapipe face processing to image
@@ -8678,86 +7679,6 @@ export type components = {
        */
       value: string | number;
     };
-    /**
-     * 2D Noise Image
-     * @description Creates an image of 2D Noise approximating the desired characteristics
-     */
-    NoiseImage2DInvocation: {
-      /** @description Optional metadata to be saved with the image */
-      metadata?: components["schemas"]["MetadataField"] | null;
-      /**
-       * Id
-       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
-       */
-      id: string;
-      /**
-       * Is Intermediate
-       * @description Whether or not this is an intermediate invocation.
-       * @default false
-       */
-      is_intermediate?: boolean;
-      /**
-       * Use Cache
-       * @description Whether or not to use the cache
-       * @default true
-       */
-      use_cache?: boolean;
-      /**
-       * Noise Type
-       * @description Desired noise spectral characteristics
-       * @default White
-       * @enum {string}
-       */
-      noise_type?: "White" | "Red" | "Blue" | "Green";
-      /**
-       * Width
-       * @description Desired image width
-       * @default 512
-       */
-      width?: number;
-      /**
-       * Height
-       * @description Desired image height
-       * @default 512
-       */
-      height?: number;
-      /**
-       * Seed
-       * @description Seed for noise generation
-       * @default 0
-       */
-      seed?: number;
-      /**
-       * Iterations
-       * @description Noise approx. iterations
-       * @default 15
-       */
-      iterations?: number;
-      /**
-       * Blur Threshold
-       * @description Threshold used in computing noise (lower is better/slower)
-       * @default 0.2
-       */
-      blur_threshold?: number;
-      /**
-       * Sigma Red
-       * @description Sigma for strong gaussian blur LPF for red/green
-       * @default 3
-       */
-      sigma_red?: number;
-      /**
-       * Sigma Blue
-       * @description Sigma for weak gaussian blur HPF for blue/green
-       * @default 1
-       */
-      sigma_blue?: number;
-      /**
-       * type
-       * @default noiseimg_2d
-       * @constant
-       */
-      type: "noiseimg_2d";
-    };
     /**
      * Noise
      * @description Generates latent noise.
@@ -8835,84 +7756,6 @@ export type components = {
        */
       type: "noise_output";
     };
-    /**
-     * Noise (Spectral characteristics)
-     * @description Creates an image of 2D Noise approximating the desired characteristics
-     */
-    NoiseSpectralInvocation: {
-      /**
-       * Id
-       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
-       */
-      id: string;
-      /**
-       * Is Intermediate
-       * @description Whether or not this is an intermediate invocation.
-       * @default false
-       */
-      is_intermediate?: boolean;
-      /**
-       * Use Cache
-       * @description Whether or not to use the cache
-       * @default true
-       */
-      use_cache?: boolean;
-      /**
-       * Noise Type
-       * @description Desired noise spectral characteristics
-       * @default White
-       * @enum {string}
-       */
-      noise_type?: "White" | "Red" | "Blue" | "Green";
-      /**
-       * Width
-       * @description Desired image width
-       * @default 512
-       */
-      width?: number;
-      /**
-       * Height
-       * @description Desired image height
-       * @default 512
-       */
-      height?: number;
-      /**
-       * Seed
-       * @description Seed for noise generation
-       * @default 0
-       */
-      seed?: number;
-      /**
-       * Iterations
-       * @description Noise approx. iterations
-       * @default 15
-       */
-      iterations?: number;
-      /**
-       * Blur Threshold
-       * @description Threshold used in computing noise (lower is better/slower)
-       * @default 0.2
-       */
-      blur_threshold?: number;
-      /**
-       * Sigma Red
-       * @description Sigma for strong gaussian blur LPF for red/green
-       * @default 3
-       */
-      sigma_red?: number;
-      /**
-       * Sigma Blue
-       * @description Sigma for weak gaussian blur HPF for blue/green
-       * @default 1
-       */
-      sigma_blue?: number;
-      /**
-       * type
-       * @default noise_spectral
-       * @constant
-       */
-      type: "noise_spectral";
-    };
     /**
      * Normal BAE Processor
      * @description Applies NormalBae processing to image
@@ -8960,107 +7803,6 @@ export type components = {
        */
       type: "normalbae_image_processor";
     };
-    /**
-     * ONNX Latents to Image
-     * @description Generates an image from latents.
-     */
-    ONNXLatentsToImageInvocation: {
-      /** @description Optional metadata to be saved with the image */
-      metadata?: components["schemas"]["MetadataField"] | null;
-      /**
-       * Id
-       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
-       */
-      id: string;
-      /**
-       * Is Intermediate
-       * @description Whether or not this is an intermediate invocation.
-       * @default false
-       */
-      is_intermediate?: boolean;
-      /**
-       * Use Cache
-       * @description Whether or not to use the cache
-       * @default true
-       */
-      use_cache?: boolean;
-      /** @description Denoised latents tensor */
-      latents?: components["schemas"]["LatentsField"];
-      /** @description VAE */
-      vae?: components["schemas"]["VaeField"];
-      /**
-       * type
-       * @default l2i_onnx
-       * @constant
-       */
-      type: "l2i_onnx";
-    };
-    /**
-     * ONNXModelLoaderOutput
-     * @description Model loader output
-     */
-    ONNXModelLoaderOutput: {
-      /**
-       * UNet
-       * @description UNet (scheduler, LoRAs)
-       */
-      unet?: components["schemas"]["UNetField"];
-      /**
-       * CLIP
-       * @description CLIP (tokenizer, text encoder, LoRAs) and skipped layer count
-       */
-      clip?: components["schemas"]["ClipField"];
-      /**
-       * VAE Decoder
-       * @description VAE
-       */
-      vae_decoder?: components["schemas"]["VaeField"];
-      /**
-       * VAE Encoder
-       * @description VAE
-       */
-      vae_encoder?: components["schemas"]["VaeField"];
-      /**
-       * type
-       * @default model_loader_output_onnx
-       * @constant
-       */
-      type: "model_loader_output_onnx";
-    };
-    /** ONNX Prompt (Raw) */
-    ONNXPromptInvocation: {
-      /**
-       * Id
-       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
-       */
-      id: string;
-      /**
-       * Is Intermediate
-       * @description Whether or not this is an intermediate invocation.
-       * @default false
-       */
-      is_intermediate?: boolean;
-      /**
-       * Use Cache
-       * @description Whether or not to use the cache
-       * @default true
-       */
-      use_cache?: boolean;
-      /**
-       * Prompt
-       * @description Raw prompt text (no parsing)
-       * @default
-       */
-      prompt?: string;
-      /** @description CLIP (tokenizer, text encoder, LoRAs) and skipped layer count */
-      clip?: components["schemas"]["ClipField"];
-      /**
-       * type
-       * @default prompt_onnx
-       * @constant
-       */
-      type: "prompt_onnx";
-    };
     /**
      * ONNXSD1Config
      * @description Model config for ONNX format models based on sd-1.
@@ -9242,117 +7984,6 @@ export type components = {
       /** Upcast Attention */
       upcast_attention: boolean;
     };
-    /**
-     * ONNX Text to Latents
-     * @description Generates latents from conditionings.
-     */
-    ONNXTextToLatentsInvocation: {
-      /**
-       * Id
-       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
-       */
-      id: string;
-      /**
-       * Is Intermediate
-       * @description Whether or not this is an intermediate invocation.
-       * @default false
-       */
-      is_intermediate?: boolean;
-      /**
-       * Use Cache
-       * @description Whether or not to use the cache
-       * @default true
-       */
-      use_cache?: boolean;
-      /** @description Positive conditioning tensor */
-      positive_conditioning?: components["schemas"]["ConditioningField"];
-      /** @description Negative conditioning tensor */
-      negative_conditioning?: components["schemas"]["ConditioningField"];
-      /** @description Noise tensor */
-      noise?: components["schemas"]["LatentsField"];
-      /**
-       * Steps
-       * @description Number of steps to run
-       * @default 10
-       */
-      steps?: number;
-      /**
-       * Cfg Scale
-       * @description Classifier-Free Guidance scale
-       * @default 7.5
-       */
-      cfg_scale?: number | number[];
-      /**
-       * Scheduler
-       * @description Scheduler to use during inference
-       * @default euler
-       * @enum {string}
-       */
-      scheduler?: "ddim" | "ddpm" | "deis" | "lms" | "lms_k" | "pndm" | "heun" | "heun_k" | "euler" | "euler_k" | "euler_a" | "kdpm_2" | "kdpm_2_a" | "dpmpp_2s" | "dpmpp_2s_k" | "dpmpp_2m" | "dpmpp_2m_k" | "dpmpp_2m_sde" | "dpmpp_2m_sde_k" | "dpmpp_sde" | "dpmpp_sde_k" | "unipc" | "lcm";
-      /**
-       * Precision
-       * @description Precision to use
-       * @default tensor(float16)
-       * @enum {string}
-       */
-      precision?: "tensor(bool)" | "tensor(int8)" | "tensor(uint8)" | "tensor(int16)" | "tensor(uint16)" | "tensor(int32)" | "tensor(uint32)" | "tensor(int64)" | "tensor(uint64)" | "tensor(float16)" | "tensor(float)" | "tensor(double)";
-      /** @description UNet (scheduler, LoRAs) */
-      unet?: components["schemas"]["UNetField"];
-      /**
-       * Control
-       * @description ControlNet(s) to apply
-       */
-      control?: components["schemas"]["ControlField"] | components["schemas"]["ControlField"][];
-      /**
-       * type
-       * @default t2l_onnx
-       * @constant
-       */
-      type: "t2l_onnx";
-    };
-    /**
-     * Offset Latents
-     * @description Offsets a latents tensor by a given percentage of height/width.
-     */
-    OffsetLatentsInvocation: {
-      /**
-       * Id
-       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
-       */
-      id: string;
-      /**
-       * Is Intermediate
-       * @description Whether or not this is an intermediate invocation.
-       * @default false
-       */
-      is_intermediate?: boolean;
-      /**
-       * Use Cache
-       * @description Whether or not to use the cache
-       * @default true
-       */
-      use_cache?: boolean;
-      /** @description Latents tensor */
-      latents?: components["schemas"]["LatentsField"];
-      /**
-       * X Offset
-       * @description Approx percentage to offset (H)
-       * @default 0.5
-       */
-      x_offset?: number;
-      /**
-       * Y Offset
-       * @description Approx percentage to offset (V)
-       * @default 0.5
-       */
-      y_offset?: number;
-      /**
-       * type
-       * @default offset_latents
-       * @constant
-       */
-      type: "offset_latents";
-    };
     /** OffsetPaginatedResults[BoardDTO] */
     OffsetPaginatedResults_BoardDTO_: {
       /**
@@ -9399,52 +8030,6 @@ export type components = {
        */
       items: components["schemas"]["ImageDTO"][];
     };
-    /**
-     * OnnxModelField
-     * @description Onnx model field
-     */
-    OnnxModelField: {
-      /**
-       * Model Name
-       * @description Name of the model
-       */
-      model_name: string;
-      /** @description Base model */
-      base_model: components["schemas"]["invokeai__backend__model_management__models__base__BaseModelType"];
-      /** @description Model Type */
-      model_type: components["schemas"]["invokeai__backend__model_management__models__base__ModelType"];
-    };
-    /**
-     * ONNX Main Model
-     * @description Loads a main model, outputting its submodels.
-     */
-    OnnxModelLoaderInvocation: {
-      /**
-       * Id
-       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
-       */
-      id: string;
-      /**
-       * Is Intermediate
-       * @description Whether or not this is an intermediate invocation.
-       * @default false
-       */
-      is_intermediate?: boolean;
-      /**
-       * Use Cache
-       * @description Whether or not to use the cache
-       * @default true
-       */
-      use_cache?: boolean;
-      /** @description ONNX Main model (UNet, VAE, CLIP) to load */
-      model: components["schemas"]["OnnxModelField"];
-      /**
-       * type
-       * @default onnx_model_loader
-       * @constant
-       */
-      type: "onnx_model_loader";
-    };
     /** PaginatedResults[ModelSummary] */
     PaginatedResults_ModelSummary_: {
       /**
@@ -10852,106 +9437,6 @@ export type components = {
        */
       total: number;
     };
-    /**
-     * Shadows/Highlights/Midtones
-     * @description Extract a Shadows/Highlights/Midtones mask from an image
-     */
-    ShadowsHighlightsMidtonesMaskInvocation: {
-      /** @description Optional metadata to be saved with the image */
-      metadata?: components["schemas"]["MetadataField"] | null;
-      /**
-       * Id
-       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
-       */
-      id: string;
-      /**
-       * Is Intermediate
-       * @description Whether or not this is an intermediate invocation.
-       * @default false
-       */
-      is_intermediate?: boolean;
-      /**
-       * Use Cache
-       * @description Whether or not to use the cache
-       * @default true
-       */
-      use_cache?: boolean;
-      /** @description Image from which to extract mask */
-      image?: components["schemas"]["ImageField"];
-      /**
-       * Invert Output
-       * @description Off: white on black / On: black on white
-       * @default true
-       */
-      invert_output?: boolean;
-      /**
-       * Highlight Threshold
-       * @description Threshold beyond which mask values will be at extremum
-       * @default 0.75
-       */
-      highlight_threshold?: number;
-      /**
-       * Upper Mid Threshold
-       * @description Threshold to which to extend mask border by 0..1 gradient
-       * @default 0.7
-       */
-      upper_mid_threshold?: number;
-      /**
-       * Lower Mid Threshold
-       * @description Threshold to which to extend mask border by 0..1 gradient
-       * @default 0.3
-       */
-      lower_mid_threshold?: number;
-      /**
-       * Shadow Threshold
-       * @description Threshold beyond which mask values will be at extremum
-       * @default 0.25
-       */
-      shadow_threshold?: number;
-      /**
-       * Mask Expand Or Contract
-       * @description Pixels to grow (or shrink) the mask areas
-       * @default 0
-       */
-      mask_expand_or_contract?: number;
-      /**
-       * Mask Blur
-       * @description Gaussian blur radius to apply to the masks
-       * @default 0
-       */
-      mask_blur?: number;
-      /**
-       * type
-       * @default shmmask
-       * @constant
-       */
-      type: "shmmask";
-    };
-    /** ShadowsHighlightsMidtonesMasksOutput */
-    ShadowsHighlightsMidtonesMasksOutput: {
-      /** @description Soft-edged highlights mask */
-      highlights_mask?: components["schemas"]["ImageField"];
-      /** @description Soft-edged midtones mask */
-      midtones_mask?: components["schemas"]["ImageField"];
-      /** @description Soft-edged shadows mask */
-      shadows_mask?: components["schemas"]["ImageField"];
-      /**
-       * Width
-       * @description Width of the input/outputs
-       */
-      width: number;
-      /**
-       * Height
-       * @description Height of the input/outputs
-       */
-      height: number;
-      /**
-       * type
-       * @default shmmask_output
-       * @constant
-       */
-      type: "shmmask_output";
-    };
     /**
      * Show Image
      * @description Displays a provided image using the OS image viewer, and passes it forward in the pipeline.
@@ -11833,249 +10318,6 @@ export type components = {
       /** Right */
       right: number;
     };
-    /**
-     * Text Mask
-     * @description Creates a 2D rendering of a text mask from a given font
-     */
-    TextMaskInvocation: {
-      /** @description Optional metadata to be saved with the image */
-      metadata?: components["schemas"]["MetadataField"] | null;
-      /**
-       * Id
-       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
-       */
-      id: string;
-      /**
-       * Is Intermediate
-       * @description Whether or not this is an intermediate invocation.
-       * @default false
-       */
-      is_intermediate?: boolean;
-      /**
-       * Use Cache
-       * @description Whether or not to use the cache
-       * @default true
-       */
-      use_cache?: boolean;
-      /**
-       * Width
-       * @description The width of the desired mask
-       * @default 512
-       */
-      width?: number;
-      /**
-       * Height
-       * @description The height of the desired mask
-       * @default 512
-       */
-      height?: number;
-      /**
-       * Text
-       * @description The text to render
-       * @default
-       */
-      text?: string;
-      /**
-       * Font
-       * @description Path to a FreeType-supported TTF/OTF font file
-       * @default
-       */
-      font?: string;
-      /**
-       * Size
-       * @description Desired point size of text to use
-       * @default 64
-       */
-      size?: number;
-      /**
-       * Angle
-       * @description Angle of rotation to apply to the text
-       * @default 0
-       */
-      angle?: number;
-      /**
-       * X Offset
-       * @description x-offset for text rendering
-       * @default 24
-       */
-      x_offset?: number;
-      /**
-       * Y Offset
-       * @description y-offset for text rendering
-       * @default 36
-       */
-      y_offset?: number;
-      /**
-       * Invert
-       * @description Whether to invert color of the output
-       * @default false
-       */
-      invert?: boolean;
-      /**
-       * type
-       * @default text_mask
-       * @constant
-       */
-      type: "text_mask";
-    };
-    /**
-     * Text to Mask Advanced (Clipseg)
-     * @description Uses the Clipseg model to generate an image mask from a text prompt
-     */
-    TextToMaskClipsegAdvancedInvocation: {
-      /** @description Optional metadata to be saved with the image */
-      metadata?: components["schemas"]["MetadataField"] | null;
-      /**
-       * Id
-       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
-       */
-      id: string;
-      /**
-       * Is Intermediate
-       * @description Whether or not this is an intermediate invocation.
-       * @default false
-       */
-      is_intermediate?: boolean;
-      /**
-       * Use Cache
-       * @description Whether or not to use the cache
-       * @default true
-       */
-      use_cache?: boolean;
-      /** @description The image from which to create a mask */
-      image?: components["schemas"]["ImageField"];
-      /**
-       * Invert Output
-       * @description Off: white on black / On: black on white
-       * @default true
-       */
-      invert_output?: boolean;
-      /**
-       * Prompt 1
-       * @description First prompt with which to create a mask
-       */
-      prompt_1?: string;
-      /**
-       * Prompt 2
-       * @description Second prompt with which to create a mask (optional)
-       */
-      prompt_2?: string;
-      /**
-       * Prompt 3
-       * @description Third prompt with which to create a mask (optional)
-       */
-      prompt_3?: string;
-      /**
-       * Prompt 4
-       * @description Fourth prompt with which to create a mask (optional)
-       */
-      prompt_4?: string;
-      /**
-       * Combine
-       * @description How to combine the results
-       * @default or
-       * @enum {string}
-       */
-      combine?: "or" | "and" | "none (rgba multiplex)";
-      /**
-       * Smoothing
-       * @description Radius of blur to apply before thresholding
-       * @default 4
-       */
-      smoothing?: number;
-      /**
-       * Subject Threshold
-       * @description Threshold above which is considered the subject
-       * @default 1
-       */
-      subject_threshold?: number;
-      /**
-       * Background Threshold
-       * @description Threshold below which is considered the background
-       * @default 0
-       */
-      background_threshold?: number;
-      /**
-       * type
-       * @default txt2mask_clipseg_adv
-       * @constant
-       */
-      type: "txt2mask_clipseg_adv";
-    };
-    /**
-     * Text to Mask (Clipseg)
-     * @description Uses the Clipseg model to generate an image mask from a text prompt
-     */
-    TextToMaskClipsegInvocation: {
-      /** @description Optional metadata to be saved with the image */
-      metadata?: components["schemas"]["MetadataField"] | null;
-      /**
-       * Id
-       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
-       */
-      id: string;
-      /**
-       * Is Intermediate
-       * @description Whether or not this is an intermediate invocation.
-       * @default false
-       */
-      is_intermediate?: boolean;
-      /**
-       * Use Cache
-       * @description Whether or not to use the cache
-       * @default true
-       */
-      use_cache?: boolean;
-      /** @description The image from which to create a mask */
-      image?: components["schemas"]["ImageField"];
-      /**
-       * Invert Output
-       * @description Off: white on black / On: black on white
-       * @default true
-       */
-      invert_output?: boolean;
-      /**
-       * Prompt
-       * @description The prompt with which to create a mask
-       */
-      prompt?: string;
-      /**
-       * Smoothing
-       * @description Radius of blur to apply before thresholding
-       * @default 4
-       */
-      smoothing?: number;
-      /**
-       * Subject Threshold
-       * @description Threshold above which is considered the subject
-       * @default 0.4
-       */
-      subject_threshold?: number;
-      /**
-       * Background Threshold
-       * @description Threshold below which is considered the background
-       * @default 0.4
-       */
-      background_threshold?: number;
-      /**
-       * Mask Expand Or Contract
-       * @description Pixels by which to grow (or shrink) mask after thresholding
-       * @default 0
-       */
-      mask_expand_or_contract?: number;
-      /**
-       * Mask Blur
-       * @description Radius of blur to apply after thresholding
-       * @default 0
-       */
-      mask_blur?: number;
-      /**
-       * type
-       * @default txt2mask_clipseg
-       * @constant
-       */
-      type: "txt2mask_clipseg";
-    };
     /**
      * TextualInversionConfig
      * @description Model config for textual inversion embeddings.
@@ -13066,18 +11308,6 @@ export type components = {
      * @enum {string}
      */
     UIType: "SDXLMainModelField" | "SDXLRefinerModelField" | "ONNXModelField" | "VAEModelField" | "LoRAModelField" | "ControlNetModelField" | "IPAdapterModelField" | "SchedulerField" | "AnyField" | "CollectionField" | "CollectionItemField" | "DEPRECATED_Boolean" | "DEPRECATED_Color" | "DEPRECATED_Conditioning" | "DEPRECATED_Control" | "DEPRECATED_Float" | "DEPRECATED_Image" | "DEPRECATED_Integer" | "DEPRECATED_Latents" | "DEPRECATED_String" | "DEPRECATED_BooleanCollection" | "DEPRECATED_ColorCollection" | "DEPRECATED_ConditioningCollection" | "DEPRECATED_ControlCollection" | "DEPRECATED_FloatCollection" | "DEPRECATED_ImageCollection" | "DEPRECATED_IntegerCollection" | "DEPRECATED_LatentsCollection" | "DEPRECATED_StringCollection" | "DEPRECATED_BooleanPolymorphic" | "DEPRECATED_ColorPolymorphic" | "DEPRECATED_ConditioningPolymorphic" | "DEPRECATED_ControlPolymorphic" | "DEPRECATED_FloatPolymorphic" | "DEPRECATED_ImagePolymorphic" | "DEPRECATED_IntegerPolymorphic" | "DEPRECATED_LatentsPolymorphic" | "DEPRECATED_StringPolymorphic" | "DEPRECATED_MainModel" | "DEPRECATED_UNet" | "DEPRECATED_Vae" | "DEPRECATED_CLIP" | "DEPRECATED_Collection" | "DEPRECATED_CollectionItem" | "DEPRECATED_Enum" | "DEPRECATED_WorkflowField" | "DEPRECATED_IsIntermediate" | "DEPRECATED_BoardField" | "DEPRECATED_MetadataItem" | "DEPRECATED_MetadataItemCollection" | "DEPRECATED_MetadataItemPolymorphic" | "DEPRECATED_MetadataDict";
-    /**
-     * T2IAdapterModelFormat
-     * @description An enumeration.
-     * @enum {string}
-     */
-    T2IAdapterModelFormat: "diffusers";
-    /**
-     * IPAdapterModelFormat
-     * @description An enumeration.
-     * @enum {string}
-     */
-    IPAdapterModelFormat: "invokeai";
     /**
      * StableDiffusionXLModelFormat
      * @description An enumeration.
@@ -13085,11 +11315,11 @@ export type components = {
      */
     StableDiffusionXLModelFormat: "checkpoint" | "diffusers";
     /**
-     * StableDiffusionOnnxModelFormat
+     * T2IAdapterModelFormat
      * @description An enumeration.
      * @enum {string}
      */
-    StableDiffusionOnnxModelFormat: "olive" | "onnx";
+    T2IAdapterModelFormat: "diffusers";
     /**
      * CLIPVisionModelFormat
      * @description An enumeration.
@@ -13097,11 +11327,11 @@ export type components = {
      */
     CLIPVisionModelFormat: "diffusers";
     /**
-     * StableDiffusion2ModelFormat
+     * ControlNetModelFormat
      * @description An enumeration.
      * @enum {string}
      */
-    StableDiffusion2ModelFormat: "checkpoint" | "diffusers";
+    ControlNetModelFormat: "checkpoint" | "diffusers";
     /**
      * StableDiffusion1ModelFormat
      * @description An enumeration.
@@ -13109,11 +11339,23 @@ export type components = {
      */
     StableDiffusion1ModelFormat: "checkpoint" | "diffusers";
     /**
-     * ControlNetModelFormat
+     * IPAdapterModelFormat
      * @description An enumeration.
      * @enum {string}
      */
-    ControlNetModelFormat: "checkpoint" | "diffusers";
+    IPAdapterModelFormat: "invokeai";
+    /**
+     * StableDiffusion2ModelFormat
+     * @description An enumeration.
+     * @enum {string}
+     */
+    StableDiffusion2ModelFormat: "checkpoint" | "diffusers";
+    /**
+     * StableDiffusionOnnxModelFormat
+     * @description An enumeration.
+     * @enum {string}
+     */
+    StableDiffusionOnnxModelFormat: "olive" | "onnx";
   };
   responses: never;
   parameters: never;

From f8525837b2fd6ce8a06d021c324e57ae5c7587aa Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 13 Feb 2024 16:30:00 +1100
Subject: [PATCH 106/411] feat(ui): workflow schema v3 (WIP)

The changes aim to deduplicate data between workflows and node templates, decoupling workflows from internal implementation details. A good amount of data that was needlessly duplicated from the node template to the workflow is removed.

These changes substantially reduce the file size of workflows (and therefore the images with embedded workflows):

- Default T2I SD1.5 workflow JSON is reduced from 23.7kb (798 lines) to 10.9kb (407 lines).
- Default tiled upscale workflow JSON is reduced from 102.7kb (3341 lines) to 51.9kb (1774 lines).

The trade-off is that we need to reference node templates to get things like the field type and other things. In practice, this is a non-issue, because we need a node template to do anything with a node anyways.

- Field types are not included in the workflow. They are always pulled from the node templates.

The field type is now properly an internal implementation detail and we can change it as needed. Previously this would require a migration for the workflow itself. With the v3 schema, the structure of a field type is an internal implementation detail that we are free to change as we see fit.

- Workflow nodes no long have an `outputs` property and there is no longer such a thing as a `FieldOutputInstance`. These are only on the templates.

These were never referenced at a time when we didn't also have the templates available, and there'd be no reason to do so.

- Node width and height are no longer stored in the node.

These weren't used. Also, per https://reactflow.dev/api-reference/types/node, we shouldn't be programmatically changing these properties. A future enhancement can properly add node resizing.

- `nodeTemplates` slice is merged back into `nodesSlice` as `nodes.templates`. Turns out it's just a hassle having these separate in separate slices.

- Workflow migration logic updated to support the new schema. V1 workflows migrate all the way to v3 now.

- Changes throughout the nodes code to accommodate the above changes.
---
 .../middleware/devtools/actionSanitizer.ts    |   2 +-
 .../listeners/getOpenAPISchema.ts             |   2 +-
 .../listeners/updateAllNodesRequested.ts      |   3 +-
 .../listeners/workflowLoadRequested.ts        |   2 +-
 invokeai/frontend/web/src/app/store/store.ts  |   2 -
 .../frontend/web/src/app/store/storeHooks.ts  |   3 +-
 invokeai/frontend/web/src/app/store/util.ts   |   2 +
 .../src/common/hooks/useIsReadyToEnqueue.ts   |   6 +-
 .../flow/AddNodePopover/AddNodePopover.tsx    |  14 +-
 .../flow/edges/util/makeEdgeSelector.ts       |  18 +-
 .../InvocationNodeCollapsedHandles.tsx        |  19 +-
 .../Invocation/InvocationNodeWrapper.tsx      |   4 +-
 .../Invocation/fields/EditableFieldTitle.tsx  |   4 +-
 .../nodes/Invocation/fields/FieldTitle.tsx    |   2 +-
 .../Invocation/fields/FieldTooltipContent.tsx |   6 +-
 .../nodes/Invocation/fields/InputField.tsx    |   6 +-
 .../Invocation/fields/InputFieldRenderer.tsx  |  29 +-
 .../Invocation/fields/LinearViewField.tsx     |   4 +-
 .../nodes/Invocation/fields/OutputField.tsx   |  10 +-
 .../inspector/InspectorDetailsTab.tsx         |   5 +-
 .../inspector/InspectorOutputsTab.tsx         |   5 +-
 .../inspector/InspectorTemplateTab.tsx        |   5 +-
 .../hooks/useAnyOrDirectInputFieldNames.ts    |  20 +-
 .../src/features/nodes/hooks/useBuildNode.ts  |   2 +-
 .../hooks/useConnectionInputFieldNames.ts     |  20 +-
 .../nodes/hooks/useConnectionState.ts         |  10 +-
 .../nodes/hooks/useDoNodeVersionsMatch.ts     |  18 +-
 .../nodes/hooks/useDoesInputHaveValue.ts      |  12 +-
 .../src/features/nodes/hooks/useFieldData.ts  |  23 -
 .../nodes/hooks/useFieldInputInstance.ts      |  15 +-
 .../features/nodes/hooks/useFieldInputKind.ts |  15 +-
 .../nodes/hooks/useFieldInputTemplate.ts      |  15 +-
 .../src/features/nodes/hooks/useFieldLabel.ts |  10 +-
 .../nodes/hooks/useFieldOutputInstance.ts     |  23 -
 .../nodes/hooks/useFieldOutputTemplate.ts     |  15 +-
 .../features/nodes/hooks/useFieldTemplate.ts  |  21 +-
 .../nodes/hooks/useFieldTemplateTitle.ts      |  16 +-
 .../features/nodes/hooks/useFieldType.ts.ts   |  14 +-
 .../nodes/hooks/useGetNodesNeedUpdate.ts      |   5 +-
 .../features/nodes/hooks/useHasImageOutput.ts |  13 +-
 .../features/nodes/hooks/useIsIntermediate.ts |  10 +-
 .../nodes/hooks/useIsValidConnection.ts       |  44 +-
 .../nodes/hooks/useNodeClassification.ts      |  17 +-
 .../src/features/nodes/hooks/useNodeData.ts   |   7 +-
 .../src/features/nodes/hooks/useNodeLabel.ts  |   9 +-
 .../nodes/hooks/useNodeNeedsUpdate.ts         |  15 +-
 .../src/features/nodes/hooks/useNodePack.ts   |  10 +-
 .../features/nodes/hooks/useNodeTemplate.ts   |  13 +-
 .../nodes/hooks/useNodeTemplateByType.ts      |  10 +-
 .../nodes/hooks/useNodeTemplateTitle.ts       |  15 +-
 .../nodes/hooks/useOutputFieldNames.ts        |  20 +-
 .../src/features/nodes/hooks/useUseCache.ts   |   8 +-
 .../nodes/hooks/useWorkflowWatcher.ts         |   4 +-
 .../web/src/features/nodes/store/actions.ts   |   4 +-
 .../nodes/store/nodeTemplatesSlice.ts         |  24 -
 .../src/features/nodes/store/nodesSlice.ts    |  15 +-
 .../web/src/features/nodes/store/selectors.ts |  51 +
 .../web/src/features/nodes/store/types.ts     |   5 +-
 .../store/util/findConnectionToValidHandle.ts |  30 +-
 .../util/makeIsConnectionValidSelector.ts     |   2 +-
 .../src/features/nodes/store/workflowSlice.ts |   6 +-
 .../web/src/features/nodes/types/field.ts     | 130 +--
 .../src/features/nodes/types/invocation.ts    |  24 +-
 .../web/src/features/nodes/types/v2/common.ts | 188 ++++
 .../src/features/nodes/types/v2/constants.ts  |  80 ++
 .../web/src/features/nodes/types/v2/error.ts  |  58 ++
 .../web/src/features/nodes/types/v2/field.ts  | 875 ++++++++++++++++++
 .../src/features/nodes/types/v2/invocation.ts |  93 ++
 .../src/features/nodes/types/v2/metadata.ts   |  77 ++
 .../src/features/nodes/types/v2/openapi.ts    |  86 ++
 .../web/src/features/nodes/types/v2/semver.ts |  21 +
 .../src/features/nodes/types/v2/workflow.ts   |  89 ++
 .../web/src/features/nodes/types/workflow.ts  |  10 +-
 .../nodes/util/node/buildInvocationNode.ts    |  22 +-
 .../features/nodes/util/node/nodeUpdate.ts    |   1 -
 .../util/schema/buildFieldInputInstance.ts    |   3 -
 .../nodes/util/workflow/buildWorkflow.ts      |  20 +-
 .../nodes/util/workflow/migrations.ts         |  32 +-
 .../nodes/util/workflow/validateWorkflow.ts   |   4 +-
 .../workflowLibrary/hooks/useSaveWorkflow.ts  |   4 +-
 80 files changed, 1940 insertions(+), 616 deletions(-)
 create mode 100644 invokeai/frontend/web/src/app/store/util.ts
 delete mode 100644 invokeai/frontend/web/src/features/nodes/hooks/useFieldData.ts
 delete mode 100644 invokeai/frontend/web/src/features/nodes/hooks/useFieldOutputInstance.ts
 delete mode 100644 invokeai/frontend/web/src/features/nodes/store/nodeTemplatesSlice.ts
 create mode 100644 invokeai/frontend/web/src/features/nodes/store/selectors.ts
 create mode 100644 invokeai/frontend/web/src/features/nodes/types/v2/common.ts
 create mode 100644 invokeai/frontend/web/src/features/nodes/types/v2/constants.ts
 create mode 100644 invokeai/frontend/web/src/features/nodes/types/v2/error.ts
 create mode 100644 invokeai/frontend/web/src/features/nodes/types/v2/field.ts
 create mode 100644 invokeai/frontend/web/src/features/nodes/types/v2/invocation.ts
 create mode 100644 invokeai/frontend/web/src/features/nodes/types/v2/metadata.ts
 create mode 100644 invokeai/frontend/web/src/features/nodes/types/v2/openapi.ts
 create mode 100644 invokeai/frontend/web/src/features/nodes/types/v2/semver.ts
 create mode 100644 invokeai/frontend/web/src/features/nodes/types/v2/workflow.ts

diff --git a/invokeai/frontend/web/src/app/store/middleware/devtools/actionSanitizer.ts b/invokeai/frontend/web/src/app/store/middleware/devtools/actionSanitizer.ts
index 2e2d2014b2..ed8c82d91c 100644
--- a/invokeai/frontend/web/src/app/store/middleware/devtools/actionSanitizer.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/devtools/actionSanitizer.ts
@@ -1,6 +1,6 @@
 import type { UnknownAction } from '@reduxjs/toolkit';
 import { isAnyGraphBuilt } from 'features/nodes/store/actions';
-import { nodeTemplatesBuilt } from 'features/nodes/store/nodeTemplatesSlice';
+import { nodeTemplatesBuilt } from 'features/nodes/store/nodesSlice';
 import { cloneDeep } from 'lodash-es';
 import { appInfoApi } from 'services/api/endpoints/appInfo';
 import type { Graph } from 'services/api/types';
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/getOpenAPISchema.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/getOpenAPISchema.ts
index b2d3615909..88518e2c0b 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/getOpenAPISchema.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/getOpenAPISchema.ts
@@ -1,6 +1,6 @@
 import { logger } from 'app/logging/logger';
 import { parseify } from 'common/util/serialize';
-import { nodeTemplatesBuilt } from 'features/nodes/store/nodeTemplatesSlice';
+import { nodeTemplatesBuilt } from 'features/nodes/store/nodesSlice';
 import { parseSchema } from 'features/nodes/util/schema/parseSchema';
 import { size } from 'lodash-es';
 import { appInfoApi } from 'services/api/endpoints/appInfo';
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/updateAllNodesRequested.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/updateAllNodesRequested.ts
index 752c3b09df..ac1298da5b 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/updateAllNodesRequested.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/updateAllNodesRequested.ts
@@ -15,8 +15,7 @@ export const addUpdateAllNodesRequestedListener = () => {
     actionCreator: updateAllNodesRequested,
     effect: (action, { dispatch, getState }) => {
       const log = logger('nodes');
-      const nodes = getState().nodes.nodes;
-      const templates = getState().nodeTemplates.templates;
+      const { nodes, templates } = getState().nodes;
 
       let unableToUpdateCount = 0;
 
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/workflowLoadRequested.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/workflowLoadRequested.ts
index 9307031e6d..ad41dc2654 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/workflowLoadRequested.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/workflowLoadRequested.ts
@@ -18,7 +18,7 @@ export const addWorkflowLoadRequestedListener = () => {
     effect: (action, { dispatch, getState }) => {
       const log = logger('nodes');
       const { workflow, asCopy } = action.payload;
-      const nodeTemplates = getState().nodeTemplates.templates;
+      const nodeTemplates = getState().nodes.templates;
 
       try {
         const { workflow: validatedWorkflow, warnings } = validateWorkflow(workflow, nodeTemplates);
diff --git a/invokeai/frontend/web/src/app/store/store.ts b/invokeai/frontend/web/src/app/store/store.ts
index e25e1351eb..270662c3d2 100644
--- a/invokeai/frontend/web/src/app/store/store.ts
+++ b/invokeai/frontend/web/src/app/store/store.ts
@@ -16,7 +16,6 @@ import { hrfPersistConfig, hrfSlice } from 'features/hrf/store/hrfSlice';
 import { loraPersistConfig, loraSlice } from 'features/lora/store/loraSlice';
 import { modelManagerPersistConfig, modelManagerSlice } from 'features/modelManager/store/modelManagerSlice';
 import { nodesPersistConfig, nodesSlice } from 'features/nodes/store/nodesSlice';
-import { nodesTemplatesSlice } from 'features/nodes/store/nodeTemplatesSlice';
 import { workflowPersistConfig, workflowSlice } from 'features/nodes/store/workflowSlice';
 import { generationPersistConfig, generationSlice } from 'features/parameters/store/generationSlice';
 import { postprocessingPersistConfig, postprocessingSlice } from 'features/parameters/store/postprocessingSlice';
@@ -46,7 +45,6 @@ const allReducers = {
   [gallerySlice.name]: gallerySlice.reducer,
   [generationSlice.name]: generationSlice.reducer,
   [nodesSlice.name]: nodesSlice.reducer,
-  [nodesTemplatesSlice.name]: nodesTemplatesSlice.reducer,
   [postprocessingSlice.name]: postprocessingSlice.reducer,
   [systemSlice.name]: systemSlice.reducer,
   [configSlice.name]: configSlice.reducer,
diff --git a/invokeai/frontend/web/src/app/store/storeHooks.ts b/invokeai/frontend/web/src/app/store/storeHooks.ts
index f1a9aa979c..6bc904acb3 100644
--- a/invokeai/frontend/web/src/app/store/storeHooks.ts
+++ b/invokeai/frontend/web/src/app/store/storeHooks.ts
@@ -1,7 +1,8 @@
 import type { AppThunkDispatch, RootState } from 'app/store/store';
 import type { TypedUseSelectorHook } from 'react-redux';
-import { useDispatch, useSelector } from 'react-redux';
+import { useDispatch, useSelector, useStore } from 'react-redux';
 
 // Use throughout your app instead of plain `useDispatch` and `useSelector`
 export const useAppDispatch = () => useDispatch<AppThunkDispatch>();
 export const useAppSelector: TypedUseSelectorHook<RootState> = useSelector;
+export const useAppStore = () => useStore<RootState>();
diff --git a/invokeai/frontend/web/src/app/store/util.ts b/invokeai/frontend/web/src/app/store/util.ts
new file mode 100644
index 0000000000..381f7f85d2
--- /dev/null
+++ b/invokeai/frontend/web/src/app/store/util.ts
@@ -0,0 +1,2 @@
+export const EMPTY_ARRAY = [];
+export const EMPTY_OBJECT = {};
diff --git a/invokeai/frontend/web/src/common/hooks/useIsReadyToEnqueue.ts b/invokeai/frontend/web/src/common/hooks/useIsReadyToEnqueue.ts
index 4952fa1c47..baa704e75c 100644
--- a/invokeai/frontend/web/src/common/hooks/useIsReadyToEnqueue.ts
+++ b/invokeai/frontend/web/src/common/hooks/useIsReadyToEnqueue.ts
@@ -8,7 +8,6 @@ import { isControlNetOrT2IAdapter } from 'features/controlAdapters/store/types';
 import { selectDynamicPromptsSlice } from 'features/dynamicPrompts/store/dynamicPromptsSlice';
 import { getShouldProcessPrompt } from 'features/dynamicPrompts/util/getShouldProcessPrompt';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { selectNodeTemplatesSlice } from 'features/nodes/store/nodeTemplatesSlice';
 import { isInvocationNode } from 'features/nodes/types/invocation';
 import { selectGenerationSlice } from 'features/parameters/store/generationSlice';
 import { selectSystemSlice } from 'features/system/store/systemSlice';
@@ -23,11 +22,10 @@ const selector = createMemoizedSelector(
     selectGenerationSlice,
     selectSystemSlice,
     selectNodesSlice,
-    selectNodeTemplatesSlice,
     selectDynamicPromptsSlice,
     activeTabNameSelector,
   ],
-  (controlAdapters, generation, system, nodes, nodeTemplates, dynamicPrompts, activeTabName) => {
+  (controlAdapters, generation, system, nodes, dynamicPrompts, activeTabName) => {
     const { initialImage, model, positivePrompt } = generation;
 
     const { isConnected } = system;
@@ -54,7 +52,7 @@ const selector = createMemoizedSelector(
             return;
           }
 
-          const nodeTemplate = nodeTemplates.templates[node.data.type];
+          const nodeTemplate = nodes.templates[node.data.type];
 
           if (!nodeTemplate) {
             // Node type not found
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/AddNodePopover/AddNodePopover.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/AddNodePopover/AddNodePopover.tsx
index b24b52c6ab..061209cafc 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/AddNodePopover/AddNodePopover.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/AddNodePopover/AddNodePopover.tsx
@@ -7,8 +7,12 @@ import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import type { SelectInstance } from 'chakra-react-select';
 import { useBuildNode } from 'features/nodes/hooks/useBuildNode';
-import { addNodePopoverClosed, addNodePopoverOpened, nodeAdded } from 'features/nodes/store/nodesSlice';
-import { selectNodeTemplatesSlice } from 'features/nodes/store/nodeTemplatesSlice';
+import {
+  addNodePopoverClosed,
+  addNodePopoverOpened,
+  nodeAdded,
+  selectNodesSlice,
+} from 'features/nodes/store/nodesSlice';
 import { validateSourceAndTargetTypes } from 'features/nodes/store/util/validateSourceAndTargetTypes';
 import { filter, map, memoize, some } from 'lodash-es';
 import type { KeyboardEventHandler } from 'react';
@@ -54,10 +58,10 @@ const AddNodePopover = () => {
   const fieldFilter = useAppSelector((s) => s.nodes.connectionStartFieldType);
   const handleFilter = useAppSelector((s) => s.nodes.connectionStartParams?.handleType);
 
-  const selector = createMemoizedSelector(selectNodeTemplatesSlice, (nodeTemplates) => {
+  const selector = createMemoizedSelector(selectNodesSlice, (nodes) => {
     // If we have a connection in progress, we need to filter the node choices
     const filteredNodeTemplates = fieldFilter
-      ? filter(nodeTemplates.templates, (template) => {
+      ? filter(nodes.templates, (template) => {
           const handles = handleFilter === 'source' ? template.inputs : template.outputs;
 
           return some(handles, (handle) => {
@@ -67,7 +71,7 @@ const AddNodePopover = () => {
             return validateSourceAndTargetTypes(sourceType, targetType);
           });
         })
-      : map(nodeTemplates.templates);
+      : map(nodes.templates);
 
     const options: ComboboxOption[] = map(filteredNodeTemplates, (template) => {
       return {
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/edges/util/makeEdgeSelector.ts b/invokeai/frontend/web/src/features/nodes/components/flow/edges/util/makeEdgeSelector.ts
index 4bfc588e67..ba40b4984c 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/edges/util/makeEdgeSelector.ts
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/edges/util/makeEdgeSelector.ts
@@ -1,10 +1,17 @@
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { colorTokenToCssVar } from 'common/util/colorTokenToCssVar';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
+import { selectFieldOutputTemplate } from 'features/nodes/store/selectors';
 import { isInvocationNode } from 'features/nodes/types/invocation';
 
 import { getFieldColor } from './getEdgeColor';
 
+const defaultReturnValue = {
+  isSelected: false,
+  shouldAnimate: false,
+  stroke: colorTokenToCssVar('base.500'),
+};
+
 export const makeEdgeSelector = (
   source: string,
   sourceHandleId: string | null | undefined,
@@ -12,14 +19,19 @@ export const makeEdgeSelector = (
   targetHandleId: string | null | undefined,
   selected?: boolean
 ) =>
-  createMemoizedSelector(selectNodesSlice, (nodes) => {
+  createMemoizedSelector(selectNodesSlice, (nodes): { isSelected: boolean; shouldAnimate: boolean; stroke: string } => {
     const sourceNode = nodes.nodes.find((node) => node.id === source);
     const targetNode = nodes.nodes.find((node) => node.id === target);
 
     const isInvocationToInvocationEdge = isInvocationNode(sourceNode) && isInvocationNode(targetNode);
 
-    const isSelected = sourceNode?.selected || targetNode?.selected || selected;
-    const sourceType = isInvocationToInvocationEdge ? sourceNode?.data?.outputs[sourceHandleId || '']?.type : undefined;
+    const isSelected = Boolean(sourceNode?.selected || targetNode?.selected || selected);
+    if (!sourceNode || !sourceHandleId) {
+      return defaultReturnValue;
+    }
+
+    const outputFieldTemplate = selectFieldOutputTemplate(nodes, sourceNode.id, sourceHandleId);
+    const sourceType = isInvocationToInvocationEdge ? outputFieldTemplate?.type : undefined;
 
     const stroke = sourceType && nodes.shouldColorEdges ? getFieldColor(sourceType) : colorTokenToCssVar('base.500');
 
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/InvocationNodeCollapsedHandles.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/InvocationNodeCollapsedHandles.tsx
index c287842f6e..b888e8a516 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/InvocationNodeCollapsedHandles.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/InvocationNodeCollapsedHandles.tsx
@@ -1,6 +1,5 @@
 import { useChakraThemeTokens } from 'common/hooks/useChakraThemeTokens';
-import { useNodeData } from 'features/nodes/hooks/useNodeData';
-import { isInvocationNodeData } from 'features/nodes/types/invocation';
+import { useNodeTemplate } from 'features/nodes/hooks/useNodeTemplate';
 import { map } from 'lodash-es';
 import type { CSSProperties } from 'react';
 import { memo, useMemo } from 'react';
@@ -13,7 +12,7 @@ interface Props {
 const hiddenHandleStyles: CSSProperties = { visibility: 'hidden' };
 
 const InvocationNodeCollapsedHandles = ({ nodeId }: Props) => {
-  const data = useNodeData(nodeId);
+  const template = useNodeTemplate(nodeId);
   const { base600 } = useChakraThemeTokens();
 
   const dummyHandleStyles: CSSProperties = useMemo(
@@ -37,7 +36,7 @@ const InvocationNodeCollapsedHandles = ({ nodeId }: Props) => {
     [dummyHandleStyles]
   );
 
-  if (!isInvocationNodeData(data)) {
+  if (!template) {
     return null;
   }
 
@@ -45,14 +44,14 @@ const InvocationNodeCollapsedHandles = ({ nodeId }: Props) => {
     <>
       <Handle
         type="target"
-        id={`${data.id}-collapsed-target`}
+        id={`${nodeId}-collapsed-target`}
         isConnectable={false}
         position={Position.Left}
         style={collapsedTargetStyles}
       />
-      {map(data.inputs, (input) => (
+      {map(template.inputs, (input) => (
         <Handle
-          key={`${data.id}-${input.name}-collapsed-input-handle`}
+          key={`${nodeId}-${input.name}-collapsed-input-handle`}
           type="target"
           id={input.name}
           isConnectable={false}
@@ -62,14 +61,14 @@ const InvocationNodeCollapsedHandles = ({ nodeId }: Props) => {
       ))}
       <Handle
         type="source"
-        id={`${data.id}-collapsed-source`}
+        id={`${nodeId}-collapsed-source`}
         isConnectable={false}
         position={Position.Right}
         style={collapsedSourceStyles}
       />
-      {map(data.outputs, (output) => (
+      {map(template.outputs, (output) => (
         <Handle
-          key={`${data.id}-${output.name}-collapsed-output-handle`}
+          key={`${nodeId}-${output.name}-collapsed-output-handle`}
           type="source"
           id={output.name}
           isConnectable={false}
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/InvocationNodeWrapper.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/InvocationNodeWrapper.tsx
index d7a5dc3895..0fe81c0882 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/InvocationNodeWrapper.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/InvocationNodeWrapper.tsx
@@ -1,7 +1,7 @@
 import { createSelector } from '@reduxjs/toolkit';
 import { useAppSelector } from 'app/store/storeHooks';
 import InvocationNode from 'features/nodes/components/flow/nodes/Invocation/InvocationNode';
-import { selectNodeTemplatesSlice } from 'features/nodes/store/nodeTemplatesSlice';
+import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
 import type { InvocationNodeData } from 'features/nodes/types/invocation';
 import { memo, useMemo } from 'react';
 import type { NodeProps } from 'reactflow';
@@ -13,7 +13,7 @@ const InvocationNodeWrapper = (props: NodeProps<InvocationNodeData>) => {
   const { id: nodeId, type, isOpen, label } = data;
 
   const hasTemplateSelector = useMemo(
-    () => createSelector(selectNodeTemplatesSlice, (nodeTemplates) => Boolean(nodeTemplates.templates[type])),
+    () => createSelector(selectNodesSlice, (nodes) => Boolean(nodes.templates[type])),
     [type]
   );
 
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/EditableFieldTitle.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/EditableFieldTitle.tsx
index c2231f703a..e02b1a1474 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/EditableFieldTitle.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/EditableFieldTitle.tsx
@@ -22,7 +22,7 @@ import FieldTooltipContent from './FieldTooltipContent';
 interface Props {
   nodeId: string;
   fieldName: string;
-  kind: 'input' | 'output';
+  kind: 'inputs' | 'outputs';
   isMissingInput?: boolean;
   withTooltip?: boolean;
 }
@@ -58,7 +58,7 @@ const EditableFieldTitle = forwardRef((props: Props, ref) => {
 
   return (
     <Tooltip
-      label={withTooltip ? <FieldTooltipContent nodeId={nodeId} fieldName={fieldName} kind="input" /> : undefined}
+      label={withTooltip ? <FieldTooltipContent nodeId={nodeId} fieldName={fieldName} kind="inputs" /> : undefined}
       openDelay={HANDLE_TOOLTIP_OPEN_DELAY}
     >
       <Editable
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/FieldTitle.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/FieldTitle.tsx
index 0d01aaf0ca..61ce8fd971 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/FieldTitle.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/FieldTitle.tsx
@@ -6,7 +6,7 @@ import { memo } from 'react';
 interface Props {
   nodeId: string;
   fieldName: string;
-  kind: 'input' | 'output';
+  kind: 'inputs' | 'outputs';
   isMissingInput?: boolean;
 }
 
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/FieldTooltipContent.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/FieldTooltipContent.tsx
index ce5ab2f8bb..a8925f5b3a 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/FieldTooltipContent.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/FieldTooltipContent.tsx
@@ -1,5 +1,5 @@
 import { Flex, Text } from '@invoke-ai/ui-library';
-import { useFieldInstance } from 'features/nodes/hooks/useFieldData';
+import { useFieldInputInstance } from 'features/nodes/hooks/useFieldInputInstance';
 import { useFieldTemplate } from 'features/nodes/hooks/useFieldTemplate';
 import { useFieldTypeName } from 'features/nodes/hooks/usePrettyFieldType';
 import { isFieldInputInstance, isFieldInputTemplate } from 'features/nodes/types/field';
@@ -9,11 +9,11 @@ import { useTranslation } from 'react-i18next';
 interface Props {
   nodeId: string;
   fieldName: string;
-  kind: 'input' | 'output';
+  kind: 'inputs' | 'outputs';
 }
 
 const FieldTooltipContent = ({ nodeId, fieldName, kind }: Props) => {
-  const field = useFieldInstance(nodeId, fieldName);
+  const field = useFieldInputInstance(nodeId, fieldName);
   const fieldTemplate = useFieldTemplate(nodeId, fieldName, kind);
   const isInputTemplate = isFieldInputTemplate(fieldTemplate);
   const fieldTypeName = useFieldTypeName(fieldTemplate?.type);
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/InputField.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/InputField.tsx
index 2b9f7960e4..66b0d3f755 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/InputField.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/InputField.tsx
@@ -25,7 +25,7 @@ const InputField = ({ nodeId, fieldName }: Props) => {
   const [isHovered, setIsHovered] = useState(false);
 
   const { isConnected, isConnectionInProgress, isConnectionStartField, connectionError, shouldDim } =
-    useConnectionState({ nodeId, fieldName, kind: 'input' });
+    useConnectionState({ nodeId, fieldName, kind: 'inputs' });
 
   const isMissingInput = useMemo(() => {
     if (!fieldTemplate) {
@@ -76,7 +76,7 @@ const InputField = ({ nodeId, fieldName }: Props) => {
           <EditableFieldTitle
             nodeId={nodeId}
             fieldName={fieldName}
-            kind="input"
+            kind="inputs"
             isMissingInput={isMissingInput}
             withTooltip
           />
@@ -101,7 +101,7 @@ const InputField = ({ nodeId, fieldName }: Props) => {
             <EditableFieldTitle
               nodeId={nodeId}
               fieldName={fieldName}
-              kind="input"
+              kind="inputs"
               isMissingInput={isMissingInput}
               withTooltip
             />
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/InputFieldRenderer.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/InputFieldRenderer.tsx
index c1d52c1d4f..b6e331c114 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/InputFieldRenderer.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/InputFieldRenderer.tsx
@@ -1,6 +1,5 @@
-import { Box, Text } from '@invoke-ai/ui-library';
-import { useFieldInstance } from 'features/nodes/hooks/useFieldData';
-import { useFieldTemplate } from 'features/nodes/hooks/useFieldTemplate';
+import { useFieldInputInstance } from 'features/nodes/hooks/useFieldInputInstance';
+import { useFieldInputTemplate } from 'features/nodes/hooks/useFieldInputTemplate';
 import {
   isBoardFieldInputInstance,
   isBoardFieldInputTemplate,
@@ -38,7 +37,6 @@ import {
   isVAEModelFieldInputTemplate,
 } from 'features/nodes/types/field';
 import { memo } from 'react';
-import { useTranslation } from 'react-i18next';
 
 import BoardFieldInputComponent from './inputs/BoardFieldInputComponent';
 import BooleanFieldInputComponent from './inputs/BooleanFieldInputComponent';
@@ -63,17 +61,8 @@ type InputFieldProps = {
 };
 
 const InputFieldRenderer = ({ nodeId, fieldName }: InputFieldProps) => {
-  const { t } = useTranslation();
-  const fieldInstance = useFieldInstance(nodeId, fieldName);
-  const fieldTemplate = useFieldTemplate(nodeId, fieldName, 'input');
-
-  if (fieldTemplate?.fieldKind === 'output') {
-    return (
-      <Box p={2}>
-        {t('nodes.outputFieldInInput')}: {fieldInstance?.type.name}
-      </Box>
-    );
-  }
+  const fieldInstance = useFieldInputInstance(nodeId, fieldName);
+  const fieldTemplate = useFieldInputTemplate(nodeId, fieldName);
 
   if (isStringFieldInputInstance(fieldInstance) && isStringFieldInputTemplate(fieldTemplate)) {
     return <StringFieldInputComponent nodeId={nodeId} field={fieldInstance} fieldTemplate={fieldTemplate} />;
@@ -141,18 +130,10 @@ const InputFieldRenderer = ({ nodeId, fieldName }: InputFieldProps) => {
     return <SchedulerFieldInputComponent nodeId={nodeId} field={fieldInstance} fieldTemplate={fieldTemplate} />;
   }
 
-  if (fieldInstance && fieldTemplate) {
+  if (fieldTemplate) {
     // Fallback for when there is no component for the type
     return null;
   }
-
-  return (
-    <Box p={1}>
-      <Text fontSize="sm" fontWeight="semibold" color="error.300">
-        {t('nodes.unknownFieldType', { type: fieldInstance?.type.name })}
-      </Text>
-    </Box>
-  );
 };
 
 export default memo(InputFieldRenderer);
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx
index d0a30ecc3c..0cd199f7a4 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx
@@ -62,7 +62,7 @@ const LinearViewField = ({ nodeId, fieldName }: Props) => {
       />
       <Flex flexDir="column" w="full">
         <Flex alignItems="center">
-          <EditableFieldTitle nodeId={nodeId} fieldName={fieldName} kind="input" />
+          <EditableFieldTitle nodeId={nodeId} fieldName={fieldName} kind="inputs" />
           <Spacer />
           {isValueChanged && (
             <IconButton
@@ -75,7 +75,7 @@ const LinearViewField = ({ nodeId, fieldName }: Props) => {
             />
           )}
           <Tooltip
-            label={<FieldTooltipContent nodeId={nodeId} fieldName={fieldName} kind="input" />}
+            label={<FieldTooltipContent nodeId={nodeId} fieldName={fieldName} kind="inputs" />}
             openDelay={HANDLE_TOOLTIP_OPEN_DELAY}
             placement="top"
           >
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/OutputField.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/OutputField.tsx
index 48c4c0d740..f2d776a2da 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/OutputField.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/OutputField.tsx
@@ -1,6 +1,5 @@
 import { Flex, FormControl, FormLabel, Tooltip } from '@invoke-ai/ui-library';
 import { useConnectionState } from 'features/nodes/hooks/useConnectionState';
-import { useFieldOutputInstance } from 'features/nodes/hooks/useFieldOutputInstance';
 import { useFieldOutputTemplate } from 'features/nodes/hooks/useFieldOutputTemplate';
 import { HANDLE_TOOLTIP_OPEN_DELAY } from 'features/nodes/types/constants';
 import type { PropsWithChildren } from 'react';
@@ -18,18 +17,17 @@ interface Props {
 const OutputField = ({ nodeId, fieldName }: Props) => {
   const { t } = useTranslation();
   const fieldTemplate = useFieldOutputTemplate(nodeId, fieldName);
-  const fieldInstance = useFieldOutputInstance(nodeId, fieldName);
 
   const { isConnected, isConnectionInProgress, isConnectionStartField, connectionError, shouldDim } =
-    useConnectionState({ nodeId, fieldName, kind: 'output' });
+    useConnectionState({ nodeId, fieldName, kind: 'outputs' });
 
-  if (!fieldTemplate || !fieldInstance) {
+  if (!fieldTemplate) {
     return (
       <OutputFieldWrapper shouldDim={shouldDim}>
         <FormControl alignItems="stretch" justifyContent="space-between" gap={2} h="full" w="full">
           <FormLabel display="flex" alignItems="center" h="full" color="error.300" mb={0} px={1} gap={2}>
             {t('nodes.unknownOutput', {
-              name: fieldTemplate?.title ?? fieldName,
+              name: fieldName,
             })}
           </FormLabel>
         </FormControl>
@@ -40,7 +38,7 @@ const OutputField = ({ nodeId, fieldName }: Props) => {
   return (
     <OutputFieldWrapper shouldDim={shouldDim}>
       <Tooltip
-        label={<FieldTooltipContent nodeId={nodeId} fieldName={fieldName} kind="output" />}
+        label={<FieldTooltipContent nodeId={nodeId} fieldName={fieldName} kind="outputs" />}
         openDelay={HANDLE_TOOLTIP_OPEN_DELAY}
         placement="top"
         shouldWrapChildren
diff --git a/invokeai/frontend/web/src/features/nodes/components/sidePanel/inspector/InspectorDetailsTab.tsx b/invokeai/frontend/web/src/features/nodes/components/sidePanel/inspector/InspectorDetailsTab.tsx
index b7c9033d6b..d72d2f5aa8 100644
--- a/invokeai/frontend/web/src/features/nodes/components/sidePanel/inspector/InspectorDetailsTab.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/sidePanel/inspector/InspectorDetailsTab.tsx
@@ -6,19 +6,18 @@ import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableCon
 import NotesTextarea from 'features/nodes/components/flow/nodes/Invocation/NotesTextarea';
 import { useNodeNeedsUpdate } from 'features/nodes/hooks/useNodeNeedsUpdate';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { selectNodeTemplatesSlice } from 'features/nodes/store/nodeTemplatesSlice';
 import { isInvocationNode } from 'features/nodes/types/invocation';
 import { memo } from 'react';
 import { useTranslation } from 'react-i18next';
 
 import EditableNodeTitle from './details/EditableNodeTitle';
 
-const selector = createMemoizedSelector(selectNodesSlice, selectNodeTemplatesSlice, (nodes, nodeTemplates) => {
+const selector = createMemoizedSelector(selectNodesSlice, (nodes) => {
   const lastSelectedNodeId = nodes.selectedNodes[nodes.selectedNodes.length - 1];
 
   const lastSelectedNode = nodes.nodes.find((node) => node.id === lastSelectedNodeId);
 
-  const lastSelectedNodeTemplate = lastSelectedNode ? nodeTemplates.templates[lastSelectedNode.data.type] : undefined;
+  const lastSelectedNodeTemplate = lastSelectedNode ? nodes.templates[lastSelectedNode.data.type] : undefined;
 
   if (!isInvocationNode(lastSelectedNode) || !lastSelectedNodeTemplate) {
     return;
diff --git a/invokeai/frontend/web/src/features/nodes/components/sidePanel/inspector/InspectorOutputsTab.tsx b/invokeai/frontend/web/src/features/nodes/components/sidePanel/inspector/InspectorOutputsTab.tsx
index ee7dfaa693..978eeddd24 100644
--- a/invokeai/frontend/web/src/features/nodes/components/sidePanel/inspector/InspectorOutputsTab.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/sidePanel/inspector/InspectorOutputsTab.tsx
@@ -5,7 +5,6 @@ import { IAINoContentFallback } from 'common/components/IAIImageFallback';
 import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
 import DataViewer from 'features/gallery/components/ImageMetadataViewer/DataViewer';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { selectNodeTemplatesSlice } from 'features/nodes/store/nodeTemplatesSlice';
 import { isInvocationNode } from 'features/nodes/types/invocation';
 import { memo } from 'react';
 import { useTranslation } from 'react-i18next';
@@ -14,12 +13,12 @@ import type { AnyResult } from 'services/events/types';
 
 import ImageOutputPreview from './outputs/ImageOutputPreview';
 
-const selector = createMemoizedSelector(selectNodesSlice, selectNodeTemplatesSlice, (nodes, nodeTemplates) => {
+const selector = createMemoizedSelector(selectNodesSlice, (nodes) => {
   const lastSelectedNodeId = nodes.selectedNodes[nodes.selectedNodes.length - 1];
 
   const lastSelectedNode = nodes.nodes.find((node) => node.id === lastSelectedNodeId);
 
-  const lastSelectedNodeTemplate = lastSelectedNode ? nodeTemplates.templates[lastSelectedNode.data.type] : undefined;
+  const lastSelectedNodeTemplate = lastSelectedNode ? nodes.templates[lastSelectedNode.data.type] : undefined;
 
   const nes = nodes.nodeExecutionStates[lastSelectedNodeId ?? '__UNKNOWN_NODE__'];
 
diff --git a/invokeai/frontend/web/src/features/nodes/components/sidePanel/inspector/InspectorTemplateTab.tsx b/invokeai/frontend/web/src/features/nodes/components/sidePanel/inspector/InspectorTemplateTab.tsx
index 28f0e82d68..ea6e8ed704 100644
--- a/invokeai/frontend/web/src/features/nodes/components/sidePanel/inspector/InspectorTemplateTab.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/sidePanel/inspector/InspectorTemplateTab.tsx
@@ -3,16 +3,15 @@ import { useAppSelector } from 'app/store/storeHooks';
 import { IAINoContentFallback } from 'common/components/IAIImageFallback';
 import DataViewer from 'features/gallery/components/ImageMetadataViewer/DataViewer';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { selectNodeTemplatesSlice } from 'features/nodes/store/nodeTemplatesSlice';
 import { memo } from 'react';
 import { useTranslation } from 'react-i18next';
 
-const selector = createMemoizedSelector(selectNodesSlice, selectNodeTemplatesSlice, (nodes, nodeTemplates) => {
+const selector = createMemoizedSelector(selectNodesSlice, (nodes) => {
   const lastSelectedNodeId = nodes.selectedNodes[nodes.selectedNodes.length - 1];
 
   const lastSelectedNode = nodes.nodes.find((node) => node.id === lastSelectedNodeId);
 
-  const lastSelectedNodeTemplate = lastSelectedNode ? nodeTemplates.templates[lastSelectedNode.data.type] : undefined;
+  const lastSelectedNodeTemplate = lastSelectedNode ? nodes.templates[lastSelectedNode.data.type] : undefined;
 
   return {
     template: lastSelectedNodeTemplate,
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useAnyOrDirectInputFieldNames.ts b/invokeai/frontend/web/src/features/nodes/hooks/useAnyOrDirectInputFieldNames.ts
index d0263a8bda..c882924e24 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useAnyOrDirectInputFieldNames.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useAnyOrDirectInputFieldNames.ts
@@ -1,26 +1,22 @@
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppSelector } from 'app/store/storeHooks';
+import { EMPTY_ARRAY } from 'app/store/util';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { selectNodeTemplatesSlice } from 'features/nodes/store/nodeTemplatesSlice';
-import { isInvocationNode } from 'features/nodes/types/invocation';
+import { selectNodeTemplate } from 'features/nodes/store/selectors';
 import { getSortedFilteredFieldNames } from 'features/nodes/util/node/getSortedFilteredFieldNames';
 import { TEMPLATE_BUILDER_MAP } from 'features/nodes/util/schema/buildFieldInputTemplate';
 import { keys, map } from 'lodash-es';
 import { useMemo } from 'react';
 
-export const useAnyOrDirectInputFieldNames = (nodeId: string) => {
+export const useAnyOrDirectInputFieldNames = (nodeId: string): string[] => {
   const selector = useMemo(
     () =>
-      createMemoizedSelector(selectNodesSlice, selectNodeTemplatesSlice, (nodes, nodeTemplates) => {
-        const node = nodes.nodes.find((node) => node.id === nodeId);
-        if (!isInvocationNode(node)) {
-          return [];
+      createMemoizedSelector(selectNodesSlice, (nodes) => {
+        const template = selectNodeTemplate(nodes, nodeId);
+        if (!template) {
+          return EMPTY_ARRAY;
         }
-        const nodeTemplate = nodeTemplates.templates[node.data.type];
-        if (!nodeTemplate) {
-          return [];
-        }
-        const fields = map(nodeTemplate.inputs).filter(
+        const fields = map(template.inputs).filter(
           (field) =>
             (['any', 'direct'].includes(field.input) || field.type.isCollectionOrScalar) &&
             keys(TEMPLATE_BUILDER_MAP).includes(field.type.name)
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useBuildNode.ts b/invokeai/frontend/web/src/features/nodes/hooks/useBuildNode.ts
index aecc931893..b19edf3c85 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useBuildNode.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useBuildNode.ts
@@ -13,7 +13,7 @@ export const SHARED_NODE_PROPERTIES: Partial<Node> = {
 };
 
 export const useBuildNode = () => {
-  const nodeTemplates = useAppSelector((s) => s.nodeTemplates.templates);
+  const nodeTemplates = useAppSelector((s) => s.nodes.templates);
 
   const flow = useReactFlow();
 
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useConnectionInputFieldNames.ts b/invokeai/frontend/web/src/features/nodes/hooks/useConnectionInputFieldNames.ts
index 23f318517b..dc8a05b88c 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useConnectionInputFieldNames.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useConnectionInputFieldNames.ts
@@ -1,28 +1,24 @@
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppSelector } from 'app/store/storeHooks';
+import { EMPTY_ARRAY } from 'app/store/util';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { selectNodeTemplatesSlice } from 'features/nodes/store/nodeTemplatesSlice';
-import { isInvocationNode } from 'features/nodes/types/invocation';
+import { selectNodeTemplate } from 'features/nodes/store/selectors';
 import { getSortedFilteredFieldNames } from 'features/nodes/util/node/getSortedFilteredFieldNames';
 import { TEMPLATE_BUILDER_MAP } from 'features/nodes/util/schema/buildFieldInputTemplate';
 import { keys, map } from 'lodash-es';
 import { useMemo } from 'react';
 
-export const useConnectionInputFieldNames = (nodeId: string) => {
+export const useConnectionInputFieldNames = (nodeId: string): string[] => {
   const selector = useMemo(
     () =>
-      createMemoizedSelector(selectNodesSlice, selectNodeTemplatesSlice, (nodes, nodeTemplates) => {
-        const node = nodes.nodes.find((node) => node.id === nodeId);
-        if (!isInvocationNode(node)) {
-          return [];
-        }
-        const nodeTemplate = nodeTemplates.templates[node.data.type];
-        if (!nodeTemplate) {
-          return [];
+      createMemoizedSelector(selectNodesSlice, (nodes) => {
+        const template = selectNodeTemplate(nodes, nodeId);
+        if (!template) {
+          return EMPTY_ARRAY;
         }
 
         // get the visible fields
-        const fields = map(nodeTemplate.inputs).filter(
+        const fields = map(template.inputs).filter(
           (field) =>
             (field.input === 'connection' && !field.type.isCollectionOrScalar) ||
             !keys(TEMPLATE_BUILDER_MAP).includes(field.type.name)
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useConnectionState.ts b/invokeai/frontend/web/src/features/nodes/hooks/useConnectionState.ts
index a6f8b663f6..97b96f323a 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useConnectionState.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useConnectionState.ts
@@ -14,7 +14,7 @@ const selectIsConnectionInProgress = createSelector(
 export type UseConnectionStateProps = {
   nodeId: string;
   fieldName: string;
-  kind: 'input' | 'output';
+  kind: 'inputs' | 'outputs';
 };
 
 export const useConnectionState = ({ nodeId, fieldName, kind }: UseConnectionStateProps) => {
@@ -26,8 +26,8 @@ export const useConnectionState = ({ nodeId, fieldName, kind }: UseConnectionSta
         Boolean(
           nodes.edges.filter((edge) => {
             return (
-              (kind === 'input' ? edge.target : edge.source) === nodeId &&
-              (kind === 'input' ? edge.targetHandle : edge.sourceHandle) === fieldName
+              (kind === 'inputs' ? edge.target : edge.source) === nodeId &&
+              (kind === 'inputs' ? edge.targetHandle : edge.sourceHandle) === fieldName
             );
           }).length
         )
@@ -36,7 +36,7 @@ export const useConnectionState = ({ nodeId, fieldName, kind }: UseConnectionSta
   );
 
   const selectConnectionError = useMemo(
-    () => makeConnectionErrorSelector(nodeId, fieldName, kind === 'input' ? 'target' : 'source', fieldType),
+    () => makeConnectionErrorSelector(nodeId, fieldName, kind === 'inputs' ? 'target' : 'source', fieldType),
     [nodeId, fieldName, kind, fieldType]
   );
 
@@ -46,7 +46,7 @@ export const useConnectionState = ({ nodeId, fieldName, kind }: UseConnectionSta
         Boolean(
           nodes.connectionStartParams?.nodeId === nodeId &&
             nodes.connectionStartParams?.handleId === fieldName &&
-            nodes.connectionStartParams?.handleType === { input: 'target', output: 'source' }[kind]
+            nodes.connectionStartParams?.handleType === { inputs: 'target', outputs: 'source' }[kind]
         )
       ),
     [fieldName, kind, nodeId]
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useDoNodeVersionsMatch.ts b/invokeai/frontend/web/src/features/nodes/hooks/useDoNodeVersionsMatch.ts
index bfbf0a3b2d..91994cf752 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useDoNodeVersionsMatch.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useDoNodeVersionsMatch.ts
@@ -2,23 +2,19 @@ import { createSelector } from '@reduxjs/toolkit';
 import { useAppSelector } from 'app/store/storeHooks';
 import { compareVersions } from 'compare-versions';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { selectNodeTemplatesSlice } from 'features/nodes/store/nodeTemplatesSlice';
-import { isInvocationNode } from 'features/nodes/types/invocation';
+import { selectNodeData, selectNodeTemplate } from 'features/nodes/store/selectors';
 import { useMemo } from 'react';
 
-export const useDoNodeVersionsMatch = (nodeId: string) => {
+export const useDoNodeVersionsMatch = (nodeId: string): boolean => {
   const selector = useMemo(
     () =>
-      createSelector(selectNodesSlice, selectNodeTemplatesSlice, (nodes, nodeTemplates) => {
-        const node = nodes.nodes.find((node) => node.id === nodeId);
-        if (!isInvocationNode(node)) {
+      createSelector(selectNodesSlice, (nodes) => {
+        const data = selectNodeData(nodes, nodeId);
+        const template = selectNodeTemplate(nodes, nodeId);
+        if (!template?.version || !data?.version) {
           return false;
         }
-        const nodeTemplate = nodeTemplates.templates[node?.data.type ?? ''];
-        if (!nodeTemplate?.version || !node.data?.version) {
-          return false;
-        }
-        return compareVersions(nodeTemplate.version, node.data.version) === 0;
+        return compareVersions(template.version, data.version) === 0;
       }),
     [nodeId]
   );
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useDoesInputHaveValue.ts b/invokeai/frontend/web/src/features/nodes/hooks/useDoesInputHaveValue.ts
index cfe5c90d9c..5051eaa55b 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useDoesInputHaveValue.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useDoesInputHaveValue.ts
@@ -1,18 +1,18 @@
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppSelector } from 'app/store/storeHooks';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { isInvocationNode } from 'features/nodes/types/invocation';
+import { selectNodeData } from 'features/nodes/store/selectors';
 import { useMemo } from 'react';
 
-export const useDoesInputHaveValue = (nodeId: string, fieldName: string) => {
+export const useDoesInputHaveValue = (nodeId: string, fieldName: string): boolean => {
   const selector = useMemo(
     () =>
       createMemoizedSelector(selectNodesSlice, (nodes) => {
-        const node = nodes.nodes.find((node) => node.id === nodeId);
-        if (!isInvocationNode(node)) {
-          return;
+        const data = selectNodeData(nodes, nodeId);
+        if (!data) {
+          return false;
         }
-        return node?.data.inputs[fieldName]?.value !== undefined;
+        return data.inputs[fieldName]?.value !== undefined;
       }),
     [fieldName, nodeId]
   );
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useFieldData.ts b/invokeai/frontend/web/src/features/nodes/hooks/useFieldData.ts
deleted file mode 100644
index 8b35a2d44b..0000000000
--- a/invokeai/frontend/web/src/features/nodes/hooks/useFieldData.ts
+++ /dev/null
@@ -1,23 +0,0 @@
-import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
-import { useAppSelector } from 'app/store/storeHooks';
-import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { isInvocationNode } from 'features/nodes/types/invocation';
-import { useMemo } from 'react';
-
-export const useFieldInstance = (nodeId: string, fieldName: string) => {
-  const selector = useMemo(
-    () =>
-      createMemoizedSelector(selectNodesSlice, (nodes) => {
-        const node = nodes.nodes.find((node) => node.id === nodeId);
-        if (!isInvocationNode(node)) {
-          return;
-        }
-        return node?.data.inputs[fieldName];
-      }),
-    [fieldName, nodeId]
-  );
-
-  const fieldData = useAppSelector(selector);
-
-  return fieldData;
-};
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useFieldInputInstance.ts b/invokeai/frontend/web/src/features/nodes/hooks/useFieldInputInstance.ts
index 0793f1f952..25065e7aba 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useFieldInputInstance.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useFieldInputInstance.ts
@@ -1,23 +1,20 @@
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppSelector } from 'app/store/storeHooks';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { isInvocationNode } from 'features/nodes/types/invocation';
+import { selectFieldInputInstance } from 'features/nodes/store/selectors';
+import type { FieldInputInstance } from 'features/nodes/types/field';
 import { useMemo } from 'react';
 
-export const useFieldInputInstance = (nodeId: string, fieldName: string) => {
+export const useFieldInputInstance = (nodeId: string, fieldName: string): FieldInputInstance | null => {
   const selector = useMemo(
     () =>
       createMemoizedSelector(selectNodesSlice, (nodes) => {
-        const node = nodes.nodes.find((node) => node.id === nodeId);
-        if (!isInvocationNode(node)) {
-          return;
-        }
-        return node.data.inputs[fieldName];
+        return selectFieldInputInstance(nodes, nodeId, fieldName);
       }),
     [fieldName, nodeId]
   );
 
-  const fieldTemplate = useAppSelector(selector);
+  const fieldData = useAppSelector(selector);
 
-  return fieldTemplate;
+  return fieldData;
 };
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useFieldInputKind.ts b/invokeai/frontend/web/src/features/nodes/hooks/useFieldInputKind.ts
index 11d44dbde2..08de3d9b20 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useFieldInputKind.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useFieldInputKind.ts
@@ -1,21 +1,16 @@
 import { createSelector } from '@reduxjs/toolkit';
 import { useAppSelector } from 'app/store/storeHooks';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { selectNodeTemplatesSlice } from 'features/nodes/store/nodeTemplatesSlice';
-import { isInvocationNode } from 'features/nodes/types/invocation';
+import { selectFieldInputTemplate } from 'features/nodes/store/selectors';
+import type { FieldInput } from 'features/nodes/types/field';
 import { useMemo } from 'react';
 
 export const useFieldInputKind = (nodeId: string, fieldName: string) => {
   const selector = useMemo(
     () =>
-      createSelector(selectNodesSlice, selectNodeTemplatesSlice, (nodes, nodeTemplates) => {
-        const node = nodes.nodes.find((node) => node.id === nodeId);
-        if (!isInvocationNode(node)) {
-          return;
-        }
-        const nodeTemplate = nodeTemplates.templates[node?.data.type ?? ''];
-        const fieldTemplate = nodeTemplate?.inputs[fieldName];
-        return fieldTemplate?.input;
+      createSelector(selectNodesSlice, (nodes): FieldInput | null => {
+        const template = selectFieldInputTemplate(nodes, nodeId, fieldName);
+        return template?.input ?? null;
       }),
     [fieldName, nodeId]
   );
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useFieldInputTemplate.ts b/invokeai/frontend/web/src/features/nodes/hooks/useFieldInputTemplate.ts
index 8533d2be8d..e8289d7e07 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useFieldInputTemplate.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useFieldInputTemplate.ts
@@ -1,20 +1,15 @@
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppSelector } from 'app/store/storeHooks';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { selectNodeTemplatesSlice } from 'features/nodes/store/nodeTemplatesSlice';
-import { isInvocationNode } from 'features/nodes/types/invocation';
+import { selectFieldInputTemplate } from 'features/nodes/store/selectors';
+import type { FieldInputTemplate } from 'features/nodes/types/field';
 import { useMemo } from 'react';
 
-export const useFieldInputTemplate = (nodeId: string, fieldName: string) => {
+export const useFieldInputTemplate = (nodeId: string, fieldName: string): FieldInputTemplate | null => {
   const selector = useMemo(
     () =>
-      createMemoizedSelector(selectNodesSlice, selectNodeTemplatesSlice, (nodes, nodeTemplates) => {
-        const node = nodes.nodes.find((node) => node.id === nodeId);
-        if (!isInvocationNode(node)) {
-          return;
-        }
-        const nodeTemplate = nodeTemplates.templates[node?.data.type ?? ''];
-        return nodeTemplate?.inputs[fieldName];
+      createMemoizedSelector(selectNodesSlice, (nodes) => {
+        return selectFieldInputTemplate(nodes, nodeId, fieldName);
       }),
     [fieldName, nodeId]
   );
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useFieldLabel.ts b/invokeai/frontend/web/src/features/nodes/hooks/useFieldLabel.ts
index ef57956047..92eab8d1b1 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useFieldLabel.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useFieldLabel.ts
@@ -1,18 +1,14 @@
 import { createSelector } from '@reduxjs/toolkit';
 import { useAppSelector } from 'app/store/storeHooks';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { isInvocationNode } from 'features/nodes/types/invocation';
+import { selectFieldInputInstance } from 'features/nodes/store/selectors';
 import { useMemo } from 'react';
 
-export const useFieldLabel = (nodeId: string, fieldName: string) => {
+export const useFieldLabel = (nodeId: string, fieldName: string): string | null => {
   const selector = useMemo(
     () =>
       createSelector(selectNodesSlice, (nodes) => {
-        const node = nodes.nodes.find((node) => node.id === nodeId);
-        if (!isInvocationNode(node)) {
-          return;
-        }
-        return node?.data.inputs[fieldName]?.label;
+        return selectFieldInputInstance(nodes, nodeId, fieldName)?.label ?? null;
       }),
     [fieldName, nodeId]
   );
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useFieldOutputInstance.ts b/invokeai/frontend/web/src/features/nodes/hooks/useFieldOutputInstance.ts
deleted file mode 100644
index 8b71f1ea01..0000000000
--- a/invokeai/frontend/web/src/features/nodes/hooks/useFieldOutputInstance.ts
+++ /dev/null
@@ -1,23 +0,0 @@
-import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
-import { useAppSelector } from 'app/store/storeHooks';
-import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { isInvocationNode } from 'features/nodes/types/invocation';
-import { useMemo } from 'react';
-
-export const useFieldOutputInstance = (nodeId: string, fieldName: string) => {
-  const selector = useMemo(
-    () =>
-      createMemoizedSelector(selectNodesSlice, (nodes) => {
-        const node = nodes.nodes.find((node) => node.id === nodeId);
-        if (!isInvocationNode(node)) {
-          return;
-        }
-        return node.data.outputs[fieldName];
-      }),
-    [fieldName, nodeId]
-  );
-
-  const fieldTemplate = useAppSelector(selector);
-
-  return fieldTemplate;
-};
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useFieldOutputTemplate.ts b/invokeai/frontend/web/src/features/nodes/hooks/useFieldOutputTemplate.ts
index 11f592b399..cb154071e9 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useFieldOutputTemplate.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useFieldOutputTemplate.ts
@@ -1,20 +1,15 @@
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppSelector } from 'app/store/storeHooks';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { selectNodeTemplatesSlice } from 'features/nodes/store/nodeTemplatesSlice';
-import { isInvocationNode } from 'features/nodes/types/invocation';
+import { selectFieldOutputTemplate } from 'features/nodes/store/selectors';
+import type { FieldOutputTemplate } from 'features/nodes/types/field';
 import { useMemo } from 'react';
 
-export const useFieldOutputTemplate = (nodeId: string, fieldName: string) => {
+export const useFieldOutputTemplate = (nodeId: string, fieldName: string): FieldOutputTemplate | null => {
   const selector = useMemo(
     () =>
-      createMemoizedSelector(selectNodesSlice, selectNodeTemplatesSlice, (nodes, nodeTemplates) => {
-        const node = nodes.nodes.find((node) => node.id === nodeId);
-        if (!isInvocationNode(node)) {
-          return;
-        }
-        const nodeTemplate = nodeTemplates.templates[node?.data.type ?? ''];
-        return nodeTemplate?.outputs[fieldName];
+      createMemoizedSelector(selectNodesSlice, (nodes) => {
+        return selectFieldOutputTemplate(nodes, nodeId, fieldName);
       }),
     [fieldName, nodeId]
   );
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useFieldTemplate.ts b/invokeai/frontend/web/src/features/nodes/hooks/useFieldTemplate.ts
index 663821da81..7be4ecfd4d 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useFieldTemplate.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useFieldTemplate.ts
@@ -1,21 +1,22 @@
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppSelector } from 'app/store/storeHooks';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { selectNodeTemplatesSlice } from 'features/nodes/store/nodeTemplatesSlice';
-import { KIND_MAP } from 'features/nodes/types/constants';
-import { isInvocationNode } from 'features/nodes/types/invocation';
+import { selectFieldInputTemplate, selectFieldOutputTemplate } from 'features/nodes/store/selectors';
+import type { FieldInputTemplate, FieldOutputTemplate } from 'features/nodes/types/field';
 import { useMemo } from 'react';
 
-export const useFieldTemplate = (nodeId: string, fieldName: string, kind: 'input' | 'output') => {
+export const useFieldTemplate = (
+  nodeId: string,
+  fieldName: string,
+  kind: 'inputs' | 'outputs'
+): FieldInputTemplate | FieldOutputTemplate | null => {
   const selector = useMemo(
     () =>
-      createMemoizedSelector(selectNodesSlice, selectNodeTemplatesSlice, (nodes, nodeTemplates) => {
-        const node = nodes.nodes.find((node) => node.id === nodeId);
-        if (!isInvocationNode(node)) {
-          return;
+      createMemoizedSelector(selectNodesSlice, (nodes) => {
+        if (kind === 'inputs') {
+          return selectFieldInputTemplate(nodes, nodeId, fieldName);
         }
-        const nodeTemplate = nodeTemplates.templates[node?.data.type ?? ''];
-        return nodeTemplate?.[KIND_MAP[kind]][fieldName];
+        return selectFieldOutputTemplate(nodes, nodeId, fieldName);
       }),
     [fieldName, kind, nodeId]
   );
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useFieldTemplateTitle.ts b/invokeai/frontend/web/src/features/nodes/hooks/useFieldTemplateTitle.ts
index cfdcda6efa..e41e019572 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useFieldTemplateTitle.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useFieldTemplateTitle.ts
@@ -1,21 +1,17 @@
 import { createSelector } from '@reduxjs/toolkit';
 import { useAppSelector } from 'app/store/storeHooks';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { selectNodeTemplatesSlice } from 'features/nodes/store/nodeTemplatesSlice';
-import { KIND_MAP } from 'features/nodes/types/constants';
-import { isInvocationNode } from 'features/nodes/types/invocation';
+import { selectFieldInputTemplate, selectFieldOutputTemplate } from 'features/nodes/store/selectors';
 import { useMemo } from 'react';
 
-export const useFieldTemplateTitle = (nodeId: string, fieldName: string, kind: 'input' | 'output') => {
+export const useFieldTemplateTitle = (nodeId: string, fieldName: string, kind: 'inputs' | 'outputs'): string | null => {
   const selector = useMemo(
     () =>
-      createSelector(selectNodesSlice, selectNodeTemplatesSlice, (nodes, nodeTemplates) => {
-        const node = nodes.nodes.find((node) => node.id === nodeId);
-        if (!isInvocationNode(node)) {
-          return;
+      createSelector(selectNodesSlice, (nodes) => {
+        if (kind === 'inputs') {
+          return selectFieldInputTemplate(nodes, nodeId, fieldName)?.title ?? null;
         }
-        const nodeTemplate = nodeTemplates.templates[node?.data.type ?? ''];
-        return nodeTemplate?.[KIND_MAP[kind]][fieldName]?.title;
+        return selectFieldOutputTemplate(nodes, nodeId, fieldName)?.title ?? null;
       }),
     [fieldName, kind, nodeId]
   );
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useFieldType.ts.ts b/invokeai/frontend/web/src/features/nodes/hooks/useFieldType.ts.ts
index a834726a13..a71a4d044e 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useFieldType.ts.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useFieldType.ts.ts
@@ -1,20 +1,18 @@
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppSelector } from 'app/store/storeHooks';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { KIND_MAP } from 'features/nodes/types/constants';
-import { isInvocationNode } from 'features/nodes/types/invocation';
+import { selectFieldInputTemplate, selectFieldOutputTemplate } from 'features/nodes/store/selectors';
+import type { FieldType } from 'features/nodes/types/field';
 import { useMemo } from 'react';
 
-export const useFieldType = (nodeId: string, fieldName: string, kind: 'input' | 'output') => {
+export const useFieldType = (nodeId: string, fieldName: string, kind: 'inputs' | 'outputs'): FieldType | null => {
   const selector = useMemo(
     () =>
       createMemoizedSelector(selectNodesSlice, (nodes) => {
-        const node = nodes.nodes.find((node) => node.id === nodeId);
-        if (!isInvocationNode(node)) {
-          return;
+        if (kind === 'inputs') {
+          return selectFieldInputTemplate(nodes, nodeId, fieldName)?.type ?? null;
         }
-        const field = node.data[KIND_MAP[kind]][fieldName];
-        return field?.type;
+        return selectFieldOutputTemplate(nodes, nodeId, fieldName)?.type ?? null;
       }),
     [fieldName, kind, nodeId]
   );
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useGetNodesNeedUpdate.ts b/invokeai/frontend/web/src/features/nodes/hooks/useGetNodesNeedUpdate.ts
index a8019c92d6..71344197d5 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useGetNodesNeedUpdate.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useGetNodesNeedUpdate.ts
@@ -1,13 +1,12 @@
 import { createSelector } from '@reduxjs/toolkit';
 import { useAppSelector } from 'app/store/storeHooks';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { selectNodeTemplatesSlice } from 'features/nodes/store/nodeTemplatesSlice';
 import { isInvocationNode } from 'features/nodes/types/invocation';
 import { getNeedsUpdate } from 'features/nodes/util/node/nodeUpdate';
 
-const selector = createSelector(selectNodesSlice, selectNodeTemplatesSlice, (nodes, nodeTemplates) =>
+const selector = createSelector(selectNodesSlice, (nodes) =>
   nodes.nodes.filter(isInvocationNode).some((node) => {
-    const template = nodeTemplates.templates[node.data.type];
+    const template = nodes.templates[node.data.type];
     if (!template) {
       return false;
     }
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useHasImageOutput.ts b/invokeai/frontend/web/src/features/nodes/hooks/useHasImageOutput.ts
index 617e713c7c..3ac3cabb22 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useHasImageOutput.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useHasImageOutput.ts
@@ -1,24 +1,21 @@
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppSelector } from 'app/store/storeHooks';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { isInvocationNode } from 'features/nodes/types/invocation';
+import { selectNodeTemplate } from 'features/nodes/store/selectors';
 import { some } from 'lodash-es';
 import { useMemo } from 'react';
 
-export const useHasImageOutput = (nodeId: string) => {
+export const useHasImageOutput = (nodeId: string): boolean => {
   const selector = useMemo(
     () =>
       createMemoizedSelector(selectNodesSlice, (nodes) => {
-        const node = nodes.nodes.find((node) => node.id === nodeId);
-        if (!isInvocationNode(node)) {
-          return false;
-        }
+        const template = selectNodeTemplate(nodes, nodeId);
         return some(
-          node.data.outputs,
+          template?.outputs,
           (output) =>
             output.type.name === 'ImageField' &&
             // the image primitive node (node type "image") does not actually save the image, do not show the image-saving checkboxes
-            node.data.type !== 'image'
+            template?.type !== 'image'
         );
       }),
     [nodeId]
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useIsIntermediate.ts b/invokeai/frontend/web/src/features/nodes/hooks/useIsIntermediate.ts
index 729bfa0cea..3fad0a2a86 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useIsIntermediate.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useIsIntermediate.ts
@@ -1,18 +1,14 @@
 import { createSelector } from '@reduxjs/toolkit';
 import { useAppSelector } from 'app/store/storeHooks';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { isInvocationNode } from 'features/nodes/types/invocation';
+import { selectNodeData } from 'features/nodes/store/selectors';
 import { useMemo } from 'react';
 
-export const useIsIntermediate = (nodeId: string) => {
+export const useIsIntermediate = (nodeId: string): boolean => {
   const selector = useMemo(
     () =>
       createSelector(selectNodesSlice, (nodes) => {
-        const node = nodes.nodes.find((node) => node.id === nodeId);
-        if (!isInvocationNode(node)) {
-          return false;
-        }
-        return node.data.isIntermediate;
+        return selectNodeData(nodes, nodeId)?.isIntermediate ?? false;
       }),
     [nodeId]
   );
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useIsValidConnection.ts b/invokeai/frontend/web/src/features/nodes/hooks/useIsValidConnection.ts
index 39a8abbe7a..ded05c7b9b 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useIsValidConnection.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useIsValidConnection.ts
@@ -1,11 +1,10 @@
 // TODO: enable this at some point
-import { useAppSelector } from 'app/store/storeHooks';
+import { useAppSelector, useAppStore } from 'app/store/storeHooks';
 import { getIsGraphAcyclic } from 'features/nodes/store/util/getIsGraphAcyclic';
 import { validateSourceAndTargetTypes } from 'features/nodes/store/util/validateSourceAndTargetTypes';
 import type { InvocationNodeData } from 'features/nodes/types/invocation';
 import { useCallback } from 'react';
 import type { Connection, Node } from 'reactflow';
-import { useReactFlow } from 'reactflow';
 
 /**
  * NOTE: The logic here must be duplicated in `invokeai/frontend/web/src/features/nodes/store/util/makeIsConnectionValidSelector.ts`
@@ -13,39 +12,34 @@ import { useReactFlow } from 'reactflow';
  */
 
 export const useIsValidConnection = () => {
-  const flow = useReactFlow();
+  const store = useAppStore();
   const shouldValidateGraph = useAppSelector((s) => s.nodes.shouldValidateGraph);
   const isValidConnection = useCallback(
     ({ source, sourceHandle, target, targetHandle }: Connection): boolean => {
-      const edges = flow.getEdges();
-      const nodes = flow.getNodes();
       // Connection must have valid targets
       if (!(source && sourceHandle && target && targetHandle)) {
         return false;
       }
 
-      // Find the source and target nodes
-      const sourceNode = flow.getNode(source) as Node<InvocationNodeData>;
-      const targetNode = flow.getNode(target) as Node<InvocationNodeData>;
-
-      // Conditional guards against undefined nodes/handles
-      if (!(sourceNode && targetNode && sourceNode.data && targetNode.data)) {
-        return false;
-      }
-
-      const sourceField = sourceNode.data.outputs[sourceHandle];
-      const targetField = targetNode.data.inputs[targetHandle];
-
-      if (!sourceField || !targetField) {
-        // something has gone terribly awry
-        return false;
-      }
-
       if (source === target) {
         // Don't allow nodes to connect to themselves, even if validation is disabled
         return false;
       }
 
+      const state = store.getState();
+      const { nodes, edges, templates } = state.nodes;
+
+      // Find the source and target nodes
+      const sourceNode = nodes.find((node) => node.id === source) as Node<InvocationNodeData>;
+      const targetNode = nodes.find((node) => node.id === target) as Node<InvocationNodeData>;
+      const sourceFieldTemplate = templates[sourceNode.data.type]?.outputs[sourceHandle];
+      const targetFieldTemplate = templates[targetNode.data.type]?.inputs[targetHandle];
+
+      // Conditional guards against undefined nodes/handles
+      if (!(sourceFieldTemplate && targetFieldTemplate)) {
+        return false;
+      }
+
       if (!shouldValidateGraph) {
         // manual override!
         return true;
@@ -69,20 +63,20 @@ export const useIsValidConnection = () => {
           return edge.target === target && edge.targetHandle === targetHandle;
         }) &&
         // except CollectionItem inputs can have multiples
-        targetField.type.name !== 'CollectionItemField'
+        targetFieldTemplate.type.name !== 'CollectionItemField'
       ) {
         return false;
       }
 
       // Must use the originalType here if it exists
-      if (!validateSourceAndTargetTypes(sourceField.type, targetField.type)) {
+      if (!validateSourceAndTargetTypes(sourceFieldTemplate.type, targetFieldTemplate.type)) {
         return false;
       }
 
       // Graphs much be acyclic (no loops!)
       return getIsGraphAcyclic(source, target, nodes, edges);
     },
-    [flow, shouldValidateGraph]
+    [shouldValidateGraph, store]
   );
 
   return isValidConnection;
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useNodeClassification.ts b/invokeai/frontend/web/src/features/nodes/hooks/useNodeClassification.ts
index c61721030e..bab8ff3f19 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useNodeClassification.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useNodeClassification.ts
@@ -1,20 +1,15 @@
-import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
+import { createSelector } from '@reduxjs/toolkit';
 import { useAppSelector } from 'app/store/storeHooks';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { selectNodeTemplatesSlice } from 'features/nodes/store/nodeTemplatesSlice';
-import { isInvocationNode } from 'features/nodes/types/invocation';
+import { selectNodeTemplate } from 'features/nodes/store/selectors';
+import type { Classification } from 'features/nodes/types/common';
 import { useMemo } from 'react';
 
-export const useNodeClassification = (nodeId: string) => {
+export const useNodeClassification = (nodeId: string): Classification | null => {
   const selector = useMemo(
     () =>
-      createMemoizedSelector(selectNodesSlice, selectNodeTemplatesSlice, (nodes, nodeTemplates) => {
-        const node = nodes.nodes.find((node) => node.id === nodeId);
-        if (!isInvocationNode(node)) {
-          return false;
-        }
-        const nodeTemplate = nodeTemplates.templates[node?.data.type ?? ''];
-        return nodeTemplate?.classification;
+      createSelector(selectNodesSlice, (nodes) => {
+        return selectNodeTemplate(nodes, nodeId)?.classification ?? null;
       }),
     [nodeId]
   );
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useNodeData.ts b/invokeai/frontend/web/src/features/nodes/hooks/useNodeData.ts
index c507def5ee..fa21008ff8 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useNodeData.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useNodeData.ts
@@ -1,14 +1,15 @@
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppSelector } from 'app/store/storeHooks';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
+import { selectNodeData } from 'features/nodes/store/selectors';
+import type { InvocationNodeData } from 'features/nodes/types/invocation';
 import { useMemo } from 'react';
 
-export const useNodeData = (nodeId: string) => {
+export const useNodeData = (nodeId: string): InvocationNodeData | null => {
   const selector = useMemo(
     () =>
       createMemoizedSelector(selectNodesSlice, (nodes) => {
-        const node = nodes.nodes.find((node) => node.id === nodeId);
-        return node?.data;
+        return selectNodeData(nodes, nodeId);
       }),
     [nodeId]
   );
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useNodeLabel.ts b/invokeai/frontend/web/src/features/nodes/hooks/useNodeLabel.ts
index c5fc43742a..31dcb9c466 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useNodeLabel.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useNodeLabel.ts
@@ -1,19 +1,14 @@
 import { createSelector } from '@reduxjs/toolkit';
 import { useAppSelector } from 'app/store/storeHooks';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { isInvocationNode } from 'features/nodes/types/invocation';
+import { selectNodeData } from 'features/nodes/store/selectors';
 import { useMemo } from 'react';
 
 export const useNodeLabel = (nodeId: string) => {
   const selector = useMemo(
     () =>
       createSelector(selectNodesSlice, (nodes) => {
-        const node = nodes.nodes.find((node) => node.id === nodeId);
-        if (!isInvocationNode(node)) {
-          return false;
-        }
-
-        return node.data.label;
+        return selectNodeData(nodes, nodeId)?.label ?? null;
       }),
     [nodeId]
   );
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useNodeNeedsUpdate.ts b/invokeai/frontend/web/src/features/nodes/hooks/useNodeNeedsUpdate.ts
index e6efa667f1..aa0294f70f 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useNodeNeedsUpdate.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useNodeNeedsUpdate.ts
@@ -1,21 +1,20 @@
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppSelector } from 'app/store/storeHooks';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { selectNodeTemplatesSlice } from 'features/nodes/store/nodeTemplatesSlice';
-import { isInvocationNode } from 'features/nodes/types/invocation';
+import { selectInvocationNode, selectNodeTemplate } from 'features/nodes/store/selectors';
 import { getNeedsUpdate } from 'features/nodes/util/node/nodeUpdate';
 import { useMemo } from 'react';
 
 export const useNodeNeedsUpdate = (nodeId: string) => {
   const selector = useMemo(
     () =>
-      createMemoizedSelector(selectNodesSlice, selectNodeTemplatesSlice, (nodes, nodeTemplates) => {
-        const node = nodes.nodes.find((node) => node.id === nodeId);
-        const template = nodeTemplates.templates[node?.data.type ?? ''];
-        if (isInvocationNode(node) && template) {
-          return getNeedsUpdate(node, template);
+      createMemoizedSelector(selectNodesSlice, (nodes) => {
+        const node = selectInvocationNode(nodes, nodeId);
+        const template = selectNodeTemplate(nodes, nodeId);
+        if (!node || !template) {
+          return false;
         }
-        return false;
+        return getNeedsUpdate(node, template);
       }),
     [nodeId]
   );
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useNodePack.ts b/invokeai/frontend/web/src/features/nodes/hooks/useNodePack.ts
index ca3dd5cfdf..5c920866e9 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useNodePack.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useNodePack.ts
@@ -1,18 +1,14 @@
 import { createSelector } from '@reduxjs/toolkit';
 import { useAppSelector } from 'app/store/storeHooks';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { isInvocationNode } from 'features/nodes/types/invocation';
+import { selectNodeData } from 'features/nodes/store/selectors';
 import { useMemo } from 'react';
 
-export const useNodePack = (nodeId: string) => {
+export const useNodePack = (nodeId: string): string | null => {
   const selector = useMemo(
     () =>
       createSelector(selectNodesSlice, (nodes) => {
-        const node = nodes.nodes.find((node) => node.id === nodeId);
-        if (!isInvocationNode(node)) {
-          return false;
-        }
-        return node.data.nodePack;
+        return selectNodeData(nodes, nodeId)?.nodePack ?? null;
       }),
     [nodeId]
   );
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useNodeTemplate.ts b/invokeai/frontend/web/src/features/nodes/hooks/useNodeTemplate.ts
index 7544cbff46..866c9275fb 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useNodeTemplate.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useNodeTemplate.ts
@@ -1,16 +1,15 @@
-import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
+import { createSelector } from '@reduxjs/toolkit';
 import { useAppSelector } from 'app/store/storeHooks';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { selectNodeTemplatesSlice } from 'features/nodes/store/nodeTemplatesSlice';
+import { selectNodeTemplate } from 'features/nodes/store/selectors';
+import type { InvocationTemplate } from 'features/nodes/types/invocation';
 import { useMemo } from 'react';
 
-export const useNodeTemplate = (nodeId: string) => {
+export const useNodeTemplate = (nodeId: string): InvocationTemplate | null => {
   const selector = useMemo(
     () =>
-      createMemoizedSelector(selectNodesSlice, selectNodeTemplatesSlice, (nodes, nodeTemplates) => {
-        const node = nodes.nodes.find((node) => node.id === nodeId);
-        const nodeTemplate = nodeTemplates.templates[node?.data.type ?? ''];
-        return nodeTemplate;
+      createSelector(selectNodesSlice, (nodes) => {
+        return selectNodeTemplate(nodes, nodeId);
       }),
     [nodeId]
   );
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useNodeTemplateByType.ts b/invokeai/frontend/web/src/features/nodes/hooks/useNodeTemplateByType.ts
index 8fd1345f6f..a0c870f694 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useNodeTemplateByType.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useNodeTemplateByType.ts
@@ -1,14 +1,14 @@
-import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
+import { createSelector } from '@reduxjs/toolkit';
 import { useAppSelector } from 'app/store/storeHooks';
-import { selectNodeTemplatesSlice } from 'features/nodes/store/nodeTemplatesSlice';
+import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
 import type { InvocationTemplate } from 'features/nodes/types/invocation';
 import { useMemo } from 'react';
 
-export const useNodeTemplateByType = (type: string) => {
+export const useNodeTemplateByType = (type: string): InvocationTemplate | null => {
   const selector = useMemo(
     () =>
-      createMemoizedSelector(selectNodeTemplatesSlice, (nodeTemplates): InvocationTemplate | undefined => {
-        return nodeTemplates.templates[type];
+      createSelector(selectNodesSlice, (nodes) => {
+        return nodes.templates[type] ?? null;
       }),
     [type]
   );
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useNodeTemplateTitle.ts b/invokeai/frontend/web/src/features/nodes/hooks/useNodeTemplateTitle.ts
index 15d2ec38c3..120b8c758b 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useNodeTemplateTitle.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useNodeTemplateTitle.ts
@@ -1,21 +1,14 @@
 import { createSelector } from '@reduxjs/toolkit';
 import { useAppSelector } from 'app/store/storeHooks';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { selectNodeTemplatesSlice } from 'features/nodes/store/nodeTemplatesSlice';
-import { isInvocationNode } from 'features/nodes/types/invocation';
+import { selectNodeTemplate } from 'features/nodes/store/selectors';
 import { useMemo } from 'react';
 
-export const useNodeTemplateTitle = (nodeId: string) => {
+export const useNodeTemplateTitle = (nodeId: string): string | null => {
   const selector = useMemo(
     () =>
-      createSelector(selectNodesSlice, selectNodeTemplatesSlice, (nodes, nodeTemplates) => {
-        const node = nodes.nodes.find((node) => node.id === nodeId);
-        if (!isInvocationNode(node)) {
-          return false;
-        }
-        const nodeTemplate = node ? nodeTemplates.templates[node.data.type] : undefined;
-
-        return nodeTemplate?.title;
+      createSelector(selectNodesSlice, (nodes) => {
+        return selectNodeTemplate(nodes, nodeId)?.title ?? null;
       }),
     [nodeId]
   );
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useOutputFieldNames.ts b/invokeai/frontend/web/src/features/nodes/hooks/useOutputFieldNames.ts
index e352bd8b90..24863080a7 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useOutputFieldNames.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useOutputFieldNames.ts
@@ -1,8 +1,8 @@
-import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
+import { createSelector } from '@reduxjs/toolkit';
 import { useAppSelector } from 'app/store/storeHooks';
+import { EMPTY_ARRAY } from 'app/store/util';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { selectNodeTemplatesSlice } from 'features/nodes/store/nodeTemplatesSlice';
-import { isInvocationNode } from 'features/nodes/types/invocation';
+import { selectNodeTemplate } from 'features/nodes/store/selectors';
 import { getSortedFilteredFieldNames } from 'features/nodes/util/node/getSortedFilteredFieldNames';
 import { map } from 'lodash-es';
 import { useMemo } from 'react';
@@ -10,17 +10,13 @@ import { useMemo } from 'react';
 export const useOutputFieldNames = (nodeId: string) => {
   const selector = useMemo(
     () =>
-      createMemoizedSelector(selectNodesSlice, selectNodeTemplatesSlice, (nodes, nodeTemplates) => {
-        const node = nodes.nodes.find((node) => node.id === nodeId);
-        if (!isInvocationNode(node)) {
-          return [];
-        }
-        const nodeTemplate = nodeTemplates.templates[node.data.type];
-        if (!nodeTemplate) {
-          return [];
+      createSelector(selectNodesSlice, (nodes) => {
+        const template = selectNodeTemplate(nodes, nodeId);
+        if (!template) {
+          return EMPTY_ARRAY;
         }
 
-        return getSortedFilteredFieldNames(map(nodeTemplate.outputs));
+        return getSortedFilteredFieldNames(map(template.outputs));
       }),
     [nodeId]
   );
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useUseCache.ts b/invokeai/frontend/web/src/features/nodes/hooks/useUseCache.ts
index edfc990882..aaca80039b 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useUseCache.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useUseCache.ts
@@ -1,18 +1,14 @@
 import { createSelector } from '@reduxjs/toolkit';
 import { useAppSelector } from 'app/store/storeHooks';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { isInvocationNode } from 'features/nodes/types/invocation';
+import { selectNodeData } from 'features/nodes/store/selectors';
 import { useMemo } from 'react';
 
 export const useUseCache = (nodeId: string) => {
   const selector = useMemo(
     () =>
       createSelector(selectNodesSlice, (nodes) => {
-        const node = nodes.nodes.find((node) => node.id === nodeId);
-        if (!isInvocationNode(node)) {
-          return false;
-        }
-        return node.data.useCache;
+        return selectNodeData(nodes, nodeId)?.useCache ?? false;
       }),
     [nodeId]
   );
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useWorkflowWatcher.ts b/invokeai/frontend/web/src/features/nodes/hooks/useWorkflowWatcher.ts
index 0e4806d81b..5d79c15442 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useWorkflowWatcher.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useWorkflowWatcher.ts
@@ -2,14 +2,14 @@ import { createSelector } from '@reduxjs/toolkit';
 import { useAppSelector } from 'app/store/storeHooks';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
 import { selectWorkflowSlice } from 'features/nodes/store/workflowSlice';
-import type { WorkflowV2 } from 'features/nodes/types/workflow';
+import type { WorkflowV3 } from 'features/nodes/types/workflow';
 import type { BuildWorkflowArg } from 'features/nodes/util/workflow/buildWorkflow';
 import { buildWorkflowFast } from 'features/nodes/util/workflow/buildWorkflow';
 import { debounce } from 'lodash-es';
 import { atom } from 'nanostores';
 import { useEffect } from 'react';
 
-export const $builtWorkflow = atom<WorkflowV2 | null>(null);
+export const $builtWorkflow = atom<WorkflowV3 | null>(null);
 
 const debouncedBuildWorkflow = debounce((arg: BuildWorkflowArg) => {
   $builtWorkflow.set(buildWorkflowFast(arg));
diff --git a/invokeai/frontend/web/src/features/nodes/store/actions.ts b/invokeai/frontend/web/src/features/nodes/store/actions.ts
index 00457494bf..b32a3ba997 100644
--- a/invokeai/frontend/web/src/features/nodes/store/actions.ts
+++ b/invokeai/frontend/web/src/features/nodes/store/actions.ts
@@ -1,5 +1,5 @@
 import { createAction, isAnyOf } from '@reduxjs/toolkit';
-import type { WorkflowV2 } from 'features/nodes/types/workflow';
+import type { WorkflowV3 } from 'features/nodes/types/workflow';
 import type { Graph } from 'services/api/types';
 
 export const textToImageGraphBuilt = createAction<Graph>('nodes/textToImageGraphBuilt');
@@ -21,4 +21,4 @@ export const workflowLoadRequested = createAction<{
 
 export const updateAllNodesRequested = createAction('nodes/updateAllNodesRequested');
 
-export const workflowLoaded = createAction<WorkflowV2>('workflow/workflowLoaded');
+export const workflowLoaded = createAction<WorkflowV3>('workflow/workflowLoaded');
diff --git a/invokeai/frontend/web/src/features/nodes/store/nodeTemplatesSlice.ts b/invokeai/frontend/web/src/features/nodes/store/nodeTemplatesSlice.ts
deleted file mode 100644
index c211131aab..0000000000
--- a/invokeai/frontend/web/src/features/nodes/store/nodeTemplatesSlice.ts
+++ /dev/null
@@ -1,24 +0,0 @@
-import type { PayloadAction } from '@reduxjs/toolkit';
-import { createSlice } from '@reduxjs/toolkit';
-import type { RootState } from 'app/store/store';
-import type { InvocationTemplate } from 'features/nodes/types/invocation';
-
-import type { NodeTemplatesState } from './types';
-
-export const initialNodeTemplatesState: NodeTemplatesState = {
-  templates: {},
-};
-
-export const nodesTemplatesSlice = createSlice({
-  name: 'nodeTemplates',
-  initialState: initialNodeTemplatesState,
-  reducers: {
-    nodeTemplatesBuilt: (state, action: PayloadAction<Record<string, InvocationTemplate>>) => {
-      state.templates = action.payload;
-    },
-  },
-});
-
-export const { nodeTemplatesBuilt } = nodesTemplatesSlice.actions;
-
-export const selectNodeTemplatesSlice = (state: RootState) => state.nodeTemplates;
diff --git a/invokeai/frontend/web/src/features/nodes/store/nodesSlice.ts b/invokeai/frontend/web/src/features/nodes/store/nodesSlice.ts
index aee01b381b..6b596da063 100644
--- a/invokeai/frontend/web/src/features/nodes/store/nodesSlice.ts
+++ b/invokeai/frontend/web/src/features/nodes/store/nodesSlice.ts
@@ -42,7 +42,7 @@ import {
   zT2IAdapterModelFieldValue,
   zVAEModelFieldValue,
 } from 'features/nodes/types/field';
-import type { AnyNode, NodeExecutionState } from 'features/nodes/types/invocation';
+import type { AnyNode, InvocationTemplate, NodeExecutionState } from 'features/nodes/types/invocation';
 import { isInvocationNode, isNotesNode, zNodeStatus } from 'features/nodes/types/invocation';
 import { cloneDeep, forEach } from 'lodash-es';
 import type {
@@ -92,6 +92,7 @@ export const initialNodesState: NodesState = {
   _version: 1,
   nodes: [],
   edges: [],
+  templates: {},
   connectionStartParams: null,
   connectionStartFieldType: null,
   connectionMade: false,
@@ -190,6 +191,7 @@ export const nodesSlice = createSlice({
             node,
             state.nodes,
             state.edges,
+            state.templates,
             nodeId,
             handleId,
             handleType,
@@ -224,12 +226,12 @@ export const nodesSlice = createSlice({
       if (!nodeId || !handleId) {
         return;
       }
-      const nodeIndex = state.nodes.findIndex((n) => n.id === nodeId);
-      const node = state.nodes?.[nodeIndex];
+      const node = state.nodes.find((n) => n.id === nodeId);
       if (!isInvocationNode(node)) {
         return;
       }
-      const field = handleType === 'source' ? node.data.outputs[handleId] : node.data.inputs[handleId];
+      const template = state.templates[node.data.type];
+      const field = handleType === 'source' ? template?.outputs[handleId] : template?.inputs[handleId];
       state.connectionStartFieldType = field?.type ?? null;
     },
     connectionMade: (state, action: PayloadAction<Connection>) => {
@@ -260,6 +262,7 @@ export const nodesSlice = createSlice({
                 mouseOverNode,
                 state.nodes,
                 state.edges,
+                state.templates,
                 nodeId,
                 handleId,
                 handleType,
@@ -677,6 +680,9 @@ export const nodesSlice = createSlice({
     selectionModeChanged: (state, action: PayloadAction<boolean>) => {
       state.selectionMode = action.payload ? SelectionMode.Full : SelectionMode.Partial;
     },
+    nodeTemplatesBuilt: (state, action: PayloadAction<Record<string, InvocationTemplate>>) => {
+      state.templates = action.payload;
+    },
   },
   extraReducers: (builder) => {
     builder.addCase(workflowLoaded, (state, action) => {
@@ -808,6 +814,7 @@ export const {
   shouldValidateGraphChanged,
   viewportChanged,
   edgeAdded,
+  nodeTemplatesBuilt,
 } = nodesSlice.actions;
 
 // This is used for tracking `state.workflow.isTouched`
diff --git a/invokeai/frontend/web/src/features/nodes/store/selectors.ts b/invokeai/frontend/web/src/features/nodes/store/selectors.ts
new file mode 100644
index 0000000000..90675d6270
--- /dev/null
+++ b/invokeai/frontend/web/src/features/nodes/store/selectors.ts
@@ -0,0 +1,51 @@
+import type { NodesState } from 'features/nodes/store/types';
+import type { FieldInputInstance, FieldInputTemplate, FieldOutputTemplate } from 'features/nodes/types/field';
+import type { InvocationNode, InvocationNodeData, InvocationTemplate } from 'features/nodes/types/invocation';
+import { isInvocationNode } from 'features/nodes/types/invocation';
+
+export const selectInvocationNode = (nodesSlice: NodesState, nodeId: string): InvocationNode | null => {
+  const node = nodesSlice.nodes.find((node) => node.id === nodeId);
+  if (!isInvocationNode(node)) {
+    return null;
+  }
+  return node;
+};
+
+export const selectNodeData = (nodesSlice: NodesState, nodeId: string): InvocationNodeData | null => {
+  return selectInvocationNode(nodesSlice, nodeId)?.data ?? null;
+};
+
+export const selectNodeTemplate = (nodesSlice: NodesState, nodeId: string): InvocationTemplate | null => {
+  const node = selectInvocationNode(nodesSlice, nodeId);
+  if (!node) {
+    return null;
+  }
+  return nodesSlice.templates[node.data.type] ?? null;
+};
+
+export const selectFieldInputInstance = (
+  nodesSlice: NodesState,
+  nodeId: string,
+  fieldName: string
+): FieldInputInstance | null => {
+  const data = selectNodeData(nodesSlice, nodeId);
+  return data?.inputs[fieldName] ?? null;
+};
+
+export const selectFieldInputTemplate = (
+  nodesSlice: NodesState,
+  nodeId: string,
+  fieldName: string
+): FieldInputTemplate | null => {
+  const template = selectNodeTemplate(nodesSlice, nodeId);
+  return template?.inputs[fieldName] ?? null;
+};
+
+export const selectFieldOutputTemplate = (
+  nodesSlice: NodesState,
+  nodeId: string,
+  fieldName: string
+): FieldOutputTemplate | null => {
+  const template = selectNodeTemplate(nodesSlice, nodeId);
+  return template?.outputs[fieldName] ?? null;
+};
diff --git a/invokeai/frontend/web/src/features/nodes/store/types.ts b/invokeai/frontend/web/src/features/nodes/store/types.ts
index 8b0de447e4..1a040d2c70 100644
--- a/invokeai/frontend/web/src/features/nodes/store/types.ts
+++ b/invokeai/frontend/web/src/features/nodes/store/types.ts
@@ -5,13 +5,14 @@ import type {
   InvocationTemplate,
   NodeExecutionState,
 } from 'features/nodes/types/invocation';
-import type { WorkflowV2 } from 'features/nodes/types/workflow';
+import type { WorkflowV3 } from 'features/nodes/types/workflow';
 import type { OnConnectStartParams, SelectionMode, Viewport, XYPosition } from 'reactflow';
 
 export type NodesState = {
   _version: 1;
   nodes: AnyNode[];
   edges: InvocationNodeEdge[];
+  templates: Record<string, InvocationTemplate>;
   connectionStartParams: OnConnectStartParams | null;
   connectionStartFieldType: FieldType | null;
   connectionMade: boolean;
@@ -38,7 +39,7 @@ export type FieldIdentifierWithValue = FieldIdentifier & {
   value: StatefulFieldValue;
 };
 
-export type WorkflowsState = Omit<WorkflowV2, 'nodes' | 'edges'> & {
+export type WorkflowsState = Omit<WorkflowV3, 'nodes' | 'edges'> & {
   _version: 1;
   isTouched: boolean;
   mode: WorkflowMode;
diff --git a/invokeai/frontend/web/src/features/nodes/store/util/findConnectionToValidHandle.ts b/invokeai/frontend/web/src/features/nodes/store/util/findConnectionToValidHandle.ts
index 9f2c37a2ad..ef899c5f41 100644
--- a/invokeai/frontend/web/src/features/nodes/store/util/findConnectionToValidHandle.ts
+++ b/invokeai/frontend/web/src/features/nodes/store/util/findConnectionToValidHandle.ts
@@ -1,4 +1,6 @@
-import type { FieldInputInstance, FieldOutputInstance, FieldType } from 'features/nodes/types/field';
+import type { FieldInputTemplate, FieldOutputTemplate, FieldType } from 'features/nodes/types/field';
+import type { AnyNode, InvocationNodeEdge, InvocationTemplate } from 'features/nodes/types/invocation';
+import { isInvocationNode } from 'features/nodes/types/invocation';
 import type { Connection, Edge, HandleType, Node } from 'reactflow';
 
 import { getIsGraphAcyclic } from './getIsGraphAcyclic';
@@ -9,7 +11,7 @@ const isValidConnection = (
   handleCurrentType: HandleType,
   handleCurrentFieldType: FieldType,
   node: Node,
-  handle: FieldInputInstance | FieldOutputInstance
+  handle: FieldInputTemplate | FieldOutputTemplate
 ) => {
   let isValidConnection = true;
   if (handleCurrentType === 'source') {
@@ -38,24 +40,31 @@ const isValidConnection = (
 };
 
 export const findConnectionToValidHandle = (
-  node: Node,
-  nodes: Node[],
-  edges: Edge[],
+  node: AnyNode,
+  nodes: AnyNode[],
+  edges: InvocationNodeEdge[],
+  templates: Record<string, InvocationTemplate>,
   handleCurrentNodeId: string,
   handleCurrentName: string,
   handleCurrentType: HandleType,
   handleCurrentFieldType: FieldType
 ): Connection | null => {
-  if (node.id === handleCurrentNodeId) {
+  if (node.id === handleCurrentNodeId || !isInvocationNode(node)) {
     return null;
   }
 
-  const handles = handleCurrentType === 'source' ? node.data.inputs : node.data.outputs;
+  const template = templates[node.data.type];
+
+  if (!template) {
+    return null;
+  }
+
+  const handles = handleCurrentType === 'source' ? template.inputs : template.outputs;
 
   //Prioritize handles whos name matches the node we're coming from
-  if (handles[handleCurrentName]) {
-    const handle = handles[handleCurrentName];
+  const handle = handles[handleCurrentName];
 
+  if (handle) {
     const sourceID = handleCurrentType === 'source' ? handleCurrentNodeId : node.id;
     const targetID = handleCurrentType === 'source' ? node.id : handleCurrentNodeId;
     const sourceHandle = handleCurrentType === 'source' ? handleCurrentName : handle.name;
@@ -77,6 +86,9 @@ export const findConnectionToValidHandle = (
 
   for (const handleName in handles) {
     const handle = handles[handleName];
+    if (!handle) {
+      continue;
+    }
 
     const sourceID = handleCurrentType === 'source' ? handleCurrentNodeId : node.id;
     const targetID = handleCurrentType === 'source' ? node.id : handleCurrentNodeId;
diff --git a/invokeai/frontend/web/src/features/nodes/store/util/makeIsConnectionValidSelector.ts b/invokeai/frontend/web/src/features/nodes/store/util/makeIsConnectionValidSelector.ts
index 8575932cbd..d6ea0d9c86 100644
--- a/invokeai/frontend/web/src/features/nodes/store/util/makeIsConnectionValidSelector.ts
+++ b/invokeai/frontend/web/src/features/nodes/store/util/makeIsConnectionValidSelector.ts
@@ -16,7 +16,7 @@ export const makeConnectionErrorSelector = (
   nodeId: string,
   fieldName: string,
   handleType: HandleType,
-  fieldType?: FieldType
+  fieldType?: FieldType | null
 ) => {
   return createSelector(selectNodesSlice, (nodesSlice) => {
     if (!fieldType) {
diff --git a/invokeai/frontend/web/src/features/nodes/store/workflowSlice.ts b/invokeai/frontend/web/src/features/nodes/store/workflowSlice.ts
index 2978f25138..4f40a68e1f 100644
--- a/invokeai/frontend/web/src/features/nodes/store/workflowSlice.ts
+++ b/invokeai/frontend/web/src/features/nodes/store/workflowSlice.ts
@@ -10,10 +10,10 @@ import type {
 } from 'features/nodes/store/types';
 import type { FieldIdentifier } from 'features/nodes/types/field';
 import { isInvocationNode } from 'features/nodes/types/invocation';
-import type { WorkflowCategory, WorkflowV2 } from 'features/nodes/types/workflow';
+import type { WorkflowCategory, WorkflowV3 } from 'features/nodes/types/workflow';
 import { cloneDeep, isEqual, omit, uniqBy } from 'lodash-es';
 
-export const blankWorkflow: Omit<WorkflowV2, 'nodes' | 'edges'> = {
+export const blankWorkflow: Omit<WorkflowV3, 'nodes' | 'edges'> = {
   name: '',
   author: '',
   description: '',
@@ -22,7 +22,7 @@ export const blankWorkflow: Omit<WorkflowV2, 'nodes' | 'edges'> = {
   tags: '',
   notes: '',
   exposedFields: [],
-  meta: { version: '2.0.0', category: 'user' },
+  meta: { version: '3.0.0', category: 'user' },
   id: undefined,
 };
 
diff --git a/invokeai/frontend/web/src/features/nodes/types/field.ts b/invokeai/frontend/web/src/features/nodes/types/field.ts
index 38f1af55dd..aa6164d6e5 100644
--- a/invokeai/frontend/web/src/features/nodes/types/field.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/field.ts
@@ -46,20 +46,11 @@ export type FieldInput = z.infer<typeof zFieldInput>;
 export const zFieldUIComponent = z.enum(['none', 'textarea', 'slider']);
 export type FieldUIComponent = z.infer<typeof zFieldUIComponent>;
 
-export const zFieldInstanceBase = z.object({
-  id: z.string().trim().min(1),
+export const zFieldInputInstanceBase = z.object({
   name: z.string().trim().min(1),
-});
-export const zFieldInputInstanceBase = zFieldInstanceBase.extend({
-  fieldKind: z.literal('input'),
   label: z.string().nullish(),
 });
-export const zFieldOutputInstanceBase = zFieldInstanceBase.extend({
-  fieldKind: z.literal('output'),
-});
-export type FieldInstanceBase = z.infer<typeof zFieldInstanceBase>;
 export type FieldInputInstanceBase = z.infer<typeof zFieldInputInstanceBase>;
-export type FieldOutputInstanceBase = z.infer<typeof zFieldOutputInstanceBase>;
 
 export const zFieldTemplateBase = z.object({
   name: z.string().min(1),
@@ -102,12 +93,8 @@ export const zIntegerFieldType = zFieldTypeBase.extend({
 });
 export const zIntegerFieldValue = z.number().int();
 export const zIntegerFieldInputInstance = zFieldInputInstanceBase.extend({
-  type: zIntegerFieldType,
   value: zIntegerFieldValue,
 });
-export const zIntegerFieldOutputInstance = zFieldOutputInstanceBase.extend({
-  type: zIntegerFieldType,
-});
 export const zIntegerFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zIntegerFieldType,
   default: zIntegerFieldValue,
@@ -136,12 +123,8 @@ export const zFloatFieldType = zFieldTypeBase.extend({
 });
 export const zFloatFieldValue = z.number();
 export const zFloatFieldInputInstance = zFieldInputInstanceBase.extend({
-  type: zFloatFieldType,
   value: zFloatFieldValue,
 });
-export const zFloatFieldOutputInstance = zFieldOutputInstanceBase.extend({
-  type: zFloatFieldType,
-});
 export const zFloatFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zFloatFieldType,
   default: zFloatFieldValue,
@@ -157,7 +140,6 @@ export const zFloatFieldOutputTemplate = zFieldOutputTemplateBase.extend({
 export type FloatFieldType = z.infer<typeof zFloatFieldType>;
 export type FloatFieldValue = z.infer<typeof zFloatFieldValue>;
 export type FloatFieldInputInstance = z.infer<typeof zFloatFieldInputInstance>;
-export type FloatFieldOutputInstance = z.infer<typeof zFloatFieldOutputInstance>;
 export type FloatFieldInputTemplate = z.infer<typeof zFloatFieldInputTemplate>;
 export type FloatFieldOutputTemplate = z.infer<typeof zFloatFieldOutputTemplate>;
 export const isFloatFieldInputInstance = (val: unknown): val is FloatFieldInputInstance =>
@@ -172,12 +154,8 @@ export const zStringFieldType = zFieldTypeBase.extend({
 });
 export const zStringFieldValue = z.string();
 export const zStringFieldInputInstance = zFieldInputInstanceBase.extend({
-  type: zStringFieldType,
   value: zStringFieldValue,
 });
-export const zStringFieldOutputInstance = zFieldOutputInstanceBase.extend({
-  type: zStringFieldType,
-});
 export const zStringFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zStringFieldType,
   default: zStringFieldValue,
@@ -191,7 +169,6 @@ export const zStringFieldOutputTemplate = zFieldOutputTemplateBase.extend({
 export type StringFieldType = z.infer<typeof zStringFieldType>;
 export type StringFieldValue = z.infer<typeof zStringFieldValue>;
 export type StringFieldInputInstance = z.infer<typeof zStringFieldInputInstance>;
-export type StringFieldOutputInstance = z.infer<typeof zStringFieldOutputInstance>;
 export type StringFieldInputTemplate = z.infer<typeof zStringFieldInputTemplate>;
 export type StringFieldOutputTemplate = z.infer<typeof zStringFieldOutputTemplate>;
 export const isStringFieldInputInstance = (val: unknown): val is StringFieldInputInstance =>
@@ -206,12 +183,8 @@ export const zBooleanFieldType = zFieldTypeBase.extend({
 });
 export const zBooleanFieldValue = z.boolean();
 export const zBooleanFieldInputInstance = zFieldInputInstanceBase.extend({
-  type: zBooleanFieldType,
   value: zBooleanFieldValue,
 });
-export const zBooleanFieldOutputInstance = zFieldOutputInstanceBase.extend({
-  type: zBooleanFieldType,
-});
 export const zBooleanFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zBooleanFieldType,
   default: zBooleanFieldValue,
@@ -222,7 +195,6 @@ export const zBooleanFieldOutputTemplate = zFieldOutputTemplateBase.extend({
 export type BooleanFieldType = z.infer<typeof zBooleanFieldType>;
 export type BooleanFieldValue = z.infer<typeof zBooleanFieldValue>;
 export type BooleanFieldInputInstance = z.infer<typeof zBooleanFieldInputInstance>;
-export type BooleanFieldOutputInstance = z.infer<typeof zBooleanFieldOutputInstance>;
 export type BooleanFieldInputTemplate = z.infer<typeof zBooleanFieldInputTemplate>;
 export type BooleanFieldOutputTemplate = z.infer<typeof zBooleanFieldOutputTemplate>;
 export const isBooleanFieldInputInstance = (val: unknown): val is BooleanFieldInputInstance =>
@@ -237,12 +209,8 @@ export const zEnumFieldType = zFieldTypeBase.extend({
 });
 export const zEnumFieldValue = z.string();
 export const zEnumFieldInputInstance = zFieldInputInstanceBase.extend({
-  type: zEnumFieldType,
   value: zEnumFieldValue,
 });
-export const zEnumFieldOutputInstance = zFieldOutputInstanceBase.extend({
-  type: zEnumFieldType,
-});
 export const zEnumFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zEnumFieldType,
   default: zEnumFieldValue,
@@ -255,7 +223,6 @@ export const zEnumFieldOutputTemplate = zFieldOutputTemplateBase.extend({
 export type EnumFieldType = z.infer<typeof zEnumFieldType>;
 export type EnumFieldValue = z.infer<typeof zEnumFieldValue>;
 export type EnumFieldInputInstance = z.infer<typeof zEnumFieldInputInstance>;
-export type EnumFieldOutputInstance = z.infer<typeof zEnumFieldOutputInstance>;
 export type EnumFieldInputTemplate = z.infer<typeof zEnumFieldInputTemplate>;
 export type EnumFieldOutputTemplate = z.infer<typeof zEnumFieldOutputTemplate>;
 export const isEnumFieldInputInstance = (val: unknown): val is EnumFieldInputInstance =>
@@ -270,12 +237,8 @@ export const zImageFieldType = zFieldTypeBase.extend({
 });
 export const zImageFieldValue = zImageField.optional();
 export const zImageFieldInputInstance = zFieldInputInstanceBase.extend({
-  type: zImageFieldType,
   value: zImageFieldValue,
 });
-export const zImageFieldOutputInstance = zFieldOutputInstanceBase.extend({
-  type: zImageFieldType,
-});
 export const zImageFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zImageFieldType,
   default: zImageFieldValue,
@@ -286,7 +249,6 @@ export const zImageFieldOutputTemplate = zFieldOutputTemplateBase.extend({
 export type ImageFieldType = z.infer<typeof zImageFieldType>;
 export type ImageFieldValue = z.infer<typeof zImageFieldValue>;
 export type ImageFieldInputInstance = z.infer<typeof zImageFieldInputInstance>;
-export type ImageFieldOutputInstance = z.infer<typeof zImageFieldOutputInstance>;
 export type ImageFieldInputTemplate = z.infer<typeof zImageFieldInputTemplate>;
 export type ImageFieldOutputTemplate = z.infer<typeof zImageFieldOutputTemplate>;
 export const isImageFieldInputInstance = (val: unknown): val is ImageFieldInputInstance =>
@@ -301,12 +263,8 @@ export const zBoardFieldType = zFieldTypeBase.extend({
 });
 export const zBoardFieldValue = zBoardField.optional();
 export const zBoardFieldInputInstance = zFieldInputInstanceBase.extend({
-  type: zBoardFieldType,
   value: zBoardFieldValue,
 });
-export const zBoardFieldOutputInstance = zFieldOutputInstanceBase.extend({
-  type: zBoardFieldType,
-});
 export const zBoardFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zBoardFieldType,
   default: zBoardFieldValue,
@@ -317,7 +275,6 @@ export const zBoardFieldOutputTemplate = zFieldOutputTemplateBase.extend({
 export type BoardFieldType = z.infer<typeof zBoardFieldType>;
 export type BoardFieldValue = z.infer<typeof zBoardFieldValue>;
 export type BoardFieldInputInstance = z.infer<typeof zBoardFieldInputInstance>;
-export type BoardFieldOutputInstance = z.infer<typeof zBoardFieldOutputInstance>;
 export type BoardFieldInputTemplate = z.infer<typeof zBoardFieldInputTemplate>;
 export type BoardFieldOutputTemplate = z.infer<typeof zBoardFieldOutputTemplate>;
 export const isBoardFieldInputInstance = (val: unknown): val is BoardFieldInputInstance =>
@@ -332,12 +289,8 @@ export const zColorFieldType = zFieldTypeBase.extend({
 });
 export const zColorFieldValue = zColorField.optional();
 export const zColorFieldInputInstance = zFieldInputInstanceBase.extend({
-  type: zColorFieldType,
   value: zColorFieldValue,
 });
-export const zColorFieldOutputInstance = zFieldOutputInstanceBase.extend({
-  type: zColorFieldType,
-});
 export const zColorFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zColorFieldType,
   default: zColorFieldValue,
@@ -348,7 +301,6 @@ export const zColorFieldOutputTemplate = zFieldOutputTemplateBase.extend({
 export type ColorFieldType = z.infer<typeof zColorFieldType>;
 export type ColorFieldValue = z.infer<typeof zColorFieldValue>;
 export type ColorFieldInputInstance = z.infer<typeof zColorFieldInputInstance>;
-export type ColorFieldOutputInstance = z.infer<typeof zColorFieldOutputInstance>;
 export type ColorFieldInputTemplate = z.infer<typeof zColorFieldInputTemplate>;
 export type ColorFieldOutputTemplate = z.infer<typeof zColorFieldOutputTemplate>;
 export const isColorFieldInputInstance = (val: unknown): val is ColorFieldInputInstance =>
@@ -363,12 +315,8 @@ export const zMainModelFieldType = zFieldTypeBase.extend({
 });
 export const zMainModelFieldValue = zMainModelField.optional();
 export const zMainModelFieldInputInstance = zFieldInputInstanceBase.extend({
-  type: zMainModelFieldType,
   value: zMainModelFieldValue,
 });
-export const zMainModelFieldOutputInstance = zFieldOutputInstanceBase.extend({
-  type: zMainModelFieldType,
-});
 export const zMainModelFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zMainModelFieldType,
   default: zMainModelFieldValue,
@@ -379,7 +327,6 @@ export const zMainModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
 export type MainModelFieldType = z.infer<typeof zMainModelFieldType>;
 export type MainModelFieldValue = z.infer<typeof zMainModelFieldValue>;
 export type MainModelFieldInputInstance = z.infer<typeof zMainModelFieldInputInstance>;
-export type MainModelFieldOutputInstance = z.infer<typeof zMainModelFieldOutputInstance>;
 export type MainModelFieldInputTemplate = z.infer<typeof zMainModelFieldInputTemplate>;
 export type MainModelFieldOutputTemplate = z.infer<typeof zMainModelFieldOutputTemplate>;
 export const isMainModelFieldInputInstance = (val: unknown): val is MainModelFieldInputInstance =>
@@ -394,12 +341,8 @@ export const zSDXLMainModelFieldType = zFieldTypeBase.extend({
 });
 export const zSDXLMainModelFieldValue = zMainModelFieldValue; // TODO: Narrow to SDXL models only.
 export const zSDXLMainModelFieldInputInstance = zFieldInputInstanceBase.extend({
-  type: zSDXLMainModelFieldType,
   value: zSDXLMainModelFieldValue,
 });
-export const zSDXLMainModelFieldOutputInstance = zFieldOutputInstanceBase.extend({
-  type: zSDXLMainModelFieldType,
-});
 export const zSDXLMainModelFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zSDXLMainModelFieldType,
   default: zSDXLMainModelFieldValue,
@@ -410,7 +353,6 @@ export const zSDXLMainModelFieldOutputTemplate = zFieldOutputTemplateBase.extend
 export type SDXLMainModelFieldType = z.infer<typeof zSDXLMainModelFieldType>;
 export type SDXLMainModelFieldValue = z.infer<typeof zSDXLMainModelFieldValue>;
 export type SDXLMainModelFieldInputInstance = z.infer<typeof zSDXLMainModelFieldInputInstance>;
-export type SDXLMainModelFieldOutputInstance = z.infer<typeof zSDXLMainModelFieldOutputInstance>;
 export type SDXLMainModelFieldInputTemplate = z.infer<typeof zSDXLMainModelFieldInputTemplate>;
 export type SDXLMainModelFieldOutputTemplate = z.infer<typeof zSDXLMainModelFieldOutputTemplate>;
 export const isSDXLMainModelFieldInputInstance = (val: unknown): val is SDXLMainModelFieldInputInstance =>
@@ -425,12 +367,8 @@ export const zSDXLRefinerModelFieldType = zFieldTypeBase.extend({
 });
 export const zSDXLRefinerModelFieldValue = zMainModelFieldValue; // TODO: Narrow to SDXL Refiner models only.
 export const zSDXLRefinerModelFieldInputInstance = zFieldInputInstanceBase.extend({
-  type: zSDXLRefinerModelFieldType,
   value: zSDXLRefinerModelFieldValue,
 });
-export const zSDXLRefinerModelFieldOutputInstance = zFieldOutputInstanceBase.extend({
-  type: zSDXLRefinerModelFieldType,
-});
 export const zSDXLRefinerModelFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zSDXLRefinerModelFieldType,
   default: zSDXLRefinerModelFieldValue,
@@ -441,7 +379,6 @@ export const zSDXLRefinerModelFieldOutputTemplate = zFieldOutputTemplateBase.ext
 export type SDXLRefinerModelFieldType = z.infer<typeof zSDXLRefinerModelFieldType>;
 export type SDXLRefinerModelFieldValue = z.infer<typeof zSDXLRefinerModelFieldValue>;
 export type SDXLRefinerModelFieldInputInstance = z.infer<typeof zSDXLRefinerModelFieldInputInstance>;
-export type SDXLRefinerModelFieldOutputInstance = z.infer<typeof zSDXLRefinerModelFieldOutputInstance>;
 export type SDXLRefinerModelFieldInputTemplate = z.infer<typeof zSDXLRefinerModelFieldInputTemplate>;
 export type SDXLRefinerModelFieldOutputTemplate = z.infer<typeof zSDXLRefinerModelFieldOutputTemplate>;
 export const isSDXLRefinerModelFieldInputInstance = (val: unknown): val is SDXLRefinerModelFieldInputInstance =>
@@ -456,12 +393,8 @@ export const zVAEModelFieldType = zFieldTypeBase.extend({
 });
 export const zVAEModelFieldValue = zVAEModelField.optional();
 export const zVAEModelFieldInputInstance = zFieldInputInstanceBase.extend({
-  type: zVAEModelFieldType,
   value: zVAEModelFieldValue,
 });
-export const zVAEModelFieldOutputInstance = zFieldOutputInstanceBase.extend({
-  type: zVAEModelFieldType,
-});
 export const zVAEModelFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zVAEModelFieldType,
   default: zVAEModelFieldValue,
@@ -472,7 +405,6 @@ export const zVAEModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
 export type VAEModelFieldType = z.infer<typeof zVAEModelFieldType>;
 export type VAEModelFieldValue = z.infer<typeof zVAEModelFieldValue>;
 export type VAEModelFieldInputInstance = z.infer<typeof zVAEModelFieldInputInstance>;
-export type VAEModelFieldOutputInstance = z.infer<typeof zVAEModelFieldOutputInstance>;
 export type VAEModelFieldInputTemplate = z.infer<typeof zVAEModelFieldInputTemplate>;
 export type VAEModelFieldOutputTemplate = z.infer<typeof zVAEModelFieldOutputTemplate>;
 export const isVAEModelFieldInputInstance = (val: unknown): val is VAEModelFieldInputInstance =>
@@ -487,12 +419,8 @@ export const zLoRAModelFieldType = zFieldTypeBase.extend({
 });
 export const zLoRAModelFieldValue = zLoRAModelField.optional();
 export const zLoRAModelFieldInputInstance = zFieldInputInstanceBase.extend({
-  type: zLoRAModelFieldType,
   value: zLoRAModelFieldValue,
 });
-export const zLoRAModelFieldOutputInstance = zFieldOutputInstanceBase.extend({
-  type: zLoRAModelFieldType,
-});
 export const zLoRAModelFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zLoRAModelFieldType,
   default: zLoRAModelFieldValue,
@@ -503,7 +431,6 @@ export const zLoRAModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
 export type LoRAModelFieldType = z.infer<typeof zLoRAModelFieldType>;
 export type LoRAModelFieldValue = z.infer<typeof zLoRAModelFieldValue>;
 export type LoRAModelFieldInputInstance = z.infer<typeof zLoRAModelFieldInputInstance>;
-export type LoRAModelFieldOutputInstance = z.infer<typeof zLoRAModelFieldOutputInstance>;
 export type LoRAModelFieldInputTemplate = z.infer<typeof zLoRAModelFieldInputTemplate>;
 export type LoRAModelFieldOutputTemplate = z.infer<typeof zLoRAModelFieldOutputTemplate>;
 export const isLoRAModelFieldInputInstance = (val: unknown): val is LoRAModelFieldInputInstance =>
@@ -518,12 +445,8 @@ export const zControlNetModelFieldType = zFieldTypeBase.extend({
 });
 export const zControlNetModelFieldValue = zControlNetModelField.optional();
 export const zControlNetModelFieldInputInstance = zFieldInputInstanceBase.extend({
-  type: zControlNetModelFieldType,
   value: zControlNetModelFieldValue,
 });
-export const zControlNetModelFieldOutputInstance = zFieldOutputInstanceBase.extend({
-  type: zControlNetModelFieldType,
-});
 export const zControlNetModelFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zControlNetModelFieldType,
   default: zControlNetModelFieldValue,
@@ -534,7 +457,6 @@ export const zControlNetModelFieldOutputTemplate = zFieldOutputTemplateBase.exte
 export type ControlNetModelFieldType = z.infer<typeof zControlNetModelFieldType>;
 export type ControlNetModelFieldValue = z.infer<typeof zControlNetModelFieldValue>;
 export type ControlNetModelFieldInputInstance = z.infer<typeof zControlNetModelFieldInputInstance>;
-export type ControlNetModelFieldOutputInstance = z.infer<typeof zControlNetModelFieldOutputInstance>;
 export type ControlNetModelFieldInputTemplate = z.infer<typeof zControlNetModelFieldInputTemplate>;
 export type ControlNetModelFieldOutputTemplate = z.infer<typeof zControlNetModelFieldOutputTemplate>;
 export const isControlNetModelFieldInputInstance = (val: unknown): val is ControlNetModelFieldInputInstance =>
@@ -551,12 +473,8 @@ export const zIPAdapterModelFieldType = zFieldTypeBase.extend({
 });
 export const zIPAdapterModelFieldValue = zIPAdapterModelField.optional();
 export const zIPAdapterModelFieldInputInstance = zFieldInputInstanceBase.extend({
-  type: zIPAdapterModelFieldType,
   value: zIPAdapterModelFieldValue,
 });
-export const zIPAdapterModelFieldOutputInstance = zFieldOutputInstanceBase.extend({
-  type: zIPAdapterModelFieldType,
-});
 export const zIPAdapterModelFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zIPAdapterModelFieldType,
   default: zIPAdapterModelFieldValue,
@@ -567,7 +485,6 @@ export const zIPAdapterModelFieldOutputTemplate = zFieldOutputTemplateBase.exten
 export type IPAdapterModelFieldType = z.infer<typeof zIPAdapterModelFieldType>;
 export type IPAdapterModelFieldValue = z.infer<typeof zIPAdapterModelFieldValue>;
 export type IPAdapterModelFieldInputInstance = z.infer<typeof zIPAdapterModelFieldInputInstance>;
-export type IPAdapterModelFieldOutputInstance = z.infer<typeof zIPAdapterModelFieldOutputInstance>;
 export type IPAdapterModelFieldInputTemplate = z.infer<typeof zIPAdapterModelFieldInputTemplate>;
 export type IPAdapterModelFieldOutputTemplate = z.infer<typeof zIPAdapterModelFieldOutputTemplate>;
 export const isIPAdapterModelFieldInputInstance = (val: unknown): val is IPAdapterModelFieldInputInstance =>
@@ -584,12 +501,8 @@ export const zT2IAdapterModelFieldType = zFieldTypeBase.extend({
 });
 export const zT2IAdapterModelFieldValue = zT2IAdapterModelField.optional();
 export const zT2IAdapterModelFieldInputInstance = zFieldInputInstanceBase.extend({
-  type: zT2IAdapterModelFieldType,
   value: zT2IAdapterModelFieldValue,
 });
-export const zT2IAdapterModelFieldOutputInstance = zFieldOutputInstanceBase.extend({
-  type: zT2IAdapterModelFieldType,
-});
 export const zT2IAdapterModelFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zT2IAdapterModelFieldType,
   default: zT2IAdapterModelFieldValue,
@@ -600,7 +513,6 @@ export const zT2IAdapterModelFieldOutputTemplate = zFieldOutputTemplateBase.exte
 export type T2IAdapterModelFieldType = z.infer<typeof zT2IAdapterModelFieldType>;
 export type T2IAdapterModelFieldValue = z.infer<typeof zT2IAdapterModelFieldValue>;
 export type T2IAdapterModelFieldInputInstance = z.infer<typeof zT2IAdapterModelFieldInputInstance>;
-export type T2IAdapterModelFieldOutputInstance = z.infer<typeof zT2IAdapterModelFieldOutputInstance>;
 export type T2IAdapterModelFieldInputTemplate = z.infer<typeof zT2IAdapterModelFieldInputTemplate>;
 export type T2IAdapterModelFieldOutputTemplate = z.infer<typeof zT2IAdapterModelFieldOutputTemplate>;
 export const isT2IAdapterModelFieldInputInstance = (val: unknown): val is T2IAdapterModelFieldInputInstance =>
@@ -615,12 +527,8 @@ export const zSchedulerFieldType = zFieldTypeBase.extend({
 });
 export const zSchedulerFieldValue = zSchedulerField.optional();
 export const zSchedulerFieldInputInstance = zFieldInputInstanceBase.extend({
-  type: zSchedulerFieldType,
   value: zSchedulerFieldValue,
 });
-export const zSchedulerFieldOutputInstance = zFieldOutputInstanceBase.extend({
-  type: zSchedulerFieldType,
-});
 export const zSchedulerFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zSchedulerFieldType,
   default: zSchedulerFieldValue,
@@ -631,7 +539,6 @@ export const zSchedulerFieldOutputTemplate = zFieldOutputTemplateBase.extend({
 export type SchedulerFieldType = z.infer<typeof zSchedulerFieldType>;
 export type SchedulerFieldValue = z.infer<typeof zSchedulerFieldValue>;
 export type SchedulerFieldInputInstance = z.infer<typeof zSchedulerFieldInputInstance>;
-export type SchedulerFieldOutputInstance = z.infer<typeof zSchedulerFieldOutputInstance>;
 export type SchedulerFieldInputTemplate = z.infer<typeof zSchedulerFieldInputTemplate>;
 export type SchedulerFieldOutputTemplate = z.infer<typeof zSchedulerFieldOutputTemplate>;
 export const isSchedulerFieldInputInstance = (val: unknown): val is SchedulerFieldInputInstance =>
@@ -657,12 +564,8 @@ export const zStatelessFieldType = zFieldTypeBase.extend({
 });
 export const zStatelessFieldValue = z.undefined().catch(undefined); // stateless --> no value, but making this z.never() introduces a lot of extra TS fanagling
 export const zStatelessFieldInputInstance = zFieldInputInstanceBase.extend({
-  type: zStatelessFieldType,
   value: zStatelessFieldValue,
 });
-export const zStatelessFieldOutputInstance = zFieldOutputInstanceBase.extend({
-  type: zStatelessFieldType,
-});
 export const zStatelessFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zStatelessFieldType,
   default: zStatelessFieldValue,
@@ -675,7 +578,6 @@ export const zStatelessFieldOutputTemplate = zFieldOutputTemplateBase.extend({
 export type StatelessFieldType = z.infer<typeof zStatelessFieldType>;
 export type StatelessFieldValue = z.infer<typeof zStatelessFieldValue>;
 export type StatelessFieldInputInstance = z.infer<typeof zStatelessFieldInputInstance>;
-export type StatelessFieldOutputInstance = z.infer<typeof zStatelessFieldOutputInstance>;
 export type StatelessFieldInputTemplate = z.infer<typeof zStatelessFieldInputTemplate>;
 export type StatelessFieldOutputTemplate = z.infer<typeof zStatelessFieldOutputTemplate>;
 // #endregion
@@ -783,36 +685,6 @@ export const isFieldInputInstance = (val: unknown): val is FieldInputInstance =>
   zFieldInputInstance.safeParse(val).success;
 // #endregion
 
-// #region StatefulFieldOutputInstance & FieldOutputInstance
-export const zStatefulFieldOutputInstance = z.union([
-  zIntegerFieldOutputInstance,
-  zFloatFieldOutputInstance,
-  zStringFieldOutputInstance,
-  zBooleanFieldOutputInstance,
-  zEnumFieldOutputInstance,
-  zImageFieldOutputInstance,
-  zBoardFieldOutputInstance,
-  zMainModelFieldOutputInstance,
-  zSDXLMainModelFieldOutputInstance,
-  zSDXLRefinerModelFieldOutputInstance,
-  zVAEModelFieldOutputInstance,
-  zLoRAModelFieldOutputInstance,
-  zControlNetModelFieldOutputInstance,
-  zIPAdapterModelFieldOutputInstance,
-  zT2IAdapterModelFieldOutputInstance,
-  zColorFieldOutputInstance,
-  zSchedulerFieldOutputInstance,
-]);
-export type StatefulFieldOutputInstance = z.infer<typeof zStatefulFieldOutputInstance>;
-export const isStatefulFieldOutputInstance = (val: unknown): val is StatefulFieldOutputInstance =>
-  zStatefulFieldOutputInstance.safeParse(val).success;
-
-export const zFieldOutputInstance = z.union([zStatefulFieldOutputInstance, zStatelessFieldOutputInstance]);
-export type FieldOutputInstance = z.infer<typeof zFieldOutputInstance>;
-export const isFieldOutputInstance = (val: unknown): val is FieldOutputInstance =>
-  zFieldOutputInstance.safeParse(val).success;
-// #endregion
-
 // #region StatefulFieldInputTemplate & FieldInputTemplate
 export const zStatefulFieldInputTemplate = z.union([
   zIntegerFieldInputTemplate,
diff --git a/invokeai/frontend/web/src/features/nodes/types/invocation.ts b/invokeai/frontend/web/src/features/nodes/types/invocation.ts
index 86ec70fd9b..5ccb19430d 100644
--- a/invokeai/frontend/web/src/features/nodes/types/invocation.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/invocation.ts
@@ -2,7 +2,7 @@ import type { Edge, Node } from 'reactflow';
 import { z } from 'zod';
 
 import { zClassification, zProgressImage } from './common';
-import { zFieldInputInstance, zFieldInputTemplate, zFieldOutputInstance, zFieldOutputTemplate } from './field';
+import { zFieldInputInstance, zFieldInputTemplate, zFieldOutputTemplate } from './field';
 import { zSemVer } from './semver';
 
 // #region InvocationTemplate
@@ -25,16 +25,15 @@ export type InvocationTemplate = z.infer<typeof zInvocationTemplate>;
 // #region NodeData
 export const zInvocationNodeData = z.object({
   id: z.string().trim().min(1),
-  type: z.string().trim().min(1),
-  label: z.string(),
-  isOpen: z.boolean(),
-  notes: z.string(),
-  isIntermediate: z.boolean(),
-  useCache: z.boolean(),
   version: zSemVer,
   nodePack: z.string().min(1).nullish(),
+  label: z.string(),
+  notes: z.string(),
+  type: z.string().trim().min(1),
   inputs: z.record(zFieldInputInstance),
-  outputs: z.record(zFieldOutputInstance),
+  isOpen: z.boolean(),
+  isIntermediate: z.boolean(),
+  useCache: z.boolean(),
 });
 
 export const zNotesNodeData = z.object({
@@ -62,11 +61,12 @@ export type NotesNode = Node<NotesNodeData, 'notes'>;
 export type CurrentImageNode = Node<CurrentImageNodeData, 'current_image'>;
 export type AnyNode = Node<AnyNodeData>;
 
-export const isInvocationNode = (node?: AnyNode): node is InvocationNode => Boolean(node && node.type === 'invocation');
-export const isNotesNode = (node?: AnyNode): node is NotesNode => Boolean(node && node.type === 'notes');
-export const isCurrentImageNode = (node?: AnyNode): node is CurrentImageNode =>
+export const isInvocationNode = (node?: AnyNode | null): node is InvocationNode =>
+  Boolean(node && node.type === 'invocation');
+export const isNotesNode = (node?: AnyNode | null): node is NotesNode => Boolean(node && node.type === 'notes');
+export const isCurrentImageNode = (node?: AnyNode | null): node is CurrentImageNode =>
   Boolean(node && node.type === 'current_image');
-export const isInvocationNodeData = (node?: AnyNodeData): node is InvocationNodeData =>
+export const isInvocationNodeData = (node?: AnyNodeData | null): node is InvocationNodeData =>
   Boolean(node && !['notes', 'current_image'].includes(node.type)); // node.type may be 'notes', 'current_image', or any invocation type
 // #endregion
 
diff --git a/invokeai/frontend/web/src/features/nodes/types/v2/common.ts b/invokeai/frontend/web/src/features/nodes/types/v2/common.ts
new file mode 100644
index 0000000000..b524474379
--- /dev/null
+++ b/invokeai/frontend/web/src/features/nodes/types/v2/common.ts
@@ -0,0 +1,188 @@
+import { z } from 'zod';
+
+// #region Field data schemas
+export const zImageField = z.object({
+  image_name: z.string().trim().min(1),
+});
+export type ImageField = z.infer<typeof zImageField>;
+
+export const zBoardField = z.object({
+  board_id: z.string().trim().min(1),
+});
+export type BoardField = z.infer<typeof zBoardField>;
+
+export const zColorField = z.object({
+  r: z.number().int().min(0).max(255),
+  g: z.number().int().min(0).max(255),
+  b: z.number().int().min(0).max(255),
+  a: z.number().int().min(0).max(255),
+});
+export type ColorField = z.infer<typeof zColorField>;
+
+export const zClassification = z.enum(['stable', 'beta', 'prototype']);
+export type Classification = z.infer<typeof zClassification>;
+
+export const zSchedulerField = z.enum([
+  'euler',
+  'deis',
+  'ddim',
+  'ddpm',
+  'dpmpp_2s',
+  'dpmpp_2m',
+  'dpmpp_2m_sde',
+  'dpmpp_sde',
+  'heun',
+  'kdpm_2',
+  'lms',
+  'pndm',
+  'unipc',
+  'euler_k',
+  'dpmpp_2s_k',
+  'dpmpp_2m_k',
+  'dpmpp_2m_sde_k',
+  'dpmpp_sde_k',
+  'heun_k',
+  'lms_k',
+  'euler_a',
+  'kdpm_2_a',
+  'lcm',
+]);
+export type SchedulerField = z.infer<typeof zSchedulerField>;
+// #endregion
+
+// #region Model-related schemas
+export const zBaseModel = z.enum(['any', 'sd-1', 'sd-2', 'sdxl', 'sdxl-refiner']);
+export const zModelType = z.enum(['main', 'vae', 'lora', 'controlnet', 'embedding']);
+export const zModelName = z.string().min(3);
+export const zModelIdentifier = z.object({
+  model_name: zModelName,
+  base_model: zBaseModel,
+});
+export type BaseModel = z.infer<typeof zBaseModel>;
+export type ModelType = z.infer<typeof zModelType>;
+export type ModelIdentifier = z.infer<typeof zModelIdentifier>;
+
+export const zMainModelField = z.object({
+  model_name: zModelName,
+  base_model: zBaseModel,
+  model_type: z.literal('main'),
+});
+export const zSDXLRefinerModelField = z.object({
+  model_name: z.string().min(1),
+  base_model: z.literal('sdxl-refiner'),
+  model_type: z.literal('main'),
+});
+export type MainModelField = z.infer<typeof zMainModelField>;
+export type SDXLRefinerModelField = z.infer<typeof zSDXLRefinerModelField>;
+
+export const zSubModelType = z.enum([
+  'unet',
+  'text_encoder',
+  'text_encoder_2',
+  'tokenizer',
+  'tokenizer_2',
+  'vae',
+  'vae_decoder',
+  'vae_encoder',
+  'scheduler',
+  'safety_checker',
+]);
+export type SubModelType = z.infer<typeof zSubModelType>;
+
+export const zVAEModelField = zModelIdentifier;
+
+export const zModelInfo = zModelIdentifier.extend({
+  model_type: zModelType,
+  submodel: zSubModelType.optional(),
+});
+export type ModelInfo = z.infer<typeof zModelInfo>;
+
+export const zLoRAModelField = zModelIdentifier;
+export type LoRAModelField = z.infer<typeof zLoRAModelField>;
+
+export const zControlNetModelField = zModelIdentifier;
+export type ControlNetModelField = z.infer<typeof zControlNetModelField>;
+
+export const zIPAdapterModelField = zModelIdentifier;
+export type IPAdapterModelField = z.infer<typeof zIPAdapterModelField>;
+
+export const zT2IAdapterModelField = zModelIdentifier;
+export type T2IAdapterModelField = z.infer<typeof zT2IAdapterModelField>;
+
+export const zLoraInfo = zModelInfo.extend({
+  weight: z.number().optional(),
+});
+export type LoraInfo = z.infer<typeof zLoraInfo>;
+
+export const zUNetField = z.object({
+  unet: zModelInfo,
+  scheduler: zModelInfo,
+  loras: z.array(zLoraInfo),
+});
+export type UNetField = z.infer<typeof zUNetField>;
+
+export const zCLIPField = z.object({
+  tokenizer: zModelInfo,
+  text_encoder: zModelInfo,
+  skipped_layers: z.number(),
+  loras: z.array(zLoraInfo),
+});
+export type CLIPField = z.infer<typeof zCLIPField>;
+
+export const zVAEField = z.object({
+  vae: zModelInfo,
+});
+export type VAEField = z.infer<typeof zVAEField>;
+// #endregion
+
+// #region Control Adapters
+export const zControlField = z.object({
+  image: zImageField,
+  control_model: zControlNetModelField,
+  control_weight: z.union([z.number(), z.array(z.number())]).optional(),
+  begin_step_percent: z.number().optional(),
+  end_step_percent: z.number().optional(),
+  control_mode: z.enum(['balanced', 'more_prompt', 'more_control', 'unbalanced']).optional(),
+  resize_mode: z.enum(['just_resize', 'crop_resize', 'fill_resize', 'just_resize_simple']).optional(),
+});
+export type ControlField = z.infer<typeof zControlField>;
+
+export const zIPAdapterField = z.object({
+  image: zImageField,
+  ip_adapter_model: zIPAdapterModelField,
+  weight: z.number(),
+  begin_step_percent: z.number().optional(),
+  end_step_percent: z.number().optional(),
+});
+export type IPAdapterField = z.infer<typeof zIPAdapterField>;
+
+export const zT2IAdapterField = z.object({
+  image: zImageField,
+  t2i_adapter_model: zT2IAdapterModelField,
+  weight: z.union([z.number(), z.array(z.number())]).optional(),
+  begin_step_percent: z.number().optional(),
+  end_step_percent: z.number().optional(),
+  resize_mode: z.enum(['just_resize', 'crop_resize', 'fill_resize', 'just_resize_simple']).optional(),
+});
+export type T2IAdapterField = z.infer<typeof zT2IAdapterField>;
+// #endregion
+
+// #region ProgressImage
+export const zProgressImage = z.object({
+  dataURL: z.string(),
+  width: z.number().int(),
+  height: z.number().int(),
+});
+export type ProgressImage = z.infer<typeof zProgressImage>;
+// #endregion
+
+// #region ImageOutput
+export const zImageOutput = z.object({
+  image: zImageField,
+  width: z.number().int().gt(0),
+  height: z.number().int().gt(0),
+  type: z.literal('image_output'),
+});
+export type ImageOutput = z.infer<typeof zImageOutput>;
+export const isImageOutput = (output: unknown): output is ImageOutput => zImageOutput.safeParse(output).success;
+// #endregion
diff --git a/invokeai/frontend/web/src/features/nodes/types/v2/constants.ts b/invokeai/frontend/web/src/features/nodes/types/v2/constants.ts
new file mode 100644
index 0000000000..35ef9e9fd2
--- /dev/null
+++ b/invokeai/frontend/web/src/features/nodes/types/v2/constants.ts
@@ -0,0 +1,80 @@
+import type { Node } from 'reactflow';
+
+/**
+ * How long to wait before showing a tooltip when hovering a field handle.
+ */
+export const HANDLE_TOOLTIP_OPEN_DELAY = 500;
+
+/**
+ * The width of a node in the UI in pixels.
+ */
+export const NODE_WIDTH = 320;
+
+/**
+ * This class name is special - reactflow uses it to identify the drag handle of a node,
+ * applying the appropriate listeners to it.
+ */
+export const DRAG_HANDLE_CLASSNAME = 'node-drag-handle';
+
+/**
+ * reactflow-specifc properties shared between all node types.
+ */
+export const SHARED_NODE_PROPERTIES: Partial<Node> = {
+  dragHandle: `.${DRAG_HANDLE_CLASSNAME}`,
+};
+
+/**
+ * Helper for getting the kind of a field.
+ */
+export const KIND_MAP = {
+  input: 'inputs' as const,
+  output: 'outputs' as const,
+};
+
+/**
+ * Model types' handles are rendered as squares in the UI.
+ */
+export const MODEL_TYPES = [
+  'IPAdapterModelField',
+  'ControlNetModelField',
+  'LoRAModelField',
+  'MainModelField',
+  'SDXLMainModelField',
+  'SDXLRefinerModelField',
+  'VaeModelField',
+  'UNetField',
+  'VaeField',
+  'ClipField',
+  'T2IAdapterModelField',
+  'IPAdapterModelField',
+];
+
+/**
+ * Colors for each field type - applies to their handles and edges.
+ */
+export const FIELD_COLORS: { [key: string]: string } = {
+  BoardField: 'purple.500',
+  BooleanField: 'green.500',
+  ClipField: 'green.500',
+  ColorField: 'pink.300',
+  ConditioningField: 'cyan.500',
+  ControlField: 'teal.500',
+  ControlNetModelField: 'teal.500',
+  EnumField: 'blue.500',
+  FloatField: 'orange.500',
+  ImageField: 'purple.500',
+  IntegerField: 'red.500',
+  IPAdapterField: 'teal.500',
+  IPAdapterModelField: 'teal.500',
+  LatentsField: 'pink.500',
+  LoRAModelField: 'teal.500',
+  MainModelField: 'teal.500',
+  SDXLMainModelField: 'teal.500',
+  SDXLRefinerModelField: 'teal.500',
+  StringField: 'yellow.500',
+  T2IAdapterField: 'teal.500',
+  T2IAdapterModelField: 'teal.500',
+  UNetField: 'red.500',
+  VaeField: 'blue.500',
+  VaeModelField: 'teal.500',
+};
diff --git a/invokeai/frontend/web/src/features/nodes/types/v2/error.ts b/invokeai/frontend/web/src/features/nodes/types/v2/error.ts
new file mode 100644
index 0000000000..905b487fb0
--- /dev/null
+++ b/invokeai/frontend/web/src/features/nodes/types/v2/error.ts
@@ -0,0 +1,58 @@
+/**
+ * Invalid Workflow Version Error
+ * Raised when a workflow version is not recognized.
+ */
+export class WorkflowVersionError extends Error {
+  /**
+   * Create WorkflowVersionError
+   * @param {String} message
+   */
+  constructor(message: string) {
+    super(message);
+    this.name = this.constructor.name;
+  }
+}
+/**
+ * Workflow Migration Error
+ * Raised when a workflow migration fails.
+ */
+export class WorkflowMigrationError extends Error {
+  /**
+   * Create WorkflowMigrationError
+   * @param {String} message
+   */
+  constructor(message: string) {
+    super(message);
+    this.name = this.constructor.name;
+  }
+}
+
+/**
+ * Unable to Update Node Error
+ * Raised when a node cannot be updated.
+ */
+export class NodeUpdateError extends Error {
+  /**
+   * Create NodeUpdateError
+   * @param {String} message
+   */
+  constructor(message: string) {
+    super(message);
+    this.name = this.constructor.name;
+  }
+}
+
+/**
+ * FieldParseError
+ * Raised when a field cannot be parsed from a field schema.
+ */
+export class FieldParseError extends Error {
+  /**
+   * Create FieldTypeParseError
+   * @param {String} message
+   */
+  constructor(message: string) {
+    super(message);
+    this.name = this.constructor.name;
+  }
+}
diff --git a/invokeai/frontend/web/src/features/nodes/types/v2/field.ts b/invokeai/frontend/web/src/features/nodes/types/v2/field.ts
new file mode 100644
index 0000000000..38f1af55dd
--- /dev/null
+++ b/invokeai/frontend/web/src/features/nodes/types/v2/field.ts
@@ -0,0 +1,875 @@
+import { z } from 'zod';
+
+import {
+  zBoardField,
+  zColorField,
+  zControlNetModelField,
+  zImageField,
+  zIPAdapterModelField,
+  zLoRAModelField,
+  zMainModelField,
+  zSchedulerField,
+  zT2IAdapterModelField,
+  zVAEModelField,
+} from './common';
+
+/**
+ * zod schemas & inferred types for fields.
+ *
+ * These schemas and types are only required for stateful field - fields that have UI components
+ * and allow the user to directly provide values.
+ *
+ * This includes primitive values (numbers, strings, booleans), models, scheduler, etc.
+ *
+ * If a field type does not have a UI component, then it does not need to be included here, because
+ * we never store its value. Such field types will be handled via the "StatelessField" logic.
+ *
+ * Fields require:
+ * - z<TypeName>FieldType - zod schema for the field type
+ * - z<TypeName>FieldValue - zod schema for the field value
+ * - z<TypeName>FieldInputInstance - zod schema for the field's input instance
+ * - z<TypeName>FieldOutputInstance - zod schema for the field's output instance
+ * - z<TypeName>FieldInputTemplate - zod schema for the field's input template
+ * - z<TypeName>FieldOutputTemplate - zod schema for the field's output template
+ * - inferred types for each schema
+ * - type guards for InputInstance and InputTemplate
+ *
+ * These then must be added to the unions at the bottom of this file.
+ */
+
+/** */
+
+// #region Base schemas & misc
+export const zFieldInput = z.enum(['connection', 'direct', 'any']);
+export type FieldInput = z.infer<typeof zFieldInput>;
+
+export const zFieldUIComponent = z.enum(['none', 'textarea', 'slider']);
+export type FieldUIComponent = z.infer<typeof zFieldUIComponent>;
+
+export const zFieldInstanceBase = z.object({
+  id: z.string().trim().min(1),
+  name: z.string().trim().min(1),
+});
+export const zFieldInputInstanceBase = zFieldInstanceBase.extend({
+  fieldKind: z.literal('input'),
+  label: z.string().nullish(),
+});
+export const zFieldOutputInstanceBase = zFieldInstanceBase.extend({
+  fieldKind: z.literal('output'),
+});
+export type FieldInstanceBase = z.infer<typeof zFieldInstanceBase>;
+export type FieldInputInstanceBase = z.infer<typeof zFieldInputInstanceBase>;
+export type FieldOutputInstanceBase = z.infer<typeof zFieldOutputInstanceBase>;
+
+export const zFieldTemplateBase = z.object({
+  name: z.string().min(1),
+  title: z.string().min(1),
+  description: z.string().nullish(),
+  ui_hidden: z.boolean(),
+  ui_type: z.string().nullish(),
+  ui_order: z.number().int().nullish(),
+});
+export const zFieldInputTemplateBase = zFieldTemplateBase.extend({
+  fieldKind: z.literal('input'),
+  input: zFieldInput,
+  required: z.boolean(),
+  ui_component: zFieldUIComponent.nullish(),
+  ui_choice_labels: z.record(z.string()).nullish(),
+});
+export const zFieldOutputTemplateBase = zFieldTemplateBase.extend({
+  fieldKind: z.literal('output'),
+});
+export type FieldTemplateBase = z.infer<typeof zFieldTemplateBase>;
+export type FieldInputTemplateBase = z.infer<typeof zFieldInputTemplateBase>;
+export type FieldOutputTemplateBase = z.infer<typeof zFieldOutputTemplateBase>;
+
+export const zFieldTypeBase = z.object({
+  isCollection: z.boolean(),
+  isCollectionOrScalar: z.boolean(),
+});
+
+export const zFieldIdentifier = z.object({
+  nodeId: z.string().trim().min(1),
+  fieldName: z.string().trim().min(1),
+});
+export type FieldIdentifier = z.infer<typeof zFieldIdentifier>;
+export const isFieldIdentifier = (val: unknown): val is FieldIdentifier => zFieldIdentifier.safeParse(val).success;
+// #endregion
+
+// #region IntegerField
+export const zIntegerFieldType = zFieldTypeBase.extend({
+  name: z.literal('IntegerField'),
+});
+export const zIntegerFieldValue = z.number().int();
+export const zIntegerFieldInputInstance = zFieldInputInstanceBase.extend({
+  type: zIntegerFieldType,
+  value: zIntegerFieldValue,
+});
+export const zIntegerFieldOutputInstance = zFieldOutputInstanceBase.extend({
+  type: zIntegerFieldType,
+});
+export const zIntegerFieldInputTemplate = zFieldInputTemplateBase.extend({
+  type: zIntegerFieldType,
+  default: zIntegerFieldValue,
+  multipleOf: z.number().int().optional(),
+  maximum: z.number().int().optional(),
+  exclusiveMaximum: z.number().int().optional(),
+  minimum: z.number().int().optional(),
+  exclusiveMinimum: z.number().int().optional(),
+});
+export const zIntegerFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+  type: zIntegerFieldType,
+});
+export type IntegerFieldType = z.infer<typeof zIntegerFieldType>;
+export type IntegerFieldValue = z.infer<typeof zIntegerFieldValue>;
+export type IntegerFieldInputInstance = z.infer<typeof zIntegerFieldInputInstance>;
+export type IntegerFieldInputTemplate = z.infer<typeof zIntegerFieldInputTemplate>;
+export const isIntegerFieldInputInstance = (val: unknown): val is IntegerFieldInputInstance =>
+  zIntegerFieldInputInstance.safeParse(val).success;
+export const isIntegerFieldInputTemplate = (val: unknown): val is IntegerFieldInputTemplate =>
+  zIntegerFieldInputTemplate.safeParse(val).success;
+// #endregion
+
+// #region FloatField
+export const zFloatFieldType = zFieldTypeBase.extend({
+  name: z.literal('FloatField'),
+});
+export const zFloatFieldValue = z.number();
+export const zFloatFieldInputInstance = zFieldInputInstanceBase.extend({
+  type: zFloatFieldType,
+  value: zFloatFieldValue,
+});
+export const zFloatFieldOutputInstance = zFieldOutputInstanceBase.extend({
+  type: zFloatFieldType,
+});
+export const zFloatFieldInputTemplate = zFieldInputTemplateBase.extend({
+  type: zFloatFieldType,
+  default: zFloatFieldValue,
+  multipleOf: z.number().optional(),
+  maximum: z.number().optional(),
+  exclusiveMaximum: z.number().optional(),
+  minimum: z.number().optional(),
+  exclusiveMinimum: z.number().optional(),
+});
+export const zFloatFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+  type: zFloatFieldType,
+});
+export type FloatFieldType = z.infer<typeof zFloatFieldType>;
+export type FloatFieldValue = z.infer<typeof zFloatFieldValue>;
+export type FloatFieldInputInstance = z.infer<typeof zFloatFieldInputInstance>;
+export type FloatFieldOutputInstance = z.infer<typeof zFloatFieldOutputInstance>;
+export type FloatFieldInputTemplate = z.infer<typeof zFloatFieldInputTemplate>;
+export type FloatFieldOutputTemplate = z.infer<typeof zFloatFieldOutputTemplate>;
+export const isFloatFieldInputInstance = (val: unknown): val is FloatFieldInputInstance =>
+  zFloatFieldInputInstance.safeParse(val).success;
+export const isFloatFieldInputTemplate = (val: unknown): val is FloatFieldInputTemplate =>
+  zFloatFieldInputTemplate.safeParse(val).success;
+// #endregion
+
+// #region StringField
+export const zStringFieldType = zFieldTypeBase.extend({
+  name: z.literal('StringField'),
+});
+export const zStringFieldValue = z.string();
+export const zStringFieldInputInstance = zFieldInputInstanceBase.extend({
+  type: zStringFieldType,
+  value: zStringFieldValue,
+});
+export const zStringFieldOutputInstance = zFieldOutputInstanceBase.extend({
+  type: zStringFieldType,
+});
+export const zStringFieldInputTemplate = zFieldInputTemplateBase.extend({
+  type: zStringFieldType,
+  default: zStringFieldValue,
+  maxLength: z.number().int().optional(),
+  minLength: z.number().int().optional(),
+});
+export const zStringFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+  type: zStringFieldType,
+});
+
+export type StringFieldType = z.infer<typeof zStringFieldType>;
+export type StringFieldValue = z.infer<typeof zStringFieldValue>;
+export type StringFieldInputInstance = z.infer<typeof zStringFieldInputInstance>;
+export type StringFieldOutputInstance = z.infer<typeof zStringFieldOutputInstance>;
+export type StringFieldInputTemplate = z.infer<typeof zStringFieldInputTemplate>;
+export type StringFieldOutputTemplate = z.infer<typeof zStringFieldOutputTemplate>;
+export const isStringFieldInputInstance = (val: unknown): val is StringFieldInputInstance =>
+  zStringFieldInputInstance.safeParse(val).success;
+export const isStringFieldInputTemplate = (val: unknown): val is StringFieldInputTemplate =>
+  zStringFieldInputTemplate.safeParse(val).success;
+// #endregion
+
+// #region BooleanField
+export const zBooleanFieldType = zFieldTypeBase.extend({
+  name: z.literal('BooleanField'),
+});
+export const zBooleanFieldValue = z.boolean();
+export const zBooleanFieldInputInstance = zFieldInputInstanceBase.extend({
+  type: zBooleanFieldType,
+  value: zBooleanFieldValue,
+});
+export const zBooleanFieldOutputInstance = zFieldOutputInstanceBase.extend({
+  type: zBooleanFieldType,
+});
+export const zBooleanFieldInputTemplate = zFieldInputTemplateBase.extend({
+  type: zBooleanFieldType,
+  default: zBooleanFieldValue,
+});
+export const zBooleanFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+  type: zBooleanFieldType,
+});
+export type BooleanFieldType = z.infer<typeof zBooleanFieldType>;
+export type BooleanFieldValue = z.infer<typeof zBooleanFieldValue>;
+export type BooleanFieldInputInstance = z.infer<typeof zBooleanFieldInputInstance>;
+export type BooleanFieldOutputInstance = z.infer<typeof zBooleanFieldOutputInstance>;
+export type BooleanFieldInputTemplate = z.infer<typeof zBooleanFieldInputTemplate>;
+export type BooleanFieldOutputTemplate = z.infer<typeof zBooleanFieldOutputTemplate>;
+export const isBooleanFieldInputInstance = (val: unknown): val is BooleanFieldInputInstance =>
+  zBooleanFieldInputInstance.safeParse(val).success;
+export const isBooleanFieldInputTemplate = (val: unknown): val is BooleanFieldInputTemplate =>
+  zBooleanFieldInputTemplate.safeParse(val).success;
+// #endregion
+
+// #region EnumField
+export const zEnumFieldType = zFieldTypeBase.extend({
+  name: z.literal('EnumField'),
+});
+export const zEnumFieldValue = z.string();
+export const zEnumFieldInputInstance = zFieldInputInstanceBase.extend({
+  type: zEnumFieldType,
+  value: zEnumFieldValue,
+});
+export const zEnumFieldOutputInstance = zFieldOutputInstanceBase.extend({
+  type: zEnumFieldType,
+});
+export const zEnumFieldInputTemplate = zFieldInputTemplateBase.extend({
+  type: zEnumFieldType,
+  default: zEnumFieldValue,
+  options: z.array(z.string()),
+  labels: z.record(z.string()).optional(),
+});
+export const zEnumFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+  type: zEnumFieldType,
+});
+export type EnumFieldType = z.infer<typeof zEnumFieldType>;
+export type EnumFieldValue = z.infer<typeof zEnumFieldValue>;
+export type EnumFieldInputInstance = z.infer<typeof zEnumFieldInputInstance>;
+export type EnumFieldOutputInstance = z.infer<typeof zEnumFieldOutputInstance>;
+export type EnumFieldInputTemplate = z.infer<typeof zEnumFieldInputTemplate>;
+export type EnumFieldOutputTemplate = z.infer<typeof zEnumFieldOutputTemplate>;
+export const isEnumFieldInputInstance = (val: unknown): val is EnumFieldInputInstance =>
+  zEnumFieldInputInstance.safeParse(val).success;
+export const isEnumFieldInputTemplate = (val: unknown): val is EnumFieldInputTemplate =>
+  zEnumFieldInputTemplate.safeParse(val).success;
+// #endregion
+
+// #region ImageField
+export const zImageFieldType = zFieldTypeBase.extend({
+  name: z.literal('ImageField'),
+});
+export const zImageFieldValue = zImageField.optional();
+export const zImageFieldInputInstance = zFieldInputInstanceBase.extend({
+  type: zImageFieldType,
+  value: zImageFieldValue,
+});
+export const zImageFieldOutputInstance = zFieldOutputInstanceBase.extend({
+  type: zImageFieldType,
+});
+export const zImageFieldInputTemplate = zFieldInputTemplateBase.extend({
+  type: zImageFieldType,
+  default: zImageFieldValue,
+});
+export const zImageFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+  type: zImageFieldType,
+});
+export type ImageFieldType = z.infer<typeof zImageFieldType>;
+export type ImageFieldValue = z.infer<typeof zImageFieldValue>;
+export type ImageFieldInputInstance = z.infer<typeof zImageFieldInputInstance>;
+export type ImageFieldOutputInstance = z.infer<typeof zImageFieldOutputInstance>;
+export type ImageFieldInputTemplate = z.infer<typeof zImageFieldInputTemplate>;
+export type ImageFieldOutputTemplate = z.infer<typeof zImageFieldOutputTemplate>;
+export const isImageFieldInputInstance = (val: unknown): val is ImageFieldInputInstance =>
+  zImageFieldInputInstance.safeParse(val).success;
+export const isImageFieldInputTemplate = (val: unknown): val is ImageFieldInputTemplate =>
+  zImageFieldInputTemplate.safeParse(val).success;
+// #endregion
+
+// #region BoardField
+export const zBoardFieldType = zFieldTypeBase.extend({
+  name: z.literal('BoardField'),
+});
+export const zBoardFieldValue = zBoardField.optional();
+export const zBoardFieldInputInstance = zFieldInputInstanceBase.extend({
+  type: zBoardFieldType,
+  value: zBoardFieldValue,
+});
+export const zBoardFieldOutputInstance = zFieldOutputInstanceBase.extend({
+  type: zBoardFieldType,
+});
+export const zBoardFieldInputTemplate = zFieldInputTemplateBase.extend({
+  type: zBoardFieldType,
+  default: zBoardFieldValue,
+});
+export const zBoardFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+  type: zBoardFieldType,
+});
+export type BoardFieldType = z.infer<typeof zBoardFieldType>;
+export type BoardFieldValue = z.infer<typeof zBoardFieldValue>;
+export type BoardFieldInputInstance = z.infer<typeof zBoardFieldInputInstance>;
+export type BoardFieldOutputInstance = z.infer<typeof zBoardFieldOutputInstance>;
+export type BoardFieldInputTemplate = z.infer<typeof zBoardFieldInputTemplate>;
+export type BoardFieldOutputTemplate = z.infer<typeof zBoardFieldOutputTemplate>;
+export const isBoardFieldInputInstance = (val: unknown): val is BoardFieldInputInstance =>
+  zBoardFieldInputInstance.safeParse(val).success;
+export const isBoardFieldInputTemplate = (val: unknown): val is BoardFieldInputTemplate =>
+  zBoardFieldInputTemplate.safeParse(val).success;
+// #endregion
+
+// #region ColorField
+export const zColorFieldType = zFieldTypeBase.extend({
+  name: z.literal('ColorField'),
+});
+export const zColorFieldValue = zColorField.optional();
+export const zColorFieldInputInstance = zFieldInputInstanceBase.extend({
+  type: zColorFieldType,
+  value: zColorFieldValue,
+});
+export const zColorFieldOutputInstance = zFieldOutputInstanceBase.extend({
+  type: zColorFieldType,
+});
+export const zColorFieldInputTemplate = zFieldInputTemplateBase.extend({
+  type: zColorFieldType,
+  default: zColorFieldValue,
+});
+export const zColorFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+  type: zColorFieldType,
+});
+export type ColorFieldType = z.infer<typeof zColorFieldType>;
+export type ColorFieldValue = z.infer<typeof zColorFieldValue>;
+export type ColorFieldInputInstance = z.infer<typeof zColorFieldInputInstance>;
+export type ColorFieldOutputInstance = z.infer<typeof zColorFieldOutputInstance>;
+export type ColorFieldInputTemplate = z.infer<typeof zColorFieldInputTemplate>;
+export type ColorFieldOutputTemplate = z.infer<typeof zColorFieldOutputTemplate>;
+export const isColorFieldInputInstance = (val: unknown): val is ColorFieldInputInstance =>
+  zColorFieldInputInstance.safeParse(val).success;
+export const isColorFieldInputTemplate = (val: unknown): val is ColorFieldInputTemplate =>
+  zColorFieldInputTemplate.safeParse(val).success;
+// #endregion
+
+// #region MainModelField
+export const zMainModelFieldType = zFieldTypeBase.extend({
+  name: z.literal('MainModelField'),
+});
+export const zMainModelFieldValue = zMainModelField.optional();
+export const zMainModelFieldInputInstance = zFieldInputInstanceBase.extend({
+  type: zMainModelFieldType,
+  value: zMainModelFieldValue,
+});
+export const zMainModelFieldOutputInstance = zFieldOutputInstanceBase.extend({
+  type: zMainModelFieldType,
+});
+export const zMainModelFieldInputTemplate = zFieldInputTemplateBase.extend({
+  type: zMainModelFieldType,
+  default: zMainModelFieldValue,
+});
+export const zMainModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+  type: zMainModelFieldType,
+});
+export type MainModelFieldType = z.infer<typeof zMainModelFieldType>;
+export type MainModelFieldValue = z.infer<typeof zMainModelFieldValue>;
+export type MainModelFieldInputInstance = z.infer<typeof zMainModelFieldInputInstance>;
+export type MainModelFieldOutputInstance = z.infer<typeof zMainModelFieldOutputInstance>;
+export type MainModelFieldInputTemplate = z.infer<typeof zMainModelFieldInputTemplate>;
+export type MainModelFieldOutputTemplate = z.infer<typeof zMainModelFieldOutputTemplate>;
+export const isMainModelFieldInputInstance = (val: unknown): val is MainModelFieldInputInstance =>
+  zMainModelFieldInputInstance.safeParse(val).success;
+export const isMainModelFieldInputTemplate = (val: unknown): val is MainModelFieldInputTemplate =>
+  zMainModelFieldInputTemplate.safeParse(val).success;
+// #endregion
+
+// #region SDXLMainModelField
+export const zSDXLMainModelFieldType = zFieldTypeBase.extend({
+  name: z.literal('SDXLMainModelField'),
+});
+export const zSDXLMainModelFieldValue = zMainModelFieldValue; // TODO: Narrow to SDXL models only.
+export const zSDXLMainModelFieldInputInstance = zFieldInputInstanceBase.extend({
+  type: zSDXLMainModelFieldType,
+  value: zSDXLMainModelFieldValue,
+});
+export const zSDXLMainModelFieldOutputInstance = zFieldOutputInstanceBase.extend({
+  type: zSDXLMainModelFieldType,
+});
+export const zSDXLMainModelFieldInputTemplate = zFieldInputTemplateBase.extend({
+  type: zSDXLMainModelFieldType,
+  default: zSDXLMainModelFieldValue,
+});
+export const zSDXLMainModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+  type: zSDXLMainModelFieldType,
+});
+export type SDXLMainModelFieldType = z.infer<typeof zSDXLMainModelFieldType>;
+export type SDXLMainModelFieldValue = z.infer<typeof zSDXLMainModelFieldValue>;
+export type SDXLMainModelFieldInputInstance = z.infer<typeof zSDXLMainModelFieldInputInstance>;
+export type SDXLMainModelFieldOutputInstance = z.infer<typeof zSDXLMainModelFieldOutputInstance>;
+export type SDXLMainModelFieldInputTemplate = z.infer<typeof zSDXLMainModelFieldInputTemplate>;
+export type SDXLMainModelFieldOutputTemplate = z.infer<typeof zSDXLMainModelFieldOutputTemplate>;
+export const isSDXLMainModelFieldInputInstance = (val: unknown): val is SDXLMainModelFieldInputInstance =>
+  zSDXLMainModelFieldInputInstance.safeParse(val).success;
+export const isSDXLMainModelFieldInputTemplate = (val: unknown): val is SDXLMainModelFieldInputTemplate =>
+  zSDXLMainModelFieldInputTemplate.safeParse(val).success;
+// #endregion
+
+// #region SDXLRefinerModelField
+export const zSDXLRefinerModelFieldType = zFieldTypeBase.extend({
+  name: z.literal('SDXLRefinerModelField'),
+});
+export const zSDXLRefinerModelFieldValue = zMainModelFieldValue; // TODO: Narrow to SDXL Refiner models only.
+export const zSDXLRefinerModelFieldInputInstance = zFieldInputInstanceBase.extend({
+  type: zSDXLRefinerModelFieldType,
+  value: zSDXLRefinerModelFieldValue,
+});
+export const zSDXLRefinerModelFieldOutputInstance = zFieldOutputInstanceBase.extend({
+  type: zSDXLRefinerModelFieldType,
+});
+export const zSDXLRefinerModelFieldInputTemplate = zFieldInputTemplateBase.extend({
+  type: zSDXLRefinerModelFieldType,
+  default: zSDXLRefinerModelFieldValue,
+});
+export const zSDXLRefinerModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+  type: zSDXLRefinerModelFieldType,
+});
+export type SDXLRefinerModelFieldType = z.infer<typeof zSDXLRefinerModelFieldType>;
+export type SDXLRefinerModelFieldValue = z.infer<typeof zSDXLRefinerModelFieldValue>;
+export type SDXLRefinerModelFieldInputInstance = z.infer<typeof zSDXLRefinerModelFieldInputInstance>;
+export type SDXLRefinerModelFieldOutputInstance = z.infer<typeof zSDXLRefinerModelFieldOutputInstance>;
+export type SDXLRefinerModelFieldInputTemplate = z.infer<typeof zSDXLRefinerModelFieldInputTemplate>;
+export type SDXLRefinerModelFieldOutputTemplate = z.infer<typeof zSDXLRefinerModelFieldOutputTemplate>;
+export const isSDXLRefinerModelFieldInputInstance = (val: unknown): val is SDXLRefinerModelFieldInputInstance =>
+  zSDXLRefinerModelFieldInputInstance.safeParse(val).success;
+export const isSDXLRefinerModelFieldInputTemplate = (val: unknown): val is SDXLRefinerModelFieldInputTemplate =>
+  zSDXLRefinerModelFieldInputTemplate.safeParse(val).success;
+// #endregion
+
+// #region VAEModelField
+export const zVAEModelFieldType = zFieldTypeBase.extend({
+  name: z.literal('VAEModelField'),
+});
+export const zVAEModelFieldValue = zVAEModelField.optional();
+export const zVAEModelFieldInputInstance = zFieldInputInstanceBase.extend({
+  type: zVAEModelFieldType,
+  value: zVAEModelFieldValue,
+});
+export const zVAEModelFieldOutputInstance = zFieldOutputInstanceBase.extend({
+  type: zVAEModelFieldType,
+});
+export const zVAEModelFieldInputTemplate = zFieldInputTemplateBase.extend({
+  type: zVAEModelFieldType,
+  default: zVAEModelFieldValue,
+});
+export const zVAEModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+  type: zVAEModelFieldType,
+});
+export type VAEModelFieldType = z.infer<typeof zVAEModelFieldType>;
+export type VAEModelFieldValue = z.infer<typeof zVAEModelFieldValue>;
+export type VAEModelFieldInputInstance = z.infer<typeof zVAEModelFieldInputInstance>;
+export type VAEModelFieldOutputInstance = z.infer<typeof zVAEModelFieldOutputInstance>;
+export type VAEModelFieldInputTemplate = z.infer<typeof zVAEModelFieldInputTemplate>;
+export type VAEModelFieldOutputTemplate = z.infer<typeof zVAEModelFieldOutputTemplate>;
+export const isVAEModelFieldInputInstance = (val: unknown): val is VAEModelFieldInputInstance =>
+  zVAEModelFieldInputInstance.safeParse(val).success;
+export const isVAEModelFieldInputTemplate = (val: unknown): val is VAEModelFieldInputTemplate =>
+  zVAEModelFieldInputTemplate.safeParse(val).success;
+// #endregion
+
+// #region LoRAModelField
+export const zLoRAModelFieldType = zFieldTypeBase.extend({
+  name: z.literal('LoRAModelField'),
+});
+export const zLoRAModelFieldValue = zLoRAModelField.optional();
+export const zLoRAModelFieldInputInstance = zFieldInputInstanceBase.extend({
+  type: zLoRAModelFieldType,
+  value: zLoRAModelFieldValue,
+});
+export const zLoRAModelFieldOutputInstance = zFieldOutputInstanceBase.extend({
+  type: zLoRAModelFieldType,
+});
+export const zLoRAModelFieldInputTemplate = zFieldInputTemplateBase.extend({
+  type: zLoRAModelFieldType,
+  default: zLoRAModelFieldValue,
+});
+export const zLoRAModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+  type: zLoRAModelFieldType,
+});
+export type LoRAModelFieldType = z.infer<typeof zLoRAModelFieldType>;
+export type LoRAModelFieldValue = z.infer<typeof zLoRAModelFieldValue>;
+export type LoRAModelFieldInputInstance = z.infer<typeof zLoRAModelFieldInputInstance>;
+export type LoRAModelFieldOutputInstance = z.infer<typeof zLoRAModelFieldOutputInstance>;
+export type LoRAModelFieldInputTemplate = z.infer<typeof zLoRAModelFieldInputTemplate>;
+export type LoRAModelFieldOutputTemplate = z.infer<typeof zLoRAModelFieldOutputTemplate>;
+export const isLoRAModelFieldInputInstance = (val: unknown): val is LoRAModelFieldInputInstance =>
+  zLoRAModelFieldInputInstance.safeParse(val).success;
+export const isLoRAModelFieldInputTemplate = (val: unknown): val is LoRAModelFieldInputTemplate =>
+  zLoRAModelFieldInputTemplate.safeParse(val).success;
+// #endregion
+
+// #region ControlNetModelField
+export const zControlNetModelFieldType = zFieldTypeBase.extend({
+  name: z.literal('ControlNetModelField'),
+});
+export const zControlNetModelFieldValue = zControlNetModelField.optional();
+export const zControlNetModelFieldInputInstance = zFieldInputInstanceBase.extend({
+  type: zControlNetModelFieldType,
+  value: zControlNetModelFieldValue,
+});
+export const zControlNetModelFieldOutputInstance = zFieldOutputInstanceBase.extend({
+  type: zControlNetModelFieldType,
+});
+export const zControlNetModelFieldInputTemplate = zFieldInputTemplateBase.extend({
+  type: zControlNetModelFieldType,
+  default: zControlNetModelFieldValue,
+});
+export const zControlNetModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+  type: zControlNetModelFieldType,
+});
+export type ControlNetModelFieldType = z.infer<typeof zControlNetModelFieldType>;
+export type ControlNetModelFieldValue = z.infer<typeof zControlNetModelFieldValue>;
+export type ControlNetModelFieldInputInstance = z.infer<typeof zControlNetModelFieldInputInstance>;
+export type ControlNetModelFieldOutputInstance = z.infer<typeof zControlNetModelFieldOutputInstance>;
+export type ControlNetModelFieldInputTemplate = z.infer<typeof zControlNetModelFieldInputTemplate>;
+export type ControlNetModelFieldOutputTemplate = z.infer<typeof zControlNetModelFieldOutputTemplate>;
+export const isControlNetModelFieldInputInstance = (val: unknown): val is ControlNetModelFieldInputInstance =>
+  zControlNetModelFieldInputInstance.safeParse(val).success;
+export const isControlNetModelFieldInputTemplate = (val: unknown): val is ControlNetModelFieldInputTemplate =>
+  zControlNetModelFieldInputTemplate.safeParse(val).success;
+export const isControlNetModelFieldValue = (v: unknown): v is ControlNetModelFieldValue =>
+  zControlNetModelFieldValue.safeParse(v).success;
+// #endregion
+
+// #region IPAdapterModelField
+export const zIPAdapterModelFieldType = zFieldTypeBase.extend({
+  name: z.literal('IPAdapterModelField'),
+});
+export const zIPAdapterModelFieldValue = zIPAdapterModelField.optional();
+export const zIPAdapterModelFieldInputInstance = zFieldInputInstanceBase.extend({
+  type: zIPAdapterModelFieldType,
+  value: zIPAdapterModelFieldValue,
+});
+export const zIPAdapterModelFieldOutputInstance = zFieldOutputInstanceBase.extend({
+  type: zIPAdapterModelFieldType,
+});
+export const zIPAdapterModelFieldInputTemplate = zFieldInputTemplateBase.extend({
+  type: zIPAdapterModelFieldType,
+  default: zIPAdapterModelFieldValue,
+});
+export const zIPAdapterModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+  type: zIPAdapterModelFieldType,
+});
+export type IPAdapterModelFieldType = z.infer<typeof zIPAdapterModelFieldType>;
+export type IPAdapterModelFieldValue = z.infer<typeof zIPAdapterModelFieldValue>;
+export type IPAdapterModelFieldInputInstance = z.infer<typeof zIPAdapterModelFieldInputInstance>;
+export type IPAdapterModelFieldOutputInstance = z.infer<typeof zIPAdapterModelFieldOutputInstance>;
+export type IPAdapterModelFieldInputTemplate = z.infer<typeof zIPAdapterModelFieldInputTemplate>;
+export type IPAdapterModelFieldOutputTemplate = z.infer<typeof zIPAdapterModelFieldOutputTemplate>;
+export const isIPAdapterModelFieldInputInstance = (val: unknown): val is IPAdapterModelFieldInputInstance =>
+  zIPAdapterModelFieldInputInstance.safeParse(val).success;
+export const isIPAdapterModelFieldInputTemplate = (val: unknown): val is IPAdapterModelFieldInputTemplate =>
+  zIPAdapterModelFieldInputTemplate.safeParse(val).success;
+export const isIPAdapterModelFieldValue = (val: unknown): val is IPAdapterModelFieldValue =>
+  zIPAdapterModelFieldValue.safeParse(val).success;
+// #endregion
+
+// #region T2IAdapterField
+export const zT2IAdapterModelFieldType = zFieldTypeBase.extend({
+  name: z.literal('T2IAdapterModelField'),
+});
+export const zT2IAdapterModelFieldValue = zT2IAdapterModelField.optional();
+export const zT2IAdapterModelFieldInputInstance = zFieldInputInstanceBase.extend({
+  type: zT2IAdapterModelFieldType,
+  value: zT2IAdapterModelFieldValue,
+});
+export const zT2IAdapterModelFieldOutputInstance = zFieldOutputInstanceBase.extend({
+  type: zT2IAdapterModelFieldType,
+});
+export const zT2IAdapterModelFieldInputTemplate = zFieldInputTemplateBase.extend({
+  type: zT2IAdapterModelFieldType,
+  default: zT2IAdapterModelFieldValue,
+});
+export const zT2IAdapterModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+  type: zT2IAdapterModelFieldType,
+});
+export type T2IAdapterModelFieldType = z.infer<typeof zT2IAdapterModelFieldType>;
+export type T2IAdapterModelFieldValue = z.infer<typeof zT2IAdapterModelFieldValue>;
+export type T2IAdapterModelFieldInputInstance = z.infer<typeof zT2IAdapterModelFieldInputInstance>;
+export type T2IAdapterModelFieldOutputInstance = z.infer<typeof zT2IAdapterModelFieldOutputInstance>;
+export type T2IAdapterModelFieldInputTemplate = z.infer<typeof zT2IAdapterModelFieldInputTemplate>;
+export type T2IAdapterModelFieldOutputTemplate = z.infer<typeof zT2IAdapterModelFieldOutputTemplate>;
+export const isT2IAdapterModelFieldInputInstance = (val: unknown): val is T2IAdapterModelFieldInputInstance =>
+  zT2IAdapterModelFieldInputInstance.safeParse(val).success;
+export const isT2IAdapterModelFieldInputTemplate = (val: unknown): val is T2IAdapterModelFieldInputTemplate =>
+  zT2IAdapterModelFieldInputTemplate.safeParse(val).success;
+// #endregion
+
+// #region SchedulerField
+export const zSchedulerFieldType = zFieldTypeBase.extend({
+  name: z.literal('SchedulerField'),
+});
+export const zSchedulerFieldValue = zSchedulerField.optional();
+export const zSchedulerFieldInputInstance = zFieldInputInstanceBase.extend({
+  type: zSchedulerFieldType,
+  value: zSchedulerFieldValue,
+});
+export const zSchedulerFieldOutputInstance = zFieldOutputInstanceBase.extend({
+  type: zSchedulerFieldType,
+});
+export const zSchedulerFieldInputTemplate = zFieldInputTemplateBase.extend({
+  type: zSchedulerFieldType,
+  default: zSchedulerFieldValue,
+});
+export const zSchedulerFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+  type: zSchedulerFieldType,
+});
+export type SchedulerFieldType = z.infer<typeof zSchedulerFieldType>;
+export type SchedulerFieldValue = z.infer<typeof zSchedulerFieldValue>;
+export type SchedulerFieldInputInstance = z.infer<typeof zSchedulerFieldInputInstance>;
+export type SchedulerFieldOutputInstance = z.infer<typeof zSchedulerFieldOutputInstance>;
+export type SchedulerFieldInputTemplate = z.infer<typeof zSchedulerFieldInputTemplate>;
+export type SchedulerFieldOutputTemplate = z.infer<typeof zSchedulerFieldOutputTemplate>;
+export const isSchedulerFieldInputInstance = (val: unknown): val is SchedulerFieldInputInstance =>
+  zSchedulerFieldInputInstance.safeParse(val).success;
+export const isSchedulerFieldInputTemplate = (val: unknown): val is SchedulerFieldInputTemplate =>
+  zSchedulerFieldInputTemplate.safeParse(val).success;
+// #endregion
+
+// #region StatelessField
+/**
+ * StatelessField is a catchall for stateless fields with no UI input components. They do not
+ * do not support "direct" input, instead only accepting connections from other fields.
+ *
+ * This field type serves as a "generic" field type.
+ *
+ * Examples include:
+ * - Fields like UNetField or LatentsField where we do not allow direct UI input
+ * - Reserved fields like IsIntermediate
+ * - Any other field we don't have full-on schemas for
+ */
+export const zStatelessFieldType = zFieldTypeBase.extend({
+  name: z.string().min(1), // stateless --> we accept the field's name as the type
+});
+export const zStatelessFieldValue = z.undefined().catch(undefined); // stateless --> no value, but making this z.never() introduces a lot of extra TS fanagling
+export const zStatelessFieldInputInstance = zFieldInputInstanceBase.extend({
+  type: zStatelessFieldType,
+  value: zStatelessFieldValue,
+});
+export const zStatelessFieldOutputInstance = zFieldOutputInstanceBase.extend({
+  type: zStatelessFieldType,
+});
+export const zStatelessFieldInputTemplate = zFieldInputTemplateBase.extend({
+  type: zStatelessFieldType,
+  default: zStatelessFieldValue,
+  input: z.literal('connection'), // stateless --> only accepts connection inputs
+});
+export const zStatelessFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+  type: zStatelessFieldType,
+});
+
+export type StatelessFieldType = z.infer<typeof zStatelessFieldType>;
+export type StatelessFieldValue = z.infer<typeof zStatelessFieldValue>;
+export type StatelessFieldInputInstance = z.infer<typeof zStatelessFieldInputInstance>;
+export type StatelessFieldOutputInstance = z.infer<typeof zStatelessFieldOutputInstance>;
+export type StatelessFieldInputTemplate = z.infer<typeof zStatelessFieldInputTemplate>;
+export type StatelessFieldOutputTemplate = z.infer<typeof zStatelessFieldOutputTemplate>;
+// #endregion
+
+/**
+ * Here we define the main field unions:
+ * - FieldType
+ * - FieldValue
+ * - FieldInputInstance
+ * - FieldOutputInstance
+ * - FieldInputTemplate
+ * - FieldOutputTemplate
+ *
+ * All stateful fields are unioned together, and then that union is unioned with StatelessField.
+ *
+ * This allows us to interact with stateful fields without needing to worry about "generic" handling
+ * for all other StatelessFields.
+ */
+
+// #region StatefulFieldType & FieldType
+export const zStatefulFieldType = z.union([
+  zIntegerFieldType,
+  zFloatFieldType,
+  zStringFieldType,
+  zBooleanFieldType,
+  zEnumFieldType,
+  zImageFieldType,
+  zBoardFieldType,
+  zMainModelFieldType,
+  zSDXLMainModelFieldType,
+  zSDXLRefinerModelFieldType,
+  zVAEModelFieldType,
+  zLoRAModelFieldType,
+  zControlNetModelFieldType,
+  zIPAdapterModelFieldType,
+  zT2IAdapterModelFieldType,
+  zColorFieldType,
+  zSchedulerFieldType,
+]);
+export type StatefulFieldType = z.infer<typeof zStatefulFieldType>;
+export const isStatefulFieldType = (val: unknown): val is StatefulFieldType =>
+  zStatefulFieldType.safeParse(val).success;
+
+export const zFieldType = z.union([zStatefulFieldType, zStatelessFieldType]);
+export type FieldType = z.infer<typeof zFieldType>;
+export const isFieldType = (val: unknown): val is FieldType => zFieldType.safeParse(val).success;
+// #endregion
+
+// #region StatefulFieldValue & FieldValue
+export const zStatefulFieldValue = z.union([
+  zIntegerFieldValue,
+  zFloatFieldValue,
+  zStringFieldValue,
+  zBooleanFieldValue,
+  zEnumFieldValue,
+  zImageFieldValue,
+  zBoardFieldValue,
+  zMainModelFieldValue,
+  zSDXLMainModelFieldValue,
+  zSDXLRefinerModelFieldValue,
+  zVAEModelFieldValue,
+  zLoRAModelFieldValue,
+  zControlNetModelFieldValue,
+  zIPAdapterModelFieldValue,
+  zT2IAdapterModelFieldValue,
+  zColorFieldValue,
+  zSchedulerFieldValue,
+]);
+export type StatefulFieldValue = z.infer<typeof zStatefulFieldValue>;
+export const isStatefulFieldValue = (val: unknown): val is StatefulFieldValue =>
+  zStatefulFieldValue.safeParse(val).success;
+
+export const zFieldValue = z.union([zStatefulFieldValue, zStatelessFieldValue]);
+export type FieldValue = z.infer<typeof zFieldValue>;
+export const isFieldValue = (val: unknown): val is FieldValue => zFieldValue.safeParse(val).success;
+// #endregion
+
+// #region StatefulFieldInputInstance & FieldInputInstance
+export const zStatefulFieldInputInstance = z.union([
+  zIntegerFieldInputInstance,
+  zFloatFieldInputInstance,
+  zStringFieldInputInstance,
+  zBooleanFieldInputInstance,
+  zEnumFieldInputInstance,
+  zImageFieldInputInstance,
+  zBoardFieldInputInstance,
+  zMainModelFieldInputInstance,
+  zSDXLMainModelFieldInputInstance,
+  zSDXLRefinerModelFieldInputInstance,
+  zVAEModelFieldInputInstance,
+  zLoRAModelFieldInputInstance,
+  zControlNetModelFieldInputInstance,
+  zIPAdapterModelFieldInputInstance,
+  zT2IAdapterModelFieldInputInstance,
+  zColorFieldInputInstance,
+  zSchedulerFieldInputInstance,
+]);
+export type StatefulFieldInputInstance = z.infer<typeof zStatefulFieldInputInstance>;
+export const isStatefulFieldInputInstance = (val: unknown): val is StatefulFieldInputInstance =>
+  zStatefulFieldInputInstance.safeParse(val).success;
+
+export const zFieldInputInstance = z.union([zStatefulFieldInputInstance, zStatelessFieldInputInstance]);
+export type FieldInputInstance = z.infer<typeof zFieldInputInstance>;
+export const isFieldInputInstance = (val: unknown): val is FieldInputInstance =>
+  zFieldInputInstance.safeParse(val).success;
+// #endregion
+
+// #region StatefulFieldOutputInstance & FieldOutputInstance
+export const zStatefulFieldOutputInstance = z.union([
+  zIntegerFieldOutputInstance,
+  zFloatFieldOutputInstance,
+  zStringFieldOutputInstance,
+  zBooleanFieldOutputInstance,
+  zEnumFieldOutputInstance,
+  zImageFieldOutputInstance,
+  zBoardFieldOutputInstance,
+  zMainModelFieldOutputInstance,
+  zSDXLMainModelFieldOutputInstance,
+  zSDXLRefinerModelFieldOutputInstance,
+  zVAEModelFieldOutputInstance,
+  zLoRAModelFieldOutputInstance,
+  zControlNetModelFieldOutputInstance,
+  zIPAdapterModelFieldOutputInstance,
+  zT2IAdapterModelFieldOutputInstance,
+  zColorFieldOutputInstance,
+  zSchedulerFieldOutputInstance,
+]);
+export type StatefulFieldOutputInstance = z.infer<typeof zStatefulFieldOutputInstance>;
+export const isStatefulFieldOutputInstance = (val: unknown): val is StatefulFieldOutputInstance =>
+  zStatefulFieldOutputInstance.safeParse(val).success;
+
+export const zFieldOutputInstance = z.union([zStatefulFieldOutputInstance, zStatelessFieldOutputInstance]);
+export type FieldOutputInstance = z.infer<typeof zFieldOutputInstance>;
+export const isFieldOutputInstance = (val: unknown): val is FieldOutputInstance =>
+  zFieldOutputInstance.safeParse(val).success;
+// #endregion
+
+// #region StatefulFieldInputTemplate & FieldInputTemplate
+export const zStatefulFieldInputTemplate = z.union([
+  zIntegerFieldInputTemplate,
+  zFloatFieldInputTemplate,
+  zStringFieldInputTemplate,
+  zBooleanFieldInputTemplate,
+  zEnumFieldInputTemplate,
+  zImageFieldInputTemplate,
+  zBoardFieldInputTemplate,
+  zMainModelFieldInputTemplate,
+  zSDXLMainModelFieldInputTemplate,
+  zSDXLRefinerModelFieldInputTemplate,
+  zVAEModelFieldInputTemplate,
+  zLoRAModelFieldInputTemplate,
+  zControlNetModelFieldInputTemplate,
+  zIPAdapterModelFieldInputTemplate,
+  zT2IAdapterModelFieldInputTemplate,
+  zColorFieldInputTemplate,
+  zSchedulerFieldInputTemplate,
+  zStatelessFieldInputTemplate,
+]);
+export type StatefulFieldInputTemplate = z.infer<typeof zFieldInputTemplate>;
+export const isStatefulFieldInputTemplate = (val: unknown): val is StatefulFieldInputTemplate =>
+  zStatefulFieldInputTemplate.safeParse(val).success;
+
+export const zFieldInputTemplate = z.union([zStatefulFieldInputTemplate, zStatelessFieldInputTemplate]);
+export type FieldInputTemplate = z.infer<typeof zFieldInputTemplate>;
+export const isFieldInputTemplate = (val: unknown): val is FieldInputTemplate =>
+  zFieldInputTemplate.safeParse(val).success;
+// #endregion
+
+// #region StatefulFieldOutputTemplate & FieldOutputTemplate
+export const zStatefulFieldOutputTemplate = z.union([
+  zIntegerFieldOutputTemplate,
+  zFloatFieldOutputTemplate,
+  zStringFieldOutputTemplate,
+  zBooleanFieldOutputTemplate,
+  zEnumFieldOutputTemplate,
+  zImageFieldOutputTemplate,
+  zBoardFieldOutputTemplate,
+  zMainModelFieldOutputTemplate,
+  zSDXLMainModelFieldOutputTemplate,
+  zSDXLRefinerModelFieldOutputTemplate,
+  zVAEModelFieldOutputTemplate,
+  zLoRAModelFieldOutputTemplate,
+  zControlNetModelFieldOutputTemplate,
+  zIPAdapterModelFieldOutputTemplate,
+  zT2IAdapterModelFieldOutputTemplate,
+  zColorFieldOutputTemplate,
+  zSchedulerFieldOutputTemplate,
+]);
+export type StatefulFieldOutputTemplate = z.infer<typeof zStatefulFieldOutputTemplate>;
+export const isStatefulFieldOutputTemplate = (val: unknown): val is StatefulFieldOutputTemplate =>
+  zStatefulFieldOutputTemplate.safeParse(val).success;
+
+export const zFieldOutputTemplate = z.union([zStatefulFieldOutputTemplate, zStatelessFieldOutputTemplate]);
+export type FieldOutputTemplate = z.infer<typeof zFieldOutputTemplate>;
+export const isFieldOutputTemplate = (val: unknown): val is FieldOutputTemplate =>
+  zFieldOutputTemplate.safeParse(val).success;
+// #endregion
diff --git a/invokeai/frontend/web/src/features/nodes/types/v2/invocation.ts b/invokeai/frontend/web/src/features/nodes/types/v2/invocation.ts
new file mode 100644
index 0000000000..86ec70fd9b
--- /dev/null
+++ b/invokeai/frontend/web/src/features/nodes/types/v2/invocation.ts
@@ -0,0 +1,93 @@
+import type { Edge, Node } from 'reactflow';
+import { z } from 'zod';
+
+import { zClassification, zProgressImage } from './common';
+import { zFieldInputInstance, zFieldInputTemplate, zFieldOutputInstance, zFieldOutputTemplate } from './field';
+import { zSemVer } from './semver';
+
+// #region InvocationTemplate
+export const zInvocationTemplate = z.object({
+  type: z.string(),
+  title: z.string(),
+  description: z.string(),
+  tags: z.array(z.string().min(1)),
+  inputs: z.record(zFieldInputTemplate),
+  outputs: z.record(zFieldOutputTemplate),
+  outputType: z.string().min(1),
+  version: zSemVer,
+  useCache: z.boolean(),
+  nodePack: z.string().min(1).nullish(),
+  classification: zClassification,
+});
+export type InvocationTemplate = z.infer<typeof zInvocationTemplate>;
+// #endregion
+
+// #region NodeData
+export const zInvocationNodeData = z.object({
+  id: z.string().trim().min(1),
+  type: z.string().trim().min(1),
+  label: z.string(),
+  isOpen: z.boolean(),
+  notes: z.string(),
+  isIntermediate: z.boolean(),
+  useCache: z.boolean(),
+  version: zSemVer,
+  nodePack: z.string().min(1).nullish(),
+  inputs: z.record(zFieldInputInstance),
+  outputs: z.record(zFieldOutputInstance),
+});
+
+export const zNotesNodeData = z.object({
+  id: z.string().trim().min(1),
+  type: z.literal('notes'),
+  label: z.string(),
+  isOpen: z.boolean(),
+  notes: z.string(),
+});
+export const zCurrentImageNodeData = z.object({
+  id: z.string().trim().min(1),
+  type: z.literal('current_image'),
+  label: z.string(),
+  isOpen: z.boolean(),
+});
+export const zAnyNodeData = z.union([zInvocationNodeData, zNotesNodeData, zCurrentImageNodeData]);
+
+export type NotesNodeData = z.infer<typeof zNotesNodeData>;
+export type InvocationNodeData = z.infer<typeof zInvocationNodeData>;
+export type CurrentImageNodeData = z.infer<typeof zCurrentImageNodeData>;
+export type AnyNodeData = z.infer<typeof zAnyNodeData>;
+
+export type InvocationNode = Node<InvocationNodeData, 'invocation'>;
+export type NotesNode = Node<NotesNodeData, 'notes'>;
+export type CurrentImageNode = Node<CurrentImageNodeData, 'current_image'>;
+export type AnyNode = Node<AnyNodeData>;
+
+export const isInvocationNode = (node?: AnyNode): node is InvocationNode => Boolean(node && node.type === 'invocation');
+export const isNotesNode = (node?: AnyNode): node is NotesNode => Boolean(node && node.type === 'notes');
+export const isCurrentImageNode = (node?: AnyNode): node is CurrentImageNode =>
+  Boolean(node && node.type === 'current_image');
+export const isInvocationNodeData = (node?: AnyNodeData): node is InvocationNodeData =>
+  Boolean(node && !['notes', 'current_image'].includes(node.type)); // node.type may be 'notes', 'current_image', or any invocation type
+// #endregion
+
+// #region NodeExecutionState
+export const zNodeStatus = z.enum(['PENDING', 'IN_PROGRESS', 'COMPLETED', 'FAILED']);
+export const zNodeExecutionState = z.object({
+  nodeId: z.string().trim().min(1),
+  status: zNodeStatus,
+  progress: z.number().nullable(),
+  progressImage: zProgressImage.nullable(),
+  error: z.string().nullable(),
+  outputs: z.array(z.any()),
+});
+export type NodeExecutionState = z.infer<typeof zNodeExecutionState>;
+export type NodeStatus = z.infer<typeof zNodeStatus>;
+// #endregion
+
+// #region Edges
+export const zInvocationNodeEdgeExtra = z.object({
+  type: z.union([z.literal('default'), z.literal('collapsed')]),
+});
+export type InvocationNodeEdgeExtra = z.infer<typeof zInvocationNodeEdgeExtra>;
+export type InvocationNodeEdge = Edge<InvocationNodeEdgeExtra>;
+// #endregion
diff --git a/invokeai/frontend/web/src/features/nodes/types/v2/metadata.ts b/invokeai/frontend/web/src/features/nodes/types/v2/metadata.ts
new file mode 100644
index 0000000000..0cc30499e3
--- /dev/null
+++ b/invokeai/frontend/web/src/features/nodes/types/v2/metadata.ts
@@ -0,0 +1,77 @@
+import { z } from 'zod';
+
+import {
+  zControlField,
+  zIPAdapterField,
+  zLoRAModelField,
+  zMainModelField,
+  zSDXLRefinerModelField,
+  zT2IAdapterField,
+  zVAEModelField,
+} from './common';
+
+// #region Metadata-optimized versions of schemas
+// TODO: It's possible that `deepPartial` will be deprecated:
+// - https://github.com/colinhacks/zod/issues/2106
+// - https://github.com/colinhacks/zod/issues/2854
+export const zLoRAMetadataItem = z.object({
+  lora: zLoRAModelField.deepPartial(),
+  weight: z.number(),
+});
+const zControlNetMetadataItem = zControlField.deepPartial();
+const zIPAdapterMetadataItem = zIPAdapterField.deepPartial();
+const zT2IAdapterMetadataItem = zT2IAdapterField.deepPartial();
+const zSDXLRefinerModelMetadataItem = zSDXLRefinerModelField.deepPartial();
+const zModelMetadataItem = zMainModelField.deepPartial();
+const zVAEModelMetadataItem = zVAEModelField.deepPartial();
+export type LoRAMetadataItem = z.infer<typeof zLoRAMetadataItem>;
+export type ControlNetMetadataItem = z.infer<typeof zControlNetMetadataItem>;
+export type IPAdapterMetadataItem = z.infer<typeof zIPAdapterMetadataItem>;
+export type T2IAdapterMetadataItem = z.infer<typeof zT2IAdapterMetadataItem>;
+export type SDXLRefinerModelMetadataItem = z.infer<typeof zSDXLRefinerModelMetadataItem>;
+export type ModelMetadataItem = z.infer<typeof zModelMetadataItem>;
+export type VAEModelMetadataItem = z.infer<typeof zVAEModelMetadataItem>;
+// #endregion
+
+// #region CoreMetadata
+export const zCoreMetadata = z
+  .object({
+    app_version: z.string().nullish().catch(null),
+    generation_mode: z.string().nullish().catch(null),
+    created_by: z.string().nullish().catch(null),
+    positive_prompt: z.string().nullish().catch(null),
+    negative_prompt: z.string().nullish().catch(null),
+    width: z.number().int().nullish().catch(null),
+    height: z.number().int().nullish().catch(null),
+    seed: z.number().int().nullish().catch(null),
+    rand_device: z.string().nullish().catch(null),
+    cfg_scale: z.number().nullish().catch(null),
+    cfg_rescale_multiplier: z.number().nullish().catch(null),
+    steps: z.number().int().nullish().catch(null),
+    scheduler: z.string().nullish().catch(null),
+    clip_skip: z.number().int().nullish().catch(null),
+    model: zModelMetadataItem.nullish().catch(null),
+    controlnets: z.array(zControlNetMetadataItem).nullish().catch(null),
+    ipAdapters: z.array(zIPAdapterMetadataItem).nullish().catch(null),
+    t2iAdapters: z.array(zT2IAdapterMetadataItem).nullish().catch(null),
+    loras: z.array(zLoRAMetadataItem).nullish().catch(null),
+    vae: zVAEModelMetadataItem.nullish().catch(null),
+    strength: z.number().nullish().catch(null),
+    hrf_enabled: z.boolean().nullish().catch(null),
+    hrf_strength: z.number().nullish().catch(null),
+    hrf_method: z.string().nullish().catch(null),
+    init_image: z.string().nullish().catch(null),
+    positive_style_prompt: z.string().nullish().catch(null),
+    negative_style_prompt: z.string().nullish().catch(null),
+    refiner_model: zSDXLRefinerModelMetadataItem.nullish().catch(null),
+    refiner_cfg_scale: z.number().nullish().catch(null),
+    refiner_steps: z.number().int().nullish().catch(null),
+    refiner_scheduler: z.string().nullish().catch(null),
+    refiner_positive_aesthetic_score: z.number().nullish().catch(null),
+    refiner_negative_aesthetic_score: z.number().nullish().catch(null),
+    refiner_start: z.number().nullish().catch(null),
+  })
+  .passthrough();
+export type CoreMetadata = z.infer<typeof zCoreMetadata>;
+
+// #endregion
diff --git a/invokeai/frontend/web/src/features/nodes/types/v2/openapi.ts b/invokeai/frontend/web/src/features/nodes/types/v2/openapi.ts
new file mode 100644
index 0000000000..83d774439a
--- /dev/null
+++ b/invokeai/frontend/web/src/features/nodes/types/v2/openapi.ts
@@ -0,0 +1,86 @@
+import type { OpenAPIV3_1 } from 'openapi-types';
+import type {
+  InputFieldJSONSchemaExtra,
+  InvocationJSONSchemaExtra,
+  OutputFieldJSONSchemaExtra,
+} from 'services/api/types';
+
+// Janky customization of OpenAPI Schema :/
+
+export type InvocationSchemaExtra = InvocationJSONSchemaExtra & {
+  output: OpenAPIV3_1.ReferenceObject; // the output of the invocation
+  title: string;
+  category?: string;
+  tags?: string[];
+  version: string;
+  properties: Omit<
+    NonNullable<OpenAPIV3_1.SchemaObject['properties']> & (InputFieldJSONSchemaExtra | OutputFieldJSONSchemaExtra),
+    'type'
+  > & {
+    type: Omit<OpenAPIV3_1.SchemaObject, 'default'> & {
+      default: string;
+    };
+    use_cache: Omit<OpenAPIV3_1.SchemaObject, 'default'> & {
+      default: boolean;
+    };
+  };
+};
+
+export type InvocationSchemaType = {
+  default: string; // the type of the invocation
+};
+
+export type InvocationBaseSchemaObject = Omit<OpenAPIV3_1.BaseSchemaObject, 'title' | 'type' | 'properties'> &
+  InvocationSchemaExtra;
+
+export type InvocationOutputSchemaObject = Omit<OpenAPIV3_1.SchemaObject, 'properties'> & {
+  properties: OpenAPIV3_1.SchemaObject['properties'] & {
+    type: Omit<OpenAPIV3_1.SchemaObject, 'default'> & {
+      default: string;
+    };
+  } & {
+    class: 'output';
+  };
+};
+
+export type InvocationFieldSchema = OpenAPIV3_1.SchemaObject & InputFieldJSONSchemaExtra;
+
+export type OpenAPIV3_1SchemaOrRef = OpenAPIV3_1.ReferenceObject | OpenAPIV3_1.SchemaObject;
+
+export interface ArraySchemaObject extends InvocationBaseSchemaObject {
+  type: OpenAPIV3_1.ArraySchemaObjectType;
+  items: OpenAPIV3_1.ReferenceObject | OpenAPIV3_1.SchemaObject;
+}
+export interface NonArraySchemaObject extends InvocationBaseSchemaObject {
+  type?: OpenAPIV3_1.NonArraySchemaObjectType;
+}
+
+export type InvocationSchemaObject = (ArraySchemaObject | NonArraySchemaObject) & { class: 'invocation' };
+
+export const isSchemaObject = (
+  obj: OpenAPIV3_1.ReferenceObject | OpenAPIV3_1.SchemaObject | undefined
+): obj is OpenAPIV3_1.SchemaObject => Boolean(obj && !('$ref' in obj));
+
+export const isArraySchemaObject = (
+  obj: OpenAPIV3_1.ReferenceObject | OpenAPIV3_1.SchemaObject | undefined
+): obj is OpenAPIV3_1.ArraySchemaObject => Boolean(obj && !('$ref' in obj) && obj.type === 'array');
+
+export const isNonArraySchemaObject = (
+  obj: OpenAPIV3_1.ReferenceObject | OpenAPIV3_1.SchemaObject | undefined
+): obj is OpenAPIV3_1.NonArraySchemaObject => Boolean(obj && !('$ref' in obj) && obj.type !== 'array');
+
+export const isRefObject = (
+  obj: OpenAPIV3_1.ReferenceObject | OpenAPIV3_1.SchemaObject | undefined
+): obj is OpenAPIV3_1.ReferenceObject => Boolean(obj && '$ref' in obj);
+
+export const isInvocationSchemaObject = (
+  obj: OpenAPIV3_1.ReferenceObject | OpenAPIV3_1.SchemaObject | InvocationSchemaObject
+): obj is InvocationSchemaObject => 'class' in obj && obj.class === 'invocation';
+
+export const isInvocationOutputSchemaObject = (
+  obj: OpenAPIV3_1.ReferenceObject | OpenAPIV3_1.SchemaObject | InvocationOutputSchemaObject
+): obj is InvocationOutputSchemaObject => 'class' in obj && obj.class === 'output';
+
+export const isInvocationFieldSchema = (
+  obj: OpenAPIV3_1.ReferenceObject | OpenAPIV3_1.SchemaObject
+): obj is InvocationFieldSchema => !('$ref' in obj);
diff --git a/invokeai/frontend/web/src/features/nodes/types/v2/semver.ts b/invokeai/frontend/web/src/features/nodes/types/v2/semver.ts
new file mode 100644
index 0000000000..3ba330eac4
--- /dev/null
+++ b/invokeai/frontend/web/src/features/nodes/types/v2/semver.ts
@@ -0,0 +1,21 @@
+import { z } from 'zod';
+
+// Schemas and types for working with semver
+
+const zVersionInt = z.coerce.number().int().min(0);
+
+export const zSemVer = z.string().refine((val) => {
+  const [major, minor, patch] = val.split('.');
+  return (
+    zVersionInt.safeParse(major).success && zVersionInt.safeParse(minor).success && zVersionInt.safeParse(patch).success
+  );
+});
+
+export const zParsedSemver = zSemVer.transform((val) => {
+  const [major, minor, patch] = val.split('.');
+  return {
+    major: Number(major),
+    minor: Number(minor),
+    patch: Number(patch),
+  };
+});
diff --git a/invokeai/frontend/web/src/features/nodes/types/v2/workflow.ts b/invokeai/frontend/web/src/features/nodes/types/v2/workflow.ts
new file mode 100644
index 0000000000..723a354013
--- /dev/null
+++ b/invokeai/frontend/web/src/features/nodes/types/v2/workflow.ts
@@ -0,0 +1,89 @@
+import { z } from 'zod';
+
+import { zFieldIdentifier } from './field';
+import { zInvocationNodeData, zNotesNodeData } from './invocation';
+
+// #region Workflow misc
+export const zXYPosition = z
+  .object({
+    x: z.number(),
+    y: z.number(),
+  })
+  .default({ x: 0, y: 0 });
+export type XYPosition = z.infer<typeof zXYPosition>;
+
+export const zDimension = z.number().gt(0).nullish();
+export type Dimension = z.infer<typeof zDimension>;
+
+export const zWorkflowCategory = z.enum(['user', 'default', 'project']);
+export type WorkflowCategory = z.infer<typeof zWorkflowCategory>;
+// #endregion
+
+// #region Workflow Nodes
+export const zWorkflowInvocationNode = z.object({
+  id: z.string().trim().min(1),
+  type: z.literal('invocation'),
+  data: zInvocationNodeData,
+  width: zDimension,
+  height: zDimension,
+  position: zXYPosition,
+});
+export const zWorkflowNotesNode = z.object({
+  id: z.string().trim().min(1),
+  type: z.literal('notes'),
+  data: zNotesNodeData,
+  width: zDimension,
+  height: zDimension,
+  position: zXYPosition,
+});
+export const zWorkflowNode = z.union([zWorkflowInvocationNode, zWorkflowNotesNode]);
+
+export type WorkflowInvocationNode = z.infer<typeof zWorkflowInvocationNode>;
+export type WorkflowNotesNode = z.infer<typeof zWorkflowNotesNode>;
+export type WorkflowNode = z.infer<typeof zWorkflowNode>;
+
+export const isWorkflowInvocationNode = (val: unknown): val is WorkflowInvocationNode =>
+  zWorkflowInvocationNode.safeParse(val).success;
+// #endregion
+
+// #region Workflow Edges
+export const zWorkflowEdgeBase = z.object({
+  id: z.string().trim().min(1),
+  source: z.string().trim().min(1),
+  target: z.string().trim().min(1),
+});
+export const zWorkflowEdgeDefault = zWorkflowEdgeBase.extend({
+  type: z.literal('default'),
+  sourceHandle: z.string().trim().min(1),
+  targetHandle: z.string().trim().min(1),
+});
+export const zWorkflowEdgeCollapsed = zWorkflowEdgeBase.extend({
+  type: z.literal('collapsed'),
+});
+export const zWorkflowEdge = z.union([zWorkflowEdgeDefault, zWorkflowEdgeCollapsed]);
+
+export type WorkflowEdgeDefault = z.infer<typeof zWorkflowEdgeDefault>;
+export type WorkflowEdgeCollapsed = z.infer<typeof zWorkflowEdgeCollapsed>;
+export type WorkflowEdge = z.infer<typeof zWorkflowEdge>;
+// #endregion
+
+// #region Workflow
+export const zWorkflowV2 = z.object({
+  id: z.string().min(1).optional(),
+  name: z.string(),
+  author: z.string(),
+  description: z.string(),
+  version: z.string(),
+  contact: z.string(),
+  tags: z.string(),
+  notes: z.string(),
+  nodes: z.array(zWorkflowNode),
+  edges: z.array(zWorkflowEdge),
+  exposedFields: z.array(zFieldIdentifier),
+  meta: z.object({
+    category: zWorkflowCategory.default('user'),
+    version: z.literal('2.0.0'),
+  }),
+});
+export type WorkflowV2 = z.infer<typeof zWorkflowV2>;
+// #endregion
diff --git a/invokeai/frontend/web/src/features/nodes/types/workflow.ts b/invokeai/frontend/web/src/features/nodes/types/workflow.ts
index 723a354013..adad7c0f21 100644
--- a/invokeai/frontend/web/src/features/nodes/types/workflow.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/workflow.ts
@@ -24,16 +24,12 @@ export const zWorkflowInvocationNode = z.object({
   id: z.string().trim().min(1),
   type: z.literal('invocation'),
   data: zInvocationNodeData,
-  width: zDimension,
-  height: zDimension,
   position: zXYPosition,
 });
 export const zWorkflowNotesNode = z.object({
   id: z.string().trim().min(1),
   type: z.literal('notes'),
   data: zNotesNodeData,
-  width: zDimension,
-  height: zDimension,
   position: zXYPosition,
 });
 export const zWorkflowNode = z.union([zWorkflowInvocationNode, zWorkflowNotesNode]);
@@ -68,7 +64,7 @@ export type WorkflowEdge = z.infer<typeof zWorkflowEdge>;
 // #endregion
 
 // #region Workflow
-export const zWorkflowV2 = z.object({
+export const zWorkflowV3 = z.object({
   id: z.string().min(1).optional(),
   name: z.string(),
   author: z.string(),
@@ -82,8 +78,8 @@ export const zWorkflowV2 = z.object({
   exposedFields: z.array(zFieldIdentifier),
   meta: z.object({
     category: zWorkflowCategory.default('user'),
-    version: z.literal('2.0.0'),
+    version: z.literal('3.0.0'),
   }),
 });
-export type WorkflowV2 = z.infer<typeof zWorkflowV2>;
+export type WorkflowV3 = z.infer<typeof zWorkflowV3>;
 // #endregion
diff --git a/invokeai/frontend/web/src/features/nodes/util/node/buildInvocationNode.ts b/invokeai/frontend/web/src/features/nodes/util/node/buildInvocationNode.ts
index ea40bd4660..af19aa86ea 100644
--- a/invokeai/frontend/web/src/features/nodes/util/node/buildInvocationNode.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/node/buildInvocationNode.ts
@@ -1,5 +1,5 @@
 import { SHARED_NODE_PROPERTIES } from 'features/nodes/types/constants';
-import type { FieldInputInstance, FieldOutputInstance } from 'features/nodes/types/field';
+import type { FieldInputInstance } from 'features/nodes/types/field';
 import type { InvocationNode, InvocationTemplate } from 'features/nodes/types/invocation';
 import { buildFieldInputInstance } from 'features/nodes/util/schema/buildFieldInputInstance';
 import { reduce } from 'lodash-es';
@@ -24,25 +24,6 @@ export const buildInvocationNode = (position: XYPosition, template: InvocationTe
     {} as Record<string, FieldInputInstance>
   );
 
-  const outputs = reduce(
-    template.outputs,
-    (outputsAccumulator, outputTemplate, outputName) => {
-      const fieldId = uuidv4();
-
-      const outputFieldValue: FieldOutputInstance = {
-        id: fieldId,
-        name: outputName,
-        type: outputTemplate.type,
-        fieldKind: 'output',
-      };
-
-      outputsAccumulator[outputName] = outputFieldValue;
-
-      return outputsAccumulator;
-    },
-    {} as Record<string, FieldOutputInstance>
-  );
-
   const node: InvocationNode = {
     ...SHARED_NODE_PROPERTIES,
     id: nodeId,
@@ -58,7 +39,6 @@ export const buildInvocationNode = (position: XYPosition, template: InvocationTe
       isIntermediate: type === 'save_image' ? false : true,
       useCache: template.useCache,
       inputs,
-      outputs,
     },
   };
 
diff --git a/invokeai/frontend/web/src/features/nodes/util/node/nodeUpdate.ts b/invokeai/frontend/web/src/features/nodes/util/node/nodeUpdate.ts
index f195c49d30..5ece51d0f3 100644
--- a/invokeai/frontend/web/src/features/nodes/util/node/nodeUpdate.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/node/nodeUpdate.ts
@@ -54,6 +54,5 @@ export const updateNode = (node: InvocationNode, template: InvocationTemplate):
 
   // Remove any fields that are not in the template
   clone.data.inputs = pick(clone.data.inputs, keys(defaults.data.inputs));
-  clone.data.outputs = pick(clone.data.outputs, keys(defaults.data.outputs));
   return clone;
 };
diff --git a/invokeai/frontend/web/src/features/nodes/util/schema/buildFieldInputInstance.ts b/invokeai/frontend/web/src/features/nodes/util/schema/buildFieldInputInstance.ts
index dd3cf0ad7b..f8097566c9 100644
--- a/invokeai/frontend/web/src/features/nodes/util/schema/buildFieldInputInstance.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/schema/buildFieldInputInstance.ts
@@ -23,11 +23,8 @@ const FIELD_VALUE_FALLBACK_MAP: Record<StatefulFieldType['name'], FieldValue> =
 
 export const buildFieldInputInstance = (id: string, template: FieldInputTemplate): FieldInputInstance => {
   const fieldInstance: FieldInputInstance = {
-    id,
     name: template.name,
-    type: template.type,
     label: '',
-    fieldKind: 'input' as const,
     value: template.default ?? get(FIELD_VALUE_FALLBACK_MAP, template.type.name),
   };
 
diff --git a/invokeai/frontend/web/src/features/nodes/util/workflow/buildWorkflow.ts b/invokeai/frontend/web/src/features/nodes/util/workflow/buildWorkflow.ts
index 70775a9882..720da16464 100644
--- a/invokeai/frontend/web/src/features/nodes/util/workflow/buildWorkflow.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/workflow/buildWorkflow.ts
@@ -2,8 +2,8 @@ import { logger } from 'app/logging/logger';
 import { parseify } from 'common/util/serialize';
 import type { NodesState, WorkflowsState } from 'features/nodes/store/types';
 import { isInvocationNode, isNotesNode } from 'features/nodes/types/invocation';
-import type { WorkflowV2 } from 'features/nodes/types/workflow';
-import { zWorkflowV2 } from 'features/nodes/types/workflow';
+import type { WorkflowV3 } from 'features/nodes/types/workflow';
+import { zWorkflowV3 } from 'features/nodes/types/workflow';
 import i18n from 'i18n';
 import { cloneDeep, pick } from 'lodash-es';
 import { fromZodError } from 'zod-validation-error';
@@ -25,14 +25,14 @@ const workflowKeys = [
   'exposedFields',
   'meta',
   'id',
-] satisfies (keyof WorkflowV2)[];
+] satisfies (keyof WorkflowV3)[];
 
-export type BuildWorkflowFunction = (arg: BuildWorkflowArg) => WorkflowV2;
+export type BuildWorkflowFunction = (arg: BuildWorkflowArg) => WorkflowV3;
 
-export const buildWorkflowFast: BuildWorkflowFunction = ({ nodes, edges, workflow }: BuildWorkflowArg): WorkflowV2 => {
+export const buildWorkflowFast: BuildWorkflowFunction = ({ nodes, edges, workflow }: BuildWorkflowArg): WorkflowV3 => {
   const clonedWorkflow = pick(cloneDeep(workflow), workflowKeys);
 
-  const newWorkflow: WorkflowV2 = {
+  const newWorkflow: WorkflowV3 = {
     ...clonedWorkflow,
     nodes: [],
     edges: [],
@@ -45,8 +45,6 @@ export const buildWorkflowFast: BuildWorkflowFunction = ({ nodes, edges, workflo
         type: node.type,
         data: cloneDeep(node.data),
         position: { ...node.position },
-        width: node.width,
-        height: node.height,
       });
     } else if (isNotesNode(node) && node.type) {
       newWorkflow.nodes.push({
@@ -54,8 +52,6 @@ export const buildWorkflowFast: BuildWorkflowFunction = ({ nodes, edges, workflo
         type: node.type,
         data: cloneDeep(node.data),
         position: { ...node.position },
-        width: node.width,
-        height: node.height,
       });
     }
   });
@@ -83,12 +79,12 @@ export const buildWorkflowFast: BuildWorkflowFunction = ({ nodes, edges, workflo
   return newWorkflow;
 };
 
-export const buildWorkflowWithValidation = ({ nodes, edges, workflow }: BuildWorkflowArg): WorkflowV2 | null => {
+export const buildWorkflowWithValidation = ({ nodes, edges, workflow }: BuildWorkflowArg): WorkflowV3 | null => {
   // builds what really, really should be a valid workflow
   const workflowToValidate = buildWorkflowFast({ nodes, edges, workflow });
 
   // but bc we are storing this in the DB, let's be extra sure
-  const result = zWorkflowV2.safeParse(workflowToValidate);
+  const result = zWorkflowV3.safeParse(workflowToValidate);
 
   if (!result.success) {
     const { message } = fromZodError(result.error, {
diff --git a/invokeai/frontend/web/src/features/nodes/util/workflow/migrations.ts b/invokeai/frontend/web/src/features/nodes/util/workflow/migrations.ts
index a2677f3d17..a023c96ba9 100644
--- a/invokeai/frontend/web/src/features/nodes/util/workflow/migrations.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/workflow/migrations.ts
@@ -6,8 +6,10 @@ import { zSemVer } from 'features/nodes/types/semver';
 import { FIELD_TYPE_V1_TO_FIELD_TYPE_V2_MAPPING } from 'features/nodes/types/v1/fieldTypeMap';
 import type { WorkflowV1 } from 'features/nodes/types/v1/workflowV1';
 import { zWorkflowV1 } from 'features/nodes/types/v1/workflowV1';
-import type { WorkflowV2 } from 'features/nodes/types/workflow';
-import { zWorkflowV2 } from 'features/nodes/types/workflow';
+import type { WorkflowV2 } from 'features/nodes/types/v2/workflow';
+import { zWorkflowV2 } from 'features/nodes/types/v2/workflow';
+import type { WorkflowV3 } from 'features/nodes/types/workflow';
+import { zWorkflowV3 } from 'features/nodes/types/workflow';
 import { t } from 'i18next';
 import { forEach } from 'lodash-es';
 import { z } from 'zod';
@@ -30,7 +32,7 @@ const zWorkflowMetaVersion = z.object({
  * - Workflow schema version bumped to 2.0.0
  */
 const migrateV1toV2 = (workflowToMigrate: WorkflowV1): WorkflowV2 => {
-  const invocationTemplates = $store.get()?.getState().nodeTemplates.templates;
+  const invocationTemplates = $store.get()?.getState().nodes.templates;
 
   if (!invocationTemplates) {
     throw new Error(t('app.storeNotInitialized'));
@@ -70,26 +72,34 @@ const migrateV1toV2 = (workflowToMigrate: WorkflowV1): WorkflowV2 => {
   return zWorkflowV2.parse(workflowToMigrate);
 };
 
+const migrateV2toV3 = (workflowToMigrate: WorkflowV2): WorkflowV3 => {
+  // Bump version
+  (workflowToMigrate as unknown as WorkflowV3).meta.version = '3.0.0';
+  // Parsing strips out any extra properties not in the latest version
+  return zWorkflowV3.parse(workflowToMigrate);
+};
+
 /**
  * Parses a workflow and migrates it to the latest version if necessary.
  */
-export const parseAndMigrateWorkflow = (data: unknown): WorkflowV2 => {
+export const parseAndMigrateWorkflow = (data: unknown): WorkflowV3 => {
   const workflowVersionResult = zWorkflowMetaVersion.safeParse(data);
 
   if (!workflowVersionResult.success) {
     throw new WorkflowVersionError(t('nodes.unableToGetWorkflowVersion'));
   }
 
-  const { version } = workflowVersionResult.data.meta;
+  let workflow = data as WorkflowV1 | WorkflowV2 | WorkflowV3;
 
-  if (version === '1.0.0') {
-    const v1 = zWorkflowV1.parse(data);
-    return migrateV1toV2(v1);
+  if (workflow.meta.version === '1.0.0') {
+    const v1 = zWorkflowV1.parse(workflow);
+    workflow = migrateV1toV2(v1);
   }
 
-  if (version === '2.0.0') {
-    return zWorkflowV2.parse(data);
+  if (workflow.meta.version === '2.0.0') {
+    const v2 = zWorkflowV2.parse(workflow);
+    workflow = migrateV2toV3(v2);
   }
 
-  throw new WorkflowVersionError(t('nodes.unrecognizedWorkflowVersion', { version }));
+  return workflow as WorkflowV3;
 };
diff --git a/invokeai/frontend/web/src/features/nodes/util/workflow/validateWorkflow.ts b/invokeai/frontend/web/src/features/nodes/util/workflow/validateWorkflow.ts
index 848d2aee77..5096e588b0 100644
--- a/invokeai/frontend/web/src/features/nodes/util/workflow/validateWorkflow.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/workflow/validateWorkflow.ts
@@ -1,6 +1,6 @@
 import { parseify } from 'common/util/serialize';
 import type { InvocationTemplate } from 'features/nodes/types/invocation';
-import type { WorkflowV2 } from 'features/nodes/types/workflow';
+import type { WorkflowV3 } from 'features/nodes/types/workflow';
 import { isWorkflowInvocationNode } from 'features/nodes/types/workflow';
 import { getNeedsUpdate } from 'features/nodes/util/node/nodeUpdate';
 import { t } from 'i18next';
@@ -16,7 +16,7 @@ type WorkflowWarning = {
 };
 
 type ValidateWorkflowResult = {
-  workflow: WorkflowV2;
+  workflow: WorkflowV3;
   warnings: WorkflowWarning[];
 };
 
diff --git a/invokeai/frontend/web/src/features/workflowLibrary/hooks/useSaveWorkflow.ts b/invokeai/frontend/web/src/features/workflowLibrary/hooks/useSaveWorkflow.ts
index 5d484b6897..7b49d70213 100644
--- a/invokeai/frontend/web/src/features/workflowLibrary/hooks/useSaveWorkflow.ts
+++ b/invokeai/frontend/web/src/features/workflowLibrary/hooks/useSaveWorkflow.ts
@@ -3,7 +3,7 @@ import { useToast } from '@invoke-ai/ui-library';
 import { useAppDispatch } from 'app/store/storeHooks';
 import { $builtWorkflow } from 'features/nodes/hooks/useWorkflowWatcher';
 import { workflowIDChanged, workflowSaved } from 'features/nodes/store/workflowSlice';
-import type { WorkflowV2 } from 'features/nodes/types/workflow';
+import type { WorkflowV3 } from 'features/nodes/types/workflow';
 import { workflowUpdated } from 'features/workflowLibrary/store/actions';
 import { useCallback, useRef } from 'react';
 import { useTranslation } from 'react-i18next';
@@ -18,7 +18,7 @@ type UseSaveLibraryWorkflowReturn = {
 
 type UseSaveLibraryWorkflow = () => UseSaveLibraryWorkflowReturn;
 
-export const isWorkflowWithID = (workflow: WorkflowV2): workflow is O.Required<WorkflowV2, 'id'> =>
+export const isWorkflowWithID = (workflow: WorkflowV3): workflow is O.Required<WorkflowV3, 'id'> =>
   Boolean(workflow.id);
 
 export const useSaveLibraryWorkflow: UseSaveLibraryWorkflow = () => {

From fe27af461a999ad9de51fcede354a2f6d8e431f3 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 13 Feb 2024 22:51:44 +1100
Subject: [PATCH 107/411] feat(ui): add vitest

- Add vitest.
- Consolidate vite configs into single file (easier to config everything based on env for testing)
---
 invokeai/frontend/web/config/common.mts       |  12 -
 .../frontend/web/config/vite.app.config.mts   |  33 ---
 .../web/config/vite.package.config.mts        |  46 ----
 invokeai/frontend/web/package.json            |   7 +-
 invokeai/frontend/web/pnpm-lock.yaml          | 222 +++++++++++++++++-
 invokeai/frontend/web/vite.config.mts         |  88 ++++++-
 6 files changed, 306 insertions(+), 102 deletions(-)
 delete mode 100644 invokeai/frontend/web/config/common.mts
 delete mode 100644 invokeai/frontend/web/config/vite.app.config.mts
 delete mode 100644 invokeai/frontend/web/config/vite.package.config.mts

diff --git a/invokeai/frontend/web/config/common.mts b/invokeai/frontend/web/config/common.mts
deleted file mode 100644
index fd559cabd1..0000000000
--- a/invokeai/frontend/web/config/common.mts
+++ /dev/null
@@ -1,12 +0,0 @@
-import react from '@vitejs/plugin-react-swc';
-import { visualizer } from 'rollup-plugin-visualizer';
-import type { PluginOption, UserConfig } from 'vite';
-import eslint from 'vite-plugin-eslint';
-import tsconfigPaths from 'vite-tsconfig-paths';
-
-export const commonPlugins: UserConfig['plugins'] = [
-  react(),
-  eslint(),
-  tsconfigPaths(),
-  visualizer() as unknown as PluginOption,
-];
diff --git a/invokeai/frontend/web/config/vite.app.config.mts b/invokeai/frontend/web/config/vite.app.config.mts
deleted file mode 100644
index 9683ed26a4..0000000000
--- a/invokeai/frontend/web/config/vite.app.config.mts
+++ /dev/null
@@ -1,33 +0,0 @@
-import type { UserConfig } from 'vite';
-
-import { commonPlugins } from './common.mjs';
-
-export const appConfig: UserConfig = {
-  base: './',
-  plugins: [...commonPlugins],
-  build: {
-    chunkSizeWarningLimit: 1500,
-  },
-  server: {
-    // Proxy HTTP requests to the flask server
-    proxy: {
-      // Proxy socket.io to the nodes socketio server
-      '/ws/socket.io': {
-        target: 'ws://127.0.0.1:9090',
-        ws: true,
-      },
-      // Proxy openapi schema definiton
-      '/openapi.json': {
-        target: 'http://127.0.0.1:9090/openapi.json',
-        rewrite: (path) => path.replace(/^\/openapi.json/, ''),
-        changeOrigin: true,
-      },
-      // proxy nodes api
-      '/api/v1': {
-        target: 'http://127.0.0.1:9090/api/v1',
-        rewrite: (path) => path.replace(/^\/api\/v1/, ''),
-        changeOrigin: true,
-      },
-    },
-  },
-};
diff --git a/invokeai/frontend/web/config/vite.package.config.mts b/invokeai/frontend/web/config/vite.package.config.mts
deleted file mode 100644
index 3c05d52e00..0000000000
--- a/invokeai/frontend/web/config/vite.package.config.mts
+++ /dev/null
@@ -1,46 +0,0 @@
-import path from 'path';
-import type { UserConfig } from 'vite';
-import cssInjectedByJsPlugin from 'vite-plugin-css-injected-by-js';
-import dts from 'vite-plugin-dts';
-
-import { commonPlugins } from './common.mjs';
-
-export const packageConfig: UserConfig = {
-  base: './',
-  plugins: [
-    ...commonPlugins,
-    dts({
-      insertTypesEntry: true,
-    }),
-    cssInjectedByJsPlugin(),
-  ],
-  build: {
-    cssCodeSplit: true,
-    lib: {
-      entry: path.resolve(__dirname, '../src/index.ts'),
-      name: 'InvokeAIUI',
-      fileName: (format) => `invoke-ai-ui.${format}.js`,
-    },
-    rollupOptions: {
-      external: ['react', 'react-dom', '@emotion/react', '@chakra-ui/react', '@invoke-ai/ui-library'],
-      output: {
-        globals: {
-          react: 'React',
-          'react-dom': 'ReactDOM',
-          '@emotion/react': 'EmotionReact',
-          '@invoke-ai/ui-library': 'UiLibrary',
-        },
-      },
-    },
-  },
-  resolve: {
-    alias: {
-      app: path.resolve(__dirname, '../src/app'),
-      assets: path.resolve(__dirname, '../src/assets'),
-      common: path.resolve(__dirname, '../src/common'),
-      features: path.resolve(__dirname, '../src/features'),
-      services: path.resolve(__dirname, '../src/services'),
-      theme: path.resolve(__dirname, '../src/theme'),
-    },
-  },
-};
diff --git a/invokeai/frontend/web/package.json b/invokeai/frontend/web/package.json
index cd95183c7a..b2838e538c 100644
--- a/invokeai/frontend/web/package.json
+++ b/invokeai/frontend/web/package.json
@@ -33,7 +33,9 @@
     "preinstall": "npx only-allow pnpm",
     "storybook": "storybook dev -p 6006",
     "build-storybook": "storybook build",
-    "unimported": "npx unimported"
+    "unimported": "npx unimported",
+    "test": "vitest",
+    "test:no-watch": "vitest --no-watch"
   },
   "madge": {
     "excludeRegExp": [
@@ -157,7 +159,8 @@
     "vite-plugin-css-injected-by-js": "^3.3.1",
     "vite-plugin-dts": "^3.7.1",
     "vite-plugin-eslint": "^1.8.1",
-    "vite-tsconfig-paths": "^4.3.1"
+    "vite-tsconfig-paths": "^4.3.1",
+    "vitest": "^1.2.2"
   },
   "pnpm": {
     "patchedDependencies": {
diff --git a/invokeai/frontend/web/pnpm-lock.yaml b/invokeai/frontend/web/pnpm-lock.yaml
index 1d9083d1b4..f3bf68cf1d 100644
--- a/invokeai/frontend/web/pnpm-lock.yaml
+++ b/invokeai/frontend/web/pnpm-lock.yaml
@@ -215,7 +215,7 @@ devDependencies:
     version: 7.6.10(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)(vite@5.0.12)
   '@storybook/test':
     specifier: ^7.6.10
-    version: 7.6.10
+    version: 7.6.10(vitest@1.2.2)
   '@storybook/theming':
     specifier: ^7.6.10
     version: 7.6.10(react-dom@18.2.0)(react@18.2.0)
@@ -318,6 +318,9 @@ devDependencies:
   vite-tsconfig-paths:
     specifier: ^4.3.1
     version: 4.3.1(typescript@5.3.3)(vite@5.0.12)
+  vitest:
+    specifier: ^1.2.2
+    version: 1.2.2(@types/node@20.11.5)
 
 packages:
 
@@ -5464,7 +5467,7 @@ packages:
       - supports-color
     dev: true
 
-  /@storybook/test@7.6.10:
+  /@storybook/test@7.6.10(vitest@1.2.2):
     resolution: {integrity: sha512-dn/T+HcWOBlVh3c74BHurp++BaqBoQgNbSIaXlYDpJoZ+DzNIoEQVsWFYm5gCbtKK27iFd4n52RiQI3f6Vblqw==}
     dependencies:
       '@storybook/client-logger': 7.6.10
@@ -5472,7 +5475,7 @@ packages:
       '@storybook/instrumenter': 7.6.10
       '@storybook/preview-api': 7.6.10
       '@testing-library/dom': 9.3.4
-      '@testing-library/jest-dom': 6.2.0
+      '@testing-library/jest-dom': 6.2.0(vitest@1.2.2)
       '@testing-library/user-event': 14.3.0(@testing-library/dom@9.3.4)
       '@types/chai': 4.3.11
       '@vitest/expect': 0.34.7
@@ -5652,7 +5655,7 @@ packages:
       pretty-format: 27.5.1
     dev: true
 
-  /@testing-library/jest-dom@6.2.0:
+  /@testing-library/jest-dom@6.2.0(vitest@1.2.2):
     resolution: {integrity: sha512-+BVQlJ9cmEn5RDMUS8c2+TU6giLvzaHZ8sU/x0Jj7fk+6/46wPdwlgOPcpxS17CjcanBi/3VmGMqVr2rmbUmNw==}
     engines: {node: '>=14', npm: '>=6', yarn: '>=1'}
     peerDependencies:
@@ -5678,6 +5681,7 @@ packages:
       dom-accessibility-api: 0.6.3
       lodash: 4.17.21
       redent: 3.0.0
+      vitest: 1.2.2(@types/node@20.11.5)
     dev: true
 
   /@testing-library/user-event@14.3.0(@testing-library/dom@9.3.4):
@@ -6490,12 +6494,42 @@ packages:
       chai: 4.4.1
     dev: true
 
+  /@vitest/expect@1.2.2:
+    resolution: {integrity: sha512-3jpcdPAD7LwHUUiT2pZTj2U82I2Tcgg2oVPvKxhn6mDI2On6tfvPQTjAI4628GUGDZrCm4Zna9iQHm5cEexOAg==}
+    dependencies:
+      '@vitest/spy': 1.2.2
+      '@vitest/utils': 1.2.2
+      chai: 4.4.1
+    dev: true
+
+  /@vitest/runner@1.2.2:
+    resolution: {integrity: sha512-JctG7QZ4LSDXr5CsUweFgcpEvrcxOV1Gft7uHrvkQ+fsAVylmWQvnaAr/HDp3LAH1fztGMQZugIheTWjaGzYIg==}
+    dependencies:
+      '@vitest/utils': 1.2.2
+      p-limit: 5.0.0
+      pathe: 1.1.2
+    dev: true
+
+  /@vitest/snapshot@1.2.2:
+    resolution: {integrity: sha512-SmGY4saEw1+bwE1th6S/cZmPxz/Q4JWsl7LvbQIky2tKE35US4gd0Mjzqfr84/4OD0tikGWaWdMja/nWL5NIPA==}
+    dependencies:
+      magic-string: 0.30.5
+      pathe: 1.1.2
+      pretty-format: 29.7.0
+    dev: true
+
   /@vitest/spy@0.34.7:
     resolution: {integrity: sha512-NMMSzOY2d8L0mcOt4XcliDOS1ISyGlAXuQtERWVOoVHnKwmG+kKhinAiGw3dTtMQWybfa89FG8Ucg9tiC/FhTQ==}
     dependencies:
       tinyspy: 2.2.0
     dev: true
 
+  /@vitest/spy@1.2.2:
+    resolution: {integrity: sha512-k9Gcahssw8d7X3pSLq3e3XEu/0L78mUkCjivUqCQeXJm9clfXR/Td8+AP+VC1O6fKPIDLcHDTAmBOINVuv6+7g==}
+    dependencies:
+      tinyspy: 2.2.0
+    dev: true
+
   /@vitest/utils@0.34.7:
     resolution: {integrity: sha512-ziAavQLpCYS9sLOorGrFFKmy2gnfiNU0ZJ15TsMz/K92NAPS/rp9K4z6AJQQk5Y8adCy4Iwpxy7pQumQ/psnRg==}
     dependencies:
@@ -6504,6 +6538,15 @@ packages:
       pretty-format: 29.7.0
     dev: true
 
+  /@vitest/utils@1.2.2:
+    resolution: {integrity: sha512-WKITBHLsBHlpjnDQahr+XK6RE7MiAsgrIkr0pGhQ9ygoxBfUeG0lUG5iLlzqjmKSlBv3+j5EGsriBzh+C3Tq9g==}
+    dependencies:
+      diff-sequences: 29.6.3
+      estree-walker: 3.0.3
+      loupe: 2.3.7
+      pretty-format: 29.7.0
+    dev: true
+
   /@volar/language-core@1.11.1:
     resolution: {integrity: sha512-dOcNn3i9GgZAcJt43wuaEykSluAuOkQgzni1cuxLxTV0nJKanQztp7FxyswdRILaKH+P2XZMPRp2S4MV/pElCw==}
     dependencies:
@@ -7184,6 +7227,11 @@ packages:
     engines: {node: '>=0.4.0'}
     dev: true
 
+  /acorn-walk@8.3.2:
+    resolution: {integrity: sha512-cjkyv4OtNCIeqhHrfS81QWXoCBPExR/J62oyEqepVw8WaQeSqpW2uhuLPh1m9eWhDuOo/jUXVTlifvesOWp/4A==}
+    engines: {node: '>=0.4.0'}
+    dev: true
+
   /acorn@7.4.1:
     resolution: {integrity: sha512-nQyp0o1/mNdbTO1PO6kHkwSrmgZ0MT/jCCpNiwbUjGoRN4dlBhqJtoQuCnEOKzgTVwg0ZWiCoQy6SxMebQVh8A==}
     engines: {node: '>=0.4.0'}
@@ -7661,6 +7709,11 @@ packages:
     engines: {node: '>= 0.8'}
     dev: true
 
+  /cac@6.7.14:
+    resolution: {integrity: sha512-b6Ilus+c3RrdDk+JhLKUAQfzzgLEPy6wcXqS7f/xe1EETvsDP6GORG7SFuOs6cID5YkqchW/LXZbX5bc8j7ZcQ==}
+    engines: {node: '>=8'}
+    dev: true
+
   /call-bind@1.0.5:
     resolution: {integrity: sha512-C3nQxfFZxFRVoJoGKKI8y3MOEo129NQ+FgQ08iye+Mk4zNZZGdjfs06bVTr+DBSlA66Q2VEcMki/cUCP4SercQ==}
     dependencies:
@@ -9173,6 +9226,12 @@ packages:
     resolution: {integrity: sha512-Rfkk/Mp/DL7JVje3u18FxFujQlTNR2q6QfMSMB7AvCBx91NGj/ba3kCfza0f6dVDbw7YlRf/nDrn7pQrCCyQ/w==}
     dev: true
 
+  /estree-walker@3.0.3:
+    resolution: {integrity: sha512-7RUKfXgSMMkzt6ZuXmqapOurLGPPfgj6l9uRZ7lRGolvk0y2yocc35LdcxKC5PQZdn2DMqioAQ2NoWcrTKmm6g==}
+    dependencies:
+      '@types/estree': 1.0.5
+    dev: true
+
   /esutils@2.0.3:
     resolution: {integrity: sha512-kVscqXk4OCp68SZ0dkgEKVi6/8ij300KBWTJq32P/dYeWTSwK41WyTxalN1eRmA5Z9UU/LX9D7FWSmV9SAYx6g==}
     engines: {node: '>=0.10.0'}
@@ -10547,6 +10606,10 @@ packages:
     hasBin: true
     dev: true
 
+  /jsonc-parser@3.2.1:
+    resolution: {integrity: sha512-AilxAyFOAcK5wA1+LeaySVBrHsGQvUFCDWXKpZjzaL0PqW+xfBOttn8GNtWKFWqneyMZj41MWF9Kl6iPWLwgOA==}
+    dev: true
+
   /jsondiffpatch@0.6.0:
     resolution: {integrity: sha512-3QItJOXp2AP1uv7waBkao5nCvhEv+QmJAd38Ybq7wNI74Q+BBmnLn4EDKz6yI9xGAIQoUF87qHt+kc1IVxB4zQ==}
     engines: {node: ^18.0.0 || >=20.0.0}
@@ -10648,6 +10711,14 @@ packages:
     engines: {node: ^12.20.0 || ^14.13.1 || >=16.0.0}
     dev: true
 
+  /local-pkg@0.5.0:
+    resolution: {integrity: sha512-ok6z3qlYyCDS4ZEU27HaU6x/xZa9Whf8jD4ptH5UZTQYZVYeb9bnZ3ojVhiJNLiXK1Hfc0GNbLXcmZ5plLDDBg==}
+    engines: {node: '>=14'}
+    dependencies:
+      mlly: 1.5.0
+      pkg-types: 1.0.3
+    dev: true
+
   /locate-path@3.0.0:
     resolution: {integrity: sha512-7AO748wWnIhNqAuaty2ZWHkQHRSNfPVIsPIfwEOWO22AmaoVrWavlOcMR5nzTLNYvp36X220/maaRsrec1G65A==}
     engines: {node: '>=6'}
@@ -10986,6 +11057,15 @@ packages:
     hasBin: true
     dev: true
 
+  /mlly@1.5.0:
+    resolution: {integrity: sha512-NPVQvAY1xr1QoVeG0cy8yUYC7FQcOx6evl/RjT1wL5FvzPnzOysoqB/jmx/DhssT2dYa8nxECLAaFI/+gVLhDQ==}
+    dependencies:
+      acorn: 8.11.3
+      pathe: 1.1.2
+      pkg-types: 1.0.3
+      ufo: 1.3.2
+    dev: true
+
   /module-definition@3.4.0:
     resolution: {integrity: sha512-XxJ88R1v458pifaSkPNLUTdSPNVGMP2SXVncVmApGO+gAfrLANiYe6JofymCzVceGOMwQE2xogxBSc8uB7XegA==}
     engines: {node: '>=6.0'}
@@ -11380,6 +11460,13 @@ packages:
       yocto-queue: 0.1.0
     dev: true
 
+  /p-limit@5.0.0:
+    resolution: {integrity: sha512-/Eaoq+QyLSiXQ4lyYV23f14mZRQcXnxfHrN0vCai+ak9G0pp9iEQukIIZq5NccEvwRB8PUnZT0KsOoDCINS1qQ==}
+    engines: {node: '>=18'}
+    dependencies:
+      yocto-queue: 1.0.0
+    dev: true
+
   /p-locate@3.0.0:
     resolution: {integrity: sha512-x+12w/To+4GFfgJhBEpiDcLozRJGegY+Ei7/z0tSLkMmxGZNybVMSfWj9aJn8Z5Fc7dBUNJOOVgPv2H7IwulSQ==}
     engines: {node: '>=6'}
@@ -11550,6 +11637,14 @@ packages:
       find-up: 5.0.0
     dev: true
 
+  /pkg-types@1.0.3:
+    resolution: {integrity: sha512-nN7pYi0AQqJnoLPC9eHFQ8AcyaixBUOwvqc5TDnIKCMEE6I0y8P7OKA7fPexsXGCGxQDl/cmrLAp26LhcwxZ4A==}
+    dependencies:
+      jsonc-parser: 3.2.1
+      mlly: 1.5.0
+      pathe: 1.1.2
+    dev: true
+
   /pluralize@8.0.0:
     resolution: {integrity: sha512-Nc3IT5yHzflTfbjgqWcCPpo7DaKy4FnpB0l/zCAW0Tc7jxAiuqSxHasntB3D7887LSrA93kDJ9IXovxJYxyLCA==}
     engines: {node: '>=4'}
@@ -12850,6 +12945,10 @@ packages:
       object-inspect: 1.13.1
     dev: true
 
+  /siginfo@2.0.0:
+    resolution: {integrity: sha512-ybx0WO1/8bSBLEWXZvEd7gMW3Sn3JFlW3TvX1nREbDLRNQNaeNN8WK0meBwPdAaOI7TtRRRJn/Es1zhrrCHu7g==}
+    dev: true
+
   /signal-exit@3.0.7:
     resolution: {integrity: sha512-wnD2ZE+l+SPC/uoS0vXeE9L1+0wuaMqKlfz9AMUo38JsyLSBWSFcHR1Rri62LZc12vLr1gb3jl7iwQhgwpAbGQ==}
     dev: true
@@ -12968,6 +13067,10 @@ packages:
       stackframe: 1.3.4
     dev: false
 
+  /stackback@0.0.2:
+    resolution: {integrity: sha512-1XMJE5fQo1jGH6Y/7ebnwPOBEkIEnT4QF32d5R1+VXdXveM0IBMJt8zfaxX1P3QhVwrYe+576+jkANtSS2mBbw==}
+    dev: true
+
   /stackframe@1.3.4:
     resolution: {integrity: sha512-oeVtt7eWQS+Na6F//S4kJ2K2VbRlS9D43mAlMyVpVWovy9o+jfgH8O9agzANzaiLjclA0oYzUXEM4PurhSUChw==}
     dev: false
@@ -12992,6 +13095,10 @@ packages:
     engines: {node: '>= 0.8'}
     dev: true
 
+  /std-env@3.7.0:
+    resolution: {integrity: sha512-JPbdCEQLj1w5GilpiHAx3qJvFndqybBysA3qUOnznweH4QbNYUsW/ea8QzSrnh0vNsezMMw5bcVool8lM0gwzg==}
+    dev: true
+
   /stop-iteration-iterator@1.0.0:
     resolution: {integrity: sha512-iCGQj+0l0HOdZ2AEeBADlsRC+vsnDsZsbdSiH1yNSjcfKM7fdpCMfqAL/dwF5BLiw/XhRft/Wax6zQbhq2BcjQ==}
     engines: {node: '>= 0.4'}
@@ -13161,6 +13268,12 @@ packages:
     engines: {node: '>=8'}
     dev: true
 
+  /strip-literal@1.3.0:
+    resolution: {integrity: sha512-PugKzOsyXpArk0yWmUwqOZecSO0GH0bPoctLcqNDH9J04pVW3lflYE0ujElBGTloevcxF5MofAOZ7C5l2b+wLg==}
+    dependencies:
+      acorn: 8.11.3
+    dev: true
+
   /stylis@4.2.0:
     resolution: {integrity: sha512-Orov6g6BB1sDfYgzWfTHDOxamtX1bE/zo104Dh9e6fqJ3PooipYyfJ0pUmrZO2wAvO8YbEyeFrkV91XTsGMSrw==}
     dev: false
@@ -13311,6 +13424,15 @@ packages:
   /tiny-invariant@1.3.1:
     resolution: {integrity: sha512-AD5ih2NlSssTCwsMznbvwMZpJ1cbhkGd2uueNxzv2jDlEeZdU04JQfRnggJQ8DrcVBGjAsCKwFBbDlVNtEMlzw==}
 
+  /tinybench@2.6.0:
+    resolution: {integrity: sha512-N8hW3PG/3aOoZAN5V/NSAEDz0ZixDSSt5b/a05iqtpgfLWMSVuCo7w0k2vVvEjdrIoeGqZzweX2WlyioNIHchA==}
+    dev: true
+
+  /tinypool@0.8.2:
+    resolution: {integrity: sha512-SUszKYe5wgsxnNOVlBYO6IC+8VGWdVGZWAqUxp3UErNBtptZvWbwyUOyzNL59zigz2rCA92QiL3wvG+JDSdJdQ==}
+    engines: {node: '>=14.0.0'}
+    dev: true
+
   /tinyspy@2.2.0:
     resolution: {integrity: sha512-d2eda04AN/cPOR89F7Xv5bK/jrQEhmcLFe6HFldoeO9AJtps+fqEnh486vnT/8y4bw38pSyxDcTCAq+Ks2aJTg==}
     engines: {node: '>=14.0.0'}
@@ -13828,6 +13950,27 @@ packages:
     engines: {node: '>= 0.8'}
     dev: true
 
+  /vite-node@1.2.2(@types/node@20.11.5):
+    resolution: {integrity: sha512-1as4rDTgVWJO3n1uHmUYqq7nsFgINQ9u+mRcXpjeOMJUmviqNKjcZB7UfRZrlM7MjYXMKpuWp5oGkjaFLnjawg==}
+    engines: {node: ^18.0.0 || >=20.0.0}
+    hasBin: true
+    dependencies:
+      cac: 6.7.14
+      debug: 4.3.4
+      pathe: 1.1.2
+      picocolors: 1.0.0
+      vite: 5.0.12(@types/node@20.11.5)
+    transitivePeerDependencies:
+      - '@types/node'
+      - less
+      - lightningcss
+      - sass
+      - stylus
+      - sugarss
+      - supports-color
+      - terser
+    dev: true
+
   /vite-plugin-css-injected-by-js@3.3.1(vite@5.0.12):
     resolution: {integrity: sha512-PjM/X45DR3/V1K1fTRs8HtZHEQ55kIfdrn+dzaqNBFrOYO073SeSNCxp4j7gSYhV9NffVHaEnOL4myoko0ePAg==}
     peerDependencies:
@@ -13926,6 +14069,63 @@ packages:
       fsevents: 2.3.3
     dev: true
 
+  /vitest@1.2.2(@types/node@20.11.5):
+    resolution: {integrity: sha512-d5Ouvrnms3GD9USIK36KG8OZ5bEvKEkITFtnGv56HFaSlbItJuYr7hv2Lkn903+AvRAgSixiamozUVfORUekjw==}
+    engines: {node: ^18.0.0 || >=20.0.0}
+    hasBin: true
+    peerDependencies:
+      '@edge-runtime/vm': '*'
+      '@types/node': ^18.0.0 || >=20.0.0
+      '@vitest/browser': ^1.0.0
+      '@vitest/ui': ^1.0.0
+      happy-dom: '*'
+      jsdom: '*'
+    peerDependenciesMeta:
+      '@edge-runtime/vm':
+        optional: true
+      '@types/node':
+        optional: true
+      '@vitest/browser':
+        optional: true
+      '@vitest/ui':
+        optional: true
+      happy-dom:
+        optional: true
+      jsdom:
+        optional: true
+    dependencies:
+      '@types/node': 20.11.5
+      '@vitest/expect': 1.2.2
+      '@vitest/runner': 1.2.2
+      '@vitest/snapshot': 1.2.2
+      '@vitest/spy': 1.2.2
+      '@vitest/utils': 1.2.2
+      acorn-walk: 8.3.2
+      cac: 6.7.14
+      chai: 4.4.1
+      debug: 4.3.4
+      execa: 8.0.1
+      local-pkg: 0.5.0
+      magic-string: 0.30.5
+      pathe: 1.1.2
+      picocolors: 1.0.0
+      std-env: 3.7.0
+      strip-literal: 1.3.0
+      tinybench: 2.6.0
+      tinypool: 0.8.2
+      vite: 5.0.12(@types/node@20.11.5)
+      vite-node: 1.2.2(@types/node@20.11.5)
+      why-is-node-running: 2.2.2
+    transitivePeerDependencies:
+      - less
+      - lightningcss
+      - sass
+      - stylus
+      - sugarss
+      - supports-color
+      - terser
+    dev: true
+
   /void-elements@3.1.0:
     resolution: {integrity: sha512-Dhxzh5HZuiHQhbvTW9AMetFfBHDMYpo23Uo9btPXgdYP+3T5S+p+jgNy7spra+veYhBP2dCSgxR/i2Y02h5/6w==}
     engines: {node: '>=0.10.0'}
@@ -14049,6 +14249,15 @@ packages:
       isexe: 2.0.0
     dev: true
 
+  /why-is-node-running@2.2.2:
+    resolution: {integrity: sha512-6tSwToZxTOcotxHeA+qGCq1mVzKR3CwcJGmVcY+QE8SHy6TnpFnh8PAvPNHYr7EcuVeG0QSMxtYCuO1ta/G/oA==}
+    engines: {node: '>=8'}
+    hasBin: true
+    dependencies:
+      siginfo: 2.0.0
+      stackback: 0.0.2
+    dev: true
+
   /wordwrap@1.0.0:
     resolution: {integrity: sha512-gvVzJFlPycKc5dZN4yPkP8w7Dc37BtP1yczEneOb4uq34pXZcvrtRTmWV8W+Ume+XCxKgbjM+nevkyFPMybd4Q==}
     dev: true
@@ -14189,6 +14398,11 @@ packages:
     engines: {node: '>=10'}
     dev: true
 
+  /yocto-queue@1.0.0:
+    resolution: {integrity: sha512-9bnSc/HEW2uRy67wc+T8UwauLuPJVn28jb+GtJY16iiKWyvmYJRXVT4UamsAEGQfPohgr2q4Tq0sQbQlxTfi1g==}
+    engines: {node: '>=12.20'}
+    dev: true
+
   /z-schema@5.0.5:
     resolution: {integrity: sha512-D7eujBWkLa3p2sIpJA0d1pr7es+a7m0vFAnZLlCEKq/Ij2k0MLi9Br2UPxoxdYystm5K1yeBGzub0FlYUEWj2Q==}
     engines: {node: '>=8.0.0'}
diff --git a/invokeai/frontend/web/vite.config.mts b/invokeai/frontend/web/vite.config.mts
index b76dd24b62..325c6467de 100644
--- a/invokeai/frontend/web/vite.config.mts
+++ b/invokeai/frontend/web/vite.config.mts
@@ -1,12 +1,90 @@
+/// <reference types="vitest" />
+import react from '@vitejs/plugin-react-swc';
+import path from 'path';
+import { visualizer } from 'rollup-plugin-visualizer';
+import type { PluginOption } from 'vite';
 import { defineConfig } from 'vite';
-
-import { appConfig } from './config/vite.app.config.mjs';
-import { packageConfig } from './config/vite.package.config.mjs';
+import cssInjectedByJsPlugin from 'vite-plugin-css-injected-by-js';
+import dts from 'vite-plugin-dts';
+import eslint from 'vite-plugin-eslint';
+import tsconfigPaths from 'vite-tsconfig-paths';
 
 export default defineConfig(({ mode }) => {
   if (mode === 'package') {
-    return packageConfig;
+    return {
+      base: './',
+      plugins: [
+        react(),
+        eslint(),
+        tsconfigPaths(),
+        visualizer() as unknown as PluginOption,
+        dts({
+          insertTypesEntry: true,
+        }),
+        cssInjectedByJsPlugin(),
+      ],
+      build: {
+        cssCodeSplit: true,
+        lib: {
+          entry: path.resolve(__dirname, '../src/index.ts'),
+          name: 'InvokeAIUI',
+          fileName: (format) => `invoke-ai-ui.${format}.js`,
+        },
+        rollupOptions: {
+          external: ['react', 'react-dom', '@emotion/react', '@chakra-ui/react', '@invoke-ai/ui-library'],
+          output: {
+            globals: {
+              react: 'React',
+              'react-dom': 'ReactDOM',
+              '@emotion/react': 'EmotionReact',
+              '@invoke-ai/ui-library': 'UiLibrary',
+            },
+          },
+        },
+      },
+      resolve: {
+        alias: {
+          app: path.resolve(__dirname, '../src/app'),
+          assets: path.resolve(__dirname, '../src/assets'),
+          common: path.resolve(__dirname, '../src/common'),
+          features: path.resolve(__dirname, '../src/features'),
+          services: path.resolve(__dirname, '../src/services'),
+          theme: path.resolve(__dirname, '../src/theme'),
+        },
+      },
+    };
   }
 
-  return appConfig;
+  return {
+    base: './',
+    plugins: [react(), mode !== 'test' && eslint(), tsconfigPaths(), visualizer() as unknown as PluginOption],
+    build: {
+      chunkSizeWarningLimit: 1500,
+    },
+    server: {
+      // Proxy HTTP requests to the flask server
+      proxy: {
+        // Proxy socket.io to the nodes socketio server
+        '/ws/socket.io': {
+          target: 'ws://127.0.0.1:9090',
+          ws: true,
+        },
+        // Proxy openapi schema definiton
+        '/openapi.json': {
+          target: 'http://127.0.0.1:9090/openapi.json',
+          rewrite: (path) => path.replace(/^\/openapi.json/, ''),
+          changeOrigin: true,
+        },
+        // proxy nodes api
+        '/api/v1': {
+          target: 'http://127.0.0.1:9090/api/v1',
+          rewrite: (path) => path.replace(/^\/api\/v1/, ''),
+          changeOrigin: true,
+        },
+      },
+    },
+    test: {
+      //
+    },
+  };
 });

From 30db708c4fa058837faeda7eb20fcab1fb60af85 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 13 Feb 2024 22:53:30 +1100
Subject: [PATCH 108/411] feat(ui): add more types of FieldParseError

Unfortunately you cannot test for both a specific type of error and match its message. Splitting the error classes makes it easier to test expected error conditions.
---
 .../web/src/features/nodes/types/error.ts     |  5 ++++
 .../nodes/util/schema/parseFieldType.ts       | 30 +++++++++++--------
 2 files changed, 23 insertions(+), 12 deletions(-)

diff --git a/invokeai/frontend/web/src/features/nodes/types/error.ts b/invokeai/frontend/web/src/features/nodes/types/error.ts
index 905b487fb0..c3da136c7a 100644
--- a/invokeai/frontend/web/src/features/nodes/types/error.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/error.ts
@@ -56,3 +56,8 @@ export class FieldParseError extends Error {
     this.name = this.constructor.name;
   }
 }
+
+export class UnableToExtractSchemaNameFromRefError extends FieldParseError {}
+export class UnsupportedArrayItemType extends FieldParseError {}
+export class UnsupportedUnionError extends FieldParseError {}
+export class UnsupportedPrimitiveTypeError extends FieldParseError {}
\ No newline at end of file
diff --git a/invokeai/frontend/web/src/features/nodes/util/schema/parseFieldType.ts b/invokeai/frontend/web/src/features/nodes/util/schema/parseFieldType.ts
index 14b1aefd6d..13da6b3831 100644
--- a/invokeai/frontend/web/src/features/nodes/util/schema/parseFieldType.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/schema/parseFieldType.ts
@@ -1,6 +1,12 @@
-import { FieldParseError } from 'features/nodes/types/error';
+import {
+  FieldParseError,
+  UnableToExtractSchemaNameFromRefError,
+  UnsupportedArrayItemType,
+  UnsupportedPrimitiveTypeError,
+  UnsupportedUnionError,
+} from 'features/nodes/types/error';
 import type { FieldType } from 'features/nodes/types/field';
-import type { OpenAPIV3_1SchemaOrRef } from 'features/nodes/types/openapi';
+import type { InvocationFieldSchema, OpenAPIV3_1SchemaOrRef } from 'features/nodes/types/openapi';
 import {
   isArraySchemaObject,
   isInvocationFieldSchema,
@@ -42,7 +48,7 @@ const isCollectionFieldType = (fieldType: string) => {
   return false;
 };
 
-export const parseFieldType = (schemaObject: OpenAPIV3_1SchemaOrRef): FieldType => {
+export const parseFieldType = (schemaObject: OpenAPIV3_1SchemaOrRef | InvocationFieldSchema): FieldType => {
   if (isInvocationFieldSchema(schemaObject)) {
     // Check if this field has an explicit type provided by the node schema
     const { ui_type } = schemaObject;
@@ -72,7 +78,7 @@ export const parseFieldType = (schemaObject: OpenAPIV3_1SchemaOrRef): FieldType
           // This is a single ref type
           const name = refObjectToSchemaName(allOf[0]);
           if (!name) {
-            throw new FieldParseError(t('nodes.unableToExtractSchemaNameFromRef'));
+            throw new UnableToExtractSchemaNameFromRefError(t('nodes.unableToExtractSchemaNameFromRef'));
           }
           return {
             name,
@@ -95,7 +101,7 @@ export const parseFieldType = (schemaObject: OpenAPIV3_1SchemaOrRef): FieldType
           if (isRefObject(filteredAnyOf[0])) {
             const name = refObjectToSchemaName(filteredAnyOf[0]);
             if (!name) {
-              throw new FieldParseError(t('nodes.unableToExtractSchemaNameFromRef'));
+              throw new UnableToExtractSchemaNameFromRefError(t('nodes.unableToExtractSchemaNameFromRef'));
             }
 
             return {
@@ -118,7 +124,7 @@ export const parseFieldType = (schemaObject: OpenAPIV3_1SchemaOrRef): FieldType
 
         if (filteredAnyOf.length !== 2) {
           // This is a union of more than 2 types, which we don't support
-          throw new FieldParseError(
+          throw new UnsupportedUnionError(
             t('nodes.unsupportedAnyOfLength', {
               count: filteredAnyOf.length,
             })
@@ -159,7 +165,7 @@ export const parseFieldType = (schemaObject: OpenAPIV3_1SchemaOrRef): FieldType
           };
         }
 
-        throw new FieldParseError(
+        throw new UnsupportedUnionError(
           t('nodes.unsupportedMismatchedUnion', {
             firstType,
             secondType,
@@ -178,7 +184,7 @@ export const parseFieldType = (schemaObject: OpenAPIV3_1SchemaOrRef): FieldType
         if (isSchemaObject(schemaObject.items)) {
           const itemType = schemaObject.items.type;
           if (!itemType || isArray(itemType)) {
-            throw new FieldParseError(
+            throw new UnsupportedArrayItemType(
               t('nodes.unsupportedArrayItemType', {
                 type: itemType,
               })
@@ -188,7 +194,7 @@ export const parseFieldType = (schemaObject: OpenAPIV3_1SchemaOrRef): FieldType
           const name = OPENAPI_TO_FIELD_TYPE_MAP[itemType];
           if (!name) {
             // it's 'null', 'object', or 'array' - skip
-            throw new FieldParseError(
+            throw new UnsupportedArrayItemType(
               t('nodes.unsupportedArrayItemType', {
                 type: itemType,
               })
@@ -204,7 +210,7 @@ export const parseFieldType = (schemaObject: OpenAPIV3_1SchemaOrRef): FieldType
         // This is a ref object, extract the type name
         const name = refObjectToSchemaName(schemaObject.items);
         if (!name) {
-          throw new FieldParseError(t('nodes.unableToExtractSchemaNameFromRef'));
+          throw new UnableToExtractSchemaNameFromRefError(t('nodes.unableToExtractSchemaNameFromRef'));
         }
         return {
           name,
@@ -216,7 +222,7 @@ export const parseFieldType = (schemaObject: OpenAPIV3_1SchemaOrRef): FieldType
         const name = OPENAPI_TO_FIELD_TYPE_MAP[schemaObject.type];
         if (!name) {
           // it's 'null', 'object', or 'array' - skip
-          throw new FieldParseError(
+          throw new UnsupportedPrimitiveTypeError(
             t('nodes.unsupportedArrayItemType', {
               type: schemaObject.type,
             })
@@ -232,7 +238,7 @@ export const parseFieldType = (schemaObject: OpenAPIV3_1SchemaOrRef): FieldType
   } else if (isRefObject(schemaObject)) {
     const name = refObjectToSchemaName(schemaObject);
     if (!name) {
-      throw new FieldParseError(t('nodes.unableToExtractSchemaNameFromRef'));
+      throw new UnableToExtractSchemaNameFromRefError(t('nodes.unableToExtractSchemaNameFromRef'));
     }
     return {
       name,

From 95453a22b1f991b29fd99d40d1cff2f924330272 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 13 Feb 2024 22:53:52 +1100
Subject: [PATCH 109/411] tests(ui): add `parseFieldType.test.ts`

---
 .../nodes/util/schema/parseFieldType.test.ts  | 379 ++++++++++++++++++
 1 file changed, 379 insertions(+)
 create mode 100644 invokeai/frontend/web/src/features/nodes/util/schema/parseFieldType.test.ts

diff --git a/invokeai/frontend/web/src/features/nodes/util/schema/parseFieldType.test.ts b/invokeai/frontend/web/src/features/nodes/util/schema/parseFieldType.test.ts
new file mode 100644
index 0000000000..2f4ce48a32
--- /dev/null
+++ b/invokeai/frontend/web/src/features/nodes/util/schema/parseFieldType.test.ts
@@ -0,0 +1,379 @@
+import {
+  UnableToExtractSchemaNameFromRefError,
+  UnsupportedArrayItemType,
+  UnsupportedPrimitiveTypeError,
+  UnsupportedUnionError,
+} from 'features/nodes/types/error';
+import type { InvocationFieldSchema, OpenAPIV3_1SchemaOrRef } from 'features/nodes/types/openapi';
+import { parseFieldType, refObjectToSchemaName } from 'features/nodes/util/schema/parseFieldType';
+import { describe, expect, it } from 'vitest';
+
+type ParseFieldTypeTestCase = {
+  name: string;
+  schema: OpenAPIV3_1SchemaOrRef | InvocationFieldSchema;
+  expected: { name: string; isCollection: boolean; isCollectionOrScalar: boolean };
+};
+
+const primitiveTypes: ParseFieldTypeTestCase[] = [
+  {
+    name: 'Scalar IntegerField',
+    schema: { type: 'integer' },
+    expected: { name: 'IntegerField', isCollection: false, isCollectionOrScalar: false },
+  },
+  {
+    name: 'Scalar FloatField',
+    schema: { type: 'number' },
+    expected: { name: 'FloatField', isCollection: false, isCollectionOrScalar: false },
+  },
+  {
+    name: 'Scalar StringField',
+    schema: { type: 'string' },
+    expected: { name: 'StringField', isCollection: false, isCollectionOrScalar: false },
+  },
+  {
+    name: 'Scalar BooleanField',
+    schema: { type: 'boolean' },
+    expected: { name: 'BooleanField', isCollection: false, isCollectionOrScalar: false },
+  },
+  {
+    name: 'Collection IntegerField',
+    schema: { items: { type: 'integer' }, type: 'array' },
+    expected: { name: 'IntegerField', isCollection: true, isCollectionOrScalar: false },
+  },
+  {
+    name: 'Collection FloatField',
+    schema: { items: { type: 'number' }, type: 'array' },
+    expected: { name: 'FloatField', isCollection: true, isCollectionOrScalar: false },
+  },
+  {
+    name: 'Collection StringField',
+    schema: { items: { type: 'string' }, type: 'array' },
+    expected: { name: 'StringField', isCollection: true, isCollectionOrScalar: false },
+  },
+  {
+    name: 'Collection BooleanField',
+    schema: { items: { type: 'boolean' }, type: 'array' },
+    expected: { name: 'BooleanField', isCollection: true, isCollectionOrScalar: false },
+  },
+  {
+    name: 'CollectionOrScalar IntegerField',
+    schema: {
+      anyOf: [
+        {
+          type: 'integer',
+        },
+        {
+          items: {
+            type: 'integer',
+          },
+          type: 'array',
+        },
+      ],
+    },
+    expected: { name: 'IntegerField', isCollection: false, isCollectionOrScalar: true },
+  },
+  {
+    name: 'CollectionOrScalar FloatField',
+    schema: {
+      anyOf: [
+        {
+          type: 'number',
+        },
+        {
+          items: {
+            type: 'number',
+          },
+          type: 'array',
+        },
+      ],
+    },
+    expected: { name: 'FloatField', isCollection: false, isCollectionOrScalar: true },
+  },
+  {
+    name: 'CollectionOrScalar StringField',
+    schema: {
+      anyOf: [
+        {
+          type: 'string',
+        },
+        {
+          items: {
+            type: 'string',
+          },
+          type: 'array',
+        },
+      ],
+    },
+    expected: { name: 'StringField', isCollection: false, isCollectionOrScalar: true },
+  },
+  {
+    name: 'CollectionOrScalar BooleanField',
+    schema: {
+      anyOf: [
+        {
+          type: 'boolean',
+        },
+        {
+          items: {
+            type: 'boolean',
+          },
+          type: 'array',
+        },
+      ],
+    },
+    expected: { name: 'BooleanField', isCollection: false, isCollectionOrScalar: true },
+  },
+];
+
+const complexTypes: ParseFieldTypeTestCase[] = [
+  {
+    name: 'Scalar ConditioningField',
+    schema: {
+      allOf: [
+        {
+          $ref: '#/components/schemas/ConditioningField',
+        },
+      ],
+    },
+    expected: { name: 'ConditioningField', isCollection: false, isCollectionOrScalar: false },
+  },
+  {
+    name: 'Nullable Scalar ConditioningField',
+    schema: {
+      anyOf: [
+        {
+          $ref: '#/components/schemas/ConditioningField',
+        },
+        {
+          type: 'null',
+        },
+      ],
+    },
+    expected: { name: 'ConditioningField', isCollection: false, isCollectionOrScalar: false },
+  },
+  {
+    name: 'Collection ConditioningField',
+    schema: {
+      anyOf: [
+        {
+          items: {
+            $ref: '#/components/schemas/ConditioningField',
+          },
+          type: 'array',
+        },
+      ],
+    },
+    expected: { name: 'ConditioningField', isCollection: true, isCollectionOrScalar: false },
+  },
+  {
+    name: 'Nullable Collection ConditioningField',
+    schema: {
+      anyOf: [
+        {
+          items: {
+            $ref: '#/components/schemas/ConditioningField',
+          },
+          type: 'array',
+        },
+        {
+          type: 'null',
+        },
+      ],
+    },
+    expected: { name: 'ConditioningField', isCollection: true, isCollectionOrScalar: false },
+  },
+  {
+    name: 'CollectionOrScalar ConditioningField',
+    schema: {
+      anyOf: [
+        {
+          items: {
+            $ref: '#/components/schemas/ConditioningField',
+          },
+          type: 'array',
+        },
+        {
+          $ref: '#/components/schemas/ConditioningField',
+        },
+      ],
+    },
+    expected: { name: 'ConditioningField', isCollection: false, isCollectionOrScalar: true },
+  },
+  {
+    name: 'Nullable CollectionOrScalar ConditioningField',
+    schema: {
+      anyOf: [
+        {
+          items: {
+            $ref: '#/components/schemas/ConditioningField',
+          },
+          type: 'array',
+        },
+        {
+          $ref: '#/components/schemas/ConditioningField',
+        },
+        {
+          type: 'null',
+        },
+      ],
+    },
+    expected: { name: 'ConditioningField', isCollection: false, isCollectionOrScalar: true },
+  },
+];
+
+const specialCases: ParseFieldTypeTestCase[] = [
+  {
+    name: 'String EnumField',
+    schema: {
+      type: 'string',
+      enum: ['large', 'base', 'small'],
+    },
+    expected: { name: 'EnumField', isCollection: false, isCollectionOrScalar: false },
+  },
+  {
+    name: 'String EnumField with one value',
+    schema: {
+      const: 'Some Value',
+    },
+    expected: { name: 'EnumField', isCollection: false, isCollectionOrScalar: false },
+  },
+  {
+    name: 'Explicit ui_type (SchedulerField)',
+    schema: {
+      type: 'string',
+      enum: ['ddim', 'ddpm', 'deis'],
+      ui_type: 'SchedulerField',
+    },
+    expected: { name: 'SchedulerField', isCollection: false, isCollectionOrScalar: false },
+  },
+  {
+    name: 'Explicit ui_type (AnyField)',
+    schema: {
+      type: 'string',
+      enum: ['ddim', 'ddpm', 'deis'],
+      ui_type: 'AnyField',
+    },
+    expected: { name: 'AnyField', isCollection: false, isCollectionOrScalar: false },
+  },
+  {
+    name: 'Explicit ui_type (CollectionField)',
+    schema: {
+      type: 'string',
+      enum: ['ddim', 'ddpm', 'deis'],
+      ui_type: 'CollectionField',
+    },
+    expected: { name: 'CollectionField', isCollection: true, isCollectionOrScalar: false },
+  },
+];
+
+describe('refObjectToSchemaName', async () => {
+  it('parses ref object 1', () => {
+    expect(
+      refObjectToSchemaName({
+        $ref: '#/components/schemas/ImageField',
+      })
+    ).toEqual('ImageField');
+  });
+  it('parses ref object 2', () => {
+    expect(
+      refObjectToSchemaName({
+        $ref: '#/components/schemas/T2IAdapterModelField',
+      })
+    ).toEqual('T2IAdapterModelField');
+  });
+});
+
+describe.concurrent('parseFieldType', async () => {
+  it.each(primitiveTypes)('parses primitive types ($name)', ({ schema, expected }) => {
+    expect(parseFieldType(schema)).toEqual(expected);
+  });
+  it.each(complexTypes)('parses complex types ($name)', ({ schema, expected }) => {
+    expect(parseFieldType(schema)).toEqual(expected);
+  });
+  it.each(specialCases)('parses special case types ($name)', ({ schema, expected }) => {
+    expect(parseFieldType(schema)).toEqual(expected);
+  });
+
+  it('raises if it cannot extract a schema name from a ref', () => {
+    expect(() =>
+      parseFieldType({
+        allOf: [
+          {
+            $ref: '#/components/schemas/',
+          },
+        ],
+      })
+    ).toThrowError(UnableToExtractSchemaNameFromRefError);
+  });
+
+  it('raises if it receives a union of mismatched types', () => {
+    expect(() =>
+      parseFieldType({
+        anyOf: [
+          {
+            type: 'string',
+          },
+          {
+            type: 'integer',
+          },
+        ],
+      })
+    ).toThrowError(UnsupportedUnionError);
+  });
+
+  it('raises if it receives a union of mismatched types (excluding null)', () => {
+    expect(() =>
+      parseFieldType({
+        anyOf: [
+          {
+            type: 'string',
+          },
+          {
+            type: 'integer',
+          },
+          {
+            type: 'null',
+          },
+        ],
+      })
+    ).toThrowError(UnsupportedUnionError);
+  });
+
+  it('raises if it received an unsupported primitive type (object)', () => {
+    expect(() =>
+      parseFieldType({
+        type: 'object',
+      })
+    ).toThrowError(UnsupportedPrimitiveTypeError);
+  });
+
+  it('raises if it received an unsupported primitive type (null)', () => {
+    expect(() =>
+      parseFieldType({
+        type: 'null',
+      })
+    ).toThrowError(UnsupportedPrimitiveTypeError);
+  });
+
+  it('raises if it received an unsupported array item type (object)', () => {
+    expect(() =>
+      parseFieldType({
+        items: {
+          type: 'object',
+        },
+        type: 'array',
+      })
+    ).toThrowError(UnsupportedArrayItemType);
+  });
+
+  it('raises if it received an unsupported array item type (null)', () => {
+    expect(() =>
+      parseFieldType({
+        items: {
+          type: 'null',
+        },
+        type: 'array',
+      })
+    ).toThrowError(UnsupportedArrayItemType);
+  });
+});

From 010c4eae65b2001d1ff6882128417f1238bafabf Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lstein@gmail.com>
Date: Mon, 22 Jan 2024 14:37:23 -0500
Subject: [PATCH 110/411] add concept of repo variant

---
 invokeai/backend/model_manager/config.py      |  4 +-
 invokeai/backend/model_manager/probe.py       | 19 ++++++++++
 tests/test_model_probe.py                     |  9 ++++-
 .../vae/taesdxl-fp16/config.json              | 37 +++++++++++++++++++
 .../diffusion_pytorch_model.fp16.safetensors  |  0
 5 files changed, 65 insertions(+), 4 deletions(-)
 create mode 100644 tests/test_model_probe/vae/taesdxl-fp16/config.json
 create mode 100644 tests/test_model_probe/vae/taesdxl-fp16/diffusion_pytorch_model.fp16.safetensors

diff --git a/invokeai/backend/model_manager/config.py b/invokeai/backend/model_manager/config.py
index 964cc19f19..b4685caf10 100644
--- a/invokeai/backend/model_manager/config.py
+++ b/invokeai/backend/model_manager/config.py
@@ -150,7 +150,7 @@ class _DiffusersConfig(ModelConfigBase):
     """Model config for diffusers-style models."""
 
     format: Literal[ModelFormat.Diffusers] = ModelFormat.Diffusers
-
+    repo_variant: Optional[ModelRepoVariant] = ModelRepoVariant.DEFAULT
 
 class LoRAConfig(ModelConfigBase):
     """Model config for LoRA/Lycoris models."""
@@ -179,7 +179,6 @@ class ControlNetDiffusersConfig(_DiffusersConfig):
     type: Literal[ModelType.ControlNet] = ModelType.ControlNet
     format: Literal[ModelFormat.Diffusers] = ModelFormat.Diffusers
 
-
 class ControlNetCheckpointConfig(_CheckpointConfig):
     """Model config for ControlNet models (diffusers version)."""
 
@@ -215,7 +214,6 @@ class MainDiffusersConfig(_DiffusersConfig, _MainConfig):
     prediction_type: SchedulerPredictionType = SchedulerPredictionType.Epsilon
     upcast_attention: bool = False
 
-
 class ONNXSD1Config(_MainConfig):
     """Model config for ONNX format models based on sd-1."""
 
diff --git a/invokeai/backend/model_manager/probe.py b/invokeai/backend/model_manager/probe.py
index cd048d2fe7..ba3ac3dd0c 100644
--- a/invokeai/backend/model_manager/probe.py
+++ b/invokeai/backend/model_manager/probe.py
@@ -20,6 +20,7 @@ from .config import (
     ModelFormat,
     ModelType,
     ModelVariantType,
+    ModelRepoVariant,
     SchedulerPredictionType,
 )
 from .hash import FastModelHash
@@ -155,6 +156,9 @@ class ModelProbe(object):
         fields["original_hash"] = fields.get("original_hash") or hash
         fields["current_hash"] = fields.get("current_hash") or hash
 
+        if format_type == ModelFormat.Diffusers:
+            fields["repo_variant"] = fields.get("repo_variant") or probe.get_repo_variant()
+
         # additional fields needed for main and controlnet models
         if fields["type"] in [ModelType.Main, ModelType.ControlNet] and fields["format"] == ModelFormat.Checkpoint:
             fields["config"] = cls._get_checkpoint_config_path(
@@ -477,6 +481,20 @@ class FolderProbeBase(ProbeBase):
     def get_format(self) -> ModelFormat:
         return ModelFormat("diffusers")
 
+    def get_repo_variant(self) -> ModelRepoVariant:
+        # get all files ending in .bin or .safetensors
+        weight_files = list(self.model_path.glob('**/*.safetensors'))
+        weight_files.extend(list(self.model_path.glob('**/*.bin')))
+        for x in weight_files:
+            if ".fp16" in x.suffixes:
+                return ModelRepoVariant.FP16
+            if "openvino_model" in x.name:
+                return ModelRepoVariant.OPENVINO
+            if "flax_model" in x.name:
+                return ModelRepoVariant.FLAX
+            if x.suffix == ".onnx":
+                return ModelRepoVariant.ONNX
+        return ModelRepoVariant.DEFAULT
 
 class PipelineFolderProbe(FolderProbeBase):
     def get_base_type(self) -> BaseModelType:
@@ -522,6 +540,7 @@ class PipelineFolderProbe(FolderProbeBase):
         except Exception:
             pass
         return ModelVariantType.Normal
+        
 
 
 class VaeFolderProbe(FolderProbeBase):
diff --git a/tests/test_model_probe.py b/tests/test_model_probe.py
index 248b7d602f..415559a64c 100644
--- a/tests/test_model_probe.py
+++ b/tests/test_model_probe.py
@@ -3,7 +3,7 @@ from pathlib import Path
 import pytest
 
 from invokeai.backend import BaseModelType
-from invokeai.backend.model_management.model_probe import VaeFolderProbe
+from invokeai.backend.model_manager.probe import VaeFolderProbe
 
 
 @pytest.mark.parametrize(
@@ -20,3 +20,10 @@ def test_get_base_type(vae_path: str, expected_type: BaseModelType, datadir: Pat
     probe = VaeFolderProbe(sd1_vae_path)
     base_type = probe.get_base_type()
     assert base_type == expected_type
+    repo_variant = probe.get_repo_variant()
+    assert repo_variant == 'default'
+
+def test_repo_variant(datadir: Path):
+    probe = VaeFolderProbe(datadir / "vae" / "taesdxl-fp16")
+    repo_variant = probe.get_repo_variant()
+    assert repo_variant == 'fp16'
diff --git a/tests/test_model_probe/vae/taesdxl-fp16/config.json b/tests/test_model_probe/vae/taesdxl-fp16/config.json
new file mode 100644
index 0000000000..62f01c3eb4
--- /dev/null
+++ b/tests/test_model_probe/vae/taesdxl-fp16/config.json
@@ -0,0 +1,37 @@
+{
+  "_class_name": "AutoencoderTiny",
+  "_diffusers_version": "0.20.0.dev0",
+  "act_fn": "relu",
+  "decoder_block_out_channels": [
+    64,
+    64,
+    64,
+    64
+  ],
+  "encoder_block_out_channels": [
+    64,
+    64,
+    64,
+    64
+  ],
+  "force_upcast": false,
+  "in_channels": 3,
+  "latent_channels": 4,
+  "latent_magnitude": 3,
+  "latent_shift": 0.5,
+  "num_decoder_blocks": [
+    3,
+    3,
+    3,
+    1
+  ],
+  "num_encoder_blocks": [
+    1,
+    3,
+    3,
+    3
+  ],
+  "out_channels": 3,
+  "scaling_factor": 1.0,
+  "upsampling_scaling_factor": 2
+}
diff --git a/tests/test_model_probe/vae/taesdxl-fp16/diffusion_pytorch_model.fp16.safetensors b/tests/test_model_probe/vae/taesdxl-fp16/diffusion_pytorch_model.fp16.safetensors
new file mode 100644
index 0000000000..e69de29bb2

From b8e875bb7359957ed542561589ac65e5facf6465 Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lstein@gmail.com>
Date: Wed, 31 Jan 2024 23:37:59 -0500
Subject: [PATCH 111/411] add ram cache module and support files

---
 invokeai/backend/model_manager/config.py      |   3 +
 .../backend/model_manager/load/__init__.py    |   0
 .../backend/model_manager/load/load_base.py   | 193 ++++++++++
 .../model_manager/load/load_default.py        | 168 +++++++++
 .../model_manager/load/memory_snapshot.py     | 100 ++++++
 .../backend/model_manager/load/model_util.py  | 109 ++++++
 .../model_manager/load/optimizations.py       |  30 ++
 .../model_manager/load/ram_cache/__init__.py  |   0
 .../load/ram_cache/ram_cache_base.py          | 145 ++++++++
 .../load/ram_cache/ram_cache_default.py       | 332 ++++++++++++++++++
 invokeai/backend/model_manager/load/vae.py    |  31 ++
 .../backend/model_manager/onnx_runtime.py     | 216 ++++++++++++
 invokeai/backend/model_manager/probe.py       |   8 +-
 tests/test_model_probe.py                     |   5 +-
 14 files changed, 1334 insertions(+), 6 deletions(-)
 create mode 100644 invokeai/backend/model_manager/load/__init__.py
 create mode 100644 invokeai/backend/model_manager/load/load_base.py
 create mode 100644 invokeai/backend/model_manager/load/load_default.py
 create mode 100644 invokeai/backend/model_manager/load/memory_snapshot.py
 create mode 100644 invokeai/backend/model_manager/load/model_util.py
 create mode 100644 invokeai/backend/model_manager/load/optimizations.py
 create mode 100644 invokeai/backend/model_manager/load/ram_cache/__init__.py
 create mode 100644 invokeai/backend/model_manager/load/ram_cache/ram_cache_base.py
 create mode 100644 invokeai/backend/model_manager/load/ram_cache/ram_cache_default.py
 create mode 100644 invokeai/backend/model_manager/load/vae.py
 create mode 100644 invokeai/backend/model_manager/onnx_runtime.py

diff --git a/invokeai/backend/model_manager/config.py b/invokeai/backend/model_manager/config.py
index b4685caf10..338669c873 100644
--- a/invokeai/backend/model_manager/config.py
+++ b/invokeai/backend/model_manager/config.py
@@ -152,6 +152,7 @@ class _DiffusersConfig(ModelConfigBase):
     format: Literal[ModelFormat.Diffusers] = ModelFormat.Diffusers
     repo_variant: Optional[ModelRepoVariant] = ModelRepoVariant.DEFAULT
 
+
 class LoRAConfig(ModelConfigBase):
     """Model config for LoRA/Lycoris models."""
 
@@ -179,6 +180,7 @@ class ControlNetDiffusersConfig(_DiffusersConfig):
     type: Literal[ModelType.ControlNet] = ModelType.ControlNet
     format: Literal[ModelFormat.Diffusers] = ModelFormat.Diffusers
 
+
 class ControlNetCheckpointConfig(_CheckpointConfig):
     """Model config for ControlNet models (diffusers version)."""
 
@@ -214,6 +216,7 @@ class MainDiffusersConfig(_DiffusersConfig, _MainConfig):
     prediction_type: SchedulerPredictionType = SchedulerPredictionType.Epsilon
     upcast_attention: bool = False
 
+
 class ONNXSD1Config(_MainConfig):
     """Model config for ONNX format models based on sd-1."""
 
diff --git a/invokeai/backend/model_manager/load/__init__.py b/invokeai/backend/model_manager/load/__init__.py
new file mode 100644
index 0000000000..e69de29bb2
diff --git a/invokeai/backend/model_manager/load/load_base.py b/invokeai/backend/model_manager/load/load_base.py
new file mode 100644
index 0000000000..7cb7222b71
--- /dev/null
+++ b/invokeai/backend/model_manager/load/load_base.py
@@ -0,0 +1,193 @@
+# Copyright (c) 2024, Lincoln D. Stein and the InvokeAI Development Team
+"""
+Base class for model loading in InvokeAI.
+
+Use like this:
+
+  loader = AnyModelLoader(...)
+  loaded_model = loader.get_model('019ab39adfa1840455')
+  with loaded_model as model:  # context manager moves model into VRAM
+       # do something with loaded_model
+"""
+
+from abc import ABC, abstractmethod
+from dataclasses import dataclass
+from logging import Logger
+from pathlib import Path
+from typing import Any, Callable, Dict, Optional, Type, Union
+
+import torch
+from diffusers import DiffusionPipeline
+from injector import inject
+
+from invokeai.app.services.config import InvokeAIAppConfig
+from invokeai.app.services.model_records import ModelRecordServiceBase
+from invokeai.backend.model_manager import AnyModelConfig, BaseModelType, ModelFormat, ModelType, SubModelType
+from invokeai.backend.model_manager.convert_cache import ModelConvertCacheBase
+from invokeai.backend.model_manager.onnx_runtime import IAIOnnxRuntimeModel
+from invokeai.backend.model_manager.ram_cache import ModelCacheBase
+
+AnyModel = Union[DiffusionPipeline, torch.nn.Module, IAIOnnxRuntimeModel]
+
+
+class ModelLockerBase(ABC):
+    """Base class for the model locker used by the loader."""
+
+    @abstractmethod
+    def lock(self) -> None:
+        """Lock the contained model and move it into VRAM."""
+        pass
+
+    @abstractmethod
+    def unlock(self) -> None:
+        """Unlock the contained model, and remove it from VRAM."""
+        pass
+
+    @property
+    @abstractmethod
+    def model(self) -> AnyModel:
+        """Return the model."""
+        pass
+
+
+@dataclass
+class LoadedModel:
+    """Context manager object that mediates transfer from RAM<->VRAM."""
+
+    config: AnyModelConfig
+    locker: ModelLockerBase
+
+    def __enter__(self) -> AnyModel:  # I think load_file() always returns a dict
+        """Context entry."""
+        self.locker.lock()
+        return self.model
+
+    def __exit__(self, *args: Any, **kwargs: Any) -> None:
+        """Context exit."""
+        self.locker.unlock()
+
+    @property
+    def model(self) -> AnyModel:
+        """Return the model without locking it."""
+        return self.locker.model()
+
+
+class ModelLoaderBase(ABC):
+    """Abstract base class for loading models into RAM/VRAM."""
+
+    @abstractmethod
+    def __init__(
+        self,
+        app_config: InvokeAIAppConfig,
+        logger: Logger,
+        ram_cache: ModelCacheBase,
+        convert_cache: ModelConvertCacheBase,
+    ):
+        """Initialize the loader."""
+        pass
+
+    @abstractmethod
+    def load_model(self, model_config: AnyModelConfig, submodel_type: Optional[SubModelType] = None) -> LoadedModel:
+        """
+        Return a model given its key.
+
+        Given a model key identified in the model configuration backend,
+        return a ModelInfo object that can be used to retrieve the model.
+
+        :param model_config: Model configuration, as returned by ModelConfigRecordStore
+        :param submodel_type: an ModelType enum indicating the portion of
+               the model to retrieve (e.g. ModelType.Vae)
+        """
+        pass
+
+    @abstractmethod
+    def get_size_fs(
+        self, config: AnyModelConfig, model_path: Path, submodel_type: Optional[SubModelType] = None
+    ) -> int:
+        """Return size in bytes of the model, calculated before loading."""
+        pass
+
+
+# TO DO: Better name?
+class AnyModelLoader:
+    """This class manages the model loaders and invokes the correct one to load a model of given base and type."""
+
+    # this tracks the loader subclasses
+    _registry: Dict[str, Type[ModelLoaderBase]] = {}
+
+    @inject
+    def __init__(
+        self,
+        store: ModelRecordServiceBase,
+        app_config: InvokeAIAppConfig,
+        logger: Logger,
+        ram_cache: ModelCacheBase,
+        convert_cache: ModelConvertCacheBase,
+    ):
+        """Store the provided ModelRecordServiceBase and empty the registry."""
+        self._store = store
+        self._app_config = app_config
+        self._logger = logger
+        self._ram_cache = ram_cache
+        self._convert_cache = convert_cache
+
+    def get_model(self, key: str, submodel_type: Optional[SubModelType] = None) -> LoadedModel:
+        """
+        Return a model given its key.
+
+        Given a model key identified in the model configuration backend,
+        return a ModelInfo object that can be used to retrieve the model.
+
+        :param key: model key, as known to the config backend
+        :param submodel_type: an ModelType enum indicating the portion of
+               the model to retrieve (e.g. ModelType.Vae)
+        """
+        model_config = self._store.get_model(key)
+        implementation = self.__class__.get_implementation(
+            base=model_config.base, type=model_config.type, format=model_config.format
+        )
+        return implementation(
+            app_config=self._app_config,
+            logger=self._logger,
+            ram_cache=self._ram_cache,
+            convert_cache=self._convert_cache,
+        ).load_model(model_config, submodel_type)
+
+    @staticmethod
+    def _to_registry_key(base: BaseModelType, type: ModelType, format: ModelFormat) -> str:
+        return "-".join([base.value, type.value, format.value])
+
+    @classmethod
+    def get_implementation(cls, base: BaseModelType, type: ModelType, format: ModelFormat) -> Type[ModelLoaderBase]:
+        """Get subclass of ModelLoaderBase registered to handle base and type."""
+        key1 = cls._to_registry_key(base, type, format)  # for a specific base type
+        key2 = cls._to_registry_key(BaseModelType.Any, type, format)  # with wildcard Any
+        implementation = cls._registry.get(key1) or cls._registry.get(key2)
+        if not implementation:
+            raise NotImplementedError(
+                "No subclass of LoadedModel is registered for base={base}, type={type}, format={format}"
+            )
+        return implementation
+
+    @classmethod
+    def register(
+        cls, type: ModelType, format: ModelFormat, base: BaseModelType = BaseModelType.Any
+    ) -> Callable[[Type[ModelLoaderBase]], Type[ModelLoaderBase]]:
+        """Define a decorator which registers the subclass of loader."""
+
+        def decorator(subclass: Type[ModelLoaderBase]) -> Type[ModelLoaderBase]:
+            print("Registering class", subclass.__name__)
+            key = cls._to_registry_key(base, type, format)
+            cls._registry[key] = subclass
+            return subclass
+
+        return decorator
+
+
+# in _init__.py will call something like
+# def configure_loader_dependencies(binder):
+#     binder.bind(ModelRecordServiceBase, ApiDependencies.invoker.services.model_records, scope=singleton)
+#     binder.bind(InvokeAIAppConfig, ApiDependencies.invoker.services.configuration, scope=singleton)
+# etc
+# injector = Injector(configure_loader_dependencies)
+# loader = injector.get(ModelFactory)
diff --git a/invokeai/backend/model_manager/load/load_default.py b/invokeai/backend/model_manager/load/load_default.py
new file mode 100644
index 0000000000..eb2d432aaa
--- /dev/null
+++ b/invokeai/backend/model_manager/load/load_default.py
@@ -0,0 +1,168 @@
+# Copyright (c) 2024, Lincoln D. Stein and the InvokeAI Development Team
+"""Default implementation of model loading in InvokeAI."""
+
+import sys
+from logging import Logger
+from pathlib import Path
+from typing import Any, Dict, Optional, Tuple
+
+from diffusers import ModelMixin
+from diffusers.configuration_utils import ConfigMixin
+from injector import inject
+
+from invokeai.app.services.config import InvokeAIAppConfig
+from invokeai.backend.model_manager import AnyModelConfig, InvalidModelConfigException, ModelRepoVariant, SubModelType
+from invokeai.backend.model_manager.convert_cache import ModelConvertCacheBase
+from invokeai.backend.model_manager.load.load_base import AnyModel, LoadedModel, ModelLoaderBase
+from invokeai.backend.model_manager.load.model_util import calc_model_size_by_fs
+from invokeai.backend.model_manager.load.optimizations import skip_torch_weight_init
+from invokeai.backend.model_manager.ram_cache import ModelCacheBase, ModelLockerBase
+from invokeai.backend.util.devices import choose_torch_device, torch_dtype
+
+
+class ConfigLoader(ConfigMixin):
+    """Subclass of ConfigMixin for loading diffusers configuration files."""
+
+    @classmethod
+    def load_config(cls, *args: Any, **kwargs: Any) -> Dict[str, Any]:
+        """Load a diffusrs ConfigMixin configuration."""
+        cls.config_name = kwargs.pop("config_name")
+        # Diffusers doesn't provide typing info
+        return super().load_config(*args, **kwargs)  # type: ignore
+
+
+# TO DO: The loader is not thread safe!
+class ModelLoader(ModelLoaderBase):
+    """Default implementation of ModelLoaderBase."""
+
+    @inject  # can inject instances of each of the classes in the call signature
+    def __init__(
+        self,
+        app_config: InvokeAIAppConfig,
+        logger: Logger,
+        ram_cache: ModelCacheBase,
+        convert_cache: ModelConvertCacheBase,
+    ):
+        """Initialize the loader."""
+        self._app_config = app_config
+        self._logger = logger
+        self._ram_cache = ram_cache
+        self._convert_cache = convert_cache
+        self._torch_dtype = torch_dtype(choose_torch_device())
+        self._size: Optional[int] = None  # model size
+
+    def load_model(self, model_config: AnyModelConfig, submodel_type: Optional[SubModelType] = None) -> LoadedModel:
+        """
+        Return a model given its configuration.
+
+        Given a model's configuration as returned by the ModelRecordConfigStore service,
+        return a LoadedModel object that can be used for inference.
+
+        :param model config: Configuration record for this model
+        :param submodel_type: an ModelType enum indicating the portion of
+               the model to retrieve (e.g. ModelType.Vae)
+        """
+        if model_config.type == "main" and not submodel_type:
+            raise InvalidModelConfigException("submodel_type is required when loading a main model")
+
+        model_path, is_submodel_override = self._get_model_path(model_config, submodel_type)
+        if is_submodel_override:
+            submodel_type = None
+
+        if not model_path.exists():
+            raise InvalidModelConfigException(f"Files for model 'model_config.name' not found at {model_path}")
+
+        model_path = self._convert_if_needed(model_config, model_path, submodel_type)
+        locker = self._load_if_needed(model_config, model_path, submodel_type)
+        return LoadedModel(config=model_config, locker=locker)
+
+    # IMPORTANT: This needs to be overridden in the StableDiffusion subclass so as to handle vae overrides
+    # and submodels!!!!
+    def _get_model_path(
+        self, config: AnyModelConfig, submodel_type: Optional[SubModelType] = None
+    ) -> Tuple[Path, bool]:
+        model_base = self._app_config.models_path
+        return ((model_base / config.path).resolve(), False)
+
+    def _convert_if_needed(
+        self, config: AnyModelConfig, model_path: Path, submodel_type: Optional[SubModelType] = None
+    ) -> Path:
+        if not self._needs_conversion(config):
+            return model_path
+
+        self._convert_cache.make_room(self._size or self.get_size_fs(config, model_path, submodel_type))
+        cache_path: Path = self._convert_cache.cache_path(config.key)
+        if cache_path.exists():
+            return cache_path
+
+        self._convert_model(model_path, cache_path)
+        return cache_path
+
+    def _needs_conversion(self, config: AnyModelConfig) -> bool:
+        return False
+
+    def _load_if_needed(
+        self, config: AnyModelConfig, model_path: Path, submodel_type: Optional[SubModelType] = None
+    ) -> ModelLockerBase:
+        # TO DO: This is not thread safe!
+        if self._ram_cache.exists(config.key, submodel_type):
+            return self._ram_cache.get(config.key, submodel_type)
+
+        model_variant = getattr(config, "repo_variant", None)
+        self._ram_cache.make_room(self.get_size_fs(config, model_path, submodel_type))
+
+        # This is where the model is actually loaded!
+        with skip_torch_weight_init():
+            loaded_model = self._load_model(model_path, model_variant=model_variant, submodel_type=submodel_type)
+
+        self._ram_cache.put(
+            config.key,
+            submodel_type=submodel_type,
+            model=loaded_model,
+        )
+
+        return self._ram_cache.get(config.key, submodel_type)
+
+    def get_size_fs(
+        self, config: AnyModelConfig, model_path: Path, submodel_type: Optional[SubModelType] = None
+    ) -> int:
+        """Get the size of the model on disk."""
+        return calc_model_size_by_fs(
+            model_path=model_path,
+            subfolder=submodel_type.value if submodel_type else None,
+            variant=config.repo_variant if hasattr(config, "repo_variant") else None,
+        )
+
+    def _convert_model(self, model_path: Path, cache_path: Path) -> None:
+        raise NotImplementedError
+
+    def _load_model(
+        self,
+        model_path: Path,
+        model_variant: Optional[ModelRepoVariant] = None,
+        submodel_type: Optional[SubModelType] = None,
+    ) -> AnyModel:
+        raise NotImplementedError
+
+    def _load_diffusers_config(self, model_path: Path, config_name: str = "config.json") -> Dict[str, Any]:
+        return ConfigLoader.load_config(model_path, config_name=config_name)
+
+    # TO DO: Add exception handling
+    def _hf_definition_to_type(self, module: str, class_name: str) -> ModelMixin:  # fix with correct type
+        if module in ["diffusers", "transformers"]:
+            res_type = sys.modules[module]
+        else:
+            res_type = sys.modules["diffusers"].pipelines
+        result: ModelMixin = getattr(res_type, class_name)
+        return result
+
+    # TO DO: Add exception handling
+    def _get_hf_load_class(self, model_path: Path, submodel_type: Optional[SubModelType] = None) -> ModelMixin:
+        if submodel_type:
+            config = self._load_diffusers_config(model_path, config_name="model_index.json")
+            module, class_name = config[submodel_type.value]
+            return self._hf_definition_to_type(module=module, class_name=class_name)
+        else:
+            config = self._load_diffusers_config(model_path, config_name="config.json")
+            class_name = config["_class_name"]
+            return self._hf_definition_to_type(module="diffusers", class_name=class_name)
diff --git a/invokeai/backend/model_manager/load/memory_snapshot.py b/invokeai/backend/model_manager/load/memory_snapshot.py
new file mode 100644
index 0000000000..504829a427
--- /dev/null
+++ b/invokeai/backend/model_manager/load/memory_snapshot.py
@@ -0,0 +1,100 @@
+import gc
+from typing import Optional
+
+import psutil
+import torch
+from typing_extensions import Self
+
+from invokeai.backend.model_management.libc_util import LibcUtil, Struct_mallinfo2
+
+GB = 2**30  # 1 GB
+
+
+class MemorySnapshot:
+    """A snapshot of RAM and VRAM usage. All values are in bytes."""
+
+    def __init__(self, process_ram: int, vram: Optional[int], malloc_info: Optional[Struct_mallinfo2]):
+        """Initialize a MemorySnapshot.
+
+        Most of the time, `MemorySnapshot` will be constructed with `MemorySnapshot.capture()`.
+
+        Args:
+            process_ram (int): CPU RAM used by the current process.
+            vram (Optional[int]): VRAM used by torch.
+            malloc_info (Optional[Struct_mallinfo2]): Malloc info obtained from LibcUtil.
+        """
+        self.process_ram = process_ram
+        self.vram = vram
+        self.malloc_info = malloc_info
+
+    @classmethod
+    def capture(cls, run_garbage_collector: bool = True) -> Self:
+        """Capture and return a MemorySnapshot.
+
+        Note: This function has significant overhead, particularly if `run_garbage_collector == True`.
+
+        Args:
+            run_garbage_collector (bool, optional): If true, gc.collect() will be run before checking the process RAM
+                usage. Defaults to True.
+
+        Returns:
+            MemorySnapshot
+        """
+        if run_garbage_collector:
+            gc.collect()
+
+        # According to the psutil docs (https://psutil.readthedocs.io/en/latest/#psutil.Process.memory_info), rss is
+        # supported on all platforms.
+        process_ram = psutil.Process().memory_info().rss
+
+        if torch.cuda.is_available():
+            vram = torch.cuda.memory_allocated()
+        else:
+            # TODO: We could add support for mps.current_allocated_memory() as well. Leaving out for now until we have
+            # time to test it properly.
+            vram = None
+
+        try:
+            malloc_info = LibcUtil().mallinfo2()  # type: ignore
+        except (OSError, AttributeError):
+            # OSError: This is expected in environments that do not have the 'libc.so.6' shared library.
+            # AttributeError: This is expected in environments that have `libc.so.6` but do not have the `mallinfo2` (e.g. glibc < 2.33)
+            # TODO: Does `mallinfo` work?
+            malloc_info = None
+
+        return cls(process_ram, vram, malloc_info)
+
+
+def get_pretty_snapshot_diff(snapshot_1: Optional[MemorySnapshot], snapshot_2: Optional[MemorySnapshot]) -> str:
+    """Get a pretty string describing the difference between two `MemorySnapshot`s."""
+
+    def get_msg_line(prefix: str, val1: int, val2: int) -> str:
+        diff = val2 - val1
+        return f"{prefix: <30} ({(diff/GB):+5.3f}): {(val1/GB):5.3f}GB -> {(val2/GB):5.3f}GB\n"
+
+    msg = ""
+
+    if snapshot_1 is None or snapshot_2 is None:
+        return msg
+
+    msg += get_msg_line("Process RAM", snapshot_1.process_ram, snapshot_2.process_ram)
+
+    if snapshot_1.malloc_info is not None and snapshot_2.malloc_info is not None:
+        msg += get_msg_line("libc mmap allocated", snapshot_1.malloc_info.hblkhd, snapshot_2.malloc_info.hblkhd)
+
+        msg += get_msg_line("libc arena used", snapshot_1.malloc_info.uordblks, snapshot_2.malloc_info.uordblks)
+
+        msg += get_msg_line("libc arena free", snapshot_1.malloc_info.fordblks, snapshot_2.malloc_info.fordblks)
+
+        libc_total_allocated_1 = snapshot_1.malloc_info.arena + snapshot_1.malloc_info.hblkhd
+        libc_total_allocated_2 = snapshot_2.malloc_info.arena + snapshot_2.malloc_info.hblkhd
+        msg += get_msg_line("libc total allocated", libc_total_allocated_1, libc_total_allocated_2)
+
+        libc_total_used_1 = snapshot_1.malloc_info.uordblks + snapshot_1.malloc_info.hblkhd
+        libc_total_used_2 = snapshot_2.malloc_info.uordblks + snapshot_2.malloc_info.hblkhd
+        msg += get_msg_line("libc total used", libc_total_used_1, libc_total_used_2)
+
+    if snapshot_1.vram is not None and snapshot_2.vram is not None:
+        msg += get_msg_line("VRAM", snapshot_1.vram, snapshot_2.vram)
+
+    return msg
diff --git a/invokeai/backend/model_manager/load/model_util.py b/invokeai/backend/model_manager/load/model_util.py
new file mode 100644
index 0000000000..18407cbca2
--- /dev/null
+++ b/invokeai/backend/model_manager/load/model_util.py
@@ -0,0 +1,109 @@
+# Copyright (c) 2024 The InvokeAI Development Team
+"""Various utility functions needed by the loader and caching system."""
+
+import json
+from pathlib import Path
+from typing import Optional, Union
+
+import torch
+from diffusers import DiffusionPipeline
+
+from invokeai.backend.model_manager.onnx_runtime import IAIOnnxRuntimeModel
+
+
+def calc_model_size_by_data(model: Union[DiffusionPipeline, torch.nn.Module, IAIOnnxRuntimeModel]) -> int:
+    """Get size of a model in memory in bytes."""
+    if isinstance(model, DiffusionPipeline):
+        return _calc_pipeline_by_data(model)
+    elif isinstance(model, torch.nn.Module):
+        return _calc_model_by_data(model)
+    elif isinstance(model, IAIOnnxRuntimeModel):
+        return _calc_onnx_model_by_data(model)
+    else:
+        return 0
+
+
+def _calc_pipeline_by_data(pipeline: DiffusionPipeline) -> int:
+    res = 0
+    assert hasattr(pipeline, "components")
+    for submodel_key in pipeline.components.keys():
+        submodel = getattr(pipeline, submodel_key)
+        if submodel is not None and isinstance(submodel, torch.nn.Module):
+            res += _calc_model_by_data(submodel)
+    return res
+
+
+def _calc_model_by_data(model: torch.nn.Module) -> int:
+    mem_params = sum([param.nelement() * param.element_size() for param in model.parameters()])
+    mem_bufs = sum([buf.nelement() * buf.element_size() for buf in model.buffers()])
+    mem: int = mem_params + mem_bufs  # in bytes
+    return mem
+
+
+def _calc_onnx_model_by_data(model: IAIOnnxRuntimeModel) -> int:
+    tensor_size = model.tensors.size() * 2  # The session doubles this
+    mem = tensor_size  # in bytes
+    return mem
+
+
+def calc_model_size_by_fs(model_path: Path, subfolder: Optional[str] = None, variant: Optional[str] = None) -> int:
+    """Estimate the size of a model on disk in bytes."""
+    if subfolder is not None:
+        model_path = model_path / subfolder
+
+    # this can happen when, for example, the safety checker is not downloaded.
+    if not model_path.exists():
+        return 0
+
+    all_files = [f for f in model_path.iterdir() if (model_path / f).is_file()]
+
+    fp16_files = {f for f in all_files if ".fp16." in f.name or ".fp16-" in f.name}
+    bit8_files = {f for f in all_files if ".8bit." in f.name or ".8bit-" in f.name}
+    other_files = set(all_files) - fp16_files - bit8_files
+
+    if variant is None:
+        files = other_files
+    elif variant == "fp16":
+        files = fp16_files
+    elif variant == "8bit":
+        files = bit8_files
+    else:
+        raise NotImplementedError(f"Unknown variant: {variant}")
+
+    # try read from index if exists
+    index_postfix = ".index.json"
+    if variant is not None:
+        index_postfix = f".index.{variant}.json"
+
+    for file in files:
+        if not file.name.endswith(index_postfix):
+            continue
+        try:
+            with open(model_path / file, "r") as f:
+                index_data = json.loads(f.read())
+            return int(index_data["metadata"]["total_size"])
+        except Exception:
+            pass
+
+    # calculate files size if there is no index file
+    formats = [
+        (".safetensors",),  # safetensors
+        (".bin",),  # torch
+        (".onnx", ".pb"),  # onnx
+        (".msgpack",),  # flax
+        (".ckpt",),  # tf
+        (".h5",),  # tf2
+    ]
+
+    for file_format in formats:
+        model_files = [f for f in files if f.suffix in file_format]
+        if len(model_files) == 0:
+            continue
+
+        model_size = 0
+        for model_file in model_files:
+            file_stats = (model_path / model_file).stat()
+            model_size += file_stats.st_size
+        return model_size
+
+    return 0  # scheduler/feature_extractor/tokenizer - models without loading to gpu
diff --git a/invokeai/backend/model_manager/load/optimizations.py b/invokeai/backend/model_manager/load/optimizations.py
new file mode 100644
index 0000000000..a46d262175
--- /dev/null
+++ b/invokeai/backend/model_manager/load/optimizations.py
@@ -0,0 +1,30 @@
+from contextlib import contextmanager
+
+import torch
+
+
+def _no_op(*args, **kwargs):
+    pass
+
+
+@contextmanager
+def skip_torch_weight_init():
+    """A context manager that monkey-patches several of the common torch layers (torch.nn.Linear, torch.nn.Conv1d, etc.)
+    to skip weight initialization.
+
+    By default, `torch.nn.Linear` and `torch.nn.ConvNd` layers initialize their weights (according to a particular
+    distribution) when __init__ is called. This weight initialization step can take a significant amount of time, and is
+    completely unnecessary if the intent is to load checkpoint weights from disk for the layer. This context manager
+    monkey-patches common torch layers to skip the weight initialization step.
+    """
+    torch_modules = [torch.nn.Linear, torch.nn.modules.conv._ConvNd, torch.nn.Embedding]
+    saved_functions = [m.reset_parameters for m in torch_modules]
+
+    try:
+        for torch_module in torch_modules:
+            torch_module.reset_parameters = _no_op
+
+        yield None
+    finally:
+        for torch_module, saved_function in zip(torch_modules, saved_functions, strict=True):
+            torch_module.reset_parameters = saved_function
diff --git a/invokeai/backend/model_manager/load/ram_cache/__init__.py b/invokeai/backend/model_manager/load/ram_cache/__init__.py
new file mode 100644
index 0000000000..e69de29bb2
diff --git a/invokeai/backend/model_manager/load/ram_cache/ram_cache_base.py b/invokeai/backend/model_manager/load/ram_cache/ram_cache_base.py
new file mode 100644
index 0000000000..cd80d1e78b
--- /dev/null
+++ b/invokeai/backend/model_manager/load/ram_cache/ram_cache_base.py
@@ -0,0 +1,145 @@
+# Copyright (c) 2024 Lincoln D. Stein and the InvokeAI Development team
+# TODO: Add Stalker's proper name to copyright
+"""
+Manage a RAM cache of diffusion/transformer models for fast switching.
+They are moved between GPU VRAM and CPU RAM as necessary. If the cache
+grows larger than a preset maximum, then the least recently used
+model will be cleared and (re)loaded from disk when next needed.
+"""
+
+from abc import ABC, abstractmethod
+from dataclasses import dataclass, field
+from logging import Logger
+from typing import Dict, Optional
+
+import torch
+
+from invokeai.backend.model_manager import SubModelType
+from invokeai.backend.model_manager.load.load_base import AnyModel, ModelLockerBase
+
+
+@dataclass
+class CacheStats(object):
+    """Data object to record statistics on cache hits/misses."""
+
+    hits: int = 0  # cache hits
+    misses: int = 0  # cache misses
+    high_watermark: int = 0  # amount of cache used
+    in_cache: int = 0  # number of models in cache
+    cleared: int = 0  # number of models cleared to make space
+    cache_size: int = 0  # total size of cache
+    loaded_model_sizes: Dict[str, int] = field(default_factory=dict)
+
+
+@dataclass
+class CacheRecord:
+    """Elements of the cache."""
+
+    key: str
+    model: AnyModel
+    size: int
+    _locks: int = 0
+
+    def lock(self) -> None:
+        """Lock this record."""
+        self._locks += 1
+
+    def unlock(self) -> None:
+        """Unlock this record."""
+        self._locks -= 1
+        assert self._locks >= 0
+
+    @property
+    def locked(self) -> bool:
+        """Return true if record is locked."""
+        return self._locks > 0
+
+
+class ModelCacheBase(ABC):
+    """Virtual base class for RAM model cache."""
+
+    @property
+    @abstractmethod
+    def storage_device(self) -> torch.device:
+        """Return the storage device (e.g. "CPU" for RAM)."""
+        pass
+
+    @property
+    @abstractmethod
+    def execution_device(self) -> torch.device:
+        """Return the exection device (e.g. "cuda" for VRAM)."""
+        pass
+
+    @property
+    @abstractmethod
+    def lazy_offloading(self) -> bool:
+        """Return true if the cache is configured to lazily offload models in VRAM."""
+        pass
+
+    @abstractmethod
+    def offload_unlocked_models(self) -> None:
+        """Offload from VRAM any models not actively in use."""
+        pass
+
+    @abstractmethod
+    def move_model_to_device(self, cache_entry: CacheRecord, device: torch.device) -> None:
+        """Move model into the indicated device."""
+        pass
+
+    @property
+    @abstractmethod
+    def logger(self) -> Logger:
+        """Return the logger used by the cache."""
+        pass
+
+    @abstractmethod
+    def make_room(self, size: int) -> None:
+        """Make enough room in the cache to accommodate a new model of indicated size."""
+        pass
+
+    @abstractmethod
+    def put(
+        self,
+        key: str,
+        model: AnyModel,
+        submodel_type: Optional[SubModelType] = None,
+    ) -> None:
+        """Store model under key and optional submodel_type."""
+        pass
+
+    @abstractmethod
+    def get(
+        self,
+        key: str,
+        submodel_type: Optional[SubModelType] = None,
+    ) -> ModelLockerBase:
+        """
+        Retrieve model locker object using key and optional submodel_type.
+
+        This may return an UnknownModelException if the model is not in the cache.
+        """
+        pass
+
+    @abstractmethod
+    def exists(
+        self,
+        key: str,
+        submodel_type: Optional[SubModelType] = None,
+    ) -> bool:
+        """Return true if the model identified by key and submodel_type is in the cache."""
+        pass
+
+    @abstractmethod
+    def cache_size(self) -> int:
+        """Get the total size of the models currently cached."""
+        pass
+
+    @abstractmethod
+    def get_stats(self) -> CacheStats:
+        """Return cache hit/miss/size statistics."""
+        pass
+
+    @abstractmethod
+    def print_cuda_stats(self) -> None:
+        """Log debugging information on CUDA usage."""
+        pass
diff --git a/invokeai/backend/model_manager/load/ram_cache/ram_cache_default.py b/invokeai/backend/model_manager/load/ram_cache/ram_cache_default.py
new file mode 100644
index 0000000000..bd43e978c8
--- /dev/null
+++ b/invokeai/backend/model_manager/load/ram_cache/ram_cache_default.py
@@ -0,0 +1,332 @@
+# Copyright (c) 2024 Lincoln D. Stein and the InvokeAI Development team
+# TODO: Add Stalker's proper name to copyright
+"""
+Manage a RAM cache of diffusion/transformer models for fast switching.
+They are moved between GPU VRAM and CPU RAM as necessary. If the cache
+grows larger than a preset maximum, then the least recently used
+model will be cleared and (re)loaded from disk when next needed.
+
+The cache returns context manager generators designed to load the
+model into the GPU within the context, and unload outside the
+context. Use like this:
+
+   cache = ModelCache(max_cache_size=7.5)
+   with cache.get_model('runwayml/stable-diffusion-1-5') as SD1,
+          cache.get_model('stabilityai/stable-diffusion-2') as SD2:
+       do_something_in_GPU(SD1,SD2)
+
+
+"""
+
+import math
+import time
+from contextlib import suppress
+from logging import Logger
+from typing import Any, Dict, List, Optional
+
+import torch
+
+from invokeai.app.services.model_records import UnknownModelException
+from invokeai.backend.model_manager import SubModelType
+from invokeai.backend.model_manager.load.load_base import AnyModel, ModelLockerBase
+from invokeai.backend.model_manager.load.memory_snapshot import MemorySnapshot, get_pretty_snapshot_diff
+from invokeai.backend.model_manager.load.model_util import calc_model_size_by_data
+from invokeai.backend.model_manager.load.ram_cache.ram_cache_base import CacheRecord, CacheStats, ModelCacheBase
+from invokeai.backend.util.devices import choose_torch_device
+from invokeai.backend.util.logging import InvokeAILogger
+
+if choose_torch_device() == torch.device("mps"):
+    from torch import mps
+
+# Maximum size of the cache, in gigs
+# Default is roughly enough to hold three fp16 diffusers models in RAM simultaneously
+DEFAULT_MAX_CACHE_SIZE = 6.0
+
+# amount of GPU memory to hold in reserve for use by generations (GB)
+DEFAULT_MAX_VRAM_CACHE_SIZE = 2.75
+
+# actual size of a gig
+GIG = 1073741824
+
+# Size of a MB in bytes.
+MB = 2**20
+
+
+class ModelCache(ModelCacheBase):
+    """Implementation of ModelCacheBase."""
+
+    def __init__(
+        self,
+        max_cache_size: float = DEFAULT_MAX_CACHE_SIZE,
+        max_vram_cache_size: float = DEFAULT_MAX_VRAM_CACHE_SIZE,
+        execution_device: torch.device = torch.device("cuda"),
+        storage_device: torch.device = torch.device("cpu"),
+        precision: torch.dtype = torch.float16,
+        sequential_offload: bool = False,
+        lazy_offloading: bool = True,
+        sha_chunksize: int = 16777216,
+        log_memory_usage: bool = False,
+        logger: Optional[Logger] = None,
+    ):
+        """
+        Initialize the model RAM cache.
+
+        :param max_cache_size: Maximum size of the RAM cache [6.0 GB]
+        :param execution_device: Torch device to load active model into [torch.device('cuda')]
+        :param storage_device: Torch device to save inactive model in [torch.device('cpu')]
+        :param precision: Precision for loaded models [torch.float16]
+        :param lazy_offloading: Keep model in VRAM until another model needs to be loaded
+        :param sequential_offload: Conserve VRAM by loading and unloading each stage of the pipeline sequentially
+        :param log_memory_usage: If True, a memory snapshot will be captured before and after every model cache
+            operation, and the result will be logged (at debug level). There is a time cost to capturing the memory
+            snapshots, so it is recommended to disable this feature unless you are actively inspecting the model cache's
+            behaviour.
+        """
+        # allow lazy offloading only when vram cache enabled
+        self._lazy_offloading = lazy_offloading and max_vram_cache_size > 0
+        self._precision: torch.dtype = precision
+        self._max_cache_size: float = max_cache_size
+        self._max_vram_cache_size: float = max_vram_cache_size
+        self._execution_device: torch.device = execution_device
+        self._storage_device: torch.device = storage_device
+        self._logger = logger or InvokeAILogger.get_logger(self.__class__.__name__)
+        self._log_memory_usage = log_memory_usage
+
+        # used for stats collection
+        self.stats = None
+
+        self._cached_models: Dict[str, CacheRecord] = {}
+        self._cache_stack: List[str] = []
+
+    class ModelLocker(ModelLockerBase):
+        """Internal class that mediates movement in and out of GPU."""
+
+        def __init__(self, cache: ModelCacheBase, cache_entry: CacheRecord):
+            """
+            Initialize the model locker.
+
+            :param cache: The ModelCache object
+            :param cache_entry: The entry in the model cache
+            """
+            self._cache = cache
+            self._cache_entry = cache_entry
+
+        @property
+        def model(self) -> AnyModel:
+            """Return the model without moving it around."""
+            return self._cache_entry.model
+
+        def lock(self) -> Any:
+            """Move the model into the execution device (GPU) and lock it."""
+            if not hasattr(self.model, "to"):
+                return self.model
+
+            # NOTE that the model has to have the to() method in order for this code to move it into GPU!
+            self._cache_entry.lock()
+
+            try:
+                if self._cache.lazy_offloading:
+                    self._cache.offload_unlocked_models()
+
+                self._cache.move_model_to_device(self._cache_entry, self._cache.execution_device)
+
+                self._cache.logger.debug(f"Locking {self._cache_entry.key} in {self._cache.execution_device}")
+                self._cache.print_cuda_stats()
+
+            except Exception:
+                self._cache_entry.unlock()
+                raise
+            return self.model
+
+        def unlock(self) -> None:
+            """Call upon exit from context."""
+            if not hasattr(self.model, "to"):
+                return
+
+            self._cache_entry.unlock()
+            if not self._cache.lazy_offloading:
+                self._cache.offload_unlocked_models()
+                self._cache.print_cuda_stats()
+
+    @property
+    def logger(self) -> Logger:
+        """Return the logger used by the cache."""
+        return self._logger
+
+    @property
+    def lazy_offloading(self) -> bool:
+        """Return true if the cache is configured to lazily offload models in VRAM."""
+        return self._lazy_offloading
+
+    @property
+    def storage_device(self) -> torch.device:
+        """Return the storage device (e.g. "CPU" for RAM)."""
+        return self._storage_device
+
+    @property
+    def execution_device(self) -> torch.device:
+        """Return the exection device (e.g. "cuda" for VRAM)."""
+        return self._execution_device
+
+    def cache_size(self) -> int:
+        """Get the total size of the models currently cached."""
+        total = 0
+        for cache_record in self._cached_models.values():
+            total += cache_record.size
+        return total
+
+    def exists(
+        self,
+        key: str,
+        submodel_type: Optional[SubModelType] = None,
+    ) -> bool:
+        """Return true if the model identified by key and submodel_type is in the cache."""
+        key = self._make_cache_key(key, submodel_type)
+        return key in self._cached_models
+
+    def put(
+        self,
+        key: str,
+        model: AnyModel,
+        submodel_type: Optional[SubModelType] = None,
+    ) -> None:
+        """Store model under key and optional submodel_type."""
+        key = self._make_cache_key(key, submodel_type)
+        assert key not in self._cached_models
+
+        loaded_model_size = calc_model_size_by_data(model)
+        cache_record = CacheRecord(key, model, loaded_model_size)
+        self._cached_models[key] = cache_record
+        self._cache_stack.append(key)
+
+    def get(
+        self,
+        key: str,
+        submodel_type: Optional[SubModelType] = None,
+    ) -> ModelLockerBase:
+        """
+        Retrieve model using key and optional submodel_type.
+
+        This may return an UnknownModelException if the model is not in the cache.
+        """
+        key = self._make_cache_key(key, submodel_type)
+        if key not in self._cached_models:
+            raise UnknownModelException
+
+        # this moves the entry to the top (right end) of the stack
+        with suppress(Exception):
+            self._cache_stack.remove(key)
+        self._cache_stack.append(key)
+        cache_entry = self._cached_models[key]
+        return self.ModelLocker(
+            cache=self,
+            cache_entry=cache_entry,
+        )
+
+    def _capture_memory_snapshot(self) -> Optional[MemorySnapshot]:
+        if self._log_memory_usage:
+            return MemorySnapshot.capture()
+        return None
+
+    def _make_cache_key(self, model_key: str, submodel_type: Optional[SubModelType] = None) -> str:
+        if submodel_type:
+            return f"{model_key}:{submodel_type.value}"
+        else:
+            return model_key
+
+    def offload_unlocked_models(self) -> None:
+        """Move any unused models from VRAM."""
+        reserved = self._max_vram_cache_size * GIG
+        vram_in_use = torch.cuda.memory_allocated()
+        self.logger.debug(f"{(vram_in_use/GIG):.2f}GB VRAM used for models; max allowed={(reserved/GIG):.2f}GB")
+        for _, cache_entry in sorted(self._cached_models.items(), key=lambda x: x[1].size):
+            if vram_in_use <= reserved:
+                break
+            if not cache_entry.locked:
+                self.move_model_to_device(cache_entry, self.storage_device)
+
+                vram_in_use = torch.cuda.memory_allocated()
+                self.logger.debug(f"{(vram_in_use/GIG):.2f}GB VRAM used for models; max allowed={(reserved/GIG):.2f}GB")
+
+        torch.cuda.empty_cache()
+        if choose_torch_device() == torch.device("mps"):
+            mps.empty_cache()
+
+    # TO DO: Only reason to pass the CacheRecord rather than the model is to get the key and size
+    # for printing debugging messages. Revisit whether this is necessary
+    def move_model_to_device(self, cache_entry: CacheRecord, target_device: torch.device) -> None:
+        """Move model into the indicated device."""
+        # These attributes are not in the base class but in derived classes
+        assert hasattr(cache_entry.model, "device")
+        assert hasattr(cache_entry.model, "to")
+
+        source_device = cache_entry.model.device
+
+        # Note: We compare device types only so that 'cuda' == 'cuda:0'. This would need to be revised to support
+        # multi-GPU.
+        if torch.device(source_device).type == torch.device(target_device).type:
+            return
+
+        start_model_to_time = time.time()
+        snapshot_before = self._capture_memory_snapshot()
+        cache_entry.model.to(target_device)
+        snapshot_after = self._capture_memory_snapshot()
+        end_model_to_time = time.time()
+        self.logger.debug(
+            f"Moved model '{cache_entry.key}' from {source_device} to"
+            f" {target_device} in {(end_model_to_time-start_model_to_time):.2f}s.\n"
+            f"Estimated model size: {(cache_entry.size/GIG):.3f} GB.\n"
+            f"{get_pretty_snapshot_diff(snapshot_before, snapshot_after)}"
+        )
+
+        if (
+            snapshot_before is not None
+            and snapshot_after is not None
+            and snapshot_before.vram is not None
+            and snapshot_after.vram is not None
+        ):
+            vram_change = abs(snapshot_before.vram - snapshot_after.vram)
+
+            # If the estimated model size does not match the change in VRAM, log a warning.
+            if not math.isclose(
+                vram_change,
+                cache_entry.size,
+                rel_tol=0.1,
+                abs_tol=10 * MB,
+            ):
+                self.logger.debug(
+                    f"Moving model '{cache_entry.key}' from {source_device} to"
+                    f" {target_device} caused an unexpected change in VRAM usage. The model's"
+                    " estimated size may be incorrect. Estimated model size:"
+                    f" {(cache_entry.size/GIG):.3f} GB.\n"
+                    f"{get_pretty_snapshot_diff(snapshot_before, snapshot_after)}"
+                )
+
+    def print_cuda_stats(self) -> None:
+        """Log CUDA diagnostics."""
+        vram = "%4.2fG" % (torch.cuda.memory_allocated() / GIG)
+        ram = "%4.2fG" % self.cache_size()
+
+        cached_models = 0
+        loaded_models = 0
+        locked_models = 0
+        for cache_record in self._cached_models.values():
+            cached_models += 1
+            assert hasattr(cache_record.model, "device")
+            if cache_record.model.device is self.storage_device:
+                loaded_models += 1
+            if cache_record.locked:
+                locked_models += 1
+
+        self.logger.debug(
+            f"Current VRAM/RAM usage: {vram}/{ram}; cached_models/loaded_models/locked_models/ ="
+            f" {cached_models}/{loaded_models}/{locked_models}"
+        )
+
+    def get_stats(self) -> CacheStats:
+        """Return cache hit/miss/size statistics."""
+        raise NotImplementedError
+
+    def make_room(self, size: int) -> None:
+        """Make enough room in the cache to accommodate a new model of indicated size."""
+        raise NotImplementedError
diff --git a/invokeai/backend/model_manager/load/vae.py b/invokeai/backend/model_manager/load/vae.py
new file mode 100644
index 0000000000..a6cbe241e1
--- /dev/null
+++ b/invokeai/backend/model_manager/load/vae.py
@@ -0,0 +1,31 @@
+# Copyright (c) 2024, Lincoln D. Stein and the InvokeAI Development Team
+"""Class for VAE model loading in InvokeAI."""
+
+from pathlib import Path
+from typing import Dict, Optional
+
+import torch
+
+from invokeai.backend.model_manager import BaseModelType, ModelFormat, ModelRepoVariant, ModelType, SubModelType
+from invokeai.backend.model_manager.load.load_base import AnyModelLoader
+from invokeai.backend.model_manager.load.load_default import ModelLoader
+
+
+@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.Vae, format=ModelFormat.Diffusers)
+class VaeDiffusersModel(ModelLoader):
+    """Class to load VAE models."""
+
+    def _load_model(
+        self,
+        model_path: Path,
+        model_variant: Optional[ModelRepoVariant] = None,
+        submodel_type: Optional[SubModelType] = None,
+    ) -> Dict[str, torch.Tensor]:
+        if submodel_type is not None:
+            raise Exception("There are no submodels in VAEs")
+        vae_class = self._get_hf_load_class(model_path)
+        variant = model_variant.value if model_variant else ""
+        result: Dict[str, torch.Tensor] = vae_class.from_pretrained(
+            model_path, torch_dtype=self._torch_dtype, variant=variant
+        )  # type: ignore
+        return result
diff --git a/invokeai/backend/model_manager/onnx_runtime.py b/invokeai/backend/model_manager/onnx_runtime.py
new file mode 100644
index 0000000000..f79fa01569
--- /dev/null
+++ b/invokeai/backend/model_manager/onnx_runtime.py
@@ -0,0 +1,216 @@
+# Copyright (c) 2024 The InvokeAI Development Team
+import os
+import sys
+from pathlib import Path
+from typing import Any, List, Optional, Tuple, Union
+
+import numpy as np
+import onnx
+from onnx import numpy_helper
+from onnxruntime import InferenceSession, SessionOptions, get_available_providers
+
+ONNX_WEIGHTS_NAME = "model.onnx"
+
+
+# NOTE FROM LS: This was copied from Stalker's original implementation.
+# I have not yet gone through and fixed all the type hints
+class IAIOnnxRuntimeModel:
+    class _tensor_access:
+        def __init__(self, model):  # type: ignore
+            self.model = model
+            self.indexes = {}
+            for idx, obj in enumerate(self.model.proto.graph.initializer):
+                self.indexes[obj.name] = idx
+
+        def __getitem__(self, key: str):  # type: ignore
+            value = self.model.proto.graph.initializer[self.indexes[key]]
+            return numpy_helper.to_array(value)
+
+        def __setitem__(self, key: str, value: np.ndarray):  # type: ignore
+            new_node = numpy_helper.from_array(value)
+            # set_external_data(new_node, location="in-memory-location")
+            new_node.name = key
+            # new_node.ClearField("raw_data")
+            del self.model.proto.graph.initializer[self.indexes[key]]
+            self.model.proto.graph.initializer.insert(self.indexes[key], new_node)
+            # self.model.data[key] = OrtValue.ortvalue_from_numpy(value)
+
+        # __delitem__
+
+        def __contains__(self, key: str) -> bool:
+            return self.indexes[key] in self.model.proto.graph.initializer
+
+        def items(self) -> List[Tuple[str, Any]]:  # fixme
+            raise NotImplementedError("tensor.items")
+            # return [(obj.name, obj) for obj in self.raw_proto]
+
+        def keys(self) -> List[str]:
+            return list(self.indexes.keys())
+
+        def values(self) -> List[Any]:  # fixme
+            raise NotImplementedError("tensor.values")
+            # return [obj for obj in self.raw_proto]
+
+        def size(self) -> int:
+            bytesSum = 0
+            for node in self.model.proto.graph.initializer:
+                bytesSum += sys.getsizeof(node.raw_data)
+            return bytesSum
+
+    class _access_helper:
+        def __init__(self, raw_proto):  # type: ignore
+            self.indexes = {}
+            self.raw_proto = raw_proto
+            for idx, obj in enumerate(raw_proto):
+                self.indexes[obj.name] = idx
+
+        def __getitem__(self, key: str):  # type: ignore
+            return self.raw_proto[self.indexes[key]]
+
+        def __setitem__(self, key: str, value):  # type: ignore
+            index = self.indexes[key]
+            del self.raw_proto[index]
+            self.raw_proto.insert(index, value)
+
+        # __delitem__
+
+        def __contains__(self, key: str) -> bool:
+            return key in self.indexes
+
+        def items(self) -> List[Tuple[str, Any]]:
+            return [(obj.name, obj) for obj in self.raw_proto]
+
+        def keys(self) -> List[str]:
+            return list(self.indexes.keys())
+
+        def values(self) -> List[Any]:  # fixme
+            return list(self.raw_proto)
+
+    def __init__(self, model_path: str, provider: Optional[str]):
+        self.path = model_path
+        self.session = None
+        self.provider = provider
+        """
+        self.data_path = self.path + "_data"
+        if not os.path.exists(self.data_path):
+            print(f"Moving model tensors to separate file: {self.data_path}")
+            tmp_proto = onnx.load(model_path, load_external_data=True)
+            onnx.save_model(tmp_proto, self.path, save_as_external_data=True, all_tensors_to_one_file=True, location=os.path.basename(self.data_path), size_threshold=1024, convert_attribute=False)
+            del tmp_proto
+            gc.collect()
+
+        self.proto = onnx.load(model_path, load_external_data=False)
+        """
+
+        self.proto = onnx.load(model_path, load_external_data=True)
+        # self.data = dict()
+        # for tensor in self.proto.graph.initializer:
+        #     name = tensor.name
+
+        #     if tensor.HasField("raw_data"):
+        #         npt = numpy_helper.to_array(tensor)
+        #         orv = OrtValue.ortvalue_from_numpy(npt)
+        #         # self.data[name] = orv
+        #         # set_external_data(tensor, location="in-memory-location")
+        #         tensor.name = name
+        #         # tensor.ClearField("raw_data")
+
+        self.nodes = self._access_helper(self.proto.graph.node)  # type: ignore
+        # self.initializers = self._access_helper(self.proto.graph.initializer)
+        # print(self.proto.graph.input)
+        # print(self.proto.graph.initializer)
+
+        self.tensors = self._tensor_access(self)  # type: ignore
+
+    # TODO: integrate with model manager/cache
+    def create_session(self, height=None, width=None):
+        if self.session is None or self.session_width != width or self.session_height != height:
+            # onnx.save(self.proto, "tmp.onnx")
+            # onnx.save_model(self.proto, "tmp.onnx", save_as_external_data=True, all_tensors_to_one_file=True, location="tmp.onnx_data", size_threshold=1024, convert_attribute=False)
+            # TODO: something to be able to get weight when they already moved outside of model proto
+            # (trimmed_model, external_data) = buffer_external_data_tensors(self.proto)
+            sess = SessionOptions()
+            # self._external_data.update(**external_data)
+            # sess.add_external_initializers(list(self.data.keys()), list(self.data.values()))
+            # sess.enable_profiling = True
+
+            # sess.intra_op_num_threads = 1
+            # sess.inter_op_num_threads = 1
+            # sess.execution_mode = ExecutionMode.ORT_SEQUENTIAL
+            # sess.graph_optimization_level = GraphOptimizationLevel.ORT_ENABLE_ALL
+            # sess.enable_cpu_mem_arena = True
+            # sess.enable_mem_pattern = True
+            # sess.add_session_config_entry("session.intra_op.use_xnnpack_threadpool", "1") ########### It's the key code
+            self.session_height = height
+            self.session_width = width
+            if height and width:
+                sess.add_free_dimension_override_by_name("unet_sample_batch", 2)
+                sess.add_free_dimension_override_by_name("unet_sample_channels", 4)
+                sess.add_free_dimension_override_by_name("unet_hidden_batch", 2)
+                sess.add_free_dimension_override_by_name("unet_hidden_sequence", 77)
+                sess.add_free_dimension_override_by_name("unet_sample_height", self.session_height)
+                sess.add_free_dimension_override_by_name("unet_sample_width", self.session_width)
+                sess.add_free_dimension_override_by_name("unet_time_batch", 1)
+            providers = []
+            if self.provider:
+                providers.append(self.provider)
+            else:
+                providers = get_available_providers()
+            if "TensorrtExecutionProvider" in providers:
+                providers.remove("TensorrtExecutionProvider")
+            try:
+                self.session = InferenceSession(self.proto.SerializeToString(), providers=providers, sess_options=sess)
+            except Exception as e:
+                raise e
+            # self.session = InferenceSession("tmp.onnx", providers=[self.provider], sess_options=self.sess_options)
+            # self.io_binding = self.session.io_binding()
+
+    def release_session(self):
+        self.session = None
+        import gc
+
+        gc.collect()
+        return
+
+    def __call__(self, **kwargs):
+        if self.session is None:
+            raise Exception("You should call create_session before running model")
+
+        inputs = {k: np.array(v) for k, v in kwargs.items()}
+        # output_names = self.session.get_outputs()
+        # for k in inputs:
+        #     self.io_binding.bind_cpu_input(k, inputs[k])
+        # for name in output_names:
+        #     self.io_binding.bind_output(name.name)
+        # self.session.run_with_iobinding(self.io_binding, None)
+        # return self.io_binding.copy_outputs_to_cpu()
+        return self.session.run(None, inputs)
+
+    # compatability with diffusers load code
+    @classmethod
+    def from_pretrained(
+        cls,
+        model_id: Union[str, Path],
+        subfolder: Optional[Union[str, Path]] = None,
+        file_name: Optional[str] = None,
+        provider: Optional[str] = None,
+        sess_options: Optional["SessionOptions"] = None,
+        **kwargs: Any,
+    ) -> Any:  # fixme
+        file_name = file_name or ONNX_WEIGHTS_NAME
+
+        if os.path.isdir(model_id):
+            model_path = model_id
+            if subfolder is not None:
+                model_path = os.path.join(model_path, subfolder)
+            model_path = os.path.join(model_path, file_name)
+
+        else:
+            model_path = model_id
+
+        # load model from local directory
+        if not os.path.isfile(model_path):
+            raise Exception(f"Model not found: {model_path}")
+
+        # TODO: session options
+        return cls(str(model_path), provider=provider)
diff --git a/invokeai/backend/model_manager/probe.py b/invokeai/backend/model_manager/probe.py
index ba3ac3dd0c..9fd118b782 100644
--- a/invokeai/backend/model_manager/probe.py
+++ b/invokeai/backend/model_manager/probe.py
@@ -18,9 +18,9 @@ from .config import (
     InvalidModelConfigException,
     ModelConfigFactory,
     ModelFormat,
+    ModelRepoVariant,
     ModelType,
     ModelVariantType,
-    ModelRepoVariant,
     SchedulerPredictionType,
 )
 from .hash import FastModelHash
@@ -483,8 +483,8 @@ class FolderProbeBase(ProbeBase):
 
     def get_repo_variant(self) -> ModelRepoVariant:
         # get all files ending in .bin or .safetensors
-        weight_files = list(self.model_path.glob('**/*.safetensors'))
-        weight_files.extend(list(self.model_path.glob('**/*.bin')))
+        weight_files = list(self.model_path.glob("**/*.safetensors"))
+        weight_files.extend(list(self.model_path.glob("**/*.bin")))
         for x in weight_files:
             if ".fp16" in x.suffixes:
                 return ModelRepoVariant.FP16
@@ -496,6 +496,7 @@ class FolderProbeBase(ProbeBase):
                 return ModelRepoVariant.ONNX
         return ModelRepoVariant.DEFAULT
 
+
 class PipelineFolderProbe(FolderProbeBase):
     def get_base_type(self) -> BaseModelType:
         with open(self.model_path / "unet" / "config.json", "r") as file:
@@ -540,7 +541,6 @@ class PipelineFolderProbe(FolderProbeBase):
         except Exception:
             pass
         return ModelVariantType.Normal
-        
 
 
 class VaeFolderProbe(FolderProbeBase):
diff --git a/tests/test_model_probe.py b/tests/test_model_probe.py
index 415559a64c..aacae06a8b 100644
--- a/tests/test_model_probe.py
+++ b/tests/test_model_probe.py
@@ -21,9 +21,10 @@ def test_get_base_type(vae_path: str, expected_type: BaseModelType, datadir: Pat
     base_type = probe.get_base_type()
     assert base_type == expected_type
     repo_variant = probe.get_repo_variant()
-    assert repo_variant == 'default'
+    assert repo_variant == "default"
+
 
 def test_repo_variant(datadir: Path):
     probe = VaeFolderProbe(datadir / "vae" / "taesdxl-fp16")
     repo_variant = probe.get_repo_variant()
-    assert repo_variant == 'fp16'
+    assert repo_variant == "fp16"

From 8ba5360269ce075e330abeb01b7a862373886a50 Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lstein@gmail.com>
Date: Sat, 3 Feb 2024 22:55:09 -0500
Subject: [PATCH 112/411] model loading and conversion implemented for vaes

---
 invokeai/app/api/dependencies.py              |   17 +-
 .../app/services/config/config_default.py     |   21 +-
 .../model_install/model_install_default.py    |    5 +-
 .../model_records/model_records_base.py       |   15 +-
 .../model_records/model_records_sql.py        |   43 +-
 .../app/services/shared/sqlite/sqlite_util.py |    2 +
 .../sqlite_migrator/migrations/migration_6.py |   44 +
 invokeai/backend/install/install_helper.py    |   11 +-
 invokeai/backend/model_manager/__init__.py    |    4 +
 invokeai/backend/model_manager/config.py      |   10 +-
 .../convert_ckpt_to_diffusers.py              | 1744 +++++++++++++++++
 .../backend/model_manager/load/__init__.py    |   35 +
 .../load/convert_cache/__init__.py            |    4 +
 .../load/convert_cache/convert_cache_base.py  |   28 +
 .../convert_cache/convert_cache_default.py    |   64 +
 .../backend/model_manager/load/load_base.py   |   72 +-
 .../model_manager/load/load_default.py        |   23 +-
 .../load/model_cache/__init__.py              |    5 +
 .../model_cache_base.py}                      |   60 +-
 .../model_cache_default.py}                   |  202 +-
 .../load/model_cache/model_locker.py          |   59 +
 .../load/model_loaders/__init__.py            |    3 +
 .../model_manager/load/model_loaders/vae.py   |   83 +
 .../backend/model_manager/load/model_util.py  |    3 +
 .../model_manager/load/ram_cache/__init__.py  |    0
 invokeai/backend/model_manager/load/vae.py    |   31 -
 invokeai/backend/util/__init__.py             |   12 +-
 invokeai/backend/util/devices.py              |    5 +-
 invokeai/backend/util/util.py                 |   14 +
 29 files changed, 2382 insertions(+), 237 deletions(-)
 create mode 100644 invokeai/app/services/shared/sqlite_migrator/migrations/migration_6.py
 create mode 100644 invokeai/backend/model_manager/convert_ckpt_to_diffusers.py
 create mode 100644 invokeai/backend/model_manager/load/convert_cache/__init__.py
 create mode 100644 invokeai/backend/model_manager/load/convert_cache/convert_cache_base.py
 create mode 100644 invokeai/backend/model_manager/load/convert_cache/convert_cache_default.py
 create mode 100644 invokeai/backend/model_manager/load/model_cache/__init__.py
 rename invokeai/backend/model_manager/load/{ram_cache/ram_cache_base.py => model_cache/model_cache_base.py} (77%)
 rename invokeai/backend/model_manager/load/{ram_cache/ram_cache_default.py => model_cache/model_cache_default.py} (63%)
 create mode 100644 invokeai/backend/model_manager/load/model_cache/model_locker.py
 create mode 100644 invokeai/backend/model_manager/load/model_loaders/__init__.py
 create mode 100644 invokeai/backend/model_manager/load/model_loaders/vae.py
 delete mode 100644 invokeai/backend/model_manager/load/ram_cache/__init__.py
 delete mode 100644 invokeai/backend/model_manager/load/vae.py

diff --git a/invokeai/app/api/dependencies.py b/invokeai/app/api/dependencies.py
index 0f2a92b5c8..dcb8d21997 100644
--- a/invokeai/app/api/dependencies.py
+++ b/invokeai/app/api/dependencies.py
@@ -8,6 +8,8 @@ from invokeai.app.services.item_storage.item_storage_memory import ItemStorageMe
 from invokeai.app.services.object_serializer.object_serializer_disk import ObjectSerializerDisk
 from invokeai.app.services.object_serializer.object_serializer_forward_cache import ObjectSerializerForwardCache
 from invokeai.app.services.shared.sqlite.sqlite_util import init_db
+from invokeai.backend.model_manager.load import AnyModelLoader, ModelConvertCache
+from invokeai.backend.model_manager.load.model_cache import ModelCache
 from invokeai.backend.model_manager.metadata import ModelMetadataStore
 from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ConditioningFieldData
 from invokeai.backend.util.logging import InvokeAILogger
@@ -98,15 +100,26 @@ class ApiDependencies:
         )
         model_manager = ModelManagerService(config, logger)
         model_record_service = ModelRecordServiceSQL(db=db)
+        model_loader = AnyModelLoader(
+            app_config=config,
+            logger=logger,
+            ram_cache=ModelCache(
+                max_cache_size=config.ram_cache_size, max_vram_cache_size=config.vram_cache_size, logger=logger
+            ),
+            convert_cache=ModelConvertCache(
+                cache_path=config.models_convert_cache_path, max_size=config.convert_cache_size
+            ),
+        )
+        model_record_service = ModelRecordServiceSQL(db=db, loader=model_loader)
         download_queue_service = DownloadQueueService(event_bus=events)
-        metadata_store = ModelMetadataStore(db=db)
         model_install_service = ModelInstallService(
             app_config=config,
             record_store=model_record_service,
             download_queue=download_queue_service,
-            metadata_store=metadata_store,
+            metadata_store=ModelMetadataStore(db=db),
             event_bus=events,
         )
+        model_manager = ModelManagerService(config, logger)  # TO DO: legacy model manager v1. Remove
         names = SimpleNameService()
         performance_statistics = InvocationStatsService()
         processor = DefaultInvocationProcessor()
diff --git a/invokeai/app/services/config/config_default.py b/invokeai/app/services/config/config_default.py
index 132afc2272..b161ea18d6 100644
--- a/invokeai/app/services/config/config_default.py
+++ b/invokeai/app/services/config/config_default.py
@@ -237,6 +237,7 @@ class InvokeAIAppConfig(InvokeAISettings):
     autoimport_dir      : Path = Field(default=Path('autoimport'), description='Path to a directory of models files to be imported on startup.', json_schema_extra=Categories.Paths)
     conf_path           : Path = Field(default=Path('configs/models.yaml'), description='Path to models definition file', json_schema_extra=Categories.Paths)
     models_dir          : Path = Field(default=Path('models'), description='Path to the models directory', json_schema_extra=Categories.Paths)
+    convert_cache_dir   : Path = Field(default=Path('models/.cache'), description='Path to the converted models cache directory', json_schema_extra=Categories.Paths)
     legacy_conf_dir     : Path = Field(default=Path('configs/stable-diffusion'), description='Path to directory of legacy checkpoint config files', json_schema_extra=Categories.Paths)
     db_dir              : Path = Field(default=Path('databases'), description='Path to InvokeAI databases directory', json_schema_extra=Categories.Paths)
     outdir              : Path = Field(default=Path('outputs'), description='Default folder for output images', json_schema_extra=Categories.Paths)
@@ -262,6 +263,8 @@ class InvokeAIAppConfig(InvokeAISettings):
     # CACHE
     ram                 : float = Field(default=7.5, gt=0, description="Maximum memory amount used by model cache for rapid switching (floating point number, GB)", json_schema_extra=Categories.ModelCache, )
     vram                : float = Field(default=0.25, ge=0, description="Amount of VRAM reserved for model storage (floating point number, GB)", json_schema_extra=Categories.ModelCache, )
+    convert_cache       : float = Field(default=10.0, ge=0, description="Maximum size of on-disk converted models cache (GB)", json_schema_extra=Categories.ModelCache)
+
     lazy_offload        : bool = Field(default=True, description="Keep models in VRAM until their space is needed", json_schema_extra=Categories.ModelCache, )
     log_memory_usage    : bool = Field(default=False, description="If True, a memory snapshot will be captured before and after every model cache operation, and the result will be logged (at debug level). There is a time cost to capturing the memory snapshots, so it is recommended to only enable this feature if you are actively inspecting the model cache's behaviour.", json_schema_extra=Categories.ModelCache)
 
@@ -404,6 +407,11 @@ class InvokeAIAppConfig(InvokeAISettings):
         """Path to the models directory."""
         return self._resolve(self.models_dir)
 
+    @property
+    def models_convert_cache_path(self) -> Path:
+        """Path to the converted cache models directory."""
+        return self._resolve(self.convert_cache_dir)
+
     @property
     def custom_nodes_path(self) -> Path:
         """Path to the custom nodes directory."""
@@ -433,15 +441,20 @@ class InvokeAIAppConfig(InvokeAISettings):
         return True
 
     @property
-    def ram_cache_size(self) -> Union[Literal["auto"], float]:
-        """Return the ram cache size using the legacy or modern setting."""
+    def ram_cache_size(self) -> float:
+        """Return the ram cache size using the legacy or modern setting (GB)."""
         return self.max_cache_size or self.ram
 
     @property
-    def vram_cache_size(self) -> Union[Literal["auto"], float]:
-        """Return the vram cache size using the legacy or modern setting."""
+    def vram_cache_size(self) -> float:
+        """Return the vram cache size using the legacy or modern setting (GB)."""
         return self.max_vram_cache_size or self.vram
 
+    @property
+    def convert_cache_size(self) -> float:
+        """Return the convert cache size on disk (GB)."""
+        return self.convert_cache
+
     @property
     def use_cpu(self) -> bool:
         """Return true if the device is set to CPU or the always_use_cpu flag is set."""
diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py
index 82c667f584..2b2294bfce 100644
--- a/invokeai/app/services/model_install/model_install_default.py
+++ b/invokeai/app/services/model_install/model_install_default.py
@@ -145,7 +145,7 @@ class ModelInstallService(ModelInstallServiceBase):
     ) -> str:  # noqa D102
         model_path = Path(model_path)
         config = config or {}
-        if config.get("source") is None:
+        if not config.get("source"):
             config["source"] = model_path.resolve().as_posix()
         return self._register(model_path, config)
 
@@ -156,7 +156,7 @@ class ModelInstallService(ModelInstallServiceBase):
     ) -> str:  # noqa D102
         model_path = Path(model_path)
         config = config or {}
-        if config.get("source") is None:
+        if not config.get("source"):
             config["source"] = model_path.resolve().as_posix()
 
         info: AnyModelConfig = self._probe_model(Path(model_path), config)
@@ -300,6 +300,7 @@ class ModelInstallService(ModelInstallServiceBase):
                     job.total_bytes = self._stat_size(job.local_path)
                     job.bytes = job.total_bytes
                     self._signal_job_running(job)
+                    job.config_in["source"] = str(job.source)
                     if job.inplace:
                         key = self.register_path(job.local_path, job.config_in)
                     else:
diff --git a/invokeai/app/services/model_records/model_records_base.py b/invokeai/app/services/model_records/model_records_base.py
index 57597570cd..31cfecb4ec 100644
--- a/invokeai/app/services/model_records/model_records_base.py
+++ b/invokeai/app/services/model_records/model_records_base.py
@@ -11,7 +11,7 @@ from typing import Any, Dict, List, Optional, Set, Tuple, Union
 from pydantic import BaseModel, Field
 
 from invokeai.app.services.shared.pagination import PaginatedResults
-from invokeai.backend.model_manager.config import AnyModelConfig, BaseModelType, ModelFormat, ModelType
+from invokeai.backend.model_manager import LoadedModel, AnyModelConfig, BaseModelType, ModelFormat, ModelType, SubModelType
 from invokeai.backend.model_manager.metadata import AnyModelRepoMetadata, ModelMetadataStore
 
 
@@ -102,6 +102,19 @@ class ModelRecordServiceBase(ABC):
         """
         pass
 
+    @abstractmethod
+    def load_model(self, key: str, submodel_type: Optional[SubModelType]) -> LoadedModel:
+        """
+        Load the indicated model into memory and return a LoadedModel object.
+
+        :param key: Key of model config to be fetched.
+        :param submodel_type: For main (pipeline models), the submodel to fetch 
+
+        Exceptions: UnknownModelException -- model with this key not known
+                    NotImplementedException -- a model loader was not provided at initialization time
+        """
+        pass
+
     @property
     @abstractmethod
     def metadata_store(self) -> ModelMetadataStore:
diff --git a/invokeai/app/services/model_records/model_records_sql.py b/invokeai/app/services/model_records/model_records_sql.py
index 4512da5d41..eee867ccb4 100644
--- a/invokeai/app/services/model_records/model_records_sql.py
+++ b/invokeai/app/services/model_records/model_records_sql.py
@@ -42,6 +42,7 @@ Typical usage:
 
 import json
 import sqlite3
+import time
 from math import ceil
 from pathlib import Path
 from typing import Any, Dict, List, Optional, Set, Tuple, Union
@@ -53,8 +54,10 @@ from invokeai.backend.model_manager.config import (
     ModelConfigFactory,
     ModelFormat,
     ModelType,
+    SubModelType,
 )
 from invokeai.backend.model_manager.metadata import AnyModelRepoMetadata, ModelMetadataStore, UnknownMetadataException
+from invokeai.backend.model_manager.load import AnyModelLoader, LoadedModel
 
 from ..shared.sqlite.sqlite_database import SqliteDatabase
 from .model_records_base import (
@@ -69,16 +72,17 @@ from .model_records_base import (
 class ModelRecordServiceSQL(ModelRecordServiceBase):
     """Implementation of the ModelConfigStore ABC using a SQL database."""
 
-    def __init__(self, db: SqliteDatabase):
+    def __init__(self, db: SqliteDatabase, loader: Optional[AnyModelLoader]=None):
         """
         Initialize a new object from preexisting sqlite3 connection and threading lock objects.
 
-        :param conn: sqlite3 connection object
-        :param lock: threading Lock object
+        :param db: Sqlite connection object
+        :param loader: Initialized model loader object (optional)
         """
         super().__init__()
         self._db = db
-        self._cursor = self._db.conn.cursor()
+        self._cursor = db.conn.cursor()
+        self._loader = loader
 
     @property
     def db(self) -> SqliteDatabase:
@@ -199,7 +203,7 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
         with self._db.lock:
             self._cursor.execute(
                 """--sql
-                SELECT config FROM model_config
+                SELECT config, strftime('%s',updated_at) FROM model_config
                 WHERE id=?;
                 """,
                 (key,),
@@ -207,9 +211,24 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
             rows = self._cursor.fetchone()
             if not rows:
                 raise UnknownModelException("model not found")
-            model = ModelConfigFactory.make_config(json.loads(rows[0]))
+            model = ModelConfigFactory.make_config(json.loads(rows[0]), timestamp=rows[1])
         return model
 
+    def load_model(self, key: str, submodel_type: Optional[SubModelType]) -> LoadedModel:
+        """
+        Load the indicated model into memory and return a LoadedModel object.
+
+        :param key: Key of model config to be fetched.
+        :param submodel_type: For main (pipeline models), the submodel to fetch.
+
+        Exceptions: UnknownModelException -- model with this key not known
+                    NotImplementedException -- a model loader was not provided at initialization time
+        """
+        if not self._loader:
+            raise NotImplementedError(f"Class {self.__class__} was not initialized with a model loader")
+        model_config = self.get_model(key)
+        return self._loader.load_model(model_config, submodel_type)
+
     def exists(self, key: str) -> bool:
         """
         Return True if a model with the indicated key exists in the databse.
@@ -265,12 +284,12 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
         with self._db.lock:
             self._cursor.execute(
                 f"""--sql
-                select config FROM model_config
+                select config, strftime('%s',updated_at) FROM model_config
                 {where};
                 """,
                 tuple(bindings),
             )
-            results = [ModelConfigFactory.make_config(json.loads(x[0])) for x in self._cursor.fetchall()]
+            results = [ModelConfigFactory.make_config(json.loads(x[0]), timestamp=x[1]) for x in self._cursor.fetchall()]
         return results
 
     def search_by_path(self, path: Union[str, Path]) -> List[AnyModelConfig]:
@@ -279,12 +298,12 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
         with self._db.lock:
             self._cursor.execute(
                 """--sql
-                SELECT config FROM model_config
+                SELECT config, strftime('%s',updated_at) FROM model_config
                 WHERE path=?;
                 """,
                 (str(path),),
             )
-            results = [ModelConfigFactory.make_config(json.loads(x[0])) for x in self._cursor.fetchall()]
+            results = [ModelConfigFactory.make_config(json.loads(x[0]), timestamp=x[1]) for x in self._cursor.fetchall()]
         return results
 
     def search_by_hash(self, hash: str) -> List[AnyModelConfig]:
@@ -293,12 +312,12 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
         with self._db.lock:
             self._cursor.execute(
                 """--sql
-                SELECT config FROM model_config
+                SELECT config, strftime('%s',updated_at) FROM model_config
                 WHERE original_hash=?;
                 """,
                 (hash,),
             )
-            results = [ModelConfigFactory.make_config(json.loads(x[0])) for x in self._cursor.fetchall()]
+            results = [ModelConfigFactory.make_config(json.loads(x[0]), timestamp=x[1]) for x in self._cursor.fetchall()]
         return results
 
     @property
diff --git a/invokeai/app/services/shared/sqlite/sqlite_util.py b/invokeai/app/services/shared/sqlite/sqlite_util.py
index 6079b3f08d..681886eacd 100644
--- a/invokeai/app/services/shared/sqlite/sqlite_util.py
+++ b/invokeai/app/services/shared/sqlite/sqlite_util.py
@@ -8,6 +8,7 @@ from invokeai.app.services.shared.sqlite_migrator.migrations.migration_2 import
 from invokeai.app.services.shared.sqlite_migrator.migrations.migration_3 import build_migration_3
 from invokeai.app.services.shared.sqlite_migrator.migrations.migration_4 import build_migration_4
 from invokeai.app.services.shared.sqlite_migrator.migrations.migration_5 import build_migration_5
+from invokeai.app.services.shared.sqlite_migrator.migrations.migration_6 import build_migration_6
 from invokeai.app.services.shared.sqlite_migrator.sqlite_migrator_impl import SqliteMigrator
 
 
@@ -33,6 +34,7 @@ def init_db(config: InvokeAIAppConfig, logger: Logger, image_files: ImageFileSto
     migrator.register_migration(build_migration_3(app_config=config, logger=logger))
     migrator.register_migration(build_migration_4())
     migrator.register_migration(build_migration_5())
+    migrator.register_migration(build_migration_6())
     migrator.run_migrations()
 
     return db
diff --git a/invokeai/app/services/shared/sqlite_migrator/migrations/migration_6.py b/invokeai/app/services/shared/sqlite_migrator/migrations/migration_6.py
new file mode 100644
index 0000000000..e72878f726
--- /dev/null
+++ b/invokeai/app/services/shared/sqlite_migrator/migrations/migration_6.py
@@ -0,0 +1,44 @@
+import sqlite3
+from logging import Logger
+
+from invokeai.app.services.config import InvokeAIAppConfig
+from invokeai.app.services.shared.sqlite_migrator.sqlite_migrator_common import Migration
+
+class Migration6Callback:
+
+    def __call__(self, cursor: sqlite3.Cursor) -> None:
+        self._recreate_model_triggers(cursor)
+
+    def _recreate_model_triggers(self, cursor: sqlite3.Cursor) -> None:
+        """
+        Adds the timestamp trigger to the model_config table.
+
+        This trigger was inadvertently dropped in earlier migration scripts.
+        """
+
+        cursor.execute(
+            """--sql
+            CREATE TRIGGER IF NOT EXISTS model_config_updated_at
+            AFTER UPDATE
+            ON model_config FOR EACH ROW
+            BEGIN
+                UPDATE model_config SET updated_at = STRFTIME('%Y-%m-%d %H:%M:%f', 'NOW')
+                    WHERE id = old.id;
+            END;
+            """
+        )
+
+def build_migration_6() -> Migration:
+    """
+    Build the migration from database version 5 to 6.
+
+    This migration does the following:
+    - Adds the model_config_updated_at trigger if it does not exist
+    """
+    migration_6 = Migration(
+        from_version=5,
+        to_version=6,
+        callback=Migration6Callback(),
+    )
+
+    return migration_6
diff --git a/invokeai/backend/install/install_helper.py b/invokeai/backend/install/install_helper.py
index e54be527d9..8c03d2ccf8 100644
--- a/invokeai/backend/install/install_helper.py
+++ b/invokeai/backend/install/install_helper.py
@@ -98,11 +98,13 @@ class TqdmEventService(EventServiceBase):
         super().__init__()
         self._bars: Dict[str, tqdm] = {}
         self._last: Dict[str, int] = {}
+        self._logger = InvokeAILogger.get_logger(__name__)
 
     def dispatch(self, event_name: str, payload: Any) -> None:
         """Dispatch an event by appending it to self.events."""
+        data = payload["data"]
+        source = data["source"]
         if payload["event"] == "model_install_downloading":
-            data = payload["data"]
             dest = data["local_path"]
             total_bytes = data["total_bytes"]
             bytes = data["bytes"]
@@ -111,7 +113,12 @@ class TqdmEventService(EventServiceBase):
                 self._last[dest] = 0
             self._bars[dest].update(bytes - self._last[dest])
             self._last[dest] = bytes
-
+        elif payload["event"] == "model_install_completed":
+            self._logger.info(f"{source}: installed successfully.")
+        elif payload["event"] == "model_install_error":
+            self._logger.warning(f"{source}: installation failed with error {data['error']}")
+        elif payload["event"] == "model_install_cancelled":
+            self._logger.warning(f"{source}: installation cancelled")
 
 class InstallHelper(object):
     """Capture information stored jointly in INITIAL_MODELS.yaml and the installed models db."""
diff --git a/invokeai/backend/model_manager/__init__.py b/invokeai/backend/model_manager/__init__.py
index 0f16852c93..f3c84cd01f 100644
--- a/invokeai/backend/model_manager/__init__.py
+++ b/invokeai/backend/model_manager/__init__.py
@@ -1,6 +1,7 @@
 """Re-export frequently-used symbols from the Model Manager backend."""
 
 from .config import (
+    AnyModel,
     AnyModelConfig,
     BaseModelType,
     InvalidModelConfigException,
@@ -14,12 +15,15 @@ from .config import (
 )
 from .probe import ModelProbe
 from .search import ModelSearch
+from .load import LoadedModel
 
 __all__ = [
+    "AnyModel",
     "AnyModelConfig",
     "BaseModelType",
     "ModelRepoVariant",
     "InvalidModelConfigException",
+    "LoadedModel",
     "ModelConfigFactory",
     "ModelFormat",
     "ModelProbe",
diff --git a/invokeai/backend/model_manager/config.py b/invokeai/backend/model_manager/config.py
index 338669c873..796ccbacde 100644
--- a/invokeai/backend/model_manager/config.py
+++ b/invokeai/backend/model_manager/config.py
@@ -19,12 +19,15 @@ Typical usage:
 Validation errors will raise an InvalidModelConfigException error.
 
 """
+import time
+import torch
 from enum import Enum
 from typing import Literal, Optional, Type, Union
 
 from pydantic import BaseModel, ConfigDict, Field, TypeAdapter
+from diffusers import ModelMixin
 from typing_extensions import Annotated, Any, Dict
-
+from .onnx_runtime import IAIOnnxRuntimeModel
 
 class InvalidModelConfigException(Exception):
     """Exception for when config parser doesn't recognized this combination of model type and format."""
@@ -127,6 +130,7 @@ class ModelConfigBase(BaseModel):
     )  # if model is converted or otherwise modified, this will hold updated hash
     description: Optional[str] = Field(default=None)
     source: Optional[str] = Field(description="Model download source (URL or repo_id)", default=None)
+    last_modified: Optional[float] = Field(description="Timestamp for modification time", default_factory=time.time)
 
     model_config = ConfigDict(
         use_enum_values=False,
@@ -280,6 +284,7 @@ AnyModelConfig = Union[
 ]
 
 AnyModelConfigValidator = TypeAdapter(AnyModelConfig)
+AnyModel = Union[ModelMixin, torch.nn.Module, IAIOnnxRuntimeModel]
 
 # IMPLEMENTATION NOTE:
 # The preferred alternative to the above is a discriminated Union as shown
@@ -312,6 +317,7 @@ class ModelConfigFactory(object):
         model_data: Union[dict, AnyModelConfig],
         key: Optional[str] = None,
         dest_class: Optional[Type] = None,
+        timestamp: Optional[float] = None
     ) -> AnyModelConfig:
         """
         Return the appropriate config object from raw dict values.
@@ -330,4 +336,6 @@ class ModelConfigFactory(object):
             model = AnyModelConfigValidator.validate_python(model_data)
         if key:
             model.key = key
+        if timestamp:
+            model.last_modified = timestamp
         return model
diff --git a/invokeai/backend/model_manager/convert_ckpt_to_diffusers.py b/invokeai/backend/model_manager/convert_ckpt_to_diffusers.py
new file mode 100644
index 0000000000..9d6fc4841f
--- /dev/null
+++ b/invokeai/backend/model_manager/convert_ckpt_to_diffusers.py
@@ -0,0 +1,1744 @@
+# coding=utf-8
+# Copyright 2023 The HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+# Adapted for use in InvokeAI by Lincoln Stein, July 2023
+#
+""" Conversion script for the Stable Diffusion checkpoints."""
+
+import re
+from contextlib import nullcontext
+from io import BytesIO
+from pathlib import Path
+from typing import Optional, Union
+
+import requests
+import torch
+from diffusers.models import AutoencoderKL, ControlNetModel, PriorTransformer, UNet2DConditionModel
+from diffusers.pipelines.latent_diffusion.pipeline_latent_diffusion import LDMBertConfig, LDMBertModel
+from diffusers.pipelines.paint_by_example import PaintByExampleImageEncoder
+from diffusers.pipelines.pipeline_utils import DiffusionPipeline
+from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
+from diffusers.pipelines.stable_diffusion.stable_unclip_image_normalizer import StableUnCLIPImageNormalizer
+from diffusers.schedulers import (
+    DDIMScheduler,
+    DDPMScheduler,
+    DPMSolverMultistepScheduler,
+    EulerAncestralDiscreteScheduler,
+    EulerDiscreteScheduler,
+    HeunDiscreteScheduler,
+    LMSDiscreteScheduler,
+    PNDMScheduler,
+    UnCLIPScheduler,
+)
+from diffusers.utils import is_accelerate_available
+from diffusers.utils.import_utils import BACKENDS_MAPPING
+from picklescan.scanner import scan_file_path
+from transformers import (
+    AutoFeatureExtractor,
+    BertTokenizerFast,
+    CLIPImageProcessor,
+    CLIPTextConfig,
+    CLIPTextModel,
+    CLIPTextModelWithProjection,
+    CLIPTokenizer,
+    CLIPVisionConfig,
+    CLIPVisionModelWithProjection,
+)
+
+from invokeai.app.services.config import InvokeAIAppConfig
+from invokeai.backend.util.logging import InvokeAILogger
+from invokeai.backend.model_manager import BaseModelType, ModelVariantType
+
+try:
+    from omegaconf import OmegaConf
+    from omegaconf.dictconfig import DictConfig
+except ImportError:
+    raise ImportError(
+        "OmegaConf is required to convert the LDM checkpoints. Please install it with `pip install OmegaConf`."
+    )
+
+if is_accelerate_available():
+    from accelerate import init_empty_weights
+    from accelerate.utils import set_module_tensor_to_device
+
+logger = InvokeAILogger.get_logger(__name__)
+CONVERT_MODEL_ROOT = InvokeAIAppConfig.get_config().models_path / "core/convert"
+
+
+def shave_segments(path, n_shave_prefix_segments=1):
+    """
+    Removes segments. Positive values shave the first segments, negative shave the last segments.
+    """
+    if n_shave_prefix_segments >= 0:
+        return ".".join(path.split(".")[n_shave_prefix_segments:])
+    else:
+        return ".".join(path.split(".")[:n_shave_prefix_segments])
+
+
+def renew_resnet_paths(old_list, n_shave_prefix_segments=0):
+    """
+    Updates paths inside resnets to the new naming scheme (local renaming)
+    """
+    mapping = []
+    for old_item in old_list:
+        new_item = old_item.replace("in_layers.0", "norm1")
+        new_item = new_item.replace("in_layers.2", "conv1")
+
+        new_item = new_item.replace("out_layers.0", "norm2")
+        new_item = new_item.replace("out_layers.3", "conv2")
+
+        new_item = new_item.replace("emb_layers.1", "time_emb_proj")
+        new_item = new_item.replace("skip_connection", "conv_shortcut")
+
+        new_item = shave_segments(new_item, n_shave_prefix_segments=n_shave_prefix_segments)
+
+        mapping.append({"old": old_item, "new": new_item})
+
+    return mapping
+
+
+def renew_vae_resnet_paths(old_list, n_shave_prefix_segments=0):
+    """
+    Updates paths inside resnets to the new naming scheme (local renaming)
+    """
+    mapping = []
+    for old_item in old_list:
+        new_item = old_item
+
+        new_item = new_item.replace("nin_shortcut", "conv_shortcut")
+        new_item = shave_segments(new_item, n_shave_prefix_segments=n_shave_prefix_segments)
+
+        mapping.append({"old": old_item, "new": new_item})
+
+    return mapping
+
+
+def renew_attention_paths(old_list, n_shave_prefix_segments=0):
+    """
+    Updates paths inside attentions to the new naming scheme (local renaming)
+    """
+    mapping = []
+    for old_item in old_list:
+        new_item = old_item
+
+        #         new_item = new_item.replace('norm.weight', 'group_norm.weight')
+        #         new_item = new_item.replace('norm.bias', 'group_norm.bias')
+
+        #         new_item = new_item.replace('proj_out.weight', 'proj_attn.weight')
+        #         new_item = new_item.replace('proj_out.bias', 'proj_attn.bias')
+
+        #         new_item = shave_segments(new_item, n_shave_prefix_segments=n_shave_prefix_segments)
+
+        mapping.append({"old": old_item, "new": new_item})
+
+    return mapping
+
+
+def renew_vae_attention_paths(old_list, n_shave_prefix_segments=0):
+    """
+    Updates paths inside attentions to the new naming scheme (local renaming)
+    """
+    mapping = []
+    for old_item in old_list:
+        new_item = old_item
+
+        new_item = new_item.replace("norm.weight", "group_norm.weight")
+        new_item = new_item.replace("norm.bias", "group_norm.bias")
+
+        new_item = new_item.replace("q.weight", "to_q.weight")
+        new_item = new_item.replace("q.bias", "to_q.bias")
+
+        new_item = new_item.replace("k.weight", "to_k.weight")
+        new_item = new_item.replace("k.bias", "to_k.bias")
+
+        new_item = new_item.replace("v.weight", "to_v.weight")
+        new_item = new_item.replace("v.bias", "to_v.bias")
+
+        new_item = new_item.replace("proj_out.weight", "to_out.0.weight")
+        new_item = new_item.replace("proj_out.bias", "to_out.0.bias")
+
+        new_item = shave_segments(new_item, n_shave_prefix_segments=n_shave_prefix_segments)
+
+        mapping.append({"old": old_item, "new": new_item})
+
+    return mapping
+
+
+def assign_to_checkpoint(
+    paths, checkpoint, old_checkpoint, attention_paths_to_split=None, additional_replacements=None, config=None
+):
+    """
+    This does the final conversion step: take locally converted weights and apply a global renaming to them. It splits
+    attention layers, and takes into account additional replacements that may arise.
+
+    Assigns the weights to the new checkpoint.
+    """
+    assert isinstance(paths, list), "Paths should be a list of dicts containing 'old' and 'new' keys."
+
+    # Splits the attention layers into three variables.
+    if attention_paths_to_split is not None:
+        for path, path_map in attention_paths_to_split.items():
+            old_tensor = old_checkpoint[path]
+            channels = old_tensor.shape[0] // 3
+
+            target_shape = (-1, channels) if len(old_tensor.shape) == 3 else (-1)
+
+            num_heads = old_tensor.shape[0] // config["num_head_channels"] // 3
+
+            old_tensor = old_tensor.reshape((num_heads, 3 * channels // num_heads) + old_tensor.shape[1:])
+            query, key, value = old_tensor.split(channels // num_heads, dim=1)
+
+            checkpoint[path_map["query"]] = query.reshape(target_shape)
+            checkpoint[path_map["key"]] = key.reshape(target_shape)
+            checkpoint[path_map["value"]] = value.reshape(target_shape)
+
+    for path in paths:
+        new_path = path["new"]
+
+        # These have already been assigned
+        if attention_paths_to_split is not None and new_path in attention_paths_to_split:
+            continue
+
+        # Global renaming happens here
+        new_path = new_path.replace("middle_block.0", "mid_block.resnets.0")
+        new_path = new_path.replace("middle_block.1", "mid_block.attentions.0")
+        new_path = new_path.replace("middle_block.2", "mid_block.resnets.1")
+
+        if additional_replacements is not None:
+            for replacement in additional_replacements:
+                new_path = new_path.replace(replacement["old"], replacement["new"])
+
+        # proj_attn.weight has to be converted from conv 1D to linear
+        is_attn_weight = "proj_attn.weight" in new_path or ("attentions" in new_path and "to_" in new_path)
+        shape = old_checkpoint[path["old"]].shape
+        if is_attn_weight and len(shape) == 3:
+            checkpoint[new_path] = old_checkpoint[path["old"]][:, :, 0]
+        elif is_attn_weight and len(shape) == 4:
+            checkpoint[new_path] = old_checkpoint[path["old"]][:, :, 0, 0]
+        else:
+            checkpoint[new_path] = old_checkpoint[path["old"]]
+
+
+def conv_attn_to_linear(checkpoint):
+    keys = list(checkpoint.keys())
+    attn_keys = ["query.weight", "key.weight", "value.weight"]
+    for key in keys:
+        if ".".join(key.split(".")[-2:]) in attn_keys:
+            if checkpoint[key].ndim > 2:
+                checkpoint[key] = checkpoint[key][:, :, 0, 0]
+        elif "proj_attn.weight" in key:
+            if checkpoint[key].ndim > 2:
+                checkpoint[key] = checkpoint[key][:, :, 0]
+
+
+def create_unet_diffusers_config(original_config, image_size: int, controlnet=False):
+    """
+    Creates a config for the diffusers based on the config of the LDM model.
+    """
+    if controlnet:
+        unet_params = original_config.model.params.control_stage_config.params
+    else:
+        if "unet_config" in original_config.model.params and original_config.model.params.unet_config is not None:
+            unet_params = original_config.model.params.unet_config.params
+        else:
+            unet_params = original_config.model.params.network_config.params
+
+    vae_params = original_config.model.params.first_stage_config.params.ddconfig
+
+    block_out_channels = [unet_params.model_channels * mult for mult in unet_params.channel_mult]
+
+    down_block_types = []
+    resolution = 1
+    for i in range(len(block_out_channels)):
+        block_type = "CrossAttnDownBlock2D" if resolution in unet_params.attention_resolutions else "DownBlock2D"
+        down_block_types.append(block_type)
+        if i != len(block_out_channels) - 1:
+            resolution *= 2
+
+    up_block_types = []
+    for _i in range(len(block_out_channels)):
+        block_type = "CrossAttnUpBlock2D" if resolution in unet_params.attention_resolutions else "UpBlock2D"
+        up_block_types.append(block_type)
+        resolution //= 2
+
+    if unet_params.transformer_depth is not None:
+        transformer_layers_per_block = (
+            unet_params.transformer_depth
+            if isinstance(unet_params.transformer_depth, int)
+            else list(unet_params.transformer_depth)
+        )
+    else:
+        transformer_layers_per_block = 1
+
+    vae_scale_factor = 2 ** (len(vae_params.ch_mult) - 1)
+
+    head_dim = unet_params.num_heads if "num_heads" in unet_params else None
+    use_linear_projection = (
+        unet_params.use_linear_in_transformer if "use_linear_in_transformer" in unet_params else False
+    )
+    if use_linear_projection:
+        # stable diffusion 2-base-512 and 2-768
+        if head_dim is None:
+            head_dim_mult = unet_params.model_channels // unet_params.num_head_channels
+            head_dim = [head_dim_mult * c for c in list(unet_params.channel_mult)]
+
+    class_embed_type = None
+    addition_embed_type = None
+    addition_time_embed_dim = None
+    projection_class_embeddings_input_dim = None
+    context_dim = None
+
+    if unet_params.context_dim is not None:
+        context_dim = (
+            unet_params.context_dim if isinstance(unet_params.context_dim, int) else unet_params.context_dim[0]
+        )
+
+    if "num_classes" in unet_params:
+        if unet_params.num_classes == "sequential":
+            if context_dim in [2048, 1280]:
+                # SDXL
+                addition_embed_type = "text_time"
+                addition_time_embed_dim = 256
+            else:
+                class_embed_type = "projection"
+            assert "adm_in_channels" in unet_params
+            projection_class_embeddings_input_dim = unet_params.adm_in_channels
+        else:
+            raise NotImplementedError(f"Unknown conditional unet num_classes config: {unet_params.num_classes}")
+
+    config = {
+        "sample_size": image_size // vae_scale_factor,
+        "in_channels": unet_params.in_channels,
+        "down_block_types": tuple(down_block_types),
+        "block_out_channels": tuple(block_out_channels),
+        "layers_per_block": unet_params.num_res_blocks,
+        "cross_attention_dim": context_dim,
+        "attention_head_dim": head_dim,
+        "use_linear_projection": use_linear_projection,
+        "class_embed_type": class_embed_type,
+        "addition_embed_type": addition_embed_type,
+        "addition_time_embed_dim": addition_time_embed_dim,
+        "projection_class_embeddings_input_dim": projection_class_embeddings_input_dim,
+        "transformer_layers_per_block": transformer_layers_per_block,
+    }
+
+    if controlnet:
+        config["conditioning_channels"] = unet_params.hint_channels
+    else:
+        config["out_channels"] = unet_params.out_channels
+        config["up_block_types"] = tuple(up_block_types)
+
+    return config
+
+
+def create_vae_diffusers_config(original_config, image_size: int):
+    """
+    Creates a config for the diffusers based on the config of the LDM model.
+    """
+    vae_params = original_config.model.params.first_stage_config.params.ddconfig
+    _ = original_config.model.params.first_stage_config.params.embed_dim
+
+    block_out_channels = [vae_params.ch * mult for mult in vae_params.ch_mult]
+    down_block_types = ["DownEncoderBlock2D"] * len(block_out_channels)
+    up_block_types = ["UpDecoderBlock2D"] * len(block_out_channels)
+
+    config = {
+        "sample_size": image_size,
+        "in_channels": vae_params.in_channels,
+        "out_channels": vae_params.out_ch,
+        "down_block_types": tuple(down_block_types),
+        "up_block_types": tuple(up_block_types),
+        "block_out_channels": tuple(block_out_channels),
+        "latent_channels": vae_params.z_channels,
+        "layers_per_block": vae_params.num_res_blocks,
+    }
+    return config
+
+
+def create_diffusers_schedular(original_config):
+    schedular = DDIMScheduler(
+        num_train_timesteps=original_config.model.params.timesteps,
+        beta_start=original_config.model.params.linear_start,
+        beta_end=original_config.model.params.linear_end,
+        beta_schedule="scaled_linear",
+    )
+    return schedular
+
+
+def create_ldm_bert_config(original_config):
+    bert_params = original_config.model.parms.cond_stage_config.params
+    config = LDMBertConfig(
+        d_model=bert_params.n_embed,
+        encoder_layers=bert_params.n_layer,
+        encoder_ffn_dim=bert_params.n_embed * 4,
+    )
+    return config
+
+
+def convert_ldm_unet_checkpoint(
+    checkpoint, config, path=None, extract_ema=False, controlnet=False, skip_extract_state_dict=False
+):
+    """
+    Takes a state dict and a config, and returns a converted checkpoint.
+    """
+
+    if skip_extract_state_dict:
+        unet_state_dict = checkpoint
+    else:
+        # extract state_dict for UNet
+        unet_state_dict = {}
+        keys = list(checkpoint.keys())
+
+        if controlnet:
+            unet_key = "control_model."
+        else:
+            unet_key = "model.diffusion_model."
+
+        # at least a 100 parameters have to start with `model_ema` in order for the checkpoint to be EMA
+        if sum(k.startswith("model_ema") for k in keys) > 100 and extract_ema:
+            logger.warning(f"Checkpoint {path} has both EMA and non-EMA weights.")
+            logger.warning(
+                "In this conversion only the EMA weights are extracted. If you want to instead extract the non-EMA"
+                " weights (useful to continue fine-tuning), please make sure to remove the `--extract_ema` flag."
+            )
+            for key in keys:
+                if key.startswith("model.diffusion_model"):
+                    flat_ema_key = "model_ema." + "".join(key.split(".")[1:])
+                    unet_state_dict[key.replace(unet_key, "")] = checkpoint.pop(flat_ema_key)
+        else:
+            if sum(k.startswith("model_ema") for k in keys) > 100:
+                logger.warning(
+                    "In this conversion only the non-EMA weights are extracted. If you want to instead extract the EMA"
+                    " weights (usually better for inference), please make sure to add the `--extract_ema` flag."
+                )
+
+            for key in keys:
+                if key.startswith(unet_key):
+                    unet_state_dict[key.replace(unet_key, "")] = checkpoint.pop(key)
+
+    new_checkpoint = {}
+
+    new_checkpoint["time_embedding.linear_1.weight"] = unet_state_dict["time_embed.0.weight"]
+    new_checkpoint["time_embedding.linear_1.bias"] = unet_state_dict["time_embed.0.bias"]
+    new_checkpoint["time_embedding.linear_2.weight"] = unet_state_dict["time_embed.2.weight"]
+    new_checkpoint["time_embedding.linear_2.bias"] = unet_state_dict["time_embed.2.bias"]
+
+    if config["class_embed_type"] is None:
+        # No parameters to port
+        ...
+    elif config["class_embed_type"] == "timestep" or config["class_embed_type"] == "projection":
+        new_checkpoint["class_embedding.linear_1.weight"] = unet_state_dict["label_emb.0.0.weight"]
+        new_checkpoint["class_embedding.linear_1.bias"] = unet_state_dict["label_emb.0.0.bias"]
+        new_checkpoint["class_embedding.linear_2.weight"] = unet_state_dict["label_emb.0.2.weight"]
+        new_checkpoint["class_embedding.linear_2.bias"] = unet_state_dict["label_emb.0.2.bias"]
+    else:
+        raise NotImplementedError(f"Not implemented `class_embed_type`: {config['class_embed_type']}")
+
+    if config["addition_embed_type"] == "text_time":
+        new_checkpoint["add_embedding.linear_1.weight"] = unet_state_dict["label_emb.0.0.weight"]
+        new_checkpoint["add_embedding.linear_1.bias"] = unet_state_dict["label_emb.0.0.bias"]
+        new_checkpoint["add_embedding.linear_2.weight"] = unet_state_dict["label_emb.0.2.weight"]
+        new_checkpoint["add_embedding.linear_2.bias"] = unet_state_dict["label_emb.0.2.bias"]
+
+    new_checkpoint["conv_in.weight"] = unet_state_dict["input_blocks.0.0.weight"]
+    new_checkpoint["conv_in.bias"] = unet_state_dict["input_blocks.0.0.bias"]
+
+    if not controlnet:
+        new_checkpoint["conv_norm_out.weight"] = unet_state_dict["out.0.weight"]
+        new_checkpoint["conv_norm_out.bias"] = unet_state_dict["out.0.bias"]
+        new_checkpoint["conv_out.weight"] = unet_state_dict["out.2.weight"]
+        new_checkpoint["conv_out.bias"] = unet_state_dict["out.2.bias"]
+
+    # Retrieves the keys for the input blocks only
+    num_input_blocks = len({".".join(layer.split(".")[:2]) for layer in unet_state_dict if "input_blocks" in layer})
+    input_blocks = {
+        layer_id: [key for key in unet_state_dict if f"input_blocks.{layer_id}" in key]
+        for layer_id in range(num_input_blocks)
+    }
+
+    # Retrieves the keys for the middle blocks only
+    num_middle_blocks = len({".".join(layer.split(".")[:2]) for layer in unet_state_dict if "middle_block" in layer})
+    middle_blocks = {
+        layer_id: [key for key in unet_state_dict if f"middle_block.{layer_id}" in key]
+        for layer_id in range(num_middle_blocks)
+    }
+
+    # Retrieves the keys for the output blocks only
+    num_output_blocks = len({".".join(layer.split(".")[:2]) for layer in unet_state_dict if "output_blocks" in layer})
+    output_blocks = {
+        layer_id: [key for key in unet_state_dict if f"output_blocks.{layer_id}" in key]
+        for layer_id in range(num_output_blocks)
+    }
+
+    for i in range(1, num_input_blocks):
+        block_id = (i - 1) // (config["layers_per_block"] + 1)
+        layer_in_block_id = (i - 1) % (config["layers_per_block"] + 1)
+
+        resnets = [
+            key for key in input_blocks[i] if f"input_blocks.{i}.0" in key and f"input_blocks.{i}.0.op" not in key
+        ]
+        attentions = [key for key in input_blocks[i] if f"input_blocks.{i}.1" in key]
+
+        if f"input_blocks.{i}.0.op.weight" in unet_state_dict:
+            new_checkpoint[f"down_blocks.{block_id}.downsamplers.0.conv.weight"] = unet_state_dict.pop(
+                f"input_blocks.{i}.0.op.weight"
+            )
+            new_checkpoint[f"down_blocks.{block_id}.downsamplers.0.conv.bias"] = unet_state_dict.pop(
+                f"input_blocks.{i}.0.op.bias"
+            )
+
+        paths = renew_resnet_paths(resnets)
+        meta_path = {"old": f"input_blocks.{i}.0", "new": f"down_blocks.{block_id}.resnets.{layer_in_block_id}"}
+        assign_to_checkpoint(paths, new_checkpoint, unet_state_dict, additional_replacements=[meta_path], config=config)
+
+        if len(attentions):
+            paths = renew_attention_paths(attentions)
+            meta_path = {"old": f"input_blocks.{i}.1", "new": f"down_blocks.{block_id}.attentions.{layer_in_block_id}"}
+            assign_to_checkpoint(
+                paths, new_checkpoint, unet_state_dict, additional_replacements=[meta_path], config=config
+            )
+
+    resnet_0 = middle_blocks[0]
+    attentions = middle_blocks[1]
+    resnet_1 = middle_blocks[2]
+
+    resnet_0_paths = renew_resnet_paths(resnet_0)
+    assign_to_checkpoint(resnet_0_paths, new_checkpoint, unet_state_dict, config=config)
+
+    resnet_1_paths = renew_resnet_paths(resnet_1)
+    assign_to_checkpoint(resnet_1_paths, new_checkpoint, unet_state_dict, config=config)
+
+    attentions_paths = renew_attention_paths(attentions)
+    meta_path = {"old": "middle_block.1", "new": "mid_block.attentions.0"}
+    assign_to_checkpoint(
+        attentions_paths, new_checkpoint, unet_state_dict, additional_replacements=[meta_path], config=config
+    )
+
+    for i in range(num_output_blocks):
+        block_id = i // (config["layers_per_block"] + 1)
+        layer_in_block_id = i % (config["layers_per_block"] + 1)
+        output_block_layers = [shave_segments(name, 2) for name in output_blocks[i]]
+        output_block_list = {}
+
+        for layer in output_block_layers:
+            layer_id, layer_name = layer.split(".")[0], shave_segments(layer, 1)
+            if layer_id in output_block_list:
+                output_block_list[layer_id].append(layer_name)
+            else:
+                output_block_list[layer_id] = [layer_name]
+
+        if len(output_block_list) > 1:
+            resnets = [key for key in output_blocks[i] if f"output_blocks.{i}.0" in key]
+            attentions = [key for key in output_blocks[i] if f"output_blocks.{i}.1" in key]
+
+            resnet_0_paths = renew_resnet_paths(resnets)
+            paths = renew_resnet_paths(resnets)
+
+            meta_path = {"old": f"output_blocks.{i}.0", "new": f"up_blocks.{block_id}.resnets.{layer_in_block_id}"}
+            assign_to_checkpoint(
+                paths, new_checkpoint, unet_state_dict, additional_replacements=[meta_path], config=config
+            )
+
+            output_block_list = {k: sorted(v) for k, v in output_block_list.items()}
+            if ["conv.bias", "conv.weight"] in output_block_list.values():
+                index = list(output_block_list.values()).index(["conv.bias", "conv.weight"])
+                new_checkpoint[f"up_blocks.{block_id}.upsamplers.0.conv.weight"] = unet_state_dict[
+                    f"output_blocks.{i}.{index}.conv.weight"
+                ]
+                new_checkpoint[f"up_blocks.{block_id}.upsamplers.0.conv.bias"] = unet_state_dict[
+                    f"output_blocks.{i}.{index}.conv.bias"
+                ]
+
+                # Clear attentions as they have been attributed above.
+                if len(attentions) == 2:
+                    attentions = []
+
+            if len(attentions):
+                paths = renew_attention_paths(attentions)
+                meta_path = {
+                    "old": f"output_blocks.{i}.1",
+                    "new": f"up_blocks.{block_id}.attentions.{layer_in_block_id}",
+                }
+                assign_to_checkpoint(
+                    paths, new_checkpoint, unet_state_dict, additional_replacements=[meta_path], config=config
+                )
+        else:
+            resnet_0_paths = renew_resnet_paths(output_block_layers, n_shave_prefix_segments=1)
+            for path in resnet_0_paths:
+                old_path = ".".join(["output_blocks", str(i), path["old"]])
+                new_path = ".".join(["up_blocks", str(block_id), "resnets", str(layer_in_block_id), path["new"]])
+
+                new_checkpoint[new_path] = unet_state_dict[old_path]
+
+    if controlnet:
+        # conditioning embedding
+
+        orig_index = 0
+
+        new_checkpoint["controlnet_cond_embedding.conv_in.weight"] = unet_state_dict.pop(
+            f"input_hint_block.{orig_index}.weight"
+        )
+        new_checkpoint["controlnet_cond_embedding.conv_in.bias"] = unet_state_dict.pop(
+            f"input_hint_block.{orig_index}.bias"
+        )
+
+        orig_index += 2
+
+        diffusers_index = 0
+
+        while diffusers_index < 6:
+            new_checkpoint[f"controlnet_cond_embedding.blocks.{diffusers_index}.weight"] = unet_state_dict.pop(
+                f"input_hint_block.{orig_index}.weight"
+            )
+            new_checkpoint[f"controlnet_cond_embedding.blocks.{diffusers_index}.bias"] = unet_state_dict.pop(
+                f"input_hint_block.{orig_index}.bias"
+            )
+            diffusers_index += 1
+            orig_index += 2
+
+        new_checkpoint["controlnet_cond_embedding.conv_out.weight"] = unet_state_dict.pop(
+            f"input_hint_block.{orig_index}.weight"
+        )
+        new_checkpoint["controlnet_cond_embedding.conv_out.bias"] = unet_state_dict.pop(
+            f"input_hint_block.{orig_index}.bias"
+        )
+
+        # down blocks
+        for i in range(num_input_blocks):
+            new_checkpoint[f"controlnet_down_blocks.{i}.weight"] = unet_state_dict.pop(f"zero_convs.{i}.0.weight")
+            new_checkpoint[f"controlnet_down_blocks.{i}.bias"] = unet_state_dict.pop(f"zero_convs.{i}.0.bias")
+
+        # mid block
+        new_checkpoint["controlnet_mid_block.weight"] = unet_state_dict.pop("middle_block_out.0.weight")
+        new_checkpoint["controlnet_mid_block.bias"] = unet_state_dict.pop("middle_block_out.0.bias")
+
+    return new_checkpoint
+
+
+def convert_ldm_vae_checkpoint(checkpoint, config):
+    # extract state dict for VAE
+    vae_state_dict = {}
+    keys = list(checkpoint.keys())
+    vae_key = "first_stage_model." if any(k.startswith("first_stage_model.") for k in keys) else ""
+    for key in keys:
+        if key.startswith(vae_key):
+            vae_state_dict[key.replace(vae_key, "")] = checkpoint.get(key)
+
+    new_checkpoint = {}
+
+    new_checkpoint["encoder.conv_in.weight"] = vae_state_dict["encoder.conv_in.weight"]
+    new_checkpoint["encoder.conv_in.bias"] = vae_state_dict["encoder.conv_in.bias"]
+    new_checkpoint["encoder.conv_out.weight"] = vae_state_dict["encoder.conv_out.weight"]
+    new_checkpoint["encoder.conv_out.bias"] = vae_state_dict["encoder.conv_out.bias"]
+    new_checkpoint["encoder.conv_norm_out.weight"] = vae_state_dict["encoder.norm_out.weight"]
+    new_checkpoint["encoder.conv_norm_out.bias"] = vae_state_dict["encoder.norm_out.bias"]
+
+    new_checkpoint["decoder.conv_in.weight"] = vae_state_dict["decoder.conv_in.weight"]
+    new_checkpoint["decoder.conv_in.bias"] = vae_state_dict["decoder.conv_in.bias"]
+    new_checkpoint["decoder.conv_out.weight"] = vae_state_dict["decoder.conv_out.weight"]
+    new_checkpoint["decoder.conv_out.bias"] = vae_state_dict["decoder.conv_out.bias"]
+    new_checkpoint["decoder.conv_norm_out.weight"] = vae_state_dict["decoder.norm_out.weight"]
+    new_checkpoint["decoder.conv_norm_out.bias"] = vae_state_dict["decoder.norm_out.bias"]
+
+    new_checkpoint["quant_conv.weight"] = vae_state_dict["quant_conv.weight"]
+    new_checkpoint["quant_conv.bias"] = vae_state_dict["quant_conv.bias"]
+    new_checkpoint["post_quant_conv.weight"] = vae_state_dict["post_quant_conv.weight"]
+    new_checkpoint["post_quant_conv.bias"] = vae_state_dict["post_quant_conv.bias"]
+
+    # Retrieves the keys for the encoder down blocks only
+    num_down_blocks = len({".".join(layer.split(".")[:3]) for layer in vae_state_dict if "encoder.down" in layer})
+    down_blocks = {
+        layer_id: [key for key in vae_state_dict if f"down.{layer_id}" in key] for layer_id in range(num_down_blocks)
+    }
+
+    # Retrieves the keys for the decoder up blocks only
+    num_up_blocks = len({".".join(layer.split(".")[:3]) for layer in vae_state_dict if "decoder.up" in layer})
+    up_blocks = {
+        layer_id: [key for key in vae_state_dict if f"up.{layer_id}" in key] for layer_id in range(num_up_blocks)
+    }
+
+    for i in range(num_down_blocks):
+        resnets = [key for key in down_blocks[i] if f"down.{i}" in key and f"down.{i}.downsample" not in key]
+
+        if f"encoder.down.{i}.downsample.conv.weight" in vae_state_dict:
+            new_checkpoint[f"encoder.down_blocks.{i}.downsamplers.0.conv.weight"] = vae_state_dict.pop(
+                f"encoder.down.{i}.downsample.conv.weight"
+            )
+            new_checkpoint[f"encoder.down_blocks.{i}.downsamplers.0.conv.bias"] = vae_state_dict.pop(
+                f"encoder.down.{i}.downsample.conv.bias"
+            )
+
+        paths = renew_vae_resnet_paths(resnets)
+        meta_path = {"old": f"down.{i}.block", "new": f"down_blocks.{i}.resnets"}
+        assign_to_checkpoint(paths, new_checkpoint, vae_state_dict, additional_replacements=[meta_path], config=config)
+
+    mid_resnets = [key for key in vae_state_dict if "encoder.mid.block" in key]
+    num_mid_res_blocks = 2
+    for i in range(1, num_mid_res_blocks + 1):
+        resnets = [key for key in mid_resnets if f"encoder.mid.block_{i}" in key]
+
+        paths = renew_vae_resnet_paths(resnets)
+        meta_path = {"old": f"mid.block_{i}", "new": f"mid_block.resnets.{i - 1}"}
+        assign_to_checkpoint(paths, new_checkpoint, vae_state_dict, additional_replacements=[meta_path], config=config)
+
+    mid_attentions = [key for key in vae_state_dict if "encoder.mid.attn" in key]
+    paths = renew_vae_attention_paths(mid_attentions)
+    meta_path = {"old": "mid.attn_1", "new": "mid_block.attentions.0"}
+    assign_to_checkpoint(paths, new_checkpoint, vae_state_dict, additional_replacements=[meta_path], config=config)
+    conv_attn_to_linear(new_checkpoint)
+
+    for i in range(num_up_blocks):
+        block_id = num_up_blocks - 1 - i
+        resnets = [
+            key for key in up_blocks[block_id] if f"up.{block_id}" in key and f"up.{block_id}.upsample" not in key
+        ]
+
+        if f"decoder.up.{block_id}.upsample.conv.weight" in vae_state_dict:
+            new_checkpoint[f"decoder.up_blocks.{i}.upsamplers.0.conv.weight"] = vae_state_dict[
+                f"decoder.up.{block_id}.upsample.conv.weight"
+            ]
+            new_checkpoint[f"decoder.up_blocks.{i}.upsamplers.0.conv.bias"] = vae_state_dict[
+                f"decoder.up.{block_id}.upsample.conv.bias"
+            ]
+
+        paths = renew_vae_resnet_paths(resnets)
+        meta_path = {"old": f"up.{block_id}.block", "new": f"up_blocks.{i}.resnets"}
+        assign_to_checkpoint(paths, new_checkpoint, vae_state_dict, additional_replacements=[meta_path], config=config)
+
+    mid_resnets = [key for key in vae_state_dict if "decoder.mid.block" in key]
+    num_mid_res_blocks = 2
+    for i in range(1, num_mid_res_blocks + 1):
+        resnets = [key for key in mid_resnets if f"decoder.mid.block_{i}" in key]
+
+        paths = renew_vae_resnet_paths(resnets)
+        meta_path = {"old": f"mid.block_{i}", "new": f"mid_block.resnets.{i - 1}"}
+        assign_to_checkpoint(paths, new_checkpoint, vae_state_dict, additional_replacements=[meta_path], config=config)
+
+    mid_attentions = [key for key in vae_state_dict if "decoder.mid.attn" in key]
+    paths = renew_vae_attention_paths(mid_attentions)
+    meta_path = {"old": "mid.attn_1", "new": "mid_block.attentions.0"}
+    assign_to_checkpoint(paths, new_checkpoint, vae_state_dict, additional_replacements=[meta_path], config=config)
+    conv_attn_to_linear(new_checkpoint)
+    return new_checkpoint
+
+
+def convert_ldm_bert_checkpoint(checkpoint, config):
+    def _copy_attn_layer(hf_attn_layer, pt_attn_layer):
+        hf_attn_layer.q_proj.weight.data = pt_attn_layer.to_q.weight
+        hf_attn_layer.k_proj.weight.data = pt_attn_layer.to_k.weight
+        hf_attn_layer.v_proj.weight.data = pt_attn_layer.to_v.weight
+
+        hf_attn_layer.out_proj.weight = pt_attn_layer.to_out.weight
+        hf_attn_layer.out_proj.bias = pt_attn_layer.to_out.bias
+
+    def _copy_linear(hf_linear, pt_linear):
+        hf_linear.weight = pt_linear.weight
+        hf_linear.bias = pt_linear.bias
+
+    def _copy_layer(hf_layer, pt_layer):
+        # copy layer norms
+        _copy_linear(hf_layer.self_attn_layer_norm, pt_layer[0][0])
+        _copy_linear(hf_layer.final_layer_norm, pt_layer[1][0])
+
+        # copy attn
+        _copy_attn_layer(hf_layer.self_attn, pt_layer[0][1])
+
+        # copy MLP
+        pt_mlp = pt_layer[1][1]
+        _copy_linear(hf_layer.fc1, pt_mlp.net[0][0])
+        _copy_linear(hf_layer.fc2, pt_mlp.net[2])
+
+    def _copy_layers(hf_layers, pt_layers):
+        for i, hf_layer in enumerate(hf_layers):
+            if i != 0:
+                i += i
+            pt_layer = pt_layers[i : i + 2]
+            _copy_layer(hf_layer, pt_layer)
+
+    hf_model = LDMBertModel(config).eval()
+
+    # copy  embeds
+    hf_model.model.embed_tokens.weight = checkpoint.transformer.token_emb.weight
+    hf_model.model.embed_positions.weight.data = checkpoint.transformer.pos_emb.emb.weight
+
+    # copy layer norm
+    _copy_linear(hf_model.model.layer_norm, checkpoint.transformer.norm)
+
+    # copy hidden layers
+    _copy_layers(hf_model.model.layers, checkpoint.transformer.attn_layers.layers)
+
+    _copy_linear(hf_model.to_logits, checkpoint.transformer.to_logits)
+
+    return hf_model
+
+
+def convert_ldm_clip_checkpoint(checkpoint, local_files_only=False, text_encoder=None):
+    if text_encoder is None:
+        config = CLIPTextConfig.from_pretrained(CONVERT_MODEL_ROOT / "clip-vit-large-patch14")
+
+        ctx = init_empty_weights if is_accelerate_available() else nullcontext
+        with ctx():
+            text_model = CLIPTextModel(config)
+
+    keys = list(checkpoint.keys())
+
+    text_model_dict = {}
+
+    remove_prefixes = ["cond_stage_model.transformer", "conditioner.embedders.0.transformer"]
+
+    for key in keys:
+        for prefix in remove_prefixes:
+            if key.startswith(prefix):
+                text_model_dict[key[len(prefix + ".") :]] = checkpoint[key]
+
+    if is_accelerate_available():
+        for param_name, param in text_model_dict.items():
+            set_module_tensor_to_device(text_model, param_name, "cpu", value=param)
+    else:
+        text_model.load_state_dict(text_model_dict)
+
+    return text_model
+
+
+textenc_conversion_lst = [
+    ("positional_embedding", "text_model.embeddings.position_embedding.weight"),
+    ("token_embedding.weight", "text_model.embeddings.token_embedding.weight"),
+    ("ln_final.weight", "text_model.final_layer_norm.weight"),
+    ("ln_final.bias", "text_model.final_layer_norm.bias"),
+    ("text_projection", "text_projection.weight"),
+]
+textenc_conversion_map = {x[0]: x[1] for x in textenc_conversion_lst}
+
+textenc_transformer_conversion_lst = [
+    # (stable-diffusion, HF Diffusers)
+    ("resblocks.", "text_model.encoder.layers."),
+    ("ln_1", "layer_norm1"),
+    ("ln_2", "layer_norm2"),
+    (".c_fc.", ".fc1."),
+    (".c_proj.", ".fc2."),
+    (".attn", ".self_attn"),
+    ("ln_final.", "transformer.text_model.final_layer_norm."),
+    ("token_embedding.weight", "transformer.text_model.embeddings.token_embedding.weight"),
+    ("positional_embedding", "transformer.text_model.embeddings.position_embedding.weight"),
+]
+protected = {re.escape(x[0]): x[1] for x in textenc_transformer_conversion_lst}
+textenc_pattern = re.compile("|".join(protected.keys()))
+
+
+def convert_paint_by_example_checkpoint(checkpoint):
+    config = CLIPVisionConfig.from_pretrained(CONVERT_MODEL_ROOT / "clip-vit-large-patch14")
+    model = PaintByExampleImageEncoder(config)
+
+    keys = list(checkpoint.keys())
+
+    text_model_dict = {}
+
+    for key in keys:
+        if key.startswith("cond_stage_model.transformer"):
+            text_model_dict[key[len("cond_stage_model.transformer.") :]] = checkpoint[key]
+
+    # load clip vision
+    model.model.load_state_dict(text_model_dict)
+
+    # load mapper
+    keys_mapper = {
+        k[len("cond_stage_model.mapper.res") :]: v
+        for k, v in checkpoint.items()
+        if k.startswith("cond_stage_model.mapper")
+    }
+
+    MAPPING = {
+        "attn.c_qkv": ["attn1.to_q", "attn1.to_k", "attn1.to_v"],
+        "attn.c_proj": ["attn1.to_out.0"],
+        "ln_1": ["norm1"],
+        "ln_2": ["norm3"],
+        "mlp.c_fc": ["ff.net.0.proj"],
+        "mlp.c_proj": ["ff.net.2"],
+    }
+
+    mapped_weights = {}
+    for key, value in keys_mapper.items():
+        prefix = key[: len("blocks.i")]
+        suffix = key.split(prefix)[-1].split(".")[-1]
+        name = key.split(prefix)[-1].split(suffix)[0][1:-1]
+        mapped_names = MAPPING[name]
+
+        num_splits = len(mapped_names)
+        for i, mapped_name in enumerate(mapped_names):
+            new_name = ".".join([prefix, mapped_name, suffix])
+            shape = value.shape[0] // num_splits
+            mapped_weights[new_name] = value[i * shape : (i + 1) * shape]
+
+    model.mapper.load_state_dict(mapped_weights)
+
+    # load final layer norm
+    model.final_layer_norm.load_state_dict(
+        {
+            "bias": checkpoint["cond_stage_model.final_ln.bias"],
+            "weight": checkpoint["cond_stage_model.final_ln.weight"],
+        }
+    )
+
+    # load final proj
+    model.proj_out.load_state_dict(
+        {
+            "bias": checkpoint["proj_out.bias"],
+            "weight": checkpoint["proj_out.weight"],
+        }
+    )
+
+    # load uncond vector
+    model.uncond_vector.data = torch.nn.Parameter(checkpoint["learnable_vector"])
+    return model
+
+
+def convert_open_clip_checkpoint(
+    checkpoint, config_name, prefix="cond_stage_model.model.", has_projection=False, **config_kwargs
+):
+    # text_model = CLIPTextModel.from_pretrained("stabilityai/stable-diffusion-2", subfolder="text_encoder")
+    # text_model = CLIPTextModelWithProjection.from_pretrained(
+    #    "laion/CLIP-ViT-bigG-14-laion2B-39B-b160k", projection_dim=1280
+    # )
+    config = CLIPTextConfig.from_pretrained(config_name, **config_kwargs)
+
+    ctx = init_empty_weights if is_accelerate_available() else nullcontext
+    with ctx():
+        text_model = CLIPTextModelWithProjection(config) if has_projection else CLIPTextModel(config)
+
+    keys = list(checkpoint.keys())
+
+    keys_to_ignore = []
+    if config_name == "stabilityai/stable-diffusion-2" and config.num_hidden_layers == 23:
+        # make sure to remove all keys > 22
+        keys_to_ignore += [k for k in keys if k.startswith("cond_stage_model.model.transformer.resblocks.23")]
+        keys_to_ignore += ["cond_stage_model.model.text_projection"]
+
+    text_model_dict = {}
+
+    if prefix + "text_projection" in checkpoint:
+        d_model = int(checkpoint[prefix + "text_projection"].shape[0])
+    else:
+        d_model = 1024
+
+    text_model_dict["text_model.embeddings.position_ids"] = text_model.text_model.embeddings.get_buffer("position_ids")
+
+    for key in keys:
+        if key in keys_to_ignore:
+            continue
+        if key[len(prefix) :] in textenc_conversion_map:
+            if key.endswith("text_projection"):
+                value = checkpoint[key].T.contiguous()
+            else:
+                value = checkpoint[key]
+
+            text_model_dict[textenc_conversion_map[key[len(prefix) :]]] = value
+
+        if key.startswith(prefix + "transformer."):
+            new_key = key[len(prefix + "transformer.") :]
+            if new_key.endswith(".in_proj_weight"):
+                new_key = new_key[: -len(".in_proj_weight")]
+                new_key = textenc_pattern.sub(lambda m: protected[re.escape(m.group(0))], new_key)
+                text_model_dict[new_key + ".q_proj.weight"] = checkpoint[key][:d_model, :]
+                text_model_dict[new_key + ".k_proj.weight"] = checkpoint[key][d_model : d_model * 2, :]
+                text_model_dict[new_key + ".v_proj.weight"] = checkpoint[key][d_model * 2 :, :]
+            elif new_key.endswith(".in_proj_bias"):
+                new_key = new_key[: -len(".in_proj_bias")]
+                new_key = textenc_pattern.sub(lambda m: protected[re.escape(m.group(0))], new_key)
+                text_model_dict[new_key + ".q_proj.bias"] = checkpoint[key][:d_model]
+                text_model_dict[new_key + ".k_proj.bias"] = checkpoint[key][d_model : d_model * 2]
+                text_model_dict[new_key + ".v_proj.bias"] = checkpoint[key][d_model * 2 :]
+            else:
+                new_key = textenc_pattern.sub(lambda m: protected[re.escape(m.group(0))], new_key)
+
+                text_model_dict[new_key] = checkpoint[key]
+
+    if is_accelerate_available():
+        for param_name, param in text_model_dict.items():
+            set_module_tensor_to_device(text_model, param_name, "cpu", value=param)
+    else:
+        text_model.load_state_dict(text_model_dict)
+
+    return text_model
+
+
+def stable_unclip_image_encoder(original_config):
+    """
+    Returns the image processor and clip image encoder for the img2img unclip pipeline.
+
+    We currently know of two types of stable unclip models which separately use the clip and the openclip image
+    encoders.
+    """
+
+    image_embedder_config = original_config.model.params.embedder_config
+
+    sd_clip_image_embedder_class = image_embedder_config.target
+    sd_clip_image_embedder_class = sd_clip_image_embedder_class.split(".")[-1]
+
+    if sd_clip_image_embedder_class == "ClipImageEmbedder":
+        clip_model_name = image_embedder_config.params.model
+
+        if clip_model_name == "ViT-L/14":
+            feature_extractor = CLIPImageProcessor()
+            image_encoder = CLIPVisionModelWithProjection.from_pretrained(CONVERT_MODEL_ROOT / "clip-vit-large-patch14")
+        else:
+            raise NotImplementedError(f"Unknown CLIP checkpoint name in stable diffusion checkpoint {clip_model_name}")
+
+    elif sd_clip_image_embedder_class == "FrozenOpenCLIPImageEmbedder":
+        feature_extractor = CLIPImageProcessor()
+        # InvokeAI doesn't use CLIPVisionModelWithProjection so it isn't in the core - if this code is hit a download will occur
+        image_encoder = CLIPVisionModelWithProjection.from_pretrained(
+            CONVERT_MODEL_ROOT / "CLIP-ViT-H-14-laion2B-s32B-b79K"
+        )
+    else:
+        raise NotImplementedError(
+            f"Unknown CLIP image embedder class in stable diffusion checkpoint {sd_clip_image_embedder_class}"
+        )
+
+    return feature_extractor, image_encoder
+
+
+def stable_unclip_image_noising_components(
+    original_config, clip_stats_path: Optional[str] = None, device: Optional[str] = None
+):
+    """
+    Returns the noising components for the img2img and txt2img unclip pipelines.
+
+    Converts the stability noise augmentor into
+    1. a `StableUnCLIPImageNormalizer` for holding the CLIP stats
+    2. a `DDPMScheduler` for holding the noise schedule
+
+    If the noise augmentor config specifies a clip stats path, the `clip_stats_path` must be provided.
+    """
+    noise_aug_config = original_config.model.params.noise_aug_config
+    noise_aug_class = noise_aug_config.target
+    noise_aug_class = noise_aug_class.split(".")[-1]
+
+    if noise_aug_class == "CLIPEmbeddingNoiseAugmentation":
+        noise_aug_config = noise_aug_config.params
+        embedding_dim = noise_aug_config.timestep_dim
+        max_noise_level = noise_aug_config.noise_schedule_config.timesteps
+        beta_schedule = noise_aug_config.noise_schedule_config.beta_schedule
+
+        image_normalizer = StableUnCLIPImageNormalizer(embedding_dim=embedding_dim)
+        image_noising_scheduler = DDPMScheduler(num_train_timesteps=max_noise_level, beta_schedule=beta_schedule)
+
+        if "clip_stats_path" in noise_aug_config:
+            if clip_stats_path is None:
+                raise ValueError("This stable unclip config requires a `clip_stats_path`")
+
+            clip_mean, clip_std = torch.load(clip_stats_path, map_location=device)
+            clip_mean = clip_mean[None, :]
+            clip_std = clip_std[None, :]
+
+            clip_stats_state_dict = {
+                "mean": clip_mean,
+                "std": clip_std,
+            }
+
+            image_normalizer.load_state_dict(clip_stats_state_dict)
+    else:
+        raise NotImplementedError(f"Unknown noise augmentor class: {noise_aug_class}")
+
+    return image_normalizer, image_noising_scheduler
+
+
+def convert_controlnet_checkpoint(
+    checkpoint,
+    original_config,
+    checkpoint_path,
+    image_size,
+    upcast_attention,
+    extract_ema,
+    use_linear_projection=None,
+    cross_attention_dim=None,
+    precision: Optional[torch.dtype] = None,
+):
+    ctrlnet_config = create_unet_diffusers_config(original_config, image_size=image_size, controlnet=True)
+    ctrlnet_config["upcast_attention"] = upcast_attention
+
+    ctrlnet_config.pop("sample_size")
+    original_config = ctrlnet_config.copy()
+
+    ctrlnet_config.pop("addition_embed_type")
+    ctrlnet_config.pop("addition_time_embed_dim")
+    ctrlnet_config.pop("transformer_layers_per_block")
+
+    if use_linear_projection is not None:
+        ctrlnet_config["use_linear_projection"] = use_linear_projection
+
+    if cross_attention_dim is not None:
+        ctrlnet_config["cross_attention_dim"] = cross_attention_dim
+
+    controlnet = ControlNetModel(**ctrlnet_config)
+
+    # Some controlnet ckpt files are distributed independently from the rest of the
+    # model components i.e. https://huggingface.co/thibaud/controlnet-sd21/
+    if "time_embed.0.weight" in checkpoint:
+        skip_extract_state_dict = True
+    else:
+        skip_extract_state_dict = False
+
+    converted_ctrl_checkpoint = convert_ldm_unet_checkpoint(
+        checkpoint,
+        original_config,
+        path=checkpoint_path,
+        extract_ema=extract_ema,
+        controlnet=True,
+        skip_extract_state_dict=skip_extract_state_dict,
+    )
+
+    controlnet.load_state_dict(converted_ctrl_checkpoint)
+
+    return controlnet.to(precision)
+
+
+def download_from_original_stable_diffusion_ckpt(
+    checkpoint_path: str,
+    model_version: BaseModelType,
+    model_variant: ModelVariantType,
+    original_config_file: str = None,
+    image_size: Optional[int] = None,
+    prediction_type: str = None,
+    model_type: str = None,
+    extract_ema: bool = False,
+    precision: Optional[torch.dtype] = None,
+    scheduler_type: str = "pndm",
+    num_in_channels: Optional[int] = None,
+    upcast_attention: Optional[bool] = None,
+    device: str = None,
+    from_safetensors: bool = False,
+    stable_unclip: Optional[str] = None,
+    stable_unclip_prior: Optional[str] = None,
+    clip_stats_path: Optional[str] = None,
+    controlnet: Optional[bool] = None,
+    load_safety_checker: bool = True,
+    pipeline_class: DiffusionPipeline = None,
+    local_files_only=False,
+    vae_path=None,
+    text_encoder=None,
+    tokenizer=None,
+    scan_needed: bool = True,
+) -> DiffusionPipeline:
+    """
+    Load a Stable Diffusion pipeline object from a CompVis-style `.ckpt`/`.safetensors` file and (ideally) a `.yaml`
+    config file.
+
+    Although many of the arguments can be automatically inferred, some of these rely on brittle checks against the
+    global step count, which will likely fail for models that have undergone further fine-tuning. Therefore, it is
+    recommended that you override the default values and/or supply an `original_config_file` wherever possible.
+
+    Args:
+        checkpoint_path (`str`): Path to `.ckpt` file.
+        original_config_file (`str`):
+            Path to `.yaml` config file corresponding to the original architecture. If `None`, will be automatically
+            inferred by looking for a key that only exists in SD2.0 models.
+        image_size (`int`, *optional*, defaults to 512):
+            The image size that the model was trained on. Use 512 for Stable Diffusion v1.X and Stable Diffusion v2
+            Base. Use 768 for Stable Diffusion v2.
+        prediction_type (`str`, *optional*):
+            The prediction type that the model was trained on. Use `'epsilon'` for Stable Diffusion v1.X and Stable
+            Diffusion v2 Base. Use `'v_prediction'` for Stable Diffusion v2.
+        num_in_channels (`int`, *optional*, defaults to None):
+            The number of input channels. If `None`, it will be automatically inferred.
+        scheduler_type (`str`, *optional*, defaults to 'pndm'):
+            Type of scheduler to use. Should be one of `["pndm", "lms", "heun", "euler", "euler-ancestral", "dpm",
+            "ddim"]`.
+        model_type (`str`, *optional*, defaults to `None`):
+            The pipeline type. `None` to automatically infer, or one of `["FrozenOpenCLIPEmbedder",
+            "FrozenCLIPEmbedder", "PaintByExample"]`.
+        is_img2img (`bool`, *optional*, defaults to `False`):
+            Whether the model should be loaded as an img2img pipeline.
+        extract_ema (`bool`, *optional*, defaults to `False`): Only relevant for
+            checkpoints that have both EMA and non-EMA weights. Whether to extract the EMA weights or not. Defaults to
+            `False`. Pass `True` to extract the EMA weights. EMA weights usually yield higher quality images for
+            inference. Non-EMA weights are usually better to continue fine-tuning.
+        upcast_attention (`bool`, *optional*, defaults to `None`):
+            Whether the attention computation should always be upcasted. This is necessary when running stable
+            diffusion 2.1.
+        device (`str`, *optional*, defaults to `None`):
+            The device to use. Pass `None` to determine automatically.
+        from_safetensors (`str`, *optional*, defaults to `False`):
+            If `checkpoint_path` is in `safetensors` format, load checkpoint with safetensors instead of PyTorch.
+        load_safety_checker (`bool`, *optional*, defaults to `True`):
+            Whether to load the safety checker or not. Defaults to `True`.
+        pipeline_class (`str`, *optional*, defaults to `None`):
+            The pipeline class to use. Pass `None` to determine automatically.
+        local_files_only (`bool`, *optional*, defaults to `False`):
+            Whether or not to only look at local files (i.e., do not try to download the model).
+        text_encoder (`CLIPTextModel`, *optional*, defaults to `None`):
+            An instance of [CLIP](https://huggingface.co/docs/transformers/model_doc/clip#transformers.CLIPTextModel)
+            to use, specifically the [clip-vit-large-patch14](https://huggingface.co/openai/clip-vit-large-patch14)
+            variant. If this parameter is `None`, the function will load a new instance of [CLIP] by itself, if needed.
+        tokenizer (`CLIPTokenizer`, *optional*, defaults to `None`):
+            An instance of
+            [CLIPTokenizer](https://huggingface.co/docs/transformers/v4.21.0/en/model_doc/clip#transformers.CLIPTokenizer)
+            to use. If this parameter is `None`, the function will load a new instance of [CLIPTokenizer] by itself, if
+            needed.
+        precision (`torch.dtype`, *optional*, defauts to `None`):
+            If not provided the precision will be set to the precision of the original file.
+        return: A StableDiffusionPipeline object representing the passed-in `.ckpt`/`.safetensors` file.
+    """
+
+    # import pipelines here to avoid circular import error when using from_single_file method
+    from diffusers import (
+        LDMTextToImagePipeline,
+        PaintByExamplePipeline,
+        StableDiffusionControlNetPipeline,
+        StableDiffusionInpaintPipeline,
+        StableDiffusionPipeline,
+        StableDiffusionXLImg2ImgPipeline,
+        StableDiffusionXLPipeline,
+        StableUnCLIPImg2ImgPipeline,
+        StableUnCLIPPipeline,
+    )
+
+    if pipeline_class is None:
+        pipeline_class = StableDiffusionPipeline if not controlnet else StableDiffusionControlNetPipeline
+
+    if prediction_type == "v-prediction":
+        prediction_type = "v_prediction"
+
+    if from_safetensors:
+        from safetensors.torch import load_file as safe_load
+
+        checkpoint = safe_load(checkpoint_path, device="cpu")
+    else:
+        if scan_needed:
+            # scan model
+            scan_result = scan_file_path(checkpoint_path)
+            if scan_result.infected_files != 0:
+                raise Exception("The model {checkpoint_path} is potentially infected by malware. Aborting import.")
+        if device is None:
+            device = "cuda" if torch.cuda.is_available() else "cpu"
+            checkpoint = torch.load(checkpoint_path, map_location=device)
+        else:
+            checkpoint = torch.load(checkpoint_path, map_location=device)
+
+    # Sometimes models don't have the global_step item
+    if "global_step" in checkpoint:
+        global_step = checkpoint["global_step"]
+    else:
+        logger.debug("global_step key not found in model")
+        global_step = None
+
+    # NOTE: this while loop isn't great but this controlnet checkpoint has one additional
+    # "state_dict" key https://huggingface.co/thibaud/controlnet-canny-sd21
+    while "state_dict" in checkpoint:
+        checkpoint = checkpoint["state_dict"]
+
+    logger.debug(f"model_type = {model_type}; original_config_file = {original_config_file}")
+
+    precision_probing_key = "model.diffusion_model.input_blocks.0.0.bias"
+    logger.debug(f"original checkpoint precision == {checkpoint[precision_probing_key].dtype}")
+    precision = precision or checkpoint[precision_probing_key].dtype
+
+    if original_config_file is None:
+        key_name_v2_1 = "model.diffusion_model.input_blocks.2.1.transformer_blocks.0.attn2.to_k.weight"
+        key_name_sd_xl_base = "conditioner.embedders.1.model.transformer.resblocks.9.mlp.c_proj.bias"
+        key_name_sd_xl_refiner = "conditioner.embedders.0.model.transformer.resblocks.9.mlp.c_proj.bias"
+
+        # model_type = "v1"
+        config_url = (
+            "https://raw.githubusercontent.com/CompVis/stable-diffusion/main/configs/stable-diffusion/v1-inference.yaml"
+        )
+
+        if key_name_v2_1 in checkpoint and checkpoint[key_name_v2_1].shape[-1] == 1024:
+            # model_type = "v2"
+            config_url = "https://raw.githubusercontent.com/Stability-AI/stablediffusion/main/configs/stable-diffusion/v2-inference-v.yaml"
+
+            if global_step == 110000:
+                # v2.1 needs to upcast attention
+                upcast_attention = True
+        elif key_name_sd_xl_base in checkpoint:
+            # only base xl has two text embedders
+            config_url = "https://raw.githubusercontent.com/Stability-AI/generative-models/main/configs/inference/sd_xl_base.yaml"
+        elif key_name_sd_xl_refiner in checkpoint:
+            # only refiner xl has embedder and one text embedders
+            config_url = "https://raw.githubusercontent.com/Stability-AI/generative-models/main/configs/inference/sd_xl_refiner.yaml"
+
+        original_config_file = BytesIO(requests.get(config_url).content)
+
+    original_config = OmegaConf.load(original_config_file)
+    if original_config["model"]["params"].get("use_ema") is not None:
+        extract_ema = original_config["model"]["params"]["use_ema"]
+
+    if (
+        model_version in [BaseModelType.StableDiffusion2, BaseModelType.StableDiffusion1]
+        and original_config["model"]["params"].get("parameterization") == "v"
+    ):
+        prediction_type = "v_prediction"
+        upcast_attention = True
+        image_size = 768 if model_version == BaseModelType.StableDiffusion2 else 512
+    else:
+        prediction_type = "epsilon"
+        upcast_attention = False
+        image_size = 512
+
+    # Convert the text model.
+    if (
+        model_type is None
+        and "cond_stage_config" in original_config.model.params
+        and original_config.model.params.cond_stage_config is not None
+    ):
+        model_type = original_config.model.params.cond_stage_config.target.split(".")[-1]
+        logger.debug(f"no `model_type` given, `model_type` inferred as: {model_type}")
+    elif model_type is None and original_config.model.params.network_config is not None:
+        if original_config.model.params.network_config.params.context_dim == 2048:
+            model_type = "SDXL"
+        else:
+            model_type = "SDXL-Refiner"
+        if image_size is None:
+            image_size = 1024
+
+    if num_in_channels is None and pipeline_class == StableDiffusionInpaintPipeline:
+        num_in_channels = 9
+    elif num_in_channels is None:
+        num_in_channels = 4
+
+    if "unet_config" in original_config.model.params:
+        original_config["model"]["params"]["unet_config"]["params"]["in_channels"] = num_in_channels
+
+    if (
+        "parameterization" in original_config["model"]["params"]
+        and original_config["model"]["params"]["parameterization"] == "v"
+    ):
+        if prediction_type is None:
+            # NOTE: For stable diffusion 2 base it is recommended to pass `prediction_type=="epsilon"`
+            # as it relies on a brittle global step parameter here
+            prediction_type = "epsilon" if global_step == 875000 else "v_prediction"
+        if image_size is None:
+            # NOTE: For stable diffusion 2 base one has to pass `image_size==512`
+            # as it relies on a brittle global step parameter here
+            image_size = 512 if global_step == 875000 else 768
+    else:
+        if prediction_type is None:
+            prediction_type = "epsilon"
+        if image_size is None:
+            image_size = 512
+
+    if controlnet is None and "control_stage_config" in original_config.model.params:
+        controlnet = convert_controlnet_checkpoint(
+            checkpoint, original_config, checkpoint_path, image_size, upcast_attention, extract_ema
+        )
+
+    num_train_timesteps = getattr(original_config.model.params, "timesteps", None) or 1000
+
+    if model_type in ["SDXL", "SDXL-Refiner"]:
+        scheduler_dict = {
+            "beta_schedule": "scaled_linear",
+            "beta_start": 0.00085,
+            "beta_end": 0.012,
+            "interpolation_type": "linear",
+            "num_train_timesteps": num_train_timesteps,
+            "prediction_type": "epsilon",
+            "sample_max_value": 1.0,
+            "set_alpha_to_one": False,
+            "skip_prk_steps": True,
+            "steps_offset": 1,
+            "timestep_spacing": "leading",
+        }
+        scheduler = EulerDiscreteScheduler.from_config(scheduler_dict)
+        scheduler_type = "euler"
+    else:
+        beta_start = getattr(original_config.model.params, "linear_start", None) or 0.02
+        beta_end = getattr(original_config.model.params, "linear_end", None) or 0.085
+        scheduler = DDIMScheduler(
+            beta_end=beta_end,
+            beta_schedule="scaled_linear",
+            beta_start=beta_start,
+            num_train_timesteps=num_train_timesteps,
+            steps_offset=1,
+            clip_sample=False,
+            set_alpha_to_one=False,
+            prediction_type=prediction_type,
+        )
+    # make sure scheduler works correctly with DDIM
+    scheduler.register_to_config(clip_sample=False)
+
+    if scheduler_type == "pndm":
+        config = dict(scheduler.config)
+        config["skip_prk_steps"] = True
+        scheduler = PNDMScheduler.from_config(config)
+    elif scheduler_type == "lms":
+        scheduler = LMSDiscreteScheduler.from_config(scheduler.config)
+    elif scheduler_type == "heun":
+        scheduler = HeunDiscreteScheduler.from_config(scheduler.config)
+    elif scheduler_type == "euler":
+        scheduler = EulerDiscreteScheduler.from_config(scheduler.config)
+    elif scheduler_type == "euler-ancestral":
+        scheduler = EulerAncestralDiscreteScheduler.from_config(scheduler.config)
+    elif scheduler_type == "dpm":
+        scheduler = DPMSolverMultistepScheduler.from_config(scheduler.config)
+    elif scheduler_type == "ddim":
+        scheduler = scheduler
+    else:
+        raise ValueError(f"Scheduler of type {scheduler_type} doesn't exist!")
+
+    # Convert the UNet2DConditionModel model.
+    unet_config = create_unet_diffusers_config(original_config, image_size=image_size)
+    unet_config["upcast_attention"] = upcast_attention
+    converted_unet_checkpoint = convert_ldm_unet_checkpoint(
+        checkpoint, unet_config, path=checkpoint_path, extract_ema=extract_ema
+    )
+
+    ctx = init_empty_weights if is_accelerate_available() else nullcontext
+    with ctx():
+        unet = UNet2DConditionModel(**unet_config)
+
+    if is_accelerate_available():
+        for param_name, param in converted_unet_checkpoint.items():
+            set_module_tensor_to_device(unet, param_name, "cpu", value=param)
+    else:
+        unet.load_state_dict(converted_unet_checkpoint)
+
+    # Convert the VAE model.
+    if vae_path is None:
+        vae_config = create_vae_diffusers_config(original_config, image_size=image_size)
+        converted_vae_checkpoint = convert_ldm_vae_checkpoint(checkpoint, vae_config)
+
+        if (
+            "model" in original_config
+            and "params" in original_config.model
+            and "scale_factor" in original_config.model.params
+        ):
+            vae_scaling_factor = original_config.model.params.scale_factor
+        else:
+            vae_scaling_factor = 0.18215  # default SD scaling factor
+
+        vae_config["scaling_factor"] = vae_scaling_factor
+
+        ctx = init_empty_weights if is_accelerate_available() else nullcontext
+        with ctx():
+            vae = AutoencoderKL(**vae_config)
+
+        if is_accelerate_available():
+            for param_name, param in converted_vae_checkpoint.items():
+                set_module_tensor_to_device(vae, param_name, "cpu", value=param)
+        else:
+            vae.load_state_dict(converted_vae_checkpoint)
+    else:
+        vae = AutoencoderKL.from_pretrained(vae_path)
+
+    if model_type == "FrozenOpenCLIPEmbedder":
+        config_name = "stabilityai/stable-diffusion-2"
+        config_kwargs = {"subfolder": "text_encoder"}
+
+        text_model = convert_open_clip_checkpoint(checkpoint, config_name, **config_kwargs)
+        tokenizer = CLIPTokenizer.from_pretrained(CONVERT_MODEL_ROOT / "stable-diffusion-2-clip", subfolder="tokenizer")
+
+        if stable_unclip is None:
+            if controlnet:
+                pipe = pipeline_class(
+                    vae=vae.to(precision),
+                    text_encoder=text_model.to(precision),
+                    tokenizer=tokenizer,
+                    unet=unet.to(precision),
+                    scheduler=scheduler,
+                    controlnet=controlnet,
+                    safety_checker=None,
+                    feature_extractor=None,
+                    requires_safety_checker=False,
+                )
+            else:
+                pipe = pipeline_class(
+                    vae=vae.to(precision),
+                    text_encoder=text_model.to(precision),
+                    tokenizer=tokenizer,
+                    unet=unet.to(precision),
+                    scheduler=scheduler,
+                    safety_checker=None,
+                    feature_extractor=None,
+                    requires_safety_checker=False,
+                )
+        else:
+            image_normalizer, image_noising_scheduler = stable_unclip_image_noising_components(
+                original_config, clip_stats_path=clip_stats_path, device=device
+            )
+
+            if stable_unclip == "img2img":
+                feature_extractor, image_encoder = stable_unclip_image_encoder(original_config)
+
+                pipe = StableUnCLIPImg2ImgPipeline(
+                    # image encoding components
+                    feature_extractor=feature_extractor,
+                    image_encoder=image_encoder,
+                    # image noising components
+                    image_normalizer=image_normalizer,
+                    image_noising_scheduler=image_noising_scheduler,
+                    # regular denoising components
+                    tokenizer=tokenizer,
+                    text_encoder=text_model.to(precision),
+                    unet=unet.to(precision),
+                    scheduler=scheduler,
+                    # vae
+                    vae=vae,
+                )
+            elif stable_unclip == "txt2img":
+                if stable_unclip_prior is None or stable_unclip_prior == "karlo":
+                    karlo_model = "kakaobrain/karlo-v1-alpha"
+                    prior = PriorTransformer.from_pretrained(karlo_model, subfolder="prior")
+
+                    prior_tokenizer = CLIPTokenizer.from_pretrained(CONVERT_MODEL_ROOT / "clip-vit-large-patch14")
+                    prior_text_model = CLIPTextModelWithProjection.from_pretrained(
+                        CONVERT_MODEL_ROOT / "clip-vit-large-patch14"
+                    )
+
+                    prior_scheduler = UnCLIPScheduler.from_pretrained(karlo_model, subfolder="prior_scheduler")
+                    prior_scheduler = DDPMScheduler.from_config(prior_scheduler.config)
+                else:
+                    raise NotImplementedError(f"unknown prior for stable unclip model: {stable_unclip_prior}")
+
+                pipe = StableUnCLIPPipeline(
+                    # prior components
+                    prior_tokenizer=prior_tokenizer,
+                    prior_text_encoder=prior_text_model,
+                    prior=prior,
+                    prior_scheduler=prior_scheduler,
+                    # image noising components
+                    image_normalizer=image_normalizer,
+                    image_noising_scheduler=image_noising_scheduler,
+                    # regular denoising components
+                    tokenizer=tokenizer,
+                    text_encoder=text_model,
+                    unet=unet,
+                    scheduler=scheduler,
+                    # vae
+                    vae=vae,
+                )
+            else:
+                raise NotImplementedError(f"unknown `stable_unclip` type: {stable_unclip}")
+    elif model_type == "PaintByExample":
+        vision_model = convert_paint_by_example_checkpoint(checkpoint)
+        tokenizer = CLIPTokenizer.from_pretrained(CONVERT_MODEL_ROOT / "clip-vit-large-patch14")
+        feature_extractor = AutoFeatureExtractor.from_pretrained(CONVERT_MODEL_ROOT / "stable-diffusion-safety-checker")
+        pipe = PaintByExamplePipeline(
+            vae=vae,
+            image_encoder=vision_model,
+            unet=unet,
+            scheduler=scheduler,
+            safety_checker=None,
+            feature_extractor=feature_extractor,
+        )
+    elif model_type == "FrozenCLIPEmbedder":
+        text_model = convert_ldm_clip_checkpoint(
+            checkpoint, local_files_only=local_files_only, text_encoder=text_encoder
+        )
+        tokenizer = (
+            CLIPTokenizer.from_pretrained(CONVERT_MODEL_ROOT / "clip-vit-large-patch14")
+            if tokenizer is None
+            else tokenizer
+        )
+
+        if load_safety_checker:
+            safety_checker = StableDiffusionSafetyChecker.from_pretrained(
+                CONVERT_MODEL_ROOT / "stable-diffusion-safety-checker"
+            )
+            feature_extractor = AutoFeatureExtractor.from_pretrained(
+                CONVERT_MODEL_ROOT / "stable-diffusion-safety-checker"
+            )
+        else:
+            safety_checker = None
+            feature_extractor = None
+
+        if controlnet:
+            pipe = pipeline_class(
+                vae=vae.to(precision),
+                text_encoder=text_model.to(precision),
+                tokenizer=tokenizer,
+                unet=unet.to(precision),
+                controlnet=controlnet,
+                scheduler=scheduler,
+                safety_checker=safety_checker,
+                feature_extractor=feature_extractor,
+            )
+        else:
+            pipe = pipeline_class(
+                vae=vae.to(precision),
+                text_encoder=text_model.to(precision),
+                tokenizer=tokenizer,
+                unet=unet.to(precision),
+                scheduler=scheduler,
+                safety_checker=safety_checker,
+                feature_extractor=feature_extractor,
+            )
+    elif model_type in ["SDXL", "SDXL-Refiner"]:
+        if model_type == "SDXL":
+            tokenizer = CLIPTokenizer.from_pretrained(CONVERT_MODEL_ROOT / "clip-vit-large-patch14")
+            text_encoder = convert_ldm_clip_checkpoint(checkpoint, local_files_only=local_files_only)
+
+            tokenizer_name = CONVERT_MODEL_ROOT / "CLIP-ViT-bigG-14-laion2B-39B-b160k"
+            tokenizer_2 = CLIPTokenizer.from_pretrained(tokenizer_name, pad_token="!")
+
+            config_name = tokenizer_name
+            config_kwargs = {"projection_dim": 1280}
+            text_encoder_2 = convert_open_clip_checkpoint(
+                checkpoint, config_name, prefix="conditioner.embedders.1.model.", has_projection=True, **config_kwargs
+            )
+
+            pipe = StableDiffusionXLPipeline(
+                vae=vae.to(precision),
+                text_encoder=text_encoder.to(precision),
+                tokenizer=tokenizer,
+                text_encoder_2=text_encoder_2.to(precision),
+                tokenizer_2=tokenizer_2,
+                unet=unet.to(precision),
+                scheduler=scheduler,
+                force_zeros_for_empty_prompt=True,
+            )
+        else:
+            tokenizer = None
+            text_encoder = None
+            tokenizer_name = CONVERT_MODEL_ROOT / "CLIP-ViT-bigG-14-laion2B-39B-b160k"
+            tokenizer_2 = CLIPTokenizer.from_pretrained(tokenizer_name, pad_token="!")
+
+            config_name = tokenizer_name
+            config_kwargs = {"projection_dim": 1280}
+            text_encoder_2 = convert_open_clip_checkpoint(
+                checkpoint, config_name, prefix="conditioner.embedders.0.model.", has_projection=True, **config_kwargs
+            )
+
+            pipe = StableDiffusionXLImg2ImgPipeline(
+                vae=vae.to(precision),
+                text_encoder=text_encoder,
+                tokenizer=tokenizer,
+                text_encoder_2=text_encoder_2,
+                tokenizer_2=tokenizer_2,
+                unet=unet.to(precision),
+                scheduler=scheduler,
+                requires_aesthetics_score=True,
+                force_zeros_for_empty_prompt=False,
+            )
+    else:
+        text_config = create_ldm_bert_config(original_config)
+        text_model = convert_ldm_bert_checkpoint(checkpoint, text_config)
+        tokenizer = BertTokenizerFast.from_pretrained(CONVERT_MODEL_ROOT / "bert-base-uncased")
+        pipe = LDMTextToImagePipeline(vqvae=vae, bert=text_model, tokenizer=tokenizer, unet=unet, scheduler=scheduler)
+
+    return pipe
+
+
+def download_controlnet_from_original_ckpt(
+    checkpoint_path: str,
+    original_config_file: str,
+    image_size: int = 512,
+    extract_ema: bool = False,
+    precision: Optional[torch.dtype] = None,
+    num_in_channels: Optional[int] = None,
+    upcast_attention: Optional[bool] = None,
+    device: str = None,
+    from_safetensors: bool = False,
+    use_linear_projection: Optional[bool] = None,
+    cross_attention_dim: Optional[bool] = None,
+    scan_needed: bool = False,
+) -> DiffusionPipeline:
+
+    from omegaconf import OmegaConf
+
+    if from_safetensors:
+        from safetensors import safe_open
+
+        checkpoint = {}
+        with safe_open(checkpoint_path, framework="pt", device="cpu") as f:
+            for key in f.keys():
+                checkpoint[key] = f.get_tensor(key)
+    else:
+        if scan_needed:
+            # scan model
+            scan_result = scan_file_path(checkpoint_path)
+            if scan_result.infected_files != 0:
+                raise Exception("The model {checkpoint_path} is potentially infected by malware. Aborting import.")
+        if device is None:
+            device = "cuda" if torch.cuda.is_available() else "cpu"
+            checkpoint = torch.load(checkpoint_path, map_location=device)
+        else:
+            checkpoint = torch.load(checkpoint_path, map_location=device)
+
+    # NOTE: this while loop isn't great but this controlnet checkpoint has one additional
+    # "state_dict" key https://huggingface.co/thibaud/controlnet-canny-sd21
+    while "state_dict" in checkpoint:
+        checkpoint = checkpoint["state_dict"]
+
+    # use original precision
+    precision_probing_key = "input_blocks.0.0.bias"
+    ckpt_precision = checkpoint[precision_probing_key].dtype
+    logger.debug(f"original controlnet precision = {ckpt_precision}")
+    precision = precision or ckpt_precision
+
+    original_config = OmegaConf.load(original_config_file)
+
+    if num_in_channels is not None:
+        original_config["model"]["params"]["unet_config"]["params"]["in_channels"] = num_in_channels
+
+    if "control_stage_config" not in original_config.model.params:
+        raise ValueError("`control_stage_config` not present in original config")
+
+    controlnet = convert_controlnet_checkpoint(
+        checkpoint,
+        original_config,
+        checkpoint_path,
+        image_size,
+        upcast_attention,
+        extract_ema,
+        use_linear_projection=use_linear_projection,
+        cross_attention_dim=cross_attention_dim,
+    )
+
+    return controlnet.to(precision)
+
+
+def convert_ldm_vae_to_diffusers(checkpoint, vae_config: DictConfig, image_size: int) -> AutoencoderKL:
+    vae_config = create_vae_diffusers_config(vae_config, image_size=image_size)
+
+    converted_vae_checkpoint = convert_ldm_vae_checkpoint(checkpoint, vae_config)
+
+    vae = AutoencoderKL(**vae_config)
+    vae.load_state_dict(converted_vae_checkpoint)
+    return vae
+
+
+def convert_ckpt_to_diffusers(
+    checkpoint_path: Union[str, Path],
+    dump_path: Union[str, Path],
+    use_safetensors: bool = True,
+    **kwargs,
+):
+    """
+    Takes all the arguments of download_from_original_stable_diffusion_ckpt(),
+    and in addition a path-like object indicating the location of the desired diffusers
+    model to be written.
+    """
+    pipe = download_from_original_stable_diffusion_ckpt(checkpoint_path, **kwargs)
+
+    # TO DO: save correct repo variant
+    pipe.save_pretrained(
+        dump_path,
+        safe_serialization=use_safetensors,
+    )
+
+
+def convert_controlnet_to_diffusers(
+    checkpoint_path: Union[str, Path],
+    dump_path: Union[str, Path],
+    **kwargs,
+):
+    """
+    Takes all the arguments of download_controlnet_from_original_ckpt(),
+    and in addition a path-like object indicating the location of the desired diffusers
+    model to be written.
+    """
+    pipe = download_controlnet_from_original_ckpt(checkpoint_path, **kwargs)
+
+    # TO DO: save correct repo variant
+    pipe.save_pretrained(dump_path, safe_serialization=True)
diff --git a/invokeai/backend/model_manager/load/__init__.py b/invokeai/backend/model_manager/load/__init__.py
index e69de29bb2..357677bb7f 100644
--- a/invokeai/backend/model_manager/load/__init__.py
+++ b/invokeai/backend/model_manager/load/__init__.py
@@ -0,0 +1,35 @@
+# Copyright (c) 2024 Lincoln D. Stein and the InvokeAI Development Team
+"""
+Init file for the model loader.
+"""
+from importlib import import_module
+from pathlib import Path
+from typing import Optional
+
+from invokeai.app.services.config import InvokeAIAppConfig
+from invokeai.backend.util.logging import InvokeAILogger
+from .load_base import AnyModelLoader, LoadedModel
+from .model_cache.model_cache_default import ModelCache
+from .convert_cache.convert_cache_default import ModelConvertCache
+
+# This registers the subclasses that implement loaders of specific model types
+loaders = [x.stem for x in Path(Path(__file__).parent,'model_loaders').glob('*.py') if x.stem != '__init__']
+for module in loaders:
+    print(f'module={module}')
+    import_module(f"{__package__}.model_loaders.{module}")
+
+__all__ = ["AnyModelLoader", "LoadedModel"]
+
+
+def get_standalone_loader(app_config: Optional[InvokeAIAppConfig]) -> AnyModelLoader:
+    app_config = app_config or InvokeAIAppConfig.get_config()
+    logger = InvokeAILogger.get_logger(config=app_config)
+    return AnyModelLoader(app_config=app_config,
+                          logger=logger,
+                          ram_cache=ModelCache(logger=logger,
+                                               max_cache_size=app_config.ram_cache_size,
+                                               max_vram_cache_size=app_config.vram_cache_size
+                                               ),
+                          convert_cache=ModelConvertCache(app_config.models_convert_cache_path)
+                          )
+
diff --git a/invokeai/backend/model_manager/load/convert_cache/__init__.py b/invokeai/backend/model_manager/load/convert_cache/__init__.py
new file mode 100644
index 0000000000..eb3149be32
--- /dev/null
+++ b/invokeai/backend/model_manager/load/convert_cache/__init__.py
@@ -0,0 +1,4 @@
+from .convert_cache_base import ModelConvertCacheBase
+from .convert_cache_default import ModelConvertCache
+
+__all__ = ['ModelConvertCacheBase', 'ModelConvertCache']
diff --git a/invokeai/backend/model_manager/load/convert_cache/convert_cache_base.py b/invokeai/backend/model_manager/load/convert_cache/convert_cache_base.py
new file mode 100644
index 0000000000..25263f96aa
--- /dev/null
+++ b/invokeai/backend/model_manager/load/convert_cache/convert_cache_base.py
@@ -0,0 +1,28 @@
+"""
+Disk-based converted model cache.
+"""
+from abc import ABC, abstractmethod
+from pathlib import Path
+
+class ModelConvertCacheBase(ABC):
+
+    @property
+    @abstractmethod
+    def max_size(self) -> float:
+        """Return the maximum size of this cache directory."""
+        pass
+
+    @abstractmethod
+    def make_room(self, size: float) -> None:
+        """
+        Make sufficient room in the cache directory for a model of max_size.
+
+        :param size: Size required (GB)
+        """
+        pass
+
+    @abstractmethod
+    def cache_path(self, key: str) -> Path:
+        """Return the path for a model with the indicated key."""
+        pass
+
diff --git a/invokeai/backend/model_manager/load/convert_cache/convert_cache_default.py b/invokeai/backend/model_manager/load/convert_cache/convert_cache_default.py
new file mode 100644
index 0000000000..f799510ec5
--- /dev/null
+++ b/invokeai/backend/model_manager/load/convert_cache/convert_cache_default.py
@@ -0,0 +1,64 @@
+"""
+Placeholder for convert cache implementation.
+"""
+
+from pathlib import Path
+import shutil
+from invokeai.backend.util.logging import InvokeAILogger
+from invokeai.backend.util import GIG, directory_size
+from .convert_cache_base import ModelConvertCacheBase
+
+class ModelConvertCache(ModelConvertCacheBase):
+
+    def __init__(self, cache_path: Path, max_size: float=10.0):
+        """Initialize the convert cache with the base directory and a limit on its maximum size (in GBs)."""
+        if not cache_path.exists():
+            cache_path.mkdir(parents=True)
+        self._cache_path = cache_path
+        self._max_size = max_size
+
+    @property
+    def max_size(self) -> float:
+        """Return the maximum size of this cache directory (GB)."""
+        return self._max_size
+
+    def cache_path(self, key: str) -> Path:
+        """Return the path for a model with the indicated key."""
+        return self._cache_path / key
+
+    def make_room(self, size: float) -> None:
+        """
+        Make sufficient room in the cache directory for a model of max_size.
+
+        :param size: Size required (GB)
+        """
+        size_needed = directory_size(self._cache_path) + size
+        max_size = int(self.max_size) * GIG
+        logger = InvokeAILogger.get_logger()
+
+        if size_needed <= max_size:
+            return
+
+        logger.debug(
+            f"Convert cache has gotten too large {(size_needed / GIG):4.2f} > {(max_size / GIG):4.2f}G.. Trimming."
+        )
+
+        # For this to work, we make the assumption that the directory contains
+        # a 'model_index.json', 'unet/config.json' file, or a 'config.json' file at top level.
+        # This should be true for any diffusers model.
+        def by_atime(path: Path) -> float:
+            for config in ["model_index.json", "unet/config.json", "config.json"]:
+                sentinel = path / config
+                if sentinel.exists():
+                    return sentinel.stat().st_atime
+            return 0.0
+
+        # sort by last access time - least accessed files will be at the end
+        lru_models = sorted(self._cache_path.iterdir(), key=by_atime, reverse=True)
+        logger.debug(f"cached models in descending atime order: {lru_models}")
+        while size_needed > max_size and len(lru_models) > 0:
+            next_victim = lru_models.pop()
+            victim_size = directory_size(next_victim)
+            logger.debug(f"Removing cached converted model {next_victim} to free {victim_size / GIG} GB")
+            shutil.rmtree(next_victim)
+            size_needed -= victim_size
diff --git a/invokeai/backend/model_manager/load/load_base.py b/invokeai/backend/model_manager/load/load_base.py
index 7cb7222b71..3ade83160a 100644
--- a/invokeai/backend/model_manager/load/load_base.py
+++ b/invokeai/backend/model_manager/load/load_base.py
@@ -16,39 +16,11 @@ from logging import Logger
 from pathlib import Path
 from typing import Any, Callable, Dict, Optional, Type, Union
 
-import torch
-from diffusers import DiffusionPipeline
-from injector import inject
-
 from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.app.services.model_records import ModelRecordServiceBase
-from invokeai.backend.model_manager import AnyModelConfig, BaseModelType, ModelFormat, ModelType, SubModelType
-from invokeai.backend.model_manager.convert_cache import ModelConvertCacheBase
-from invokeai.backend.model_manager.onnx_runtime import IAIOnnxRuntimeModel
-from invokeai.backend.model_manager.ram_cache import ModelCacheBase
-
-AnyModel = Union[DiffusionPipeline, torch.nn.Module, IAIOnnxRuntimeModel]
-
-
-class ModelLockerBase(ABC):
-    """Base class for the model locker used by the loader."""
-
-    @abstractmethod
-    def lock(self) -> None:
-        """Lock the contained model and move it into VRAM."""
-        pass
-
-    @abstractmethod
-    def unlock(self) -> None:
-        """Unlock the contained model, and remove it from VRAM."""
-        pass
-
-    @property
-    @abstractmethod
-    def model(self) -> AnyModel:
-        """Return the model."""
-        pass
-
+from invokeai.backend.model_manager import AnyModel, AnyModelConfig, BaseModelType, ModelFormat, ModelType, SubModelType
+from invokeai.backend.model_manager.load.model_cache.model_cache_base import ModelCacheBase
+from invokeai.backend.model_manager.load.model_cache.model_locker import ModelLockerBase
+from invokeai.backend.model_manager.load.convert_cache.convert_cache_base import ModelConvertCacheBase
 
 @dataclass
 class LoadedModel:
@@ -69,7 +41,7 @@ class LoadedModel:
     @property
     def model(self) -> AnyModel:
         """Return the model without locking it."""
-        return self.locker.model()
+        return self.locker.model
 
 
 class ModelLoaderBase(ABC):
@@ -89,9 +61,9 @@ class ModelLoaderBase(ABC):
     @abstractmethod
     def load_model(self, model_config: AnyModelConfig, submodel_type: Optional[SubModelType] = None) -> LoadedModel:
         """
-        Return a model given its key.
+        Return a model given its confguration.
 
-        Given a model key identified in the model configuration backend,
+        Given a model identified in the model configuration backend,
         return a ModelInfo object that can be used to retrieve the model.
 
         :param model_config: Model configuration, as returned by ModelConfigRecordStore
@@ -115,34 +87,32 @@ class AnyModelLoader:
     # this tracks the loader subclasses
     _registry: Dict[str, Type[ModelLoaderBase]] = {}
 
-    @inject
     def __init__(
         self,
-        store: ModelRecordServiceBase,
         app_config: InvokeAIAppConfig,
         logger: Logger,
         ram_cache: ModelCacheBase,
         convert_cache: ModelConvertCacheBase,
     ):
-        """Store the provided ModelRecordServiceBase and empty the registry."""
-        self._store = store
+        """Initialize AnyModelLoader with its dependencies."""
         self._app_config = app_config
         self._logger = logger
         self._ram_cache = ram_cache
         self._convert_cache = convert_cache
 
-    def get_model(self, key: str, submodel_type: Optional[SubModelType] = None) -> LoadedModel:
-        """
-        Return a model given its key.
+    @property
+    def ram_cache(self) -> ModelCacheBase:
+        """Return the RAM cache associated used by the loaders."""
+        return self._ram_cache
 
-        Given a model key identified in the model configuration backend,
-        return a ModelInfo object that can be used to retrieve the model.
+    def load_model(self, model_config: AnyModelConfig, submodel_type: Optional[SubModelType]=None) -> LoadedModel:
+        """
+        Return a model given its configuration.
 
         :param key: model key, as known to the config backend
         :param submodel_type: an ModelType enum indicating the portion of
                the model to retrieve (e.g. ModelType.Vae)
         """
-        model_config = self._store.get_model(key)
         implementation = self.__class__.get_implementation(
             base=model_config.base, type=model_config.type, format=model_config.format
         )
@@ -165,7 +135,7 @@ class AnyModelLoader:
         implementation = cls._registry.get(key1) or cls._registry.get(key2)
         if not implementation:
             raise NotImplementedError(
-                "No subclass of LoadedModel is registered for base={base}, type={type}, format={format}"
+                f"No subclass of LoadedModel is registered for base={base}, type={type}, format={format}"
             )
         return implementation
 
@@ -176,18 +146,10 @@ class AnyModelLoader:
         """Define a decorator which registers the subclass of loader."""
 
         def decorator(subclass: Type[ModelLoaderBase]) -> Type[ModelLoaderBase]:
-            print("Registering class", subclass.__name__)
+            print("DEBUG: Registering class", subclass.__name__)
             key = cls._to_registry_key(base, type, format)
             cls._registry[key] = subclass
             return subclass
 
         return decorator
 
-
-# in _init__.py will call something like
-# def configure_loader_dependencies(binder):
-#     binder.bind(ModelRecordServiceBase, ApiDependencies.invoker.services.model_records, scope=singleton)
-#     binder.bind(InvokeAIAppConfig, ApiDependencies.invoker.services.configuration, scope=singleton)
-# etc
-# injector = Injector(configure_loader_dependencies)
-# loader = injector.get(ModelFactory)
diff --git a/invokeai/backend/model_manager/load/load_default.py b/invokeai/backend/model_manager/load/load_default.py
index eb2d432aaa..0b028235fd 100644
--- a/invokeai/backend/model_manager/load/load_default.py
+++ b/invokeai/backend/model_manager/load/load_default.py
@@ -8,15 +8,14 @@ from typing import Any, Dict, Optional, Tuple
 
 from diffusers import ModelMixin
 from diffusers.configuration_utils import ConfigMixin
-from injector import inject
 
 from invokeai.app.services.config import InvokeAIAppConfig
 from invokeai.backend.model_manager import AnyModelConfig, InvalidModelConfigException, ModelRepoVariant, SubModelType
-from invokeai.backend.model_manager.convert_cache import ModelConvertCacheBase
+from invokeai.backend.model_manager.load.convert_cache import ModelConvertCacheBase
 from invokeai.backend.model_manager.load.load_base import AnyModel, LoadedModel, ModelLoaderBase
 from invokeai.backend.model_manager.load.model_util import calc_model_size_by_fs
 from invokeai.backend.model_manager.load.optimizations import skip_torch_weight_init
-from invokeai.backend.model_manager.ram_cache import ModelCacheBase, ModelLockerBase
+from invokeai.backend.model_manager.load.model_cache.model_cache_base import ModelCacheBase, ModelLockerBase
 from invokeai.backend.util.devices import choose_torch_device, torch_dtype
 
 
@@ -35,7 +34,6 @@ class ConfigLoader(ConfigMixin):
 class ModelLoader(ModelLoaderBase):
     """Default implementation of ModelLoaderBase."""
 
-    @inject  # can inject instances of each of the classes in the call signature
     def __init__(
         self,
         app_config: InvokeAIAppConfig,
@@ -87,18 +85,15 @@ class ModelLoader(ModelLoaderBase):
     def _convert_if_needed(
         self, config: AnyModelConfig, model_path: Path, submodel_type: Optional[SubModelType] = None
     ) -> Path:
-        if not self._needs_conversion(config):
-            return model_path
+        cache_path: Path = self._convert_cache.cache_path(config.key)
+
+        if not self._needs_conversion(config, model_path, cache_path):
+            return cache_path if cache_path.exists() else model_path
 
         self._convert_cache.make_room(self._size or self.get_size_fs(config, model_path, submodel_type))
-        cache_path: Path = self._convert_cache.cache_path(config.key)
-        if cache_path.exists():
-            return cache_path
+        return self._convert_model(config, model_path, cache_path)
 
-        self._convert_model(model_path, cache_path)
-        return cache_path
-
-    def _needs_conversion(self, config: AnyModelConfig) -> bool:
+    def _needs_conversion(self, config: AnyModelConfig, model_path: Path, cache_path: Path) -> bool:
         return False
 
     def _load_if_needed(
@@ -133,7 +128,7 @@ class ModelLoader(ModelLoaderBase):
             variant=config.repo_variant if hasattr(config, "repo_variant") else None,
         )
 
-    def _convert_model(self, model_path: Path, cache_path: Path) -> None:
+    def _convert_model(self, config: AnyModelConfig, weights_path: Path, output_path: Path) -> Path:
         raise NotImplementedError
 
     def _load_model(
diff --git a/invokeai/backend/model_manager/load/model_cache/__init__.py b/invokeai/backend/model_manager/load/model_cache/__init__.py
new file mode 100644
index 0000000000..776b9d8936
--- /dev/null
+++ b/invokeai/backend/model_manager/load/model_cache/__init__.py
@@ -0,0 +1,5 @@
+"""Init file for RamCache."""
+
+from .model_cache_base import ModelCacheBase
+from .model_cache_default import ModelCache
+_all__ = ['ModelCacheBase', 'ModelCache']
diff --git a/invokeai/backend/model_manager/load/ram_cache/ram_cache_base.py b/invokeai/backend/model_manager/load/model_cache/model_cache_base.py
similarity index 77%
rename from invokeai/backend/model_manager/load/ram_cache/ram_cache_base.py
rename to invokeai/backend/model_manager/load/model_cache/model_cache_base.py
index cd80d1e78b..50b69d961c 100644
--- a/invokeai/backend/model_manager/load/ram_cache/ram_cache_base.py
+++ b/invokeai/backend/model_manager/load/model_cache/model_cache_base.py
@@ -10,34 +10,41 @@ model will be cleared and (re)loaded from disk when next needed.
 from abc import ABC, abstractmethod
 from dataclasses import dataclass, field
 from logging import Logger
-from typing import Dict, Optional
+from typing import Dict, Optional, TypeVar, Generic
 
 import torch
 
-from invokeai.backend.model_manager import SubModelType
-from invokeai.backend.model_manager.load.load_base import AnyModel, ModelLockerBase
+from invokeai.backend.model_manager import AnyModel, SubModelType
 
+class ModelLockerBase(ABC):
+    """Base class for the model locker used by the loader."""
+
+    @abstractmethod
+    def lock(self) -> AnyModel:
+        """Lock the contained model and move it into VRAM."""
+        pass
+
+    @abstractmethod
+    def unlock(self) -> None:
+        """Unlock the contained model, and remove it from VRAM."""
+        pass
+
+    @property
+    @abstractmethod
+    def model(self) -> AnyModel:
+        """Return the model."""
+        pass
+
+T = TypeVar("T")
 
 @dataclass
-class CacheStats(object):
-    """Data object to record statistics on cache hits/misses."""
-
-    hits: int = 0  # cache hits
-    misses: int = 0  # cache misses
-    high_watermark: int = 0  # amount of cache used
-    in_cache: int = 0  # number of models in cache
-    cleared: int = 0  # number of models cleared to make space
-    cache_size: int = 0  # total size of cache
-    loaded_model_sizes: Dict[str, int] = field(default_factory=dict)
-
-
-@dataclass
-class CacheRecord:
+class CacheRecord(Generic[T]):
     """Elements of the cache."""
 
     key: str
-    model: AnyModel
+    model: T
     size: int
+    loaded: bool = False
     _locks: int = 0
 
     def lock(self) -> None:
@@ -55,7 +62,7 @@ class CacheRecord:
         return self._locks > 0
 
 
-class ModelCacheBase(ABC):
+class ModelCacheBase(ABC, Generic[T]):
     """Virtual base class for RAM model cache."""
 
     @property
@@ -76,8 +83,14 @@ class ModelCacheBase(ABC):
         """Return true if the cache is configured to lazily offload models in VRAM."""
         pass
 
+    @property
     @abstractmethod
-    def offload_unlocked_models(self) -> None:
+    def max_cache_size(self) -> float:
+        """Return true if the cache is configured to lazily offload models in VRAM."""
+        pass
+
+    @abstractmethod
+    def offload_unlocked_models(self, size_required: int) -> None:
         """Offload from VRAM any models not actively in use."""
         pass
 
@@ -101,7 +114,7 @@ class ModelCacheBase(ABC):
     def put(
         self,
         key: str,
-        model: AnyModel,
+        model: T,
         submodel_type: Optional[SubModelType] = None,
     ) -> None:
         """Store model under key and optional submodel_type."""
@@ -134,11 +147,6 @@ class ModelCacheBase(ABC):
         """Get the total size of the models currently cached."""
         pass
 
-    @abstractmethod
-    def get_stats(self) -> CacheStats:
-        """Return cache hit/miss/size statistics."""
-        pass
-
     @abstractmethod
     def print_cuda_stats(self) -> None:
         """Log debugging information on CUDA usage."""
diff --git a/invokeai/backend/model_manager/load/ram_cache/ram_cache_default.py b/invokeai/backend/model_manager/load/model_cache/model_cache_default.py
similarity index 63%
rename from invokeai/backend/model_manager/load/ram_cache/ram_cache_default.py
rename to invokeai/backend/model_manager/load/model_cache/model_cache_default.py
index bd43e978c8..961f68a4be 100644
--- a/invokeai/backend/model_manager/load/ram_cache/ram_cache_default.py
+++ b/invokeai/backend/model_manager/load/model_cache/model_cache_default.py
@@ -18,6 +18,7 @@ context. Use like this:
 
 """
 
+import gc
 import math
 import time
 from contextlib import suppress
@@ -26,14 +27,14 @@ from typing import Any, Dict, List, Optional
 
 import torch
 
-from invokeai.app.services.model_records import UnknownModelException
 from invokeai.backend.model_manager import SubModelType
-from invokeai.backend.model_manager.load.load_base import AnyModel, ModelLockerBase
+from invokeai.backend.model_manager.load.load_base import AnyModel
 from invokeai.backend.model_manager.load.memory_snapshot import MemorySnapshot, get_pretty_snapshot_diff
 from invokeai.backend.model_manager.load.model_util import calc_model_size_by_data
-from invokeai.backend.model_manager.load.ram_cache.ram_cache_base import CacheRecord, CacheStats, ModelCacheBase
 from invokeai.backend.util.devices import choose_torch_device
 from invokeai.backend.util.logging import InvokeAILogger
+from .model_cache_base import CacheRecord, ModelCacheBase
+from .model_locker import ModelLockerBase, ModelLocker
 
 if choose_torch_device() == torch.device("mps"):
     from torch import mps
@@ -52,7 +53,7 @@ GIG = 1073741824
 MB = 2**20
 
 
-class ModelCache(ModelCacheBase):
+class ModelCache(ModelCacheBase[AnyModel]):
     """Implementation of ModelCacheBase."""
 
     def __init__(
@@ -92,62 +93,9 @@ class ModelCache(ModelCacheBase):
         self._logger = logger or InvokeAILogger.get_logger(self.__class__.__name__)
         self._log_memory_usage = log_memory_usage
 
-        # used for stats collection
-        self.stats = None
-
-        self._cached_models: Dict[str, CacheRecord] = {}
+        self._cached_models: Dict[str, CacheRecord[AnyModel]] = {}
         self._cache_stack: List[str] = []
 
-    class ModelLocker(ModelLockerBase):
-        """Internal class that mediates movement in and out of GPU."""
-
-        def __init__(self, cache: ModelCacheBase, cache_entry: CacheRecord):
-            """
-            Initialize the model locker.
-
-            :param cache: The ModelCache object
-            :param cache_entry: The entry in the model cache
-            """
-            self._cache = cache
-            self._cache_entry = cache_entry
-
-        @property
-        def model(self) -> AnyModel:
-            """Return the model without moving it around."""
-            return self._cache_entry.model
-
-        def lock(self) -> Any:
-            """Move the model into the execution device (GPU) and lock it."""
-            if not hasattr(self.model, "to"):
-                return self.model
-
-            # NOTE that the model has to have the to() method in order for this code to move it into GPU!
-            self._cache_entry.lock()
-
-            try:
-                if self._cache.lazy_offloading:
-                    self._cache.offload_unlocked_models()
-
-                self._cache.move_model_to_device(self._cache_entry, self._cache.execution_device)
-
-                self._cache.logger.debug(f"Locking {self._cache_entry.key} in {self._cache.execution_device}")
-                self._cache.print_cuda_stats()
-
-            except Exception:
-                self._cache_entry.unlock()
-                raise
-            return self.model
-
-        def unlock(self) -> None:
-            """Call upon exit from context."""
-            if not hasattr(self.model, "to"):
-                return
-
-            self._cache_entry.unlock()
-            if not self._cache.lazy_offloading:
-                self._cache.offload_unlocked_models()
-                self._cache.print_cuda_stats()
-
     @property
     def logger(self) -> Logger:
         """Return the logger used by the cache."""
@@ -168,6 +116,11 @@ class ModelCache(ModelCacheBase):
         """Return the exection device (e.g. "cuda" for VRAM)."""
         return self._execution_device
 
+    @property
+    def max_cache_size(self) -> float:
+        """Return the cap on cache size."""
+        return self._max_cache_size
+
     def cache_size(self) -> int:
         """Get the total size of the models currently cached."""
         total = 0
@@ -207,18 +160,18 @@ class ModelCache(ModelCacheBase):
         """
         Retrieve model using key and optional submodel_type.
 
-        This may return an UnknownModelException if the model is not in the cache.
+        This may return an IndexError if the model is not in the cache.
         """
         key = self._make_cache_key(key, submodel_type)
         if key not in self._cached_models:
-            raise UnknownModelException
+            raise IndexError(f"The model with key {key} is not in the cache.")
 
         # this moves the entry to the top (right end) of the stack
         with suppress(Exception):
             self._cache_stack.remove(key)
         self._cache_stack.append(key)
         cache_entry = self._cached_models[key]
-        return self.ModelLocker(
+        return ModelLocker(
             cache=self,
             cache_entry=cache_entry,
         )
@@ -234,19 +187,19 @@ class ModelCache(ModelCacheBase):
         else:
             return model_key
 
-    def offload_unlocked_models(self) -> None:
+    def offload_unlocked_models(self, size_required: int) -> None:
         """Move any unused models from VRAM."""
         reserved = self._max_vram_cache_size * GIG
-        vram_in_use = torch.cuda.memory_allocated()
-        self.logger.debug(f"{(vram_in_use/GIG):.2f}GB VRAM used for models; max allowed={(reserved/GIG):.2f}GB")
+        vram_in_use = torch.cuda.memory_allocated() + size_required
+        self.logger.debug(f"{(vram_in_use/GIG):.2f}GB VRAM needed for models; max allowed={(reserved/GIG):.2f}GB")
         for _, cache_entry in sorted(self._cached_models.items(), key=lambda x: x[1].size):
             if vram_in_use <= reserved:
                 break
             if not cache_entry.locked:
                 self.move_model_to_device(cache_entry, self.storage_device)
-
-                vram_in_use = torch.cuda.memory_allocated()
-                self.logger.debug(f"{(vram_in_use/GIG):.2f}GB VRAM used for models; max allowed={(reserved/GIG):.2f}GB")
+                cache_entry.loaded = False
+                vram_in_use = torch.cuda.memory_allocated() + size_required
+                self.logger.debug(f"{(vram_in_use/GIG):.2f}GB VRAM now available for models; max allowed={(reserved/GIG):.2f}GB")
 
         torch.cuda.empty_cache()
         if choose_torch_device() == torch.device("mps"):
@@ -305,28 +258,111 @@ class ModelCache(ModelCacheBase):
     def print_cuda_stats(self) -> None:
         """Log CUDA diagnostics."""
         vram = "%4.2fG" % (torch.cuda.memory_allocated() / GIG)
-        ram = "%4.2fG" % self.cache_size()
+        ram = "%4.2fG" % (self.cache_size() / GIG)
 
-        cached_models = 0
-        loaded_models = 0
-        locked_models = 0
+        in_ram_models = 0
+        in_vram_models = 0
+        locked_in_vram_models = 0
         for cache_record in self._cached_models.values():
-            cached_models += 1
             assert hasattr(cache_record.model, "device")
-            if cache_record.model.device is self.storage_device:
-                loaded_models += 1
+            if cache_record.model.device == self.storage_device:
+                in_ram_models += 1
+            else:
+                in_vram_models += 1
             if cache_record.locked:
-                locked_models += 1
+                locked_in_vram_models += 1
 
         self.logger.debug(
-            f"Current VRAM/RAM usage: {vram}/{ram}; cached_models/loaded_models/locked_models/ ="
-            f" {cached_models}/{loaded_models}/{locked_models}"
+            f"Current VRAM/RAM usage: {vram}/{ram}; models_in_ram/models_in_vram(locked) ="
+            f" {in_ram_models}/{in_vram_models}({locked_in_vram_models})"
         )
 
-    def get_stats(self) -> CacheStats:
-        """Return cache hit/miss/size statistics."""
-        raise NotImplementedError
-
-    def make_room(self, size: int) -> None:
+    def make_room(self, model_size: int) -> None:
         """Make enough room in the cache to accommodate a new model of indicated size."""
-        raise NotImplementedError
+        # calculate how much memory this model will require
+        # multiplier = 2 if self.precision==torch.float32 else 1
+        bytes_needed = model_size
+        maximum_size = self.max_cache_size * GIG  # stored in GB, convert to bytes
+        current_size = self.cache_size()
+
+        if current_size + bytes_needed > maximum_size:
+            self.logger.debug(
+                f"Max cache size exceeded: {(current_size/GIG):.2f}/{self.max_cache_size:.2f} GB, need an additional"
+                f" {(bytes_needed/GIG):.2f} GB"
+            )
+
+        self.logger.debug(f"Before unloading: cached_models={len(self._cached_models)}")
+
+        pos = 0
+        models_cleared = 0
+        while current_size + bytes_needed > maximum_size and pos < len(self._cache_stack):
+            model_key = self._cache_stack[pos]
+            cache_entry = self._cached_models[model_key]
+
+            refs = sys.getrefcount(cache_entry.model)
+
+            # HACK: This is a workaround for a memory-management issue that we haven't tracked down yet. We are directly
+            # going against the advice in the Python docs by using `gc.get_referrers(...)` in this way:
+            # https://docs.python.org/3/library/gc.html#gc.get_referrers
+
+            # manualy clear local variable references of just finished function calls
+            # for some reason python don't want to collect it even by gc.collect() immidiately
+            if refs > 2:
+                while True:
+                    cleared = False
+                    for referrer in gc.get_referrers(cache_entry.model):
+                        if type(referrer).__name__ == "frame":
+                            # RuntimeError: cannot clear an executing frame
+                            with suppress(RuntimeError):
+                                referrer.clear()
+                                cleared = True
+                                # break
+
+                    # repeat if referrers changes(due to frame clear), else exit loop
+                    if cleared:
+                        gc.collect()
+                    else:
+                        break
+
+            device = cache_entry.model.device if hasattr(cache_entry.model, "device") else None
+            self.logger.debug(
+                f"Model: {model_key}, locks: {cache_entry._locks}, device: {device}, loaded: {cache_entry.loaded},"
+                f" refs: {refs}"
+            )
+
+            # Expected refs:
+            # 1 from cache_entry
+            # 1 from getrefcount function
+            # 1 from onnx runtime object
+            if not cache_entry.locked and refs <= (3 if "onnx" in model_key else 2):
+                self.logger.debug(
+                    f"Unloading model {model_key} to free {(model_size/GIG):.2f} GB (-{(cache_entry.size/GIG):.2f} GB)"
+                )
+                current_size -= cache_entry.size
+                models_cleared += 1
+                del self._cache_stack[pos]
+                del self._cached_models[model_key]
+                del cache_entry
+
+            else:
+                pos += 1
+
+        if models_cleared > 0:
+            # There would likely be some 'garbage' to be collected regardless of whether a model was cleared or not, but
+            # there is a significant time cost to calling `gc.collect()`, so we want to use it sparingly. (The time cost
+            # is high even if no garbage gets collected.)
+            #
+            # Calling gc.collect(...) when a model is cleared seems like a good middle-ground:
+            # - If models had to be cleared, it's a signal that we are close to our memory limit.
+            # - If models were cleared, there's a good chance that there's a significant amount of garbage to be
+            #   collected.
+            #
+            # Keep in mind that gc is only responsible for handling reference cycles. Most objects should be cleaned up
+            # immediately when their reference count hits 0.
+            gc.collect()
+
+        torch.cuda.empty_cache()
+        if choose_torch_device() == torch.device("mps"):
+            mps.empty_cache()
+
+        self.logger.debug(f"After unloading: cached_models={len(self._cached_models)}")
diff --git a/invokeai/backend/model_manager/load/model_cache/model_locker.py b/invokeai/backend/model_manager/load/model_cache/model_locker.py
new file mode 100644
index 0000000000..506d012949
--- /dev/null
+++ b/invokeai/backend/model_manager/load/model_cache/model_locker.py
@@ -0,0 +1,59 @@
+"""
+Base class and implementation of a class that moves models in and out of VRAM.
+"""
+
+from abc import ABC, abstractmethod
+from invokeai.backend.model_manager import AnyModel
+from .model_cache_base import ModelLockerBase, ModelCacheBase, CacheRecord
+
+class ModelLocker(ModelLockerBase):
+    """Internal class that mediates movement in and out of GPU."""
+
+    def __init__(self, cache: ModelCacheBase[AnyModel], cache_entry: CacheRecord[AnyModel]):
+        """
+        Initialize the model locker.
+
+        :param cache: The ModelCache object
+        :param cache_entry: The entry in the model cache
+        """
+        self._cache = cache
+        self._cache_entry = cache_entry
+
+    @property
+    def model(self) -> AnyModel:
+        """Return the model without moving it around."""
+        return self._cache_entry.model
+
+    def lock(self) -> AnyModel:
+        """Move the model into the execution device (GPU) and lock it."""
+        if not hasattr(self.model, "to"):
+            return self.model
+
+        # NOTE that the model has to have the to() method in order for this code to move it into GPU!
+        self._cache_entry.lock()
+
+        try:
+            if self._cache.lazy_offloading:
+                self._cache.offload_unlocked_models(self._cache_entry.size)
+
+            self._cache.move_model_to_device(self._cache_entry, self._cache.execution_device)
+            self._cache_entry.loaded = True
+
+            self._cache.logger.debug(f"Locking {self._cache_entry.key} in {self._cache.execution_device}")
+            self._cache.print_cuda_stats()
+
+        except Exception:
+            self._cache_entry.unlock()
+            raise
+        return self.model
+
+    def unlock(self) -> None:
+        """Call upon exit from context."""
+        if not hasattr(self.model, "to"):
+            return
+
+        self._cache_entry.unlock()
+        if not self._cache.lazy_offloading:
+            self._cache.offload_unlocked_models(self._cache_entry.size)
+            self._cache.print_cuda_stats()
+
diff --git a/invokeai/backend/model_manager/load/model_loaders/__init__.py b/invokeai/backend/model_manager/load/model_loaders/__init__.py
new file mode 100644
index 0000000000..962cba5481
--- /dev/null
+++ b/invokeai/backend/model_manager/load/model_loaders/__init__.py
@@ -0,0 +1,3 @@
+"""
+Init file for model_loaders.
+"""
diff --git a/invokeai/backend/model_manager/load/model_loaders/vae.py b/invokeai/backend/model_manager/load/model_loaders/vae.py
new file mode 100644
index 0000000000..6f21c3d090
--- /dev/null
+++ b/invokeai/backend/model_manager/load/model_loaders/vae.py
@@ -0,0 +1,83 @@
+# Copyright (c) 2024, Lincoln D. Stein and the InvokeAI Development Team
+"""Class for VAE model loading in InvokeAI."""
+
+from pathlib import Path
+from typing import Optional
+
+import torch
+import safetensors
+from omegaconf import OmegaConf, DictConfig
+from invokeai.backend.util.devices import torch_dtype
+from invokeai.backend.model_manager import AnyModel, AnyModelConfig, BaseModelType, ModelFormat, ModelRepoVariant, ModelType, SubModelType
+from invokeai.backend.model_manager.load.load_base import AnyModelLoader
+from invokeai.backend.model_manager.load.load_default import ModelLoader
+from invokeai.backend.model_manager.convert_ckpt_to_diffusers import convert_ldm_vae_to_diffusers
+
+@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.Vae, format=ModelFormat.Diffusers)
+@AnyModelLoader.register(base=BaseModelType.StableDiffusion1, type=ModelType.Vae, format=ModelFormat.Checkpoint)
+@AnyModelLoader.register(base=BaseModelType.StableDiffusion2, type=ModelType.Vae, format=ModelFormat.Checkpoint)
+class VaeDiffusersModel(ModelLoader):
+    """Class to load VAE models."""
+
+    def _load_model(
+        self,
+        model_path: Path,
+        model_variant: Optional[ModelRepoVariant] = None,
+        submodel_type: Optional[SubModelType] = None,
+    ) -> AnyModel:
+        if submodel_type is not None:
+            raise Exception("There are no submodels in VAEs")
+        vae_class = self._get_hf_load_class(model_path)
+        variant = model_variant.value if model_variant else None
+        result: AnyModel = vae_class.from_pretrained(
+            model_path, torch_dtype=self._torch_dtype, variant=variant
+        )  # type: ignore
+        return result
+
+    def _needs_conversion(self, config: AnyModelConfig, model_path: Path, dest_path: Path) -> bool:
+        print(f'DEBUG: last_modified={config.last_modified}')
+        print(f'DEBUG: cache_path={(dest_path / "config.json").stat().st_mtime}')
+        print(f'DEBUG: model_path={model_path.stat().st_mtime}')
+        if config.format != ModelFormat.Checkpoint:
+            return False
+        elif dest_path.exists() \
+             and (dest_path / "config.json").stat().st_mtime >= config.last_modified \
+             and (dest_path / "config.json").stat().st_mtime >= model_path.stat().st_mtime:
+            return False
+        else:
+            return True
+
+    def _convert_model(self,
+                       config: AnyModelConfig,
+                       weights_path: Path,
+                       output_path: Path
+                       ) -> Path:
+        if config.base not in {BaseModelType.StableDiffusion1, BaseModelType.StableDiffusion2}:
+            raise Exception(f"Vae conversion not supported for model type: {config.base}")
+        else:
+            config_file = 'v1-inference.yaml' if config.base == BaseModelType.StableDiffusion1 else "v2-inference-v.yaml"
+
+        if weights_path.suffix == ".safetensors":
+            checkpoint = safetensors.torch.load_file(weights_path, device="cpu")
+        else:
+            checkpoint = torch.load(weights_path, map_location="cpu")
+
+        dtype = torch_dtype()
+
+        # sometimes weights are hidden under "state_dict", and sometimes not
+        if "state_dict" in checkpoint:
+            checkpoint = checkpoint["state_dict"]
+
+        ckpt_config = OmegaConf.load(self._app_config.legacy_conf_path / config_file)
+        assert isinstance(ckpt_config, DictConfig)
+
+        print(f'DEBUG: CONVERTIGN')
+        vae_model = convert_ldm_vae_to_diffusers(
+            checkpoint=checkpoint,
+            vae_config=ckpt_config,
+            image_size=512,
+        )
+        vae_model.to(dtype) # set precision appropriately
+        vae_model.save_pretrained(output_path, safe_serialization=True, torch_dtype=dtype)
+        return output_path
+
diff --git a/invokeai/backend/model_manager/load/model_util.py b/invokeai/backend/model_manager/load/model_util.py
index 18407cbca2..7c27e66472 100644
--- a/invokeai/backend/model_manager/load/model_util.py
+++ b/invokeai/backend/model_manager/load/model_util.py
@@ -48,6 +48,9 @@ def _calc_onnx_model_by_data(model: IAIOnnxRuntimeModel) -> int:
 
 def calc_model_size_by_fs(model_path: Path, subfolder: Optional[str] = None, variant: Optional[str] = None) -> int:
     """Estimate the size of a model on disk in bytes."""
+    if model_path.is_file():
+        return model_path.stat().st_size
+        
     if subfolder is not None:
         model_path = model_path / subfolder
 
diff --git a/invokeai/backend/model_manager/load/ram_cache/__init__.py b/invokeai/backend/model_manager/load/ram_cache/__init__.py
deleted file mode 100644
index e69de29bb2..0000000000
diff --git a/invokeai/backend/model_manager/load/vae.py b/invokeai/backend/model_manager/load/vae.py
deleted file mode 100644
index a6cbe241e1..0000000000
--- a/invokeai/backend/model_manager/load/vae.py
+++ /dev/null
@@ -1,31 +0,0 @@
-# Copyright (c) 2024, Lincoln D. Stein and the InvokeAI Development Team
-"""Class for VAE model loading in InvokeAI."""
-
-from pathlib import Path
-from typing import Dict, Optional
-
-import torch
-
-from invokeai.backend.model_manager import BaseModelType, ModelFormat, ModelRepoVariant, ModelType, SubModelType
-from invokeai.backend.model_manager.load.load_base import AnyModelLoader
-from invokeai.backend.model_manager.load.load_default import ModelLoader
-
-
-@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.Vae, format=ModelFormat.Diffusers)
-class VaeDiffusersModel(ModelLoader):
-    """Class to load VAE models."""
-
-    def _load_model(
-        self,
-        model_path: Path,
-        model_variant: Optional[ModelRepoVariant] = None,
-        submodel_type: Optional[SubModelType] = None,
-    ) -> Dict[str, torch.Tensor]:
-        if submodel_type is not None:
-            raise Exception("There are no submodels in VAEs")
-        vae_class = self._get_hf_load_class(model_path)
-        variant = model_variant.value if model_variant else ""
-        result: Dict[str, torch.Tensor] = vae_class.from_pretrained(
-            model_path, torch_dtype=self._torch_dtype, variant=variant
-        )  # type: ignore
-        return result
diff --git a/invokeai/backend/util/__init__.py b/invokeai/backend/util/__init__.py
index 87ae1480f5..0164dffe30 100644
--- a/invokeai/backend/util/__init__.py
+++ b/invokeai/backend/util/__init__.py
@@ -12,6 +12,14 @@ from .devices import (  # noqa: F401
     torch_dtype,
 )
 from .logging import InvokeAILogger
-from .util import Chdir, ask_user, download_with_resume, instantiate_from_config, url_attachment_name  # noqa: F401
+from .util import ( # TO DO: Clean this up; remove the unused symbols
+    GIG,
+    Chdir,
+    ask_user,  # noqa
+    directory_size,
+    download_with_resume,
+    instantiate_from_config, # noqa
+    url_attachment_name,  # noqa
+    )
 
-__all__ = ["Chdir", "InvokeAILogger", "choose_precision", "choose_torch_device"]
+__all__ = ["GIG", "directory_size","Chdir", "download_with_resume", "InvokeAILogger", "choose_precision", "choose_torch_device"]
diff --git a/invokeai/backend/util/devices.py b/invokeai/backend/util/devices.py
index d6d3ad727f..ad3f4e139a 100644
--- a/invokeai/backend/util/devices.py
+++ b/invokeai/backend/util/devices.py
@@ -1,7 +1,7 @@
 from __future__ import annotations
 
 from contextlib import nullcontext
-from typing import Union
+from typing import Union, Optional
 
 import torch
 from torch import autocast
@@ -43,7 +43,8 @@ def choose_precision(device: torch.device) -> str:
     return "float32"
 
 
-def torch_dtype(device: torch.device) -> torch.dtype:
+def torch_dtype(device: Optional[torch.device] = None) -> torch.dtype:
+    device = device or choose_torch_device()
     precision = choose_precision(device)
     if precision == "float16":
         return torch.float16
diff --git a/invokeai/backend/util/util.py b/invokeai/backend/util/util.py
index 13751e2770..6589aa7278 100644
--- a/invokeai/backend/util/util.py
+++ b/invokeai/backend/util/util.py
@@ -24,6 +24,20 @@ import invokeai.backend.util.logging as logger
 
 from .devices import torch_dtype
 
+# actual size of a gig
+GIG = 1073741824
+
+def directory_size(directory: Path) -> int:
+    """
+    Return the aggregate size of all files in a directory (bytes).
+    """
+    sum = 0
+    for root, dirs, files in os.walk(directory):
+        for f in files:
+            sum += Path(root, f).stat().st_size
+        for d in dirs:
+            sum += Path(root, d).stat().st_size
+    return sum
 
 def log_txt_as_img(wh, xc, size=10):
     # wh a tuple of (width, height)

From 67eb71509370214a04d7f5512eb3663dc3df5a9d Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lstein@gmail.com>
Date: Sun, 4 Feb 2024 17:23:10 -0500
Subject: [PATCH 113/411] loaders for main, controlnet, ip-adapter, clipvision
 and t2i

---
 .../app/services/config/config_default.py     |   2 +-
 .../model_records/model_records_base.py       |  11 +-
 .../model_records/model_records_sql.py        |  17 +-
 .../sqlite_migrator/migrations/migration_6.py |   5 +-
 invokeai/backend/install/install_helper.py    |   1 +
 .../model_management/models/controlnet.py     |   1 -
 invokeai/backend/model_manager/__init__.py    |   2 +-
 invokeai/backend/model_manager/config.py      |  15 +-
 .../convert_ckpt_to_diffusers.py              |   4 +-
 .../backend/model_manager/load/__init__.py    |  24 +-
 .../load/convert_cache/__init__.py            |   2 +-
 .../load/convert_cache/convert_cache_base.py  |   3 +-
 .../convert_cache/convert_cache_default.py    |  10 +-
 .../backend/model_manager/load/load_base.py   |  52 +-
 .../model_manager/load/load_default.py        |  50 +-
 .../model_manager/load/memory_snapshot.py     |   2 +-
 .../load/model_cache/__init__.py              |   2 +-
 .../load/model_cache/model_cache_base.py      |   8 +-
 .../load/model_cache/model_cache_default.py   |  46 +-
 .../load/model_cache/model_locker.py          |   6 +-
 .../load/model_loaders/controlnet.py          |  60 ++
 .../load/model_loaders/generic_diffusers.py   |  34 +
 .../load/model_loaders/ip_adapter.py          |  39 ++
 .../model_manager/load/model_loaders/lora.py  |  76 +++
 .../load/model_loaders/stable_diffusion.py    |  93 +++
 .../model_manager/load/model_loaders/vae.py   |  66 +-
 .../backend/model_manager/load/model_util.py  |   5 +-
 invokeai/backend/model_manager/lora.py        | 620 ++++++++++++++++++
 invokeai/backend/model_manager/probe.py       |   6 +-
 invokeai/backend/util/__init__.py             |  16 +-
 invokeai/backend/util/devices.py              |   2 +-
 invokeai/backend/util/util.py                 |   2 +
 32 files changed, 1123 insertions(+), 159 deletions(-)
 create mode 100644 invokeai/backend/model_manager/load/model_loaders/controlnet.py
 create mode 100644 invokeai/backend/model_manager/load/model_loaders/generic_diffusers.py
 create mode 100644 invokeai/backend/model_manager/load/model_loaders/ip_adapter.py
 create mode 100644 invokeai/backend/model_manager/load/model_loaders/lora.py
 create mode 100644 invokeai/backend/model_manager/load/model_loaders/stable_diffusion.py
 create mode 100644 invokeai/backend/model_manager/lora.py

diff --git a/invokeai/app/services/config/config_default.py b/invokeai/app/services/config/config_default.py
index b161ea18d6..b39e916da3 100644
--- a/invokeai/app/services/config/config_default.py
+++ b/invokeai/app/services/config/config_default.py
@@ -173,7 +173,7 @@ from __future__ import annotations
 
 import os
 from pathlib import Path
-from typing import Any, ClassVar, Dict, List, Literal, Optional, Union
+from typing import Any, ClassVar, Dict, List, Literal, Optional
 
 from omegaconf import DictConfig, OmegaConf
 from pydantic import Field
diff --git a/invokeai/app/services/model_records/model_records_base.py b/invokeai/app/services/model_records/model_records_base.py
index 31cfecb4ec..42e3c8f83a 100644
--- a/invokeai/app/services/model_records/model_records_base.py
+++ b/invokeai/app/services/model_records/model_records_base.py
@@ -11,7 +11,14 @@ from typing import Any, Dict, List, Optional, Set, Tuple, Union
 from pydantic import BaseModel, Field
 
 from invokeai.app.services.shared.pagination import PaginatedResults
-from invokeai.backend.model_manager import LoadedModel, AnyModelConfig, BaseModelType, ModelFormat, ModelType, SubModelType
+from invokeai.backend.model_manager import (
+    AnyModelConfig,
+    BaseModelType,
+    LoadedModel,
+    ModelFormat,
+    ModelType,
+    SubModelType,
+)
 from invokeai.backend.model_manager.metadata import AnyModelRepoMetadata, ModelMetadataStore
 
 
@@ -108,7 +115,7 @@ class ModelRecordServiceBase(ABC):
         Load the indicated model into memory and return a LoadedModel object.
 
         :param key: Key of model config to be fetched.
-        :param submodel_type: For main (pipeline models), the submodel to fetch 
+        :param submodel_type: For main (pipeline models), the submodel to fetch
 
         Exceptions: UnknownModelException -- model with this key not known
                     NotImplementedException -- a model loader was not provided at initialization time
diff --git a/invokeai/app/services/model_records/model_records_sql.py b/invokeai/app/services/model_records/model_records_sql.py
index eee867ccb4..b50cd17a75 100644
--- a/invokeai/app/services/model_records/model_records_sql.py
+++ b/invokeai/app/services/model_records/model_records_sql.py
@@ -42,7 +42,6 @@ Typical usage:
 
 import json
 import sqlite3
-import time
 from math import ceil
 from pathlib import Path
 from typing import Any, Dict, List, Optional, Set, Tuple, Union
@@ -56,8 +55,8 @@ from invokeai.backend.model_manager.config import (
     ModelType,
     SubModelType,
 )
-from invokeai.backend.model_manager.metadata import AnyModelRepoMetadata, ModelMetadataStore, UnknownMetadataException
 from invokeai.backend.model_manager.load import AnyModelLoader, LoadedModel
+from invokeai.backend.model_manager.metadata import AnyModelRepoMetadata, ModelMetadataStore, UnknownMetadataException
 
 from ..shared.sqlite.sqlite_database import SqliteDatabase
 from .model_records_base import (
@@ -72,7 +71,7 @@ from .model_records_base import (
 class ModelRecordServiceSQL(ModelRecordServiceBase):
     """Implementation of the ModelConfigStore ABC using a SQL database."""
 
-    def __init__(self, db: SqliteDatabase, loader: Optional[AnyModelLoader]=None):
+    def __init__(self, db: SqliteDatabase, loader: Optional[AnyModelLoader] = None):
         """
         Initialize a new object from preexisting sqlite3 connection and threading lock objects.
 
@@ -289,7 +288,9 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
                 """,
                 tuple(bindings),
             )
-            results = [ModelConfigFactory.make_config(json.loads(x[0]), timestamp=x[1]) for x in self._cursor.fetchall()]
+            results = [
+                ModelConfigFactory.make_config(json.loads(x[0]), timestamp=x[1]) for x in self._cursor.fetchall()
+            ]
         return results
 
     def search_by_path(self, path: Union[str, Path]) -> List[AnyModelConfig]:
@@ -303,7 +304,9 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
                 """,
                 (str(path),),
             )
-            results = [ModelConfigFactory.make_config(json.loads(x[0]), timestamp=x[1]) for x in self._cursor.fetchall()]
+            results = [
+                ModelConfigFactory.make_config(json.loads(x[0]), timestamp=x[1]) for x in self._cursor.fetchall()
+            ]
         return results
 
     def search_by_hash(self, hash: str) -> List[AnyModelConfig]:
@@ -317,7 +320,9 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
                 """,
                 (hash,),
             )
-            results = [ModelConfigFactory.make_config(json.loads(x[0]), timestamp=x[1]) for x in self._cursor.fetchall()]
+            results = [
+                ModelConfigFactory.make_config(json.loads(x[0]), timestamp=x[1]) for x in self._cursor.fetchall()
+            ]
         return results
 
     @property
diff --git a/invokeai/app/services/shared/sqlite_migrator/migrations/migration_6.py b/invokeai/app/services/shared/sqlite_migrator/migrations/migration_6.py
index e72878f726..b473444511 100644
--- a/invokeai/app/services/shared/sqlite_migrator/migrations/migration_6.py
+++ b/invokeai/app/services/shared/sqlite_migrator/migrations/migration_6.py
@@ -1,11 +1,9 @@
 import sqlite3
-from logging import Logger
 
-from invokeai.app.services.config import InvokeAIAppConfig
 from invokeai.app.services.shared.sqlite_migrator.sqlite_migrator_common import Migration
 
-class Migration6Callback:
 
+class Migration6Callback:
     def __call__(self, cursor: sqlite3.Cursor) -> None:
         self._recreate_model_triggers(cursor)
 
@@ -28,6 +26,7 @@ class Migration6Callback:
             """
         )
 
+
 def build_migration_6() -> Migration:
     """
     Build the migration from database version 5 to 6.
diff --git a/invokeai/backend/install/install_helper.py b/invokeai/backend/install/install_helper.py
index 8c03d2ccf8..9f219132d4 100644
--- a/invokeai/backend/install/install_helper.py
+++ b/invokeai/backend/install/install_helper.py
@@ -120,6 +120,7 @@ class TqdmEventService(EventServiceBase):
         elif payload["event"] == "model_install_cancelled":
             self._logger.warning(f"{source}: installation cancelled")
 
+
 class InstallHelper(object):
     """Capture information stored jointly in INITIAL_MODELS.yaml and the installed models db."""
 
diff --git a/invokeai/backend/model_management/models/controlnet.py b/invokeai/backend/model_management/models/controlnet.py
index da269eba4b..3b534cb9d1 100644
--- a/invokeai/backend/model_management/models/controlnet.py
+++ b/invokeai/backend/model_management/models/controlnet.py
@@ -139,7 +139,6 @@ def _convert_controlnet_ckpt_and_cache(
     cache it to disk, and return Path to converted
     file. If already on disk then just returns Path.
     """
-    print(f"DEBUG: controlnet config = {model_config}")
     app_config = InvokeAIAppConfig.get_config()
     weights = app_config.root_path / model_path
     output_path = Path(output_path)
diff --git a/invokeai/backend/model_manager/__init__.py b/invokeai/backend/model_manager/__init__.py
index f3c84cd01f..98cc5054c7 100644
--- a/invokeai/backend/model_manager/__init__.py
+++ b/invokeai/backend/model_manager/__init__.py
@@ -13,9 +13,9 @@ from .config import (
     SchedulerPredictionType,
     SubModelType,
 )
+from .load import LoadedModel
 from .probe import ModelProbe
 from .search import ModelSearch
-from .load import LoadedModel
 
 __all__ = [
     "AnyModel",
diff --git a/invokeai/backend/model_manager/config.py b/invokeai/backend/model_manager/config.py
index 796ccbacde..e59a84d729 100644
--- a/invokeai/backend/model_manager/config.py
+++ b/invokeai/backend/model_manager/config.py
@@ -20,14 +20,16 @@ Validation errors will raise an InvalidModelConfigException error.
 
 """
 import time
-import torch
 from enum import Enum
 from typing import Literal, Optional, Type, Union
 
-from pydantic import BaseModel, ConfigDict, Field, TypeAdapter
+import torch
 from diffusers import ModelMixin
+from pydantic import BaseModel, ConfigDict, Field, TypeAdapter
 from typing_extensions import Annotated, Any, Dict
+
 from .onnx_runtime import IAIOnnxRuntimeModel
+from ..ip_adapter.ip_adapter import IPAdapter, IPAdapterPlus
 
 class InvalidModelConfigException(Exception):
     """Exception for when config parser doesn't recognized this combination of model type and format."""
@@ -204,6 +206,8 @@ class _MainConfig(ModelConfigBase):
 
     vae: Optional[str] = Field(default=None)
     variant: ModelVariantType = ModelVariantType.Normal
+    prediction_type: SchedulerPredictionType = SchedulerPredictionType.Epsilon
+    upcast_attention: bool = False
     ztsnr_training: bool = False
 
 
@@ -217,8 +221,6 @@ class MainDiffusersConfig(_DiffusersConfig, _MainConfig):
     """Model config for main diffusers models."""
 
     type: Literal[ModelType.Main] = ModelType.Main
-    prediction_type: SchedulerPredictionType = SchedulerPredictionType.Epsilon
-    upcast_attention: bool = False
 
 
 class ONNXSD1Config(_MainConfig):
@@ -276,6 +278,7 @@ AnyModelConfig = Union[
     _ONNXConfig,
     _VaeConfig,
     _ControlNetConfig,
+    # ModelConfigBase,
     LoRAConfig,
     TextualInversionConfig,
     IPAdapterConfig,
@@ -284,7 +287,7 @@ AnyModelConfig = Union[
 ]
 
 AnyModelConfigValidator = TypeAdapter(AnyModelConfig)
-AnyModel = Union[ModelMixin, torch.nn.Module, IAIOnnxRuntimeModel]
+AnyModel = Union[ModelMixin, torch.nn.Module, IAIOnnxRuntimeModel, IPAdapter, IPAdapterPlus]
 
 # IMPLEMENTATION NOTE:
 # The preferred alternative to the above is a discriminated Union as shown
@@ -317,7 +320,7 @@ class ModelConfigFactory(object):
         model_data: Union[dict, AnyModelConfig],
         key: Optional[str] = None,
         dest_class: Optional[Type] = None,
-        timestamp: Optional[float] = None
+        timestamp: Optional[float] = None,
     ) -> AnyModelConfig:
         """
         Return the appropriate config object from raw dict values.
diff --git a/invokeai/backend/model_manager/convert_ckpt_to_diffusers.py b/invokeai/backend/model_manager/convert_ckpt_to_diffusers.py
index 9d6fc4841f..6f5acd5832 100644
--- a/invokeai/backend/model_manager/convert_ckpt_to_diffusers.py
+++ b/invokeai/backend/model_manager/convert_ckpt_to_diffusers.py
@@ -43,7 +43,6 @@ from diffusers.schedulers import (
     UnCLIPScheduler,
 )
 from diffusers.utils import is_accelerate_available
-from diffusers.utils.import_utils import BACKENDS_MAPPING
 from picklescan.scanner import scan_file_path
 from transformers import (
     AutoFeatureExtractor,
@@ -58,8 +57,8 @@ from transformers import (
 )
 
 from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.backend.util.logging import InvokeAILogger
 from invokeai.backend.model_manager import BaseModelType, ModelVariantType
+from invokeai.backend.util.logging import InvokeAILogger
 
 try:
     from omegaconf import OmegaConf
@@ -1643,7 +1642,6 @@ def download_controlnet_from_original_ckpt(
     cross_attention_dim: Optional[bool] = None,
     scan_needed: bool = False,
 ) -> DiffusionPipeline:
-
     from omegaconf import OmegaConf
 
     if from_safetensors:
diff --git a/invokeai/backend/model_manager/load/__init__.py b/invokeai/backend/model_manager/load/__init__.py
index 357677bb7f..19b0116ba3 100644
--- a/invokeai/backend/model_manager/load/__init__.py
+++ b/invokeai/backend/model_manager/load/__init__.py
@@ -8,14 +8,15 @@ from typing import Optional
 
 from invokeai.app.services.config import InvokeAIAppConfig
 from invokeai.backend.util.logging import InvokeAILogger
+
+from .convert_cache.convert_cache_default import ModelConvertCache
 from .load_base import AnyModelLoader, LoadedModel
 from .model_cache.model_cache_default import ModelCache
-from .convert_cache.convert_cache_default import ModelConvertCache
 
 # This registers the subclasses that implement loaders of specific model types
-loaders = [x.stem for x in Path(Path(__file__).parent,'model_loaders').glob('*.py') if x.stem != '__init__']
+loaders = [x.stem for x in Path(Path(__file__).parent, "model_loaders").glob("*.py") if x.stem != "__init__"]
 for module in loaders:
-    print(f'module={module}')
+    print(f"module={module}")
     import_module(f"{__package__}.model_loaders.{module}")
 
 __all__ = ["AnyModelLoader", "LoadedModel"]
@@ -24,12 +25,11 @@ __all__ = ["AnyModelLoader", "LoadedModel"]
 def get_standalone_loader(app_config: Optional[InvokeAIAppConfig]) -> AnyModelLoader:
     app_config = app_config or InvokeAIAppConfig.get_config()
     logger = InvokeAILogger.get_logger(config=app_config)
-    return AnyModelLoader(app_config=app_config,
-                          logger=logger,
-                          ram_cache=ModelCache(logger=logger,
-                                               max_cache_size=app_config.ram_cache_size,
-                                               max_vram_cache_size=app_config.vram_cache_size
-                                               ),
-                          convert_cache=ModelConvertCache(app_config.models_convert_cache_path)
-                          )
-
+    return AnyModelLoader(
+        app_config=app_config,
+        logger=logger,
+        ram_cache=ModelCache(
+            logger=logger, max_cache_size=app_config.ram_cache_size, max_vram_cache_size=app_config.vram_cache_size
+        ),
+        convert_cache=ModelConvertCache(app_config.models_convert_cache_path),
+    )
diff --git a/invokeai/backend/model_manager/load/convert_cache/__init__.py b/invokeai/backend/model_manager/load/convert_cache/__init__.py
index eb3149be32..5be56d2d58 100644
--- a/invokeai/backend/model_manager/load/convert_cache/__init__.py
+++ b/invokeai/backend/model_manager/load/convert_cache/__init__.py
@@ -1,4 +1,4 @@
 from .convert_cache_base import ModelConvertCacheBase
 from .convert_cache_default import ModelConvertCache
 
-__all__ = ['ModelConvertCacheBase', 'ModelConvertCache']
+__all__ = ["ModelConvertCacheBase", "ModelConvertCache"]
diff --git a/invokeai/backend/model_manager/load/convert_cache/convert_cache_base.py b/invokeai/backend/model_manager/load/convert_cache/convert_cache_base.py
index 25263f96aa..6268c099a5 100644
--- a/invokeai/backend/model_manager/load/convert_cache/convert_cache_base.py
+++ b/invokeai/backend/model_manager/load/convert_cache/convert_cache_base.py
@@ -4,8 +4,8 @@ Disk-based converted model cache.
 from abc import ABC, abstractmethod
 from pathlib import Path
 
-class ModelConvertCacheBase(ABC):
 
+class ModelConvertCacheBase(ABC):
     @property
     @abstractmethod
     def max_size(self) -> float:
@@ -25,4 +25,3 @@ class ModelConvertCacheBase(ABC):
     def cache_path(self, key: str) -> Path:
         """Return the path for a model with the indicated key."""
         pass
-
diff --git a/invokeai/backend/model_manager/load/convert_cache/convert_cache_default.py b/invokeai/backend/model_manager/load/convert_cache/convert_cache_default.py
index f799510ec5..4c361258d9 100644
--- a/invokeai/backend/model_manager/load/convert_cache/convert_cache_default.py
+++ b/invokeai/backend/model_manager/load/convert_cache/convert_cache_default.py
@@ -2,15 +2,17 @@
 Placeholder for convert cache implementation.
 """
 
-from pathlib import Path
 import shutil
-from invokeai.backend.util.logging import InvokeAILogger
+from pathlib import Path
+
 from invokeai.backend.util import GIG, directory_size
+from invokeai.backend.util.logging import InvokeAILogger
+
 from .convert_cache_base import ModelConvertCacheBase
 
-class ModelConvertCache(ModelConvertCacheBase):
 
-    def __init__(self, cache_path: Path, max_size: float=10.0):
+class ModelConvertCache(ModelConvertCacheBase):
+    def __init__(self, cache_path: Path, max_size: float = 10.0):
         """Initialize the convert cache with the base directory and a limit on its maximum size (in GBs)."""
         if not cache_path.exists():
             cache_path.mkdir(parents=True)
diff --git a/invokeai/backend/model_manager/load/load_base.py b/invokeai/backend/model_manager/load/load_base.py
index 3ade83160a..7d4e8337c3 100644
--- a/invokeai/backend/model_manager/load/load_base.py
+++ b/invokeai/backend/model_manager/load/load_base.py
@@ -10,17 +10,19 @@ Use like this:
        # do something with loaded_model
 """
 
+import hashlib
 from abc import ABC, abstractmethod
 from dataclasses import dataclass
 from logging import Logger
 from pathlib import Path
-from typing import Any, Callable, Dict, Optional, Type, Union
+from typing import Any, Callable, Dict, Optional, Tuple, Type
 
 from invokeai.app.services.config import InvokeAIAppConfig
 from invokeai.backend.model_manager import AnyModel, AnyModelConfig, BaseModelType, ModelFormat, ModelType, SubModelType
-from invokeai.backend.model_manager.load.model_cache.model_cache_base import ModelCacheBase
-from invokeai.backend.model_manager.load.model_cache.model_locker import ModelLockerBase
+from invokeai.backend.model_manager.config import VaeCheckpointConfig, VaeDiffusersConfig
 from invokeai.backend.model_manager.load.convert_cache.convert_cache_base import ModelConvertCacheBase
+from invokeai.backend.model_manager.load.model_cache.model_cache_base import ModelCacheBase, ModelLockerBase
+
 
 @dataclass
 class LoadedModel:
@@ -52,7 +54,7 @@ class ModelLoaderBase(ABC):
         self,
         app_config: InvokeAIAppConfig,
         logger: Logger,
-        ram_cache: ModelCacheBase,
+        ram_cache: ModelCacheBase[AnyModel],
         convert_cache: ModelConvertCacheBase,
     ):
         """Initialize the loader."""
@@ -91,7 +93,7 @@ class AnyModelLoader:
         self,
         app_config: InvokeAIAppConfig,
         logger: Logger,
-        ram_cache: ModelCacheBase,
+        ram_cache: ModelCacheBase[AnyModel],
         convert_cache: ModelConvertCacheBase,
     ):
         """Initialize AnyModelLoader with its dependencies."""
@@ -101,11 +103,11 @@ class AnyModelLoader:
         self._convert_cache = convert_cache
 
     @property
-    def ram_cache(self) -> ModelCacheBase:
+    def ram_cache(self) -> ModelCacheBase[AnyModel]:
         """Return the RAM cache associated used by the loaders."""
         return self._ram_cache
 
-    def load_model(self, model_config: AnyModelConfig, submodel_type: Optional[SubModelType]=None) -> LoadedModel:
+    def load_model(self, model_config: AnyModelConfig, submodel_type: Optional[SubModelType] = None) -> LoadedModel:
         """
         Return a model given its configuration.
 
@@ -113,9 +115,7 @@ class AnyModelLoader:
         :param submodel_type: an ModelType enum indicating the portion of
                the model to retrieve (e.g. ModelType.Vae)
         """
-        implementation = self.__class__.get_implementation(
-            base=model_config.base, type=model_config.type, format=model_config.format
-        )
+        implementation, model_config, submodel_type = self.__class__.get_implementation(model_config, submodel_type)
         return implementation(
             app_config=self._app_config,
             logger=self._logger,
@@ -128,16 +128,37 @@ class AnyModelLoader:
         return "-".join([base.value, type.value, format.value])
 
     @classmethod
-    def get_implementation(cls, base: BaseModelType, type: ModelType, format: ModelFormat) -> Type[ModelLoaderBase]:
+    def get_implementation(
+        cls, config: AnyModelConfig, submodel_type: Optional[SubModelType]
+    ) -> Tuple[Type[ModelLoaderBase], AnyModelConfig, Optional[SubModelType]]:
         """Get subclass of ModelLoaderBase registered to handle base and type."""
-        key1 = cls._to_registry_key(base, type, format)  # for a specific base type
-        key2 = cls._to_registry_key(BaseModelType.Any, type, format)  # with wildcard Any
+        # We have to handle VAE overrides here because this will change the model type and the corresponding implementation returned
+        conf2, submodel_type = cls._handle_subtype_overrides(config, submodel_type)
+
+        key1 = cls._to_registry_key(conf2.base, conf2.type, conf2.format)  # for a specific base type
+        key2 = cls._to_registry_key(BaseModelType.Any, conf2.type, conf2.format)  # with wildcard Any
         implementation = cls._registry.get(key1) or cls._registry.get(key2)
         if not implementation:
             raise NotImplementedError(
-                f"No subclass of LoadedModel is registered for base={base}, type={type}, format={format}"
+                f"No subclass of LoadedModel is registered for base={config.base}, type={config.type}, format={config.format}"
             )
-        return implementation
+        return implementation, conf2, submodel_type
+
+    @classmethod
+    def _handle_subtype_overrides(
+        cls, config: AnyModelConfig, submodel_type: Optional[SubModelType]
+    ) -> Tuple[AnyModelConfig, Optional[SubModelType]]:
+        if submodel_type == SubModelType.Vae and hasattr(config, "vae") and config.vae is not None:
+            model_path = Path(config.vae)
+            config_class = (
+                VaeCheckpointConfig if model_path.suffix in [".pt", ".safetensors", ".ckpt"] else VaeDiffusersConfig
+            )
+            hash = hashlib.md5(model_path.as_posix().encode("utf-8")).hexdigest()
+            new_conf = config_class(path=model_path.as_posix(), name=model_path.stem, base=config.base, key=hash)
+            submodel_type = None
+        else:
+            new_conf = config
+        return new_conf, submodel_type
 
     @classmethod
     def register(
@@ -152,4 +173,3 @@ class AnyModelLoader:
             return subclass
 
         return decorator
-
diff --git a/invokeai/backend/model_manager/load/load_default.py b/invokeai/backend/model_manager/load/load_default.py
index 0b028235fd..453283e9b4 100644
--- a/invokeai/backend/model_manager/load/load_default.py
+++ b/invokeai/backend/model_manager/load/load_default.py
@@ -10,12 +10,12 @@ from diffusers import ModelMixin
 from diffusers.configuration_utils import ConfigMixin
 
 from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.backend.model_manager import AnyModelConfig, InvalidModelConfigException, ModelRepoVariant, SubModelType
+from invokeai.backend.model_manager import AnyModel, AnyModelConfig, InvalidModelConfigException, ModelRepoVariant, SubModelType
 from invokeai.backend.model_manager.load.convert_cache import ModelConvertCacheBase
-from invokeai.backend.model_manager.load.load_base import AnyModel, LoadedModel, ModelLoaderBase
-from invokeai.backend.model_manager.load.model_util import calc_model_size_by_fs
-from invokeai.backend.model_manager.load.optimizations import skip_torch_weight_init
+from invokeai.backend.model_manager.load.load_base import LoadedModel, ModelLoaderBase
 from invokeai.backend.model_manager.load.model_cache.model_cache_base import ModelCacheBase, ModelLockerBase
+from invokeai.backend.model_manager.load.model_util import calc_model_size_by_fs, calc_model_size_by_data
+from invokeai.backend.model_manager.load.optimizations import skip_torch_weight_init
 from invokeai.backend.util.devices import choose_torch_device, torch_dtype
 
 
@@ -38,7 +38,7 @@ class ModelLoader(ModelLoaderBase):
         self,
         app_config: InvokeAIAppConfig,
         logger: Logger,
-        ram_cache: ModelCacheBase,
+        ram_cache: ModelCacheBase[AnyModel],
         convert_cache: ModelConvertCacheBase,
     ):
         """Initialize the loader."""
@@ -47,7 +47,6 @@ class ModelLoader(ModelLoaderBase):
         self._ram_cache = ram_cache
         self._convert_cache = convert_cache
         self._torch_dtype = torch_dtype(choose_torch_device())
-        self._size: Optional[int] = None  # model size
 
     def load_model(self, model_config: AnyModelConfig, submodel_type: Optional[SubModelType] = None) -> LoadedModel:
         """
@@ -63,9 +62,7 @@ class ModelLoader(ModelLoaderBase):
         if model_config.type == "main" and not submodel_type:
             raise InvalidModelConfigException("submodel_type is required when loading a main model")
 
-        model_path, is_submodel_override = self._get_model_path(model_config, submodel_type)
-        if is_submodel_override:
-            submodel_type = None
+        model_path, model_config, submodel_type = self._get_model_path(model_config, submodel_type)
 
         if not model_path.exists():
             raise InvalidModelConfigException(f"Files for model 'model_config.name' not found at {model_path}")
@@ -74,13 +71,12 @@ class ModelLoader(ModelLoaderBase):
         locker = self._load_if_needed(model_config, model_path, submodel_type)
         return LoadedModel(config=model_config, locker=locker)
 
-    # IMPORTANT: This needs to be overridden in the StableDiffusion subclass so as to handle vae overrides
-    # and submodels!!!!
     def _get_model_path(
         self, config: AnyModelConfig, submodel_type: Optional[SubModelType] = None
-    ) -> Tuple[Path, bool]:
+    ) -> Tuple[Path, AnyModelConfig, Optional[SubModelType]]:
         model_base = self._app_config.models_path
-        return ((model_base / config.path).resolve(), False)
+        result = (model_base / config.path).resolve(), config, submodel_type
+        return result
 
     def _convert_if_needed(
         self, config: AnyModelConfig, model_path: Path, submodel_type: Optional[SubModelType] = None
@@ -90,7 +86,7 @@ class ModelLoader(ModelLoaderBase):
         if not self._needs_conversion(config, model_path, cache_path):
             return cache_path if cache_path.exists() else model_path
 
-        self._convert_cache.make_room(self._size or self.get_size_fs(config, model_path, submodel_type))
+        self._convert_cache.make_room(self.get_size_fs(config, model_path, submodel_type))
         return self._convert_model(config, model_path, cache_path)
 
     def _needs_conversion(self, config: AnyModelConfig, model_path: Path, cache_path: Path) -> bool:
@@ -114,6 +110,7 @@ class ModelLoader(ModelLoaderBase):
             config.key,
             submodel_type=submodel_type,
             model=loaded_model,
+            size=calc_model_size_by_data(loaded_model),
         )
 
         return self._ram_cache.get(config.key, submodel_type)
@@ -128,17 +125,6 @@ class ModelLoader(ModelLoaderBase):
             variant=config.repo_variant if hasattr(config, "repo_variant") else None,
         )
 
-    def _convert_model(self, config: AnyModelConfig, weights_path: Path, output_path: Path) -> Path:
-        raise NotImplementedError
-
-    def _load_model(
-        self,
-        model_path: Path,
-        model_variant: Optional[ModelRepoVariant] = None,
-        submodel_type: Optional[SubModelType] = None,
-    ) -> AnyModel:
-        raise NotImplementedError
-
     def _load_diffusers_config(self, model_path: Path, config_name: str = "config.json") -> Dict[str, Any]:
         return ConfigLoader.load_config(model_path, config_name=config_name)
 
@@ -161,3 +147,17 @@ class ModelLoader(ModelLoaderBase):
             config = self._load_diffusers_config(model_path, config_name="config.json")
             class_name = config["_class_name"]
             return self._hf_definition_to_type(module="diffusers", class_name=class_name)
+
+    # This needs to be implemented in subclasses that handle checkpoints
+    def _convert_model(self, config: AnyModelConfig, weights_path: Path, output_path: Path) -> Path:
+        raise NotImplementedError
+
+    # This needs to be implemented in the subclass
+    def _load_model(
+        self,
+        model_path: Path,
+        model_variant: Optional[ModelRepoVariant] = None,
+        submodel_type: Optional[SubModelType] = None,
+    ) -> AnyModel:
+        raise NotImplementedError
+
diff --git a/invokeai/backend/model_manager/load/memory_snapshot.py b/invokeai/backend/model_manager/load/memory_snapshot.py
index 504829a427..295be0c551 100644
--- a/invokeai/backend/model_manager/load/memory_snapshot.py
+++ b/invokeai/backend/model_manager/load/memory_snapshot.py
@@ -97,4 +97,4 @@ def get_pretty_snapshot_diff(snapshot_1: Optional[MemorySnapshot], snapshot_2: O
     if snapshot_1.vram is not None and snapshot_2.vram is not None:
         msg += get_msg_line("VRAM", snapshot_1.vram, snapshot_2.vram)
 
-    return msg
+    return "\n"+msg if len(msg)>0 else msg
diff --git a/invokeai/backend/model_manager/load/model_cache/__init__.py b/invokeai/backend/model_manager/load/model_cache/__init__.py
index 776b9d8936..50cafa3769 100644
--- a/invokeai/backend/model_manager/load/model_cache/__init__.py
+++ b/invokeai/backend/model_manager/load/model_cache/__init__.py
@@ -2,4 +2,4 @@
 
 from .model_cache_base import ModelCacheBase
 from .model_cache_default import ModelCache
-_all__ = ['ModelCacheBase', 'ModelCache']
+_all__ = ["ModelCacheBase", "ModelCache"]
diff --git a/invokeai/backend/model_manager/load/model_cache/model_cache_base.py b/invokeai/backend/model_manager/load/model_cache/model_cache_base.py
index 50b69d961c..14a7dfb4a1 100644
--- a/invokeai/backend/model_manager/load/model_cache/model_cache_base.py
+++ b/invokeai/backend/model_manager/load/model_cache/model_cache_base.py
@@ -8,14 +8,15 @@ model will be cleared and (re)loaded from disk when next needed.
 """
 
 from abc import ABC, abstractmethod
-from dataclasses import dataclass, field
+from dataclasses import dataclass
 from logging import Logger
-from typing import Dict, Optional, TypeVar, Generic
+from typing import Generic, Optional, TypeVar
 
 import torch
 
 from invokeai.backend.model_manager import AnyModel, SubModelType
 
+
 class ModelLockerBase(ABC):
     """Base class for the model locker used by the loader."""
 
@@ -35,8 +36,10 @@ class ModelLockerBase(ABC):
         """Return the model."""
         pass
 
+
 T = TypeVar("T")
 
+
 @dataclass
 class CacheRecord(Generic[T]):
     """Elements of the cache."""
@@ -115,6 +118,7 @@ class ModelCacheBase(ABC, Generic[T]):
         self,
         key: str,
         model: T,
+        size: int,
         submodel_type: Optional[SubModelType] = None,
     ) -> None:
         """Store model under key and optional submodel_type."""
diff --git a/invokeai/backend/model_manager/load/model_cache/model_cache_default.py b/invokeai/backend/model_manager/load/model_cache/model_cache_default.py
index 961f68a4be..688be8ceb4 100644
--- a/invokeai/backend/model_manager/load/model_cache/model_cache_default.py
+++ b/invokeai/backend/model_manager/load/model_cache/model_cache_default.py
@@ -19,22 +19,24 @@ context. Use like this:
 """
 
 import gc
+import logging
 import math
+import sys
 import time
 from contextlib import suppress
 from logging import Logger
-from typing import Any, Dict, List, Optional
+from typing import Dict, List, Optional
 
 import torch
 
 from invokeai.backend.model_manager import SubModelType
 from invokeai.backend.model_manager.load.load_base import AnyModel
 from invokeai.backend.model_manager.load.memory_snapshot import MemorySnapshot, get_pretty_snapshot_diff
-from invokeai.backend.model_manager.load.model_util import calc_model_size_by_data
 from invokeai.backend.util.devices import choose_torch_device
 from invokeai.backend.util.logging import InvokeAILogger
+
 from .model_cache_base import CacheRecord, ModelCacheBase
-from .model_locker import ModelLockerBase, ModelLocker
+from .model_locker import ModelLocker, ModelLockerBase
 
 if choose_torch_device() == torch.device("mps"):
     from torch import mps
@@ -91,7 +93,7 @@ class ModelCache(ModelCacheBase[AnyModel]):
         self._execution_device: torch.device = execution_device
         self._storage_device: torch.device = storage_device
         self._logger = logger or InvokeAILogger.get_logger(self.__class__.__name__)
-        self._log_memory_usage = log_memory_usage
+        self._log_memory_usage = log_memory_usage or self._logger.level == logging.DEBUG
 
         self._cached_models: Dict[str, CacheRecord[AnyModel]] = {}
         self._cache_stack: List[str] = []
@@ -141,14 +143,14 @@ class ModelCache(ModelCacheBase[AnyModel]):
         self,
         key: str,
         model: AnyModel,
+        size: int,
         submodel_type: Optional[SubModelType] = None,
     ) -> None:
         """Store model under key and optional submodel_type."""
         key = self._make_cache_key(key, submodel_type)
         assert key not in self._cached_models
 
-        loaded_model_size = calc_model_size_by_data(model)
-        cache_record = CacheRecord(key, model, loaded_model_size)
+        cache_record = CacheRecord(key, model, size)
         self._cached_models[key] = cache_record
         self._cache_stack.append(key)
 
@@ -195,28 +197,32 @@ class ModelCache(ModelCacheBase[AnyModel]):
         for _, cache_entry in sorted(self._cached_models.items(), key=lambda x: x[1].size):
             if vram_in_use <= reserved:
                 break
+            if not cache_entry.loaded:
+                continue
             if not cache_entry.locked:
                 self.move_model_to_device(cache_entry, self.storage_device)
                 cache_entry.loaded = False
                 vram_in_use = torch.cuda.memory_allocated() + size_required
-                self.logger.debug(f"{(vram_in_use/GIG):.2f}GB VRAM now available for models; max allowed={(reserved/GIG):.2f}GB")
+                self.logger.debug(
+                    f"Removing {cache_entry.key} from VRAM to free {(cache_entry.size/GIG):.2f}GB; vram free = {(torch.cuda.memory_allocated()/GIG):.2f}GB"
+                )
 
         torch.cuda.empty_cache()
         if choose_torch_device() == torch.device("mps"):
             mps.empty_cache()
 
-    # TO DO: Only reason to pass the CacheRecord rather than the model is to get the key and size
-    # for printing debugging messages. Revisit whether this is necessary
-    def move_model_to_device(self, cache_entry: CacheRecord, target_device: torch.device) -> None:
+    def move_model_to_device(self, cache_entry: CacheRecord[AnyModel], target_device: torch.device) -> None:
         """Move model into the indicated device."""
-        # These attributes are not in the base class but in derived classes
-        assert hasattr(cache_entry.model, "device")
-        assert hasattr(cache_entry.model, "to")
+        # These attributes are not in the base ModelMixin class but in derived classes.
+        # Some models don't have these attributes, in which case they run in RAM/CPU.
+        self.logger.debug(f"Called to move {cache_entry.key} to {target_device}")
+        if not (hasattr(cache_entry.model, "device") and hasattr(cache_entry.model, "to")):
+            return
 
         source_device = cache_entry.model.device
 
-        # Note: We compare device types only so that 'cuda' == 'cuda:0'. This would need to be revised to support
-        # multi-GPU.
+        # Note: We compare device types only so that 'cuda' == 'cuda:0'.
+        # This would need to be revised to support multi-GPU.
         if torch.device(source_device).type == torch.device(target_device).type:
             return
 
@@ -227,8 +233,8 @@ class ModelCache(ModelCacheBase[AnyModel]):
         end_model_to_time = time.time()
         self.logger.debug(
             f"Moved model '{cache_entry.key}' from {source_device} to"
-            f" {target_device} in {(end_model_to_time-start_model_to_time):.2f}s.\n"
-            f"Estimated model size: {(cache_entry.size/GIG):.3f} GB.\n"
+            f" {target_device} in {(end_model_to_time-start_model_to_time):.2f}s."
+            f"Estimated model size: {(cache_entry.size/GIG):.3f} GB."
             f"{get_pretty_snapshot_diff(snapshot_before, snapshot_after)}"
         )
 
@@ -291,7 +297,7 @@ class ModelCache(ModelCacheBase[AnyModel]):
                 f" {(bytes_needed/GIG):.2f} GB"
             )
 
-        self.logger.debug(f"Before unloading: cached_models={len(self._cached_models)}")
+        self.logger.debug(f"Before making_room: cached_models={len(self._cached_models)}")
 
         pos = 0
         models_cleared = 0
@@ -336,7 +342,7 @@ class ModelCache(ModelCacheBase[AnyModel]):
             # 1 from onnx runtime object
             if not cache_entry.locked and refs <= (3 if "onnx" in model_key else 2):
                 self.logger.debug(
-                    f"Unloading model {model_key} to free {(model_size/GIG):.2f} GB (-{(cache_entry.size/GIG):.2f} GB)"
+                    f"Removing {model_key} from RAM cache to free at least {(model_size/GIG):.2f} GB (-{(cache_entry.size/GIG):.2f} GB)"
                 )
                 current_size -= cache_entry.size
                 models_cleared += 1
@@ -365,4 +371,4 @@ class ModelCache(ModelCacheBase[AnyModel]):
         if choose_torch_device() == torch.device("mps"):
             mps.empty_cache()
 
-        self.logger.debug(f"After unloading: cached_models={len(self._cached_models)}")
+        self.logger.debug(f"After making room: cached_models={len(self._cached_models)}")
diff --git a/invokeai/backend/model_manager/load/model_cache/model_locker.py b/invokeai/backend/model_manager/load/model_cache/model_locker.py
index 506d012949..7a5fdd4284 100644
--- a/invokeai/backend/model_manager/load/model_cache/model_locker.py
+++ b/invokeai/backend/model_manager/load/model_cache/model_locker.py
@@ -2,9 +2,10 @@
 Base class and implementation of a class that moves models in and out of VRAM.
 """
 
-from abc import ABC, abstractmethod
 from invokeai.backend.model_manager import AnyModel
-from .model_cache_base import ModelLockerBase, ModelCacheBase, CacheRecord
+
+from .model_cache_base import CacheRecord, ModelCacheBase, ModelLockerBase
+
 
 class ModelLocker(ModelLockerBase):
     """Internal class that mediates movement in and out of GPU."""
@@ -56,4 +57,3 @@ class ModelLocker(ModelLockerBase):
         if not self._cache.lazy_offloading:
             self._cache.offload_unlocked_models(self._cache_entry.size)
             self._cache.print_cuda_stats()
-
diff --git a/invokeai/backend/model_manager/load/model_loaders/controlnet.py b/invokeai/backend/model_manager/load/model_loaders/controlnet.py
new file mode 100644
index 0000000000..8e6a80ceb2
--- /dev/null
+++ b/invokeai/backend/model_manager/load/model_loaders/controlnet.py
@@ -0,0 +1,60 @@
+# Copyright (c) 2024, Lincoln D. Stein and the InvokeAI Development Team
+"""Class for ControlNet model loading in InvokeAI."""
+
+from pathlib import Path
+
+import safetensors
+import torch
+
+from invokeai.backend.model_manager import (
+    AnyModelConfig,
+    BaseModelType,
+    ModelFormat,
+    ModelType,
+)
+from invokeai.backend.model_manager.convert_ckpt_to_diffusers import convert_controlnet_to_diffusers
+from invokeai.backend.model_manager.load.load_base import AnyModelLoader
+from .generic_diffusers import GenericDiffusersLoader
+
+@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.ControlNet, format=ModelFormat.Diffusers)
+@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.ControlNet, format=ModelFormat.Checkpoint)
+class ControlnetLoader(GenericDiffusersLoader):
+    """Class to load ControlNet models."""
+
+    def _needs_conversion(self, config: AnyModelConfig, model_path: Path, dest_path: Path) -> bool:
+        if config.format != ModelFormat.Checkpoint:
+            return False
+        elif (
+            dest_path.exists()
+            and (dest_path / "config.json").stat().st_mtime >= (config.last_modified or 0.0)
+            and (dest_path / "config.json").stat().st_mtime >= model_path.stat().st_mtime
+        ):
+            return False
+        else:
+            return True
+
+    def _convert_model(self, config: AnyModelConfig, weights_path: Path, output_path: Path) -> Path:
+        if config.base not in {BaseModelType.StableDiffusion1, BaseModelType.StableDiffusion2}:
+            raise Exception(f"Vae conversion not supported for model type: {config.base}")
+        else:
+            assert hasattr(config, 'config')
+            config_file = config.config
+
+        if weights_path.suffix == ".safetensors":
+            checkpoint = safetensors.torch.load_file(weights_path, device="cpu")
+        else:
+            checkpoint = torch.load(weights_path, map_location="cpu")
+
+        # sometimes weights are hidden under "state_dict", and sometimes not
+        if "state_dict" in checkpoint:
+            checkpoint = checkpoint["state_dict"]
+
+        convert_controlnet_to_diffusers(
+            weights_path,
+            output_path,
+            original_config_file=self._app_config.root_path / config_file,
+            image_size=512,
+            scan_needed=True,
+            from_safetensors=weights_path.suffix == ".safetensors",
+        )
+        return output_path
diff --git a/invokeai/backend/model_manager/load/model_loaders/generic_diffusers.py b/invokeai/backend/model_manager/load/model_loaders/generic_diffusers.py
new file mode 100644
index 0000000000..f92a9048c5
--- /dev/null
+++ b/invokeai/backend/model_manager/load/model_loaders/generic_diffusers.py
@@ -0,0 +1,34 @@
+# Copyright (c) 2024, Lincoln D. Stein and the InvokeAI Development Team
+"""Class for simple diffusers model loading in InvokeAI."""
+
+from pathlib import Path
+from typing import Optional
+
+from invokeai.backend.model_manager import (
+    AnyModel,
+    BaseModelType,
+    ModelFormat,
+    ModelRepoVariant,
+    ModelType,
+    SubModelType,
+)
+from invokeai.backend.model_manager.load.load_base import AnyModelLoader
+from invokeai.backend.model_manager.load.load_default import ModelLoader
+
+@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.CLIPVision, format=ModelFormat.Diffusers)
+@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.T2IAdapter, format=ModelFormat.Diffusers)
+class GenericDiffusersLoader(ModelLoader):
+    """Class to load simple diffusers models."""
+
+    def _load_model(
+        self,
+        model_path: Path,
+        model_variant: Optional[ModelRepoVariant] = None,
+        submodel_type: Optional[SubModelType] = None,
+    ) -> AnyModel:
+        model_class = self._get_hf_load_class(model_path)
+        if submodel_type is not None:
+            raise Exception(f"There are no submodels in models of type {model_class}")
+        variant = model_variant.value if model_variant else None
+        result: AnyModel = model_class.from_pretrained(model_path, torch_dtype=self._torch_dtype, variant=variant)  # type: ignore
+        return result
diff --git a/invokeai/backend/model_manager/load/model_loaders/ip_adapter.py b/invokeai/backend/model_manager/load/model_loaders/ip_adapter.py
new file mode 100644
index 0000000000..63dc3790f1
--- /dev/null
+++ b/invokeai/backend/model_manager/load/model_loaders/ip_adapter.py
@@ -0,0 +1,39 @@
+# Copyright (c) 2024, Lincoln D. Stein and the InvokeAI Development Team
+"""Class for IP Adapter model loading in InvokeAI."""
+
+import torch
+
+from pathlib import Path
+from typing import Optional
+
+from invokeai.backend.ip_adapter.ip_adapter import build_ip_adapter
+from invokeai.backend.model_manager import (
+    AnyModel,
+    BaseModelType,
+    ModelFormat,
+    ModelRepoVariant,
+    ModelType,
+    SubModelType,
+)
+from invokeai.backend.model_manager.load.load_base import AnyModelLoader
+from invokeai.backend.model_manager.load.load_default import ModelLoader
+
+@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.IPAdapter, format=ModelFormat.InvokeAI)
+class IPAdapterInvokeAILoader(ModelLoader):
+    """Class to load IP Adapter diffusers models."""
+
+    def _load_model(
+        self,
+        model_path: Path,
+        model_variant: Optional[ModelRepoVariant] = None,
+        submodel_type: Optional[SubModelType] = None,
+    ) -> AnyModel:
+        if submodel_type is not None:
+            raise ValueError("There are no submodels in an IP-Adapter model.")
+        model = build_ip_adapter(
+            ip_adapter_ckpt_path=model_path / "ip_adapter.bin",
+            device=torch.device("cpu"),
+            dtype=self._torch_dtype,
+        )
+        return model
+
diff --git a/invokeai/backend/model_manager/load/model_loaders/lora.py b/invokeai/backend/model_manager/load/model_loaders/lora.py
new file mode 100644
index 0000000000..4d19aadb7d
--- /dev/null
+++ b/invokeai/backend/model_manager/load/model_loaders/lora.py
@@ -0,0 +1,76 @@
+# Copyright (c) 2024, Lincoln D. Stein and the InvokeAI Development Team
+"""Class for LoRA model loading in InvokeAI."""
+
+
+from pathlib import Path
+from typing import Optional, Tuple
+from logging import Logger
+
+from invokeai.backend.model_manager.load.model_cache.model_cache_base import ModelCacheBase
+from invokeai.backend.model_manager.load.convert_cache import ModelConvertCacheBase
+from invokeai.app.services.config import InvokeAIAppConfig
+from invokeai.backend.model_manager import (
+    AnyModel,
+    AnyModelConfig,
+    BaseModelType,
+    ModelFormat,
+    ModelRepoVariant,
+    ModelType,
+    SubModelType,
+)
+from invokeai.backend.model_manager.lora import LoRAModelRaw
+from invokeai.backend.model_manager.load.load_base import AnyModelLoader
+from invokeai.backend.model_manager.load.load_default import ModelLoader
+
+@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.Lora, format=ModelFormat.Diffusers)
+@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.Lora, format=ModelFormat.Lycoris)
+class LoraLoader(ModelLoader):
+    """Class to load LoRA models."""
+
+    # We cheat a little bit to get access to the model base
+    def __init__(
+        self,
+        app_config: InvokeAIAppConfig,
+        logger: Logger,
+        ram_cache: ModelCacheBase[AnyModel],
+        convert_cache: ModelConvertCacheBase,
+    ):
+        """Initialize the loader."""
+        super().__init__(app_config, logger, ram_cache, convert_cache)
+        self._model_base: Optional[BaseModelType] = None
+
+    def _load_model(
+        self,
+        model_path: Path,
+        model_variant: Optional[ModelRepoVariant] = None,
+        submodel_type: Optional[SubModelType] = None,
+    ) -> AnyModel:
+        if submodel_type is not None:
+            raise ValueError("There are no submodels in a LoRA model.")
+        model = LoRAModelRaw.from_checkpoint(
+            file_path=model_path,
+            dtype=self._torch_dtype,
+            base_model=self._model_base,
+        )
+        return model
+
+    # override
+    def _get_model_path(
+            self, config: AnyModelConfig, submodel_type: Optional[SubModelType] = None
+    ) -> Tuple[Path, AnyModelConfig, Optional[SubModelType]]:
+        self._model_base = config.base  # cheating a little - setting this variable for later call to _load_model()
+
+        model_base_path = self._app_config.models_path
+        model_path = model_base_path / config.path
+
+        if config.format == ModelFormat.Diffusers:
+            for ext in ["safetensors", "bin"]:  # return path to the safetensors file inside the folder
+                path = model_base_path / config.path / f"pytorch_lora_weights.{ext}"
+                if path.exists():
+                    model_path = path
+                    break
+
+        result = model_path.resolve(), config, submodel_type
+        return result
+
+
diff --git a/invokeai/backend/model_manager/load/model_loaders/stable_diffusion.py b/invokeai/backend/model_manager/load/model_loaders/stable_diffusion.py
new file mode 100644
index 0000000000..a963e8403b
--- /dev/null
+++ b/invokeai/backend/model_manager/load/model_loaders/stable_diffusion.py
@@ -0,0 +1,93 @@
+# Copyright (c) 2024, Lincoln D. Stein and the InvokeAI Development Team
+"""Class for StableDiffusion model loading in InvokeAI."""
+
+
+from pathlib import Path
+from typing import Optional
+
+from diffusers import StableDiffusionInpaintPipeline, StableDiffusionPipeline
+
+from invokeai.backend.model_manager import (
+    AnyModel,
+    AnyModelConfig,
+    BaseModelType,
+    ModelFormat,
+    ModelRepoVariant,
+    ModelType,
+    ModelVariantType,
+    SubModelType,
+)
+from invokeai.backend.model_manager.config import MainCheckpointConfig
+from invokeai.backend.model_manager.convert_ckpt_to_diffusers import convert_ckpt_to_diffusers
+from invokeai.backend.model_manager.load.load_base import AnyModelLoader
+from invokeai.backend.model_manager.load.load_default import ModelLoader
+
+
+@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.Main, format=ModelFormat.Diffusers)
+@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.Main, format=ModelFormat.Checkpoint)
+class StableDiffusionDiffusersModel(ModelLoader):
+    """Class to load main models."""
+
+    model_base_to_model_type = {
+        BaseModelType.StableDiffusion1: "FrozenCLIPEmbedder",
+        BaseModelType.StableDiffusion2: "FrozenOpenCLIPEmbedder",
+        BaseModelType.StableDiffusionXL: "SDXL",
+        BaseModelType.StableDiffusionXLRefiner: "SDXL-Refiner",
+    }
+
+    def _load_model(
+        self,
+        model_path: Path,
+        model_variant: Optional[ModelRepoVariant] = None,
+        submodel_type: Optional[SubModelType] = None,
+    ) -> AnyModel:
+        if not submodel_type is not None:
+            raise Exception("A submodel type must be provided when loading main pipelines.")
+        load_class = self._get_hf_load_class(model_path, submodel_type)
+        variant = model_variant.value if model_variant else None
+        model_path = model_path / submodel_type.value
+        result: AnyModel = load_class.from_pretrained(
+            model_path,
+            torch_dtype=self._torch_dtype,
+            variant=variant,
+        )  # type: ignore
+        return result
+
+    def _needs_conversion(self, config: AnyModelConfig, model_path: Path, dest_path: Path) -> bool:
+        if config.format != ModelFormat.Checkpoint:
+            return False
+        elif (
+            dest_path.exists()
+            and (dest_path / "model_index.json").stat().st_mtime >= (config.last_modified or 0.0)
+            and (dest_path / "model_index.json").stat().st_mtime >= model_path.stat().st_mtime
+        ):
+            return False
+        else:
+            return True
+
+    def _convert_model(self, config: AnyModelConfig, weights_path: Path, output_path: Path) -> Path:
+        assert isinstance(config, MainCheckpointConfig)
+        variant = config.variant
+        base = config.base
+        pipeline_class = (
+            StableDiffusionInpaintPipeline if variant == ModelVariantType.Inpaint else StableDiffusionPipeline
+        )
+
+        config_file = config.config
+
+        self._logger.info(f"Converting {weights_path} to diffusers format")
+        convert_ckpt_to_diffusers(
+            weights_path,
+            output_path,
+            model_type=self.model_base_to_model_type[base],
+            model_version=base,
+            model_variant=variant,
+            original_config_file=self._app_config.root_path / config_file,
+            extract_ema=True,
+            scan_needed=True,
+            pipeline_class=pipeline_class,
+            from_safetensors=weights_path.suffix == ".safetensors",
+            precision=self._torch_dtype,
+            load_safety_checker=False,
+        )
+        return output_path
diff --git a/invokeai/backend/model_manager/load/model_loaders/vae.py b/invokeai/backend/model_manager/load/model_loaders/vae.py
index 6f21c3d090..7a35e53459 100644
--- a/invokeai/backend/model_manager/load/model_loaders/vae.py
+++ b/invokeai/backend/model_manager/load/model_loaders/vae.py
@@ -2,68 +2,54 @@
 """Class for VAE model loading in InvokeAI."""
 
 from pathlib import Path
-from typing import Optional
 
-import torch
 import safetensors
-from omegaconf import OmegaConf, DictConfig
-from invokeai.backend.util.devices import torch_dtype
-from invokeai.backend.model_manager import AnyModel, AnyModelConfig, BaseModelType, ModelFormat, ModelRepoVariant, ModelType, SubModelType
-from invokeai.backend.model_manager.load.load_base import AnyModelLoader
-from invokeai.backend.model_manager.load.load_default import ModelLoader
+import torch
+from omegaconf import DictConfig, OmegaConf
+
+from invokeai.backend.model_manager import (
+    AnyModelConfig,
+    BaseModelType,
+    ModelFormat,
+    ModelType,
+)
 from invokeai.backend.model_manager.convert_ckpt_to_diffusers import convert_ldm_vae_to_diffusers
+from invokeai.backend.model_manager.load.load_base import AnyModelLoader
+from .generic_diffusers import GenericDiffusersLoader
+
 
 @AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.Vae, format=ModelFormat.Diffusers)
 @AnyModelLoader.register(base=BaseModelType.StableDiffusion1, type=ModelType.Vae, format=ModelFormat.Checkpoint)
 @AnyModelLoader.register(base=BaseModelType.StableDiffusion2, type=ModelType.Vae, format=ModelFormat.Checkpoint)
-class VaeDiffusersModel(ModelLoader):
+class VaeLoader(GenericDiffusersLoader):
     """Class to load VAE models."""
 
-    def _load_model(
-        self,
-        model_path: Path,
-        model_variant: Optional[ModelRepoVariant] = None,
-        submodel_type: Optional[SubModelType] = None,
-    ) -> AnyModel:
-        if submodel_type is not None:
-            raise Exception("There are no submodels in VAEs")
-        vae_class = self._get_hf_load_class(model_path)
-        variant = model_variant.value if model_variant else None
-        result: AnyModel = vae_class.from_pretrained(
-            model_path, torch_dtype=self._torch_dtype, variant=variant
-        )  # type: ignore
-        return result
-
     def _needs_conversion(self, config: AnyModelConfig, model_path: Path, dest_path: Path) -> bool:
-        print(f'DEBUG: last_modified={config.last_modified}')
-        print(f'DEBUG: cache_path={(dest_path / "config.json").stat().st_mtime}')
-        print(f'DEBUG: model_path={model_path.stat().st_mtime}')
         if config.format != ModelFormat.Checkpoint:
             return False
-        elif dest_path.exists() \
-             and (dest_path / "config.json").stat().st_mtime >= config.last_modified \
-             and (dest_path / "config.json").stat().st_mtime >= model_path.stat().st_mtime:
+        elif (
+            dest_path.exists()
+            and (dest_path / "config.json").stat().st_mtime >= (config.last_modified or 0.0)
+            and (dest_path / "config.json").stat().st_mtime >= model_path.stat().st_mtime
+        ):
             return False
         else:
             return True
 
-    def _convert_model(self,
-                       config: AnyModelConfig,
-                       weights_path: Path,
-                       output_path: Path
-                       ) -> Path:
+    def _convert_model(self, config: AnyModelConfig, weights_path: Path, output_path: Path) -> Path:
+        # TO DO: check whether sdxl VAE models convert.
         if config.base not in {BaseModelType.StableDiffusion1, BaseModelType.StableDiffusion2}:
             raise Exception(f"Vae conversion not supported for model type: {config.base}")
         else:
-            config_file = 'v1-inference.yaml' if config.base == BaseModelType.StableDiffusion1 else "v2-inference-v.yaml"
+            config_file = (
+                "v1-inference.yaml" if config.base == BaseModelType.StableDiffusion1 else "v2-inference-v.yaml"
+            )
 
         if weights_path.suffix == ".safetensors":
             checkpoint = safetensors.torch.load_file(weights_path, device="cpu")
         else:
             checkpoint = torch.load(weights_path, map_location="cpu")
 
-        dtype = torch_dtype()
-
         # sometimes weights are hidden under "state_dict", and sometimes not
         if "state_dict" in checkpoint:
             checkpoint = checkpoint["state_dict"]
@@ -71,13 +57,11 @@ class VaeDiffusersModel(ModelLoader):
         ckpt_config = OmegaConf.load(self._app_config.legacy_conf_path / config_file)
         assert isinstance(ckpt_config, DictConfig)
 
-        print(f'DEBUG: CONVERTIGN')
         vae_model = convert_ldm_vae_to_diffusers(
             checkpoint=checkpoint,
             vae_config=ckpt_config,
             image_size=512,
         )
-        vae_model.to(dtype) # set precision appropriately
-        vae_model.save_pretrained(output_path, safe_serialization=True, torch_dtype=dtype)
+        vae_model.to(self._torch_dtype)  # set precision appropriately
+        vae_model.save_pretrained(output_path, safe_serialization=True)
         return output_path
-
diff --git a/invokeai/backend/model_manager/load/model_util.py b/invokeai/backend/model_manager/load/model_util.py
index 7c27e66472..404c88bbbc 100644
--- a/invokeai/backend/model_manager/load/model_util.py
+++ b/invokeai/backend/model_manager/load/model_util.py
@@ -8,10 +8,11 @@ from typing import Optional, Union
 import torch
 from diffusers import DiffusionPipeline
 
+from invokeai.backend.model_manager.config import AnyModel
 from invokeai.backend.model_manager.onnx_runtime import IAIOnnxRuntimeModel
 
 
-def calc_model_size_by_data(model: Union[DiffusionPipeline, torch.nn.Module, IAIOnnxRuntimeModel]) -> int:
+def calc_model_size_by_data(model: AnyModel) -> int:
     """Get size of a model in memory in bytes."""
     if isinstance(model, DiffusionPipeline):
         return _calc_pipeline_by_data(model)
@@ -50,7 +51,7 @@ def calc_model_size_by_fs(model_path: Path, subfolder: Optional[str] = None, var
     """Estimate the size of a model on disk in bytes."""
     if model_path.is_file():
         return model_path.stat().st_size
-        
+
     if subfolder is not None:
         model_path = model_path / subfolder
 
diff --git a/invokeai/backend/model_manager/lora.py b/invokeai/backend/model_manager/lora.py
new file mode 100644
index 0000000000..4c48de48ec
--- /dev/null
+++ b/invokeai/backend/model_manager/lora.py
@@ -0,0 +1,620 @@
+# Copyright (c) 2024 The InvokeAI Development team
+"""LoRA model support."""
+
+import torch
+from safetensors.torch import load_file
+from pathlib import Path
+from typing import Dict, Optional, Union, List, Tuple
+from typing_extensions import Self
+from invokeai.backend.model_manager import BaseModelType
+
+class LoRALayerBase:
+    # rank: Optional[int]
+    # alpha: Optional[float]
+    # bias: Optional[torch.Tensor]
+    # layer_key: str
+
+    # @property
+    # def scale(self):
+    #    return self.alpha / self.rank if (self.alpha and self.rank) else 1.0
+
+    def __init__(
+        self,
+        layer_key: str,
+        values: Dict[str, torch.Tensor],
+    ):
+        if "alpha" in values:
+            self.alpha = values["alpha"].item()
+        else:
+            self.alpha = None
+
+        if "bias_indices" in values and "bias_values" in values and "bias_size" in values:
+            self.bias: Optional[torch.Tensor] = torch.sparse_coo_tensor(
+                values["bias_indices"],
+                values["bias_values"],
+                tuple(values["bias_size"]),
+            )
+
+        else:
+            self.bias = None
+
+        self.rank = None  # set in layer implementation
+        self.layer_key = layer_key
+
+    def get_weight(self, orig_weight: torch.Tensor) -> torch.Tensor:
+        raise NotImplementedError()
+
+    def calc_size(self) -> int:
+        model_size = 0
+        for val in [self.bias]:
+            if val is not None:
+                model_size += val.nelement() * val.element_size()
+        return model_size
+
+    def to(
+        self,
+        device: Optional[torch.device] = None,
+        dtype: Optional[torch.dtype] = None,
+    ) -> None:
+        if self.bias is not None:
+            self.bias = self.bias.to(device=device, dtype=dtype)
+
+
+# TODO: find and debug lora/locon with bias
+class LoRALayer(LoRALayerBase):
+    # up: torch.Tensor
+    # mid: Optional[torch.Tensor]
+    # down: torch.Tensor
+
+    def __init__(
+        self,
+        layer_key: str,
+        values: Dict[str, torch.Tensor],
+    ):
+        super().__init__(layer_key, values)
+
+        self.up = values["lora_up.weight"]
+        self.down = values["lora_down.weight"]
+        if "lora_mid.weight" in values:
+            self.mid: Optional[torch.Tensor] = values["lora_mid.weight"]
+        else:
+            self.mid = None
+
+        self.rank = self.down.shape[0]
+
+    def get_weight(self, orig_weight: torch.Tensor):
+        if self.mid is not None:
+            up = self.up.reshape(self.up.shape[0], self.up.shape[1])
+            down = self.down.reshape(self.down.shape[0], self.down.shape[1])
+            weight = torch.einsum("m n w h, i m, n j -> i j w h", self.mid, up, down)
+        else:
+            weight = self.up.reshape(self.up.shape[0], -1) @ self.down.reshape(self.down.shape[0], -1)
+
+        return weight
+
+    def calc_size(self) -> int:
+        model_size = super().calc_size()
+        for val in [self.up, self.mid, self.down]:
+            if val is not None:
+                model_size += val.nelement() * val.element_size()
+        return model_size
+
+    def to(
+        self,
+        device: Optional[torch.device] = None,
+        dtype: Optional[torch.dtype] = None,
+    ) -> None:
+        super().to(device=device, dtype=dtype)
+
+        self.up = self.up.to(device=device, dtype=dtype)
+        self.down = self.down.to(device=device, dtype=dtype)
+
+        if self.mid is not None:
+            self.mid = self.mid.to(device=device, dtype=dtype)
+
+
+class LoHALayer(LoRALayerBase):
+    # w1_a: torch.Tensor
+    # w1_b: torch.Tensor
+    # w2_a: torch.Tensor
+    # w2_b: torch.Tensor
+    # t1: Optional[torch.Tensor] = None
+    # t2: Optional[torch.Tensor] = None
+
+    def __init__(
+        self,
+        layer_key: str,
+        values: Dict[str, torch.Tensor]
+    ):
+        super().__init__(layer_key, values)
+
+        self.w1_a = values["hada_w1_a"]
+        self.w1_b = values["hada_w1_b"]
+        self.w2_a = values["hada_w2_a"]
+        self.w2_b = values["hada_w2_b"]
+
+        if "hada_t1" in values:
+            self.t1: Optional[torch.Tensor] = values["hada_t1"]
+        else:
+            self.t1 = None
+
+        if "hada_t2" in values:
+            self.t2: Optional[torch.Tensor] = values["hada_t2"]
+        else:
+            self.t2 = None
+
+        self.rank = self.w1_b.shape[0]
+
+    def get_weight(self, orig_weight: torch.Tensor) -> torch.Tensor:
+        if self.t1 is None:
+            weight: torch.Tensor = (self.w1_a @ self.w1_b) * (self.w2_a @ self.w2_b)
+
+        else:
+            rebuild1 = torch.einsum("i j k l, j r, i p -> p r k l", self.t1, self.w1_b, self.w1_a)
+            rebuild2 = torch.einsum("i j k l, j r, i p -> p r k l", self.t2, self.w2_b, self.w2_a)
+            weight = rebuild1 * rebuild2
+
+        return weight
+
+    def calc_size(self) -> int:
+        model_size = super().calc_size()
+        for val in [self.w1_a, self.w1_b, self.w2_a, self.w2_b, self.t1, self.t2]:
+            if val is not None:
+                model_size += val.nelement() * val.element_size()
+        return model_size
+
+    def to(
+        self,
+        device: Optional[torch.device] = None,
+        dtype: Optional[torch.dtype] = None,
+    ) -> None:
+        super().to(device=device, dtype=dtype)
+
+        self.w1_a = self.w1_a.to(device=device, dtype=dtype)
+        self.w1_b = self.w1_b.to(device=device, dtype=dtype)
+        if self.t1 is not None:
+            self.t1 = self.t1.to(device=device, dtype=dtype)
+
+        self.w2_a = self.w2_a.to(device=device, dtype=dtype)
+        self.w2_b = self.w2_b.to(device=device, dtype=dtype)
+        if self.t2 is not None:
+            self.t2 = self.t2.to(device=device, dtype=dtype)
+
+
+class LoKRLayer(LoRALayerBase):
+    # w1: Optional[torch.Tensor] = None
+    # w1_a: Optional[torch.Tensor] = None
+    # w1_b: Optional[torch.Tensor] = None
+    # w2: Optional[torch.Tensor] = None
+    # w2_a: Optional[torch.Tensor] = None
+    # w2_b: Optional[torch.Tensor] = None
+    # t2: Optional[torch.Tensor] = None
+
+    def __init__(
+        self,
+        layer_key: str,
+        values: Dict[str, torch.Tensor],
+    ):
+        super().__init__(layer_key, values)
+
+        if "lokr_w1" in values:
+            self.w1: Optional[torch.Tensor] = values["lokr_w1"]
+            self.w1_a = None
+            self.w1_b = None
+        else:
+            self.w1 = None
+            self.w1_a = values["lokr_w1_a"]
+            self.w1_b = values["lokr_w1_b"]
+
+        if "lokr_w2" in values:
+            self.w2: Optional[torch.Tensor] = values["lokr_w2"]
+            self.w2_a = None
+            self.w2_b = None
+        else:
+            self.w2 = None
+            self.w2_a = values["lokr_w2_a"]
+            self.w2_b = values["lokr_w2_b"]
+
+        if "lokr_t2" in values:
+            self.t2: Optional[torch.Tensor] = values["lokr_t2"]
+        else:
+            self.t2 = None
+
+        if "lokr_w1_b" in values:
+            self.rank = values["lokr_w1_b"].shape[0]
+        elif "lokr_w2_b" in values:
+            self.rank = values["lokr_w2_b"].shape[0]
+        else:
+            self.rank = None  # unscaled
+
+    def get_weight(self, orig_weight: torch.Tensor) -> torch.Tensor:
+        w1: Optional[torch.Tensor] = self.w1
+        if w1 is None:
+            assert self.w1_a is not None
+            assert self.w1_b is not None
+            w1 = self.w1_a @ self.w1_b
+
+        w2 = self.w2
+        if w2 is None:
+            if self.t2 is None:
+                assert self.w2_a is not None
+                assert self.w2_b is not None
+                w2 = self.w2_a @ self.w2_b
+            else:
+                w2 = torch.einsum("i j k l, i p, j r -> p r k l", self.t2, self.w2_a, self.w2_b)
+
+        if len(w2.shape) == 4:
+            w1 = w1.unsqueeze(2).unsqueeze(2)
+        w2 = w2.contiguous()
+        assert w1 is not None
+        assert w2 is not None
+        weight = torch.kron(w1, w2)
+
+        return weight
+
+    def calc_size(self) -> int:
+        model_size = super().calc_size()
+        for val in [self.w1, self.w1_a, self.w1_b, self.w2, self.w2_a, self.w2_b, self.t2]:
+            if val is not None:
+                model_size += val.nelement() * val.element_size()
+        return model_size
+
+    def to(
+        self,
+        device: Optional[torch.device] = None,
+        dtype: Optional[torch.dtype] = None,
+    ) -> None:
+        super().to(device=device, dtype=dtype)
+
+        if self.w1 is not None:
+            self.w1 = self.w1.to(device=device, dtype=dtype)
+        else:
+            assert self.w1_a is not None
+            assert self.w1_b is not None
+            self.w1_a = self.w1_a.to(device=device, dtype=dtype)
+            self.w1_b = self.w1_b.to(device=device, dtype=dtype)
+
+        if self.w2 is not None:
+            self.w2 = self.w2.to(device=device, dtype=dtype)
+        else:
+            assert self.w2_a is not None
+            assert self.w2_b is not None
+            self.w2_a = self.w2_a.to(device=device, dtype=dtype)
+            self.w2_b = self.w2_b.to(device=device, dtype=dtype)
+
+        if self.t2 is not None:
+            self.t2 = self.t2.to(device=device, dtype=dtype)
+
+
+class FullLayer(LoRALayerBase):
+    # weight: torch.Tensor
+
+    def __init__(
+        self,
+        layer_key: str,
+        values: Dict[str, torch.Tensor],
+    ):
+        super().__init__(layer_key, values)
+
+        self.weight = values["diff"]
+
+        if len(values.keys()) > 1:
+            _keys = list(values.keys())
+            _keys.remove("diff")
+            raise NotImplementedError(f"Unexpected keys in lora diff layer: {_keys}")
+
+        self.rank = None  # unscaled
+
+    def get_weight(self, orig_weight: torch.Tensor) -> torch.Tensor:
+        return self.weight
+
+    def calc_size(self) -> int:
+        model_size = super().calc_size()
+        model_size += self.weight.nelement() * self.weight.element_size()
+        return model_size
+
+    def to(
+        self,
+        device: Optional[torch.device] = None,
+        dtype: Optional[torch.dtype] = None,
+    ):
+        super().to(device=device, dtype=dtype)
+
+        self.weight = self.weight.to(device=device, dtype=dtype)
+
+
+class IA3Layer(LoRALayerBase):
+    # weight: torch.Tensor
+    # on_input: torch.Tensor
+
+    def __init__(
+        self,
+        layer_key: str,
+            values: Dict[str, torch.Tensor],
+    ):
+        super().__init__(layer_key, values)
+
+        self.weight = values["weight"]
+        self.on_input = values["on_input"]
+
+        self.rank = None  # unscaled
+
+    def get_weight(self, orig_weight: torch.Tensor):
+        weight = self.weight
+        if not self.on_input:
+            weight = weight.reshape(-1, 1)
+        return orig_weight * weight
+
+    def calc_size(self) -> int:
+        model_size = super().calc_size()
+        model_size += self.weight.nelement() * self.weight.element_size()
+        model_size += self.on_input.nelement() * self.on_input.element_size()
+        return model_size
+
+    def to(
+        self,
+        device: Optional[torch.device] = None,
+        dtype: Optional[torch.dtype] = None,
+    ):
+        super().to(device=device, dtype=dtype)
+
+        self.weight = self.weight.to(device=device, dtype=dtype)
+        self.on_input = self.on_input.to(device=device, dtype=dtype)
+
+AnyLoRALayer = Union[LoRALayer, LoHALayer, LoKRLayer, FullLayer, IA3Layer]
+        
+# TODO: rename all methods used in model logic with Info postfix and remove here Raw postfix
+class LoRAModelRaw:  # (torch.nn.Module):
+    _name: str
+    layers: Dict[str, AnyLoRALayer]
+
+    def __init__(
+        self,
+        name: str,
+        layers: Dict[str, AnyLoRALayer],
+    ):
+        self._name = name
+        self.layers = layers
+
+    @property
+    def name(self) -> str:
+        return self._name
+
+    def to(
+        self,
+        device: Optional[torch.device] = None,
+        dtype: Optional[torch.dtype] = None,
+    ) -> None:
+        # TODO: try revert if exception?
+        for _key, layer in self.layers.items():
+            layer.to(device=device, dtype=dtype)
+
+    def calc_size(self) -> int:
+        model_size = 0
+        for _, layer in self.layers.items():
+            model_size += layer.calc_size()
+        return model_size
+
+    @classmethod
+    def _convert_sdxl_keys_to_diffusers_format(cls, state_dict: Dict[str, torch.Tensor]) -> Dict[str, torch.Tensor]:
+        """Convert the keys of an SDXL LoRA state_dict to diffusers format.
+
+        The input state_dict can be in either Stability AI format or diffusers format. If the state_dict is already in
+        diffusers format, then this function will have no effect.
+
+        This function is adapted from:
+        https://github.com/bmaltais/kohya_ss/blob/2accb1305979ba62f5077a23aabac23b4c37e935/networks/lora_diffusers.py#L385-L409
+
+        Args:
+            state_dict (Dict[str, Tensor]): The SDXL LoRA state_dict.
+
+        Raises:
+            ValueError: If state_dict contains an unrecognized key, or not all keys could be converted.
+
+        Returns:
+            Dict[str, Tensor]: The diffusers-format state_dict.
+        """
+        converted_count = 0  # The number of Stability AI keys converted to diffusers format.
+        not_converted_count = 0  # The number of keys that were not converted.
+
+        # Get a sorted list of Stability AI UNet keys so that we can efficiently search for keys with matching prefixes.
+        # For example, we want to efficiently find `input_blocks_4_1` in the list when searching for
+        # `input_blocks_4_1_proj_in`.
+        stability_unet_keys = list(SDXL_UNET_STABILITY_TO_DIFFUSERS_MAP)
+        stability_unet_keys.sort()
+
+        new_state_dict = {}
+        for full_key, value in state_dict.items():
+            if full_key.startswith("lora_unet_"):
+                search_key = full_key.replace("lora_unet_", "")
+                # Use bisect to find the key in stability_unet_keys that *may* match the search_key's prefix.
+                position = bisect.bisect_right(stability_unet_keys, search_key)
+                map_key = stability_unet_keys[position - 1]
+                # Now, check if the map_key *actually* matches the search_key.
+                if search_key.startswith(map_key):
+                    new_key = full_key.replace(map_key, SDXL_UNET_STABILITY_TO_DIFFUSERS_MAP[map_key])
+                    new_state_dict[new_key] = value
+                    converted_count += 1
+                else:
+                    new_state_dict[full_key] = value
+                    not_converted_count += 1
+            elif full_key.startswith("lora_te1_") or full_key.startswith("lora_te2_"):
+                # The CLIP text encoders have the same keys in both Stability AI and diffusers formats.
+                new_state_dict[full_key] = value
+                continue
+            else:
+                raise ValueError(f"Unrecognized SDXL LoRA key prefix: '{full_key}'.")
+
+        if converted_count > 0 and not_converted_count > 0:
+            raise ValueError(
+                f"The SDXL LoRA could only be partially converted to diffusers format. converted={converted_count},"
+                f" not_converted={not_converted_count}"
+            )
+
+        return new_state_dict
+
+    @classmethod
+    def from_checkpoint(
+        cls,
+        file_path: Union[str, Path],
+        device: Optional[torch.device] = None,
+        dtype: Optional[torch.dtype] = None,
+        base_model: Optional[BaseModelType] = None,
+    ) -> Self:
+        device = device or torch.device("cpu")
+        dtype = dtype or torch.float32
+
+        if isinstance(file_path, str):
+            file_path = Path(file_path)
+
+        model = cls(
+            name=file_path.stem,  # TODO:
+            layers={},
+        )
+
+        if file_path.suffix == ".safetensors":
+            state_dict = load_file(file_path.absolute().as_posix(), device="cpu")
+        else:
+            state_dict = torch.load(file_path, map_location="cpu")
+
+        state_dict = cls._group_state(state_dict)
+
+        if base_model == BaseModelType.StableDiffusionXL:
+            state_dict = cls._convert_sdxl_keys_to_diffusers_format(state_dict)
+
+        for layer_key, values in state_dict.items():
+            # lora and locon
+            if "lora_down.weight" in values:
+                layer: AnyLoRALayer = LoRALayer(layer_key, values)
+
+            # loha
+            elif "hada_w1_b" in values:
+                layer = LoHALayer(layer_key, values)
+
+            # lokr
+            elif "lokr_w1_b" in values or "lokr_w1" in values:
+                layer = LoKRLayer(layer_key, values)
+
+            # diff
+            elif "diff" in values:
+                layer = FullLayer(layer_key, values)
+
+            # ia3
+            elif "weight" in values and "on_input" in values:
+                layer = IA3Layer(layer_key, values)
+
+            else:
+                print(f">> Encountered unknown lora layer module in {model.name}: {layer_key} - {list(values.keys())}")
+                raise Exception("Unknown lora format!")
+
+            # lower memory consumption by removing already parsed layer values
+            state_dict[layer_key].clear()
+
+            layer.to(device=device, dtype=dtype)
+            model.layers[layer_key] = layer
+
+        return model
+
+    @staticmethod
+    def _group_state(state_dict: Dict[str, torch.Tensor]) -> Dict[str, Dict[str, torch.Tensor]]:
+        state_dict_groupped: Dict[str, Dict[str, torch.Tensor]] = {}
+
+        for key, value in state_dict.items():
+            stem, leaf = key.split(".", 1)
+            if stem not in state_dict_groupped:
+                state_dict_groupped[stem] = {}
+            state_dict_groupped[stem][leaf] = value
+
+        return state_dict_groupped
+
+
+# code from
+# https://github.com/bmaltais/kohya_ss/blob/2accb1305979ba62f5077a23aabac23b4c37e935/networks/lora_diffusers.py#L15C1-L97C32
+def make_sdxl_unet_conversion_map() -> List[Tuple[str,str]]:
+    """Create a dict mapping state_dict keys from Stability AI SDXL format to diffusers SDXL format."""
+    unet_conversion_map_layer = []
+
+    for i in range(3):  # num_blocks is 3 in sdxl
+        # loop over downblocks/upblocks
+        for j in range(2):
+            # loop over resnets/attentions for downblocks
+            hf_down_res_prefix = f"down_blocks.{i}.resnets.{j}."
+            sd_down_res_prefix = f"input_blocks.{3*i + j + 1}.0."
+            unet_conversion_map_layer.append((sd_down_res_prefix, hf_down_res_prefix))
+
+            if i < 3:
+                # no attention layers in down_blocks.3
+                hf_down_atn_prefix = f"down_blocks.{i}.attentions.{j}."
+                sd_down_atn_prefix = f"input_blocks.{3*i + j + 1}.1."
+                unet_conversion_map_layer.append((sd_down_atn_prefix, hf_down_atn_prefix))
+
+        for j in range(3):
+            # loop over resnets/attentions for upblocks
+            hf_up_res_prefix = f"up_blocks.{i}.resnets.{j}."
+            sd_up_res_prefix = f"output_blocks.{3*i + j}.0."
+            unet_conversion_map_layer.append((sd_up_res_prefix, hf_up_res_prefix))
+
+            # if i > 0: commentout for sdxl
+            # no attention layers in up_blocks.0
+            hf_up_atn_prefix = f"up_blocks.{i}.attentions.{j}."
+            sd_up_atn_prefix = f"output_blocks.{3*i + j}.1."
+            unet_conversion_map_layer.append((sd_up_atn_prefix, hf_up_atn_prefix))
+
+        if i < 3:
+            # no downsample in down_blocks.3
+            hf_downsample_prefix = f"down_blocks.{i}.downsamplers.0.conv."
+            sd_downsample_prefix = f"input_blocks.{3*(i+1)}.0.op."
+            unet_conversion_map_layer.append((sd_downsample_prefix, hf_downsample_prefix))
+
+            # no upsample in up_blocks.3
+            hf_upsample_prefix = f"up_blocks.{i}.upsamplers.0."
+            sd_upsample_prefix = f"output_blocks.{3*i + 2}.{2}."  # change for sdxl
+            unet_conversion_map_layer.append((sd_upsample_prefix, hf_upsample_prefix))
+
+    hf_mid_atn_prefix = "mid_block.attentions.0."
+    sd_mid_atn_prefix = "middle_block.1."
+    unet_conversion_map_layer.append((sd_mid_atn_prefix, hf_mid_atn_prefix))
+
+    for j in range(2):
+        hf_mid_res_prefix = f"mid_block.resnets.{j}."
+        sd_mid_res_prefix = f"middle_block.{2*j}."
+        unet_conversion_map_layer.append((sd_mid_res_prefix, hf_mid_res_prefix))
+
+    unet_conversion_map_resnet = [
+        # (stable-diffusion, HF Diffusers)
+        ("in_layers.0.", "norm1."),
+        ("in_layers.2.", "conv1."),
+        ("out_layers.0.", "norm2."),
+        ("out_layers.3.", "conv2."),
+        ("emb_layers.1.", "time_emb_proj."),
+        ("skip_connection.", "conv_shortcut."),
+    ]
+
+    unet_conversion_map = []
+    for sd, hf in unet_conversion_map_layer:
+        if "resnets" in hf:
+            for sd_res, hf_res in unet_conversion_map_resnet:
+                unet_conversion_map.append((sd + sd_res, hf + hf_res))
+        else:
+            unet_conversion_map.append((sd, hf))
+
+    for j in range(2):
+        hf_time_embed_prefix = f"time_embedding.linear_{j+1}."
+        sd_time_embed_prefix = f"time_embed.{j*2}."
+        unet_conversion_map.append((sd_time_embed_prefix, hf_time_embed_prefix))
+
+    for j in range(2):
+        hf_label_embed_prefix = f"add_embedding.linear_{j+1}."
+        sd_label_embed_prefix = f"label_emb.0.{j*2}."
+        unet_conversion_map.append((sd_label_embed_prefix, hf_label_embed_prefix))
+
+    unet_conversion_map.append(("input_blocks.0.0.", "conv_in."))
+    unet_conversion_map.append(("out.0.", "conv_norm_out."))
+    unet_conversion_map.append(("out.2.", "conv_out."))
+
+    return unet_conversion_map
+
+
+SDXL_UNET_STABILITY_TO_DIFFUSERS_MAP = {
+    sd.rstrip(".").replace(".", "_"): hf.rstrip(".").replace(".", "_") for sd, hf in make_sdxl_unet_conversion_map()
+}
diff --git a/invokeai/backend/model_manager/probe.py b/invokeai/backend/model_manager/probe.py
index 9fd118b782..64a20a2092 100644
--- a/invokeai/backend/model_manager/probe.py
+++ b/invokeai/backend/model_manager/probe.py
@@ -29,8 +29,12 @@ CkptType = Dict[str, Any]
 
 LEGACY_CONFIGS: Dict[BaseModelType, Dict[ModelVariantType, Union[str, Dict[SchedulerPredictionType, str]]]] = {
     BaseModelType.StableDiffusion1: {
-        ModelVariantType.Normal: "v1-inference.yaml",
+        ModelVariantType.Normal: {
+            SchedulerPredictionType.Epsilon: "v1-inference.yaml",
+            SchedulerPredictionType.VPrediction: "v1-inference-v.yaml",
+        },
         ModelVariantType.Inpaint: "v1-inpainting-inference.yaml",
+        ModelVariantType.Depth: "v2-midas-inference.yaml",
     },
     BaseModelType.StableDiffusion2: {
         ModelVariantType.Normal: {
diff --git a/invokeai/backend/util/__init__.py b/invokeai/backend/util/__init__.py
index 0164dffe30..7b48f0364e 100644
--- a/invokeai/backend/util/__init__.py
+++ b/invokeai/backend/util/__init__.py
@@ -12,14 +12,22 @@ from .devices import (  # noqa: F401
     torch_dtype,
 )
 from .logging import InvokeAILogger
-from .util import ( # TO DO: Clean this up; remove the unused symbols
+from .util import (  # TO DO: Clean this up; remove the unused symbols
     GIG,
     Chdir,
     ask_user,  # noqa
     directory_size,
     download_with_resume,
-    instantiate_from_config, # noqa
+    instantiate_from_config,  # noqa
     url_attachment_name,  # noqa
-    )
+)
 
-__all__ = ["GIG", "directory_size","Chdir", "download_with_resume", "InvokeAILogger", "choose_precision", "choose_torch_device"]
+__all__ = [
+    "GIG",
+    "directory_size",
+    "Chdir",
+    "download_with_resume",
+    "InvokeAILogger",
+    "choose_precision",
+    "choose_torch_device",
+]
diff --git a/invokeai/backend/util/devices.py b/invokeai/backend/util/devices.py
index ad3f4e139a..a787f9b6f4 100644
--- a/invokeai/backend/util/devices.py
+++ b/invokeai/backend/util/devices.py
@@ -1,7 +1,7 @@
 from __future__ import annotations
 
 from contextlib import nullcontext
-from typing import Union, Optional
+from typing import Optional, Union
 
 import torch
 from torch import autocast
diff --git a/invokeai/backend/util/util.py b/invokeai/backend/util/util.py
index 6589aa7278..ae376b41b2 100644
--- a/invokeai/backend/util/util.py
+++ b/invokeai/backend/util/util.py
@@ -27,6 +27,7 @@ from .devices import torch_dtype
 # actual size of a gig
 GIG = 1073741824
 
+
 def directory_size(directory: Path) -> int:
     """
     Return the aggregate size of all files in a directory (bytes).
@@ -39,6 +40,7 @@ def directory_size(directory: Path) -> int:
             sum += Path(root, d).stat().st_size
     return sum
 
+
 def log_txt_as_img(wh, xc, size=10):
     # wh a tuple of (width, height)
     # xc a list of captions to plot

From 0d3addc69bd333058b77feb1d9b9be23c1ce10e6 Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lstein@gmail.com>
Date: Sun, 4 Feb 2024 23:18:00 -0500
Subject: [PATCH 114/411] added textual inversion and lora loaders

---
 .../model_install/model_install_default.py    |   5 +
 .../{model_manager => embeddings}/lora.py     |  35 +-
 invokeai/backend/embeddings/model_patcher.py  | 586 ++++++++++++++++++
 invokeai/backend/model_management/lora.py     |   5 +-
 invokeai/backend/model_manager/config.py      |   4 +-
 .../model_manager/load/load_default.py        |  11 +-
 .../model_manager/load/memory_snapshot.py     |   2 +-
 .../load/model_cache/__init__.py              |   2 -
 .../load/model_loaders/controlnet.py          |   4 +-
 .../load/model_loaders/generic_diffusers.py   |   1 +
 .../load/model_loaders/ip_adapter.py          |   6 +-
 .../model_manager/load/model_loaders/lora.py  |  18 +-
 .../load/model_loaders/textual_inversion.py   |  55 ++
 .../model_manager/load/model_loaders/vae.py   |   1 +
 .../backend/model_manager/load/model_util.py  |   4 +-
 .../{model_manager => onnx}/onnx_runtime.py   |   0
 16 files changed, 701 insertions(+), 38 deletions(-)
 rename invokeai/backend/{model_manager => embeddings}/lora.py (96%)
 create mode 100644 invokeai/backend/embeddings/model_patcher.py
 create mode 100644 invokeai/backend/model_manager/load/model_loaders/textual_inversion.py
 rename invokeai/backend/{model_manager => onnx}/onnx_runtime.py (100%)

diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py
index 2b2294bfce..1c188b300d 100644
--- a/invokeai/app/services/model_install/model_install_default.py
+++ b/invokeai/app/services/model_install/model_install_default.py
@@ -178,6 +178,11 @@ class ModelInstallService(ModelInstallServiceBase):
         )
 
     def import_model(self, source: ModelSource, config: Optional[Dict[str, Any]] = None) -> ModelInstallJob:  # noqa D102
+        similar_jobs = [x for x in self.list_jobs() if x.source == source and not x.in_terminal_state]
+        if similar_jobs:
+            self._logger.warning(f"There is already an active install job for {source}. Not enqueuing.")
+            return similar_jobs[0]
+
         if isinstance(source, LocalModelSource):
             install_job = self._import_local_model(source, config)
             self._install_queue.put(install_job)  # synchronously install
diff --git a/invokeai/backend/model_manager/lora.py b/invokeai/backend/embeddings/lora.py
similarity index 96%
rename from invokeai/backend/model_manager/lora.py
rename to invokeai/backend/embeddings/lora.py
index 4c48de48ec..9a59a97708 100644
--- a/invokeai/backend/model_manager/lora.py
+++ b/invokeai/backend/embeddings/lora.py
@@ -1,13 +1,17 @@
 # Copyright (c) 2024 The InvokeAI Development team
 """LoRA model support."""
 
+import bisect
+from pathlib import Path
+from typing import Dict, List, Optional, Tuple, Union
+
 import torch
 from safetensors.torch import load_file
-from pathlib import Path
-from typing import Dict, Optional, Union, List, Tuple
 from typing_extensions import Self
+
 from invokeai.backend.model_manager import BaseModelType
 
+
 class LoRALayerBase:
     # rank: Optional[int]
     # alpha: Optional[float]
@@ -41,7 +45,7 @@ class LoRALayerBase:
         self.rank = None  # set in layer implementation
         self.layer_key = layer_key
 
-    def get_weight(self, orig_weight: torch.Tensor) -> torch.Tensor:
+    def get_weight(self, orig_weight: Optional[torch.Tensor]) -> torch.Tensor:
         raise NotImplementedError()
 
     def calc_size(self) -> int:
@@ -82,7 +86,7 @@ class LoRALayer(LoRALayerBase):
 
         self.rank = self.down.shape[0]
 
-    def get_weight(self, orig_weight: torch.Tensor):
+    def get_weight(self, orig_weight: Optional[torch.Tensor]) -> torch.Tensor:
         if self.mid is not None:
             up = self.up.reshape(self.up.shape[0], self.up.shape[1])
             down = self.down.reshape(self.down.shape[0], self.down.shape[1])
@@ -121,11 +125,7 @@ class LoHALayer(LoRALayerBase):
     # t1: Optional[torch.Tensor] = None
     # t2: Optional[torch.Tensor] = None
 
-    def __init__(
-        self,
-        layer_key: str,
-        values: Dict[str, torch.Tensor]
-    ):
+    def __init__(self, layer_key: str, values: Dict[str, torch.Tensor]):
         super().__init__(layer_key, values)
 
         self.w1_a = values["hada_w1_a"]
@@ -145,7 +145,7 @@ class LoHALayer(LoRALayerBase):
 
         self.rank = self.w1_b.shape[0]
 
-    def get_weight(self, orig_weight: torch.Tensor) -> torch.Tensor:
+    def get_weight(self, orig_weight: Optional[torch.Tensor]) -> torch.Tensor:
         if self.t1 is None:
             weight: torch.Tensor = (self.w1_a @ self.w1_b) * (self.w2_a @ self.w2_b)
 
@@ -227,7 +227,7 @@ class LoKRLayer(LoRALayerBase):
         else:
             self.rank = None  # unscaled
 
-    def get_weight(self, orig_weight: torch.Tensor) -> torch.Tensor:
+    def get_weight(self, orig_weight: Optional[torch.Tensor]) -> torch.Tensor:
         w1: Optional[torch.Tensor] = self.w1
         if w1 is None:
             assert self.w1_a is not None
@@ -305,7 +305,7 @@ class FullLayer(LoRALayerBase):
 
         self.rank = None  # unscaled
 
-    def get_weight(self, orig_weight: torch.Tensor) -> torch.Tensor:
+    def get_weight(self, orig_weight: Optional[torch.Tensor]) -> torch.Tensor:
         return self.weight
 
     def calc_size(self) -> int:
@@ -330,7 +330,7 @@ class IA3Layer(LoRALayerBase):
     def __init__(
         self,
         layer_key: str,
-            values: Dict[str, torch.Tensor],
+        values: Dict[str, torch.Tensor],
     ):
         super().__init__(layer_key, values)
 
@@ -339,10 +339,11 @@ class IA3Layer(LoRALayerBase):
 
         self.rank = None  # unscaled
 
-    def get_weight(self, orig_weight: torch.Tensor):
+    def get_weight(self, orig_weight: Optional[torch.Tensor]) -> torch.Tensor:
         weight = self.weight
         if not self.on_input:
             weight = weight.reshape(-1, 1)
+        assert orig_weight is not None
         return orig_weight * weight
 
     def calc_size(self) -> int:
@@ -361,8 +362,10 @@ class IA3Layer(LoRALayerBase):
         self.weight = self.weight.to(device=device, dtype=dtype)
         self.on_input = self.on_input.to(device=device, dtype=dtype)
 
+
 AnyLoRALayer = Union[LoRALayer, LoHALayer, LoKRLayer, FullLayer, IA3Layer]
-        
+
+
 # TODO: rename all methods used in model logic with Info postfix and remove here Raw postfix
 class LoRAModelRaw:  # (torch.nn.Module):
     _name: str
@@ -530,7 +533,7 @@ class LoRAModelRaw:  # (torch.nn.Module):
 
 # code from
 # https://github.com/bmaltais/kohya_ss/blob/2accb1305979ba62f5077a23aabac23b4c37e935/networks/lora_diffusers.py#L15C1-L97C32
-def make_sdxl_unet_conversion_map() -> List[Tuple[str,str]]:
+def make_sdxl_unet_conversion_map() -> List[Tuple[str, str]]:
     """Create a dict mapping state_dict keys from Stability AI SDXL format to diffusers SDXL format."""
     unet_conversion_map_layer = []
 
diff --git a/invokeai/backend/embeddings/model_patcher.py b/invokeai/backend/embeddings/model_patcher.py
new file mode 100644
index 0000000000..6d73235197
--- /dev/null
+++ b/invokeai/backend/embeddings/model_patcher.py
@@ -0,0 +1,586 @@
+# Copyright (c) 2024 Ryan Dick, Lincoln D. Stein, and the InvokeAI Development Team
+"""These classes implement model patching with LoRAs and Textual Inversions."""
+from __future__ import annotations
+
+import pickle
+from contextlib import contextmanager
+from pathlib import Path
+from typing import Any, Dict, Generator, List, Optional, Tuple, Union
+
+import numpy as np
+import torch
+from compel.embeddings_provider import BaseTextualInversionManager
+from diffusers import ModelMixin, OnnxRuntimeModel, UNet2DConditionModel
+from safetensors.torch import load_file
+from transformers import CLIPTextModel, CLIPTokenizer
+from typing_extensions import Self
+
+from invokeai.app.shared.models import FreeUConfig
+from invokeai.backend.model_manager.load.optimizations import skip_torch_weight_init
+from invokeai.backend.onnx.onnx_runtime import IAIOnnxRuntimeModel
+
+from .lora import LoRAModelRaw
+
+"""
+loras = [
+    (lora_model1, 0.7),
+    (lora_model2, 0.4),
+]
+with LoRAHelper.apply_lora_unet(unet, loras):
+    # unet with applied loras
+# unmodified unet
+
+"""
+
+
+# TODO: rename smth like ModelPatcher and add TI method?
+class ModelPatcher:
+    @staticmethod
+    def _resolve_lora_key(model: torch.nn.Module, lora_key: str, prefix: str) -> Tuple[str, torch.nn.Module]:
+        assert "." not in lora_key
+
+        if not lora_key.startswith(prefix):
+            raise Exception(f"lora_key with invalid prefix: {lora_key}, {prefix}")
+
+        module = model
+        module_key = ""
+        key_parts = lora_key[len(prefix) :].split("_")
+
+        submodule_name = key_parts.pop(0)
+
+        while len(key_parts) > 0:
+            try:
+                module = module.get_submodule(submodule_name)
+                module_key += "." + submodule_name
+                submodule_name = key_parts.pop(0)
+            except Exception:
+                submodule_name += "_" + key_parts.pop(0)
+
+        module = module.get_submodule(submodule_name)
+        module_key = (module_key + "." + submodule_name).lstrip(".")
+
+        return (module_key, module)
+
+    @classmethod
+    @contextmanager
+    def apply_lora_unet(
+        cls,
+        unet: UNet2DConditionModel,
+        loras: List[Tuple[LoRAModelRaw, float]],
+    ) -> Generator[None, None, None]:
+        with cls.apply_lora(unet, loras, "lora_unet_"):
+            yield
+
+    @classmethod
+    @contextmanager
+    def apply_lora_text_encoder(
+        cls,
+        text_encoder: CLIPTextModel,
+        loras: List[Tuple[LoRAModelRaw, float]],
+    ):
+        with cls.apply_lora(text_encoder, loras, "lora_te_"):
+            yield
+
+    @classmethod
+    @contextmanager
+    def apply_sdxl_lora_text_encoder(
+        cls,
+        text_encoder: CLIPTextModel,
+        loras: List[Tuple[LoRAModelRaw, float]],
+    ):
+        with cls.apply_lora(text_encoder, loras, "lora_te1_"):
+            yield
+
+    @classmethod
+    @contextmanager
+    def apply_sdxl_lora_text_encoder2(
+        cls,
+        text_encoder: CLIPTextModel,
+        loras: List[Tuple[LoRAModelRaw, float]],
+    ):
+        with cls.apply_lora(text_encoder, loras, "lora_te2_"):
+            yield
+
+    @classmethod
+    @contextmanager
+    def apply_lora(
+        cls,
+        model: Union[torch.nn.Module, ModelMixin, UNet2DConditionModel],
+        loras: List[Tuple[LoRAModelRaw, float]],
+        prefix: str,
+    ) -> Generator[None, None, None]:
+        original_weights = {}
+        try:
+            with torch.no_grad():
+                for lora, lora_weight in loras:
+                    # assert lora.device.type == "cpu"
+                    for layer_key, layer in lora.layers.items():
+                        if not layer_key.startswith(prefix):
+                            continue
+
+                        # TODO(ryand): A non-negligible amount of time is currently spent resolving LoRA keys. This
+                        # should be improved in the following ways:
+                        # 1. The key mapping could be more-efficiently pre-computed. This would save time every time a
+                        #    LoRA model is applied.
+                        # 2. From an API perspective, there's no reason that the `ModelPatcher` should be aware of the
+                        #    intricacies of Stable Diffusion key resolution. It should just expect the input LoRA
+                        #    weights to have valid keys.
+                        module_key, module = cls._resolve_lora_key(model, layer_key, prefix)
+
+                        # All of the LoRA weight calculations will be done on the same device as the module weight.
+                        # (Performance will be best if this is a CUDA device.)
+                        device = module.weight.device
+                        dtype = module.weight.dtype
+
+                        if module_key not in original_weights:
+                            original_weights[module_key] = module.weight.detach().to(device="cpu", copy=True)
+
+                        layer_scale = layer.alpha / layer.rank if (layer.alpha and layer.rank) else 1.0
+
+                        # We intentionally move to the target device first, then cast. Experimentally, this was found to
+                        # be significantly faster for 16-bit CPU tensors being moved to a CUDA device than doing the
+                        # same thing in a single call to '.to(...)'.
+                        layer.to(device=device)
+                        layer.to(dtype=torch.float32)
+                        # TODO(ryand): Using torch.autocast(...) over explicit casting may offer a speed benefit on CUDA
+                        # devices here. Experimentally, it was found to be very slow on CPU. More investigation needed.
+                        layer_weight = layer.get_weight(module.weight) * (lora_weight * layer_scale)
+                        layer.to(device=torch.device("cpu"))
+
+                        assert isinstance(layer_weight, torch.Tensor)  # mypy thinks layer_weight is a float|Any ??!
+                        if module.weight.shape != layer_weight.shape:
+                            # TODO: debug on lycoris
+                            assert hasattr(layer_weight, "reshape")
+                            layer_weight = layer_weight.reshape(module.weight.shape)
+
+                        assert isinstance(layer_weight, torch.Tensor)  # mypy thinks layer_weight is a float|Any ??!
+                        module.weight += layer_weight.to(dtype=dtype)
+
+            yield  # wait for context manager exit
+
+        finally:
+            assert hasattr(model, "get_submodule")  # mypy not picking up fact that torch.nn.Module has get_submodule()
+            with torch.no_grad():
+                for module_key, weight in original_weights.items():
+                    model.get_submodule(module_key).weight.copy_(weight)
+
+    @classmethod
+    @contextmanager
+    def apply_ti(
+        cls,
+        tokenizer: CLIPTokenizer,
+        text_encoder: CLIPTextModel,
+        ti_list: List[Tuple[str, TextualInversionModel]],
+    ) -> Generator[Tuple[CLIPTokenizer, TextualInversionManager], None, None]:
+        init_tokens_count = None
+        new_tokens_added = None
+
+        # TODO: This is required since Transformers 4.32 see
+        # https://github.com/huggingface/transformers/pull/25088
+        # More information by NVIDIA:
+        # https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
+        # This value might need to be changed in the future and take the GPUs model into account as there seem
+        # to be ideal values for different GPUS. This value is temporary!
+        # For references to the current discussion please see https://github.com/invoke-ai/InvokeAI/pull/4817
+        pad_to_multiple_of = 8
+
+        try:
+            # HACK: The CLIPTokenizer API does not include a way to remove tokens after calling add_tokens(...). As a
+            # workaround, we create a full copy of `tokenizer` so that its original behavior can be restored after
+            # exiting this `apply_ti(...)` context manager.
+            #
+            # In a previous implementation, the deep copy was obtained with `ti_tokenizer = copy.deepcopy(tokenizer)`,
+            # but a pickle roundtrip was found to be much faster (1 sec vs. 0.05 secs).
+            ti_tokenizer = pickle.loads(pickle.dumps(tokenizer))
+            ti_manager = TextualInversionManager(ti_tokenizer)
+            init_tokens_count = text_encoder.resize_token_embeddings(None, pad_to_multiple_of).num_embeddings
+
+            def _get_trigger(ti_name: str, index: int) -> str:
+                trigger = ti_name
+                if index > 0:
+                    trigger += f"-!pad-{i}"
+                return f"<{trigger}>"
+
+            def _get_ti_embedding(model_embeddings: torch.nn.Module, ti: TextualInversionModel) -> torch.Tensor:
+                # for SDXL models, select the embedding that matches the text encoder's dimensions
+                if ti.embedding_2 is not None:
+                    return (
+                        ti.embedding_2
+                        if ti.embedding_2.shape[1] == model_embeddings.weight.data[0].shape[0]
+                        else ti.embedding
+                    )
+                else:
+                    return ti.embedding
+
+            # modify tokenizer
+            new_tokens_added = 0
+            for ti_name, ti in ti_list:
+                ti_embedding = _get_ti_embedding(text_encoder.get_input_embeddings(), ti)
+
+                for i in range(ti_embedding.shape[0]):
+                    new_tokens_added += ti_tokenizer.add_tokens(_get_trigger(ti_name, i))
+
+            # Modify text_encoder.
+            # resize_token_embeddings(...) constructs a new torch.nn.Embedding internally. Initializing the weights of
+            # this embedding is slow and unnecessary, so we wrap this step in skip_torch_weight_init() to save some
+            # time.
+            with skip_torch_weight_init():
+                text_encoder.resize_token_embeddings(init_tokens_count + new_tokens_added, pad_to_multiple_of)
+            model_embeddings = text_encoder.get_input_embeddings()
+
+            for ti_name, ti in ti_list:
+                ti_embedding = _get_ti_embedding(text_encoder.get_input_embeddings(), ti)
+
+                ti_tokens = []
+                for i in range(ti_embedding.shape[0]):
+                    embedding = ti_embedding[i]
+                    trigger = _get_trigger(ti_name, i)
+
+                    token_id = ti_tokenizer.convert_tokens_to_ids(trigger)
+                    if token_id == ti_tokenizer.unk_token_id:
+                        raise RuntimeError(f"Unable to find token id for token '{trigger}'")
+
+                    if model_embeddings.weight.data[token_id].shape != embedding.shape:
+                        raise ValueError(
+                            f"Cannot load embedding for {trigger}. It was trained on a model with token dimension"
+                            f" {embedding.shape[0]}, but the current model has token dimension"
+                            f" {model_embeddings.weight.data[token_id].shape[0]}."
+                        )
+
+                    model_embeddings.weight.data[token_id] = embedding.to(
+                        device=text_encoder.device, dtype=text_encoder.dtype
+                    )
+                    ti_tokens.append(token_id)
+
+                if len(ti_tokens) > 1:
+                    ti_manager.pad_tokens[ti_tokens[0]] = ti_tokens[1:]
+
+            yield ti_tokenizer, ti_manager
+
+        finally:
+            if init_tokens_count and new_tokens_added:
+                text_encoder.resize_token_embeddings(init_tokens_count, pad_to_multiple_of)
+
+    @classmethod
+    @contextmanager
+    def apply_clip_skip(
+        cls,
+        text_encoder: CLIPTextModel,
+        clip_skip: int,
+    ) -> Generator[None, None, None]:
+        skipped_layers = []
+        try:
+            for _i in range(clip_skip):
+                skipped_layers.append(text_encoder.text_model.encoder.layers.pop(-1))
+
+            yield
+
+        finally:
+            while len(skipped_layers) > 0:
+                text_encoder.text_model.encoder.layers.append(skipped_layers.pop())
+
+    @classmethod
+    @contextmanager
+    def apply_freeu(
+        cls,
+        unet: UNet2DConditionModel,
+        freeu_config: Optional[FreeUConfig] = None,
+    ) -> Generator[None, None, None]:
+        did_apply_freeu = False
+        try:
+            assert hasattr(unet, "enable_freeu")  # mypy doesn't pick up this attribute?
+            if freeu_config is not None:
+                unet.enable_freeu(b1=freeu_config.b1, b2=freeu_config.b2, s1=freeu_config.s1, s2=freeu_config.s2)
+                did_apply_freeu = True
+
+            yield
+
+        finally:
+            assert hasattr(unet, "disable_freeu")  # mypy doesn't pick up this attribute?
+            if did_apply_freeu:
+                unet.disable_freeu()
+
+
+class TextualInversionModel:
+    embedding: torch.Tensor  # [n, 768]|[n, 1280]
+    embedding_2: Optional[torch.Tensor] = None  # [n, 768]|[n, 1280]   - for SDXL models
+
+    @classmethod
+    def from_checkpoint(
+        cls,
+        file_path: Union[str, Path],
+        device: Optional[torch.device] = None,
+        dtype: Optional[torch.dtype] = None,
+    ) -> Self:
+        if not isinstance(file_path, Path):
+            file_path = Path(file_path)
+
+        result = cls()  # TODO:
+
+        if file_path.suffix == ".safetensors":
+            state_dict = load_file(file_path.absolute().as_posix(), device="cpu")
+        else:
+            state_dict = torch.load(file_path, map_location="cpu")
+
+        # both v1 and v2 format embeddings
+        # difference mostly in metadata
+        if "string_to_param" in state_dict:
+            if len(state_dict["string_to_param"]) > 1:
+                print(
+                    f'Warn: Embedding "{file_path.name}" contains multiple tokens, which is not supported. The first',
+                    " token will be used.",
+                )
+
+            result.embedding = next(iter(state_dict["string_to_param"].values()))
+
+        # v3 (easynegative)
+        elif "emb_params" in state_dict:
+            result.embedding = state_dict["emb_params"]
+
+        # v5(sdxl safetensors file)
+        elif "clip_g" in state_dict and "clip_l" in state_dict:
+            result.embedding = state_dict["clip_g"]
+            result.embedding_2 = state_dict["clip_l"]
+
+        # v4(diffusers bin files)
+        else:
+            result.embedding = next(iter(state_dict.values()))
+
+            if len(result.embedding.shape) == 1:
+                result.embedding = result.embedding.unsqueeze(0)
+
+            if not isinstance(result.embedding, torch.Tensor):
+                raise ValueError(f"Invalid embeddings file: {file_path.name}")
+
+        return result
+
+
+# no type hints for BaseTextualInversionManager?
+class TextualInversionManager(BaseTextualInversionManager):  # type: ignore
+    pad_tokens: Dict[int, List[int]]
+    tokenizer: CLIPTokenizer
+
+    def __init__(self, tokenizer: CLIPTokenizer):
+        self.pad_tokens = {}
+        self.tokenizer = tokenizer
+
+    def expand_textual_inversion_token_ids_if_necessary(self, token_ids: list[int]) -> list[int]:
+        if len(self.pad_tokens) == 0:
+            return token_ids
+
+        if token_ids[0] == self.tokenizer.bos_token_id:
+            raise ValueError("token_ids must not start with bos_token_id")
+        if token_ids[-1] == self.tokenizer.eos_token_id:
+            raise ValueError("token_ids must not end with eos_token_id")
+
+        new_token_ids = []
+        for token_id in token_ids:
+            new_token_ids.append(token_id)
+            if token_id in self.pad_tokens:
+                new_token_ids.extend(self.pad_tokens[token_id])
+
+        # Do not exceed the max model input size
+        # The -2 here is compensating for compensate compel.embeddings_provider.get_token_ids(),
+        # which first removes and then adds back the start and end tokens.
+        max_length = list(self.tokenizer.max_model_input_sizes.values())[0] - 2
+        if len(new_token_ids) > max_length:
+            new_token_ids = new_token_ids[0:max_length]
+
+        return new_token_ids
+
+
+class ONNXModelPatcher:
+    @classmethod
+    @contextmanager
+    def apply_lora_unet(
+        cls,
+        unet: OnnxRuntimeModel,
+        loras: List[Tuple[LoRAModelRaw, float]],
+    ) -> Generator[None, None, None]:
+        with cls.apply_lora(unet, loras, "lora_unet_"):
+            yield
+
+    @classmethod
+    @contextmanager
+    def apply_lora_text_encoder(
+        cls,
+        text_encoder: OnnxRuntimeModel,
+        loras: List[Tuple[LoRAModelRaw, float]],
+    ) -> Generator[None, None, None]:
+        with cls.apply_lora(text_encoder, loras, "lora_te_"):
+            yield
+
+    # based on
+    # https://github.com/ssube/onnx-web/blob/ca2e436f0623e18b4cfe8a0363fcfcf10508acf7/api/onnx_web/convert/diffusion/lora.py#L323
+    @classmethod
+    @contextmanager
+    def apply_lora(
+        cls,
+        model: IAIOnnxRuntimeModel,
+        loras: List[Tuple[LoRAModelRaw, float]],
+        prefix: str,
+    ) -> Generator[None, None, None]:
+        from .models.base import IAIOnnxRuntimeModel
+
+        if not isinstance(model, IAIOnnxRuntimeModel):
+            raise Exception("Only IAIOnnxRuntimeModel models supported")
+
+        orig_weights = {}
+
+        try:
+            blended_loras: Dict[str, torch.Tensor] = {}
+
+            for lora, lora_weight in loras:
+                for layer_key, layer in lora.layers.items():
+                    if not layer_key.startswith(prefix):
+                        continue
+
+                    layer.to(dtype=torch.float32)
+                    layer_key = layer_key.replace(prefix, "")
+                    # TODO: rewrite to pass original tensor weight(required by ia3)
+                    layer_weight = layer.get_weight(None).detach().cpu().numpy() * lora_weight
+                    if layer_key in blended_loras:
+                        blended_loras[layer_key] += layer_weight
+                    else:
+                        blended_loras[layer_key] = layer_weight
+
+            node_names = {}
+            for node in model.nodes.values():
+                node_names[node.name.replace("/", "_").replace(".", "_").lstrip("_")] = node.name
+
+            for layer_key, lora_weight in blended_loras.items():
+                conv_key = layer_key + "_Conv"
+                gemm_key = layer_key + "_Gemm"
+                matmul_key = layer_key + "_MatMul"
+
+                if conv_key in node_names or gemm_key in node_names:
+                    if conv_key in node_names:
+                        conv_node = model.nodes[node_names[conv_key]]
+                    else:
+                        conv_node = model.nodes[node_names[gemm_key]]
+
+                    weight_name = [n for n in conv_node.input if ".weight" in n][0]
+                    orig_weight = model.tensors[weight_name]
+
+                    if orig_weight.shape[-2:] == (1, 1):
+                        if lora_weight.shape[-2:] == (1, 1):
+                            new_weight = orig_weight.squeeze((3, 2)) + lora_weight.squeeze((3, 2))
+                        else:
+                            new_weight = orig_weight.squeeze((3, 2)) + lora_weight
+
+                        new_weight = np.expand_dims(new_weight, (2, 3))
+                    else:
+                        if orig_weight.shape != lora_weight.shape:
+                            new_weight = orig_weight + lora_weight.reshape(orig_weight.shape)
+                        else:
+                            new_weight = orig_weight + lora_weight
+
+                    orig_weights[weight_name] = orig_weight
+                    model.tensors[weight_name] = new_weight.astype(orig_weight.dtype)
+
+                elif matmul_key in node_names:
+                    weight_node = model.nodes[node_names[matmul_key]]
+                    matmul_name = [n for n in weight_node.input if "MatMul" in n][0]
+
+                    orig_weight = model.tensors[matmul_name]
+                    new_weight = orig_weight + lora_weight.transpose()
+
+                    orig_weights[matmul_name] = orig_weight
+                    model.tensors[matmul_name] = new_weight.astype(orig_weight.dtype)
+
+                else:
+                    # warn? err?
+                    pass
+
+            yield
+
+        finally:
+            # restore original weights
+            for name, orig_weight in orig_weights.items():
+                model.tensors[name] = orig_weight
+
+    @classmethod
+    @contextmanager
+    def apply_ti(
+        cls,
+        tokenizer: CLIPTokenizer,
+        text_encoder: IAIOnnxRuntimeModel,
+        ti_list: List[Tuple[str, Any]],
+    ) -> Generator[Tuple[CLIPTokenizer, TextualInversionManager], None, None]:
+        from .models.base import IAIOnnxRuntimeModel
+
+        if not isinstance(text_encoder, IAIOnnxRuntimeModel):
+            raise Exception("Only IAIOnnxRuntimeModel models supported")
+
+        orig_embeddings = None
+
+        try:
+            # HACK: The CLIPTokenizer API does not include a way to remove tokens after calling add_tokens(...). As a
+            # workaround, we create a full copy of `tokenizer` so that its original behavior can be restored after
+            # exiting this `apply_ti(...)` context manager.
+            #
+            # In a previous implementation, the deep copy was obtained with `ti_tokenizer = copy.deepcopy(tokenizer)`,
+            # but a pickle roundtrip was found to be much faster (1 sec vs. 0.05 secs).
+            ti_tokenizer = pickle.loads(pickle.dumps(tokenizer))
+            ti_manager = TextualInversionManager(ti_tokenizer)
+
+            def _get_trigger(ti_name: str, index: int) -> str:
+                trigger = ti_name
+                if index > 0:
+                    trigger += f"-!pad-{i}"
+                return f"<{trigger}>"
+
+            # modify text_encoder
+            orig_embeddings = text_encoder.tensors["text_model.embeddings.token_embedding.weight"]
+
+            # modify tokenizer
+            new_tokens_added = 0
+            for ti_name, ti in ti_list:
+                if ti.embedding_2 is not None:
+                    ti_embedding = (
+                        ti.embedding_2 if ti.embedding_2.shape[1] == orig_embeddings.shape[0] else ti.embedding
+                    )
+                else:
+                    ti_embedding = ti.embedding
+
+                for i in range(ti_embedding.shape[0]):
+                    new_tokens_added += ti_tokenizer.add_tokens(_get_trigger(ti_name, i))
+
+            embeddings = np.concatenate(
+                (np.copy(orig_embeddings), np.zeros((new_tokens_added, orig_embeddings.shape[1]))),
+                axis=0,
+            )
+
+            for ti_name, _ in ti_list:
+                ti_tokens = []
+                for i in range(ti_embedding.shape[0]):
+                    embedding = ti_embedding[i].detach().numpy()
+                    trigger = _get_trigger(ti_name, i)
+
+                    token_id = ti_tokenizer.convert_tokens_to_ids(trigger)
+                    if token_id == ti_tokenizer.unk_token_id:
+                        raise RuntimeError(f"Unable to find token id for token '{trigger}'")
+
+                    if embeddings[token_id].shape != embedding.shape:
+                        raise ValueError(
+                            f"Cannot load embedding for {trigger}. It was trained on a model with token dimension"
+                            f" {embedding.shape[0]}, but the current model has token dimension"
+                            f" {embeddings[token_id].shape[0]}."
+                        )
+
+                    embeddings[token_id] = embedding
+                    ti_tokens.append(token_id)
+
+                if len(ti_tokens) > 1:
+                    ti_manager.pad_tokens[ti_tokens[0]] = ti_tokens[1:]
+
+            text_encoder.tensors["text_model.embeddings.token_embedding.weight"] = embeddings.astype(
+                orig_embeddings.dtype
+            )
+
+            yield ti_tokenizer, ti_manager
+
+        finally:
+            # restore
+            if orig_embeddings is not None:
+                text_encoder.tensors["text_model.embeddings.token_embedding.weight"] = orig_embeddings
diff --git a/invokeai/backend/model_management/lora.py b/invokeai/backend/model_management/lora.py
index d72f55794d..aed5eb60d5 100644
--- a/invokeai/backend/model_management/lora.py
+++ b/invokeai/backend/model_management/lora.py
@@ -102,7 +102,7 @@ class ModelPatcher:
     def apply_lora(
         cls,
         model: torch.nn.Module,
-        loras: List[Tuple[LoRAModel, float]],
+        loras: List[Tuple[LoRAModel, float]],  # THIS IS INCORRECT. IT IS ACTUALLY A LoRAModelRaw
         prefix: str,
     ):
         original_weights = {}
@@ -194,6 +194,8 @@ class ModelPatcher:
                 return f"<{trigger}>"
 
             def _get_ti_embedding(model_embeddings, ti):
+                print(f"DEBUG: model_embeddings={type(model_embeddings)}, ti={type(ti)}")
+                print(f"DEBUG: is it an nn.Module? {isinstance(model_embeddings, torch.nn.Module)}")
                 # for SDXL models, select the embedding that matches the text encoder's dimensions
                 if ti.embedding_2 is not None:
                     return (
@@ -202,6 +204,7 @@ class ModelPatcher:
                         else ti.embedding
                     )
                 else:
+                    print(f"DEBUG: ti.embedding={type(ti.embedding)}")
                     return ti.embedding
 
             # modify tokenizer
diff --git a/invokeai/backend/model_manager/config.py b/invokeai/backend/model_manager/config.py
index e59a84d729..4488f8eafc 100644
--- a/invokeai/backend/model_manager/config.py
+++ b/invokeai/backend/model_manager/config.py
@@ -28,9 +28,11 @@ from diffusers import ModelMixin
 from pydantic import BaseModel, ConfigDict, Field, TypeAdapter
 from typing_extensions import Annotated, Any, Dict
 
-from .onnx_runtime import IAIOnnxRuntimeModel
+from invokeai.backend.onnx.onnx_runtime import IAIOnnxRuntimeModel
+
 from ..ip_adapter.ip_adapter import IPAdapter, IPAdapterPlus
 
+
 class InvalidModelConfigException(Exception):
     """Exception for when config parser doesn't recognized this combination of model type and format."""
 
diff --git a/invokeai/backend/model_manager/load/load_default.py b/invokeai/backend/model_manager/load/load_default.py
index 453283e9b4..adc84d2051 100644
--- a/invokeai/backend/model_manager/load/load_default.py
+++ b/invokeai/backend/model_manager/load/load_default.py
@@ -10,11 +10,17 @@ from diffusers import ModelMixin
 from diffusers.configuration_utils import ConfigMixin
 
 from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.backend.model_manager import AnyModel, AnyModelConfig, InvalidModelConfigException, ModelRepoVariant, SubModelType
+from invokeai.backend.model_manager import (
+    AnyModel,
+    AnyModelConfig,
+    InvalidModelConfigException,
+    ModelRepoVariant,
+    SubModelType,
+)
 from invokeai.backend.model_manager.load.convert_cache import ModelConvertCacheBase
 from invokeai.backend.model_manager.load.load_base import LoadedModel, ModelLoaderBase
 from invokeai.backend.model_manager.load.model_cache.model_cache_base import ModelCacheBase, ModelLockerBase
-from invokeai.backend.model_manager.load.model_util import calc_model_size_by_fs, calc_model_size_by_data
+from invokeai.backend.model_manager.load.model_util import calc_model_size_by_data, calc_model_size_by_fs
 from invokeai.backend.model_manager.load.optimizations import skip_torch_weight_init
 from invokeai.backend.util.devices import choose_torch_device, torch_dtype
 
@@ -160,4 +166,3 @@ class ModelLoader(ModelLoaderBase):
         submodel_type: Optional[SubModelType] = None,
     ) -> AnyModel:
         raise NotImplementedError
-
diff --git a/invokeai/backend/model_manager/load/memory_snapshot.py b/invokeai/backend/model_manager/load/memory_snapshot.py
index 295be0c551..346f5dc424 100644
--- a/invokeai/backend/model_manager/load/memory_snapshot.py
+++ b/invokeai/backend/model_manager/load/memory_snapshot.py
@@ -97,4 +97,4 @@ def get_pretty_snapshot_diff(snapshot_1: Optional[MemorySnapshot], snapshot_2: O
     if snapshot_1.vram is not None and snapshot_2.vram is not None:
         msg += get_msg_line("VRAM", snapshot_1.vram, snapshot_2.vram)
 
-    return "\n"+msg if len(msg)>0 else msg
+    return "\n" + msg if len(msg) > 0 else msg
diff --git a/invokeai/backend/model_manager/load/model_cache/__init__.py b/invokeai/backend/model_manager/load/model_cache/__init__.py
index 50cafa3769..6c87e2519e 100644
--- a/invokeai/backend/model_manager/load/model_cache/__init__.py
+++ b/invokeai/backend/model_manager/load/model_cache/__init__.py
@@ -1,5 +1,3 @@
 """Init file for RamCache."""
 
-from .model_cache_base import ModelCacheBase
-from .model_cache_default import ModelCache
 _all__ = ["ModelCacheBase", "ModelCache"]
diff --git a/invokeai/backend/model_manager/load/model_loaders/controlnet.py b/invokeai/backend/model_manager/load/model_loaders/controlnet.py
index 8e6a80ceb2..e61e2b46a6 100644
--- a/invokeai/backend/model_manager/load/model_loaders/controlnet.py
+++ b/invokeai/backend/model_manager/load/model_loaders/controlnet.py
@@ -14,8 +14,10 @@ from invokeai.backend.model_manager import (
 )
 from invokeai.backend.model_manager.convert_ckpt_to_diffusers import convert_controlnet_to_diffusers
 from invokeai.backend.model_manager.load.load_base import AnyModelLoader
+
 from .generic_diffusers import GenericDiffusersLoader
 
+
 @AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.ControlNet, format=ModelFormat.Diffusers)
 @AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.ControlNet, format=ModelFormat.Checkpoint)
 class ControlnetLoader(GenericDiffusersLoader):
@@ -37,7 +39,7 @@ class ControlnetLoader(GenericDiffusersLoader):
         if config.base not in {BaseModelType.StableDiffusion1, BaseModelType.StableDiffusion2}:
             raise Exception(f"Vae conversion not supported for model type: {config.base}")
         else:
-            assert hasattr(config, 'config')
+            assert hasattr(config, "config")
             config_file = config.config
 
         if weights_path.suffix == ".safetensors":
diff --git a/invokeai/backend/model_manager/load/model_loaders/generic_diffusers.py b/invokeai/backend/model_manager/load/model_loaders/generic_diffusers.py
index f92a9048c5..03c26f3a0c 100644
--- a/invokeai/backend/model_manager/load/model_loaders/generic_diffusers.py
+++ b/invokeai/backend/model_manager/load/model_loaders/generic_diffusers.py
@@ -15,6 +15,7 @@ from invokeai.backend.model_manager import (
 from invokeai.backend.model_manager.load.load_base import AnyModelLoader
 from invokeai.backend.model_manager.load.load_default import ModelLoader
 
+
 @AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.CLIPVision, format=ModelFormat.Diffusers)
 @AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.T2IAdapter, format=ModelFormat.Diffusers)
 class GenericDiffusersLoader(ModelLoader):
diff --git a/invokeai/backend/model_manager/load/model_loaders/ip_adapter.py b/invokeai/backend/model_manager/load/model_loaders/ip_adapter.py
index 63dc3790f1..27ced41c1e 100644
--- a/invokeai/backend/model_manager/load/model_loaders/ip_adapter.py
+++ b/invokeai/backend/model_manager/load/model_loaders/ip_adapter.py
@@ -1,11 +1,11 @@
 # Copyright (c) 2024, Lincoln D. Stein and the InvokeAI Development Team
 """Class for IP Adapter model loading in InvokeAI."""
 
-import torch
-
 from pathlib import Path
 from typing import Optional
 
+import torch
+
 from invokeai.backend.ip_adapter.ip_adapter import build_ip_adapter
 from invokeai.backend.model_manager import (
     AnyModel,
@@ -18,6 +18,7 @@ from invokeai.backend.model_manager import (
 from invokeai.backend.model_manager.load.load_base import AnyModelLoader
 from invokeai.backend.model_manager.load.load_default import ModelLoader
 
+
 @AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.IPAdapter, format=ModelFormat.InvokeAI)
 class IPAdapterInvokeAILoader(ModelLoader):
     """Class to load IP Adapter diffusers models."""
@@ -36,4 +37,3 @@ class IPAdapterInvokeAILoader(ModelLoader):
             dtype=self._torch_dtype,
         )
         return model
-
diff --git a/invokeai/backend/model_manager/load/model_loaders/lora.py b/invokeai/backend/model_manager/load/model_loaders/lora.py
index 4d19aadb7d..d8e5f920e2 100644
--- a/invokeai/backend/model_manager/load/model_loaders/lora.py
+++ b/invokeai/backend/model_manager/load/model_loaders/lora.py
@@ -2,13 +2,12 @@
 """Class for LoRA model loading in InvokeAI."""
 
 
+from logging import Logger
 from pathlib import Path
 from typing import Optional, Tuple
-from logging import Logger
 
-from invokeai.backend.model_manager.load.model_cache.model_cache_base import ModelCacheBase
-from invokeai.backend.model_manager.load.convert_cache import ModelConvertCacheBase
 from invokeai.app.services.config import InvokeAIAppConfig
+from invokeai.backend.embeddings.lora import LoRAModelRaw
 from invokeai.backend.model_manager import (
     AnyModel,
     AnyModelConfig,
@@ -18,9 +17,11 @@ from invokeai.backend.model_manager import (
     ModelType,
     SubModelType,
 )
-from invokeai.backend.model_manager.lora import LoRAModelRaw
+from invokeai.backend.model_manager.load.convert_cache import ModelConvertCacheBase
 from invokeai.backend.model_manager.load.load_base import AnyModelLoader
 from invokeai.backend.model_manager.load.load_default import ModelLoader
+from invokeai.backend.model_manager.load.model_cache.model_cache_base import ModelCacheBase
+
 
 @AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.Lora, format=ModelFormat.Diffusers)
 @AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.Lora, format=ModelFormat.Lycoris)
@@ -47,6 +48,7 @@ class LoraLoader(ModelLoader):
     ) -> AnyModel:
         if submodel_type is not None:
             raise ValueError("There are no submodels in a LoRA model.")
+        assert self._model_base is not None
         model = LoRAModelRaw.from_checkpoint(
             file_path=model_path,
             dtype=self._torch_dtype,
@@ -56,9 +58,11 @@ class LoraLoader(ModelLoader):
 
     # override
     def _get_model_path(
-            self, config: AnyModelConfig, submodel_type: Optional[SubModelType] = None
+        self, config: AnyModelConfig, submodel_type: Optional[SubModelType] = None
     ) -> Tuple[Path, AnyModelConfig, Optional[SubModelType]]:
-        self._model_base = config.base  # cheating a little - setting this variable for later call to _load_model()
+        self._model_base = (
+            config.base
+        )  # cheating a little - we remember this variable for using in the subsequent call to _load_model()
 
         model_base_path = self._app_config.models_path
         model_path = model_base_path / config.path
@@ -72,5 +76,3 @@ class LoraLoader(ModelLoader):
 
         result = model_path.resolve(), config, submodel_type
         return result
-
-
diff --git a/invokeai/backend/model_manager/load/model_loaders/textual_inversion.py b/invokeai/backend/model_manager/load/model_loaders/textual_inversion.py
new file mode 100644
index 0000000000..394fddc75d
--- /dev/null
+++ b/invokeai/backend/model_manager/load/model_loaders/textual_inversion.py
@@ -0,0 +1,55 @@
+# Copyright (c) 2024, Lincoln D. Stein and the InvokeAI Development Team
+"""Class for TI model loading in InvokeAI."""
+
+
+from pathlib import Path
+from typing import Optional, Tuple
+
+from invokeai.backend.embeddings.model_patcher import TextualInversionModel as TextualInversionModelRaw
+from invokeai.backend.model_manager import (
+    AnyModel,
+    AnyModelConfig,
+    BaseModelType,
+    ModelFormat,
+    ModelRepoVariant,
+    ModelType,
+    SubModelType,
+)
+from invokeai.backend.model_manager.load.load_base import AnyModelLoader
+from invokeai.backend.model_manager.load.load_default import ModelLoader
+
+
+@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.TextualInversion, format=ModelFormat.EmbeddingFile)
+@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.TextualInversion, format=ModelFormat.EmbeddingFolder)
+class TextualInversionLoader(ModelLoader):
+    """Class to load TI models."""
+
+    def _load_model(
+        self,
+        model_path: Path,
+        model_variant: Optional[ModelRepoVariant] = None,
+        submodel_type: Optional[SubModelType] = None,
+    ) -> AnyModel:
+        if submodel_type is not None:
+            raise ValueError("There are no submodels in a TI model.")
+        model = TextualInversionModelRaw.from_checkpoint(
+            file_path=model_path,
+            dtype=self._torch_dtype,
+        )
+        return model
+
+    # override
+    def _get_model_path(
+        self, config: AnyModelConfig, submodel_type: Optional[SubModelType] = None
+    ) -> Tuple[Path, AnyModelConfig, Optional[SubModelType]]:
+        model_path = self._app_config.models_path / config.path
+
+        if config.format == ModelFormat.EmbeddingFolder:
+            path = model_path / "learned_embeds.bin"
+        else:
+            path = model_path
+
+        if not path.exists():
+            raise OSError(f"The embedding file at {path} was not found")
+
+        return path, config, submodel_type
diff --git a/invokeai/backend/model_manager/load/model_loaders/vae.py b/invokeai/backend/model_manager/load/model_loaders/vae.py
index 7a35e53459..882ae05577 100644
--- a/invokeai/backend/model_manager/load/model_loaders/vae.py
+++ b/invokeai/backend/model_manager/load/model_loaders/vae.py
@@ -15,6 +15,7 @@ from invokeai.backend.model_manager import (
 )
 from invokeai.backend.model_manager.convert_ckpt_to_diffusers import convert_ldm_vae_to_diffusers
 from invokeai.backend.model_manager.load.load_base import AnyModelLoader
+
 from .generic_diffusers import GenericDiffusersLoader
 
 
diff --git a/invokeai/backend/model_manager/load/model_util.py b/invokeai/backend/model_manager/load/model_util.py
index 404c88bbbc..3f2d22595e 100644
--- a/invokeai/backend/model_manager/load/model_util.py
+++ b/invokeai/backend/model_manager/load/model_util.py
@@ -3,13 +3,13 @@
 
 import json
 from pathlib import Path
-from typing import Optional, Union
+from typing import Optional
 
 import torch
 from diffusers import DiffusionPipeline
 
 from invokeai.backend.model_manager.config import AnyModel
-from invokeai.backend.model_manager.onnx_runtime import IAIOnnxRuntimeModel
+from invokeai.backend.onnx.onnx_runtime import IAIOnnxRuntimeModel
 
 
 def calc_model_size_by_data(model: AnyModel) -> int:
diff --git a/invokeai/backend/model_manager/onnx_runtime.py b/invokeai/backend/onnx/onnx_runtime.py
similarity index 100%
rename from invokeai/backend/model_manager/onnx_runtime.py
rename to invokeai/backend/onnx/onnx_runtime.py

From 5745ce9c7db13aa50c09b9a0c3901456616aaf13 Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lstein@gmail.com>
Date: Mon, 5 Feb 2024 21:55:11 -0500
Subject: [PATCH 115/411] Multiple refinements on loaders:

- Cache stat collection enabled.
- Implemented ONNX loading.
- Add ability to specify the repo version variant in installer CLI.
- If caller asks for a repo version that doesn't exist, will fall back
  to empty version rather than raising an error.
---
 .../model_install/model_install_default.py    |  6 +--
 invokeai/backend/install/install_helper.py    | 18 ++++++--
 invokeai/backend/model_manager/config.py      | 14 ++++++-
 .../backend/model_manager/load/__init__.py    |  1 -
 .../backend/model_manager/load/load_base.py   |  4 +-
 .../model_manager/load/load_default.py        | 32 ++++++++++----
 .../load/model_cache/__init__.py              |  3 +-
 .../load/model_cache/model_cache_base.py      | 10 ++++-
 .../load/model_cache/model_cache_default.py   | 42 +++++++++++++++++--
 .../model_manager/load/model_loaders/onnx.py  | 41 ++++++++++++++++++
 .../model_manager/metadata/fetch/civitai.py   |  7 +++-
 .../metadata/fetch/fetch_base.py              |  7 +++-
 .../metadata/fetch/huggingface.py             | 26 ++++++++----
 .../model_manager/metadata/metadata_base.py   |  1 -
 invokeai/backend/model_manager/probe.py       | 16 +++++--
 .../model_manager/util/select_hf_files.py     | 14 +++++--
 invokeai/backend/util/devices.py              | 20 ++++++---
 invokeai/frontend/install/model_install2.py   |  2 +-
 18 files changed, 215 insertions(+), 49 deletions(-)
 create mode 100644 invokeai/backend/model_manager/load/model_loaders/onnx.py

diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py
index 1c188b300d..d32af4a513 100644
--- a/invokeai/app/services/model_install/model_install_default.py
+++ b/invokeai/app/services/model_install/model_install_default.py
@@ -495,10 +495,10 @@ class ModelInstallService(ModelInstallServiceBase):
         return id
 
     @staticmethod
-    def _guess_variant() -> ModelRepoVariant:
+    def _guess_variant() -> Optional[ModelRepoVariant]:
         """Guess the best HuggingFace variant type to download."""
         precision = choose_precision(choose_torch_device())
-        return ModelRepoVariant.FP16 if precision == "float16" else ModelRepoVariant.DEFAULT
+        return ModelRepoVariant.FP16 if precision == "float16" else None
 
     def _import_local_model(self, source: LocalModelSource, config: Optional[Dict[str, Any]]) -> ModelInstallJob:
         return ModelInstallJob(
@@ -523,7 +523,7 @@ class ModelInstallService(ModelInstallServiceBase):
         if not source.access_token:
             self._logger.info("No HuggingFace access token present; some models may not be downloadable.")
 
-        metadata = HuggingFaceMetadataFetch(self._session).from_id(source.repo_id)
+        metadata = HuggingFaceMetadataFetch(self._session).from_id(source.repo_id, source.variant)
         assert isinstance(metadata, ModelMetadataWithFiles)
         remote_files = metadata.download_urls(
             variant=source.variant or self._guess_variant(),
diff --git a/invokeai/backend/install/install_helper.py b/invokeai/backend/install/install_helper.py
index 9f219132d4..57dfadcaea 100644
--- a/invokeai/backend/install/install_helper.py
+++ b/invokeai/backend/install/install_helper.py
@@ -30,6 +30,7 @@ from invokeai.app.services.shared.sqlite.sqlite_util import init_db
 from invokeai.backend.model_manager import (
     BaseModelType,
     InvalidModelConfigException,
+    ModelRepoVariant,
     ModelType,
 )
 from invokeai.backend.model_manager.metadata import UnknownMetadataException
@@ -233,11 +234,18 @@ class InstallHelper(object):
 
         if model_path.exists():  # local file on disk
             return LocalModelSource(path=model_path.absolute(), inplace=True)
-        if re.match(r"^[^/]+/[^/]+$", model_path_id_or_url):  # hugging face repo_id
+
+        # parsing huggingface repo ids
+        # we're going to do a little trick that allows for extended repo_ids of form "foo/bar:fp16"
+        variants = "|".join([x.lower() for x in ModelRepoVariant.__members__])
+        if match := re.match(f"^([^/]+/[^/]+?)(?::({variants}))?$", model_path_id_or_url):
+            repo_id = match.group(1)
+            repo_variant = ModelRepoVariant(match.group(2)) if match.group(2) else None
             return HFModelSource(
-                repo_id=model_path_id_or_url,
+                repo_id=repo_id,
                 access_token=HfFolder.get_token(),
                 subfolder=model_info.subfolder,
+                variant=repo_variant,
             )
         if re.match(r"^(http|https):", model_path_id_or_url):
             return URLModelSource(url=AnyHttpUrl(model_path_id_or_url))
@@ -278,9 +286,11 @@ class InstallHelper(object):
                 model_name=model_name,
             )
             if len(matches) > 1:
-                print(f"{model} is ambiguous. Please use model_type:model_name (e.g. main:my_model) to disambiguate.")
+                print(
+                    f"{model_to_remove} is ambiguous. Please use model_base/model_type/model_name (e.g. sd-1/main/my_model) to disambiguate."
+                )
             elif not matches:
-                print(f"{model}: unknown model")
+                print(f"{model_to_remove}: unknown model")
             else:
                 for m in matches:
                     print(f"Deleting {m.type}:{m.name}")
diff --git a/invokeai/backend/model_manager/config.py b/invokeai/backend/model_manager/config.py
index 4488f8eafc..49ce6af2b8 100644
--- a/invokeai/backend/model_manager/config.py
+++ b/invokeai/backend/model_manager/config.py
@@ -109,7 +109,7 @@ class SchedulerPredictionType(str, Enum):
 class ModelRepoVariant(str, Enum):
     """Various hugging face variants on the diffusers format."""
 
-    DEFAULT = "default"  # model files without "fp16" or other qualifier
+    DEFAULT = ""  # model files without "fp16" or other qualifier - empty str
     FP16 = "fp16"
     FP32 = "fp32"
     ONNX = "onnx"
@@ -246,6 +246,16 @@ class ONNXSD2Config(_MainConfig):
     upcast_attention: bool = True
 
 
+class ONNXSDXLConfig(_MainConfig):
+    """Model config for ONNX format models based on sdxl."""
+
+    type: Literal[ModelType.ONNX] = ModelType.ONNX
+    format: Literal[ModelFormat.Onnx, ModelFormat.Olive]
+    # No yaml config file for ONNX, so these are part of config
+    base: Literal[BaseModelType.StableDiffusionXL] = BaseModelType.StableDiffusionXL
+    prediction_type: SchedulerPredictionType = SchedulerPredictionType.VPrediction
+
+
 class IPAdapterConfig(ModelConfigBase):
     """Model config for IP Adaptor format models."""
 
@@ -267,7 +277,7 @@ class T2IConfig(ModelConfigBase):
     format: Literal[ModelFormat.Diffusers]
 
 
-_ONNXConfig = Annotated[Union[ONNXSD1Config, ONNXSD2Config], Field(discriminator="base")]
+_ONNXConfig = Annotated[Union[ONNXSD1Config, ONNXSD2Config, ONNXSDXLConfig], Field(discriminator="base")]
 _ControlNetConfig = Annotated[
     Union[ControlNetDiffusersConfig, ControlNetCheckpointConfig],
     Field(discriminator="format"),
diff --git a/invokeai/backend/model_manager/load/__init__.py b/invokeai/backend/model_manager/load/__init__.py
index 19b0116ba3..e4c7077f78 100644
--- a/invokeai/backend/model_manager/load/__init__.py
+++ b/invokeai/backend/model_manager/load/__init__.py
@@ -16,7 +16,6 @@ from .model_cache.model_cache_default import ModelCache
 # This registers the subclasses that implement loaders of specific model types
 loaders = [x.stem for x in Path(Path(__file__).parent, "model_loaders").glob("*.py") if x.stem != "__init__"]
 for module in loaders:
-    print(f"module={module}")
     import_module(f"{__package__}.model_loaders.{module}")
 
 __all__ = ["AnyModelLoader", "LoadedModel"]
diff --git a/invokeai/backend/model_manager/load/load_base.py b/invokeai/backend/model_manager/load/load_base.py
index 7d4e8337c3..ee9d6d53e3 100644
--- a/invokeai/backend/model_manager/load/load_base.py
+++ b/invokeai/backend/model_manager/load/load_base.py
@@ -22,6 +22,7 @@ from invokeai.backend.model_manager import AnyModel, AnyModelConfig, BaseModelTy
 from invokeai.backend.model_manager.config import VaeCheckpointConfig, VaeDiffusersConfig
 from invokeai.backend.model_manager.load.convert_cache.convert_cache_base import ModelConvertCacheBase
 from invokeai.backend.model_manager.load.model_cache.model_cache_base import ModelCacheBase, ModelLockerBase
+from invokeai.backend.util.logging import InvokeAILogger
 
 
 @dataclass
@@ -88,6 +89,7 @@ class AnyModelLoader:
 
     # this tracks the loader subclasses
     _registry: Dict[str, Type[ModelLoaderBase]] = {}
+    _logger: Logger = InvokeAILogger.get_logger()
 
     def __init__(
         self,
@@ -167,7 +169,7 @@ class AnyModelLoader:
         """Define a decorator which registers the subclass of loader."""
 
         def decorator(subclass: Type[ModelLoaderBase]) -> Type[ModelLoaderBase]:
-            print("DEBUG: Registering class", subclass.__name__)
+            cls._logger.debug(f"Registering class {subclass.__name__} to load models of type {base}/{type}/{format}")
             key = cls._to_registry_key(base, type, format)
             cls._registry[key] = subclass
             return subclass
diff --git a/invokeai/backend/model_manager/load/load_default.py b/invokeai/backend/model_manager/load/load_default.py
index adc84d2051..757745072d 100644
--- a/invokeai/backend/model_manager/load/load_default.py
+++ b/invokeai/backend/model_manager/load/load_default.py
@@ -52,7 +52,7 @@ class ModelLoader(ModelLoaderBase):
         self._logger = logger
         self._ram_cache = ram_cache
         self._convert_cache = convert_cache
-        self._torch_dtype = torch_dtype(choose_torch_device())
+        self._torch_dtype = torch_dtype(choose_torch_device(), app_config)
 
     def load_model(self, model_config: AnyModelConfig, submodel_type: Optional[SubModelType] = None) -> LoadedModel:
         """
@@ -102,8 +102,10 @@ class ModelLoader(ModelLoaderBase):
         self, config: AnyModelConfig, model_path: Path, submodel_type: Optional[SubModelType] = None
     ) -> ModelLockerBase:
         # TO DO: This is not thread safe!
-        if self._ram_cache.exists(config.key, submodel_type):
+        try:
             return self._ram_cache.get(config.key, submodel_type)
+        except IndexError:
+            pass
 
         model_variant = getattr(config, "repo_variant", None)
         self._ram_cache.make_room(self.get_size_fs(config, model_path, submodel_type))
@@ -119,7 +121,11 @@ class ModelLoader(ModelLoaderBase):
             size=calc_model_size_by_data(loaded_model),
         )
 
-        return self._ram_cache.get(config.key, submodel_type)
+        return self._ram_cache.get(
+            key=config.key,
+            submodel_type=submodel_type,
+            stats_name=":".join([config.base, config.type, config.name, (submodel_type or "")]),
+        )
 
     def get_size_fs(
         self, config: AnyModelConfig, model_path: Path, submodel_type: Optional[SubModelType] = None
@@ -146,13 +152,21 @@ class ModelLoader(ModelLoaderBase):
     # TO DO: Add exception handling
     def _get_hf_load_class(self, model_path: Path, submodel_type: Optional[SubModelType] = None) -> ModelMixin:
         if submodel_type:
-            config = self._load_diffusers_config(model_path, config_name="model_index.json")
-            module, class_name = config[submodel_type.value]
-            return self._hf_definition_to_type(module=module, class_name=class_name)
+            try:
+                config = self._load_diffusers_config(model_path, config_name="model_index.json")
+                module, class_name = config[submodel_type.value]
+                return self._hf_definition_to_type(module=module, class_name=class_name)
+            except KeyError as e:
+                raise InvalidModelConfigException(
+                    f'The "{submodel_type}" submodel is not available for this model.'
+                ) from e
         else:
-            config = self._load_diffusers_config(model_path, config_name="config.json")
-            class_name = config["_class_name"]
-            return self._hf_definition_to_type(module="diffusers", class_name=class_name)
+            try:
+                config = self._load_diffusers_config(model_path, config_name="config.json")
+                class_name = config["_class_name"]
+                return self._hf_definition_to_type(module="diffusers", class_name=class_name)
+            except KeyError as e:
+                raise InvalidModelConfigException("An expected config.json file is missing from this model.") from e
 
     # This needs to be implemented in subclasses that handle checkpoints
     def _convert_model(self, config: AnyModelConfig, weights_path: Path, output_path: Path) -> Path:
diff --git a/invokeai/backend/model_manager/load/model_cache/__init__.py b/invokeai/backend/model_manager/load/model_cache/__init__.py
index 6c87e2519e..0cb5184f3a 100644
--- a/invokeai/backend/model_manager/load/model_cache/__init__.py
+++ b/invokeai/backend/model_manager/load/model_cache/__init__.py
@@ -1,3 +1,4 @@
-"""Init file for RamCache."""
+"""Init file for ModelCache."""
+
 
 _all__ = ["ModelCacheBase", "ModelCache"]
diff --git a/invokeai/backend/model_manager/load/model_cache/model_cache_base.py b/invokeai/backend/model_manager/load/model_cache/model_cache_base.py
index 14a7dfb4a1..b1a6768ee8 100644
--- a/invokeai/backend/model_manager/load/model_cache/model_cache_base.py
+++ b/invokeai/backend/model_manager/load/model_cache/model_cache_base.py
@@ -129,11 +129,17 @@ class ModelCacheBase(ABC, Generic[T]):
         self,
         key: str,
         submodel_type: Optional[SubModelType] = None,
+        stats_name: Optional[str] = None,
     ) -> ModelLockerBase:
         """
-        Retrieve model locker object using key and optional submodel_type.
+        Retrieve model using key and optional submodel_type.
 
-        This may return an UnknownModelException if the model is not in the cache.
+        :param key: Opaque model key
+        :param submodel_type: Type of the submodel to fetch
+        :param stats_name: A human-readable id for the model for the purposes of
+        stats reporting.
+
+        This may raise an IndexError if the model is not in the cache.
         """
         pass
 
diff --git a/invokeai/backend/model_manager/load/model_cache/model_cache_default.py b/invokeai/backend/model_manager/load/model_cache/model_cache_default.py
index 688be8ceb4..7e30512a58 100644
--- a/invokeai/backend/model_manager/load/model_cache/model_cache_default.py
+++ b/invokeai/backend/model_manager/load/model_cache/model_cache_default.py
@@ -24,6 +24,7 @@ import math
 import sys
 import time
 from contextlib import suppress
+from dataclasses import dataclass, field
 from logging import Logger
 from typing import Dict, List, Optional
 
@@ -55,6 +56,20 @@ GIG = 1073741824
 MB = 2**20
 
 
+@dataclass
+class CacheStats(object):
+    """Collect statistics on cache performance."""
+
+    hits: int = 0  # cache hits
+    misses: int = 0  # cache misses
+    high_watermark: int = 0  # amount of cache used
+    in_cache: int = 0  # number of models in cache
+    cleared: int = 0  # number of models cleared to make space
+    cache_size: int = 0  # total size of cache
+    # {submodel_key => size}
+    loaded_model_sizes: Dict[str, int] = field(default_factory=dict)
+
+
 class ModelCache(ModelCacheBase[AnyModel]):
     """Implementation of ModelCacheBase."""
 
@@ -94,6 +109,8 @@ class ModelCache(ModelCacheBase[AnyModel]):
         self._storage_device: torch.device = storage_device
         self._logger = logger or InvokeAILogger.get_logger(self.__class__.__name__)
         self._log_memory_usage = log_memory_usage or self._logger.level == logging.DEBUG
+        # used for stats collection
+        self.stats = CacheStats()
 
         self._cached_models: Dict[str, CacheRecord[AnyModel]] = {}
         self._cache_stack: List[str] = []
@@ -158,21 +175,40 @@ class ModelCache(ModelCacheBase[AnyModel]):
         self,
         key: str,
         submodel_type: Optional[SubModelType] = None,
+        stats_name: Optional[str] = None,
     ) -> ModelLockerBase:
         """
         Retrieve model using key and optional submodel_type.
 
-        This may return an IndexError if the model is not in the cache.
+        :param key: Opaque model key
+        :param submodel_type: Type of the submodel to fetch
+        :param stats_name: A human-readable id for the model for the purposes of
+        stats reporting.
+
+        This may raise an IndexError if the model is not in the cache.
         """
         key = self._make_cache_key(key, submodel_type)
-        if key not in self._cached_models:
+        if key in self._cached_models:
+            self.stats.hits += 1
+        else:
+            self.stats.misses += 1
             raise IndexError(f"The model with key {key} is not in the cache.")
 
+        cache_entry = self._cached_models[key]
+
+        # more stats
+        stats_name = stats_name or key
+        self.stats.cache_size = int(self._max_cache_size * GIG)
+        self.stats.high_watermark = max(self.stats.high_watermark, self.cache_size())
+        self.stats.in_cache = len(self._cached_models)
+        self.stats.loaded_model_sizes[stats_name] = max(
+            self.stats.loaded_model_sizes.get(stats_name, 0), cache_entry.size
+        )
+
         # this moves the entry to the top (right end) of the stack
         with suppress(Exception):
             self._cache_stack.remove(key)
         self._cache_stack.append(key)
-        cache_entry = self._cached_models[key]
         return ModelLocker(
             cache=self,
             cache_entry=cache_entry,
diff --git a/invokeai/backend/model_manager/load/model_loaders/onnx.py b/invokeai/backend/model_manager/load/model_loaders/onnx.py
new file mode 100644
index 0000000000..935a6b7c95
--- /dev/null
+++ b/invokeai/backend/model_manager/load/model_loaders/onnx.py
@@ -0,0 +1,41 @@
+# Copyright (c) 2024, Lincoln D. Stein and the InvokeAI Development Team
+"""Class for Onnx model loading in InvokeAI."""
+
+# This should work the same as Stable Diffusion pipelines
+from pathlib import Path
+from typing import Optional
+
+from invokeai.backend.model_manager import (
+    AnyModel,
+    BaseModelType,
+    ModelFormat,
+    ModelRepoVariant,
+    ModelType,
+    SubModelType,
+)
+from invokeai.backend.model_manager.load.load_base import AnyModelLoader
+from invokeai.backend.model_manager.load.load_default import ModelLoader
+
+
+@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.ONNX, format=ModelFormat.Onnx)
+@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.ONNX, format=ModelFormat.Olive)
+class OnnyxDiffusersModel(ModelLoader):
+    """Class to load onnx models."""
+
+    def _load_model(
+        self,
+        model_path: Path,
+        model_variant: Optional[ModelRepoVariant] = None,
+        submodel_type: Optional[SubModelType] = None,
+    ) -> AnyModel:
+        if not submodel_type is not None:
+            raise Exception("A submodel type must be provided when loading onnx pipelines.")
+        load_class = self._get_hf_load_class(model_path, submodel_type)
+        variant = model_variant.value if model_variant else None
+        model_path = model_path / submodel_type.value
+        result: AnyModel = load_class.from_pretrained(
+            model_path,
+            torch_dtype=self._torch_dtype,
+            variant=variant,
+        )  # type: ignore
+        return result
diff --git a/invokeai/backend/model_manager/metadata/fetch/civitai.py b/invokeai/backend/model_manager/metadata/fetch/civitai.py
index 6e41d6f11b..7991f6a748 100644
--- a/invokeai/backend/model_manager/metadata/fetch/civitai.py
+++ b/invokeai/backend/model_manager/metadata/fetch/civitai.py
@@ -32,6 +32,8 @@ import requests
 from pydantic.networks import AnyHttpUrl
 from requests.sessions import Session
 
+from invokeai.backend.model_manager import ModelRepoVariant
+
 from ..metadata_base import (
     AnyModelRepoMetadata,
     CivitaiMetadata,
@@ -82,10 +84,13 @@ class CivitaiMetadataFetch(ModelMetadataFetchBase):
             return self.from_civitai_versionid(int(version_id))
         raise UnknownMetadataException("The url '{url}' does not match any known Civitai URL patterns")
 
-    def from_id(self, id: str) -> AnyModelRepoMetadata:
+    def from_id(self, id: str, variant: Optional[ModelRepoVariant] = None) -> AnyModelRepoMetadata:
         """
         Given a Civitai model version ID, return a ModelRepoMetadata object.
 
+        :param id: An ID.
+        :param variant: A model variant from the ModelRepoVariant enum (currently ignored)
+
         May raise an `UnknownMetadataException`.
         """
         return self.from_civitai_versionid(int(id))
diff --git a/invokeai/backend/model_manager/metadata/fetch/fetch_base.py b/invokeai/backend/model_manager/metadata/fetch/fetch_base.py
index 58b65b6947..d628ab5c17 100644
--- a/invokeai/backend/model_manager/metadata/fetch/fetch_base.py
+++ b/invokeai/backend/model_manager/metadata/fetch/fetch_base.py
@@ -18,6 +18,8 @@ from typing import Optional
 from pydantic.networks import AnyHttpUrl
 from requests.sessions import Session
 
+from invokeai.backend.model_manager import ModelRepoVariant
+
 from ..metadata_base import AnyModelRepoMetadata, AnyModelRepoMetadataValidator
 
 
@@ -45,10 +47,13 @@ class ModelMetadataFetchBase(ABC):
         pass
 
     @abstractmethod
-    def from_id(self, id: str) -> AnyModelRepoMetadata:
+    def from_id(self, id: str, variant: Optional[ModelRepoVariant] = None) -> AnyModelRepoMetadata:
         """
         Given an ID for a model, return a ModelMetadata object.
 
+        :param id: An ID.
+        :param variant: A model variant from the ModelRepoVariant enum.
+
         This method will raise a `UnknownMetadataException`
         in the event that the requested model's metadata is not found at the provided id.
         """
diff --git a/invokeai/backend/model_manager/metadata/fetch/huggingface.py b/invokeai/backend/model_manager/metadata/fetch/huggingface.py
index 5d1eb0cc9e..6f04e8713b 100644
--- a/invokeai/backend/model_manager/metadata/fetch/huggingface.py
+++ b/invokeai/backend/model_manager/metadata/fetch/huggingface.py
@@ -19,10 +19,12 @@ from typing import Optional
 
 import requests
 from huggingface_hub import HfApi, configure_http_backend, hf_hub_url
-from huggingface_hub.utils._errors import RepositoryNotFoundError
+from huggingface_hub.utils._errors import RepositoryNotFoundError, RevisionNotFoundError
 from pydantic.networks import AnyHttpUrl
 from requests.sessions import Session
 
+from invokeai.backend.model_manager import ModelRepoVariant
+
 from ..metadata_base import (
     AnyModelRepoMetadata,
     HuggingFaceMetadata,
@@ -53,12 +55,22 @@ class HuggingFaceMetadataFetch(ModelMetadataFetchBase):
         metadata = HuggingFaceMetadata.model_validate_json(json)
         return metadata
 
-    def from_id(self, id: str) -> AnyModelRepoMetadata:
+    def from_id(self, id: str, variant: Optional[ModelRepoVariant] = None) -> AnyModelRepoMetadata:
         """Return a HuggingFaceMetadata object given the model's repo_id."""
-        try:
-            model_info = HfApi().model_info(repo_id=id, files_metadata=True)
-        except RepositoryNotFoundError as excp:
-            raise UnknownMetadataException(f"'{id}' not found. See trace for details.") from excp
+        # Little loop which tries fetching a revision corresponding to the selected variant.
+        # If not available, then set variant to None and get the default.
+        # If this too fails, raise exception.
+        model_info = None
+        while not model_info:
+            try:
+                model_info = HfApi().model_info(repo_id=id, files_metadata=True, revision=variant)
+            except RepositoryNotFoundError as excp:
+                raise UnknownMetadataException(f"'{id}' not found. See trace for details.") from excp
+            except RevisionNotFoundError:
+                if variant is None:
+                    raise
+                else:
+                    variant = None
 
         _, name = id.split("/")
         return HuggingFaceMetadata(
@@ -70,7 +82,7 @@ class HuggingFaceMetadataFetch(ModelMetadataFetchBase):
             tags=model_info.tags,
             files=[
                 RemoteModelFile(
-                    url=hf_hub_url(id, x.rfilename),
+                    url=hf_hub_url(id, x.rfilename, revision=variant),
                     path=Path(name, x.rfilename),
                     size=x.size,
                     sha256=x.lfs.get("sha256") if x.lfs else None,
diff --git a/invokeai/backend/model_manager/metadata/metadata_base.py b/invokeai/backend/model_manager/metadata/metadata_base.py
index 5aa883d26d..5c3afcdc96 100644
--- a/invokeai/backend/model_manager/metadata/metadata_base.py
+++ b/invokeai/backend/model_manager/metadata/metadata_base.py
@@ -184,7 +184,6 @@ class HuggingFaceMetadata(ModelMetadataWithFiles):
             [x.path for x in self.files], variant, subfolder
         )  #  all files in the model
         prefix = f"{subfolder}/" if subfolder else ""
-
         # the next step reads model_index.json to determine which subdirectories belong
         # to the model
         if Path(f"{prefix}model_index.json") in paths:
diff --git a/invokeai/backend/model_manager/probe.py b/invokeai/backend/model_manager/probe.py
index 64a20a2092..55a9c0464a 100644
--- a/invokeai/backend/model_manager/probe.py
+++ b/invokeai/backend/model_manager/probe.py
@@ -7,6 +7,7 @@ import safetensors.torch
 import torch
 from picklescan.scanner import scan_file_path
 
+import invokeai.backend.util.logging as logger
 from invokeai.backend.model_management.models.base import read_checkpoint_meta
 from invokeai.backend.model_management.models.ip_adapter import IPAdapterModelFormat
 from invokeai.backend.model_management.util import lora_token_vector_length
@@ -590,13 +591,20 @@ class TextualInversionFolderProbe(FolderProbeBase):
         return TextualInversionCheckpointProbe(path).get_base_type()
 
 
-class ONNXFolderProbe(FolderProbeBase):
+class ONNXFolderProbe(PipelineFolderProbe):
+    def get_base_type(self) -> BaseModelType:
+        # Due to the way the installer is set up, the configuration file for safetensors
+        # will come along for the ride if both the onnx and safetensors forms
+        # share the same directory. We take advantage of this here.
+        if (self.model_path / "unet" / "config.json").exists():
+            return super().get_base_type()
+        else:
+            logger.warning('Base type probing is not implemented for ONNX models. Assuming "sd-1"')
+            return BaseModelType.StableDiffusion1
+
     def get_format(self) -> ModelFormat:
         return ModelFormat("onnx")
 
-    def get_base_type(self) -> BaseModelType:
-        return BaseModelType.StableDiffusion1
-
     def get_variant_type(self) -> ModelVariantType:
         return ModelVariantType.Normal
 
diff --git a/invokeai/backend/model_manager/util/select_hf_files.py b/invokeai/backend/model_manager/util/select_hf_files.py
index 6976059044..a894d915de 100644
--- a/invokeai/backend/model_manager/util/select_hf_files.py
+++ b/invokeai/backend/model_manager/util/select_hf_files.py
@@ -41,13 +41,21 @@ def filter_files(
     for file in files:
         if file.name.endswith((".json", ".txt")):
             paths.append(file)
-        elif file.name.endswith(("learned_embeds.bin", "ip_adapter.bin", "lora_weights.safetensors")):
+        elif file.name.endswith(
+            (
+                "learned_embeds.bin",
+                "ip_adapter.bin",
+                "lora_weights.safetensors",
+                "weights.pb",
+                "onnx_data",
+            )
+        ):
             paths.append(file)
         # BRITTLENESS WARNING!!
         # Diffusers models always seem to have "model" in their name, and the regex filter below is applied to avoid
         # downloading random checkpoints that might also be in the repo. However there is no guarantee
         # that a checkpoint doesn't contain "model" in its name, and no guarantee that future diffusers models
-        # will adhere to this naming convention, so this is an area of brittleness.
+        # will adhere to this naming convention, so this is an area to be careful of.
         elif re.search(r"model(\.[^.]+)?\.(safetensors|bin|onnx|xml|pth|pt|ckpt|msgpack)$", file.name):
             paths.append(file)
 
@@ -64,7 +72,7 @@ def _filter_by_variant(files: List[Path], variant: ModelRepoVariant) -> Set[Path
     result = set()
     basenames: Dict[Path, Path] = {}
     for path in files:
-        if path.suffix == ".onnx":
+        if path.suffix in [".onnx", ".pb", ".onnx_data"]:
             if variant == ModelRepoVariant.ONNX:
                 result.add(path)
 
diff --git a/invokeai/backend/util/devices.py b/invokeai/backend/util/devices.py
index a787f9b6f4..b4f24d8483 100644
--- a/invokeai/backend/util/devices.py
+++ b/invokeai/backend/util/devices.py
@@ -29,12 +29,17 @@ def choose_torch_device() -> torch.device:
         return torch.device(config.device)
 
 
-def choose_precision(device: torch.device) -> str:
-    """Returns an appropriate precision for the given torch device"""
+# We are in transition here from using a single global AppConfig to allowing multiple
+# configurations. It is strongly recommended to pass the app_config to this function.
+def choose_precision(device: torch.device, app_config: Optional[InvokeAIAppConfig] = None) -> str:
+    """Return an appropriate precision for the given torch device."""
+    app_config = app_config or config
     if device.type == "cuda":
         device_name = torch.cuda.get_device_name(device)
         if not ("GeForce GTX 1660" in device_name or "GeForce GTX 1650" in device_name):
-            if config.precision == "bfloat16":
+            if app_config.precision == "float32":
+                return "float32"
+            elif app_config.precision == "bfloat16":
                 return "bfloat16"
             else:
                 return "float16"
@@ -43,9 +48,14 @@ def choose_precision(device: torch.device) -> str:
     return "float32"
 
 
-def torch_dtype(device: Optional[torch.device] = None) -> torch.dtype:
+# We are in transition here from using a single global AppConfig to allowing multiple
+# configurations. It is strongly recommended to pass the app_config to this function.
+def torch_dtype(
+    device: Optional[torch.device] = None,
+    app_config: Optional[InvokeAIAppConfig] = None,
+) -> torch.dtype:
     device = device or choose_torch_device()
-    precision = choose_precision(device)
+    precision = choose_precision(device, app_config)
     if precision == "float16":
         return torch.float16
     if precision == "bfloat16":
diff --git a/invokeai/frontend/install/model_install2.py b/invokeai/frontend/install/model_install2.py
index 6eb480c8d9..51a633a565 100644
--- a/invokeai/frontend/install/model_install2.py
+++ b/invokeai/frontend/install/model_install2.py
@@ -505,7 +505,7 @@ def list_models(installer: ModelInstallService, model_type: ModelType):
     print(f"Installed models of type `{model_type}`:")
     for model in models:
         path = (config.models_path / model.path).resolve()
-        print(f"{model.name:40}{model.base.value:14}{path}")
+        print(f"{model.name:40}{model.base.value:5}{model.type.value:8}{model.format.value:12}{path}")
 
 
 # --------------------------------------------------------

From 78ef946e010ca9e149d91e85fe49cdc8e615bc47 Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lstein@gmail.com>
Date: Mon, 5 Feb 2024 22:56:32 -0500
Subject: [PATCH 116/411] BREAKING CHANGES: invocations now require model key,
 not base/type/name

- Implement new model loader and modify invocations and embeddings

- Finish implementation loaders for all models currently supported by
  InvokeAI.

- Move lora, textual_inversion, and model patching support into
  backend/embeddings.

- Restore support for model cache statistics collection (a little ugly,
  needs work).

- Fixed up invocations that load and patch models.

- Move seamless and silencewarnings utils into better location
---
 invokeai/app/api/routers/download_queue.py    |   2 +-
 invokeai/app/invocations/compel.py            | 114 +++++++-----
 .../controlnet_image_processors.py            |   7 +-
 invokeai/app/invocations/ip_adapter.py        |  49 +++--
 invokeai/app/invocations/latent.py            |  86 +++++----
 invokeai/app/invocations/model.py             | 174 +++++-------------
 invokeai/app/invocations/sdxl.py              |  74 ++------
 invokeai/app/invocations/t2i_adapter.py       |   8 +-
 invokeai/app/services/events/events_base.py   |  27 +--
 .../invocation_stats_default.py               |  16 +-
 .../model_records/model_records_base.py       |  47 ++++-
 .../model_records/model_records_sql.py        |  92 ++++++++-
 invokeai/backend/embeddings/__init__.py       |   4 +
 invokeai/backend/embeddings/embedding_base.py |  12 ++
 invokeai/backend/embeddings/lora.py           |  14 +-
 invokeai/backend/embeddings/model_patcher.py  | 134 +++-----------
 .../backend/embeddings/textual_inversion.py   | 100 ++++++++++
 invokeai/backend/install/install_helper.py    |   3 +-
 invokeai/backend/model_manager/config.py      |   5 +-
 .../backend/model_manager/load/load_base.py   |   4 +-
 .../model_manager/load/load_default.py        |   4 +-
 .../load/model_cache/__init__.py              |   4 +-
 .../load/model_cache/model_cache_base.py      |  33 +++-
 .../load/model_cache/model_cache_default.py   |  53 +++---
 .../load/model_loaders/textual_inversion.py   |   2 +-
 invokeai/backend/stable_diffusion/__init__.py |   9 +
 invokeai/backend/stable_diffusion/seamless.py | 102 ++++++++++
 invokeai/backend/util/silence_warnings.py     |  28 +++
 invokeai/frontend/install/model_install2.py   |   8 +-
 .../util/test_hf_model_select.py              |   2 +
 tests/test_model_probe.py                     |   6 +-
 31 files changed, 727 insertions(+), 496 deletions(-)
 create mode 100644 invokeai/backend/embeddings/__init__.py
 create mode 100644 invokeai/backend/embeddings/embedding_base.py
 create mode 100644 invokeai/backend/embeddings/textual_inversion.py
 create mode 100644 invokeai/backend/stable_diffusion/seamless.py
 create mode 100644 invokeai/backend/util/silence_warnings.py

diff --git a/invokeai/app/api/routers/download_queue.py b/invokeai/app/api/routers/download_queue.py
index 92b658c370..2dba376c18 100644
--- a/invokeai/app/api/routers/download_queue.py
+++ b/invokeai/app/api/routers/download_queue.py
@@ -55,7 +55,7 @@ async def download(
 ) -> DownloadJob:
     """Download the source URL to the file or directory indicted in dest."""
     queue = ApiDependencies.invoker.services.download_queue
-    return queue.download(source, dest, priority, access_token)
+    return queue.download(source, Path(dest), priority, access_token)
 
 
 @download_queue_router.get(
diff --git a/invokeai/app/invocations/compel.py b/invokeai/app/invocations/compel.py
index 978c6dcb17..0e1a6bdc6f 100644
--- a/invokeai/app/invocations/compel.py
+++ b/invokeai/app/invocations/compel.py
@@ -1,9 +1,10 @@
-from typing import List, Optional, Union
+from typing import Iterator, List, Optional, Tuple, Union
 
 import torch
 from compel import Compel, ReturnedEmbeddingsType
 from compel.prompt_parser import Blend, Conjunction, CrossAttentionControlSubstitute, FlattenedPrompt, Fragment
 
+import invokeai.backend.util.logging as logger
 from invokeai.app.invocations.fields import (
     FieldDescriptions,
     Input,
@@ -12,18 +13,21 @@ from invokeai.app.invocations.fields import (
     UIComponent,
 )
 from invokeai.app.invocations.primitives import ConditioningOutput
+from invokeai.app.services.model_records import UnknownModelException
 from invokeai.app.services.shared.invocation_context import InvocationContext
+from invokeai.app.util.ti_utils import extract_ti_triggers_from_prompt
+from invokeai.backend.embeddings.lora import LoRAModelRaw
+from invokeai.backend.embeddings.model_patcher import ModelPatcher
+from invokeai.backend.embeddings.textual_inversion import TextualInversionModelRaw
+from invokeai.backend.model_manager import ModelType
 from invokeai.backend.stable_diffusion.diffusion.conditioning_data import (
     BasicConditioningInfo,
     ConditioningFieldData,
     ExtraConditioningInfo,
     SDXLConditioningInfo,
 )
+from invokeai.backend.util.devices import torch_dtype
 
-from ...backend.model_management.lora import ModelPatcher
-from ...backend.model_management.models import ModelNotFoundException, ModelType
-from ...backend.util.devices import torch_dtype
-from ..util.ti_utils import extract_ti_triggers_from_prompt
 from .baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
@@ -64,13 +68,22 @@ class CompelInvocation(BaseInvocation):
 
     @torch.no_grad()
     def invoke(self, context: InvocationContext) -> ConditioningOutput:
-        tokenizer_info = context.models.load(**self.clip.tokenizer.model_dump())
-        text_encoder_info = context.models.load(**self.clip.text_encoder.model_dump())
+        tokenizer_info = context.services.model_records.load_model(
+            **self.clip.tokenizer.model_dump(),
+            context=context,
+        )
+        text_encoder_info = context.services.model_records.load_model(
+            **self.clip.text_encoder.model_dump(),
+            context=context,
+        )
 
-        def _lora_loader():
+        def _lora_loader() -> Iterator[Tuple[LoRAModelRaw, float]]:
             for lora in self.clip.loras:
-                lora_info = context.models.load(**lora.model_dump(exclude={"weight"}))
-                yield (lora_info.context.model, lora.weight)
+                lora_info = context.services.model_records.load_model(
+                    **lora.model_dump(exclude={"weight"}), context=context
+                )
+                assert isinstance(lora_info.model, LoRAModelRaw)
+                yield (lora_info.model, lora.weight)
                 del lora_info
             return
 
@@ -80,24 +93,20 @@ class CompelInvocation(BaseInvocation):
         for trigger in extract_ti_triggers_from_prompt(self.prompt):
             name = trigger[1:-1]
             try:
-                ti_list.append(
-                    (
-                        name,
-                        context.models.load(
-                            model_name=name,
-                            base_model=self.clip.text_encoder.base_model,
-                            model_type=ModelType.TextualInversion,
-                        ).context.model,
-                    )
-                )
-            except ModelNotFoundException:
+                loaded_model = context.services.model_records.load_model(
+                    **self.clip.text_encoder.model_dump(),
+                    context=context,
+                ).model
+                assert isinstance(loaded_model, TextualInversionModelRaw)
+                ti_list.append((name, loaded_model))
+            except UnknownModelException:
                 # print(e)
                 # import traceback
                 # print(traceback.format_exc())
                 print(f'Warn: trigger: "{trigger}" not found')
 
         with (
-            ModelPatcher.apply_ti(tokenizer_info.context.model, text_encoder_info.context.model, ti_list) as (
+            ModelPatcher.apply_ti(tokenizer_info.model, text_encoder_info.model, ti_list) as (
                 tokenizer,
                 ti_manager,
             ),
@@ -105,7 +114,7 @@ class CompelInvocation(BaseInvocation):
             # Apply the LoRA after text_encoder has been moved to its target device for faster patching.
             ModelPatcher.apply_lora_text_encoder(text_encoder, _lora_loader()),
             # Apply CLIP Skip after LoRA to prevent LoRA application from failing on skipped layers.
-            ModelPatcher.apply_clip_skip(text_encoder_info.context.model, self.clip.skipped_layers),
+            ModelPatcher.apply_clip_skip(text_encoder_info.model, self.clip.skipped_layers),
         ):
             compel = Compel(
                 tokenizer=tokenizer,
@@ -144,6 +153,8 @@ class CompelInvocation(BaseInvocation):
 
 
 class SDXLPromptInvocationBase:
+    """Prompt processor for SDXL models."""
+
     def run_clip_compel(
         self,
         context: InvocationContext,
@@ -152,20 +163,27 @@ class SDXLPromptInvocationBase:
         get_pooled: bool,
         lora_prefix: str,
         zero_on_empty: bool,
-    ):
-        tokenizer_info = context.models.load(**clip_field.tokenizer.model_dump())
-        text_encoder_info = context.models.load(**clip_field.text_encoder.model_dump())
+    ) -> Tuple[torch.Tensor, Optional[torch.Tensor], Optional[ExtraConditioningInfo]]:
+        tokenizer_info = context.services.model_records.load_model(
+            **clip_field.tokenizer.model_dump(),
+            context=context,
+        )
+        text_encoder_info = context.services.model_records.load_model(
+            **clip_field.text_encoder.model_dump(),
+            context=context,
+        )
 
         # return zero on empty
         if prompt == "" and zero_on_empty:
-            cpu_text_encoder = text_encoder_info.context.model
+            cpu_text_encoder = text_encoder_info.model
+            assert isinstance(cpu_text_encoder, torch.nn.Module)
             c = torch.zeros(
                 (
                     1,
                     cpu_text_encoder.config.max_position_embeddings,
                     cpu_text_encoder.config.hidden_size,
                 ),
-                dtype=text_encoder_info.context.cache.precision,
+                dtype=cpu_text_encoder.dtype,
             )
             if get_pooled:
                 c_pooled = torch.zeros(
@@ -176,10 +194,14 @@ class SDXLPromptInvocationBase:
                 c_pooled = None
             return c, c_pooled, None
 
-        def _lora_loader():
+        def _lora_loader() -> Iterator[Tuple[LoRAModelRaw, float]]:
             for lora in clip_field.loras:
-                lora_info = context.models.load(**lora.model_dump(exclude={"weight"}))
-                yield (lora_info.context.model, lora.weight)
+                lora_info = context.services.model_records.load_model(
+                    **lora.model_dump(exclude={"weight"}), context=context
+                )
+                lora_model = lora_info.model
+                assert isinstance(lora_model, LoRAModelRaw)
+                yield (lora_model, lora.weight)
                 del lora_info
             return
 
@@ -189,24 +211,24 @@ class SDXLPromptInvocationBase:
         for trigger in extract_ti_triggers_from_prompt(prompt):
             name = trigger[1:-1]
             try:
-                ti_list.append(
-                    (
-                        name,
-                        context.models.load(
-                            model_name=name,
-                            base_model=clip_field.text_encoder.base_model,
-                            model_type=ModelType.TextualInversion,
-                        ).context.model,
-                    )
-                )
-            except ModelNotFoundException:
+                ti_model = context.services.model_records.load_model_by_attr(
+                    model_name=name,
+                    base_model=text_encoder_info.config.base,
+                    model_type=ModelType.TextualInversion,
+                    context=context,
+                ).model
+                assert isinstance(ti_model, TextualInversionModelRaw)
+                ti_list.append((name, ti_model))
+            except UnknownModelException:
                 # print(e)
                 # import traceback
                 # print(traceback.format_exc())
-                print(f'Warn: trigger: "{trigger}" not found')
+                logger.warning(f'trigger: "{trigger}" not found')
+            except ValueError:
+                logger.warning(f'trigger: "{trigger}" more than one similarly-named textual inversion models')
 
         with (
-            ModelPatcher.apply_ti(tokenizer_info.context.model, text_encoder_info.context.model, ti_list) as (
+            ModelPatcher.apply_ti(tokenizer_info.model, text_encoder_info.model, ti_list) as (
                 tokenizer,
                 ti_manager,
             ),
@@ -214,7 +236,7 @@ class SDXLPromptInvocationBase:
             # Apply the LoRA after text_encoder has been moved to its target device for faster patching.
             ModelPatcher.apply_lora(text_encoder, _lora_loader(), lora_prefix),
             # Apply CLIP Skip after LoRA to prevent LoRA application from failing on skipped layers.
-            ModelPatcher.apply_clip_skip(text_encoder_info.context.model, clip_field.skipped_layers),
+            ModelPatcher.apply_clip_skip(text_encoder_info.model, clip_field.skipped_layers),
         ):
             compel = Compel(
                 tokenizer=tokenizer,
@@ -332,6 +354,7 @@ class SDXLCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase):
                 dim=1,
             )
 
+        assert c2_pooled is not None
         conditioning_data = ConditioningFieldData(
             conditionings=[
                 SDXLConditioningInfo(
@@ -380,6 +403,7 @@ class SDXLRefinerCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase
 
         add_time_ids = torch.tensor([original_size + crop_coords + (self.aesthetic_score,)])
 
+        assert c2_pooled is not None
         conditioning_data = ConditioningFieldData(
             conditionings=[
                 SDXLConditioningInfo(
diff --git a/invokeai/app/invocations/controlnet_image_processors.py b/invokeai/app/invocations/controlnet_image_processors.py
index 37954c1097..580ee08562 100644
--- a/invokeai/app/invocations/controlnet_image_processors.py
+++ b/invokeai/app/invocations/controlnet_image_processors.py
@@ -23,7 +23,7 @@ from controlnet_aux import (
 )
 from controlnet_aux.util import HWC3, ade_palette
 from PIL import Image
-from pydantic import BaseModel, ConfigDict, Field, field_validator, model_validator
+from pydantic import BaseModel, Field, field_validator, model_validator
 
 from invokeai.app.invocations.fields import (
     FieldDescriptions,
@@ -60,10 +60,7 @@ CONTROLNET_RESIZE_VALUES = Literal[
 class ControlNetModelField(BaseModel):
     """ControlNet model field"""
 
-    model_name: str = Field(description="Name of the ControlNet model")
-    base_model: BaseModelType = Field(description="Base model")
-
-    model_config = ConfigDict(protected_namespaces=())
+    key: str = Field(description="Model config record key for the ControlNet model")
 
 
 class ControlField(BaseModel):
diff --git a/invokeai/app/invocations/ip_adapter.py b/invokeai/app/invocations/ip_adapter.py
index 845fcfa284..700b285a45 100644
--- a/invokeai/app/invocations/ip_adapter.py
+++ b/invokeai/app/invocations/ip_adapter.py
@@ -2,7 +2,8 @@ import os
 from builtins import float
 from typing import List, Union
 
-from pydantic import BaseModel, ConfigDict, Field, field_validator, model_validator
+from pydantic import BaseModel, Field, field_validator, model_validator
+from typing_extensions import Self
 
 from invokeai.app.invocations.baseinvocation import (
     BaseInvocation,
@@ -18,18 +19,13 @@ from invokeai.backend.model_management.models.base import BaseModelType, ModelTy
 from invokeai.backend.model_management.models.ip_adapter import get_ip_adapter_image_encoder_model_id
 
 
+# LS: Consider moving these two classes into model.py
 class IPAdapterModelField(BaseModel):
-    model_name: str = Field(description="Name of the IP-Adapter model")
-    base_model: BaseModelType = Field(description="Base model")
-
-    model_config = ConfigDict(protected_namespaces=())
+    key: str = Field(description="Key to the IP-Adapter model")
 
 
 class CLIPVisionModelField(BaseModel):
-    model_name: str = Field(description="Name of the CLIP Vision image encoder model")
-    base_model: BaseModelType = Field(description="Base model (usually 'Any')")
-
-    model_config = ConfigDict(protected_namespaces=())
+    key: str = Field(description="Key to the CLIP Vision image encoder model")
 
 
 class IPAdapterField(BaseModel):
@@ -46,16 +42,26 @@ class IPAdapterField(BaseModel):
 
     @field_validator("weight")
     @classmethod
-    def validate_ip_adapter_weight(cls, v):
+    def validate_ip_adapter_weight(cls, v: float) -> float:
         validate_weights(v)
         return v
 
     @model_validator(mode="after")
-    def validate_begin_end_step_percent(self):
+    def validate_begin_end_step_percent(self) -> Self:
         validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
         return self
 
 
+def get_ip_adapter_image_encoder_model_id(model_path: str):
+    """Read the ID of the image encoder associated with the IP-Adapter at `model_path`."""
+    image_encoder_config_file = os.path.join(model_path, "image_encoder.txt")
+
+    with open(image_encoder_config_file, "r") as f:
+        image_encoder_model = f.readline().strip()
+
+    return image_encoder_model
+
+
 @invocation_output("ip_adapter_output")
 class IPAdapterOutput(BaseInvocationOutput):
     # Outputs
@@ -84,33 +90,36 @@ class IPAdapterInvocation(BaseInvocation):
 
     @field_validator("weight")
     @classmethod
-    def validate_ip_adapter_weight(cls, v):
+    def validate_ip_adapter_weight(cls, v: float) -> float:
         validate_weights(v)
         return v
 
     @model_validator(mode="after")
-    def validate_begin_end_step_percent(self):
+    def validate_begin_end_step_percent(self) -> Self:
         validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
         return self
 
     def invoke(self, context: InvocationContext) -> IPAdapterOutput:
         # Lookup the CLIP Vision encoder that is intended to be used with the IP-Adapter model.
-        ip_adapter_info = context.models.get_info(
-            self.ip_adapter_model.model_name, self.ip_adapter_model.base_model, ModelType.IPAdapter
-        )
+        ip_adapter_info = context.services.model_records.get_model(self.ip_adapter_model.key)
         # HACK(ryand): This is bad for a couple of reasons: 1) we are bypassing the model manager to read the model
         # directly, and 2) we are reading from disk every time this invocation is called without caching the result.
         # A better solution would be to store the image encoder model reference in the IP-Adapter model info, but this
         # is currently messy due to differences between how the model info is generated when installing a model from
         # disk vs. downloading the model.
+        # TODO (LS): Fix the issue above by:
+        #    1. Change IPAdapterConfig definition to include a field for the repo_id of the image encoder model.
+        #    2. Update probe.py to read `image_encoder.txt` and store it in the config.
+        #    3. Change below to get the image encoder from the configuration record.
         image_encoder_model_id = get_ip_adapter_image_encoder_model_id(
-            os.path.join(context.config.get().models_path, ip_adapter_info["path"])
+            os.path.join(context.services.configuration.get_config().models_path, ip_adapter_info.path)
         )
         image_encoder_model_name = image_encoder_model_id.split("/")[-1].strip()
-        image_encoder_model = CLIPVisionModelField(
-            model_name=image_encoder_model_name,
-            base_model=BaseModelType.Any,
+        image_encoder_models = context.services.model_records.search_by_attr(
+            model_name=image_encoder_model_name, base_model=BaseModelType.Any, model_type=ModelType.CLIPVision
         )
+        assert len(image_encoder_models) == 1
+        image_encoder_model = CLIPVisionModelField(key=image_encoder_models[0].key)
         return IPAdapterOutput(
             ip_adapter=IPAdapterField(
                 image=self.image,
diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py
index 69e3f055ca..063b23fa58 100644
--- a/invokeai/app/invocations/latent.py
+++ b/invokeai/app/invocations/latent.py
@@ -3,13 +3,13 @@
 import math
 from contextlib import ExitStack
 from functools import singledispatchmethod
-from typing import List, Literal, Optional, Union
+from typing import Iterator, List, Literal, Optional, Tuple, Union
 
 import einops
 import numpy as np
 import torch
 import torchvision.transforms as T
-from diffusers import AutoencoderKL, AutoencoderTiny
+from diffusers import AutoencoderKL, AutoencoderTiny, UNet2DConditionModel
 from diffusers.image_processor import VaeImageProcessor
 from diffusers.models.adapter import T2IAdapter
 from diffusers.models.attention_processor import (
@@ -46,14 +46,13 @@ from invokeai.app.invocations.primitives import (
 from invokeai.app.invocations.t2i_adapter import T2IAdapterField
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.app.util.controlnet_utils import prepare_control_image
+from invokeai.backend.embeddings.model_patcher import ModelPatcher
 from invokeai.backend.ip_adapter.ip_adapter import IPAdapter, IPAdapterPlus
-from invokeai.backend.model_management.models import ModelType, SilenceWarnings
+from invokeai.backend.model_manager import AnyModel, BaseModelType
+from invokeai.backend.stable_diffusion import PipelineIntermediateState, set_seamless
 from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ConditioningData, IPAdapterConditioningInfo
+from invokeai.backend.util.silence_warnings import SilenceWarnings
 
-from ...backend.model_management.lora import ModelPatcher
-from ...backend.model_management.models import BaseModelType
-from ...backend.model_management.seamless import set_seamless
-from ...backend.stable_diffusion import PipelineIntermediateState
 from ...backend.stable_diffusion.diffusers_pipeline import (
     ControlNetData,
     IPAdapterData,
@@ -149,7 +148,10 @@ class CreateDenoiseMaskInvocation(BaseInvocation):
         )
 
         if image is not None:
-            vae_info = context.models.load(**self.vae.vae.model_dump())
+            vae_info = context.services.model_records.load_model(
+                **self.vae.vae.model_dump(),
+                context=context,
+            )
 
             img_mask = tv_resize(mask, image.shape[-2:], T.InterpolationMode.BILINEAR, antialias=False)
             masked_image = image * torch.where(img_mask < 0.5, 0.0, 1.0)
@@ -175,7 +177,10 @@ def get_scheduler(
     seed: int,
 ) -> Scheduler:
     scheduler_class, scheduler_extra_config = SCHEDULER_MAP.get(scheduler_name, SCHEDULER_MAP["ddim"])
-    orig_scheduler_info = context.models.load(**scheduler_info.model_dump())
+    orig_scheduler_info = context.services.model_records.load_model(
+        **scheduler_info.model_dump(),
+        context=context,
+    )
     with orig_scheduler_info as orig_scheduler:
         scheduler_config = orig_scheduler.config
 
@@ -389,10 +394,9 @@ class DenoiseLatentsInvocation(BaseInvocation):
         controlnet_data = []
         for control_info in control_list:
             control_model = exit_stack.enter_context(
-                context.models.load(
-                    model_name=control_info.control_model.model_name,
-                    model_type=ModelType.ControlNet,
-                    base_model=control_info.control_model.base_model,
+                context.services.model_records.load_model(
+                    key=control_info.control_model.key,
+                    context=context,
                 )
             )
 
@@ -456,17 +460,15 @@ class DenoiseLatentsInvocation(BaseInvocation):
         conditioning_data.ip_adapter_conditioning = []
         for single_ip_adapter in ip_adapter:
             ip_adapter_model: Union[IPAdapter, IPAdapterPlus] = exit_stack.enter_context(
-                context.models.load(
-                    model_name=single_ip_adapter.ip_adapter_model.model_name,
-                    model_type=ModelType.IPAdapter,
-                    base_model=single_ip_adapter.ip_adapter_model.base_model,
+                context.services.model_records.load_model(
+                    key=single_ip_adapter.ip_adapter_model.key,
+                    context=context,
                 )
             )
 
-            image_encoder_model_info = context.models.load(
-                model_name=single_ip_adapter.image_encoder_model.model_name,
-                model_type=ModelType.CLIPVision,
-                base_model=single_ip_adapter.image_encoder_model.base_model,
+            image_encoder_model_info = context.services.model_records.load_model(
+                key=single_ip_adapter.image_encoder_model.key,
+                context=context,
             )
 
             # `single_ip_adapter.image` could be a list or a single ImageField. Normalize to a list here.
@@ -518,10 +520,9 @@ class DenoiseLatentsInvocation(BaseInvocation):
 
         t2i_adapter_data = []
         for t2i_adapter_field in t2i_adapter:
-            t2i_adapter_model_info = context.models.load(
-                model_name=t2i_adapter_field.t2i_adapter_model.model_name,
-                model_type=ModelType.T2IAdapter,
-                base_model=t2i_adapter_field.t2i_adapter_model.base_model,
+            t2i_adapter_model_info = context.services.model_records.load_model(
+                key=t2i_adapter_field.t2i_adapter_model.key,
+                context=context,
             )
             image = context.images.get_pil(t2i_adapter_field.image.image_name)
 
@@ -556,7 +557,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
                     do_classifier_free_guidance=False,
                     width=t2i_input_width,
                     height=t2i_input_height,
-                    num_channels=t2i_adapter_model.config.in_channels,
+                    num_channels=t2i_adapter_model.config["in_channels"],  # mypy treats this as a FrozenDict
                     device=t2i_adapter_model.device,
                     dtype=t2i_adapter_model.dtype,
                     resize_mode=t2i_adapter_field.resize_mode,
@@ -662,22 +663,30 @@ class DenoiseLatentsInvocation(BaseInvocation):
             def step_callback(state: PipelineIntermediateState):
                 context.util.sd_step_callback(state, self.unet.unet.base_model)
 
-            def _lora_loader():
+            def _lora_loader() -> Iterator[Tuple[AnyModel, float]]:
                 for lora in self.unet.loras:
-                    lora_info = context.models.load(**lora.model_dump(exclude={"weight"}))
-                    yield (lora_info.context.model, lora.weight)
+                    lora_info = context.services.model_records.load_model(
+                        **lora.model_dump(exclude={"weight"}),
+                        context=context,
+                    )
+                    yield (lora_info.model, lora.weight)
                     del lora_info
                 return
 
-            unet_info = context.models.load(**self.unet.unet.model_dump())
+            unet_info = context.services.model_records.load_model(
+                **self.unet.unet.model_dump(),
+                context=context,
+            )
+            assert isinstance(unet_info.model, UNet2DConditionModel)
             with (
                 ExitStack() as exit_stack,
-                ModelPatcher.apply_freeu(unet_info.context.model, self.unet.freeu_config),
-                set_seamless(unet_info.context.model, self.unet.seamless_axes),
+                ModelPatcher.apply_freeu(unet_info.model, self.unet.freeu_config),
+                set_seamless(unet_info.model, self.unet.seamless_axes),  # FIXME
                 unet_info as unet,
                 # Apply the LoRA after unet has been moved to its target device for faster patching.
                 ModelPatcher.apply_lora_unet(unet, _lora_loader()),
             ):
+                assert isinstance(unet, torch.Tensor)
                 latents = latents.to(device=unet.device, dtype=unet.dtype)
                 if noise is not None:
                     noise = noise.to(device=unet.device, dtype=unet.dtype)
@@ -774,9 +783,13 @@ class LatentsToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
     def invoke(self, context: InvocationContext) -> ImageOutput:
         latents = context.tensors.load(self.latents.latents_name)
 
-        vae_info = context.models.load(**self.vae.vae.model_dump())
+        vae_info = context.services.model_records.load_model(
+            **self.vae.vae.model_dump(),
+            context=context,
+        )
 
-        with set_seamless(vae_info.context.model, self.vae.seamless_axes), vae_info as vae:
+        with set_seamless(vae_info.model, self.vae.seamless_axes), vae_info as vae:
+            assert isinstance(vae, torch.Tensor)
             latents = latents.to(vae.device)
             if self.fp32:
                 vae.to(dtype=torch.float32)
@@ -995,7 +1008,10 @@ class ImageToLatentsInvocation(BaseInvocation):
     def invoke(self, context: InvocationContext) -> LatentsOutput:
         image = context.images.get_pil(self.image.image_name)
 
-        vae_info = context.models.load(**self.vae.vae.model_dump())
+        vae_info = context.services.model_records.load_model(
+            **self.vae.vae.model_dump(),
+            context=context,
+        )
 
         image_tensor = image_resized_to_grid_as_tensor(image.convert("RGB"))
         if image_tensor.dim() == 3:
diff --git a/invokeai/app/invocations/model.py b/invokeai/app/invocations/model.py
index 6a1fd6d36b..e2ea744283 100644
--- a/invokeai/app/invocations/model.py
+++ b/invokeai/app/invocations/model.py
@@ -1,13 +1,13 @@
 import copy
 from typing import List, Optional
 
-from pydantic import BaseModel, ConfigDict, Field
+from pydantic import BaseModel, Field
 
 from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.app.shared.models import FreeUConfig
 
-from ...backend.model_management import BaseModelType, ModelType, SubModelType
+from ...backend.model_manager import SubModelType
 from .baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
@@ -17,13 +17,9 @@ from .baseinvocation import (
 
 
 class ModelInfo(BaseModel):
-    model_name: str = Field(description="Info to load submodel")
-    base_model: BaseModelType = Field(description="Base model")
-    model_type: ModelType = Field(description="Info to load submodel")
+    key: str = Field(description="Info to load submodel")
     submodel: Optional[SubModelType] = Field(default=None, description="Info to load submodel")
 
-    model_config = ConfigDict(protected_namespaces=())
-
 
 class LoraInfo(ModelInfo):
     weight: float = Field(description="Lora's weight which to use when apply to model")
@@ -52,7 +48,7 @@ class VaeField(BaseModel):
 
 @invocation_output("unet_output")
 class UNetOutput(BaseInvocationOutput):
-    """Base class for invocations that output a UNet field"""
+    """Base class for invocations that output a UNet field."""
 
     unet: UNetField = OutputField(description=FieldDescriptions.unet, title="UNet")
 
@@ -81,20 +77,13 @@ class ModelLoaderOutput(UNetOutput, CLIPOutput, VAEOutput):
 class MainModelField(BaseModel):
     """Main model field"""
 
-    model_name: str = Field(description="Name of the model")
-    base_model: BaseModelType = Field(description="Base model")
-    model_type: ModelType = Field(description="Model Type")
-
-    model_config = ConfigDict(protected_namespaces=())
+    key: str = Field(description="Model key")
 
 
 class LoRAModelField(BaseModel):
     """LoRA model field"""
 
-    model_name: str = Field(description="Name of the LoRA model")
-    base_model: BaseModelType = Field(description="Base model")
-
-    model_config = ConfigDict(protected_namespaces=())
+    key: str = Field(description="LoRA model key")
 
 
 @invocation(
@@ -111,74 +100,31 @@ class MainModelLoaderInvocation(BaseInvocation):
     # TODO: precision?
 
     def invoke(self, context: InvocationContext) -> ModelLoaderOutput:
-        base_model = self.model.base_model
-        model_name = self.model.model_name
-        model_type = ModelType.Main
+        key = self.model.key
 
         # TODO: not found exceptions
-        if not context.models.exists(
-            model_name=model_name,
-            base_model=base_model,
-            model_type=model_type,
-        ):
-            raise Exception(f"Unknown {base_model} {model_type} model: {model_name}")
-
-        """
-        if not context.services.model_manager.model_exists(
-            model_name=self.model_name,
-            model_type=SDModelType.Diffusers,
-            submodel=SDModelType.Tokenizer,
-        ):
-            raise Exception(
-                f"Failed to find tokenizer submodel in {self.model_name}! Check if model corrupted"
-            )
-
-        if not context.services.model_manager.model_exists(
-            model_name=self.model_name,
-            model_type=SDModelType.Diffusers,
-            submodel=SDModelType.TextEncoder,
-        ):
-            raise Exception(
-                f"Failed to find text_encoder submodel in {self.model_name}! Check if model corrupted"
-            )
-
-        if not context.services.model_manager.model_exists(
-            model_name=self.model_name,
-            model_type=SDModelType.Diffusers,
-            submodel=SDModelType.UNet,
-        ):
-            raise Exception(
-                f"Failed to find unet submodel from {self.model_name}! Check if model corrupted"
-            )
-        """
+        if not context.services.model_records.exists(key):
+            raise Exception(f"Unknown model {key}")
 
         return ModelLoaderOutput(
             unet=UNetField(
                 unet=ModelInfo(
-                    model_name=model_name,
-                    base_model=base_model,
-                    model_type=model_type,
+                    key=key,
                     submodel=SubModelType.UNet,
                 ),
                 scheduler=ModelInfo(
-                    model_name=model_name,
-                    base_model=base_model,
-                    model_type=model_type,
+                    key=key,
                     submodel=SubModelType.Scheduler,
                 ),
                 loras=[],
             ),
             clip=ClipField(
                 tokenizer=ModelInfo(
-                    model_name=model_name,
-                    base_model=base_model,
-                    model_type=model_type,
+                    key=key,
                     submodel=SubModelType.Tokenizer,
                 ),
                 text_encoder=ModelInfo(
-                    model_name=model_name,
-                    base_model=base_model,
-                    model_type=model_type,
+                    key=key,
                     submodel=SubModelType.TextEncoder,
                 ),
                 loras=[],
@@ -186,9 +132,7 @@ class MainModelLoaderInvocation(BaseInvocation):
             ),
             vae=VaeField(
                 vae=ModelInfo(
-                    model_name=model_name,
-                    base_model=base_model,
-                    model_type=model_type,
+                    key=key,
                     submodel=SubModelType.Vae,
                 ),
             ),
@@ -226,21 +170,16 @@ class LoraLoaderInvocation(BaseInvocation):
         if self.lora is None:
             raise Exception("No LoRA provided")
 
-        base_model = self.lora.base_model
-        lora_name = self.lora.model_name
+        lora_key = self.lora.key
 
-        if not context.models.exists(
-            base_model=base_model,
-            model_name=lora_name,
-            model_type=ModelType.Lora,
-        ):
-            raise Exception(f"Unkown lora name: {lora_name}!")
+        if not context.services.model_records.exists(lora_key):
+            raise Exception(f"Unkown lora: {lora_key}!")
 
-        if self.unet is not None and any(lora.model_name == lora_name for lora in self.unet.loras):
-            raise Exception(f'Lora "{lora_name}" already applied to unet')
+        if self.unet is not None and any(lora.key == lora_key for lora in self.unet.loras):
+            raise Exception(f'Lora "{lora_key}" already applied to unet')
 
-        if self.clip is not None and any(lora.model_name == lora_name for lora in self.clip.loras):
-            raise Exception(f'Lora "{lora_name}" already applied to clip')
+        if self.clip is not None and any(lora.key == lora_key for lora in self.clip.loras):
+            raise Exception(f'Lora "{lora_key}" already applied to clip')
 
         output = LoraLoaderOutput()
 
@@ -248,9 +187,7 @@ class LoraLoaderInvocation(BaseInvocation):
             output.unet = copy.deepcopy(self.unet)
             output.unet.loras.append(
                 LoraInfo(
-                    base_model=base_model,
-                    model_name=lora_name,
-                    model_type=ModelType.Lora,
+                    key=lora_key,
                     submodel=None,
                     weight=self.weight,
                 )
@@ -260,9 +197,7 @@ class LoraLoaderInvocation(BaseInvocation):
             output.clip = copy.deepcopy(self.clip)
             output.clip.loras.append(
                 LoraInfo(
-                    base_model=base_model,
-                    model_name=lora_name,
-                    model_type=ModelType.Lora,
+                    key=lora_key,
                     submodel=None,
                     weight=self.weight,
                 )
@@ -315,24 +250,19 @@ class SDXLLoraLoaderInvocation(BaseInvocation):
         if self.lora is None:
             raise Exception("No LoRA provided")
 
-        base_model = self.lora.base_model
-        lora_name = self.lora.model_name
+        lora_key = self.lora.key
 
-        if not context.models.exists(
-            base_model=base_model,
-            model_name=lora_name,
-            model_type=ModelType.Lora,
-        ):
-            raise Exception(f"Unknown lora name: {lora_name}!")
+        if not context.services.model_records.exists(lora_key):
+            raise Exception(f"Unknown lora: {lora_key}!")
 
-        if self.unet is not None and any(lora.model_name == lora_name for lora in self.unet.loras):
-            raise Exception(f'Lora "{lora_name}" already applied to unet')
+        if self.unet is not None and any(lora.key == lora_key for lora in self.unet.loras):
+            raise Exception(f'Lora "{lora_key}" already applied to unet')
 
-        if self.clip is not None and any(lora.model_name == lora_name for lora in self.clip.loras):
-            raise Exception(f'Lora "{lora_name}" already applied to clip')
+        if self.clip is not None and any(lora.key == lora_key for lora in self.clip.loras):
+            raise Exception(f'Lora "{lora_key}" already applied to clip')
 
-        if self.clip2 is not None and any(lora.model_name == lora_name for lora in self.clip2.loras):
-            raise Exception(f'Lora "{lora_name}" already applied to clip2')
+        if self.clip2 is not None and any(lora.key == lora_key for lora in self.clip2.loras):
+            raise Exception(f'Lora "{lora_key}" already applied to clip2')
 
         output = SDXLLoraLoaderOutput()
 
@@ -340,9 +270,7 @@ class SDXLLoraLoaderInvocation(BaseInvocation):
             output.unet = copy.deepcopy(self.unet)
             output.unet.loras.append(
                 LoraInfo(
-                    base_model=base_model,
-                    model_name=lora_name,
-                    model_type=ModelType.Lora,
+                    key=lora_key,
                     submodel=None,
                     weight=self.weight,
                 )
@@ -352,9 +280,7 @@ class SDXLLoraLoaderInvocation(BaseInvocation):
             output.clip = copy.deepcopy(self.clip)
             output.clip.loras.append(
                 LoraInfo(
-                    base_model=base_model,
-                    model_name=lora_name,
-                    model_type=ModelType.Lora,
+                    key=lora_key,
                     submodel=None,
                     weight=self.weight,
                 )
@@ -364,9 +290,7 @@ class SDXLLoraLoaderInvocation(BaseInvocation):
             output.clip2 = copy.deepcopy(self.clip2)
             output.clip2.loras.append(
                 LoraInfo(
-                    base_model=base_model,
-                    model_name=lora_name,
-                    model_type=ModelType.Lora,
+                    key=lora_key,
                     submodel=None,
                     weight=self.weight,
                 )
@@ -378,10 +302,7 @@ class SDXLLoraLoaderInvocation(BaseInvocation):
 class VAEModelField(BaseModel):
     """Vae model field"""
 
-    model_name: str = Field(description="Name of the model")
-    base_model: BaseModelType = Field(description="Base model")
-
-    model_config = ConfigDict(protected_namespaces=())
+    key: str = Field(description="Model's key")
 
 
 @invocation("vae_loader", title="VAE", tags=["vae", "model"], category="model", version="1.0.1")
@@ -395,25 +316,12 @@ class VaeLoaderInvocation(BaseInvocation):
     )
 
     def invoke(self, context: InvocationContext) -> VAEOutput:
-        base_model = self.vae_model.base_model
-        model_name = self.vae_model.model_name
-        model_type = ModelType.Vae
+        key = self.vae_model.key
 
-        if not context.models.exists(
-            base_model=base_model,
-            model_name=model_name,
-            model_type=model_type,
-        ):
-            raise Exception(f"Unkown vae name: {model_name}!")
-        return VAEOutput(
-            vae=VaeField(
-                vae=ModelInfo(
-                    model_name=model_name,
-                    base_model=base_model,
-                    model_type=model_type,
-                )
-            )
-        )
+        if not context.services.model_records.exists(key):
+            raise Exception(f"Unkown vae: {key}!")
+
+        return VAEOutput(vae=VaeField(vae=ModelInfo(key=key)))
 
 
 @invocation_output("seamless_output")
diff --git a/invokeai/app/invocations/sdxl.py b/invokeai/app/invocations/sdxl.py
index 8d51674a04..633a6477fd 100644
--- a/invokeai/app/invocations/sdxl.py
+++ b/invokeai/app/invocations/sdxl.py
@@ -1,7 +1,7 @@
 from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField, UIType
 from invokeai.app.services.shared.invocation_context import InvocationContext
+from invokeai.backend.model_manager import SubModelType
 
-from ...backend.model_management import ModelType, SubModelType
 from .baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
@@ -40,45 +40,31 @@ class SDXLModelLoaderInvocation(BaseInvocation):
     # TODO: precision?
 
     def invoke(self, context: InvocationContext) -> SDXLModelLoaderOutput:
-        base_model = self.model.base_model
-        model_name = self.model.model_name
-        model_type = ModelType.Main
+        model_key = self.model.key
 
         # TODO: not found exceptions
-        if not context.models.exists(
-            model_name=model_name,
-            base_model=base_model,
-            model_type=model_type,
-        ):
-            raise Exception(f"Unknown {base_model} {model_type} model: {model_name}")
+        if not context.services.model_records.exists(model_key):
+            raise Exception(f"Unknown model: {model_key}")
 
         return SDXLModelLoaderOutput(
             unet=UNetField(
                 unet=ModelInfo(
-                    model_name=model_name,
-                    base_model=base_model,
-                    model_type=model_type,
+                    key=model_key,
                     submodel=SubModelType.UNet,
                 ),
                 scheduler=ModelInfo(
-                    model_name=model_name,
-                    base_model=base_model,
-                    model_type=model_type,
+                    key=model_key,
                     submodel=SubModelType.Scheduler,
                 ),
                 loras=[],
             ),
             clip=ClipField(
                 tokenizer=ModelInfo(
-                    model_name=model_name,
-                    base_model=base_model,
-                    model_type=model_type,
+                    key=model_key,
                     submodel=SubModelType.Tokenizer,
                 ),
                 text_encoder=ModelInfo(
-                    model_name=model_name,
-                    base_model=base_model,
-                    model_type=model_type,
+                    key=model_key,
                     submodel=SubModelType.TextEncoder,
                 ),
                 loras=[],
@@ -86,15 +72,11 @@ class SDXLModelLoaderInvocation(BaseInvocation):
             ),
             clip2=ClipField(
                 tokenizer=ModelInfo(
-                    model_name=model_name,
-                    base_model=base_model,
-                    model_type=model_type,
+                    key=model_key,
                     submodel=SubModelType.Tokenizer2,
                 ),
                 text_encoder=ModelInfo(
-                    model_name=model_name,
-                    base_model=base_model,
-                    model_type=model_type,
+                    key=model_key,
                     submodel=SubModelType.TextEncoder2,
                 ),
                 loras=[],
@@ -102,9 +84,7 @@ class SDXLModelLoaderInvocation(BaseInvocation):
             ),
             vae=VaeField(
                 vae=ModelInfo(
-                    model_name=model_name,
-                    base_model=base_model,
-                    model_type=model_type,
+                    key=model_key,
                     submodel=SubModelType.Vae,
                 ),
             ),
@@ -129,45 +109,31 @@ class SDXLRefinerModelLoaderInvocation(BaseInvocation):
     # TODO: precision?
 
     def invoke(self, context: InvocationContext) -> SDXLRefinerModelLoaderOutput:
-        base_model = self.model.base_model
-        model_name = self.model.model_name
-        model_type = ModelType.Main
+        model_key = self.model.key
 
         # TODO: not found exceptions
-        if not context.models.exists(
-            model_name=model_name,
-            base_model=base_model,
-            model_type=model_type,
-        ):
-            raise Exception(f"Unknown {base_model} {model_type} model: {model_name}")
+        if not context.services.model_records.exists(model_key):
+            raise Exception(f"Unknown model: {model_key}")
 
         return SDXLRefinerModelLoaderOutput(
             unet=UNetField(
                 unet=ModelInfo(
-                    model_name=model_name,
-                    base_model=base_model,
-                    model_type=model_type,
+                    key=model_key,
                     submodel=SubModelType.UNet,
                 ),
                 scheduler=ModelInfo(
-                    model_name=model_name,
-                    base_model=base_model,
-                    model_type=model_type,
+                    key=model_key,
                     submodel=SubModelType.Scheduler,
                 ),
                 loras=[],
             ),
             clip2=ClipField(
                 tokenizer=ModelInfo(
-                    model_name=model_name,
-                    base_model=base_model,
-                    model_type=model_type,
+                    key=model_key,
                     submodel=SubModelType.Tokenizer2,
                 ),
                 text_encoder=ModelInfo(
-                    model_name=model_name,
-                    base_model=base_model,
-                    model_type=model_type,
+                    key=model_key,
                     submodel=SubModelType.TextEncoder2,
                 ),
                 loras=[],
@@ -175,9 +141,7 @@ class SDXLRefinerModelLoaderInvocation(BaseInvocation):
             ),
             vae=VaeField(
                 vae=ModelInfo(
-                    model_name=model_name,
-                    base_model=base_model,
-                    model_type=model_type,
+                    key=model_key,
                     submodel=SubModelType.Vae,
                 ),
             ),
diff --git a/invokeai/app/invocations/t2i_adapter.py b/invokeai/app/invocations/t2i_adapter.py
index 0f4fe66ada..0f1e251bb3 100644
--- a/invokeai/app/invocations/t2i_adapter.py
+++ b/invokeai/app/invocations/t2i_adapter.py
@@ -1,6 +1,6 @@
 from typing import Union
 
-from pydantic import BaseModel, ConfigDict, Field, field_validator, model_validator
+from pydantic import BaseModel, Field, field_validator, model_validator
 
 from invokeai.app.invocations.baseinvocation import (
     BaseInvocation,
@@ -12,14 +12,10 @@ from invokeai.app.invocations.controlnet_image_processors import CONTROLNET_RESI
 from invokeai.app.invocations.fields import FieldDescriptions, ImageField, Input, InputField, OutputField
 from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
 from invokeai.app.services.shared.invocation_context import InvocationContext
-from invokeai.backend.model_management.models.base import BaseModelType
 
 
 class T2IAdapterModelField(BaseModel):
-    model_name: str = Field(description="Name of the T2I-Adapter model")
-    base_model: BaseModelType = Field(description="Base model")
-
-    model_config = ConfigDict(protected_namespaces=())
+    key: str = Field(description="Model record key for the T2I-Adapter model")
 
 
 class T2IAdapterField(BaseModel):
diff --git a/invokeai/app/services/events/events_base.py b/invokeai/app/services/events/events_base.py
index 6b441efc2b..90d9068b88 100644
--- a/invokeai/app/services/events/events_base.py
+++ b/invokeai/app/services/events/events_base.py
@@ -11,8 +11,7 @@ from invokeai.app.services.session_queue.session_queue_common import (
     SessionQueueStatus,
 )
 from invokeai.app.util.misc import get_timestamp
-from invokeai.backend.model_management.model_manager import LoadedModelInfo
-from invokeai.backend.model_management.models.base import BaseModelType, ModelType, SubModelType
+from invokeai.backend.model_manager import AnyModelConfig
 
 
 class EventServiceBase:
@@ -171,10 +170,7 @@ class EventServiceBase:
         queue_item_id: int,
         queue_batch_id: str,
         graph_execution_state_id: str,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-        submodel: SubModelType,
+        model_config: AnyModelConfig,
     ) -> None:
         """Emitted when a model is requested"""
         self.__emit_queue_event(
@@ -184,10 +180,7 @@ class EventServiceBase:
                 "queue_item_id": queue_item_id,
                 "queue_batch_id": queue_batch_id,
                 "graph_execution_state_id": graph_execution_state_id,
-                "model_name": model_name,
-                "base_model": base_model,
-                "model_type": model_type,
-                "submodel": submodel,
+                "model_config": model_config.model_dump(),
             },
         )
 
@@ -197,11 +190,7 @@ class EventServiceBase:
         queue_item_id: int,
         queue_batch_id: str,
         graph_execution_state_id: str,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-        submodel: SubModelType,
-        loaded_model_info: LoadedModelInfo,
+        model_config: AnyModelConfig,
     ) -> None:
         """Emitted when a model is correctly loaded (returns model info)"""
         self.__emit_queue_event(
@@ -211,13 +200,7 @@ class EventServiceBase:
                 "queue_item_id": queue_item_id,
                 "queue_batch_id": queue_batch_id,
                 "graph_execution_state_id": graph_execution_state_id,
-                "model_name": model_name,
-                "base_model": base_model,
-                "model_type": model_type,
-                "submodel": submodel,
-                "hash": loaded_model_info.hash,
-                "location": str(loaded_model_info.location),
-                "precision": str(loaded_model_info.precision),
+                "model_config": model_config.model_dump(),
             },
         )
 
diff --git a/invokeai/app/services/invocation_stats/invocation_stats_default.py b/invokeai/app/services/invocation_stats/invocation_stats_default.py
index be58aaad2d..0c63b545ff 100644
--- a/invokeai/app/services/invocation_stats/invocation_stats_default.py
+++ b/invokeai/app/services/invocation_stats/invocation_stats_default.py
@@ -2,6 +2,7 @@ import json
 import time
 from contextlib import contextmanager
 from pathlib import Path
+from typing import Iterator
 
 import psutil
 import torch
@@ -10,7 +11,7 @@ import invokeai.backend.util.logging as logger
 from invokeai.app.invocations.baseinvocation import BaseInvocation
 from invokeai.app.services.invoker import Invoker
 from invokeai.app.services.item_storage.item_storage_common import ItemNotFoundError
-from invokeai.backend.model_management.model_cache import CacheStats
+from invokeai.backend.model_manager.load.model_cache import CacheStats
 
 from .invocation_stats_base import InvocationStatsServiceBase
 from .invocation_stats_common import (
@@ -41,7 +42,10 @@ class InvocationStatsService(InvocationStatsServiceBase):
         self._invoker = invoker
 
     @contextmanager
-    def collect_stats(self, invocation: BaseInvocation, graph_execution_state_id: str):
+    def collect_stats(self, invocation: BaseInvocation, graph_execution_state_id: str) -> Iterator[None]:
+        services = self._invoker.services
+        if services.model_records is None or services.model_records.loader is None:
+            yield None
         if not self._stats.get(graph_execution_state_id):
             # First time we're seeing this graph_execution_state_id.
             self._stats[graph_execution_state_id] = GraphExecutionStats()
@@ -55,8 +59,10 @@ class InvocationStatsService(InvocationStatsServiceBase):
         start_ram = psutil.Process().memory_info().rss
         if torch.cuda.is_available():
             torch.cuda.reset_peak_memory_stats()
-        if self._invoker.services.model_manager:
-            self._invoker.services.model_manager.collect_cache_stats(self._cache_stats[graph_execution_state_id])
+
+        # TO DO [LS]: clean up loader service - shouldn't be an attribute of model records
+        assert services.model_records.loader is not None
+        services.model_records.loader.ram_cache.stats = self._cache_stats[graph_execution_state_id]
 
         try:
             # Let the invocation run.
@@ -73,7 +79,7 @@ class InvocationStatsService(InvocationStatsServiceBase):
             )
             self._stats[graph_execution_state_id].add_node_execution_stats(node_stats)
 
-    def _prune_stale_stats(self):
+    def _prune_stale_stats(self) -> None:
         """Check all graphs being tracked and prune any that have completed/errored.
 
         This shouldn't be necessary, but we don't have totally robust upstream handling of graph completions/errors, so
diff --git a/invokeai/app/services/model_records/model_records_base.py b/invokeai/app/services/model_records/model_records_base.py
index 42e3c8f83a..e00dd4169d 100644
--- a/invokeai/app/services/model_records/model_records_base.py
+++ b/invokeai/app/services/model_records/model_records_base.py
@@ -10,6 +10,7 @@ from typing import Any, Dict, List, Optional, Set, Tuple, Union
 
 from pydantic import BaseModel, Field
 
+from invokeai.app.invocations.baseinvocation import InvocationContext
 from invokeai.app.services.shared.pagination import PaginatedResults
 from invokeai.backend.model_manager import (
     AnyModelConfig,
@@ -19,6 +20,7 @@ from invokeai.backend.model_manager import (
     ModelType,
     SubModelType,
 )
+from invokeai.backend.model_manager.load import AnyModelLoader
 from invokeai.backend.model_manager.metadata import AnyModelRepoMetadata, ModelMetadataStore
 
 
@@ -110,12 +112,45 @@ class ModelRecordServiceBase(ABC):
         pass
 
     @abstractmethod
-    def load_model(self, key: str, submodel_type: Optional[SubModelType]) -> LoadedModel:
+    def load_model(
+        self,
+        key: str,
+        submodel: Optional[SubModelType] = None,
+        context: Optional[InvocationContext] = None,
+    ) -> LoadedModel:
         """
         Load the indicated model into memory and return a LoadedModel object.
 
         :param key: Key of model config to be fetched.
-        :param submodel_type: For main (pipeline models), the submodel to fetch
+        :param submodel: For main (pipeline models), the submodel to fetch
+        :param context: Invocation context, used for event issuing.
+
+        Exceptions: UnknownModelException -- model with this key not known
+                    NotImplementedException -- a model loader was not provided at initialization time
+        """
+        pass
+
+    @abstractmethod
+    def load_model_by_attr(
+        self,
+        model_name: str,
+        base_model: BaseModelType,
+        model_type: ModelType,
+        submodel: Optional[SubModelType] = None,
+        context: Optional[InvocationContext] = None,
+    ) -> LoadedModel:
+        """
+        Load the indicated model into memory and return a LoadedModel object.
+
+        This is provided for API compatability with the get_model() method
+        in the original model manager. However, note that LoadedModel is
+        not the same as the original ModelInfo that ws returned.
+
+        :param model_name: Key of model config to be fetched.
+        :param base_model: Base model
+        :param model_type: Type of the model
+        :param submodel: For main (pipeline models), the submodel to fetch
+        :param context: The invocation context.
 
         Exceptions: UnknownModelException -- model with this key not known
                     NotImplementedException -- a model loader was not provided at initialization time
@@ -166,7 +201,7 @@ class ModelRecordServiceBase(ABC):
     @abstractmethod
     def exists(self, key: str) -> bool:
         """
-        Return True if a model with the indicated key exists in the databse.
+        Return True if a model with the indicated key exists in the database.
 
         :param key: Unique key for the model to be deleted
         """
@@ -209,6 +244,12 @@ class ModelRecordServiceBase(ABC):
         """
         pass
 
+    @property
+    @abstractmethod
+    def loader(self) -> Optional[AnyModelLoader]:
+        """Return the model loader used by this instance."""
+        pass
+
     def all_models(self) -> List[AnyModelConfig]:
         """Return all the model configs in the database."""
         return self.search_by_attr()
diff --git a/invokeai/app/services/model_records/model_records_sql.py b/invokeai/app/services/model_records/model_records_sql.py
index b50cd17a75..28a77b1b1a 100644
--- a/invokeai/app/services/model_records/model_records_sql.py
+++ b/invokeai/app/services/model_records/model_records_sql.py
@@ -46,6 +46,8 @@ from math import ceil
 from pathlib import Path
 from typing import Any, Dict, List, Optional, Set, Tuple, Union
 
+from invokeai.app.invocations.baseinvocation import InvocationContext
+from invokeai.app.services.invocation_processor.invocation_processor_common import CanceledException
 from invokeai.app.services.shared.pagination import PaginatedResults
 from invokeai.backend.model_manager.config import (
     AnyModelConfig,
@@ -88,6 +90,11 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
         """Return the underlying database."""
         return self._db
 
+    @property
+    def loader(self) -> Optional[AnyModelLoader]:
+        """Return the model loader used by this instance."""
+        return self._loader
+
     def add_model(self, key: str, config: Union[Dict[str, Any], AnyModelConfig]) -> AnyModelConfig:
         """
         Add a model to the database.
@@ -213,20 +220,73 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
             model = ModelConfigFactory.make_config(json.loads(rows[0]), timestamp=rows[1])
         return model
 
-    def load_model(self, key: str, submodel_type: Optional[SubModelType]) -> LoadedModel:
+    def load_model(
+        self,
+        key: str,
+        submodel: Optional[SubModelType],
+        context: Optional[InvocationContext] = None,
+    ) -> LoadedModel:
         """
         Load the indicated model into memory and return a LoadedModel object.
 
         :param key: Key of model config to be fetched.
-        :param submodel_type: For main (pipeline models), the submodel to fetch.
+        :param submodel: For main (pipeline models), the submodel to fetch.
+        :param context: Invocation context used for event reporting
 
         Exceptions: UnknownModelException -- model with this key not known
                     NotImplementedException -- a model loader was not provided at initialization time
         """
         if not self._loader:
             raise NotImplementedError(f"Class {self.__class__} was not initialized with a model loader")
+        # we can emit model loading events if we are executing with access to the invocation context
+
         model_config = self.get_model(key)
-        return self._loader.load_model(model_config, submodel_type)
+        if context:
+            self._emit_load_event(
+                context=context,
+                model_config=model_config,
+            )
+        loaded_model = self._loader.load_model(model_config, submodel)
+        if context:
+            self._emit_load_event(
+                context=context,
+                model_config=model_config,
+                loaded=True,
+            )
+        return loaded_model
+
+    def load_model_by_attr(
+        self,
+        model_name: str,
+        base_model: BaseModelType,
+        model_type: ModelType,
+        submodel: Optional[SubModelType] = None,
+        context: Optional[InvocationContext] = None,
+    ) -> LoadedModel:
+        """
+        Load the indicated model into memory and return a LoadedModel object.
+
+        This is provided for API compatability with the get_model() method
+        in the original model manager. However, note that LoadedModel is
+        not the same as the original ModelInfo that ws returned.
+
+        :param model_name: Key of model config to be fetched.
+        :param base_model: Base model
+        :param model_type: Type of the model
+        :param submodel: For main (pipeline models), the submodel to fetch
+        :param context: The invocation context.
+
+        Exceptions: UnknownModelException -- model with this key not known
+                    NotImplementedException -- a model loader was not provided at initialization time
+                    ValueError -- more than one model matches this combination
+        """
+        configs = self.search_by_attr(model_name, base_model, model_type)
+        if len(configs) == 0:
+            raise UnknownModelException(f"{base_model}/{model_type}/{model_name}: Unknown model")
+        elif len(configs) > 1:
+            raise ValueError(f"{base_model}/{model_type}/{model_name}: More than one model matches.")
+        else:
+            return self.load_model(configs[0].key, submodel)
 
     def exists(self, key: str) -> bool:
         """
@@ -416,3 +476,29 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
             return PaginatedResults(
                 page=page, pages=ceil(total / per_page), per_page=per_page, total=total, items=items
             )
+
+    def _emit_load_event(
+        self,
+        context: InvocationContext,
+        model_config: AnyModelConfig,
+        loaded: Optional[bool] = False,
+    ) -> None:
+        if context.services.queue.is_canceled(context.graph_execution_state_id):
+            raise CanceledException()
+
+        if not loaded:
+            context.services.events.emit_model_load_started(
+                queue_id=context.queue_id,
+                queue_item_id=context.queue_item_id,
+                queue_batch_id=context.queue_batch_id,
+                graph_execution_state_id=context.graph_execution_state_id,
+                model_config=model_config,
+            )
+        else:
+            context.services.events.emit_model_load_completed(
+                queue_id=context.queue_id,
+                queue_item_id=context.queue_item_id,
+                queue_batch_id=context.queue_batch_id,
+                graph_execution_state_id=context.graph_execution_state_id,
+                model_config=model_config,
+            )
diff --git a/invokeai/backend/embeddings/__init__.py b/invokeai/backend/embeddings/__init__.py
new file mode 100644
index 0000000000..46ead533c4
--- /dev/null
+++ b/invokeai/backend/embeddings/__init__.py
@@ -0,0 +1,4 @@
+"""Initialization file for invokeai.backend.embeddings modules."""
+
+# from .model_patcher import ModelPatcher
+# __all__ = ["ModelPatcher"]
diff --git a/invokeai/backend/embeddings/embedding_base.py b/invokeai/backend/embeddings/embedding_base.py
new file mode 100644
index 0000000000..5e752a29e1
--- /dev/null
+++ b/invokeai/backend/embeddings/embedding_base.py
@@ -0,0 +1,12 @@
+"""Base class for LoRA and Textual Inversion models.
+
+The EmbeddingRaw class is the base class of LoRAModelRaw and TextualInversionModelRaw,
+and is used for type checking of calls to the model patcher.
+
+The use of "Raw" here is a historical artifact, and carried forward in
+order to avoid confusion.
+"""
+
+
+class EmbeddingModelRaw:
+    """Base class for LoRA and Textual Inversion models."""
diff --git a/invokeai/backend/embeddings/lora.py b/invokeai/backend/embeddings/lora.py
index 9a59a97708..3c7ef074ef 100644
--- a/invokeai/backend/embeddings/lora.py
+++ b/invokeai/backend/embeddings/lora.py
@@ -11,6 +11,8 @@ from typing_extensions import Self
 
 from invokeai.backend.model_manager import BaseModelType
 
+from .embedding_base import EmbeddingModelRaw
+
 
 class LoRALayerBase:
     # rank: Optional[int]
@@ -317,7 +319,7 @@ class FullLayer(LoRALayerBase):
         self,
         device: Optional[torch.device] = None,
         dtype: Optional[torch.dtype] = None,
-    ):
+    ) -> None:
         super().to(device=device, dtype=dtype)
 
         self.weight = self.weight.to(device=device, dtype=dtype)
@@ -367,7 +369,7 @@ AnyLoRALayer = Union[LoRALayer, LoHALayer, LoKRLayer, FullLayer, IA3Layer]
 
 
 # TODO: rename all methods used in model logic with Info postfix and remove here Raw postfix
-class LoRAModelRaw:  # (torch.nn.Module):
+class LoRAModelRaw(EmbeddingModelRaw):  # (torch.nn.Module):
     _name: str
     layers: Dict[str, AnyLoRALayer]
 
@@ -471,16 +473,16 @@ class LoRAModelRaw:  # (torch.nn.Module):
             file_path = Path(file_path)
 
         model = cls(
-            name=file_path.stem,  # TODO:
+            name=file_path.stem,
             layers={},
         )
 
         if file_path.suffix == ".safetensors":
-            state_dict = load_file(file_path.absolute().as_posix(), device="cpu")
+            sd = load_file(file_path.absolute().as_posix(), device="cpu")
         else:
-            state_dict = torch.load(file_path, map_location="cpu")
+            sd = torch.load(file_path, map_location="cpu")
 
-        state_dict = cls._group_state(state_dict)
+        state_dict = cls._group_state(sd)
 
         if base_model == BaseModelType.StableDiffusionXL:
             state_dict = cls._convert_sdxl_keys_to_diffusers_format(state_dict)
diff --git a/invokeai/backend/embeddings/model_patcher.py b/invokeai/backend/embeddings/model_patcher.py
index 6d73235197..4725181b8e 100644
--- a/invokeai/backend/embeddings/model_patcher.py
+++ b/invokeai/backend/embeddings/model_patcher.py
@@ -4,22 +4,20 @@ from __future__ import annotations
 
 import pickle
 from contextlib import contextmanager
-from pathlib import Path
-from typing import Any, Dict, Generator, List, Optional, Tuple, Union
+from typing import Any, Dict, Iterator, List, Optional, Tuple
 
 import numpy as np
 import torch
-from compel.embeddings_provider import BaseTextualInversionManager
-from diffusers import ModelMixin, OnnxRuntimeModel, UNet2DConditionModel
-from safetensors.torch import load_file
+from diffusers import OnnxRuntimeModel, UNet2DConditionModel
 from transformers import CLIPTextModel, CLIPTokenizer
-from typing_extensions import Self
 
 from invokeai.app.shared.models import FreeUConfig
+from invokeai.backend.model_manager import AnyModel
 from invokeai.backend.model_manager.load.optimizations import skip_torch_weight_init
 from invokeai.backend.onnx.onnx_runtime import IAIOnnxRuntimeModel
 
 from .lora import LoRAModelRaw
+from .textual_inversion import TextualInversionManager, TextualInversionModelRaw
 
 """
 loras = [
@@ -67,7 +65,7 @@ class ModelPatcher:
         cls,
         unet: UNet2DConditionModel,
         loras: List[Tuple[LoRAModelRaw, float]],
-    ) -> Generator[None, None, None]:
+    ) -> None:
         with cls.apply_lora(unet, loras, "lora_unet_"):
             yield
 
@@ -76,8 +74,8 @@ class ModelPatcher:
     def apply_lora_text_encoder(
         cls,
         text_encoder: CLIPTextModel,
-        loras: List[Tuple[LoRAModelRaw, float]],
-    ):
+        loras: Iterator[Tuple[LoRAModelRaw, float]],
+    ) -> None:
         with cls.apply_lora(text_encoder, loras, "lora_te_"):
             yield
 
@@ -87,7 +85,7 @@ class ModelPatcher:
         cls,
         text_encoder: CLIPTextModel,
         loras: List[Tuple[LoRAModelRaw, float]],
-    ):
+    ) -> None:
         with cls.apply_lora(text_encoder, loras, "lora_te1_"):
             yield
 
@@ -97,7 +95,7 @@ class ModelPatcher:
         cls,
         text_encoder: CLIPTextModel,
         loras: List[Tuple[LoRAModelRaw, float]],
-    ):
+    ) -> None:
         with cls.apply_lora(text_encoder, loras, "lora_te2_"):
             yield
 
@@ -105,10 +103,10 @@ class ModelPatcher:
     @contextmanager
     def apply_lora(
         cls,
-        model: Union[torch.nn.Module, ModelMixin, UNet2DConditionModel],
-        loras: List[Tuple[LoRAModelRaw, float]],
+        model: AnyModel,
+        loras: Iterator[Tuple[LoRAModelRaw, float]],
         prefix: str,
-    ) -> Generator[None, None, None]:
+    ) -> None:
         original_weights = {}
         try:
             with torch.no_grad():
@@ -125,6 +123,7 @@ class ModelPatcher:
                         # 2. From an API perspective, there's no reason that the `ModelPatcher` should be aware of the
                         #    intricacies of Stable Diffusion key resolution. It should just expect the input LoRA
                         #    weights to have valid keys.
+                        assert isinstance(model, torch.nn.Module)
                         module_key, module = cls._resolve_lora_key(model, layer_key, prefix)
 
                         # All of the LoRA weight calculations will be done on the same device as the module weight.
@@ -170,8 +169,8 @@ class ModelPatcher:
         cls,
         tokenizer: CLIPTokenizer,
         text_encoder: CLIPTextModel,
-        ti_list: List[Tuple[str, TextualInversionModel]],
-    ) -> Generator[Tuple[CLIPTokenizer, TextualInversionManager], None, None]:
+        ti_list: List[Tuple[str, TextualInversionModelRaw]],
+    ) -> Iterator[Tuple[CLIPTokenizer, TextualInversionManager]]:
         init_tokens_count = None
         new_tokens_added = None
 
@@ -201,7 +200,7 @@ class ModelPatcher:
                     trigger += f"-!pad-{i}"
                 return f"<{trigger}>"
 
-            def _get_ti_embedding(model_embeddings: torch.nn.Module, ti: TextualInversionModel) -> torch.Tensor:
+            def _get_ti_embedding(model_embeddings: torch.nn.Module, ti: TextualInversionModelRaw) -> torch.Tensor:
                 # for SDXL models, select the embedding that matches the text encoder's dimensions
                 if ti.embedding_2 is not None:
                     return (
@@ -229,6 +228,7 @@ class ModelPatcher:
             model_embeddings = text_encoder.get_input_embeddings()
 
             for ti_name, ti in ti_list:
+                assert isinstance(ti, TextualInversionModelRaw)
                 ti_embedding = _get_ti_embedding(text_encoder.get_input_embeddings(), ti)
 
                 ti_tokens = []
@@ -267,7 +267,7 @@ class ModelPatcher:
         cls,
         text_encoder: CLIPTextModel,
         clip_skip: int,
-    ) -> Generator[None, None, None]:
+    ) -> None:
         skipped_layers = []
         try:
             for _i in range(clip_skip):
@@ -285,7 +285,7 @@ class ModelPatcher:
         cls,
         unet: UNet2DConditionModel,
         freeu_config: Optional[FreeUConfig] = None,
-    ) -> Generator[None, None, None]:
+    ) -> None:
         did_apply_freeu = False
         try:
             assert hasattr(unet, "enable_freeu")  # mypy doesn't pick up this attribute?
@@ -301,94 +301,6 @@ class ModelPatcher:
                 unet.disable_freeu()
 
 
-class TextualInversionModel:
-    embedding: torch.Tensor  # [n, 768]|[n, 1280]
-    embedding_2: Optional[torch.Tensor] = None  # [n, 768]|[n, 1280]   - for SDXL models
-
-    @classmethod
-    def from_checkpoint(
-        cls,
-        file_path: Union[str, Path],
-        device: Optional[torch.device] = None,
-        dtype: Optional[torch.dtype] = None,
-    ) -> Self:
-        if not isinstance(file_path, Path):
-            file_path = Path(file_path)
-
-        result = cls()  # TODO:
-
-        if file_path.suffix == ".safetensors":
-            state_dict = load_file(file_path.absolute().as_posix(), device="cpu")
-        else:
-            state_dict = torch.load(file_path, map_location="cpu")
-
-        # both v1 and v2 format embeddings
-        # difference mostly in metadata
-        if "string_to_param" in state_dict:
-            if len(state_dict["string_to_param"]) > 1:
-                print(
-                    f'Warn: Embedding "{file_path.name}" contains multiple tokens, which is not supported. The first',
-                    " token will be used.",
-                )
-
-            result.embedding = next(iter(state_dict["string_to_param"].values()))
-
-        # v3 (easynegative)
-        elif "emb_params" in state_dict:
-            result.embedding = state_dict["emb_params"]
-
-        # v5(sdxl safetensors file)
-        elif "clip_g" in state_dict and "clip_l" in state_dict:
-            result.embedding = state_dict["clip_g"]
-            result.embedding_2 = state_dict["clip_l"]
-
-        # v4(diffusers bin files)
-        else:
-            result.embedding = next(iter(state_dict.values()))
-
-            if len(result.embedding.shape) == 1:
-                result.embedding = result.embedding.unsqueeze(0)
-
-            if not isinstance(result.embedding, torch.Tensor):
-                raise ValueError(f"Invalid embeddings file: {file_path.name}")
-
-        return result
-
-
-# no type hints for BaseTextualInversionManager?
-class TextualInversionManager(BaseTextualInversionManager):  # type: ignore
-    pad_tokens: Dict[int, List[int]]
-    tokenizer: CLIPTokenizer
-
-    def __init__(self, tokenizer: CLIPTokenizer):
-        self.pad_tokens = {}
-        self.tokenizer = tokenizer
-
-    def expand_textual_inversion_token_ids_if_necessary(self, token_ids: list[int]) -> list[int]:
-        if len(self.pad_tokens) == 0:
-            return token_ids
-
-        if token_ids[0] == self.tokenizer.bos_token_id:
-            raise ValueError("token_ids must not start with bos_token_id")
-        if token_ids[-1] == self.tokenizer.eos_token_id:
-            raise ValueError("token_ids must not end with eos_token_id")
-
-        new_token_ids = []
-        for token_id in token_ids:
-            new_token_ids.append(token_id)
-            if token_id in self.pad_tokens:
-                new_token_ids.extend(self.pad_tokens[token_id])
-
-        # Do not exceed the max model input size
-        # The -2 here is compensating for compensate compel.embeddings_provider.get_token_ids(),
-        # which first removes and then adds back the start and end tokens.
-        max_length = list(self.tokenizer.max_model_input_sizes.values())[0] - 2
-        if len(new_token_ids) > max_length:
-            new_token_ids = new_token_ids[0:max_length]
-
-        return new_token_ids
-
-
 class ONNXModelPatcher:
     @classmethod
     @contextmanager
@@ -396,7 +308,7 @@ class ONNXModelPatcher:
         cls,
         unet: OnnxRuntimeModel,
         loras: List[Tuple[LoRAModelRaw, float]],
-    ) -> Generator[None, None, None]:
+    ) -> None:
         with cls.apply_lora(unet, loras, "lora_unet_"):
             yield
 
@@ -406,7 +318,7 @@ class ONNXModelPatcher:
         cls,
         text_encoder: OnnxRuntimeModel,
         loras: List[Tuple[LoRAModelRaw, float]],
-    ) -> Generator[None, None, None]:
+    ) -> None:
         with cls.apply_lora(text_encoder, loras, "lora_te_"):
             yield
 
@@ -419,7 +331,7 @@ class ONNXModelPatcher:
         model: IAIOnnxRuntimeModel,
         loras: List[Tuple[LoRAModelRaw, float]],
         prefix: str,
-    ) -> Generator[None, None, None]:
+    ) -> None:
         from .models.base import IAIOnnxRuntimeModel
 
         if not isinstance(model, IAIOnnxRuntimeModel):
@@ -506,7 +418,7 @@ class ONNXModelPatcher:
         tokenizer: CLIPTokenizer,
         text_encoder: IAIOnnxRuntimeModel,
         ti_list: List[Tuple[str, Any]],
-    ) -> Generator[Tuple[CLIPTokenizer, TextualInversionManager], None, None]:
+    ) -> Iterator[Tuple[CLIPTokenizer, TextualInversionManager]]:
         from .models.base import IAIOnnxRuntimeModel
 
         if not isinstance(text_encoder, IAIOnnxRuntimeModel):
diff --git a/invokeai/backend/embeddings/textual_inversion.py b/invokeai/backend/embeddings/textual_inversion.py
new file mode 100644
index 0000000000..389edff039
--- /dev/null
+++ b/invokeai/backend/embeddings/textual_inversion.py
@@ -0,0 +1,100 @@
+"""Textual Inversion wrapper class."""
+
+from pathlib import Path
+from typing import Dict, List, Optional, Union
+
+import torch
+from compel.embeddings_provider import BaseTextualInversionManager
+from safetensors.torch import load_file
+from transformers import CLIPTokenizer
+from typing_extensions import Self
+
+from .embedding_base import EmbeddingModelRaw
+
+
+class TextualInversionModelRaw(EmbeddingModelRaw):
+    embedding: torch.Tensor  # [n, 768]|[n, 1280]
+    embedding_2: Optional[torch.Tensor] = None  # [n, 768]|[n, 1280]   - for SDXL models
+
+    @classmethod
+    def from_checkpoint(
+        cls,
+        file_path: Union[str, Path],
+        device: Optional[torch.device] = None,
+        dtype: Optional[torch.dtype] = None,
+    ) -> Self:
+        if not isinstance(file_path, Path):
+            file_path = Path(file_path)
+
+        result = cls()  # TODO:
+
+        if file_path.suffix == ".safetensors":
+            state_dict = load_file(file_path.absolute().as_posix(), device="cpu")
+        else:
+            state_dict = torch.load(file_path, map_location="cpu")
+
+        # both v1 and v2 format embeddings
+        # difference mostly in metadata
+        if "string_to_param" in state_dict:
+            if len(state_dict["string_to_param"]) > 1:
+                print(
+                    f'Warn: Embedding "{file_path.name}" contains multiple tokens, which is not supported. The first',
+                    " token will be used.",
+                )
+
+            result.embedding = next(iter(state_dict["string_to_param"].values()))
+
+        # v3 (easynegative)
+        elif "emb_params" in state_dict:
+            result.embedding = state_dict["emb_params"]
+
+        # v5(sdxl safetensors file)
+        elif "clip_g" in state_dict and "clip_l" in state_dict:
+            result.embedding = state_dict["clip_g"]
+            result.embedding_2 = state_dict["clip_l"]
+
+        # v4(diffusers bin files)
+        else:
+            result.embedding = next(iter(state_dict.values()))
+
+            if len(result.embedding.shape) == 1:
+                result.embedding = result.embedding.unsqueeze(0)
+
+            if not isinstance(result.embedding, torch.Tensor):
+                raise ValueError(f"Invalid embeddings file: {file_path.name}")
+
+        return result
+
+
+# no type hints for BaseTextualInversionManager?
+class TextualInversionManager(BaseTextualInversionManager):  # type: ignore
+    pad_tokens: Dict[int, List[int]]
+    tokenizer: CLIPTokenizer
+
+    def __init__(self, tokenizer: CLIPTokenizer):
+        self.pad_tokens = {}
+        self.tokenizer = tokenizer
+
+    def expand_textual_inversion_token_ids_if_necessary(self, token_ids: list[int]) -> list[int]:
+        if len(self.pad_tokens) == 0:
+            return token_ids
+
+        if token_ids[0] == self.tokenizer.bos_token_id:
+            raise ValueError("token_ids must not start with bos_token_id")
+        if token_ids[-1] == self.tokenizer.eos_token_id:
+            raise ValueError("token_ids must not end with eos_token_id")
+
+        new_token_ids = []
+        for token_id in token_ids:
+            new_token_ids.append(token_id)
+            if token_id in self.pad_tokens:
+                new_token_ids.extend(self.pad_tokens[token_id])
+
+        # Do not exceed the max model input size
+        # The -2 here is compensating for compensate compel.embeddings_provider.get_token_ids(),
+        # which first removes and then adds back the start and end tokens.
+        max_length = list(self.tokenizer.max_model_input_sizes.values())[0] - 2
+        if len(new_token_ids) > max_length:
+            new_token_ids = new_token_ids[0:max_length]
+
+        return new_token_ids
diff --git a/invokeai/backend/install/install_helper.py b/invokeai/backend/install/install_helper.py
index 57dfadcaea..8877e33092 100644
--- a/invokeai/backend/install/install_helper.py
+++ b/invokeai/backend/install/install_helper.py
@@ -241,10 +241,11 @@ class InstallHelper(object):
         if match := re.match(f"^([^/]+/[^/]+?)(?::({variants}))?$", model_path_id_or_url):
             repo_id = match.group(1)
             repo_variant = ModelRepoVariant(match.group(2)) if match.group(2) else None
+            subfolder = Path(model_info.subfolder) if model_info.subfolder else None
             return HFModelSource(
                 repo_id=repo_id,
                 access_token=HfFolder.get_token(),
-                subfolder=model_info.subfolder,
+                subfolder=subfolder,
                 variant=repo_variant,
             )
         if re.match(r"^(http|https):", model_path_id_or_url):
diff --git a/invokeai/backend/model_manager/config.py b/invokeai/backend/model_manager/config.py
index 49ce6af2b8..0dcd925c84 100644
--- a/invokeai/backend/model_manager/config.py
+++ b/invokeai/backend/model_manager/config.py
@@ -30,8 +30,11 @@ from typing_extensions import Annotated, Any, Dict
 
 from invokeai.backend.onnx.onnx_runtime import IAIOnnxRuntimeModel
 
+from ..embeddings.embedding_base import EmbeddingModelRaw
 from ..ip_adapter.ip_adapter import IPAdapter, IPAdapterPlus
 
+AnyModel = Union[ModelMixin, torch.nn.Module, IAIOnnxRuntimeModel, IPAdapter, IPAdapterPlus, EmbeddingModelRaw]
+
 
 class InvalidModelConfigException(Exception):
     """Exception for when config parser doesn't recognized this combination of model type and format."""
@@ -299,7 +302,7 @@ AnyModelConfig = Union[
 ]
 
 AnyModelConfigValidator = TypeAdapter(AnyModelConfig)
-AnyModel = Union[ModelMixin, torch.nn.Module, IAIOnnxRuntimeModel, IPAdapter, IPAdapterPlus]
+
 
 # IMPLEMENTATION NOTE:
 # The preferred alternative to the above is a discriminated Union as shown
diff --git a/invokeai/backend/model_manager/load/load_base.py b/invokeai/backend/model_manager/load/load_base.py
index ee9d6d53e3..9d98ee3053 100644
--- a/invokeai/backend/model_manager/load/load_base.py
+++ b/invokeai/backend/model_manager/load/load_base.py
@@ -18,8 +18,8 @@ from pathlib import Path
 from typing import Any, Callable, Dict, Optional, Tuple, Type
 
 from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.backend.model_manager import AnyModel, AnyModelConfig, BaseModelType, ModelFormat, ModelType, SubModelType
-from invokeai.backend.model_manager.config import VaeCheckpointConfig, VaeDiffusersConfig
+from invokeai.backend.model_manager import AnyModelConfig, BaseModelType, ModelFormat, ModelType, SubModelType
+from invokeai.backend.model_manager.config import AnyModel, VaeCheckpointConfig, VaeDiffusersConfig
 from invokeai.backend.model_manager.load.convert_cache.convert_cache_base import ModelConvertCacheBase
 from invokeai.backend.model_manager.load.model_cache.model_cache_base import ModelCacheBase, ModelLockerBase
 from invokeai.backend.util.logging import InvokeAILogger
diff --git a/invokeai/backend/model_manager/load/load_default.py b/invokeai/backend/model_manager/load/load_default.py
index 757745072d..2192c88ac2 100644
--- a/invokeai/backend/model_manager/load/load_default.py
+++ b/invokeai/backend/model_manager/load/load_default.py
@@ -19,7 +19,7 @@ from invokeai.backend.model_manager import (
 )
 from invokeai.backend.model_manager.load.convert_cache import ModelConvertCacheBase
 from invokeai.backend.model_manager.load.load_base import LoadedModel, ModelLoaderBase
-from invokeai.backend.model_manager.load.model_cache.model_cache_base import ModelCacheBase, ModelLockerBase
+from invokeai.backend.model_manager.load.model_cache.model_cache_base import CacheStats, ModelCacheBase, ModelLockerBase
 from invokeai.backend.model_manager.load.model_util import calc_model_size_by_data, calc_model_size_by_fs
 from invokeai.backend.model_manager.load.optimizations import skip_torch_weight_init
 from invokeai.backend.util.devices import choose_torch_device, torch_dtype
@@ -71,7 +71,7 @@ class ModelLoader(ModelLoaderBase):
         model_path, model_config, submodel_type = self._get_model_path(model_config, submodel_type)
 
         if not model_path.exists():
-            raise InvalidModelConfigException(f"Files for model 'model_config.name' not found at {model_path}")
+            raise InvalidModelConfigException(f"Files for model '{model_config.name}' not found at {model_path}")
 
         model_path = self._convert_if_needed(model_config, model_path, submodel_type)
         locker = self._load_if_needed(model_config, model_path, submodel_type)
diff --git a/invokeai/backend/model_manager/load/model_cache/__init__.py b/invokeai/backend/model_manager/load/model_cache/__init__.py
index 0cb5184f3a..32c682d042 100644
--- a/invokeai/backend/model_manager/load/model_cache/__init__.py
+++ b/invokeai/backend/model_manager/load/model_cache/__init__.py
@@ -1,4 +1,6 @@
 """Init file for ModelCache."""
 
+from .model_cache_base import ModelCacheBase, CacheStats  # noqa F401
+from .model_cache_default import ModelCache  # noqa F401
 
-_all__ = ["ModelCacheBase", "ModelCache"]
+_all__ = ["ModelCacheBase", "ModelCache", "CacheStats"]
diff --git a/invokeai/backend/model_manager/load/model_cache/model_cache_base.py b/invokeai/backend/model_manager/load/model_cache/model_cache_base.py
index b1a6768ee8..4a4a3c7d29 100644
--- a/invokeai/backend/model_manager/load/model_cache/model_cache_base.py
+++ b/invokeai/backend/model_manager/load/model_cache/model_cache_base.py
@@ -8,13 +8,13 @@ model will be cleared and (re)loaded from disk when next needed.
 """
 
 from abc import ABC, abstractmethod
-from dataclasses import dataclass
+from dataclasses import dataclass, field
 from logging import Logger
-from typing import Generic, Optional, TypeVar
+from typing import Dict, Generic, Optional, TypeVar
 
 import torch
 
-from invokeai.backend.model_manager import AnyModel, SubModelType
+from invokeai.backend.model_manager.config import AnyModel, SubModelType
 
 
 class ModelLockerBase(ABC):
@@ -65,6 +65,19 @@ class CacheRecord(Generic[T]):
         return self._locks > 0
 
 
+@dataclass
+class CacheStats(object):
+    """Collect statistics on cache performance."""
+
+    hits: int = 0  # cache hits
+    misses: int = 0  # cache misses
+    high_watermark: int = 0  # amount of cache used
+    in_cache: int = 0  # number of models in cache
+    cleared: int = 0  # number of models cleared to make space
+    cache_size: int = 0  # total size of cache
+    loaded_model_sizes: Dict[str, int] = field(default_factory=dict)
+
+
 class ModelCacheBase(ABC, Generic[T]):
     """Virtual base class for RAM model cache."""
 
@@ -98,10 +111,22 @@ class ModelCacheBase(ABC, Generic[T]):
         pass
 
     @abstractmethod
-    def move_model_to_device(self, cache_entry: CacheRecord, device: torch.device) -> None:
+    def move_model_to_device(self, cache_entry: CacheRecord[AnyModel], device: torch.device) -> None:
         """Move model into the indicated device."""
         pass
 
+    @property
+    @abstractmethod
+    def stats(self) -> CacheStats:
+        """Return collected CacheStats object."""
+        pass
+
+    @stats.setter
+    @abstractmethod
+    def stats(self, stats: CacheStats) -> None:
+        """Set the CacheStats object for collectin cache statistics."""
+        pass
+
     @property
     @abstractmethod
     def logger(self) -> Logger:
diff --git a/invokeai/backend/model_manager/load/model_cache/model_cache_default.py b/invokeai/backend/model_manager/load/model_cache/model_cache_default.py
index 7e30512a58..b1deb215b2 100644
--- a/invokeai/backend/model_manager/load/model_cache/model_cache_default.py
+++ b/invokeai/backend/model_manager/load/model_cache/model_cache_default.py
@@ -24,19 +24,17 @@ import math
 import sys
 import time
 from contextlib import suppress
-from dataclasses import dataclass, field
 from logging import Logger
 from typing import Dict, List, Optional
 
 import torch
 
-from invokeai.backend.model_manager import SubModelType
-from invokeai.backend.model_manager.load.load_base import AnyModel
+from invokeai.backend.model_manager import AnyModel, SubModelType
 from invokeai.backend.model_manager.load.memory_snapshot import MemorySnapshot, get_pretty_snapshot_diff
 from invokeai.backend.util.devices import choose_torch_device
 from invokeai.backend.util.logging import InvokeAILogger
 
-from .model_cache_base import CacheRecord, ModelCacheBase
+from .model_cache_base import CacheRecord, CacheStats, ModelCacheBase
 from .model_locker import ModelLocker, ModelLockerBase
 
 if choose_torch_device() == torch.device("mps"):
@@ -56,20 +54,6 @@ GIG = 1073741824
 MB = 2**20
 
 
-@dataclass
-class CacheStats(object):
-    """Collect statistics on cache performance."""
-
-    hits: int = 0  # cache hits
-    misses: int = 0  # cache misses
-    high_watermark: int = 0  # amount of cache used
-    in_cache: int = 0  # number of models in cache
-    cleared: int = 0  # number of models cleared to make space
-    cache_size: int = 0  # total size of cache
-    # {submodel_key => size}
-    loaded_model_sizes: Dict[str, int] = field(default_factory=dict)
-
-
 class ModelCache(ModelCacheBase[AnyModel]):
     """Implementation of ModelCacheBase."""
 
@@ -110,7 +94,7 @@ class ModelCache(ModelCacheBase[AnyModel]):
         self._logger = logger or InvokeAILogger.get_logger(self.__class__.__name__)
         self._log_memory_usage = log_memory_usage or self._logger.level == logging.DEBUG
         # used for stats collection
-        self.stats = CacheStats()
+        self._stats: Optional[CacheStats] = None
 
         self._cached_models: Dict[str, CacheRecord[AnyModel]] = {}
         self._cache_stack: List[str] = []
@@ -140,6 +124,16 @@ class ModelCache(ModelCacheBase[AnyModel]):
         """Return the cap on cache size."""
         return self._max_cache_size
 
+    @property
+    def stats(self) -> Optional[CacheStats]:
+        """Return collected CacheStats object."""
+        return self._stats
+
+    @stats.setter
+    def stats(self, stats: CacheStats) -> None:
+        """Set the CacheStats object for collectin cache statistics."""
+        self._stats = stats
+
     def cache_size(self) -> int:
         """Get the total size of the models currently cached."""
         total = 0
@@ -189,21 +183,24 @@ class ModelCache(ModelCacheBase[AnyModel]):
         """
         key = self._make_cache_key(key, submodel_type)
         if key in self._cached_models:
-            self.stats.hits += 1
+            if self.stats:
+                self.stats.hits += 1
         else:
-            self.stats.misses += 1
+            if self.stats:
+                self.stats.misses += 1
             raise IndexError(f"The model with key {key} is not in the cache.")
 
         cache_entry = self._cached_models[key]
 
         # more stats
-        stats_name = stats_name or key
-        self.stats.cache_size = int(self._max_cache_size * GIG)
-        self.stats.high_watermark = max(self.stats.high_watermark, self.cache_size())
-        self.stats.in_cache = len(self._cached_models)
-        self.stats.loaded_model_sizes[stats_name] = max(
-            self.stats.loaded_model_sizes.get(stats_name, 0), cache_entry.size
-        )
+        if self.stats:
+            stats_name = stats_name or key
+            self.stats.cache_size = int(self._max_cache_size * GIG)
+            self.stats.high_watermark = max(self.stats.high_watermark, self.cache_size())
+            self.stats.in_cache = len(self._cached_models)
+            self.stats.loaded_model_sizes[stats_name] = max(
+                self.stats.loaded_model_sizes.get(stats_name, 0), cache_entry.size
+            )
 
         # this moves the entry to the top (right end) of the stack
         with suppress(Exception):
diff --git a/invokeai/backend/model_manager/load/model_loaders/textual_inversion.py b/invokeai/backend/model_manager/load/model_loaders/textual_inversion.py
index 394fddc75d..6635f6b43f 100644
--- a/invokeai/backend/model_manager/load/model_loaders/textual_inversion.py
+++ b/invokeai/backend/model_manager/load/model_loaders/textual_inversion.py
@@ -5,7 +5,7 @@
 from pathlib import Path
 from typing import Optional, Tuple
 
-from invokeai.backend.embeddings.model_patcher import TextualInversionModel as TextualInversionModelRaw
+from invokeai.backend.embeddings.textual_inversion import TextualInversionModelRaw
 from invokeai.backend.model_manager import (
     AnyModel,
     AnyModelConfig,
diff --git a/invokeai/backend/stable_diffusion/__init__.py b/invokeai/backend/stable_diffusion/__init__.py
index 212045f81b..75e6aa0a5d 100644
--- a/invokeai/backend/stable_diffusion/__init__.py
+++ b/invokeai/backend/stable_diffusion/__init__.py
@@ -4,3 +4,12 @@ Initialization file for the invokeai.backend.stable_diffusion package
 from .diffusers_pipeline import PipelineIntermediateState, StableDiffusionGeneratorPipeline  # noqa: F401
 from .diffusion import InvokeAIDiffuserComponent  # noqa: F401
 from .diffusion.cross_attention_map_saving import AttentionMapSaver  # noqa: F401
+from .seamless import set_seamless  # noqa: F401
+
+__all__ = [
+    "PipelineIntermediateState",
+    "StableDiffusionGeneratorPipeline",
+    "InvokeAIDiffuserComponent",
+    "AttentionMapSaver",
+    "set_seamless",
+]
diff --git a/invokeai/backend/stable_diffusion/seamless.py b/invokeai/backend/stable_diffusion/seamless.py
new file mode 100644
index 0000000000..bfdf9e0c53
--- /dev/null
+++ b/invokeai/backend/stable_diffusion/seamless.py
@@ -0,0 +1,102 @@
+from __future__ import annotations
+
+from contextlib import contextmanager
+from typing import List, Union
+
+import torch.nn as nn
+from diffusers.models import AutoencoderKL, UNet2DConditionModel
+
+
+def _conv_forward_asymmetric(self, input, weight, bias):
+    """
+    Patch for Conv2d._conv_forward that supports asymmetric padding
+    """
+    working = nn.functional.pad(input, self.asymmetric_padding["x"], mode=self.asymmetric_padding_mode["x"])
+    working = nn.functional.pad(working, self.asymmetric_padding["y"], mode=self.asymmetric_padding_mode["y"])
+    return nn.functional.conv2d(
+        working,
+        weight,
+        bias,
+        self.stride,
+        nn.modules.utils._pair(0),
+        self.dilation,
+        self.groups,
+    )
+
+
+@contextmanager
+def set_seamless(model: Union[UNet2DConditionModel, AutoencoderKL], seamless_axes: List[str]):
+    try:
+        to_restore = []
+
+        for m_name, m in model.named_modules():
+            if isinstance(model, UNet2DConditionModel):
+                if ".attentions." in m_name:
+                    continue
+
+                if ".resnets." in m_name:
+                    if ".conv2" in m_name:
+                        continue
+                    if ".conv_shortcut" in m_name:
+                        continue
+
+            """
+            if isinstance(model, UNet2DConditionModel):
+                if False and ".upsamplers." in m_name:
+                    continue
+
+                if False and ".downsamplers." in m_name:
+                    continue
+
+                if True and ".resnets." in m_name:
+                    if True and ".conv1" in m_name:
+                        if False and "down_blocks" in m_name:
+                            continue
+                        if False and "mid_block" in m_name:
+                            continue
+                        if False and "up_blocks" in m_name:
+                            continue
+
+                    if True and ".conv2" in m_name:
+                        continue
+
+                    if True and ".conv_shortcut" in m_name:
+                        continue
+
+                if True and ".attentions." in m_name:
+                    continue
+
+                if False and m_name in ["conv_in", "conv_out"]:
+                    continue
+            """
+
+            if isinstance(m, (nn.Conv2d, nn.ConvTranspose2d)):
+                m.asymmetric_padding_mode = {}
+                m.asymmetric_padding = {}
+                m.asymmetric_padding_mode["x"] = "circular" if ("x" in seamless_axes) else "constant"
+                m.asymmetric_padding["x"] = (
+                    m._reversed_padding_repeated_twice[0],
+                    m._reversed_padding_repeated_twice[1],
+                    0,
+                    0,
+                )
+                m.asymmetric_padding_mode["y"] = "circular" if ("y" in seamless_axes) else "constant"
+                m.asymmetric_padding["y"] = (
+                    0,
+                    0,
+                    m._reversed_padding_repeated_twice[2],
+                    m._reversed_padding_repeated_twice[3],
+                )
+
+                to_restore.append((m, m._conv_forward))
+                m._conv_forward = _conv_forward_asymmetric.__get__(m, nn.Conv2d)
+
+        yield
+
+    finally:
+        for module, orig_conv_forward in to_restore:
+            module._conv_forward = orig_conv_forward
+            if hasattr(module, "asymmetric_padding_mode"):
+                del module.asymmetric_padding_mode
+            if hasattr(module, "asymmetric_padding"):
+                del module.asymmetric_padding
diff --git a/invokeai/backend/util/silence_warnings.py b/invokeai/backend/util/silence_warnings.py
new file mode 100644
index 0000000000..068b605da9
--- /dev/null
+++ b/invokeai/backend/util/silence_warnings.py
@@ -0,0 +1,28 @@
+"""Context class to silence transformers and diffusers warnings."""
+import warnings
+from typing import Any
+
+from diffusers import logging as diffusers_logging
+from transformers import logging as transformers_logging
+
+
+class SilenceWarnings(object):
+    """Use in context to temporarily turn off warnings from transformers & diffusers modules.
+
+    with SilenceWarnings():
+        # do something
+    """
+
+    def __init__(self) -> None:
+        self.transformers_verbosity = transformers_logging.get_verbosity()
+        self.diffusers_verbosity = diffusers_logging.get_verbosity()
+
+    def __enter__(self) -> None:
+        transformers_logging.set_verbosity_error()
+        diffusers_logging.set_verbosity_error()
+        warnings.simplefilter("ignore")
+
+    def __exit__(self, *args: Any) -> None:
+        transformers_logging.set_verbosity(self.transformers_verbosity)
+        diffusers_logging.set_verbosity(self.diffusers_verbosity)
+        warnings.simplefilter("default")
diff --git a/invokeai/frontend/install/model_install2.py b/invokeai/frontend/install/model_install2.py
index 51a633a565..22b132370e 100644
--- a/invokeai/frontend/install/model_install2.py
+++ b/invokeai/frontend/install/model_install2.py
@@ -23,7 +23,7 @@ import torch
 from npyscreen import widget
 
 from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.app.services.model_install import ModelInstallService
+from invokeai.app.services.model_install import ModelInstallServiceBase
 from invokeai.backend.install.install_helper import InstallHelper, InstallSelections, UnifiedModelInfo
 from invokeai.backend.model_manager import ModelType
 from invokeai.backend.util import choose_precision, choose_torch_device
@@ -499,7 +499,7 @@ class AddModelApplication(npyscreen.NPSAppManaged):  # type: ignore
         )
 
 
-def list_models(installer: ModelInstallService, model_type: ModelType):
+def list_models(installer: ModelInstallServiceBase, model_type: ModelType):
     """Print out all models of type model_type."""
     models = installer.record_store.search_by_attr(model_type=model_type)
     print(f"Installed models of type `{model_type}`:")
@@ -527,7 +527,9 @@ def select_and_download_models(opt: Namespace) -> None:
         install_helper.add_or_delete(selections)
 
     elif opt.default_only:
-        selections = InstallSelections(install_models=[install_helper.default_model()])
+        default_model = install_helper.default_model()
+        assert default_model is not None
+        selections = InstallSelections(install_models=[default_model])
         install_helper.add_or_delete(selections)
 
     elif opt.yes_to_all:
diff --git a/tests/backend/model_manager_2/util/test_hf_model_select.py b/tests/backend/model_manager_2/util/test_hf_model_select.py
index f14d9a6823..5bef9cb2e1 100644
--- a/tests/backend/model_manager_2/util/test_hf_model_select.py
+++ b/tests/backend/model_manager_2/util/test_hf_model_select.py
@@ -192,6 +192,7 @@ def sdxl_base_files() -> List[Path]:
                 "text_encoder/model.onnx",
                 "text_encoder_2/config.json",
                 "text_encoder_2/model.onnx",
+                "text_encoder_2/model.onnx_data",
                 "tokenizer/merges.txt",
                 "tokenizer/special_tokens_map.json",
                 "tokenizer/tokenizer_config.json",
@@ -202,6 +203,7 @@ def sdxl_base_files() -> List[Path]:
                 "tokenizer_2/vocab.json",
                 "unet/config.json",
                 "unet/model.onnx",
+                "unet/model.onnx_data",
                 "vae_decoder/config.json",
                 "vae_decoder/model.onnx",
                 "vae_encoder/config.json",
diff --git a/tests/test_model_probe.py b/tests/test_model_probe.py
index aacae06a8b..be823e2be9 100644
--- a/tests/test_model_probe.py
+++ b/tests/test_model_probe.py
@@ -2,7 +2,7 @@ from pathlib import Path
 
 import pytest
 
-from invokeai.backend import BaseModelType
+from invokeai.backend.model_manager import BaseModelType, ModelRepoVariant
 from invokeai.backend.model_manager.probe import VaeFolderProbe
 
 
@@ -21,10 +21,10 @@ def test_get_base_type(vae_path: str, expected_type: BaseModelType, datadir: Pat
     base_type = probe.get_base_type()
     assert base_type == expected_type
     repo_variant = probe.get_repo_variant()
-    assert repo_variant == "default"
+    assert repo_variant == ModelRepoVariant.DEFAULT
 
 
 def test_repo_variant(datadir: Path):
     probe = VaeFolderProbe(datadir / "vae" / "taesdxl-fp16")
     repo_variant = probe.get_repo_variant()
-    assert repo_variant == "fp16"
+    assert repo_variant == ModelRepoVariant.FP16

From db340bc25376a0302b4ff508cee5bc35146bd471 Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lstein@gmail.com>
Date: Fri, 9 Feb 2024 16:42:33 -0500
Subject: [PATCH 117/411] fix invokeai_configure script to work with new mm;
 rename CLIs

---
 .../app/services/config/config_default.py     |  10 +-
 invokeai/backend/install/install_helper.py    |   2 +-
 .../backend/install/invokeai_configure.py     | 197 ++++----
 .../model_manager/load/load_default.py        |   2 +-
 invokeai/backend/util/devices.py              |   6 +-
 invokeai/configs/INITIAL_MODELS.yaml          | 106 +++--
 ...L_MODELS2.yaml => INITIAL_MODELS.yaml.OLD} | 106 ++---
 invokeai/frontend/install/model_install.py    | 444 +++++-------------
 ...model_install2.py => model_install.py.OLD} | 444 +++++++++++++-----
 invokeai/frontend/install/widgets.py          |  11 +
 ...e_diffusers2.py => merge_diffusers.py.OLD} |   0
 pyproject.toml                                |   3 +-
 tests/test_model_manager.py                   |  47 --
 13 files changed, 686 insertions(+), 692 deletions(-)
 rename invokeai/configs/{INITIAL_MODELS2.yaml => INITIAL_MODELS.yaml.OLD} (59%)
 rename invokeai/frontend/install/{model_install2.py => model_install.py.OLD} (57%)
 rename invokeai/frontend/merge/{merge_diffusers2.py => merge_diffusers.py.OLD} (100%)
 delete mode 100644 tests/test_model_manager.py

diff --git a/invokeai/app/services/config/config_default.py b/invokeai/app/services/config/config_default.py
index b39e916da3..2af775372d 100644
--- a/invokeai/app/services/config/config_default.py
+++ b/invokeai/app/services/config/config_default.py
@@ -185,7 +185,9 @@ from .config_base import InvokeAISettings
 INIT_FILE = Path("invokeai.yaml")
 DB_FILE = Path("invokeai.db")
 LEGACY_INIT_FILE = Path("invokeai.init")
-DEFAULT_MAX_VRAM = 0.5
+DEFAULT_RAM_CACHE = 10.0
+DEFAULT_VRAM_CACHE = 0.25
+DEFAULT_CONVERT_CACHE = 20.0
 
 
 class Categories(object):
@@ -261,9 +263,9 @@ class InvokeAIAppConfig(InvokeAISettings):
     version             : bool = Field(default=False, description="Show InvokeAI version and exit", json_schema_extra=Categories.Other)
 
     # CACHE
-    ram                 : float = Field(default=7.5, gt=0, description="Maximum memory amount used by model cache for rapid switching (floating point number, GB)", json_schema_extra=Categories.ModelCache, )
-    vram                : float = Field(default=0.25, ge=0, description="Amount of VRAM reserved for model storage (floating point number, GB)", json_schema_extra=Categories.ModelCache, )
-    convert_cache       : float = Field(default=10.0, ge=0, description="Maximum size of on-disk converted models cache (GB)", json_schema_extra=Categories.ModelCache)
+    ram                 : float = Field(default=DEFAULT_RAM_CACHE, gt=0, description="Maximum memory amount used by model cache for rapid switching (floating point number, GB)", json_schema_extra=Categories.ModelCache, )
+    vram                : float = Field(default=DEFAULT_VRAM_CACHE, ge=0, description="Amount of VRAM reserved for model storage (floating point number, GB)", json_schema_extra=Categories.ModelCache, )
+    convert_cache       : float = Field(default=DEFAULT_CONVERT_CACHE, ge=0, description="Maximum size of on-disk converted models cache (GB)", json_schema_extra=Categories.ModelCache)
 
     lazy_offload        : bool = Field(default=True, description="Keep models in VRAM until their space is needed", json_schema_extra=Categories.ModelCache, )
     log_memory_usage    : bool = Field(default=False, description="If True, a memory snapshot will be captured before and after every model cache operation, and the result will be logged (at debug level). There is a time cost to capturing the memory snapshots, so it is recommended to only enable this feature if you are actively inspecting the model cache's behaviour.", json_schema_extra=Categories.ModelCache)
diff --git a/invokeai/backend/install/install_helper.py b/invokeai/backend/install/install_helper.py
index 8877e33092..9c386c209c 100644
--- a/invokeai/backend/install/install_helper.py
+++ b/invokeai/backend/install/install_helper.py
@@ -37,7 +37,7 @@ from invokeai.backend.model_manager.metadata import UnknownMetadataException
 from invokeai.backend.util.logging import InvokeAILogger
 
 # name of the starter models file
-INITIAL_MODELS = "INITIAL_MODELS2.yaml"
+INITIAL_MODELS = "INITIAL_MODELS.yaml"
 
 
 def initialize_record_store(app_config: InvokeAIAppConfig) -> ModelRecordServiceBase:
diff --git a/invokeai/backend/install/invokeai_configure.py b/invokeai/backend/install/invokeai_configure.py
index 3cb7db6c82..4dfa2b070c 100755
--- a/invokeai/backend/install/invokeai_configure.py
+++ b/invokeai/backend/install/invokeai_configure.py
@@ -18,31 +18,30 @@ from argparse import Namespace
 from enum import Enum
 from pathlib import Path
 from shutil import get_terminal_size
-from typing import Any, get_args, get_type_hints
+from typing import Any, Optional, Set, Tuple, Type, get_args, get_type_hints
 from urllib import request
 
 import npyscreen
-import omegaconf
 import psutil
 import torch
 import transformers
-import yaml
-from diffusers import AutoencoderKL
+from diffusers import AutoencoderKL, ModelMixin
 from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
 from huggingface_hub import HfFolder
 from huggingface_hub import login as hf_hub_login
-from omegaconf import OmegaConf
-from pydantic import ValidationError
+from omegaconf import DictConfig, OmegaConf
+from pydantic.error_wrappers import ValidationError
 from tqdm import tqdm
 from transformers import AutoFeatureExtractor, BertTokenizerFast, CLIPTextConfig, CLIPTextModel, CLIPTokenizer
 
 import invokeai.configs as configs
 from invokeai.app.services.config import InvokeAIAppConfig
+from invokeai.backend.install.install_helper import InstallHelper, InstallSelections
 from invokeai.backend.install.legacy_arg_parsing import legacy_parser
-from invokeai.backend.install.model_install_backend import InstallSelections, ModelInstall, hf_download_from_pretrained
-from invokeai.backend.model_management.model_probe import BaseModelType, ModelType
+from invokeai.backend.model_manager import BaseModelType, ModelType
+from invokeai.backend.util import choose_precision, choose_torch_device
 from invokeai.backend.util.logging import InvokeAILogger
-from invokeai.frontend.install.model_install import addModelsForm, process_and_execute
+from invokeai.frontend.install.model_install import addModelsForm
 
 # TO DO - Move all the frontend code into invokeai.frontend.install
 from invokeai.frontend.install.widgets import (
@@ -61,7 +60,7 @@ warnings.filterwarnings("ignore")
 transformers.logging.set_verbosity_error()
 
 
-def get_literal_fields(field) -> list[Any]:
+def get_literal_fields(field: str) -> Tuple[Any]:
     return get_args(get_type_hints(InvokeAIAppConfig).get(field))
 
 
@@ -80,8 +79,7 @@ ATTENTION_SLICE_CHOICES = get_literal_fields("attention_slice_size")
 GENERATION_OPT_CHOICES = ["sequential_guidance", "force_tiled_decode", "lazy_offload"]
 GB = 1073741824  # GB in bytes
 HAS_CUDA = torch.cuda.is_available()
-_, MAX_VRAM = torch.cuda.mem_get_info() if HAS_CUDA else (0, 0)
-
+_, MAX_VRAM = torch.cuda.mem_get_info() if HAS_CUDA else (0.0, 0.0)
 
 MAX_VRAM /= GB
 MAX_RAM = psutil.virtual_memory().total / GB
@@ -96,13 +94,15 @@ logger = InvokeAILogger.get_logger()
 
 
 class DummyWidgetValue(Enum):
+    """Dummy widget values."""
+
     zero = 0
     true = True
     false = False
 
 
 # --------------------------------------------
-def postscript(errors: None):
+def postscript(errors: Set[str]) -> None:
     if not any(errors):
         message = f"""
 ** INVOKEAI INSTALLATION SUCCESSFUL **
@@ -143,7 +143,7 @@ def yes_or_no(prompt: str, default_yes=True):
 
 
 # ---------------------------------------------
-def HfLogin(access_token) -> str:
+def HfLogin(access_token) -> None:
     """
     Helper for logging in to Huggingface
     The stdout capture is needed to hide the irrelevant "git credential helper" warning
@@ -162,7 +162,7 @@ def HfLogin(access_token) -> str:
 
 # -------------------------------------
 class ProgressBar:
-    def __init__(self, model_name="file"):
+    def __init__(self, model_name: str = "file"):
         self.pbar = None
         self.name = model_name
 
@@ -179,6 +179,22 @@ class ProgressBar:
         self.pbar.update(block_size)
 
 
+# ---------------------------------------------
+def hf_download_from_pretrained(model_class: Type[ModelMixin], model_name: str, destination: Path, **kwargs: Any):
+    filter = lambda x: "fp16 is not a valid" not in x.getMessage()  # noqa E731
+    logger.addFilter(filter)
+    try:
+        model = model_class.from_pretrained(
+            model_name,
+            resume_download=True,
+            **kwargs,
+        )
+        model.save_pretrained(destination, safe_serialization=True)
+    finally:
+        logger.removeFilter(filter)
+    return destination
+
+
 # ---------------------------------------------
 def download_with_progress_bar(model_url: str, model_dest: str, label: str = "the"):
     try:
@@ -249,6 +265,7 @@ def download_conversion_models():
 
 
 # ---------------------------------------------
+# TO DO: use the download queue here.
 def download_realesrgan():
     logger.info("Installing ESRGAN Upscaling models...")
     URLs = [
@@ -288,18 +305,19 @@ def download_lama():
 
 
 # ---------------------------------------------
-def download_support_models():
+def download_support_models() -> None:
     download_realesrgan()
     download_lama()
     download_conversion_models()
 
 
 # -------------------------------------
-def get_root(root: str = None) -> str:
+def get_root(root: Optional[str] = None) -> str:
     if root:
         return root
-    elif os.environ.get("INVOKEAI_ROOT"):
-        return os.environ.get("INVOKEAI_ROOT")
+    elif root := os.environ.get("INVOKEAI_ROOT"):
+        assert root is not None
+        return root
     else:
         return str(config.root_path)
 
@@ -455,6 +473,25 @@ Use cursor arrows to make a checkbox selection, and space to toggle.
             max_width=110,
             scroll_exit=True,
         )
+        self.add_widget_intelligent(
+            npyscreen.TitleFixedText,
+            name="Model disk conversion cache size (GB). This is used to cache safetensors files that need to be converted to diffusers..",
+            begin_entry_at=0,
+            editable=False,
+            color="CONTROL",
+            scroll_exit=True,
+        )
+        self.nextrely -= 1
+        self.disk = self.add_widget_intelligent(
+            npyscreen.Slider,
+            value=clip(old_opts.convert_cache, range=(0, 100), step=0.5),
+            out_of=100,
+            lowest=0.0,
+            step=0.5,
+            relx=8,
+            scroll_exit=True,
+        )
+        self.nextrely += 1
         self.add_widget_intelligent(
             npyscreen.TitleFixedText,
             name="Model RAM cache size (GB). Make this at least large enough to hold a single full model (2GB for SD-1, 6GB for SDXL).",
@@ -495,6 +532,14 @@ Use cursor arrows to make a checkbox selection, and space to toggle.
             )
         else:
             self.vram = DummyWidgetValue.zero
+
+        self.nextrely += 1
+        self.add_widget_intelligent(
+            npyscreen.FixedText,
+            value="Location of the database used to store model path and configuration information:",
+            editable=False,
+            color="CONTROL",
+        )
         self.nextrely += 1
         self.outdir = self.add_widget_intelligent(
             FileBox,
@@ -506,19 +551,21 @@ Use cursor arrows to make a checkbox selection, and space to toggle.
             labelColor="GOOD",
             begin_entry_at=40,
             max_height=3,
+            max_width=127,
             scroll_exit=True,
         )
         self.autoimport_dirs = {}
         self.autoimport_dirs["autoimport_dir"] = self.add_widget_intelligent(
             FileBox,
-            name="Folder to recursively scan for new checkpoints, ControlNets, LoRAs and TI models",
-            value=str(config.root_path / config.autoimport_dir),
+            name="Optional folder to scan for new checkpoints, ControlNets, LoRAs and TI models",
+            value=str(config.root_path / config.autoimport_dir) if config.autoimport_dir else "",
             select_dir=True,
             must_exist=False,
             use_two_lines=False,
             labelColor="GOOD",
             begin_entry_at=32,
             max_height=3,
+            max_width=127,
             scroll_exit=True,
         )
         self.nextrely += 1
@@ -555,6 +602,10 @@ https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/blob/main/LICENS
         self.attention_slice_label.hidden = not show
         self.attention_slice_size.hidden = not show
 
+    def show_hide_model_conf_override(self, value):
+        self.model_conf_override.hidden = value
+        self.model_conf_override.display()
+
     def on_ok(self):
         options = self.marshall_arguments()
         if self.validate_field_values(options):
@@ -584,18 +635,21 @@ https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/blob/main/LICENS
         else:
             return True
 
-    def marshall_arguments(self):
+    def marshall_arguments(self) -> Namespace:
         new_opts = Namespace()
 
         for attr in [
             "ram",
             "vram",
+            "convert_cache",
             "outdir",
         ]:
             if hasattr(self, attr):
                 setattr(new_opts, attr, getattr(self, attr).value)
 
         for attr in self.autoimport_dirs:
+            if not self.autoimport_dirs[attr].value:
+                continue
             directory = Path(self.autoimport_dirs[attr].value)
             if directory.is_relative_to(config.root_path):
                 directory = directory.relative_to(config.root_path)
@@ -615,13 +669,14 @@ https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/blob/main/LICENS
 
 
 class EditOptApplication(npyscreen.NPSAppManaged):
-    def __init__(self, program_opts: Namespace, invokeai_opts: Namespace):
+    def __init__(self, program_opts: Namespace, invokeai_opts: InvokeAIAppConfig, install_helper: InstallHelper):
         super().__init__()
         self.program_opts = program_opts
         self.invokeai_opts = invokeai_opts
         self.user_cancelled = False
         self.autoload_pending = True
-        self.install_selections = default_user_selections(program_opts)
+        self.install_helper = install_helper
+        self.install_selections = default_user_selections(program_opts, install_helper)
 
     def onStart(self):
         npyscreen.setTheme(npyscreen.Themes.DefaultTheme)
@@ -640,16 +695,10 @@ class EditOptApplication(npyscreen.NPSAppManaged):
                 cycle_widgets=False,
             )
 
-    def new_opts(self):
+    def new_opts(self) -> Namespace:
         return self.options.marshall_arguments()
 
 
-def edit_opts(program_opts: Namespace, invokeai_opts: Namespace) -> argparse.Namespace:
-    editApp = EditOptApplication(program_opts, invokeai_opts)
-    editApp.run()
-    return editApp.new_opts()
-
-
 def default_ramcache() -> float:
     """Run a heuristic for the default RAM cache based on installed RAM."""
 
@@ -660,27 +709,18 @@ def default_ramcache() -> float:
     )  # 2.1 is just large enough for sd 1.5 ;-)
 
 
-def default_startup_options(init_file: Path) -> Namespace:
+def default_startup_options(init_file: Path) -> InvokeAIAppConfig:
     opts = InvokeAIAppConfig.get_config()
-    opts.ram = opts.ram or default_ramcache()
+    opts.ram = default_ramcache()
     return opts
 
 
-def default_user_selections(program_opts: Namespace) -> InstallSelections:
-    try:
-        installer = ModelInstall(config)
-    except omegaconf.errors.ConfigKeyError:
-        logger.warning("Your models.yaml file is corrupt or out of date. Reinitializing")
-        initialize_rootdir(config.root_path, True)
-        installer = ModelInstall(config)
-
-    models = installer.all_models()
+def default_user_selections(program_opts: Namespace, install_helper: InstallHelper) -> InstallSelections:
+    default_model = install_helper.default_model()
+    assert default_model is not None
+    default_models = [default_model] if program_opts.default_only else install_helper.recommended_models()
     return InstallSelections(
-        install_models=[models[installer.default_model()].path or models[installer.default_model()].repo_id]
-        if program_opts.default_only
-        else [models[x].path or models[x].repo_id for x in installer.recommended_models()]
-        if program_opts.yes_to_all
-        else [],
+        install_models=default_models if program_opts.yes_to_all else [],
     )
 
 
@@ -716,21 +756,10 @@ def initialize_rootdir(root: Path, yes_to_all: bool = False):
     path.mkdir(parents=True, exist_ok=True)
 
 
-def maybe_create_models_yaml(root: Path):
-    models_yaml = root / "configs" / "models.yaml"
-    if models_yaml.exists():
-        if OmegaConf.load(models_yaml).get("__metadata__"):  # up to date
-            return
-        else:
-            logger.info("Creating new models.yaml, original saved as models.yaml.orig")
-            models_yaml.rename(models_yaml.parent / "models.yaml.orig")
-
-    with open(models_yaml, "w") as yaml_file:
-        yaml_file.write(yaml.dump({"__metadata__": {"version": "3.0.0"}}))
-
-
 # -------------------------------------
-def run_console_ui(program_opts: Namespace, initfile: Path = None) -> (Namespace, Namespace):
+def run_console_ui(
+    program_opts: Namespace, initfile: Path, install_helper: InstallHelper
+) -> Tuple[Optional[Namespace], Optional[InstallSelections]]:
     invokeai_opts = default_startup_options(initfile)
     invokeai_opts.root = program_opts.root
 
@@ -739,22 +768,16 @@ def run_console_ui(program_opts: Namespace, initfile: Path = None) -> (Namespace
             "Could not increase terminal size. Try running again with a larger window or smaller font size."
         )
 
-    # the install-models application spawns a subprocess to install
-    # models, and will crash unless this is set before running.
-    import torch
-
-    torch.multiprocessing.set_start_method("spawn")
-
-    editApp = EditOptApplication(program_opts, invokeai_opts)
+    editApp = EditOptApplication(program_opts, invokeai_opts, install_helper)
     editApp.run()
     if editApp.user_cancelled:
         return (None, None)
     else:
-        return (editApp.new_opts, editApp.install_selections)
+        return (editApp.new_opts(), editApp.install_selections)
 
 
 # -------------------------------------
-def write_opts(opts: Namespace, init_file: Path):
+def write_opts(opts: InvokeAIAppConfig, init_file: Path) -> None:
     """
     Update the invokeai.yaml file with values from current settings.
     """
@@ -762,7 +785,7 @@ def write_opts(opts: Namespace, init_file: Path):
     new_config = InvokeAIAppConfig.get_config()
     new_config.root = config.root
 
-    for key, value in opts.__dict__.items():
+    for key, value in opts.model_dump().items():
         if hasattr(new_config, key):
             setattr(new_config, key, value)
 
@@ -779,7 +802,7 @@ def default_output_dir() -> Path:
 
 
 # -------------------------------------
-def write_default_options(program_opts: Namespace, initfile: Path):
+def write_default_options(program_opts: Namespace, initfile: Path) -> None:
     opt = default_startup_options(initfile)
     write_opts(opt, initfile)
 
@@ -789,16 +812,11 @@ def write_default_options(program_opts: Namespace, initfile: Path):
 # the legacy Args object in order to parse
 # the old init file and write out the new
 # yaml format.
-def migrate_init_file(legacy_format: Path):
+def migrate_init_file(legacy_format: Path) -> None:
     old = legacy_parser.parse_args([f"@{str(legacy_format)}"])
     new = InvokeAIAppConfig.get_config()
 
-    fields = [
-        x
-        for x, y in InvokeAIAppConfig.model_fields.items()
-        if (y.json_schema_extra.get("category", None) if y.json_schema_extra else None) != "DEPRECATED"
-    ]
-    for attr in fields:
+    for attr in InvokeAIAppConfig.model_fields.keys():
         if hasattr(old, attr):
             try:
                 setattr(new, attr, getattr(old, attr))
@@ -819,7 +837,7 @@ def migrate_init_file(legacy_format: Path):
 
 
 # -------------------------------------
-def migrate_models(root: Path):
+def migrate_models(root: Path) -> None:
     from invokeai.backend.install.migrate_to_3 import do_migrate
 
     do_migrate(root, root)
@@ -838,7 +856,9 @@ def migrate_if_needed(opt: Namespace, root: Path) -> bool:
         ):
             logger.info("** Migrating invokeai.init to invokeai.yaml")
             migrate_init_file(old_init_file)
-            config.parse_args(argv=[], conf=OmegaConf.load(new_init_file))
+            omegaconf = OmegaConf.load(new_init_file)
+            assert isinstance(omegaconf, DictConfig)
+            config.parse_args(argv=[], conf=omegaconf)
 
             if old_hub.exists():
                 migrate_models(config.root_path)
@@ -849,7 +869,7 @@ def migrate_if_needed(opt: Namespace, root: Path) -> bool:
 
 
 # -------------------------------------
-def main() -> None:
+def main():
     parser = argparse.ArgumentParser(description="InvokeAI model downloader")
     parser.add_argument(
         "--skip-sd-weights",
@@ -908,6 +928,7 @@ def main() -> None:
     if opt.full_precision:
         invoke_args.extend(["--precision", "float32"])
     config.parse_args(invoke_args)
+    config.precision = "float32" if opt.full_precision else choose_precision(torch.device(choose_torch_device()))
     logger = InvokeAILogger().get_logger(config=config)
 
     errors = set()
@@ -921,14 +942,18 @@ def main() -> None:
         # run this unconditionally in case new directories need to be added
         initialize_rootdir(config.root_path, opt.yes_to_all)
 
-        models_to_download = default_user_selections(opt)
+        # this will initialize the models.yaml file if not present
+        install_helper = InstallHelper(config, logger)
+
+        models_to_download = default_user_selections(opt, install_helper)
         new_init_file = config.root_path / "invokeai.yaml"
 
         if opt.yes_to_all:
             write_default_options(opt, new_init_file)
             init_options = Namespace(precision="float32" if opt.full_precision else "float16")
+
         else:
-            init_options, models_to_download = run_console_ui(opt, new_init_file)
+            init_options, models_to_download = run_console_ui(opt, new_init_file, install_helper)
             if init_options:
                 write_opts(init_options, new_init_file)
             else:
@@ -943,10 +968,12 @@ def main() -> None:
 
         if opt.skip_sd_weights:
             logger.warning("Skipping diffusion weights download per user request")
+
         elif models_to_download:
-            process_and_execute(opt, models_to_download)
+            install_helper.add_or_delete(models_to_download)
 
         postscript(errors=errors)
+
         if not opt.yes_to_all:
             input("Press any key to continue...")
     except WindowTooSmallException as e:
diff --git a/invokeai/backend/model_manager/load/load_default.py b/invokeai/backend/model_manager/load/load_default.py
index 2192c88ac2..c1dfe729af 100644
--- a/invokeai/backend/model_manager/load/load_default.py
+++ b/invokeai/backend/model_manager/load/load_default.py
@@ -19,7 +19,7 @@ from invokeai.backend.model_manager import (
 )
 from invokeai.backend.model_manager.load.convert_cache import ModelConvertCacheBase
 from invokeai.backend.model_manager.load.load_base import LoadedModel, ModelLoaderBase
-from invokeai.backend.model_manager.load.model_cache.model_cache_base import CacheStats, ModelCacheBase, ModelLockerBase
+from invokeai.backend.model_manager.load.model_cache.model_cache_base import ModelCacheBase, ModelLockerBase
 from invokeai.backend.model_manager.load.model_util import calc_model_size_by_data, calc_model_size_by_fs
 from invokeai.backend.model_manager.load.optimizations import skip_torch_weight_init
 from invokeai.backend.util.devices import choose_torch_device, torch_dtype
diff --git a/invokeai/backend/util/devices.py b/invokeai/backend/util/devices.py
index b4f24d8483..a83d1045f7 100644
--- a/invokeai/backend/util/devices.py
+++ b/invokeai/backend/util/devices.py
@@ -1,7 +1,7 @@
 from __future__ import annotations
 
 from contextlib import nullcontext
-from typing import Optional, Union
+from typing import Literal, Optional, Union
 
 import torch
 from torch import autocast
@@ -31,7 +31,9 @@ def choose_torch_device() -> torch.device:
 
 # We are in transition here from using a single global AppConfig to allowing multiple
 # configurations. It is strongly recommended to pass the app_config to this function.
-def choose_precision(device: torch.device, app_config: Optional[InvokeAIAppConfig] = None) -> str:
+def choose_precision(
+    device: torch.device, app_config: Optional[InvokeAIAppConfig] = None
+) -> Literal["float32", "float16", "bfloat16"]:
     """Return an appropriate precision for the given torch device."""
     app_config = app_config or config
     if device.type == "cuda":
diff --git a/invokeai/configs/INITIAL_MODELS.yaml b/invokeai/configs/INITIAL_MODELS.yaml
index c230665e3a..ca2283ab81 100644
--- a/invokeai/configs/INITIAL_MODELS.yaml
+++ b/invokeai/configs/INITIAL_MODELS.yaml
@@ -1,153 +1,157 @@
 # This file predefines a few models that the user may want to install.
 sd-1/main/stable-diffusion-v1-5:
    description: Stable Diffusion version 1.5 diffusers model (4.27 GB)
-   repo_id: runwayml/stable-diffusion-v1-5
+   source: runwayml/stable-diffusion-v1-5
    recommended: True
    default: True
 sd-1/main/stable-diffusion-v1-5-inpainting:
    description: RunwayML SD 1.5 model optimized for inpainting, diffusers version (4.27 GB)
-   repo_id: runwayml/stable-diffusion-inpainting
+   source: runwayml/stable-diffusion-inpainting
    recommended: True
 sd-2/main/stable-diffusion-2-1:
    description: Stable Diffusion version 2.1 diffusers model, trained on 768 pixel images (5.21 GB)
-   repo_id: stabilityai/stable-diffusion-2-1
+   source: stabilityai/stable-diffusion-2-1
    recommended: False
 sd-2/main/stable-diffusion-2-inpainting:
    description: Stable Diffusion version 2.0 inpainting model (5.21 GB)
-   repo_id: stabilityai/stable-diffusion-2-inpainting
+   source: stabilityai/stable-diffusion-2-inpainting
    recommended: False
 sdxl/main/stable-diffusion-xl-base-1-0:
    description: Stable Diffusion XL base model (12 GB)
-   repo_id: stabilityai/stable-diffusion-xl-base-1.0
+   source: stabilityai/stable-diffusion-xl-base-1.0
    recommended: True
 sdxl-refiner/main/stable-diffusion-xl-refiner-1-0:
    description: Stable Diffusion XL refiner model (12 GB)
-   repo_id: stabilityai/stable-diffusion-xl-refiner-1.0
+   source: stabilityai/stable-diffusion-xl-refiner-1.0
    recommended: False
-sdxl/vae/sdxl-1-0-vae-fix:
-   description: Fine tuned version of the SDXL-1.0 VAE
-   repo_id: madebyollin/sdxl-vae-fp16-fix
+sdxl/vae/sdxl-vae-fp16-fix:
+   description: Version of the SDXL-1.0 VAE that works in half precision mode
+   source: madebyollin/sdxl-vae-fp16-fix
    recommended: True
 sd-1/main/Analog-Diffusion:
    description: An SD-1.5 model trained on diverse analog photographs (2.13 GB)
-   repo_id: wavymulder/Analog-Diffusion
+   source: wavymulder/Analog-Diffusion
    recommended: False
-sd-1/main/Deliberate_v5:
+sd-1/main/Deliberate:
    description: Versatile model that produces detailed images up to 768px (4.27 GB)
-   path: https://huggingface.co/XpucT/Deliberate/resolve/main/Deliberate_v5.safetensors
+   source: XpucT/Deliberate
    recommended: False
 sd-1/main/Dungeons-and-Diffusion:
    description: Dungeons & Dragons characters (2.13 GB)
-   repo_id: 0xJustin/Dungeons-and-Diffusion
+   source: 0xJustin/Dungeons-and-Diffusion
    recommended: False
 sd-1/main/dreamlike-photoreal-2:
    description: A photorealistic model trained on 768 pixel images based on SD 1.5 (2.13 GB)
-   repo_id: dreamlike-art/dreamlike-photoreal-2.0
+   source: dreamlike-art/dreamlike-photoreal-2.0
    recommended: False
 sd-1/main/Inkpunk-Diffusion:
    description: Stylized illustrations inspired by Gorillaz, FLCL and Shinkawa; prompt with "nvinkpunk" (4.27 GB)
-   repo_id: Envvi/Inkpunk-Diffusion
+   source: Envvi/Inkpunk-Diffusion
    recommended: False
 sd-1/main/openjourney:
    description: An SD 1.5 model fine tuned on Midjourney; prompt with "mdjrny-v4 style" (2.13 GB)
-   repo_id: prompthero/openjourney
+   source: prompthero/openjourney
    recommended: False
 sd-1/main/seek.art_MEGA:
-   repo_id: coreco/seek.art_MEGA
+   source: coreco/seek.art_MEGA
    description: A general use SD-1.5 "anything" model that supports multiple styles (2.1 GB)
    recommended: False
 sd-1/main/trinart_stable_diffusion_v2:
    description: An SD-1.5 model finetuned with ~40K assorted high resolution manga/anime-style images (2.13 GB)
-   repo_id: naclbit/trinart_stable_diffusion_v2
+   source: naclbit/trinart_stable_diffusion_v2
    recommended: False
 sd-1/controlnet/qrcode_monster:
-   repo_id: monster-labs/control_v1p_sd15_qrcode_monster
+   source: monster-labs/control_v1p_sd15_qrcode_monster
    subfolder: v2
 sd-1/controlnet/canny:
-   repo_id: lllyasviel/control_v11p_sd15_canny
+   source: lllyasviel/control_v11p_sd15_canny
    recommended: True
 sd-1/controlnet/inpaint:
-   repo_id: lllyasviel/control_v11p_sd15_inpaint
+   source: lllyasviel/control_v11p_sd15_inpaint
 sd-1/controlnet/mlsd:
-   repo_id: lllyasviel/control_v11p_sd15_mlsd
+   source: lllyasviel/control_v11p_sd15_mlsd
 sd-1/controlnet/depth:
-   repo_id: lllyasviel/control_v11f1p_sd15_depth
+   source: lllyasviel/control_v11f1p_sd15_depth
    recommended: True
 sd-1/controlnet/normal_bae:
-   repo_id: lllyasviel/control_v11p_sd15_normalbae
+   source: lllyasviel/control_v11p_sd15_normalbae
 sd-1/controlnet/seg:
-   repo_id: lllyasviel/control_v11p_sd15_seg
+   source: lllyasviel/control_v11p_sd15_seg
 sd-1/controlnet/lineart:
-   repo_id: lllyasviel/control_v11p_sd15_lineart
+   source: lllyasviel/control_v11p_sd15_lineart
    recommended: True
 sd-1/controlnet/lineart_anime:
-   repo_id: lllyasviel/control_v11p_sd15s2_lineart_anime
+   source: lllyasviel/control_v11p_sd15s2_lineart_anime
 sd-1/controlnet/openpose:
-   repo_id: lllyasviel/control_v11p_sd15_openpose
+   source: lllyasviel/control_v11p_sd15_openpose
    recommended: True
 sd-1/controlnet/scribble:
-   repo_id: lllyasviel/control_v11p_sd15_scribble
+   source: lllyasviel/control_v11p_sd15_scribble
    recommended: False
 sd-1/controlnet/softedge:
-   repo_id: lllyasviel/control_v11p_sd15_softedge
+   source: lllyasviel/control_v11p_sd15_softedge
 sd-1/controlnet/shuffle:
-   repo_id: lllyasviel/control_v11e_sd15_shuffle
+   source: lllyasviel/control_v11e_sd15_shuffle
 sd-1/controlnet/tile:
-   repo_id: lllyasviel/control_v11f1e_sd15_tile
+   source: lllyasviel/control_v11f1e_sd15_tile
 sd-1/controlnet/ip2p:
-   repo_id: lllyasviel/control_v11e_sd15_ip2p
+   source: lllyasviel/control_v11e_sd15_ip2p
 sd-1/t2i_adapter/canny-sd15:
-   repo_id: TencentARC/t2iadapter_canny_sd15v2
+   source: TencentARC/t2iadapter_canny_sd15v2
 sd-1/t2i_adapter/sketch-sd15:
-   repo_id: TencentARC/t2iadapter_sketch_sd15v2
+   source: TencentARC/t2iadapter_sketch_sd15v2
 sd-1/t2i_adapter/depth-sd15:
-   repo_id: TencentARC/t2iadapter_depth_sd15v2
+   source: TencentARC/t2iadapter_depth_sd15v2
 sd-1/t2i_adapter/zoedepth-sd15:
-   repo_id: TencentARC/t2iadapter_zoedepth_sd15v1
+   source: TencentARC/t2iadapter_zoedepth_sd15v1
 sdxl/t2i_adapter/canny-sdxl:
-   repo_id: TencentARC/t2i-adapter-canny-sdxl-1.0
+   source: TencentARC/t2i-adapter-canny-sdxl-1.0
 sdxl/t2i_adapter/zoedepth-sdxl:
-   repo_id: TencentARC/t2i-adapter-depth-zoe-sdxl-1.0
+   source: TencentARC/t2i-adapter-depth-zoe-sdxl-1.0
 sdxl/t2i_adapter/lineart-sdxl:
-   repo_id: TencentARC/t2i-adapter-lineart-sdxl-1.0
+   source: TencentARC/t2i-adapter-lineart-sdxl-1.0
 sdxl/t2i_adapter/sketch-sdxl:
-   repo_id: TencentARC/t2i-adapter-sketch-sdxl-1.0
+   source: TencentARC/t2i-adapter-sketch-sdxl-1.0
 sd-1/embedding/EasyNegative:
-   path: https://huggingface.co/embed/EasyNegative/resolve/main/EasyNegative.safetensors
+   source: https://huggingface.co/embed/EasyNegative/resolve/main/EasyNegative.safetensors
    recommended: True
-sd-1/embedding/ahx-beta-453407d:
-   repo_id: sd-concepts-library/ahx-beta-453407d
+   description: A textual inversion to use in the negative prompt to reduce bad anatomy
+sd-1/lora/FlatColor:
+   source: https://civitai.com/models/6433/loraflatcolor
+   recommended: True
+   description: A LoRA that generates scenery using solid blocks of color
 sd-1/lora/Ink scenery:
-   path: https://civitai.com/api/download/models/83390
+   source: https://civitai.com/api/download/models/83390
+   description: Generate india ink-like landscapes
 sd-1/ip_adapter/ip_adapter_sd15:
-   repo_id: InvokeAI/ip_adapter_sd15
+   source: InvokeAI/ip_adapter_sd15
    recommended: True
    requires:
       - InvokeAI/ip_adapter_sd_image_encoder
    description: IP-Adapter for SD 1.5 models
 sd-1/ip_adapter/ip_adapter_plus_sd15:
-   repo_id: InvokeAI/ip_adapter_plus_sd15
+   source: InvokeAI/ip_adapter_plus_sd15
    recommended: False
    requires:
       - InvokeAI/ip_adapter_sd_image_encoder
    description: Refined IP-Adapter for SD 1.5 models
 sd-1/ip_adapter/ip_adapter_plus_face_sd15:
-   repo_id: InvokeAI/ip_adapter_plus_face_sd15
+   source: InvokeAI/ip_adapter_plus_face_sd15
    recommended: False
    requires:
       - InvokeAI/ip_adapter_sd_image_encoder
    description: Refined IP-Adapter for SD 1.5 models, adapted for faces
 sdxl/ip_adapter/ip_adapter_sdxl:
-   repo_id: InvokeAI/ip_adapter_sdxl
+   source: InvokeAI/ip_adapter_sdxl
    recommended: False
    requires:
       - InvokeAI/ip_adapter_sdxl_image_encoder
    description: IP-Adapter for SDXL models
 any/clip_vision/ip_adapter_sd_image_encoder:
-   repo_id: InvokeAI/ip_adapter_sd_image_encoder
+   source: InvokeAI/ip_adapter_sd_image_encoder
    recommended: False
    description: Required model for using IP-Adapters with SD-1/2 models
 any/clip_vision/ip_adapter_sdxl_image_encoder:
-   repo_id: InvokeAI/ip_adapter_sdxl_image_encoder
+   source: InvokeAI/ip_adapter_sdxl_image_encoder
    recommended: False
    description: Required model for using IP-Adapters with SDXL models
diff --git a/invokeai/configs/INITIAL_MODELS2.yaml b/invokeai/configs/INITIAL_MODELS.yaml.OLD
similarity index 59%
rename from invokeai/configs/INITIAL_MODELS2.yaml
rename to invokeai/configs/INITIAL_MODELS.yaml.OLD
index ca2283ab81..c230665e3a 100644
--- a/invokeai/configs/INITIAL_MODELS2.yaml
+++ b/invokeai/configs/INITIAL_MODELS.yaml.OLD
@@ -1,157 +1,153 @@
 # This file predefines a few models that the user may want to install.
 sd-1/main/stable-diffusion-v1-5:
    description: Stable Diffusion version 1.5 diffusers model (4.27 GB)
-   source: runwayml/stable-diffusion-v1-5
+   repo_id: runwayml/stable-diffusion-v1-5
    recommended: True
    default: True
 sd-1/main/stable-diffusion-v1-5-inpainting:
    description: RunwayML SD 1.5 model optimized for inpainting, diffusers version (4.27 GB)
-   source: runwayml/stable-diffusion-inpainting
+   repo_id: runwayml/stable-diffusion-inpainting
    recommended: True
 sd-2/main/stable-diffusion-2-1:
    description: Stable Diffusion version 2.1 diffusers model, trained on 768 pixel images (5.21 GB)
-   source: stabilityai/stable-diffusion-2-1
+   repo_id: stabilityai/stable-diffusion-2-1
    recommended: False
 sd-2/main/stable-diffusion-2-inpainting:
    description: Stable Diffusion version 2.0 inpainting model (5.21 GB)
-   source: stabilityai/stable-diffusion-2-inpainting
+   repo_id: stabilityai/stable-diffusion-2-inpainting
    recommended: False
 sdxl/main/stable-diffusion-xl-base-1-0:
    description: Stable Diffusion XL base model (12 GB)
-   source: stabilityai/stable-diffusion-xl-base-1.0
+   repo_id: stabilityai/stable-diffusion-xl-base-1.0
    recommended: True
 sdxl-refiner/main/stable-diffusion-xl-refiner-1-0:
    description: Stable Diffusion XL refiner model (12 GB)
-   source: stabilityai/stable-diffusion-xl-refiner-1.0
+   repo_id: stabilityai/stable-diffusion-xl-refiner-1.0
    recommended: False
-sdxl/vae/sdxl-vae-fp16-fix:
-   description: Version of the SDXL-1.0 VAE that works in half precision mode
-   source: madebyollin/sdxl-vae-fp16-fix
+sdxl/vae/sdxl-1-0-vae-fix:
+   description: Fine tuned version of the SDXL-1.0 VAE
+   repo_id: madebyollin/sdxl-vae-fp16-fix
    recommended: True
 sd-1/main/Analog-Diffusion:
    description: An SD-1.5 model trained on diverse analog photographs (2.13 GB)
-   source: wavymulder/Analog-Diffusion
+   repo_id: wavymulder/Analog-Diffusion
    recommended: False
-sd-1/main/Deliberate:
+sd-1/main/Deliberate_v5:
    description: Versatile model that produces detailed images up to 768px (4.27 GB)
-   source: XpucT/Deliberate
+   path: https://huggingface.co/XpucT/Deliberate/resolve/main/Deliberate_v5.safetensors
    recommended: False
 sd-1/main/Dungeons-and-Diffusion:
    description: Dungeons & Dragons characters (2.13 GB)
-   source: 0xJustin/Dungeons-and-Diffusion
+   repo_id: 0xJustin/Dungeons-and-Diffusion
    recommended: False
 sd-1/main/dreamlike-photoreal-2:
    description: A photorealistic model trained on 768 pixel images based on SD 1.5 (2.13 GB)
-   source: dreamlike-art/dreamlike-photoreal-2.0
+   repo_id: dreamlike-art/dreamlike-photoreal-2.0
    recommended: False
 sd-1/main/Inkpunk-Diffusion:
    description: Stylized illustrations inspired by Gorillaz, FLCL and Shinkawa; prompt with "nvinkpunk" (4.27 GB)
-   source: Envvi/Inkpunk-Diffusion
+   repo_id: Envvi/Inkpunk-Diffusion
    recommended: False
 sd-1/main/openjourney:
    description: An SD 1.5 model fine tuned on Midjourney; prompt with "mdjrny-v4 style" (2.13 GB)
-   source: prompthero/openjourney
+   repo_id: prompthero/openjourney
    recommended: False
 sd-1/main/seek.art_MEGA:
-   source: coreco/seek.art_MEGA
+   repo_id: coreco/seek.art_MEGA
    description: A general use SD-1.5 "anything" model that supports multiple styles (2.1 GB)
    recommended: False
 sd-1/main/trinart_stable_diffusion_v2:
    description: An SD-1.5 model finetuned with ~40K assorted high resolution manga/anime-style images (2.13 GB)
-   source: naclbit/trinart_stable_diffusion_v2
+   repo_id: naclbit/trinart_stable_diffusion_v2
    recommended: False
 sd-1/controlnet/qrcode_monster:
-   source: monster-labs/control_v1p_sd15_qrcode_monster
+   repo_id: monster-labs/control_v1p_sd15_qrcode_monster
    subfolder: v2
 sd-1/controlnet/canny:
-   source: lllyasviel/control_v11p_sd15_canny
+   repo_id: lllyasviel/control_v11p_sd15_canny
    recommended: True
 sd-1/controlnet/inpaint:
-   source: lllyasviel/control_v11p_sd15_inpaint
+   repo_id: lllyasviel/control_v11p_sd15_inpaint
 sd-1/controlnet/mlsd:
-   source: lllyasviel/control_v11p_sd15_mlsd
+   repo_id: lllyasviel/control_v11p_sd15_mlsd
 sd-1/controlnet/depth:
-   source: lllyasviel/control_v11f1p_sd15_depth
+   repo_id: lllyasviel/control_v11f1p_sd15_depth
    recommended: True
 sd-1/controlnet/normal_bae:
-   source: lllyasviel/control_v11p_sd15_normalbae
+   repo_id: lllyasviel/control_v11p_sd15_normalbae
 sd-1/controlnet/seg:
-   source: lllyasviel/control_v11p_sd15_seg
+   repo_id: lllyasviel/control_v11p_sd15_seg
 sd-1/controlnet/lineart:
-   source: lllyasviel/control_v11p_sd15_lineart
+   repo_id: lllyasviel/control_v11p_sd15_lineart
    recommended: True
 sd-1/controlnet/lineart_anime:
-   source: lllyasviel/control_v11p_sd15s2_lineart_anime
+   repo_id: lllyasviel/control_v11p_sd15s2_lineart_anime
 sd-1/controlnet/openpose:
-   source: lllyasviel/control_v11p_sd15_openpose
+   repo_id: lllyasviel/control_v11p_sd15_openpose
    recommended: True
 sd-1/controlnet/scribble:
-   source: lllyasviel/control_v11p_sd15_scribble
+   repo_id: lllyasviel/control_v11p_sd15_scribble
    recommended: False
 sd-1/controlnet/softedge:
-   source: lllyasviel/control_v11p_sd15_softedge
+   repo_id: lllyasviel/control_v11p_sd15_softedge
 sd-1/controlnet/shuffle:
-   source: lllyasviel/control_v11e_sd15_shuffle
+   repo_id: lllyasviel/control_v11e_sd15_shuffle
 sd-1/controlnet/tile:
-   source: lllyasviel/control_v11f1e_sd15_tile
+   repo_id: lllyasviel/control_v11f1e_sd15_tile
 sd-1/controlnet/ip2p:
-   source: lllyasviel/control_v11e_sd15_ip2p
+   repo_id: lllyasviel/control_v11e_sd15_ip2p
 sd-1/t2i_adapter/canny-sd15:
-   source: TencentARC/t2iadapter_canny_sd15v2
+   repo_id: TencentARC/t2iadapter_canny_sd15v2
 sd-1/t2i_adapter/sketch-sd15:
-   source: TencentARC/t2iadapter_sketch_sd15v2
+   repo_id: TencentARC/t2iadapter_sketch_sd15v2
 sd-1/t2i_adapter/depth-sd15:
-   source: TencentARC/t2iadapter_depth_sd15v2
+   repo_id: TencentARC/t2iadapter_depth_sd15v2
 sd-1/t2i_adapter/zoedepth-sd15:
-   source: TencentARC/t2iadapter_zoedepth_sd15v1
+   repo_id: TencentARC/t2iadapter_zoedepth_sd15v1
 sdxl/t2i_adapter/canny-sdxl:
-   source: TencentARC/t2i-adapter-canny-sdxl-1.0
+   repo_id: TencentARC/t2i-adapter-canny-sdxl-1.0
 sdxl/t2i_adapter/zoedepth-sdxl:
-   source: TencentARC/t2i-adapter-depth-zoe-sdxl-1.0
+   repo_id: TencentARC/t2i-adapter-depth-zoe-sdxl-1.0
 sdxl/t2i_adapter/lineart-sdxl:
-   source: TencentARC/t2i-adapter-lineart-sdxl-1.0
+   repo_id: TencentARC/t2i-adapter-lineart-sdxl-1.0
 sdxl/t2i_adapter/sketch-sdxl:
-   source: TencentARC/t2i-adapter-sketch-sdxl-1.0
+   repo_id: TencentARC/t2i-adapter-sketch-sdxl-1.0
 sd-1/embedding/EasyNegative:
-   source: https://huggingface.co/embed/EasyNegative/resolve/main/EasyNegative.safetensors
+   path: https://huggingface.co/embed/EasyNegative/resolve/main/EasyNegative.safetensors
    recommended: True
-   description: A textual inversion to use in the negative prompt to reduce bad anatomy
-sd-1/lora/FlatColor:
-   source: https://civitai.com/models/6433/loraflatcolor
-   recommended: True
-   description: A LoRA that generates scenery using solid blocks of color
+sd-1/embedding/ahx-beta-453407d:
+   repo_id: sd-concepts-library/ahx-beta-453407d
 sd-1/lora/Ink scenery:
-   source: https://civitai.com/api/download/models/83390
-   description: Generate india ink-like landscapes
+   path: https://civitai.com/api/download/models/83390
 sd-1/ip_adapter/ip_adapter_sd15:
-   source: InvokeAI/ip_adapter_sd15
+   repo_id: InvokeAI/ip_adapter_sd15
    recommended: True
    requires:
       - InvokeAI/ip_adapter_sd_image_encoder
    description: IP-Adapter for SD 1.5 models
 sd-1/ip_adapter/ip_adapter_plus_sd15:
-   source: InvokeAI/ip_adapter_plus_sd15
+   repo_id: InvokeAI/ip_adapter_plus_sd15
    recommended: False
    requires:
       - InvokeAI/ip_adapter_sd_image_encoder
    description: Refined IP-Adapter for SD 1.5 models
 sd-1/ip_adapter/ip_adapter_plus_face_sd15:
-   source: InvokeAI/ip_adapter_plus_face_sd15
+   repo_id: InvokeAI/ip_adapter_plus_face_sd15
    recommended: False
    requires:
       - InvokeAI/ip_adapter_sd_image_encoder
    description: Refined IP-Adapter for SD 1.5 models, adapted for faces
 sdxl/ip_adapter/ip_adapter_sdxl:
-   source: InvokeAI/ip_adapter_sdxl
+   repo_id: InvokeAI/ip_adapter_sdxl
    recommended: False
    requires:
       - InvokeAI/ip_adapter_sdxl_image_encoder
    description: IP-Adapter for SDXL models
 any/clip_vision/ip_adapter_sd_image_encoder:
-   source: InvokeAI/ip_adapter_sd_image_encoder
+   repo_id: InvokeAI/ip_adapter_sd_image_encoder
    recommended: False
    description: Required model for using IP-Adapters with SD-1/2 models
 any/clip_vision/ip_adapter_sdxl_image_encoder:
-   source: InvokeAI/ip_adapter_sdxl_image_encoder
+   repo_id: InvokeAI/ip_adapter_sdxl_image_encoder
    recommended: False
    description: Required model for using IP-Adapters with SDXL models
diff --git a/invokeai/frontend/install/model_install.py b/invokeai/frontend/install/model_install.py
index e23538ffd6..22b132370e 100644
--- a/invokeai/frontend/install/model_install.py
+++ b/invokeai/frontend/install/model_install.py
@@ -6,47 +6,45 @@
 
 """
 This is the npyscreen frontend to the model installation application.
-The work is actually done in backend code in model_install_backend.py.
+It is currently named model_install2.py, but will ultimately replace model_install.py.
 """
 
 import argparse
 import curses
-import logging
 import sys
-import textwrap
 import traceback
+import warnings
 from argparse import Namespace
-from multiprocessing import Process
-from multiprocessing.connection import Connection, Pipe
-from pathlib import Path
 from shutil import get_terminal_size
-from typing import Optional
+from typing import Any, Dict, List, Optional, Set
 
 import npyscreen
 import torch
 from npyscreen import widget
 
 from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.backend.install.model_install_backend import InstallSelections, ModelInstall, SchedulerPredictionType
-from invokeai.backend.model_management import ModelManager, ModelType
+from invokeai.app.services.model_install import ModelInstallServiceBase
+from invokeai.backend.install.install_helper import InstallHelper, InstallSelections, UnifiedModelInfo
+from invokeai.backend.model_manager import ModelType
 from invokeai.backend.util import choose_precision, choose_torch_device
 from invokeai.backend.util.logging import InvokeAILogger
 from invokeai.frontend.install.widgets import (
     MIN_COLS,
     MIN_LINES,
-    BufferBox,
     CenteredTitleText,
     CyclingForm,
     MultiSelectColumns,
     SingleSelectColumns,
     TextBox,
     WindowTooSmallException,
-    select_stable_diffusion_config_file,
     set_min_terminal_size,
 )
 
+warnings.filterwarnings("ignore", category=UserWarning)  # noqa: E402
 config = InvokeAIAppConfig.get_config()
-logger = InvokeAILogger.get_logger()
+logger = InvokeAILogger.get_logger("ModelInstallService")
+logger.setLevel("WARNING")
+# logger.setLevel('DEBUG')
 
 # build a table mapping all non-printable characters to None
 # for stripping control characters
@@ -58,44 +56,42 @@ MAX_OTHER_MODELS = 72
 
 
 def make_printable(s: str) -> str:
-    """Replace non-printable characters in a string"""
+    """Replace non-printable characters in a string."""
     return s.translate(NOPRINT_TRANS_TABLE)
 
 
 class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
+    """Main form for interactive TUI."""
+
     # for responsive resizing set to False, but this seems to cause a crash!
     FIX_MINIMUM_SIZE_WHEN_CREATED = True
 
     # for persistence
     current_tab = 0
 
-    def __init__(self, parentApp, name, multipage=False, *args, **keywords):
+    def __init__(self, parentApp: npyscreen.NPSAppManaged, name: str, multipage: bool = False, **keywords: Any):
         self.multipage = multipage
         self.subprocess = None
-        super().__init__(parentApp=parentApp, name=name, *args, **keywords)  # noqa: B026 # TODO: maybe this is bad?
+        super().__init__(parentApp=parentApp, name=name, **keywords)
 
-    def create(self):
+    def create(self) -> None:
+        self.installer = self.parentApp.install_helper.installer
+        self.model_labels = self._get_model_labels()
         self.keypress_timeout = 10
         self.counter = 0
         self.subprocess_connection = None
 
-        if not config.model_conf_path.exists():
-            with open(config.model_conf_path, "w") as file:
-                print("# InvokeAI model configuration file", file=file)
-        self.installer = ModelInstall(config)
-        self.all_models = self.installer.all_models()
-        self.starter_models = self.installer.starter_models()
-        self.model_labels = self._get_model_labels()
         window_width, window_height = get_terminal_size()
 
-        self.nextrely -= 1
+        # npyscreen has no typing hints
+        self.nextrely -= 1  # type: ignore
         self.add_widget_intelligent(
             npyscreen.FixedText,
             value="Use ctrl-N and ctrl-P to move to the <N>ext and <P>revious fields. Cursor keys navigate, and <space> selects.",
             editable=False,
             color="CAUTION",
         )
-        self.nextrely += 1
+        self.nextrely += 1  # type: ignore
         self.tabs = self.add_widget_intelligent(
             SingleSelectColumns,
             values=[
@@ -115,9 +111,9 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
         )
         self.tabs.on_changed = self._toggle_tables
 
-        top_of_table = self.nextrely
+        top_of_table = self.nextrely  # type: ignore
         self.starter_pipelines = self.add_starter_pipelines()
-        bottom_of_table = self.nextrely
+        bottom_of_table = self.nextrely  # type: ignore
 
         self.nextrely = top_of_table
         self.pipeline_models = self.add_pipeline_widgets(
@@ -162,15 +158,7 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
 
         self.nextrely = bottom_of_table + 1
 
-        self.monitor = self.add_widget_intelligent(
-            BufferBox,
-            name="Log Messages",
-            editable=False,
-            max_height=6,
-        )
-
         self.nextrely += 1
-        done_label = "APPLY CHANGES"
         back_label = "BACK"
         cancel_label = "CANCEL"
         current_position = self.nextrely
@@ -186,14 +174,8 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
                 npyscreen.ButtonPress, name=cancel_label, when_pressed_function=self.on_cancel
             )
             self.nextrely = current_position
-            self.ok_button = self.add_widget_intelligent(
-                npyscreen.ButtonPress,
-                name=done_label,
-                relx=(window_width - len(done_label)) // 2,
-                when_pressed_function=self.on_execute,
-            )
 
-        label = "APPLY CHANGES & EXIT"
+        label = "APPLY CHANGES"
         self.nextrely = current_position
         self.done = self.add_widget_intelligent(
             npyscreen.ButtonPress,
@@ -210,17 +192,16 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
     ############# diffusers tab ##########
     def add_starter_pipelines(self) -> dict[str, npyscreen.widget]:
         """Add widgets responsible for selecting diffusers models"""
-        widgets = {}
-        models = self.all_models
-        starters = self.starter_models
-        starter_model_labels = self.model_labels
+        widgets: Dict[str, npyscreen.widget] = {}
 
-        self.installed_models = sorted([x for x in starters if models[x].installed])
+        all_models = self.all_models  # master dict of all models, indexed by key
+        model_list = [x for x in self.starter_models if all_models[x].type in ["main", "vae"]]
+        model_labels = [self.model_labels[x] for x in model_list]
 
         widgets.update(
             label1=self.add_widget_intelligent(
                 CenteredTitleText,
-                name="Select from a starter set of Stable Diffusion models from HuggingFace.",
+                name="Select from a starter set of Stable Diffusion models from HuggingFace and Civitae.",
                 editable=False,
                 labelColor="CAUTION",
             )
@@ -230,23 +211,24 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
         # if user has already installed some initial models, then don't patronize them
         # by showing more recommendations
         show_recommended = len(self.installed_models) == 0
-        keys = [x for x in models.keys() if x in starters]
+
+        checked = [
+            model_list.index(x)
+            for x in model_list
+            if (show_recommended and all_models[x].recommended) or all_models[x].installed
+        ]
         widgets.update(
             models_selected=self.add_widget_intelligent(
                 MultiSelectColumns,
                 columns=1,
                 name="Install Starter Models",
-                values=[starter_model_labels[x] for x in keys],
-                value=[
-                    keys.index(x)
-                    for x in keys
-                    if (show_recommended and models[x].recommended) or (x in self.installed_models)
-                ],
-                max_height=len(starters) + 1,
+                values=model_labels,
+                value=checked,
+                max_height=len(model_list) + 1,
                 relx=4,
                 scroll_exit=True,
             ),
-            models=keys,
+            models=model_list,
         )
 
         self.nextrely += 1
@@ -257,14 +239,18 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
         self,
         model_type: ModelType,
         window_width: int = 120,
-        install_prompt: str = None,
-        exclude: set = None,
+        install_prompt: Optional[str] = None,
+        exclude: Optional[Set[str]] = None,
     ) -> dict[str, npyscreen.widget]:
         """Generic code to create model selection widgets"""
         if exclude is None:
             exclude = set()
-        widgets = {}
-        model_list = [x for x in self.all_models if self.all_models[x].model_type == model_type and x not in exclude]
+        widgets: Dict[str, npyscreen.widget] = {}
+        all_models = self.all_models
+        model_list = sorted(
+            [x for x in all_models if all_models[x].type == model_type and x not in exclude],
+            key=lambda x: all_models[x].name or "",
+        )
         model_labels = [self.model_labels[x] for x in model_list]
 
         show_recommended = len(self.installed_models) == 0
@@ -300,7 +286,7 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
                     value=[
                         model_list.index(x)
                         for x in model_list
-                        if (show_recommended and self.all_models[x].recommended) or self.all_models[x].installed
+                        if (show_recommended and all_models[x].recommended) or all_models[x].installed
                     ],
                     max_height=len(model_list) // columns + 1,
                     relx=4,
@@ -324,7 +310,7 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
             download_ids=self.add_widget_intelligent(
                 TextBox,
                 name="Additional URLs, or HuggingFace repo_ids to install (Space separated. Use shift-control-V to paste):",
-                max_height=4,
+                max_height=6,
                 scroll_exit=True,
                 editable=True,
             )
@@ -349,13 +335,13 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
 
         return widgets
 
-    def resize(self):
+    def resize(self) -> None:
         super().resize()
         if s := self.starter_pipelines.get("models_selected"):
-            keys = [x for x in self.all_models.keys() if x in self.starter_models]
-            s.values = [self.model_labels[x] for x in keys]
+            if model_list := self.starter_pipelines.get("models"):
+                s.values = [self.model_labels[x] for x in model_list]
 
-    def _toggle_tables(self, value=None):
+    def _toggle_tables(self, value: List[int]) -> None:
         selected_tab = value[0]
         widgets = [
             self.starter_pipelines,
@@ -385,17 +371,18 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
         self.display()
 
     def _get_model_labels(self) -> dict[str, str]:
+        """Return a list of trimmed labels for all models."""
         window_width, window_height = get_terminal_size()
         checkbox_width = 4
         spacing_width = 2
+        result = {}
 
         models = self.all_models
-        label_width = max([len(models[x].name) for x in models])
+        label_width = max([len(models[x].name or "") for x in self.starter_models])
         description_width = window_width - label_width - checkbox_width - spacing_width
 
-        result = {}
-        for x in models.keys():
-            description = models[x].description
+        for key in self.all_models:
+            description = models[key].description
             description = (
                 description[0 : description_width - 3] + "..."
                 if description and len(description) > description_width
@@ -403,7 +390,8 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
                 if description
                 else ""
             )
-            result[x] = f"%-{label_width}s %s" % (models[x].name, description)
+            result[key] = f"%-{label_width}s %s" % (models[key].name, description)
+
         return result
 
     def _get_columns(self) -> int:
@@ -413,50 +401,40 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
 
     def confirm_deletions(self, selections: InstallSelections) -> bool:
         remove_models = selections.remove_models
-        if len(remove_models) > 0:
-            mods = "\n".join([ModelManager.parse_key(x)[0] for x in remove_models])
-            return npyscreen.notify_ok_cancel(
+        if remove_models:
+            model_names = [self.all_models[x].name or "" for x in remove_models]
+            mods = "\n".join(model_names)
+            is_ok = npyscreen.notify_ok_cancel(
                 f"These unchecked models will be deleted from disk. Continue?\n---------\n{mods}"
             )
+            assert isinstance(is_ok, bool)  # npyscreen doesn't have return type annotations
+            return is_ok
         else:
             return True
 
-    def on_execute(self):
-        self.marshall_arguments()
-        app = self.parentApp
-        if not self.confirm_deletions(app.install_selections):
-            return
+    @property
+    def all_models(self) -> Dict[str, UnifiedModelInfo]:
+        # npyscreen doesn't having typing hints
+        return self.parentApp.install_helper.all_models  # type: ignore
 
-        self.monitor.entry_widget.buffer(["Processing..."], scroll_end=True)
-        self.ok_button.hidden = True
-        self.display()
+    @property
+    def starter_models(self) -> List[str]:
+        return self.parentApp.install_helper._starter_models  # type: ignore
 
-        # TO DO: Spawn a worker thread, not a subprocess
-        parent_conn, child_conn = Pipe()
-        p = Process(
-            target=process_and_execute,
-            kwargs={
-                "opt": app.program_opts,
-                "selections": app.install_selections,
-                "conn_out": child_conn,
-            },
-        )
-        p.start()
-        child_conn.close()
-        self.subprocess_connection = parent_conn
-        self.subprocess = p
-        app.install_selections = InstallSelections()
+    @property
+    def installed_models(self) -> List[str]:
+        return self.parentApp.install_helper._installed_models  # type: ignore
 
-    def on_back(self):
+    def on_back(self) -> None:
         self.parentApp.switchFormPrevious()
         self.editing = False
 
-    def on_cancel(self):
+    def on_cancel(self) -> None:
         self.parentApp.setNextForm(None)
         self.parentApp.user_cancelled = True
         self.editing = False
 
-    def on_done(self):
+    def on_done(self) -> None:
         self.marshall_arguments()
         if not self.confirm_deletions(self.parentApp.install_selections):
             return
@@ -464,77 +442,7 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
         self.parentApp.user_cancelled = False
         self.editing = False
 
-    ########## This routine monitors the child process that is performing model installation and removal #####
-    def while_waiting(self):
-        """Called during idle periods. Main task is to update the Log Messages box with messages
-        from the child process that does the actual installation/removal"""
-        c = self.subprocess_connection
-        if not c:
-            return
-
-        monitor_widget = self.monitor.entry_widget
-        while c.poll():
-            try:
-                data = c.recv_bytes().decode("utf-8")
-                data.strip("\n")
-
-                # processing child is requesting user input to select the
-                # right configuration file
-                if data.startswith("*need v2 config"):
-                    _, model_path, *_ = data.split(":", 2)
-                    self._return_v2_config(model_path)
-
-                # processing child is done
-                elif data == "*done*":
-                    self._close_subprocess_and_regenerate_form()
-                    break
-
-                # update the log message box
-                else:
-                    data = make_printable(data)
-                    data = data.replace("[A", "")
-                    monitor_widget.buffer(
-                        textwrap.wrap(
-                            data,
-                            width=monitor_widget.width,
-                            subsequent_indent="   ",
-                        ),
-                        scroll_end=True,
-                    )
-                    self.display()
-            except (EOFError, OSError):
-                self.subprocess_connection = None
-
-    def _return_v2_config(self, model_path: str):
-        c = self.subprocess_connection
-        model_name = Path(model_path).name
-        message = select_stable_diffusion_config_file(model_name=model_name)
-        c.send_bytes(message.encode("utf-8"))
-
-    def _close_subprocess_and_regenerate_form(self):
-        app = self.parentApp
-        self.subprocess_connection.close()
-        self.subprocess_connection = None
-        self.monitor.entry_widget.buffer(["** Action Complete **"])
-        self.display()
-
-        # rebuild the form, saving and restoring some of the fields that need to be preserved.
-        saved_messages = self.monitor.entry_widget.values
-
-        app.main_form = app.addForm(
-            "MAIN",
-            addModelsForm,
-            name="Install Stable Diffusion Models",
-            multipage=self.multipage,
-        )
-        app.switchForm("MAIN")
-
-        app.main_form.monitor.entry_widget.values = saved_messages
-        app.main_form.monitor.entry_widget.buffer([""], scroll_end=True)
-        # app.main_form.pipeline_models['autoload_directory'].value = autoload_dir
-        # app.main_form.pipeline_models['autoscan_on_startup'].value = autoscan
-
-    def marshall_arguments(self):
+    def marshall_arguments(self) -> None:
         """
         Assemble arguments and store as attributes of the application:
         .starter_models: dict of model names to install from INITIAL_CONFIGURE.yaml
@@ -564,46 +472,24 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
             models_to_install = [x for x in selected if not self.all_models[x].installed]
             models_to_remove = [x for x in section["models"] if x not in selected and self.all_models[x].installed]
             selections.remove_models.extend(models_to_remove)
-            selections.install_models.extend(
-                all_models[x].path or all_models[x].repo_id
-                for x in models_to_install
-                if all_models[x].path or all_models[x].repo_id
-            )
+            selections.install_models.extend([all_models[x] for x in models_to_install])
 
         # models located in the 'download_ids" section
         for section in ui_sections:
             if downloads := section.get("download_ids"):
-                selections.install_models.extend(downloads.value.split())
-
-        # NOT NEEDED - DONE IN BACKEND NOW
-        # # special case for the ipadapter_models. If any of the adapters are
-        # # chosen, then we add the corresponding encoder(s) to the install list.
-        # section = self.ipadapter_models
-        # if section.get("models_selected"):
-        #     selected_adapters = [
-        #         self.all_models[section["models"][x]].name for x in section.get("models_selected").value
-        #     ]
-        #     encoders = []
-        #     if any(["sdxl" in x for x in selected_adapters]):
-        #         encoders.append("ip_adapter_sdxl_image_encoder")
-        #     if any(["sd15" in x for x in selected_adapters]):
-        #         encoders.append("ip_adapter_sd_image_encoder")
-        #     for encoder in encoders:
-        #         key = f"any/clip_vision/{encoder}"
-        #         repo_id = f"InvokeAI/{encoder}"
-        #         if key not in self.all_models:
-        #             selections.install_models.append(repo_id)
+                models = [UnifiedModelInfo(source=x) for x in downloads.value.split()]
+                selections.install_models.extend(models)
 
 
-class AddModelApplication(npyscreen.NPSAppManaged):
-    def __init__(self, opt):
+class AddModelApplication(npyscreen.NPSAppManaged):  # type: ignore
+    def __init__(self, opt: Namespace, install_helper: InstallHelper):
         super().__init__()
         self.program_opts = opt
         self.user_cancelled = False
-        # self.autoload_pending = True
         self.install_selections = InstallSelections()
+        self.install_helper = install_helper
 
-    def onStart(self):
+    def onStart(self) -> None:
         npyscreen.setTheme(npyscreen.Themes.DefaultTheme)
         self.main_form = self.addForm(
             "MAIN",
@@ -613,138 +499,62 @@ class AddModelApplication(npyscreen.NPSAppManaged):
         )
 
 
-class StderrToMessage:
-    def __init__(self, connection: Connection):
-        self.connection = connection
-
-    def write(self, data: str):
-        self.connection.send_bytes(data.encode("utf-8"))
-
-    def flush(self):
-        pass
+def list_models(installer: ModelInstallServiceBase, model_type: ModelType):
+    """Print out all models of type model_type."""
+    models = installer.record_store.search_by_attr(model_type=model_type)
+    print(f"Installed models of type `{model_type}`:")
+    for model in models:
+        path = (config.models_path / model.path).resolve()
+        print(f"{model.name:40}{model.base.value:5}{model.type.value:8}{model.format.value:12}{path}")
 
 
 # --------------------------------------------------------
-def ask_user_for_prediction_type(model_path: Path, tui_conn: Connection = None) -> SchedulerPredictionType:
-    if tui_conn:
-        logger.debug("Waiting for user response...")
-        return _ask_user_for_pt_tui(model_path, tui_conn)
-    else:
-        return _ask_user_for_pt_cmdline(model_path)
-
-
-def _ask_user_for_pt_cmdline(model_path: Path) -> Optional[SchedulerPredictionType]:
-    choices = [SchedulerPredictionType.Epsilon, SchedulerPredictionType.VPrediction, None]
-    print(
-        f"""
-Please select the scheduler prediction type of the checkpoint named {model_path.name}:
-[1] "epsilon" - most v1.5 models and v2 models trained on 512 pixel images
-[2] "vprediction" - v2 models trained on 768 pixel images and a few v1.5 models
-[3] Accept the best guess;  you can fix it in the Web UI later
-"""
-    )
-    choice = None
-    ok = False
-    while not ok:
-        try:
-            choice = input("select [3]> ").strip()
-            if not choice:
-                return None
-            choice = choices[int(choice) - 1]
-            ok = True
-        except (ValueError, IndexError):
-            print(f"{choice} is not a valid choice")
-        except EOFError:
-            return
-    return choice
-
-
-def _ask_user_for_pt_tui(model_path: Path, tui_conn: Connection) -> SchedulerPredictionType:
-    tui_conn.send_bytes(f"*need v2 config for:{model_path}".encode("utf-8"))
-    # note that we don't do any status checking here
-    response = tui_conn.recv_bytes().decode("utf-8")
-    if response is None:
-        return None
-    elif response == "epsilon":
-        return SchedulerPredictionType.epsilon
-    elif response == "v":
-        return SchedulerPredictionType.VPrediction
-    elif response == "guess":
-        return None
-    else:
-        return None
-
-
-# --------------------------------------------------------
-def process_and_execute(
-    opt: Namespace,
-    selections: InstallSelections,
-    conn_out: Connection = None,
-):
-    # need to reinitialize config in subprocess
-    config = InvokeAIAppConfig.get_config()
-    args = ["--root", opt.root] if opt.root else []
-    config.parse_args(args)
-
-    # set up so that stderr is sent to conn_out
-    if conn_out:
-        translator = StderrToMessage(conn_out)
-        sys.stderr = translator
-        sys.stdout = translator
-        logger = InvokeAILogger.get_logger()
-        logger.handlers.clear()
-        logger.addHandler(logging.StreamHandler(translator))
-
-    installer = ModelInstall(config, prediction_type_helper=lambda x: ask_user_for_prediction_type(x, conn_out))
-    installer.install(selections)
-
-    if conn_out:
-        conn_out.send_bytes("*done*".encode("utf-8"))
-        conn_out.close()
-
-
-# --------------------------------------------------------
-def select_and_download_models(opt: Namespace):
+def select_and_download_models(opt: Namespace) -> None:
+    """Prompt user for install/delete selections and execute."""
     precision = "float32" if opt.full_precision else choose_precision(torch.device(choose_torch_device()))
-    config.precision = precision
-    installer = ModelInstall(config, prediction_type_helper=ask_user_for_prediction_type)
+    # unsure how to avoid a typing complaint in the next line: config.precision is an enumerated Literal
+    config.precision = precision  # type: ignore
+    install_helper = InstallHelper(config, logger)
+    installer = install_helper.installer
+
     if opt.list_models:
-        installer.list_models(opt.list_models)
+        list_models(installer, opt.list_models)
+
     elif opt.add or opt.delete:
-        selections = InstallSelections(install_models=opt.add or [], remove_models=opt.delete or [])
-        installer.install(selections)
+        selections = InstallSelections(
+            install_models=[UnifiedModelInfo(source=x) for x in (opt.add or [])], remove_models=opt.delete or []
+        )
+        install_helper.add_or_delete(selections)
+
     elif opt.default_only:
-        selections = InstallSelections(install_models=installer.default_model())
-        installer.install(selections)
+        default_model = install_helper.default_model()
+        assert default_model is not None
+        selections = InstallSelections(install_models=[default_model])
+        install_helper.add_or_delete(selections)
+
     elif opt.yes_to_all:
-        selections = InstallSelections(install_models=installer.recommended_models())
-        installer.install(selections)
+        selections = InstallSelections(install_models=install_helper.recommended_models())
+        install_helper.add_or_delete(selections)
 
     # this is where the TUI is called
     else:
-        # needed to support the probe() method running under a subprocess
-        torch.multiprocessing.set_start_method("spawn")
-
         if not set_min_terminal_size(MIN_COLS, MIN_LINES):
             raise WindowTooSmallException(
                 "Could not increase terminal size. Try running again with a larger window or smaller font size."
             )
 
-        installApp = AddModelApplication(opt)
+        installApp = AddModelApplication(opt, install_helper)
         try:
             installApp.run()
-        except KeyboardInterrupt as e:
-            if hasattr(installApp, "main_form"):
-                if installApp.main_form.subprocess and installApp.main_form.subprocess.is_alive():
-                    logger.info("Terminating subprocesses")
-                    installApp.main_form.subprocess.terminate()
-                    installApp.main_form.subprocess = None
-            raise e
-        process_and_execute(opt, installApp.install_selections)
+        except KeyboardInterrupt:
+            print("Aborted...")
+            sys.exit(-1)
+
+        install_helper.add_or_delete(installApp.install_selections)
 
 
 # -------------------------------------
-def main():
+def main() -> None:
     parser = argparse.ArgumentParser(description="InvokeAI model downloader")
     parser.add_argument(
         "--add",
@@ -754,7 +564,7 @@ def main():
     parser.add_argument(
         "--delete",
         nargs="*",
-        help="List of names of models to idelete",
+        help="List of names of models to delete. Use type:name to disambiguate, as in `controlnet:my_model`",
     )
     parser.add_argument(
         "--full-precision",
@@ -781,14 +591,6 @@ def main():
         choices=[x.value for x in ModelType],
         help="list installed models",
     )
-    parser.add_argument(
-        "--config_file",
-        "-c",
-        dest="config_file",
-        type=str,
-        default=None,
-        help="path to configuration file to create",
-    )
     parser.add_argument(
         "--root_dir",
         dest="root",
diff --git a/invokeai/frontend/install/model_install2.py b/invokeai/frontend/install/model_install.py.OLD
similarity index 57%
rename from invokeai/frontend/install/model_install2.py
rename to invokeai/frontend/install/model_install.py.OLD
index 22b132370e..e23538ffd6 100644
--- a/invokeai/frontend/install/model_install2.py
+++ b/invokeai/frontend/install/model_install.py.OLD
@@ -6,45 +6,47 @@
 
 """
 This is the npyscreen frontend to the model installation application.
-It is currently named model_install2.py, but will ultimately replace model_install.py.
+The work is actually done in backend code in model_install_backend.py.
 """
 
 import argparse
 import curses
+import logging
 import sys
+import textwrap
 import traceback
-import warnings
 from argparse import Namespace
+from multiprocessing import Process
+from multiprocessing.connection import Connection, Pipe
+from pathlib import Path
 from shutil import get_terminal_size
-from typing import Any, Dict, List, Optional, Set
+from typing import Optional
 
 import npyscreen
 import torch
 from npyscreen import widget
 
 from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.app.services.model_install import ModelInstallServiceBase
-from invokeai.backend.install.install_helper import InstallHelper, InstallSelections, UnifiedModelInfo
-from invokeai.backend.model_manager import ModelType
+from invokeai.backend.install.model_install_backend import InstallSelections, ModelInstall, SchedulerPredictionType
+from invokeai.backend.model_management import ModelManager, ModelType
 from invokeai.backend.util import choose_precision, choose_torch_device
 from invokeai.backend.util.logging import InvokeAILogger
 from invokeai.frontend.install.widgets import (
     MIN_COLS,
     MIN_LINES,
+    BufferBox,
     CenteredTitleText,
     CyclingForm,
     MultiSelectColumns,
     SingleSelectColumns,
     TextBox,
     WindowTooSmallException,
+    select_stable_diffusion_config_file,
     set_min_terminal_size,
 )
 
-warnings.filterwarnings("ignore", category=UserWarning)  # noqa: E402
 config = InvokeAIAppConfig.get_config()
-logger = InvokeAILogger.get_logger("ModelInstallService")
-logger.setLevel("WARNING")
-# logger.setLevel('DEBUG')
+logger = InvokeAILogger.get_logger()
 
 # build a table mapping all non-printable characters to None
 # for stripping control characters
@@ -56,42 +58,44 @@ MAX_OTHER_MODELS = 72
 
 
 def make_printable(s: str) -> str:
-    """Replace non-printable characters in a string."""
+    """Replace non-printable characters in a string"""
     return s.translate(NOPRINT_TRANS_TABLE)
 
 
 class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
-    """Main form for interactive TUI."""
-
     # for responsive resizing set to False, but this seems to cause a crash!
     FIX_MINIMUM_SIZE_WHEN_CREATED = True
 
     # for persistence
     current_tab = 0
 
-    def __init__(self, parentApp: npyscreen.NPSAppManaged, name: str, multipage: bool = False, **keywords: Any):
+    def __init__(self, parentApp, name, multipage=False, *args, **keywords):
         self.multipage = multipage
         self.subprocess = None
-        super().__init__(parentApp=parentApp, name=name, **keywords)
+        super().__init__(parentApp=parentApp, name=name, *args, **keywords)  # noqa: B026 # TODO: maybe this is bad?
 
-    def create(self) -> None:
-        self.installer = self.parentApp.install_helper.installer
-        self.model_labels = self._get_model_labels()
+    def create(self):
         self.keypress_timeout = 10
         self.counter = 0
         self.subprocess_connection = None
 
+        if not config.model_conf_path.exists():
+            with open(config.model_conf_path, "w") as file:
+                print("# InvokeAI model configuration file", file=file)
+        self.installer = ModelInstall(config)
+        self.all_models = self.installer.all_models()
+        self.starter_models = self.installer.starter_models()
+        self.model_labels = self._get_model_labels()
         window_width, window_height = get_terminal_size()
 
-        # npyscreen has no typing hints
-        self.nextrely -= 1  # type: ignore
+        self.nextrely -= 1
         self.add_widget_intelligent(
             npyscreen.FixedText,
             value="Use ctrl-N and ctrl-P to move to the <N>ext and <P>revious fields. Cursor keys navigate, and <space> selects.",
             editable=False,
             color="CAUTION",
         )
-        self.nextrely += 1  # type: ignore
+        self.nextrely += 1
         self.tabs = self.add_widget_intelligent(
             SingleSelectColumns,
             values=[
@@ -111,9 +115,9 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
         )
         self.tabs.on_changed = self._toggle_tables
 
-        top_of_table = self.nextrely  # type: ignore
+        top_of_table = self.nextrely
         self.starter_pipelines = self.add_starter_pipelines()
-        bottom_of_table = self.nextrely  # type: ignore
+        bottom_of_table = self.nextrely
 
         self.nextrely = top_of_table
         self.pipeline_models = self.add_pipeline_widgets(
@@ -158,7 +162,15 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
 
         self.nextrely = bottom_of_table + 1
 
+        self.monitor = self.add_widget_intelligent(
+            BufferBox,
+            name="Log Messages",
+            editable=False,
+            max_height=6,
+        )
+
         self.nextrely += 1
+        done_label = "APPLY CHANGES"
         back_label = "BACK"
         cancel_label = "CANCEL"
         current_position = self.nextrely
@@ -174,8 +186,14 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
                 npyscreen.ButtonPress, name=cancel_label, when_pressed_function=self.on_cancel
             )
             self.nextrely = current_position
+            self.ok_button = self.add_widget_intelligent(
+                npyscreen.ButtonPress,
+                name=done_label,
+                relx=(window_width - len(done_label)) // 2,
+                when_pressed_function=self.on_execute,
+            )
 
-        label = "APPLY CHANGES"
+        label = "APPLY CHANGES & EXIT"
         self.nextrely = current_position
         self.done = self.add_widget_intelligent(
             npyscreen.ButtonPress,
@@ -192,16 +210,17 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
     ############# diffusers tab ##########
     def add_starter_pipelines(self) -> dict[str, npyscreen.widget]:
         """Add widgets responsible for selecting diffusers models"""
-        widgets: Dict[str, npyscreen.widget] = {}
+        widgets = {}
+        models = self.all_models
+        starters = self.starter_models
+        starter_model_labels = self.model_labels
 
-        all_models = self.all_models  # master dict of all models, indexed by key
-        model_list = [x for x in self.starter_models if all_models[x].type in ["main", "vae"]]
-        model_labels = [self.model_labels[x] for x in model_list]
+        self.installed_models = sorted([x for x in starters if models[x].installed])
 
         widgets.update(
             label1=self.add_widget_intelligent(
                 CenteredTitleText,
-                name="Select from a starter set of Stable Diffusion models from HuggingFace and Civitae.",
+                name="Select from a starter set of Stable Diffusion models from HuggingFace.",
                 editable=False,
                 labelColor="CAUTION",
             )
@@ -211,24 +230,23 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
         # if user has already installed some initial models, then don't patronize them
         # by showing more recommendations
         show_recommended = len(self.installed_models) == 0
-
-        checked = [
-            model_list.index(x)
-            for x in model_list
-            if (show_recommended and all_models[x].recommended) or all_models[x].installed
-        ]
+        keys = [x for x in models.keys() if x in starters]
         widgets.update(
             models_selected=self.add_widget_intelligent(
                 MultiSelectColumns,
                 columns=1,
                 name="Install Starter Models",
-                values=model_labels,
-                value=checked,
-                max_height=len(model_list) + 1,
+                values=[starter_model_labels[x] for x in keys],
+                value=[
+                    keys.index(x)
+                    for x in keys
+                    if (show_recommended and models[x].recommended) or (x in self.installed_models)
+                ],
+                max_height=len(starters) + 1,
                 relx=4,
                 scroll_exit=True,
             ),
-            models=model_list,
+            models=keys,
         )
 
         self.nextrely += 1
@@ -239,18 +257,14 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
         self,
         model_type: ModelType,
         window_width: int = 120,
-        install_prompt: Optional[str] = None,
-        exclude: Optional[Set[str]] = None,
+        install_prompt: str = None,
+        exclude: set = None,
     ) -> dict[str, npyscreen.widget]:
         """Generic code to create model selection widgets"""
         if exclude is None:
             exclude = set()
-        widgets: Dict[str, npyscreen.widget] = {}
-        all_models = self.all_models
-        model_list = sorted(
-            [x for x in all_models if all_models[x].type == model_type and x not in exclude],
-            key=lambda x: all_models[x].name or "",
-        )
+        widgets = {}
+        model_list = [x for x in self.all_models if self.all_models[x].model_type == model_type and x not in exclude]
         model_labels = [self.model_labels[x] for x in model_list]
 
         show_recommended = len(self.installed_models) == 0
@@ -286,7 +300,7 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
                     value=[
                         model_list.index(x)
                         for x in model_list
-                        if (show_recommended and all_models[x].recommended) or all_models[x].installed
+                        if (show_recommended and self.all_models[x].recommended) or self.all_models[x].installed
                     ],
                     max_height=len(model_list) // columns + 1,
                     relx=4,
@@ -310,7 +324,7 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
             download_ids=self.add_widget_intelligent(
                 TextBox,
                 name="Additional URLs, or HuggingFace repo_ids to install (Space separated. Use shift-control-V to paste):",
-                max_height=6,
+                max_height=4,
                 scroll_exit=True,
                 editable=True,
             )
@@ -335,13 +349,13 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
 
         return widgets
 
-    def resize(self) -> None:
+    def resize(self):
         super().resize()
         if s := self.starter_pipelines.get("models_selected"):
-            if model_list := self.starter_pipelines.get("models"):
-                s.values = [self.model_labels[x] for x in model_list]
+            keys = [x for x in self.all_models.keys() if x in self.starter_models]
+            s.values = [self.model_labels[x] for x in keys]
 
-    def _toggle_tables(self, value: List[int]) -> None:
+    def _toggle_tables(self, value=None):
         selected_tab = value[0]
         widgets = [
             self.starter_pipelines,
@@ -371,18 +385,17 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
         self.display()
 
     def _get_model_labels(self) -> dict[str, str]:
-        """Return a list of trimmed labels for all models."""
         window_width, window_height = get_terminal_size()
         checkbox_width = 4
         spacing_width = 2
-        result = {}
 
         models = self.all_models
-        label_width = max([len(models[x].name or "") for x in self.starter_models])
+        label_width = max([len(models[x].name) for x in models])
         description_width = window_width - label_width - checkbox_width - spacing_width
 
-        for key in self.all_models:
-            description = models[key].description
+        result = {}
+        for x in models.keys():
+            description = models[x].description
             description = (
                 description[0 : description_width - 3] + "..."
                 if description and len(description) > description_width
@@ -390,8 +403,7 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
                 if description
                 else ""
             )
-            result[key] = f"%-{label_width}s %s" % (models[key].name, description)
-
+            result[x] = f"%-{label_width}s %s" % (models[x].name, description)
         return result
 
     def _get_columns(self) -> int:
@@ -401,40 +413,50 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
 
     def confirm_deletions(self, selections: InstallSelections) -> bool:
         remove_models = selections.remove_models
-        if remove_models:
-            model_names = [self.all_models[x].name or "" for x in remove_models]
-            mods = "\n".join(model_names)
-            is_ok = npyscreen.notify_ok_cancel(
+        if len(remove_models) > 0:
+            mods = "\n".join([ModelManager.parse_key(x)[0] for x in remove_models])
+            return npyscreen.notify_ok_cancel(
                 f"These unchecked models will be deleted from disk. Continue?\n---------\n{mods}"
             )
-            assert isinstance(is_ok, bool)  # npyscreen doesn't have return type annotations
-            return is_ok
         else:
             return True
 
-    @property
-    def all_models(self) -> Dict[str, UnifiedModelInfo]:
-        # npyscreen doesn't having typing hints
-        return self.parentApp.install_helper.all_models  # type: ignore
+    def on_execute(self):
+        self.marshall_arguments()
+        app = self.parentApp
+        if not self.confirm_deletions(app.install_selections):
+            return
 
-    @property
-    def starter_models(self) -> List[str]:
-        return self.parentApp.install_helper._starter_models  # type: ignore
+        self.monitor.entry_widget.buffer(["Processing..."], scroll_end=True)
+        self.ok_button.hidden = True
+        self.display()
 
-    @property
-    def installed_models(self) -> List[str]:
-        return self.parentApp.install_helper._installed_models  # type: ignore
+        # TO DO: Spawn a worker thread, not a subprocess
+        parent_conn, child_conn = Pipe()
+        p = Process(
+            target=process_and_execute,
+            kwargs={
+                "opt": app.program_opts,
+                "selections": app.install_selections,
+                "conn_out": child_conn,
+            },
+        )
+        p.start()
+        child_conn.close()
+        self.subprocess_connection = parent_conn
+        self.subprocess = p
+        app.install_selections = InstallSelections()
 
-    def on_back(self) -> None:
+    def on_back(self):
         self.parentApp.switchFormPrevious()
         self.editing = False
 
-    def on_cancel(self) -> None:
+    def on_cancel(self):
         self.parentApp.setNextForm(None)
         self.parentApp.user_cancelled = True
         self.editing = False
 
-    def on_done(self) -> None:
+    def on_done(self):
         self.marshall_arguments()
         if not self.confirm_deletions(self.parentApp.install_selections):
             return
@@ -442,7 +464,77 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
         self.parentApp.user_cancelled = False
         self.editing = False
 
-    def marshall_arguments(self) -> None:
+    ########## This routine monitors the child process that is performing model installation and removal #####
+    def while_waiting(self):
+        """Called during idle periods. Main task is to update the Log Messages box with messages
+        from the child process that does the actual installation/removal"""
+        c = self.subprocess_connection
+        if not c:
+            return
+
+        monitor_widget = self.monitor.entry_widget
+        while c.poll():
+            try:
+                data = c.recv_bytes().decode("utf-8")
+                data.strip("\n")
+
+                # processing child is requesting user input to select the
+                # right configuration file
+                if data.startswith("*need v2 config"):
+                    _, model_path, *_ = data.split(":", 2)
+                    self._return_v2_config(model_path)
+
+                # processing child is done
+                elif data == "*done*":
+                    self._close_subprocess_and_regenerate_form()
+                    break
+
+                # update the log message box
+                else:
+                    data = make_printable(data)
+                    data = data.replace("[A", "")
+                    monitor_widget.buffer(
+                        textwrap.wrap(
+                            data,
+                            width=monitor_widget.width,
+                            subsequent_indent="   ",
+                        ),
+                        scroll_end=True,
+                    )
+                    self.display()
+            except (EOFError, OSError):
+                self.subprocess_connection = None
+
+    def _return_v2_config(self, model_path: str):
+        c = self.subprocess_connection
+        model_name = Path(model_path).name
+        message = select_stable_diffusion_config_file(model_name=model_name)
+        c.send_bytes(message.encode("utf-8"))
+
+    def _close_subprocess_and_regenerate_form(self):
+        app = self.parentApp
+        self.subprocess_connection.close()
+        self.subprocess_connection = None
+        self.monitor.entry_widget.buffer(["** Action Complete **"])
+        self.display()
+
+        # rebuild the form, saving and restoring some of the fields that need to be preserved.
+        saved_messages = self.monitor.entry_widget.values
+
+        app.main_form = app.addForm(
+            "MAIN",
+            addModelsForm,
+            name="Install Stable Diffusion Models",
+            multipage=self.multipage,
+        )
+        app.switchForm("MAIN")
+
+        app.main_form.monitor.entry_widget.values = saved_messages
+        app.main_form.monitor.entry_widget.buffer([""], scroll_end=True)
+        # app.main_form.pipeline_models['autoload_directory'].value = autoload_dir
+        # app.main_form.pipeline_models['autoscan_on_startup'].value = autoscan
+
+    def marshall_arguments(self):
         """
         Assemble arguments and store as attributes of the application:
         .starter_models: dict of model names to install from INITIAL_CONFIGURE.yaml
@@ -472,24 +564,46 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
             models_to_install = [x for x in selected if not self.all_models[x].installed]
             models_to_remove = [x for x in section["models"] if x not in selected and self.all_models[x].installed]
             selections.remove_models.extend(models_to_remove)
-            selections.install_models.extend([all_models[x] for x in models_to_install])
+            selections.install_models.extend(
+                all_models[x].path or all_models[x].repo_id
+                for x in models_to_install
+                if all_models[x].path or all_models[x].repo_id
+            )
 
         # models located in the 'download_ids" section
         for section in ui_sections:
             if downloads := section.get("download_ids"):
-                models = [UnifiedModelInfo(source=x) for x in downloads.value.split()]
-                selections.install_models.extend(models)
+                selections.install_models.extend(downloads.value.split())
+
+        # NOT NEEDED - DONE IN BACKEND NOW
+        # # special case for the ipadapter_models. If any of the adapters are
+        # # chosen, then we add the corresponding encoder(s) to the install list.
+        # section = self.ipadapter_models
+        # if section.get("models_selected"):
+        #     selected_adapters = [
+        #         self.all_models[section["models"][x]].name for x in section.get("models_selected").value
+        #     ]
+        #     encoders = []
+        #     if any(["sdxl" in x for x in selected_adapters]):
+        #         encoders.append("ip_adapter_sdxl_image_encoder")
+        #     if any(["sd15" in x for x in selected_adapters]):
+        #         encoders.append("ip_adapter_sd_image_encoder")
+        #     for encoder in encoders:
+        #         key = f"any/clip_vision/{encoder}"
+        #         repo_id = f"InvokeAI/{encoder}"
+        #         if key not in self.all_models:
+        #             selections.install_models.append(repo_id)
 
 
-class AddModelApplication(npyscreen.NPSAppManaged):  # type: ignore
-    def __init__(self, opt: Namespace, install_helper: InstallHelper):
+class AddModelApplication(npyscreen.NPSAppManaged):
+    def __init__(self, opt):
         super().__init__()
         self.program_opts = opt
         self.user_cancelled = False
+        # self.autoload_pending = True
         self.install_selections = InstallSelections()
-        self.install_helper = install_helper
 
-    def onStart(self) -> None:
+    def onStart(self):
         npyscreen.setTheme(npyscreen.Themes.DefaultTheme)
         self.main_form = self.addForm(
             "MAIN",
@@ -499,62 +613,138 @@ class AddModelApplication(npyscreen.NPSAppManaged):  # type: ignore
         )
 
 
-def list_models(installer: ModelInstallServiceBase, model_type: ModelType):
-    """Print out all models of type model_type."""
-    models = installer.record_store.search_by_attr(model_type=model_type)
-    print(f"Installed models of type `{model_type}`:")
-    for model in models:
-        path = (config.models_path / model.path).resolve()
-        print(f"{model.name:40}{model.base.value:5}{model.type.value:8}{model.format.value:12}{path}")
+class StderrToMessage:
+    def __init__(self, connection: Connection):
+        self.connection = connection
+
+    def write(self, data: str):
+        self.connection.send_bytes(data.encode("utf-8"))
+
+    def flush(self):
+        pass
 
 
 # --------------------------------------------------------
-def select_and_download_models(opt: Namespace) -> None:
-    """Prompt user for install/delete selections and execute."""
+def ask_user_for_prediction_type(model_path: Path, tui_conn: Connection = None) -> SchedulerPredictionType:
+    if tui_conn:
+        logger.debug("Waiting for user response...")
+        return _ask_user_for_pt_tui(model_path, tui_conn)
+    else:
+        return _ask_user_for_pt_cmdline(model_path)
+
+
+def _ask_user_for_pt_cmdline(model_path: Path) -> Optional[SchedulerPredictionType]:
+    choices = [SchedulerPredictionType.Epsilon, SchedulerPredictionType.VPrediction, None]
+    print(
+        f"""
+Please select the scheduler prediction type of the checkpoint named {model_path.name}:
+[1] "epsilon" - most v1.5 models and v2 models trained on 512 pixel images
+[2] "vprediction" - v2 models trained on 768 pixel images and a few v1.5 models
+[3] Accept the best guess;  you can fix it in the Web UI later
+"""
+    )
+    choice = None
+    ok = False
+    while not ok:
+        try:
+            choice = input("select [3]> ").strip()
+            if not choice:
+                return None
+            choice = choices[int(choice) - 1]
+            ok = True
+        except (ValueError, IndexError):
+            print(f"{choice} is not a valid choice")
+        except EOFError:
+            return
+    return choice
+
+
+def _ask_user_for_pt_tui(model_path: Path, tui_conn: Connection) -> SchedulerPredictionType:
+    tui_conn.send_bytes(f"*need v2 config for:{model_path}".encode("utf-8"))
+    # note that we don't do any status checking here
+    response = tui_conn.recv_bytes().decode("utf-8")
+    if response is None:
+        return None
+    elif response == "epsilon":
+        return SchedulerPredictionType.epsilon
+    elif response == "v":
+        return SchedulerPredictionType.VPrediction
+    elif response == "guess":
+        return None
+    else:
+        return None
+
+
+# --------------------------------------------------------
+def process_and_execute(
+    opt: Namespace,
+    selections: InstallSelections,
+    conn_out: Connection = None,
+):
+    # need to reinitialize config in subprocess
+    config = InvokeAIAppConfig.get_config()
+    args = ["--root", opt.root] if opt.root else []
+    config.parse_args(args)
+
+    # set up so that stderr is sent to conn_out
+    if conn_out:
+        translator = StderrToMessage(conn_out)
+        sys.stderr = translator
+        sys.stdout = translator
+        logger = InvokeAILogger.get_logger()
+        logger.handlers.clear()
+        logger.addHandler(logging.StreamHandler(translator))
+
+    installer = ModelInstall(config, prediction_type_helper=lambda x: ask_user_for_prediction_type(x, conn_out))
+    installer.install(selections)
+
+    if conn_out:
+        conn_out.send_bytes("*done*".encode("utf-8"))
+        conn_out.close()
+
+
+# --------------------------------------------------------
+def select_and_download_models(opt: Namespace):
     precision = "float32" if opt.full_precision else choose_precision(torch.device(choose_torch_device()))
-    # unsure how to avoid a typing complaint in the next line: config.precision is an enumerated Literal
-    config.precision = precision  # type: ignore
-    install_helper = InstallHelper(config, logger)
-    installer = install_helper.installer
-
+    config.precision = precision
+    installer = ModelInstall(config, prediction_type_helper=ask_user_for_prediction_type)
     if opt.list_models:
-        list_models(installer, opt.list_models)
-
+        installer.list_models(opt.list_models)
     elif opt.add or opt.delete:
-        selections = InstallSelections(
-            install_models=[UnifiedModelInfo(source=x) for x in (opt.add or [])], remove_models=opt.delete or []
-        )
-        install_helper.add_or_delete(selections)
-
+        selections = InstallSelections(install_models=opt.add or [], remove_models=opt.delete or [])
+        installer.install(selections)
     elif opt.default_only:
-        default_model = install_helper.default_model()
-        assert default_model is not None
-        selections = InstallSelections(install_models=[default_model])
-        install_helper.add_or_delete(selections)
-
+        selections = InstallSelections(install_models=installer.default_model())
+        installer.install(selections)
     elif opt.yes_to_all:
-        selections = InstallSelections(install_models=install_helper.recommended_models())
-        install_helper.add_or_delete(selections)
+        selections = InstallSelections(install_models=installer.recommended_models())
+        installer.install(selections)
 
     # this is where the TUI is called
     else:
+        # needed to support the probe() method running under a subprocess
+        torch.multiprocessing.set_start_method("spawn")
+
         if not set_min_terminal_size(MIN_COLS, MIN_LINES):
             raise WindowTooSmallException(
                 "Could not increase terminal size. Try running again with a larger window or smaller font size."
             )
 
-        installApp = AddModelApplication(opt, install_helper)
+        installApp = AddModelApplication(opt)
         try:
             installApp.run()
-        except KeyboardInterrupt:
-            print("Aborted...")
-            sys.exit(-1)
-
-        install_helper.add_or_delete(installApp.install_selections)
+        except KeyboardInterrupt as e:
+            if hasattr(installApp, "main_form"):
+                if installApp.main_form.subprocess and installApp.main_form.subprocess.is_alive():
+                    logger.info("Terminating subprocesses")
+                    installApp.main_form.subprocess.terminate()
+                    installApp.main_form.subprocess = None
+            raise e
+        process_and_execute(opt, installApp.install_selections)
 
 
 # -------------------------------------
-def main() -> None:
+def main():
     parser = argparse.ArgumentParser(description="InvokeAI model downloader")
     parser.add_argument(
         "--add",
@@ -564,7 +754,7 @@ def main() -> None:
     parser.add_argument(
         "--delete",
         nargs="*",
-        help="List of names of models to delete. Use type:name to disambiguate, as in `controlnet:my_model`",
+        help="List of names of models to idelete",
     )
     parser.add_argument(
         "--full-precision",
@@ -591,6 +781,14 @@ def main() -> None:
         choices=[x.value for x in ModelType],
         help="list installed models",
     )
+    parser.add_argument(
+        "--config_file",
+        "-c",
+        dest="config_file",
+        type=str,
+        default=None,
+        help="path to configuration file to create",
+    )
     parser.add_argument(
         "--root_dir",
         dest="root",
diff --git a/invokeai/frontend/install/widgets.py b/invokeai/frontend/install/widgets.py
index 5905ae29da..4dbc6349a0 100644
--- a/invokeai/frontend/install/widgets.py
+++ b/invokeai/frontend/install/widgets.py
@@ -267,6 +267,17 @@ class SingleSelectWithChanged(npyscreen.SelectOne):
             self.on_changed(self.value)
 
 
+class CheckboxWithChanged(npyscreen.Checkbox):
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        self.on_changed = None
+
+    def whenToggled(self):
+        super().whenToggled()
+        if self.on_changed:
+            self.on_changed(self.value)
+
+
 class SingleSelectColumnsSimple(SelectColumnBase, SingleSelectWithChanged):
     """Row of radio buttons. Spacebar to select."""
 
diff --git a/invokeai/frontend/merge/merge_diffusers2.py b/invokeai/frontend/merge/merge_diffusers.py.OLD
similarity index 100%
rename from invokeai/frontend/merge/merge_diffusers2.py
rename to invokeai/frontend/merge/merge_diffusers.py.OLD
diff --git a/pyproject.toml b/pyproject.toml
index 8b28375e29..2958e3629a 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -136,8 +136,7 @@ dependencies = [
 
 # full commands
 "invokeai-configure" = "invokeai.frontend.install.invokeai_configure:invokeai_configure"
-"invokeai-merge" = "invokeai.frontend.merge:invokeai_merge_diffusers"
-"invokeai-merge2" = "invokeai.frontend.merge.merge_diffusers2:main"
+"invokeai-merge" = "invokeai.frontend.merge.merge_diffusers:main"
 "invokeai-ti" = "invokeai.frontend.training:invokeai_textual_inversion"
 "invokeai-model-install" = "invokeai.frontend.install.model_install:main"
 "invokeai-model-install2" = "invokeai.frontend.install.model_install2:main"              # will eventually be renamed to invokeai-model-install
diff --git a/tests/test_model_manager.py b/tests/test_model_manager.py
deleted file mode 100644
index 3e48c7ed6f..0000000000
--- a/tests/test_model_manager.py
+++ /dev/null
@@ -1,47 +0,0 @@
-from pathlib import Path
-
-import pytest
-
-from invokeai.app.services.config.config_default import InvokeAIAppConfig
-from invokeai.backend import BaseModelType, ModelManager, ModelType, SubModelType
-
-BASIC_MODEL_NAME = ("SDXL base", BaseModelType.StableDiffusionXL, ModelType.Main)
-VAE_OVERRIDE_MODEL_NAME = ("SDXL with VAE", BaseModelType.StableDiffusionXL, ModelType.Main)
-VAE_NULL_OVERRIDE_MODEL_NAME = ("SDXL with empty VAE", BaseModelType.StableDiffusionXL, ModelType.Main)
-
-
-@pytest.fixture
-def model_manager(datadir) -> ModelManager:
-    InvokeAIAppConfig.get_config(root=datadir)
-    return ModelManager(datadir / "configs" / "relative_sub.models.yaml")
-
-
-def test_get_model_names(model_manager: ModelManager):
-    names = model_manager.model_names()
-    assert names[:2] == [BASIC_MODEL_NAME, VAE_OVERRIDE_MODEL_NAME]
-
-
-def test_get_model_path_for_diffusers(model_manager: ModelManager, datadir: Path):
-    model_config = model_manager._get_model_config(BASIC_MODEL_NAME[1], BASIC_MODEL_NAME[0], BASIC_MODEL_NAME[2])
-    top_model_path, is_override = model_manager._get_model_path(model_config)
-    expected_model_path = datadir / "models" / "sdxl" / "main" / "SDXL base 1_0"
-    assert top_model_path == expected_model_path
-    assert not is_override
-
-
-def test_get_model_path_for_overridden_vae(model_manager: ModelManager, datadir: Path):
-    model_config = model_manager._get_model_config(
-        VAE_OVERRIDE_MODEL_NAME[1], VAE_OVERRIDE_MODEL_NAME[0], VAE_OVERRIDE_MODEL_NAME[2]
-    )
-    vae_model_path, is_override = model_manager._get_model_path(model_config, SubModelType.Vae)
-    expected_vae_path = datadir / "models" / "sdxl" / "vae" / "sdxl-vae-fp16-fix"
-    assert vae_model_path == expected_vae_path
-    assert is_override
-
-
-def test_get_model_path_for_null_overridden_vae(model_manager: ModelManager, datadir: Path):
-    model_config = model_manager._get_model_config(
-        VAE_NULL_OVERRIDE_MODEL_NAME[1], VAE_NULL_OVERRIDE_MODEL_NAME[0], VAE_NULL_OVERRIDE_MODEL_NAME[2]
-    )
-    vae_model_path, is_override = model_manager._get_model_path(model_config, SubModelType.Vae)
-    assert not is_override

From 8db01ab1b3478e7b967c1354e84813f38c5723fe Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lstein@gmail.com>
Date: Fri, 9 Feb 2024 20:46:47 -0500
Subject: [PATCH 118/411] probe for required encoder for IPAdapters and add to
 config

---
 invokeai/app/invocations/ip_adapter.py   | 24 +-----------------------
 invokeai/backend/model_manager/config.py |  1 +
 invokeai/backend/model_manager/probe.py  | 13 +++++++++++++
 3 files changed, 15 insertions(+), 23 deletions(-)

diff --git a/invokeai/app/invocations/ip_adapter.py b/invokeai/app/invocations/ip_adapter.py
index 700b285a45..f64b3266bb 100644
--- a/invokeai/app/invocations/ip_adapter.py
+++ b/invokeai/app/invocations/ip_adapter.py
@@ -1,4 +1,3 @@
-import os
 from builtins import float
 from typing import List, Union
 
@@ -52,16 +51,6 @@ class IPAdapterField(BaseModel):
         return self
 
 
-def get_ip_adapter_image_encoder_model_id(model_path: str):
-    """Read the ID of the image encoder associated with the IP-Adapter at `model_path`."""
-    image_encoder_config_file = os.path.join(model_path, "image_encoder.txt")
-
-    with open(image_encoder_config_file, "r") as f:
-        image_encoder_model = f.readline().strip()
-
-    return image_encoder_model
-
-
 @invocation_output("ip_adapter_output")
 class IPAdapterOutput(BaseInvocationOutput):
     # Outputs
@@ -102,18 +91,7 @@ class IPAdapterInvocation(BaseInvocation):
     def invoke(self, context: InvocationContext) -> IPAdapterOutput:
         # Lookup the CLIP Vision encoder that is intended to be used with the IP-Adapter model.
         ip_adapter_info = context.services.model_records.get_model(self.ip_adapter_model.key)
-        # HACK(ryand): This is bad for a couple of reasons: 1) we are bypassing the model manager to read the model
-        # directly, and 2) we are reading from disk every time this invocation is called without caching the result.
-        # A better solution would be to store the image encoder model reference in the IP-Adapter model info, but this
-        # is currently messy due to differences between how the model info is generated when installing a model from
-        # disk vs. downloading the model.
-        # TODO (LS): Fix the issue above by:
-        #    1. Change IPAdapterConfig definition to include a field for the repo_id of the image encoder model.
-        #    2. Update probe.py to read `image_encoder.txt` and store it in the config.
-        #    3. Change below to get the image encoder from the configuration record.
-        image_encoder_model_id = get_ip_adapter_image_encoder_model_id(
-            os.path.join(context.services.configuration.get_config().models_path, ip_adapter_info.path)
-        )
+        image_encoder_model_id = ip_adapter_info.image_encoder_model_id
         image_encoder_model_name = image_encoder_model_id.split("/")[-1].strip()
         image_encoder_models = context.services.model_records.search_by_attr(
             model_name=image_encoder_model_name, base_model=BaseModelType.Any, model_type=ModelType.CLIPVision
diff --git a/invokeai/backend/model_manager/config.py b/invokeai/backend/model_manager/config.py
index 0dcd925c84..d2e7a0923a 100644
--- a/invokeai/backend/model_manager/config.py
+++ b/invokeai/backend/model_manager/config.py
@@ -263,6 +263,7 @@ class IPAdapterConfig(ModelConfigBase):
     """Model config for IP Adaptor format models."""
 
     type: Literal[ModelType.IPAdapter] = ModelType.IPAdapter
+    image_encoder_model_id: str
     format: Literal[ModelFormat.InvokeAI]
 
 
diff --git a/invokeai/backend/model_manager/probe.py b/invokeai/backend/model_manager/probe.py
index 55a9c0464a..e7d21c578f 100644
--- a/invokeai/backend/model_manager/probe.py
+++ b/invokeai/backend/model_manager/probe.py
@@ -78,6 +78,10 @@ class ProbeBase(object):
         """Get model scheduler prediction type."""
         return None
 
+    def get_image_encoder_model_id(self) -> Optional[str]:
+        """Get image encoder (IP adapters only)."""
+        return None
+
 
 class ModelProbe(object):
     PROBES: Dict[str, Dict[ModelType, type[ProbeBase]]] = {
@@ -153,6 +157,7 @@ class ModelProbe(object):
         fields["base"] = fields.get("base") or probe.get_base_type()
         fields["variant"] = fields.get("variant") or probe.get_variant_type()
         fields["prediction_type"] = fields.get("prediction_type") or probe.get_scheduler_prediction_type()
+        fields["image_encoder_model_id"] = fields.get("image_encoder_model_id") or probe.get_image_encoder_model_id()
         fields["name"] = fields.get("name") or cls.get_model_name(model_path)
         fields["description"] = (
             fields.get("description") or f"{fields['base'].value} {fields['type'].value} model {fields['name']}"
@@ -669,6 +674,14 @@ class IPAdapterFolderProbe(FolderProbeBase):
                 f"IP-Adapter had unexpected cross-attention dimension: {cross_attention_dim}."
             )
 
+    def get_image_encoder_model_id(self) -> Optional[str]:
+        encoder_id_path = self.model_path / "image_encoder.txt"
+        if not encoder_id_path.exists():
+            return None
+        with open(encoder_id_path, "r") as f:
+            image_encoder_model = f.readline().strip()
+        return image_encoder_model
+
 
 class CLIPVisionFolderProbe(FolderProbeBase):
     def get_base_type(self) -> BaseModelType:

From 7956602b193cab0eaacfe8a85007aa45f0569ad6 Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lstein@gmail.com>
Date: Fri, 9 Feb 2024 23:08:38 -0500
Subject: [PATCH 119/411] consolidate model manager parts into a single class

---
 invokeai/app/services/model_load/__init__.py  |   6 +
 .../services/model_load/model_load_base.py    |  22 +
 .../services/model_load/model_load_default.py |  54 +++
 .../app/services/model_manager/__init__.py    |  17 +-
 .../model_manager/model_manager_base.py       | 298 ++----------
 .../model_manager/model_manager_default.py    | 456 ++----------------
 invokeai/backend/__init__.py                  |   9 -
 invokeai/backend/model_manager/config.py      |   6 +-
 .../backend/model_manager/load/__init__.py    |   2 +-
 invokeai/backend/model_manager/search.py      |  12 +-
 10 files changed, 186 insertions(+), 696 deletions(-)
 create mode 100644 invokeai/app/services/model_load/__init__.py
 create mode 100644 invokeai/app/services/model_load/model_load_base.py
 create mode 100644 invokeai/app/services/model_load/model_load_default.py

diff --git a/invokeai/app/services/model_load/__init__.py b/invokeai/app/services/model_load/__init__.py
new file mode 100644
index 0000000000..b4a86e9348
--- /dev/null
+++ b/invokeai/app/services/model_load/__init__.py
@@ -0,0 +1,6 @@
+"""Initialization file for model load service module."""
+
+from .model_load_base import ModelLoadServiceBase
+from .model_load_default import ModelLoadService
+
+__all__ = ["ModelLoadServiceBase", "ModelLoadService"]
diff --git a/invokeai/app/services/model_load/model_load_base.py b/invokeai/app/services/model_load/model_load_base.py
new file mode 100644
index 0000000000..7228806e80
--- /dev/null
+++ b/invokeai/app/services/model_load/model_load_base.py
@@ -0,0 +1,22 @@
+# Copyright (c) 2024 Lincoln D. Stein and the InvokeAI Team
+"""Base class for model loader."""
+
+from abc import ABC, abstractmethod
+from typing import Optional
+
+from invokeai.backend.model_manager import AnyModelConfig, SubModelType
+from invokeai.backend.model_manager.load import LoadedModel
+
+
+class ModelLoadServiceBase(ABC):
+    """Wrapper around AnyModelLoader."""
+
+    @abstractmethod
+    def load_model_by_key(self, key: str, submodel_type: Optional[SubModelType] = None) -> LoadedModel:
+        """Given a model's key, load it and return the LoadedModel object."""
+        pass
+
+    @abstractmethod
+    def load_model_by_config(self, config: AnyModelConfig, submodel_type: Optional[SubModelType] = None) -> LoadedModel:
+        """Given a model's configuration, load it and return the LoadedModel object."""
+        pass
diff --git a/invokeai/app/services/model_load/model_load_default.py b/invokeai/app/services/model_load/model_load_default.py
new file mode 100644
index 0000000000..80e2fe161d
--- /dev/null
+++ b/invokeai/app/services/model_load/model_load_default.py
@@ -0,0 +1,54 @@
+# Copyright (c) 2024 Lincoln D. Stein and the InvokeAI Team
+"""Implementation of model loader service."""
+
+from typing import Optional
+
+from invokeai.app.services.config import InvokeAIAppConfig
+from invokeai.app.services.model_records import ModelRecordServiceBase
+from invokeai.backend.model_manager import AnyModelConfig, SubModelType
+from invokeai.backend.model_manager.load import AnyModelLoader, LoadedModel, ModelCache, ModelConvertCache
+from invokeai.backend.model_manager.load.convert_cache import ModelConvertCacheBase
+from invokeai.backend.model_manager.load.ram_cache import ModelCacheBase
+from invokeai.backend.util.logging import InvokeAILogger
+
+from .model_load_base import ModelLoadServiceBase
+
+
+class ModelLoadService(ModelLoadServiceBase):
+    """Wrapper around AnyModelLoader."""
+
+    def __init__(
+        self,
+        app_config: InvokeAIAppConfig,
+        record_store: ModelRecordServiceBase,
+        ram_cache: Optional[ModelCacheBase] = None,
+        convert_cache: Optional[ModelConvertCacheBase] = None,
+    ):
+        """Initialize the model load service."""
+        logger = InvokeAILogger.get_logger(self.__class__.__name__)
+        logger.setLevel(app_config.log_level.upper())
+        self._store = record_store
+        self._any_loader = AnyModelLoader(
+            app_config=app_config,
+            logger=logger,
+            ram_cache=ram_cache
+            or ModelCache(
+                max_cache_size=app_config.ram_cache_size,
+                max_vram_cache_size=app_config.vram_cache_size,
+                logger=logger,
+            ),
+            convert_cache=convert_cache
+            or ModelConvertCache(
+                cache_path=app_config.models_convert_cache_path,
+                max_size=app_config.convert_cache_size,
+            ),
+        )
+
+    def load_model_by_key(self, key: str, submodel_type: Optional[SubModelType] = None) -> LoadedModel:
+        """Given a model's key, load it and return the LoadedModel object."""
+        config = self._store.get_model(key)
+        return self.load_model_by_config(config, submodel_type)
+
+    def load_model_by_config(self, config: AnyModelConfig, submodel_type: Optional[SubModelType] = None) -> LoadedModel:
+        """Given a model's configuration, load it and return the LoadedModel object."""
+        return self._any_loader.load_model(config, submodel_type)
diff --git a/invokeai/app/services/model_manager/__init__.py b/invokeai/app/services/model_manager/__init__.py
index 3d6a9c248c..5e281922a8 100644
--- a/invokeai/app/services/model_manager/__init__.py
+++ b/invokeai/app/services/model_manager/__init__.py
@@ -1 +1,16 @@
-from .model_manager_default import ModelManagerService  # noqa F401
+"""Initialization file for model manager service."""
+
+from invokeai.backend.model_manager import AnyModel, AnyModelConfig, BaseModelType, ModelType, SubModelType
+from invokeai.backend.model_manager.load import LoadedModel
+
+from .model_manager_default import ModelManagerService
+
+__all__ = [
+    "ModelManagerService",
+    "AnyModel",
+    "AnyModelConfig",
+    "BaseModelType",
+    "ModelType",
+    "SubModelType",
+    "LoadedModel",
+]
diff --git a/invokeai/app/services/model_manager/model_manager_base.py b/invokeai/app/services/model_manager/model_manager_base.py
index f888c0ec97..c6e77fa163 100644
--- a/invokeai/app/services/model_manager/model_manager_base.py
+++ b/invokeai/app/services/model_manager/model_manager_base.py
@@ -1,283 +1,39 @@
 # Copyright (c) 2023 Lincoln D. Stein and the InvokeAI Team
 
-from __future__ import annotations
-
 from abc import ABC, abstractmethod
-from logging import Logger
-from pathlib import Path
-from typing import Callable, List, Literal, Optional, Tuple, Union
 
-from pydantic import Field
+from pydantic import BaseModel, Field
+from typing_extensions import Self
 
-from invokeai.app.services.config.config_default import InvokeAIAppConfig
-from invokeai.app.services.shared.invocation_context import InvocationContextData
-from invokeai.backend.model_management import (
-    AddModelResult,
-    BaseModelType,
-    LoadedModelInfo,
-    MergeInterpolationMethod,
-    ModelType,
-    SchedulerPredictionType,
-    SubModelType,
-)
-from invokeai.backend.model_management.model_cache import CacheStats
+from ..config import InvokeAIAppConfig
+from ..download import DownloadQueueServiceBase
+from ..events.events_base import EventServiceBase
+from ..model_install import ModelInstallServiceBase
+from ..model_load import ModelLoadServiceBase
+from ..model_records import ModelRecordServiceBase
+from ..shared.sqlite.sqlite_database import SqliteDatabase
 
 
-class ModelManagerServiceBase(ABC):
-    """Responsible for managing models on disk and in memory"""
+class ModelManagerServiceBase(BaseModel, ABC):
+    """Abstract base class for the model manager service."""
 
+    store: ModelRecordServiceBase = Field(description="An instance of the model record configuration service.")
+    install: ModelInstallServiceBase = Field(description="An instance of the model install service.")
+    load: ModelLoadServiceBase = Field(description="An instance of the model load service.")
+
+    @classmethod
     @abstractmethod
-    def __init__(
-        self,
-        config: InvokeAIAppConfig,
-        logger: Logger,
-    ):
+    def build_model_manager(
+        cls,
+        app_config: InvokeAIAppConfig,
+        db: SqliteDatabase,
+        download_queue: DownloadQueueServiceBase,
+        events: EventServiceBase,
+    ) -> Self:
         """
-        Initialize with the path to the models.yaml config file.
-        Optional parameters are the torch device type, precision, max_models,
-        and sequential_offload boolean. Note that the default device
-        type and precision are set up for a CUDA system running at half precision.
-        """
-        pass
-
-    @abstractmethod
-    def get_model(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-        submodel: Optional[SubModelType] = None,
-        context_data: Optional[InvocationContextData] = None,
-    ) -> LoadedModelInfo:
-        """Retrieve the indicated model with name and type.
-        submodel can be used to get a part (such as the vae)
-        of a diffusers pipeline."""
-        pass
-
-    @property
-    @abstractmethod
-    def logger(self):
-        pass
-
-    @abstractmethod
-    def model_exists(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-    ) -> bool:
-        pass
-
-    @abstractmethod
-    def model_info(self, model_name: str, base_model: BaseModelType, model_type: ModelType) -> dict:
-        """
-        Given a model name returns a dict-like (OmegaConf) object describing it.
-        Uses the exact format as the omegaconf stanza.
-        """
-        pass
-
-    @abstractmethod
-    def list_models(self, base_model: Optional[BaseModelType] = None, model_type: Optional[ModelType] = None) -> dict:
-        """
-        Return a dict of models in the format:
-        { model_type1:
-          { model_name1: {'status': 'active'|'cached'|'not loaded',
-                         'model_name' : name,
-                         'model_type' : SDModelType,
-                         'description': description,
-                         'format': 'folder'|'safetensors'|'ckpt'
-                         },
-            model_name2: { etc }
-          },
-          model_type2:
-            { model_name_n: etc
-        }
-        """
-        pass
-
-    @abstractmethod
-    def list_model(self, model_name: str, base_model: BaseModelType, model_type: ModelType) -> dict:
-        """
-        Return information about the model using the same format as list_models()
-        """
-        pass
-
-    @abstractmethod
-    def model_names(self) -> List[Tuple[str, BaseModelType, ModelType]]:
-        """
-        Returns a list of all the model names known.
-        """
-        pass
-
-    @abstractmethod
-    def add_model(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-        model_attributes: dict,
-        clobber: bool = False,
-    ) -> AddModelResult:
-        """
-        Update the named model with a dictionary of attributes. Will fail with an
-        assertion error if the name already exists. Pass clobber=True to overwrite.
-        On a successful update, the config will be changed in memory. Will fail
-        with an assertion error if provided attributes are incorrect or
-        the model name is missing. Call commit() to write changes to disk.
-        """
-        pass
-
-    @abstractmethod
-    def update_model(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-        model_attributes: dict,
-    ) -> AddModelResult:
-        """
-        Update the named model with a dictionary of attributes. Will fail with a
-        ModelNotFoundException if the name does not already exist.
-
-        On a successful update, the config will be changed in memory. Will fail
-        with an assertion error if provided attributes are incorrect or
-        the model name is missing. Call commit() to write changes to disk.
-        """
-        pass
-
-    @abstractmethod
-    def del_model(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-    ):
-        """
-        Delete the named model from configuration. If delete_files is true,
-        then the underlying weight file or diffusers directory will be deleted
-        as well. Call commit() to write to disk.
-        """
-        pass
-
-    @abstractmethod
-    def rename_model(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-        new_name: str,
-    ):
-        """
-        Rename the indicated model.
-        """
-        pass
-
-    @abstractmethod
-    def list_checkpoint_configs(self) -> List[Path]:
-        """
-        List the checkpoint config paths from ROOT/configs/stable-diffusion.
-        """
-        pass
-
-    @abstractmethod
-    def convert_model(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: Literal[ModelType.Main, ModelType.Vae],
-    ) -> AddModelResult:
-        """
-        Convert a checkpoint file into a diffusers folder, deleting the cached
-        version and deleting the original checkpoint file if it is in the models
-        directory.
-        :param model_name: Name of the model to convert
-        :param base_model: Base model type
-        :param model_type: Type of model ['vae' or 'main']
-
-        This will raise a ValueError unless the model is not a checkpoint. It will
-        also raise a ValueError in the event that there is a similarly-named diffusers
-        directory already in place.
-        """
-        pass
-
-    @abstractmethod
-    def heuristic_import(
-        self,
-        items_to_import: set[str],
-        prediction_type_helper: Optional[Callable[[Path], SchedulerPredictionType]] = None,
-    ) -> dict[str, AddModelResult]:
-        """Import a list of paths, repo_ids or URLs. Returns the set of
-        successfully imported items.
-        :param items_to_import: Set of strings corresponding to models to be imported.
-        :param prediction_type_helper: A callback that receives the Path of a Stable Diffusion 2 checkpoint model and returns a SchedulerPredictionType.
-
-        The prediction type helper is necessary to distinguish between
-        models based on Stable Diffusion 2 Base (requiring
-        SchedulerPredictionType.Epsilson) and Stable Diffusion 768
-        (requiring SchedulerPredictionType.VPrediction). It is
-        generally impossible to do this programmatically, so the
-        prediction_type_helper usually asks the user to choose.
-
-        The result is a set of successfully installed models. Each element
-        of the set is a dict corresponding to the newly-created OmegaConf stanza for
-        that model.
-        """
-        pass
-
-    @abstractmethod
-    def merge_models(
-        self,
-        model_names: List[str] = Field(
-            default=None, min_length=2, max_length=3, description="List of model names to merge"
-        ),
-        base_model: Union[BaseModelType, str] = Field(
-            default=None, description="Base model shared by all models to be merged"
-        ),
-        merged_model_name: str = Field(default=None, description="Name of destination model after merging"),
-        alpha: Optional[float] = 0.5,
-        interp: Optional[MergeInterpolationMethod] = None,
-        force: Optional[bool] = False,
-        merge_dest_directory: Optional[Path] = None,
-    ) -> AddModelResult:
-        """
-        Merge two to three diffusrs pipeline models and save as a new model.
-        :param model_names: List of 2-3 models to merge
-        :param base_model: Base model to use for all models
-        :param merged_model_name: Name of destination merged model
-        :param alpha: Alpha strength to apply to 2d and 3d model
-        :param interp: Interpolation method. None (default)
-        :param merge_dest_directory: Save the merged model to the designated directory (with 'merged_model_name' appended)
-        """
-        pass
-
-    @abstractmethod
-    def search_for_models(self, directory: Path) -> List[Path]:
-        """
-        Return list of all models found in the designated directory.
-        """
-        pass
-
-    @abstractmethod
-    def sync_to_config(self):
-        """
-        Re-read models.yaml, rescan the models directory, and reimport models
-        in the autoimport directories. Call after making changes outside the
-        model manager API.
-        """
-        pass
-
-    @abstractmethod
-    def collect_cache_stats(self, cache_stats: CacheStats):
-        """
-        Reset model cache statistics for graph with graph_id.
-        """
-        pass
-
-    @abstractmethod
-    def commit(self, conf_file: Optional[Path] = None) -> None:
-        """
-        Write current configuration out to the indicated file.
-        If no conf_file is provided, then replaces the
-        original file/database used to initialize the object.
+        Construct the model manager service instance.
+
+        Use it rather than the __init__ constructor. This class
+        method simplifies the construction considerably.
         """
         pass
diff --git a/invokeai/app/services/model_manager/model_manager_default.py b/invokeai/app/services/model_manager/model_manager_default.py
index c3712abf8e..ad0fd66dbb 100644
--- a/invokeai/app/services/model_manager/model_manager_default.py
+++ b/invokeai/app/services/model_manager/model_manager_default.py
@@ -1,421 +1,67 @@
 # Copyright (c) 2023 Lincoln D. Stein and the InvokeAI Team
+"""Implementation of ModelManagerServiceBase."""
 
-from __future__ import annotations
+from typing_extensions import Self
 
-from logging import Logger
-from pathlib import Path
-from typing import TYPE_CHECKING, Callable, List, Literal, Optional, Tuple, Union
-
-import torch
-from pydantic import Field
-
-from invokeai.app.services.config.config_default import InvokeAIAppConfig
-from invokeai.app.services.invocation_processor.invocation_processor_common import CanceledException
-from invokeai.app.services.invoker import Invoker
-from invokeai.app.services.shared.invocation_context import InvocationContextData
-from invokeai.backend.model_management import (
-    AddModelResult,
-    BaseModelType,
-    LoadedModelInfo,
-    MergeInterpolationMethod,
-    ModelManager,
-    ModelMerger,
-    ModelNotFoundException,
-    ModelType,
-    SchedulerPredictionType,
-    SubModelType,
-)
-from invokeai.backend.model_management.model_cache import CacheStats
-from invokeai.backend.model_management.model_search import FindModels
-from invokeai.backend.util import choose_precision, choose_torch_device
+from invokeai.backend.model_manager.load import ModelCache, ModelConvertCache
+from invokeai.backend.model_manager.metadata import ModelMetadataStore
+from invokeai.backend.util.logging import InvokeAILogger
 
+from ..config import InvokeAIAppConfig
+from ..download import DownloadQueueServiceBase
+from ..events.events_base import EventServiceBase
+from ..model_install import ModelInstallService
+from ..model_load import ModelLoadService
+from ..model_records import ModelRecordServiceSQL
+from ..shared.sqlite.sqlite_database import SqliteDatabase
 from .model_manager_base import ModelManagerServiceBase
 
-if TYPE_CHECKING:
-    pass
 
-
-# simple implementation
 class ModelManagerService(ModelManagerServiceBase):
-    """Responsible for managing models on disk and in memory"""
+    """
+    The ModelManagerService handles various aspects of model installation, maintenance and loading.
 
-    def __init__(
-        self,
-        config: InvokeAIAppConfig,
-        logger: Logger,
-    ):
+    It bundles three distinct services:
+    model_manager.store   -- Routines to manage the database of model configuration records.
+    model_manager.install -- Routines to install, move and delete models.
+    model_manager.load    -- Routines to load models into memory.
+    """
+
+    @classmethod
+    def build_model_manager(
+        cls,
+        app_config: InvokeAIAppConfig,
+        db: SqliteDatabase,
+        download_queue: DownloadQueueServiceBase,
+        events: EventServiceBase,
+    ) -> Self:
         """
-        Initialize with the path to the models.yaml config file.
-        Optional parameters are the torch device type, precision, max_models,
-        and sequential_offload boolean. Note that the default device
-        type and precision are set up for a CUDA system running at half precision.
+        Construct the model manager service instance.
+
+        For simplicity, use this class method rather than the __init__ constructor.
         """
-        if config.model_conf_path and config.model_conf_path.exists():
-            config_file = config.model_conf_path
-        else:
-            config_file = config.root_dir / "configs/models.yaml"
+        logger = InvokeAILogger.get_logger(cls.__name__)
+        logger.setLevel(app_config.log_level.upper())
 
-        logger.debug(f"Config file={config_file}")
-
-        device = torch.device(choose_torch_device())
-        device_name = torch.cuda.get_device_name() if device == torch.device("cuda") else ""
-        logger.info(f"GPU device = {device} {device_name}")
-
-        precision = config.precision
-        if precision == "auto":
-            precision = choose_precision(device)
-        dtype = torch.float32 if precision == "float32" else torch.float16
-
-        # this is transitional backward compatibility
-        # support for the deprecated `max_loaded_models`
-        # configuration value. If present, then the
-        # cache size is set to 2.5 GB times
-        # the number of max_loaded_models. Otherwise
-        # use new `ram_cache_size` config setting
-        max_cache_size = config.ram_cache_size
-
-        logger.debug(f"Maximum RAM cache size: {max_cache_size} GiB")
-
-        sequential_offload = config.sequential_guidance
-
-        self.mgr = ModelManager(
-            config=config_file,
-            device_type=device,
-            precision=dtype,
-            max_cache_size=max_cache_size,
-            sequential_offload=sequential_offload,
-            logger=logger,
+        ram_cache = ModelCache(
+            max_cache_size=app_config.ram_cache_size, max_vram_cache_size=app_config.vram_cache_size, logger=logger
         )
-        logger.info("Model manager service initialized")
-
-    def start(self, invoker: Invoker) -> None:
-        self._invoker: Optional[Invoker] = invoker
-
-    def get_model(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-        submodel: Optional[SubModelType] = None,
-        context_data: Optional[InvocationContextData] = None,
-    ) -> LoadedModelInfo:
-        """
-        Retrieve the indicated model. submodel can be used to get a
-        part (such as the vae) of a diffusers mode.
-        """
-
-        # we can emit model loading events if we are executing with access to the invocation context
-        if context_data is not None:
-            self._emit_load_event(
-                context_data=context_data,
-                model_name=model_name,
-                base_model=base_model,
-                model_type=model_type,
-                submodel=submodel,
-            )
-
-        loaded_model_info = self.mgr.get_model(
-            model_name,
-            base_model,
-            model_type,
-            submodel,
+        convert_cache = ModelConvertCache(
+            cache_path=app_config.models_convert_cache_path, max_size=app_config.convert_cache_size
         )
-
-        if context_data is not None:
-            self._emit_load_event(
-                context_data=context_data,
-                model_name=model_name,
-                base_model=base_model,
-                model_type=model_type,
-                submodel=submodel,
-                loaded_model_info=loaded_model_info,
-            )
-
-        return loaded_model_info
-
-    def model_exists(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-    ) -> bool:
-        """
-        Given a model name, returns True if it is a valid
-        identifier.
-        """
-        return self.mgr.model_exists(
-            model_name,
-            base_model,
-            model_type,
+        record_store = ModelRecordServiceSQL(db=db)
+        loader = ModelLoadService(
+            app_config=app_config,
+            record_store=record_store,
+            ram_cache=ram_cache,
+            convert_cache=convert_cache,
         )
-
-    def model_info(self, model_name: str, base_model: BaseModelType, model_type: ModelType) -> Union[dict, None]:
-        """
-        Given a model name returns a dict-like (OmegaConf) object describing it.
-        """
-        return self.mgr.model_info(model_name, base_model, model_type)
-
-    def model_names(self) -> List[Tuple[str, BaseModelType, ModelType]]:
-        """
-        Returns a list of all the model names known.
-        """
-        return self.mgr.model_names()
-
-    def list_models(
-        self, base_model: Optional[BaseModelType] = None, model_type: Optional[ModelType] = None
-    ) -> list[dict]:
-        """
-        Return a list of models.
-        """
-        return self.mgr.list_models(base_model, model_type)
-
-    def list_model(self, model_name: str, base_model: BaseModelType, model_type: ModelType) -> Union[dict, None]:
-        """
-        Return information about the model using the same format as list_models()
-        """
-        return self.mgr.list_model(model_name=model_name, base_model=base_model, model_type=model_type)
-
-    def add_model(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-        model_attributes: dict,
-        clobber: bool = False,
-    ) -> AddModelResult:
-        """
-        Update the named model with a dictionary of attributes. Will fail with an
-        assertion error if the name already exists. Pass clobber=True to overwrite.
-        On a successful update, the config will be changed in memory. Will fail
-        with an assertion error if provided attributes are incorrect or
-        the model name is missing. Call commit() to write changes to disk.
-        """
-        self.logger.debug(f"add/update model {model_name}")
-        return self.mgr.add_model(model_name, base_model, model_type, model_attributes, clobber)
-
-    def update_model(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-        model_attributes: dict,
-    ) -> AddModelResult:
-        """
-        Update the named model with a dictionary of attributes. Will fail with a
-        ModelNotFoundException exception if the name does not already exist.
-        On a successful update, the config will be changed in memory. Will fail
-        with an assertion error if provided attributes are incorrect or
-        the model name is missing. Call commit() to write changes to disk.
-        """
-        self.logger.debug(f"update model {model_name}")
-        if not self.model_exists(model_name, base_model, model_type):
-            raise ModelNotFoundException(f"Unknown model {model_name}")
-        return self.add_model(model_name, base_model, model_type, model_attributes, clobber=True)
-
-    def del_model(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-    ):
-        """
-        Delete the named model from configuration. If delete_files is true,
-        then the underlying weight file or diffusers directory will be deleted
-        as well.
-        """
-        self.logger.debug(f"delete model {model_name}")
-        self.mgr.del_model(model_name, base_model, model_type)
-        self.mgr.commit()
-
-    def convert_model(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: Literal[ModelType.Main, ModelType.Vae],
-        convert_dest_directory: Optional[Path] = Field(
-            default=None, description="Optional directory location for merged model"
-        ),
-    ) -> AddModelResult:
-        """
-        Convert a checkpoint file into a diffusers folder, deleting the cached
-        version and deleting the original checkpoint file if it is in the models
-        directory.
-        :param model_name: Name of the model to convert
-        :param base_model: Base model type
-        :param model_type: Type of model ['vae' or 'main']
-        :param convert_dest_directory: Save the converted model to the designated directory (`models/etc/etc` by default)
-
-        This will raise a ValueError unless the model is not a checkpoint. It will
-        also raise a ValueError in the event that there is a similarly-named diffusers
-        directory already in place.
-        """
-        self.logger.debug(f"convert model {model_name}")
-        return self.mgr.convert_model(model_name, base_model, model_type, convert_dest_directory)
-
-    def collect_cache_stats(self, cache_stats: CacheStats):
-        """
-        Reset model cache statistics for graph with graph_id.
-        """
-        self.mgr.cache.stats = cache_stats
-
-    def commit(self, conf_file: Optional[Path] = None):
-        """
-        Write current configuration out to the indicated file.
-        If no conf_file is provided, then replaces the
-        original file/database used to initialize the object.
-        """
-        return self.mgr.commit(conf_file)
-
-    def _emit_load_event(
-        self,
-        context_data: InvocationContextData,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-        submodel: Optional[SubModelType] = None,
-        loaded_model_info: Optional[LoadedModelInfo] = None,
-    ):
-        if self._invoker is None:
-            return
-
-        if self._invoker.services.queue.is_canceled(context_data.session_id):
-            raise CanceledException()
-
-        if loaded_model_info:
-            self._invoker.services.events.emit_model_load_completed(
-                queue_id=context_data.queue_id,
-                queue_item_id=context_data.queue_item_id,
-                queue_batch_id=context_data.batch_id,
-                graph_execution_state_id=context_data.session_id,
-                model_name=model_name,
-                base_model=base_model,
-                model_type=model_type,
-                submodel=submodel,
-                loaded_model_info=loaded_model_info,
-            )
-        else:
-            self._invoker.services.events.emit_model_load_started(
-                queue_id=context_data.queue_id,
-                queue_item_id=context_data.queue_item_id,
-                queue_batch_id=context_data.batch_id,
-                graph_execution_state_id=context_data.session_id,
-                model_name=model_name,
-                base_model=base_model,
-                model_type=model_type,
-                submodel=submodel,
-            )
-
-    @property
-    def logger(self):
-        return self.mgr.logger
-
-    def heuristic_import(
-        self,
-        items_to_import: set[str],
-        prediction_type_helper: Optional[Callable[[Path], SchedulerPredictionType]] = None,
-    ) -> dict[str, AddModelResult]:
-        """Import a list of paths, repo_ids or URLs. Returns the set of
-        successfully imported items.
-        :param items_to_import: Set of strings corresponding to models to be imported.
-        :param prediction_type_helper: A callback that receives the Path of a Stable Diffusion 2 checkpoint model and returns a SchedulerPredictionType.
-
-        The prediction type helper is necessary to distinguish between
-        models based on Stable Diffusion 2 Base (requiring
-        SchedulerPredictionType.Epsilson) and Stable Diffusion 768
-        (requiring SchedulerPredictionType.VPrediction). It is
-        generally impossible to do this programmatically, so the
-        prediction_type_helper usually asks the user to choose.
-
-        The result is a set of successfully installed models. Each element
-        of the set is a dict corresponding to the newly-created OmegaConf stanza for
-        that model.
-        """
-        return self.mgr.heuristic_import(items_to_import, prediction_type_helper)
-
-    def merge_models(
-        self,
-        model_names: List[str] = Field(
-            default=None, min_length=2, max_length=3, description="List of model names to merge"
-        ),
-        base_model: Union[BaseModelType, str] = Field(
-            default=None, description="Base model shared by all models to be merged"
-        ),
-        merged_model_name: str = Field(default=None, description="Name of destination model after merging"),
-        alpha: float = 0.5,
-        interp: Optional[MergeInterpolationMethod] = None,
-        force: bool = False,
-        merge_dest_directory: Optional[Path] = Field(
-            default=None, description="Optional directory location for merged model"
-        ),
-    ) -> AddModelResult:
-        """
-        Merge two to three diffusrs pipeline models and save as a new model.
-        :param model_names: List of 2-3 models to merge
-        :param base_model: Base model to use for all models
-        :param merged_model_name: Name of destination merged model
-        :param alpha: Alpha strength to apply to 2d and 3d model
-        :param interp: Interpolation method. None (default)
-        :param merge_dest_directory: Save the merged model to the designated directory (with 'merged_model_name' appended)
-        """
-        merger = ModelMerger(self.mgr)
-        try:
-            result = merger.merge_diffusion_models_and_save(
-                model_names=model_names,
-                base_model=base_model,
-                merged_model_name=merged_model_name,
-                alpha=alpha,
-                interp=interp,
-                force=force,
-                merge_dest_directory=merge_dest_directory,
-            )
-        except AssertionError as e:
-            raise ValueError(e)
-        return result
-
-    def search_for_models(self, directory: Path) -> List[Path]:
-        """
-        Return list of all models found in the designated directory.
-        """
-        search = FindModels([directory], self.logger)
-        return search.list_models()
-
-    def sync_to_config(self):
-        """
-        Re-read models.yaml, rescan the models directory, and reimport models
-        in the autoimport directories. Call after making changes outside the
-        model manager API.
-        """
-        return self.mgr.sync_to_config()
-
-    def list_checkpoint_configs(self) -> List[Path]:
-        """
-        List the checkpoint config paths from ROOT/configs/stable-diffusion.
-        """
-        config = self.mgr.app_config
-        conf_path = config.legacy_conf_path
-        root_path = config.root_path
-        return [(conf_path / x).relative_to(root_path) for x in conf_path.glob("**/*.yaml")]
-
-    def rename_model(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-        new_name: Optional[str] = None,
-        new_base: Optional[BaseModelType] = None,
-    ):
-        """
-        Rename the indicated model. Can provide a new name and/or a new base.
-        :param model_name: Current name of the model
-        :param base_model: Current base of the model
-        :param model_type: Model type (can't be changed)
-        :param new_name: New name for the model
-        :param new_base: New base for the model
-        """
-        self.mgr.rename_model(
-            base_model=base_model,
-            model_type=model_type,
-            model_name=model_name,
-            new_name=new_name,
-            new_base=new_base,
+        record_store._loader = loader  # yeah, there is a circular reference here
+        installer = ModelInstallService(
+            app_config=app_config,
+            record_store=record_store,
+            download_queue=download_queue,
+            metadata_store=ModelMetadataStore(db=db),
+            event_bus=events,
         )
+        return cls(store=record_store, install=installer, load=loader)
diff --git a/invokeai/backend/__init__.py b/invokeai/backend/__init__.py
index 54a1843d46..9fe97ee525 100644
--- a/invokeai/backend/__init__.py
+++ b/invokeai/backend/__init__.py
@@ -1,12 +1,3 @@
 """
 Initialization file for invokeai.backend
 """
-from .model_management import (  # noqa: F401
-    BaseModelType,
-    LoadedModelInfo,
-    ModelCache,
-    ModelManager,
-    ModelType,
-    SubModelType,
-)
-from .model_management.models import SilenceWarnings  # noqa: F401
diff --git a/invokeai/backend/model_manager/config.py b/invokeai/backend/model_manager/config.py
index d2e7a0923a..4534a4892f 100644
--- a/invokeai/backend/model_manager/config.py
+++ b/invokeai/backend/model_manager/config.py
@@ -21,7 +21,7 @@ Validation errors will raise an InvalidModelConfigException error.
 """
 import time
 from enum import Enum
-from typing import Literal, Optional, Type, Union
+from typing import Literal, Optional, Type, Union, Class
 
 import torch
 from diffusers import ModelMixin
@@ -333,9 +333,9 @@ class ModelConfigFactory(object):
     @classmethod
     def make_config(
         cls,
-        model_data: Union[dict, AnyModelConfig],
+        model_data: Union[Dict[str, Any], AnyModelConfig],
         key: Optional[str] = None,
-        dest_class: Optional[Type] = None,
+        dest_class: Optional[Type[Class]] = None,
         timestamp: Optional[float] = None,
     ) -> AnyModelConfig:
         """
diff --git a/invokeai/backend/model_manager/load/__init__.py b/invokeai/backend/model_manager/load/__init__.py
index e4c7077f78..966a739237 100644
--- a/invokeai/backend/model_manager/load/__init__.py
+++ b/invokeai/backend/model_manager/load/__init__.py
@@ -18,7 +18,7 @@ loaders = [x.stem for x in Path(Path(__file__).parent, "model_loaders").glob("*.
 for module in loaders:
     import_module(f"{__package__}.model_loaders.{module}")
 
-__all__ = ["AnyModelLoader", "LoadedModel"]
+__all__ = ["AnyModelLoader", "LoadedModel", "ModelCache", "ModelConvertCache"]
 
 
 def get_standalone_loader(app_config: Optional[InvokeAIAppConfig]) -> AnyModelLoader:
diff --git a/invokeai/backend/model_manager/search.py b/invokeai/backend/model_manager/search.py
index 4cc3caebe4..a54938fdd5 100644
--- a/invokeai/backend/model_manager/search.py
+++ b/invokeai/backend/model_manager/search.py
@@ -26,10 +26,10 @@ from pathlib import Path
 from typing import Callable, Optional, Set, Union
 
 from pydantic import BaseModel, Field
-
+from logging import Logger
 from invokeai.backend.util.logging import InvokeAILogger
 
-default_logger = InvokeAILogger.get_logger()
+default_logger: Logger = InvokeAILogger.get_logger()
 
 
 class SearchStats(BaseModel):
@@ -56,7 +56,7 @@ class ModelSearchBase(ABC, BaseModel):
     on_model_found      : Optional[Callable[[Path], bool]]      = Field(default=None, description="Called when a model is found.")          # noqa E221
     on_search_completed : Optional[Callable[[Set[Path]], None]] = Field(default=None, description="Called when search is complete.")        # noqa E221
     stats               : SearchStats                           = Field(default_factory=SearchStats, description="Summary statistics after search")  # noqa E221
-    logger              : InvokeAILogger                        = Field(default=default_logger, description="Logger instance.")     # noqa E221
+    logger              : Logger                                = Field(default=default_logger, description="Logger instance.")     # noqa E221
     # fmt: on
 
     class Config:
@@ -128,13 +128,13 @@ class ModelSearch(ModelSearchBase):
 
     def model_found(self, model: Path) -> None:
         self.stats.models_found += 1
-        if not self.on_model_found or self.on_model_found(model):
+        if self.on_model_found is None or self.on_model_found(model):
             self.stats.models_filtered += 1
             self.models_found.add(model)
 
     def search_completed(self) -> None:
-        if self.on_search_completed:
-            self.on_search_completed(self._models_found)
+        if self.on_search_completed is not None:
+            self.on_search_completed(self.models_found)
 
     def search(self, directory: Union[Path, str]) -> Set[Path]:
         self._directory = Path(directory)

From a23dedd2ee00c3d6bf6da6d71c78997bd311da30 Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lstein@gmail.com>
Date: Sat, 10 Feb 2024 18:09:45 -0500
Subject: [PATCH 120/411] make model manager v2 ready for PR review

- Replace legacy model manager service with the v2 manager.

- Update invocations to use new load interface.

- Fixed many but not all type checking errors in the invocations. Most
  were unrelated to model manager

- Updated routes. All the new routes live under the route tag
  `model_manager_v2`. To avoid confusion with the old routes,
  they have the URL prefix `/api/v2/models`. The old routes
  have been de-registered.

- Added a pytest for the loader.

- Updated documentation in contributing/MODEL_MANAGER.md
---
 docs/contributing/MODEL_MANAGER.md            | 223 ++++++++++++------
 invokeai/app/api/dependencies.py              |  29 +--
 .../{model_records.py => model_manager_v2.py} |  82 ++++---
 invokeai/app/api/routers/models.py            |   3 +-
 invokeai/app/api_app.py                       |   5 +-
 invokeai/app/invocations/compel.py            |  43 ++--
 invokeai/app/invocations/latent.py            | 168 ++++++++-----
 invokeai/app/invocations/model.py             |   2 +-
 invokeai/app/services/invocation_services.py  |   6 -
 .../invocation_stats_default.py               |   9 +-
 .../services/model_load/model_load_base.py    |  60 ++++-
 .../services/model_load/model_load_default.py | 117 ++++++++-
 .../model_manager/model_manager_base.py       |  38 ++-
 .../model_manager/model_manager_default.py    |  39 ++-
 .../model_records/model_records_base.py       |  49 ----
 .../model_records/model_records_sql.py        |  99 +-------
 .../sqlite_migrator/migrations/migration_6.py |  19 ++
 invokeai/backend/embeddings/model_patcher.py  |   4 +-
 invokeai/backend/image_util/safety_checker.py |   2 +-
 invokeai/backend/ip_adapter/ip_adapter.py     |   4 +-
 invokeai/backend/model_manager/config.py      |  13 +-
 .../backend/model_manager/load/load_base.py   |  18 +-
 .../model_manager/load/load_default.py        |   2 +-
 .../load/model_cache/model_cache_default.py   |   2 +-
 .../load/model_loaders/controlnet.py          |  12 +-
 .../load/model_loaders/generic_diffusers.py   |   5 +-
 .../load/model_loaders/stable_diffusion.py    |   8 +-
 .../model_manager/load/model_loaders/vae.py   |   8 +-
 .../backend/model_manager/load/model_util.py  |   2 +-
 invokeai/backend/model_manager/search.py      |   3 +-
 .../stable_diffusion/schedulers/__init__.py   |   2 +
 invokeai/frontend/install/model_install.py    |   2 +-
 tests/aa_nodes/test_graph_execution_state.py  |   2 -
 tests/aa_nodes/test_invoker.py                |   2 -
 .../model_loading/test_model_load.py          |  22 ++
 .../model_manager_2_fixtures.py               |  11 +
 36 files changed, 680 insertions(+), 435 deletions(-)
 rename invokeai/app/api/routers/{model_records.py => model_manager_v2.py} (86%)
 create mode 100644 tests/backend/model_manager_2/model_loading/test_model_load.py

diff --git a/docs/contributing/MODEL_MANAGER.md b/docs/contributing/MODEL_MANAGER.md
index 880c8b2480..39220f4ba8 100644
--- a/docs/contributing/MODEL_MANAGER.md
+++ b/docs/contributing/MODEL_MANAGER.md
@@ -28,7 +28,7 @@ model. These are the:
   Hugging Face, as well as discriminating among model versions in
   Civitai, but can be used for arbitrary content.
   
-  * _ModelLoadServiceBase_ (**CURRENTLY UNDER DEVELOPMENT - NOT IMPLEMENTED**)
+  * _ModelLoadServiceBase_
   Responsible for loading a model from disk
   into RAM and VRAM and getting it ready for inference.
 
@@ -41,10 +41,10 @@ The four main services can be found in
 * `invokeai/app/services/model_records/`
 * `invokeai/app/services/model_install/`
 * `invokeai/app/services/downloads/`
-* `invokeai/app/services/model_loader/` (**under development**)
+* `invokeai/app/services/model_load/`
 
 Code related to the FastAPI web API can be found in
-`invokeai/app/api/routers/model_records.py`.
+`invokeai/app/api/routers/model_manager_v2.py`.
 
 ***
 
@@ -84,10 +84,10 @@ diffusers model. When this happens, `original_hash` is unchanged, but
 `ModelType`, `ModelFormat` and `BaseModelType` are string enums that
 are defined in `invokeai.backend.model_manager.config`. They are also
 imported by, and can be reexported from,
-`invokeai.app.services.model_record_service`:
+`invokeai.app.services.model_manager.model_records`:
 
 ```
-from invokeai.app.services.model_record_service import ModelType, ModelFormat, BaseModelType
+from invokeai.app.services.model_records import ModelType, ModelFormat, BaseModelType
 ```
 
 The `path` field can be absolute or relative. If relative, it is taken
@@ -123,7 +123,7 @@ taken to be the `models_dir` directory.
 
 `variant` is an enumerated string class with values `normal`,
 `inpaint` and `depth`. If needed, it can be imported if needed from
-either `invokeai.app.services.model_record_service` or
+either `invokeai.app.services.model_records` or
 `invokeai.backend.model_manager.config`.
 
 ### ONNXSD2Config
@@ -134,7 +134,7 @@ either `invokeai.app.services.model_record_service` or
 | `upcast_attention`  | bool | Model requires its attention module to be upcast |
 
 The `SchedulerPredictionType` enum can be imported from either
-`invokeai.app.services.model_record_service` or
+`invokeai.app.services.model_records` or
 `invokeai.backend.model_manager.config`.
 
 ### Other config classes
@@ -157,15 +157,6 @@ indicates that the model is compatible with any of the base
 models. This works OK for some models, such as the IP Adapter image
 encoders, but is an all-or-nothing proposition.
 
-Another issue is that the config class hierarchy is paralleled to some
-extent by a `ModelBase` class hierarchy defined in
-`invokeai.backend.model_manager.models.base` and its subclasses. These
-are classes representing the models after they are loaded into RAM and
-include runtime information such as load status and bytes used. Some
-of the fields, including `name`, `model_type` and `base_model`, are
-shared between `ModelConfigBase` and `ModelBase`, and this is a
-potential source of confusion.
-
 ## Reading and Writing Model Configuration Records
 
 The `ModelRecordService` provides the ability to retrieve model
@@ -177,11 +168,11 @@ initialization and can be retrieved within an invocation from the
 `InvocationContext` object:
 
 ```
-store = context.services.model_record_store
+store = context.services.model_manager.store
 ```
 
 or from elsewhere in the code by accessing
-`ApiDependencies.invoker.services.model_record_store`.
+`ApiDependencies.invoker.services.model_manager.store`.
 
 ### Creating a `ModelRecordService` 
 
@@ -190,7 +181,7 @@ you can directly create either a `ModelRecordServiceSQL` or a
 `ModelRecordServiceFile` object:
 
 ```
-from invokeai.app.services.model_record_service import ModelRecordServiceSQL, ModelRecordServiceFile
+from invokeai.app.services.model_records import ModelRecordServiceSQL, ModelRecordServiceFile
 
 store = ModelRecordServiceSQL.from_connection(connection, lock)
 store = ModelRecordServiceSQL.from_db_file('/path/to/sqlite_database.db')
@@ -252,7 +243,7 @@ So a typical startup pattern would be:
 ```
 import sqlite3
 from invokeai.app.services.thread import lock
-from invokeai.app.services.model_record_service import ModelRecordServiceBase
+from invokeai.app.services.model_records import ModelRecordServiceBase
 from invokeai.app.services.config import InvokeAIAppConfig
 
 config = InvokeAIAppConfig.get_config()
@@ -260,19 +251,6 @@ db_conn = sqlite3.connect(config.db_path.as_posix(), check_same_thread=False)
 store = ModelRecordServiceBase.open(config, db_conn, lock)
 ```
 
-_A note on simultaneous access to `invokeai.db`_: The current InvokeAI
-service architecture for the image and graph databases is careful to
-use a shared sqlite3 connection and a thread lock to ensure that two
-threads don't attempt to access the database simultaneously. However,
-the default `sqlite3` library used by Python reports using
-**Serialized** mode, which allows multiple threads to access the
-database simultaneously using multiple database connections (see
-https://www.sqlite.org/threadsafe.html and
-https://ricardoanderegg.com/posts/python-sqlite-thread-safety/). Therefore
-it should be safe to allow the record service to open its own SQLite
-database connection. Opening a model record service should then be as
-simple as `ModelRecordServiceBase.open(config)`.
-
 ### Fetching a Model's Configuration from `ModelRecordServiceBase`
 
 Configurations can be retrieved in several ways.
@@ -1465,7 +1443,7 @@ create alternative instances if you wish.
 ### Creating a ModelLoadService object
 
 The class is defined in
-`invokeai.app.services.model_loader_service`. It is initialized with
+`invokeai.app.services.model_load`. It is initialized with
 an InvokeAIAppConfig object, from which it gets configuration
 information such as the user's desired GPU and precision, and with a
 previously-created `ModelRecordServiceBase` object, from which it
@@ -1475,8 +1453,8 @@ Here is a typical initialization pattern:
 
 ```
 from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.app.services.model_record_service import ModelRecordServiceBase
-from invokeai.app.services.model_loader_service import ModelLoadService
+from invokeai.app.services.model_records import ModelRecordServiceBase
+from invokeai.app.services.model_load import ModelLoadService
 
 config = InvokeAIAppConfig.get_config()
 store = ModelRecordServiceBase.open(config)
@@ -1487,14 +1465,11 @@ Note that we are relying on the contents of the application
 configuration to choose the implementation of
 `ModelRecordServiceBase`.
 
-### get_model(key, [submodel_type], [context]) -> ModelInfo:
+### load_model_by_key(key, [submodel_type], [context]) -> LoadedModel
 
-*** TO DO: change to get_model(key, context=None, **kwargs)
-
-The `get_model()` method, like its similarly-named cousin in
-`ModelRecordService`, receives the unique key that identifies the
-model.  It loads the model into memory, gets the model ready for use,
-and returns a `ModelInfo` object. 
+The `load_model_by_key()` method receives the unique key that
+identifies the model.  It loads the model into memory, gets the model
+ready for use, and returns a `LoadedModel` object.
 
 The optional second argument, `subtype` is a `SubModelType` string
 enum, such as "vae". It is mandatory when used with a main model, and
@@ -1504,46 +1479,64 @@ The optional third argument, `context` can be provided by
 an invocation to trigger model load event reporting. See below for
 details.
 
-The returned `ModelInfo` object shares some fields in common with
-`ModelConfigBase`, but is otherwise a completely different beast:
+The returned `LoadedModel` object contains a copy of the configuration
+record returned by the model record `get_model()` method, as well as
+the in-memory loaded model:
 
-| **Field Name** | **Type**        |  **Description** |
+
+| **Attribute Name** | **Type**        |  **Description** |
 |----------------|-----------------|------------------|
-| `key`          | str                    | The model key derived from the ModelRecordService database |
-| `name`         | str                    | Name of this model |
-| `base_model`   | BaseModelType          | Base model for this model |
-| `type`         | ModelType or SubModelType   | Either the model type (non-main) or the submodel type (main models)|
-| `location`     | Path or str            | Location of the model on the filesystem |
-| `precision`    | torch.dtype            | The torch.precision to use for inference |
-| `context`      | ModelCache.ModelLocker | A context class used to lock the model in VRAM while in use |
+| `config`       | AnyModelConfig         | A copy of the model's configuration record for retrieving base type, etc. |
+| `model`        | AnyModel               | The instantiated model (details below) |
+| `locker`       | ModelLockerBase        | A context manager that mediates the movement of the model into VRAM |
 
-The types for `ModelInfo` and `SubModelType` can be imported from
-`invokeai.app.services.model_loader_service`.
+Because the loader can return multiple model types, it is typed to
+return `AnyModel`, a Union `ModelMixin`, `torch.nn.Module`,
+`IAIOnnxRuntimeModel`, `IPAdapter`, `IPAdapterPlus`, and
+`EmbeddingModelRaw`. `ModelMixin` is the base class of all diffusers
+models, `EmbeddingModelRaw` is used for LoRA and TextualInversion
+models. The others are obvious.
 
-To use the model, you use the `ModelInfo` as a context manager using
-the following pattern:
+
+`LoadedModel` acts as a context manager. The context loads the model
+into the execution device (e.g. VRAM on CUDA systems), locks the model
+in the execution device for the duration of the context, and returns
+the model. Use it like this:
 
 ```
-model_info = loader.get_model('f13dd932c0c35c22dcb8d6cda4203764', SubModelType('vae'))
+model_info = loader.get_model_by_key('f13dd932c0c35c22dcb8d6cda4203764', SubModelType('vae'))
 with model_info as vae:
 	image = vae.decode(latents)[0]
 ```
 
-The `vae` model will stay locked in the GPU during the period of time
-it is in the context manager's scope.
+`get_model_by_key()` may raise any of the following exceptions:
 
-`get_model()` may raise any of the following exceptions:
-
-- `UnknownModelException`  -- key not in database
-- `ModelNotFoundException` -- key in database but model not found at path
-- `InvalidModelException`  -- the model is guilty of a variety of sins
+- `UnknownModelException`   -- key not in database
+- `ModelNotFoundException`  -- key in database but model not found at path
+- `NotImplementedException` -- the loader doesn't know how to load this type of model
   
-** TO DO: ** Resolve discrepancy between ModelInfo.location and
-ModelConfig.path.
+### load_model_by_attr(model_name, base_model, model_type, [submodel], [context]) -> LoadedModel
+
+This is similar to `load_model_by_key`, but instead it accepts the
+combination of the model's name, type and base, which it passes to the
+model record config store for retrieval. If successful, this method
+returns a `LoadedModel`. It can raise the following exceptions:
+
+```
+UnknownModelException -- model with these attributes not known
+NotImplementedException -- the loader doesn't know how to load this type of model
+ValueError -- more than one model matches this combination of base/type/name
+```
+
+### load_model_by_config(config, [submodel], [context]) -> LoadedModel
+
+This method takes an `AnyModelConfig` returned by
+ModelRecordService.get_model() and returns the corresponding loaded
+model. It may raise a `NotImplementedException`.
 
 ### Emitting model loading events
 
-When the `context` argument is passed to `get_model()`, it will
+When the `context` argument is passed to `load_model_*()`, it will
 retrieve the invocation event bus from the passed `InvocationContext`
 object to emit events on the invocation bus. The two events are
 "model_load_started" and "model_load_completed". Both carry the
@@ -1563,3 +1556,97 @@ payload=dict(
 )
 ```
 
+### Adding Model Loaders
+
+Model loaders are small classes that inherit from the `ModelLoader`
+base class. They typically implement one method `_load_model()` whose
+signature is:
+
+```
+def _load_model(
+    self,
+    model_path: Path,
+    model_variant: Optional[ModelRepoVariant] = None,
+    submodel_type: Optional[SubModelType] = None,
+) -> AnyModel:
+```
+
+`_load_model()` will be passed the path to the model on disk, an
+optional repository variant (used by the diffusers loaders to select,
+e.g.  the `fp16` variant, and an optional submodel_type for main and
+onnx models.
+
+To install a new loader, place it in
+`invokeai/backend/model_manager/load/model_loaders`. Inherit from
+`ModelLoader` and use the `@AnyModelLoader.register()` decorator to
+indicate what type of models the loader can handle.
+
+Here is a complete example from `generic_diffusers.py`, which is able
+to load several different diffusers types:
+
+```
+from pathlib import Path
+from typing import Optional
+
+from invokeai.backend.model_manager import (
+    AnyModel,
+    BaseModelType,
+    ModelFormat,
+    ModelRepoVariant,
+    ModelType,
+    SubModelType,
+)
+from ..load_base import AnyModelLoader
+from ..load_default import ModelLoader
+
+
+@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.CLIPVision, format=ModelFormat.Diffusers)
+@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.T2IAdapter, format=ModelFormat.Diffusers)
+class GenericDiffusersLoader(ModelLoader):
+    """Class to load simple diffusers models."""
+
+    def _load_model(
+        self,
+        model_path: Path,
+        model_variant: Optional[ModelRepoVariant] = None,
+        submodel_type: Optional[SubModelType] = None,
+    ) -> AnyModel:
+        model_class = self._get_hf_load_class(model_path)
+        if submodel_type is not None:
+            raise Exception(f"There are no submodels in models of type {model_class}")
+        variant = model_variant.value if model_variant else None
+        result: AnyModel = model_class.from_pretrained(model_path, torch_dtype=self._torch_dtype, variant=variant)  # type: ignore
+        return result
+```
+
+Note that a loader can register itself to handle several different
+model types. An exception will be raised if more than one loader tries
+to register the same model type.
+
+#### Conversion
+
+Some models require conversion to diffusers format before they can be
+loaded. These loaders should override two additional methods:
+
+```
+_needs_conversion(self, config: AnyModelConfig, model_path: Path, dest_path: Path) -> bool
+_convert_model(self, config: AnyModelConfig, model_path: Path, output_path: Path) -> Path:
+```
+
+The first method accepts the model configuration, the path to where
+the unmodified model is currently installed, and a proposed
+destination for the converted model. This method returns True if the
+model needs to be converted. It typically does this by comparing the
+last modification time of the original model file to the modification
+time of the converted model. In some cases you will also want to check
+the modification date of the configuration record, in the event that
+the user has changed something like the scheduler prediction type that
+will require the model to be re-converted. See `controlnet.py` for an
+example of this logic.
+
+The second method accepts the model configuration, the path to the
+original model on disk, and the desired output path for the converted
+model. It does whatever it needs to do to get the model into diffusers
+format, and returns the Path of the resulting model. (The path should
+ordinarily be the same as `output_path`.)
+
diff --git a/invokeai/app/api/dependencies.py b/invokeai/app/api/dependencies.py
index dcb8d21997..378961a055 100644
--- a/invokeai/app/api/dependencies.py
+++ b/invokeai/app/api/dependencies.py
@@ -8,9 +8,6 @@ from invokeai.app.services.item_storage.item_storage_memory import ItemStorageMe
 from invokeai.app.services.object_serializer.object_serializer_disk import ObjectSerializerDisk
 from invokeai.app.services.object_serializer.object_serializer_forward_cache import ObjectSerializerForwardCache
 from invokeai.app.services.shared.sqlite.sqlite_util import init_db
-from invokeai.backend.model_manager.load import AnyModelLoader, ModelConvertCache
-from invokeai.backend.model_manager.load.model_cache import ModelCache
-from invokeai.backend.model_manager.metadata import ModelMetadataStore
 from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ConditioningFieldData
 from invokeai.backend.util.logging import InvokeAILogger
 from invokeai.version.invokeai_version import __version__
@@ -30,9 +27,7 @@ from ..services.invocation_queue.invocation_queue_memory import MemoryInvocation
 from ..services.invocation_services import InvocationServices
 from ..services.invocation_stats.invocation_stats_default import InvocationStatsService
 from ..services.invoker import Invoker
-from ..services.model_install import ModelInstallService
 from ..services.model_manager.model_manager_default import ModelManagerService
-from ..services.model_records import ModelRecordServiceSQL
 from ..services.names.names_default import SimpleNameService
 from ..services.session_processor.session_processor_default import DefaultSessionProcessor
 from ..services.session_queue.session_queue_sqlite import SqliteSessionQueue
@@ -98,28 +93,10 @@ class ApiDependencies:
         conditioning = ObjectSerializerForwardCache(
             ObjectSerializerDisk[ConditioningFieldData](output_folder / "conditioning", ephemeral=True)
         )
-        model_manager = ModelManagerService(config, logger)
-        model_record_service = ModelRecordServiceSQL(db=db)
-        model_loader = AnyModelLoader(
-            app_config=config,
-            logger=logger,
-            ram_cache=ModelCache(
-                max_cache_size=config.ram_cache_size, max_vram_cache_size=config.vram_cache_size, logger=logger
-            ),
-            convert_cache=ModelConvertCache(
-                cache_path=config.models_convert_cache_path, max_size=config.convert_cache_size
-            ),
-        )
-        model_record_service = ModelRecordServiceSQL(db=db, loader=model_loader)
         download_queue_service = DownloadQueueService(event_bus=events)
-        model_install_service = ModelInstallService(
-            app_config=config,
-            record_store=model_record_service,
-            download_queue=download_queue_service,
-            metadata_store=ModelMetadataStore(db=db),
-            event_bus=events,
+        model_manager = ModelManagerService.build_model_manager(
+            app_config=configuration, db=db, download_queue=download_queue_service, events=events
         )
-        model_manager = ModelManagerService(config, logger)  # TO DO: legacy model manager v1. Remove
         names = SimpleNameService()
         performance_statistics = InvocationStatsService()
         processor = DefaultInvocationProcessor()
@@ -143,9 +120,7 @@ class ApiDependencies:
             invocation_cache=invocation_cache,
             logger=logger,
             model_manager=model_manager,
-            model_records=model_record_service,
             download_queue=download_queue_service,
-            model_install=model_install_service,
             names=names,
             performance_statistics=performance_statistics,
             processor=processor,
diff --git a/invokeai/app/api/routers/model_records.py b/invokeai/app/api/routers/model_manager_v2.py
similarity index 86%
rename from invokeai/app/api/routers/model_records.py
rename to invokeai/app/api/routers/model_manager_v2.py
index f9a3e40898..4fc785e4f7 100644
--- a/invokeai/app/api/routers/model_records.py
+++ b/invokeai/app/api/routers/model_manager_v2.py
@@ -32,7 +32,7 @@ from invokeai.backend.model_manager.metadata import AnyModelRepoMetadata
 
 from ..dependencies import ApiDependencies
 
-model_records_router = APIRouter(prefix="/v1/model/record", tags=["model_manager_v2_unstable"])
+model_manager_v2_router = APIRouter(prefix="/v2/models", tags=["model_manager_v2"])
 
 
 class ModelsList(BaseModel):
@@ -52,7 +52,7 @@ class ModelTagSet(BaseModel):
     tags: Set[str]
 
 
-@model_records_router.get(
+@model_manager_v2_router.get(
     "/",
     operation_id="list_model_records",
 )
@@ -65,7 +65,7 @@ async def list_model_records(
     ),
 ) -> ModelsList:
     """Get a list of models."""
-    record_store = ApiDependencies.invoker.services.model_records
+    record_store = ApiDependencies.invoker.services.model_manager.store
     found_models: list[AnyModelConfig] = []
     if base_models:
         for base_model in base_models:
@@ -81,7 +81,7 @@ async def list_model_records(
     return ModelsList(models=found_models)
 
 
-@model_records_router.get(
+@model_manager_v2_router.get(
     "/i/{key}",
     operation_id="get_model_record",
     responses={
@@ -94,24 +94,27 @@ async def get_model_record(
     key: str = Path(description="Key of the model record to fetch."),
 ) -> AnyModelConfig:
     """Get a model record"""
-    record_store = ApiDependencies.invoker.services.model_records
+    record_store = ApiDependencies.invoker.services.model_manager.store
     try:
-        return record_store.get_model(key)
+        config: AnyModelConfig = record_store.get_model(key)
+        return config
     except UnknownModelException as e:
         raise HTTPException(status_code=404, detail=str(e))
 
 
-@model_records_router.get("/meta", operation_id="list_model_summary")
+@model_manager_v2_router.get("/meta", operation_id="list_model_summary")
 async def list_model_summary(
     page: int = Query(default=0, description="The page to get"),
     per_page: int = Query(default=10, description="The number of models per page"),
     order_by: ModelRecordOrderBy = Query(default=ModelRecordOrderBy.Default, description="The attribute to order by"),
 ) -> PaginatedResults[ModelSummary]:
     """Gets a page of model summary data."""
-    return ApiDependencies.invoker.services.model_records.list_models(page=page, per_page=per_page, order_by=order_by)
+    record_store = ApiDependencies.invoker.services.model_manager.store
+    results: PaginatedResults[ModelSummary] = record_store.list_models(page=page, per_page=per_page, order_by=order_by)
+    return results
 
 
-@model_records_router.get(
+@model_manager_v2_router.get(
     "/meta/i/{key}",
     operation_id="get_model_metadata",
     responses={
@@ -124,24 +127,25 @@ async def get_model_metadata(
     key: str = Path(description="Key of the model repo metadata to fetch."),
 ) -> Optional[AnyModelRepoMetadata]:
     """Get a model metadata object."""
-    record_store = ApiDependencies.invoker.services.model_records
-    result = record_store.get_metadata(key)
+    record_store = ApiDependencies.invoker.services.model_manager.store
+    result: Optional[AnyModelRepoMetadata] = record_store.get_metadata(key)
     if not result:
         raise HTTPException(status_code=404, detail="No metadata for a model with this key")
     return result
 
 
-@model_records_router.get(
+@model_manager_v2_router.get(
     "/tags",
     operation_id="list_tags",
 )
 async def list_tags() -> Set[str]:
     """Get a unique set of all the model tags."""
-    record_store = ApiDependencies.invoker.services.model_records
-    return record_store.list_tags()
+    record_store = ApiDependencies.invoker.services.model_manager.store
+    result: Set[str] = record_store.list_tags()
+    return result
 
 
-@model_records_router.get(
+@model_manager_v2_router.get(
     "/tags/search",
     operation_id="search_by_metadata_tags",
 )
@@ -149,12 +153,12 @@ async def search_by_metadata_tags(
     tags: Set[str] = Query(default=None, description="Tags to search for"),
 ) -> ModelsList:
     """Get a list of models."""
-    record_store = ApiDependencies.invoker.services.model_records
+    record_store = ApiDependencies.invoker.services.model_manager.store
     results = record_store.search_by_metadata_tag(tags)
     return ModelsList(models=results)
 
 
-@model_records_router.patch(
+@model_manager_v2_router.patch(
     "/i/{key}",
     operation_id="update_model_record",
     responses={
@@ -172,9 +176,9 @@ async def update_model_record(
 ) -> AnyModelConfig:
     """Update model contents with a new config. If the model name or base fields are changed, then the model is renamed."""
     logger = ApiDependencies.invoker.services.logger
-    record_store = ApiDependencies.invoker.services.model_records
+    record_store = ApiDependencies.invoker.services.model_manager.store
     try:
-        model_response = record_store.update_model(key, config=info)
+        model_response: AnyModelConfig = record_store.update_model(key, config=info)
         logger.info(f"Updated model: {key}")
     except UnknownModelException as e:
         raise HTTPException(status_code=404, detail=str(e))
@@ -184,7 +188,7 @@ async def update_model_record(
     return model_response
 
 
-@model_records_router.delete(
+@model_manager_v2_router.delete(
     "/i/{key}",
     operation_id="del_model_record",
     responses={
@@ -205,7 +209,7 @@ async def del_model_record(
     logger = ApiDependencies.invoker.services.logger
 
     try:
-        installer = ApiDependencies.invoker.services.model_install
+        installer = ApiDependencies.invoker.services.model_manager.install
         installer.delete(key)
         logger.info(f"Deleted model: {key}")
         return Response(status_code=204)
@@ -214,7 +218,7 @@ async def del_model_record(
         raise HTTPException(status_code=404, detail=str(e))
 
 
-@model_records_router.post(
+@model_manager_v2_router.post(
     "/i/",
     operation_id="add_model_record",
     responses={
@@ -229,7 +233,7 @@ async def add_model_record(
 ) -> AnyModelConfig:
     """Add a model using the configuration information appropriate for its type."""
     logger = ApiDependencies.invoker.services.logger
-    record_store = ApiDependencies.invoker.services.model_records
+    record_store = ApiDependencies.invoker.services.model_manager.store
     if config.key == "<NOKEY>":
         config.key = sha1(randbytes(100)).hexdigest()
         logger.info(f"Created model {config.key} for {config.name}")
@@ -243,10 +247,11 @@ async def add_model_record(
         raise HTTPException(status_code=415)
 
     # now fetch it out
-    return record_store.get_model(config.key)
+    result: AnyModelConfig = record_store.get_model(config.key)
+    return result
 
 
-@model_records_router.post(
+@model_manager_v2_router.post(
     "/import",
     operation_id="import_model_record",
     responses={
@@ -322,7 +327,7 @@ async def import_model(
     logger = ApiDependencies.invoker.services.logger
 
     try:
-        installer = ApiDependencies.invoker.services.model_install
+        installer = ApiDependencies.invoker.services.model_manager.install
         result: ModelInstallJob = installer.import_model(
             source=source,
             config=config,
@@ -340,17 +345,17 @@ async def import_model(
     return result
 
 
-@model_records_router.get(
+@model_manager_v2_router.get(
     "/import",
     operation_id="list_model_install_jobs",
 )
 async def list_model_install_jobs() -> List[ModelInstallJob]:
     """Return list of model install jobs."""
-    jobs: List[ModelInstallJob] = ApiDependencies.invoker.services.model_install.list_jobs()
+    jobs: List[ModelInstallJob] = ApiDependencies.invoker.services.model_manager.install.list_jobs()
     return jobs
 
 
-@model_records_router.get(
+@model_manager_v2_router.get(
     "/import/{id}",
     operation_id="get_model_install_job",
     responses={
@@ -361,12 +366,13 @@ async def list_model_install_jobs() -> List[ModelInstallJob]:
 async def get_model_install_job(id: int = Path(description="Model install id")) -> ModelInstallJob:
     """Return model install job corresponding to the given source."""
     try:
-        return ApiDependencies.invoker.services.model_install.get_job_by_id(id)
+        result: ModelInstallJob = ApiDependencies.invoker.services.model_manager.install.get_job_by_id(id)
+        return result
     except ValueError as e:
         raise HTTPException(status_code=404, detail=str(e))
 
 
-@model_records_router.delete(
+@model_manager_v2_router.delete(
     "/import/{id}",
     operation_id="cancel_model_install_job",
     responses={
@@ -377,7 +383,7 @@ async def get_model_install_job(id: int = Path(description="Model install id"))
 )
 async def cancel_model_install_job(id: int = Path(description="Model install job ID")) -> None:
     """Cancel the model install job(s) corresponding to the given job ID."""
-    installer = ApiDependencies.invoker.services.model_install
+    installer = ApiDependencies.invoker.services.model_manager.install
     try:
         job = installer.get_job_by_id(id)
     except ValueError as e:
@@ -385,7 +391,7 @@ async def cancel_model_install_job(id: int = Path(description="Model install job
     installer.cancel_job(job)
 
 
-@model_records_router.patch(
+@model_manager_v2_router.patch(
     "/import",
     operation_id="prune_model_install_jobs",
     responses={
@@ -395,11 +401,11 @@ async def cancel_model_install_job(id: int = Path(description="Model install job
 )
 async def prune_model_install_jobs() -> Response:
     """Prune all completed and errored jobs from the install job list."""
-    ApiDependencies.invoker.services.model_install.prune_jobs()
+    ApiDependencies.invoker.services.model_manager.install.prune_jobs()
     return Response(status_code=204)
 
 
-@model_records_router.patch(
+@model_manager_v2_router.patch(
     "/sync",
     operation_id="sync_models_to_config",
     responses={
@@ -414,11 +420,11 @@ async def sync_models_to_config() -> Response:
     Model files without a corresponding
     record in the database are added. Orphan records without a models file are deleted.
     """
-    ApiDependencies.invoker.services.model_install.sync_to_config()
+    ApiDependencies.invoker.services.model_manager.install.sync_to_config()
     return Response(status_code=204)
 
 
-@model_records_router.put(
+@model_manager_v2_router.put(
     "/merge",
     operation_id="merge",
 )
@@ -451,7 +457,7 @@ async def merge(
     try:
         logger.info(f"Merging models: {keys} into {merge_dest_directory or '<MODELS>'}/{merged_model_name}")
         dest = pathlib.Path(merge_dest_directory) if merge_dest_directory else None
-        installer = ApiDependencies.invoker.services.model_install
+        installer = ApiDependencies.invoker.services.model_manager.install
         merger = ModelMerger(installer)
         model_names = [installer.record_store.get_model(x).name for x in keys]
         response = merger.merge_diffusion_models_and_save(
diff --git a/invokeai/app/api/routers/models.py b/invokeai/app/api/routers/models.py
index 8f83820cf8..0aa7aa0ecb 100644
--- a/invokeai/app/api/routers/models.py
+++ b/invokeai/app/api/routers/models.py
@@ -8,8 +8,7 @@ from fastapi.routing import APIRouter
 from pydantic import BaseModel, ConfigDict, Field, TypeAdapter
 from starlette.exceptions import HTTPException
 
-from invokeai.backend import BaseModelType, ModelType
-from invokeai.backend.model_management import MergeInterpolationMethod
+from invokeai.backend.model_management import BaseModelType, MergeInterpolationMethod, ModelType
 from invokeai.backend.model_management.models import (
     OPENAPI_MODEL_CONFIGS,
     InvalidModelException,
diff --git a/invokeai/app/api_app.py b/invokeai/app/api_app.py
index f48074de7c..851cbc8160 100644
--- a/invokeai/app/api_app.py
+++ b/invokeai/app/api_app.py
@@ -48,7 +48,7 @@ if True:  # hack to make flake8 happy with imports coming after setting up the c
         boards,
         download_queue,
         images,
-        model_records,
+        model_manager_v2,
         models,
         session_queue,
         sessions,
@@ -114,8 +114,7 @@ async def shutdown_event() -> None:
 app.include_router(sessions.session_router, prefix="/api")
 
 app.include_router(utilities.utilities_router, prefix="/api")
-app.include_router(models.models_router, prefix="/api")
-app.include_router(model_records.model_records_router, prefix="/api")
+app.include_router(model_manager_v2.model_manager_v2_router, prefix="/api")
 app.include_router(download_queue.download_queue_router, prefix="/api")
 app.include_router(images.images_router, prefix="/api")
 app.include_router(boards.boards_router, prefix="/api")
diff --git a/invokeai/app/invocations/compel.py b/invokeai/app/invocations/compel.py
index 0e1a6bdc6f..3850fb6cc3 100644
--- a/invokeai/app/invocations/compel.py
+++ b/invokeai/app/invocations/compel.py
@@ -3,6 +3,7 @@ from typing import Iterator, List, Optional, Tuple, Union
 import torch
 from compel import Compel, ReturnedEmbeddingsType
 from compel.prompt_parser import Blend, Conjunction, CrossAttentionControlSubstitute, FlattenedPrompt, Fragment
+from transformers import CLIPTokenizer
 
 import invokeai.backend.util.logging as logger
 from invokeai.app.invocations.fields import (
@@ -68,18 +69,18 @@ class CompelInvocation(BaseInvocation):
 
     @torch.no_grad()
     def invoke(self, context: InvocationContext) -> ConditioningOutput:
-        tokenizer_info = context.services.model_records.load_model(
+        tokenizer_info = context.services.model_manager.load.load_model_by_key(
             **self.clip.tokenizer.model_dump(),
             context=context,
         )
-        text_encoder_info = context.services.model_records.load_model(
+        text_encoder_info = context.services.model_manager.load.load_model_by_key(
             **self.clip.text_encoder.model_dump(),
             context=context,
         )
 
         def _lora_loader() -> Iterator[Tuple[LoRAModelRaw, float]]:
             for lora in self.clip.loras:
-                lora_info = context.services.model_records.load_model(
+                lora_info = context.services.model_manager.load.load_model_by_key(
                     **lora.model_dump(exclude={"weight"}), context=context
                 )
                 assert isinstance(lora_info.model, LoRAModelRaw)
@@ -93,7 +94,7 @@ class CompelInvocation(BaseInvocation):
         for trigger in extract_ti_triggers_from_prompt(self.prompt):
             name = trigger[1:-1]
             try:
-                loaded_model = context.services.model_records.load_model(
+                loaded_model = context.services.model_manager.load.load_model_by_key(
                     **self.clip.text_encoder.model_dump(),
                     context=context,
                 ).model
@@ -164,11 +165,11 @@ class SDXLPromptInvocationBase:
         lora_prefix: str,
         zero_on_empty: bool,
     ) -> Tuple[torch.Tensor, Optional[torch.Tensor], Optional[ExtraConditioningInfo]]:
-        tokenizer_info = context.services.model_records.load_model(
+        tokenizer_info = context.services.model_manager.load.load_model_by_key(
             **clip_field.tokenizer.model_dump(),
             context=context,
         )
-        text_encoder_info = context.services.model_records.load_model(
+        text_encoder_info = context.services.model_manager.load.load_model_by_key(
             **clip_field.text_encoder.model_dump(),
             context=context,
         )
@@ -196,7 +197,7 @@ class SDXLPromptInvocationBase:
 
         def _lora_loader() -> Iterator[Tuple[LoRAModelRaw, float]]:
             for lora in clip_field.loras:
-                lora_info = context.services.model_records.load_model(
+                lora_info = context.services.model_manager.load.load_model_by_key(
                     **lora.model_dump(exclude={"weight"}), context=context
                 )
                 lora_model = lora_info.model
@@ -211,7 +212,7 @@ class SDXLPromptInvocationBase:
         for trigger in extract_ti_triggers_from_prompt(prompt):
             name = trigger[1:-1]
             try:
-                ti_model = context.services.model_records.load_model_by_attr(
+                ti_model = context.services.model_manager.load.load_model_by_attr(
                     model_name=name,
                     base_model=text_encoder_info.config.base,
                     model_type=ModelType.TextualInversion,
@@ -448,9 +449,9 @@ class ClipSkipInvocation(BaseInvocation):
 
 
 def get_max_token_count(
-    tokenizer,
+    tokenizer: CLIPTokenizer,
     prompt: Union[FlattenedPrompt, Blend, Conjunction],
-    truncate_if_too_long=False,
+    truncate_if_too_long: bool = False,
 ) -> int:
     if type(prompt) is Blend:
         blend: Blend = prompt
@@ -462,7 +463,9 @@ def get_max_token_count(
         return len(get_tokens_for_prompt_object(tokenizer, prompt, truncate_if_too_long))
 
 
-def get_tokens_for_prompt_object(tokenizer, parsed_prompt: FlattenedPrompt, truncate_if_too_long=True) -> List[str]:
+def get_tokens_for_prompt_object(
+    tokenizer: CLIPTokenizer, parsed_prompt: FlattenedPrompt, truncate_if_too_long: bool = True
+) -> List[str]:
     if type(parsed_prompt) is Blend:
         raise ValueError("Blend is not supported here - you need to get tokens for each of its .children")
 
@@ -475,24 +478,29 @@ def get_tokens_for_prompt_object(tokenizer, parsed_prompt: FlattenedPrompt, trun
         for x in parsed_prompt.children
     ]
     text = " ".join(text_fragments)
-    tokens = tokenizer.tokenize(text)
+    tokens: List[str] = tokenizer.tokenize(text)
     if truncate_if_too_long:
         max_tokens_length = tokenizer.model_max_length - 2  # typically 75
         tokens = tokens[0:max_tokens_length]
     return tokens
 
 
-def log_tokenization_for_conjunction(c: Conjunction, tokenizer, display_label_prefix=None):
+def log_tokenization_for_conjunction(
+    c: Conjunction, tokenizer: CLIPTokenizer, display_label_prefix: Optional[str] = None
+) -> None:
     display_label_prefix = display_label_prefix or ""
     for i, p in enumerate(c.prompts):
         if len(c.prompts) > 1:
             this_display_label_prefix = f"{display_label_prefix}(conjunction part {i + 1}, weight={c.weights[i]})"
         else:
+            assert display_label_prefix is not None
             this_display_label_prefix = display_label_prefix
         log_tokenization_for_prompt_object(p, tokenizer, display_label_prefix=this_display_label_prefix)
 
 
-def log_tokenization_for_prompt_object(p: Union[Blend, FlattenedPrompt], tokenizer, display_label_prefix=None):
+def log_tokenization_for_prompt_object(
+    p: Union[Blend, FlattenedPrompt], tokenizer: CLIPTokenizer, display_label_prefix: Optional[str] = None
+) -> None:
     display_label_prefix = display_label_prefix or ""
     if type(p) is Blend:
         blend: Blend = p
@@ -532,7 +540,12 @@ def log_tokenization_for_prompt_object(p: Union[Blend, FlattenedPrompt], tokeniz
             log_tokenization_for_text(text, tokenizer, display_label=display_label_prefix)
 
 
-def log_tokenization_for_text(text, tokenizer, display_label=None, truncate_if_too_long=False):
+def log_tokenization_for_text(
+    text: str,
+    tokenizer: CLIPTokenizer,
+    display_label: Optional[str] = None,
+    truncate_if_too_long: Optional[bool] = False,
+) -> None:
     """shows how the prompt is tokenized
     # usually tokens have '</w>' to indicate end-of-word,
     # but for readability it has been replaced with ' '
diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py
index 063b23fa58..289da2dd73 100644
--- a/invokeai/app/invocations/latent.py
+++ b/invokeai/app/invocations/latent.py
@@ -3,13 +3,15 @@
 import math
 from contextlib import ExitStack
 from functools import singledispatchmethod
-from typing import Iterator, List, Literal, Optional, Tuple, Union
+from typing import Any, Iterator, List, Literal, Optional, Tuple, Union
 
 import einops
 import numpy as np
+import numpy.typing as npt
 import torch
 import torchvision.transforms as T
-from diffusers import AutoencoderKL, AutoencoderTiny, UNet2DConditionModel
+from diffusers import AutoencoderKL, AutoencoderTiny
+from diffusers.configuration_utils import ConfigMixin
 from diffusers.image_processor import VaeImageProcessor
 from diffusers.models.adapter import T2IAdapter
 from diffusers.models.attention_processor import (
@@ -18,8 +20,10 @@ from diffusers.models.attention_processor import (
     LoRAXFormersAttnProcessor,
     XFormersAttnProcessor,
 )
+from diffusers.models.unets.unet_2d_condition import UNet2DConditionModel
 from diffusers.schedulers import DPMSolverSDEScheduler
 from diffusers.schedulers import SchedulerMixin as Scheduler
+from PIL import Image
 from pydantic import field_validator
 from torchvision.transforms.functional import resize as tv_resize
 
@@ -46,9 +50,10 @@ from invokeai.app.invocations.primitives import (
 from invokeai.app.invocations.t2i_adapter import T2IAdapterField
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.app.util.controlnet_utils import prepare_control_image
+from invokeai.backend.embeddings.lora import LoRAModelRaw
 from invokeai.backend.embeddings.model_patcher import ModelPatcher
 from invokeai.backend.ip_adapter.ip_adapter import IPAdapter, IPAdapterPlus
-from invokeai.backend.model_manager import AnyModel, BaseModelType
+from invokeai.backend.model_manager import BaseModelType, LoadedModel
 from invokeai.backend.stable_diffusion import PipelineIntermediateState, set_seamless
 from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ConditioningData, IPAdapterConditioningInfo
 from invokeai.backend.util.silence_warnings import SilenceWarnings
@@ -123,10 +128,10 @@ class CreateDenoiseMaskInvocation(BaseInvocation):
         ui_order=4,
     )
 
-    def prep_mask_tensor(self, mask_image):
+    def prep_mask_tensor(self, mask_image: Image) -> torch.Tensor:
         if mask_image.mode != "L":
             mask_image = mask_image.convert("L")
-        mask_tensor = image_resized_to_grid_as_tensor(mask_image, normalize=False)
+        mask_tensor: torch.Tensor = image_resized_to_grid_as_tensor(mask_image, normalize=False)
         if mask_tensor.dim() == 3:
             mask_tensor = mask_tensor.unsqueeze(0)
         # if shape is not None:
@@ -136,25 +141,25 @@ class CreateDenoiseMaskInvocation(BaseInvocation):
     @torch.no_grad()
     def invoke(self, context: InvocationContext) -> DenoiseMaskOutput:
         if self.image is not None:
-            image = context.images.get_pil(self.image.image_name)
-            image = image_resized_to_grid_as_tensor(image.convert("RGB"))
-            if image.dim() == 3:
-                image = image.unsqueeze(0)
+            image = context.services.images.get_pil_image(self.image.image_name)
+            image_tensor = image_resized_to_grid_as_tensor(image.convert("RGB"))
+            if image_tensor.dim() == 3:
+                image_tensor = image_tensor.unsqueeze(0)
         else:
-            image = None
+            image_tensor = None
 
         mask = self.prep_mask_tensor(
             context.images.get_pil(self.mask.image_name),
         )
 
-        if image is not None:
-            vae_info = context.services.model_records.load_model(
+        if image_tensor is not None:
+            vae_info = context.services.model_manager.load.load_model_by_key(
                 **self.vae.vae.model_dump(),
                 context=context,
             )
 
-            img_mask = tv_resize(mask, image.shape[-2:], T.InterpolationMode.BILINEAR, antialias=False)
-            masked_image = image * torch.where(img_mask < 0.5, 0.0, 1.0)
+            img_mask = tv_resize(mask, image_tensor.shape[-2:], T.InterpolationMode.BILINEAR, antialias=False)
+            masked_image = image_tensor * torch.where(img_mask < 0.5, 0.0, 1.0)
             # TODO:
             masked_latents = ImageToLatentsInvocation.vae_encode(vae_info, self.fp32, self.tiled, masked_image.clone())
 
@@ -177,7 +182,7 @@ def get_scheduler(
     seed: int,
 ) -> Scheduler:
     scheduler_class, scheduler_extra_config = SCHEDULER_MAP.get(scheduler_name, SCHEDULER_MAP["ddim"])
-    orig_scheduler_info = context.services.model_records.load_model(
+    orig_scheduler_info = context.services.model_manager.load.load_model_by_key(
         **scheduler_info.model_dump(),
         context=context,
     )
@@ -188,7 +193,7 @@ def get_scheduler(
         scheduler_config = scheduler_config["_backup"]
     scheduler_config = {
         **scheduler_config,
-        **scheduler_extra_config,
+        **scheduler_extra_config,  # FIXME
         "_backup": scheduler_config,
     }
 
@@ -201,6 +206,7 @@ def get_scheduler(
     # hack copied over from generate.py
     if not hasattr(scheduler, "uses_inpainting_model"):
         scheduler.uses_inpainting_model = lambda: False
+    assert isinstance(scheduler, Scheduler)
     return scheduler
 
 
@@ -284,7 +290,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
     )
 
     @field_validator("cfg_scale")
-    def ge_one(cls, v):
+    def ge_one(cls, v: Union[List[float], float]) -> Union[List[float], float]:
         """validate that all cfg_scale values are >= 1"""
         if isinstance(v, list):
             for i in v:
@@ -298,9 +304,9 @@ class DenoiseLatentsInvocation(BaseInvocation):
     def get_conditioning_data(
         self,
         context: InvocationContext,
-        scheduler,
-        unet,
-        seed,
+        scheduler: Scheduler,
+        unet: UNet2DConditionModel,
+        seed: int,
     ) -> ConditioningData:
         positive_cond_data = context.conditioning.load(self.positive_conditioning.conditioning_name)
         c = positive_cond_data.conditionings[0].to(device=unet.device, dtype=unet.dtype)
@@ -323,7 +329,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
             ),
         )
 
-        conditioning_data = conditioning_data.add_scheduler_args_if_applicable(
+        conditioning_data = conditioning_data.add_scheduler_args_if_applicable(  # FIXME
             scheduler,
             # for ddim scheduler
             eta=0.0,  # ddim_eta
@@ -335,8 +341,8 @@ class DenoiseLatentsInvocation(BaseInvocation):
 
     def create_pipeline(
         self,
-        unet,
-        scheduler,
+        unet: UNet2DConditionModel,
+        scheduler: Scheduler,
     ) -> StableDiffusionGeneratorPipeline:
         # TODO:
         # configure_model_padding(
@@ -347,10 +353,10 @@ class DenoiseLatentsInvocation(BaseInvocation):
 
         class FakeVae:
             class FakeVaeConfig:
-                def __init__(self):
+                def __init__(self) -> None:
                     self.block_out_channels = [0]
 
-            def __init__(self):
+            def __init__(self) -> None:
                 self.config = FakeVae.FakeVaeConfig()
 
         return StableDiffusionGeneratorPipeline(
@@ -367,11 +373,11 @@ class DenoiseLatentsInvocation(BaseInvocation):
     def prep_control_data(
         self,
         context: InvocationContext,
-        control_input: Union[ControlField, List[ControlField]],
+        control_input: Optional[Union[ControlField, List[ControlField]]],
         latents_shape: List[int],
         exit_stack: ExitStack,
         do_classifier_free_guidance: bool = True,
-    ) -> List[ControlNetData]:
+    ) -> Optional[List[ControlNetData]]:
         # Assuming fixed dimensional scaling of LATENT_SCALE_FACTOR.
         control_height_resize = latents_shape[2] * LATENT_SCALE_FACTOR
         control_width_resize = latents_shape[3] * LATENT_SCALE_FACTOR
@@ -394,7 +400,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
         controlnet_data = []
         for control_info in control_list:
             control_model = exit_stack.enter_context(
-                context.services.model_records.load_model(
+                context.services.model_manager.load.load_model_by_key(
                     key=control_info.control_model.key,
                     context=context,
                 )
@@ -460,23 +466,25 @@ class DenoiseLatentsInvocation(BaseInvocation):
         conditioning_data.ip_adapter_conditioning = []
         for single_ip_adapter in ip_adapter:
             ip_adapter_model: Union[IPAdapter, IPAdapterPlus] = exit_stack.enter_context(
-                context.services.model_records.load_model(
+                context.services.model_manager.load.load_model_by_key(
                     key=single_ip_adapter.ip_adapter_model.key,
                     context=context,
                 )
             )
 
-            image_encoder_model_info = context.services.model_records.load_model(
+            image_encoder_model_info = context.services.model_manager.load.load_model_by_key(
                 key=single_ip_adapter.image_encoder_model.key,
                 context=context,
             )
 
             # `single_ip_adapter.image` could be a list or a single ImageField. Normalize to a list here.
-            single_ipa_images = single_ip_adapter.image
-            if not isinstance(single_ipa_images, list):
-                single_ipa_images = [single_ipa_images]
+            single_ipa_image_fields = single_ip_adapter.image
+            if not isinstance(single_ipa_image_fields, list):
+                single_ipa_image_fields = [single_ipa_image_fields]
 
-            single_ipa_images = [context.images.get_pil(image.image_name) for image in single_ipa_images]
+            single_ipa_images = [
+                context.services.images.get_pil_image(image.image_name) for image in single_ipa_image_fields
+            ]
 
             # TODO(ryand): With some effort, the step of running the CLIP Vision encoder could be done before any other
             # models are needed in memory. This would help to reduce peak memory utilization in low-memory environments.
@@ -520,21 +528,19 @@ class DenoiseLatentsInvocation(BaseInvocation):
 
         t2i_adapter_data = []
         for t2i_adapter_field in t2i_adapter:
-            t2i_adapter_model_info = context.services.model_records.load_model(
+            t2i_adapter_model_info = context.services.model_manager.load.load_model_by_key(
                 key=t2i_adapter_field.t2i_adapter_model.key,
                 context=context,
             )
             image = context.images.get_pil(t2i_adapter_field.image.image_name)
 
             # The max_unet_downscale is the maximum amount that the UNet model downscales the latent image internally.
-            if t2i_adapter_field.t2i_adapter_model.base_model == BaseModelType.StableDiffusion1:
+            if t2i_adapter_model_info.base == BaseModelType.StableDiffusion1:
                 max_unet_downscale = 8
-            elif t2i_adapter_field.t2i_adapter_model.base_model == BaseModelType.StableDiffusionXL:
+            elif t2i_adapter_model_info.base == BaseModelType.StableDiffusionXL:
                 max_unet_downscale = 4
             else:
-                raise ValueError(
-                    f"Unexpected T2I-Adapter base model type: '{t2i_adapter_field.t2i_adapter_model.base_model}'."
-                )
+                raise ValueError(f"Unexpected T2I-Adapter base model type: '{t2i_adapter_model_info.base}'.")
 
             t2i_adapter_model: T2IAdapter
             with t2i_adapter_model_info as t2i_adapter_model:
@@ -582,7 +588,15 @@ class DenoiseLatentsInvocation(BaseInvocation):
 
     # original idea by https://github.com/AmericanPresidentJimmyCarter
     # TODO: research more for second order schedulers timesteps
-    def init_scheduler(self, scheduler, device, steps, denoising_start, denoising_end):
+    def init_scheduler(
+        self,
+        scheduler: Union[Scheduler, ConfigMixin],
+        device: torch.device,
+        steps: int,
+        denoising_start: float,
+        denoising_end: float,
+    ) -> Tuple[int, List[int], int]:
+        assert isinstance(scheduler, ConfigMixin)
         if scheduler.config.get("cpu_only", False):
             scheduler.set_timesteps(steps, device="cpu")
             timesteps = scheduler.timesteps.to(device=device)
@@ -594,11 +608,11 @@ class DenoiseLatentsInvocation(BaseInvocation):
         _timesteps = timesteps[:: scheduler.order]
 
         # get start timestep index
-        t_start_val = int(round(scheduler.config.num_train_timesteps * (1 - denoising_start)))
+        t_start_val = int(round(scheduler.config["num_train_timesteps"] * (1 - denoising_start)))
         t_start_idx = len(list(filter(lambda ts: ts >= t_start_val, _timesteps)))
 
         # get end timestep index
-        t_end_val = int(round(scheduler.config.num_train_timesteps * (1 - denoising_end)))
+        t_end_val = int(round(scheduler.config["num_train_timesteps"] * (1 - denoising_end)))
         t_end_idx = len(list(filter(lambda ts: ts >= t_end_val, _timesteps[t_start_idx:])))
 
         # apply order to indexes
@@ -611,7 +625,9 @@ class DenoiseLatentsInvocation(BaseInvocation):
 
         return num_inference_steps, timesteps, init_timestep
 
-    def prep_inpaint_mask(self, context: InvocationContext, latents):
+    def prep_inpaint_mask(
+        self, context: InvocationContext, latents: torch.Tensor
+    ) -> Tuple[Optional[torch.Tensor], Optional[torch.Tensor]]:
         if self.denoise_mask is None:
             return None, None
 
@@ -660,12 +676,19 @@ class DenoiseLatentsInvocation(BaseInvocation):
                 do_classifier_free_guidance=True,
             )
 
-            def step_callback(state: PipelineIntermediateState):
-                context.util.sd_step_callback(state, self.unet.unet.base_model)
+            # Get the source node id (we are invoking the prepared node)
+            graph_execution_state = context.services.graph_execution_manager.get(context.graph_execution_state_id)
+            source_node_id = graph_execution_state.prepared_source_mapping[self.id]
 
-            def _lora_loader() -> Iterator[Tuple[AnyModel, float]]:
+            # get the unet's config so that we can pass the base to dispatch_progress()
+            unet_config = context.services.model_manager.store.get_model(**self.unet.unet.model_dump())
+
+            def step_callback(state: PipelineIntermediateState) -> None:
+                self.dispatch_progress(context, source_node_id, state, unet_config.base)
+
+            def _lora_loader() -> Iterator[Tuple[LoRAModelRaw, float]]:
                 for lora in self.unet.loras:
-                    lora_info = context.services.model_records.load_model(
+                    lora_info = context.services.model_manager.load.load_model_by_key(
                         **lora.model_dump(exclude={"weight"}),
                         context=context,
                     )
@@ -673,7 +696,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
                     del lora_info
                 return
 
-            unet_info = context.services.model_records.load_model(
+            unet_info = context.services.model_manager.load.load_model_by_key(
                 **self.unet.unet.model_dump(),
                 context=context,
             )
@@ -783,7 +806,7 @@ class LatentsToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
     def invoke(self, context: InvocationContext) -> ImageOutput:
         latents = context.tensors.load(self.latents.latents_name)
 
-        vae_info = context.services.model_records.load_model(
+        vae_info = context.services.model_manager.load.load_model_by_key(
             **self.vae.vae.model_dump(),
             context=context,
         )
@@ -961,8 +984,9 @@ class ImageToLatentsInvocation(BaseInvocation):
     fp32: bool = InputField(default=DEFAULT_PRECISION == "float32", description=FieldDescriptions.fp32)
 
     @staticmethod
-    def vae_encode(vae_info, upcast, tiled, image_tensor):
+    def vae_encode(vae_info: LoadedModel, upcast: bool, tiled: bool, image_tensor: torch.Tensor) -> torch.Tensor:
         with vae_info as vae:
+            assert isinstance(vae, torch.nn.Module)
             orig_dtype = vae.dtype
             if upcast:
                 vae.to(dtype=torch.float32)
@@ -1008,7 +1032,7 @@ class ImageToLatentsInvocation(BaseInvocation):
     def invoke(self, context: InvocationContext) -> LatentsOutput:
         image = context.images.get_pil(self.image.image_name)
 
-        vae_info = context.services.model_records.load_model(
+        vae_info = context.services.model_manager.load.load_model_by_key(
             **self.vae.vae.model_dump(),
             context=context,
         )
@@ -1026,14 +1050,19 @@ class ImageToLatentsInvocation(BaseInvocation):
     @singledispatchmethod
     @staticmethod
     def _encode_to_tensor(vae: AutoencoderKL, image_tensor: torch.FloatTensor) -> torch.FloatTensor:
+        assert isinstance(vae, torch.nn.Module)
         image_tensor_dist = vae.encode(image_tensor).latent_dist
-        latents = image_tensor_dist.sample().to(dtype=vae.dtype)  # FIXME: uses torch.randn. make reproducible!
+        latents: torch.Tensor = image_tensor_dist.sample().to(
+            dtype=vae.dtype
+        )  # FIXME: uses torch.randn. make reproducible!
         return latents
 
     @_encode_to_tensor.register
     @staticmethod
     def _(vae: AutoencoderTiny, image_tensor: torch.FloatTensor) -> torch.FloatTensor:
-        return vae.encode(image_tensor).latents
+        assert isinstance(vae, torch.nn.Module)
+        latents: torch.FloatTensor = vae.encode(image_tensor).latents
+        return latents
 
 
 @invocation(
@@ -1066,7 +1095,12 @@ class BlendLatentsInvocation(BaseInvocation):
         # TODO:
         device = choose_torch_device()
 
-        def slerp(t, v0, v1, DOT_THRESHOLD=0.9995):
+        def slerp(
+            t: Union[float, npt.NDArray[Any]],  # FIXME: maybe use np.float32 here?
+            v0: Union[torch.Tensor, npt.NDArray[Any]],
+            v1: Union[torch.Tensor, npt.NDArray[Any]],
+            DOT_THRESHOLD: float = 0.9995,
+        ) -> Union[torch.Tensor, npt.NDArray[Any]]:
             """
             Spherical linear interpolation
             Args:
@@ -1099,12 +1133,16 @@ class BlendLatentsInvocation(BaseInvocation):
                 v2 = s0 * v0 + s1 * v1
 
             if inputs_are_torch:
-                v2 = torch.from_numpy(v2).to(device)
-
-            return v2
+                v2_torch: torch.Tensor = torch.from_numpy(v2).to(device)
+                return v2_torch
+            else:
+                assert isinstance(v2, np.ndarray)
+                return v2
 
         # blend
-        blended_latents = slerp(self.alpha, latents_a, latents_b)
+        bl = slerp(self.alpha, latents_a, latents_b)
+        assert isinstance(bl, torch.Tensor)
+        blended_latents: torch.Tensor = bl  # for type checking convenience
 
         # https://discuss.huggingface.co/t/memory-usage-by-later-pipeline-stages/23699
         blended_latents = blended_latents.to("cpu")
@@ -1197,15 +1235,19 @@ class IdealSizeInvocation(BaseInvocation):
         description="Amount to multiply the model's dimensions by when calculating the ideal size (may result in initial generation artifacts if too large)",
     )
 
-    def trim_to_multiple_of(self, *args, multiple_of=LATENT_SCALE_FACTOR):
+    def trim_to_multiple_of(self, *args: int, multiple_of: int = LATENT_SCALE_FACTOR) -> Tuple[int, ...]:
         return tuple((x - x % multiple_of) for x in args)
 
     def invoke(self, context: InvocationContext) -> IdealSizeOutput:
+        unet_config = context.services.model_manager.load.load_model_by_key(
+            **self.unet.unet.model_dump(),
+            context=context,
+        )
         aspect = self.width / self.height
-        dimension = 512
-        if self.unet.unet.base_model == BaseModelType.StableDiffusion2:
+        dimension: float = 512
+        if unet_config.base == BaseModelType.StableDiffusion2:
             dimension = 768
-        elif self.unet.unet.base_model == BaseModelType.StableDiffusionXL:
+        elif unet_config.base == BaseModelType.StableDiffusionXL:
             dimension = 1024
         dimension = dimension * self.multiplier
         min_dimension = math.floor(dimension * 0.5)
diff --git a/invokeai/app/invocations/model.py b/invokeai/app/invocations/model.py
index e2ea744283..fa6e8b98da 100644
--- a/invokeai/app/invocations/model.py
+++ b/invokeai/app/invocations/model.py
@@ -17,7 +17,7 @@ from .baseinvocation import (
 
 
 class ModelInfo(BaseModel):
-    key: str = Field(description="Info to load submodel")
+    key: str = Field(description="Key of model as returned by ModelRecordServiceBase.get_model()")
     submodel: Optional[SubModelType] = Field(default=None, description="Info to load submodel")
 
 
diff --git a/invokeai/app/services/invocation_services.py b/invokeai/app/services/invocation_services.py
index e893be8763..0a1fa1e922 100644
--- a/invokeai/app/services/invocation_services.py
+++ b/invokeai/app/services/invocation_services.py
@@ -27,9 +27,7 @@ if TYPE_CHECKING:
     from .invocation_queue.invocation_queue_base import InvocationQueueABC
     from .invocation_stats.invocation_stats_base import InvocationStatsServiceBase
     from .item_storage.item_storage_base import ItemStorageABC
-    from .model_install import ModelInstallServiceBase
     from .model_manager.model_manager_base import ModelManagerServiceBase
-    from .model_records import ModelRecordServiceBase
     from .names.names_base import NameServiceBase
     from .session_processor.session_processor_base import SessionProcessorBase
     from .session_queue.session_queue_base import SessionQueueBase
@@ -55,9 +53,7 @@ class InvocationServices:
         image_records: "ImageRecordStorageBase",
         logger: "Logger",
         model_manager: "ModelManagerServiceBase",
-        model_records: "ModelRecordServiceBase",
         download_queue: "DownloadQueueServiceBase",
-        model_install: "ModelInstallServiceBase",
         processor: "InvocationProcessorABC",
         performance_statistics: "InvocationStatsServiceBase",
         queue: "InvocationQueueABC",
@@ -82,9 +78,7 @@ class InvocationServices:
         self.image_records = image_records
         self.logger = logger
         self.model_manager = model_manager
-        self.model_records = model_records
         self.download_queue = download_queue
-        self.model_install = model_install
         self.processor = processor
         self.performance_statistics = performance_statistics
         self.queue = queue
diff --git a/invokeai/app/services/invocation_stats/invocation_stats_default.py b/invokeai/app/services/invocation_stats/invocation_stats_default.py
index 0c63b545ff..6c893021de 100644
--- a/invokeai/app/services/invocation_stats/invocation_stats_default.py
+++ b/invokeai/app/services/invocation_stats/invocation_stats_default.py
@@ -43,8 +43,10 @@ class InvocationStatsService(InvocationStatsServiceBase):
 
     @contextmanager
     def collect_stats(self, invocation: BaseInvocation, graph_execution_state_id: str) -> Iterator[None]:
+        # This is to handle case of the model manager not being initialized, which happens
+        # during some tests.
         services = self._invoker.services
-        if services.model_records is None or services.model_records.loader is None:
+        if services.model_manager is None or services.model_manager.load is None:
             yield None
         if not self._stats.get(graph_execution_state_id):
             # First time we're seeing this graph_execution_state_id.
@@ -60,9 +62,8 @@ class InvocationStatsService(InvocationStatsServiceBase):
         if torch.cuda.is_available():
             torch.cuda.reset_peak_memory_stats()
 
-        # TO DO [LS]: clean up loader service - shouldn't be an attribute of model records
-        assert services.model_records.loader is not None
-        services.model_records.loader.ram_cache.stats = self._cache_stats[graph_execution_state_id]
+        assert services.model_manager.load is not None
+        services.model_manager.load.ram_cache.stats = self._cache_stats[graph_execution_state_id]
 
         try:
             # Let the invocation run.
diff --git a/invokeai/app/services/model_load/model_load_base.py b/invokeai/app/services/model_load/model_load_base.py
index 7228806e80..f298d98ce6 100644
--- a/invokeai/app/services/model_load/model_load_base.py
+++ b/invokeai/app/services/model_load/model_load_base.py
@@ -4,7 +4,8 @@
 from abc import ABC, abstractmethod
 from typing import Optional
 
-from invokeai.backend.model_manager import AnyModelConfig, SubModelType
+from invokeai.app.invocations.baseinvocation import InvocationContext
+from invokeai.backend.model_manager import AnyModelConfig, BaseModelType, ModelType, SubModelType
 from invokeai.backend.model_manager.load import LoadedModel
 
 
@@ -12,11 +13,60 @@ class ModelLoadServiceBase(ABC):
     """Wrapper around AnyModelLoader."""
 
     @abstractmethod
-    def load_model_by_key(self, key: str, submodel_type: Optional[SubModelType] = None) -> LoadedModel:
-        """Given a model's key, load it and return the LoadedModel object."""
+    def load_model_by_key(
+        self,
+        key: str,
+        submodel_type: Optional[SubModelType] = None,
+        context: Optional[InvocationContext] = None,
+    ) -> LoadedModel:
+        """
+        Given a model's key, load it and return the LoadedModel object.
+
+        :param key: Key of model config to be fetched.
+        :param submodel: For main (pipeline models), the submodel to fetch.
+        :param context: Invocation context used for event reporting
+        """
         pass
 
     @abstractmethod
-    def load_model_by_config(self, config: AnyModelConfig, submodel_type: Optional[SubModelType] = None) -> LoadedModel:
-        """Given a model's configuration, load it and return the LoadedModel object."""
+    def load_model_by_config(
+        self,
+        model_config: AnyModelConfig,
+        submodel_type: Optional[SubModelType] = None,
+        context: Optional[InvocationContext] = None,
+    ) -> LoadedModel:
+        """
+        Given a model's configuration, load it and return the LoadedModel object.
+
+        :param model_config: Model configuration record (as returned by ModelRecordBase.get_model())
+        :param submodel: For main (pipeline models), the submodel to fetch.
+        :param context: Invocation context used for event reporting
+        """
         pass
+
+    @abstractmethod
+    def load_model_by_attr(
+        self,
+        model_name: str,
+        base_model: BaseModelType,
+        model_type: ModelType,
+        submodel: Optional[SubModelType] = None,
+        context: Optional[InvocationContext] = None,
+    ) -> LoadedModel:
+        """
+        Given a model's attributes, search the database for it, and if found, load and return the LoadedModel object.
+
+        This is provided for API compatability with the get_model() method
+        in the original model manager. However, note that LoadedModel is
+        not the same as the original ModelInfo that ws returned.
+
+        :param model_name: Name of to be fetched.
+        :param base_model: Base model
+        :param model_type: Type of the model
+        :param submodel: For main (pipeline models), the submodel to fetch
+        :param context: The invocation context.
+
+        Exceptions: UnknownModelException -- model with these attributes not known
+                    NotImplementedException -- a model loader was not provided at initialization time
+                    ValueError -- more than one model matches this combination
+        """
diff --git a/invokeai/app/services/model_load/model_load_default.py b/invokeai/app/services/model_load/model_load_default.py
index 80e2fe161d..67107cada6 100644
--- a/invokeai/app/services/model_load/model_load_default.py
+++ b/invokeai/app/services/model_load/model_load_default.py
@@ -3,12 +3,14 @@
 
 from typing import Optional
 
+from invokeai.app.invocations.baseinvocation import InvocationContext
 from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.app.services.model_records import ModelRecordServiceBase
-from invokeai.backend.model_manager import AnyModelConfig, SubModelType
+from invokeai.app.services.invocation_processor.invocation_processor_common import CanceledException
+from invokeai.app.services.model_records import ModelRecordServiceBase, UnknownModelException
+from invokeai.backend.model_manager import AnyModel, AnyModelConfig, BaseModelType, ModelType, SubModelType
 from invokeai.backend.model_manager.load import AnyModelLoader, LoadedModel, ModelCache, ModelConvertCache
 from invokeai.backend.model_manager.load.convert_cache import ModelConvertCacheBase
-from invokeai.backend.model_manager.load.ram_cache import ModelCacheBase
+from invokeai.backend.model_manager.load.model_cache import ModelCacheBase
 from invokeai.backend.util.logging import InvokeAILogger
 
 from .model_load_base import ModelLoadServiceBase
@@ -21,7 +23,7 @@ class ModelLoadService(ModelLoadServiceBase):
         self,
         app_config: InvokeAIAppConfig,
         record_store: ModelRecordServiceBase,
-        ram_cache: Optional[ModelCacheBase] = None,
+        ram_cache: Optional[ModelCacheBase[AnyModel]] = None,
         convert_cache: Optional[ModelConvertCacheBase] = None,
     ):
         """Initialize the model load service."""
@@ -44,11 +46,104 @@ class ModelLoadService(ModelLoadServiceBase):
             ),
         )
 
-    def load_model_by_key(self, key: str, submodel_type: Optional[SubModelType] = None) -> LoadedModel:
-        """Given a model's key, load it and return the LoadedModel object."""
-        config = self._store.get_model(key)
-        return self.load_model_by_config(config, submodel_type)
+    def load_model_by_key(
+        self,
+        key: str,
+        submodel_type: Optional[SubModelType] = None,
+        context: Optional[InvocationContext] = None,
+    ) -> LoadedModel:
+        """
+        Given a model's key, load it and return the LoadedModel object.
 
-    def load_model_by_config(self, config: AnyModelConfig, submodel_type: Optional[SubModelType] = None) -> LoadedModel:
-        """Given a model's configuration, load it and return the LoadedModel object."""
-        return self._any_loader.load_model(config, submodel_type)
+        :param key: Key of model config to be fetched.
+        :param submodel: For main (pipeline models), the submodel to fetch.
+        :param context: Invocation context used for event reporting
+        """
+        config = self._store.get_model(key)
+        return self.load_model_by_config(config, submodel_type, context)
+
+    def load_model_by_attr(
+        self,
+        model_name: str,
+        base_model: BaseModelType,
+        model_type: ModelType,
+        submodel: Optional[SubModelType] = None,
+        context: Optional[InvocationContext] = None,
+    ) -> LoadedModel:
+        """
+        Given a model's attributes, search the database for it, and if found, load and return the LoadedModel object.
+
+        This is provided for API compatability with the get_model() method
+        in the original model manager. However, note that LoadedModel is
+        not the same as the original ModelInfo that ws returned.
+
+        :param model_name: Name of to be fetched.
+        :param base_model: Base model
+        :param model_type: Type of the model
+        :param submodel: For main (pipeline models), the submodel to fetch
+        :param context: The invocation context.
+
+        Exceptions: UnknownModelException -- model with this key not known
+                    NotImplementedException -- a model loader was not provided at initialization time
+                    ValueError -- more than one model matches this combination
+        """
+        configs = self._store.search_by_attr(model_name, base_model, model_type)
+        if len(configs) == 0:
+            raise UnknownModelException(f"{base_model}/{model_type}/{model_name}: Unknown model")
+        elif len(configs) > 1:
+            raise ValueError(f"{base_model}/{model_type}/{model_name}: More than one model matches.")
+        else:
+            return self.load_model_by_key(configs[0].key, submodel)
+
+    def load_model_by_config(
+        self,
+        model_config: AnyModelConfig,
+        submodel_type: Optional[SubModelType] = None,
+        context: Optional[InvocationContext] = None,
+    ) -> LoadedModel:
+        """
+        Given a model's configuration, load it and return the LoadedModel object.
+
+        :param model_config: Model configuration record (as returned by ModelRecordBase.get_model())
+        :param submodel: For main (pipeline models), the submodel to fetch.
+        :param context: Invocation context used for event reporting
+        """
+        if context:
+            self._emit_load_event(
+                context=context,
+                model_config=model_config,
+            )
+        loaded_model = self._any_loader.load_model(model_config, submodel_type)
+        if context:
+            self._emit_load_event(
+                context=context,
+                model_config=model_config,
+                loaded=True,
+            )
+        return loaded_model
+
+    def _emit_load_event(
+        self,
+        context: InvocationContext,
+        model_config: AnyModelConfig,
+        loaded: Optional[bool] = False,
+    ) -> None:
+        if context.services.queue.is_canceled(context.graph_execution_state_id):
+            raise CanceledException()
+
+        if not loaded:
+            context.services.events.emit_model_load_started(
+                queue_id=context.queue_id,
+                queue_item_id=context.queue_item_id,
+                queue_batch_id=context.queue_batch_id,
+                graph_execution_state_id=context.graph_execution_state_id,
+                model_config=model_config,
+            )
+        else:
+            context.services.events.emit_model_load_completed(
+                queue_id=context.queue_id,
+                queue_item_id=context.queue_item_id,
+                queue_batch_id=context.queue_batch_id,
+                graph_execution_state_id=context.graph_execution_state_id,
+                model_config=model_config,
+            )
diff --git a/invokeai/app/services/model_manager/model_manager_base.py b/invokeai/app/services/model_manager/model_manager_base.py
index c6e77fa163..1116c82ff1 100644
--- a/invokeai/app/services/model_manager/model_manager_base.py
+++ b/invokeai/app/services/model_manager/model_manager_base.py
@@ -2,9 +2,10 @@
 
 from abc import ABC, abstractmethod
 
-from pydantic import BaseModel, Field
 from typing_extensions import Self
 
+from invokeai.app.services.invoker import Invoker
+
 from ..config import InvokeAIAppConfig
 from ..download import DownloadQueueServiceBase
 from ..events.events_base import EventServiceBase
@@ -14,12 +15,13 @@ from ..model_records import ModelRecordServiceBase
 from ..shared.sqlite.sqlite_database import SqliteDatabase
 
 
-class ModelManagerServiceBase(BaseModel, ABC):
+class ModelManagerServiceBase(ABC):
     """Abstract base class for the model manager service."""
 
-    store: ModelRecordServiceBase = Field(description="An instance of the model record configuration service.")
-    install: ModelInstallServiceBase = Field(description="An instance of the model install service.")
-    load: ModelLoadServiceBase = Field(description="An instance of the model load service.")
+    # attributes:
+    # store: ModelRecordServiceBase = Field(description="An instance of the model record configuration service.")
+    # install: ModelInstallServiceBase = Field(description="An instance of the model install service.")
+    # load: ModelLoadServiceBase = Field(description="An instance of the model load service.")
 
     @classmethod
     @abstractmethod
@@ -37,3 +39,29 @@ class ModelManagerServiceBase(BaseModel, ABC):
         method simplifies the construction considerably.
         """
         pass
+
+    @property
+    @abstractmethod
+    def store(self) -> ModelRecordServiceBase:
+        """Return the ModelRecordServiceBase used to store and retrieve configuration records."""
+        pass
+
+    @property
+    @abstractmethod
+    def load(self) -> ModelLoadServiceBase:
+        """Return the ModelLoadServiceBase used to load models from their configuration records."""
+        pass
+
+    @property
+    @abstractmethod
+    def install(self) -> ModelInstallServiceBase:
+        """Return the ModelInstallServiceBase used to download and manipulate model files."""
+        pass
+
+    @abstractmethod
+    def start(self, invoker: Invoker) -> None:
+        pass
+
+    @abstractmethod
+    def stop(self, invoker: Invoker) -> None:
+        pass
diff --git a/invokeai/app/services/model_manager/model_manager_default.py b/invokeai/app/services/model_manager/model_manager_default.py
index ad0fd66dbb..028d4af615 100644
--- a/invokeai/app/services/model_manager/model_manager_default.py
+++ b/invokeai/app/services/model_manager/model_manager_default.py
@@ -3,6 +3,7 @@
 
 from typing_extensions import Self
 
+from invokeai.app.services.invoker import Invoker
 from invokeai.backend.model_manager.load import ModelCache, ModelConvertCache
 from invokeai.backend.model_manager.metadata import ModelMetadataStore
 from invokeai.backend.util.logging import InvokeAILogger
@@ -10,9 +11,9 @@ from invokeai.backend.util.logging import InvokeAILogger
 from ..config import InvokeAIAppConfig
 from ..download import DownloadQueueServiceBase
 from ..events.events_base import EventServiceBase
-from ..model_install import ModelInstallService
-from ..model_load import ModelLoadService
-from ..model_records import ModelRecordServiceSQL
+from ..model_install import ModelInstallService, ModelInstallServiceBase
+from ..model_load import ModelLoadService, ModelLoadServiceBase
+from ..model_records import ModelRecordServiceBase, ModelRecordServiceSQL
 from ..shared.sqlite.sqlite_database import SqliteDatabase
 from .model_manager_base import ModelManagerServiceBase
 
@@ -27,6 +28,38 @@ class ModelManagerService(ModelManagerServiceBase):
     model_manager.load    -- Routines to load models into memory.
     """
 
+    def __init__(
+        self,
+        store: ModelRecordServiceBase,
+        install: ModelInstallServiceBase,
+        load: ModelLoadServiceBase,
+    ):
+        self._store = store
+        self._install = install
+        self._load = load
+
+    @property
+    def store(self) -> ModelRecordServiceBase:
+        return self._store
+
+    @property
+    def install(self) -> ModelInstallServiceBase:
+        return self._install
+
+    @property
+    def load(self) -> ModelLoadServiceBase:
+        return self._load
+
+    def start(self, invoker: Invoker) -> None:
+        for service in [self._store, self._install, self._load]:
+            if hasattr(service, "start"):
+                service.start(invoker)
+
+    def stop(self, invoker: Invoker) -> None:
+        for service in [self._store, self._install, self._load]:
+            if hasattr(service, "stop"):
+                service.stop(invoker)
+
     @classmethod
     def build_model_manager(
         cls,
diff --git a/invokeai/app/services/model_records/model_records_base.py b/invokeai/app/services/model_records/model_records_base.py
index e00dd4169d..e2e98c7e89 100644
--- a/invokeai/app/services/model_records/model_records_base.py
+++ b/invokeai/app/services/model_records/model_records_base.py
@@ -10,15 +10,12 @@ from typing import Any, Dict, List, Optional, Set, Tuple, Union
 
 from pydantic import BaseModel, Field
 
-from invokeai.app.invocations.baseinvocation import InvocationContext
 from invokeai.app.services.shared.pagination import PaginatedResults
 from invokeai.backend.model_manager import (
     AnyModelConfig,
     BaseModelType,
-    LoadedModel,
     ModelFormat,
     ModelType,
-    SubModelType,
 )
 from invokeai.backend.model_manager.load import AnyModelLoader
 from invokeai.backend.model_manager.metadata import AnyModelRepoMetadata, ModelMetadataStore
@@ -111,52 +108,6 @@ class ModelRecordServiceBase(ABC):
         """
         pass
 
-    @abstractmethod
-    def load_model(
-        self,
-        key: str,
-        submodel: Optional[SubModelType] = None,
-        context: Optional[InvocationContext] = None,
-    ) -> LoadedModel:
-        """
-        Load the indicated model into memory and return a LoadedModel object.
-
-        :param key: Key of model config to be fetched.
-        :param submodel: For main (pipeline models), the submodel to fetch
-        :param context: Invocation context, used for event issuing.
-
-        Exceptions: UnknownModelException -- model with this key not known
-                    NotImplementedException -- a model loader was not provided at initialization time
-        """
-        pass
-
-    @abstractmethod
-    def load_model_by_attr(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-        submodel: Optional[SubModelType] = None,
-        context: Optional[InvocationContext] = None,
-    ) -> LoadedModel:
-        """
-        Load the indicated model into memory and return a LoadedModel object.
-
-        This is provided for API compatability with the get_model() method
-        in the original model manager. However, note that LoadedModel is
-        not the same as the original ModelInfo that ws returned.
-
-        :param model_name: Key of model config to be fetched.
-        :param base_model: Base model
-        :param model_type: Type of the model
-        :param submodel: For main (pipeline models), the submodel to fetch
-        :param context: The invocation context.
-
-        Exceptions: UnknownModelException -- model with this key not known
-                    NotImplementedException -- a model loader was not provided at initialization time
-        """
-        pass
-
     @property
     @abstractmethod
     def metadata_store(self) -> ModelMetadataStore:
diff --git a/invokeai/app/services/model_records/model_records_sql.py b/invokeai/app/services/model_records/model_records_sql.py
index 28a77b1b1a..f48175351d 100644
--- a/invokeai/app/services/model_records/model_records_sql.py
+++ b/invokeai/app/services/model_records/model_records_sql.py
@@ -46,8 +46,6 @@ from math import ceil
 from pathlib import Path
 from typing import Any, Dict, List, Optional, Set, Tuple, Union
 
-from invokeai.app.invocations.baseinvocation import InvocationContext
-from invokeai.app.services.invocation_processor.invocation_processor_common import CanceledException
 from invokeai.app.services.shared.pagination import PaginatedResults
 from invokeai.backend.model_manager.config import (
     AnyModelConfig,
@@ -55,9 +53,8 @@ from invokeai.backend.model_manager.config import (
     ModelConfigFactory,
     ModelFormat,
     ModelType,
-    SubModelType,
 )
-from invokeai.backend.model_manager.load import AnyModelLoader, LoadedModel
+from invokeai.backend.model_manager.load import AnyModelLoader
 from invokeai.backend.model_manager.metadata import AnyModelRepoMetadata, ModelMetadataStore, UnknownMetadataException
 
 from ..shared.sqlite.sqlite_database import SqliteDatabase
@@ -220,74 +217,6 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
             model = ModelConfigFactory.make_config(json.loads(rows[0]), timestamp=rows[1])
         return model
 
-    def load_model(
-        self,
-        key: str,
-        submodel: Optional[SubModelType],
-        context: Optional[InvocationContext] = None,
-    ) -> LoadedModel:
-        """
-        Load the indicated model into memory and return a LoadedModel object.
-
-        :param key: Key of model config to be fetched.
-        :param submodel: For main (pipeline models), the submodel to fetch.
-        :param context: Invocation context used for event reporting
-
-        Exceptions: UnknownModelException -- model with this key not known
-                    NotImplementedException -- a model loader was not provided at initialization time
-        """
-        if not self._loader:
-            raise NotImplementedError(f"Class {self.__class__} was not initialized with a model loader")
-        # we can emit model loading events if we are executing with access to the invocation context
-
-        model_config = self.get_model(key)
-        if context:
-            self._emit_load_event(
-                context=context,
-                model_config=model_config,
-            )
-        loaded_model = self._loader.load_model(model_config, submodel)
-        if context:
-            self._emit_load_event(
-                context=context,
-                model_config=model_config,
-                loaded=True,
-            )
-        return loaded_model
-
-    def load_model_by_attr(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-        submodel: Optional[SubModelType] = None,
-        context: Optional[InvocationContext] = None,
-    ) -> LoadedModel:
-        """
-        Load the indicated model into memory and return a LoadedModel object.
-
-        This is provided for API compatability with the get_model() method
-        in the original model manager. However, note that LoadedModel is
-        not the same as the original ModelInfo that ws returned.
-
-        :param model_name: Key of model config to be fetched.
-        :param base_model: Base model
-        :param model_type: Type of the model
-        :param submodel: For main (pipeline models), the submodel to fetch
-        :param context: The invocation context.
-
-        Exceptions: UnknownModelException -- model with this key not known
-                    NotImplementedException -- a model loader was not provided at initialization time
-                    ValueError -- more than one model matches this combination
-        """
-        configs = self.search_by_attr(model_name, base_model, model_type)
-        if len(configs) == 0:
-            raise UnknownModelException(f"{base_model}/{model_type}/{model_name}: Unknown model")
-        elif len(configs) > 1:
-            raise ValueError(f"{base_model}/{model_type}/{model_name}: More than one model matches.")
-        else:
-            return self.load_model(configs[0].key, submodel)
-
     def exists(self, key: str) -> bool:
         """
         Return True if a model with the indicated key exists in the databse.
@@ -476,29 +405,3 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
             return PaginatedResults(
                 page=page, pages=ceil(total / per_page), per_page=per_page, total=total, items=items
             )
-
-    def _emit_load_event(
-        self,
-        context: InvocationContext,
-        model_config: AnyModelConfig,
-        loaded: Optional[bool] = False,
-    ) -> None:
-        if context.services.queue.is_canceled(context.graph_execution_state_id):
-            raise CanceledException()
-
-        if not loaded:
-            context.services.events.emit_model_load_started(
-                queue_id=context.queue_id,
-                queue_item_id=context.queue_item_id,
-                queue_batch_id=context.queue_batch_id,
-                graph_execution_state_id=context.graph_execution_state_id,
-                model_config=model_config,
-            )
-        else:
-            context.services.events.emit_model_load_completed(
-                queue_id=context.queue_id,
-                queue_item_id=context.queue_item_id,
-                queue_batch_id=context.queue_batch_id,
-                graph_execution_state_id=context.graph_execution_state_id,
-                model_config=model_config,
-            )
diff --git a/invokeai/app/services/shared/sqlite_migrator/migrations/migration_6.py b/invokeai/app/services/shared/sqlite_migrator/migrations/migration_6.py
index b473444511..1f9ac56518 100644
--- a/invokeai/app/services/shared/sqlite_migrator/migrations/migration_6.py
+++ b/invokeai/app/services/shared/sqlite_migrator/migrations/migration_6.py
@@ -6,6 +6,7 @@ from invokeai.app.services.shared.sqlite_migrator.sqlite_migrator_common import
 class Migration6Callback:
     def __call__(self, cursor: sqlite3.Cursor) -> None:
         self._recreate_model_triggers(cursor)
+        self._delete_ip_adapters(cursor)
 
     def _recreate_model_triggers(self, cursor: sqlite3.Cursor) -> None:
         """
@@ -26,6 +27,22 @@ class Migration6Callback:
             """
         )
 
+    def _delete_ip_adapters(self, cursor: sqlite3.Cursor) -> None:
+        """
+        Delete all the IP adapters.
+
+        The model manager will automatically find and re-add them after the migration
+        is done. This allows the manager to add the correct image encoder to their
+        configuration records.
+        """
+
+        cursor.execute(
+            """--sql
+            DELETE FROM model_config
+              WHERE type='ip_adapter';
+            """
+        )
+
 
 def build_migration_6() -> Migration:
     """
@@ -33,6 +50,8 @@ def build_migration_6() -> Migration:
 
     This migration does the following:
     - Adds the model_config_updated_at trigger if it does not exist
+    - Delete all ip_adapter models so that the model prober can find and
+      update with the correct image processor model.
     """
     migration_6 = Migration(
         from_version=5,
diff --git a/invokeai/backend/embeddings/model_patcher.py b/invokeai/backend/embeddings/model_patcher.py
index 4725181b8e..bee8909c31 100644
--- a/invokeai/backend/embeddings/model_patcher.py
+++ b/invokeai/backend/embeddings/model_patcher.py
@@ -64,7 +64,7 @@ class ModelPatcher:
     def apply_lora_unet(
         cls,
         unet: UNet2DConditionModel,
-        loras: List[Tuple[LoRAModelRaw, float]],
+        loras: Iterator[Tuple[LoRAModelRaw, float]],
     ) -> None:
         with cls.apply_lora(unet, loras, "lora_unet_"):
             yield
@@ -307,7 +307,7 @@ class ONNXModelPatcher:
     def apply_lora_unet(
         cls,
         unet: OnnxRuntimeModel,
-        loras: List[Tuple[LoRAModelRaw, float]],
+        loras: Iterator[Tuple[LoRAModelRaw, float]],
     ) -> None:
         with cls.apply_lora(unet, loras, "lora_unet_"):
             yield
diff --git a/invokeai/backend/image_util/safety_checker.py b/invokeai/backend/image_util/safety_checker.py
index b9649925e1..92ddef5ecc 100644
--- a/invokeai/backend/image_util/safety_checker.py
+++ b/invokeai/backend/image_util/safety_checker.py
@@ -8,8 +8,8 @@ from PIL import Image
 
 import invokeai.backend.util.logging as logger
 from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.backend import SilenceWarnings
 from invokeai.backend.util.devices import choose_torch_device
+from invokeai.backend.util.silence_warnings import SilenceWarnings
 
 config = InvokeAIAppConfig.get_config()
 
diff --git a/invokeai/backend/ip_adapter/ip_adapter.py b/invokeai/backend/ip_adapter/ip_adapter.py
index 9176bf1f49..b4706ea99c 100644
--- a/invokeai/backend/ip_adapter/ip_adapter.py
+++ b/invokeai/backend/ip_adapter/ip_adapter.py
@@ -8,7 +8,6 @@ from PIL import Image
 from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
 
 from invokeai.backend.ip_adapter.ip_attention_weights import IPAttentionWeights
-from invokeai.backend.model_management.models.base import calc_model_size_by_data
 
 from .resampler import Resampler
 
@@ -124,6 +123,9 @@ class IPAdapter:
         self.attn_weights.to(device=self.device, dtype=self.dtype)
 
     def calc_size(self):
+        # workaround for circular import
+        from invokeai.backend.model_manager.load.model_util import calc_model_size_by_data
+
         return calc_model_size_by_data(self._image_proj_model) + calc_model_size_by_data(self.attn_weights)
 
     def _init_image_proj_model(self, state_dict):
diff --git a/invokeai/backend/model_manager/config.py b/invokeai/backend/model_manager/config.py
index 4534a4892f..9f0f774b49 100644
--- a/invokeai/backend/model_manager/config.py
+++ b/invokeai/backend/model_manager/config.py
@@ -21,7 +21,7 @@ Validation errors will raise an InvalidModelConfigException error.
 """
 import time
 from enum import Enum
-from typing import Literal, Optional, Type, Union, Class
+from typing import Literal, Optional, Type, Union
 
 import torch
 from diffusers import ModelMixin
@@ -335,7 +335,7 @@ class ModelConfigFactory(object):
         cls,
         model_data: Union[Dict[str, Any], AnyModelConfig],
         key: Optional[str] = None,
-        dest_class: Optional[Type[Class]] = None,
+        dest_class: Optional[Type[ModelConfigBase]] = None,
         timestamp: Optional[float] = None,
     ) -> AnyModelConfig:
         """
@@ -347,14 +347,17 @@ class ModelConfigFactory(object):
         :param dest_class: The config class to be returned. If not provided, will
         be selected automatically.
         """
+        model: Optional[ModelConfigBase] = None
         if isinstance(model_data, ModelConfigBase):
             model = model_data
         elif dest_class:
-            model = dest_class.validate_python(model_data)
+            model = dest_class.model_validate(model_data)
         else:
-            model = AnyModelConfigValidator.validate_python(model_data)
+            # mypy doesn't typecheck TypeAdapters well?
+            model = AnyModelConfigValidator.validate_python(model_data)  # type: ignore
+        assert model is not None
         if key:
             model.key = key
         if timestamp:
             model.last_modified = timestamp
-        return model
+        return model  # type: ignore
diff --git a/invokeai/backend/model_manager/load/load_base.py b/invokeai/backend/model_manager/load/load_base.py
index 9d98ee3053..3d026af226 100644
--- a/invokeai/backend/model_manager/load/load_base.py
+++ b/invokeai/backend/model_manager/load/load_base.py
@@ -18,8 +18,16 @@ from pathlib import Path
 from typing import Any, Callable, Dict, Optional, Tuple, Type
 
 from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.backend.model_manager import AnyModelConfig, BaseModelType, ModelFormat, ModelType, SubModelType
-from invokeai.backend.model_manager.config import AnyModel, VaeCheckpointConfig, VaeDiffusersConfig
+from invokeai.backend.model_manager.config import (
+    AnyModel,
+    AnyModelConfig,
+    BaseModelType,
+    ModelFormat,
+    ModelType,
+    SubModelType,
+    VaeCheckpointConfig,
+    VaeDiffusersConfig,
+)
 from invokeai.backend.model_manager.load.convert_cache.convert_cache_base import ModelConvertCacheBase
 from invokeai.backend.model_manager.load.model_cache.model_cache_base import ModelCacheBase, ModelLockerBase
 from invokeai.backend.util.logging import InvokeAILogger
@@ -32,7 +40,7 @@ class LoadedModel:
     config: AnyModelConfig
     locker: ModelLockerBase
 
-    def __enter__(self) -> AnyModel:  # I think load_file() always returns a dict
+    def __enter__(self) -> AnyModel:
         """Context entry."""
         self.locker.lock()
         return self.model
@@ -171,6 +179,10 @@ class AnyModelLoader:
         def decorator(subclass: Type[ModelLoaderBase]) -> Type[ModelLoaderBase]:
             cls._logger.debug(f"Registering class {subclass.__name__} to load models of type {base}/{type}/{format}")
             key = cls._to_registry_key(base, type, format)
+            if key in cls._registry:
+                raise Exception(
+                    f"{subclass.__name__} is trying to register as a loader for {base}/{type}/{format}, but this type of model has already been registered by {cls._registry[key].__name__}"
+                )
             cls._registry[key] = subclass
             return subclass
 
diff --git a/invokeai/backend/model_manager/load/load_default.py b/invokeai/backend/model_manager/load/load_default.py
index c1dfe729af..df83c8320d 100644
--- a/invokeai/backend/model_manager/load/load_default.py
+++ b/invokeai/backend/model_manager/load/load_default.py
@@ -169,7 +169,7 @@ class ModelLoader(ModelLoaderBase):
                 raise InvalidModelConfigException("An expected config.json file is missing from this model.") from e
 
     # This needs to be implemented in subclasses that handle checkpoints
-    def _convert_model(self, config: AnyModelConfig, weights_path: Path, output_path: Path) -> Path:
+    def _convert_model(self, config: AnyModelConfig, model_path: Path, output_path: Path) -> Path:
         raise NotImplementedError
 
     # This needs to be implemented in the subclass
diff --git a/invokeai/backend/model_manager/load/model_cache/model_cache_default.py b/invokeai/backend/model_manager/load/model_cache/model_cache_default.py
index b1deb215b2..98d6f34cea 100644
--- a/invokeai/backend/model_manager/load/model_cache/model_cache_default.py
+++ b/invokeai/backend/model_manager/load/model_cache/model_cache_default.py
@@ -246,7 +246,7 @@ class ModelCache(ModelCacheBase[AnyModel]):
 
     def move_model_to_device(self, cache_entry: CacheRecord[AnyModel], target_device: torch.device) -> None:
         """Move model into the indicated device."""
-        # These attributes are not in the base ModelMixin class but in derived classes.
+        # These attributes are not in the base ModelMixin class but in various derived classes.
         # Some models don't have these attributes, in which case they run in RAM/CPU.
         self.logger.debug(f"Called to move {cache_entry.key} to {target_device}")
         if not (hasattr(cache_entry.model, "device") and hasattr(cache_entry.model, "to")):
diff --git a/invokeai/backend/model_manager/load/model_loaders/controlnet.py b/invokeai/backend/model_manager/load/model_loaders/controlnet.py
index e61e2b46a6..d446d07933 100644
--- a/invokeai/backend/model_manager/load/model_loaders/controlnet.py
+++ b/invokeai/backend/model_manager/load/model_loaders/controlnet.py
@@ -35,28 +35,28 @@ class ControlnetLoader(GenericDiffusersLoader):
         else:
             return True
 
-    def _convert_model(self, config: AnyModelConfig, weights_path: Path, output_path: Path) -> Path:
+    def _convert_model(self, config: AnyModelConfig, model_path: Path, output_path: Path) -> Path:
         if config.base not in {BaseModelType.StableDiffusion1, BaseModelType.StableDiffusion2}:
             raise Exception(f"Vae conversion not supported for model type: {config.base}")
         else:
             assert hasattr(config, "config")
             config_file = config.config
 
-        if weights_path.suffix == ".safetensors":
-            checkpoint = safetensors.torch.load_file(weights_path, device="cpu")
+        if model_path.suffix == ".safetensors":
+            checkpoint = safetensors.torch.load_file(model_path, device="cpu")
         else:
-            checkpoint = torch.load(weights_path, map_location="cpu")
+            checkpoint = torch.load(model_path, map_location="cpu")
 
         # sometimes weights are hidden under "state_dict", and sometimes not
         if "state_dict" in checkpoint:
             checkpoint = checkpoint["state_dict"]
 
         convert_controlnet_to_diffusers(
-            weights_path,
+            model_path,
             output_path,
             original_config_file=self._app_config.root_path / config_file,
             image_size=512,
             scan_needed=True,
-            from_safetensors=weights_path.suffix == ".safetensors",
+            from_safetensors=model_path.suffix == ".safetensors",
         )
         return output_path
diff --git a/invokeai/backend/model_manager/load/model_loaders/generic_diffusers.py b/invokeai/backend/model_manager/load/model_loaders/generic_diffusers.py
index 03c26f3a0c..114e317f3c 100644
--- a/invokeai/backend/model_manager/load/model_loaders/generic_diffusers.py
+++ b/invokeai/backend/model_manager/load/model_loaders/generic_diffusers.py
@@ -12,8 +12,9 @@ from invokeai.backend.model_manager import (
     ModelType,
     SubModelType,
 )
-from invokeai.backend.model_manager.load.load_base import AnyModelLoader
-from invokeai.backend.model_manager.load.load_default import ModelLoader
+
+from ..load_base import AnyModelLoader
+from ..load_default import ModelLoader
 
 
 @AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.CLIPVision, format=ModelFormat.Diffusers)
diff --git a/invokeai/backend/model_manager/load/model_loaders/stable_diffusion.py b/invokeai/backend/model_manager/load/model_loaders/stable_diffusion.py
index a963e8403b..23b4e1fccd 100644
--- a/invokeai/backend/model_manager/load/model_loaders/stable_diffusion.py
+++ b/invokeai/backend/model_manager/load/model_loaders/stable_diffusion.py
@@ -65,7 +65,7 @@ class StableDiffusionDiffusersModel(ModelLoader):
         else:
             return True
 
-    def _convert_model(self, config: AnyModelConfig, weights_path: Path, output_path: Path) -> Path:
+    def _convert_model(self, config: AnyModelConfig, model_path: Path, output_path: Path) -> Path:
         assert isinstance(config, MainCheckpointConfig)
         variant = config.variant
         base = config.base
@@ -75,9 +75,9 @@ class StableDiffusionDiffusersModel(ModelLoader):
 
         config_file = config.config
 
-        self._logger.info(f"Converting {weights_path} to diffusers format")
+        self._logger.info(f"Converting {model_path} to diffusers format")
         convert_ckpt_to_diffusers(
-            weights_path,
+            model_path,
             output_path,
             model_type=self.model_base_to_model_type[base],
             model_version=base,
@@ -86,7 +86,7 @@ class StableDiffusionDiffusersModel(ModelLoader):
             extract_ema=True,
             scan_needed=True,
             pipeline_class=pipeline_class,
-            from_safetensors=weights_path.suffix == ".safetensors",
+            from_safetensors=model_path.suffix == ".safetensors",
             precision=self._torch_dtype,
             load_safety_checker=False,
         )
diff --git a/invokeai/backend/model_manager/load/model_loaders/vae.py b/invokeai/backend/model_manager/load/model_loaders/vae.py
index 882ae05577..3983ea7595 100644
--- a/invokeai/backend/model_manager/load/model_loaders/vae.py
+++ b/invokeai/backend/model_manager/load/model_loaders/vae.py
@@ -37,7 +37,7 @@ class VaeLoader(GenericDiffusersLoader):
         else:
             return True
 
-    def _convert_model(self, config: AnyModelConfig, weights_path: Path, output_path: Path) -> Path:
+    def _convert_model(self, config: AnyModelConfig, model_path: Path, output_path: Path) -> Path:
         # TO DO: check whether sdxl VAE models convert.
         if config.base not in {BaseModelType.StableDiffusion1, BaseModelType.StableDiffusion2}:
             raise Exception(f"Vae conversion not supported for model type: {config.base}")
@@ -46,10 +46,10 @@ class VaeLoader(GenericDiffusersLoader):
                 "v1-inference.yaml" if config.base == BaseModelType.StableDiffusion1 else "v2-inference-v.yaml"
             )
 
-        if weights_path.suffix == ".safetensors":
-            checkpoint = safetensors.torch.load_file(weights_path, device="cpu")
+        if model_path.suffix == ".safetensors":
+            checkpoint = safetensors.torch.load_file(model_path, device="cpu")
         else:
-            checkpoint = torch.load(weights_path, map_location="cpu")
+            checkpoint = torch.load(model_path, map_location="cpu")
 
         # sometimes weights are hidden under "state_dict", and sometimes not
         if "state_dict" in checkpoint:
diff --git a/invokeai/backend/model_manager/load/model_util.py b/invokeai/backend/model_manager/load/model_util.py
index 3f2d22595e..c55eee48fa 100644
--- a/invokeai/backend/model_manager/load/model_util.py
+++ b/invokeai/backend/model_manager/load/model_util.py
@@ -65,7 +65,7 @@ def calc_model_size_by_fs(model_path: Path, subfolder: Optional[str] = None, var
     bit8_files = {f for f in all_files if ".8bit." in f.name or ".8bit-" in f.name}
     other_files = set(all_files) - fp16_files - bit8_files
 
-    if variant is None:
+    if not variant:  # ModelRepoVariant.DEFAULT evaluates to empty string for compatability with HF
         files = other_files
     elif variant == "fp16":
         files = fp16_files
diff --git a/invokeai/backend/model_manager/search.py b/invokeai/backend/model_manager/search.py
index a54938fdd5..f7e1e1bed7 100644
--- a/invokeai/backend/model_manager/search.py
+++ b/invokeai/backend/model_manager/search.py
@@ -22,11 +22,12 @@ Example usage:
 
 import os
 from abc import ABC, abstractmethod
+from logging import Logger
 from pathlib import Path
 from typing import Callable, Optional, Set, Union
 
 from pydantic import BaseModel, Field
-from logging import Logger
+
 from invokeai.backend.util.logging import InvokeAILogger
 
 default_logger: Logger = InvokeAILogger.get_logger()
diff --git a/invokeai/backend/stable_diffusion/schedulers/__init__.py b/invokeai/backend/stable_diffusion/schedulers/__init__.py
index a4e9dbf9da..0b780d3ee2 100644
--- a/invokeai/backend/stable_diffusion/schedulers/__init__.py
+++ b/invokeai/backend/stable_diffusion/schedulers/__init__.py
@@ -1 +1,3 @@
 from .schedulers import SCHEDULER_MAP  # noqa: F401
+
+__all__ = ["SCHEDULER_MAP"]
diff --git a/invokeai/frontend/install/model_install.py b/invokeai/frontend/install/model_install.py
index 22b132370e..20b630dfc6 100644
--- a/invokeai/frontend/install/model_install.py
+++ b/invokeai/frontend/install/model_install.py
@@ -513,7 +513,7 @@ def select_and_download_models(opt: Namespace) -> None:
     """Prompt user for install/delete selections and execute."""
     precision = "float32" if opt.full_precision else choose_precision(torch.device(choose_torch_device()))
     # unsure how to avoid a typing complaint in the next line: config.precision is an enumerated Literal
-    config.precision = precision  # type: ignore
+    config.precision = precision
     install_helper = InstallHelper(config, logger)
     installer = install_helper.installer
 
diff --git a/tests/aa_nodes/test_graph_execution_state.py b/tests/aa_nodes/test_graph_execution_state.py
index 27d2d2230a..f839a4a878 100644
--- a/tests/aa_nodes/test_graph_execution_state.py
+++ b/tests/aa_nodes/test_graph_execution_state.py
@@ -62,9 +62,7 @@ def mock_services() -> InvocationServices:
         invocation_cache=MemoryInvocationCache(max_cache_size=0),
         logger=logging,  # type: ignore
         model_manager=None,  # type: ignore
-        model_records=None,  # type: ignore
         download_queue=None,  # type: ignore
-        model_install=None,  # type: ignore
         names=None,  # type: ignore
         performance_statistics=InvocationStatsService(),
         processor=DefaultInvocationProcessor(),
diff --git a/tests/aa_nodes/test_invoker.py b/tests/aa_nodes/test_invoker.py
index 437ea0f00d..774f7501dc 100644
--- a/tests/aa_nodes/test_invoker.py
+++ b/tests/aa_nodes/test_invoker.py
@@ -65,9 +65,7 @@ def mock_services() -> InvocationServices:
         invocation_cache=MemoryInvocationCache(max_cache_size=0),
         logger=logging,  # type: ignore
         model_manager=None,  # type: ignore
-        model_records=None,  # type: ignore
         download_queue=None,  # type: ignore
-        model_install=None,  # type: ignore
         names=None,  # type: ignore
         performance_statistics=InvocationStatsService(),
         processor=DefaultInvocationProcessor(),
diff --git a/tests/backend/model_manager_2/model_loading/test_model_load.py b/tests/backend/model_manager_2/model_loading/test_model_load.py
new file mode 100644
index 0000000000..a7a64e91ac
--- /dev/null
+++ b/tests/backend/model_manager_2/model_loading/test_model_load.py
@@ -0,0 +1,22 @@
+"""
+Test model loading
+"""
+
+from pathlib import Path
+
+from invokeai.app.services.model_install import ModelInstallServiceBase
+from invokeai.backend.embeddings.textual_inversion import TextualInversionModelRaw
+from invokeai.backend.model_manager.load import AnyModelLoader
+from tests.backend.model_manager_2.model_manager_2_fixtures import *  # noqa F403
+
+
+def test_loading(mm2_installer: ModelInstallServiceBase, mm2_loader: AnyModelLoader, embedding_file: Path):
+    store = mm2_installer.record_store
+    matches = store.search_by_attr(model_name="test_embedding")
+    assert len(matches) == 0
+    key = mm2_installer.register_path(embedding_file)
+    loaded_model = mm2_loader.load_model(store.get_model(key))
+    assert loaded_model is not None
+    assert loaded_model.config.key == key
+    with loaded_model as model:
+        assert isinstance(model, TextualInversionModelRaw)
diff --git a/tests/backend/model_manager_2/model_manager_2_fixtures.py b/tests/backend/model_manager_2/model_manager_2_fixtures.py
index d6d091befe..d85eab67dd 100644
--- a/tests/backend/model_manager_2/model_manager_2_fixtures.py
+++ b/tests/backend/model_manager_2/model_manager_2_fixtures.py
@@ -20,6 +20,7 @@ from invokeai.backend.model_manager.config import (
     ModelFormat,
     ModelType,
 )
+from invokeai.backend.model_manager.load import AnyModelLoader, ModelCache, ModelConvertCache
 from invokeai.backend.model_manager.metadata import ModelMetadataStore
 from invokeai.backend.util.logging import InvokeAILogger
 from tests.backend.model_manager_2.model_metadata.metadata_examples import (
@@ -89,6 +90,16 @@ def mm2_app_config(mm2_root_dir: Path) -> InvokeAIAppConfig:
     return app_config
 
 
+@pytest.fixture
+def mm2_loader(mm2_app_config: InvokeAIAppConfig, mm2_record_store: ModelRecordServiceSQL) -> AnyModelLoader:
+    logger = InvokeAILogger.get_logger(config=mm2_app_config)
+    ram_cache = ModelCache(
+        logger=logger, max_cache_size=mm2_app_config.ram_cache_size, max_vram_cache_size=mm2_app_config.vram_cache_size
+    )
+    convert_cache = ModelConvertCache(mm2_app_config.models_convert_cache_path)
+    return AnyModelLoader(app_config=mm2_app_config, logger=logger, ram_cache=ram_cache, convert_cache=convert_cache)
+
+
 @pytest.fixture
 def mm2_record_store(mm2_app_config: InvokeAIAppConfig) -> ModelRecordServiceSQL:
     logger = InvokeAILogger.get_logger(config=mm2_app_config)

From 4027e845d47437e371446f2f520cc8895fdeab25 Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lstein@gmail.com>
Date: Sun, 11 Feb 2024 23:37:49 -0500
Subject: [PATCH 121/411] add back the `heuristic_import()` method and extend
 repo_ids to arbitrary file paths

---
 docs/contributing/MODEL_MANAGER.md            | 52 ++++++++++++--
 invokeai/app/api/routers/model_manager_v2.py  | 70 ++++++++++++++++++-
 invokeai/app/api_app.py                       |  1 -
 .../model_install/model_install_base.py       | 39 ++++++++++-
 .../model_install/model_install_default.py    | 43 +++++++++++-
 .../model_manager/util/select_hf_files.py     |  6 ++
 6 files changed, 199 insertions(+), 12 deletions(-)

diff --git a/docs/contributing/MODEL_MANAGER.md b/docs/contributing/MODEL_MANAGER.md
index 39220f4ba8..959b7f9733 100644
--- a/docs/contributing/MODEL_MANAGER.md
+++ b/docs/contributing/MODEL_MANAGER.md
@@ -446,6 +446,44 @@ required parameters:
 
 Once initialized, the installer will provide the following methods:
 
+#### install_job = installer.heuristic_import(source, [config], [access_token])
+
+This is a simplified interface to the installer which takes a source
+string, an optional model configuration dictionary and an optional
+access token.
+
+The `source` is a string that can be any of these forms
+
+1. A path on the local filesystem (`C:\\users\\fred\\model.safetensors`)
+2. A Url pointing to a single downloadable model file (`https://civitai.com/models/58390/detail-tweaker-lora-lora`)
+3. A HuggingFace repo_id with any of the following formats:
+   - `model/name` -- entire model
+   - `model/name:fp32` -- entire model, using the fp32 variant
+   - `model/name:fp16:vae` -- vae submodel, using the fp16 variant
+   - `model/name::vae` -- vae submodel, using default precision
+   - `model/name:fp16:path/to/model.safetensors` -- an individual model file, fp16 variant
+   - `model/name::path/to/model.safetensors` -- an individual model file, default variant
+
+Note that by specifying a relative path to the top of the HuggingFace
+repo, you can download and install arbitrary models files. 
+
+The variant, if not provided, will be automatically filled in with
+`fp32` if the user has requested full precision, and `fp16`
+otherwise. If a variant that does not exist is requested, then the
+method will install whatever HuggingFace returns as its default
+revision.
+
+`config` is an optional dict of values that will override the
+autoprobed values for model type, base, scheduler prediction type, and
+so forth. See [Model configuration and
+probing](#Model-configuration-and-probing) for details.
+
+`access_token` is an optional access token for accessing resources
+that need authentication.
+
+The method will return a `ModelInstallJob`. This object is discussed
+at length in the following section.
+
 #### install_job = installer.import_model()
 
 The `import_model()` method is the core of the installer. The
@@ -464,9 +502,10 @@ source2 = LocalModelSource(path='/opt/models/sushi_diffusers')     # a local dif
 source3 = HFModelSource(repo_id='runwayml/stable-diffusion-v1-5')  # a repo_id
 source4 = HFModelSource(repo_id='runwayml/stable-diffusion-v1-5', subfolder='vae')  # a subfolder within a repo_id
 source5 = HFModelSource(repo_id='runwayml/stable-diffusion-v1-5', variant='fp16')   # a named variant of a HF model
+source6 = HFModelSource(repo_id='runwayml/stable-diffusion-v1-5', subfolder='OrangeMix/OrangeMix1.ckpt')   # path to an individual model file
 
-source6 = URLModelSource(url='https://civitai.com/api/download/models/63006')       # model located at a URL
-source7 = URLModelSource(url='https://civitai.com/api/download/models/63006', access_token='letmein') # with an access token
+source7 = URLModelSource(url='https://civitai.com/api/download/models/63006')       # model located at a URL
+source8 = URLModelSource(url='https://civitai.com/api/download/models/63006', access_token='letmein') # with an access token
 
 for source in [source1, source2, source3, source4, source5, source6, source7]:
    install_job = installer.install_model(source)
@@ -522,7 +561,6 @@ can be passed to `import_model()`.
 attributes returned by the model prober. See the section below for
 details.
 
-
 #### LocalModelSource
 
 This is used for a model that is located on a locally-accessible Posix
@@ -715,7 +753,7 @@ and `cancelled`, as well as `in_terminal_state`. The last will return
 True if the job is in the complete, errored or cancelled states.
 
 
-#### Model confguration and probing
+#### Model configuration and probing
 
 The install service uses the `invokeai.backend.model_manager.probe`
 module during import to determine the model's type, base type, and
@@ -1106,7 +1144,7 @@ job = queue.create_download_job(
 		 event_handlers=[my_handler1, my_handler2], # if desired
 		 start=True,
 	)
- ```
+```
  
 The `filename` argument forces the downloader to use the specified
 name for the file rather than the name provided by the remote source,
@@ -1427,9 +1465,9 @@ set of keys to the corresponding model config objects.
 Find all model metadata records that have the given author and return
 a set of keys to the corresponding model config objects.
 
-# The remainder of this documentation is provisional, pending implementation of the Load service
+***
 
-## Let's get loaded, the lowdown on ModelLoadService
+## The Lowdown on the ModelLoadService
 
 The `ModelLoadService` is responsible for loading a named model into
 memory so that it can be used for inference. Despite the fact that it
diff --git a/invokeai/app/api/routers/model_manager_v2.py b/invokeai/app/api/routers/model_manager_v2.py
index 4fc785e4f7..4482edfa0f 100644
--- a/invokeai/app/api/routers/model_manager_v2.py
+++ b/invokeai/app/api/routers/model_manager_v2.py
@@ -251,9 +251,75 @@ async def add_model_record(
     return result
 
 
+@model_manager_v2_router.post(
+    "/heuristic_import",
+    operation_id="heuristic_import_model",
+    responses={
+        201: {"description": "The model imported successfully"},
+        415: {"description": "Unrecognized file/folder format"},
+        424: {"description": "The model appeared to import successfully, but could not be found in the model manager"},
+        409: {"description": "There is already a model corresponding to this path or repo_id"},
+    },
+    status_code=201,
+)
+async def heuristic_import(
+    source: str,
+    config: Optional[Dict[str, Any]] = Body(
+        description="Dict of fields that override auto-probed values in the model config record, such as name, description and prediction_type ",
+        default=None,
+    ),
+    access_token: Optional[str] = None,
+) -> ModelInstallJob:
+    """Install a model using a string identifier.
+
+    `source` can be any of the following.
+
+    1. A path on the local filesystem ('C:\\users\\fred\\model.safetensors')
+    2. A Url pointing to a single downloadable model file
+    3. A HuggingFace repo_id with any of the following formats:
+       - model/name
+       - model/name:fp16:vae
+       - model/name::vae          -- use default precision
+       - model/name:fp16:path/to/model.safetensors
+       - model/name::path/to/model.safetensors
+
+    `config` is an optional dict containing model configuration values that will override
+    the ones that are probed automatically.
+
+    `access_token` is an optional access token for use with Urls that require
+    authentication.
+
+    Models will be downloaded, probed, configured and installed in a
+    series of background threads. The return object has `status` attribute
+    that can be used to monitor progress.
+
+    See the documentation for `import_model_record` for more information on
+    interpreting the job information returned by this route.
+    """
+    logger = ApiDependencies.invoker.services.logger
+
+    try:
+        installer = ApiDependencies.invoker.services.model_manager.install
+        result: ModelInstallJob = installer.heuristic_import(
+            source=source,
+            config=config,
+        )
+        logger.info(f"Started installation of {source}")
+    except UnknownModelException as e:
+        logger.error(str(e))
+        raise HTTPException(status_code=424, detail=str(e))
+    except InvalidModelException as e:
+        logger.error(str(e))
+        raise HTTPException(status_code=415)
+    except ValueError as e:
+        logger.error(str(e))
+        raise HTTPException(status_code=409, detail=str(e))
+    return result
+
+
 @model_manager_v2_router.post(
     "/import",
-    operation_id="import_model_record",
+    operation_id="import_model",
     responses={
         201: {"description": "The model imported successfully"},
         415: {"description": "Unrecognized file/folder format"},
@@ -269,7 +335,7 @@ async def import_model(
         default=None,
     ),
 ) -> ModelInstallJob:
-    """Add a model using its local path, repo_id, or remote URL.
+    """Install a model using its local path, repo_id, or remote URL.
 
     Models will be downloaded, probed, configured and installed in a
     series of background threads. The return object has `status` attribute
diff --git a/invokeai/app/api_app.py b/invokeai/app/api_app.py
index 851cbc8160..1831b54c13 100644
--- a/invokeai/app/api_app.py
+++ b/invokeai/app/api_app.py
@@ -49,7 +49,6 @@ if True:  # hack to make flake8 happy with imports coming after setting up the c
         download_queue,
         images,
         model_manager_v2,
-        models,
         session_queue,
         sessions,
         utilities,
diff --git a/invokeai/app/services/model_install/model_install_base.py b/invokeai/app/services/model_install/model_install_base.py
index 635cb154d6..943cdf1157 100644
--- a/invokeai/app/services/model_install/model_install_base.py
+++ b/invokeai/app/services/model_install/model_install_base.py
@@ -127,8 +127,8 @@ class HFModelSource(StringLikeSource):
     def __str__(self) -> str:
         """Return string version of repoid when string rep needed."""
         base: str = self.repo_id
+        base += f":{self.variant or ''}"
         base += f":{self.subfolder}" if self.subfolder else ""
-        base += f" ({self.variant})" if self.variant else ""
         return base
 
 
@@ -324,6 +324,43 @@ class ModelInstallServiceBase(ABC):
         :returns id: The string ID of the registered model.
         """
 
+    @abstractmethod
+    def heuristic_import(
+        self,
+        source: str,
+        config: Optional[Dict[str, Any]] = None,
+        access_token: Optional[str] = None,
+    ) -> ModelInstallJob:
+        r"""Install the indicated model using heuristics to interpret user intentions.
+
+        :param source: String source
+        :param config: Optional dict. Any fields in this dict
+         will override corresponding autoassigned probe fields in the
+         model's config record as described in `import_model()`.
+        :param access_token: Optional access token for remote sources.
+
+        The source can be:
+        1. A local file path in posix() format (`/foo/bar` or `C:\foo\bar`)
+        2. An http or https URL (`https://foo.bar/foo`)
+        3. A HuggingFace repo_id (`foo/bar`, `foo/bar:fp16`, `foo/bar:fp16:vae`)
+
+        We extend the HuggingFace repo_id syntax to include the variant and the
+        subfolder or path. The following are acceptable alternatives:
+            stabilityai/stable-diffusion-v4
+            stabilityai/stable-diffusion-v4:fp16
+            stabilityai/stable-diffusion-v4:fp16:vae
+            stabilityai/stable-diffusion-v4::/checkpoints/sd4.safetensors
+            stabilityai/stable-diffusion-v4:onnx:vae
+
+        Because a local file path can look like a huggingface repo_id, the logic
+        first checks whether the path exists on disk, and if not, it is treated as
+        a parseable huggingface repo.
+
+        The previous support for recursing into a local folder and loading all model-like files
+        has been removed.
+        """
+        pass
+
     @abstractmethod
     def import_model(
         self,
diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py
index d32af4a513..df73fcb8cb 100644
--- a/invokeai/app/services/model_install/model_install_default.py
+++ b/invokeai/app/services/model_install/model_install_default.py
@@ -50,6 +50,7 @@ from .model_install_base import (
     ModelInstallJob,
     ModelInstallServiceBase,
     ModelSource,
+    StringLikeSource,
     URLModelSource,
 )
 
@@ -177,6 +178,34 @@ class ModelInstallService(ModelInstallServiceBase):
             info,
         )
 
+    def heuristic_import(
+        self,
+        source: str,
+        config: Optional[Dict[str, Any]] = None,
+        access_token: Optional[str] = None,
+    ) -> ModelInstallJob:
+        variants = "|".join(ModelRepoVariant.__members__.values())
+        hf_repoid_re = f"^([^/:]+/[^/:]+)(?::({variants})?(?::/?([^:]+))?)?$"
+        source_obj: Optional[StringLikeSource] = None
+
+        if Path(source).exists():  # A local file or directory
+            source_obj = LocalModelSource(path=Path(source))
+        elif match := re.match(hf_repoid_re, source):
+            source_obj = HFModelSource(
+                repo_id=match.group(1),
+                variant=match.group(2) if match.group(2) else None,  # pass None rather than ''
+                subfolder=Path(match.group(3)) if match.group(3) else None,
+                access_token=access_token,
+            )
+        elif re.match(r"^https?://[^/]+", source):
+            source_obj = URLModelSource(
+                url=AnyHttpUrl(source),
+                access_token=access_token,
+            )
+        else:
+            raise ValueError(f"Unsupported model source: '{source}'")
+        return self.import_model(source_obj, config)
+
     def import_model(self, source: ModelSource, config: Optional[Dict[str, Any]] = None) -> ModelInstallJob:  # noqa D102
         similar_jobs = [x for x in self.list_jobs() if x.source == source and not x.in_terminal_state]
         if similar_jobs:
@@ -571,6 +600,8 @@ class ModelInstallService(ModelInstallServiceBase):
         # TODO: Replace with tempfile.tmpdir() when multithreading is cleaned up.
         # Currently the tmpdir isn't automatically removed at exit because it is
         # being held in a daemon thread.
+        if len(remote_files) == 0:
+            raise ValueError(f"{source}: No downloadable files found")
         tmpdir = Path(
             mkdtemp(
                 dir=self._app_config.models_path,
@@ -586,6 +617,16 @@ class ModelInstallService(ModelInstallServiceBase):
             bytes=0,
             total_bytes=0,
         )
+        # In the event that there is a subfolder specified in the source,
+        # we need to remove it from the destination path in order to avoid
+        # creating unwanted subfolders
+        if hasattr(source, "subfolder") and source.subfolder:
+            root = Path(remote_files[0].path.parts[0])
+            subfolder = root / source.subfolder
+        else:
+            root = Path(".")
+            subfolder = Path(".")
+
         # we remember the path up to the top of the tmpdir so that it may be
         # removed safely at the end of the install process.
         install_job._install_tmpdir = tmpdir
@@ -595,7 +636,7 @@ class ModelInstallService(ModelInstallServiceBase):
         self._logger.debug(f"remote_files={remote_files}")
         for model_file in remote_files:
             url = model_file.url
-            path = model_file.path
+            path = root / model_file.path.relative_to(subfolder)
             self._logger.info(f"Downloading {url} => {path}")
             install_job.total_bytes += model_file.size
             assert hasattr(source, "access_token")
diff --git a/invokeai/backend/model_manager/util/select_hf_files.py b/invokeai/backend/model_manager/util/select_hf_files.py
index a894d915de..2fd7a3721a 100644
--- a/invokeai/backend/model_manager/util/select_hf_files.py
+++ b/invokeai/backend/model_manager/util/select_hf_files.py
@@ -36,6 +36,11 @@ def filter_files(
     """
     variant = variant or ModelRepoVariant.DEFAULT
     paths: List[Path] = []
+    root = files[0].parts[0]
+
+    # if the subfolder is a single file, then bypass the selection and just return it
+    if subfolder and subfolder.suffix in [".safetensors", ".bin", ".onnx", ".xml", ".pth", ".pt", ".ckpt", ".msgpack"]:
+        return [root / subfolder]
 
     # Start by filtering on model file extensions, discarding images, docs, etc
     for file in files:
@@ -61,6 +66,7 @@ def filter_files(
 
     # limit search to subfolder if requested
     if subfolder:
+        subfolder = root / subfolder
         paths = [x for x in paths if x.parent == Path(subfolder)]
 
     # _filter_by_variant uniquifies the paths and returns a set

From a2cc4047f9f026d48218145bd3ff925a7936949c Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lstein@gmail.com>
Date: Mon, 12 Feb 2024 14:27:17 -0500
Subject: [PATCH 122/411] add a JIT download_and_cache() call to the model
 installer

---
 docs/contributing/MODEL_MANAGER.md            | 40 +++++++++++++++
 .../app/services/download/download_base.py    | 13 +++++
 .../app/services/download/download_default.py | 15 +++++-
 .../model_install/model_install_base.py       | 34 ++++++++++++-
 .../model_install/model_install_default.py    | 49 ++++++++++++++++++-
 .../convert_cache/convert_cache_default.py    |  8 ++-
 6 files changed, 154 insertions(+), 5 deletions(-)

diff --git a/docs/contributing/MODEL_MANAGER.md b/docs/contributing/MODEL_MANAGER.md
index 959b7f9733..b711c654de 100644
--- a/docs/contributing/MODEL_MANAGER.md
+++ b/docs/contributing/MODEL_MANAGER.md
@@ -792,6 +792,14 @@ returns a list of completed jobs. The optional `timeout` argument will
 return from the call if jobs aren't completed in the specified
 time. An argument of 0 (the default) will block indefinitely.
 
+#### jobs = installer.wait_for_job(job, [timeout])
+
+Like `wait_for_installs()`, but block until a specific job has
+completed or errored, and then return the job.  The optional `timeout`
+argument will return from the call if the job doesn't complete in the
+specified time. An argument of 0 (the default) will block
+indefinitely.
+
 #### jobs = installer.list_jobs()
 
 Return a list of all active and complete `ModelInstallJobs`.
@@ -854,6 +862,31 @@ This method is similar to `unregister()`, but also unconditionally
 deletes the corresponding model weights file(s), regardless of whether
 they are inside or outside the InvokeAI models hierarchy.
 
+
+#### path = installer.download_and_cache(remote_source, [access_token], [timeout])
+
+This utility routine will download the model file located at source,
+cache it, and return the path to the cached file. It does not attempt
+to determine the model type, probe its configuration values, or
+register it with the models database.
+
+You may provide an access token if the remote source requires
+authorization. The call will block indefinitely until the file is
+completely downloaded, cancelled or raises an error of some sort. If
+you provide a timeout (in seconds), the call will raise a
+`TimeoutError` exception if the download hasn't completed in the
+specified period.
+
+You may use this mechanism to request any type of file, not just a
+model. The file will be stored in a subdirectory of
+`INVOKEAI_ROOT/models/.cache`. If the requested file is found in the
+cache, its path will be returned without redownloading it.
+
+Be aware that the models cache is cleared of infrequently-used files
+and directories at regular intervals when the size of the cache
+exceeds the value specified in Invoke's `convert_cache` configuration
+variable.
+
 #### List[str]=installer.scan_directory(scan_dir: Path, install: bool)
 
 This method will recursively scan the directory indicated in
@@ -1187,6 +1220,13 @@ queue or was not created by this queue.
 This method will block until all the active jobs in the queue have
 reached a terminal state (completed, errored or cancelled).
 
+#### queue.wait_for_job(job, [timeout])
+
+This method will block until the indicated job has reached a terminal
+state (completed, errored or cancelled). If the optional timeout is
+provided, the call will block for at most timeout seconds, and raise a
+TimeoutError otherwise.
+
 #### jobs = queue.list_jobs()
 
 This will return a list of all jobs, including ones that have not yet
diff --git a/invokeai/app/services/download/download_base.py b/invokeai/app/services/download/download_base.py
index f854f64f58..2ac13b825f 100644
--- a/invokeai/app/services/download/download_base.py
+++ b/invokeai/app/services/download/download_base.py
@@ -260,3 +260,16 @@ class DownloadQueueServiceBase(ABC):
     def join(self) -> None:
         """Wait until all jobs are off the queue."""
         pass
+
+    @abstractmethod
+    def wait_for_job(self, job: DownloadJob, timeout: int = 0) -> DownloadJob:
+        """Wait until the indicated download job has reached a terminal state.
+
+        This will block until the indicated install job has completed,
+        been cancelled, or errored out.
+
+        :param job: The job to wait on.
+        :param timeout: Wait up to indicated number of seconds. Raise a TimeoutError if
+        the job hasn't completed within the indicated time.
+        """
+        pass
diff --git a/invokeai/app/services/download/download_default.py b/invokeai/app/services/download/download_default.py
index 7613c0893f..f740c50087 100644
--- a/invokeai/app/services/download/download_default.py
+++ b/invokeai/app/services/download/download_default.py
@@ -4,6 +4,7 @@
 import os
 import re
 import threading
+import time
 import traceback
 from pathlib import Path
 from queue import Empty, PriorityQueue
@@ -52,6 +53,7 @@ class DownloadQueueService(DownloadQueueServiceBase):
         self._next_job_id = 0
         self._queue = PriorityQueue()
         self._stop_event = threading.Event()
+        self._job_completed_event = threading.Event()
         self._worker_pool = set()
         self._lock = threading.Lock()
         self._logger = InvokeAILogger.get_logger("DownloadQueueService")
@@ -188,6 +190,16 @@ class DownloadQueueService(DownloadQueueServiceBase):
             if not job.in_terminal_state:
                 self.cancel_job(job)
 
+    def wait_for_job(self, job: DownloadJob, timeout: int = 0) -> DownloadJob:
+        """Block until the indicated job has reached terminal state, or when timeout limit reached."""
+        start = time.time()
+        while not job.in_terminal_state:
+            if self._job_completed_event.wait(timeout=5):  # in case we miss an event
+                self._job_completed_event.clear()
+            if timeout > 0 and time.time() - start > timeout:
+                raise TimeoutError("Timeout exceeded")
+        return job
+
     def _start_workers(self, max_workers: int) -> None:
         """Start the requested number of worker threads."""
         self._stop_event.clear()
@@ -223,6 +235,7 @@ class DownloadQueueService(DownloadQueueServiceBase):
 
             finally:
                 job.job_ended = get_iso_timestamp()
+                self._job_completed_event.set()  # signal a change to terminal state
                 self._queue.task_done()
         self._logger.debug(f"Download queue worker thread {threading.current_thread().name} exiting.")
 
@@ -407,7 +420,7 @@ class DownloadQueueService(DownloadQueueServiceBase):
 
 # Example on_progress event handler to display a TQDM status bar
 # Activate with:
-#   download_service.download('http://foo.bar/baz', '/tmp', on_progress=TqdmProgress().job_update
+#   download_service.download(DownloadJob('http://foo.bar/baz', '/tmp', on_progress=TqdmProgress().update))
 class TqdmProgress(object):
     """TQDM-based progress bar object to use in on_progress handlers."""
 
diff --git a/invokeai/app/services/model_install/model_install_base.py b/invokeai/app/services/model_install/model_install_base.py
index 943cdf1157..39ea8c4a0d 100644
--- a/invokeai/app/services/model_install/model_install_base.py
+++ b/invokeai/app/services/model_install/model_install_base.py
@@ -422,6 +422,18 @@ class ModelInstallServiceBase(ABC):
     def cancel_job(self, job: ModelInstallJob) -> None:
         """Cancel the indicated job."""
 
+    @abstractmethod
+    def wait_for_job(self, job: ModelInstallJob, timeout: int = 0) -> ModelInstallJob:
+        """Wait for the indicated job to reach a terminal state.
+
+        This will block until the indicated install job has completed,
+        been cancelled, or errored out.
+
+        :param job: The job to wait on.
+        :param timeout: Wait up to indicated number of seconds. Raise a TimeoutError if
+        the job hasn't completed within the indicated time.
+        """
+
     @abstractmethod
     def wait_for_installs(self, timeout: int = 0) -> List[ModelInstallJob]:
         """
@@ -431,7 +443,8 @@ class ModelInstallServiceBase(ABC):
         completed, been cancelled, or errored out.
 
         :param timeout: Wait up to indicated number of seconds. Raise an Exception('timeout') if
-        installs do not complete within the indicated time.
+        installs do not complete within the indicated time. A timeout of zero (the default)
+        will block indefinitely until the installs complete.
         """
 
     @abstractmethod
@@ -447,3 +460,22 @@ class ModelInstallServiceBase(ABC):
     @abstractmethod
     def sync_to_config(self) -> None:
         """Synchronize models on disk to those in the model record database."""
+
+    @abstractmethod
+    def download_and_cache(self, source: Union[str, AnyHttpUrl], access_token: Optional[str] = None) -> Path:
+        """
+        Download the model file located at source to the models cache and return its Path.
+
+        :param source: A Url or a string that can be converted into one.
+        :param access_token: Optional access token to access restricted resources.
+
+        The model file will be downloaded into the system-wide model cache
+        (`models/.cache`) if it isn't already there. Note that the model cache
+        is periodically cleared of infrequently-used entries when the model
+        converter runs.
+
+        Note that this doesn't automaticallly install or register the model, but is
+        intended for use by nodes that need access to models that aren't directly
+        supported by InvokeAI. The downloading process takes advantage of the download queue
+        to avoid interrupting other operations.
+        """
diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py
index df73fcb8cb..414e300715 100644
--- a/invokeai/app/services/model_install/model_install_default.py
+++ b/invokeai/app/services/model_install/model_install_default.py
@@ -17,7 +17,7 @@ from pydantic.networks import AnyHttpUrl
 from requests import Session
 
 from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.app.services.download import DownloadJob, DownloadQueueServiceBase
+from invokeai.app.services.download import DownloadJob, DownloadQueueServiceBase, TqdmProgress
 from invokeai.app.services.events.events_base import EventServiceBase
 from invokeai.app.services.invoker import Invoker
 from invokeai.app.services.model_records import DuplicateModelException, ModelRecordServiceBase, ModelRecordServiceSQL
@@ -87,6 +87,7 @@ class ModelInstallService(ModelInstallServiceBase):
         self._lock = threading.Lock()
         self._stop_event = threading.Event()
         self._downloads_changed_event = threading.Event()
+        self._install_completed_event = threading.Event()
         self._download_queue = download_queue
         self._download_cache: Dict[AnyHttpUrl, ModelInstallJob] = {}
         self._running = False
@@ -241,6 +242,17 @@ class ModelInstallService(ModelInstallServiceBase):
         assert isinstance(jobs[0], ModelInstallJob)
         return jobs[0]
 
+    def wait_for_job(self, job: ModelInstallJob, timeout: int = 0) -> ModelInstallJob:
+        """Block until the indicated job has reached terminal state, or when timeout limit reached."""
+        start = time.time()
+        while not job.in_terminal_state:
+            if self._install_completed_event.wait(timeout=5):  # in case we miss an event
+                self._install_completed_event.clear()
+            if timeout > 0 and time.time() - start > timeout:
+                raise TimeoutError("Timeout exceeded")
+        return job
+
+    # TODO: Better name? Maybe wait_for_jobs()? Maybe too easily confused with above
     def wait_for_installs(self, timeout: int = 0) -> List[ModelInstallJob]:  # noqa D102
         """Block until all installation jobs are done."""
         start = time.time()
@@ -248,7 +260,7 @@ class ModelInstallService(ModelInstallServiceBase):
             if self._downloads_changed_event.wait(timeout=5):  # in case we miss an event
                 self._downloads_changed_event.clear()
             if timeout > 0 and time.time() - start > timeout:
-                raise Exception("Timeout exceeded")
+                raise TimeoutError("Timeout exceeded")
         self._install_queue.join()
         return self._install_jobs
 
@@ -302,6 +314,38 @@ class ModelInstallService(ModelInstallServiceBase):
             path.unlink()
         self.unregister(key)
 
+    def download_and_cache(
+        self,
+        source: Union[str, AnyHttpUrl],
+        access_token: Optional[str] = None,
+        timeout: int = 0,
+    ) -> Path:
+        """Download the model file located at source to the models cache and return its Path."""
+        model_hash = sha256(str(source).encode("utf-8")).hexdigest()[0:32]
+        model_path = self._app_config.models_convert_cache_path / model_hash
+
+        # We expect the cache directory to contain one and only one downloaded file.
+        # We don't know the file's name in advance, as it is set by the download
+        # content-disposition header.
+        if model_path.exists():
+            contents = [x for x in model_path.iterdir() if x.is_file()]
+            if len(contents) > 0:
+                return contents[0]
+
+        model_path.mkdir(parents=True, exist_ok=True)
+        job = self._download_queue.download(
+            source=AnyHttpUrl(str(source)),
+            dest=model_path,
+            access_token=access_token,
+            on_progress=TqdmProgress().update,
+        )
+        self._download_queue.wait_for_job(job, timeout)
+        if job.complete:
+            assert job.download_path is not None
+            return job.download_path
+        else:
+            raise Exception(job.error)
+
     # --------------------------------------------------------------------------------------------
     # Internal functions that manage the installer threads
     # --------------------------------------------------------------------------------------------
@@ -365,6 +409,7 @@ class ModelInstallService(ModelInstallServiceBase):
                 # if this is an install of a remote file, then clean up the temporary directory
                 if job._install_tmpdir is not None:
                     rmtree(job._install_tmpdir)
+                self._install_completed_event.set()
                 self._install_queue.task_done()
 
         self._logger.info("Install thread exiting")
diff --git a/invokeai/backend/model_manager/load/convert_cache/convert_cache_default.py b/invokeai/backend/model_manager/load/convert_cache/convert_cache_default.py
index 4c361258d9..84f4f76299 100644
--- a/invokeai/backend/model_manager/load/convert_cache/convert_cache_default.py
+++ b/invokeai/backend/model_manager/load/convert_cache/convert_cache_default.py
@@ -53,7 +53,13 @@ class ModelConvertCache(ModelConvertCacheBase):
                 sentinel = path / config
                 if sentinel.exists():
                     return sentinel.stat().st_atime
-            return 0.0
+
+            # no sentinel file found! - pick the most recent file in the directory
+            try:
+                atimes = sorted([x.stat().st_atime for x in path.iterdir() if x.is_file()], reverse=True)
+                return atimes[0]
+            except IndexError:
+                return 0.0
 
         # sort by last access time - least accessed files will be at the end
         lru_models = sorted(self._cache_path.iterdir(), key=by_atime, reverse=True)

From ff6e94f828ab2f5549de93b4b1b4b379417e2020 Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lstein@gmail.com>
Date: Mon, 12 Feb 2024 21:25:42 -0500
Subject: [PATCH 123/411] add route for model conversion from safetensors to
 diffusers

- Begin to add SwaggerUI documentation for AnyModelConfig and other
  discriminated Unions.
---
 invokeai/app/api/routers/model_manager_v2.py  | 80 ++++++++++++++++++-
 .../model_install/model_install_default.py    |  6 +-
 .../services/model_load/model_load_base.py    | 14 +++-
 .../services/model_load/model_load_default.py | 12 ++-
 .../model_records/model_records_base.py       |  7 --
 .../model_records/model_records_sql.py        | 10 +--
 .../backend/model_manager/load/load_base.py   |  5 ++
 7 files changed, 113 insertions(+), 21 deletions(-)

diff --git a/invokeai/app/api/routers/model_manager_v2.py b/invokeai/app/api/routers/model_manager_v2.py
index 4482edfa0f..8d31c6f286 100644
--- a/invokeai/app/api/routers/model_manager_v2.py
+++ b/invokeai/app/api/routers/model_manager_v2.py
@@ -2,6 +2,7 @@
 """FastAPI route for model configuration records."""
 
 import pathlib
+import shutil
 from hashlib import sha1
 from random import randbytes
 from typing import Any, Dict, List, Optional, Set
@@ -24,8 +25,10 @@ from invokeai.app.services.shared.pagination import PaginatedResults
 from invokeai.backend.model_manager.config import (
     AnyModelConfig,
     BaseModelType,
+    MainCheckpointConfig,
     ModelFormat,
     ModelType,
+    SubModelType,
 )
 from invokeai.backend.model_manager.merge import MergeInterpolationMethod, ModelMerger
 from invokeai.backend.model_manager.metadata import AnyModelRepoMetadata
@@ -318,7 +321,7 @@ async def heuristic_import(
 
 
 @model_manager_v2_router.post(
-    "/import",
+    "/install",
     operation_id="import_model",
     responses={
         201: {"description": "The model imported successfully"},
@@ -490,6 +493,81 @@ async def sync_models_to_config() -> Response:
     return Response(status_code=204)
 
 
+@model_manager_v2_router.put(
+    "/convert/{key}",
+    operation_id="convert_model",
+    responses={
+        200: {"description": "Model converted successfully"},
+        400: {"description": "Bad request"},
+        404: {"description": "Model not found"},
+        409: {"description": "There is already a model registered at this location"},
+    },
+)
+async def convert_model(
+    key: str = Path(description="Unique key of the safetensors main model to convert to diffusers format."),
+) -> AnyModelConfig:
+    """
+    Permanently convert a model into diffusers format, replacing the safetensors version.
+    Note that the key and model hash will change. Use the model configuration record returned
+    by this call to get the new values.
+    """
+    logger = ApiDependencies.invoker.services.logger
+    loader = ApiDependencies.invoker.services.model_manager.load
+    store = ApiDependencies.invoker.services.model_manager.store
+    installer = ApiDependencies.invoker.services.model_manager.install
+
+    try:
+        model_config = store.get_model(key)
+    except UnknownModelException as e:
+        logger.error(str(e))
+        raise HTTPException(status_code=424, detail=str(e))
+
+    if not isinstance(model_config, MainCheckpointConfig):
+        logger.error(f"The model with key {key} is not a main checkpoint model.")
+        raise HTTPException(400, f"The model with key {key} is not a main checkpoint model.")
+
+    # loading the model will convert it into a cached diffusers file
+    loader.load_model_by_config(model_config, submodel_type=SubModelType.Scheduler)
+
+    # Get the path of the converted model from the loader
+    cache_path = loader.convert_cache.cache_path(key)
+    assert cache_path.exists()
+
+    # temporarily rename the original safetensors file so that there is no naming conflict
+    original_name = model_config.name
+    model_config.name = f"{original_name}.DELETE"
+    store.update_model(key, config=model_config)
+
+    # install the diffusers
+    try:
+        new_key = installer.install_path(
+            cache_path,
+            config={
+                "name": original_name,
+                "description": model_config.description,
+                "original_hash": model_config.original_hash,
+                "source": model_config.source,
+            },
+        )
+    except DuplicateModelException as e:
+        logger.error(str(e))
+        raise HTTPException(status_code=409, detail=str(e))
+
+    # get the original metadata
+    if orig_metadata := store.get_metadata(key):
+        store.metadata_store.add_metadata(new_key, orig_metadata)
+
+    # delete the original safetensors file
+    installer.delete(key)
+
+    # delete the cached version
+    shutil.rmtree(cache_path)
+
+    # return the config record for the new diffusers directory
+    new_config: AnyModelConfig = store.get_model(new_key)
+    return new_config
+
+
 @model_manager_v2_router.put(
     "/merge",
     operation_id="merge",
diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py
index 414e300715..20a85a82a1 100644
--- a/invokeai/app/services/model_install/model_install_default.py
+++ b/invokeai/app/services/model_install/model_install_default.py
@@ -162,8 +162,10 @@ class ModelInstallService(ModelInstallServiceBase):
             config["source"] = model_path.resolve().as_posix()
 
         info: AnyModelConfig = self._probe_model(Path(model_path), config)
-        old_hash = info.original_hash
-        dest_path = self.app_config.models_path / info.base.value / info.type.value / model_path.name
+        old_hash = info.current_hash
+        dest_path = (
+            self.app_config.models_path / info.base.value / info.type.value / (config.get("name") or model_path.name)
+        )
         try:
             new_path = self._copy_model(model_path, dest_path)
         except FileExistsError as excp:
diff --git a/invokeai/app/services/model_load/model_load_base.py b/invokeai/app/services/model_load/model_load_base.py
index f298d98ce6..45eaf4652f 100644
--- a/invokeai/app/services/model_load/model_load_base.py
+++ b/invokeai/app/services/model_load/model_load_base.py
@@ -5,8 +5,10 @@ from abc import ABC, abstractmethod
 from typing import Optional
 
 from invokeai.app.invocations.baseinvocation import InvocationContext
-from invokeai.backend.model_manager import AnyModelConfig, BaseModelType, ModelType, SubModelType
+from invokeai.backend.model_manager import AnyModel, AnyModelConfig, BaseModelType, ModelType, SubModelType
 from invokeai.backend.model_manager.load import LoadedModel
+from invokeai.backend.model_manager.load.convert_cache import ModelConvertCacheBase
+from invokeai.backend.model_manager.load.model_cache.model_cache_base import ModelCacheBase
 
 
 class ModelLoadServiceBase(ABC):
@@ -70,3 +72,13 @@ class ModelLoadServiceBase(ABC):
                     NotImplementedException -- a model loader was not provided at initialization time
                     ValueError -- more than one model matches this combination
         """
+
+    @property
+    @abstractmethod
+    def ram_cache(self) -> ModelCacheBase[AnyModel]:
+        """Return the RAM cache used by this loader."""
+
+    @property
+    @abstractmethod
+    def convert_cache(self) -> ModelConvertCacheBase:
+        """Return the checkpoint convert cache used by this loader."""
diff --git a/invokeai/app/services/model_load/model_load_default.py b/invokeai/app/services/model_load/model_load_default.py
index 67107cada6..a6ccd5afbc 100644
--- a/invokeai/app/services/model_load/model_load_default.py
+++ b/invokeai/app/services/model_load/model_load_default.py
@@ -10,7 +10,7 @@ from invokeai.app.services.model_records import ModelRecordServiceBase, UnknownM
 from invokeai.backend.model_manager import AnyModel, AnyModelConfig, BaseModelType, ModelType, SubModelType
 from invokeai.backend.model_manager.load import AnyModelLoader, LoadedModel, ModelCache, ModelConvertCache
 from invokeai.backend.model_manager.load.convert_cache import ModelConvertCacheBase
-from invokeai.backend.model_manager.load.model_cache import ModelCacheBase
+from invokeai.backend.model_manager.load.model_cache.model_cache_base import ModelCacheBase
 from invokeai.backend.util.logging import InvokeAILogger
 
 from .model_load_base import ModelLoadServiceBase
@@ -46,6 +46,16 @@ class ModelLoadService(ModelLoadServiceBase):
             ),
         )
 
+    @property
+    def ram_cache(self) -> ModelCacheBase[AnyModel]:
+        """Return the RAM cache used by this loader."""
+        return self._any_loader.ram_cache
+
+    @property
+    def convert_cache(self) -> ModelConvertCacheBase:
+        """Return the checkpoint convert cache used by this loader."""
+        return self._any_loader.convert_cache
+
     def load_model_by_key(
         self,
         key: str,
diff --git a/invokeai/app/services/model_records/model_records_base.py b/invokeai/app/services/model_records/model_records_base.py
index e2e98c7e89..b2eacc524b 100644
--- a/invokeai/app/services/model_records/model_records_base.py
+++ b/invokeai/app/services/model_records/model_records_base.py
@@ -17,7 +17,6 @@ from invokeai.backend.model_manager import (
     ModelFormat,
     ModelType,
 )
-from invokeai.backend.model_manager.load import AnyModelLoader
 from invokeai.backend.model_manager.metadata import AnyModelRepoMetadata, ModelMetadataStore
 
 
@@ -195,12 +194,6 @@ class ModelRecordServiceBase(ABC):
         """
         pass
 
-    @property
-    @abstractmethod
-    def loader(self) -> Optional[AnyModelLoader]:
-        """Return the model loader used by this instance."""
-        pass
-
     def all_models(self) -> List[AnyModelConfig]:
         """Return all the model configs in the database."""
         return self.search_by_attr()
diff --git a/invokeai/app/services/model_records/model_records_sql.py b/invokeai/app/services/model_records/model_records_sql.py
index f48175351d..84a1412383 100644
--- a/invokeai/app/services/model_records/model_records_sql.py
+++ b/invokeai/app/services/model_records/model_records_sql.py
@@ -54,7 +54,6 @@ from invokeai.backend.model_manager.config import (
     ModelFormat,
     ModelType,
 )
-from invokeai.backend.model_manager.load import AnyModelLoader
 from invokeai.backend.model_manager.metadata import AnyModelRepoMetadata, ModelMetadataStore, UnknownMetadataException
 
 from ..shared.sqlite.sqlite_database import SqliteDatabase
@@ -70,28 +69,21 @@ from .model_records_base import (
 class ModelRecordServiceSQL(ModelRecordServiceBase):
     """Implementation of the ModelConfigStore ABC using a SQL database."""
 
-    def __init__(self, db: SqliteDatabase, loader: Optional[AnyModelLoader] = None):
+    def __init__(self, db: SqliteDatabase):
         """
         Initialize a new object from preexisting sqlite3 connection and threading lock objects.
 
         :param db: Sqlite connection object
-        :param loader: Initialized model loader object (optional)
         """
         super().__init__()
         self._db = db
         self._cursor = db.conn.cursor()
-        self._loader = loader
 
     @property
     def db(self) -> SqliteDatabase:
         """Return the underlying database."""
         return self._db
 
-    @property
-    def loader(self) -> Optional[AnyModelLoader]:
-        """Return the model loader used by this instance."""
-        return self._loader
-
     def add_model(self, key: str, config: Union[Dict[str, Any], AnyModelConfig]) -> AnyModelConfig:
         """
         Add a model to the database.
diff --git a/invokeai/backend/model_manager/load/load_base.py b/invokeai/backend/model_manager/load/load_base.py
index 3d026af226..5f392ada75 100644
--- a/invokeai/backend/model_manager/load/load_base.py
+++ b/invokeai/backend/model_manager/load/load_base.py
@@ -117,6 +117,11 @@ class AnyModelLoader:
         """Return the RAM cache associated used by the loaders."""
         return self._ram_cache
 
+    @property
+    def convert_cache(self) -> ModelConvertCacheBase:
+        """Return the convert cache associated used by the loaders."""
+        return self._convert_cache
+
     def load_model(self, model_config: AnyModelConfig, submodel_type: Optional[SubModelType] = None) -> LoadedModel:
         """
         Return a model given its configuration.

From 3e330d7d9dce1b1f4cb1b3ede864bf143d207680 Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lstein@gmail.com>
Date: Tue, 13 Feb 2024 00:26:49 -0500
Subject: [PATCH 124/411] fix a number of typechecking errors

---
 invokeai/app/api/routers/download_queue.py    |  6 +-
 invokeai/app/api/routers/model_manager_v2.py  | 69 ++++++++++++++++---
 invokeai/app/invocations/ip_adapter.py        |  4 +-
 invokeai/app/invocations/model.py             |  8 +--
 invokeai/app/services/config/config_base.py   | 11 +--
 invokeai/app/services/config/config_common.py |  2 +-
 .../app/services/download/download_default.py | 12 ++--
 invokeai/app/util/misc.py                     |  8 +--
 .../backend/model_manager/load/load_base.py   | 13 ++--
 .../load/model_cache/model_cache_default.py   |  4 +-
 .../metadata/fetch/fetch_base.py              |  4 +-
 invokeai/backend/model_manager/probe.py       |  2 +-
 invokeai/backend/model_manager/search.py      |  6 +-
 13 files changed, 101 insertions(+), 48 deletions(-)

diff --git a/invokeai/app/api/routers/download_queue.py b/invokeai/app/api/routers/download_queue.py
index 2dba376c18..a6e53c7a5c 100644
--- a/invokeai/app/api/routers/download_queue.py
+++ b/invokeai/app/api/routers/download_queue.py
@@ -36,7 +36,7 @@ async def list_downloads() -> List[DownloadJob]:
         400: {"description": "Bad request"},
     },
 )
-async def prune_downloads():
+async def prune_downloads() -> Response:
     """Prune completed and errored jobs."""
     queue = ApiDependencies.invoker.services.download_queue
     queue.prune_jobs()
@@ -87,7 +87,7 @@ async def get_download_job(
 )
 async def cancel_download_job(
     id: int = Path(description="ID of the download job to cancel."),
-):
+) -> Response:
     """Cancel a download job using its ID."""
     try:
         queue = ApiDependencies.invoker.services.download_queue
@@ -105,7 +105,7 @@ async def cancel_download_job(
         204: {"description": "Download jobs have been cancelled"},
     },
 )
-async def cancel_all_download_jobs():
+async def cancel_all_download_jobs() -> Response:
     """Cancel all download jobs."""
     ApiDependencies.invoker.services.download_queue.cancel_all_jobs()
     return Response(status_code=204)
diff --git a/invokeai/app/api/routers/model_manager_v2.py b/invokeai/app/api/routers/model_manager_v2.py
index 8d31c6f286..029c620707 100644
--- a/invokeai/app/api/routers/model_manager_v2.py
+++ b/invokeai/app/api/routers/model_manager_v2.py
@@ -9,7 +9,7 @@ from typing import Any, Dict, List, Optional, Set
 
 from fastapi import Body, Path, Query, Response
 from fastapi.routing import APIRouter
-from pydantic import BaseModel, ConfigDict
+from pydantic import BaseModel, ConfigDict, Field
 from starlette.exceptions import HTTPException
 from typing_extensions import Annotated
 
@@ -37,6 +37,35 @@ from ..dependencies import ApiDependencies
 
 model_manager_v2_router = APIRouter(prefix="/v2/models", tags=["model_manager_v2"])
 
+example_model_output = {
+    "path": "sd-1/main/openjourney",
+    "name": "openjourney",
+    "base": "sd-1",
+    "type": "main",
+    "format": "diffusers",
+    "key": "3a0e45ff858926fd4a63da630688b1e1",
+    "original_hash": "1c12f18fb6e403baef26fb9d720fbd2f",
+    "current_hash": "1c12f18fb6e403baef26fb9d720fbd2f",
+    "description": "sd-1 main model openjourney",
+    "source": "/opt/invokeai/models/sd-1/main/openjourney",
+    "last_modified": 1707794711,
+    "vae": "/opt/invokeai/models/sd-1/vae/vae-ft-mse-840000-ema-pruned_fp16.safetensors",
+    "variant": "normal",
+    "prediction_type": "epsilon",
+    "repo_variant": "fp16",
+}
+
+example_model_input = {
+    "path": "base/type/name",
+    "name": "model_name",
+    "base": "sd-1",
+    "type": "main",
+    "format": "diffusers",
+    "description": "Model description",
+    "vae": None,
+    "variant": "normal",
+}
+
 
 class ModelsList(BaseModel):
     """Return list of configs."""
@@ -88,7 +117,10 @@ async def list_model_records(
     "/i/{key}",
     operation_id="get_model_record",
     responses={
-        200: {"description": "Success"},
+        200: {
+            "description": "The model configuration was retrieved successfully",
+            "content": {"application/json": {"example": example_model_output}},
+        },
         400: {"description": "Bad request"},
         404: {"description": "The model could not be found"},
     },
@@ -165,18 +197,22 @@ async def search_by_metadata_tags(
     "/i/{key}",
     operation_id="update_model_record",
     responses={
-        200: {"description": "The model was updated successfully"},
+        200: {
+            "description": "The model was updated successfully",
+            "content": {"application/json": {"example": example_model_output}},
+        },
         400: {"description": "Bad request"},
         404: {"description": "The model could not be found"},
         409: {"description": "There is already a model corresponding to the new name"},
     },
     status_code=200,
-    response_model=AnyModelConfig,
 )
 async def update_model_record(
     key: Annotated[str, Path(description="Unique key of model")],
-    info: Annotated[AnyModelConfig, Body(description="Model config", discriminator="type")],
-) -> AnyModelConfig:
+    info: Annotated[
+        AnyModelConfig, Body(description="Model config", discriminator="type", example=example_model_input)
+    ],
+) -> Annotated[AnyModelConfig, Field(example="this is neat")]:
     """Update model contents with a new config. If the model name or base fields are changed, then the model is renamed."""
     logger = ApiDependencies.invoker.services.logger
     record_store = ApiDependencies.invoker.services.model_manager.store
@@ -225,7 +261,10 @@ async def del_model_record(
     "/i/",
     operation_id="add_model_record",
     responses={
-        201: {"description": "The model added successfully"},
+        201: {
+            "description": "The model added successfully",
+            "content": {"application/json": {"example": example_model_output}},
+        },
         409: {"description": "There is already a model corresponding to this path or repo_id"},
         415: {"description": "Unrecognized file/folder format"},
     },
@@ -270,6 +309,7 @@ async def heuristic_import(
     config: Optional[Dict[str, Any]] = Body(
         description="Dict of fields that override auto-probed values in the model config record, such as name, description and prediction_type ",
         default=None,
+        example={"name": "modelT", "description": "antique cars"},
     ),
     access_token: Optional[str] = None,
 ) -> ModelInstallJob:
@@ -497,7 +537,10 @@ async def sync_models_to_config() -> Response:
     "/convert/{key}",
     operation_id="convert_model",
     responses={
-        200: {"description": "Model converted successfully"},
+        200: {
+            "description": "Model converted successfully",
+            "content": {"application/json": {"example": example_model_output}},
+        },
         400: {"description": "Bad request"},
         404: {"description": "Model not found"},
         409: {"description": "There is already a model registered at this location"},
@@ -571,6 +614,15 @@ async def convert_model(
 @model_manager_v2_router.put(
     "/merge",
     operation_id="merge",
+    responses={
+        200: {
+            "description": "Model converted successfully",
+            "content": {"application/json": {"example": example_model_output}},
+        },
+        400: {"description": "Bad request"},
+        404: {"description": "Model not found"},
+        409: {"description": "There is already a model registered at this location"},
+    },
 )
 async def merge(
     keys: List[str] = Body(description="Keys for two to three models to merge", min_length=2, max_length=3),
@@ -596,7 +648,6 @@ async def merge(
         interp: Interpolation method. One of "weighted_sum", "sigmoid", "inv_sigmoid" or "add_difference" [weighted_sum]
         merge_dest_directory: Specify a directory to store the merged model in [models directory]
     """
-    print(f"here i am, keys={keys}")
     logger = ApiDependencies.invoker.services.logger
     try:
         logger.info(f"Merging models: {keys} into {merge_dest_directory or '<MODELS>'}/{merged_model_name}")
diff --git a/invokeai/app/invocations/ip_adapter.py b/invokeai/app/invocations/ip_adapter.py
index f64b3266bb..01124f62f3 100644
--- a/invokeai/app/invocations/ip_adapter.py
+++ b/invokeai/app/invocations/ip_adapter.py
@@ -90,10 +90,10 @@ class IPAdapterInvocation(BaseInvocation):
 
     def invoke(self, context: InvocationContext) -> IPAdapterOutput:
         # Lookup the CLIP Vision encoder that is intended to be used with the IP-Adapter model.
-        ip_adapter_info = context.services.model_records.get_model(self.ip_adapter_model.key)
+        ip_adapter_info = context.services.model_manager.store.get_model(self.ip_adapter_model.key)
         image_encoder_model_id = ip_adapter_info.image_encoder_model_id
         image_encoder_model_name = image_encoder_model_id.split("/")[-1].strip()
-        image_encoder_models = context.services.model_records.search_by_attr(
+        image_encoder_models = context.services.model_manager.store.search_by_attr(
             model_name=image_encoder_model_name, base_model=BaseModelType.Any, model_type=ModelType.CLIPVision
         )
         assert len(image_encoder_models) == 1
diff --git a/invokeai/app/invocations/model.py b/invokeai/app/invocations/model.py
index fa6e8b98da..f78425c6ee 100644
--- a/invokeai/app/invocations/model.py
+++ b/invokeai/app/invocations/model.py
@@ -103,7 +103,7 @@ class MainModelLoaderInvocation(BaseInvocation):
         key = self.model.key
 
         # TODO: not found exceptions
-        if not context.services.model_records.exists(key):
+        if not context.services.model_manager.store.exists(key):
             raise Exception(f"Unknown model {key}")
 
         return ModelLoaderOutput(
@@ -172,7 +172,7 @@ class LoraLoaderInvocation(BaseInvocation):
 
         lora_key = self.lora.key
 
-        if not context.services.model_records.exists(lora_key):
+        if not context.services.model_manager.store.exists(lora_key):
             raise Exception(f"Unkown lora: {lora_key}!")
 
         if self.unet is not None and any(lora.key == lora_key for lora in self.unet.loras):
@@ -252,7 +252,7 @@ class SDXLLoraLoaderInvocation(BaseInvocation):
 
         lora_key = self.lora.key
 
-        if not context.services.model_records.exists(lora_key):
+        if not context.services.model_manager.store.exists(lora_key):
             raise Exception(f"Unknown lora: {lora_key}!")
 
         if self.unet is not None and any(lora.key == lora_key for lora in self.unet.loras):
@@ -318,7 +318,7 @@ class VaeLoaderInvocation(BaseInvocation):
     def invoke(self, context: InvocationContext) -> VAEOutput:
         key = self.vae_model.key
 
-        if not context.services.model_records.exists(key):
+        if not context.services.model_manager.store.exists(key):
             raise Exception(f"Unkown vae: {key}!")
 
         return VAEOutput(vae=VaeField(vae=ModelInfo(key=key)))
diff --git a/invokeai/app/services/config/config_base.py b/invokeai/app/services/config/config_base.py
index a304b38a95..983df6b468 100644
--- a/invokeai/app/services/config/config_base.py
+++ b/invokeai/app/services/config/config_base.py
@@ -27,11 +27,11 @@ class InvokeAISettings(BaseSettings):
     """Runtime configuration settings in which default values are read from an omegaconf .yaml file."""
 
     initconf: ClassVar[Optional[DictConfig]] = None
-    argparse_groups: ClassVar[Dict] = {}
+    argparse_groups: ClassVar[Dict[str, Any]] = {}
 
     model_config = SettingsConfigDict(env_file_encoding="utf-8", arbitrary_types_allowed=True, case_sensitive=True)
 
-    def parse_args(self, argv: Optional[list] = sys.argv[1:]):
+    def parse_args(self, argv: Optional[List[str]] = sys.argv[1:]) -> None:
         """Call to parse command-line arguments."""
         parser = self.get_parser()
         opt, unknown_opts = parser.parse_known_args(argv)
@@ -68,7 +68,7 @@ class InvokeAISettings(BaseSettings):
         return OmegaConf.to_yaml(conf)
 
     @classmethod
-    def add_parser_arguments(cls, parser):
+    def add_parser_arguments(cls, parser) -> None:
         """Dynamically create arguments for a settings parser."""
         if "type" in get_type_hints(cls):
             settings_stanza = get_args(get_type_hints(cls)["type"])[0]
@@ -117,7 +117,8 @@ class InvokeAISettings(BaseSettings):
         """Return the category of a setting."""
         hints = get_type_hints(cls)
         if command_field in hints:
-            return get_args(hints[command_field])[0]
+            result: str = get_args(hints[command_field])[0]
+            return result
         else:
             return "Uncategorized"
 
@@ -158,7 +159,7 @@ class InvokeAISettings(BaseSettings):
         ]
 
     @classmethod
-    def add_field_argument(cls, command_parser, name: str, field, default_override=None):
+    def add_field_argument(cls, command_parser, name: str, field, default_override=None) -> None:
         """Add the argparse arguments for a setting parser."""
         field_type = get_type_hints(cls).get(name)
         default = (
diff --git a/invokeai/app/services/config/config_common.py b/invokeai/app/services/config/config_common.py
index d11bcabcf9..27a0f859c2 100644
--- a/invokeai/app/services/config/config_common.py
+++ b/invokeai/app/services/config/config_common.py
@@ -21,7 +21,7 @@ class PagingArgumentParser(argparse.ArgumentParser):
     It also supports reading defaults from an init file.
     """
 
-    def print_help(self, file=None):
+    def print_help(self, file=None) -> None:
         text = self.format_help()
         pydoc.pager(text)
 
diff --git a/invokeai/app/services/download/download_default.py b/invokeai/app/services/download/download_default.py
index f740c50087..7008f8ed74 100644
--- a/invokeai/app/services/download/download_default.py
+++ b/invokeai/app/services/download/download_default.py
@@ -8,12 +8,12 @@ import time
 import traceback
 from pathlib import Path
 from queue import Empty, PriorityQueue
-from typing import Any, Dict, List, Optional
+from typing import Any, Dict, List, Optional, Set
 
 import requests
 from pydantic.networks import AnyHttpUrl
 from requests import HTTPError
-from tqdm import tqdm
+from tqdm import tqdm, std
 
 from invokeai.app.services.events.events_base import EventServiceBase
 from invokeai.app.util.misc import get_iso_timestamp
@@ -49,12 +49,12 @@ class DownloadQueueService(DownloadQueueServiceBase):
         :param max_parallel_dl: Number of simultaneous downloads allowed [5].
         :param requests_session: Optional requests.sessions.Session object, for unit tests.
         """
-        self._jobs = {}
+        self._jobs: Dict[int, DownloadJob] = {}
         self._next_job_id = 0
-        self._queue = PriorityQueue()
+        self._queue: PriorityQueue[DownloadJob] = PriorityQueue()
         self._stop_event = threading.Event()
         self._job_completed_event = threading.Event()
-        self._worker_pool = set()
+        self._worker_pool: Set[threading.Thread] = set()
         self._lock = threading.Lock()
         self._logger = InvokeAILogger.get_logger("DownloadQueueService")
         self._event_bus = event_bus
@@ -424,7 +424,7 @@ class DownloadQueueService(DownloadQueueServiceBase):
 class TqdmProgress(object):
     """TQDM-based progress bar object to use in on_progress handlers."""
 
-    _bars: Dict[int, tqdm]  # the tqdm object
+    _bars: Dict[int, tqdm]  # type: ignore
     _last: Dict[int, int]  # last bytes downloaded
 
     def __init__(self) -> None:  # noqa D107
diff --git a/invokeai/app/util/misc.py b/invokeai/app/util/misc.py
index 910b05d8dd..da431929db 100644
--- a/invokeai/app/util/misc.py
+++ b/invokeai/app/util/misc.py
@@ -5,7 +5,7 @@ import uuid
 import numpy as np
 
 
-def get_timestamp():
+def get_timestamp() -> int:
     return int(datetime.datetime.now(datetime.timezone.utc).timestamp())
 
 
@@ -20,16 +20,16 @@ def get_datetime_from_iso_timestamp(iso_timestamp: str) -> datetime.datetime:
 SEED_MAX = np.iinfo(np.uint32).max
 
 
-def get_random_seed():
+def get_random_seed() -> int:
     rng = np.random.default_rng(seed=None)
     return int(rng.integers(0, SEED_MAX))
 
 
-def uuid_string():
+def uuid_string() -> str:
     res = uuid.uuid4()
     return str(res)
 
 
-def is_optional(value: typing.Any):
+def is_optional(value: typing.Any) -> bool:
     """Checks if a value is typed as Optional. Note that Optional is sugar for Union[x, None]."""
     return typing.get_origin(value) is typing.Union and type(None) in typing.get_args(value)
diff --git a/invokeai/backend/model_manager/load/load_base.py b/invokeai/backend/model_manager/load/load_base.py
index 5f392ada75..7649dee762 100644
--- a/invokeai/backend/model_manager/load/load_base.py
+++ b/invokeai/backend/model_manager/load/load_base.py
@@ -22,6 +22,7 @@ from invokeai.backend.model_manager.config import (
     AnyModel,
     AnyModelConfig,
     BaseModelType,
+    ModelConfigBase,
     ModelFormat,
     ModelType,
     SubModelType,
@@ -70,7 +71,7 @@ class ModelLoaderBase(ABC):
         pass
 
     @abstractmethod
-    def load_model(self, model_config: AnyModelConfig, submodel_type: Optional[SubModelType] = None) -> LoadedModel:
+    def load_model(self, model_config: ModelConfigBase, submodel_type: Optional[SubModelType] = None) -> LoadedModel:
         """
         Return a model given its confguration.
 
@@ -122,7 +123,7 @@ class AnyModelLoader:
         """Return the convert cache associated used by the loaders."""
         return self._convert_cache
 
-    def load_model(self, model_config: AnyModelConfig, submodel_type: Optional[SubModelType] = None) -> LoadedModel:
+    def load_model(self, model_config: ModelConfigBase, submodel_type: Optional[SubModelType] = None) -> LoadedModel:
         """
         Return a model given its configuration.
 
@@ -144,8 +145,8 @@ class AnyModelLoader:
 
     @classmethod
     def get_implementation(
-        cls, config: AnyModelConfig, submodel_type: Optional[SubModelType]
-    ) -> Tuple[Type[ModelLoaderBase], AnyModelConfig, Optional[SubModelType]]:
+        cls, config: ModelConfigBase, submodel_type: Optional[SubModelType]
+    ) -> Tuple[Type[ModelLoaderBase], ModelConfigBase, Optional[SubModelType]]:
         """Get subclass of ModelLoaderBase registered to handle base and type."""
         # We have to handle VAE overrides here because this will change the model type and the corresponding implementation returned
         conf2, submodel_type = cls._handle_subtype_overrides(config, submodel_type)
@@ -161,8 +162,8 @@ class AnyModelLoader:
 
     @classmethod
     def _handle_subtype_overrides(
-        cls, config: AnyModelConfig, submodel_type: Optional[SubModelType]
-    ) -> Tuple[AnyModelConfig, Optional[SubModelType]]:
+        cls, config: ModelConfigBase, submodel_type: Optional[SubModelType]
+    ) -> Tuple[ModelConfigBase, Optional[SubModelType]]:
         if submodel_type == SubModelType.Vae and hasattr(config, "vae") and config.vae is not None:
             model_path = Path(config.vae)
             config_class = (
diff --git a/invokeai/backend/model_manager/load/model_cache/model_cache_default.py b/invokeai/backend/model_manager/load/model_cache/model_cache_default.py
index 98d6f34cea..786396062c 100644
--- a/invokeai/backend/model_manager/load/model_cache/model_cache_default.py
+++ b/invokeai/backend/model_manager/load/model_cache/model_cache_default.py
@@ -34,8 +34,8 @@ from invokeai.backend.model_manager.load.memory_snapshot import MemorySnapshot,
 from invokeai.backend.util.devices import choose_torch_device
 from invokeai.backend.util.logging import InvokeAILogger
 
-from .model_cache_base import CacheRecord, CacheStats, ModelCacheBase
-from .model_locker import ModelLocker, ModelLockerBase
+from .model_cache_base import CacheRecord, CacheStats, ModelCacheBase, ModelLockerBase
+from .model_locker import ModelLocker
 
 if choose_torch_device() == torch.device("mps"):
     from torch import mps
diff --git a/invokeai/backend/model_manager/metadata/fetch/fetch_base.py b/invokeai/backend/model_manager/metadata/fetch/fetch_base.py
index d628ab5c17..5d75493b92 100644
--- a/invokeai/backend/model_manager/metadata/fetch/fetch_base.py
+++ b/invokeai/backend/model_manager/metadata/fetch/fetch_base.py
@@ -20,7 +20,7 @@ from requests.sessions import Session
 
 from invokeai.backend.model_manager import ModelRepoVariant
 
-from ..metadata_base import AnyModelRepoMetadata, AnyModelRepoMetadataValidator
+from ..metadata_base import AnyModelRepoMetadata, AnyModelRepoMetadataValidator, BaseMetadata
 
 
 class ModelMetadataFetchBase(ABC):
@@ -62,5 +62,5 @@ class ModelMetadataFetchBase(ABC):
     @classmethod
     def from_json(cls, json: str) -> AnyModelRepoMetadata:
         """Given the JSON representation of the metadata, return the corresponding Pydantic object."""
-        metadata = AnyModelRepoMetadataValidator.validate_json(json)
+        metadata: BaseMetadata = AnyModelRepoMetadataValidator.validate_json(json)  # type: ignore
         return metadata
diff --git a/invokeai/backend/model_manager/probe.py b/invokeai/backend/model_manager/probe.py
index e7d21c578f..2c2066d7c5 100644
--- a/invokeai/backend/model_manager/probe.py
+++ b/invokeai/backend/model_manager/probe.py
@@ -166,7 +166,7 @@ class ModelProbe(object):
         fields["original_hash"] = fields.get("original_hash") or hash
         fields["current_hash"] = fields.get("current_hash") or hash
 
-        if format_type == ModelFormat.Diffusers:
+        if format_type == ModelFormat.Diffusers and hasattr(probe, "get_repo_variant"):
             fields["repo_variant"] = fields.get("repo_variant") or probe.get_repo_variant()
 
         # additional fields needed for main and controlnet models
diff --git a/invokeai/backend/model_manager/search.py b/invokeai/backend/model_manager/search.py
index f7e1e1bed7..0ead22b743 100644
--- a/invokeai/backend/model_manager/search.py
+++ b/invokeai/backend/model_manager/search.py
@@ -116,9 +116,9 @@ class ModelSearch(ModelSearchBase):
        # returns all models that have 'anime' in the path
     """
 
-    models_found: Set[Path] = Field(default=None)
-    scanned_dirs: Set[Path] = Field(default=None)
-    pruned_paths: Set[Path] = Field(default=None)
+    models_found: Optional[Set[Path]] = Field(default=None)
+    scanned_dirs: Optional[Set[Path]] = Field(default=None)
+    pruned_paths: Optional[Set[Path]] = Field(default=None)
 
     def search_started(self) -> None:
         self.models_found = set()

From b0835db47d25b7d563cc462dbcfcae317d623c3f Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lstein@gmail.com>
Date: Wed, 14 Feb 2024 11:10:50 -0500
Subject: [PATCH 125/411] improve swagger documentation

---
 invokeai/app/api/routers/model_manager_v2.py  | 216 ++++++++++++------
 .../app/services/download/download_default.py |   2 +-
 invokeai/backend/model_manager/config.py      |  16 +-
 3 files changed, 160 insertions(+), 74 deletions(-)

diff --git a/invokeai/app/api/routers/model_manager_v2.py b/invokeai/app/api/routers/model_manager_v2.py
index 029c620707..2471e0d8c9 100644
--- a/invokeai/app/api/routers/model_manager_v2.py
+++ b/invokeai/app/api/routers/model_manager_v2.py
@@ -9,7 +9,7 @@ from typing import Any, Dict, List, Optional, Set
 
 from fastapi import Body, Path, Query, Response
 from fastapi.routing import APIRouter
-from pydantic import BaseModel, ConfigDict, Field
+from pydantic import BaseModel, ConfigDict
 from starlette.exceptions import HTTPException
 from typing_extensions import Annotated
 
@@ -37,35 +37,6 @@ from ..dependencies import ApiDependencies
 
 model_manager_v2_router = APIRouter(prefix="/v2/models", tags=["model_manager_v2"])
 
-example_model_output = {
-    "path": "sd-1/main/openjourney",
-    "name": "openjourney",
-    "base": "sd-1",
-    "type": "main",
-    "format": "diffusers",
-    "key": "3a0e45ff858926fd4a63da630688b1e1",
-    "original_hash": "1c12f18fb6e403baef26fb9d720fbd2f",
-    "current_hash": "1c12f18fb6e403baef26fb9d720fbd2f",
-    "description": "sd-1 main model openjourney",
-    "source": "/opt/invokeai/models/sd-1/main/openjourney",
-    "last_modified": 1707794711,
-    "vae": "/opt/invokeai/models/sd-1/vae/vae-ft-mse-840000-ema-pruned_fp16.safetensors",
-    "variant": "normal",
-    "prediction_type": "epsilon",
-    "repo_variant": "fp16",
-}
-
-example_model_input = {
-    "path": "base/type/name",
-    "name": "model_name",
-    "base": "sd-1",
-    "type": "main",
-    "format": "diffusers",
-    "description": "Model description",
-    "vae": None,
-    "variant": "normal",
-}
-
 
 class ModelsList(BaseModel):
     """Return list of configs."""
@@ -84,6 +55,86 @@ class ModelTagSet(BaseModel):
     tags: Set[str]
 
 
+##############################################################################
+# These are example inputs and outputs that are used in places where Swagger
+# is unable to generate a correct example.
+##############################################################################
+example_model_config = {
+    "path": "string",
+    "name": "string",
+    "base": "sd-1",
+    "type": "main",
+    "format": "checkpoint",
+    "config": "string",
+    "key": "string",
+    "original_hash": "string",
+    "current_hash": "string",
+    "description": "string",
+    "source": "string",
+    "last_modified": 0,
+    "vae": "string",
+    "variant": "normal",
+    "prediction_type": "epsilon",
+    "repo_variant": "fp16",
+    "upcast_attention": False,
+    "ztsnr_training": False,
+}
+
+example_model_input = {
+    "path": "/path/to/model",
+    "name": "model_name",
+    "base": "sd-1",
+    "type": "main",
+    "format": "checkpoint",
+    "config": "configs/stable-diffusion/v1-inference.yaml",
+    "description": "Model description",
+    "vae": None,
+    "variant": "normal",
+}
+
+example_model_metadata = {
+    "name": "ip_adapter_sd_image_encoder",
+    "author": "InvokeAI",
+    "tags": [
+        "transformers",
+        "safetensors",
+        "clip_vision_model",
+        "endpoints_compatible",
+        "region:us",
+        "has_space",
+        "license:apache-2.0",
+    ],
+    "files": [
+        {
+            "url": "https://huggingface.co/InvokeAI/ip_adapter_sd_image_encoder/resolve/main/README.md",
+            "path": "ip_adapter_sd_image_encoder/README.md",
+            "size": 628,
+            "sha256": None,
+        },
+        {
+            "url": "https://huggingface.co/InvokeAI/ip_adapter_sd_image_encoder/resolve/main/config.json",
+            "path": "ip_adapter_sd_image_encoder/config.json",
+            "size": 560,
+            "sha256": None,
+        },
+        {
+            "url": "https://huggingface.co/InvokeAI/ip_adapter_sd_image_encoder/resolve/main/model.safetensors",
+            "path": "ip_adapter_sd_image_encoder/model.safetensors",
+            "size": 2528373448,
+            "sha256": "6ca9667da1ca9e0b0f75e46bb030f7e011f44f86cbfb8d5a36590fcd7507b030",
+        },
+    ],
+    "type": "huggingface",
+    "id": "InvokeAI/ip_adapter_sd_image_encoder",
+    "tag_dict": {"license": "apache-2.0"},
+    "last_modified": "2023-09-23T17:33:25Z",
+}
+
+##############################################################################
+# ROUTES
+##############################################################################
+
+
 @model_manager_v2_router.get(
     "/",
     operation_id="list_model_records",
@@ -119,7 +170,7 @@ async def list_model_records(
     responses={
         200: {
             "description": "The model configuration was retrieved successfully",
-            "content": {"application/json": {"example": example_model_output}},
+            "content": {"application/json": {"example": example_model_config}},
         },
         400: {"description": "Bad request"},
         404: {"description": "The model could not be found"},
@@ -137,7 +188,7 @@ async def get_model_record(
         raise HTTPException(status_code=404, detail=str(e))
 
 
-@model_manager_v2_router.get("/meta", operation_id="list_model_summary")
+@model_manager_v2_router.get("/summary", operation_id="list_model_summary")
 async def list_model_summary(
     page: int = Query(default=0, description="The page to get"),
     per_page: int = Query(default=10, description="The number of models per page"),
@@ -153,7 +204,10 @@ async def list_model_summary(
     "/meta/i/{key}",
     operation_id="get_model_metadata",
     responses={
-        200: {"description": "Success"},
+        200: {
+            "description": "The model metadata was retrieved successfully",
+            "content": {"application/json": {"example": example_model_metadata}},
+        },
         400: {"description": "Bad request"},
         404: {"description": "No metadata available"},
     },
@@ -199,7 +253,7 @@ async def search_by_metadata_tags(
     responses={
         200: {
             "description": "The model was updated successfully",
-            "content": {"application/json": {"example": example_model_output}},
+            "content": {"application/json": {"example": example_model_config}},
         },
         400: {"description": "Bad request"},
         404: {"description": "The model could not be found"},
@@ -212,7 +266,7 @@ async def update_model_record(
     info: Annotated[
         AnyModelConfig, Body(description="Model config", discriminator="type", example=example_model_input)
     ],
-) -> Annotated[AnyModelConfig, Field(example="this is neat")]:
+) -> AnyModelConfig:
     """Update model contents with a new config. If the model name or base fields are changed, then the model is renamed."""
     logger = ApiDependencies.invoker.services.logger
     record_store = ApiDependencies.invoker.services.model_manager.store
@@ -263,7 +317,7 @@ async def del_model_record(
     responses={
         201: {
             "description": "The model added successfully",
-            "content": {"application/json": {"example": example_model_output}},
+            "content": {"application/json": {"example": example_model_config}},
         },
         409: {"description": "There is already a model corresponding to this path or repo_id"},
         415: {"description": "Unrecognized file/folder format"},
@@ -271,7 +325,9 @@ async def del_model_record(
     status_code=201,
 )
 async def add_model_record(
-    config: Annotated[AnyModelConfig, Body(description="Model config", discriminator="type")],
+    config: Annotated[
+        AnyModelConfig, Body(description="Model config", discriminator="type", example=example_model_input)
+    ],
 ) -> AnyModelConfig:
     """Add a model using the configuration information appropriate for its type."""
     logger = ApiDependencies.invoker.services.logger
@@ -389,32 +445,38 @@ async def import_model(
     appropriate value:
 
     * To install a local path using LocalModelSource, pass a source of form:
-      `{
+      ```
+      {
         "type": "local",
         "path": "/path/to/model",
         "inplace": false
-      }`
-       The "inplace" flag, if true, will register the model in place in its
-       current filesystem location. Otherwise, the model will be copied
-       into the InvokeAI models directory.
+      }
+      ```
+      The "inplace" flag, if true, will register the model in place in its
+      current filesystem location. Otherwise, the model will be copied
+      into the InvokeAI models directory.
 
     * To install a HuggingFace repo_id using HFModelSource, pass a source of form:
-      `{
+      ```
+      {
         "type": "hf",
         "repo_id": "stabilityai/stable-diffusion-2.0",
         "variant": "fp16",
         "subfolder": "vae",
         "access_token": "f5820a918aaf01"
-      }`
-     The `variant`, `subfolder` and `access_token` fields are optional.
+      }
+      ```
+      The `variant`, `subfolder` and `access_token` fields are optional.
 
     * To install a remote model using an arbitrary URL, pass:
-      `{
+      ```
+      {
         "type": "url",
         "url": "http://www.civitai.com/models/123456",
         "access_token": "f5820a918aaf01"
-      }`
-    The `access_token` field is optonal
+      }
+      ```
+      The `access_token` field is optonal
 
     The model's configuration record will be probed and filled in
     automatically.  To override the default guesses, pass "metadata"
@@ -423,9 +485,9 @@ async def import_model(
     Installation occurs in the background. Either use list_model_install_jobs()
     to poll for completion, or listen on the event bus for the following events:
 
-      "model_install_running"
-      "model_install_completed"
-      "model_install_error"
+      * "model_install_running"
+      * "model_install_completed"
+      * "model_install_error"
 
     On successful completion, the event's payload will contain the field "key"
     containing the installed ID of the model. On an error, the event's payload
@@ -459,7 +521,25 @@ async def import_model(
     operation_id="list_model_install_jobs",
 )
 async def list_model_install_jobs() -> List[ModelInstallJob]:
-    """Return list of model install jobs."""
+    """Return the list of model install jobs.
+
+    Install jobs have a numeric `id`, a `status`, and other fields that provide information on
+    the nature of the job and its progress. The `status` is one of:
+
+    * "waiting" -- Job is waiting in the queue to run
+    * "downloading" -- Model file(s) are downloading
+    * "running" -- Model has downloaded and the model probing and registration process is running
+    * "completed" -- Installation completed successfully
+    * "error" -- An error occurred. Details will be in the "error_type" and "error" fields.
+    * "cancelled" -- Job was cancelled before completion.
+
+    Once completed, information about the model such as its size, base
+    model, type, and metadata can be retrieved from the `config_out`
+    field. For multi-file models such as diffusers, information on individual files
+    can be retrieved from `download_parts`.
+
+    See the example and schema below for more information.
+    """
     jobs: List[ModelInstallJob] = ApiDependencies.invoker.services.model_manager.install.list_jobs()
     return jobs
 
@@ -473,7 +553,10 @@ async def list_model_install_jobs() -> List[ModelInstallJob]:
     },
 )
 async def get_model_install_job(id: int = Path(description="Model install id")) -> ModelInstallJob:
-    """Return model install job corresponding to the given source."""
+    """
+    Return model install job corresponding to the given source. See the documentation for 'List Model Install Jobs'
+    for information on the format of the return value.
+    """
     try:
         result: ModelInstallJob = ApiDependencies.invoker.services.model_manager.install.get_job_by_id(id)
         return result
@@ -539,7 +622,7 @@ async def sync_models_to_config() -> Response:
     responses={
         200: {
             "description": "Model converted successfully",
-            "content": {"application/json": {"example": example_model_output}},
+            "content": {"application/json": {"example": example_model_config}},
         },
         400: {"description": "Bad request"},
         404: {"description": "Model not found"},
@@ -551,8 +634,8 @@ async def convert_model(
 ) -> AnyModelConfig:
     """
     Permanently convert a model into diffusers format, replacing the safetensors version.
-    Note that the key and model hash will change. Use the model configuration record returned
-    by this call to get the new values.
+    Note that during the conversion process the key and model hash will change.
+    The return value is the model configuration for the converted model.
     """
     logger = ApiDependencies.invoker.services.logger
     loader = ApiDependencies.invoker.services.model_manager.load
@@ -617,7 +700,7 @@ async def convert_model(
     responses={
         200: {
             "description": "Model converted successfully",
-            "content": {"application/json": {"example": example_model_output}},
+            "content": {"application/json": {"example": example_model_config}},
         },
         400: {"description": "Bad request"},
         404: {"description": "Model not found"},
@@ -639,14 +722,17 @@ async def merge(
     ),
 ) -> AnyModelConfig:
     """
-    Merge diffusers models.
-
-        keys: List of 2-3 model keys to merge together. All models must use the same base type.
-        merged_model_name: Name for the merged model [Concat model names]
-        alpha: Alpha value (0.0-1.0). Higher values give more weight to the second model [0.5]
-        force: If true, force the merge even if the models were generated by different versions of the diffusers library [False]
-        interp: Interpolation method. One of "weighted_sum", "sigmoid", "inv_sigmoid" or "add_difference" [weighted_sum]
-        merge_dest_directory: Specify a directory to store the merged model in [models directory]
+    Merge diffusers models. The process is controlled by a set parameters provided in the body of the request.
+    ```
+    Argument                Description [default]
+    --------               ----------------------
+    keys                   List of 2-3 model keys to merge together. All models must use the same base type.
+    merged_model_name      Name for the merged model [Concat model names]
+    alpha                  Alpha value (0.0-1.0). Higher values give more weight to the second model [0.5]
+    force                  If true, force the merge even if the models were generated by different versions of the diffusers library [False]
+    interp                 Interpolation method. One of "weighted_sum", "sigmoid", "inv_sigmoid" or "add_difference" [weighted_sum]
+    merge_dest_directory   Specify a directory to store the merged model in [models directory]
+    ```
     """
     logger = ApiDependencies.invoker.services.logger
     try:
diff --git a/invokeai/app/services/download/download_default.py b/invokeai/app/services/download/download_default.py
index 7008f8ed74..6d5cedbcad 100644
--- a/invokeai/app/services/download/download_default.py
+++ b/invokeai/app/services/download/download_default.py
@@ -13,7 +13,7 @@ from typing import Any, Dict, List, Optional, Set
 import requests
 from pydantic.networks import AnyHttpUrl
 from requests import HTTPError
-from tqdm import tqdm, std
+from tqdm import tqdm
 
 from invokeai.app.services.events.events_base import EventServiceBase
 from invokeai.app.util.misc import get_iso_timestamp
diff --git a/invokeai/backend/model_manager/config.py b/invokeai/backend/model_manager/config.py
index 9f0f774b49..42921f0b32 100644
--- a/invokeai/backend/model_manager/config.py
+++ b/invokeai/backend/model_manager/config.py
@@ -123,11 +123,11 @@ class ModelRepoVariant(str, Enum):
 class ModelConfigBase(BaseModel):
     """Base class for model configuration information."""
 
-    path: str
-    name: str
-    base: BaseModelType
-    type: ModelType
-    format: ModelFormat
+    path: str = Field(description="filesystem path to the model file or directory")
+    name: str = Field(description="model name")
+    base: BaseModelType = Field(description="base model")
+    type: ModelType = Field(description="type of the model")
+    format: ModelFormat = Field(description="model format")
     key: str = Field(description="unique key for model", default="<NOKEY>")
     original_hash: Optional[str] = Field(
         description="original fasthash of model contents", default=None
@@ -135,9 +135,9 @@ class ModelConfigBase(BaseModel):
     current_hash: Optional[str] = Field(
         description="current fasthash of model contents", default=None
     )  # if model is converted or otherwise modified, this will hold updated hash
-    description: Optional[str] = Field(default=None)
-    source: Optional[str] = Field(description="Model download source (URL or repo_id)", default=None)
-    last_modified: Optional[float] = Field(description="Timestamp for modification time", default_factory=time.time)
+    description: Optional[str] = Field(description="human readable description of the model", default=None)
+    source: Optional[str] = Field(description="model original source (path, URL or repo_id)", default=None)
+    last_modified: Optional[float] = Field(description="timestamp for modification time", default_factory=time.time)
 
     model_config = ConfigDict(
         use_enum_values=False,

From 35e8a33dfd4bdf374f1db526484ad8801203b642 Mon Sep 17 00:00:00 2001
From: Brandon Rising <brandon@invoke.ai>
Date: Wed, 14 Feb 2024 09:36:30 -0500
Subject: [PATCH 126/411] Remove references to model_records service, change
 submodel property on ModelInfo to submodel_type to support new params in
 model manager

---
 docs/contributing/MODEL_MANAGER.md            |  2 +-
 invokeai/app/invocations/latent.py            |  2 +-
 invokeai/app/invocations/model.py             | 22 +++++++--------
 invokeai/app/invocations/sdxl.py              | 28 +++++++++----------
 .../backend/model_management/model_manager.py |  2 +-
 pyproject.toml                                |  2 +-
 6 files changed, 29 insertions(+), 29 deletions(-)

diff --git a/docs/contributing/MODEL_MANAGER.md b/docs/contributing/MODEL_MANAGER.md
index b711c654de..b19699de73 100644
--- a/docs/contributing/MODEL_MANAGER.md
+++ b/docs/contributing/MODEL_MANAGER.md
@@ -1627,7 +1627,7 @@ payload=dict(
 	queue_batch_id=queue_batch_id,
 	graph_execution_state_id=graph_execution_state_id,
 	model_key=model_key,
-	submodel=submodel,
+	submodel_type=submodel,
 	hash=model_info.hash,
 	location=str(model_info.location),
 	precision=str(model_info.precision),
diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py
index 289da2dd73..c3de521940 100644
--- a/invokeai/app/invocations/latent.py
+++ b/invokeai/app/invocations/latent.py
@@ -812,7 +812,7 @@ class LatentsToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
         )
 
         with set_seamless(vae_info.model, self.vae.seamless_axes), vae_info as vae:
-            assert isinstance(vae, torch.Tensor)
+            assert isinstance(vae, torch.nn.Module)
             latents = latents.to(vae.device)
             if self.fp32:
                 vae.to(dtype=torch.float32)
diff --git a/invokeai/app/invocations/model.py b/invokeai/app/invocations/model.py
index f78425c6ee..71a71a63c8 100644
--- a/invokeai/app/invocations/model.py
+++ b/invokeai/app/invocations/model.py
@@ -18,7 +18,7 @@ from .baseinvocation import (
 
 class ModelInfo(BaseModel):
     key: str = Field(description="Key of model as returned by ModelRecordServiceBase.get_model()")
-    submodel: Optional[SubModelType] = Field(default=None, description="Info to load submodel")
+    submodel_type: Optional[SubModelType] = Field(default=None, description="Info to load submodel")
 
 
 class LoraInfo(ModelInfo):
@@ -110,22 +110,22 @@ class MainModelLoaderInvocation(BaseInvocation):
             unet=UNetField(
                 unet=ModelInfo(
                     key=key,
-                    submodel=SubModelType.UNet,
+                    submodel_type=SubModelType.UNet,
                 ),
                 scheduler=ModelInfo(
                     key=key,
-                    submodel=SubModelType.Scheduler,
+                    submodel_type=SubModelType.Scheduler,
                 ),
                 loras=[],
             ),
             clip=ClipField(
                 tokenizer=ModelInfo(
                     key=key,
-                    submodel=SubModelType.Tokenizer,
+                    submodel_type=SubModelType.Tokenizer,
                 ),
                 text_encoder=ModelInfo(
                     key=key,
-                    submodel=SubModelType.TextEncoder,
+                    submodel_type=SubModelType.TextEncoder,
                 ),
                 loras=[],
                 skipped_layers=0,
@@ -133,7 +133,7 @@ class MainModelLoaderInvocation(BaseInvocation):
             vae=VaeField(
                 vae=ModelInfo(
                     key=key,
-                    submodel=SubModelType.Vae,
+                    submodel_type=SubModelType.Vae,
                 ),
             ),
         )
@@ -188,7 +188,7 @@ class LoraLoaderInvocation(BaseInvocation):
             output.unet.loras.append(
                 LoraInfo(
                     key=lora_key,
-                    submodel=None,
+                    submodel_type=None,
                     weight=self.weight,
                 )
             )
@@ -198,7 +198,7 @@ class LoraLoaderInvocation(BaseInvocation):
             output.clip.loras.append(
                 LoraInfo(
                     key=lora_key,
-                    submodel=None,
+                    submodel_type=None,
                     weight=self.weight,
                 )
             )
@@ -271,7 +271,7 @@ class SDXLLoraLoaderInvocation(BaseInvocation):
             output.unet.loras.append(
                 LoraInfo(
                     key=lora_key,
-                    submodel=None,
+                    submodel_type=None,
                     weight=self.weight,
                 )
             )
@@ -281,7 +281,7 @@ class SDXLLoraLoaderInvocation(BaseInvocation):
             output.clip.loras.append(
                 LoraInfo(
                     key=lora_key,
-                    submodel=None,
+                    submodel_type=None,
                     weight=self.weight,
                 )
             )
@@ -291,7 +291,7 @@ class SDXLLoraLoaderInvocation(BaseInvocation):
             output.clip2.loras.append(
                 LoraInfo(
                     key=lora_key,
-                    submodel=None,
+                    submodel_type=None,
                     weight=self.weight,
                 )
             )
diff --git a/invokeai/app/invocations/sdxl.py b/invokeai/app/invocations/sdxl.py
index 633a6477fd..85e6fb787f 100644
--- a/invokeai/app/invocations/sdxl.py
+++ b/invokeai/app/invocations/sdxl.py
@@ -43,29 +43,29 @@ class SDXLModelLoaderInvocation(BaseInvocation):
         model_key = self.model.key
 
         # TODO: not found exceptions
-        if not context.services.model_records.exists(model_key):
+        if not context.services.model_manager.store.exists(model_key):
             raise Exception(f"Unknown model: {model_key}")
 
         return SDXLModelLoaderOutput(
             unet=UNetField(
                 unet=ModelInfo(
                     key=model_key,
-                    submodel=SubModelType.UNet,
+                    submodel_type=SubModelType.UNet,
                 ),
                 scheduler=ModelInfo(
                     key=model_key,
-                    submodel=SubModelType.Scheduler,
+                    submodel_type=SubModelType.Scheduler,
                 ),
                 loras=[],
             ),
             clip=ClipField(
                 tokenizer=ModelInfo(
                     key=model_key,
-                    submodel=SubModelType.Tokenizer,
+                    submodel_type=SubModelType.Tokenizer,
                 ),
                 text_encoder=ModelInfo(
                     key=model_key,
-                    submodel=SubModelType.TextEncoder,
+                    submodel_type=SubModelType.TextEncoder,
                 ),
                 loras=[],
                 skipped_layers=0,
@@ -73,11 +73,11 @@ class SDXLModelLoaderInvocation(BaseInvocation):
             clip2=ClipField(
                 tokenizer=ModelInfo(
                     key=model_key,
-                    submodel=SubModelType.Tokenizer2,
+                    submodel_type=SubModelType.Tokenizer2,
                 ),
                 text_encoder=ModelInfo(
                     key=model_key,
-                    submodel=SubModelType.TextEncoder2,
+                    submodel_type=SubModelType.TextEncoder2,
                 ),
                 loras=[],
                 skipped_layers=0,
@@ -85,7 +85,7 @@ class SDXLModelLoaderInvocation(BaseInvocation):
             vae=VaeField(
                 vae=ModelInfo(
                     key=model_key,
-                    submodel=SubModelType.Vae,
+                    submodel_type=SubModelType.Vae,
                 ),
             ),
         )
@@ -112,29 +112,29 @@ class SDXLRefinerModelLoaderInvocation(BaseInvocation):
         model_key = self.model.key
 
         # TODO: not found exceptions
-        if not context.services.model_records.exists(model_key):
+        if not context.services.model_manager.store.exists(model_key):
             raise Exception(f"Unknown model: {model_key}")
 
         return SDXLRefinerModelLoaderOutput(
             unet=UNetField(
                 unet=ModelInfo(
                     key=model_key,
-                    submodel=SubModelType.UNet,
+                    submodel_type=SubModelType.UNet,
                 ),
                 scheduler=ModelInfo(
                     key=model_key,
-                    submodel=SubModelType.Scheduler,
+                    submodel_type=SubModelType.Scheduler,
                 ),
                 loras=[],
             ),
             clip2=ClipField(
                 tokenizer=ModelInfo(
                     key=model_key,
-                    submodel=SubModelType.Tokenizer2,
+                    submodel_type=SubModelType.Tokenizer2,
                 ),
                 text_encoder=ModelInfo(
                     key=model_key,
-                    submodel=SubModelType.TextEncoder2,
+                    submodel_type=SubModelType.TextEncoder2,
                 ),
                 loras=[],
                 skipped_layers=0,
@@ -142,7 +142,7 @@ class SDXLRefinerModelLoaderInvocation(BaseInvocation):
             vae=VaeField(
                 vae=ModelInfo(
                     key=model_key,
-                    submodel=SubModelType.Vae,
+                    submodel_type=SubModelType.Vae,
                 ),
             ),
         )
diff --git a/invokeai/backend/model_management/model_manager.py b/invokeai/backend/model_management/model_manager.py
index da74ca3fb5..84d93f15fa 100644
--- a/invokeai/backend/model_management/model_manager.py
+++ b/invokeai/backend/model_management/model_manager.py
@@ -499,7 +499,7 @@ class ModelManager(object):
             model_class=model_class,
             base_model=base_model,
             model_type=model_type,
-            submodel=submodel_type,
+            submodel_type=submodel_type,
         )
 
         if model_key not in self.cache_keys:
diff --git a/pyproject.toml b/pyproject.toml
index 2958e3629a..f57607bc0a 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -245,7 +245,7 @@ module = [
   "invokeai.app.services.invocation_stats.invocation_stats_default",
   "invokeai.app.services.model_manager.model_manager_base",
   "invokeai.app.services.model_manager.model_manager_default",
-  "invokeai.app.services.model_records.model_records_sql",
+  "invokeai.app.services.model_manager.store.model_records_sql",
   "invokeai.app.util.controlnet_utils",
   "invokeai.backend.image_util.txt2mask",
   "invokeai.backend.image_util.safety_checker",

From 262cbaacdd36a50681bb6bc8f4541dac4911e6c5 Mon Sep 17 00:00:00 2001
From: Brandon Rising <brandon@invoke.ai>
Date: Wed, 14 Feb 2024 09:51:11 -0500
Subject: [PATCH 127/411] References to
 context.services.model_manager.store.get_model can only accept keys, remove
 invalid assertion

---
 invokeai/app/invocations/latent.py            |  4 ++--
 .../load/model_cache/model_cache_default.py   | 22 +++++++++----------
 2 files changed, 13 insertions(+), 13 deletions(-)

diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py
index c3de521940..05293fdfee 100644
--- a/invokeai/app/invocations/latent.py
+++ b/invokeai/app/invocations/latent.py
@@ -681,7 +681,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
             source_node_id = graph_execution_state.prepared_source_mapping[self.id]
 
             # get the unet's config so that we can pass the base to dispatch_progress()
-            unet_config = context.services.model_manager.store.get_model(**self.unet.unet.model_dump())
+            unet_config = context.services.model_manager.store.get_model(self.unet.unet.key)
 
             def step_callback(state: PipelineIntermediateState) -> None:
                 self.dispatch_progress(context, source_node_id, state, unet_config.base)
@@ -709,7 +709,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
                 # Apply the LoRA after unet has been moved to its target device for faster patching.
                 ModelPatcher.apply_lora_unet(unet, _lora_loader()),
             ):
-                assert isinstance(unet, torch.Tensor)
+                assert isinstance(unet, UNet2DConditionModel)
                 latents = latents.to(device=unet.device, dtype=unet.dtype)
                 if noise is not None:
                     noise = noise.to(device=unet.device, dtype=unet.dtype)
diff --git a/invokeai/backend/model_manager/load/model_cache/model_cache_default.py b/invokeai/backend/model_manager/load/model_cache/model_cache_default.py
index 786396062c..02ce1266c7 100644
--- a/invokeai/backend/model_manager/load/model_cache/model_cache_default.py
+++ b/invokeai/backend/model_manager/load/model_cache/model_cache_default.py
@@ -303,18 +303,18 @@ class ModelCache(ModelCacheBase[AnyModel]):
         in_vram_models = 0
         locked_in_vram_models = 0
         for cache_record in self._cached_models.values():
-            assert hasattr(cache_record.model, "device")
-            if cache_record.model.device == self.storage_device:
-                in_ram_models += 1
-            else:
-                in_vram_models += 1
-            if cache_record.locked:
-                locked_in_vram_models += 1
+            if hasattr(cache_record.model, "device"):
+                if cache_record.model.device == self.storage_device:
+                    in_ram_models += 1
+                else:
+                    in_vram_models += 1
+                if cache_record.locked:
+                    locked_in_vram_models += 1
 
-        self.logger.debug(
-            f"Current VRAM/RAM usage: {vram}/{ram}; models_in_ram/models_in_vram(locked) ="
-            f" {in_ram_models}/{in_vram_models}({locked_in_vram_models})"
-        )
+                self.logger.debug(
+                    f"Current VRAM/RAM usage: {vram}/{ram}; models_in_ram/models_in_vram(locked) ="
+                    f" {in_ram_models}/{in_vram_models}({locked_in_vram_models})"
+                )
 
     def make_room(self, model_size: int) -> None:
         """Make enough room in the cache to accommodate a new model of indicated size."""

From 4c6e34b216e442e2f3a3582fa576fbb0c8904e31 Mon Sep 17 00:00:00 2001
From: Brandon Rising <brandon@invoke.ai>
Date: Wed, 14 Feb 2024 13:07:11 -0500
Subject: [PATCH 128/411] Update _get_hf_load_class to support clipvision
 models

---
 invokeai/backend/model_manager/load/load_default.py | 8 ++++++--
 1 file changed, 6 insertions(+), 2 deletions(-)

diff --git a/invokeai/backend/model_manager/load/load_default.py b/invokeai/backend/model_manager/load/load_default.py
index df83c8320d..9ed0ccb2d3 100644
--- a/invokeai/backend/model_manager/load/load_default.py
+++ b/invokeai/backend/model_manager/load/load_default.py
@@ -163,8 +163,12 @@ class ModelLoader(ModelLoaderBase):
         else:
             try:
                 config = self._load_diffusers_config(model_path, config_name="config.json")
-                class_name = config["_class_name"]
-                return self._hf_definition_to_type(module="diffusers", class_name=class_name)
+                class_name = config.get("_class_name", None)
+                if class_name:
+                    return self._hf_definition_to_type(module="diffusers", class_name=class_name)
+                if config.get("model_type", None) == "clip_vision_model":
+                    class_name = config.get("architectures")[0]
+                    return self._hf_definition_to_type(module="transformers", class_name=class_name)
             except KeyError as e:
                 raise InvalidModelConfigException("An expected config.json file is missing from this model.") from e
 

From 88d6de4101ad7ddbaa0a52e0b8ea5096dffa0d6f Mon Sep 17 00:00:00 2001
From: Brandon Rising <brandon@invoke.ai>
Date: Wed, 14 Feb 2024 13:16:15 -0500
Subject: [PATCH 129/411] Raise InvalidModelConfigException when unable to
 detect load class in ModelLoader

---
 invokeai/backend/model_manager/load/load_default.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/invokeai/backend/model_manager/load/load_default.py b/invokeai/backend/model_manager/load/load_default.py
index 9ed0ccb2d3..1dac121a30 100644
--- a/invokeai/backend/model_manager/load/load_default.py
+++ b/invokeai/backend/model_manager/load/load_default.py
@@ -169,6 +169,8 @@ class ModelLoader(ModelLoaderBase):
                 if config.get("model_type", None) == "clip_vision_model":
                     class_name = config.get("architectures")[0]
                     return self._hf_definition_to_type(module="transformers", class_name=class_name)
+                if not class_name:
+                    raise InvalidModelConfigException("Unable to decifer Load Class based on given config.json")
             except KeyError as e:
                 raise InvalidModelConfigException("An expected config.json file is missing from this model.") from e
 

From 539570cc7a3cc486055ef61d3a279344dd81b978 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Thu, 15 Feb 2024 20:43:41 +1100
Subject: [PATCH 130/411] feat(nodes): update invocation context for mm2,
 update nodes model usage

---
 invokeai/app/invocations/compel.py            | 40 ++------
 invokeai/app/invocations/ip_adapter.py        |  7 +-
 invokeai/app/invocations/latent.py            | 71 +++-----------
 invokeai/app/invocations/model.py             |  8 +-
 invokeai/app/invocations/sdxl.py              |  4 +-
 .../services/model_load/model_load_base.py    | 14 +--
 .../services/model_load/model_load_default.py | 48 +++++-----
 .../app/services/shared/invocation_context.py | 94 ++++++++++++++-----
 invokeai/app/util/step_callback.py            |  2 +-
 9 files changed, 141 insertions(+), 147 deletions(-)

diff --git a/invokeai/app/invocations/compel.py b/invokeai/app/invocations/compel.py
index 3850fb6cc3..5159d5b89c 100644
--- a/invokeai/app/invocations/compel.py
+++ b/invokeai/app/invocations/compel.py
@@ -69,20 +69,12 @@ class CompelInvocation(BaseInvocation):
 
     @torch.no_grad()
     def invoke(self, context: InvocationContext) -> ConditioningOutput:
-        tokenizer_info = context.services.model_manager.load.load_model_by_key(
-            **self.clip.tokenizer.model_dump(),
-            context=context,
-        )
-        text_encoder_info = context.services.model_manager.load.load_model_by_key(
-            **self.clip.text_encoder.model_dump(),
-            context=context,
-        )
+        tokenizer_info = context.models.load(**self.clip.tokenizer.model_dump())
+        text_encoder_info = context.models.load(**self.clip.text_encoder.model_dump())
 
         def _lora_loader() -> Iterator[Tuple[LoRAModelRaw, float]]:
             for lora in self.clip.loras:
-                lora_info = context.services.model_manager.load.load_model_by_key(
-                    **lora.model_dump(exclude={"weight"}), context=context
-                )
+                lora_info = context.models.load(**lora.model_dump(exclude={"weight"}))
                 assert isinstance(lora_info.model, LoRAModelRaw)
                 yield (lora_info.model, lora.weight)
                 del lora_info
@@ -94,10 +86,7 @@ class CompelInvocation(BaseInvocation):
         for trigger in extract_ti_triggers_from_prompt(self.prompt):
             name = trigger[1:-1]
             try:
-                loaded_model = context.services.model_manager.load.load_model_by_key(
-                    **self.clip.text_encoder.model_dump(),
-                    context=context,
-                ).model
+                loaded_model = context.models.load(**self.clip.text_encoder.model_dump()).model
                 assert isinstance(loaded_model, TextualInversionModelRaw)
                 ti_list.append((name, loaded_model))
             except UnknownModelException:
@@ -165,14 +154,8 @@ class SDXLPromptInvocationBase:
         lora_prefix: str,
         zero_on_empty: bool,
     ) -> Tuple[torch.Tensor, Optional[torch.Tensor], Optional[ExtraConditioningInfo]]:
-        tokenizer_info = context.services.model_manager.load.load_model_by_key(
-            **clip_field.tokenizer.model_dump(),
-            context=context,
-        )
-        text_encoder_info = context.services.model_manager.load.load_model_by_key(
-            **clip_field.text_encoder.model_dump(),
-            context=context,
-        )
+        tokenizer_info = context.models.load(**clip_field.tokenizer.model_dump())
+        text_encoder_info = context.models.load(**clip_field.text_encoder.model_dump())
 
         # return zero on empty
         if prompt == "" and zero_on_empty:
@@ -197,9 +180,7 @@ class SDXLPromptInvocationBase:
 
         def _lora_loader() -> Iterator[Tuple[LoRAModelRaw, float]]:
             for lora in clip_field.loras:
-                lora_info = context.services.model_manager.load.load_model_by_key(
-                    **lora.model_dump(exclude={"weight"}), context=context
-                )
+                lora_info = context.models.load(**lora.model_dump(exclude={"weight"}))
                 lora_model = lora_info.model
                 assert isinstance(lora_model, LoRAModelRaw)
                 yield (lora_model, lora.weight)
@@ -212,11 +193,8 @@ class SDXLPromptInvocationBase:
         for trigger in extract_ti_triggers_from_prompt(prompt):
             name = trigger[1:-1]
             try:
-                ti_model = context.services.model_manager.load.load_model_by_attr(
-                    model_name=name,
-                    base_model=text_encoder_info.config.base,
-                    model_type=ModelType.TextualInversion,
-                    context=context,
+                ti_model = context.models.load_by_attrs(
+                    model_name=name, base_model=text_encoder_info.config.base, model_type=ModelType.TextualInversion
                 ).model
                 assert isinstance(ti_model, TextualInversionModelRaw)
                 ti_list.append((name, ti_model))
diff --git a/invokeai/app/invocations/ip_adapter.py b/invokeai/app/invocations/ip_adapter.py
index 01124f62f3..15e254010b 100644
--- a/invokeai/app/invocations/ip_adapter.py
+++ b/invokeai/app/invocations/ip_adapter.py
@@ -14,8 +14,7 @@ from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField
 from invokeai.app.invocations.primitives import ImageField
 from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
 from invokeai.app.services.shared.invocation_context import InvocationContext
-from invokeai.backend.model_management.models.base import BaseModelType, ModelType
-from invokeai.backend.model_management.models.ip_adapter import get_ip_adapter_image_encoder_model_id
+from invokeai.backend.model_manager.config import BaseModelType, ModelType
 
 
 # LS: Consider moving these two classes into model.py
@@ -90,10 +89,10 @@ class IPAdapterInvocation(BaseInvocation):
 
     def invoke(self, context: InvocationContext) -> IPAdapterOutput:
         # Lookup the CLIP Vision encoder that is intended to be used with the IP-Adapter model.
-        ip_adapter_info = context.services.model_manager.store.get_model(self.ip_adapter_model.key)
+        ip_adapter_info = context.models.get_config(self.ip_adapter_model.key)
         image_encoder_model_id = ip_adapter_info.image_encoder_model_id
         image_encoder_model_name = image_encoder_model_id.split("/")[-1].strip()
-        image_encoder_models = context.services.model_manager.store.search_by_attr(
+        image_encoder_models = context.models.search_by_attrs(
             model_name=image_encoder_model_name, base_model=BaseModelType.Any, model_type=ModelType.CLIPVision
         )
         assert len(image_encoder_models) == 1
diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py
index 05293fdfee..5dd0eb074d 100644
--- a/invokeai/app/invocations/latent.py
+++ b/invokeai/app/invocations/latent.py
@@ -141,7 +141,7 @@ class CreateDenoiseMaskInvocation(BaseInvocation):
     @torch.no_grad()
     def invoke(self, context: InvocationContext) -> DenoiseMaskOutput:
         if self.image is not None:
-            image = context.services.images.get_pil_image(self.image.image_name)
+            image = context.images.get_pil(self.image.image_name)
             image_tensor = image_resized_to_grid_as_tensor(image.convert("RGB"))
             if image_tensor.dim() == 3:
                 image_tensor = image_tensor.unsqueeze(0)
@@ -153,10 +153,7 @@ class CreateDenoiseMaskInvocation(BaseInvocation):
         )
 
         if image_tensor is not None:
-            vae_info = context.services.model_manager.load.load_model_by_key(
-                **self.vae.vae.model_dump(),
-                context=context,
-            )
+            vae_info = context.models.load(**self.vae.vae.model_dump())
 
             img_mask = tv_resize(mask, image_tensor.shape[-2:], T.InterpolationMode.BILINEAR, antialias=False)
             masked_image = image_tensor * torch.where(img_mask < 0.5, 0.0, 1.0)
@@ -182,10 +179,7 @@ def get_scheduler(
     seed: int,
 ) -> Scheduler:
     scheduler_class, scheduler_extra_config = SCHEDULER_MAP.get(scheduler_name, SCHEDULER_MAP["ddim"])
-    orig_scheduler_info = context.services.model_manager.load.load_model_by_key(
-        **scheduler_info.model_dump(),
-        context=context,
-    )
+    orig_scheduler_info = context.models.load(**scheduler_info.model_dump())
     with orig_scheduler_info as orig_scheduler:
         scheduler_config = orig_scheduler.config
 
@@ -399,12 +393,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
         #        and if weight is None, populate with default 1.0?
         controlnet_data = []
         for control_info in control_list:
-            control_model = exit_stack.enter_context(
-                context.services.model_manager.load.load_model_by_key(
-                    key=control_info.control_model.key,
-                    context=context,
-                )
-            )
+            control_model = exit_stack.enter_context(context.models.load(key=control_info.control_model.key))
 
             # control_models.append(control_model)
             control_image_field = control_info.image
@@ -466,25 +455,17 @@ class DenoiseLatentsInvocation(BaseInvocation):
         conditioning_data.ip_adapter_conditioning = []
         for single_ip_adapter in ip_adapter:
             ip_adapter_model: Union[IPAdapter, IPAdapterPlus] = exit_stack.enter_context(
-                context.services.model_manager.load.load_model_by_key(
-                    key=single_ip_adapter.ip_adapter_model.key,
-                    context=context,
-                )
+                context.models.load(key=single_ip_adapter.ip_adapter_model.key)
             )
 
-            image_encoder_model_info = context.services.model_manager.load.load_model_by_key(
-                key=single_ip_adapter.image_encoder_model.key,
-                context=context,
-            )
+            image_encoder_model_info = context.models.load(key=single_ip_adapter.image_encoder_model.key)
 
             # `single_ip_adapter.image` could be a list or a single ImageField. Normalize to a list here.
             single_ipa_image_fields = single_ip_adapter.image
             if not isinstance(single_ipa_image_fields, list):
                 single_ipa_image_fields = [single_ipa_image_fields]
 
-            single_ipa_images = [
-                context.services.images.get_pil_image(image.image_name) for image in single_ipa_image_fields
-            ]
+            single_ipa_images = [context.images.get_pil(image.image_name) for image in single_ipa_image_fields]
 
             # TODO(ryand): With some effort, the step of running the CLIP Vision encoder could be done before any other
             # models are needed in memory. This would help to reduce peak memory utilization in low-memory environments.
@@ -528,10 +509,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
 
         t2i_adapter_data = []
         for t2i_adapter_field in t2i_adapter:
-            t2i_adapter_model_info = context.services.model_manager.load.load_model_by_key(
-                key=t2i_adapter_field.t2i_adapter_model.key,
-                context=context,
-            )
+            t2i_adapter_model_info = context.models.load(key=t2i_adapter_field.t2i_adapter_model.key)
             image = context.images.get_pil(t2i_adapter_field.image.image_name)
 
             # The max_unet_downscale is the maximum amount that the UNet model downscales the latent image internally.
@@ -676,30 +654,20 @@ class DenoiseLatentsInvocation(BaseInvocation):
                 do_classifier_free_guidance=True,
             )
 
-            # Get the source node id (we are invoking the prepared node)
-            graph_execution_state = context.services.graph_execution_manager.get(context.graph_execution_state_id)
-            source_node_id = graph_execution_state.prepared_source_mapping[self.id]
-
             # get the unet's config so that we can pass the base to dispatch_progress()
-            unet_config = context.services.model_manager.store.get_model(self.unet.unet.key)
+            unet_config = context.models.get_config(self.unet.unet.key)
 
             def step_callback(state: PipelineIntermediateState) -> None:
-                self.dispatch_progress(context, source_node_id, state, unet_config.base)
+                context.util.sd_step_callback(state, unet_config.base)
 
             def _lora_loader() -> Iterator[Tuple[LoRAModelRaw, float]]:
                 for lora in self.unet.loras:
-                    lora_info = context.services.model_manager.load.load_model_by_key(
-                        **lora.model_dump(exclude={"weight"}),
-                        context=context,
-                    )
+                    lora_info = context.models.load(**lora.model_dump(exclude={"weight"}))
                     yield (lora_info.model, lora.weight)
                     del lora_info
                 return
 
-            unet_info = context.services.model_manager.load.load_model_by_key(
-                **self.unet.unet.model_dump(),
-                context=context,
-            )
+            unet_info = context.models.load(**self.unet.unet.model_dump())
             assert isinstance(unet_info.model, UNet2DConditionModel)
             with (
                 ExitStack() as exit_stack,
@@ -806,10 +774,7 @@ class LatentsToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
     def invoke(self, context: InvocationContext) -> ImageOutput:
         latents = context.tensors.load(self.latents.latents_name)
 
-        vae_info = context.services.model_manager.load.load_model_by_key(
-            **self.vae.vae.model_dump(),
-            context=context,
-        )
+        vae_info = context.models.load(**self.vae.vae.model_dump())
 
         with set_seamless(vae_info.model, self.vae.seamless_axes), vae_info as vae:
             assert isinstance(vae, torch.nn.Module)
@@ -1032,10 +997,7 @@ class ImageToLatentsInvocation(BaseInvocation):
     def invoke(self, context: InvocationContext) -> LatentsOutput:
         image = context.images.get_pil(self.image.image_name)
 
-        vae_info = context.services.model_manager.load.load_model_by_key(
-            **self.vae.vae.model_dump(),
-            context=context,
-        )
+        vae_info = context.models.load(**self.vae.vae.model_dump())
 
         image_tensor = image_resized_to_grid_as_tensor(image.convert("RGB"))
         if image_tensor.dim() == 3:
@@ -1239,10 +1201,7 @@ class IdealSizeInvocation(BaseInvocation):
         return tuple((x - x % multiple_of) for x in args)
 
     def invoke(self, context: InvocationContext) -> IdealSizeOutput:
-        unet_config = context.services.model_manager.load.load_model_by_key(
-            **self.unet.unet.model_dump(),
-            context=context,
-        )
+        unet_config = context.models.get_config(**self.unet.unet.model_dump())
         aspect = self.width / self.height
         dimension: float = 512
         if unet_config.base == BaseModelType.StableDiffusion2:
diff --git a/invokeai/app/invocations/model.py b/invokeai/app/invocations/model.py
index 71a71a63c8..6087bc82db 100644
--- a/invokeai/app/invocations/model.py
+++ b/invokeai/app/invocations/model.py
@@ -103,7 +103,7 @@ class MainModelLoaderInvocation(BaseInvocation):
         key = self.model.key
 
         # TODO: not found exceptions
-        if not context.services.model_manager.store.exists(key):
+        if not context.models.exists(key):
             raise Exception(f"Unknown model {key}")
 
         return ModelLoaderOutput(
@@ -172,7 +172,7 @@ class LoraLoaderInvocation(BaseInvocation):
 
         lora_key = self.lora.key
 
-        if not context.services.model_manager.store.exists(lora_key):
+        if not context.models.exists(lora_key):
             raise Exception(f"Unkown lora: {lora_key}!")
 
         if self.unet is not None and any(lora.key == lora_key for lora in self.unet.loras):
@@ -252,7 +252,7 @@ class SDXLLoraLoaderInvocation(BaseInvocation):
 
         lora_key = self.lora.key
 
-        if not context.services.model_manager.store.exists(lora_key):
+        if not context.models.exists(lora_key):
             raise Exception(f"Unknown lora: {lora_key}!")
 
         if self.unet is not None and any(lora.key == lora_key for lora in self.unet.loras):
@@ -318,7 +318,7 @@ class VaeLoaderInvocation(BaseInvocation):
     def invoke(self, context: InvocationContext) -> VAEOutput:
         key = self.vae_model.key
 
-        if not context.services.model_manager.store.exists(key):
+        if not context.models.exists(key):
             raise Exception(f"Unkown vae: {key}!")
 
         return VAEOutput(vae=VaeField(vae=ModelInfo(key=key)))
diff --git a/invokeai/app/invocations/sdxl.py b/invokeai/app/invocations/sdxl.py
index 85e6fb787f..0df27c0011 100644
--- a/invokeai/app/invocations/sdxl.py
+++ b/invokeai/app/invocations/sdxl.py
@@ -43,7 +43,7 @@ class SDXLModelLoaderInvocation(BaseInvocation):
         model_key = self.model.key
 
         # TODO: not found exceptions
-        if not context.services.model_manager.store.exists(model_key):
+        if not context.models.exists(model_key):
             raise Exception(f"Unknown model: {model_key}")
 
         return SDXLModelLoaderOutput(
@@ -112,7 +112,7 @@ class SDXLRefinerModelLoaderInvocation(BaseInvocation):
         model_key = self.model.key
 
         # TODO: not found exceptions
-        if not context.services.model_manager.store.exists(model_key):
+        if not context.models.exists(model_key):
             raise Exception(f"Unknown model: {model_key}")
 
         return SDXLRefinerModelLoaderOutput(
diff --git a/invokeai/app/services/model_load/model_load_base.py b/invokeai/app/services/model_load/model_load_base.py
index 45eaf4652f..f4dd905135 100644
--- a/invokeai/app/services/model_load/model_load_base.py
+++ b/invokeai/app/services/model_load/model_load_base.py
@@ -4,7 +4,7 @@
 from abc import ABC, abstractmethod
 from typing import Optional
 
-from invokeai.app.invocations.baseinvocation import InvocationContext
+from invokeai.app.services.shared.invocation_context import InvocationContextData
 from invokeai.backend.model_manager import AnyModel, AnyModelConfig, BaseModelType, ModelType, SubModelType
 from invokeai.backend.model_manager.load import LoadedModel
 from invokeai.backend.model_manager.load.convert_cache import ModelConvertCacheBase
@@ -19,14 +19,14 @@ class ModelLoadServiceBase(ABC):
         self,
         key: str,
         submodel_type: Optional[SubModelType] = None,
-        context: Optional[InvocationContext] = None,
+        context_data: Optional[InvocationContextData] = None,
     ) -> LoadedModel:
         """
         Given a model's key, load it and return the LoadedModel object.
 
         :param key: Key of model config to be fetched.
         :param submodel: For main (pipeline models), the submodel to fetch.
-        :param context: Invocation context used for event reporting
+        :param context_data: Invocation context data used for event reporting
         """
         pass
 
@@ -35,14 +35,14 @@ class ModelLoadServiceBase(ABC):
         self,
         model_config: AnyModelConfig,
         submodel_type: Optional[SubModelType] = None,
-        context: Optional[InvocationContext] = None,
+        context_data: Optional[InvocationContextData] = None,
     ) -> LoadedModel:
         """
         Given a model's configuration, load it and return the LoadedModel object.
 
         :param model_config: Model configuration record (as returned by ModelRecordBase.get_model())
         :param submodel: For main (pipeline models), the submodel to fetch.
-        :param context: Invocation context used for event reporting
+        :param context_data: Invocation context data used for event reporting
         """
         pass
 
@@ -53,7 +53,7 @@ class ModelLoadServiceBase(ABC):
         base_model: BaseModelType,
         model_type: ModelType,
         submodel: Optional[SubModelType] = None,
-        context: Optional[InvocationContext] = None,
+        context_data: Optional[InvocationContextData] = None,
     ) -> LoadedModel:
         """
         Given a model's attributes, search the database for it, and if found, load and return the LoadedModel object.
@@ -66,7 +66,7 @@ class ModelLoadServiceBase(ABC):
         :param base_model: Base model
         :param model_type: Type of the model
         :param submodel: For main (pipeline models), the submodel to fetch
-        :param context: The invocation context.
+        :param context_data: The invocation context data.
 
         Exceptions: UnknownModelException -- model with these attributes not known
                     NotImplementedException -- a model loader was not provided at initialization time
diff --git a/invokeai/app/services/model_load/model_load_default.py b/invokeai/app/services/model_load/model_load_default.py
index a6ccd5afbc..29b297c814 100644
--- a/invokeai/app/services/model_load/model_load_default.py
+++ b/invokeai/app/services/model_load/model_load_default.py
@@ -3,10 +3,11 @@
 
 from typing import Optional
 
-from invokeai.app.invocations.baseinvocation import InvocationContext
 from invokeai.app.services.config import InvokeAIAppConfig
 from invokeai.app.services.invocation_processor.invocation_processor_common import CanceledException
+from invokeai.app.services.invoker import Invoker
 from invokeai.app.services.model_records import ModelRecordServiceBase, UnknownModelException
+from invokeai.app.services.shared.invocation_context import InvocationContextData
 from invokeai.backend.model_manager import AnyModel, AnyModelConfig, BaseModelType, ModelType, SubModelType
 from invokeai.backend.model_manager.load import AnyModelLoader, LoadedModel, ModelCache, ModelConvertCache
 from invokeai.backend.model_manager.load.convert_cache import ModelConvertCacheBase
@@ -46,6 +47,9 @@ class ModelLoadService(ModelLoadServiceBase):
             ),
         )
 
+    def start(self, invoker: Invoker) -> None:
+        self._invoker = invoker
+
     @property
     def ram_cache(self) -> ModelCacheBase[AnyModel]:
         """Return the RAM cache used by this loader."""
@@ -60,7 +64,7 @@ class ModelLoadService(ModelLoadServiceBase):
         self,
         key: str,
         submodel_type: Optional[SubModelType] = None,
-        context: Optional[InvocationContext] = None,
+        context_data: Optional[InvocationContextData] = None,
     ) -> LoadedModel:
         """
         Given a model's key, load it and return the LoadedModel object.
@@ -70,7 +74,7 @@ class ModelLoadService(ModelLoadServiceBase):
         :param context: Invocation context used for event reporting
         """
         config = self._store.get_model(key)
-        return self.load_model_by_config(config, submodel_type, context)
+        return self.load_model_by_config(config, submodel_type, context_data)
 
     def load_model_by_attr(
         self,
@@ -78,7 +82,7 @@ class ModelLoadService(ModelLoadServiceBase):
         base_model: BaseModelType,
         model_type: ModelType,
         submodel: Optional[SubModelType] = None,
-        context: Optional[InvocationContext] = None,
+        context_data: Optional[InvocationContextData] = None,
     ) -> LoadedModel:
         """
         Given a model's attributes, search the database for it, and if found, load and return the LoadedModel object.
@@ -109,7 +113,7 @@ class ModelLoadService(ModelLoadServiceBase):
         self,
         model_config: AnyModelConfig,
         submodel_type: Optional[SubModelType] = None,
-        context: Optional[InvocationContext] = None,
+        context_data: Optional[InvocationContextData] = None,
     ) -> LoadedModel:
         """
         Given a model's configuration, load it and return the LoadedModel object.
@@ -118,15 +122,15 @@ class ModelLoadService(ModelLoadServiceBase):
         :param submodel: For main (pipeline models), the submodel to fetch.
         :param context: Invocation context used for event reporting
         """
-        if context:
+        if context_data:
             self._emit_load_event(
-                context=context,
+                context_data=context_data,
                 model_config=model_config,
             )
         loaded_model = self._any_loader.load_model(model_config, submodel_type)
-        if context:
+        if context_data:
             self._emit_load_event(
-                context=context,
+                context_data=context_data,
                 model_config=model_config,
                 loaded=True,
             )
@@ -134,26 +138,28 @@ class ModelLoadService(ModelLoadServiceBase):
 
     def _emit_load_event(
         self,
-        context: InvocationContext,
+        context_data: InvocationContextData,
         model_config: AnyModelConfig,
         loaded: Optional[bool] = False,
     ) -> None:
-        if context.services.queue.is_canceled(context.graph_execution_state_id):
+        if not self._invoker:
+            return
+        if self._invoker.services.queue.is_canceled(context_data.session_id):
             raise CanceledException()
 
         if not loaded:
-            context.services.events.emit_model_load_started(
-                queue_id=context.queue_id,
-                queue_item_id=context.queue_item_id,
-                queue_batch_id=context.queue_batch_id,
-                graph_execution_state_id=context.graph_execution_state_id,
+            self._invoker.services.events.emit_model_load_started(
+                queue_id=context_data.queue_id,
+                queue_item_id=context_data.queue_item_id,
+                queue_batch_id=context_data.batch_id,
+                graph_execution_state_id=context_data.session_id,
                 model_config=model_config,
             )
         else:
-            context.services.events.emit_model_load_completed(
-                queue_id=context.queue_id,
-                queue_item_id=context.queue_item_id,
-                queue_batch_id=context.queue_batch_id,
-                graph_execution_state_id=context.graph_execution_state_id,
+            self._invoker.services.events.emit_model_load_completed(
+                queue_id=context_data.queue_id,
+                queue_item_id=context_data.queue_item_id,
+                queue_batch_id=context_data.batch_id,
+                graph_execution_state_id=context_data.session_id,
                 model_config=model_config,
             )
diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index c68dc1140b..089d09f825 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -1,4 +1,5 @@
 from dataclasses import dataclass
+from pathlib import Path
 from typing import TYPE_CHECKING, Optional
 
 from PIL.Image import Image
@@ -12,8 +13,9 @@ from invokeai.app.services.images.images_common import ImageDTO
 from invokeai.app.services.invocation_services import InvocationServices
 from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID
 from invokeai.app.util.step_callback import stable_diffusion_step_callback
-from invokeai.backend.model_management.model_manager import LoadedModelInfo
-from invokeai.backend.model_management.models.base import BaseModelType, ModelType, SubModelType
+from invokeai.backend.model_manager.config import AnyModelConfig, BaseModelType, ModelFormat, ModelType, SubModelType
+from invokeai.backend.model_manager.load.load_base import LoadedModel
+from invokeai.backend.model_manager.metadata.metadata_base import AnyModelRepoMetadata
 from invokeai.backend.stable_diffusion.diffusers_pipeline import PipelineIntermediateState
 from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ConditioningFieldData
 
@@ -259,45 +261,95 @@ class ConditioningInterface(InvocationContextInterface):
 
 
 class ModelsInterface(InvocationContextInterface):
-    def exists(self, model_name: str, base_model: BaseModelType, model_type: ModelType) -> bool:
+    def exists(self, key: str) -> bool:
         """
         Checks if a model exists.
 
-        :param model_name: The name of the model to check.
-        :param base_model: The base model of the model to check.
-        :param model_type: The type of the model to check.
+        :param key: The key of the model.
         """
-        return self._services.model_manager.model_exists(model_name, base_model, model_type)
+        return self._services.model_manager.store.exists(key)
 
-    def load(
-        self, model_name: str, base_model: BaseModelType, model_type: ModelType, submodel: Optional[SubModelType] = None
-    ) -> LoadedModelInfo:
+    def load(self, key: str, submodel_type: Optional[SubModelType] = None) -> LoadedModel:
         """
         Loads a model.
 
-        :param model_name: The name of the model to get.
-        :param base_model: The base model of the model to get.
-        :param model_type: The type of the model to get.
-        :param submodel: The submodel of the model to get.
+        :param key: The key of the model.
+        :param submodel_type: The submodel of the model to get.
         :returns: An object representing the loaded model.
         """
 
         # The model manager emits events as it loads the model. It needs the context data to build
         # the event payloads.
 
-        return self._services.model_manager.get_model(
-            model_name, base_model, model_type, submodel, context_data=self._context_data
+        return self._services.model_manager.load.load_model_by_key(
+            key=key, submodel_type=submodel_type, context_data=self._context_data
         )
 
-    def get_info(self, model_name: str, base_model: BaseModelType, model_type: ModelType) -> dict:
+    def load_by_attrs(
+        self, model_name: str, base_model: BaseModelType, model_type: ModelType, submodel: Optional[SubModelType] = None
+    ) -> LoadedModel:
+        """
+        Loads a model by its attributes.
+
+        :param model_name: Name of to be fetched.
+        :param base_model: Base model
+        :param model_type: Type of the model
+        :param submodel: For main (pipeline models), the submodel to fetch
+        """
+        return self._services.model_manager.load.load_model_by_attr(
+            model_name=model_name,
+            base_model=base_model,
+            model_type=model_type,
+            submodel=submodel,
+            context_data=self._context_data,
+        )
+
+    def get_config(self, key: str) -> AnyModelConfig:
         """
         Gets a model's info, an dict-like object.
 
-        :param model_name: The name of the model to get.
-        :param base_model: The base model of the model to get.
-        :param model_type: The type of the model to get.
+        :param key: The key of the model.
         """
-        return self._services.model_manager.model_info(model_name, base_model, model_type)
+        return self._services.model_manager.store.get_model(key=key)
+
+    def get_metadata(self, key: str) -> Optional[AnyModelRepoMetadata]:
+        """
+        Gets a model's metadata, if it has any.
+
+        :param key: The key of the model.
+        """
+        return self._services.model_manager.store.get_metadata(key=key)
+
+    def search_by_path(self, path: Path) -> list[AnyModelConfig]:
+        """
+        Searches for models by path.
+
+        :param path: The path to search for.
+        """
+        return self._services.model_manager.store.search_by_path(path)
+
+    def search_by_attrs(
+        self,
+        model_name: Optional[str] = None,
+        base_model: Optional[BaseModelType] = None,
+        model_type: Optional[ModelType] = None,
+        model_format: Optional[ModelFormat] = None,
+    ) -> list[AnyModelConfig]:
+        """
+        Searches for models by attributes.
+
+        :param model_name: Name of to be fetched.
+        :param base_model: Base model
+        :param model_type: Type of the model
+        :param submodel: For main (pipeline models), the submodel to fetch
+        """
+
+        return self._services.model_manager.store.search_by_attr(
+            model_name=model_name,
+            base_model=base_model,
+            model_type=model_type,
+            model_format=model_format,
+        )
 
 
 class ConfigInterface(InvocationContextInterface):
diff --git a/invokeai/app/util/step_callback.py b/invokeai/app/util/step_callback.py
index d83b380d95..33d00ca366 100644
--- a/invokeai/app/util/step_callback.py
+++ b/invokeai/app/util/step_callback.py
@@ -4,8 +4,8 @@ import torch
 from PIL import Image
 
 from invokeai.app.services.invocation_processor.invocation_processor_common import CanceledException, ProgressImage
+from invokeai.backend.model_manager.config import BaseModelType
 
-from ...backend.model_management.models import BaseModelType
 from ...backend.stable_diffusion import PipelineIntermediateState
 from ...backend.util.util import image_to_dataURL
 

From c80987eb8a3cd36398a195bc3532d72abaa9d19a Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Thu, 15 Feb 2024 20:50:47 +1100
Subject: [PATCH 131/411] chore: ruff

---
 invokeai/app/invocations/controlnet_image_processors.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/invokeai/app/invocations/controlnet_image_processors.py b/invokeai/app/invocations/controlnet_image_processors.py
index 580ee08562..8542134fff 100644
--- a/invokeai/app/invocations/controlnet_image_processors.py
+++ b/invokeai/app/invocations/controlnet_image_processors.py
@@ -39,7 +39,6 @@ from invokeai.app.invocations.util import validate_begin_end_step, validate_weig
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.backend.image_util.depth_anything import DepthAnythingDetector
 from invokeai.backend.image_util.dw_openpose import DWOpenposeDetector
-from invokeai.backend.model_management.models.base import BaseModelType
 
 from .baseinvocation import (
     BaseInvocation,

From 68f53460f05f686df3c7cf8df36805adc1ce9f27 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Thu, 15 Feb 2024 20:52:44 +1100
Subject: [PATCH 132/411] chore: lint

---
 invokeai/frontend/web/src/features/nodes/types/error.ts | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/invokeai/frontend/web/src/features/nodes/types/error.ts b/invokeai/frontend/web/src/features/nodes/types/error.ts
index c3da136c7a..82bc0f86e0 100644
--- a/invokeai/frontend/web/src/features/nodes/types/error.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/error.ts
@@ -60,4 +60,4 @@ export class FieldParseError extends Error {
 export class UnableToExtractSchemaNameFromRefError extends FieldParseError {}
 export class UnsupportedArrayItemType extends FieldParseError {}
 export class UnsupportedUnionError extends FieldParseError {}
-export class UnsupportedPrimitiveTypeError extends FieldParseError {}
\ No newline at end of file
+export class UnsupportedPrimitiveTypeError extends FieldParseError {}

From 651ac56b2c47c6301cfa4092946bfbc9b1264569 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Thu, 15 Feb 2024 20:53:41 +1100
Subject: [PATCH 133/411] fix(ui): fix type issues

---
 .../nodes/components/sidePanel/viewMode/WorkflowField.tsx   | 4 ++--
 .../src/features/nodes/util/schema/parseFieldType.test.ts   | 6 +++---
 2 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/invokeai/frontend/web/src/features/nodes/components/sidePanel/viewMode/WorkflowField.tsx b/invokeai/frontend/web/src/features/nodes/components/sidePanel/viewMode/WorkflowField.tsx
index 0e5857933a..e707dd4f54 100644
--- a/invokeai/frontend/web/src/features/nodes/components/sidePanel/viewMode/WorkflowField.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/sidePanel/viewMode/WorkflowField.tsx
@@ -16,7 +16,7 @@ type Props = {
 
 const WorkflowField = ({ nodeId, fieldName }: Props) => {
   const label = useFieldLabel(nodeId, fieldName);
-  const fieldTemplateTitle = useFieldTemplateTitle(nodeId, fieldName, 'input');
+  const fieldTemplateTitle = useFieldTemplateTitle(nodeId, fieldName, 'inputs');
   const { isValueChanged, onReset } = useFieldOriginalValue(nodeId, fieldName);
 
   return (
@@ -36,7 +36,7 @@ const WorkflowField = ({ nodeId, fieldName }: Props) => {
           />
         )}
         <Tooltip
-          label={<FieldTooltipContent nodeId={nodeId} fieldName={fieldName} kind="input" />}
+          label={<FieldTooltipContent nodeId={nodeId} fieldName={fieldName} kind="inputs" />}
           openDelay={HANDLE_TOOLTIP_OPEN_DELAY}
           placement="top"
         >
diff --git a/invokeai/frontend/web/src/features/nodes/util/schema/parseFieldType.test.ts b/invokeai/frontend/web/src/features/nodes/util/schema/parseFieldType.test.ts
index 2f4ce48a32..d7011ad6f8 100644
--- a/invokeai/frontend/web/src/features/nodes/util/schema/parseFieldType.test.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/schema/parseFieldType.test.ts
@@ -284,13 +284,13 @@ describe('refObjectToSchemaName', async () => {
 });
 
 describe.concurrent('parseFieldType', async () => {
-  it.each(primitiveTypes)('parses primitive types ($name)', ({ schema, expected }) => {
+  it.each(primitiveTypes)('parses primitive types ($name)', ({ schema, expected }: ParseFieldTypeTestCase) => {
     expect(parseFieldType(schema)).toEqual(expected);
   });
-  it.each(complexTypes)('parses complex types ($name)', ({ schema, expected }) => {
+  it.each(complexTypes)('parses complex types ($name)', ({ schema, expected }: ParseFieldTypeTestCase) => {
     expect(parseFieldType(schema)).toEqual(expected);
   });
-  it.each(specialCases)('parses special case types ($name)', ({ schema, expected }) => {
+  it.each(specialCases)('parses special case types ($name)', ({ schema, expected }: ParseFieldTypeTestCase) => {
     expect(parseFieldType(schema)).toEqual(expected);
   });
 

From fab30b5a11fc1f0d7704c31a75f30be7567a4721 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Thu, 15 Feb 2024 21:16:25 +1100
Subject: [PATCH 134/411] feat(ui): export components type

---
 .../frontend/web/src/services/api/types.ts    | 228 +++++++++---------
 1 file changed, 114 insertions(+), 114 deletions(-)

diff --git a/invokeai/frontend/web/src/services/api/types.ts b/invokeai/frontend/web/src/services/api/types.ts
index 55ff808b40..f9a1decf65 100644
--- a/invokeai/frontend/web/src/services/api/types.ts
+++ b/invokeai/frontend/web/src/services/api/types.ts
@@ -3,7 +3,7 @@ import type { EntityState } from '@reduxjs/toolkit';
 import type { components, paths } from 'services/api/schema';
 import type { O } from 'ts-toolbelt';
 
-type s = components['schemas'];
+export type S = components['schemas'];
 
 export type ImageCache = EntityState<ImageDTO, string>;
 
@@ -23,60 +23,60 @@ export type BatchConfig =
 
 export type EnqueueBatchResult = components['schemas']['EnqueueBatchResult'];
 
-export type InputFieldJSONSchemaExtra = s['InputFieldJSONSchemaExtra'];
-export type OutputFieldJSONSchemaExtra = s['OutputFieldJSONSchemaExtra'];
-export type InvocationJSONSchemaExtra = s['UIConfigBase'];
+export type InputFieldJSONSchemaExtra = S['InputFieldJSONSchemaExtra'];
+export type OutputFieldJSONSchemaExtra = S['OutputFieldJSONSchemaExtra'];
+export type InvocationJSONSchemaExtra = S['UIConfigBase'];
 
 // App Info
-export type AppVersion = s['AppVersion'];
-export type AppConfig = s['AppConfig'];
-export type AppDependencyVersions = s['AppDependencyVersions'];
+export type AppVersion = S['AppVersion'];
+export type AppConfig = S['AppConfig'];
+export type AppDependencyVersions = S['AppDependencyVersions'];
 
 // Images
-export type ImageDTO = s['ImageDTO'];
-export type BoardDTO = s['BoardDTO'];
-export type BoardChanges = s['BoardChanges'];
-export type ImageChanges = s['ImageRecordChanges'];
-export type ImageCategory = s['ImageCategory'];
-export type ResourceOrigin = s['ResourceOrigin'];
-export type ImageField = s['ImageField'];
-export type OffsetPaginatedResults_BoardDTO_ = s['OffsetPaginatedResults_BoardDTO_'];
-export type OffsetPaginatedResults_ImageDTO_ = s['OffsetPaginatedResults_ImageDTO_'];
+export type ImageDTO = S['ImageDTO'];
+export type BoardDTO = S['BoardDTO'];
+export type BoardChanges = S['BoardChanges'];
+export type ImageChanges = S['ImageRecordChanges'];
+export type ImageCategory = S['ImageCategory'];
+export type ResourceOrigin = S['ResourceOrigin'];
+export type ImageField = S['ImageField'];
+export type OffsetPaginatedResults_BoardDTO_ = S['OffsetPaginatedResults_BoardDTO_'];
+export type OffsetPaginatedResults_ImageDTO_ = S['OffsetPaginatedResults_ImageDTO_'];
 
 // Models
-export type ModelType = s['invokeai__backend__model_management__models__base__ModelType'];
-export type SubModelType = s['SubModelType'];
-export type BaseModelType = s['invokeai__backend__model_management__models__base__BaseModelType'];
-export type MainModelField = s['MainModelField'];
-export type VAEModelField = s['VAEModelField'];
-export type LoRAModelField = s['LoRAModelField'];
-export type LoRAModelFormat = s['LoRAModelFormat'];
-export type ControlNetModelField = s['ControlNetModelField'];
-export type IPAdapterModelField = s['IPAdapterModelField'];
-export type T2IAdapterModelField = s['T2IAdapterModelField'];
-export type ModelsList = s['invokeai__app__api__routers__models__ModelsList'];
-export type ControlField = s['ControlField'];
-export type IPAdapterField = s['IPAdapterField'];
+export type ModelType = S['ModelType'];
+export type SubModelType = S['SubModelType'];
+export type BaseModelType = S['BaseModelType'];
+export type MainModelField = S['MainModelField'];
+export type VAEModelField = S['VAEModelField'];
+export type LoRAModelField = S['LoRAModelField'];
+export type LoRAModelFormat = S['LoRAModelFormat'];
+export type ControlNetModelField = S['ControlNetModelField'];
+export type IPAdapterModelField = S['IPAdapterModelField'];
+export type T2IAdapterModelField = S['T2IAdapterModelField'];
+export type ModelsList = S['invokeai__app__api__routers__models__ModelsList'];
+export type ControlField = S['ControlField'];
+export type IPAdapterField = S['IPAdapterField'];
 
 // Model Configs
-export type LoRAModelConfig = s['LoRAModelConfig'];
-export type VaeModelConfig = s['VaeModelConfig'];
-export type ControlNetModelCheckpointConfig = s['ControlNetModelCheckpointConfig'];
-export type ControlNetModelDiffusersConfig = s['ControlNetModelDiffusersConfig'];
+export type LoRAModelConfig = S['LoRAModelConfig'];
+export type VaeModelConfig = S['VaeModelConfig'];
+export type ControlNetModelCheckpointConfig = S['ControlNetModelCheckpointConfig'];
+export type ControlNetModelDiffusersConfig = S['ControlNetModelDiffusersConfig'];
 export type ControlNetModelConfig = ControlNetModelCheckpointConfig | ControlNetModelDiffusersConfig;
-export type IPAdapterModelInvokeAIConfig = s['IPAdapterModelInvokeAIConfig'];
+export type IPAdapterModelInvokeAIConfig = S['IPAdapterModelInvokeAIConfig'];
 export type IPAdapterModelConfig = IPAdapterModelInvokeAIConfig;
-export type T2IAdapterModelDiffusersConfig = s['T2IAdapterModelDiffusersConfig'];
+export type T2IAdapterModelDiffusersConfig = S['T2IAdapterModelDiffusersConfig'];
 export type T2IAdapterModelConfig = T2IAdapterModelDiffusersConfig;
-export type TextualInversionModelConfig = s['TextualInversionModelConfig'];
+export type TextualInversionModelConfig = S['TextualInversionModelConfig'];
 export type DiffusersModelConfig =
-  | s['StableDiffusion1ModelDiffusersConfig']
-  | s['StableDiffusion2ModelDiffusersConfig']
-  | s['StableDiffusionXLModelDiffusersConfig'];
+  | S['StableDiffusion1ModelDiffusersConfig']
+  | S['StableDiffusion2ModelDiffusersConfig']
+  | S['StableDiffusionXLModelDiffusersConfig'];
 export type CheckpointModelConfig =
-  | s['StableDiffusion1ModelCheckpointConfig']
-  | s['StableDiffusion2ModelCheckpointConfig']
-  | s['StableDiffusionXLModelCheckpointConfig'];
+  | S['StableDiffusion1ModelCheckpointConfig']
+  | S['StableDiffusion2ModelCheckpointConfig']
+  | S['StableDiffusionXLModelCheckpointConfig'];
 export type MainModelConfig = DiffusersModelConfig | CheckpointModelConfig;
 export type AnyModelConfig =
   | LoRAModelConfig
@@ -87,87 +87,87 @@ export type AnyModelConfig =
   | TextualInversionModelConfig
   | MainModelConfig;
 
-export type MergeModelConfig = s['Body_merge_models'];
-export type ImportModelConfig = s['Body_import_model'];
+export type MergeModelConfig = S['Body_merge_models'];
+export type ImportModelConfig = S['Body_import_model'];
 
 // Graphs
-export type Graph = s['Graph'];
+export type Graph = S['Graph'];
 export type NonNullableGraph = O.Required<Graph, 'nodes' | 'edges'>;
-export type Edge = s['Edge'];
-export type GraphExecutionState = s['GraphExecutionState'];
-export type Batch = s['Batch'];
-export type SessionQueueItemDTO = s['SessionQueueItemDTO'];
-export type SessionQueueItem = s['SessionQueueItem'];
-export type WorkflowRecordOrderBy = s['WorkflowRecordOrderBy'];
-export type SQLiteDirection = s['SQLiteDirection'];
-export type WorkflowDTO = s['WorkflowRecordDTO'];
-export type WorkflowRecordListItemDTO = s['WorkflowRecordListItemDTO'];
+export type Edge = S['Edge'];
+export type GraphExecutionState = S['GraphExecutionState'];
+export type Batch = S['Batch'];
+export type SessionQueueItemDTO = S['SessionQueueItemDTO'];
+export type SessionQueueItem = S['SessionQueueItem'];
+export type WorkflowRecordOrderBy = S['WorkflowRecordOrderBy'];
+export type SQLiteDirection = S['SQLiteDirection'];
+export type WorkflowDTO = S['WorkflowRecordDTO'];
+export type WorkflowRecordListItemDTO = S['WorkflowRecordListItemDTO'];
 
 // General nodes
-export type CollectInvocation = s['CollectInvocation'];
-export type IterateInvocation = s['IterateInvocation'];
-export type RangeInvocation = s['RangeInvocation'];
-export type RandomRangeInvocation = s['RandomRangeInvocation'];
-export type RangeOfSizeInvocation = s['RangeOfSizeInvocation'];
-export type ImageResizeInvocation = s['ImageResizeInvocation'];
-export type ImageBlurInvocation = s['ImageBlurInvocation'];
-export type ImageScaleInvocation = s['ImageScaleInvocation'];
-export type InfillPatchMatchInvocation = s['InfillPatchMatchInvocation'];
-export type InfillTileInvocation = s['InfillTileInvocation'];
-export type CreateDenoiseMaskInvocation = s['CreateDenoiseMaskInvocation'];
-export type MaskEdgeInvocation = s['MaskEdgeInvocation'];
-export type RandomIntInvocation = s['RandomIntInvocation'];
-export type CompelInvocation = s['CompelInvocation'];
-export type DynamicPromptInvocation = s['DynamicPromptInvocation'];
-export type NoiseInvocation = s['NoiseInvocation'];
-export type DenoiseLatentsInvocation = s['DenoiseLatentsInvocation'];
-export type SDXLLoraLoaderInvocation = s['SDXLLoraLoaderInvocation'];
-export type ImageToLatentsInvocation = s['ImageToLatentsInvocation'];
-export type LatentsToImageInvocation = s['LatentsToImageInvocation'];
-export type ImageCollectionInvocation = s['ImageCollectionInvocation'];
-export type MainModelLoaderInvocation = s['MainModelLoaderInvocation'];
-export type LoraLoaderInvocation = s['LoraLoaderInvocation'];
-export type ESRGANInvocation = s['ESRGANInvocation'];
-export type DivideInvocation = s['DivideInvocation'];
-export type ImageNSFWBlurInvocation = s['ImageNSFWBlurInvocation'];
-export type ImageWatermarkInvocation = s['ImageWatermarkInvocation'];
-export type SeamlessModeInvocation = s['SeamlessModeInvocation'];
-export type MetadataInvocation = s['MetadataInvocation'];
-export type CoreMetadataInvocation = s['CoreMetadataInvocation'];
-export type MetadataItemInvocation = s['MetadataItemInvocation'];
-export type MergeMetadataInvocation = s['MergeMetadataInvocation'];
-export type IPAdapterMetadataField = s['IPAdapterMetadataField'];
-export type T2IAdapterField = s['T2IAdapterField'];
-export type LoRAMetadataField = s['LoRAMetadataField'];
+export type CollectInvocation = S['CollectInvocation'];
+export type IterateInvocation = S['IterateInvocation'];
+export type RangeInvocation = S['RangeInvocation'];
+export type RandomRangeInvocation = S['RandomRangeInvocation'];
+export type RangeOfSizeInvocation = S['RangeOfSizeInvocation'];
+export type ImageResizeInvocation = S['ImageResizeInvocation'];
+export type ImageBlurInvocation = S['ImageBlurInvocation'];
+export type ImageScaleInvocation = S['ImageScaleInvocation'];
+export type InfillPatchMatchInvocation = S['InfillPatchMatchInvocation'];
+export type InfillTileInvocation = S['InfillTileInvocation'];
+export type CreateDenoiseMaskInvocation = S['CreateDenoiseMaskInvocation'];
+export type MaskEdgeInvocation = S['MaskEdgeInvocation'];
+export type RandomIntInvocation = S['RandomIntInvocation'];
+export type CompelInvocation = S['CompelInvocation'];
+export type DynamicPromptInvocation = S['DynamicPromptInvocation'];
+export type NoiseInvocation = S['NoiseInvocation'];
+export type DenoiseLatentsInvocation = S['DenoiseLatentsInvocation'];
+export type SDXLLoraLoaderInvocation = S['SDXLLoraLoaderInvocation'];
+export type ImageToLatentsInvocation = S['ImageToLatentsInvocation'];
+export type LatentsToImageInvocation = S['LatentsToImageInvocation'];
+export type ImageCollectionInvocation = S['ImageCollectionInvocation'];
+export type MainModelLoaderInvocation = S['MainModelLoaderInvocation'];
+export type LoraLoaderInvocation = S['LoraLoaderInvocation'];
+export type ESRGANInvocation = S['ESRGANInvocation'];
+export type DivideInvocation = S['DivideInvocation'];
+export type ImageNSFWBlurInvocation = S['ImageNSFWBlurInvocation'];
+export type ImageWatermarkInvocation = S['ImageWatermarkInvocation'];
+export type SeamlessModeInvocation = S['SeamlessModeInvocation'];
+export type MetadataInvocation = S['MetadataInvocation'];
+export type CoreMetadataInvocation = S['CoreMetadataInvocation'];
+export type MetadataItemInvocation = S['MetadataItemInvocation'];
+export type MergeMetadataInvocation = S['MergeMetadataInvocation'];
+export type IPAdapterMetadataField = S['IPAdapterMetadataField'];
+export type T2IAdapterField = S['T2IAdapterField'];
+export type LoRAMetadataField = S['LoRAMetadataField'];
 
 // ControlNet Nodes
-export type ControlNetInvocation = s['ControlNetInvocation'];
-export type T2IAdapterInvocation = s['T2IAdapterInvocation'];
-export type IPAdapterInvocation = s['IPAdapterInvocation'];
-export type CannyImageProcessorInvocation = s['CannyImageProcessorInvocation'];
-export type ColorMapImageProcessorInvocation = s['ColorMapImageProcessorInvocation'];
-export type ContentShuffleImageProcessorInvocation = s['ContentShuffleImageProcessorInvocation'];
-export type DepthAnythingImageProcessorInvocation = s['DepthAnythingImageProcessorInvocation'];
-export type HedImageProcessorInvocation = s['HedImageProcessorInvocation'];
-export type LineartAnimeImageProcessorInvocation = s['LineartAnimeImageProcessorInvocation'];
-export type LineartImageProcessorInvocation = s['LineartImageProcessorInvocation'];
-export type MediapipeFaceProcessorInvocation = s['MediapipeFaceProcessorInvocation'];
-export type MidasDepthImageProcessorInvocation = s['MidasDepthImageProcessorInvocation'];
-export type MlsdImageProcessorInvocation = s['MlsdImageProcessorInvocation'];
-export type NormalbaeImageProcessorInvocation = s['NormalbaeImageProcessorInvocation'];
-export type DWOpenposeImageProcessorInvocation = s['DWOpenposeImageProcessorInvocation'];
-export type PidiImageProcessorInvocation = s['PidiImageProcessorInvocation'];
-export type ZoeDepthImageProcessorInvocation = s['ZoeDepthImageProcessorInvocation'];
+export type ControlNetInvocation = S['ControlNetInvocation'];
+export type T2IAdapterInvocation = S['T2IAdapterInvocation'];
+export type IPAdapterInvocation = S['IPAdapterInvocation'];
+export type CannyImageProcessorInvocation = S['CannyImageProcessorInvocation'];
+export type ColorMapImageProcessorInvocation = S['ColorMapImageProcessorInvocation'];
+export type ContentShuffleImageProcessorInvocation = S['ContentShuffleImageProcessorInvocation'];
+export type DepthAnythingImageProcessorInvocation = S['DepthAnythingImageProcessorInvocation'];
+export type HedImageProcessorInvocation = S['HedImageProcessorInvocation'];
+export type LineartAnimeImageProcessorInvocation = S['LineartAnimeImageProcessorInvocation'];
+export type LineartImageProcessorInvocation = S['LineartImageProcessorInvocation'];
+export type MediapipeFaceProcessorInvocation = S['MediapipeFaceProcessorInvocation'];
+export type MidasDepthImageProcessorInvocation = S['MidasDepthImageProcessorInvocation'];
+export type MlsdImageProcessorInvocation = S['MlsdImageProcessorInvocation'];
+export type NormalbaeImageProcessorInvocation = S['NormalbaeImageProcessorInvocation'];
+export type DWOpenposeImageProcessorInvocation = S['DWOpenposeImageProcessorInvocation'];
+export type PidiImageProcessorInvocation = S['PidiImageProcessorInvocation'];
+export type ZoeDepthImageProcessorInvocation = S['ZoeDepthImageProcessorInvocation'];
 
 // Node Outputs
-export type ImageOutput = s['ImageOutput'];
-export type StringOutput = s['StringOutput'];
-export type FloatOutput = s['FloatOutput'];
-export type IntegerOutput = s['IntegerOutput'];
-export type IterateInvocationOutput = s['IterateInvocationOutput'];
-export type CollectInvocationOutput = s['CollectInvocationOutput'];
-export type LatentsOutput = s['LatentsOutput'];
-export type GraphInvocationOutput = s['GraphInvocationOutput'];
+export type ImageOutput = S['ImageOutput'];
+export type StringOutput = S['StringOutput'];
+export type FloatOutput = S['FloatOutput'];
+export type IntegerOutput = S['IntegerOutput'];
+export type IterateInvocationOutput = S['IterateInvocationOutput'];
+export type CollectInvocationOutput = S['CollectInvocationOutput'];
+export type LatentsOutput = S['LatentsOutput'];
+export type GraphInvocationOutput = S['GraphInvocationOutput'];
 
 // Post-image upload actions, controls workflows when images are uploaded
 

From 7996d43af90433bcd99c2b76b5ab25e4c021a490 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Thu, 15 Feb 2024 22:15:21 +1100
Subject: [PATCH 135/411] chore(ui): typegen

---
 .../frontend/web/src/services/api/schema.ts   | 2012 +++++++----------
 1 file changed, 841 insertions(+), 1171 deletions(-)

diff --git a/invokeai/frontend/web/src/services/api/schema.ts b/invokeai/frontend/web/src/services/api/schema.ts
index 1599b310c9..3393e74d48 100644
--- a/invokeai/frontend/web/src/services/api/schema.ts
+++ b/invokeai/frontend/web/src/services/api/schema.ts
@@ -19,80 +19,14 @@ export type paths = {
      */
     post: operations["parse_dynamicprompts"];
   };
-  "/api/v1/models/": {
-    /**
-     * List Models
-     * @description Gets a list of models
-     */
-    get: operations["list_models"];
-  };
-  "/api/v1/models/{base_model}/{model_type}/{model_name}": {
-    /**
-     * Delete Model
-     * @description Delete Model
-     */
-    delete: operations["del_model"];
-    /**
-     * Update Model
-     * @description Update model contents with a new config. If the model name or base fields are changed, then the model is renamed.
-     */
-    patch: operations["update_model"];
-  };
-  "/api/v1/models/import": {
-    /**
-     * Import Model
-     * @description Add a model using its local path, repo_id, or remote URL. Model characteristics will be probed and configured automatically
-     */
-    post: operations["import_model"];
-  };
-  "/api/v1/models/add": {
-    /**
-     * Add Model
-     * @description Add a model using the configuration information appropriate for its type. Only local models can be added by path
-     */
-    post: operations["add_model"];
-  };
-  "/api/v1/models/convert/{base_model}/{model_type}/{model_name}": {
-    /**
-     * Convert Model
-     * @description Convert a checkpoint model into a diffusers model, optionally saving to the indicated destination directory, or `models` if none.
-     */
-    put: operations["convert_model"];
-  };
-  "/api/v1/models/search": {
-    /** Search For Models */
-    get: operations["search_for_models"];
-  };
-  "/api/v1/models/ckpt_confs": {
-    /**
-     * List Ckpt Configs
-     * @description Return a list of the legacy checkpoint configuration files stored in `ROOT/configs/stable-diffusion`, relative to ROOT.
-     */
-    get: operations["list_ckpt_configs"];
-  };
-  "/api/v1/models/sync": {
-    /**
-     * Sync To Config
-     * @description Call after making changes to models.yaml, autoimport directories or models directory to synchronize
-     * in-memory data structures with disk data structures.
-     */
-    post: operations["sync_to_config"];
-  };
-  "/api/v1/models/merge/{base_model}": {
-    /**
-     * Merge Models
-     * @description Convert a checkpoint model into a diffusers model
-     */
-    put: operations["merge_models"];
-  };
-  "/api/v1/model/record/": {
+  "/api/v2/models/": {
     /**
      * List Model Records
      * @description Get a list of models.
      */
     get: operations["list_model_records"];
   };
-  "/api/v1/model/record/i/{key}": {
+  "/api/v2/models/i/{key}": {
     /**
      * Get Model Record
      * @description Get a model record
@@ -112,50 +46,76 @@ export type paths = {
      */
     patch: operations["update_model_record"];
   };
-  "/api/v1/model/record/meta": {
+  "/api/v2/models/summary": {
     /**
      * List Model Summary
      * @description Gets a page of model summary data.
      */
     get: operations["list_model_summary"];
   };
-  "/api/v1/model/record/meta/i/{key}": {
+  "/api/v2/models/meta/i/{key}": {
     /**
      * Get Model Metadata
      * @description Get a model metadata object.
      */
     get: operations["get_model_metadata"];
   };
-  "/api/v1/model/record/tags": {
+  "/api/v2/models/tags": {
     /**
      * List Tags
      * @description Get a unique set of all the model tags.
      */
     get: operations["list_tags"];
   };
-  "/api/v1/model/record/tags/search": {
+  "/api/v2/models/tags/search": {
     /**
      * Search By Metadata Tags
      * @description Get a list of models.
      */
     get: operations["search_by_metadata_tags"];
   };
-  "/api/v1/model/record/i/": {
+  "/api/v2/models/i/": {
     /**
      * Add Model Record
      * @description Add a model using the configuration information appropriate for its type.
      */
     post: operations["add_model_record"];
   };
-  "/api/v1/model/record/import": {
+  "/api/v2/models/heuristic_import": {
     /**
-     * List Model Install Jobs
-     * @description Return list of model install jobs.
+     * Heuristic Import
+     * @description Install a model using a string identifier.
+     *
+     * `source` can be any of the following.
+     *
+     * 1. A path on the local filesystem ('C:\users\fred\model.safetensors')
+     * 2. A Url pointing to a single downloadable model file
+     * 3. A HuggingFace repo_id with any of the following formats:
+     *    - model/name
+     *    - model/name:fp16:vae
+     *    - model/name::vae          -- use default precision
+     *    - model/name:fp16:path/to/model.safetensors
+     *    - model/name::path/to/model.safetensors
+     *
+     * `config` is an optional dict containing model configuration values that will override
+     * the ones that are probed automatically.
+     *
+     * `access_token` is an optional access token for use with Urls that require
+     * authentication.
+     *
+     * Models will be downloaded, probed, configured and installed in a
+     * series of background threads. The return object has `status` attribute
+     * that can be used to monitor progress.
+     *
+     * See the documentation for `import_model_record` for more information on
+     * interpreting the job information returned by this route.
      */
-    get: operations["list_model_install_jobs"];
+    post: operations["heuristic_import_model"];
+  };
+  "/api/v2/models/install": {
     /**
      * Import Model
-     * @description Add a model using its local path, repo_id, or remote URL.
+     * @description Install a model using its local path, repo_id, or remote URL.
      *
      * Models will be downloaded, probed, configured and installed in a
      * series of background threads. The return object has `status` attribute
@@ -166,32 +126,38 @@ export type paths = {
      * appropriate value:
      *
      * * To install a local path using LocalModelSource, pass a source of form:
-     *   `{
+     *   ```
+     *   {
      *     "type": "local",
      *     "path": "/path/to/model",
      *     "inplace": false
-     *   }`
-     *    The "inplace" flag, if true, will register the model in place in its
-     *    current filesystem location. Otherwise, the model will be copied
-     *    into the InvokeAI models directory.
+     *   }
+     *   ```
+     *   The "inplace" flag, if true, will register the model in place in its
+     *   current filesystem location. Otherwise, the model will be copied
+     *   into the InvokeAI models directory.
      *
      * * To install a HuggingFace repo_id using HFModelSource, pass a source of form:
-     *   `{
+     *   ```
+     *   {
      *     "type": "hf",
      *     "repo_id": "stabilityai/stable-diffusion-2.0",
      *     "variant": "fp16",
      *     "subfolder": "vae",
      *     "access_token": "f5820a918aaf01"
-     *   }`
-     *  The `variant`, `subfolder` and `access_token` fields are optional.
+     *   }
+     *   ```
+     *   The `variant`, `subfolder` and `access_token` fields are optional.
      *
      * * To install a remote model using an arbitrary URL, pass:
-     *   `{
+     *   ```
+     *   {
      *     "type": "url",
      *     "url": "http://www.civitai.com/models/123456",
      *     "access_token": "f5820a918aaf01"
-     *   }`
-     * The `access_token` field is optonal
+     *   }
+     *   ```
+     *   The `access_token` field is optonal
      *
      * The model's configuration record will be probed and filled in
      * automatically.  To override the default guesses, pass "metadata"
@@ -200,26 +166,51 @@ export type paths = {
      * Installation occurs in the background. Either use list_model_install_jobs()
      * to poll for completion, or listen on the event bus for the following events:
      *
-     *   "model_install_running"
-     *   "model_install_completed"
-     *   "model_install_error"
+     *   * "model_install_running"
+     *   * "model_install_completed"
+     *   * "model_install_error"
      *
      * On successful completion, the event's payload will contain the field "key"
      * containing the installed ID of the model. On an error, the event's payload
      * will contain the fields "error_type" and "error" describing the nature of the
      * error and its traceback, respectively.
      */
-    post: operations["import_model_record"];
+    post: operations["import_model"];
+  };
+  "/api/v2/models/import": {
+    /**
+     * List Model Install Jobs
+     * @description Return the list of model install jobs.
+     *
+     * Install jobs have a numeric `id`, a `status`, and other fields that provide information on
+     * the nature of the job and its progress. The `status` is one of:
+     *
+     * * "waiting" -- Job is waiting in the queue to run
+     * * "downloading" -- Model file(s) are downloading
+     * * "running" -- Model has downloaded and the model probing and registration process is running
+     * * "completed" -- Installation completed successfully
+     * * "error" -- An error occurred. Details will be in the "error_type" and "error" fields.
+     * * "cancelled" -- Job was cancelled before completion.
+     *
+     * Once completed, information about the model such as its size, base
+     * model, type, and metadata can be retrieved from the `config_out`
+     * field. For multi-file models such as diffusers, information on individual files
+     * can be retrieved from `download_parts`.
+     *
+     * See the example and schema below for more information.
+     */
+    get: operations["list_model_install_jobs"];
     /**
      * Prune Model Install Jobs
      * @description Prune all completed and errored jobs from the install job list.
      */
     patch: operations["prune_model_install_jobs"];
   };
-  "/api/v1/model/record/import/{id}": {
+  "/api/v2/models/import/{id}": {
     /**
      * Get Model Install Job
-     * @description Return model install job corresponding to the given source.
+     * @description Return model install job corresponding to the given source. See the documentation for 'List Model Install Jobs'
+     * for information on the format of the return value.
      */
     get: operations["get_model_install_job"];
     /**
@@ -228,7 +219,7 @@ export type paths = {
      */
     delete: operations["cancel_model_install_job"];
   };
-  "/api/v1/model/record/sync": {
+  "/api/v2/models/sync": {
     /**
      * Sync Models To Config
      * @description Traverse the models and autoimport directories.
@@ -238,17 +229,29 @@ export type paths = {
      */
     patch: operations["sync_models_to_config"];
   };
-  "/api/v1/model/record/merge": {
+  "/api/v2/models/convert/{key}": {
+    /**
+     * Convert Model
+     * @description Permanently convert a model into diffusers format, replacing the safetensors version.
+     * Note that during the conversion process the key and model hash will change.
+     * The return value is the model configuration for the converted model.
+     */
+    put: operations["convert_model"];
+  };
+  "/api/v2/models/merge": {
     /**
      * Merge
-     * @description Merge diffusers models.
-     *
-     *     keys: List of 2-3 model keys to merge together. All models must use the same base type.
-     *     merged_model_name: Name for the merged model [Concat model names]
-     *     alpha: Alpha value (0.0-1.0). Higher values give more weight to the second model [0.5]
-     *     force: If true, force the merge even if the models were generated by different versions of the diffusers library [False]
-     *     interp: Interpolation method. One of "weighted_sum", "sigmoid", "inv_sigmoid" or "add_difference" [weighted_sum]
-     *     merge_dest_directory: Specify a directory to store the merged model in [models directory]
+     * @description Merge diffusers models. The process is controlled by a set parameters provided in the body of the request.
+     * ```
+     * Argument                Description [default]
+     * --------               ----------------------
+     * keys                   List of 2-3 model keys to merge together. All models must use the same base type.
+     * merged_model_name      Name for the merged model [Concat model names]
+     * alpha                  Alpha value (0.0-1.0). Higher values give more weight to the second model [0.5]
+     * force                  If true, force the merge even if the models were generated by different versions of the diffusers library [False]
+     * interp                 Interpolation method. One of "weighted_sum", "sigmoid", "inv_sigmoid" or "add_difference" [weighted_sum]
+     * merge_dest_directory   Specify a directory to store the merged model in [models directory]
+     * ```
      */
     put: operations["merge"];
   };
@@ -815,6 +818,12 @@ export type components = {
        */
       type?: "basemetadata";
     };
+    /**
+     * BaseModelType
+     * @description Base model type.
+     * @enum {string}
+     */
+    BaseModelType: "any" | "sd-1" | "sd-2" | "sdxl" | "sdxl-refiner";
     /** Batch */
     Batch: {
       /**
@@ -1163,19 +1172,6 @@ export type components = {
     };
     /** Body_import_model */
     Body_import_model: {
-      /**
-       * Location
-       * @description A model path, repo_id or URL to import
-       */
-      location: string;
-      /**
-       * Prediction Type
-       * @description Prediction type for SDv2 checkpoints and rare SDv1 checkpoints
-       */
-      prediction_type?: ("v_prediction" | "epsilon" | "sample") | null;
-    };
-    /** Body_import_model_record */
-    Body_import_model_record: {
       /** Source */
       source: components["schemas"]["LocalModelSource"] | components["schemas"]["HFModelSource"] | components["schemas"]["CivitaiModelSource"] | components["schemas"]["URLModelSource"];
       /**
@@ -1216,11 +1212,6 @@ export type components = {
        */
       merge_dest_directory?: string | null;
     };
-    /** Body_merge_models */
-    Body_merge_models: {
-      /** @description Model configuration */
-      body: components["schemas"]["MergeModelsBody"];
-    };
     /** Body_parse_dynamicprompts */
     Body_parse_dynamicprompts: {
       /**
@@ -1412,11 +1403,18 @@ export type components = {
      * @description Model config for ClipVision.
      */
     CLIPVisionDiffusersConfig: {
-      /** Path */
+      /**
+       * Path
+       * @description filesystem path to the model file or directory
+       */
       path: string;
-      /** Name */
+      /**
+       * Name
+       * @description model name
+       */
       name: string;
-      base: components["schemas"]["invokeai__backend__model_manager__config__BaseModelType"];
+      /** @description base model */
+      base: components["schemas"]["BaseModelType"];
       /**
        * Type
        * @default clip_vision
@@ -1444,45 +1442,29 @@ export type components = {
        * @description current fasthash of model contents
        */
       current_hash?: string | null;
-      /** Description */
+      /**
+       * Description
+       * @description human readable description of the model
+       */
       description?: string | null;
       /**
        * Source
-       * @description Model download source (URL or repo_id)
+       * @description model original source (path, URL or repo_id)
        */
       source?: string | null;
-    };
-    /** CLIPVisionModelDiffusersConfig */
-    CLIPVisionModelDiffusersConfig: {
-      /** Model Name */
-      model_name: string;
-      base_model: components["schemas"]["invokeai__backend__model_management__models__base__BaseModelType"];
       /**
-       * Model Type
-       * @default clip_vision
-       * @constant
+       * Last Modified
+       * @description timestamp for modification time
        */
-      model_type: "clip_vision";
-      /** Path */
-      path: string;
-      /** Description */
-      description?: string | null;
-      /**
-       * Model Format
-       * @constant
-       */
-      model_format: "diffusers";
-      error?: components["schemas"]["ModelError"] | null;
+      last_modified?: number | null;
     };
     /** CLIPVisionModelField */
     CLIPVisionModelField: {
       /**
-       * Model Name
-       * @description Name of the CLIP Vision image encoder model
+       * Key
+       * @description Key to the CLIP Vision image encoder model
        */
-      model_name: string;
-      /** @description Base model (usually 'Any') */
-      base_model: components["schemas"]["invokeai__backend__model_management__models__base__BaseModelType"];
+      key: string;
     };
     /**
      * CV2 Infill
@@ -2538,11 +2520,18 @@ export type components = {
      * @description Model config for ControlNet models (diffusers version).
      */
     ControlNetCheckpointConfig: {
-      /** Path */
+      /**
+       * Path
+       * @description filesystem path to the model file or directory
+       */
       path: string;
-      /** Name */
+      /**
+       * Name
+       * @description model name
+       */
       name: string;
-      base: components["schemas"]["invokeai__backend__model_manager__config__BaseModelType"];
+      /** @description base model */
+      base: components["schemas"]["BaseModelType"];
       /**
        * Type
        * @default controlnet
@@ -2571,13 +2560,21 @@ export type components = {
        * @description current fasthash of model contents
        */
       current_hash?: string | null;
-      /** Description */
+      /**
+       * Description
+       * @description human readable description of the model
+       */
       description?: string | null;
       /**
        * Source
-       * @description Model download source (URL or repo_id)
+       * @description model original source (path, URL or repo_id)
        */
       source?: string | null;
+      /**
+       * Last Modified
+       * @description timestamp for modification time
+       */
+      last_modified?: number | null;
       /**
        * Config
        * @description path to the checkpoint model config file
@@ -2589,11 +2586,18 @@ export type components = {
      * @description Model config for ControlNet models (diffusers version).
      */
     ControlNetDiffusersConfig: {
-      /** Path */
+      /**
+       * Path
+       * @description filesystem path to the model file or directory
+       */
       path: string;
-      /** Name */
+      /**
+       * Name
+       * @description model name
+       */
       name: string;
-      base: components["schemas"]["invokeai__backend__model_manager__config__BaseModelType"];
+      /** @description base model */
+      base: components["schemas"]["BaseModelType"];
       /**
        * Type
        * @default controlnet
@@ -2622,13 +2626,23 @@ export type components = {
        * @description current fasthash of model contents
        */
       current_hash?: string | null;
-      /** Description */
+      /**
+       * Description
+       * @description human readable description of the model
+       */
       description?: string | null;
       /**
        * Source
-       * @description Model download source (URL or repo_id)
+       * @description model original source (path, URL or repo_id)
        */
       source?: string | null;
+      /**
+       * Last Modified
+       * @description timestamp for modification time
+       */
+      last_modified?: number | null;
+      /** @default */
+      repo_variant?: components["schemas"]["ModelRepoVariant"] | null;
     };
     /**
      * ControlNet
@@ -2695,64 +2709,16 @@ export type components = {
        */
       type: "controlnet";
     };
-    /** ControlNetModelCheckpointConfig */
-    ControlNetModelCheckpointConfig: {
-      /** Model Name */
-      model_name: string;
-      base_model: components["schemas"]["invokeai__backend__model_management__models__base__BaseModelType"];
-      /**
-       * Model Type
-       * @default controlnet
-       * @constant
-       */
-      model_type: "controlnet";
-      /** Path */
-      path: string;
-      /** Description */
-      description?: string | null;
-      /**
-       * Model Format
-       * @constant
-       */
-      model_format: "checkpoint";
-      error?: components["schemas"]["ModelError"] | null;
-      /** Config */
-      config: string;
-    };
-    /** ControlNetModelDiffusersConfig */
-    ControlNetModelDiffusersConfig: {
-      /** Model Name */
-      model_name: string;
-      base_model: components["schemas"]["invokeai__backend__model_management__models__base__BaseModelType"];
-      /**
-       * Model Type
-       * @default controlnet
-       * @constant
-       */
-      model_type: "controlnet";
-      /** Path */
-      path: string;
-      /** Description */
-      description?: string | null;
-      /**
-       * Model Format
-       * @constant
-       */
-      model_format: "diffusers";
-      error?: components["schemas"]["ModelError"] | null;
-    };
     /**
      * ControlNetModelField
      * @description ControlNet model field
      */
     ControlNetModelField: {
       /**
-       * Model Name
-       * @description Name of the ControlNet model
+       * Key
+       * @description Model config record key for the ControlNet model
        */
-      model_name: string;
-      /** @description Base model */
-      base_model: components["schemas"]["invokeai__backend__model_management__models__base__BaseModelType"];
+      key: string;
     };
     /**
      * ControlOutput
@@ -4246,7 +4212,7 @@ export type components = {
        * @description The nodes in this graph
        */
       nodes?: {
-        [key: string]: components["schemas"]["ImageCropInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["DepthAnythingImageProcessorInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["DWOpenposeImageProcessorInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["GraphInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["ColorMapImageProcessorInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["IdealSizeInvocation"];
+        [key: string]: components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["GraphInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["ColorMapImageProcessorInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["DWOpenposeImageProcessorInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["DepthAnythingImageProcessorInvocation"];
       };
       /**
        * Edges
@@ -4283,7 +4249,7 @@ export type components = {
        * @description The results of node executions
        */
       results: {
-        [key: string]: components["schemas"]["MetadataOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["SDXLLoraLoaderOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["VAEOutput"] | components["schemas"]["LoraLoaderOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["GraphInvocationOutput"] | components["schemas"]["String2Output"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["LatentsOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["ClipSkipInvocationOutput"];
+        [key: string]: components["schemas"]["ImageCollectionOutput"] | components["schemas"]["LatentsOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["MetadataOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["SDXLLoraLoaderOutput"] | components["schemas"]["String2Output"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["VAEOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["GraphInvocationOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["LoraLoaderOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["ClipSkipInvocationOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["CLIPOutput"];
       };
       /**
        * Errors
@@ -4477,11 +4443,18 @@ export type components = {
      * @description Model config for IP Adaptor format models.
      */
     IPAdapterConfig: {
-      /** Path */
+      /**
+       * Path
+       * @description filesystem path to the model file or directory
+       */
       path: string;
-      /** Name */
+      /**
+       * Name
+       * @description model name
+       */
       name: string;
-      base: components["schemas"]["invokeai__backend__model_manager__config__BaseModelType"];
+      /** @description base model */
+      base: components["schemas"]["BaseModelType"];
       /**
        * Type
        * @default ip_adapter
@@ -4509,13 +4482,23 @@ export type components = {
        * @description current fasthash of model contents
        */
       current_hash?: string | null;
-      /** Description */
+      /**
+       * Description
+       * @description human readable description of the model
+       */
       description?: string | null;
       /**
        * Source
-       * @description Model download source (URL or repo_id)
+       * @description model original source (path, URL or repo_id)
        */
       source?: string | null;
+      /**
+       * Last Modified
+       * @description timestamp for modification time
+       */
+      last_modified?: number | null;
+      /** Image Encoder Model Id */
+      image_encoder_model_id: string;
     };
     /** IPAdapterField */
     IPAdapterField: {
@@ -4632,34 +4615,10 @@ export type components = {
     /** IPAdapterModelField */
     IPAdapterModelField: {
       /**
-       * Model Name
-       * @description Name of the IP-Adapter model
+       * Key
+       * @description Key to the IP-Adapter model
        */
-      model_name: string;
-      /** @description Base model */
-      base_model: components["schemas"]["invokeai__backend__model_management__models__base__BaseModelType"];
-    };
-    /** IPAdapterModelInvokeAIConfig */
-    IPAdapterModelInvokeAIConfig: {
-      /** Model Name */
-      model_name: string;
-      base_model: components["schemas"]["invokeai__backend__model_management__models__base__BaseModelType"];
-      /**
-       * Model Type
-       * @default ip_adapter
-       * @constant
-       */
-      model_type: "ip_adapter";
-      /** Path */
-      path: string;
-      /** Description */
-      description?: string | null;
-      /**
-       * Model Format
-       * @constant
-       */
-      model_format: "invokeai";
-      error?: components["schemas"]["ModelError"] | null;
+      key: string;
     };
     /** IPAdapterOutput */
     IPAdapterOutput: {
@@ -6562,11 +6521,18 @@ export type components = {
      * @description Model config for LoRA/Lycoris models.
      */
     LoRAConfig: {
-      /** Path */
+      /**
+       * Path
+       * @description filesystem path to the model file or directory
+       */
       path: string;
-      /** Name */
+      /**
+       * Name
+       * @description model name
+       */
       name: string;
-      base: components["schemas"]["invokeai__backend__model_manager__config__BaseModelType"];
+      /** @description base model */
+      base: components["schemas"]["BaseModelType"];
       /**
        * Type
        * @default lora
@@ -6594,13 +6560,21 @@ export type components = {
        * @description current fasthash of model contents
        */
       current_hash?: string | null;
-      /** Description */
+      /**
+       * Description
+       * @description human readable description of the model
+       */
       description?: string | null;
       /**
        * Source
-       * @description Model download source (URL or repo_id)
+       * @description model original source (path, URL or repo_id)
        */
       source?: string | null;
+      /**
+       * Last Modified
+       * @description timestamp for modification time
+       */
+      last_modified?: number | null;
     };
     /**
      * LoRAMetadataField
@@ -6615,42 +6589,17 @@ export type components = {
        */
       weight: number;
     };
-    /** LoRAModelConfig */
-    LoRAModelConfig: {
-      /** Model Name */
-      model_name: string;
-      base_model: components["schemas"]["invokeai__backend__model_management__models__base__BaseModelType"];
-      /**
-       * Model Type
-       * @default lora
-       * @constant
-       */
-      model_type: "lora";
-      /** Path */
-      path: string;
-      /** Description */
-      description?: string | null;
-      model_format: components["schemas"]["LoRAModelFormat"];
-      error?: components["schemas"]["ModelError"] | null;
-    };
     /**
      * LoRAModelField
      * @description LoRA model field
      */
     LoRAModelField: {
       /**
-       * Model Name
-       * @description Name of the LoRA model
+       * Key
+       * @description LoRA model key
        */
-      model_name: string;
-      /** @description Base model */
-      base_model: components["schemas"]["invokeai__backend__model_management__models__base__BaseModelType"];
+      key: string;
     };
-    /**
-     * LoRAModelFormat
-     * @enum {string}
-     */
-    LoRAModelFormat: "lycoris" | "diffusers";
     /**
      * LocalModelSource
      * @description A local file or directory path.
@@ -6678,16 +6627,12 @@ export type components = {
     /** LoraInfo */
     LoraInfo: {
       /**
-       * Model Name
-       * @description Info to load submodel
+       * Key
+       * @description Key of model as returned by ModelRecordServiceBase.get_model()
        */
-      model_name: string;
-      /** @description Base model */
-      base_model: components["schemas"]["invokeai__backend__model_management__models__base__BaseModelType"];
+      key: string;
       /** @description Info to load submodel */
-      model_type: components["schemas"]["invokeai__backend__model_management__models__base__ModelType"];
-      /** @description Info to load submodel */
-      submodel?: components["schemas"]["SubModelType"] | null;
+      submodel_type?: components["schemas"]["SubModelType"] | null;
       /**
        * Weight
        * @description Lora's weight which to use when apply to model
@@ -6771,11 +6716,18 @@ export type components = {
      * @description Model config for main checkpoint models.
      */
     MainCheckpointConfig: {
-      /** Path */
+      /**
+       * Path
+       * @description filesystem path to the model file or directory
+       */
       path: string;
-      /** Name */
+      /**
+       * Name
+       * @description model name
+       */
       name: string;
-      base: components["schemas"]["invokeai__backend__model_manager__config__BaseModelType"];
+      /** @description base model */
+      base: components["schemas"]["BaseModelType"];
       /**
        * Type
        * @default main
@@ -6804,17 +6756,32 @@ export type components = {
        * @description current fasthash of model contents
        */
       current_hash?: string | null;
-      /** Description */
+      /**
+       * Description
+       * @description human readable description of the model
+       */
       description?: string | null;
       /**
        * Source
-       * @description Model download source (URL or repo_id)
+       * @description model original source (path, URL or repo_id)
        */
       source?: string | null;
+      /**
+       * Last Modified
+       * @description timestamp for modification time
+       */
+      last_modified?: number | null;
       /** Vae */
       vae?: string | null;
       /** @default normal */
-      variant?: components["schemas"]["invokeai__backend__model_manager__config__ModelVariantType"];
+      variant?: components["schemas"]["ModelVariantType"];
+      /** @default epsilon */
+      prediction_type?: components["schemas"]["SchedulerPredictionType"];
+      /**
+       * Upcast Attention
+       * @default false
+       */
+      upcast_attention?: boolean;
       /**
        * Ztsnr Training
        * @default false
@@ -6831,11 +6798,18 @@ export type components = {
      * @description Model config for main diffusers models.
      */
     MainDiffusersConfig: {
-      /** Path */
+      /**
+       * Path
+       * @description filesystem path to the model file or directory
+       */
       path: string;
-      /** Name */
+      /**
+       * Name
+       * @description model name
+       */
       name: string;
-      base: components["schemas"]["invokeai__backend__model_manager__config__BaseModelType"];
+      /** @description base model */
+      base: components["schemas"]["BaseModelType"];
       /**
        * Type
        * @default main
@@ -6864,29 +6838,39 @@ export type components = {
        * @description current fasthash of model contents
        */
       current_hash?: string | null;
-      /** Description */
+      /**
+       * Description
+       * @description human readable description of the model
+       */
       description?: string | null;
       /**
        * Source
-       * @description Model download source (URL or repo_id)
+       * @description model original source (path, URL or repo_id)
        */
       source?: string | null;
+      /**
+       * Last Modified
+       * @description timestamp for modification time
+       */
+      last_modified?: number | null;
       /** Vae */
       vae?: string | null;
       /** @default normal */
-      variant?: components["schemas"]["invokeai__backend__model_manager__config__ModelVariantType"];
-      /**
-       * Ztsnr Training
-       * @default false
-       */
-      ztsnr_training?: boolean;
+      variant?: components["schemas"]["ModelVariantType"];
       /** @default epsilon */
-      prediction_type?: components["schemas"]["invokeai__backend__model_manager__config__SchedulerPredictionType"];
+      prediction_type?: components["schemas"]["SchedulerPredictionType"];
       /**
        * Upcast Attention
        * @default false
        */
       upcast_attention?: boolean;
+      /**
+       * Ztsnr Training
+       * @default false
+       */
+      ztsnr_training?: boolean;
+      /** @default */
+      repo_variant?: components["schemas"]["ModelRepoVariant"] | null;
     };
     /**
      * MainModelField
@@ -6894,14 +6878,10 @@ export type components = {
      */
     MainModelField: {
       /**
-       * Model Name
-       * @description Name of the model
+       * Key
+       * @description Model key
        */
-      model_name: string;
-      /** @description Base model */
-      base_model: components["schemas"]["invokeai__backend__model_management__models__base__BaseModelType"];
-      /** @description Model Type */
-      model_type: components["schemas"]["invokeai__backend__model_management__models__base__ModelType"];
+      key: string;
     };
     /**
      * Main Model
@@ -7153,38 +7133,6 @@ export type components = {
        */
       type: "merge_metadata";
     };
-    /** MergeModelsBody */
-    MergeModelsBody: {
-      /**
-       * Model Names
-       * @description model name
-       */
-      model_names: string[];
-      /**
-       * Merged Model Name
-       * @description Name of destination model
-       */
-      merged_model_name: string | null;
-      /**
-       * Alpha
-       * @description Alpha weighting strength to apply to 2d and 3d models
-       * @default 0.5
-       */
-      alpha?: number | null;
-      /** @description Interpolation method */
-      interp: components["schemas"]["MergeInterpolationMethod"] | null;
-      /**
-       * Force
-       * @description Force merging of models created with different versions of diffusers
-       * @default false
-       */
-      force?: boolean | null;
-      /**
-       * Merge Dest Directory
-       * @description Save the merged model to the designated directory (with 'merged_model_name' appended)
-       */
-      merge_dest_directory?: string | null;
-    };
     /**
      * Merge Tiles to Image
      * @description Merge multiple tile images into a single image.
@@ -7459,11 +7407,6 @@ export type components = {
        */
       type: "mlsd_image_processor";
     };
-    /**
-     * ModelError
-     * @constant
-     */
-    ModelError: "not_found";
     /**
      * ModelFormat
      * @description Storage format of model.
@@ -7473,16 +7416,12 @@ export type components = {
     /** ModelInfo */
     ModelInfo: {
       /**
-       * Model Name
-       * @description Info to load submodel
+       * Key
+       * @description Key of model as returned by ModelRecordServiceBase.get_model()
        */
-      model_name: string;
-      /** @description Base model */
-      base_model: components["schemas"]["invokeai__backend__model_management__models__base__BaseModelType"];
+      key: string;
       /** @description Info to load submodel */
-      model_type: components["schemas"]["invokeai__backend__model_management__models__base__ModelType"];
-      /** @description Info to load submodel */
-      submodel?: components["schemas"]["SubModelType"] | null;
+      submodel_type?: components["schemas"]["SubModelType"] | null;
     };
     /**
      * ModelInstallJob
@@ -7508,7 +7447,7 @@ export type components = {
        * Config Out
        * @description After successful installation, this will hold the configuration object.
        */
-      config_out?: (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["ONNXSD1Config"] | components["schemas"]["ONNXSD2Config"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"] | null;
+      config_out?: (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["ONNXSD1Config"] | components["schemas"]["ONNXSD2Config"] | components["schemas"]["ONNXSDXLConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"] | null;
       /**
        * Inplace
        * @description Leave model in its current location; otherwise install under models directory
@@ -7587,7 +7526,7 @@ export type components = {
      * @description Various hugging face variants on the diffusers format.
      * @enum {string}
      */
-    ModelRepoVariant: "default" | "fp16" | "fp32" | "onnx" | "openvino" | "flax";
+    ModelRepoVariant: "" | "fp16" | "fp32" | "onnx" | "openvino" | "flax";
     /**
      * ModelSummary
      * @description A short summary of models for UI listing purposes.
@@ -7599,9 +7538,9 @@ export type components = {
        */
       key: string;
       /** @description model type */
-      type: components["schemas"]["invokeai__backend__model_manager__config__ModelType"];
+      type: components["schemas"]["ModelType"];
       /** @description base model */
-      base: components["schemas"]["invokeai__backend__model_manager__config__BaseModelType"];
+      base: components["schemas"]["BaseModelType"];
       /** @description model format */
       format: components["schemas"]["ModelFormat"];
       /**
@@ -7620,6 +7559,26 @@ export type components = {
        */
       tags: string[];
     };
+    /**
+     * ModelType
+     * @description Model type.
+     * @enum {string}
+     */
+    ModelType: "onnx" | "main" | "vae" | "lora" | "controlnet" | "embedding" | "ip_adapter" | "clip_vision" | "t2i_adapter";
+    /**
+     * ModelVariantType
+     * @description Variant type.
+     * @enum {string}
+     */
+    ModelVariantType: "normal" | "inpaint" | "depth";
+    /**
+     * ModelsList
+     * @description Return list of configs.
+     */
+    ModelsList: {
+      /** Models */
+      models: ((components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["ONNXSD1Config"] | components["schemas"]["ONNXSD2Config"] | components["schemas"]["ONNXSDXLConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"])[];
+    };
     /**
      * Multiply Integers
      * @description Multiplies two numbers
@@ -7808,9 +7767,15 @@ export type components = {
      * @description Model config for ONNX format models based on sd-1.
      */
     ONNXSD1Config: {
-      /** Path */
+      /**
+       * Path
+       * @description filesystem path to the model file or directory
+       */
       path: string;
-      /** Name */
+      /**
+       * Name
+       * @description model name
+       */
       name: string;
       /**
        * Base
@@ -7845,38 +7810,52 @@ export type components = {
        * @description current fasthash of model contents
        */
       current_hash?: string | null;
-      /** Description */
+      /**
+       * Description
+       * @description human readable description of the model
+       */
       description?: string | null;
       /**
        * Source
-       * @description Model download source (URL or repo_id)
+       * @description model original source (path, URL or repo_id)
        */
       source?: string | null;
+      /**
+       * Last Modified
+       * @description timestamp for modification time
+       */
+      last_modified?: number | null;
       /** Vae */
       vae?: string | null;
       /** @default normal */
-      variant?: components["schemas"]["invokeai__backend__model_manager__config__ModelVariantType"];
-      /**
-       * Ztsnr Training
-       * @default false
-       */
-      ztsnr_training?: boolean;
+      variant?: components["schemas"]["ModelVariantType"];
       /** @default epsilon */
-      prediction_type?: components["schemas"]["invokeai__backend__model_manager__config__SchedulerPredictionType"];
+      prediction_type?: components["schemas"]["SchedulerPredictionType"];
       /**
        * Upcast Attention
        * @default false
        */
       upcast_attention?: boolean;
+      /**
+       * Ztsnr Training
+       * @default false
+       */
+      ztsnr_training?: boolean;
     };
     /**
      * ONNXSD2Config
      * @description Model config for ONNX format models based on sd-2.
      */
     ONNXSD2Config: {
-      /** Path */
+      /**
+       * Path
+       * @description filesystem path to the model file or directory
+       */
       path: string;
-      /** Name */
+      /**
+       * Name
+       * @description model name
+       */
       name: string;
       /**
        * Base
@@ -7911,78 +7890,117 @@ export type components = {
        * @description current fasthash of model contents
        */
       current_hash?: string | null;
-      /** Description */
+      /**
+       * Description
+       * @description human readable description of the model
+       */
       description?: string | null;
       /**
        * Source
-       * @description Model download source (URL or repo_id)
+       * @description model original source (path, URL or repo_id)
        */
       source?: string | null;
+      /**
+       * Last Modified
+       * @description timestamp for modification time
+       */
+      last_modified?: number | null;
       /** Vae */
       vae?: string | null;
       /** @default normal */
-      variant?: components["schemas"]["invokeai__backend__model_manager__config__ModelVariantType"];
-      /**
-       * Ztsnr Training
-       * @default false
-       */
-      ztsnr_training?: boolean;
+      variant?: components["schemas"]["ModelVariantType"];
       /** @default v_prediction */
-      prediction_type?: components["schemas"]["invokeai__backend__model_manager__config__SchedulerPredictionType"];
+      prediction_type?: components["schemas"]["SchedulerPredictionType"];
       /**
        * Upcast Attention
        * @default true
        */
       upcast_attention?: boolean;
-    };
-    /** ONNXStableDiffusion1ModelConfig */
-    ONNXStableDiffusion1ModelConfig: {
-      /** Model Name */
-      model_name: string;
-      base_model: components["schemas"]["invokeai__backend__model_management__models__base__BaseModelType"];
       /**
-       * Model Type
+       * Ztsnr Training
+       * @default false
+       */
+      ztsnr_training?: boolean;
+    };
+    /**
+     * ONNXSDXLConfig
+     * @description Model config for ONNX format models based on sdxl.
+     */
+    ONNXSDXLConfig: {
+      /**
+       * Path
+       * @description filesystem path to the model file or directory
+       */
+      path: string;
+      /**
+       * Name
+       * @description model name
+       */
+      name: string;
+      /**
+       * Base
+       * @default sdxl
+       * @constant
+       */
+      base?: "sdxl";
+      /**
+       * Type
        * @default onnx
        * @constant
        */
-      model_type: "onnx";
-      /** Path */
-      path: string;
-      /** Description */
+      type?: "onnx";
+      /**
+       * Format
+       * @enum {string}
+       */
+      format: "onnx" | "olive";
+      /**
+       * Key
+       * @description unique key for model
+       * @default <NOKEY>
+       */
+      key?: string;
+      /**
+       * Original Hash
+       * @description original fasthash of model contents
+       */
+      original_hash?: string | null;
+      /**
+       * Current Hash
+       * @description current fasthash of model contents
+       */
+      current_hash?: string | null;
+      /**
+       * Description
+       * @description human readable description of the model
+       */
       description?: string | null;
       /**
-       * Model Format
-       * @constant
+       * Source
+       * @description model original source (path, URL or repo_id)
        */
-      model_format: "onnx";
-      error?: components["schemas"]["ModelError"] | null;
-      variant: components["schemas"]["invokeai__backend__model_management__models__base__ModelVariantType"];
-    };
-    /** ONNXStableDiffusion2ModelConfig */
-    ONNXStableDiffusion2ModelConfig: {
-      /** Model Name */
-      model_name: string;
-      base_model: components["schemas"]["invokeai__backend__model_management__models__base__BaseModelType"];
+      source?: string | null;
       /**
-       * Model Type
-       * @default onnx
-       * @constant
+       * Last Modified
+       * @description timestamp for modification time
        */
-      model_type: "onnx";
-      /** Path */
-      path: string;
-      /** Description */
-      description?: string | null;
+      last_modified?: number | null;
+      /** Vae */
+      vae?: string | null;
+      /** @default normal */
+      variant?: components["schemas"]["ModelVariantType"];
+      /** @default v_prediction */
+      prediction_type?: components["schemas"]["SchedulerPredictionType"];
       /**
-       * Model Format
-       * @constant
+       * Upcast Attention
+       * @default false
        */
-      model_format: "onnx";
-      error?: components["schemas"]["ModelError"] | null;
-      variant: components["schemas"]["invokeai__backend__model_management__models__base__ModelVariantType"];
-      prediction_type: components["schemas"]["invokeai__backend__model_management__models__base__SchedulerPredictionType"];
-      /** Upcast Attention */
-      upcast_attention: boolean;
+      upcast_attention?: boolean;
+      /**
+       * Ztsnr Training
+       * @default false
+       */
+      ztsnr_training?: boolean;
     };
     /** OffsetPaginatedResults[BoardDTO] */
     OffsetPaginatedResults_BoardDTO_: {
@@ -9119,6 +9137,12 @@ export type components = {
        */
       type: "scheduler_output";
     };
+    /**
+     * SchedulerPredictionType
+     * @description Scheduler prediction type.
+     * @enum {string}
+     */
+    SchedulerPredictionType: "epsilon" | "v_prediction" | "sample";
     /**
      * Seamless
      * @description Applies the seamless transformation to the Model UNet and VAE.
@@ -9468,162 +9492,6 @@ export type components = {
        */
       type: "show_image";
     };
-    /** StableDiffusion1ModelCheckpointConfig */
-    StableDiffusion1ModelCheckpointConfig: {
-      /** Model Name */
-      model_name: string;
-      base_model: components["schemas"]["invokeai__backend__model_management__models__base__BaseModelType"];
-      /**
-       * Model Type
-       * @default main
-       * @constant
-       */
-      model_type: "main";
-      /** Path */
-      path: string;
-      /** Description */
-      description?: string | null;
-      /**
-       * Model Format
-       * @constant
-       */
-      model_format: "checkpoint";
-      error?: components["schemas"]["ModelError"] | null;
-      /** Vae */
-      vae?: string | null;
-      /** Config */
-      config: string;
-      variant: components["schemas"]["invokeai__backend__model_management__models__base__ModelVariantType"];
-    };
-    /** StableDiffusion1ModelDiffusersConfig */
-    StableDiffusion1ModelDiffusersConfig: {
-      /** Model Name */
-      model_name: string;
-      base_model: components["schemas"]["invokeai__backend__model_management__models__base__BaseModelType"];
-      /**
-       * Model Type
-       * @default main
-       * @constant
-       */
-      model_type: "main";
-      /** Path */
-      path: string;
-      /** Description */
-      description?: string | null;
-      /**
-       * Model Format
-       * @constant
-       */
-      model_format: "diffusers";
-      error?: components["schemas"]["ModelError"] | null;
-      /** Vae */
-      vae?: string | null;
-      variant: components["schemas"]["invokeai__backend__model_management__models__base__ModelVariantType"];
-    };
-    /** StableDiffusion2ModelCheckpointConfig */
-    StableDiffusion2ModelCheckpointConfig: {
-      /** Model Name */
-      model_name: string;
-      base_model: components["schemas"]["invokeai__backend__model_management__models__base__BaseModelType"];
-      /**
-       * Model Type
-       * @default main
-       * @constant
-       */
-      model_type: "main";
-      /** Path */
-      path: string;
-      /** Description */
-      description?: string | null;
-      /**
-       * Model Format
-       * @constant
-       */
-      model_format: "checkpoint";
-      error?: components["schemas"]["ModelError"] | null;
-      /** Vae */
-      vae?: string | null;
-      /** Config */
-      config: string;
-      variant: components["schemas"]["invokeai__backend__model_management__models__base__ModelVariantType"];
-    };
-    /** StableDiffusion2ModelDiffusersConfig */
-    StableDiffusion2ModelDiffusersConfig: {
-      /** Model Name */
-      model_name: string;
-      base_model: components["schemas"]["invokeai__backend__model_management__models__base__BaseModelType"];
-      /**
-       * Model Type
-       * @default main
-       * @constant
-       */
-      model_type: "main";
-      /** Path */
-      path: string;
-      /** Description */
-      description?: string | null;
-      /**
-       * Model Format
-       * @constant
-       */
-      model_format: "diffusers";
-      error?: components["schemas"]["ModelError"] | null;
-      /** Vae */
-      vae?: string | null;
-      variant: components["schemas"]["invokeai__backend__model_management__models__base__ModelVariantType"];
-    };
-    /** StableDiffusionXLModelCheckpointConfig */
-    StableDiffusionXLModelCheckpointConfig: {
-      /** Model Name */
-      model_name: string;
-      base_model: components["schemas"]["invokeai__backend__model_management__models__base__BaseModelType"];
-      /**
-       * Model Type
-       * @default main
-       * @constant
-       */
-      model_type: "main";
-      /** Path */
-      path: string;
-      /** Description */
-      description?: string | null;
-      /**
-       * Model Format
-       * @constant
-       */
-      model_format: "checkpoint";
-      error?: components["schemas"]["ModelError"] | null;
-      /** Vae */
-      vae?: string | null;
-      /** Config */
-      config: string;
-      variant: components["schemas"]["invokeai__backend__model_management__models__base__ModelVariantType"];
-    };
-    /** StableDiffusionXLModelDiffusersConfig */
-    StableDiffusionXLModelDiffusersConfig: {
-      /** Model Name */
-      model_name: string;
-      base_model: components["schemas"]["invokeai__backend__model_management__models__base__BaseModelType"];
-      /**
-       * Model Type
-       * @default main
-       * @constant
-       */
-      model_type: "main";
-      /** Path */
-      path: string;
-      /** Description */
-      description?: string | null;
-      /**
-       * Model Format
-       * @constant
-       */
-      model_format: "diffusers";
-      error?: components["schemas"]["ModelError"] | null;
-      /** Vae */
-      vae?: string | null;
-      variant: components["schemas"]["invokeai__backend__model_management__models__base__ModelVariantType"];
-    };
     /**
      * Step Param Easing
      * @description Experimental per-step parameter easing for denoising steps
@@ -10079,6 +9947,7 @@ export type components = {
     };
     /**
      * SubModelType
+     * @description Submodel type.
      * @enum {string}
      */
     SubModelType: "unet" | "text_encoder" | "text_encoder_2" | "tokenizer" | "tokenizer_2" | "vae" | "vae_decoder" | "vae_encoder" | "scheduler" | "safety_checker";
@@ -10216,37 +10085,13 @@ export type components = {
        */
       type: "t2i_adapter";
     };
-    /** T2IAdapterModelDiffusersConfig */
-    T2IAdapterModelDiffusersConfig: {
-      /** Model Name */
-      model_name: string;
-      base_model: components["schemas"]["invokeai__backend__model_management__models__base__BaseModelType"];
-      /**
-       * Model Type
-       * @default t2i_adapter
-       * @constant
-       */
-      model_type: "t2i_adapter";
-      /** Path */
-      path: string;
-      /** Description */
-      description?: string | null;
-      /**
-       * Model Format
-       * @constant
-       */
-      model_format: "diffusers";
-      error?: components["schemas"]["ModelError"] | null;
-    };
     /** T2IAdapterModelField */
     T2IAdapterModelField: {
       /**
-       * Model Name
-       * @description Name of the T2I-Adapter model
+       * Key
+       * @description Model record key for the T2I-Adapter model
        */
-      model_name: string;
-      /** @description Base model */
-      base_model: components["schemas"]["invokeai__backend__model_management__models__base__BaseModelType"];
+      key: string;
     };
     /** T2IAdapterOutput */
     T2IAdapterOutput: {
@@ -10267,11 +10112,18 @@ export type components = {
      * @description Model config for T2I.
      */
     T2IConfig: {
-      /** Path */
+      /**
+       * Path
+       * @description filesystem path to the model file or directory
+       */
       path: string;
-      /** Name */
+      /**
+       * Name
+       * @description model name
+       */
       name: string;
-      base: components["schemas"]["invokeai__backend__model_manager__config__BaseModelType"];
+      /** @description base model */
+      base: components["schemas"]["BaseModelType"];
       /**
        * Type
        * @default t2i_adapter
@@ -10299,13 +10151,21 @@ export type components = {
        * @description current fasthash of model contents
        */
       current_hash?: string | null;
-      /** Description */
+      /**
+       * Description
+       * @description human readable description of the model
+       */
       description?: string | null;
       /**
        * Source
-       * @description Model download source (URL or repo_id)
+       * @description model original source (path, URL or repo_id)
        */
       source?: string | null;
+      /**
+       * Last Modified
+       * @description timestamp for modification time
+       */
+      last_modified?: number | null;
     };
     /** TBLR */
     TBLR: {
@@ -10323,11 +10183,18 @@ export type components = {
      * @description Model config for textual inversion embeddings.
      */
     TextualInversionConfig: {
-      /** Path */
+      /**
+       * Path
+       * @description filesystem path to the model file or directory
+       */
       path: string;
-      /** Name */
+      /**
+       * Name
+       * @description model name
+       */
       name: string;
-      base: components["schemas"]["invokeai__backend__model_manager__config__BaseModelType"];
+      /** @description base model */
+      base: components["schemas"]["BaseModelType"];
       /**
        * Type
        * @default embedding
@@ -10355,32 +10222,21 @@ export type components = {
        * @description current fasthash of model contents
        */
       current_hash?: string | null;
-      /** Description */
+      /**
+       * Description
+       * @description human readable description of the model
+       */
       description?: string | null;
       /**
        * Source
-       * @description Model download source (URL or repo_id)
+       * @description model original source (path, URL or repo_id)
        */
       source?: string | null;
-    };
-    /** TextualInversionModelConfig */
-    TextualInversionModelConfig: {
-      /** Model Name */
-      model_name: string;
-      base_model: components["schemas"]["invokeai__backend__model_management__models__base__BaseModelType"];
       /**
-       * Model Type
-       * @default embedding
-       * @constant
+       * Last Modified
+       * @description timestamp for modification time
        */
-      model_type: "embedding";
-      /** Path */
-      path: string;
-      /** Description */
-      description?: string | null;
-      /** Model Format */
-      model_format: null;
-      error?: components["schemas"]["ModelError"] | null;
+      last_modified?: number | null;
     };
     /** Tile */
     Tile: {
@@ -10546,7 +10402,7 @@ export type components = {
     };
     /**
      * UNetOutput
-     * @description Base class for invocations that output a UNet field
+     * @description Base class for invocations that output a UNet field.
      */
     UNetOutput: {
       /**
@@ -10646,12 +10502,10 @@ export type components = {
      */
     VAEModelField: {
       /**
-       * Model Name
-       * @description Name of the model
+       * Key
+       * @description Model's key
        */
-      model_name: string;
-      /** @description Base model */
-      base_model: components["schemas"]["invokeai__backend__model_management__models__base__BaseModelType"];
+      key: string;
     };
     /**
      * VAEOutput
@@ -10675,11 +10529,18 @@ export type components = {
      * @description Model config for standalone VAE models.
      */
     VaeCheckpointConfig: {
-      /** Path */
+      /**
+       * Path
+       * @description filesystem path to the model file or directory
+       */
       path: string;
-      /** Name */
+      /**
+       * Name
+       * @description model name
+       */
       name: string;
-      base: components["schemas"]["invokeai__backend__model_manager__config__BaseModelType"];
+      /** @description base model */
+      base: components["schemas"]["BaseModelType"];
       /**
        * Type
        * @default vae
@@ -10708,24 +10569,39 @@ export type components = {
        * @description current fasthash of model contents
        */
       current_hash?: string | null;
-      /** Description */
+      /**
+       * Description
+       * @description human readable description of the model
+       */
       description?: string | null;
       /**
        * Source
-       * @description Model download source (URL or repo_id)
+       * @description model original source (path, URL or repo_id)
        */
       source?: string | null;
+      /**
+       * Last Modified
+       * @description timestamp for modification time
+       */
+      last_modified?: number | null;
     };
     /**
      * VaeDiffusersConfig
      * @description Model config for standalone VAE models (diffusers version).
      */
     VaeDiffusersConfig: {
-      /** Path */
+      /**
+       * Path
+       * @description filesystem path to the model file or directory
+       */
       path: string;
-      /** Name */
+      /**
+       * Name
+       * @description model name
+       */
       name: string;
-      base: components["schemas"]["invokeai__backend__model_manager__config__BaseModelType"];
+      /** @description base model */
+      base: components["schemas"]["BaseModelType"];
       /**
        * Type
        * @default vae
@@ -10754,13 +10630,21 @@ export type components = {
        * @description current fasthash of model contents
        */
       current_hash?: string | null;
-      /** Description */
+      /**
+       * Description
+       * @description human readable description of the model
+       */
       description?: string | null;
       /**
        * Source
-       * @description Model download source (URL or repo_id)
+       * @description model original source (path, URL or repo_id)
        */
       source?: string | null;
+      /**
+       * Last Modified
+       * @description timestamp for modification time
+       */
+      last_modified?: number | null;
     };
     /** VaeField */
     VaeField: {
@@ -10806,29 +10690,6 @@ export type components = {
        */
       type: "vae_loader";
     };
-    /** VaeModelConfig */
-    VaeModelConfig: {
-      /** Model Name */
-      model_name: string;
-      base_model: components["schemas"]["invokeai__backend__model_management__models__base__BaseModelType"];
-      /**
-       * Model Type
-       * @default vae
-       * @constant
-       */
-      model_type: "vae";
-      /** Path */
-      path: string;
-      /** Description */
-      description?: string | null;
-      model_format: components["schemas"]["VaeModelFormat"];
-      error?: components["schemas"]["ModelError"] | null;
-    };
-    /**
-     * VaeModelFormat
-     * @enum {string}
-     */
-    VaeModelFormat: "checkpoint" | "diffusers";
     /** ValidationError */
     ValidationError: {
       /** Location */
@@ -11085,63 +10946,6 @@ export type components = {
        */
       type: "zoe_depth_image_processor";
     };
-    /**
-     * ModelsList
-     * @description Return list of configs.
-     */
-    invokeai__app__api__routers__model_records__ModelsList: {
-      /** Models */
-      models: ((components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["ONNXSD1Config"] | components["schemas"]["ONNXSD2Config"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"])[];
-    };
-    /** ModelsList */
-    invokeai__app__api__routers__models__ModelsList: {
-      /** Models */
-      models: (components["schemas"]["ONNXStableDiffusion1ModelConfig"] | components["schemas"]["StableDiffusion1ModelCheckpointConfig"] | components["schemas"]["StableDiffusion1ModelDiffusersConfig"] | components["schemas"]["VaeModelConfig"] | components["schemas"]["LoRAModelConfig"] | components["schemas"]["ControlNetModelCheckpointConfig"] | components["schemas"]["ControlNetModelDiffusersConfig"] | components["schemas"]["TextualInversionModelConfig"] | components["schemas"]["IPAdapterModelInvokeAIConfig"] | components["schemas"]["CLIPVisionModelDiffusersConfig"] | components["schemas"]["T2IAdapterModelDiffusersConfig"] | components["schemas"]["ONNXStableDiffusion2ModelConfig"] | components["schemas"]["StableDiffusion2ModelCheckpointConfig"] | components["schemas"]["StableDiffusion2ModelDiffusersConfig"] | components["schemas"]["StableDiffusionXLModelCheckpointConfig"] | components["schemas"]["StableDiffusionXLModelDiffusersConfig"])[];
-    };
-    /**
-     * BaseModelType
-     * @enum {string}
-     */
-    invokeai__backend__model_management__models__base__BaseModelType: "any" | "sd-1" | "sd-2" | "sdxl" | "sdxl-refiner";
-    /**
-     * ModelType
-     * @enum {string}
-     */
-    invokeai__backend__model_management__models__base__ModelType: "onnx" | "main" | "vae" | "lora" | "controlnet" | "embedding" | "ip_adapter" | "clip_vision" | "t2i_adapter";
-    /**
-     * ModelVariantType
-     * @enum {string}
-     */
-    invokeai__backend__model_management__models__base__ModelVariantType: "normal" | "inpaint" | "depth";
-    /**
-     * SchedulerPredictionType
-     * @enum {string}
-     */
-    invokeai__backend__model_management__models__base__SchedulerPredictionType: "epsilon" | "v_prediction" | "sample";
-    /**
-     * BaseModelType
-     * @description Base model type.
-     * @enum {string}
-     */
-    invokeai__backend__model_manager__config__BaseModelType: "any" | "sd-1" | "sd-2" | "sdxl" | "sdxl-refiner";
-    /**
-     * ModelType
-     * @description Model type.
-     * @enum {string}
-     */
-    invokeai__backend__model_manager__config__ModelType: "onnx" | "main" | "vae" | "lora" | "controlnet" | "embedding" | "ip_adapter" | "clip_vision" | "t2i_adapter";
-    /**
-     * ModelVariantType
-     * @description Variant type.
-     * @enum {string}
-     */
-    invokeai__backend__model_manager__config__ModelVariantType: "normal" | "inpaint" | "depth";
-    /**
-     * SchedulerPredictionType
-     * @description Scheduler prediction type.
-     * @enum {string}
-     */
-    invokeai__backend__model_manager__config__SchedulerPredictionType: "epsilon" | "v_prediction" | "sample";
     /**
      * Classification
      * @description The classification of an Invocation.
@@ -11309,53 +11113,65 @@ export type components = {
      */
     UIType: "SDXLMainModelField" | "SDXLRefinerModelField" | "ONNXModelField" | "VAEModelField" | "LoRAModelField" | "ControlNetModelField" | "IPAdapterModelField" | "SchedulerField" | "AnyField" | "CollectionField" | "CollectionItemField" | "DEPRECATED_Boolean" | "DEPRECATED_Color" | "DEPRECATED_Conditioning" | "DEPRECATED_Control" | "DEPRECATED_Float" | "DEPRECATED_Image" | "DEPRECATED_Integer" | "DEPRECATED_Latents" | "DEPRECATED_String" | "DEPRECATED_BooleanCollection" | "DEPRECATED_ColorCollection" | "DEPRECATED_ConditioningCollection" | "DEPRECATED_ControlCollection" | "DEPRECATED_FloatCollection" | "DEPRECATED_ImageCollection" | "DEPRECATED_IntegerCollection" | "DEPRECATED_LatentsCollection" | "DEPRECATED_StringCollection" | "DEPRECATED_BooleanPolymorphic" | "DEPRECATED_ColorPolymorphic" | "DEPRECATED_ConditioningPolymorphic" | "DEPRECATED_ControlPolymorphic" | "DEPRECATED_FloatPolymorphic" | "DEPRECATED_ImagePolymorphic" | "DEPRECATED_IntegerPolymorphic" | "DEPRECATED_LatentsPolymorphic" | "DEPRECATED_StringPolymorphic" | "DEPRECATED_MainModel" | "DEPRECATED_UNet" | "DEPRECATED_Vae" | "DEPRECATED_CLIP" | "DEPRECATED_Collection" | "DEPRECATED_CollectionItem" | "DEPRECATED_Enum" | "DEPRECATED_WorkflowField" | "DEPRECATED_IsIntermediate" | "DEPRECATED_BoardField" | "DEPRECATED_MetadataItem" | "DEPRECATED_MetadataItemCollection" | "DEPRECATED_MetadataItemPolymorphic" | "DEPRECATED_MetadataDict";
     /**
-     * StableDiffusionXLModelFormat
+     * VaeModelFormat
      * @description An enumeration.
      * @enum {string}
      */
-    StableDiffusionXLModelFormat: "checkpoint" | "diffusers";
-    /**
-     * T2IAdapterModelFormat
-     * @description An enumeration.
-     * @enum {string}
-     */
-    T2IAdapterModelFormat: "diffusers";
-    /**
-     * CLIPVisionModelFormat
-     * @description An enumeration.
-     * @enum {string}
-     */
-    CLIPVisionModelFormat: "diffusers";
-    /**
-     * ControlNetModelFormat
-     * @description An enumeration.
-     * @enum {string}
-     */
-    ControlNetModelFormat: "checkpoint" | "diffusers";
-    /**
-     * StableDiffusion1ModelFormat
-     * @description An enumeration.
-     * @enum {string}
-     */
-    StableDiffusion1ModelFormat: "checkpoint" | "diffusers";
-    /**
-     * IPAdapterModelFormat
-     * @description An enumeration.
-     * @enum {string}
-     */
-    IPAdapterModelFormat: "invokeai";
+    VaeModelFormat: "checkpoint" | "diffusers";
     /**
      * StableDiffusion2ModelFormat
      * @description An enumeration.
      * @enum {string}
      */
     StableDiffusion2ModelFormat: "checkpoint" | "diffusers";
+    /**
+     * CLIPVisionModelFormat
+     * @description An enumeration.
+     * @enum {string}
+     */
+    CLIPVisionModelFormat: "diffusers";
+    /**
+     * StableDiffusionXLModelFormat
+     * @description An enumeration.
+     * @enum {string}
+     */
+    StableDiffusionXLModelFormat: "checkpoint" | "diffusers";
+    /**
+     * StableDiffusion1ModelFormat
+     * @description An enumeration.
+     * @enum {string}
+     */
+    StableDiffusion1ModelFormat: "checkpoint" | "diffusers";
+    /**
+     * ControlNetModelFormat
+     * @description An enumeration.
+     * @enum {string}
+     */
+    ControlNetModelFormat: "checkpoint" | "diffusers";
     /**
      * StableDiffusionOnnxModelFormat
      * @description An enumeration.
      * @enum {string}
      */
     StableDiffusionOnnxModelFormat: "olive" | "onnx";
+    /**
+     * T2IAdapterModelFormat
+     * @description An enumeration.
+     * @enum {string}
+     */
+    T2IAdapterModelFormat: "diffusers";
+    /**
+     * LoRAModelFormat
+     * @description An enumeration.
+     * @enum {string}
+     */
+    LoRAModelFormat: "lycoris" | "diffusers";
+    /**
+     * IPAdapterModelFormat
+     * @description An enumeration.
+     * @enum {string}
+     */
+    IPAdapterModelFormat: "invokeai";
   };
   responses: never;
   parameters: never;
@@ -11425,328 +11241,6 @@ export type operations = {
       };
     };
   };
-  /**
-   * List Models
-   * @description Gets a list of models
-   */
-  list_models: {
-    parameters: {
-      query?: {
-        /** @description Base models to include */
-        base_models?: components["schemas"]["invokeai__backend__model_management__models__base__BaseModelType"][] | null;
-        /** @description The type of model to get */
-        model_type?: components["schemas"]["invokeai__backend__model_management__models__base__ModelType"] | null;
-      };
-    };
-    responses: {
-      /** @description Successful Response */
-      200: {
-        content: {
-          "application/json": components["schemas"]["invokeai__app__api__routers__models__ModelsList"];
-        };
-      };
-      /** @description Validation Error */
-      422: {
-        content: {
-          "application/json": components["schemas"]["HTTPValidationError"];
-        };
-      };
-    };
-  };
-  /**
-   * Delete Model
-   * @description Delete Model
-   */
-  del_model: {
-    parameters: {
-      path: {
-        /** @description Base model */
-        base_model: components["schemas"]["invokeai__backend__model_management__models__base__BaseModelType"];
-        /** @description The type of model */
-        model_type: components["schemas"]["invokeai__backend__model_management__models__base__ModelType"];
-        /** @description model name */
-        model_name: string;
-      };
-    };
-    responses: {
-      /** @description Model deleted successfully */
-      204: {
-        content: never;
-      };
-      /** @description Model not found */
-      404: {
-        content: never;
-      };
-      /** @description Validation Error */
-      422: {
-        content: {
-          "application/json": components["schemas"]["HTTPValidationError"];
-        };
-      };
-    };
-  };
-  /**
-   * Update Model
-   * @description Update model contents with a new config. If the model name or base fields are changed, then the model is renamed.
-   */
-  update_model: {
-    parameters: {
-      path: {
-        /** @description Base model */
-        base_model: components["schemas"]["invokeai__backend__model_management__models__base__BaseModelType"];
-        /** @description The type of model */
-        model_type: components["schemas"]["invokeai__backend__model_management__models__base__ModelType"];
-        /** @description model name */
-        model_name: string;
-      };
-    };
-    requestBody: {
-      content: {
-        "application/json": components["schemas"]["ONNXStableDiffusion1ModelConfig"] | components["schemas"]["StableDiffusion1ModelCheckpointConfig"] | components["schemas"]["StableDiffusion1ModelDiffusersConfig"] | components["schemas"]["VaeModelConfig"] | components["schemas"]["LoRAModelConfig"] | components["schemas"]["ControlNetModelCheckpointConfig"] | components["schemas"]["ControlNetModelDiffusersConfig"] | components["schemas"]["TextualInversionModelConfig"] | components["schemas"]["IPAdapterModelInvokeAIConfig"] | components["schemas"]["CLIPVisionModelDiffusersConfig"] | components["schemas"]["T2IAdapterModelDiffusersConfig"] | components["schemas"]["ONNXStableDiffusion2ModelConfig"] | components["schemas"]["StableDiffusion2ModelCheckpointConfig"] | components["schemas"]["StableDiffusion2ModelDiffusersConfig"] | components["schemas"]["StableDiffusionXLModelCheckpointConfig"] | components["schemas"]["StableDiffusionXLModelDiffusersConfig"];
-      };
-    };
-    responses: {
-      /** @description The model was updated successfully */
-      200: {
-        content: {
-          "application/json": components["schemas"]["ONNXStableDiffusion1ModelConfig"] | components["schemas"]["StableDiffusion1ModelCheckpointConfig"] | components["schemas"]["StableDiffusion1ModelDiffusersConfig"] | components["schemas"]["VaeModelConfig"] | components["schemas"]["LoRAModelConfig"] | components["schemas"]["ControlNetModelCheckpointConfig"] | components["schemas"]["ControlNetModelDiffusersConfig"] | components["schemas"]["TextualInversionModelConfig"] | components["schemas"]["IPAdapterModelInvokeAIConfig"] | components["schemas"]["CLIPVisionModelDiffusersConfig"] | components["schemas"]["T2IAdapterModelDiffusersConfig"] | components["schemas"]["ONNXStableDiffusion2ModelConfig"] | components["schemas"]["StableDiffusion2ModelCheckpointConfig"] | components["schemas"]["StableDiffusion2ModelDiffusersConfig"] | components["schemas"]["StableDiffusionXLModelCheckpointConfig"] | components["schemas"]["StableDiffusionXLModelDiffusersConfig"];
-        };
-      };
-      /** @description Bad request */
-      400: {
-        content: never;
-      };
-      /** @description The model could not be found */
-      404: {
-        content: never;
-      };
-      /** @description There is already a model corresponding to the new name */
-      409: {
-        content: never;
-      };
-      /** @description Validation Error */
-      422: {
-        content: {
-          "application/json": components["schemas"]["HTTPValidationError"];
-        };
-      };
-    };
-  };
-  /**
-   * Import Model
-   * @description Add a model using its local path, repo_id, or remote URL. Model characteristics will be probed and configured automatically
-   */
-  import_model: {
-    requestBody: {
-      content: {
-        "application/json": components["schemas"]["Body_import_model"];
-      };
-    };
-    responses: {
-      /** @description The model imported successfully */
-      201: {
-        content: {
-          "application/json": components["schemas"]["ONNXStableDiffusion1ModelConfig"] | components["schemas"]["StableDiffusion1ModelCheckpointConfig"] | components["schemas"]["StableDiffusion1ModelDiffusersConfig"] | components["schemas"]["VaeModelConfig"] | components["schemas"]["LoRAModelConfig"] | components["schemas"]["ControlNetModelCheckpointConfig"] | components["schemas"]["ControlNetModelDiffusersConfig"] | components["schemas"]["TextualInversionModelConfig"] | components["schemas"]["IPAdapterModelInvokeAIConfig"] | components["schemas"]["CLIPVisionModelDiffusersConfig"] | components["schemas"]["T2IAdapterModelDiffusersConfig"] | components["schemas"]["ONNXStableDiffusion2ModelConfig"] | components["schemas"]["StableDiffusion2ModelCheckpointConfig"] | components["schemas"]["StableDiffusion2ModelDiffusersConfig"] | components["schemas"]["StableDiffusionXLModelCheckpointConfig"] | components["schemas"]["StableDiffusionXLModelDiffusersConfig"];
-        };
-      };
-      /** @description The model could not be found */
-      404: {
-        content: never;
-      };
-      /** @description There is already a model corresponding to this path or repo_id */
-      409: {
-        content: never;
-      };
-      /** @description Unrecognized file/folder format */
-      415: {
-        content: never;
-      };
-      /** @description Validation Error */
-      422: {
-        content: {
-          "application/json": components["schemas"]["HTTPValidationError"];
-        };
-      };
-      /** @description The model appeared to import successfully, but could not be found in the model manager */
-      424: {
-        content: never;
-      };
-    };
-  };
-  /**
-   * Add Model
-   * @description Add a model using the configuration information appropriate for its type. Only local models can be added by path
-   */
-  add_model: {
-    requestBody: {
-      content: {
-        "application/json": components["schemas"]["ONNXStableDiffusion1ModelConfig"] | components["schemas"]["StableDiffusion1ModelCheckpointConfig"] | components["schemas"]["StableDiffusion1ModelDiffusersConfig"] | components["schemas"]["VaeModelConfig"] | components["schemas"]["LoRAModelConfig"] | components["schemas"]["ControlNetModelCheckpointConfig"] | components["schemas"]["ControlNetModelDiffusersConfig"] | components["schemas"]["TextualInversionModelConfig"] | components["schemas"]["IPAdapterModelInvokeAIConfig"] | components["schemas"]["CLIPVisionModelDiffusersConfig"] | components["schemas"]["T2IAdapterModelDiffusersConfig"] | components["schemas"]["ONNXStableDiffusion2ModelConfig"] | components["schemas"]["StableDiffusion2ModelCheckpointConfig"] | components["schemas"]["StableDiffusion2ModelDiffusersConfig"] | components["schemas"]["StableDiffusionXLModelCheckpointConfig"] | components["schemas"]["StableDiffusionXLModelDiffusersConfig"];
-      };
-    };
-    responses: {
-      /** @description The model added successfully */
-      201: {
-        content: {
-          "application/json": components["schemas"]["ONNXStableDiffusion1ModelConfig"] | components["schemas"]["StableDiffusion1ModelCheckpointConfig"] | components["schemas"]["StableDiffusion1ModelDiffusersConfig"] | components["schemas"]["VaeModelConfig"] | components["schemas"]["LoRAModelConfig"] | components["schemas"]["ControlNetModelCheckpointConfig"] | components["schemas"]["ControlNetModelDiffusersConfig"] | components["schemas"]["TextualInversionModelConfig"] | components["schemas"]["IPAdapterModelInvokeAIConfig"] | components["schemas"]["CLIPVisionModelDiffusersConfig"] | components["schemas"]["T2IAdapterModelDiffusersConfig"] | components["schemas"]["ONNXStableDiffusion2ModelConfig"] | components["schemas"]["StableDiffusion2ModelCheckpointConfig"] | components["schemas"]["StableDiffusion2ModelDiffusersConfig"] | components["schemas"]["StableDiffusionXLModelCheckpointConfig"] | components["schemas"]["StableDiffusionXLModelDiffusersConfig"];
-        };
-      };
-      /** @description The model could not be found */
-      404: {
-        content: never;
-      };
-      /** @description There is already a model corresponding to this path or repo_id */
-      409: {
-        content: never;
-      };
-      /** @description Validation Error */
-      422: {
-        content: {
-          "application/json": components["schemas"]["HTTPValidationError"];
-        };
-      };
-      /** @description The model appeared to add successfully, but could not be found in the model manager */
-      424: {
-        content: never;
-      };
-    };
-  };
-  /**
-   * Convert Model
-   * @description Convert a checkpoint model into a diffusers model, optionally saving to the indicated destination directory, or `models` if none.
-   */
-  convert_model: {
-    parameters: {
-      query?: {
-        /** @description Save the converted model to the designated directory */
-        convert_dest_directory?: string | null;
-      };
-      path: {
-        /** @description Base model */
-        base_model: components["schemas"]["invokeai__backend__model_management__models__base__BaseModelType"];
-        /** @description The type of model */
-        model_type: components["schemas"]["invokeai__backend__model_management__models__base__ModelType"];
-        /** @description model name */
-        model_name: string;
-      };
-    };
-    responses: {
-      /** @description Model converted successfully */
-      200: {
-        content: {
-          "application/json": components["schemas"]["ONNXStableDiffusion1ModelConfig"] | components["schemas"]["StableDiffusion1ModelCheckpointConfig"] | components["schemas"]["StableDiffusion1ModelDiffusersConfig"] | components["schemas"]["VaeModelConfig"] | components["schemas"]["LoRAModelConfig"] | components["schemas"]["ControlNetModelCheckpointConfig"] | components["schemas"]["ControlNetModelDiffusersConfig"] | components["schemas"]["TextualInversionModelConfig"] | components["schemas"]["IPAdapterModelInvokeAIConfig"] | components["schemas"]["CLIPVisionModelDiffusersConfig"] | components["schemas"]["T2IAdapterModelDiffusersConfig"] | components["schemas"]["ONNXStableDiffusion2ModelConfig"] | components["schemas"]["StableDiffusion2ModelCheckpointConfig"] | components["schemas"]["StableDiffusion2ModelDiffusersConfig"] | components["schemas"]["StableDiffusionXLModelCheckpointConfig"] | components["schemas"]["StableDiffusionXLModelDiffusersConfig"];
-        };
-      };
-      /** @description Bad request */
-      400: {
-        content: never;
-      };
-      /** @description Model not found */
-      404: {
-        content: never;
-      };
-      /** @description Validation Error */
-      422: {
-        content: {
-          "application/json": components["schemas"]["HTTPValidationError"];
-        };
-      };
-    };
-  };
-  /** Search For Models */
-  search_for_models: {
-    parameters: {
-      query: {
-        /** @description Directory path to search for models */
-        search_path: string;
-      };
-    };
-    responses: {
-      /** @description Directory searched successfully */
-      200: {
-        content: {
-          "application/json": string[];
-        };
-      };
-      /** @description Invalid directory path */
-      404: {
-        content: never;
-      };
-      /** @description Validation Error */
-      422: {
-        content: {
-          "application/json": components["schemas"]["HTTPValidationError"];
-        };
-      };
-    };
-  };
-  /**
-   * List Ckpt Configs
-   * @description Return a list of the legacy checkpoint configuration files stored in `ROOT/configs/stable-diffusion`, relative to ROOT.
-   */
-  list_ckpt_configs: {
-    responses: {
-      /** @description paths retrieved successfully */
-      200: {
-        content: {
-          "application/json": string[];
-        };
-      };
-    };
-  };
-  /**
-   * Sync To Config
-   * @description Call after making changes to models.yaml, autoimport directories or models directory to synchronize
-   * in-memory data structures with disk data structures.
-   */
-  sync_to_config: {
-    responses: {
-      /** @description synchronization successful */
-      201: {
-        content: {
-          "application/json": boolean;
-        };
-      };
-    };
-  };
-  /**
-   * Merge Models
-   * @description Convert a checkpoint model into a diffusers model
-   */
-  merge_models: {
-    parameters: {
-      path: {
-        /** @description Base model */
-        base_model: components["schemas"]["invokeai__backend__model_management__models__base__BaseModelType"];
-      };
-    };
-    requestBody: {
-      content: {
-        "application/json": components["schemas"]["Body_merge_models"];
-      };
-    };
-    responses: {
-      /** @description Model converted successfully */
-      200: {
-        content: {
-          "application/json": components["schemas"]["ONNXStableDiffusion1ModelConfig"] | components["schemas"]["StableDiffusion1ModelCheckpointConfig"] | components["schemas"]["StableDiffusion1ModelDiffusersConfig"] | components["schemas"]["VaeModelConfig"] | components["schemas"]["LoRAModelConfig"] | components["schemas"]["ControlNetModelCheckpointConfig"] | components["schemas"]["ControlNetModelDiffusersConfig"] | components["schemas"]["TextualInversionModelConfig"] | components["schemas"]["IPAdapterModelInvokeAIConfig"] | components["schemas"]["CLIPVisionModelDiffusersConfig"] | components["schemas"]["T2IAdapterModelDiffusersConfig"] | components["schemas"]["ONNXStableDiffusion2ModelConfig"] | components["schemas"]["StableDiffusion2ModelCheckpointConfig"] | components["schemas"]["StableDiffusion2ModelDiffusersConfig"] | components["schemas"]["StableDiffusionXLModelCheckpointConfig"] | components["schemas"]["StableDiffusionXLModelDiffusersConfig"];
-        };
-      };
-      /** @description Incompatible models */
-      400: {
-        content: never;
-      };
-      /** @description One or more models not found */
-      404: {
-        content: never;
-      };
-      /** @description Validation Error */
-      422: {
-        content: {
-          "application/json": components["schemas"]["HTTPValidationError"];
-        };
-      };
-    };
-  };
   /**
    * List Model Records
    * @description Get a list of models.
@@ -11755,9 +11249,9 @@ export type operations = {
     parameters: {
       query?: {
         /** @description Base models to include */
-        base_models?: components["schemas"]["invokeai__backend__model_manager__config__BaseModelType"][] | null;
+        base_models?: components["schemas"]["BaseModelType"][] | null;
         /** @description The type of model to get */
-        model_type?: components["schemas"]["invokeai__backend__model_manager__config__ModelType"] | null;
+        model_type?: components["schemas"]["ModelType"] | null;
         /** @description Exact match on the name of the model */
         model_name?: string | null;
         /** @description Exact match on the format of the model (e.g. 'diffusers') */
@@ -11768,7 +11262,7 @@ export type operations = {
       /** @description Successful Response */
       200: {
         content: {
-          "application/json": components["schemas"]["invokeai__app__api__routers__model_records__ModelsList"];
+          "application/json": components["schemas"]["ModelsList"];
         };
       };
       /** @description Validation Error */
@@ -11791,10 +11285,10 @@ export type operations = {
       };
     };
     responses: {
-      /** @description Success */
+      /** @description The model configuration was retrieved successfully */
       200: {
         content: {
-          "application/json": (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["ONNXSD1Config"] | components["schemas"]["ONNXSD2Config"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
+          "application/json": (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["ONNXSD1Config"] | components["schemas"]["ONNXSD2Config"] | components["schemas"]["ONNXSDXLConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
         };
       };
       /** @description Bad request */
@@ -11857,14 +11351,26 @@ export type operations = {
     };
     requestBody: {
       content: {
-        "application/json": (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["ONNXSD1Config"] | components["schemas"]["ONNXSD2Config"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
+        /**
+         * @example {
+         *   "path": "/path/to/model",
+         *   "name": "model_name",
+         *   "base": "sd-1",
+         *   "type": "main",
+         *   "format": "checkpoint",
+         *   "config": "configs/stable-diffusion/v1-inference.yaml",
+         *   "description": "Model description",
+         *   "variant": "normal"
+         * }
+         */
+        "application/json": (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["ONNXSD1Config"] | components["schemas"]["ONNXSD2Config"] | components["schemas"]["ONNXSDXLConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
       };
     };
     responses: {
       /** @description The model was updated successfully */
       200: {
         content: {
-          "application/json": (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["ONNXSD1Config"] | components["schemas"]["ONNXSD2Config"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
+          "application/json": (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["ONNXSD1Config"] | components["schemas"]["ONNXSD2Config"] | components["schemas"]["ONNXSDXLConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
         };
       };
       /** @description Bad request */
@@ -11929,7 +11435,7 @@ export type operations = {
       };
     };
     responses: {
-      /** @description Success */
+      /** @description The model metadata was retrieved successfully */
       200: {
         content: {
           "application/json": (components["schemas"]["BaseMetadata"] | components["schemas"]["HuggingFaceMetadata"] | components["schemas"]["CivitaiMetadata"]) | null;
@@ -11980,7 +11486,7 @@ export type operations = {
       /** @description Successful Response */
       200: {
         content: {
-          "application/json": components["schemas"]["invokeai__app__api__routers__model_records__ModelsList"];
+          "application/json": components["schemas"]["ModelsList"];
         };
       };
       /** @description Validation Error */
@@ -11998,14 +11504,26 @@ export type operations = {
   add_model_record: {
     requestBody: {
       content: {
-        "application/json": (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["ONNXSD1Config"] | components["schemas"]["ONNXSD2Config"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
+        /**
+         * @example {
+         *   "path": "/path/to/model",
+         *   "name": "model_name",
+         *   "base": "sd-1",
+         *   "type": "main",
+         *   "format": "checkpoint",
+         *   "config": "configs/stable-diffusion/v1-inference.yaml",
+         *   "description": "Model description",
+         *   "variant": "normal"
+         * }
+         */
+        "application/json": (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["ONNXSD1Config"] | components["schemas"]["ONNXSD2Config"] | components["schemas"]["ONNXSDXLConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
       };
     };
     responses: {
       /** @description The model added successfully */
       201: {
         content: {
-          "application/json": (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["ONNXSD1Config"] | components["schemas"]["ONNXSD2Config"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
+          "application/json": (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["ONNXSD1Config"] | components["schemas"]["ONNXSD2Config"] | components["schemas"]["ONNXSDXLConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
         };
       };
       /** @description There is already a model corresponding to this path or repo_id */
@@ -12025,79 +11543,49 @@ export type operations = {
     };
   };
   /**
-   * List Model Install Jobs
-   * @description Return list of model install jobs.
-   */
-  list_model_install_jobs: {
-    responses: {
-      /** @description Successful Response */
-      200: {
-        content: {
-          "application/json": components["schemas"]["ModelInstallJob"][];
-        };
-      };
-    };
-  };
-  /**
-   * Import Model
-   * @description Add a model using its local path, repo_id, or remote URL.
+   * Heuristic Import
+   * @description Install a model using a string identifier.
+   *
+   * `source` can be any of the following.
+   *
+   * 1. A path on the local filesystem ('C:\users\fred\model.safetensors')
+   * 2. A Url pointing to a single downloadable model file
+   * 3. A HuggingFace repo_id with any of the following formats:
+   *    - model/name
+   *    - model/name:fp16:vae
+   *    - model/name::vae          -- use default precision
+   *    - model/name:fp16:path/to/model.safetensors
+   *    - model/name::path/to/model.safetensors
+   *
+   * `config` is an optional dict containing model configuration values that will override
+   * the ones that are probed automatically.
+   *
+   * `access_token` is an optional access token for use with Urls that require
+   * authentication.
    *
    * Models will be downloaded, probed, configured and installed in a
    * series of background threads. The return object has `status` attribute
    * that can be used to monitor progress.
    *
-   * The source object is a discriminated Union of LocalModelSource,
-   * HFModelSource and URLModelSource. Set the "type" field to the
-   * appropriate value:
-   *
-   * * To install a local path using LocalModelSource, pass a source of form:
-   *   `{
-   *     "type": "local",
-   *     "path": "/path/to/model",
-   *     "inplace": false
-   *   }`
-   *    The "inplace" flag, if true, will register the model in place in its
-   *    current filesystem location. Otherwise, the model will be copied
-   *    into the InvokeAI models directory.
-   *
-   * * To install a HuggingFace repo_id using HFModelSource, pass a source of form:
-   *   `{
-   *     "type": "hf",
-   *     "repo_id": "stabilityai/stable-diffusion-2.0",
-   *     "variant": "fp16",
-   *     "subfolder": "vae",
-   *     "access_token": "f5820a918aaf01"
-   *   }`
-   *  The `variant`, `subfolder` and `access_token` fields are optional.
-   *
-   * * To install a remote model using an arbitrary URL, pass:
-   *   `{
-   *     "type": "url",
-   *     "url": "http://www.civitai.com/models/123456",
-   *     "access_token": "f5820a918aaf01"
-   *   }`
-   * The `access_token` field is optonal
-   *
-   * The model's configuration record will be probed and filled in
-   * automatically.  To override the default guesses, pass "metadata"
-   * with a Dict containing the attributes you wish to override.
-   *
-   * Installation occurs in the background. Either use list_model_install_jobs()
-   * to poll for completion, or listen on the event bus for the following events:
-   *
-   *   "model_install_running"
-   *   "model_install_completed"
-   *   "model_install_error"
-   *
-   * On successful completion, the event's payload will contain the field "key"
-   * containing the installed ID of the model. On an error, the event's payload
-   * will contain the fields "error_type" and "error" describing the nature of the
-   * error and its traceback, respectively.
+   * See the documentation for `import_model_record` for more information on
+   * interpreting the job information returned by this route.
    */
-  import_model_record: {
-    requestBody: {
+  heuristic_import_model: {
+    parameters: {
+      query: {
+        source: string;
+        access_token?: string | null;
+      };
+    };
+    requestBody?: {
       content: {
-        "application/json": components["schemas"]["Body_import_model_record"];
+        /**
+         * @example {
+         *   "name": "modelT",
+         *   "description": "antique cars"
+         * }
+         */
+        "application/json": Record<string, never> | null;
       };
     };
     responses: {
@@ -12127,6 +11615,132 @@ export type operations = {
       };
     };
   };
+  /**
+   * Import Model
+   * @description Install a model using its local path, repo_id, or remote URL.
+   *
+   * Models will be downloaded, probed, configured and installed in a
+   * series of background threads. The return object has `status` attribute
+   * that can be used to monitor progress.
+   *
+   * The source object is a discriminated Union of LocalModelSource,
+   * HFModelSource and URLModelSource. Set the "type" field to the
+   * appropriate value:
+   *
+   * * To install a local path using LocalModelSource, pass a source of form:
+   *   ```
+   *   {
+   *     "type": "local",
+   *     "path": "/path/to/model",
+   *     "inplace": false
+   *   }
+   *   ```
+   *   The "inplace" flag, if true, will register the model in place in its
+   *   current filesystem location. Otherwise, the model will be copied
+   *   into the InvokeAI models directory.
+   *
+   * * To install a HuggingFace repo_id using HFModelSource, pass a source of form:
+   *   ```
+   *   {
+   *     "type": "hf",
+   *     "repo_id": "stabilityai/stable-diffusion-2.0",
+   *     "variant": "fp16",
+   *     "subfolder": "vae",
+   *     "access_token": "f5820a918aaf01"
+   *   }
+   *   ```
+   *   The `variant`, `subfolder` and `access_token` fields are optional.
+   *
+   * * To install a remote model using an arbitrary URL, pass:
+   *   ```
+   *   {
+   *     "type": "url",
+   *     "url": "http://www.civitai.com/models/123456",
+   *     "access_token": "f5820a918aaf01"
+   *   }
+   *   ```
+   *   The `access_token` field is optonal
+   *
+   * The model's configuration record will be probed and filled in
+   * automatically.  To override the default guesses, pass "metadata"
+   * with a Dict containing the attributes you wish to override.
+   *
+   * Installation occurs in the background. Either use list_model_install_jobs()
+   * to poll for completion, or listen on the event bus for the following events:
+   *
+   *   * "model_install_running"
+   *   * "model_install_completed"
+   *   * "model_install_error"
+   *
+   * On successful completion, the event's payload will contain the field "key"
+   * containing the installed ID of the model. On an error, the event's payload
+   * will contain the fields "error_type" and "error" describing the nature of the
+   * error and its traceback, respectively.
+   */
+  import_model: {
+    requestBody: {
+      content: {
+        "application/json": components["schemas"]["Body_import_model"];
+      };
+    };
+    responses: {
+      /** @description The model imported successfully */
+      201: {
+        content: {
+          "application/json": components["schemas"]["ModelInstallJob"];
+        };
+      };
+      /** @description There is already a model corresponding to this path or repo_id */
+      409: {
+        content: never;
+      };
+      /** @description Unrecognized file/folder format */
+      415: {
+        content: never;
+      };
+      /** @description Validation Error */
+      422: {
+        content: {
+          "application/json": components["schemas"]["HTTPValidationError"];
+        };
+      };
+      /** @description The model appeared to import successfully, but could not be found in the model manager */
+      424: {
+        content: never;
+      };
+    };
+  };
+  /**
+   * List Model Install Jobs
+   * @description Return the list of model install jobs.
+   *
+   * Install jobs have a numeric `id`, a `status`, and other fields that provide information on
+   * the nature of the job and its progress. The `status` is one of:
+   *
+   * * "waiting" -- Job is waiting in the queue to run
+   * * "downloading" -- Model file(s) are downloading
+   * * "running" -- Model has downloaded and the model probing and registration process is running
+   * * "completed" -- Installation completed successfully
+   * * "error" -- An error occurred. Details will be in the "error_type" and "error" fields.
+   * * "cancelled" -- Job was cancelled before completion.
+   *
+   * Once completed, information about the model such as its size, base
+   * model, type, and metadata can be retrieved from the `config_out`
+   * field. For multi-file models such as diffusers, information on individual files
+   * can be retrieved from `download_parts`.
+   *
+   * See the example and schema below for more information.
+   */
+  list_model_install_jobs: {
+    responses: {
+      /** @description Successful Response */
+      200: {
+        content: {
+          "application/json": components["schemas"]["ModelInstallJob"][];
+        };
+      };
+    };
+  };
   /**
    * Prune Model Install Jobs
    * @description Prune all completed and errored jobs from the install job list.
@@ -12151,7 +11765,8 @@ export type operations = {
   };
   /**
    * Get Model Install Job
-   * @description Return model install job corresponding to the given source.
+   * @description Return model install job corresponding to the given source. See the documentation for 'List Model Install Jobs'
+   * for information on the format of the return value.
    */
   get_model_install_job: {
     parameters: {
@@ -12234,16 +11849,59 @@ export type operations = {
       };
     };
   };
+  /**
+   * Convert Model
+   * @description Permanently convert a model into diffusers format, replacing the safetensors version.
+   * Note that during the conversion process the key and model hash will change.
+   * The return value is the model configuration for the converted model.
+   */
+  convert_model: {
+    parameters: {
+      path: {
+        /** @description Unique key of the safetensors main model to convert to diffusers format. */
+        key: string;
+      };
+    };
+    responses: {
+      /** @description Model converted successfully */
+      200: {
+        content: {
+          "application/json": (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["ONNXSD1Config"] | components["schemas"]["ONNXSD2Config"] | components["schemas"]["ONNXSDXLConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
+        };
+      };
+      /** @description Bad request */
+      400: {
+        content: never;
+      };
+      /** @description Model not found */
+      404: {
+        content: never;
+      };
+      /** @description There is already a model registered at this location */
+      409: {
+        content: never;
+      };
+      /** @description Validation Error */
+      422: {
+        content: {
+          "application/json": components["schemas"]["HTTPValidationError"];
+        };
+      };
+    };
+  };
   /**
    * Merge
-   * @description Merge diffusers models.
-   *
-   *     keys: List of 2-3 model keys to merge together. All models must use the same base type.
-   *     merged_model_name: Name for the merged model [Concat model names]
-   *     alpha: Alpha value (0.0-1.0). Higher values give more weight to the second model [0.5]
-   *     force: If true, force the merge even if the models were generated by different versions of the diffusers library [False]
-   *     interp: Interpolation method. One of "weighted_sum", "sigmoid", "inv_sigmoid" or "add_difference" [weighted_sum]
-   *     merge_dest_directory: Specify a directory to store the merged model in [models directory]
+   * @description Merge diffusers models. The process is controlled by a set parameters provided in the body of the request.
+   * ```
+   * Argument                Description [default]
+   * --------               ----------------------
+   * keys                   List of 2-3 model keys to merge together. All models must use the same base type.
+   * merged_model_name      Name for the merged model [Concat model names]
+   * alpha                  Alpha value (0.0-1.0). Higher values give more weight to the second model [0.5]
+   * force                  If true, force the merge even if the models were generated by different versions of the diffusers library [False]
+   * interp                 Interpolation method. One of "weighted_sum", "sigmoid", "inv_sigmoid" or "add_difference" [weighted_sum]
+   * merge_dest_directory   Specify a directory to store the merged model in [models directory]
+   * ```
    */
   merge: {
     requestBody: {
@@ -12252,12 +11910,24 @@ export type operations = {
       };
     };
     responses: {
-      /** @description Successful Response */
+      /** @description Model converted successfully */
       200: {
         content: {
-          "application/json": (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["ONNXSD1Config"] | components["schemas"]["ONNXSD2Config"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
+          "application/json": (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["ONNXSD1Config"] | components["schemas"]["ONNXSD2Config"] | components["schemas"]["ONNXSDXLConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
         };
       };
+      /** @description Bad request */
+      400: {
+        content: never;
+      };
+      /** @description Model not found */
+      404: {
+        content: never;
+      };
+      /** @description There is already a model registered at this location */
+      409: {
+        content: never;
+      };
       /** @description Validation Error */
       422: {
         content: {

From cb804e75ed51ff7762be315e5857211f7fe44e35 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Thu, 15 Feb 2024 22:16:11 +1100
Subject: [PATCH 136/411] tests(ui): enable vitest type testing

This is useful for the zod schemas and types we have created to match the backend.
---
 invokeai/frontend/web/.gitignore      | 3 +++
 invokeai/frontend/web/package.json    | 1 +
 invokeai/frontend/web/pnpm-lock.yaml  | 7 +++++++
 invokeai/frontend/web/vite.config.mts | 5 ++++-
 4 files changed, 15 insertions(+), 1 deletion(-)

diff --git a/invokeai/frontend/web/.gitignore b/invokeai/frontend/web/.gitignore
index 8e7ebc76a1..3e8a372bc7 100644
--- a/invokeai/frontend/web/.gitignore
+++ b/invokeai/frontend/web/.gitignore
@@ -41,3 +41,6 @@ stats.html
 # Yalc
 .yalc
 yalc.lock
+
+# vitest
+tsconfig.vitest-temp.json
\ No newline at end of file
diff --git a/invokeai/frontend/web/package.json b/invokeai/frontend/web/package.json
index b2838e538c..cea13350d2 100644
--- a/invokeai/frontend/web/package.json
+++ b/invokeai/frontend/web/package.json
@@ -154,6 +154,7 @@
     "rollup-plugin-visualizer": "^5.12.0",
     "storybook": "^7.6.10",
     "ts-toolbelt": "^9.6.0",
+    "tsafe": "^1.6.6",
     "typescript": "^5.3.3",
     "vite": "^5.0.12",
     "vite-plugin-css-injected-by-js": "^3.3.1",
diff --git a/invokeai/frontend/web/pnpm-lock.yaml b/invokeai/frontend/web/pnpm-lock.yaml
index f3bf68cf1d..0ec2e47a0c 100644
--- a/invokeai/frontend/web/pnpm-lock.yaml
+++ b/invokeai/frontend/web/pnpm-lock.yaml
@@ -300,6 +300,9 @@ devDependencies:
   ts-toolbelt:
     specifier: ^9.6.0
     version: 9.6.0
+  tsafe:
+    specifier: ^1.6.6
+    version: 1.6.6
   typescript:
     specifier: ^5.3.3
     version: 5.3.3
@@ -13505,6 +13508,10 @@ packages:
     resolution: {integrity: sha512-nsZd8ZeNUzukXPlJmTBwUAuABDe/9qtVDelJeT/qW0ow3ZS3BsQJtNkan1802aM9Uf68/Y8ljw86Hu0h5IUW3w==}
     dev: true
 
+  /tsafe@1.6.6:
+    resolution: {integrity: sha512-gzkapsdbMNwBnTIjgO758GujLCj031IgHK/PKr2mrmkCSJMhSOR5FeOuSxKLMUoYc0vAA4RGEYYbjt/v6afD3g==}
+    dev: true
+
   /tsconfck@3.0.1(typescript@5.3.3):
     resolution: {integrity: sha512-7ppiBlF3UEddCLeI1JRx5m2Ryq+xk4JrZuq4EuYXykipebaq1dV0Fhgr1hb7CkmHt32QSgOZlcqVLEtHBG4/mg==}
     engines: {node: ^18 || >=20}
diff --git a/invokeai/frontend/web/vite.config.mts b/invokeai/frontend/web/vite.config.mts
index 325c6467de..f4dbae7123 100644
--- a/invokeai/frontend/web/vite.config.mts
+++ b/invokeai/frontend/web/vite.config.mts
@@ -84,7 +84,10 @@ export default defineConfig(({ mode }) => {
       },
     },
     test: {
-      //
+      typecheck: {
+        enabled: true,
+        ignoreSourceErrors: true,
+      },
     },
   };
 });

From fc107ed7113f1eca1ace560e2b1bcede17d65770 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Thu, 15 Feb 2024 22:16:55 +1100
Subject: [PATCH 137/411] tests(ui): add type tests

---
 .../src/features/nodes/types/common.test-d.ts | 69 +++++++++++++++++++
 .../features/nodes/types/workflow.test-d.ts   | 18 +++++
 2 files changed, 87 insertions(+)
 create mode 100644 invokeai/frontend/web/src/features/nodes/types/common.test-d.ts
 create mode 100644 invokeai/frontend/web/src/features/nodes/types/workflow.test-d.ts

diff --git a/invokeai/frontend/web/src/features/nodes/types/common.test-d.ts b/invokeai/frontend/web/src/features/nodes/types/common.test-d.ts
new file mode 100644
index 0000000000..7f28e864a1
--- /dev/null
+++ b/invokeai/frontend/web/src/features/nodes/types/common.test-d.ts
@@ -0,0 +1,69 @@
+import type {
+  BaseModel,
+  BoardField,
+  Classification,
+  CLIPField,
+  ColorField,
+  ControlField,
+  ControlNetModelField,
+  ImageField,
+  ImageOutput,
+  IPAdapterField,
+  IPAdapterModelField,
+  LoraInfo,
+  LoRAModelField,
+  MainModelField,
+  ModelInfo,
+  ModelType,
+  ProgressImage,
+  SchedulerField,
+  SDXLRefinerModelField,
+  SubModelType,
+  T2IAdapterField,
+  T2IAdapterModelField,
+  UNetField,
+  VAEField,
+} from 'features/nodes/types/common';
+import type { S } from 'services/api/types';
+import type { Equals, Extends } from 'tsafe';
+import { assert } from 'tsafe';
+import { describe, test } from 'vitest';
+
+/**
+ * These types originate from the server and are recreated as zod schemas manually, for use at runtime.
+ * The tests ensure that the types are correctly recreated.
+ */
+
+describe('Common types', () => {
+  // Complex field types
+  test('ImageField', () => assert<Equals<ImageField, S['ImageField']>>());
+  test('BoardField', () => assert<Equals<BoardField, S['BoardField']>>());
+  test('ColorField', () => assert<Equals<ColorField, S['ColorField']>>());
+  test('SchedulerField', () => assert<Equals<SchedulerField, NonNullable<S['SchedulerInvocation']['scheduler']>>>());
+  test('UNetField', () => assert<Extends<S['UNetField'], UNetField>>());
+  test('CLIPField', () => assert<Extends<S['ClipField'], CLIPField>>());
+  test('MainModelField', () => assert<Equals<MainModelField, S['MainModelField']>>());
+  test('SDXLRefinerModelField', () => assert<Equals<SDXLRefinerModelField, S['MainModelField']>>());
+  test('VAEField', () => assert<Extends<S['VaeField'], VAEField>>());
+  test('ControlField', () => assert<Equals<ControlField, S['ControlField']>>());
+  // @ts-expect-error TODO(psyche): fix types
+  test('IPAdapterField', () => assert<Extends<IPAdapterField, S['IPAdapterField']>>());
+  test('T2IAdapterField', () => assert<Equals<T2IAdapterField, S['T2IAdapterField']>>());
+  test('LoRAModelField', () => assert<Equals<LoRAModelField, S['LoRAModelField']>>());
+  test('ControlNetModelField', () => assert<Equals<ControlNetModelField, S['ControlNetModelField']>>());
+  test('IPAdapterModelField', () => assert<Equals<IPAdapterModelField, S['IPAdapterModelField']>>());
+  test('T2IAdapterModelField', () => assert<Equals<T2IAdapterModelField, S['T2IAdapterModelField']>>());
+
+  // Model component types
+  test('BaseModel', () => assert<Equals<BaseModel, S['BaseModelType']>>());
+  test('ModelType', () => assert<Equals<ModelType, S['ModelType']>>());
+  test('SubModelType', () => assert<Equals<SubModelType, S['SubModelType']>>());
+  test('ModelInfo', () => assert<Equals<ModelInfo, S['ModelInfo']>>());
+
+  // Misc types
+  test('LoraInfo', () => assert<Extends<S['LoraInfo'], LoraInfo>>());
+  // @ts-expect-error TODO(psyche): There is no `ProgressImage` in the server types yet
+  test('ProgressImage', () => assert<Equals<ProgressImage, S['ProgressImage']>>());
+  test('ImageOutput', () => assert<Equals<ImageOutput, S['ImageOutput']>>());
+  test('Classification', () => assert<Equals<Classification, S['Classification']>>());
+});
diff --git a/invokeai/frontend/web/src/features/nodes/types/workflow.test-d.ts b/invokeai/frontend/web/src/features/nodes/types/workflow.test-d.ts
new file mode 100644
index 0000000000..7cb1ea230c
--- /dev/null
+++ b/invokeai/frontend/web/src/features/nodes/types/workflow.test-d.ts
@@ -0,0 +1,18 @@
+import type { WorkflowCategory, WorkflowV3, XYPosition } from 'features/nodes/types/workflow';
+import type * as ReactFlow from 'reactflow';
+import type { S } from 'services/api/types';
+import type { Equals, Extends } from 'tsafe';
+import { assert } from 'tsafe';
+import { describe, test } from 'vitest';
+
+/**
+ * These types originate from the server and are recreated as zod schemas manually, for use at runtime.
+ * The tests ensure that the types are correctly recreated.
+ */
+
+describe('Workflow types', () => {
+  test('XYPosition', () => assert<Equals<XYPosition, ReactFlow.XYPosition>>());
+  test('WorkflowCategory', () => assert<Equals<WorkflowCategory, S['WorkflowCategory']>>());
+  // @ts-expect-error TODO(psyche): Need to revise server types!
+  test('WorkflowV3', () => assert<Extends<WorkflowV3, S['Workflow']>>());
+});

From b7ba65fef4f29c2e47e680c97d2d4552a0bfc90a Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Thu, 15 Feb 2024 22:17:16 +1100
Subject: [PATCH 138/411] fix(ui): update model types

---
 .../web/src/features/nodes/types/common.ts    | 31 ++++++++++---------
 1 file changed, 16 insertions(+), 15 deletions(-)

diff --git a/invokeai/frontend/web/src/features/nodes/types/common.ts b/invokeai/frontend/web/src/features/nodes/types/common.ts
index b524474379..ef579fce8c 100644
--- a/invokeai/frontend/web/src/features/nodes/types/common.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/common.ts
@@ -52,27 +52,29 @@ export type SchedulerField = z.infer<typeof zSchedulerField>;
 
 // #region Model-related schemas
 export const zBaseModel = z.enum(['any', 'sd-1', 'sd-2', 'sdxl', 'sdxl-refiner']);
-export const zModelType = z.enum(['main', 'vae', 'lora', 'controlnet', 'embedding']);
+export const zModelType = z.enum([
+  'main',
+  'vae',
+  'lora',
+  'controlnet',
+  'embedding',
+  'ip_adapter',
+  'clip_vision',
+  't2i_adapter',
+  'onnx', // TODO(psyche): Remove this when removed from backend
+]);
 export const zModelName = z.string().min(3);
 export const zModelIdentifier = z.object({
-  model_name: zModelName,
-  base_model: zBaseModel,
+  key: z.string().min(1),
 });
 export type BaseModel = z.infer<typeof zBaseModel>;
 export type ModelType = z.infer<typeof zModelType>;
 export type ModelIdentifier = z.infer<typeof zModelIdentifier>;
 
-export const zMainModelField = z.object({
-  model_name: zModelName,
-  base_model: zBaseModel,
-  model_type: z.literal('main'),
-});
-export const zSDXLRefinerModelField = z.object({
-  model_name: z.string().min(1),
-  base_model: z.literal('sdxl-refiner'),
-  model_type: z.literal('main'),
-});
+export const zMainModelField = zModelIdentifier;
 export type MainModelField = z.infer<typeof zMainModelField>;
+
+export const zSDXLRefinerModelField = zModelIdentifier;
 export type SDXLRefinerModelField = z.infer<typeof zSDXLRefinerModelField>;
 
 export const zSubModelType = z.enum([
@@ -92,8 +94,7 @@ export type SubModelType = z.infer<typeof zSubModelType>;
 export const zVAEModelField = zModelIdentifier;
 
 export const zModelInfo = zModelIdentifier.extend({
-  model_type: zModelType,
-  submodel: zSubModelType.optional(),
+  submodel_type: zSubModelType.nullish(),
 });
 export type ModelInfo = z.infer<typeof zModelInfo>;
 

From 6df3c450e8955a4112b074eb6b9ef20d23e8350a Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Fri, 16 Feb 2024 22:51:47 +1100
Subject: [PATCH 139/411] fix(nodes): fix t2i adapter model loading

---
 invokeai/app/invocations/latent.py | 11 ++++++-----
 1 file changed, 6 insertions(+), 5 deletions(-)

diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py
index 5dd0eb074d..1f21b539dc 100644
--- a/invokeai/app/invocations/latent.py
+++ b/invokeai/app/invocations/latent.py
@@ -509,19 +509,20 @@ class DenoiseLatentsInvocation(BaseInvocation):
 
         t2i_adapter_data = []
         for t2i_adapter_field in t2i_adapter:
-            t2i_adapter_model_info = context.models.load(key=t2i_adapter_field.t2i_adapter_model.key)
+            t2i_adapter_model_config = context.models.get_config(key=t2i_adapter_field.t2i_adapter_model.key)
+            t2i_adapter_loaded_model = context.models.load(key=t2i_adapter_field.t2i_adapter_model.key)
             image = context.images.get_pil(t2i_adapter_field.image.image_name)
 
             # The max_unet_downscale is the maximum amount that the UNet model downscales the latent image internally.
-            if t2i_adapter_model_info.base == BaseModelType.StableDiffusion1:
+            if t2i_adapter_model_config.base == BaseModelType.StableDiffusion1:
                 max_unet_downscale = 8
-            elif t2i_adapter_model_info.base == BaseModelType.StableDiffusionXL:
+            elif t2i_adapter_model_config.base == BaseModelType.StableDiffusionXL:
                 max_unet_downscale = 4
             else:
-                raise ValueError(f"Unexpected T2I-Adapter base model type: '{t2i_adapter_model_info.base}'.")
+                raise ValueError(f"Unexpected T2I-Adapter base model type: '{t2i_adapter_model_config.base}'.")
 
             t2i_adapter_model: T2IAdapter
-            with t2i_adapter_model_info as t2i_adapter_model:
+            with t2i_adapter_loaded_model as t2i_adapter_model:
                 total_downscale_factor = t2i_adapter_model.total_downscale_factor
 
                 # Resize the T2I-Adapter input image.

From dab939f7d17a139a6652c0c525af61d5a900ef4c Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Fri, 16 Feb 2024 18:56:02 +1100
Subject: [PATCH 140/411] feat(ui): update model identifier to be key (wip)

- Update most model identifiers to be `{key: string}` instead of name/base/type. Doesn't change the model select components yet.
- Update model _parameters_, stored in redux, to be `{key: string, base: BaseModel}` - we need to store the base model to be able to check model compatibility. May want to store the whole config? Not sure...
---
 .../frontend/web/.storybook/ReduxInit.tsx     |   8 +-
 .../listeners/enqueueRequestedLinear.ts       |   2 +-
 .../listeners/modelSelected.ts                |  10 +-
 .../listeners/modelsLoaded.ts                 |  43 +--
 .../common/hooks/useGroupedModelCombobox.ts   |   6 +-
 .../src/common/hooks/useIsReadyToEnqueue.ts   |   2 +-
 .../web/src/common/hooks/useModelCombobox.ts  |   6 +-
 .../src/features/canvas/store/canvasSlice.ts  |   2 +-
 .../parameters/ParamControlAdapterModel.tsx   |  17 +-
 .../hooks/useAddControlAdapter.ts             |   4 +-
 .../store/controlAdaptersSlice.ts             |   6 +-
 .../features/embedding/EmbeddingSelect.tsx    |   8 +-
 .../ImageMetadataActions.tsx                  |  14 +-
 .../src/features/lora/components/LoRACard.tsx |   2 +-
 .../src/features/lora/components/LoRAList.tsx |   2 +-
 .../features/lora/components/LoRASelect.tsx   |   6 +-
 .../web/src/features/lora/store/loraSlice.ts  |  35 ++-
 .../subpanels/ModelManagerPanel.tsx           |  10 +-
 .../ModelManagerPanel/CheckpointModelEdit.tsx |   4 +-
 .../ModelManagerPanel/DiffusersModelEdit.tsx  |   4 +-
 .../ModelManagerPanel/LoRAModelEdit.tsx       |  14 +-
 .../subpanels/ModelManagerPanel/ModelList.tsx |   6 +-
 .../ModelManagerPanel/ModelListItem.tsx       |   4 +-
 .../ControlNetModelFieldInputComponent.tsx    |   4 +-
 .../IPAdapterModelFieldInputComponent.tsx     |   4 +-
 .../inputs/LoRAModelFieldInputComponent.tsx   |   4 +-
 .../inputs/MainModelFieldInputComponent.tsx   |   4 +-
 .../RefinerModelFieldInputComponent.tsx       |   4 +-
 .../SDXLMainModelFieldInputComponent.tsx      |   4 +-
 .../T2IAdapterModelFieldInputComponent.tsx    |   4 +-
 .../inputs/VAEModelFieldInputComponent.tsx    |   4 +-
 .../web/src/features/nodes/types/common.ts    |  16 +-
 .../util/graph/addControlNetToLinearGraph.ts  |   2 +-
 .../util/graph/addIPAdapterToLinearGraph.ts   |   2 +-
 .../nodes/util/graph/addLoRAsToGraph.ts       |   9 +-
 .../nodes/util/graph/addSDXLLoRAstoGraph.ts   |   9 +-
 .../util/graph/addT2IAdapterToLinearGraph.ts  |   2 +-
 .../nodes/util/graph/buildCanvasGraph.ts      |   8 +-
 .../util/graph/buildLinearBatchConfig.ts      |   2 +-
 .../components/Advanced/ParamClipSkip.tsx     |   6 +-
 .../components/Core/ParamPositivePrompt.tsx   |   2 +-
 .../MainModel/ParamMainModelSelect.tsx        |   4 +-
 .../VAEModel/ParamVAEModelSelect.tsx          |   6 +-
 .../parameters/hooks/useRecallParameters.ts   |  29 +-
 .../parameters/store/generationSlice.ts       |   6 +-
 .../parameters/types/parameterSchemas.ts      |  15 +-
 .../parameters/util/optimalDimension.ts       |   6 +-
 .../ParamSDXLRefinerModelSelect.tsx           |   6 +-
 .../AdvancedSettingsAccordion.tsx             |   3 +-
 .../GenerationSettingsAccordion.tsx           |   5 +-
 .../ImageSettingsAccordion.tsx                |   2 +-
 .../ui/components/ParametersPanel.tsx         |   2 +-
 .../web/src/services/api/endpoints/models.ts  | 284 +++++-------------
 .../frontend/web/src/services/api/types.ts    |  47 ++-
 54 files changed, 267 insertions(+), 453 deletions(-)

diff --git a/invokeai/frontend/web/.storybook/ReduxInit.tsx b/invokeai/frontend/web/.storybook/ReduxInit.tsx
index 55d0132242..7d3f8e0d2b 100644
--- a/invokeai/frontend/web/.storybook/ReduxInit.tsx
+++ b/invokeai/frontend/web/.storybook/ReduxInit.tsx
@@ -10,13 +10,7 @@ export const ReduxInit = memo((props: PropsWithChildren) => {
   const dispatch = useAppDispatch();
   useGlobalModifiersInit();
   useEffect(() => {
-    dispatch(
-      modelChanged({
-        model_name: 'test_model',
-        base_model: 'sd-1',
-        model_type: 'main',
-      })
-    );
+    dispatch(modelChanged({ key: 'test_model', base: 'sd-1' }));
   }, []);
 
   return props.children;
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/enqueueRequestedLinear.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/enqueueRequestedLinear.ts
index e1e13fadbe..d1cb692c98 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/enqueueRequestedLinear.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/enqueueRequestedLinear.ts
@@ -19,7 +19,7 @@ export const addEnqueueRequestedLinear = () => {
 
       let graph;
 
-      if (model && model.base_model === 'sdxl') {
+      if (model && model.base === 'sdxl') {
         if (action.payload.tabName === 'txt2img') {
           graph = buildLinearSDXLTextToImageGraph(state);
         } else {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/modelSelected.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/modelSelected.ts
index 7638c5522a..35e2ad5f9b 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/modelSelected.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/modelSelected.ts
@@ -30,8 +30,8 @@ export const addModelSelectedListener = () => {
 
       const newModel = result.data;
 
-      const newBaseModel = newModel.base_model;
-      const didBaseModelChange = state.generation.model?.base_model !== newBaseModel;
+      const newBaseModel = newModel.base;
+      const didBaseModelChange = state.generation.model?.base !== newBaseModel;
 
       if (didBaseModelChange) {
         // we may need to reset some incompatible submodels
@@ -39,7 +39,7 @@ export const addModelSelectedListener = () => {
 
         // handle incompatible loras
         forEach(state.lora.loras, (lora, id) => {
-          if (lora.base_model !== newBaseModel) {
+          if (lora.base !== newBaseModel) {
             dispatch(loraRemoved(id));
             modelsCleared += 1;
           }
@@ -47,14 +47,14 @@ export const addModelSelectedListener = () => {
 
         // handle incompatible vae
         const { vae } = state.generation;
-        if (vae && vae.base_model !== newBaseModel) {
+        if (vae && vae.base !== newBaseModel) {
           dispatch(vaeSelected(null));
           modelsCleared += 1;
         }
 
         // handle incompatible controlnets
         selectControlAdapterAll(state.controlAdapters).forEach((ca) => {
-          if (ca.model?.base_model !== newBaseModel) {
+          if (ca.model?.base !== newBaseModel) {
             dispatch(controlAdapterIsEnabledChanged({ id: ca.id, isEnabled: false }));
             modelsCleared += 1;
           }
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/modelsLoaded.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/modelsLoaded.ts
index 0ffe88cd07..366644fa68 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/modelsLoaded.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/modelsLoaded.ts
@@ -34,14 +34,7 @@ export const addModelsLoadedListener = () => {
         return;
       }
 
-      const isCurrentModelAvailable = currentModel
-        ? models.some(
-            (m) =>
-              m.model_name === currentModel.model_name &&
-              m.base_model === currentModel.base_model &&
-              m.model_type === currentModel.model_type
-          )
-        : false;
+      const isCurrentModelAvailable = currentModel ? models.some((m) => m.key === currentModel.key) : false;
 
       if (isCurrentModelAvailable) {
         return;
@@ -74,14 +67,7 @@ export const addModelsLoadedListener = () => {
         return;
       }
 
-      const isCurrentModelAvailable = currentModel
-        ? models.some(
-            (m) =>
-              m.model_name === currentModel.model_name &&
-              m.base_model === currentModel.base_model &&
-              m.model_type === currentModel.model_type
-          )
-        : false;
+      const isCurrentModelAvailable = currentModel ? models.some((m) => m.key === currentModel.key) : false;
 
       if (!isCurrentModelAvailable) {
         dispatch(refinerModelChanged(null));
@@ -103,10 +89,7 @@ export const addModelsLoadedListener = () => {
         return;
       }
 
-      const isCurrentVAEAvailable = some(
-        action.payload.entities,
-        (m) => m?.model_name === currentVae?.model_name && m?.base_model === currentVae?.base_model
-      );
+      const isCurrentVAEAvailable = some(action.payload.entities, (m) => m?.key === currentVae?.key);
 
       if (isCurrentVAEAvailable) {
         return;
@@ -140,10 +123,7 @@ export const addModelsLoadedListener = () => {
       const loras = getState().lora.loras;
 
       forEach(loras, (lora, id) => {
-        const isLoRAAvailable = some(
-          action.payload.entities,
-          (m) => m?.model_name === lora?.model_name && m?.base_model === lora?.base_model
-        );
+        const isLoRAAvailable = some(action.payload.entities, (m) => m?.key === lora?.key);
 
         if (isLoRAAvailable) {
           return;
@@ -161,10 +141,7 @@ export const addModelsLoadedListener = () => {
       log.info({ models: action.payload.entities }, `ControlNet models loaded (${action.payload.ids.length})`);
 
       selectAllControlNets(getState().controlAdapters).forEach((ca) => {
-        const isModelAvailable = some(
-          action.payload.entities,
-          (m) => m?.model_name === ca?.model?.model_name && m?.base_model === ca?.model?.base_model
-        );
+        const isModelAvailable = some(action.payload.entities, (m) => m?.key === ca?.model?.key);
 
         if (isModelAvailable) {
           return;
@@ -182,10 +159,7 @@ export const addModelsLoadedListener = () => {
       log.info({ models: action.payload.entities }, `T2I Adapter models loaded (${action.payload.ids.length})`);
 
       selectAllT2IAdapters(getState().controlAdapters).forEach((ca) => {
-        const isModelAvailable = some(
-          action.payload.entities,
-          (m) => m?.model_name === ca?.model?.model_name && m?.base_model === ca?.model?.base_model
-        );
+        const isModelAvailable = some(action.payload.entities, (m) => m?.key === ca?.model?.key);
 
         if (isModelAvailable) {
           return;
@@ -203,10 +177,7 @@ export const addModelsLoadedListener = () => {
       log.info({ models: action.payload.entities }, `IP Adapter models loaded (${action.payload.ids.length})`);
 
       selectAllIPAdapters(getState().controlAdapters).forEach((ca) => {
-        const isModelAvailable = some(
-          action.payload.entities,
-          (m) => m?.model_name === ca?.model?.model_name && m?.base_model === ca?.model?.base_model
-        );
+        const isModelAvailable = some(action.payload.entities, (m) => m?.key === ca?.model?.key);
 
         if (isModelAvailable) {
           return;
diff --git a/invokeai/frontend/web/src/common/hooks/useGroupedModelCombobox.ts b/invokeai/frontend/web/src/common/hooks/useGroupedModelCombobox.ts
index eb55db79ca..875ce1f1c4 100644
--- a/invokeai/frontend/web/src/common/hooks/useGroupedModelCombobox.ts
+++ b/invokeai/frontend/web/src/common/hooks/useGroupedModelCombobox.ts
@@ -5,10 +5,10 @@ import type { GroupBase } from 'chakra-react-select';
 import { groupBy, map, reduce } from 'lodash-es';
 import { useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
-import type { AnyModelConfigEntity } from 'services/api/endpoints/models';
+import type { AnyModelConfig } from 'services/api/endpoints/models';
 import { getModelId } from 'services/api/endpoints/models';
 
-type UseGroupedModelComboboxArg<T extends AnyModelConfigEntity> = {
+type UseGroupedModelComboboxArg<T extends AnyModelConfig> = {
   modelEntities: EntityState<T, string> | undefined;
   selectedModel?: Pick<T, 'base_model' | 'model_name' | 'model_type'> | null;
   onChange: (value: T | null) => void;
@@ -24,7 +24,7 @@ type UseGroupedModelComboboxReturn = {
   noOptionsMessage: () => string;
 };
 
-export const useGroupedModelCombobox = <T extends AnyModelConfigEntity>(
+export const useGroupedModelCombobox = <T extends AnyModelConfig>(
   arg: UseGroupedModelComboboxArg<T>
 ): UseGroupedModelComboboxReturn => {
   const { t } = useTranslation();
diff --git a/invokeai/frontend/web/src/common/hooks/useIsReadyToEnqueue.ts b/invokeai/frontend/web/src/common/hooks/useIsReadyToEnqueue.ts
index baa704e75c..b31efed970 100644
--- a/invokeai/frontend/web/src/common/hooks/useIsReadyToEnqueue.ts
+++ b/invokeai/frontend/web/src/common/hooks/useIsReadyToEnqueue.ts
@@ -105,7 +105,7 @@ const selector = createMemoizedSelector(
               number: i + 1,
             })
           );
-        } else if (ca.model.base_model !== model?.base_model) {
+        } else if (ca.model.base !== model?.base) {
           // This should never happen, just a sanity check
           reasons.push(
             i18n.t('parameters.invoke.incompatibleBaseModelForControlAdapter', {
diff --git a/invokeai/frontend/web/src/common/hooks/useModelCombobox.ts b/invokeai/frontend/web/src/common/hooks/useModelCombobox.ts
index 880b316379..341fed1e47 100644
--- a/invokeai/frontend/web/src/common/hooks/useModelCombobox.ts
+++ b/invokeai/frontend/web/src/common/hooks/useModelCombobox.ts
@@ -3,10 +3,10 @@ import type { EntityState } from '@reduxjs/toolkit';
 import { map } from 'lodash-es';
 import { useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
-import type { AnyModelConfigEntity } from 'services/api/endpoints/models';
+import type { AnyModelConfig } from 'services/api/endpoints/models';
 import { getModelId } from 'services/api/endpoints/models';
 
-type UseModelComboboxArg<T extends AnyModelConfigEntity> = {
+type UseModelComboboxArg<T extends AnyModelConfig> = {
   modelEntities: EntityState<T, string> | undefined;
   selectedModel?: Pick<T, 'base_model' | 'model_name' | 'model_type'> | null;
   onChange: (value: T | null) => void;
@@ -23,7 +23,7 @@ type UseModelComboboxReturn = {
   noOptionsMessage: () => string;
 };
 
-export const useModelCombobox = <T extends AnyModelConfigEntity>(
+export const useModelCombobox = <T extends AnyModelConfig>(
   arg: UseModelComboboxArg<T>
 ): UseModelComboboxReturn => {
   const { t } = useTranslation();
diff --git a/invokeai/frontend/web/src/features/canvas/store/canvasSlice.ts b/invokeai/frontend/web/src/features/canvas/store/canvasSlice.ts
index cd734d3f00..f50d52c1bf 100644
--- a/invokeai/frontend/web/src/features/canvas/store/canvasSlice.ts
+++ b/invokeai/frontend/web/src/features/canvas/store/canvasSlice.ts
@@ -626,7 +626,7 @@ export const canvasSlice = createSlice({
   },
   extraReducers: (builder) => {
     builder.addCase(modelChanged, (state, action) => {
-      if (action.meta.previousModel?.base_model === action.payload?.base_model) {
+      if (action.meta.previousModel?.base === action.payload?.base) {
         // The base model hasn't changed, we don't need to optimize the size
         return;
       }
diff --git a/invokeai/frontend/web/src/features/controlAdapters/components/parameters/ParamControlAdapterModel.tsx b/invokeai/frontend/web/src/features/controlAdapters/components/parameters/ParamControlAdapterModel.tsx
index 13851b143c..a320238445 100644
--- a/invokeai/frontend/web/src/features/controlAdapters/components/parameters/ParamControlAdapterModel.tsx
+++ b/invokeai/frontend/web/src/features/controlAdapters/components/parameters/ParamControlAdapterModel.tsx
@@ -11,12 +11,7 @@ import { selectGenerationSlice } from 'features/parameters/store/generationSlice
 import { pick } from 'lodash-es';
 import { memo, useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
-import type {
-  ControlNetModelConfigEntity,
-  IPAdapterModelConfigEntity,
-  T2IAdapterModelConfigEntity,
-} from 'services/api/endpoints/models';
-import type { AnyModelConfig } from 'services/api/types';
+import type { AnyModelConfig, ControlNetConfig, IPAdapterConfig, T2IAdapterConfig } from 'services/api/types';
 
 type ParamControlAdapterModelProps = {
   id: string;
@@ -29,21 +24,21 @@ const ParamControlAdapterModel = ({ id }: ParamControlAdapterModelProps) => {
   const controlAdapterType = useControlAdapterType(id);
   const model = useControlAdapterModel(id);
   const dispatch = useAppDispatch();
-  const currentBaseModel = useAppSelector((s) => s.generation.model?.base_model);
+  const currentBaseModel = useAppSelector((s) => s.generation.model?.base);
   const mainModel = useAppSelector(selectMainModel);
   const { t } = useTranslation();
 
   const models = useControlAdapterModelEntities(controlAdapterType);
 
   const _onChange = useCallback(
-    (model: ControlNetModelConfigEntity | IPAdapterModelConfigEntity | T2IAdapterModelConfigEntity | null) => {
+    (model: ControlNetConfig | IPAdapterConfig | T2IAdapterConfig | null) => {
       if (!model) {
         return;
       }
       dispatch(
         controlAdapterModelChanged({
           id,
-          model: pick(model, 'base_model', 'model_name'),
+          model: pick(model, 'base', 'key'),
         })
       );
     },
@@ -57,7 +52,7 @@ const ParamControlAdapterModel = ({ id }: ParamControlAdapterModelProps) => {
 
   const getIsDisabled = useCallback(
     (model: AnyModelConfig): boolean => {
-      const isCompatible = currentBaseModel === model.base_model;
+      const isCompatible = currentBaseModel === model.base;
       const hasMainModel = Boolean(currentBaseModel);
       return !hasMainModel || !isCompatible;
     },
@@ -73,7 +68,7 @@ const ParamControlAdapterModel = ({ id }: ParamControlAdapterModelProps) => {
 
   return (
     <Tooltip label={value?.description}>
-      <FormControl isDisabled={!isEnabled} isInvalid={!value || mainModel?.base_model !== model?.base_model}>
+      <FormControl isDisabled={!isEnabled} isInvalid={!value || mainModel?.base !== model?.base}>
         <Combobox
           options={options}
           placeholder={t('controlnet.selectModel')}
diff --git a/invokeai/frontend/web/src/features/controlAdapters/hooks/useAddControlAdapter.ts b/invokeai/frontend/web/src/features/controlAdapters/hooks/useAddControlAdapter.ts
index 51b36968d2..7fd1088767 100644
--- a/invokeai/frontend/web/src/features/controlAdapters/hooks/useAddControlAdapter.ts
+++ b/invokeai/frontend/web/src/features/controlAdapters/hooks/useAddControlAdapter.ts
@@ -6,14 +6,14 @@ import { useCallback, useMemo } from 'react';
 import { useControlAdapterModels } from './useControlAdapterModels';
 
 export const useAddControlAdapter = (type: ControlAdapterType) => {
-  const baseModel = useAppSelector((s) => s.generation.model?.base_model);
+  const baseModel = useAppSelector((s) => s.generation.model?.base);
   const dispatch = useAppDispatch();
 
   const models = useControlAdapterModels(type);
 
   const firstModel = useMemo(() => {
     // prefer to use a model that matches the base model
-    const firstCompatibleModel = models.filter((m) => (baseModel ? m.base_model === baseModel : true))[0];
+    const firstCompatibleModel = models.filter((m) => (baseModel ? m.base === baseModel : true))[0];
 
     if (firstCompatibleModel) {
       return firstCompatibleModel;
diff --git a/invokeai/frontend/web/src/features/controlAdapters/store/controlAdaptersSlice.ts b/invokeai/frontend/web/src/features/controlAdapters/store/controlAdaptersSlice.ts
index 49b07f16a1..fce94ad019 100644
--- a/invokeai/frontend/web/src/features/controlAdapters/store/controlAdaptersSlice.ts
+++ b/invokeai/frontend/web/src/features/controlAdapters/store/controlAdaptersSlice.ts
@@ -236,7 +236,8 @@ export const controlAdaptersSlice = createSlice({
       let processorType: ControlAdapterProcessorType | undefined = undefined;
 
       for (const modelSubstring in CONTROLADAPTER_MODEL_DEFAULT_PROCESSORS) {
-        if (model.model_name.includes(modelSubstring)) {
+        // TODO(MM2): matching modelSubstring to the model key is no longer a valid way to figure out the default processorType
+        if (model.key.includes(modelSubstring)) {
           processorType = CONTROLADAPTER_MODEL_DEFAULT_PROCESSORS[modelSubstring];
           break;
         }
@@ -359,7 +360,8 @@ export const controlAdaptersSlice = createSlice({
         let processorType: ControlAdapterProcessorType | undefined = undefined;
 
         for (const modelSubstring in CONTROLADAPTER_MODEL_DEFAULT_PROCESSORS) {
-          if (cn.model?.model_name.includes(modelSubstring)) {
+          // TODO(MM2): matching modelSubstring to the model key is no longer a valid way to figure out the default processorType
+          if (cn.model?.key.includes(modelSubstring)) {
             processorType = CONTROLADAPTER_MODEL_DEFAULT_PROCESSORS[modelSubstring];
             break;
           }
diff --git a/invokeai/frontend/web/src/features/embedding/EmbeddingSelect.tsx b/invokeai/frontend/web/src/features/embedding/EmbeddingSelect.tsx
index ffe9d63360..426ddd21e2 100644
--- a/invokeai/frontend/web/src/features/embedding/EmbeddingSelect.tsx
+++ b/invokeai/frontend/web/src/features/embedding/EmbeddingSelect.tsx
@@ -6,18 +6,18 @@ import type { EmbeddingSelectProps } from 'features/embedding/types';
 import { t } from 'i18next';
 import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
-import type { TextualInversionModelConfigEntity } from 'services/api/endpoints/models';
 import { useGetTextualInversionModelsQuery } from 'services/api/endpoints/models';
+import type { TextualInversionConfig } from 'services/api/types';
 
 const noOptionsMessage = () => t('embedding.noMatchingEmbedding');
 
 export const EmbeddingSelect = memo(({ onSelect, onClose }: EmbeddingSelectProps) => {
   const { t } = useTranslation();
 
-  const currentBaseModel = useAppSelector((s) => s.generation.model?.base_model);
+  const currentBaseModel = useAppSelector((s) => s.generation.model?.base);
 
   const getIsDisabled = useCallback(
-    (embedding: TextualInversionModelConfigEntity): boolean => {
+    (embedding: TextualInversionConfig): boolean => {
       const isCompatible = currentBaseModel === embedding.base_model;
       const hasMainModel = Boolean(currentBaseModel);
       return !hasMainModel || !isCompatible;
@@ -27,7 +27,7 @@ export const EmbeddingSelect = memo(({ onSelect, onClose }: EmbeddingSelectProps
   const { data, isLoading } = useGetTextualInversionModelsQuery();
 
   const _onChange = useCallback(
-    (embedding: TextualInversionModelConfigEntity | null) => {
+    (embedding: TextualInversionConfig | null) => {
       if (!embedding) {
         return;
       }
diff --git a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataActions.tsx b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataActions.tsx
index e9a1461186..5907ba0700 100644
--- a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataActions.tsx
+++ b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataActions.tsx
@@ -208,8 +208,8 @@ const ImageMetadataActions = (props: Props) => {
       {metadata.seed !== undefined && metadata.seed !== null && (
         <ImageMetadataItem label={t('metadata.seed')} value={metadata.seed} onClick={handleRecallSeed} />
       )}
-      {metadata.model !== undefined && metadata.model !== null && metadata.model.model_name && (
-        <ImageMetadataItem label={t('metadata.model')} value={metadata.model.model_name} onClick={handleRecallModel} />
+      {metadata.model !== undefined && metadata.model !== null && metadata.model.key && (
+        <ImageMetadataItem label={t('metadata.model')} value={metadata.model.key} onClick={handleRecallModel} />
       )}
       {metadata.width && (
         <ImageMetadataItem label={t('metadata.width')} value={metadata.width} onClick={handleRecallWidth} />
@@ -222,7 +222,7 @@ const ImageMetadataActions = (props: Props) => {
       )}
       <ImageMetadataItem
         label={t('metadata.vae')}
-        value={metadata.vae?.model_name ?? 'Default'}
+        value={metadata.vae?.key ?? 'Default'}
         onClick={handleRecallVaeModel}
       />
       {metadata.steps && (
@@ -269,7 +269,7 @@ const ImageMetadataActions = (props: Props) => {
               <ImageMetadataItem
                 key={index}
                 label="LoRA"
-                value={`${lora.lora.model_name} - ${lora.weight}`}
+                value={`${lora.lora.key} - ${lora.weight}`}
                 onClick={handleRecallLoRA.bind(null, lora)}
               />
             );
@@ -279,7 +279,7 @@ const ImageMetadataActions = (props: Props) => {
         <ImageMetadataItem
           key={index}
           label="ControlNet"
-          value={`${controlnet.control_model?.model_name} - ${controlnet.control_weight}`}
+          value={`${controlnet.control_model?.key} - ${controlnet.control_weight}`}
           onClick={handleRecallControlNet.bind(null, controlnet)}
         />
       ))}
@@ -287,7 +287,7 @@ const ImageMetadataActions = (props: Props) => {
         <ImageMetadataItem
           key={index}
           label="IP Adapter"
-          value={`${ipAdapter.ip_adapter_model?.model_name} - ${ipAdapter.weight}`}
+          value={`${ipAdapter.ip_adapter_model?.key} - ${ipAdapter.weight}`}
           onClick={handleRecallIPAdapter.bind(null, ipAdapter)}
         />
       ))}
@@ -295,7 +295,7 @@ const ImageMetadataActions = (props: Props) => {
         <ImageMetadataItem
           key={index}
           label="T2I Adapter"
-          value={`${t2iAdapter.t2i_adapter_model?.model_name} - ${t2iAdapter.weight}`}
+          value={`${t2iAdapter.t2i_adapter_model?.key} - ${t2iAdapter.weight}`}
           onClick={handleRecallT2IAdapter.bind(null, t2iAdapter)}
         />
       ))}
diff --git a/invokeai/frontend/web/src/features/lora/components/LoRACard.tsx b/invokeai/frontend/web/src/features/lora/components/LoRACard.tsx
index 28bd8afe95..81e0027b2d 100644
--- a/invokeai/frontend/web/src/features/lora/components/LoRACard.tsx
+++ b/invokeai/frontend/web/src/features/lora/components/LoRACard.tsx
@@ -44,7 +44,7 @@ export const LoRACard = memo((props: LoRACardProps) => {
       <CardHeader>
         <Flex alignItems="center" justifyContent="space-between" width="100%" gap={2}>
           <Text noOfLines={1} wordBreak="break-all" color={lora.isEnabled ? 'base.200' : 'base.500'}>
-            {lora.model_name}
+            {lora.key}
           </Text>
           <Flex alignItems="center" gap={2}>
             <Switch size="sm" onChange={handleSetLoraToggle} isChecked={lora.isEnabled} />
diff --git a/invokeai/frontend/web/src/features/lora/components/LoRAList.tsx b/invokeai/frontend/web/src/features/lora/components/LoRAList.tsx
index 9f37454d16..7bcd537805 100644
--- a/invokeai/frontend/web/src/features/lora/components/LoRAList.tsx
+++ b/invokeai/frontend/web/src/features/lora/components/LoRAList.tsx
@@ -18,7 +18,7 @@ export const LoRAList = memo(() => {
   return (
     <Flex flexWrap="wrap" gap={2}>
       {lorasArray.map((lora) => (
-        <LoRACard key={lora.model_name} lora={lora} />
+        <LoRACard key={lora.key} lora={lora} />
       ))}
     </Flex>
   );
diff --git a/invokeai/frontend/web/src/features/lora/components/LoRASelect.tsx b/invokeai/frontend/web/src/features/lora/components/LoRASelect.tsx
index ed70a4d44a..069c557aef 100644
--- a/invokeai/frontend/web/src/features/lora/components/LoRASelect.tsx
+++ b/invokeai/frontend/web/src/features/lora/components/LoRASelect.tsx
@@ -7,7 +7,7 @@ import { useGroupedModelCombobox } from 'common/hooks/useGroupedModelCombobox';
 import { loraAdded, selectLoraSlice } from 'features/lora/store/loraSlice';
 import { memo, useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
-import type { LoRAModelConfigEntity } from 'services/api/endpoints/models';
+import type { LoRAConfig } from 'services/api/endpoints/models';
 import { useGetLoRAModelsQuery } from 'services/api/endpoints/models';
 
 const selectAddedLoRAs = createMemoizedSelector(selectLoraSlice, (lora) => lora.loras);
@@ -19,7 +19,7 @@ const LoRASelect = () => {
   const addedLoRAs = useAppSelector(selectAddedLoRAs);
   const currentBaseModel = useAppSelector((s) => s.generation.model?.base_model);
 
-  const getIsDisabled = (lora: LoRAModelConfigEntity): boolean => {
+  const getIsDisabled = (lora: LoRAConfig): boolean => {
     const isCompatible = currentBaseModel === lora.base_model;
     const isAdded = Boolean(addedLoRAs[lora.id]);
     const hasMainModel = Boolean(currentBaseModel);
@@ -27,7 +27,7 @@ const LoRASelect = () => {
   };
 
   const _onChange = useCallback(
-    (lora: LoRAModelConfigEntity | null) => {
+    (lora: LoRAConfig | null) => {
       if (!lora) {
         return;
       }
diff --git a/invokeai/frontend/web/src/features/lora/store/loraSlice.ts b/invokeai/frontend/web/src/features/lora/store/loraSlice.ts
index ab1b140a7c..dd455e12c3 100644
--- a/invokeai/frontend/web/src/features/lora/store/loraSlice.ts
+++ b/invokeai/frontend/web/src/features/lora/store/loraSlice.ts
@@ -2,10 +2,9 @@ import type { PayloadAction } from '@reduxjs/toolkit';
 import { createSlice } from '@reduxjs/toolkit';
 import type { PersistConfig, RootState } from 'app/store/store';
 import type { ParameterLoRAModel } from 'features/parameters/types/parameterSchemas';
-import type { LoRAModelConfigEntity } from 'services/api/endpoints/models';
+import type { LoRAConfig } from 'services/api/types';
 
 export type LoRA = ParameterLoRAModel & {
-  id: string;
   weight: number;
   isEnabled?: boolean;
 };
@@ -29,40 +28,40 @@ export const loraSlice = createSlice({
   name: 'lora',
   initialState: initialLoraState,
   reducers: {
-    loraAdded: (state, action: PayloadAction<LoRAModelConfigEntity>) => {
-      const { model_name, id, base_model } = action.payload;
-      state.loras[id] = { id, model_name, base_model, ...defaultLoRAConfig };
+    loraAdded: (state, action: PayloadAction<LoRAConfig>) => {
+      const { key, base } = action.payload;
+      state.loras[key] = { key, base, ...defaultLoRAConfig };
     },
-    loraRecalled: (state, action: PayloadAction<LoRAModelConfigEntity & { weight: number }>) => {
-      const { model_name, id, base_model, weight } = action.payload;
-      state.loras[id] = { id, model_name, base_model, weight, isEnabled: true };
+    loraRecalled: (state, action: PayloadAction<LoRAConfig & { weight: number }>) => {
+      const { key, base, weight } = action.payload;
+      state.loras[key] = { key, base, weight, isEnabled: true };
     },
     loraRemoved: (state, action: PayloadAction<string>) => {
-      const id = action.payload;
-      delete state.loras[id];
+      const key = action.payload;
+      delete state.loras[key];
     },
     lorasCleared: (state) => {
       state.loras = {};
     },
-    loraWeightChanged: (state, action: PayloadAction<{ id: string; weight: number }>) => {
-      const { id, weight } = action.payload;
-      const lora = state.loras[id];
+    loraWeightChanged: (state, action: PayloadAction<{ key: string; weight: number }>) => {
+      const { key, weight } = action.payload;
+      const lora = state.loras[key];
       if (!lora) {
         return;
       }
       lora.weight = weight;
     },
     loraWeightReset: (state, action: PayloadAction<string>) => {
-      const id = action.payload;
-      const lora = state.loras[id];
+      const key = action.payload;
+      const lora = state.loras[key];
       if (!lora) {
         return;
       }
       lora.weight = defaultLoRAConfig.weight;
     },
-    loraIsEnabledChanged: (state, action: PayloadAction<Pick<LoRA, 'id' | 'isEnabled'>>) => {
-      const { id, isEnabled } = action.payload;
-      const lora = state.loras[id];
+    loraIsEnabledChanged: (state, action: PayloadAction<Pick<LoRA, 'key' | 'isEnabled'>>) => {
+      const { key, isEnabled } = action.payload;
+      const lora = state.loras[key];
       if (!lora) {
         return;
       }
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel.tsx
index 6b9abdbfec..7501151ba4 100644
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel.tsx
+++ b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel.tsx
@@ -3,9 +3,9 @@ import { memo, useState } from 'react';
 import { useTranslation } from 'react-i18next';
 import { ALL_BASE_MODELS } from 'services/api/constants';
 import type {
-  DiffusersModelConfigEntity,
-  LoRAModelConfigEntity,
-  MainModelConfigEntity,
+  DiffusersModelConfig,
+  LoRAConfig,
+  MainModelConfig,
 } from 'services/api/endpoints/models';
 import { useGetLoRAModelsQuery, useGetMainModelsQuery } from 'services/api/endpoints/models';
 
@@ -38,7 +38,7 @@ const ModelManagerPanel = () => {
 };
 
 type ModelEditProps = {
-  model: MainModelConfigEntity | LoRAModelConfigEntity | undefined;
+  model: MainModelConfig | LoRAConfig | undefined;
 };
 
 const ModelEdit = (props: ModelEditProps) => {
@@ -50,7 +50,7 @@ const ModelEdit = (props: ModelEditProps) => {
   }
 
   if (model?.model_format === 'diffusers') {
-    return <DiffusersModelEdit key={model.id} model={model as DiffusersModelConfigEntity} />;
+    return <DiffusersModelEdit key={model.id} model={model as DiffusersModelConfig} />;
   }
 
   if (model?.model_type === 'lora') {
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/CheckpointModelEdit.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/CheckpointModelEdit.tsx
index f4d271187d..43707308e0 100644
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/CheckpointModelEdit.tsx
+++ b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/CheckpointModelEdit.tsx
@@ -21,14 +21,14 @@ import { memo, useCallback, useEffect, useState } from 'react';
 import type { SubmitHandler } from 'react-hook-form';
 import { useForm } from 'react-hook-form';
 import { useTranslation } from 'react-i18next';
-import type { CheckpointModelConfigEntity } from 'services/api/endpoints/models';
+import type { CheckpointModelConfig } from 'services/api/endpoints/models';
 import { useGetCheckpointConfigsQuery, useUpdateMainModelsMutation } from 'services/api/endpoints/models';
 import type { CheckpointModelConfig } from 'services/api/types';
 
 import ModelConvert from './ModelConvert';
 
 type CheckpointModelEditProps = {
-  model: CheckpointModelConfigEntity;
+  model: CheckpointModelConfig;
 };
 
 const CheckpointModelEdit = (props: CheckpointModelEditProps) => {
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/DiffusersModelEdit.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/DiffusersModelEdit.tsx
index 4670f32157..bf6349234f 100644
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/DiffusersModelEdit.tsx
+++ b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/DiffusersModelEdit.tsx
@@ -9,12 +9,12 @@ import { memo, useCallback } from 'react';
 import type { SubmitHandler } from 'react-hook-form';
 import { useForm } from 'react-hook-form';
 import { useTranslation } from 'react-i18next';
-import type { DiffusersModelConfigEntity } from 'services/api/endpoints/models';
+import type { DiffusersModelConfig } from 'services/api/endpoints/models';
 import { useUpdateMainModelsMutation } from 'services/api/endpoints/models';
 import type { DiffusersModelConfig } from 'services/api/types';
 
 type DiffusersModelEditProps = {
-  model: DiffusersModelConfigEntity;
+  model: DiffusersModelConfig;
 };
 
 const DiffusersModelEdit = (props: DiffusersModelEditProps) => {
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/LoRAModelEdit.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/LoRAModelEdit.tsx
index 2baf735bee..75151cd001 100644
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/LoRAModelEdit.tsx
+++ b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/LoRAModelEdit.tsx
@@ -8,12 +8,12 @@ import { memo, useCallback } from 'react';
 import type { SubmitHandler } from 'react-hook-form';
 import { useForm } from 'react-hook-form';
 import { useTranslation } from 'react-i18next';
-import type { LoRAModelConfigEntity } from 'services/api/endpoints/models';
+import type { LoRAConfig } from 'services/api/endpoints/models';
 import { useUpdateLoRAModelsMutation } from 'services/api/endpoints/models';
-import type { LoRAModelConfig } from 'services/api/types';
+import type { LoRAConfig } from 'services/api/types';
 
 type LoRAModelEditProps = {
-  model: LoRAModelConfigEntity;
+  model: LoRAConfig;
 };
 
 const LoRAModelEdit = (props: LoRAModelEditProps) => {
@@ -30,7 +30,7 @@ const LoRAModelEdit = (props: LoRAModelEditProps) => {
     control,
     formState: { errors },
     reset,
-  } = useForm<LoRAModelConfig>({
+  } = useForm<LoRAConfig>({
     defaultValues: {
       model_name: model.model_name ? model.model_name : '',
       base_model: model.base_model,
@@ -42,7 +42,7 @@ const LoRAModelEdit = (props: LoRAModelEditProps) => {
     mode: 'onChange',
   });
 
-  const onSubmit = useCallback<SubmitHandler<LoRAModelConfig>>(
+  const onSubmit = useCallback<SubmitHandler<LoRAConfig>>(
     (values) => {
       const responseBody = {
         base_model: model.base_model,
@@ -53,7 +53,7 @@ const LoRAModelEdit = (props: LoRAModelEditProps) => {
       updateLoRAModel(responseBody)
         .unwrap()
         .then((payload) => {
-          reset(payload as LoRAModelConfig, { keepDefaultValues: true });
+          reset(payload as LoRAConfig, { keepDefaultValues: true });
           dispatch(
             addToast(
               makeToast({
@@ -106,7 +106,7 @@ const LoRAModelEdit = (props: LoRAModelEditProps) => {
             <FormLabel>{t('modelManager.description')}</FormLabel>
             <Input {...register('description')} />
           </FormControl>
-          <BaseModelSelect<LoRAModelConfig> control={control} name="base_model" />
+          <BaseModelSelect<LoRAConfig> control={control} name="base_model" />
 
           <FormControl isInvalid={Boolean(errors.path)}>
             <FormLabel>{t('modelManager.modelLocation')}</FormLabel>
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelList.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelList.tsx
index 94db3d20c3..dd74bb0c23 100644
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelList.tsx
+++ b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelList.tsx
@@ -5,7 +5,7 @@ import type { ChangeEvent, PropsWithChildren } from 'react';
 import { memo, useCallback, useState } from 'react';
 import { useTranslation } from 'react-i18next';
 import { ALL_BASE_MODELS } from 'services/api/constants';
-import type { LoRAModelConfigEntity, MainModelConfigEntity } from 'services/api/endpoints/models';
+import type { LoRAConfig, MainModelConfig } from 'services/api/endpoints/models';
 import { useGetLoRAModelsQuery, useGetMainModelsQuery } from 'services/api/endpoints/models';
 
 import ModelListItem from './ModelListItem';
@@ -127,7 +127,7 @@ const ModelList = (props: ModelListProps) => {
 
 export default memo(ModelList);
 
-const modelsFilter = <T extends MainModelConfigEntity | LoRAModelConfigEntity>(
+const modelsFilter = <T extends MainModelConfig | LoRAConfig>(
   data: EntityState<T, string> | undefined,
   model_type: ModelType,
   model_format: ModelFormat | undefined,
@@ -163,7 +163,7 @@ StyledModelContainer.displayName = 'StyledModelContainer';
 
 type ModelListWrapperProps = {
   title: string;
-  modelList: MainModelConfigEntity[] | LoRAModelConfigEntity[];
+  modelList: MainModelConfig[] | LoRAConfig[];
   selected: ModelListProps;
 };
 
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelListItem.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelListItem.tsx
index fdd13e09f5..835499d25a 100644
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelListItem.tsx
+++ b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelListItem.tsx
@@ -15,11 +15,11 @@ import { makeToast } from 'features/system/util/makeToast';
 import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 import { PiTrashSimpleBold } from 'react-icons/pi';
-import type { LoRAModelConfigEntity, MainModelConfigEntity } from 'services/api/endpoints/models';
+import type { LoRAConfig, MainModelConfig } from 'services/api/endpoints/models';
 import { useDeleteLoRAModelsMutation, useDeleteMainModelsMutation } from 'services/api/endpoints/models';
 
 type ModelListItemProps = {
-  model: MainModelConfigEntity | LoRAModelConfigEntity;
+  model: MainModelConfig | LoRAConfig;
   isSelected: boolean;
   setSelectedModelId: (v: string | undefined) => void;
 };
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/ControlNetModelFieldInputComponent.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/ControlNetModelFieldInputComponent.tsx
index 22024f3d3c..53d800e7b6 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/ControlNetModelFieldInputComponent.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/ControlNetModelFieldInputComponent.tsx
@@ -4,7 +4,7 @@ import { useGroupedModelCombobox } from 'common/hooks/useGroupedModelCombobox';
 import { fieldControlNetModelValueChanged } from 'features/nodes/store/nodesSlice';
 import type { ControlNetModelFieldInputInstance, ControlNetModelFieldInputTemplate } from 'features/nodes/types/field';
 import { memo, useCallback } from 'react';
-import type { ControlNetModelConfigEntity } from 'services/api/endpoints/models';
+import type { ControlNetConfig } from 'services/api/endpoints/models';
 import { useGetControlNetModelsQuery } from 'services/api/endpoints/models';
 
 import type { FieldComponentProps } from './types';
@@ -17,7 +17,7 @@ const ControlNetModelFieldInputComponent = (props: Props) => {
   const { data, isLoading } = useGetControlNetModelsQuery();
 
   const _onChange = useCallback(
-    (value: ControlNetModelConfigEntity | null) => {
+    (value: ControlNetConfig | null) => {
       if (!value) {
         return;
       }
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/IPAdapterModelFieldInputComponent.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/IPAdapterModelFieldInputComponent.tsx
index 2cde347247..3f195ceb32 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/IPAdapterModelFieldInputComponent.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/IPAdapterModelFieldInputComponent.tsx
@@ -4,7 +4,7 @@ import { useGroupedModelCombobox } from 'common/hooks/useGroupedModelCombobox';
 import { fieldIPAdapterModelValueChanged } from 'features/nodes/store/nodesSlice';
 import type { IPAdapterModelFieldInputInstance, IPAdapterModelFieldInputTemplate } from 'features/nodes/types/field';
 import { memo, useCallback } from 'react';
-import type { IPAdapterModelConfigEntity } from 'services/api/endpoints/models';
+import type { IPAdapterConfig } from 'services/api/endpoints/models';
 import { useGetIPAdapterModelsQuery } from 'services/api/endpoints/models';
 
 import type { FieldComponentProps } from './types';
@@ -17,7 +17,7 @@ const IPAdapterModelFieldInputComponent = (
   const { data: ipAdapterModels } = useGetIPAdapterModelsQuery();
 
   const _onChange = useCallback(
-    (value: IPAdapterModelConfigEntity | null) => {
+    (value: IPAdapterConfig | null) => {
       if (!value) {
         return;
       }
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/LoRAModelFieldInputComponent.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/LoRAModelFieldInputComponent.tsx
index 96208d68d4..eeb07fa08e 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/LoRAModelFieldInputComponent.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/LoRAModelFieldInputComponent.tsx
@@ -4,7 +4,7 @@ import { useGroupedModelCombobox } from 'common/hooks/useGroupedModelCombobox';
 import { fieldLoRAModelValueChanged } from 'features/nodes/store/nodesSlice';
 import type { LoRAModelFieldInputInstance, LoRAModelFieldInputTemplate } from 'features/nodes/types/field';
 import { memo, useCallback } from 'react';
-import type { LoRAModelConfigEntity } from 'services/api/endpoints/models';
+import type { LoRAConfig } from 'services/api/endpoints/models';
 import { useGetLoRAModelsQuery } from 'services/api/endpoints/models';
 
 import type { FieldComponentProps } from './types';
@@ -16,7 +16,7 @@ const LoRAModelFieldInputComponent = (props: Props) => {
   const dispatch = useAppDispatch();
   const { data, isLoading } = useGetLoRAModelsQuery();
   const _onChange = useCallback(
-    (value: LoRAModelConfigEntity | null) => {
+    (value: LoRAConfig | null) => {
       if (!value) {
         return;
       }
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/MainModelFieldInputComponent.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/MainModelFieldInputComponent.tsx
index 64c6970cae..7ddde08816 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/MainModelFieldInputComponent.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/MainModelFieldInputComponent.tsx
@@ -6,7 +6,7 @@ import { fieldMainModelValueChanged } from 'features/nodes/store/nodesSlice';
 import type { MainModelFieldInputInstance, MainModelFieldInputTemplate } from 'features/nodes/types/field';
 import { memo, useCallback } from 'react';
 import { NON_SDXL_MAIN_MODELS } from 'services/api/constants';
-import type { MainModelConfigEntity } from 'services/api/endpoints/models';
+import type { MainModelConfig } from 'services/api/endpoints/models';
 import { useGetMainModelsQuery } from 'services/api/endpoints/models';
 
 import type { FieldComponentProps } from './types';
@@ -18,7 +18,7 @@ const MainModelFieldInputComponent = (props: Props) => {
   const dispatch = useAppDispatch();
   const { data, isLoading } = useGetMainModelsQuery(NON_SDXL_MAIN_MODELS);
   const _onChange = useCallback(
-    (value: MainModelConfigEntity | null) => {
+    (value: MainModelConfig | null) => {
       if (!value) {
         return;
       }
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/RefinerModelFieldInputComponent.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/RefinerModelFieldInputComponent.tsx
index 98901af38b..9b5a1138d4 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/RefinerModelFieldInputComponent.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/RefinerModelFieldInputComponent.tsx
@@ -9,7 +9,7 @@ import type {
 } from 'features/nodes/types/field';
 import { memo, useCallback } from 'react';
 import { REFINER_BASE_MODELS } from 'services/api/constants';
-import type { MainModelConfigEntity } from 'services/api/endpoints/models';
+import type { MainModelConfig } from 'services/api/endpoints/models';
 import { useGetMainModelsQuery } from 'services/api/endpoints/models';
 
 import type { FieldComponentProps } from './types';
@@ -21,7 +21,7 @@ const RefinerModelFieldInputComponent = (props: Props) => {
   const dispatch = useAppDispatch();
   const { data, isLoading } = useGetMainModelsQuery(REFINER_BASE_MODELS);
   const _onChange = useCallback(
-    (value: MainModelConfigEntity | null) => {
+    (value: MainModelConfig | null) => {
       if (!value) {
         return;
       }
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/SDXLMainModelFieldInputComponent.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/SDXLMainModelFieldInputComponent.tsx
index f5bc7ac3e4..cf353619e8 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/SDXLMainModelFieldInputComponent.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/SDXLMainModelFieldInputComponent.tsx
@@ -6,7 +6,7 @@ import { fieldMainModelValueChanged } from 'features/nodes/store/nodesSlice';
 import type { SDXLMainModelFieldInputInstance, SDXLMainModelFieldInputTemplate } from 'features/nodes/types/field';
 import { memo, useCallback } from 'react';
 import { SDXL_MAIN_MODELS } from 'services/api/constants';
-import type { MainModelConfigEntity } from 'services/api/endpoints/models';
+import type { MainModelConfig } from 'services/api/endpoints/models';
 import { useGetMainModelsQuery } from 'services/api/endpoints/models';
 
 import type { FieldComponentProps } from './types';
@@ -18,7 +18,7 @@ const SDXLMainModelFieldInputComponent = (props: Props) => {
   const dispatch = useAppDispatch();
   const { data, isLoading } = useGetMainModelsQuery(SDXL_MAIN_MODELS);
   const _onChange = useCallback(
-    (value: MainModelConfigEntity | null) => {
+    (value: MainModelConfig | null) => {
       if (!value) {
         return;
       }
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/T2IAdapterModelFieldInputComponent.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/T2IAdapterModelFieldInputComponent.tsx
index 9baf0d2d61..8402c56343 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/T2IAdapterModelFieldInputComponent.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/T2IAdapterModelFieldInputComponent.tsx
@@ -4,7 +4,7 @@ import { useGroupedModelCombobox } from 'common/hooks/useGroupedModelCombobox';
 import { fieldT2IAdapterModelValueChanged } from 'features/nodes/store/nodesSlice';
 import type { T2IAdapterModelFieldInputInstance, T2IAdapterModelFieldInputTemplate } from 'features/nodes/types/field';
 import { memo, useCallback } from 'react';
-import type { T2IAdapterModelConfigEntity } from 'services/api/endpoints/models';
+import type { T2IAdapterConfig } from 'services/api/endpoints/models';
 import { useGetT2IAdapterModelsQuery } from 'services/api/endpoints/models';
 
 import type { FieldComponentProps } from './types';
@@ -18,7 +18,7 @@ const T2IAdapterModelFieldInputComponent = (
   const { data: t2iAdapterModels } = useGetT2IAdapterModelsQuery();
 
   const _onChange = useCallback(
-    (value: T2IAdapterModelConfigEntity | null) => {
+    (value: T2IAdapterConfig | null) => {
       if (!value) {
         return;
       }
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/VAEModelFieldInputComponent.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/VAEModelFieldInputComponent.tsx
index 070178f32a..af09f2d8f2 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/VAEModelFieldInputComponent.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/VAEModelFieldInputComponent.tsx
@@ -5,7 +5,7 @@ import { SyncModelsIconButton } from 'features/modelManager/components/SyncModel
 import { fieldVaeModelValueChanged } from 'features/nodes/store/nodesSlice';
 import type { VAEModelFieldInputInstance, VAEModelFieldInputTemplate } from 'features/nodes/types/field';
 import { memo, useCallback } from 'react';
-import type { VaeModelConfigEntity } from 'services/api/endpoints/models';
+import type { VAEConfig } from 'services/api/endpoints/models';
 import { useGetVaeModelsQuery } from 'services/api/endpoints/models';
 
 import type { FieldComponentProps } from './types';
@@ -17,7 +17,7 @@ const VAEModelFieldInputComponent = (props: Props) => {
   const dispatch = useAppDispatch();
   const { data, isLoading } = useGetVaeModelsQuery();
   const _onChange = useCallback(
-    (value: VaeModelConfigEntity | null) => {
+    (value: VAEConfig | null) => {
       if (!value) {
         return;
       }
diff --git a/invokeai/frontend/web/src/features/nodes/types/common.ts b/invokeai/frontend/web/src/features/nodes/types/common.ts
index ef579fce8c..891bd29bc8 100644
--- a/invokeai/frontend/web/src/features/nodes/types/common.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/common.ts
@@ -67,11 +67,13 @@ export const zModelName = z.string().min(3);
 export const zModelIdentifier = z.object({
   key: z.string().min(1),
 });
+export const zModelFieldBase = zModelIdentifier;
+export const zModelIdentifierWithBase = zModelIdentifier.extend({ base: zBaseModel });
 export type BaseModel = z.infer<typeof zBaseModel>;
 export type ModelType = z.infer<typeof zModelType>;
 export type ModelIdentifier = z.infer<typeof zModelIdentifier>;
-
-export const zMainModelField = zModelIdentifier;
+export type ModelIdentifierWithBase = z.infer<typeof zModelIdentifierWithBase>;
+export const zMainModelField = zModelFieldBase;
 export type MainModelField = z.infer<typeof zMainModelField>;
 
 export const zSDXLRefinerModelField = zModelIdentifier;
@@ -91,23 +93,23 @@ export const zSubModelType = z.enum([
 ]);
 export type SubModelType = z.infer<typeof zSubModelType>;
 
-export const zVAEModelField = zModelIdentifier;
+export const zVAEModelField = zModelFieldBase;
 
 export const zModelInfo = zModelIdentifier.extend({
   submodel_type: zSubModelType.nullish(),
 });
 export type ModelInfo = z.infer<typeof zModelInfo>;
 
-export const zLoRAModelField = zModelIdentifier;
+export const zLoRAModelField = zModelFieldBase;
 export type LoRAModelField = z.infer<typeof zLoRAModelField>;
 
-export const zControlNetModelField = zModelIdentifier;
+export const zControlNetModelField = zModelFieldBase;
 export type ControlNetModelField = z.infer<typeof zControlNetModelField>;
 
-export const zIPAdapterModelField = zModelIdentifier;
+export const zIPAdapterModelField = zModelFieldBase;
 export type IPAdapterModelField = z.infer<typeof zIPAdapterModelField>;
 
-export const zT2IAdapterModelField = zModelIdentifier;
+export const zT2IAdapterModelField = zModelFieldBase;
 export type T2IAdapterModelField = z.infer<typeof zT2IAdapterModelField>;
 
 export const zLoraInfo = zModelInfo.extend({
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/addControlNetToLinearGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/addControlNetToLinearGraph.ts
index d862b0986e..1853d3722c 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/addControlNetToLinearGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/addControlNetToLinearGraph.ts
@@ -14,7 +14,7 @@ import { upsertMetadata } from './metadata';
 
 export const addControlNetToLinearGraph = (state: RootState, graph: NonNullableGraph, baseNodeId: string): void => {
   const validControlNets = selectValidControlNets(state.controlAdapters).filter(
-    (ca) => ca.model?.base_model === state.generation.model?.base_model
+    (ca) => ca.model?.base === state.generation.model?.base
   );
 
   // const metadataAccumulator = graph.nodes[METADATA_ACCUMULATOR] as
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/addIPAdapterToLinearGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/addIPAdapterToLinearGraph.ts
index 3a79b78c6e..b51ac1bd52 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/addIPAdapterToLinearGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/addIPAdapterToLinearGraph.ts
@@ -14,7 +14,7 @@ import { upsertMetadata } from './metadata';
 
 export const addIPAdapterToLinearGraph = (state: RootState, graph: NonNullableGraph, baseNodeId: string): void => {
   const validIPAdapters = selectValidIPAdapters(state.controlAdapters).filter(
-    (ca) => ca.model?.base_model === state.generation.model?.base_model
+    (ca) => ca.model?.base === state.generation.model?.base
   );
 
   if (validIPAdapters.length) {
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/addLoRAsToGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/addLoRAsToGraph.ts
index 3ed71b7529..95bba9b441 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/addLoRAsToGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/addLoRAsToGraph.ts
@@ -28,6 +28,7 @@ export const addLoRAsToGraph = (
    * So we need to inject a LoRA chain into the graph.
    */
 
+  // TODO(MM2): check base model
   const enabledLoRAs = filter(state.lora.loras, (l) => l.isEnabled ?? false);
   const loraCount = size(enabledLoRAs);
 
@@ -48,19 +49,19 @@ export const addLoRAsToGraph = (
   const loraMetadata: CoreMetadataInvocation['loras'] = [];
 
   enabledLoRAs.forEach((lora) => {
-    const { model_name, base_model, weight } = lora;
-    const currentLoraNodeId = `${LORA_LOADER}_${model_name.replace('.', '_')}`;
+    const { key, weight } = lora;
+    const currentLoraNodeId = `${LORA_LOADER}_${key}`;
 
     const loraLoaderNode: LoraLoaderInvocation = {
       type: 'lora_loader',
       id: currentLoraNodeId,
       is_intermediate: true,
-      lora: { model_name, base_model },
+      lora: { key },
       weight,
     };
 
     loraMetadata.push({
-      lora: { model_name, base_model },
+      lora: { key },
       weight,
     });
 
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/addSDXLLoRAstoGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/addSDXLLoRAstoGraph.ts
index 9553568922..7874b059c9 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/addSDXLLoRAstoGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/addSDXLLoRAstoGraph.ts
@@ -31,6 +31,7 @@ export const addSDXLLoRAsToGraph = (
    * So we need to inject a LoRA chain into the graph.
    */
 
+  // TODO(MM2): check base model
   const enabledLoRAs = filter(state.lora.loras, (l) => l.isEnabled ?? false);
   const loraCount = size(enabledLoRAs);
 
@@ -60,20 +61,20 @@ export const addSDXLLoRAsToGraph = (
   let currentLoraIndex = 0;
 
   enabledLoRAs.forEach((lora) => {
-    const { model_name, base_model, weight } = lora;
-    const currentLoraNodeId = `${LORA_LOADER}_${model_name.replace('.', '_')}`;
+    const { key, weight } = lora;
+    const currentLoraNodeId = `${LORA_LOADER}_${key}`;
 
     const loraLoaderNode: SDXLLoraLoaderInvocation = {
       type: 'sdxl_lora_loader',
       id: currentLoraNodeId,
       is_intermediate: true,
-      lora: { model_name, base_model },
+      lora: { key },
       weight,
     };
 
     loraMetadata.push(
       zLoRAMetadataItem.parse({
-        lora: { model_name, base_model },
+        lora: { key },
         weight,
       })
     );
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/addT2IAdapterToLinearGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/addT2IAdapterToLinearGraph.ts
index d35f72a2b4..84002337d7 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/addT2IAdapterToLinearGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/addT2IAdapterToLinearGraph.ts
@@ -14,7 +14,7 @@ import { upsertMetadata } from './metadata';
 
 export const addT2IAdaptersToLinearGraph = (state: RootState, graph: NonNullableGraph, baseNodeId: string): void => {
   const validT2IAdapters = selectValidT2IAdapters(state.controlAdapters).filter(
-    (ca) => ca.model?.base_model === state.generation.model?.base_model
+    (ca) => ca.model?.base === state.generation.model?.base
   );
 
   if (validT2IAdapters.length) {
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasGraph.ts
index 2b64f4898b..4ce2e4d673 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasGraph.ts
@@ -19,7 +19,7 @@ export const buildCanvasGraph = (
   let graph: NonNullableGraph;
 
   if (generationMode === 'txt2img') {
-    if (state.generation.model && state.generation.model.base_model === 'sdxl') {
+    if (state.generation.model && state.generation.model.base === 'sdxl') {
       graph = buildCanvasSDXLTextToImageGraph(state);
     } else {
       graph = buildCanvasTextToImageGraph(state);
@@ -28,7 +28,7 @@ export const buildCanvasGraph = (
     if (!canvasInitImage) {
       throw new Error('Missing canvas init image');
     }
-    if (state.generation.model && state.generation.model.base_model === 'sdxl') {
+    if (state.generation.model && state.generation.model.base === 'sdxl') {
       graph = buildCanvasSDXLImageToImageGraph(state, canvasInitImage);
     } else {
       graph = buildCanvasImageToImageGraph(state, canvasInitImage);
@@ -37,7 +37,7 @@ export const buildCanvasGraph = (
     if (!canvasInitImage || !canvasMaskImage) {
       throw new Error('Missing canvas init and mask images');
     }
-    if (state.generation.model && state.generation.model.base_model === 'sdxl') {
+    if (state.generation.model && state.generation.model.base === 'sdxl') {
       graph = buildCanvasSDXLInpaintGraph(state, canvasInitImage, canvasMaskImage);
     } else {
       graph = buildCanvasInpaintGraph(state, canvasInitImage, canvasMaskImage);
@@ -46,7 +46,7 @@ export const buildCanvasGraph = (
     if (!canvasInitImage) {
       throw new Error('Missing canvas init image');
     }
-    if (state.generation.model && state.generation.model.base_model === 'sdxl') {
+    if (state.generation.model && state.generation.model.base === 'sdxl') {
       graph = buildCanvasSDXLOutpaintGraph(state, canvasInitImage, canvasMaskImage);
     } else {
       graph = buildCanvasOutpaintGraph(state, canvasInitImage, canvasMaskImage);
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildLinearBatchConfig.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildLinearBatchConfig.ts
index d0e331fb46..9fcc6afaa0 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildLinearBatchConfig.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildLinearBatchConfig.ts
@@ -105,7 +105,7 @@ export const prepareLinearUIBatch = (state: RootState, graph: NonNullableGraph,
     });
   }
 
-  if (shouldConcatSDXLStylePrompt && model?.base_model === 'sdxl') {
+  if (shouldConcatSDXLStylePrompt && model?.base === 'sdxl') {
     if (graph.nodes[POSITIVE_CONDITIONING]) {
       firstBatchDatumList.push({
         node_path: POSITIVE_CONDITIONING,
diff --git a/invokeai/frontend/web/src/features/parameters/components/Advanced/ParamClipSkip.tsx b/invokeai/frontend/web/src/features/parameters/components/Advanced/ParamClipSkip.tsx
index 621ed56ef6..c23d541613 100644
--- a/invokeai/frontend/web/src/features/parameters/components/Advanced/ParamClipSkip.tsx
+++ b/invokeai/frontend/web/src/features/parameters/components/Advanced/ParamClipSkip.tsx
@@ -29,17 +29,17 @@ const ParamClipSkip = () => {
     if (!model) {
       return CLIP_SKIP_MAP['sd-1'].maxClip;
     }
-    return CLIP_SKIP_MAP[model.base_model].maxClip;
+    return CLIP_SKIP_MAP[model.base].maxClip;
   }, [model]);
 
   const sliderMarks = useMemo(() => {
     if (!model) {
       return CLIP_SKIP_MAP['sd-1'].markers;
     }
-    return CLIP_SKIP_MAP[model.base_model].markers;
+    return CLIP_SKIP_MAP[model.base].markers;
   }, [model]);
 
-  if (model?.base_model === 'sdxl') {
+  if (model?.base === 'sdxl') {
     return null;
   }
 
diff --git a/invokeai/frontend/web/src/features/parameters/components/Core/ParamPositivePrompt.tsx b/invokeai/frontend/web/src/features/parameters/components/Core/ParamPositivePrompt.tsx
index ae81f78fd1..a1852bfafe 100644
--- a/invokeai/frontend/web/src/features/parameters/components/Core/ParamPositivePrompt.tsx
+++ b/invokeai/frontend/web/src/features/parameters/components/Core/ParamPositivePrompt.tsx
@@ -15,7 +15,7 @@ import { useTranslation } from 'react-i18next';
 export const ParamPositivePrompt = memo(() => {
   const dispatch = useAppDispatch();
   const prompt = useAppSelector((s) => s.generation.positivePrompt);
-  const baseModel = useAppSelector((s) => s.generation.model)?.base_model;
+  const baseModel = useAppSelector((s) => s.generation.model)?.base;
 
   const textareaRef = useRef<HTMLTextAreaElement>(null);
   const { t } = useTranslation();
diff --git a/invokeai/frontend/web/src/features/parameters/components/MainModel/ParamMainModelSelect.tsx b/invokeai/frontend/web/src/features/parameters/components/MainModel/ParamMainModelSelect.tsx
index c6c77b5fe9..18f780bdee 100644
--- a/invokeai/frontend/web/src/features/parameters/components/MainModel/ParamMainModelSelect.tsx
+++ b/invokeai/frontend/web/src/features/parameters/components/MainModel/ParamMainModelSelect.tsx
@@ -9,7 +9,7 @@ import { pick } from 'lodash-es';
 import { memo, useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
 import { NON_REFINER_BASE_MODELS } from 'services/api/constants';
-import type { MainModelConfigEntity } from 'services/api/endpoints/models';
+import type { MainModelConfig } from 'services/api/endpoints/models';
 import { getModelId, mainModelsAdapterSelectors, useGetMainModelsQuery } from 'services/api/endpoints/models';
 
 const selectModel = createMemoizedSelector(selectGenerationSlice, (generation) => generation.model);
@@ -26,7 +26,7 @@ const ParamMainModelSelect = () => {
     return mainModelsAdapterSelectors.selectById(data, getModelId(model))?.description;
   }, [data, model]);
   const _onChange = useCallback(
-    (model: MainModelConfigEntity | null) => {
+    (model: MainModelConfig | null) => {
       if (!model) {
         return;
       }
diff --git a/invokeai/frontend/web/src/features/parameters/components/VAEModel/ParamVAEModelSelect.tsx b/invokeai/frontend/web/src/features/parameters/components/VAEModel/ParamVAEModelSelect.tsx
index f290378aa8..cc0164153d 100644
--- a/invokeai/frontend/web/src/features/parameters/components/VAEModel/ParamVAEModelSelect.tsx
+++ b/invokeai/frontend/web/src/features/parameters/components/VAEModel/ParamVAEModelSelect.tsx
@@ -7,7 +7,7 @@ import { selectGenerationSlice, vaeSelected } from 'features/parameters/store/ge
 import { pick } from 'lodash-es';
 import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
-import type { VaeModelConfigEntity } from 'services/api/endpoints/models';
+import type { VAEConfig } from 'services/api/endpoints/models';
 import { useGetVaeModelsQuery } from 'services/api/endpoints/models';
 
 const selector = createMemoizedSelector(selectGenerationSlice, (generation) => {
@@ -21,7 +21,7 @@ const ParamVAEModelSelect = () => {
   const { model, vae } = useAppSelector(selector);
   const { data, isLoading } = useGetVaeModelsQuery();
   const getIsDisabled = useCallback(
-    (vae: VaeModelConfigEntity): boolean => {
+    (vae: VAEConfig): boolean => {
       const isCompatible = model?.base_model === vae.base_model;
       const hasMainModel = Boolean(model?.base_model);
       return !hasMainModel || !isCompatible;
@@ -29,7 +29,7 @@ const ParamVAEModelSelect = () => {
     [model?.base_model]
   );
   const _onChange = useCallback(
-    (vae: VaeModelConfigEntity | null) => {
+    (vae: VAEConfig | null) => {
       dispatch(vaeSelected(vae ? pick(vae, 'base_model', 'model_name') : null));
     },
     [dispatch]
diff --git a/invokeai/frontend/web/src/features/parameters/hooks/useRecallParameters.ts b/invokeai/frontend/web/src/features/parameters/hooks/useRecallParameters.ts
index 5a9fa6c66d..c8b17816bb 100644
--- a/invokeai/frontend/web/src/features/parameters/hooks/useRecallParameters.ts
+++ b/invokeai/frontend/web/src/features/parameters/hooks/useRecallParameters.ts
@@ -464,17 +464,15 @@ export const useRecallParameters = () => {
         return { lora: null, error: 'Invalid LoRA model' };
       }
 
-      const { base_model, model_name } = loraMetadataItem.lora;
+      const { lora } = loraMetadataItem;
 
-      const matchingLoRA = loraModels
-        ? loraModelsAdapterSelectors.selectById(loraModels, `${base_model}/lora/${model_name}`)
-        : undefined;
+      const matchingLoRA = loraModels ? loraModelsAdapterSelectors.selectById(loraModels, lora.key) : undefined;
 
       if (!matchingLoRA) {
         return { lora: null, error: 'LoRA model is not installed' };
       }
 
-      const isCompatibleBaseModel = matchingLoRA?.base_model === (newModel ?? model)?.base_model;
+      const isCompatibleBaseModel = matchingLoRA?.base === (newModel ?? model)?.base;
 
       if (!isCompatibleBaseModel) {
         return {
@@ -520,17 +518,14 @@ export const useRecallParameters = () => {
         controlnetMetadataItem;
 
       const matchingControlNetModel = controlNetModels
-        ? controlNetModelsAdapterSelectors.selectById(
-            controlNetModels,
-            `${control_model.base_model}/controlnet/${control_model.model_name}`
-          )
+        ? controlNetModelsAdapterSelectors.selectById(controlNetModels, control_model.key)
         : undefined;
 
       if (!matchingControlNetModel) {
         return { controlnet: null, error: 'ControlNet model is not installed' };
       }
 
-      const isCompatibleBaseModel = matchingControlNetModel?.base_model === (newModel ?? model)?.base_model;
+      const isCompatibleBaseModel = matchingControlNetModel?.base === (newModel ?? model)?.base;
 
       if (!isCompatibleBaseModel) {
         return {
@@ -597,17 +592,14 @@ export const useRecallParameters = () => {
         t2iAdapterMetadataItem;
 
       const matchingT2IAdapterModel = t2iAdapterModels
-        ? t2iAdapterModelsAdapterSelectors.selectById(
-            t2iAdapterModels,
-            `${t2i_adapter_model.base_model}/t2i_adapter/${t2i_adapter_model.model_name}`
-          )
+        ? t2iAdapterModelsAdapterSelectors.selectById(t2iAdapterModels, t2i_adapter_model.key)
         : undefined;
 
       if (!matchingT2IAdapterModel) {
         return { controlnet: null, error: 'ControlNet model is not installed' };
       }
 
-      const isCompatibleBaseModel = matchingT2IAdapterModel?.base_model === (newModel ?? model)?.base_model;
+      const isCompatibleBaseModel = matchingT2IAdapterModel?.base === (newModel ?? model)?.base;
 
       if (!isCompatibleBaseModel) {
         return {
@@ -672,17 +664,14 @@ export const useRecallParameters = () => {
       const { image, ip_adapter_model, weight, begin_step_percent, end_step_percent } = ipAdapterMetadataItem;
 
       const matchingIPAdapterModel = ipAdapterModels
-        ? ipAdapterModelsAdapterSelectors.selectById(
-            ipAdapterModels,
-            `${ip_adapter_model.base_model}/ip_adapter/${ip_adapter_model.model_name}`
-          )
+        ? ipAdapterModelsAdapterSelectors.selectById(ipAdapterModels, ip_adapter_model.key)
         : undefined;
 
       if (!matchingIPAdapterModel) {
         return { ipAdapter: null, error: 'IP Adapter model is not installed' };
       }
 
-      const isCompatibleBaseModel = matchingIPAdapterModel?.base_model === (newModel ?? model)?.base_model;
+      const isCompatibleBaseModel = matchingIPAdapterModel?.base === (newModel ?? model)?.base;
 
       if (!isCompatibleBaseModel) {
         return {
diff --git a/invokeai/frontend/web/src/features/parameters/store/generationSlice.ts b/invokeai/frontend/web/src/features/parameters/store/generationSlice.ts
index df98943cd3..1666a34d6a 100644
--- a/invokeai/frontend/web/src/features/parameters/store/generationSlice.ts
+++ b/invokeai/frontend/web/src/features/parameters/store/generationSlice.ts
@@ -158,15 +158,15 @@ export const generationSlice = createSlice({
         // Clamp ClipSkip Based On Selected Model
         // TODO(psyche): remove this special handling when https://github.com/invoke-ai/InvokeAI/issues/4583 is resolved
         // WIP PR here: https://github.com/invoke-ai/InvokeAI/pull/4624
-        if (newModel.base_model === 'sdxl') {
+        if (newModel.base === 'sdxl') {
           // We don't support clip skip for SDXL yet - it's not in the graphs
           state.clipSkip = 0;
         } else {
-          const { maxClip } = CLIP_SKIP_MAP[newModel.base_model];
+          const { maxClip } = CLIP_SKIP_MAP[newModel.base];
           state.clipSkip = clamp(state.clipSkip, 0, maxClip);
         }
 
-        if (action.meta.previousModel?.base_model === newModel.base_model) {
+        if (action.meta.previousModel?.base === newModel.base) {
           // The base model hasn't changed, we don't need to optimize the size
           return;
         }
diff --git a/invokeai/frontend/web/src/features/parameters/types/parameterSchemas.ts b/invokeai/frontend/web/src/features/parameters/types/parameterSchemas.ts
index 7a5efe9dcf..abd8ee2810 100644
--- a/invokeai/frontend/web/src/features/parameters/types/parameterSchemas.ts
+++ b/invokeai/frontend/web/src/features/parameters/types/parameterSchemas.ts
@@ -1,5 +1,6 @@
 import { NUMPY_RAND_MAX } from 'app/constants';
 import {
+  zBaseModel,
   zControlNetModelField,
   zIPAdapterModelField,
   zLoRAModelField,
@@ -104,48 +105,48 @@ export const isParameterAspectRatio = (val: unknown): val is ParameterAspectRati
 // #endregion
 
 // #region Model
-export const zParameterModel = zMainModelField;
+export const zParameterModel = zMainModelField.extend({ base: zBaseModel });
 export type ParameterModel = z.infer<typeof zParameterModel>;
 export const isParameterModel = (val: unknown): val is ParameterModel => zParameterModel.safeParse(val).success;
 // #endregion
 
 // #region SDXL Refiner Model
-export const zParameterSDXLRefinerModel = zSDXLRefinerModelField;
+export const zParameterSDXLRefinerModel = zSDXLRefinerModelField.extend({ base: zBaseModel });
 export type ParameterSDXLRefinerModel = z.infer<typeof zParameterSDXLRefinerModel>;
 export const isParameterSDXLRefinerModel = (val: unknown): val is ParameterSDXLRefinerModel =>
   zParameterSDXLRefinerModel.safeParse(val).success;
 // #endregion
 
 // #region VAE Model
-export const zParameterVAEModel = zVAEModelField;
+export const zParameterVAEModel = zVAEModelField.extend({ base: zBaseModel });
 export type ParameterVAEModel = z.infer<typeof zParameterVAEModel>;
 export const isParameterVAEModel = (val: unknown): val is ParameterVAEModel =>
   zParameterVAEModel.safeParse(val).success;
 // #endregion
 
 // #region LoRA Model
-export const zParameterLoRAModel = zLoRAModelField;
+export const zParameterLoRAModel = zLoRAModelField.extend({ base: zBaseModel });
 export type ParameterLoRAModel = z.infer<typeof zParameterLoRAModel>;
 export const isParameterLoRAModel = (val: unknown): val is ParameterLoRAModel =>
   zParameterLoRAModel.safeParse(val).success;
 // #endregion
 
 // #region ControlNet Model
-export const zParameterControlNetModel = zControlNetModelField;
+export const zParameterControlNetModel = zControlNetModelField.extend({ base: zBaseModel });
 export type ParameterControlNetModel = z.infer<typeof zParameterLoRAModel>;
 export const isParameterControlNetModel = (val: unknown): val is ParameterControlNetModel =>
   zParameterControlNetModel.safeParse(val).success;
 // #endregion
 
 // #region IP Adapter Model
-export const zParameterIPAdapterModel = zIPAdapterModelField;
+export const zParameterIPAdapterModel = zIPAdapterModelField.extend({ base: zBaseModel });
 export type ParameterIPAdapterModel = z.infer<typeof zParameterIPAdapterModel>;
 export const isParameterIPAdapterModel = (val: unknown): val is ParameterIPAdapterModel =>
   zParameterIPAdapterModel.safeParse(val).success;
 // #endregion
 
 // #region T2I Adapter Model
-export const zParameterT2IAdapterModel = zT2IAdapterModelField;
+export const zParameterT2IAdapterModel = zT2IAdapterModelField.extend({ base: zBaseModel });
 export type ParameterT2IAdapterModel = z.infer<typeof zParameterT2IAdapterModel>;
 export const isParameterT2IAdapterModel = (val: unknown): val is ParameterT2IAdapterModel =>
   zParameterT2IAdapterModel.safeParse(val).success;
diff --git a/invokeai/frontend/web/src/features/parameters/util/optimalDimension.ts b/invokeai/frontend/web/src/features/parameters/util/optimalDimension.ts
index 1c550eb8a4..92b4f18272 100644
--- a/invokeai/frontend/web/src/features/parameters/util/optimalDimension.ts
+++ b/invokeai/frontend/web/src/features/parameters/util/optimalDimension.ts
@@ -1,12 +1,12 @@
-import type { ModelIdentifier } from 'features/nodes/types/common';
+import type { ModelIdentifierWithBase } from 'features/nodes/types/common';
 
 /**
  * Gets the optimal dimension for a givel model, based on the model's base_model
  * @param model The model identifier
  * @returns The optimal dimension for the model
  */
-export const getOptimalDimension = (model?: ModelIdentifier | null): number =>
-  model?.base_model === 'sdxl' ? 1024 : 512;
+export const getOptimalDimension = (model?: ModelIdentifierWithBase | null): number =>
+  model?.base === 'sdxl' ? 1024 : 512;
 
 const MIN_AREA_FACTOR = 0.8;
 const MAX_AREA_FACTOR = 1.2;
diff --git a/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerModelSelect.tsx b/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerModelSelect.tsx
index 5559ec76b7..4c54251557 100644
--- a/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerModelSelect.tsx
+++ b/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerModelSelect.tsx
@@ -7,12 +7,12 @@ import { refinerModelChanged, selectSdxlSlice } from 'features/sdxl/store/sdxlSl
 import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 import { REFINER_BASE_MODELS } from 'services/api/constants';
-import type { MainModelConfigEntity } from 'services/api/endpoints/models';
+import type { MainModelConfig } from 'services/api/endpoints/models';
 import { useGetMainModelsQuery } from 'services/api/endpoints/models';
 
 const selectModel = createMemoizedSelector(selectSdxlSlice, (sdxl) => sdxl.refinerModel);
 
-const optionsFilter = (model: MainModelConfigEntity) => model.base_model === 'sdxl-refiner';
+const optionsFilter = (model: MainModelConfig) => model.base_model === 'sdxl-refiner';
 
 const ParamSDXLRefinerModelSelect = () => {
   const dispatch = useAppDispatch();
@@ -20,7 +20,7 @@ const ParamSDXLRefinerModelSelect = () => {
   const { t } = useTranslation();
   const { data, isLoading } = useGetMainModelsQuery(REFINER_BASE_MODELS);
   const _onChange = useCallback(
-    (model: MainModelConfigEntity | null) => {
+    (model: MainModelConfig | null) => {
       if (!model) {
         dispatch(refinerModelChanged(null));
         return;
diff --git a/invokeai/frontend/web/src/features/settingsAccordions/components/AdvancedSettingsAccordion/AdvancedSettingsAccordion.tsx b/invokeai/frontend/web/src/features/settingsAccordions/components/AdvancedSettingsAccordion/AdvancedSettingsAccordion.tsx
index bceee915cd..fc8c54576c 100644
--- a/invokeai/frontend/web/src/features/settingsAccordions/components/AdvancedSettingsAccordion/AdvancedSettingsAccordion.tsx
+++ b/invokeai/frontend/web/src/features/settingsAccordions/components/AdvancedSettingsAccordion/AdvancedSettingsAccordion.tsx
@@ -24,7 +24,8 @@ const formLabelProps2: FormLabelProps = {
 const selectBadges = createMemoizedSelector(selectGenerationSlice, (generation) => {
   const badges: (string | number)[] = [];
   if (generation.vae) {
-    let vaeBadge = generation.vae.model_name;
+    // TODO(MM2): Fetch the vae name
+    let vaeBadge = generation.vae.key;
     if (generation.vaePrecision === 'fp16') {
       vaeBadge += ` ${generation.vaePrecision}`;
     }
diff --git a/invokeai/frontend/web/src/features/settingsAccordions/components/GenerationSettingsAccordion/GenerationSettingsAccordion.tsx b/invokeai/frontend/web/src/features/settingsAccordions/components/GenerationSettingsAccordion/GenerationSettingsAccordion.tsx
index 077875a8a7..cda7dcf6e9 100644
--- a/invokeai/frontend/web/src/features/settingsAccordions/components/GenerationSettingsAccordion/GenerationSettingsAccordion.tsx
+++ b/invokeai/frontend/web/src/features/settingsAccordions/components/GenerationSettingsAccordion/GenerationSettingsAccordion.tsx
@@ -35,9 +35,10 @@ const badgesSelector = createMemoizedSelector(selectLoraSlice, selectGenerationS
   const enabledLoRAsCount = filter(lora.loras, (l) => !!l.isEnabled).length;
   const loraTabBadges = enabledLoRAsCount ? [enabledLoRAsCount] : [];
   const accordionBadges: (string | number)[] = [];
+  // TODO(MM2): fetch model name
   if (generation.model) {
-    accordionBadges.push(generation.model.model_name);
-    accordionBadges.push(generation.model.base_model);
+    accordionBadges.push(generation.model.key);
+    accordionBadges.push(generation.model.base);
   }
 
   return { loraTabBadges, accordionBadges };
diff --git a/invokeai/frontend/web/src/features/settingsAccordions/components/ImageSettingsAccordion/ImageSettingsAccordion.tsx b/invokeai/frontend/web/src/features/settingsAccordions/components/ImageSettingsAccordion/ImageSettingsAccordion.tsx
index 2f778fe717..8f876850e8 100644
--- a/invokeai/frontend/web/src/features/settingsAccordions/components/ImageSettingsAccordion/ImageSettingsAccordion.tsx
+++ b/invokeai/frontend/web/src/features/settingsAccordions/components/ImageSettingsAccordion/ImageSettingsAccordion.tsx
@@ -56,7 +56,7 @@ const selector = createMemoizedSelector(
     if (hrfEnabled) {
       badges.push('HiRes Fix');
     }
-    return { badges, activeTabName, isSDXL: model?.base_model === 'sdxl' };
+    return { badges, activeTabName, isSDXL: model?.base === 'sdxl' };
   }
 );
 
diff --git a/invokeai/frontend/web/src/features/ui/components/ParametersPanel.tsx b/invokeai/frontend/web/src/features/ui/components/ParametersPanel.tsx
index d52b2d9000..a74d132bd6 100644
--- a/invokeai/frontend/web/src/features/ui/components/ParametersPanel.tsx
+++ b/invokeai/frontend/web/src/features/ui/components/ParametersPanel.tsx
@@ -22,7 +22,7 @@ const overlayScrollbarsStyles: CSSProperties = {
 
 const ParametersPanel = () => {
   const activeTabName = useAppSelector(activeTabNameSelector);
-  const isSDXL = useAppSelector((s) => s.generation.model?.base_model === 'sdxl');
+  const isSDXL = useAppSelector((s) => s.generation.model?.base === 'sdxl');
 
   return (
     <Flex w="full" h="full" flexDir="column" gap={2}>
diff --git a/invokeai/frontend/web/src/services/api/endpoints/models.ts b/invokeai/frontend/web/src/services/api/endpoints/models.ts
index c11c8b45e5..97e221454d 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/models.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/models.ts
@@ -1,64 +1,26 @@
-import type { EntityState } from '@reduxjs/toolkit';
+import type { EntityAdapter, EntityState } from '@reduxjs/toolkit';
 import { createEntityAdapter } from '@reduxjs/toolkit';
 import { getSelectorsOptions } from 'app/store/createMemoizedSelector';
-import { cloneDeep } from 'lodash-es';
 import queryString from 'query-string';
 import type { operations, paths } from 'services/api/schema';
 import type {
   AnyModelConfig,
   BaseModelType,
-  CheckpointModelConfig,
-  ControlNetModelConfig,
-  DiffusersModelConfig,
+  ControlNetConfig,
   ImportModelConfig,
-  IPAdapterModelConfig,
-  LoRAModelConfig,
+  IPAdapterConfig,
+  LoRAConfig,
   MainModelConfig,
   MergeModelConfig,
   ModelType,
-  T2IAdapterModelConfig,
-  TextualInversionModelConfig,
-  VaeModelConfig,
+  T2IAdapterConfig,
+  TextualInversionConfig,
+  VAEConfig,
 } from 'services/api/types';
 
-import type { ApiTagDescription } from '..';
+import type { ApiTagDescription, tagTypes } from '..';
 import { api, LIST_TAG } from '..';
 
-export type DiffusersModelConfigEntity = DiffusersModelConfig & { id: string };
-export type CheckpointModelConfigEntity = CheckpointModelConfig & {
-  id: string;
-};
-export type MainModelConfigEntity = DiffusersModelConfigEntity | CheckpointModelConfigEntity;
-
-export type LoRAModelConfigEntity = LoRAModelConfig & { id: string };
-
-export type ControlNetModelConfigEntity = ControlNetModelConfig & {
-  id: string;
-};
-
-export type IPAdapterModelConfigEntity = IPAdapterModelConfig & {
-  id: string;
-};
-
-export type T2IAdapterModelConfigEntity = T2IAdapterModelConfig & {
-  id: string;
-};
-
-export type TextualInversionModelConfigEntity = TextualInversionModelConfig & {
-  id: string;
-};
-
-export type VaeModelConfigEntity = VaeModelConfig & { id: string };
-
-export type AnyModelConfigEntity =
-  | MainModelConfigEntity
-  | LoRAModelConfigEntity
-  | ControlNetModelConfigEntity
-  | IPAdapterModelConfigEntity
-  | T2IAdapterModelConfigEntity
-  | TextualInversionModelConfigEntity
-  | VaeModelConfigEntity;
-
 type UpdateMainModelArg = {
   base_model: BaseModelType;
   model_name: string;
@@ -68,11 +30,11 @@ type UpdateMainModelArg = {
 type UpdateLoRAModelArg = {
   base_model: BaseModelType;
   model_name: string;
-  body: LoRAModelConfig;
+  body: LoRAConfig;
 };
 
 type UpdateMainModelResponse =
-  paths['/api/v1/models/{base_model}/{model_type}/{model_name}']['patch']['responses']['200']['content']['application/json'];
+  paths['/api/v2/models/i/{key}']['patch']['responses']['200']['content']['application/json'];
 
 type UpdateLoRAModelResponse = UpdateMainModelResponse;
 
@@ -128,59 +90,71 @@ type CheckpointConfigsResponse =
 
 type SearchFolderArg = operations['search_for_models']['parameters']['query'];
 
-export const mainModelsAdapter = createEntityAdapter<MainModelConfigEntity>({
-  sortComparer: (a, b) => a.model_name.localeCompare(b.model_name),
+export const mainModelsAdapter = createEntityAdapter<MainModelConfig, string>({
+  selectId: (entity) => entity.key,
+  sortComparer: (a, b) => a.name.localeCompare(b.name),
 });
 export const mainModelsAdapterSelectors = mainModelsAdapter.getSelectors(undefined, getSelectorsOptions);
-export const loraModelsAdapter = createEntityAdapter<LoRAModelConfigEntity>({
-  sortComparer: (a, b) => a.model_name.localeCompare(b.model_name),
+export const loraModelsAdapter = createEntityAdapter<LoRAConfig, string>({
+  selectId: (entity) => entity.key,
+  sortComparer: (a, b) => a.name.localeCompare(b.name),
 });
 export const loraModelsAdapterSelectors = loraModelsAdapter.getSelectors(undefined, getSelectorsOptions);
-export const controlNetModelsAdapter = createEntityAdapter<ControlNetModelConfigEntity>({
-  sortComparer: (a, b) => a.model_name.localeCompare(b.model_name),
+export const controlNetModelsAdapter = createEntityAdapter<ControlNetConfig, string>({
+  selectId: (entity) => entity.key,
+  sortComparer: (a, b) => a.name.localeCompare(b.name),
 });
 export const controlNetModelsAdapterSelectors = controlNetModelsAdapter.getSelectors(undefined, getSelectorsOptions);
-export const ipAdapterModelsAdapter = createEntityAdapter<IPAdapterModelConfigEntity>({
-  sortComparer: (a, b) => a.model_name.localeCompare(b.model_name),
+export const ipAdapterModelsAdapter = createEntityAdapter<IPAdapterConfig, string>({
+  selectId: (entity) => entity.key,
+  sortComparer: (a, b) => a.name.localeCompare(b.name),
 });
 export const ipAdapterModelsAdapterSelectors = ipAdapterModelsAdapter.getSelectors(undefined, getSelectorsOptions);
-export const t2iAdapterModelsAdapter = createEntityAdapter<T2IAdapterModelConfigEntity>({
-  sortComparer: (a, b) => a.model_name.localeCompare(b.model_name),
+export const t2iAdapterModelsAdapter = createEntityAdapter<T2IAdapterConfig, string>({
+  selectId: (entity) => entity.key,
+  sortComparer: (a, b) => a.name.localeCompare(b.name),
 });
 export const t2iAdapterModelsAdapterSelectors = t2iAdapterModelsAdapter.getSelectors(undefined, getSelectorsOptions);
-export const textualInversionModelsAdapter = createEntityAdapter<TextualInversionModelConfigEntity>({
-  sortComparer: (a, b) => a.model_name.localeCompare(b.model_name),
+export const textualInversionModelsAdapter = createEntityAdapter<TextualInversionConfig, string>({
+  selectId: (entity) => entity.key,
+  sortComparer: (a, b) => a.name.localeCompare(b.name),
 });
 export const textualInversionModelsAdapterSelectors = textualInversionModelsAdapter.getSelectors(
   undefined,
   getSelectorsOptions
 );
-export const vaeModelsAdapter = createEntityAdapter<VaeModelConfigEntity>({
-  sortComparer: (a, b) => a.model_name.localeCompare(b.model_name),
+export const vaeModelsAdapter = createEntityAdapter<VAEConfig, string>({
+  selectId: (entity) => entity.key,
+  sortComparer: (a, b) => a.name.localeCompare(b.name),
 });
 export const vaeModelsAdapterSelectors = vaeModelsAdapter.getSelectors(undefined, getSelectorsOptions);
 
-export const getModelId = ({
-  base_model,
-  model_type,
-  model_name,
-}: Pick<AnyModelConfig, 'base_model' | 'model_name' | 'model_type'>) => `${base_model}/${model_type}/${model_name}`;
+const buildProvidesTags =
+  <TEntity extends AnyModelConfig>(tagType: (typeof tagTypes)[number]) =>
+  (result: EntityState<TEntity, string> | undefined) => {
+    const tags: ApiTagDescription[] = [{ type: tagType, id: LIST_TAG }, 'Model'];
 
-const createModelEntities = <T extends AnyModelConfigEntity>(models: AnyModelConfig[]): T[] => {
-  const entityArray: T[] = [];
-  models.forEach((model) => {
-    const entity = {
-      ...cloneDeep(model),
-      id: getModelId(model),
-    } as T;
-    entityArray.push(entity);
-  });
-  return entityArray;
-};
+    if (result) {
+      tags.push(
+        ...result.ids.map((id) => ({
+          type: tagType,
+          id,
+        }))
+      );
+    }
+
+    return tags;
+  };
+
+const buildTransformResponse =
+  <T extends AnyModelConfig>(adapter: EntityAdapter<T, string>) =>
+  (response: { models: T[] }) => {
+    return adapter.setAll(adapter.getInitialState(), response.models);
+  };
 
 export const modelsApi = api.injectEndpoints({
   endpoints: (build) => ({
-    getMainModels: build.query<EntityState<MainModelConfigEntity, string>, BaseModelType[]>({
+    getMainModels: build.query<EntityState<MainModelConfig, string>, BaseModelType[]>({
       query: (base_models) => {
         const params = {
           model_type: 'main',
@@ -190,24 +164,8 @@ export const modelsApi = api.injectEndpoints({
         const query = queryString.stringify(params, { arrayFormat: 'none' });
         return `models/?${query}`;
       },
-      providesTags: (result) => {
-        const tags: ApiTagDescription[] = [{ type: 'MainModel', id: LIST_TAG }, 'Model'];
-
-        if (result) {
-          tags.push(
-            ...result.ids.map((id) => ({
-              type: 'MainModel' as const,
-              id,
-            }))
-          );
-        }
-
-        return tags;
-      },
-      transformResponse: (response: { models: MainModelConfig[] }) => {
-        const entities = createModelEntities<MainModelConfigEntity>(response.models);
-        return mainModelsAdapter.setAll(mainModelsAdapter.getInitialState(), entities);
-      },
+      providesTags: buildProvidesTags<MainModelConfig>('MainModel'),
+      transformResponse: buildTransformResponse<MainModelConfig>(mainModelsAdapter),
     }),
     updateMainModels: build.mutation<UpdateMainModelResponse, UpdateMainModelArg>({
       query: ({ base_model, model_name, body }) => {
@@ -277,26 +235,10 @@ export const modelsApi = api.injectEndpoints({
       },
       invalidatesTags: ['Model'],
     }),
-    getLoRAModels: build.query<EntityState<LoRAModelConfigEntity, string>, void>({
+    getLoRAModels: build.query<EntityState<LoRAConfig, string>, void>({
       query: () => ({ url: 'models/', params: { model_type: 'lora' } }),
-      providesTags: (result) => {
-        const tags: ApiTagDescription[] = [{ type: 'LoRAModel', id: LIST_TAG }, 'Model'];
-
-        if (result) {
-          tags.push(
-            ...result.ids.map((id) => ({
-              type: 'LoRAModel' as const,
-              id,
-            }))
-          );
-        }
-
-        return tags;
-      },
-      transformResponse: (response: { models: LoRAModelConfig[] }) => {
-        const entities = createModelEntities<LoRAModelConfigEntity>(response.models);
-        return loraModelsAdapter.setAll(loraModelsAdapter.getInitialState(), entities);
-      },
+      providesTags: buildProvidesTags<LoRAConfig>('LoRAModel'),
+      transformResponse: buildTransformResponse<LoRAConfig>(loraModelsAdapter),
     }),
     updateLoRAModels: build.mutation<UpdateLoRAModelResponse, UpdateLoRAModelArg>({
       query: ({ base_model, model_name, body }) => {
@@ -317,110 +259,30 @@ export const modelsApi = api.injectEndpoints({
       },
       invalidatesTags: [{ type: 'LoRAModel', id: LIST_TAG }],
     }),
-    getControlNetModels: build.query<EntityState<ControlNetModelConfigEntity, string>, void>({
+    getControlNetModels: build.query<EntityState<ControlNetConfig, string>, void>({
       query: () => ({ url: 'models/', params: { model_type: 'controlnet' } }),
-      providesTags: (result) => {
-        const tags: ApiTagDescription[] = [{ type: 'ControlNetModel', id: LIST_TAG }, 'Model'];
-
-        if (result) {
-          tags.push(
-            ...result.ids.map((id) => ({
-              type: 'ControlNetModel' as const,
-              id,
-            }))
-          );
-        }
-
-        return tags;
-      },
-      transformResponse: (response: { models: ControlNetModelConfig[] }) => {
-        const entities = createModelEntities<ControlNetModelConfigEntity>(response.models);
-        return controlNetModelsAdapter.setAll(controlNetModelsAdapter.getInitialState(), entities);
-      },
+      providesTags: buildProvidesTags<ControlNetConfig>('ControlNetModel'),
+      transformResponse: buildTransformResponse<ControlNetConfig>(controlNetModelsAdapter),
     }),
-    getIPAdapterModels: build.query<EntityState<IPAdapterModelConfigEntity, string>, void>({
+    getIPAdapterModels: build.query<EntityState<IPAdapterConfig, string>, void>({
       query: () => ({ url: 'models/', params: { model_type: 'ip_adapter' } }),
-      providesTags: (result) => {
-        const tags: ApiTagDescription[] = [{ type: 'IPAdapterModel', id: LIST_TAG }, 'Model'];
-
-        if (result) {
-          tags.push(
-            ...result.ids.map((id) => ({
-              type: 'IPAdapterModel' as const,
-              id,
-            }))
-          );
-        }
-
-        return tags;
-      },
-      transformResponse: (response: { models: IPAdapterModelConfig[] }) => {
-        const entities = createModelEntities<IPAdapterModelConfigEntity>(response.models);
-        return ipAdapterModelsAdapter.setAll(ipAdapterModelsAdapter.getInitialState(), entities);
-      },
+      providesTags: buildProvidesTags<IPAdapterConfig>('IPAdapterModel'),
+      transformResponse: buildTransformResponse<IPAdapterConfig>(ipAdapterModelsAdapter),
     }),
-    getT2IAdapterModels: build.query<EntityState<T2IAdapterModelConfigEntity, string>, void>({
+    getT2IAdapterModels: build.query<EntityState<T2IAdapterConfig, string>, void>({
       query: () => ({ url: 'models/', params: { model_type: 't2i_adapter' } }),
-      providesTags: (result) => {
-        const tags: ApiTagDescription[] = [{ type: 'T2IAdapterModel', id: LIST_TAG }, 'Model'];
-
-        if (result) {
-          tags.push(
-            ...result.ids.map((id) => ({
-              type: 'T2IAdapterModel' as const,
-              id,
-            }))
-          );
-        }
-
-        return tags;
-      },
-      transformResponse: (response: { models: T2IAdapterModelConfig[] }) => {
-        const entities = createModelEntities<T2IAdapterModelConfigEntity>(response.models);
-        return t2iAdapterModelsAdapter.setAll(t2iAdapterModelsAdapter.getInitialState(), entities);
-      },
+      providesTags: buildProvidesTags<T2IAdapterConfig>('T2IAdapterModel'),
+      transformResponse: buildTransformResponse<T2IAdapterConfig>(t2iAdapterModelsAdapter),
     }),
-    getVaeModels: build.query<EntityState<VaeModelConfigEntity, string>, void>({
+    getVaeModels: build.query<EntityState<VAEConfig, string>, void>({
       query: () => ({ url: 'models/', params: { model_type: 'vae' } }),
-      providesTags: (result) => {
-        const tags: ApiTagDescription[] = [{ type: 'VaeModel', id: LIST_TAG }, 'Model'];
-
-        if (result) {
-          tags.push(
-            ...result.ids.map((id) => ({
-              type: 'VaeModel' as const,
-              id,
-            }))
-          );
-        }
-
-        return tags;
-      },
-      transformResponse: (response: { models: VaeModelConfig[] }) => {
-        const entities = createModelEntities<VaeModelConfigEntity>(response.models);
-        return vaeModelsAdapter.setAll(vaeModelsAdapter.getInitialState(), entities);
-      },
+      providesTags: buildProvidesTags<VAEConfig>('VaeModel'),
+      transformResponse: buildTransformResponse<VAEConfig>(vaeModelsAdapter),
     }),
-    getTextualInversionModels: build.query<EntityState<TextualInversionModelConfigEntity, string>, void>({
+    getTextualInversionModels: build.query<EntityState<TextualInversionConfig, string>, void>({
       query: () => ({ url: 'models/', params: { model_type: 'embedding' } }),
-      providesTags: (result) => {
-        const tags: ApiTagDescription[] = [{ type: 'TextualInversionModel', id: LIST_TAG }, 'Model'];
-
-        if (result) {
-          tags.push(
-            ...result.ids.map((id) => ({
-              type: 'TextualInversionModel' as const,
-              id,
-            }))
-          );
-        }
-
-        return tags;
-      },
-      transformResponse: (response: { models: TextualInversionModelConfig[] }) => {
-        const entities = createModelEntities<TextualInversionModelConfigEntity>(response.models);
-        return textualInversionModelsAdapter.setAll(textualInversionModelsAdapter.getInitialState(), entities);
-      },
+      providesTags: buildProvidesTags<TextualInversionConfig>('TextualInversionModel'),
+      transformResponse: buildTransformResponse<TextualInversionConfig>(textualInversionModelsAdapter),
     }),
     getModelsInFolder: build.query<SearchFolderResponse, SearchFolderArg>({
       query: (arg) => {
diff --git a/invokeai/frontend/web/src/services/api/types.ts b/invokeai/frontend/web/src/services/api/types.ts
index f9a1decf65..7a02cc5568 100644
--- a/invokeai/frontend/web/src/services/api/types.ts
+++ b/invokeai/frontend/web/src/services/api/types.ts
@@ -2,6 +2,7 @@ import type { UseToastOptions } from '@invoke-ai/ui-library';
 import type { EntityState } from '@reduxjs/toolkit';
 import type { components, paths } from 'services/api/schema';
 import type { O } from 'ts-toolbelt';
+import type { SetRequired } from 'type-fest';
 
 export type S = components['schemas'];
 
@@ -54,40 +55,34 @@ export type LoRAModelFormat = S['LoRAModelFormat'];
 export type ControlNetModelField = S['ControlNetModelField'];
 export type IPAdapterModelField = S['IPAdapterModelField'];
 export type T2IAdapterModelField = S['T2IAdapterModelField'];
-export type ModelsList = S['invokeai__app__api__routers__models__ModelsList'];
 export type ControlField = S['ControlField'];
 export type IPAdapterField = S['IPAdapterField'];
 
 // Model Configs
-export type LoRAModelConfig = S['LoRAModelConfig'];
-export type VaeModelConfig = S['VaeModelConfig'];
-export type ControlNetModelCheckpointConfig = S['ControlNetModelCheckpointConfig'];
-export type ControlNetModelDiffusersConfig = S['ControlNetModelDiffusersConfig'];
-export type ControlNetModelConfig = ControlNetModelCheckpointConfig | ControlNetModelDiffusersConfig;
-export type IPAdapterModelInvokeAIConfig = S['IPAdapterModelInvokeAIConfig'];
-export type IPAdapterModelConfig = IPAdapterModelInvokeAIConfig;
-export type T2IAdapterModelDiffusersConfig = S['T2IAdapterModelDiffusersConfig'];
-export type T2IAdapterModelConfig = T2IAdapterModelDiffusersConfig;
-export type TextualInversionModelConfig = S['TextualInversionModelConfig'];
-export type DiffusersModelConfig =
-  | S['StableDiffusion1ModelDiffusersConfig']
-  | S['StableDiffusion2ModelDiffusersConfig']
-  | S['StableDiffusionXLModelDiffusersConfig'];
-export type CheckpointModelConfig =
-  | S['StableDiffusion1ModelCheckpointConfig']
-  | S['StableDiffusion2ModelCheckpointConfig']
-  | S['StableDiffusionXLModelCheckpointConfig'];
+
+// TODO(MM2): Can we make key required in the pydantic model?
+type KeyRequired<T extends {key?: string}> = SetRequired<T, 'key'>;
+export type LoRAConfig = KeyRequired<S['LoRAConfig']>;
+// TODO(MM2): Can we rename this from Vae -> VAE
+export type VAEConfig = KeyRequired<S['VaeCheckpointConfig']> | KeyRequired<S['VaeDiffusersConfig']>;
+export type ControlNetConfig = KeyRequired<S['ControlNetDiffusersConfig']> | KeyRequired<S['ControlNetCheckpointConfig']>;
+export type IPAdapterConfig = KeyRequired<S['IPAdapterConfig']>;
+// TODO(MM2): Can we rename this to T2IAdapterConfig
+export type T2IAdapterConfig = KeyRequired<S['T2IConfig']>;
+export type TextualInversionConfig = KeyRequired<S['TextualInversionConfig']>;
+export type DiffusersModelConfig = KeyRequired<S['MainDiffusersConfig']>;
+export type CheckpointModelConfig = KeyRequired<S['MainCheckpointConfig']>;
 export type MainModelConfig = DiffusersModelConfig | CheckpointModelConfig;
 export type AnyModelConfig =
-  | LoRAModelConfig
-  | VaeModelConfig
-  | ControlNetModelConfig
-  | IPAdapterModelConfig
-  | T2IAdapterModelConfig
-  | TextualInversionModelConfig
+  | LoRAConfig
+  | VAEConfig
+  | ControlNetConfig
+  | IPAdapterConfig
+  | T2IAdapterConfig
+  | TextualInversionConfig
   | MainModelConfig;
 
-export type MergeModelConfig = S['Body_merge_models'];
+export type MergeModelConfig = S['Body_merge'];
 export type ImportModelConfig = S['Body_import_model'];
 
 // Graphs

From db363b517880e874370d633d88d0917606be8a5a Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Fri, 16 Feb 2024 21:57:30 +1100
Subject: [PATCH 141/411] refactor(ui): url builders for each router

The MM2 router is at `api/v2/models`. URL builder utils make this a bit easier to manage.
---
 .../web/src/services/api/endpoints/appInfo.ts | 24 +++++---
 .../web/src/services/api/endpoints/boards.ts  | 20 +++++--
 .../web/src/services/api/endpoints/images.ts  | 56 ++++++++++++-------
 .../web/src/services/api/endpoints/models.ts  | 53 +++++++++++-------
 .../web/src/services/api/endpoints/queue.ts   | 40 +++++++------
 .../src/services/api/endpoints/utilities.ts   | 12 +++-
 .../src/services/api/endpoints/workflows.ts   | 20 +++++--
 .../frontend/web/src/services/api/index.ts    |  3 +
 .../frontend/web/src/services/api/schema.ts   | 36 ++++++------
 .../frontend/web/src/services/api/types.ts    |  6 +-
 .../frontend/web/src/services/api/util.ts     |  3 +-
 invokeai/frontend/web/vite.config.mts         |  6 +-
 12 files changed, 177 insertions(+), 102 deletions(-)

diff --git a/invokeai/frontend/web/src/services/api/endpoints/appInfo.ts b/invokeai/frontend/web/src/services/api/endpoints/appInfo.ts
index c0916f568e..a7efaafcc8 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/appInfo.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/appInfo.ts
@@ -3,27 +3,35 @@ import type { OpenAPIV3_1 } from 'openapi-types';
 import type { paths } from 'services/api/schema';
 import type { AppConfig, AppDependencyVersions, AppVersion } from 'services/api/types';
 
-import { api } from '..';
+import { api, buildV1Url } from '..';
+
+/**
+ * Builds an endpoint URL for the app router
+ * @example
+ * buildAppInfoUrl('some-path')
+ * // '/api/v1/app/some-path'
+ */
+const buildAppInfoUrl = (path: string = '') => buildV1Url(`app/${path}`);
 
 export const appInfoApi = api.injectEndpoints({
   endpoints: (build) => ({
     getAppVersion: build.query<AppVersion, void>({
       query: () => ({
-        url: `app/version`,
+        url: buildAppInfoUrl('version'),
         method: 'GET',
       }),
       providesTags: ['FetchOnReconnect'],
     }),
     getAppDeps: build.query<AppDependencyVersions, void>({
       query: () => ({
-        url: `app/app_deps`,
+        url: buildAppInfoUrl('app_deps'),
         method: 'GET',
       }),
       providesTags: ['FetchOnReconnect'],
     }),
     getAppConfig: build.query<AppConfig, void>({
       query: () => ({
-        url: `app/config`,
+        url: buildAppInfoUrl('config'),
         method: 'GET',
       }),
       providesTags: ['FetchOnReconnect'],
@@ -33,28 +41,28 @@ export const appInfoApi = api.injectEndpoints({
       void
     >({
       query: () => ({
-        url: `app/invocation_cache/status`,
+        url: buildAppInfoUrl('invocation_cache/status'),
         method: 'GET',
       }),
       providesTags: ['InvocationCacheStatus', 'FetchOnReconnect'],
     }),
     clearInvocationCache: build.mutation<void, void>({
       query: () => ({
-        url: `app/invocation_cache`,
+        url: buildAppInfoUrl('invocation_cache'),
         method: 'DELETE',
       }),
       invalidatesTags: ['InvocationCacheStatus'],
     }),
     enableInvocationCache: build.mutation<void, void>({
       query: () => ({
-        url: `app/invocation_cache/enable`,
+        url: buildAppInfoUrl('invocation_cache/enable'),
         method: 'PUT',
       }),
       invalidatesTags: ['InvocationCacheStatus'],
     }),
     disableInvocationCache: build.mutation<void, void>({
       query: () => ({
-        url: `app/invocation_cache/disable`,
+        url: buildAppInfoUrl('invocation_cache/disable'),
         method: 'PUT',
       }),
       invalidatesTags: ['InvocationCacheStatus'],
diff --git a/invokeai/frontend/web/src/services/api/endpoints/boards.ts b/invokeai/frontend/web/src/services/api/endpoints/boards.ts
index 6977a2bd53..8efda86737 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/boards.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/boards.ts
@@ -9,7 +9,15 @@ import type {
 import { getListImagesUrl } from 'services/api/util';
 
 import type { ApiTagDescription } from '..';
-import { api, LIST_TAG } from '..';
+import { api, buildV1Url, LIST_TAG } from '..';
+
+/**
+ * Builds an endpoint URL for the boards router
+ * @example
+ * buildBoardsUrl('some-path')
+ * // '/api/v1/boards/some-path'
+ */
+export const buildBoardsUrl = (path: string = '') => buildV1Url(`boards/${path}`);
 
 export const boardsApi = api.injectEndpoints({
   endpoints: (build) => ({
@@ -17,7 +25,7 @@ export const boardsApi = api.injectEndpoints({
      * Boards Queries
      */
     listBoards: build.query<OffsetPaginatedResults_BoardDTO_, ListBoardsArg>({
-      query: (arg) => ({ url: 'boards/', params: arg }),
+      query: (arg) => ({ url: buildBoardsUrl(), params: arg }),
       providesTags: (result) => {
         // any list of boards
         const tags: ApiTagDescription[] = [{ type: 'Board', id: LIST_TAG }, 'FetchOnReconnect'];
@@ -38,7 +46,7 @@ export const boardsApi = api.injectEndpoints({
 
     listAllBoards: build.query<Array<BoardDTO>, void>({
       query: () => ({
-        url: 'boards/',
+        url: buildBoardsUrl(),
         params: { all: true },
       }),
       providesTags: (result) => {
@@ -61,7 +69,7 @@ export const boardsApi = api.injectEndpoints({
 
     listAllImageNamesForBoard: build.query<Array<string>, string>({
       query: (board_id) => ({
-        url: `boards/${board_id}/image_names`,
+        url: buildBoardsUrl(`${board_id}/image_names`),
       }),
       providesTags: (result, error, arg) => [{ type: 'ImageNameList', id: arg }, 'FetchOnReconnect'],
       keepUnusedDataFor: 0,
@@ -107,7 +115,7 @@ export const boardsApi = api.injectEndpoints({
 
     createBoard: build.mutation<BoardDTO, string>({
       query: (board_name) => ({
-        url: `boards/`,
+        url: buildBoardsUrl(),
         method: 'POST',
         params: { board_name },
       }),
@@ -116,7 +124,7 @@ export const boardsApi = api.injectEndpoints({
 
     updateBoard: build.mutation<BoardDTO, UpdateBoardArg>({
       query: ({ board_id, changes }) => ({
-        url: `boards/${board_id}`,
+        url: buildBoardsUrl(board_id),
         method: 'PATCH',
         body: changes,
       }),
diff --git a/invokeai/frontend/web/src/services/api/endpoints/images.ts b/invokeai/frontend/web/src/services/api/endpoints/images.ts
index 181c8d23fc..49eb28390f 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/images.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/images.ts
@@ -26,8 +26,24 @@ import {
 } from 'services/api/util';
 
 import type { ApiTagDescription } from '..';
-import { api, LIST_TAG } from '..';
-import { boardsApi } from './boards';
+import { api, buildV1Url, LIST_TAG } from '..';
+import { boardsApi, buildBoardsUrl } from './boards';
+
+/**
+ * Builds an endpoint URL for the images router
+ * @example
+ * buildImagesUrl('some-path')
+ * // '/api/v1/images/some-path'
+ */
+const buildImagesUrl = (path: string = '') => buildV1Url(`images/${path}`);
+
+/**
+ * Builds an endpoint URL for the board_images router
+ * @example
+ * buildBoardImagesUrl('some-path')
+ * // '/api/v1/board_images/some-path'
+ */
+const buildBoardImagesUrl = (path: string = '') => buildV1Url(`board_images/${path}`);
 
 export const imagesApi = api.injectEndpoints({
   endpoints: (build) => ({
@@ -90,20 +106,20 @@ export const imagesApi = api.injectEndpoints({
       keepUnusedDataFor: 86400,
     }),
     getIntermediatesCount: build.query<number, void>({
-      query: () => ({ url: 'images/intermediates' }),
+      query: () => ({ url: buildImagesUrl('intermediates') }),
       providesTags: ['IntermediatesCount', 'FetchOnReconnect'],
     }),
     clearIntermediates: build.mutation<number, void>({
-      query: () => ({ url: `images/intermediates`, method: 'DELETE' }),
+      query: () => ({ url: buildImagesUrl('intermediates'), method: 'DELETE' }),
       invalidatesTags: ['IntermediatesCount'],
     }),
     getImageDTO: build.query<ImageDTO, string>({
-      query: (image_name) => ({ url: `images/i/${image_name}` }),
+      query: (image_name) => ({ url: buildImagesUrl(`i/${image_name}`) }),
       providesTags: (result, error, image_name) => [{ type: 'Image', id: image_name }],
       keepUnusedDataFor: 86400, // 24 hours
     }),
     getImageMetadata: build.query<CoreMetadata | undefined, string>({
-      query: (image_name) => ({ url: `images/i/${image_name}/metadata` }),
+      query: (image_name) => ({ url: buildImagesUrl(`i/${image_name}/metadata`) }),
       providesTags: (result, error, image_name) => [{ type: 'ImageMetadata', id: image_name }],
       transformResponse: (
         response: paths['/api/v1/images/i/{image_name}/metadata']['get']['responses']['200']['content']['application/json']
@@ -130,7 +146,7 @@ export const imagesApi = api.injectEndpoints({
     }),
     deleteImage: build.mutation<void, ImageDTO>({
       query: ({ image_name }) => ({
-        url: `images/i/${image_name}`,
+        url: buildImagesUrl(`i/${image_name}`),
         method: 'DELETE',
       }),
       async onQueryStarted(imageDTO, { dispatch, queryFulfilled }) {
@@ -185,7 +201,7 @@ export const imagesApi = api.injectEndpoints({
       query: ({ imageDTOs }) => {
         const image_names = imageDTOs.map((imageDTO) => imageDTO.image_name);
         return {
-          url: `images/delete`,
+          url: buildImagesUrl('delete'),
           method: 'POST',
           body: {
             image_names,
@@ -258,7 +274,7 @@ export const imagesApi = api.injectEndpoints({
      */
     changeImageIsIntermediate: build.mutation<ImageDTO, { imageDTO: ImageDTO; is_intermediate: boolean }>({
       query: ({ imageDTO, is_intermediate }) => ({
-        url: `images/i/${imageDTO.image_name}`,
+        url: buildImagesUrl(`i/${imageDTO.image_name}`),
         method: 'PATCH',
         body: { is_intermediate },
       }),
@@ -380,7 +396,7 @@ export const imagesApi = api.injectEndpoints({
      */
     changeImageSessionId: build.mutation<ImageDTO, { imageDTO: ImageDTO; session_id: string }>({
       query: ({ imageDTO, session_id }) => ({
-        url: `images/i/${imageDTO.image_name}`,
+        url: buildImagesUrl(`i/${imageDTO.image_name}`),
         method: 'PATCH',
         body: { session_id },
       }),
@@ -417,7 +433,7 @@ export const imagesApi = api.injectEndpoints({
       { imageDTOs: ImageDTO[] }
     >({
       query: ({ imageDTOs: images }) => ({
-        url: `images/star`,
+        url: buildImagesUrl('star'),
         method: 'POST',
         body: { image_names: images.map((img) => img.image_name) },
       }),
@@ -511,7 +527,7 @@ export const imagesApi = api.injectEndpoints({
       { imageDTOs: ImageDTO[] }
     >({
       query: ({ imageDTOs: images }) => ({
-        url: `images/unstar`,
+        url: buildImagesUrl('unstar'),
         method: 'POST',
         body: { image_names: images.map((img) => img.image_name) },
       }),
@@ -611,7 +627,7 @@ export const imagesApi = api.injectEndpoints({
         const formData = new FormData();
         formData.append('file', file);
         return {
-          url: `images/upload`,
+          url: buildImagesUrl('upload'),
           method: 'POST',
           body: formData,
           params: {
@@ -674,7 +690,7 @@ export const imagesApi = api.injectEndpoints({
     }),
 
     deleteBoard: build.mutation<DeleteBoardResult, string>({
-      query: (board_id) => ({ url: `boards/${board_id}`, method: 'DELETE' }),
+      query: (board_id) => ({ url: buildBoardsUrl(board_id), method: 'DELETE' }),
       invalidatesTags: () => [
         { type: 'Board', id: LIST_TAG },
         // invalidate the 'No Board' cache
@@ -764,7 +780,7 @@ export const imagesApi = api.injectEndpoints({
 
     deleteBoardAndImages: build.mutation<DeleteBoardResult, string>({
       query: (board_id) => ({
-        url: `boards/${board_id}`,
+        url: buildBoardsUrl(board_id),
         method: 'DELETE',
         params: { include_images: true },
       }),
@@ -840,7 +856,7 @@ export const imagesApi = api.injectEndpoints({
       query: ({ board_id, imageDTO }) => {
         const { image_name } = imageDTO;
         return {
-          url: `board_images/`,
+          url: buildBoardImagesUrl(),
           method: 'POST',
           body: { board_id, image_name },
         };
@@ -961,7 +977,7 @@ export const imagesApi = api.injectEndpoints({
       query: ({ imageDTO }) => {
         const { image_name } = imageDTO;
         return {
-          url: `board_images/`,
+          url: buildBoardImagesUrl(),
           method: 'DELETE',
           body: { image_name },
         };
@@ -1080,7 +1096,7 @@ export const imagesApi = api.injectEndpoints({
       }
     >({
       query: ({ board_id, imageDTOs }) => ({
-        url: `board_images/batch`,
+        url: buildBoardImagesUrl('batch'),
         method: 'POST',
         body: {
           image_names: imageDTOs.map((i) => i.image_name),
@@ -1197,7 +1213,7 @@ export const imagesApi = api.injectEndpoints({
       }
     >({
       query: ({ imageDTOs }) => ({
-        url: `board_images/batch/delete`,
+        url: buildBoardImagesUrl('batch/delete'),
         method: 'POST',
         body: {
           image_names: imageDTOs.map((i) => i.image_name),
@@ -1321,7 +1337,7 @@ export const imagesApi = api.injectEndpoints({
       components['schemas']['Body_download_images_from_list']
     >({
       query: ({ image_names, board_id }) => ({
-        url: `images/download`,
+        url: buildImagesUrl('download'),
         method: 'POST',
         body: {
           image_names,
diff --git a/invokeai/frontend/web/src/services/api/endpoints/models.ts b/invokeai/frontend/web/src/services/api/endpoints/models.ts
index 97e221454d..9a7f108056 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/models.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/models.ts
@@ -19,7 +19,10 @@ import type {
 } from 'services/api/types';
 
 import type { ApiTagDescription, tagTypes } from '..';
-import { api, LIST_TAG } from '..';
+import { api, buildV2Url, LIST_TAG } from '..';
+
+/* eslint-disable @typescript-eslint/no-explicit-any */
+export const getModelId = (input: any): any => input;
 
 type UpdateMainModelArg = {
   base_model: BaseModelType;
@@ -36,6 +39,8 @@ type UpdateLoRAModelArg = {
 type UpdateMainModelResponse =
   paths['/api/v2/models/i/{key}']['patch']['responses']['200']['content']['application/json'];
 
+type ListModelsArg = NonNullable<paths['/api/models_v2/']['get']['parameters']['query']>;
+
 type UpdateLoRAModelResponse = UpdateMainModelResponse;
 
 type DeleteMainModelArg = {
@@ -152,17 +157,25 @@ const buildTransformResponse =
     return adapter.setAll(adapter.getInitialState(), response.models);
   };
 
+/**
+ * Builds an endpoint URL for the models router
+ * @example
+ * buildModelsUrl('some-path')
+ * // '/api/v1/models/some-path'
+ */
+const buildModelsUrl = (path: string = '') => buildV2Url(`models/${path}`);
+
 export const modelsApi = api.injectEndpoints({
   endpoints: (build) => ({
     getMainModels: build.query<EntityState<MainModelConfig, string>, BaseModelType[]>({
       query: (base_models) => {
-        const params = {
+        const params: ListModelsArg = {
           model_type: 'main',
           base_models,
         };
 
         const query = queryString.stringify(params, { arrayFormat: 'none' });
-        return `models/?${query}`;
+        return buildModelsUrl(`?${query}`);
       },
       providesTags: buildProvidesTags<MainModelConfig>('MainModel'),
       transformResponse: buildTransformResponse<MainModelConfig>(mainModelsAdapter),
@@ -170,7 +183,7 @@ export const modelsApi = api.injectEndpoints({
     updateMainModels: build.mutation<UpdateMainModelResponse, UpdateMainModelArg>({
       query: ({ base_model, model_name, body }) => {
         return {
-          url: `models/${base_model}/main/${model_name}`,
+          url: buildModelsUrl(`${base_model}/main/${model_name}`),
           method: 'PATCH',
           body: body,
         };
@@ -180,7 +193,7 @@ export const modelsApi = api.injectEndpoints({
     importMainModels: build.mutation<ImportMainModelResponse, ImportMainModelArg>({
       query: ({ body }) => {
         return {
-          url: `models/import`,
+          url: buildModelsUrl('import'),
           method: 'POST',
           body: body,
         };
@@ -190,7 +203,7 @@ export const modelsApi = api.injectEndpoints({
     addMainModels: build.mutation<AddMainModelResponse, AddMainModelArg>({
       query: ({ body }) => {
         return {
-          url: `models/add`,
+          url: buildModelsUrl('add'),
           method: 'POST',
           body: body,
         };
@@ -200,7 +213,7 @@ export const modelsApi = api.injectEndpoints({
     deleteMainModels: build.mutation<DeleteMainModelResponse, DeleteMainModelArg>({
       query: ({ base_model, model_name, model_type }) => {
         return {
-          url: `models/${base_model}/${model_type}/${model_name}`,
+          url: buildModelsUrl(`${base_model}/${model_type}/${model_name}`),
           method: 'DELETE',
         };
       },
@@ -209,7 +222,7 @@ export const modelsApi = api.injectEndpoints({
     convertMainModels: build.mutation<ConvertMainModelResponse, ConvertMainModelArg>({
       query: ({ base_model, model_name, convert_dest_directory }) => {
         return {
-          url: `models/convert/${base_model}/main/${model_name}`,
+          url: buildModelsUrl(`convert/${base_model}/main/${model_name}`),
           method: 'PUT',
           params: { convert_dest_directory },
         };
@@ -219,7 +232,7 @@ export const modelsApi = api.injectEndpoints({
     mergeMainModels: build.mutation<MergeMainModelResponse, MergeMainModelArg>({
       query: ({ base_model, body }) => {
         return {
-          url: `models/merge/${base_model}`,
+          url: buildModelsUrl(`merge/${base_model}`),
           method: 'PUT',
           body: body,
         };
@@ -229,21 +242,21 @@ export const modelsApi = api.injectEndpoints({
     syncModels: build.mutation<SyncModelsResponse, void>({
       query: () => {
         return {
-          url: `models/sync`,
+          url: buildModelsUrl('sync'),
           method: 'POST',
         };
       },
       invalidatesTags: ['Model'],
     }),
     getLoRAModels: build.query<EntityState<LoRAConfig, string>, void>({
-      query: () => ({ url: 'models/', params: { model_type: 'lora' } }),
+      query: () => ({ url: buildModelsUrl(), params: { model_type: 'lora' } }),
       providesTags: buildProvidesTags<LoRAConfig>('LoRAModel'),
       transformResponse: buildTransformResponse<LoRAConfig>(loraModelsAdapter),
     }),
     updateLoRAModels: build.mutation<UpdateLoRAModelResponse, UpdateLoRAModelArg>({
       query: ({ base_model, model_name, body }) => {
         return {
-          url: `models/${base_model}/lora/${model_name}`,
+          url: buildModelsUrl(`${base_model}/lora/${model_name}`),
           method: 'PATCH',
           body: body,
         };
@@ -253,34 +266,34 @@ export const modelsApi = api.injectEndpoints({
     deleteLoRAModels: build.mutation<DeleteLoRAModelResponse, DeleteLoRAModelArg>({
       query: ({ base_model, model_name }) => {
         return {
-          url: `models/${base_model}/lora/${model_name}`,
+          url: buildModelsUrl(`${base_model}/lora/${model_name}`),
           method: 'DELETE',
         };
       },
       invalidatesTags: [{ type: 'LoRAModel', id: LIST_TAG }],
     }),
     getControlNetModels: build.query<EntityState<ControlNetConfig, string>, void>({
-      query: () => ({ url: 'models/', params: { model_type: 'controlnet' } }),
+      query: () => ({ url: buildModelsUrl(), params: { model_type: 'controlnet' } }),
       providesTags: buildProvidesTags<ControlNetConfig>('ControlNetModel'),
       transformResponse: buildTransformResponse<ControlNetConfig>(controlNetModelsAdapter),
     }),
     getIPAdapterModels: build.query<EntityState<IPAdapterConfig, string>, void>({
-      query: () => ({ url: 'models/', params: { model_type: 'ip_adapter' } }),
+      query: () => ({ url: buildModelsUrl(), params: { model_type: 'ip_adapter' } }),
       providesTags: buildProvidesTags<IPAdapterConfig>('IPAdapterModel'),
       transformResponse: buildTransformResponse<IPAdapterConfig>(ipAdapterModelsAdapter),
     }),
     getT2IAdapterModels: build.query<EntityState<T2IAdapterConfig, string>, void>({
-      query: () => ({ url: 'models/', params: { model_type: 't2i_adapter' } }),
+      query: () => ({ url: buildModelsUrl(), params: { model_type: 't2i_adapter' } }),
       providesTags: buildProvidesTags<T2IAdapterConfig>('T2IAdapterModel'),
       transformResponse: buildTransformResponse<T2IAdapterConfig>(t2iAdapterModelsAdapter),
     }),
     getVaeModels: build.query<EntityState<VAEConfig, string>, void>({
-      query: () => ({ url: 'models/', params: { model_type: 'vae' } }),
+      query: () => ({ url: buildModelsUrl(), params: { model_type: 'vae' } }),
       providesTags: buildProvidesTags<VAEConfig>('VaeModel'),
       transformResponse: buildTransformResponse<VAEConfig>(vaeModelsAdapter),
     }),
     getTextualInversionModels: build.query<EntityState<TextualInversionConfig, string>, void>({
-      query: () => ({ url: 'models/', params: { model_type: 'embedding' } }),
+      query: () => ({ url: buildModelsUrl(), params: { model_type: 'embedding' } }),
       providesTags: buildProvidesTags<TextualInversionConfig>('TextualInversionModel'),
       transformResponse: buildTransformResponse<TextualInversionConfig>(textualInversionModelsAdapter),
     }),
@@ -288,14 +301,14 @@ export const modelsApi = api.injectEndpoints({
       query: (arg) => {
         const folderQueryStr = queryString.stringify(arg, {});
         return {
-          url: `/models/search?${folderQueryStr}`,
+          url: buildModelsUrl(`search?${folderQueryStr}`),
         };
       },
     }),
     getCheckpointConfigs: build.query<CheckpointConfigsResponse, void>({
       query: () => {
         return {
-          url: `/models/ckpt_confs`,
+          url: buildModelsUrl(`ckpt_confs`),
         };
       },
     }),
diff --git a/invokeai/frontend/web/src/services/api/endpoints/queue.ts b/invokeai/frontend/web/src/services/api/endpoints/queue.ts
index 6c0798a936..385aa8ad12 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/queue.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/queue.ts
@@ -7,7 +7,15 @@ import queryString from 'query-string';
 import type { components, paths } from 'services/api/schema';
 
 import type { ApiTagDescription } from '..';
-import { api } from '..';
+import { api, buildV1Url } from '..';
+
+/**
+ * Builds an endpoint URL for the queue router
+ * @example
+ * buildQueueUrl('some-path')
+ * // '/api/v1/queue/queue_id/some-path'
+ */
+const buildQueueUrl = (path: string = '') => buildV1Url(`queue/${$queueId.get()}/${path}`);
 
 const getListQueueItemsUrl = (queryArgs?: paths['/api/v1/queue/{queue_id}/list']['get']['parameters']['query']) => {
   const query = queryArgs
@@ -17,10 +25,10 @@ const getListQueueItemsUrl = (queryArgs?: paths['/api/v1/queue/{queue_id}/list']
     : undefined;
 
   if (query) {
-    return `queue/${$queueId.get()}/list?${query}`;
+    return buildQueueUrl(`list?${query}`);
   }
 
-  return `queue/${$queueId.get()}/list`;
+  return buildQueueUrl('list');
 };
 
 export type SessionQueueItemStatus = NonNullable<
@@ -58,7 +66,7 @@ export const queueApi = api.injectEndpoints({
       paths['/api/v1/queue/{queue_id}/enqueue_batch']['post']['requestBody']['content']['application/json']
     >({
       query: (arg) => ({
-        url: `queue/${$queueId.get()}/enqueue_batch`,
+        url: buildQueueUrl('enqueue_batch'),
         body: arg,
         method: 'POST',
       }),
@@ -78,7 +86,7 @@ export const queueApi = api.injectEndpoints({
       void
     >({
       query: () => ({
-        url: `queue/${$queueId.get()}/processor/resume`,
+        url: buildQueueUrl('processor/resume'),
         method: 'PUT',
       }),
       invalidatesTags: ['CurrentSessionQueueItem', 'SessionQueueStatus'],
@@ -88,7 +96,7 @@ export const queueApi = api.injectEndpoints({
       void
     >({
       query: () => ({
-        url: `queue/${$queueId.get()}/processor/pause`,
+        url: buildQueueUrl('processor/pause'),
         method: 'PUT',
       }),
       invalidatesTags: ['CurrentSessionQueueItem', 'SessionQueueStatus'],
@@ -98,7 +106,7 @@ export const queueApi = api.injectEndpoints({
       void
     >({
       query: () => ({
-        url: `queue/${$queueId.get()}/prune`,
+        url: buildQueueUrl('prune'),
         method: 'PUT',
       }),
       invalidatesTags: ['SessionQueueStatus', 'BatchStatus'],
@@ -117,7 +125,7 @@ export const queueApi = api.injectEndpoints({
       void
     >({
       query: () => ({
-        url: `queue/${$queueId.get()}/clear`,
+        url: buildQueueUrl('clear'),
         method: 'PUT',
       }),
       invalidatesTags: [
@@ -142,7 +150,7 @@ export const queueApi = api.injectEndpoints({
       void
     >({
       query: () => ({
-        url: `queue/${$queueId.get()}/current`,
+        url: buildQueueUrl('current'),
         method: 'GET',
       }),
       providesTags: (result) => {
@@ -158,7 +166,7 @@ export const queueApi = api.injectEndpoints({
       void
     >({
       query: () => ({
-        url: `queue/${$queueId.get()}/next`,
+        url: buildQueueUrl('next'),
         method: 'GET',
       }),
       providesTags: (result) => {
@@ -174,7 +182,7 @@ export const queueApi = api.injectEndpoints({
       void
     >({
       query: () => ({
-        url: `queue/${$queueId.get()}/status`,
+        url: buildQueueUrl('status'),
         method: 'GET',
       }),
       providesTags: ['SessionQueueStatus', 'FetchOnReconnect'],
@@ -184,7 +192,7 @@ export const queueApi = api.injectEndpoints({
       { batch_id: string }
     >({
       query: ({ batch_id }) => ({
-        url: `queue/${$queueId.get()}/b/${batch_id}/status`,
+        url: buildQueueUrl(`/b/${batch_id}/status`),
         method: 'GET',
       }),
       providesTags: (result) => {
@@ -200,7 +208,7 @@ export const queueApi = api.injectEndpoints({
       number
     >({
       query: (item_id) => ({
-        url: `queue/${$queueId.get()}/i/${item_id}`,
+        url: buildQueueUrl(`i/${item_id}`),
         method: 'GET',
       }),
       providesTags: (result) => {
@@ -216,7 +224,7 @@ export const queueApi = api.injectEndpoints({
       number
     >({
       query: (item_id) => ({
-        url: `queue/${$queueId.get()}/i/${item_id}/cancel`,
+        url: buildQueueUrl(`i/${item_id}/cancel`),
         method: 'PUT',
       }),
       onQueryStarted: async (item_id, { dispatch, queryFulfilled }) => {
@@ -253,7 +261,7 @@ export const queueApi = api.injectEndpoints({
       paths['/api/v1/queue/{queue_id}/cancel_by_batch_ids']['put']['requestBody']['content']['application/json']
     >({
       query: (body) => ({
-        url: `queue/${$queueId.get()}/cancel_by_batch_ids`,
+        url: buildQueueUrl('cancel_by_batch_ids'),
         method: 'PUT',
         body,
       }),
@@ -279,7 +287,7 @@ export const queueApi = api.injectEndpoints({
         method: 'GET',
       }),
       serializeQueryArgs: () => {
-        return `queue/${$queueId.get()}/list`;
+        return buildQueueUrl('list');
       },
       transformResponse: (response: components['schemas']['CursorPaginatedResults_SessionQueueItemDTO_']) =>
         queueItemsAdapter.addMany(
diff --git a/invokeai/frontend/web/src/services/api/endpoints/utilities.ts b/invokeai/frontend/web/src/services/api/endpoints/utilities.ts
index c08ee62dc9..309dd2dc79 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/utilities.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/utilities.ts
@@ -1,6 +1,14 @@
 import type { components } from 'services/api/schema';
 
-import { api } from '..';
+import { api, buildV1Url } from '..';
+
+/**
+ * Builds an endpoint URL for the utilities router
+ * @example
+ * buildUtilitiesUrl('some-path')
+ * // '/api/v1/utilities/some-path'
+ */
+const buildUtilitiesUrl = (path: string = '') => buildV1Url(`utilities/${path}`);
 
 export const utilitiesApi = api.injectEndpoints({
   endpoints: (build) => ({
@@ -9,7 +17,7 @@ export const utilitiesApi = api.injectEndpoints({
       { prompt: string; max_prompts: number }
     >({
       query: (arg) => ({
-        url: 'utilities/dynamicprompts',
+        url: buildUtilitiesUrl('dynamicprompts'),
         body: arg,
         method: 'POST',
       }),
diff --git a/invokeai/frontend/web/src/services/api/endpoints/workflows.ts b/invokeai/frontend/web/src/services/api/endpoints/workflows.ts
index c382f7e111..1e64809e5a 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/workflows.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/workflows.ts
@@ -1,6 +1,14 @@
 import type { paths } from 'services/api/schema';
 
-import { api, LIST_TAG } from '..';
+import { api, buildV1Url, LIST_TAG } from '..';
+
+/**
+ * Builds an endpoint URL for the workflows router
+ * @example
+ * buildWorkflowsUrl('some-path') 
+ * // '/api/v1/workflows/some-path'
+ */
+const buildWorkflowsUrl = (path: string = '') => buildV1Url(`workflows/${path}`);
 
 export const workflowsApi = api.injectEndpoints({
   endpoints: (build) => ({
@@ -8,7 +16,7 @@ export const workflowsApi = api.injectEndpoints({
       paths['/api/v1/workflows/i/{workflow_id}']['get']['responses']['200']['content']['application/json'],
       string
     >({
-      query: (workflow_id) => `workflows/i/${workflow_id}`,
+      query: (workflow_id) => buildWorkflowsUrl(`i/${workflow_id}`),
       providesTags: (result, error, workflow_id) => [{ type: 'Workflow', id: workflow_id }, 'FetchOnReconnect'],
       onQueryStarted: async (arg, api) => {
         const { dispatch, queryFulfilled } = api;
@@ -22,7 +30,7 @@ export const workflowsApi = api.injectEndpoints({
     }),
     deleteWorkflow: build.mutation<void, string>({
       query: (workflow_id) => ({
-        url: `workflows/i/${workflow_id}`,
+        url: buildWorkflowsUrl(`i/${workflow_id}`),
         method: 'DELETE',
       }),
       invalidatesTags: (result, error, workflow_id) => [
@@ -36,7 +44,7 @@ export const workflowsApi = api.injectEndpoints({
       paths['/api/v1/workflows/']['post']['requestBody']['content']['application/json']['workflow']
     >({
       query: (workflow) => ({
-        url: 'workflows/',
+        url: buildWorkflowsUrl(),
         method: 'POST',
         body: { workflow },
       }),
@@ -50,7 +58,7 @@ export const workflowsApi = api.injectEndpoints({
       paths['/api/v1/workflows/i/{workflow_id}']['patch']['requestBody']['content']['application/json']['workflow']
     >({
       query: (workflow) => ({
-        url: `workflows/i/${workflow.id}`,
+        url: buildWorkflowsUrl(`i/${workflow.id}`),
         method: 'PATCH',
         body: { workflow },
       }),
@@ -65,7 +73,7 @@ export const workflowsApi = api.injectEndpoints({
       NonNullable<paths['/api/v1/workflows/']['get']['parameters']['query']>
     >({
       query: (params) => ({
-        url: 'workflows/',
+        url: buildWorkflowsUrl(),
         params,
       }),
       providesTags: ['FetchOnReconnect', { type: 'Workflow', id: LIST_TAG }],
diff --git a/invokeai/frontend/web/src/services/api/index.ts b/invokeai/frontend/web/src/services/api/index.ts
index 6a342bb72d..f32ae34cb7 100644
--- a/invokeai/frontend/web/src/services/api/index.ts
+++ b/invokeai/frontend/web/src/services/api/index.ts
@@ -112,3 +112,6 @@ function getCircularReplacer() {
     return value;
   };
 }
+
+export const buildV1Url = (path: string): string => `api/v1/${path}`;
+export const buildV2Url = (path: string): string => `api/v2/${path}`;
diff --git a/invokeai/frontend/web/src/services/api/schema.ts b/invokeai/frontend/web/src/services/api/schema.ts
index 3393e74d48..40fc262be2 100644
--- a/invokeai/frontend/web/src/services/api/schema.ts
+++ b/invokeai/frontend/web/src/services/api/schema.ts
@@ -4212,7 +4212,7 @@ export type components = {
        * @description The nodes in this graph
        */
       nodes?: {
-        [key: string]: components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["GraphInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["ColorMapImageProcessorInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["DWOpenposeImageProcessorInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["DepthAnythingImageProcessorInvocation"];
+        [key: string]: components["schemas"]["ControlNetInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["ColorMapImageProcessorInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["DWOpenposeImageProcessorInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["GraphInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["DepthAnythingImageProcessorInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["CvInpaintInvocation"];
       };
       /**
        * Edges
@@ -4249,7 +4249,7 @@ export type components = {
        * @description The results of node executions
        */
       results: {
-        [key: string]: components["schemas"]["ImageCollectionOutput"] | components["schemas"]["LatentsOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["MetadataOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["SDXLLoraLoaderOutput"] | components["schemas"]["String2Output"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["VAEOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["GraphInvocationOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["LoraLoaderOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["ClipSkipInvocationOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["CLIPOutput"];
+        [key: string]: components["schemas"]["SchedulerOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["LoraLoaderOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["GraphInvocationOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["SDXLLoraLoaderOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["VAEOutput"] | components["schemas"]["ClipSkipInvocationOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["String2Output"] | components["schemas"]["IntegerOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["LatentsOutput"] | components["schemas"]["MetadataOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["IterateInvocationOutput"];
       };
       /**
        * Errors
@@ -11119,17 +11119,11 @@ export type components = {
      */
     VaeModelFormat: "checkpoint" | "diffusers";
     /**
-     * StableDiffusion2ModelFormat
+     * T2IAdapterModelFormat
      * @description An enumeration.
      * @enum {string}
      */
-    StableDiffusion2ModelFormat: "checkpoint" | "diffusers";
-    /**
-     * CLIPVisionModelFormat
-     * @description An enumeration.
-     * @enum {string}
-     */
-    CLIPVisionModelFormat: "diffusers";
+    T2IAdapterModelFormat: "diffusers";
     /**
      * StableDiffusionXLModelFormat
      * @description An enumeration.
@@ -11142,12 +11136,6 @@ export type components = {
      * @enum {string}
      */
     StableDiffusion1ModelFormat: "checkpoint" | "diffusers";
-    /**
-     * ControlNetModelFormat
-     * @description An enumeration.
-     * @enum {string}
-     */
-    ControlNetModelFormat: "checkpoint" | "diffusers";
     /**
      * StableDiffusionOnnxModelFormat
      * @description An enumeration.
@@ -11155,17 +11143,29 @@ export type components = {
      */
     StableDiffusionOnnxModelFormat: "olive" | "onnx";
     /**
-     * T2IAdapterModelFormat
+     * ControlNetModelFormat
      * @description An enumeration.
      * @enum {string}
      */
-    T2IAdapterModelFormat: "diffusers";
+    ControlNetModelFormat: "checkpoint" | "diffusers";
+    /**
+     * StableDiffusion2ModelFormat
+     * @description An enumeration.
+     * @enum {string}
+     */
+    StableDiffusion2ModelFormat: "checkpoint" | "diffusers";
     /**
      * LoRAModelFormat
      * @description An enumeration.
      * @enum {string}
      */
     LoRAModelFormat: "lycoris" | "diffusers";
+    /**
+     * CLIPVisionModelFormat
+     * @description An enumeration.
+     * @enum {string}
+     */
+    CLIPVisionModelFormat: "diffusers";
     /**
      * IPAdapterModelFormat
      * @description An enumeration.
diff --git a/invokeai/frontend/web/src/services/api/types.ts b/invokeai/frontend/web/src/services/api/types.ts
index 7a02cc5568..4ae2f9b594 100644
--- a/invokeai/frontend/web/src/services/api/types.ts
+++ b/invokeai/frontend/web/src/services/api/types.ts
@@ -61,11 +61,13 @@ export type IPAdapterField = S['IPAdapterField'];
 // Model Configs
 
 // TODO(MM2): Can we make key required in the pydantic model?
-type KeyRequired<T extends {key?: string}> = SetRequired<T, 'key'>;
+type KeyRequired<T extends { key?: string }> = SetRequired<T, 'key'>;
 export type LoRAConfig = KeyRequired<S['LoRAConfig']>;
 // TODO(MM2): Can we rename this from Vae -> VAE
 export type VAEConfig = KeyRequired<S['VaeCheckpointConfig']> | KeyRequired<S['VaeDiffusersConfig']>;
-export type ControlNetConfig = KeyRequired<S['ControlNetDiffusersConfig']> | KeyRequired<S['ControlNetCheckpointConfig']>;
+export type ControlNetConfig =
+  | KeyRequired<S['ControlNetDiffusersConfig']>
+  | KeyRequired<S['ControlNetCheckpointConfig']>;
 export type IPAdapterConfig = KeyRequired<S['IPAdapterConfig']>;
 // TODO(MM2): Can we rename this to T2IAdapterConfig
 export type T2IAdapterConfig = KeyRequired<S['T2IConfig']>;
diff --git a/invokeai/frontend/web/src/services/api/util.ts b/invokeai/frontend/web/src/services/api/util.ts
index f7f36f4630..a7a5d6451e 100644
--- a/invokeai/frontend/web/src/services/api/util.ts
+++ b/invokeai/frontend/web/src/services/api/util.ts
@@ -3,6 +3,7 @@ import { getSelectorsOptions } from 'app/store/createMemoizedSelector';
 import { dateComparator } from 'common/util/dateComparator';
 import { ASSETS_CATEGORIES, IMAGE_CATEGORIES } from 'features/gallery/store/types';
 import queryString from 'query-string';
+import { buildV1Url } from 'services/api';
 
 import type { ImageCache, ImageDTO, ListImagesArgs } from './types';
 
@@ -79,4 +80,4 @@ export const imagesSelectors = imagesAdapter.getSelectors(undefined, getSelector
 
 // Helper to create the url for the listImages endpoint. Also we use it to create the cache key.
 export const getListImagesUrl = (queryArgs: ListImagesArgs) =>
-  `images/?${queryString.stringify(queryArgs, { arrayFormat: 'none' })}`;
+  buildV1Url(`images/?${queryString.stringify(queryArgs, { arrayFormat: 'none' })}`);
diff --git a/invokeai/frontend/web/vite.config.mts b/invokeai/frontend/web/vite.config.mts
index f4dbae7123..32e3e1f64f 100644
--- a/invokeai/frontend/web/vite.config.mts
+++ b/invokeai/frontend/web/vite.config.mts
@@ -76,9 +76,9 @@ export default defineConfig(({ mode }) => {
           changeOrigin: true,
         },
         // proxy nodes api
-        '/api/v1': {
-          target: 'http://127.0.0.1:9090/api/v1',
-          rewrite: (path) => path.replace(/^\/api\/v1/, ''),
+        '/api/': {
+          target: 'http://127.0.0.1:9090/api/',
+          rewrite: (path) => path.replace(/^\/api/, ''),
           changeOrigin: true,
         },
       },

From e50b76571adf5ba65904edeb02938f95a5b450e3 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Fri, 16 Feb 2024 22:41:09 +1100
Subject: [PATCH 142/411] feat(ui): fix main model & control adapter model
 selects

---
 .../src/common/hooks/useModelCustomSelect.ts  | 88 +++++++++++++++++++
 .../parameters/ParamControlAdapterModel.tsx   | 49 +++--------
 .../hooks/useControlAdapterModelEntities.ts   | 23 -----
 .../hooks/useControlAdapterModelQuery.ts      | 26 ++++++
 .../hooks/useControlAdapterType.ts            | 10 ++-
 .../subpanels/ModelManagerPanel.tsx           |  6 +-
 .../MainModel/ParamMainModelSelect.tsx        | 45 ++++------
 .../src/features/parameters/store/actions.ts  |  5 +-
 .../features/parameters/types/constants.ts    |  4 +-
 9 files changed, 154 insertions(+), 102 deletions(-)
 create mode 100644 invokeai/frontend/web/src/common/hooks/useModelCustomSelect.ts
 delete mode 100644 invokeai/frontend/web/src/features/controlAdapters/hooks/useControlAdapterModelEntities.ts
 create mode 100644 invokeai/frontend/web/src/features/controlAdapters/hooks/useControlAdapterModelQuery.ts

diff --git a/invokeai/frontend/web/src/common/hooks/useModelCustomSelect.ts b/invokeai/frontend/web/src/common/hooks/useModelCustomSelect.ts
new file mode 100644
index 0000000000..07ea98a274
--- /dev/null
+++ b/invokeai/frontend/web/src/common/hooks/useModelCustomSelect.ts
@@ -0,0 +1,88 @@
+import type { Item } from '@invoke-ai/ui-library';
+import type { EntityState } from '@reduxjs/toolkit';
+import { EMPTY_ARRAY } from 'app/store/util';
+import type { ModelIdentifierWithBase } from 'features/nodes/types/common';
+import { MODEL_TYPE_SHORT_MAP } from 'features/parameters/types/constants';
+import { filter } from 'lodash-es';
+import { useCallback, useMemo } from 'react';
+import { useTranslation } from 'react-i18next';
+import type { AnyModelConfig } from 'services/api/types';
+
+type UseModelCustomSelectArg<T extends AnyModelConfig> = {
+  data: EntityState<T, string> | undefined;
+  isLoading: boolean;
+  selectedModel?: ModelIdentifierWithBase | null;
+  onChange: (value: T | null) => void;
+  modelFilter?: (model: T) => boolean;
+  isModelDisabled?: (model: T) => boolean;
+};
+
+type UseModelCustomSelectReturn = {
+  selectedItem: Item | null;
+  items: Item[];
+  onChange: (item: Item | null) => void;
+  placeholder: string;
+};
+
+const modelFilterDefault = () => true;
+const isModelDisabledDefault = () => false;
+
+export const useModelCustomSelect = <T extends AnyModelConfig>({
+  data,
+  isLoading,
+  selectedModel,
+  onChange,
+  modelFilter = modelFilterDefault,
+  isModelDisabled = isModelDisabledDefault,
+}: UseModelCustomSelectArg<T>): UseModelCustomSelectReturn => {
+  const { t } = useTranslation();
+
+  const items: Item[] = useMemo(
+    () =>
+      data
+        ? filter(data.entities, modelFilter).map<Item>((m) => ({
+            label: m.name,
+            value: m.key,
+            description: m.description,
+            group: MODEL_TYPE_SHORT_MAP[m.base],
+            isDisabled: isModelDisabled(m),
+          }))
+        : EMPTY_ARRAY,
+    [data, isModelDisabled, modelFilter]
+  );
+
+  const _onChange = useCallback(
+    (item: Item | null) => {
+      if (!item || !data) {
+        return;
+      }
+      const model = data.entities[item.value];
+      if (!model) {
+        return;
+      }
+      onChange(model);
+    },
+    [data, onChange]
+  );
+
+  const selectedItem = useMemo(() => items.find((o) => o.value === selectedModel?.key) ?? null, [selectedModel, items]);
+
+  const placeholder = useMemo(() => {
+    if (isLoading) {
+      return t('common.loading');
+    }
+
+    if (items.length === 0) {
+      return t('models.noModelsAvailable');
+    }
+
+    return t('models.selectModel');
+  }, [isLoading, items, t]);
+
+  return {
+    items,
+    onChange: _onChange,
+    selectedItem,
+    placeholder,
+  };
+};
diff --git a/invokeai/frontend/web/src/features/controlAdapters/components/parameters/ParamControlAdapterModel.tsx b/invokeai/frontend/web/src/features/controlAdapters/components/parameters/ParamControlAdapterModel.tsx
index a320238445..696bf47b2a 100644
--- a/invokeai/frontend/web/src/features/controlAdapters/components/parameters/ParamControlAdapterModel.tsx
+++ b/invokeai/frontend/web/src/features/controlAdapters/components/parameters/ParamControlAdapterModel.tsx
@@ -1,34 +1,27 @@
-import { Combobox, FormControl, Tooltip } from '@invoke-ai/ui-library';
-import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
+import { CustomSelect, FormControl } from '@invoke-ai/ui-library';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import { useGroupedModelCombobox } from 'common/hooks/useGroupedModelCombobox';
+import { useModelCustomSelect } from 'common/hooks/useModelCustomSelect';
 import { useControlAdapterIsEnabled } from 'features/controlAdapters/hooks/useControlAdapterIsEnabled';
 import { useControlAdapterModel } from 'features/controlAdapters/hooks/useControlAdapterModel';
-import { useControlAdapterModelEntities } from 'features/controlAdapters/hooks/useControlAdapterModelEntities';
+import { useControlAdapterModelQuery } from 'features/controlAdapters/hooks/useControlAdapterModelQuery';
 import { useControlAdapterType } from 'features/controlAdapters/hooks/useControlAdapterType';
 import { controlAdapterModelChanged } from 'features/controlAdapters/store/controlAdaptersSlice';
-import { selectGenerationSlice } from 'features/parameters/store/generationSlice';
 import { pick } from 'lodash-es';
 import { memo, useCallback, useMemo } from 'react';
-import { useTranslation } from 'react-i18next';
-import type { AnyModelConfig, ControlNetConfig, IPAdapterConfig, T2IAdapterConfig } from 'services/api/types';
+import type { ControlNetConfig, IPAdapterConfig, T2IAdapterConfig } from 'services/api/types';
 
 type ParamControlAdapterModelProps = {
   id: string;
 };
 
-const selectMainModel = createMemoizedSelector(selectGenerationSlice, (generation) => generation.model);
-
 const ParamControlAdapterModel = ({ id }: ParamControlAdapterModelProps) => {
   const isEnabled = useControlAdapterIsEnabled(id);
   const controlAdapterType = useControlAdapterType(id);
   const model = useControlAdapterModel(id);
   const dispatch = useAppDispatch();
   const currentBaseModel = useAppSelector((s) => s.generation.model?.base);
-  const mainModel = useAppSelector(selectMainModel);
-  const { t } = useTranslation();
 
-  const models = useControlAdapterModelEntities(controlAdapterType);
+  const { data, isLoading } = useControlAdapterModelQuery(controlAdapterType);
 
   const _onChange = useCallback(
     (model: ControlNetConfig | IPAdapterConfig | T2IAdapterConfig | null) => {
@@ -50,34 +43,18 @@ const ParamControlAdapterModel = ({ id }: ParamControlAdapterModelProps) => {
     [controlAdapterType, model]
   );
 
-  const getIsDisabled = useCallback(
-    (model: AnyModelConfig): boolean => {
-      const isCompatible = currentBaseModel === model.base;
-      const hasMainModel = Boolean(currentBaseModel);
-      return !hasMainModel || !isCompatible;
-    },
-    [currentBaseModel]
-  );
-
-  const { options, value, onChange, noOptionsMessage } = useGroupedModelCombobox({
-    modelEntities: models,
-    onChange: _onChange,
+  const { items, selectedItem, onChange, placeholder } = useModelCustomSelect({
+    data,
+    isLoading,
     selectedModel,
-    getIsDisabled,
+    onChange: _onChange,
+    modelFilter: (model) => model.base === currentBaseModel,
   });
 
   return (
-    <Tooltip label={value?.description}>
-      <FormControl isDisabled={!isEnabled} isInvalid={!value || mainModel?.base !== model?.base}>
-        <Combobox
-          options={options}
-          placeholder={t('controlnet.selectModel')}
-          value={value}
-          onChange={onChange}
-          noOptionsMessage={noOptionsMessage}
-        />
-      </FormControl>
-    </Tooltip>
+    <FormControl isDisabled={!items.length || !isEnabled} isInvalid={!selectedItem || !items.length}>
+      <CustomSelect selectedItem={selectedItem} placeholder={placeholder} items={items} onChange={onChange} />
+    </FormControl>
   );
 };
 
diff --git a/invokeai/frontend/web/src/features/controlAdapters/hooks/useControlAdapterModelEntities.ts b/invokeai/frontend/web/src/features/controlAdapters/hooks/useControlAdapterModelEntities.ts
deleted file mode 100644
index 0c8baaacc2..0000000000
--- a/invokeai/frontend/web/src/features/controlAdapters/hooks/useControlAdapterModelEntities.ts
+++ /dev/null
@@ -1,23 +0,0 @@
-import type { ControlAdapterType } from 'features/controlAdapters/store/types';
-import {
-  useGetControlNetModelsQuery,
-  useGetIPAdapterModelsQuery,
-  useGetT2IAdapterModelsQuery,
-} from 'services/api/endpoints/models';
-
-export const useControlAdapterModelEntities = (type?: ControlAdapterType) => {
-  const { data: controlNetModelsData } = useGetControlNetModelsQuery();
-  const { data: t2iAdapterModelsData } = useGetT2IAdapterModelsQuery();
-  const { data: ipAdapterModelsData } = useGetIPAdapterModelsQuery();
-
-  if (type === 'controlnet') {
-    return controlNetModelsData;
-  }
-  if (type === 't2i_adapter') {
-    return t2iAdapterModelsData;
-  }
-  if (type === 'ip_adapter') {
-    return ipAdapterModelsData;
-  }
-  return;
-};
diff --git a/invokeai/frontend/web/src/features/controlAdapters/hooks/useControlAdapterModelQuery.ts b/invokeai/frontend/web/src/features/controlAdapters/hooks/useControlAdapterModelQuery.ts
new file mode 100644
index 0000000000..1d092497af
--- /dev/null
+++ b/invokeai/frontend/web/src/features/controlAdapters/hooks/useControlAdapterModelQuery.ts
@@ -0,0 +1,26 @@
+import type { ControlAdapterType } from 'features/controlAdapters/store/types';
+import {
+  useGetControlNetModelsQuery,
+  useGetIPAdapterModelsQuery,
+  useGetT2IAdapterModelsQuery,
+} from 'services/api/endpoints/models';
+
+export const useControlAdapterModelQuery = (type: ControlAdapterType) => {
+  const controlNetModelsQuery = useGetControlNetModelsQuery();
+  const t2iAdapterModelsQuery = useGetT2IAdapterModelsQuery();
+  const ipAdapterModelsQuery = useGetIPAdapterModelsQuery();
+
+  if (type === 'controlnet') {
+    return controlNetModelsQuery;
+  }
+  if (type === 't2i_adapter') {
+    return t2iAdapterModelsQuery;
+  }
+  if (type === 'ip_adapter') {
+    return ipAdapterModelsQuery;
+  }
+
+  // Assert that the end of the function is not reachable.
+  const exhaustiveCheck: never = type;
+  return exhaustiveCheck;
+};
diff --git a/invokeai/frontend/web/src/features/controlAdapters/hooks/useControlAdapterType.ts b/invokeai/frontend/web/src/features/controlAdapters/hooks/useControlAdapterType.ts
index 4e15dc9e64..fe818f3287 100644
--- a/invokeai/frontend/web/src/features/controlAdapters/hooks/useControlAdapterType.ts
+++ b/invokeai/frontend/web/src/features/controlAdapters/hooks/useControlAdapterType.ts
@@ -5,14 +5,16 @@ import {
   selectControlAdaptersSlice,
 } from 'features/controlAdapters/store/controlAdaptersSlice';
 import { useMemo } from 'react';
+import { assert } from 'tsafe';
 
 export const useControlAdapterType = (id: string) => {
   const selector = useMemo(
     () =>
-      createMemoizedSelector(
-        selectControlAdaptersSlice,
-        (controlAdapters) => selectControlAdapterById(controlAdapters, id)?.type
-      ),
+      createMemoizedSelector(selectControlAdaptersSlice, (controlAdapters) => {
+        const type = selectControlAdapterById(controlAdapters, id)?.type;
+        assert(type !== undefined, `Control adapter with id ${id} not found`);
+        return type;
+      }),
     [id]
   );
 
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel.tsx
index 7501151ba4..15149b339b 100644
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel.tsx
+++ b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel.tsx
@@ -2,11 +2,7 @@ import { Flex, Text } from '@invoke-ai/ui-library';
 import { memo, useState } from 'react';
 import { useTranslation } from 'react-i18next';
 import { ALL_BASE_MODELS } from 'services/api/constants';
-import type {
-  DiffusersModelConfig,
-  LoRAConfig,
-  MainModelConfig,
-} from 'services/api/endpoints/models';
+import type { DiffusersModelConfig, LoRAConfig, MainModelConfig } from 'services/api/endpoints/models';
 import { useGetLoRAModelsQuery, useGetMainModelsQuery } from 'services/api/endpoints/models';
 
 import CheckpointModelEdit from './ModelManagerPanel/CheckpointModelEdit';
diff --git a/invokeai/frontend/web/src/features/parameters/components/MainModel/ParamMainModelSelect.tsx b/invokeai/frontend/web/src/features/parameters/components/MainModel/ParamMainModelSelect.tsx
index 18f780bdee..0759020cc8 100644
--- a/invokeai/frontend/web/src/features/parameters/components/MainModel/ParamMainModelSelect.tsx
+++ b/invokeai/frontend/web/src/features/parameters/components/MainModel/ParamMainModelSelect.tsx
@@ -1,62 +1,47 @@
-import { Box, Combobox, FormControl, FormLabel, Tooltip } from '@invoke-ai/ui-library';
+import { CustomSelect, FormControl, FormLabel } from '@invoke-ai/ui-library';
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
-import { useGroupedModelCombobox } from 'common/hooks/useGroupedModelCombobox';
+import { useModelCustomSelect } from 'common/hooks/useModelCustomSelect';
 import { modelSelected } from 'features/parameters/store/actions';
 import { selectGenerationSlice } from 'features/parameters/store/generationSlice';
-import { pick } from 'lodash-es';
-import { memo, useCallback, useMemo } from 'react';
+import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 import { NON_REFINER_BASE_MODELS } from 'services/api/constants';
-import type { MainModelConfig } from 'services/api/endpoints/models';
-import { getModelId, mainModelsAdapterSelectors, useGetMainModelsQuery } from 'services/api/endpoints/models';
+import { useGetMainModelsQuery } from 'services/api/endpoints/models';
+import type { MainModelConfig } from 'services/api/types';
 
 const selectModel = createMemoizedSelector(selectGenerationSlice, (generation) => generation.model);
 
 const ParamMainModelSelect = () => {
   const dispatch = useAppDispatch();
   const { t } = useTranslation();
-  const model = useAppSelector(selectModel);
+  const selectedModel = useAppSelector(selectModel);
   const { data, isLoading } = useGetMainModelsQuery(NON_REFINER_BASE_MODELS);
-  const tooltipLabel = useMemo(() => {
-    if (!data || !model) {
-      return;
-    }
-    return mainModelsAdapterSelectors.selectById(data, getModelId(model))?.description;
-  }, [data, model]);
+
   const _onChange = useCallback(
     (model: MainModelConfig | null) => {
       if (!model) {
         return;
       }
-      dispatch(modelSelected(pick(model, ['base_model', 'model_name', 'model_type'])));
+      dispatch(modelSelected({ key: model.key, base: model.base }));
     },
     [dispatch]
   );
-  const { options, value, onChange, placeholder, noOptionsMessage } = useGroupedModelCombobox({
-    modelEntities: data,
-    onChange: _onChange,
-    selectedModel: model,
+
+  const { items, selectedItem, onChange, placeholder } = useModelCustomSelect({
+    data,
     isLoading,
+    selectedModel,
+    onChange: _onChange,
   });
 
   return (
-    <FormControl isDisabled={!options.length} isInvalid={!options.length}>
+    <FormControl isDisabled={!items.length} isInvalid={!selectedItem || !items.length}>
       <InformationalPopover feature="paramModel">
         <FormLabel>{t('modelManager.model')}</FormLabel>
       </InformationalPopover>
-      <Tooltip label={tooltipLabel}>
-        <Box w="full">
-          <Combobox
-            value={value}
-            placeholder={placeholder}
-            options={options}
-            onChange={onChange}
-            noOptionsMessage={noOptionsMessage}
-          />
-        </Box>
-      </Tooltip>
+      <CustomSelect selectedItem={selectedItem} placeholder={placeholder} items={items} onChange={onChange} />
     </FormControl>
   );
 };
diff --git a/invokeai/frontend/web/src/features/parameters/store/actions.ts b/invokeai/frontend/web/src/features/parameters/store/actions.ts
index 0d4dda0e87..f7bf127c05 100644
--- a/invokeai/frontend/web/src/features/parameters/store/actions.ts
+++ b/invokeai/frontend/web/src/features/parameters/store/actions.ts
@@ -1,6 +1,7 @@
 import { createAction } from '@reduxjs/toolkit';
-import type { ImageDTO, MainModelField } from 'services/api/types';
+import type { ParameterModel } from 'features/parameters/types/parameterSchemas';
+import type { ImageDTO } from 'services/api/types';
 
 export const initialImageSelected = createAction<ImageDTO | undefined>('generation/initialImageSelected');
 
-export const modelSelected = createAction<MainModelField>('generation/modelSelected');
+export const modelSelected = createAction<ParameterModel>('generation/modelSelected');
diff --git a/invokeai/frontend/web/src/features/parameters/types/constants.ts b/invokeai/frontend/web/src/features/parameters/types/constants.ts
index a74807a959..bd78759b39 100644
--- a/invokeai/frontend/web/src/features/parameters/types/constants.ts
+++ b/invokeai/frontend/web/src/features/parameters/types/constants.ts
@@ -17,8 +17,8 @@ export const MODEL_TYPE_MAP = {
  */
 export const MODEL_TYPE_SHORT_MAP = {
   any: 'Any',
-  'sd-1': 'SD1',
-  'sd-2': 'SD2',
+  'sd-1': 'SD1.X',
+  'sd-2': 'SD2.X',
   sdxl: 'SDXL',
   'sdxl-refiner': 'SDXLR',
 };

From f1597bd6da1bd411f5e2d7feb540cf68c1fe5db5 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Fri, 16 Feb 2024 22:42:15 +1100
Subject: [PATCH 143/411] chore(ui): lint

---
 invokeai/frontend/web/src/common/hooks/useModelCombobox.ts    | 4 +---
 invokeai/frontend/web/src/services/api/endpoints/workflows.ts | 2 +-
 2 files changed, 2 insertions(+), 4 deletions(-)

diff --git a/invokeai/frontend/web/src/common/hooks/useModelCombobox.ts b/invokeai/frontend/web/src/common/hooks/useModelCombobox.ts
index 341fed1e47..07e6aeb34c 100644
--- a/invokeai/frontend/web/src/common/hooks/useModelCombobox.ts
+++ b/invokeai/frontend/web/src/common/hooks/useModelCombobox.ts
@@ -23,9 +23,7 @@ type UseModelComboboxReturn = {
   noOptionsMessage: () => string;
 };
 
-export const useModelCombobox = <T extends AnyModelConfig>(
-  arg: UseModelComboboxArg<T>
-): UseModelComboboxReturn => {
+export const useModelCombobox = <T extends AnyModelConfig>(arg: UseModelComboboxArg<T>): UseModelComboboxReturn => {
   const { t } = useTranslation();
   const { modelEntities, selectedModel, getIsDisabled, onChange, isLoading, optionsFilter = () => true } = arg;
   const options = useMemo<ComboboxOption[]>(() => {
diff --git a/invokeai/frontend/web/src/services/api/endpoints/workflows.ts b/invokeai/frontend/web/src/services/api/endpoints/workflows.ts
index 1e64809e5a..0280e2ebc4 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/workflows.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/workflows.ts
@@ -5,7 +5,7 @@ import { api, buildV1Url, LIST_TAG } from '..';
 /**
  * Builds an endpoint URL for the workflows router
  * @example
- * buildWorkflowsUrl('some-path') 
+ * buildWorkflowsUrl('some-path')
  * // '/api/v1/workflows/some-path'
  */
 const buildWorkflowsUrl = (path: string = '') => buildV1Url(`workflows/${path}`);

From 996eb96b4e06fe4f82e672c482793cf8fe428506 Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lstein@gmail.com>
Date: Thu, 15 Feb 2024 22:41:29 -0500
Subject: [PATCH 144/411] Fix issues identified during PR review by RyanjDick
 and brandonrising

- ModelMetadataStoreService is now injected into ModelRecordStoreService
  (these two services are really joined at the hip, and should someday be merged)
- ModelRecordStoreService is now injected into ModelManagerService
- Reduced timeout value for the various installer and download wait*() methods
- Introduced a Mock modelmanager for testing
- Removed bare print() statement with _logger in the install helper backend.
- Removed unused code from model loader init file
- Made `locker` a private variable in the `LoadedModel` object.
- Fixed up model merge frontend (will be deprecated anyway!)
---
 invokeai/app/api/dependencies.py              |   8 +-
 .../app/services/download/download_default.py |   2 +-
 .../invocation_stats_default.py               |   2 -
 .../model_install/model_install_base.py       |   6 +-
 .../model_install/model_install_default.py    |  15 +-
 .../model_manager/model_manager_default.py    |  15 +-
 .../app/services/model_metadata/__init__.py   |   9 +
 .../model_metadata/metadata_store_base.py     |  65 +++++
 .../model_metadata/metadata_store_sql.py      | 222 ++++++++++++++++++
 .../model_records/model_records_base.py       |   6 +-
 .../model_records/model_records_sql.py        |  18 +-
 invokeai/backend/install/install_helper.py    |  13 +-
 .../backend/model_manager/load/__init__.py    |  17 --
 .../backend/model_manager/load/load_base.py   |   8 +-
 .../model_manager/load/load_default.py        |   2 +-
 invokeai/backend/model_manager/merge.py       |   5 +-
 .../model_manager/metadata/__init__.py        |   5 +-
 invokeai/frontend/merge/merge_diffusers.py    | 133 +++++++----
 tests/aa_nodes/test_invoker.py                |   3 +-
 .../model_records/test_model_records_sql.py   |   3 +-
 .../model_manager_2_fixtures.py               |  15 +-
 .../model_metadata/test_model_metadata.py     |   8 +-
 22 files changed, 449 insertions(+), 131 deletions(-)
 create mode 100644 invokeai/app/services/model_metadata/__init__.py
 create mode 100644 invokeai/app/services/model_metadata/metadata_store_base.py
 create mode 100644 invokeai/app/services/model_metadata/metadata_store_sql.py

diff --git a/invokeai/app/api/dependencies.py b/invokeai/app/api/dependencies.py
index 378961a055..8e79b26e2d 100644
--- a/invokeai/app/api/dependencies.py
+++ b/invokeai/app/api/dependencies.py
@@ -28,6 +28,8 @@ from ..services.invocation_services import InvocationServices
 from ..services.invocation_stats.invocation_stats_default import InvocationStatsService
 from ..services.invoker import Invoker
 from ..services.model_manager.model_manager_default import ModelManagerService
+from ..services.model_metadata import ModelMetadataStoreSQL
+from ..services.model_records import ModelRecordServiceSQL
 from ..services.names.names_default import SimpleNameService
 from ..services.session_processor.session_processor_default import DefaultSessionProcessor
 from ..services.session_queue.session_queue_sqlite import SqliteSessionQueue
@@ -94,8 +96,12 @@ class ApiDependencies:
             ObjectSerializerDisk[ConditioningFieldData](output_folder / "conditioning", ephemeral=True)
         )
         download_queue_service = DownloadQueueService(event_bus=events)
+        model_metadata_service = ModelMetadataStoreSQL(db=db)
         model_manager = ModelManagerService.build_model_manager(
-            app_config=configuration, db=db, download_queue=download_queue_service, events=events
+            app_config=configuration,
+            model_record_service=ModelRecordServiceSQL(db=db, metadata_store=model_metadata_service),
+            download_queue=download_queue_service,
+            events=events,
         )
         names = SimpleNameService()
         performance_statistics = InvocationStatsService()
diff --git a/invokeai/app/services/download/download_default.py b/invokeai/app/services/download/download_default.py
index 6d5cedbcad..50cac80d09 100644
--- a/invokeai/app/services/download/download_default.py
+++ b/invokeai/app/services/download/download_default.py
@@ -194,7 +194,7 @@ class DownloadQueueService(DownloadQueueServiceBase):
         """Block until the indicated job has reached terminal state, or when timeout limit reached."""
         start = time.time()
         while not job.in_terminal_state:
-            if self._job_completed_event.wait(timeout=5):  # in case we miss an event
+            if self._job_completed_event.wait(timeout=0.25):  # in case we miss an event
                 self._job_completed_event.clear()
             if timeout > 0 and time.time() - start > timeout:
                 raise TimeoutError("Timeout exceeded")
diff --git a/invokeai/app/services/invocation_stats/invocation_stats_default.py b/invokeai/app/services/invocation_stats/invocation_stats_default.py
index 6c893021de..486a1ca5b3 100644
--- a/invokeai/app/services/invocation_stats/invocation_stats_default.py
+++ b/invokeai/app/services/invocation_stats/invocation_stats_default.py
@@ -46,8 +46,6 @@ class InvocationStatsService(InvocationStatsServiceBase):
         # This is to handle case of the model manager not being initialized, which happens
         # during some tests.
         services = self._invoker.services
-        if services.model_manager is None or services.model_manager.load is None:
-            yield None
         if not self._stats.get(graph_execution_state_id):
             # First time we're seeing this graph_execution_state_id.
             self._stats[graph_execution_state_id] = GraphExecutionStats()
diff --git a/invokeai/app/services/model_install/model_install_base.py b/invokeai/app/services/model_install/model_install_base.py
index 39ea8c4a0d..2f03db0af7 100644
--- a/invokeai/app/services/model_install/model_install_base.py
+++ b/invokeai/app/services/model_install/model_install_base.py
@@ -18,7 +18,9 @@ from invokeai.app.services.events import EventServiceBase
 from invokeai.app.services.invoker import Invoker
 from invokeai.app.services.model_records import ModelRecordServiceBase
 from invokeai.backend.model_manager import AnyModelConfig, ModelRepoVariant
-from invokeai.backend.model_manager.metadata import AnyModelRepoMetadata, ModelMetadataStore
+from invokeai.backend.model_manager.metadata import AnyModelRepoMetadata
+
+from ..model_metadata import ModelMetadataStoreBase
 
 
 class InstallStatus(str, Enum):
@@ -243,7 +245,7 @@ class ModelInstallServiceBase(ABC):
         app_config: InvokeAIAppConfig,
         record_store: ModelRecordServiceBase,
         download_queue: DownloadQueueServiceBase,
-        metadata_store: ModelMetadataStore,
+        metadata_store: ModelMetadataStoreBase,
         event_bus: Optional["EventServiceBase"] = None,
     ):
         """
diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py
index 20a85a82a1..7dee8bfd8c 100644
--- a/invokeai/app/services/model_install/model_install_default.py
+++ b/invokeai/app/services/model_install/model_install_default.py
@@ -20,7 +20,7 @@ from invokeai.app.services.config import InvokeAIAppConfig
 from invokeai.app.services.download import DownloadJob, DownloadQueueServiceBase, TqdmProgress
 from invokeai.app.services.events.events_base import EventServiceBase
 from invokeai.app.services.invoker import Invoker
-from invokeai.app.services.model_records import DuplicateModelException, ModelRecordServiceBase, ModelRecordServiceSQL
+from invokeai.app.services.model_records import DuplicateModelException, ModelRecordServiceBase
 from invokeai.backend.model_manager.config import (
     AnyModelConfig,
     BaseModelType,
@@ -33,7 +33,6 @@ from invokeai.backend.model_manager.metadata import (
     AnyModelRepoMetadata,
     CivitaiMetadataFetch,
     HuggingFaceMetadataFetch,
-    ModelMetadataStore,
     ModelMetadataWithFiles,
     RemoteModelFile,
 )
@@ -65,7 +64,6 @@ class ModelInstallService(ModelInstallServiceBase):
         app_config: InvokeAIAppConfig,
         record_store: ModelRecordServiceBase,
         download_queue: DownloadQueueServiceBase,
-        metadata_store: Optional[ModelMetadataStore] = None,
         event_bus: Optional[EventServiceBase] = None,
         session: Optional[Session] = None,
     ):
@@ -93,14 +91,7 @@ class ModelInstallService(ModelInstallServiceBase):
         self._running = False
         self._session = session
         self._next_job_id = 0
-        # There may not necessarily be a metadata store initialized
-        # so we create one and initialize it with the same sql database
-        # used by the record store service.
-        if metadata_store:
-            self._metadata_store = metadata_store
-        else:
-            assert isinstance(record_store, ModelRecordServiceSQL)
-            self._metadata_store = ModelMetadataStore(record_store.db)
+        self._metadata_store = record_store.metadata_store  # for convenience
 
     @property
     def app_config(self) -> InvokeAIAppConfig:  # noqa D102
@@ -259,7 +250,7 @@ class ModelInstallService(ModelInstallServiceBase):
         """Block until all installation jobs are done."""
         start = time.time()
         while len(self._download_cache) > 0:
-            if self._downloads_changed_event.wait(timeout=5):  # in case we miss an event
+            if self._downloads_changed_event.wait(timeout=0.25):  # in case we miss an event
                 self._downloads_changed_event.clear()
             if timeout > 0 and time.time() - start > timeout:
                 raise TimeoutError("Timeout exceeded")
diff --git a/invokeai/app/services/model_manager/model_manager_default.py b/invokeai/app/services/model_manager/model_manager_default.py
index 028d4af615..b96341be69 100644
--- a/invokeai/app/services/model_manager/model_manager_default.py
+++ b/invokeai/app/services/model_manager/model_manager_default.py
@@ -5,7 +5,6 @@ from typing_extensions import Self
 
 from invokeai.app.services.invoker import Invoker
 from invokeai.backend.model_manager.load import ModelCache, ModelConvertCache
-from invokeai.backend.model_manager.metadata import ModelMetadataStore
 from invokeai.backend.util.logging import InvokeAILogger
 
 from ..config import InvokeAIAppConfig
@@ -13,8 +12,7 @@ from ..download import DownloadQueueServiceBase
 from ..events.events_base import EventServiceBase
 from ..model_install import ModelInstallService, ModelInstallServiceBase
 from ..model_load import ModelLoadService, ModelLoadServiceBase
-from ..model_records import ModelRecordServiceBase, ModelRecordServiceSQL
-from ..shared.sqlite.sqlite_database import SqliteDatabase
+from ..model_records import ModelRecordServiceBase
 from .model_manager_base import ModelManagerServiceBase
 
 
@@ -64,7 +62,7 @@ class ModelManagerService(ModelManagerServiceBase):
     def build_model_manager(
         cls,
         app_config: InvokeAIAppConfig,
-        db: SqliteDatabase,
+        model_record_service: ModelRecordServiceBase,
         download_queue: DownloadQueueServiceBase,
         events: EventServiceBase,
     ) -> Self:
@@ -82,19 +80,16 @@ class ModelManagerService(ModelManagerServiceBase):
         convert_cache = ModelConvertCache(
             cache_path=app_config.models_convert_cache_path, max_size=app_config.convert_cache_size
         )
-        record_store = ModelRecordServiceSQL(db=db)
         loader = ModelLoadService(
             app_config=app_config,
-            record_store=record_store,
+            record_store=model_record_service,
             ram_cache=ram_cache,
             convert_cache=convert_cache,
         )
-        record_store._loader = loader  # yeah, there is a circular reference here
         installer = ModelInstallService(
             app_config=app_config,
-            record_store=record_store,
+            record_store=model_record_service,
             download_queue=download_queue,
-            metadata_store=ModelMetadataStore(db=db),
             event_bus=events,
         )
-        return cls(store=record_store, install=installer, load=loader)
+        return cls(store=model_record_service, install=installer, load=loader)
diff --git a/invokeai/app/services/model_metadata/__init__.py b/invokeai/app/services/model_metadata/__init__.py
new file mode 100644
index 0000000000..981c96b709
--- /dev/null
+++ b/invokeai/app/services/model_metadata/__init__.py
@@ -0,0 +1,9 @@
+"""Init file for ModelMetadataStoreService module."""
+
+from .metadata_store_base import ModelMetadataStoreBase
+from .metadata_store_sql import ModelMetadataStoreSQL
+
+__all__ = [
+    "ModelMetadataStoreBase",
+    "ModelMetadataStoreSQL",
+]
diff --git a/invokeai/app/services/model_metadata/metadata_store_base.py b/invokeai/app/services/model_metadata/metadata_store_base.py
new file mode 100644
index 0000000000..e0e4381b09
--- /dev/null
+++ b/invokeai/app/services/model_metadata/metadata_store_base.py
@@ -0,0 +1,65 @@
+# Copyright (c) 2023 Lincoln D. Stein and the InvokeAI Development Team
+"""
+Storage for Model Metadata
+"""
+
+from abc import ABC, abstractmethod
+from typing import List, Set, Tuple
+
+from invokeai.backend.model_manager.metadata import AnyModelRepoMetadata
+
+
+class ModelMetadataStoreBase(ABC):
+    """Store, search and fetch model metadata retrieved from remote repositories."""
+
+    @abstractmethod
+    def add_metadata(self, model_key: str, metadata: AnyModelRepoMetadata) -> None:
+        """
+        Add a block of repo metadata to a model record.
+
+        The model record config must already exist in the database with the
+        same key. Otherwise a FOREIGN KEY constraint exception will be raised.
+
+        :param model_key: Existing model key in the `model_config` table
+        :param metadata: ModelRepoMetadata object to store
+        """
+
+    @abstractmethod
+    def get_metadata(self, model_key: str) -> AnyModelRepoMetadata:
+        """Retrieve the ModelRepoMetadata corresponding to model key."""
+
+    @abstractmethod
+    def list_all_metadata(self) -> List[Tuple[str, AnyModelRepoMetadata]]:  # key, metadata
+        """Dump out all the metadata."""
+
+    @abstractmethod
+    def update_metadata(self, model_key: str, metadata: AnyModelRepoMetadata) -> AnyModelRepoMetadata:
+        """
+        Update metadata corresponding to the model with the indicated key.
+
+        :param model_key: Existing model key in the `model_config` table
+        :param metadata: ModelRepoMetadata object to update
+        """
+
+    @abstractmethod
+    def list_tags(self) -> Set[str]:
+        """Return all tags in the tags table."""
+
+    @abstractmethod
+    def search_by_tag(self, tags: Set[str]) -> Set[str]:
+        """Return the keys of models containing all of the listed tags."""
+
+    @abstractmethod
+    def search_by_author(self, author: str) -> Set[str]:
+        """Return the keys of models authored by the indicated author."""
+
+    @abstractmethod
+    def search_by_name(self, name: str) -> Set[str]:
+        """
+        Return the keys of models with the indicated name.
+
+        Note that this is the name of the model given to it by
+        the remote source. The user may have changed the local
+        name. The local name will be located in the model config
+        record object.
+        """
diff --git a/invokeai/app/services/model_metadata/metadata_store_sql.py b/invokeai/app/services/model_metadata/metadata_store_sql.py
new file mode 100644
index 0000000000..afe9d2c8c6
--- /dev/null
+++ b/invokeai/app/services/model_metadata/metadata_store_sql.py
@@ -0,0 +1,222 @@
+# Copyright (c) 2023 Lincoln D. Stein and the InvokeAI Development Team
+"""
+SQL Storage for Model Metadata
+"""
+
+import sqlite3
+from typing import List, Optional, Set, Tuple
+
+from invokeai.app.services.shared.sqlite.sqlite_database import SqliteDatabase
+from invokeai.backend.model_manager.metadata import AnyModelRepoMetadata, UnknownMetadataException
+from invokeai.backend.model_manager.metadata.fetch import ModelMetadataFetchBase
+
+from .metadata_store_base import ModelMetadataStoreBase
+
+
+class ModelMetadataStoreSQL(ModelMetadataStoreBase):
+    """Store, search and fetch model metadata retrieved from remote repositories."""
+
+    def __init__(self, db: SqliteDatabase):
+        """
+        Initialize a new object from preexisting sqlite3 connection and threading lock objects.
+
+        :param conn: sqlite3 connection object
+        :param lock: threading Lock object
+        """
+        super().__init__()
+        self._db = db
+        self._cursor = self._db.conn.cursor()
+
+    def add_metadata(self, model_key: str, metadata: AnyModelRepoMetadata) -> None:
+        """
+        Add a block of repo metadata to a model record.
+
+        The model record config must already exist in the database with the
+        same key. Otherwise a FOREIGN KEY constraint exception will be raised.
+
+        :param model_key: Existing model key in the `model_config` table
+        :param metadata: ModelRepoMetadata object to store
+        """
+        json_serialized = metadata.model_dump_json()
+        with self._db.lock:
+            try:
+                self._cursor.execute(
+                    """--sql
+                    INSERT INTO model_metadata(
+                       id,
+                       metadata
+                    )
+                    VALUES (?,?);
+                    """,
+                    (
+                        model_key,
+                        json_serialized,
+                    ),
+                )
+                self._update_tags(model_key, metadata.tags)
+                self._db.conn.commit()
+            except sqlite3.IntegrityError as excp:  # FOREIGN KEY error: the key was not in model_config table
+                self._db.conn.rollback()
+                raise UnknownMetadataException from excp
+            except sqlite3.Error as excp:
+                self._db.conn.rollback()
+                raise excp
+
+    def get_metadata(self, model_key: str) -> AnyModelRepoMetadata:
+        """Retrieve the ModelRepoMetadata corresponding to model key."""
+        with self._db.lock:
+            self._cursor.execute(
+                """--sql
+                SELECT metadata FROM model_metadata
+                WHERE id=?;
+                """,
+                (model_key,),
+            )
+            rows = self._cursor.fetchone()
+            if not rows:
+                raise UnknownMetadataException("model metadata not found")
+            return ModelMetadataFetchBase.from_json(rows[0])
+
+    def list_all_metadata(self) -> List[Tuple[str, AnyModelRepoMetadata]]:  # key, metadata
+        """Dump out all the metadata."""
+        with self._db.lock:
+            self._cursor.execute(
+                """--sql
+                SELECT id,metadata FROM model_metadata;
+                """,
+                (),
+            )
+            rows = self._cursor.fetchall()
+        return [(x[0], ModelMetadataFetchBase.from_json(x[1])) for x in rows]
+
+    def update_metadata(self, model_key: str, metadata: AnyModelRepoMetadata) -> AnyModelRepoMetadata:
+        """
+        Update metadata corresponding to the model with the indicated key.
+
+        :param model_key: Existing model key in the `model_config` table
+        :param metadata: ModelRepoMetadata object to update
+        """
+        json_serialized = metadata.model_dump_json()  # turn it into a json string.
+        with self._db.lock:
+            try:
+                self._cursor.execute(
+                    """--sql
+                    UPDATE model_metadata
+                    SET
+                        metadata=?
+                    WHERE id=?;
+                    """,
+                    (json_serialized, model_key),
+                )
+                if self._cursor.rowcount == 0:
+                    raise UnknownMetadataException("model metadata not found")
+                self._update_tags(model_key, metadata.tags)
+                self._db.conn.commit()
+            except sqlite3.Error as e:
+                self._db.conn.rollback()
+                raise e
+
+        return self.get_metadata(model_key)
+
+    def list_tags(self) -> Set[str]:
+        """Return all tags in the tags table."""
+        self._cursor.execute(
+            """--sql
+            select tag_text from tags;
+            """
+        )
+        return {x[0] for x in self._cursor.fetchall()}
+
+    def search_by_tag(self, tags: Set[str]) -> Set[str]:
+        """Return the keys of models containing all of the listed tags."""
+        with self._db.lock:
+            try:
+                matches: Optional[Set[str]] = None
+                for tag in tags:
+                    self._cursor.execute(
+                        """--sql
+                        SELECT a.model_id FROM model_tags AS a,
+                                                     tags AS b
+                        WHERE a.tag_id=b.tag_id
+                          AND b.tag_text=?;
+                        """,
+                        (tag,),
+                    )
+                    model_keys = {x[0] for x in self._cursor.fetchall()}
+                    if matches is None:
+                        matches = model_keys
+                    matches = matches.intersection(model_keys)
+            except sqlite3.Error as e:
+                raise e
+        return matches if matches else set()
+
+    def search_by_author(self, author: str) -> Set[str]:
+        """Return the keys of models authored by the indicated author."""
+        self._cursor.execute(
+            """--sql
+            SELECT id FROM model_metadata
+            WHERE author=?;
+            """,
+            (author,),
+        )
+        return {x[0] for x in self._cursor.fetchall()}
+
+    def search_by_name(self, name: str) -> Set[str]:
+        """
+        Return the keys of models with the indicated name.
+
+        Note that this is the name of the model given to it by
+        the remote source. The user may have changed the local
+        name. The local name will be located in the model config
+        record object.
+        """
+        self._cursor.execute(
+            """--sql
+            SELECT id FROM model_metadata
+            WHERE name=?;
+            """,
+            (name,),
+        )
+        return {x[0] for x in self._cursor.fetchall()}
+
+    def _update_tags(self, model_key: str, tags: Set[str]) -> None:
+        """Update tags for the model referenced by model_key."""
+        # remove previous tags from this model
+        self._cursor.execute(
+            """--sql
+            DELETE FROM model_tags
+            WHERE model_id=?;
+            """,
+            (model_key,),
+        )
+
+        for tag in tags:
+            self._cursor.execute(
+                """--sql
+                INSERT OR IGNORE INTO tags (
+                  tag_text
+                  )
+                VALUES (?);
+                """,
+                (tag,),
+            )
+            self._cursor.execute(
+                """--sql
+                SELECT tag_id
+                FROM tags
+                WHERE tag_text = ?
+                LIMIT 1;
+                """,
+                (tag,),
+            )
+            tag_id = self._cursor.fetchone()[0]
+            self._cursor.execute(
+                """--sql
+                INSERT OR IGNORE INTO model_tags (
+                   model_id,
+                   tag_id
+                  )
+                VALUES (?,?);
+                """,
+                (model_key, tag_id),
+            )
diff --git a/invokeai/app/services/model_records/model_records_base.py b/invokeai/app/services/model_records/model_records_base.py
index b2eacc524b..d6014db448 100644
--- a/invokeai/app/services/model_records/model_records_base.py
+++ b/invokeai/app/services/model_records/model_records_base.py
@@ -17,7 +17,9 @@ from invokeai.backend.model_manager import (
     ModelFormat,
     ModelType,
 )
-from invokeai.backend.model_manager.metadata import AnyModelRepoMetadata, ModelMetadataStore
+from invokeai.backend.model_manager.metadata import AnyModelRepoMetadata
+
+from ..model_metadata import ModelMetadataStoreBase
 
 
 class DuplicateModelException(Exception):
@@ -109,7 +111,7 @@ class ModelRecordServiceBase(ABC):
 
     @property
     @abstractmethod
-    def metadata_store(self) -> ModelMetadataStore:
+    def metadata_store(self) -> ModelMetadataStoreBase:
         """Return a ModelMetadataStore initialized on the same database."""
         pass
 
diff --git a/invokeai/app/services/model_records/model_records_sql.py b/invokeai/app/services/model_records/model_records_sql.py
index 84a1412383..dcd1114655 100644
--- a/invokeai/app/services/model_records/model_records_sql.py
+++ b/invokeai/app/services/model_records/model_records_sql.py
@@ -54,8 +54,9 @@ from invokeai.backend.model_manager.config import (
     ModelFormat,
     ModelType,
 )
-from invokeai.backend.model_manager.metadata import AnyModelRepoMetadata, ModelMetadataStore, UnknownMetadataException
+from invokeai.backend.model_manager.metadata import AnyModelRepoMetadata, UnknownMetadataException
 
+from ..model_metadata import ModelMetadataStoreBase, ModelMetadataStoreSQL
 from ..shared.sqlite.sqlite_database import SqliteDatabase
 from .model_records_base import (
     DuplicateModelException,
@@ -69,7 +70,7 @@ from .model_records_base import (
 class ModelRecordServiceSQL(ModelRecordServiceBase):
     """Implementation of the ModelConfigStore ABC using a SQL database."""
 
-    def __init__(self, db: SqliteDatabase):
+    def __init__(self, db: SqliteDatabase, metadata_store: ModelMetadataStoreBase):
         """
         Initialize a new object from preexisting sqlite3 connection and threading lock objects.
 
@@ -78,6 +79,7 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
         super().__init__()
         self._db = db
         self._cursor = db.conn.cursor()
+        self._metadata_store = metadata_store
 
     @property
     def db(self) -> SqliteDatabase:
@@ -157,7 +159,7 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
                 self._db.conn.rollback()
                 raise e
 
-    def update_model(self, key: str, config: Union[dict, AnyModelConfig]) -> AnyModelConfig:
+    def update_model(self, key: str, config: Union[Dict[str, Any], AnyModelConfig]) -> AnyModelConfig:
         """
         Update the model, returning the updated version.
 
@@ -307,9 +309,9 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
         return results
 
     @property
-    def metadata_store(self) -> ModelMetadataStore:
+    def metadata_store(self) -> ModelMetadataStoreBase:
         """Return a ModelMetadataStore initialized on the same database."""
-        return ModelMetadataStore(self._db)
+        return self._metadata_store
 
     def get_metadata(self, key: str) -> Optional[AnyModelRepoMetadata]:
         """
@@ -330,18 +332,18 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
 
         :param tags: Set of tags to search for. All tags must be present.
         """
-        store = ModelMetadataStore(self._db)
+        store = ModelMetadataStoreSQL(self._db)
         keys = store.search_by_tag(tags)
         return [self.get_model(x) for x in keys]
 
     def list_tags(self) -> Set[str]:
         """Return a unique set of all the model tags in the metadata database."""
-        store = ModelMetadataStore(self._db)
+        store = ModelMetadataStoreSQL(self._db)
         return store.list_tags()
 
     def list_all_metadata(self) -> List[Tuple[str, AnyModelRepoMetadata]]:
         """List metadata for all models that have it."""
-        store = ModelMetadataStore(self._db)
+        store = ModelMetadataStoreSQL(self._db)
         return store.list_all_metadata()
 
     def list_models(
diff --git a/invokeai/backend/install/install_helper.py b/invokeai/backend/install/install_helper.py
index 9c386c209c..3623b623a9 100644
--- a/invokeai/backend/install/install_helper.py
+++ b/invokeai/backend/install/install_helper.py
@@ -25,6 +25,7 @@ from invokeai.app.services.model_install import (
     ModelSource,
     URLModelSource,
 )
+from invokeai.app.services.model_metadata import ModelMetadataStoreSQL
 from invokeai.app.services.model_records import ModelRecordServiceBase, ModelRecordServiceSQL
 from invokeai.app.services.shared.sqlite.sqlite_util import init_db
 from invokeai.backend.model_manager import (
@@ -45,7 +46,7 @@ def initialize_record_store(app_config: InvokeAIAppConfig) -> ModelRecordService
     logger = InvokeAILogger.get_logger(config=app_config)
     image_files = DiskImageFileStorage(f"{app_config.output_path}/images")
     db = init_db(config=app_config, logger=logger, image_files=image_files)
-    obj: ModelRecordServiceBase = ModelRecordServiceSQL(db)
+    obj: ModelRecordServiceBase = ModelRecordServiceSQL(db, ModelMetadataStoreSQL(db))
     return obj
 
 
@@ -54,12 +55,10 @@ def initialize_installer(
 ) -> ModelInstallServiceBase:
     """Return an initialized ModelInstallService object."""
     record_store = initialize_record_store(app_config)
-    metadata_store = record_store.metadata_store
     download_queue = DownloadQueueService()
     installer = ModelInstallService(
         app_config=app_config,
         record_store=record_store,
-        metadata_store=metadata_store,
         download_queue=download_queue,
         event_bus=event_bus,
     )
@@ -287,14 +286,14 @@ class InstallHelper(object):
                 model_name=model_name,
             )
             if len(matches) > 1:
-                print(
-                    f"{model_to_remove} is ambiguous. Please use model_base/model_type/model_name (e.g. sd-1/main/my_model) to disambiguate."
+                self._logger.error(
+                    "{model_to_remove} is ambiguous. Please use model_base/model_type/model_name (e.g. sd-1/main/my_model) to disambiguate"
                 )
             elif not matches:
-                print(f"{model_to_remove}: unknown model")
+                self._logger.error(f"{model_to_remove}: unknown model")
             else:
                 for m in matches:
-                    print(f"Deleting {m.type}:{m.name}")
+                    self._logger.info(f"Deleting {m.type}:{m.name}")
                     installer.delete(m.key)
 
         installer.wait_for_installs()
diff --git a/invokeai/backend/model_manager/load/__init__.py b/invokeai/backend/model_manager/load/__init__.py
index 966a739237..a3a840b625 100644
--- a/invokeai/backend/model_manager/load/__init__.py
+++ b/invokeai/backend/model_manager/load/__init__.py
@@ -4,10 +4,6 @@ Init file for the model loader.
 """
 from importlib import import_module
 from pathlib import Path
-from typing import Optional
-
-from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.backend.util.logging import InvokeAILogger
 
 from .convert_cache.convert_cache_default import ModelConvertCache
 from .load_base import AnyModelLoader, LoadedModel
@@ -19,16 +15,3 @@ for module in loaders:
     import_module(f"{__package__}.model_loaders.{module}")
 
 __all__ = ["AnyModelLoader", "LoadedModel", "ModelCache", "ModelConvertCache"]
-
-
-def get_standalone_loader(app_config: Optional[InvokeAIAppConfig]) -> AnyModelLoader:
-    app_config = app_config or InvokeAIAppConfig.get_config()
-    logger = InvokeAILogger.get_logger(config=app_config)
-    return AnyModelLoader(
-        app_config=app_config,
-        logger=logger,
-        ram_cache=ModelCache(
-            logger=logger, max_cache_size=app_config.ram_cache_size, max_vram_cache_size=app_config.vram_cache_size
-        ),
-        convert_cache=ModelConvertCache(app_config.models_convert_cache_path),
-    )
diff --git a/invokeai/backend/model_manager/load/load_base.py b/invokeai/backend/model_manager/load/load_base.py
index 7649dee762..4c5e899aa3 100644
--- a/invokeai/backend/model_manager/load/load_base.py
+++ b/invokeai/backend/model_manager/load/load_base.py
@@ -39,21 +39,21 @@ class LoadedModel:
     """Context manager object that mediates transfer from RAM<->VRAM."""
 
     config: AnyModelConfig
-    locker: ModelLockerBase
+    _locker: ModelLockerBase
 
     def __enter__(self) -> AnyModel:
         """Context entry."""
-        self.locker.lock()
+        self._locker.lock()
         return self.model
 
     def __exit__(self, *args: Any, **kwargs: Any) -> None:
         """Context exit."""
-        self.locker.unlock()
+        self._locker.unlock()
 
     @property
     def model(self) -> AnyModel:
         """Return the model without locking it."""
-        return self.locker.model
+        return self._locker.model
 
 
 class ModelLoaderBase(ABC):
diff --git a/invokeai/backend/model_manager/load/load_default.py b/invokeai/backend/model_manager/load/load_default.py
index 1dac121a30..79c9311de1 100644
--- a/invokeai/backend/model_manager/load/load_default.py
+++ b/invokeai/backend/model_manager/load/load_default.py
@@ -75,7 +75,7 @@ class ModelLoader(ModelLoaderBase):
 
         model_path = self._convert_if_needed(model_config, model_path, submodel_type)
         locker = self._load_if_needed(model_config, model_path, submodel_type)
-        return LoadedModel(config=model_config, locker=locker)
+        return LoadedModel(config=model_config, _locker=locker)
 
     def _get_model_path(
         self, config: AnyModelConfig, submodel_type: Optional[SubModelType] = None
diff --git a/invokeai/backend/model_manager/merge.py b/invokeai/backend/model_manager/merge.py
index 2c94af4af3..108f1f0e6f 100644
--- a/invokeai/backend/model_manager/merge.py
+++ b/invokeai/backend/model_manager/merge.py
@@ -39,10 +39,7 @@ class ModelMerger(object):
 
     def __init__(self, installer: ModelInstallServiceBase):
         """
-        Initialize a ModelMerger object.
-
-        :param store: Underlying storage manager for the running process.
-        :param config: InvokeAIAppConfig object (if not provided, default will be selected).
+        Initialize a ModelMerger object with the model installer.
         """
         self._installer = installer
 
diff --git a/invokeai/backend/model_manager/metadata/__init__.py b/invokeai/backend/model_manager/metadata/__init__.py
index 672e378c7f..a35e55f3d2 100644
--- a/invokeai/backend/model_manager/metadata/__init__.py
+++ b/invokeai/backend/model_manager/metadata/__init__.py
@@ -18,7 +18,7 @@ assert isinstance(data, CivitaiMetadata)
 if data.allow_commercial_use:
    print("Commercial use of this model is allowed")
 """
-from .fetch import CivitaiMetadataFetch, HuggingFaceMetadataFetch
+from .fetch import CivitaiMetadataFetch, HuggingFaceMetadataFetch, ModelMetadataFetchBase
 from .metadata_base import (
     AnyModelRepoMetadata,
     AnyModelRepoMetadataValidator,
@@ -31,7 +31,6 @@ from .metadata_base import (
     RemoteModelFile,
     UnknownMetadataException,
 )
-from .metadata_store import ModelMetadataStore
 
 __all__ = [
     "AnyModelRepoMetadata",
@@ -42,7 +41,7 @@ __all__ = [
     "HuggingFaceMetadata",
     "HuggingFaceMetadataFetch",
     "LicenseRestrictions",
-    "ModelMetadataStore",
+    "ModelMetadataFetchBase",
     "BaseMetadata",
     "ModelMetadataWithFiles",
     "RemoteModelFile",
diff --git a/invokeai/frontend/merge/merge_diffusers.py b/invokeai/frontend/merge/merge_diffusers.py
index 92b98b52f9..5484040674 100644
--- a/invokeai/frontend/merge/merge_diffusers.py
+++ b/invokeai/frontend/merge/merge_diffusers.py
@@ -6,20 +6,40 @@ Copyright (c) 2023 Lincoln Stein and the InvokeAI Development Team
 """
 import argparse
 import curses
+import re
 import sys
 from argparse import Namespace
 from pathlib import Path
-from typing import List
+from typing import List, Optional, Tuple
 
 import npyscreen
 from npyscreen import widget
 
-import invokeai.backend.util.logging as logger
 from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.backend.model_management import BaseModelType, ModelManager, ModelMerger, ModelType
+from invokeai.app.services.download import DownloadQueueService
+from invokeai.app.services.image_files.image_files_disk import DiskImageFileStorage
+from invokeai.app.services.model_install import ModelInstallService
+from invokeai.app.services.model_metadata import ModelMetadataStoreSQL
+from invokeai.app.services.model_records import ModelRecordServiceBase, ModelRecordServiceSQL
+from invokeai.app.services.shared.sqlite.sqlite_util import init_db
+from invokeai.backend.model_manager import (
+    BaseModelType,
+    ModelFormat,
+    ModelType,
+    ModelVariantType,
+)
+from invokeai.backend.model_manager.merge import ModelMerger
+from invokeai.backend.util.logging import InvokeAILogger
 from invokeai.frontend.install.widgets import FloatTitleSlider, SingleSelectColumns, TextBox
 
 config = InvokeAIAppConfig.get_config()
+logger = InvokeAILogger.get_logger()
+
+BASE_TYPES = [
+    (BaseModelType.StableDiffusion1, "Models Built on SD-1.x"),
+    (BaseModelType.StableDiffusion2, "Models Built on SD-2.x"),
+    (BaseModelType.StableDiffusionXL, "Models Built on SDXL"),
+]
 
 
 def _parse_args() -> Namespace:
@@ -48,7 +68,7 @@ def _parse_args() -> Namespace:
     parser.add_argument(
         "--base_model",
         type=str,
-        choices=[x.value for x in BaseModelType],
+        choices=[x[0].value for x in BASE_TYPES],
         help="The base model shared by the models to be merged",
     )
     parser.add_argument(
@@ -98,17 +118,17 @@ class mergeModelsForm(npyscreen.FormMultiPageAction):
         super().__init__(parentApp, name)
 
     @property
-    def model_manager(self):
-        return self.parentApp.model_manager
+    def record_store(self):
+        return self.parentApp.record_store
 
     def afterEditing(self):
         self.parentApp.setNextForm(None)
 
     def create(self):
         window_height, window_width = curses.initscr().getmaxyx()
-
-        self.model_names = self.get_model_names()
         self.current_base = 0
+        self.models = self.get_models(BASE_TYPES[self.current_base][0])
+        self.model_names = [x[1] for x in self.models]
         max_width = max([len(x) for x in self.model_names])
         max_width += 6
         horizontal_layout = max_width * 3 < window_width
@@ -128,11 +148,7 @@ class mergeModelsForm(npyscreen.FormMultiPageAction):
         self.nextrely += 1
         self.base_select = self.add_widget_intelligent(
             SingleSelectColumns,
-            values=[
-                "Models Built on SD-1.x",
-                "Models Built on SD-2.x",
-                "Models Built on SDXL",
-            ],
+            values=[x[1] for x in BASE_TYPES],
             value=[self.current_base],
             columns=4,
             max_height=2,
@@ -263,21 +279,20 @@ class mergeModelsForm(npyscreen.FormMultiPageAction):
         sys.exit(0)
 
     def marshall_arguments(self) -> dict:
-        model_names = self.model_names
+        model_keys = [x[0] for x in self.models]
         models = [
-            model_names[self.model1.value[0]],
-            model_names[self.model2.value[0]],
+            model_keys[self.model1.value[0]],
+            model_keys[self.model2.value[0]],
         ]
         if self.model3.value[0] > 0:
-            models.append(model_names[self.model3.value[0] - 1])
+            models.append(model_keys[self.model3.value[0] - 1])
             interp = "add_difference"
         else:
             interp = self.interpolations[self.merge_method.value[0]]
 
-        bases = ["sd-1", "sd-2", "sdxl"]
         args = {
-            "model_names": models,
-            "base_model": BaseModelType(bases[self.base_select.value[0]]),
+            "model_keys": models,
+            "base_model": tuple(BaseModelType)[self.base_select.value[0]],
             "alpha": self.alpha.value,
             "interp": interp,
             "force": self.force.value,
@@ -311,18 +326,18 @@ class mergeModelsForm(npyscreen.FormMultiPageAction):
         else:
             return True
 
-    def get_model_names(self, base_model: BaseModelType = BaseModelType.StableDiffusion1) -> List[str]:
-        model_names = [
-            info["model_name"]
-            for info in self.model_manager.list_models(model_type=ModelType.Main, base_model=base_model)
-            if info["model_format"] == "diffusers"
+    def get_models(self, base_model: Optional[BaseModelType] = None) -> List[Tuple[str, str]]:  # key to name
+        models = [
+            (x.key, x.name)
+            for x in self.record_store.search_by_attr(model_type=ModelType.Main, base_model=base_model)
+            if x.format == ModelFormat("diffusers") and x.variant == ModelVariantType("normal")
         ]
-        return sorted(model_names)
+        return sorted(models, key=lambda x: x[1])
 
-    def _populate_models(self, value=None):
-        bases = ["sd-1", "sd-2", "sdxl"]
-        base_model = BaseModelType(bases[value[0]])
-        self.model_names = self.get_model_names(base_model)
+    def _populate_models(self, value: List[int]):
+        base_model = BASE_TYPES[value[0]][0]
+        self.models = self.get_models(base_model)
+        self.model_names = [x[1] for x in self.models]
 
         models_plus_none = self.model_names.copy()
         models_plus_none.insert(0, "None")
@@ -334,24 +349,24 @@ class mergeModelsForm(npyscreen.FormMultiPageAction):
 
 
 class Mergeapp(npyscreen.NPSAppManaged):
-    def __init__(self, model_manager: ModelManager):
+    def __init__(self, record_store: ModelRecordServiceBase):
         super().__init__()
-        self.model_manager = model_manager
+        self.record_store = record_store
 
     def onStart(self):
         npyscreen.setTheme(npyscreen.Themes.ElegantTheme)
         self.main = self.addForm("MAIN", mergeModelsForm, name="Merge Models Settings")
 
 
-def run_gui(args: Namespace):
-    model_manager = ModelManager(config.model_conf_path)
-    mergeapp = Mergeapp(model_manager)
+def run_gui(args: Namespace) -> None:
+    record_store: ModelRecordServiceBase = get_config_store()
+    mergeapp = Mergeapp(record_store)
     mergeapp.run()
-
     args = mergeapp.merge_arguments
-    merger = ModelMerger(model_manager)
+    merger = get_model_merger(record_store)
     merger.merge_diffusion_models_and_save(**args)
-    logger.info(f'Models merged into new model: "{args["merged_model_name"]}".')
+    merged_model_name = args["merged_model_name"]
+    logger.info(f'Models merged into new model: "{merged_model_name}".')
 
 
 def run_cli(args: Namespace):
@@ -364,20 +379,54 @@ def run_cli(args: Namespace):
         args.merged_model_name = "+".join(args.model_names)
         logger.info(f'No --merged_model_name provided. Defaulting to "{args.merged_model_name}"')
 
-    model_manager = ModelManager(config.model_conf_path)
+    record_store: ModelRecordServiceBase = get_config_store()
     assert (
-        not model_manager.model_exists(args.merged_model_name, args.base_model, ModelType.Main) or args.clobber
+        len(record_store.search_by_attr(args.merged_model_name, args.base_model, ModelType.Main)) == 0 or args.clobber
     ), f'A model named "{args.merged_model_name}" already exists. Use --clobber to overwrite.'
 
-    merger = ModelMerger(model_manager)
-    merger.merge_diffusion_models_and_save(**vars(args))
+    merger = get_model_merger(record_store)
+    model_keys = []
+    for name in args.model_names:
+        if len(name) == 32 and re.match(r"^[0-9a-f]$", name):
+            model_keys.append(name)
+        else:
+            models = record_store.search_by_attr(
+                model_name=name, model_type=ModelType.Main, base_model=BaseModelType(args.base_model)
+            )
+            assert len(models) > 0, f"{name}: Unknown model"
+            assert len(models) < 2, f"{name}: More than one model by this name. Please specify the model key instead."
+            model_keys.append(models[0].key)
+
+    merger.merge_diffusion_models_and_save(
+        alpha=args.alpha,
+        model_keys=model_keys,
+        merged_model_name=args.merged_model_name,
+        interp=args.interp,
+        force=args.force,
+    )
     logger.info(f'Models merged into new model: "{args.merged_model_name}".')
 
 
+def get_config_store() -> ModelRecordServiceSQL:
+    output_path = config.output_path
+    assert output_path is not None
+    image_files = DiskImageFileStorage(output_path / "images")
+    db = init_db(config=config, logger=InvokeAILogger.get_logger(), image_files=image_files)
+    return ModelRecordServiceSQL(db, ModelMetadataStoreSQL(db))
+
+
+def get_model_merger(record_store: ModelRecordServiceBase) -> ModelMerger:
+    installer = ModelInstallService(app_config=config, record_store=record_store, download_queue=DownloadQueueService())
+    installer.start()
+    return ModelMerger(installer)
+
+
 def main():
     args = _parse_args()
     if args.root_dir:
         config.parse_args(["--root", str(args.root_dir)])
+    else:
+        config.parse_args([])
 
     try:
         if args.front_end:
diff --git a/tests/aa_nodes/test_invoker.py b/tests/aa_nodes/test_invoker.py
index 774f7501dc..f67b5a2ac5 100644
--- a/tests/aa_nodes/test_invoker.py
+++ b/tests/aa_nodes/test_invoker.py
@@ -1,4 +1,5 @@
 import logging
+from unittest.mock import Mock
 
 import pytest
 
@@ -64,7 +65,7 @@ def mock_services() -> InvocationServices:
         images=None,  # type: ignore
         invocation_cache=MemoryInvocationCache(max_cache_size=0),
         logger=logging,  # type: ignore
-        model_manager=None,  # type: ignore
+        model_manager=Mock(),  # type: ignore
         download_queue=None,  # type: ignore
         names=None,  # type: ignore
         performance_statistics=InvocationStatsService(),
diff --git a/tests/app/services/model_records/test_model_records_sql.py b/tests/app/services/model_records/test_model_records_sql.py
index 46afe0105b..852e1da979 100644
--- a/tests/app/services/model_records/test_model_records_sql.py
+++ b/tests/app/services/model_records/test_model_records_sql.py
@@ -8,6 +8,7 @@ from typing import Any
 import pytest
 
 from invokeai.app.services.config import InvokeAIAppConfig
+from invokeai.app.services.model_metadata import ModelMetadataStoreSQL
 from invokeai.app.services.model_records import (
     DuplicateModelException,
     ModelRecordOrderBy,
@@ -36,7 +37,7 @@ def store(
     config = InvokeAIAppConfig(root=datadir)
     logger = InvokeAILogger.get_logger(config=config)
     db = create_mock_sqlite_database(config, logger)
-    return ModelRecordServiceSQL(db)
+    return ModelRecordServiceSQL(db, ModelMetadataStoreSQL(db))
 
 
 def example_config() -> TextualInversionConfig:
diff --git a/tests/backend/model_manager_2/model_manager_2_fixtures.py b/tests/backend/model_manager_2/model_manager_2_fixtures.py
index d85eab67dd..ebdc9cb5cd 100644
--- a/tests/backend/model_manager_2/model_manager_2_fixtures.py
+++ b/tests/backend/model_manager_2/model_manager_2_fixtures.py
@@ -14,6 +14,7 @@ from invokeai.app.services.config import InvokeAIAppConfig
 from invokeai.app.services.download import DownloadQueueService
 from invokeai.app.services.events.events_base import EventServiceBase
 from invokeai.app.services.model_install import ModelInstallService, ModelInstallServiceBase
+from invokeai.app.services.model_metadata import ModelMetadataStoreBase, ModelMetadataStoreSQL
 from invokeai.app.services.model_records import ModelRecordServiceSQL
 from invokeai.backend.model_manager.config import (
     BaseModelType,
@@ -21,7 +22,6 @@ from invokeai.backend.model_manager.config import (
     ModelType,
 )
 from invokeai.backend.model_manager.load import AnyModelLoader, ModelCache, ModelConvertCache
-from invokeai.backend.model_manager.metadata import ModelMetadataStore
 from invokeai.backend.util.logging import InvokeAILogger
 from tests.backend.model_manager_2.model_metadata.metadata_examples import (
     RepoCivitaiModelMetadata1,
@@ -104,7 +104,7 @@ def mm2_loader(mm2_app_config: InvokeAIAppConfig, mm2_record_store: ModelRecordS
 def mm2_record_store(mm2_app_config: InvokeAIAppConfig) -> ModelRecordServiceSQL:
     logger = InvokeAILogger.get_logger(config=mm2_app_config)
     db = create_mock_sqlite_database(mm2_app_config, logger)
-    store = ModelRecordServiceSQL(db)
+    store = ModelRecordServiceSQL(db, ModelMetadataStoreSQL(db))
     # add five simple config records to the database
     raw1 = {
         "path": "/tmp/foo1",
@@ -163,15 +163,14 @@ def mm2_record_store(mm2_app_config: InvokeAIAppConfig) -> ModelRecordServiceSQL
 
 
 @pytest.fixture
-def mm2_metadata_store(mm2_record_store: ModelRecordServiceSQL) -> ModelMetadataStore:
-    db = mm2_record_store._db  # to ensure we are sharing the same database
-    return ModelMetadataStore(db)
+def mm2_metadata_store(mm2_record_store: ModelRecordServiceSQL) -> ModelMetadataStoreBase:
+    return mm2_record_store.metadata_store
 
 
 @pytest.fixture
 def mm2_session(embedding_file: Path, diffusers_dir: Path) -> Session:
     """This fixtures defines a series of mock URLs for testing download and installation."""
-    sess = TestSession()
+    sess: Session = TestSession()
     sess.mount(
         "https://test.com/missing_model.safetensors",
         TestAdapter(
@@ -258,8 +257,7 @@ def mm2_installer(mm2_app_config: InvokeAIAppConfig, mm2_session: Session) -> Mo
     logger = InvokeAILogger.get_logger()
     db = create_mock_sqlite_database(mm2_app_config, logger)
     events = DummyEventService()
-    store = ModelRecordServiceSQL(db)
-    metadata_store = ModelMetadataStore(db)
+    store = ModelRecordServiceSQL(db, ModelMetadataStoreSQL(db))
 
     download_queue = DownloadQueueService(requests_session=mm2_session)
     download_queue.start()
@@ -268,7 +266,6 @@ def mm2_installer(mm2_app_config: InvokeAIAppConfig, mm2_session: Session) -> Mo
         app_config=mm2_app_config,
         record_store=store,
         download_queue=download_queue,
-        metadata_store=metadata_store,
         event_bus=events,
         session=mm2_session,
     )
diff --git a/tests/backend/model_manager_2/model_metadata/test_model_metadata.py b/tests/backend/model_manager_2/model_metadata/test_model_metadata.py
index 5a2ec93767..f61eab1b5d 100644
--- a/tests/backend/model_manager_2/model_metadata/test_model_metadata.py
+++ b/tests/backend/model_manager_2/model_metadata/test_model_metadata.py
@@ -8,6 +8,7 @@ import pytest
 from pydantic.networks import HttpUrl
 from requests.sessions import Session
 
+from invokeai.app.services.model_metadata import ModelMetadataStoreBase
 from invokeai.backend.model_manager.config import ModelRepoVariant
 from invokeai.backend.model_manager.metadata import (
     CivitaiMetadata,
@@ -15,14 +16,13 @@ from invokeai.backend.model_manager.metadata import (
     CommercialUsage,
     HuggingFaceMetadata,
     HuggingFaceMetadataFetch,
-    ModelMetadataStore,
     UnknownMetadataException,
 )
 from invokeai.backend.model_manager.util import select_hf_files
 from tests.backend.model_manager_2.model_manager_2_fixtures import *  # noqa F403
 
 
-def test_metadata_store_put_get(mm2_metadata_store: ModelMetadataStore) -> None:
+def test_metadata_store_put_get(mm2_metadata_store: ModelMetadataStoreBase) -> None:
     tags = {"text-to-image", "diffusers"}
     input_metadata = HuggingFaceMetadata(
         name="sdxl-vae",
@@ -40,7 +40,7 @@ def test_metadata_store_put_get(mm2_metadata_store: ModelMetadataStore) -> None:
     assert mm2_metadata_store.list_tags() == tags
 
 
-def test_metadata_store_update(mm2_metadata_store: ModelMetadataStore) -> None:
+def test_metadata_store_update(mm2_metadata_store: ModelMetadataStoreBase) -> None:
     input_metadata = HuggingFaceMetadata(
         name="sdxl-vae",
         author="stabilityai",
@@ -57,7 +57,7 @@ def test_metadata_store_update(mm2_metadata_store: ModelMetadataStore) -> None:
     assert input_metadata == output_metadata
 
 
-def test_metadata_search(mm2_metadata_store: ModelMetadataStore) -> None:
+def test_metadata_search(mm2_metadata_store: ModelMetadataStoreBase) -> None:
     metadata1 = HuggingFaceMetadata(
         name="sdxl-vae",
         author="stabilityai",

From 5d612ec0958280f5709a22f9872c905abbab12ad Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lstein@gmail.com>
Date: Sat, 17 Feb 2024 11:45:32 -0500
Subject: [PATCH 145/411] Tidy names and locations of modules

- Rename old "model_management" directory to "model_management_OLD" in order to catch
  dangling references to original model manager.
- Caught and fixed most dangling references (still checking)
- Rename lora, textual_inversion and model_patcher modules
- Introduce a RawModel base class to simplfy the Union returned by the
  model loaders.
- Tidy up the model manager 2-related tests. Add useful fixtures, and
  a finalizer to the queue and installer fixtures that will stop the
  services and release threads.
---
 invokeai/app/invocations/compel.py            |   6 +-
 invokeai/app/invocations/latent.py            |   4 +-
 .../services/model_load/model_load_default.py |  23 +-
 .../app/services/model_manager/__init__.py    |   3 +-
 invokeai/backend/ip_adapter/ip_adapter.py     |   3 +-
 invokeai/backend/{embeddings => }/lora.py     |   7 +-
 .../README.md                                 |   0
 .../__init__.py                               |   0
 .../convert_ckpt_to_diffusers.py              |   0
 .../detect_baked_in_vae.py                    |   0
 .../lora.py                                   |   0
 .../memory_snapshot.py                        |   0
 .../model_cache.py                            |   0
 .../model_load_optimizations.py               |   0
 .../model_manager.py                          |   0
 .../model_merge.py                            |   0
 .../model_probe.py                            |   0
 .../model_search.py                           |   0
 .../models/__init__.py                        |   0
 .../models/base.py                            |   0
 .../models/clip_vision.py                     |   0
 .../models/controlnet.py                      |   0
 .../models/ip_adapter.py                      |   0
 .../models/lora.py                            |   0
 .../models/sdxl.py                            |   0
 .../models/stable_diffusion.py                |   0
 .../models/stable_diffusion_onnx.py           |   0
 .../models/t2i_adapter.py                     |   0
 .../models/textual_inversion.py               |   0
 .../models/vae.py                             |   0
 .../seamless.py                               |   0
 .../util.py                                   |   0
 invokeai/backend/model_manager/config.py      |   9 +-
 .../libc_util.py                              |   0
 .../model_manager/load/memory_snapshot.py     |   4 +-
 .../model_manager/load/model_loaders/lora.py  |   2 +-
 .../load/model_loaders/textual_inversion.py   |   2 +-
 invokeai/backend/model_manager/probe.py       |   9 +-
 .../backend/model_manager/util/libc_util.py   |  75 ++
 .../backend/model_manager/util/model_util.py  | 129 +++
 .../backend/{embeddings => }/model_patcher.py |   0
 invokeai/backend/onnx/onnx_runtime.py         |   1 +
 invokeai/backend/raw_model.py                 |  14 +
 .../{embeddings => }/textual_inversion.py     |   6 +-
 invokeai/backend/util/test_utils.py           |  45 +-
 invokeai/configs/INITIAL_MODELS.yaml.OLD      | 153 ----
 invokeai/configs/models.yaml.example          |  47 -
 .../frontend/install/model_install.py.OLD     | 845 ------------------
 .../frontend/merge/merge_diffusers.py.OLD     | 438 ---------
 .../model_install/test_model_install.py       |   2 +-
 .../model_records/test_model_records_sql.py   |   2 +-
 tests/backend/ip_adapter/test_ip_adapter.py   |   2 +-
 .../data/invokeai_root/README                 |   0
 .../stable-diffusion/v1-inference.yaml        |   0
 .../data/invokeai_root/databases/README       |   0
 .../data/invokeai_root/models/README          |   0
 .../test-diffusers-main/model_index.json      |   0
 .../scheduler/scheduler_config.json           |   0
 .../text_encoder/config.json                  |   0
 .../text_encoder/model.fp16.safetensors       |   0
 .../text_encoder/model.safetensors            |   0
 .../text_encoder_2/config.json                |   0
 .../text_encoder_2/model.fp16.safetensors     |   0
 .../text_encoder_2/model.safetensors          |   0
 .../test-diffusers-main/tokenizer/merges.txt  |   0
 .../tokenizer/special_tokens_map.json         |   0
 .../tokenizer/tokenizer_config.json           |   0
 .../test-diffusers-main/tokenizer/vocab.json  |   0
 .../tokenizer_2/merges.txt                    |   0
 .../tokenizer_2/special_tokens_map.json       |   0
 .../tokenizer_2/tokenizer_config.json         |   0
 .../tokenizer_2/vocab.json                    |   0
 .../test-diffusers-main/unet/config.json      |   0
 .../diffusion_pytorch_model.fp16.safetensors  |   0
 .../unet/diffusion_pytorch_model.safetensors  |   0
 .../test-diffusers-main/vae/config.json       |   0
 .../diffusion_pytorch_model.fp16.safetensors  |   0
 .../vae/diffusion_pytorch_model.safetensors   |   0
 .../test_files/test_embedding.safetensors     | Bin
 .../model_loading/test_model_load.py          |  11 +-
 .../model_manager_fixtures.py}                | 101 ++-
 .../model_metadata/metadata_examples.py       |   0
 .../model_metadata/test_model_metadata.py     |   2 +-
 .../test_libc_util.py                         |   2 +-
 .../test_lora.py                              |   4 +-
 .../test_memory_snapshot.py                   |   6 +-
 .../test_model_load_optimization.py           |   2 +-
 .../util/test_hf_model_select.py              |   0
 tests/conftest.py                             |   5 -
 89 files changed, 355 insertions(+), 1609 deletions(-)
 rename invokeai/backend/{embeddings => }/lora.py (99%)
 rename invokeai/backend/{model_management => model_management_OLD}/README.md (100%)
 rename invokeai/backend/{model_management => model_management_OLD}/__init__.py (100%)
 rename invokeai/backend/{model_management => model_management_OLD}/convert_ckpt_to_diffusers.py (100%)
 rename invokeai/backend/{model_management => model_management_OLD}/detect_baked_in_vae.py (100%)
 rename invokeai/backend/{model_management => model_management_OLD}/lora.py (100%)
 rename invokeai/backend/{model_management => model_management_OLD}/memory_snapshot.py (100%)
 rename invokeai/backend/{model_management => model_management_OLD}/model_cache.py (100%)
 rename invokeai/backend/{model_management => model_management_OLD}/model_load_optimizations.py (100%)
 rename invokeai/backend/{model_management => model_management_OLD}/model_manager.py (100%)
 rename invokeai/backend/{model_management => model_management_OLD}/model_merge.py (100%)
 rename invokeai/backend/{model_management => model_management_OLD}/model_probe.py (100%)
 rename invokeai/backend/{model_management => model_management_OLD}/model_search.py (100%)
 rename invokeai/backend/{model_management => model_management_OLD}/models/__init__.py (100%)
 rename invokeai/backend/{model_management => model_management_OLD}/models/base.py (100%)
 rename invokeai/backend/{model_management => model_management_OLD}/models/clip_vision.py (100%)
 rename invokeai/backend/{model_management => model_management_OLD}/models/controlnet.py (100%)
 rename invokeai/backend/{model_management => model_management_OLD}/models/ip_adapter.py (100%)
 rename invokeai/backend/{model_management => model_management_OLD}/models/lora.py (100%)
 rename invokeai/backend/{model_management => model_management_OLD}/models/sdxl.py (100%)
 rename invokeai/backend/{model_management => model_management_OLD}/models/stable_diffusion.py (100%)
 rename invokeai/backend/{model_management => model_management_OLD}/models/stable_diffusion_onnx.py (100%)
 rename invokeai/backend/{model_management => model_management_OLD}/models/t2i_adapter.py (100%)
 rename invokeai/backend/{model_management => model_management_OLD}/models/textual_inversion.py (100%)
 rename invokeai/backend/{model_management => model_management_OLD}/models/vae.py (100%)
 rename invokeai/backend/{model_management => model_management_OLD}/seamless.py (100%)
 rename invokeai/backend/{model_management => model_management_OLD}/util.py (100%)
 rename invokeai/backend/{model_management => model_manager}/libc_util.py (100%)
 create mode 100644 invokeai/backend/model_manager/util/libc_util.py
 create mode 100644 invokeai/backend/model_manager/util/model_util.py
 rename invokeai/backend/{embeddings => }/model_patcher.py (100%)
 create mode 100644 invokeai/backend/raw_model.py
 rename invokeai/backend/{embeddings => }/textual_inversion.py (97%)
 delete mode 100644 invokeai/configs/INITIAL_MODELS.yaml.OLD
 delete mode 100644 invokeai/configs/models.yaml.example
 delete mode 100644 invokeai/frontend/install/model_install.py.OLD
 delete mode 100644 invokeai/frontend/merge/merge_diffusers.py.OLD
 rename tests/backend/{model_manager_2 => model_manager}/data/invokeai_root/README (100%)
 rename tests/backend/{model_manager_2 => model_manager}/data/invokeai_root/configs/stable-diffusion/v1-inference.yaml (100%)
 rename tests/backend/{model_manager_2 => model_manager}/data/invokeai_root/databases/README (100%)
 rename tests/backend/{model_manager_2 => model_manager}/data/invokeai_root/models/README (100%)
 rename tests/backend/{model_manager_2 => model_manager}/data/test_files/test-diffusers-main/model_index.json (100%)
 rename tests/backend/{model_manager_2 => model_manager}/data/test_files/test-diffusers-main/scheduler/scheduler_config.json (100%)
 rename tests/backend/{model_manager_2 => model_manager}/data/test_files/test-diffusers-main/text_encoder/config.json (100%)
 rename tests/backend/{model_manager_2 => model_manager}/data/test_files/test-diffusers-main/text_encoder/model.fp16.safetensors (100%)
 rename tests/backend/{model_manager_2 => model_manager}/data/test_files/test-diffusers-main/text_encoder/model.safetensors (100%)
 rename tests/backend/{model_manager_2 => model_manager}/data/test_files/test-diffusers-main/text_encoder_2/config.json (100%)
 rename tests/backend/{model_manager_2 => model_manager}/data/test_files/test-diffusers-main/text_encoder_2/model.fp16.safetensors (100%)
 rename tests/backend/{model_manager_2 => model_manager}/data/test_files/test-diffusers-main/text_encoder_2/model.safetensors (100%)
 rename tests/backend/{model_manager_2 => model_manager}/data/test_files/test-diffusers-main/tokenizer/merges.txt (100%)
 rename tests/backend/{model_manager_2 => model_manager}/data/test_files/test-diffusers-main/tokenizer/special_tokens_map.json (100%)
 rename tests/backend/{model_manager_2 => model_manager}/data/test_files/test-diffusers-main/tokenizer/tokenizer_config.json (100%)
 rename tests/backend/{model_manager_2 => model_manager}/data/test_files/test-diffusers-main/tokenizer/vocab.json (100%)
 rename tests/backend/{model_manager_2 => model_manager}/data/test_files/test-diffusers-main/tokenizer_2/merges.txt (100%)
 rename tests/backend/{model_manager_2 => model_manager}/data/test_files/test-diffusers-main/tokenizer_2/special_tokens_map.json (100%)
 rename tests/backend/{model_manager_2 => model_manager}/data/test_files/test-diffusers-main/tokenizer_2/tokenizer_config.json (100%)
 rename tests/backend/{model_manager_2 => model_manager}/data/test_files/test-diffusers-main/tokenizer_2/vocab.json (100%)
 rename tests/backend/{model_manager_2 => model_manager}/data/test_files/test-diffusers-main/unet/config.json (100%)
 rename tests/backend/{model_manager_2 => model_manager}/data/test_files/test-diffusers-main/unet/diffusion_pytorch_model.fp16.safetensors (100%)
 rename tests/backend/{model_manager_2 => model_manager}/data/test_files/test-diffusers-main/unet/diffusion_pytorch_model.safetensors (100%)
 rename tests/backend/{model_manager_2 => model_manager}/data/test_files/test-diffusers-main/vae/config.json (100%)
 rename tests/backend/{model_manager_2 => model_manager}/data/test_files/test-diffusers-main/vae/diffusion_pytorch_model.fp16.safetensors (100%)
 rename tests/backend/{model_manager_2 => model_manager}/data/test_files/test-diffusers-main/vae/diffusion_pytorch_model.safetensors (100%)
 rename tests/backend/{model_manager_2 => model_manager}/data/test_files/test_embedding.safetensors (100%)
 rename tests/backend/{model_manager_2 => model_manager}/model_loading/test_model_load.py (61%)
 rename tests/backend/{model_manager_2/model_manager_2_fixtures.py => model_manager/model_manager_fixtures.py} (80%)
 rename tests/backend/{model_manager_2 => model_manager}/model_metadata/metadata_examples.py (100%)
 rename tests/backend/{model_manager_2 => model_manager}/model_metadata/test_model_metadata.py (99%)
 rename tests/backend/{model_management => model_manager}/test_libc_util.py (88%)
 rename tests/backend/{model_management => model_manager}/test_lora.py (96%)
 rename tests/backend/{model_management => model_manager}/test_memory_snapshot.py (87%)
 rename tests/backend/{model_management => model_manager}/test_model_load_optimization.py (96%)
 rename tests/backend/{model_manager_2 => model_manager}/util/test_hf_model_select.py (100%)

diff --git a/invokeai/app/invocations/compel.py b/invokeai/app/invocations/compel.py
index 5159d5b89c..593121ba60 100644
--- a/invokeai/app/invocations/compel.py
+++ b/invokeai/app/invocations/compel.py
@@ -17,9 +17,9 @@ from invokeai.app.invocations.primitives import ConditioningOutput
 from invokeai.app.services.model_records import UnknownModelException
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.app.util.ti_utils import extract_ti_triggers_from_prompt
-from invokeai.backend.embeddings.lora import LoRAModelRaw
-from invokeai.backend.embeddings.model_patcher import ModelPatcher
-from invokeai.backend.embeddings.textual_inversion import TextualInversionModelRaw
+from invokeai.backend.lora import LoRAModelRaw
+from invokeai.backend.model_patcher import ModelPatcher
+from invokeai.backend.textual_inversion import TextualInversionModelRaw
 from invokeai.backend.model_manager import ModelType
 from invokeai.backend.stable_diffusion.diffusion.conditioning_data import (
     BasicConditioningInfo,
diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py
index 1f21b539dc..bfe7255b62 100644
--- a/invokeai/app/invocations/latent.py
+++ b/invokeai/app/invocations/latent.py
@@ -50,10 +50,10 @@ from invokeai.app.invocations.primitives import (
 from invokeai.app.invocations.t2i_adapter import T2IAdapterField
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.app.util.controlnet_utils import prepare_control_image
-from invokeai.backend.embeddings.lora import LoRAModelRaw
-from invokeai.backend.embeddings.model_patcher import ModelPatcher
 from invokeai.backend.ip_adapter.ip_adapter import IPAdapter, IPAdapterPlus
+from invokeai.backend.lora import LoRAModelRaw
 from invokeai.backend.model_manager import BaseModelType, LoadedModel
+from invokeai.backend.model_patcher import ModelPatcher
 from invokeai.backend.stable_diffusion import PipelineIntermediateState, set_seamless
 from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ConditioningData, IPAdapterConditioningInfo
 from invokeai.backend.util.silence_warnings import SilenceWarnings
diff --git a/invokeai/app/services/model_load/model_load_default.py b/invokeai/app/services/model_load/model_load_default.py
index 29b297c814..fa96a4672d 100644
--- a/invokeai/app/services/model_load/model_load_default.py
+++ b/invokeai/app/services/model_load/model_load_default.py
@@ -21,11 +21,11 @@ class ModelLoadService(ModelLoadServiceBase):
     """Wrapper around AnyModelLoader."""
 
     def __init__(
-        self,
-        app_config: InvokeAIAppConfig,
-        record_store: ModelRecordServiceBase,
-        ram_cache: Optional[ModelCacheBase[AnyModel]] = None,
-        convert_cache: Optional[ModelConvertCacheBase] = None,
+            self,
+            app_config: InvokeAIAppConfig,
+            record_store: ModelRecordServiceBase,
+            ram_cache: ModelCacheBase[AnyModel],
+            convert_cache: ModelConvertCacheBase,
     ):
         """Initialize the model load service."""
         logger = InvokeAILogger.get_logger(self.__class__.__name__)
@@ -34,17 +34,8 @@ class ModelLoadService(ModelLoadServiceBase):
         self._any_loader = AnyModelLoader(
             app_config=app_config,
             logger=logger,
-            ram_cache=ram_cache
-            or ModelCache(
-                max_cache_size=app_config.ram_cache_size,
-                max_vram_cache_size=app_config.vram_cache_size,
-                logger=logger,
-            ),
-            convert_cache=convert_cache
-            or ModelConvertCache(
-                cache_path=app_config.models_convert_cache_path,
-                max_size=app_config.convert_cache_size,
-            ),
+            ram_cache=ram_cache,
+            convert_cache=convert_cache,
         )
 
     def start(self, invoker: Invoker) -> None:
diff --git a/invokeai/app/services/model_manager/__init__.py b/invokeai/app/services/model_manager/__init__.py
index 5e281922a8..66707493f7 100644
--- a/invokeai/app/services/model_manager/__init__.py
+++ b/invokeai/app/services/model_manager/__init__.py
@@ -3,9 +3,10 @@
 from invokeai.backend.model_manager import AnyModel, AnyModelConfig, BaseModelType, ModelType, SubModelType
 from invokeai.backend.model_manager.load import LoadedModel
 
-from .model_manager_default import ModelManagerService
+from .model_manager_default import ModelManagerServiceBase, ModelManagerService
 
 __all__ = [
+    "ModelManagerServiceBase",
     "ModelManagerService",
     "AnyModel",
     "AnyModelConfig",
diff --git a/invokeai/backend/ip_adapter/ip_adapter.py b/invokeai/backend/ip_adapter/ip_adapter.py
index b4706ea99c..3ba6fc5a23 100644
--- a/invokeai/backend/ip_adapter/ip_adapter.py
+++ b/invokeai/backend/ip_adapter/ip_adapter.py
@@ -10,6 +10,7 @@ from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
 from invokeai.backend.ip_adapter.ip_attention_weights import IPAttentionWeights
 
 from .resampler import Resampler
+from ..raw_model import RawModel
 
 
 class ImageProjModel(torch.nn.Module):
@@ -91,7 +92,7 @@ class MLPProjModel(torch.nn.Module):
         return clip_extra_context_tokens
 
 
-class IPAdapter:
+class IPAdapter(RawModel):
     """IP-Adapter: https://arxiv.org/pdf/2308.06721.pdf"""
 
     def __init__(
diff --git a/invokeai/backend/embeddings/lora.py b/invokeai/backend/lora.py
similarity index 99%
rename from invokeai/backend/embeddings/lora.py
rename to invokeai/backend/lora.py
index 3c7ef074ef..fb0c23067f 100644
--- a/invokeai/backend/embeddings/lora.py
+++ b/invokeai/backend/lora.py
@@ -10,8 +10,7 @@ from safetensors.torch import load_file
 from typing_extensions import Self
 
 from invokeai.backend.model_manager import BaseModelType
-
-from .embedding_base import EmbeddingModelRaw
+from .raw_model import RawModel
 
 
 class LoRALayerBase:
@@ -367,9 +366,7 @@ class IA3Layer(LoRALayerBase):
 
 AnyLoRALayer = Union[LoRALayer, LoHALayer, LoKRLayer, FullLayer, IA3Layer]
 
-
-# TODO: rename all methods used in model logic with Info postfix and remove here Raw postfix
-class LoRAModelRaw(EmbeddingModelRaw):  # (torch.nn.Module):
+class LoRAModelRaw(RawModel):  # (torch.nn.Module):
     _name: str
     layers: Dict[str, AnyLoRALayer]
 
diff --git a/invokeai/backend/model_management/README.md b/invokeai/backend/model_management_OLD/README.md
similarity index 100%
rename from invokeai/backend/model_management/README.md
rename to invokeai/backend/model_management_OLD/README.md
diff --git a/invokeai/backend/model_management/__init__.py b/invokeai/backend/model_management_OLD/__init__.py
similarity index 100%
rename from invokeai/backend/model_management/__init__.py
rename to invokeai/backend/model_management_OLD/__init__.py
diff --git a/invokeai/backend/model_management/convert_ckpt_to_diffusers.py b/invokeai/backend/model_management_OLD/convert_ckpt_to_diffusers.py
similarity index 100%
rename from invokeai/backend/model_management/convert_ckpt_to_diffusers.py
rename to invokeai/backend/model_management_OLD/convert_ckpt_to_diffusers.py
diff --git a/invokeai/backend/model_management/detect_baked_in_vae.py b/invokeai/backend/model_management_OLD/detect_baked_in_vae.py
similarity index 100%
rename from invokeai/backend/model_management/detect_baked_in_vae.py
rename to invokeai/backend/model_management_OLD/detect_baked_in_vae.py
diff --git a/invokeai/backend/model_management/lora.py b/invokeai/backend/model_management_OLD/lora.py
similarity index 100%
rename from invokeai/backend/model_management/lora.py
rename to invokeai/backend/model_management_OLD/lora.py
diff --git a/invokeai/backend/model_management/memory_snapshot.py b/invokeai/backend/model_management_OLD/memory_snapshot.py
similarity index 100%
rename from invokeai/backend/model_management/memory_snapshot.py
rename to invokeai/backend/model_management_OLD/memory_snapshot.py
diff --git a/invokeai/backend/model_management/model_cache.py b/invokeai/backend/model_management_OLD/model_cache.py
similarity index 100%
rename from invokeai/backend/model_management/model_cache.py
rename to invokeai/backend/model_management_OLD/model_cache.py
diff --git a/invokeai/backend/model_management/model_load_optimizations.py b/invokeai/backend/model_management_OLD/model_load_optimizations.py
similarity index 100%
rename from invokeai/backend/model_management/model_load_optimizations.py
rename to invokeai/backend/model_management_OLD/model_load_optimizations.py
diff --git a/invokeai/backend/model_management/model_manager.py b/invokeai/backend/model_management_OLD/model_manager.py
similarity index 100%
rename from invokeai/backend/model_management/model_manager.py
rename to invokeai/backend/model_management_OLD/model_manager.py
diff --git a/invokeai/backend/model_management/model_merge.py b/invokeai/backend/model_management_OLD/model_merge.py
similarity index 100%
rename from invokeai/backend/model_management/model_merge.py
rename to invokeai/backend/model_management_OLD/model_merge.py
diff --git a/invokeai/backend/model_management/model_probe.py b/invokeai/backend/model_management_OLD/model_probe.py
similarity index 100%
rename from invokeai/backend/model_management/model_probe.py
rename to invokeai/backend/model_management_OLD/model_probe.py
diff --git a/invokeai/backend/model_management/model_search.py b/invokeai/backend/model_management_OLD/model_search.py
similarity index 100%
rename from invokeai/backend/model_management/model_search.py
rename to invokeai/backend/model_management_OLD/model_search.py
diff --git a/invokeai/backend/model_management/models/__init__.py b/invokeai/backend/model_management_OLD/models/__init__.py
similarity index 100%
rename from invokeai/backend/model_management/models/__init__.py
rename to invokeai/backend/model_management_OLD/models/__init__.py
diff --git a/invokeai/backend/model_management/models/base.py b/invokeai/backend/model_management_OLD/models/base.py
similarity index 100%
rename from invokeai/backend/model_management/models/base.py
rename to invokeai/backend/model_management_OLD/models/base.py
diff --git a/invokeai/backend/model_management/models/clip_vision.py b/invokeai/backend/model_management_OLD/models/clip_vision.py
similarity index 100%
rename from invokeai/backend/model_management/models/clip_vision.py
rename to invokeai/backend/model_management_OLD/models/clip_vision.py
diff --git a/invokeai/backend/model_management/models/controlnet.py b/invokeai/backend/model_management_OLD/models/controlnet.py
similarity index 100%
rename from invokeai/backend/model_management/models/controlnet.py
rename to invokeai/backend/model_management_OLD/models/controlnet.py
diff --git a/invokeai/backend/model_management/models/ip_adapter.py b/invokeai/backend/model_management_OLD/models/ip_adapter.py
similarity index 100%
rename from invokeai/backend/model_management/models/ip_adapter.py
rename to invokeai/backend/model_management_OLD/models/ip_adapter.py
diff --git a/invokeai/backend/model_management/models/lora.py b/invokeai/backend/model_management_OLD/models/lora.py
similarity index 100%
rename from invokeai/backend/model_management/models/lora.py
rename to invokeai/backend/model_management_OLD/models/lora.py
diff --git a/invokeai/backend/model_management/models/sdxl.py b/invokeai/backend/model_management_OLD/models/sdxl.py
similarity index 100%
rename from invokeai/backend/model_management/models/sdxl.py
rename to invokeai/backend/model_management_OLD/models/sdxl.py
diff --git a/invokeai/backend/model_management/models/stable_diffusion.py b/invokeai/backend/model_management_OLD/models/stable_diffusion.py
similarity index 100%
rename from invokeai/backend/model_management/models/stable_diffusion.py
rename to invokeai/backend/model_management_OLD/models/stable_diffusion.py
diff --git a/invokeai/backend/model_management/models/stable_diffusion_onnx.py b/invokeai/backend/model_management_OLD/models/stable_diffusion_onnx.py
similarity index 100%
rename from invokeai/backend/model_management/models/stable_diffusion_onnx.py
rename to invokeai/backend/model_management_OLD/models/stable_diffusion_onnx.py
diff --git a/invokeai/backend/model_management/models/t2i_adapter.py b/invokeai/backend/model_management_OLD/models/t2i_adapter.py
similarity index 100%
rename from invokeai/backend/model_management/models/t2i_adapter.py
rename to invokeai/backend/model_management_OLD/models/t2i_adapter.py
diff --git a/invokeai/backend/model_management/models/textual_inversion.py b/invokeai/backend/model_management_OLD/models/textual_inversion.py
similarity index 100%
rename from invokeai/backend/model_management/models/textual_inversion.py
rename to invokeai/backend/model_management_OLD/models/textual_inversion.py
diff --git a/invokeai/backend/model_management/models/vae.py b/invokeai/backend/model_management_OLD/models/vae.py
similarity index 100%
rename from invokeai/backend/model_management/models/vae.py
rename to invokeai/backend/model_management_OLD/models/vae.py
diff --git a/invokeai/backend/model_management/seamless.py b/invokeai/backend/model_management_OLD/seamless.py
similarity index 100%
rename from invokeai/backend/model_management/seamless.py
rename to invokeai/backend/model_management_OLD/seamless.py
diff --git a/invokeai/backend/model_management/util.py b/invokeai/backend/model_management_OLD/util.py
similarity index 100%
rename from invokeai/backend/model_management/util.py
rename to invokeai/backend/model_management_OLD/util.py
diff --git a/invokeai/backend/model_manager/config.py b/invokeai/backend/model_manager/config.py
index 42921f0b32..bc4848b0a5 100644
--- a/invokeai/backend/model_manager/config.py
+++ b/invokeai/backend/model_manager/config.py
@@ -28,12 +28,11 @@ from diffusers import ModelMixin
 from pydantic import BaseModel, ConfigDict, Field, TypeAdapter
 from typing_extensions import Annotated, Any, Dict
 
-from invokeai.backend.onnx.onnx_runtime import IAIOnnxRuntimeModel
+from ..raw_model import RawModel
 
-from ..embeddings.embedding_base import EmbeddingModelRaw
-from ..ip_adapter.ip_adapter import IPAdapter, IPAdapterPlus
-
-AnyModel = Union[ModelMixin, torch.nn.Module, IAIOnnxRuntimeModel, IPAdapter, IPAdapterPlus, EmbeddingModelRaw]
+# ModelMixin is the base class for all diffusers and transformers models
+# RawModel is the InvokeAI wrapper class for ip_adapters, loras, textual_inversion and onnx runtime
+AnyModel = Union[ModelMixin, RawModel, torch.nn.Module]
 
 
 class InvalidModelConfigException(Exception):
diff --git a/invokeai/backend/model_management/libc_util.py b/invokeai/backend/model_manager/libc_util.py
similarity index 100%
rename from invokeai/backend/model_management/libc_util.py
rename to invokeai/backend/model_manager/libc_util.py
diff --git a/invokeai/backend/model_manager/load/memory_snapshot.py b/invokeai/backend/model_manager/load/memory_snapshot.py
index 346f5dc424..209d7166f3 100644
--- a/invokeai/backend/model_manager/load/memory_snapshot.py
+++ b/invokeai/backend/model_manager/load/memory_snapshot.py
@@ -5,7 +5,7 @@ import psutil
 import torch
 from typing_extensions import Self
 
-from invokeai.backend.model_management.libc_util import LibcUtil, Struct_mallinfo2
+from ..util.libc_util import LibcUtil, Struct_mallinfo2
 
 GB = 2**30  # 1 GB
 
@@ -97,4 +97,4 @@ def get_pretty_snapshot_diff(snapshot_1: Optional[MemorySnapshot], snapshot_2: O
     if snapshot_1.vram is not None and snapshot_2.vram is not None:
         msg += get_msg_line("VRAM", snapshot_1.vram, snapshot_2.vram)
 
-    return "\n" + msg if len(msg) > 0 else msg
+    return msg
diff --git a/invokeai/backend/model_manager/load/model_loaders/lora.py b/invokeai/backend/model_manager/load/model_loaders/lora.py
index d8e5f920e2..6ff2dcc918 100644
--- a/invokeai/backend/model_manager/load/model_loaders/lora.py
+++ b/invokeai/backend/model_manager/load/model_loaders/lora.py
@@ -7,7 +7,7 @@ from pathlib import Path
 from typing import Optional, Tuple
 
 from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.backend.embeddings.lora import LoRAModelRaw
+from invokeai.backend.lora import LoRAModelRaw
 from invokeai.backend.model_manager import (
     AnyModel,
     AnyModelConfig,
diff --git a/invokeai/backend/model_manager/load/model_loaders/textual_inversion.py b/invokeai/backend/model_manager/load/model_loaders/textual_inversion.py
index 6635f6b43f..9476747960 100644
--- a/invokeai/backend/model_manager/load/model_loaders/textual_inversion.py
+++ b/invokeai/backend/model_manager/load/model_loaders/textual_inversion.py
@@ -5,7 +5,7 @@
 from pathlib import Path
 from typing import Optional, Tuple
 
-from invokeai.backend.embeddings.textual_inversion import TextualInversionModelRaw
+from invokeai.backend.textual_inversion import TextualInversionModelRaw
 from invokeai.backend.model_manager import (
     AnyModel,
     AnyModelConfig,
diff --git a/invokeai/backend/model_manager/probe.py b/invokeai/backend/model_manager/probe.py
index 2c2066d7c5..d511ffa875 100644
--- a/invokeai/backend/model_manager/probe.py
+++ b/invokeai/backend/model_manager/probe.py
@@ -8,9 +8,7 @@ import torch
 from picklescan.scanner import scan_file_path
 
 import invokeai.backend.util.logging as logger
-from invokeai.backend.model_management.models.base import read_checkpoint_meta
-from invokeai.backend.model_management.models.ip_adapter import IPAdapterModelFormat
-from invokeai.backend.model_management.util import lora_token_vector_length
+from .util.model_util import lora_token_vector_length, read_checkpoint_meta
 from invokeai.backend.util.util import SilenceWarnings
 
 from .config import (
@@ -55,7 +53,6 @@ LEGACY_CONFIGS: Dict[BaseModelType, Dict[ModelVariantType, Union[str, Dict[Sched
     },
 }
 
-
 class ProbeBase(object):
     """Base class for probes."""
 
@@ -653,8 +650,8 @@ class LoRAFolderProbe(FolderProbeBase):
 
 
 class IPAdapterFolderProbe(FolderProbeBase):
-    def get_format(self) -> IPAdapterModelFormat:
-        return IPAdapterModelFormat.InvokeAI.value
+    def get_format(self) -> ModelFormat:
+        return ModelFormat.InvokeAI
 
     def get_base_type(self) -> BaseModelType:
         model_file = self.model_path / "ip_adapter.bin"
diff --git a/invokeai/backend/model_manager/util/libc_util.py b/invokeai/backend/model_manager/util/libc_util.py
new file mode 100644
index 0000000000..1fbcae0a93
--- /dev/null
+++ b/invokeai/backend/model_manager/util/libc_util.py
@@ -0,0 +1,75 @@
+import ctypes
+
+
+class Struct_mallinfo2(ctypes.Structure):
+    """A ctypes Structure that matches the libc mallinfo2 struct.
+
+    Docs:
+    - https://man7.org/linux/man-pages/man3/mallinfo.3.html
+    - https://www.gnu.org/software/libc/manual/html_node/Statistics-of-Malloc.html
+
+    struct mallinfo2 {
+        size_t arena;     /* Non-mmapped space allocated (bytes) */
+        size_t ordblks;   /* Number of free chunks */
+        size_t smblks;    /* Number of free fastbin blocks */
+        size_t hblks;     /* Number of mmapped regions */
+        size_t hblkhd;    /* Space allocated in mmapped regions (bytes) */
+        size_t usmblks;   /* See below */
+        size_t fsmblks;   /* Space in freed fastbin blocks (bytes) */
+        size_t uordblks;  /* Total allocated space (bytes) */
+        size_t fordblks;  /* Total free space (bytes) */
+        size_t keepcost;  /* Top-most, releasable space (bytes) */
+    };
+    """
+
+    _fields_ = [
+        ("arena", ctypes.c_size_t),
+        ("ordblks", ctypes.c_size_t),
+        ("smblks", ctypes.c_size_t),
+        ("hblks", ctypes.c_size_t),
+        ("hblkhd", ctypes.c_size_t),
+        ("usmblks", ctypes.c_size_t),
+        ("fsmblks", ctypes.c_size_t),
+        ("uordblks", ctypes.c_size_t),
+        ("fordblks", ctypes.c_size_t),
+        ("keepcost", ctypes.c_size_t),
+    ]
+
+    def __str__(self):
+        s = ""
+        s += f"{'arena': <10}= {(self.arena/2**30):15.5f}   # Non-mmapped space allocated (GB) (uordblks + fordblks)\n"
+        s += f"{'ordblks': <10}= {(self.ordblks): >15}   # Number of free chunks\n"
+        s += f"{'smblks': <10}= {(self.smblks): >15}   # Number of free fastbin blocks \n"
+        s += f"{'hblks': <10}= {(self.hblks): >15}   # Number of mmapped regions \n"
+        s += f"{'hblkhd': <10}= {(self.hblkhd/2**30):15.5f}   # Space allocated in mmapped regions (GB)\n"
+        s += f"{'usmblks': <10}= {(self.usmblks): >15}   # Unused\n"
+        s += f"{'fsmblks': <10}= {(self.fsmblks/2**30):15.5f}   # Space in freed fastbin blocks (GB)\n"
+        s += (
+            f"{'uordblks': <10}= {(self.uordblks/2**30):15.5f}   # Space used by in-use allocations (non-mmapped)"
+            " (GB)\n"
+        )
+        s += f"{'fordblks': <10}= {(self.fordblks/2**30):15.5f}   # Space in free blocks (non-mmapped) (GB)\n"
+        s += f"{'keepcost': <10}= {(self.keepcost/2**30):15.5f}   # Top-most, releasable space (GB)\n"
+        return s
+
+
+class LibcUtil:
+    """A utility class for interacting with the C Standard Library (`libc`) via ctypes.
+
+    Note that this class will raise on __init__() if 'libc.so.6' can't be found. Take care to handle environments where
+    this shared library is not available.
+
+    TODO: Improve cross-OS compatibility of this class.
+    """
+
+    def __init__(self):
+        self._libc = ctypes.cdll.LoadLibrary("libc.so.6")
+
+    def mallinfo2(self) -> Struct_mallinfo2:
+        """Calls `libc` `mallinfo2`.
+
+        Docs: https://man7.org/linux/man-pages/man3/mallinfo.3.html
+        """
+        mallinfo2 = self._libc.mallinfo2
+        mallinfo2.restype = Struct_mallinfo2
+        return mallinfo2()
diff --git a/invokeai/backend/model_manager/util/model_util.py b/invokeai/backend/model_manager/util/model_util.py
new file mode 100644
index 0000000000..6847a40878
--- /dev/null
+++ b/invokeai/backend/model_manager/util/model_util.py
@@ -0,0 +1,129 @@
+"""Utilities for parsing model files, used mostly by probe.py"""
+
+import json
+import torch
+from typing import Union
+from pathlib import Path
+from picklescan.scanner import scan_file_path
+
+def _fast_safetensors_reader(path: str):
+    checkpoint = {}
+    device = torch.device("meta")
+    with open(path, "rb") as f:
+        definition_len = int.from_bytes(f.read(8), "little")
+        definition_json = f.read(definition_len)
+        definition = json.loads(definition_json)
+
+        if "__metadata__" in definition and definition["__metadata__"].get("format", "pt") not in {
+            "pt",
+            "torch",
+            "pytorch",
+        }:
+            raise Exception("Supported only pytorch safetensors files")
+        definition.pop("__metadata__", None)
+
+        for key, info in definition.items():
+            dtype = {
+                "I8": torch.int8,
+                "I16": torch.int16,
+                "I32": torch.int32,
+                "I64": torch.int64,
+                "F16": torch.float16,
+                "F32": torch.float32,
+                "F64": torch.float64,
+            }[info["dtype"]]
+
+            checkpoint[key] = torch.empty(info["shape"], dtype=dtype, device=device)
+
+    return checkpoint
+
+def read_checkpoint_meta(path: Union[str, Path], scan: bool = False):
+    if str(path).endswith(".safetensors"):
+        try:
+            checkpoint = _fast_safetensors_reader(path)
+        except Exception:
+            # TODO: create issue for support "meta"?
+            checkpoint = safetensors.torch.load_file(path, device="cpu")
+    else:
+        if scan:
+            scan_result = scan_file_path(path)
+            if scan_result.infected_files != 0:
+                raise Exception(f'The model file "{path}" is potentially infected by malware. Aborting import.')
+        checkpoint = torch.load(path, map_location=torch.device("meta"))
+    return checkpoint
+
+def lora_token_vector_length(checkpoint: dict) -> int:
+    """
+    Given a checkpoint in memory, return the lora token vector length
+
+    :param checkpoint: The checkpoint
+    """
+
+    def _get_shape_1(key: str, tensor, checkpoint) -> int:
+        lora_token_vector_length = None
+
+        if "." not in key:
+            return lora_token_vector_length  # wrong key format
+        model_key, lora_key = key.split(".", 1)
+
+        # check lora/locon
+        if lora_key == "lora_down.weight":
+            lora_token_vector_length = tensor.shape[1]
+
+        # check loha (don't worry about hada_t1/hada_t2 as it used only in 4d shapes)
+        elif lora_key in ["hada_w1_b", "hada_w2_b"]:
+            lora_token_vector_length = tensor.shape[1]
+
+        # check lokr (don't worry about lokr_t2 as it used only in 4d shapes)
+        elif "lokr_" in lora_key:
+            if model_key + ".lokr_w1" in checkpoint:
+                _lokr_w1 = checkpoint[model_key + ".lokr_w1"]
+            elif model_key + "lokr_w1_b" in checkpoint:
+                _lokr_w1 = checkpoint[model_key + ".lokr_w1_b"]
+            else:
+                return lora_token_vector_length  # unknown format
+
+            if model_key + ".lokr_w2" in checkpoint:
+                _lokr_w2 = checkpoint[model_key + ".lokr_w2"]
+            elif model_key + "lokr_w2_b" in checkpoint:
+                _lokr_w2 = checkpoint[model_key + ".lokr_w2_b"]
+            else:
+                return lora_token_vector_length  # unknown format
+
+            lora_token_vector_length = _lokr_w1.shape[1] * _lokr_w2.shape[1]
+
+        elif lora_key == "diff":
+            lora_token_vector_length = tensor.shape[1]
+
+        # ia3 can be detected only by shape[0] in text encoder
+        elif lora_key == "weight" and "lora_unet_" not in model_key:
+            lora_token_vector_length = tensor.shape[0]
+
+        return lora_token_vector_length
+
+    lora_token_vector_length = None
+    lora_te1_length = None
+    lora_te2_length = None
+    for key, tensor in checkpoint.items():
+        if key.startswith("lora_unet_") and ("_attn2_to_k." in key or "_attn2_to_v." in key):
+            lora_token_vector_length = _get_shape_1(key, tensor, checkpoint)
+        elif key.startswith("lora_unet_") and (
+            "time_emb_proj.lora_down" in key
+        ):  # recognizes format at https://civitai.com/models/224641
+            lora_token_vector_length = _get_shape_1(key, tensor, checkpoint)
+        elif key.startswith("lora_te") and "_self_attn_" in key:
+            tmp_length = _get_shape_1(key, tensor, checkpoint)
+            if key.startswith("lora_te_"):
+                lora_token_vector_length = tmp_length
+            elif key.startswith("lora_te1_"):
+                lora_te1_length = tmp_length
+            elif key.startswith("lora_te2_"):
+                lora_te2_length = tmp_length
+
+        if lora_te1_length is not None and lora_te2_length is not None:
+            lora_token_vector_length = lora_te1_length + lora_te2_length
+
+        if lora_token_vector_length is not None:
+            break
+
+    return lora_token_vector_length
diff --git a/invokeai/backend/embeddings/model_patcher.py b/invokeai/backend/model_patcher.py
similarity index 100%
rename from invokeai/backend/embeddings/model_patcher.py
rename to invokeai/backend/model_patcher.py
diff --git a/invokeai/backend/onnx/onnx_runtime.py b/invokeai/backend/onnx/onnx_runtime.py
index f79fa01569..9b2096abdf 100644
--- a/invokeai/backend/onnx/onnx_runtime.py
+++ b/invokeai/backend/onnx/onnx_runtime.py
@@ -8,6 +8,7 @@ import numpy as np
 import onnx
 from onnx import numpy_helper
 from onnxruntime import InferenceSession, SessionOptions, get_available_providers
+from ..raw_model import RawModel
 
 ONNX_WEIGHTS_NAME = "model.onnx"
 
diff --git a/invokeai/backend/raw_model.py b/invokeai/backend/raw_model.py
new file mode 100644
index 0000000000..2e224d538b
--- /dev/null
+++ b/invokeai/backend/raw_model.py
@@ -0,0 +1,14 @@
+"""Base class for 'Raw' models.
+
+The RawModel class is the base class of LoRAModelRaw and TextualInversionModelRaw,
+and is used for type checking of calls to the model patcher. Its main purpose
+is to avoid a circular import issues when lora.py tries to import BaseModelType
+from invokeai.backend.model_manager.config, and the latter tries to import LoRAModelRaw
+from lora.py.
+
+The term 'raw' was introduced to describe a wrapper around a torch.nn.Module
+that adds additional methods and attributes.
+"""
+
+class RawModel:
+    """Base class for 'Raw' model wrappers."""
diff --git a/invokeai/backend/embeddings/textual_inversion.py b/invokeai/backend/textual_inversion.py
similarity index 97%
rename from invokeai/backend/embeddings/textual_inversion.py
rename to invokeai/backend/textual_inversion.py
index 389edff039..9a4fa0b540 100644
--- a/invokeai/backend/embeddings/textual_inversion.py
+++ b/invokeai/backend/textual_inversion.py
@@ -8,11 +8,9 @@ from compel.embeddings_provider import BaseTextualInversionManager
 from safetensors.torch import load_file
 from transformers import CLIPTokenizer
 from typing_extensions import Self
+from .raw_model import RawModel
 
-from .embedding_base import EmbeddingModelRaw
-
-
-class TextualInversionModelRaw(EmbeddingModelRaw):
+class TextualInversionModelRaw(RawModel):
     embedding: torch.Tensor  # [n, 768]|[n, 1280]
     embedding_2: Optional[torch.Tensor] = None  # [n, 768]|[n, 1280]   - for SDXL models
 
diff --git a/invokeai/backend/util/test_utils.py b/invokeai/backend/util/test_utils.py
index 685603cedc..a3def182c8 100644
--- a/invokeai/backend/util/test_utils.py
+++ b/invokeai/backend/util/test_utils.py
@@ -5,10 +5,9 @@ from typing import Optional, Union
 import pytest
 import torch
 
-from invokeai.app.services.config.config_default import InvokeAIAppConfig
-from invokeai.backend.install.model_install_backend import ModelInstall
-from invokeai.backend.model_management.model_manager import LoadedModelInfo
-from invokeai.backend.model_management.models.base import BaseModelType, ModelNotFoundException, ModelType, SubModelType
+from invokeai.app.services.model_manager import ModelManagerServiceBase
+from invokeai.app.services.model_records import UnknownModelException
+from invokeai.backend.model_manager import BaseModelType, LoadedModel, ModelType, SubModelType
 
 
 @pytest.fixture(scope="session")
@@ -16,31 +15,20 @@ def torch_device():
     return "cuda" if torch.cuda.is_available() else "cpu"
 
 
-@pytest.fixture(scope="module")
-def model_installer():
-    """A global ModelInstall pytest fixture to be used by many tests."""
-    # HACK(ryand): InvokeAIAppConfig.get_config() returns a singleton config object. This can lead to weird interactions
-    # between tests that need to alter the config. For example, some tests change the 'root' directory in the config,
-    # which can cause `install_and_load_model(...)` to re-download the model unnecessarily. As a temporary workaround,
-    # we pass a kwarg to get_config, which causes the config to be re-loaded. To fix this properly, we should stop using
-    # a singleton.
-    return ModelInstall(InvokeAIAppConfig.get_config(log_level="info"))
-
-
 def install_and_load_model(
-    model_installer: ModelInstall,
+    model_manager: ModelManagerServiceBase,
     model_path_id_or_url: Union[str, Path],
     model_name: str,
     base_model: BaseModelType,
     model_type: ModelType,
     submodel_type: Optional[SubModelType] = None,
-) -> LoadedModelInfo:
-    """Install a model if it is not already installed, then get the LoadedModelInfo for that model.
+) -> LoadedModel:
+    """Install a model if it is not already installed, then get the LoadedModel for that model.
 
     This is intended as a utility function for tests.
 
     Args:
-        model_installer (ModelInstall): The model installer.
+        mm2_model_manager (ModelManagerServiceBase): The model manager
         model_path_id_or_url (Union[str, Path]): The path, HF ID, URL, etc. where the model can be installed from if it
             is not already installed.
         model_name (str): The model name, forwarded to ModelManager.get_model(...).
@@ -51,16 +39,23 @@ def install_and_load_model(
     Returns:
         LoadedModelInfo
     """
-    # If the requested model is already installed, return its LoadedModelInfo.
-    with contextlib.suppress(ModelNotFoundException):
-        return model_installer.mgr.get_model(model_name, base_model, model_type, submodel_type)
+    # If the requested model is already installed, return its LoadedModel
+    with contextlib.suppress(UnknownModelException):
+        # TODO: Replace with wrapper call
+        loaded_model: LoadedModel = model_manager.load.load_model_by_attr(
+            model_name=model_name, base_model=base_model, model_type=model_type
+        )
+        return loaded_model
 
     # Install the requested model.
-    model_installer.heuristic_import(model_path_id_or_url)
+    job = model_manager.install.heuristic_import(model_path_id_or_url)
+    model_manager.install.wait_for_job(job, timeout=10)
+    assert job.complete
 
     try:
-        return model_installer.mgr.get_model(model_name, base_model, model_type, submodel_type)
-    except ModelNotFoundException as e:
+        loaded_model = model_manager.load.load_model_by_config(job.config_out)
+        return loaded_model
+    except UnknownModelException as e:
         raise Exception(
             "Failed to get model info after installing it. There could be a mismatch between the requested model and"
             f" the installation id ('{model_path_id_or_url}'). Error: {e}"
diff --git a/invokeai/configs/INITIAL_MODELS.yaml.OLD b/invokeai/configs/INITIAL_MODELS.yaml.OLD
deleted file mode 100644
index c230665e3a..0000000000
--- a/invokeai/configs/INITIAL_MODELS.yaml.OLD
+++ /dev/null
@@ -1,153 +0,0 @@
-# This file predefines a few models that the user may want to install.
-sd-1/main/stable-diffusion-v1-5:
-   description: Stable Diffusion version 1.5 diffusers model (4.27 GB)
-   repo_id: runwayml/stable-diffusion-v1-5
-   recommended: True
-   default: True
-sd-1/main/stable-diffusion-v1-5-inpainting:
-   description: RunwayML SD 1.5 model optimized for inpainting, diffusers version (4.27 GB)
-   repo_id: runwayml/stable-diffusion-inpainting
-   recommended: True
-sd-2/main/stable-diffusion-2-1:
-   description: Stable Diffusion version 2.1 diffusers model, trained on 768 pixel images (5.21 GB)
-   repo_id: stabilityai/stable-diffusion-2-1
-   recommended: False
-sd-2/main/stable-diffusion-2-inpainting:
-   description: Stable Diffusion version 2.0 inpainting model (5.21 GB)
-   repo_id: stabilityai/stable-diffusion-2-inpainting
-   recommended: False
-sdxl/main/stable-diffusion-xl-base-1-0:
-   description: Stable Diffusion XL base model (12 GB)
-   repo_id: stabilityai/stable-diffusion-xl-base-1.0
-   recommended: True
-sdxl-refiner/main/stable-diffusion-xl-refiner-1-0:
-   description: Stable Diffusion XL refiner model (12 GB)
-   repo_id: stabilityai/stable-diffusion-xl-refiner-1.0
-   recommended: False
-sdxl/vae/sdxl-1-0-vae-fix:
-   description: Fine tuned version of the SDXL-1.0 VAE
-   repo_id: madebyollin/sdxl-vae-fp16-fix
-   recommended: True
-sd-1/main/Analog-Diffusion:
-   description: An SD-1.5 model trained on diverse analog photographs (2.13 GB)
-   repo_id: wavymulder/Analog-Diffusion
-   recommended: False
-sd-1/main/Deliberate_v5:
-   description: Versatile model that produces detailed images up to 768px (4.27 GB)
-   path: https://huggingface.co/XpucT/Deliberate/resolve/main/Deliberate_v5.safetensors
-   recommended: False
-sd-1/main/Dungeons-and-Diffusion:
-   description: Dungeons & Dragons characters (2.13 GB)
-   repo_id: 0xJustin/Dungeons-and-Diffusion
-   recommended: False
-sd-1/main/dreamlike-photoreal-2:
-   description: A photorealistic model trained on 768 pixel images based on SD 1.5 (2.13 GB)
-   repo_id: dreamlike-art/dreamlike-photoreal-2.0
-   recommended: False
-sd-1/main/Inkpunk-Diffusion:
-   description: Stylized illustrations inspired by Gorillaz, FLCL and Shinkawa; prompt with "nvinkpunk" (4.27 GB)
-   repo_id: Envvi/Inkpunk-Diffusion
-   recommended: False
-sd-1/main/openjourney:
-   description: An SD 1.5 model fine tuned on Midjourney; prompt with "mdjrny-v4 style" (2.13 GB)
-   repo_id: prompthero/openjourney
-   recommended: False
-sd-1/main/seek.art_MEGA:
-   repo_id: coreco/seek.art_MEGA
-   description: A general use SD-1.5 "anything" model that supports multiple styles (2.1 GB)
-   recommended: False
-sd-1/main/trinart_stable_diffusion_v2:
-   description: An SD-1.5 model finetuned with ~40K assorted high resolution manga/anime-style images (2.13 GB)
-   repo_id: naclbit/trinart_stable_diffusion_v2
-   recommended: False
-sd-1/controlnet/qrcode_monster:
-   repo_id: monster-labs/control_v1p_sd15_qrcode_monster
-   subfolder: v2
-sd-1/controlnet/canny:
-   repo_id: lllyasviel/control_v11p_sd15_canny
-   recommended: True
-sd-1/controlnet/inpaint:
-   repo_id: lllyasviel/control_v11p_sd15_inpaint
-sd-1/controlnet/mlsd:
-   repo_id: lllyasviel/control_v11p_sd15_mlsd
-sd-1/controlnet/depth:
-   repo_id: lllyasviel/control_v11f1p_sd15_depth
-   recommended: True
-sd-1/controlnet/normal_bae:
-   repo_id: lllyasviel/control_v11p_sd15_normalbae
-sd-1/controlnet/seg:
-   repo_id: lllyasviel/control_v11p_sd15_seg
-sd-1/controlnet/lineart:
-   repo_id: lllyasviel/control_v11p_sd15_lineart
-   recommended: True
-sd-1/controlnet/lineart_anime:
-   repo_id: lllyasviel/control_v11p_sd15s2_lineart_anime
-sd-1/controlnet/openpose:
-   repo_id: lllyasviel/control_v11p_sd15_openpose
-   recommended: True
-sd-1/controlnet/scribble:
-   repo_id: lllyasviel/control_v11p_sd15_scribble
-   recommended: False
-sd-1/controlnet/softedge:
-   repo_id: lllyasviel/control_v11p_sd15_softedge
-sd-1/controlnet/shuffle:
-   repo_id: lllyasviel/control_v11e_sd15_shuffle
-sd-1/controlnet/tile:
-   repo_id: lllyasviel/control_v11f1e_sd15_tile
-sd-1/controlnet/ip2p:
-   repo_id: lllyasviel/control_v11e_sd15_ip2p
-sd-1/t2i_adapter/canny-sd15:
-   repo_id: TencentARC/t2iadapter_canny_sd15v2
-sd-1/t2i_adapter/sketch-sd15:
-   repo_id: TencentARC/t2iadapter_sketch_sd15v2
-sd-1/t2i_adapter/depth-sd15:
-   repo_id: TencentARC/t2iadapter_depth_sd15v2
-sd-1/t2i_adapter/zoedepth-sd15:
-   repo_id: TencentARC/t2iadapter_zoedepth_sd15v1
-sdxl/t2i_adapter/canny-sdxl:
-   repo_id: TencentARC/t2i-adapter-canny-sdxl-1.0
-sdxl/t2i_adapter/zoedepth-sdxl:
-   repo_id: TencentARC/t2i-adapter-depth-zoe-sdxl-1.0
-sdxl/t2i_adapter/lineart-sdxl:
-   repo_id: TencentARC/t2i-adapter-lineart-sdxl-1.0
-sdxl/t2i_adapter/sketch-sdxl:
-   repo_id: TencentARC/t2i-adapter-sketch-sdxl-1.0
-sd-1/embedding/EasyNegative:
-   path: https://huggingface.co/embed/EasyNegative/resolve/main/EasyNegative.safetensors
-   recommended: True
-sd-1/embedding/ahx-beta-453407d:
-   repo_id: sd-concepts-library/ahx-beta-453407d
-sd-1/lora/Ink scenery:
-   path: https://civitai.com/api/download/models/83390
-sd-1/ip_adapter/ip_adapter_sd15:
-   repo_id: InvokeAI/ip_adapter_sd15
-   recommended: True
-   requires:
-      - InvokeAI/ip_adapter_sd_image_encoder
-   description: IP-Adapter for SD 1.5 models
-sd-1/ip_adapter/ip_adapter_plus_sd15:
-   repo_id: InvokeAI/ip_adapter_plus_sd15
-   recommended: False
-   requires:
-      - InvokeAI/ip_adapter_sd_image_encoder
-   description: Refined IP-Adapter for SD 1.5 models
-sd-1/ip_adapter/ip_adapter_plus_face_sd15:
-   repo_id: InvokeAI/ip_adapter_plus_face_sd15
-   recommended: False
-   requires:
-      - InvokeAI/ip_adapter_sd_image_encoder
-   description: Refined IP-Adapter for SD 1.5 models, adapted for faces
-sdxl/ip_adapter/ip_adapter_sdxl:
-   repo_id: InvokeAI/ip_adapter_sdxl
-   recommended: False
-   requires:
-      - InvokeAI/ip_adapter_sdxl_image_encoder
-   description: IP-Adapter for SDXL models
-any/clip_vision/ip_adapter_sd_image_encoder:
-   repo_id: InvokeAI/ip_adapter_sd_image_encoder
-   recommended: False
-   description: Required model for using IP-Adapters with SD-1/2 models
-any/clip_vision/ip_adapter_sdxl_image_encoder:
-   repo_id: InvokeAI/ip_adapter_sdxl_image_encoder
-   recommended: False
-   description: Required model for using IP-Adapters with SDXL models
diff --git a/invokeai/configs/models.yaml.example b/invokeai/configs/models.yaml.example
deleted file mode 100644
index 98f8f77e62..0000000000
--- a/invokeai/configs/models.yaml.example
+++ /dev/null
@@ -1,47 +0,0 @@
-# This file describes the alternative machine learning models
-# available to InvokeAI script.
-#
-# To add a new model, follow the examples below. Each
-# model requires a model config file, a weights file,
-# and the width and height of the images it
-# was trained on.
-diffusers-1.4:
-  description: 🤗🧨 Stable Diffusion v1.4
-  format: diffusers
-  repo_id: CompVis/stable-diffusion-v1-4
-diffusers-1.5:
-  description: 🤗🧨 Stable Diffusion v1.5
-  format: diffusers
-  repo_id: runwayml/stable-diffusion-v1-5
-  default: true
-diffusers-1.5+mse:
-  description: 🤗🧨 Stable Diffusion v1.5 + MSE-finetuned VAE
-  format: diffusers
-  repo_id: runwayml/stable-diffusion-v1-5
-  vae:
-    repo_id: stabilityai/sd-vae-ft-mse
-diffusers-inpainting-1.5:
-  description: 🤗🧨 inpainting for Stable Diffusion v1.5
-  format: diffusers
-  repo_id: runwayml/stable-diffusion-inpainting
-stable-diffusion-1.5:
-  description: The newest Stable Diffusion version 1.5 weight file (4.27 GB)
-  weights: models/ldm/stable-diffusion-v1/v1-5-pruned-emaonly.ckpt
-  config: configs/stable-diffusion/v1-inference.yaml
-  width: 512
-  height: 512
-  vae: ./models/ldm/stable-diffusion-v1/vae-ft-mse-840000-ema-pruned.ckpt
-stable-diffusion-1.4:
-  description: Stable Diffusion inference model version 1.4
-  config: configs/stable-diffusion/v1-inference.yaml
-  weights: models/ldm/stable-diffusion-v1/sd-v1-4.ckpt
-  vae: models/ldm/stable-diffusion-v1/vae-ft-mse-840000-ema-pruned.ckpt
-  width: 512
-  height: 512
-inpainting-1.5:
-  weights: models/ldm/stable-diffusion-v1/sd-v1-5-inpainting.ckpt
-  config: configs/stable-diffusion/v1-inpainting-inference.yaml
-  vae: models/ldm/stable-diffusion-v1/vae-ft-mse-840000-ema-pruned.ckpt
-  description: RunwayML SD 1.5 model optimized for inpainting
-  width: 512
-  height: 512
diff --git a/invokeai/frontend/install/model_install.py.OLD b/invokeai/frontend/install/model_install.py.OLD
deleted file mode 100644
index e23538ffd6..0000000000
--- a/invokeai/frontend/install/model_install.py.OLD
+++ /dev/null
@@ -1,845 +0,0 @@
-#!/usr/bin/env python
-# Copyright (c) 2022 Lincoln D. Stein (https://github.com/lstein)
-# Before running stable-diffusion on an internet-isolated machine,
-# run this script from one with internet connectivity. The
-# two machines must share a common .cache directory.
-
-"""
-This is the npyscreen frontend to the model installation application.
-The work is actually done in backend code in model_install_backend.py.
-"""
-
-import argparse
-import curses
-import logging
-import sys
-import textwrap
-import traceback
-from argparse import Namespace
-from multiprocessing import Process
-from multiprocessing.connection import Connection, Pipe
-from pathlib import Path
-from shutil import get_terminal_size
-from typing import Optional
-
-import npyscreen
-import torch
-from npyscreen import widget
-
-from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.backend.install.model_install_backend import InstallSelections, ModelInstall, SchedulerPredictionType
-from invokeai.backend.model_management import ModelManager, ModelType
-from invokeai.backend.util import choose_precision, choose_torch_device
-from invokeai.backend.util.logging import InvokeAILogger
-from invokeai.frontend.install.widgets import (
-    MIN_COLS,
-    MIN_LINES,
-    BufferBox,
-    CenteredTitleText,
-    CyclingForm,
-    MultiSelectColumns,
-    SingleSelectColumns,
-    TextBox,
-    WindowTooSmallException,
-    select_stable_diffusion_config_file,
-    set_min_terminal_size,
-)
-
-config = InvokeAIAppConfig.get_config()
-logger = InvokeAILogger.get_logger()
-
-# build a table mapping all non-printable characters to None
-# for stripping control characters
-# from https://stackoverflow.com/questions/92438/stripping-non-printable-characters-from-a-string-in-python
-NOPRINT_TRANS_TABLE = {i: None for i in range(0, sys.maxunicode + 1) if not chr(i).isprintable()}
-
-# maximum number of installed models we can display before overflowing vertically
-MAX_OTHER_MODELS = 72
-
-
-def make_printable(s: str) -> str:
-    """Replace non-printable characters in a string"""
-    return s.translate(NOPRINT_TRANS_TABLE)
-
-
-class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
-    # for responsive resizing set to False, but this seems to cause a crash!
-    FIX_MINIMUM_SIZE_WHEN_CREATED = True
-
-    # for persistence
-    current_tab = 0
-
-    def __init__(self, parentApp, name, multipage=False, *args, **keywords):
-        self.multipage = multipage
-        self.subprocess = None
-        super().__init__(parentApp=parentApp, name=name, *args, **keywords)  # noqa: B026 # TODO: maybe this is bad?
-
-    def create(self):
-        self.keypress_timeout = 10
-        self.counter = 0
-        self.subprocess_connection = None
-
-        if not config.model_conf_path.exists():
-            with open(config.model_conf_path, "w") as file:
-                print("# InvokeAI model configuration file", file=file)
-        self.installer = ModelInstall(config)
-        self.all_models = self.installer.all_models()
-        self.starter_models = self.installer.starter_models()
-        self.model_labels = self._get_model_labels()
-        window_width, window_height = get_terminal_size()
-
-        self.nextrely -= 1
-        self.add_widget_intelligent(
-            npyscreen.FixedText,
-            value="Use ctrl-N and ctrl-P to move to the <N>ext and <P>revious fields. Cursor keys navigate, and <space> selects.",
-            editable=False,
-            color="CAUTION",
-        )
-        self.nextrely += 1
-        self.tabs = self.add_widget_intelligent(
-            SingleSelectColumns,
-            values=[
-                "STARTERS",
-                "MAINS",
-                "CONTROLNETS",
-                "T2I-ADAPTERS",
-                "IP-ADAPTERS",
-                "LORAS",
-                "TI EMBEDDINGS",
-            ],
-            value=[self.current_tab],
-            columns=7,
-            max_height=2,
-            relx=8,
-            scroll_exit=True,
-        )
-        self.tabs.on_changed = self._toggle_tables
-
-        top_of_table = self.nextrely
-        self.starter_pipelines = self.add_starter_pipelines()
-        bottom_of_table = self.nextrely
-
-        self.nextrely = top_of_table
-        self.pipeline_models = self.add_pipeline_widgets(
-            model_type=ModelType.Main, window_width=window_width, exclude=self.starter_models
-        )
-        # self.pipeline_models['autoload_pending'] = True
-        bottom_of_table = max(bottom_of_table, self.nextrely)
-
-        self.nextrely = top_of_table
-        self.controlnet_models = self.add_model_widgets(
-            model_type=ModelType.ControlNet,
-            window_width=window_width,
-        )
-        bottom_of_table = max(bottom_of_table, self.nextrely)
-
-        self.nextrely = top_of_table
-        self.t2i_models = self.add_model_widgets(
-            model_type=ModelType.T2IAdapter,
-            window_width=window_width,
-        )
-        bottom_of_table = max(bottom_of_table, self.nextrely)
-        self.nextrely = top_of_table
-        self.ipadapter_models = self.add_model_widgets(
-            model_type=ModelType.IPAdapter,
-            window_width=window_width,
-        )
-        bottom_of_table = max(bottom_of_table, self.nextrely)
-
-        self.nextrely = top_of_table
-        self.lora_models = self.add_model_widgets(
-            model_type=ModelType.Lora,
-            window_width=window_width,
-        )
-        bottom_of_table = max(bottom_of_table, self.nextrely)
-
-        self.nextrely = top_of_table
-        self.ti_models = self.add_model_widgets(
-            model_type=ModelType.TextualInversion,
-            window_width=window_width,
-        )
-        bottom_of_table = max(bottom_of_table, self.nextrely)
-
-        self.nextrely = bottom_of_table + 1
-
-        self.monitor = self.add_widget_intelligent(
-            BufferBox,
-            name="Log Messages",
-            editable=False,
-            max_height=6,
-        )
-
-        self.nextrely += 1
-        done_label = "APPLY CHANGES"
-        back_label = "BACK"
-        cancel_label = "CANCEL"
-        current_position = self.nextrely
-        if self.multipage:
-            self.back_button = self.add_widget_intelligent(
-                npyscreen.ButtonPress,
-                name=back_label,
-                when_pressed_function=self.on_back,
-            )
-        else:
-            self.nextrely = current_position
-            self.cancel_button = self.add_widget_intelligent(
-                npyscreen.ButtonPress, name=cancel_label, when_pressed_function=self.on_cancel
-            )
-            self.nextrely = current_position
-            self.ok_button = self.add_widget_intelligent(
-                npyscreen.ButtonPress,
-                name=done_label,
-                relx=(window_width - len(done_label)) // 2,
-                when_pressed_function=self.on_execute,
-            )
-
-        label = "APPLY CHANGES & EXIT"
-        self.nextrely = current_position
-        self.done = self.add_widget_intelligent(
-            npyscreen.ButtonPress,
-            name=label,
-            relx=window_width - len(label) - 15,
-            when_pressed_function=self.on_done,
-        )
-
-        # This restores the selected page on return from an installation
-        for _i in range(1, self.current_tab + 1):
-            self.tabs.h_cursor_line_down(1)
-        self._toggle_tables([self.current_tab])
-
-    ############# diffusers tab ##########
-    def add_starter_pipelines(self) -> dict[str, npyscreen.widget]:
-        """Add widgets responsible for selecting diffusers models"""
-        widgets = {}
-        models = self.all_models
-        starters = self.starter_models
-        starter_model_labels = self.model_labels
-
-        self.installed_models = sorted([x for x in starters if models[x].installed])
-
-        widgets.update(
-            label1=self.add_widget_intelligent(
-                CenteredTitleText,
-                name="Select from a starter set of Stable Diffusion models from HuggingFace.",
-                editable=False,
-                labelColor="CAUTION",
-            )
-        )
-
-        self.nextrely -= 1
-        # if user has already installed some initial models, then don't patronize them
-        # by showing more recommendations
-        show_recommended = len(self.installed_models) == 0
-        keys = [x for x in models.keys() if x in starters]
-        widgets.update(
-            models_selected=self.add_widget_intelligent(
-                MultiSelectColumns,
-                columns=1,
-                name="Install Starter Models",
-                values=[starter_model_labels[x] for x in keys],
-                value=[
-                    keys.index(x)
-                    for x in keys
-                    if (show_recommended and models[x].recommended) or (x in self.installed_models)
-                ],
-                max_height=len(starters) + 1,
-                relx=4,
-                scroll_exit=True,
-            ),
-            models=keys,
-        )
-
-        self.nextrely += 1
-        return widgets
-
-    ############# Add a set of model install widgets ########
-    def add_model_widgets(
-        self,
-        model_type: ModelType,
-        window_width: int = 120,
-        install_prompt: str = None,
-        exclude: set = None,
-    ) -> dict[str, npyscreen.widget]:
-        """Generic code to create model selection widgets"""
-        if exclude is None:
-            exclude = set()
-        widgets = {}
-        model_list = [x for x in self.all_models if self.all_models[x].model_type == model_type and x not in exclude]
-        model_labels = [self.model_labels[x] for x in model_list]
-
-        show_recommended = len(self.installed_models) == 0
-        truncated = False
-        if len(model_list) > 0:
-            max_width = max([len(x) for x in model_labels])
-            columns = window_width // (max_width + 8)  # 8 characters for "[x] " and padding
-            columns = min(len(model_list), columns) or 1
-            prompt = (
-                install_prompt
-                or f"Select the desired {model_type.value.title()} models to install. Unchecked models will be purged from disk."
-            )
-
-            widgets.update(
-                label1=self.add_widget_intelligent(
-                    CenteredTitleText,
-                    name=prompt,
-                    editable=False,
-                    labelColor="CAUTION",
-                )
-            )
-
-            if len(model_labels) > MAX_OTHER_MODELS:
-                model_labels = model_labels[0:MAX_OTHER_MODELS]
-                truncated = True
-
-            widgets.update(
-                models_selected=self.add_widget_intelligent(
-                    MultiSelectColumns,
-                    columns=columns,
-                    name=f"Install {model_type} Models",
-                    values=model_labels,
-                    value=[
-                        model_list.index(x)
-                        for x in model_list
-                        if (show_recommended and self.all_models[x].recommended) or self.all_models[x].installed
-                    ],
-                    max_height=len(model_list) // columns + 1,
-                    relx=4,
-                    scroll_exit=True,
-                ),
-                models=model_list,
-            )
-
-        if truncated:
-            widgets.update(
-                warning_message=self.add_widget_intelligent(
-                    npyscreen.FixedText,
-                    value=f"Too many models to display (max={MAX_OTHER_MODELS}). Some are not displayed.",
-                    editable=False,
-                    color="CAUTION",
-                )
-            )
-
-        self.nextrely += 1
-        widgets.update(
-            download_ids=self.add_widget_intelligent(
-                TextBox,
-                name="Additional URLs, or HuggingFace repo_ids to install (Space separated. Use shift-control-V to paste):",
-                max_height=4,
-                scroll_exit=True,
-                editable=True,
-            )
-        )
-        return widgets
-
-    ### Tab for arbitrary diffusers widgets ###
-    def add_pipeline_widgets(
-        self,
-        model_type: ModelType = ModelType.Main,
-        window_width: int = 120,
-        **kwargs,
-    ) -> dict[str, npyscreen.widget]:
-        """Similar to add_model_widgets() but adds some additional widgets at the bottom
-        to support the autoload directory"""
-        widgets = self.add_model_widgets(
-            model_type=model_type,
-            window_width=window_width,
-            install_prompt=f"Installed {model_type.value.title()} models. Unchecked models in the InvokeAI root directory will be deleted. Enter URLs, paths or repo_ids to import.",
-            **kwargs,
-        )
-
-        return widgets
-
-    def resize(self):
-        super().resize()
-        if s := self.starter_pipelines.get("models_selected"):
-            keys = [x for x in self.all_models.keys() if x in self.starter_models]
-            s.values = [self.model_labels[x] for x in keys]
-
-    def _toggle_tables(self, value=None):
-        selected_tab = value[0]
-        widgets = [
-            self.starter_pipelines,
-            self.pipeline_models,
-            self.controlnet_models,
-            self.t2i_models,
-            self.ipadapter_models,
-            self.lora_models,
-            self.ti_models,
-        ]
-
-        for group in widgets:
-            for _k, v in group.items():
-                try:
-                    v.hidden = True
-                    v.editable = False
-                except Exception:
-                    pass
-        for _k, v in widgets[selected_tab].items():
-            try:
-                v.hidden = False
-                if not isinstance(v, (npyscreen.FixedText, npyscreen.TitleFixedText, CenteredTitleText)):
-                    v.editable = True
-            except Exception:
-                pass
-        self.__class__.current_tab = selected_tab  # for persistence
-        self.display()
-
-    def _get_model_labels(self) -> dict[str, str]:
-        window_width, window_height = get_terminal_size()
-        checkbox_width = 4
-        spacing_width = 2
-
-        models = self.all_models
-        label_width = max([len(models[x].name) for x in models])
-        description_width = window_width - label_width - checkbox_width - spacing_width
-
-        result = {}
-        for x in models.keys():
-            description = models[x].description
-            description = (
-                description[0 : description_width - 3] + "..."
-                if description and len(description) > description_width
-                else description
-                if description
-                else ""
-            )
-            result[x] = f"%-{label_width}s %s" % (models[x].name, description)
-        return result
-
-    def _get_columns(self) -> int:
-        window_width, window_height = get_terminal_size()
-        cols = 4 if window_width > 240 else 3 if window_width > 160 else 2 if window_width > 80 else 1
-        return min(cols, len(self.installed_models))
-
-    def confirm_deletions(self, selections: InstallSelections) -> bool:
-        remove_models = selections.remove_models
-        if len(remove_models) > 0:
-            mods = "\n".join([ModelManager.parse_key(x)[0] for x in remove_models])
-            return npyscreen.notify_ok_cancel(
-                f"These unchecked models will be deleted from disk. Continue?\n---------\n{mods}"
-            )
-        else:
-            return True
-
-    def on_execute(self):
-        self.marshall_arguments()
-        app = self.parentApp
-        if not self.confirm_deletions(app.install_selections):
-            return
-
-        self.monitor.entry_widget.buffer(["Processing..."], scroll_end=True)
-        self.ok_button.hidden = True
-        self.display()
-
-        # TO DO: Spawn a worker thread, not a subprocess
-        parent_conn, child_conn = Pipe()
-        p = Process(
-            target=process_and_execute,
-            kwargs={
-                "opt": app.program_opts,
-                "selections": app.install_selections,
-                "conn_out": child_conn,
-            },
-        )
-        p.start()
-        child_conn.close()
-        self.subprocess_connection = parent_conn
-        self.subprocess = p
-        app.install_selections = InstallSelections()
-
-    def on_back(self):
-        self.parentApp.switchFormPrevious()
-        self.editing = False
-
-    def on_cancel(self):
-        self.parentApp.setNextForm(None)
-        self.parentApp.user_cancelled = True
-        self.editing = False
-
-    def on_done(self):
-        self.marshall_arguments()
-        if not self.confirm_deletions(self.parentApp.install_selections):
-            return
-        self.parentApp.setNextForm(None)
-        self.parentApp.user_cancelled = False
-        self.editing = False
-
-    ########## This routine monitors the child process that is performing model installation and removal #####
-    def while_waiting(self):
-        """Called during idle periods. Main task is to update the Log Messages box with messages
-        from the child process that does the actual installation/removal"""
-        c = self.subprocess_connection
-        if not c:
-            return
-
-        monitor_widget = self.monitor.entry_widget
-        while c.poll():
-            try:
-                data = c.recv_bytes().decode("utf-8")
-                data.strip("\n")
-
-                # processing child is requesting user input to select the
-                # right configuration file
-                if data.startswith("*need v2 config"):
-                    _, model_path, *_ = data.split(":", 2)
-                    self._return_v2_config(model_path)
-
-                # processing child is done
-                elif data == "*done*":
-                    self._close_subprocess_and_regenerate_form()
-                    break
-
-                # update the log message box
-                else:
-                    data = make_printable(data)
-                    data = data.replace("[A", "")
-                    monitor_widget.buffer(
-                        textwrap.wrap(
-                            data,
-                            width=monitor_widget.width,
-                            subsequent_indent="   ",
-                        ),
-                        scroll_end=True,
-                    )
-                    self.display()
-            except (EOFError, OSError):
-                self.subprocess_connection = None
-
-    def _return_v2_config(self, model_path: str):
-        c = self.subprocess_connection
-        model_name = Path(model_path).name
-        message = select_stable_diffusion_config_file(model_name=model_name)
-        c.send_bytes(message.encode("utf-8"))
-
-    def _close_subprocess_and_regenerate_form(self):
-        app = self.parentApp
-        self.subprocess_connection.close()
-        self.subprocess_connection = None
-        self.monitor.entry_widget.buffer(["** Action Complete **"])
-        self.display()
-
-        # rebuild the form, saving and restoring some of the fields that need to be preserved.
-        saved_messages = self.monitor.entry_widget.values
-
-        app.main_form = app.addForm(
-            "MAIN",
-            addModelsForm,
-            name="Install Stable Diffusion Models",
-            multipage=self.multipage,
-        )
-        app.switchForm("MAIN")
-
-        app.main_form.monitor.entry_widget.values = saved_messages
-        app.main_form.monitor.entry_widget.buffer([""], scroll_end=True)
-        # app.main_form.pipeline_models['autoload_directory'].value = autoload_dir
-        # app.main_form.pipeline_models['autoscan_on_startup'].value = autoscan
-
-    def marshall_arguments(self):
-        """
-        Assemble arguments and store as attributes of the application:
-        .starter_models: dict of model names to install from INITIAL_CONFIGURE.yaml
-                         True  => Install
-                         False => Remove
-        .scan_directory: Path to a directory of models to scan and import
-        .autoscan_on_startup:  True if invokeai should scan and import at startup time
-        .import_model_paths:   list of URLs, repo_ids and file paths to import
-        """
-        selections = self.parentApp.install_selections
-        all_models = self.all_models
-
-        # Defined models (in INITIAL_CONFIG.yaml or models.yaml) to add/remove
-        ui_sections = [
-            self.starter_pipelines,
-            self.pipeline_models,
-            self.controlnet_models,
-            self.t2i_models,
-            self.ipadapter_models,
-            self.lora_models,
-            self.ti_models,
-        ]
-        for section in ui_sections:
-            if "models_selected" not in section:
-                continue
-            selected = {section["models"][x] for x in section["models_selected"].value}
-            models_to_install = [x for x in selected if not self.all_models[x].installed]
-            models_to_remove = [x for x in section["models"] if x not in selected and self.all_models[x].installed]
-            selections.remove_models.extend(models_to_remove)
-            selections.install_models.extend(
-                all_models[x].path or all_models[x].repo_id
-                for x in models_to_install
-                if all_models[x].path or all_models[x].repo_id
-            )
-
-        # models located in the 'download_ids" section
-        for section in ui_sections:
-            if downloads := section.get("download_ids"):
-                selections.install_models.extend(downloads.value.split())
-
-        # NOT NEEDED - DONE IN BACKEND NOW
-        # # special case for the ipadapter_models. If any of the adapters are
-        # # chosen, then we add the corresponding encoder(s) to the install list.
-        # section = self.ipadapter_models
-        # if section.get("models_selected"):
-        #     selected_adapters = [
-        #         self.all_models[section["models"][x]].name for x in section.get("models_selected").value
-        #     ]
-        #     encoders = []
-        #     if any(["sdxl" in x for x in selected_adapters]):
-        #         encoders.append("ip_adapter_sdxl_image_encoder")
-        #     if any(["sd15" in x for x in selected_adapters]):
-        #         encoders.append("ip_adapter_sd_image_encoder")
-        #     for encoder in encoders:
-        #         key = f"any/clip_vision/{encoder}"
-        #         repo_id = f"InvokeAI/{encoder}"
-        #         if key not in self.all_models:
-        #             selections.install_models.append(repo_id)
-
-
-class AddModelApplication(npyscreen.NPSAppManaged):
-    def __init__(self, opt):
-        super().__init__()
-        self.program_opts = opt
-        self.user_cancelled = False
-        # self.autoload_pending = True
-        self.install_selections = InstallSelections()
-
-    def onStart(self):
-        npyscreen.setTheme(npyscreen.Themes.DefaultTheme)
-        self.main_form = self.addForm(
-            "MAIN",
-            addModelsForm,
-            name="Install Stable Diffusion Models",
-            cycle_widgets=False,
-        )
-
-
-class StderrToMessage:
-    def __init__(self, connection: Connection):
-        self.connection = connection
-
-    def write(self, data: str):
-        self.connection.send_bytes(data.encode("utf-8"))
-
-    def flush(self):
-        pass
-
-
-# --------------------------------------------------------
-def ask_user_for_prediction_type(model_path: Path, tui_conn: Connection = None) -> SchedulerPredictionType:
-    if tui_conn:
-        logger.debug("Waiting for user response...")
-        return _ask_user_for_pt_tui(model_path, tui_conn)
-    else:
-        return _ask_user_for_pt_cmdline(model_path)
-
-
-def _ask_user_for_pt_cmdline(model_path: Path) -> Optional[SchedulerPredictionType]:
-    choices = [SchedulerPredictionType.Epsilon, SchedulerPredictionType.VPrediction, None]
-    print(
-        f"""
-Please select the scheduler prediction type of the checkpoint named {model_path.name}:
-[1] "epsilon" - most v1.5 models and v2 models trained on 512 pixel images
-[2] "vprediction" - v2 models trained on 768 pixel images and a few v1.5 models
-[3] Accept the best guess;  you can fix it in the Web UI later
-"""
-    )
-    choice = None
-    ok = False
-    while not ok:
-        try:
-            choice = input("select [3]> ").strip()
-            if not choice:
-                return None
-            choice = choices[int(choice) - 1]
-            ok = True
-        except (ValueError, IndexError):
-            print(f"{choice} is not a valid choice")
-        except EOFError:
-            return
-    return choice
-
-
-def _ask_user_for_pt_tui(model_path: Path, tui_conn: Connection) -> SchedulerPredictionType:
-    tui_conn.send_bytes(f"*need v2 config for:{model_path}".encode("utf-8"))
-    # note that we don't do any status checking here
-    response = tui_conn.recv_bytes().decode("utf-8")
-    if response is None:
-        return None
-    elif response == "epsilon":
-        return SchedulerPredictionType.epsilon
-    elif response == "v":
-        return SchedulerPredictionType.VPrediction
-    elif response == "guess":
-        return None
-    else:
-        return None
-
-
-# --------------------------------------------------------
-def process_and_execute(
-    opt: Namespace,
-    selections: InstallSelections,
-    conn_out: Connection = None,
-):
-    # need to reinitialize config in subprocess
-    config = InvokeAIAppConfig.get_config()
-    args = ["--root", opt.root] if opt.root else []
-    config.parse_args(args)
-
-    # set up so that stderr is sent to conn_out
-    if conn_out:
-        translator = StderrToMessage(conn_out)
-        sys.stderr = translator
-        sys.stdout = translator
-        logger = InvokeAILogger.get_logger()
-        logger.handlers.clear()
-        logger.addHandler(logging.StreamHandler(translator))
-
-    installer = ModelInstall(config, prediction_type_helper=lambda x: ask_user_for_prediction_type(x, conn_out))
-    installer.install(selections)
-
-    if conn_out:
-        conn_out.send_bytes("*done*".encode("utf-8"))
-        conn_out.close()
-
-
-# --------------------------------------------------------
-def select_and_download_models(opt: Namespace):
-    precision = "float32" if opt.full_precision else choose_precision(torch.device(choose_torch_device()))
-    config.precision = precision
-    installer = ModelInstall(config, prediction_type_helper=ask_user_for_prediction_type)
-    if opt.list_models:
-        installer.list_models(opt.list_models)
-    elif opt.add or opt.delete:
-        selections = InstallSelections(install_models=opt.add or [], remove_models=opt.delete or [])
-        installer.install(selections)
-    elif opt.default_only:
-        selections = InstallSelections(install_models=installer.default_model())
-        installer.install(selections)
-    elif opt.yes_to_all:
-        selections = InstallSelections(install_models=installer.recommended_models())
-        installer.install(selections)
-
-    # this is where the TUI is called
-    else:
-        # needed to support the probe() method running under a subprocess
-        torch.multiprocessing.set_start_method("spawn")
-
-        if not set_min_terminal_size(MIN_COLS, MIN_LINES):
-            raise WindowTooSmallException(
-                "Could not increase terminal size. Try running again with a larger window or smaller font size."
-            )
-
-        installApp = AddModelApplication(opt)
-        try:
-            installApp.run()
-        except KeyboardInterrupt as e:
-            if hasattr(installApp, "main_form"):
-                if installApp.main_form.subprocess and installApp.main_form.subprocess.is_alive():
-                    logger.info("Terminating subprocesses")
-                    installApp.main_form.subprocess.terminate()
-                    installApp.main_form.subprocess = None
-            raise e
-        process_and_execute(opt, installApp.install_selections)
-
-
-# -------------------------------------
-def main():
-    parser = argparse.ArgumentParser(description="InvokeAI model downloader")
-    parser.add_argument(
-        "--add",
-        nargs="*",
-        help="List of URLs, local paths or repo_ids of models to install",
-    )
-    parser.add_argument(
-        "--delete",
-        nargs="*",
-        help="List of names of models to idelete",
-    )
-    parser.add_argument(
-        "--full-precision",
-        dest="full_precision",
-        action=argparse.BooleanOptionalAction,
-        type=bool,
-        default=False,
-        help="use 32-bit weights instead of faster 16-bit weights",
-    )
-    parser.add_argument(
-        "--yes",
-        "-y",
-        dest="yes_to_all",
-        action="store_true",
-        help='answer "yes" to all prompts',
-    )
-    parser.add_argument(
-        "--default_only",
-        action="store_true",
-        help="Only install the default model",
-    )
-    parser.add_argument(
-        "--list-models",
-        choices=[x.value for x in ModelType],
-        help="list installed models",
-    )
-    parser.add_argument(
-        "--config_file",
-        "-c",
-        dest="config_file",
-        type=str,
-        default=None,
-        help="path to configuration file to create",
-    )
-    parser.add_argument(
-        "--root_dir",
-        dest="root",
-        type=str,
-        default=None,
-        help="path to root of install directory",
-    )
-    opt = parser.parse_args()
-
-    invoke_args = []
-    if opt.root:
-        invoke_args.extend(["--root", opt.root])
-    if opt.full_precision:
-        invoke_args.extend(["--precision", "float32"])
-    config.parse_args(invoke_args)
-    logger = InvokeAILogger().get_logger(config=config)
-
-    if not config.model_conf_path.exists():
-        logger.info("Your InvokeAI root directory is not set up. Calling invokeai-configure.")
-        from invokeai.frontend.install.invokeai_configure import invokeai_configure
-
-        invokeai_configure()
-        sys.exit(0)
-
-    try:
-        select_and_download_models(opt)
-    except AssertionError as e:
-        logger.error(e)
-        sys.exit(-1)
-    except KeyboardInterrupt:
-        curses.nocbreak()
-        curses.echo()
-        curses.endwin()
-        logger.info("Goodbye! Come back soon.")
-    except WindowTooSmallException as e:
-        logger.error(str(e))
-    except widget.NotEnoughSpaceForWidget as e:
-        if str(e).startswith("Height of 1 allocated"):
-            logger.error("Insufficient vertical space for the interface. Please make your window taller and try again")
-        input("Press any key to continue...")
-    except Exception as e:
-        if str(e).startswith("addwstr"):
-            logger.error(
-                "Insufficient horizontal space for the interface. Please make your window wider and try again."
-            )
-        else:
-            print(f"An exception has occurred: {str(e)} Details:")
-            print(traceback.format_exc(), file=sys.stderr)
-        input("Press any key to continue...")
-
-
-# -------------------------------------
-if __name__ == "__main__":
-    main()
diff --git a/invokeai/frontend/merge/merge_diffusers.py.OLD b/invokeai/frontend/merge/merge_diffusers.py.OLD
deleted file mode 100644
index b365198f87..0000000000
--- a/invokeai/frontend/merge/merge_diffusers.py.OLD
+++ /dev/null
@@ -1,438 +0,0 @@
-"""
-invokeai.frontend.merge exports a single function called merge_diffusion_models().
-
-It merges 2-3 models together and create a new InvokeAI-registered diffusion model.
-
-Copyright (c) 2023-24 Lincoln Stein and the InvokeAI Development Team
-"""
-import argparse
-import curses
-import re
-import sys
-from argparse import Namespace
-from pathlib import Path
-from typing import List, Optional, Tuple
-
-import npyscreen
-from npyscreen import widget
-
-import invokeai.backend.util.logging as logger
-from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.app.services.model_install import ModelInstallServiceBase
-from invokeai.app.services.model_records import ModelRecordServiceBase
-from invokeai.backend.install.install_helper import initialize_installer
-from invokeai.backend.model_manager import (
-    BaseModelType,
-    ModelFormat,
-    ModelType,
-    ModelVariantType,
-)
-from invokeai.backend.model_manager.merge import ModelMerger
-from invokeai.frontend.install.widgets import FloatTitleSlider, SingleSelectColumns, TextBox
-
-config = InvokeAIAppConfig.get_config()
-
-BASE_TYPES = [
-    (BaseModelType.StableDiffusion1, "Models Built on SD-1.x"),
-    (BaseModelType.StableDiffusion2, "Models Built on SD-2.x"),
-    (BaseModelType.StableDiffusionXL, "Models Built on SDXL"),
-]
-
-
-def _parse_args() -> Namespace:
-    parser = argparse.ArgumentParser(description="InvokeAI model merging")
-    parser.add_argument(
-        "--root_dir",
-        type=Path,
-        default=config.root,
-        help="Path to the invokeai runtime directory",
-    )
-    parser.add_argument(
-        "--front_end",
-        "--gui",
-        dest="front_end",
-        action="store_true",
-        default=False,
-        help="Activate the text-based graphical front end for collecting parameters. Aside from --root_dir, other parameters will be ignored.",
-    )
-    parser.add_argument(
-        "--models",
-        dest="model_names",
-        type=str,
-        nargs="+",
-        help="Two to three model names to be merged",
-    )
-    parser.add_argument(
-        "--base_model",
-        type=str,
-        choices=[x[0].value for x in BASE_TYPES],
-        help="The base model shared by the models to be merged",
-    )
-    parser.add_argument(
-        "--merged_model_name",
-        "--destination",
-        dest="merged_model_name",
-        type=str,
-        help="Name of the output model. If not specified, will be the concatenation of the input model names.",
-    )
-    parser.add_argument(
-        "--alpha",
-        type=float,
-        default=0.5,
-        help="The interpolation parameter, ranging from 0 to 1. It affects the ratio in which the checkpoints are merged. Higher values give more weight to the 2d and 3d models",
-    )
-    parser.add_argument(
-        "--interpolation",
-        dest="interp",
-        type=str,
-        choices=["weighted_sum", "sigmoid", "inv_sigmoid", "add_difference"],
-        default="weighted_sum",
-        help='Interpolation method to use. If three models are present, only "add_difference" will work.',
-    )
-    parser.add_argument(
-        "--force",
-        action="store_true",
-        help="Try to merge models even if they are incompatible with each other",
-    )
-    parser.add_argument(
-        "--clobber",
-        "--overwrite",
-        dest="clobber",
-        action="store_true",
-        help="Overwrite the merged model if --merged_model_name already exists",
-    )
-    return parser.parse_args()
-
-
-# ------------------------- GUI HERE -------------------------
-class mergeModelsForm(npyscreen.FormMultiPageAction):
-    interpolations = ["weighted_sum", "sigmoid", "inv_sigmoid"]
-
-    def __init__(self, parentApp, name):
-        self.parentApp = parentApp
-        self.ALLOW_RESIZE = True
-        self.FIX_MINIMUM_SIZE_WHEN_CREATED = False
-        super().__init__(parentApp, name)
-
-    @property
-    def model_record_store(self) -> ModelRecordServiceBase:
-        installer: ModelInstallServiceBase = self.parentApp.installer
-        return installer.record_store
-
-    def afterEditing(self) -> None:
-        self.parentApp.setNextForm(None)
-
-    def create(self) -> None:
-        window_height, window_width = curses.initscr().getmaxyx()
-        self.current_base = 0
-        self.models = self.get_models(BASE_TYPES[self.current_base][0])
-        self.model_names = [x[1] for x in self.models]
-        max_width = max([len(x) for x in self.model_names])
-        max_width += 6
-        horizontal_layout = max_width * 3 < window_width
-
-        self.add_widget_intelligent(
-            npyscreen.FixedText,
-            color="CONTROL",
-            value="Select two models to merge and optionally a third.",
-            editable=False,
-        )
-        self.add_widget_intelligent(
-            npyscreen.FixedText,
-            color="CONTROL",
-            value="Use up and down arrows to move, <space> to select an item, <tab> and <shift-tab> to move from one field to the next.",
-            editable=False,
-        )
-        self.nextrely += 1
-        self.base_select = self.add_widget_intelligent(
-            SingleSelectColumns,
-            values=[x[1] for x in BASE_TYPES],
-            value=[self.current_base],
-            columns=4,
-            max_height=2,
-            relx=8,
-            scroll_exit=True,
-        )
-        self.base_select.on_changed = self._populate_models
-        self.add_widget_intelligent(
-            npyscreen.FixedText,
-            value="MODEL 1",
-            color="GOOD",
-            editable=False,
-            rely=6 if horizontal_layout else None,
-        )
-        self.model1 = self.add_widget_intelligent(
-            npyscreen.SelectOne,
-            values=self.model_names,
-            value=0,
-            max_height=len(self.model_names),
-            max_width=max_width,
-            scroll_exit=True,
-            rely=7,
-        )
-        self.add_widget_intelligent(
-            npyscreen.FixedText,
-            value="MODEL 2",
-            color="GOOD",
-            editable=False,
-            relx=max_width + 3 if horizontal_layout else None,
-            rely=6 if horizontal_layout else None,
-        )
-        self.model2 = self.add_widget_intelligent(
-            npyscreen.SelectOne,
-            name="(2)",
-            values=self.model_names,
-            value=1,
-            max_height=len(self.model_names),
-            max_width=max_width,
-            relx=max_width + 3 if horizontal_layout else None,
-            rely=7 if horizontal_layout else None,
-            scroll_exit=True,
-        )
-        self.add_widget_intelligent(
-            npyscreen.FixedText,
-            value="MODEL 3",
-            color="GOOD",
-            editable=False,
-            relx=max_width * 2 + 3 if horizontal_layout else None,
-            rely=6 if horizontal_layout else None,
-        )
-        models_plus_none = self.model_names.copy()
-        models_plus_none.insert(0, "None")
-        self.model3 = self.add_widget_intelligent(
-            npyscreen.SelectOne,
-            name="(3)",
-            values=models_plus_none,
-            value=0,
-            max_height=len(self.model_names) + 1,
-            max_width=max_width,
-            scroll_exit=True,
-            relx=max_width * 2 + 3 if horizontal_layout else None,
-            rely=7 if horizontal_layout else None,
-        )
-        for m in [self.model1, self.model2, self.model3]:
-            m.when_value_edited = self.models_changed
-        self.merged_model_name = self.add_widget_intelligent(
-            TextBox,
-            name="Name for merged model:",
-            labelColor="CONTROL",
-            max_height=3,
-            value="",
-            scroll_exit=True,
-        )
-        self.force = self.add_widget_intelligent(
-            npyscreen.Checkbox,
-            name="Force merge of models created by different diffusers library versions",
-            labelColor="CONTROL",
-            value=True,
-            scroll_exit=True,
-        )
-        self.nextrely += 1
-        self.merge_method = self.add_widget_intelligent(
-            npyscreen.TitleSelectOne,
-            name="Merge Method:",
-            values=self.interpolations,
-            value=0,
-            labelColor="CONTROL",
-            max_height=len(self.interpolations) + 1,
-            scroll_exit=True,
-        )
-        self.alpha = self.add_widget_intelligent(
-            FloatTitleSlider,
-            name="Weight (alpha) to assign to second and third models:",
-            out_of=1.0,
-            step=0.01,
-            lowest=0,
-            value=0.5,
-            labelColor="CONTROL",
-            scroll_exit=True,
-        )
-        self.model1.editing = True
-
-    def models_changed(self) -> None:
-        models = self.model1.values
-        selected_model1 = self.model1.value[0]
-        selected_model2 = self.model2.value[0]
-        selected_model3 = self.model3.value[0]
-        merged_model_name = f"{models[selected_model1]}+{models[selected_model2]}"
-        self.merged_model_name.value = merged_model_name
-
-        if selected_model3 > 0:
-            self.merge_method.values = ["add_difference ( A+(B-C) )"]
-            self.merged_model_name.value += f"+{models[selected_model3 -1]}"  # In model3 there is one more element in the list (None). So we have to subtract one.
-        else:
-            self.merge_method.values = self.interpolations
-        self.merge_method.value = 0
-
-    def on_ok(self) -> None:
-        if self.validate_field_values() and self.check_for_overwrite():
-            self.parentApp.setNextForm(None)
-            self.editing = False
-            self.parentApp.merge_arguments = self.marshall_arguments()
-            npyscreen.notify("Starting the merge...")
-        else:
-            self.editing = True
-
-    def on_cancel(self) -> None:
-        sys.exit(0)
-
-    def marshall_arguments(self) -> dict:
-        model_keys = [x[0] for x in self.models]
-        models = [
-            model_keys[self.model1.value[0]],
-            model_keys[self.model2.value[0]],
-        ]
-        if self.model3.value[0] > 0:
-            models.append(model_keys[self.model3.value[0] - 1])
-            interp = "add_difference"
-        else:
-            interp = self.interpolations[self.merge_method.value[0]]
-
-        args = {
-            "model_keys": models,
-            "alpha": self.alpha.value,
-            "interp": interp,
-            "force": self.force.value,
-            "merged_model_name": self.merged_model_name.value,
-        }
-        return args
-
-    def check_for_overwrite(self) -> bool:
-        model_out = self.merged_model_name.value
-        if model_out not in self.model_names:
-            return True
-        else:
-            result: bool = npyscreen.notify_yes_no(
-                f"The chosen merged model destination, {model_out}, is already in use. Overwrite?"
-            )
-            return result
-
-    def validate_field_values(self) -> bool:
-        bad_fields = []
-        model_names = self.model_names
-        selected_models = {model_names[self.model1.value[0]], model_names[self.model2.value[0]]}
-        if self.model3.value[0] > 0:
-            selected_models.add(model_names[self.model3.value[0] - 1])
-        if len(selected_models) < 2:
-            bad_fields.append(f"Please select two or three DIFFERENT models to compare. You selected {selected_models}")
-        if len(bad_fields) > 0:
-            message = "The following problems were detected and must be corrected:"
-            for problem in bad_fields:
-                message += f"\n* {problem}"
-            npyscreen.notify_confirm(message)
-            return False
-        else:
-            return True
-
-    def get_models(self, base_model: Optional[BaseModelType] = None) -> List[Tuple[str, str]]:  # key to name
-        models = [
-            (x.key, x.name)
-            for x in self.model_record_store.search_by_attr(model_type=ModelType.Main, base_model=base_model)
-            if x.format == ModelFormat("diffusers")
-            and hasattr(x, "variant")
-            and x.variant == ModelVariantType("normal")
-        ]
-        return sorted(models, key=lambda x: x[1])
-
-    def _populate_models(self, value: List[int]) -> None:
-        base_model = BASE_TYPES[value[0]][0]
-        self.models = self.get_models(base_model)
-        self.model_names = [x[1] for x in self.models]
-
-        models_plus_none = self.model_names.copy()
-        models_plus_none.insert(0, "None")
-        self.model1.values = self.model_names
-        self.model2.values = self.model_names
-        self.model3.values = models_plus_none
-
-        self.display()
-
-
-# npyscreen is untyped and causes mypy to get naggy
-class Mergeapp(npyscreen.NPSAppManaged):  # type: ignore
-    def __init__(self, installer: ModelInstallServiceBase):
-        """Initialize the npyscreen application."""
-        super().__init__()
-        self.installer = installer
-
-    def onStart(self) -> None:
-        npyscreen.setTheme(npyscreen.Themes.ElegantTheme)
-        self.main = self.addForm("MAIN", mergeModelsForm, name="Merge Models Settings")
-
-
-def run_gui(args: Namespace) -> None:
-    installer = initialize_installer(config)
-    mergeapp = Mergeapp(installer)
-    mergeapp.run()
-    merge_args = mergeapp.merge_arguments
-    merger = ModelMerger(installer)
-    merger.merge_diffusion_models_and_save(**merge_args)
-    logger.info(f'Models merged into new model: "{merge_args.merged_model_name}".')
-
-
-def run_cli(args: Namespace) -> None:
-    assert args.alpha >= 0 and args.alpha <= 1.0, "alpha must be between 0 and 1"
-    assert (
-        args.model_names and len(args.model_names) >= 1 and len(args.model_names) <= 3
-    ), "Please provide the --models argument to list 2 to 3 models to merge. Use --help for full usage."
-
-    if not args.merged_model_name:
-        args.merged_model_name = "+".join(args.model_names)
-        logger.info(f'No --merged_model_name provided. Defaulting to "{args.merged_model_name}"')
-
-    installer = initialize_installer(config)
-    store = installer.record_store
-    assert (
-        len(store.search_by_attr(args.merged_model_name, args.base_model, ModelType.Main)) == 0 or args.clobber
-    ), f'A model named "{args.merged_model_name}" already exists. Use --clobber to overwrite.'
-
-    merger = ModelMerger(installer)
-    model_keys = []
-    for name in args.model_names:
-        if len(name) == 32 and re.match(r"^[0-9a-f]$", name):
-            model_keys.append(name)
-        else:
-            models = store.search_by_attr(
-                model_name=name, model_type=ModelType.Main, base_model=BaseModelType(args.base_model)
-            )
-            assert len(models) > 0, f"{name}: Unknown model"
-            assert len(models) < 2, f"{name}: More than one model by this name. Please specify the model key instead."
-            model_keys.append(models[0].key)
-
-    merger.merge_diffusion_models_and_save(
-        alpha=args.alpha,
-        model_keys=model_keys,
-        merged_model_name=args.merged_model_name,
-        interp=args.interp,
-        force=args.force,
-    )
-    logger.info(f'Models merged into new model: "{args.merged_model_name}".')
-
-
-def main() -> None:
-    args = _parse_args()
-    if args.root_dir:
-        config.parse_args(["--root", str(args.root_dir)])
-    else:
-        config.parse_args([])
-
-    try:
-        if args.front_end:
-            run_gui(args)
-        else:
-            run_cli(args)
-    except widget.NotEnoughSpaceForWidget as e:
-        if str(e).startswith("Height of 1 allocated"):
-            logger.error("You need to have at least two diffusers models defined in models.yaml in order to merge")
-        else:
-            logger.error("Not enough room for the user interface. Try making this window larger.")
-        sys.exit(-1)
-    except Exception as e:
-        logger.error(str(e))
-        sys.exit(-1)
-    except KeyboardInterrupt:
-        sys.exit(-1)
-
-
-if __name__ == "__main__":
-    main()
diff --git a/tests/app/services/model_install/test_model_install.py b/tests/app/services/model_install/test_model_install.py
index 5694432ebd..55f7e86541 100644
--- a/tests/app/services/model_install/test_model_install.py
+++ b/tests/app/services/model_install/test_model_install.py
@@ -20,7 +20,7 @@ from invokeai.app.services.model_install import (
 )
 from invokeai.app.services.model_records import UnknownModelException
 from invokeai.backend.model_manager.config import BaseModelType, ModelFormat, ModelType
-from tests.backend.model_manager_2.model_manager_2_fixtures import *  # noqa F403
+from tests.backend.model_manager.model_manager_fixtures import *  # noqa F403
 
 OS = platform.uname().system
 
diff --git a/tests/app/services/model_records/test_model_records_sql.py b/tests/app/services/model_records/test_model_records_sql.py
index 852e1da979..57515ac81b 100644
--- a/tests/app/services/model_records/test_model_records_sql.py
+++ b/tests/app/services/model_records/test_model_records_sql.py
@@ -26,7 +26,7 @@ from invokeai.backend.model_manager.config import (
 )
 from invokeai.backend.model_manager.metadata import BaseMetadata
 from invokeai.backend.util.logging import InvokeAILogger
-from tests.backend.model_manager_2.model_manager_2_fixtures import *  # noqa F403
+from tests.backend.model_manager.model_manager_fixtures import *  # noqa F403
 from tests.fixtures.sqlite_database import create_mock_sqlite_database
 
 
diff --git a/tests/backend/ip_adapter/test_ip_adapter.py b/tests/backend/ip_adapter/test_ip_adapter.py
index 6a3ec510a2..9ed3c9bc50 100644
--- a/tests/backend/ip_adapter/test_ip_adapter.py
+++ b/tests/backend/ip_adapter/test_ip_adapter.py
@@ -2,7 +2,7 @@ import pytest
 import torch
 
 from invokeai.backend.ip_adapter.unet_patcher import UNetPatcher
-from invokeai.backend.model_management.models.base import BaseModelType, ModelType, SubModelType
+from invokeai.backend.model_manager import BaseModelType, ModelType, SubModelType
 from invokeai.backend.util.test_utils import install_and_load_model
 
 
diff --git a/tests/backend/model_manager_2/data/invokeai_root/README b/tests/backend/model_manager/data/invokeai_root/README
similarity index 100%
rename from tests/backend/model_manager_2/data/invokeai_root/README
rename to tests/backend/model_manager/data/invokeai_root/README
diff --git a/tests/backend/model_manager_2/data/invokeai_root/configs/stable-diffusion/v1-inference.yaml b/tests/backend/model_manager/data/invokeai_root/configs/stable-diffusion/v1-inference.yaml
similarity index 100%
rename from tests/backend/model_manager_2/data/invokeai_root/configs/stable-diffusion/v1-inference.yaml
rename to tests/backend/model_manager/data/invokeai_root/configs/stable-diffusion/v1-inference.yaml
diff --git a/tests/backend/model_manager_2/data/invokeai_root/databases/README b/tests/backend/model_manager/data/invokeai_root/databases/README
similarity index 100%
rename from tests/backend/model_manager_2/data/invokeai_root/databases/README
rename to tests/backend/model_manager/data/invokeai_root/databases/README
diff --git a/tests/backend/model_manager_2/data/invokeai_root/models/README b/tests/backend/model_manager/data/invokeai_root/models/README
similarity index 100%
rename from tests/backend/model_manager_2/data/invokeai_root/models/README
rename to tests/backend/model_manager/data/invokeai_root/models/README
diff --git a/tests/backend/model_manager_2/data/test_files/test-diffusers-main/model_index.json b/tests/backend/model_manager/data/test_files/test-diffusers-main/model_index.json
similarity index 100%
rename from tests/backend/model_manager_2/data/test_files/test-diffusers-main/model_index.json
rename to tests/backend/model_manager/data/test_files/test-diffusers-main/model_index.json
diff --git a/tests/backend/model_manager_2/data/test_files/test-diffusers-main/scheduler/scheduler_config.json b/tests/backend/model_manager/data/test_files/test-diffusers-main/scheduler/scheduler_config.json
similarity index 100%
rename from tests/backend/model_manager_2/data/test_files/test-diffusers-main/scheduler/scheduler_config.json
rename to tests/backend/model_manager/data/test_files/test-diffusers-main/scheduler/scheduler_config.json
diff --git a/tests/backend/model_manager_2/data/test_files/test-diffusers-main/text_encoder/config.json b/tests/backend/model_manager/data/test_files/test-diffusers-main/text_encoder/config.json
similarity index 100%
rename from tests/backend/model_manager_2/data/test_files/test-diffusers-main/text_encoder/config.json
rename to tests/backend/model_manager/data/test_files/test-diffusers-main/text_encoder/config.json
diff --git a/tests/backend/model_manager_2/data/test_files/test-diffusers-main/text_encoder/model.fp16.safetensors b/tests/backend/model_manager/data/test_files/test-diffusers-main/text_encoder/model.fp16.safetensors
similarity index 100%
rename from tests/backend/model_manager_2/data/test_files/test-diffusers-main/text_encoder/model.fp16.safetensors
rename to tests/backend/model_manager/data/test_files/test-diffusers-main/text_encoder/model.fp16.safetensors
diff --git a/tests/backend/model_manager_2/data/test_files/test-diffusers-main/text_encoder/model.safetensors b/tests/backend/model_manager/data/test_files/test-diffusers-main/text_encoder/model.safetensors
similarity index 100%
rename from tests/backend/model_manager_2/data/test_files/test-diffusers-main/text_encoder/model.safetensors
rename to tests/backend/model_manager/data/test_files/test-diffusers-main/text_encoder/model.safetensors
diff --git a/tests/backend/model_manager_2/data/test_files/test-diffusers-main/text_encoder_2/config.json b/tests/backend/model_manager/data/test_files/test-diffusers-main/text_encoder_2/config.json
similarity index 100%
rename from tests/backend/model_manager_2/data/test_files/test-diffusers-main/text_encoder_2/config.json
rename to tests/backend/model_manager/data/test_files/test-diffusers-main/text_encoder_2/config.json
diff --git a/tests/backend/model_manager_2/data/test_files/test-diffusers-main/text_encoder_2/model.fp16.safetensors b/tests/backend/model_manager/data/test_files/test-diffusers-main/text_encoder_2/model.fp16.safetensors
similarity index 100%
rename from tests/backend/model_manager_2/data/test_files/test-diffusers-main/text_encoder_2/model.fp16.safetensors
rename to tests/backend/model_manager/data/test_files/test-diffusers-main/text_encoder_2/model.fp16.safetensors
diff --git a/tests/backend/model_manager_2/data/test_files/test-diffusers-main/text_encoder_2/model.safetensors b/tests/backend/model_manager/data/test_files/test-diffusers-main/text_encoder_2/model.safetensors
similarity index 100%
rename from tests/backend/model_manager_2/data/test_files/test-diffusers-main/text_encoder_2/model.safetensors
rename to tests/backend/model_manager/data/test_files/test-diffusers-main/text_encoder_2/model.safetensors
diff --git a/tests/backend/model_manager_2/data/test_files/test-diffusers-main/tokenizer/merges.txt b/tests/backend/model_manager/data/test_files/test-diffusers-main/tokenizer/merges.txt
similarity index 100%
rename from tests/backend/model_manager_2/data/test_files/test-diffusers-main/tokenizer/merges.txt
rename to tests/backend/model_manager/data/test_files/test-diffusers-main/tokenizer/merges.txt
diff --git a/tests/backend/model_manager_2/data/test_files/test-diffusers-main/tokenizer/special_tokens_map.json b/tests/backend/model_manager/data/test_files/test-diffusers-main/tokenizer/special_tokens_map.json
similarity index 100%
rename from tests/backend/model_manager_2/data/test_files/test-diffusers-main/tokenizer/special_tokens_map.json
rename to tests/backend/model_manager/data/test_files/test-diffusers-main/tokenizer/special_tokens_map.json
diff --git a/tests/backend/model_manager_2/data/test_files/test-diffusers-main/tokenizer/tokenizer_config.json b/tests/backend/model_manager/data/test_files/test-diffusers-main/tokenizer/tokenizer_config.json
similarity index 100%
rename from tests/backend/model_manager_2/data/test_files/test-diffusers-main/tokenizer/tokenizer_config.json
rename to tests/backend/model_manager/data/test_files/test-diffusers-main/tokenizer/tokenizer_config.json
diff --git a/tests/backend/model_manager_2/data/test_files/test-diffusers-main/tokenizer/vocab.json b/tests/backend/model_manager/data/test_files/test-diffusers-main/tokenizer/vocab.json
similarity index 100%
rename from tests/backend/model_manager_2/data/test_files/test-diffusers-main/tokenizer/vocab.json
rename to tests/backend/model_manager/data/test_files/test-diffusers-main/tokenizer/vocab.json
diff --git a/tests/backend/model_manager_2/data/test_files/test-diffusers-main/tokenizer_2/merges.txt b/tests/backend/model_manager/data/test_files/test-diffusers-main/tokenizer_2/merges.txt
similarity index 100%
rename from tests/backend/model_manager_2/data/test_files/test-diffusers-main/tokenizer_2/merges.txt
rename to tests/backend/model_manager/data/test_files/test-diffusers-main/tokenizer_2/merges.txt
diff --git a/tests/backend/model_manager_2/data/test_files/test-diffusers-main/tokenizer_2/special_tokens_map.json b/tests/backend/model_manager/data/test_files/test-diffusers-main/tokenizer_2/special_tokens_map.json
similarity index 100%
rename from tests/backend/model_manager_2/data/test_files/test-diffusers-main/tokenizer_2/special_tokens_map.json
rename to tests/backend/model_manager/data/test_files/test-diffusers-main/tokenizer_2/special_tokens_map.json
diff --git a/tests/backend/model_manager_2/data/test_files/test-diffusers-main/tokenizer_2/tokenizer_config.json b/tests/backend/model_manager/data/test_files/test-diffusers-main/tokenizer_2/tokenizer_config.json
similarity index 100%
rename from tests/backend/model_manager_2/data/test_files/test-diffusers-main/tokenizer_2/tokenizer_config.json
rename to tests/backend/model_manager/data/test_files/test-diffusers-main/tokenizer_2/tokenizer_config.json
diff --git a/tests/backend/model_manager_2/data/test_files/test-diffusers-main/tokenizer_2/vocab.json b/tests/backend/model_manager/data/test_files/test-diffusers-main/tokenizer_2/vocab.json
similarity index 100%
rename from tests/backend/model_manager_2/data/test_files/test-diffusers-main/tokenizer_2/vocab.json
rename to tests/backend/model_manager/data/test_files/test-diffusers-main/tokenizer_2/vocab.json
diff --git a/tests/backend/model_manager_2/data/test_files/test-diffusers-main/unet/config.json b/tests/backend/model_manager/data/test_files/test-diffusers-main/unet/config.json
similarity index 100%
rename from tests/backend/model_manager_2/data/test_files/test-diffusers-main/unet/config.json
rename to tests/backend/model_manager/data/test_files/test-diffusers-main/unet/config.json
diff --git a/tests/backend/model_manager_2/data/test_files/test-diffusers-main/unet/diffusion_pytorch_model.fp16.safetensors b/tests/backend/model_manager/data/test_files/test-diffusers-main/unet/diffusion_pytorch_model.fp16.safetensors
similarity index 100%
rename from tests/backend/model_manager_2/data/test_files/test-diffusers-main/unet/diffusion_pytorch_model.fp16.safetensors
rename to tests/backend/model_manager/data/test_files/test-diffusers-main/unet/diffusion_pytorch_model.fp16.safetensors
diff --git a/tests/backend/model_manager_2/data/test_files/test-diffusers-main/unet/diffusion_pytorch_model.safetensors b/tests/backend/model_manager/data/test_files/test-diffusers-main/unet/diffusion_pytorch_model.safetensors
similarity index 100%
rename from tests/backend/model_manager_2/data/test_files/test-diffusers-main/unet/diffusion_pytorch_model.safetensors
rename to tests/backend/model_manager/data/test_files/test-diffusers-main/unet/diffusion_pytorch_model.safetensors
diff --git a/tests/backend/model_manager_2/data/test_files/test-diffusers-main/vae/config.json b/tests/backend/model_manager/data/test_files/test-diffusers-main/vae/config.json
similarity index 100%
rename from tests/backend/model_manager_2/data/test_files/test-diffusers-main/vae/config.json
rename to tests/backend/model_manager/data/test_files/test-diffusers-main/vae/config.json
diff --git a/tests/backend/model_manager_2/data/test_files/test-diffusers-main/vae/diffusion_pytorch_model.fp16.safetensors b/tests/backend/model_manager/data/test_files/test-diffusers-main/vae/diffusion_pytorch_model.fp16.safetensors
similarity index 100%
rename from tests/backend/model_manager_2/data/test_files/test-diffusers-main/vae/diffusion_pytorch_model.fp16.safetensors
rename to tests/backend/model_manager/data/test_files/test-diffusers-main/vae/diffusion_pytorch_model.fp16.safetensors
diff --git a/tests/backend/model_manager_2/data/test_files/test-diffusers-main/vae/diffusion_pytorch_model.safetensors b/tests/backend/model_manager/data/test_files/test-diffusers-main/vae/diffusion_pytorch_model.safetensors
similarity index 100%
rename from tests/backend/model_manager_2/data/test_files/test-diffusers-main/vae/diffusion_pytorch_model.safetensors
rename to tests/backend/model_manager/data/test_files/test-diffusers-main/vae/diffusion_pytorch_model.safetensors
diff --git a/tests/backend/model_manager_2/data/test_files/test_embedding.safetensors b/tests/backend/model_manager/data/test_files/test_embedding.safetensors
similarity index 100%
rename from tests/backend/model_manager_2/data/test_files/test_embedding.safetensors
rename to tests/backend/model_manager/data/test_files/test_embedding.safetensors
diff --git a/tests/backend/model_manager_2/model_loading/test_model_load.py b/tests/backend/model_manager/model_loading/test_model_load.py
similarity index 61%
rename from tests/backend/model_manager_2/model_loading/test_model_load.py
rename to tests/backend/model_manager/model_loading/test_model_load.py
index a7a64e91ac..38d9b8afb8 100644
--- a/tests/backend/model_manager_2/model_loading/test_model_load.py
+++ b/tests/backend/model_manager/model_loading/test_model_load.py
@@ -5,17 +5,16 @@ Test model loading
 from pathlib import Path
 
 from invokeai.app.services.model_install import ModelInstallServiceBase
-from invokeai.backend.embeddings.textual_inversion import TextualInversionModelRaw
-from invokeai.backend.model_manager.load import AnyModelLoader
-from tests.backend.model_manager_2.model_manager_2_fixtures import *  # noqa F403
+from invokeai.app.services.model_load import ModelLoadServiceBase
+from invokeai.backend.textual_inversion import TextualInversionModelRaw
+from tests.backend.model_manager.model_manager_fixtures import *  # noqa F403
 
-
-def test_loading(mm2_installer: ModelInstallServiceBase, mm2_loader: AnyModelLoader, embedding_file: Path):
+def test_loading(mm2_installer: ModelInstallServiceBase, mm2_loader: ModelLoadServiceBase, embedding_file: Path):
     store = mm2_installer.record_store
     matches = store.search_by_attr(model_name="test_embedding")
     assert len(matches) == 0
     key = mm2_installer.register_path(embedding_file)
-    loaded_model = mm2_loader.load_model(store.get_model(key))
+    loaded_model = mm2_loader.load_model_by_config(store.get_model(key))
     assert loaded_model is not None
     assert loaded_model.config.key == key
     with loaded_model as model:
diff --git a/tests/backend/model_manager_2/model_manager_2_fixtures.py b/tests/backend/model_manager/model_manager_fixtures.py
similarity index 80%
rename from tests/backend/model_manager_2/model_manager_2_fixtures.py
rename to tests/backend/model_manager/model_manager_fixtures.py
index ebdc9cb5cd..5f7f44c018 100644
--- a/tests/backend/model_manager_2/model_manager_2_fixtures.py
+++ b/tests/backend/model_manager/model_manager_fixtures.py
@@ -6,24 +6,27 @@ from pathlib import Path
 from typing import Any, Dict, List
 
 import pytest
+from pytest import FixtureRequest
 from pydantic import BaseModel
 from requests.sessions import Session
 from requests_testadapter import TestAdapter, TestSession
 
 from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.app.services.download import DownloadQueueService
+from invokeai.app.services.download import DownloadQueueServiceBase, DownloadQueueService
 from invokeai.app.services.events.events_base import EventServiceBase
+from invokeai.app.services.model_manager import ModelManagerServiceBase, ModelManagerService
+from invokeai.app.services.model_load import ModelLoadServiceBase, ModelLoadService
 from invokeai.app.services.model_install import ModelInstallService, ModelInstallServiceBase
 from invokeai.app.services.model_metadata import ModelMetadataStoreBase, ModelMetadataStoreSQL
-from invokeai.app.services.model_records import ModelRecordServiceSQL
+from invokeai.app.services.model_records import ModelRecordServiceBase, ModelRecordServiceSQL
 from invokeai.backend.model_manager.config import (
     BaseModelType,
     ModelFormat,
     ModelType,
 )
-from invokeai.backend.model_manager.load import AnyModelLoader, ModelCache, ModelConvertCache
+from invokeai.backend.model_manager.load import ModelCache, ModelConvertCache
 from invokeai.backend.util.logging import InvokeAILogger
-from tests.backend.model_manager_2.model_metadata.metadata_examples import (
+from tests.backend.model_manager.model_metadata.metadata_examples import (
     RepoCivitaiModelMetadata1,
     RepoCivitaiVersionMetadata1,
     RepoHFMetadata1,
@@ -86,22 +89,71 @@ def mm2_app_config(mm2_root_dir: Path) -> InvokeAIAppConfig:
     app_config = InvokeAIAppConfig(
         root=mm2_root_dir,
         models_dir=mm2_root_dir / "models",
+        log_level="info",
     )
     return app_config
 
 
 @pytest.fixture
-def mm2_loader(mm2_app_config: InvokeAIAppConfig, mm2_record_store: ModelRecordServiceSQL) -> AnyModelLoader:
-    logger = InvokeAILogger.get_logger(config=mm2_app_config)
+def mm2_download_queue(mm2_session: Session,
+                       request: FixtureRequest
+                       ) -> DownloadQueueServiceBase:
+    download_queue = DownloadQueueService(requests_session=mm2_session)
+    download_queue.start()
+
+    def stop_queue() -> None:
+        download_queue.stop()
+
+    request.addfinalizer(stop_queue)
+    return download_queue
+
+@pytest.fixture
+def mm2_metadata_store(mm2_record_store: ModelRecordServiceSQL) -> ModelMetadataStoreBase:
+    return mm2_record_store.metadata_store
+
+@pytest.fixture
+def mm2_loader(mm2_app_config: InvokeAIAppConfig, mm2_record_store: ModelRecordServiceBase) -> ModelLoadServiceBase:
     ram_cache = ModelCache(
-        logger=logger, max_cache_size=mm2_app_config.ram_cache_size, max_vram_cache_size=mm2_app_config.vram_cache_size
+        logger=InvokeAILogger.get_logger(),
+        max_cache_size=mm2_app_config.ram_cache_size,
+        max_vram_cache_size=mm2_app_config.vram_cache_size
     )
     convert_cache = ModelConvertCache(mm2_app_config.models_convert_cache_path)
-    return AnyModelLoader(app_config=mm2_app_config, logger=logger, ram_cache=ram_cache, convert_cache=convert_cache)
+    return ModelLoadService(app_config=mm2_app_config,
+                            record_store=mm2_record_store,
+                            ram_cache=ram_cache,
+                            convert_cache=convert_cache,
+                          )
+
+@pytest.fixture
+def mm2_installer(mm2_app_config: InvokeAIAppConfig,
+                  mm2_download_queue: DownloadQueueServiceBase,
+                  mm2_session: Session,
+                  request: FixtureRequest,
+                  ) -> ModelInstallServiceBase:
+    logger = InvokeAILogger.get_logger()
+    db = create_mock_sqlite_database(mm2_app_config, logger)
+    events = DummyEventService()
+    store = ModelRecordServiceSQL(db, ModelMetadataStoreSQL(db))
+
+    installer = ModelInstallService(
+        app_config=mm2_app_config,
+        record_store=store,
+        download_queue=mm2_download_queue,
+        event_bus=events,
+        session=mm2_session,
+    )
+    installer.start()
+
+    def stop_installer() -> None:
+        installer.stop()
+
+    request.addfinalizer(stop_installer)
+    return installer
 
 
 @pytest.fixture
-def mm2_record_store(mm2_app_config: InvokeAIAppConfig) -> ModelRecordServiceSQL:
+def mm2_record_store(mm2_app_config: InvokeAIAppConfig) -> ModelRecordServiceBase:
     logger = InvokeAILogger.get_logger(config=mm2_app_config)
     db = create_mock_sqlite_database(mm2_app_config, logger)
     store = ModelRecordServiceSQL(db, ModelMetadataStoreSQL(db))
@@ -161,11 +213,15 @@ def mm2_record_store(mm2_app_config: InvokeAIAppConfig) -> ModelRecordServiceSQL
     store.add_model("test_config_5", raw5)
     return store
 
-
 @pytest.fixture
-def mm2_metadata_store(mm2_record_store: ModelRecordServiceSQL) -> ModelMetadataStoreBase:
-    return mm2_record_store.metadata_store
-
+def mm2_model_manager(mm2_record_store: ModelRecordServiceBase,
+                      mm2_installer: ModelInstallServiceBase,
+                      mm2_loader: ModelLoadServiceBase) -> ModelManagerServiceBase:
+    return ModelManagerService(
+        store=mm2_record_store,
+        install=mm2_installer,
+        load=mm2_loader
+    )
 
 @pytest.fixture
 def mm2_session(embedding_file: Path, diffusers_dir: Path) -> Session:
@@ -252,22 +308,3 @@ def mm2_session(embedding_file: Path, diffusers_dir: Path) -> Session:
     return sess
 
 
-@pytest.fixture
-def mm2_installer(mm2_app_config: InvokeAIAppConfig, mm2_session: Session) -> ModelInstallServiceBase:
-    logger = InvokeAILogger.get_logger()
-    db = create_mock_sqlite_database(mm2_app_config, logger)
-    events = DummyEventService()
-    store = ModelRecordServiceSQL(db, ModelMetadataStoreSQL(db))
-
-    download_queue = DownloadQueueService(requests_session=mm2_session)
-    download_queue.start()
-
-    installer = ModelInstallService(
-        app_config=mm2_app_config,
-        record_store=store,
-        download_queue=download_queue,
-        event_bus=events,
-        session=mm2_session,
-    )
-    installer.start()
-    return installer
diff --git a/tests/backend/model_manager_2/model_metadata/metadata_examples.py b/tests/backend/model_manager/model_metadata/metadata_examples.py
similarity index 100%
rename from tests/backend/model_manager_2/model_metadata/metadata_examples.py
rename to tests/backend/model_manager/model_metadata/metadata_examples.py
diff --git a/tests/backend/model_manager_2/model_metadata/test_model_metadata.py b/tests/backend/model_manager/model_metadata/test_model_metadata.py
similarity index 99%
rename from tests/backend/model_manager_2/model_metadata/test_model_metadata.py
rename to tests/backend/model_manager/model_metadata/test_model_metadata.py
index f61eab1b5d..09b18916d3 100644
--- a/tests/backend/model_manager_2/model_metadata/test_model_metadata.py
+++ b/tests/backend/model_manager/model_metadata/test_model_metadata.py
@@ -19,7 +19,7 @@ from invokeai.backend.model_manager.metadata import (
     UnknownMetadataException,
 )
 from invokeai.backend.model_manager.util import select_hf_files
-from tests.backend.model_manager_2.model_manager_2_fixtures import *  # noqa F403
+from tests.backend.model_manager.model_manager_fixtures import *  # noqa F403
 
 
 def test_metadata_store_put_get(mm2_metadata_store: ModelMetadataStoreBase) -> None:
diff --git a/tests/backend/model_management/test_libc_util.py b/tests/backend/model_manager/test_libc_util.py
similarity index 88%
rename from tests/backend/model_management/test_libc_util.py
rename to tests/backend/model_manager/test_libc_util.py
index e13a2fd3a2..4309dc7c34 100644
--- a/tests/backend/model_management/test_libc_util.py
+++ b/tests/backend/model_manager/test_libc_util.py
@@ -1,6 +1,6 @@
 import pytest
 
-from invokeai.backend.model_management.libc_util import LibcUtil, Struct_mallinfo2
+from invokeai.backend.model_manager.util.libc_util import LibcUtil, Struct_mallinfo2
 
 
 def test_libc_util_mallinfo2():
diff --git a/tests/backend/model_management/test_lora.py b/tests/backend/model_manager/test_lora.py
similarity index 96%
rename from tests/backend/model_management/test_lora.py
rename to tests/backend/model_manager/test_lora.py
index 14bcc87c89..e124bb68ef 100644
--- a/tests/backend/model_management/test_lora.py
+++ b/tests/backend/model_manager/test_lora.py
@@ -5,8 +5,8 @@
 import pytest
 import torch
 
-from invokeai.backend.model_management.lora import ModelPatcher
-from invokeai.backend.model_management.models.lora import LoRALayer, LoRAModelRaw
+from invokeai.backend.model_patcher import ModelPatcher
+from invokeai.backend.lora import LoRALayer, LoRAModelRaw
 
 
 @pytest.mark.parametrize(
diff --git a/tests/backend/model_management/test_memory_snapshot.py b/tests/backend/model_manager/test_memory_snapshot.py
similarity index 87%
rename from tests/backend/model_management/test_memory_snapshot.py
rename to tests/backend/model_manager/test_memory_snapshot.py
index 216cd62171..87ec8c34ee 100644
--- a/tests/backend/model_management/test_memory_snapshot.py
+++ b/tests/backend/model_manager/test_memory_snapshot.py
@@ -1,8 +1,7 @@
 import pytest
 
-from invokeai.backend.model_management.libc_util import Struct_mallinfo2
-from invokeai.backend.model_management.memory_snapshot import MemorySnapshot, get_pretty_snapshot_diff
-
+from invokeai.backend.model_manager.util.libc_util import Struct_mallinfo2
+from invokeai.backend.model_manager.load.memory_snapshot import MemorySnapshot, get_pretty_snapshot_diff
 
 def test_memory_snapshot_capture():
     """Smoke test of MemorySnapshot.capture()."""
@@ -26,6 +25,7 @@ snapshots = [
 def test_get_pretty_snapshot_diff(snapshot_1, snapshot_2):
     """Test that get_pretty_snapshot_diff() works with various combinations of missing MemorySnapshot fields."""
     msg = get_pretty_snapshot_diff(snapshot_1, snapshot_2)
+    print(msg)
 
     expected_lines = 0
     if snapshot_1 is not None and snapshot_2 is not None:
diff --git a/tests/backend/model_management/test_model_load_optimization.py b/tests/backend/model_manager/test_model_load_optimization.py
similarity index 96%
rename from tests/backend/model_management/test_model_load_optimization.py
rename to tests/backend/model_manager/test_model_load_optimization.py
index a4fe1dd597..f627f3a298 100644
--- a/tests/backend/model_management/test_model_load_optimization.py
+++ b/tests/backend/model_manager/test_model_load_optimization.py
@@ -1,7 +1,7 @@
 import pytest
 import torch
 
-from invokeai.backend.model_management.model_load_optimizations import _no_op, skip_torch_weight_init
+from invokeai.backend.model_manager.load.optimizations import _no_op, skip_torch_weight_init
 
 
 @pytest.mark.parametrize(
diff --git a/tests/backend/model_manager_2/util/test_hf_model_select.py b/tests/backend/model_manager/util/test_hf_model_select.py
similarity index 100%
rename from tests/backend/model_manager_2/util/test_hf_model_select.py
rename to tests/backend/model_manager/util/test_hf_model_select.py
diff --git a/tests/conftest.py b/tests/conftest.py
index 6e7d559be4..1c81600229 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -1,7 +1,2 @@
 # conftest.py is a special pytest file. Fixtures defined in this file will be accessible to all tests in this directory
 # without needing to explicitly import them. (https://docs.pytest.org/en/6.2.x/fixture.html)
-
-
-# We import the model_installer and torch_device fixtures here so that they can be used by all tests. Flake8 does not
-# play well with fixtures (F401 and F811), so this is cleaner than importing in all files that use these fixtures.
-from invokeai.backend.util.test_utils import model_installer, torch_device  # noqa: F401

From 5a3195f7578a1b4eaf053444f8d6d513e966048f Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sun, 18 Feb 2024 17:27:42 +1100
Subject: [PATCH 146/411] final tidying before marking PR as ready for review

- Replace AnyModelLoader with ModelLoaderRegistry
- Fix type check errors in multiple files
- Remove apparently unneeded `get_model_config_enum()` method from model manager
- Remove last vestiges of old model manager
- Updated tests and documentation

resolve conflict with seamless.py
---
 docs/contributing/MODEL_MANAGER.md            |  129 +-
 .../{model_manager_v2.py => model_manager.py} |   38 +-
 invokeai/app/api/routers/models.py            |  426 ----
 invokeai/app/api_app.py                       |   32 +-
 invokeai/app/invocations/compel.py            |    4 +-
 invokeai/app/services/config/config_base.py   |    2 +-
 .../invocation_stats/invocation_stats_base.py |   11 +-
 .../model_install/model_install_base.py       |    2 +-
 .../services/model_load/model_load_base.py    |   48 +-
 .../services/model_load/model_load_default.py |  100 +-
 .../app/services/model_manager/__init__.py    |    2 +-
 .../model_manager/model_manager_base.py       |   33 +
 .../model_manager/model_manager_default.py    |   60 +-
 .../app/services/shared/invocation_context.py |    4 +-
 invokeai/backend/install/migrate_to_3.py      |  591 ------
 .../backend/install/model_install_backend.py  |  637 ------
 invokeai/backend/ip_adapter/ip_adapter.py     |    2 +-
 invokeai/backend/lora.py                      |    2 +
 .../backend/model_management_OLD/README.md    |   27 -
 .../backend/model_management_OLD/__init__.py  |   20 -
 .../convert_ckpt_to_diffusers.py              | 1739 -----------------
 .../detect_baked_in_vae.py                    |   31 -
 invokeai/backend/model_management_OLD/lora.py |  582 ------
 .../model_management_OLD/memory_snapshot.py   |   99 -
 .../model_management_OLD/model_cache.py       |  553 ------
 .../model_load_optimizations.py               |   30 -
 .../model_management_OLD/model_manager.py     | 1121 -----------
 .../model_management_OLD/model_merge.py       |  140 --
 .../model_management_OLD/model_probe.py       |  664 -------
 .../model_management_OLD/model_search.py      |  112 --
 .../model_management_OLD/models/__init__.py   |  167 --
 .../model_management_OLD/models/base.py       |  681 -------
 .../models/clip_vision.py                     |   82 -
 .../model_management_OLD/models/controlnet.py |  162 --
 .../model_management_OLD/models/ip_adapter.py |   98 -
 .../model_management_OLD/models/lora.py       |  696 -------
 .../model_management_OLD/models/sdxl.py       |  148 --
 .../models/stable_diffusion.py                |  337 ----
 .../models/stable_diffusion_onnx.py           |  150 --
 .../models/t2i_adapter.py                     |  102 -
 .../models/textual_inversion.py               |   87 -
 .../model_management_OLD/models/vae.py        |  179 --
 .../backend/model_management_OLD/seamless.py  |   84 -
 invokeai/backend/model_management_OLD/util.py |   79 -
 invokeai/backend/model_manager/__init__.py    |   40 +-
 .../backend/model_manager/load/__init__.py    |   14 +-
 .../backend/model_manager/load/load_base.py   |  130 +-
 .../model_manager/load/load_default.py        |   54 +-
 .../model_manager/load/memory_snapshot.py     |    2 +-
 .../load/model_loader_registry.py             |  122 ++
 .../load/model_loaders/controlnet.py          |    6 +-
 .../load/model_loaders/generic_diffusers.py   |   66 +-
 .../load/model_loaders/ip_adapter.py          |    5 +-
 .../model_manager/load/model_loaders/lora.py  |    8 +-
 .../model_manager/load/model_loaders/onnx.py  |   13 +-
 .../load/model_loaders/stable_diffusion.py    |   13 +-
 .../load/model_loaders/textual_inversion.py   |   12 +-
 .../model_manager/load/model_loaders/vae.py   |    8 +-
 .../model_manager/load/optimizations.py       |   13 +-
 invokeai/backend/model_manager/merge.py       |    4 +-
 .../model_manager/metadata/metadata_base.py   |    9 +-
 invokeai/backend/model_manager/probe.py       |    3 +-
 invokeai/backend/model_manager/search.py      |    6 +-
 .../backend/model_manager/util/libc_util.py   |    7 +-
 .../backend/model_manager/util/model_util.py  |   20 +-
 invokeai/backend/onnx/onnx_runtime.py         |    3 +-
 invokeai/backend/raw_model.py                 |    1 +
 invokeai/backend/stable_diffusion/seamless.py |   96 +-
 invokeai/backend/textual_inversion.py         |    2 +
 invokeai/backend/util/test_utils.py           |    4 +-
 .../model_loading/test_model_load.py          |   21 +-
 .../model_manager/model_manager_fixtures.py   |   54 +-
 tests/backend/model_manager/test_lora.py      |    2 +-
 .../model_manager/test_memory_snapshot.py     |    3 +-
 74 files changed, 672 insertions(+), 10362 deletions(-)
 rename invokeai/app/api/routers/{model_manager_v2.py => model_manager.py} (97%)
 delete mode 100644 invokeai/app/api/routers/models.py
 delete mode 100644 invokeai/backend/install/migrate_to_3.py
 delete mode 100644 invokeai/backend/install/model_install_backend.py
 delete mode 100644 invokeai/backend/model_management_OLD/README.md
 delete mode 100644 invokeai/backend/model_management_OLD/__init__.py
 delete mode 100644 invokeai/backend/model_management_OLD/convert_ckpt_to_diffusers.py
 delete mode 100644 invokeai/backend/model_management_OLD/detect_baked_in_vae.py
 delete mode 100644 invokeai/backend/model_management_OLD/lora.py
 delete mode 100644 invokeai/backend/model_management_OLD/memory_snapshot.py
 delete mode 100644 invokeai/backend/model_management_OLD/model_cache.py
 delete mode 100644 invokeai/backend/model_management_OLD/model_load_optimizations.py
 delete mode 100644 invokeai/backend/model_management_OLD/model_manager.py
 delete mode 100644 invokeai/backend/model_management_OLD/model_merge.py
 delete mode 100644 invokeai/backend/model_management_OLD/model_probe.py
 delete mode 100644 invokeai/backend/model_management_OLD/model_search.py
 delete mode 100644 invokeai/backend/model_management_OLD/models/__init__.py
 delete mode 100644 invokeai/backend/model_management_OLD/models/base.py
 delete mode 100644 invokeai/backend/model_management_OLD/models/clip_vision.py
 delete mode 100644 invokeai/backend/model_management_OLD/models/controlnet.py
 delete mode 100644 invokeai/backend/model_management_OLD/models/ip_adapter.py
 delete mode 100644 invokeai/backend/model_management_OLD/models/lora.py
 delete mode 100644 invokeai/backend/model_management_OLD/models/sdxl.py
 delete mode 100644 invokeai/backend/model_management_OLD/models/stable_diffusion.py
 delete mode 100644 invokeai/backend/model_management_OLD/models/stable_diffusion_onnx.py
 delete mode 100644 invokeai/backend/model_management_OLD/models/t2i_adapter.py
 delete mode 100644 invokeai/backend/model_management_OLD/models/textual_inversion.py
 delete mode 100644 invokeai/backend/model_management_OLD/models/vae.py
 delete mode 100644 invokeai/backend/model_management_OLD/seamless.py
 delete mode 100644 invokeai/backend/model_management_OLD/util.py
 create mode 100644 invokeai/backend/model_manager/load/model_loader_registry.py

diff --git a/docs/contributing/MODEL_MANAGER.md b/docs/contributing/MODEL_MANAGER.md
index b19699de73..8351904b61 100644
--- a/docs/contributing/MODEL_MANAGER.md
+++ b/docs/contributing/MODEL_MANAGER.md
@@ -1531,23 +1531,29 @@ Here is a typical initialization pattern:
 
 ```
 from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.app.services.model_records import ModelRecordServiceBase
-from invokeai.app.services.model_load import ModelLoadService
+from invokeai.app.services.model_load import ModelLoadService, ModelLoaderRegistry
 
 config = InvokeAIAppConfig.get_config()
-store = ModelRecordServiceBase.open(config)
-loader = ModelLoadService(config, store)
+ram_cache = ModelCache(
+	max_cache_size=config.ram_cache_size, max_vram_cache_size=config.vram_cache_size, logger=logger
+)
+convert_cache = ModelConvertCache(
+	cache_path=config.models_convert_cache_path, max_size=config.convert_cache_size
+)
+loader = ModelLoadService(
+	app_config=config,
+	ram_cache=ram_cache,
+	convert_cache=convert_cache,
+	registry=ModelLoaderRegistry
+)
 ```
 
-Note that we are relying on the contents of the application
-configuration to choose the implementation of
-`ModelRecordServiceBase`.
+### load_model(model_config, [submodel_type], [context]) -> LoadedModel
 
-### load_model_by_key(key, [submodel_type], [context]) -> LoadedModel
-
-The `load_model_by_key()` method receives the unique key that
-identifies the model.  It loads the model into memory, gets the model
-ready for use, and returns a `LoadedModel` object.
+The `load_model()` method takes an `AnyModelConfig` returned by
+`ModelRecordService.get_model()` and returns the corresponding loaded
+model.  It loads the model into memory, gets the model ready for use,
+and returns a `LoadedModel` object.
 
 The optional second argument, `subtype` is a `SubModelType` string
 enum, such as "vae". It is mandatory when used with a main model, and
@@ -1593,25 +1599,6 @@ with model_info as vae:
 - `ModelNotFoundException`  -- key in database but model not found at path
 - `NotImplementedException` -- the loader doesn't know how to load this type of model
   
-### load_model_by_attr(model_name, base_model, model_type, [submodel], [context]) -> LoadedModel
-
-This is similar to `load_model_by_key`, but instead it accepts the
-combination of the model's name, type and base, which it passes to the
-model record config store for retrieval. If successful, this method
-returns a `LoadedModel`. It can raise the following exceptions:
-
-```
-UnknownModelException -- model with these attributes not known
-NotImplementedException -- the loader doesn't know how to load this type of model
-ValueError -- more than one model matches this combination of base/type/name
-```
-
-### load_model_by_config(config, [submodel], [context]) -> LoadedModel
-
-This method takes an `AnyModelConfig` returned by
-ModelRecordService.get_model() and returns the corresponding loaded
-model. It may raise a `NotImplementedException`.
-
 ### Emitting model loading events
 
 When the `context` argument is passed to `load_model_*()`, it will
@@ -1656,7 +1643,7 @@ onnx models.
 
 To install a new loader, place it in
 `invokeai/backend/model_manager/load/model_loaders`. Inherit from
-`ModelLoader` and use the `@AnyModelLoader.register()` decorator to
+`ModelLoader` and use the `@ModelLoaderRegistry.register()` decorator to
 indicate what type of models the loader can handle.
 
 Here is a complete example from `generic_diffusers.py`, which is able
@@ -1674,12 +1661,11 @@ from invokeai.backend.model_manager import (
     ModelType,
     SubModelType,
 )
-from ..load_base import AnyModelLoader
-from ..load_default import ModelLoader
+from .. import ModelLoader, ModelLoaderRegistry
 
 
-@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.CLIPVision, format=ModelFormat.Diffusers)
-@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.T2IAdapter, format=ModelFormat.Diffusers)
+@ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.CLIPVision, format=ModelFormat.Diffusers)
+@ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.T2IAdapter, format=ModelFormat.Diffusers)
 class GenericDiffusersLoader(ModelLoader):
     """Class to load simple diffusers models."""
 
@@ -1728,3 +1714,74 @@ model. It does whatever it needs to do to get the model into diffusers
 format, and returns the Path of the resulting model. (The path should
 ordinarily be the same as `output_path`.)
 
+## The ModelManagerService object
+
+For convenience, the API provides a `ModelManagerService` object which
+gives a single point of access to the major model manager
+services. This object is created at initialization time and can be
+found in the global `ApiDependencies.invoker.services.model_manager`
+object, or in `context.services.model_manager` from within an
+invocation.
+
+In the examples below, we have retrieved the manager using:
+```
+mm = ApiDependencies.invoker.services.model_manager
+```
+
+The following properties and methods will be available:
+
+### mm.store
+
+This retrieves the `ModelRecordService` associated with the
+manager. Example:
+
+```
+configs = mm.store.get_model_by_attr(name='stable-diffusion-v1-5')
+```
+
+### mm.install
+
+This retrieves the `ModelInstallService` associated with the manager.
+Example:
+
+```
+job = mm.install.heuristic_import(`https://civitai.com/models/58390/detail-tweaker-lora-lora`)
+```
+
+### mm.load
+
+This retrieves the `ModelLoaderService` associated with the manager. Example:
+
+```
+configs = mm.store.get_model_by_attr(name='stable-diffusion-v1-5')
+assert len(configs) > 0
+
+loaded_model = mm.load.load_model(configs[0])
+```
+
+The model manager also offers a few convenience shortcuts for loading
+models:
+
+### mm.load_model_by_config(model_config, [submodel], [context]) -> LoadedModel
+
+Same as `mm.load.load_model()`.
+
+### mm.load_model_by_attr(model_name, base_model, model_type, [submodel], [context]) -> LoadedModel
+
+This accepts the combination of the model's name, type and base, which
+it passes to the model record config store for retrieval. If a unique
+model config is found, this method returns a `LoadedModel`. It can
+raise the following exceptions:
+
+```
+UnknownModelException -- model with these attributes not known
+NotImplementedException -- the loader doesn't know how to load this type of model
+ValueError -- more than one model matches this combination of base/type/name
+```
+
+### mm.load_model_by_key(key, [submodel], [context]) -> LoadedModel
+
+This method takes a model key, looks it up using the
+`ModelRecordServiceBase` object in `mm.store`, and passes the returned
+model configuration to `load_model_by_config()`.  It may raise a
+`NotImplementedException`.
diff --git a/invokeai/app/api/routers/model_manager_v2.py b/invokeai/app/api/routers/model_manager.py
similarity index 97%
rename from invokeai/app/api/routers/model_manager_v2.py
rename to invokeai/app/api/routers/model_manager.py
index 2471e0d8c9..6b7111dd2c 100644
--- a/invokeai/app/api/routers/model_manager_v2.py
+++ b/invokeai/app/api/routers/model_manager.py
@@ -35,7 +35,7 @@ from invokeai.backend.model_manager.metadata import AnyModelRepoMetadata
 
 from ..dependencies import ApiDependencies
 
-model_manager_v2_router = APIRouter(prefix="/v2/models", tags=["model_manager_v2"])
+model_manager_router = APIRouter(prefix="/v2/models", tags=["model_manager"])
 
 
 class ModelsList(BaseModel):
@@ -135,7 +135,7 @@ example_model_metadata = {
 ##############################################################################
 
 
-@model_manager_v2_router.get(
+@model_manager_router.get(
     "/",
     operation_id="list_model_records",
 )
@@ -164,7 +164,7 @@ async def list_model_records(
     return ModelsList(models=found_models)
 
 
-@model_manager_v2_router.get(
+@model_manager_router.get(
     "/i/{key}",
     operation_id="get_model_record",
     responses={
@@ -188,7 +188,7 @@ async def get_model_record(
         raise HTTPException(status_code=404, detail=str(e))
 
 
-@model_manager_v2_router.get("/summary", operation_id="list_model_summary")
+@model_manager_router.get("/summary", operation_id="list_model_summary")
 async def list_model_summary(
     page: int = Query(default=0, description="The page to get"),
     per_page: int = Query(default=10, description="The number of models per page"),
@@ -200,7 +200,7 @@ async def list_model_summary(
     return results
 
 
-@model_manager_v2_router.get(
+@model_manager_router.get(
     "/meta/i/{key}",
     operation_id="get_model_metadata",
     responses={
@@ -223,7 +223,7 @@ async def get_model_metadata(
     return result
 
 
-@model_manager_v2_router.get(
+@model_manager_router.get(
     "/tags",
     operation_id="list_tags",
 )
@@ -234,7 +234,7 @@ async def list_tags() -> Set[str]:
     return result
 
 
-@model_manager_v2_router.get(
+@model_manager_router.get(
     "/tags/search",
     operation_id="search_by_metadata_tags",
 )
@@ -247,7 +247,7 @@ async def search_by_metadata_tags(
     return ModelsList(models=results)
 
 
-@model_manager_v2_router.patch(
+@model_manager_router.patch(
     "/i/{key}",
     operation_id="update_model_record",
     responses={
@@ -281,7 +281,7 @@ async def update_model_record(
     return model_response
 
 
-@model_manager_v2_router.delete(
+@model_manager_router.delete(
     "/i/{key}",
     operation_id="del_model_record",
     responses={
@@ -311,7 +311,7 @@ async def del_model_record(
         raise HTTPException(status_code=404, detail=str(e))
 
 
-@model_manager_v2_router.post(
+@model_manager_router.post(
     "/i/",
     operation_id="add_model_record",
     responses={
@@ -349,7 +349,7 @@ async def add_model_record(
     return result
 
 
-@model_manager_v2_router.post(
+@model_manager_router.post(
     "/heuristic_import",
     operation_id="heuristic_import_model",
     responses={
@@ -416,7 +416,7 @@ async def heuristic_import(
     return result
 
 
-@model_manager_v2_router.post(
+@model_manager_router.post(
     "/install",
     operation_id="import_model",
     responses={
@@ -516,7 +516,7 @@ async def import_model(
     return result
 
 
-@model_manager_v2_router.get(
+@model_manager_router.get(
     "/import",
     operation_id="list_model_install_jobs",
 )
@@ -544,7 +544,7 @@ async def list_model_install_jobs() -> List[ModelInstallJob]:
     return jobs
 
 
-@model_manager_v2_router.get(
+@model_manager_router.get(
     "/import/{id}",
     operation_id="get_model_install_job",
     responses={
@@ -564,7 +564,7 @@ async def get_model_install_job(id: int = Path(description="Model install id"))
         raise HTTPException(status_code=404, detail=str(e))
 
 
-@model_manager_v2_router.delete(
+@model_manager_router.delete(
     "/import/{id}",
     operation_id="cancel_model_install_job",
     responses={
@@ -583,7 +583,7 @@ async def cancel_model_install_job(id: int = Path(description="Model install job
     installer.cancel_job(job)
 
 
-@model_manager_v2_router.patch(
+@model_manager_router.patch(
     "/import",
     operation_id="prune_model_install_jobs",
     responses={
@@ -597,7 +597,7 @@ async def prune_model_install_jobs() -> Response:
     return Response(status_code=204)
 
 
-@model_manager_v2_router.patch(
+@model_manager_router.patch(
     "/sync",
     operation_id="sync_models_to_config",
     responses={
@@ -616,7 +616,7 @@ async def sync_models_to_config() -> Response:
     return Response(status_code=204)
 
 
-@model_manager_v2_router.put(
+@model_manager_router.put(
     "/convert/{key}",
     operation_id="convert_model",
     responses={
@@ -694,7 +694,7 @@ async def convert_model(
     return new_config
 
 
-@model_manager_v2_router.put(
+@model_manager_router.put(
     "/merge",
     operation_id="merge",
     responses={
diff --git a/invokeai/app/api/routers/models.py b/invokeai/app/api/routers/models.py
deleted file mode 100644
index 0aa7aa0ecb..0000000000
--- a/invokeai/app/api/routers/models.py
+++ /dev/null
@@ -1,426 +0,0 @@
-# Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654), 2023 Kent Keirsey (https://github.com/hipsterusername), 2023 Lincoln D. Stein
-
-import pathlib
-from typing import Annotated, List, Literal, Optional, Union
-
-from fastapi import Body, Path, Query, Response
-from fastapi.routing import APIRouter
-from pydantic import BaseModel, ConfigDict, Field, TypeAdapter
-from starlette.exceptions import HTTPException
-
-from invokeai.backend.model_management import BaseModelType, MergeInterpolationMethod, ModelType
-from invokeai.backend.model_management.models import (
-    OPENAPI_MODEL_CONFIGS,
-    InvalidModelException,
-    ModelNotFoundException,
-    SchedulerPredictionType,
-)
-
-from ..dependencies import ApiDependencies
-
-models_router = APIRouter(prefix="/v1/models", tags=["models"])
-
-UpdateModelResponse = Union[tuple(OPENAPI_MODEL_CONFIGS)]
-UpdateModelResponseValidator = TypeAdapter(UpdateModelResponse)
-
-ImportModelResponse = Union[tuple(OPENAPI_MODEL_CONFIGS)]
-ImportModelResponseValidator = TypeAdapter(ImportModelResponse)
-
-ConvertModelResponse = Union[tuple(OPENAPI_MODEL_CONFIGS)]
-ConvertModelResponseValidator = TypeAdapter(ConvertModelResponse)
-
-MergeModelResponse = Union[tuple(OPENAPI_MODEL_CONFIGS)]
-ImportModelAttributes = Union[tuple(OPENAPI_MODEL_CONFIGS)]
-
-
-class ModelsList(BaseModel):
-    models: list[Union[tuple(OPENAPI_MODEL_CONFIGS)]]
-
-    model_config = ConfigDict(use_enum_values=True)
-
-
-ModelsListValidator = TypeAdapter(ModelsList)
-
-
-@models_router.get(
-    "/",
-    operation_id="list_models",
-    responses={200: {"model": ModelsList}},
-)
-async def list_models(
-    base_models: Optional[List[BaseModelType]] = Query(default=None, description="Base models to include"),
-    model_type: Optional[ModelType] = Query(default=None, description="The type of model to get"),
-) -> ModelsList:
-    """Gets a list of models"""
-    if base_models and len(base_models) > 0:
-        models_raw = []
-        for base_model in base_models:
-            models_raw.extend(ApiDependencies.invoker.services.model_manager.list_models(base_model, model_type))
-    else:
-        models_raw = ApiDependencies.invoker.services.model_manager.list_models(None, model_type)
-    models = ModelsListValidator.validate_python({"models": models_raw})
-    return models
-
-
-@models_router.patch(
-    "/{base_model}/{model_type}/{model_name}",
-    operation_id="update_model",
-    responses={
-        200: {"description": "The model was updated successfully"},
-        400: {"description": "Bad request"},
-        404: {"description": "The model could not be found"},
-        409: {"description": "There is already a model corresponding to the new name"},
-    },
-    status_code=200,
-    response_model=UpdateModelResponse,
-)
-async def update_model(
-    base_model: BaseModelType = Path(description="Base model"),
-    model_type: ModelType = Path(description="The type of model"),
-    model_name: str = Path(description="model name"),
-    info: Union[tuple(OPENAPI_MODEL_CONFIGS)] = Body(description="Model configuration"),
-) -> UpdateModelResponse:
-    """Update model contents with a new config. If the model name or base fields are changed, then the model is renamed."""
-    logger = ApiDependencies.invoker.services.logger
-
-    try:
-        previous_info = ApiDependencies.invoker.services.model_manager.list_model(
-            model_name=model_name,
-            base_model=base_model,
-            model_type=model_type,
-        )
-
-        # rename operation requested
-        if info.model_name != model_name or info.base_model != base_model:
-            ApiDependencies.invoker.services.model_manager.rename_model(
-                base_model=base_model,
-                model_type=model_type,
-                model_name=model_name,
-                new_name=info.model_name,
-                new_base=info.base_model,
-            )
-            logger.info(f"Successfully renamed {base_model.value}/{model_name}=>{info.base_model}/{info.model_name}")
-            # update information to support an update of attributes
-            model_name = info.model_name
-            base_model = info.base_model
-            new_info = ApiDependencies.invoker.services.model_manager.list_model(
-                model_name=model_name,
-                base_model=base_model,
-                model_type=model_type,
-            )
-            if new_info.get("path") != previous_info.get(
-                "path"
-            ):  # model manager moved model path during rename - don't overwrite it
-                info.path = new_info.get("path")
-
-        # replace empty string values with None/null to avoid phenomenon of vae: ''
-        info_dict = info.model_dump()
-        info_dict = {x: info_dict[x] if info_dict[x] else None for x in info_dict.keys()}
-
-        ApiDependencies.invoker.services.model_manager.update_model(
-            model_name=model_name,
-            base_model=base_model,
-            model_type=model_type,
-            model_attributes=info_dict,
-        )
-
-        model_raw = ApiDependencies.invoker.services.model_manager.list_model(
-            model_name=model_name,
-            base_model=base_model,
-            model_type=model_type,
-        )
-        model_response = UpdateModelResponseValidator.validate_python(model_raw)
-    except ModelNotFoundException as e:
-        raise HTTPException(status_code=404, detail=str(e))
-    except ValueError as e:
-        logger.error(str(e))
-        raise HTTPException(status_code=409, detail=str(e))
-    except Exception as e:
-        logger.error(str(e))
-        raise HTTPException(status_code=400, detail=str(e))
-
-    return model_response
-
-
-@models_router.post(
-    "/import",
-    operation_id="import_model",
-    responses={
-        201: {"description": "The model imported successfully"},
-        404: {"description": "The model could not be found"},
-        415: {"description": "Unrecognized file/folder format"},
-        424: {"description": "The model appeared to import successfully, but could not be found in the model manager"},
-        409: {"description": "There is already a model corresponding to this path or repo_id"},
-    },
-    status_code=201,
-    response_model=ImportModelResponse,
-)
-async def import_model(
-    location: str = Body(description="A model path, repo_id or URL to import"),
-    prediction_type: Optional[Literal["v_prediction", "epsilon", "sample"]] = Body(
-        description="Prediction type for SDv2 checkpoints and rare SDv1 checkpoints",
-        default=None,
-    ),
-) -> ImportModelResponse:
-    """Add a model using its local path, repo_id, or remote URL. Model characteristics will be probed and configured automatically"""
-
-    location = location.strip("\"' ")
-    items_to_import = {location}
-    prediction_types = {x.value: x for x in SchedulerPredictionType}
-    logger = ApiDependencies.invoker.services.logger
-
-    try:
-        installed_models = ApiDependencies.invoker.services.model_manager.heuristic_import(
-            items_to_import=items_to_import,
-            prediction_type_helper=lambda x: prediction_types.get(prediction_type),
-        )
-        info = installed_models.get(location)
-
-        if not info:
-            logger.error("Import failed")
-            raise HTTPException(status_code=415)
-
-        logger.info(f"Successfully imported {location}, got {info}")
-        model_raw = ApiDependencies.invoker.services.model_manager.list_model(
-            model_name=info.name, base_model=info.base_model, model_type=info.model_type
-        )
-        return ImportModelResponseValidator.validate_python(model_raw)
-
-    except ModelNotFoundException as e:
-        logger.error(str(e))
-        raise HTTPException(status_code=404, detail=str(e))
-    except InvalidModelException as e:
-        logger.error(str(e))
-        raise HTTPException(status_code=415)
-    except ValueError as e:
-        logger.error(str(e))
-        raise HTTPException(status_code=409, detail=str(e))
-
-
-@models_router.post(
-    "/add",
-    operation_id="add_model",
-    responses={
-        201: {"description": "The model added successfully"},
-        404: {"description": "The model could not be found"},
-        424: {"description": "The model appeared to add successfully, but could not be found in the model manager"},
-        409: {"description": "There is already a model corresponding to this path or repo_id"},
-    },
-    status_code=201,
-    response_model=ImportModelResponse,
-)
-async def add_model(
-    info: Union[tuple(OPENAPI_MODEL_CONFIGS)] = Body(description="Model configuration"),
-) -> ImportModelResponse:
-    """Add a model using the configuration information appropriate for its type. Only local models can be added by path"""
-
-    logger = ApiDependencies.invoker.services.logger
-
-    try:
-        ApiDependencies.invoker.services.model_manager.add_model(
-            info.model_name,
-            info.base_model,
-            info.model_type,
-            model_attributes=info.model_dump(),
-        )
-        logger.info(f"Successfully added {info.model_name}")
-        model_raw = ApiDependencies.invoker.services.model_manager.list_model(
-            model_name=info.model_name,
-            base_model=info.base_model,
-            model_type=info.model_type,
-        )
-        return ImportModelResponseValidator.validate_python(model_raw)
-    except ModelNotFoundException as e:
-        logger.error(str(e))
-        raise HTTPException(status_code=404, detail=str(e))
-    except ValueError as e:
-        logger.error(str(e))
-        raise HTTPException(status_code=409, detail=str(e))
-
-
-@models_router.delete(
-    "/{base_model}/{model_type}/{model_name}",
-    operation_id="del_model",
-    responses={
-        204: {"description": "Model deleted successfully"},
-        404: {"description": "Model not found"},
-    },
-    status_code=204,
-    response_model=None,
-)
-async def delete_model(
-    base_model: BaseModelType = Path(description="Base model"),
-    model_type: ModelType = Path(description="The type of model"),
-    model_name: str = Path(description="model name"),
-) -> Response:
-    """Delete Model"""
-    logger = ApiDependencies.invoker.services.logger
-
-    try:
-        ApiDependencies.invoker.services.model_manager.del_model(
-            model_name, base_model=base_model, model_type=model_type
-        )
-        logger.info(f"Deleted model: {model_name}")
-        return Response(status_code=204)
-    except ModelNotFoundException as e:
-        logger.error(str(e))
-        raise HTTPException(status_code=404, detail=str(e))
-
-
-@models_router.put(
-    "/convert/{base_model}/{model_type}/{model_name}",
-    operation_id="convert_model",
-    responses={
-        200: {"description": "Model converted successfully"},
-        400: {"description": "Bad request"},
-        404: {"description": "Model not found"},
-    },
-    status_code=200,
-    response_model=ConvertModelResponse,
-)
-async def convert_model(
-    base_model: BaseModelType = Path(description="Base model"),
-    model_type: ModelType = Path(description="The type of model"),
-    model_name: str = Path(description="model name"),
-    convert_dest_directory: Optional[str] = Query(
-        default=None, description="Save the converted model to the designated directory"
-    ),
-) -> ConvertModelResponse:
-    """Convert a checkpoint model into a diffusers model, optionally saving to the indicated destination directory, or `models` if none."""
-    logger = ApiDependencies.invoker.services.logger
-    try:
-        logger.info(f"Converting model: {model_name}")
-        dest = pathlib.Path(convert_dest_directory) if convert_dest_directory else None
-        ApiDependencies.invoker.services.model_manager.convert_model(
-            model_name,
-            base_model=base_model,
-            model_type=model_type,
-            convert_dest_directory=dest,
-        )
-        model_raw = ApiDependencies.invoker.services.model_manager.list_model(
-            model_name, base_model=base_model, model_type=model_type
-        )
-        response = ConvertModelResponseValidator.validate_python(model_raw)
-    except ModelNotFoundException as e:
-        raise HTTPException(status_code=404, detail=f"Model '{model_name}' not found: {str(e)}")
-    except ValueError as e:
-        raise HTTPException(status_code=400, detail=str(e))
-    return response
-
-
-@models_router.get(
-    "/search",
-    operation_id="search_for_models",
-    responses={
-        200: {"description": "Directory searched successfully"},
-        404: {"description": "Invalid directory path"},
-    },
-    status_code=200,
-    response_model=List[pathlib.Path],
-)
-async def search_for_models(
-    search_path: pathlib.Path = Query(description="Directory path to search for models"),
-) -> List[pathlib.Path]:
-    if not search_path.is_dir():
-        raise HTTPException(
-            status_code=404,
-            detail=f"The search path '{search_path}' does not exist or is not directory",
-        )
-    return ApiDependencies.invoker.services.model_manager.search_for_models(search_path)
-
-
-@models_router.get(
-    "/ckpt_confs",
-    operation_id="list_ckpt_configs",
-    responses={
-        200: {"description": "paths retrieved successfully"},
-    },
-    status_code=200,
-    response_model=List[pathlib.Path],
-)
-async def list_ckpt_configs() -> List[pathlib.Path]:
-    """Return a list of the legacy checkpoint configuration files stored in `ROOT/configs/stable-diffusion`, relative to ROOT."""
-    return ApiDependencies.invoker.services.model_manager.list_checkpoint_configs()
-
-
-@models_router.post(
-    "/sync",
-    operation_id="sync_to_config",
-    responses={
-        201: {"description": "synchronization successful"},
-    },
-    status_code=201,
-    response_model=bool,
-)
-async def sync_to_config() -> bool:
-    """Call after making changes to models.yaml, autoimport directories or models directory to synchronize
-    in-memory data structures with disk data structures."""
-    ApiDependencies.invoker.services.model_manager.sync_to_config()
-    return True
-
-
-# There's some weird pydantic-fastapi behaviour that requires this to be a separate class
-# TODO: After a few updates, see if it works inside the route operation handler?
-class MergeModelsBody(BaseModel):
-    model_names: List[str] = Field(description="model name", min_length=2, max_length=3)
-    merged_model_name: Optional[str] = Field(description="Name of destination model")
-    alpha: Optional[float] = Field(description="Alpha weighting strength to apply to 2d and 3d models", default=0.5)
-    interp: Optional[MergeInterpolationMethod] = Field(description="Interpolation method")
-    force: Optional[bool] = Field(
-        description="Force merging of models created with different versions of diffusers",
-        default=False,
-    )
-
-    merge_dest_directory: Optional[str] = Field(
-        description="Save the merged model to the designated directory (with 'merged_model_name' appended)",
-        default=None,
-    )
-
-    model_config = ConfigDict(protected_namespaces=())
-
-
-@models_router.put(
-    "/merge/{base_model}",
-    operation_id="merge_models",
-    responses={
-        200: {"description": "Model converted successfully"},
-        400: {"description": "Incompatible models"},
-        404: {"description": "One or more models not found"},
-    },
-    status_code=200,
-    response_model=MergeModelResponse,
-)
-async def merge_models(
-    body: Annotated[MergeModelsBody, Body(description="Model configuration", embed=True)],
-    base_model: BaseModelType = Path(description="Base model"),
-) -> MergeModelResponse:
-    """Convert a checkpoint model into a diffusers model"""
-    logger = ApiDependencies.invoker.services.logger
-    try:
-        logger.info(
-            f"Merging models: {body.model_names} into {body.merge_dest_directory or '<MODELS>'}/{body.merged_model_name}"
-        )
-        dest = pathlib.Path(body.merge_dest_directory) if body.merge_dest_directory else None
-        result = ApiDependencies.invoker.services.model_manager.merge_models(
-            model_names=body.model_names,
-            base_model=base_model,
-            merged_model_name=body.merged_model_name or "+".join(body.model_names),
-            alpha=body.alpha,
-            interp=body.interp,
-            force=body.force,
-            merge_dest_directory=dest,
-        )
-        model_raw = ApiDependencies.invoker.services.model_manager.list_model(
-            result.name,
-            base_model=base_model,
-            model_type=ModelType.Main,
-        )
-        response = ConvertModelResponseValidator.validate_python(model_raw)
-    except ModelNotFoundException:
-        raise HTTPException(
-            status_code=404,
-            detail=f"One or more of the models '{body.model_names}' not found",
-        )
-    except ValueError as e:
-        raise HTTPException(status_code=400, detail=str(e))
-    return response
diff --git a/invokeai/app/api_app.py b/invokeai/app/api_app.py
index 1831b54c13..149d47fb96 100644
--- a/invokeai/app/api_app.py
+++ b/invokeai/app/api_app.py
@@ -48,7 +48,7 @@ if True:  # hack to make flake8 happy with imports coming after setting up the c
         boards,
         download_queue,
         images,
-        model_manager_v2,
+        model_manager,
         session_queue,
         sessions,
         utilities,
@@ -113,7 +113,7 @@ async def shutdown_event() -> None:
 app.include_router(sessions.session_router, prefix="/api")
 
 app.include_router(utilities.utilities_router, prefix="/api")
-app.include_router(model_manager_v2.model_manager_v2_router, prefix="/api")
+app.include_router(model_manager.model_manager_router, prefix="/api")
 app.include_router(download_queue.download_queue_router, prefix="/api")
 app.include_router(images.images_router, prefix="/api")
 app.include_router(boards.boards_router, prefix="/api")
@@ -175,21 +175,23 @@ def custom_openapi() -> dict[str, Any]:
         invoker_schema["class"] = "invocation"
         openapi_schema["components"]["schemas"][f"{output_type_title}"]["class"] = "output"
 
-    from invokeai.backend.model_management.models import get_model_config_enums
+    # This code no longer seems to be necessary?
+    # Leave it here just in case
+    #
+    # from invokeai.backend.model_manager import get_model_config_formats
+    # formats = get_model_config_formats()
+    # for model_config_name, enum_set in formats.items():
 
-    for model_config_format_enum in set(get_model_config_enums()):
-        name = model_config_format_enum.__qualname__
+    #     if model_config_name in openapi_schema["components"]["schemas"]:
+    #         # print(f"Config with name {name} already defined")
+    #         continue
 
-        if name in openapi_schema["components"]["schemas"]:
-            # print(f"Config with name {name} already defined")
-            continue
-
-        openapi_schema["components"]["schemas"][name] = {
-            "title": name,
-            "description": "An enumeration.",
-            "type": "string",
-            "enum": [v.value for v in model_config_format_enum],
-        }
+    #     openapi_schema["components"]["schemas"][model_config_name] = {
+    #         "title": model_config_name,
+    #         "description": "An enumeration.",
+    #         "type": "string",
+    #         "enum": [v.value for v in enum_set],
+    #     }
 
     app.openapi_schema = openapi_schema
     return app.openapi_schema
diff --git a/invokeai/app/invocations/compel.py b/invokeai/app/invocations/compel.py
index 593121ba60..517da4375e 100644
--- a/invokeai/app/invocations/compel.py
+++ b/invokeai/app/invocations/compel.py
@@ -18,15 +18,15 @@ from invokeai.app.services.model_records import UnknownModelException
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.app.util.ti_utils import extract_ti_triggers_from_prompt
 from invokeai.backend.lora import LoRAModelRaw
-from invokeai.backend.model_patcher import ModelPatcher
-from invokeai.backend.textual_inversion import TextualInversionModelRaw
 from invokeai.backend.model_manager import ModelType
+from invokeai.backend.model_patcher import ModelPatcher
 from invokeai.backend.stable_diffusion.diffusion.conditioning_data import (
     BasicConditioningInfo,
     ConditioningFieldData,
     ExtraConditioningInfo,
     SDXLConditioningInfo,
 )
+from invokeai.backend.textual_inversion import TextualInversionModelRaw
 from invokeai.backend.util.devices import torch_dtype
 
 from .baseinvocation import (
diff --git a/invokeai/app/services/config/config_base.py b/invokeai/app/services/config/config_base.py
index 983df6b468..c73aa43809 100644
--- a/invokeai/app/services/config/config_base.py
+++ b/invokeai/app/services/config/config_base.py
@@ -68,7 +68,7 @@ class InvokeAISettings(BaseSettings):
         return OmegaConf.to_yaml(conf)
 
     @classmethod
-    def add_parser_arguments(cls, parser) -> None:
+    def add_parser_arguments(cls, parser: ArgumentParser) -> None:
         """Dynamically create arguments for a settings parser."""
         if "type" in get_type_hints(cls):
             settings_stanza = get_args(get_type_hints(cls)["type"])[0]
diff --git a/invokeai/app/services/invocation_stats/invocation_stats_base.py b/invokeai/app/services/invocation_stats/invocation_stats_base.py
index 22624a6579..ec8a453323 100644
--- a/invokeai/app/services/invocation_stats/invocation_stats_base.py
+++ b/invokeai/app/services/invocation_stats/invocation_stats_base.py
@@ -29,8 +29,8 @@ writes to the system log is stored in InvocationServices.performance_statistics.
 """
 
 from abc import ABC, abstractmethod
-from contextlib import AbstractContextManager
 from pathlib import Path
+from typing import Iterator
 
 from invokeai.app.invocations.baseinvocation import BaseInvocation
 from invokeai.app.services.invocation_stats.invocation_stats_common import InvocationStatsSummary
@@ -40,18 +40,17 @@ class InvocationStatsServiceBase(ABC):
     "Abstract base class for recording node memory/time performance statistics"
 
     @abstractmethod
-    def __init__(self):
+    def __init__(self) -> None:
         """
         Initialize the InvocationStatsService and reset counters to zero
         """
-        pass
 
     @abstractmethod
     def collect_stats(
         self,
         invocation: BaseInvocation,
         graph_execution_state_id: str,
-    ) -> AbstractContextManager:
+    ) -> Iterator[None]:
         """
         Return a context object that will capture the statistics on the execution
         of invocaation. Use with: to place around the part of the code that executes the invocation.
@@ -61,7 +60,7 @@ class InvocationStatsServiceBase(ABC):
         pass
 
     @abstractmethod
-    def reset_stats(self, graph_execution_state_id: str):
+    def reset_stats(self, graph_execution_state_id: str) -> None:
         """
         Reset all statistics for the indicated graph.
         :param graph_execution_state_id: The id of the session whose stats to reset.
@@ -70,7 +69,7 @@ class InvocationStatsServiceBase(ABC):
         pass
 
     @abstractmethod
-    def log_stats(self, graph_execution_state_id: str):
+    def log_stats(self, graph_execution_state_id: str) -> None:
         """
         Write out the accumulated statistics to the log or somewhere else.
         :param graph_execution_state_id: The id of the session whose stats to log.
diff --git a/invokeai/app/services/model_install/model_install_base.py b/invokeai/app/services/model_install/model_install_base.py
index 2f03db0af7..080219af75 100644
--- a/invokeai/app/services/model_install/model_install_base.py
+++ b/invokeai/app/services/model_install/model_install_base.py
@@ -14,7 +14,7 @@ from typing_extensions import Annotated
 
 from invokeai.app.services.config import InvokeAIAppConfig
 from invokeai.app.services.download import DownloadJob, DownloadQueueServiceBase
-from invokeai.app.services.events import EventServiceBase
+from invokeai.app.services.events.events_base import EventServiceBase
 from invokeai.app.services.invoker import Invoker
 from invokeai.app.services.model_records import ModelRecordServiceBase
 from invokeai.backend.model_manager import AnyModelConfig, ModelRepoVariant
diff --git a/invokeai/app/services/model_load/model_load_base.py b/invokeai/app/services/model_load/model_load_base.py
index f4dd905135..cc80333e93 100644
--- a/invokeai/app/services/model_load/model_load_base.py
+++ b/invokeai/app/services/model_load/model_load_base.py
@@ -5,7 +5,7 @@ from abc import ABC, abstractmethod
 from typing import Optional
 
 from invokeai.app.services.shared.invocation_context import InvocationContextData
-from invokeai.backend.model_manager import AnyModel, AnyModelConfig, BaseModelType, ModelType, SubModelType
+from invokeai.backend.model_manager import AnyModel, AnyModelConfig, SubModelType
 from invokeai.backend.model_manager.load import LoadedModel
 from invokeai.backend.model_manager.load.convert_cache import ModelConvertCacheBase
 from invokeai.backend.model_manager.load.model_cache.model_cache_base import ModelCacheBase
@@ -15,23 +15,7 @@ class ModelLoadServiceBase(ABC):
     """Wrapper around AnyModelLoader."""
 
     @abstractmethod
-    def load_model_by_key(
-        self,
-        key: str,
-        submodel_type: Optional[SubModelType] = None,
-        context_data: Optional[InvocationContextData] = None,
-    ) -> LoadedModel:
-        """
-        Given a model's key, load it and return the LoadedModel object.
-
-        :param key: Key of model config to be fetched.
-        :param submodel: For main (pipeline models), the submodel to fetch.
-        :param context_data: Invocation context data used for event reporting
-        """
-        pass
-
-    @abstractmethod
-    def load_model_by_config(
+    def load_model(
         self,
         model_config: AnyModelConfig,
         submodel_type: Optional[SubModelType] = None,
@@ -44,34 +28,6 @@ class ModelLoadServiceBase(ABC):
         :param submodel: For main (pipeline models), the submodel to fetch.
         :param context_data: Invocation context data used for event reporting
         """
-        pass
-
-    @abstractmethod
-    def load_model_by_attr(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-        submodel: Optional[SubModelType] = None,
-        context_data: Optional[InvocationContextData] = None,
-    ) -> LoadedModel:
-        """
-        Given a model's attributes, search the database for it, and if found, load and return the LoadedModel object.
-
-        This is provided for API compatability with the get_model() method
-        in the original model manager. However, note that LoadedModel is
-        not the same as the original ModelInfo that ws returned.
-
-        :param model_name: Name of to be fetched.
-        :param base_model: Base model
-        :param model_type: Type of the model
-        :param submodel: For main (pipeline models), the submodel to fetch
-        :param context_data: The invocation context data.
-
-        Exceptions: UnknownModelException -- model with these attributes not known
-                    NotImplementedException -- a model loader was not provided at initialization time
-                    ValueError -- more than one model matches this combination
-        """
 
     @property
     @abstractmethod
diff --git a/invokeai/app/services/model_load/model_load_default.py b/invokeai/app/services/model_load/model_load_default.py
index fa96a4672d..15c6283d8a 100644
--- a/invokeai/app/services/model_load/model_load_default.py
+++ b/invokeai/app/services/model_load/model_load_default.py
@@ -1,15 +1,18 @@
 # Copyright (c) 2024 Lincoln D. Stein and the InvokeAI Team
 """Implementation of model loader service."""
 
-from typing import Optional
+from typing import Optional, Type
 
 from invokeai.app.services.config import InvokeAIAppConfig
 from invokeai.app.services.invocation_processor.invocation_processor_common import CanceledException
 from invokeai.app.services.invoker import Invoker
-from invokeai.app.services.model_records import ModelRecordServiceBase, UnknownModelException
 from invokeai.app.services.shared.invocation_context import InvocationContextData
-from invokeai.backend.model_manager import AnyModel, AnyModelConfig, BaseModelType, ModelType, SubModelType
-from invokeai.backend.model_manager.load import AnyModelLoader, LoadedModel, ModelCache, ModelConvertCache
+from invokeai.backend.model_manager import AnyModel, AnyModelConfig, SubModelType
+from invokeai.backend.model_manager.load import (
+    LoadedModel,
+    ModelLoaderRegistry,
+    ModelLoaderRegistryBase,
+)
 from invokeai.backend.model_manager.load.convert_cache import ModelConvertCacheBase
 from invokeai.backend.model_manager.load.model_cache.model_cache_base import ModelCacheBase
 from invokeai.backend.util.logging import InvokeAILogger
@@ -18,25 +21,23 @@ from .model_load_base import ModelLoadServiceBase
 
 
 class ModelLoadService(ModelLoadServiceBase):
-    """Wrapper around AnyModelLoader."""
+    """Wrapper around ModelLoaderRegistry."""
 
     def __init__(
-            self,
-            app_config: InvokeAIAppConfig,
-            record_store: ModelRecordServiceBase,
-            ram_cache: ModelCacheBase[AnyModel],
-            convert_cache: ModelConvertCacheBase,
+        self,
+        app_config: InvokeAIAppConfig,
+        ram_cache: ModelCacheBase[AnyModel],
+        convert_cache: ModelConvertCacheBase,
+        registry: Optional[Type[ModelLoaderRegistryBase]] = ModelLoaderRegistry,
     ):
         """Initialize the model load service."""
         logger = InvokeAILogger.get_logger(self.__class__.__name__)
         logger.setLevel(app_config.log_level.upper())
-        self._store = record_store
-        self._any_loader = AnyModelLoader(
-            app_config=app_config,
-            logger=logger,
-            ram_cache=ram_cache,
-            convert_cache=convert_cache,
-        )
+        self._logger = logger
+        self._app_config = app_config
+        self._ram_cache = ram_cache
+        self._convert_cache = convert_cache
+        self._registry = registry
 
     def start(self, invoker: Invoker) -> None:
         self._invoker = invoker
@@ -44,63 +45,14 @@ class ModelLoadService(ModelLoadServiceBase):
     @property
     def ram_cache(self) -> ModelCacheBase[AnyModel]:
         """Return the RAM cache used by this loader."""
-        return self._any_loader.ram_cache
+        return self._ram_cache
 
     @property
     def convert_cache(self) -> ModelConvertCacheBase:
         """Return the checkpoint convert cache used by this loader."""
-        return self._any_loader.convert_cache
+        return self._convert_cache
 
-    def load_model_by_key(
-        self,
-        key: str,
-        submodel_type: Optional[SubModelType] = None,
-        context_data: Optional[InvocationContextData] = None,
-    ) -> LoadedModel:
-        """
-        Given a model's key, load it and return the LoadedModel object.
-
-        :param key: Key of model config to be fetched.
-        :param submodel: For main (pipeline models), the submodel to fetch.
-        :param context: Invocation context used for event reporting
-        """
-        config = self._store.get_model(key)
-        return self.load_model_by_config(config, submodel_type, context_data)
-
-    def load_model_by_attr(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-        submodel: Optional[SubModelType] = None,
-        context_data: Optional[InvocationContextData] = None,
-    ) -> LoadedModel:
-        """
-        Given a model's attributes, search the database for it, and if found, load and return the LoadedModel object.
-
-        This is provided for API compatability with the get_model() method
-        in the original model manager. However, note that LoadedModel is
-        not the same as the original ModelInfo that ws returned.
-
-        :param model_name: Name of to be fetched.
-        :param base_model: Base model
-        :param model_type: Type of the model
-        :param submodel: For main (pipeline models), the submodel to fetch
-        :param context: The invocation context.
-
-        Exceptions: UnknownModelException -- model with this key not known
-                    NotImplementedException -- a model loader was not provided at initialization time
-                    ValueError -- more than one model matches this combination
-        """
-        configs = self._store.search_by_attr(model_name, base_model, model_type)
-        if len(configs) == 0:
-            raise UnknownModelException(f"{base_model}/{model_type}/{model_name}: Unknown model")
-        elif len(configs) > 1:
-            raise ValueError(f"{base_model}/{model_type}/{model_name}: More than one model matches.")
-        else:
-            return self.load_model_by_key(configs[0].key, submodel)
-
-    def load_model_by_config(
+    def load_model(
         self,
         model_config: AnyModelConfig,
         submodel_type: Optional[SubModelType] = None,
@@ -118,7 +70,15 @@ class ModelLoadService(ModelLoadServiceBase):
                 context_data=context_data,
                 model_config=model_config,
             )
-        loaded_model = self._any_loader.load_model(model_config, submodel_type)
+
+        implementation, model_config, submodel_type = self._registry.get_implementation(model_config, submodel_type)  # type: ignore
+        loaded_model: LoadedModel = implementation(
+            app_config=self._app_config,
+            logger=self._logger,
+            ram_cache=self._ram_cache,
+            convert_cache=self._convert_cache,
+        ).load_model(model_config, submodel_type)
+
         if context_data:
             self._emit_load_event(
                 context_data=context_data,
diff --git a/invokeai/app/services/model_manager/__init__.py b/invokeai/app/services/model_manager/__init__.py
index 66707493f7..5455577266 100644
--- a/invokeai/app/services/model_manager/__init__.py
+++ b/invokeai/app/services/model_manager/__init__.py
@@ -3,7 +3,7 @@
 from invokeai.backend.model_manager import AnyModel, AnyModelConfig, BaseModelType, ModelType, SubModelType
 from invokeai.backend.model_manager.load import LoadedModel
 
-from .model_manager_default import ModelManagerServiceBase, ModelManagerService
+from .model_manager_default import ModelManagerService, ModelManagerServiceBase
 
 __all__ = [
     "ModelManagerServiceBase",
diff --git a/invokeai/app/services/model_manager/model_manager_base.py b/invokeai/app/services/model_manager/model_manager_base.py
index 1116c82ff1..c25aa6fb47 100644
--- a/invokeai/app/services/model_manager/model_manager_base.py
+++ b/invokeai/app/services/model_manager/model_manager_base.py
@@ -1,10 +1,14 @@
 # Copyright (c) 2023 Lincoln D. Stein and the InvokeAI Team
 
 from abc import ABC, abstractmethod
+from typing import Optional
 
 from typing_extensions import Self
 
 from invokeai.app.services.invoker import Invoker
+from invokeai.app.services.shared.invocation_context import InvocationContextData
+from invokeai.backend.model_manager.config import AnyModelConfig, BaseModelType, ModelType, SubModelType
+from invokeai.backend.model_manager.load.load_base import LoadedModel
 
 from ..config import InvokeAIAppConfig
 from ..download import DownloadQueueServiceBase
@@ -65,3 +69,32 @@ class ModelManagerServiceBase(ABC):
     @abstractmethod
     def stop(self, invoker: Invoker) -> None:
         pass
+
+    @abstractmethod
+    def load_model_by_config(
+        self,
+        model_config: AnyModelConfig,
+        submodel_type: Optional[SubModelType] = None,
+        context_data: Optional[InvocationContextData] = None,
+    ) -> LoadedModel:
+        pass
+
+    @abstractmethod
+    def load_model_by_key(
+        self,
+        key: str,
+        submodel_type: Optional[SubModelType] = None,
+        context_data: Optional[InvocationContextData] = None,
+    ) -> LoadedModel:
+        pass
+
+    @abstractmethod
+    def load_model_by_attr(
+        self,
+        model_name: str,
+        base_model: BaseModelType,
+        model_type: ModelType,
+        submodel: Optional[SubModelType] = None,
+        context_data: Optional[InvocationContextData] = None,
+    ) -> LoadedModel:
+        pass
diff --git a/invokeai/app/services/model_manager/model_manager_default.py b/invokeai/app/services/model_manager/model_manager_default.py
index b96341be69..d029f9e033 100644
--- a/invokeai/app/services/model_manager/model_manager_default.py
+++ b/invokeai/app/services/model_manager/model_manager_default.py
@@ -1,10 +1,14 @@
 # Copyright (c) 2023 Lincoln D. Stein and the InvokeAI Team
 """Implementation of ModelManagerServiceBase."""
 
+from typing import Optional
+
 from typing_extensions import Self
 
 from invokeai.app.services.invoker import Invoker
-from invokeai.backend.model_manager.load import ModelCache, ModelConvertCache
+from invokeai.app.services.shared.invocation_context import InvocationContextData
+from invokeai.backend.model_manager import AnyModelConfig, BaseModelType, LoadedModel, ModelType, SubModelType
+from invokeai.backend.model_manager.load import ModelCache, ModelConvertCache, ModelLoaderRegistry
 from invokeai.backend.util.logging import InvokeAILogger
 
 from ..config import InvokeAIAppConfig
@@ -12,7 +16,7 @@ from ..download import DownloadQueueServiceBase
 from ..events.events_base import EventServiceBase
 from ..model_install import ModelInstallService, ModelInstallServiceBase
 from ..model_load import ModelLoadService, ModelLoadServiceBase
-from ..model_records import ModelRecordServiceBase
+from ..model_records import ModelRecordServiceBase, UnknownModelException
 from .model_manager_base import ModelManagerServiceBase
 
 
@@ -58,6 +62,56 @@ class ModelManagerService(ModelManagerServiceBase):
             if hasattr(service, "stop"):
                 service.stop(invoker)
 
+    def load_model_by_config(
+        self,
+        model_config: AnyModelConfig,
+        submodel_type: Optional[SubModelType] = None,
+        context_data: Optional[InvocationContextData] = None,
+    ) -> LoadedModel:
+        return self.load.load_model(model_config, submodel_type, context_data)
+
+    def load_model_by_key(
+        self,
+        key: str,
+        submodel_type: Optional[SubModelType] = None,
+        context_data: Optional[InvocationContextData] = None,
+    ) -> LoadedModel:
+        config = self.store.get_model(key)
+        return self.load.load_model(config, submodel_type, context_data)
+
+    def load_model_by_attr(
+        self,
+        model_name: str,
+        base_model: BaseModelType,
+        model_type: ModelType,
+        submodel: Optional[SubModelType] = None,
+        context_data: Optional[InvocationContextData] = None,
+    ) -> LoadedModel:
+        """
+        Given a model's attributes, search the database for it, and if found, load and return the LoadedModel object.
+
+        This is provided for API compatability with the get_model() method
+        in the original model manager. However, note that LoadedModel is
+        not the same as the original ModelInfo that ws returned.
+
+        :param model_name: Name of to be fetched.
+        :param base_model: Base model
+        :param model_type: Type of the model
+        :param submodel: For main (pipeline models), the submodel to fetch
+        :param context: The invocation context.
+
+        Exceptions: UnknownModelException -- model with this key not known
+                    NotImplementedException -- a model loader was not provided at initialization time
+                    ValueError -- more than one model matches this combination
+        """
+        configs = self.store.search_by_attr(model_name, base_model, model_type)
+        if len(configs) == 0:
+            raise UnknownModelException(f"{base_model}/{model_type}/{model_name}: Unknown model")
+        elif len(configs) > 1:
+            raise ValueError(f"{base_model}/{model_type}/{model_name}: More than one model matches.")
+        else:
+            return self.load.load_model(configs[0], submodel, context_data)
+
     @classmethod
     def build_model_manager(
         cls,
@@ -82,9 +136,9 @@ class ModelManagerService(ModelManagerServiceBase):
         )
         loader = ModelLoadService(
             app_config=app_config,
-            record_store=model_record_service,
             ram_cache=ram_cache,
             convert_cache=convert_cache,
+            registry=ModelLoaderRegistry,
         )
         installer = ModelInstallService(
             app_config=app_config,
diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index 089d09f825..1395427a97 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -281,7 +281,7 @@ class ModelsInterface(InvocationContextInterface):
         # The model manager emits events as it loads the model. It needs the context data to build
         # the event payloads.
 
-        return self._services.model_manager.load.load_model_by_key(
+        return self._services.model_manager.load_model_by_key(
             key=key, submodel_type=submodel_type, context_data=self._context_data
         )
 
@@ -296,7 +296,7 @@ class ModelsInterface(InvocationContextInterface):
         :param model_type: Type of the model
         :param submodel: For main (pipeline models), the submodel to fetch
         """
-        return self._services.model_manager.load.load_model_by_attr(
+        return self._services.model_manager.load_model_by_attr(
             model_name=model_name,
             base_model=base_model,
             model_type=model_type,
diff --git a/invokeai/backend/install/migrate_to_3.py b/invokeai/backend/install/migrate_to_3.py
deleted file mode 100644
index e15eb23f5b..0000000000
--- a/invokeai/backend/install/migrate_to_3.py
+++ /dev/null
@@ -1,591 +0,0 @@
-"""
-Migrate the models directory and models.yaml file from an existing
-InvokeAI 2.3 installation to 3.0.0.
-"""
-
-import argparse
-import os
-import shutil
-import warnings
-from dataclasses import dataclass
-from pathlib import Path
-from typing import Union
-
-import diffusers
-import transformers
-import yaml
-from diffusers import AutoencoderKL, StableDiffusionPipeline
-from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
-from omegaconf import DictConfig, OmegaConf
-from transformers import AutoFeatureExtractor, BertTokenizerFast, CLIPTextModel, CLIPTokenizer
-
-import invokeai.backend.util.logging as logger
-from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.backend.model_management import ModelManager
-from invokeai.backend.model_management.model_probe import BaseModelType, ModelProbe, ModelProbeInfo, ModelType
-
-warnings.filterwarnings("ignore")
-transformers.logging.set_verbosity_error()
-diffusers.logging.set_verbosity_error()
-
-
-# holder for paths that we will migrate
-@dataclass
-class ModelPaths:
-    models: Path
-    embeddings: Path
-    loras: Path
-    controlnets: Path
-
-
-class MigrateTo3(object):
-    def __init__(
-        self,
-        from_root: Path,
-        to_models: Path,
-        model_manager: ModelManager,
-        src_paths: ModelPaths,
-    ):
-        self.root_directory = from_root
-        self.dest_models = to_models
-        self.mgr = model_manager
-        self.src_paths = src_paths
-
-    @classmethod
-    def initialize_yaml(cls, yaml_file: Path):
-        with open(yaml_file, "w") as file:
-            file.write(yaml.dump({"__metadata__": {"version": "3.0.0"}}))
-
-    def create_directory_structure(self):
-        """
-        Create the basic directory structure for the models folder.
-        """
-        for model_base in [BaseModelType.StableDiffusion1, BaseModelType.StableDiffusion2]:
-            for model_type in [
-                ModelType.Main,
-                ModelType.Vae,
-                ModelType.Lora,
-                ModelType.ControlNet,
-                ModelType.TextualInversion,
-            ]:
-                path = self.dest_models / model_base.value / model_type.value
-                path.mkdir(parents=True, exist_ok=True)
-        path = self.dest_models / "core"
-        path.mkdir(parents=True, exist_ok=True)
-
-    @staticmethod
-    def copy_file(src: Path, dest: Path):
-        """
-        copy a single file with logging
-        """
-        if dest.exists():
-            logger.info(f"Skipping existing {str(dest)}")
-            return
-        logger.info(f"Copying {str(src)} to {str(dest)}")
-        try:
-            shutil.copy(src, dest)
-        except Exception as e:
-            logger.error(f"COPY FAILED: {str(e)}")
-
-    @staticmethod
-    def copy_dir(src: Path, dest: Path):
-        """
-        Recursively copy a directory with logging
-        """
-        if dest.exists():
-            logger.info(f"Skipping existing {str(dest)}")
-            return
-
-        logger.info(f"Copying {str(src)} to {str(dest)}")
-        try:
-            shutil.copytree(src, dest)
-        except Exception as e:
-            logger.error(f"COPY FAILED: {str(e)}")
-
-    def migrate_models(self, src_dir: Path):
-        """
-        Recursively walk through src directory, probe anything
-        that looks like a model, and copy the model into the
-        appropriate location within the destination models directory.
-        """
-        directories_scanned = set()
-        for root, dirs, files in os.walk(src_dir, followlinks=True):
-            for d in dirs:
-                try:
-                    model = Path(root, d)
-                    info = ModelProbe().heuristic_probe(model)
-                    if not info:
-                        continue
-                    dest = self._model_probe_to_path(info) / model.name
-                    self.copy_dir(model, dest)
-                    directories_scanned.add(model)
-                except Exception as e:
-                    logger.error(str(e))
-                except KeyboardInterrupt:
-                    raise
-            for f in files:
-                # don't copy raw learned_embeds.bin or pytorch_lora_weights.bin
-                # let them be copied as part of a tree copy operation
-                try:
-                    if f in {"learned_embeds.bin", "pytorch_lora_weights.bin"}:
-                        continue
-                    model = Path(root, f)
-                    if model.parent in directories_scanned:
-                        continue
-                    info = ModelProbe().heuristic_probe(model)
-                    if not info:
-                        continue
-                    dest = self._model_probe_to_path(info) / f
-                    self.copy_file(model, dest)
-                except Exception as e:
-                    logger.error(str(e))
-                except KeyboardInterrupt:
-                    raise
-
-    def migrate_support_models(self):
-        """
-        Copy the clipseg, upscaler, and restoration models to their new
-        locations.
-        """
-        dest_directory = self.dest_models
-        if (self.root_directory / "models/clipseg").exists():
-            self.copy_dir(self.root_directory / "models/clipseg", dest_directory / "core/misc/clipseg")
-        if (self.root_directory / "models/realesrgan").exists():
-            self.copy_dir(self.root_directory / "models/realesrgan", dest_directory / "core/upscaling/realesrgan")
-        for d in ["codeformer", "gfpgan"]:
-            path = self.root_directory / "models" / d
-            if path.exists():
-                self.copy_dir(path, dest_directory / f"core/face_restoration/{d}")
-
-    def migrate_tuning_models(self):
-        """
-        Migrate the embeddings, loras and controlnets directories to their new homes.
-        """
-        for src in [self.src_paths.embeddings, self.src_paths.loras, self.src_paths.controlnets]:
-            if not src:
-                continue
-            if src.is_dir():
-                logger.info(f"Scanning {src}")
-                self.migrate_models(src)
-            else:
-                logger.info(f"{src} directory not found; skipping")
-                continue
-
-    def migrate_conversion_models(self):
-        """
-        Migrate all the models that are needed by the ckpt_to_diffusers conversion
-        script.
-        """
-
-        dest_directory = self.dest_models
-        kwargs = {
-            "cache_dir": self.root_directory / "models/hub",
-            # local_files_only = True
-        }
-        try:
-            logger.info("Migrating core tokenizers and text encoders")
-            target_dir = dest_directory / "core" / "convert"
-
-            self._migrate_pretrained(
-                BertTokenizerFast, repo_id="bert-base-uncased", dest=target_dir / "bert-base-uncased", **kwargs
-            )
-
-            # sd-1
-            repo_id = "openai/clip-vit-large-patch14"
-            self._migrate_pretrained(
-                CLIPTokenizer, repo_id=repo_id, dest=target_dir / "clip-vit-large-patch14", **kwargs
-            )
-            self._migrate_pretrained(
-                CLIPTextModel, repo_id=repo_id, dest=target_dir / "clip-vit-large-patch14", force=True, **kwargs
-            )
-
-            # sd-2
-            repo_id = "stabilityai/stable-diffusion-2"
-            self._migrate_pretrained(
-                CLIPTokenizer,
-                repo_id=repo_id,
-                dest=target_dir / "stable-diffusion-2-clip" / "tokenizer",
-                **{"subfolder": "tokenizer", **kwargs},
-            )
-            self._migrate_pretrained(
-                CLIPTextModel,
-                repo_id=repo_id,
-                dest=target_dir / "stable-diffusion-2-clip" / "text_encoder",
-                **{"subfolder": "text_encoder", **kwargs},
-            )
-
-            # VAE
-            logger.info("Migrating stable diffusion VAE")
-            self._migrate_pretrained(
-                AutoencoderKL, repo_id="stabilityai/sd-vae-ft-mse", dest=target_dir / "sd-vae-ft-mse", **kwargs
-            )
-
-            # safety checking
-            logger.info("Migrating safety checker")
-            repo_id = "CompVis/stable-diffusion-safety-checker"
-            self._migrate_pretrained(
-                AutoFeatureExtractor, repo_id=repo_id, dest=target_dir / "stable-diffusion-safety-checker", **kwargs
-            )
-            self._migrate_pretrained(
-                StableDiffusionSafetyChecker,
-                repo_id=repo_id,
-                dest=target_dir / "stable-diffusion-safety-checker",
-                **kwargs,
-            )
-        except KeyboardInterrupt:
-            raise
-        except Exception as e:
-            logger.error(str(e))
-
-    def _model_probe_to_path(self, info: ModelProbeInfo) -> Path:
-        return Path(self.dest_models, info.base_type.value, info.model_type.value)
-
-    def _migrate_pretrained(self, model_class, repo_id: str, dest: Path, force: bool = False, **kwargs):
-        if dest.exists() and not force:
-            logger.info(f"Skipping existing {dest}")
-            return
-        model = model_class.from_pretrained(repo_id, **kwargs)
-        self._save_pretrained(model, dest, overwrite=force)
-
-    def _save_pretrained(self, model, dest: Path, overwrite: bool = False):
-        model_name = dest.name
-        if overwrite:
-            model.save_pretrained(dest, safe_serialization=True)
-        else:
-            download_path = dest.with_name(f"{model_name}.downloading")
-            model.save_pretrained(download_path, safe_serialization=True)
-            download_path.replace(dest)
-
-    def _download_vae(self, repo_id: str, subfolder: str = None) -> Path:
-        vae = AutoencoderKL.from_pretrained(repo_id, cache_dir=self.root_directory / "models/hub", subfolder=subfolder)
-        info = ModelProbe().heuristic_probe(vae)
-        _, model_name = repo_id.split("/")
-        dest = self._model_probe_to_path(info) / self.unique_name(model_name, info)
-        vae.save_pretrained(dest, safe_serialization=True)
-        return dest
-
-    def _vae_path(self, vae: Union[str, dict]) -> Path:
-        """
-        Convert 2.3 VAE stanza to a straight path.
-        """
-        vae_path = None
-
-        # First get a path
-        if isinstance(vae, str):
-            vae_path = vae
-
-        elif isinstance(vae, DictConfig):
-            if p := vae.get("path"):
-                vae_path = p
-            elif repo_id := vae.get("repo_id"):
-                if repo_id == "stabilityai/sd-vae-ft-mse":  # this guy is already downloaded
-                    vae_path = "models/core/convert/sd-vae-ft-mse"
-                    return vae_path
-                else:
-                    vae_path = self._download_vae(repo_id, vae.get("subfolder"))
-
-        assert vae_path is not None, "Couldn't find VAE for this model"
-
-        # if the VAE is in the old models directory, then we must move it into the new
-        # one. VAEs outside of this directory can stay where they are.
-        vae_path = Path(vae_path)
-        if vae_path.is_relative_to(self.src_paths.models):
-            info = ModelProbe().heuristic_probe(vae_path)
-            dest = self._model_probe_to_path(info) / vae_path.name
-            if not dest.exists():
-                if vae_path.is_dir():
-                    self.copy_dir(vae_path, dest)
-                else:
-                    self.copy_file(vae_path, dest)
-            vae_path = dest
-
-        if vae_path.is_relative_to(self.dest_models):
-            rel_path = vae_path.relative_to(self.dest_models)
-            return Path("models", rel_path)
-        else:
-            return vae_path
-
-    def migrate_repo_id(self, repo_id: str, model_name: str = None, **extra_config):
-        """
-        Migrate a locally-cached diffusers pipeline identified with a repo_id
-        """
-        dest_dir = self.dest_models
-
-        cache = self.root_directory / "models/hub"
-        kwargs = {
-            "cache_dir": cache,
-            "safety_checker": None,
-            # local_files_only = True,
-        }
-
-        owner, repo_name = repo_id.split("/")
-        model_name = model_name or repo_name
-        model = cache / "--".join(["models", owner, repo_name])
-
-        if len(list(model.glob("snapshots/**/model_index.json"))) == 0:
-            return
-        revisions = [x.name for x in model.glob("refs/*")]
-
-        # if an fp16 is available we use that
-        revision = "fp16" if len(revisions) > 1 and "fp16" in revisions else revisions[0]
-        pipeline = StableDiffusionPipeline.from_pretrained(repo_id, revision=revision, **kwargs)
-
-        info = ModelProbe().heuristic_probe(pipeline)
-        if not info:
-            return
-
-        if self.mgr.model_exists(model_name, info.base_type, info.model_type):
-            logger.warning(f"A model named {model_name} already exists at the destination. Skipping migration.")
-            return
-
-        dest = self._model_probe_to_path(info) / model_name
-        self._save_pretrained(pipeline, dest)
-
-        rel_path = Path("models", dest.relative_to(dest_dir))
-        self._add_model(model_name, info, rel_path, **extra_config)
-
-    def migrate_path(self, location: Path, model_name: str = None, **extra_config):
-        """
-        Migrate a model referred to using 'weights' or 'path'
-        """
-
-        # handle relative paths
-        dest_dir = self.dest_models
-        location = self.root_directory / location
-        model_name = model_name or location.stem
-
-        info = ModelProbe().heuristic_probe(location)
-        if not info:
-            return
-
-        if self.mgr.model_exists(model_name, info.base_type, info.model_type):
-            logger.warning(f"A model named {model_name} already exists at the destination. Skipping migration.")
-            return
-
-        # uh oh, weights is in the old models directory - move it into the new one
-        if Path(location).is_relative_to(self.src_paths.models):
-            dest = Path(dest_dir, info.base_type.value, info.model_type.value, location.name)
-            if location.is_dir():
-                self.copy_dir(location, dest)
-            else:
-                self.copy_file(location, dest)
-            location = Path("models", info.base_type.value, info.model_type.value, location.name)
-
-        self._add_model(model_name, info, location, **extra_config)
-
-    def _add_model(self, model_name: str, info: ModelProbeInfo, location: Path, **extra_config):
-        if info.model_type != ModelType.Main:
-            return
-
-        self.mgr.add_model(
-            model_name=model_name,
-            base_model=info.base_type,
-            model_type=info.model_type,
-            clobber=True,
-            model_attributes={
-                "path": str(location),
-                "description": f"A {info.base_type.value} {info.model_type.value} model",
-                "model_format": info.format,
-                "variant": info.variant_type.value,
-                **extra_config,
-            },
-        )
-
-    def migrate_defined_models(self):
-        """
-        Migrate models defined in models.yaml
-        """
-        # find any models referred to in old models.yaml
-        conf = OmegaConf.load(self.root_directory / "configs/models.yaml")
-
-        for model_name, stanza in conf.items():
-            try:
-                passthru_args = {}
-
-                if vae := stanza.get("vae"):
-                    try:
-                        passthru_args["vae"] = str(self._vae_path(vae))
-                    except Exception as e:
-                        logger.warning(f'Could not find a VAE matching "{vae}" for model "{model_name}"')
-                        logger.warning(str(e))
-
-                if config := stanza.get("config"):
-                    passthru_args["config"] = config
-
-                if description := stanza.get("description"):
-                    passthru_args["description"] = description
-
-                if repo_id := stanza.get("repo_id"):
-                    logger.info(f"Migrating diffusers model {model_name}")
-                    self.migrate_repo_id(repo_id, model_name, **passthru_args)
-
-                elif location := stanza.get("weights"):
-                    logger.info(f"Migrating checkpoint model {model_name}")
-                    self.migrate_path(Path(location), model_name, **passthru_args)
-
-                elif location := stanza.get("path"):
-                    logger.info(f"Migrating diffusers model {model_name}")
-                    self.migrate_path(Path(location), model_name, **passthru_args)
-
-            except KeyboardInterrupt:
-                raise
-            except Exception as e:
-                logger.error(str(e))
-
-    def migrate(self):
-        self.create_directory_structure()
-        # the configure script is doing this
-        self.migrate_support_models()
-        self.migrate_conversion_models()
-        self.migrate_tuning_models()
-        self.migrate_defined_models()
-
-
-def _parse_legacy_initfile(root: Path, initfile: Path) -> ModelPaths:
-    """
-    Returns tuple of (embedding_path, lora_path, controlnet_path)
-    """
-    parser = argparse.ArgumentParser(fromfile_prefix_chars="@")
-    parser.add_argument(
-        "--embedding_directory",
-        "--embedding_path",
-        type=Path,
-        dest="embedding_path",
-        default=Path("embeddings"),
-    )
-    parser.add_argument(
-        "--lora_directory",
-        dest="lora_path",
-        type=Path,
-        default=Path("loras"),
-    )
-    opt, _ = parser.parse_known_args([f"@{str(initfile)}"])
-    return ModelPaths(
-        models=root / "models",
-        embeddings=root / str(opt.embedding_path).strip('"'),
-        loras=root / str(opt.lora_path).strip('"'),
-        controlnets=root / "controlnets",
-    )
-
-
-def _parse_legacy_yamlfile(root: Path, initfile: Path) -> ModelPaths:
-    """
-    Returns tuple of (embedding_path, lora_path, controlnet_path)
-    """
-    # Don't use the config object because it is unforgiving of version updates
-    # Just use omegaconf directly
-    opt = OmegaConf.load(initfile)
-    paths = opt.InvokeAI.Paths
-    models = paths.get("models_dir", "models")
-    embeddings = paths.get("embedding_dir", "embeddings")
-    loras = paths.get("lora_dir", "loras")
-    controlnets = paths.get("controlnet_dir", "controlnets")
-    return ModelPaths(
-        models=root / models if models else None,
-        embeddings=root / embeddings if embeddings else None,
-        loras=root / loras if loras else None,
-        controlnets=root / controlnets if controlnets else None,
-    )
-
-
-def get_legacy_embeddings(root: Path) -> ModelPaths:
-    path = root / "invokeai.init"
-    if path.exists():
-        return _parse_legacy_initfile(root, path)
-    path = root / "invokeai.yaml"
-    if path.exists():
-        return _parse_legacy_yamlfile(root, path)
-
-
-def do_migrate(src_directory: Path, dest_directory: Path):
-    """
-    Migrate models from src to dest InvokeAI root directories
-    """
-    config_file = dest_directory / "configs" / "models.yaml.3"
-    dest_models = dest_directory / "models.3"
-
-    version_3 = (dest_directory / "models" / "core").exists()
-
-    # Here we create the destination models.yaml file.
-    # If we are writing into a version 3 directory and the
-    # file already exists, then we write into a copy of it to
-    # avoid deleting its previous customizations. Otherwise we
-    # create a new empty one.
-    if version_3:  # write into the dest directory
-        try:
-            shutil.copy(dest_directory / "configs" / "models.yaml", config_file)
-        except Exception:
-            MigrateTo3.initialize_yaml(config_file)
-        mgr = ModelManager(config_file)  # important to initialize BEFORE moving the models directory
-        (dest_directory / "models").replace(dest_models)
-    else:
-        MigrateTo3.initialize_yaml(config_file)
-        mgr = ModelManager(config_file)
-
-    paths = get_legacy_embeddings(src_directory)
-    migrator = MigrateTo3(from_root=src_directory, to_models=dest_models, model_manager=mgr, src_paths=paths)
-    migrator.migrate()
-    print("Migration successful.")
-
-    if not version_3:
-        (dest_directory / "models").replace(src_directory / "models.orig")
-        print(f"Original models directory moved to {dest_directory}/models.orig")
-
-    (dest_directory / "configs" / "models.yaml").replace(src_directory / "configs" / "models.yaml.orig")
-    print(f"Original models.yaml file moved to {dest_directory}/configs/models.yaml.orig")
-
-    config_file.replace(config_file.with_suffix(""))
-    dest_models.replace(dest_models.with_suffix(""))
-
-
-def main():
-    parser = argparse.ArgumentParser(
-        prog="invokeai-migrate3",
-        description="""
-This will copy and convert the models directory and the configs/models.yaml from the InvokeAI 2.3 format
-'--from-directory' root to the InvokeAI 3.0 '--to-directory' root. These may be abbreviated '--from' and '--to'.a
-
-The old models directory and config file will be renamed 'models.orig' and 'models.yaml.orig' respectively.
-It is safe to provide the same directory for both arguments, but it is better to use the invokeai_configure
-script, which will perform a full upgrade in place.""",
-    )
-    parser.add_argument(
-        "--from-directory",
-        dest="src_root",
-        type=Path,
-        required=True,
-        help='Source InvokeAI 2.3 root directory (containing "invokeai.init" or "invokeai.yaml")',
-    )
-    parser.add_argument(
-        "--to-directory",
-        dest="dest_root",
-        type=Path,
-        required=True,
-        help='Destination InvokeAI 3.0 directory (containing "invokeai.yaml")',
-    )
-    args = parser.parse_args()
-    src_root = args.src_root
-    assert src_root.is_dir(), f"{src_root} is not a valid directory"
-    assert (src_root / "models").is_dir(), f"{src_root} does not contain a 'models' subdirectory"
-    assert (src_root / "models" / "hub").exists(), f"{src_root} does not contain a version 2.3 models directory"
-    assert (src_root / "invokeai.init").exists() or (
-        src_root / "invokeai.yaml"
-    ).exists(), f"{src_root} does not contain an InvokeAI init file."
-
-    dest_root = args.dest_root
-    assert dest_root.is_dir(), f"{dest_root} is not a valid directory"
-    config = InvokeAIAppConfig.get_config()
-    config.parse_args(["--root", str(dest_root)])
-
-    # TODO: revisit - don't rely on invokeai.yaml to exist yet!
-    dest_is_setup = (dest_root / "models/core").exists() and (dest_root / "databases").exists()
-    if not dest_is_setup:
-        from invokeai.backend.install.invokeai_configure import initialize_rootdir
-
-        initialize_rootdir(dest_root, True)
-
-    do_migrate(src_root, dest_root)
-
-
-if __name__ == "__main__":
-    main()
diff --git a/invokeai/backend/install/model_install_backend.py b/invokeai/backend/install/model_install_backend.py
deleted file mode 100644
index fdbe714f62..0000000000
--- a/invokeai/backend/install/model_install_backend.py
+++ /dev/null
@@ -1,637 +0,0 @@
-"""
-Utility (backend) functions used by model_install.py
-"""
-import os
-import re
-import shutil
-import warnings
-from dataclasses import dataclass, field
-from pathlib import Path
-from tempfile import TemporaryDirectory
-from typing import Callable, Dict, List, Optional, Set, Union
-
-import requests
-import torch
-from diffusers import DiffusionPipeline
-from diffusers import logging as dlogging
-from huggingface_hub import HfApi, HfFolder, hf_hub_url
-from omegaconf import OmegaConf
-from tqdm import tqdm
-
-import invokeai.configs as configs
-from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.backend.model_management import AddModelResult, BaseModelType, ModelManager, ModelType, ModelVariantType
-from invokeai.backend.model_management.model_probe import ModelProbe, ModelProbeInfo, SchedulerPredictionType
-from invokeai.backend.util import download_with_resume
-from invokeai.backend.util.devices import choose_torch_device, torch_dtype
-
-from ..util.logging import InvokeAILogger
-
-warnings.filterwarnings("ignore")
-
-# --------------------------globals-----------------------
-config = InvokeAIAppConfig.get_config()
-logger = InvokeAILogger.get_logger(name="InvokeAI")
-
-# the initial "configs" dir is now bundled in the `invokeai.configs` package
-Dataset_path = Path(configs.__path__[0]) / "INITIAL_MODELS.yaml"
-
-Config_preamble = """
-# This file describes the alternative machine learning models
-# available to InvokeAI script.
-#
-# To add a new model, follow the examples below. Each
-# model requires a model config file, a weights file,
-# and the width and height of the images it
-# was trained on.
-"""
-
-LEGACY_CONFIGS = {
-    BaseModelType.StableDiffusion1: {
-        ModelVariantType.Normal: {
-            SchedulerPredictionType.Epsilon: "v1-inference.yaml",
-            SchedulerPredictionType.VPrediction: "v1-inference-v.yaml",
-        },
-        ModelVariantType.Inpaint: {
-            SchedulerPredictionType.Epsilon: "v1-inpainting-inference.yaml",
-            SchedulerPredictionType.VPrediction: "v1-inpainting-inference-v.yaml",
-        },
-    },
-    BaseModelType.StableDiffusion2: {
-        ModelVariantType.Normal: {
-            SchedulerPredictionType.Epsilon: "v2-inference.yaml",
-            SchedulerPredictionType.VPrediction: "v2-inference-v.yaml",
-        },
-        ModelVariantType.Inpaint: {
-            SchedulerPredictionType.Epsilon: "v2-inpainting-inference.yaml",
-            SchedulerPredictionType.VPrediction: "v2-inpainting-inference-v.yaml",
-        },
-    },
-    BaseModelType.StableDiffusionXL: {
-        ModelVariantType.Normal: "sd_xl_base.yaml",
-    },
-    BaseModelType.StableDiffusionXLRefiner: {
-        ModelVariantType.Normal: "sd_xl_refiner.yaml",
-    },
-}
-
-
-@dataclass
-class InstallSelections:
-    install_models: List[str] = field(default_factory=list)
-    remove_models: List[str] = field(default_factory=list)
-
-
-@dataclass
-class ModelLoadInfo:
-    name: str
-    model_type: ModelType
-    base_type: BaseModelType
-    path: Optional[Path] = None
-    repo_id: Optional[str] = None
-    subfolder: Optional[str] = None
-    description: str = ""
-    installed: bool = False
-    recommended: bool = False
-    default: bool = False
-    requires: Optional[List[str]] = field(default_factory=list)
-
-
-class ModelInstall(object):
-    def __init__(
-        self,
-        config: InvokeAIAppConfig,
-        prediction_type_helper: Optional[Callable[[Path], SchedulerPredictionType]] = None,
-        model_manager: Optional[ModelManager] = None,
-        access_token: Optional[str] = None,
-        civitai_api_key: Optional[str] = None,
-    ):
-        self.config = config
-        self.mgr = model_manager or ModelManager(config.model_conf_path)
-        self.datasets = OmegaConf.load(Dataset_path)
-        self.prediction_helper = prediction_type_helper
-        self.access_token = access_token or HfFolder.get_token()
-        self.civitai_api_key = civitai_api_key or config.civitai_api_key
-        self.reverse_paths = self._reverse_paths(self.datasets)
-
-    def all_models(self) -> Dict[str, ModelLoadInfo]:
-        """
-        Return dict of model_key=>ModelLoadInfo objects.
-        This method consolidates and simplifies the entries in both
-        models.yaml and INITIAL_MODELS.yaml so that they can
-        be treated uniformly. It also sorts the models alphabetically
-        by their name, to improve the display somewhat.
-        """
-        model_dict = {}
-
-        # first populate with the entries in INITIAL_MODELS.yaml
-        for key, value in self.datasets.items():
-            name, base, model_type = ModelManager.parse_key(key)
-            value["name"] = name
-            value["base_type"] = base
-            value["model_type"] = model_type
-            model_info = ModelLoadInfo(**value)
-            if model_info.subfolder and model_info.repo_id:
-                model_info.repo_id += f":{model_info.subfolder}"
-            model_dict[key] = model_info
-
-        # supplement with entries in models.yaml
-        installed_models = list(self.mgr.list_models())
-
-        for md in installed_models:
-            base = md["base_model"]
-            model_type = md["model_type"]
-            name = md["model_name"]
-            key = ModelManager.create_key(name, base, model_type)
-            if key in model_dict:
-                model_dict[key].installed = True
-            else:
-                model_dict[key] = ModelLoadInfo(
-                    name=name,
-                    base_type=base,
-                    model_type=model_type,
-                    path=value.get("path"),
-                    installed=True,
-                )
-        return {x: model_dict[x] for x in sorted(model_dict.keys(), key=lambda y: model_dict[y].name.lower())}
-
-    def _is_autoloaded(self, model_info: dict) -> bool:
-        path = model_info.get("path")
-        if not path:
-            return False
-        for autodir in ["autoimport_dir", "lora_dir", "embedding_dir", "controlnet_dir"]:
-            if autodir_path := getattr(self.config, autodir):
-                autodir_path = self.config.root_path / autodir_path
-                if Path(path).is_relative_to(autodir_path):
-                    return True
-        return False
-
-    def list_models(self, model_type):
-        installed = self.mgr.list_models(model_type=model_type)
-        print()
-        print(f"Installed models of type `{model_type}`:")
-        print(f"{'Model Key':50} Model Path")
-        for i in installed:
-            print(f"{'/'.join([i['base_model'],i['model_type'],i['model_name']]):50} {i['path']}")
-        print()
-
-    # logic here a little reversed to maintain backward compatibility
-    def starter_models(self, all_models: bool = False) -> Set[str]:
-        models = set()
-        for key, _value in self.datasets.items():
-            name, base, model_type = ModelManager.parse_key(key)
-            if all_models or model_type in [ModelType.Main, ModelType.Vae]:
-                models.add(key)
-        return models
-
-    def recommended_models(self) -> Set[str]:
-        starters = self.starter_models(all_models=True)
-        return {x for x in starters if self.datasets[x].get("recommended", False)}
-
-    def default_model(self) -> str:
-        starters = self.starter_models()
-        defaults = [x for x in starters if self.datasets[x].get("default", False)]
-        return defaults[0]
-
-    def install(self, selections: InstallSelections):
-        verbosity = dlogging.get_verbosity()  # quench NSFW nags
-        dlogging.set_verbosity_error()
-
-        job = 1
-        jobs = len(selections.remove_models) + len(selections.install_models)
-
-        # remove requested models
-        for key in selections.remove_models:
-            name, base, mtype = self.mgr.parse_key(key)
-            logger.info(f"Deleting {mtype} model {name} [{job}/{jobs}]")
-            try:
-                self.mgr.del_model(name, base, mtype)
-            except FileNotFoundError as e:
-                logger.warning(e)
-            job += 1
-
-        # add requested models
-        self._remove_installed(selections.install_models)
-        self._add_required_models(selections.install_models)
-        for path in selections.install_models:
-            logger.info(f"Installing {path} [{job}/{jobs}]")
-            try:
-                self.heuristic_import(path)
-            except (ValueError, KeyError) as e:
-                logger.error(str(e))
-            job += 1
-
-        dlogging.set_verbosity(verbosity)
-        self.mgr.commit()
-
-    def heuristic_import(
-        self,
-        model_path_id_or_url: Union[str, Path],
-        models_installed: Set[Path] = None,
-    ) -> Dict[str, AddModelResult]:
-        """
-        :param model_path_id_or_url: A Path to a local model to import, or a string representing its repo_id or URL
-        :param models_installed: Set of installed models, used for recursive invocation
-        Returns a set of dict objects corresponding to newly-created stanzas in models.yaml.
-        """
-
-        if not models_installed:
-            models_installed = {}
-
-        model_path_id_or_url = str(model_path_id_or_url).strip("\"' ")
-
-        # A little hack to allow nested routines to retrieve info on the requested ID
-        self.current_id = model_path_id_or_url
-        path = Path(model_path_id_or_url)
-
-        # fix relative paths
-        if path.exists() and not path.is_absolute():
-            path = path.absolute()  # make relative to current WD
-
-        # checkpoint file, or similar
-        if path.is_file():
-            models_installed.update({str(path): self._install_path(path)})
-
-        # folders style or similar
-        elif path.is_dir() and any(
-            (path / x).exists()
-            for x in {
-                "config.json",
-                "model_index.json",
-                "learned_embeds.bin",
-                "pytorch_lora_weights.bin",
-                "pytorch_lora_weights.safetensors",
-            }
-        ):
-            models_installed.update({str(model_path_id_or_url): self._install_path(path)})
-
-        # recursive scan
-        elif path.is_dir():
-            for child in path.iterdir():
-                self.heuristic_import(child, models_installed=models_installed)
-
-        # huggingface repo
-        elif len(str(model_path_id_or_url).split("/")) == 2:
-            models_installed.update({str(model_path_id_or_url): self._install_repo(str(model_path_id_or_url))})
-
-        # a URL
-        elif str(model_path_id_or_url).startswith(("http:", "https:", "ftp:")):
-            models_installed.update({str(model_path_id_or_url): self._install_url(model_path_id_or_url)})
-
-        else:
-            raise KeyError(f"{str(model_path_id_or_url)} is not recognized as a local path, repo ID or URL. Skipping")
-
-        return models_installed
-
-    def _remove_installed(self, model_list: List[str]):
-        all_models = self.all_models()
-        models_to_remove = []
-
-        for path in model_list:
-            key = self.reverse_paths.get(path)
-            if key and all_models[key].installed:
-                models_to_remove.append(path)
-
-        for path in models_to_remove:
-            logger.warning(f"{path} already installed. Skipping")
-            model_list.remove(path)
-
-    def _add_required_models(self, model_list: List[str]):
-        additional_models = []
-        all_models = self.all_models()
-        for path in model_list:
-            if not (key := self.reverse_paths.get(path)):
-                continue
-            for requirement in all_models[key].requires:
-                requirement_key = self.reverse_paths.get(requirement)
-                if not all_models[requirement_key].installed:
-                    additional_models.append(requirement)
-        model_list.extend(additional_models)
-
-    # install a model from a local path. The optional info parameter is there to prevent
-    # the model from being probed twice in the event that it has already been probed.
-    def _install_path(self, path: Path, info: ModelProbeInfo = None) -> AddModelResult:
-        info = info or ModelProbe().heuristic_probe(path, self.prediction_helper)
-        if not info:
-            logger.warning(f"Unable to parse format of {path}")
-            return None
-        model_name = path.stem if path.is_file() else path.name
-        if self.mgr.model_exists(model_name, info.base_type, info.model_type):
-            raise ValueError(f'A model named "{model_name}" is already installed.')
-        attributes = self._make_attributes(path, info)
-        return self.mgr.add_model(
-            model_name=model_name,
-            base_model=info.base_type,
-            model_type=info.model_type,
-            model_attributes=attributes,
-        )
-
-    def _install_url(self, url: str) -> AddModelResult:
-        with TemporaryDirectory(dir=self.config.models_path) as staging:
-            CIVITAI_RE = r".*civitai.com.*"
-            civit_url = re.match(CIVITAI_RE, url, re.IGNORECASE)
-            location = download_with_resume(
-                url, Path(staging), access_token=self.civitai_api_key if civit_url else None
-            )
-            if not location:
-                logger.error(f"Unable to download {url}. Skipping.")
-            info = ModelProbe().heuristic_probe(location, self.prediction_helper)
-            dest = self.config.models_path / info.base_type.value / info.model_type.value / location.name
-            dest.parent.mkdir(parents=True, exist_ok=True)
-            models_path = shutil.move(location, dest)
-
-        # staged version will be garbage-collected at this time
-        return self._install_path(Path(models_path), info)
-
-    def _install_repo(self, repo_id: str) -> AddModelResult:
-        # hack to recover models stored in subfolders --
-        # Required to get the "v2" model of monster-labs/control_v1p_sd15_qrcode_monster
-        subfolder = None
-        if match := re.match(r"^([^/]+/[^/]+):(\w+)$", repo_id):
-            repo_id = match.group(1)
-            subfolder = match.group(2)
-
-        hinfo = HfApi().model_info(repo_id)
-
-        # we try to figure out how to download this most economically
-        # list all the files in the repo
-        files = [x.rfilename for x in hinfo.siblings]
-        if subfolder:
-            files = [x for x in files if x.startswith(f"{subfolder}/")]
-        prefix = f"{subfolder}/" if subfolder else ""
-
-        location = None
-
-        with TemporaryDirectory(dir=self.config.models_path) as staging:
-            staging = Path(staging)
-            if f"{prefix}model_index.json" in files:
-                location = self._download_hf_pipeline(repo_id, staging, subfolder=subfolder)  # pipeline
-            elif f"{prefix}unet/model.onnx" in files:
-                location = self._download_hf_model(repo_id, files, staging)
-            else:
-                for suffix in ["safetensors", "bin"]:
-                    if f"{prefix}pytorch_lora_weights.{suffix}" in files:
-                        location = self._download_hf_model(
-                            repo_id, [f"pytorch_lora_weights.{suffix}"], staging, subfolder=subfolder
-                        )  # LoRA
-                        break
-                    elif (
-                        self.config.precision == "float16" and f"{prefix}diffusion_pytorch_model.fp16.{suffix}" in files
-                    ):  # vae, controlnet or some other standalone
-                        files = ["config.json", f"diffusion_pytorch_model.fp16.{suffix}"]
-                        location = self._download_hf_model(repo_id, files, staging, subfolder=subfolder)
-                        break
-                    elif f"{prefix}diffusion_pytorch_model.{suffix}" in files:
-                        files = ["config.json", f"diffusion_pytorch_model.{suffix}"]
-                        location = self._download_hf_model(repo_id, files, staging, subfolder=subfolder)
-                        break
-                    elif f"{prefix}learned_embeds.{suffix}" in files:
-                        location = self._download_hf_model(
-                            repo_id, [f"learned_embeds.{suffix}"], staging, subfolder=subfolder
-                        )
-                        break
-                    elif (
-                        f"{prefix}image_encoder.txt" in files and f"{prefix}ip_adapter.{suffix}" in files
-                    ):  # IP-Adapter
-                        files = ["image_encoder.txt", f"ip_adapter.{suffix}"]
-                        location = self._download_hf_model(repo_id, files, staging, subfolder=subfolder)
-                        break
-                    elif f"{prefix}model.{suffix}" in files and f"{prefix}config.json" in files:
-                        # This elif-condition is pretty fragile, but it is intended to handle CLIP Vision models hosted
-                        # by InvokeAI for use with IP-Adapters.
-                        files = ["config.json", f"model.{suffix}"]
-                        location = self._download_hf_model(repo_id, files, staging, subfolder=subfolder)
-                        break
-            if not location:
-                logger.warning(f"Could not determine type of repo {repo_id}. Skipping install.")
-                return {}
-
-            info = ModelProbe().heuristic_probe(location, self.prediction_helper)
-            if not info:
-                logger.warning(f"Could not probe {location}. Skipping install.")
-                return {}
-            dest = (
-                self.config.models_path
-                / info.base_type.value
-                / info.model_type.value
-                / self._get_model_name(repo_id, location)
-            )
-            if dest.exists():
-                shutil.rmtree(dest)
-            shutil.copytree(location, dest)
-            return self._install_path(dest, info)
-
-    def _get_model_name(self, path_name: str, location: Path) -> str:
-        """
-        Calculate a name for the model - primitive implementation.
-        """
-        if key := self.reverse_paths.get(path_name):
-            (name, base, mtype) = ModelManager.parse_key(key)
-            return name
-        elif location.is_dir():
-            return location.name
-        else:
-            return location.stem
-
-    def _make_attributes(self, path: Path, info: ModelProbeInfo) -> dict:
-        model_name = path.name if path.is_dir() else path.stem
-        description = f"{info.base_type.value} {info.model_type.value} model {model_name}"
-        if key := self.reverse_paths.get(self.current_id):
-            if key in self.datasets:
-                description = self.datasets[key].get("description") or description
-
-        rel_path = self.relative_to_root(path, self.config.models_path)
-
-        attributes = {
-            "path": str(rel_path),
-            "description": str(description),
-            "model_format": info.format,
-        }
-        legacy_conf = None
-        if info.model_type == ModelType.Main or info.model_type == ModelType.ONNX:
-            attributes.update(
-                {
-                    "variant": info.variant_type,
-                }
-            )
-            if info.format == "checkpoint":
-                try:
-                    possible_conf = path.with_suffix(".yaml")
-                    if possible_conf.exists():
-                        legacy_conf = str(self.relative_to_root(possible_conf))
-                    elif info.base_type in [BaseModelType.StableDiffusion1, BaseModelType.StableDiffusion2]:
-                        legacy_conf = Path(
-                            self.config.legacy_conf_dir,
-                            LEGACY_CONFIGS[info.base_type][info.variant_type][info.prediction_type],
-                        )
-                    else:
-                        legacy_conf = Path(
-                            self.config.legacy_conf_dir, LEGACY_CONFIGS[info.base_type][info.variant_type]
-                        )
-                except KeyError:
-                    legacy_conf = Path(self.config.legacy_conf_dir, "v1-inference.yaml")  # best guess
-
-        if info.model_type == ModelType.ControlNet and info.format == "checkpoint":
-            possible_conf = path.with_suffix(".yaml")
-            if possible_conf.exists():
-                legacy_conf = str(self.relative_to_root(possible_conf))
-            else:
-                legacy_conf = Path(
-                    self.config.root_path,
-                    "configs/controlnet",
-                    ("cldm_v15.yaml" if info.base_type == BaseModelType("sd-1") else "cldm_v21.yaml"),
-                )
-
-        if legacy_conf:
-            attributes.update({"config": str(legacy_conf)})
-        return attributes
-
-    def relative_to_root(self, path: Path, root: Optional[Path] = None) -> Path:
-        root = root or self.config.root_path
-        if path.is_relative_to(root):
-            return path.relative_to(root)
-        else:
-            return path
-
-    def _download_hf_pipeline(self, repo_id: str, staging: Path, subfolder: str = None) -> Path:
-        """
-        Retrieve a StableDiffusion model from cache or remote and then
-        does a save_pretrained() to the indicated staging area.
-        """
-        _, name = repo_id.split("/")
-        precision = torch_dtype(choose_torch_device())
-        variants = ["fp16", None] if precision == torch.float16 else [None, "fp16"]
-
-        model = None
-        for variant in variants:
-            try:
-                model = DiffusionPipeline.from_pretrained(
-                    repo_id,
-                    variant=variant,
-                    torch_dtype=precision,
-                    safety_checker=None,
-                    subfolder=subfolder,
-                )
-            except Exception as e:  # most errors are due to fp16 not being present. Fix this to catch other errors
-                if "fp16" not in str(e):
-                    print(e)
-
-            if model:
-                break
-
-        if not model:
-            logger.error(f"Diffusers model {repo_id} could not be downloaded. Skipping.")
-            return None
-        model.save_pretrained(staging / name, safe_serialization=True)
-        return staging / name
-
-    def _download_hf_model(self, repo_id: str, files: List[str], staging: Path, subfolder: None) -> Path:
-        _, name = repo_id.split("/")
-        location = staging / name
-        paths = []
-        for filename in files:
-            filePath = Path(filename)
-            p = hf_download_with_resume(
-                repo_id,
-                model_dir=location / filePath.parent,
-                model_name=filePath.name,
-                access_token=self.access_token,
-                subfolder=filePath.parent / subfolder if subfolder else filePath.parent,
-            )
-            if p:
-                paths.append(p)
-            else:
-                logger.warning(f"Could not download {filename} from {repo_id}.")
-
-        return location if len(paths) > 0 else None
-
-    @classmethod
-    def _reverse_paths(cls, datasets) -> dict:
-        """
-        Reverse mapping from repo_id/path to destination name.
-        """
-        return {v.get("path") or v.get("repo_id"): k for k, v in datasets.items()}
-
-
-# -------------------------------------
-def yes_or_no(prompt: str, default_yes=True):
-    default = "y" if default_yes else "n"
-    response = input(f"{prompt} [{default}] ") or default
-    if default_yes:
-        return response[0] not in ("n", "N")
-    else:
-        return response[0] in ("y", "Y")
-
-
-# ---------------------------------------------
-def hf_download_from_pretrained(model_class: object, model_name: str, destination: Path, **kwargs):
-    logger = InvokeAILogger.get_logger("InvokeAI")
-    logger.addFilter(lambda x: "fp16 is not a valid" not in x.getMessage())
-
-    model = model_class.from_pretrained(
-        model_name,
-        resume_download=True,
-        **kwargs,
-    )
-    model.save_pretrained(destination, safe_serialization=True)
-    return destination
-
-
-# ---------------------------------------------
-def hf_download_with_resume(
-    repo_id: str,
-    model_dir: str,
-    model_name: str,
-    model_dest: Path = None,
-    access_token: str = None,
-    subfolder: str = None,
-) -> Path:
-    model_dest = model_dest or Path(os.path.join(model_dir, model_name))
-    os.makedirs(model_dir, exist_ok=True)
-
-    url = hf_hub_url(repo_id, model_name, subfolder=subfolder)
-
-    header = {"Authorization": f"Bearer {access_token}"} if access_token else {}
-    open_mode = "wb"
-    exist_size = 0
-
-    if os.path.exists(model_dest):
-        exist_size = os.path.getsize(model_dest)
-        header["Range"] = f"bytes={exist_size}-"
-        open_mode = "ab"
-
-    resp = requests.get(url, headers=header, stream=True)
-    total = int(resp.headers.get("content-length", 0))
-
-    if resp.status_code == 416:  # "range not satisfiable", which means nothing to return
-        logger.info(f"{model_name}: complete file found. Skipping.")
-        return model_dest
-    elif resp.status_code == 404:
-        logger.warning("File not found")
-        return None
-    elif resp.status_code != 200:
-        logger.warning(f"{model_name}: {resp.reason}")
-    elif exist_size > 0:
-        logger.info(f"{model_name}: partial file found. Resuming...")
-    else:
-        logger.info(f"{model_name}: Downloading...")
-
-    try:
-        with (
-            open(model_dest, open_mode) as file,
-            tqdm(
-                desc=model_name,
-                initial=exist_size,
-                total=total + exist_size,
-                unit="iB",
-                unit_scale=True,
-                unit_divisor=1000,
-            ) as bar,
-        ):
-            for data in resp.iter_content(chunk_size=1024):
-                size = file.write(data)
-                bar.update(size)
-    except Exception as e:
-        logger.error(f"An error occurred while downloading {model_name}: {str(e)}")
-        return None
-    return model_dest
diff --git a/invokeai/backend/ip_adapter/ip_adapter.py b/invokeai/backend/ip_adapter/ip_adapter.py
index 3ba6fc5a23..e51966c779 100644
--- a/invokeai/backend/ip_adapter/ip_adapter.py
+++ b/invokeai/backend/ip_adapter/ip_adapter.py
@@ -9,8 +9,8 @@ from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
 
 from invokeai.backend.ip_adapter.ip_attention_weights import IPAttentionWeights
 
-from .resampler import Resampler
 from ..raw_model import RawModel
+from .resampler import Resampler
 
 
 class ImageProjModel(torch.nn.Module):
diff --git a/invokeai/backend/lora.py b/invokeai/backend/lora.py
index fb0c23067f..0b7128034a 100644
--- a/invokeai/backend/lora.py
+++ b/invokeai/backend/lora.py
@@ -10,6 +10,7 @@ from safetensors.torch import load_file
 from typing_extensions import Self
 
 from invokeai.backend.model_manager import BaseModelType
+
 from .raw_model import RawModel
 
 
@@ -366,6 +367,7 @@ class IA3Layer(LoRALayerBase):
 
 AnyLoRALayer = Union[LoRALayer, LoHALayer, LoKRLayer, FullLayer, IA3Layer]
 
+
 class LoRAModelRaw(RawModel):  # (torch.nn.Module):
     _name: str
     layers: Dict[str, AnyLoRALayer]
diff --git a/invokeai/backend/model_management_OLD/README.md b/invokeai/backend/model_management_OLD/README.md
deleted file mode 100644
index 0d94f39642..0000000000
--- a/invokeai/backend/model_management_OLD/README.md
+++ /dev/null
@@ -1,27 +0,0 @@
-# Model Cache
-
-## `glibc` Memory Allocator Fragmentation
-
-Python (and PyTorch) relies on the memory allocator from the C Standard Library (`libc`). On linux, with the GNU C Standard Library implementation (`glibc`), our memory access patterns have been observed to cause severe memory fragmentation. This fragmentation results in large amounts of memory that has been freed but can't be released back to the OS. Loading models from disk and moving them between CPU/CUDA seem to be the operations that contribute most to the fragmentation. This memory fragmentation issue can result in OOM crashes during frequent model switching, even if `max_cache_size` is set to a reasonable value (e.g. a OOM crash with `max_cache_size=16` on a system with 32GB of RAM).
-
-This problem may also exist on other OSes, and other `libc` implementations. But, at the time of writing, it has only been investigated on linux with `glibc`.
-
-To better understand how the `glibc` memory allocator works, see these references:
-- Basics: https://www.gnu.org/software/libc/manual/html_node/The-GNU-Allocator.html
-- Details: https://sourceware.org/glibc/wiki/MallocInternals
-
-Note the differences between memory allocated as chunks in an arena vs. memory allocated with `mmap`. Under `glibc`'s default configuration, most model tensors get allocated as chunks in an arena making them vulnerable to the problem of fragmentation.
-
-We can work around this memory fragmentation issue by setting the following env var:
-
-```bash
-# Force blocks >1MB to be allocated with `mmap` so that they are released to the system immediately when they are freed.
-MALLOC_MMAP_THRESHOLD_=1048576
-```
-
-See the following references for more information about the `malloc` tunable parameters:
-- https://www.gnu.org/software/libc/manual/html_node/Malloc-Tunable-Parameters.html
-- https://www.gnu.org/software/libc/manual/html_node/Memory-Allocation-Tunables.html
-- https://man7.org/linux/man-pages/man3/mallopt.3.html
-
-The model cache emits debug logs that provide visibility into the state of the `libc` memory allocator. See the `LibcUtil` class for more info on how these `libc` malloc stats are collected.
diff --git a/invokeai/backend/model_management_OLD/__init__.py b/invokeai/backend/model_management_OLD/__init__.py
deleted file mode 100644
index d523a7a0c8..0000000000
--- a/invokeai/backend/model_management_OLD/__init__.py
+++ /dev/null
@@ -1,20 +0,0 @@
-# ruff: noqa: I001, F401
-"""
-Initialization file for invokeai.backend.model_management
-"""
-# This import must be first
-from .model_manager import AddModelResult, LoadedModelInfo, ModelManager, SchedulerPredictionType
-from .lora import ModelPatcher, ONNXModelPatcher
-from .model_cache import ModelCache
-
-from .models import (
-    BaseModelType,
-    DuplicateModelException,
-    ModelNotFoundException,
-    ModelType,
-    ModelVariantType,
-    SubModelType,
-)
-
-# This import must be last
-from .model_merge import MergeInterpolationMethod, ModelMerger
diff --git a/invokeai/backend/model_management_OLD/convert_ckpt_to_diffusers.py b/invokeai/backend/model_management_OLD/convert_ckpt_to_diffusers.py
deleted file mode 100644
index 6878218f67..0000000000
--- a/invokeai/backend/model_management_OLD/convert_ckpt_to_diffusers.py
+++ /dev/null
@@ -1,1739 +0,0 @@
-# coding=utf-8
-# Copyright 2023 The HuggingFace Inc. team.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-#
-# Adapted for use in InvokeAI by Lincoln Stein, July 2023
-#
-""" Conversion script for the Stable Diffusion checkpoints."""
-
-import re
-from contextlib import nullcontext
-from io import BytesIO
-from pathlib import Path
-from typing import Optional, Union
-
-import requests
-import torch
-from diffusers.models import AutoencoderKL, ControlNetModel, PriorTransformer, UNet2DConditionModel
-from diffusers.pipelines.latent_diffusion.pipeline_latent_diffusion import LDMBertConfig, LDMBertModel
-from diffusers.pipelines.paint_by_example import PaintByExampleImageEncoder
-from diffusers.pipelines.pipeline_utils import DiffusionPipeline
-from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
-from diffusers.pipelines.stable_diffusion.stable_unclip_image_normalizer import StableUnCLIPImageNormalizer
-from diffusers.schedulers import (
-    DDIMScheduler,
-    DDPMScheduler,
-    DPMSolverMultistepScheduler,
-    EulerAncestralDiscreteScheduler,
-    EulerDiscreteScheduler,
-    HeunDiscreteScheduler,
-    LMSDiscreteScheduler,
-    PNDMScheduler,
-    UnCLIPScheduler,
-)
-from diffusers.utils import is_accelerate_available
-from picklescan.scanner import scan_file_path
-from transformers import (
-    AutoFeatureExtractor,
-    BertTokenizerFast,
-    CLIPImageProcessor,
-    CLIPTextConfig,
-    CLIPTextModel,
-    CLIPTextModelWithProjection,
-    CLIPTokenizer,
-    CLIPVisionConfig,
-    CLIPVisionModelWithProjection,
-)
-
-from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.backend.util.logging import InvokeAILogger
-
-from .models import BaseModelType, ModelVariantType
-
-try:
-    from omegaconf import OmegaConf
-    from omegaconf.dictconfig import DictConfig
-except ImportError:
-    raise ImportError(
-        "OmegaConf is required to convert the LDM checkpoints. Please install it with `pip install OmegaConf`."
-    )
-
-if is_accelerate_available():
-    from accelerate import init_empty_weights
-    from accelerate.utils import set_module_tensor_to_device
-
-logger = InvokeAILogger.get_logger(__name__)
-CONVERT_MODEL_ROOT = InvokeAIAppConfig.get_config().models_path / "core/convert"
-
-
-def shave_segments(path, n_shave_prefix_segments=1):
-    """
-    Removes segments. Positive values shave the first segments, negative shave the last segments.
-    """
-    if n_shave_prefix_segments >= 0:
-        return ".".join(path.split(".")[n_shave_prefix_segments:])
-    else:
-        return ".".join(path.split(".")[:n_shave_prefix_segments])
-
-
-def renew_resnet_paths(old_list, n_shave_prefix_segments=0):
-    """
-    Updates paths inside resnets to the new naming scheme (local renaming)
-    """
-    mapping = []
-    for old_item in old_list:
-        new_item = old_item.replace("in_layers.0", "norm1")
-        new_item = new_item.replace("in_layers.2", "conv1")
-
-        new_item = new_item.replace("out_layers.0", "norm2")
-        new_item = new_item.replace("out_layers.3", "conv2")
-
-        new_item = new_item.replace("emb_layers.1", "time_emb_proj")
-        new_item = new_item.replace("skip_connection", "conv_shortcut")
-
-        new_item = shave_segments(new_item, n_shave_prefix_segments=n_shave_prefix_segments)
-
-        mapping.append({"old": old_item, "new": new_item})
-
-    return mapping
-
-
-def renew_vae_resnet_paths(old_list, n_shave_prefix_segments=0):
-    """
-    Updates paths inside resnets to the new naming scheme (local renaming)
-    """
-    mapping = []
-    for old_item in old_list:
-        new_item = old_item
-
-        new_item = new_item.replace("nin_shortcut", "conv_shortcut")
-        new_item = shave_segments(new_item, n_shave_prefix_segments=n_shave_prefix_segments)
-
-        mapping.append({"old": old_item, "new": new_item})
-
-    return mapping
-
-
-def renew_attention_paths(old_list, n_shave_prefix_segments=0):
-    """
-    Updates paths inside attentions to the new naming scheme (local renaming)
-    """
-    mapping = []
-    for old_item in old_list:
-        new_item = old_item
-
-        #         new_item = new_item.replace('norm.weight', 'group_norm.weight')
-        #         new_item = new_item.replace('norm.bias', 'group_norm.bias')
-
-        #         new_item = new_item.replace('proj_out.weight', 'proj_attn.weight')
-        #         new_item = new_item.replace('proj_out.bias', 'proj_attn.bias')
-
-        #         new_item = shave_segments(new_item, n_shave_prefix_segments=n_shave_prefix_segments)
-
-        mapping.append({"old": old_item, "new": new_item})
-
-    return mapping
-
-
-def renew_vae_attention_paths(old_list, n_shave_prefix_segments=0):
-    """
-    Updates paths inside attentions to the new naming scheme (local renaming)
-    """
-    mapping = []
-    for old_item in old_list:
-        new_item = old_item
-
-        new_item = new_item.replace("norm.weight", "group_norm.weight")
-        new_item = new_item.replace("norm.bias", "group_norm.bias")
-
-        new_item = new_item.replace("q.weight", "to_q.weight")
-        new_item = new_item.replace("q.bias", "to_q.bias")
-
-        new_item = new_item.replace("k.weight", "to_k.weight")
-        new_item = new_item.replace("k.bias", "to_k.bias")
-
-        new_item = new_item.replace("v.weight", "to_v.weight")
-        new_item = new_item.replace("v.bias", "to_v.bias")
-
-        new_item = new_item.replace("proj_out.weight", "to_out.0.weight")
-        new_item = new_item.replace("proj_out.bias", "to_out.0.bias")
-
-        new_item = shave_segments(new_item, n_shave_prefix_segments=n_shave_prefix_segments)
-
-        mapping.append({"old": old_item, "new": new_item})
-
-    return mapping
-
-
-def assign_to_checkpoint(
-    paths, checkpoint, old_checkpoint, attention_paths_to_split=None, additional_replacements=None, config=None
-):
-    """
-    This does the final conversion step: take locally converted weights and apply a global renaming to them. It splits
-    attention layers, and takes into account additional replacements that may arise.
-
-    Assigns the weights to the new checkpoint.
-    """
-    assert isinstance(paths, list), "Paths should be a list of dicts containing 'old' and 'new' keys."
-
-    # Splits the attention layers into three variables.
-    if attention_paths_to_split is not None:
-        for path, path_map in attention_paths_to_split.items():
-            old_tensor = old_checkpoint[path]
-            channels = old_tensor.shape[0] // 3
-
-            target_shape = (-1, channels) if len(old_tensor.shape) == 3 else (-1)
-
-            num_heads = old_tensor.shape[0] // config["num_head_channels"] // 3
-
-            old_tensor = old_tensor.reshape((num_heads, 3 * channels // num_heads) + old_tensor.shape[1:])
-            query, key, value = old_tensor.split(channels // num_heads, dim=1)
-
-            checkpoint[path_map["query"]] = query.reshape(target_shape)
-            checkpoint[path_map["key"]] = key.reshape(target_shape)
-            checkpoint[path_map["value"]] = value.reshape(target_shape)
-
-    for path in paths:
-        new_path = path["new"]
-
-        # These have already been assigned
-        if attention_paths_to_split is not None and new_path in attention_paths_to_split:
-            continue
-
-        # Global renaming happens here
-        new_path = new_path.replace("middle_block.0", "mid_block.resnets.0")
-        new_path = new_path.replace("middle_block.1", "mid_block.attentions.0")
-        new_path = new_path.replace("middle_block.2", "mid_block.resnets.1")
-
-        if additional_replacements is not None:
-            for replacement in additional_replacements:
-                new_path = new_path.replace(replacement["old"], replacement["new"])
-
-        # proj_attn.weight has to be converted from conv 1D to linear
-        is_attn_weight = "proj_attn.weight" in new_path or ("attentions" in new_path and "to_" in new_path)
-        shape = old_checkpoint[path["old"]].shape
-        if is_attn_weight and len(shape) == 3:
-            checkpoint[new_path] = old_checkpoint[path["old"]][:, :, 0]
-        elif is_attn_weight and len(shape) == 4:
-            checkpoint[new_path] = old_checkpoint[path["old"]][:, :, 0, 0]
-        else:
-            checkpoint[new_path] = old_checkpoint[path["old"]]
-
-
-def conv_attn_to_linear(checkpoint):
-    keys = list(checkpoint.keys())
-    attn_keys = ["query.weight", "key.weight", "value.weight"]
-    for key in keys:
-        if ".".join(key.split(".")[-2:]) in attn_keys:
-            if checkpoint[key].ndim > 2:
-                checkpoint[key] = checkpoint[key][:, :, 0, 0]
-        elif "proj_attn.weight" in key:
-            if checkpoint[key].ndim > 2:
-                checkpoint[key] = checkpoint[key][:, :, 0]
-
-
-def create_unet_diffusers_config(original_config, image_size: int, controlnet=False):
-    """
-    Creates a config for the diffusers based on the config of the LDM model.
-    """
-    if controlnet:
-        unet_params = original_config.model.params.control_stage_config.params
-    else:
-        if "unet_config" in original_config.model.params and original_config.model.params.unet_config is not None:
-            unet_params = original_config.model.params.unet_config.params
-        else:
-            unet_params = original_config.model.params.network_config.params
-
-    vae_params = original_config.model.params.first_stage_config.params.ddconfig
-
-    block_out_channels = [unet_params.model_channels * mult for mult in unet_params.channel_mult]
-
-    down_block_types = []
-    resolution = 1
-    for i in range(len(block_out_channels)):
-        block_type = "CrossAttnDownBlock2D" if resolution in unet_params.attention_resolutions else "DownBlock2D"
-        down_block_types.append(block_type)
-        if i != len(block_out_channels) - 1:
-            resolution *= 2
-
-    up_block_types = []
-    for _i in range(len(block_out_channels)):
-        block_type = "CrossAttnUpBlock2D" if resolution in unet_params.attention_resolutions else "UpBlock2D"
-        up_block_types.append(block_type)
-        resolution //= 2
-
-    if unet_params.transformer_depth is not None:
-        transformer_layers_per_block = (
-            unet_params.transformer_depth
-            if isinstance(unet_params.transformer_depth, int)
-            else list(unet_params.transformer_depth)
-        )
-    else:
-        transformer_layers_per_block = 1
-
-    vae_scale_factor = 2 ** (len(vae_params.ch_mult) - 1)
-
-    head_dim = unet_params.num_heads if "num_heads" in unet_params else None
-    use_linear_projection = (
-        unet_params.use_linear_in_transformer if "use_linear_in_transformer" in unet_params else False
-    )
-    if use_linear_projection:
-        # stable diffusion 2-base-512 and 2-768
-        if head_dim is None:
-            head_dim_mult = unet_params.model_channels // unet_params.num_head_channels
-            head_dim = [head_dim_mult * c for c in list(unet_params.channel_mult)]
-
-    class_embed_type = None
-    addition_embed_type = None
-    addition_time_embed_dim = None
-    projection_class_embeddings_input_dim = None
-    context_dim = None
-
-    if unet_params.context_dim is not None:
-        context_dim = (
-            unet_params.context_dim if isinstance(unet_params.context_dim, int) else unet_params.context_dim[0]
-        )
-
-    if "num_classes" in unet_params:
-        if unet_params.num_classes == "sequential":
-            if context_dim in [2048, 1280]:
-                # SDXL
-                addition_embed_type = "text_time"
-                addition_time_embed_dim = 256
-            else:
-                class_embed_type = "projection"
-            assert "adm_in_channels" in unet_params
-            projection_class_embeddings_input_dim = unet_params.adm_in_channels
-        else:
-            raise NotImplementedError(f"Unknown conditional unet num_classes config: {unet_params.num_classes}")
-
-    config = {
-        "sample_size": image_size // vae_scale_factor,
-        "in_channels": unet_params.in_channels,
-        "down_block_types": tuple(down_block_types),
-        "block_out_channels": tuple(block_out_channels),
-        "layers_per_block": unet_params.num_res_blocks,
-        "cross_attention_dim": context_dim,
-        "attention_head_dim": head_dim,
-        "use_linear_projection": use_linear_projection,
-        "class_embed_type": class_embed_type,
-        "addition_embed_type": addition_embed_type,
-        "addition_time_embed_dim": addition_time_embed_dim,
-        "projection_class_embeddings_input_dim": projection_class_embeddings_input_dim,
-        "transformer_layers_per_block": transformer_layers_per_block,
-    }
-
-    if controlnet:
-        config["conditioning_channels"] = unet_params.hint_channels
-    else:
-        config["out_channels"] = unet_params.out_channels
-        config["up_block_types"] = tuple(up_block_types)
-
-    return config
-
-
-def create_vae_diffusers_config(original_config, image_size: int):
-    """
-    Creates a config for the diffusers based on the config of the LDM model.
-    """
-    vae_params = original_config.model.params.first_stage_config.params.ddconfig
-    _ = original_config.model.params.first_stage_config.params.embed_dim
-
-    block_out_channels = [vae_params.ch * mult for mult in vae_params.ch_mult]
-    down_block_types = ["DownEncoderBlock2D"] * len(block_out_channels)
-    up_block_types = ["UpDecoderBlock2D"] * len(block_out_channels)
-
-    config = {
-        "sample_size": image_size,
-        "in_channels": vae_params.in_channels,
-        "out_channels": vae_params.out_ch,
-        "down_block_types": tuple(down_block_types),
-        "up_block_types": tuple(up_block_types),
-        "block_out_channels": tuple(block_out_channels),
-        "latent_channels": vae_params.z_channels,
-        "layers_per_block": vae_params.num_res_blocks,
-    }
-    return config
-
-
-def create_diffusers_schedular(original_config):
-    schedular = DDIMScheduler(
-        num_train_timesteps=original_config.model.params.timesteps,
-        beta_start=original_config.model.params.linear_start,
-        beta_end=original_config.model.params.linear_end,
-        beta_schedule="scaled_linear",
-    )
-    return schedular
-
-
-def create_ldm_bert_config(original_config):
-    bert_params = original_config.model.parms.cond_stage_config.params
-    config = LDMBertConfig(
-        d_model=bert_params.n_embed,
-        encoder_layers=bert_params.n_layer,
-        encoder_ffn_dim=bert_params.n_embed * 4,
-    )
-    return config
-
-
-def convert_ldm_unet_checkpoint(
-    checkpoint, config, path=None, extract_ema=False, controlnet=False, skip_extract_state_dict=False
-):
-    """
-    Takes a state dict and a config, and returns a converted checkpoint.
-    """
-
-    if skip_extract_state_dict:
-        unet_state_dict = checkpoint
-    else:
-        # extract state_dict for UNet
-        unet_state_dict = {}
-        keys = list(checkpoint.keys())
-
-        if controlnet:
-            unet_key = "control_model."
-        else:
-            unet_key = "model.diffusion_model."
-
-        # at least a 100 parameters have to start with `model_ema` in order for the checkpoint to be EMA
-        if sum(k.startswith("model_ema") for k in keys) > 100 and extract_ema:
-            logger.warning(f"Checkpoint {path} has both EMA and non-EMA weights.")
-            logger.warning(
-                "In this conversion only the EMA weights are extracted. If you want to instead extract the non-EMA"
-                " weights (useful to continue fine-tuning), please make sure to remove the `--extract_ema` flag."
-            )
-            for key in keys:
-                if key.startswith("model.diffusion_model"):
-                    flat_ema_key = "model_ema." + "".join(key.split(".")[1:])
-                    unet_state_dict[key.replace(unet_key, "")] = checkpoint.pop(flat_ema_key)
-        else:
-            if sum(k.startswith("model_ema") for k in keys) > 100:
-                logger.warning(
-                    "In this conversion only the non-EMA weights are extracted. If you want to instead extract the EMA"
-                    " weights (usually better for inference), please make sure to add the `--extract_ema` flag."
-                )
-
-            for key in keys:
-                if key.startswith(unet_key):
-                    unet_state_dict[key.replace(unet_key, "")] = checkpoint.pop(key)
-
-    new_checkpoint = {}
-
-    new_checkpoint["time_embedding.linear_1.weight"] = unet_state_dict["time_embed.0.weight"]
-    new_checkpoint["time_embedding.linear_1.bias"] = unet_state_dict["time_embed.0.bias"]
-    new_checkpoint["time_embedding.linear_2.weight"] = unet_state_dict["time_embed.2.weight"]
-    new_checkpoint["time_embedding.linear_2.bias"] = unet_state_dict["time_embed.2.bias"]
-
-    if config["class_embed_type"] is None:
-        # No parameters to port
-        ...
-    elif config["class_embed_type"] == "timestep" or config["class_embed_type"] == "projection":
-        new_checkpoint["class_embedding.linear_1.weight"] = unet_state_dict["label_emb.0.0.weight"]
-        new_checkpoint["class_embedding.linear_1.bias"] = unet_state_dict["label_emb.0.0.bias"]
-        new_checkpoint["class_embedding.linear_2.weight"] = unet_state_dict["label_emb.0.2.weight"]
-        new_checkpoint["class_embedding.linear_2.bias"] = unet_state_dict["label_emb.0.2.bias"]
-    else:
-        raise NotImplementedError(f"Not implemented `class_embed_type`: {config['class_embed_type']}")
-
-    if config["addition_embed_type"] == "text_time":
-        new_checkpoint["add_embedding.linear_1.weight"] = unet_state_dict["label_emb.0.0.weight"]
-        new_checkpoint["add_embedding.linear_1.bias"] = unet_state_dict["label_emb.0.0.bias"]
-        new_checkpoint["add_embedding.linear_2.weight"] = unet_state_dict["label_emb.0.2.weight"]
-        new_checkpoint["add_embedding.linear_2.bias"] = unet_state_dict["label_emb.0.2.bias"]
-
-    new_checkpoint["conv_in.weight"] = unet_state_dict["input_blocks.0.0.weight"]
-    new_checkpoint["conv_in.bias"] = unet_state_dict["input_blocks.0.0.bias"]
-
-    if not controlnet:
-        new_checkpoint["conv_norm_out.weight"] = unet_state_dict["out.0.weight"]
-        new_checkpoint["conv_norm_out.bias"] = unet_state_dict["out.0.bias"]
-        new_checkpoint["conv_out.weight"] = unet_state_dict["out.2.weight"]
-        new_checkpoint["conv_out.bias"] = unet_state_dict["out.2.bias"]
-
-    # Retrieves the keys for the input blocks only
-    num_input_blocks = len({".".join(layer.split(".")[:2]) for layer in unet_state_dict if "input_blocks" in layer})
-    input_blocks = {
-        layer_id: [key for key in unet_state_dict if f"input_blocks.{layer_id}" in key]
-        for layer_id in range(num_input_blocks)
-    }
-
-    # Retrieves the keys for the middle blocks only
-    num_middle_blocks = len({".".join(layer.split(".")[:2]) for layer in unet_state_dict if "middle_block" in layer})
-    middle_blocks = {
-        layer_id: [key for key in unet_state_dict if f"middle_block.{layer_id}" in key]
-        for layer_id in range(num_middle_blocks)
-    }
-
-    # Retrieves the keys for the output blocks only
-    num_output_blocks = len({".".join(layer.split(".")[:2]) for layer in unet_state_dict if "output_blocks" in layer})
-    output_blocks = {
-        layer_id: [key for key in unet_state_dict if f"output_blocks.{layer_id}" in key]
-        for layer_id in range(num_output_blocks)
-    }
-
-    for i in range(1, num_input_blocks):
-        block_id = (i - 1) // (config["layers_per_block"] + 1)
-        layer_in_block_id = (i - 1) % (config["layers_per_block"] + 1)
-
-        resnets = [
-            key for key in input_blocks[i] if f"input_blocks.{i}.0" in key and f"input_blocks.{i}.0.op" not in key
-        ]
-        attentions = [key for key in input_blocks[i] if f"input_blocks.{i}.1" in key]
-
-        if f"input_blocks.{i}.0.op.weight" in unet_state_dict:
-            new_checkpoint[f"down_blocks.{block_id}.downsamplers.0.conv.weight"] = unet_state_dict.pop(
-                f"input_blocks.{i}.0.op.weight"
-            )
-            new_checkpoint[f"down_blocks.{block_id}.downsamplers.0.conv.bias"] = unet_state_dict.pop(
-                f"input_blocks.{i}.0.op.bias"
-            )
-
-        paths = renew_resnet_paths(resnets)
-        meta_path = {"old": f"input_blocks.{i}.0", "new": f"down_blocks.{block_id}.resnets.{layer_in_block_id}"}
-        assign_to_checkpoint(paths, new_checkpoint, unet_state_dict, additional_replacements=[meta_path], config=config)
-
-        if len(attentions):
-            paths = renew_attention_paths(attentions)
-            meta_path = {"old": f"input_blocks.{i}.1", "new": f"down_blocks.{block_id}.attentions.{layer_in_block_id}"}
-            assign_to_checkpoint(
-                paths, new_checkpoint, unet_state_dict, additional_replacements=[meta_path], config=config
-            )
-
-    resnet_0 = middle_blocks[0]
-    attentions = middle_blocks[1]
-    resnet_1 = middle_blocks[2]
-
-    resnet_0_paths = renew_resnet_paths(resnet_0)
-    assign_to_checkpoint(resnet_0_paths, new_checkpoint, unet_state_dict, config=config)
-
-    resnet_1_paths = renew_resnet_paths(resnet_1)
-    assign_to_checkpoint(resnet_1_paths, new_checkpoint, unet_state_dict, config=config)
-
-    attentions_paths = renew_attention_paths(attentions)
-    meta_path = {"old": "middle_block.1", "new": "mid_block.attentions.0"}
-    assign_to_checkpoint(
-        attentions_paths, new_checkpoint, unet_state_dict, additional_replacements=[meta_path], config=config
-    )
-
-    for i in range(num_output_blocks):
-        block_id = i // (config["layers_per_block"] + 1)
-        layer_in_block_id = i % (config["layers_per_block"] + 1)
-        output_block_layers = [shave_segments(name, 2) for name in output_blocks[i]]
-        output_block_list = {}
-
-        for layer in output_block_layers:
-            layer_id, layer_name = layer.split(".")[0], shave_segments(layer, 1)
-            if layer_id in output_block_list:
-                output_block_list[layer_id].append(layer_name)
-            else:
-                output_block_list[layer_id] = [layer_name]
-
-        if len(output_block_list) > 1:
-            resnets = [key for key in output_blocks[i] if f"output_blocks.{i}.0" in key]
-            attentions = [key for key in output_blocks[i] if f"output_blocks.{i}.1" in key]
-
-            resnet_0_paths = renew_resnet_paths(resnets)
-            paths = renew_resnet_paths(resnets)
-
-            meta_path = {"old": f"output_blocks.{i}.0", "new": f"up_blocks.{block_id}.resnets.{layer_in_block_id}"}
-            assign_to_checkpoint(
-                paths, new_checkpoint, unet_state_dict, additional_replacements=[meta_path], config=config
-            )
-
-            output_block_list = {k: sorted(v) for k, v in output_block_list.items()}
-            if ["conv.bias", "conv.weight"] in output_block_list.values():
-                index = list(output_block_list.values()).index(["conv.bias", "conv.weight"])
-                new_checkpoint[f"up_blocks.{block_id}.upsamplers.0.conv.weight"] = unet_state_dict[
-                    f"output_blocks.{i}.{index}.conv.weight"
-                ]
-                new_checkpoint[f"up_blocks.{block_id}.upsamplers.0.conv.bias"] = unet_state_dict[
-                    f"output_blocks.{i}.{index}.conv.bias"
-                ]
-
-                # Clear attentions as they have been attributed above.
-                if len(attentions) == 2:
-                    attentions = []
-
-            if len(attentions):
-                paths = renew_attention_paths(attentions)
-                meta_path = {
-                    "old": f"output_blocks.{i}.1",
-                    "new": f"up_blocks.{block_id}.attentions.{layer_in_block_id}",
-                }
-                assign_to_checkpoint(
-                    paths, new_checkpoint, unet_state_dict, additional_replacements=[meta_path], config=config
-                )
-        else:
-            resnet_0_paths = renew_resnet_paths(output_block_layers, n_shave_prefix_segments=1)
-            for path in resnet_0_paths:
-                old_path = ".".join(["output_blocks", str(i), path["old"]])
-                new_path = ".".join(["up_blocks", str(block_id), "resnets", str(layer_in_block_id), path["new"]])
-
-                new_checkpoint[new_path] = unet_state_dict[old_path]
-
-    if controlnet:
-        # conditioning embedding
-
-        orig_index = 0
-
-        new_checkpoint["controlnet_cond_embedding.conv_in.weight"] = unet_state_dict.pop(
-            f"input_hint_block.{orig_index}.weight"
-        )
-        new_checkpoint["controlnet_cond_embedding.conv_in.bias"] = unet_state_dict.pop(
-            f"input_hint_block.{orig_index}.bias"
-        )
-
-        orig_index += 2
-
-        diffusers_index = 0
-
-        while diffusers_index < 6:
-            new_checkpoint[f"controlnet_cond_embedding.blocks.{diffusers_index}.weight"] = unet_state_dict.pop(
-                f"input_hint_block.{orig_index}.weight"
-            )
-            new_checkpoint[f"controlnet_cond_embedding.blocks.{diffusers_index}.bias"] = unet_state_dict.pop(
-                f"input_hint_block.{orig_index}.bias"
-            )
-            diffusers_index += 1
-            orig_index += 2
-
-        new_checkpoint["controlnet_cond_embedding.conv_out.weight"] = unet_state_dict.pop(
-            f"input_hint_block.{orig_index}.weight"
-        )
-        new_checkpoint["controlnet_cond_embedding.conv_out.bias"] = unet_state_dict.pop(
-            f"input_hint_block.{orig_index}.bias"
-        )
-
-        # down blocks
-        for i in range(num_input_blocks):
-            new_checkpoint[f"controlnet_down_blocks.{i}.weight"] = unet_state_dict.pop(f"zero_convs.{i}.0.weight")
-            new_checkpoint[f"controlnet_down_blocks.{i}.bias"] = unet_state_dict.pop(f"zero_convs.{i}.0.bias")
-
-        # mid block
-        new_checkpoint["controlnet_mid_block.weight"] = unet_state_dict.pop("middle_block_out.0.weight")
-        new_checkpoint["controlnet_mid_block.bias"] = unet_state_dict.pop("middle_block_out.0.bias")
-
-    return new_checkpoint
-
-
-def convert_ldm_vae_checkpoint(checkpoint, config):
-    # extract state dict for VAE
-    vae_state_dict = {}
-    keys = list(checkpoint.keys())
-    vae_key = "first_stage_model." if any(k.startswith("first_stage_model.") for k in keys) else ""
-    for key in keys:
-        if key.startswith(vae_key):
-            vae_state_dict[key.replace(vae_key, "")] = checkpoint.get(key)
-
-    new_checkpoint = {}
-
-    new_checkpoint["encoder.conv_in.weight"] = vae_state_dict["encoder.conv_in.weight"]
-    new_checkpoint["encoder.conv_in.bias"] = vae_state_dict["encoder.conv_in.bias"]
-    new_checkpoint["encoder.conv_out.weight"] = vae_state_dict["encoder.conv_out.weight"]
-    new_checkpoint["encoder.conv_out.bias"] = vae_state_dict["encoder.conv_out.bias"]
-    new_checkpoint["encoder.conv_norm_out.weight"] = vae_state_dict["encoder.norm_out.weight"]
-    new_checkpoint["encoder.conv_norm_out.bias"] = vae_state_dict["encoder.norm_out.bias"]
-
-    new_checkpoint["decoder.conv_in.weight"] = vae_state_dict["decoder.conv_in.weight"]
-    new_checkpoint["decoder.conv_in.bias"] = vae_state_dict["decoder.conv_in.bias"]
-    new_checkpoint["decoder.conv_out.weight"] = vae_state_dict["decoder.conv_out.weight"]
-    new_checkpoint["decoder.conv_out.bias"] = vae_state_dict["decoder.conv_out.bias"]
-    new_checkpoint["decoder.conv_norm_out.weight"] = vae_state_dict["decoder.norm_out.weight"]
-    new_checkpoint["decoder.conv_norm_out.bias"] = vae_state_dict["decoder.norm_out.bias"]
-
-    new_checkpoint["quant_conv.weight"] = vae_state_dict["quant_conv.weight"]
-    new_checkpoint["quant_conv.bias"] = vae_state_dict["quant_conv.bias"]
-    new_checkpoint["post_quant_conv.weight"] = vae_state_dict["post_quant_conv.weight"]
-    new_checkpoint["post_quant_conv.bias"] = vae_state_dict["post_quant_conv.bias"]
-
-    # Retrieves the keys for the encoder down blocks only
-    num_down_blocks = len({".".join(layer.split(".")[:3]) for layer in vae_state_dict if "encoder.down" in layer})
-    down_blocks = {
-        layer_id: [key for key in vae_state_dict if f"down.{layer_id}" in key] for layer_id in range(num_down_blocks)
-    }
-
-    # Retrieves the keys for the decoder up blocks only
-    num_up_blocks = len({".".join(layer.split(".")[:3]) for layer in vae_state_dict if "decoder.up" in layer})
-    up_blocks = {
-        layer_id: [key for key in vae_state_dict if f"up.{layer_id}" in key] for layer_id in range(num_up_blocks)
-    }
-
-    for i in range(num_down_blocks):
-        resnets = [key for key in down_blocks[i] if f"down.{i}" in key and f"down.{i}.downsample" not in key]
-
-        if f"encoder.down.{i}.downsample.conv.weight" in vae_state_dict:
-            new_checkpoint[f"encoder.down_blocks.{i}.downsamplers.0.conv.weight"] = vae_state_dict.pop(
-                f"encoder.down.{i}.downsample.conv.weight"
-            )
-            new_checkpoint[f"encoder.down_blocks.{i}.downsamplers.0.conv.bias"] = vae_state_dict.pop(
-                f"encoder.down.{i}.downsample.conv.bias"
-            )
-
-        paths = renew_vae_resnet_paths(resnets)
-        meta_path = {"old": f"down.{i}.block", "new": f"down_blocks.{i}.resnets"}
-        assign_to_checkpoint(paths, new_checkpoint, vae_state_dict, additional_replacements=[meta_path], config=config)
-
-    mid_resnets = [key for key in vae_state_dict if "encoder.mid.block" in key]
-    num_mid_res_blocks = 2
-    for i in range(1, num_mid_res_blocks + 1):
-        resnets = [key for key in mid_resnets if f"encoder.mid.block_{i}" in key]
-
-        paths = renew_vae_resnet_paths(resnets)
-        meta_path = {"old": f"mid.block_{i}", "new": f"mid_block.resnets.{i - 1}"}
-        assign_to_checkpoint(paths, new_checkpoint, vae_state_dict, additional_replacements=[meta_path], config=config)
-
-    mid_attentions = [key for key in vae_state_dict if "encoder.mid.attn" in key]
-    paths = renew_vae_attention_paths(mid_attentions)
-    meta_path = {"old": "mid.attn_1", "new": "mid_block.attentions.0"}
-    assign_to_checkpoint(paths, new_checkpoint, vae_state_dict, additional_replacements=[meta_path], config=config)
-    conv_attn_to_linear(new_checkpoint)
-
-    for i in range(num_up_blocks):
-        block_id = num_up_blocks - 1 - i
-        resnets = [
-            key for key in up_blocks[block_id] if f"up.{block_id}" in key and f"up.{block_id}.upsample" not in key
-        ]
-
-        if f"decoder.up.{block_id}.upsample.conv.weight" in vae_state_dict:
-            new_checkpoint[f"decoder.up_blocks.{i}.upsamplers.0.conv.weight"] = vae_state_dict[
-                f"decoder.up.{block_id}.upsample.conv.weight"
-            ]
-            new_checkpoint[f"decoder.up_blocks.{i}.upsamplers.0.conv.bias"] = vae_state_dict[
-                f"decoder.up.{block_id}.upsample.conv.bias"
-            ]
-
-        paths = renew_vae_resnet_paths(resnets)
-        meta_path = {"old": f"up.{block_id}.block", "new": f"up_blocks.{i}.resnets"}
-        assign_to_checkpoint(paths, new_checkpoint, vae_state_dict, additional_replacements=[meta_path], config=config)
-
-    mid_resnets = [key for key in vae_state_dict if "decoder.mid.block" in key]
-    num_mid_res_blocks = 2
-    for i in range(1, num_mid_res_blocks + 1):
-        resnets = [key for key in mid_resnets if f"decoder.mid.block_{i}" in key]
-
-        paths = renew_vae_resnet_paths(resnets)
-        meta_path = {"old": f"mid.block_{i}", "new": f"mid_block.resnets.{i - 1}"}
-        assign_to_checkpoint(paths, new_checkpoint, vae_state_dict, additional_replacements=[meta_path], config=config)
-
-    mid_attentions = [key for key in vae_state_dict if "decoder.mid.attn" in key]
-    paths = renew_vae_attention_paths(mid_attentions)
-    meta_path = {"old": "mid.attn_1", "new": "mid_block.attentions.0"}
-    assign_to_checkpoint(paths, new_checkpoint, vae_state_dict, additional_replacements=[meta_path], config=config)
-    conv_attn_to_linear(new_checkpoint)
-    return new_checkpoint
-
-
-def convert_ldm_bert_checkpoint(checkpoint, config):
-    def _copy_attn_layer(hf_attn_layer, pt_attn_layer):
-        hf_attn_layer.q_proj.weight.data = pt_attn_layer.to_q.weight
-        hf_attn_layer.k_proj.weight.data = pt_attn_layer.to_k.weight
-        hf_attn_layer.v_proj.weight.data = pt_attn_layer.to_v.weight
-
-        hf_attn_layer.out_proj.weight = pt_attn_layer.to_out.weight
-        hf_attn_layer.out_proj.bias = pt_attn_layer.to_out.bias
-
-    def _copy_linear(hf_linear, pt_linear):
-        hf_linear.weight = pt_linear.weight
-        hf_linear.bias = pt_linear.bias
-
-    def _copy_layer(hf_layer, pt_layer):
-        # copy layer norms
-        _copy_linear(hf_layer.self_attn_layer_norm, pt_layer[0][0])
-        _copy_linear(hf_layer.final_layer_norm, pt_layer[1][0])
-
-        # copy attn
-        _copy_attn_layer(hf_layer.self_attn, pt_layer[0][1])
-
-        # copy MLP
-        pt_mlp = pt_layer[1][1]
-        _copy_linear(hf_layer.fc1, pt_mlp.net[0][0])
-        _copy_linear(hf_layer.fc2, pt_mlp.net[2])
-
-    def _copy_layers(hf_layers, pt_layers):
-        for i, hf_layer in enumerate(hf_layers):
-            if i != 0:
-                i += i
-            pt_layer = pt_layers[i : i + 2]
-            _copy_layer(hf_layer, pt_layer)
-
-    hf_model = LDMBertModel(config).eval()
-
-    # copy  embeds
-    hf_model.model.embed_tokens.weight = checkpoint.transformer.token_emb.weight
-    hf_model.model.embed_positions.weight.data = checkpoint.transformer.pos_emb.emb.weight
-
-    # copy layer norm
-    _copy_linear(hf_model.model.layer_norm, checkpoint.transformer.norm)
-
-    # copy hidden layers
-    _copy_layers(hf_model.model.layers, checkpoint.transformer.attn_layers.layers)
-
-    _copy_linear(hf_model.to_logits, checkpoint.transformer.to_logits)
-
-    return hf_model
-
-
-def convert_ldm_clip_checkpoint(checkpoint, local_files_only=False, text_encoder=None):
-    if text_encoder is None:
-        config = CLIPTextConfig.from_pretrained(CONVERT_MODEL_ROOT / "clip-vit-large-patch14")
-
-        ctx = init_empty_weights if is_accelerate_available() else nullcontext
-        with ctx():
-            text_model = CLIPTextModel(config)
-
-    keys = list(checkpoint.keys())
-
-    text_model_dict = {}
-
-    remove_prefixes = ["cond_stage_model.transformer", "conditioner.embedders.0.transformer"]
-
-    for key in keys:
-        for prefix in remove_prefixes:
-            if key.startswith(prefix):
-                text_model_dict[key[len(prefix + ".") :]] = checkpoint[key]
-
-    if is_accelerate_available():
-        for param_name, param in text_model_dict.items():
-            set_module_tensor_to_device(text_model, param_name, "cpu", value=param)
-    else:
-        text_model.load_state_dict(text_model_dict)
-
-    return text_model
-
-
-textenc_conversion_lst = [
-    ("positional_embedding", "text_model.embeddings.position_embedding.weight"),
-    ("token_embedding.weight", "text_model.embeddings.token_embedding.weight"),
-    ("ln_final.weight", "text_model.final_layer_norm.weight"),
-    ("ln_final.bias", "text_model.final_layer_norm.bias"),
-    ("text_projection", "text_projection.weight"),
-]
-textenc_conversion_map = {x[0]: x[1] for x in textenc_conversion_lst}
-
-textenc_transformer_conversion_lst = [
-    # (stable-diffusion, HF Diffusers)
-    ("resblocks.", "text_model.encoder.layers."),
-    ("ln_1", "layer_norm1"),
-    ("ln_2", "layer_norm2"),
-    (".c_fc.", ".fc1."),
-    (".c_proj.", ".fc2."),
-    (".attn", ".self_attn"),
-    ("ln_final.", "transformer.text_model.final_layer_norm."),
-    ("token_embedding.weight", "transformer.text_model.embeddings.token_embedding.weight"),
-    ("positional_embedding", "transformer.text_model.embeddings.position_embedding.weight"),
-]
-protected = {re.escape(x[0]): x[1] for x in textenc_transformer_conversion_lst}
-textenc_pattern = re.compile("|".join(protected.keys()))
-
-
-def convert_paint_by_example_checkpoint(checkpoint):
-    config = CLIPVisionConfig.from_pretrained(CONVERT_MODEL_ROOT / "clip-vit-large-patch14")
-    model = PaintByExampleImageEncoder(config)
-
-    keys = list(checkpoint.keys())
-
-    text_model_dict = {}
-
-    for key in keys:
-        if key.startswith("cond_stage_model.transformer"):
-            text_model_dict[key[len("cond_stage_model.transformer.") :]] = checkpoint[key]
-
-    # load clip vision
-    model.model.load_state_dict(text_model_dict)
-
-    # load mapper
-    keys_mapper = {
-        k[len("cond_stage_model.mapper.res") :]: v
-        for k, v in checkpoint.items()
-        if k.startswith("cond_stage_model.mapper")
-    }
-
-    MAPPING = {
-        "attn.c_qkv": ["attn1.to_q", "attn1.to_k", "attn1.to_v"],
-        "attn.c_proj": ["attn1.to_out.0"],
-        "ln_1": ["norm1"],
-        "ln_2": ["norm3"],
-        "mlp.c_fc": ["ff.net.0.proj"],
-        "mlp.c_proj": ["ff.net.2"],
-    }
-
-    mapped_weights = {}
-    for key, value in keys_mapper.items():
-        prefix = key[: len("blocks.i")]
-        suffix = key.split(prefix)[-1].split(".")[-1]
-        name = key.split(prefix)[-1].split(suffix)[0][1:-1]
-        mapped_names = MAPPING[name]
-
-        num_splits = len(mapped_names)
-        for i, mapped_name in enumerate(mapped_names):
-            new_name = ".".join([prefix, mapped_name, suffix])
-            shape = value.shape[0] // num_splits
-            mapped_weights[new_name] = value[i * shape : (i + 1) * shape]
-
-    model.mapper.load_state_dict(mapped_weights)
-
-    # load final layer norm
-    model.final_layer_norm.load_state_dict(
-        {
-            "bias": checkpoint["cond_stage_model.final_ln.bias"],
-            "weight": checkpoint["cond_stage_model.final_ln.weight"],
-        }
-    )
-
-    # load final proj
-    model.proj_out.load_state_dict(
-        {
-            "bias": checkpoint["proj_out.bias"],
-            "weight": checkpoint["proj_out.weight"],
-        }
-    )
-
-    # load uncond vector
-    model.uncond_vector.data = torch.nn.Parameter(checkpoint["learnable_vector"])
-    return model
-
-
-def convert_open_clip_checkpoint(
-    checkpoint, config_name, prefix="cond_stage_model.model.", has_projection=False, **config_kwargs
-):
-    # text_model = CLIPTextModel.from_pretrained("stabilityai/stable-diffusion-2", subfolder="text_encoder")
-    # text_model = CLIPTextModelWithProjection.from_pretrained(
-    #    "laion/CLIP-ViT-bigG-14-laion2B-39B-b160k", projection_dim=1280
-    # )
-    config = CLIPTextConfig.from_pretrained(config_name, **config_kwargs)
-
-    ctx = init_empty_weights if is_accelerate_available() else nullcontext
-    with ctx():
-        text_model = CLIPTextModelWithProjection(config) if has_projection else CLIPTextModel(config)
-
-    keys = list(checkpoint.keys())
-
-    keys_to_ignore = []
-    if config_name == "stabilityai/stable-diffusion-2" and config.num_hidden_layers == 23:
-        # make sure to remove all keys > 22
-        keys_to_ignore += [k for k in keys if k.startswith("cond_stage_model.model.transformer.resblocks.23")]
-        keys_to_ignore += ["cond_stage_model.model.text_projection"]
-
-    text_model_dict = {}
-
-    if prefix + "text_projection" in checkpoint:
-        d_model = int(checkpoint[prefix + "text_projection"].shape[0])
-    else:
-        d_model = 1024
-
-    text_model_dict["text_model.embeddings.position_ids"] = text_model.text_model.embeddings.get_buffer("position_ids")
-
-    for key in keys:
-        if key in keys_to_ignore:
-            continue
-        if key[len(prefix) :] in textenc_conversion_map:
-            if key.endswith("text_projection"):
-                value = checkpoint[key].T.contiguous()
-            else:
-                value = checkpoint[key]
-
-            text_model_dict[textenc_conversion_map[key[len(prefix) :]]] = value
-
-        if key.startswith(prefix + "transformer."):
-            new_key = key[len(prefix + "transformer.") :]
-            if new_key.endswith(".in_proj_weight"):
-                new_key = new_key[: -len(".in_proj_weight")]
-                new_key = textenc_pattern.sub(lambda m: protected[re.escape(m.group(0))], new_key)
-                text_model_dict[new_key + ".q_proj.weight"] = checkpoint[key][:d_model, :]
-                text_model_dict[new_key + ".k_proj.weight"] = checkpoint[key][d_model : d_model * 2, :]
-                text_model_dict[new_key + ".v_proj.weight"] = checkpoint[key][d_model * 2 :, :]
-            elif new_key.endswith(".in_proj_bias"):
-                new_key = new_key[: -len(".in_proj_bias")]
-                new_key = textenc_pattern.sub(lambda m: protected[re.escape(m.group(0))], new_key)
-                text_model_dict[new_key + ".q_proj.bias"] = checkpoint[key][:d_model]
-                text_model_dict[new_key + ".k_proj.bias"] = checkpoint[key][d_model : d_model * 2]
-                text_model_dict[new_key + ".v_proj.bias"] = checkpoint[key][d_model * 2 :]
-            else:
-                new_key = textenc_pattern.sub(lambda m: protected[re.escape(m.group(0))], new_key)
-
-                text_model_dict[new_key] = checkpoint[key]
-
-    if is_accelerate_available():
-        for param_name, param in text_model_dict.items():
-            set_module_tensor_to_device(text_model, param_name, "cpu", value=param)
-    else:
-        text_model.load_state_dict(text_model_dict)
-
-    return text_model
-
-
-def stable_unclip_image_encoder(original_config):
-    """
-    Returns the image processor and clip image encoder for the img2img unclip pipeline.
-
-    We currently know of two types of stable unclip models which separately use the clip and the openclip image
-    encoders.
-    """
-
-    image_embedder_config = original_config.model.params.embedder_config
-
-    sd_clip_image_embedder_class = image_embedder_config.target
-    sd_clip_image_embedder_class = sd_clip_image_embedder_class.split(".")[-1]
-
-    if sd_clip_image_embedder_class == "ClipImageEmbedder":
-        clip_model_name = image_embedder_config.params.model
-
-        if clip_model_name == "ViT-L/14":
-            feature_extractor = CLIPImageProcessor()
-            image_encoder = CLIPVisionModelWithProjection.from_pretrained(CONVERT_MODEL_ROOT / "clip-vit-large-patch14")
-        else:
-            raise NotImplementedError(f"Unknown CLIP checkpoint name in stable diffusion checkpoint {clip_model_name}")
-
-    elif sd_clip_image_embedder_class == "FrozenOpenCLIPImageEmbedder":
-        feature_extractor = CLIPImageProcessor()
-        # InvokeAI doesn't use CLIPVisionModelWithProjection so it isn't in the core - if this code is hit a download will occur
-        image_encoder = CLIPVisionModelWithProjection.from_pretrained(
-            CONVERT_MODEL_ROOT / "CLIP-ViT-H-14-laion2B-s32B-b79K"
-        )
-    else:
-        raise NotImplementedError(
-            f"Unknown CLIP image embedder class in stable diffusion checkpoint {sd_clip_image_embedder_class}"
-        )
-
-    return feature_extractor, image_encoder
-
-
-def stable_unclip_image_noising_components(
-    original_config, clip_stats_path: Optional[str] = None, device: Optional[str] = None
-):
-    """
-    Returns the noising components for the img2img and txt2img unclip pipelines.
-
-    Converts the stability noise augmentor into
-    1. a `StableUnCLIPImageNormalizer` for holding the CLIP stats
-    2. a `DDPMScheduler` for holding the noise schedule
-
-    If the noise augmentor config specifies a clip stats path, the `clip_stats_path` must be provided.
-    """
-    noise_aug_config = original_config.model.params.noise_aug_config
-    noise_aug_class = noise_aug_config.target
-    noise_aug_class = noise_aug_class.split(".")[-1]
-
-    if noise_aug_class == "CLIPEmbeddingNoiseAugmentation":
-        noise_aug_config = noise_aug_config.params
-        embedding_dim = noise_aug_config.timestep_dim
-        max_noise_level = noise_aug_config.noise_schedule_config.timesteps
-        beta_schedule = noise_aug_config.noise_schedule_config.beta_schedule
-
-        image_normalizer = StableUnCLIPImageNormalizer(embedding_dim=embedding_dim)
-        image_noising_scheduler = DDPMScheduler(num_train_timesteps=max_noise_level, beta_schedule=beta_schedule)
-
-        if "clip_stats_path" in noise_aug_config:
-            if clip_stats_path is None:
-                raise ValueError("This stable unclip config requires a `clip_stats_path`")
-
-            clip_mean, clip_std = torch.load(clip_stats_path, map_location=device)
-            clip_mean = clip_mean[None, :]
-            clip_std = clip_std[None, :]
-
-            clip_stats_state_dict = {
-                "mean": clip_mean,
-                "std": clip_std,
-            }
-
-            image_normalizer.load_state_dict(clip_stats_state_dict)
-    else:
-        raise NotImplementedError(f"Unknown noise augmentor class: {noise_aug_class}")
-
-    return image_normalizer, image_noising_scheduler
-
-
-def convert_controlnet_checkpoint(
-    checkpoint,
-    original_config,
-    checkpoint_path,
-    image_size,
-    upcast_attention,
-    extract_ema,
-    use_linear_projection=None,
-    cross_attention_dim=None,
-    precision: Optional[torch.dtype] = None,
-):
-    ctrlnet_config = create_unet_diffusers_config(original_config, image_size=image_size, controlnet=True)
-    ctrlnet_config["upcast_attention"] = upcast_attention
-
-    ctrlnet_config.pop("sample_size")
-    original_config = ctrlnet_config.copy()
-
-    ctrlnet_config.pop("addition_embed_type")
-    ctrlnet_config.pop("addition_time_embed_dim")
-    ctrlnet_config.pop("transformer_layers_per_block")
-
-    if use_linear_projection is not None:
-        ctrlnet_config["use_linear_projection"] = use_linear_projection
-
-    if cross_attention_dim is not None:
-        ctrlnet_config["cross_attention_dim"] = cross_attention_dim
-
-    controlnet = ControlNetModel(**ctrlnet_config)
-
-    # Some controlnet ckpt files are distributed independently from the rest of the
-    # model components i.e. https://huggingface.co/thibaud/controlnet-sd21/
-    if "time_embed.0.weight" in checkpoint:
-        skip_extract_state_dict = True
-    else:
-        skip_extract_state_dict = False
-
-    converted_ctrl_checkpoint = convert_ldm_unet_checkpoint(
-        checkpoint,
-        original_config,
-        path=checkpoint_path,
-        extract_ema=extract_ema,
-        controlnet=True,
-        skip_extract_state_dict=skip_extract_state_dict,
-    )
-
-    controlnet.load_state_dict(converted_ctrl_checkpoint)
-
-    return controlnet.to(precision)
-
-
-def download_from_original_stable_diffusion_ckpt(
-    checkpoint_path: str,
-    model_version: BaseModelType,
-    model_variant: ModelVariantType,
-    original_config_file: str = None,
-    image_size: Optional[int] = None,
-    prediction_type: str = None,
-    model_type: str = None,
-    extract_ema: bool = False,
-    precision: Optional[torch.dtype] = None,
-    scheduler_type: str = "pndm",
-    num_in_channels: Optional[int] = None,
-    upcast_attention: Optional[bool] = None,
-    device: str = None,
-    from_safetensors: bool = False,
-    stable_unclip: Optional[str] = None,
-    stable_unclip_prior: Optional[str] = None,
-    clip_stats_path: Optional[str] = None,
-    controlnet: Optional[bool] = None,
-    load_safety_checker: bool = True,
-    pipeline_class: DiffusionPipeline = None,
-    local_files_only=False,
-    vae_path=None,
-    text_encoder=None,
-    tokenizer=None,
-    scan_needed: bool = True,
-) -> DiffusionPipeline:
-    """
-    Load a Stable Diffusion pipeline object from a CompVis-style `.ckpt`/`.safetensors` file and (ideally) a `.yaml`
-    config file.
-
-    Although many of the arguments can be automatically inferred, some of these rely on brittle checks against the
-    global step count, which will likely fail for models that have undergone further fine-tuning. Therefore, it is
-    recommended that you override the default values and/or supply an `original_config_file` wherever possible.
-
-    Args:
-        checkpoint_path (`str`): Path to `.ckpt` file.
-        original_config_file (`str`):
-            Path to `.yaml` config file corresponding to the original architecture. If `None`, will be automatically
-            inferred by looking for a key that only exists in SD2.0 models.
-        image_size (`int`, *optional*, defaults to 512):
-            The image size that the model was trained on. Use 512 for Stable Diffusion v1.X and Stable Diffusion v2
-            Base. Use 768 for Stable Diffusion v2.
-        prediction_type (`str`, *optional*):
-            The prediction type that the model was trained on. Use `'epsilon'` for Stable Diffusion v1.X and Stable
-            Diffusion v2 Base. Use `'v_prediction'` for Stable Diffusion v2.
-        num_in_channels (`int`, *optional*, defaults to None):
-            The number of input channels. If `None`, it will be automatically inferred.
-        scheduler_type (`str`, *optional*, defaults to 'pndm'):
-            Type of scheduler to use. Should be one of `["pndm", "lms", "heun", "euler", "euler-ancestral", "dpm",
-            "ddim"]`.
-        model_type (`str`, *optional*, defaults to `None`):
-            The pipeline type. `None` to automatically infer, or one of `["FrozenOpenCLIPEmbedder",
-            "FrozenCLIPEmbedder", "PaintByExample"]`.
-        is_img2img (`bool`, *optional*, defaults to `False`):
-            Whether the model should be loaded as an img2img pipeline.
-        extract_ema (`bool`, *optional*, defaults to `False`): Only relevant for
-            checkpoints that have both EMA and non-EMA weights. Whether to extract the EMA weights or not. Defaults to
-            `False`. Pass `True` to extract the EMA weights. EMA weights usually yield higher quality images for
-            inference. Non-EMA weights are usually better to continue fine-tuning.
-        upcast_attention (`bool`, *optional*, defaults to `None`):
-            Whether the attention computation should always be upcasted. This is necessary when running stable
-            diffusion 2.1.
-        device (`str`, *optional*, defaults to `None`):
-            The device to use. Pass `None` to determine automatically.
-        from_safetensors (`str`, *optional*, defaults to `False`):
-            If `checkpoint_path` is in `safetensors` format, load checkpoint with safetensors instead of PyTorch.
-        load_safety_checker (`bool`, *optional*, defaults to `True`):
-            Whether to load the safety checker or not. Defaults to `True`.
-        pipeline_class (`str`, *optional*, defaults to `None`):
-            The pipeline class to use. Pass `None` to determine automatically.
-        local_files_only (`bool`, *optional*, defaults to `False`):
-            Whether or not to only look at local files (i.e., do not try to download the model).
-        text_encoder (`CLIPTextModel`, *optional*, defaults to `None`):
-            An instance of [CLIP](https://huggingface.co/docs/transformers/model_doc/clip#transformers.CLIPTextModel)
-            to use, specifically the [clip-vit-large-patch14](https://huggingface.co/openai/clip-vit-large-patch14)
-            variant. If this parameter is `None`, the function will load a new instance of [CLIP] by itself, if needed.
-        tokenizer (`CLIPTokenizer`, *optional*, defaults to `None`):
-            An instance of
-            [CLIPTokenizer](https://huggingface.co/docs/transformers/v4.21.0/en/model_doc/clip#transformers.CLIPTokenizer)
-            to use. If this parameter is `None`, the function will load a new instance of [CLIPTokenizer] by itself, if
-            needed.
-        precision (`torch.dtype`, *optional*, defauts to `None`):
-            If not provided the precision will be set to the precision of the original file.
-        return: A StableDiffusionPipeline object representing the passed-in `.ckpt`/`.safetensors` file.
-    """
-
-    # import pipelines here to avoid circular import error when using from_single_file method
-    from diffusers import (
-        LDMTextToImagePipeline,
-        PaintByExamplePipeline,
-        StableDiffusionControlNetPipeline,
-        StableDiffusionInpaintPipeline,
-        StableDiffusionPipeline,
-        StableDiffusionXLImg2ImgPipeline,
-        StableDiffusionXLPipeline,
-        StableUnCLIPImg2ImgPipeline,
-        StableUnCLIPPipeline,
-    )
-
-    if pipeline_class is None:
-        pipeline_class = StableDiffusionPipeline if not controlnet else StableDiffusionControlNetPipeline
-
-    if prediction_type == "v-prediction":
-        prediction_type = "v_prediction"
-
-    if from_safetensors:
-        from safetensors.torch import load_file as safe_load
-
-        checkpoint = safe_load(checkpoint_path, device="cpu")
-    else:
-        if scan_needed:
-            # scan model
-            scan_result = scan_file_path(checkpoint_path)
-            if scan_result.infected_files != 0:
-                raise Exception("The model {checkpoint_path} is potentially infected by malware. Aborting import.")
-        if device is None:
-            device = "cuda" if torch.cuda.is_available() else "cpu"
-            checkpoint = torch.load(checkpoint_path, map_location=device)
-        else:
-            checkpoint = torch.load(checkpoint_path, map_location=device)
-
-    # Sometimes models don't have the global_step item
-    if "global_step" in checkpoint:
-        global_step = checkpoint["global_step"]
-    else:
-        logger.debug("global_step key not found in model")
-        global_step = None
-
-    # NOTE: this while loop isn't great but this controlnet checkpoint has one additional
-    # "state_dict" key https://huggingface.co/thibaud/controlnet-canny-sd21
-    while "state_dict" in checkpoint:
-        checkpoint = checkpoint["state_dict"]
-
-    logger.debug(f"model_type = {model_type}; original_config_file = {original_config_file}")
-
-    precision_probing_key = "model.diffusion_model.input_blocks.0.0.bias"
-    logger.debug(f"original checkpoint precision == {checkpoint[precision_probing_key].dtype}")
-    precision = precision or checkpoint[precision_probing_key].dtype
-
-    if original_config_file is None:
-        key_name_v2_1 = "model.diffusion_model.input_blocks.2.1.transformer_blocks.0.attn2.to_k.weight"
-        key_name_sd_xl_base = "conditioner.embedders.1.model.transformer.resblocks.9.mlp.c_proj.bias"
-        key_name_sd_xl_refiner = "conditioner.embedders.0.model.transformer.resblocks.9.mlp.c_proj.bias"
-
-        # model_type = "v1"
-        config_url = (
-            "https://raw.githubusercontent.com/CompVis/stable-diffusion/main/configs/stable-diffusion/v1-inference.yaml"
-        )
-
-        if key_name_v2_1 in checkpoint and checkpoint[key_name_v2_1].shape[-1] == 1024:
-            # model_type = "v2"
-            config_url = "https://raw.githubusercontent.com/Stability-AI/stablediffusion/main/configs/stable-diffusion/v2-inference-v.yaml"
-
-            if global_step == 110000:
-                # v2.1 needs to upcast attention
-                upcast_attention = True
-        elif key_name_sd_xl_base in checkpoint:
-            # only base xl has two text embedders
-            config_url = "https://raw.githubusercontent.com/Stability-AI/generative-models/main/configs/inference/sd_xl_base.yaml"
-        elif key_name_sd_xl_refiner in checkpoint:
-            # only refiner xl has embedder and one text embedders
-            config_url = "https://raw.githubusercontent.com/Stability-AI/generative-models/main/configs/inference/sd_xl_refiner.yaml"
-
-        original_config_file = BytesIO(requests.get(config_url).content)
-
-    original_config = OmegaConf.load(original_config_file)
-    if original_config["model"]["params"].get("use_ema") is not None:
-        extract_ema = original_config["model"]["params"]["use_ema"]
-
-    if (
-        model_version in [BaseModelType.StableDiffusion2, BaseModelType.StableDiffusion1]
-        and original_config["model"]["params"].get("parameterization") == "v"
-    ):
-        prediction_type = "v_prediction"
-        upcast_attention = True
-        image_size = 768 if model_version == BaseModelType.StableDiffusion2 else 512
-    else:
-        prediction_type = "epsilon"
-        upcast_attention = False
-        image_size = 512
-
-    # Convert the text model.
-    if (
-        model_type is None
-        and "cond_stage_config" in original_config.model.params
-        and original_config.model.params.cond_stage_config is not None
-    ):
-        model_type = original_config.model.params.cond_stage_config.target.split(".")[-1]
-        logger.debug(f"no `model_type` given, `model_type` inferred as: {model_type}")
-    elif model_type is None and original_config.model.params.network_config is not None:
-        if original_config.model.params.network_config.params.context_dim == 2048:
-            model_type = "SDXL"
-        else:
-            model_type = "SDXL-Refiner"
-        if image_size is None:
-            image_size = 1024
-
-    if num_in_channels is None and pipeline_class == StableDiffusionInpaintPipeline:
-        num_in_channels = 9
-    elif num_in_channels is None:
-        num_in_channels = 4
-
-    if "unet_config" in original_config.model.params:
-        original_config["model"]["params"]["unet_config"]["params"]["in_channels"] = num_in_channels
-
-    if (
-        "parameterization" in original_config["model"]["params"]
-        and original_config["model"]["params"]["parameterization"] == "v"
-    ):
-        if prediction_type is None:
-            # NOTE: For stable diffusion 2 base it is recommended to pass `prediction_type=="epsilon"`
-            # as it relies on a brittle global step parameter here
-            prediction_type = "epsilon" if global_step == 875000 else "v_prediction"
-        if image_size is None:
-            # NOTE: For stable diffusion 2 base one has to pass `image_size==512`
-            # as it relies on a brittle global step parameter here
-            image_size = 512 if global_step == 875000 else 768
-    else:
-        if prediction_type is None:
-            prediction_type = "epsilon"
-        if image_size is None:
-            image_size = 512
-
-    if controlnet is None and "control_stage_config" in original_config.model.params:
-        controlnet = convert_controlnet_checkpoint(
-            checkpoint, original_config, checkpoint_path, image_size, upcast_attention, extract_ema
-        )
-
-    num_train_timesteps = getattr(original_config.model.params, "timesteps", None) or 1000
-
-    if model_type in ["SDXL", "SDXL-Refiner"]:
-        scheduler_dict = {
-            "beta_schedule": "scaled_linear",
-            "beta_start": 0.00085,
-            "beta_end": 0.012,
-            "interpolation_type": "linear",
-            "num_train_timesteps": num_train_timesteps,
-            "prediction_type": "epsilon",
-            "sample_max_value": 1.0,
-            "set_alpha_to_one": False,
-            "skip_prk_steps": True,
-            "steps_offset": 1,
-            "timestep_spacing": "leading",
-        }
-        scheduler = EulerDiscreteScheduler.from_config(scheduler_dict)
-        scheduler_type = "euler"
-    else:
-        beta_start = getattr(original_config.model.params, "linear_start", None) or 0.02
-        beta_end = getattr(original_config.model.params, "linear_end", None) or 0.085
-        scheduler = DDIMScheduler(
-            beta_end=beta_end,
-            beta_schedule="scaled_linear",
-            beta_start=beta_start,
-            num_train_timesteps=num_train_timesteps,
-            steps_offset=1,
-            clip_sample=False,
-            set_alpha_to_one=False,
-            prediction_type=prediction_type,
-        )
-    # make sure scheduler works correctly with DDIM
-    scheduler.register_to_config(clip_sample=False)
-
-    if scheduler_type == "pndm":
-        config = dict(scheduler.config)
-        config["skip_prk_steps"] = True
-        scheduler = PNDMScheduler.from_config(config)
-    elif scheduler_type == "lms":
-        scheduler = LMSDiscreteScheduler.from_config(scheduler.config)
-    elif scheduler_type == "heun":
-        scheduler = HeunDiscreteScheduler.from_config(scheduler.config)
-    elif scheduler_type == "euler":
-        scheduler = EulerDiscreteScheduler.from_config(scheduler.config)
-    elif scheduler_type == "euler-ancestral":
-        scheduler = EulerAncestralDiscreteScheduler.from_config(scheduler.config)
-    elif scheduler_type == "dpm":
-        scheduler = DPMSolverMultistepScheduler.from_config(scheduler.config)
-    elif scheduler_type == "ddim":
-        scheduler = scheduler
-    else:
-        raise ValueError(f"Scheduler of type {scheduler_type} doesn't exist!")
-
-    # Convert the UNet2DConditionModel model.
-    unet_config = create_unet_diffusers_config(original_config, image_size=image_size)
-    unet_config["upcast_attention"] = upcast_attention
-    converted_unet_checkpoint = convert_ldm_unet_checkpoint(
-        checkpoint, unet_config, path=checkpoint_path, extract_ema=extract_ema
-    )
-
-    ctx = init_empty_weights if is_accelerate_available() else nullcontext
-    with ctx():
-        unet = UNet2DConditionModel(**unet_config)
-
-    if is_accelerate_available():
-        for param_name, param in converted_unet_checkpoint.items():
-            set_module_tensor_to_device(unet, param_name, "cpu", value=param)
-    else:
-        unet.load_state_dict(converted_unet_checkpoint)
-
-    # Convert the VAE model.
-    if vae_path is None:
-        vae_config = create_vae_diffusers_config(original_config, image_size=image_size)
-        converted_vae_checkpoint = convert_ldm_vae_checkpoint(checkpoint, vae_config)
-
-        if (
-            "model" in original_config
-            and "params" in original_config.model
-            and "scale_factor" in original_config.model.params
-        ):
-            vae_scaling_factor = original_config.model.params.scale_factor
-        else:
-            vae_scaling_factor = 0.18215  # default SD scaling factor
-
-        vae_config["scaling_factor"] = vae_scaling_factor
-
-        ctx = init_empty_weights if is_accelerate_available() else nullcontext
-        with ctx():
-            vae = AutoencoderKL(**vae_config)
-
-        if is_accelerate_available():
-            for param_name, param in converted_vae_checkpoint.items():
-                set_module_tensor_to_device(vae, param_name, "cpu", value=param)
-        else:
-            vae.load_state_dict(converted_vae_checkpoint)
-    else:
-        vae = AutoencoderKL.from_pretrained(vae_path)
-
-    if model_type == "FrozenOpenCLIPEmbedder":
-        config_name = "stabilityai/stable-diffusion-2"
-        config_kwargs = {"subfolder": "text_encoder"}
-
-        text_model = convert_open_clip_checkpoint(checkpoint, config_name, **config_kwargs)
-        tokenizer = CLIPTokenizer.from_pretrained(CONVERT_MODEL_ROOT / "stable-diffusion-2-clip", subfolder="tokenizer")
-
-        if stable_unclip is None:
-            if controlnet:
-                pipe = pipeline_class(
-                    vae=vae.to(precision),
-                    text_encoder=text_model.to(precision),
-                    tokenizer=tokenizer,
-                    unet=unet.to(precision),
-                    scheduler=scheduler,
-                    controlnet=controlnet,
-                    safety_checker=None,
-                    feature_extractor=None,
-                    requires_safety_checker=False,
-                )
-            else:
-                pipe = pipeline_class(
-                    vae=vae.to(precision),
-                    text_encoder=text_model.to(precision),
-                    tokenizer=tokenizer,
-                    unet=unet.to(precision),
-                    scheduler=scheduler,
-                    safety_checker=None,
-                    feature_extractor=None,
-                    requires_safety_checker=False,
-                )
-        else:
-            image_normalizer, image_noising_scheduler = stable_unclip_image_noising_components(
-                original_config, clip_stats_path=clip_stats_path, device=device
-            )
-
-            if stable_unclip == "img2img":
-                feature_extractor, image_encoder = stable_unclip_image_encoder(original_config)
-
-                pipe = StableUnCLIPImg2ImgPipeline(
-                    # image encoding components
-                    feature_extractor=feature_extractor,
-                    image_encoder=image_encoder,
-                    # image noising components
-                    image_normalizer=image_normalizer,
-                    image_noising_scheduler=image_noising_scheduler,
-                    # regular denoising components
-                    tokenizer=tokenizer,
-                    text_encoder=text_model.to(precision),
-                    unet=unet.to(precision),
-                    scheduler=scheduler,
-                    # vae
-                    vae=vae,
-                )
-            elif stable_unclip == "txt2img":
-                if stable_unclip_prior is None or stable_unclip_prior == "karlo":
-                    karlo_model = "kakaobrain/karlo-v1-alpha"
-                    prior = PriorTransformer.from_pretrained(karlo_model, subfolder="prior")
-
-                    prior_tokenizer = CLIPTokenizer.from_pretrained(CONVERT_MODEL_ROOT / "clip-vit-large-patch14")
-                    prior_text_model = CLIPTextModelWithProjection.from_pretrained(
-                        CONVERT_MODEL_ROOT / "clip-vit-large-patch14"
-                    )
-
-                    prior_scheduler = UnCLIPScheduler.from_pretrained(karlo_model, subfolder="prior_scheduler")
-                    prior_scheduler = DDPMScheduler.from_config(prior_scheduler.config)
-                else:
-                    raise NotImplementedError(f"unknown prior for stable unclip model: {stable_unclip_prior}")
-
-                pipe = StableUnCLIPPipeline(
-                    # prior components
-                    prior_tokenizer=prior_tokenizer,
-                    prior_text_encoder=prior_text_model,
-                    prior=prior,
-                    prior_scheduler=prior_scheduler,
-                    # image noising components
-                    image_normalizer=image_normalizer,
-                    image_noising_scheduler=image_noising_scheduler,
-                    # regular denoising components
-                    tokenizer=tokenizer,
-                    text_encoder=text_model,
-                    unet=unet,
-                    scheduler=scheduler,
-                    # vae
-                    vae=vae,
-                )
-            else:
-                raise NotImplementedError(f"unknown `stable_unclip` type: {stable_unclip}")
-    elif model_type == "PaintByExample":
-        vision_model = convert_paint_by_example_checkpoint(checkpoint)
-        tokenizer = CLIPTokenizer.from_pretrained(CONVERT_MODEL_ROOT / "clip-vit-large-patch14")
-        feature_extractor = AutoFeatureExtractor.from_pretrained(CONVERT_MODEL_ROOT / "stable-diffusion-safety-checker")
-        pipe = PaintByExamplePipeline(
-            vae=vae,
-            image_encoder=vision_model,
-            unet=unet,
-            scheduler=scheduler,
-            safety_checker=None,
-            feature_extractor=feature_extractor,
-        )
-    elif model_type == "FrozenCLIPEmbedder":
-        text_model = convert_ldm_clip_checkpoint(
-            checkpoint, local_files_only=local_files_only, text_encoder=text_encoder
-        )
-        tokenizer = (
-            CLIPTokenizer.from_pretrained(CONVERT_MODEL_ROOT / "clip-vit-large-patch14")
-            if tokenizer is None
-            else tokenizer
-        )
-
-        if load_safety_checker:
-            safety_checker = StableDiffusionSafetyChecker.from_pretrained(
-                CONVERT_MODEL_ROOT / "stable-diffusion-safety-checker"
-            )
-            feature_extractor = AutoFeatureExtractor.from_pretrained(
-                CONVERT_MODEL_ROOT / "stable-diffusion-safety-checker"
-            )
-        else:
-            safety_checker = None
-            feature_extractor = None
-
-        if controlnet:
-            pipe = pipeline_class(
-                vae=vae.to(precision),
-                text_encoder=text_model.to(precision),
-                tokenizer=tokenizer,
-                unet=unet.to(precision),
-                controlnet=controlnet,
-                scheduler=scheduler,
-                safety_checker=safety_checker,
-                feature_extractor=feature_extractor,
-            )
-        else:
-            pipe = pipeline_class(
-                vae=vae.to(precision),
-                text_encoder=text_model.to(precision),
-                tokenizer=tokenizer,
-                unet=unet.to(precision),
-                scheduler=scheduler,
-                safety_checker=safety_checker,
-                feature_extractor=feature_extractor,
-            )
-    elif model_type in ["SDXL", "SDXL-Refiner"]:
-        if model_type == "SDXL":
-            tokenizer = CLIPTokenizer.from_pretrained(CONVERT_MODEL_ROOT / "clip-vit-large-patch14")
-            text_encoder = convert_ldm_clip_checkpoint(checkpoint, local_files_only=local_files_only)
-
-            tokenizer_name = CONVERT_MODEL_ROOT / "CLIP-ViT-bigG-14-laion2B-39B-b160k"
-            tokenizer_2 = CLIPTokenizer.from_pretrained(tokenizer_name, pad_token="!")
-
-            config_name = tokenizer_name
-            config_kwargs = {"projection_dim": 1280}
-            text_encoder_2 = convert_open_clip_checkpoint(
-                checkpoint, config_name, prefix="conditioner.embedders.1.model.", has_projection=True, **config_kwargs
-            )
-
-            pipe = StableDiffusionXLPipeline(
-                vae=vae.to(precision),
-                text_encoder=text_encoder.to(precision),
-                tokenizer=tokenizer,
-                text_encoder_2=text_encoder_2.to(precision),
-                tokenizer_2=tokenizer_2,
-                unet=unet.to(precision),
-                scheduler=scheduler,
-                force_zeros_for_empty_prompt=True,
-            )
-        else:
-            tokenizer = None
-            text_encoder = None
-            tokenizer_name = CONVERT_MODEL_ROOT / "CLIP-ViT-bigG-14-laion2B-39B-b160k"
-            tokenizer_2 = CLIPTokenizer.from_pretrained(tokenizer_name, pad_token="!")
-
-            config_name = tokenizer_name
-            config_kwargs = {"projection_dim": 1280}
-            text_encoder_2 = convert_open_clip_checkpoint(
-                checkpoint, config_name, prefix="conditioner.embedders.0.model.", has_projection=True, **config_kwargs
-            )
-
-            pipe = StableDiffusionXLImg2ImgPipeline(
-                vae=vae.to(precision),
-                text_encoder=text_encoder,
-                tokenizer=tokenizer,
-                text_encoder_2=text_encoder_2,
-                tokenizer_2=tokenizer_2,
-                unet=unet.to(precision),
-                scheduler=scheduler,
-                requires_aesthetics_score=True,
-                force_zeros_for_empty_prompt=False,
-            )
-    else:
-        text_config = create_ldm_bert_config(original_config)
-        text_model = convert_ldm_bert_checkpoint(checkpoint, text_config)
-        tokenizer = BertTokenizerFast.from_pretrained(CONVERT_MODEL_ROOT / "bert-base-uncased")
-        pipe = LDMTextToImagePipeline(vqvae=vae, bert=text_model, tokenizer=tokenizer, unet=unet, scheduler=scheduler)
-
-    return pipe
-
-
-def download_controlnet_from_original_ckpt(
-    checkpoint_path: str,
-    original_config_file: str,
-    image_size: int = 512,
-    extract_ema: bool = False,
-    precision: Optional[torch.dtype] = None,
-    num_in_channels: Optional[int] = None,
-    upcast_attention: Optional[bool] = None,
-    device: str = None,
-    from_safetensors: bool = False,
-    use_linear_projection: Optional[bool] = None,
-    cross_attention_dim: Optional[bool] = None,
-    scan_needed: bool = False,
-) -> DiffusionPipeline:
-    if from_safetensors:
-        from safetensors import safe_open
-
-        checkpoint = {}
-        with safe_open(checkpoint_path, framework="pt", device="cpu") as f:
-            for key in f.keys():
-                checkpoint[key] = f.get_tensor(key)
-    else:
-        if scan_needed:
-            # scan model
-            scan_result = scan_file_path(checkpoint_path)
-            if scan_result.infected_files != 0:
-                raise Exception("The model {checkpoint_path} is potentially infected by malware. Aborting import.")
-        if device is None:
-            device = "cuda" if torch.cuda.is_available() else "cpu"
-            checkpoint = torch.load(checkpoint_path, map_location=device)
-        else:
-            checkpoint = torch.load(checkpoint_path, map_location=device)
-
-    # NOTE: this while loop isn't great but this controlnet checkpoint has one additional
-    # "state_dict" key https://huggingface.co/thibaud/controlnet-canny-sd21
-    while "state_dict" in checkpoint:
-        checkpoint = checkpoint["state_dict"]
-
-    # use original precision
-    precision_probing_key = "input_blocks.0.0.bias"
-    ckpt_precision = checkpoint[precision_probing_key].dtype
-    logger.debug(f"original controlnet precision = {ckpt_precision}")
-    precision = precision or ckpt_precision
-
-    original_config = OmegaConf.load(original_config_file)
-
-    if num_in_channels is not None:
-        original_config["model"]["params"]["unet_config"]["params"]["in_channels"] = num_in_channels
-
-    if "control_stage_config" not in original_config.model.params:
-        raise ValueError("`control_stage_config` not present in original config")
-
-    controlnet = convert_controlnet_checkpoint(
-        checkpoint,
-        original_config,
-        checkpoint_path,
-        image_size,
-        upcast_attention,
-        extract_ema,
-        use_linear_projection=use_linear_projection,
-        cross_attention_dim=cross_attention_dim,
-    )
-
-    return controlnet.to(precision)
-
-
-def convert_ldm_vae_to_diffusers(checkpoint, vae_config: DictConfig, image_size: int) -> AutoencoderKL:
-    vae_config = create_vae_diffusers_config(vae_config, image_size=image_size)
-
-    converted_vae_checkpoint = convert_ldm_vae_checkpoint(checkpoint, vae_config)
-
-    vae = AutoencoderKL(**vae_config)
-    vae.load_state_dict(converted_vae_checkpoint)
-    return vae
-
-
-def convert_ckpt_to_diffusers(
-    checkpoint_path: Union[str, Path],
-    dump_path: Union[str, Path],
-    use_safetensors: bool = True,
-    **kwargs,
-):
-    """
-    Takes all the arguments of download_from_original_stable_diffusion_ckpt(),
-    and in addition a path-like object indicating the location of the desired diffusers
-    model to be written.
-    """
-    pipe = download_from_original_stable_diffusion_ckpt(checkpoint_path, **kwargs)
-
-    pipe.save_pretrained(
-        dump_path,
-        safe_serialization=use_safetensors,
-    )
-
-
-def convert_controlnet_to_diffusers(
-    checkpoint_path: Union[str, Path],
-    dump_path: Union[str, Path],
-    **kwargs,
-):
-    """
-    Takes all the arguments of download_controlnet_from_original_ckpt(),
-    and in addition a path-like object indicating the location of the desired diffusers
-    model to be written.
-    """
-    pipe = download_controlnet_from_original_ckpt(checkpoint_path, **kwargs)
-
-    pipe.save_pretrained(dump_path, safe_serialization=True)
diff --git a/invokeai/backend/model_management_OLD/detect_baked_in_vae.py b/invokeai/backend/model_management_OLD/detect_baked_in_vae.py
deleted file mode 100644
index 9118438548..0000000000
--- a/invokeai/backend/model_management_OLD/detect_baked_in_vae.py
+++ /dev/null
@@ -1,31 +0,0 @@
-# Copyright (c) 2024 Lincoln Stein and the InvokeAI Development Team
-"""
-This module exports the function has_baked_in_sdxl_vae().
-It returns True if an SDXL checkpoint model has the original SDXL 1.0 VAE,
-which doesn't work properly in fp16 mode.
-"""
-
-import hashlib
-from pathlib import Path
-
-from safetensors.torch import load_file
-
-SDXL_1_0_VAE_HASH = "bc40b16c3a0fa4625abdfc01c04ffc21bf3cefa6af6c7768ec61eb1f1ac0da51"
-
-
-def has_baked_in_sdxl_vae(checkpoint_path: Path) -> bool:
-    """Return true if the checkpoint contains a custom (non SDXL-1.0) VAE."""
-    hash = _vae_hash(checkpoint_path)
-    return hash != SDXL_1_0_VAE_HASH
-
-
-def _vae_hash(checkpoint_path: Path) -> str:
-    checkpoint = load_file(checkpoint_path, device="cpu")
-    vae_keys = [x for x in checkpoint.keys() if x.startswith("first_stage_model.")]
-    hash = hashlib.new("sha256")
-    for key in vae_keys:
-        value = checkpoint[key]
-        hash.update(bytes(key, "UTF-8"))
-        hash.update(bytes(str(value), "UTF-8"))
-
-    return hash.hexdigest()
diff --git a/invokeai/backend/model_management_OLD/lora.py b/invokeai/backend/model_management_OLD/lora.py
deleted file mode 100644
index aed5eb60d5..0000000000
--- a/invokeai/backend/model_management_OLD/lora.py
+++ /dev/null
@@ -1,582 +0,0 @@
-from __future__ import annotations
-
-import pickle
-from contextlib import contextmanager
-from pathlib import Path
-from typing import Any, Dict, List, Optional, Tuple, Union
-
-import numpy as np
-import torch
-from compel.embeddings_provider import BaseTextualInversionManager
-from diffusers.models import UNet2DConditionModel
-from safetensors.torch import load_file
-from transformers import CLIPTextModel, CLIPTokenizer
-
-from invokeai.app.shared.models import FreeUConfig
-from invokeai.backend.model_management.model_load_optimizations import skip_torch_weight_init
-
-from .models.lora import LoRAModel
-
-"""
-loras = [
-    (lora_model1, 0.7),
-    (lora_model2, 0.4),
-]
-with LoRAHelper.apply_lora_unet(unet, loras):
-    # unet with applied loras
-# unmodified unet
-
-"""
-
-
-# TODO: rename smth like ModelPatcher and add TI method?
-class ModelPatcher:
-    @staticmethod
-    def _resolve_lora_key(model: torch.nn.Module, lora_key: str, prefix: str) -> Tuple[str, torch.nn.Module]:
-        assert "." not in lora_key
-
-        if not lora_key.startswith(prefix):
-            raise Exception(f"lora_key with invalid prefix: {lora_key}, {prefix}")
-
-        module = model
-        module_key = ""
-        key_parts = lora_key[len(prefix) :].split("_")
-
-        submodule_name = key_parts.pop(0)
-
-        while len(key_parts) > 0:
-            try:
-                module = module.get_submodule(submodule_name)
-                module_key += "." + submodule_name
-                submodule_name = key_parts.pop(0)
-            except Exception:
-                submodule_name += "_" + key_parts.pop(0)
-
-        module = module.get_submodule(submodule_name)
-        module_key = (module_key + "." + submodule_name).lstrip(".")
-
-        return (module_key, module)
-
-    @classmethod
-    @contextmanager
-    def apply_lora_unet(
-        cls,
-        unet: UNet2DConditionModel,
-        loras: List[Tuple[LoRAModel, float]],
-    ):
-        with cls.apply_lora(unet, loras, "lora_unet_"):
-            yield
-
-    @classmethod
-    @contextmanager
-    def apply_lora_text_encoder(
-        cls,
-        text_encoder: CLIPTextModel,
-        loras: List[Tuple[LoRAModel, float]],
-    ):
-        with cls.apply_lora(text_encoder, loras, "lora_te_"):
-            yield
-
-    @classmethod
-    @contextmanager
-    def apply_sdxl_lora_text_encoder(
-        cls,
-        text_encoder: CLIPTextModel,
-        loras: List[Tuple[LoRAModel, float]],
-    ):
-        with cls.apply_lora(text_encoder, loras, "lora_te1_"):
-            yield
-
-    @classmethod
-    @contextmanager
-    def apply_sdxl_lora_text_encoder2(
-        cls,
-        text_encoder: CLIPTextModel,
-        loras: List[Tuple[LoRAModel, float]],
-    ):
-        with cls.apply_lora(text_encoder, loras, "lora_te2_"):
-            yield
-
-    @classmethod
-    @contextmanager
-    def apply_lora(
-        cls,
-        model: torch.nn.Module,
-        loras: List[Tuple[LoRAModel, float]],  # THIS IS INCORRECT. IT IS ACTUALLY A LoRAModelRaw
-        prefix: str,
-    ):
-        original_weights = {}
-        try:
-            with torch.no_grad():
-                for lora, lora_weight in loras:
-                    # assert lora.device.type == "cpu"
-                    for layer_key, layer in lora.layers.items():
-                        if not layer_key.startswith(prefix):
-                            continue
-
-                        # TODO(ryand): A non-negligible amount of time is currently spent resolving LoRA keys. This
-                        # should be improved in the following ways:
-                        # 1. The key mapping could be more-efficiently pre-computed. This would save time every time a
-                        #    LoRA model is applied.
-                        # 2. From an API perspective, there's no reason that the `ModelPatcher` should be aware of the
-                        #    intricacies of Stable Diffusion key resolution. It should just expect the input LoRA
-                        #    weights to have valid keys.
-                        module_key, module = cls._resolve_lora_key(model, layer_key, prefix)
-
-                        # All of the LoRA weight calculations will be done on the same device as the module weight.
-                        # (Performance will be best if this is a CUDA device.)
-                        device = module.weight.device
-                        dtype = module.weight.dtype
-
-                        if module_key not in original_weights:
-                            original_weights[module_key] = module.weight.detach().to(device="cpu", copy=True)
-
-                        layer_scale = layer.alpha / layer.rank if (layer.alpha and layer.rank) else 1.0
-
-                        # We intentionally move to the target device first, then cast. Experimentally, this was found to
-                        # be significantly faster for 16-bit CPU tensors being moved to a CUDA device than doing the
-                        # same thing in a single call to '.to(...)'.
-                        layer.to(device=device)
-                        layer.to(dtype=torch.float32)
-                        # TODO(ryand): Using torch.autocast(...) over explicit casting may offer a speed benefit on CUDA
-                        # devices here. Experimentally, it was found to be very slow on CPU. More investigation needed.
-                        layer_weight = layer.get_weight(module.weight) * (lora_weight * layer_scale)
-                        layer.to(device="cpu")
-
-                        if module.weight.shape != layer_weight.shape:
-                            # TODO: debug on lycoris
-                            layer_weight = layer_weight.reshape(module.weight.shape)
-
-                        module.weight += layer_weight.to(dtype=dtype)
-
-            yield  # wait for context manager exit
-
-        finally:
-            with torch.no_grad():
-                for module_key, weight in original_weights.items():
-                    model.get_submodule(module_key).weight.copy_(weight)
-
-    @classmethod
-    @contextmanager
-    def apply_ti(
-        cls,
-        tokenizer: CLIPTokenizer,
-        text_encoder: CLIPTextModel,
-        ti_list: List[Tuple[str, Any]],
-    ) -> Tuple[CLIPTokenizer, TextualInversionManager]:
-        init_tokens_count = None
-        new_tokens_added = None
-
-        # TODO: This is required since Transformers 4.32 see
-        # https://github.com/huggingface/transformers/pull/25088
-        # More information by NVIDIA:
-        # https://docs.nvidia.com/deeplearning/performance/dl-performance-matrix-multiplication/index.html#requirements-tc
-        # This value might need to be changed in the future and take the GPUs model into account as there seem
-        # to be ideal values for different GPUS. This value is temporary!
-        # For references to the current discussion please see https://github.com/invoke-ai/InvokeAI/pull/4817
-        pad_to_multiple_of = 8
-
-        try:
-            # HACK: The CLIPTokenizer API does not include a way to remove tokens after calling add_tokens(...). As a
-            # workaround, we create a full copy of `tokenizer` so that its original behavior can be restored after
-            # exiting this `apply_ti(...)` context manager.
-            #
-            # In a previous implementation, the deep copy was obtained with `ti_tokenizer = copy.deepcopy(tokenizer)`,
-            # but a pickle roundtrip was found to be much faster (1 sec vs. 0.05 secs).
-            ti_tokenizer = pickle.loads(pickle.dumps(tokenizer))
-            ti_manager = TextualInversionManager(ti_tokenizer)
-            init_tokens_count = text_encoder.resize_token_embeddings(None, pad_to_multiple_of).num_embeddings
-
-            def _get_trigger(ti_name, index):
-                trigger = ti_name
-                if index > 0:
-                    trigger += f"-!pad-{i}"
-                return f"<{trigger}>"
-
-            def _get_ti_embedding(model_embeddings, ti):
-                print(f"DEBUG: model_embeddings={type(model_embeddings)}, ti={type(ti)}")
-                print(f"DEBUG: is it an nn.Module? {isinstance(model_embeddings, torch.nn.Module)}")
-                # for SDXL models, select the embedding that matches the text encoder's dimensions
-                if ti.embedding_2 is not None:
-                    return (
-                        ti.embedding_2
-                        if ti.embedding_2.shape[1] == model_embeddings.weight.data[0].shape[0]
-                        else ti.embedding
-                    )
-                else:
-                    print(f"DEBUG: ti.embedding={type(ti.embedding)}")
-                    return ti.embedding
-
-            # modify tokenizer
-            new_tokens_added = 0
-            for ti_name, ti in ti_list:
-                ti_embedding = _get_ti_embedding(text_encoder.get_input_embeddings(), ti)
-
-                for i in range(ti_embedding.shape[0]):
-                    new_tokens_added += ti_tokenizer.add_tokens(_get_trigger(ti_name, i))
-
-            # Modify text_encoder.
-            # resize_token_embeddings(...) constructs a new torch.nn.Embedding internally. Initializing the weights of
-            # this embedding is slow and unnecessary, so we wrap this step in skip_torch_weight_init() to save some
-            # time.
-            with skip_torch_weight_init():
-                text_encoder.resize_token_embeddings(init_tokens_count + new_tokens_added, pad_to_multiple_of)
-            model_embeddings = text_encoder.get_input_embeddings()
-
-            for ti_name, ti in ti_list:
-                ti_embedding = _get_ti_embedding(text_encoder.get_input_embeddings(), ti)
-
-                ti_tokens = []
-                for i in range(ti_embedding.shape[0]):
-                    embedding = ti_embedding[i]
-                    trigger = _get_trigger(ti_name, i)
-
-                    token_id = ti_tokenizer.convert_tokens_to_ids(trigger)
-                    if token_id == ti_tokenizer.unk_token_id:
-                        raise RuntimeError(f"Unable to find token id for token '{trigger}'")
-
-                    if model_embeddings.weight.data[token_id].shape != embedding.shape:
-                        raise ValueError(
-                            f"Cannot load embedding for {trigger}. It was trained on a model with token dimension"
-                            f" {embedding.shape[0]}, but the current model has token dimension"
-                            f" {model_embeddings.weight.data[token_id].shape[0]}."
-                        )
-
-                    model_embeddings.weight.data[token_id] = embedding.to(
-                        device=text_encoder.device, dtype=text_encoder.dtype
-                    )
-                    ti_tokens.append(token_id)
-
-                if len(ti_tokens) > 1:
-                    ti_manager.pad_tokens[ti_tokens[0]] = ti_tokens[1:]
-
-            yield ti_tokenizer, ti_manager
-
-        finally:
-            if init_tokens_count and new_tokens_added:
-                text_encoder.resize_token_embeddings(init_tokens_count, pad_to_multiple_of)
-
-    @classmethod
-    @contextmanager
-    def apply_clip_skip(
-        cls,
-        text_encoder: CLIPTextModel,
-        clip_skip: int,
-    ):
-        skipped_layers = []
-        try:
-            for _i in range(clip_skip):
-                skipped_layers.append(text_encoder.text_model.encoder.layers.pop(-1))
-
-            yield
-
-        finally:
-            while len(skipped_layers) > 0:
-                text_encoder.text_model.encoder.layers.append(skipped_layers.pop())
-
-    @classmethod
-    @contextmanager
-    def apply_freeu(
-        cls,
-        unet: UNet2DConditionModel,
-        freeu_config: Optional[FreeUConfig] = None,
-    ):
-        did_apply_freeu = False
-        try:
-            if freeu_config is not None:
-                unet.enable_freeu(b1=freeu_config.b1, b2=freeu_config.b2, s1=freeu_config.s1, s2=freeu_config.s2)
-                did_apply_freeu = True
-
-            yield
-
-        finally:
-            if did_apply_freeu:
-                unet.disable_freeu()
-
-
-class TextualInversionModel:
-    embedding: torch.Tensor  # [n, 768]|[n, 1280]
-    embedding_2: Optional[torch.Tensor] = None  # [n, 768]|[n, 1280]   - for SDXL models
-
-    @classmethod
-    def from_checkpoint(
-        cls,
-        file_path: Union[str, Path],
-        device: Optional[torch.device] = None,
-        dtype: Optional[torch.dtype] = None,
-    ):
-        if not isinstance(file_path, Path):
-            file_path = Path(file_path)
-
-        result = cls()  # TODO:
-
-        if file_path.suffix == ".safetensors":
-            state_dict = load_file(file_path.absolute().as_posix(), device="cpu")
-        else:
-            state_dict = torch.load(file_path, map_location="cpu")
-
-        # both v1 and v2 format embeddings
-        # difference mostly in metadata
-        if "string_to_param" in state_dict:
-            if len(state_dict["string_to_param"]) > 1:
-                print(
-                    f'Warn: Embedding "{file_path.name}" contains multiple tokens, which is not supported. The first',
-                    " token will be used.",
-                )
-
-            result.embedding = next(iter(state_dict["string_to_param"].values()))
-
-        # v3 (easynegative)
-        elif "emb_params" in state_dict:
-            result.embedding = state_dict["emb_params"]
-
-        # v5(sdxl safetensors file)
-        elif "clip_g" in state_dict and "clip_l" in state_dict:
-            result.embedding = state_dict["clip_g"]
-            result.embedding_2 = state_dict["clip_l"]
-
-        # v4(diffusers bin files)
-        else:
-            result.embedding = next(iter(state_dict.values()))
-
-            if len(result.embedding.shape) == 1:
-                result.embedding = result.embedding.unsqueeze(0)
-
-            if not isinstance(result.embedding, torch.Tensor):
-                raise ValueError(f"Invalid embeddings file: {file_path.name}")
-
-        return result
-
-
-class TextualInversionManager(BaseTextualInversionManager):
-    pad_tokens: Dict[int, List[int]]
-    tokenizer: CLIPTokenizer
-
-    def __init__(self, tokenizer: CLIPTokenizer):
-        self.pad_tokens = {}
-        self.tokenizer = tokenizer
-
-    def expand_textual_inversion_token_ids_if_necessary(self, token_ids: list[int]) -> list[int]:
-        if len(self.pad_tokens) == 0:
-            return token_ids
-
-        if token_ids[0] == self.tokenizer.bos_token_id:
-            raise ValueError("token_ids must not start with bos_token_id")
-        if token_ids[-1] == self.tokenizer.eos_token_id:
-            raise ValueError("token_ids must not end with eos_token_id")
-
-        new_token_ids = []
-        for token_id in token_ids:
-            new_token_ids.append(token_id)
-            if token_id in self.pad_tokens:
-                new_token_ids.extend(self.pad_tokens[token_id])
-
-        # Do not exceed the max model input size
-        # The -2 here is compensating for compensate compel.embeddings_provider.get_token_ids(),
-        # which first removes and then adds back the start and end tokens.
-        max_length = list(self.tokenizer.max_model_input_sizes.values())[0] - 2
-        if len(new_token_ids) > max_length:
-            new_token_ids = new_token_ids[0:max_length]
-
-        return new_token_ids
-
-
-class ONNXModelPatcher:
-    from diffusers import OnnxRuntimeModel
-
-    from .models.base import IAIOnnxRuntimeModel
-
-    @classmethod
-    @contextmanager
-    def apply_lora_unet(
-        cls,
-        unet: OnnxRuntimeModel,
-        loras: List[Tuple[LoRAModel, float]],
-    ):
-        with cls.apply_lora(unet, loras, "lora_unet_"):
-            yield
-
-    @classmethod
-    @contextmanager
-    def apply_lora_text_encoder(
-        cls,
-        text_encoder: OnnxRuntimeModel,
-        loras: List[Tuple[LoRAModel, float]],
-    ):
-        with cls.apply_lora(text_encoder, loras, "lora_te_"):
-            yield
-
-    # based on
-    # https://github.com/ssube/onnx-web/blob/ca2e436f0623e18b4cfe8a0363fcfcf10508acf7/api/onnx_web/convert/diffusion/lora.py#L323
-    @classmethod
-    @contextmanager
-    def apply_lora(
-        cls,
-        model: IAIOnnxRuntimeModel,
-        loras: List[Tuple[LoRAModel, float]],
-        prefix: str,
-    ):
-        from .models.base import IAIOnnxRuntimeModel
-
-        if not isinstance(model, IAIOnnxRuntimeModel):
-            raise Exception("Only IAIOnnxRuntimeModel models supported")
-
-        orig_weights = {}
-
-        try:
-            blended_loras = {}
-
-            for lora, lora_weight in loras:
-                for layer_key, layer in lora.layers.items():
-                    if not layer_key.startswith(prefix):
-                        continue
-
-                    layer.to(dtype=torch.float32)
-                    layer_key = layer_key.replace(prefix, "")
-                    # TODO: rewrite to pass original tensor weight(required by ia3)
-                    layer_weight = layer.get_weight(None).detach().cpu().numpy() * lora_weight
-                    if layer_key is blended_loras:
-                        blended_loras[layer_key] += layer_weight
-                    else:
-                        blended_loras[layer_key] = layer_weight
-
-            node_names = {}
-            for node in model.nodes.values():
-                node_names[node.name.replace("/", "_").replace(".", "_").lstrip("_")] = node.name
-
-            for layer_key, lora_weight in blended_loras.items():
-                conv_key = layer_key + "_Conv"
-                gemm_key = layer_key + "_Gemm"
-                matmul_key = layer_key + "_MatMul"
-
-                if conv_key in node_names or gemm_key in node_names:
-                    if conv_key in node_names:
-                        conv_node = model.nodes[node_names[conv_key]]
-                    else:
-                        conv_node = model.nodes[node_names[gemm_key]]
-
-                    weight_name = [n for n in conv_node.input if ".weight" in n][0]
-                    orig_weight = model.tensors[weight_name]
-
-                    if orig_weight.shape[-2:] == (1, 1):
-                        if lora_weight.shape[-2:] == (1, 1):
-                            new_weight = orig_weight.squeeze((3, 2)) + lora_weight.squeeze((3, 2))
-                        else:
-                            new_weight = orig_weight.squeeze((3, 2)) + lora_weight
-
-                        new_weight = np.expand_dims(new_weight, (2, 3))
-                    else:
-                        if orig_weight.shape != lora_weight.shape:
-                            new_weight = orig_weight + lora_weight.reshape(orig_weight.shape)
-                        else:
-                            new_weight = orig_weight + lora_weight
-
-                    orig_weights[weight_name] = orig_weight
-                    model.tensors[weight_name] = new_weight.astype(orig_weight.dtype)
-
-                elif matmul_key in node_names:
-                    weight_node = model.nodes[node_names[matmul_key]]
-                    matmul_name = [n for n in weight_node.input if "MatMul" in n][0]
-
-                    orig_weight = model.tensors[matmul_name]
-                    new_weight = orig_weight + lora_weight.transpose()
-
-                    orig_weights[matmul_name] = orig_weight
-                    model.tensors[matmul_name] = new_weight.astype(orig_weight.dtype)
-
-                else:
-                    # warn? err?
-                    pass
-
-            yield
-
-        finally:
-            # restore original weights
-            for name, orig_weight in orig_weights.items():
-                model.tensors[name] = orig_weight
-
-    @classmethod
-    @contextmanager
-    def apply_ti(
-        cls,
-        tokenizer: CLIPTokenizer,
-        text_encoder: IAIOnnxRuntimeModel,
-        ti_list: List[Tuple[str, Any]],
-    ) -> Tuple[CLIPTokenizer, TextualInversionManager]:
-        from .models.base import IAIOnnxRuntimeModel
-
-        if not isinstance(text_encoder, IAIOnnxRuntimeModel):
-            raise Exception("Only IAIOnnxRuntimeModel models supported")
-
-        orig_embeddings = None
-
-        try:
-            # HACK: The CLIPTokenizer API does not include a way to remove tokens after calling add_tokens(...). As a
-            # workaround, we create a full copy of `tokenizer` so that its original behavior can be restored after
-            # exiting this `apply_ti(...)` context manager.
-            #
-            # In a previous implementation, the deep copy was obtained with `ti_tokenizer = copy.deepcopy(tokenizer)`,
-            # but a pickle roundtrip was found to be much faster (1 sec vs. 0.05 secs).
-            ti_tokenizer = pickle.loads(pickle.dumps(tokenizer))
-            ti_manager = TextualInversionManager(ti_tokenizer)
-
-            def _get_trigger(ti_name, index):
-                trigger = ti_name
-                if index > 0:
-                    trigger += f"-!pad-{i}"
-                return f"<{trigger}>"
-
-            # modify text_encoder
-            orig_embeddings = text_encoder.tensors["text_model.embeddings.token_embedding.weight"]
-
-            # modify tokenizer
-            new_tokens_added = 0
-            for ti_name, ti in ti_list:
-                if ti.embedding_2 is not None:
-                    ti_embedding = (
-                        ti.embedding_2 if ti.embedding_2.shape[1] == orig_embeddings.shape[0] else ti.embedding
-                    )
-                else:
-                    ti_embedding = ti.embedding
-
-                for i in range(ti_embedding.shape[0]):
-                    new_tokens_added += ti_tokenizer.add_tokens(_get_trigger(ti_name, i))
-
-            embeddings = np.concatenate(
-                (np.copy(orig_embeddings), np.zeros((new_tokens_added, orig_embeddings.shape[1]))),
-                axis=0,
-            )
-
-            for ti_name, _ in ti_list:
-                ti_tokens = []
-                for i in range(ti_embedding.shape[0]):
-                    embedding = ti_embedding[i].detach().numpy()
-                    trigger = _get_trigger(ti_name, i)
-
-                    token_id = ti_tokenizer.convert_tokens_to_ids(trigger)
-                    if token_id == ti_tokenizer.unk_token_id:
-                        raise RuntimeError(f"Unable to find token id for token '{trigger}'")
-
-                    if embeddings[token_id].shape != embedding.shape:
-                        raise ValueError(
-                            f"Cannot load embedding for {trigger}. It was trained on a model with token dimension"
-                            f" {embedding.shape[0]}, but the current model has token dimension"
-                            f" {embeddings[token_id].shape[0]}."
-                        )
-
-                    embeddings[token_id] = embedding
-                    ti_tokens.append(token_id)
-
-                if len(ti_tokens) > 1:
-                    ti_manager.pad_tokens[ti_tokens[0]] = ti_tokens[1:]
-
-            text_encoder.tensors["text_model.embeddings.token_embedding.weight"] = embeddings.astype(
-                orig_embeddings.dtype
-            )
-
-            yield ti_tokenizer, ti_manager
-
-        finally:
-            # restore
-            if orig_embeddings is not None:
-                text_encoder.tensors["text_model.embeddings.token_embedding.weight"] = orig_embeddings
diff --git a/invokeai/backend/model_management_OLD/memory_snapshot.py b/invokeai/backend/model_management_OLD/memory_snapshot.py
deleted file mode 100644
index fe54af191c..0000000000
--- a/invokeai/backend/model_management_OLD/memory_snapshot.py
+++ /dev/null
@@ -1,99 +0,0 @@
-import gc
-from typing import Optional
-
-import psutil
-import torch
-
-from invokeai.backend.model_management.libc_util import LibcUtil, Struct_mallinfo2
-
-GB = 2**30  # 1 GB
-
-
-class MemorySnapshot:
-    """A snapshot of RAM and VRAM usage. All values are in bytes."""
-
-    def __init__(self, process_ram: int, vram: Optional[int], malloc_info: Optional[Struct_mallinfo2]):
-        """Initialize a MemorySnapshot.
-
-        Most of the time, `MemorySnapshot` will be constructed with `MemorySnapshot.capture()`.
-
-        Args:
-            process_ram (int): CPU RAM used by the current process.
-            vram (Optional[int]): VRAM used by torch.
-            malloc_info (Optional[Struct_mallinfo2]): Malloc info obtained from LibcUtil.
-        """
-        self.process_ram = process_ram
-        self.vram = vram
-        self.malloc_info = malloc_info
-
-    @classmethod
-    def capture(cls, run_garbage_collector: bool = True):
-        """Capture and return a MemorySnapshot.
-
-        Note: This function has significant overhead, particularly if `run_garbage_collector == True`.
-
-        Args:
-            run_garbage_collector (bool, optional): If true, gc.collect() will be run before checking the process RAM
-                usage. Defaults to True.
-
-        Returns:
-            MemorySnapshot
-        """
-        if run_garbage_collector:
-            gc.collect()
-
-        # According to the psutil docs (https://psutil.readthedocs.io/en/latest/#psutil.Process.memory_info), rss is
-        # supported on all platforms.
-        process_ram = psutil.Process().memory_info().rss
-
-        if torch.cuda.is_available():
-            vram = torch.cuda.memory_allocated()
-        else:
-            # TODO: We could add support for mps.current_allocated_memory() as well. Leaving out for now until we have
-            # time to test it properly.
-            vram = None
-
-        try:
-            malloc_info = LibcUtil().mallinfo2()
-        except (OSError, AttributeError):
-            # OSError: This is expected in environments that do not have the 'libc.so.6' shared library.
-            # AttributeError: This is expected in environments that have `libc.so.6` but do not have the `mallinfo2` (e.g. glibc < 2.33)
-            # TODO: Does `mallinfo` work?
-            malloc_info = None
-
-        return cls(process_ram, vram, malloc_info)
-
-
-def get_pretty_snapshot_diff(snapshot_1: Optional[MemorySnapshot], snapshot_2: Optional[MemorySnapshot]) -> str:
-    """Get a pretty string describing the difference between two `MemorySnapshot`s."""
-
-    def get_msg_line(prefix: str, val1: int, val2: int):
-        diff = val2 - val1
-        return f"{prefix: <30} ({(diff/GB):+5.3f}): {(val1/GB):5.3f}GB -> {(val2/GB):5.3f}GB\n"
-
-    msg = ""
-
-    if snapshot_1 is None or snapshot_2 is None:
-        return msg
-
-    msg += get_msg_line("Process RAM", snapshot_1.process_ram, snapshot_2.process_ram)
-
-    if snapshot_1.malloc_info is not None and snapshot_2.malloc_info is not None:
-        msg += get_msg_line("libc mmap allocated", snapshot_1.malloc_info.hblkhd, snapshot_2.malloc_info.hblkhd)
-
-        msg += get_msg_line("libc arena used", snapshot_1.malloc_info.uordblks, snapshot_2.malloc_info.uordblks)
-
-        msg += get_msg_line("libc arena free", snapshot_1.malloc_info.fordblks, snapshot_2.malloc_info.fordblks)
-
-        libc_total_allocated_1 = snapshot_1.malloc_info.arena + snapshot_1.malloc_info.hblkhd
-        libc_total_allocated_2 = snapshot_2.malloc_info.arena + snapshot_2.malloc_info.hblkhd
-        msg += get_msg_line("libc total allocated", libc_total_allocated_1, libc_total_allocated_2)
-
-        libc_total_used_1 = snapshot_1.malloc_info.uordblks + snapshot_1.malloc_info.hblkhd
-        libc_total_used_2 = snapshot_2.malloc_info.uordblks + snapshot_2.malloc_info.hblkhd
-        msg += get_msg_line("libc total used", libc_total_used_1, libc_total_used_2)
-
-    if snapshot_1.vram is not None and snapshot_2.vram is not None:
-        msg += get_msg_line("VRAM", snapshot_1.vram, snapshot_2.vram)
-
-    return msg
diff --git a/invokeai/backend/model_management_OLD/model_cache.py b/invokeai/backend/model_management_OLD/model_cache.py
deleted file mode 100644
index 2a7f4b5a95..0000000000
--- a/invokeai/backend/model_management_OLD/model_cache.py
+++ /dev/null
@@ -1,553 +0,0 @@
-"""
-Manage a RAM cache of diffusion/transformer models for fast switching.
-They are moved between GPU VRAM and CPU RAM as necessary. If the cache
-grows larger than a preset maximum, then the least recently used
-model will be cleared and (re)loaded from disk when next needed.
-
-The cache returns context manager generators designed to load the
-model into the GPU within the context, and unload outside the
-context. Use like this:
-
-   cache = ModelCache(max_cache_size=7.5)
-   with cache.get_model('runwayml/stable-diffusion-1-5') as SD1,
-          cache.get_model('stabilityai/stable-diffusion-2') as SD2:
-       do_something_in_GPU(SD1,SD2)
-
-
-"""
-
-import gc
-import hashlib
-import math
-import os
-import sys
-import time
-from contextlib import suppress
-from dataclasses import dataclass, field
-from pathlib import Path
-from typing import Any, Dict, Optional, Type, Union, types
-
-import torch
-
-import invokeai.backend.util.logging as logger
-from invokeai.backend.model_management.memory_snapshot import MemorySnapshot, get_pretty_snapshot_diff
-from invokeai.backend.model_management.model_load_optimizations import skip_torch_weight_init
-
-from ..util.devices import choose_torch_device
-from .models import BaseModelType, ModelBase, ModelType, SubModelType
-
-if choose_torch_device() == torch.device("mps"):
-    from torch import mps
-
-# Maximum size of the cache, in gigs
-# Default is roughly enough to hold three fp16 diffusers models in RAM simultaneously
-DEFAULT_MAX_CACHE_SIZE = 6.0
-
-# amount of GPU memory to hold in reserve for use by generations (GB)
-DEFAULT_MAX_VRAM_CACHE_SIZE = 2.75
-
-# actual size of a gig
-GIG = 1073741824
-# Size of a MB in bytes.
-MB = 2**20
-
-
-@dataclass
-class CacheStats(object):
-    hits: int = 0  # cache hits
-    misses: int = 0  # cache misses
-    high_watermark: int = 0  # amount of cache used
-    in_cache: int = 0  # number of models in cache
-    cleared: int = 0  # number of models cleared to make space
-    cache_size: int = 0  # total size of cache
-    # {submodel_key => size}
-    loaded_model_sizes: Dict[str, int] = field(default_factory=dict)
-
-
-class ModelLocker(object):
-    "Forward declaration"
-
-    pass
-
-
-class ModelCache(object):
-    "Forward declaration"
-
-    pass
-
-
-class _CacheRecord:
-    size: int
-    model: Any
-    cache: ModelCache
-    _locks: int
-
-    def __init__(self, cache, model: Any, size: int):
-        self.size = size
-        self.model = model
-        self.cache = cache
-        self._locks = 0
-
-    def lock(self):
-        self._locks += 1
-
-    def unlock(self):
-        self._locks -= 1
-        assert self._locks >= 0
-
-    @property
-    def locked(self):
-        return self._locks > 0
-
-    @property
-    def loaded(self):
-        if self.model is not None and hasattr(self.model, "device"):
-            return self.model.device != self.cache.storage_device
-        else:
-            return False
-
-
-class ModelCache(object):
-    def __init__(
-        self,
-        max_cache_size: float = DEFAULT_MAX_CACHE_SIZE,
-        max_vram_cache_size: float = DEFAULT_MAX_VRAM_CACHE_SIZE,
-        execution_device: torch.device = torch.device("cuda"),
-        storage_device: torch.device = torch.device("cpu"),
-        precision: torch.dtype = torch.float16,
-        sequential_offload: bool = False,
-        lazy_offloading: bool = True,
-        sha_chunksize: int = 16777216,
-        logger: types.ModuleType = logger,
-        log_memory_usage: bool = False,
-    ):
-        """
-        :param max_cache_size: Maximum size of the RAM cache [6.0 GB]
-        :param execution_device: Torch device to load active model into [torch.device('cuda')]
-        :param storage_device: Torch device to save inactive model in [torch.device('cpu')]
-        :param precision: Precision for loaded models [torch.float16]
-        :param lazy_offloading: Keep model in VRAM until another model needs to be loaded
-        :param sequential_offload: Conserve VRAM by loading and unloading each stage of the pipeline sequentially
-        :param sha_chunksize: Chunksize to use when calculating sha256 model hash
-        :param log_memory_usage: If True, a memory snapshot will be captured before and after every model cache
-            operation, and the result will be logged (at debug level). There is a time cost to capturing the memory
-            snapshots, so it is recommended to disable this feature unless you are actively inspecting the model cache's
-            behaviour.
-        """
-        self.model_infos: Dict[str, ModelBase] = {}
-        # allow lazy offloading only when vram cache enabled
-        self.lazy_offloading = lazy_offloading and max_vram_cache_size > 0
-        self.precision: torch.dtype = precision
-        self.max_cache_size: float = max_cache_size
-        self.max_vram_cache_size: float = max_vram_cache_size
-        self.execution_device: torch.device = execution_device
-        self.storage_device: torch.device = storage_device
-        self.sha_chunksize = sha_chunksize
-        self.logger = logger
-        self._log_memory_usage = log_memory_usage
-
-        # used for stats collection
-        self.stats = None
-
-        self._cached_models = {}
-        self._cache_stack = []
-
-    def _capture_memory_snapshot(self) -> Optional[MemorySnapshot]:
-        if self._log_memory_usage:
-            return MemorySnapshot.capture()
-        return None
-
-    def get_key(
-        self,
-        model_path: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-        submodel_type: Optional[SubModelType] = None,
-    ):
-        key = f"{model_path}:{base_model}:{model_type}"
-        if submodel_type:
-            key += f":{submodel_type}"
-        return key
-
-    def _get_model_info(
-        self,
-        model_path: str,
-        model_class: Type[ModelBase],
-        base_model: BaseModelType,
-        model_type: ModelType,
-    ):
-        model_info_key = self.get_key(
-            model_path=model_path,
-            base_model=base_model,
-            model_type=model_type,
-            submodel_type=None,
-        )
-
-        if model_info_key not in self.model_infos:
-            self.model_infos[model_info_key] = model_class(
-                model_path,
-                base_model,
-                model_type,
-            )
-
-        return self.model_infos[model_info_key]
-
-    # TODO: args
-    def get_model(
-        self,
-        model_path: Union[str, Path],
-        model_class: Type[ModelBase],
-        base_model: BaseModelType,
-        model_type: ModelType,
-        submodel: Optional[SubModelType] = None,
-        gpu_load: bool = True,
-    ) -> Any:
-        if not isinstance(model_path, Path):
-            model_path = Path(model_path)
-
-        if not os.path.exists(model_path):
-            raise Exception(f"Model not found: {model_path}")
-
-        model_info = self._get_model_info(
-            model_path=model_path,
-            model_class=model_class,
-            base_model=base_model,
-            model_type=model_type,
-        )
-        key = self.get_key(
-            model_path=model_path,
-            base_model=base_model,
-            model_type=model_type,
-            submodel_type=submodel,
-        )
-        # TODO: lock for no copies on simultaneous calls?
-        cache_entry = self._cached_models.get(key, None)
-        if cache_entry is None:
-            self.logger.info(
-                f"Loading model {model_path}, type"
-                f" {base_model.value}:{model_type.value}{':'+submodel.value if submodel else ''}"
-            )
-            if self.stats:
-                self.stats.misses += 1
-
-            self_reported_model_size_before_load = model_info.get_size(submodel)
-            # Remove old models from the cache to make room for the new model.
-            self._make_cache_room(self_reported_model_size_before_load)
-
-            # Load the model from disk and capture a memory snapshot before/after.
-            start_load_time = time.time()
-            snapshot_before = self._capture_memory_snapshot()
-            with skip_torch_weight_init():
-                model = model_info.get_model(child_type=submodel, torch_dtype=self.precision)
-            snapshot_after = self._capture_memory_snapshot()
-            end_load_time = time.time()
-
-            self_reported_model_size_after_load = model_info.get_size(submodel)
-
-            self.logger.debug(
-                f"Moved model '{key}' from disk to cpu in {(end_load_time-start_load_time):.2f}s.\n"
-                f"Self-reported size before/after load: {(self_reported_model_size_before_load/GIG):.3f}GB /"
-                f" {(self_reported_model_size_after_load/GIG):.3f}GB.\n"
-                f"{get_pretty_snapshot_diff(snapshot_before, snapshot_after)}"
-            )
-
-            if abs(self_reported_model_size_after_load - self_reported_model_size_before_load) > 10 * MB:
-                self.logger.debug(
-                    f"Model '{key}' mis-reported its size before load. Self-reported size before/after load:"
-                    f" {(self_reported_model_size_before_load/GIG):.2f}GB /"
-                    f" {(self_reported_model_size_after_load/GIG):.2f}GB."
-                )
-
-            cache_entry = _CacheRecord(self, model, self_reported_model_size_after_load)
-            self._cached_models[key] = cache_entry
-        else:
-            if self.stats:
-                self.stats.hits += 1
-
-        if self.stats:
-            self.stats.cache_size = self.max_cache_size * GIG
-            self.stats.high_watermark = max(self.stats.high_watermark, self._cache_size())
-            self.stats.in_cache = len(self._cached_models)
-            self.stats.loaded_model_sizes[key] = max(
-                self.stats.loaded_model_sizes.get(key, 0), model_info.get_size(submodel)
-            )
-
-        with suppress(Exception):
-            self._cache_stack.remove(key)
-        self._cache_stack.append(key)
-
-        return self.ModelLocker(self, key, cache_entry.model, gpu_load, cache_entry.size)
-
-    def _move_model_to_device(self, key: str, target_device: torch.device):
-        cache_entry = self._cached_models[key]
-
-        source_device = cache_entry.model.device
-        # Note: We compare device types only so that 'cuda' == 'cuda:0'. This would need to be revised to support
-        # multi-GPU.
-        if torch.device(source_device).type == torch.device(target_device).type:
-            return
-
-        start_model_to_time = time.time()
-        snapshot_before = self._capture_memory_snapshot()
-        cache_entry.model.to(target_device)
-        snapshot_after = self._capture_memory_snapshot()
-        end_model_to_time = time.time()
-        self.logger.debug(
-            f"Moved model '{key}' from {source_device} to"
-            f" {target_device} in {(end_model_to_time-start_model_to_time):.2f}s.\n"
-            f"Estimated model size: {(cache_entry.size/GIG):.3f} GB.\n"
-            f"{get_pretty_snapshot_diff(snapshot_before, snapshot_after)}"
-        )
-
-        if (
-            snapshot_before is not None
-            and snapshot_after is not None
-            and snapshot_before.vram is not None
-            and snapshot_after.vram is not None
-        ):
-            vram_change = abs(snapshot_before.vram - snapshot_after.vram)
-
-            # If the estimated model size does not match the change in VRAM, log a warning.
-            if not math.isclose(
-                vram_change,
-                cache_entry.size,
-                rel_tol=0.1,
-                abs_tol=10 * MB,
-            ):
-                self.logger.debug(
-                    f"Moving model '{key}' from {source_device} to"
-                    f" {target_device} caused an unexpected change in VRAM usage. The model's"
-                    " estimated size may be incorrect. Estimated model size:"
-                    f" {(cache_entry.size/GIG):.3f} GB.\n"
-                    f"{get_pretty_snapshot_diff(snapshot_before, snapshot_after)}"
-                )
-
-    class ModelLocker(object):
-        def __init__(self, cache, key, model, gpu_load, size_needed):
-            """
-            :param cache: The model_cache object
-            :param key: The key of the model to lock in GPU
-            :param model: The model to lock
-            :param gpu_load: True if load into gpu
-            :param size_needed: Size of the model to load
-            """
-            self.gpu_load = gpu_load
-            self.cache = cache
-            self.key = key
-            self.model = model
-            self.size_needed = size_needed
-            self.cache_entry = self.cache._cached_models[self.key]
-
-        def __enter__(self) -> Any:
-            if not hasattr(self.model, "to"):
-                return self.model
-
-            # NOTE that the model has to have the to() method in order for this
-            # code to move it into GPU!
-            if self.gpu_load:
-                self.cache_entry.lock()
-
-                try:
-                    if self.cache.lazy_offloading:
-                        self.cache._offload_unlocked_models(self.size_needed)
-
-                    self.cache._move_model_to_device(self.key, self.cache.execution_device)
-
-                    self.cache.logger.debug(f"Locking {self.key} in {self.cache.execution_device}")
-                    self.cache._print_cuda_stats()
-
-                except Exception:
-                    self.cache_entry.unlock()
-                    raise
-
-            # TODO: not fully understand
-            # in the event that the caller wants the model in RAM, we
-            # move it into CPU if it is in GPU and not locked
-            elif self.cache_entry.loaded and not self.cache_entry.locked:
-                self.cache._move_model_to_device(self.key, self.cache.storage_device)
-
-            return self.model
-
-        def __exit__(self, type, value, traceback):
-            if not hasattr(self.model, "to"):
-                return
-
-            self.cache_entry.unlock()
-            if not self.cache.lazy_offloading:
-                self.cache._offload_unlocked_models()
-                self.cache._print_cuda_stats()
-
-    # TODO: should it be called untrack_model?
-    def uncache_model(self, cache_id: str):
-        with suppress(ValueError):
-            self._cache_stack.remove(cache_id)
-        self._cached_models.pop(cache_id, None)
-
-    def model_hash(
-        self,
-        model_path: Union[str, Path],
-    ) -> str:
-        """
-        Given the HF repo id or path to a model on disk, returns a unique
-        hash. Works for legacy checkpoint files, HF models on disk, and HF repo IDs
-
-        :param model_path: Path to model file/directory on disk.
-        """
-        return self._local_model_hash(model_path)
-
-    def cache_size(self) -> float:
-        """Return the current size of the cache, in GB."""
-        return self._cache_size() / GIG
-
-    def _has_cuda(self) -> bool:
-        return self.execution_device.type == "cuda"
-
-    def _print_cuda_stats(self):
-        vram = "%4.2fG" % (torch.cuda.memory_allocated() / GIG)
-        ram = "%4.2fG" % self.cache_size()
-
-        cached_models = 0
-        loaded_models = 0
-        locked_models = 0
-        for model_info in self._cached_models.values():
-            cached_models += 1
-            if model_info.loaded:
-                loaded_models += 1
-            if model_info.locked:
-                locked_models += 1
-
-        self.logger.debug(
-            f"Current VRAM/RAM usage: {vram}/{ram}; cached_models/loaded_models/locked_models/ ="
-            f" {cached_models}/{loaded_models}/{locked_models}"
-        )
-
-    def _cache_size(self) -> int:
-        return sum([m.size for m in self._cached_models.values()])
-
-    def _make_cache_room(self, model_size):
-        # calculate how much memory this model will require
-        # multiplier = 2 if self.precision==torch.float32 else 1
-        bytes_needed = model_size
-        maximum_size = self.max_cache_size * GIG  # stored in GB, convert to bytes
-        current_size = self._cache_size()
-
-        if current_size + bytes_needed > maximum_size:
-            self.logger.debug(
-                f"Max cache size exceeded: {(current_size/GIG):.2f}/{self.max_cache_size:.2f} GB, need an additional"
-                f" {(bytes_needed/GIG):.2f} GB"
-            )
-
-        self.logger.debug(f"Before unloading: cached_models={len(self._cached_models)}")
-
-        pos = 0
-        models_cleared = 0
-        while current_size + bytes_needed > maximum_size and pos < len(self._cache_stack):
-            model_key = self._cache_stack[pos]
-            cache_entry = self._cached_models[model_key]
-
-            refs = sys.getrefcount(cache_entry.model)
-
-            # HACK: This is a workaround for a memory-management issue that we haven't tracked down yet. We are directly
-            # going against the advice in the Python docs by using `gc.get_referrers(...)` in this way:
-            # https://docs.python.org/3/library/gc.html#gc.get_referrers
-
-            # manualy clear local variable references of just finished function calls
-            # for some reason python don't want to collect it even by gc.collect() immidiately
-            if refs > 2:
-                while True:
-                    cleared = False
-                    for referrer in gc.get_referrers(cache_entry.model):
-                        if type(referrer).__name__ == "frame":
-                            # RuntimeError: cannot clear an executing frame
-                            with suppress(RuntimeError):
-                                referrer.clear()
-                                cleared = True
-                                # break
-
-                    # repeat if referrers changes(due to frame clear), else exit loop
-                    if cleared:
-                        gc.collect()
-                    else:
-                        break
-
-            device = cache_entry.model.device if hasattr(cache_entry.model, "device") else None
-            self.logger.debug(
-                f"Model: {model_key}, locks: {cache_entry._locks}, device: {device}, loaded: {cache_entry.loaded},"
-                f" refs: {refs}"
-            )
-
-            # Expected refs:
-            # 1 from cache_entry
-            # 1 from getrefcount function
-            # 1 from onnx runtime object
-            if not cache_entry.locked and refs <= (3 if "onnx" in model_key else 2):
-                self.logger.debug(
-                    f"Unloading model {model_key} to free {(model_size/GIG):.2f} GB (-{(cache_entry.size/GIG):.2f} GB)"
-                )
-                current_size -= cache_entry.size
-                models_cleared += 1
-                if self.stats:
-                    self.stats.cleared += 1
-                del self._cache_stack[pos]
-                del self._cached_models[model_key]
-                del cache_entry
-
-            else:
-                pos += 1
-
-        if models_cleared > 0:
-            # There would likely be some 'garbage' to be collected regardless of whether a model was cleared or not, but
-            # there is a significant time cost to calling `gc.collect()`, so we want to use it sparingly. (The time cost
-            # is high even if no garbage gets collected.)
-            #
-            # Calling gc.collect(...) when a model is cleared seems like a good middle-ground:
-            # - If models had to be cleared, it's a signal that we are close to our memory limit.
-            # - If models were cleared, there's a good chance that there's a significant amount of garbage to be
-            #   collected.
-            #
-            # Keep in mind that gc is only responsible for handling reference cycles. Most objects should be cleaned up
-            # immediately when their reference count hits 0.
-            gc.collect()
-
-        torch.cuda.empty_cache()
-        if choose_torch_device() == torch.device("mps"):
-            mps.empty_cache()
-
-        self.logger.debug(f"After unloading: cached_models={len(self._cached_models)}")
-
-    def _offload_unlocked_models(self, size_needed: int = 0):
-        reserved = self.max_vram_cache_size * GIG
-        vram_in_use = torch.cuda.memory_allocated()
-        self.logger.debug(f"{(vram_in_use/GIG):.2f}GB VRAM used for models; max allowed={(reserved/GIG):.2f}GB")
-        for model_key, cache_entry in sorted(self._cached_models.items(), key=lambda x: x[1].size):
-            if vram_in_use <= reserved:
-                break
-            if not cache_entry.locked and cache_entry.loaded:
-                self._move_model_to_device(model_key, self.storage_device)
-
-                vram_in_use = torch.cuda.memory_allocated()
-                self.logger.debug(f"{(vram_in_use/GIG):.2f}GB VRAM used for models; max allowed={(reserved/GIG):.2f}GB")
-
-        torch.cuda.empty_cache()
-        if choose_torch_device() == torch.device("mps"):
-            mps.empty_cache()
-
-    def _local_model_hash(self, model_path: Union[str, Path]) -> str:
-        sha = hashlib.sha256()
-        path = Path(model_path)
-
-        hashpath = path / "checksum.sha256"
-        if hashpath.exists() and path.stat().st_mtime <= hashpath.stat().st_mtime:
-            with open(hashpath) as f:
-                hash = f.read()
-            return hash
-
-        self.logger.debug(f"computing hash of model {path.name}")
-        for file in list(path.rglob("*.ckpt")) + list(path.rglob("*.safetensors")) + list(path.rglob("*.pth")):
-            with open(file, "rb") as f:
-                while chunk := f.read(self.sha_chunksize):
-                    sha.update(chunk)
-        hash = sha.hexdigest()
-        with open(hashpath, "w") as f:
-            f.write(hash)
-        return hash
diff --git a/invokeai/backend/model_management_OLD/model_load_optimizations.py b/invokeai/backend/model_management_OLD/model_load_optimizations.py
deleted file mode 100644
index a46d262175..0000000000
--- a/invokeai/backend/model_management_OLD/model_load_optimizations.py
+++ /dev/null
@@ -1,30 +0,0 @@
-from contextlib import contextmanager
-
-import torch
-
-
-def _no_op(*args, **kwargs):
-    pass
-
-
-@contextmanager
-def skip_torch_weight_init():
-    """A context manager that monkey-patches several of the common torch layers (torch.nn.Linear, torch.nn.Conv1d, etc.)
-    to skip weight initialization.
-
-    By default, `torch.nn.Linear` and `torch.nn.ConvNd` layers initialize their weights (according to a particular
-    distribution) when __init__ is called. This weight initialization step can take a significant amount of time, and is
-    completely unnecessary if the intent is to load checkpoint weights from disk for the layer. This context manager
-    monkey-patches common torch layers to skip the weight initialization step.
-    """
-    torch_modules = [torch.nn.Linear, torch.nn.modules.conv._ConvNd, torch.nn.Embedding]
-    saved_functions = [m.reset_parameters for m in torch_modules]
-
-    try:
-        for torch_module in torch_modules:
-            torch_module.reset_parameters = _no_op
-
-        yield None
-    finally:
-        for torch_module, saved_function in zip(torch_modules, saved_functions, strict=True):
-            torch_module.reset_parameters = saved_function
diff --git a/invokeai/backend/model_management_OLD/model_manager.py b/invokeai/backend/model_management_OLD/model_manager.py
deleted file mode 100644
index 84d93f15fa..0000000000
--- a/invokeai/backend/model_management_OLD/model_manager.py
+++ /dev/null
@@ -1,1121 +0,0 @@
-"""This module manages the InvokeAI `models.yaml` file, mapping
-symbolic diffusers model names to the paths and repo_ids used by the
-underlying `from_pretrained()` call.
-
-SYNOPSIS:
-
- mgr = ModelManager('/home/phi/invokeai/configs/models.yaml')
- sd1_5 = mgr.get_model('stable-diffusion-v1-5',
-                       model_type=ModelType.Main,
-                       base_model=BaseModelType.StableDiffusion1,
-                       submodel_type=SubModelType.Unet)
- with sd1_5 as unet:
-    run_some_inference(unet)
-
-FETCHING MODELS:
-
-Models are described using four attributes:
-
-  1) model_name -- the symbolic name for the model
-
-  2) ModelType  -- an enum describing the type of the model. Currently
-                  defined types are:
-         ModelType.Main -- a full model capable of generating images
-         ModelType.Vae  -- a VAE model
-         ModelType.Lora -- a LoRA or LyCORIS fine-tune
-         ModelType.TextualInversion -- a textual inversion embedding
-         ModelType.ControlNet -- a ControlNet model
-         ModelType.IPAdapter -- an IPAdapter model
-
-  3) BaseModelType -- an enum indicating the stable diffusion base model, one of:
-         BaseModelType.StableDiffusion1
-         BaseModelType.StableDiffusion2
-
-  4) SubModelType (optional) -- an enum that refers to one of the submodels contained
-                                within the main model. Values are:
-
-         SubModelType.UNet
-         SubModelType.TextEncoder
-         SubModelType.Tokenizer
-         SubModelType.Scheduler
-         SubModelType.SafetyChecker
-
-To fetch a model, use `manager.get_model()`. This takes the symbolic
-name of the model, the ModelType, the BaseModelType and the
-SubModelType. The latter is required for ModelType.Main.
-
-get_model() will return a ModelInfo object that can then be used in
-context to retrieve the model and move it into GPU VRAM (on GPU
-systems).
-
-A typical example is:
-
- sd1_5 = mgr.get_model('stable-diffusion-v1-5',
-                       model_type=ModelType.Main,
-                       base_model=BaseModelType.StableDiffusion1,
-                       submodel_type=SubModelType.UNet)
- with sd1_5 as unet:
-    run_some_inference(unet)
-
-The ModelInfo object provides a number of useful fields describing the
-model, including:
-
-   name  -- symbolic name of the model
-   base_model -- base model (BaseModelType)
-   type -- model type (ModelType)
-   location -- path to the model file
-   precision -- torch precision of the model
-   hash -- unique sha256 checksum for this model
-
-SUBMODELS:
-
-When fetching a main model, you must specify the submodel. Retrieval
-of full pipelines is not supported.
-
- vae_info = mgr.get_model('stable-diffusion-1.5',
-                          model_type = ModelType.Main,
-                          base_model = BaseModelType.StableDiffusion1,
-                          submodel_type = SubModelType.Vae
-                          )
- with vae_info as vae:
-    do_something(vae)
-
-This rule does not apply to controlnets, embeddings, loras and standalone
-VAEs, which do not have submodels.
-
-LISTING MODELS
-
-The model_names() method will return a list of Tuples describing each
-model it knows about:
-
-  >> mgr.model_names()
-  [
-    ('stable-diffusion-1.5', <BaseModelType.StableDiffusion1: 'sd-1'>, <ModelType.Main: 'main'>),
-    ('stable-diffusion-2.1', <BaseModelType.StableDiffusion2: 'sd-2'>, <ModelType.Main: 'main'>),
-    ('inpaint', <BaseModelType.StableDiffusion1: 'sd-1'>, <ModelType.ControlNet: 'controlnet'>)
-    ('Ink scenery', <BaseModelType.StableDiffusion1: 'sd-1'>, <ModelType.Lora: 'lora'>)
-    ...
-  ]
-
-The tuple is in the correct order to pass to get_model():
-
-   for m in mgr.model_names():
-       info = get_model(*m)
-
-In contrast, the list_models() method returns a list of dicts, each
-providing information about a model defined in models.yaml. For example:
-
-   >>> models = mgr.list_models()
-   >>> json.dumps(models[0])
-  {"path": "/home/lstein/invokeai-main/models/sd-1/controlnet/canny",
-    "model_format": "diffusers",
-    "name": "canny",
-    "base_model": "sd-1",
-    "type": "controlnet"
-   }
-
-You can filter by model type and base model as shown here:
-
-
-  controlnets = mgr.list_models(model_type=ModelType.ControlNet,
-                                base_model=BaseModelType.StableDiffusion1)
-  for c in controlnets:
-     name = c['name']
-     format = c['model_format']
-     path = c['path']
-     type = c['type']
-     # etc
-
-ADDING AND REMOVING MODELS
-
-At startup time, the `models` directory will be scanned for
-checkpoints, diffusers pipelines, controlnets, LoRAs and TI
-embeddings. New entries will be added to the model manager and defunct
-ones removed. Anything that is a main model (ModelType.Main) will be
-added to models.yaml. For scanning to succeed, files need to be in
-their proper places. For example, a controlnet folder built on the
-stable diffusion 2 base, will need to be placed in
-`models/sd-2/controlnet`.
-
-Layout of the `models` directory:
-
- models
- ├── sd-1
- │   ├── controlnet
- │   ├── lora
- │   ├── main
- │   └── embedding
- ├── sd-2
- │   ├── controlnet
- │   ├── lora
- │   ├── main
- │   └── embedding
- └── core
-     ├── face_reconstruction
-     │   ├── codeformer
-     │   └── gfpgan
-     ├── sd-conversion
-     │   ├── clip-vit-large-patch14 - tokenizer, text_encoder subdirs
-     │   ├── stable-diffusion-2 - tokenizer, text_encoder subdirs
-     │   └── stable-diffusion-safety-checker
-     └── upscaling
-         └─── esrgan
-
-
-
-class ConfigMeta(BaseModel):Loras, textual_inversion and controlnet models are not listed
-explicitly in models.yaml, but are added to the in-memory data
-structure at initialization time by scanning the models directory. The
-in-memory data structure can be resynchronized by calling
-`manager.scan_models_directory()`.
-
-Files and folders placed inside the `autoimport` paths (paths
-defined in `invokeai.yaml`) will also be scanned for new models at
-initialization time and added to `models.yaml`. Files will not be
-moved from this location but preserved in-place. These directories
-are:
-
-  configuration    default              description
-  -------------    -------              -----------
-  autoimport_dir  autoimport/main       main models
-  lora_dir        autoimport/lora       LoRA/LyCORIS models
-  embedding_dir   autoimport/embedding  TI embeddings
-  controlnet_dir  autoimport/controlnet ControlNet models
-
-In actuality, models located in any of these directories are scanned
-to determine their type, so it isn't strictly necessary to organize
-the different types in this way. This entry in `invokeai.yaml` will
-recursively scan all subdirectories within `autoimport`, scan models
-files it finds, and import them if recognized.
-
-  Paths:
-     autoimport_dir: autoimport
-
-A model can be manually added using `add_model()` using the model's
-name, base model, type and a dict of model attributes. See
-`invokeai/backend/model_management/models` for the attributes required
-by each model type.
-
-A model can be deleted using `del_model()`, providing the same
-identifying information as `get_model()`
-
-The `heuristic_import()` method will take a set of strings
-corresponding to local paths, remote URLs, and repo_ids, probe the
-object to determine what type of model it is (if any), and import new
-models into the manager. If passed a directory, it will recursively
-scan it for models to import. The return value is a set of the models
-successfully added.
-
-MODELS.YAML
-
-The general format of a models.yaml section is:
-
- type-of-model/name-of-model:
-     path: /path/to/local/file/or/directory
-     description: a description
-     format: diffusers|checkpoint
-     variant: normal|inpaint|depth
-
-The type of model is given in the stanza key, and is one of
-{main, vae, lora, controlnet, textual}
-
-The format indicates whether the model is organized as a diffusers
-folder with model subdirectories, or is contained in a single
-checkpoint or safetensors file.
-
-The path points to a file or directory on disk. If a relative path,
-the root is the InvokeAI ROOTDIR.
-
-"""
-from __future__ import annotations
-
-import hashlib
-import os
-import textwrap
-import types
-from dataclasses import dataclass
-from pathlib import Path
-from shutil import move, rmtree
-from typing import Callable, Dict, List, Literal, Optional, Set, Tuple, Union, cast
-
-import torch
-import yaml
-from omegaconf import OmegaConf
-from omegaconf.dictconfig import DictConfig
-from pydantic import BaseModel, ConfigDict, Field
-
-import invokeai.backend.util.logging as logger
-from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.backend.util import CUDA_DEVICE, Chdir
-
-from .model_cache import ModelCache, ModelLocker
-from .model_search import ModelSearch
-from .models import (
-    MODEL_CLASSES,
-    BaseModelType,
-    DuplicateModelException,
-    InvalidModelException,
-    ModelBase,
-    ModelConfigBase,
-    ModelError,
-    ModelNotFoundException,
-    ModelType,
-    SchedulerPredictionType,
-    SubModelType,
-)
-
-# We are only starting to number the config file with release 3.
-# The config file version doesn't have to start at release version, but it will help
-# reduce confusion.
-CONFIG_FILE_VERSION = "3.0.0"
-
-
-@dataclass
-class LoadedModelInfo:
-    context: ModelLocker
-    name: str
-    base_model: BaseModelType
-    type: ModelType
-    hash: str
-    location: Union[Path, str]
-    precision: torch.dtype
-    _cache: Optional[ModelCache] = None
-
-    def __enter__(self):
-        return self.context.__enter__()
-
-    def __exit__(self, *args, **kwargs):
-        self.context.__exit__(*args, **kwargs)
-
-
-class AddModelResult(BaseModel):
-    name: str = Field(description="The name of the model after installation")
-    model_type: ModelType = Field(description="The type of model")
-    base_model: BaseModelType = Field(description="The base model")
-    config: ModelConfigBase = Field(description="The configuration of the model")
-
-    model_config = ConfigDict(protected_namespaces=())
-
-
-MAX_CACHE_SIZE = 6.0  # GB
-
-
-class ConfigMeta(BaseModel):
-    version: str
-
-
-class ModelManager(object):
-    """
-    High-level interface to model management.
-    """
-
-    logger: types.ModuleType = logger
-
-    def __init__(
-        self,
-        config: Union[Path, DictConfig, str],
-        device_type: torch.device = CUDA_DEVICE,
-        precision: torch.dtype = torch.float16,
-        max_cache_size=MAX_CACHE_SIZE,
-        sequential_offload=False,
-        logger: types.ModuleType = logger,
-    ):
-        """
-        Initialize with the path to the models.yaml config file.
-        Optional parameters are the torch device type, precision, max_models,
-        and sequential_offload boolean. Note that the default device
-        type and precision are set up for a CUDA system running at half precision.
-        """
-        self.config_path = None
-        if isinstance(config, (str, Path)):
-            self.config_path = Path(config)
-            if not self.config_path.exists():
-                logger.warning(f"The file {self.config_path} was not found. Initializing a new file")
-                self.initialize_model_config(self.config_path)
-            config = OmegaConf.load(self.config_path)
-
-        elif not isinstance(config, DictConfig):
-            raise ValueError("config argument must be an OmegaConf object, a Path or a string")
-
-        self.config_meta = ConfigMeta(**config.pop("__metadata__"))
-        # TODO: metadata not found
-        # TODO: version check
-
-        self.app_config = InvokeAIAppConfig.get_config()
-        self.logger = logger
-        self.cache = ModelCache(
-            max_cache_size=max_cache_size,
-            max_vram_cache_size=self.app_config.vram_cache_size,
-            lazy_offloading=self.app_config.lazy_offload,
-            execution_device=device_type,
-            precision=precision,
-            sequential_offload=sequential_offload,
-            logger=logger,
-            log_memory_usage=self.app_config.log_memory_usage,
-        )
-
-        self._read_models(config)
-
-    def _read_models(self, config: Optional[DictConfig] = None):
-        if not config:
-            if self.config_path:
-                config = OmegaConf.load(self.config_path)
-            else:
-                return
-
-        self.models = {}
-        for model_key, model_config in config.items():
-            if model_key.startswith("_"):
-                continue
-            model_name, base_model, model_type = self.parse_key(model_key)
-            model_class = self._get_implementation(base_model, model_type)
-            # alias for config file
-            model_config["model_format"] = model_config.pop("format")
-            self.models[model_key] = model_class.create_config(**model_config)
-
-        # check config version number and update on disk/RAM if necessary
-        self.cache_keys = {}
-
-        # add controlnet, lora and textual_inversion models from disk
-        self.scan_models_directory()
-
-    def sync_to_config(self):
-        """
-        Call this when `models.yaml` has been changed externally.
-        This will reinitialize internal data structures
-        """
-        # Reread models directory; note that this will reinitialize the cache,
-        # causing otherwise unreferenced models to be removed from memory
-        self._read_models()
-
-    def model_exists(self, model_name: str, base_model: BaseModelType, model_type: ModelType, *, rescan=False) -> bool:
-        """
-        Given a model name, returns True if it is a valid identifier.
-
-        :param model_name: symbolic name of the model in models.yaml
-        :param model_type: ModelType enum indicating the type of model to return
-        :param base_model: BaseModelType enum indicating the base model used by this model
-        :param rescan: if True, scan_models_directory
-        """
-        model_key = self.create_key(model_name, base_model, model_type)
-        exists = model_key in self.models
-
-        # if model not found try to find it (maybe file just pasted)
-        if rescan and not exists:
-            self.scan_models_directory(base_model=base_model, model_type=model_type)
-            exists = self.model_exists(model_name, base_model, model_type, rescan=False)
-
-        return exists
-
-    @classmethod
-    def create_key(
-        cls,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-    ) -> str:
-        # In 3.11, the behavior of (str,enum) when interpolated into a
-        # string has changed. The next two lines are defensive.
-        base_model = BaseModelType(base_model)
-        model_type = ModelType(model_type)
-        return f"{base_model.value}/{model_type.value}/{model_name}"
-
-    @classmethod
-    def parse_key(cls, model_key: str) -> Tuple[str, BaseModelType, ModelType]:
-        base_model_str, model_type_str, model_name = model_key.split("/", 2)
-        try:
-            model_type = ModelType(model_type_str)
-        except Exception:
-            raise Exception(f"Unknown model type: {model_type_str}")
-
-        try:
-            base_model = BaseModelType(base_model_str)
-        except Exception:
-            raise Exception(f"Unknown base model: {base_model_str}")
-
-        return (model_name, base_model, model_type)
-
-    def _get_model_cache_path(self, model_path):
-        return self.resolve_model_path(Path(".cache") / hashlib.md5(str(model_path).encode()).hexdigest())
-
-    @classmethod
-    def initialize_model_config(cls, config_path: Path):
-        """Create empty config file"""
-        with open(config_path, "w") as yaml_file:
-            yaml_file.write(yaml.dump({"__metadata__": {"version": "3.0.0"}}))
-
-    def get_model(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-        submodel_type: Optional[SubModelType] = None,
-    ) -> LoadedModelInfo:
-        """Given a model named identified in models.yaml, return
-        an ModelInfo object describing it.
-        :param model_name: symbolic name of the model in models.yaml
-        :param model_type: ModelType enum indicating the type of model to return
-        :param base_model: BaseModelType enum indicating the base model used by this model
-        :param submodel_type: an ModelType enum indicating the portion of
-               the model to retrieve (e.g. ModelType.Vae)
-        """
-        model_key = self.create_key(model_name, base_model, model_type)
-
-        if not self.model_exists(model_name, base_model, model_type, rescan=True):
-            raise ModelNotFoundException(f"Model not found - {model_key}")
-
-        model_config = self._get_model_config(base_model, model_name, model_type)
-
-        model_path, is_submodel_override = self._get_model_path(model_config, submodel_type)
-
-        if is_submodel_override:
-            model_type = submodel_type
-            submodel_type = None
-
-        model_class = self._get_implementation(base_model, model_type)
-
-        if not model_path.exists():
-            if model_class.save_to_config:
-                self.models[model_key].error = ModelError.NotFound
-                raise Exception(f'Files for model "{model_key}" not found at {model_path}')
-
-            else:
-                self.models.pop(model_key, None)
-                raise ModelNotFoundException(f'Files for model "{model_key}" not found at {model_path}')
-
-        # TODO: path
-        # TODO: is it accurate to use path as id
-        dst_convert_path = self._get_model_cache_path(model_path)
-
-        model_path = model_class.convert_if_required(
-            base_model=base_model,
-            model_path=str(model_path),  # TODO: refactor str/Path types logic
-            output_path=dst_convert_path,
-            config=model_config,
-        )
-
-        model_context = self.cache.get_model(
-            model_path=model_path,
-            model_class=model_class,
-            base_model=base_model,
-            model_type=model_type,
-            submodel_type=submodel_type,
-        )
-
-        if model_key not in self.cache_keys:
-            self.cache_keys[model_key] = set()
-        self.cache_keys[model_key].add(model_context.key)
-
-        model_hash = "<NO_HASH>"  # TODO:
-
-        return LoadedModelInfo(
-            context=model_context,
-            name=model_name,
-            base_model=base_model,
-            type=submodel_type or model_type,
-            hash=model_hash,
-            location=model_path,  # TODO:
-            precision=self.cache.precision,
-            _cache=self.cache,
-        )
-
-    def _get_model_path(
-        self, model_config: ModelConfigBase, submodel_type: Optional[SubModelType] = None
-    ) -> (Path, bool):
-        """Extract a model's filesystem path from its config.
-
-        :return: The fully qualified Path of the module (or submodule).
-        """
-        model_path = model_config.path
-        is_submodel_override = False
-
-        # Does the config explicitly override the submodel?
-        if submodel_type is not None and hasattr(model_config, submodel_type):
-            submodel_path = getattr(model_config, submodel_type)
-            if submodel_path is not None and len(submodel_path) > 0:
-                model_path = getattr(model_config, submodel_type)
-                is_submodel_override = True
-
-        model_path = self.resolve_model_path(model_path)
-        return model_path, is_submodel_override
-
-    def _get_model_config(self, base_model: BaseModelType, model_name: str, model_type: ModelType) -> ModelConfigBase:
-        """Get a model's config object."""
-        model_key = self.create_key(model_name, base_model, model_type)
-        try:
-            model_config = self.models[model_key]
-        except KeyError:
-            raise ModelNotFoundException(f"Model not found - {model_key}")
-        return model_config
-
-    def _get_implementation(self, base_model: BaseModelType, model_type: ModelType) -> type[ModelBase]:
-        """Get the concrete implementation class for a specific model type."""
-        model_class = MODEL_CLASSES[base_model][model_type]
-        return model_class
-
-    def _instantiate(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-        submodel_type: Optional[SubModelType] = None,
-    ) -> ModelBase:
-        """Make a new instance of this model, without loading it."""
-        model_config = self._get_model_config(base_model, model_name, model_type)
-        model_path, is_submodel_override = self._get_model_path(model_config, submodel_type)
-        # FIXME: do non-overriden submodels get the right class?
-        constructor = self._get_implementation(base_model, model_type)
-        instance = constructor(model_path, base_model, model_type)
-        return instance
-
-    def model_info(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-    ) -> Union[dict, None]:
-        """
-        Given a model name returns the OmegaConf (dict-like) object describing it.
-        """
-        model_key = self.create_key(model_name, base_model, model_type)
-        if model_key in self.models:
-            return self.models[model_key].model_dump(exclude_defaults=True)
-        else:
-            return None  # TODO: None or empty dict on not found
-
-    def model_names(self) -> List[Tuple[str, BaseModelType, ModelType]]:
-        """
-        Return a list of (str, BaseModelType, ModelType) corresponding to all models
-        known to the configuration.
-        """
-        return [(self.parse_key(x)) for x in self.models.keys()]
-
-    def list_model(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-    ) -> Union[dict, None]:
-        """
-        Returns a dict describing one installed model, using
-        the combined format of the list_models() method.
-        """
-        models = self.list_models(base_model, model_type, model_name)
-        if len(models) >= 1:
-            return models[0]
-        else:
-            return None
-
-    def list_models(
-        self,
-        base_model: Optional[BaseModelType] = None,
-        model_type: Optional[ModelType] = None,
-        model_name: Optional[str] = None,
-    ) -> list[dict]:
-        """
-        Return a list of models.
-        """
-
-        model_keys = (
-            [self.create_key(model_name, base_model, model_type)]
-            if model_name and base_model and model_type
-            else sorted(self.models, key=str.casefold)
-        )
-        models = []
-        for model_key in model_keys:
-            model_config = self.models.get(model_key)
-            if not model_config:
-                self.logger.error(f"Unknown model {model_name}")
-                raise ModelNotFoundException(f"Unknown model {model_name}")
-
-            cur_model_name, cur_base_model, cur_model_type = self.parse_key(model_key)
-            if base_model is not None and cur_base_model != base_model:
-                continue
-            if model_type is not None and cur_model_type != model_type:
-                continue
-
-            model_dict = dict(
-                **model_config.model_dump(exclude_defaults=True),
-                # OpenAPIModelInfoBase
-                model_name=cur_model_name,
-                base_model=cur_base_model,
-                model_type=cur_model_type,
-            )
-
-            # expose paths as absolute to help web UI
-            if path := model_dict.get("path"):
-                model_dict["path"] = str(self.resolve_model_path(path))
-            models.append(model_dict)
-
-        return models
-
-    def print_models(self) -> None:
-        """
-        Print a table of models and their descriptions. This needs to be redone
-        """
-        # TODO: redo
-        for model_dict in self.list_models():
-            for _model_name, model_info in model_dict.items():
-                line = f'{model_info["name"]:25s} {model_info["type"]:10s} {model_info["description"]}'
-                print(line)
-
-    # Tested - LS
-    def del_model(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-    ):
-        """
-        Delete the named model.
-        """
-        model_key = self.create_key(model_name, base_model, model_type)
-        model_cfg = self.models.pop(model_key, None)
-
-        if model_cfg is None:
-            raise ModelNotFoundException(f"Unknown model {model_key}")
-
-        # note: it not garantie to release memory(model can has other references)
-        cache_ids = self.cache_keys.pop(model_key, [])
-        for cache_id in cache_ids:
-            self.cache.uncache_model(cache_id)
-
-        # if model inside invoke models folder - delete files
-        model_path = self.resolve_model_path(model_cfg.path)
-        cache_path = self._get_model_cache_path(model_path)
-        if cache_path.exists():
-            rmtree(str(cache_path))
-
-        if model_path.is_relative_to(self.app_config.models_path):
-            if model_path.is_dir():
-                rmtree(str(model_path))
-            else:
-                model_path.unlink()
-        self.commit()
-
-    # LS: tested
-    def add_model(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-        model_attributes: dict,
-        clobber: bool = False,
-    ) -> AddModelResult:
-        """
-        Update the named model with a dictionary of attributes. Will fail with an
-        assertion error if the name already exists. Pass clobber=True to overwrite.
-        On a successful update, the config will be changed in memory and the
-        method will return True. Will fail with an assertion error if provided
-        attributes are incorrect or the model name is missing.
-
-        The returned dict has the same format as the dict returned by
-        model_info().
-        """
-        # relativize paths as they go in - this makes it easier to move the models directory around
-        if path := model_attributes.get("path"):
-            model_attributes["path"] = str(self.relative_model_path(Path(path)))
-
-        model_class = self._get_implementation(base_model, model_type)
-        model_config = model_class.create_config(**model_attributes)
-        model_key = self.create_key(model_name, base_model, model_type)
-
-        if model_key in self.models and not clobber:
-            raise Exception(f'Attempt to overwrite existing model definition "{model_key}"')
-
-        old_model = self.models.pop(model_key, None)
-        if old_model is not None:
-            # TODO: if path changed and old_model.path inside models folder should we delete this too?
-
-            # remove conversion cache as config changed
-            old_model_path = self.resolve_model_path(old_model.path)
-            old_model_cache = self._get_model_cache_path(old_model_path)
-            if old_model_cache.exists():
-                if old_model_cache.is_dir():
-                    rmtree(str(old_model_cache))
-                else:
-                    old_model_cache.unlink()
-
-            # remove in-memory cache
-            # note: it not guaranteed to release memory(model can has other references)
-            cache_ids = self.cache_keys.pop(model_key, [])
-            for cache_id in cache_ids:
-                self.cache.uncache_model(cache_id)
-
-        self.models[model_key] = model_config
-        self.commit()
-
-        return AddModelResult(
-            name=model_name,
-            model_type=model_type,
-            base_model=base_model,
-            config=model_config,
-        )
-
-    def rename_model(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-        new_name: Optional[str] = None,
-        new_base: Optional[BaseModelType] = None,
-    ) -> None:
-        """
-        Rename or rebase a model.
-        """
-        if new_name is None and new_base is None:
-            self.logger.error("rename_model() called with neither a new_name nor a new_base. {model_name} unchanged.")
-            return
-
-        model_key = self.create_key(model_name, base_model, model_type)
-        model_cfg = self.models.get(model_key, None)
-        if not model_cfg:
-            raise ModelNotFoundException(f"Unknown model: {model_key}")
-
-        old_path = self.resolve_model_path(model_cfg.path)
-        new_name = new_name or model_name
-        new_base = new_base or base_model
-        new_key = self.create_key(new_name, new_base, model_type)
-        if new_key in self.models:
-            raise ValueError(f'Attempt to overwrite existing model definition "{new_key}"')
-
-        # if this is a model file/directory that we manage ourselves, we need to move it
-        if old_path.is_relative_to(self.app_config.models_path):
-            # keep the suffix!
-            if old_path.is_file():
-                new_name = Path(new_name).with_suffix(old_path.suffix).as_posix()
-            new_path = self.resolve_model_path(
-                Path(
-                    BaseModelType(new_base).value,
-                    ModelType(model_type).value,
-                    new_name,
-                )
-            )
-            move(old_path, new_path)
-            model_cfg.path = str(new_path.relative_to(self.app_config.models_path))
-
-        # clean up caches
-        old_model_cache = self._get_model_cache_path(old_path)
-        if old_model_cache.exists():
-            if old_model_cache.is_dir():
-                rmtree(str(old_model_cache))
-            else:
-                old_model_cache.unlink()
-
-        cache_ids = self.cache_keys.pop(model_key, [])
-        for cache_id in cache_ids:
-            self.cache.uncache_model(cache_id)
-
-        self.models.pop(model_key, None)  # delete
-        self.models[new_key] = model_cfg
-        self.commit()
-
-    def convert_model(
-        self,
-        model_name: str,
-        base_model: BaseModelType,
-        model_type: Literal[ModelType.Main, ModelType.Vae],
-        dest_directory: Optional[Path] = None,
-    ) -> AddModelResult:
-        """
-        Convert a checkpoint file into a diffusers folder, deleting the cached
-        version and deleting the original checkpoint file if it is in the models
-        directory.
-        :param model_name: Name of the model to convert
-        :param base_model: Base model type
-        :param model_type: Type of model ['vae' or 'main']
-
-        This will raise a ValueError unless the model is a checkpoint.
-        """
-        info = self.model_info(model_name, base_model, model_type)
-
-        if info is None:
-            raise FileNotFoundError(f"model not found: {model_name}")
-
-        if info["model_format"] != "checkpoint":
-            raise ValueError(f"not a checkpoint format model: {model_name}")
-
-        # We are taking advantage of a side effect of get_model() that converts check points
-        # into cached diffusers directories stored at `location`. It doesn't matter
-        # what submodeltype we request here, so we get the smallest.
-        submodel = {"submodel_type": SubModelType.Scheduler} if model_type == ModelType.Main else {}
-        model = self.get_model(
-            model_name,
-            base_model,
-            model_type,
-            **submodel,
-        )
-        checkpoint_path = self.resolve_model_path(info["path"])
-        old_diffusers_path = self.resolve_model_path(model.location)
-        new_diffusers_path = (
-            dest_directory or self.app_config.models_path / base_model.value / model_type.value
-        ) / model_name
-        if new_diffusers_path.exists():
-            raise ValueError(f"A diffusers model already exists at {new_diffusers_path}")
-
-        try:
-            move(old_diffusers_path, new_diffusers_path)
-            info["model_format"] = "diffusers"
-            info["path"] = (
-                str(new_diffusers_path)
-                if dest_directory
-                else str(new_diffusers_path.relative_to(self.app_config.models_path))
-            )
-            info.pop("config")
-
-            result = self.add_model(model_name, base_model, model_type, model_attributes=info, clobber=True)
-        except Exception:
-            # something went wrong, so don't leave dangling diffusers model in directory or it will cause a duplicate model error!
-            rmtree(new_diffusers_path)
-            raise
-
-        if checkpoint_path.exists() and checkpoint_path.is_relative_to(self.app_config.models_path):
-            checkpoint_path.unlink()
-
-        return result
-
-    def resolve_model_path(self, path: Union[Path, str]) -> Path:
-        """return relative paths based on configured models_path"""
-        return self.app_config.models_path / path
-
-    def relative_model_path(self, model_path: Path) -> Path:
-        if model_path.is_relative_to(self.app_config.models_path):
-            model_path = model_path.relative_to(self.app_config.models_path)
-        return model_path
-
-    def search_models(self, search_folder):
-        self.logger.info(f"Finding Models In: {search_folder}")
-        models_folder_ckpt = Path(search_folder).glob("**/*.ckpt")
-        models_folder_safetensors = Path(search_folder).glob("**/*.safetensors")
-
-        ckpt_files = [x for x in models_folder_ckpt if x.is_file()]
-        safetensor_files = [x for x in models_folder_safetensors if x.is_file()]
-
-        files = ckpt_files + safetensor_files
-
-        found_models = []
-        for file in files:
-            location = str(file.resolve()).replace("\\", "/")
-            if "model.safetensors" not in location and "diffusion_pytorch_model.safetensors" not in location:
-                found_models.append({"name": file.stem, "location": location})
-
-        return search_folder, found_models
-
-    def commit(self, conf_file: Optional[Path] = None) -> None:
-        """
-        Write current configuration out to the indicated file.
-        """
-        data_to_save = {}
-        data_to_save["__metadata__"] = self.config_meta.model_dump()
-
-        for model_key, model_config in self.models.items():
-            model_name, base_model, model_type = self.parse_key(model_key)
-            model_class = self._get_implementation(base_model, model_type)
-            if model_class.save_to_config:
-                # TODO: or exclude_unset better fits here?
-                data_to_save[model_key] = cast(BaseModel, model_config).model_dump(
-                    exclude_defaults=True, exclude={"error"}, mode="json"
-                )
-                # alias for config file
-                data_to_save[model_key]["format"] = data_to_save[model_key].pop("model_format")
-
-        yaml_str = OmegaConf.to_yaml(data_to_save)
-        config_file_path = conf_file or self.config_path
-        assert config_file_path is not None, "no config file path to write to"
-        config_file_path = self.app_config.root_path / config_file_path
-        tmpfile = os.path.join(os.path.dirname(config_file_path), "new_config.tmp")
-        try:
-            with open(tmpfile, "w", encoding="utf-8") as outfile:
-                outfile.write(self.preamble())
-                outfile.write(yaml_str)
-            os.replace(tmpfile, config_file_path)
-        except OSError as err:
-            self.logger.warning(f"Could not modify the config file at {config_file_path}")
-            self.logger.warning(err)
-
-    def preamble(self) -> str:
-        """
-        Returns the preamble for the config file.
-        """
-        return textwrap.dedent(
-            """
-            # This file describes the alternative machine learning models
-            # available to InvokeAI script.
-            #
-            # To add a new model, follow the examples below. Each
-            # model requires a model config file, a weights file,
-            # and the width and height of the images it
-            # was trained on.
-        """
-        )
-
-    def scan_models_directory(
-        self,
-        base_model: Optional[BaseModelType] = None,
-        model_type: Optional[ModelType] = None,
-    ):
-        loaded_files = set()
-        new_models_found = False
-
-        self.logger.info(f"Scanning {self.app_config.models_path} for new models")
-        with Chdir(self.app_config.models_path):
-            for model_key, model_config in list(self.models.items()):
-                model_name, cur_base_model, cur_model_type = self.parse_key(model_key)
-
-                # Patch for relative path bug in older models.yaml - paths should not
-                # be starting with a hard-coded 'models'. This will also fix up
-                # models.yaml when committed.
-                if model_config.path.startswith("models"):
-                    model_config.path = str(Path(*Path(model_config.path).parts[1:]))
-
-                model_path = self.resolve_model_path(model_config.path).absolute()
-                if not model_path.exists():
-                    model_class = self._get_implementation(cur_base_model, cur_model_type)
-                    if model_class.save_to_config:
-                        model_config.error = ModelError.NotFound
-                        self.models.pop(model_key, None)
-                    else:
-                        self.models.pop(model_key, None)
-                else:
-                    loaded_files.add(model_path)
-
-            for cur_base_model in BaseModelType:
-                if base_model is not None and cur_base_model != base_model:
-                    continue
-
-                for cur_model_type in ModelType:
-                    if model_type is not None and cur_model_type != model_type:
-                        continue
-                    model_class = self._get_implementation(cur_base_model, cur_model_type)
-                    models_dir = self.resolve_model_path(Path(cur_base_model.value, cur_model_type.value))
-
-                    if not models_dir.exists():
-                        continue  # TODO: or create all folders?
-
-                    for model_path in models_dir.iterdir():
-                        if model_path not in loaded_files:  # TODO: check
-                            if model_path.name.startswith("."):
-                                continue
-                            model_name = model_path.name if model_path.is_dir() else model_path.stem
-                            model_key = self.create_key(model_name, cur_base_model, cur_model_type)
-
-                            try:
-                                if model_key in self.models:
-                                    raise DuplicateModelException(f"Model with key {model_key} added twice")
-
-                                model_path = self.relative_model_path(model_path)
-                                model_config: ModelConfigBase = model_class.probe_config(
-                                    str(model_path), model_base=cur_base_model
-                                )
-                                self.models[model_key] = model_config
-                                new_models_found = True
-                            except DuplicateModelException as e:
-                                self.logger.warning(e)
-                            except InvalidModelException as e:
-                                self.logger.warning(f"Not a valid model: {model_path}. {e}")
-                            except NotImplementedError as e:
-                                self.logger.warning(e)
-                            except Exception as e:
-                                self.logger.warning(f"Error loading model {model_path}. {e}")
-
-        imported_models = self.scan_autoimport_directory()
-        if (new_models_found or imported_models) and self.config_path:
-            self.commit()
-
-    def scan_autoimport_directory(self) -> Dict[str, AddModelResult]:
-        """
-        Scan the autoimport directory (if defined) and import new models, delete defunct models.
-        """
-        # avoid circular import
-        from invokeai.backend.install.model_install_backend import ModelInstall
-        from invokeai.frontend.install.model_install import ask_user_for_prediction_type
-
-        class ScanAndImport(ModelSearch):
-            def __init__(self, directories, logger, ignore: Set[Path], installer: ModelInstall):
-                super().__init__(directories, logger)
-                self.installer = installer
-                self.ignore = ignore
-
-            def on_search_started(self):
-                self.new_models_found = {}
-
-            def on_model_found(self, model: Path):
-                if model not in self.ignore:
-                    self.new_models_found.update(self.installer.heuristic_import(model))
-
-            def on_search_completed(self):
-                self.logger.info(
-                    f"Scanned {self._items_scanned} files and directories, imported {len(self.new_models_found)} models"
-                )
-
-            def models_found(self):
-                return self.new_models_found
-
-        config = self.app_config
-
-        # LS: hacky
-        # Patch in the SD VAE from core so that it is available for use by the UI
-        try:
-            self.heuristic_import({str(self.resolve_model_path("core/convert/sd-vae-ft-mse"))})
-        except Exception:
-            pass
-
-        installer = ModelInstall(
-            config=self.app_config,
-            model_manager=self,
-            prediction_type_helper=ask_user_for_prediction_type,
-        )
-        known_paths = {self.resolve_model_path(x["path"]) for x in self.list_models()}
-        directories = {
-            config.root_path / x
-            for x in [
-                config.autoimport_dir,
-                config.lora_dir,
-                config.embedding_dir,
-                config.controlnet_dir,
-            ]
-            if x
-        }
-        scanner = ScanAndImport(directories, self.logger, ignore=known_paths, installer=installer)
-        scanner.search()
-
-        return scanner.models_found()
-
-    def heuristic_import(
-        self,
-        items_to_import: Set[str],
-        prediction_type_helper: Optional[Callable[[Path], SchedulerPredictionType]] = None,
-    ) -> Dict[str, AddModelResult]:
-        """Import a list of paths, repo_ids or URLs. Returns the set of
-        successfully imported items.
-        :param items_to_import: Set of strings corresponding to models to be imported.
-        :param prediction_type_helper: A callback that receives the Path of a Stable Diffusion 2 checkpoint model and returns a SchedulerPredictionType.
-
-        The prediction type helper is necessary to distinguish between
-        models based on Stable Diffusion 2 Base (requiring
-        SchedulerPredictionType.Epsilson) and Stable Diffusion 768
-        (requiring SchedulerPredictionType.VPrediction). It is
-        generally impossible to do this programmatically, so the
-        prediction_type_helper usually asks the user to choose.
-
-        The result is a set of successfully installed models. Each element
-        of the set is a dict corresponding to the newly-created OmegaConf stanza for
-        that model.
-
-        May return the following exceptions:
-        - ModelNotFoundException   - one or more of the items to import is not a valid path, repo_id or URL
-        - ValueError - a corresponding model already exists
-        """
-        # avoid circular import here
-        from invokeai.backend.install.model_install_backend import ModelInstall
-
-        successfully_installed = {}
-
-        installer = ModelInstall(
-            config=self.app_config, prediction_type_helper=prediction_type_helper, model_manager=self
-        )
-        for thing in items_to_import:
-            installed = installer.heuristic_import(thing)
-            successfully_installed.update(installed)
-        self.commit()
-        return successfully_installed
diff --git a/invokeai/backend/model_management_OLD/model_merge.py b/invokeai/backend/model_management_OLD/model_merge.py
deleted file mode 100644
index a9f0a23618..0000000000
--- a/invokeai/backend/model_management_OLD/model_merge.py
+++ /dev/null
@@ -1,140 +0,0 @@
-"""
-invokeai.backend.model_management.model_merge exports:
-merge_diffusion_models() -- combine multiple models by location and return a pipeline object
-merge_diffusion_models_and_commit() -- combine multiple models by ModelManager ID and write to models.yaml
-
-Copyright (c) 2023 Lincoln Stein and the InvokeAI Development Team
-"""
-
-import warnings
-from enum import Enum
-from pathlib import Path
-from typing import List, Optional, Union
-
-from diffusers import DiffusionPipeline
-from diffusers import logging as dlogging
-
-import invokeai.backend.util.logging as logger
-
-from ...backend.model_management import AddModelResult, BaseModelType, ModelManager, ModelType, ModelVariantType
-
-
-class MergeInterpolationMethod(str, Enum):
-    WeightedSum = "weighted_sum"
-    Sigmoid = "sigmoid"
-    InvSigmoid = "inv_sigmoid"
-    AddDifference = "add_difference"
-
-
-class ModelMerger(object):
-    def __init__(self, manager: ModelManager):
-        self.manager = manager
-
-    def merge_diffusion_models(
-        self,
-        model_paths: List[Path],
-        alpha: float = 0.5,
-        interp: Optional[MergeInterpolationMethod] = None,
-        force: bool = False,
-        **kwargs,
-    ) -> DiffusionPipeline:
-        """
-        :param model_paths:  up to three models, designated by their local paths or HuggingFace repo_ids
-        :param alpha: The interpolation parameter. Ranges from 0 to 1.  It affects the ratio in which the checkpoints are merged. A 0.8 alpha
-                   would mean that the first model checkpoints would affect the final result far less than an alpha of 0.2
-        :param interp: The interpolation method to use for the merging. Supports "sigmoid", "inv_sigmoid", "add_difference" and None.
-                   Passing None uses the default interpolation which is weighted sum interpolation. For merging three checkpoints, only "add_difference" is supported.
-        :param force:  Whether to ignore mismatch in model_config.json for the current models. Defaults to False.
-
-        **kwargs - the default DiffusionPipeline.get_config_dict kwargs:
-             cache_dir, resume_download, force_download, proxies, local_files_only, use_auth_token, revision, torch_dtype, device_map
-        """
-        with warnings.catch_warnings():
-            warnings.simplefilter("ignore")
-            verbosity = dlogging.get_verbosity()
-            dlogging.set_verbosity_error()
-
-            pipe = DiffusionPipeline.from_pretrained(
-                model_paths[0],
-                custom_pipeline="checkpoint_merger",
-            )
-            merged_pipe = pipe.merge(
-                pretrained_model_name_or_path_list=model_paths,
-                alpha=alpha,
-                interp=interp.value if interp else None,  # diffusers API treats None as "weighted sum"
-                force=force,
-                **kwargs,
-            )
-            dlogging.set_verbosity(verbosity)
-        return merged_pipe
-
-    def merge_diffusion_models_and_save(
-        self,
-        model_names: List[str],
-        base_model: Union[BaseModelType, str],
-        merged_model_name: str,
-        alpha: float = 0.5,
-        interp: Optional[MergeInterpolationMethod] = None,
-        force: bool = False,
-        merge_dest_directory: Optional[Path] = None,
-        **kwargs,
-    ) -> AddModelResult:
-        """
-        :param models: up to three models, designated by their InvokeAI models.yaml model name
-        :param base_model: base model (must be the same for all merged models!)
-        :param merged_model_name: name for new model
-        :param alpha: The interpolation parameter. Ranges from 0 to 1.  It affects the ratio in which the checkpoints are merged. A 0.8 alpha
-                   would mean that the first model checkpoints would affect the final result far less than an alpha of 0.2
-        :param interp: The interpolation method to use for the merging. Supports "weighted_average", "sigmoid", "inv_sigmoid", "add_difference" and None.
-                   Passing None uses the default interpolation which is weighted sum interpolation. For merging three checkpoints, only "add_difference" is supported. Add_difference is A+(B-C).
-        :param force:  Whether to ignore mismatch in model_config.json for the current models. Defaults to False.
-        :param merge_dest_directory: Save the merged model to the designated directory (with 'merged_model_name' appended)
-        **kwargs - the default DiffusionPipeline.get_config_dict kwargs:
-             cache_dir, resume_download, force_download, proxies, local_files_only, use_auth_token, revision, torch_dtype, device_map
-        """
-        model_paths = []
-        config = self.manager.app_config
-        base_model = BaseModelType(base_model)
-        vae = None
-
-        for mod in model_names:
-            info = self.manager.list_model(mod, base_model=base_model, model_type=ModelType.Main)
-            assert info, f"model {mod}, base_model {base_model}, is unknown"
-            assert (
-                info["model_format"] == "diffusers"
-            ), f"{mod} is not a diffusers model. It must be optimized before merging"
-            assert info["variant"] == "normal", f"{mod} is a {info['variant']} model, which cannot currently be merged"
-            assert (
-                len(model_names) <= 2 or interp == MergeInterpolationMethod.AddDifference
-            ), "When merging three models, only the 'add_difference' merge method is supported"
-            # pick up the first model's vae
-            if mod == model_names[0]:
-                vae = info.get("vae")
-            model_paths.extend([(config.root_path / info["path"]).as_posix()])
-
-        merge_method = None if interp == "weighted_sum" else MergeInterpolationMethod(interp)
-        logger.debug(f"interp = {interp}, merge_method={merge_method}")
-        merged_pipe = self.merge_diffusion_models(model_paths, alpha, merge_method, force, **kwargs)
-        dump_path = (
-            Path(merge_dest_directory)
-            if merge_dest_directory
-            else config.models_path / base_model.value / ModelType.Main.value
-        )
-        dump_path.mkdir(parents=True, exist_ok=True)
-        dump_path = (dump_path / merged_model_name).as_posix()
-
-        merged_pipe.save_pretrained(dump_path, safe_serialization=True)
-        attributes = {
-            "path": dump_path,
-            "description": f"Merge of models {', '.join(model_names)}",
-            "model_format": "diffusers",
-            "variant": ModelVariantType.Normal.value,
-            "vae": vae,
-        }
-        return self.manager.add_model(
-            merged_model_name,
-            base_model=base_model,
-            model_type=ModelType.Main,
-            model_attributes=attributes,
-            clobber=True,
-        )
diff --git a/invokeai/backend/model_management_OLD/model_probe.py b/invokeai/backend/model_management_OLD/model_probe.py
deleted file mode 100644
index 74b1b72d31..0000000000
--- a/invokeai/backend/model_management_OLD/model_probe.py
+++ /dev/null
@@ -1,664 +0,0 @@
-import json
-import re
-from dataclasses import dataclass
-from pathlib import Path
-from typing import Callable, Dict, Literal, Optional, Union
-
-import safetensors.torch
-import torch
-from diffusers import ConfigMixin, ModelMixin
-from picklescan.scanner import scan_file_path
-
-from invokeai.backend.model_management.models.ip_adapter import IPAdapterModelFormat
-
-from .models import (
-    BaseModelType,
-    InvalidModelException,
-    ModelType,
-    ModelVariantType,
-    SchedulerPredictionType,
-    SilenceWarnings,
-)
-from .models.base import read_checkpoint_meta
-from .util import lora_token_vector_length
-
-
-@dataclass
-class ModelProbeInfo(object):
-    model_type: ModelType
-    base_type: BaseModelType
-    variant_type: ModelVariantType
-    prediction_type: SchedulerPredictionType
-    upcast_attention: bool
-    format: Literal["diffusers", "checkpoint", "lycoris", "olive", "onnx"]
-    image_size: int
-    name: Optional[str] = None
-    description: Optional[str] = None
-
-
-class ProbeBase(object):
-    """forward declaration"""
-
-    pass
-
-
-class ModelProbe(object):
-    PROBES = {
-        "diffusers": {},
-        "checkpoint": {},
-        "onnx": {},
-    }
-
-    CLASS2TYPE = {
-        "StableDiffusionPipeline": ModelType.Main,
-        "StableDiffusionInpaintPipeline": ModelType.Main,
-        "StableDiffusionXLPipeline": ModelType.Main,
-        "StableDiffusionXLImg2ImgPipeline": ModelType.Main,
-        "StableDiffusionXLInpaintPipeline": ModelType.Main,
-        "LatentConsistencyModelPipeline": ModelType.Main,
-        "AutoencoderKL": ModelType.Vae,
-        "AutoencoderTiny": ModelType.Vae,
-        "ControlNetModel": ModelType.ControlNet,
-        "CLIPVisionModelWithProjection": ModelType.CLIPVision,
-        "T2IAdapter": ModelType.T2IAdapter,
-    }
-
-    @classmethod
-    def register_probe(
-        cls, format: Literal["diffusers", "checkpoint", "onnx"], model_type: ModelType, probe_class: ProbeBase
-    ):
-        cls.PROBES[format][model_type] = probe_class
-
-    @classmethod
-    def heuristic_probe(
-        cls,
-        model: Union[Dict, ModelMixin, Path],
-        prediction_type_helper: Callable[[Path], SchedulerPredictionType] = None,
-    ) -> ModelProbeInfo:
-        if isinstance(model, Path):
-            return cls.probe(model_path=model, prediction_type_helper=prediction_type_helper)
-        elif isinstance(model, (dict, ModelMixin, ConfigMixin)):
-            return cls.probe(model_path=None, model=model, prediction_type_helper=prediction_type_helper)
-        else:
-            raise InvalidModelException("model parameter {model} is neither a Path, nor a model")
-
-    @classmethod
-    def probe(
-        cls,
-        model_path: Path,
-        model: Optional[Union[Dict, ModelMixin]] = None,
-        prediction_type_helper: Optional[Callable[[Path], SchedulerPredictionType]] = None,
-    ) -> ModelProbeInfo:
-        """
-        Probe the model at model_path and return sufficient information about it
-        to place it somewhere in the models directory hierarchy. If the model is
-        already loaded into memory, you may provide it as model in order to avoid
-        opening it a second time. The prediction_type_helper callable is a function that receives
-        the path to the model and returns the SchedulerPredictionType.
-        """
-        if model_path:
-            format_type = "diffusers" if model_path.is_dir() else "checkpoint"
-        else:
-            format_type = "diffusers" if isinstance(model, (ConfigMixin, ModelMixin)) else "checkpoint"
-        model_info = None
-        try:
-            model_type = (
-                cls.get_model_type_from_folder(model_path, model)
-                if format_type == "diffusers"
-                else cls.get_model_type_from_checkpoint(model_path, model)
-            )
-            format_type = "onnx" if model_type == ModelType.ONNX else format_type
-            probe_class = cls.PROBES[format_type].get(model_type)
-            if not probe_class:
-                return None
-            probe = probe_class(model_path, model, prediction_type_helper)
-            base_type = probe.get_base_type()
-            variant_type = probe.get_variant_type()
-            prediction_type = probe.get_scheduler_prediction_type()
-            name = cls.get_model_name(model_path)
-            description = f"{base_type.value} {model_type.value} model {name}"
-            format = probe.get_format()
-            model_info = ModelProbeInfo(
-                model_type=model_type,
-                base_type=base_type,
-                variant_type=variant_type,
-                prediction_type=prediction_type,
-                name=name,
-                description=description,
-                upcast_attention=(
-                    base_type == BaseModelType.StableDiffusion2
-                    and prediction_type == SchedulerPredictionType.VPrediction
-                ),
-                format=format,
-                image_size=(
-                    1024
-                    if (base_type in {BaseModelType.StableDiffusionXL, BaseModelType.StableDiffusionXLRefiner})
-                    else (
-                        768
-                        if (
-                            base_type == BaseModelType.StableDiffusion2
-                            and prediction_type == SchedulerPredictionType.VPrediction
-                        )
-                        else 512
-                    )
-                ),
-            )
-        except Exception:
-            raise
-
-        return model_info
-
-    @classmethod
-    def get_model_name(cls, model_path: Path) -> str:
-        if model_path.suffix in {".safetensors", ".bin", ".pt", ".ckpt"}:
-            return model_path.stem
-        else:
-            return model_path.name
-
-    @classmethod
-    def get_model_type_from_checkpoint(cls, model_path: Path, checkpoint: dict) -> ModelType:
-        if model_path.suffix not in (".bin", ".pt", ".ckpt", ".safetensors", ".pth"):
-            return None
-
-        if model_path.name == "learned_embeds.bin":
-            return ModelType.TextualInversion
-
-        ckpt = checkpoint if checkpoint else read_checkpoint_meta(model_path, scan=True)
-        ckpt = ckpt.get("state_dict", ckpt)
-
-        for key in ckpt.keys():
-            if any(key.startswith(v) for v in {"cond_stage_model.", "first_stage_model.", "model.diffusion_model."}):
-                return ModelType.Main
-            elif any(key.startswith(v) for v in {"encoder.conv_in", "decoder.conv_in"}):
-                return ModelType.Vae
-            elif any(key.startswith(v) for v in {"lora_te_", "lora_unet_"}):
-                return ModelType.Lora
-            elif any(key.endswith(v) for v in {"to_k_lora.up.weight", "to_q_lora.down.weight"}):
-                return ModelType.Lora
-            elif any(key.startswith(v) for v in {"control_model", "input_blocks"}):
-                return ModelType.ControlNet
-            elif key in {"emb_params", "string_to_param"}:
-                return ModelType.TextualInversion
-
-        else:
-            # diffusers-ti
-            if len(ckpt) < 10 and all(isinstance(v, torch.Tensor) for v in ckpt.values()):
-                return ModelType.TextualInversion
-
-        raise InvalidModelException(f"Unable to determine model type for {model_path}")
-
-    @classmethod
-    def get_model_type_from_folder(cls, folder_path: Path, model: ModelMixin) -> ModelType:
-        """
-        Get the model type of a hugging-face style folder.
-        """
-        class_name = None
-        error_hint = None
-        if model:
-            class_name = model.__class__.__name__
-        else:
-            for suffix in ["bin", "safetensors"]:
-                if (folder_path / f"learned_embeds.{suffix}").exists():
-                    return ModelType.TextualInversion
-                if (folder_path / f"pytorch_lora_weights.{suffix}").exists():
-                    return ModelType.Lora
-            if (folder_path / "unet/model.onnx").exists():
-                return ModelType.ONNX
-            if (folder_path / "image_encoder.txt").exists():
-                return ModelType.IPAdapter
-
-            i = folder_path / "model_index.json"
-            c = folder_path / "config.json"
-            config_path = i if i.exists() else c if c.exists() else None
-
-            if config_path:
-                with open(config_path, "r") as file:
-                    conf = json.load(file)
-                if "_class_name" in conf:
-                    class_name = conf["_class_name"]
-                elif "architectures" in conf:
-                    class_name = conf["architectures"][0]
-                else:
-                    class_name = None
-            else:
-                error_hint = f"No model_index.json or config.json found in {folder_path}."
-
-        if class_name and (type := cls.CLASS2TYPE.get(class_name)):
-            return type
-        else:
-            error_hint = f"class {class_name} is not one of the supported classes [{', '.join(cls.CLASS2TYPE.keys())}]"
-
-        # give up
-        raise InvalidModelException(
-            f"Unable to determine model type for {folder_path}" + (f"; {error_hint}" if error_hint else "")
-        )
-
-    @classmethod
-    def _scan_and_load_checkpoint(cls, model_path: Path) -> dict:
-        with SilenceWarnings():
-            if model_path.suffix.endswith((".ckpt", ".pt", ".bin")):
-                cls._scan_model(model_path, model_path)
-                return torch.load(model_path, map_location="cpu")
-            else:
-                return safetensors.torch.load_file(model_path)
-
-    @classmethod
-    def _scan_model(cls, model_name, checkpoint):
-        """
-        Apply picklescanner to the indicated checkpoint and issue a warning
-        and option to exit if an infected file is identified.
-        """
-        # scan model
-        scan_result = scan_file_path(checkpoint)
-        if scan_result.infected_files != 0:
-            raise Exception("The model {model_name} is potentially infected by malware. Aborting import.")
-
-
-# ##################################################3
-# Checkpoint probing
-# ##################################################3
-class ProbeBase(object):
-    def get_base_type(self) -> BaseModelType:
-        pass
-
-    def get_variant_type(self) -> ModelVariantType:
-        pass
-
-    def get_scheduler_prediction_type(self) -> SchedulerPredictionType:
-        pass
-
-    def get_format(self) -> str:
-        pass
-
-
-class CheckpointProbeBase(ProbeBase):
-    def __init__(
-        self, checkpoint_path: Path, checkpoint: dict, helper: Callable[[Path], SchedulerPredictionType] = None
-    ) -> BaseModelType:
-        self.checkpoint = checkpoint or ModelProbe._scan_and_load_checkpoint(checkpoint_path)
-        self.checkpoint_path = checkpoint_path
-        self.helper = helper
-
-    def get_base_type(self) -> BaseModelType:
-        pass
-
-    def get_format(self) -> str:
-        return "checkpoint"
-
-    def get_variant_type(self) -> ModelVariantType:
-        model_type = ModelProbe.get_model_type_from_checkpoint(self.checkpoint_path, self.checkpoint)
-        if model_type != ModelType.Main:
-            return ModelVariantType.Normal
-        state_dict = self.checkpoint.get("state_dict") or self.checkpoint
-        in_channels = state_dict["model.diffusion_model.input_blocks.0.0.weight"].shape[1]
-        if in_channels == 9:
-            return ModelVariantType.Inpaint
-        elif in_channels == 5:
-            return ModelVariantType.Depth
-        elif in_channels == 4:
-            return ModelVariantType.Normal
-        else:
-            raise InvalidModelException(
-                f"Cannot determine variant type (in_channels={in_channels}) at {self.checkpoint_path}"
-            )
-
-
-class PipelineCheckpointProbe(CheckpointProbeBase):
-    def get_base_type(self) -> BaseModelType:
-        checkpoint = self.checkpoint
-        state_dict = self.checkpoint.get("state_dict") or checkpoint
-        key_name = "model.diffusion_model.input_blocks.2.1.transformer_blocks.0.attn2.to_k.weight"
-        if key_name in state_dict and state_dict[key_name].shape[-1] == 768:
-            return BaseModelType.StableDiffusion1
-        if key_name in state_dict and state_dict[key_name].shape[-1] == 1024:
-            return BaseModelType.StableDiffusion2
-        key_name = "model.diffusion_model.input_blocks.4.1.transformer_blocks.0.attn2.to_k.weight"
-        if key_name in state_dict and state_dict[key_name].shape[-1] == 2048:
-            return BaseModelType.StableDiffusionXL
-        elif key_name in state_dict and state_dict[key_name].shape[-1] == 1280:
-            return BaseModelType.StableDiffusionXLRefiner
-        else:
-            raise InvalidModelException("Cannot determine base type")
-
-    def get_scheduler_prediction_type(self) -> Optional[SchedulerPredictionType]:
-        """Return model prediction type."""
-        # if there is a .yaml associated with this checkpoint, then we do not need
-        # to probe for the prediction type as it will be ignored.
-        if self.checkpoint_path and self.checkpoint_path.with_suffix(".yaml").exists():
-            return None
-
-        type = self.get_base_type()
-        if type == BaseModelType.StableDiffusion2:
-            checkpoint = self.checkpoint
-            state_dict = self.checkpoint.get("state_dict") or checkpoint
-            key_name = "model.diffusion_model.input_blocks.2.1.transformer_blocks.0.attn2.to_k.weight"
-            if key_name in state_dict and state_dict[key_name].shape[-1] == 1024:
-                if "global_step" in checkpoint:
-                    if checkpoint["global_step"] == 220000:
-                        return SchedulerPredictionType.Epsilon
-                    elif checkpoint["global_step"] == 110000:
-                        return SchedulerPredictionType.VPrediction
-            if self.helper and self.checkpoint_path:
-                if helper_guess := self.helper(self.checkpoint_path):
-                    return helper_guess
-            return SchedulerPredictionType.VPrediction  # a guess for sd2 ckpts
-
-        elif type == BaseModelType.StableDiffusion1:
-            if self.helper and self.checkpoint_path:
-                if helper_guess := self.helper(self.checkpoint_path):
-                    return helper_guess
-            return SchedulerPredictionType.Epsilon  # a reasonable guess for sd1 ckpts
-        else:
-            return None
-
-
-class VaeCheckpointProbe(CheckpointProbeBase):
-    def get_base_type(self) -> BaseModelType:
-        # I can't find any standalone 2.X VAEs to test with!
-        return BaseModelType.StableDiffusion1
-
-
-class LoRACheckpointProbe(CheckpointProbeBase):
-    def get_format(self) -> str:
-        return "lycoris"
-
-    def get_base_type(self) -> BaseModelType:
-        checkpoint = self.checkpoint
-        token_vector_length = lora_token_vector_length(checkpoint)
-
-        if token_vector_length == 768:
-            return BaseModelType.StableDiffusion1
-        elif token_vector_length == 1024:
-            return BaseModelType.StableDiffusion2
-        elif token_vector_length == 1280:
-            return BaseModelType.StableDiffusionXL  # recognizes format at https://civitai.com/models/224641
-        elif token_vector_length == 2048:
-            return BaseModelType.StableDiffusionXL
-        else:
-            raise InvalidModelException(f"Unknown LoRA type: {self.checkpoint_path}")
-
-
-class TextualInversionCheckpointProbe(CheckpointProbeBase):
-    def get_format(self) -> str:
-        return None
-
-    def get_base_type(self) -> BaseModelType:
-        checkpoint = self.checkpoint
-        if "string_to_token" in checkpoint:
-            token_dim = list(checkpoint["string_to_param"].values())[0].shape[-1]
-        elif "emb_params" in checkpoint:
-            token_dim = checkpoint["emb_params"].shape[-1]
-        elif "clip_g" in checkpoint:
-            token_dim = checkpoint["clip_g"].shape[-1]
-        else:
-            token_dim = list(checkpoint.values())[0].shape[-1]
-        if token_dim == 768:
-            return BaseModelType.StableDiffusion1
-        elif token_dim == 1024:
-            return BaseModelType.StableDiffusion2
-        elif token_dim == 1280:
-            return BaseModelType.StableDiffusionXL
-        else:
-            return None
-
-
-class ControlNetCheckpointProbe(CheckpointProbeBase):
-    def get_base_type(self) -> BaseModelType:
-        checkpoint = self.checkpoint
-        for key_name in (
-            "control_model.input_blocks.2.1.transformer_blocks.0.attn2.to_k.weight",
-            "input_blocks.2.1.transformer_blocks.0.attn2.to_k.weight",
-        ):
-            if key_name not in checkpoint:
-                continue
-            if checkpoint[key_name].shape[-1] == 768:
-                return BaseModelType.StableDiffusion1
-            elif checkpoint[key_name].shape[-1] == 1024:
-                return BaseModelType.StableDiffusion2
-            elif self.checkpoint_path and self.helper:
-                return self.helper(self.checkpoint_path)
-        raise InvalidModelException("Unable to determine base type for {self.checkpoint_path}")
-
-
-class IPAdapterCheckpointProbe(CheckpointProbeBase):
-    def get_base_type(self) -> BaseModelType:
-        raise NotImplementedError()
-
-
-class CLIPVisionCheckpointProbe(CheckpointProbeBase):
-    def get_base_type(self) -> BaseModelType:
-        raise NotImplementedError()
-
-
-class T2IAdapterCheckpointProbe(CheckpointProbeBase):
-    def get_base_type(self) -> BaseModelType:
-        raise NotImplementedError()
-
-
-########################################################
-# classes for probing folders
-#######################################################
-class FolderProbeBase(ProbeBase):
-    def __init__(self, folder_path: Path, model: ModelMixin = None, helper: Callable = None):  # not used
-        self.model = model
-        self.folder_path = folder_path
-
-    def get_variant_type(self) -> ModelVariantType:
-        return ModelVariantType.Normal
-
-    def get_format(self) -> str:
-        return "diffusers"
-
-
-class PipelineFolderProbe(FolderProbeBase):
-    def get_base_type(self) -> BaseModelType:
-        if self.model:
-            unet_conf = self.model.unet.config
-        else:
-            with open(self.folder_path / "unet" / "config.json", "r") as file:
-                unet_conf = json.load(file)
-        if unet_conf["cross_attention_dim"] == 768:
-            return BaseModelType.StableDiffusion1
-        elif unet_conf["cross_attention_dim"] == 1024:
-            return BaseModelType.StableDiffusion2
-        elif unet_conf["cross_attention_dim"] == 1280:
-            return BaseModelType.StableDiffusionXLRefiner
-        elif unet_conf["cross_attention_dim"] == 2048:
-            return BaseModelType.StableDiffusionXL
-        else:
-            raise InvalidModelException(f"Unknown base model for {self.folder_path}")
-
-    def get_scheduler_prediction_type(self) -> SchedulerPredictionType:
-        if self.model:
-            scheduler_conf = self.model.scheduler.config
-        else:
-            with open(self.folder_path / "scheduler" / "scheduler_config.json", "r") as file:
-                scheduler_conf = json.load(file)
-        if scheduler_conf["prediction_type"] == "v_prediction":
-            return SchedulerPredictionType.VPrediction
-        elif scheduler_conf["prediction_type"] == "epsilon":
-            return SchedulerPredictionType.Epsilon
-        else:
-            return None
-
-    def get_variant_type(self) -> ModelVariantType:
-        # This only works for pipelines! Any kind of
-        # exception results in our returning the
-        # "normal" variant type
-        try:
-            if self.model:
-                conf = self.model.unet.config
-            else:
-                config_file = self.folder_path / "unet" / "config.json"
-                with open(config_file, "r") as file:
-                    conf = json.load(file)
-
-            in_channels = conf["in_channels"]
-            if in_channels == 9:
-                return ModelVariantType.Inpaint
-            elif in_channels == 5:
-                return ModelVariantType.Depth
-            elif in_channels == 4:
-                return ModelVariantType.Normal
-        except Exception:
-            pass
-        return ModelVariantType.Normal
-
-
-class VaeFolderProbe(FolderProbeBase):
-    def get_base_type(self) -> BaseModelType:
-        if self._config_looks_like_sdxl():
-            return BaseModelType.StableDiffusionXL
-        elif self._name_looks_like_sdxl():
-            # but SD and SDXL VAE are the same shape (3-channel RGB to 4-channel float scaled down
-            # by a factor of 8), we can't necessarily tell them apart by config hyperparameters.
-            return BaseModelType.StableDiffusionXL
-        else:
-            return BaseModelType.StableDiffusion1
-
-    def _config_looks_like_sdxl(self) -> bool:
-        # config values that distinguish Stability's SD 1.x VAE from their SDXL VAE.
-        config_file = self.folder_path / "config.json"
-        if not config_file.exists():
-            raise InvalidModelException(f"Cannot determine base type for {self.folder_path}")
-        with open(config_file, "r") as file:
-            config = json.load(file)
-        return config.get("scaling_factor", 0) == 0.13025 and config.get("sample_size") in [512, 1024]
-
-    def _name_looks_like_sdxl(self) -> bool:
-        return bool(re.search(r"xl\b", self._guess_name(), re.IGNORECASE))
-
-    def _guess_name(self) -> str:
-        name = self.folder_path.name
-        if name == "vae":
-            name = self.folder_path.parent.name
-        return name
-
-
-class TextualInversionFolderProbe(FolderProbeBase):
-    def get_format(self) -> str:
-        return None
-
-    def get_base_type(self) -> BaseModelType:
-        path = self.folder_path / "learned_embeds.bin"
-        if not path.exists():
-            return None
-        checkpoint = ModelProbe._scan_and_load_checkpoint(path)
-        return TextualInversionCheckpointProbe(None, checkpoint=checkpoint).get_base_type()
-
-
-class ONNXFolderProbe(FolderProbeBase):
-    def get_format(self) -> str:
-        return "onnx"
-
-    def get_base_type(self) -> BaseModelType:
-        return BaseModelType.StableDiffusion1
-
-    def get_variant_type(self) -> ModelVariantType:
-        return ModelVariantType.Normal
-
-
-class ControlNetFolderProbe(FolderProbeBase):
-    def get_base_type(self) -> BaseModelType:
-        config_file = self.folder_path / "config.json"
-        if not config_file.exists():
-            raise InvalidModelException(f"Cannot determine base type for {self.folder_path}")
-        with open(config_file, "r") as file:
-            config = json.load(file)
-        # no obvious way to distinguish between sd2-base and sd2-768
-        dimension = config["cross_attention_dim"]
-        base_model = (
-            BaseModelType.StableDiffusion1
-            if dimension == 768
-            else (
-                BaseModelType.StableDiffusion2
-                if dimension == 1024
-                else BaseModelType.StableDiffusionXL
-                if dimension == 2048
-                else None
-            )
-        )
-        if not base_model:
-            raise InvalidModelException(f"Unable to determine model base for {self.folder_path}")
-        return base_model
-
-
-class LoRAFolderProbe(FolderProbeBase):
-    def get_base_type(self) -> BaseModelType:
-        model_file = None
-        for suffix in ["safetensors", "bin"]:
-            base_file = self.folder_path / f"pytorch_lora_weights.{suffix}"
-            if base_file.exists():
-                model_file = base_file
-                break
-        if not model_file:
-            raise InvalidModelException("Unknown LoRA format encountered")
-        return LoRACheckpointProbe(model_file, None).get_base_type()
-
-
-class IPAdapterFolderProbe(FolderProbeBase):
-    def get_format(self) -> str:
-        return IPAdapterModelFormat.InvokeAI.value
-
-    def get_base_type(self) -> BaseModelType:
-        model_file = self.folder_path / "ip_adapter.bin"
-        if not model_file.exists():
-            raise InvalidModelException("Unknown IP-Adapter model format.")
-
-        state_dict = torch.load(model_file, map_location="cpu")
-        cross_attention_dim = state_dict["ip_adapter"]["1.to_k_ip.weight"].shape[-1]
-        if cross_attention_dim == 768:
-            return BaseModelType.StableDiffusion1
-        elif cross_attention_dim == 1024:
-            return BaseModelType.StableDiffusion2
-        elif cross_attention_dim == 2048:
-            return BaseModelType.StableDiffusionXL
-        else:
-            raise InvalidModelException(f"IP-Adapter had unexpected cross-attention dimension: {cross_attention_dim}.")
-
-
-class CLIPVisionFolderProbe(FolderProbeBase):
-    def get_base_type(self) -> BaseModelType:
-        return BaseModelType.Any
-
-
-class T2IAdapterFolderProbe(FolderProbeBase):
-    def get_base_type(self) -> BaseModelType:
-        config_file = self.folder_path / "config.json"
-        if not config_file.exists():
-            raise InvalidModelException(f"Cannot determine base type for {self.folder_path}")
-        with open(config_file, "r") as file:
-            config = json.load(file)
-
-        adapter_type = config.get("adapter_type", None)
-        if adapter_type == "full_adapter_xl":
-            return BaseModelType.StableDiffusionXL
-        elif adapter_type == "full_adapter" or "light_adapter":
-            # I haven't seen any T2I adapter models for SD2, so assume that this is an SD1 adapter.
-            return BaseModelType.StableDiffusion1
-        else:
-            raise InvalidModelException(
-                f"Unable to determine base model for '{self.folder_path}' (adapter_type = {adapter_type})."
-            )
-
-
-############## register probe classes ######
-ModelProbe.register_probe("diffusers", ModelType.Main, PipelineFolderProbe)
-ModelProbe.register_probe("diffusers", ModelType.Vae, VaeFolderProbe)
-ModelProbe.register_probe("diffusers", ModelType.Lora, LoRAFolderProbe)
-ModelProbe.register_probe("diffusers", ModelType.TextualInversion, TextualInversionFolderProbe)
-ModelProbe.register_probe("diffusers", ModelType.ControlNet, ControlNetFolderProbe)
-ModelProbe.register_probe("diffusers", ModelType.IPAdapter, IPAdapterFolderProbe)
-ModelProbe.register_probe("diffusers", ModelType.CLIPVision, CLIPVisionFolderProbe)
-ModelProbe.register_probe("diffusers", ModelType.T2IAdapter, T2IAdapterFolderProbe)
-
-ModelProbe.register_probe("checkpoint", ModelType.Main, PipelineCheckpointProbe)
-ModelProbe.register_probe("checkpoint", ModelType.Vae, VaeCheckpointProbe)
-ModelProbe.register_probe("checkpoint", ModelType.Lora, LoRACheckpointProbe)
-ModelProbe.register_probe("checkpoint", ModelType.TextualInversion, TextualInversionCheckpointProbe)
-ModelProbe.register_probe("checkpoint", ModelType.ControlNet, ControlNetCheckpointProbe)
-ModelProbe.register_probe("checkpoint", ModelType.IPAdapter, IPAdapterCheckpointProbe)
-ModelProbe.register_probe("checkpoint", ModelType.CLIPVision, CLIPVisionCheckpointProbe)
-ModelProbe.register_probe("checkpoint", ModelType.T2IAdapter, T2IAdapterCheckpointProbe)
-
-ModelProbe.register_probe("onnx", ModelType.ONNX, ONNXFolderProbe)
diff --git a/invokeai/backend/model_management_OLD/model_search.py b/invokeai/backend/model_management_OLD/model_search.py
deleted file mode 100644
index e125c3ced7..0000000000
--- a/invokeai/backend/model_management_OLD/model_search.py
+++ /dev/null
@@ -1,112 +0,0 @@
-# Copyright 2023, Lincoln D. Stein and the InvokeAI Team
-"""
-Abstract base class for recursive directory search for models.
-"""
-
-import os
-from abc import ABC, abstractmethod
-from pathlib import Path
-from typing import List, Set, types
-
-import invokeai.backend.util.logging as logger
-
-
-class ModelSearch(ABC):
-    def __init__(self, directories: List[Path], logger: types.ModuleType = logger):
-        """
-        Initialize a recursive model directory search.
-        :param directories: List of directory Paths to recurse through
-        :param logger: Logger to use
-        """
-        self.directories = directories
-        self.logger = logger
-        self._items_scanned = 0
-        self._models_found = 0
-        self._scanned_dirs = set()
-        self._scanned_paths = set()
-        self._pruned_paths = set()
-
-    @abstractmethod
-    def on_search_started(self):
-        """
-        Called before the scan starts.
-        """
-        pass
-
-    @abstractmethod
-    def on_model_found(self, model: Path):
-        """
-        Process a found model. Raise an exception if something goes wrong.
-        :param model: Model to process - could be a directory or checkpoint.
-        """
-        pass
-
-    @abstractmethod
-    def on_search_completed(self):
-        """
-        Perform some activity when the scan is completed. May use instance
-        variables, items_scanned and models_found
-        """
-        pass
-
-    def search(self):
-        self.on_search_started()
-        for dir in self.directories:
-            self.walk_directory(dir)
-        self.on_search_completed()
-
-    def walk_directory(self, path: Path):
-        for root, dirs, files in os.walk(path, followlinks=True):
-            if str(Path(root).name).startswith("."):
-                self._pruned_paths.add(root)
-            if any(Path(root).is_relative_to(x) for x in self._pruned_paths):
-                continue
-
-            self._items_scanned += len(dirs) + len(files)
-            for d in dirs:
-                path = Path(root) / d
-                if path in self._scanned_paths or path.parent in self._scanned_dirs:
-                    self._scanned_dirs.add(path)
-                    continue
-                if any(
-                    (path / x).exists()
-                    for x in {
-                        "config.json",
-                        "model_index.json",
-                        "learned_embeds.bin",
-                        "pytorch_lora_weights.bin",
-                        "image_encoder.txt",
-                    }
-                ):
-                    try:
-                        self.on_model_found(path)
-                        self._models_found += 1
-                        self._scanned_dirs.add(path)
-                    except Exception as e:
-                        self.logger.warning(f"Failed to process '{path}': {e}")
-
-            for f in files:
-                path = Path(root) / f
-                if path.parent in self._scanned_dirs:
-                    continue
-                if path.suffix in {".ckpt", ".bin", ".pth", ".safetensors", ".pt"}:
-                    try:
-                        self.on_model_found(path)
-                        self._models_found += 1
-                    except Exception as e:
-                        self.logger.warning(f"Failed to process '{path}': {e}")
-
-
-class FindModels(ModelSearch):
-    def on_search_started(self):
-        self.models_found: Set[Path] = set()
-
-    def on_model_found(self, model: Path):
-        self.models_found.add(model)
-
-    def on_search_completed(self):
-        pass
-
-    def list_models(self) -> List[Path]:
-        self.search()
-        return list(self.models_found)
diff --git a/invokeai/backend/model_management_OLD/models/__init__.py b/invokeai/backend/model_management_OLD/models/__init__.py
deleted file mode 100644
index 5f9b13b96f..0000000000
--- a/invokeai/backend/model_management_OLD/models/__init__.py
+++ /dev/null
@@ -1,167 +0,0 @@
-import inspect
-from enum import Enum
-from typing import Literal, get_origin
-
-from pydantic import BaseModel, ConfigDict, create_model
-
-from .base import (  # noqa: F401
-    BaseModelType,
-    DuplicateModelException,
-    InvalidModelException,
-    ModelBase,
-    ModelConfigBase,
-    ModelError,
-    ModelNotFoundException,
-    ModelType,
-    ModelVariantType,
-    SchedulerPredictionType,
-    SilenceWarnings,
-    SubModelType,
-)
-from .clip_vision import CLIPVisionModel
-from .controlnet import ControlNetModel  # TODO:
-from .ip_adapter import IPAdapterModel
-from .lora import LoRAModel
-from .sdxl import StableDiffusionXLModel
-from .stable_diffusion import StableDiffusion1Model, StableDiffusion2Model
-from .stable_diffusion_onnx import ONNXStableDiffusion1Model, ONNXStableDiffusion2Model
-from .t2i_adapter import T2IAdapterModel
-from .textual_inversion import TextualInversionModel
-from .vae import VaeModel
-
-MODEL_CLASSES = {
-    BaseModelType.StableDiffusion1: {
-        ModelType.ONNX: ONNXStableDiffusion1Model,
-        ModelType.Main: StableDiffusion1Model,
-        ModelType.Vae: VaeModel,
-        ModelType.Lora: LoRAModel,
-        ModelType.ControlNet: ControlNetModel,
-        ModelType.TextualInversion: TextualInversionModel,
-        ModelType.IPAdapter: IPAdapterModel,
-        ModelType.CLIPVision: CLIPVisionModel,
-        ModelType.T2IAdapter: T2IAdapterModel,
-    },
-    BaseModelType.StableDiffusion2: {
-        ModelType.ONNX: ONNXStableDiffusion2Model,
-        ModelType.Main: StableDiffusion2Model,
-        ModelType.Vae: VaeModel,
-        ModelType.Lora: LoRAModel,
-        ModelType.ControlNet: ControlNetModel,
-        ModelType.TextualInversion: TextualInversionModel,
-        ModelType.IPAdapter: IPAdapterModel,
-        ModelType.CLIPVision: CLIPVisionModel,
-        ModelType.T2IAdapter: T2IAdapterModel,
-    },
-    BaseModelType.StableDiffusionXL: {
-        ModelType.Main: StableDiffusionXLModel,
-        ModelType.Vae: VaeModel,
-        # will not work until support written
-        ModelType.Lora: LoRAModel,
-        ModelType.ControlNet: ControlNetModel,
-        ModelType.TextualInversion: TextualInversionModel,
-        ModelType.ONNX: ONNXStableDiffusion2Model,
-        ModelType.IPAdapter: IPAdapterModel,
-        ModelType.CLIPVision: CLIPVisionModel,
-        ModelType.T2IAdapter: T2IAdapterModel,
-    },
-    BaseModelType.StableDiffusionXLRefiner: {
-        ModelType.Main: StableDiffusionXLModel,
-        ModelType.Vae: VaeModel,
-        # will not work until support written
-        ModelType.Lora: LoRAModel,
-        ModelType.ControlNet: ControlNetModel,
-        ModelType.TextualInversion: TextualInversionModel,
-        ModelType.ONNX: ONNXStableDiffusion2Model,
-        ModelType.IPAdapter: IPAdapterModel,
-        ModelType.CLIPVision: CLIPVisionModel,
-        ModelType.T2IAdapter: T2IAdapterModel,
-    },
-    BaseModelType.Any: {
-        ModelType.CLIPVision: CLIPVisionModel,
-        # The following model types are not expected to be used with BaseModelType.Any.
-        ModelType.ONNX: ONNXStableDiffusion2Model,
-        ModelType.Main: StableDiffusion2Model,
-        ModelType.Vae: VaeModel,
-        ModelType.Lora: LoRAModel,
-        ModelType.ControlNet: ControlNetModel,
-        ModelType.TextualInversion: TextualInversionModel,
-        ModelType.IPAdapter: IPAdapterModel,
-        ModelType.T2IAdapter: T2IAdapterModel,
-    },
-    # BaseModelType.Kandinsky2_1: {
-    #    ModelType.Main: Kandinsky2_1Model,
-    #    ModelType.MoVQ: MoVQModel,
-    #    ModelType.Lora: LoRAModel,
-    #    ModelType.ControlNet: ControlNetModel,
-    #    ModelType.TextualInversion: TextualInversionModel,
-    # },
-}
-
-MODEL_CONFIGS = []
-OPENAPI_MODEL_CONFIGS = []
-
-
-class OpenAPIModelInfoBase(BaseModel):
-    model_name: str
-    base_model: BaseModelType
-    model_type: ModelType
-
-    model_config = ConfigDict(protected_namespaces=())
-
-
-for _base_model, models in MODEL_CLASSES.items():
-    for model_type, model_class in models.items():
-        model_configs = set(model_class._get_configs().values())
-        model_configs.discard(None)
-        MODEL_CONFIGS.extend(model_configs)
-
-        # LS: sort to get the checkpoint configs first, which makes
-        # for a better template in the Swagger docs
-        for cfg in sorted(model_configs, key=lambda x: str(x)):
-            model_name, cfg_name = cfg.__qualname__.split(".")[-2:]
-            openapi_cfg_name = model_name + cfg_name
-            if openapi_cfg_name in vars():
-                continue
-
-            api_wrapper = create_model(
-                openapi_cfg_name,
-                __base__=(cfg, OpenAPIModelInfoBase),
-                model_type=(Literal[model_type], model_type),  # type: ignore
-            )
-            vars()[openapi_cfg_name] = api_wrapper
-            OPENAPI_MODEL_CONFIGS.append(api_wrapper)
-
-
-def get_model_config_enums():
-    enums = []
-
-    for model_config in MODEL_CONFIGS:
-        if hasattr(inspect, "get_annotations"):
-            fields = inspect.get_annotations(model_config)
-        else:
-            fields = model_config.__annotations__
-        try:
-            field = fields["model_format"]
-        except Exception:
-            raise Exception("format field not found")
-
-        # model_format: None
-        # model_format: SomeModelFormat
-        # model_format: Literal[SomeModelFormat.Diffusers]
-        # model_format: Literal[SomeModelFormat.Diffusers, SomeModelFormat.Checkpoint]
-
-        if isinstance(field, type) and issubclass(field, str) and issubclass(field, Enum):
-            enums.append(field)
-
-        elif get_origin(field) is Literal and all(
-            isinstance(arg, str) and isinstance(arg, Enum) for arg in field.__args__
-        ):
-            enums.append(type(field.__args__[0]))
-
-        elif field is None:
-            pass
-
-        else:
-            raise Exception(f"Unsupported format definition in {model_configs.__qualname__}")
-
-    return enums
diff --git a/invokeai/backend/model_management_OLD/models/base.py b/invokeai/backend/model_management_OLD/models/base.py
deleted file mode 100644
index 7807cb9a54..0000000000
--- a/invokeai/backend/model_management_OLD/models/base.py
+++ /dev/null
@@ -1,681 +0,0 @@
-import inspect
-import json
-import os
-import sys
-import typing
-import warnings
-from abc import ABCMeta, abstractmethod
-from contextlib import suppress
-from enum import Enum
-from pathlib import Path
-from typing import Any, Callable, Dict, Generic, List, Literal, Optional, Type, TypeVar, Union
-
-import numpy as np
-import onnx
-import safetensors.torch
-import torch
-from diffusers import ConfigMixin, DiffusionPipeline
-from diffusers import logging as diffusers_logging
-from onnx import numpy_helper
-from onnxruntime import InferenceSession, SessionOptions, get_available_providers
-from picklescan.scanner import scan_file_path
-from pydantic import BaseModel, ConfigDict, Field
-from transformers import logging as transformers_logging
-
-
-class DuplicateModelException(Exception):
-    pass
-
-
-class InvalidModelException(Exception):
-    pass
-
-
-class ModelNotFoundException(Exception):
-    pass
-
-
-class BaseModelType(str, Enum):
-    Any = "any"  # For models that are not associated with any particular base model.
-    StableDiffusion1 = "sd-1"
-    StableDiffusion2 = "sd-2"
-    StableDiffusionXL = "sdxl"
-    StableDiffusionXLRefiner = "sdxl-refiner"
-    # Kandinsky2_1 = "kandinsky-2.1"
-
-
-class ModelType(str, Enum):
-    ONNX = "onnx"
-    Main = "main"
-    Vae = "vae"
-    Lora = "lora"
-    ControlNet = "controlnet"  # used by model_probe
-    TextualInversion = "embedding"
-    IPAdapter = "ip_adapter"
-    CLIPVision = "clip_vision"
-    T2IAdapter = "t2i_adapter"
-
-
-class SubModelType(str, Enum):
-    UNet = "unet"
-    TextEncoder = "text_encoder"
-    TextEncoder2 = "text_encoder_2"
-    Tokenizer = "tokenizer"
-    Tokenizer2 = "tokenizer_2"
-    Vae = "vae"
-    VaeDecoder = "vae_decoder"
-    VaeEncoder = "vae_encoder"
-    Scheduler = "scheduler"
-    SafetyChecker = "safety_checker"
-    # MoVQ = "movq"
-
-
-class ModelVariantType(str, Enum):
-    Normal = "normal"
-    Inpaint = "inpaint"
-    Depth = "depth"
-
-
-class SchedulerPredictionType(str, Enum):
-    Epsilon = "epsilon"
-    VPrediction = "v_prediction"
-    Sample = "sample"
-
-
-class ModelError(str, Enum):
-    NotFound = "not_found"
-
-
-def model_config_json_schema_extra(schema: dict[str, Any]) -> None:
-    if "required" not in schema:
-        schema["required"] = []
-    schema["required"].append("model_type")
-
-
-class ModelConfigBase(BaseModel):
-    path: str  # or Path
-    description: Optional[str] = Field(None)
-    model_format: Optional[str] = Field(None)
-    error: Optional[ModelError] = Field(None)
-
-    model_config = ConfigDict(
-        use_enum_values=True, protected_namespaces=(), json_schema_extra=model_config_json_schema_extra
-    )
-
-
-class EmptyConfigLoader(ConfigMixin):
-    @classmethod
-    def load_config(cls, *args, **kwargs):
-        cls.config_name = kwargs.pop("config_name")
-        return super().load_config(*args, **kwargs)
-
-
-T_co = TypeVar("T_co", covariant=True)
-
-
-class classproperty(Generic[T_co]):
-    def __init__(self, fget: Callable[[Any], T_co]) -> None:
-        self.fget = fget
-
-    def __get__(self, instance: Optional[Any], owner: Type[Any]) -> T_co:
-        return self.fget(owner)
-
-    def __set__(self, instance: Optional[Any], value: Any) -> None:
-        raise AttributeError("cannot set attribute")
-
-
-class ModelBase(metaclass=ABCMeta):
-    # model_path: str
-    # base_model: BaseModelType
-    # model_type: ModelType
-
-    def __init__(
-        self,
-        model_path: str,
-        base_model: BaseModelType,
-        model_type: ModelType,
-    ):
-        self.model_path = model_path
-        self.base_model = base_model
-        self.model_type = model_type
-
-    def _hf_definition_to_type(self, subtypes: List[str]) -> Type:
-        if len(subtypes) < 2:
-            raise Exception("Invalid subfolder definition!")
-        if all(t is None for t in subtypes):
-            return None
-        elif any(t is None for t in subtypes):
-            raise Exception(f"Unsupported definition: {subtypes}")
-
-        if subtypes[0] in ["diffusers", "transformers"]:
-            res_type = sys.modules[subtypes[0]]
-            subtypes = subtypes[1:]
-
-        else:
-            res_type = sys.modules["diffusers"]
-            res_type = res_type.pipelines
-
-        for subtype in subtypes:
-            res_type = getattr(res_type, subtype)
-        return res_type
-
-    @classmethod
-    def _get_configs(cls):
-        with suppress(Exception):
-            return cls.__configs
-
-        configs = {}
-        for name in dir(cls):
-            if name.startswith("__"):
-                continue
-
-            value = getattr(cls, name)
-            if not isinstance(value, type) or not issubclass(value, ModelConfigBase):
-                continue
-
-            if hasattr(inspect, "get_annotations"):
-                fields = inspect.get_annotations(value)
-            else:
-                fields = value.__annotations__
-            try:
-                field = fields["model_format"]
-            except Exception:
-                raise Exception(f"Invalid config definition - format field not found({cls.__qualname__})")
-
-            if isinstance(field, type) and issubclass(field, str) and issubclass(field, Enum):
-                for model_format in field:
-                    configs[model_format.value] = value
-
-            elif typing.get_origin(field) is Literal and all(
-                isinstance(arg, str) and isinstance(arg, Enum) for arg in field.__args__
-            ):
-                for model_format in field.__args__:
-                    configs[model_format.value] = value
-
-            elif field is None:
-                configs[None] = value
-
-            else:
-                raise Exception(f"Unsupported format definition in {cls.__qualname__}")
-
-        cls.__configs = configs
-        return cls.__configs
-
-    @classmethod
-    def create_config(cls, **kwargs) -> ModelConfigBase:
-        if "model_format" not in kwargs:
-            raise Exception("Field 'model_format' not found in model config")
-
-        configs = cls._get_configs()
-        return configs[kwargs["model_format"]](**kwargs)
-
-    @classmethod
-    def probe_config(cls, path: str, **kwargs) -> ModelConfigBase:
-        return cls.create_config(
-            path=path,
-            model_format=cls.detect_format(path),
-        )
-
-    @classmethod
-    @abstractmethod
-    def detect_format(cls, path: str) -> str:
-        raise NotImplementedError()
-
-    @classproperty
-    @abstractmethod
-    def save_to_config(cls) -> bool:
-        raise NotImplementedError()
-
-    @abstractmethod
-    def get_size(self, child_type: Optional[SubModelType] = None) -> int:
-        raise NotImplementedError()
-
-    @abstractmethod
-    def get_model(
-        self,
-        torch_dtype: Optional[torch.dtype],
-        child_type: Optional[SubModelType] = None,
-    ) -> Any:
-        raise NotImplementedError()
-
-
-class DiffusersModel(ModelBase):
-    # child_types: Dict[str, Type]
-    # child_sizes: Dict[str, int]
-
-    def __init__(self, model_path: str, base_model: BaseModelType, model_type: ModelType):
-        super().__init__(model_path, base_model, model_type)
-
-        self.child_types: Dict[str, Type] = {}
-        self.child_sizes: Dict[str, int] = {}
-
-        try:
-            config_data = DiffusionPipeline.load_config(self.model_path)
-            # config_data = json.loads(os.path.join(self.model_path, "model_index.json"))
-        except Exception:
-            raise Exception("Invalid diffusers model! (model_index.json not found or invalid)")
-
-        config_data.pop("_ignore_files", None)
-
-        # retrieve all folder_names that contain relevant files
-        child_components = [k for k, v in config_data.items() if isinstance(v, list)]
-
-        for child_name in child_components:
-            child_type = self._hf_definition_to_type(config_data[child_name])
-            self.child_types[child_name] = child_type
-            self.child_sizes[child_name] = calc_model_size_by_fs(self.model_path, subfolder=child_name)
-
-    def get_size(self, child_type: Optional[SubModelType] = None):
-        if child_type is None:
-            return sum(self.child_sizes.values())
-        else:
-            return self.child_sizes[child_type]
-
-    def get_model(
-        self,
-        torch_dtype: Optional[torch.dtype],
-        child_type: Optional[SubModelType] = None,
-    ):
-        # return pipeline in different function to pass more arguments
-        if child_type is None:
-            raise Exception("Child model type can't be null on diffusers model")
-        if child_type not in self.child_types:
-            return None  # TODO: or raise
-
-        if torch_dtype == torch.float16:
-            variants = ["fp16", None]
-        else:
-            variants = [None, "fp16"]
-
-        # TODO: better error handling(differentiate not found from others)
-        for variant in variants:
-            try:
-                # TODO: set cache_dir to /dev/null to be sure that cache not used?
-                model = self.child_types[child_type].from_pretrained(
-                    self.model_path,
-                    subfolder=child_type.value,
-                    torch_dtype=torch_dtype,
-                    variant=variant,
-                    local_files_only=True,
-                )
-                break
-            except Exception as e:
-                if not str(e).startswith("Error no file"):
-                    print("====ERR LOAD====")
-                    print(f"{variant}: {e}")
-                pass
-        else:
-            raise Exception(f"Failed to load {self.base_model}:{self.model_type}:{child_type} model")
-
-        # calc more accurate size
-        self.child_sizes[child_type] = calc_model_size_by_data(model)
-        return model
-
-    # def convert_if_required(model_path: str, cache_path: str, config: Optional[dict]) -> str:
-
-
-def calc_model_size_by_fs(model_path: str, subfolder: Optional[str] = None, variant: Optional[str] = None):
-    if subfolder is not None:
-        model_path = os.path.join(model_path, subfolder)
-
-    # this can happen when, for example, the safety checker
-    # is not downloaded.
-    if not os.path.exists(model_path):
-        return 0
-
-    all_files = os.listdir(model_path)
-    all_files = [f for f in all_files if os.path.isfile(os.path.join(model_path, f))]
-
-    fp16_files = {f for f in all_files if ".fp16." in f or ".fp16-" in f}
-    bit8_files = {f for f in all_files if ".8bit." in f or ".8bit-" in f}
-    other_files = set(all_files) - fp16_files - bit8_files
-
-    if variant is None:
-        files = other_files
-    elif variant == "fp16":
-        files = fp16_files
-    elif variant == "8bit":
-        files = bit8_files
-    else:
-        raise NotImplementedError(f"Unknown variant: {variant}")
-
-    # try read from index if exists
-    index_postfix = ".index.json"
-    if variant is not None:
-        index_postfix = f".index.{variant}.json"
-
-    for file in files:
-        if not file.endswith(index_postfix):
-            continue
-        try:
-            with open(os.path.join(model_path, file), "r") as f:
-                index_data = json.loads(f.read())
-            return int(index_data["metadata"]["total_size"])
-        except Exception:
-            pass
-
-    # calculate files size if there is no index file
-    formats = [
-        (".safetensors",),  # safetensors
-        (".bin",),  # torch
-        (".onnx", ".pb"),  # onnx
-        (".msgpack",),  # flax
-        (".ckpt",),  # tf
-        (".h5",),  # tf2
-    ]
-
-    for file_format in formats:
-        model_files = [f for f in files if f.endswith(file_format)]
-        if len(model_files) == 0:
-            continue
-
-        model_size = 0
-        for model_file in model_files:
-            file_stats = os.stat(os.path.join(model_path, model_file))
-            model_size += file_stats.st_size
-        return model_size
-
-    # raise NotImplementedError(f"Unknown model structure! Files: {all_files}")
-    return 0  # scheduler/feature_extractor/tokenizer - models without loading to gpu
-
-
-def calc_model_size_by_data(model) -> int:
-    if isinstance(model, DiffusionPipeline):
-        return _calc_pipeline_by_data(model)
-    elif isinstance(model, torch.nn.Module):
-        return _calc_model_by_data(model)
-    elif isinstance(model, IAIOnnxRuntimeModel):
-        return _calc_onnx_model_by_data(model)
-    else:
-        return 0
-
-
-def _calc_pipeline_by_data(pipeline) -> int:
-    res = 0
-    for submodel_key in pipeline.components.keys():
-        submodel = getattr(pipeline, submodel_key)
-        if submodel is not None and isinstance(submodel, torch.nn.Module):
-            res += _calc_model_by_data(submodel)
-    return res
-
-
-def _calc_model_by_data(model) -> int:
-    mem_params = sum([param.nelement() * param.element_size() for param in model.parameters()])
-    mem_bufs = sum([buf.nelement() * buf.element_size() for buf in model.buffers()])
-    mem = mem_params + mem_bufs  # in bytes
-    return mem
-
-
-def _calc_onnx_model_by_data(model) -> int:
-    tensor_size = model.tensors.size() * 2  # The session doubles this
-    mem = tensor_size  # in bytes
-    return mem
-
-
-def _fast_safetensors_reader(path: str):
-    checkpoint = {}
-    device = torch.device("meta")
-    with open(path, "rb") as f:
-        definition_len = int.from_bytes(f.read(8), "little")
-        definition_json = f.read(definition_len)
-        definition = json.loads(definition_json)
-
-        if "__metadata__" in definition and definition["__metadata__"].get("format", "pt") not in {
-            "pt",
-            "torch",
-            "pytorch",
-        }:
-            raise Exception("Supported only pytorch safetensors files")
-        definition.pop("__metadata__", None)
-
-        for key, info in definition.items():
-            dtype = {
-                "I8": torch.int8,
-                "I16": torch.int16,
-                "I32": torch.int32,
-                "I64": torch.int64,
-                "F16": torch.float16,
-                "F32": torch.float32,
-                "F64": torch.float64,
-            }[info["dtype"]]
-
-            checkpoint[key] = torch.empty(info["shape"], dtype=dtype, device=device)
-
-    return checkpoint
-
-
-def read_checkpoint_meta(path: Union[str, Path], scan: bool = False):
-    if str(path).endswith(".safetensors"):
-        try:
-            checkpoint = _fast_safetensors_reader(path)
-        except Exception:
-            # TODO: create issue for support "meta"?
-            checkpoint = safetensors.torch.load_file(path, device="cpu")
-    else:
-        if scan:
-            scan_result = scan_file_path(path)
-            if scan_result.infected_files != 0:
-                raise Exception(f'The model file "{path}" is potentially infected by malware. Aborting import.')
-        checkpoint = torch.load(path, map_location=torch.device("meta"))
-    return checkpoint
-
-
-class SilenceWarnings(object):
-    def __init__(self):
-        self.transformers_verbosity = transformers_logging.get_verbosity()
-        self.diffusers_verbosity = diffusers_logging.get_verbosity()
-
-    def __enter__(self):
-        transformers_logging.set_verbosity_error()
-        diffusers_logging.set_verbosity_error()
-        warnings.simplefilter("ignore")
-
-    def __exit__(self, type, value, traceback):
-        transformers_logging.set_verbosity(self.transformers_verbosity)
-        diffusers_logging.set_verbosity(self.diffusers_verbosity)
-        warnings.simplefilter("default")
-
-
-ONNX_WEIGHTS_NAME = "model.onnx"
-
-
-class IAIOnnxRuntimeModel:
-    class _tensor_access:
-        def __init__(self, model):
-            self.model = model
-            self.indexes = {}
-            for idx, obj in enumerate(self.model.proto.graph.initializer):
-                self.indexes[obj.name] = idx
-
-        def __getitem__(self, key: str):
-            value = self.model.proto.graph.initializer[self.indexes[key]]
-            return numpy_helper.to_array(value)
-
-        def __setitem__(self, key: str, value: np.ndarray):
-            new_node = numpy_helper.from_array(value)
-            # set_external_data(new_node, location="in-memory-location")
-            new_node.name = key
-            # new_node.ClearField("raw_data")
-            del self.model.proto.graph.initializer[self.indexes[key]]
-            self.model.proto.graph.initializer.insert(self.indexes[key], new_node)
-            # self.model.data[key] = OrtValue.ortvalue_from_numpy(value)
-
-        # __delitem__
-
-        def __contains__(self, key: str):
-            return self.indexes[key] in self.model.proto.graph.initializer
-
-        def items(self):
-            raise NotImplementedError("tensor.items")
-            # return [(obj.name, obj) for obj in self.raw_proto]
-
-        def keys(self):
-            return self.indexes.keys()
-
-        def values(self):
-            raise NotImplementedError("tensor.values")
-            # return [obj for obj in self.raw_proto]
-
-        def size(self):
-            bytesSum = 0
-            for node in self.model.proto.graph.initializer:
-                bytesSum += sys.getsizeof(node.raw_data)
-            return bytesSum
-
-    class _access_helper:
-        def __init__(self, raw_proto):
-            self.indexes = {}
-            self.raw_proto = raw_proto
-            for idx, obj in enumerate(raw_proto):
-                self.indexes[obj.name] = idx
-
-        def __getitem__(self, key: str):
-            return self.raw_proto[self.indexes[key]]
-
-        def __setitem__(self, key: str, value):
-            index = self.indexes[key]
-            del self.raw_proto[index]
-            self.raw_proto.insert(index, value)
-
-        # __delitem__
-
-        def __contains__(self, key: str):
-            return key in self.indexes
-
-        def items(self):
-            return [(obj.name, obj) for obj in self.raw_proto]
-
-        def keys(self):
-            return self.indexes.keys()
-
-        def values(self):
-            return list(self.raw_proto)
-
-    def __init__(self, model_path: str, provider: Optional[str]):
-        self.path = model_path
-        self.session = None
-        self.provider = provider
-        """
-        self.data_path = self.path + "_data"
-        if not os.path.exists(self.data_path):
-            print(f"Moving model tensors to separate file: {self.data_path}")
-            tmp_proto = onnx.load(model_path, load_external_data=True)
-            onnx.save_model(tmp_proto, self.path, save_as_external_data=True, all_tensors_to_one_file=True, location=os.path.basename(self.data_path), size_threshold=1024, convert_attribute=False)
-            del tmp_proto
-            gc.collect()
-
-        self.proto = onnx.load(model_path, load_external_data=False)
-        """
-
-        self.proto = onnx.load(model_path, load_external_data=True)
-        # self.data = dict()
-        # for tensor in self.proto.graph.initializer:
-        #     name = tensor.name
-
-        #     if tensor.HasField("raw_data"):
-        #         npt = numpy_helper.to_array(tensor)
-        #         orv = OrtValue.ortvalue_from_numpy(npt)
-        #         # self.data[name] = orv
-        #         # set_external_data(tensor, location="in-memory-location")
-        #         tensor.name = name
-        #         # tensor.ClearField("raw_data")
-
-        self.nodes = self._access_helper(self.proto.graph.node)
-        # self.initializers = self._access_helper(self.proto.graph.initializer)
-        # print(self.proto.graph.input)
-        # print(self.proto.graph.initializer)
-
-        self.tensors = self._tensor_access(self)
-
-    # TODO: integrate with model manager/cache
-    def create_session(self, height=None, width=None):
-        if self.session is None or self.session_width != width or self.session_height != height:
-            # onnx.save(self.proto, "tmp.onnx")
-            # onnx.save_model(self.proto, "tmp.onnx", save_as_external_data=True, all_tensors_to_one_file=True, location="tmp.onnx_data", size_threshold=1024, convert_attribute=False)
-            # TODO: something to be able to get weight when they already moved outside of model proto
-            # (trimmed_model, external_data) = buffer_external_data_tensors(self.proto)
-            sess = SessionOptions()
-            # self._external_data.update(**external_data)
-            # sess.add_external_initializers(list(self.data.keys()), list(self.data.values()))
-            # sess.enable_profiling = True
-
-            # sess.intra_op_num_threads = 1
-            # sess.inter_op_num_threads = 1
-            # sess.execution_mode = ExecutionMode.ORT_SEQUENTIAL
-            # sess.graph_optimization_level = GraphOptimizationLevel.ORT_ENABLE_ALL
-            # sess.enable_cpu_mem_arena = True
-            # sess.enable_mem_pattern = True
-            # sess.add_session_config_entry("session.intra_op.use_xnnpack_threadpool", "1") ########### It's the key code
-            self.session_height = height
-            self.session_width = width
-            if height and width:
-                sess.add_free_dimension_override_by_name("unet_sample_batch", 2)
-                sess.add_free_dimension_override_by_name("unet_sample_channels", 4)
-                sess.add_free_dimension_override_by_name("unet_hidden_batch", 2)
-                sess.add_free_dimension_override_by_name("unet_hidden_sequence", 77)
-                sess.add_free_dimension_override_by_name("unet_sample_height", self.session_height)
-                sess.add_free_dimension_override_by_name("unet_sample_width", self.session_width)
-                sess.add_free_dimension_override_by_name("unet_time_batch", 1)
-            providers = []
-            if self.provider:
-                providers.append(self.provider)
-            else:
-                providers = get_available_providers()
-            if "TensorrtExecutionProvider" in providers:
-                providers.remove("TensorrtExecutionProvider")
-            try:
-                self.session = InferenceSession(self.proto.SerializeToString(), providers=providers, sess_options=sess)
-            except Exception as e:
-                raise e
-            # self.session = InferenceSession("tmp.onnx", providers=[self.provider], sess_options=self.sess_options)
-            # self.io_binding = self.session.io_binding()
-
-    def release_session(self):
-        self.session = None
-        import gc
-
-        gc.collect()
-        return
-
-    def __call__(self, **kwargs):
-        if self.session is None:
-            raise Exception("You should call create_session before running model")
-
-        inputs = {k: np.array(v) for k, v in kwargs.items()}
-        # output_names = self.session.get_outputs()
-        # for k in inputs:
-        #     self.io_binding.bind_cpu_input(k, inputs[k])
-        # for name in output_names:
-        #     self.io_binding.bind_output(name.name)
-        # self.session.run_with_iobinding(self.io_binding, None)
-        # return self.io_binding.copy_outputs_to_cpu()
-        return self.session.run(None, inputs)
-
-    # compatability with diffusers load code
-    @classmethod
-    def from_pretrained(
-        cls,
-        model_id: Union[str, Path],
-        subfolder: Union[str, Path] = None,
-        file_name: Optional[str] = None,
-        provider: Optional[str] = None,
-        sess_options: Optional["SessionOptions"] = None,
-        **kwargs,
-    ):
-        file_name = file_name or ONNX_WEIGHTS_NAME
-
-        if os.path.isdir(model_id):
-            model_path = model_id
-            if subfolder is not None:
-                model_path = os.path.join(model_path, subfolder)
-            model_path = os.path.join(model_path, file_name)
-
-        else:
-            model_path = model_id
-
-        # load model from local directory
-        if not os.path.isfile(model_path):
-            raise Exception(f"Model not found: {model_path}")
-
-        # TODO: session options
-        return cls(model_path, provider=provider)
diff --git a/invokeai/backend/model_management_OLD/models/clip_vision.py b/invokeai/backend/model_management_OLD/models/clip_vision.py
deleted file mode 100644
index 2276c6beed..0000000000
--- a/invokeai/backend/model_management_OLD/models/clip_vision.py
+++ /dev/null
@@ -1,82 +0,0 @@
-import os
-from enum import Enum
-from typing import Literal, Optional
-
-import torch
-from transformers import CLIPVisionModelWithProjection
-
-from invokeai.backend.model_management.models.base import (
-    BaseModelType,
-    InvalidModelException,
-    ModelBase,
-    ModelConfigBase,
-    ModelType,
-    SubModelType,
-    calc_model_size_by_data,
-    calc_model_size_by_fs,
-    classproperty,
-)
-
-
-class CLIPVisionModelFormat(str, Enum):
-    Diffusers = "diffusers"
-
-
-class CLIPVisionModel(ModelBase):
-    class DiffusersConfig(ModelConfigBase):
-        model_format: Literal[CLIPVisionModelFormat.Diffusers]
-
-    def __init__(self, model_path: str, base_model: BaseModelType, model_type: ModelType):
-        assert model_type == ModelType.CLIPVision
-        super().__init__(model_path, base_model, model_type)
-
-        self.model_size = calc_model_size_by_fs(self.model_path)
-
-    @classmethod
-    def detect_format(cls, path: str) -> str:
-        if not os.path.exists(path):
-            raise ModuleNotFoundError(f"No CLIP Vision model at path '{path}'.")
-
-        if os.path.isdir(path) and os.path.exists(os.path.join(path, "config.json")):
-            return CLIPVisionModelFormat.Diffusers
-
-        raise InvalidModelException(f"Unexpected CLIP Vision model format: {path}")
-
-    @classproperty
-    def save_to_config(cls) -> bool:
-        return True
-
-    def get_size(self, child_type: Optional[SubModelType] = None) -> int:
-        if child_type is not None:
-            raise ValueError("There are no child models in a CLIP Vision model.")
-
-        return self.model_size
-
-    def get_model(
-        self,
-        torch_dtype: Optional[torch.dtype],
-        child_type: Optional[SubModelType] = None,
-    ) -> CLIPVisionModelWithProjection:
-        if child_type is not None:
-            raise ValueError("There are no child models in a CLIP Vision model.")
-
-        model = CLIPVisionModelWithProjection.from_pretrained(self.model_path, torch_dtype=torch_dtype)
-
-        # Calculate a more accurate model size.
-        self.model_size = calc_model_size_by_data(model)
-
-        return model
-
-    @classmethod
-    def convert_if_required(
-        cls,
-        model_path: str,
-        output_path: str,
-        config: ModelConfigBase,
-        base_model: BaseModelType,
-    ) -> str:
-        format = cls.detect_format(model_path)
-        if format == CLIPVisionModelFormat.Diffusers:
-            return model_path
-        else:
-            raise ValueError(f"Unsupported format: '{format}'.")
diff --git a/invokeai/backend/model_management_OLD/models/controlnet.py b/invokeai/backend/model_management_OLD/models/controlnet.py
deleted file mode 100644
index 3b534cb9d1..0000000000
--- a/invokeai/backend/model_management_OLD/models/controlnet.py
+++ /dev/null
@@ -1,162 +0,0 @@
-import os
-from enum import Enum
-from pathlib import Path
-from typing import Literal, Optional
-
-import torch
-
-import invokeai.backend.util.logging as logger
-from invokeai.app.services.config import InvokeAIAppConfig
-
-from .base import (
-    BaseModelType,
-    EmptyConfigLoader,
-    InvalidModelException,
-    ModelBase,
-    ModelConfigBase,
-    ModelNotFoundException,
-    ModelType,
-    SubModelType,
-    calc_model_size_by_data,
-    calc_model_size_by_fs,
-    classproperty,
-)
-
-
-class ControlNetModelFormat(str, Enum):
-    Checkpoint = "checkpoint"
-    Diffusers = "diffusers"
-
-
-class ControlNetModel(ModelBase):
-    # model_class: Type
-    # model_size: int
-
-    class DiffusersConfig(ModelConfigBase):
-        model_format: Literal[ControlNetModelFormat.Diffusers]
-
-    class CheckpointConfig(ModelConfigBase):
-        model_format: Literal[ControlNetModelFormat.Checkpoint]
-        config: str
-
-    def __init__(self, model_path: str, base_model: BaseModelType, model_type: ModelType):
-        assert model_type == ModelType.ControlNet
-        super().__init__(model_path, base_model, model_type)
-
-        try:
-            config = EmptyConfigLoader.load_config(self.model_path, config_name="config.json")
-            # config = json.loads(os.path.join(self.model_path, "config.json"))
-        except Exception:
-            raise Exception("Invalid controlnet model! (config.json not found or invalid)")
-
-        model_class_name = config.get("_class_name", None)
-        if model_class_name not in {"ControlNetModel"}:
-            raise Exception(f"Invalid ControlNet model! Unknown _class_name: {model_class_name}")
-
-        try:
-            self.model_class = self._hf_definition_to_type(["diffusers", model_class_name])
-            self.model_size = calc_model_size_by_fs(self.model_path)
-        except Exception:
-            raise Exception("Invalid ControlNet model!")
-
-    def get_size(self, child_type: Optional[SubModelType] = None):
-        if child_type is not None:
-            raise Exception("There is no child models in controlnet model")
-        return self.model_size
-
-    def get_model(
-        self,
-        torch_dtype: Optional[torch.dtype],
-        child_type: Optional[SubModelType] = None,
-    ):
-        if child_type is not None:
-            raise Exception("There are no child models in controlnet model")
-
-        model = None
-        for variant in ["fp16", None]:
-            try:
-                model = self.model_class.from_pretrained(
-                    self.model_path,
-                    torch_dtype=torch_dtype,
-                    variant=variant,
-                )
-                break
-            except Exception:
-                pass
-        if not model:
-            raise ModelNotFoundException()
-
-        # calc more accurate size
-        self.model_size = calc_model_size_by_data(model)
-        return model
-
-    @classproperty
-    def save_to_config(cls) -> bool:
-        return False
-
-    @classmethod
-    def detect_format(cls, path: str):
-        if not os.path.exists(path):
-            raise ModelNotFoundException()
-
-        if os.path.isdir(path):
-            if os.path.exists(os.path.join(path, "config.json")):
-                return ControlNetModelFormat.Diffusers
-
-        if os.path.isfile(path):
-            if any(path.endswith(f".{ext}") for ext in ["safetensors", "ckpt", "pt", "pth"]):
-                return ControlNetModelFormat.Checkpoint
-
-        raise InvalidModelException(f"Not a valid model: {path}")
-
-    @classmethod
-    def convert_if_required(
-        cls,
-        model_path: str,
-        output_path: str,
-        config: ModelConfigBase,
-        base_model: BaseModelType,
-    ) -> str:
-        if cls.detect_format(model_path) == ControlNetModelFormat.Checkpoint:
-            return _convert_controlnet_ckpt_and_cache(
-                model_path=model_path,
-                model_config=config.config,
-                output_path=output_path,
-                base_model=base_model,
-            )
-        else:
-            return model_path
-
-
-def _convert_controlnet_ckpt_and_cache(
-    model_path: str,
-    output_path: str,
-    base_model: BaseModelType,
-    model_config: str,
-) -> str:
-    """
-    Convert the controlnet from checkpoint format to diffusers format,
-    cache it to disk, and return Path to converted
-    file. If already on disk then just returns Path.
-    """
-    app_config = InvokeAIAppConfig.get_config()
-    weights = app_config.root_path / model_path
-    output_path = Path(output_path)
-
-    logger.info(f"Converting {weights} to diffusers format")
-    # return cached version if it exists
-    if output_path.exists():
-        return output_path
-
-    # to avoid circular import errors
-    from ..convert_ckpt_to_diffusers import convert_controlnet_to_diffusers
-
-    convert_controlnet_to_diffusers(
-        weights,
-        output_path,
-        original_config_file=app_config.root_path / model_config,
-        image_size=512,
-        scan_needed=True,
-        from_safetensors=weights.suffix == ".safetensors",
-    )
-    return output_path
diff --git a/invokeai/backend/model_management_OLD/models/ip_adapter.py b/invokeai/backend/model_management_OLD/models/ip_adapter.py
deleted file mode 100644
index c60edd0abe..0000000000
--- a/invokeai/backend/model_management_OLD/models/ip_adapter.py
+++ /dev/null
@@ -1,98 +0,0 @@
-import os
-import typing
-from enum import Enum
-from typing import Literal, Optional
-
-import torch
-
-from invokeai.backend.ip_adapter.ip_adapter import IPAdapter, IPAdapterPlus, build_ip_adapter
-from invokeai.backend.model_management.models.base import (
-    BaseModelType,
-    InvalidModelException,
-    ModelBase,
-    ModelConfigBase,
-    ModelType,
-    SubModelType,
-    calc_model_size_by_fs,
-    classproperty,
-)
-
-
-class IPAdapterModelFormat(str, Enum):
-    # The custom IP-Adapter model format defined by InvokeAI.
-    InvokeAI = "invokeai"
-
-
-class IPAdapterModel(ModelBase):
-    class InvokeAIConfig(ModelConfigBase):
-        model_format: Literal[IPAdapterModelFormat.InvokeAI]
-
-    def __init__(self, model_path: str, base_model: BaseModelType, model_type: ModelType):
-        assert model_type == ModelType.IPAdapter
-        super().__init__(model_path, base_model, model_type)
-
-        self.model_size = calc_model_size_by_fs(self.model_path)
-
-    @classmethod
-    def detect_format(cls, path: str) -> str:
-        if not os.path.exists(path):
-            raise ModuleNotFoundError(f"No IP-Adapter model at path '{path}'.")
-
-        if os.path.isdir(path):
-            model_file = os.path.join(path, "ip_adapter.bin")
-            image_encoder_config_file = os.path.join(path, "image_encoder.txt")
-            if os.path.exists(model_file) and os.path.exists(image_encoder_config_file):
-                return IPAdapterModelFormat.InvokeAI
-
-        raise InvalidModelException(f"Unexpected IP-Adapter model format: {path}")
-
-    @classproperty
-    def save_to_config(cls) -> bool:
-        return True
-
-    def get_size(self, child_type: Optional[SubModelType] = None) -> int:
-        if child_type is not None:
-            raise ValueError("There are no child models in an IP-Adapter model.")
-
-        return self.model_size
-
-    def get_model(
-        self,
-        torch_dtype: torch.dtype,
-        child_type: Optional[SubModelType] = None,
-    ) -> typing.Union[IPAdapter, IPAdapterPlus]:
-        if child_type is not None:
-            raise ValueError("There are no child models in an IP-Adapter model.")
-
-        model = build_ip_adapter(
-            ip_adapter_ckpt_path=os.path.join(self.model_path, "ip_adapter.bin"),
-            device=torch.device("cpu"),
-            dtype=torch_dtype,
-        )
-
-        self.model_size = model.calc_size()
-        return model
-
-    @classmethod
-    def convert_if_required(
-        cls,
-        model_path: str,
-        output_path: str,
-        config: ModelConfigBase,
-        base_model: BaseModelType,
-    ) -> str:
-        format = cls.detect_format(model_path)
-        if format == IPAdapterModelFormat.InvokeAI:
-            return model_path
-        else:
-            raise ValueError(f"Unsupported format: '{format}'.")
-
-
-def get_ip_adapter_image_encoder_model_id(model_path: str):
-    """Read the ID of the image encoder associated with the IP-Adapter at `model_path`."""
-    image_encoder_config_file = os.path.join(model_path, "image_encoder.txt")
-
-    with open(image_encoder_config_file, "r") as f:
-        image_encoder_model = f.readline().strip()
-
-    return image_encoder_model
diff --git a/invokeai/backend/model_management_OLD/models/lora.py b/invokeai/backend/model_management_OLD/models/lora.py
deleted file mode 100644
index b110d75d22..0000000000
--- a/invokeai/backend/model_management_OLD/models/lora.py
+++ /dev/null
@@ -1,696 +0,0 @@
-import bisect
-import os
-from enum import Enum
-from pathlib import Path
-from typing import Dict, Optional, Union
-
-import torch
-from safetensors.torch import load_file
-
-from .base import (
-    BaseModelType,
-    InvalidModelException,
-    ModelBase,
-    ModelConfigBase,
-    ModelNotFoundException,
-    ModelType,
-    SubModelType,
-    classproperty,
-)
-
-
-class LoRAModelFormat(str, Enum):
-    LyCORIS = "lycoris"
-    Diffusers = "diffusers"
-
-
-class LoRAModel(ModelBase):
-    # model_size: int
-
-    class Config(ModelConfigBase):
-        model_format: LoRAModelFormat  # TODO:
-
-    def __init__(self, model_path: str, base_model: BaseModelType, model_type: ModelType):
-        assert model_type == ModelType.Lora
-        super().__init__(model_path, base_model, model_type)
-
-        self.model_size = os.path.getsize(self.model_path)
-
-    def get_size(self, child_type: Optional[SubModelType] = None):
-        if child_type is not None:
-            raise Exception("There is no child models in lora")
-        return self.model_size
-
-    def get_model(
-        self,
-        torch_dtype: Optional[torch.dtype],
-        child_type: Optional[SubModelType] = None,
-    ):
-        if child_type is not None:
-            raise Exception("There is no child models in lora")
-
-        model = LoRAModelRaw.from_checkpoint(
-            file_path=self.model_path,
-            dtype=torch_dtype,
-            base_model=self.base_model,
-        )
-
-        self.model_size = model.calc_size()
-        return model
-
-    @classproperty
-    def save_to_config(cls) -> bool:
-        return True
-
-    @classmethod
-    def detect_format(cls, path: str):
-        if not os.path.exists(path):
-            raise ModelNotFoundException()
-
-        if os.path.isdir(path):
-            for ext in ["safetensors", "bin"]:
-                if os.path.exists(os.path.join(path, f"pytorch_lora_weights.{ext}")):
-                    return LoRAModelFormat.Diffusers
-
-        if os.path.isfile(path):
-            if any(path.endswith(f".{ext}") for ext in ["safetensors", "ckpt", "pt"]):
-                return LoRAModelFormat.LyCORIS
-
-        raise InvalidModelException(f"Not a valid model: {path}")
-
-    @classmethod
-    def convert_if_required(
-        cls,
-        model_path: str,
-        output_path: str,
-        config: ModelConfigBase,
-        base_model: BaseModelType,
-    ) -> str:
-        if cls.detect_format(model_path) == LoRAModelFormat.Diffusers:
-            for ext in ["safetensors", "bin"]:  # return path to the safetensors file inside the folder
-                path = Path(model_path, f"pytorch_lora_weights.{ext}")
-                if path.exists():
-                    return path
-        else:
-            return model_path
-
-
-class LoRALayerBase:
-    # rank: Optional[int]
-    # alpha: Optional[float]
-    # bias: Optional[torch.Tensor]
-    # layer_key: str
-
-    # @property
-    # def scale(self):
-    #    return self.alpha / self.rank if (self.alpha and self.rank) else 1.0
-
-    def __init__(
-        self,
-        layer_key: str,
-        values: dict,
-    ):
-        if "alpha" in values:
-            self.alpha = values["alpha"].item()
-        else:
-            self.alpha = None
-
-        if "bias_indices" in values and "bias_values" in values and "bias_size" in values:
-            self.bias = torch.sparse_coo_tensor(
-                values["bias_indices"],
-                values["bias_values"],
-                tuple(values["bias_size"]),
-            )
-
-        else:
-            self.bias = None
-
-        self.rank = None  # set in layer implementation
-        self.layer_key = layer_key
-
-    def get_weight(self, orig_weight: torch.Tensor):
-        raise NotImplementedError()
-
-    def calc_size(self) -> int:
-        model_size = 0
-        for val in [self.bias]:
-            if val is not None:
-                model_size += val.nelement() * val.element_size()
-        return model_size
-
-    def to(
-        self,
-        device: Optional[torch.device] = None,
-        dtype: Optional[torch.dtype] = None,
-    ):
-        if self.bias is not None:
-            self.bias = self.bias.to(device=device, dtype=dtype)
-
-
-# TODO: find and debug lora/locon with bias
-class LoRALayer(LoRALayerBase):
-    # up: torch.Tensor
-    # mid: Optional[torch.Tensor]
-    # down: torch.Tensor
-
-    def __init__(
-        self,
-        layer_key: str,
-        values: dict,
-    ):
-        super().__init__(layer_key, values)
-
-        self.up = values["lora_up.weight"]
-        self.down = values["lora_down.weight"]
-        if "lora_mid.weight" in values:
-            self.mid = values["lora_mid.weight"]
-        else:
-            self.mid = None
-
-        self.rank = self.down.shape[0]
-
-    def get_weight(self, orig_weight: torch.Tensor):
-        if self.mid is not None:
-            up = self.up.reshape(self.up.shape[0], self.up.shape[1])
-            down = self.down.reshape(self.down.shape[0], self.down.shape[1])
-            weight = torch.einsum("m n w h, i m, n j -> i j w h", self.mid, up, down)
-        else:
-            weight = self.up.reshape(self.up.shape[0], -1) @ self.down.reshape(self.down.shape[0], -1)
-
-        return weight
-
-    def calc_size(self) -> int:
-        model_size = super().calc_size()
-        for val in [self.up, self.mid, self.down]:
-            if val is not None:
-                model_size += val.nelement() * val.element_size()
-        return model_size
-
-    def to(
-        self,
-        device: Optional[torch.device] = None,
-        dtype: Optional[torch.dtype] = None,
-    ):
-        super().to(device=device, dtype=dtype)
-
-        self.up = self.up.to(device=device, dtype=dtype)
-        self.down = self.down.to(device=device, dtype=dtype)
-
-        if self.mid is not None:
-            self.mid = self.mid.to(device=device, dtype=dtype)
-
-
-class LoHALayer(LoRALayerBase):
-    # w1_a: torch.Tensor
-    # w1_b: torch.Tensor
-    # w2_a: torch.Tensor
-    # w2_b: torch.Tensor
-    # t1: Optional[torch.Tensor] = None
-    # t2: Optional[torch.Tensor] = None
-
-    def __init__(
-        self,
-        layer_key: str,
-        values: dict,
-    ):
-        super().__init__(layer_key, values)
-
-        self.w1_a = values["hada_w1_a"]
-        self.w1_b = values["hada_w1_b"]
-        self.w2_a = values["hada_w2_a"]
-        self.w2_b = values["hada_w2_b"]
-
-        if "hada_t1" in values:
-            self.t1 = values["hada_t1"]
-        else:
-            self.t1 = None
-
-        if "hada_t2" in values:
-            self.t2 = values["hada_t2"]
-        else:
-            self.t2 = None
-
-        self.rank = self.w1_b.shape[0]
-
-    def get_weight(self, orig_weight: torch.Tensor):
-        if self.t1 is None:
-            weight = (self.w1_a @ self.w1_b) * (self.w2_a @ self.w2_b)
-
-        else:
-            rebuild1 = torch.einsum("i j k l, j r, i p -> p r k l", self.t1, self.w1_b, self.w1_a)
-            rebuild2 = torch.einsum("i j k l, j r, i p -> p r k l", self.t2, self.w2_b, self.w2_a)
-            weight = rebuild1 * rebuild2
-
-        return weight
-
-    def calc_size(self) -> int:
-        model_size = super().calc_size()
-        for val in [self.w1_a, self.w1_b, self.w2_a, self.w2_b, self.t1, self.t2]:
-            if val is not None:
-                model_size += val.nelement() * val.element_size()
-        return model_size
-
-    def to(
-        self,
-        device: Optional[torch.device] = None,
-        dtype: Optional[torch.dtype] = None,
-    ):
-        super().to(device=device, dtype=dtype)
-
-        self.w1_a = self.w1_a.to(device=device, dtype=dtype)
-        self.w1_b = self.w1_b.to(device=device, dtype=dtype)
-        if self.t1 is not None:
-            self.t1 = self.t1.to(device=device, dtype=dtype)
-
-        self.w2_a = self.w2_a.to(device=device, dtype=dtype)
-        self.w2_b = self.w2_b.to(device=device, dtype=dtype)
-        if self.t2 is not None:
-            self.t2 = self.t2.to(device=device, dtype=dtype)
-
-
-class LoKRLayer(LoRALayerBase):
-    # w1: Optional[torch.Tensor] = None
-    # w1_a: Optional[torch.Tensor] = None
-    # w1_b: Optional[torch.Tensor] = None
-    # w2: Optional[torch.Tensor] = None
-    # w2_a: Optional[torch.Tensor] = None
-    # w2_b: Optional[torch.Tensor] = None
-    # t2: Optional[torch.Tensor] = None
-
-    def __init__(
-        self,
-        layer_key: str,
-        values: dict,
-    ):
-        super().__init__(layer_key, values)
-
-        if "lokr_w1" in values:
-            self.w1 = values["lokr_w1"]
-            self.w1_a = None
-            self.w1_b = None
-        else:
-            self.w1 = None
-            self.w1_a = values["lokr_w1_a"]
-            self.w1_b = values["lokr_w1_b"]
-
-        if "lokr_w2" in values:
-            self.w2 = values["lokr_w2"]
-            self.w2_a = None
-            self.w2_b = None
-        else:
-            self.w2 = None
-            self.w2_a = values["lokr_w2_a"]
-            self.w2_b = values["lokr_w2_b"]
-
-        if "lokr_t2" in values:
-            self.t2 = values["lokr_t2"]
-        else:
-            self.t2 = None
-
-        if "lokr_w1_b" in values:
-            self.rank = values["lokr_w1_b"].shape[0]
-        elif "lokr_w2_b" in values:
-            self.rank = values["lokr_w2_b"].shape[0]
-        else:
-            self.rank = None  # unscaled
-
-    def get_weight(self, orig_weight: torch.Tensor):
-        w1 = self.w1
-        if w1 is None:
-            w1 = self.w1_a @ self.w1_b
-
-        w2 = self.w2
-        if w2 is None:
-            if self.t2 is None:
-                w2 = self.w2_a @ self.w2_b
-            else:
-                w2 = torch.einsum("i j k l, i p, j r -> p r k l", self.t2, self.w2_a, self.w2_b)
-
-        if len(w2.shape) == 4:
-            w1 = w1.unsqueeze(2).unsqueeze(2)
-        w2 = w2.contiguous()
-        weight = torch.kron(w1, w2)
-
-        return weight
-
-    def calc_size(self) -> int:
-        model_size = super().calc_size()
-        for val in [self.w1, self.w1_a, self.w1_b, self.w2, self.w2_a, self.w2_b, self.t2]:
-            if val is not None:
-                model_size += val.nelement() * val.element_size()
-        return model_size
-
-    def to(
-        self,
-        device: Optional[torch.device] = None,
-        dtype: Optional[torch.dtype] = None,
-    ):
-        super().to(device=device, dtype=dtype)
-
-        if self.w1 is not None:
-            self.w1 = self.w1.to(device=device, dtype=dtype)
-        else:
-            self.w1_a = self.w1_a.to(device=device, dtype=dtype)
-            self.w1_b = self.w1_b.to(device=device, dtype=dtype)
-
-        if self.w2 is not None:
-            self.w2 = self.w2.to(device=device, dtype=dtype)
-        else:
-            self.w2_a = self.w2_a.to(device=device, dtype=dtype)
-            self.w2_b = self.w2_b.to(device=device, dtype=dtype)
-
-        if self.t2 is not None:
-            self.t2 = self.t2.to(device=device, dtype=dtype)
-
-
-class FullLayer(LoRALayerBase):
-    # weight: torch.Tensor
-
-    def __init__(
-        self,
-        layer_key: str,
-        values: dict,
-    ):
-        super().__init__(layer_key, values)
-
-        self.weight = values["diff"]
-
-        if len(values.keys()) > 1:
-            _keys = list(values.keys())
-            _keys.remove("diff")
-            raise NotImplementedError(f"Unexpected keys in lora diff layer: {_keys}")
-
-        self.rank = None  # unscaled
-
-    def get_weight(self, orig_weight: torch.Tensor):
-        return self.weight
-
-    def calc_size(self) -> int:
-        model_size = super().calc_size()
-        model_size += self.weight.nelement() * self.weight.element_size()
-        return model_size
-
-    def to(
-        self,
-        device: Optional[torch.device] = None,
-        dtype: Optional[torch.dtype] = None,
-    ):
-        super().to(device=device, dtype=dtype)
-
-        self.weight = self.weight.to(device=device, dtype=dtype)
-
-
-class IA3Layer(LoRALayerBase):
-    # weight: torch.Tensor
-    # on_input: torch.Tensor
-
-    def __init__(
-        self,
-        layer_key: str,
-        values: dict,
-    ):
-        super().__init__(layer_key, values)
-
-        self.weight = values["weight"]
-        self.on_input = values["on_input"]
-
-        self.rank = None  # unscaled
-
-    def get_weight(self, orig_weight: torch.Tensor):
-        weight = self.weight
-        if not self.on_input:
-            weight = weight.reshape(-1, 1)
-        return orig_weight * weight
-
-    def calc_size(self) -> int:
-        model_size = super().calc_size()
-        model_size += self.weight.nelement() * self.weight.element_size()
-        model_size += self.on_input.nelement() * self.on_input.element_size()
-        return model_size
-
-    def to(
-        self,
-        device: Optional[torch.device] = None,
-        dtype: Optional[torch.dtype] = None,
-    ):
-        super().to(device=device, dtype=dtype)
-
-        self.weight = self.weight.to(device=device, dtype=dtype)
-        self.on_input = self.on_input.to(device=device, dtype=dtype)
-
-
-# TODO: rename all methods used in model logic with Info postfix and remove here Raw postfix
-class LoRAModelRaw:  # (torch.nn.Module):
-    _name: str
-    layers: Dict[str, LoRALayer]
-
-    def __init__(
-        self,
-        name: str,
-        layers: Dict[str, LoRALayer],
-    ):
-        self._name = name
-        self.layers = layers
-
-    @property
-    def name(self):
-        return self._name
-
-    def to(
-        self,
-        device: Optional[torch.device] = None,
-        dtype: Optional[torch.dtype] = None,
-    ):
-        # TODO: try revert if exception?
-        for _key, layer in self.layers.items():
-            layer.to(device=device, dtype=dtype)
-
-    def calc_size(self) -> int:
-        model_size = 0
-        for _, layer in self.layers.items():
-            model_size += layer.calc_size()
-        return model_size
-
-    @classmethod
-    def _convert_sdxl_keys_to_diffusers_format(cls, state_dict):
-        """Convert the keys of an SDXL LoRA state_dict to diffusers format.
-
-        The input state_dict can be in either Stability AI format or diffusers format. If the state_dict is already in
-        diffusers format, then this function will have no effect.
-
-        This function is adapted from:
-        https://github.com/bmaltais/kohya_ss/blob/2accb1305979ba62f5077a23aabac23b4c37e935/networks/lora_diffusers.py#L385-L409
-
-        Args:
-            state_dict (Dict[str, Tensor]): The SDXL LoRA state_dict.
-
-        Raises:
-            ValueError: If state_dict contains an unrecognized key, or not all keys could be converted.
-
-        Returns:
-            Dict[str, Tensor]: The diffusers-format state_dict.
-        """
-        converted_count = 0  # The number of Stability AI keys converted to diffusers format.
-        not_converted_count = 0  # The number of keys that were not converted.
-
-        # Get a sorted list of Stability AI UNet keys so that we can efficiently search for keys with matching prefixes.
-        # For example, we want to efficiently find `input_blocks_4_1` in the list when searching for
-        # `input_blocks_4_1_proj_in`.
-        stability_unet_keys = list(SDXL_UNET_STABILITY_TO_DIFFUSERS_MAP)
-        stability_unet_keys.sort()
-
-        new_state_dict = {}
-        for full_key, value in state_dict.items():
-            if full_key.startswith("lora_unet_"):
-                search_key = full_key.replace("lora_unet_", "")
-                # Use bisect to find the key in stability_unet_keys that *may* match the search_key's prefix.
-                position = bisect.bisect_right(stability_unet_keys, search_key)
-                map_key = stability_unet_keys[position - 1]
-                # Now, check if the map_key *actually* matches the search_key.
-                if search_key.startswith(map_key):
-                    new_key = full_key.replace(map_key, SDXL_UNET_STABILITY_TO_DIFFUSERS_MAP[map_key])
-                    new_state_dict[new_key] = value
-                    converted_count += 1
-                else:
-                    new_state_dict[full_key] = value
-                    not_converted_count += 1
-            elif full_key.startswith("lora_te1_") or full_key.startswith("lora_te2_"):
-                # The CLIP text encoders have the same keys in both Stability AI and diffusers formats.
-                new_state_dict[full_key] = value
-                continue
-            else:
-                raise ValueError(f"Unrecognized SDXL LoRA key prefix: '{full_key}'.")
-
-        if converted_count > 0 and not_converted_count > 0:
-            raise ValueError(
-                f"The SDXL LoRA could only be partially converted to diffusers format. converted={converted_count},"
-                f" not_converted={not_converted_count}"
-            )
-
-        return new_state_dict
-
-    @classmethod
-    def from_checkpoint(
-        cls,
-        file_path: Union[str, Path],
-        device: Optional[torch.device] = None,
-        dtype: Optional[torch.dtype] = None,
-        base_model: Optional[BaseModelType] = None,
-    ):
-        device = device or torch.device("cpu")
-        dtype = dtype or torch.float32
-
-        if isinstance(file_path, str):
-            file_path = Path(file_path)
-
-        model = cls(
-            name=file_path.stem,  # TODO:
-            layers={},
-        )
-
-        if file_path.suffix == ".safetensors":
-            state_dict = load_file(file_path.absolute().as_posix(), device="cpu")
-        else:
-            state_dict = torch.load(file_path, map_location="cpu")
-
-        state_dict = cls._group_state(state_dict)
-
-        if base_model == BaseModelType.StableDiffusionXL:
-            state_dict = cls._convert_sdxl_keys_to_diffusers_format(state_dict)
-
-        for layer_key, values in state_dict.items():
-            # lora and locon
-            if "lora_down.weight" in values:
-                layer = LoRALayer(layer_key, values)
-
-            # loha
-            elif "hada_w1_b" in values:
-                layer = LoHALayer(layer_key, values)
-
-            # lokr
-            elif "lokr_w1_b" in values or "lokr_w1" in values:
-                layer = LoKRLayer(layer_key, values)
-
-            # diff
-            elif "diff" in values:
-                layer = FullLayer(layer_key, values)
-
-            # ia3
-            elif "weight" in values and "on_input" in values:
-                layer = IA3Layer(layer_key, values)
-
-            else:
-                print(f">> Encountered unknown lora layer module in {model.name}: {layer_key} - {list(values.keys())}")
-                raise Exception("Unknown lora format!")
-
-            # lower memory consumption by removing already parsed layer values
-            state_dict[layer_key].clear()
-
-            layer.to(device=device, dtype=dtype)
-            model.layers[layer_key] = layer
-
-        return model
-
-    @staticmethod
-    def _group_state(state_dict: dict):
-        state_dict_groupped = {}
-
-        for key, value in state_dict.items():
-            stem, leaf = key.split(".", 1)
-            if stem not in state_dict_groupped:
-                state_dict_groupped[stem] = {}
-            state_dict_groupped[stem][leaf] = value
-
-        return state_dict_groupped
-
-
-# code from
-# https://github.com/bmaltais/kohya_ss/blob/2accb1305979ba62f5077a23aabac23b4c37e935/networks/lora_diffusers.py#L15C1-L97C32
-def make_sdxl_unet_conversion_map():
-    """Create a dict mapping state_dict keys from Stability AI SDXL format to diffusers SDXL format."""
-    unet_conversion_map_layer = []
-
-    for i in range(3):  # num_blocks is 3 in sdxl
-        # loop over downblocks/upblocks
-        for j in range(2):
-            # loop over resnets/attentions for downblocks
-            hf_down_res_prefix = f"down_blocks.{i}.resnets.{j}."
-            sd_down_res_prefix = f"input_blocks.{3*i + j + 1}.0."
-            unet_conversion_map_layer.append((sd_down_res_prefix, hf_down_res_prefix))
-
-            if i < 3:
-                # no attention layers in down_blocks.3
-                hf_down_atn_prefix = f"down_blocks.{i}.attentions.{j}."
-                sd_down_atn_prefix = f"input_blocks.{3*i + j + 1}.1."
-                unet_conversion_map_layer.append((sd_down_atn_prefix, hf_down_atn_prefix))
-
-        for j in range(3):
-            # loop over resnets/attentions for upblocks
-            hf_up_res_prefix = f"up_blocks.{i}.resnets.{j}."
-            sd_up_res_prefix = f"output_blocks.{3*i + j}.0."
-            unet_conversion_map_layer.append((sd_up_res_prefix, hf_up_res_prefix))
-
-            # if i > 0: commentout for sdxl
-            # no attention layers in up_blocks.0
-            hf_up_atn_prefix = f"up_blocks.{i}.attentions.{j}."
-            sd_up_atn_prefix = f"output_blocks.{3*i + j}.1."
-            unet_conversion_map_layer.append((sd_up_atn_prefix, hf_up_atn_prefix))
-
-        if i < 3:
-            # no downsample in down_blocks.3
-            hf_downsample_prefix = f"down_blocks.{i}.downsamplers.0.conv."
-            sd_downsample_prefix = f"input_blocks.{3*(i+1)}.0.op."
-            unet_conversion_map_layer.append((sd_downsample_prefix, hf_downsample_prefix))
-
-            # no upsample in up_blocks.3
-            hf_upsample_prefix = f"up_blocks.{i}.upsamplers.0."
-            sd_upsample_prefix = f"output_blocks.{3*i + 2}.{2}."  # change for sdxl
-            unet_conversion_map_layer.append((sd_upsample_prefix, hf_upsample_prefix))
-
-    hf_mid_atn_prefix = "mid_block.attentions.0."
-    sd_mid_atn_prefix = "middle_block.1."
-    unet_conversion_map_layer.append((sd_mid_atn_prefix, hf_mid_atn_prefix))
-
-    for j in range(2):
-        hf_mid_res_prefix = f"mid_block.resnets.{j}."
-        sd_mid_res_prefix = f"middle_block.{2*j}."
-        unet_conversion_map_layer.append((sd_mid_res_prefix, hf_mid_res_prefix))
-
-    unet_conversion_map_resnet = [
-        # (stable-diffusion, HF Diffusers)
-        ("in_layers.0.", "norm1."),
-        ("in_layers.2.", "conv1."),
-        ("out_layers.0.", "norm2."),
-        ("out_layers.3.", "conv2."),
-        ("emb_layers.1.", "time_emb_proj."),
-        ("skip_connection.", "conv_shortcut."),
-    ]
-
-    unet_conversion_map = []
-    for sd, hf in unet_conversion_map_layer:
-        if "resnets" in hf:
-            for sd_res, hf_res in unet_conversion_map_resnet:
-                unet_conversion_map.append((sd + sd_res, hf + hf_res))
-        else:
-            unet_conversion_map.append((sd, hf))
-
-    for j in range(2):
-        hf_time_embed_prefix = f"time_embedding.linear_{j+1}."
-        sd_time_embed_prefix = f"time_embed.{j*2}."
-        unet_conversion_map.append((sd_time_embed_prefix, hf_time_embed_prefix))
-
-    for j in range(2):
-        hf_label_embed_prefix = f"add_embedding.linear_{j+1}."
-        sd_label_embed_prefix = f"label_emb.0.{j*2}."
-        unet_conversion_map.append((sd_label_embed_prefix, hf_label_embed_prefix))
-
-    unet_conversion_map.append(("input_blocks.0.0.", "conv_in."))
-    unet_conversion_map.append(("out.0.", "conv_norm_out."))
-    unet_conversion_map.append(("out.2.", "conv_out."))
-
-    return unet_conversion_map
-
-
-SDXL_UNET_STABILITY_TO_DIFFUSERS_MAP = {
-    sd.rstrip(".").replace(".", "_"): hf.rstrip(".").replace(".", "_") for sd, hf in make_sdxl_unet_conversion_map()
-}
diff --git a/invokeai/backend/model_management_OLD/models/sdxl.py b/invokeai/backend/model_management_OLD/models/sdxl.py
deleted file mode 100644
index 01e9420fed..0000000000
--- a/invokeai/backend/model_management_OLD/models/sdxl.py
+++ /dev/null
@@ -1,148 +0,0 @@
-import json
-import os
-from enum import Enum
-from pathlib import Path
-from typing import Literal, Optional
-
-from omegaconf import OmegaConf
-from pydantic import Field
-
-from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.backend.model_management.detect_baked_in_vae import has_baked_in_sdxl_vae
-from invokeai.backend.util.logging import InvokeAILogger
-
-from .base import (
-    BaseModelType,
-    DiffusersModel,
-    InvalidModelException,
-    ModelConfigBase,
-    ModelType,
-    ModelVariantType,
-    classproperty,
-    read_checkpoint_meta,
-)
-
-
-class StableDiffusionXLModelFormat(str, Enum):
-    Checkpoint = "checkpoint"
-    Diffusers = "diffusers"
-
-
-class StableDiffusionXLModel(DiffusersModel):
-    # TODO: check that configs overwriten properly
-    class DiffusersConfig(ModelConfigBase):
-        model_format: Literal[StableDiffusionXLModelFormat.Diffusers]
-        vae: Optional[str] = Field(None)
-        variant: ModelVariantType
-
-    class CheckpointConfig(ModelConfigBase):
-        model_format: Literal[StableDiffusionXLModelFormat.Checkpoint]
-        vae: Optional[str] = Field(None)
-        config: str
-        variant: ModelVariantType
-
-    def __init__(self, model_path: str, base_model: BaseModelType, model_type: ModelType):
-        assert base_model in {BaseModelType.StableDiffusionXL, BaseModelType.StableDiffusionXLRefiner}
-        assert model_type == ModelType.Main
-        super().__init__(
-            model_path=model_path,
-            base_model=BaseModelType.StableDiffusionXL,
-            model_type=ModelType.Main,
-        )
-
-    @classmethod
-    def probe_config(cls, path: str, **kwargs):
-        model_format = cls.detect_format(path)
-        ckpt_config_path = kwargs.get("config", None)
-        if model_format == StableDiffusionXLModelFormat.Checkpoint:
-            if ckpt_config_path:
-                ckpt_config = OmegaConf.load(ckpt_config_path)
-                in_channels = ckpt_config["model"]["params"]["unet_config"]["params"]["in_channels"]
-
-            else:
-                checkpoint = read_checkpoint_meta(path)
-                checkpoint = checkpoint.get("state_dict", checkpoint)
-                in_channels = checkpoint["model.diffusion_model.input_blocks.0.0.weight"].shape[1]
-
-        elif model_format == StableDiffusionXLModelFormat.Diffusers:
-            unet_config_path = os.path.join(path, "unet", "config.json")
-            if os.path.exists(unet_config_path):
-                with open(unet_config_path, "r") as f:
-                    unet_config = json.loads(f.read())
-                in_channels = unet_config["in_channels"]
-
-            else:
-                raise InvalidModelException(f"{path} is not a recognized Stable Diffusion diffusers model")
-
-        else:
-            raise NotImplementedError(f"Unknown stable diffusion 2.* format: {model_format}")
-
-        if in_channels == 9:
-            variant = ModelVariantType.Inpaint
-        elif in_channels == 5:
-            variant = ModelVariantType.Depth
-        elif in_channels == 4:
-            variant = ModelVariantType.Normal
-        else:
-            raise Exception("Unkown stable diffusion 2.* model format")
-
-        if ckpt_config_path is None:
-            # avoid circular import
-            from .stable_diffusion import _select_ckpt_config
-
-            ckpt_config_path = _select_ckpt_config(kwargs.get("model_base", BaseModelType.StableDiffusionXL), variant)
-
-        return cls.create_config(
-            path=path,
-            model_format=model_format,
-            config=ckpt_config_path,
-            variant=variant,
-        )
-
-    @classproperty
-    def save_to_config(cls) -> bool:
-        return True
-
-    @classmethod
-    def detect_format(cls, model_path: str):
-        if os.path.isdir(model_path):
-            return StableDiffusionXLModelFormat.Diffusers
-        else:
-            return StableDiffusionXLModelFormat.Checkpoint
-
-    @classmethod
-    def convert_if_required(
-        cls,
-        model_path: str,
-        output_path: str,
-        config: ModelConfigBase,
-        base_model: BaseModelType,
-    ) -> str:
-        # The convert script adapted from the diffusers package uses
-        # strings for the base model type. To avoid making too many
-        # source code changes, we simply translate here
-        if Path(output_path).exists():
-            return output_path
-
-        if isinstance(config, cls.CheckpointConfig):
-            from invokeai.backend.model_management.models.stable_diffusion import _convert_ckpt_and_cache
-
-            # Hack in VAE-fp16 fix - If model sdxl-vae-fp16-fix is installed,
-            # then we bake it into the converted model unless there is already
-            # a nonstandard VAE installed.
-            kwargs = {}
-            app_config = InvokeAIAppConfig.get_config()
-            vae_path = app_config.models_path / "sdxl/vae/sdxl-vae-fp16-fix"
-            if vae_path.exists() and not has_baked_in_sdxl_vae(Path(model_path)):
-                InvokeAILogger.get_logger().warning("No baked-in VAE detected. Inserting sdxl-vae-fp16-fix.")
-                kwargs["vae_path"] = vae_path
-
-            return _convert_ckpt_and_cache(
-                version=base_model,
-                model_config=config,
-                output_path=output_path,
-                use_safetensors=True,
-                **kwargs,
-            )
-        else:
-            return model_path
diff --git a/invokeai/backend/model_management_OLD/models/stable_diffusion.py b/invokeai/backend/model_management_OLD/models/stable_diffusion.py
deleted file mode 100644
index a38a44fccf..0000000000
--- a/invokeai/backend/model_management_OLD/models/stable_diffusion.py
+++ /dev/null
@@ -1,337 +0,0 @@
-import json
-import os
-from enum import Enum
-from pathlib import Path
-from typing import Literal, Optional, Union
-
-from diffusers import StableDiffusionInpaintPipeline, StableDiffusionPipeline
-from omegaconf import OmegaConf
-from pydantic import Field
-
-import invokeai.backend.util.logging as logger
-from invokeai.app.services.config import InvokeAIAppConfig
-
-from .base import (
-    BaseModelType,
-    DiffusersModel,
-    InvalidModelException,
-    ModelConfigBase,
-    ModelNotFoundException,
-    ModelType,
-    ModelVariantType,
-    SilenceWarnings,
-    classproperty,
-    read_checkpoint_meta,
-)
-from .sdxl import StableDiffusionXLModel
-
-
-class StableDiffusion1ModelFormat(str, Enum):
-    Checkpoint = "checkpoint"
-    Diffusers = "diffusers"
-
-
-class StableDiffusion1Model(DiffusersModel):
-    class DiffusersConfig(ModelConfigBase):
-        model_format: Literal[StableDiffusion1ModelFormat.Diffusers]
-        vae: Optional[str] = Field(None)
-        variant: ModelVariantType
-
-    class CheckpointConfig(ModelConfigBase):
-        model_format: Literal[StableDiffusion1ModelFormat.Checkpoint]
-        vae: Optional[str] = Field(None)
-        config: str
-        variant: ModelVariantType
-
-    def __init__(self, model_path: str, base_model: BaseModelType, model_type: ModelType):
-        assert base_model == BaseModelType.StableDiffusion1
-        assert model_type == ModelType.Main
-        super().__init__(
-            model_path=model_path,
-            base_model=BaseModelType.StableDiffusion1,
-            model_type=ModelType.Main,
-        )
-
-    @classmethod
-    def probe_config(cls, path: str, **kwargs):
-        model_format = cls.detect_format(path)
-        ckpt_config_path = kwargs.get("config", None)
-        if model_format == StableDiffusion1ModelFormat.Checkpoint:
-            if ckpt_config_path:
-                ckpt_config = OmegaConf.load(ckpt_config_path)
-                ckpt_config["model"]["params"]["unet_config"]["params"]["in_channels"]
-
-            else:
-                checkpoint = read_checkpoint_meta(path)
-                checkpoint = checkpoint.get("state_dict", checkpoint)
-                in_channels = checkpoint["model.diffusion_model.input_blocks.0.0.weight"].shape[1]
-
-        elif model_format == StableDiffusion1ModelFormat.Diffusers:
-            unet_config_path = os.path.join(path, "unet", "config.json")
-            if os.path.exists(unet_config_path):
-                with open(unet_config_path, "r") as f:
-                    unet_config = json.loads(f.read())
-                in_channels = unet_config["in_channels"]
-
-            else:
-                raise NotImplementedError(f"{path} is not a supported stable diffusion diffusers format")
-
-        else:
-            raise NotImplementedError(f"Unknown stable diffusion 1.* format: {model_format}")
-
-        if in_channels == 9:
-            variant = ModelVariantType.Inpaint
-        elif in_channels == 4:
-            variant = ModelVariantType.Normal
-        else:
-            raise Exception("Unkown stable diffusion 1.* model format")
-
-        if ckpt_config_path is None:
-            ckpt_config_path = _select_ckpt_config(BaseModelType.StableDiffusion1, variant)
-
-        return cls.create_config(
-            path=path,
-            model_format=model_format,
-            config=ckpt_config_path,
-            variant=variant,
-        )
-
-    @classproperty
-    def save_to_config(cls) -> bool:
-        return True
-
-    @classmethod
-    def detect_format(cls, model_path: str):
-        if not os.path.exists(model_path):
-            raise ModelNotFoundException()
-
-        if os.path.isdir(model_path):
-            if os.path.exists(os.path.join(model_path, "model_index.json")):
-                return StableDiffusion1ModelFormat.Diffusers
-
-        if os.path.isfile(model_path):
-            if any(model_path.endswith(f".{ext}") for ext in ["safetensors", "ckpt", "pt"]):
-                return StableDiffusion1ModelFormat.Checkpoint
-
-        raise InvalidModelException(f"Not a valid model: {model_path}")
-
-    @classmethod
-    def convert_if_required(
-        cls,
-        model_path: str,
-        output_path: str,
-        config: ModelConfigBase,
-        base_model: BaseModelType,
-    ) -> str:
-        if isinstance(config, cls.CheckpointConfig):
-            return _convert_ckpt_and_cache(
-                version=BaseModelType.StableDiffusion1,
-                model_config=config,
-                load_safety_checker=False,
-                output_path=output_path,
-            )
-        else:
-            return model_path
-
-
-class StableDiffusion2ModelFormat(str, Enum):
-    Checkpoint = "checkpoint"
-    Diffusers = "diffusers"
-
-
-class StableDiffusion2Model(DiffusersModel):
-    # TODO: check that configs overwriten properly
-    class DiffusersConfig(ModelConfigBase):
-        model_format: Literal[StableDiffusion2ModelFormat.Diffusers]
-        vae: Optional[str] = Field(None)
-        variant: ModelVariantType
-
-    class CheckpointConfig(ModelConfigBase):
-        model_format: Literal[StableDiffusion2ModelFormat.Checkpoint]
-        vae: Optional[str] = Field(None)
-        config: str
-        variant: ModelVariantType
-
-    def __init__(self, model_path: str, base_model: BaseModelType, model_type: ModelType):
-        assert base_model == BaseModelType.StableDiffusion2
-        assert model_type == ModelType.Main
-        super().__init__(
-            model_path=model_path,
-            base_model=BaseModelType.StableDiffusion2,
-            model_type=ModelType.Main,
-        )
-
-    @classmethod
-    def probe_config(cls, path: str, **kwargs):
-        model_format = cls.detect_format(path)
-        ckpt_config_path = kwargs.get("config", None)
-        if model_format == StableDiffusion2ModelFormat.Checkpoint:
-            if ckpt_config_path:
-                ckpt_config = OmegaConf.load(ckpt_config_path)
-                ckpt_config["model"]["params"]["unet_config"]["params"]["in_channels"]
-
-            else:
-                checkpoint = read_checkpoint_meta(path)
-                checkpoint = checkpoint.get("state_dict", checkpoint)
-                in_channels = checkpoint["model.diffusion_model.input_blocks.0.0.weight"].shape[1]
-
-        elif model_format == StableDiffusion2ModelFormat.Diffusers:
-            unet_config_path = os.path.join(path, "unet", "config.json")
-            if os.path.exists(unet_config_path):
-                with open(unet_config_path, "r") as f:
-                    unet_config = json.loads(f.read())
-                in_channels = unet_config["in_channels"]
-
-            else:
-                raise Exception("Not supported stable diffusion diffusers format(possibly onnx?)")
-
-        else:
-            raise NotImplementedError(f"Unknown stable diffusion 2.* format: {model_format}")
-
-        if in_channels == 9:
-            variant = ModelVariantType.Inpaint
-        elif in_channels == 5:
-            variant = ModelVariantType.Depth
-        elif in_channels == 4:
-            variant = ModelVariantType.Normal
-        else:
-            raise Exception("Unkown stable diffusion 2.* model format")
-
-        if ckpt_config_path is None:
-            ckpt_config_path = _select_ckpt_config(BaseModelType.StableDiffusion2, variant)
-
-        return cls.create_config(
-            path=path,
-            model_format=model_format,
-            config=ckpt_config_path,
-            variant=variant,
-        )
-
-    @classproperty
-    def save_to_config(cls) -> bool:
-        return True
-
-    @classmethod
-    def detect_format(cls, model_path: str):
-        if not os.path.exists(model_path):
-            raise ModelNotFoundException()
-
-        if os.path.isdir(model_path):
-            if os.path.exists(os.path.join(model_path, "model_index.json")):
-                return StableDiffusion2ModelFormat.Diffusers
-
-        if os.path.isfile(model_path):
-            if any(model_path.endswith(f".{ext}") for ext in ["safetensors", "ckpt", "pt"]):
-                return StableDiffusion2ModelFormat.Checkpoint
-
-        raise InvalidModelException(f"Not a valid model: {model_path}")
-
-    @classmethod
-    def convert_if_required(
-        cls,
-        model_path: str,
-        output_path: str,
-        config: ModelConfigBase,
-        base_model: BaseModelType,
-    ) -> str:
-        if isinstance(config, cls.CheckpointConfig):
-            return _convert_ckpt_and_cache(
-                version=BaseModelType.StableDiffusion2,
-                model_config=config,
-                output_path=output_path,
-            )
-        else:
-            return model_path
-
-
-# TODO: rework
-# pass precision - currently defaulting to fp16
-def _convert_ckpt_and_cache(
-    version: BaseModelType,
-    model_config: Union[
-        StableDiffusion1Model.CheckpointConfig,
-        StableDiffusion2Model.CheckpointConfig,
-        StableDiffusionXLModel.CheckpointConfig,
-    ],
-    output_path: str,
-    use_save_model: bool = False,
-    **kwargs,
-) -> str:
-    """
-    Convert the checkpoint model indicated in mconfig into a
-    diffusers, cache it to disk, and return Path to converted
-    file. If already on disk then just returns Path.
-    """
-    app_config = InvokeAIAppConfig.get_config()
-
-    weights = app_config.models_path / model_config.path
-    config_file = app_config.root_path / model_config.config
-    output_path = Path(output_path)
-    variant = model_config.variant
-    pipeline_class = StableDiffusionInpaintPipeline if variant == "inpaint" else StableDiffusionPipeline
-
-    # return cached version if it exists
-    if output_path.exists():
-        return output_path
-
-    # to avoid circular import errors
-    from ...util.devices import choose_torch_device, torch_dtype
-    from ..convert_ckpt_to_diffusers import convert_ckpt_to_diffusers
-
-    model_base_to_model_type = {
-        BaseModelType.StableDiffusion1: "FrozenCLIPEmbedder",
-        BaseModelType.StableDiffusion2: "FrozenOpenCLIPEmbedder",
-        BaseModelType.StableDiffusionXL: "SDXL",
-        BaseModelType.StableDiffusionXLRefiner: "SDXL-Refiner",
-    }
-    logger.info(f"Converting {weights} to diffusers format")
-    with SilenceWarnings():
-        convert_ckpt_to_diffusers(
-            weights,
-            output_path,
-            model_type=model_base_to_model_type[version],
-            model_version=version,
-            model_variant=model_config.variant,
-            original_config_file=config_file,
-            extract_ema=True,
-            scan_needed=True,
-            pipeline_class=pipeline_class,
-            from_safetensors=weights.suffix == ".safetensors",
-            precision=torch_dtype(choose_torch_device()),
-            **kwargs,
-        )
-    return output_path
-
-
-def _select_ckpt_config(version: BaseModelType, variant: ModelVariantType):
-    ckpt_configs = {
-        BaseModelType.StableDiffusion1: {
-            ModelVariantType.Normal: "v1-inference.yaml",
-            ModelVariantType.Inpaint: "v1-inpainting-inference.yaml",
-        },
-        BaseModelType.StableDiffusion2: {
-            ModelVariantType.Normal: "v2-inference-v.yaml",  # best guess, as we can't differentiate with base(512)
-            ModelVariantType.Inpaint: "v2-inpainting-inference.yaml",
-            ModelVariantType.Depth: "v2-midas-inference.yaml",
-        },
-        BaseModelType.StableDiffusionXL: {
-            ModelVariantType.Normal: "sd_xl_base.yaml",
-            ModelVariantType.Inpaint: None,
-            ModelVariantType.Depth: None,
-        },
-        BaseModelType.StableDiffusionXLRefiner: {
-            ModelVariantType.Normal: "sd_xl_refiner.yaml",
-            ModelVariantType.Inpaint: None,
-            ModelVariantType.Depth: None,
-        },
-    }
-
-    app_config = InvokeAIAppConfig.get_config()
-    try:
-        config_path = app_config.legacy_conf_path / ckpt_configs[version][variant]
-        if config_path.is_relative_to(app_config.root_path):
-            config_path = config_path.relative_to(app_config.root_path)
-        return str(config_path)
-
-    except Exception:
-        return None
diff --git a/invokeai/backend/model_management_OLD/models/stable_diffusion_onnx.py b/invokeai/backend/model_management_OLD/models/stable_diffusion_onnx.py
deleted file mode 100644
index 2d0dd22c43..0000000000
--- a/invokeai/backend/model_management_OLD/models/stable_diffusion_onnx.py
+++ /dev/null
@@ -1,150 +0,0 @@
-from enum import Enum
-from typing import Literal
-
-from diffusers import OnnxRuntimeModel
-
-from .base import (
-    BaseModelType,
-    DiffusersModel,
-    IAIOnnxRuntimeModel,
-    ModelConfigBase,
-    ModelType,
-    ModelVariantType,
-    SchedulerPredictionType,
-    classproperty,
-)
-
-
-class StableDiffusionOnnxModelFormat(str, Enum):
-    Olive = "olive"
-    Onnx = "onnx"
-
-
-class ONNXStableDiffusion1Model(DiffusersModel):
-    class Config(ModelConfigBase):
-        model_format: Literal[StableDiffusionOnnxModelFormat.Onnx]
-        variant: ModelVariantType
-
-    def __init__(self, model_path: str, base_model: BaseModelType, model_type: ModelType):
-        assert base_model == BaseModelType.StableDiffusion1
-        assert model_type == ModelType.ONNX
-        super().__init__(
-            model_path=model_path,
-            base_model=BaseModelType.StableDiffusion1,
-            model_type=ModelType.ONNX,
-        )
-
-        for child_name, child_type in self.child_types.items():
-            if child_type is OnnxRuntimeModel:
-                self.child_types[child_name] = IAIOnnxRuntimeModel
-
-            # TODO: check that no optimum models provided
-
-    @classmethod
-    def probe_config(cls, path: str, **kwargs):
-        model_format = cls.detect_format(path)
-        in_channels = 4  # TODO:
-
-        if in_channels == 9:
-            variant = ModelVariantType.Inpaint
-        elif in_channels == 4:
-            variant = ModelVariantType.Normal
-        else:
-            raise Exception("Unkown stable diffusion 1.* model format")
-
-        return cls.create_config(
-            path=path,
-            model_format=model_format,
-            variant=variant,
-        )
-
-    @classproperty
-    def save_to_config(cls) -> bool:
-        return True
-
-    @classmethod
-    def detect_format(cls, model_path: str):
-        # TODO: Detect onnx vs olive
-        return StableDiffusionOnnxModelFormat.Onnx
-
-    @classmethod
-    def convert_if_required(
-        cls,
-        model_path: str,
-        output_path: str,
-        config: ModelConfigBase,
-        base_model: BaseModelType,
-    ) -> str:
-        return model_path
-
-
-class ONNXStableDiffusion2Model(DiffusersModel):
-    # TODO: check that configs overwriten properly
-    class Config(ModelConfigBase):
-        model_format: Literal[StableDiffusionOnnxModelFormat.Onnx]
-        variant: ModelVariantType
-        prediction_type: SchedulerPredictionType
-        upcast_attention: bool
-
-    def __init__(self, model_path: str, base_model: BaseModelType, model_type: ModelType):
-        assert base_model == BaseModelType.StableDiffusion2
-        assert model_type == ModelType.ONNX
-        super().__init__(
-            model_path=model_path,
-            base_model=BaseModelType.StableDiffusion2,
-            model_type=ModelType.ONNX,
-        )
-
-        for child_name, child_type in self.child_types.items():
-            if child_type is OnnxRuntimeModel:
-                self.child_types[child_name] = IAIOnnxRuntimeModel
-            # TODO: check that no optimum models provided
-
-    @classmethod
-    def probe_config(cls, path: str, **kwargs):
-        model_format = cls.detect_format(path)
-        in_channels = 4  # TODO:
-
-        if in_channels == 9:
-            variant = ModelVariantType.Inpaint
-        elif in_channels == 5:
-            variant = ModelVariantType.Depth
-        elif in_channels == 4:
-            variant = ModelVariantType.Normal
-        else:
-            raise Exception("Unkown stable diffusion 2.* model format")
-
-        if variant == ModelVariantType.Normal:
-            prediction_type = SchedulerPredictionType.VPrediction
-            upcast_attention = True
-
-        else:
-            prediction_type = SchedulerPredictionType.Epsilon
-            upcast_attention = False
-
-        return cls.create_config(
-            path=path,
-            model_format=model_format,
-            variant=variant,
-            prediction_type=prediction_type,
-            upcast_attention=upcast_attention,
-        )
-
-    @classproperty
-    def save_to_config(cls) -> bool:
-        return True
-
-    @classmethod
-    def detect_format(cls, model_path: str):
-        # TODO: Detect onnx vs olive
-        return StableDiffusionOnnxModelFormat.Onnx
-
-    @classmethod
-    def convert_if_required(
-        cls,
-        model_path: str,
-        output_path: str,
-        config: ModelConfigBase,
-        base_model: BaseModelType,
-    ) -> str:
-        return model_path
diff --git a/invokeai/backend/model_management_OLD/models/t2i_adapter.py b/invokeai/backend/model_management_OLD/models/t2i_adapter.py
deleted file mode 100644
index 4adb9901f9..0000000000
--- a/invokeai/backend/model_management_OLD/models/t2i_adapter.py
+++ /dev/null
@@ -1,102 +0,0 @@
-import os
-from enum import Enum
-from typing import Literal, Optional
-
-import torch
-from diffusers import T2IAdapter
-
-from invokeai.backend.model_management.models.base import (
-    BaseModelType,
-    EmptyConfigLoader,
-    InvalidModelException,
-    ModelBase,
-    ModelConfigBase,
-    ModelNotFoundException,
-    ModelType,
-    SubModelType,
-    calc_model_size_by_data,
-    calc_model_size_by_fs,
-    classproperty,
-)
-
-
-class T2IAdapterModelFormat(str, Enum):
-    Diffusers = "diffusers"
-
-
-class T2IAdapterModel(ModelBase):
-    class DiffusersConfig(ModelConfigBase):
-        model_format: Literal[T2IAdapterModelFormat.Diffusers]
-
-    def __init__(self, model_path: str, base_model: BaseModelType, model_type: ModelType):
-        assert model_type == ModelType.T2IAdapter
-        super().__init__(model_path, base_model, model_type)
-
-        config = EmptyConfigLoader.load_config(self.model_path, config_name="config.json")
-
-        model_class_name = config.get("_class_name", None)
-        if model_class_name not in {"T2IAdapter"}:
-            raise InvalidModelException(f"Invalid T2I-Adapter model. Unknown _class_name: '{model_class_name}'.")
-
-        self.model_class = self._hf_definition_to_type(["diffusers", model_class_name])
-        self.model_size = calc_model_size_by_fs(self.model_path)
-
-    def get_size(self, child_type: Optional[SubModelType] = None):
-        if child_type is not None:
-            raise ValueError(f"T2I-Adapters do not have child models. Invalid child type: '{child_type}'.")
-        return self.model_size
-
-    def get_model(
-        self,
-        torch_dtype: Optional[torch.dtype],
-        child_type: Optional[SubModelType] = None,
-    ) -> T2IAdapter:
-        if child_type is not None:
-            raise ValueError(f"T2I-Adapters do not have child models. Invalid child type: '{child_type}'.")
-
-        model = None
-        for variant in ["fp16", None]:
-            try:
-                model = self.model_class.from_pretrained(
-                    self.model_path,
-                    torch_dtype=torch_dtype,
-                    variant=variant,
-                )
-                break
-            except Exception:
-                pass
-        if not model:
-            raise ModelNotFoundException()
-
-        # Calculate a more accurate size after loading the model into memory.
-        self.model_size = calc_model_size_by_data(model)
-        return model
-
-    @classproperty
-    def save_to_config(cls) -> bool:
-        return False
-
-    @classmethod
-    def detect_format(cls, path: str):
-        if not os.path.exists(path):
-            raise ModelNotFoundException(f"Model not found at '{path}'.")
-
-        if os.path.isdir(path):
-            if os.path.exists(os.path.join(path, "config.json")):
-                return T2IAdapterModelFormat.Diffusers
-
-        raise InvalidModelException(f"Unsupported T2I-Adapter format: '{path}'.")
-
-    @classmethod
-    def convert_if_required(
-        cls,
-        model_path: str,
-        output_path: str,
-        config: ModelConfigBase,
-        base_model: BaseModelType,
-    ) -> str:
-        format = cls.detect_format(model_path)
-        if format == T2IAdapterModelFormat.Diffusers:
-            return model_path
-        else:
-            raise ValueError(f"Unsupported format: '{format}'.")
diff --git a/invokeai/backend/model_management_OLD/models/textual_inversion.py b/invokeai/backend/model_management_OLD/models/textual_inversion.py
deleted file mode 100644
index 99358704b8..0000000000
--- a/invokeai/backend/model_management_OLD/models/textual_inversion.py
+++ /dev/null
@@ -1,87 +0,0 @@
-import os
-from typing import Optional
-
-import torch
-
-# TODO: naming
-from ..lora import TextualInversionModel as TextualInversionModelRaw
-from .base import (
-    BaseModelType,
-    InvalidModelException,
-    ModelBase,
-    ModelConfigBase,
-    ModelNotFoundException,
-    ModelType,
-    SubModelType,
-    classproperty,
-)
-
-
-class TextualInversionModel(ModelBase):
-    # model_size: int
-
-    class Config(ModelConfigBase):
-        model_format: None
-
-    def __init__(self, model_path: str, base_model: BaseModelType, model_type: ModelType):
-        assert model_type == ModelType.TextualInversion
-        super().__init__(model_path, base_model, model_type)
-
-        self.model_size = os.path.getsize(self.model_path)
-
-    def get_size(self, child_type: Optional[SubModelType] = None):
-        if child_type is not None:
-            raise Exception("There is no child models in textual inversion")
-        return self.model_size
-
-    def get_model(
-        self,
-        torch_dtype: Optional[torch.dtype],
-        child_type: Optional[SubModelType] = None,
-    ):
-        if child_type is not None:
-            raise Exception("There is no child models in textual inversion")
-
-        checkpoint_path = self.model_path
-        if os.path.isdir(checkpoint_path):
-            checkpoint_path = os.path.join(checkpoint_path, "learned_embeds.bin")
-
-        if not os.path.exists(checkpoint_path):
-            raise ModelNotFoundException()
-
-        model = TextualInversionModelRaw.from_checkpoint(
-            file_path=checkpoint_path,
-            dtype=torch_dtype,
-        )
-
-        self.model_size = model.embedding.nelement() * model.embedding.element_size()
-        return model
-
-    @classproperty
-    def save_to_config(cls) -> bool:
-        return False
-
-    @classmethod
-    def detect_format(cls, path: str):
-        if not os.path.exists(path):
-            raise ModelNotFoundException()
-
-        if os.path.isdir(path):
-            if os.path.exists(os.path.join(path, "learned_embeds.bin")):
-                return None  # diffusers-ti
-
-        if os.path.isfile(path):
-            if any(path.endswith(f".{ext}") for ext in ["safetensors", "ckpt", "pt", "bin"]):
-                return None
-
-        raise InvalidModelException(f"Not a valid model: {path}")
-
-    @classmethod
-    def convert_if_required(
-        cls,
-        model_path: str,
-        output_path: str,
-        config: ModelConfigBase,
-        base_model: BaseModelType,
-    ) -> str:
-        return model_path
diff --git a/invokeai/backend/model_management_OLD/models/vae.py b/invokeai/backend/model_management_OLD/models/vae.py
deleted file mode 100644
index 8cc37e67a7..0000000000
--- a/invokeai/backend/model_management_OLD/models/vae.py
+++ /dev/null
@@ -1,179 +0,0 @@
-import os
-from enum import Enum
-from pathlib import Path
-from typing import Optional
-
-import safetensors
-import torch
-from omegaconf import OmegaConf
-
-from invokeai.app.services.config import InvokeAIAppConfig
-
-from .base import (
-    BaseModelType,
-    EmptyConfigLoader,
-    InvalidModelException,
-    ModelBase,
-    ModelConfigBase,
-    ModelNotFoundException,
-    ModelType,
-    ModelVariantType,
-    SubModelType,
-    calc_model_size_by_data,
-    calc_model_size_by_fs,
-    classproperty,
-)
-
-
-class VaeModelFormat(str, Enum):
-    Checkpoint = "checkpoint"
-    Diffusers = "diffusers"
-
-
-class VaeModel(ModelBase):
-    # vae_class: Type
-    # model_size: int
-
-    class Config(ModelConfigBase):
-        model_format: VaeModelFormat
-
-    def __init__(self, model_path: str, base_model: BaseModelType, model_type: ModelType):
-        assert model_type == ModelType.Vae
-        super().__init__(model_path, base_model, model_type)
-
-        try:
-            config = EmptyConfigLoader.load_config(self.model_path, config_name="config.json")
-            # config = json.loads(os.path.join(self.model_path, "config.json"))
-        except Exception:
-            raise Exception("Invalid vae model! (config.json not found or invalid)")
-
-        try:
-            vae_class_name = config.get("_class_name", "AutoencoderKL")
-            self.vae_class = self._hf_definition_to_type(["diffusers", vae_class_name])
-            self.model_size = calc_model_size_by_fs(self.model_path)
-        except Exception:
-            raise Exception("Invalid vae model! (Unkown vae type)")
-
-    def get_size(self, child_type: Optional[SubModelType] = None):
-        if child_type is not None:
-            raise Exception("There is no child models in vae model")
-        return self.model_size
-
-    def get_model(
-        self,
-        torch_dtype: Optional[torch.dtype],
-        child_type: Optional[SubModelType] = None,
-    ):
-        if child_type is not None:
-            raise Exception("There is no child models in vae model")
-
-        model = self.vae_class.from_pretrained(
-            self.model_path,
-            torch_dtype=torch_dtype,
-        )
-        # calc more accurate size
-        self.model_size = calc_model_size_by_data(model)
-        return model
-
-    @classproperty
-    def save_to_config(cls) -> bool:
-        return False
-
-    @classmethod
-    def detect_format(cls, path: str):
-        if not os.path.exists(path):
-            raise ModelNotFoundException(f"Does not exist as local file: {path}")
-
-        if os.path.isdir(path):
-            if os.path.exists(os.path.join(path, "config.json")):
-                return VaeModelFormat.Diffusers
-
-        if os.path.isfile(path):
-            if any(path.endswith(f".{ext}") for ext in ["safetensors", "ckpt", "pt"]):
-                return VaeModelFormat.Checkpoint
-
-        raise InvalidModelException(f"Not a valid model: {path}")
-
-    @classmethod
-    def convert_if_required(
-        cls,
-        model_path: str,
-        output_path: str,
-        config: ModelConfigBase,  # empty config or config of parent model
-        base_model: BaseModelType,
-    ) -> str:
-        if cls.detect_format(model_path) == VaeModelFormat.Checkpoint:
-            return _convert_vae_ckpt_and_cache(
-                weights_path=model_path,
-                output_path=output_path,
-                base_model=base_model,
-                model_config=config,
-            )
-        else:
-            return model_path
-
-
-# TODO: rework
-def _convert_vae_ckpt_and_cache(
-    weights_path: str,
-    output_path: str,
-    base_model: BaseModelType,
-    model_config: ModelConfigBase,
-) -> str:
-    """
-    Convert the VAE indicated in mconfig into a diffusers AutoencoderKL
-    object, cache it to disk, and return Path to converted
-    file. If already on disk then just returns Path.
-    """
-    app_config = InvokeAIAppConfig.get_config()
-    weights_path = app_config.root_dir / weights_path
-    output_path = Path(output_path)
-
-    """
-    this size used only in when tiling enabled to separate input in tiles
-    sizes in configs from stable diffusion githubs(1 and 2) set to 256
-    on huggingface it:
-    1.5 - 512
-    1.5-inpainting - 256
-    2-inpainting - 512
-    2-depth - 256
-    2-base - 512
-    2 - 768
-    2.1-base - 768
-    2.1 - 768
-    """
-    image_size = 512
-
-    # return cached version if it exists
-    if output_path.exists():
-        return output_path
-
-    if base_model in {BaseModelType.StableDiffusion1, BaseModelType.StableDiffusion2}:
-        from .stable_diffusion import _select_ckpt_config
-
-        # all sd models use same vae settings
-        config_file = _select_ckpt_config(base_model, ModelVariantType.Normal)
-    else:
-        raise Exception(f"Vae conversion not supported for model type: {base_model}")
-
-    # this avoids circular import error
-    from ..convert_ckpt_to_diffusers import convert_ldm_vae_to_diffusers
-
-    if weights_path.suffix == ".safetensors":
-        checkpoint = safetensors.torch.load_file(weights_path, device="cpu")
-    else:
-        checkpoint = torch.load(weights_path, map_location="cpu")
-
-    # sometimes weights are hidden under "state_dict", and sometimes not
-    if "state_dict" in checkpoint:
-        checkpoint = checkpoint["state_dict"]
-
-    config = OmegaConf.load(app_config.root_path / config_file)
-
-    vae_model = convert_ldm_vae_to_diffusers(
-        checkpoint=checkpoint,
-        vae_config=config,
-        image_size=image_size,
-    )
-    vae_model.save_pretrained(output_path, safe_serialization=True)
-    return output_path
diff --git a/invokeai/backend/model_management_OLD/seamless.py b/invokeai/backend/model_management_OLD/seamless.py
deleted file mode 100644
index fb9112b56d..0000000000
--- a/invokeai/backend/model_management_OLD/seamless.py
+++ /dev/null
@@ -1,84 +0,0 @@
-from __future__ import annotations
-
-from contextlib import contextmanager
-from typing import Callable, List, Union
-
-import torch.nn as nn
-from diffusers.models.autoencoders.autoencoder_kl import AutoencoderKL
-from diffusers.models.unets.unet_2d_condition import UNet2DConditionModel
-
-
-def _conv_forward_asymmetric(self, input, weight, bias):
-    """
-    Patch for Conv2d._conv_forward that supports asymmetric padding
-    """
-    working = nn.functional.pad(input, self.asymmetric_padding["x"], mode=self.asymmetric_padding_mode["x"])
-    working = nn.functional.pad(working, self.asymmetric_padding["y"], mode=self.asymmetric_padding_mode["y"])
-    return nn.functional.conv2d(
-        working,
-        weight,
-        bias,
-        self.stride,
-        nn.modules.utils._pair(0),
-        self.dilation,
-        self.groups,
-    )
-
-
-@contextmanager
-def set_seamless(model: Union[UNet2DConditionModel, AutoencoderKL], seamless_axes: List[str]):
-    # Callable: (input: Tensor, weight: Tensor, bias: Optional[Tensor]) -> Tensor
-    to_restore: list[tuple[nn.Conv2d | nn.ConvTranspose2d, Callable]] = []
-    try:
-        # Hard coded to skip down block layers, allowing for seamless tiling at the expense of prompt adherence
-        skipped_layers = 1
-        for m_name, m in model.named_modules():
-            if not isinstance(m, (nn.Conv2d, nn.ConvTranspose2d)):
-                continue
-
-            if isinstance(model, UNet2DConditionModel) and m_name.startswith("down_blocks.") and ".resnets." in m_name:
-                # down_blocks.1.resnets.1.conv1
-                _, block_num, _, resnet_num, submodule_name = m_name.split(".")
-                block_num = int(block_num)
-                resnet_num = int(resnet_num)
-
-                if block_num >= len(model.down_blocks) - skipped_layers:
-                    continue
-
-                # Skip the second resnet (could be configurable)
-                if resnet_num > 0:
-                    continue
-
-                # Skip Conv2d layers (could be configurable)
-                if submodule_name == "conv2":
-                    continue
-
-            m.asymmetric_padding_mode = {}
-            m.asymmetric_padding = {}
-            m.asymmetric_padding_mode["x"] = "circular" if ("x" in seamless_axes) else "constant"
-            m.asymmetric_padding["x"] = (
-                m._reversed_padding_repeated_twice[0],
-                m._reversed_padding_repeated_twice[1],
-                0,
-                0,
-            )
-            m.asymmetric_padding_mode["y"] = "circular" if ("y" in seamless_axes) else "constant"
-            m.asymmetric_padding["y"] = (
-                0,
-                0,
-                m._reversed_padding_repeated_twice[2],
-                m._reversed_padding_repeated_twice[3],
-            )
-
-            to_restore.append((m, m._conv_forward))
-            m._conv_forward = _conv_forward_asymmetric.__get__(m, nn.Conv2d)
-
-        yield
-
-    finally:
-        for module, orig_conv_forward in to_restore:
-            module._conv_forward = orig_conv_forward
-            if hasattr(module, "asymmetric_padding_mode"):
-                del module.asymmetric_padding_mode
-            if hasattr(module, "asymmetric_padding"):
-                del module.asymmetric_padding
diff --git a/invokeai/backend/model_management_OLD/util.py b/invokeai/backend/model_management_OLD/util.py
deleted file mode 100644
index f4737d9f0b..0000000000
--- a/invokeai/backend/model_management_OLD/util.py
+++ /dev/null
@@ -1,79 +0,0 @@
-# Copyright (c) 2023 The InvokeAI Development Team
-"""Utilities used by the Model Manager"""
-
-
-def lora_token_vector_length(checkpoint: dict) -> int:
-    """
-    Given a checkpoint in memory, return the lora token vector length
-
-    :param checkpoint: The checkpoint
-    """
-
-    def _get_shape_1(key: str, tensor, checkpoint) -> int:
-        lora_token_vector_length = None
-
-        if "." not in key:
-            return lora_token_vector_length  # wrong key format
-        model_key, lora_key = key.split(".", 1)
-
-        # check lora/locon
-        if lora_key == "lora_down.weight":
-            lora_token_vector_length = tensor.shape[1]
-
-        # check loha (don't worry about hada_t1/hada_t2 as it used only in 4d shapes)
-        elif lora_key in ["hada_w1_b", "hada_w2_b"]:
-            lora_token_vector_length = tensor.shape[1]
-
-        # check lokr (don't worry about lokr_t2 as it used only in 4d shapes)
-        elif "lokr_" in lora_key:
-            if model_key + ".lokr_w1" in checkpoint:
-                _lokr_w1 = checkpoint[model_key + ".lokr_w1"]
-            elif model_key + "lokr_w1_b" in checkpoint:
-                _lokr_w1 = checkpoint[model_key + ".lokr_w1_b"]
-            else:
-                return lora_token_vector_length  # unknown format
-
-            if model_key + ".lokr_w2" in checkpoint:
-                _lokr_w2 = checkpoint[model_key + ".lokr_w2"]
-            elif model_key + "lokr_w2_b" in checkpoint:
-                _lokr_w2 = checkpoint[model_key + ".lokr_w2_b"]
-            else:
-                return lora_token_vector_length  # unknown format
-
-            lora_token_vector_length = _lokr_w1.shape[1] * _lokr_w2.shape[1]
-
-        elif lora_key == "diff":
-            lora_token_vector_length = tensor.shape[1]
-
-        # ia3 can be detected only by shape[0] in text encoder
-        elif lora_key == "weight" and "lora_unet_" not in model_key:
-            lora_token_vector_length = tensor.shape[0]
-
-        return lora_token_vector_length
-
-    lora_token_vector_length = None
-    lora_te1_length = None
-    lora_te2_length = None
-    for key, tensor in checkpoint.items():
-        if key.startswith("lora_unet_") and ("_attn2_to_k." in key or "_attn2_to_v." in key):
-            lora_token_vector_length = _get_shape_1(key, tensor, checkpoint)
-        elif key.startswith("lora_unet_") and (
-            "time_emb_proj.lora_down" in key
-        ):  # recognizes format at https://civitai.com/models/224641
-            lora_token_vector_length = _get_shape_1(key, tensor, checkpoint)
-        elif key.startswith("lora_te") and "_self_attn_" in key:
-            tmp_length = _get_shape_1(key, tensor, checkpoint)
-            if key.startswith("lora_te_"):
-                lora_token_vector_length = tmp_length
-            elif key.startswith("lora_te1_"):
-                lora_te1_length = tmp_length
-            elif key.startswith("lora_te2_"):
-                lora_te2_length = tmp_length
-
-        if lora_te1_length is not None and lora_te2_length is not None:
-            lora_token_vector_length = lora_te1_length + lora_te2_length
-
-        if lora_token_vector_length is not None:
-            break
-
-    return lora_token_vector_length
diff --git a/invokeai/backend/model_manager/__init__.py b/invokeai/backend/model_manager/__init__.py
index 98cc5054c7..88356d0468 100644
--- a/invokeai/backend/model_manager/__init__.py
+++ b/invokeai/backend/model_manager/__init__.py
@@ -1,5 +1,4 @@
 """Re-export frequently-used symbols from the Model Manager backend."""
-
 from .config import (
     AnyModel,
     AnyModelConfig,
@@ -33,3 +32,42 @@ __all__ = [
     "SchedulerPredictionType",
     "SubModelType",
 ]
+
+########## to help populate the openapi_schema with format enums for each config ###########
+# This code is no longer necessary?
+# leave it here just in case
+#
+# import inspect
+# from enum import Enum
+# from typing import Any, Iterable, Dict, get_args, Set
+# def _expand(something: Any) -> Iterable[type]:
+#     if isinstance(something, type):
+#         yield something
+#     else:
+#         for x in get_args(something):
+#             for y in _expand(x):
+#                 yield y
+
+# def _find_format(cls: type) -> Iterable[Enum]:
+#     if hasattr(inspect, "get_annotations"):
+#         fields = inspect.get_annotations(cls)
+#     else:
+#         fields = cls.__annotations__
+#     if "format" in fields:
+#         for x in get_args(fields["format"]):
+#             yield x
+#     for parent_class in cls.__bases__:
+#         for x in _find_format(parent_class):
+#             yield x
+#     return None
+
+# def get_model_config_formats() -> Dict[str, Set[Enum]]:
+#     result: Dict[str, Set[Enum]] = {}
+#     for model_config in _expand(AnyModelConfig):
+#         for field in _find_format(model_config):
+#             if field is None:
+#                 continue
+#             if not result.get(model_config.__qualname__):
+#                 result[model_config.__qualname__] = set()
+#             result[model_config.__qualname__].add(field)
+#     return result
diff --git a/invokeai/backend/model_manager/load/__init__.py b/invokeai/backend/model_manager/load/__init__.py
index a3a840b625..a0421017db 100644
--- a/invokeai/backend/model_manager/load/__init__.py
+++ b/invokeai/backend/model_manager/load/__init__.py
@@ -6,12 +6,22 @@ from importlib import import_module
 from pathlib import Path
 
 from .convert_cache.convert_cache_default import ModelConvertCache
-from .load_base import AnyModelLoader, LoadedModel
+from .load_base import LoadedModel, ModelLoaderBase
+from .load_default import ModelLoader
 from .model_cache.model_cache_default import ModelCache
+from .model_loader_registry import ModelLoaderRegistry, ModelLoaderRegistryBase
 
 # This registers the subclasses that implement loaders of specific model types
 loaders = [x.stem for x in Path(Path(__file__).parent, "model_loaders").glob("*.py") if x.stem != "__init__"]
 for module in loaders:
     import_module(f"{__package__}.model_loaders.{module}")
 
-__all__ = ["AnyModelLoader", "LoadedModel", "ModelCache", "ModelConvertCache"]
+__all__ = [
+    "LoadedModel",
+    "ModelCache",
+    "ModelConvertCache",
+    "ModelLoaderBase",
+    "ModelLoader",
+    "ModelLoaderRegistryBase",
+    "ModelLoaderRegistry",
+]
diff --git a/invokeai/backend/model_manager/load/load_base.py b/invokeai/backend/model_manager/load/load_base.py
index 4c5e899aa3..b8ce56eb16 100644
--- a/invokeai/backend/model_manager/load/load_base.py
+++ b/invokeai/backend/model_manager/load/load_base.py
@@ -1,37 +1,22 @@
 # Copyright (c) 2024, Lincoln D. Stein and the InvokeAI Development Team
 """
 Base class for model loading in InvokeAI.
-
-Use like this:
-
-  loader = AnyModelLoader(...)
-  loaded_model = loader.get_model('019ab39adfa1840455')
-  with loaded_model as model:  # context manager moves model into VRAM
-       # do something with loaded_model
 """
 
-import hashlib
 from abc import ABC, abstractmethod
 from dataclasses import dataclass
 from logging import Logger
 from pathlib import Path
-from typing import Any, Callable, Dict, Optional, Tuple, Type
+from typing import Any, Optional
 
 from invokeai.app.services.config import InvokeAIAppConfig
 from invokeai.backend.model_manager.config import (
     AnyModel,
     AnyModelConfig,
-    BaseModelType,
-    ModelConfigBase,
-    ModelFormat,
-    ModelType,
     SubModelType,
-    VaeCheckpointConfig,
-    VaeDiffusersConfig,
 )
 from invokeai.backend.model_manager.load.convert_cache.convert_cache_base import ModelConvertCacheBase
 from invokeai.backend.model_manager.load.model_cache.model_cache_base import ModelCacheBase, ModelLockerBase
-from invokeai.backend.util.logging import InvokeAILogger
 
 
 @dataclass
@@ -56,6 +41,14 @@ class LoadedModel:
         return self._locker.model
 
 
+# TODO(MM2):
+# Some "intermediary" subclasses in the ModelLoaderBase class hierarchy define methods that their subclasses don't
+# know about. I think the problem may be related to this class being an ABC.
+#
+# For example, GenericDiffusersLoader defines `get_hf_load_class()`, and StableDiffusionDiffusersModel attempts to
+# call it. However, the method is not defined in the ABC, so it is not guaranteed to be implemented.
+
+
 class ModelLoaderBase(ABC):
     """Abstract base class for loading models into RAM/VRAM."""
 
@@ -71,7 +64,7 @@ class ModelLoaderBase(ABC):
         pass
 
     @abstractmethod
-    def load_model(self, model_config: ModelConfigBase, submodel_type: Optional[SubModelType] = None) -> LoadedModel:
+    def load_model(self, model_config: AnyModelConfig, submodel_type: Optional[SubModelType] = None) -> LoadedModel:
         """
         Return a model given its confguration.
 
@@ -90,106 +83,3 @@ class ModelLoaderBase(ABC):
     ) -> int:
         """Return size in bytes of the model, calculated before loading."""
         pass
-
-
-# TO DO: Better name?
-class AnyModelLoader:
-    """This class manages the model loaders and invokes the correct one to load a model of given base and type."""
-
-    # this tracks the loader subclasses
-    _registry: Dict[str, Type[ModelLoaderBase]] = {}
-    _logger: Logger = InvokeAILogger.get_logger()
-
-    def __init__(
-        self,
-        app_config: InvokeAIAppConfig,
-        logger: Logger,
-        ram_cache: ModelCacheBase[AnyModel],
-        convert_cache: ModelConvertCacheBase,
-    ):
-        """Initialize AnyModelLoader with its dependencies."""
-        self._app_config = app_config
-        self._logger = logger
-        self._ram_cache = ram_cache
-        self._convert_cache = convert_cache
-
-    @property
-    def ram_cache(self) -> ModelCacheBase[AnyModel]:
-        """Return the RAM cache associated used by the loaders."""
-        return self._ram_cache
-
-    @property
-    def convert_cache(self) -> ModelConvertCacheBase:
-        """Return the convert cache associated used by the loaders."""
-        return self._convert_cache
-
-    def load_model(self, model_config: ModelConfigBase, submodel_type: Optional[SubModelType] = None) -> LoadedModel:
-        """
-        Return a model given its configuration.
-
-        :param key: model key, as known to the config backend
-        :param submodel_type: an ModelType enum indicating the portion of
-               the model to retrieve (e.g. ModelType.Vae)
-        """
-        implementation, model_config, submodel_type = self.__class__.get_implementation(model_config, submodel_type)
-        return implementation(
-            app_config=self._app_config,
-            logger=self._logger,
-            ram_cache=self._ram_cache,
-            convert_cache=self._convert_cache,
-        ).load_model(model_config, submodel_type)
-
-    @staticmethod
-    def _to_registry_key(base: BaseModelType, type: ModelType, format: ModelFormat) -> str:
-        return "-".join([base.value, type.value, format.value])
-
-    @classmethod
-    def get_implementation(
-        cls, config: ModelConfigBase, submodel_type: Optional[SubModelType]
-    ) -> Tuple[Type[ModelLoaderBase], ModelConfigBase, Optional[SubModelType]]:
-        """Get subclass of ModelLoaderBase registered to handle base and type."""
-        # We have to handle VAE overrides here because this will change the model type and the corresponding implementation returned
-        conf2, submodel_type = cls._handle_subtype_overrides(config, submodel_type)
-
-        key1 = cls._to_registry_key(conf2.base, conf2.type, conf2.format)  # for a specific base type
-        key2 = cls._to_registry_key(BaseModelType.Any, conf2.type, conf2.format)  # with wildcard Any
-        implementation = cls._registry.get(key1) or cls._registry.get(key2)
-        if not implementation:
-            raise NotImplementedError(
-                f"No subclass of LoadedModel is registered for base={config.base}, type={config.type}, format={config.format}"
-            )
-        return implementation, conf2, submodel_type
-
-    @classmethod
-    def _handle_subtype_overrides(
-        cls, config: ModelConfigBase, submodel_type: Optional[SubModelType]
-    ) -> Tuple[ModelConfigBase, Optional[SubModelType]]:
-        if submodel_type == SubModelType.Vae and hasattr(config, "vae") and config.vae is not None:
-            model_path = Path(config.vae)
-            config_class = (
-                VaeCheckpointConfig if model_path.suffix in [".pt", ".safetensors", ".ckpt"] else VaeDiffusersConfig
-            )
-            hash = hashlib.md5(model_path.as_posix().encode("utf-8")).hexdigest()
-            new_conf = config_class(path=model_path.as_posix(), name=model_path.stem, base=config.base, key=hash)
-            submodel_type = None
-        else:
-            new_conf = config
-        return new_conf, submodel_type
-
-    @classmethod
-    def register(
-        cls, type: ModelType, format: ModelFormat, base: BaseModelType = BaseModelType.Any
-    ) -> Callable[[Type[ModelLoaderBase]], Type[ModelLoaderBase]]:
-        """Define a decorator which registers the subclass of loader."""
-
-        def decorator(subclass: Type[ModelLoaderBase]) -> Type[ModelLoaderBase]:
-            cls._logger.debug(f"Registering class {subclass.__name__} to load models of type {base}/{type}/{format}")
-            key = cls._to_registry_key(base, type, format)
-            if key in cls._registry:
-                raise Exception(
-                    f"{subclass.__name__} is trying to register as a loader for {base}/{type}/{format}, but this type of model has already been registered by {cls._registry[key].__name__}"
-                )
-            cls._registry[key] = subclass
-            return subclass
-
-        return decorator
diff --git a/invokeai/backend/model_manager/load/load_default.py b/invokeai/backend/model_manager/load/load_default.py
index 79c9311de1..642cffaf4b 100644
--- a/invokeai/backend/model_manager/load/load_default.py
+++ b/invokeai/backend/model_manager/load/load_default.py
@@ -1,13 +1,9 @@
 # Copyright (c) 2024, Lincoln D. Stein and the InvokeAI Development Team
 """Default implementation of model loading in InvokeAI."""
 
-import sys
 from logging import Logger
 from pathlib import Path
-from typing import Any, Dict, Optional, Tuple
-
-from diffusers import ModelMixin
-from diffusers.configuration_utils import ConfigMixin
+from typing import Optional, Tuple
 
 from invokeai.app.services.config import InvokeAIAppConfig
 from invokeai.backend.model_manager import (
@@ -25,17 +21,6 @@ from invokeai.backend.model_manager.load.optimizations import skip_torch_weight_
 from invokeai.backend.util.devices import choose_torch_device, torch_dtype
 
 
-class ConfigLoader(ConfigMixin):
-    """Subclass of ConfigMixin for loading diffusers configuration files."""
-
-    @classmethod
-    def load_config(cls, *args: Any, **kwargs: Any) -> Dict[str, Any]:
-        """Load a diffusrs ConfigMixin configuration."""
-        cls.config_name = kwargs.pop("config_name")
-        # Diffusers doesn't provide typing info
-        return super().load_config(*args, **kwargs)  # type: ignore
-
-
 # TO DO: The loader is not thread safe!
 class ModelLoader(ModelLoaderBase):
     """Default implementation of ModelLoaderBase."""
@@ -137,43 +122,6 @@ class ModelLoader(ModelLoaderBase):
             variant=config.repo_variant if hasattr(config, "repo_variant") else None,
         )
 
-    def _load_diffusers_config(self, model_path: Path, config_name: str = "config.json") -> Dict[str, Any]:
-        return ConfigLoader.load_config(model_path, config_name=config_name)
-
-    # TO DO: Add exception handling
-    def _hf_definition_to_type(self, module: str, class_name: str) -> ModelMixin:  # fix with correct type
-        if module in ["diffusers", "transformers"]:
-            res_type = sys.modules[module]
-        else:
-            res_type = sys.modules["diffusers"].pipelines
-        result: ModelMixin = getattr(res_type, class_name)
-        return result
-
-    # TO DO: Add exception handling
-    def _get_hf_load_class(self, model_path: Path, submodel_type: Optional[SubModelType] = None) -> ModelMixin:
-        if submodel_type:
-            try:
-                config = self._load_diffusers_config(model_path, config_name="model_index.json")
-                module, class_name = config[submodel_type.value]
-                return self._hf_definition_to_type(module=module, class_name=class_name)
-            except KeyError as e:
-                raise InvalidModelConfigException(
-                    f'The "{submodel_type}" submodel is not available for this model.'
-                ) from e
-        else:
-            try:
-                config = self._load_diffusers_config(model_path, config_name="config.json")
-                class_name = config.get("_class_name", None)
-                if class_name:
-                    return self._hf_definition_to_type(module="diffusers", class_name=class_name)
-                if config.get("model_type", None) == "clip_vision_model":
-                    class_name = config.get("architectures")[0]
-                    return self._hf_definition_to_type(module="transformers", class_name=class_name)
-                if not class_name:
-                    raise InvalidModelConfigException("Unable to decifer Load Class based on given config.json")
-            except KeyError as e:
-                raise InvalidModelConfigException("An expected config.json file is missing from this model.") from e
-
     # This needs to be implemented in subclasses that handle checkpoints
     def _convert_model(self, config: AnyModelConfig, model_path: Path, output_path: Path) -> Path:
         raise NotImplementedError
diff --git a/invokeai/backend/model_manager/load/memory_snapshot.py b/invokeai/backend/model_manager/load/memory_snapshot.py
index 209d7166f3..195e39361b 100644
--- a/invokeai/backend/model_manager/load/memory_snapshot.py
+++ b/invokeai/backend/model_manager/load/memory_snapshot.py
@@ -55,7 +55,7 @@ class MemorySnapshot:
             vram = None
 
         try:
-            malloc_info = LibcUtil().mallinfo2()  # type: ignore
+            malloc_info = LibcUtil().mallinfo2()
         except (OSError, AttributeError):
             # OSError: This is expected in environments that do not have the 'libc.so.6' shared library.
             # AttributeError: This is expected in environments that have `libc.so.6` but do not have the `mallinfo2` (e.g. glibc < 2.33)
diff --git a/invokeai/backend/model_manager/load/model_loader_registry.py b/invokeai/backend/model_manager/load/model_loader_registry.py
new file mode 100644
index 0000000000..ce1110e749
--- /dev/null
+++ b/invokeai/backend/model_manager/load/model_loader_registry.py
@@ -0,0 +1,122 @@
+# Copyright (c) 2024 Lincoln D. Stein and the InvokeAI Development team
+"""
+This module implements a system in which model loaders register the
+type, base and format of models that they know how to load.
+
+Use like this:
+
+  cls, model_config, submodel_type = ModelLoaderRegistry.get_implementation(model_config, submodel_type)  # type: ignore
+  loaded_model = cls(
+       app_config=app_config,
+       logger=logger,
+       ram_cache=ram_cache,
+       convert_cache=convert_cache
+    ).load_model(model_config, submodel_type)
+
+"""
+import hashlib
+from abc import ABC, abstractmethod
+from pathlib import Path
+from typing import Callable, Dict, Optional, Tuple, Type
+
+from ..config import (
+    AnyModelConfig,
+    BaseModelType,
+    ModelConfigBase,
+    ModelFormat,
+    ModelType,
+    SubModelType,
+    VaeCheckpointConfig,
+    VaeDiffusersConfig,
+)
+from . import ModelLoaderBase
+
+
+class ModelLoaderRegistryBase(ABC):
+    """This class allows model loaders to register their type, base and format."""
+
+    @classmethod
+    @abstractmethod
+    def register(
+        cls, type: ModelType, format: ModelFormat, base: BaseModelType = BaseModelType.Any
+    ) -> Callable[[Type[ModelLoaderBase]], Type[ModelLoaderBase]]:
+        """Define a decorator which registers the subclass of loader."""
+
+    @classmethod
+    @abstractmethod
+    def get_implementation(
+        cls, config: AnyModelConfig, submodel_type: Optional[SubModelType]
+    ) -> Tuple[Type[ModelLoaderBase], ModelConfigBase, Optional[SubModelType]]:
+        """
+        Get subclass of ModelLoaderBase registered to handle base and type.
+
+        Parameters:
+        :param config: Model configuration record, as returned by ModelRecordService
+        :param submodel_type: Submodel to fetch (main models only)
+        :return: tuple(loader_class, model_config, submodel_type)
+
+        Note that the returned model config may be different from one what passed
+        in, in the event that a submodel type is provided.
+        """
+
+
+class ModelLoaderRegistry:
+    """
+    This class allows model loaders to register their type, base and format.
+    """
+
+    _registry: Dict[str, Type[ModelLoaderBase]] = {}
+
+    @classmethod
+    def register(
+        cls, type: ModelType, format: ModelFormat, base: BaseModelType = BaseModelType.Any
+    ) -> Callable[[Type[ModelLoaderBase]], Type[ModelLoaderBase]]:
+        """Define a decorator which registers the subclass of loader."""
+
+        def decorator(subclass: Type[ModelLoaderBase]) -> Type[ModelLoaderBase]:
+            key = cls._to_registry_key(base, type, format)
+            if key in cls._registry:
+                raise Exception(
+                    f"{subclass.__name__} is trying to register as a loader for {base}/{type}/{format}, but this type of model has already been registered by {cls._registry[key].__name__}"
+                )
+            cls._registry[key] = subclass
+            return subclass
+
+        return decorator
+
+    @classmethod
+    def get_implementation(
+        cls, config: AnyModelConfig, submodel_type: Optional[SubModelType]
+    ) -> Tuple[Type[ModelLoaderBase], ModelConfigBase, Optional[SubModelType]]:
+        """Get subclass of ModelLoaderBase registered to handle base and type."""
+        # We have to handle VAE overrides here because this will change the model type and the corresponding implementation returned
+        conf2, submodel_type = cls._handle_subtype_overrides(config, submodel_type)
+
+        key1 = cls._to_registry_key(conf2.base, conf2.type, conf2.format)  # for a specific base type
+        key2 = cls._to_registry_key(BaseModelType.Any, conf2.type, conf2.format)  # with wildcard Any
+        implementation = cls._registry.get(key1) or cls._registry.get(key2)
+        if not implementation:
+            raise NotImplementedError(
+                f"No subclass of LoadedModel is registered for base={config.base}, type={config.type}, format={config.format}"
+            )
+        return implementation, conf2, submodel_type
+
+    @classmethod
+    def _handle_subtype_overrides(
+        cls, config: AnyModelConfig, submodel_type: Optional[SubModelType]
+    ) -> Tuple[ModelConfigBase, Optional[SubModelType]]:
+        if submodel_type == SubModelType.Vae and hasattr(config, "vae") and config.vae is not None:
+            model_path = Path(config.vae)
+            config_class = (
+                VaeCheckpointConfig if model_path.suffix in [".pt", ".safetensors", ".ckpt"] else VaeDiffusersConfig
+            )
+            hash = hashlib.md5(model_path.as_posix().encode("utf-8")).hexdigest()
+            new_conf = config_class(path=model_path.as_posix(), name=model_path.stem, base=config.base, key=hash)
+            submodel_type = None
+        else:
+            new_conf = config
+        return new_conf, submodel_type
+
+    @staticmethod
+    def _to_registry_key(base: BaseModelType, type: ModelType, format: ModelFormat) -> str:
+        return "-".join([base.value, type.value, format.value])
diff --git a/invokeai/backend/model_manager/load/model_loaders/controlnet.py b/invokeai/backend/model_manager/load/model_loaders/controlnet.py
index d446d07933..43393f5a84 100644
--- a/invokeai/backend/model_manager/load/model_loaders/controlnet.py
+++ b/invokeai/backend/model_manager/load/model_loaders/controlnet.py
@@ -13,13 +13,13 @@ from invokeai.backend.model_manager import (
     ModelType,
 )
 from invokeai.backend.model_manager.convert_ckpt_to_diffusers import convert_controlnet_to_diffusers
-from invokeai.backend.model_manager.load.load_base import AnyModelLoader
 
+from .. import ModelLoaderRegistry
 from .generic_diffusers import GenericDiffusersLoader
 
 
-@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.ControlNet, format=ModelFormat.Diffusers)
-@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.ControlNet, format=ModelFormat.Checkpoint)
+@ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.ControlNet, format=ModelFormat.Diffusers)
+@ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.ControlNet, format=ModelFormat.Checkpoint)
 class ControlnetLoader(GenericDiffusersLoader):
     """Class to load ControlNet models."""
 
diff --git a/invokeai/backend/model_manager/load/model_loaders/generic_diffusers.py b/invokeai/backend/model_manager/load/model_loaders/generic_diffusers.py
index 114e317f3c..9a9b25aec5 100644
--- a/invokeai/backend/model_manager/load/model_loaders/generic_diffusers.py
+++ b/invokeai/backend/model_manager/load/model_loaders/generic_diffusers.py
@@ -1,24 +1,27 @@
 # Copyright (c) 2024, Lincoln D. Stein and the InvokeAI Development Team
 """Class for simple diffusers model loading in InvokeAI."""
 
+import sys
 from pathlib import Path
-from typing import Optional
+from typing import Any, Dict, Optional
+
+from diffusers import ConfigMixin, ModelMixin
 
 from invokeai.backend.model_manager import (
     AnyModel,
     BaseModelType,
+    InvalidModelConfigException,
     ModelFormat,
     ModelRepoVariant,
     ModelType,
     SubModelType,
 )
 
-from ..load_base import AnyModelLoader
-from ..load_default import ModelLoader
+from .. import ModelLoader, ModelLoaderRegistry
 
 
-@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.CLIPVision, format=ModelFormat.Diffusers)
-@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.T2IAdapter, format=ModelFormat.Diffusers)
+@ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.CLIPVision, format=ModelFormat.Diffusers)
+@ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.T2IAdapter, format=ModelFormat.Diffusers)
 class GenericDiffusersLoader(ModelLoader):
     """Class to load simple diffusers models."""
 
@@ -28,9 +31,60 @@ class GenericDiffusersLoader(ModelLoader):
         model_variant: Optional[ModelRepoVariant] = None,
         submodel_type: Optional[SubModelType] = None,
     ) -> AnyModel:
-        model_class = self._get_hf_load_class(model_path)
+        model_class = self.get_hf_load_class(model_path)
         if submodel_type is not None:
             raise Exception(f"There are no submodels in models of type {model_class}")
         variant = model_variant.value if model_variant else None
         result: AnyModel = model_class.from_pretrained(model_path, torch_dtype=self._torch_dtype, variant=variant)  # type: ignore
         return result
+
+    # TO DO: Add exception handling
+    def get_hf_load_class(self, model_path: Path, submodel_type: Optional[SubModelType] = None) -> ModelMixin:
+        """Given the model path and submodel, returns the diffusers ModelMixin subclass needed to load."""
+        if submodel_type:
+            try:
+                config = self._load_diffusers_config(model_path, config_name="model_index.json")
+                module, class_name = config[submodel_type.value]
+                result = self._hf_definition_to_type(module=module, class_name=class_name)
+            except KeyError as e:
+                raise InvalidModelConfigException(
+                    f'The "{submodel_type}" submodel is not available for this model.'
+                ) from e
+        else:
+            try:
+                config = self._load_diffusers_config(model_path, config_name="config.json")
+                class_name = config.get("_class_name", None)
+                if class_name:
+                    result = self._hf_definition_to_type(module="diffusers", class_name=class_name)
+                if config.get("model_type", None) == "clip_vision_model":
+                    class_name = config.get("architectures")
+                    assert class_name is not None
+                    result = self._hf_definition_to_type(module="transformers", class_name=class_name[0])
+                if not class_name:
+                    raise InvalidModelConfigException("Unable to decifer Load Class based on given config.json")
+            except KeyError as e:
+                raise InvalidModelConfigException("An expected config.json file is missing from this model.") from e
+        return result
+
+    # TO DO: Add exception handling
+    def _hf_definition_to_type(self, module: str, class_name: str) -> ModelMixin:  # fix with correct type
+        if module in ["diffusers", "transformers"]:
+            res_type = sys.modules[module]
+        else:
+            res_type = sys.modules["diffusers"].pipelines
+        result: ModelMixin = getattr(res_type, class_name)
+        return result
+
+    def _load_diffusers_config(self, model_path: Path, config_name: str = "config.json") -> Dict[str, Any]:
+        return ConfigLoader.load_config(model_path, config_name=config_name)
+
+
+class ConfigLoader(ConfigMixin):
+    """Subclass of ConfigMixin for loading diffusers configuration files."""
+
+    @classmethod
+    def load_config(cls, *args: Any, **kwargs: Any) -> Dict[str, Any]:
+        """Load a diffusrs ConfigMixin configuration."""
+        cls.config_name = kwargs.pop("config_name")
+        # Diffusers doesn't provide typing info
+        return super().load_config(*args, **kwargs)  # type: ignore
diff --git a/invokeai/backend/model_manager/load/model_loaders/ip_adapter.py b/invokeai/backend/model_manager/load/model_loaders/ip_adapter.py
index 27ced41c1e..7d25e9d218 100644
--- a/invokeai/backend/model_manager/load/model_loaders/ip_adapter.py
+++ b/invokeai/backend/model_manager/load/model_loaders/ip_adapter.py
@@ -15,11 +15,10 @@ from invokeai.backend.model_manager import (
     ModelType,
     SubModelType,
 )
-from invokeai.backend.model_manager.load.load_base import AnyModelLoader
-from invokeai.backend.model_manager.load.load_default import ModelLoader
+from invokeai.backend.model_manager.load import ModelLoader, ModelLoaderRegistry
 
 
-@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.IPAdapter, format=ModelFormat.InvokeAI)
+@ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.IPAdapter, format=ModelFormat.InvokeAI)
 class IPAdapterInvokeAILoader(ModelLoader):
     """Class to load IP Adapter diffusers models."""
 
diff --git a/invokeai/backend/model_manager/load/model_loaders/lora.py b/invokeai/backend/model_manager/load/model_loaders/lora.py
index 6ff2dcc918..fe804ef565 100644
--- a/invokeai/backend/model_manager/load/model_loaders/lora.py
+++ b/invokeai/backend/model_manager/load/model_loaders/lora.py
@@ -18,13 +18,13 @@ from invokeai.backend.model_manager import (
     SubModelType,
 )
 from invokeai.backend.model_manager.load.convert_cache import ModelConvertCacheBase
-from invokeai.backend.model_manager.load.load_base import AnyModelLoader
-from invokeai.backend.model_manager.load.load_default import ModelLoader
 from invokeai.backend.model_manager.load.model_cache.model_cache_base import ModelCacheBase
 
+from .. import ModelLoader, ModelLoaderRegistry
 
-@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.Lora, format=ModelFormat.Diffusers)
-@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.Lora, format=ModelFormat.Lycoris)
+
+@ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.Lora, format=ModelFormat.Diffusers)
+@ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.Lora, format=ModelFormat.Lycoris)
 class LoraLoader(ModelLoader):
     """Class to load LoRA models."""
 
diff --git a/invokeai/backend/model_manager/load/model_loaders/onnx.py b/invokeai/backend/model_manager/load/model_loaders/onnx.py
index 935a6b7c95..38f0274acc 100644
--- a/invokeai/backend/model_manager/load/model_loaders/onnx.py
+++ b/invokeai/backend/model_manager/load/model_loaders/onnx.py
@@ -13,13 +13,14 @@ from invokeai.backend.model_manager import (
     ModelType,
     SubModelType,
 )
-from invokeai.backend.model_manager.load.load_base import AnyModelLoader
-from invokeai.backend.model_manager.load.load_default import ModelLoader
+
+from .. import ModelLoaderRegistry
+from .generic_diffusers import GenericDiffusersLoader
 
 
-@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.ONNX, format=ModelFormat.Onnx)
-@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.ONNX, format=ModelFormat.Olive)
-class OnnyxDiffusersModel(ModelLoader):
+@ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.ONNX, format=ModelFormat.Onnx)
+@ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.ONNX, format=ModelFormat.Olive)
+class OnnyxDiffusersModel(GenericDiffusersLoader):
     """Class to load onnx models."""
 
     def _load_model(
@@ -30,7 +31,7 @@ class OnnyxDiffusersModel(ModelLoader):
     ) -> AnyModel:
         if not submodel_type is not None:
             raise Exception("A submodel type must be provided when loading onnx pipelines.")
-        load_class = self._get_hf_load_class(model_path, submodel_type)
+        load_class = self.get_hf_load_class(model_path, submodel_type)
         variant = model_variant.value if model_variant else None
         model_path = model_path / submodel_type.value
         result: AnyModel = load_class.from_pretrained(
diff --git a/invokeai/backend/model_manager/load/model_loaders/stable_diffusion.py b/invokeai/backend/model_manager/load/model_loaders/stable_diffusion.py
index 23b4e1fccd..5884f84e8d 100644
--- a/invokeai/backend/model_manager/load/model_loaders/stable_diffusion.py
+++ b/invokeai/backend/model_manager/load/model_loaders/stable_diffusion.py
@@ -19,13 +19,14 @@ from invokeai.backend.model_manager import (
 )
 from invokeai.backend.model_manager.config import MainCheckpointConfig
 from invokeai.backend.model_manager.convert_ckpt_to_diffusers import convert_ckpt_to_diffusers
-from invokeai.backend.model_manager.load.load_base import AnyModelLoader
-from invokeai.backend.model_manager.load.load_default import ModelLoader
+
+from .. import ModelLoaderRegistry
+from .generic_diffusers import GenericDiffusersLoader
 
 
-@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.Main, format=ModelFormat.Diffusers)
-@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.Main, format=ModelFormat.Checkpoint)
-class StableDiffusionDiffusersModel(ModelLoader):
+@ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.Main, format=ModelFormat.Diffusers)
+@ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.Main, format=ModelFormat.Checkpoint)
+class StableDiffusionDiffusersModel(GenericDiffusersLoader):
     """Class to load main models."""
 
     model_base_to_model_type = {
@@ -43,7 +44,7 @@ class StableDiffusionDiffusersModel(ModelLoader):
     ) -> AnyModel:
         if not submodel_type is not None:
             raise Exception("A submodel type must be provided when loading main pipelines.")
-        load_class = self._get_hf_load_class(model_path, submodel_type)
+        load_class = self.get_hf_load_class(model_path, submodel_type)
         variant = model_variant.value if model_variant else None
         model_path = model_path / submodel_type.value
         result: AnyModel = load_class.from_pretrained(
diff --git a/invokeai/backend/model_manager/load/model_loaders/textual_inversion.py b/invokeai/backend/model_manager/load/model_loaders/textual_inversion.py
index 9476747960..094d4d7c5c 100644
--- a/invokeai/backend/model_manager/load/model_loaders/textual_inversion.py
+++ b/invokeai/backend/model_manager/load/model_loaders/textual_inversion.py
@@ -5,7 +5,6 @@
 from pathlib import Path
 from typing import Optional, Tuple
 
-from invokeai.backend.textual_inversion import TextualInversionModelRaw
 from invokeai.backend.model_manager import (
     AnyModel,
     AnyModelConfig,
@@ -15,12 +14,15 @@ from invokeai.backend.model_manager import (
     ModelType,
     SubModelType,
 )
-from invokeai.backend.model_manager.load.load_base import AnyModelLoader
-from invokeai.backend.model_manager.load.load_default import ModelLoader
+from invokeai.backend.textual_inversion import TextualInversionModelRaw
+
+from .. import ModelLoader, ModelLoaderRegistry
 
 
-@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.TextualInversion, format=ModelFormat.EmbeddingFile)
-@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.TextualInversion, format=ModelFormat.EmbeddingFolder)
+@ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.TextualInversion, format=ModelFormat.EmbeddingFile)
+@ModelLoaderRegistry.register(
+    base=BaseModelType.Any, type=ModelType.TextualInversion, format=ModelFormat.EmbeddingFolder
+)
 class TextualInversionLoader(ModelLoader):
     """Class to load TI models."""
 
diff --git a/invokeai/backend/model_manager/load/model_loaders/vae.py b/invokeai/backend/model_manager/load/model_loaders/vae.py
index 3983ea7595..7ade1494eb 100644
--- a/invokeai/backend/model_manager/load/model_loaders/vae.py
+++ b/invokeai/backend/model_manager/load/model_loaders/vae.py
@@ -14,14 +14,14 @@ from invokeai.backend.model_manager import (
     ModelType,
 )
 from invokeai.backend.model_manager.convert_ckpt_to_diffusers import convert_ldm_vae_to_diffusers
-from invokeai.backend.model_manager.load.load_base import AnyModelLoader
 
+from .. import ModelLoaderRegistry
 from .generic_diffusers import GenericDiffusersLoader
 
 
-@AnyModelLoader.register(base=BaseModelType.Any, type=ModelType.Vae, format=ModelFormat.Diffusers)
-@AnyModelLoader.register(base=BaseModelType.StableDiffusion1, type=ModelType.Vae, format=ModelFormat.Checkpoint)
-@AnyModelLoader.register(base=BaseModelType.StableDiffusion2, type=ModelType.Vae, format=ModelFormat.Checkpoint)
+@ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.Vae, format=ModelFormat.Diffusers)
+@ModelLoaderRegistry.register(base=BaseModelType.StableDiffusion1, type=ModelType.Vae, format=ModelFormat.Checkpoint)
+@ModelLoaderRegistry.register(base=BaseModelType.StableDiffusion2, type=ModelType.Vae, format=ModelFormat.Checkpoint)
 class VaeLoader(GenericDiffusersLoader):
     """Class to load VAE models."""
 
diff --git a/invokeai/backend/model_manager/load/optimizations.py b/invokeai/backend/model_manager/load/optimizations.py
index a46d262175..030fcfa639 100644
--- a/invokeai/backend/model_manager/load/optimizations.py
+++ b/invokeai/backend/model_manager/load/optimizations.py
@@ -1,16 +1,16 @@
 from contextlib import contextmanager
+from typing import Any, Generator
 
 import torch
 
 
-def _no_op(*args, **kwargs):
+def _no_op(*args: Any, **kwargs: Any) -> None:
     pass
 
 
 @contextmanager
-def skip_torch_weight_init():
-    """A context manager that monkey-patches several of the common torch layers (torch.nn.Linear, torch.nn.Conv1d, etc.)
-    to skip weight initialization.
+def skip_torch_weight_init() -> Generator[None, None, None]:
+    """Monkey patch several of the common torch layers (torch.nn.Linear, torch.nn.Conv1d, etc.) to skip weight initialization.
 
     By default, `torch.nn.Linear` and `torch.nn.ConvNd` layers initialize their weights (according to a particular
     distribution) when __init__ is called. This weight initialization step can take a significant amount of time, and is
@@ -18,13 +18,14 @@ def skip_torch_weight_init():
     monkey-patches common torch layers to skip the weight initialization step.
     """
     torch_modules = [torch.nn.Linear, torch.nn.modules.conv._ConvNd, torch.nn.Embedding]
-    saved_functions = [m.reset_parameters for m in torch_modules]
+    saved_functions = [hasattr(m, "reset_parameters") and m.reset_parameters for m in torch_modules]
 
     try:
         for torch_module in torch_modules:
+            assert hasattr(torch_module, "reset_parameters")
             torch_module.reset_parameters = _no_op
-
         yield None
     finally:
         for torch_module, saved_function in zip(torch_modules, saved_functions, strict=True):
+            assert hasattr(torch_module, "reset_parameters")
             torch_module.reset_parameters = saved_function
diff --git a/invokeai/backend/model_manager/merge.py b/invokeai/backend/model_manager/merge.py
index 108f1f0e6f..7063cb907d 100644
--- a/invokeai/backend/model_manager/merge.py
+++ b/invokeai/backend/model_manager/merge.py
@@ -13,7 +13,7 @@ from typing import Any, List, Optional, Set
 
 import torch
 from diffusers import AutoPipelineForText2Image
-from diffusers import logging as dlogging
+from diffusers.utils import logging as dlogging
 
 from invokeai.app.services.model_install import ModelInstallServiceBase
 from invokeai.backend.util.devices import choose_torch_device, torch_dtype
@@ -76,7 +76,7 @@ class ModelMerger(object):
                 custom_pipeline="checkpoint_merger",
                 torch_dtype=dtype,
                 variant=variant,
-            )
+            )  # type: ignore
             merged_pipe = pipe.merge(
                 pretrained_model_name_or_path_list=model_paths,
                 alpha=alpha,
diff --git a/invokeai/backend/model_manager/metadata/metadata_base.py b/invokeai/backend/model_manager/metadata/metadata_base.py
index 5c3afcdc96..6e410d8222 100644
--- a/invokeai/backend/model_manager/metadata/metadata_base.py
+++ b/invokeai/backend/model_manager/metadata/metadata_base.py
@@ -54,8 +54,8 @@ class LicenseRestrictions(BaseModel):
     AllowDifferentLicense: bool = Field(
         description="if true, derivatives of this model be redistributed under a different license", default=False
     )
-    AllowCommercialUse: CommercialUsage = Field(
-        description="Type of commercial use allowed or 'No' if no commercial use is allowed.", default_factory=set
+    AllowCommercialUse: Optional[CommercialUsage] = Field(
+        description="Type of commercial use allowed or 'No' if no commercial use is allowed.", default=None
     )
 
 
@@ -139,7 +139,10 @@ class CivitaiMetadata(ModelMetadataWithFiles):
     @property
     def allow_commercial_use(self) -> bool:
         """Return True if commercial use is allowed."""
-        return self.restrictions.AllowCommercialUse != CommercialUsage("None")
+        if self.restrictions.AllowCommercialUse is None:
+            return False
+        else:
+            return self.restrictions.AllowCommercialUse != CommercialUsage("None")
 
     @property
     def allow_derivatives(self) -> bool:
diff --git a/invokeai/backend/model_manager/probe.py b/invokeai/backend/model_manager/probe.py
index d511ffa875..7de4289466 100644
--- a/invokeai/backend/model_manager/probe.py
+++ b/invokeai/backend/model_manager/probe.py
@@ -8,7 +8,6 @@ import torch
 from picklescan.scanner import scan_file_path
 
 import invokeai.backend.util.logging as logger
-from .util.model_util import lora_token_vector_length, read_checkpoint_meta
 from invokeai.backend.util.util import SilenceWarnings
 
 from .config import (
@@ -23,6 +22,7 @@ from .config import (
     SchedulerPredictionType,
 )
 from .hash import FastModelHash
+from .util.model_util import lora_token_vector_length, read_checkpoint_meta
 
 CkptType = Dict[str, Any]
 
@@ -53,6 +53,7 @@ LEGACY_CONFIGS: Dict[BaseModelType, Dict[ModelVariantType, Union[str, Dict[Sched
     },
 }
 
+
 class ProbeBase(object):
     """Base class for probes."""
 
diff --git a/invokeai/backend/model_manager/search.py b/invokeai/backend/model_manager/search.py
index 0ead22b743..f7ef2e049d 100644
--- a/invokeai/backend/model_manager/search.py
+++ b/invokeai/backend/model_manager/search.py
@@ -116,9 +116,9 @@ class ModelSearch(ModelSearchBase):
        # returns all models that have 'anime' in the path
     """
 
-    models_found: Optional[Set[Path]] = Field(default=None)
-    scanned_dirs: Optional[Set[Path]] = Field(default=None)
-    pruned_paths: Optional[Set[Path]] = Field(default=None)
+    models_found: Set[Path] = Field(default_factory=set)
+    scanned_dirs: Set[Path] = Field(default_factory=set)
+    pruned_paths: Set[Path] = Field(default_factory=set)
 
     def search_started(self) -> None:
         self.models_found = set()
diff --git a/invokeai/backend/model_manager/util/libc_util.py b/invokeai/backend/model_manager/util/libc_util.py
index 1fbcae0a93..ef1ac2f8a4 100644
--- a/invokeai/backend/model_manager/util/libc_util.py
+++ b/invokeai/backend/model_manager/util/libc_util.py
@@ -35,7 +35,7 @@ class Struct_mallinfo2(ctypes.Structure):
         ("keepcost", ctypes.c_size_t),
     ]
 
-    def __str__(self):
+    def __str__(self) -> str:
         s = ""
         s += f"{'arena': <10}= {(self.arena/2**30):15.5f}   # Non-mmapped space allocated (GB) (uordblks + fordblks)\n"
         s += f"{'ordblks': <10}= {(self.ordblks): >15}   # Number of free chunks\n"
@@ -62,7 +62,7 @@ class LibcUtil:
     TODO: Improve cross-OS compatibility of this class.
     """
 
-    def __init__(self):
+    def __init__(self) -> None:
         self._libc = ctypes.cdll.LoadLibrary("libc.so.6")
 
     def mallinfo2(self) -> Struct_mallinfo2:
@@ -72,4 +72,5 @@ class LibcUtil:
         """
         mallinfo2 = self._libc.mallinfo2
         mallinfo2.restype = Struct_mallinfo2
-        return mallinfo2()
+        result: Struct_mallinfo2 = mallinfo2()
+        return result
diff --git a/invokeai/backend/model_manager/util/model_util.py b/invokeai/backend/model_manager/util/model_util.py
index 6847a40878..2e448520e5 100644
--- a/invokeai/backend/model_manager/util/model_util.py
+++ b/invokeai/backend/model_manager/util/model_util.py
@@ -1,12 +1,15 @@
 """Utilities for parsing model files, used mostly by probe.py"""
 
 import json
-import torch
-from typing import Union
 from pathlib import Path
+from typing import Dict, Optional, Union
+
+import safetensors
+import torch
 from picklescan.scanner import scan_file_path
 
-def _fast_safetensors_reader(path: str):
+
+def _fast_safetensors_reader(path: str) -> Dict[str, torch.Tensor]:
     checkpoint = {}
     device = torch.device("meta")
     with open(path, "rb") as f:
@@ -37,10 +40,12 @@ def _fast_safetensors_reader(path: str):
 
     return checkpoint
 
-def read_checkpoint_meta(path: Union[str, Path], scan: bool = False):
+
+def read_checkpoint_meta(path: Union[str, Path], scan: bool = False) -> Dict[str, torch.Tensor]:
     if str(path).endswith(".safetensors"):
         try:
-            checkpoint = _fast_safetensors_reader(path)
+            path_str = path.as_posix() if isinstance(path, Path) else path
+            checkpoint = _fast_safetensors_reader(path_str)
         except Exception:
             # TODO: create issue for support "meta"?
             checkpoint = safetensors.torch.load_file(path, device="cpu")
@@ -52,14 +57,15 @@ def read_checkpoint_meta(path: Union[str, Path], scan: bool = False):
         checkpoint = torch.load(path, map_location=torch.device("meta"))
     return checkpoint
 
-def lora_token_vector_length(checkpoint: dict) -> int:
+
+def lora_token_vector_length(checkpoint: Dict[str, torch.Tensor]) -> Optional[int]:
     """
     Given a checkpoint in memory, return the lora token vector length
 
     :param checkpoint: The checkpoint
     """
 
-    def _get_shape_1(key: str, tensor, checkpoint) -> int:
+    def _get_shape_1(key: str, tensor: torch.Tensor, checkpoint: Dict[str, torch.Tensor]) -> Optional[int]:
         lora_token_vector_length = None
 
         if "." not in key:
diff --git a/invokeai/backend/onnx/onnx_runtime.py b/invokeai/backend/onnx/onnx_runtime.py
index 9b2096abdf..8916865dd5 100644
--- a/invokeai/backend/onnx/onnx_runtime.py
+++ b/invokeai/backend/onnx/onnx_runtime.py
@@ -8,6 +8,7 @@ import numpy as np
 import onnx
 from onnx import numpy_helper
 from onnxruntime import InferenceSession, SessionOptions, get_available_providers
+
 from ..raw_model import RawModel
 
 ONNX_WEIGHTS_NAME = "model.onnx"
@@ -15,7 +16,7 @@ ONNX_WEIGHTS_NAME = "model.onnx"
 
 # NOTE FROM LS: This was copied from Stalker's original implementation.
 # I have not yet gone through and fixed all the type hints
-class IAIOnnxRuntimeModel:
+class IAIOnnxRuntimeModel(RawModel):
     class _tensor_access:
         def __init__(self, model):  # type: ignore
             self.model = model
diff --git a/invokeai/backend/raw_model.py b/invokeai/backend/raw_model.py
index 2e224d538b..d0dc50c456 100644
--- a/invokeai/backend/raw_model.py
+++ b/invokeai/backend/raw_model.py
@@ -10,5 +10,6 @@ The term 'raw' was introduced to describe a wrapper around a torch.nn.Module
 that adds additional methods and attributes.
 """
 
+
 class RawModel:
     """Base class for 'Raw' model wrappers."""
diff --git a/invokeai/backend/stable_diffusion/seamless.py b/invokeai/backend/stable_diffusion/seamless.py
index bfdf9e0c53..fb9112b56d 100644
--- a/invokeai/backend/stable_diffusion/seamless.py
+++ b/invokeai/backend/stable_diffusion/seamless.py
@@ -1,10 +1,11 @@
 from __future__ import annotations
 
 from contextlib import contextmanager
-from typing import List, Union
+from typing import Callable, List, Union
 
 import torch.nn as nn
-from diffusers.models import AutoencoderKL, UNet2DConditionModel
+from diffusers.models.autoencoders.autoencoder_kl import AutoencoderKL
+from diffusers.models.unets.unet_2d_condition import UNet2DConditionModel
 
 
 def _conv_forward_asymmetric(self, input, weight, bias):
@@ -26,70 +27,51 @@ def _conv_forward_asymmetric(self, input, weight, bias):
 
 @contextmanager
 def set_seamless(model: Union[UNet2DConditionModel, AutoencoderKL], seamless_axes: List[str]):
+    # Callable: (input: Tensor, weight: Tensor, bias: Optional[Tensor]) -> Tensor
+    to_restore: list[tuple[nn.Conv2d | nn.ConvTranspose2d, Callable]] = []
     try:
-        to_restore = []
-
+        # Hard coded to skip down block layers, allowing for seamless tiling at the expense of prompt adherence
+        skipped_layers = 1
         for m_name, m in model.named_modules():
-            if isinstance(model, UNet2DConditionModel):
-                if ".attentions." in m_name:
+            if not isinstance(m, (nn.Conv2d, nn.ConvTranspose2d)):
+                continue
+
+            if isinstance(model, UNet2DConditionModel) and m_name.startswith("down_blocks.") and ".resnets." in m_name:
+                # down_blocks.1.resnets.1.conv1
+                _, block_num, _, resnet_num, submodule_name = m_name.split(".")
+                block_num = int(block_num)
+                resnet_num = int(resnet_num)
+
+                if block_num >= len(model.down_blocks) - skipped_layers:
                     continue
 
-                if ".resnets." in m_name:
-                    if ".conv2" in m_name:
-                        continue
-                    if ".conv_shortcut" in m_name:
-                        continue
-
-            """
-            if isinstance(model, UNet2DConditionModel):
-                if False and ".upsamplers." in m_name:
+                # Skip the second resnet (could be configurable)
+                if resnet_num > 0:
                     continue
 
-                if False and ".downsamplers." in m_name:
+                # Skip Conv2d layers (could be configurable)
+                if submodule_name == "conv2":
                     continue
 
-                if True and ".resnets." in m_name:
-                    if True and ".conv1" in m_name:
-                        if False and "down_blocks" in m_name:
-                            continue
-                        if False and "mid_block" in m_name:
-                            continue
-                        if False and "up_blocks" in m_name:
-                            continue
+            m.asymmetric_padding_mode = {}
+            m.asymmetric_padding = {}
+            m.asymmetric_padding_mode["x"] = "circular" if ("x" in seamless_axes) else "constant"
+            m.asymmetric_padding["x"] = (
+                m._reversed_padding_repeated_twice[0],
+                m._reversed_padding_repeated_twice[1],
+                0,
+                0,
+            )
+            m.asymmetric_padding_mode["y"] = "circular" if ("y" in seamless_axes) else "constant"
+            m.asymmetric_padding["y"] = (
+                0,
+                0,
+                m._reversed_padding_repeated_twice[2],
+                m._reversed_padding_repeated_twice[3],
+            )
 
-                    if True and ".conv2" in m_name:
-                        continue
-
-                    if True and ".conv_shortcut" in m_name:
-                        continue
-
-                if True and ".attentions." in m_name:
-                    continue
-
-                if False and m_name in ["conv_in", "conv_out"]:
-                    continue
-            """
-
-            if isinstance(m, (nn.Conv2d, nn.ConvTranspose2d)):
-                m.asymmetric_padding_mode = {}
-                m.asymmetric_padding = {}
-                m.asymmetric_padding_mode["x"] = "circular" if ("x" in seamless_axes) else "constant"
-                m.asymmetric_padding["x"] = (
-                    m._reversed_padding_repeated_twice[0],
-                    m._reversed_padding_repeated_twice[1],
-                    0,
-                    0,
-                )
-                m.asymmetric_padding_mode["y"] = "circular" if ("y" in seamless_axes) else "constant"
-                m.asymmetric_padding["y"] = (
-                    0,
-                    0,
-                    m._reversed_padding_repeated_twice[2],
-                    m._reversed_padding_repeated_twice[3],
-                )
-
-                to_restore.append((m, m._conv_forward))
-                m._conv_forward = _conv_forward_asymmetric.__get__(m, nn.Conv2d)
+            to_restore.append((m, m._conv_forward))
+            m._conv_forward = _conv_forward_asymmetric.__get__(m, nn.Conv2d)
 
         yield
 
diff --git a/invokeai/backend/textual_inversion.py b/invokeai/backend/textual_inversion.py
index 9a4fa0b540..f7390979bb 100644
--- a/invokeai/backend/textual_inversion.py
+++ b/invokeai/backend/textual_inversion.py
@@ -8,8 +8,10 @@ from compel.embeddings_provider import BaseTextualInversionManager
 from safetensors.torch import load_file
 from transformers import CLIPTokenizer
 from typing_extensions import Self
+
 from .raw_model import RawModel
 
+
 class TextualInversionModelRaw(RawModel):
     embedding: torch.Tensor  # [n, 768]|[n, 1280]
     embedding_2: Optional[torch.Tensor] = None  # [n, 768]|[n, 1280]   - for SDXL models
diff --git a/invokeai/backend/util/test_utils.py b/invokeai/backend/util/test_utils.py
index a3def182c8..0d76c4633c 100644
--- a/invokeai/backend/util/test_utils.py
+++ b/invokeai/backend/util/test_utils.py
@@ -42,7 +42,7 @@ def install_and_load_model(
     # If the requested model is already installed, return its LoadedModel
     with contextlib.suppress(UnknownModelException):
         # TODO: Replace with wrapper call
-        loaded_model: LoadedModel = model_manager.load.load_model_by_attr(
+        loaded_model: LoadedModel = model_manager.load_model_by_attr(
             model_name=model_name, base_model=base_model, model_type=model_type
         )
         return loaded_model
@@ -53,7 +53,7 @@ def install_and_load_model(
     assert job.complete
 
     try:
-        loaded_model = model_manager.load.load_model_by_config(job.config_out)
+        loaded_model = model_manager.load_model_by_config(job.config_out)
         return loaded_model
     except UnknownModelException as e:
         raise Exception(
diff --git a/tests/backend/model_manager/model_loading/test_model_load.py b/tests/backend/model_manager/model_loading/test_model_load.py
index 38d9b8afb8..c1fde504ea 100644
--- a/tests/backend/model_manager/model_loading/test_model_load.py
+++ b/tests/backend/model_manager/model_loading/test_model_load.py
@@ -4,18 +4,27 @@ Test model loading
 
 from pathlib import Path
 
-from invokeai.app.services.model_install import ModelInstallServiceBase
-from invokeai.app.services.model_load import ModelLoadServiceBase
+from invokeai.app.services.model_manager import ModelManagerServiceBase
 from invokeai.backend.textual_inversion import TextualInversionModelRaw
 from tests.backend.model_manager.model_manager_fixtures import *  # noqa F403
 
-def test_loading(mm2_installer: ModelInstallServiceBase, mm2_loader: ModelLoadServiceBase, embedding_file: Path):
-    store = mm2_installer.record_store
+
+def test_loading(mm2_model_manager: ModelManagerServiceBase, embedding_file: Path):
+    store = mm2_model_manager.store
     matches = store.search_by_attr(model_name="test_embedding")
     assert len(matches) == 0
-    key = mm2_installer.register_path(embedding_file)
-    loaded_model = mm2_loader.load_model_by_config(store.get_model(key))
+    key = mm2_model_manager.install.register_path(embedding_file)
+    loaded_model = mm2_model_manager.load_model_by_config(store.get_model(key))
     assert loaded_model is not None
     assert loaded_model.config.key == key
     with loaded_model as model:
         assert isinstance(model, TextualInversionModelRaw)
+    loaded_model_2 = mm2_model_manager.load_model_by_key(key)
+    assert loaded_model.config.key == loaded_model_2.config.key
+
+    loaded_model_3 = mm2_model_manager.load_model_by_attr(
+        model_name=loaded_model.config.name,
+        model_type=loaded_model.config.type,
+        base_model=loaded_model.config.base,
+    )
+    assert loaded_model.config.key == loaded_model_3.config.key
diff --git a/tests/backend/model_manager/model_manager_fixtures.py b/tests/backend/model_manager/model_manager_fixtures.py
index 5f7f44c018..df54e2f926 100644
--- a/tests/backend/model_manager/model_manager_fixtures.py
+++ b/tests/backend/model_manager/model_manager_fixtures.py
@@ -6,17 +6,17 @@ from pathlib import Path
 from typing import Any, Dict, List
 
 import pytest
-from pytest import FixtureRequest
 from pydantic import BaseModel
+from pytest import FixtureRequest
 from requests.sessions import Session
 from requests_testadapter import TestAdapter, TestSession
 
 from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.app.services.download import DownloadQueueServiceBase, DownloadQueueService
+from invokeai.app.services.download import DownloadQueueService, DownloadQueueServiceBase
 from invokeai.app.services.events.events_base import EventServiceBase
-from invokeai.app.services.model_manager import ModelManagerServiceBase, ModelManagerService
-from invokeai.app.services.model_load import ModelLoadServiceBase, ModelLoadService
 from invokeai.app.services.model_install import ModelInstallService, ModelInstallServiceBase
+from invokeai.app.services.model_load import ModelLoadService, ModelLoadServiceBase
+from invokeai.app.services.model_manager import ModelManagerService, ModelManagerServiceBase
 from invokeai.app.services.model_metadata import ModelMetadataStoreBase, ModelMetadataStoreSQL
 from invokeai.app.services.model_records import ModelRecordServiceBase, ModelRecordServiceSQL
 from invokeai.backend.model_manager.config import (
@@ -95,9 +95,7 @@ def mm2_app_config(mm2_root_dir: Path) -> InvokeAIAppConfig:
 
 
 @pytest.fixture
-def mm2_download_queue(mm2_session: Session,
-                       request: FixtureRequest
-                       ) -> DownloadQueueServiceBase:
+def mm2_download_queue(mm2_session: Session, request: FixtureRequest) -> DownloadQueueServiceBase:
     download_queue = DownloadQueueService(requests_session=mm2_session)
     download_queue.start()
 
@@ -107,30 +105,34 @@ def mm2_download_queue(mm2_session: Session,
     request.addfinalizer(stop_queue)
     return download_queue
 
+
 @pytest.fixture
 def mm2_metadata_store(mm2_record_store: ModelRecordServiceSQL) -> ModelMetadataStoreBase:
     return mm2_record_store.metadata_store
 
+
 @pytest.fixture
 def mm2_loader(mm2_app_config: InvokeAIAppConfig, mm2_record_store: ModelRecordServiceBase) -> ModelLoadServiceBase:
     ram_cache = ModelCache(
         logger=InvokeAILogger.get_logger(),
         max_cache_size=mm2_app_config.ram_cache_size,
-        max_vram_cache_size=mm2_app_config.vram_cache_size
+        max_vram_cache_size=mm2_app_config.vram_cache_size,
     )
     convert_cache = ModelConvertCache(mm2_app_config.models_convert_cache_path)
-    return ModelLoadService(app_config=mm2_app_config,
-                            record_store=mm2_record_store,
-                            ram_cache=ram_cache,
-                            convert_cache=convert_cache,
-                          )
+    return ModelLoadService(
+        app_config=mm2_app_config,
+        ram_cache=ram_cache,
+        convert_cache=convert_cache,
+    )
+
 
 @pytest.fixture
-def mm2_installer(mm2_app_config: InvokeAIAppConfig,
-                  mm2_download_queue: DownloadQueueServiceBase,
-                  mm2_session: Session,
-                  request: FixtureRequest,
-                  ) -> ModelInstallServiceBase:
+def mm2_installer(
+    mm2_app_config: InvokeAIAppConfig,
+    mm2_download_queue: DownloadQueueServiceBase,
+    mm2_session: Session,
+    request: FixtureRequest,
+) -> ModelInstallServiceBase:
     logger = InvokeAILogger.get_logger()
     db = create_mock_sqlite_database(mm2_app_config, logger)
     events = DummyEventService()
@@ -213,15 +215,13 @@ def mm2_record_store(mm2_app_config: InvokeAIAppConfig) -> ModelRecordServiceBas
     store.add_model("test_config_5", raw5)
     return store
 
+
 @pytest.fixture
-def mm2_model_manager(mm2_record_store: ModelRecordServiceBase,
-                      mm2_installer: ModelInstallServiceBase,
-                      mm2_loader: ModelLoadServiceBase) -> ModelManagerServiceBase:
-    return ModelManagerService(
-        store=mm2_record_store,
-        install=mm2_installer,
-        load=mm2_loader
-    )
+def mm2_model_manager(
+    mm2_record_store: ModelRecordServiceBase, mm2_installer: ModelInstallServiceBase, mm2_loader: ModelLoadServiceBase
+) -> ModelManagerServiceBase:
+    return ModelManagerService(store=mm2_record_store, install=mm2_installer, load=mm2_loader)
+
 
 @pytest.fixture
 def mm2_session(embedding_file: Path, diffusers_dir: Path) -> Session:
@@ -306,5 +306,3 @@ def mm2_session(embedding_file: Path, diffusers_dir: Path) -> Session:
                 ),
             )
     return sess
-
-
diff --git a/tests/backend/model_manager/test_lora.py b/tests/backend/model_manager/test_lora.py
index e124bb68ef..114a4cfdcf 100644
--- a/tests/backend/model_manager/test_lora.py
+++ b/tests/backend/model_manager/test_lora.py
@@ -5,8 +5,8 @@
 import pytest
 import torch
 
-from invokeai.backend.model_patcher import ModelPatcher
 from invokeai.backend.lora import LoRALayer, LoRAModelRaw
+from invokeai.backend.model_patcher import ModelPatcher
 
 
 @pytest.mark.parametrize(
diff --git a/tests/backend/model_manager/test_memory_snapshot.py b/tests/backend/model_manager/test_memory_snapshot.py
index 87ec8c34ee..d31ae79b66 100644
--- a/tests/backend/model_manager/test_memory_snapshot.py
+++ b/tests/backend/model_manager/test_memory_snapshot.py
@@ -1,7 +1,8 @@
 import pytest
 
-from invokeai.backend.model_manager.util.libc_util import Struct_mallinfo2
 from invokeai.backend.model_manager.load.memory_snapshot import MemorySnapshot, get_pretty_snapshot_diff
+from invokeai.backend.model_manager.util.libc_util import Struct_mallinfo2
+
 
 def test_memory_snapshot_capture():
     """Smoke test of MemorySnapshot.capture()."""

From fc2082259542985c259d962449714debd0349833 Mon Sep 17 00:00:00 2001
From: blessedcoolant <54517381+blessedcoolant@users.noreply.github.com>
Date: Mon, 19 Feb 2024 00:56:27 +0530
Subject: [PATCH 147/411] fix: Alpha channel causing issue with DW Processor

---
 .../app/invocations/controlnet_image_processors.py | 14 ++++----------
 1 file changed, 4 insertions(+), 10 deletions(-)

diff --git a/invokeai/app/invocations/controlnet_image_processors.py b/invokeai/app/invocations/controlnet_image_processors.py
index 8542134fff..5b15981caa 100644
--- a/invokeai/app/invocations/controlnet_image_processors.py
+++ b/invokeai/app/invocations/controlnet_image_processors.py
@@ -40,12 +40,7 @@ from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.backend.image_util.depth_anything import DepthAnythingDetector
 from invokeai.backend.image_util.dw_openpose import DWOpenposeDetector
 
-from .baseinvocation import (
-    BaseInvocation,
-    BaseInvocationOutput,
-    invocation,
-    invocation_output,
-)
+from .baseinvocation import BaseInvocation, BaseInvocationOutput, invocation, invocation_output
 
 CONTROLNET_MODE_VALUES = Literal["balanced", "more_prompt", "more_control", "unbalanced"]
 CONTROLNET_RESIZE_VALUES = Literal[
@@ -593,9 +588,7 @@ class DepthAnythingImageProcessorInvocation(ImageProcessorInvocation):
         depth_anything_detector = DepthAnythingDetector()
         depth_anything_detector.load_model(model_size=self.model_size)
 
-        if image.mode == "RGBA":
-            image = image.convert("RGB")
-
+        image = image.convert("RGB") if image.mode != "RGB" else image
         processed_image = depth_anything_detector(image=image, resolution=self.resolution, offload=self.offload)
         return processed_image
 
@@ -615,7 +608,8 @@ class DWOpenposeImageProcessorInvocation(ImageProcessorInvocation):
     draw_hands: bool = InputField(default=False)
     image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res)
 
-    def run_processor(self, image):
+    def run_processor(self, image: Image.Image):
+        image = image.convert("RGB") if image.mode != "RGB" else image
         dw_openpose = DWOpenposeDetector()
         processed_image = dw_openpose(
             image,

From 43d94c8108784e1d13fe6ccfce98d9b9b5eaf22f Mon Sep 17 00:00:00 2001
From: dunkeroni <dunkeroni@gmail.com>
Date: Sun, 18 Feb 2024 15:42:58 -0500
Subject: [PATCH 148/411] feat(nodes): format option for get_image method Also
 default CNet preprocessors to "RGB"

---
 .../app/invocations/controlnet_image_processors.py    |  2 +-
 invokeai/app/services/shared/invocation_context.py    | 11 +++++++++--
 2 files changed, 10 insertions(+), 3 deletions(-)

diff --git a/invokeai/app/invocations/controlnet_image_processors.py b/invokeai/app/invocations/controlnet_image_processors.py
index 5b15981caa..1ef5352db6 100644
--- a/invokeai/app/invocations/controlnet_image_processors.py
+++ b/invokeai/app/invocations/controlnet_image_processors.py
@@ -144,7 +144,7 @@ class ImageProcessorInvocation(BaseInvocation, WithMetadata, WithBoard):
         return image
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
-        raw_image = context.images.get_pil(self.image.image_name)
+        raw_image = context.images.get_pil(self.image.image_name, "RGB")
         # image type should be PIL.PngImagePlugin.PngImageFile ?
         processed_image = self.run_processor(raw_image)
 
diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index 1395427a97..d217a865af 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -194,13 +194,20 @@ class ImagesInterface(InvocationContextInterface):
             node_id=self._context_data.invocation.id,
         )
 
-    def get_pil(self, image_name: str) -> Image:
+    def get_pil(self, image_name: str, format: str | None = None) -> Image:
         """
         Gets an image as a PIL Image object.
 
         :param image_name: The name of the image to get.
+        :param format: The color format to convert the image to. If None, the original format is used.
         """
-        return self._services.images.get_pil_image(image_name)
+        image = self._services.images.get_pil_image(image_name)
+        if format and format != image.mode:
+            try:
+                image = image.convert(format)
+            except ValueError:
+                self._services.logger.warning(f"Could not convert image from {image.mode} to {format}. Using original format.")
+        return image
 
     def get_metadata(self, image_name: str) -> Optional[MetadataField]:
         """

From 92394ab75107a5209bb5300d24fe8a861d59c846 Mon Sep 17 00:00:00 2001
From: dunkeroni <dunkeroni@gmail.com>
Date: Sun, 18 Feb 2024 16:29:31 -0500
Subject: [PATCH 149/411] fix(nodes): canny preprocessor uses RGBA again

---
 .../app/invocations/controlnet_image_processors.py     | 10 +++++++++-
 .../app/invocations/custom_nodes/InvokeAI_DemoFusion   |  1 +
 2 files changed, 10 insertions(+), 1 deletion(-)
 create mode 160000 invokeai/app/invocations/custom_nodes/InvokeAI_DemoFusion

diff --git a/invokeai/app/invocations/controlnet_image_processors.py b/invokeai/app/invocations/controlnet_image_processors.py
index 1ef5352db6..797ea62f7c 100644
--- a/invokeai/app/invocations/controlnet_image_processors.py
+++ b/invokeai/app/invocations/controlnet_image_processors.py
@@ -143,8 +143,12 @@ class ImageProcessorInvocation(BaseInvocation, WithMetadata, WithBoard):
         # superclass just passes through image without processing
         return image
 
+    def load_image(self, context: InvocationContext) -> Image.Image:
+        # allows override for any special formatting specific to the preprocessor
+        return context.images.get_pil(self.image.image_name, "RGB")
+
     def invoke(self, context: InvocationContext) -> ImageOutput:
-        raw_image = context.images.get_pil(self.image.image_name, "RGB")
+        raw_image = self.load_image(context)
         # image type should be PIL.PngImagePlugin.PngImageFile ?
         processed_image = self.run_processor(raw_image)
 
@@ -181,6 +185,10 @@ class CannyImageProcessorInvocation(ImageProcessorInvocation):
         default=200, ge=0, le=255, description="The high threshold of the Canny pixel gradient (0-255)"
     )
 
+    def load_image(self, context: InvocationContext) -> Image.Image:
+        # Keep alpha channel for Canny processing to detect edges of transparent areas
+        return context.images.get_pil(self.image.image_name, "RGBA")
+
     def run_processor(self, image):
         canny_processor = CannyDetector()
         processed_image = canny_processor(image, self.low_threshold, self.high_threshold)
diff --git a/invokeai/app/invocations/custom_nodes/InvokeAI_DemoFusion b/invokeai/app/invocations/custom_nodes/InvokeAI_DemoFusion
new file mode 160000
index 0000000000..aae207914f
--- /dev/null
+++ b/invokeai/app/invocations/custom_nodes/InvokeAI_DemoFusion
@@ -0,0 +1 @@
+Subproject commit aae207914f08f77324691ae984fae6dabb0b8976

From 2d007ce532a1e06f2f23293de3412b9ea2008f33 Mon Sep 17 00:00:00 2001
From: dunkeroni <dunkeroni@gmail.com>
Date: Sun, 18 Feb 2024 16:48:05 -0500
Subject: [PATCH 150/411] fix: removed custom module

---
 invokeai/app/invocations/custom_nodes/InvokeAI_DemoFusion | 1 -
 1 file changed, 1 deletion(-)
 delete mode 160000 invokeai/app/invocations/custom_nodes/InvokeAI_DemoFusion

diff --git a/invokeai/app/invocations/custom_nodes/InvokeAI_DemoFusion b/invokeai/app/invocations/custom_nodes/InvokeAI_DemoFusion
deleted file mode 160000
index aae207914f..0000000000
--- a/invokeai/app/invocations/custom_nodes/InvokeAI_DemoFusion
+++ /dev/null
@@ -1 +0,0 @@
-Subproject commit aae207914f08f77324691ae984fae6dabb0b8976

From 965867151bc5194824847d0151ac0642ba609e21 Mon Sep 17 00:00:00 2001
From: dunkeroni <dunkeroni@gmail.com>
Date: Sun, 18 Feb 2024 16:56:46 -0500
Subject: [PATCH 151/411] chore(invocations): use IMAGE_MODES constant literal

---
 invokeai/app/invocations/constants.py              |  3 +++
 invokeai/app/invocations/image.py                  |  4 +---
 invokeai/app/services/shared/invocation_context.py | 11 ++++++-----
 3 files changed, 10 insertions(+), 8 deletions(-)

diff --git a/invokeai/app/invocations/constants.py b/invokeai/app/invocations/constants.py
index 795e7a3b60..fca5a2ec7f 100644
--- a/invokeai/app/invocations/constants.py
+++ b/invokeai/app/invocations/constants.py
@@ -12,3 +12,6 @@ The ratio of image:latent dimensions is LATENT_SCALE_FACTOR:1, or 8:1.
 
 SCHEDULER_NAME_VALUES = Literal[tuple(SCHEDULER_MAP.keys())]
 """A literal type representing the valid scheduler names."""
+
+IMAGE_MODES = Literal["L", "RGB", "RGBA", "CMYK", "YCbCr", "LAB", "HSV", "I", "F"]
+"""A literal type for PIL image modes supported by Invoke"""
\ No newline at end of file
diff --git a/invokeai/app/invocations/image.py b/invokeai/app/invocations/image.py
index f5ad5515a6..1f3b5b7368 100644
--- a/invokeai/app/invocations/image.py
+++ b/invokeai/app/invocations/image.py
@@ -16,6 +16,7 @@ from invokeai.app.invocations.fields import (
     WithMetadata,
 )
 from invokeai.app.invocations.primitives import ImageOutput
+from invokeai.app.invocations.constants import IMAGE_MODES
 from invokeai.app.services.image_records.image_records_common import ImageCategory
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.backend.image_util.invisible_watermark import InvisibleWatermark
@@ -263,9 +264,6 @@ class ImageChannelInvocation(BaseInvocation, WithMetadata, WithBoard):
         return ImageOutput.build(image_dto)
 
 
-IMAGE_MODES = Literal["L", "RGB", "RGBA", "CMYK", "YCbCr", "LAB", "HSV", "I", "F"]
-
-
 @invocation(
     "img_conv",
     title="Convert Image Mode",
diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index d217a865af..2383785ad4 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -6,6 +6,7 @@ from PIL.Image import Image
 from torch import Tensor
 
 from invokeai.app.invocations.fields import MetadataField, WithBoard, WithMetadata
+from invokeai.app.invocations.constants import IMAGE_MODES
 from invokeai.app.services.boards.boards_common import BoardDTO
 from invokeai.app.services.config.config_default import InvokeAIAppConfig
 from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
@@ -194,19 +195,19 @@ class ImagesInterface(InvocationContextInterface):
             node_id=self._context_data.invocation.id,
         )
 
-    def get_pil(self, image_name: str, format: str | None = None) -> Image:
+    def get_pil(self, image_name: str, mode: IMAGE_MODES | None = None) -> Image:
         """
         Gets an image as a PIL Image object.
 
         :param image_name: The name of the image to get.
-        :param format: The color format to convert the image to. If None, the original format is used.
+        :param mode: The color mode to convert the image to. If None, the original mode is used.
         """
         image = self._services.images.get_pil_image(image_name)
-        if format and format != image.mode:
+        if mode and mode != image.mode:
             try:
-                image = image.convert(format)
+                image = image.convert(mode)
             except ValueError:
-                self._services.logger.warning(f"Could not convert image from {image.mode} to {format}. Using original format.")
+                self._services.logger.warning(f"Could not convert image from {image.mode} to {mode}. Using original mode instead.")
         return image
 
     def get_metadata(self, image_name: str) -> Optional[MetadataField]:

From 56ac2104e3cb3c03006f903226a2db9e4a0ad9bc Mon Sep 17 00:00:00 2001
From: dunkeroni <dunkeroni@gmail.com>
Date: Sun, 18 Feb 2024 23:10:38 -0500
Subject: [PATCH 152/411] chore(invocations): remove redundant RGB conversions

---
 invokeai/app/invocations/controlnet_image_processors.py | 8 +-------
 1 file changed, 1 insertion(+), 7 deletions(-)

diff --git a/invokeai/app/invocations/controlnet_image_processors.py b/invokeai/app/invocations/controlnet_image_processors.py
index 797ea62f7c..1e998e4b61 100644
--- a/invokeai/app/invocations/controlnet_image_processors.py
+++ b/invokeai/app/invocations/controlnet_image_processors.py
@@ -423,10 +423,6 @@ class MediapipeFaceProcessorInvocation(ImageProcessorInvocation):
     min_confidence: float = InputField(default=0.5, ge=0, le=1, description="Minimum confidence for face detection")
 
     def run_processor(self, image):
-        # MediaPipeFaceDetector throws an error if image has alpha channel
-        #     so convert to RGB if needed
-        if image.mode == "RGBA":
-            image = image.convert("RGB")
         mediapipe_face_processor = MediapipeFaceDetector()
         processed_image = mediapipe_face_processor(image, max_faces=self.max_faces, min_confidence=self.min_confidence)
         return processed_image
@@ -595,8 +591,7 @@ class DepthAnythingImageProcessorInvocation(ImageProcessorInvocation):
     def run_processor(self, image: Image.Image):
         depth_anything_detector = DepthAnythingDetector()
         depth_anything_detector.load_model(model_size=self.model_size)
-
-        image = image.convert("RGB") if image.mode != "RGB" else image
+        
         processed_image = depth_anything_detector(image=image, resolution=self.resolution, offload=self.offload)
         return processed_image
 
@@ -617,7 +612,6 @@ class DWOpenposeImageProcessorInvocation(ImageProcessorInvocation):
     image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res)
 
     def run_processor(self, image: Image.Image):
-        image = image.convert("RGB") if image.mode != "RGB" else image
         dw_openpose = DWOpenposeDetector()
         processed_image = dw_openpose(
             image,

From cd070d8be9daf3992ce6c080015749fa35a3488a Mon Sep 17 00:00:00 2001
From: dunkeroni <dunkeroni@gmail.com>
Date: Sun, 18 Feb 2024 23:11:36 -0500
Subject: [PATCH 153/411] chore: ruff formatting

---
 invokeai/app/invocations/constants.py                   | 2 +-
 invokeai/app/invocations/controlnet_image_processors.py | 2 +-
 invokeai/app/invocations/image.py                       | 2 +-
 invokeai/app/services/shared/invocation_context.py      | 6 ++++--
 4 files changed, 7 insertions(+), 5 deletions(-)

diff --git a/invokeai/app/invocations/constants.py b/invokeai/app/invocations/constants.py
index fca5a2ec7f..cebe0eb30f 100644
--- a/invokeai/app/invocations/constants.py
+++ b/invokeai/app/invocations/constants.py
@@ -14,4 +14,4 @@ SCHEDULER_NAME_VALUES = Literal[tuple(SCHEDULER_MAP.keys())]
 """A literal type representing the valid scheduler names."""
 
 IMAGE_MODES = Literal["L", "RGB", "RGBA", "CMYK", "YCbCr", "LAB", "HSV", "I", "F"]
-"""A literal type for PIL image modes supported by Invoke"""
\ No newline at end of file
+"""A literal type for PIL image modes supported by Invoke"""
diff --git a/invokeai/app/invocations/controlnet_image_processors.py b/invokeai/app/invocations/controlnet_image_processors.py
index 1e998e4b61..8774f2fb27 100644
--- a/invokeai/app/invocations/controlnet_image_processors.py
+++ b/invokeai/app/invocations/controlnet_image_processors.py
@@ -591,7 +591,7 @@ class DepthAnythingImageProcessorInvocation(ImageProcessorInvocation):
     def run_processor(self, image: Image.Image):
         depth_anything_detector = DepthAnythingDetector()
         depth_anything_detector.load_model(model_size=self.model_size)
-        
+
         processed_image = depth_anything_detector(image=image, resolution=self.resolution, offload=self.offload)
         return processed_image
 
diff --git a/invokeai/app/invocations/image.py b/invokeai/app/invocations/image.py
index 1f3b5b7368..a0c41161c3 100644
--- a/invokeai/app/invocations/image.py
+++ b/invokeai/app/invocations/image.py
@@ -7,6 +7,7 @@ import cv2
 import numpy
 from PIL import Image, ImageChops, ImageFilter, ImageOps
 
+from invokeai.app.invocations.constants import IMAGE_MODES
 from invokeai.app.invocations.fields import (
     ColorField,
     FieldDescriptions,
@@ -16,7 +17,6 @@ from invokeai.app.invocations.fields import (
     WithMetadata,
 )
 from invokeai.app.invocations.primitives import ImageOutput
-from invokeai.app.invocations.constants import IMAGE_MODES
 from invokeai.app.services.image_records.image_records_common import ImageCategory
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.backend.image_util.invisible_watermark import InvisibleWatermark
diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index 2383785ad4..43ecb2c543 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -5,8 +5,8 @@ from typing import TYPE_CHECKING, Optional
 from PIL.Image import Image
 from torch import Tensor
 
-from invokeai.app.invocations.fields import MetadataField, WithBoard, WithMetadata
 from invokeai.app.invocations.constants import IMAGE_MODES
+from invokeai.app.invocations.fields import MetadataField, WithBoard, WithMetadata
 from invokeai.app.services.boards.boards_common import BoardDTO
 from invokeai.app.services.config.config_default import InvokeAIAppConfig
 from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
@@ -207,7 +207,9 @@ class ImagesInterface(InvocationContextInterface):
             try:
                 image = image.convert(mode)
             except ValueError:
-                self._services.logger.warning(f"Could not convert image from {image.mode} to {mode}. Using original mode instead.")
+                self._services.logger.warning(
+                    f"Could not convert image from {image.mode} to {mode}. Using original mode instead."
+                )
         return image
 
     def get_metadata(self, image_name: str) -> Optional[MetadataField]:

From 1242cb4f8511933f0fe2e86409dc97df1fa64b94 Mon Sep 17 00:00:00 2001
From: dunkeroni <dunkeroni@gmail.com>
Date: Sun, 18 Feb 2024 23:15:28 -0500
Subject: [PATCH 154/411] one more redundant RGB convert removed

---
 invokeai/app/invocations/controlnet_image_processors.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/invokeai/app/invocations/controlnet_image_processors.py b/invokeai/app/invocations/controlnet_image_processors.py
index 8774f2fb27..9eba3acdca 100644
--- a/invokeai/app/invocations/controlnet_image_processors.py
+++ b/invokeai/app/invocations/controlnet_image_processors.py
@@ -552,7 +552,6 @@ class ColorMapImageProcessorInvocation(ImageProcessorInvocation):
     color_map_tile_size: int = InputField(default=64, ge=0, description=FieldDescriptions.tile_size)
 
     def run_processor(self, image: Image.Image):
-        image = image.convert("RGB")
         np_image = np.array(image, dtype=np.uint8)
         height, width = np_image.shape[:2]
 

From af2117dc0c1f13030cdb26be033da44948a2d50f Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lstein@gmail.com>
Date: Sun, 18 Feb 2024 18:02:58 -0500
Subject: [PATCH 155/411] remove errant def that was crashing
 invokeai-configure

---
 .../backend/install/invokeai_configure.py     | 25 ++++++++-----------
 invokeai/frontend/install/model_install.py    |  2 +-
 2 files changed, 12 insertions(+), 15 deletions(-)

diff --git a/invokeai/backend/install/invokeai_configure.py b/invokeai/backend/install/invokeai_configure.py
index 4dfa2b070c..ac3e583de3 100755
--- a/invokeai/backend/install/invokeai_configure.py
+++ b/invokeai/backend/install/invokeai_configure.py
@@ -84,6 +84,8 @@ _, MAX_VRAM = torch.cuda.mem_get_info() if HAS_CUDA else (0.0, 0.0)
 MAX_VRAM /= GB
 MAX_RAM = psutil.virtual_memory().total / GB
 
+FORCE_FULL_PRECISION = False
+
 INIT_FILE_PREAMBLE = """# InvokeAI initialization file
 # This is the InvokeAI initialization file, which contains command-line default values.
 # Feel free to edit. If anything goes wrong, you can re-initialize this file by deleting
@@ -112,9 +114,6 @@ then run one of the following commands to start InvokeAI.
 Web UI:
    invokeai-web
 
-Command-line client:
-   invokeai
-
 If you installed using an installation script, run:
   {config.root_path}/invoke.{"bat" if sys.platform == "win32" else "sh"}
 
@@ -408,7 +407,7 @@ Use cursor arrows to make a checkbox selection, and space to toggle.
             begin_entry_at=3,
             max_height=2,
             relx=30,
-            max_width=56,
+            max_width=80,
             scroll_exit=True,
         )
         self.add_widget_intelligent(
@@ -664,7 +663,6 @@ https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/blob/main/LICENS
         generation_options = [GENERATION_OPT_CHOICES[x] for x in self.generation_options.value]
         for v in GENERATION_OPT_CHOICES:
             setattr(new_opts, v, v in generation_options)
-
         return new_opts
 
 
@@ -695,9 +693,6 @@ class EditOptApplication(npyscreen.NPSAppManaged):
                 cycle_widgets=False,
             )
 
-    def new_opts(self) -> Namespace:
-        return self.options.marshall_arguments()
-
 
 def default_ramcache() -> float:
     """Run a heuristic for the default RAM cache based on installed RAM."""
@@ -712,6 +707,7 @@ def default_ramcache() -> float:
 def default_startup_options(init_file: Path) -> InvokeAIAppConfig:
     opts = InvokeAIAppConfig.get_config()
     opts.ram = default_ramcache()
+    opts.precision = "float32" if FORCE_FULL_PRECISION else choose_precision(torch.device(choose_torch_device()))
     return opts
 
 
@@ -760,7 +756,8 @@ def initialize_rootdir(root: Path, yes_to_all: bool = False):
 def run_console_ui(
     program_opts: Namespace, initfile: Path, install_helper: InstallHelper
 ) -> Tuple[Optional[Namespace], Optional[InstallSelections]]:
-    invokeai_opts = default_startup_options(initfile)
+    first_time = not (config.root_path / "invokeai.yaml").exists()
+    invokeai_opts = default_startup_options(initfile) if first_time else config
     invokeai_opts.root = program_opts.root
 
     if not set_min_terminal_size(MIN_COLS, MIN_LINES):
@@ -773,7 +770,7 @@ def run_console_ui(
     if editApp.user_cancelled:
         return (None, None)
     else:
-        return (editApp.new_opts(), editApp.install_selections)
+        return (editApp.new_opts, editApp.install_selections)
 
 
 # -------------------------------------
@@ -785,7 +782,7 @@ def write_opts(opts: InvokeAIAppConfig, init_file: Path) -> None:
     new_config = InvokeAIAppConfig.get_config()
     new_config.root = config.root
 
-    for key, value in opts.model_dump().items():
+    for key, value in vars(opts).items():
         if hasattr(new_config, key):
             setattr(new_config, key, value)
 
@@ -869,7 +866,8 @@ def migrate_if_needed(opt: Namespace, root: Path) -> bool:
 
 
 # -------------------------------------
-def main():
+def main() -> None:
+    global FORCE_FULL_PRECISION  # FIXME
     parser = argparse.ArgumentParser(description="InvokeAI model downloader")
     parser.add_argument(
         "--skip-sd-weights",
@@ -921,17 +919,16 @@ def main():
         help="path to root of install directory",
     )
     opt = parser.parse_args()
-
     invoke_args = []
     if opt.root:
         invoke_args.extend(["--root", opt.root])
     if opt.full_precision:
         invoke_args.extend(["--precision", "float32"])
     config.parse_args(invoke_args)
-    config.precision = "float32" if opt.full_precision else choose_precision(torch.device(choose_torch_device()))
     logger = InvokeAILogger().get_logger(config=config)
 
     errors = set()
+    FORCE_FULL_PRECISION = opt.full_precision  # FIXME global
 
     try:
         # if we do a root migration/upgrade, then we are keeping previous
diff --git a/invokeai/frontend/install/model_install.py b/invokeai/frontend/install/model_install.py
index 20b630dfc6..3a4d66ae0a 100644
--- a/invokeai/frontend/install/model_install.py
+++ b/invokeai/frontend/install/model_install.py
@@ -43,7 +43,7 @@ from invokeai.frontend.install.widgets import (
 warnings.filterwarnings("ignore", category=UserWarning)  # noqa: E402
 config = InvokeAIAppConfig.get_config()
 logger = InvokeAILogger.get_logger("ModelInstallService")
-logger.setLevel("WARNING")
+# logger.setLevel("WARNING")
 # logger.setLevel('DEBUG')
 
 # build a table mapping all non-printable characters to None

From 731860c332a00286a4f54383e5ff3224b56478a9 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 17 Feb 2024 11:22:08 +1100
Subject: [PATCH 156/411] feat(nodes): JIT graph nodes validation

We use pydantic to validate a union of valid invocations when instantiating a graph.

Previously, we constructed the union while creating the `Graph` class. This introduces a dependency on the order of imports.

For example, consider a setup where we have 3 invocations in the app:

- Python executes the module where `FirstInvocation` is defined, registering `FirstInvocation`.
- Python executes the module where `SecondInvocation` is defined, registering `SecondInvocation`.
- Python executes the module where `Graph` is defined. A union of invocations is created and used to define the `Graph.nodes` field. The union contains `FirstInvocation` and `SecondInvocation`.
- Python executes the module where `ThirdInvocation` is defined, registering `ThirdInvocation`.
- A graph is created that includes `ThirdInvocation`. Pydantic validates the graph using the union, which does not know about `ThirdInvocation`, raising a `ValidationError` about an unknown invocation type.

This scenario has been particularly problematic in tests, where we may create invocations dynamically. The test files have to be structured in such a way that the imports happen in the right order. It's a major pain.

This PR refactors the validation of graph nodes to resolve this issue:

- `BaseInvocation` gets a new method `get_typeadapter`. This builds a pydantic `TypeAdapter` for the union of all registered invocations, caching it after the first call.
- `Graph.nodes`'s type is widened to `dict[str, BaseInvocation]`. This actually is a nice bonus, because we get better type hints whenever we reference `some_graph.nodes`.
- A "plain" field validator takes over the validation logic for `Graph.nodes`. "Plain" validators totally override pydantic's own validation logic. The validator grabs the `TypeAdapter` from `BaseInvocation`, then validates each node with it. The validation is identical to the previous implementation - we get the same errors.

`BaseInvocationOutput` gets the same treatment.
---
 invokeai/app/invocations/baseinvocation.py | 45 ++++++++++++++++------
 invokeai/app/invocations/compel.py         |  2 +-
 invokeai/app/services/shared/graph.py      | 41 +++++++++++++-------
 3 files changed, 63 insertions(+), 25 deletions(-)

diff --git a/invokeai/app/invocations/baseinvocation.py b/invokeai/app/invocations/baseinvocation.py
index 3243714937..5edae5342d 100644
--- a/invokeai/app/invocations/baseinvocation.py
+++ b/invokeai/app/invocations/baseinvocation.py
@@ -8,13 +8,26 @@ import warnings
 from abc import ABC, abstractmethod
 from enum import Enum
 from inspect import signature
-from types import UnionType
-from typing import TYPE_CHECKING, Any, Callable, ClassVar, Iterable, Literal, Optional, Type, TypeVar, Union, cast
+from typing import (
+    TYPE_CHECKING,
+    Annotated,
+    Any,
+    Callable,
+    ClassVar,
+    Iterable,
+    Literal,
+    Optional,
+    Type,
+    TypeVar,
+    Union,
+    cast,
+)
 
 import semver
-from pydantic import BaseModel, ConfigDict, Field, create_model
+from pydantic import BaseModel, ConfigDict, Field, TypeAdapter, create_model
 from pydantic.fields import FieldInfo
 from pydantic_core import PydanticUndefined
+from typing_extensions import TypeAliasType
 
 from invokeai.app.invocations.fields import (
     FieldKind,
@@ -84,6 +97,7 @@ class BaseInvocationOutput(BaseModel):
     """
 
     _output_classes: ClassVar[set[BaseInvocationOutput]] = set()
+    _typeadapter: ClassVar[Optional[TypeAdapter[Any]]] = None
 
     @classmethod
     def register_output(cls, output: BaseInvocationOutput) -> None:
@@ -96,10 +110,14 @@ class BaseInvocationOutput(BaseModel):
         return cls._output_classes
 
     @classmethod
-    def get_outputs_union(cls) -> UnionType:
-        """Gets a union of all invocation outputs."""
-        outputs_union = Union[tuple(cls._output_classes)]  # type: ignore [valid-type]
-        return outputs_union  # type: ignore [return-value]
+    def get_typeadapter(cls) -> TypeAdapter[Any]:
+        """Gets a pydantc TypeAdapter for the union of all invocation output types."""
+        if not cls._typeadapter:
+            InvocationOutputsUnion = TypeAliasType(
+                "InvocationOutputsUnion", Annotated[Union[tuple(cls._output_classes)], Field(discriminator="type")]
+            )
+            cls._typeadapter = TypeAdapter(InvocationOutputsUnion)
+        return cls._typeadapter
 
     @classmethod
     def get_output_types(cls) -> Iterable[str]:
@@ -148,6 +166,7 @@ class BaseInvocation(ABC, BaseModel):
     """
 
     _invocation_classes: ClassVar[set[BaseInvocation]] = set()
+    _typeadapter: ClassVar[Optional[TypeAdapter[Any]]] = None
 
     @classmethod
     def get_type(cls) -> str:
@@ -160,10 +179,14 @@ class BaseInvocation(ABC, BaseModel):
         cls._invocation_classes.add(invocation)
 
     @classmethod
-    def get_invocations_union(cls) -> UnionType:
-        """Gets a union of all invocation types."""
-        invocations_union = Union[tuple(cls._invocation_classes)]  # type: ignore [valid-type]
-        return invocations_union  # type: ignore [return-value]
+    def get_typeadapter(cls) -> TypeAdapter[Any]:
+        """Gets a pydantc TypeAdapter for the union of all invocation types."""
+        if not cls._typeadapter:
+            InvocationsUnion = TypeAliasType(
+                "InvocationsUnion", Annotated[Union[tuple(cls._invocation_classes)], Field(discriminator="type")]
+            )
+            cls._typeadapter = TypeAdapter(InvocationsUnion)
+        return cls._typeadapter
 
     @classmethod
     def get_invocations(cls) -> Iterable[BaseInvocation]:
diff --git a/invokeai/app/invocations/compel.py b/invokeai/app/invocations/compel.py
index 517da4375e..47be380626 100644
--- a/invokeai/app/invocations/compel.py
+++ b/invokeai/app/invocations/compel.py
@@ -417,7 +417,7 @@ class ClipSkipInvocation(BaseInvocation):
     """Skip layers in clip text_encoder model."""
 
     clip: ClipField = InputField(description=FieldDescriptions.clip, input=Input.Connection, title="CLIP")
-    skipped_layers: int = InputField(default=0, description=FieldDescriptions.skipped_layers)
+    skipped_layers: int = InputField(default=0, ge=0, description=FieldDescriptions.skipped_layers)
 
     def invoke(self, context: InvocationContext) -> ClipSkipInvocationOutput:
         self.clip.skipped_layers += self.skipped_layers
diff --git a/invokeai/app/services/shared/graph.py b/invokeai/app/services/shared/graph.py
index 3df230f5ee..3066af0e50 100644
--- a/invokeai/app/services/shared/graph.py
+++ b/invokeai/app/services/shared/graph.py
@@ -2,10 +2,15 @@
 
 import copy
 import itertools
-from typing import Annotated, Any, Optional, TypeVar, Union, get_args, get_origin, get_type_hints
+from typing import Any, Optional, TypeVar, Union, get_args, get_origin, get_type_hints
 
 import networkx as nx
-from pydantic import BaseModel, ConfigDict, field_validator, model_validator
+from pydantic import (
+    BaseModel,
+    ConfigDict,
+    field_validator,
+    model_validator,
+)
 from pydantic.fields import Field
 
 # Importing * is bad karma but needed here for node detection
@@ -260,21 +265,24 @@ class CollectInvocation(BaseInvocation):
         return CollectInvocationOutput(collection=copy.copy(self.collection))
 
 
-InvocationsUnion: Any = BaseInvocation.get_invocations_union()
-InvocationOutputsUnion: Any = BaseInvocationOutput.get_outputs_union()
-
-
 class Graph(BaseModel):
     id: str = Field(description="The id of this graph", default_factory=uuid_string)
     # TODO: use a list (and never use dict in a BaseModel) because pydantic/fastapi hates me
-    nodes: dict[str, Annotated[InvocationsUnion, Field(discriminator="type")]] = Field(
-        description="The nodes in this graph", default_factory=dict
-    )
+    nodes: dict[str, BaseInvocation] = Field(description="The nodes in this graph", default_factory=dict)
     edges: list[Edge] = Field(
         description="The connections between nodes and their fields in this graph",
         default_factory=list,
     )
 
+    @field_validator("nodes", mode="plain")
+    @classmethod
+    def validate_nodes(cls, v: dict[str, Any]):
+        nodes: dict[str, BaseInvocation] = {}
+        typeadapter = BaseInvocation.get_typeadapter()
+        for node_id, node in v.items():
+            nodes[node_id] = typeadapter.validate_python(node)
+        return nodes
+
     def add_node(self, node: BaseInvocation) -> None:
         """Adds a node to a graph
 
@@ -824,9 +832,7 @@ class GraphExecutionState(BaseModel):
     )
 
     # The results of executed nodes
-    results: dict[str, Annotated[InvocationOutputsUnion, Field(discriminator="type")]] = Field(
-        description="The results of node executions", default_factory=dict
-    )
+    results: dict[str, BaseInvocationOutput] = Field(description="The results of node executions", default_factory=dict)
 
     # Errors raised when executing nodes
     errors: dict[str, str] = Field(description="Errors raised when executing nodes", default_factory=dict)
@@ -843,6 +849,15 @@ class GraphExecutionState(BaseModel):
         default_factory=dict,
     )
 
+    @field_validator("results", mode="plain")
+    @classmethod
+    def validate_results(cls, v: dict[str, BaseInvocationOutput]):
+        results: dict[str, BaseInvocationOutput] = {}
+        typeadapter = BaseInvocationOutput.get_typeadapter()
+        for result_id, result in v.items():
+            results[result_id] = typeadapter.validate_python(result)
+        return results
+
     @field_validator("graph")
     def graph_is_valid(cls, v: Graph):
         """Validates that the graph is valid"""
@@ -1247,6 +1262,6 @@ class LibraryGraph(BaseModel):
         return values
 
 
-GraphInvocation.model_rebuild(force=True)
 Graph.model_rebuild(force=True)
+GraphInvocation.model_rebuild(force=True)
 GraphExecutionState.model_rebuild(force=True)

From b79ae3a10132aeb3b9a338af6bd5cb22557ca709 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 17 Feb 2024 18:19:22 +1100
Subject: [PATCH 157/411] fix(nodes): fix OpenAPI schema generation

The change to `Graph.nodes` and `GraphExecutionState.results` validation requires some fanagling to get the OpenAPI schema generation to work. See new comments for a details.
---
 invokeai/app/api_app.py               |  3 +-
 invokeai/app/services/shared/graph.py | 90 +++++++++++++++++++++++++--
 2 files changed, 86 insertions(+), 7 deletions(-)

diff --git a/invokeai/app/api_app.py b/invokeai/app/api_app.py
index 149d47fb96..65607c436a 100644
--- a/invokeai/app/api_app.py
+++ b/invokeai/app/api_app.py
@@ -151,6 +151,8 @@ def custom_openapi() -> dict[str, Any]:
         # TODO: note that we assume the schema_key here is the TYPE.__name__
         # This could break in some cases, figure out a better way to do it
         output_type_titles[schema_key] = output_schema["title"]
+        openapi_schema["components"]["schemas"][schema_key] = output_schema
+        openapi_schema["components"]["schemas"][schema_key]["class"] = "output"
 
     # Add Node Editor UI helper schemas
     ui_config_schemas = models_json_schema(
@@ -173,7 +175,6 @@ def custom_openapi() -> dict[str, Any]:
         outputs_ref = {"$ref": f"#/components/schemas/{output_type_title}"}
         invoker_schema["output"] = outputs_ref
         invoker_schema["class"] = "invocation"
-        openapi_schema["components"]["schemas"][f"{output_type_title}"]["class"] = "output"
 
     # This code no longer seems to be necessary?
     # Leave it here just in case
diff --git a/invokeai/app/services/shared/graph.py b/invokeai/app/services/shared/graph.py
index 3066af0e50..1b53f64222 100644
--- a/invokeai/app/services/shared/graph.py
+++ b/invokeai/app/services/shared/graph.py
@@ -2,16 +2,19 @@
 
 import copy
 import itertools
-from typing import Any, Optional, TypeVar, Union, get_args, get_origin, get_type_hints
+from typing import Annotated, Any, Optional, TypeVar, Union, get_args, get_origin, get_type_hints
 
 import networkx as nx
 from pydantic import (
     BaseModel,
     ConfigDict,
+    GetJsonSchemaHandler,
     field_validator,
     model_validator,
 )
 from pydantic.fields import Field
+from pydantic.json_schema import JsonSchemaValue
+from pydantic_core import CoreSchema
 
 # Importing * is bad karma but needed here for node detection
 from invokeai.app.invocations import *  # noqa: F401 F403
@@ -277,12 +280,61 @@ class Graph(BaseModel):
     @field_validator("nodes", mode="plain")
     @classmethod
     def validate_nodes(cls, v: dict[str, Any]):
+        """Validates the nodes in the graph by retrieving a union of all node types and validating each node."""
+
+        # Invocations register themselves as their python modules are executed. The union of all invocations is
+        # constructed at runtime. We use pydantic to validate `Graph.nodes` using that union.
+        #
+        # It's possible that when `graph.py` is executed, not all invocation-containing modules will have executed. If
+        # we construct the invocation union as `graph.py` is executed, we may miss some invocations. Those missing
+        # invocations will cause a graph to fail if they are used.
+        #
+        # We can get around this by validating the nodes in the graph using a "plain" validator, which overrides the
+        # pydantic validation entirely. This allows us to validate the nodes using the union of invocations at runtime.
+        #
+        # This same pattern is used in `GraphExecutionState`.
+
         nodes: dict[str, BaseInvocation] = {}
         typeadapter = BaseInvocation.get_typeadapter()
         for node_id, node in v.items():
             nodes[node_id] = typeadapter.validate_python(node)
         return nodes
 
+    @classmethod
+    def __get_pydantic_json_schema__(cls, core_schema: CoreSchema, handler: GetJsonSchemaHandler) -> JsonSchemaValue:
+        # We use a "plain" validator to validate the nodes in the graph. Pydantic is unable to create a JSON Schema for
+        # fields that use "plain" validators, so we have to hack around this. Also, we need to add all invocations to
+        # the generated schema as options for the `nodes` field.
+        #
+        # The workaround is to create a new BaseModel that has the same fields as `Graph` but without the validator and
+        # with the invocation union as the type for the `nodes` field. Pydantic then generates the JSON Schema as
+        # expected.
+        #
+        # You might be tempted to do something like this:
+        #
+        # ```py
+        # cloned_model = create_model(cls.__name__, __base__=cls, nodes=...)
+        # delattr(cloned_model, "validate_nodes")
+        # cloned_model.model_rebuild(force=True)
+        # json_schema = handler(cloned_model.__pydantic_core_schema__)
+        # ```
+        #
+        # Unfortunately, this does not work. Calling `handler` here results in infinite recursion as pydantic attempts
+        # to build the JSON Schema for the cloned model. Instead, we have to manually clone the model.
+        #
+        # This same pattern is used in `GraphExecutionState`.
+
+        class Graph(BaseModel):
+            id: Optional[str] = Field(default=None, description="The id of this graph")
+            nodes: dict[
+                str, Annotated[Union[tuple(BaseInvocation._invocation_classes)], Field(discriminator="type")]
+            ] = Field(description="The nodes in this graph")
+            edges: list[Edge] = Field(description="The connections between nodes and their fields in this graph")
+
+        json_schema = handler(Graph.__pydantic_core_schema__)
+        json_schema = handler.resolve_ref_schema(json_schema)
+        return json_schema
+
     def add_node(self, node: BaseInvocation) -> None:
         """Adds a node to a graph
 
@@ -852,6 +904,9 @@ class GraphExecutionState(BaseModel):
     @field_validator("results", mode="plain")
     @classmethod
     def validate_results(cls, v: dict[str, BaseInvocationOutput]):
+        """Validates the results in the GES by retrieving a union of all output types and validating each result."""
+
+        # See the comment in `Graph.validate_nodes` for an explanation of this logic.
         results: dict[str, BaseInvocationOutput] = {}
         typeadapter = BaseInvocationOutput.get_typeadapter()
         for result_id, result in v.items():
@@ -864,6 +919,34 @@ class GraphExecutionState(BaseModel):
         v.validate_self()
         return v
 
+    @classmethod
+    def __get_pydantic_json_schema__(cls, core_schema: CoreSchema, handler: GetJsonSchemaHandler) -> JsonSchemaValue:
+        # See the comment in `Graph.__get_pydantic_json_schema__` for an explanation of this logic.
+        class GraphExecutionState(BaseModel):
+            """Tracks the state of a graph execution"""
+
+            id: str = Field(description="The id of the execution state")
+            graph: Graph = Field(description="The graph being executed")
+            execution_graph: Graph = Field(description="The expanded graph of activated and executed nodes")
+            executed: set[str] = Field(description="The set of node ids that have been executed")
+            executed_history: list[str] = Field(
+                description="The list of node ids that have been executed, in order of execution"
+            )
+            results: dict[
+                str, Annotated[Union[tuple(BaseInvocationOutput._output_classes)], Field(discriminator="type")]
+            ] = Field(description="The results of node executions")
+            errors: dict[str, str] = Field(description="Errors raised when executing nodes")
+            prepared_source_mapping: dict[str, str] = Field(
+                description="The map of prepared nodes to original graph nodes"
+            )
+            source_prepared_mapping: dict[str, set[str]] = Field(
+                description="The map of original graph nodes to prepared nodes"
+            )
+
+        json_schema = handler(GraphExecutionState.__pydantic_core_schema__)
+        json_schema = handler.resolve_ref_schema(json_schema)
+        return json_schema
+
     model_config = ConfigDict(
         json_schema_extra={
             "required": [
@@ -1260,8 +1343,3 @@ class LibraryGraph(BaseModel):
                 )
 
         return values
-
-
-Graph.model_rebuild(force=True)
-GraphInvocation.model_rebuild(force=True)
-GraphExecutionState.model_rebuild(force=True)

From 641d235102d786c7d3556e1403fbfc8102f6ef38 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 17 Feb 2024 19:56:13 +1100
Subject: [PATCH 158/411] tidy(nodes): remove GraphInvocation

`GraphInvocation` is a node that can contain a whole graph. It is removed for a number of reasons:

1. This feature was unused (the UI doesn't support it) and there is no plan for it to be used.

The use-case it served is known in other node execution engines as "node groups" or "blocks" - a self-contained group of nodes, which has group inputs and outputs. This is a planned feature that will be handled client-side.

2. It adds substantial complexity to the graph processing logic. It's probably not enough to have a measurable performance impact but it does make it harder to work in the graph logic.

3. It allows for graphs to be recursive, and the improved invocations union handling does not play well with it. Actually, it works fine within `graph.py` but not in the tests for some reason. I do not understand why. There's probably a workaround, but I took this as encouragement to remove `GraphInvocation` from the app since we don't use it.
---
 invokeai/app/services/shared/graph.py | 292 +++++++-------------------
 tests/aa_nodes/test_invoker.py        |  13 +-
 tests/aa_nodes/test_node_graph.py     | 168 ++++++++-------
 tests/aa_nodes/test_session_queue.py  |  41 ++--
 4 files changed, 178 insertions(+), 336 deletions(-)

diff --git a/invokeai/app/services/shared/graph.py b/invokeai/app/services/shared/graph.py
index 1b53f64222..4df9f0c4b0 100644
--- a/invokeai/app/services/shared/graph.py
+++ b/invokeai/app/services/shared/graph.py
@@ -184,10 +184,6 @@ class NodeIdMismatchError(ValueError):
     pass
 
 
-class InvalidSubGraphError(ValueError):
-    pass
-
-
 class CyclicalGraphError(ValueError):
     pass
 
@@ -196,25 +192,6 @@ class UnknownGraphValidationError(ValueError):
     pass
 
 
-# TODO: Create and use an Empty output?
-@invocation_output("graph_output")
-class GraphInvocationOutput(BaseInvocationOutput):
-    pass
-
-
-# TODO: Fill this out and move to invocations
-@invocation("graph", version="1.0.0")
-class GraphInvocation(BaseInvocation):
-    """Execute a graph"""
-
-    # TODO: figure out how to create a default here
-    graph: "Graph" = InputField(description="The graph to run", default=None)
-
-    def invoke(self, context: InvocationContext) -> GraphInvocationOutput:
-        """Invoke with provided services and return outputs."""
-        return GraphInvocationOutput()
-
-
 @invocation_output("iterate_output")
 class IterateInvocationOutput(BaseInvocationOutput):
     """Used to connect iteration outputs. Will be expanded to a specific output."""
@@ -346,41 +323,21 @@ class Graph(BaseModel):
 
         self.nodes[node.id] = node
 
-    def _get_graph_and_node(self, node_path: str) -> tuple["Graph", str]:
-        """Returns the graph and node id for a node path."""
-        # Materialized graphs may have nodes at the top level
-        if node_path in self.nodes:
-            return (self, node_path)
-
-        node_id = node_path if "." not in node_path else node_path[: node_path.index(".")]
-        if node_id not in self.nodes:
-            raise NodeNotFoundError(f"Node {node_path} not found in graph")
-
-        node = self.nodes[node_id]
-
-        if not isinstance(node, GraphInvocation):
-            # There's more node path left but this isn't a graph - failure
-            raise NodeNotFoundError("Node path terminated early at a non-graph node")
-
-        return node.graph._get_graph_and_node(node_path[node_path.index(".") + 1 :])
-
-    def delete_node(self, node_path: str) -> None:
+    def delete_node(self, node_id: str) -> None:
         """Deletes a node from a graph"""
 
         try:
-            graph, node_id = self._get_graph_and_node(node_path)
-
             # Delete edges for this node
-            input_edges = self._get_input_edges_and_graphs(node_path)
-            output_edges = self._get_output_edges_and_graphs(node_path)
+            input_edges = self._get_input_edges(node_id)
+            output_edges = self._get_output_edges(node_id)
 
-            for edge_graph, _, edge in input_edges:
-                edge_graph.delete_edge(edge)
+            for edge in input_edges:
+                self.delete_edge(edge)
 
-            for edge_graph, _, edge in output_edges:
-                edge_graph.delete_edge(edge)
+            for edge in output_edges:
+                self.delete_edge(edge)
 
-            del graph.nodes[node_id]
+            del self.nodes[node_id]
 
         except NodeNotFoundError:
             pass  # Ignore, not doesn't exist (should this throw?)
@@ -430,13 +387,6 @@ class Graph(BaseModel):
             if k != v.id:
                 raise NodeIdMismatchError(f"Node ids must match, got {k} and {v.id}")
 
-        # Validate all subgraphs
-        for gn in (n for n in self.nodes.values() if isinstance(n, GraphInvocation)):
-            try:
-                gn.graph.validate_self()
-            except Exception as e:
-                raise InvalidSubGraphError(f"Subgraph {gn.id} is invalid") from e
-
         # Validate that all edges match nodes and fields in the graph
         for edge in self.edges:
             source_node = self.nodes.get(edge.source.node_id, None)
@@ -498,7 +448,6 @@ class Graph(BaseModel):
         except (
             DuplicateNodeIdError,
             NodeIdMismatchError,
-            InvalidSubGraphError,
             NodeNotFoundError,
             NodeFieldNotFoundError,
             CyclicalGraphError,
@@ -519,7 +468,7 @@ class Graph(BaseModel):
     def _validate_edge(self, edge: Edge):
         """Validates that a new edge doesn't create a cycle in the graph"""
 
-        # Validate that the nodes exist (edges may contain node paths, so we can't just check for nodes directly)
+        # Validate that the nodes exist
         try:
             from_node = self.get_node(edge.source.node_id)
             to_node = self.get_node(edge.destination.node_id)
@@ -586,171 +535,90 @@ class Graph(BaseModel):
                     f"Collector input type does not match collector output type: {edge.source.node_id}.{edge.source.field} to {edge.destination.node_id}.{edge.destination.field}"
                 )
 
-    def has_node(self, node_path: str) -> bool:
+    def has_node(self, node_id: str) -> bool:
         """Determines whether or not a node exists in the graph."""
         try:
-            n = self.get_node(node_path)
-            if n is not None:
-                return True
-            else:
-                return False
+            _ = self.get_node(node_id)
+            return True
         except NodeNotFoundError:
             return False
 
-    def get_node(self, node_path: str) -> BaseInvocation:
-        """Gets a node from the graph using a node path."""
-        # Materialized graphs may have nodes at the top level
-        graph, node_id = self._get_graph_and_node(node_path)
-        return graph.nodes[node_id]
+    def get_node(self, node_id: str) -> BaseInvocation:
+        """Gets a node from the graph."""
+        try:
+            return self.nodes[node_id]
+        except KeyError as e:
+            raise NodeNotFoundError(f"Node {node_id} not found in graph") from e
 
-    def _get_node_path(self, node_id: str, prefix: Optional[str] = None) -> str:
-        return node_id if prefix is None or prefix == "" else f"{prefix}.{node_id}"
-
-    def update_node(self, node_path: str, new_node: BaseInvocation) -> None:
+    def update_node(self, node_id: str, new_node: BaseInvocation) -> None:
         """Updates a node in the graph."""
-        graph, node_id = self._get_graph_and_node(node_path)
-        node = graph.nodes[node_id]
+        node = self.nodes[node_id]
 
         # Ensure the node type matches the new node
         if type(node) is not type(new_node):
-            raise TypeError(f"Node {node_path} is type {type(node)} but new node is type {type(new_node)}")
+            raise TypeError(f"Node {node_id} is type {type(node)} but new node is type {type(new_node)}")
 
         # Ensure the new id is either the same or is not in the graph
-        prefix = None if "." not in node_path else node_path[: node_path.rindex(".")]
-        new_path = self._get_node_path(new_node.id, prefix=prefix)
-        if new_node.id != node.id and self.has_node(new_path):
-            raise NodeAlreadyInGraphError("Node with id {new_node.id} already exists in graph")
+        if new_node.id != node.id and self.has_node(new_node.id):
+            raise NodeAlreadyInGraphError(f"Node with id {new_node.id} already exists in graph")
 
         # Set the new node in the graph
-        graph.nodes[new_node.id] = new_node
+        self.nodes[new_node.id] = new_node
         if new_node.id != node.id:
-            input_edges = self._get_input_edges_and_graphs(node_path)
-            output_edges = self._get_output_edges_and_graphs(node_path)
+            input_edges = self._get_input_edges(node_id)
+            output_edges = self._get_output_edges(node_id)
 
             # Delete node and all edges
-            graph.delete_node(node_path)
+            self.delete_node(node_id)
 
             # Create new edges for each input and output
-            for graph, _, edge in input_edges:
-                # Remove the graph prefix from the node path
-                new_graph_node_path = (
-                    new_node.id
-                    if "." not in edge.destination.node_id
-                    else f'{edge.destination.node_id[edge.destination.node_id.rindex("."):]}.{new_node.id}'
-                )
-                graph.add_edge(
+            for edge in input_edges:
+                self.add_edge(
                     Edge(
                         source=edge.source,
-                        destination=EdgeConnection(node_id=new_graph_node_path, field=edge.destination.field),
+                        destination=EdgeConnection(node_id=new_node.id, field=edge.destination.field),
                     )
                 )
 
-            for graph, _, edge in output_edges:
-                # Remove the graph prefix from the node path
-                new_graph_node_path = (
-                    new_node.id
-                    if "." not in edge.source.node_id
-                    else f'{edge.source.node_id[edge.source.node_id.rindex("."):]}.{new_node.id}'
-                )
-                graph.add_edge(
+            for edge in output_edges:
+                self.add_edge(
                     Edge(
-                        source=EdgeConnection(node_id=new_graph_node_path, field=edge.source.field),
+                        source=EdgeConnection(node_id=new_node.id, field=edge.source.field),
                         destination=edge.destination,
                     )
                 )
 
-    def _get_input_edges(self, node_path: str, field: Optional[str] = None) -> list[Edge]:
-        """Gets all input edges for a node"""
-        edges = self._get_input_edges_and_graphs(node_path)
+    def _get_input_edges(self, node_id: str, field: Optional[str] = None) -> list[Edge]:
+        """Gets all input edges for a node. If field is provided, only edges to that field are returned."""
 
-        # Filter to edges that match the field
-        filtered_edges = (e for e in edges if field is None or e[2].destination.field == field)
+        edges = [e for e in self.edges if e.destination.node_id == node_id]
 
-        # Create full node paths for each edge
-        return [
-            Edge(
-                source=EdgeConnection(
-                    node_id=self._get_node_path(e.source.node_id, prefix=prefix),
-                    field=e.source.field,
-                ),
-                destination=EdgeConnection(
-                    node_id=self._get_node_path(e.destination.node_id, prefix=prefix),
-                    field=e.destination.field,
-                ),
-            )
-            for _, prefix, e in filtered_edges
-        ]
+        if field is None:
+            return edges
 
-    def _get_input_edges_and_graphs(
-        self, node_path: str, prefix: Optional[str] = None
-    ) -> list[tuple["Graph", Union[str, None], Edge]]:
-        """Gets all input edges for a node along with the graph they are in and the graph's path"""
-        edges = []
+        filtered_edges = [e for e in edges if e.destination.field == field]
 
-        # Return any input edges that appear in this graph
-        edges.extend([(self, prefix, e) for e in self.edges if e.destination.node_id == node_path])
+        return filtered_edges
 
-        node_id = node_path if "." not in node_path else node_path[: node_path.index(".")]
-        node = self.nodes[node_id]
+    def _get_output_edges(self, node_id: str, field: Optional[str] = None) -> list[Edge]:
+        """Gets all output edges for a node. If field is provided, only edges from that field are returned."""
+        edges = [e for e in self.edges if e.source.node_id == node_id]
 
-        if isinstance(node, GraphInvocation):
-            graph = node.graph
-            graph_path = node.id if prefix is None or prefix == "" else self._get_node_path(node.id, prefix=prefix)
-            graph_edges = graph._get_input_edges_and_graphs(node_path[(len(node_id) + 1) :], prefix=graph_path)
-            edges.extend(graph_edges)
+        if field is None:
+            return edges
 
-        return edges
+        filtered_edges = [e for e in edges if e.source.field == field]
 
-    def _get_output_edges(self, node_path: str, field: str) -> list[Edge]:
-        """Gets all output edges for a node"""
-        edges = self._get_output_edges_and_graphs(node_path)
-
-        # Filter to edges that match the field
-        filtered_edges = (e for e in edges if e[2].source.field == field)
-
-        # Create full node paths for each edge
-        return [
-            Edge(
-                source=EdgeConnection(
-                    node_id=self._get_node_path(e.source.node_id, prefix=prefix),
-                    field=e.source.field,
-                ),
-                destination=EdgeConnection(
-                    node_id=self._get_node_path(e.destination.node_id, prefix=prefix),
-                    field=e.destination.field,
-                ),
-            )
-            for _, prefix, e in filtered_edges
-        ]
-
-    def _get_output_edges_and_graphs(
-        self, node_path: str, prefix: Optional[str] = None
-    ) -> list[tuple["Graph", Union[str, None], Edge]]:
-        """Gets all output edges for a node along with the graph they are in and the graph's path"""
-        edges = []
-
-        # Return any input edges that appear in this graph
-        edges.extend([(self, prefix, e) for e in self.edges if e.source.node_id == node_path])
-
-        node_id = node_path if "." not in node_path else node_path[: node_path.index(".")]
-        node = self.nodes[node_id]
-
-        if isinstance(node, GraphInvocation):
-            graph = node.graph
-            graph_path = node.id if prefix is None or prefix == "" else self._get_node_path(node.id, prefix=prefix)
-            graph_edges = graph._get_output_edges_and_graphs(node_path[(len(node_id) + 1) :], prefix=graph_path)
-            edges.extend(graph_edges)
-
-        return edges
+        return filtered_edges
 
     def _is_iterator_connection_valid(
         self,
-        node_path: str,
+        node_id: str,
         new_input: Optional[EdgeConnection] = None,
         new_output: Optional[EdgeConnection] = None,
     ) -> bool:
-        inputs = [e.source for e in self._get_input_edges(node_path, "collection")]
-        outputs = [e.destination for e in self._get_output_edges(node_path, "item")]
+        inputs = [e.source for e in self._get_input_edges(node_id, "collection")]
+        outputs = [e.destination for e in self._get_output_edges(node_id, "item")]
 
         if new_input is not None:
             inputs.append(new_input)
@@ -778,12 +646,12 @@ class Graph(BaseModel):
 
     def _is_collector_connection_valid(
         self,
-        node_path: str,
+        node_id: str,
         new_input: Optional[EdgeConnection] = None,
         new_output: Optional[EdgeConnection] = None,
     ) -> bool:
-        inputs = [e.source for e in self._get_input_edges(node_path, "item")]
-        outputs = [e.destination for e in self._get_output_edges(node_path, "collection")]
+        inputs = [e.source for e in self._get_input_edges(node_id, "item")]
+        outputs = [e.destination for e in self._get_output_edges(node_id, "collection")]
 
         if new_input is not None:
             inputs.append(new_input)
@@ -839,27 +707,17 @@ class Graph(BaseModel):
         g.add_edges_from({(e.source.node_id, e.destination.node_id) for e in self.edges})
         return g
 
-    def nx_graph_flat(self, nx_graph: Optional[nx.DiGraph] = None, prefix: Optional[str] = None) -> nx.DiGraph:
+    def nx_graph_flat(self, nx_graph: Optional[nx.DiGraph] = None) -> nx.DiGraph:
         """Returns a flattened NetworkX DiGraph, including all subgraphs (but not with iterations expanded)"""
         g = nx_graph or nx.DiGraph()
 
         # Add all nodes from this graph except graph/iteration nodes
-        g.add_nodes_from(
-            [
-                self._get_node_path(n.id, prefix)
-                for n in self.nodes.values()
-                if not isinstance(n, GraphInvocation) and not isinstance(n, IterateInvocation)
-            ]
-        )
-
-        # Expand graph nodes
-        for sgn in (gn for gn in self.nodes.values() if isinstance(gn, GraphInvocation)):
-            g = sgn.graph.nx_graph_flat(g, self._get_node_path(sgn.id, prefix))
+        g.add_nodes_from([n.id for n in self.nodes.values() if not isinstance(n, IterateInvocation)])
 
         # TODO: figure out if iteration nodes need to be expanded
 
         unique_edges = {(e.source.node_id, e.destination.node_id) for e in self.edges}
-        g.add_edges_from([(self._get_node_path(e[0], prefix), self._get_node_path(e[1], prefix)) for e in unique_edges])
+        g.add_edges_from([(e[0], e[1]) for e in unique_edges])
         return g
 
 
@@ -1017,17 +875,17 @@ class GraphExecutionState(BaseModel):
         """Returns true if the graph has any errors"""
         return len(self.errors) > 0
 
-    def _create_execution_node(self, node_path: str, iteration_node_map: list[tuple[str, str]]) -> list[str]:
+    def _create_execution_node(self, node_id: str, iteration_node_map: list[tuple[str, str]]) -> list[str]:
         """Prepares an iteration node and connects all edges, returning the new node id"""
 
-        node = self.graph.get_node(node_path)
+        node = self.graph.get_node(node_id)
 
         self_iteration_count = -1
 
         # If this is an iterator node, we must create a copy for each iteration
         if isinstance(node, IterateInvocation):
             # Get input collection edge (should error if there are no inputs)
-            input_collection_edge = next(iter(self.graph._get_input_edges(node_path, "collection")))
+            input_collection_edge = next(iter(self.graph._get_input_edges(node_id, "collection")))
             input_collection_prepared_node_id = next(
                 n[1] for n in iteration_node_map if n[0] == input_collection_edge.source.node_id
             )
@@ -1041,7 +899,7 @@ class GraphExecutionState(BaseModel):
             return new_nodes
 
         # Get all input edges
-        input_edges = self.graph._get_input_edges(node_path)
+        input_edges = self.graph._get_input_edges(node_id)
 
         # Create new edges for this iteration
         # For collect nodes, this may contain multiple inputs to the same field
@@ -1068,10 +926,10 @@ class GraphExecutionState(BaseModel):
 
             # Add to execution graph
             self.execution_graph.add_node(new_node)
-            self.prepared_source_mapping[new_node.id] = node_path
-            if node_path not in self.source_prepared_mapping:
-                self.source_prepared_mapping[node_path] = set()
-            self.source_prepared_mapping[node_path].add(new_node.id)
+            self.prepared_source_mapping[new_node.id] = node_id
+            if node_id not in self.source_prepared_mapping:
+                self.source_prepared_mapping[node_id] = set()
+            self.source_prepared_mapping[node_id].add(new_node.id)
 
             # Add new edges to execution graph
             for edge in new_edges:
@@ -1175,13 +1033,13 @@ class GraphExecutionState(BaseModel):
 
     def _get_iteration_node(
         self,
-        source_node_path: str,
+        source_node_id: str,
         graph: nx.DiGraph,
         execution_graph: nx.DiGraph,
         prepared_iterator_nodes: list[str],
     ) -> Optional[str]:
         """Gets the prepared version of the specified source node that matches every iteration specified"""
-        prepared_nodes = self.source_prepared_mapping[source_node_path]
+        prepared_nodes = self.source_prepared_mapping[source_node_id]
         if len(prepared_nodes) == 1:
             return next(iter(prepared_nodes))
 
@@ -1192,7 +1050,7 @@ class GraphExecutionState(BaseModel):
 
         # Filter to only iterator nodes that are a parent of the specified node, in tuple format (prepared, source)
         iterator_source_node_mapping = [(n, self.prepared_source_mapping[n]) for n in prepared_iterator_nodes]
-        parent_iterators = [itn for itn in iterator_source_node_mapping if nx.has_path(graph, itn[1], source_node_path)]
+        parent_iterators = [itn for itn in iterator_source_node_mapping if nx.has_path(graph, itn[1], source_node_id)]
 
         return next(
             (n for n in prepared_nodes if all(nx.has_path(execution_graph, pit[0], n) for pit in parent_iterators)),
@@ -1261,19 +1119,19 @@ class GraphExecutionState(BaseModel):
     def add_node(self, node: BaseInvocation) -> None:
         self.graph.add_node(node)
 
-    def update_node(self, node_path: str, new_node: BaseInvocation) -> None:
-        if not self._is_node_updatable(node_path):
+    def update_node(self, node_id: str, new_node: BaseInvocation) -> None:
+        if not self._is_node_updatable(node_id):
             raise NodeAlreadyExecutedError(
-                f"Node {node_path} has already been prepared or executed and cannot be updated"
+                f"Node {node_id} has already been prepared or executed and cannot be updated"
             )
-        self.graph.update_node(node_path, new_node)
+        self.graph.update_node(node_id, new_node)
 
-    def delete_node(self, node_path: str) -> None:
-        if not self._is_node_updatable(node_path):
+    def delete_node(self, node_id: str) -> None:
+        if not self._is_node_updatable(node_id):
             raise NodeAlreadyExecutedError(
-                f"Node {node_path} has already been prepared or executed and cannot be deleted"
+                f"Node {node_id} has already been prepared or executed and cannot be deleted"
             )
-        self.graph.delete_node(node_path)
+        self.graph.delete_node(node_id)
 
     def add_edge(self, edge: Edge) -> None:
         if not self._is_node_updatable(edge.destination.node_id):
diff --git a/tests/aa_nodes/test_invoker.py b/tests/aa_nodes/test_invoker.py
index f67b5a2ac5..38fcf859a5 100644
--- a/tests/aa_nodes/test_invoker.py
+++ b/tests/aa_nodes/test_invoker.py
@@ -23,7 +23,7 @@ from invokeai.app.services.invocation_services import InvocationServices
 from invokeai.app.services.invocation_stats.invocation_stats_default import InvocationStatsService
 from invokeai.app.services.invoker import Invoker
 from invokeai.app.services.session_queue.session_queue_common import DEFAULT_QUEUE_ID
-from invokeai.app.services.shared.graph import Graph, GraphExecutionState, GraphInvocation
+from invokeai.app.services.shared.graph import Graph, GraphExecutionState
 
 
 @pytest.fixture
@@ -35,17 +35,6 @@ def simple_graph():
     return g
 
 
-@pytest.fixture
-def graph_with_subgraph():
-    sub_g = Graph()
-    sub_g.add_node(PromptTestInvocation(id="1", prompt="Banana sushi"))
-    sub_g.add_node(TextToImageTestInvocation(id="2"))
-    sub_g.add_edge(create_edge("1", "prompt", "2", "prompt"))
-    g = Graph()
-    g.add_node(GraphInvocation(id="1", graph=sub_g))
-    return g
-
-
 # This must be defined here to avoid issues with the dynamic creation of the union of all invocation types
 # Defining it in a separate module will cause the union to be incomplete, and pydantic will not validate
 # the test invocations.
diff --git a/tests/aa_nodes/test_node_graph.py b/tests/aa_nodes/test_node_graph.py
index 12a181f392..94682962ad 100644
--- a/tests/aa_nodes/test_node_graph.py
+++ b/tests/aa_nodes/test_node_graph.py
@@ -8,8 +8,6 @@ from invokeai.app.invocations.baseinvocation import (
     invocation,
     invocation_output,
 )
-from invokeai.app.invocations.image import ShowImageInvocation
-from invokeai.app.invocations.math import AddInvocation, SubtractInvocation
 from invokeai.app.invocations.primitives import (
     FloatCollectionInvocation,
     FloatInvocation,
@@ -17,13 +15,11 @@ from invokeai.app.invocations.primitives import (
     StringInvocation,
 )
 from invokeai.app.invocations.upscale import ESRGANInvocation
-from invokeai.app.services.shared.default_graphs import create_text_to_image
 from invokeai.app.services.shared.graph import (
     CollectInvocation,
     Edge,
     EdgeConnection,
     Graph,
-    GraphInvocation,
     InvalidEdgeError,
     IterateInvocation,
     NodeAlreadyInGraphError,
@@ -425,19 +421,19 @@ def test_graph_invalid_if_edges_reference_missing_nodes():
     assert g.is_valid() is False
 
 
-def test_graph_invalid_if_subgraph_invalid():
-    g = Graph()
-    n1 = GraphInvocation(id="1")
-    n1.graph = Graph()
+# def test_graph_invalid_if_subgraph_invalid():
+#     g = Graph()
+#     n1 = GraphInvocation(id="1")
+#     n1.graph = Graph()
 
-    n1_1 = TextToImageTestInvocation(id="2", prompt="Banana sushi")
-    n1.graph.nodes[n1_1.id] = n1_1
-    e1 = create_edge("1", "image", "2", "image")
-    n1.graph.edges.append(e1)
+#     n1_1 = TextToImageTestInvocation(id="2", prompt="Banana sushi")
+#     n1.graph.nodes[n1_1.id] = n1_1
+#     e1 = create_edge("1", "image", "2", "image")
+#     n1.graph.edges.append(e1)
 
-    g.nodes[n1.id] = n1
+#     g.nodes[n1.id] = n1
 
-    assert g.is_valid() is False
+#     assert g.is_valid() is False
 
 
 def test_graph_invalid_if_has_cycle():
@@ -466,108 +462,108 @@ def test_graph_invalid_with_invalid_connection():
     assert g.is_valid() is False
 
 
-# TODO: Subgraph operations
-def test_graph_gets_subgraph_node():
-    g = Graph()
-    n1 = GraphInvocation(id="1")
-    n1.graph = Graph()
+# # TODO: Subgraph operations
+# def test_graph_gets_subgraph_node():
+#     g = Graph()
+#     n1 = GraphInvocation(id="1")
+#     n1.graph = Graph()
 
-    n1_1 = TextToImageTestInvocation(id="1", prompt="Banana sushi")
-    n1.graph.add_node(n1_1)
+#     n1_1 = TextToImageTestInvocation(id="1", prompt="Banana sushi")
+#     n1.graph.add_node(n1_1)
 
-    g.add_node(n1)
+#     g.add_node(n1)
 
-    result = g.get_node("1.1")
+#     result = g.get_node("1.1")
 
-    assert result is not None
-    assert result.id == "1"
-    assert result == n1_1
+#     assert result is not None
+#     assert result.id == "1"
+#     assert result == n1_1
 
 
-def test_graph_expands_subgraph():
-    g = Graph()
-    n1 = GraphInvocation(id="1")
-    n1.graph = Graph()
+# def test_graph_expands_subgraph():
+#     g = Graph()
+#     n1 = GraphInvocation(id="1")
+#     n1.graph = Graph()
 
-    n1_1 = AddInvocation(id="1", a=1, b=2)
-    n1_2 = SubtractInvocation(id="2", b=3)
-    n1.graph.add_node(n1_1)
-    n1.graph.add_node(n1_2)
-    n1.graph.add_edge(create_edge("1", "value", "2", "a"))
+#     n1_1 = AddInvocation(id="1", a=1, b=2)
+#     n1_2 = SubtractInvocation(id="2", b=3)
+#     n1.graph.add_node(n1_1)
+#     n1.graph.add_node(n1_2)
+#     n1.graph.add_edge(create_edge("1", "value", "2", "a"))
 
-    g.add_node(n1)
+#     g.add_node(n1)
 
-    n2 = AddInvocation(id="2", b=5)
-    g.add_node(n2)
-    g.add_edge(create_edge("1.2", "value", "2", "a"))
+#     n2 = AddInvocation(id="2", b=5)
+#     g.add_node(n2)
+#     g.add_edge(create_edge("1.2", "value", "2", "a"))
 
-    dg = g.nx_graph_flat()
-    assert set(dg.nodes) == {"1.1", "1.2", "2"}
-    assert set(dg.edges) == {("1.1", "1.2"), ("1.2", "2")}
+#     dg = g.nx_graph_flat()
+#     assert set(dg.nodes) == {"1.1", "1.2", "2"}
+#     assert set(dg.edges) == {("1.1", "1.2"), ("1.2", "2")}
 
 
-def test_graph_subgraph_t2i():
-    g = Graph()
-    n1 = GraphInvocation(id="1")
+# def test_graph_subgraph_t2i():
+#     g = Graph()
+#     n1 = GraphInvocation(id="1")
 
-    # Get text to image default graph
-    lg = create_text_to_image()
-    n1.graph = lg.graph
+#     # Get text to image default graph
+#     lg = create_text_to_image()
+#     n1.graph = lg.graph
 
-    g.add_node(n1)
+#     g.add_node(n1)
 
-    n2 = IntegerInvocation(id="2", value=512)
-    n3 = IntegerInvocation(id="3", value=256)
+#     n2 = IntegerInvocation(id="2", value=512)
+#     n3 = IntegerInvocation(id="3", value=256)
 
-    g.add_node(n2)
-    g.add_node(n3)
+#     g.add_node(n2)
+#     g.add_node(n3)
 
-    g.add_edge(create_edge("2", "value", "1.width", "value"))
-    g.add_edge(create_edge("3", "value", "1.height", "value"))
+#     g.add_edge(create_edge("2", "value", "1.width", "value"))
+#     g.add_edge(create_edge("3", "value", "1.height", "value"))
 
-    n4 = ShowImageInvocation(id="4")
-    g.add_node(n4)
-    g.add_edge(create_edge("1.8", "image", "4", "image"))
+#     n4 = ShowImageInvocation(id="4")
+#     g.add_node(n4)
+#     g.add_edge(create_edge("1.8", "image", "4", "image"))
 
-    # Validate
-    dg = g.nx_graph_flat()
-    assert set(dg.nodes) == {"1.width", "1.height", "1.seed", "1.3", "1.4", "1.5", "1.6", "1.7", "1.8", "2", "3", "4"}
-    expected_edges = [(f"1.{e.source.node_id}", f"1.{e.destination.node_id}") for e in lg.graph.edges]
-    expected_edges.extend([("2", "1.width"), ("3", "1.height"), ("1.8", "4")])
-    print(expected_edges)
-    print(list(dg.edges))
-    assert set(dg.edges) == set(expected_edges)
+#     # Validate
+#     dg = g.nx_graph_flat()
+#     assert set(dg.nodes) == {"1.width", "1.height", "1.seed", "1.3", "1.4", "1.5", "1.6", "1.7", "1.8", "2", "3", "4"}
+#     expected_edges = [(f"1.{e.source.node_id}", f"1.{e.destination.node_id}") for e in lg.graph.edges]
+#     expected_edges.extend([("2", "1.width"), ("3", "1.height"), ("1.8", "4")])
+#     print(expected_edges)
+#     print(list(dg.edges))
+#     assert set(dg.edges) == set(expected_edges)
 
 
-def test_graph_fails_to_get_missing_subgraph_node():
-    g = Graph()
-    n1 = GraphInvocation(id="1")
-    n1.graph = Graph()
+# def test_graph_fails_to_get_missing_subgraph_node():
+#     g = Graph()
+#     n1 = GraphInvocation(id="1")
+#     n1.graph = Graph()
 
-    n1_1 = TextToImageTestInvocation(id="1", prompt="Banana sushi")
-    n1.graph.add_node(n1_1)
+#     n1_1 = TextToImageTestInvocation(id="1", prompt="Banana sushi")
+#     n1.graph.add_node(n1_1)
 
-    g.add_node(n1)
+#     g.add_node(n1)
 
-    with pytest.raises(NodeNotFoundError):
-        _ = g.get_node("1.2")
+#     with pytest.raises(NodeNotFoundError):
+#         _ = g.get_node("1.2")
 
 
-def test_graph_fails_to_enumerate_non_subgraph_node():
-    g = Graph()
-    n1 = GraphInvocation(id="1")
-    n1.graph = Graph()
+# def test_graph_fails_to_enumerate_non_subgraph_node():
+#     g = Graph()
+#     n1 = GraphInvocation(id="1")
+#     n1.graph = Graph()
 
-    n1_1 = TextToImageTestInvocation(id="1", prompt="Banana sushi")
-    n1.graph.add_node(n1_1)
+#     n1_1 = TextToImageTestInvocation(id="1", prompt="Banana sushi")
+#     n1.graph.add_node(n1_1)
 
-    g.add_node(n1)
+#     g.add_node(n1)
 
-    n2 = ESRGANInvocation(id="2")
-    g.add_node(n2)
+#     n2 = ESRGANInvocation(id="2")
+#     g.add_node(n2)
 
-    with pytest.raises(NodeNotFoundError):
-        _ = g.get_node("2.1")
+#     with pytest.raises(NodeNotFoundError):
+#         _ = g.get_node("2.1")
 
 
 def test_graph_gets_networkx_graph():
diff --git a/tests/aa_nodes/test_session_queue.py b/tests/aa_nodes/test_session_queue.py
index b15bb9df36..bfe6444de8 100644
--- a/tests/aa_nodes/test_session_queue.py
+++ b/tests/aa_nodes/test_session_queue.py
@@ -8,10 +8,9 @@ from invokeai.app.services.session_queue.session_queue_common import (
     NodeFieldValue,
     calc_session_count,
     create_session_nfv_tuples,
-    populate_graph,
     prepare_values_to_insert,
 )
-from invokeai.app.services.shared.graph import Graph, GraphExecutionState, GraphInvocation
+from invokeai.app.services.shared.graph import Graph, GraphExecutionState
 from tests.aa_nodes.test_nodes import PromptTestInvocation
 
 
@@ -39,28 +38,28 @@ def batch_graph() -> Graph:
     return g
 
 
-def test_populate_graph_with_subgraph():
-    g1 = Graph()
-    g1.add_node(PromptTestInvocation(id="1", prompt="Banana sushi"))
-    g1.add_node(PromptTestInvocation(id="2", prompt="Banana sushi"))
-    n1 = PromptTestInvocation(id="1", prompt="Banana snake")
-    subgraph = Graph()
-    subgraph.add_node(n1)
-    g1.add_node(GraphInvocation(id="3", graph=subgraph))
+# def test_populate_graph_with_subgraph():
+#     g1 = Graph()
+#     g1.add_node(PromptTestInvocation(id="1", prompt="Banana sushi"))
+#     g1.add_node(PromptTestInvocation(id="2", prompt="Banana sushi"))
+#     n1 = PromptTestInvocation(id="1", prompt="Banana snake")
+#     subgraph = Graph()
+#     subgraph.add_node(n1)
+#     g1.add_node(GraphInvocation(id="3", graph=subgraph))
 
-    nfvs = [
-        NodeFieldValue(node_path="1", field_name="prompt", value="Strawberry sushi"),
-        NodeFieldValue(node_path="2", field_name="prompt", value="Strawberry sunday"),
-        NodeFieldValue(node_path="3.1", field_name="prompt", value="Strawberry snake"),
-    ]
+#     nfvs = [
+#         NodeFieldValue(node_path="1", field_name="prompt", value="Strawberry sushi"),
+#         NodeFieldValue(node_path="2", field_name="prompt", value="Strawberry sunday"),
+#         NodeFieldValue(node_path="3.1", field_name="prompt", value="Strawberry snake"),
+#     ]
 
-    g2 = populate_graph(g1, nfvs)
+#     g2 = populate_graph(g1, nfvs)
 
-    # do not mutate g1
-    assert g1 is not g2
-    assert g2.get_node("1").prompt == "Strawberry sushi"
-    assert g2.get_node("2").prompt == "Strawberry sunday"
-    assert g2.get_node("3.1").prompt == "Strawberry snake"
+#     # do not mutate g1
+#     assert g1 is not g2
+#     assert g2.get_node("1").prompt == "Strawberry sushi"
+#     assert g2.get_node("2").prompt == "Strawberry sunday"
+#     assert g2.get_node("3.1").prompt == "Strawberry snake"
 
 
 def test_create_sessions_from_batch_with_runs(batch_data_collection, batch_graph):

From 0b81703c9f5b570388fa1e09171897d16a15e3b0 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 17 Feb 2024 19:59:21 +1100
Subject: [PATCH 159/411] tidy(nodes): move node tests to parent dir

Thanks to the resolution of the import vs union issue, we can put tests anywhere.
---
 tests/aa_nodes/__init__.py                         | 0
 tests/{aa_nodes => }/test_graph_execution_state.py | 0
 tests/{aa_nodes => }/test_invoker.py               | 0
 tests/{aa_nodes => }/test_node_graph.py            | 0
 tests/{aa_nodes => }/test_nodes.py                 | 0
 tests/{aa_nodes => }/test_session_queue.py         | 3 ++-
 6 files changed, 2 insertions(+), 1 deletion(-)
 delete mode 100644 tests/aa_nodes/__init__.py
 rename tests/{aa_nodes => }/test_graph_execution_state.py (100%)
 rename tests/{aa_nodes => }/test_invoker.py (100%)
 rename tests/{aa_nodes => }/test_node_graph.py (100%)
 rename tests/{aa_nodes => }/test_nodes.py (100%)
 rename tests/{aa_nodes => }/test_session_queue.py (99%)

diff --git a/tests/aa_nodes/__init__.py b/tests/aa_nodes/__init__.py
deleted file mode 100644
index e69de29bb2..0000000000
diff --git a/tests/aa_nodes/test_graph_execution_state.py b/tests/test_graph_execution_state.py
similarity index 100%
rename from tests/aa_nodes/test_graph_execution_state.py
rename to tests/test_graph_execution_state.py
diff --git a/tests/aa_nodes/test_invoker.py b/tests/test_invoker.py
similarity index 100%
rename from tests/aa_nodes/test_invoker.py
rename to tests/test_invoker.py
diff --git a/tests/aa_nodes/test_node_graph.py b/tests/test_node_graph.py
similarity index 100%
rename from tests/aa_nodes/test_node_graph.py
rename to tests/test_node_graph.py
diff --git a/tests/aa_nodes/test_nodes.py b/tests/test_nodes.py
similarity index 100%
rename from tests/aa_nodes/test_nodes.py
rename to tests/test_nodes.py
diff --git a/tests/aa_nodes/test_session_queue.py b/tests/test_session_queue.py
similarity index 99%
rename from tests/aa_nodes/test_session_queue.py
rename to tests/test_session_queue.py
index bfe6444de8..48b980539c 100644
--- a/tests/aa_nodes/test_session_queue.py
+++ b/tests/test_session_queue.py
@@ -11,7 +11,8 @@ from invokeai.app.services.session_queue.session_queue_common import (
     prepare_values_to_insert,
 )
 from invokeai.app.services.shared.graph import Graph, GraphExecutionState
-from tests.aa_nodes.test_nodes import PromptTestInvocation
+
+from .test_nodes import PromptTestInvocation
 
 
 @pytest.fixture

From e93bd1539252b735739b624539784179df506c23 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 17 Feb 2024 20:00:58 +1100
Subject: [PATCH 160/411] tidy(nodes): remove LibraryGraphs

The workflow library supersedes this unused feature.
---
 .../app/services/shared/default_graphs.py     | 92 -------------------
 invokeai/app/services/shared/graph.py         | 56 -----------
 2 files changed, 148 deletions(-)
 delete mode 100644 invokeai/app/services/shared/default_graphs.py

diff --git a/invokeai/app/services/shared/default_graphs.py b/invokeai/app/services/shared/default_graphs.py
deleted file mode 100644
index 7e62c6d0a1..0000000000
--- a/invokeai/app/services/shared/default_graphs.py
+++ /dev/null
@@ -1,92 +0,0 @@
-from invokeai.app.services.item_storage.item_storage_base import ItemStorageABC
-
-from ...invocations.compel import CompelInvocation
-from ...invocations.image import ImageNSFWBlurInvocation
-from ...invocations.latent import DenoiseLatentsInvocation, LatentsToImageInvocation
-from ...invocations.noise import NoiseInvocation
-from ...invocations.primitives import IntegerInvocation
-from .graph import Edge, EdgeConnection, ExposedNodeInput, ExposedNodeOutput, Graph, LibraryGraph
-
-default_text_to_image_graph_id = "539b2af5-2b4d-4d8c-8071-e54a3255fc74"
-
-
-def create_text_to_image() -> LibraryGraph:
-    graph = Graph(
-        nodes={
-            "width": IntegerInvocation(id="width", value=512),
-            "height": IntegerInvocation(id="height", value=512),
-            "seed": IntegerInvocation(id="seed", value=-1),
-            "3": NoiseInvocation(id="3"),
-            "4": CompelInvocation(id="4"),
-            "5": CompelInvocation(id="5"),
-            "6": DenoiseLatentsInvocation(id="6"),
-            "7": LatentsToImageInvocation(id="7"),
-            "8": ImageNSFWBlurInvocation(id="8"),
-        },
-        edges=[
-            Edge(
-                source=EdgeConnection(node_id="width", field="value"),
-                destination=EdgeConnection(node_id="3", field="width"),
-            ),
-            Edge(
-                source=EdgeConnection(node_id="height", field="value"),
-                destination=EdgeConnection(node_id="3", field="height"),
-            ),
-            Edge(
-                source=EdgeConnection(node_id="seed", field="value"),
-                destination=EdgeConnection(node_id="3", field="seed"),
-            ),
-            Edge(
-                source=EdgeConnection(node_id="3", field="noise"),
-                destination=EdgeConnection(node_id="6", field="noise"),
-            ),
-            Edge(
-                source=EdgeConnection(node_id="6", field="latents"),
-                destination=EdgeConnection(node_id="7", field="latents"),
-            ),
-            Edge(
-                source=EdgeConnection(node_id="4", field="conditioning"),
-                destination=EdgeConnection(node_id="6", field="positive_conditioning"),
-            ),
-            Edge(
-                source=EdgeConnection(node_id="5", field="conditioning"),
-                destination=EdgeConnection(node_id="6", field="negative_conditioning"),
-            ),
-            Edge(
-                source=EdgeConnection(node_id="7", field="image"),
-                destination=EdgeConnection(node_id="8", field="image"),
-            ),
-        ],
-    )
-    return LibraryGraph(
-        id=default_text_to_image_graph_id,
-        name="t2i",
-        description="Converts text to an image",
-        graph=graph,
-        exposed_inputs=[
-            ExposedNodeInput(node_path="4", field="prompt", alias="positive_prompt"),
-            ExposedNodeInput(node_path="5", field="prompt", alias="negative_prompt"),
-            ExposedNodeInput(node_path="width", field="value", alias="width"),
-            ExposedNodeInput(node_path="height", field="value", alias="height"),
-            ExposedNodeInput(node_path="seed", field="value", alias="seed"),
-        ],
-        exposed_outputs=[ExposedNodeOutput(node_path="8", field="image", alias="image")],
-    )
-
-
-def create_system_graphs(graph_library: ItemStorageABC[LibraryGraph]) -> list[LibraryGraph]:
-    """Creates the default system graphs, or adds new versions if the old ones don't match"""
-
-    # TODO: Uncomment this when we are ready to fix this up to prevent breaking changes
-    graphs: list[LibraryGraph] = []
-
-    text_to_image = graph_library.get(default_text_to_image_graph_id)
-
-    # TODO: Check if the graph is the same as the default one, and if not, update it
-    # if text_to_image is None:
-    text_to_image = create_text_to_image()
-    graph_library.set(text_to_image)
-
-    graphs.append(text_to_image)
-
-    return graphs
diff --git a/invokeai/app/services/shared/graph.py b/invokeai/app/services/shared/graph.py
index 4df9f0c4b0..5380c2e795 100644
--- a/invokeai/app/services/shared/graph.py
+++ b/invokeai/app/services/shared/graph.py
@@ -10,7 +10,6 @@ from pydantic import (
     ConfigDict,
     GetJsonSchemaHandler,
     field_validator,
-    model_validator,
 )
 from pydantic.fields import Field
 from pydantic.json_schema import JsonSchemaValue
@@ -1146,58 +1145,3 @@ class GraphExecutionState(BaseModel):
                 f"Destination node {edge.destination.node_id} has already been prepared or executed and cannot have a source edge deleted"
             )
         self.graph.delete_edge(edge)
-
-
-class ExposedNodeInput(BaseModel):
-    node_path: str = Field(description="The node path to the node with the input")
-    field: str = Field(description="The field name of the input")
-    alias: str = Field(description="The alias of the input")
-
-
-class ExposedNodeOutput(BaseModel):
-    node_path: str = Field(description="The node path to the node with the output")
-    field: str = Field(description="The field name of the output")
-    alias: str = Field(description="The alias of the output")
-
-
-class LibraryGraph(BaseModel):
-    id: str = Field(description="The unique identifier for this library graph", default_factory=uuid_string)
-    graph: Graph = Field(description="The graph")
-    name: str = Field(description="The name of the graph")
-    description: str = Field(description="The description of the graph")
-    exposed_inputs: list[ExposedNodeInput] = Field(description="The inputs exposed by this graph", default_factory=list)
-    exposed_outputs: list[ExposedNodeOutput] = Field(
-        description="The outputs exposed by this graph", default_factory=list
-    )
-
-    @field_validator("exposed_inputs", "exposed_outputs")
-    def validate_exposed_aliases(cls, v: list[Union[ExposedNodeInput, ExposedNodeOutput]]):
-        if len(v) != len({i.alias for i in v}):
-            raise ValueError("Duplicate exposed alias")
-        return v
-
-    @model_validator(mode="after")
-    def validate_exposed_nodes(cls, values):
-        graph = values.graph
-
-        # Validate exposed inputs
-        for exposed_input in values.exposed_inputs:
-            if not graph.has_node(exposed_input.node_path):
-                raise ValueError(f"Exposed input node {exposed_input.node_path} does not exist")
-            node = graph.get_node(exposed_input.node_path)
-            if get_input_field(node, exposed_input.field) is None:
-                raise ValueError(
-                    f"Exposed input field {exposed_input.field} does not exist on node {exposed_input.node_path}"
-                )
-
-        # Validate exposed outputs
-        for exposed_output in values.exposed_outputs:
-            if not graph.has_node(exposed_output.node_path):
-                raise ValueError(f"Exposed output node {exposed_output.node_path} does not exist")
-            node = graph.get_node(exposed_output.node_path)
-            if get_output_field(node, exposed_output.field) is None:
-                raise ValueError(
-                    f"Exposed output field {exposed_output.field} does not exist on node {exposed_output.node_path}"
-                )
-
-        return values

From 7e71effa170e706bd136f9f8bed7b813679e9186 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 17 Feb 2024 20:02:37 +1100
Subject: [PATCH 161/411] tidy(nodes): remove no-op model_config

Because we now customize the JSON Schema creation for GraphExecutionState, the model_config did nothing.
---
 invokeai/app/services/shared/graph.py | 17 -----------------
 1 file changed, 17 deletions(-)

diff --git a/invokeai/app/services/shared/graph.py b/invokeai/app/services/shared/graph.py
index 5380c2e795..e3941d9ca3 100644
--- a/invokeai/app/services/shared/graph.py
+++ b/invokeai/app/services/shared/graph.py
@@ -7,7 +7,6 @@ from typing import Annotated, Any, Optional, TypeVar, Union, get_args, get_origi
 import networkx as nx
 from pydantic import (
     BaseModel,
-    ConfigDict,
     GetJsonSchemaHandler,
     field_validator,
 )
@@ -804,22 +803,6 @@ class GraphExecutionState(BaseModel):
         json_schema = handler.resolve_ref_schema(json_schema)
         return json_schema
 
-    model_config = ConfigDict(
-        json_schema_extra={
-            "required": [
-                "id",
-                "graph",
-                "execution_graph",
-                "executed",
-                "executed_history",
-                "results",
-                "errors",
-                "prepared_source_mapping",
-                "source_prepared_mapping",
-            ]
-        }
-    )
-
     def next(self) -> Optional[BaseInvocation]:
         """Gets the next node ready to execute."""
 

From 67daa127e3393c2f4514e0712b496533268f0d09 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 17 Feb 2024 20:02:51 +1100
Subject: [PATCH 162/411] chore(ui): typegen

---
 .../frontend/web/src/services/api/schema.ts   | 165 ++++++++----------
 1 file changed, 72 insertions(+), 93 deletions(-)

diff --git a/invokeai/frontend/web/src/services/api/schema.ts b/invokeai/frontend/web/src/services/api/schema.ts
index 40fc262be2..47a257ffe6 100644
--- a/invokeai/frontend/web/src/services/api/schema.ts
+++ b/invokeai/frontend/web/src/services/api/schema.ts
@@ -2011,8 +2011,9 @@ export type components = {
       /**
        * CLIP
        * @description CLIP (tokenizer, text encoder, LoRAs) and skipped layer count
+       * @default null
        */
-      clip?: components["schemas"]["ClipField"] | null;
+      clip: components["schemas"]["ClipField"] | null;
       /**
        * type
        * @default clip_skip_output
@@ -3264,6 +3265,7 @@ export type components = {
       /**
        * Masked Latents Name
        * @description The name of the masked image latents
+       * @default null
        */
       masked_latents_name?: string | null;
     };
@@ -4211,14 +4213,14 @@ export type components = {
        * Nodes
        * @description The nodes in this graph
        */
-      nodes?: {
-        [key: string]: components["schemas"]["ControlNetInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["ColorMapImageProcessorInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["DWOpenposeImageProcessorInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["GraphInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["DepthAnythingImageProcessorInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["CvInpaintInvocation"];
+      nodes: {
+        [key: string]: components["schemas"]["ImageInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["ColorMapImageProcessorInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["DWOpenposeImageProcessorInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["DepthAnythingImageProcessorInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["CompelInvocation"];
       };
       /**
        * Edges
        * @description The connections between nodes and their fields in this graph
        */
-      edges?: components["schemas"]["Edge"][];
+      edges: components["schemas"]["Edge"][];
     };
     /**
      * GraphExecutionState
@@ -4249,7 +4251,7 @@ export type components = {
        * @description The results of node executions
        */
       results: {
-        [key: string]: components["schemas"]["SchedulerOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["LoraLoaderOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["GraphInvocationOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["SDXLLoraLoaderOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["VAEOutput"] | components["schemas"]["ClipSkipInvocationOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["String2Output"] | components["schemas"]["IntegerOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["LatentsOutput"] | components["schemas"]["MetadataOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["IterateInvocationOutput"];
+        [key: string]: components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["MetadataOutput"] | components["schemas"]["String2Output"] | components["schemas"]["ControlOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["LatentsOutput"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["ClipSkipInvocationOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["LoraLoaderOutput"] | components["schemas"]["VAEOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["SDXLLoraLoaderOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["LatentsCollectionOutput"];
       };
       /**
        * Errors
@@ -4273,46 +4275,6 @@ export type components = {
         [key: string]: string[];
       };
     };
-    /**
-     * GraphInvocation
-     * @description Execute a graph
-     */
-    GraphInvocation: {
-      /**
-       * Id
-       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
-       */
-      id: string;
-      /**
-       * Is Intermediate
-       * @description Whether or not this is an intermediate invocation.
-       * @default false
-       */
-      is_intermediate?: boolean;
-      /**
-       * Use Cache
-       * @description Whether or not to use the cache
-       * @default true
-       */
-      use_cache?: boolean;
-      /** @description The graph to run */
-      graph?: components["schemas"]["Graph"];
-      /**
-       * type
-       * @default graph
-       * @constant
-       */
-      type: "graph";
-    };
-    /** GraphInvocationOutput */
-    GraphInvocationOutput: {
-      /**
-       * type
-       * @default graph_output
-       * @constant
-       */
-      type: "graph_output";
-    };
     /**
      * HFModelSource
      * @description A HuggingFace repo_id with optional variant, sub-folder and access token.
@@ -6218,6 +6180,7 @@ export type components = {
       /**
        * Seed
        * @description Seed used to generate this latents
+       * @default null
        */
       seed?: number | null;
     };
@@ -6631,7 +6594,10 @@ export type components = {
        * @description Key of model as returned by ModelRecordServiceBase.get_model()
        */
       key: string;
-      /** @description Info to load submodel */
+      /**
+       * @description Info to load submodel
+       * @default null
+       */
       submodel_type?: components["schemas"]["SubModelType"] | null;
       /**
        * Weight
@@ -6697,13 +6663,15 @@ export type components = {
       /**
        * UNet
        * @description UNet (scheduler, LoRAs)
+       * @default null
        */
-      unet?: components["schemas"]["UNetField"] | null;
+      unet: components["schemas"]["UNetField"] | null;
       /**
        * CLIP
        * @description CLIP (tokenizer, text encoder, LoRAs) and skipped layer count
+       * @default null
        */
-      clip?: components["schemas"]["ClipField"] | null;
+      clip: components["schemas"]["ClipField"] | null;
       /**
        * type
        * @default lora_loader_output
@@ -7420,7 +7388,10 @@ export type components = {
        * @description Key of model as returned by ModelRecordServiceBase.get_model()
        */
       key: string;
-      /** @description Info to load submodel */
+      /**
+       * @description Info to load submodel
+       * @default null
+       */
       submodel_type?: components["schemas"]["SubModelType"] | null;
     };
     /**
@@ -8794,18 +8765,21 @@ export type components = {
       /**
        * UNet
        * @description UNet (scheduler, LoRAs)
+       * @default null
        */
-      unet?: components["schemas"]["UNetField"] | null;
+      unet: components["schemas"]["UNetField"] | null;
       /**
        * CLIP 1
        * @description CLIP (tokenizer, text encoder, LoRAs) and skipped layer count
+       * @default null
        */
-      clip?: components["schemas"]["ClipField"] | null;
+      clip: components["schemas"]["ClipField"] | null;
       /**
        * CLIP 2
        * @description CLIP (tokenizer, text encoder, LoRAs) and skipped layer count
+       * @default null
        */
-      clip2?: components["schemas"]["ClipField"] | null;
+      clip2: components["schemas"]["ClipField"] | null;
       /**
        * type
        * @default sdxl_lora_loader_output
@@ -9202,13 +9176,15 @@ export type components = {
       /**
        * UNet
        * @description UNet (scheduler, LoRAs)
+       * @default null
        */
-      unet?: components["schemas"]["UNetField"] | null;
+      unet: components["schemas"]["UNetField"] | null;
       /**
        * VAE
        * @description VAE
+       * @default null
        */
-      vae?: components["schemas"]["VaeField"] | null;
+      vae: components["schemas"]["VaeField"] | null;
       /**
        * type
        * @default seamless_output
@@ -10397,7 +10373,10 @@ export type components = {
        * @description Axes("x" and "y") to which apply seamless
        */
       seamless_axes?: string[];
-      /** @description FreeU configuration */
+      /**
+       * @description FreeU configuration
+       * @default null
+       */
       freeu_config?: components["schemas"]["FreeUConfig"] | null;
     };
     /**
@@ -11112,48 +11091,12 @@ export type components = {
      * @enum {string}
      */
     UIType: "SDXLMainModelField" | "SDXLRefinerModelField" | "ONNXModelField" | "VAEModelField" | "LoRAModelField" | "ControlNetModelField" | "IPAdapterModelField" | "SchedulerField" | "AnyField" | "CollectionField" | "CollectionItemField" | "DEPRECATED_Boolean" | "DEPRECATED_Color" | "DEPRECATED_Conditioning" | "DEPRECATED_Control" | "DEPRECATED_Float" | "DEPRECATED_Image" | "DEPRECATED_Integer" | "DEPRECATED_Latents" | "DEPRECATED_String" | "DEPRECATED_BooleanCollection" | "DEPRECATED_ColorCollection" | "DEPRECATED_ConditioningCollection" | "DEPRECATED_ControlCollection" | "DEPRECATED_FloatCollection" | "DEPRECATED_ImageCollection" | "DEPRECATED_IntegerCollection" | "DEPRECATED_LatentsCollection" | "DEPRECATED_StringCollection" | "DEPRECATED_BooleanPolymorphic" | "DEPRECATED_ColorPolymorphic" | "DEPRECATED_ConditioningPolymorphic" | "DEPRECATED_ControlPolymorphic" | "DEPRECATED_FloatPolymorphic" | "DEPRECATED_ImagePolymorphic" | "DEPRECATED_IntegerPolymorphic" | "DEPRECATED_LatentsPolymorphic" | "DEPRECATED_StringPolymorphic" | "DEPRECATED_MainModel" | "DEPRECATED_UNet" | "DEPRECATED_Vae" | "DEPRECATED_CLIP" | "DEPRECATED_Collection" | "DEPRECATED_CollectionItem" | "DEPRECATED_Enum" | "DEPRECATED_WorkflowField" | "DEPRECATED_IsIntermediate" | "DEPRECATED_BoardField" | "DEPRECATED_MetadataItem" | "DEPRECATED_MetadataItemCollection" | "DEPRECATED_MetadataItemPolymorphic" | "DEPRECATED_MetadataDict";
-    /**
-     * VaeModelFormat
-     * @description An enumeration.
-     * @enum {string}
-     */
-    VaeModelFormat: "checkpoint" | "diffusers";
-    /**
-     * T2IAdapterModelFormat
-     * @description An enumeration.
-     * @enum {string}
-     */
-    T2IAdapterModelFormat: "diffusers";
-    /**
-     * StableDiffusionXLModelFormat
-     * @description An enumeration.
-     * @enum {string}
-     */
-    StableDiffusionXLModelFormat: "checkpoint" | "diffusers";
-    /**
-     * StableDiffusion1ModelFormat
-     * @description An enumeration.
-     * @enum {string}
-     */
-    StableDiffusion1ModelFormat: "checkpoint" | "diffusers";
-    /**
-     * StableDiffusionOnnxModelFormat
-     * @description An enumeration.
-     * @enum {string}
-     */
-    StableDiffusionOnnxModelFormat: "olive" | "onnx";
     /**
      * ControlNetModelFormat
      * @description An enumeration.
      * @enum {string}
      */
     ControlNetModelFormat: "checkpoint" | "diffusers";
-    /**
-     * StableDiffusion2ModelFormat
-     * @description An enumeration.
-     * @enum {string}
-     */
-    StableDiffusion2ModelFormat: "checkpoint" | "diffusers";
     /**
      * LoRAModelFormat
      * @description An enumeration.
@@ -11161,17 +11104,53 @@ export type components = {
      */
     LoRAModelFormat: "lycoris" | "diffusers";
     /**
-     * CLIPVisionModelFormat
+     * StableDiffusionXLModelFormat
      * @description An enumeration.
      * @enum {string}
      */
-    CLIPVisionModelFormat: "diffusers";
+    StableDiffusionXLModelFormat: "checkpoint" | "diffusers";
     /**
      * IPAdapterModelFormat
      * @description An enumeration.
      * @enum {string}
      */
     IPAdapterModelFormat: "invokeai";
+    /**
+     * T2IAdapterModelFormat
+     * @description An enumeration.
+     * @enum {string}
+     */
+    T2IAdapterModelFormat: "diffusers";
+    /**
+     * StableDiffusion1ModelFormat
+     * @description An enumeration.
+     * @enum {string}
+     */
+    StableDiffusion1ModelFormat: "checkpoint" | "diffusers";
+    /**
+     * CLIPVisionModelFormat
+     * @description An enumeration.
+     * @enum {string}
+     */
+    CLIPVisionModelFormat: "diffusers";
+    /**
+     * StableDiffusionOnnxModelFormat
+     * @description An enumeration.
+     * @enum {string}
+     */
+    StableDiffusionOnnxModelFormat: "olive" | "onnx";
+    /**
+     * StableDiffusion2ModelFormat
+     * @description An enumeration.
+     * @enum {string}
+     */
+    StableDiffusion2ModelFormat: "checkpoint" | "diffusers";
+    /**
+     * VaeModelFormat
+     * @description An enumeration.
+     * @enum {string}
+     */
+    VaeModelFormat: "checkpoint" | "diffusers";
   };
   responses: never;
   parameters: never;

From da9991e36130875968c3edbc407656d11ec4ab7c Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 17 Feb 2024 20:08:22 +1100
Subject: [PATCH 163/411] tidy(nodes): remove commented tests

---
 tests/test_node_graph.py    | 119 ------------------------------------
 tests/test_session_queue.py |  24 --------
 2 files changed, 143 deletions(-)

diff --git a/tests/test_node_graph.py b/tests/test_node_graph.py
index 94682962ad..87a4948af4 100644
--- a/tests/test_node_graph.py
+++ b/tests/test_node_graph.py
@@ -421,21 +421,6 @@ def test_graph_invalid_if_edges_reference_missing_nodes():
     assert g.is_valid() is False
 
 
-# def test_graph_invalid_if_subgraph_invalid():
-#     g = Graph()
-#     n1 = GraphInvocation(id="1")
-#     n1.graph = Graph()
-
-#     n1_1 = TextToImageTestInvocation(id="2", prompt="Banana sushi")
-#     n1.graph.nodes[n1_1.id] = n1_1
-#     e1 = create_edge("1", "image", "2", "image")
-#     n1.graph.edges.append(e1)
-
-#     g.nodes[n1.id] = n1
-
-#     assert g.is_valid() is False
-
-
 def test_graph_invalid_if_has_cycle():
     g = Graph()
     n1 = ESRGANInvocation(id="1")
@@ -462,110 +447,6 @@ def test_graph_invalid_with_invalid_connection():
     assert g.is_valid() is False
 
 
-# # TODO: Subgraph operations
-# def test_graph_gets_subgraph_node():
-#     g = Graph()
-#     n1 = GraphInvocation(id="1")
-#     n1.graph = Graph()
-
-#     n1_1 = TextToImageTestInvocation(id="1", prompt="Banana sushi")
-#     n1.graph.add_node(n1_1)
-
-#     g.add_node(n1)
-
-#     result = g.get_node("1.1")
-
-#     assert result is not None
-#     assert result.id == "1"
-#     assert result == n1_1
-
-
-# def test_graph_expands_subgraph():
-#     g = Graph()
-#     n1 = GraphInvocation(id="1")
-#     n1.graph = Graph()
-
-#     n1_1 = AddInvocation(id="1", a=1, b=2)
-#     n1_2 = SubtractInvocation(id="2", b=3)
-#     n1.graph.add_node(n1_1)
-#     n1.graph.add_node(n1_2)
-#     n1.graph.add_edge(create_edge("1", "value", "2", "a"))
-
-#     g.add_node(n1)
-
-#     n2 = AddInvocation(id="2", b=5)
-#     g.add_node(n2)
-#     g.add_edge(create_edge("1.2", "value", "2", "a"))
-
-#     dg = g.nx_graph_flat()
-#     assert set(dg.nodes) == {"1.1", "1.2", "2"}
-#     assert set(dg.edges) == {("1.1", "1.2"), ("1.2", "2")}
-
-
-# def test_graph_subgraph_t2i():
-#     g = Graph()
-#     n1 = GraphInvocation(id="1")
-
-#     # Get text to image default graph
-#     lg = create_text_to_image()
-#     n1.graph = lg.graph
-
-#     g.add_node(n1)
-
-#     n2 = IntegerInvocation(id="2", value=512)
-#     n3 = IntegerInvocation(id="3", value=256)
-
-#     g.add_node(n2)
-#     g.add_node(n3)
-
-#     g.add_edge(create_edge("2", "value", "1.width", "value"))
-#     g.add_edge(create_edge("3", "value", "1.height", "value"))
-
-#     n4 = ShowImageInvocation(id="4")
-#     g.add_node(n4)
-#     g.add_edge(create_edge("1.8", "image", "4", "image"))
-
-#     # Validate
-#     dg = g.nx_graph_flat()
-#     assert set(dg.nodes) == {"1.width", "1.height", "1.seed", "1.3", "1.4", "1.5", "1.6", "1.7", "1.8", "2", "3", "4"}
-#     expected_edges = [(f"1.{e.source.node_id}", f"1.{e.destination.node_id}") for e in lg.graph.edges]
-#     expected_edges.extend([("2", "1.width"), ("3", "1.height"), ("1.8", "4")])
-#     print(expected_edges)
-#     print(list(dg.edges))
-#     assert set(dg.edges) == set(expected_edges)
-
-
-# def test_graph_fails_to_get_missing_subgraph_node():
-#     g = Graph()
-#     n1 = GraphInvocation(id="1")
-#     n1.graph = Graph()
-
-#     n1_1 = TextToImageTestInvocation(id="1", prompt="Banana sushi")
-#     n1.graph.add_node(n1_1)
-
-#     g.add_node(n1)
-
-#     with pytest.raises(NodeNotFoundError):
-#         _ = g.get_node("1.2")
-
-
-# def test_graph_fails_to_enumerate_non_subgraph_node():
-#     g = Graph()
-#     n1 = GraphInvocation(id="1")
-#     n1.graph = Graph()
-
-#     n1_1 = TextToImageTestInvocation(id="1", prompt="Banana sushi")
-#     n1.graph.add_node(n1_1)
-
-#     g.add_node(n1)
-
-#     n2 = ESRGANInvocation(id="2")
-#     g.add_node(n2)
-
-#     with pytest.raises(NodeNotFoundError):
-#         _ = g.get_node("2.1")
-
-
 def test_graph_gets_networkx_graph():
     g = Graph()
     n1 = TextToImageTestInvocation(id="1", prompt="Banana sushi")
diff --git a/tests/test_session_queue.py b/tests/test_session_queue.py
index 48b980539c..bf26b9b002 100644
--- a/tests/test_session_queue.py
+++ b/tests/test_session_queue.py
@@ -39,30 +39,6 @@ def batch_graph() -> Graph:
     return g
 
 
-# def test_populate_graph_with_subgraph():
-#     g1 = Graph()
-#     g1.add_node(PromptTestInvocation(id="1", prompt="Banana sushi"))
-#     g1.add_node(PromptTestInvocation(id="2", prompt="Banana sushi"))
-#     n1 = PromptTestInvocation(id="1", prompt="Banana snake")
-#     subgraph = Graph()
-#     subgraph.add_node(n1)
-#     g1.add_node(GraphInvocation(id="3", graph=subgraph))
-
-#     nfvs = [
-#         NodeFieldValue(node_path="1", field_name="prompt", value="Strawberry sushi"),
-#         NodeFieldValue(node_path="2", field_name="prompt", value="Strawberry sunday"),
-#         NodeFieldValue(node_path="3.1", field_name="prompt", value="Strawberry snake"),
-#     ]
-
-#     g2 = populate_graph(g1, nfvs)
-
-#     # do not mutate g1
-#     assert g1 is not g2
-#     assert g2.get_node("1").prompt == "Strawberry sushi"
-#     assert g2.get_node("2").prompt == "Strawberry sunday"
-#     assert g2.get_node("3.1").prompt == "Strawberry snake"
-
-
 def test_create_sessions_from_batch_with_runs(batch_data_collection, batch_graph):
     b = Batch(graph=batch_graph, data=batch_data_collection, runs=2)
     t = list(create_session_nfv_tuples(batch=b, maximum=1000))

From 725c03cf87a2d937c714770b83a74a419de3e0de Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sun, 18 Feb 2024 01:41:04 +1100
Subject: [PATCH 164/411] refactor(nodes): merge processors

Consolidate graph processing logic into session processor.

With graphs as the unit of work, and the session queue distributing graphs, we no longer need the invocation queue or processor.

Instead, the session processor dequeues the next session and processes it in a simple loop, greatly simplifying the app.

- Remove `graph_execution_manager` service.
- Remove `queue` (invocation queue) service.
- Remove `processor` (invocation processor) service.
- Remove queue-related logic from `Invoker`. It now only starts and stops the services, providing them with access to other services.
- Remove unused `invocation_retrieval_error` and `session_retrieval_error` events, these are no longer needed.
- Clean up stats service now that it is less coupled to the rest of the app.
- Refactor cancellation logic - cancellations now originate from session queue (i.e. HTTP cancel endpoint) and are emitted as events. Processor gets the events and sets the canceled event. Access to this event is provided to the invocation context for e.g. the step callback.
- Remove `sessions` router; it provided access to `graph_executions` but that no longer exists.
---
 invokeai/app/api/dependencies.py              |  10 -
 invokeai/app/api/routers/sessions.py          | 276 ------------------
 invokeai/app/api_app.py                       |   3 -
 invokeai/app/services/events/events_base.py   |  48 +--
 .../services/invocation_processor/__init__.py |   0
 .../invocation_processor_base.py              |   5 -
 .../invocation_processor_common.py            |  15 -
 .../invocation_processor_default.py           | 241 ---------------
 .../app/services/invocation_queue/__init__.py |   0
 .../invocation_queue/invocation_queue_base.py |  26 --
 .../invocation_queue_common.py                |  23 --
 .../invocation_queue_memory.py                |  44 ---
 invokeai/app/services/invocation_services.py  |  10 -
 .../invocation_stats/invocation_stats_base.py |  10 +-
 .../invocation_stats_default.py               |  43 +--
 invokeai/app/services/invoker.py              |  52 ----
 .../services/model_load/model_load_default.py |   3 -
 .../session_processor_common.py               |  14 +
 .../session_processor_default.py              | 249 +++++++++++-----
 .../session_queue/session_queue_sqlite.py     |   5 +-
 .../app/services/shared/invocation_context.py |  20 +-
 invokeai/app/util/step_callback.py            |   9 +-
 22 files changed, 227 insertions(+), 879 deletions(-)
 delete mode 100644 invokeai/app/api/routers/sessions.py
 delete mode 100644 invokeai/app/services/invocation_processor/__init__.py
 delete mode 100644 invokeai/app/services/invocation_processor/invocation_processor_base.py
 delete mode 100644 invokeai/app/services/invocation_processor/invocation_processor_common.py
 delete mode 100644 invokeai/app/services/invocation_processor/invocation_processor_default.py
 delete mode 100644 invokeai/app/services/invocation_queue/__init__.py
 delete mode 100644 invokeai/app/services/invocation_queue/invocation_queue_base.py
 delete mode 100644 invokeai/app/services/invocation_queue/invocation_queue_common.py
 delete mode 100644 invokeai/app/services/invocation_queue/invocation_queue_memory.py

diff --git a/invokeai/app/api/dependencies.py b/invokeai/app/api/dependencies.py
index 8e79b26e2d..a9132516a8 100644
--- a/invokeai/app/api/dependencies.py
+++ b/invokeai/app/api/dependencies.py
@@ -4,7 +4,6 @@ from logging import Logger
 
 import torch
 
-from invokeai.app.services.item_storage.item_storage_memory import ItemStorageMemory
 from invokeai.app.services.object_serializer.object_serializer_disk import ObjectSerializerDisk
 from invokeai.app.services.object_serializer.object_serializer_forward_cache import ObjectSerializerForwardCache
 from invokeai.app.services.shared.sqlite.sqlite_util import init_db
@@ -22,8 +21,6 @@ from ..services.image_files.image_files_disk import DiskImageFileStorage
 from ..services.image_records.image_records_sqlite import SqliteImageRecordStorage
 from ..services.images.images_default import ImageService
 from ..services.invocation_cache.invocation_cache_memory import MemoryInvocationCache
-from ..services.invocation_processor.invocation_processor_default import DefaultInvocationProcessor
-from ..services.invocation_queue.invocation_queue_memory import MemoryInvocationQueue
 from ..services.invocation_services import InvocationServices
 from ..services.invocation_stats.invocation_stats_default import InvocationStatsService
 from ..services.invoker import Invoker
@@ -33,7 +30,6 @@ from ..services.model_records import ModelRecordServiceSQL
 from ..services.names.names_default import SimpleNameService
 from ..services.session_processor.session_processor_default import DefaultSessionProcessor
 from ..services.session_queue.session_queue_sqlite import SqliteSessionQueue
-from ..services.shared.graph import GraphExecutionState
 from ..services.urls.urls_default import LocalUrlService
 from ..services.workflow_records.workflow_records_sqlite import SqliteWorkflowRecordsStorage
 from .events import FastAPIEventService
@@ -85,7 +81,6 @@ class ApiDependencies:
         board_records = SqliteBoardRecordStorage(db=db)
         boards = BoardService()
         events = FastAPIEventService(event_handler_id)
-        graph_execution_manager = ItemStorageMemory[GraphExecutionState]()
         image_records = SqliteImageRecordStorage(db=db)
         images = ImageService()
         invocation_cache = MemoryInvocationCache(max_cache_size=config.node_cache_size)
@@ -105,8 +100,6 @@ class ApiDependencies:
         )
         names = SimpleNameService()
         performance_statistics = InvocationStatsService()
-        processor = DefaultInvocationProcessor()
-        queue = MemoryInvocationQueue()
         session_processor = DefaultSessionProcessor()
         session_queue = SqliteSessionQueue(db=db)
         urls = LocalUrlService()
@@ -119,7 +112,6 @@ class ApiDependencies:
             boards=boards,
             configuration=configuration,
             events=events,
-            graph_execution_manager=graph_execution_manager,
             image_files=image_files,
             image_records=image_records,
             images=images,
@@ -129,8 +121,6 @@ class ApiDependencies:
             download_queue=download_queue_service,
             names=names,
             performance_statistics=performance_statistics,
-            processor=processor,
-            queue=queue,
             session_processor=session_processor,
             session_queue=session_queue,
             urls=urls,
diff --git a/invokeai/app/api/routers/sessions.py b/invokeai/app/api/routers/sessions.py
deleted file mode 100644
index fb850d0b2b..0000000000
--- a/invokeai/app/api/routers/sessions.py
+++ /dev/null
@@ -1,276 +0,0 @@
-# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
-
-
-from fastapi import HTTPException, Path
-from fastapi.routing import APIRouter
-
-from ...services.shared.graph import GraphExecutionState
-from ..dependencies import ApiDependencies
-
-session_router = APIRouter(prefix="/v1/sessions", tags=["sessions"])
-
-
-# @session_router.post(
-#     "/",
-#     operation_id="create_session",
-#     responses={
-#         200: {"model": GraphExecutionState},
-#         400: {"description": "Invalid json"},
-#     },
-#     deprecated=True,
-# )
-# async def create_session(
-#     queue_id: str = Query(default="", description="The id of the queue to associate the session with"),
-#     graph: Optional[Graph] = Body(default=None, description="The graph to initialize the session with"),
-# ) -> GraphExecutionState:
-#     """Creates a new session, optionally initializing it with an invocation graph"""
-#     session = ApiDependencies.invoker.create_execution_state(queue_id=queue_id, graph=graph)
-#     return session
-
-
-# @session_router.get(
-#     "/",
-#     operation_id="list_sessions",
-#     responses={200: {"model": PaginatedResults[GraphExecutionState]}},
-#     deprecated=True,
-# )
-# async def list_sessions(
-#     page: int = Query(default=0, description="The page of results to get"),
-#     per_page: int = Query(default=10, description="The number of results per page"),
-#     query: str = Query(default="", description="The query string to search for"),
-# ) -> PaginatedResults[GraphExecutionState]:
-#     """Gets a list of sessions, optionally searching"""
-#     if query == "":
-#         result = ApiDependencies.invoker.services.graph_execution_manager.list(page, per_page)
-#     else:
-#         result = ApiDependencies.invoker.services.graph_execution_manager.search(query, page, per_page)
-#     return result
-
-
-@session_router.get(
-    "/{session_id}",
-    operation_id="get_session",
-    responses={
-        200: {"model": GraphExecutionState},
-        404: {"description": "Session not found"},
-    },
-)
-async def get_session(
-    session_id: str = Path(description="The id of the session to get"),
-) -> GraphExecutionState:
-    """Gets a session"""
-    session = ApiDependencies.invoker.services.graph_execution_manager.get(session_id)
-    if session is None:
-        raise HTTPException(status_code=404)
-    else:
-        return session
-
-
-# @session_router.post(
-#     "/{session_id}/nodes",
-#     operation_id="add_node",
-#     responses={
-#         200: {"model": str},
-#         400: {"description": "Invalid node or link"},
-#         404: {"description": "Session not found"},
-#     },
-#     deprecated=True,
-# )
-# async def add_node(
-#     session_id: str = Path(description="The id of the session"),
-#     node: Annotated[Union[BaseInvocation.get_invocations()], Field(discriminator="type")] = Body(  # type: ignore
-#         description="The node to add"
-#     ),
-# ) -> str:
-#     """Adds a node to the graph"""
-#     session = ApiDependencies.invoker.services.graph_execution_manager.get(session_id)
-#     if session is None:
-#         raise HTTPException(status_code=404)
-
-#     try:
-#         session.add_node(node)
-#         ApiDependencies.invoker.services.graph_execution_manager.set(
-#             session
-#         )  # TODO: can this be done automatically, or add node through an API?
-#         return session.id
-#     except NodeAlreadyExecutedError:
-#         raise HTTPException(status_code=400)
-#     except IndexError:
-#         raise HTTPException(status_code=400)
-
-
-# @session_router.put(
-#     "/{session_id}/nodes/{node_path}",
-#     operation_id="update_node",
-#     responses={
-#         200: {"model": GraphExecutionState},
-#         400: {"description": "Invalid node or link"},
-#         404: {"description": "Session not found"},
-#     },
-#     deprecated=True,
-# )
-# async def update_node(
-#     session_id: str = Path(description="The id of the session"),
-#     node_path: str = Path(description="The path to the node in the graph"),
-#     node: Annotated[Union[BaseInvocation.get_invocations()], Field(discriminator="type")] = Body(  # type: ignore
-#         description="The new node"
-#     ),
-# ) -> GraphExecutionState:
-#     """Updates a node in the graph and removes all linked edges"""
-#     session = ApiDependencies.invoker.services.graph_execution_manager.get(session_id)
-#     if session is None:
-#         raise HTTPException(status_code=404)
-
-#     try:
-#         session.update_node(node_path, node)
-#         ApiDependencies.invoker.services.graph_execution_manager.set(
-#             session
-#         )  # TODO: can this be done automatically, or add node through an API?
-#         return session
-#     except NodeAlreadyExecutedError:
-#         raise HTTPException(status_code=400)
-#     except IndexError:
-#         raise HTTPException(status_code=400)
-
-
-# @session_router.delete(
-#     "/{session_id}/nodes/{node_path}",
-#     operation_id="delete_node",
-#     responses={
-#         200: {"model": GraphExecutionState},
-#         400: {"description": "Invalid node or link"},
-#         404: {"description": "Session not found"},
-#     },
-#     deprecated=True,
-# )
-# async def delete_node(
-#     session_id: str = Path(description="The id of the session"),
-#     node_path: str = Path(description="The path to the node to delete"),
-# ) -> GraphExecutionState:
-#     """Deletes a node in the graph and removes all linked edges"""
-#     session = ApiDependencies.invoker.services.graph_execution_manager.get(session_id)
-#     if session is None:
-#         raise HTTPException(status_code=404)
-
-#     try:
-#         session.delete_node(node_path)
-#         ApiDependencies.invoker.services.graph_execution_manager.set(
-#             session
-#         )  # TODO: can this be done automatically, or add node through an API?
-#         return session
-#     except NodeAlreadyExecutedError:
-#         raise HTTPException(status_code=400)
-#     except IndexError:
-#         raise HTTPException(status_code=400)
-
-
-# @session_router.post(
-#     "/{session_id}/edges",
-#     operation_id="add_edge",
-#     responses={
-#         200: {"model": GraphExecutionState},
-#         400: {"description": "Invalid node or link"},
-#         404: {"description": "Session not found"},
-#     },
-#     deprecated=True,
-# )
-# async def add_edge(
-#     session_id: str = Path(description="The id of the session"),
-#     edge: Edge = Body(description="The edge to add"),
-# ) -> GraphExecutionState:
-#     """Adds an edge to the graph"""
-#     session = ApiDependencies.invoker.services.graph_execution_manager.get(session_id)
-#     if session is None:
-#         raise HTTPException(status_code=404)
-
-#     try:
-#         session.add_edge(edge)
-#         ApiDependencies.invoker.services.graph_execution_manager.set(
-#             session
-#         )  # TODO: can this be done automatically, or add node through an API?
-#         return session
-#     except NodeAlreadyExecutedError:
-#         raise HTTPException(status_code=400)
-#     except IndexError:
-#         raise HTTPException(status_code=400)
-
-
-# # TODO: the edge being in the path here is really ugly, find a better solution
-# @session_router.delete(
-#     "/{session_id}/edges/{from_node_id}/{from_field}/{to_node_id}/{to_field}",
-#     operation_id="delete_edge",
-#     responses={
-#         200: {"model": GraphExecutionState},
-#         400: {"description": "Invalid node or link"},
-#         404: {"description": "Session not found"},
-#     },
-#     deprecated=True,
-# )
-# async def delete_edge(
-#     session_id: str = Path(description="The id of the session"),
-#     from_node_id: str = Path(description="The id of the node the edge is coming from"),
-#     from_field: str = Path(description="The field of the node the edge is coming from"),
-#     to_node_id: str = Path(description="The id of the node the edge is going to"),
-#     to_field: str = Path(description="The field of the node the edge is going to"),
-# ) -> GraphExecutionState:
-#     """Deletes an edge from the graph"""
-#     session = ApiDependencies.invoker.services.graph_execution_manager.get(session_id)
-#     if session is None:
-#         raise HTTPException(status_code=404)
-
-#     try:
-#         edge = Edge(
-#             source=EdgeConnection(node_id=from_node_id, field=from_field),
-#             destination=EdgeConnection(node_id=to_node_id, field=to_field),
-#         )
-#         session.delete_edge(edge)
-#         ApiDependencies.invoker.services.graph_execution_manager.set(
-#             session
-#         )  # TODO: can this be done automatically, or add node through an API?
-#         return session
-#     except NodeAlreadyExecutedError:
-#         raise HTTPException(status_code=400)
-#     except IndexError:
-#         raise HTTPException(status_code=400)
-
-
-# @session_router.put(
-#     "/{session_id}/invoke",
-#     operation_id="invoke_session",
-#     responses={
-#         200: {"model": None},
-#         202: {"description": "The invocation is queued"},
-#         400: {"description": "The session has no invocations ready to invoke"},
-#         404: {"description": "Session not found"},
-#     },
-#     deprecated=True,
-# )
-# async def invoke_session(
-#     queue_id: str = Query(description="The id of the queue to associate the session with"),
-#     session_id: str = Path(description="The id of the session to invoke"),
-#     all: bool = Query(default=False, description="Whether or not to invoke all remaining invocations"),
-# ) -> Response:
-#     """Invokes a session"""
-#     session = ApiDependencies.invoker.services.graph_execution_manager.get(session_id)
-#     if session is None:
-#         raise HTTPException(status_code=404)
-
-#     if session.is_complete():
-#         raise HTTPException(status_code=400)
-
-#     ApiDependencies.invoker.invoke(queue_id, session, invoke_all=all)
-#     return Response(status_code=202)
-
-
-# @session_router.delete(
-#     "/{session_id}/invoke",
-#     operation_id="cancel_session_invoke",
-#     responses={202: {"description": "The invocation is canceled"}},
-#     deprecated=True,
-# )
-# async def cancel_session_invoke(
-#     session_id: str = Path(description="The id of the session to cancel"),
-# ) -> Response:
-#     """Invokes a session"""
-#     ApiDependencies.invoker.cancel(session_id)
-#     return Response(status_code=202)
diff --git a/invokeai/app/api_app.py b/invokeai/app/api_app.py
index 65607c436a..f6b08ddba6 100644
--- a/invokeai/app/api_app.py
+++ b/invokeai/app/api_app.py
@@ -50,7 +50,6 @@ if True:  # hack to make flake8 happy with imports coming after setting up the c
         images,
         model_manager,
         session_queue,
-        sessions,
         utilities,
         workflows,
     )
@@ -110,8 +109,6 @@ async def shutdown_event() -> None:
 
 
 # Include all routers
-app.include_router(sessions.session_router, prefix="/api")
-
 app.include_router(utilities.utilities_router, prefix="/api")
 app.include_router(model_manager.model_manager_router, prefix="/api")
 app.include_router(download_queue.download_queue_router, prefix="/api")
diff --git a/invokeai/app/services/events/events_base.py b/invokeai/app/services/events/events_base.py
index 90d9068b88..5355fe2298 100644
--- a/invokeai/app/services/events/events_base.py
+++ b/invokeai/app/services/events/events_base.py
@@ -3,7 +3,7 @@
 
 from typing import Any, Dict, List, Optional, Union
 
-from invokeai.app.services.invocation_processor.invocation_processor_common import ProgressImage
+from invokeai.app.services.session_processor.session_processor_common import ProgressImage
 from invokeai.app.services.session_queue.session_queue_common import (
     BatchStatus,
     EnqueueBatchResult,
@@ -204,52 +204,6 @@ class EventServiceBase:
             },
         )
 
-    def emit_session_retrieval_error(
-        self,
-        queue_id: str,
-        queue_item_id: int,
-        queue_batch_id: str,
-        graph_execution_state_id: str,
-        error_type: str,
-        error: str,
-    ) -> None:
-        """Emitted when session retrieval fails"""
-        self.__emit_queue_event(
-            event_name="session_retrieval_error",
-            payload={
-                "queue_id": queue_id,
-                "queue_item_id": queue_item_id,
-                "queue_batch_id": queue_batch_id,
-                "graph_execution_state_id": graph_execution_state_id,
-                "error_type": error_type,
-                "error": error,
-            },
-        )
-
-    def emit_invocation_retrieval_error(
-        self,
-        queue_id: str,
-        queue_item_id: int,
-        queue_batch_id: str,
-        graph_execution_state_id: str,
-        node_id: str,
-        error_type: str,
-        error: str,
-    ) -> None:
-        """Emitted when invocation retrieval fails"""
-        self.__emit_queue_event(
-            event_name="invocation_retrieval_error",
-            payload={
-                "queue_id": queue_id,
-                "queue_item_id": queue_item_id,
-                "queue_batch_id": queue_batch_id,
-                "graph_execution_state_id": graph_execution_state_id,
-                "node_id": node_id,
-                "error_type": error_type,
-                "error": error,
-            },
-        )
-
     def emit_session_canceled(
         self,
         queue_id: str,
diff --git a/invokeai/app/services/invocation_processor/__init__.py b/invokeai/app/services/invocation_processor/__init__.py
deleted file mode 100644
index e69de29bb2..0000000000
diff --git a/invokeai/app/services/invocation_processor/invocation_processor_base.py b/invokeai/app/services/invocation_processor/invocation_processor_base.py
deleted file mode 100644
index 7947a201dd..0000000000
--- a/invokeai/app/services/invocation_processor/invocation_processor_base.py
+++ /dev/null
@@ -1,5 +0,0 @@
-from abc import ABC
-
-
-class InvocationProcessorABC(ABC):  # noqa: B024
-    pass
diff --git a/invokeai/app/services/invocation_processor/invocation_processor_common.py b/invokeai/app/services/invocation_processor/invocation_processor_common.py
deleted file mode 100644
index 347f6c7323..0000000000
--- a/invokeai/app/services/invocation_processor/invocation_processor_common.py
+++ /dev/null
@@ -1,15 +0,0 @@
-from pydantic import BaseModel, Field
-
-
-class ProgressImage(BaseModel):
-    """The progress image sent intermittently during processing"""
-
-    width: int = Field(description="The effective width of the image in pixels")
-    height: int = Field(description="The effective height of the image in pixels")
-    dataURL: str = Field(description="The image data as a b64 data URL")
-
-
-class CanceledException(Exception):
-    """Execution canceled by user."""
-
-    pass
diff --git a/invokeai/app/services/invocation_processor/invocation_processor_default.py b/invokeai/app/services/invocation_processor/invocation_processor_default.py
deleted file mode 100644
index d2ebe235e6..0000000000
--- a/invokeai/app/services/invocation_processor/invocation_processor_default.py
+++ /dev/null
@@ -1,241 +0,0 @@
-import time
-import traceback
-from contextlib import suppress
-from threading import BoundedSemaphore, Event, Thread
-from typing import Optional
-
-import invokeai.backend.util.logging as logger
-from invokeai.app.services.invocation_queue.invocation_queue_common import InvocationQueueItem
-from invokeai.app.services.invocation_stats.invocation_stats_common import (
-    GESStatsNotFoundError,
-)
-from invokeai.app.services.shared.invocation_context import InvocationContextData, build_invocation_context
-from invokeai.app.util.profiler import Profiler
-
-from ..invoker import Invoker
-from .invocation_processor_base import InvocationProcessorABC
-from .invocation_processor_common import CanceledException
-
-
-class DefaultInvocationProcessor(InvocationProcessorABC):
-    __invoker_thread: Thread
-    __stop_event: Event
-    __invoker: Invoker
-    __threadLimit: BoundedSemaphore
-
-    def start(self, invoker: Invoker) -> None:
-        # if we do want multithreading at some point, we could make this configurable
-        self.__threadLimit = BoundedSemaphore(1)
-        self.__invoker = invoker
-        self.__stop_event = Event()
-        self.__invoker_thread = Thread(
-            name="invoker_processor",
-            target=self.__process,
-            kwargs={"stop_event": self.__stop_event},
-        )
-        self.__invoker_thread.daemon = True  # TODO: make async and do not use threads
-        self.__invoker_thread.start()
-
-    def stop(self, *args, **kwargs) -> None:
-        self.__stop_event.set()
-
-    def __process(self, stop_event: Event):
-        try:
-            self.__threadLimit.acquire()
-            queue_item: Optional[InvocationQueueItem] = None
-
-            profiler = (
-                Profiler(
-                    logger=self.__invoker.services.logger,
-                    output_dir=self.__invoker.services.configuration.profiles_path,
-                    prefix=self.__invoker.services.configuration.profile_prefix,
-                )
-                if self.__invoker.services.configuration.profile_graphs
-                else None
-            )
-
-            def stats_cleanup(graph_execution_state_id: str) -> None:
-                if profiler:
-                    profile_path = profiler.stop()
-                    stats_path = profile_path.with_suffix(".json")
-                    self.__invoker.services.performance_statistics.dump_stats(
-                        graph_execution_state_id=graph_execution_state_id, output_path=stats_path
-                    )
-                with suppress(GESStatsNotFoundError):
-                    self.__invoker.services.performance_statistics.log_stats(graph_execution_state_id)
-                    self.__invoker.services.performance_statistics.reset_stats(graph_execution_state_id)
-
-            while not stop_event.is_set():
-                try:
-                    queue_item = self.__invoker.services.queue.get()
-                except Exception as e:
-                    self.__invoker.services.logger.error("Exception while getting from queue:\n%s" % e)
-
-                if not queue_item:  # Probably stopping
-                    # do not hammer the queue
-                    time.sleep(0.5)
-                    continue
-
-                if profiler and profiler.profile_id != queue_item.graph_execution_state_id:
-                    profiler.start(profile_id=queue_item.graph_execution_state_id)
-
-                try:
-                    graph_execution_state = self.__invoker.services.graph_execution_manager.get(
-                        queue_item.graph_execution_state_id
-                    )
-                except Exception as e:
-                    self.__invoker.services.logger.error("Exception while retrieving session:\n%s" % e)
-                    self.__invoker.services.events.emit_session_retrieval_error(
-                        queue_batch_id=queue_item.session_queue_batch_id,
-                        queue_item_id=queue_item.session_queue_item_id,
-                        queue_id=queue_item.session_queue_id,
-                        graph_execution_state_id=queue_item.graph_execution_state_id,
-                        error_type=e.__class__.__name__,
-                        error=traceback.format_exc(),
-                    )
-                    continue
-
-                try:
-                    invocation = graph_execution_state.execution_graph.get_node(queue_item.invocation_id)
-                except Exception as e:
-                    self.__invoker.services.logger.error("Exception while retrieving invocation:\n%s" % e)
-                    self.__invoker.services.events.emit_invocation_retrieval_error(
-                        queue_batch_id=queue_item.session_queue_batch_id,
-                        queue_item_id=queue_item.session_queue_item_id,
-                        queue_id=queue_item.session_queue_id,
-                        graph_execution_state_id=queue_item.graph_execution_state_id,
-                        node_id=queue_item.invocation_id,
-                        error_type=e.__class__.__name__,
-                        error=traceback.format_exc(),
-                    )
-                    continue
-
-                # get the source node id to provide to clients (the prepared node id is not as useful)
-                source_node_id = graph_execution_state.prepared_source_mapping[invocation.id]
-
-                # Send starting event
-                self.__invoker.services.events.emit_invocation_started(
-                    queue_batch_id=queue_item.session_queue_batch_id,
-                    queue_item_id=queue_item.session_queue_item_id,
-                    queue_id=queue_item.session_queue_id,
-                    graph_execution_state_id=graph_execution_state.id,
-                    node=invocation.model_dump(),
-                    source_node_id=source_node_id,
-                )
-
-                # Invoke
-                try:
-                    graph_id = graph_execution_state.id
-                    with self.__invoker.services.performance_statistics.collect_stats(invocation, graph_id):
-                        # use the internal invoke_internal(), which wraps the node's invoke() method,
-                        # which handles a few things:
-                        # - nodes that require a value, but get it only from a connection
-                        # - referencing the invocation cache instead of executing the node
-                        context_data = InvocationContextData(
-                            invocation=invocation,
-                            session_id=graph_id,
-                            workflow=queue_item.workflow,
-                            source_node_id=source_node_id,
-                            queue_id=queue_item.session_queue_id,
-                            queue_item_id=queue_item.session_queue_item_id,
-                            batch_id=queue_item.session_queue_batch_id,
-                        )
-                        context = build_invocation_context(
-                            services=self.__invoker.services,
-                            context_data=context_data,
-                        )
-                        outputs = invocation.invoke_internal(context=context, services=self.__invoker.services)
-
-                        # Check queue to see if this is canceled, and skip if so
-                        if self.__invoker.services.queue.is_canceled(graph_execution_state.id):
-                            continue
-
-                        # Save outputs and history
-                        graph_execution_state.complete(invocation.id, outputs)
-
-                        # Save the state changes
-                        self.__invoker.services.graph_execution_manager.set(graph_execution_state)
-
-                        # Send complete event
-                        self.__invoker.services.events.emit_invocation_complete(
-                            queue_batch_id=queue_item.session_queue_batch_id,
-                            queue_item_id=queue_item.session_queue_item_id,
-                            queue_id=queue_item.session_queue_id,
-                            graph_execution_state_id=graph_execution_state.id,
-                            node=invocation.model_dump(),
-                            source_node_id=source_node_id,
-                            result=outputs.model_dump(),
-                        )
-
-                except KeyboardInterrupt:
-                    pass
-
-                except CanceledException:
-                    stats_cleanup(graph_execution_state.id)
-                    pass
-
-                except Exception as e:
-                    error = traceback.format_exc()
-                    logger.error(error)
-
-                    # Save error
-                    graph_execution_state.set_node_error(invocation.id, error)
-
-                    # Save the state changes
-                    self.__invoker.services.graph_execution_manager.set(graph_execution_state)
-
-                    self.__invoker.services.logger.error("Error while invoking:\n%s" % e)
-                    # Send error event
-                    self.__invoker.services.events.emit_invocation_error(
-                        queue_batch_id=queue_item.session_queue_batch_id,
-                        queue_item_id=queue_item.session_queue_item_id,
-                        queue_id=queue_item.session_queue_id,
-                        graph_execution_state_id=graph_execution_state.id,
-                        node=invocation.model_dump(),
-                        source_node_id=source_node_id,
-                        error_type=e.__class__.__name__,
-                        error=error,
-                    )
-                    pass
-
-                # Check queue to see if this is canceled, and skip if so
-                if self.__invoker.services.queue.is_canceled(graph_execution_state.id):
-                    continue
-
-                # Queue any further commands if invoking all
-                is_complete = graph_execution_state.is_complete()
-                if queue_item.invoke_all and not is_complete:
-                    try:
-                        self.__invoker.invoke(
-                            session_queue_batch_id=queue_item.session_queue_batch_id,
-                            session_queue_item_id=queue_item.session_queue_item_id,
-                            session_queue_id=queue_item.session_queue_id,
-                            graph_execution_state=graph_execution_state,
-                            workflow=queue_item.workflow,
-                            invoke_all=True,
-                        )
-                    except Exception as e:
-                        self.__invoker.services.logger.error("Error while invoking:\n%s" % e)
-                        self.__invoker.services.events.emit_invocation_error(
-                            queue_batch_id=queue_item.session_queue_batch_id,
-                            queue_item_id=queue_item.session_queue_item_id,
-                            queue_id=queue_item.session_queue_id,
-                            graph_execution_state_id=graph_execution_state.id,
-                            node=invocation.model_dump(),
-                            source_node_id=source_node_id,
-                            error_type=e.__class__.__name__,
-                            error=traceback.format_exc(),
-                        )
-                elif is_complete:
-                    self.__invoker.services.events.emit_graph_execution_complete(
-                        queue_batch_id=queue_item.session_queue_batch_id,
-                        queue_item_id=queue_item.session_queue_item_id,
-                        queue_id=queue_item.session_queue_id,
-                        graph_execution_state_id=graph_execution_state.id,
-                    )
-                    stats_cleanup(graph_execution_state.id)
-
-        except KeyboardInterrupt:
-            pass  # Log something? KeyboardInterrupt is probably not going to be seen by the processor
-        finally:
-            self.__threadLimit.release()
diff --git a/invokeai/app/services/invocation_queue/__init__.py b/invokeai/app/services/invocation_queue/__init__.py
deleted file mode 100644
index e69de29bb2..0000000000
diff --git a/invokeai/app/services/invocation_queue/invocation_queue_base.py b/invokeai/app/services/invocation_queue/invocation_queue_base.py
deleted file mode 100644
index 09f4875c5f..0000000000
--- a/invokeai/app/services/invocation_queue/invocation_queue_base.py
+++ /dev/null
@@ -1,26 +0,0 @@
-# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
-
-from abc import ABC, abstractmethod
-from typing import Optional
-
-from .invocation_queue_common import InvocationQueueItem
-
-
-class InvocationQueueABC(ABC):
-    """Abstract base class for all invocation queues"""
-
-    @abstractmethod
-    def get(self) -> InvocationQueueItem:
-        pass
-
-    @abstractmethod
-    def put(self, item: Optional[InvocationQueueItem]) -> None:
-        pass
-
-    @abstractmethod
-    def cancel(self, graph_execution_state_id: str) -> None:
-        pass
-
-    @abstractmethod
-    def is_canceled(self, graph_execution_state_id: str) -> bool:
-        pass
diff --git a/invokeai/app/services/invocation_queue/invocation_queue_common.py b/invokeai/app/services/invocation_queue/invocation_queue_common.py
deleted file mode 100644
index 696f6a981d..0000000000
--- a/invokeai/app/services/invocation_queue/invocation_queue_common.py
+++ /dev/null
@@ -1,23 +0,0 @@
-# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
-
-import time
-from typing import Optional
-
-from pydantic import BaseModel, Field
-
-from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID
-
-
-class InvocationQueueItem(BaseModel):
-    graph_execution_state_id: str = Field(description="The ID of the graph execution state")
-    invocation_id: str = Field(description="The ID of the node being invoked")
-    session_queue_id: str = Field(description="The ID of the session queue from which this invocation queue item came")
-    session_queue_item_id: int = Field(
-        description="The ID of session queue item from which this invocation queue item came"
-    )
-    session_queue_batch_id: str = Field(
-        description="The ID of the session batch from which this invocation queue item came"
-    )
-    workflow: Optional[WorkflowWithoutID] = Field(description="The workflow associated with this queue item")
-    invoke_all: bool = Field(default=False)
-    timestamp: float = Field(default_factory=time.time)
diff --git a/invokeai/app/services/invocation_queue/invocation_queue_memory.py b/invokeai/app/services/invocation_queue/invocation_queue_memory.py
deleted file mode 100644
index 8d6fff7052..0000000000
--- a/invokeai/app/services/invocation_queue/invocation_queue_memory.py
+++ /dev/null
@@ -1,44 +0,0 @@
-# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
-
-import time
-from queue import Queue
-from typing import Optional
-
-from .invocation_queue_base import InvocationQueueABC
-from .invocation_queue_common import InvocationQueueItem
-
-
-class MemoryInvocationQueue(InvocationQueueABC):
-    __queue: Queue
-    __cancellations: dict[str, float]
-
-    def __init__(self):
-        self.__queue = Queue()
-        self.__cancellations = {}
-
-    def get(self) -> InvocationQueueItem:
-        item = self.__queue.get()
-
-        while (
-            isinstance(item, InvocationQueueItem)
-            and item.graph_execution_state_id in self.__cancellations
-            and self.__cancellations[item.graph_execution_state_id] > item.timestamp
-        ):
-            item = self.__queue.get()
-
-        # Clear old items
-        for graph_execution_state_id in list(self.__cancellations.keys()):
-            if self.__cancellations[graph_execution_state_id] < item.timestamp:
-                del self.__cancellations[graph_execution_state_id]
-
-        return item
-
-    def put(self, item: Optional[InvocationQueueItem]) -> None:
-        self.__queue.put(item)
-
-    def cancel(self, graph_execution_state_id: str) -> None:
-        if graph_execution_state_id not in self.__cancellations:
-            self.__cancellations[graph_execution_state_id] = time.time()
-
-    def is_canceled(self, graph_execution_state_id: str) -> bool:
-        return graph_execution_state_id in self.__cancellations
diff --git a/invokeai/app/services/invocation_services.py b/invokeai/app/services/invocation_services.py
index 0a1fa1e922..04fe71a3eb 100644
--- a/invokeai/app/services/invocation_services.py
+++ b/invokeai/app/services/invocation_services.py
@@ -23,15 +23,11 @@ if TYPE_CHECKING:
     from .image_records.image_records_base import ImageRecordStorageBase
     from .images.images_base import ImageServiceABC
     from .invocation_cache.invocation_cache_base import InvocationCacheBase
-    from .invocation_processor.invocation_processor_base import InvocationProcessorABC
-    from .invocation_queue.invocation_queue_base import InvocationQueueABC
     from .invocation_stats.invocation_stats_base import InvocationStatsServiceBase
-    from .item_storage.item_storage_base import ItemStorageABC
     from .model_manager.model_manager_base import ModelManagerServiceBase
     from .names.names_base import NameServiceBase
     from .session_processor.session_processor_base import SessionProcessorBase
     from .session_queue.session_queue_base import SessionQueueBase
-    from .shared.graph import GraphExecutionState
     from .urls.urls_base import UrlServiceBase
     from .workflow_records.workflow_records_base import WorkflowRecordsStorageBase
 
@@ -47,16 +43,13 @@ class InvocationServices:
         board_records: "BoardRecordStorageBase",
         configuration: "InvokeAIAppConfig",
         events: "EventServiceBase",
-        graph_execution_manager: "ItemStorageABC[GraphExecutionState]",
         images: "ImageServiceABC",
         image_files: "ImageFileStorageBase",
         image_records: "ImageRecordStorageBase",
         logger: "Logger",
         model_manager: "ModelManagerServiceBase",
         download_queue: "DownloadQueueServiceBase",
-        processor: "InvocationProcessorABC",
         performance_statistics: "InvocationStatsServiceBase",
-        queue: "InvocationQueueABC",
         session_queue: "SessionQueueBase",
         session_processor: "SessionProcessorBase",
         invocation_cache: "InvocationCacheBase",
@@ -72,16 +65,13 @@ class InvocationServices:
         self.board_records = board_records
         self.configuration = configuration
         self.events = events
-        self.graph_execution_manager = graph_execution_manager
         self.images = images
         self.image_files = image_files
         self.image_records = image_records
         self.logger = logger
         self.model_manager = model_manager
         self.download_queue = download_queue
-        self.processor = processor
         self.performance_statistics = performance_statistics
-        self.queue = queue
         self.session_queue = session_queue
         self.session_processor = session_processor
         self.invocation_cache = invocation_cache
diff --git a/invokeai/app/services/invocation_stats/invocation_stats_base.py b/invokeai/app/services/invocation_stats/invocation_stats_base.py
index ec8a453323..b28220e74c 100644
--- a/invokeai/app/services/invocation_stats/invocation_stats_base.py
+++ b/invokeai/app/services/invocation_stats/invocation_stats_base.py
@@ -3,7 +3,7 @@
 
 Usage:
 
-statistics = InvocationStatsService(graph_execution_manager)
+statistics = InvocationStatsService()
 with statistics.collect_stats(invocation, graph_execution_state.id):
       ... execute graphs...
 statistics.log_stats()
@@ -60,12 +60,8 @@ class InvocationStatsServiceBase(ABC):
         pass
 
     @abstractmethod
-    def reset_stats(self, graph_execution_state_id: str) -> None:
-        """
-        Reset all statistics for the indicated graph.
-        :param graph_execution_state_id: The id of the session whose stats to reset.
-        :raises GESStatsNotFoundError: if the graph isn't tracked in the stats.
-        """
+    def reset_stats(self):
+        """Reset all stored statistics."""
         pass
 
     @abstractmethod
diff --git a/invokeai/app/services/invocation_stats/invocation_stats_default.py b/invokeai/app/services/invocation_stats/invocation_stats_default.py
index 486a1ca5b3..06a5b675c3 100644
--- a/invokeai/app/services/invocation_stats/invocation_stats_default.py
+++ b/invokeai/app/services/invocation_stats/invocation_stats_default.py
@@ -10,7 +10,6 @@ import torch
 import invokeai.backend.util.logging as logger
 from invokeai.app.invocations.baseinvocation import BaseInvocation
 from invokeai.app.services.invoker import Invoker
-from invokeai.app.services.item_storage.item_storage_common import ItemNotFoundError
 from invokeai.backend.model_manager.load.model_cache import CacheStats
 
 from .invocation_stats_base import InvocationStatsServiceBase
@@ -51,9 +50,6 @@ class InvocationStatsService(InvocationStatsServiceBase):
             self._stats[graph_execution_state_id] = GraphExecutionStats()
             self._cache_stats[graph_execution_state_id] = CacheStats()
 
-            # Prune stale stats. There should be none since we're starting a new graph, but just in case.
-            self._prune_stale_stats()
-
         # Record state before the invocation.
         start_time = time.time()
         start_ram = psutil.Process().memory_info().rss
@@ -78,42 +74,9 @@ class InvocationStatsService(InvocationStatsServiceBase):
             )
             self._stats[graph_execution_state_id].add_node_execution_stats(node_stats)
 
-    def _prune_stale_stats(self) -> None:
-        """Check all graphs being tracked and prune any that have completed/errored.
-
-        This shouldn't be necessary, but we don't have totally robust upstream handling of graph completions/errors, so
-        for now we call this function periodically to prevent them from accumulating.
-        """
-        to_prune: list[str] = []
-        for graph_execution_state_id in self._stats:
-            try:
-                graph_execution_state = self._invoker.services.graph_execution_manager.get(graph_execution_state_id)
-            except ItemNotFoundError:
-                # TODO(ryand): What would cause this? Should this exception just be allowed to propagate?
-                logger.warning(f"Failed to get graph state for {graph_execution_state_id}.")
-                continue
-
-            if not graph_execution_state.is_complete():
-                # The graph is still running, don't prune it.
-                continue
-
-            to_prune.append(graph_execution_state_id)
-
-        for graph_execution_state_id in to_prune:
-            del self._stats[graph_execution_state_id]
-            del self._cache_stats[graph_execution_state_id]
-
-        if len(to_prune) > 0:
-            logger.info(f"Pruned stale graph stats for {to_prune}.")
-
-    def reset_stats(self, graph_execution_state_id: str):
-        try:
-            del self._stats[graph_execution_state_id]
-            del self._cache_stats[graph_execution_state_id]
-        except KeyError as e:
-            raise GESStatsNotFoundError(
-                f"Attempted to clear statistics for unknown graph {graph_execution_state_id}: {e}."
-            ) from e
+    def reset_stats(self):
+        self._stats = {}
+        self._cache_stats = {}
 
     def get_stats(self, graph_execution_state_id: str) -> InvocationStatsSummary:
         graph_stats_summary = self._get_graph_summary(graph_execution_state_id)
diff --git a/invokeai/app/services/invoker.py b/invokeai/app/services/invoker.py
index a04c6f2059..527afb37f4 100644
--- a/invokeai/app/services/invoker.py
+++ b/invokeai/app/services/invoker.py
@@ -1,12 +1,7 @@
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
 
-from typing import Optional
 
-from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID
-
-from .invocation_queue.invocation_queue_common import InvocationQueueItem
 from .invocation_services import InvocationServices
-from .shared.graph import Graph, GraphExecutionState
 
 
 class Invoker:
@@ -18,51 +13,6 @@ class Invoker:
         self.services = services
         self._start()
 
-    def invoke(
-        self,
-        session_queue_id: str,
-        session_queue_item_id: int,
-        session_queue_batch_id: str,
-        graph_execution_state: GraphExecutionState,
-        workflow: Optional[WorkflowWithoutID] = None,
-        invoke_all: bool = False,
-    ) -> Optional[str]:
-        """Determines the next node to invoke and enqueues it, preparing if needed.
-        Returns the id of the queued node, or `None` if there are no nodes left to enqueue."""
-
-        # Get the next invocation
-        invocation = graph_execution_state.next()
-        if not invocation:
-            return None
-
-        # Save the execution state
-        self.services.graph_execution_manager.set(graph_execution_state)
-
-        # Queue the invocation
-        self.services.queue.put(
-            InvocationQueueItem(
-                session_queue_id=session_queue_id,
-                session_queue_item_id=session_queue_item_id,
-                session_queue_batch_id=session_queue_batch_id,
-                graph_execution_state_id=graph_execution_state.id,
-                invocation_id=invocation.id,
-                workflow=workflow,
-                invoke_all=invoke_all,
-            )
-        )
-
-        return invocation.id
-
-    def create_execution_state(self, graph: Optional[Graph] = None) -> GraphExecutionState:
-        """Creates a new execution state for the given graph"""
-        new_state = GraphExecutionState(graph=Graph() if graph is None else graph)
-        self.services.graph_execution_manager.set(new_state)
-        return new_state
-
-    def cancel(self, graph_execution_state_id: str) -> None:
-        """Cancels the given execution state"""
-        self.services.queue.cancel(graph_execution_state_id)
-
     def __start_service(self, service) -> None:
         # Call start() method on any services that have it
         start_op = getattr(service, "start", None)
@@ -85,5 +35,3 @@ class Invoker:
         # First stop all services
         for service in vars(self.services):
             self.__stop_service(getattr(self.services, service))
-
-        self.services.queue.put(None)
diff --git a/invokeai/app/services/model_load/model_load_default.py b/invokeai/app/services/model_load/model_load_default.py
index 15c6283d8a..24ab10b427 100644
--- a/invokeai/app/services/model_load/model_load_default.py
+++ b/invokeai/app/services/model_load/model_load_default.py
@@ -4,7 +4,6 @@
 from typing import Optional, Type
 
 from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.app.services.invocation_processor.invocation_processor_common import CanceledException
 from invokeai.app.services.invoker import Invoker
 from invokeai.app.services.shared.invocation_context import InvocationContextData
 from invokeai.backend.model_manager import AnyModel, AnyModelConfig, SubModelType
@@ -95,8 +94,6 @@ class ModelLoadService(ModelLoadServiceBase):
     ) -> None:
         if not self._invoker:
             return
-        if self._invoker.services.queue.is_canceled(context_data.session_id):
-            raise CanceledException()
 
         if not loaded:
             self._invoker.services.events.emit_model_load_started(
diff --git a/invokeai/app/services/session_processor/session_processor_common.py b/invokeai/app/services/session_processor/session_processor_common.py
index 00195a773f..0ca51de517 100644
--- a/invokeai/app/services/session_processor/session_processor_common.py
+++ b/invokeai/app/services/session_processor/session_processor_common.py
@@ -4,3 +4,17 @@ from pydantic import BaseModel, Field
 class SessionProcessorStatus(BaseModel):
     is_started: bool = Field(description="Whether the session processor is started")
     is_processing: bool = Field(description="Whether a session is being processed")
+
+
+class CanceledException(Exception):
+    """Execution canceled by user."""
+
+    pass
+
+
+class ProgressImage(BaseModel):
+    """The progress image sent intermittently during processing"""
+
+    width: int = Field(description="The effective width of the image in pixels")
+    height: int = Field(description="The effective height of the image in pixels")
+    dataURL: str = Field(description="The image data as a b64 data URL")
diff --git a/invokeai/app/services/session_processor/session_processor_default.py b/invokeai/app/services/session_processor/session_processor_default.py
index 32e94a305d..dd34c78252 100644
--- a/invokeai/app/services/session_processor/session_processor_default.py
+++ b/invokeai/app/services/session_processor/session_processor_default.py
@@ -1,4 +1,5 @@
 import traceback
+from contextlib import suppress
 from threading import BoundedSemaphore, Thread
 from threading import Event as ThreadEvent
 from typing import Optional
@@ -7,7 +8,11 @@ from fastapi_events.handlers.local import local_handler
 from fastapi_events.typing import Event as FastAPIEvent
 
 from invokeai.app.services.events.events_base import EventServiceBase
+from invokeai.app.services.invocation_stats.invocation_stats_common import GESStatsNotFoundError
+from invokeai.app.services.session_processor.session_processor_common import CanceledException
 from invokeai.app.services.session_queue.session_queue_common import SessionQueueItem
+from invokeai.app.services.shared.invocation_context import InvocationContextData, build_invocation_context
+from invokeai.app.util.profiler import Profiler
 
 from ..invoker import Invoker
 from .session_processor_base import SessionProcessorBase
@@ -19,123 +24,237 @@ THREAD_LIMIT = 1
 
 class DefaultSessionProcessor(SessionProcessorBase):
     def start(self, invoker: Invoker) -> None:
-        self.__invoker: Invoker = invoker
-        self.__queue_item: Optional[SessionQueueItem] = None
+        self._invoker: Invoker = invoker
+        self._queue_item: Optional[SessionQueueItem] = None
 
-        self.__resume_event = ThreadEvent()
-        self.__stop_event = ThreadEvent()
-        self.__poll_now_event = ThreadEvent()
+        self._resume_event = ThreadEvent()
+        self._stop_event = ThreadEvent()
+        self._poll_now_event = ThreadEvent()
+        self._cancel_event = ThreadEvent()
 
         local_handler.register(event_name=EventServiceBase.queue_event, _func=self._on_queue_event)
 
-        self.__threadLimit = BoundedSemaphore(THREAD_LIMIT)
-        self.__thread = Thread(
+        self._thread_limit = BoundedSemaphore(THREAD_LIMIT)
+        self._thread = Thread(
             name="session_processor",
-            target=self.__process,
+            target=self._process,
             kwargs={
-                "stop_event": self.__stop_event,
-                "poll_now_event": self.__poll_now_event,
-                "resume_event": self.__resume_event,
+                "stop_event": self._stop_event,
+                "poll_now_event": self._poll_now_event,
+                "resume_event": self._resume_event,
+                "cancel_event": self._cancel_event,
             },
         )
-        self.__thread.start()
+        self._thread.start()
 
     def stop(self, *args, **kwargs) -> None:
-        self.__stop_event.set()
+        self._stop_event.set()
 
     def _poll_now(self) -> None:
-        self.__poll_now_event.set()
+        self._poll_now_event.set()
 
     async def _on_queue_event(self, event: FastAPIEvent) -> None:
         event_name = event[1]["event"]
 
-        # This was a match statement, but match is not supported on python 3.9
-        if event_name in [
-            "graph_execution_state_complete",
-            "invocation_error",
-            "session_retrieval_error",
-            "invocation_retrieval_error",
-        ]:
-            self.__queue_item = None
-            self._poll_now()
-        elif (
-            event_name == "session_canceled"
-            and self.__queue_item is not None
-            and self.__queue_item.session_id == event[1]["data"]["graph_execution_state_id"]
-        ):
-            self.__queue_item = None
+        if event_name == "session_canceled" or event_name == "queue_cleared":
+            # These both mean we should cancel the current session.
+            self._cancel_event.set()
             self._poll_now()
         elif event_name == "batch_enqueued":
             self._poll_now()
-        elif event_name == "queue_cleared":
-            self.__queue_item = None
-            self._poll_now()
 
     def resume(self) -> SessionProcessorStatus:
-        if not self.__resume_event.is_set():
-            self.__resume_event.set()
+        if not self._resume_event.is_set():
+            self._resume_event.set()
         return self.get_status()
 
     def pause(self) -> SessionProcessorStatus:
-        if self.__resume_event.is_set():
-            self.__resume_event.clear()
+        if self._resume_event.is_set():
+            self._resume_event.clear()
         return self.get_status()
 
     def get_status(self) -> SessionProcessorStatus:
         return SessionProcessorStatus(
-            is_started=self.__resume_event.is_set(),
-            is_processing=self.__queue_item is not None,
+            is_started=self._resume_event.is_set(),
+            is_processing=self._queue_item is not None,
         )
 
-    def __process(
+    def _process(
         self,
         stop_event: ThreadEvent,
         poll_now_event: ThreadEvent,
         resume_event: ThreadEvent,
+        cancel_event: ThreadEvent,
     ):
+        # Outermost processor try block; any unhandled exception is a fatal processor error
         try:
+            self._thread_limit.acquire()
             stop_event.clear()
             resume_event.set()
-            self.__threadLimit.acquire()
-            queue_item: Optional[SessionQueueItem] = None
+            cancel_event.clear()
+
+            # If profiling is enabled, create a profiler. The same profiler will be used for all sessions. Internally,
+            # the profiler will create a new profile for each session.
+            profiler = (
+                Profiler(
+                    logger=self._invoker.services.logger,
+                    output_dir=self._invoker.services.configuration.profiles_path,
+                    prefix=self._invoker.services.configuration.profile_prefix,
+                )
+                if self._invoker.services.configuration.profile_graphs
+                else None
+            )
+
+            # Helper function to stop the profiler and save the stats
+            def stats_cleanup(graph_execution_state_id: str) -> None:
+                if profiler:
+                    profile_path = profiler.stop()
+                    stats_path = profile_path.with_suffix(".json")
+                    self._invoker.services.performance_statistics.dump_stats(
+                        graph_execution_state_id=graph_execution_state_id, output_path=stats_path
+                    )
+                # We'll get a GESStatsNotFoundError if we try to log stats for an untracked graph, but in the processor
+                # we don't care about that - suppress the error.
+                with suppress(GESStatsNotFoundError):
+                    self._invoker.services.performance_statistics.log_stats(graph_execution_state_id)
+                    self._invoker.services.performance_statistics.reset_stats()
+
             while not stop_event.is_set():
                 poll_now_event.clear()
+                # Middle processor try block; any unhandled exception is a non-fatal processor error
                 try:
-                    # do not dequeue if there is already a session running
-                    if self.__queue_item is None and resume_event.is_set():
-                        queue_item = self.__invoker.services.session_queue.dequeue()
+                    # Get the next session to process
+                    self._queue_item = self._invoker.services.session_queue.dequeue()
+                    if self._queue_item is not None and resume_event.is_set():
+                        self._invoker.services.logger.debug(f"Executing queue item {self._queue_item.item_id}")
+                        cancel_event.clear()
 
-                        if queue_item is not None:
-                            self.__invoker.services.logger.debug(f"Executing queue item {queue_item.item_id}")
-                            self.__queue_item = queue_item
-                            self.__invoker.services.graph_execution_manager.set(queue_item.session)
-                            self.__invoker.invoke(
-                                session_queue_batch_id=queue_item.batch_id,
-                                session_queue_id=queue_item.queue_id,
-                                session_queue_item_id=queue_item.item_id,
-                                graph_execution_state=queue_item.session,
-                                workflow=queue_item.workflow,
-                                invoke_all=True,
+                        # If profiling is enabled, start the profiler
+                        if profiler is not None:
+                            profiler.start(profile_id=self._queue_item.session_id)
+
+                        # Prepare invocations and take the first
+                        invocation = self._queue_item.session.next()
+
+                        # Loop over invocations until the session is complete or canceled
+                        while invocation is not None and not cancel_event.is_set():
+                            # get the source node id to provide to clients (the prepared node id is not as useful)
+                            source_node_id = self._queue_item.session.prepared_source_mapping[invocation.id]
+
+                            # Send starting event
+                            self._invoker.services.events.emit_invocation_started(
+                                queue_batch_id=self._queue_item.batch_id,
+                                queue_item_id=self._queue_item.item_id,
+                                queue_id=self._queue_item.queue_id,
+                                graph_execution_state_id=self._queue_item.session_id,
+                                node=invocation.model_dump(),
+                                source_node_id=source_node_id,
                             )
-                            queue_item = None
 
-                    if queue_item is None:
-                        self.__invoker.services.logger.debug("Waiting for next polling interval or event")
+                            # Innermost processor try block; any unhandled exception is an invocation error & will fail the graph
+                            try:
+                                with self._invoker.services.performance_statistics.collect_stats(
+                                    invocation, self._queue_item.session.id
+                                ):
+                                    # Build invocation context (the node-facing API)
+                                    context_data = InvocationContextData(
+                                        invocation=invocation,
+                                        source_node_id=source_node_id,
+                                        session_id=self._queue_item.session.id,
+                                        workflow=self._queue_item.workflow,
+                                        queue_id=self._queue_item.queue_id,
+                                        queue_item_id=self._queue_item.item_id,
+                                        batch_id=self._queue_item.batch_id,
+                                    )
+                                    context = build_invocation_context(
+                                        context_data=context_data,
+                                        services=self._invoker.services,
+                                        cancel_event=self._cancel_event,
+                                    )
+
+                                    # Invoke the node
+                                    outputs = invocation.invoke_internal(
+                                        context=context, services=self._invoker.services
+                                    )
+
+                                    # Save outputs and history
+                                    self._queue_item.session.complete(invocation.id, outputs)
+
+                                    # Send complete event
+                                    self._invoker.services.events.emit_invocation_complete(
+                                        queue_batch_id=self._queue_item.batch_id,
+                                        queue_item_id=self._queue_item.item_id,
+                                        queue_id=self._queue_item.queue_id,
+                                        graph_execution_state_id=self._queue_item.session.id,
+                                        node=invocation.model_dump(),
+                                        source_node_id=source_node_id,
+                                        result=outputs.model_dump(),
+                                    )
+
+                            except KeyboardInterrupt:
+                                pass
+
+                            except CanceledException:
+                                pass
+
+                            except Exception as e:
+                                error = traceback.format_exc()
+
+                                # Save error
+                                self._queue_item.session.set_node_error(invocation.id, error)
+                                self._invoker.services.logger.error("Error while invoking:\n%s" % e)
+
+                                # Send error event
+                                self._invoker.services.events.emit_invocation_error(
+                                    queue_batch_id=self._queue_item.session_id,
+                                    queue_item_id=self._queue_item.item_id,
+                                    queue_id=self._queue_item.queue_id,
+                                    graph_execution_state_id=self._queue_item.session.id,
+                                    node=invocation.model_dump(),
+                                    source_node_id=source_node_id,
+                                    error_type=e.__class__.__name__,
+                                    error=error,
+                                )
+                                pass
+
+                            if self._queue_item.session.is_complete() or cancel_event.is_set():
+                                # Send complete event
+                                self._invoker.services.events.emit_graph_execution_complete(
+                                    queue_batch_id=self._queue_item.batch_id,
+                                    queue_item_id=self._queue_item.item_id,
+                                    queue_id=self._queue_item.queue_id,
+                                    graph_execution_state_id=self._queue_item.session.id,
+                                )
+                                # Save the stats and stop the profiler if it's running
+                                stats_cleanup(self._queue_item.session.id)
+                                invocation = None
+                            else:
+                                # Prepare the next invocation
+                                invocation = self._queue_item.session.next()
+
+                        # The session is complete, immediately poll for next session
+                        self._queue_item = None
+                        poll_now_event.set()
+                    else:
+                        # The queue was empty, wait for next polling interval or event to try again
+                        self._invoker.services.logger.debug("Waiting for next polling interval or event")
                         poll_now_event.wait(POLLING_INTERVAL)
                         continue
                 except Exception as e:
-                    self.__invoker.services.logger.error(f"Error in session processor: {e}")
-                    if queue_item is not None:
-                        self.__invoker.services.session_queue.cancel_queue_item(
-                            queue_item.item_id, error=traceback.format_exc()
+                    # Non-fatal error in processor, cancel the queue item and wait for next polling interval or event
+                    self._invoker.services.logger.error(f"Error in session processor: {e}")
+                    if self._queue_item is not None:
+                        self._invoker.services.session_queue.cancel_queue_item(
+                            self._queue_item.item_id, error=traceback.format_exc()
                         )
                     poll_now_event.wait(POLLING_INTERVAL)
                     continue
         except Exception as e:
-            self.__invoker.services.logger.error(f"Fatal Error in session processor: {e}")
+            # Fatal error in processor, log and pass - we're done here
+            self._invoker.services.logger.error(f"Fatal Error in session processor: {e}")
             pass
         finally:
             stop_event.clear()
             poll_now_event.clear()
-            self.__queue_item = None
-            self.__threadLimit.release()
+            self._queue_item = None
+            self._thread_limit.release()
diff --git a/invokeai/app/services/session_queue/session_queue_sqlite.py b/invokeai/app/services/session_queue/session_queue_sqlite.py
index 64642690e9..7af9f0e08c 100644
--- a/invokeai/app/services/session_queue/session_queue_sqlite.py
+++ b/invokeai/app/services/session_queue/session_queue_sqlite.py
@@ -60,7 +60,7 @@ class SqliteSessionQueue(SessionQueueBase):
         # This was a match statement, but match is not supported on python 3.9
         if event_name == "graph_execution_state_complete":
             await self._handle_complete_event(event)
-        elif event_name in ["invocation_error", "session_retrieval_error", "invocation_retrieval_error"]:
+        elif event_name == "invocation_error":
             await self._handle_error_event(event)
         elif event_name == "session_canceled":
             await self._handle_cancel_event(event)
@@ -429,7 +429,6 @@ class SqliteSessionQueue(SessionQueueBase):
         if queue_item.status not in ["canceled", "failed", "completed"]:
             status = "failed" if error is not None else "canceled"
             queue_item = self._set_queue_item_status(item_id=item_id, status=status, error=error)  # type: ignore [arg-type] # mypy seems to not narrow the Literals here
-            self.__invoker.services.queue.cancel(queue_item.session_id)
             self.__invoker.services.events.emit_session_canceled(
                 queue_item_id=queue_item.item_id,
                 queue_id=queue_item.queue_id,
@@ -471,7 +470,6 @@ class SqliteSessionQueue(SessionQueueBase):
             )
             self.__conn.commit()
             if current_queue_item is not None and current_queue_item.batch_id in batch_ids:
-                self.__invoker.services.queue.cancel(current_queue_item.session_id)
                 self.__invoker.services.events.emit_session_canceled(
                     queue_item_id=current_queue_item.item_id,
                     queue_id=current_queue_item.queue_id,
@@ -523,7 +521,6 @@ class SqliteSessionQueue(SessionQueueBase):
             )
             self.__conn.commit()
             if current_queue_item is not None and current_queue_item.queue_id == queue_id:
-                self.__invoker.services.queue.cancel(current_queue_item.session_id)
                 self.__invoker.services.events.emit_session_canceled(
                     queue_item_id=current_queue_item.item_id,
                     queue_id=current_queue_item.queue_id,
diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index 43ecb2c543..4606bd9e03 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -1,6 +1,7 @@
+import threading
 from dataclasses import dataclass
 from pathlib import Path
-from typing import TYPE_CHECKING, Optional
+from typing import TYPE_CHECKING, Callable, Optional
 
 from PIL.Image import Image
 from torch import Tensor
@@ -370,6 +371,12 @@ class ConfigInterface(InvocationContextInterface):
 
 
 class UtilInterface(InvocationContextInterface):
+    def __init__(
+        self, services: InvocationServices, context_data: InvocationContextData, is_canceled: Callable[[], bool]
+    ) -> None:
+        super().__init__(services, context_data)
+        self._is_canceled = is_canceled
+
     def sd_step_callback(self, intermediate_state: PipelineIntermediateState, base_model: BaseModelType) -> None:
         """
         The step callback emits a progress event with the current step, the total number of
@@ -390,8 +397,8 @@ class UtilInterface(InvocationContextInterface):
             context_data=self._context_data,
             intermediate_state=intermediate_state,
             base_model=base_model,
-            invocation_queue=self._services.queue,
             events=self._services.events,
+            is_canceled=self._is_canceled,
         )
 
 
@@ -412,6 +419,7 @@ class InvocationContext:
         boards: BoardsInterface,
         context_data: InvocationContextData,
         services: InvocationServices,
+        is_canceled: Callable[[], bool],
     ) -> None:
         self.images = images
         """Provides methods to save, get and update images and their metadata."""
@@ -433,11 +441,13 @@ class InvocationContext:
         """Provides data about the current queue item and invocation. This is an internal API and may change without warning."""
         self._services = services
         """Provides access to the full application services. This is an internal API and may change without warning."""
+        self._is_canceled = is_canceled
 
 
 def build_invocation_context(
     services: InvocationServices,
     context_data: InvocationContextData,
+    cancel_event: threading.Event,
 ) -> InvocationContext:
     """
     Builds the invocation context for a specific invocation execution.
@@ -446,12 +456,15 @@ def build_invocation_context(
     :param invocation_context_data: The invocation context data.
     """
 
+    def is_canceled() -> bool:
+        return cancel_event.is_set()
+
     logger = LoggerInterface(services=services, context_data=context_data)
     images = ImagesInterface(services=services, context_data=context_data)
     tensors = TensorsInterface(services=services, context_data=context_data)
     models = ModelsInterface(services=services, context_data=context_data)
     config = ConfigInterface(services=services, context_data=context_data)
-    util = UtilInterface(services=services, context_data=context_data)
+    util = UtilInterface(services=services, context_data=context_data, is_canceled=is_canceled)
     conditioning = ConditioningInterface(services=services, context_data=context_data)
     boards = BoardsInterface(services=services, context_data=context_data)
 
@@ -466,6 +479,7 @@ def build_invocation_context(
         conditioning=conditioning,
         services=services,
         boards=boards,
+        is_canceled=is_canceled,
     )
 
     return ctx
diff --git a/invokeai/app/util/step_callback.py b/invokeai/app/util/step_callback.py
index 33d00ca366..9c9f5254a4 100644
--- a/invokeai/app/util/step_callback.py
+++ b/invokeai/app/util/step_callback.py
@@ -1,9 +1,9 @@
-from typing import TYPE_CHECKING
+from typing import TYPE_CHECKING, Callable
 
 import torch
 from PIL import Image
 
-from invokeai.app.services.invocation_processor.invocation_processor_common import CanceledException, ProgressImage
+from invokeai.app.services.session_processor.session_processor_common import CanceledException, ProgressImage
 from invokeai.backend.model_manager.config import BaseModelType
 
 from ...backend.stable_diffusion import PipelineIntermediateState
@@ -11,7 +11,6 @@ from ...backend.util.util import image_to_dataURL
 
 if TYPE_CHECKING:
     from invokeai.app.services.events.events_base import EventServiceBase
-    from invokeai.app.services.invocation_queue.invocation_queue_base import InvocationQueueABC
     from invokeai.app.services.shared.invocation_context import InvocationContextData
 
 
@@ -34,10 +33,10 @@ def stable_diffusion_step_callback(
     context_data: "InvocationContextData",
     intermediate_state: PipelineIntermediateState,
     base_model: BaseModelType,
-    invocation_queue: "InvocationQueueABC",
     events: "EventServiceBase",
+    is_canceled: Callable[[], bool],
 ) -> None:
-    if invocation_queue.is_canceled(context_data.session_id):
+    if is_canceled():
         raise CanceledException
 
     # Some schedulers report not only the noisy latents at the current timestep,

From 317d076a1acb67d3602f573b7c9c99c9791e70b1 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sun, 18 Feb 2024 11:25:00 +1100
Subject: [PATCH 165/411] feat(nodes): promote `is_canceled` to public node API

---
 invokeai/app/services/shared/invocation_context.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index 4606bd9e03..317cbdbb23 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -437,11 +437,12 @@ class InvocationContext:
         """Provides utility methods."""
         self.boards = boards
         """Provides methods to interact with boards."""
+        self.is_canceled = is_canceled
+        """Checks if the current invocation has been canceled."""
         self._data = context_data
         """Provides data about the current queue item and invocation. This is an internal API and may change without warning."""
         self._services = services
         """Provides access to the full application services. This is an internal API and may change without warning."""
-        self._is_canceled = is_canceled
 
 
 def build_invocation_context(
@@ -457,6 +458,7 @@ def build_invocation_context(
     """
 
     def is_canceled() -> bool:
+        """Checks if the current invocation has been canceled."""
         return cancel_event.is_set()
 
     logger = LoggerInterface(services=services, context_data=context_data)

From 0788b6eceefcdaf44012abfcd9944c624f685615 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sun, 18 Feb 2024 11:42:40 +1100
Subject: [PATCH 166/411] chore(nodes): add comments for cancel state

---
 .../session_processor/session_processor_default.py    | 11 +++++++++++
 1 file changed, 11 insertions(+)

diff --git a/invokeai/app/services/session_processor/session_processor_default.py b/invokeai/app/services/session_processor/session_processor_default.py
index dd34c78252..2ff76c06e4 100644
--- a/invokeai/app/services/session_processor/session_processor_default.py
+++ b/invokeai/app/services/session_processor/session_processor_default.py
@@ -192,9 +192,20 @@ class DefaultSessionProcessor(SessionProcessorBase):
                                     )
 
                             except KeyboardInterrupt:
+                                # TODO(psyche): should we set the cancel event here and/or cancel the queue item?
                                 pass
 
                             except CanceledException:
+                                # When the user cancels the graph, we first set the cancel event. The event is checked
+                                # between invocations, in this loop. Some invocations are long-running, and we need to
+                                # be able to cancel them mid-execution.
+                                #
+                                # For example, denoising is a long-running invocation with many steps. A step callback
+                                # is executed after each step. This step callback checks if the canceled event is set,
+                                # then raises a CanceledException to stop execution immediately.
+                                #
+                                # When we get a CanceledException, we don't need to do anything - just pass and let the
+                                # loop go to its next iteration, and the cancel event will be handled correctly.
                                 pass
 
                             except Exception as e:

From 3cfac8b843fd37acb49bf7680b1cb3307422f0f4 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sun, 18 Feb 2024 11:42:53 +1100
Subject: [PATCH 167/411] feat(nodes): better invocation error messages

---
 .../services/session_processor/session_processor_default.py   | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/invokeai/app/services/session_processor/session_processor_default.py b/invokeai/app/services/session_processor/session_processor_default.py
index 2ff76c06e4..f235544405 100644
--- a/invokeai/app/services/session_processor/session_processor_default.py
+++ b/invokeai/app/services/session_processor/session_processor_default.py
@@ -213,7 +213,9 @@ class DefaultSessionProcessor(SessionProcessorBase):
 
                                 # Save error
                                 self._queue_item.session.set_node_error(invocation.id, error)
-                                self._invoker.services.logger.error("Error while invoking:\n%s" % e)
+                                self._invoker.services.logger.error(
+                                    f"Error while invoking session {self._queue_item.session_id}, invocation {invocation.id} ({invocation.get_type()}):\n{e}"
+                                )
 
                                 # Send error event
                                 self._invoker.services.events.emit_invocation_error(

From 86c50f2d5b3c15eac98fa8acfcba4d897aeda194 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sun, 18 Feb 2024 11:44:08 +1100
Subject: [PATCH 168/411] tidy(nodes): remove extraneous comments

---
 invokeai/app/services/shared/invocation_context.py | 6 ------
 1 file changed, 6 deletions(-)

diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index 317cbdbb23..6b6379dc5d 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -388,11 +388,6 @@ class UtilInterface(InvocationContextInterface):
         :param base_model: The base model for the current denoising step.
         """
 
-        # The step callback needs access to the events and the invocation queue services, but this
-        # represents a dangerous level of access.
-        #
-        # We wrap the step callback so that nodes do not have direct access to these services.
-
         stable_diffusion_step_callback(
             context_data=self._context_data,
             intermediate_state=intermediate_state,
@@ -458,7 +453,6 @@ def build_invocation_context(
     """
 
     def is_canceled() -> bool:
-        """Checks if the current invocation has been canceled."""
         return cancel_event.is_set()
 
     logger = LoggerInterface(services=services, context_data=context_data)

From 18adcc1dd26804e5b6e73a5b19fcbd25d81bf52e Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sun, 18 Feb 2024 11:51:50 +1100
Subject: [PATCH 169/411] feat(nodes): add whole queue_item to
 InvocationContextData

No reason to not have the whole thing in there.
---
 .../session_processor_default.py              | 16 +++++---------
 .../app/services/shared/invocation_context.py | 22 ++++++-------------
 invokeai/app/util/step_callback.py            | 10 ++++-----
 3 files changed, 18 insertions(+), 30 deletions(-)

diff --git a/invokeai/app/services/session_processor/session_processor_default.py b/invokeai/app/services/session_processor/session_processor_default.py
index f235544405..e49f79bcf3 100644
--- a/invokeai/app/services/session_processor/session_processor_default.py
+++ b/invokeai/app/services/session_processor/session_processor_default.py
@@ -139,7 +139,7 @@ class DefaultSessionProcessor(SessionProcessorBase):
                         # Loop over invocations until the session is complete or canceled
                         while invocation is not None and not cancel_event.is_set():
                             # get the source node id to provide to clients (the prepared node id is not as useful)
-                            source_node_id = self._queue_item.session.prepared_source_mapping[invocation.id]
+                            source_invocation_id = self._queue_item.session.prepared_source_mapping[invocation.id]
 
                             # Send starting event
                             self._invoker.services.events.emit_invocation_started(
@@ -148,7 +148,7 @@ class DefaultSessionProcessor(SessionProcessorBase):
                                 queue_id=self._queue_item.queue_id,
                                 graph_execution_state_id=self._queue_item.session_id,
                                 node=invocation.model_dump(),
-                                source_node_id=source_node_id,
+                                source_node_id=source_invocation_id,
                             )
 
                             # Innermost processor try block; any unhandled exception is an invocation error & will fail the graph
@@ -159,12 +159,8 @@ class DefaultSessionProcessor(SessionProcessorBase):
                                     # Build invocation context (the node-facing API)
                                     context_data = InvocationContextData(
                                         invocation=invocation,
-                                        source_node_id=source_node_id,
-                                        session_id=self._queue_item.session.id,
-                                        workflow=self._queue_item.workflow,
-                                        queue_id=self._queue_item.queue_id,
-                                        queue_item_id=self._queue_item.item_id,
-                                        batch_id=self._queue_item.batch_id,
+                                        source_invocation_id=source_invocation_id,
+                                        queue_item=self._queue_item,
                                     )
                                     context = build_invocation_context(
                                         context_data=context_data,
@@ -187,7 +183,7 @@ class DefaultSessionProcessor(SessionProcessorBase):
                                         queue_id=self._queue_item.queue_id,
                                         graph_execution_state_id=self._queue_item.session.id,
                                         node=invocation.model_dump(),
-                                        source_node_id=source_node_id,
+                                        source_node_id=source_invocation_id,
                                         result=outputs.model_dump(),
                                     )
 
@@ -224,7 +220,7 @@ class DefaultSessionProcessor(SessionProcessorBase):
                                     queue_id=self._queue_item.queue_id,
                                     graph_execution_state_id=self._queue_item.session.id,
                                     node=invocation.model_dump(),
-                                    source_node_id=source_node_id,
+                                    source_node_id=source_invocation_id,
                                     error_type=e.__class__.__name__,
                                     error=error,
                                 )
diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index 6b6379dc5d..6b314d10bf 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -13,7 +13,6 @@ from invokeai.app.services.config.config_default import InvokeAIAppConfig
 from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
 from invokeai.app.services.images.images_common import ImageDTO
 from invokeai.app.services.invocation_services import InvocationServices
-from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID
 from invokeai.app.util.step_callback import stable_diffusion_step_callback
 from invokeai.backend.model_manager.config import AnyModelConfig, BaseModelType, ModelFormat, ModelType, SubModelType
 from invokeai.backend.model_manager.load.load_base import LoadedModel
@@ -23,6 +22,7 @@ from invokeai.backend.stable_diffusion.diffusion.conditioning_data import Condit
 
 if TYPE_CHECKING:
     from invokeai.app.invocations.baseinvocation import BaseInvocation
+    from invokeai.app.services.session_queue.session_queue_common import SessionQueueItem
 
 """
 The InvocationContext provides access to various services and data about the current invocation.
@@ -49,20 +49,12 @@ Note: The docstrings are in weird places, but that's where they must be to get I
 
 @dataclass
 class InvocationContextData:
+    queue_item: "SessionQueueItem"
+    """The queue item that is being executed."""
     invocation: "BaseInvocation"
     """The invocation that is being executed."""
-    session_id: str
-    """The session that is being executed."""
-    queue_id: str
-    """The queue in which the session is being executed."""
-    source_node_id: str
-    """The ID of the node from which the currently executing invocation was prepared."""
-    queue_item_id: int
-    """The ID of the queue item that is being executed."""
-    batch_id: str
-    """The ID of the batch that is being executed."""
-    workflow: Optional[WorkflowWithoutID] = None
-    """The workflow associated with this queue item, if any."""
+    source_invocation_id: str
+    """The ID of the invocation from which the currently executing invocation was prepared."""
 
 
 class InvocationContextInterface:
@@ -191,8 +183,8 @@ class ImagesInterface(InvocationContextInterface):
             board_id=board_id_,
             metadata=metadata_,
             image_origin=ResourceOrigin.INTERNAL,
-            workflow=self._context_data.workflow,
-            session_id=self._context_data.session_id,
+            workflow=self._context_data.queue_item.workflow,
+            session_id=self._context_data.queue_item.session_id,
             node_id=self._context_data.invocation.id,
         )
 
diff --git a/invokeai/app/util/step_callback.py b/invokeai/app/util/step_callback.py
index 9c9f5254a4..8cb59f5b3a 100644
--- a/invokeai/app/util/step_callback.py
+++ b/invokeai/app/util/step_callback.py
@@ -114,12 +114,12 @@ def stable_diffusion_step_callback(
     dataURL = image_to_dataURL(image, image_format="JPEG")
 
     events.emit_generator_progress(
-        queue_id=context_data.queue_id,
-        queue_item_id=context_data.queue_item_id,
-        queue_batch_id=context_data.batch_id,
-        graph_execution_state_id=context_data.session_id,
+        queue_id=context_data.queue_item.queue_id,
+        queue_item_id=context_data.queue_item.item_id,
+        queue_batch_id=context_data.queue_item.batch_id,
+        graph_execution_state_id=context_data.queue_item.session_id,
         node_id=context_data.invocation.id,
-        source_node_id=context_data.source_node_id,
+        source_node_id=context_data.source_invocation_id,
         progress_image=ProgressImage(width=width, height=height, dataURL=dataURL),
         step=intermediate_state.step,
         order=intermediate_state.order,

From fdac0c3c9ba9dbd52534f8caa1b1492640cf6a5c Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sun, 18 Feb 2024 11:54:16 +1100
Subject: [PATCH 170/411] refactor(nodes): move is_canceled to `context.util`

---
 .../app/services/shared/invocation_context.py | 21 ++++++++-----------
 1 file changed, 9 insertions(+), 12 deletions(-)

diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index 6b314d10bf..994c99dc45 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -1,7 +1,7 @@
 import threading
 from dataclasses import dataclass
 from pathlib import Path
-from typing import TYPE_CHECKING, Callable, Optional
+from typing import TYPE_CHECKING, Optional
 
 from PIL.Image import Image
 from torch import Tensor
@@ -364,10 +364,14 @@ class ConfigInterface(InvocationContextInterface):
 
 class UtilInterface(InvocationContextInterface):
     def __init__(
-        self, services: InvocationServices, context_data: InvocationContextData, is_canceled: Callable[[], bool]
+        self, services: InvocationServices, context_data: InvocationContextData, cancel_event: threading.Event
     ) -> None:
         super().__init__(services, context_data)
-        self._is_canceled = is_canceled
+        self._cancel_event = cancel_event
+
+    def is_canceled(self) -> bool:
+        """Checks if the current invocation has been canceled."""
+        return self._cancel_event.is_set()
 
     def sd_step_callback(self, intermediate_state: PipelineIntermediateState, base_model: BaseModelType) -> None:
         """
@@ -385,7 +389,7 @@ class UtilInterface(InvocationContextInterface):
             intermediate_state=intermediate_state,
             base_model=base_model,
             events=self._services.events,
-            is_canceled=self._is_canceled,
+            is_canceled=self.is_canceled,
         )
 
 
@@ -406,7 +410,6 @@ class InvocationContext:
         boards: BoardsInterface,
         context_data: InvocationContextData,
         services: InvocationServices,
-        is_canceled: Callable[[], bool],
     ) -> None:
         self.images = images
         """Provides methods to save, get and update images and their metadata."""
@@ -424,8 +427,6 @@ class InvocationContext:
         """Provides utility methods."""
         self.boards = boards
         """Provides methods to interact with boards."""
-        self.is_canceled = is_canceled
-        """Checks if the current invocation has been canceled."""
         self._data = context_data
         """Provides data about the current queue item and invocation. This is an internal API and may change without warning."""
         self._services = services
@@ -444,15 +445,12 @@ def build_invocation_context(
     :param invocation_context_data: The invocation context data.
     """
 
-    def is_canceled() -> bool:
-        return cancel_event.is_set()
-
     logger = LoggerInterface(services=services, context_data=context_data)
     images = ImagesInterface(services=services, context_data=context_data)
     tensors = TensorsInterface(services=services, context_data=context_data)
     models = ModelsInterface(services=services, context_data=context_data)
     config = ConfigInterface(services=services, context_data=context_data)
-    util = UtilInterface(services=services, context_data=context_data, is_canceled=is_canceled)
+    util = UtilInterface(services=services, context_data=context_data, cancel_event=cancel_event)
     conditioning = ConditioningInterface(services=services, context_data=context_data)
     boards = BoardsInterface(services=services, context_data=context_data)
 
@@ -467,7 +465,6 @@ def build_invocation_context(
         conditioning=conditioning,
         services=services,
         boards=boards,
-        is_canceled=is_canceled,
     )
 
     return ctx

From ccfe6b6befabeabe6e5956639448c96167eab5f1 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sun, 18 Feb 2024 11:56:54 +1100
Subject: [PATCH 171/411] chore(nodes): "context_data" -> "data"

Changed within InvocationContext, for brevity.
---
 .../session_processor_default.py              |  4 +-
 .../app/services/shared/invocation_context.py | 54 +++++++++----------
 tests/test_graph_execution_state.py           |  2 +-
 3 files changed, 30 insertions(+), 30 deletions(-)

diff --git a/invokeai/app/services/session_processor/session_processor_default.py b/invokeai/app/services/session_processor/session_processor_default.py
index e49f79bcf3..dc08fc8345 100644
--- a/invokeai/app/services/session_processor/session_processor_default.py
+++ b/invokeai/app/services/session_processor/session_processor_default.py
@@ -157,13 +157,13 @@ class DefaultSessionProcessor(SessionProcessorBase):
                                     invocation, self._queue_item.session.id
                                 ):
                                     # Build invocation context (the node-facing API)
-                                    context_data = InvocationContextData(
+                                    data = InvocationContextData(
                                         invocation=invocation,
                                         source_invocation_id=source_invocation_id,
                                         queue_item=self._queue_item,
                                     )
                                     context = build_invocation_context(
-                                        context_data=context_data,
+                                        data=data,
                                         services=self._invoker.services,
                                         cancel_event=self._cancel_event,
                                     )
diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index 994c99dc45..f8425523bf 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -58,9 +58,9 @@ class InvocationContextData:
 
 
 class InvocationContextInterface:
-    def __init__(self, services: InvocationServices, context_data: InvocationContextData) -> None:
+    def __init__(self, services: InvocationServices, data: InvocationContextData) -> None:
         self._services = services
-        self._context_data = context_data
+        self._data = data
 
 
 class BoardsInterface(InvocationContextInterface):
@@ -166,26 +166,26 @@ class ImagesInterface(InvocationContextInterface):
         metadata_ = None
         if metadata:
             metadata_ = metadata
-        elif isinstance(self._context_data.invocation, WithMetadata):
-            metadata_ = self._context_data.invocation.metadata
+        elif isinstance(self._data.invocation, WithMetadata):
+            metadata_ = self._data.invocation.metadata
 
         # If `board_id` is provided directly, use that. Else, use the board provided by `WithBoard`, falling back to None.
         board_id_ = None
         if board_id:
             board_id_ = board_id
-        elif isinstance(self._context_data.invocation, WithBoard) and self._context_data.invocation.board:
-            board_id_ = self._context_data.invocation.board.board_id
+        elif isinstance(self._data.invocation, WithBoard) and self._data.invocation.board:
+            board_id_ = self._data.invocation.board.board_id
 
         return self._services.images.create(
             image=image,
-            is_intermediate=self._context_data.invocation.is_intermediate,
+            is_intermediate=self._data.invocation.is_intermediate,
             image_category=image_category,
             board_id=board_id_,
             metadata=metadata_,
             image_origin=ResourceOrigin.INTERNAL,
-            workflow=self._context_data.queue_item.workflow,
-            session_id=self._context_data.queue_item.session_id,
-            node_id=self._context_data.invocation.id,
+            workflow=self._data.queue_item.workflow,
+            session_id=self._data.queue_item.session_id,
+            node_id=self._data.invocation.id,
         )
 
     def get_pil(self, image_name: str, mode: IMAGE_MODES | None = None) -> Image:
@@ -285,7 +285,7 @@ class ModelsInterface(InvocationContextInterface):
         # the event payloads.
 
         return self._services.model_manager.load_model_by_key(
-            key=key, submodel_type=submodel_type, context_data=self._context_data
+            key=key, submodel_type=submodel_type, context_data=self._data
         )
 
     def load_by_attrs(
@@ -304,7 +304,7 @@ class ModelsInterface(InvocationContextInterface):
             base_model=base_model,
             model_type=model_type,
             submodel=submodel,
-            context_data=self._context_data,
+            context_data=self._data,
         )
 
     def get_config(self, key: str) -> AnyModelConfig:
@@ -364,9 +364,9 @@ class ConfigInterface(InvocationContextInterface):
 
 class UtilInterface(InvocationContextInterface):
     def __init__(
-        self, services: InvocationServices, context_data: InvocationContextData, cancel_event: threading.Event
+        self, services: InvocationServices, data: InvocationContextData, cancel_event: threading.Event
     ) -> None:
-        super().__init__(services, context_data)
+        super().__init__(services, data)
         self._cancel_event = cancel_event
 
     def is_canceled(self) -> bool:
@@ -385,7 +385,7 @@ class UtilInterface(InvocationContextInterface):
         """
 
         stable_diffusion_step_callback(
-            context_data=self._context_data,
+            context_data=self._data,
             intermediate_state=intermediate_state,
             base_model=base_model,
             events=self._services.events,
@@ -408,7 +408,7 @@ class InvocationContext:
         config: ConfigInterface,
         util: UtilInterface,
         boards: BoardsInterface,
-        context_data: InvocationContextData,
+        data: InvocationContextData,
         services: InvocationServices,
     ) -> None:
         self.images = images
@@ -427,7 +427,7 @@ class InvocationContext:
         """Provides utility methods."""
         self.boards = boards
         """Provides methods to interact with boards."""
-        self._data = context_data
+        self._data = data
         """Provides data about the current queue item and invocation. This is an internal API and may change without warning."""
         self._services = services
         """Provides access to the full application services. This is an internal API and may change without warning."""
@@ -435,7 +435,7 @@ class InvocationContext:
 
 def build_invocation_context(
     services: InvocationServices,
-    context_data: InvocationContextData,
+    data: InvocationContextData,
     cancel_event: threading.Event,
 ) -> InvocationContext:
     """
@@ -445,14 +445,14 @@ def build_invocation_context(
     :param invocation_context_data: The invocation context data.
     """
 
-    logger = LoggerInterface(services=services, context_data=context_data)
-    images = ImagesInterface(services=services, context_data=context_data)
-    tensors = TensorsInterface(services=services, context_data=context_data)
-    models = ModelsInterface(services=services, context_data=context_data)
-    config = ConfigInterface(services=services, context_data=context_data)
-    util = UtilInterface(services=services, context_data=context_data, cancel_event=cancel_event)
-    conditioning = ConditioningInterface(services=services, context_data=context_data)
-    boards = BoardsInterface(services=services, context_data=context_data)
+    logger = LoggerInterface(services=services, data=data)
+    images = ImagesInterface(services=services, data=data)
+    tensors = TensorsInterface(services=services, data=data)
+    models = ModelsInterface(services=services, data=data)
+    config = ConfigInterface(services=services, data=data)
+    util = UtilInterface(services=services, data=data, cancel_event=cancel_event)
+    conditioning = ConditioningInterface(services=services, data=data)
+    boards = BoardsInterface(services=services, data=data)
 
     ctx = InvocationContext(
         images=images,
@@ -460,7 +460,7 @@ def build_invocation_context(
         config=config,
         tensors=tensors,
         models=models,
-        context_data=context_data,
+        data=data,
         util=util,
         conditioning=conditioning,
         services=services,
diff --git a/tests/test_graph_execution_state.py b/tests/test_graph_execution_state.py
index f839a4a878..9cff502acf 100644
--- a/tests/test_graph_execution_state.py
+++ b/tests/test_graph_execution_state.py
@@ -86,7 +86,7 @@ def invoke_next(g: GraphExecutionState, services: InvocationServices) -> tuple[B
         InvocationContext(
             conditioning=None,
             config=None,
-            context_data=None,
+            data=None,
             images=None,
             tensors=None,
             logger=None,

From d53a2a2d4eb7b21d6c84f80b484407da4ee67ff9 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sun, 18 Feb 2024 12:03:43 +1100
Subject: [PATCH 172/411] chore(nodes): better comments for invocation context

---
 .../app/services/shared/invocation_context.py | 26 +++++++++----------
 1 file changed, 13 insertions(+), 13 deletions(-)

diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index f8425523bf..31064a5e7c 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -247,7 +247,7 @@ class ConditioningInterface(InvocationContextInterface):
         """
         Saves a conditioning data object, returning its name.
 
-        :param conditioning_context_data: The conditioning data to save.
+        :param conditioning_data: The conditioning data to save.
         """
 
         name = self._services.conditioning.save(obj=conditioning_data)
@@ -412,25 +412,25 @@ class InvocationContext:
         services: InvocationServices,
     ) -> None:
         self.images = images
-        """Provides methods to save, get and update images and their metadata."""
+        """Methods to save, get and update images and their metadata."""
         self.tensors = tensors
-        """Provides methods to save and get tensors, including image, noise, masks, and masked images."""
+        """Methods to save and get tensors, including image, noise, masks, and masked images."""
         self.conditioning = conditioning
-        """Provides methods to save and get conditioning data."""
+        """Methods to save and get conditioning data."""
         self.models = models
-        """Provides methods to check if a model exists, get a model, and get a model's info."""
+        """Methods to check if a model exists, get a model, and get a model's info."""
         self.logger = logger
-        """Provides access to the app logger."""
+        """The app logger."""
         self.config = config
-        """Provides access to the app's config."""
+        """The app config."""
         self.util = util
-        """Provides utility methods."""
+        """Utility methods, including a method to check if an invocation was canceled and step callbacks."""
         self.boards = boards
-        """Provides methods to interact with boards."""
+        """Methods to interact with boards."""
         self._data = data
-        """Provides data about the current queue item and invocation. This is an internal API and may change without warning."""
+        """An internal API providing access to data about the current queue item and invocation. You probably shouldn't use this. It may change without warning."""
         self._services = services
-        """Provides access to the full application services. This is an internal API and may change without warning."""
+        """An internal API providing access to all application services. You probably shouldn't use this. It may change without warning."""
 
 
 def build_invocation_context(
@@ -441,8 +441,8 @@ def build_invocation_context(
     """
     Builds the invocation context for a specific invocation execution.
 
-    :param invocation_services: The invocation services to wrap.
-    :param invocation_context_data: The invocation context data.
+    :param services: The invocation services to wrap.
+    :param data: The invocation context data.
     """
 
     logger = LoggerInterface(services=services, data=data)

From 0788a27a8042fd73cbff2dca435bd52a327e0cb6 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sun, 18 Feb 2024 12:29:08 +1100
Subject: [PATCH 173/411] tests(nodes): fix tests following removal of services

---
 tests/test_graph_execution_state.py |  89 ++++++---------
 tests/test_invoker.py               | 163 ----------------------------
 2 files changed, 35 insertions(+), 217 deletions(-)
 delete mode 100644 tests/test_invoker.py

diff --git a/tests/test_graph_execution_state.py b/tests/test_graph_execution_state.py
index 9cff502acf..2e88178424 100644
--- a/tests/test_graph_execution_state.py
+++ b/tests/test_graph_execution_state.py
@@ -1,9 +1,9 @@
 import logging
+from typing import Optional
+from unittest.mock import Mock
 
 import pytest
 
-from invokeai.app.services.item_storage.item_storage_memory import ItemStorageMemory
-
 # This import must happen before other invoke imports or test in other files(!!) break
 from .test_nodes import (  # isort: split
     PromptCollectionTestInvocation,
@@ -17,8 +17,6 @@ from invokeai.app.invocations.collections import RangeInvocation
 from invokeai.app.invocations.math import AddInvocation, MultiplyInvocation
 from invokeai.app.services.config.config_default import InvokeAIAppConfig
 from invokeai.app.services.invocation_cache.invocation_cache_memory import MemoryInvocationCache
-from invokeai.app.services.invocation_processor.invocation_processor_default import DefaultInvocationProcessor
-from invokeai.app.services.invocation_queue.invocation_queue_memory import MemoryInvocationQueue
 from invokeai.app.services.invocation_services import InvocationServices
 from invokeai.app.services.invocation_stats.invocation_stats_default import InvocationStatsService
 from invokeai.app.services.shared.graph import (
@@ -28,11 +26,11 @@ from invokeai.app.services.shared.graph import (
     IterateInvocation,
 )
 
-from .test_invoker import create_edge
+from .test_nodes import create_edge
 
 
 @pytest.fixture
-def simple_graph():
+def simple_graph() -> Graph:
     g = Graph()
     g.add_node(PromptTestInvocation(id="1", prompt="Banana sushi"))
     g.add_node(TextToImageTestInvocation(id="2"))
@@ -47,7 +45,6 @@ def simple_graph():
 def mock_services() -> InvocationServices:
     configuration = InvokeAIAppConfig(use_memory_db=True, node_cache_size=0)
     # NOTE: none of these are actually called by the test invocations
-    graph_execution_manager = ItemStorageMemory[GraphExecutionState]()
     return InvocationServices(
         board_image_records=None,  # type: ignore
         board_images=None,  # type: ignore
@@ -55,7 +52,6 @@ def mock_services() -> InvocationServices:
         boards=None,  # type: ignore
         configuration=configuration,
         events=TestEventService(),
-        graph_execution_manager=graph_execution_manager,
         image_files=None,  # type: ignore
         image_records=None,  # type: ignore
         images=None,  # type: ignore
@@ -65,47 +61,32 @@ def mock_services() -> InvocationServices:
         download_queue=None,  # type: ignore
         names=None,  # type: ignore
         performance_statistics=InvocationStatsService(),
-        processor=DefaultInvocationProcessor(),
-        queue=MemoryInvocationQueue(),
         session_processor=None,  # type: ignore
         session_queue=None,  # type: ignore
         urls=None,  # type: ignore
         workflow_records=None,  # type: ignore
-        tensors=None,
-        conditioning=None,
+        tensors=None,  # type: ignore
+        conditioning=None,  # type: ignore
     )
 
 
-def invoke_next(g: GraphExecutionState, services: InvocationServices) -> tuple[BaseInvocation, BaseInvocationOutput]:
+def invoke_next(g: GraphExecutionState) -> tuple[Optional[BaseInvocation], Optional[BaseInvocationOutput]]:
     n = g.next()
     if n is None:
         return (None, None)
 
     print(f"invoking {n.id}: {type(n)}")
-    o = n.invoke(
-        InvocationContext(
-            conditioning=None,
-            config=None,
-            data=None,
-            images=None,
-            tensors=None,
-            logger=None,
-            models=None,
-            util=None,
-            boards=None,
-            services=None,
-        )
-    )
+    o = n.invoke(Mock(InvocationContext))
     g.complete(n.id, o)
 
     return (n, o)
 
 
-def test_graph_state_executes_in_order(simple_graph, mock_services):
+def test_graph_state_executes_in_order(simple_graph: Graph):
     g = GraphExecutionState(graph=simple_graph)
 
-    n1 = invoke_next(g, mock_services)
-    n2 = invoke_next(g, mock_services)
+    n1 = invoke_next(g)
+    n2 = invoke_next(g)
     n3 = g.next()
 
     assert g.prepared_source_mapping[n1[0].id] == "1"
@@ -115,18 +96,18 @@ def test_graph_state_executes_in_order(simple_graph, mock_services):
     assert n2[0].prompt == n1[0].prompt
 
 
-def test_graph_is_complete(simple_graph, mock_services):
+def test_graph_is_complete(simple_graph: Graph):
     g = GraphExecutionState(graph=simple_graph)
-    _ = invoke_next(g, mock_services)
-    _ = invoke_next(g, mock_services)
+    _ = invoke_next(g)
+    _ = invoke_next(g)
     _ = g.next()
 
     assert g.is_complete()
 
 
-def test_graph_is_not_complete(simple_graph, mock_services):
+def test_graph_is_not_complete(simple_graph: Graph):
     g = GraphExecutionState(graph=simple_graph)
-    _ = invoke_next(g, mock_services)
+    _ = invoke_next(g)
     _ = g.next()
 
     assert not g.is_complete()
@@ -135,7 +116,7 @@ def test_graph_is_not_complete(simple_graph, mock_services):
 # TODO: test completion with iterators/subgraphs
 
 
-def test_graph_state_expands_iterator(mock_services):
+def test_graph_state_expands_iterator():
     graph = Graph()
     graph.add_node(RangeInvocation(id="0", start=0, stop=3, step=1))
     graph.add_node(IterateInvocation(id="1"))
@@ -147,7 +128,7 @@ def test_graph_state_expands_iterator(mock_services):
 
     g = GraphExecutionState(graph=graph)
     while not g.is_complete():
-        invoke_next(g, mock_services)
+        invoke_next(g)
 
     prepared_add_nodes = g.source_prepared_mapping["3"]
     results = {g.results[n].value for n in prepared_add_nodes}
@@ -155,7 +136,7 @@ def test_graph_state_expands_iterator(mock_services):
     assert results == expected
 
 
-def test_graph_state_collects(mock_services):
+def test_graph_state_collects():
     graph = Graph()
     test_prompts = ["Banana sushi", "Cat sushi"]
     graph.add_node(PromptCollectionTestInvocation(id="1", collection=list(test_prompts)))
@@ -167,19 +148,19 @@ def test_graph_state_collects(mock_services):
     graph.add_edge(create_edge("3", "prompt", "4", "item"))
 
     g = GraphExecutionState(graph=graph)
-    _ = invoke_next(g, mock_services)
-    _ = invoke_next(g, mock_services)
-    _ = invoke_next(g, mock_services)
-    _ = invoke_next(g, mock_services)
-    _ = invoke_next(g, mock_services)
-    n6 = invoke_next(g, mock_services)
+    _ = invoke_next(g)
+    _ = invoke_next(g)
+    _ = invoke_next(g)
+    _ = invoke_next(g)
+    _ = invoke_next(g)
+    n6 = invoke_next(g)
 
     assert isinstance(n6[0], CollectInvocation)
 
     assert sorted(g.results[n6[0].id].collection) == sorted(test_prompts)
 
 
-def test_graph_state_prepares_eagerly(mock_services):
+def test_graph_state_prepares_eagerly():
     """Tests that all prepareable nodes are prepared"""
     graph = Graph()
 
@@ -208,7 +189,7 @@ def test_graph_state_prepares_eagerly(mock_services):
     assert "prompt_iterated" not in g.source_prepared_mapping
 
 
-def test_graph_executes_depth_first(mock_services):
+def test_graph_executes_depth_first():
     """Tests that the graph executes depth-first, executing a branch as far as possible before moving to the next branch"""
     graph = Graph()
 
@@ -222,14 +203,14 @@ def test_graph_executes_depth_first(mock_services):
     graph.add_edge(create_edge("prompt_iterated", "prompt", "prompt_successor", "prompt"))
 
     g = GraphExecutionState(graph=graph)
-    _ = invoke_next(g, mock_services)
-    _ = invoke_next(g, mock_services)
-    _ = invoke_next(g, mock_services)
-    _ = invoke_next(g, mock_services)
+    _ = invoke_next(g)
+    _ = invoke_next(g)
+    _ = invoke_next(g)
+    _ = invoke_next(g)
 
     # Because ordering is not guaranteed, we cannot compare results directly.
     # Instead, we must count the number of results.
-    def get_completed_count(g, id):
+    def get_completed_count(g: GraphExecutionState, id: str):
         ids = list(g.source_prepared_mapping[id])
         completed_ids = [i for i in g.executed if i in ids]
         return len(completed_ids)
@@ -238,17 +219,17 @@ def test_graph_executes_depth_first(mock_services):
     assert get_completed_count(g, "prompt_iterated") == 1
     assert get_completed_count(g, "prompt_successor") == 0
 
-    _ = invoke_next(g, mock_services)
+    _ = invoke_next(g)
 
     assert get_completed_count(g, "prompt_iterated") == 1
     assert get_completed_count(g, "prompt_successor") == 1
 
-    _ = invoke_next(g, mock_services)
+    _ = invoke_next(g)
 
     assert get_completed_count(g, "prompt_iterated") == 2
     assert get_completed_count(g, "prompt_successor") == 1
 
-    _ = invoke_next(g, mock_services)
+    _ = invoke_next(g)
 
     assert get_completed_count(g, "prompt_iterated") == 2
     assert get_completed_count(g, "prompt_successor") == 2
diff --git a/tests/test_invoker.py b/tests/test_invoker.py
deleted file mode 100644
index 38fcf859a5..0000000000
--- a/tests/test_invoker.py
+++ /dev/null
@@ -1,163 +0,0 @@
-import logging
-from unittest.mock import Mock
-
-import pytest
-
-from invokeai.app.services.config.config_default import InvokeAIAppConfig
-from invokeai.app.services.item_storage.item_storage_memory import ItemStorageMemory
-
-# This import must happen before other invoke imports or test in other files(!!) break
-from .test_nodes import (  # isort: split
-    ErrorInvocation,
-    PromptTestInvocation,
-    TestEventService,
-    TextToImageTestInvocation,
-    create_edge,
-    wait_until,
-)
-
-from invokeai.app.services.invocation_cache.invocation_cache_memory import MemoryInvocationCache
-from invokeai.app.services.invocation_processor.invocation_processor_default import DefaultInvocationProcessor
-from invokeai.app.services.invocation_queue.invocation_queue_memory import MemoryInvocationQueue
-from invokeai.app.services.invocation_services import InvocationServices
-from invokeai.app.services.invocation_stats.invocation_stats_default import InvocationStatsService
-from invokeai.app.services.invoker import Invoker
-from invokeai.app.services.session_queue.session_queue_common import DEFAULT_QUEUE_ID
-from invokeai.app.services.shared.graph import Graph, GraphExecutionState
-
-
-@pytest.fixture
-def simple_graph():
-    g = Graph()
-    g.add_node(PromptTestInvocation(id="1", prompt="Banana sushi"))
-    g.add_node(TextToImageTestInvocation(id="2"))
-    g.add_edge(create_edge("1", "prompt", "2", "prompt"))
-    return g
-
-
-# This must be defined here to avoid issues with the dynamic creation of the union of all invocation types
-# Defining it in a separate module will cause the union to be incomplete, and pydantic will not validate
-# the test invocations.
-@pytest.fixture
-def mock_services() -> InvocationServices:
-    configuration = InvokeAIAppConfig(use_memory_db=True, node_cache_size=0)
-    return InvocationServices(
-        board_image_records=None,  # type: ignore
-        board_images=None,  # type: ignore
-        board_records=None,  # type: ignore
-        boards=None,  # type: ignore
-        configuration=configuration,
-        events=TestEventService(),
-        graph_execution_manager=ItemStorageMemory[GraphExecutionState](),
-        image_files=None,  # type: ignore
-        image_records=None,  # type: ignore
-        images=None,  # type: ignore
-        invocation_cache=MemoryInvocationCache(max_cache_size=0),
-        logger=logging,  # type: ignore
-        model_manager=Mock(),  # type: ignore
-        download_queue=None,  # type: ignore
-        names=None,  # type: ignore
-        performance_statistics=InvocationStatsService(),
-        processor=DefaultInvocationProcessor(),
-        queue=MemoryInvocationQueue(),
-        session_processor=None,  # type: ignore
-        session_queue=None,  # type: ignore
-        urls=None,  # type: ignore
-        workflow_records=None,  # type: ignore
-        tensors=None,
-        conditioning=None,
-    )
-
-
-@pytest.fixture()
-def mock_invoker(mock_services: InvocationServices) -> Invoker:
-    return Invoker(services=mock_services)
-
-
-def test_can_create_graph_state(mock_invoker: Invoker):
-    g = mock_invoker.create_execution_state()
-    mock_invoker.stop()
-
-    assert g is not None
-    assert isinstance(g, GraphExecutionState)
-
-
-def test_can_create_graph_state_from_graph(mock_invoker: Invoker, simple_graph):
-    g = mock_invoker.create_execution_state(graph=simple_graph)
-    mock_invoker.stop()
-
-    assert g is not None
-    assert isinstance(g, GraphExecutionState)
-    assert g.graph == simple_graph
-
-
-# @pytest.mark.xfail(reason = "Requires fixing following the model manager refactor")
-def test_can_invoke(mock_invoker: Invoker, simple_graph):
-    g = mock_invoker.create_execution_state(graph=simple_graph)
-    invocation_id = mock_invoker.invoke(
-        session_queue_batch_id="1",
-        session_queue_item_id=1,
-        session_queue_id=DEFAULT_QUEUE_ID,
-        graph_execution_state=g,
-    )
-    assert invocation_id is not None
-
-    def has_executed_any(g: GraphExecutionState):
-        g = mock_invoker.services.graph_execution_manager.get(g.id)
-        return len(g.executed) > 0
-
-    wait_until(lambda: has_executed_any(g), timeout=5, interval=1)
-    mock_invoker.stop()
-
-    g = mock_invoker.services.graph_execution_manager.get(g.id)
-    assert len(g.executed) > 0
-
-
-# @pytest.mark.xfail(reason = "Requires fixing following the model manager refactor")
-def test_can_invoke_all(mock_invoker: Invoker, simple_graph):
-    g = mock_invoker.create_execution_state(graph=simple_graph)
-    invocation_id = mock_invoker.invoke(
-        session_queue_batch_id="1",
-        session_queue_item_id=1,
-        session_queue_id=DEFAULT_QUEUE_ID,
-        graph_execution_state=g,
-        invoke_all=True,
-    )
-    assert invocation_id is not None
-
-    def has_executed_all(g: GraphExecutionState):
-        g = mock_invoker.services.graph_execution_manager.get(g.id)
-        return g.is_complete()
-
-    wait_until(lambda: has_executed_all(g), timeout=5, interval=1)
-    mock_invoker.stop()
-
-    g = mock_invoker.services.graph_execution_manager.get(g.id)
-    assert g.is_complete()
-
-
-# @pytest.mark.xfail(reason = "Requires fixing following the model manager refactor")
-def test_handles_errors(mock_invoker: Invoker):
-    g = mock_invoker.create_execution_state()
-    g.graph.add_node(ErrorInvocation(id="1"))
-
-    mock_invoker.invoke(
-        session_queue_batch_id="1",
-        session_queue_item_id=1,
-        session_queue_id=DEFAULT_QUEUE_ID,
-        graph_execution_state=g,
-        invoke_all=True,
-    )
-
-    def has_executed_all(g: GraphExecutionState):
-        g = mock_invoker.services.graph_execution_manager.get(g.id)
-        return g.is_complete()
-
-    wait_until(lambda: has_executed_all(g), timeout=5, interval=1)
-    mock_invoker.stop()
-
-    g = mock_invoker.services.graph_execution_manager.get(g.id)
-    assert g.has_error()
-    assert g.is_complete()
-
-    assert all((i in g.errors for i in g.source_prepared_mapping["1"]))

From 16676feea84663b6075a42ef8bd3641ca4d7fc7e Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sun, 18 Feb 2024 12:33:16 +1100
Subject: [PATCH 174/411] feat(nodes): make processor thread limit and polling
 interval configurable

---
 .../session_processor_default.py               | 18 +++++++++---------
 1 file changed, 9 insertions(+), 9 deletions(-)

diff --git a/invokeai/app/services/session_processor/session_processor_default.py b/invokeai/app/services/session_processor/session_processor_default.py
index dc08fc8345..3035a74a5a 100644
--- a/invokeai/app/services/session_processor/session_processor_default.py
+++ b/invokeai/app/services/session_processor/session_processor_default.py
@@ -18,12 +18,9 @@ from ..invoker import Invoker
 from .session_processor_base import SessionProcessorBase
 from .session_processor_common import SessionProcessorStatus
 
-POLLING_INTERVAL = 1
-THREAD_LIMIT = 1
-
 
 class DefaultSessionProcessor(SessionProcessorBase):
-    def start(self, invoker: Invoker) -> None:
+    def start(self, invoker: Invoker, thread_limit: int = 1, polling_interval: int = 1) -> None:
         self._invoker: Invoker = invoker
         self._queue_item: Optional[SessionQueueItem] = None
 
@@ -34,7 +31,10 @@ class DefaultSessionProcessor(SessionProcessorBase):
 
         local_handler.register(event_name=EventServiceBase.queue_event, _func=self._on_queue_event)
 
-        self._thread_limit = BoundedSemaphore(THREAD_LIMIT)
+        self._thread_limit = thread_limit
+        self._thread_semaphore = BoundedSemaphore(thread_limit)
+        self._polling_interval = polling_interval
+
         self._thread = Thread(
             name="session_processor",
             target=self._process,
@@ -88,7 +88,7 @@ class DefaultSessionProcessor(SessionProcessorBase):
     ):
         # Outermost processor try block; any unhandled exception is a fatal processor error
         try:
-            self._thread_limit.acquire()
+            self._thread_semaphore.acquire()
             stop_event.clear()
             resume_event.set()
             cancel_event.clear()
@@ -247,7 +247,7 @@ class DefaultSessionProcessor(SessionProcessorBase):
                     else:
                         # The queue was empty, wait for next polling interval or event to try again
                         self._invoker.services.logger.debug("Waiting for next polling interval or event")
-                        poll_now_event.wait(POLLING_INTERVAL)
+                        poll_now_event.wait(self._polling_interval)
                         continue
                 except Exception as e:
                     # Non-fatal error in processor, cancel the queue item and wait for next polling interval or event
@@ -256,7 +256,7 @@ class DefaultSessionProcessor(SessionProcessorBase):
                         self._invoker.services.session_queue.cancel_queue_item(
                             self._queue_item.item_id, error=traceback.format_exc()
                         )
-                    poll_now_event.wait(POLLING_INTERVAL)
+                    poll_now_event.wait(self._polling_interval)
                     continue
         except Exception as e:
             # Fatal error in processor, log and pass - we're done here
@@ -266,4 +266,4 @@ class DefaultSessionProcessor(SessionProcessorBase):
             stop_event.clear()
             poll_now_event.clear()
             self._queue_item = None
-            self._thread_limit.release()
+            self._thread_semaphore.release()

From fa39523b110ce76c15a33d2e542eff9ad3fbc290 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sun, 18 Feb 2024 15:58:53 +1100
Subject: [PATCH 175/411] feat(nodes): improved error messages in processor

---
 .../session_processor/session_processor_default.py     | 10 ++++++----
 1 file changed, 6 insertions(+), 4 deletions(-)

diff --git a/invokeai/app/services/session_processor/session_processor_default.py b/invokeai/app/services/session_processor/session_processor_default.py
index 3035a74a5a..7d761e627f 100644
--- a/invokeai/app/services/session_processor/session_processor_default.py
+++ b/invokeai/app/services/session_processor/session_processor_default.py
@@ -249,18 +249,20 @@ class DefaultSessionProcessor(SessionProcessorBase):
                         self._invoker.services.logger.debug("Waiting for next polling interval or event")
                         poll_now_event.wait(self._polling_interval)
                         continue
-                except Exception as e:
+                except Exception:
                     # Non-fatal error in processor, cancel the queue item and wait for next polling interval or event
-                    self._invoker.services.logger.error(f"Error in session processor: {e}")
+                    self._invoker.services.logger.error(
+                        f"Non-fatal error in session processor:\n{traceback.format_exc()}"
+                    )
                     if self._queue_item is not None:
                         self._invoker.services.session_queue.cancel_queue_item(
                             self._queue_item.item_id, error=traceback.format_exc()
                         )
                     poll_now_event.wait(self._polling_interval)
                     continue
-        except Exception as e:
+        except Exception:
             # Fatal error in processor, log and pass - we're done here
-            self._invoker.services.logger.error(f"Fatal Error in session processor: {e}")
+            self._invoker.services.logger.error(f"Fatal Error in session processor:\n{traceback.format_exc()}")
             pass
         finally:
             stop_event.clear()

From 0b0cb0ccc66e00a037da4d691fef3b0c643ffa2e Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sun, 18 Feb 2024 16:47:55 +1100
Subject: [PATCH 176/411] feat(nodes): making invocation class var in processor

---
 .../session_processor_default.py              | 30 ++++++++++---------
 1 file changed, 16 insertions(+), 14 deletions(-)

diff --git a/invokeai/app/services/session_processor/session_processor_default.py b/invokeai/app/services/session_processor/session_processor_default.py
index 7d761e627f..9ba726bff3 100644
--- a/invokeai/app/services/session_processor/session_processor_default.py
+++ b/invokeai/app/services/session_processor/session_processor_default.py
@@ -7,6 +7,7 @@ from typing import Optional
 from fastapi_events.handlers.local import local_handler
 from fastapi_events.typing import Event as FastAPIEvent
 
+from invokeai.app.invocations.baseinvocation import BaseInvocation
 from invokeai.app.services.events.events_base import EventServiceBase
 from invokeai.app.services.invocation_stats.invocation_stats_common import GESStatsNotFoundError
 from invokeai.app.services.session_processor.session_processor_common import CanceledException
@@ -23,6 +24,7 @@ class DefaultSessionProcessor(SessionProcessorBase):
     def start(self, invoker: Invoker, thread_limit: int = 1, polling_interval: int = 1) -> None:
         self._invoker: Invoker = invoker
         self._queue_item: Optional[SessionQueueItem] = None
+        self._invocation: Optional[BaseInvocation] = None
 
         self._resume_event = ThreadEvent()
         self._stop_event = ThreadEvent()
@@ -134,12 +136,12 @@ class DefaultSessionProcessor(SessionProcessorBase):
                             profiler.start(profile_id=self._queue_item.session_id)
 
                         # Prepare invocations and take the first
-                        invocation = self._queue_item.session.next()
+                        self._invocation = self._queue_item.session.next()
 
                         # Loop over invocations until the session is complete or canceled
-                        while invocation is not None and not cancel_event.is_set():
+                        while self._invocation is not None and not cancel_event.is_set():
                             # get the source node id to provide to clients (the prepared node id is not as useful)
-                            source_invocation_id = self._queue_item.session.prepared_source_mapping[invocation.id]
+                            source_invocation_id = self._queue_item.session.prepared_source_mapping[self._invocation.id]
 
                             # Send starting event
                             self._invoker.services.events.emit_invocation_started(
@@ -147,18 +149,18 @@ class DefaultSessionProcessor(SessionProcessorBase):
                                 queue_item_id=self._queue_item.item_id,
                                 queue_id=self._queue_item.queue_id,
                                 graph_execution_state_id=self._queue_item.session_id,
-                                node=invocation.model_dump(),
+                                node=self._invocation.model_dump(),
                                 source_node_id=source_invocation_id,
                             )
 
                             # Innermost processor try block; any unhandled exception is an invocation error & will fail the graph
                             try:
                                 with self._invoker.services.performance_statistics.collect_stats(
-                                    invocation, self._queue_item.session.id
+                                    self._invocation, self._queue_item.session.id
                                 ):
                                     # Build invocation context (the node-facing API)
                                     data = InvocationContextData(
-                                        invocation=invocation,
+                                        invocation=self._invocation,
                                         source_invocation_id=source_invocation_id,
                                         queue_item=self._queue_item,
                                     )
@@ -169,12 +171,12 @@ class DefaultSessionProcessor(SessionProcessorBase):
                                     )
 
                                     # Invoke the node
-                                    outputs = invocation.invoke_internal(
+                                    outputs = self._invocation.invoke_internal(
                                         context=context, services=self._invoker.services
                                     )
 
                                     # Save outputs and history
-                                    self._queue_item.session.complete(invocation.id, outputs)
+                                    self._queue_item.session.complete(self._invocation.id, outputs)
 
                                     # Send complete event
                                     self._invoker.services.events.emit_invocation_complete(
@@ -182,7 +184,7 @@ class DefaultSessionProcessor(SessionProcessorBase):
                                         queue_item_id=self._queue_item.item_id,
                                         queue_id=self._queue_item.queue_id,
                                         graph_execution_state_id=self._queue_item.session.id,
-                                        node=invocation.model_dump(),
+                                        node=self._invocation.model_dump(),
                                         source_node_id=source_invocation_id,
                                         result=outputs.model_dump(),
                                     )
@@ -208,9 +210,9 @@ class DefaultSessionProcessor(SessionProcessorBase):
                                 error = traceback.format_exc()
 
                                 # Save error
-                                self._queue_item.session.set_node_error(invocation.id, error)
+                                self._queue_item.session.set_node_error(self._invocation.id, error)
                                 self._invoker.services.logger.error(
-                                    f"Error while invoking session {self._queue_item.session_id}, invocation {invocation.id} ({invocation.get_type()}):\n{e}"
+                                    f"Error while invoking session {self._queue_item.session_id}, invocation {self._invocation.id} ({self._invocation.get_type()}):\n{e}"
                                 )
 
                                 # Send error event
@@ -219,7 +221,7 @@ class DefaultSessionProcessor(SessionProcessorBase):
                                     queue_item_id=self._queue_item.item_id,
                                     queue_id=self._queue_item.queue_id,
                                     graph_execution_state_id=self._queue_item.session.id,
-                                    node=invocation.model_dump(),
+                                    node=self._invocation.model_dump(),
                                     source_node_id=source_invocation_id,
                                     error_type=e.__class__.__name__,
                                     error=error,
@@ -236,10 +238,10 @@ class DefaultSessionProcessor(SessionProcessorBase):
                                 )
                                 # Save the stats and stop the profiler if it's running
                                 stats_cleanup(self._queue_item.session.id)
-                                invocation = None
+                                self._invocation = None
                             else:
                                 # Prepare the next invocation
-                                invocation = self._queue_item.session.next()
+                                self._invocation = self._queue_item.session.next()
 
                         # The session is complete, immediately poll for next session
                         self._queue_item = None

From 8bf9fd34ad19d07d33931bd711aac2191dfaa92f Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sun, 18 Feb 2024 16:51:58 +1100
Subject: [PATCH 177/411] fix(nodes): fix model load events

was accessing incorrect properties in event data
---
 .../services/model_load/model_load_default.py    | 16 ++++++++--------
 1 file changed, 8 insertions(+), 8 deletions(-)

diff --git a/invokeai/app/services/model_load/model_load_default.py b/invokeai/app/services/model_load/model_load_default.py
index 24ab10b427..3ff7898c0e 100644
--- a/invokeai/app/services/model_load/model_load_default.py
+++ b/invokeai/app/services/model_load/model_load_default.py
@@ -97,17 +97,17 @@ class ModelLoadService(ModelLoadServiceBase):
 
         if not loaded:
             self._invoker.services.events.emit_model_load_started(
-                queue_id=context_data.queue_id,
-                queue_item_id=context_data.queue_item_id,
-                queue_batch_id=context_data.batch_id,
-                graph_execution_state_id=context_data.session_id,
+                queue_id=context_data.queue_item.queue_id,
+                queue_item_id=context_data.queue_item.item_id,
+                queue_batch_id=context_data.queue_item.batch_id,
+                graph_execution_state_id=context_data.queue_item.session_id,
                 model_config=model_config,
             )
         else:
             self._invoker.services.events.emit_model_load_completed(
-                queue_id=context_data.queue_id,
-                queue_item_id=context_data.queue_item_id,
-                queue_batch_id=context_data.batch_id,
-                graph_execution_state_id=context_data.session_id,
+                queue_id=context_data.queue_item.queue_id,
+                queue_item_id=context_data.queue_item.item_id,
+                queue_batch_id=context_data.queue_item.batch_id,
+                graph_execution_state_id=context_data.queue_item.session_id,
                 model_config=model_config,
             )

From 763debdeebeb80133cb1be79fb57f279d5513292 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 19 Feb 2024 12:57:05 +1100
Subject: [PATCH 178/411] fix(nodes): fix typing on stats service context
 manager

---
 .../app/services/invocation_stats/invocation_stats_base.py    | 4 ++--
 .../app/services/invocation_stats/invocation_stats_default.py | 4 ++--
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/invokeai/app/services/invocation_stats/invocation_stats_base.py b/invokeai/app/services/invocation_stats/invocation_stats_base.py
index b28220e74c..3266d985fe 100644
--- a/invokeai/app/services/invocation_stats/invocation_stats_base.py
+++ b/invokeai/app/services/invocation_stats/invocation_stats_base.py
@@ -30,7 +30,7 @@ writes to the system log is stored in InvocationServices.performance_statistics.
 
 from abc import ABC, abstractmethod
 from pathlib import Path
-from typing import Iterator
+from typing import ContextManager
 
 from invokeai.app.invocations.baseinvocation import BaseInvocation
 from invokeai.app.services.invocation_stats.invocation_stats_common import InvocationStatsSummary
@@ -50,7 +50,7 @@ class InvocationStatsServiceBase(ABC):
         self,
         invocation: BaseInvocation,
         graph_execution_state_id: str,
-    ) -> Iterator[None]:
+    ) -> ContextManager[None]:
         """
         Return a context object that will capture the statistics on the execution
         of invocaation. Use with: to place around the part of the code that executes the invocation.
diff --git a/invokeai/app/services/invocation_stats/invocation_stats_default.py b/invokeai/app/services/invocation_stats/invocation_stats_default.py
index 06a5b675c3..5a41f1f5d6 100644
--- a/invokeai/app/services/invocation_stats/invocation_stats_default.py
+++ b/invokeai/app/services/invocation_stats/invocation_stats_default.py
@@ -2,7 +2,7 @@ import json
 import time
 from contextlib import contextmanager
 from pathlib import Path
-from typing import Iterator
+from typing import Generator
 
 import psutil
 import torch
@@ -41,7 +41,7 @@ class InvocationStatsService(InvocationStatsServiceBase):
         self._invoker = invoker
 
     @contextmanager
-    def collect_stats(self, invocation: BaseInvocation, graph_execution_state_id: str) -> Iterator[None]:
+    def collect_stats(self, invocation: BaseInvocation, graph_execution_state_id: str) -> Generator[None, None, None]:
         # This is to handle case of the model manager not being initialized, which happens
         # during some tests.
         services = self._invoker.services

From e3f9da29ba4580c7e9a9504b15d8d00f3846f46d Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 19 Feb 2024 13:09:00 +1100
Subject: [PATCH 179/411] tidy(nodes): clean up profiler/stats in processor,
 better comments

---
 .../session_processor_default.py              | 65 ++++++++++---------
 1 file changed, 34 insertions(+), 31 deletions(-)

diff --git a/invokeai/app/services/session_processor/session_processor_default.py b/invokeai/app/services/session_processor/session_processor_default.py
index 9ba726bff3..cff7bb6c6c 100644
--- a/invokeai/app/services/session_processor/session_processor_default.py
+++ b/invokeai/app/services/session_processor/session_processor_default.py
@@ -37,6 +37,18 @@ class DefaultSessionProcessor(SessionProcessorBase):
         self._thread_semaphore = BoundedSemaphore(thread_limit)
         self._polling_interval = polling_interval
 
+        # If profiling is enabled, create a profiler. The same profiler will be used for all sessions. Internally,
+        # the profiler will create a new profile for each session.
+        self._profiler = (
+            Profiler(
+                logger=self._invoker.services.logger,
+                output_dir=self._invoker.services.configuration.profiles_path,
+                prefix=self._invoker.services.configuration.profile_prefix,
+            )
+            if self._invoker.services.configuration.profile_graphs
+            else None
+        )
+
         self._thread = Thread(
             name="session_processor",
             target=self._process,
@@ -95,32 +107,6 @@ class DefaultSessionProcessor(SessionProcessorBase):
             resume_event.set()
             cancel_event.clear()
 
-            # If profiling is enabled, create a profiler. The same profiler will be used for all sessions. Internally,
-            # the profiler will create a new profile for each session.
-            profiler = (
-                Profiler(
-                    logger=self._invoker.services.logger,
-                    output_dir=self._invoker.services.configuration.profiles_path,
-                    prefix=self._invoker.services.configuration.profile_prefix,
-                )
-                if self._invoker.services.configuration.profile_graphs
-                else None
-            )
-
-            # Helper function to stop the profiler and save the stats
-            def stats_cleanup(graph_execution_state_id: str) -> None:
-                if profiler:
-                    profile_path = profiler.stop()
-                    stats_path = profile_path.with_suffix(".json")
-                    self._invoker.services.performance_statistics.dump_stats(
-                        graph_execution_state_id=graph_execution_state_id, output_path=stats_path
-                    )
-                # We'll get a GESStatsNotFoundError if we try to log stats for an untracked graph, but in the processor
-                # we don't care about that - suppress the error.
-                with suppress(GESStatsNotFoundError):
-                    self._invoker.services.performance_statistics.log_stats(graph_execution_state_id)
-                    self._invoker.services.performance_statistics.reset_stats()
-
             while not stop_event.is_set():
                 poll_now_event.clear()
                 # Middle processor try block; any unhandled exception is a non-fatal processor error
@@ -132,8 +118,8 @@ class DefaultSessionProcessor(SessionProcessorBase):
                         cancel_event.clear()
 
                         # If profiling is enabled, start the profiler
-                        if profiler is not None:
-                            profiler.start(profile_id=self._queue_item.session_id)
+                        if self._profiler is not None:
+                            self._profiler.start(profile_id=self._queue_item.session_id)
 
                         # Prepare invocations and take the first
                         self._invocation = self._queue_item.session.next()
@@ -228,6 +214,7 @@ class DefaultSessionProcessor(SessionProcessorBase):
                                 )
                                 pass
 
+                            # The session is complete if the all invocations are complete or there was an error
                             if self._queue_item.session.is_complete() or cancel_event.is_set():
                                 # Send complete event
                                 self._invoker.services.events.emit_graph_execution_complete(
@@ -236,8 +223,20 @@ class DefaultSessionProcessor(SessionProcessorBase):
                                     queue_id=self._queue_item.queue_id,
                                     graph_execution_state_id=self._queue_item.session.id,
                                 )
-                                # Save the stats and stop the profiler if it's running
-                                stats_cleanup(self._queue_item.session.id)
+                                # If we are profiling, stop the profiler and dump the profile & stats
+                                if self._profiler:
+                                    profile_path = self._profiler.stop()
+                                    stats_path = profile_path.with_suffix(".json")
+                                    self._invoker.services.performance_statistics.dump_stats(
+                                        graph_execution_state_id=self._queue_item.session.id, output_path=stats_path
+                                    )
+                                # We'll get a GESStatsNotFoundError if we try to log stats for an untracked graph, but in the processor
+                                # we don't care about that - suppress the error.
+                                with suppress(GESStatsNotFoundError):
+                                    self._invoker.services.performance_statistics.log_stats(self._queue_item.session.id)
+                                    self._invoker.services.performance_statistics.reset_stats()
+
+                                # Set the invocation to None to prepare for the next session
                                 self._invocation = None
                             else:
                                 # Prepare the next invocation
@@ -252,14 +251,18 @@ class DefaultSessionProcessor(SessionProcessorBase):
                         poll_now_event.wait(self._polling_interval)
                         continue
                 except Exception:
-                    # Non-fatal error in processor, cancel the queue item and wait for next polling interval or event
+                    # Non-fatal error in processor
                     self._invoker.services.logger.error(
                         f"Non-fatal error in session processor:\n{traceback.format_exc()}"
                     )
+                    # Cancel the queue item
                     if self._queue_item is not None:
                         self._invoker.services.session_queue.cancel_queue_item(
                             self._queue_item.item_id, error=traceback.format_exc()
                         )
+                    # Reset the invocation to None to prepare for the next session
+                    self._invocation = None
+                    # Immediately poll for next queue item
                     poll_now_event.wait(self._polling_interval)
                     continue
         except Exception:

From 89fa36a818d12ef572cc66c81180a96530640e8b Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 19 Feb 2024 13:16:06 +1100
Subject: [PATCH 180/411] chore(nodes): update TODO comment

---
 .../app/services/session_processor/session_processor_default.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/invokeai/app/services/session_processor/session_processor_default.py b/invokeai/app/services/session_processor/session_processor_default.py
index cff7bb6c6c..c0b98220c8 100644
--- a/invokeai/app/services/session_processor/session_processor_default.py
+++ b/invokeai/app/services/session_processor/session_processor_default.py
@@ -176,7 +176,7 @@ class DefaultSessionProcessor(SessionProcessorBase):
                                     )
 
                             except KeyboardInterrupt:
-                                # TODO(psyche): should we set the cancel event here and/or cancel the queue item?
+                                # TODO(MM2): Create an event for this
                                 pass
 
                             except CanceledException:

From 5b133ad198b8551c7fa0acb330d50025227c4dcf Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lstein@gmail.com>
Date: Mon, 19 Feb 2024 11:40:53 -0500
Subject: [PATCH 181/411] Add a few convenience targets to Makefile

- "test" to run pytests
- "frontend-install" to reinstall pnpm's node modeuls
---
 Makefile | 39 +++++++++++++++++++++++++--------------
 1 file changed, 25 insertions(+), 14 deletions(-)

diff --git a/Makefile b/Makefile
index 10d7a257c5..c3eec094f7 100644
--- a/Makefile
+++ b/Makefile
@@ -6,33 +6,44 @@ default: help
 help:
 	@echo Developer commands:
 	@echo
-	@echo "ruff           Run ruff, fixing any safely-fixable errors and formatting"
-	@echo "ruff-unsafe    Run ruff, fixing all fixable errors and formatting"
-	@echo "mypy           Run mypy using the config in pyproject.toml to identify type mismatches and other coding errors"
-	@echo "mypy-all       Run mypy ignoring the config in pyproject.tom but still ignoring missing imports"
-	@echo "frontend-build Build the frontend in order to run on localhost:9090"
-	@echo "frontend-dev   Run the frontend in developer mode on localhost:5173"
-	@echo "installer-zip  Build the installer .zip file for the current version"
-	@echo "tag-release    Tag the GitHub repository with the current version (use at release time only!)"
+	@echo "ruff              Run ruff, fixing any safely-fixable errors and formatting"
+	@echo "ruff-unsafe       Run ruff, fixing all fixable errors and formatting"
+	@echo "mypy              Run mypy using the config in pyproject.toml to identify type mismatches and other coding errors"
+	@echo "mypy-all          Run mypy ignoring the config in pyproject.tom but still ignoring missing imports"
+	@echo "test"             Run the unit tests.
+	@echo "frontend-install" Install the pnpm modules needed for the front end
+	@echo "frontend-build    Build the frontend in order to run on localhost:9090"
+	@echo "frontend-dev      Run the frontend in developer mode on localhost:5173"
+	@echo "installer-zip     Build the installer .zip file for the current version"
+	@echo "tag-release       Tag the GitHub repository with the current version (use at release time only!)"
 
 # Runs ruff, fixing any safely-fixable errors and formatting
 ruff:
-		ruff check . --fix
-		ruff format .
+	ruff check . --fix
+	ruff format .
 
 # Runs ruff, fixing all errors it can fix and formatting
 ruff-unsafe:
-		ruff check . --fix --unsafe-fixes
-		ruff format .
+	ruff check . --fix --unsafe-fixes
+	ruff format .
 
 # Runs mypy, using the config in pyproject.toml
 mypy:
-		mypy scripts/invokeai-web.py
+	mypy scripts/invokeai-web.py
 
 # Runs mypy, ignoring the config in pyproject.toml but still ignoring missing (untyped) imports
 # (many files are ignored by the config, so this is useful for checking all files)
 mypy-all:
-		mypy scripts/invokeai-web.py --config-file= --ignore-missing-imports
+	mypy scripts/invokeai-web.py --config-file= --ignore-missing-imports
+
+# Run the unit tests
+test:
+	pytest ./tests
+
+# Install the pnpm modules needed for the front end
+frontend-install:
+	rm -rf invokeai/frontend/web/node_modules
+	cd invokeai/frontend/web && pnpm install
 
 # Build the frontend
 frontend-build:

From ca7e9287108b634b88d9ab1af4d2cf0fc8df7692 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 20 Feb 2024 10:16:25 +1100
Subject: [PATCH 182/411] fix(ui): fix low-hanging fruit types

---
 .../listenerMiddleware/listeners/controlNetImageProcessed.ts    | 1 +
 invokeai/frontend/web/src/services/api/endpoints/models.ts      | 2 +-
 invokeai/frontend/web/src/services/api/types.ts                 | 1 -
 3 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/controlNetImageProcessed.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/controlNetImageProcessed.ts
index fba274beb8..73de931297 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/controlNetImageProcessed.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/controlNetImageProcessed.ts
@@ -51,6 +51,7 @@ export const addControlNetImageProcessedListener = () => {
                 image: { image_name: ca.controlImage },
               },
             },
+            edges: [],
           },
           runs: 1,
         },
diff --git a/invokeai/frontend/web/src/services/api/endpoints/models.ts b/invokeai/frontend/web/src/services/api/endpoints/models.ts
index 9a7f108056..57cf7dacfc 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/models.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/models.ts
@@ -39,7 +39,7 @@ type UpdateLoRAModelArg = {
 type UpdateMainModelResponse =
   paths['/api/v2/models/i/{key}']['patch']['responses']['200']['content']['application/json'];
 
-type ListModelsArg = NonNullable<paths['/api/models_v2/']['get']['parameters']['query']>;
+type ListModelsArg = NonNullable<paths['/api/v2/models/']['get']['parameters']['query']>;
 
 type UpdateLoRAModelResponse = UpdateMainModelResponse;
 
diff --git a/invokeai/frontend/web/src/services/api/types.ts b/invokeai/frontend/web/src/services/api/types.ts
index 4ae2f9b594..aaa70a2684 100644
--- a/invokeai/frontend/web/src/services/api/types.ts
+++ b/invokeai/frontend/web/src/services/api/types.ts
@@ -164,7 +164,6 @@ export type IntegerOutput = S['IntegerOutput'];
 export type IterateInvocationOutput = S['IterateInvocationOutput'];
 export type CollectInvocationOutput = S['CollectInvocationOutput'];
 export type LatentsOutput = S['LatentsOutput'];
-export type GraphInvocationOutput = S['GraphInvocationOutput'];
 
 // Post-image upload actions, controls workflows when images are uploaded
 

From 7e5a85496e63add7f15b239e00495f3d4f66395b Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 20 Feb 2024 10:42:14 +1100
Subject: [PATCH 183/411] chore(ui): bump `@invoke-ai/ui-library`

---
 invokeai/frontend/web/package.json   |   2 +-
 invokeai/frontend/web/pnpm-lock.yaml | 110 ++++++++++++++++-----------
 2 files changed, 68 insertions(+), 44 deletions(-)

diff --git a/invokeai/frontend/web/package.json b/invokeai/frontend/web/package.json
index cea13350d2..a9f37f76ad 100644
--- a/invokeai/frontend/web/package.json
+++ b/invokeai/frontend/web/package.json
@@ -57,7 +57,7 @@
     "@dnd-kit/sortable": "^8.0.0",
     "@dnd-kit/utilities": "^3.2.2",
     "@fontsource-variable/inter": "^5.0.16",
-    "@invoke-ai/ui-library": "^0.0.18",
+    "@invoke-ai/ui-library": "^0.0.21",
     "@mantine/form": "6.0.21",
     "@nanostores/react": "^0.7.1",
     "@reduxjs/toolkit": "2.0.1",
diff --git a/invokeai/frontend/web/pnpm-lock.yaml b/invokeai/frontend/web/pnpm-lock.yaml
index 0ec2e47a0c..4f9902299c 100644
--- a/invokeai/frontend/web/pnpm-lock.yaml
+++ b/invokeai/frontend/web/pnpm-lock.yaml
@@ -32,8 +32,8 @@ dependencies:
     specifier: ^5.0.16
     version: 5.0.16
   '@invoke-ai/ui-library':
-    specifier: ^0.0.18
-    version: 0.0.18(@chakra-ui/form-control@2.2.0)(@chakra-ui/icon@3.2.0)(@chakra-ui/media-query@3.3.0)(@chakra-ui/menu@2.2.1)(@chakra-ui/spinner@2.1.0)(@chakra-ui/system@2.6.2)(@fontsource-variable/inter@5.0.16)(@internationalized/date@3.5.1)(@types/react@18.2.48)(i18next@23.7.16)(react-dom@18.2.0)(react@18.2.0)
+    specifier: ^0.0.21
+    version: 0.0.21(@chakra-ui/form-control@2.2.0)(@chakra-ui/icon@3.2.0)(@chakra-ui/media-query@3.3.0)(@chakra-ui/menu@2.2.1)(@chakra-ui/spinner@2.1.0)(@chakra-ui/system@2.6.2)(@fontsource-variable/inter@5.0.16)(@internationalized/date@3.5.2)(@types/react@18.2.48)(i18next@23.7.16)(react-dom@18.2.0)(react@18.2.0)
   '@mantine/form':
     specifier: 6.0.21
     version: 6.0.21(react@18.2.0)
@@ -344,7 +344,7 @@ packages:
       '@jridgewell/trace-mapping': 0.3.21
     dev: true
 
-  /@ark-ui/anatomy@1.3.0(@internationalized/date@3.5.1):
+  /@ark-ui/anatomy@1.3.0(@internationalized/date@3.5.2):
     resolution: {integrity: sha512-1yG2MrzUlix6KthjQMCNiHnkXrWwEdFAX6D+HqGJaNu0XvaGul2J+wDNtjsdX+gxiWu1nXXEEOAWlFVYMUf65w==}
     dependencies:
       '@zag-js/accordion': 0.32.1
@@ -356,7 +356,7 @@ packages:
       '@zag-js/color-utils': 0.32.1
       '@zag-js/combobox': 0.32.1
       '@zag-js/date-picker': 0.32.1
-      '@zag-js/date-utils': 0.32.1(@internationalized/date@3.5.1)
+      '@zag-js/date-utils': 0.32.1(@internationalized/date@3.5.2)
       '@zag-js/dialog': 0.32.1
       '@zag-js/editable': 0.32.1
       '@zag-js/file-upload': 0.32.1
@@ -383,13 +383,13 @@ packages:
       - '@internationalized/date'
     dev: false
 
-  /@ark-ui/react@1.3.0(@internationalized/date@3.5.1)(react-dom@18.2.0)(react@18.2.0):
+  /@ark-ui/react@1.3.0(@internationalized/date@3.5.2)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-JHjNoIX50+mUCTaEGMjfGQWGGi31pKsV646jZJlR/1xohpYJigzg8BvO97cTsVk8fwtur+cm11gz3Nf7f5QUnA==}
     peerDependencies:
       react: '>=18.0.0'
       react-dom: '>=18.0.0'
     dependencies:
-      '@ark-ui/anatomy': 1.3.0(@internationalized/date@3.5.1)
+      '@ark-ui/anatomy': 1.3.0(@internationalized/date@3.5.2)
       '@zag-js/accordion': 0.32.1
       '@zag-js/avatar': 0.32.1
       '@zag-js/carousel': 0.32.1
@@ -399,7 +399,7 @@ packages:
       '@zag-js/combobox': 0.32.1
       '@zag-js/core': 0.32.1
       '@zag-js/date-picker': 0.32.1
-      '@zag-js/date-utils': 0.32.1(@internationalized/date@3.5.1)
+      '@zag-js/date-utils': 0.32.1(@internationalized/date@3.5.2)
       '@zag-js/dialog': 0.32.1
       '@zag-js/editable': 0.32.1
       '@zag-js/file-upload': 0.32.1
@@ -1709,6 +1709,13 @@ packages:
     dependencies:
       regenerator-runtime: 0.14.1
 
+  /@babel/runtime@7.23.9:
+    resolution: {integrity: sha512-0CX6F+BI2s9dkUqr08KFrAIZgNFj75rdBU/DjCyYLIaV/quFjkk6T+EJ2LkZHyZTbEV4L5p97mNkUsHl2wLFAw==}
+    engines: {node: '>=6.9.0'}
+    dependencies:
+      regenerator-runtime: 0.14.1
+    dev: false
+
   /@babel/template@7.22.15:
     resolution: {integrity: sha512-QPErUVm4uyJa60rkI73qneDacvdvzxshT3kksGqlGWYdOTIUOwJ7RDUL8sGqslY1uXWSL6xMFKEXDS3ox2uF0w==}
     engines: {node: '>=6.9.0'}
@@ -1969,7 +1976,7 @@ packages:
     dependencies:
       '@chakra-ui/dom-utils': 2.1.0
       react: 18.2.0
-      react-focus-lock: 2.9.6(@types/react@18.2.48)(react@18.2.0)
+      react-focus-lock: 2.11.1(@types/react@18.2.48)(react@18.2.0)
     transitivePeerDependencies:
       - '@types/react'
     dev: false
@@ -3013,7 +3020,7 @@ packages:
       '@types/react':
         optional: true
     dependencies:
-      '@babel/runtime': 7.23.8
+      '@babel/runtime': 7.23.9
       '@emotion/babel-plugin': 11.11.0
       '@emotion/is-prop-valid': 1.2.1
       '@emotion/react': 11.11.3(@types/react@18.2.48)(react@18.2.0)
@@ -3560,16 +3567,16 @@ packages:
     resolution: {integrity: sha512-dvuCeX5fC9dXgJn9t+X5atfmgQAzUOWqS1254Gh0m6i8wKd10ebXkfNKiRK+1GWi/yTvvLDHpoxLr0xxxeslWw==}
     dev: true
 
-  /@internationalized/date@3.5.1:
-    resolution: {integrity: sha512-LUQIfwU9e+Fmutc/DpRTGXSdgYZLBegi4wygCWDSVmUdLTaMHsQyASDiJtREwanwKuQLq0hY76fCJ9J/9I2xOQ==}
+  /@internationalized/date@3.5.2:
+    resolution: {integrity: sha512-vo1yOMUt2hzp63IutEaTUxROdvQg1qlMRsbCvbay2AK2Gai7wIgCyK5weEX3nHkiLgo4qCXHijFNC/ILhlRpOQ==}
     dependencies:
-      '@swc/helpers': 0.5.3
+      '@swc/helpers': 0.5.6
     dev: false
 
-  /@internationalized/number@3.5.0:
-    resolution: {integrity: sha512-ZY1BW8HT9WKYvaubbuqXbbDdHhOUMfE2zHHFJeTppid0S+pc8HtdIxFxaYMsGjCb4UsF+MEJ4n2TfU7iHnUK8w==}
+  /@internationalized/number@3.5.1:
+    resolution: {integrity: sha512-N0fPU/nz15SwR9IbfJ5xaS9Ss/O5h1sVXMZf43vc9mxEG48ovglvvzBjF53aHlq20uoR6c+88CrIXipU/LSzwg==}
     dependencies:
-      '@swc/helpers': 0.5.3
+      '@swc/helpers': 0.5.6
     dev: false
 
   /@invoke-ai/eslint-config-react@0.0.13(@typescript-eslint/eslint-plugin@6.19.0)(@typescript-eslint/parser@6.19.0)(eslint-config-prettier@9.1.0)(eslint-plugin-import@2.29.1)(eslint-plugin-react-hooks@4.6.0)(eslint-plugin-react-refresh@0.4.5)(eslint-plugin-react@7.33.2)(eslint-plugin-simple-import-sort@10.0.0)(eslint-plugin-storybook@0.6.15)(eslint-plugin-unused-imports@3.0.0)(eslint@8.56.0):
@@ -3608,14 +3615,14 @@ packages:
       prettier: 3.2.4
     dev: true
 
-  /@invoke-ai/ui-library@0.0.18(@chakra-ui/form-control@2.2.0)(@chakra-ui/icon@3.2.0)(@chakra-ui/media-query@3.3.0)(@chakra-ui/menu@2.2.1)(@chakra-ui/spinner@2.1.0)(@chakra-ui/system@2.6.2)(@fontsource-variable/inter@5.0.16)(@internationalized/date@3.5.1)(@types/react@18.2.48)(i18next@23.7.16)(react-dom@18.2.0)(react@18.2.0):
-    resolution: {integrity: sha512-Yme+2+pzYy3TPb7ZT0hYmBwahH29ZRSVIxLKSexh3BsbJXbTzGssRQU78QvK6Ymxemgbso3P8Rs+IW0zNhQKjQ==}
+  /@invoke-ai/ui-library@0.0.21(@chakra-ui/form-control@2.2.0)(@chakra-ui/icon@3.2.0)(@chakra-ui/media-query@3.3.0)(@chakra-ui/menu@2.2.1)(@chakra-ui/spinner@2.1.0)(@chakra-ui/system@2.6.2)(@fontsource-variable/inter@5.0.16)(@internationalized/date@3.5.2)(@types/react@18.2.48)(i18next@23.7.16)(react-dom@18.2.0)(react@18.2.0):
+    resolution: {integrity: sha512-tCvgkBPDt0gNq+8IcR03e/Mw7R8Mb/SMXTqx3FEIxlTQEo93A/D38dKXeDCzTdx4sQ+sknfB+JLBbHs6sg5hhQ==}
     peerDependencies:
       '@fontsource-variable/inter': ^5.0.16
       react: ^18.2.0
       react-dom: ^18.2.0
     dependencies:
-      '@ark-ui/react': 1.3.0(@internationalized/date@3.5.1)(react-dom@18.2.0)(react@18.2.0)
+      '@ark-ui/react': 1.3.0(@internationalized/date@3.5.2)(react-dom@18.2.0)(react@18.2.0)
       '@chakra-ui/anatomy': 2.2.2
       '@chakra-ui/icons': 2.1.1(@chakra-ui/system@2.6.2)(react@18.2.0)
       '@chakra-ui/layout': 2.3.1(@chakra-ui/system@2.6.2)(react@18.2.0)
@@ -3631,11 +3638,11 @@ packages:
       framer-motion: 10.18.0(react-dom@18.2.0)(react@18.2.0)
       lodash-es: 4.17.21
       nanostores: 0.9.5
-      overlayscrollbars: 2.4.7
-      overlayscrollbars-react: 0.5.4(overlayscrollbars@2.4.7)(react@18.2.0)
+      overlayscrollbars: 2.5.0
+      overlayscrollbars-react: 0.5.4(overlayscrollbars@2.5.0)(react@18.2.0)
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
-      react-i18next: 14.0.1(i18next@23.7.16)(react-dom@18.2.0)(react@18.2.0)
+      react-i18next: 14.0.5(i18next@23.7.16)(react-dom@18.2.0)(react@18.2.0)
       react-icons: 5.0.1(react@18.2.0)
       react-select: 5.8.0(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
     transitivePeerDependencies:
@@ -5634,8 +5641,8 @@ packages:
     resolution: {integrity: sha512-9F4ys4C74eSTEUNndnER3VJ15oru2NumfQxS8geE+f3eB5xvfxpWyqE5XlVnxb/R14uoXi6SLbBwwiDSkv+XEw==}
     dev: true
 
-  /@swc/helpers@0.5.3:
-    resolution: {integrity: sha512-FaruWX6KdudYloq1AHD/4nU+UsMTdNE8CKyrseXWEcgjDAbvkwJg2QGPAnfIJLIWsjZOSPLOAykK6fuYp4vp4A==}
+  /@swc/helpers@0.5.6:
+    resolution: {integrity: sha512-aYX01Ke9hunpoCexYAgQucEpARGQ5w/cqHFrIR+e9gdKb1QWTsVJuTJ2ozQzIAxLyRQe/m+2RqzkyOOGiMKRQA==}
     dependencies:
       tslib: 2.6.2
     dev: false
@@ -6754,10 +6761,10 @@ packages:
   /@zag-js/date-picker@0.32.1:
     resolution: {integrity: sha512-n/hYmF+/R4+NuyfPRzCgeuLT6LJihKSuKzK29STPWy3sC/tBBHiqhNv1/4UKbatHUJXdBW2XF+N8Rw08RffcFQ==}
     dependencies:
-      '@internationalized/date': 3.5.1
+      '@internationalized/date': 3.5.2
       '@zag-js/anatomy': 0.32.1
       '@zag-js/core': 0.32.1
-      '@zag-js/date-utils': 0.32.1(@internationalized/date@3.5.1)
+      '@zag-js/date-utils': 0.32.1(@internationalized/date@3.5.2)
       '@zag-js/dismissable': 0.32.1
       '@zag-js/dom-event': 0.32.1
       '@zag-js/dom-query': 0.32.1
@@ -6769,12 +6776,12 @@ packages:
       '@zag-js/utils': 0.32.1
     dev: false
 
-  /@zag-js/date-utils@0.32.1(@internationalized/date@3.5.1):
+  /@zag-js/date-utils@0.32.1(@internationalized/date@3.5.2):
     resolution: {integrity: sha512-dbBDRSVr5pRUw3rXndyGuSshZiWqQI5JQO4D2KIFGkXzorj6WzoOpcO910Z7AdM/9cCAMpCjUrka8d8o9BpJBg==}
     peerDependencies:
       '@internationalized/date': '>=3.0.0'
     dependencies:
-      '@internationalized/date': 3.5.1
+      '@internationalized/date': 3.5.2
     dev: false
 
   /@zag-js/dialog@0.32.1:
@@ -6917,7 +6924,7 @@ packages:
   /@zag-js/number-input@0.32.1:
     resolution: {integrity: sha512-atyIOvoMITb4hZtQym7yD6I7grvPW83UeMFO8hCQg3HWwd2zR4+63mouWuyMoWb4QrzVFRVQBaU8OG5xGlknEw==}
     dependencies:
-      '@internationalized/number': 3.5.0
+      '@internationalized/number': 3.5.1
       '@zag-js/anatomy': 0.32.1
       '@zag-js/core': 0.32.1
       '@zag-js/dom-event': 0.32.1
@@ -9537,8 +9544,8 @@ packages:
     engines: {node: '>=0.4.0'}
     dev: true
 
-  /focus-lock@1.0.0:
-    resolution: {integrity: sha512-a8Ge6cdKh9za/GZR/qtigTAk7SrGore56EFcoMshClsh7FLk1zwszc/ltuMfKhx56qeuyL/jWQ4J4axou0iJ9w==}
+  /focus-lock@1.3.2:
+    resolution: {integrity: sha512-kFI92jZVqa8rP4Yer2sLNlUDcOdEFxYum2tIIr4eCH0XF+pOmlg0xiY4tkbDmHJXt3phtbJoWs1L6PgUVk97rA==}
     engines: {node: '>=10'}
     dependencies:
       tslib: 2.6.2
@@ -11431,13 +11438,13 @@ packages:
       react: 18.2.0
     dev: false
 
-  /overlayscrollbars-react@0.5.4(overlayscrollbars@2.4.7)(react@18.2.0):
+  /overlayscrollbars-react@0.5.4(overlayscrollbars@2.5.0)(react@18.2.0):
     resolution: {integrity: sha512-FPKx9XnXovTnI4+2JXig5uEaTLSEJ6svOwPzIfBBXTHBRNsz2+WhYUmfM0K/BNYxjgDEwuPm+NQhEoOA0RoG1g==}
     peerDependencies:
       overlayscrollbars: ^2.0.0
       react: '>=16.8.0'
     dependencies:
-      overlayscrollbars: 2.4.7
+      overlayscrollbars: 2.5.0
       react: 18.2.0
     dev: false
 
@@ -11445,8 +11452,8 @@ packages:
     resolution: {integrity: sha512-C7tmhetwMv9frEvIT/RfkAVEgbjRNz/Gh2zE8BVmN+jl35GRaAnz73rlGQCMRoC2arpACAXyMNnJkzHb7GBrcA==}
     dev: false
 
-  /overlayscrollbars@2.4.7:
-    resolution: {integrity: sha512-02X2/nHno35dzebCx+EO2tRDaKAOltZqUKdUqvq3Pt8htCuhJbYi+mjr0CYerVeGRRoZ2Uo6/8XrNg//DJJ+GA==}
+  /overlayscrollbars@2.5.0:
+    resolution: {integrity: sha512-CWVC2dwS07XZfLHDm5GmZN1iYggiJ8Vufnvzwt0gwR9Yz1hVckKeTxg7VILZeYVGhDYJHZ1Xc8Xfys5dWZ1qiA==}
     dev: false
 
   /p-limit@2.3.0:
@@ -11949,7 +11956,7 @@ packages:
     peerDependencies:
       react: ^15.3.0 || ^16.0.0 || ^17.0.0 || ^18.0.0
     dependencies:
-      '@babel/runtime': 7.23.8
+      '@babel/runtime': 7.23.9
       react: 18.2.0
     dev: false
 
@@ -12035,8 +12042,8 @@ packages:
     resolution: {integrity: sha512-nsO+KSNgo1SbJqJEYRE9ERzo7YtYbou/OqjSQKxV7jcKox7+usiUVZOAC+XnDOABXggQTno0Y1CpVnuWEc1boQ==}
     dev: false
 
-  /react-focus-lock@2.9.6(@types/react@18.2.48)(react@18.2.0):
-    resolution: {integrity: sha512-B7gYnCjHNrNYwY2juS71dHbf0+UpXXojt02svxybj8N5bxceAkzPChKEncHuratjUHkIFNCn06k2qj1DRlzTug==}
+  /react-focus-lock@2.11.1(@types/react@18.2.48)(react@18.2.0):
+    resolution: {integrity: sha512-IXLwnTBrLTlKTpASZXqqXJ8oymWrgAlOfuuDYN4XCuN1YJ72dwX198UCaF1QqGUk5C3QOnlMik//n3ufcfe8Ig==}
     peerDependencies:
       '@types/react': ^16.8.0 || ^17.0.0 || ^18.0.0
       react: ^16.8.0 || ^17.0.0 || ^18.0.0
@@ -12044,9 +12051,9 @@ packages:
       '@types/react':
         optional: true
     dependencies:
-      '@babel/runtime': 7.23.8
+      '@babel/runtime': 7.23.9
       '@types/react': 18.2.48
-      focus-lock: 1.0.0
+      focus-lock: 1.3.2
       prop-types: 15.8.1
       react: 18.2.0
       react-clientside-effect: 1.2.6(react@18.2.0)
@@ -12093,8 +12100,8 @@ packages:
       react-dom: 18.2.0(react@18.2.0)
     dev: false
 
-  /react-i18next@14.0.1(i18next@23.7.16)(react-dom@18.2.0)(react@18.2.0):
-    resolution: {integrity: sha512-TMV8hFismBmpMdIehoFHin/okfvgjFhp723RYgIqB4XyhDobVMyukyM3Z8wtTRmajyFMZrBl/OaaXF2P6WjUAw==}
+  /react-i18next@14.0.5(i18next@23.7.16)(react-dom@18.2.0)(react@18.2.0):
+    resolution: {integrity: sha512-5+bQSeEtgJrMBABBL5lO7jPdSNAbeAZ+MlFWDw//7FnVacuVu3l9EeWFzBQvZsKy+cihkbThWOAThEdH8YjGEw==}
     peerDependencies:
       i18next: '>= 23.2.3'
       react: '>= 16.8.0'
@@ -12106,7 +12113,7 @@ packages:
       react-native:
         optional: true
     dependencies:
-      '@babel/runtime': 7.23.8
+      '@babel/runtime': 7.23.9
       html-parse-stringify: 3.0.1
       i18next: 23.7.16
       react: 18.2.0
@@ -12204,6 +12211,23 @@ packages:
       react: 18.2.0
       react-style-singleton: 2.2.1(@types/react@18.2.48)(react@18.2.0)
       tslib: 2.6.2
+    dev: true
+
+  /react-remove-scroll-bar@2.3.5(@types/react@18.2.48)(react@18.2.0):
+    resolution: {integrity: sha512-3cqjOqg6s0XbOjWvmasmqHch+RLxIEk2r/70rzGXuz3iIGQsQheEQyqYCBb5EECoD01Vo2SIbDqW4paLeLTASw==}
+    engines: {node: '>=10'}
+    peerDependencies:
+      '@types/react': ^16.8.0 || ^17.0.0 || ^18.0.0
+      react: ^16.8.0 || ^17.0.0 || ^18.0.0
+    peerDependenciesMeta:
+      '@types/react':
+        optional: true
+    dependencies:
+      '@types/react': 18.2.48
+      react: 18.2.0
+      react-style-singleton: 2.2.1(@types/react@18.2.48)(react@18.2.0)
+      tslib: 2.6.2
+    dev: false
 
   /react-remove-scroll@2.5.5(@types/react@18.2.48)(react@18.2.0):
     resolution: {integrity: sha512-ImKhrzJJsyXJfBZ4bzu8Bwpka14c/fQt0k+cyFp/PBhTfyDnU5hjOtM4AG/0AMyy8oKzOTR0lDgJIM7pYXI0kw==}
@@ -12236,7 +12260,7 @@ packages:
     dependencies:
       '@types/react': 18.2.48
       react: 18.2.0
-      react-remove-scroll-bar: 2.3.4(@types/react@18.2.48)(react@18.2.0)
+      react-remove-scroll-bar: 2.3.5(@types/react@18.2.48)(react@18.2.0)
       react-style-singleton: 2.2.1(@types/react@18.2.48)(react@18.2.0)
       tslib: 2.6.2
       use-callback-ref: 1.3.1(@types/react@18.2.48)(react@18.2.0)

From a793103d7ac882c1c56c9638deeb23626d92b9fe Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 20 Feb 2024 10:42:44 +1100
Subject: [PATCH 184/411] fix(ui): get lora select working

---
 .../web/src/common/hooks/useGroupedModelCombobox.ts  | 11 ++++++-----
 .../web/src/features/lora/components/LoRACard.tsx    | 12 ++++++------
 .../web/src/features/lora/components/LoRASelect.tsx  |  8 ++++----
 3 files changed, 16 insertions(+), 15 deletions(-)

diff --git a/invokeai/frontend/web/src/common/hooks/useGroupedModelCombobox.ts b/invokeai/frontend/web/src/common/hooks/useGroupedModelCombobox.ts
index 875ce1f1c4..140cf3eaa6 100644
--- a/invokeai/frontend/web/src/common/hooks/useGroupedModelCombobox.ts
+++ b/invokeai/frontend/web/src/common/hooks/useGroupedModelCombobox.ts
@@ -2,15 +2,16 @@ import type { ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
 import type { EntityState } from '@reduxjs/toolkit';
 import { useAppSelector } from 'app/store/storeHooks';
 import type { GroupBase } from 'chakra-react-select';
+import type { ModelIdentifierWithBase } from 'features/nodes/types/common';
 import { groupBy, map, reduce } from 'lodash-es';
 import { useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
-import type { AnyModelConfig } from 'services/api/endpoints/models';
 import { getModelId } from 'services/api/endpoints/models';
+import type { AnyModelConfig } from 'services/api/types';
 
 type UseGroupedModelComboboxArg<T extends AnyModelConfig> = {
   modelEntities: EntityState<T, string> | undefined;
-  selectedModel?: Pick<T, 'base_model' | 'model_name' | 'model_type'> | null;
+  selectedModel?: ModelIdentifierWithBase | null;
   onChange: (value: T | null) => void;
   getIsDisabled?: (model: T) => boolean;
   isLoading?: boolean;
@@ -28,7 +29,7 @@ export const useGroupedModelCombobox = <T extends AnyModelConfig>(
   arg: UseGroupedModelComboboxArg<T>
 ): UseGroupedModelComboboxReturn => {
   const { t } = useTranslation();
-  const base_model = useAppSelector((s) => s.generation.model?.base_model ?? 'sdxl');
+  const base_model = useAppSelector((s) => s.generation.model?.base ?? 'sdxl');
   const { modelEntities, selectedModel, getIsDisabled, onChange, isLoading } = arg;
   const options = useMemo<GroupBase<ComboboxOption>[]>(() => {
     if (!modelEntities) {
@@ -42,8 +43,8 @@ export const useGroupedModelCombobox = <T extends AnyModelConfig>(
         acc.push({
           label,
           options: val.map((model) => ({
-            label: model.model_name,
-            value: model.id,
+            label: model.name,
+            value: model.key,
             isDisabled: getIsDisabled ? getIsDisabled(model) : false,
           })),
         });
diff --git a/invokeai/frontend/web/src/features/lora/components/LoRACard.tsx b/invokeai/frontend/web/src/features/lora/components/LoRACard.tsx
index 81e0027b2d..71ce145786 100644
--- a/invokeai/frontend/web/src/features/lora/components/LoRACard.tsx
+++ b/invokeai/frontend/web/src/features/lora/components/LoRACard.tsx
@@ -26,18 +26,18 @@ export const LoRACard = memo((props: LoRACardProps) => {
 
   const handleChange = useCallback(
     (v: number) => {
-      dispatch(loraWeightChanged({ id: lora.id, weight: v }));
+      dispatch(loraWeightChanged({ key: lora.key, weight: v }));
     },
-    [dispatch, lora.id]
+    [dispatch, lora.key]
   );
 
   const handleSetLoraToggle = useCallback(() => {
-    dispatch(loraIsEnabledChanged({ id: lora.id, isEnabled: !lora.isEnabled }));
-  }, [dispatch, lora.id, lora.isEnabled]);
+    dispatch(loraIsEnabledChanged({ key: lora.key, isEnabled: !lora.isEnabled }));
+  }, [dispatch, lora.key, lora.isEnabled]);
 
   const handleRemoveLora = useCallback(() => {
-    dispatch(loraRemoved(lora.id));
-  }, [dispatch, lora.id]);
+    dispatch(loraRemoved(lora.key));
+  }, [dispatch, lora.key]);
 
   return (
     <Card variant="lora">
diff --git a/invokeai/frontend/web/src/features/lora/components/LoRASelect.tsx b/invokeai/frontend/web/src/features/lora/components/LoRASelect.tsx
index 069c557aef..b58751ca5e 100644
--- a/invokeai/frontend/web/src/features/lora/components/LoRASelect.tsx
+++ b/invokeai/frontend/web/src/features/lora/components/LoRASelect.tsx
@@ -7,8 +7,8 @@ import { useGroupedModelCombobox } from 'common/hooks/useGroupedModelCombobox';
 import { loraAdded, selectLoraSlice } from 'features/lora/store/loraSlice';
 import { memo, useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
-import type { LoRAConfig } from 'services/api/endpoints/models';
 import { useGetLoRAModelsQuery } from 'services/api/endpoints/models';
+import type { LoRAConfig } from 'services/api/types';
 
 const selectAddedLoRAs = createMemoizedSelector(selectLoraSlice, (lora) => lora.loras);
 
@@ -17,11 +17,11 @@ const LoRASelect = () => {
   const { data, isLoading } = useGetLoRAModelsQuery();
   const { t } = useTranslation();
   const addedLoRAs = useAppSelector(selectAddedLoRAs);
-  const currentBaseModel = useAppSelector((s) => s.generation.model?.base_model);
+  const currentBaseModel = useAppSelector((s) => s.generation.model?.base);
 
   const getIsDisabled = (lora: LoRAConfig): boolean => {
-    const isCompatible = currentBaseModel === lora.base_model;
-    const isAdded = Boolean(addedLoRAs[lora.id]);
+    const isCompatible = currentBaseModel === lora.base;
+    const isAdded = Boolean(addedLoRAs[lora.key]);
     const hasMainModel = Boolean(currentBaseModel);
     return !hasMainModel || !isCompatible || isAdded;
   };

From f870f810d5a068769fff893f16196b964119f42e Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 20 Feb 2024 10:45:05 +1100
Subject: [PATCH 185/411] fix(ui): get embedding select working

---
 .../frontend/web/src/features/embedding/EmbeddingSelect.tsx   | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/invokeai/frontend/web/src/features/embedding/EmbeddingSelect.tsx b/invokeai/frontend/web/src/features/embedding/EmbeddingSelect.tsx
index 426ddd21e2..fd05edc466 100644
--- a/invokeai/frontend/web/src/features/embedding/EmbeddingSelect.tsx
+++ b/invokeai/frontend/web/src/features/embedding/EmbeddingSelect.tsx
@@ -18,7 +18,7 @@ export const EmbeddingSelect = memo(({ onSelect, onClose }: EmbeddingSelectProps
 
   const getIsDisabled = useCallback(
     (embedding: TextualInversionConfig): boolean => {
-      const isCompatible = currentBaseModel === embedding.base_model;
+      const isCompatible = currentBaseModel === embedding.base;
       const hasMainModel = Boolean(currentBaseModel);
       return !hasMainModel || !isCompatible;
     },
@@ -31,7 +31,7 @@ export const EmbeddingSelect = memo(({ onSelect, onClose }: EmbeddingSelectProps
       if (!embedding) {
         return;
       }
-      onSelect(embedding.model_name);
+      onSelect(embedding.key);
     },
     [onSelect]
   );

From e7e3045a8ac1ed714cf4ccbb6ae16a9f3e3958ed Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 20 Feb 2024 11:14:08 +1100
Subject: [PATCH 186/411] fix(ui): get vae model select working

---
 .../common/hooks/useGroupedModelCombobox.ts    |  4 +---
 .../web/src/common/hooks/useModelCombobox.ts   | 12 ++++++------
 .../VAEModel/ParamVAEModelSelect.tsx           | 18 ++++++++++--------
 .../web/src/services/api/endpoints/models.ts   |  3 ---
 4 files changed, 17 insertions(+), 20 deletions(-)

diff --git a/invokeai/frontend/web/src/common/hooks/useGroupedModelCombobox.ts b/invokeai/frontend/web/src/common/hooks/useGroupedModelCombobox.ts
index 140cf3eaa6..fc5bc455ee 100644
--- a/invokeai/frontend/web/src/common/hooks/useGroupedModelCombobox.ts
+++ b/invokeai/frontend/web/src/common/hooks/useGroupedModelCombobox.ts
@@ -6,7 +6,6 @@ import type { ModelIdentifierWithBase } from 'features/nodes/types/common';
 import { groupBy, map, reduce } from 'lodash-es';
 import { useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
-import { getModelId } from 'services/api/endpoints/models';
 import type { AnyModelConfig } from 'services/api/types';
 
 type UseGroupedModelComboboxArg<T extends AnyModelConfig> = {
@@ -58,8 +57,7 @@ export const useGroupedModelCombobox = <T extends AnyModelConfig>(
 
   const value = useMemo(
     () =>
-      options.flatMap((o) => o.options).find((m) => (selectedModel ? m.value === getModelId(selectedModel) : false)) ??
-      null,
+      options.flatMap((o) => o.options).find((m) => (selectedModel ? m.value === selectedModel.key : false)) ?? null,
     [options, selectedModel]
   );
 
diff --git a/invokeai/frontend/web/src/common/hooks/useModelCombobox.ts b/invokeai/frontend/web/src/common/hooks/useModelCombobox.ts
index 07e6aeb34c..e0718d6413 100644
--- a/invokeai/frontend/web/src/common/hooks/useModelCombobox.ts
+++ b/invokeai/frontend/web/src/common/hooks/useModelCombobox.ts
@@ -1,14 +1,14 @@
 import type { ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
 import type { EntityState } from '@reduxjs/toolkit';
+import type { ModelIdentifierWithBase } from 'features/nodes/types/common';
 import { map } from 'lodash-es';
 import { useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
-import type { AnyModelConfig } from 'services/api/endpoints/models';
-import { getModelId } from 'services/api/endpoints/models';
+import type { AnyModelConfig } from 'services/api/types';
 
 type UseModelComboboxArg<T extends AnyModelConfig> = {
   modelEntities: EntityState<T, string> | undefined;
-  selectedModel?: Pick<T, 'base_model' | 'model_name' | 'model_type'> | null;
+  selectedModel?: ModelIdentifierWithBase | null;
   onChange: (value: T | null) => void;
   getIsDisabled?: (model: T) => boolean;
   optionsFilter?: (model: T) => boolean;
@@ -33,14 +33,14 @@ export const useModelCombobox = <T extends AnyModelConfig>(arg: UseModelCombobox
     return map(modelEntities.entities)
       .filter(optionsFilter)
       .map((model) => ({
-        label: model.model_name,
-        value: model.id,
+        label: model.name,
+        value: model.key,
         isDisabled: getIsDisabled ? getIsDisabled(model) : false,
       }));
   }, [optionsFilter, getIsDisabled, modelEntities]);
 
   const value = useMemo(
-    () => options.find((m) => (selectedModel ? m.value === getModelId(selectedModel) : false)),
+    () => options.find((m) => (selectedModel ? m.value === selectedModel.key : false)),
     [options, selectedModel]
   );
 
diff --git a/invokeai/frontend/web/src/features/parameters/components/VAEModel/ParamVAEModelSelect.tsx b/invokeai/frontend/web/src/features/parameters/components/VAEModel/ParamVAEModelSelect.tsx
index cc0164153d..1810c3ff68 100644
--- a/invokeai/frontend/web/src/features/parameters/components/VAEModel/ParamVAEModelSelect.tsx
+++ b/invokeai/frontend/web/src/features/parameters/components/VAEModel/ParamVAEModelSelect.tsx
@@ -7,8 +7,8 @@ import { selectGenerationSlice, vaeSelected } from 'features/parameters/store/ge
 import { pick } from 'lodash-es';
 import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
-import type { VAEConfig } from 'services/api/endpoints/models';
 import { useGetVaeModelsQuery } from 'services/api/endpoints/models';
+import type { VAEConfig } from 'services/api/types';
 
 const selector = createMemoizedSelector(selectGenerationSlice, (generation) => {
   const { model, vae } = generation;
@@ -22,25 +22,27 @@ const ParamVAEModelSelect = () => {
   const { data, isLoading } = useGetVaeModelsQuery();
   const getIsDisabled = useCallback(
     (vae: VAEConfig): boolean => {
-      const isCompatible = model?.base_model === vae.base_model;
-      const hasMainModel = Boolean(model?.base_model);
+      const isCompatible = model?.base === vae.base;
+      const hasMainModel = Boolean(model?.base);
       return !hasMainModel || !isCompatible;
     },
-    [model?.base_model]
+    [model?.base]
   );
   const _onChange = useCallback(
     (vae: VAEConfig | null) => {
-      dispatch(vaeSelected(vae ? pick(vae, 'base_model', 'model_name') : null));
+      dispatch(vaeSelected(vae ? pick(vae, 'key', 'base') : null));
     },
     [dispatch]
   );
-  const { options, value, onChange, placeholder, noOptionsMessage } = useGroupedModelCombobox({
+  const { options, value, onChange, noOptionsMessage } = useGroupedModelCombobox({
     modelEntities: data,
     onChange: _onChange,
-    selectedModel: vae ? { ...vae, model_type: 'vae' } : null,
+    selectedModel: vae ? pick(vae, 'key', 'base') : null,
     isLoading,
     getIsDisabled,
   });
+  
+  console.log(value)
 
   return (
     <FormControl isDisabled={!options.length} isInvalid={!options.length}>
@@ -50,7 +52,7 @@ const ParamVAEModelSelect = () => {
       <Combobox
         isClearable
         value={value}
-        placeholder={value ? placeholder : t('models.defaultVAE')}
+        placeholder={value ? value.value : t('models.defaultVAE')}
         options={options}
         onChange={onChange}
         noOptionsMessage={noOptionsMessage}
diff --git a/invokeai/frontend/web/src/services/api/endpoints/models.ts b/invokeai/frontend/web/src/services/api/endpoints/models.ts
index 57cf7dacfc..46be42d9e5 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/models.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/models.ts
@@ -21,9 +21,6 @@ import type {
 import type { ApiTagDescription, tagTypes } from '..';
 import { api, buildV2Url, LIST_TAG } from '..';
 
-/* eslint-disable @typescript-eslint/no-explicit-any */
-export const getModelId = (input: any): any => input;
-
 type UpdateMainModelArg = {
   base_model: BaseModelType;
   model_name: string;

From e771c5f4670896570b4ae90647c0544a7571b5a2 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 20 Feb 2024 11:16:17 +1100
Subject: [PATCH 187/411] fix(ui): get refiner model select working

---
 .../SDXLRefiner/ParamSDXLRefinerModelSelect.tsx     | 13 ++++---------
 1 file changed, 4 insertions(+), 9 deletions(-)

diff --git a/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerModelSelect.tsx b/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerModelSelect.tsx
index 4c54251557..e5978ca21b 100644
--- a/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerModelSelect.tsx
+++ b/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerModelSelect.tsx
@@ -4,15 +4,16 @@ import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { useModelCombobox } from 'common/hooks/useModelCombobox';
 import { refinerModelChanged, selectSdxlSlice } from 'features/sdxl/store/sdxlSlice';
+import { pick } from 'lodash-es';
 import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 import { REFINER_BASE_MODELS } from 'services/api/constants';
-import type { MainModelConfig } from 'services/api/endpoints/models';
 import { useGetMainModelsQuery } from 'services/api/endpoints/models';
+import type { MainModelConfig } from 'services/api/types';
 
 const selectModel = createMemoizedSelector(selectSdxlSlice, (sdxl) => sdxl.refinerModel);
 
-const optionsFilter = (model: MainModelConfig) => model.base_model === 'sdxl-refiner';
+const optionsFilter = (model: MainModelConfig) => model.base === 'sdxl-refiner';
 
 const ParamSDXLRefinerModelSelect = () => {
   const dispatch = useAppDispatch();
@@ -25,13 +26,7 @@ const ParamSDXLRefinerModelSelect = () => {
         dispatch(refinerModelChanged(null));
         return;
       }
-      dispatch(
-        refinerModelChanged({
-          base_model: 'sdxl-refiner',
-          model_name: model.model_name,
-          model_type: model.model_type,
-        })
-      );
+      dispatch(refinerModelChanged(pick(model, ['key', 'base'])));
     },
     [dispatch]
   );

From 8afe328af08eb8a68070d75ee87e93bd6c5daf9a Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 20 Feb 2024 11:32:58 +1100
Subject: [PATCH 188/411] fix(ui): get workflow editor model selects working

---
 .../inputs/ControlNetModelFieldInputComponent.tsx    |  5 +++--
 .../inputs/IPAdapterModelFieldInputComponent.tsx     |  5 +++--
 .../fields/inputs/LoRAModelFieldInputComponent.tsx   |  5 +++--
 .../fields/inputs/MainModelFieldInputComponent.tsx   |  2 +-
 .../inputs/RefinerModelFieldInputComponent.tsx       |  2 +-
 .../inputs/SDXLMainModelFieldInputComponent.tsx      |  2 +-
 .../inputs/T2IAdapterModelFieldInputComponent.tsx    |  5 +++--
 .../fields/inputs/VAEModelFieldInputComponent.tsx    |  5 +++--
 .../frontend/web/src/features/nodes/types/common.ts  | 12 ++++++------
 9 files changed, 24 insertions(+), 19 deletions(-)

diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/ControlNetModelFieldInputComponent.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/ControlNetModelFieldInputComponent.tsx
index 53d800e7b6..1951ec60d3 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/ControlNetModelFieldInputComponent.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/ControlNetModelFieldInputComponent.tsx
@@ -3,9 +3,10 @@ import { useAppDispatch } from 'app/store/storeHooks';
 import { useGroupedModelCombobox } from 'common/hooks/useGroupedModelCombobox';
 import { fieldControlNetModelValueChanged } from 'features/nodes/store/nodesSlice';
 import type { ControlNetModelFieldInputInstance, ControlNetModelFieldInputTemplate } from 'features/nodes/types/field';
+import { pick } from 'lodash-es';
 import { memo, useCallback } from 'react';
-import type { ControlNetConfig } from 'services/api/endpoints/models';
 import { useGetControlNetModelsQuery } from 'services/api/endpoints/models';
+import type { ControlNetConfig } from 'services/api/types';
 
 import type { FieldComponentProps } from './types';
 
@@ -35,7 +36,7 @@ const ControlNetModelFieldInputComponent = (props: Props) => {
   const { options, value, onChange, placeholder, noOptionsMessage } = useGroupedModelCombobox({
     modelEntities: data,
     onChange: _onChange,
-    selectedModel: field.value ? { ...field.value, model_type: 'controlnet' } : undefined,
+    selectedModel: field.value ? pick(field.value, ['key', 'base']) : undefined,
     isLoading,
   });
 
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/IPAdapterModelFieldInputComponent.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/IPAdapterModelFieldInputComponent.tsx
index 3f195ceb32..137f751fca 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/IPAdapterModelFieldInputComponent.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/IPAdapterModelFieldInputComponent.tsx
@@ -3,9 +3,10 @@ import { useAppDispatch } from 'app/store/storeHooks';
 import { useGroupedModelCombobox } from 'common/hooks/useGroupedModelCombobox';
 import { fieldIPAdapterModelValueChanged } from 'features/nodes/store/nodesSlice';
 import type { IPAdapterModelFieldInputInstance, IPAdapterModelFieldInputTemplate } from 'features/nodes/types/field';
+import { pick } from 'lodash-es';
 import { memo, useCallback } from 'react';
-import type { IPAdapterConfig } from 'services/api/endpoints/models';
 import { useGetIPAdapterModelsQuery } from 'services/api/endpoints/models';
+import type { IPAdapterConfig } from 'services/api/types';
 
 import type { FieldComponentProps } from './types';
 
@@ -35,7 +36,7 @@ const IPAdapterModelFieldInputComponent = (
   const { options, value, onChange } = useGroupedModelCombobox({
     modelEntities: ipAdapterModels,
     onChange: _onChange,
-    selectedModel: field.value ? { ...field.value, model_type: 'ip_adapter' } : undefined,
+    selectedModel: field.value ? pick(field.value, ['key', 'base']) : undefined,
   });
 
   return (
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/LoRAModelFieldInputComponent.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/LoRAModelFieldInputComponent.tsx
index eeb07fa08e..5f6318de9e 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/LoRAModelFieldInputComponent.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/LoRAModelFieldInputComponent.tsx
@@ -3,9 +3,10 @@ import { useAppDispatch } from 'app/store/storeHooks';
 import { useGroupedModelCombobox } from 'common/hooks/useGroupedModelCombobox';
 import { fieldLoRAModelValueChanged } from 'features/nodes/store/nodesSlice';
 import type { LoRAModelFieldInputInstance, LoRAModelFieldInputTemplate } from 'features/nodes/types/field';
+import { pick } from 'lodash-es';
 import { memo, useCallback } from 'react';
-import type { LoRAConfig } from 'services/api/endpoints/models';
 import { useGetLoRAModelsQuery } from 'services/api/endpoints/models';
+import type { LoRAConfig } from 'services/api/types';
 
 import type { FieldComponentProps } from './types';
 
@@ -34,7 +35,7 @@ const LoRAModelFieldInputComponent = (props: Props) => {
   const { options, value, onChange, placeholder, noOptionsMessage } = useGroupedModelCombobox({
     modelEntities: data,
     onChange: _onChange,
-    selectedModel: field.value ? { ...field.value, model_type: 'lora' } : undefined,
+    selectedModel: field.value ? pick(field.value, ['key', 'base']) : undefined,
     isLoading,
   });
 
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/MainModelFieldInputComponent.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/MainModelFieldInputComponent.tsx
index 7ddde08816..1cb0658b81 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/MainModelFieldInputComponent.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/MainModelFieldInputComponent.tsx
@@ -6,8 +6,8 @@ import { fieldMainModelValueChanged } from 'features/nodes/store/nodesSlice';
 import type { MainModelFieldInputInstance, MainModelFieldInputTemplate } from 'features/nodes/types/field';
 import { memo, useCallback } from 'react';
 import { NON_SDXL_MAIN_MODELS } from 'services/api/constants';
-import type { MainModelConfig } from 'services/api/endpoints/models';
 import { useGetMainModelsQuery } from 'services/api/endpoints/models';
+import type { MainModelConfig } from 'services/api/types';
 
 import type { FieldComponentProps } from './types';
 
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/RefinerModelFieldInputComponent.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/RefinerModelFieldInputComponent.tsx
index 9b5a1138d4..be2b4a4d4f 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/RefinerModelFieldInputComponent.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/RefinerModelFieldInputComponent.tsx
@@ -9,8 +9,8 @@ import type {
 } from 'features/nodes/types/field';
 import { memo, useCallback } from 'react';
 import { REFINER_BASE_MODELS } from 'services/api/constants';
-import type { MainModelConfig } from 'services/api/endpoints/models';
 import { useGetMainModelsQuery } from 'services/api/endpoints/models';
+import type { MainModelConfig } from 'services/api/types';
 
 import type { FieldComponentProps } from './types';
 
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/SDXLMainModelFieldInputComponent.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/SDXLMainModelFieldInputComponent.tsx
index cf353619e8..d0d7754606 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/SDXLMainModelFieldInputComponent.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/SDXLMainModelFieldInputComponent.tsx
@@ -6,8 +6,8 @@ import { fieldMainModelValueChanged } from 'features/nodes/store/nodesSlice';
 import type { SDXLMainModelFieldInputInstance, SDXLMainModelFieldInputTemplate } from 'features/nodes/types/field';
 import { memo, useCallback } from 'react';
 import { SDXL_MAIN_MODELS } from 'services/api/constants';
-import type { MainModelConfig } from 'services/api/endpoints/models';
 import { useGetMainModelsQuery } from 'services/api/endpoints/models';
+import type { MainModelConfig } from 'services/api/types';
 
 import type { FieldComponentProps } from './types';
 
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/T2IAdapterModelFieldInputComponent.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/T2IAdapterModelFieldInputComponent.tsx
index 8402c56343..9115f22c14 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/T2IAdapterModelFieldInputComponent.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/T2IAdapterModelFieldInputComponent.tsx
@@ -3,9 +3,10 @@ import { useAppDispatch } from 'app/store/storeHooks';
 import { useGroupedModelCombobox } from 'common/hooks/useGroupedModelCombobox';
 import { fieldT2IAdapterModelValueChanged } from 'features/nodes/store/nodesSlice';
 import type { T2IAdapterModelFieldInputInstance, T2IAdapterModelFieldInputTemplate } from 'features/nodes/types/field';
+import { pick } from 'lodash-es';
 import { memo, useCallback } from 'react';
-import type { T2IAdapterConfig } from 'services/api/endpoints/models';
 import { useGetT2IAdapterModelsQuery } from 'services/api/endpoints/models';
+import type { T2IAdapterConfig } from 'services/api/types';
 
 import type { FieldComponentProps } from './types';
 
@@ -36,7 +37,7 @@ const T2IAdapterModelFieldInputComponent = (
   const { options, value, onChange } = useGroupedModelCombobox({
     modelEntities: t2iAdapterModels,
     onChange: _onChange,
-    selectedModel: field.value ? { ...field.value, model_type: 't2i_adapter' } : undefined,
+    selectedModel: field.value ? pick(field.value, ['key', 'base']) : undefined,
   });
 
   return (
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/VAEModelFieldInputComponent.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/VAEModelFieldInputComponent.tsx
index af09f2d8f2..87272f48b9 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/VAEModelFieldInputComponent.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/VAEModelFieldInputComponent.tsx
@@ -4,9 +4,10 @@ import { useGroupedModelCombobox } from 'common/hooks/useGroupedModelCombobox';
 import { SyncModelsIconButton } from 'features/modelManager/components/SyncModels/SyncModelsIconButton';
 import { fieldVaeModelValueChanged } from 'features/nodes/store/nodesSlice';
 import type { VAEModelFieldInputInstance, VAEModelFieldInputTemplate } from 'features/nodes/types/field';
+import { pick } from 'lodash-es';
 import { memo, useCallback } from 'react';
-import type { VAEConfig } from 'services/api/endpoints/models';
 import { useGetVaeModelsQuery } from 'services/api/endpoints/models';
+import type { VAEConfig } from 'services/api/types';
 
 import type { FieldComponentProps } from './types';
 
@@ -34,7 +35,7 @@ const VAEModelFieldInputComponent = (props: Props) => {
   const { options, value, onChange, placeholder, noOptionsMessage } = useGroupedModelCombobox({
     modelEntities: data,
     onChange: _onChange,
-    selectedModel: field.value ? { ...field.value, model_type: 'vae' } : null,
+    selectedModel: field.value ? pick(field.value, ['key', 'base']) : null,
     isLoading,
   });
 
diff --git a/invokeai/frontend/web/src/features/nodes/types/common.ts b/invokeai/frontend/web/src/features/nodes/types/common.ts
index 891bd29bc8..d5d04deaa5 100644
--- a/invokeai/frontend/web/src/features/nodes/types/common.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/common.ts
@@ -73,7 +73,7 @@ export type BaseModel = z.infer<typeof zBaseModel>;
 export type ModelType = z.infer<typeof zModelType>;
 export type ModelIdentifier = z.infer<typeof zModelIdentifier>;
 export type ModelIdentifierWithBase = z.infer<typeof zModelIdentifierWithBase>;
-export const zMainModelField = zModelFieldBase;
+export const zMainModelField = zModelIdentifierWithBase;
 export type MainModelField = z.infer<typeof zMainModelField>;
 
 export const zSDXLRefinerModelField = zModelIdentifier;
@@ -93,23 +93,23 @@ export const zSubModelType = z.enum([
 ]);
 export type SubModelType = z.infer<typeof zSubModelType>;
 
-export const zVAEModelField = zModelFieldBase;
+export const zVAEModelField = zModelIdentifierWithBase;
 
 export const zModelInfo = zModelIdentifier.extend({
   submodel_type: zSubModelType.nullish(),
 });
 export type ModelInfo = z.infer<typeof zModelInfo>;
 
-export const zLoRAModelField = zModelFieldBase;
+export const zLoRAModelField = zModelIdentifierWithBase;
 export type LoRAModelField = z.infer<typeof zLoRAModelField>;
 
-export const zControlNetModelField = zModelFieldBase;
+export const zControlNetModelField = zModelIdentifierWithBase;
 export type ControlNetModelField = z.infer<typeof zControlNetModelField>;
 
-export const zIPAdapterModelField = zModelFieldBase;
+export const zIPAdapterModelField = zModelIdentifierWithBase;
 export type IPAdapterModelField = z.infer<typeof zIPAdapterModelField>;
 
-export const zT2IAdapterModelField = zModelFieldBase;
+export const zT2IAdapterModelField = zModelIdentifierWithBase;
 export type T2IAdapterModelField = z.infer<typeof zT2IAdapterModelField>;
 
 export const zLoraInfo = zModelInfo.extend({

From 812e24cbd271dd0cf7b84bf0eb87bdedcde581f2 Mon Sep 17 00:00:00 2001
From: Stefan Tobler <toblerlstefan@gmail.com>
Date: Sun, 7 Jan 2024 19:54:58 -0500
Subject: [PATCH 189/411] groundwork for the bulk_download_service

---
 .../app/services/bulk_download/__init__.py    |  0
 .../bulk_download/bulk_download_base.py       | 32 +++++++++++++++++++
 .../bulk_download/bulk_download_common.py     | 21 ++++++++++++
 3 files changed, 53 insertions(+)
 create mode 100644 invokeai/app/services/bulk_download/__init__.py
 create mode 100644 invokeai/app/services/bulk_download/bulk_download_base.py
 create mode 100644 invokeai/app/services/bulk_download/bulk_download_common.py

diff --git a/invokeai/app/services/bulk_download/__init__.py b/invokeai/app/services/bulk_download/__init__.py
new file mode 100644
index 0000000000..e69de29bb2
diff --git a/invokeai/app/services/bulk_download/bulk_download_base.py b/invokeai/app/services/bulk_download/bulk_download_base.py
new file mode 100644
index 0000000000..54c8771437
--- /dev/null
+++ b/invokeai/app/services/bulk_download/bulk_download_base.py
@@ -0,0 +1,32 @@
+from pathlib import Path
+from typing import Optional, Union
+
+from abc import ABC, abstractmethod
+
+from invokeai.app.services.events.events_base import EventServiceBase
+from invokeai.app.services.invoker import Invoker
+
+class BulkDownloadBase(ABC):
+
+    @abstractmethod
+    def __init__(
+        self,
+        output_folder: Union[str, Path],
+        event_bus: Optional["EventServiceBase"] = None,
+    ):
+        """
+        Create BulkDownloadBase object.
+
+        :param output_folder: The path to the output folder where the bulk download files can be temporarily stored.
+        :param event_bus: InvokeAI event bus for reporting events to.
+        """
+
+    @abstractmethod
+    def start(self, invoker: Invoker, image_names: list[str], board_id: Optional[str]) -> str:
+        """
+        Starts a a bulk download job.
+        
+        :param invoker: The Invoker that holds all the services, required to be passed as a parameter to avoid circular dependencies.
+        :param image_names: A list of image names to include in the zip file.
+        :param board_id: The ID of the board. If provided, all images associated with the board will be included in the zip file.
+        """
\ No newline at end of file
diff --git a/invokeai/app/services/bulk_download/bulk_download_common.py b/invokeai/app/services/bulk_download/bulk_download_common.py
new file mode 100644
index 0000000000..3ac1f5bba8
--- /dev/null
+++ b/invokeai/app/services/bulk_download/bulk_download_common.py
@@ -0,0 +1,21 @@
+
+class BulkDownloadException(Exception):
+    """Exception raised when a bulk download fails."""
+
+    def __init__(self, message="Bulk download failed"):
+        super().__init__(message)
+        self.message = message
+
+class BulkDownloadTargetException(BulkDownloadException):
+    """Exception raised when a bulk download target is not found."""
+
+    def __init__(self, message="The bulk download target was not found"):
+        super().__init__(message)
+        self.message = message
+
+class BulkDownloadParametersException(BulkDownloadException):
+    """Exception raised when a bulk download parameter is invalid."""
+
+    def __init__(self, message="The bulk download parameters are invalid, either an array of image names or a board id must be provided"):
+        super().__init__(message)
+        self.message = message
\ No newline at end of file

From f1967c339305a7df0089e81cd4966e5ca29db775 Mon Sep 17 00:00:00 2001
From: Stefan Tobler <toblerlstefan@gmail.com>
Date: Sun, 7 Jan 2024 19:55:59 -0500
Subject: [PATCH 190/411] adding socket events for bulk download

---
 invokeai/app/api/sockets.py                 | 30 ++++++++++++++++++--
 invokeai/app/services/events/events_base.py | 31 +++++++++++++++++++++
 2 files changed, 59 insertions(+), 2 deletions(-)

diff --git a/invokeai/app/api/sockets.py b/invokeai/app/api/sockets.py
index e651e43559..c5d9ace8d2 100644
--- a/invokeai/app/api/sockets.py
+++ b/invokeai/app/api/sockets.py
@@ -12,16 +12,27 @@ class SocketIO:
     __sio: AsyncServer
     __app: ASGIApp
 
+    __sub_queue: str = "subscribe_queue"
+    __unsub_queue: str = "unsubscribe_queue"
+
+    __sub_bulk_download: str = "subscribe_bulk_download"
+    __unsub_bulk_download: str = "unsubscribe_bulk_download"
+
+
     def __init__(self, app: FastAPI):
         self.__sio = AsyncServer(async_mode="asgi", cors_allowed_origins="*")
         self.__app = ASGIApp(socketio_server=self.__sio, socketio_path="/ws/socket.io")
         app.mount("/ws", self.__app)
 
-        self.__sio.on("subscribe_queue", handler=self._handle_sub_queue)
-        self.__sio.on("unsubscribe_queue", handler=self._handle_unsub_queue)
+        self.__sio.on(self.__sub_queue, handler=self._handle_sub_queue)
+        self.__sio.on(self.__unsub_queue, handler=self._handle_unsub_queue)
         local_handler.register(event_name=EventServiceBase.queue_event, _func=self._handle_queue_event)
         local_handler.register(event_name=EventServiceBase.model_event, _func=self._handle_model_event)
 
+        self.__sio.on(self.__sub_bulk_download, handler=self._handle_sub_bulk_download)
+        self.__sio.on(self.__unsub_bulk_download, handler=self._handle_unsub_bulk_download)
+        local_handler.register(event_name=EventServiceBase.bulk_download_event, _func=self._handle_bulk_download_event)
+
     async def _handle_queue_event(self, event: Event):
         await self.__sio.emit(
             event=event[1]["event"],
@@ -39,3 +50,18 @@ class SocketIO:
 
     async def _handle_model_event(self, event: Event) -> None:
         await self.__sio.emit(event=event[1]["event"], data=event[1]["data"])
+
+    async def _handle_bulk_download_event(self, event: Event):
+        await self.__sio.emit(
+            event=event[1]["event"],
+            data=event[1]["data"],
+            room=event[1]["data"]["bulk_download_id"],
+        )
+
+    async def _handle_sub_bulk_download(self, sid, data, *args, **kwargs):
+        if "bulk_download_id" in data:
+            await self.__sio.enter_room(sid, data["bulk_download_id"])
+
+    async def _handle_unsub_bulk_download(self, sid, data, *args, **kwargs):
+        if "bulk_download_id" in data:
+            await self.__sio.leave_room(sid, data["bulk_download_id"])
diff --git a/invokeai/app/services/events/events_base.py b/invokeai/app/services/events/events_base.py
index 5355fe2298..0a0668b274 100644
--- a/invokeai/app/services/events/events_base.py
+++ b/invokeai/app/services/events/events_base.py
@@ -16,6 +16,7 @@ from invokeai.backend.model_manager import AnyModelConfig
 
 class EventServiceBase:
     queue_event: str = "queue_event"
+    bulk_download_event: str = "bulk_download_event"
     download_event: str = "download_event"
     model_event: str = "model_event"
 
@@ -24,6 +25,14 @@ class EventServiceBase:
     def dispatch(self, event_name: str, payload: Any) -> None:
         pass
 
+    def _emit_bulk_download_event(self, event_name: str, payload: dict) -> None:
+        """Bulk download events are emitted to a room with queue_id as the room name"""
+        payload["timestamp"] = get_timestamp()
+        self.dispatch(
+            event_name=EventServiceBase.bulk_download_event,
+            payload={"event": event_name, "data": payload},
+        )
+
     def __emit_queue_event(self, event_name: str, payload: dict) -> None:
         """Queue events are emitted to a room with queue_id as the room name"""
         payload["timestamp"] = get_timestamp()
@@ -430,3 +439,25 @@ class EventServiceBase:
                 "error": error,
             },
         )
+
+    def emit_bulk_download_started(self, bulk_download_id: str) -> None:
+        """Emitted when a bulk download starts"""
+        self._emit_bulk_download_event(
+            event_name="bulk_download_started",
+            payload={"bulk_download_id": bulk_download_id, }
+        )
+    
+    def emit_bulk_download_completed(self, bulk_download_id: str, file_path: str) -> None:
+        """Emitted when a bulk download completes"""
+        self._emit_bulk_download_event(
+            event_name="bulk_download_completed",
+            payload={"bulk_download_id": bulk_download_id,
+                    "file_path": file_path}
+        )
+    
+    def emit_bulk_download_failed(self, bulk_download_id: str, error: str) -> None:
+        """Emitted when a bulk download fails"""
+        self._emit_bulk_download_event(
+            event_name="bulk_download_failed",
+            payload={"bulk_download_id": bulk_download_id, "error": error}
+        )

From 56d2d220a812990a0b28305e2df3153331f913db Mon Sep 17 00:00:00 2001
From: Stefan Tobler <toblerlstefan@gmail.com>
Date: Sun, 7 Jan 2024 21:29:42 -0500
Subject: [PATCH 191/411] implementation of bulkdownload background task

---
 invokeai/app/api/dependencies.py              |   3 +
 invokeai/app/api/routers/images.py            |  14 ++-
 .../bulk_download/bulk_download_base.py       |   2 +-
 .../bulk_download/bulk_download_defauilt.py   | 114 ++++++++++++++++++
 invokeai/app/services/invocation_services.py  |   3 +
 5 files changed, 130 insertions(+), 6 deletions(-)
 create mode 100644 invokeai/app/services/bulk_download/bulk_download_defauilt.py

diff --git a/invokeai/app/api/dependencies.py b/invokeai/app/api/dependencies.py
index a9132516a8..ab09d1e5d7 100644
--- a/invokeai/app/api/dependencies.py
+++ b/invokeai/app/api/dependencies.py
@@ -15,6 +15,7 @@ from ..services.board_image_records.board_image_records_sqlite import SqliteBoar
 from ..services.board_images.board_images_default import BoardImagesService
 from ..services.board_records.board_records_sqlite import SqliteBoardRecordStorage
 from ..services.boards.boards_default import BoardService
+from ..services.bulk_download.bulk_download_defauilt import BulkDownloadService
 from ..services.config import InvokeAIAppConfig
 from ..services.download import DownloadQueueService
 from ..services.image_files.image_files_disk import DiskImageFileStorage
@@ -81,6 +82,7 @@ class ApiDependencies:
         board_records = SqliteBoardRecordStorage(db=db)
         boards = BoardService()
         events = FastAPIEventService(event_handler_id)
+        bulk_download = BulkDownloadService(output_folder=f"{output_folder}", event_bus=events)
         image_records = SqliteImageRecordStorage(db=db)
         images = ImageService()
         invocation_cache = MemoryInvocationCache(max_cache_size=config.node_cache_size)
@@ -110,6 +112,7 @@ class ApiDependencies:
             board_images=board_images,
             board_records=board_records,
             boards=boards,
+            bulk_download=bulk_download,
             configuration=configuration,
             events=events,
             image_files=image_files,
diff --git a/invokeai/app/api/routers/images.py b/invokeai/app/api/routers/images.py
index cc60ad1be8..2a8e1e7ec7 100644
--- a/invokeai/app/api/routers/images.py
+++ b/invokeai/app/api/routers/images.py
@@ -2,7 +2,7 @@ import io
 import traceback
 from typing import Optional
 
-from fastapi import Body, HTTPException, Path, Query, Request, Response, UploadFile
+from fastapi import BackgroundTasks, Body, HTTPException, Path, Query, Request, Response, UploadFile
 from fastapi.responses import FileResponse
 from fastapi.routing import APIRouter
 from PIL import Image
@@ -10,6 +10,7 @@ from pydantic import BaseModel, Field, ValidationError
 
 from invokeai.app.invocations.fields import MetadataField, MetadataFieldValidator
 from invokeai.app.services.image_records.image_records_common import ImageCategory, ImageRecordChanges, ResourceOrigin
+from invokeai.app.services.board_records.board_records_common import BoardRecordNotFoundException
 from invokeai.app.services.images.images_common import ImageDTO, ImageUrlsDTO
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
 from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID, WorkflowWithoutIDValidator
@@ -372,19 +373,22 @@ async def unstar_images_in_list(
     except Exception:
         raise HTTPException(status_code=500, detail="Failed to unstar images")
 
-
 class ImagesDownloaded(BaseModel):
     response: Optional[str] = Field(
         description="If defined, the message to display to the user when images begin downloading"
     )
 
 
-@images_router.post("/download", operation_id="download_images_from_list", response_model=ImagesDownloaded)
+@images_router.post("/download", operation_id="download_images_from_list", response_model=ImagesDownloaded, status_code=202)
 async def download_images_from_list(
+    background_tasks: BackgroundTasks,
     image_names: list[str] = Body(description="The list of names of images to download", embed=True),
     board_id: Optional[str] = Body(
         default=None, description="The board from which image should be downloaded from", embed=True
     ),
 ) -> ImagesDownloaded:
-    # return ImagesDownloaded(response="Your images are downloading")
-    raise HTTPException(status_code=501, detail="Endpoint is not yet implemented")
+    if (image_names is None or len(image_names) == 0) and board_id is None:
+        raise HTTPException(status_code=400, detail="No images or board id specified.")
+    background_tasks.add_task(ApiDependencies.invoker.services.bulk_download.handler, ApiDependencies.invoker, image_names, board_id)
+    return ImagesDownloaded(response="Your images are preparing to be downloaded")
+    
diff --git a/invokeai/app/services/bulk_download/bulk_download_base.py b/invokeai/app/services/bulk_download/bulk_download_base.py
index 54c8771437..b788020bba 100644
--- a/invokeai/app/services/bulk_download/bulk_download_base.py
+++ b/invokeai/app/services/bulk_download/bulk_download_base.py
@@ -22,7 +22,7 @@ class BulkDownloadBase(ABC):
         """
 
     @abstractmethod
-    def start(self, invoker: Invoker, image_names: list[str], board_id: Optional[str]) -> str:
+    def handler(self, invoker: Invoker, image_names: list[str], board_id: Optional[str]) -> None:
         """
         Starts a a bulk download job.
         
diff --git a/invokeai/app/services/bulk_download/bulk_download_defauilt.py b/invokeai/app/services/bulk_download/bulk_download_defauilt.py
new file mode 100644
index 0000000000..ebeaa4be5a
--- /dev/null
+++ b/invokeai/app/services/bulk_download/bulk_download_defauilt.py
@@ -0,0 +1,114 @@
+from pathlib import Path
+from typing import Optional, Union
+import uuid
+from zipfile import ZipFile
+
+from invokeai.app.services.board_records.board_records_common import BoardRecordNotFoundException
+from invokeai.app.services.bulk_download.bulk_download_common import BulkDownloadException
+from invokeai.app.services.events.events_base import EventServiceBase
+from invokeai.app.services.image_records.image_records_common import ImageRecordNotFoundException
+from invokeai.app.services.invoker import Invoker
+
+from .bulk_download_base import BulkDownloadBase
+
+class BulkDownloadService(BulkDownloadBase):
+
+    __output_folder: Path
+    __bulk_downloads_folder: Path
+    __event_bus: Optional[EventServiceBase]
+
+    def __init__(self,
+                 output_folder: Union[str, Path],
+        event_bus: Optional[EventServiceBase] = None,):
+        """
+        Initialize the downloader object.
+
+        :param event_bus: Optional EventService object
+        """
+        self.__output_folder: Path = output_folder if isinstance(output_folder, Path) else Path(output_folder)
+        self.__bulk_downloads_folder = self.__output_folder / "bulk_downloads"
+        self.__bulk_downloads_folder.mkdir(parents=True, exist_ok=True)
+        self.__event_bus = event_bus
+
+
+    def handler(self,  invoker: Invoker, image_names: list[str], board_id: Optional[str]) -> None:
+        """
+        Create a zip file containing the images specified by the given image names or board id.
+
+        param: image_names: A list of image names to include in the zip file.
+        param: board_id: The ID of the board. If provided, all images associated with the board will be included in the zip file.
+        """
+        bulk_download_id = str(uuid.uuid4())
+        
+        self._signal_job_started(bulk_download_id)
+        try:
+            board_name: Union[str, None] = None
+            if board_id:
+                image_names = invoker.services.board_image_records.get_all_board_image_names_for_board(board_id)
+                if board_id == "none":
+                    board_id = "Uncategorized"
+            image_names_to_paths: dict[str, str] = self._get_image_name_to_path_map(invoker, image_names)
+            file_path: str = self._create_zip_file(image_names_to_paths, bulk_download_id)
+            self._signal_job_completed(bulk_download_id, file_path)
+        except (ImageRecordNotFoundException, BoardRecordNotFoundException, BulkDownloadException) as e:
+            self._signal_job_failed(bulk_download_id, e)
+        except Exception as e:
+            self._signal_job_failed(bulk_download_id, e)
+
+    def _get_image_name_to_path_map(self, invoker: Invoker, image_names: list[str]) -> dict[str, str]:
+        """
+        Create a map of image names to their paths.
+        :param image_names: A list of image names.
+        """
+        image_names_to_paths: dict[str, str] = {}
+        for image_name in image_names:
+            image_names_to_paths[image_name] = invoker.services.images.get_path(image_name)
+        return image_names_to_paths
+        
+    
+
+    def _create_zip_file(self, image_names_to_paths: dict[str, str], bulk_download_id: str) -> str:
+        """
+        Create a zip file containing the images specified by the given image names or board id. 
+        If download with the same bulk_download_id already exists, it will be overwritten.
+        """
+
+        zip_file_path = self.__bulk_downloads_folder / (bulk_download_id + ".zip")
+        
+        with ZipFile(zip_file_path, "w") as zip_file:
+            for image_name, image_path in image_names_to_paths.items():
+                zip_file.write(image_path, arcname=image_name)
+
+        return str(zip_file_path)
+
+
+    def _signal_job_started(self, bulk_download_id: str) -> None:
+        """Signal that a bulk download job has started."""
+        if self.__event_bus:
+            assert bulk_download_id is not None
+            self.__event_bus.emit_bulk_download_started(
+                bulk_download_id=bulk_download_id,
+            )
+
+
+    def _signal_job_completed(self, bulk_download_id: str, file_path: str) -> None:
+        """Signal that a bulk download job has completed."""
+        if self.__event_bus:
+            assert bulk_download_id is not None
+            assert file_path is not None
+            self.__event_bus.emit_bulk_download_completed(
+                bulk_download_id=bulk_download_id,
+                file_path=file_path,
+            )
+    
+    def _signal_job_failed(self, bulk_download_id: str, exception: Exception) -> None:
+        """Signal that a bulk download job has failed."""
+        if self.__event_bus:
+            assert bulk_download_id is not None
+            assert exception is not None
+            self.__event_bus.emit_bulk_download_failed(
+                bulk_download_id=bulk_download_id,
+                error=str(exception),
+            )
+
+    
\ No newline at end of file
diff --git a/invokeai/app/services/invocation_services.py b/invokeai/app/services/invocation_services.py
index 04fe71a3eb..a560696692 100644
--- a/invokeai/app/services/invocation_services.py
+++ b/invokeai/app/services/invocation_services.py
@@ -16,6 +16,7 @@ if TYPE_CHECKING:
     from .board_images.board_images_base import BoardImagesServiceABC
     from .board_records.board_records_base import BoardRecordStorageBase
     from .boards.boards_base import BoardServiceABC
+    from .bulk_download.bulk_download_base import BulkDownloadBase
     from .config import InvokeAIAppConfig
     from .download import DownloadQueueServiceBase
     from .events.events_base import EventServiceBase
@@ -41,6 +42,7 @@ class InvocationServices:
         board_image_records: "BoardImageRecordStorageBase",
         boards: "BoardServiceABC",
         board_records: "BoardRecordStorageBase",
+        bulk_download: "BulkDownloadBase",
         configuration: "InvokeAIAppConfig",
         events: "EventServiceBase",
         images: "ImageServiceABC",
@@ -63,6 +65,7 @@ class InvocationServices:
         self.board_image_records = board_image_records
         self.boards = boards
         self.board_records = board_records
+        self.bulk_download = bulk_download
         self.configuration = configuration
         self.events = events
         self.images = images

From 7ecc18938ba207e686dc363838436e341befcd17 Mon Sep 17 00:00:00 2001
From: Stefan Tobler <toblerlstefan@gmail.com>
Date: Sun, 7 Jan 2024 22:17:03 -0500
Subject: [PATCH 192/411] linted and styling

---
 invokeai/app/api/routers/images.py            | 11 ++++---
 invokeai/app/api/sockets.py                   |  1 -
 .../bulk_download/bulk_download_base.py       |  9 +++---
 .../bulk_download/bulk_download_common.py     | 10 ++++--
 .../bulk_download/bulk_download_defauilt.py   | 31 +++++++------------
 invokeai/app/services/events/events_base.py   | 15 +++++----
 6 files changed, 37 insertions(+), 40 deletions(-)

diff --git a/invokeai/app/api/routers/images.py b/invokeai/app/api/routers/images.py
index 2a8e1e7ec7..e32f7fb9ee 100644
--- a/invokeai/app/api/routers/images.py
+++ b/invokeai/app/api/routers/images.py
@@ -10,7 +10,6 @@ from pydantic import BaseModel, Field, ValidationError
 
 from invokeai.app.invocations.fields import MetadataField, MetadataFieldValidator
 from invokeai.app.services.image_records.image_records_common import ImageCategory, ImageRecordChanges, ResourceOrigin
-from invokeai.app.services.board_records.board_records_common import BoardRecordNotFoundException
 from invokeai.app.services.images.images_common import ImageDTO, ImageUrlsDTO
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
 from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID, WorkflowWithoutIDValidator
@@ -373,13 +372,16 @@ async def unstar_images_in_list(
     except Exception:
         raise HTTPException(status_code=500, detail="Failed to unstar images")
 
+
 class ImagesDownloaded(BaseModel):
     response: Optional[str] = Field(
         description="If defined, the message to display to the user when images begin downloading"
     )
 
 
-@images_router.post("/download", operation_id="download_images_from_list", response_model=ImagesDownloaded, status_code=202)
+@images_router.post(
+    "/download", operation_id="download_images_from_list", response_model=ImagesDownloaded, status_code=202
+)
 async def download_images_from_list(
     background_tasks: BackgroundTasks,
     image_names: list[str] = Body(description="The list of names of images to download", embed=True),
@@ -389,6 +391,7 @@ async def download_images_from_list(
 ) -> ImagesDownloaded:
     if (image_names is None or len(image_names) == 0) and board_id is None:
         raise HTTPException(status_code=400, detail="No images or board id specified.")
-    background_tasks.add_task(ApiDependencies.invoker.services.bulk_download.handler, ApiDependencies.invoker, image_names, board_id)
+    background_tasks.add_task(
+        ApiDependencies.invoker.services.bulk_download.handler, ApiDependencies.invoker, image_names, board_id
+    )
     return ImagesDownloaded(response="Your images are preparing to be downloaded")
-    
diff --git a/invokeai/app/api/sockets.py b/invokeai/app/api/sockets.py
index c5d9ace8d2..463545d9bc 100644
--- a/invokeai/app/api/sockets.py
+++ b/invokeai/app/api/sockets.py
@@ -18,7 +18,6 @@ class SocketIO:
     __sub_bulk_download: str = "subscribe_bulk_download"
     __unsub_bulk_download: str = "unsubscribe_bulk_download"
 
-
     def __init__(self, app: FastAPI):
         self.__sio = AsyncServer(async_mode="asgi", cors_allowed_origins="*")
         self.__app = ASGIApp(socketio_server=self.__sio, socketio_path="/ws/socket.io")
diff --git a/invokeai/app/services/bulk_download/bulk_download_base.py b/invokeai/app/services/bulk_download/bulk_download_base.py
index b788020bba..fc45aff280 100644
--- a/invokeai/app/services/bulk_download/bulk_download_base.py
+++ b/invokeai/app/services/bulk_download/bulk_download_base.py
@@ -1,13 +1,12 @@
+from abc import ABC, abstractmethod
 from pathlib import Path
 from typing import Optional, Union
 
-from abc import ABC, abstractmethod
-
 from invokeai.app.services.events.events_base import EventServiceBase
 from invokeai.app.services.invoker import Invoker
 
-class BulkDownloadBase(ABC):
 
+class BulkDownloadBase(ABC):
     @abstractmethod
     def __init__(
         self,
@@ -25,8 +24,8 @@ class BulkDownloadBase(ABC):
     def handler(self, invoker: Invoker, image_names: list[str], board_id: Optional[str]) -> None:
         """
         Starts a a bulk download job.
-        
+
         :param invoker: The Invoker that holds all the services, required to be passed as a parameter to avoid circular dependencies.
         :param image_names: A list of image names to include in the zip file.
         :param board_id: The ID of the board. If provided, all images associated with the board will be included in the zip file.
-        """
\ No newline at end of file
+        """
diff --git a/invokeai/app/services/bulk_download/bulk_download_common.py b/invokeai/app/services/bulk_download/bulk_download_common.py
index 3ac1f5bba8..23a0589daf 100644
--- a/invokeai/app/services/bulk_download/bulk_download_common.py
+++ b/invokeai/app/services/bulk_download/bulk_download_common.py
@@ -1,4 +1,3 @@
-
 class BulkDownloadException(Exception):
     """Exception raised when a bulk download fails."""
 
@@ -6,6 +5,7 @@ class BulkDownloadException(Exception):
         super().__init__(message)
         self.message = message
 
+
 class BulkDownloadTargetException(BulkDownloadException):
     """Exception raised when a bulk download target is not found."""
 
@@ -13,9 +13,13 @@ class BulkDownloadTargetException(BulkDownloadException):
         super().__init__(message)
         self.message = message
 
+
 class BulkDownloadParametersException(BulkDownloadException):
     """Exception raised when a bulk download parameter is invalid."""
 
-    def __init__(self, message="The bulk download parameters are invalid, either an array of image names or a board id must be provided"):
+    def __init__(
+        self,
+        message="The bulk download parameters are invalid, either an array of image names or a board id must be provided",
+    ):
         super().__init__(message)
-        self.message = message
\ No newline at end of file
+        self.message = message
diff --git a/invokeai/app/services/bulk_download/bulk_download_defauilt.py b/invokeai/app/services/bulk_download/bulk_download_defauilt.py
index ebeaa4be5a..8321f5069d 100644
--- a/invokeai/app/services/bulk_download/bulk_download_defauilt.py
+++ b/invokeai/app/services/bulk_download/bulk_download_defauilt.py
@@ -1,6 +1,6 @@
+import uuid
 from pathlib import Path
 from typing import Optional, Union
-import uuid
 from zipfile import ZipFile
 
 from invokeai.app.services.board_records.board_records_common import BoardRecordNotFoundException
@@ -11,15 +11,17 @@ from invokeai.app.services.invoker import Invoker
 
 from .bulk_download_base import BulkDownloadBase
 
-class BulkDownloadService(BulkDownloadBase):
 
+class BulkDownloadService(BulkDownloadBase):
     __output_folder: Path
     __bulk_downloads_folder: Path
     __event_bus: Optional[EventServiceBase]
 
-    def __init__(self,
-                 output_folder: Union[str, Path],
-        event_bus: Optional[EventServiceBase] = None,):
+    def __init__(
+        self,
+        output_folder: Union[str, Path],
+        event_bus: Optional[EventServiceBase] = None,
+    ):
         """
         Initialize the downloader object.
 
@@ -30,8 +32,7 @@ class BulkDownloadService(BulkDownloadBase):
         self.__bulk_downloads_folder.mkdir(parents=True, exist_ok=True)
         self.__event_bus = event_bus
 
-
-    def handler(self,  invoker: Invoker, image_names: list[str], board_id: Optional[str]) -> None:
+    def handler(self, invoker: Invoker, image_names: list[str], board_id: Optional[str]) -> None:
         """
         Create a zip file containing the images specified by the given image names or board id.
 
@@ -39,10 +40,8 @@ class BulkDownloadService(BulkDownloadBase):
         param: board_id: The ID of the board. If provided, all images associated with the board will be included in the zip file.
         """
         bulk_download_id = str(uuid.uuid4())
-        
-        self._signal_job_started(bulk_download_id)
+
         try:
-            board_name: Union[str, None] = None
             if board_id:
                 image_names = invoker.services.board_image_records.get_all_board_image_names_for_board(board_id)
                 if board_id == "none":
@@ -64,24 +63,21 @@ class BulkDownloadService(BulkDownloadBase):
         for image_name in image_names:
             image_names_to_paths[image_name] = invoker.services.images.get_path(image_name)
         return image_names_to_paths
-        
-    
 
     def _create_zip_file(self, image_names_to_paths: dict[str, str], bulk_download_id: str) -> str:
         """
-        Create a zip file containing the images specified by the given image names or board id. 
+        Create a zip file containing the images specified by the given image names or board id.
         If download with the same bulk_download_id already exists, it will be overwritten.
         """
 
         zip_file_path = self.__bulk_downloads_folder / (bulk_download_id + ".zip")
-        
+
         with ZipFile(zip_file_path, "w") as zip_file:
             for image_name, image_path in image_names_to_paths.items():
                 zip_file.write(image_path, arcname=image_name)
 
         return str(zip_file_path)
 
-
     def _signal_job_started(self, bulk_download_id: str) -> None:
         """Signal that a bulk download job has started."""
         if self.__event_bus:
@@ -90,7 +86,6 @@ class BulkDownloadService(BulkDownloadBase):
                 bulk_download_id=bulk_download_id,
             )
 
-
     def _signal_job_completed(self, bulk_download_id: str, file_path: str) -> None:
         """Signal that a bulk download job has completed."""
         if self.__event_bus:
@@ -100,7 +95,7 @@ class BulkDownloadService(BulkDownloadBase):
                 bulk_download_id=bulk_download_id,
                 file_path=file_path,
             )
-    
+
     def _signal_job_failed(self, bulk_download_id: str, exception: Exception) -> None:
         """Signal that a bulk download job has failed."""
         if self.__event_bus:
@@ -110,5 +105,3 @@ class BulkDownloadService(BulkDownloadBase):
                 bulk_download_id=bulk_download_id,
                 error=str(exception),
             )
-
-    
\ No newline at end of file
diff --git a/invokeai/app/services/events/events_base.py b/invokeai/app/services/events/events_base.py
index 0a0668b274..597a56d944 100644
--- a/invokeai/app/services/events/events_base.py
+++ b/invokeai/app/services/events/events_base.py
@@ -444,20 +444,19 @@ class EventServiceBase:
         """Emitted when a bulk download starts"""
         self._emit_bulk_download_event(
             event_name="bulk_download_started",
-            payload={"bulk_download_id": bulk_download_id, }
+            payload={
+                "bulk_download_id": bulk_download_id,
+            },
         )
-    
+
     def emit_bulk_download_completed(self, bulk_download_id: str, file_path: str) -> None:
         """Emitted when a bulk download completes"""
         self._emit_bulk_download_event(
-            event_name="bulk_download_completed",
-            payload={"bulk_download_id": bulk_download_id,
-                    "file_path": file_path}
+            event_name="bulk_download_completed", payload={"bulk_download_id": bulk_download_id, "file_path": file_path}
         )
-    
+
     def emit_bulk_download_failed(self, bulk_download_id: str, error: str) -> None:
         """Emitted when a bulk download fails"""
         self._emit_bulk_download_event(
-            event_name="bulk_download_failed",
-            payload={"bulk_download_id": bulk_download_id, "error": error}
+            event_name="bulk_download_failed", payload={"bulk_download_id": bulk_download_id, "error": error}
         )

From 52b0deb179fe2b60c14f88805c3a1884df61f02c Mon Sep 17 00:00:00 2001
From: Stefan Tobler <toblerlstefan@gmail.com>
Date: Sat, 13 Jan 2024 23:35:33 -0500
Subject: [PATCH 193/411] reworking some of the logic to use a default room,
 adding endpoint to download file on complete

---
 invokeai/app/api/dependencies.py              |  2 +-
 invokeai/app/api/routers/images.py            | 33 +++++++++
 .../bulk_download/bulk_download_base.py       | 25 +++++++
 .../bulk_download/bulk_download_common.py     |  3 +
 ...d_defauilt.py => bulk_download_default.py} | 72 +++++++++++++++----
 invokeai/app/services/events/events_base.py   | 23 ++++--
 6 files changed, 137 insertions(+), 21 deletions(-)
 rename invokeai/app/services/bulk_download/{bulk_download_defauilt.py => bulk_download_default.py} (60%)

diff --git a/invokeai/app/api/dependencies.py b/invokeai/app/api/dependencies.py
index ab09d1e5d7..aaa08a2498 100644
--- a/invokeai/app/api/dependencies.py
+++ b/invokeai/app/api/dependencies.py
@@ -15,7 +15,7 @@ from ..services.board_image_records.board_image_records_sqlite import SqliteBoar
 from ..services.board_images.board_images_default import BoardImagesService
 from ..services.board_records.board_records_sqlite import SqliteBoardRecordStorage
 from ..services.boards.boards_default import BoardService
-from ..services.bulk_download.bulk_download_defauilt import BulkDownloadService
+from ..services.bulk_download.bulk_download_default import BulkDownloadService
 from ..services.config import InvokeAIAppConfig
 from ..services.download import DownloadQueueService
 from ..services.image_files.image_files_disk import DiskImageFileStorage
diff --git a/invokeai/app/api/routers/images.py b/invokeai/app/api/routers/images.py
index e32f7fb9ee..43392dd471 100644
--- a/invokeai/app/api/routers/images.py
+++ b/invokeai/app/api/routers/images.py
@@ -395,3 +395,36 @@ async def download_images_from_list(
         ApiDependencies.invoker.services.bulk_download.handler, ApiDependencies.invoker, image_names, board_id
     )
     return ImagesDownloaded(response="Your images are preparing to be downloaded")
+
+
+@images_router.api_route(
+    "/download/{bulk_download_item_name}",
+    methods=["GET"],
+    operation_id="get_bulk_download_item",
+    response_class=Response,
+    responses={
+        200: {
+            "description": "Return the complete bulk download item",
+            "content": {"application/zip": {}},
+        },
+        404: {"description": "Image not found"},
+    },
+)
+async def get_bulk_download_item(
+    bulk_download_item_name: str = Path(description="The bulk_download_item_id of the bulk download item to get"),
+) -> FileResponse:
+    """Gets a bulk download zip file"""
+
+    try:
+        path = ApiDependencies.invoker.services.bulk_download.get_path(bulk_download_item_name)
+
+        response = FileResponse(
+            path,
+            media_type="application/zip",
+            filename=bulk_download_item_name,
+            content_disposition_type="inline",
+        )
+        response.headers["Cache-Control"] = f"max-age={IMAGE_MAX_AGE}"
+        return response
+    except Exception:
+        raise HTTPException(status_code=404)
diff --git a/invokeai/app/services/bulk_download/bulk_download_base.py b/invokeai/app/services/bulk_download/bulk_download_base.py
index fc45aff280..8a9ea1f3f2 100644
--- a/invokeai/app/services/bulk_download/bulk_download_base.py
+++ b/invokeai/app/services/bulk_download/bulk_download_base.py
@@ -29,3 +29,28 @@ class BulkDownloadBase(ABC):
         :param image_names: A list of image names to include in the zip file.
         :param board_id: The ID of the board. If provided, all images associated with the board will be included in the zip file.
         """
+
+    @abstractmethod
+    def get_path(self, bulk_download_item_id: str) -> str:
+        """
+        Get the path to the bulk download file.
+
+        :param bulk_download_item_id: The ID of the bulk download item.
+        :return: The path to the bulk download file.
+        """
+
+    @abstractmethod
+    def stop(self, *args, **kwargs) -> None:
+        """
+        Stops the BulkDownloadService and cleans up all the remnants.
+
+        This method is responsible for stopping the BulkDownloadService and performing any necessary cleanup
+        operations to remove any remnants or resources associated with the service.
+
+        Args:
+            *args: Variable length argument list.
+            **kwargs: Arbitrary keyword arguments.
+
+        Returns:
+            None
+        """
diff --git a/invokeai/app/services/bulk_download/bulk_download_common.py b/invokeai/app/services/bulk_download/bulk_download_common.py
index 23a0589daf..37b80073be 100644
--- a/invokeai/app/services/bulk_download/bulk_download_common.py
+++ b/invokeai/app/services/bulk_download/bulk_download_common.py
@@ -1,3 +1,6 @@
+DEFAULT_BULK_DOWNLOAD_ID = "default"
+
+
 class BulkDownloadException(Exception):
     """Exception raised when a bulk download fails."""
 
diff --git a/invokeai/app/services/bulk_download/bulk_download_defauilt.py b/invokeai/app/services/bulk_download/bulk_download_default.py
similarity index 60%
rename from invokeai/app/services/bulk_download/bulk_download_defauilt.py
rename to invokeai/app/services/bulk_download/bulk_download_default.py
index 8321f5069d..561fd173a8 100644
--- a/invokeai/app/services/bulk_download/bulk_download_defauilt.py
+++ b/invokeai/app/services/bulk_download/bulk_download_default.py
@@ -4,7 +4,11 @@ from typing import Optional, Union
 from zipfile import ZipFile
 
 from invokeai.app.services.board_records.board_records_common import BoardRecordNotFoundException
-from invokeai.app.services.bulk_download.bulk_download_common import BulkDownloadException
+from invokeai.app.services.bulk_download.bulk_download_common import (
+    DEFAULT_BULK_DOWNLOAD_ID,
+    BulkDownloadException,
+    BulkDownloadTargetException,
+)
 from invokeai.app.services.events.events_base import EventServiceBase
 from invokeai.app.services.image_records.image_records_common import ImageRecordNotFoundException
 from invokeai.app.services.invoker import Invoker
@@ -32,6 +36,32 @@ class BulkDownloadService(BulkDownloadBase):
         self.__bulk_downloads_folder.mkdir(parents=True, exist_ok=True)
         self.__event_bus = event_bus
 
+    def get_path(self, bulk_download_item_name: str) -> str:
+        """
+        Get the path to the bulk download file.
+
+        :param bulk_download_item_name: The name of the bulk download item.
+        :return: The path to the bulk download file.
+        """
+        path = str(self.__bulk_downloads_folder / bulk_download_item_name)
+        if not self.validate_path(path):
+            raise BulkDownloadTargetException()
+        return path
+
+    def get_bulk_download_item_name(self, bulk_download_item_id: str) -> str:
+        """
+        Get the name of the bulk download item.
+
+        :param bulk_download_item_id: The ID of the bulk download item.
+        :return: The name of the bulk download item.
+        """
+        return bulk_download_item_id + ".zip"
+
+    def validate_path(self, path: Union[str, Path]) -> bool:
+        """Validates the path given for a bulk download."""
+        path = path if isinstance(path, Path) else Path(path)
+        return path.exists()
+
     def handler(self, invoker: Invoker, image_names: list[str], board_id: Optional[str]) -> None:
         """
         Create a zip file containing the images specified by the given image names or board id.
@@ -39,7 +69,9 @@ class BulkDownloadService(BulkDownloadBase):
         param: image_names: A list of image names to include in the zip file.
         param: board_id: The ID of the board. If provided, all images associated with the board will be included in the zip file.
         """
-        bulk_download_id = str(uuid.uuid4())
+        bulk_download_id = DEFAULT_BULK_DOWNLOAD_ID
+        bulk_download_item_id = str(uuid.uuid4())
+        self._signal_job_started(bulk_download_id, bulk_download_item_id)
 
         try:
             if board_id:
@@ -47,12 +79,12 @@ class BulkDownloadService(BulkDownloadBase):
                 if board_id == "none":
                     board_id = "Uncategorized"
             image_names_to_paths: dict[str, str] = self._get_image_name_to_path_map(invoker, image_names)
-            file_path: str = self._create_zip_file(image_names_to_paths, bulk_download_id)
-            self._signal_job_completed(bulk_download_id, file_path)
+            bulk_download_item_name: str = self._create_zip_file(image_names_to_paths, bulk_download_item_id)
+            self._signal_job_completed(bulk_download_id, bulk_download_item_id, bulk_download_item_name)
         except (ImageRecordNotFoundException, BoardRecordNotFoundException, BulkDownloadException) as e:
-            self._signal_job_failed(bulk_download_id, e)
+            self._signal_job_failed(bulk_download_id, bulk_download_item_id, e)
         except Exception as e:
-            self._signal_job_failed(bulk_download_id, e)
+            self._signal_job_failed(bulk_download_id, bulk_download_item_id, e)
 
     def _get_image_name_to_path_map(self, invoker: Invoker, image_names: list[str]) -> dict[str, str]:
         """
@@ -64,44 +96,54 @@ class BulkDownloadService(BulkDownloadBase):
             image_names_to_paths[image_name] = invoker.services.images.get_path(image_name)
         return image_names_to_paths
 
-    def _create_zip_file(self, image_names_to_paths: dict[str, str], bulk_download_id: str) -> str:
+    def _create_zip_file(self, image_names_to_paths: dict[str, str], bulk_download_item_id: str) -> str:
         """
         Create a zip file containing the images specified by the given image names or board id.
         If download with the same bulk_download_id already exists, it will be overwritten.
-        """
 
-        zip_file_path = self.__bulk_downloads_folder / (bulk_download_id + ".zip")
+        :return: The name of the zip file.
+        """
+        zip_file_name = bulk_download_item_id + ".zip"
+        zip_file_path = self.__bulk_downloads_folder / (zip_file_name)
 
         with ZipFile(zip_file_path, "w") as zip_file:
             for image_name, image_path in image_names_to_paths.items():
                 zip_file.write(image_path, arcname=image_name)
 
-        return str(zip_file_path)
+        return str(zip_file_name)
 
-    def _signal_job_started(self, bulk_download_id: str) -> None:
+    def _signal_job_started(self, bulk_download_id: str, bulk_download_item_id: str) -> None:
         """Signal that a bulk download job has started."""
         if self.__event_bus:
             assert bulk_download_id is not None
             self.__event_bus.emit_bulk_download_started(
                 bulk_download_id=bulk_download_id,
+                bulk_download_item_id=bulk_download_item_id,
             )
 
-    def _signal_job_completed(self, bulk_download_id: str, file_path: str) -> None:
+    def _signal_job_completed(
+        self, bulk_download_id: str, bulk_download_item_id: str, bulk_download_item_name: str
+    ) -> None:
         """Signal that a bulk download job has completed."""
         if self.__event_bus:
             assert bulk_download_id is not None
-            assert file_path is not None
+            assert bulk_download_item_name is not None
             self.__event_bus.emit_bulk_download_completed(
                 bulk_download_id=bulk_download_id,
-                file_path=file_path,
+                bulk_download_item_id=bulk_download_item_id,
+                bulk_download_item_name=bulk_download_item_name,
             )
 
-    def _signal_job_failed(self, bulk_download_id: str, exception: Exception) -> None:
+    def _signal_job_failed(self, bulk_download_id: str, bulk_download_item_id: str, exception: Exception) -> None:
         """Signal that a bulk download job has failed."""
         if self.__event_bus:
             assert bulk_download_id is not None
             assert exception is not None
             self.__event_bus.emit_bulk_download_failed(
                 bulk_download_id=bulk_download_id,
+                bulk_download_item_id=bulk_download_item_id,
                 error=str(exception),
             )
+
+    def stop(self, *args, **kwargs):
+        pass
diff --git a/invokeai/app/services/events/events_base.py b/invokeai/app/services/events/events_base.py
index 597a56d944..3cc3ba2f28 100644
--- a/invokeai/app/services/events/events_base.py
+++ b/invokeai/app/services/events/events_base.py
@@ -440,23 +440,36 @@ class EventServiceBase:
             },
         )
 
-    def emit_bulk_download_started(self, bulk_download_id: str) -> None:
+    def emit_bulk_download_started(self, bulk_download_id: str, bulk_download_item_id: str) -> None:
         """Emitted when a bulk download starts"""
         self._emit_bulk_download_event(
             event_name="bulk_download_started",
             payload={
                 "bulk_download_id": bulk_download_id,
+                "bulk_download_item_id": bulk_download_item_id,
             },
         )
 
-    def emit_bulk_download_completed(self, bulk_download_id: str, file_path: str) -> None:
+    def emit_bulk_download_completed(
+        self, bulk_download_id: str, bulk_download_item_id: str, bulk_download_item_name: str
+    ) -> None:
         """Emitted when a bulk download completes"""
         self._emit_bulk_download_event(
-            event_name="bulk_download_completed", payload={"bulk_download_id": bulk_download_id, "file_path": file_path}
+            event_name="bulk_download_completed",
+            payload={
+                "bulk_download_id": bulk_download_id,
+                "bulk_download_item_id": bulk_download_item_id,
+                "bulk_download_item_name": bulk_download_item_name,
+            },
         )
 
-    def emit_bulk_download_failed(self, bulk_download_id: str, error: str) -> None:
+    def emit_bulk_download_failed(self, bulk_download_id: str, bulk_download_item_id: str, error: str) -> None:
         """Emitted when a bulk download fails"""
         self._emit_bulk_download_event(
-            event_name="bulk_download_failed", payload={"bulk_download_id": bulk_download_id, "error": error}
+            event_name="bulk_download_failed",
+            payload={
+                "bulk_download_id": bulk_download_id,
+                "bulk_download_item_id": bulk_download_item_id,
+                "error": error,
+            },
         )

From c43ea9f25c037a692cfdd45c0b7f357b18d30a0f Mon Sep 17 00:00:00 2001
From: Stefan Tobler <toblerlstefan@gmail.com>
Date: Sun, 14 Jan 2024 00:21:00 -0500
Subject: [PATCH 194/411] using the board name to download boards

---
 .../bulk_download/bulk_download_base.py       |  4 +-
 .../bulk_download/bulk_download_default.py    | 39 ++++++++++++-------
 2 files changed, 27 insertions(+), 16 deletions(-)

diff --git a/invokeai/app/services/bulk_download/bulk_download_base.py b/invokeai/app/services/bulk_download/bulk_download_base.py
index 8a9ea1f3f2..366a5fec5f 100644
--- a/invokeai/app/services/bulk_download/bulk_download_base.py
+++ b/invokeai/app/services/bulk_download/bulk_download_base.py
@@ -31,11 +31,11 @@ class BulkDownloadBase(ABC):
         """
 
     @abstractmethod
-    def get_path(self, bulk_download_item_id: str) -> str:
+    def get_path(self, bulk_download_item_name: str) -> str:
         """
         Get the path to the bulk download file.
 
-        :param bulk_download_item_id: The ID of the bulk download item.
+        :param bulk_download_item_name: The name of the bulk download item.
         :return: The path to the bulk download file.
         """
 
diff --git a/invokeai/app/services/bulk_download/bulk_download_default.py b/invokeai/app/services/bulk_download/bulk_download_default.py
index 561fd173a8..b80b8cc2f5 100644
--- a/invokeai/app/services/bulk_download/bulk_download_default.py
+++ b/invokeai/app/services/bulk_download/bulk_download_default.py
@@ -48,15 +48,6 @@ class BulkDownloadService(BulkDownloadBase):
             raise BulkDownloadTargetException()
         return path
 
-    def get_bulk_download_item_name(self, bulk_download_item_id: str) -> str:
-        """
-        Get the name of the bulk download item.
-
-        :param bulk_download_item_id: The ID of the bulk download item.
-        :return: The name of the bulk download item.
-        """
-        return bulk_download_item_id + ".zip"
-
     def validate_path(self, path: Union[str, Path]) -> bool:
         """Validates the path given for a bulk download."""
         path = path if isinstance(path, Path) else Path(path)
@@ -69,17 +60,27 @@ class BulkDownloadService(BulkDownloadBase):
         param: image_names: A list of image names to include in the zip file.
         param: board_id: The ID of the board. If provided, all images associated with the board will be included in the zip file.
         """
-        bulk_download_id = DEFAULT_BULK_DOWNLOAD_ID
-        bulk_download_item_id = str(uuid.uuid4())
-        self._signal_job_started(bulk_download_id, bulk_download_item_id)
+
+        bulk_download_id: str = DEFAULT_BULK_DOWNLOAD_ID
+        bulk_download_item_id: str = str(uuid.uuid4()) if board_id is None else board_id
 
         try:
+            board_name: str = ""
             if board_id:
                 image_names = invoker.services.board_image_records.get_all_board_image_names_for_board(board_id)
                 if board_id == "none":
                     board_id = "Uncategorized"
+                    board_name = "Uncategorized"
+                else:
+                    board_name = invoker.services.board_records.get(board_id).board_name
+                board_name = self._clean_string_to_path_safe(board_name)
+
+            self._signal_job_started(bulk_download_id, bulk_download_item_id)
+
             image_names_to_paths: dict[str, str] = self._get_image_name_to_path_map(invoker, image_names)
-            bulk_download_item_name: str = self._create_zip_file(image_names_to_paths, bulk_download_item_id)
+            bulk_download_item_name: str = self._create_zip_file(
+                image_names_to_paths, bulk_download_item_id if board_id is None else board_name
+            )
             self._signal_job_completed(bulk_download_id, bulk_download_item_id, bulk_download_item_name)
         except (ImageRecordNotFoundException, BoardRecordNotFoundException, BulkDownloadException) as e:
             self._signal_job_failed(bulk_download_id, bulk_download_item_id, e)
@@ -112,6 +113,10 @@ class BulkDownloadService(BulkDownloadBase):
 
         return str(zip_file_name)
 
+    def _clean_string_to_path_safe(self, s: str) -> str:
+        """Clean a string to be path safe."""
+        return "".join([c for c in s if c.isalpha() or c.isdigit() or c == " "]).rstrip()
+
     def _signal_job_started(self, bulk_download_id: str, bulk_download_item_id: str) -> None:
         """Signal that a bulk download job has started."""
         if self.__event_bus:
@@ -146,4 +151,10 @@ class BulkDownloadService(BulkDownloadBase):
             )
 
     def stop(self, *args, **kwargs):
-        pass
+        """Stop the bulk download service and delete the files in the bulk download folder."""
+        # Get all the files in the bulk downloads folder
+        files = self.__bulk_downloads_folder.glob("*")
+
+        # Delete all the files
+        for file in files:
+            file.unlink()

From 7114d64b861ab6161fc41ba5d2677403a14b20bc Mon Sep 17 00:00:00 2001
From: Stefan Tobler <toblerlstefan@gmail.com>
Date: Sun, 14 Jan 2024 01:33:43 -0500
Subject: [PATCH 195/411] fixing issue where default board did not return
 images

---
 .../bulk_download/bulk_download_default.py         | 14 ++++++++++++--
 1 file changed, 12 insertions(+), 2 deletions(-)

diff --git a/invokeai/app/services/bulk_download/bulk_download_default.py b/invokeai/app/services/bulk_download/bulk_download_default.py
index b80b8cc2f5..36d2b350b9 100644
--- a/invokeai/app/services/bulk_download/bulk_download_default.py
+++ b/invokeai/app/services/bulk_download/bulk_download_default.py
@@ -10,7 +10,7 @@ from invokeai.app.services.bulk_download.bulk_download_common import (
     BulkDownloadTargetException,
 )
 from invokeai.app.services.events.events_base import EventServiceBase
-from invokeai.app.services.image_records.image_records_common import ImageRecordNotFoundException
+from invokeai.app.services.image_records.image_records_common import ImageCategory, ImageRecordNotFoundException
 from invokeai.app.services.invoker import Invoker
 
 from .bulk_download_base import BulkDownloadBase
@@ -67,7 +67,17 @@ class BulkDownloadService(BulkDownloadBase):
         try:
             board_name: str = ""
             if board_id:
-                image_names = invoker.services.board_image_records.get_all_board_image_names_for_board(board_id)
+                # -1 is the default value for limit, which means no limit, is_intermediate only gives us completed images
+                image_names = [
+                    img.image_name
+                    for img in invoker.services.images.get_many(
+                        offset=0,
+                        limit=-1,
+                        board_id=board_id,
+                        is_intermediate=False,
+                        categories=[ImageCategory.GENERAL],
+                    ).items
+                ]
                 if board_id == "none":
                     board_id = "Uncategorized"
                     board_name = "Uncategorized"

From 795fbf0e81ec0529ca807cf39f2309bf1f7a51ac Mon Sep 17 00:00:00 2001
From: Stefan Tobler <toblerlstefan@gmail.com>
Date: Sun, 14 Jan 2024 03:09:35 -0500
Subject: [PATCH 196/411] refactoring bulkdownload to consider image category

---
 invokeai/app/api/routers/images.py            |  4 +-
 .../bulk_download/bulk_download_base.py       | 13 +++-
 .../bulk_download/bulk_download_default.py    | 62 +++++++++----------
 3 files changed, 43 insertions(+), 36 deletions(-)

diff --git a/invokeai/app/api/routers/images.py b/invokeai/app/api/routers/images.py
index 43392dd471..236961fa9e 100644
--- a/invokeai/app/api/routers/images.py
+++ b/invokeai/app/api/routers/images.py
@@ -391,9 +391,7 @@ async def download_images_from_list(
 ) -> ImagesDownloaded:
     if (image_names is None or len(image_names) == 0) and board_id is None:
         raise HTTPException(status_code=400, detail="No images or board id specified.")
-    background_tasks.add_task(
-        ApiDependencies.invoker.services.bulk_download.handler, ApiDependencies.invoker, image_names, board_id
-    )
+    background_tasks.add_task(ApiDependencies.invoker.services.bulk_download.handler, image_names, board_id)
     return ImagesDownloaded(response="Your images are preparing to be downloaded")
 
 
diff --git a/invokeai/app/services/bulk_download/bulk_download_base.py b/invokeai/app/services/bulk_download/bulk_download_base.py
index 366a5fec5f..880345fe98 100644
--- a/invokeai/app/services/bulk_download/bulk_download_base.py
+++ b/invokeai/app/services/bulk_download/bulk_download_base.py
@@ -7,6 +7,17 @@ from invokeai.app.services.invoker import Invoker
 
 
 class BulkDownloadBase(ABC):
+    @abstractmethod
+    def start(self, invoker: Invoker) -> None:
+        """
+        Starts the BulkDownloadService.
+
+        This method is responsible for starting the BulkDownloadService and performing any necessary initialization
+        operations to prepare the service for use.
+
+        param: invoker: The Invoker that holds all the services, required to be passed as a parameter to avoid circular dependencies.
+        """
+
     @abstractmethod
     def __init__(
         self,
@@ -21,7 +32,7 @@ class BulkDownloadBase(ABC):
         """
 
     @abstractmethod
-    def handler(self, invoker: Invoker, image_names: list[str], board_id: Optional[str]) -> None:
+    def handler(self, image_names: list[str], board_id: Optional[str]) -> None:
         """
         Starts a a bulk download job.
 
diff --git a/invokeai/app/services/bulk_download/bulk_download_default.py b/invokeai/app/services/bulk_download/bulk_download_default.py
index 36d2b350b9..ffc26dfa54 100644
--- a/invokeai/app/services/bulk_download/bulk_download_default.py
+++ b/invokeai/app/services/bulk_download/bulk_download_default.py
@@ -10,7 +10,8 @@ from invokeai.app.services.bulk_download.bulk_download_common import (
     BulkDownloadTargetException,
 )
 from invokeai.app.services.events.events_base import EventServiceBase
-from invokeai.app.services.image_records.image_records_common import ImageCategory, ImageRecordNotFoundException
+from invokeai.app.services.image_records.image_records_common import ImageRecordNotFoundException
+from invokeai.app.services.images.images_common import ImageDTO
 from invokeai.app.services.invoker import Invoker
 
 from .bulk_download_base import BulkDownloadBase
@@ -20,6 +21,10 @@ class BulkDownloadService(BulkDownloadBase):
     __output_folder: Path
     __bulk_downloads_folder: Path
     __event_bus: Optional[EventServiceBase]
+    __invoker: Invoker
+
+    def start(self, invoker: Invoker) -> None:
+        self.__invoker = invoker
 
     def __init__(
         self,
@@ -53,7 +58,7 @@ class BulkDownloadService(BulkDownloadBase):
         path = path if isinstance(path, Path) else Path(path)
         return path.exists()
 
-    def handler(self, invoker: Invoker, image_names: list[str], board_id: Optional[str]) -> None:
+    def handler(self, image_names: list[str], board_id: Optional[str]) -> None:
         """
         Create a zip file containing the images specified by the given image names or board id.
 
@@ -64,50 +69,40 @@ class BulkDownloadService(BulkDownloadBase):
         bulk_download_id: str = DEFAULT_BULK_DOWNLOAD_ID
         bulk_download_item_id: str = str(uuid.uuid4()) if board_id is None else board_id
 
+        self._signal_job_started(bulk_download_id, bulk_download_item_id)
+
         try:
             board_name: str = ""
+            image_dtos: list[ImageDTO] = []
+
             if board_id:
-                # -1 is the default value for limit, which means no limit, is_intermediate only gives us completed images
-                image_names = [
-                    img.image_name
-                    for img in invoker.services.images.get_many(
-                        offset=0,
-                        limit=-1,
-                        board_id=board_id,
-                        is_intermediate=False,
-                        categories=[ImageCategory.GENERAL],
-                    ).items
-                ]
                 if board_id == "none":
-                    board_id = "Uncategorized"
                     board_name = "Uncategorized"
                 else:
-                    board_name = invoker.services.board_records.get(board_id).board_name
+                    board_name = self.__invoker.services.board_records.get(board_id).board_name
                 board_name = self._clean_string_to_path_safe(board_name)
 
-            self._signal_job_started(bulk_download_id, bulk_download_item_id)
-
-            image_names_to_paths: dict[str, str] = self._get_image_name_to_path_map(invoker, image_names)
+                # -1 is the default value for limit, which means no limit, is_intermediate only gives us completed images
+                image_dtos = self.__invoker.services.images.get_many(
+                    offset=0,
+                    limit=-1,
+                    board_id=board_id,
+                    is_intermediate=False,
+                ).items
+            else:
+                image_dtos = [self.__invoker.services.images.get_dto(image_name) for image_name in image_names]
             bulk_download_item_name: str = self._create_zip_file(
-                image_names_to_paths, bulk_download_item_id if board_id is None else board_name
+                image_dtos, bulk_download_item_id if board_id is None else board_name
             )
             self._signal_job_completed(bulk_download_id, bulk_download_item_id, bulk_download_item_name)
         except (ImageRecordNotFoundException, BoardRecordNotFoundException, BulkDownloadException) as e:
             self._signal_job_failed(bulk_download_id, bulk_download_item_id, e)
         except Exception as e:
             self._signal_job_failed(bulk_download_id, bulk_download_item_id, e)
+            self.__invoker.services.logger.error("Problem bulk downloading images.")
+            raise e
 
-    def _get_image_name_to_path_map(self, invoker: Invoker, image_names: list[str]) -> dict[str, str]:
-        """
-        Create a map of image names to their paths.
-        :param image_names: A list of image names.
-        """
-        image_names_to_paths: dict[str, str] = {}
-        for image_name in image_names:
-            image_names_to_paths[image_name] = invoker.services.images.get_path(image_name)
-        return image_names_to_paths
-
-    def _create_zip_file(self, image_names_to_paths: dict[str, str], bulk_download_item_id: str) -> str:
+    def _create_zip_file(self, image_dtos: list[ImageDTO], bulk_download_item_id: str) -> str:
         """
         Create a zip file containing the images specified by the given image names or board id.
         If download with the same bulk_download_id already exists, it will be overwritten.
@@ -118,11 +113,14 @@ class BulkDownloadService(BulkDownloadBase):
         zip_file_path = self.__bulk_downloads_folder / (zip_file_name)
 
         with ZipFile(zip_file_path, "w") as zip_file:
-            for image_name, image_path in image_names_to_paths.items():
-                zip_file.write(image_path, arcname=image_name)
+            for image_dto in image_dtos:
+                image_zip_path = Path(image_dto.image_category.value) / image_dto.image_name
+                image_path = self.__invoker.services.images.get_path(image_dto.image_name)
+                zip_file.write(image_path, arcname=image_zip_path)
 
         return str(zip_file_name)
 
+    # from https://stackoverflow.com/questions/7406102/create-sane-safe-filename-from-any-unsafe-string
     def _clean_string_to_path_safe(self, s: str) -> str:
         """Clean a string to be path safe."""
         return "".join([c for c in s if c.isalpha() or c.isdigit() or c == " "]).rstrip()

From db812133e72579ccfc14bf88ab1519c04b6e0242 Mon Sep 17 00:00:00 2001
From: Stefan Tobler <toblerlstefan@gmail.com>
Date: Sun, 14 Jan 2024 22:58:07 -0500
Subject: [PATCH 197/411] refactoring dummy event service, DRY principal;
 adding bulk_download_event to existing invoker tests

---
 .../services/download/test_download_queue.py  | 28 ++-------------
 .../model_install/test_model_install.py       |  1 -
 tests/fixtures/event_service.py               | 34 +++++++++++++++++++
 tests/test_graph_execution_state.py           |  1 +
 4 files changed, 37 insertions(+), 27 deletions(-)
 create mode 100644 tests/fixtures/event_service.py

diff --git a/tests/app/services/download/test_download_queue.py b/tests/app/services/download/test_download_queue.py
index 93a3832b51..34408ac5ae 100644
--- a/tests/app/services/download/test_download_queue.py
+++ b/tests/app/services/download/test_download_queue.py
@@ -2,19 +2,17 @@
 import re
 import time
 from pathlib import Path
-from typing import Any, Dict, List
 
 import pytest
-from pydantic import BaseModel
 from pydantic.networks import AnyHttpUrl
 from requests.sessions import Session
 from requests_testadapter import TestAdapter, TestSession
 
 from invokeai.app.services.download import DownloadJob, DownloadJobStatus, DownloadQueueService
-from invokeai.app.services.events.events_base import EventServiceBase
+from tests.fixtures.event_service import DummyEventService
 
 # Prevent pytest deprecation warnings
-TestAdapter.__test__ = False
+TestAdapter.__test__ = False  # type: ignore
 
 
 @pytest.fixture
@@ -52,28 +50,6 @@ def session() -> Session:
     return sess
 
 
-class DummyEvent(BaseModel):
-    """Dummy Event to use with Dummy Event service."""
-
-    event_name: str
-    payload: Dict[str, Any]
-
-
-# A dummy event service for testing event issuing
-class DummyEventService(EventServiceBase):
-    """Dummy event service for testing."""
-
-    events: List[DummyEvent]
-
-    def __init__(self) -> None:
-        super().__init__()
-        self.events = []
-
-    def dispatch(self, event_name: str, payload: Any) -> None:
-        """Dispatch an event by appending it to self.events."""
-        self.events.append(DummyEvent(event_name=payload["event"], payload=payload["data"]))
-
-
 def test_basic_queue_download(tmp_path: Path, session: Session) -> None:
     events = set()
 
diff --git a/tests/app/services/model_install/test_model_install.py b/tests/app/services/model_install/test_model_install.py
index 55f7e86541..14c8ed5c84 100644
--- a/tests/app/services/model_install/test_model_install.py
+++ b/tests/app/services/model_install/test_model_install.py
@@ -10,7 +10,6 @@ from pydantic import ValidationError
 from pydantic.networks import Url
 
 from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.app.services.events.events_base import EventServiceBase
 from invokeai.app.services.model_install import (
     InstallStatus,
     LocalModelSource,
diff --git a/tests/fixtures/event_service.py b/tests/fixtures/event_service.py
new file mode 100644
index 0000000000..71262be3f9
--- /dev/null
+++ b/tests/fixtures/event_service.py
@@ -0,0 +1,34 @@
+from typing import Any, Dict, List
+
+import pytest
+from pydantic import BaseModel
+
+from invokeai.app.services.events.events_base import EventServiceBase
+
+
+class DummyEvent(BaseModel):
+    """Dummy Event to use with Dummy Event service."""
+
+    event_name: str
+    payload: Dict[str, Any]
+
+
+# A dummy event service for testing event issuing
+class DummyEventService(EventServiceBase):
+    """Dummy event service for testing."""
+
+    events: List[DummyEvent]
+
+    def __init__(self) -> None:
+        super().__init__()
+        self.events = []
+
+    def dispatch(self, event_name: str, payload: Any) -> None:
+        """Dispatch an event by appending it to self.events."""
+        self.events.append(DummyEvent(event_name=payload["event"], payload=payload["data"]))
+
+
+@pytest.fixture
+def mock_event_service() -> EventServiceBase:
+    """Create a dummy event service."""
+    return DummyEventService()
diff --git a/tests/test_graph_execution_state.py b/tests/test_graph_execution_state.py
index 2e88178424..9a35037431 100644
--- a/tests/test_graph_execution_state.py
+++ b/tests/test_graph_execution_state.py
@@ -50,6 +50,7 @@ def mock_services() -> InvocationServices:
         board_images=None,  # type: ignore
         board_records=None,  # type: ignore
         boards=None,  # type: ignore
+        bulk_download=None,  # type: ignore
         configuration=configuration,
         events=TestEventService(),
         image_files=None,  # type: ignore

From 7d91426d8f499b019f62e047aca2427250587f92 Mon Sep 17 00:00:00 2001
From: Stefan Tobler <toblerlstefan@gmail.com>
Date: Mon, 15 Jan 2024 12:59:45 -0500
Subject: [PATCH 198/411] refactoring bulk_download to be better managed

---
 invokeai/app/api/dependencies.py              |  2 +-
 .../bulk_download/bulk_download_base.py       |  8 +-----
 .../bulk_download/bulk_download_default.py    | 26 +++++++++----------
 3 files changed, 15 insertions(+), 21 deletions(-)

diff --git a/invokeai/app/api/dependencies.py b/invokeai/app/api/dependencies.py
index aaa08a2498..984fd8e267 100644
--- a/invokeai/app/api/dependencies.py
+++ b/invokeai/app/api/dependencies.py
@@ -82,7 +82,7 @@ class ApiDependencies:
         board_records = SqliteBoardRecordStorage(db=db)
         boards = BoardService()
         events = FastAPIEventService(event_handler_id)
-        bulk_download = BulkDownloadService(output_folder=f"{output_folder}", event_bus=events)
+        bulk_download = BulkDownloadService(output_folder=f"{output_folder}")
         image_records = SqliteImageRecordStorage(db=db)
         images = ImageService()
         invocation_cache = MemoryInvocationCache(max_cache_size=config.node_cache_size)
diff --git a/invokeai/app/services/bulk_download/bulk_download_base.py b/invokeai/app/services/bulk_download/bulk_download_base.py
index 880345fe98..7a4aa0661c 100644
--- a/invokeai/app/services/bulk_download/bulk_download_base.py
+++ b/invokeai/app/services/bulk_download/bulk_download_base.py
@@ -2,7 +2,6 @@ from abc import ABC, abstractmethod
 from pathlib import Path
 from typing import Optional, Union
 
-from invokeai.app.services.events.events_base import EventServiceBase
 from invokeai.app.services.invoker import Invoker
 
 
@@ -19,16 +18,11 @@ class BulkDownloadBase(ABC):
         """
 
     @abstractmethod
-    def __init__(
-        self,
-        output_folder: Union[str, Path],
-        event_bus: Optional["EventServiceBase"] = None,
-    ):
+    def __init__(self, output_folder: Union[str, Path]):
         """
         Create BulkDownloadBase object.
 
         :param output_folder: The path to the output folder where the bulk download files can be temporarily stored.
-        :param event_bus: InvokeAI event bus for reporting events to.
         """
 
     @abstractmethod
diff --git a/invokeai/app/services/bulk_download/bulk_download_default.py b/invokeai/app/services/bulk_download/bulk_download_default.py
index ffc26dfa54..a9ea12bfd6 100644
--- a/invokeai/app/services/bulk_download/bulk_download_default.py
+++ b/invokeai/app/services/bulk_download/bulk_download_default.py
@@ -1,4 +1,3 @@
-import uuid
 from pathlib import Path
 from typing import Optional, Union
 from zipfile import ZipFile
@@ -13,6 +12,7 @@ from invokeai.app.services.events.events_base import EventServiceBase
 from invokeai.app.services.image_records.image_records_common import ImageRecordNotFoundException
 from invokeai.app.services.images.images_common import ImageDTO
 from invokeai.app.services.invoker import Invoker
+from invokeai.app.util.misc import uuid_string
 
 from .bulk_download_base import BulkDownloadBase
 
@@ -20,26 +20,23 @@ from .bulk_download_base import BulkDownloadBase
 class BulkDownloadService(BulkDownloadBase):
     __output_folder: Path
     __bulk_downloads_folder: Path
-    __event_bus: Optional[EventServiceBase]
+    __event_bus: EventServiceBase
     __invoker: Invoker
 
     def start(self, invoker: Invoker) -> None:
         self.__invoker = invoker
+        self.__event_bus = invoker.services.events
 
     def __init__(
         self,
         output_folder: Union[str, Path],
-        event_bus: Optional[EventServiceBase] = None,
     ):
         """
         Initialize the downloader object.
-
-        :param event_bus: Optional EventService object
         """
         self.__output_folder: Path = output_folder if isinstance(output_folder, Path) else Path(output_folder)
         self.__bulk_downloads_folder = self.__output_folder / "bulk_downloads"
         self.__bulk_downloads_folder.mkdir(parents=True, exist_ok=True)
-        self.__event_bus = event_bus
 
     def get_path(self, bulk_download_item_name: str) -> str:
         """
@@ -67,7 +64,7 @@ class BulkDownloadService(BulkDownloadBase):
         """
 
         bulk_download_id: str = DEFAULT_BULK_DOWNLOAD_ID
-        bulk_download_item_id: str = str(uuid.uuid4()) if board_id is None else board_id
+        bulk_download_item_id: str = uuid_string() if board_id is None else board_id
 
         self._signal_job_started(bulk_download_id, bulk_download_item_id)
 
@@ -76,10 +73,7 @@ class BulkDownloadService(BulkDownloadBase):
             image_dtos: list[ImageDTO] = []
 
             if board_id:
-                if board_id == "none":
-                    board_name = "Uncategorized"
-                else:
-                    board_name = self.__invoker.services.board_records.get(board_id).board_name
+                board_name = self._get_board_name(board_id)
                 board_name = self._clean_string_to_path_safe(board_name)
 
                 # -1 is the default value for limit, which means no limit, is_intermediate only gives us completed images
@@ -102,6 +96,12 @@ class BulkDownloadService(BulkDownloadBase):
             self.__invoker.services.logger.error("Problem bulk downloading images.")
             raise e
 
+    def _get_board_name(self, board_id: str) -> str:
+        if board_id == "none":
+            return "Uncategorized"
+
+        return self.__invoker.services.board_records.get(board_id).board_name
+
     def _create_zip_file(self, image_dtos: list[ImageDTO], bulk_download_item_id: str) -> str:
         """
         Create a zip file containing the images specified by the given image names or board id.
@@ -115,8 +115,8 @@ class BulkDownloadService(BulkDownloadBase):
         with ZipFile(zip_file_path, "w") as zip_file:
             for image_dto in image_dtos:
                 image_zip_path = Path(image_dto.image_category.value) / image_dto.image_name
-                image_path = self.__invoker.services.images.get_path(image_dto.image_name)
-                zip_file.write(image_path, arcname=image_zip_path)
+                image_disk_path = self.__invoker.services.images.get_path(image_dto.image_name)
+                zip_file.write(image_disk_path, arcname=image_zip_path)
 
         return str(zip_file_name)
 

From 284ba041bd7a0e39aeb6f031c0ae7dcfa3602311 Mon Sep 17 00:00:00 2001
From: Stefan Tobler <toblerlstefan@gmail.com>
Date: Mon, 15 Jan 2024 13:01:06 -0500
Subject: [PATCH 199/411] 97% test coverage on bulk_download

---
 .../bulk_download/test_bulk_download.py       | 319 ++++++++++++++++++
 tests/fixtures/event_service.py               |   2 +-
 2 files changed, 320 insertions(+), 1 deletion(-)
 create mode 100644 tests/app/services/bulk_download/test_bulk_download.py

diff --git a/tests/app/services/bulk_download/test_bulk_download.py b/tests/app/services/bulk_download/test_bulk_download.py
new file mode 100644
index 0000000000..4f476c21be
--- /dev/null
+++ b/tests/app/services/bulk_download/test_bulk_download.py
@@ -0,0 +1,319 @@
+import os
+from pathlib import Path
+from typing import Any
+from zipfile import ZipFile
+
+import pytest
+
+from invokeai.app.services.board_records.board_records_common import BoardRecord, BoardRecordNotFoundException
+from invokeai.app.services.board_records.board_records_sqlite import SqliteBoardRecordStorage
+from invokeai.app.services.bulk_download.bulk_download_common import BulkDownloadTargetException
+from invokeai.app.services.bulk_download.bulk_download_default import BulkDownloadService
+from invokeai.app.services.config.config_default import InvokeAIAppConfig
+from invokeai.app.services.image_records.image_records_common import (
+    ImageCategory,
+    ImageRecordNotFoundException,
+    ResourceOrigin,
+)
+from invokeai.app.services.images.images_common import ImageDTO
+from invokeai.app.services.images.images_default import ImageService
+from invokeai.app.services.invocation_services import InvocationServices
+from invokeai.app.services.invoker import Invoker
+from invokeai.app.services.shared.pagination import OffsetPaginatedResults
+from invokeai.backend.util.logging import InvokeAILogger
+from tests.fixtures.event_service import DummyEventService, mock_event_service  # noqa: F401,F811
+from tests.fixtures.sqlite_database import create_mock_sqlite_database
+
+
+@pytest.fixture
+def mock_image_dto() -> ImageDTO:
+    """Create a mock ImageDTO."""
+    return ImageDTO(
+        image_name="mock_image.png",
+        board_id="12345",
+        image_url="None",
+        width=100,
+        height=100,
+        thumbnail_url="None",
+        image_origin=ResourceOrigin.INTERNAL,
+        image_category=ImageCategory.GENERAL,
+        created_at="None",
+        updated_at="None",
+        starred=False,
+        has_workflow=False,
+        is_intermediate=False,
+    )
+
+
+@pytest.fixture
+def mock_services(mock_event_service: DummyEventService) -> InvocationServices:
+    configuration = InvokeAIAppConfig(use_memory_db=True, node_cache_size=0)
+    logger = InvokeAILogger.get_logger()
+    db = create_mock_sqlite_database(configuration, logger)
+
+    return InvocationServices(
+        board_image_records=None,  # type: ignore
+        board_images=None,  # type: ignore
+        board_records=SqliteBoardRecordStorage(db=db),
+        boards=None,  # type: ignore
+        bulk_download=None,  # type: ignore
+        configuration=None,  # type: ignore
+        events=mock_event_service,
+        graph_execution_manager=None,  # type: ignore
+        image_files=None,  # type: ignore
+        image_records=None,  # type: ignore
+        images=ImageService(),
+        invocation_cache=None,  # type: ignore
+        latents=None,  # type: ignore
+        logger=logger,
+        model_manager=None,  # type: ignore
+        model_records=None,  # type: ignore
+        download_queue=None,  # type: ignore
+        model_install=None,  # type: ignore
+        names=None,  # type: ignore
+        performance_statistics=None,  # type: ignore
+        processor=None,  # type: ignore
+        queue=None,  # type: ignore
+        session_processor=None,  # type: ignore
+        session_queue=None,  # type: ignore
+        urls=None,  # type: ignore
+        workflow_records=None,  # type: ignore
+    )
+
+
+@pytest.fixture()
+def mock_invoker(mock_services: InvocationServices) -> Invoker:
+    return Invoker(services=mock_services)
+
+
+def test_get_path_when_file_exists(tmp_path: Path) -> None:
+    """Test get_path when the file exists."""
+
+    # Create a directory at tmp_path/bulk_downloads
+    test_bulk_downloads_dir: Path = tmp_path / "bulk_downloads"
+    test_bulk_downloads_dir.mkdir(parents=True, exist_ok=True)
+
+    # Create a file at tmp_path/bulk_downloads/test.zip
+    test_file_path: Path = test_bulk_downloads_dir / "test.zip"
+    test_file_path.touch()
+
+    bulk_download_service = BulkDownloadService(tmp_path)
+    assert bulk_download_service.get_path("test.zip") == str(test_file_path)
+
+
+def test_get_path_when_file_does_not_exist(tmp_path: Path) -> None:
+    """Test get_path when the file does not exist."""
+
+    bulk_download_service = BulkDownloadService(tmp_path)
+    with pytest.raises(BulkDownloadTargetException):
+        bulk_download_service.get_path("test")
+
+
+def test_bulk_downloads_dir_created_at_start(tmp_path: Path) -> None:
+    """Test that the bulk_downloads directory is created at start."""
+
+    BulkDownloadService(tmp_path)
+    assert (tmp_path / "bulk_downloads").exists()
+
+
+def test_handler_image_names(tmp_path: Path, monkeypatch: Any, mock_image_dto: ImageDTO, mock_invoker: Invoker):
+    """Test that the handler creates the zip file correctly when given a list of image names."""
+
+    expected_zip_path, expected_image_path, mock_image_contents = prepare_handler_test(
+        tmp_path, monkeypatch, mock_image_dto, mock_invoker
+    )
+
+    bulk_download_service = BulkDownloadService(tmp_path)
+    bulk_download_service.start(mock_invoker)
+    bulk_download_service.handler([mock_image_dto.image_name], None)
+
+    assert_handler_success(
+        expected_zip_path, expected_image_path, mock_image_contents, tmp_path, mock_invoker.services.events
+    )
+
+
+def test_handler_board_id(tmp_path: Path, monkeypatch: Any, mock_image_dto: ImageDTO, mock_invoker: Invoker):
+    """Test that the handler creates the zip file correctly when given a board id."""
+
+    expected_zip_path, expected_image_path, mock_image_contents = prepare_handler_test(
+        tmp_path, monkeypatch, mock_image_dto, mock_invoker
+    )
+
+    def mock_board_get(*args, **kwargs):
+        return BoardRecord(board_id="12345", board_name="test", created_at="None", updated_at="None")
+
+    monkeypatch.setattr(mock_invoker.services.board_records, "get", mock_board_get)
+
+    def mock_get_many(*args, **kwargs):
+        return OffsetPaginatedResults(limit=-1, total=1, offset=0, items=[mock_image_dto])
+
+    monkeypatch.setattr(mock_invoker.services.images, "get_many", mock_get_many)
+
+    bulk_download_service = BulkDownloadService(tmp_path)
+    bulk_download_service.start(mock_invoker)
+    bulk_download_service.handler([], "test")
+
+    assert_handler_success(
+        expected_zip_path, expected_image_path, mock_image_contents, tmp_path, mock_invoker.services.events
+    )
+
+
+def test_handler_board_id_default(tmp_path: Path, monkeypatch: Any, mock_image_dto: ImageDTO, mock_invoker: Invoker):
+    """Test that the handler creates the zip file correctly when given a board id."""
+
+    _, expected_image_path, mock_image_contents = prepare_handler_test(
+        tmp_path, monkeypatch, mock_image_dto, mock_invoker
+    )
+    expected_zip_path: Path = tmp_path / "bulk_downloads" / "Uncategorized.zip"
+
+    def mock_get_many(*args, **kwargs):
+        return OffsetPaginatedResults(limit=-1, total=1, offset=0, items=[mock_image_dto])
+
+    monkeypatch.setattr(mock_invoker.services.images, "get_many", mock_get_many)
+
+    bulk_download_service = BulkDownloadService(tmp_path)
+    bulk_download_service.start(mock_invoker)
+    bulk_download_service.handler([], "none")
+
+    assert_handler_success(
+        expected_zip_path, expected_image_path, mock_image_contents, tmp_path, mock_invoker.services.events
+    )
+
+
+def prepare_handler_test(tmp_path: Path, monkeypatch: Any, mock_image_dto: ImageDTO, mock_invoker: Invoker):
+    """Prepare the test for the handler tests."""
+
+    def mock_uuid_string():
+        return "test"
+
+    # You have to patch the function within the module it's being imported into. This is strange, but it works.
+    # See http://www.gregreda.com/2021/06/28/mocking-imported-module-function-python/
+    monkeypatch.setattr("invokeai.app.services.bulk_download.bulk_download_default.uuid_string", mock_uuid_string)
+
+    expected_zip_path: Path = tmp_path / "bulk_downloads" / "test.zip"
+    expected_image_path: Path = (
+        tmp_path / "bulk_downloads" / mock_image_dto.image_category.value / mock_image_dto.image_name
+    )
+
+    # Mock the get_dto method so that when the image dto needs to be retrieved it is returned
+    def mock_get_dto(*args, **kwargs):
+        return mock_image_dto
+
+    monkeypatch.setattr(mock_invoker.services.images, "get_dto", mock_get_dto)
+
+    # Create a mock image file so that the contents of the zip file are not empty
+    mock_image_path: Path = tmp_path / mock_image_dto.image_name
+    mock_image_contents: str = "Totally an image"
+    mock_image_path.write_text(mock_image_contents)
+
+    def mock_get_path(*args, **kwargs):
+        return str(mock_image_path)
+
+    monkeypatch.setattr(mock_invoker.services.images, "get_path", mock_get_path)
+
+    return expected_zip_path, expected_image_path, mock_image_contents
+
+
+def assert_handler_success(
+    expected_zip_path: Path,
+    expected_image_path: Path,
+    mock_image_contents: str,
+    tmp_path: Path,
+    event_bus: DummyEventService,
+):
+    """Assert that the handler was successful."""
+    # Check that the zip file was created
+    assert expected_zip_path.exists()
+    assert expected_zip_path.is_file()
+    assert expected_zip_path.stat().st_size > 0
+
+    # Check that the zip contents are expected
+    with ZipFile(expected_zip_path, "r") as zip_file:
+        zip_file.extractall(tmp_path / "bulk_downloads")
+        assert expected_image_path.exists()
+        assert expected_image_path.is_file()
+        assert expected_image_path.stat().st_size > 0
+        assert expected_image_path.read_text() == mock_image_contents
+
+    # Check that the correct events were emitted
+    assert len(event_bus.events) == 2
+    assert event_bus.events[0].event_name == "bulk_download_started"
+    assert event_bus.events[1].event_name == "bulk_download_completed"
+    assert event_bus.events[1].payload["bulk_download_item_name"] == os.path.basename(expected_zip_path)
+
+
+def test_stop(tmp_path: Path) -> None:
+    """Test that the stop method removes the bulk_downloads directory."""
+
+    bulk_download_service = BulkDownloadService(tmp_path)
+
+    mock_file: Path = tmp_path / "bulk_downloads" / "test.zip"
+    mock_file.write_text("contents")
+
+    bulk_download_service.stop()
+
+    assert (tmp_path / "bulk_downloads").exists()
+    assert len(os.listdir(tmp_path / "bulk_downloads")) == 0
+
+
+def test_handler_on_image_not_found(tmp_path: Path, monkeypatch: Any, mock_image_dto: ImageDTO, mock_invoker: Invoker):
+    """Test that the handler emits an error event when the image is not found."""
+    exception: Exception = ImageRecordNotFoundException("Image not found")
+
+    def mock_get_dto(*args, **kwargs):
+        raise exception
+
+    monkeypatch.setattr(mock_invoker.services.images, "get_dto", mock_get_dto)
+
+    execute_handler_test_on_error(tmp_path, monkeypatch, mock_image_dto, mock_invoker, exception)
+
+
+def test_handler_on_board_not_found(tmp_path: Path, monkeypatch: Any, mock_image_dto: ImageDTO, mock_invoker: Invoker):
+    """Test that the handler emits an error event when the image is not found."""
+
+    exception: Exception = BoardRecordNotFoundException("Image not found")
+
+    def mock_get_board_name(*args, **kwargs):
+        raise exception
+
+    monkeypatch.setattr(mock_invoker.services.images, "get_dto", mock_get_board_name)
+
+    execute_handler_test_on_error(tmp_path, monkeypatch, mock_image_dto, mock_invoker, exception)
+
+
+def test_handler_on_generic_exception(
+    tmp_path: Path, monkeypatch: Any, mock_image_dto: ImageDTO, mock_invoker: Invoker
+):
+    """Test that the handler emits an error event when the image is not found."""
+
+    exception: Exception = Exception("Generic exception")
+
+    def mock_get_board_name(*args, **kwargs):
+        raise exception
+
+    monkeypatch.setattr(mock_invoker.services.images, "get_dto", mock_get_board_name)
+
+    with pytest.raises(Exception):
+        execute_handler_test_on_error(tmp_path, monkeypatch, mock_image_dto, mock_invoker, exception)
+
+    event_bus: DummyEventService = mock_invoker.services.events
+
+    assert len(event_bus.events) == 2
+    assert event_bus.events[0].event_name == "bulk_download_started"
+    assert event_bus.events[1].event_name == "bulk_download_failed"
+    assert event_bus.events[1].payload["error"] == exception.__str__()
+
+
+def execute_handler_test_on_error(
+    tmp_path: Path, monkeypatch: Any, mock_image_dto: ImageDTO, mock_invoker: Invoker, error: Exception
+):
+    bulk_download_service = BulkDownloadService(tmp_path)
+    bulk_download_service.start(mock_invoker)
+    bulk_download_service.handler([mock_image_dto.image_name], None)
+
+    event_bus: DummyEventService = mock_invoker.services.events
+
+    assert len(event_bus.events) == 2
+    assert event_bus.events[0].event_name == "bulk_download_started"
+    assert event_bus.events[1].event_name == "bulk_download_failed"
+    assert event_bus.events[1].payload["error"] == error.__str__()
diff --git a/tests/fixtures/event_service.py b/tests/fixtures/event_service.py
index 71262be3f9..0a09fa0d64 100644
--- a/tests/fixtures/event_service.py
+++ b/tests/fixtures/event_service.py
@@ -29,6 +29,6 @@ class DummyEventService(EventServiceBase):
 
 
 @pytest.fixture
-def mock_event_service() -> EventServiceBase:
+def mock_event_service() -> DummyEventService:
     """Create a dummy event service."""
     return DummyEventService()

From 7544b350f32cc6729507cb4ef57a014c4b1b282a Mon Sep 17 00:00:00 2001
From: Stefan Tobler <toblerlstefan@gmail.com>
Date: Mon, 15 Jan 2024 14:37:42 -0500
Subject: [PATCH 200/411] replacing import removed during rebase

---
 tests/app/services/model_install/test_model_install.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/tests/app/services/model_install/test_model_install.py b/tests/app/services/model_install/test_model_install.py
index 14c8ed5c84..55f7e86541 100644
--- a/tests/app/services/model_install/test_model_install.py
+++ b/tests/app/services/model_install/test_model_install.py
@@ -10,6 +10,7 @@ from pydantic import ValidationError
 from pydantic.networks import Url
 
 from invokeai.app.services.config import InvokeAIAppConfig
+from invokeai.app.services.events.events_base import EventServiceBase
 from invokeai.app.services.model_install import (
     InstallStatus,
     LocalModelSource,

From 79eb871683273ba570de6543a020159fb3b1f611 Mon Sep 17 00:00:00 2001
From: Stefan Tobler <toblerlstefan@gmail.com>
Date: Mon, 15 Jan 2024 15:58:43 -0500
Subject: [PATCH 201/411] cleaning up bulk download zip after the response is
 complete

---
 invokeai/app/api/routers/images.py            |  3 +-
 .../bulk_download/bulk_download_base.py       |  8 ++++
 .../bulk_download/bulk_download_default.py    | 43 +++++++++++--------
 .../bulk_download/test_bulk_download.py       | 16 ++++++-
 4 files changed, 51 insertions(+), 19 deletions(-)

diff --git a/invokeai/app/api/routers/images.py b/invokeai/app/api/routers/images.py
index 236961fa9e..d11c89c749 100644
--- a/invokeai/app/api/routers/images.py
+++ b/invokeai/app/api/routers/images.py
@@ -409,10 +409,10 @@ async def download_images_from_list(
     },
 )
 async def get_bulk_download_item(
+    background_tasks: BackgroundTasks,
     bulk_download_item_name: str = Path(description="The bulk_download_item_id of the bulk download item to get"),
 ) -> FileResponse:
     """Gets a bulk download zip file"""
-
     try:
         path = ApiDependencies.invoker.services.bulk_download.get_path(bulk_download_item_name)
 
@@ -423,6 +423,7 @@ async def get_bulk_download_item(
             content_disposition_type="inline",
         )
         response.headers["Cache-Control"] = f"max-age={IMAGE_MAX_AGE}"
+        background_tasks.add_task(ApiDependencies.invoker.services.bulk_download.delete, bulk_download_item_name)
         return response
     except Exception:
         raise HTTPException(status_code=404)
diff --git a/invokeai/app/services/bulk_download/bulk_download_base.py b/invokeai/app/services/bulk_download/bulk_download_base.py
index 7a4aa0661c..a1071f254a 100644
--- a/invokeai/app/services/bulk_download/bulk_download_base.py
+++ b/invokeai/app/services/bulk_download/bulk_download_base.py
@@ -59,3 +59,11 @@ class BulkDownloadBase(ABC):
         Returns:
             None
         """
+
+    @abstractmethod
+    def delete(self, bulk_download_item_name: str) -> None:
+        """
+        Delete the bulk download file.
+
+        :param bulk_download_item_name: The name of the bulk download item.
+        """
diff --git a/invokeai/app/services/bulk_download/bulk_download_default.py b/invokeai/app/services/bulk_download/bulk_download_default.py
index a9ea12bfd6..a0abb6743a 100644
--- a/invokeai/app/services/bulk_download/bulk_download_default.py
+++ b/invokeai/app/services/bulk_download/bulk_download_default.py
@@ -38,23 +38,6 @@ class BulkDownloadService(BulkDownloadBase):
         self.__bulk_downloads_folder = self.__output_folder / "bulk_downloads"
         self.__bulk_downloads_folder.mkdir(parents=True, exist_ok=True)
 
-    def get_path(self, bulk_download_item_name: str) -> str:
-        """
-        Get the path to the bulk download file.
-
-        :param bulk_download_item_name: The name of the bulk download item.
-        :return: The path to the bulk download file.
-        """
-        path = str(self.__bulk_downloads_folder / bulk_download_item_name)
-        if not self.validate_path(path):
-            raise BulkDownloadTargetException()
-        return path
-
-    def validate_path(self, path: Union[str, Path]) -> bool:
-        """Validates the path given for a bulk download."""
-        path = path if isinstance(path, Path) else Path(path)
-        return path.exists()
-
     def handler(self, image_names: list[str], board_id: Optional[str]) -> None:
         """
         Create a zip file containing the images specified by the given image names or board id.
@@ -166,3 +149,29 @@ class BulkDownloadService(BulkDownloadBase):
         # Delete all the files
         for file in files:
             file.unlink()
+
+    def delete(self, bulk_download_item_name: str) -> None:
+        """
+        Delete the bulk download file.
+
+        :param bulk_download_item_name: The name of the bulk download item.
+        """
+        path = self.get_path(bulk_download_item_name)
+        Path(path).unlink()
+
+    def get_path(self, bulk_download_item_name: str) -> str:
+        """
+        Get the path to the bulk download file.
+
+        :param bulk_download_item_name: The name of the bulk download item.
+        :return: The path to the bulk download file.
+        """
+        path = str(self.__bulk_downloads_folder / bulk_download_item_name)
+        if not self.validate_path(path):
+            raise BulkDownloadTargetException()
+        return path
+
+    def validate_path(self, path: Union[str, Path]) -> bool:
+        """Validates the path given for a bulk download."""
+        path = path if isinstance(path, Path) else Path(path)
+        return path.exists()
diff --git a/tests/app/services/bulk_download/test_bulk_download.py b/tests/app/services/bulk_download/test_bulk_download.py
index 4f476c21be..4c9dc42612 100644
--- a/tests/app/services/bulk_download/test_bulk_download.py
+++ b/tests/app/services/bulk_download/test_bulk_download.py
@@ -293,7 +293,7 @@ def test_handler_on_generic_exception(
 
     monkeypatch.setattr(mock_invoker.services.images, "get_dto", mock_get_board_name)
 
-    with pytest.raises(Exception):
+    with pytest.raises(Exception): # noqa: B017
         execute_handler_test_on_error(tmp_path, monkeypatch, mock_image_dto, mock_invoker, exception)
 
     event_bus: DummyEventService = mock_invoker.services.events
@@ -317,3 +317,17 @@ def execute_handler_test_on_error(
     assert event_bus.events[0].event_name == "bulk_download_started"
     assert event_bus.events[1].event_name == "bulk_download_failed"
     assert event_bus.events[1].payload["error"] == error.__str__()
+
+
+def test_delete(tmp_path: Path, monkeypatch: Any, mock_image_dto: ImageDTO, mock_invoker: Invoker):
+    """Test that the delete method removes the bulk download file."""
+
+    bulk_download_service = BulkDownloadService(tmp_path)
+
+    mock_file: Path = tmp_path / "bulk_downloads" / "test.zip"
+    mock_file.write_text("contents")
+
+    bulk_download_service.delete("test.zip")
+
+    assert (tmp_path / "bulk_downloads").exists()
+    assert len(os.listdir(tmp_path / "bulk_downloads")) == 0

From 39c01a833dbc17a3a03232d2c96bdae3c57c3cdd Mon Sep 17 00:00:00 2001
From: Stefan Tobler <toblerlstefan@gmail.com>
Date: Mon, 15 Jan 2024 19:11:03 -0500
Subject: [PATCH 202/411] adding test coverage for new bulk download routes

---
 pyproject.toml                                |   1 +
 tests/app/routers/test_images.py              | 145 ++++++++++++++++++
 .../bulk_download/test_bulk_download.py       |   2 +-
 3 files changed, 147 insertions(+), 1 deletion(-)
 create mode 100644 tests/app/routers/test_images.py

diff --git a/pyproject.toml b/pyproject.toml
index f57607bc0a..5345851951 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -119,6 +119,7 @@ dependencies = [
   "pytest-cov",
   "pytest-datadir",
   "requests_testadapter",
+  "httpx",
 ]
 
 [project.scripts]
diff --git a/tests/app/routers/test_images.py b/tests/app/routers/test_images.py
new file mode 100644
index 0000000000..040ae01914
--- /dev/null
+++ b/tests/app/routers/test_images.py
@@ -0,0 +1,145 @@
+from pathlib import Path
+from typing import Any
+
+import pytest
+from fastapi import BackgroundTasks
+from fastapi.testclient import TestClient
+
+from invokeai.app.api.dependencies import ApiDependencies
+from invokeai.app.api_app import app
+from invokeai.app.services.board_records.board_records_sqlite import SqliteBoardRecordStorage
+from invokeai.app.services.bulk_download.bulk_download_default import BulkDownloadService
+from invokeai.app.services.config.config_default import InvokeAIAppConfig
+from invokeai.app.services.images.images_default import ImageService
+from invokeai.app.services.invocation_services import InvocationServices
+from invokeai.app.services.invoker import Invoker
+from invokeai.backend.util.logging import InvokeAILogger
+from tests.fixtures.sqlite_database import create_mock_sqlite_database
+
+client = TestClient(app)
+
+
+@pytest.fixture
+def mock_services(tmp_path: Path) -> InvocationServices:
+    configuration = InvokeAIAppConfig(use_memory_db=True, node_cache_size=0)
+    logger = InvokeAILogger.get_logger()
+    db = create_mock_sqlite_database(configuration, logger)
+
+    return InvocationServices(
+        board_image_records=None,  # type: ignore
+        board_images=None,  # type: ignore
+        board_records=SqliteBoardRecordStorage(db=db),
+        boards=None,  # type: ignore
+        bulk_download=BulkDownloadService(tmp_path),
+        configuration=None,  # type: ignore
+        events=None,  # type: ignore
+        graph_execution_manager=None,  # type: ignore
+        image_files=None,  # type: ignore
+        image_records=None,  # type: ignore
+        images=ImageService(),
+        invocation_cache=None,  # type: ignore
+        latents=None,  # type: ignore
+        logger=logger,
+        model_manager=None,  # type: ignore
+        model_records=None,  # type: ignore
+        download_queue=None,  # type: ignore
+        model_install=None,  # type: ignore
+        names=None,  # type: ignore
+        performance_statistics=None,  # type: ignore
+        processor=None,  # type: ignore
+        queue=None,  # type: ignore
+        session_processor=None,  # type: ignore
+        session_queue=None,  # type: ignore
+        urls=None,  # type: ignore
+        workflow_records=None,  # type: ignore
+    )
+
+
+@pytest.fixture()
+def mock_invoker(mock_services: InvocationServices) -> Invoker:
+    return Invoker(services=mock_services)
+
+
+class MockApiDependencies(ApiDependencies):
+    invoker: Invoker
+
+    def __init__(self, invoker) -> None:
+        self.invoker = invoker
+
+
+def test_download_images_from_list(monkeypatch: Any, mock_invoker: Invoker) -> None:
+    prepare_download_images_test(monkeypatch, mock_invoker)
+
+    response = client.post("/api/v1/images/download", json={"image_names": ["test.png"]})
+
+    assert response.status_code == 202
+
+
+def test_download_images_from_board_id_empty_image_name_list(monkeypatch: Any, mock_invoker: Invoker) -> None:
+    prepare_download_images_test(monkeypatch, mock_invoker)
+
+    response = client.post("/api/v1/images/download", json={"image_names": [], "board_id": "test"})
+
+    assert response.status_code == 202
+
+
+def prepare_download_images_test(monkeypatch: Any, mock_invoker: Invoker) -> None:
+    monkeypatch.setattr("invokeai.app.api.routers.images.ApiDependencies", MockApiDependencies(mock_invoker))
+
+    def mock_add_task(*args, **kwargs):
+        return None
+
+    monkeypatch.setattr(BackgroundTasks, "add_task", mock_add_task)
+
+
+def test_download_images_with_empty_image_list_and_no_board_id(monkeypatch: Any, mock_invoker: Invoker) -> None:
+    prepare_download_images_test(monkeypatch, mock_invoker)
+
+    response = client.post("/api/v1/images/download", json={"image_names": []})
+
+    assert response.status_code == 400
+
+
+def test_get_bulk_download_image(tmp_path: Path, monkeypatch: Any, mock_invoker: Invoker) -> None:
+    mock_file: Path = tmp_path / "test.zip"
+    mock_file.write_text("contents")
+
+    monkeypatch.setattr(mock_invoker.services.bulk_download, "get_path", lambda x: str(mock_file))
+    monkeypatch.setattr("invokeai.app.api.routers.images.ApiDependencies", MockApiDependencies(mock_invoker))
+
+    def mock_add_task(*args, **kwargs):
+        return None
+
+    monkeypatch.setattr(BackgroundTasks, "add_task", mock_add_task)
+
+    response = client.get("/api/v1/images/download/test.zip")
+
+    assert response.status_code == 200
+    assert response.content == b"contents"
+
+
+def test_get_bulk_download_image_not_found(monkeypatch: Any, mock_invoker: Invoker) -> None:
+    monkeypatch.setattr("invokeai.app.api.routers.images.ApiDependencies", MockApiDependencies(mock_invoker))
+
+    def mock_add_task(*args, **kwargs):
+        return None
+
+    monkeypatch.setattr(BackgroundTasks, "add_task", mock_add_task)
+
+    response = client.get("/api/v1/images/download/test.zip")
+
+    assert response.status_code == 404
+
+
+def test_get_bulk_download_image_image_deleted_after_response(
+    monkeypatch: Any, mock_invoker: Invoker, tmp_path: Path
+) -> None:
+    mock_file: Path = tmp_path / "test.zip"
+    mock_file.write_text("contents")
+
+    monkeypatch.setattr(mock_invoker.services.bulk_download, "get_path", lambda x: str(mock_file))
+    monkeypatch.setattr("invokeai.app.api.routers.images.ApiDependencies", MockApiDependencies(mock_invoker))
+
+    client.get("/api/v1/images/download/test.zip")
+
+    assert not (tmp_path / "test.zip").exists()
diff --git a/tests/app/services/bulk_download/test_bulk_download.py b/tests/app/services/bulk_download/test_bulk_download.py
index 4c9dc42612..bc6eb8d41c 100644
--- a/tests/app/services/bulk_download/test_bulk_download.py
+++ b/tests/app/services/bulk_download/test_bulk_download.py
@@ -293,7 +293,7 @@ def test_handler_on_generic_exception(
 
     monkeypatch.setattr(mock_invoker.services.images, "get_dto", mock_get_board_name)
 
-    with pytest.raises(Exception): # noqa: B017
+    with pytest.raises(Exception):  # noqa: B017
         execute_handler_test_on_error(tmp_path, monkeypatch, mock_image_dto, mock_invoker, exception)
 
     event_bus: DummyEventService = mock_invoker.services.events

From b5ca1643a607e3d1c6a7d9f2b3eb48baf55a376a Mon Sep 17 00:00:00 2001
From: Stefan Tobler <toblerlstefan@gmail.com>
Date: Sun, 28 Jan 2024 00:38:01 -0500
Subject: [PATCH 203/411] narrowing bulk_download stop service scope

---
 .../bulk_download/bulk_download_default.py    |  4 ++--
 .../bulk_download/test_bulk_download.py       | 20 ++++++++++++++++++-
 2 files changed, 21 insertions(+), 3 deletions(-)

diff --git a/invokeai/app/services/bulk_download/bulk_download_default.py b/invokeai/app/services/bulk_download/bulk_download_default.py
index a0abb6743a..87966ad622 100644
--- a/invokeai/app/services/bulk_download/bulk_download_default.py
+++ b/invokeai/app/services/bulk_download/bulk_download_default.py
@@ -143,8 +143,8 @@ class BulkDownloadService(BulkDownloadBase):
 
     def stop(self, *args, **kwargs):
         """Stop the bulk download service and delete the files in the bulk download folder."""
-        # Get all the files in the bulk downloads folder
-        files = self.__bulk_downloads_folder.glob("*")
+        # Get all the files in the bulk downloads folder, only .zip files
+        files = self.__bulk_downloads_folder.glob("*.zip")
 
         # Delete all the files
         for file in files:
diff --git a/tests/app/services/bulk_download/test_bulk_download.py b/tests/app/services/bulk_download/test_bulk_download.py
index bc6eb8d41c..184519866a 100644
--- a/tests/app/services/bulk_download/test_bulk_download.py
+++ b/tests/app/services/bulk_download/test_bulk_download.py
@@ -319,7 +319,7 @@ def execute_handler_test_on_error(
     assert event_bus.events[1].payload["error"] == error.__str__()
 
 
-def test_delete(tmp_path: Path, monkeypatch: Any, mock_image_dto: ImageDTO, mock_invoker: Invoker):
+def test_delete(tmp_path: Path):
     """Test that the delete method removes the bulk download file."""
 
     bulk_download_service = BulkDownloadService(tmp_path)
@@ -331,3 +331,21 @@ def test_delete(tmp_path: Path, monkeypatch: Any, mock_image_dto: ImageDTO, mock
 
     assert (tmp_path / "bulk_downloads").exists()
     assert len(os.listdir(tmp_path / "bulk_downloads")) == 0
+
+def test_stop(tmp_path: Path):
+    """Test that the delete method removes the bulk download file."""
+
+    bulk_download_service = BulkDownloadService(tmp_path)
+
+    mock_file: Path = tmp_path / "bulk_downloads" / "test.zip"
+    mock_file.write_text("contents")
+
+    mock_dir: Path = tmp_path / "bulk_downloads" / "test"
+    mock_dir.mkdir(parents=True, exist_ok=True)
+
+
+    bulk_download_service.stop()
+
+    assert (tmp_path / "bulk_downloads").exists()
+    assert mock_dir.exists()
+    assert len(os.listdir(tmp_path / "bulk_downloads")) == 1

From d0f3571e59cc1ec28b8d25e031557ca5d46dd5b7 Mon Sep 17 00:00:00 2001
From: Stefan Tobler <toblerlstefan@gmail.com>
Date: Sun, 28 Jan 2024 01:23:38 -0500
Subject: [PATCH 204/411] returning the bulk_download_item_name on response for
 possible polling

---
 invokeai/app/api/routers/images.py            | 28 +++++--
 .../bulk_download/bulk_download_base.py       | 11 ++-
 .../bulk_download/bulk_download_default.py    |  9 ++-
 tests/app/routers/test_images.py              | 22 +++++-
 .../bulk_download/test_bulk_download.py       | 79 ++++++++++++++-----
 5 files changed, 116 insertions(+), 33 deletions(-)

diff --git a/invokeai/app/api/routers/images.py b/invokeai/app/api/routers/images.py
index d11c89c749..c12556aed6 100644
--- a/invokeai/app/api/routers/images.py
+++ b/invokeai/app/api/routers/images.py
@@ -1,6 +1,6 @@
 import io
 import traceback
-from typing import Optional
+from typing import Optional, cast
 
 from fastapi import BackgroundTasks, Body, HTTPException, Path, Query, Request, Response, UploadFile
 from fastapi.responses import FileResponse
@@ -13,6 +13,7 @@ from invokeai.app.services.image_records.image_records_common import ImageCatego
 from invokeai.app.services.images.images_common import ImageDTO, ImageUrlsDTO
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
 from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID, WorkflowWithoutIDValidator
+from invokeai.app.util.misc import uuid_string
 
 from ..dependencies import ApiDependencies
 
@@ -377,6 +378,7 @@ class ImagesDownloaded(BaseModel):
     response: Optional[str] = Field(
         description="If defined, the message to display to the user when images begin downloading"
     )
+    bulk_download_item_name: str = Field(description="The bulk download item name of the bulk download item")
 
 
 @images_router.post(
@@ -384,15 +386,31 @@ class ImagesDownloaded(BaseModel):
 )
 async def download_images_from_list(
     background_tasks: BackgroundTasks,
-    image_names: list[str] = Body(description="The list of names of images to download", embed=True),
+    image_names: Optional[list[str]] = Body(
+        default=None, description="The list of names of images to download", embed=True
+    ),
     board_id: Optional[str] = Body(
         default=None, description="The board from which image should be downloaded from", embed=True
     ),
 ) -> ImagesDownloaded:
     if (image_names is None or len(image_names) == 0) and board_id is None:
         raise HTTPException(status_code=400, detail="No images or board id specified.")
-    background_tasks.add_task(ApiDependencies.invoker.services.bulk_download.handler, image_names, board_id)
-    return ImagesDownloaded(response="Your images are preparing to be downloaded")
+    bulk_download_item_id: str = uuid_string() if board_id is None else board_id
+    board_name: str = (
+        "" if board_id is None else ApiDependencies.invoker.services.board_records.get(board_id).board_name
+    )
+
+    # Type narrowing handled above ^, we know that image_names is not None, trying to keep null checks at the boundaries
+    background_tasks.add_task(
+        ApiDependencies.invoker.services.bulk_download.handler,
+        cast(list[str], image_names),
+        board_id,
+        bulk_download_item_id,
+    )
+    return ImagesDownloaded(
+        response="Your images are preparing to be downloaded",
+        bulk_download_item_name=bulk_download_item_id if board_id is None else board_name + ".zip",
+    )
 
 
 @images_router.api_route(
@@ -410,7 +428,7 @@ async def download_images_from_list(
 )
 async def get_bulk_download_item(
     background_tasks: BackgroundTasks,
-    bulk_download_item_name: str = Path(description="The bulk_download_item_id of the bulk download item to get"),
+    bulk_download_item_name: str = Path(description="The bulk_download_item_name of the bulk download item to get"),
 ) -> FileResponse:
     """Gets a bulk download zip file"""
     try:
diff --git a/invokeai/app/services/bulk_download/bulk_download_base.py b/invokeai/app/services/bulk_download/bulk_download_base.py
index a1071f254a..d6b0e62211 100644
--- a/invokeai/app/services/bulk_download/bulk_download_base.py
+++ b/invokeai/app/services/bulk_download/bulk_download_base.py
@@ -26,7 +26,7 @@ class BulkDownloadBase(ABC):
         """
 
     @abstractmethod
-    def handler(self, image_names: list[str], board_id: Optional[str]) -> None:
+    def handler(self, image_names: list[str], board_id: Optional[str], bulk_download_item_id: Optional[str]) -> None:
         """
         Starts a a bulk download job.
 
@@ -44,6 +44,15 @@ class BulkDownloadBase(ABC):
         :return: The path to the bulk download file.
         """
 
+    @abstractmethod
+    def get_board_name(self, board_id: str) -> str:
+        """
+        Get the name of the board.
+
+        :param board_id: The ID of the board.
+        :return: The name of the board.
+        """
+
     @abstractmethod
     def stop(self, *args, **kwargs) -> None:
         """
diff --git a/invokeai/app/services/bulk_download/bulk_download_default.py b/invokeai/app/services/bulk_download/bulk_download_default.py
index 87966ad622..be70dea2c1 100644
--- a/invokeai/app/services/bulk_download/bulk_download_default.py
+++ b/invokeai/app/services/bulk_download/bulk_download_default.py
@@ -38,7 +38,7 @@ class BulkDownloadService(BulkDownloadBase):
         self.__bulk_downloads_folder = self.__output_folder / "bulk_downloads"
         self.__bulk_downloads_folder.mkdir(parents=True, exist_ok=True)
 
-    def handler(self, image_names: list[str], board_id: Optional[str]) -> None:
+    def handler(self, image_names: list[str], board_id: Optional[str], bulk_download_item_id: Optional[str]) -> None:
         """
         Create a zip file containing the images specified by the given image names or board id.
 
@@ -47,7 +47,8 @@ class BulkDownloadService(BulkDownloadBase):
         """
 
         bulk_download_id: str = DEFAULT_BULK_DOWNLOAD_ID
-        bulk_download_item_id: str = uuid_string() if board_id is None else board_id
+        if bulk_download_item_id is None:
+            bulk_download_item_id = uuid_string() if board_id is None else board_id
 
         self._signal_job_started(bulk_download_id, bulk_download_item_id)
 
@@ -56,7 +57,7 @@ class BulkDownloadService(BulkDownloadBase):
             image_dtos: list[ImageDTO] = []
 
             if board_id:
-                board_name = self._get_board_name(board_id)
+                board_name = self.get_board_name(board_id)
                 board_name = self._clean_string_to_path_safe(board_name)
 
                 # -1 is the default value for limit, which means no limit, is_intermediate only gives us completed images
@@ -79,7 +80,7 @@ class BulkDownloadService(BulkDownloadBase):
             self.__invoker.services.logger.error("Problem bulk downloading images.")
             raise e
 
-    def _get_board_name(self, board_id: str) -> str:
+    def get_board_name(self, board_id: str) -> str:
         if board_id == "none":
             return "Uncategorized"
 
diff --git a/tests/app/routers/test_images.py b/tests/app/routers/test_images.py
index 040ae01914..a709daf24e 100644
--- a/tests/app/routers/test_images.py
+++ b/tests/app/routers/test_images.py
@@ -7,6 +7,7 @@ from fastapi.testclient import TestClient
 
 from invokeai.app.api.dependencies import ApiDependencies
 from invokeai.app.api_app import app
+from invokeai.app.services.board_records.board_records_common import BoardRecord
 from invokeai.app.services.board_records.board_records_sqlite import SqliteBoardRecordStorage
 from invokeai.app.services.bulk_download.bulk_download_default import BulkDownloadService
 from invokeai.app.services.config.config_default import InvokeAIAppConfig
@@ -70,17 +71,32 @@ class MockApiDependencies(ApiDependencies):
 def test_download_images_from_list(monkeypatch: Any, mock_invoker: Invoker) -> None:
     prepare_download_images_test(monkeypatch, mock_invoker)
 
-    response = client.post("/api/v1/images/download", json={"image_names": ["test.png"]})
+    def mock_uuid_string():
+        return "test"
 
+    # You have to patch the function within the module it's being imported into. This is strange, but it works.
+    # See http://www.gregreda.com/2021/06/28/mocking-imported-module-function-python/
+    monkeypatch.setattr("invokeai.app.api.routers.images.uuid_string", mock_uuid_string)
+
+    response = client.post("/api/v1/images/download", json={"image_names": ["test.png"]})
+    json_response = response.json()
     assert response.status_code == 202
+    assert json_response["bulk_download_item_name"] == "test"
 
 
 def test_download_images_from_board_id_empty_image_name_list(monkeypatch: Any, mock_invoker: Invoker) -> None:
+    expected_board_name = "test"
+
+    def mock_get(*args, **kwargs):
+        return BoardRecord(board_id="12345", board_name=expected_board_name, created_at="None", updated_at="None")
+
+    monkeypatch.setattr(mock_invoker.services.board_records, "get", mock_get)
     prepare_download_images_test(monkeypatch, mock_invoker)
 
-    response = client.post("/api/v1/images/download", json={"image_names": [], "board_id": "test"})
-
+    response = client.post("/api/v1/images/download", json={"board_id": "test"})
+    json_response = response.json()
     assert response.status_code == 202
+    assert json_response["bulk_download_item_name"] == "test.zip"
 
 
 def prepare_download_images_test(monkeypatch: Any, mock_invoker: Invoker) -> None:
diff --git a/tests/app/services/bulk_download/test_bulk_download.py b/tests/app/services/bulk_download/test_bulk_download.py
index 184519866a..7909c44214 100644
--- a/tests/app/services/bulk_download/test_bulk_download.py
+++ b/tests/app/services/bulk_download/test_bulk_download.py
@@ -125,7 +125,7 @@ def test_handler_image_names(tmp_path: Path, monkeypatch: Any, mock_image_dto: I
 
     bulk_download_service = BulkDownloadService(tmp_path)
     bulk_download_service.start(mock_invoker)
-    bulk_download_service.handler([mock_image_dto.image_name], None)
+    bulk_download_service.handler([mock_image_dto.image_name], None, None)
 
     assert_handler_success(
         expected_zip_path, expected_image_path, mock_image_contents, tmp_path, mock_invoker.services.events
@@ -151,7 +151,7 @@ def test_handler_board_id(tmp_path: Path, monkeypatch: Any, mock_image_dto: Imag
 
     bulk_download_service = BulkDownloadService(tmp_path)
     bulk_download_service.start(mock_invoker)
-    bulk_download_service.handler([], "test")
+    bulk_download_service.handler([], "test", None)
 
     assert_handler_success(
         expected_zip_path, expected_image_path, mock_image_contents, tmp_path, mock_invoker.services.events
@@ -173,7 +173,31 @@ def test_handler_board_id_default(tmp_path: Path, monkeypatch: Any, mock_image_d
 
     bulk_download_service = BulkDownloadService(tmp_path)
     bulk_download_service.start(mock_invoker)
-    bulk_download_service.handler([], "none")
+    bulk_download_service.handler([], "none", None)
+
+    assert_handler_success(
+        expected_zip_path, expected_image_path, mock_image_contents, tmp_path, mock_invoker.services.events
+    )
+
+
+def test_handler_bulk_download__item_id_given(
+    tmp_path: Path, monkeypatch: Any, mock_image_dto: ImageDTO, mock_invoker: Invoker
+):
+    """Test that the handler creates the zip file correctly when given a pregenerated bulk download item id."""
+
+    _, expected_image_path, mock_image_contents = prepare_handler_test(
+        tmp_path, monkeypatch, mock_image_dto, mock_invoker
+    )
+    expected_zip_path: Path = tmp_path / "bulk_downloads" / "test_id.zip"
+
+    def mock_get_many(*args, **kwargs):
+        return OffsetPaginatedResults(limit=-1, total=1, offset=0, items=[mock_image_dto])
+
+    monkeypatch.setattr(mock_invoker.services.images, "get_many", mock_get_many)
+
+    bulk_download_service = BulkDownloadService(tmp_path)
+    bulk_download_service.start(mock_invoker)
+    bulk_download_service.handler([mock_image_dto.image_name], None, "test_id")
 
     assert_handler_success(
         expected_zip_path, expected_image_path, mock_image_contents, tmp_path, mock_invoker.services.events
@@ -242,20 +266,6 @@ def assert_handler_success(
     assert event_bus.events[1].payload["bulk_download_item_name"] == os.path.basename(expected_zip_path)
 
 
-def test_stop(tmp_path: Path) -> None:
-    """Test that the stop method removes the bulk_downloads directory."""
-
-    bulk_download_service = BulkDownloadService(tmp_path)
-
-    mock_file: Path = tmp_path / "bulk_downloads" / "test.zip"
-    mock_file.write_text("contents")
-
-    bulk_download_service.stop()
-
-    assert (tmp_path / "bulk_downloads").exists()
-    assert len(os.listdir(tmp_path / "bulk_downloads")) == 0
-
-
 def test_handler_on_image_not_found(tmp_path: Path, monkeypatch: Any, mock_image_dto: ImageDTO, mock_invoker: Invoker):
     """Test that the handler emits an error event when the image is not found."""
     exception: Exception = ImageRecordNotFoundException("Image not found")
@@ -309,7 +319,7 @@ def execute_handler_test_on_error(
 ):
     bulk_download_service = BulkDownloadService(tmp_path)
     bulk_download_service.start(mock_invoker)
-    bulk_download_service.handler([mock_image_dto.image_name], None)
+    bulk_download_service.handler([mock_image_dto.image_name], None, None)
 
     event_bus: DummyEventService = mock_invoker.services.events
 
@@ -319,6 +329,35 @@ def execute_handler_test_on_error(
     assert event_bus.events[1].payload["error"] == error.__str__()
 
 
+def test_get_board_name(tmp_path: Path, monkeypatch: Any, mock_invoker: Invoker):
+    """Test that the get_board_name function returns the correct board name."""
+
+    expected_board_name = "board1"
+
+    def mock_get(*args, **kwargs):
+        return BoardRecord(board_id="12345", board_name=expected_board_name, created_at="None", updated_at="None")
+
+    monkeypatch.setattr(mock_invoker.services.board_records, "get", mock_get)
+
+    bulk_download_service = BulkDownloadService(tmp_path)
+    bulk_download_service.start(mock_invoker)
+    board_name = bulk_download_service.get_board_name("12345")
+
+    assert board_name == expected_board_name
+
+
+def test_get_board_name_default(tmp_path: Path, mock_invoker: Invoker):
+    """Test that the get_board_name function returns the correct board name."""
+
+    expected_board_name = "Uncategorized"
+
+    bulk_download_service = BulkDownloadService(tmp_path)
+    bulk_download_service.start(mock_invoker)
+    board_name = bulk_download_service.get_board_name("none")
+
+    assert board_name == expected_board_name
+
+
 def test_delete(tmp_path: Path):
     """Test that the delete method removes the bulk download file."""
 
@@ -332,8 +371,9 @@ def test_delete(tmp_path: Path):
     assert (tmp_path / "bulk_downloads").exists()
     assert len(os.listdir(tmp_path / "bulk_downloads")) == 0
 
+
 def test_stop(tmp_path: Path):
-    """Test that the delete method removes the bulk download file."""
+    """Test that the stop method removes the bulk download file and not any directories."""
 
     bulk_download_service = BulkDownloadService(tmp_path)
 
@@ -343,7 +383,6 @@ def test_stop(tmp_path: Path):
     mock_dir: Path = tmp_path / "bulk_downloads" / "test"
     mock_dir.mkdir(parents=True, exist_ok=True)
 
-
     bulk_download_service.stop()
 
     assert (tmp_path / "bulk_downloads").exists()

From f15aa562c2343bd91e1f892d16e3105a60a9b886 Mon Sep 17 00:00:00 2001
From: Stefan Tobler <toblerlstefan@gmail.com>
Date: Sun, 28 Jan 2024 18:59:56 -0500
Subject: [PATCH 205/411] using temp directory for downloads

---
 invokeai/app/api/routers/images.py            |  2 +-
 .../bulk_download/bulk_download_base.py       |  2 +-
 .../bulk_download/bulk_download_default.py    | 18 +++++-----
 .../bulk_download/test_bulk_download.py       | 35 ++++++++++++++-----
 4 files changed, 37 insertions(+), 20 deletions(-)

diff --git a/invokeai/app/api/routers/images.py b/invokeai/app/api/routers/images.py
index c12556aed6..69a76e4062 100644
--- a/invokeai/app/api/routers/images.py
+++ b/invokeai/app/api/routers/images.py
@@ -397,7 +397,7 @@ async def download_images_from_list(
         raise HTTPException(status_code=400, detail="No images or board id specified.")
     bulk_download_item_id: str = uuid_string() if board_id is None else board_id
     board_name: str = (
-        "" if board_id is None else ApiDependencies.invoker.services.board_records.get(board_id).board_name
+        "" if board_id is None else ApiDependencies.invoker.services.bulk_download.get_clean_board_name(board_id)
     )
 
     # Type narrowing handled above ^, we know that image_names is not None, trying to keep null checks at the boundaries
diff --git a/invokeai/app/services/bulk_download/bulk_download_base.py b/invokeai/app/services/bulk_download/bulk_download_base.py
index d6b0e62211..89b2e73772 100644
--- a/invokeai/app/services/bulk_download/bulk_download_base.py
+++ b/invokeai/app/services/bulk_download/bulk_download_base.py
@@ -45,7 +45,7 @@ class BulkDownloadBase(ABC):
         """
 
     @abstractmethod
-    def get_board_name(self, board_id: str) -> str:
+    def get_clean_board_name(self, board_id: str) -> str:
         """
         Get the name of the board.
 
diff --git a/invokeai/app/services/bulk_download/bulk_download_default.py b/invokeai/app/services/bulk_download/bulk_download_default.py
index be70dea2c1..fe76a12333 100644
--- a/invokeai/app/services/bulk_download/bulk_download_default.py
+++ b/invokeai/app/services/bulk_download/bulk_download_default.py
@@ -1,4 +1,5 @@
 from pathlib import Path
+from tempfile import TemporaryDirectory
 from typing import Optional, Union
 from zipfile import ZipFile
 
@@ -19,6 +20,7 @@ from .bulk_download_base import BulkDownloadBase
 
 class BulkDownloadService(BulkDownloadBase):
     __output_folder: Path
+    __temp_directory: TemporaryDirectory
     __bulk_downloads_folder: Path
     __event_bus: EventServiceBase
     __invoker: Invoker
@@ -35,7 +37,8 @@ class BulkDownloadService(BulkDownloadBase):
         Initialize the downloader object.
         """
         self.__output_folder: Path = output_folder if isinstance(output_folder, Path) else Path(output_folder)
-        self.__bulk_downloads_folder = self.__output_folder / "bulk_downloads"
+        self.__temp_directory = TemporaryDirectory(dir=self.__output_folder)
+        self.__bulk_downloads_folder = Path(self.__temp_directory.name) / "bulk_downloads"
         self.__bulk_downloads_folder.mkdir(parents=True, exist_ok=True)
 
     def handler(self, image_names: list[str], board_id: Optional[str], bulk_download_item_id: Optional[str]) -> None:
@@ -57,8 +60,7 @@ class BulkDownloadService(BulkDownloadBase):
             image_dtos: list[ImageDTO] = []
 
             if board_id:
-                board_name = self.get_board_name(board_id)
-                board_name = self._clean_string_to_path_safe(board_name)
+                board_name = self.get_clean_board_name(board_id)
 
                 # -1 is the default value for limit, which means no limit, is_intermediate only gives us completed images
                 image_dtos = self.__invoker.services.images.get_many(
@@ -80,11 +82,11 @@ class BulkDownloadService(BulkDownloadBase):
             self.__invoker.services.logger.error("Problem bulk downloading images.")
             raise e
 
-    def get_board_name(self, board_id: str) -> str:
+    def get_clean_board_name(self, board_id: str) -> str:
         if board_id == "none":
             return "Uncategorized"
 
-        return self.__invoker.services.board_records.get(board_id).board_name
+        return self._clean_string_to_path_safe(self.__invoker.services.board_records.get(board_id).board_name)
 
     def _create_zip_file(self, image_dtos: list[ImageDTO], bulk_download_item_id: str) -> str:
         """
@@ -145,11 +147,7 @@ class BulkDownloadService(BulkDownloadBase):
     def stop(self, *args, **kwargs):
         """Stop the bulk download service and delete the files in the bulk download folder."""
         # Get all the files in the bulk downloads folder, only .zip files
-        files = self.__bulk_downloads_folder.glob("*.zip")
-
-        # Delete all the files
-        for file in files:
-            file.unlink()
+        self.__temp_directory.cleanup()
 
     def delete(self, bulk_download_item_name: str) -> None:
         """
diff --git a/tests/app/services/bulk_download/test_bulk_download.py b/tests/app/services/bulk_download/test_bulk_download.py
index 7909c44214..3cd2123232 100644
--- a/tests/app/services/bulk_download/test_bulk_download.py
+++ b/tests/app/services/bulk_download/test_bulk_download.py
@@ -1,5 +1,6 @@
 import os
 from pathlib import Path
+from tempfile import TemporaryDirectory
 from typing import Any
 from zipfile import ZipFile
 
@@ -86,9 +87,28 @@ def mock_invoker(mock_services: InvocationServices) -> Invoker:
     return Invoker(services=mock_services)
 
 
+@pytest.fixture(autouse=True)
+def mock_temporary_directory(monkeypatch: Any, tmp_path: Path):
+    """Mock the TemporaryDirectory class so that it uses the tmp_path fixture."""
+
+    class MockTemporaryDirectory(TemporaryDirectory):
+        def __init__(self):
+            super().__init__(dir=tmp_path)
+            self.name = tmp_path
+
+    def mock_TemporaryDirectory(*args, **kwargs):
+        return MockTemporaryDirectory()
+
+    monkeypatch.setattr(
+        "invokeai.app.services.bulk_download.bulk_download_default.TemporaryDirectory", mock_TemporaryDirectory
+    )
+
+
 def test_get_path_when_file_exists(tmp_path: Path) -> None:
     """Test get_path when the file exists."""
 
+    bulk_download_service = BulkDownloadService(tmp_path)
+
     # Create a directory at tmp_path/bulk_downloads
     test_bulk_downloads_dir: Path = tmp_path / "bulk_downloads"
     test_bulk_downloads_dir.mkdir(parents=True, exist_ok=True)
@@ -97,7 +117,6 @@ def test_get_path_when_file_exists(tmp_path: Path) -> None:
     test_file_path: Path = test_bulk_downloads_dir / "test.zip"
     test_file_path.touch()
 
-    bulk_download_service = BulkDownloadService(tmp_path)
     assert bulk_download_service.get_path("test.zip") == str(test_file_path)
 
 
@@ -164,7 +183,6 @@ def test_handler_board_id_default(tmp_path: Path, monkeypatch: Any, mock_image_d
     _, expected_image_path, mock_image_contents = prepare_handler_test(
         tmp_path, monkeypatch, mock_image_dto, mock_invoker
     )
-    expected_zip_path: Path = tmp_path / "bulk_downloads" / "Uncategorized.zip"
 
     def mock_get_many(*args, **kwargs):
         return OffsetPaginatedResults(limit=-1, total=1, offset=0, items=[mock_image_dto])
@@ -175,6 +193,8 @@ def test_handler_board_id_default(tmp_path: Path, monkeypatch: Any, mock_image_d
     bulk_download_service.start(mock_invoker)
     bulk_download_service.handler([], "none", None)
 
+    expected_zip_path: Path = tmp_path / "bulk_downloads" / "Uncategorized.zip"
+
     assert_handler_success(
         expected_zip_path, expected_image_path, mock_image_contents, tmp_path, mock_invoker.services.events
     )
@@ -188,7 +208,6 @@ def test_handler_bulk_download__item_id_given(
     _, expected_image_path, mock_image_contents = prepare_handler_test(
         tmp_path, monkeypatch, mock_image_dto, mock_invoker
     )
-    expected_zip_path: Path = tmp_path / "bulk_downloads" / "test_id.zip"
 
     def mock_get_many(*args, **kwargs):
         return OffsetPaginatedResults(limit=-1, total=1, offset=0, items=[mock_image_dto])
@@ -199,6 +218,8 @@ def test_handler_bulk_download__item_id_given(
     bulk_download_service.start(mock_invoker)
     bulk_download_service.handler([mock_image_dto.image_name], None, "test_id")
 
+    expected_zip_path: Path = tmp_path / "bulk_downloads" / "test_id.zip"
+
     assert_handler_success(
         expected_zip_path, expected_image_path, mock_image_contents, tmp_path, mock_invoker.services.events
     )
@@ -341,7 +362,7 @@ def test_get_board_name(tmp_path: Path, monkeypatch: Any, mock_invoker: Invoker)
 
     bulk_download_service = BulkDownloadService(tmp_path)
     bulk_download_service.start(mock_invoker)
-    board_name = bulk_download_service.get_board_name("12345")
+    board_name = bulk_download_service.get_clean_board_name("12345")
 
     assert board_name == expected_board_name
 
@@ -353,7 +374,7 @@ def test_get_board_name_default(tmp_path: Path, mock_invoker: Invoker):
 
     bulk_download_service = BulkDownloadService(tmp_path)
     bulk_download_service.start(mock_invoker)
-    board_name = bulk_download_service.get_board_name("none")
+    board_name = bulk_download_service.get_clean_board_name("none")
 
     assert board_name == expected_board_name
 
@@ -385,6 +406,4 @@ def test_stop(tmp_path: Path):
 
     bulk_download_service.stop()
 
-    assert (tmp_path / "bulk_downloads").exists()
-    assert mock_dir.exists()
-    assert len(os.listdir(tmp_path / "bulk_downloads")) == 1
+    assert not (tmp_path / "bulk_downloads").exists()

From 5f4b406cfe084aa430b7750caa6550d0dc12d6b7 Mon Sep 17 00:00:00 2001
From: Stefan Tobler <toblerlstefan@gmail.com>
Date: Fri, 16 Feb 2024 14:10:50 -0500
Subject: [PATCH 206/411] updating imports to satisfy ruff

---
 tests/app/services/bulk_download/test_bulk_download.py | 2 +-
 tests/conftest.py                                      | 6 ++++++
 2 files changed, 7 insertions(+), 1 deletion(-)

diff --git a/tests/app/services/bulk_download/test_bulk_download.py b/tests/app/services/bulk_download/test_bulk_download.py
index 3cd2123232..924385f7e1 100644
--- a/tests/app/services/bulk_download/test_bulk_download.py
+++ b/tests/app/services/bulk_download/test_bulk_download.py
@@ -22,7 +22,7 @@ from invokeai.app.services.invocation_services import InvocationServices
 from invokeai.app.services.invoker import Invoker
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
 from invokeai.backend.util.logging import InvokeAILogger
-from tests.fixtures.event_service import DummyEventService, mock_event_service  # noqa: F401,F811
+from tests.fixtures.event_service import DummyEventService
 from tests.fixtures.sqlite_database import create_mock_sqlite_database
 
 
diff --git a/tests/conftest.py b/tests/conftest.py
index 1c81600229..85fecfe440 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -1,2 +1,8 @@
 # conftest.py is a special pytest file. Fixtures defined in this file will be accessible to all tests in this directory
 # without needing to explicitly import them. (https://docs.pytest.org/en/6.2.x/fixture.html)
+
+
+# We import the model_installer and torch_device fixtures here so that they can be used by all tests. Flake8 does not
+# play well with fixtures (F401 and F811), so this is cleaner than importing in all files that use these fixtures.
+from invokeai.backend.util.test_utils import torch_device  # noqa: F401
+from tests.fixtures.event_service import mock_event_service  # noqa: F401

From b5a9ed351d8764dc3dfdcfd3176b69adc00b1bf4 Mon Sep 17 00:00:00 2001
From: Stefan Tobler <toblerlstefan@gmail.com>
Date: Fri, 16 Feb 2024 15:50:48 -0500
Subject: [PATCH 207/411] moving the responsibility of cleaning up board names
 to the service not the route

---
 invokeai/app/api/routers/images.py            |  8 +--
 .../bulk_download/bulk_download_base.py       | 18 ++---
 .../bulk_download/bulk_download_default.py    | 23 +++---
 tests/app/routers/test_images.py              | 13 ++--
 .../bulk_download/test_bulk_download.py       | 71 ++++++++++---------
 5 files changed, 63 insertions(+), 70 deletions(-)

diff --git a/invokeai/app/api/routers/images.py b/invokeai/app/api/routers/images.py
index 69a76e4062..d1c64648de 100644
--- a/invokeai/app/api/routers/images.py
+++ b/invokeai/app/api/routers/images.py
@@ -13,7 +13,6 @@ from invokeai.app.services.image_records.image_records_common import ImageCatego
 from invokeai.app.services.images.images_common import ImageDTO, ImageUrlsDTO
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
 from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID, WorkflowWithoutIDValidator
-from invokeai.app.util.misc import uuid_string
 
 from ..dependencies import ApiDependencies
 
@@ -395,10 +394,7 @@ async def download_images_from_list(
 ) -> ImagesDownloaded:
     if (image_names is None or len(image_names) == 0) and board_id is None:
         raise HTTPException(status_code=400, detail="No images or board id specified.")
-    bulk_download_item_id: str = uuid_string() if board_id is None else board_id
-    board_name: str = (
-        "" if board_id is None else ApiDependencies.invoker.services.bulk_download.get_clean_board_name(board_id)
-    )
+    bulk_download_item_id: str = ApiDependencies.invoker.services.bulk_download.generate_item_id(board_id)
 
     # Type narrowing handled above ^, we know that image_names is not None, trying to keep null checks at the boundaries
     background_tasks.add_task(
@@ -409,7 +405,7 @@ async def download_images_from_list(
     )
     return ImagesDownloaded(
         response="Your images are preparing to be downloaded",
-        bulk_download_item_name=bulk_download_item_id if board_id is None else board_name + ".zip",
+        bulk_download_item_name=bulk_download_item_id + ".zip",
     )
 
 
diff --git a/invokeai/app/services/bulk_download/bulk_download_base.py b/invokeai/app/services/bulk_download/bulk_download_base.py
index 89b2e73772..5199652ad4 100644
--- a/invokeai/app/services/bulk_download/bulk_download_base.py
+++ b/invokeai/app/services/bulk_download/bulk_download_base.py
@@ -30,9 +30,9 @@ class BulkDownloadBase(ABC):
         """
         Starts a a bulk download job.
 
-        :param invoker: The Invoker that holds all the services, required to be passed as a parameter to avoid circular dependencies.
         :param image_names: A list of image names to include in the zip file.
         :param board_id: The ID of the board. If provided, all images associated with the board will be included in the zip file.
+        :param bulk_download_item_id: The bulk_download_item_id that will be used to retrieve the bulk download item when it is prepared, if none is provided a uuid will be generated.
         """
 
     @abstractmethod
@@ -45,12 +45,12 @@ class BulkDownloadBase(ABC):
         """
 
     @abstractmethod
-    def get_clean_board_name(self, board_id: str) -> str:
+    def generate_item_id(self, board_id: Optional[str]) -> str:
         """
-        Get the name of the board.
+        Generate an item ID for a bulk download item.
 
-        :param board_id: The ID of the board.
-        :return: The name of the board.
+        :param board_id: The ID of the board whose name is to be included in the item id.
+        :return: The generated item ID.
         """
 
     @abstractmethod
@@ -61,12 +61,8 @@ class BulkDownloadBase(ABC):
         This method is responsible for stopping the BulkDownloadService and performing any necessary cleanup
         operations to remove any remnants or resources associated with the service.
 
-        Args:
-            *args: Variable length argument list.
-            **kwargs: Arbitrary keyword arguments.
-
-        Returns:
-            None
+        :param *args: Variable length argument list.
+        :param **kwargs: Arbitrary keyword arguments.
         """
 
     @abstractmethod
diff --git a/invokeai/app/services/bulk_download/bulk_download_default.py b/invokeai/app/services/bulk_download/bulk_download_default.py
index fe76a12333..406bd7d997 100644
--- a/invokeai/app/services/bulk_download/bulk_download_default.py
+++ b/invokeai/app/services/bulk_download/bulk_download_default.py
@@ -50,19 +50,15 @@ class BulkDownloadService(BulkDownloadBase):
         """
 
         bulk_download_id: str = DEFAULT_BULK_DOWNLOAD_ID
-        if bulk_download_item_id is None:
-            bulk_download_item_id = uuid_string() if board_id is None else board_id
+        bulk_download_item_id = uuid_string() if bulk_download_item_id is None else bulk_download_item_id
 
         self._signal_job_started(bulk_download_id, bulk_download_item_id)
 
         try:
-            board_name: str = ""
             image_dtos: list[ImageDTO] = []
 
             if board_id:
-                board_name = self.get_clean_board_name(board_id)
-
-                # -1 is the default value for limit, which means no limit, is_intermediate only gives us completed images
+                # -1 is the default value for limit, which means no limit, is_intermediate False only gives us completed images
                 image_dtos = self.__invoker.services.images.get_many(
                     offset=0,
                     limit=-1,
@@ -71,9 +67,7 @@ class BulkDownloadService(BulkDownloadBase):
                 ).items
             else:
                 image_dtos = [self.__invoker.services.images.get_dto(image_name) for image_name in image_names]
-            bulk_download_item_name: str = self._create_zip_file(
-                image_dtos, bulk_download_item_id if board_id is None else board_name
-            )
+            bulk_download_item_name: str = self._create_zip_file(image_dtos, bulk_download_item_id)
             self._signal_job_completed(bulk_download_id, bulk_download_item_id, bulk_download_item_name)
         except (ImageRecordNotFoundException, BoardRecordNotFoundException, BulkDownloadException) as e:
             self._signal_job_failed(bulk_download_id, bulk_download_item_id, e)
@@ -82,7 +76,10 @@ class BulkDownloadService(BulkDownloadBase):
             self.__invoker.services.logger.error("Problem bulk downloading images.")
             raise e
 
-    def get_clean_board_name(self, board_id: str) -> str:
+    def generate_item_id(self, board_id: Optional[str]) -> str:
+        return uuid_string() if board_id is None else self._get_clean_board_name(board_id) + "_" + uuid_string()
+
+    def _get_clean_board_name(self, board_id: str) -> str:
         if board_id == "none":
             return "Uncategorized"
 
@@ -109,7 +106,7 @@ class BulkDownloadService(BulkDownloadBase):
     # from https://stackoverflow.com/questions/7406102/create-sane-safe-filename-from-any-unsafe-string
     def _clean_string_to_path_safe(self, s: str) -> str:
         """Clean a string to be path safe."""
-        return "".join([c for c in s if c.isalpha() or c.isdigit() or c == " "]).rstrip()
+        return "".join([c for c in s if c.isalpha() or c.isdigit() or c == " " or c == "_" or c == "-"]).rstrip()
 
     def _signal_job_started(self, bulk_download_id: str, bulk_download_item_id: str) -> None:
         """Signal that a bulk download job has started."""
@@ -166,11 +163,11 @@ class BulkDownloadService(BulkDownloadBase):
         :return: The path to the bulk download file.
         """
         path = str(self.__bulk_downloads_folder / bulk_download_item_name)
-        if not self.validate_path(path):
+        if not self._is_valid_path(path):
             raise BulkDownloadTargetException()
         return path
 
-    def validate_path(self, path: Union[str, Path]) -> bool:
+    def _is_valid_path(self, path: Union[str, Path]) -> bool:
         """Validates the path given for a bulk download."""
         path = path if isinstance(path, Path) else Path(path)
         return path.exists()
diff --git a/tests/app/routers/test_images.py b/tests/app/routers/test_images.py
index a709daf24e..e8521bf132 100644
--- a/tests/app/routers/test_images.py
+++ b/tests/app/routers/test_images.py
@@ -71,17 +71,10 @@ class MockApiDependencies(ApiDependencies):
 def test_download_images_from_list(monkeypatch: Any, mock_invoker: Invoker) -> None:
     prepare_download_images_test(monkeypatch, mock_invoker)
 
-    def mock_uuid_string():
-        return "test"
-
-    # You have to patch the function within the module it's being imported into. This is strange, but it works.
-    # See http://www.gregreda.com/2021/06/28/mocking-imported-module-function-python/
-    monkeypatch.setattr("invokeai.app.api.routers.images.uuid_string", mock_uuid_string)
-
     response = client.post("/api/v1/images/download", json={"image_names": ["test.png"]})
     json_response = response.json()
     assert response.status_code == 202
-    assert json_response["bulk_download_item_name"] == "test"
+    assert json_response["bulk_download_item_name"] == "test.zip"
 
 
 def test_download_images_from_board_id_empty_image_name_list(monkeypatch: Any, mock_invoker: Invoker) -> None:
@@ -101,6 +94,10 @@ def test_download_images_from_board_id_empty_image_name_list(monkeypatch: Any, m
 
 def prepare_download_images_test(monkeypatch: Any, mock_invoker: Invoker) -> None:
     monkeypatch.setattr("invokeai.app.api.routers.images.ApiDependencies", MockApiDependencies(mock_invoker))
+    monkeypatch.setattr(
+        "invokeai.app.api.routers.images.ApiDependencies.invoker.services.bulk_download.generate_item_id",
+        lambda arg: "test",
+    )
 
     def mock_add_task(*args, **kwargs):
         return None
diff --git a/tests/app/services/bulk_download/test_bulk_download.py b/tests/app/services/bulk_download/test_bulk_download.py
index 924385f7e1..d70510cd91 100644
--- a/tests/app/services/bulk_download/test_bulk_download.py
+++ b/tests/app/services/bulk_download/test_bulk_download.py
@@ -151,6 +151,42 @@ def test_handler_image_names(tmp_path: Path, monkeypatch: Any, mock_image_dto: I
     )
 
 
+def test_generate_id(monkeypatch: Any):
+    """Test that the generate_id method generates a unique id."""
+
+    bulk_download_service = BulkDownloadService("test")
+
+    monkeypatch.setattr("invokeai.app.services.bulk_download.bulk_download_default.uuid_string", lambda: "test")
+
+    assert bulk_download_service.generate_item_id(None) == "test"
+
+
+def test_generate_id_with_board_id(monkeypatch: Any, mock_invoker: Invoker):
+    """Test that the generate_id method generates a unique id with a board id."""
+
+    bulk_download_service = BulkDownloadService("test")
+    bulk_download_service.start(mock_invoker)
+
+    def mock_board_get(*args, **kwargs):
+        return BoardRecord(board_id="12345", board_name="test_board_name", created_at="None", updated_at="None")
+
+    monkeypatch.setattr(mock_invoker.services.board_records, "get", mock_board_get)
+
+    monkeypatch.setattr("invokeai.app.services.bulk_download.bulk_download_default.uuid_string", lambda: "test")
+
+    assert bulk_download_service.generate_item_id("12345") == "test_board_name_test"
+
+
+def test_generate_id_with_default_board_id(monkeypatch: Any):
+    """Test that the generate_id method generates a unique id with a board id."""
+
+    bulk_download_service = BulkDownloadService("test")
+
+    monkeypatch.setattr("invokeai.app.services.bulk_download.bulk_download_default.uuid_string", lambda: "test")
+
+    assert bulk_download_service.generate_item_id("none") == "Uncategorized_test"
+
+
 def test_handler_board_id(tmp_path: Path, monkeypatch: Any, mock_image_dto: ImageDTO, mock_invoker: Invoker):
     """Test that the handler creates the zip file correctly when given a board id."""
 
@@ -159,7 +195,7 @@ def test_handler_board_id(tmp_path: Path, monkeypatch: Any, mock_image_dto: Imag
     )
 
     def mock_board_get(*args, **kwargs):
-        return BoardRecord(board_id="12345", board_name="test", created_at="None", updated_at="None")
+        return BoardRecord(board_id="12345", board_name="test_board_name", created_at="None", updated_at="None")
 
     monkeypatch.setattr(mock_invoker.services.board_records, "get", mock_board_get)
 
@@ -193,14 +229,14 @@ def test_handler_board_id_default(tmp_path: Path, monkeypatch: Any, mock_image_d
     bulk_download_service.start(mock_invoker)
     bulk_download_service.handler([], "none", None)
 
-    expected_zip_path: Path = tmp_path / "bulk_downloads" / "Uncategorized.zip"
+    expected_zip_path: Path = tmp_path / "bulk_downloads" / "test.zip"
 
     assert_handler_success(
         expected_zip_path, expected_image_path, mock_image_contents, tmp_path, mock_invoker.services.events
     )
 
 
-def test_handler_bulk_download__item_id_given(
+def test_handler_bulk_download_item_id_given(
     tmp_path: Path, monkeypatch: Any, mock_image_dto: ImageDTO, mock_invoker: Invoker
 ):
     """Test that the handler creates the zip file correctly when given a pregenerated bulk download item id."""
@@ -350,35 +386,6 @@ def execute_handler_test_on_error(
     assert event_bus.events[1].payload["error"] == error.__str__()
 
 
-def test_get_board_name(tmp_path: Path, monkeypatch: Any, mock_invoker: Invoker):
-    """Test that the get_board_name function returns the correct board name."""
-
-    expected_board_name = "board1"
-
-    def mock_get(*args, **kwargs):
-        return BoardRecord(board_id="12345", board_name=expected_board_name, created_at="None", updated_at="None")
-
-    monkeypatch.setattr(mock_invoker.services.board_records, "get", mock_get)
-
-    bulk_download_service = BulkDownloadService(tmp_path)
-    bulk_download_service.start(mock_invoker)
-    board_name = bulk_download_service.get_clean_board_name("12345")
-
-    assert board_name == expected_board_name
-
-
-def test_get_board_name_default(tmp_path: Path, mock_invoker: Invoker):
-    """Test that the get_board_name function returns the correct board name."""
-
-    expected_board_name = "Uncategorized"
-
-    bulk_download_service = BulkDownloadService(tmp_path)
-    bulk_download_service.start(mock_invoker)
-    board_name = bulk_download_service.get_clean_board_name("none")
-
-    assert board_name == expected_board_name
-
-
 def test_delete(tmp_path: Path):
     """Test that the delete method removes the bulk download file."""
 

From 0ab9fe6987453bb082ea823b82689616c8bfa5e6 Mon Sep 17 00:00:00 2001
From: Stefan Tobler <toblerlstefan@gmail.com>
Date: Fri, 16 Feb 2024 22:49:38 -0500
Subject: [PATCH 208/411] relocating event_service fixture due to import
 ordering

---
 tests/app/services/bulk_download/test_bulk_download.py | 6 ++++++
 tests/conftest.py                                      | 1 -
 tests/fixtures/event_service.py                        | 7 -------
 3 files changed, 6 insertions(+), 8 deletions(-)

diff --git a/tests/app/services/bulk_download/test_bulk_download.py b/tests/app/services/bulk_download/test_bulk_download.py
index d70510cd91..b7480091d9 100644
--- a/tests/app/services/bulk_download/test_bulk_download.py
+++ b/tests/app/services/bulk_download/test_bulk_download.py
@@ -46,6 +46,12 @@ def mock_image_dto() -> ImageDTO:
     )
 
 
+@pytest.fixture
+def mock_event_service() -> DummyEventService:
+    """Create a dummy event service."""
+    return DummyEventService()
+
+
 @pytest.fixture
 def mock_services(mock_event_service: DummyEventService) -> InvocationServices:
     configuration = InvokeAIAppConfig(use_memory_db=True, node_cache_size=0)
diff --git a/tests/conftest.py b/tests/conftest.py
index 85fecfe440..873ccc13fd 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -5,4 +5,3 @@
 # We import the model_installer and torch_device fixtures here so that they can be used by all tests. Flake8 does not
 # play well with fixtures (F401 and F811), so this is cleaner than importing in all files that use these fixtures.
 from invokeai.backend.util.test_utils import torch_device  # noqa: F401
-from tests.fixtures.event_service import mock_event_service  # noqa: F401
diff --git a/tests/fixtures/event_service.py b/tests/fixtures/event_service.py
index 0a09fa0d64..8f6a45c38f 100644
--- a/tests/fixtures/event_service.py
+++ b/tests/fixtures/event_service.py
@@ -1,6 +1,5 @@
 from typing import Any, Dict, List
 
-import pytest
 from pydantic import BaseModel
 
 from invokeai.app.services.events.events_base import EventServiceBase
@@ -26,9 +25,3 @@ class DummyEventService(EventServiceBase):
     def dispatch(self, event_name: str, payload: Any) -> None:
         """Dispatch an event by appending it to self.events."""
         self.events.append(DummyEvent(event_name=payload["event"], payload=payload["data"]))
-
-
-@pytest.fixture
-def mock_event_service() -> DummyEventService:
-    """Create a dummy event service."""
-    return DummyEventService()

From 037cac81548a4e0b3076ccbb02f0db1e29dd3a02 Mon Sep 17 00:00:00 2001
From: Stefan Tobler <toblerlstefan@gmail.com>
Date: Sat, 17 Feb 2024 00:29:05 -0500
Subject: [PATCH 209/411] removing dependency on an output folder, embrace
 python temp folder for bulk download

---
 invokeai/app/api/dependencies.py              |  2 +-
 .../bulk_download/bulk_download_base.py       |  7 ++---
 .../bulk_download/bulk_download_default.py    |  9 ++-----
 tests/app/routers/test_images.py              |  2 +-
 .../bulk_download/test_bulk_download.py       | 26 +++++++++----------
 5 files changed, 19 insertions(+), 27 deletions(-)

diff --git a/invokeai/app/api/dependencies.py b/invokeai/app/api/dependencies.py
index 984fd8e267..95407291ec 100644
--- a/invokeai/app/api/dependencies.py
+++ b/invokeai/app/api/dependencies.py
@@ -82,7 +82,7 @@ class ApiDependencies:
         board_records = SqliteBoardRecordStorage(db=db)
         boards = BoardService()
         events = FastAPIEventService(event_handler_id)
-        bulk_download = BulkDownloadService(output_folder=f"{output_folder}")
+        bulk_download = BulkDownloadService()
         image_records = SqliteImageRecordStorage(db=db)
         images = ImageService()
         invocation_cache = MemoryInvocationCache(max_cache_size=config.node_cache_size)
diff --git a/invokeai/app/services/bulk_download/bulk_download_base.py b/invokeai/app/services/bulk_download/bulk_download_base.py
index 5199652ad4..d889e2ed0e 100644
--- a/invokeai/app/services/bulk_download/bulk_download_base.py
+++ b/invokeai/app/services/bulk_download/bulk_download_base.py
@@ -1,6 +1,5 @@
 from abc import ABC, abstractmethod
-from pathlib import Path
-from typing import Optional, Union
+from typing import Optional
 
 from invokeai.app.services.invoker import Invoker
 
@@ -18,11 +17,9 @@ class BulkDownloadBase(ABC):
         """
 
     @abstractmethod
-    def __init__(self, output_folder: Union[str, Path]):
+    def __init__(self):
         """
         Create BulkDownloadBase object.
-
-        :param output_folder: The path to the output folder where the bulk download files can be temporarily stored.
         """
 
     @abstractmethod
diff --git a/invokeai/app/services/bulk_download/bulk_download_default.py b/invokeai/app/services/bulk_download/bulk_download_default.py
index 406bd7d997..4f5bfb087f 100644
--- a/invokeai/app/services/bulk_download/bulk_download_default.py
+++ b/invokeai/app/services/bulk_download/bulk_download_default.py
@@ -19,7 +19,6 @@ from .bulk_download_base import BulkDownloadBase
 
 
 class BulkDownloadService(BulkDownloadBase):
-    __output_folder: Path
     __temp_directory: TemporaryDirectory
     __bulk_downloads_folder: Path
     __event_bus: EventServiceBase
@@ -29,15 +28,11 @@ class BulkDownloadService(BulkDownloadBase):
         self.__invoker = invoker
         self.__event_bus = invoker.services.events
 
-    def __init__(
-        self,
-        output_folder: Union[str, Path],
-    ):
+    def __init__(self):
         """
         Initialize the downloader object.
         """
-        self.__output_folder: Path = output_folder if isinstance(output_folder, Path) else Path(output_folder)
-        self.__temp_directory = TemporaryDirectory(dir=self.__output_folder)
+        self.__temp_directory = TemporaryDirectory()
         self.__bulk_downloads_folder = Path(self.__temp_directory.name) / "bulk_downloads"
         self.__bulk_downloads_folder.mkdir(parents=True, exist_ok=True)
 
diff --git a/tests/app/routers/test_images.py b/tests/app/routers/test_images.py
index e8521bf132..67297a116f 100644
--- a/tests/app/routers/test_images.py
+++ b/tests/app/routers/test_images.py
@@ -31,7 +31,7 @@ def mock_services(tmp_path: Path) -> InvocationServices:
         board_images=None,  # type: ignore
         board_records=SqliteBoardRecordStorage(db=db),
         boards=None,  # type: ignore
-        bulk_download=BulkDownloadService(tmp_path),
+        bulk_download=BulkDownloadService(),
         configuration=None,  # type: ignore
         events=None,  # type: ignore
         graph_execution_manager=None,  # type: ignore
diff --git a/tests/app/services/bulk_download/test_bulk_download.py b/tests/app/services/bulk_download/test_bulk_download.py
index b7480091d9..3e8b7fd2eb 100644
--- a/tests/app/services/bulk_download/test_bulk_download.py
+++ b/tests/app/services/bulk_download/test_bulk_download.py
@@ -113,7 +113,7 @@ def mock_temporary_directory(monkeypatch: Any, tmp_path: Path):
 def test_get_path_when_file_exists(tmp_path: Path) -> None:
     """Test get_path when the file exists."""
 
-    bulk_download_service = BulkDownloadService(tmp_path)
+    bulk_download_service = BulkDownloadService()
 
     # Create a directory at tmp_path/bulk_downloads
     test_bulk_downloads_dir: Path = tmp_path / "bulk_downloads"
@@ -129,7 +129,7 @@ def test_get_path_when_file_exists(tmp_path: Path) -> None:
 def test_get_path_when_file_does_not_exist(tmp_path: Path) -> None:
     """Test get_path when the file does not exist."""
 
-    bulk_download_service = BulkDownloadService(tmp_path)
+    bulk_download_service = BulkDownloadService()
     with pytest.raises(BulkDownloadTargetException):
         bulk_download_service.get_path("test")
 
@@ -137,7 +137,7 @@ def test_get_path_when_file_does_not_exist(tmp_path: Path) -> None:
 def test_bulk_downloads_dir_created_at_start(tmp_path: Path) -> None:
     """Test that the bulk_downloads directory is created at start."""
 
-    BulkDownloadService(tmp_path)
+    BulkDownloadService()
     assert (tmp_path / "bulk_downloads").exists()
 
 
@@ -148,7 +148,7 @@ def test_handler_image_names(tmp_path: Path, monkeypatch: Any, mock_image_dto: I
         tmp_path, monkeypatch, mock_image_dto, mock_invoker
     )
 
-    bulk_download_service = BulkDownloadService(tmp_path)
+    bulk_download_service = BulkDownloadService()
     bulk_download_service.start(mock_invoker)
     bulk_download_service.handler([mock_image_dto.image_name], None, None)
 
@@ -160,7 +160,7 @@ def test_handler_image_names(tmp_path: Path, monkeypatch: Any, mock_image_dto: I
 def test_generate_id(monkeypatch: Any):
     """Test that the generate_id method generates a unique id."""
 
-    bulk_download_service = BulkDownloadService("test")
+    bulk_download_service = BulkDownloadService()
 
     monkeypatch.setattr("invokeai.app.services.bulk_download.bulk_download_default.uuid_string", lambda: "test")
 
@@ -170,7 +170,7 @@ def test_generate_id(monkeypatch: Any):
 def test_generate_id_with_board_id(monkeypatch: Any, mock_invoker: Invoker):
     """Test that the generate_id method generates a unique id with a board id."""
 
-    bulk_download_service = BulkDownloadService("test")
+    bulk_download_service = BulkDownloadService()
     bulk_download_service.start(mock_invoker)
 
     def mock_board_get(*args, **kwargs):
@@ -186,7 +186,7 @@ def test_generate_id_with_board_id(monkeypatch: Any, mock_invoker: Invoker):
 def test_generate_id_with_default_board_id(monkeypatch: Any):
     """Test that the generate_id method generates a unique id with a board id."""
 
-    bulk_download_service = BulkDownloadService("test")
+    bulk_download_service = BulkDownloadService()
 
     monkeypatch.setattr("invokeai.app.services.bulk_download.bulk_download_default.uuid_string", lambda: "test")
 
@@ -210,7 +210,7 @@ def test_handler_board_id(tmp_path: Path, monkeypatch: Any, mock_image_dto: Imag
 
     monkeypatch.setattr(mock_invoker.services.images, "get_many", mock_get_many)
 
-    bulk_download_service = BulkDownloadService(tmp_path)
+    bulk_download_service = BulkDownloadService()
     bulk_download_service.start(mock_invoker)
     bulk_download_service.handler([], "test", None)
 
@@ -231,7 +231,7 @@ def test_handler_board_id_default(tmp_path: Path, monkeypatch: Any, mock_image_d
 
     monkeypatch.setattr(mock_invoker.services.images, "get_many", mock_get_many)
 
-    bulk_download_service = BulkDownloadService(tmp_path)
+    bulk_download_service = BulkDownloadService()
     bulk_download_service.start(mock_invoker)
     bulk_download_service.handler([], "none", None)
 
@@ -256,7 +256,7 @@ def test_handler_bulk_download_item_id_given(
 
     monkeypatch.setattr(mock_invoker.services.images, "get_many", mock_get_many)
 
-    bulk_download_service = BulkDownloadService(tmp_path)
+    bulk_download_service = BulkDownloadService()
     bulk_download_service.start(mock_invoker)
     bulk_download_service.handler([mock_image_dto.image_name], None, "test_id")
 
@@ -380,7 +380,7 @@ def test_handler_on_generic_exception(
 def execute_handler_test_on_error(
     tmp_path: Path, monkeypatch: Any, mock_image_dto: ImageDTO, mock_invoker: Invoker, error: Exception
 ):
-    bulk_download_service = BulkDownloadService(tmp_path)
+    bulk_download_service = BulkDownloadService()
     bulk_download_service.start(mock_invoker)
     bulk_download_service.handler([mock_image_dto.image_name], None, None)
 
@@ -395,7 +395,7 @@ def execute_handler_test_on_error(
 def test_delete(tmp_path: Path):
     """Test that the delete method removes the bulk download file."""
 
-    bulk_download_service = BulkDownloadService(tmp_path)
+    bulk_download_service = BulkDownloadService()
 
     mock_file: Path = tmp_path / "bulk_downloads" / "test.zip"
     mock_file.write_text("contents")
@@ -409,7 +409,7 @@ def test_delete(tmp_path: Path):
 def test_stop(tmp_path: Path):
     """Test that the stop method removes the bulk download file and not any directories."""
 
-    bulk_download_service = BulkDownloadService(tmp_path)
+    bulk_download_service = BulkDownloadService()
 
     mock_file: Path = tmp_path / "bulk_downloads" / "test.zip"
     mock_file.write_text("contents")

From a8d7cf4e97b15a371abe5b2441160dd50659a0a3 Mon Sep 17 00:00:00 2001
From: Stefan Tobler <toblerlstefan@gmail.com>
Date: Sat, 17 Feb 2024 23:53:38 -0500
Subject: [PATCH 210/411] refactoring handlers to do null check

---
 invokeai/app/api/routers/images.py            |  5 ++-
 .../bulk_download/bulk_download_base.py       |  4 ++-
 .../bulk_download/bulk_download_default.py    | 31 +++++++++++++------
 3 files changed, 27 insertions(+), 13 deletions(-)

diff --git a/invokeai/app/api/routers/images.py b/invokeai/app/api/routers/images.py
index d1c64648de..c3504b104d 100644
--- a/invokeai/app/api/routers/images.py
+++ b/invokeai/app/api/routers/images.py
@@ -1,6 +1,6 @@
 import io
 import traceback
-from typing import Optional, cast
+from typing import Optional
 
 from fastapi import BackgroundTasks, Body, HTTPException, Path, Query, Request, Response, UploadFile
 from fastapi.responses import FileResponse
@@ -396,10 +396,9 @@ async def download_images_from_list(
         raise HTTPException(status_code=400, detail="No images or board id specified.")
     bulk_download_item_id: str = ApiDependencies.invoker.services.bulk_download.generate_item_id(board_id)
 
-    # Type narrowing handled above ^, we know that image_names is not None, trying to keep null checks at the boundaries
     background_tasks.add_task(
         ApiDependencies.invoker.services.bulk_download.handler,
-        cast(list[str], image_names),
+        image_names,
         board_id,
         bulk_download_item_id,
     )
diff --git a/invokeai/app/services/bulk_download/bulk_download_base.py b/invokeai/app/services/bulk_download/bulk_download_base.py
index d889e2ed0e..80a2ddfb25 100644
--- a/invokeai/app/services/bulk_download/bulk_download_base.py
+++ b/invokeai/app/services/bulk_download/bulk_download_base.py
@@ -23,7 +23,9 @@ class BulkDownloadBase(ABC):
         """
 
     @abstractmethod
-    def handler(self, image_names: list[str], board_id: Optional[str], bulk_download_item_id: Optional[str]) -> None:
+    def handler(
+        self, image_names: Optional[list[str]], board_id: Optional[str], bulk_download_item_id: Optional[str]
+    ) -> None:
         """
         Starts a a bulk download job.
 
diff --git a/invokeai/app/services/bulk_download/bulk_download_default.py b/invokeai/app/services/bulk_download/bulk_download_default.py
index 4f5bfb087f..72bb5a5d52 100644
--- a/invokeai/app/services/bulk_download/bulk_download_default.py
+++ b/invokeai/app/services/bulk_download/bulk_download_default.py
@@ -7,6 +7,7 @@ from invokeai.app.services.board_records.board_records_common import BoardRecord
 from invokeai.app.services.bulk_download.bulk_download_common import (
     DEFAULT_BULK_DOWNLOAD_ID,
     BulkDownloadException,
+    BulkDownloadParametersException,
     BulkDownloadTargetException,
 )
 from invokeai.app.services.events.events_base import EventServiceBase
@@ -36,7 +37,9 @@ class BulkDownloadService(BulkDownloadBase):
         self.__bulk_downloads_folder = Path(self.__temp_directory.name) / "bulk_downloads"
         self.__bulk_downloads_folder.mkdir(parents=True, exist_ok=True)
 
-    def handler(self, image_names: list[str], board_id: Optional[str], bulk_download_item_id: Optional[str]) -> None:
+    def handler(
+        self, image_names: Optional[list[str]], board_id: Optional[str], bulk_download_item_id: Optional[str]
+    ) -> None:
         """
         Create a zip file containing the images specified by the given image names or board id.
 
@@ -53,15 +56,12 @@ class BulkDownloadService(BulkDownloadBase):
             image_dtos: list[ImageDTO] = []
 
             if board_id:
-                # -1 is the default value for limit, which means no limit, is_intermediate False only gives us completed images
-                image_dtos = self.__invoker.services.images.get_many(
-                    offset=0,
-                    limit=-1,
-                    board_id=board_id,
-                    is_intermediate=False,
-                ).items
+                image_dtos = self._board_handler(board_id)
+            elif image_names:
+                image_dtos = self._image_handler(image_names)
             else:
-                image_dtos = [self.__invoker.services.images.get_dto(image_name) for image_name in image_names]
+                raise BulkDownloadParametersException()
+
             bulk_download_item_name: str = self._create_zip_file(image_dtos, bulk_download_item_id)
             self._signal_job_completed(bulk_download_id, bulk_download_item_id, bulk_download_item_name)
         except (ImageRecordNotFoundException, BoardRecordNotFoundException, BulkDownloadException) as e:
@@ -71,6 +71,19 @@ class BulkDownloadService(BulkDownloadBase):
             self.__invoker.services.logger.error("Problem bulk downloading images.")
             raise e
 
+    def _image_handler(self, image_names: list[str]) -> list[ImageDTO]:
+        return [self.__invoker.services.images.get_dto(image_name) for image_name in image_names]
+
+    def _board_handler(self, board_id: str) -> list[ImageDTO]:
+        # -1 is the default value for limit, which means no limit, is_intermediate False only gives us completed images
+        image_dtos = self.__invoker.services.images.get_many(
+            offset=0,
+            limit=-1,
+            board_id=board_id,
+            is_intermediate=False,
+        ).items
+        return image_dtos
+
     def generate_item_id(self, board_id: Optional[str]) -> str:
         return uuid_string() if board_id is None else self._get_clean_board_name(board_id) + "_" + uuid_string()
 

From e51867756a1fe02e73fd12ca2c327528ee91d33f Mon Sep 17 00:00:00 2001
From: Stefan Tobler <toblerlstefan@gmail.com>
Date: Mon, 19 Feb 2024 13:54:48 -0500
Subject: [PATCH 211/411] adding bulk_download_item_name to socket events

---
 .../bulk_download/bulk_download_default.py    | 24 ++++++++++++++-----
 invokeai/app/services/events/events_base.py   | 10 ++++++--
 2 files changed, 26 insertions(+), 8 deletions(-)

diff --git a/invokeai/app/services/bulk_download/bulk_download_default.py b/invokeai/app/services/bulk_download/bulk_download_default.py
index 72bb5a5d52..4d0d2e7b0f 100644
--- a/invokeai/app/services/bulk_download/bulk_download_default.py
+++ b/invokeai/app/services/bulk_download/bulk_download_default.py
@@ -49,8 +49,9 @@ class BulkDownloadService(BulkDownloadBase):
 
         bulk_download_id: str = DEFAULT_BULK_DOWNLOAD_ID
         bulk_download_item_id = uuid_string() if bulk_download_item_id is None else bulk_download_item_id
+        bulk_download_item_name = bulk_download_item_id + ".zip"
 
-        self._signal_job_started(bulk_download_id, bulk_download_item_id)
+        self._signal_job_started(bulk_download_id, bulk_download_item_id, bulk_download_item_name)
 
         try:
             image_dtos: list[ImageDTO] = []
@@ -64,10 +65,15 @@ class BulkDownloadService(BulkDownloadBase):
 
             bulk_download_item_name: str = self._create_zip_file(image_dtos, bulk_download_item_id)
             self._signal_job_completed(bulk_download_id, bulk_download_item_id, bulk_download_item_name)
-        except (ImageRecordNotFoundException, BoardRecordNotFoundException, BulkDownloadException) as e:
-            self._signal_job_failed(bulk_download_id, bulk_download_item_id, e)
+        except (
+            ImageRecordNotFoundException,
+            BoardRecordNotFoundException,
+            BulkDownloadException,
+            BulkDownloadParametersException,
+        ) as e:
+            self._signal_job_failed(bulk_download_id, bulk_download_item_id, bulk_download_item_name, e)
         except Exception as e:
-            self._signal_job_failed(bulk_download_id, bulk_download_item_id, e)
+            self._signal_job_failed(bulk_download_id, bulk_download_item_id, bulk_download_item_name, e)
             self.__invoker.services.logger.error("Problem bulk downloading images.")
             raise e
 
@@ -116,13 +122,16 @@ class BulkDownloadService(BulkDownloadBase):
         """Clean a string to be path safe."""
         return "".join([c for c in s if c.isalpha() or c.isdigit() or c == " " or c == "_" or c == "-"]).rstrip()
 
-    def _signal_job_started(self, bulk_download_id: str, bulk_download_item_id: str) -> None:
+    def _signal_job_started(
+        self, bulk_download_id: str, bulk_download_item_id: str, bulk_download_item_name: str
+    ) -> None:
         """Signal that a bulk download job has started."""
         if self.__event_bus:
             assert bulk_download_id is not None
             self.__event_bus.emit_bulk_download_started(
                 bulk_download_id=bulk_download_id,
                 bulk_download_item_id=bulk_download_item_id,
+                bulk_download_item_name=bulk_download_item_name,
             )
 
     def _signal_job_completed(
@@ -138,7 +147,9 @@ class BulkDownloadService(BulkDownloadBase):
                 bulk_download_item_name=bulk_download_item_name,
             )
 
-    def _signal_job_failed(self, bulk_download_id: str, bulk_download_item_id: str, exception: Exception) -> None:
+    def _signal_job_failed(
+        self, bulk_download_id: str, bulk_download_item_id: str, bulk_download_item_name: str, exception: Exception
+    ) -> None:
         """Signal that a bulk download job has failed."""
         if self.__event_bus:
             assert bulk_download_id is not None
@@ -146,6 +157,7 @@ class BulkDownloadService(BulkDownloadBase):
             self.__event_bus.emit_bulk_download_failed(
                 bulk_download_id=bulk_download_id,
                 bulk_download_item_id=bulk_download_item_id,
+                bulk_download_item_name=bulk_download_item_name,
                 error=str(exception),
             )
 
diff --git a/invokeai/app/services/events/events_base.py b/invokeai/app/services/events/events_base.py
index 3cc3ba2f28..53df14330f 100644
--- a/invokeai/app/services/events/events_base.py
+++ b/invokeai/app/services/events/events_base.py
@@ -440,13 +440,16 @@ class EventServiceBase:
             },
         )
 
-    def emit_bulk_download_started(self, bulk_download_id: str, bulk_download_item_id: str) -> None:
+    def emit_bulk_download_started(
+        self, bulk_download_id: str, bulk_download_item_id: str, bulk_download_item_name: str
+    ) -> None:
         """Emitted when a bulk download starts"""
         self._emit_bulk_download_event(
             event_name="bulk_download_started",
             payload={
                 "bulk_download_id": bulk_download_id,
                 "bulk_download_item_id": bulk_download_item_id,
+                "bulk_download_item_name": bulk_download_item_name,
             },
         )
 
@@ -463,13 +466,16 @@ class EventServiceBase:
             },
         )
 
-    def emit_bulk_download_failed(self, bulk_download_id: str, bulk_download_item_id: str, error: str) -> None:
+    def emit_bulk_download_failed(
+        self, bulk_download_id: str, bulk_download_item_id: str, bulk_download_item_name: str, error: str
+    ) -> None:
         """Emitted when a bulk download fails"""
         self._emit_bulk_download_event(
             event_name="bulk_download_failed",
             payload={
                 "bulk_download_id": bulk_download_id,
                 "bulk_download_item_id": bulk_download_item_id,
+                "bulk_download_item_name": bulk_download_item_name,
                 "error": error,
             },
         )

From 7f8f182a00b2f8f0b870354a296b827ddacba979 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 20 Feb 2024 17:47:04 +1100
Subject: [PATCH 212/411] tidy(bulk_download): clean up comments

---
 .../bulk_download/bulk_download_base.py       | 12 ++--------
 .../bulk_download/bulk_download_default.py    | 23 -------------------
 2 files changed, 2 insertions(+), 33 deletions(-)

diff --git a/invokeai/app/services/bulk_download/bulk_download_base.py b/invokeai/app/services/bulk_download/bulk_download_base.py
index 80a2ddfb25..f085d384a9 100644
--- a/invokeai/app/services/bulk_download/bulk_download_base.py
+++ b/invokeai/app/services/bulk_download/bulk_download_base.py
@@ -27,7 +27,7 @@ class BulkDownloadBase(ABC):
         self, image_names: Optional[list[str]], board_id: Optional[str], bulk_download_item_id: Optional[str]
     ) -> None:
         """
-        Starts a a bulk download job.
+        Create a zip file containing the images specified by the given image names or board id.
 
         :param image_names: A list of image names to include in the zip file.
         :param board_id: The ID of the board. If provided, all images associated with the board will be included in the zip file.
@@ -54,15 +54,7 @@ class BulkDownloadBase(ABC):
 
     @abstractmethod
     def stop(self, *args, **kwargs) -> None:
-        """
-        Stops the BulkDownloadService and cleans up all the remnants.
-
-        This method is responsible for stopping the BulkDownloadService and performing any necessary cleanup
-        operations to remove any remnants or resources associated with the service.
-
-        :param *args: Variable length argument list.
-        :param **kwargs: Arbitrary keyword arguments.
-        """
+        """Stops the BulkDownloadService and cleans up."""
 
     @abstractmethod
     def delete(self, bulk_download_item_name: str) -> None:
diff --git a/invokeai/app/services/bulk_download/bulk_download_default.py b/invokeai/app/services/bulk_download/bulk_download_default.py
index 4d0d2e7b0f..670703db9b 100644
--- a/invokeai/app/services/bulk_download/bulk_download_default.py
+++ b/invokeai/app/services/bulk_download/bulk_download_default.py
@@ -30,9 +30,6 @@ class BulkDownloadService(BulkDownloadBase):
         self.__event_bus = invoker.services.events
 
     def __init__(self):
-        """
-        Initialize the downloader object.
-        """
         self.__temp_directory = TemporaryDirectory()
         self.__bulk_downloads_folder = Path(self.__temp_directory.name) / "bulk_downloads"
         self.__bulk_downloads_folder.mkdir(parents=True, exist_ok=True)
@@ -40,13 +37,6 @@ class BulkDownloadService(BulkDownloadBase):
     def handler(
         self, image_names: Optional[list[str]], board_id: Optional[str], bulk_download_item_id: Optional[str]
     ) -> None:
-        """
-        Create a zip file containing the images specified by the given image names or board id.
-
-        param: image_names: A list of image names to include in the zip file.
-        param: board_id: The ID of the board. If provided, all images associated with the board will be included in the zip file.
-        """
-
         bulk_download_id: str = DEFAULT_BULK_DOWNLOAD_ID
         bulk_download_item_id = uuid_string() if bulk_download_item_id is None else bulk_download_item_id
         bulk_download_item_name = bulk_download_item_id + ".zip"
@@ -162,26 +152,13 @@ class BulkDownloadService(BulkDownloadBase):
             )
 
     def stop(self, *args, **kwargs):
-        """Stop the bulk download service and delete the files in the bulk download folder."""
-        # Get all the files in the bulk downloads folder, only .zip files
         self.__temp_directory.cleanup()
 
     def delete(self, bulk_download_item_name: str) -> None:
-        """
-        Delete the bulk download file.
-
-        :param bulk_download_item_name: The name of the bulk download item.
-        """
         path = self.get_path(bulk_download_item_name)
         Path(path).unlink()
 
     def get_path(self, bulk_download_item_name: str) -> str:
-        """
-        Get the path to the bulk download file.
-
-        :param bulk_download_item_name: The name of the bulk download item.
-        :return: The path to the bulk download file.
-        """
         path = str(self.__bulk_downloads_folder / bulk_download_item_name)
         if not self._is_valid_path(path):
             raise BulkDownloadTargetException()

From bf3b10cb1c96d149433e4a36e7c456dd80940148 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 20 Feb 2024 17:48:51 +1100
Subject: [PATCH 213/411] tidy(bulk_download): remove extraneous abstract
 methods

`start`, `stop` and `__init__` are not required in implementations of an ABC or service.
---
 .../bulk_download/bulk_download_base.py       | 23 +------------------
 1 file changed, 1 insertion(+), 22 deletions(-)

diff --git a/invokeai/app/services/bulk_download/bulk_download_base.py b/invokeai/app/services/bulk_download/bulk_download_base.py
index f085d384a9..617b611f56 100644
--- a/invokeai/app/services/bulk_download/bulk_download_base.py
+++ b/invokeai/app/services/bulk_download/bulk_download_base.py
@@ -1,26 +1,9 @@
 from abc import ABC, abstractmethod
 from typing import Optional
 
-from invokeai.app.services.invoker import Invoker
-
 
 class BulkDownloadBase(ABC):
-    @abstractmethod
-    def start(self, invoker: Invoker) -> None:
-        """
-        Starts the BulkDownloadService.
-
-        This method is responsible for starting the BulkDownloadService and performing any necessary initialization
-        operations to prepare the service for use.
-
-        param: invoker: The Invoker that holds all the services, required to be passed as a parameter to avoid circular dependencies.
-        """
-
-    @abstractmethod
-    def __init__(self):
-        """
-        Create BulkDownloadBase object.
-        """
+    """Responsible for creating a zip file containing the images specified by the given image names or board id."""
 
     @abstractmethod
     def handler(
@@ -52,10 +35,6 @@ class BulkDownloadBase(ABC):
         :return: The generated item ID.
         """
 
-    @abstractmethod
-    def stop(self, *args, **kwargs) -> None:
-        """Stops the BulkDownloadService and cleans up."""
-
     @abstractmethod
     def delete(self, bulk_download_item_name: str) -> None:
         """

From 2291122c2b0c1b60ab214fa88c997f59c72abf77 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 20 Feb 2024 17:50:10 +1100
Subject: [PATCH 214/411] tidy(bulk_download): remove class-level attr
 annotations

These can be misleading as they shadow actual assigned class attributes. This pattern is in the rest of the app but it shouldn't be.
---
 .../app/services/bulk_download/bulk_download_default.py     | 6 ------
 1 file changed, 6 deletions(-)

diff --git a/invokeai/app/services/bulk_download/bulk_download_default.py b/invokeai/app/services/bulk_download/bulk_download_default.py
index 670703db9b..b44501a8d9 100644
--- a/invokeai/app/services/bulk_download/bulk_download_default.py
+++ b/invokeai/app/services/bulk_download/bulk_download_default.py
@@ -10,7 +10,6 @@ from invokeai.app.services.bulk_download.bulk_download_common import (
     BulkDownloadParametersException,
     BulkDownloadTargetException,
 )
-from invokeai.app.services.events.events_base import EventServiceBase
 from invokeai.app.services.image_records.image_records_common import ImageRecordNotFoundException
 from invokeai.app.services.images.images_common import ImageDTO
 from invokeai.app.services.invoker import Invoker
@@ -20,11 +19,6 @@ from .bulk_download_base import BulkDownloadBase
 
 
 class BulkDownloadService(BulkDownloadBase):
-    __temp_directory: TemporaryDirectory
-    __bulk_downloads_folder: Path
-    __event_bus: EventServiceBase
-    __invoker: Invoker
-
     def start(self, invoker: Invoker) -> None:
         self.__invoker = invoker
         self.__event_bus = invoker.services.events

From 38af234108f6759a8af9cf4bb9d9e04201d131e9 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 20 Feb 2024 17:52:39 +1100
Subject: [PATCH 215/411] tidy(bulk_download): use single underscore for
 private attrs

Double underscores are used in the app but it doesn't actually do or convey anything that single underscores don't already do. Considered unpythonic except for actual dunder/magic methods.
---
 .../bulk_download/bulk_download_default.py    | 38 +++++++++----------
 1 file changed, 19 insertions(+), 19 deletions(-)

diff --git a/invokeai/app/services/bulk_download/bulk_download_default.py b/invokeai/app/services/bulk_download/bulk_download_default.py
index b44501a8d9..f8475b8f6e 100644
--- a/invokeai/app/services/bulk_download/bulk_download_default.py
+++ b/invokeai/app/services/bulk_download/bulk_download_default.py
@@ -20,13 +20,13 @@ from .bulk_download_base import BulkDownloadBase
 
 class BulkDownloadService(BulkDownloadBase):
     def start(self, invoker: Invoker) -> None:
-        self.__invoker = invoker
-        self.__event_bus = invoker.services.events
+        self._invoker = invoker
+        self._event_bus = invoker.services.events
 
     def __init__(self):
-        self.__temp_directory = TemporaryDirectory()
-        self.__bulk_downloads_folder = Path(self.__temp_directory.name) / "bulk_downloads"
-        self.__bulk_downloads_folder.mkdir(parents=True, exist_ok=True)
+        self._temp_directory = TemporaryDirectory()
+        self._bulk_downloads_folder = Path(self._temp_directory.name) / "bulk_downloads"
+        self._bulk_downloads_folder.mkdir(parents=True, exist_ok=True)
 
     def handler(
         self, image_names: Optional[list[str]], board_id: Optional[str], bulk_download_item_id: Optional[str]
@@ -58,15 +58,15 @@ class BulkDownloadService(BulkDownloadBase):
             self._signal_job_failed(bulk_download_id, bulk_download_item_id, bulk_download_item_name, e)
         except Exception as e:
             self._signal_job_failed(bulk_download_id, bulk_download_item_id, bulk_download_item_name, e)
-            self.__invoker.services.logger.error("Problem bulk downloading images.")
+            self._invoker.services.logger.error("Problem bulk downloading images.")
             raise e
 
     def _image_handler(self, image_names: list[str]) -> list[ImageDTO]:
-        return [self.__invoker.services.images.get_dto(image_name) for image_name in image_names]
+        return [self._invoker.services.images.get_dto(image_name) for image_name in image_names]
 
     def _board_handler(self, board_id: str) -> list[ImageDTO]:
         # -1 is the default value for limit, which means no limit, is_intermediate False only gives us completed images
-        image_dtos = self.__invoker.services.images.get_many(
+        image_dtos = self._invoker.services.images.get_many(
             offset=0,
             limit=-1,
             board_id=board_id,
@@ -81,7 +81,7 @@ class BulkDownloadService(BulkDownloadBase):
         if board_id == "none":
             return "Uncategorized"
 
-        return self._clean_string_to_path_safe(self.__invoker.services.board_records.get(board_id).board_name)
+        return self._clean_string_to_path_safe(self._invoker.services.board_records.get(board_id).board_name)
 
     def _create_zip_file(self, image_dtos: list[ImageDTO], bulk_download_item_id: str) -> str:
         """
@@ -91,12 +91,12 @@ class BulkDownloadService(BulkDownloadBase):
         :return: The name of the zip file.
         """
         zip_file_name = bulk_download_item_id + ".zip"
-        zip_file_path = self.__bulk_downloads_folder / (zip_file_name)
+        zip_file_path = self._bulk_downloads_folder / (zip_file_name)
 
         with ZipFile(zip_file_path, "w") as zip_file:
             for image_dto in image_dtos:
                 image_zip_path = Path(image_dto.image_category.value) / image_dto.image_name
-                image_disk_path = self.__invoker.services.images.get_path(image_dto.image_name)
+                image_disk_path = self._invoker.services.images.get_path(image_dto.image_name)
                 zip_file.write(image_disk_path, arcname=image_zip_path)
 
         return str(zip_file_name)
@@ -110,9 +110,9 @@ class BulkDownloadService(BulkDownloadBase):
         self, bulk_download_id: str, bulk_download_item_id: str, bulk_download_item_name: str
     ) -> None:
         """Signal that a bulk download job has started."""
-        if self.__event_bus:
+        if self._event_bus:
             assert bulk_download_id is not None
-            self.__event_bus.emit_bulk_download_started(
+            self._event_bus.emit_bulk_download_started(
                 bulk_download_id=bulk_download_id,
                 bulk_download_item_id=bulk_download_item_id,
                 bulk_download_item_name=bulk_download_item_name,
@@ -122,10 +122,10 @@ class BulkDownloadService(BulkDownloadBase):
         self, bulk_download_id: str, bulk_download_item_id: str, bulk_download_item_name: str
     ) -> None:
         """Signal that a bulk download job has completed."""
-        if self.__event_bus:
+        if self._event_bus:
             assert bulk_download_id is not None
             assert bulk_download_item_name is not None
-            self.__event_bus.emit_bulk_download_completed(
+            self._event_bus.emit_bulk_download_completed(
                 bulk_download_id=bulk_download_id,
                 bulk_download_item_id=bulk_download_item_id,
                 bulk_download_item_name=bulk_download_item_name,
@@ -135,10 +135,10 @@ class BulkDownloadService(BulkDownloadBase):
         self, bulk_download_id: str, bulk_download_item_id: str, bulk_download_item_name: str, exception: Exception
     ) -> None:
         """Signal that a bulk download job has failed."""
-        if self.__event_bus:
+        if self._event_bus:
             assert bulk_download_id is not None
             assert exception is not None
-            self.__event_bus.emit_bulk_download_failed(
+            self._event_bus.emit_bulk_download_failed(
                 bulk_download_id=bulk_download_id,
                 bulk_download_item_id=bulk_download_item_id,
                 bulk_download_item_name=bulk_download_item_name,
@@ -146,14 +146,14 @@ class BulkDownloadService(BulkDownloadBase):
             )
 
     def stop(self, *args, **kwargs):
-        self.__temp_directory.cleanup()
+        self._temp_directory.cleanup()
 
     def delete(self, bulk_download_item_name: str) -> None:
         path = self.get_path(bulk_download_item_name)
         Path(path).unlink()
 
     def get_path(self, bulk_download_item_name: str) -> str:
-        path = str(self.__bulk_downloads_folder / bulk_download_item_name)
+        path = str(self._bulk_downloads_folder / bulk_download_item_name)
         if not self._is_valid_path(path):
             raise BulkDownloadTargetException()
         return path

From 80c67dd6e0c0d21f4e41f3242f410f8f1116fa23 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 20 Feb 2024 17:55:13 +1100
Subject: [PATCH 216/411] tidy(bulk_download): nit - use `or` as a coalescing
 operator

Just a bit cleaner.
---
 invokeai/app/services/bulk_download/bulk_download_default.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/invokeai/app/services/bulk_download/bulk_download_default.py b/invokeai/app/services/bulk_download/bulk_download_default.py
index f8475b8f6e..6c49957a5c 100644
--- a/invokeai/app/services/bulk_download/bulk_download_default.py
+++ b/invokeai/app/services/bulk_download/bulk_download_default.py
@@ -32,7 +32,7 @@ class BulkDownloadService(BulkDownloadBase):
         self, image_names: Optional[list[str]], board_id: Optional[str], bulk_download_item_id: Optional[str]
     ) -> None:
         bulk_download_id: str = DEFAULT_BULK_DOWNLOAD_ID
-        bulk_download_item_id = uuid_string() if bulk_download_item_id is None else bulk_download_item_id
+        bulk_download_item_id = bulk_download_item_id or uuid_string()
         bulk_download_item_name = bulk_download_item_id + ".zip"
 
         self._signal_job_started(bulk_download_id, bulk_download_item_id, bulk_download_item_name)

From 98441ad08d72f7ff9e791cf744a877c23bd05de6 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 20 Feb 2024 17:58:21 +1100
Subject: [PATCH 217/411] tidy(bulk_download): do not rely on pagination API to
 get all images for board

We can get all images for the board as a list of image names, then pass that to `_image_handler` to get the DTOs, decoupling from the pagination API.
---
 .../services/bulk_download/bulk_download_default.py    | 10 ++--------
 1 file changed, 2 insertions(+), 8 deletions(-)

diff --git a/invokeai/app/services/bulk_download/bulk_download_default.py b/invokeai/app/services/bulk_download/bulk_download_default.py
index 6c49957a5c..9fad0c3443 100644
--- a/invokeai/app/services/bulk_download/bulk_download_default.py
+++ b/invokeai/app/services/bulk_download/bulk_download_default.py
@@ -65,14 +65,8 @@ class BulkDownloadService(BulkDownloadBase):
         return [self._invoker.services.images.get_dto(image_name) for image_name in image_names]
 
     def _board_handler(self, board_id: str) -> list[ImageDTO]:
-        # -1 is the default value for limit, which means no limit, is_intermediate False only gives us completed images
-        image_dtos = self._invoker.services.images.get_many(
-            offset=0,
-            limit=-1,
-            board_id=board_id,
-            is_intermediate=False,
-        ).items
-        return image_dtos
+        image_names = self._invoker.services.board_image_records.get_all_board_image_names_for_board(board_id)
+        return self._image_handler(image_names)
 
     def generate_item_id(self, board_id: Optional[str]) -> str:
         return uuid_string() if board_id is None else self._get_clean_board_name(board_id) + "_" + uuid_string()

From cbb997e7d0ee5602f51005f7cebec7baceb1b949 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 20 Feb 2024 18:05:52 +1100
Subject: [PATCH 218/411] tidy(bulk_download): don't store events service
 separately

Using the invoker object directly leaves no ambiguity as to what `_events_bus` actually is.
---
 .../services/bulk_download/bulk_download_default.py | 13 ++++++-------
 1 file changed, 6 insertions(+), 7 deletions(-)

diff --git a/invokeai/app/services/bulk_download/bulk_download_default.py b/invokeai/app/services/bulk_download/bulk_download_default.py
index 9fad0c3443..04cec928f4 100644
--- a/invokeai/app/services/bulk_download/bulk_download_default.py
+++ b/invokeai/app/services/bulk_download/bulk_download_default.py
@@ -21,7 +21,6 @@ from .bulk_download_base import BulkDownloadBase
 class BulkDownloadService(BulkDownloadBase):
     def start(self, invoker: Invoker) -> None:
         self._invoker = invoker
-        self._event_bus = invoker.services.events
 
     def __init__(self):
         self._temp_directory = TemporaryDirectory()
@@ -104,9 +103,9 @@ class BulkDownloadService(BulkDownloadBase):
         self, bulk_download_id: str, bulk_download_item_id: str, bulk_download_item_name: str
     ) -> None:
         """Signal that a bulk download job has started."""
-        if self._event_bus:
+        if self._invoker:
             assert bulk_download_id is not None
-            self._event_bus.emit_bulk_download_started(
+            self._invoker.services.events.emit_bulk_download_started(
                 bulk_download_id=bulk_download_id,
                 bulk_download_item_id=bulk_download_item_id,
                 bulk_download_item_name=bulk_download_item_name,
@@ -116,10 +115,10 @@ class BulkDownloadService(BulkDownloadBase):
         self, bulk_download_id: str, bulk_download_item_id: str, bulk_download_item_name: str
     ) -> None:
         """Signal that a bulk download job has completed."""
-        if self._event_bus:
+        if self._invoker:
             assert bulk_download_id is not None
             assert bulk_download_item_name is not None
-            self._event_bus.emit_bulk_download_completed(
+            self._invoker.services.events.emit_bulk_download_completed(
                 bulk_download_id=bulk_download_id,
                 bulk_download_item_id=bulk_download_item_id,
                 bulk_download_item_name=bulk_download_item_name,
@@ -129,10 +128,10 @@ class BulkDownloadService(BulkDownloadBase):
         self, bulk_download_id: str, bulk_download_item_id: str, bulk_download_item_name: str, exception: Exception
     ) -> None:
         """Signal that a bulk download job has failed."""
-        if self._event_bus:
+        if self._invoker:
             assert bulk_download_id is not None
             assert exception is not None
-            self._event_bus.emit_bulk_download_failed(
+            self._invoker.services.events.emit_bulk_download_failed(
                 bulk_download_id=bulk_download_id,
                 bulk_download_item_id=bulk_download_item_id,
                 bulk_download_item_name=bulk_download_item_name,

From 5cba55d670843e727870e95023327a29cec0f87f Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 20 Feb 2024 18:49:55 +1100
Subject: [PATCH 219/411] test: clean up & fix tests

- Deduplicate the mock invocation services. This is possible now that the import order issue is resolved.
- Merge `DummyEventService` into `TestEventService` and update all tests to use `TestEventService`.
---
 tests/app/routers/test_images.py              | 49 -------------
 .../bulk_download/test_bulk_download.py       | 71 ++++---------------
 .../services/download/test_download_queue.py  |  6 +-
 tests/conftest.py                             | 55 +++++++++++++-
 tests/fixtures/event_service.py               | 27 -------
 tests/test_graph_execution_state.py           | 39 ----------
 tests/test_nodes.py                           | 15 ++--
 7 files changed, 78 insertions(+), 184 deletions(-)
 delete mode 100644 tests/fixtures/event_service.py

diff --git a/tests/app/routers/test_images.py b/tests/app/routers/test_images.py
index 67297a116f..5cb8cf1c37 100644
--- a/tests/app/routers/test_images.py
+++ b/tests/app/routers/test_images.py
@@ -1,66 +1,17 @@
 from pathlib import Path
 from typing import Any
 
-import pytest
 from fastapi import BackgroundTasks
 from fastapi.testclient import TestClient
 
 from invokeai.app.api.dependencies import ApiDependencies
 from invokeai.app.api_app import app
 from invokeai.app.services.board_records.board_records_common import BoardRecord
-from invokeai.app.services.board_records.board_records_sqlite import SqliteBoardRecordStorage
-from invokeai.app.services.bulk_download.bulk_download_default import BulkDownloadService
-from invokeai.app.services.config.config_default import InvokeAIAppConfig
-from invokeai.app.services.images.images_default import ImageService
-from invokeai.app.services.invocation_services import InvocationServices
 from invokeai.app.services.invoker import Invoker
-from invokeai.backend.util.logging import InvokeAILogger
-from tests.fixtures.sqlite_database import create_mock_sqlite_database
 
 client = TestClient(app)
 
 
-@pytest.fixture
-def mock_services(tmp_path: Path) -> InvocationServices:
-    configuration = InvokeAIAppConfig(use_memory_db=True, node_cache_size=0)
-    logger = InvokeAILogger.get_logger()
-    db = create_mock_sqlite_database(configuration, logger)
-
-    return InvocationServices(
-        board_image_records=None,  # type: ignore
-        board_images=None,  # type: ignore
-        board_records=SqliteBoardRecordStorage(db=db),
-        boards=None,  # type: ignore
-        bulk_download=BulkDownloadService(),
-        configuration=None,  # type: ignore
-        events=None,  # type: ignore
-        graph_execution_manager=None,  # type: ignore
-        image_files=None,  # type: ignore
-        image_records=None,  # type: ignore
-        images=ImageService(),
-        invocation_cache=None,  # type: ignore
-        latents=None,  # type: ignore
-        logger=logger,
-        model_manager=None,  # type: ignore
-        model_records=None,  # type: ignore
-        download_queue=None,  # type: ignore
-        model_install=None,  # type: ignore
-        names=None,  # type: ignore
-        performance_statistics=None,  # type: ignore
-        processor=None,  # type: ignore
-        queue=None,  # type: ignore
-        session_processor=None,  # type: ignore
-        session_queue=None,  # type: ignore
-        urls=None,  # type: ignore
-        workflow_records=None,  # type: ignore
-    )
-
-
-@pytest.fixture()
-def mock_invoker(mock_services: InvocationServices) -> Invoker:
-    return Invoker(services=mock_services)
-
-
 class MockApiDependencies(ApiDependencies):
     invoker: Invoker
 
diff --git a/tests/app/services/bulk_download/test_bulk_download.py b/tests/app/services/bulk_download/test_bulk_download.py
index 3e8b7fd2eb..b18f6e038d 100644
--- a/tests/app/services/bulk_download/test_bulk_download.py
+++ b/tests/app/services/bulk_download/test_bulk_download.py
@@ -7,23 +7,17 @@ from zipfile import ZipFile
 import pytest
 
 from invokeai.app.services.board_records.board_records_common import BoardRecord, BoardRecordNotFoundException
-from invokeai.app.services.board_records.board_records_sqlite import SqliteBoardRecordStorage
 from invokeai.app.services.bulk_download.bulk_download_common import BulkDownloadTargetException
 from invokeai.app.services.bulk_download.bulk_download_default import BulkDownloadService
-from invokeai.app.services.config.config_default import InvokeAIAppConfig
 from invokeai.app.services.image_records.image_records_common import (
     ImageCategory,
     ImageRecordNotFoundException,
     ResourceOrigin,
 )
 from invokeai.app.services.images.images_common import ImageDTO
-from invokeai.app.services.images.images_default import ImageService
-from invokeai.app.services.invocation_services import InvocationServices
 from invokeai.app.services.invoker import Invoker
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
-from invokeai.backend.util.logging import InvokeAILogger
-from tests.fixtures.event_service import DummyEventService
-from tests.fixtures.sqlite_database import create_mock_sqlite_database
+from tests.test_nodes import TestEventService
 
 
 @pytest.fixture
@@ -46,53 +40,6 @@ def mock_image_dto() -> ImageDTO:
     )
 
 
-@pytest.fixture
-def mock_event_service() -> DummyEventService:
-    """Create a dummy event service."""
-    return DummyEventService()
-
-
-@pytest.fixture
-def mock_services(mock_event_service: DummyEventService) -> InvocationServices:
-    configuration = InvokeAIAppConfig(use_memory_db=True, node_cache_size=0)
-    logger = InvokeAILogger.get_logger()
-    db = create_mock_sqlite_database(configuration, logger)
-
-    return InvocationServices(
-        board_image_records=None,  # type: ignore
-        board_images=None,  # type: ignore
-        board_records=SqliteBoardRecordStorage(db=db),
-        boards=None,  # type: ignore
-        bulk_download=None,  # type: ignore
-        configuration=None,  # type: ignore
-        events=mock_event_service,
-        graph_execution_manager=None,  # type: ignore
-        image_files=None,  # type: ignore
-        image_records=None,  # type: ignore
-        images=ImageService(),
-        invocation_cache=None,  # type: ignore
-        latents=None,  # type: ignore
-        logger=logger,
-        model_manager=None,  # type: ignore
-        model_records=None,  # type: ignore
-        download_queue=None,  # type: ignore
-        model_install=None,  # type: ignore
-        names=None,  # type: ignore
-        performance_statistics=None,  # type: ignore
-        processor=None,  # type: ignore
-        queue=None,  # type: ignore
-        session_processor=None,  # type: ignore
-        session_queue=None,  # type: ignore
-        urls=None,  # type: ignore
-        workflow_records=None,  # type: ignore
-    )
-
-
-@pytest.fixture()
-def mock_invoker(mock_services: InvocationServices) -> Invoker:
-    return Invoker(services=mock_services)
-
-
 @pytest.fixture(autouse=True)
 def mock_temporary_directory(monkeypatch: Any, tmp_path: Path):
     """Mock the TemporaryDirectory class so that it uses the tmp_path fixture."""
@@ -288,6 +235,16 @@ def prepare_handler_test(tmp_path: Path, monkeypatch: Any, mock_image_dto: Image
 
     monkeypatch.setattr(mock_invoker.services.images, "get_dto", mock_get_dto)
 
+    # This is used when preparing all images for a given board
+    def mock_get_all_board_image_names_for_board(*args, **kwargs):
+        return [mock_image_dto.image_name]
+
+    monkeypatch.setattr(
+        mock_invoker.services.board_image_records,
+        "get_all_board_image_names_for_board",
+        mock_get_all_board_image_names_for_board,
+    )
+
     # Create a mock image file so that the contents of the zip file are not empty
     mock_image_path: Path = tmp_path / mock_image_dto.image_name
     mock_image_contents: str = "Totally an image"
@@ -306,7 +263,7 @@ def assert_handler_success(
     expected_image_path: Path,
     mock_image_contents: str,
     tmp_path: Path,
-    event_bus: DummyEventService,
+    event_bus: TestEventService,
 ):
     """Assert that the handler was successful."""
     # Check that the zip file was created
@@ -369,7 +326,7 @@ def test_handler_on_generic_exception(
     with pytest.raises(Exception):  # noqa: B017
         execute_handler_test_on_error(tmp_path, monkeypatch, mock_image_dto, mock_invoker, exception)
 
-    event_bus: DummyEventService = mock_invoker.services.events
+    event_bus: TestEventService = mock_invoker.services.events
 
     assert len(event_bus.events) == 2
     assert event_bus.events[0].event_name == "bulk_download_started"
@@ -384,7 +341,7 @@ def execute_handler_test_on_error(
     bulk_download_service.start(mock_invoker)
     bulk_download_service.handler([mock_image_dto.image_name], None, None)
 
-    event_bus: DummyEventService = mock_invoker.services.events
+    event_bus: TestEventService = mock_invoker.services.events
 
     assert len(event_bus.events) == 2
     assert event_bus.events[0].event_name == "bulk_download_started"
diff --git a/tests/app/services/download/test_download_queue.py b/tests/app/services/download/test_download_queue.py
index 34408ac5ae..ff9b193b17 100644
--- a/tests/app/services/download/test_download_queue.py
+++ b/tests/app/services/download/test_download_queue.py
@@ -9,7 +9,7 @@ from requests.sessions import Session
 from requests_testadapter import TestAdapter, TestSession
 
 from invokeai.app.services.download import DownloadJob, DownloadJobStatus, DownloadQueueService
-from tests.fixtures.event_service import DummyEventService
+from tests.test_nodes import TestEventService
 
 # Prevent pytest deprecation warnings
 TestAdapter.__test__ = False  # type: ignore
@@ -101,7 +101,7 @@ def test_errors(tmp_path: Path, session: Session) -> None:
 
 
 def test_event_bus(tmp_path: Path, session: Session) -> None:
-    event_bus = DummyEventService()
+    event_bus = TestEventService()
 
     queue = DownloadQueueService(requests_session=session, event_bus=event_bus)
     queue.start()
@@ -167,7 +167,7 @@ def test_broken_callbacks(tmp_path: Path, session: Session, capsys) -> None:
 
 
 def test_cancel(tmp_path: Path, session: Session) -> None:
-    event_bus = DummyEventService()
+    event_bus = TestEventService()
 
     queue = DownloadQueueService(requests_session=session, event_bus=event_bus)
     queue.start()
diff --git a/tests/conftest.py b/tests/conftest.py
index 873ccc13fd..a483b7529a 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -4,4 +4,57 @@
 
 # We import the model_installer and torch_device fixtures here so that they can be used by all tests. Flake8 does not
 # play well with fixtures (F401 and F811), so this is cleaner than importing in all files that use these fixtures.
-from invokeai.backend.util.test_utils import torch_device  # noqa: F401
+import logging
+
+import pytest
+
+from invokeai.app.services.board_image_records.board_image_records_sqlite import SqliteBoardImageRecordStorage
+from invokeai.app.services.board_records.board_records_sqlite import SqliteBoardRecordStorage
+from invokeai.app.services.bulk_download.bulk_download_default import BulkDownloadService
+from invokeai.app.services.config.config_default import InvokeAIAppConfig
+from invokeai.app.services.images.images_default import ImageService
+from invokeai.app.services.invocation_cache.invocation_cache_memory import MemoryInvocationCache
+from invokeai.app.services.invocation_services import InvocationServices
+from invokeai.app.services.invocation_stats.invocation_stats_default import InvocationStatsService
+from invokeai.app.services.invoker import Invoker
+from invokeai.backend.util.logging import InvokeAILogger
+from tests.fixtures.sqlite_database import create_mock_sqlite_database  # noqa: F401
+from tests.test_nodes import TestEventService
+
+
+@pytest.fixture
+def mock_services() -> InvocationServices:
+    configuration = InvokeAIAppConfig(use_memory_db=True, node_cache_size=0)
+    logger = InvokeAILogger.get_logger()
+    db = create_mock_sqlite_database(configuration, logger)
+
+    # NOTE: none of these are actually called by the test invocations
+    return InvocationServices(
+        board_image_records=SqliteBoardImageRecordStorage(db=db),
+        board_images=None,  # type: ignore
+        board_records=SqliteBoardRecordStorage(db=db),
+        boards=None,  # type: ignore
+        bulk_download=BulkDownloadService(),
+        configuration=configuration,
+        events=TestEventService(),
+        image_files=None,  # type: ignore
+        image_records=None,  # type: ignore
+        images=ImageService(),
+        invocation_cache=MemoryInvocationCache(max_cache_size=0),
+        logger=logging,  # type: ignore
+        model_manager=None,  # type: ignore
+        download_queue=None,  # type: ignore
+        names=None,  # type: ignore
+        performance_statistics=InvocationStatsService(),
+        session_processor=None,  # type: ignore
+        session_queue=None,  # type: ignore
+        urls=None,  # type: ignore
+        workflow_records=None,  # type: ignore
+        tensors=None,  # type: ignore
+        conditioning=None,  # type: ignore
+    )
+
+
+@pytest.fixture()
+def mock_invoker(mock_services: InvocationServices) -> Invoker:
+    return Invoker(services=mock_services)
diff --git a/tests/fixtures/event_service.py b/tests/fixtures/event_service.py
deleted file mode 100644
index 8f6a45c38f..0000000000
--- a/tests/fixtures/event_service.py
+++ /dev/null
@@ -1,27 +0,0 @@
-from typing import Any, Dict, List
-
-from pydantic import BaseModel
-
-from invokeai.app.services.events.events_base import EventServiceBase
-
-
-class DummyEvent(BaseModel):
-    """Dummy Event to use with Dummy Event service."""
-
-    event_name: str
-    payload: Dict[str, Any]
-
-
-# A dummy event service for testing event issuing
-class DummyEventService(EventServiceBase):
-    """Dummy event service for testing."""
-
-    events: List[DummyEvent]
-
-    def __init__(self) -> None:
-        super().__init__()
-        self.events = []
-
-    def dispatch(self, event_name: str, payload: Any) -> None:
-        """Dispatch an event by appending it to self.events."""
-        self.events.append(DummyEvent(event_name=payload["event"], payload=payload["data"]))
diff --git a/tests/test_graph_execution_state.py b/tests/test_graph_execution_state.py
index 9a35037431..0bb15b17df 100644
--- a/tests/test_graph_execution_state.py
+++ b/tests/test_graph_execution_state.py
@@ -1,4 +1,3 @@
-import logging
 from typing import Optional
 from unittest.mock import Mock
 
@@ -8,17 +7,12 @@ import pytest
 from .test_nodes import (  # isort: split
     PromptCollectionTestInvocation,
     PromptTestInvocation,
-    TestEventService,
     TextToImageTestInvocation,
 )
 
 from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, InvocationContext
 from invokeai.app.invocations.collections import RangeInvocation
 from invokeai.app.invocations.math import AddInvocation, MultiplyInvocation
-from invokeai.app.services.config.config_default import InvokeAIAppConfig
-from invokeai.app.services.invocation_cache.invocation_cache_memory import MemoryInvocationCache
-from invokeai.app.services.invocation_services import InvocationServices
-from invokeai.app.services.invocation_stats.invocation_stats_default import InvocationStatsService
 from invokeai.app.services.shared.graph import (
     CollectInvocation,
     Graph,
@@ -38,39 +32,6 @@ def simple_graph() -> Graph:
     return g
 
 
-# This must be defined here to avoid issues with the dynamic creation of the union of all invocation types
-# Defining it in a separate module will cause the union to be incomplete, and pydantic will not validate
-# the test invocations.
-@pytest.fixture
-def mock_services() -> InvocationServices:
-    configuration = InvokeAIAppConfig(use_memory_db=True, node_cache_size=0)
-    # NOTE: none of these are actually called by the test invocations
-    return InvocationServices(
-        board_image_records=None,  # type: ignore
-        board_images=None,  # type: ignore
-        board_records=None,  # type: ignore
-        boards=None,  # type: ignore
-        bulk_download=None,  # type: ignore
-        configuration=configuration,
-        events=TestEventService(),
-        image_files=None,  # type: ignore
-        image_records=None,  # type: ignore
-        images=None,  # type: ignore
-        invocation_cache=MemoryInvocationCache(max_cache_size=0),
-        logger=logging,  # type: ignore
-        model_manager=None,  # type: ignore
-        download_queue=None,  # type: ignore
-        names=None,  # type: ignore
-        performance_statistics=InvocationStatsService(),
-        session_processor=None,  # type: ignore
-        session_queue=None,  # type: ignore
-        urls=None,  # type: ignore
-        workflow_records=None,  # type: ignore
-        tensors=None,  # type: ignore
-        conditioning=None,  # type: ignore
-    )
-
-
 def invoke_next(g: GraphExecutionState) -> tuple[Optional[BaseInvocation], Optional[BaseInvocationOutput]]:
     n = g.next()
     if n is None:
diff --git a/tests/test_nodes.py b/tests/test_nodes.py
index aab3d9c7b4..e1fe857040 100644
--- a/tests/test_nodes.py
+++ b/tests/test_nodes.py
@@ -1,5 +1,7 @@
 from typing import Any, Callable, Union
 
+from pydantic import BaseModel
+
 from invokeai.app.invocations.baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
@@ -115,25 +117,22 @@ def create_edge(from_id: str, from_field: str, to_id: str, to_field: str) -> Edg
     )
 
 
-class TestEvent:
-    event_name: str
-    payload: Any
+class TestEvent(BaseModel):
     __test__ = False  # not a pytest test case
 
-    def __init__(self, event_name: str, payload: Any):
-        self.event_name = event_name
-        self.payload = payload
+    event_name: str
+    payload: Any
 
 
 class TestEventService(EventServiceBase):
-    events: list
     __test__ = False  # not a pytest test case
 
     def __init__(self):
         super().__init__()
-        self.events = []
+        self.events: list[TestEvent] = []
 
     def dispatch(self, event_name: str, payload: Any) -> None:
+        self.events.append(TestEvent(event_name=payload["event"], payload=payload["data"]))
         pass
 
 

From ab94484c6c01faf0d0bd2c0fe912737c544820ef Mon Sep 17 00:00:00 2001
From: Stefan Tobler <toblerlstefan@gmail.com>
Date: Sun, 18 Feb 2024 00:01:15 -0500
Subject: [PATCH 220/411] setting up event listeners for bulk download socket

---
 .../app/store/nanostores/bulkDownloadId.ts    |  9 +++++
 .../src/features/system/store/configSlice.ts  |  2 +-
 .../web/src/services/events/actions.ts        | 15 ++++++++
 .../frontend/web/src/services/events/types.ts | 34 +++++++++++++++++--
 .../services/events/util/setEventListeners.ts | 18 ++++++++++
 5 files changed, 75 insertions(+), 3 deletions(-)
 create mode 100644 invokeai/frontend/web/src/app/store/nanostores/bulkDownloadId.ts

diff --git a/invokeai/frontend/web/src/app/store/nanostores/bulkDownloadId.ts b/invokeai/frontend/web/src/app/store/nanostores/bulkDownloadId.ts
new file mode 100644
index 0000000000..5615124493
--- /dev/null
+++ b/invokeai/frontend/web/src/app/store/nanostores/bulkDownloadId.ts
@@ -0,0 +1,9 @@
+import { atom } from 'nanostores';
+
+export const DEFAULT_BULK_DOWNLOAD_ID = 'default';
+
+/**
+ * The download id for a bulk download. Used for socket subscriptions.
+ */
+
+export const $bulkDownloadId = atom<string>(DEFAULT_BULK_DOWNLOAD_ID);
diff --git a/invokeai/frontend/web/src/features/system/store/configSlice.ts b/invokeai/frontend/web/src/features/system/store/configSlice.ts
index 1cf62e89c8..94f1f1c64a 100644
--- a/invokeai/frontend/web/src/features/system/store/configSlice.ts
+++ b/invokeai/frontend/web/src/features/system/store/configSlice.ts
@@ -18,7 +18,7 @@ export const initialConfigState: AppConfig = {
   shouldUpdateImagesOnConnect: false,
   shouldFetchMetadataFromApi: false,
   disabledTabs: [],
-  disabledFeatures: ['lightbox', 'faceRestore', 'batches', 'bulkDownload'],
+  disabledFeatures: ['lightbox', 'faceRestore', 'batches'],
   disabledSDFeatures: ['variation', 'symmetry', 'hires', 'perlinNoise', 'noiseThreshold'],
   nodesAllowlist: undefined,
   nodesDenylist: undefined,
diff --git a/invokeai/frontend/web/src/services/events/actions.ts b/invokeai/frontend/web/src/services/events/actions.ts
index 101e928f79..b80363315e 100644
--- a/invokeai/frontend/web/src/services/events/actions.ts
+++ b/invokeai/frontend/web/src/services/events/actions.ts
@@ -1,5 +1,8 @@
 import { createAction } from '@reduxjs/toolkit';
 import type {
+  BulkDownloadCompletedEvent,
+  BulkDownloadFailedEvent,
+  BulkDownloadStartedEvent,
   GeneratorProgressEvent,
   GraphExecutionStateCompleteEvent,
   InvocationCompleteEvent,
@@ -64,3 +67,15 @@ export const socketInvocationRetrievalError = createAction<{
 export const socketQueueItemStatusChanged = createAction<{
   data: QueueItemStatusChangedEvent;
 }>('socket/socketQueueItemStatusChanged');
+
+export const socketBulkDownloadStarted = createAction<{
+  data: BulkDownloadStartedEvent;
+}>('socket/socketBulkDownloadStarted');
+
+export const socketBulkDownloadCompleted = createAction<{
+  data: BulkDownloadCompletedEvent;
+}>('socket/socketBulkDownloadCompleted');
+
+export const socketBulkDownloadFailed = createAction<{
+  data: BulkDownloadFailedEvent;
+}>('socket/socketBulkDownloadFailed');
diff --git a/invokeai/frontend/web/src/services/events/types.ts b/invokeai/frontend/web/src/services/events/types.ts
index 9579b6abc1..092132fea2 100644
--- a/invokeai/frontend/web/src/services/events/types.ts
+++ b/invokeai/frontend/web/src/services/events/types.ts
@@ -156,7 +156,7 @@ export type InvocationRetrievalErrorEvent = {
  *
  * @example socket.on('queue_item_status_changed', (data: QueueItemStatusChangedEvent) => { ... }
  */
-export type QueueItemStatusChangedEvent = {
+export type  QueueItemStatusChangedEvent = {
   queue_id: string;
   queue_item: {
     queue_id: string;
@@ -191,7 +191,7 @@ export type QueueItemStatusChangedEvent = {
     failed: number;
     canceled: number;
     total: number;
-  };
+  }; 
 };
 
 export type ClientEmitSubscribeQueue = {
@@ -202,6 +202,31 @@ export type ClientEmitUnsubscribeQueue = {
   queue_id: string;
 };
 
+export type BulkDownloadStartedEvent = {
+  bulk_download_id: string;
+  bulk_download_item_id: string;
+};
+
+export type BulkDownloadCompletedEvent = {
+  bulk_download_id: string;
+  bulk_download_item_id: string;
+  bulk_download_item_name: string;
+};
+
+export type BulkDownloadFailedEvent = {
+  bulk_download_id: string;
+  bulk_download_item_id: string;
+  error: string;
+}
+
+export type ClientEmitSubscribeBulkDownload = {
+  bulk_download_id: string;
+};
+
+export type ClientEmitUnsubscribeBulkDownload = {
+  bulk_download_id: string;
+};
+
 export type ServerToClientEvents = {
   generator_progress: (payload: GeneratorProgressEvent) => void;
   invocation_complete: (payload: InvocationCompleteEvent) => void;
@@ -213,6 +238,9 @@ export type ServerToClientEvents = {
   session_retrieval_error: (payload: SessionRetrievalErrorEvent) => void;
   invocation_retrieval_error: (payload: InvocationRetrievalErrorEvent) => void;
   queue_item_status_changed: (payload: QueueItemStatusChangedEvent) => void;
+  bulk_download_started: (payload: BulkDownloadStartedEvent) => void;
+  bulk_download_completed: (payload: BulkDownloadCompletedEvent) => void;
+  bulk_download_failed: (payload: BulkDownloadFailedEvent) => void;
 };
 
 export type ClientToServerEvents = {
@@ -220,4 +248,6 @@ export type ClientToServerEvents = {
   disconnect: () => void;
   subscribe_queue: (payload: ClientEmitSubscribeQueue) => void;
   unsubscribe_queue: (payload: ClientEmitUnsubscribeQueue) => void;
+  subscribe_bulk_download: (payload: ClientEmitSubscribeBulkDownload) => void;
+  unsubscribe_bulk_download: (payload: ClientEmitUnsubscribeBulkDownload) => void;
 };
diff --git a/invokeai/frontend/web/src/services/events/util/setEventListeners.ts b/invokeai/frontend/web/src/services/events/util/setEventListeners.ts
index c66defee60..d851a185ff 100644
--- a/invokeai/frontend/web/src/services/events/util/setEventListeners.ts
+++ b/invokeai/frontend/web/src/services/events/util/setEventListeners.ts
@@ -1,8 +1,12 @@
+import { $bulkDownloadId } from 'app/store/nanostores/bulkDownloadId';
 import { $queueId } from 'app/store/nanostores/queueId';
 import type { AppDispatch } from 'app/store/store';
 import { addToast } from 'features/system/store/systemSlice';
 import { makeToast } from 'features/system/util/makeToast';
 import {
+  socketBulkDownloadCompleted,
+  socketBulkDownloadFailed,
+  socketBulkDownloadStarted,
   socketConnected,
   socketDisconnected,
   socketGeneratorProgress,
@@ -34,6 +38,8 @@ export const setEventListeners = (arg: SetEventListenersArg) => {
     dispatch(socketConnected());
     const queue_id = $queueId.get();
     socket.emit('subscribe_queue', { queue_id });
+    const bulk_download_id = $bulkDownloadId.get();
+    socket.emit('subscribe_bulk_download', { bulk_download_id });
   });
 
   socket.on('connect_error', (error) => {
@@ -150,4 +156,16 @@ export const setEventListeners = (arg: SetEventListenersArg) => {
   socket.on('queue_item_status_changed', (data) => {
     dispatch(socketQueueItemStatusChanged({ data }));
   });
+
+  socket.on('bulk_download_started', (data) => {
+    dispatch(socketBulkDownloadStarted({ data }));
+  });
+
+  socket.on('bulk_download_completed', (data) => {
+    dispatch(socketBulkDownloadCompleted({ data }));
+  });
+
+  socket.on('bulk_download_failed', (data) => {
+    dispatch(socketBulkDownloadFailed({ data }));
+  });
 };

From 9e296f6916dfae633b7a833f47b6ae41d6f84240 Mon Sep 17 00:00:00 2001
From: Stefan Tobler <toblerlstefan@gmail.com>
Date: Mon, 19 Feb 2024 14:03:26 -0500
Subject: [PATCH 221/411] implementing download for bulk_download events

---
 invokeai/frontend/web/public/locales/en.json  |  2 +
 .../middleware/listenerMiddleware/index.ts    |  4 ++
 .../socketio/socketBulkDownloadComplete.ts    | 41 +++++++++++++++++++
 .../socketio/socketBulkDownloadFailed.ts      | 32 +++++++++++++++
 .../frontend/web/src/services/events/types.ts |  8 ++--
 5 files changed, 84 insertions(+), 3 deletions(-)
 create mode 100644 invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketBulkDownloadComplete.ts
 create mode 100644 invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketBulkDownloadFailed.ts

diff --git a/invokeai/frontend/web/public/locales/en.json b/invokeai/frontend/web/public/locales/en.json
index 32c707f908..32d3d382bd 100644
--- a/invokeai/frontend/web/public/locales/en.json
+++ b/invokeai/frontend/web/public/locales/en.json
@@ -426,6 +426,8 @@
         "downloadSelection": "Download Selection",
         "preparingDownload": "Preparing Download",
         "preparingDownloadFailed": "Problem Preparing Download",
+        "bulkDownloadStarting": "Beginning Download",
+        "bulkDownloadFailed": "Problem Preparing Download",
         "problemDeletingImages": "Problem Deleting Images",
         "problemDeletingImagesDesc": "One or more images could not be deleted"
     },
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts
index 322c4eb1ec..07d9bb5df5 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts
@@ -48,6 +48,8 @@ import { addInitialImageSelectedListener } from './listeners/initialImageSelecte
 import { addModelSelectedListener } from './listeners/modelSelected';
 import { addModelsLoadedListener } from './listeners/modelsLoaded';
 import { addDynamicPromptsListener } from './listeners/promptChanged';
+import { addBulkDownloadCompleteEventListener } from './listeners/socketio/socketBulkDownloadComplete';
+import { addBulkDownloadFailedEventListener } from './listeners/socketio/socketBulkDownloadFailed';
 import { addSocketConnectedEventListener as addSocketConnectedListener } from './listeners/socketio/socketConnected';
 import { addSocketDisconnectedEventListener as addSocketDisconnectedListener } from './listeners/socketio/socketDisconnected';
 import { addGeneratorProgressEventListener as addGeneratorProgressListener } from './listeners/socketio/socketGeneratorProgress';
@@ -137,6 +139,8 @@ addModelLoadEventListener();
 addSessionRetrievalErrorEventListener();
 addInvocationRetrievalErrorEventListener();
 addSocketQueueItemStatusChangedEventListener();
+addBulkDownloadCompleteEventListener();
+addBulkDownloadFailedEventListener();
 
 // ControlNet
 addControlNetImageProcessedListener();
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketBulkDownloadComplete.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketBulkDownloadComplete.ts
new file mode 100644
index 0000000000..acdb61ff25
--- /dev/null
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketBulkDownloadComplete.ts
@@ -0,0 +1,41 @@
+import { logger } from 'app/logging/logger';
+import { addToast } from 'features/system/store/systemSlice';
+import { t } from 'i18next';
+import { socketBulkDownloadCompleted } from 'services/events/actions';
+
+import { startAppListening } from '../..';
+
+const log = logger('socketio');
+
+export const addBulkDownloadCompleteEventListener = () => {
+  startAppListening({
+    actionCreator: socketBulkDownloadCompleted,
+    effect: async (action, { dispatch }) => {
+      log.debug(action.payload, 'Bulk download complete');
+
+      const bulk_download_item_name = action.payload.data.bulk_download_item_name;
+
+      const url = `/api/v1/images/download/${bulk_download_item_name}`;
+      const a = document.createElement('a');
+      a.style.display = 'none';
+      a.href = url;
+      a.download = bulk_download_item_name;
+      document.body.appendChild(a);
+      a.click();
+
+      dispatch(
+        addToast({
+          title: t('gallery.bulkDownloadStarting'),
+          status: 'success',
+          ...(action.payload
+            ? {
+                description: bulk_download_item_name,
+                duration: null,
+                isClosable: true,
+              }
+            : {}),
+        })
+      );
+    },
+  });
+};
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketBulkDownloadFailed.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketBulkDownloadFailed.ts
new file mode 100644
index 0000000000..a9a45c42ae
--- /dev/null
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketBulkDownloadFailed.ts
@@ -0,0 +1,32 @@
+import { logger } from 'app/logging/logger';
+import { addToast } from 'features/system/store/systemSlice';
+import { t } from 'i18next';
+import { socketBulkDownloadFailed } from 'services/events/actions';
+
+import { startAppListening } from '../..';
+
+const log = logger('socketio');
+
+export const addBulkDownloadFailedEventListener = () => {
+  startAppListening({
+    actionCreator: socketBulkDownloadFailed,
+    effect: async (action, { dispatch }) => {
+      log.debug(action.payload, 'Bulk download error');
+
+
+      dispatch(
+        addToast({
+          title: t('gallery.bulkDownloadFailed'),
+          status: 'error',
+          ...(action.payload
+            ? {
+                description: action.payload.data.error,
+                duration: null,
+                isClosable: true,
+              }
+            : {}),
+        })
+      );
+    },
+  });
+};
diff --git a/invokeai/frontend/web/src/services/events/types.ts b/invokeai/frontend/web/src/services/events/types.ts
index 092132fea2..4e68131ee9 100644
--- a/invokeai/frontend/web/src/services/events/types.ts
+++ b/invokeai/frontend/web/src/services/events/types.ts
@@ -156,7 +156,7 @@ export type InvocationRetrievalErrorEvent = {
  *
  * @example socket.on('queue_item_status_changed', (data: QueueItemStatusChangedEvent) => { ... }
  */
-export type  QueueItemStatusChangedEvent = {
+export type QueueItemStatusChangedEvent = {
   queue_id: string;
   queue_item: {
     queue_id: string;
@@ -191,7 +191,7 @@ export type  QueueItemStatusChangedEvent = {
     failed: number;
     canceled: number;
     total: number;
-  }; 
+  };
 };
 
 export type ClientEmitSubscribeQueue = {
@@ -205,6 +205,7 @@ export type ClientEmitUnsubscribeQueue = {
 export type BulkDownloadStartedEvent = {
   bulk_download_id: string;
   bulk_download_item_id: string;
+  bulk_download_item_name: string;
 };
 
 export type BulkDownloadCompletedEvent = {
@@ -216,8 +217,9 @@ export type BulkDownloadCompletedEvent = {
 export type BulkDownloadFailedEvent = {
   bulk_download_id: string;
   bulk_download_item_id: string;
+  bulk_download_item_name: string;
   error: string;
-}
+};
 
 export type ClientEmitSubscribeBulkDownload = {
   bulk_download_id: string;

From a37b60db134c10ab2333da49bb782f112a75d088 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 20 Feb 2024 22:15:01 +1100
Subject: [PATCH 222/411] feat(bulk_download): update response model, messages

---
 invokeai/app/api/routers/images.py                  | 13 ++++++-------
 .../services/bulk_download/bulk_download_common.py  |  5 +----
 2 files changed, 7 insertions(+), 11 deletions(-)

diff --git a/invokeai/app/api/routers/images.py b/invokeai/app/api/routers/images.py
index c3504b104d..dc8a04b711 100644
--- a/invokeai/app/api/routers/images.py
+++ b/invokeai/app/api/routers/images.py
@@ -375,9 +375,11 @@ async def unstar_images_in_list(
 
 class ImagesDownloaded(BaseModel):
     response: Optional[str] = Field(
-        description="If defined, the message to display to the user when images begin downloading"
+        default=None, description="The message to display to the user when images begin downloading"
+    )
+    bulk_download_item_name: Optional[str] = Field(
+        default=None, description="The name of the bulk download item for which events will be emitted"
     )
-    bulk_download_item_name: str = Field(description="The bulk download item name of the bulk download item")
 
 
 @images_router.post(
@@ -389,7 +391,7 @@ async def download_images_from_list(
         default=None, description="The list of names of images to download", embed=True
     ),
     board_id: Optional[str] = Body(
-        default=None, description="The board from which image should be downloaded from", embed=True
+        default=None, description="The board from which image should be downloaded", embed=True
     ),
 ) -> ImagesDownloaded:
     if (image_names is None or len(image_names) == 0) and board_id is None:
@@ -402,10 +404,7 @@ async def download_images_from_list(
         board_id,
         bulk_download_item_id,
     )
-    return ImagesDownloaded(
-        response="Your images are preparing to be downloaded",
-        bulk_download_item_name=bulk_download_item_id + ".zip",
-    )
+    return ImagesDownloaded(bulk_download_item_name=bulk_download_item_id + ".zip")
 
 
 @images_router.api_route(
diff --git a/invokeai/app/services/bulk_download/bulk_download_common.py b/invokeai/app/services/bulk_download/bulk_download_common.py
index 37b80073be..68724eb228 100644
--- a/invokeai/app/services/bulk_download/bulk_download_common.py
+++ b/invokeai/app/services/bulk_download/bulk_download_common.py
@@ -20,9 +20,6 @@ class BulkDownloadTargetException(BulkDownloadException):
 class BulkDownloadParametersException(BulkDownloadException):
     """Exception raised when a bulk download parameter is invalid."""
 
-    def __init__(
-        self,
-        message="The bulk download parameters are invalid, either an array of image names or a board id must be provided",
-    ):
+    def __init__(self, message="No image names or board ID provided"):
         super().__init__(message)
         self.message = message

From 64908eda553ee4e168ae9a544a1560f99bfd69bf Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 20 Feb 2024 22:15:14 +1100
Subject: [PATCH 223/411] chore(ui): typegen

---
 .../frontend/web/src/services/api/schema.ts   | 159 ++++++------------
 1 file changed, 52 insertions(+), 107 deletions(-)

diff --git a/invokeai/frontend/web/src/services/api/schema.ts b/invokeai/frontend/web/src/services/api/schema.ts
index 47a257ffe6..2115e79768 100644
--- a/invokeai/frontend/web/src/services/api/schema.ts
+++ b/invokeai/frontend/web/src/services/api/schema.ts
@@ -5,13 +5,6 @@
 
 
 export type paths = {
-  "/api/v1/sessions/{session_id}": {
-    /**
-     * Get Session
-     * @description Gets a session
-     */
-    get: operations["get_session"];
-  };
   "/api/v1/utilities/dynamicprompts": {
     /**
      * Parse Dynamicprompts
@@ -389,6 +382,13 @@ export type paths = {
     /** Download Images From List */
     post: operations["download_images_from_list"];
   };
+  "/api/v1/images/download/{bulk_download_item_name}": {
+    /**
+     * Get Bulk Download Item
+     * @description Gets a bulk download zip file
+     */
+    get: operations["get_bulk_download_item"];
+  };
   "/api/v1/boards/": {
     /**
      * List Boards
@@ -1152,10 +1152,10 @@ export type components = {
        * Image Names
        * @description The list of names of images to download
        */
-      image_names: string[];
+      image_names?: string[] | null;
       /**
        * Board Id
-       * @description The board from which image should be downloaded from
+       * @description The board from which image should be downloaded
        */
       board_id?: string | null;
     };
@@ -4208,13 +4208,13 @@ export type components = {
        * Id
        * @description The id of this graph
        */
-      id?: string;
+      id?: string | null;
       /**
        * Nodes
        * @description The nodes in this graph
        */
       nodes: {
-        [key: string]: components["schemas"]["ImageInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["ColorMapImageProcessorInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["DWOpenposeImageProcessorInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["DepthAnythingImageProcessorInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["CompelInvocation"];
+        [key: string]: components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["ColorMapImageProcessorInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["DWOpenposeImageProcessorInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["DepthAnythingImageProcessorInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["FaceOffInvocation"];
       };
       /**
        * Edges
@@ -4251,7 +4251,7 @@ export type components = {
        * @description The results of node executions
        */
       results: {
-        [key: string]: components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["MetadataOutput"] | components["schemas"]["String2Output"] | components["schemas"]["ControlOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["LatentsOutput"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["ClipSkipInvocationOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["LoraLoaderOutput"] | components["schemas"]["VAEOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["SDXLLoraLoaderOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["LatentsCollectionOutput"];
+        [key: string]: components["schemas"]["ModelLoaderOutput"] | components["schemas"]["MetadataOutput"] | components["schemas"]["String2Output"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["ClipSkipInvocationOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["VAEOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["LoraLoaderOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["SDXLLoraLoaderOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["LatentsOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["StringCollectionOutput"];
       };
       /**
        * Errors
@@ -5674,9 +5674,14 @@ export type components = {
     ImagesDownloaded: {
       /**
        * Response
-       * @description If defined, the message to display to the user when images begin downloading
+       * @description The message to display to the user when images begin downloading
        */
-      response: string | null;
+      response?: string | null;
+      /**
+       * Bulk Download Item Name
+       * @description The name of the bulk download item for which events will be emitted
+       */
+      bulk_download_item_name?: string | null;
     };
     /** ImagesUpdatedFromListResult */
     ImagesUpdatedFromListResult: {
@@ -6377,7 +6382,7 @@ export type components = {
        */
       AllowDifferentLicense?: boolean;
       /** @description Type of commercial use allowed or 'No' if no commercial use is allowed. */
-      AllowCommercialUse?: components["schemas"]["CommercialUsage"];
+      AllowCommercialUse?: components["schemas"]["CommercialUsage"] | null;
     };
     /**
      * Lineart Anime Processor
@@ -11091,66 +11096,6 @@ export type components = {
      * @enum {string}
      */
     UIType: "SDXLMainModelField" | "SDXLRefinerModelField" | "ONNXModelField" | "VAEModelField" | "LoRAModelField" | "ControlNetModelField" | "IPAdapterModelField" | "SchedulerField" | "AnyField" | "CollectionField" | "CollectionItemField" | "DEPRECATED_Boolean" | "DEPRECATED_Color" | "DEPRECATED_Conditioning" | "DEPRECATED_Control" | "DEPRECATED_Float" | "DEPRECATED_Image" | "DEPRECATED_Integer" | "DEPRECATED_Latents" | "DEPRECATED_String" | "DEPRECATED_BooleanCollection" | "DEPRECATED_ColorCollection" | "DEPRECATED_ConditioningCollection" | "DEPRECATED_ControlCollection" | "DEPRECATED_FloatCollection" | "DEPRECATED_ImageCollection" | "DEPRECATED_IntegerCollection" | "DEPRECATED_LatentsCollection" | "DEPRECATED_StringCollection" | "DEPRECATED_BooleanPolymorphic" | "DEPRECATED_ColorPolymorphic" | "DEPRECATED_ConditioningPolymorphic" | "DEPRECATED_ControlPolymorphic" | "DEPRECATED_FloatPolymorphic" | "DEPRECATED_ImagePolymorphic" | "DEPRECATED_IntegerPolymorphic" | "DEPRECATED_LatentsPolymorphic" | "DEPRECATED_StringPolymorphic" | "DEPRECATED_MainModel" | "DEPRECATED_UNet" | "DEPRECATED_Vae" | "DEPRECATED_CLIP" | "DEPRECATED_Collection" | "DEPRECATED_CollectionItem" | "DEPRECATED_Enum" | "DEPRECATED_WorkflowField" | "DEPRECATED_IsIntermediate" | "DEPRECATED_BoardField" | "DEPRECATED_MetadataItem" | "DEPRECATED_MetadataItemCollection" | "DEPRECATED_MetadataItemPolymorphic" | "DEPRECATED_MetadataDict";
-    /**
-     * ControlNetModelFormat
-     * @description An enumeration.
-     * @enum {string}
-     */
-    ControlNetModelFormat: "checkpoint" | "diffusers";
-    /**
-     * LoRAModelFormat
-     * @description An enumeration.
-     * @enum {string}
-     */
-    LoRAModelFormat: "lycoris" | "diffusers";
-    /**
-     * StableDiffusionXLModelFormat
-     * @description An enumeration.
-     * @enum {string}
-     */
-    StableDiffusionXLModelFormat: "checkpoint" | "diffusers";
-    /**
-     * IPAdapterModelFormat
-     * @description An enumeration.
-     * @enum {string}
-     */
-    IPAdapterModelFormat: "invokeai";
-    /**
-     * T2IAdapterModelFormat
-     * @description An enumeration.
-     * @enum {string}
-     */
-    T2IAdapterModelFormat: "diffusers";
-    /**
-     * StableDiffusion1ModelFormat
-     * @description An enumeration.
-     * @enum {string}
-     */
-    StableDiffusion1ModelFormat: "checkpoint" | "diffusers";
-    /**
-     * CLIPVisionModelFormat
-     * @description An enumeration.
-     * @enum {string}
-     */
-    CLIPVisionModelFormat: "diffusers";
-    /**
-     * StableDiffusionOnnxModelFormat
-     * @description An enumeration.
-     * @enum {string}
-     */
-    StableDiffusionOnnxModelFormat: "olive" | "onnx";
-    /**
-     * StableDiffusion2ModelFormat
-     * @description An enumeration.
-     * @enum {string}
-     */
-    StableDiffusion2ModelFormat: "checkpoint" | "diffusers";
-    /**
-     * VaeModelFormat
-     * @description An enumeration.
-     * @enum {string}
-     */
-    VaeModelFormat: "checkpoint" | "diffusers";
   };
   responses: never;
   parameters: never;
@@ -11165,36 +11110,6 @@ export type external = Record<string, never>;
 
 export type operations = {
 
-  /**
-   * Get Session
-   * @description Gets a session
-   */
-  get_session: {
-    parameters: {
-      path: {
-        /** @description The id of the session to get */
-        session_id: string;
-      };
-    };
-    responses: {
-      /** @description Successful Response */
-      200: {
-        content: {
-          "application/json": components["schemas"]["GraphExecutionState"];
-        };
-      };
-      /** @description Session not found */
-      404: {
-        content: never;
-      };
-      /** @description Validation Error */
-      422: {
-        content: {
-          "application/json": components["schemas"]["HTTPValidationError"];
-        };
-      };
-    };
-  };
   /**
    * Parse Dynamicprompts
    * @description Creates a batch process
@@ -12451,14 +12366,14 @@ export type operations = {
   };
   /** Download Images From List */
   download_images_from_list: {
-    requestBody: {
+    requestBody?: {
       content: {
         "application/json": components["schemas"]["Body_download_images_from_list"];
       };
     };
     responses: {
       /** @description Successful Response */
-      200: {
+      202: {
         content: {
           "application/json": components["schemas"]["ImagesDownloaded"];
         };
@@ -12471,6 +12386,36 @@ export type operations = {
       };
     };
   };
+  /**
+   * Get Bulk Download Item
+   * @description Gets a bulk download zip file
+   */
+  get_bulk_download_item: {
+    parameters: {
+      path: {
+        /** @description The bulk_download_item_name of the bulk download item to get */
+        bulk_download_item_name: string;
+      };
+    };
+    responses: {
+      /** @description Return the complete bulk download item */
+      200: {
+        content: {
+          "application/zip": unknown;
+        };
+      };
+      /** @description Image not found */
+      404: {
+        content: never;
+      };
+      /** @description Validation Error */
+      422: {
+        content: {
+          "application/json": components["schemas"]["HTTPValidationError"];
+        };
+      };
+    };
+  };
   /**
    * List Boards
    * @description Gets a list of boards

From c0f0f2f39e2bfd6402f9ca19a3923df31aa9205f Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 20 Feb 2024 22:26:38 +1100
Subject: [PATCH 224/411] feat(ui): revise bulk download listeners

- Use a single listener for all of the to keep them in one spot
- Use the bulk download item name as a toast id so we can update the existing toasts
- Update handling to work with other environments
- Move all bulk download handling from components to listener
---
 invokeai/frontend/web/public/locales/en.json  |   9 +-
 .../middleware/listenerMiddleware/index.ts    |   6 +-
 .../listeners/bulkDownload.ts                 | 118 ++++++++++++++++++
 .../socketio/socketBulkDownloadComplete.ts    |  41 ------
 .../socketio/socketBulkDownloadFailed.ts      |  32 -----
 .../components/Boards/BoardContextMenu.tsx    |  33 +----
 .../MultipleSelectionMenuItems.tsx            |  32 +----
 7 files changed, 131 insertions(+), 140 deletions(-)
 create mode 100644 invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/bulkDownload.ts
 delete mode 100644 invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketBulkDownloadComplete.ts
 delete mode 100644 invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketBulkDownloadFailed.ts

diff --git a/invokeai/frontend/web/public/locales/en.json b/invokeai/frontend/web/public/locales/en.json
index 32d3d382bd..9abf0b80aa 100644
--- a/invokeai/frontend/web/public/locales/en.json
+++ b/invokeai/frontend/web/public/locales/en.json
@@ -424,10 +424,11 @@
         "uploads": "Uploads",
         "deleteSelection": "Delete Selection",
         "downloadSelection": "Download Selection",
-        "preparingDownload": "Preparing Download",
-        "preparingDownloadFailed": "Problem Preparing Download",
-        "bulkDownloadStarting": "Beginning Download",
-        "bulkDownloadFailed": "Problem Preparing Download",
+        "bulkDownloadRequested": "Preparing Download",
+        "bulkDownloadRequestedDesc": "Your download request is being prepared. This may take a few moments.",
+        "bulkDownloadRequestFailed": "Problem Preparing Download",
+        "bulkDownloadStarting": "Download Starting",
+        "bulkDownloadFailed": "Download Failed",
         "problemDeletingImages": "Problem Deleting Images",
         "problemDeletingImagesDesc": "One or more images could not be deleted"
     },
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts
index 07d9bb5df5..23e23c1140 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts
@@ -1,5 +1,6 @@
 import type { ListenerEffect, TypedAddListener, TypedStartListening, UnknownAction } from '@reduxjs/toolkit';
 import { addListener, createListenerMiddleware } from '@reduxjs/toolkit';
+import { addBulkDownloadListeners } from 'app/store/middleware/listenerMiddleware/listeners/bulkDownload';
 import { addGalleryImageClickedListener } from 'app/store/middleware/listenerMiddleware/listeners/galleryImageClicked';
 import type { AppDispatch, RootState } from 'app/store/store';
 
@@ -48,8 +49,6 @@ import { addInitialImageSelectedListener } from './listeners/initialImageSelecte
 import { addModelSelectedListener } from './listeners/modelSelected';
 import { addModelsLoadedListener } from './listeners/modelsLoaded';
 import { addDynamicPromptsListener } from './listeners/promptChanged';
-import { addBulkDownloadCompleteEventListener } from './listeners/socketio/socketBulkDownloadComplete';
-import { addBulkDownloadFailedEventListener } from './listeners/socketio/socketBulkDownloadFailed';
 import { addSocketConnectedEventListener as addSocketConnectedListener } from './listeners/socketio/socketConnected';
 import { addSocketDisconnectedEventListener as addSocketDisconnectedListener } from './listeners/socketio/socketDisconnected';
 import { addGeneratorProgressEventListener as addGeneratorProgressListener } from './listeners/socketio/socketGeneratorProgress';
@@ -139,8 +138,7 @@ addModelLoadEventListener();
 addSessionRetrievalErrorEventListener();
 addInvocationRetrievalErrorEventListener();
 addSocketQueueItemStatusChangedEventListener();
-addBulkDownloadCompleteEventListener();
-addBulkDownloadFailedEventListener();
+addBulkDownloadListeners();
 
 // ControlNet
 addControlNetImageProcessedListener();
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/bulkDownload.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/bulkDownload.ts
new file mode 100644
index 0000000000..39d7e574c2
--- /dev/null
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/bulkDownload.ts
@@ -0,0 +1,118 @@
+import type { UseToastOptions } from '@invoke-ai/ui-library';
+import { createStandaloneToast, theme, TOAST_OPTIONS } from '@invoke-ai/ui-library';
+import { logger } from 'app/logging/logger';
+import { startAppListening } from 'app/store/middleware/listenerMiddleware';
+import { t } from 'i18next';
+import { imagesApi } from 'services/api/endpoints/images';
+import {
+  socketBulkDownloadCompleted,
+  socketBulkDownloadFailed,
+  socketBulkDownloadStarted,
+} from 'services/events/actions';
+
+const log = logger('images');
+
+const { toast } = createStandaloneToast({
+  theme: theme,
+  defaultOptions: TOAST_OPTIONS.defaultOptions,
+});
+
+export const addBulkDownloadListeners = () => {
+  startAppListening({
+    matcher: imagesApi.endpoints.bulkDownloadImages.matchFulfilled,
+    effect: async (action) => {
+      log.debug(action.payload, 'Bulk download requested');
+
+      // If we have an item name, we are processing the bulk download locally and should use it as the toast id to
+      // prevent multiple toasts for the same item.
+      toast({
+        id: action.payload.bulk_download_item_name ?? undefined,
+        title: t('gallery.bulkDownloadRequested'),
+        status: 'success',
+        // Show the response message if it exists, otherwise show the default message
+        description: action.payload.response || t('gallery.bulkDownloadRequestedDesc'),
+        duration: null,
+        isClosable: true,
+      });
+    },
+  });
+
+  startAppListening({
+    matcher: imagesApi.endpoints.bulkDownloadImages.matchRejected,
+    effect: async () => {
+      log.debug('Bulk download request failed');
+
+      // There isn't any toast to update if we get this event.
+      toast({
+        title: t('gallery.bulkDownloadRequestFailed'),
+        status: 'success',
+        isClosable: true,
+      });
+    },
+  });
+
+  startAppListening({
+    actionCreator: socketBulkDownloadStarted,
+    effect: async (action) => {
+      // This should always happen immediately after the bulk download request, so we don't need to show a toast here.
+      log.debug(action.payload.data, 'Bulk download preparation started');
+    },
+  });
+
+  startAppListening({
+    actionCreator: socketBulkDownloadCompleted,
+    effect: async (action) => {
+      log.debug(action.payload.data, 'Bulk download preparation completed');
+
+      const { bulk_download_item_name } = action.payload.data;
+
+      // TODO(psyche): This URL may break in in some environments (e.g. Nvidia workbench) but we need to test it first
+      const url = `/api/v1/images/download/${bulk_download_item_name}`;
+      const a = document.createElement('a');
+      a.style.display = 'none';
+      a.href = url;
+      a.download = bulk_download_item_name;
+      document.body.appendChild(a);
+      a.click();
+
+      const toastOptions: UseToastOptions = {
+        id: bulk_download_item_name,
+        title: t('gallery.bulkDownloadStarting'),
+        status: 'success',
+        description: bulk_download_item_name,
+        duration: 5000,
+        isClosable: true,
+      };
+
+      if (toast.isActive(bulk_download_item_name)) {
+        toast.update(bulk_download_item_name, toastOptions);
+      } else {
+        toast(toastOptions);
+      }
+    },
+  });
+
+  startAppListening({
+    actionCreator: socketBulkDownloadFailed,
+    effect: async (action) => {
+      log.debug(action.payload.data, 'Bulk download preparation failed');
+
+      const { bulk_download_item_name } = action.payload.data;
+
+      const toastOptions: UseToastOptions = {
+        id: bulk_download_item_name,
+        title: t('gallery.bulkDownloadFailed'),
+        status: 'error',
+        description: action.payload.data.error,
+        duration: null,
+        isClosable: true,
+      };
+
+      if (toast.isActive(bulk_download_item_name)) {
+        toast.update(bulk_download_item_name, toastOptions);
+      } else {
+        toast(toastOptions);
+      }
+    },
+  });
+};
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketBulkDownloadComplete.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketBulkDownloadComplete.ts
deleted file mode 100644
index acdb61ff25..0000000000
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketBulkDownloadComplete.ts
+++ /dev/null
@@ -1,41 +0,0 @@
-import { logger } from 'app/logging/logger';
-import { addToast } from 'features/system/store/systemSlice';
-import { t } from 'i18next';
-import { socketBulkDownloadCompleted } from 'services/events/actions';
-
-import { startAppListening } from '../..';
-
-const log = logger('socketio');
-
-export const addBulkDownloadCompleteEventListener = () => {
-  startAppListening({
-    actionCreator: socketBulkDownloadCompleted,
-    effect: async (action, { dispatch }) => {
-      log.debug(action.payload, 'Bulk download complete');
-
-      const bulk_download_item_name = action.payload.data.bulk_download_item_name;
-
-      const url = `/api/v1/images/download/${bulk_download_item_name}`;
-      const a = document.createElement('a');
-      a.style.display = 'none';
-      a.href = url;
-      a.download = bulk_download_item_name;
-      document.body.appendChild(a);
-      a.click();
-
-      dispatch(
-        addToast({
-          title: t('gallery.bulkDownloadStarting'),
-          status: 'success',
-          ...(action.payload
-            ? {
-                description: bulk_download_item_name,
-                duration: null,
-                isClosable: true,
-              }
-            : {}),
-        })
-      );
-    },
-  });
-};
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketBulkDownloadFailed.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketBulkDownloadFailed.ts
deleted file mode 100644
index a9a45c42ae..0000000000
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketBulkDownloadFailed.ts
+++ /dev/null
@@ -1,32 +0,0 @@
-import { logger } from 'app/logging/logger';
-import { addToast } from 'features/system/store/systemSlice';
-import { t } from 'i18next';
-import { socketBulkDownloadFailed } from 'services/events/actions';
-
-import { startAppListening } from '../..';
-
-const log = logger('socketio');
-
-export const addBulkDownloadFailedEventListener = () => {
-  startAppListening({
-    actionCreator: socketBulkDownloadFailed,
-    effect: async (action, { dispatch }) => {
-      log.debug(action.payload, 'Bulk download error');
-
-
-      dispatch(
-        addToast({
-          title: t('gallery.bulkDownloadFailed'),
-          status: 'error',
-          ...(action.payload
-            ? {
-                description: action.payload.data.error,
-                duration: null,
-                isClosable: true,
-              }
-            : {}),
-        })
-      );
-    },
-  });
-};
diff --git a/invokeai/frontend/web/src/features/gallery/components/Boards/BoardContextMenu.tsx b/invokeai/frontend/web/src/features/gallery/components/Boards/BoardContextMenu.tsx
index 490e8eac9e..ad6c37532e 100644
--- a/invokeai/frontend/web/src/features/gallery/components/Boards/BoardContextMenu.tsx
+++ b/invokeai/frontend/web/src/features/gallery/components/Boards/BoardContextMenu.tsx
@@ -5,7 +5,6 @@ import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { autoAddBoardIdChanged, selectGallerySlice } from 'features/gallery/store/gallerySlice';
 import type { BoardId } from 'features/gallery/store/types';
 import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';
-import { addToast } from 'features/system/store/systemSlice';
 import { memo, useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
 import { PiDownloadBold, PiPlusBold } from 'react-icons/pi';
@@ -41,35 +40,9 @@ const BoardContextMenu = ({ board, board_id, setBoardToDelete, children }: Props
     dispatch(autoAddBoardIdChanged(board_id));
   }, [board_id, dispatch]);
 
-  const handleBulkDownload = useCallback(async () => {
-    try {
-      const response = await bulkDownload({
-        image_names: [],
-        board_id: board_id,
-      }).unwrap();
-
-      dispatch(
-        addToast({
-          title: t('gallery.preparingDownload'),
-          status: 'success',
-          ...(response.response
-            ? {
-                description: response.response,
-                duration: null,
-                isClosable: true,
-              }
-            : {}),
-        })
-      );
-    } catch {
-      dispatch(
-        addToast({
-          title: t('gallery.preparingDownloadFailed'),
-          status: 'error',
-        })
-      );
-    }
-  }, [t, board_id, bulkDownload, dispatch]);
+  const handleBulkDownload = useCallback(() => {
+    bulkDownload({ image_names: [], board_id: board_id });
+  }, [board_id, bulkDownload]);
 
   const renderMenuFunc = useCallback(
     () => (
diff --git a/invokeai/frontend/web/src/features/gallery/components/ImageContextMenu/MultipleSelectionMenuItems.tsx b/invokeai/frontend/web/src/features/gallery/components/ImageContextMenu/MultipleSelectionMenuItems.tsx
index e8f71c02f3..7b1fa73472 100644
--- a/invokeai/frontend/web/src/features/gallery/components/ImageContextMenu/MultipleSelectionMenuItems.tsx
+++ b/invokeai/frontend/web/src/features/gallery/components/ImageContextMenu/MultipleSelectionMenuItems.tsx
@@ -5,7 +5,6 @@ import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { imagesToChangeSelected, isModalOpenChanged } from 'features/changeBoardModal/store/slice';
 import { imagesToDeleteSelected } from 'features/deleteImageModal/store/slice';
 import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';
-import { addToast } from 'features/system/store/systemSlice';
 import { memo, useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
 import { PiDownloadSimpleBold, PiFoldersBold, PiStarBold, PiStarFill, PiTrashSimpleBold } from 'react-icons/pi';
@@ -44,34 +43,9 @@ const MultipleSelectionMenuItems = () => {
     unstarImages({ imageDTOs: selection });
   }, [unstarImages, selection]);
 
-  const handleBulkDownload = useCallback(async () => {
-    try {
-      const response = await bulkDownload({
-        image_names: selection.map((img) => img.image_name),
-      }).unwrap();
-
-      dispatch(
-        addToast({
-          title: t('gallery.preparingDownload'),
-          status: 'success',
-          ...(response.response
-            ? {
-                description: response.response,
-                duration: null,
-                isClosable: true,
-              }
-            : {}),
-        })
-      );
-    } catch {
-      dispatch(
-        addToast({
-          title: t('gallery.preparingDownloadFailed'),
-          status: 'error',
-        })
-      );
-    }
-  }, [t, selection, bulkDownload, dispatch]);
+  const handleBulkDownload = useCallback(() => {
+    bulkDownload({ image_names: selection.map((img) => img.image_name) });
+  }, [selection, bulkDownload]);
 
   const areAllStarred = useMemo(() => {
     return selection.every((img) => img.starred);

From 6a923cce703520f3dddfb6b0226d6d8a7d87f77c Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 20 Feb 2024 22:40:16 +1100
Subject: [PATCH 225/411] feat(ui): do not subscribe to bulk download sio room
 if baseUrl is set

---
 .../web/src/services/events/util/setEventListeners.ts      | 7 +++++--
 1 file changed, 5 insertions(+), 2 deletions(-)

diff --git a/invokeai/frontend/web/src/services/events/util/setEventListeners.ts b/invokeai/frontend/web/src/services/events/util/setEventListeners.ts
index d851a185ff..1f27955ca7 100644
--- a/invokeai/frontend/web/src/services/events/util/setEventListeners.ts
+++ b/invokeai/frontend/web/src/services/events/util/setEventListeners.ts
@@ -1,3 +1,4 @@
+import { $baseUrl } from 'app/store/nanostores/baseUrl';
 import { $bulkDownloadId } from 'app/store/nanostores/bulkDownloadId';
 import { $queueId } from 'app/store/nanostores/queueId';
 import type { AppDispatch } from 'app/store/store';
@@ -38,8 +39,10 @@ export const setEventListeners = (arg: SetEventListenersArg) => {
     dispatch(socketConnected());
     const queue_id = $queueId.get();
     socket.emit('subscribe_queue', { queue_id });
-    const bulk_download_id = $bulkDownloadId.get();
-    socket.emit('subscribe_bulk_download', { bulk_download_id });
+    if (!$baseUrl.get()) {
+      const bulk_download_id = $bulkDownloadId.get();
+      socket.emit('subscribe_bulk_download', { bulk_download_id });
+    }
   });
 
   socket.on('connect_error', (error) => {

From e3c23baae9b967496336e6ec342bb9ad7748126a Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 21 Feb 2024 09:44:16 +1100
Subject: [PATCH 226/411] fix(ui): fix package build

---
 invokeai/frontend/web/tsconfig.node.json |  2 +-
 invokeai/frontend/web/vite.config.mts    | 14 +++++++-------
 2 files changed, 8 insertions(+), 8 deletions(-)

diff --git a/invokeai/frontend/web/tsconfig.node.json b/invokeai/frontend/web/tsconfig.node.json
index b5936d415c..046964021f 100644
--- a/invokeai/frontend/web/tsconfig.node.json
+++ b/invokeai/frontend/web/tsconfig.node.json
@@ -5,5 +5,5 @@
     "moduleResolution": "Node",
     "allowSyntheticDefaultImports": true
   },
-  "include": ["vite.config.mts", "config/vite.app.config.mts", "config/vite.package.config.mts", "config/common.mts"]
+  "include": ["vite.config.mts"]
 }
diff --git a/invokeai/frontend/web/vite.config.mts b/invokeai/frontend/web/vite.config.mts
index 32e3e1f64f..ae64b7198d 100644
--- a/invokeai/frontend/web/vite.config.mts
+++ b/invokeai/frontend/web/vite.config.mts
@@ -26,7 +26,7 @@ export default defineConfig(({ mode }) => {
       build: {
         cssCodeSplit: true,
         lib: {
-          entry: path.resolve(__dirname, '../src/index.ts'),
+          entry: path.resolve(__dirname, './src/index.ts'),
           name: 'InvokeAIUI',
           fileName: (format) => `invoke-ai-ui.${format}.js`,
         },
@@ -44,12 +44,12 @@ export default defineConfig(({ mode }) => {
       },
       resolve: {
         alias: {
-          app: path.resolve(__dirname, '../src/app'),
-          assets: path.resolve(__dirname, '../src/assets'),
-          common: path.resolve(__dirname, '../src/common'),
-          features: path.resolve(__dirname, '../src/features'),
-          services: path.resolve(__dirname, '../src/services'),
-          theme: path.resolve(__dirname, '../src/theme'),
+          app: path.resolve(__dirname, './src/app'),
+          assets: path.resolve(__dirname, './src/assets'),
+          common: path.resolve(__dirname, './src/common'),
+          features: path.resolve(__dirname, './src/features'),
+          services: path.resolve(__dirname, './src/services'),
+          theme: path.resolve(__dirname, './src/theme'),
         },
       },
     };

From 34f3a39cc9a6a60ef495e305b5360883d81218d8 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 21 Feb 2024 19:04:43 +1100
Subject: [PATCH 227/411] fix(nodes): fix TI loading

---
 invokeai/app/invocations/compel.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/invokeai/app/invocations/compel.py b/invokeai/app/invocations/compel.py
index 47be380626..50f5322513 100644
--- a/invokeai/app/invocations/compel.py
+++ b/invokeai/app/invocations/compel.py
@@ -86,7 +86,7 @@ class CompelInvocation(BaseInvocation):
         for trigger in extract_ti_triggers_from_prompt(self.prompt):
             name = trigger[1:-1]
             try:
-                loaded_model = context.models.load(**self.clip.text_encoder.model_dump()).model
+                loaded_model = context.models.load(key=name).model
                 assert isinstance(loaded_model, TextualInversionModelRaw)
                 ti_list.append((name, loaded_model))
             except UnknownModelException:

From 9d9b417432192146c98369029957b29883f48988 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 21 Feb 2024 19:42:36 +1100
Subject: [PATCH 228/411] fix(ui): use model names in badges

---
 .../src/features/lora/components/LoRACard.tsx |  6 +-
 .../web/src/features/nodes/types/common.ts    |  8 ++-
 .../parameters/types/parameterSchemas.ts      |  4 +-
 .../AdvancedSettingsAccordion.tsx             | 56 ++++++++++---------
 .../GenerationSettingsAccordion.tsx           | 31 +++++-----
 .../web/src/services/api/endpoints/models.ts  | 13 +++++
 .../api/hooks/useSelectedModelConfig.ts       | 14 +++++
 .../frontend/web/src/services/api/index.ts    |  1 +
 8 files changed, 85 insertions(+), 48 deletions(-)
 create mode 100644 invokeai/frontend/web/src/services/api/hooks/useSelectedModelConfig.ts

diff --git a/invokeai/frontend/web/src/features/lora/components/LoRACard.tsx b/invokeai/frontend/web/src/features/lora/components/LoRACard.tsx
index 71ce145786..579d45054b 100644
--- a/invokeai/frontend/web/src/features/lora/components/LoRACard.tsx
+++ b/invokeai/frontend/web/src/features/lora/components/LoRACard.tsx
@@ -15,14 +15,16 @@ import type { LoRA } from 'features/lora/store/loraSlice';
 import { loraIsEnabledChanged, loraRemoved, loraWeightChanged } from 'features/lora/store/loraSlice';
 import { memo, useCallback } from 'react';
 import { PiTrashSimpleBold } from 'react-icons/pi';
+import { useGetModelConfigQuery } from 'services/api/endpoints/models';
 
 type LoRACardProps = {
   lora: LoRA;
 };
 
 export const LoRACard = memo((props: LoRACardProps) => {
-  const dispatch = useAppDispatch();
   const { lora } = props;
+  const dispatch = useAppDispatch();
+  const { data: loraConfig } = useGetModelConfigQuery(lora.key);
 
   const handleChange = useCallback(
     (v: number) => {
@@ -44,7 +46,7 @@ export const LoRACard = memo((props: LoRACardProps) => {
       <CardHeader>
         <Flex alignItems="center" justifyContent="space-between" width="100%" gap={2}>
           <Text noOfLines={1} wordBreak="break-all" color={lora.isEnabled ? 'base.200' : 'base.500'}>
-            {lora.key}
+            {loraConfig?.name ?? lora.key.substring(0, 8)}
           </Text>
           <Flex alignItems="center" gap={2}>
             <Switch size="sm" onChange={handleSetLoraToggle} isChecked={lora.isEnabled} />
diff --git a/invokeai/frontend/web/src/features/nodes/types/common.ts b/invokeai/frontend/web/src/features/nodes/types/common.ts
index d5d04deaa5..b195ce4434 100644
--- a/invokeai/frontend/web/src/features/nodes/types/common.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/common.ts
@@ -67,6 +67,8 @@ export const zModelName = z.string().min(3);
 export const zModelIdentifier = z.object({
   key: z.string().min(1),
 });
+export const isModelIdentifier = (field: unknown): field is ModelIdentifier =>
+  zModelIdentifier.safeParse(field).success;
 export const zModelFieldBase = zModelIdentifier;
 export const zModelIdentifierWithBase = zModelIdentifier.extend({ base: zBaseModel });
 export type BaseModel = z.infer<typeof zBaseModel>;
@@ -141,7 +143,7 @@ export type VAEField = z.infer<typeof zVAEField>;
 // #region Control Adapters
 export const zControlField = z.object({
   image: zImageField,
-  control_model: zControlNetModelField,
+  control_model: zModelFieldBase,
   control_weight: z.union([z.number(), z.array(z.number())]).optional(),
   begin_step_percent: z.number().optional(),
   end_step_percent: z.number().optional(),
@@ -152,7 +154,7 @@ export type ControlField = z.infer<typeof zControlField>;
 
 export const zIPAdapterField = z.object({
   image: zImageField,
-  ip_adapter_model: zIPAdapterModelField,
+  ip_adapter_model: zModelFieldBase,
   weight: z.number(),
   begin_step_percent: z.number().optional(),
   end_step_percent: z.number().optional(),
@@ -161,7 +163,7 @@ export type IPAdapterField = z.infer<typeof zIPAdapterField>;
 
 export const zT2IAdapterField = z.object({
   image: zImageField,
-  t2i_adapter_model: zT2IAdapterModelField,
+  t2i_adapter_model: zModelFieldBase,
   weight: z.union([z.number(), z.array(z.number())]).optional(),
   begin_step_percent: z.number().optional(),
   end_step_percent: z.number().optional(),
diff --git a/invokeai/frontend/web/src/features/parameters/types/parameterSchemas.ts b/invokeai/frontend/web/src/features/parameters/types/parameterSchemas.ts
index abd8ee2810..b30d5df147 100644
--- a/invokeai/frontend/web/src/features/parameters/types/parameterSchemas.ts
+++ b/invokeai/frontend/web/src/features/parameters/types/parameterSchemas.ts
@@ -4,7 +4,7 @@ import {
   zControlNetModelField,
   zIPAdapterModelField,
   zLoRAModelField,
-  zMainModelField,
+  zModelIdentifierWithBase,
   zSchedulerField,
   zSDXLRefinerModelField,
   zT2IAdapterModelField,
@@ -105,7 +105,7 @@ export const isParameterAspectRatio = (val: unknown): val is ParameterAspectRati
 // #endregion
 
 // #region Model
-export const zParameterModel = zMainModelField.extend({ base: zBaseModel });
+export const zParameterModel = zModelIdentifierWithBase;
 export type ParameterModel = z.infer<typeof zParameterModel>;
 export const isParameterModel = (val: unknown): val is ParameterModel => zParameterModel.safeParse(val).success;
 // #endregion
diff --git a/invokeai/frontend/web/src/features/settingsAccordions/components/AdvancedSettingsAccordion/AdvancedSettingsAccordion.tsx b/invokeai/frontend/web/src/features/settingsAccordions/components/AdvancedSettingsAccordion/AdvancedSettingsAccordion.tsx
index fc8c54576c..8b10d9bddd 100644
--- a/invokeai/frontend/web/src/features/settingsAccordions/components/AdvancedSettingsAccordion/AdvancedSettingsAccordion.tsx
+++ b/invokeai/frontend/web/src/features/settingsAccordions/components/AdvancedSettingsAccordion/AdvancedSettingsAccordion.tsx
@@ -1,5 +1,6 @@
 import type { FormLabelProps } from '@invoke-ai/ui-library';
 import { Flex, FormControlGroup, StandaloneAccordion } from '@invoke-ai/ui-library';
+import { skipToken } from '@reduxjs/toolkit/query';
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppSelector } from 'app/store/storeHooks';
 import ParamCFGRescaleMultiplier from 'features/parameters/components/Advanced/ParamCFGRescaleMultiplier';
@@ -10,8 +11,9 @@ import ParamVAEModelSelect from 'features/parameters/components/VAEModel/ParamVA
 import ParamVAEPrecision from 'features/parameters/components/VAEModel/ParamVAEPrecision';
 import { selectGenerationSlice } from 'features/parameters/store/generationSlice';
 import { useStandaloneAccordionToggle } from 'features/settingsAccordions/hooks/useStandaloneAccordionToggle';
-import { memo } from 'react';
+import { memo, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
+import { useGetModelConfigQuery } from 'services/api/endpoints/models';
 
 const formLabelProps: FormLabelProps = {
   minW: '9.2rem',
@@ -21,31 +23,35 @@ const formLabelProps2: FormLabelProps = {
   flexGrow: 1,
 };
 
-const selectBadges = createMemoizedSelector(selectGenerationSlice, (generation) => {
-  const badges: (string | number)[] = [];
-  if (generation.vae) {
-    // TODO(MM2): Fetch the vae name
-    let vaeBadge = generation.vae.key;
-    if (generation.vaePrecision === 'fp16') {
-      vaeBadge += ` ${generation.vaePrecision}`;
-    }
-    badges.push(vaeBadge);
-  } else if (generation.vaePrecision === 'fp16') {
-    badges.push(`VAE ${generation.vaePrecision}`);
-  }
-  if (generation.clipSkip) {
-    badges.push(`Skip ${generation.clipSkip}`);
-  }
-  if (generation.cfgRescaleMultiplier) {
-    badges.push(`Rescale ${generation.cfgRescaleMultiplier}`);
-  }
-  if (generation.seamlessXAxis || generation.seamlessYAxis) {
-    badges.push('seamless');
-  }
-  return badges;
-});
-
 export const AdvancedSettingsAccordion = memo(() => {
+  const vaeKey = useAppSelector((state) => state.generation.vae?.key);
+  const { data: vaeConfig } = useGetModelConfigQuery(vaeKey ?? skipToken);
+  const selectBadges = useMemo(
+    () =>
+      createMemoizedSelector(selectGenerationSlice, (generation) => {
+        const badges: (string | number)[] = [];
+        if (vaeConfig) {
+          let vaeBadge = vaeConfig.name;
+          if (generation.vaePrecision === 'fp16') {
+            vaeBadge += ` ${generation.vaePrecision}`;
+          }
+          badges.push(vaeBadge);
+        } else if (generation.vaePrecision === 'fp16') {
+          badges.push(`VAE ${generation.vaePrecision}`);
+        }
+        if (generation.clipSkip) {
+          badges.push(`Skip ${generation.clipSkip}`);
+        }
+        if (generation.cfgRescaleMultiplier) {
+          badges.push(`Rescale ${generation.cfgRescaleMultiplier}`);
+        }
+        if (generation.seamlessXAxis || generation.seamlessYAxis) {
+          badges.push('seamless');
+        }
+        return badges;
+      }),
+    [vaeConfig]
+  );
   const badges = useAppSelector(selectBadges);
   const { t } = useTranslation();
   const { isOpen, onToggle } = useStandaloneAccordionToggle({
diff --git a/invokeai/frontend/web/src/features/settingsAccordions/components/GenerationSettingsAccordion/GenerationSettingsAccordion.tsx b/invokeai/frontend/web/src/features/settingsAccordions/components/GenerationSettingsAccordion/GenerationSettingsAccordion.tsx
index cda7dcf6e9..d57e48f11e 100644
--- a/invokeai/frontend/web/src/features/settingsAccordions/components/GenerationSettingsAccordion/GenerationSettingsAccordion.tsx
+++ b/invokeai/frontend/web/src/features/settingsAccordions/components/GenerationSettingsAccordion/GenerationSettingsAccordion.tsx
@@ -12,6 +12,7 @@ import {
 } from '@invoke-ai/ui-library';
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppSelector } from 'app/store/storeHooks';
+import { EMPTY_ARRAY } from 'app/store/util';
 import { LoRAList } from 'features/lora/components/LoRAList';
 import LoRASelect from 'features/lora/components/LoRASelect';
 import { selectLoraSlice } from 'features/lora/store/loraSlice';
@@ -20,33 +21,31 @@ import ParamCFGScale from 'features/parameters/components/Core/ParamCFGScale';
 import ParamScheduler from 'features/parameters/components/Core/ParamScheduler';
 import ParamSteps from 'features/parameters/components/Core/ParamSteps';
 import ParamMainModelSelect from 'features/parameters/components/MainModel/ParamMainModelSelect';
-import { selectGenerationSlice } from 'features/parameters/store/generationSlice';
 import { useExpanderToggle } from 'features/settingsAccordions/hooks/useExpanderToggle';
 import { useStandaloneAccordionToggle } from 'features/settingsAccordions/hooks/useStandaloneAccordionToggle';
 import { filter } from 'lodash-es';
-import { memo } from 'react';
+import { memo, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
+import { useSelectedModelConfig } from 'services/api/hooks/useSelectedModelConfig';
 
 const formLabelProps: FormLabelProps = {
   minW: '4rem',
 };
 
-const badgesSelector = createMemoizedSelector(selectLoraSlice, selectGenerationSlice, (lora, generation) => {
-  const enabledLoRAsCount = filter(lora.loras, (l) => !!l.isEnabled).length;
-  const loraTabBadges = enabledLoRAsCount ? [enabledLoRAsCount] : [];
-  const accordionBadges: (string | number)[] = [];
-  // TODO(MM2): fetch model name
-  if (generation.model) {
-    accordionBadges.push(generation.model.key);
-    accordionBadges.push(generation.model.base);
-  }
-
-  return { loraTabBadges, accordionBadges };
-});
-
 export const GenerationSettingsAccordion = memo(() => {
   const { t } = useTranslation();
-  const { loraTabBadges, accordionBadges } = useAppSelector(badgesSelector);
+  const modelConfig = useSelectedModelConfig();
+  const selectBadges = useMemo(
+    () =>
+      createMemoizedSelector(selectLoraSlice, (lora) => {
+        const enabledLoRAsCount = filter(lora.loras, (l) => !!l.isEnabled).length;
+        const loraTabBadges = enabledLoRAsCount ? [enabledLoRAsCount] : EMPTY_ARRAY;
+        const accordionBadges = modelConfig ? [modelConfig.name, modelConfig.base] : EMPTY_ARRAY;
+        return { loraTabBadges, accordionBadges };
+      }),
+    [modelConfig]
+  );
+  const { loraTabBadges, accordionBadges } = useAppSelector(selectBadges);
   const { isOpen: isOpenExpander, onToggle: onToggleExpander } = useExpanderToggle({
     id: 'generation-settings-advanced',
     defaultIsOpen: false,
diff --git a/invokeai/frontend/web/src/services/api/endpoints/models.ts b/invokeai/frontend/web/src/services/api/endpoints/models.ts
index 46be42d9e5..666e0c707d 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/models.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/models.ts
@@ -236,6 +236,18 @@ export const modelsApi = api.injectEndpoints({
       },
       invalidatesTags: ['Model'],
     }),
+    getModelConfig: build.query<AnyModelConfig, string>({
+      query: (key) => buildModelsUrl(`i/${key}`),
+      providesTags: (result) => {
+        const tags: ApiTagDescription[] = ['Model'];
+
+        if (result) {
+          tags.push({ type: 'ModelConfig', id: result.key });
+        }
+
+        return tags;
+      },
+    }),
     syncModels: build.mutation<SyncModelsResponse, void>({
       query: () => {
         return {
@@ -313,6 +325,7 @@ export const modelsApi = api.injectEndpoints({
 });
 
 export const {
+  useGetModelConfigQuery,
   useGetMainModelsQuery,
   useGetControlNetModelsQuery,
   useGetIPAdapterModelsQuery,
diff --git a/invokeai/frontend/web/src/services/api/hooks/useSelectedModelConfig.ts b/invokeai/frontend/web/src/services/api/hooks/useSelectedModelConfig.ts
new file mode 100644
index 0000000000..4a8d8d72e2
--- /dev/null
+++ b/invokeai/frontend/web/src/services/api/hooks/useSelectedModelConfig.ts
@@ -0,0 +1,14 @@
+import { createSelector } from '@reduxjs/toolkit';
+import { skipToken } from '@reduxjs/toolkit/query';
+import { useAppSelector } from 'app/store/storeHooks';
+import { selectGenerationSlice } from 'features/parameters/store/generationSlice';
+import { useGetModelConfigQuery } from 'services/api/endpoints/models';
+
+const selectModelKey = createSelector(selectGenerationSlice, (generation) => generation.model?.key);
+
+export const useSelectedModelConfig = () => {
+  const key = useAppSelector(selectModelKey);
+  const { currentData: modelConfig } = useGetModelConfigQuery(key ?? skipToken);
+
+  return modelConfig;
+};
diff --git a/invokeai/frontend/web/src/services/api/index.ts b/invokeai/frontend/web/src/services/api/index.ts
index f32ae34cb7..82f382ee10 100644
--- a/invokeai/frontend/web/src/services/api/index.ts
+++ b/invokeai/frontend/web/src/services/api/index.ts
@@ -26,6 +26,7 @@ export const tagTypes = [
   'BatchStatus',
   'InvocationCacheStatus',
   'Model',
+  'ModelConfig',
   'T2IAdapterModel',
   'MainModel',
   'VaeModel',

From b59d23d608591d317b5a304b8b2b9bf61d0bb493 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 21 Feb 2024 19:42:49 +1100
Subject: [PATCH 229/411] fix(ui): handle new model format for metadata

---
 .../ImageMetadataActions.tsx                  |  44 +++--
 .../ImageMetadataViewer/ImageMetadataItem.tsx |  46 ++++-
 .../web/src/features/nodes/types/metadata.ts  |   4 +-
 .../parameters/hooks/useRecallParameters.ts   | 161 ++++++++++++------
 4 files changed, 178 insertions(+), 77 deletions(-)

diff --git a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataActions.tsx b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataActions.tsx
index 5907ba0700..7eec7e1875 100644
--- a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataActions.tsx
+++ b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataActions.tsx
@@ -1,3 +1,4 @@
+import { isModelIdentifier } from 'features/nodes/types/common';
 import type {
   ControlNetMetadataItem,
   CoreMetadata,
@@ -6,15 +7,10 @@ import type {
   T2IAdapterMetadataItem,
 } from 'features/nodes/types/metadata';
 import { useRecallParameters } from 'features/parameters/hooks/useRecallParameters';
-import {
-  isParameterControlNetModel,
-  isParameterLoRAModel,
-  isParameterT2IAdapterModel,
-} from 'features/parameters/types/parameterSchemas';
 import { memo, useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
 
-import ImageMetadataItem from './ImageMetadataItem';
+import ImageMetadataItem, { ModelMetadataItem, VAEMetadataItem } from './ImageMetadataItem';
 
 type Props = {
   metadata?: CoreMetadata;
@@ -147,19 +143,19 @@ const ImageMetadataActions = (props: Props) => {
 
   const validControlNets: ControlNetMetadataItem[] = useMemo(() => {
     return metadata?.controlnets
-      ? metadata.controlnets.filter((controlnet) => isParameterControlNetModel(controlnet.control_model))
+      ? metadata.controlnets.filter((controlnet) => isModelIdentifier(controlnet.control_model))
       : [];
   }, [metadata?.controlnets]);
 
   const validIPAdapters: IPAdapterMetadataItem[] = useMemo(() => {
     return metadata?.ipAdapters
-      ? metadata.ipAdapters.filter((ipAdapter) => isParameterControlNetModel(ipAdapter.ip_adapter_model))
+      ? metadata.ipAdapters.filter((ipAdapter) => isModelIdentifier(ipAdapter.ip_adapter_model))
       : [];
   }, [metadata?.ipAdapters]);
 
   const validT2IAdapters: T2IAdapterMetadataItem[] = useMemo(() => {
     return metadata?.t2iAdapters
-      ? metadata.t2iAdapters.filter((t2iAdapter) => isParameterT2IAdapterModel(t2iAdapter.t2i_adapter_model))
+      ? metadata.t2iAdapters.filter((t2iAdapter) => isModelIdentifier(t2iAdapter.t2i_adapter_model))
       : [];
   }, [metadata?.t2iAdapters]);
 
@@ -209,7 +205,7 @@ const ImageMetadataActions = (props: Props) => {
         <ImageMetadataItem label={t('metadata.seed')} value={metadata.seed} onClick={handleRecallSeed} />
       )}
       {metadata.model !== undefined && metadata.model !== null && metadata.model.key && (
-        <ImageMetadataItem label={t('metadata.model')} value={metadata.model.key} onClick={handleRecallModel} />
+        <ModelMetadataItem label={t('metadata.model')} modelKey={metadata.model.key} onClick={handleRecallModel} />
       )}
       {metadata.width && (
         <ImageMetadataItem label={t('metadata.width')} value={metadata.width} onClick={handleRecallWidth} />
@@ -220,11 +216,7 @@ const ImageMetadataActions = (props: Props) => {
       {metadata.scheduler && (
         <ImageMetadataItem label={t('metadata.scheduler')} value={metadata.scheduler} onClick={handleRecallScheduler} />
       )}
-      <ImageMetadataItem
-        label={t('metadata.vae')}
-        value={metadata.vae?.key ?? 'Default'}
-        onClick={handleRecallVaeModel}
-      />
+      <VAEMetadataItem label={t('metadata.vae')} modelKey={metadata.vae?.key} onClick={handleRecallVaeModel} />
       {metadata.steps && (
         <ImageMetadataItem label={t('metadata.steps')} value={metadata.steps} onClick={handleRecallSteps} />
       )}
@@ -264,38 +256,42 @@ const ImageMetadataActions = (props: Props) => {
       )}
       {metadata.loras &&
         metadata.loras.map((lora, index) => {
-          if (isParameterLoRAModel(lora.lora)) {
+          if (isModelIdentifier(lora.lora)) {
             return (
-              <ImageMetadataItem
+              <ModelMetadataItem
                 key={index}
                 label="LoRA"
-                value={`${lora.lora.key} - ${lora.weight}`}
+                modelKey={lora.lora.key}
+                extra={` - ${lora.weight}`}
                 onClick={handleRecallLoRA.bind(null, lora)}
               />
             );
           }
         })}
       {validControlNets.map((controlnet, index) => (
-        <ImageMetadataItem
+        <ModelMetadataItem
           key={index}
           label="ControlNet"
-          value={`${controlnet.control_model?.key} - ${controlnet.control_weight}`}
+          modelKey={controlnet.control_model?.key}
+          extra={` - ${controlnet.control_weight}`}
           onClick={handleRecallControlNet.bind(null, controlnet)}
         />
       ))}
       {validIPAdapters.map((ipAdapter, index) => (
-        <ImageMetadataItem
+        <ModelMetadataItem
           key={index}
           label="IP Adapter"
-          value={`${ipAdapter.ip_adapter_model?.key} - ${ipAdapter.weight}`}
+          modelKey={ipAdapter.ip_adapter_model?.key}
+          extra={` - ${ipAdapter.weight}`}
           onClick={handleRecallIPAdapter.bind(null, ipAdapter)}
         />
       ))}
       {validT2IAdapters.map((t2iAdapter, index) => (
-        <ImageMetadataItem
+        <ModelMetadataItem
           key={index}
           label="T2I Adapter"
-          value={`${t2iAdapter.t2i_adapter_model?.key} - ${t2iAdapter.weight}`}
+          modelKey={t2iAdapter.t2i_adapter_model?.key}
+          extra={` - ${t2iAdapter.weight}`}
           onClick={handleRecallT2IAdapter.bind(null, t2iAdapter)}
         />
       ))}
diff --git a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataItem.tsx b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataItem.tsx
index c6dbd16269..7d17a2ad3d 100644
--- a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataItem.tsx
+++ b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataItem.tsx
@@ -1,8 +1,10 @@
 import { ExternalLink, Flex, IconButton, Text, Tooltip } from '@invoke-ai/ui-library';
-import { memo, useCallback } from 'react';
+import { skipToken } from '@reduxjs/toolkit/query';
+import { memo, useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
 import { IoArrowUndoCircleOutline } from 'react-icons/io5';
 import { PiCopyBold } from 'react-icons/pi';
+import { useGetModelConfigQuery } from 'services/api/endpoints/models';
 
 type MetadataItemProps = {
   isLink?: boolean;
@@ -18,8 +20,9 @@ type MetadataItemProps = {
  */
 const ImageMetadataItem = ({ label, value, onClick, isLink, labelPosition, withCopy = false }: MetadataItemProps) => {
   const { t } = useTranslation();
-
-  const handleCopy = useCallback(() => navigator.clipboard.writeText(value.toString()), [value]);
+  const handleCopy = useCallback(() => {
+    navigator.clipboard.writeText(value?.toString());
+  }, [value]);
 
   if (!value) {
     return null;
@@ -68,3 +71,40 @@ const ImageMetadataItem = ({ label, value, onClick, isLink, labelPosition, withC
 };
 
 export default memo(ImageMetadataItem);
+
+type VAEMetadataItemProps = {
+  label: string;
+  modelKey?: string;
+  onClick: () => void;
+};
+
+export const VAEMetadataItem = memo(({ label, modelKey, onClick }: VAEMetadataItemProps) => {
+  const { data: modelConfig } = useGetModelConfigQuery(modelKey ?? skipToken);
+
+  return (
+    <ImageMetadataItem label={label} value={modelKey ? modelConfig?.name ?? modelKey : 'Default'} onClick={onClick} />
+  );
+});
+
+VAEMetadataItem.displayName = 'VAEMetadataItem';
+
+type ModelMetadataItemProps = {
+  label: string;
+  modelKey?: string;
+  
+  extra?: string;
+  onClick: () => void;
+};
+
+export const ModelMetadataItem = memo(({ label, modelKey, extra, onClick }: ModelMetadataItemProps) => {
+  const { data: modelConfig } = useGetModelConfigQuery(modelKey ?? skipToken);
+  const value = useMemo(() => {
+    if (modelConfig) {
+      return `${modelConfig.name}${extra ?? ''}`;
+    }
+    return `${modelKey}${extra ?? ''}`;
+  }, [extra, modelConfig, modelKey]);
+  return <ImageMetadataItem label={label} value={value} onClick={onClick} />;
+});
+
+ModelMetadataItem.displayName = 'ModelMetadataItem';
diff --git a/invokeai/frontend/web/src/features/nodes/types/metadata.ts b/invokeai/frontend/web/src/features/nodes/types/metadata.ts
index 0cc30499e3..493a0464b3 100644
--- a/invokeai/frontend/web/src/features/nodes/types/metadata.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/metadata.ts
@@ -3,8 +3,8 @@ import { z } from 'zod';
 import {
   zControlField,
   zIPAdapterField,
-  zLoRAModelField,
   zMainModelField,
+  zModelFieldBase,
   zSDXLRefinerModelField,
   zT2IAdapterField,
   zVAEModelField,
@@ -15,7 +15,7 @@ import {
 // - https://github.com/colinhacks/zod/issues/2106
 // - https://github.com/colinhacks/zod/issues/2854
 export const zLoRAMetadataItem = z.object({
-  lora: zLoRAModelField.deepPartial(),
+  lora: zModelFieldBase.deepPartial(),
   weight: z.number(),
 });
 const zControlNetMetadataItem = zControlField.deepPartial();
diff --git a/invokeai/frontend/web/src/features/parameters/hooks/useRecallParameters.ts b/invokeai/frontend/web/src/features/parameters/hooks/useRecallParameters.ts
index c8b17816bb..0d464cd9b9 100644
--- a/invokeai/frontend/web/src/features/parameters/hooks/useRecallParameters.ts
+++ b/invokeai/frontend/web/src/features/parameters/hooks/useRecallParameters.ts
@@ -11,6 +11,8 @@ import {
 } from 'features/controlAdapters/util/buildControlAdapter';
 import { setHrfEnabled, setHrfMethod, setHrfStrength } from 'features/hrf/store/hrfSlice';
 import { loraRecalled, lorasCleared } from 'features/lora/store/loraSlice';
+import type { ModelIdentifier } from 'features/nodes/types/common';
+import { isModelIdentifier } from 'features/nodes/types/common';
 import type {
   ControlNetMetadataItem,
   CoreMetadata,
@@ -37,13 +39,9 @@ import type { ParameterModel } from 'features/parameters/types/parameterSchemas'
 import {
   isParameterCFGRescaleMultiplier,
   isParameterCFGScale,
-  isParameterControlNetModel,
   isParameterHeight,
   isParameterHRFEnabled,
   isParameterHRFMethod,
-  isParameterIPAdapterModel,
-  isParameterLoRAModel,
-  isParameterModel,
   isParameterNegativePrompt,
   isParameterNegativeStylePromptSDXL,
   isParameterPositivePrompt,
@@ -56,7 +54,6 @@ import {
   isParameterSeed,
   isParameterSteps,
   isParameterStrength,
-  isParameterVAEModel,
   isParameterWidth,
 } from 'features/parameters/types/parameterSchemas';
 import {
@@ -73,15 +70,20 @@ import {
 import { isNil } from 'lodash-es';
 import { useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
+import { ALL_BASE_MODELS } from 'services/api/constants';
 import {
   controlNetModelsAdapterSelectors,
   ipAdapterModelsAdapterSelectors,
   loraModelsAdapterSelectors,
+  mainModelsAdapterSelectors,
   t2iAdapterModelsAdapterSelectors,
   useGetControlNetModelsQuery,
   useGetIPAdapterModelsQuery,
   useGetLoRAModelsQuery,
+  useGetMainModelsQuery,
   useGetT2IAdapterModelsQuery,
+  useGetVaeModelsQuery,
+  vaeModelsAdapterSelectors,
 } from 'services/api/endpoints/models';
 import type { ImageDTO } from 'services/api/types';
 import { v4 as uuidv4 } from 'uuid';
@@ -278,21 +280,6 @@ export const useRecallParameters = () => {
     [dispatch, parameterSetToast, parameterNotSetToast]
   );
 
-  /**
-   * Recall model with toast
-   */
-  const recallModel = useCallback(
-    (model: unknown) => {
-      if (!isParameterModel(model)) {
-        parameterNotSetToast();
-        return;
-      }
-      dispatch(modelSelected(model));
-      parameterSetToast();
-    },
-    [dispatch, parameterSetToast, parameterNotSetToast]
-  );
-
   /**
    * Recall scheduler with toast
    */
@@ -308,25 +295,6 @@ export const useRecallParameters = () => {
     [dispatch, parameterSetToast, parameterNotSetToast]
   );
 
-  /**
-   * Recall vae model
-   */
-  const recallVaeModel = useCallback(
-    (vae: unknown) => {
-      if (!isParameterVAEModel(vae) && !isNil(vae)) {
-        parameterNotSetToast();
-        return;
-      }
-      if (isNil(vae)) {
-        dispatch(vaeSelected(null));
-      } else {
-        dispatch(vaeSelected(vae));
-      }
-      parameterSetToast();
-    },
-    [dispatch, parameterSetToast, parameterNotSetToast]
-  );
-
   /**
    * Recall steps with toast
    */
@@ -452,6 +420,95 @@ export const useRecallParameters = () => {
     [dispatch, parameterSetToast, parameterNotSetToast]
   );
 
+  const { data: mainModels } = useGetMainModelsQuery(ALL_BASE_MODELS);
+
+  const prepareMainModelMetadataItem = useCallback(
+    (model: ModelIdentifier) => {
+      const matchingModel = mainModels ? mainModelsAdapterSelectors.selectById(mainModels, model.key) : undefined;
+
+      if (!matchingModel) {
+        return { model: null, error: 'Model is not installed' };
+      }
+
+      return { model: matchingModel, error: null };
+    },
+    [mainModels]
+  );
+
+  /**
+   * Recall model with toast
+   */
+  const recallModel = useCallback(
+    (model: unknown) => {
+      if (!isModelIdentifier(model)) {
+        parameterNotSetToast();
+        return;
+      }
+
+      const result = prepareMainModelMetadataItem(model);
+
+      if (!result.model) {
+        parameterNotSetToast(result.error);
+        return;
+      }
+
+      dispatch(modelSelected(result.model));
+      parameterSetToast();
+    },
+    [prepareMainModelMetadataItem, dispatch, parameterSetToast, parameterNotSetToast]
+  );
+
+  const { data: vaeModels } = useGetVaeModelsQuery();
+
+  const prepareVAEMetadataItem = useCallback(
+    (vae: ModelIdentifier, newModel?: ParameterModel) => {
+      const matchingModel = vaeModels ? vaeModelsAdapterSelectors.selectById(vaeModels, vae.key) : undefined;
+      if (!matchingModel) {
+        return { vae: null, error: 'VAE model is not installed' };
+      }
+      const isCompatibleBaseModel = matchingModel?.base === (newModel ?? model)?.base;
+
+      if (!isCompatibleBaseModel) {
+        return {
+          vae: null,
+          error: 'VAE incompatible with currently-selected model',
+        };
+      }
+
+      return { vae: matchingModel, error: null };
+    },
+    [model, vaeModels]
+  );
+
+  /**
+   * Recall vae model
+   */
+  const recallVaeModel = useCallback(
+    (vae: unknown) => {
+      if (!isModelIdentifier(vae) && !isNil(vae)) {
+        parameterNotSetToast();
+        return;
+      }
+
+      if (isNil(vae)) {
+        dispatch(vaeSelected(null));
+        parameterSetToast();
+        return;
+      }
+
+      const result = prepareVAEMetadataItem(vae);
+
+      if (!result.vae) {
+        parameterNotSetToast(result.error);
+        return;
+      }
+
+      dispatch(vaeSelected(result.vae));
+      parameterSetToast();
+    },
+    [prepareVAEMetadataItem, dispatch, parameterSetToast, parameterNotSetToast]
+  );
+
   /**
    * Recall LoRA with toast
    */
@@ -460,7 +517,7 @@ export const useRecallParameters = () => {
 
   const prepareLoRAMetadataItem = useCallback(
     (loraMetadataItem: LoRAMetadataItem, newModel?: ParameterModel) => {
-      if (!isParameterLoRAModel(loraMetadataItem.lora)) {
+      if (!isModelIdentifier(loraMetadataItem.lora)) {
         return { lora: null, error: 'Invalid LoRA model' };
       }
 
@@ -510,7 +567,7 @@ export const useRecallParameters = () => {
 
   const prepareControlNetMetadataItem = useCallback(
     (controlnetMetadataItem: ControlNetMetadataItem, newModel?: ParameterModel) => {
-      if (!isParameterControlNetModel(controlnetMetadataItem.control_model)) {
+      if (!isModelIdentifier(controlnetMetadataItem.control_model)) {
         return { controlnet: null, error: 'Invalid ControlNet model' };
       }
 
@@ -584,7 +641,7 @@ export const useRecallParameters = () => {
 
   const prepareT2IAdapterMetadataItem = useCallback(
     (t2iAdapterMetadataItem: T2IAdapterMetadataItem, newModel?: ParameterModel) => {
-      if (!isParameterControlNetModel(t2iAdapterMetadataItem.t2i_adapter_model)) {
+      if (!isModelIdentifier(t2iAdapterMetadataItem.t2i_adapter_model)) {
         return { controlnet: null, error: 'Invalid ControlNet model' };
       }
 
@@ -657,7 +714,7 @@ export const useRecallParameters = () => {
 
   const prepareIPAdapterMetadataItem = useCallback(
     (ipAdapterMetadataItem: IPAdapterMetadataItem, newModel?: ParameterModel) => {
-      if (!isParameterIPAdapterModel(ipAdapterMetadataItem?.ip_adapter_model)) {
+      if (!isModelIdentifier(ipAdapterMetadataItem?.ip_adapter_model)) {
         return { ipAdapter: null, error: 'Invalid IP Adapter model' };
       }
 
@@ -762,9 +819,12 @@ export const useRecallParameters = () => {
 
       let newModel: ParameterModel | undefined = undefined;
 
-      if (isParameterModel(model)) {
-        newModel = model;
-        dispatch(modelSelected(model));
+      if (isModelIdentifier(model)) {
+        const result = prepareMainModelMetadataItem(model);
+        if (result.model) {
+          dispatch(modelSelected(result.model));
+          newModel = result.model;
+        }
       }
 
       if (isParameterCFGScale(cfg_scale)) {
@@ -786,11 +846,14 @@ export const useRecallParameters = () => {
       if (isParameterScheduler(scheduler)) {
         dispatch(setScheduler(scheduler));
       }
-      if (isParameterVAEModel(vae) || isNil(vae)) {
+      if (isModelIdentifier(vae) || isNil(vae)) {
         if (isNil(vae)) {
           dispatch(vaeSelected(null));
         } else {
-          dispatch(vaeSelected(vae));
+          const result = prepareVAEMetadataItem(vae, newModel);
+          if (result.vae) {
+            dispatch(vaeSelected(result.vae));
+          }
         }
       }
 
@@ -898,6 +961,8 @@ export const useRecallParameters = () => {
       dispatch,
       allParameterSetToast,
       allParameterNotSetToast,
+      prepareMainModelMetadataItem,
+      prepareVAEMetadataItem,
       prepareLoRAMetadataItem,
       prepareControlNetMetadataItem,
       prepareIPAdapterMetadataItem,

From dbd929df05d1073fd830d6e57d65500c3d969a4e Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 21 Feb 2024 19:43:14 +1100
Subject: [PATCH 230/411] tidy(ui): remove debugging stmt

---
 .../parameters/components/VAEModel/ParamVAEModelSelect.tsx      | 2 --
 1 file changed, 2 deletions(-)

diff --git a/invokeai/frontend/web/src/features/parameters/components/VAEModel/ParamVAEModelSelect.tsx b/invokeai/frontend/web/src/features/parameters/components/VAEModel/ParamVAEModelSelect.tsx
index 1810c3ff68..4b9f2764bf 100644
--- a/invokeai/frontend/web/src/features/parameters/components/VAEModel/ParamVAEModelSelect.tsx
+++ b/invokeai/frontend/web/src/features/parameters/components/VAEModel/ParamVAEModelSelect.tsx
@@ -41,8 +41,6 @@ const ParamVAEModelSelect = () => {
     isLoading,
     getIsDisabled,
   });
-  
-  console.log(value)
 
   return (
     <FormControl isDisabled={!options.length} isInvalid={!options.length}>

From 571a86a965e3e6fa7943548b5de600b805a7acc7 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 21 Feb 2024 13:47:46 +1100
Subject: [PATCH 231/411] chore(ui): bump deps

Notable updates:
- Minor version of RTK includes customizable selectors for RTK Query, so we can remove the patch that was added to ensure only the LRU memoize function was used for perf reasons. Updated to use the LRU memoize function.
- Major version of react-resizable-panels. No breaking changes, works great, and you can now resize all panels when dragging at the intersection point of panels. Cool!
- Minor (?) version of nanostores. `action` API is removed, we were using it in one spot. Fixed.
- @invoke-ai/eslint-config-react has all deps bumped and now has its dependent plugins/configs listed as normal dependencies (as opposed to peer deps). This means we can remove those packages from explicit dev deps.
---
 invokeai/frontend/web/package.json            |  103 +-
 invokeai/frontend/web/pnpm-lock.yaml          | 4090 +++++++++--------
 .../store/enhancers/reduxRemember/driver.ts   |    8 +-
 .../frontend/web/src/services/api/index.ts    |   12 +-
 4 files changed, 2201 insertions(+), 2012 deletions(-)

diff --git a/invokeai/frontend/web/package.json b/invokeai/frontend/web/package.json
index a9f37f76ad..743cb1e09d 100644
--- a/invokeai/frontend/web/package.json
+++ b/invokeai/frontend/web/package.json
@@ -59,52 +59,52 @@
     "@fontsource-variable/inter": "^5.0.16",
     "@invoke-ai/ui-library": "^0.0.21",
     "@mantine/form": "6.0.21",
-    "@nanostores/react": "^0.7.1",
-    "@reduxjs/toolkit": "2.0.1",
+    "@nanostores/react": "^0.7.2",
+    "@reduxjs/toolkit": "2.2.1",
     "@roarr/browser-log-writer": "^1.3.0",
     "chakra-react-select": "^4.7.6",
     "compare-versions": "^6.1.0",
     "dateformat": "^5.0.3",
-    "framer-motion": "^10.18.0",
-    "i18next": "^23.7.16",
-    "i18next-http-backend": "^2.4.2",
+    "framer-motion": "^11.0.5",
+    "i18next": "^23.9.0",
+    "i18next-http-backend": "^2.4.3",
     "idb-keyval": "^6.2.1",
     "jsondiffpatch": "^0.6.0",
-    "konva": "^9.3.1",
+    "konva": "^9.3.3",
     "lodash-es": "^4.17.21",
-    "nanostores": "^0.9.5",
+    "nanostores": "^0.10.0",
     "new-github-issue-url": "^1.0.0",
-    "overlayscrollbars": "^2.4.6",
-    "overlayscrollbars-react": "^0.5.3",
-    "query-string": "^8.1.0",
+    "overlayscrollbars": "^2.5.0",
+    "overlayscrollbars-react": "^0.5.4",
+    "query-string": "^8.2.0",
     "react": "^18.2.0",
     "react-colorful": "^5.6.1",
     "react-dom": "^18.2.0",
     "react-dropzone": "^14.2.3",
     "react-error-boundary": "^4.0.12",
-    "react-hook-form": "^7.49.3",
-    "react-hotkeys-hook": "4.4.4",
-    "react-i18next": "^14.0.0",
+    "react-hook-form": "^7.50.1",
+    "react-hotkeys-hook": "4.5.0",
+    "react-i18next": "^14.0.5",
     "react-icons": "^5.0.1",
     "react-konva": "^18.2.10",
     "react-redux": "9.1.0",
-    "react-resizable-panels": "^1.0.9",
+    "react-resizable-panels": "^2.0.9",
     "react-select": "5.8.0",
     "react-textarea-autosize": "^8.5.3",
-    "react-use": "^17.4.3",
-    "react-virtuoso": "^4.6.2",
-    "reactflow": "^11.10.2",
+    "react-use": "^17.5.0",
+    "react-virtuoso": "^4.7.0",
+    "reactflow": "^11.10.4",
     "redux-dynamic-middlewares": "^2.2.0",
     "redux-remember": "^5.1.0",
     "roarr": "^7.21.0",
     "serialize-error": "^11.0.3",
     "socket.io-client": "^4.7.4",
-    "type-fest": "^4.9.0",
+    "type-fest": "^4.10.2",
     "use-debounce": "^10.0.0",
     "use-image": "^1.1.1",
     "uuid": "^9.0.1",
     "zod": "^3.22.4",
-    "zod-validation-error": "^3.0.0"
+    "zod-validation-error": "^3.0.2"
   },
   "peerDependencies": {
     "@chakra-ui/react": "^2.8.2",
@@ -113,59 +113,44 @@
     "ts-toolbelt": "^9.6.0"
   },
   "devDependencies": {
-    "@arthurgeron/eslint-plugin-react-usememo": "^2.2.3",
-    "@invoke-ai/eslint-config-react": "^0.0.13",
-    "@invoke-ai/prettier-config-react": "^0.0.6",
-    "@storybook/addon-docs": "^7.6.10",
-    "@storybook/addon-essentials": "^7.6.10",
-    "@storybook/addon-interactions": "^7.6.10",
-    "@storybook/addon-links": "^7.6.10",
-    "@storybook/addon-storysource": "^7.6.10",
-    "@storybook/blocks": "^7.6.10",
-    "@storybook/manager-api": "^7.6.10",
-    "@storybook/react": "^7.6.10",
-    "@storybook/react-vite": "^7.6.10",
-    "@storybook/test": "^7.6.10",
-    "@storybook/theming": "^7.6.10",
+    "@invoke-ai/eslint-config-react": "^0.0.14",
+    "@invoke-ai/prettier-config-react": "^0.0.7",
+    "@storybook/addon-docs": "^7.6.17",
+    "@storybook/addon-essentials": "^7.6.17",
+    "@storybook/addon-interactions": "^7.6.17",
+    "@storybook/addon-links": "^7.6.17",
+    "@storybook/addon-storysource": "^7.6.17",
+    "@storybook/blocks": "^7.6.17",
+    "@storybook/manager-api": "^7.6.17",
+    "@storybook/react": "^7.6.17",
+    "@storybook/react-vite": "^7.6.17",
+    "@storybook/test": "^7.6.17",
+    "@storybook/theming": "^7.6.17",
     "@types/dateformat": "^5.0.2",
     "@types/lodash-es": "^4.17.12",
-    "@types/node": "^20.11.5",
-    "@types/react": "^18.2.48",
-    "@types/react-dom": "^18.2.18",
-    "@types/uuid": "^9.0.7",
-    "@typescript-eslint/eslint-plugin": "^6.19.0",
-    "@typescript-eslint/parser": "^6.19.0",
-    "@vitejs/plugin-react-swc": "^3.5.0",
+    "@types/node": "^20.11.19",
+    "@types/react": "^18.2.57",
+    "@types/react-dom": "^18.2.19",
+    "@types/uuid": "^9.0.8",
+    "@vitejs/plugin-react-swc": "^3.6.0",
     "concurrently": "^8.2.2",
     "eslint": "^8.56.0",
-    "eslint-config-prettier": "^9.1.0",
     "eslint-plugin-i18next": "^6.0.3",
-    "eslint-plugin-import": "^2.29.1",
     "eslint-plugin-path": "^1.2.4",
-    "eslint-plugin-react": "^7.33.2",
-    "eslint-plugin-react-hooks": "^4.6.0",
-    "eslint-plugin-simple-import-sort": "^10.0.0",
-    "eslint-plugin-storybook": "^0.6.15",
-    "eslint-plugin-unused-imports": "^3.0.0",
     "madge": "^6.1.0",
     "openapi-types": "^12.1.3",
-    "openapi-typescript": "^6.7.3",
-    "prettier": "^3.2.4",
+    "openapi-typescript": "^6.7.4",
+    "prettier": "^3.2.5",
     "rollup-plugin-visualizer": "^5.12.0",
-    "storybook": "^7.6.10",
+    "storybook": "^7.6.17",
     "ts-toolbelt": "^9.6.0",
     "tsafe": "^1.6.6",
     "typescript": "^5.3.3",
-    "vite": "^5.0.12",
-    "vite-plugin-css-injected-by-js": "^3.3.1",
-    "vite-plugin-dts": "^3.7.1",
+    "vite": "^5.1.3",
+    "vite-plugin-css-injected-by-js": "^3.4.0",
+    "vite-plugin-dts": "^3.7.2",
     "vite-plugin-eslint": "^1.8.1",
     "vite-tsconfig-paths": "^4.3.1",
-    "vitest": "^1.2.2"
-  },
-  "pnpm": {
-    "patchedDependencies": {
-      "reselect@5.0.1": "patches/reselect@5.0.1.patch"
-    }
+    "vitest": "^1.3.1"
   }
 }
diff --git a/invokeai/frontend/web/pnpm-lock.yaml b/invokeai/frontend/web/pnpm-lock.yaml
index 4f9902299c..9e873102e6 100644
--- a/invokeai/frontend/web/pnpm-lock.yaml
+++ b/invokeai/frontend/web/pnpm-lock.yaml
@@ -4,15 +4,10 @@ settings:
   autoInstallPeers: true
   excludeLinksFromLockfile: false
 
-patchedDependencies:
-  reselect@5.0.1:
-    hash: kvbgwzjyy4x4fnh7znyocvb75q
-    path: patches/reselect@5.0.1.patch
-
 dependencies:
   '@chakra-ui/react':
     specifier: ^2.8.2
-    version: 2.8.2(@emotion/react@11.11.3)(@emotion/styled@11.11.0)(@types/react@18.2.48)(framer-motion@10.18.0)(react-dom@18.2.0)(react@18.2.0)
+    version: 2.8.2(@emotion/react@11.11.3)(@emotion/styled@11.11.0)(@types/react@18.2.57)(framer-motion@11.0.5)(react-dom@18.2.0)(react@18.2.0)
   '@chakra-ui/react-use-size':
     specifier: ^2.1.0
     version: 2.1.0(react@18.2.0)
@@ -33,22 +28,22 @@ dependencies:
     version: 5.0.16
   '@invoke-ai/ui-library':
     specifier: ^0.0.21
-    version: 0.0.21(@chakra-ui/form-control@2.2.0)(@chakra-ui/icon@3.2.0)(@chakra-ui/media-query@3.3.0)(@chakra-ui/menu@2.2.1)(@chakra-ui/spinner@2.1.0)(@chakra-ui/system@2.6.2)(@fontsource-variable/inter@5.0.16)(@internationalized/date@3.5.2)(@types/react@18.2.48)(i18next@23.7.16)(react-dom@18.2.0)(react@18.2.0)
+    version: 0.0.21(@chakra-ui/form-control@2.2.0)(@chakra-ui/icon@3.2.0)(@chakra-ui/media-query@3.3.0)(@chakra-ui/menu@2.2.1)(@chakra-ui/spinner@2.1.0)(@chakra-ui/system@2.6.2)(@fontsource-variable/inter@5.0.16)(@internationalized/date@3.5.2)(@types/react@18.2.57)(i18next@23.9.0)(react-dom@18.2.0)(react@18.2.0)
   '@mantine/form':
     specifier: 6.0.21
     version: 6.0.21(react@18.2.0)
   '@nanostores/react':
-    specifier: ^0.7.1
-    version: 0.7.1(nanostores@0.9.5)(react@18.2.0)
+    specifier: ^0.7.2
+    version: 0.7.2(nanostores@0.10.0)(react@18.2.0)
   '@reduxjs/toolkit':
-    specifier: 2.0.1
-    version: 2.0.1(react-redux@9.1.0)(react@18.2.0)
+    specifier: 2.2.1
+    version: 2.2.1(react-redux@9.1.0)(react@18.2.0)
   '@roarr/browser-log-writer':
     specifier: ^1.3.0
     version: 1.3.0
   chakra-react-select:
     specifier: ^4.7.6
-    version: 4.7.6(@chakra-ui/form-control@2.2.0)(@chakra-ui/icon@3.2.0)(@chakra-ui/layout@2.3.1)(@chakra-ui/media-query@3.3.0)(@chakra-ui/menu@2.2.1)(@chakra-ui/spinner@2.1.0)(@chakra-ui/system@2.6.2)(@emotion/react@11.11.3)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
+    version: 4.7.6(@chakra-ui/form-control@2.2.0)(@chakra-ui/icon@3.2.0)(@chakra-ui/layout@2.3.1)(@chakra-ui/media-query@3.3.0)(@chakra-ui/menu@2.2.1)(@chakra-ui/spinner@2.1.0)(@chakra-ui/system@2.6.2)(@emotion/react@11.11.3)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
   compare-versions:
     specifier: ^6.1.0
     version: 6.1.0
@@ -56,14 +51,14 @@ dependencies:
     specifier: ^5.0.3
     version: 5.0.3
   framer-motion:
-    specifier: ^10.18.0
-    version: 10.18.0(react-dom@18.2.0)(react@18.2.0)
+    specifier: ^11.0.5
+    version: 11.0.5(react-dom@18.2.0)(react@18.2.0)
   i18next:
-    specifier: ^23.7.16
-    version: 23.7.16
+    specifier: ^23.9.0
+    version: 23.9.0
   i18next-http-backend:
-    specifier: ^2.4.2
-    version: 2.4.2
+    specifier: ^2.4.3
+    version: 2.4.3
   idb-keyval:
     specifier: ^6.2.1
     version: 6.2.1
@@ -71,26 +66,26 @@ dependencies:
     specifier: ^0.6.0
     version: 0.6.0
   konva:
-    specifier: ^9.3.1
-    version: 9.3.1
+    specifier: ^9.3.3
+    version: 9.3.3
   lodash-es:
     specifier: ^4.17.21
     version: 4.17.21
   nanostores:
-    specifier: ^0.9.5
-    version: 0.9.5
+    specifier: ^0.10.0
+    version: 0.10.0
   new-github-issue-url:
     specifier: ^1.0.0
     version: 1.0.0
   overlayscrollbars:
-    specifier: ^2.4.6
-    version: 2.4.6
+    specifier: ^2.5.0
+    version: 2.5.0
   overlayscrollbars-react:
-    specifier: ^0.5.3
-    version: 0.5.3(overlayscrollbars@2.4.6)(react@18.2.0)
+    specifier: ^0.5.4
+    version: 0.5.4(overlayscrollbars@2.5.0)(react@18.2.0)
   query-string:
-    specifier: ^8.1.0
-    version: 8.1.0
+    specifier: ^8.2.0
+    version: 8.2.0
   react:
     specifier: ^18.2.0
     version: 18.2.0
@@ -107,41 +102,41 @@ dependencies:
     specifier: ^4.0.12
     version: 4.0.12(react@18.2.0)
   react-hook-form:
-    specifier: ^7.49.3
-    version: 7.49.3(react@18.2.0)
+    specifier: ^7.50.1
+    version: 7.50.1(react@18.2.0)
   react-hotkeys-hook:
-    specifier: 4.4.4
-    version: 4.4.4(react-dom@18.2.0)(react@18.2.0)
+    specifier: 4.5.0
+    version: 4.5.0(react-dom@18.2.0)(react@18.2.0)
   react-i18next:
-    specifier: ^14.0.0
-    version: 14.0.0(i18next@23.7.16)(react-dom@18.2.0)(react@18.2.0)
+    specifier: ^14.0.5
+    version: 14.0.5(i18next@23.9.0)(react-dom@18.2.0)(react@18.2.0)
   react-icons:
     specifier: ^5.0.1
     version: 5.0.1(react@18.2.0)
   react-konva:
     specifier: ^18.2.10
-    version: 18.2.10(konva@9.3.1)(react-dom@18.2.0)(react@18.2.0)
+    version: 18.2.10(konva@9.3.3)(react-dom@18.2.0)(react@18.2.0)
   react-redux:
     specifier: 9.1.0
-    version: 9.1.0(@types/react@18.2.48)(react@18.2.0)(redux@5.0.1)
+    version: 9.1.0(@types/react@18.2.57)(react@18.2.0)(redux@5.0.1)
   react-resizable-panels:
-    specifier: ^1.0.9
-    version: 1.0.9(react-dom@18.2.0)(react@18.2.0)
+    specifier: ^2.0.9
+    version: 2.0.9(react-dom@18.2.0)(react@18.2.0)
   react-select:
     specifier: 5.8.0
-    version: 5.8.0(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
+    version: 5.8.0(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
   react-textarea-autosize:
     specifier: ^8.5.3
-    version: 8.5.3(@types/react@18.2.48)(react@18.2.0)
+    version: 8.5.3(@types/react@18.2.57)(react@18.2.0)
   react-use:
-    specifier: ^17.4.3
-    version: 17.4.3(react-dom@18.2.0)(react@18.2.0)
+    specifier: ^17.5.0
+    version: 17.5.0(react-dom@18.2.0)(react@18.2.0)
   react-virtuoso:
-    specifier: ^4.6.2
-    version: 4.6.2(react-dom@18.2.0)(react@18.2.0)
+    specifier: ^4.7.0
+    version: 4.7.0(react-dom@18.2.0)(react@18.2.0)
   reactflow:
-    specifier: ^11.10.2
-    version: 11.10.2(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
+    specifier: ^11.10.4
+    version: 11.10.4(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
   redux-dynamic-middlewares:
     specifier: ^2.2.0
     version: 2.2.0
@@ -158,8 +153,8 @@ dependencies:
     specifier: ^4.7.4
     version: 4.7.4
   type-fest:
-    specifier: ^4.9.0
-    version: 4.9.0
+    specifier: ^4.10.2
+    version: 4.10.2
   use-debounce:
     specifier: ^10.0.0
     version: 10.0.0(react@18.2.0)
@@ -173,52 +168,49 @@ dependencies:
     specifier: ^3.22.4
     version: 3.22.4
   zod-validation-error:
-    specifier: ^3.0.0
-    version: 3.0.0(zod@3.22.4)
+    specifier: ^3.0.2
+    version: 3.0.2(zod@3.22.4)
 
 devDependencies:
-  '@arthurgeron/eslint-plugin-react-usememo':
-    specifier: ^2.2.3
-    version: 2.2.3
   '@invoke-ai/eslint-config-react':
-    specifier: ^0.0.13
-    version: 0.0.13(@typescript-eslint/eslint-plugin@6.19.0)(@typescript-eslint/parser@6.19.0)(eslint-config-prettier@9.1.0)(eslint-plugin-import@2.29.1)(eslint-plugin-react-hooks@4.6.0)(eslint-plugin-react-refresh@0.4.5)(eslint-plugin-react@7.33.2)(eslint-plugin-simple-import-sort@10.0.0)(eslint-plugin-storybook@0.6.15)(eslint-plugin-unused-imports@3.0.0)(eslint@8.56.0)
+    specifier: ^0.0.14
+    version: 0.0.14(eslint@8.56.0)(prettier@3.2.5)(typescript@5.3.3)
   '@invoke-ai/prettier-config-react':
-    specifier: ^0.0.6
-    version: 0.0.6(prettier@3.2.4)
+    specifier: ^0.0.7
+    version: 0.0.7(prettier@3.2.5)
   '@storybook/addon-docs':
-    specifier: ^7.6.10
-    version: 7.6.10(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
+    specifier: ^7.6.17
+    version: 7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
   '@storybook/addon-essentials':
-    specifier: ^7.6.10
-    version: 7.6.10(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
+    specifier: ^7.6.17
+    version: 7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
   '@storybook/addon-interactions':
-    specifier: ^7.6.10
-    version: 7.6.10
+    specifier: ^7.6.17
+    version: 7.6.17
   '@storybook/addon-links':
-    specifier: ^7.6.10
-    version: 7.6.10(react@18.2.0)
+    specifier: ^7.6.17
+    version: 7.6.17(react@18.2.0)
   '@storybook/addon-storysource':
-    specifier: ^7.6.10
-    version: 7.6.10
+    specifier: ^7.6.17
+    version: 7.6.17
   '@storybook/blocks':
-    specifier: ^7.6.10
-    version: 7.6.10(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
+    specifier: ^7.6.17
+    version: 7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
   '@storybook/manager-api':
-    specifier: ^7.6.10
-    version: 7.6.10(react-dom@18.2.0)(react@18.2.0)
+    specifier: ^7.6.17
+    version: 7.6.17(react-dom@18.2.0)(react@18.2.0)
   '@storybook/react':
-    specifier: ^7.6.10
-    version: 7.6.10(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)
+    specifier: ^7.6.17
+    version: 7.6.17(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)
   '@storybook/react-vite':
-    specifier: ^7.6.10
-    version: 7.6.10(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)(vite@5.0.12)
+    specifier: ^7.6.17
+    version: 7.6.17(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)(vite@5.1.3)
   '@storybook/test':
-    specifier: ^7.6.10
-    version: 7.6.10(vitest@1.2.2)
+    specifier: ^7.6.17
+    version: 7.6.17(vitest@1.3.1)
   '@storybook/theming':
-    specifier: ^7.6.10
-    version: 7.6.10(react-dom@18.2.0)(react@18.2.0)
+    specifier: ^7.6.17
+    version: 7.6.17(react-dom@18.2.0)(react@18.2.0)
   '@types/dateformat':
     specifier: ^5.0.2
     version: 5.0.2
@@ -226,59 +218,32 @@ devDependencies:
     specifier: ^4.17.12
     version: 4.17.12
   '@types/node':
-    specifier: ^20.11.5
-    version: 20.11.5
+    specifier: ^20.11.19
+    version: 20.11.19
   '@types/react':
-    specifier: ^18.2.48
-    version: 18.2.48
+    specifier: ^18.2.57
+    version: 18.2.57
   '@types/react-dom':
-    specifier: ^18.2.18
-    version: 18.2.18
+    specifier: ^18.2.19
+    version: 18.2.19
   '@types/uuid':
-    specifier: ^9.0.7
-    version: 9.0.7
-  '@typescript-eslint/eslint-plugin':
-    specifier: ^6.19.0
-    version: 6.19.0(@typescript-eslint/parser@6.19.0)(eslint@8.56.0)(typescript@5.3.3)
-  '@typescript-eslint/parser':
-    specifier: ^6.19.0
-    version: 6.19.0(eslint@8.56.0)(typescript@5.3.3)
+    specifier: ^9.0.8
+    version: 9.0.8
   '@vitejs/plugin-react-swc':
-    specifier: ^3.5.0
-    version: 3.5.0(vite@5.0.12)
+    specifier: ^3.6.0
+    version: 3.6.0(vite@5.1.3)
   concurrently:
     specifier: ^8.2.2
     version: 8.2.2
   eslint:
     specifier: ^8.56.0
     version: 8.56.0
-  eslint-config-prettier:
-    specifier: ^9.1.0
-    version: 9.1.0(eslint@8.56.0)
   eslint-plugin-i18next:
     specifier: ^6.0.3
     version: 6.0.3
-  eslint-plugin-import:
-    specifier: ^2.29.1
-    version: 2.29.1(@typescript-eslint/parser@6.19.0)(eslint@8.56.0)
   eslint-plugin-path:
     specifier: ^1.2.4
     version: 1.2.4(eslint@8.56.0)
-  eslint-plugin-react:
-    specifier: ^7.33.2
-    version: 7.33.2(eslint@8.56.0)
-  eslint-plugin-react-hooks:
-    specifier: ^4.6.0
-    version: 4.6.0(eslint@8.56.0)
-  eslint-plugin-simple-import-sort:
-    specifier: ^10.0.0
-    version: 10.0.0(eslint@8.56.0)
-  eslint-plugin-storybook:
-    specifier: ^0.6.15
-    version: 0.6.15(eslint@8.56.0)(typescript@5.3.3)
-  eslint-plugin-unused-imports:
-    specifier: ^3.0.0
-    version: 3.0.0(@typescript-eslint/eslint-plugin@6.19.0)(eslint@8.56.0)
   madge:
     specifier: ^6.1.0
     version: 6.1.0(typescript@5.3.3)
@@ -286,17 +251,17 @@ devDependencies:
     specifier: ^12.1.3
     version: 12.1.3
   openapi-typescript:
-    specifier: ^6.7.3
-    version: 6.7.3
+    specifier: ^6.7.4
+    version: 6.7.4
   prettier:
-    specifier: ^3.2.4
-    version: 3.2.4
+    specifier: ^3.2.5
+    version: 3.2.5
   rollup-plugin-visualizer:
     specifier: ^5.12.0
     version: 5.12.0
   storybook:
-    specifier: ^7.6.10
-    version: 7.6.10
+    specifier: ^7.6.17
+    version: 7.6.17
   ts-toolbelt:
     specifier: ^9.6.0
     version: 9.6.0
@@ -307,23 +272,23 @@ devDependencies:
     specifier: ^5.3.3
     version: 5.3.3
   vite:
-    specifier: ^5.0.12
-    version: 5.0.12(@types/node@20.11.5)
+    specifier: ^5.1.3
+    version: 5.1.3(@types/node@20.11.19)
   vite-plugin-css-injected-by-js:
-    specifier: ^3.3.1
-    version: 3.3.1(vite@5.0.12)
+    specifier: ^3.4.0
+    version: 3.4.0(vite@5.1.3)
   vite-plugin-dts:
-    specifier: ^3.7.1
-    version: 3.7.1(@types/node@20.11.5)(typescript@5.3.3)(vite@5.0.12)
+    specifier: ^3.7.2
+    version: 3.7.2(@types/node@20.11.19)(typescript@5.3.3)(vite@5.1.3)
   vite-plugin-eslint:
     specifier: ^1.8.1
-    version: 1.8.1(eslint@8.56.0)(vite@5.0.12)
+    version: 1.8.1(eslint@8.56.0)(vite@5.1.3)
   vite-tsconfig-paths:
     specifier: ^4.3.1
-    version: 4.3.1(typescript@5.3.3)(vite@5.0.12)
+    version: 4.3.1(typescript@5.3.3)(vite@5.1.3)
   vitest:
-    specifier: ^1.2.2
-    version: 1.2.2(@types/node@20.11.5)
+    specifier: ^1.3.1
+    version: 1.3.1(@types/node@20.11.19)
 
 packages:
 
@@ -332,8 +297,8 @@ packages:
     engines: {node: '>=0.10.0'}
     dev: true
 
-  /@adobe/css-tools@4.3.2:
-    resolution: {integrity: sha512-DA5a1C0gD/pLOvhv33YMrbf2FK3oUzwNl9oOJqE4XVjuEtt6XIakRcsd7eLiOSPkp1kTRQGICTA8cKra/vFbjw==}
+  /@adobe/css-tools@4.3.3:
+    resolution: {integrity: sha512-rE0Pygv0sEZ4vBWHlAgJLGDU7Pm8xoO6p3wsEceb7GYAjScrOHpEo8KK/eVkAcnSM+slAEtXjA2JpdjLp4fJQQ==}
     dev: true
 
   /@ampproject/remapping@2.2.1:
@@ -341,7 +306,7 @@ packages:
     engines: {node: '>=6.0.0'}
     dependencies:
       '@jridgewell/gen-mapping': 0.3.3
-      '@jridgewell/trace-mapping': 0.3.21
+      '@jridgewell/trace-mapping': 0.3.22
     dev: true
 
   /@ark-ui/anatomy@1.3.0(@internationalized/date@3.5.2):
@@ -430,13 +395,6 @@ packages:
       - '@internationalized/date'
     dev: false
 
-  /@arthurgeron/eslint-plugin-react-usememo@2.2.3:
-    resolution: {integrity: sha512-YJG+8hULmhHAxztaANswpa9hWNqEOSvbZcbd6R/JQzyNlEZ49Xh97kqZGuJGZ74rrmULckEO1m3Jh5ctqrGA2A==}
-    dependencies:
-      minimatch: 9.0.3
-      uuid: 9.0.1
-    dev: true
-
   /@aw-web-design/x-default-browser@1.4.126:
     resolution: {integrity: sha512-Xk1sIhyNC/esHGGVjL/niHLowM0csl/kFO5uawBy4IrWwy0o1G8LGt3jP6nmWGz+USxeeqbihAmp/oVZju6wug==}
     hasBin: true
@@ -456,20 +414,20 @@ packages:
     engines: {node: '>=6.9.0'}
     dev: true
 
-  /@babel/core@7.23.7:
-    resolution: {integrity: sha512-+UpDgowcmqe36d4NwqvKsyPMlOLNGMsfMmQ5WGCu+siCe3t3dfe9njrzGfdN4qq+bcNUt0+Vw6haRxBOycs4dw==}
+  /@babel/core@7.23.9:
+    resolution: {integrity: sha512-5q0175NOjddqpvvzU+kDiSOAk4PfdO6FvwCWoQ6RO7rTzEe8vlo+4HVfcnAREhD4npMs0e9uZypjTwzZPCf/cw==}
     engines: {node: '>=6.9.0'}
     dependencies:
       '@ampproject/remapping': 2.2.1
       '@babel/code-frame': 7.23.5
       '@babel/generator': 7.23.6
       '@babel/helper-compilation-targets': 7.23.6
-      '@babel/helper-module-transforms': 7.23.3(@babel/core@7.23.7)
-      '@babel/helpers': 7.23.8
-      '@babel/parser': 7.23.6
-      '@babel/template': 7.22.15
-      '@babel/traverse': 7.23.7
-      '@babel/types': 7.23.6
+      '@babel/helper-module-transforms': 7.23.3(@babel/core@7.23.9)
+      '@babel/helpers': 7.23.9
+      '@babel/parser': 7.23.9
+      '@babel/template': 7.23.9
+      '@babel/traverse': 7.23.9
+      '@babel/types': 7.23.9
       convert-source-map: 2.0.0
       debug: 4.3.4
       gensync: 1.0.0-beta.2
@@ -483,9 +441,9 @@ packages:
     resolution: {integrity: sha512-qrSfCYxYQB5owCmGLbl8XRpX1ytXlpueOb0N0UmQwA073KZxejgQTzAmJezxvpwQD9uGtK2shHdi55QT+MbjIw==}
     engines: {node: '>=6.9.0'}
     dependencies:
-      '@babel/types': 7.23.6
+      '@babel/types': 7.23.9
       '@jridgewell/gen-mapping': 0.3.3
-      '@jridgewell/trace-mapping': 0.3.21
+      '@jridgewell/trace-mapping': 0.3.22
       jsesc: 2.5.2
     dev: true
 
@@ -493,14 +451,14 @@ packages:
     resolution: {integrity: sha512-LvBTxu8bQSQkcyKOU+a1btnNFQ1dMAd0R6PyW3arXes06F6QLWLIrd681bxRPIXlrMGR3XYnW9JyML7dP3qgxg==}
     engines: {node: '>=6.9.0'}
     dependencies:
-      '@babel/types': 7.23.6
+      '@babel/types': 7.23.9
     dev: true
 
   /@babel/helper-builder-binary-assignment-operator-visitor@7.22.15:
     resolution: {integrity: sha512-QkBXwGgaoC2GtGZRoma6kv7Szfv06khvhFav67ZExau2RaXzy8MpHSMO2PNoP2XtmQphJQRHFfg77Bq731Yizw==}
     engines: {node: '>=6.9.0'}
     dependencies:
-      '@babel/types': 7.23.6
+      '@babel/types': 7.23.9
     dev: true
 
   /@babel/helper-compilation-targets@7.23.6:
@@ -509,62 +467,47 @@ packages:
     dependencies:
       '@babel/compat-data': 7.23.5
       '@babel/helper-validator-option': 7.23.5
-      browserslist: 4.22.2
+      browserslist: 4.23.0
       lru-cache: 5.1.1
       semver: 6.3.1
     dev: true
 
-  /@babel/helper-create-class-features-plugin@7.23.7(@babel/core@7.23.7):
-    resolution: {integrity: sha512-xCoqR/8+BoNnXOY7RVSgv6X+o7pmT5q1d+gGcRlXYkI+9B31glE4jeejhKVpA04O1AtzOt7OSQ6VYKP5FcRl9g==}
+  /@babel/helper-create-class-features-plugin@7.23.10(@babel/core@7.23.9):
+    resolution: {integrity: sha512-2XpP2XhkXzgxecPNEEK8Vz8Asj9aRxt08oKOqtiZoqV2UGZ5T+EkyP9sXQ9nwMxBIG34a7jmasVqoMop7VdPUw==}
     engines: {node: '>=6.9.0'}
     peerDependencies:
       '@babel/core': ^7.0.0
     dependencies:
-      '@babel/core': 7.23.7
+      '@babel/core': 7.23.9
       '@babel/helper-annotate-as-pure': 7.22.5
       '@babel/helper-environment-visitor': 7.22.20
       '@babel/helper-function-name': 7.23.0
       '@babel/helper-member-expression-to-functions': 7.23.0
       '@babel/helper-optimise-call-expression': 7.22.5
-      '@babel/helper-replace-supers': 7.22.20(@babel/core@7.23.7)
+      '@babel/helper-replace-supers': 7.22.20(@babel/core@7.23.9)
       '@babel/helper-skip-transparent-expression-wrappers': 7.22.5
       '@babel/helper-split-export-declaration': 7.22.6
       semver: 6.3.1
     dev: true
 
-  /@babel/helper-create-regexp-features-plugin@7.22.15(@babel/core@7.23.7):
+  /@babel/helper-create-regexp-features-plugin@7.22.15(@babel/core@7.23.9):
     resolution: {integrity: sha512-29FkPLFjn4TPEa3RE7GpW+qbE8tlsu3jntNYNfcGsc49LphF1PQIiD+vMZ1z1xVOKt+93khA9tc2JBs3kBjA7w==}
     engines: {node: '>=6.9.0'}
     peerDependencies:
       '@babel/core': ^7.0.0
     dependencies:
-      '@babel/core': 7.23.7
+      '@babel/core': 7.23.9
       '@babel/helper-annotate-as-pure': 7.22.5
       regexpu-core: 5.3.2
       semver: 6.3.1
     dev: true
 
-  /@babel/helper-define-polyfill-provider@0.4.4(@babel/core@7.23.7):
-    resolution: {integrity: sha512-QcJMILQCu2jm5TFPGA3lCpJJTeEP+mqeXooG/NZbg/h5FTFi6V0+99ahlRsW8/kRLyb24LZVCCiclDedhLKcBA==}
-    peerDependencies:
-      '@babel/core': ^7.4.0 || ^8.0.0-0 <8.0.0
-    dependencies:
-      '@babel/core': 7.23.7
-      '@babel/helper-compilation-targets': 7.23.6
-      '@babel/helper-plugin-utils': 7.22.5
-      debug: 4.3.4
-      lodash.debounce: 4.0.8
-      resolve: 1.22.8
-    transitivePeerDependencies:
-      - supports-color
-    dev: true
-
-  /@babel/helper-define-polyfill-provider@0.5.0(@babel/core@7.23.7):
+  /@babel/helper-define-polyfill-provider@0.5.0(@babel/core@7.23.9):
     resolution: {integrity: sha512-NovQquuQLAQ5HuyjCz7WQP9MjRj7dx++yspwiyUiGl9ZyadHRSql1HZh5ogRd8W8w6YM6EQ/NTB8rgjLt5W65Q==}
     peerDependencies:
       '@babel/core': ^7.4.0 || ^8.0.0-0 <8.0.0
     dependencies:
-      '@babel/core': 7.23.7
+      '@babel/core': 7.23.9
       '@babel/helper-compilation-targets': 7.23.6
       '@babel/helper-plugin-utils': 7.22.5
       debug: 4.3.4
@@ -583,37 +526,37 @@ packages:
     resolution: {integrity: sha512-OErEqsrxjZTJciZ4Oo+eoZqeW9UIiOcuYKRJA4ZAgV9myA+pOXhhmpfNCKjEH/auVfEYVFJ6y1Tc4r0eIApqiw==}
     engines: {node: '>=6.9.0'}
     dependencies:
-      '@babel/template': 7.22.15
-      '@babel/types': 7.23.6
+      '@babel/template': 7.23.9
+      '@babel/types': 7.23.9
     dev: true
 
   /@babel/helper-hoist-variables@7.22.5:
     resolution: {integrity: sha512-wGjk9QZVzvknA6yKIUURb8zY3grXCcOZt+/7Wcy8O2uctxhplmUPkOdlgoNhmdVee2c92JXbf1xpMtVNbfoxRw==}
     engines: {node: '>=6.9.0'}
     dependencies:
-      '@babel/types': 7.23.6
+      '@babel/types': 7.23.9
     dev: true
 
   /@babel/helper-member-expression-to-functions@7.23.0:
     resolution: {integrity: sha512-6gfrPwh7OuT6gZyJZvd6WbTfrqAo7vm4xCzAXOusKqq/vWdKXphTpj5klHKNmRUU6/QRGlBsyU9mAIPaWHlqJA==}
     engines: {node: '>=6.9.0'}
     dependencies:
-      '@babel/types': 7.23.6
+      '@babel/types': 7.23.9
     dev: true
 
   /@babel/helper-module-imports@7.22.15:
     resolution: {integrity: sha512-0pYVBnDKZO2fnSPCrgM/6WMc7eS20Fbok+0r88fp+YtWVLZrp4CkafFGIp+W0VKw4a22sgebPT99y+FDNMdP4w==}
     engines: {node: '>=6.9.0'}
     dependencies:
-      '@babel/types': 7.23.6
+      '@babel/types': 7.23.9
 
-  /@babel/helper-module-transforms@7.23.3(@babel/core@7.23.7):
+  /@babel/helper-module-transforms@7.23.3(@babel/core@7.23.9):
     resolution: {integrity: sha512-7bBs4ED9OmswdfDzpz4MpWgSrV7FXlc3zIagvLFjS5H+Mk7Snr21vQ6QwrsoCGMfNC4e4LQPdoULEt4ykz0SRQ==}
     engines: {node: '>=6.9.0'}
     peerDependencies:
       '@babel/core': ^7.0.0
     dependencies:
-      '@babel/core': 7.23.7
+      '@babel/core': 7.23.9
       '@babel/helper-environment-visitor': 7.22.20
       '@babel/helper-module-imports': 7.22.15
       '@babel/helper-simple-access': 7.22.5
@@ -625,7 +568,7 @@ packages:
     resolution: {integrity: sha512-HBwaojN0xFRx4yIvpwGqxiV2tUfl7401jlok564NgB9EHS1y6QT17FmKWm4ztqjeVdXLuC4fSvHc5ePpQjoTbw==}
     engines: {node: '>=6.9.0'}
     dependencies:
-      '@babel/types': 7.23.6
+      '@babel/types': 7.23.9
     dev: true
 
   /@babel/helper-plugin-utils@7.22.5:
@@ -633,25 +576,25 @@ packages:
     engines: {node: '>=6.9.0'}
     dev: true
 
-  /@babel/helper-remap-async-to-generator@7.22.20(@babel/core@7.23.7):
+  /@babel/helper-remap-async-to-generator@7.22.20(@babel/core@7.23.9):
     resolution: {integrity: sha512-pBGyV4uBqOns+0UvhsTO8qgl8hO89PmiDYv+/COyp1aeMcmfrfruz+/nCMFiYyFF/Knn0yfrC85ZzNFjembFTw==}
     engines: {node: '>=6.9.0'}
     peerDependencies:
       '@babel/core': ^7.0.0
     dependencies:
-      '@babel/core': 7.23.7
+      '@babel/core': 7.23.9
       '@babel/helper-annotate-as-pure': 7.22.5
       '@babel/helper-environment-visitor': 7.22.20
       '@babel/helper-wrap-function': 7.22.20
     dev: true
 
-  /@babel/helper-replace-supers@7.22.20(@babel/core@7.23.7):
+  /@babel/helper-replace-supers@7.22.20(@babel/core@7.23.9):
     resolution: {integrity: sha512-qsW0In3dbwQUbK8kejJ4R7IHVGwHJlV6lpG6UA7a9hSa2YEiAib+N1T2kr6PEeUT+Fl7najmSOS6SmAwCHK6Tw==}
     engines: {node: '>=6.9.0'}
     peerDependencies:
       '@babel/core': ^7.0.0
     dependencies:
-      '@babel/core': 7.23.7
+      '@babel/core': 7.23.9
       '@babel/helper-environment-visitor': 7.22.20
       '@babel/helper-member-expression-to-functions': 7.23.0
       '@babel/helper-optimise-call-expression': 7.22.5
@@ -661,21 +604,21 @@ packages:
     resolution: {integrity: sha512-n0H99E/K+Bika3++WNL17POvo4rKWZ7lZEp1Q+fStVbUi8nxPQEBOlTmCOxW/0JsS56SKKQ+ojAe2pHKJHN35w==}
     engines: {node: '>=6.9.0'}
     dependencies:
-      '@babel/types': 7.23.6
+      '@babel/types': 7.23.9
     dev: true
 
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     engines: {node: '>=6.9.0'}
     dependencies:
-      '@babel/types': 7.23.6
+      '@babel/types': 7.23.9
     dev: true
 
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+      '@babel/types': 7.23.9
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-      '@babel/template': 7.22.15
-      '@babel/types': 7.23.6
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+  /@babel/helpers@7.23.9:
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     dependencies:
-      '@babel/template': 7.22.15
-      '@babel/traverse': 7.23.7
-      '@babel/types': 7.23.6
+      '@babel/template': 7.23.9
+      '@babel/traverse': 7.23.9
+      '@babel/types': 7.23.9
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       - supports-color
     dev: true
@@ -719,966 +662,966 @@ packages:
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+      '@babel/types': 7.23.9
     dev: true
 
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     dev: true
 
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+      '@babel/plugin-transform-spread': 7.23.3(@babel/core@7.23.9)
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+      '@babel/plugin-transform-template-literals': 7.23.3(@babel/core@7.23.9)
+      '@babel/plugin-transform-typeof-symbol': 7.23.3(@babel/core@7.23.9)
+      '@babel/plugin-transform-unicode-escapes': 7.23.3(@babel/core@7.23.9)
+      '@babel/plugin-transform-unicode-property-regex': 7.23.3(@babel/core@7.23.9)
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+      '@babel/plugin-transform-unicode-sets-regex': 7.23.3(@babel/core@7.23.9)
+      '@babel/preset-modules': 0.1.6-no-external-plugins(@babel/core@7.23.9)
+      babel-plugin-polyfill-corejs2: 0.4.8(@babel/core@7.23.9)
+      babel-plugin-polyfill-corejs3: 0.9.0(@babel/core@7.23.9)
+      babel-plugin-polyfill-regenerator: 0.5.5(@babel/core@7.23.9)
+      core-js-compat: 3.36.0
       semver: 6.3.1
     transitivePeerDependencies:
       - supports-color
     dev: true
 
-  /@babel/preset-flow@7.23.3(@babel/core@7.23.7):
+  /@babel/preset-flow@7.23.3(@babel/core@7.23.9):
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+      '@babel/core': 7.23.9
       '@babel/helper-plugin-utils': 7.22.5
       '@babel/helper-validator-option': 7.23.5
-      '@babel/plugin-transform-flow-strip-types': 7.23.3(@babel/core@7.23.7)
+      '@babel/plugin-transform-flow-strip-types': 7.23.3(@babel/core@7.23.9)
     dev: true
 
-  /@babel/preset-modules@0.1.6-no-external-plugins(@babel/core@7.23.7):
+  /@babel/preset-modules@0.1.6-no-external-plugins(@babel/core@7.23.9):
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     peerDependencies:
       '@babel/core': ^7.0.0-0 || ^8.0.0-0 <8.0.0
     dependencies:
-      '@babel/core': 7.23.7
+      '@babel/core': 7.23.9
       '@babel/helper-plugin-utils': 7.22.5
-      '@babel/types': 7.23.6
+      '@babel/types': 7.23.9
       esutils: 2.0.3
     dev: true
 
-  /@babel/preset-typescript@7.23.3(@babel/core@7.23.7):
+  /@babel/preset-typescript@7.23.3(@babel/core@7.23.9):
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     engines: {node: '>=6.9.0'}
     peerDependencies:
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     dependencies:
-      '@babel/core': 7.23.7
+      '@babel/core': 7.23.9
       '@babel/helper-plugin-utils': 7.22.5
       '@babel/helper-validator-option': 7.23.5
-      '@babel/plugin-syntax-jsx': 7.23.3(@babel/core@7.23.7)
-      '@babel/plugin-transform-modules-commonjs': 7.23.3(@babel/core@7.23.7)
-      '@babel/plugin-transform-typescript': 7.23.6(@babel/core@7.23.7)
+      '@babel/plugin-syntax-jsx': 7.23.3(@babel/core@7.23.9)
+      '@babel/plugin-transform-modules-commonjs': 7.23.3(@babel/core@7.23.9)
+      '@babel/plugin-transform-typescript': 7.23.6(@babel/core@7.23.9)
     dev: true
 
-  /@babel/register@7.23.7(@babel/core@7.23.7):
+  /@babel/register@7.23.7(@babel/core@7.23.9):
     resolution: {integrity: sha512-EjJeB6+kvpk+Y5DAkEAmbOBEFkh9OASx0huoEkqYTFxAZHzOAX2Oh5uwAUuL2rUddqfM0SA+KPXV2TbzoZ2kvQ==}
     engines: {node: '>=6.9.0'}
     peerDependencies:
       '@babel/core': ^7.0.0-0
     dependencies:
-      '@babel/core': 7.23.7
+      '@babel/core': 7.23.9
       clone-deep: 4.0.1
       find-cache-dir: 2.1.0
       make-dir: 2.1.0
@@ -1690,43 +1633,23 @@ packages:
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     dev: true
 
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-    engines: {node: '>=6.9.0'}
-    dependencies:
-      regenerator-runtime: 0.14.1
-
-  /@babel/runtime@7.23.7:
-    resolution: {integrity: sha512-w06OXVOFso7LcbzMiDGt+3X7Rh7Ho8MmgPoWU3rarH+8upf+wSU/grlGbWzQyr3DkdN6ZeuMFjpdwW0Q+HxobA==}
-    engines: {node: '>=6.9.0'}
-    dependencies:
-      regenerator-runtime: 0.14.1
-    dev: false
-
-  /@babel/runtime@7.23.8:
-    resolution: {integrity: sha512-Y7KbAP984rn1VGMbGqKmBLio9V7y5Je9GvU4rQPCPinCyNfUcToxIXl06d59URp/F3LwinvODxab5N/G6qggkw==}
-    engines: {node: '>=6.9.0'}
-    dependencies:
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-
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     engines: {node: '>=6.9.0'}
     dependencies:
       regenerator-runtime: 0.14.1
-    dev: false
 
-  /@babel/template@7.22.15:
-    resolution: {integrity: sha512-QPErUVm4uyJa60rkI73qneDacvdvzxshT3kksGqlGWYdOTIUOwJ7RDUL8sGqslY1uXWSL6xMFKEXDS3ox2uF0w==}
+  /@babel/template@7.23.9:
+    resolution: {integrity: sha512-+xrD2BWLpvHKNmX2QbpdpsBaWnRxahMwJjO+KZk2JOElj5nSmKezyS1B4u+QbHMTX69t4ukm6hh9lsYQ7GHCKA==}
     engines: {node: '>=6.9.0'}
     dependencies:
       '@babel/code-frame': 7.23.5
-      '@babel/parser': 7.23.6
-      '@babel/types': 7.23.6
+      '@babel/parser': 7.23.9
+      '@babel/types': 7.23.9
     dev: true
 
-  /@babel/traverse@7.23.7:
-    resolution: {integrity: sha512-tY3mM8rH9jM0YHFGyfC0/xf+SB5eKUu7HPj7/k3fpi9dAlsMc5YbQvDi0Sh2QTPXqMhyaAtzAr807TIyfQrmyg==}
+  /@babel/traverse@7.23.9:
+    resolution: {integrity: sha512-I/4UJ9vs90OkBtY6iiiTORVMyIhJ4kAVmsKo9KFc8UOxMeUfi2hvtIBsET5u9GizXE6/GFSuKCTNfgCswuEjRg==}
     engines: {node: '>=6.9.0'}
     dependencies:
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@@ -1735,16 +1658,16 @@ packages:
       '@babel/helper-function-name': 7.23.0
       '@babel/helper-hoist-variables': 7.22.5
       '@babel/helper-split-export-declaration': 7.22.6
-      '@babel/parser': 7.23.6
-      '@babel/types': 7.23.6
+      '@babel/parser': 7.23.9
+      '@babel/types': 7.23.9
       debug: 4.3.4
       globals: 11.12.0
     transitivePeerDependencies:
       - supports-color
     dev: true
 
-  /@babel/types@7.23.6:
-    resolution: {integrity: sha512-+uarb83brBzPKN38NX1MkB6vb6+mwvR6amUulqAE7ccQw1pEl+bCia9TbdG1lsnFP7lZySvUn37CHyXQdfTwzg==}
+  /@babel/types@7.23.9:
+    resolution: {integrity: sha512-dQjSq/7HaSjRM43FFGnv5keM2HsxpmyV1PfaSVm0nzzjwwTmjOe6J4bC8e3+pTEIgHaHj+1ZlLThRJ2auc/w1Q==}
     engines: {node: '>=6.9.0'}
     dependencies:
       '@babel/helper-string-parser': 7.23.4
@@ -1774,6 +1697,25 @@ packages:
       react: 18.2.0
     dev: false
 
+  /@chakra-ui/accordion@2.3.1(@chakra-ui/system@2.6.2)(framer-motion@11.0.5)(react@18.2.0):
+    resolution: {integrity: sha512-FSXRm8iClFyU+gVaXisOSEw0/4Q+qZbFRiuhIAkVU6Boj0FxAMrlo9a8AV5TuF77rgaHytCdHk0Ng+cyUijrag==}
+    peerDependencies:
+      '@chakra-ui/system': '>=2.0.0'
+      framer-motion: '>=4.0.0'
+      react: '>=18'
+    dependencies:
+      '@chakra-ui/descendant': 3.1.0(react@18.2.0)
+      '@chakra-ui/icon': 3.2.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/react-context': 2.1.0(react@18.2.0)
+      '@chakra-ui/react-use-controllable-state': 2.1.0(react@18.2.0)
+      '@chakra-ui/react-use-merge-refs': 2.1.0(react@18.2.0)
+      '@chakra-ui/shared-utils': 2.0.5
+      '@chakra-ui/system': 2.6.2(@emotion/react@11.11.3)(@emotion/styled@11.11.0)(react@18.2.0)
+      '@chakra-ui/transition': 2.1.0(framer-motion@11.0.5)(react@18.2.0)
+      framer-motion: 11.0.5(react-dom@18.2.0)(react@18.2.0)
+      react: 18.2.0
+    dev: false
+
   /@chakra-ui/alert@2.2.2(@chakra-ui/system@2.6.2)(react@18.2.0):
     resolution: {integrity: sha512-jHg4LYMRNOJH830ViLuicjb3F+v6iriE/2G5T+Sd0Hna04nukNJ1MxUmBPE+vI22me2dIflfelu2v9wdB6Pojw==}
     peerDependencies:
@@ -1928,7 +1870,7 @@ packages:
       '@emotion/react': '>=10.0.35'
       react: '>=18'
     dependencies:
-      '@emotion/react': 11.11.3(@types/react@18.2.48)(react@18.2.0)
+      '@emotion/react': 11.11.3(@types/react@18.2.57)(react@18.2.0)
       react: 18.2.0
     dev: false
 
@@ -1969,14 +1911,14 @@ packages:
     resolution: {integrity: sha512-IGM/yGUHS+8TOQrZGpAKOJl/xGBrmRYJrmbHfUE7zrG3PpQyXvbLDP1M+RggkCFVgHlJi2wpYIf0QtQlU0XZfw==}
     dev: false
 
-  /@chakra-ui/focus-lock@2.1.0(@types/react@18.2.48)(react@18.2.0):
+  /@chakra-ui/focus-lock@2.1.0(@types/react@18.2.57)(react@18.2.0):
     resolution: {integrity: sha512-EmGx4PhWGjm4dpjRqM4Aa+rCWBxP+Rq8Uc/nAVnD4YVqkEhBkrPTpui2lnjsuxqNaZ24fIAZ10cF1hlpemte/w==}
     peerDependencies:
       react: '>=18'
     dependencies:
       '@chakra-ui/dom-utils': 2.1.0
       react: 18.2.0
-      react-focus-lock: 2.11.1(@types/react@18.2.48)(react@18.2.0)
+      react-focus-lock: 2.11.1(@types/react@18.2.57)(react@18.2.0)
     transitivePeerDependencies:
       - '@types/react'
     dev: false
@@ -2125,7 +2067,34 @@ packages:
       react: 18.2.0
     dev: false
 
-  /@chakra-ui/modal@2.3.1(@chakra-ui/system@2.6.2)(@types/react@18.2.48)(framer-motion@10.18.0)(react-dom@18.2.0)(react@18.2.0):
+  /@chakra-ui/menu@2.2.1(@chakra-ui/system@2.6.2)(framer-motion@11.0.5)(react@18.2.0):
+    resolution: {integrity: sha512-lJS7XEObzJxsOwWQh7yfG4H8FzFPRP5hVPN/CL+JzytEINCSBvsCDHrYPQGp7jzpCi8vnTqQQGQe0f8dwnXd2g==}
+    peerDependencies:
+      '@chakra-ui/system': '>=2.0.0'
+      framer-motion: '>=4.0.0'
+      react: '>=18'
+    dependencies:
+      '@chakra-ui/clickable': 2.1.0(react@18.2.0)
+      '@chakra-ui/descendant': 3.1.0(react@18.2.0)
+      '@chakra-ui/lazy-utils': 2.0.5
+      '@chakra-ui/popper': 3.1.0(react@18.2.0)
+      '@chakra-ui/react-children-utils': 2.0.6(react@18.2.0)
+      '@chakra-ui/react-context': 2.1.0(react@18.2.0)
+      '@chakra-ui/react-use-animation-state': 2.1.0(react@18.2.0)
+      '@chakra-ui/react-use-controllable-state': 2.1.0(react@18.2.0)
+      '@chakra-ui/react-use-disclosure': 2.1.0(react@18.2.0)
+      '@chakra-ui/react-use-focus-effect': 2.1.0(react@18.2.0)
+      '@chakra-ui/react-use-merge-refs': 2.1.0(react@18.2.0)
+      '@chakra-ui/react-use-outside-click': 2.2.0(react@18.2.0)
+      '@chakra-ui/react-use-update-effect': 2.1.0(react@18.2.0)
+      '@chakra-ui/shared-utils': 2.0.5
+      '@chakra-ui/system': 2.6.2(@emotion/react@11.11.3)(@emotion/styled@11.11.0)(react@18.2.0)
+      '@chakra-ui/transition': 2.1.0(framer-motion@11.0.5)(react@18.2.0)
+      framer-motion: 11.0.5(react-dom@18.2.0)(react@18.2.0)
+      react: 18.2.0
+    dev: false
+
+  /@chakra-ui/modal@2.3.1(@chakra-ui/system@2.6.2)(@types/react@18.2.57)(framer-motion@10.18.0)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-TQv1ZaiJMZN+rR9DK0snx/OPwmtaGH1HbZtlYt4W4s6CzyK541fxLRTjIXfEzIGpvNW+b6VFuFjbcR78p4DEoQ==}
     peerDependencies:
       '@chakra-ui/system': '>=2.0.0'
@@ -2134,7 +2103,7 @@ packages:
       react-dom: '>=18'
     dependencies:
       '@chakra-ui/close-button': 2.1.1(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/focus-lock': 2.1.0(@types/react@18.2.48)(react@18.2.0)
+      '@chakra-ui/focus-lock': 2.1.0(@types/react@18.2.57)(react@18.2.0)
       '@chakra-ui/portal': 2.1.0(react-dom@18.2.0)(react@18.2.0)
       '@chakra-ui/react-context': 2.1.0(react@18.2.0)
       '@chakra-ui/react-types': 2.0.7(react@18.2.0)
@@ -2146,7 +2115,33 @@ packages:
       framer-motion: 10.18.0(react-dom@18.2.0)(react@18.2.0)
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
-      react-remove-scroll: 2.5.7(@types/react@18.2.48)(react@18.2.0)
+      react-remove-scroll: 2.5.7(@types/react@18.2.57)(react@18.2.0)
+    transitivePeerDependencies:
+      - '@types/react'
+    dev: false
+
+  /@chakra-ui/modal@2.3.1(@chakra-ui/system@2.6.2)(@types/react@18.2.57)(framer-motion@11.0.5)(react-dom@18.2.0)(react@18.2.0):
+    resolution: {integrity: sha512-TQv1ZaiJMZN+rR9DK0snx/OPwmtaGH1HbZtlYt4W4s6CzyK541fxLRTjIXfEzIGpvNW+b6VFuFjbcR78p4DEoQ==}
+    peerDependencies:
+      '@chakra-ui/system': '>=2.0.0'
+      framer-motion: '>=4.0.0'
+      react: '>=18'
+      react-dom: '>=18'
+    dependencies:
+      '@chakra-ui/close-button': 2.1.1(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/focus-lock': 2.1.0(@types/react@18.2.57)(react@18.2.0)
+      '@chakra-ui/portal': 2.1.0(react-dom@18.2.0)(react@18.2.0)
+      '@chakra-ui/react-context': 2.1.0(react@18.2.0)
+      '@chakra-ui/react-types': 2.0.7(react@18.2.0)
+      '@chakra-ui/react-use-merge-refs': 2.1.0(react@18.2.0)
+      '@chakra-ui/shared-utils': 2.0.5
+      '@chakra-ui/system': 2.6.2(@emotion/react@11.11.3)(@emotion/styled@11.11.0)(react@18.2.0)
+      '@chakra-ui/transition': 2.1.0(framer-motion@11.0.5)(react@18.2.0)
+      aria-hidden: 1.2.3
+      framer-motion: 11.0.5(react-dom@18.2.0)(react@18.2.0)
+      react: 18.2.0
+      react-dom: 18.2.0(react@18.2.0)
+      react-remove-scroll: 2.5.7(@types/react@18.2.57)(react@18.2.0)
     transitivePeerDependencies:
       - '@types/react'
     dev: false
@@ -2220,6 +2215,29 @@ packages:
       react: 18.2.0
     dev: false
 
+  /@chakra-ui/popover@2.2.1(@chakra-ui/system@2.6.2)(framer-motion@11.0.5)(react@18.2.0):
+    resolution: {integrity: sha512-K+2ai2dD0ljvJnlrzesCDT9mNzLifE3noGKZ3QwLqd/K34Ym1W/0aL1ERSynrcG78NKoXS54SdEzkhCZ4Gn/Zg==}
+    peerDependencies:
+      '@chakra-ui/system': '>=2.0.0'
+      framer-motion: '>=4.0.0'
+      react: '>=18'
+    dependencies:
+      '@chakra-ui/close-button': 2.1.1(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/lazy-utils': 2.0.5
+      '@chakra-ui/popper': 3.1.0(react@18.2.0)
+      '@chakra-ui/react-context': 2.1.0(react@18.2.0)
+      '@chakra-ui/react-types': 2.0.7(react@18.2.0)
+      '@chakra-ui/react-use-animation-state': 2.1.0(react@18.2.0)
+      '@chakra-ui/react-use-disclosure': 2.1.0(react@18.2.0)
+      '@chakra-ui/react-use-focus-effect': 2.1.0(react@18.2.0)
+      '@chakra-ui/react-use-focus-on-pointer-down': 2.1.0(react@18.2.0)
+      '@chakra-ui/react-use-merge-refs': 2.1.0(react@18.2.0)
+      '@chakra-ui/shared-utils': 2.0.5
+      '@chakra-ui/system': 2.6.2(@emotion/react@11.11.3)(@emotion/styled@11.11.0)(react@18.2.0)
+      framer-motion: 11.0.5(react-dom@18.2.0)(react@18.2.0)
+      react: 18.2.0
+    dev: false
+
   /@chakra-ui/popper@3.1.0(react@18.2.0):
     resolution: {integrity: sha512-ciDdpdYbeFG7og6/6J8lkTFxsSvwTdMLFkpVylAF6VNC22jssiWfquj2eyD4rJnzkRFPvIWJq8hvbfhsm+AjSg==}
     peerDependencies:
@@ -2267,8 +2285,8 @@ packages:
       '@chakra-ui/react-env': 3.1.0(react@18.2.0)
       '@chakra-ui/system': 2.6.2(@emotion/react@11.11.3)(@emotion/styled@11.11.0)(react@18.2.0)
       '@chakra-ui/utils': 2.0.15
-      '@emotion/react': 11.11.3(@types/react@18.2.48)(react@18.2.0)
-      '@emotion/styled': 11.11.0(@emotion/react@11.11.3)(@types/react@18.2.48)(react@18.2.0)
+      '@emotion/react': 11.11.3(@types/react@18.2.57)(react@18.2.0)
+      '@emotion/styled': 11.11.0(@emotion/react@11.11.3)(@types/react@18.2.57)(react@18.2.0)
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     dev: false
@@ -2484,7 +2502,7 @@ packages:
       react: 18.2.0
     dev: false
 
-  /@chakra-ui/react@2.8.2(@emotion/react@11.11.3)(@emotion/styled@11.11.0)(@types/react@18.2.48)(framer-motion@10.18.0)(react-dom@18.2.0)(react@18.2.0):
+  /@chakra-ui/react@2.8.2(@emotion/react@11.11.3)(@emotion/styled@11.11.0)(@types/react@18.2.57)(framer-motion@10.18.0)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-Hn0moyxxyCDKuR9ywYpqgX8dvjqwu9ArwpIb9wHNYjnODETjLwazgNIliCVBRcJvysGRiV51U2/JtJVrpeCjUQ==}
     peerDependencies:
       '@emotion/react': ^11.0.0
@@ -2505,7 +2523,7 @@ packages:
       '@chakra-ui/counter': 2.1.0(react@18.2.0)
       '@chakra-ui/css-reset': 2.3.0(@emotion/react@11.11.3)(react@18.2.0)
       '@chakra-ui/editable': 3.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/focus-lock': 2.1.0(@types/react@18.2.48)(react@18.2.0)
+      '@chakra-ui/focus-lock': 2.1.0(@types/react@18.2.57)(react@18.2.0)
       '@chakra-ui/form-control': 2.2.0(@chakra-ui/system@2.6.2)(react@18.2.0)
       '@chakra-ui/hooks': 2.2.1(react@18.2.0)
       '@chakra-ui/icon': 3.2.0(@chakra-ui/system@2.6.2)(react@18.2.0)
@@ -2515,7 +2533,7 @@ packages:
       '@chakra-ui/live-region': 2.1.0(react@18.2.0)
       '@chakra-ui/media-query': 3.3.0(@chakra-ui/system@2.6.2)(react@18.2.0)
       '@chakra-ui/menu': 2.2.1(@chakra-ui/system@2.6.2)(framer-motion@10.18.0)(react@18.2.0)
-      '@chakra-ui/modal': 2.3.1(@chakra-ui/system@2.6.2)(@types/react@18.2.48)(framer-motion@10.18.0)(react-dom@18.2.0)(react@18.2.0)
+      '@chakra-ui/modal': 2.3.1(@chakra-ui/system@2.6.2)(@types/react@18.2.57)(framer-motion@10.18.0)(react-dom@18.2.0)(react@18.2.0)
       '@chakra-ui/number-input': 2.1.2(@chakra-ui/system@2.6.2)(react@18.2.0)
       '@chakra-ui/pin-input': 2.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
       '@chakra-ui/popover': 2.2.1(@chakra-ui/system@2.6.2)(framer-motion@10.18.0)(react@18.2.0)
@@ -2546,8 +2564,8 @@ packages:
       '@chakra-ui/transition': 2.1.0(framer-motion@10.18.0)(react@18.2.0)
       '@chakra-ui/utils': 2.0.15
       '@chakra-ui/visually-hidden': 2.2.0(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@emotion/react': 11.11.3(@types/react@18.2.48)(react@18.2.0)
-      '@emotion/styled': 11.11.0(@emotion/react@11.11.3)(@types/react@18.2.48)(react@18.2.0)
+      '@emotion/react': 11.11.3(@types/react@18.2.57)(react@18.2.0)
+      '@emotion/styled': 11.11.0(@emotion/react@11.11.3)(@types/react@18.2.57)(react@18.2.0)
       framer-motion: 10.18.0(react-dom@18.2.0)(react@18.2.0)
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
@@ -2555,6 +2573,77 @@ packages:
       - '@types/react'
     dev: false
 
+  /@chakra-ui/react@2.8.2(@emotion/react@11.11.3)(@emotion/styled@11.11.0)(@types/react@18.2.57)(framer-motion@11.0.5)(react-dom@18.2.0)(react@18.2.0):
+    resolution: {integrity: sha512-Hn0moyxxyCDKuR9ywYpqgX8dvjqwu9ArwpIb9wHNYjnODETjLwazgNIliCVBRcJvysGRiV51U2/JtJVrpeCjUQ==}
+    peerDependencies:
+      '@emotion/react': ^11.0.0
+      '@emotion/styled': ^11.0.0
+      framer-motion: '>=4.0.0'
+      react: '>=18'
+      react-dom: '>=18'
+    dependencies:
+      '@chakra-ui/accordion': 2.3.1(@chakra-ui/system@2.6.2)(framer-motion@11.0.5)(react@18.2.0)
+      '@chakra-ui/alert': 2.2.2(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/avatar': 2.3.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/breadcrumb': 2.2.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/button': 2.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/card': 2.2.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/checkbox': 2.3.2(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/close-button': 2.1.1(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/control-box': 2.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/counter': 2.1.0(react@18.2.0)
+      '@chakra-ui/css-reset': 2.3.0(@emotion/react@11.11.3)(react@18.2.0)
+      '@chakra-ui/editable': 3.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/focus-lock': 2.1.0(@types/react@18.2.57)(react@18.2.0)
+      '@chakra-ui/form-control': 2.2.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/hooks': 2.2.1(react@18.2.0)
+      '@chakra-ui/icon': 3.2.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/image': 2.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/input': 2.1.2(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/layout': 2.3.1(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/live-region': 2.1.0(react@18.2.0)
+      '@chakra-ui/media-query': 3.3.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/menu': 2.2.1(@chakra-ui/system@2.6.2)(framer-motion@11.0.5)(react@18.2.0)
+      '@chakra-ui/modal': 2.3.1(@chakra-ui/system@2.6.2)(@types/react@18.2.57)(framer-motion@11.0.5)(react-dom@18.2.0)(react@18.2.0)
+      '@chakra-ui/number-input': 2.1.2(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/pin-input': 2.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/popover': 2.2.1(@chakra-ui/system@2.6.2)(framer-motion@11.0.5)(react@18.2.0)
+      '@chakra-ui/popper': 3.1.0(react@18.2.0)
+      '@chakra-ui/portal': 2.1.0(react-dom@18.2.0)(react@18.2.0)
+      '@chakra-ui/progress': 2.2.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/provider': 2.4.2(@emotion/react@11.11.3)(@emotion/styled@11.11.0)(react-dom@18.2.0)(react@18.2.0)
+      '@chakra-ui/radio': 2.1.2(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/react-env': 3.1.0(react@18.2.0)
+      '@chakra-ui/select': 2.1.2(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/skeleton': 2.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/skip-nav': 2.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/slider': 2.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/spinner': 2.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/stat': 2.1.1(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/stepper': 2.3.1(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/styled-system': 2.9.2
+      '@chakra-ui/switch': 2.1.2(@chakra-ui/system@2.6.2)(framer-motion@11.0.5)(react@18.2.0)
+      '@chakra-ui/system': 2.6.2(@emotion/react@11.11.3)(@emotion/styled@11.11.0)(react@18.2.0)
+      '@chakra-ui/table': 2.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/tabs': 3.0.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/tag': 3.1.1(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/textarea': 2.1.2(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/theme': 3.3.1(@chakra-ui/styled-system@2.9.2)
+      '@chakra-ui/theme-utils': 2.0.21
+      '@chakra-ui/toast': 7.0.2(@chakra-ui/system@2.6.2)(framer-motion@11.0.5)(react-dom@18.2.0)(react@18.2.0)
+      '@chakra-ui/tooltip': 2.3.1(@chakra-ui/system@2.6.2)(framer-motion@11.0.5)(react-dom@18.2.0)(react@18.2.0)
+      '@chakra-ui/transition': 2.1.0(framer-motion@11.0.5)(react@18.2.0)
+      '@chakra-ui/utils': 2.0.15
+      '@chakra-ui/visually-hidden': 2.2.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@emotion/react': 11.11.3(@types/react@18.2.57)(react@18.2.0)
+      '@emotion/styled': 11.11.0(@emotion/react@11.11.3)(@types/react@18.2.57)(react@18.2.0)
+      framer-motion: 11.0.5(react-dom@18.2.0)(react@18.2.0)
+      react: 18.2.0
+      react-dom: 18.2.0(react@18.2.0)
+    transitivePeerDependencies:
+      - '@types/react'
+    dev: false
+
   /@chakra-ui/select@2.1.2(@chakra-ui/system@2.6.2)(react@18.2.0):
     resolution: {integrity: sha512-ZwCb7LqKCVLJhru3DXvKXpZ7Pbu1TDZ7N0PdQ0Zj1oyVLJyrpef1u9HR5u0amOpqcH++Ugt0f5JSmirjNlctjA==}
     peerDependencies:
@@ -2673,6 +2762,20 @@ packages:
       react: 18.2.0
     dev: false
 
+  /@chakra-ui/switch@2.1.2(@chakra-ui/system@2.6.2)(framer-motion@11.0.5)(react@18.2.0):
+    resolution: {integrity: sha512-pgmi/CC+E1v31FcnQhsSGjJnOE2OcND4cKPyTE+0F+bmGm48Q/b5UmKD9Y+CmZsrt/7V3h8KNczowupfuBfIHA==}
+    peerDependencies:
+      '@chakra-ui/system': '>=2.0.0'
+      framer-motion: '>=4.0.0'
+      react: '>=18'
+    dependencies:
+      '@chakra-ui/checkbox': 2.3.2(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/shared-utils': 2.0.5
+      '@chakra-ui/system': 2.6.2(@emotion/react@11.11.3)(@emotion/styled@11.11.0)(react@18.2.0)
+      framer-motion: 11.0.5(react-dom@18.2.0)(react@18.2.0)
+      react: 18.2.0
+    dev: false
+
   /@chakra-ui/system@2.6.2(@emotion/react@11.11.3)(@emotion/styled@11.11.0)(react@18.2.0):
     resolution: {integrity: sha512-EGtpoEjLrUu4W1fHD+a62XR+hzC5YfsWm+6lO0Kybcga3yYEij9beegO0jZgug27V+Rf7vns95VPVP6mFd/DEQ==}
     peerDependencies:
@@ -2686,8 +2789,8 @@ packages:
       '@chakra-ui/styled-system': 2.9.2
       '@chakra-ui/theme-utils': 2.0.21
       '@chakra-ui/utils': 2.0.15
-      '@emotion/react': 11.11.3(@types/react@18.2.48)(react@18.2.0)
-      '@emotion/styled': 11.11.0(@emotion/react@11.11.3)(@types/react@18.2.48)(react@18.2.0)
+      '@emotion/react': 11.11.3(@types/react@18.2.57)(react@18.2.0)
+      '@emotion/styled': 11.11.0(@emotion/react@11.11.3)(@types/react@18.2.57)(react@18.2.0)
       react: 18.2.0
       react-fast-compare: 3.2.2
     dev: false
@@ -2801,6 +2904,29 @@ packages:
       react-dom: 18.2.0(react@18.2.0)
     dev: false
 
+  /@chakra-ui/toast@7.0.2(@chakra-ui/system@2.6.2)(framer-motion@11.0.5)(react-dom@18.2.0)(react@18.2.0):
+    resolution: {integrity: sha512-yvRP8jFKRs/YnkuE41BVTq9nB2v/KDRmje9u6dgDmE5+1bFt3bwjdf9gVbif4u5Ve7F7BGk5E093ARRVtvLvXA==}
+    peerDependencies:
+      '@chakra-ui/system': 2.6.2
+      framer-motion: '>=4.0.0'
+      react: '>=18'
+      react-dom: '>=18'
+    dependencies:
+      '@chakra-ui/alert': 2.2.2(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/close-button': 2.1.1(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/portal': 2.1.0(react-dom@18.2.0)(react@18.2.0)
+      '@chakra-ui/react-context': 2.1.0(react@18.2.0)
+      '@chakra-ui/react-use-timeout': 2.1.0(react@18.2.0)
+      '@chakra-ui/react-use-update-effect': 2.1.0(react@18.2.0)
+      '@chakra-ui/shared-utils': 2.0.5
+      '@chakra-ui/styled-system': 2.9.2
+      '@chakra-ui/system': 2.6.2(@emotion/react@11.11.3)(@emotion/styled@11.11.0)(react@18.2.0)
+      '@chakra-ui/theme': 3.3.1(@chakra-ui/styled-system@2.9.2)
+      framer-motion: 11.0.5(react-dom@18.2.0)(react@18.2.0)
+      react: 18.2.0
+      react-dom: 18.2.0(react@18.2.0)
+    dev: false
+
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     peerDependencies:
@@ -2823,6 +2949,28 @@ packages:
       react-dom: 18.2.0(react@18.2.0)
     dev: false
 
+  /@chakra-ui/tooltip@2.3.1(@chakra-ui/system@2.6.2)(framer-motion@11.0.5)(react-dom@18.2.0)(react@18.2.0):
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+    peerDependencies:
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+      framer-motion: '>=4.0.0'
+      react: '>=18'
+      react-dom: '>=18'
+    dependencies:
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+      '@chakra-ui/popper': 3.1.0(react@18.2.0)
+      '@chakra-ui/portal': 2.1.0(react-dom@18.2.0)(react@18.2.0)
+      '@chakra-ui/react-types': 2.0.7(react@18.2.0)
+      '@chakra-ui/react-use-disclosure': 2.1.0(react@18.2.0)
+      '@chakra-ui/react-use-event-listener': 2.1.0(react@18.2.0)
+      '@chakra-ui/react-use-merge-refs': 2.1.0(react@18.2.0)
+      '@chakra-ui/shared-utils': 2.0.5
+      '@chakra-ui/system': 2.6.2(@emotion/react@11.11.3)(@emotion/styled@11.11.0)(react@18.2.0)
+      framer-motion: 11.0.5(react-dom@18.2.0)(react@18.2.0)
+      react: 18.2.0
+      react-dom: 18.2.0(react@18.2.0)
+    dev: false
+
   /@chakra-ui/transition@2.1.0(framer-motion@10.18.0)(react@18.2.0):
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     peerDependencies:
@@ -2834,6 +2982,17 @@ packages:
       react: 18.2.0
     dev: false
 
+  /@chakra-ui/transition@2.1.0(framer-motion@11.0.5)(react@18.2.0):
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+    peerDependencies:
+      framer-motion: '>=4.0.0'
+      react: '>=18'
+    dependencies:
+      '@chakra-ui/shared-utils': 2.0.5
+      framer-motion: 11.0.5(react-dom@18.2.0)(react@18.2.0)
+      react: 18.2.0
+    dev: false
+
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     dependencies:
@@ -2925,7 +3084,7 @@ packages:
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     dependencies:
       '@babel/helper-module-imports': 7.22.15
-      '@babel/runtime': 7.23.8
+      '@babel/runtime': 7.23.9
       '@emotion/hash': 0.9.1
       '@emotion/memoize': 0.8.1
       '@emotion/serialize': 1.1.3
@@ -2975,7 +3134,7 @@ packages:
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     dev: false
 
-  /@emotion/react@11.11.3(@types/react@18.2.48)(react@18.2.0):
+  /@emotion/react@11.11.3(@types/react@18.2.57)(react@18.2.0):
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     peerDependencies:
       '@types/react': '*'
@@ -2984,14 +3143,14 @@ packages:
       '@types/react':
         optional: true
     dependencies:
-      '@babel/runtime': 7.23.8
+      '@babel/runtime': 7.23.9
       '@emotion/babel-plugin': 11.11.0
       '@emotion/cache': 11.11.0
       '@emotion/serialize': 1.1.3
       '@emotion/use-insertion-effect-with-fallbacks': 1.0.1(react@18.2.0)
       '@emotion/utils': 1.2.1
       '@emotion/weak-memoize': 0.3.1
-      '@types/react': 18.2.48
+      '@types/react': 18.2.57
       hoist-non-react-statics: 3.3.2
       react: 18.2.0
     dev: false
@@ -3010,7 +3169,7 @@ packages:
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     dev: false
 
-  /@emotion/styled@11.11.0(@emotion/react@11.11.3)(@types/react@18.2.48)(react@18.2.0):
+  /@emotion/styled@11.11.0(@emotion/react@11.11.3)(@types/react@18.2.57)(react@18.2.0):
     resolution: {integrity: sha512-hM5Nnvu9P3midq5aaXj4I+lnSfNi7Pmd4EWk1fOZ3pxookaQTNew6bp4JaCBYM4HVFZF9g7UjJmsUmC2JlxOng==}
     peerDependencies:
       '@emotion/react': ^11.0.0-rc.0
@@ -3023,11 +3182,11 @@ packages:
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       '@emotion/babel-plugin': 11.11.0
       '@emotion/is-prop-valid': 1.2.1
-      '@emotion/react': 11.11.3(@types/react@18.2.48)(react@18.2.0)
+      '@emotion/react': 11.11.3(@types/react@18.2.57)(react@18.2.0)
       '@emotion/serialize': 1.1.3
       '@emotion/use-insertion-effect-with-fallbacks': 1.0.1(react@18.2.0)
       '@emotion/utils': 1.2.1
-      '@types/react': 18.2.48
+      '@types/react': 18.2.57
       react: 18.2.0
     dev: false
 
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     dev: false
 
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+  /@esbuild/aix-ppc64@0.19.12:
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     engines: {node: '>=12'}
     cpu: [ppc64]
     os: [aix]
@@ -3068,8 +3227,8 @@ packages:
     dev: true
     optional: true
 
-  /@esbuild/android-arm64@0.19.11:
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+  /@esbuild/android-arm64@0.19.12:
+    resolution: {integrity: sha512-P0UVNGIienjZv3f5zq0DP3Nt2IE/3plFzuaS96vihvD0Hd6H/q4WXUGpCxD/E8YrSXfNyRPbpTq+T8ZQioSuPA==}
     engines: {node: '>=12'}
     cpu: [arm64]
     os: [android]
@@ -3086,8 +3245,8 @@ packages:
     dev: true
     optional: true
 
-  /@esbuild/android-arm@0.19.11:
-    resolution: {integrity: sha512-5OVapq0ClabvKvQ58Bws8+wkLCV+Rxg7tUVbo9xu034Nm536QTII4YzhaFriQ7rMrorfnFKUsArD2lqKbFY4vw==}
+  /@esbuild/android-arm@0.19.12:
+    resolution: {integrity: sha512-qg/Lj1mu3CdQlDEEiWrlC4eaPZ1KztwGJ9B6J+/6G+/4ewxJg7gqj8eVYWvao1bXrqGiW2rsBZFSX3q2lcW05w==}
     engines: {node: '>=12'}
     cpu: [arm]
     os: [android]
@@ -3104,8 +3263,8 @@ packages:
     dev: true
     optional: true
 
-  /@esbuild/android-x64@0.19.11:
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+  /@esbuild/android-x64@0.19.12:
+    resolution: {integrity: sha512-3k7ZoUW6Q6YqhdhIaq/WZ7HwBpnFBlW905Fa4s4qWJyiNOgT1dOqDiVAQFwBH7gBRZr17gLrlFCRzF6jFh7Kew==}
     engines: {node: '>=12'}
     cpu: [x64]
     os: [android]
@@ -3122,8 +3281,8 @@ packages:
     dev: true
     optional: true
 
-  /@esbuild/darwin-arm64@0.19.11:
-    resolution: {integrity: sha512-ETp87DRWuSt9KdDVkqSoKoLFHYTrkyz2+65fj9nfXsaV3bMhTCjtQfw3y+um88vGRKRiF7erPrh/ZuIdLUIVxQ==}
+  /@esbuild/darwin-arm64@0.19.12:
+    resolution: {integrity: sha512-B6IeSgZgtEzGC42jsI+YYu9Z3HKRxp8ZT3cqhvliEHovq8HSX2YX8lNocDn79gCKJXOSaEot9MVYky7AKjCs8g==}
     engines: {node: '>=12'}
     cpu: [arm64]
     os: [darwin]
@@ -3140,8 +3299,8 @@ packages:
     dev: true
     optional: true
 
-  /@esbuild/darwin-x64@0.19.11:
-    resolution: {integrity: sha512-fkFUiS6IUK9WYUO/+22omwetaSNl5/A8giXvQlcinLIjVkxwTLSktbF5f/kJMftM2MJp9+fXqZ5ezS7+SALp4g==}
+  /@esbuild/darwin-x64@0.19.12:
+    resolution: {integrity: sha512-hKoVkKzFiToTgn+41qGhsUJXFlIjxI/jSYeZf3ugemDYZldIXIxhvwN6erJGlX4t5h417iFuheZ7l+YVn05N3A==}
     engines: {node: '>=12'}
     cpu: [x64]
     os: [darwin]
@@ -3158,8 +3317,8 @@ packages:
     dev: true
     optional: true
 
-  /@esbuild/freebsd-arm64@0.19.11:
-    resolution: {integrity: sha512-lhoSp5K6bxKRNdXUtHoNc5HhbXVCS8V0iZmDvyWvYq9S5WSfTIHU2UGjcGt7UeS6iEYp9eeymIl5mJBn0yiuxA==}
+  /@esbuild/freebsd-arm64@0.19.12:
+    resolution: {integrity: sha512-4aRvFIXmwAcDBw9AueDQ2YnGmz5L6obe5kmPT8Vd+/+x/JMVKCgdcRwH6APrbpNXsPz+K653Qg8HB/oXvXVukA==}
     engines: {node: '>=12'}
     cpu: [arm64]
     os: [freebsd]
@@ -3176,8 +3335,8 @@ packages:
     dev: true
     optional: true
 
-  /@esbuild/freebsd-x64@0.19.11:
-    resolution: {integrity: sha512-JkUqn44AffGXitVI6/AbQdoYAq0TEullFdqcMY/PCUZ36xJ9ZJRtQabzMA+Vi7r78+25ZIBosLTOKnUXBSi1Kw==}
+  /@esbuild/freebsd-x64@0.19.12:
+    resolution: {integrity: sha512-EYoXZ4d8xtBoVN7CEwWY2IN4ho76xjYXqSXMNccFSx2lgqOG/1TBPW0yPx1bJZk94qu3tX0fycJeeQsKovA8gg==}
     engines: {node: '>=12'}
     cpu: [x64]
     os: [freebsd]
@@ -3194,8 +3353,8 @@ packages:
     dev: true
     optional: true
 
-  /@esbuild/linux-arm64@0.19.11:
-    resolution: {integrity: sha512-LneLg3ypEeveBSMuoa0kwMpCGmpu8XQUh+mL8XXwoYZ6Be2qBnVtcDI5azSvh7vioMDhoJFZzp9GWp9IWpYoUg==}
+  /@esbuild/linux-arm64@0.19.12:
+    resolution: {integrity: sha512-EoTjyYyLuVPfdPLsGVVVC8a0p1BFFvtpQDB/YLEhaXyf/5bczaGeN15QkR+O4S5LeJ92Tqotve7i1jn35qwvdA==}
     engines: {node: '>=12'}
     cpu: [arm64]
     os: [linux]
@@ -3212,8 +3371,8 @@ packages:
     dev: true
     optional: true
 
-  /@esbuild/linux-arm@0.19.11:
-    resolution: {integrity: sha512-3CRkr9+vCV2XJbjwgzjPtO8T0SZUmRZla+UL1jw+XqHZPkPgZiyWvbDvl9rqAN8Zl7qJF0O/9ycMtjU67HN9/Q==}
+  /@esbuild/linux-arm@0.19.12:
+    resolution: {integrity: sha512-J5jPms//KhSNv+LO1S1TX1UWp1ucM6N6XuL6ITdKWElCu8wXP72l9MM0zDTzzeikVyqFE6U8YAV9/tFyj0ti+w==}
     engines: {node: '>=12'}
     cpu: [arm]
     os: [linux]
@@ -3230,8 +3389,8 @@ packages:
     dev: true
     optional: true
 
-  /@esbuild/linux-ia32@0.19.11:
-    resolution: {integrity: sha512-caHy++CsD8Bgq2V5CodbJjFPEiDPq8JJmBdeyZ8GWVQMjRD0sU548nNdwPNvKjVpamYYVL40AORekgfIubwHoA==}
+  /@esbuild/linux-ia32@0.19.12:
+    resolution: {integrity: sha512-Thsa42rrP1+UIGaWz47uydHSBOgTUnwBwNq59khgIwktK6x60Hivfbux9iNR0eHCHzOLjLMLfUMLCypBkZXMHA==}
     engines: {node: '>=12'}
     cpu: [ia32]
     os: [linux]
@@ -3248,8 +3407,8 @@ packages:
     dev: true
     optional: true
 
-  /@esbuild/linux-loong64@0.19.11:
-    resolution: {integrity: sha512-ppZSSLVpPrwHccvC6nQVZaSHlFsvCQyjnvirnVjbKSHuE5N24Yl8F3UwYUUR1UEPaFObGD2tSvVKbvR+uT1Nrg==}
+  /@esbuild/linux-loong64@0.19.12:
+    resolution: {integrity: sha512-LiXdXA0s3IqRRjm6rV6XaWATScKAXjI4R4LoDlvO7+yQqFdlr1Bax62sRwkVvRIrwXxvtYEHHI4dm50jAXkuAA==}
     engines: {node: '>=12'}
     cpu: [loong64]
     os: [linux]
@@ -3266,8 +3425,8 @@ packages:
     dev: true
     optional: true
 
-  /@esbuild/linux-mips64el@0.19.11:
-    resolution: {integrity: sha512-B5x9j0OgjG+v1dF2DkH34lr+7Gmv0kzX6/V0afF41FkPMMqaQ77pH7CrhWeR22aEeHKaeZVtZ6yFwlxOKPVFyg==}
+  /@esbuild/linux-mips64el@0.19.12:
+    resolution: {integrity: sha512-fEnAuj5VGTanfJ07ff0gOA6IPsvrVHLVb6Lyd1g2/ed67oU1eFzL0r9WL7ZzscD+/N6i3dWumGE1Un4f7Amf+w==}
     engines: {node: '>=12'}
     cpu: [mips64el]
     os: [linux]
@@ -3284,8 +3443,8 @@ packages:
     dev: true
     optional: true
 
-  /@esbuild/linux-ppc64@0.19.11:
-    resolution: {integrity: sha512-MHrZYLeCG8vXblMetWyttkdVRjQlQUb/oMgBNurVEnhj4YWOr4G5lmBfZjHYQHHN0g6yDmCAQRR8MUHldvvRDA==}
+  /@esbuild/linux-ppc64@0.19.12:
+    resolution: {integrity: sha512-nYJA2/QPimDQOh1rKWedNOe3Gfc8PabU7HT3iXWtNUbRzXS9+vgB0Fjaqr//XNbd82mCxHzik2qotuI89cfixg==}
     engines: {node: '>=12'}
     cpu: [ppc64]
     os: [linux]
@@ -3302,8 +3461,8 @@ packages:
     dev: true
     optional: true
 
-  /@esbuild/linux-riscv64@0.19.11:
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+  /@esbuild/linux-riscv64@0.19.12:
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     engines: {node: '>=12'}
     cpu: [riscv64]
     os: [linux]
@@ -3320,8 +3479,8 @@ packages:
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     optional: true
 
-  /@esbuild/linux-s390x@0.19.11:
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+  /@esbuild/linux-s390x@0.19.12:
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     engines: {node: '>=12'}
     cpu: [s390x]
     os: [linux]
@@ -3338,8 +3497,8 @@ packages:
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     optional: true
 
-  /@esbuild/linux-x64@0.19.11:
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+  /@esbuild/linux-x64@0.19.12:
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     engines: {node: '>=12'}
     cpu: [x64]
     os: [linux]
@@ -3356,8 +3515,8 @@ packages:
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     optional: true
 
-  /@esbuild/netbsd-x64@0.19.11:
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+  /@esbuild/netbsd-x64@0.19.12:
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     engines: {node: '>=12'}
     cpu: [x64]
     os: [netbsd]
@@ -3374,8 +3533,8 @@ packages:
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     optional: true
 
-  /@esbuild/openbsd-x64@0.19.11:
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+  /@esbuild/openbsd-x64@0.19.12:
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     engines: {node: '>=12'}
     cpu: [x64]
     os: [openbsd]
@@ -3392,8 +3551,8 @@ packages:
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     optional: true
 
-  /@esbuild/sunos-x64@0.19.11:
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+  /@esbuild/sunos-x64@0.19.12:
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     engines: {node: '>=12'}
     cpu: [x64]
     os: [sunos]
@@ -3410,8 +3569,8 @@ packages:
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     optional: true
 
-  /@esbuild/win32-arm64@0.19.11:
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+  /@esbuild/win32-arm64@0.19.12:
+    resolution: {integrity: sha512-URgtR1dJnmGvX864pn1B2YUYNzjmXkuJOIqG2HdU62MVS4EHpU2946OZoTMnRUHklGtJdJZ33QfzdjGACXhn1A==}
     engines: {node: '>=12'}
     cpu: [arm64]
     os: [win32]
@@ -3428,8 +3587,8 @@ packages:
     dev: true
     optional: true
 
-  /@esbuild/win32-ia32@0.19.11:
-    resolution: {integrity: sha512-6YOrWS+sDJDmshdBIQU+Uoyh7pQKrdykdefC1avn76ss5c+RN6gut3LZA4E2cH5xUEp5/cA0+YxRaVtRAb0xBg==}
+  /@esbuild/win32-ia32@0.19.12:
+    resolution: {integrity: sha512-+ZOE6pUkMOJfmxmBZElNOx72NKpIa/HFOMGzu8fqzQJ5kgf6aTGrcJaFsNiVMH4JKpMipyK+7k0n2UXN7a8YKQ==}
     engines: {node: '>=12'}
     cpu: [ia32]
     os: [win32]
@@ -3446,8 +3605,8 @@ packages:
     dev: true
     optional: true
 
-  /@esbuild/win32-x64@0.19.11:
-    resolution: {integrity: sha512-vfkhltrjCAb603XaFhqhAF4LGDi2M4OrCRrFusyQ+iTLQ/o60QQXxc9cZC/FFpihBI9N1Grn6SMKVJ4KP7Fuiw==}
+  /@esbuild/win32-x64@0.19.12:
+    resolution: {integrity: sha512-T1QyPSDCyMXaO3pzBkF96E8xMkiRYbUEZADd29SyPGabqxMViNoii+NcK7eWJAEoU6RZyEm5lVSIjTmcdoB9HA==}
     engines: {node: '>=12'}
     cpu: [x64]
     os: [win32]
@@ -3478,7 +3637,7 @@ packages:
       debug: 4.3.4
       espree: 9.6.1
       globals: 13.24.0
-      ignore: 5.3.0
+      ignore: 5.3.1
       import-fresh: 3.3.0
       js-yaml: 4.1.0
       minimatch: 3.1.2
@@ -3501,45 +3660,35 @@ packages:
     engines: {node: '>=14'}
     dev: true
 
-  /@floating-ui/core@1.5.2:
-    resolution: {integrity: sha512-Ii3MrfY/GAIN3OhXNzpCKaLxHQfJF9qvwq/kEJYdqDxeIHa01K8sldugal6TmeeXl+WMvhv9cnVzUTaFFJF09A==}
-    dependencies:
-      '@floating-ui/utils': 0.1.6
-    dev: false
-
-  /@floating-ui/core@1.5.3:
-    resolution: {integrity: sha512-O0WKDOo0yhJuugCx6trZQj5jVJ9yR0ystG2JaNAemYUWce+pmM6WUEFIibnWyEJKdrDxhm75NoSRME35FNaM/Q==}
+  /@floating-ui/core@1.6.0:
+    resolution: {integrity: sha512-PcF++MykgmTj3CIyOQbKA/hDzOAiqI3mhuoN44WRCopIs1sgoDoU4oty4Jtqaj/y3oDU6fnVSm4QG0a3t5i0+g==}
     dependencies:
       '@floating-ui/utils': 0.2.1
 
-  /@floating-ui/dom@1.5.3:
-    resolution: {integrity: sha512-ClAbQnEqJAKCJOEbbLo5IUlZHkNszqhuxS4fHAVxRPXPya6Ysf2G8KypnYcOTpx6I8xcgF9bbHb6g/2KpbV8qA==}
-    dependencies:
-      '@floating-ui/core': 1.5.2
-      '@floating-ui/utils': 0.1.6
-    dev: false
-
   /@floating-ui/dom@1.5.4:
     resolution: {integrity: sha512-jByEsHIY+eEdCjnTVu+E3ephzTOzkQ8hgUfGwos+bg7NlH33Zc5uO+QHz1mrQUOgIKKDD1RtS201P9NvAfq3XQ==}
     dependencies:
-      '@floating-ui/core': 1.5.3
+      '@floating-ui/core': 1.6.0
+      '@floating-ui/utils': 0.2.1
+    dev: false
+
+  /@floating-ui/dom@1.6.3:
+    resolution: {integrity: sha512-RnDthu3mzPlQ31Ss/BTwQ1zjzIhr3lk1gZB1OC56h/1vEtaXkESrOqL5fQVMfXpwGtRwX+YsZBdyHtJMQnkArw==}
+    dependencies:
+      '@floating-ui/core': 1.6.0
       '@floating-ui/utils': 0.2.1
 
-  /@floating-ui/react-dom@2.0.6(react-dom@18.2.0)(react@18.2.0):
-    resolution: {integrity: sha512-IB8aCRFxr8nFkdYZgH+Otd9EVQPJoynxeFRGTB8voPoZMRWo8XjYuCRgpI1btvuKY69XMiLnW+ym7zoBHM90Rw==}
+  /@floating-ui/react-dom@2.0.8(react-dom@18.2.0)(react@18.2.0):
+    resolution: {integrity: sha512-HOdqOt3R3OGeTKidaLvJKcgg75S6tibQ3Tif4eyd91QnIJWr0NLvoXFpJA/j8HqkFSL68GDca9AuyWEHlhyClw==}
     peerDependencies:
       react: '>=16.8.0'
       react-dom: '>=16.8.0'
     dependencies:
-      '@floating-ui/dom': 1.5.4
+      '@floating-ui/dom': 1.6.3
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     dev: true
 
-  /@floating-ui/utils@0.1.6:
-    resolution: {integrity: sha512-OfX7E2oUDYxtBvsuS4e/jSn4Q9Qb6DzgeYtsAdkPZ47znpoNsMgZw0+tVijiv3uGNR6dgNlty6r9rzIzHjtd/A==}
-    dev: false
-
   /@floating-ui/utils@0.2.1:
     resolution: {integrity: sha512-9TANp6GPoMtYzQdt54kfAyMmz1+osLlXdg2ENroU7zzrtflTLrrC/lgrIfaSe+Wu0b89GKccT7vxXA0MoAIO+Q==}
 
@@ -3547,11 +3696,11 @@ packages:
     resolution: {integrity: sha512-k+BUNqksTL+AN+o+OV7ILeiE9B5M5X+/jA7LWvCwjbV9ovXTqZyKRhA/x7uYv/ml8WQ0XNLBM7cRFIx4jW0/hg==}
     dev: false
 
-  /@humanwhocodes/config-array@0.11.13:
-    resolution: {integrity: sha512-JSBDMiDKSzQVngfRjOdFXgFfklaXI4K9nLF49Auh21lmBWRLIK3+xTErTWD4KU54pb6coM6ESE7Awz/FNU3zgQ==}
+  /@humanwhocodes/config-array@0.11.14:
+    resolution: {integrity: sha512-3T8LkOmg45BV5FICb15QQMsyUSWrQ8AygVfC7ZG32zOalnqrilm018ZVCw0eapXux8FtA33q8PSRSstjee3jSg==}
     engines: {node: '>=10.10.0'}
     dependencies:
-      '@humanwhocodes/object-schema': 2.0.1
+      '@humanwhocodes/object-schema': 2.0.2
       debug: 4.3.4
       minimatch: 3.1.2
     transitivePeerDependencies:
@@ -3563,8 +3712,8 @@ packages:
     engines: {node: '>=12.22'}
     dev: true
 
-  /@humanwhocodes/object-schema@2.0.1:
-    resolution: {integrity: sha512-dvuCeX5fC9dXgJn9t+X5atfmgQAzUOWqS1254Gh0m6i8wKd10ebXkfNKiRK+1GWi/yTvvLDHpoxLr0xxxeslWw==}
+  /@humanwhocodes/object-schema@2.0.2:
+    resolution: {integrity: sha512-6EwiSjwWYP7pTckG6I5eyFANjPhmPjUX9JRLUSfNPC7FX7zK9gyZAfUEaECL6ALTpGX5AjnBq3C9XmVWPitNpw==}
     dev: true
 
   /@internationalized/date@3.5.2:
@@ -3579,43 +3728,41 @@ packages:
       '@swc/helpers': 0.5.6
     dev: false
 
-  /@invoke-ai/eslint-config-react@0.0.13(@typescript-eslint/eslint-plugin@6.19.0)(@typescript-eslint/parser@6.19.0)(eslint-config-prettier@9.1.0)(eslint-plugin-import@2.29.1)(eslint-plugin-react-hooks@4.6.0)(eslint-plugin-react-refresh@0.4.5)(eslint-plugin-react@7.33.2)(eslint-plugin-simple-import-sort@10.0.0)(eslint-plugin-storybook@0.6.15)(eslint-plugin-unused-imports@3.0.0)(eslint@8.56.0):
-    resolution: {integrity: sha512-dfo9k+wPHdvpy1z6ABoYXR/Ttzs1FAnbC46ttIxVhZuqDq8K5cLWznivrOfl7f0hJb8Cb8HiuQb4pHDxhHBDqA==}
+  /@invoke-ai/eslint-config-react@0.0.14(eslint@8.56.0)(prettier@3.2.5)(typescript@5.3.3):
+    resolution: {integrity: sha512-6ZUY9zgdDhv2WUoLdDKOQdU9ImnH0CBOFtRlOaNOh34IOsNRfn+JA7wqA0PKnkiNrlfPkIQWhn4GRJp68NT5bw==}
     peerDependencies:
-      '@typescript-eslint/eslint-plugin': ^6.19.0
-      '@typescript-eslint/parser': ^6.19.0
       eslint: ^8.56.0
-      eslint-config-prettier: ^9.1.0
-      eslint-plugin-import: ^2.29.1
-      eslint-plugin-react: ^7.33.2
-      eslint-plugin-react-hooks: ^4.6.0
-      eslint-plugin-react-refresh: ^0.4.5
-      eslint-plugin-simple-import-sort: ^10.0.0
-      eslint-plugin-storybook: ^0.6.15
-      eslint-plugin-unused-imports: ^3.0.0
+      prettier: ^3.2.5
+      typescript: ^5.3.3
     dependencies:
-      '@typescript-eslint/eslint-plugin': 6.19.0(@typescript-eslint/parser@6.19.0)(eslint@8.56.0)(typescript@5.3.3)
-      '@typescript-eslint/parser': 6.19.0(eslint@8.56.0)(typescript@5.3.3)
+      '@typescript-eslint/eslint-plugin': 7.0.2(@typescript-eslint/parser@7.0.2)(eslint@8.56.0)(typescript@5.3.3)
+      '@typescript-eslint/parser': 7.0.2(eslint@8.56.0)(typescript@5.3.3)
       eslint: 8.56.0
       eslint-config-prettier: 9.1.0(eslint@8.56.0)
-      eslint-plugin-import: 2.29.1(@typescript-eslint/parser@6.19.0)(eslint@8.56.0)
+      eslint-plugin-import: 2.29.1(@typescript-eslint/parser@7.0.2)(eslint@8.56.0)
       eslint-plugin-react: 7.33.2(eslint@8.56.0)
       eslint-plugin-react-hooks: 4.6.0(eslint@8.56.0)
       eslint-plugin-react-refresh: 0.4.5(eslint@8.56.0)
-      eslint-plugin-simple-import-sort: 10.0.0(eslint@8.56.0)
-      eslint-plugin-storybook: 0.6.15(eslint@8.56.0)(typescript@5.3.3)
-      eslint-plugin-unused-imports: 3.0.0(@typescript-eslint/eslint-plugin@6.19.0)(eslint@8.56.0)
+      eslint-plugin-simple-import-sort: 12.0.0(eslint@8.56.0)
+      eslint-plugin-storybook: 0.8.0(eslint@8.56.0)(typescript@5.3.3)
+      eslint-plugin-unused-imports: 3.1.0(@typescript-eslint/eslint-plugin@7.0.2)(eslint@8.56.0)
+      prettier: 3.2.5
+      typescript: 5.3.3
+    transitivePeerDependencies:
+      - eslint-import-resolver-typescript
+      - eslint-import-resolver-webpack
+      - supports-color
     dev: true
 
-  /@invoke-ai/prettier-config-react@0.0.6(prettier@3.2.4):
-    resolution: {integrity: sha512-qHE6GAw/Aka/8TLTN9U1U+8pxjaFe5irDv/uSgzqmrBR1rGiVyMp19pEficWRRt+03zYdquiiDjTmoabWQxY0Q==}
+  /@invoke-ai/prettier-config-react@0.0.7(prettier@3.2.5):
+    resolution: {integrity: sha512-vQeWzqwih116TBlIJII93L8ictj6uv7PxcSlAGNZrzG2UcaCFMsQqKCsB/qio26uihgv/EtvN6XAF96SnE0TKw==}
     peerDependencies:
-      prettier: ^3.2.4
+      prettier: ^3.2.5
     dependencies:
-      prettier: 3.2.4
+      prettier: 3.2.5
     dev: true
 
-  /@invoke-ai/ui-library@0.0.21(@chakra-ui/form-control@2.2.0)(@chakra-ui/icon@3.2.0)(@chakra-ui/media-query@3.3.0)(@chakra-ui/menu@2.2.1)(@chakra-ui/spinner@2.1.0)(@chakra-ui/system@2.6.2)(@fontsource-variable/inter@5.0.16)(@internationalized/date@3.5.2)(@types/react@18.2.48)(i18next@23.7.16)(react-dom@18.2.0)(react@18.2.0):
+  /@invoke-ai/ui-library@0.0.21(@chakra-ui/form-control@2.2.0)(@chakra-ui/icon@3.2.0)(@chakra-ui/media-query@3.3.0)(@chakra-ui/menu@2.2.1)(@chakra-ui/spinner@2.1.0)(@chakra-ui/system@2.6.2)(@fontsource-variable/inter@5.0.16)(@internationalized/date@3.5.2)(@types/react@18.2.57)(i18next@23.9.0)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-tCvgkBPDt0gNq+8IcR03e/Mw7R8Mb/SMXTqx3FEIxlTQEo93A/D38dKXeDCzTdx4sQ+sknfB+JLBbHs6sg5hhQ==}
     peerDependencies:
       '@fontsource-variable/inter': ^5.0.16
@@ -3627,14 +3774,14 @@ packages:
       '@chakra-ui/icons': 2.1.1(@chakra-ui/system@2.6.2)(react@18.2.0)
       '@chakra-ui/layout': 2.3.1(@chakra-ui/system@2.6.2)(react@18.2.0)
       '@chakra-ui/portal': 2.1.0(react-dom@18.2.0)(react@18.2.0)
-      '@chakra-ui/react': 2.8.2(@emotion/react@11.11.3)(@emotion/styled@11.11.0)(@types/react@18.2.48)(framer-motion@10.18.0)(react-dom@18.2.0)(react@18.2.0)
+      '@chakra-ui/react': 2.8.2(@emotion/react@11.11.3)(@emotion/styled@11.11.0)(@types/react@18.2.57)(framer-motion@10.18.0)(react-dom@18.2.0)(react@18.2.0)
       '@chakra-ui/styled-system': 2.9.2
       '@chakra-ui/theme-tools': 2.1.2(@chakra-ui/styled-system@2.9.2)
-      '@emotion/react': 11.11.3(@types/react@18.2.48)(react@18.2.0)
-      '@emotion/styled': 11.11.0(@emotion/react@11.11.3)(@types/react@18.2.48)(react@18.2.0)
+      '@emotion/react': 11.11.3(@types/react@18.2.57)(react@18.2.0)
+      '@emotion/styled': 11.11.0(@emotion/react@11.11.3)(@types/react@18.2.57)(react@18.2.0)
       '@fontsource-variable/inter': 5.0.16
-      '@nanostores/react': 0.7.1(nanostores@0.9.5)(react@18.2.0)
-      chakra-react-select: 4.7.6(@chakra-ui/form-control@2.2.0)(@chakra-ui/icon@3.2.0)(@chakra-ui/layout@2.3.1)(@chakra-ui/media-query@3.3.0)(@chakra-ui/menu@2.2.1)(@chakra-ui/spinner@2.1.0)(@chakra-ui/system@2.6.2)(@emotion/react@11.11.3)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
+      '@nanostores/react': 0.7.2(nanostores@0.9.5)(react@18.2.0)
+      chakra-react-select: 4.7.6(@chakra-ui/form-control@2.2.0)(@chakra-ui/icon@3.2.0)(@chakra-ui/layout@2.3.1)(@chakra-ui/media-query@3.3.0)(@chakra-ui/menu@2.2.1)(@chakra-ui/spinner@2.1.0)(@chakra-ui/system@2.6.2)(@emotion/react@11.11.3)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
       framer-motion: 10.18.0(react-dom@18.2.0)(react@18.2.0)
       lodash-es: 4.17.21
       nanostores: 0.9.5
@@ -3642,9 +3789,9 @@ packages:
       overlayscrollbars-react: 0.5.4(overlayscrollbars@2.5.0)(react@18.2.0)
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
-      react-i18next: 14.0.5(i18next@23.7.16)(react-dom@18.2.0)(react@18.2.0)
+      react-i18next: 14.0.5(i18next@23.9.0)(react-dom@18.2.0)(react@18.2.0)
       react-icons: 5.0.1(react@18.2.0)
-      react-select: 5.8.0(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
+      react-select: 5.8.0(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
     transitivePeerDependencies:
       - '@chakra-ui/form-control'
       - '@chakra-ui/icon'
@@ -3697,9 +3844,9 @@ packages:
     resolution: {integrity: sha512-ok/BTPFzFKVMwO5eOHRrvnBVHdRy9IrsrW1GpMaQ9MCnilNLXQKmAX8s1YXDFaai9xJpac2ySzV0YeRRECr2Vw==}
     engines: {node: ^14.15.0 || ^16.10.0 || >=18.0.0}
     dependencies:
-      '@babel/core': 7.23.7
+      '@babel/core': 7.23.9
       '@jest/types': 29.6.3
-      '@jridgewell/trace-mapping': 0.3.21
+      '@jridgewell/trace-mapping': 0.3.22
       babel-plugin-istanbul: 6.1.1
       chalk: 4.1.2
       convert-source-map: 2.0.0
@@ -3722,7 +3869,7 @@ packages:
     dependencies:
       '@types/istanbul-lib-coverage': 2.0.6
       '@types/istanbul-reports': 3.0.4
-      '@types/node': 20.11.5
+      '@types/node': 20.11.19
       '@types/yargs': 16.0.9
       chalk: 4.1.2
     dev: true
@@ -3734,12 +3881,12 @@ packages:
       '@jest/schemas': 29.6.3
       '@types/istanbul-lib-coverage': 2.0.6
       '@types/istanbul-reports': 3.0.4
-      '@types/node': 20.11.5
+      '@types/node': 20.11.19
       '@types/yargs': 17.0.32
       chalk: 4.1.2
     dev: true
 
-  /@joshwooding/vite-plugin-react-docgen-typescript@0.3.0(typescript@5.3.3)(vite@5.0.12):
+  /@joshwooding/vite-plugin-react-docgen-typescript@0.3.0(typescript@5.3.3)(vite@5.1.3):
     resolution: {integrity: sha512-2D6y7fNvFmsLmRt6UCOFJPvFoPMJGT0Uh1Wg0RaigUp7kdQPs6yYn8Dmx6GZkOH/NW0yMTwRz/p0SRMMRo50vA==}
     peerDependencies:
       typescript: '>= 4.3.x'
@@ -3753,7 +3900,7 @@ packages:
       magic-string: 0.27.0
       react-docgen-typescript: 2.2.2(typescript@5.3.3)
       typescript: 5.3.3
-      vite: 5.0.12(@types/node@20.11.5)
+      vite: 5.1.3(@types/node@20.11.19)
     dev: true
 
   /@jridgewell/gen-mapping@0.3.3:
@@ -3762,11 +3909,11 @@ packages:
     dependencies:
       '@jridgewell/set-array': 1.1.2
       '@jridgewell/sourcemap-codec': 1.4.15
-      '@jridgewell/trace-mapping': 0.3.21
+      '@jridgewell/trace-mapping': 0.3.22
     dev: true
 
-  /@jridgewell/resolve-uri@3.1.1:
-    resolution: {integrity: sha512-dSYZh7HhCDtCKm4QakX0xFpsRDqjjtZf/kjI/v3T3Nwt5r8/qz/M19F9ySyOqU94SXBmeG9ttTul+YnR4LOxFA==}
+  /@jridgewell/resolve-uri@3.1.2:
+    resolution: {integrity: sha512-bRISgCIjP20/tbWSPWMEi54QVPRZExkuD9lJL+UIxUKtwVJA8wW1Trb1jMs1RFXo1CBTNZ/5hpC9QvmKWdopKw==}
     engines: {node: '>=6.0.0'}
     dev: true
 
@@ -3778,10 +3925,10 @@ packages:
   /@jridgewell/sourcemap-codec@1.4.15:
     resolution: {integrity: sha512-eF2rxCRulEKXHTRiDrDy6erMYWqNw4LPdQ8UQA4huuxaQsVeRPFl2oM8oDGxMFhJUWZf9McpLtJasDDZb/Bpeg==}
 
-  /@jridgewell/trace-mapping@0.3.21:
-    resolution: {integrity: sha512-SRfKmRe1KvYnxjEMtxEr+J4HIeMX5YBg/qhRHpxEIGjhX1rshcHlnFUE9K0GazhVKWM7B+nARSkV8LuvJdJ5/g==}
+  /@jridgewell/trace-mapping@0.3.22:
+    resolution: {integrity: sha512-Wf963MzWtA2sjrNt+g18IAln9lKnlRp+K2eH4jjIoF1wYeq3aMREpG09xhlhdzS0EjwU7qmUJYangWa+151vZw==}
     dependencies:
-      '@jridgewell/resolve-uri': 3.1.1
+      '@jridgewell/resolve-uri': 3.1.2
       '@jridgewell/sourcemap-codec': 1.4.15
     dev: true
 
@@ -3804,29 +3951,29 @@ packages:
     peerDependencies:
       react: '>=16'
     dependencies:
-      '@types/mdx': 2.0.10
-      '@types/react': 18.2.48
+      '@types/mdx': 2.0.11
+      '@types/react': 18.2.57
       react: 18.2.0
     dev: true
 
-  /@microsoft/api-extractor-model@7.28.3(@types/node@20.11.5):
+  /@microsoft/api-extractor-model@7.28.3(@types/node@20.11.19):
     resolution: {integrity: sha512-wT/kB2oDbdZXITyDh2SQLzaWwTOFbV326fP0pUwNW00WeliARs0qjmXBWmGWardEzp2U3/axkO3Lboqun6vrig==}
     dependencies:
       '@microsoft/tsdoc': 0.14.2
       '@microsoft/tsdoc-config': 0.16.2
-      '@rushstack/node-core-library': 3.62.0(@types/node@20.11.5)
+      '@rushstack/node-core-library': 3.62.0(@types/node@20.11.19)
     transitivePeerDependencies:
       - '@types/node'
     dev: true
 
-  /@microsoft/api-extractor@7.39.0(@types/node@20.11.5):
+  /@microsoft/api-extractor@7.39.0(@types/node@20.11.19):
     resolution: {integrity: sha512-PuXxzadgnvp+wdeZFPonssRAj/EW4Gm4s75TXzPk09h3wJ8RS3x7typf95B4vwZRrPTQBGopdUl+/vHvlPdAcg==}
     hasBin: true
     dependencies:
-      '@microsoft/api-extractor-model': 7.28.3(@types/node@20.11.5)
+      '@microsoft/api-extractor-model': 7.28.3(@types/node@20.11.19)
       '@microsoft/tsdoc': 0.14.2
       '@microsoft/tsdoc-config': 0.16.2
-      '@rushstack/node-core-library': 3.62.0(@types/node@20.11.5)
+      '@rushstack/node-core-library': 3.62.0(@types/node@20.11.19)
       '@rushstack/rig-package': 0.5.1
       '@rushstack/ts-command-line': 4.17.1
       colors: 1.2.5
@@ -3852,11 +3999,22 @@ packages:
     resolution: {integrity: sha512-9b8mPpKrfeGRuhFH5iO1iwCLeIIsV6+H1sRfxbkoGXIyQE2BTsPd9zqSqQJ+pv5sJ/hT5M1zvOFL02MnEezFug==}
     dev: true
 
-  /@nanostores/react@0.7.1(nanostores@0.9.5)(react@18.2.0):
-    resolution: {integrity: sha512-EXQg9N4MdI4eJQz/AZLIx3hxQ6BuBmV4Q55bCd5YCSgEOAW7tGTsIZxpRXxvxLXzflNvHTBvfrDNY38TlSVBkQ==}
-    engines: {node: ^16.0.0 || ^18.0.0 || >=20.0.0}
+  /@nanostores/react@0.7.2(nanostores@0.10.0)(react@18.2.0):
+    resolution: {integrity: sha512-e3OhHJFv3NMSFYDgREdlAQqkyBTHJM91s31kOZ4OvZwJKdFk5BLk0MLbh51EOGUz9QGX2aCHfy1RvweSi7fgwA==}
+    engines: {node: ^18.0.0 || >=20.0.0}
     peerDependencies:
-      nanostores: ^0.9.0
+      nanostores: ^0.9.0 || ^0.10.0
+      react: '>=18.0.0'
+    dependencies:
+      nanostores: 0.10.0
+      react: 18.2.0
+    dev: false
+
+  /@nanostores/react@0.7.2(nanostores@0.9.5)(react@18.2.0):
+    resolution: {integrity: sha512-e3OhHJFv3NMSFYDgREdlAQqkyBTHJM91s31kOZ4OvZwJKdFk5BLk0MLbh51EOGUz9QGX2aCHfy1RvweSi7fgwA==}
+    engines: {node: ^18.0.0 || >=20.0.0}
+    peerDependencies:
+      nanostores: ^0.9.0 || ^0.10.0
       react: '>=18.0.0'
     dependencies:
       nanostores: 0.9.5
@@ -3889,7 +4047,7 @@ packages:
     engines: {node: '>= 8'}
     dependencies:
       '@nodelib/fs.scandir': 2.1.5
-      fastq: 1.16.0
+      fastq: 1.17.1
     dev: true
 
   /@pkgjs/parseargs@0.11.0:
@@ -3906,16 +4064,16 @@ packages:
   /@radix-ui/number@1.0.1:
     resolution: {integrity: sha512-T5gIdVO2mmPW3NNhjNgEP3cqMXjXL9UbO0BzWcXfvdBs+BohbQxvd/K5hSVKmn9/lbTdsQVKbUcP5WLCwvUbBg==}
     dependencies:
-      '@babel/runtime': 7.23.8
+      '@babel/runtime': 7.23.9
     dev: true
 
   /@radix-ui/primitive@1.0.1:
     resolution: {integrity: sha512-yQ8oGX2GVsEYMWGxcovu1uGWPCxV5BFfeeYxqPmuAzUyLT9qmaMXSAhXpb0WrspIeqYzdJpkh2vHModJPgRIaw==}
     dependencies:
-      '@babel/runtime': 7.23.8
+      '@babel/runtime': 7.23.9
     dev: true
 
-  /@radix-ui/react-arrow@1.0.3(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0):
+  /@radix-ui/react-arrow@1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-wSP+pHsB/jQRaL6voubsQ/ZlrGBHHrOjmBnr19hxYgtS0WvAFwZhK2WP/YY5yF9uKECCEEDGxuLxq1NBK51wFA==}
     peerDependencies:
       '@types/react': '*'
@@ -3928,15 +4086,15 @@ packages:
       '@types/react-dom':
         optional: true
     dependencies:
-      '@babel/runtime': 7.23.8
-      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@types/react': 18.2.48
-      '@types/react-dom': 18.2.18
+      '@babel/runtime': 7.23.9
+      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@types/react': 18.2.57
+      '@types/react-dom': 18.2.19
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     dev: true
 
-  /@radix-ui/react-collection@1.0.3(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0):
+  /@radix-ui/react-collection@1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-3SzW+0PW7yBBoQlT8wNcGtaxaD0XSu0uLUFgrtHY08Acx05TaHaOmVLR73c0j/cqpDy53KBMO7s0dx2wmOIDIA==}
     peerDependencies:
       '@types/react': '*'
@@ -3949,18 +4107,18 @@ packages:
       '@types/react-dom':
         optional: true
     dependencies:
-      '@babel/runtime': 7.23.8
-      '@radix-ui/react-compose-refs': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@radix-ui/react-context': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-slot': 1.0.2(@types/react@18.2.48)(react@18.2.0)
-      '@types/react': 18.2.48
-      '@types/react-dom': 18.2.18
+      '@babel/runtime': 7.23.9
+      '@radix-ui/react-compose-refs': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@radix-ui/react-context': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-slot': 1.0.2(@types/react@18.2.57)(react@18.2.0)
+      '@types/react': 18.2.57
+      '@types/react-dom': 18.2.19
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     dev: true
 
-  /@radix-ui/react-compose-refs@1.0.1(@types/react@18.2.48)(react@18.2.0):
+  /@radix-ui/react-compose-refs@1.0.1(@types/react@18.2.57)(react@18.2.0):
     resolution: {integrity: sha512-fDSBgd44FKHa1FRMU59qBMPFcl2PZE+2nmqunj+BWFyYYjnhIDWL2ItDs3rrbJDQOtzt5nIebLCQc4QRfz6LJw==}
     peerDependencies:
       '@types/react': '*'
@@ -3969,12 +4127,12 @@ packages:
       '@types/react':
         optional: true
     dependencies:
-      '@babel/runtime': 7.23.8
-      '@types/react': 18.2.48
+      '@babel/runtime': 7.23.9
+      '@types/react': 18.2.57
       react: 18.2.0
     dev: true
 
-  /@radix-ui/react-context@1.0.1(@types/react@18.2.48)(react@18.2.0):
+  /@radix-ui/react-context@1.0.1(@types/react@18.2.57)(react@18.2.0):
     resolution: {integrity: sha512-ebbrdFoYTcuZ0v4wG5tedGnp9tzcV8awzsxYph7gXUyvnNLuTIcCk1q17JEbnVhXAKG9oX3KtchwiMIAYp9NLg==}
     peerDependencies:
       '@types/react': '*'
@@ -3983,12 +4141,12 @@ packages:
       '@types/react':
         optional: true
     dependencies:
-      '@babel/runtime': 7.23.8
-      '@types/react': 18.2.48
+      '@babel/runtime': 7.23.9
+      '@types/react': 18.2.57
       react: 18.2.0
     dev: true
 
-  /@radix-ui/react-direction@1.0.1(@types/react@18.2.48)(react@18.2.0):
+  /@radix-ui/react-direction@1.0.1(@types/react@18.2.57)(react@18.2.0):
     resolution: {integrity: sha512-RXcvnXgyvYvBEOhCBuddKecVkoMiI10Jcm5cTI7abJRAHYfFxeu+FBQs/DvdxSYucxR5mna0dNsL6QFlds5TMA==}
     peerDependencies:
       '@types/react': '*'
@@ -3997,12 +4155,12 @@ packages:
       '@types/react':
         optional: true
     dependencies:
-      '@babel/runtime': 7.23.8
-      '@types/react': 18.2.48
+      '@babel/runtime': 7.23.9
+      '@types/react': 18.2.57
       react: 18.2.0
     dev: true
 
-  /@radix-ui/react-dismissable-layer@1.0.4(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0):
+  /@radix-ui/react-dismissable-layer@1.0.4(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-7UpBa/RKMoHJYjie1gkF1DlK8l1fdU/VKDpoS3rCCo8YBJR294GwcEHyxHw72yvphJ7ld0AXEcSLAzY2F/WyCg==}
     peerDependencies:
       '@types/react': '*'
@@ -4015,19 +4173,19 @@ packages:
       '@types/react-dom':
         optional: true
     dependencies:
-      '@babel/runtime': 7.23.8
+      '@babel/runtime': 7.23.9
       '@radix-ui/primitive': 1.0.1
-      '@radix-ui/react-compose-refs': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-use-callback-ref': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@radix-ui/react-use-escape-keydown': 1.0.3(@types/react@18.2.48)(react@18.2.0)
-      '@types/react': 18.2.48
-      '@types/react-dom': 18.2.18
+      '@radix-ui/react-compose-refs': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-use-callback-ref': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@radix-ui/react-use-escape-keydown': 1.0.3(@types/react@18.2.57)(react@18.2.0)
+      '@types/react': 18.2.57
+      '@types/react-dom': 18.2.19
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     dev: true
 
-  /@radix-ui/react-focus-guards@1.0.1(@types/react@18.2.48)(react@18.2.0):
+  /@radix-ui/react-focus-guards@1.0.1(@types/react@18.2.57)(react@18.2.0):
     resolution: {integrity: sha512-Rect2dWbQ8waGzhMavsIbmSVCgYxkXLxxR3ZvCX79JOglzdEy4JXMb98lq4hPxUbLr77nP0UOGf4rcMU+s1pUA==}
     peerDependencies:
       '@types/react': '*'
@@ -4036,12 +4194,12 @@ packages:
       '@types/react':
         optional: true
     dependencies:
-      '@babel/runtime': 7.23.8
-      '@types/react': 18.2.48
+      '@babel/runtime': 7.23.9
+      '@types/react': 18.2.57
       react: 18.2.0
     dev: true
 
-  /@radix-ui/react-focus-scope@1.0.3(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0):
+  /@radix-ui/react-focus-scope@1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-upXdPfqI4islj2CslyfUBNlaJCPybbqRHAi1KER7Isel9Q2AtSJ0zRBZv8mWQiFXD2nyAJ4BhC3yXgZ6kMBSrQ==}
     peerDependencies:
       '@types/react': '*'
@@ -4054,17 +4212,17 @@ packages:
       '@types/react-dom':
         optional: true
     dependencies:
-      '@babel/runtime': 7.23.8
-      '@radix-ui/react-compose-refs': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-use-callback-ref': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@types/react': 18.2.48
-      '@types/react-dom': 18.2.18
+      '@babel/runtime': 7.23.9
+      '@radix-ui/react-compose-refs': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-use-callback-ref': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@types/react': 18.2.57
+      '@types/react-dom': 18.2.19
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     dev: true
 
-  /@radix-ui/react-id@1.0.1(@types/react@18.2.48)(react@18.2.0):
+  /@radix-ui/react-id@1.0.1(@types/react@18.2.57)(react@18.2.0):
     resolution: {integrity: sha512-tI7sT/kqYp8p96yGWY1OAnLHrqDgzHefRBKQ2YAkBS5ja7QLcZ9Z/uY7bEjPUatf8RomoXM8/1sMj1IJaE5UzQ==}
     peerDependencies:
       '@types/react': '*'
@@ -4073,13 +4231,13 @@ packages:
       '@types/react':
         optional: true
     dependencies:
-      '@babel/runtime': 7.23.8
-      '@radix-ui/react-use-layout-effect': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@types/react': 18.2.48
+      '@babel/runtime': 7.23.9
+      '@radix-ui/react-use-layout-effect': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@types/react': 18.2.57
       react: 18.2.0
     dev: true
 
-  /@radix-ui/react-popper@1.1.2(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0):
+  /@radix-ui/react-popper@1.1.2(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-1CnGGfFi/bbqtJZZ0P/NQY20xdG3E0LALJaLUEoKwPLwl6PPPfbeiCqMVQnhoFRAxjJj4RpBRJzDmUgsex2tSg==}
     peerDependencies:
       '@types/react': '*'
@@ -4092,24 +4250,24 @@ packages:
       '@types/react-dom':
         optional: true
     dependencies:
-      '@babel/runtime': 7.23.8
-      '@floating-ui/react-dom': 2.0.6(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-arrow': 1.0.3(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-compose-refs': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@radix-ui/react-context': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-use-callback-ref': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@radix-ui/react-use-layout-effect': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@radix-ui/react-use-rect': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@radix-ui/react-use-size': 1.0.1(@types/react@18.2.48)(react@18.2.0)
+      '@babel/runtime': 7.23.9
+      '@floating-ui/react-dom': 2.0.8(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-arrow': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-compose-refs': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@radix-ui/react-context': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-use-callback-ref': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@radix-ui/react-use-layout-effect': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@radix-ui/react-use-rect': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@radix-ui/react-use-size': 1.0.1(@types/react@18.2.57)(react@18.2.0)
       '@radix-ui/rect': 1.0.1
-      '@types/react': 18.2.48
-      '@types/react-dom': 18.2.18
+      '@types/react': 18.2.57
+      '@types/react-dom': 18.2.19
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     dev: true
 
-  /@radix-ui/react-portal@1.0.3(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0):
+  /@radix-ui/react-portal@1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-xLYZeHrWoPmA5mEKEfZZevoVRK/Q43GfzRXkWV6qawIWWK8t6ifIiLQdd7rmQ4Vk1bmI21XhqF9BN3jWf+phpA==}
     peerDependencies:
       '@types/react': '*'
@@ -4122,15 +4280,15 @@ packages:
       '@types/react-dom':
         optional: true
     dependencies:
-      '@babel/runtime': 7.23.8
-      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@types/react': 18.2.48
-      '@types/react-dom': 18.2.18
+      '@babel/runtime': 7.23.9
+      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@types/react': 18.2.57
+      '@types/react-dom': 18.2.19
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     dev: true
 
-  /@radix-ui/react-primitive@1.0.3(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0):
+  /@radix-ui/react-primitive@1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-yi58uVyoAcK/Nq1inRY56ZSjKypBNKTa/1mcL8qdl6oJeEaDbOldlzrGn7P6Q3Id5d+SYNGc5AJgc4vGhjs5+g==}
     peerDependencies:
       '@types/react': '*'
@@ -4143,15 +4301,15 @@ packages:
       '@types/react-dom':
         optional: true
     dependencies:
-      '@babel/runtime': 7.23.8
-      '@radix-ui/react-slot': 1.0.2(@types/react@18.2.48)(react@18.2.0)
-      '@types/react': 18.2.48
-      '@types/react-dom': 18.2.18
+      '@babel/runtime': 7.23.9
+      '@radix-ui/react-slot': 1.0.2(@types/react@18.2.57)(react@18.2.0)
+      '@types/react': 18.2.57
+      '@types/react-dom': 18.2.19
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     dev: true
 
-  /@radix-ui/react-roving-focus@1.0.4(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0):
+  /@radix-ui/react-roving-focus@1.0.4(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-2mUg5Mgcu001VkGy+FfzZyzbmuUWzgWkj3rvv4yu+mLw03+mTzbxZHvfcGyFp2b8EkQeMkpRQ5FiA2Vr2O6TeQ==}
     peerDependencies:
       '@types/react': '*'
@@ -4164,23 +4322,23 @@ packages:
       '@types/react-dom':
         optional: true
     dependencies:
-      '@babel/runtime': 7.23.8
+      '@babel/runtime': 7.23.9
       '@radix-ui/primitive': 1.0.1
-      '@radix-ui/react-collection': 1.0.3(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-compose-refs': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@radix-ui/react-context': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@radix-ui/react-direction': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@radix-ui/react-id': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-use-callback-ref': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@radix-ui/react-use-controllable-state': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@types/react': 18.2.48
-      '@types/react-dom': 18.2.18
+      '@radix-ui/react-collection': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-compose-refs': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@radix-ui/react-context': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@radix-ui/react-direction': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@radix-ui/react-id': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-use-callback-ref': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@radix-ui/react-use-controllable-state': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@types/react': 18.2.57
+      '@types/react-dom': 18.2.19
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     dev: true
 
-  /@radix-ui/react-select@1.2.2(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0):
+  /@radix-ui/react-select@1.2.2(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-zI7McXr8fNaSrUY9mZe4x/HC0jTLY9fWNhO1oLWYMQGDXuV4UCivIGTxwioSzO0ZCYX9iSLyWmAh/1TOmX3Cnw==}
     peerDependencies:
       '@types/react': '*'
@@ -4193,35 +4351,35 @@ packages:
       '@types/react-dom':
         optional: true
     dependencies:
-      '@babel/runtime': 7.23.8
+      '@babel/runtime': 7.23.9
       '@radix-ui/number': 1.0.1
       '@radix-ui/primitive': 1.0.1
-      '@radix-ui/react-collection': 1.0.3(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-compose-refs': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@radix-ui/react-context': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@radix-ui/react-direction': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@radix-ui/react-dismissable-layer': 1.0.4(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-focus-guards': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@radix-ui/react-focus-scope': 1.0.3(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-id': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@radix-ui/react-popper': 1.1.2(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-portal': 1.0.3(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-slot': 1.0.2(@types/react@18.2.48)(react@18.2.0)
-      '@radix-ui/react-use-callback-ref': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@radix-ui/react-use-controllable-state': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@radix-ui/react-use-layout-effect': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@radix-ui/react-use-previous': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@radix-ui/react-visually-hidden': 1.0.3(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@types/react': 18.2.48
-      '@types/react-dom': 18.2.18
+      '@radix-ui/react-collection': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-compose-refs': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@radix-ui/react-context': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@radix-ui/react-direction': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@radix-ui/react-dismissable-layer': 1.0.4(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-focus-guards': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@radix-ui/react-focus-scope': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-id': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@radix-ui/react-popper': 1.1.2(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-portal': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-slot': 1.0.2(@types/react@18.2.57)(react@18.2.0)
+      '@radix-ui/react-use-callback-ref': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@radix-ui/react-use-controllable-state': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@radix-ui/react-use-layout-effect': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@radix-ui/react-use-previous': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@radix-ui/react-visually-hidden': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@types/react': 18.2.57
+      '@types/react-dom': 18.2.19
       aria-hidden: 1.2.3
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
-      react-remove-scroll: 2.5.5(@types/react@18.2.48)(react@18.2.0)
+      react-remove-scroll: 2.5.5(@types/react@18.2.57)(react@18.2.0)
     dev: true
 
-  /@radix-ui/react-separator@1.0.3(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0):
+  /@radix-ui/react-separator@1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-itYmTy/kokS21aiV5+Z56MZB54KrhPgn6eHDKkFeOLR34HMN2s8PaN47qZZAGnvupcjxHaFZnW4pQEh0BvvVuw==}
     peerDependencies:
       '@types/react': '*'
@@ -4234,15 +4392,15 @@ packages:
       '@types/react-dom':
         optional: true
     dependencies:
-      '@babel/runtime': 7.23.8
-      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@types/react': 18.2.48
-      '@types/react-dom': 18.2.18
+      '@babel/runtime': 7.23.9
+      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@types/react': 18.2.57
+      '@types/react-dom': 18.2.19
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     dev: true
 
-  /@radix-ui/react-slot@1.0.2(@types/react@18.2.48)(react@18.2.0):
+  /@radix-ui/react-slot@1.0.2(@types/react@18.2.57)(react@18.2.0):
     resolution: {integrity: sha512-YeTpuq4deV+6DusvVUW4ivBgnkHwECUu0BiN43L5UCDFgdhsRUWAghhTF5MbvNTPzmiFOx90asDSUjWuCNapwg==}
     peerDependencies:
       '@types/react': '*'
@@ -4251,13 +4409,13 @@ packages:
       '@types/react':
         optional: true
     dependencies:
-      '@babel/runtime': 7.23.8
-      '@radix-ui/react-compose-refs': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@types/react': 18.2.48
+      '@babel/runtime': 7.23.9
+      '@radix-ui/react-compose-refs': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@types/react': 18.2.57
       react: 18.2.0
     dev: true
 
-  /@radix-ui/react-toggle-group@1.0.4(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0):
+  /@radix-ui/react-toggle-group@1.0.4(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-Uaj/M/cMyiyT9Bx6fOZO0SAG4Cls0GptBWiBmBxofmDbNVnYYoyRWj/2M/6VCi/7qcXFWnHhRUfdfZFvvkuu8A==}
     peerDependencies:
       '@types/react': '*'
@@ -4270,21 +4428,21 @@ packages:
       '@types/react-dom':
         optional: true
     dependencies:
-      '@babel/runtime': 7.23.8
+      '@babel/runtime': 7.23.9
       '@radix-ui/primitive': 1.0.1
-      '@radix-ui/react-context': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@radix-ui/react-direction': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-roving-focus': 1.0.4(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-toggle': 1.0.3(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-use-controllable-state': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@types/react': 18.2.48
-      '@types/react-dom': 18.2.18
+      '@radix-ui/react-context': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@radix-ui/react-direction': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-roving-focus': 1.0.4(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-toggle': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-use-controllable-state': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@types/react': 18.2.57
+      '@types/react-dom': 18.2.19
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     dev: true
 
-  /@radix-ui/react-toggle@1.0.3(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0):
+  /@radix-ui/react-toggle@1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-Pkqg3+Bc98ftZGsl60CLANXQBBQ4W3mTFS9EJvNxKMZ7magklKV69/id1mlAlOFDDfHvlCms0fx8fA4CMKDJHg==}
     peerDependencies:
       '@types/react': '*'
@@ -4297,17 +4455,17 @@ packages:
       '@types/react-dom':
         optional: true
     dependencies:
-      '@babel/runtime': 7.23.8
+      '@babel/runtime': 7.23.9
       '@radix-ui/primitive': 1.0.1
-      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-use-controllable-state': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@types/react': 18.2.48
-      '@types/react-dom': 18.2.18
+      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-use-controllable-state': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@types/react': 18.2.57
+      '@types/react-dom': 18.2.19
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     dev: true
 
-  /@radix-ui/react-toolbar@1.0.4(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0):
+  /@radix-ui/react-toolbar@1.0.4(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-tBgmM/O7a07xbaEkYJWYTXkIdU/1pW4/KZORR43toC/4XWyBCURK0ei9kMUdp+gTPPKBgYLxXmRSH1EVcIDp8Q==}
     peerDependencies:
       '@types/react': '*'
@@ -4320,21 +4478,21 @@ packages:
       '@types/react-dom':
         optional: true
     dependencies:
-      '@babel/runtime': 7.23.8
+      '@babel/runtime': 7.23.9
       '@radix-ui/primitive': 1.0.1
-      '@radix-ui/react-context': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@radix-ui/react-direction': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-roving-focus': 1.0.4(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-separator': 1.0.3(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-toggle-group': 1.0.4(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@types/react': 18.2.48
-      '@types/react-dom': 18.2.18
+      '@radix-ui/react-context': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@radix-ui/react-direction': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-roving-focus': 1.0.4(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-separator': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-toggle-group': 1.0.4(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@types/react': 18.2.57
+      '@types/react-dom': 18.2.19
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     dev: true
 
-  /@radix-ui/react-use-callback-ref@1.0.1(@types/react@18.2.48)(react@18.2.0):
+  /@radix-ui/react-use-callback-ref@1.0.1(@types/react@18.2.57)(react@18.2.0):
     resolution: {integrity: sha512-D94LjX4Sp0xJFVaoQOd3OO9k7tpBYNOXdVhkltUbGv2Qb9OXdrg/CpsjlZv7ia14Sylv398LswWBVVu5nqKzAQ==}
     peerDependencies:
       '@types/react': '*'
@@ -4343,12 +4501,12 @@ packages:
       '@types/react':
         optional: true
     dependencies:
-      '@babel/runtime': 7.23.8
-      '@types/react': 18.2.48
+      '@babel/runtime': 7.23.9
+      '@types/react': 18.2.57
       react: 18.2.0
     dev: true
 
-  /@radix-ui/react-use-controllable-state@1.0.1(@types/react@18.2.48)(react@18.2.0):
+  /@radix-ui/react-use-controllable-state@1.0.1(@types/react@18.2.57)(react@18.2.0):
     resolution: {integrity: sha512-Svl5GY5FQeN758fWKrjM6Qb7asvXeiZltlT4U2gVfl8Gx5UAv2sMR0LWo8yhsIZh2oQ0eFdZ59aoOOMV7b47VA==}
     peerDependencies:
       '@types/react': '*'
@@ -4357,13 +4515,13 @@ packages:
       '@types/react':
         optional: true
     dependencies:
-      '@babel/runtime': 7.23.8
-      '@radix-ui/react-use-callback-ref': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@types/react': 18.2.48
+      '@babel/runtime': 7.23.9
+      '@radix-ui/react-use-callback-ref': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@types/react': 18.2.57
       react: 18.2.0
     dev: true
 
-  /@radix-ui/react-use-escape-keydown@1.0.3(@types/react@18.2.48)(react@18.2.0):
+  /@radix-ui/react-use-escape-keydown@1.0.3(@types/react@18.2.57)(react@18.2.0):
     resolution: {integrity: sha512-vyL82j40hcFicA+M4Ex7hVkB9vHgSse1ZWomAqV2Je3RleKGO5iM8KMOEtfoSB0PnIelMd2lATjTGMYqN5ylTg==}
     peerDependencies:
       '@types/react': '*'
@@ -4372,13 +4530,13 @@ packages:
       '@types/react':
         optional: true
     dependencies:
-      '@babel/runtime': 7.23.8
-      '@radix-ui/react-use-callback-ref': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@types/react': 18.2.48
+      '@babel/runtime': 7.23.9
+      '@radix-ui/react-use-callback-ref': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@types/react': 18.2.57
       react: 18.2.0
     dev: true
 
-  /@radix-ui/react-use-layout-effect@1.0.1(@types/react@18.2.48)(react@18.2.0):
+  /@radix-ui/react-use-layout-effect@1.0.1(@types/react@18.2.57)(react@18.2.0):
     resolution: {integrity: sha512-v/5RegiJWYdoCvMnITBkNNx6bCj20fiaJnWtRkU18yITptraXjffz5Qbn05uOiQnOvi+dbkznkoaMltz1GnszQ==}
     peerDependencies:
       '@types/react': '*'
@@ -4387,12 +4545,12 @@ packages:
       '@types/react':
         optional: true
     dependencies:
-      '@babel/runtime': 7.23.8
-      '@types/react': 18.2.48
+      '@babel/runtime': 7.23.9
+      '@types/react': 18.2.57
       react: 18.2.0
     dev: true
 
-  /@radix-ui/react-use-previous@1.0.1(@types/react@18.2.48)(react@18.2.0):
+  /@radix-ui/react-use-previous@1.0.1(@types/react@18.2.57)(react@18.2.0):
     resolution: {integrity: sha512-cV5La9DPwiQ7S0gf/0qiD6YgNqM5Fk97Kdrlc5yBcrF3jyEZQwm7vYFqMo4IfeHgJXsRaMvLABFtd0OVEmZhDw==}
     peerDependencies:
       '@types/react': '*'
@@ -4401,12 +4559,12 @@ packages:
       '@types/react':
         optional: true
     dependencies:
-      '@babel/runtime': 7.23.8
-      '@types/react': 18.2.48
+      '@babel/runtime': 7.23.9
+      '@types/react': 18.2.57
       react: 18.2.0
     dev: true
 
-  /@radix-ui/react-use-rect@1.0.1(@types/react@18.2.48)(react@18.2.0):
+  /@radix-ui/react-use-rect@1.0.1(@types/react@18.2.57)(react@18.2.0):
     resolution: {integrity: sha512-Cq5DLuSiuYVKNU8orzJMbl15TXilTnJKUCltMVQg53BQOF1/C5toAaGrowkgksdBQ9H+SRL23g0HDmg9tvmxXw==}
     peerDependencies:
       '@types/react': '*'
@@ -4415,13 +4573,13 @@ packages:
       '@types/react':
         optional: true
     dependencies:
-      '@babel/runtime': 7.23.8
+      '@babel/runtime': 7.23.9
       '@radix-ui/rect': 1.0.1
-      '@types/react': 18.2.48
+      '@types/react': 18.2.57
       react: 18.2.0
     dev: true
 
-  /@radix-ui/react-use-size@1.0.1(@types/react@18.2.48)(react@18.2.0):
+  /@radix-ui/react-use-size@1.0.1(@types/react@18.2.57)(react@18.2.0):
     resolution: {integrity: sha512-ibay+VqrgcaI6veAojjofPATwledXiSmX+C0KrBk/xgpX9rBzPV3OsfwlhQdUOFbh+LKQorLYT+xTXW9V8yd0g==}
     peerDependencies:
       '@types/react': '*'
@@ -4430,13 +4588,13 @@ packages:
       '@types/react':
         optional: true
     dependencies:
-      '@babel/runtime': 7.23.8
-      '@radix-ui/react-use-layout-effect': 1.0.1(@types/react@18.2.48)(react@18.2.0)
-      '@types/react': 18.2.48
+      '@babel/runtime': 7.23.9
+      '@radix-ui/react-use-layout-effect': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@types/react': 18.2.57
       react: 18.2.0
     dev: true
 
-  /@radix-ui/react-visually-hidden@1.0.3(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0):
+  /@radix-ui/react-visually-hidden@1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-D4w41yN5YRKtu464TLnByKzMDG/JlMPHtfZgQAu9v6mNakUqGUI9vUrfQKz8NK41VMm/xbZbh76NUTVtIYqOMA==}
     peerDependencies:
       '@types/react': '*'
@@ -4449,10 +4607,10 @@ packages:
       '@types/react-dom':
         optional: true
     dependencies:
-      '@babel/runtime': 7.23.8
-      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@types/react': 18.2.48
-      '@types/react-dom': 18.2.18
+      '@babel/runtime': 7.23.9
+      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@types/react': 18.2.57
+      '@types/react-dom': 18.2.19
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     dev: true
@@ -4460,43 +4618,43 @@ packages:
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     resolution: {integrity: sha512-fyrgCaedtvMg9NK3en0pnOYJdtfwxUcNolezkNPUsoX57X8oQk+NkqcvzHXD2uKNij6GXmWU9NDru2IWjrO4BQ==}
     dependencies:
-      '@babel/runtime': 7.23.8
+      '@babel/runtime': 7.23.9
     dev: true
 
-  /@reactflow/background@11.3.7(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0):
-    resolution: {integrity: sha512-PhkvoFtO/NXJgFtBvfbPwdR/6/dl25egQlFhKWS3T4aYa7rh80dvf6dF3t6+JXJS4q5ToYJizD2/n8/qylo1yQ==}
+  /@reactflow/background@11.3.9(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+    resolution: {integrity: sha512-byj/G9pEC8tN0wT/ptcl/LkEP/BBfa33/SvBkqE4XwyofckqF87lKp573qGlisfnsijwAbpDlf81PuFL41So4Q==}
     peerDependencies:
       react: '>=17'
       react-dom: '>=17'
     dependencies:
-      '@reactflow/core': 11.10.2(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
+      '@reactflow/core': 11.10.4(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
       classcat: 5.0.4
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
-      zustand: 4.4.7(@types/react@18.2.48)(react@18.2.0)
+      zustand: 4.5.1(@types/react@18.2.57)(react@18.2.0)
     transitivePeerDependencies:
       - '@types/react'
       - immer
     dev: false
 
-  /@reactflow/controls@11.2.7(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0):
-    resolution: {integrity: sha512-mugzVALH/SuKlVKk+JCRm1OXQ+p8e9+k8PCTIaqL+nBl+lPF8KA4uMm8ApsOvhuSAb2A80ezewpyvYHr0qSYVA==}
+  /@reactflow/controls@11.2.9(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+    resolution: {integrity: sha512-e8nWplbYfOn83KN1BrxTXS17+enLyFnjZPbyDgHSRLtI5ZGPKF/8iRXV+VXb2LFVzlu4Wh3la/pkxtfP/0aguA==}
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       react-dom: '>=17'
     dependencies:
-      '@reactflow/core': 11.10.2(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
+      '@reactflow/core': 11.10.4(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
       classcat: 5.0.4
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
-      zustand: 4.4.7(@types/react@18.2.48)(react@18.2.0)
+      zustand: 4.5.1(@types/react@18.2.57)(react@18.2.0)
     transitivePeerDependencies:
       - '@types/react'
       - immer
     dev: false
 
-  /@reactflow/core@11.10.2(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0):
-    resolution: {integrity: sha512-/cbTxtFpfkIGReSVkcnQhS4Jx4VFY2AhPlJ5n0sbPtnR7OWowF9zodh5Yyzr4j1NOUoBgJ9h+UqGEwwY2dbAlw==}
+  /@reactflow/core@11.10.4(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+    resolution: {integrity: sha512-j3i9b2fsTX/sBbOm+RmNzYEFWbNx4jGWGuGooh2r1jQaE2eV+TLJgiG/VNOp0q5mBl9f6g1IXs3Gm86S9JfcGw==}
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       react-dom: '>=17'
@@ -4511,19 +4669,19 @@ packages:
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       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
-      zustand: 4.4.7(@types/react@18.2.48)(react@18.2.0)
+      zustand: 4.5.1(@types/react@18.2.57)(react@18.2.0)
     transitivePeerDependencies:
       - '@types/react'
       - immer
     dev: false
 
-  /@reactflow/minimap@11.7.7(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0):
-    resolution: {integrity: sha512-Pwqw31tJ663cJur6ypqyJU33nPckvTepmz96erdQZoHsfOyLmFj4nXT7afC30DJ48lp0nfNsw+028mlf7f/h4g==}
+  /@reactflow/minimap@11.7.9(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+    resolution: {integrity: sha512-le95jyTtt3TEtJ1qa7tZ5hyM4S7gaEQkW43cixcMOZLu33VAdc2aCpJg/fXcRrrf7moN2Mbl9WIMNXUKsp5ILA==}
     peerDependencies:
       react: '>=17'
       react-dom: '>=17'
     dependencies:
-      '@reactflow/core': 11.10.2(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
+      '@reactflow/core': 11.10.4(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
       '@types/d3-selection': 3.0.10
       '@types/d3-zoom': 3.0.8
       classcat: 5.0.4
@@ -4531,48 +4689,48 @@ packages:
       d3-zoom: 3.0.0
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
-      zustand: 4.4.7(@types/react@18.2.48)(react@18.2.0)
+      zustand: 4.5.1(@types/react@18.2.57)(react@18.2.0)
     transitivePeerDependencies:
       - '@types/react'
       - immer
     dev: false
 
-  /@reactflow/node-resizer@2.2.7(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0):
-    resolution: {integrity: sha512-BMBstmWNiklHnnAjHu8irkiPQ8/k8nnjzqlTql4acbVhD6Tsdxx/t/saOkELmfQODqGZNiPw9+pHcAHgtE6oNQ==}
+  /@reactflow/node-resizer@2.2.9(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+    resolution: {integrity: sha512-HfickMm0hPDIHt9qH997nLdgLt0kayQyslKE0RS/GZvZ4UMQJlx/NRRyj5y47Qyg0NnC66KYOQWDM9LLzRTnUg==}
     peerDependencies:
       react: '>=17'
       react-dom: '>=17'
     dependencies:
-      '@reactflow/core': 11.10.2(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
+      '@reactflow/core': 11.10.4(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
       classcat: 5.0.4
       d3-drag: 3.0.0
       d3-selection: 3.0.0
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
-      zustand: 4.4.7(@types/react@18.2.48)(react@18.2.0)
+      zustand: 4.5.1(@types/react@18.2.57)(react@18.2.0)
     transitivePeerDependencies:
       - '@types/react'
       - immer
     dev: false
 
-  /@reactflow/node-toolbar@1.3.7(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0):
-    resolution: {integrity: sha512-75moEQKg23YKA3A2DNSFhq719ZPmby5mpwOD+NO7ZffJ88oMS/2eY8l8qpA3hvb1PTBHDxyKazhJirW+f4t0Wg==}
+  /@reactflow/node-toolbar@1.3.9(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+    resolution: {integrity: sha512-VmgxKmToax4sX1biZ9LXA7cj/TBJ+E5cklLGwquCCVVxh+lxpZGTBF3a5FJGVHiUNBBtFsC8ldcSZIK4cAlQww==}
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       react-dom: '>=17'
     dependencies:
-      '@reactflow/core': 11.10.2(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
+      '@reactflow/core': 11.10.4(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
       classcat: 5.0.4
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
-      zustand: 4.4.7(@types/react@18.2.48)(react@18.2.0)
+      zustand: 4.5.1(@types/react@18.2.57)(react@18.2.0)
     transitivePeerDependencies:
       - '@types/react'
       - immer
     dev: false
 
-  /@reduxjs/toolkit@2.0.1(react-redux@9.1.0)(react@18.2.0):
-    resolution: {integrity: sha512-fxIjrR9934cmS8YXIGd9e7s1XRsEU++aFc9DVNMFMRTM5Vtsg2DCRMj21eslGtDt43IUf9bJL3h5bwUlZleibA==}
+  /@reduxjs/toolkit@2.2.1(react-redux@9.1.0)(react@18.2.0):
+    resolution: {integrity: sha512-8CREoqJovQW/5I4yvvijm/emUiCCmcs4Ev4XPWd4mizSO+dD3g5G6w34QK5AGeNrSH7qM8Fl66j4vuV7dpOdkw==}
     peerDependencies:
       react: ^16.9.0 || ^17.0.0 || ^18
       react-redux: ^7.2.1 || ^8.1.3 || ^9.0.0
@@ -4584,10 +4742,10 @@ packages:
     dependencies:
       immer: 10.0.3
       react: 18.2.0
-      react-redux: 9.1.0(@types/react@18.2.48)(react@18.2.0)(redux@5.0.1)
+      react-redux: 9.1.0(@types/react@18.2.57)(react@18.2.0)(redux@5.0.1)
       redux: 5.0.1
       redux-thunk: 3.1.0(redux@5.0.1)
-      reselect: 5.0.1(patch_hash=kvbgwzjyy4x4fnh7znyocvb75q)
+      reselect: 5.1.0
     dev: false
 
   /@roarr/browser-log-writer@1.3.0:
@@ -4621,111 +4779,111 @@ packages:
       picomatch: 2.3.1
     dev: true
 
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+  /@rollup/rollup-android-arm-eabi@4.12.0:
+    resolution: {integrity: sha512-+ac02NL/2TCKRrJu2wffk1kZ+RyqxVUlbjSagNgPm94frxtr+XDL12E5Ll1enWskLrtrZ2r8L3wED1orIibV/w==}
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     os: [android]
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     optional: true
 
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+  /@rollup/rollup-android-arm64@4.12.0:
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     os: [android]
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     dev: true
     optional: true
 
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+  /@rollup/rollup-win32-x64-msvc@4.12.0:
+    resolution: {integrity: sha512-ZYmr5mS2wd4Dew/JjT0Fqi2NPB/ZhZ2VvPp7SmvPZb4Y1CG/LRcS6tcRo2cYU7zLK5A7cdbhWnnWmUjoI4qapg==}
     cpu: [x64]
     os: [win32]
     requiresBuild: true
     dev: true
     optional: true
 
-  /@rushstack/node-core-library@3.62.0(@types/node@20.11.5):
+  /@rushstack/node-core-library@3.62.0(@types/node@20.11.19):
     resolution: {integrity: sha512-88aJn2h8UpSvdwuDXBv1/v1heM6GnBf3RjEy6ZPP7UnzHNCqOHA2Ut+ScYUbXcqIdfew9JlTAe3g+cnX9xQ/Aw==}
     peerDependencies:
       '@types/node': '*'
@@ -4733,7 +4891,7 @@ packages:
       '@types/node':
         optional: true
     dependencies:
-      '@types/node': 20.11.5
+      '@types/node': 20.11.19
       colors: 1.2.5
       fs-extra: 7.0.1
       import-lazy: 4.0.0
@@ -4767,29 +4925,29 @@ packages:
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     dev: false
 
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+  /@storybook/addon-actions@7.6.17:
+    resolution: {integrity: sha512-TBphs4v6LRfyTpFo/WINF0TkMaE3rrNog7wW5mbz6n0j8o53kDN4o9ZEcygSL5zQX43CAaghQTeDCss7ueG7ZQ==}
     dependencies:
-      '@storybook/core-events': 7.6.10
+      '@storybook/core-events': 7.6.17
       '@storybook/global': 5.0.0
-      '@types/uuid': 9.0.7
+      '@types/uuid': 9.0.8
       dequal: 2.0.3
-      polished: 4.2.2
+      polished: 4.3.1
       uuid: 9.0.1
     dev: true
 
-  /@storybook/addon-backgrounds@7.6.10:
-    resolution: {integrity: sha512-kGzsN1QkfyI8Cz7TErEx9OCB3PMzpCFGLd/iy7FreXwbMbeAQ3/9fYgKUsNOYgOhuTz7S09koZUWjS/WJuZGFA==}
+  /@storybook/addon-backgrounds@7.6.17:
+    resolution: {integrity: sha512-7dize7x8+37PH77kmt69b0xSaeDqOcZ4fpzW6+hk53hIaCVU26eGs4+j+743Xva31eOgZWNLupUhOpUDc6SqZw==}
     dependencies:
       '@storybook/global': 5.0.0
       memoizerific: 1.11.3
       ts-dedent: 2.2.0
     dev: true
 
-  /@storybook/addon-controls@7.6.10(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0):
-    resolution: {integrity: sha512-LjwCQRMWq1apLtFwDi6U8MI6ITUr+KhxJucZ60tfc58RgB2v8ayozyDAonFEONsx9YSR1dNIJ2Z/e2rWTBJeYA==}
+  /@storybook/addon-controls@7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+    resolution: {integrity: sha512-zR0aLaUF7FtV/nMRyfniFbCls/e0DAAoXACuOAUAwNAv0lbIS8AyZZiHSmKucCvziUQ6WceeCC7+du3C+9y0rQ==}
     dependencies:
-      '@storybook/blocks': 7.6.10(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
+      '@storybook/blocks': 7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
       lodash: 4.17.21
       ts-dedent: 2.2.0
     transitivePeerDependencies:
@@ -4801,27 +4959,27 @@ packages:
       - supports-color
     dev: true
 
-  /@storybook/addon-docs@7.6.10(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0):
-    resolution: {integrity: sha512-GtyQ9bMx1AOOtl6ZS9vwK104HFRK+tqzxddRRxhXkpyeKu3olm9aMgXp35atE/3fJSqyyDm2vFtxxH8mzBA20A==}
+  /@storybook/addon-docs@7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+    resolution: {integrity: sha512-FKa4Mdy7nhgvEVZJHpMkHriDzpVHbohn87zv9NCL+Ctjs1iAmzGwxEm0culszyDS1HN2ToVoY0h8CSi2RSSZqA==}
     peerDependencies:
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       react-dom: ^16.8.0 || ^17.0.0 || ^18.0.0
     dependencies:
       '@jest/transform': 29.7.0
       '@mdx-js/react': 2.3.0(react@18.2.0)
-      '@storybook/blocks': 7.6.10(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@storybook/client-logger': 7.6.10
-      '@storybook/components': 7.6.10(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@storybook/csf-plugin': 7.6.10
-      '@storybook/csf-tools': 7.6.10
+      '@storybook/blocks': 7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@storybook/client-logger': 7.6.17
+      '@storybook/components': 7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@storybook/csf-plugin': 7.6.17
+      '@storybook/csf-tools': 7.6.17
       '@storybook/global': 5.0.0
       '@storybook/mdx2-csf': 1.1.0
-      '@storybook/node-logger': 7.6.10
-      '@storybook/postinstall': 7.6.10
-      '@storybook/preview-api': 7.6.10
-      '@storybook/react-dom-shim': 7.6.10(react-dom@18.2.0)(react@18.2.0)
-      '@storybook/theming': 7.6.10(react-dom@18.2.0)(react@18.2.0)
-      '@storybook/types': 7.6.10
+      '@storybook/node-logger': 7.6.17
+      '@storybook/postinstall': 7.6.17
+      '@storybook/preview-api': 7.6.17
+      '@storybook/react-dom-shim': 7.6.17(react-dom@18.2.0)(react@18.2.0)
+      '@storybook/theming': 7.6.17(react-dom@18.2.0)(react@18.2.0)
+      '@storybook/types': 7.6.17
       fs-extra: 11.2.0
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
@@ -4835,25 +4993,25 @@ packages:
       - supports-color
     dev: true
 
-  /@storybook/addon-essentials@7.6.10(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0):
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+  /@storybook/addon-essentials@7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+    resolution: {integrity: sha512-qlSpamxuYfT2taF953nC9QijGF2pSbg1ewMNpdwLTj16PTZvR/d8NCDMTJujI1bDwM2m18u8Yc43ibh5LEmxCw==}
     peerDependencies:
       react: ^16.8.0 || ^17.0.0 || ^18.0.0
       react-dom: ^16.8.0 || ^17.0.0 || ^18.0.0
     dependencies:
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-      '@storybook/addon-backgrounds': 7.6.10
-      '@storybook/addon-controls': 7.6.10(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@storybook/addon-docs': 7.6.10(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@storybook/addon-highlight': 7.6.10
-      '@storybook/addon-measure': 7.6.10
-      '@storybook/addon-outline': 7.6.10
-      '@storybook/addon-toolbars': 7.6.10
-      '@storybook/addon-viewport': 7.6.10
-      '@storybook/core-common': 7.6.10
-      '@storybook/manager-api': 7.6.10(react-dom@18.2.0)(react@18.2.0)
-      '@storybook/node-logger': 7.6.10
-      '@storybook/preview-api': 7.6.10
+      '@storybook/addon-actions': 7.6.17
+      '@storybook/addon-backgrounds': 7.6.17
+      '@storybook/addon-controls': 7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@storybook/addon-docs': 7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@storybook/addon-highlight': 7.6.17
+      '@storybook/addon-measure': 7.6.17
+      '@storybook/addon-outline': 7.6.17
+      '@storybook/addon-toolbars': 7.6.17
+      '@storybook/addon-viewport': 7.6.17
+      '@storybook/core-common': 7.6.17
+      '@storybook/manager-api': 7.6.17(react-dom@18.2.0)(react@18.2.0)
+      '@storybook/node-logger': 7.6.17
+      '@storybook/preview-api': 7.6.17
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
       ts-dedent: 2.2.0
@@ -4864,24 +5022,24 @@ packages:
       - supports-color
     dev: true
 
-  /@storybook/addon-highlight@7.6.10:
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+  /@storybook/addon-highlight@7.6.17:
+    resolution: {integrity: sha512-R1yBPUUqGn+60aJakn8q+5Zt34E/gU3n3VmgPdryP0LJUdZ5q1/RZShoVDV+yYQ40htMH6oaCv3OyyPzFAGJ6A==}
     dependencies:
       '@storybook/global': 5.0.0
     dev: true
 
-  /@storybook/addon-interactions@7.6.10:
-    resolution: {integrity: sha512-lEsAdP/PrOZK/KmRbZ/fU4RjEqDP+e/PBlVVVJT2QvHniWK/xxkjCD0axsHU/XuaeQRFhmg0/KR342PC/cIf9A==}
+  /@storybook/addon-interactions@7.6.17:
+    resolution: {integrity: sha512-6zlX+RDQ1PlA6fp7C+hun8t7h2RXfCGs5dGrhEenp2lqnR/rYuUJRC0tmKpkZBb8kZVcbSChzkB/JYkBjBCzpQ==}
     dependencies:
       '@storybook/global': 5.0.0
-      '@storybook/types': 7.6.10
+      '@storybook/types': 7.6.17
       jest-mock: 27.5.1
-      polished: 4.2.2
+      polished: 4.3.1
       ts-dedent: 2.2.0
     dev: true
 
-  /@storybook/addon-links@7.6.10(react@18.2.0):
-    resolution: {integrity: sha512-s/WkSYHpr2pb9p57j6u/xDBg3TKJhBq55YMl0GB5gXgkRPIeuGbPhGJhm2yTGVFLvXgr/aHHnOxb/R/W8PiRhA==}
+  /@storybook/addon-links@7.6.17(react@18.2.0):
+    resolution: {integrity: sha512-iFUwKObRn0EKI0zMETsil2p9a/81rCuSMEWECsi+khkCAs1FUnD2cT6Ag5ydcNcBXsdtdfDJdtXQrkw+TSoStQ==}
     peerDependencies:
       react: ^16.8.0 || ^17.0.0 || ^18.0.0
     peerDependenciesMeta:
@@ -4894,62 +5052,62 @@ packages:
       ts-dedent: 2.2.0
     dev: true
 
-  /@storybook/addon-measure@7.6.10:
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+  /@storybook/addon-measure@7.6.17:
+    resolution: {integrity: sha512-O5vnHZNkduvZ95jf1UssbOl6ivIxzl5tv+4EpScPYId7w700bxWsJH+QX7ip6KlrCf2o3iUhmPe8bm05ghG2KA==}
     dependencies:
       '@storybook/global': 5.0.0
       tiny-invariant: 1.3.1
     dev: true
 
-  /@storybook/addon-outline@7.6.10:
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+  /@storybook/addon-outline@7.6.17:
+    resolution: {integrity: sha512-9o9JXDsYjNaDgz/cY5+jv694+aik/1aiRGGvsCv68e1p/ob0glkGKav4lnJe2VJqD+gCmaARoD8GOJlhoQl8JQ==}
     dependencies:
       '@storybook/global': 5.0.0
       ts-dedent: 2.2.0
     dev: true
 
-  /@storybook/addon-storysource@7.6.10:
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+  /@storybook/addon-storysource@7.6.17:
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     dependencies:
-      '@storybook/source-loader': 7.6.10
+      '@storybook/source-loader': 7.6.17
       estraverse: 5.3.0
       tiny-invariant: 1.3.1
     dev: true
 
-  /@storybook/addon-toolbars@7.6.10:
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+  /@storybook/addon-toolbars@7.6.17:
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     dev: true
 
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+  /@storybook/addon-viewport@7.6.17:
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     dependencies:
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     dev: true
 
-  /@storybook/blocks@7.6.10(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0):
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+  /@storybook/blocks@7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+    resolution: {integrity: sha512-PsNVoe0bX1mMn4Kk3nbKZ0ItDZZ0YJnYAFJ6toAbsyBAbgzg1sce88sQinzvbn58/RT9MPKeWMPB45ZS7ggiNg==}
     peerDependencies:
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       react-dom: ^16.8.0 || ^17.0.0 || ^18.0.0
     dependencies:
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-      '@storybook/client-logger': 7.6.10
-      '@storybook/components': 7.6.10(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@storybook/core-events': 7.6.10
+      '@storybook/channels': 7.6.17
+      '@storybook/client-logger': 7.6.17
+      '@storybook/components': 7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@storybook/core-events': 7.6.17
       '@storybook/csf': 0.1.2
-      '@storybook/docs-tools': 7.6.10
+      '@storybook/docs-tools': 7.6.17
       '@storybook/global': 5.0.0
-      '@storybook/manager-api': 7.6.10(react-dom@18.2.0)(react@18.2.0)
-      '@storybook/preview-api': 7.6.10
-      '@storybook/theming': 7.6.10(react-dom@18.2.0)(react@18.2.0)
-      '@storybook/types': 7.6.10
+      '@storybook/manager-api': 7.6.17(react-dom@18.2.0)(react@18.2.0)
+      '@storybook/preview-api': 7.6.17
+      '@storybook/theming': 7.6.17(react-dom@18.2.0)(react@18.2.0)
+      '@storybook/types': 7.6.17
       '@types/lodash': 4.14.202
       color-convert: 2.0.1
       dequal: 2.0.3
       lodash: 4.17.21
-      markdown-to-jsx: 7.4.0(react@18.2.0)
+      markdown-to-jsx: 7.4.1(react@18.2.0)
       memoizerific: 1.11.3
-      polished: 4.2.2
+      polished: 4.3.1
       react: 18.2.0
       react-colorful: 5.6.1(react-dom@18.2.0)(react@18.2.0)
       react-dom: 18.2.0(react@18.2.0)
@@ -4964,13 +5122,13 @@ packages:
       - supports-color
     dev: true
 
-  /@storybook/builder-manager@7.6.10:
-    resolution: {integrity: sha512-f+YrjZwohGzvfDtH8BHzqM3xW0p4vjjg9u7uzRorqUiNIAAKHpfNrZ/WvwPlPYmrpAHt4xX/nXRJae4rFSygPw==}
+  /@storybook/builder-manager@7.6.17:
+    resolution: {integrity: sha512-Sj8hcDYiPCCMfeLzus37czl0zdrAxAz4IyYam2jBjVymrIrcDAFyL1OCZvnq33ft179QYQWhUs9qwzVmlR/ZWg==}
     dependencies:
       '@fal-works/esbuild-plugin-global-externals': 2.1.2
-      '@storybook/core-common': 7.6.10
-      '@storybook/manager': 7.6.10
-      '@storybook/node-logger': 7.6.10
+      '@storybook/core-common': 7.6.17
+      '@storybook/manager': 7.6.17
+      '@storybook/node-logger': 7.6.17
       '@types/ejs': 3.1.5
       '@types/find-cache-dir': 3.2.1
       '@yarnpkg/esbuild-plugin-pnp': 3.0.0-rc.15(esbuild@0.18.20)
@@ -4988,8 +5146,8 @@ packages:
       - supports-color
     dev: true
 
-  /@storybook/builder-vite@7.6.10(typescript@5.3.3)(vite@5.0.12):
-    resolution: {integrity: sha512-qxe19axiNJVdIKj943e1ucAmADwU42fTGgMSdBzzrvfH3pSOmx2057aIxRzd8YtBRnj327eeqpgCHYIDTunMYQ==}
+  /@storybook/builder-vite@7.6.17(typescript@5.3.3)(vite@5.1.3):
+    resolution: {integrity: sha512-2Q32qalI401EsKKr9Hkk8TAOcHEerqwsjCpQgTNJnCu6GgCVKoVUcb99oRbR9Vyg0xh+jb19XiWqqQujFtLYlQ==}
     peerDependencies:
       '@preact/preset-vite': '*'
       typescript: '>= 4.3.x'
@@ -5003,64 +5161,64 @@ packages:
       vite-plugin-glimmerx:
         optional: true
     dependencies:
-      '@storybook/channels': 7.6.10
-      '@storybook/client-logger': 7.6.10
-      '@storybook/core-common': 7.6.10
-      '@storybook/csf-plugin': 7.6.10
-      '@storybook/node-logger': 7.6.10
-      '@storybook/preview': 7.6.10
-      '@storybook/preview-api': 7.6.10
-      '@storybook/types': 7.6.10
+      '@storybook/channels': 7.6.17
+      '@storybook/client-logger': 7.6.17
+      '@storybook/core-common': 7.6.17
+      '@storybook/csf-plugin': 7.6.17
+      '@storybook/node-logger': 7.6.17
+      '@storybook/preview': 7.6.17
+      '@storybook/preview-api': 7.6.17
+      '@storybook/types': 7.6.17
       '@types/find-cache-dir': 3.2.1
       browser-assert: 1.2.1
       es-module-lexer: 0.9.3
       express: 4.18.2
       find-cache-dir: 3.3.2
       fs-extra: 11.2.0
-      magic-string: 0.30.5
+      magic-string: 0.30.7
       rollup: 3.29.4
       typescript: 5.3.3
-      vite: 5.0.12(@types/node@20.11.5)
+      vite: 5.1.3(@types/node@20.11.19)
     transitivePeerDependencies:
       - encoding
       - supports-color
     dev: true
 
-  /@storybook/channels@7.6.10:
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     dependencies:
-      '@storybook/client-logger': 7.6.10
-      '@storybook/core-events': 7.6.10
+      '@storybook/client-logger': 7.6.17
+      '@storybook/core-events': 7.6.17
       '@storybook/global': 5.0.0
       qs: 6.11.2
       telejson: 7.2.0
       tiny-invariant: 1.3.1
     dev: true
 
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-      '@babel/core': 7.23.7
-      '@babel/preset-env': 7.23.8(@babel/core@7.23.7)
-      '@babel/types': 7.23.6
+      '@babel/core': 7.23.9
+      '@babel/preset-env': 7.23.9(@babel/core@7.23.9)
+      '@babel/types': 7.23.9
       '@ndelangen/get-tarball': 3.0.9
-      '@storybook/codemod': 7.6.10
-      '@storybook/core-common': 7.6.10
-      '@storybook/core-events': 7.6.10
-      '@storybook/core-server': 7.6.10
-      '@storybook/csf-tools': 7.6.10
-      '@storybook/node-logger': 7.6.10
-      '@storybook/telemetry': 7.6.10
-      '@storybook/types': 7.6.10
-      '@types/semver': 7.5.6
+      '@storybook/codemod': 7.6.17
+      '@storybook/core-common': 7.6.17
+      '@storybook/core-events': 7.6.17
+      '@storybook/core-server': 7.6.17
+      '@storybook/csf-tools': 7.6.17
+      '@storybook/node-logger': 7.6.17
+      '@storybook/telemetry': 7.6.17
+      '@storybook/types': 7.6.17
+      '@types/semver': 7.5.7
       '@yarnpkg/fslib': 2.10.3
       '@yarnpkg/libzip': 2.3.0
       chalk: 4.1.2
       commander: 6.2.1
       cross-spawn: 7.0.3
       detect-indent: 6.1.0
-      envinfo: 7.11.0
+      envinfo: 7.11.1
       execa: 5.1.1
       express: 4.18.2
       find-up: 5.0.0
@@ -5069,14 +5227,14 @@ packages:
       get-port: 5.1.1
       giget: 1.2.1
       globby: 11.1.0
-      jscodeshift: 0.15.1(@babel/preset-env@7.23.8)
+      jscodeshift: 0.15.1(@babel/preset-env@7.23.9)
       leven: 3.1.0
       ora: 5.4.1
       prettier: 2.8.8
       prompts: 2.4.2
       puppeteer-core: 2.1.1
       read-pkg-up: 7.0.1
-      semver: 7.5.4
+      semver: 7.6.0
       strip-json-comments: 3.1.1
       tempy: 1.0.1
       ts-dedent: 2.2.0
@@ -5088,26 +5246,26 @@ packages:
       - utf-8-validate
     dev: true
 
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+  /@storybook/client-logger@7.6.17:
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     dependencies:
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     dev: true
 
-  /@storybook/codemod@7.6.10:
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+  /@storybook/codemod@7.6.17:
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-      '@babel/core': 7.23.7
-      '@babel/preset-env': 7.23.8(@babel/core@7.23.7)
-      '@babel/types': 7.23.6
+      '@babel/core': 7.23.9
+      '@babel/preset-env': 7.23.9(@babel/core@7.23.9)
+      '@babel/types': 7.23.9
       '@storybook/csf': 0.1.2
-      '@storybook/csf-tools': 7.6.10
-      '@storybook/node-logger': 7.6.10
-      '@storybook/types': 7.6.10
+      '@storybook/csf-tools': 7.6.17
+      '@storybook/node-logger': 7.6.17
+      '@storybook/types': 7.6.17
       '@types/cross-spawn': 6.0.6
       cross-spawn: 7.0.3
       globby: 11.1.0
-      jscodeshift: 0.15.1(@babel/preset-env@7.23.8)
+      jscodeshift: 0.15.1(@babel/preset-env@7.23.9)
       lodash: 4.17.21
       prettier: 2.8.8
       recast: 0.23.4
@@ -5115,19 +5273,19 @@ packages:
       - supports-color
     dev: true
 
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+  /@storybook/components@7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+    resolution: {integrity: sha512-lbh7GynMidA+CZcJnstVku6Nhs+YkqjYaZ+mKPugvlVhGVWv0DaaeQFVuZ8cJtUGJ/5FFU4Y+n+gylYUHkGBMA==}
     peerDependencies:
       react: ^16.8.0 || ^17.0.0 || ^18.0.0
       react-dom: ^16.8.0 || ^17.0.0 || ^18.0.0
     dependencies:
-      '@radix-ui/react-select': 1.2.2(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-toolbar': 1.0.4(@types/react-dom@18.2.18)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@storybook/client-logger': 7.6.10
+      '@radix-ui/react-select': 1.2.2(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-toolbar': 1.0.4(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@storybook/client-logger': 7.6.17
       '@storybook/csf': 0.1.2
       '@storybook/global': 5.0.0
-      '@storybook/theming': 7.6.10(react-dom@18.2.0)(react@18.2.0)
-      '@storybook/types': 7.6.10
+      '@storybook/theming': 7.6.17(react-dom@18.2.0)(react@18.2.0)
+      '@storybook/types': 7.6.17
       memoizerific: 1.11.3
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
@@ -5138,21 +5296,21 @@ packages:
       - '@types/react-dom'
     dev: true
 
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     dependencies:
-      '@storybook/client-logger': 7.6.10
-      '@storybook/preview-api': 7.6.10
+      '@storybook/client-logger': 7.6.17
+      '@storybook/preview-api': 7.6.17
     dev: true
 
-  /@storybook/core-common@7.6.10:
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+  /@storybook/core-common@7.6.17:
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     dependencies:
-      '@storybook/core-events': 7.6.10
-      '@storybook/node-logger': 7.6.10
-      '@storybook/types': 7.6.10
+      '@storybook/core-events': 7.6.17
+      '@storybook/node-logger': 7.6.17
+      '@storybook/types': 7.6.17
       '@types/find-cache-dir': 3.2.1
-      '@types/node': 18.19.8
+      '@types/node': 18.19.17
       '@types/node-fetch': 2.6.11
       '@types/pretty-hrtime': 1.0.3
       chalk: 4.1.2
@@ -5176,34 +5334,34 @@ packages:
       - supports-color
     dev: true
 
-  /@storybook/core-events@7.6.10:
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+  /@storybook/core-events@7.6.17:
+    resolution: {integrity: sha512-AriWMCm/k1cxlv10f+jZ1wavThTRpLaN3kY019kHWbYT9XgaSuLU67G7GPr3cGnJ6HuA6uhbzu8qtqVCd6OfXA==}
     dependencies:
       ts-dedent: 2.2.0
     dev: true
 
-  /@storybook/core-server@7.6.10:
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+  /@storybook/core-server@7.6.17:
+    resolution: {integrity: sha512-KWGhTTaL1Q14FolcoKKZgytlPJUbH6sbJ1Ptj/84EYWFewcnEgVs0Zlnh1VStRZg+Rd1WC1V4yVd/bbDzxrvQA==}
     dependencies:
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       '@discoveryjs/json-ext': 0.5.7
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-      '@storybook/channels': 7.6.10
-      '@storybook/core-common': 7.6.10
-      '@storybook/core-events': 7.6.10
+      '@storybook/builder-manager': 7.6.17
+      '@storybook/channels': 7.6.17
+      '@storybook/core-common': 7.6.17
+      '@storybook/core-events': 7.6.17
       '@storybook/csf': 0.1.2
-      '@storybook/csf-tools': 7.6.10
+      '@storybook/csf-tools': 7.6.17
       '@storybook/docs-mdx': 0.1.0
       '@storybook/global': 5.0.0
-      '@storybook/manager': 7.6.10
-      '@storybook/node-logger': 7.6.10
-      '@storybook/preview-api': 7.6.10
-      '@storybook/telemetry': 7.6.10
-      '@storybook/types': 7.6.10
+      '@storybook/manager': 7.6.17
+      '@storybook/node-logger': 7.6.17
+      '@storybook/preview-api': 7.6.17
+      '@storybook/telemetry': 7.6.17
+      '@storybook/types': 7.6.17
       '@types/detect-port': 1.3.5
-      '@types/node': 18.19.8
+      '@types/node': 18.19.17
       '@types/pretty-hrtime': 1.0.3
-      '@types/semver': 7.5.6
+      '@types/semver': 7.5.7
       better-opn: 3.0.2
       chalk: 4.1.2
       cli-table3: 0.6.3
@@ -5212,13 +5370,13 @@ packages:
       express: 4.18.2
       fs-extra: 11.2.0
       globby: 11.1.0
-      ip: 2.0.0
+      ip: 2.0.1
       lodash: 4.17.21
       open: 8.4.2
       pretty-hrtime: 1.0.3
       prompts: 2.4.2
       read-pkg-up: 7.0.1
-      semver: 7.5.4
+      semver: 7.6.0
       telejson: 7.2.0
       tiny-invariant: 1.3.1
       ts-dedent: 2.2.0
@@ -5233,24 +5391,24 @@ packages:
       - utf-8-validate
     dev: true
 
-  /@storybook/csf-plugin@7.6.10:
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+  /@storybook/csf-plugin@7.6.17:
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     dependencies:
-      '@storybook/csf-tools': 7.6.10
-      unplugin: 1.6.0
+      '@storybook/csf-tools': 7.6.17
+      unplugin: 1.7.1
     transitivePeerDependencies:
       - supports-color
     dev: true
 
-  /@storybook/csf-tools@7.6.10:
-    resolution: {integrity: sha512-TnDNAwIALcN6SA4l00Cb67G02XMOrYU38bIpFJk5VMDX2dvgPjUtJNBuLmEbybGcOt7nPyyFIHzKcY5FCVGoWA==}
+  /@storybook/csf-tools@7.6.17:
+    resolution: {integrity: sha512-dAQtam0EBPeTJYcQPLxXgz4L9JFqD+HWbLFG9CmNIhMMjticrB0mpk1EFIS6vPXk/VsVWpBgMLD7dZlD6YMKcQ==}
     dependencies:
       '@babel/generator': 7.23.6
-      '@babel/parser': 7.23.6
-      '@babel/traverse': 7.23.7
-      '@babel/types': 7.23.6
+      '@babel/parser': 7.23.9
+      '@babel/traverse': 7.23.9
+      '@babel/types': 7.23.9
       '@storybook/csf': 0.1.2
-      '@storybook/types': 7.6.10
+      '@storybook/types': 7.6.17
       fs-extra: 11.2.0
       recast: 0.23.4
       ts-dedent: 2.2.0
@@ -5274,12 +5432,12 @@ packages:
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     dev: true
 
-  /@storybook/docs-tools@7.6.10:
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+  /@storybook/docs-tools@7.6.17:
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     dependencies:
-      '@storybook/core-common': 7.6.10
-      '@storybook/preview-api': 7.6.10
-      '@storybook/types': 7.6.10
+      '@storybook/core-common': 7.6.17
+      '@storybook/preview-api': 7.6.17
+      '@storybook/types': 7.6.17
       '@types/doctrine': 0.0.3
       assert: 2.1.0
       doctrine: 3.0.0
@@ -5293,33 +5451,33 @@ packages:
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     dev: true
 
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+  /@storybook/instrumenter@7.6.17:
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     dependencies:
-      '@storybook/channels': 7.6.10
-      '@storybook/client-logger': 7.6.10
-      '@storybook/core-events': 7.6.10
+      '@storybook/channels': 7.6.17
+      '@storybook/client-logger': 7.6.17
+      '@storybook/core-events': 7.6.17
       '@storybook/global': 5.0.0
-      '@storybook/preview-api': 7.6.10
+      '@storybook/preview-api': 7.6.17
       '@vitest/utils': 0.34.7
       util: 0.12.5
     dev: true
 
-  /@storybook/manager-api@7.6.10(react-dom@18.2.0)(react@18.2.0):
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+  /@storybook/manager-api@7.6.17(react-dom@18.2.0)(react@18.2.0):
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     dependencies:
-      '@storybook/channels': 7.6.10
-      '@storybook/client-logger': 7.6.10
-      '@storybook/core-events': 7.6.10
+      '@storybook/channels': 7.6.17
+      '@storybook/client-logger': 7.6.17
+      '@storybook/core-events': 7.6.17
       '@storybook/csf': 0.1.2
       '@storybook/global': 5.0.0
-      '@storybook/router': 7.6.10
-      '@storybook/theming': 7.6.10(react-dom@18.2.0)(react@18.2.0)
-      '@storybook/types': 7.6.10
+      '@storybook/router': 7.6.17
+      '@storybook/theming': 7.6.17(react-dom@18.2.0)(react@18.2.0)
+      '@storybook/types': 7.6.17
       dequal: 2.0.3
       lodash: 4.17.21
       memoizerific: 1.11.3
-      store2: 2.14.2
+      store2: 2.14.3
       telejson: 7.2.0
       ts-dedent: 2.2.0
     transitivePeerDependencies:
@@ -5327,31 +5485,31 @@ packages:
       - react-dom
     dev: true
 
-  /@storybook/manager@7.6.10:
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+  /@storybook/manager@7.6.17:
+    resolution: {integrity: sha512-A1LDDIqMpwRzq/dqkbbiza0QI04o4ZHCl2a3UMDZUV/+QLc2nsr2DAaLk4CVL4/cIc5zGqmIcaOTvprx2YKVBw==}
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     dev: true
 
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+  /@storybook/node-logger@7.6.17:
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+  /@storybook/postinstall@7.6.17:
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     dependencies:
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-      '@storybook/client-logger': 7.6.10
-      '@storybook/core-events': 7.6.10
+      '@storybook/channels': 7.6.17
+      '@storybook/client-logger': 7.6.17
+      '@storybook/core-events': 7.6.17
       '@storybook/csf': 0.1.2
       '@storybook/global': 5.0.0
-      '@storybook/types': 7.6.10
+      '@storybook/types': 7.6.17
       '@types/qs': 6.9.11
       dequal: 2.0.3
       lodash: 4.17.21
@@ -5362,12 +5520,12 @@ packages:
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     dev: true
 
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+  /@storybook/preview@7.6.17:
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     dev: true
 
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+  /@storybook/react-dom-shim@7.6.17(react-dom@18.2.0)(react@18.2.0):
+    resolution: {integrity: sha512-32Sa/G+WnvaPiQ1Wvjjw5UM9rr2c4GDohwCcWVv3/LJuiFPqNS6zglAtmnsrlIBnUwRBMLMh/ekCTdqMiUmfDw==}
     peerDependencies:
       react: ^16.8.0 || ^17.0.0 || ^18.0.0
       react-dom: ^16.8.0 || ^17.0.0 || ^18.0.0
@@ -5376,24 +5534,24 @@ packages:
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     dev: true
 
-  /@storybook/react-vite@7.6.10(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)(vite@5.0.12):
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+  /@storybook/react-vite@7.6.17(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)(vite@5.1.3):
+    resolution: {integrity: sha512-4dIm3CuRl44X1TLzN3WoZh/bChzJF7Ud28li9atj9C8db0bb/y0zl8cahrsRFoR7/LyfqdOVLqaztrnA5SsWfg==}
     engines: {node: '>=16'}
     peerDependencies:
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       react-dom: ^16.8.0 || ^17.0.0 || ^18.0.0
       vite: ^3.0.0 || ^4.0.0 || ^5.0.0
     dependencies:
-      '@joshwooding/vite-plugin-react-docgen-typescript': 0.3.0(typescript@5.3.3)(vite@5.0.12)
+      '@joshwooding/vite-plugin-react-docgen-typescript': 0.3.0(typescript@5.3.3)(vite@5.1.3)
       '@rollup/pluginutils': 5.1.0
-      '@storybook/builder-vite': 7.6.10(typescript@5.3.3)(vite@5.0.12)
-      '@storybook/react': 7.6.10(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)
-      '@vitejs/plugin-react': 3.1.0(vite@5.0.12)
-      magic-string: 0.30.5
+      '@storybook/builder-vite': 7.6.17(typescript@5.3.3)(vite@5.1.3)
+      '@storybook/react': 7.6.17(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)
+      '@vitejs/plugin-react': 3.1.0(vite@5.1.3)
+      magic-string: 0.30.7
       react: 18.2.0
       react-docgen: 7.0.3
       react-dom: 18.2.0(react@18.2.0)
-      vite: 5.0.12(@types/node@20.11.5)
+      vite: 5.1.3(@types/node@20.11.19)
     transitivePeerDependencies:
       - '@preact/preset-vite'
       - encoding
@@ -5403,8 +5561,8 @@ packages:
       - vite-plugin-glimmerx
     dev: true
 
-  /@storybook/react@7.6.10(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3):
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+  /@storybook/react@7.6.17(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3):
+    resolution: {integrity: sha512-lVqzQSU03rRJWYW+gK2gq6mSo3/qtnVICY8B8oP7gc36jVu4ksDIu45bTfukM618ODkUZy0vZe6T4engK3azjA==}
     engines: {node: '>=16.0.0'}
     peerDependencies:
       react: ^16.8.0 || ^17.0.0 || ^18.0.0
@@ -5414,16 +5572,16 @@ packages:
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         optional: true
     dependencies:
-      '@storybook/client-logger': 7.6.10
-      '@storybook/core-client': 7.6.10
-      '@storybook/docs-tools': 7.6.10
+      '@storybook/client-logger': 7.6.17
+      '@storybook/core-client': 7.6.17
+      '@storybook/docs-tools': 7.6.17
       '@storybook/global': 5.0.0
-      '@storybook/preview-api': 7.6.10
-      '@storybook/react-dom-shim': 7.6.10(react-dom@18.2.0)(react@18.2.0)
-      '@storybook/types': 7.6.10
+      '@storybook/preview-api': 7.6.17
+      '@storybook/react-dom-shim': 7.6.17(react-dom@18.2.0)(react@18.2.0)
+      '@storybook/types': 7.6.17
       '@types/escodegen': 0.0.6
       '@types/estree': 0.0.51
-      '@types/node': 18.19.8
+      '@types/node': 18.19.17
       acorn: 7.4.1
       acorn-jsx: 5.3.2(acorn@7.4.1)
       acorn-walk: 7.2.0
@@ -5443,30 +5601,30 @@ packages:
       - supports-color
     dev: true
 
-  /@storybook/router@7.6.10:
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+  /@storybook/router@7.6.17:
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     dependencies:
-      '@storybook/client-logger': 7.6.10
+      '@storybook/client-logger': 7.6.17
       memoizerific: 1.11.3
       qs: 6.11.2
     dev: true
 
-  /@storybook/source-loader@7.6.10:
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+  /@storybook/source-loader@7.6.17:
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     dependencies:
       '@storybook/csf': 0.1.2
-      '@storybook/types': 7.6.10
+      '@storybook/types': 7.6.17
       estraverse: 5.3.0
       lodash: 4.17.21
       prettier: 2.8.8
     dev: true
 
-  /@storybook/telemetry@7.6.10:
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+  /@storybook/telemetry@7.6.17:
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     dependencies:
-      '@storybook/client-logger': 7.6.10
-      '@storybook/core-common': 7.6.10
-      '@storybook/csf-tools': 7.6.10
+      '@storybook/client-logger': 7.6.17
+      '@storybook/core-common': 7.6.17
+      '@storybook/csf-tools': 7.6.17
       chalk: 4.1.2
       detect-package-manager: 2.0.1
       fetch-retry: 5.0.6
@@ -5477,15 +5635,15 @@ packages:
       - supports-color
     dev: true
 
-  /@storybook/test@7.6.10(vitest@1.2.2):
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+  /@storybook/test@7.6.17(vitest@1.3.1):
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     dependencies:
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-      '@storybook/core-events': 7.6.10
-      '@storybook/instrumenter': 7.6.10
-      '@storybook/preview-api': 7.6.10
+      '@storybook/client-logger': 7.6.17
+      '@storybook/core-events': 7.6.17
+      '@storybook/instrumenter': 7.6.17
+      '@storybook/preview-api': 7.6.17
       '@testing-library/dom': 9.3.4
-      '@testing-library/jest-dom': 6.2.0(vitest@1.2.2)
+      '@testing-library/jest-dom': 6.4.2(vitest@1.3.1)
       '@testing-library/user-event': 14.3.0(@testing-library/dom@9.3.4)
       '@types/chai': 4.3.11
       '@vitest/expect': 0.34.7
@@ -5494,36 +5652,37 @@ packages:
       util: 0.12.5
     transitivePeerDependencies:
       - '@jest/globals'
+      - '@types/bun'
       - '@types/jest'
       - jest
       - vitest
     dev: true
 
-  /@storybook/theming@7.6.10(react-dom@18.2.0)(react@18.2.0):
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+  /@storybook/theming@7.6.17(react-dom@18.2.0)(react@18.2.0):
+    resolution: {integrity: sha512-ZbaBt3KAbmBtfjNqgMY7wPMBshhSJlhodyMNQypv+95xLD/R+Az6aBYbpVAOygLaUQaQk4ar7H/Ww6lFIoiFbA==}
     peerDependencies:
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       react-dom: ^16.8.0 || ^17.0.0 || ^18.0.0
     dependencies:
       '@emotion/use-insertion-effect-with-fallbacks': 1.0.1(react@18.2.0)
-      '@storybook/client-logger': 7.6.10
+      '@storybook/client-logger': 7.6.17
       '@storybook/global': 5.0.0
       memoizerific: 1.11.3
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     dev: true
 
-  /@storybook/types@7.6.10:
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+  /@storybook/types@7.6.17:
+    resolution: {integrity: sha512-GRY0xEJQ0PrL7DY2qCNUdIfUOE0Gsue6N+GBJw9ku1IUDFLJRDOF+4Dx2BvYcVCPI5XPqdWKlEyZdMdKjiQN7Q==}
     dependencies:
-      '@storybook/channels': 7.6.10
+      '@storybook/channels': 7.6.17
       '@types/babel__core': 7.20.5
       '@types/express': 4.17.21
       file-system-cache: 2.3.0
     dev: true
 
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+  /@swc/core-darwin-arm64@1.4.2:
+    resolution: {integrity: sha512-1uSdAn1MRK5C1m/TvLZ2RDvr0zLvochgrZ2xL+lRzugLlCTlSA+Q4TWtrZaOz+vnnFVliCpw7c7qu0JouhgQIw==}
     engines: {node: '>=10'}
     cpu: [arm64]
     os: [darwin]
@@ -5531,8 +5690,8 @@ packages:
     dev: true
     optional: true
 
-  /@swc/core-darwin-x64@1.3.101:
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+  /@swc/core-darwin-x64@1.4.2:
+    resolution: {integrity: sha512-TYD28+dCQKeuxxcy7gLJUCFLqrwDZnHtC2z7cdeGfZpbI2mbfppfTf2wUPzqZk3gEC96zHd4Yr37V3Tvzar+lQ==}
     engines: {node: '>=10'}
     cpu: [x64]
     os: [darwin]
@@ -5540,8 +5699,8 @@ packages:
     dev: true
     optional: true
 
-  /@swc/core-linux-arm-gnueabihf@1.3.101:
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+  /@swc/core-linux-arm-gnueabihf@1.4.2:
+    resolution: {integrity: sha512-Eyqipf7ZPGj0vplKHo8JUOoU1un2sg5PjJMpEesX0k+6HKE2T8pdyeyXODN0YTFqzndSa/J43EEPXm+rHAsLFQ==}
     engines: {node: '>=10'}
     cpu: [arm]
     os: [linux]
@@ -5549,8 +5708,8 @@ packages:
     dev: true
     optional: true
 
-  /@swc/core-linux-arm64-gnu@1.3.101:
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+  /@swc/core-linux-arm64-gnu@1.4.2:
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     engines: {node: '>=10'}
     cpu: [arm64]
     os: [linux]
@@ -5558,8 +5717,8 @@ packages:
     dev: true
     optional: true
 
-  /@swc/core-linux-arm64-musl@1.3.101:
-    resolution: {integrity: sha512-OGjYG3H4BMOTnJWJyBIovCez6KiHF30zMIu4+lGJTCrxRI2fAjGLml3PEXj8tC3FMcud7U2WUn6TdG0/te2k6g==}
+  /@swc/core-linux-arm64-musl@1.4.2:
+    resolution: {integrity: sha512-3G0D5z9hUj9bXNcwmA1eGiFTwe5rWkuL3DsoviTj73TKLpk7u64ND0XjEfO0huVv4vVu9H1jodrKb7nvln/dlw==}
     engines: {node: '>=10'}
     cpu: [arm64]
     os: [linux]
@@ -5567,8 +5726,8 @@ packages:
     dev: true
     optional: true
 
-  /@swc/core-linux-x64-gnu@1.3.101:
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+  /@swc/core-linux-x64-gnu@1.4.2:
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     engines: {node: '>=10'}
     cpu: [x64]
     os: [linux]
@@ -5576,8 +5735,8 @@ packages:
     dev: true
     optional: true
 
-  /@swc/core-linux-x64-musl@1.3.101:
-    resolution: {integrity: sha512-kDN8lm4Eew0u1p+h1l3JzoeGgZPQ05qDE0czngnjmfpsH2sOZxVj1hdiCwS5lArpy7ktaLu5JdRnx70MkUzhXw==}
+  /@swc/core-linux-x64-musl@1.4.2:
+    resolution: {integrity: sha512-dp0fAmreeVVYTUcb4u9njTPrYzKnbIH0EhH2qvC9GOYNNREUu2GezSIDgonjOXkHiTCvopG4xU7y56XtXj4VrQ==}
     engines: {node: '>=10'}
     cpu: [x64]
     os: [linux]
@@ -5585,8 +5744,8 @@ packages:
     dev: true
     optional: true
 
-  /@swc/core-win32-arm64-msvc@1.3.101:
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+  /@swc/core-win32-arm64-msvc@1.4.2:
+    resolution: {integrity: sha512-HlVIiLMQkzthAdqMslQhDkoXJ5+AOLUSTV6fm6shFKZKqc/9cJvr4S8UveNERL9zUficA36yM3bbfo36McwnvQ==}
     engines: {node: '>=10'}
     cpu: [arm64]
     os: [win32]
@@ -5594,8 +5753,8 @@ packages:
     dev: true
     optional: true
 
-  /@swc/core-win32-ia32-msvc@1.3.101:
-    resolution: {integrity: sha512-onO5KvICRVlu2xmr4//V2je9O2XgS1SGKpbX206KmmjcJhXN5EYLSxW9qgg+kgV5mip+sKTHTAu7IkzkAtElYA==}
+  /@swc/core-win32-ia32-msvc@1.4.2:
+    resolution: {integrity: sha512-WCF8faPGjCl4oIgugkp+kL9nl3nUATlzKXCEGFowMEmVVCFM0GsqlmGdPp1pjZoWc9tpYanoXQDnp5IvlDSLhA==}
     engines: {node: '>=10'}
     cpu: [ia32]
     os: [win32]
@@ -5603,8 +5762,8 @@ packages:
     dev: true
     optional: true
 
-  /@swc/core-win32-x64-msvc@1.3.101:
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+  /@swc/core-win32-x64-msvc@1.4.2:
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     engines: {node: '>=10'}
     cpu: [x64]
     os: [win32]
@@ -5612,8 +5771,8 @@ packages:
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     optional: true
 
-  /@swc/core@1.3.101:
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+  /@swc/core@1.4.2:
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     engines: {node: '>=10'}
     requiresBuild: true
     peerDependencies:
@@ -5622,23 +5781,23 @@ packages:
       '@swc/helpers':
         optional: true
     dependencies:
-      '@swc/counter': 0.1.2
+      '@swc/counter': 0.1.3
       '@swc/types': 0.1.5
     optionalDependencies:
-      '@swc/core-darwin-arm64': 1.3.101
-      '@swc/core-darwin-x64': 1.3.101
-      '@swc/core-linux-arm-gnueabihf': 1.3.101
-      '@swc/core-linux-arm64-gnu': 1.3.101
-      '@swc/core-linux-arm64-musl': 1.3.101
-      '@swc/core-linux-x64-gnu': 1.3.101
-      '@swc/core-linux-x64-musl': 1.3.101
-      '@swc/core-win32-arm64-msvc': 1.3.101
-      '@swc/core-win32-ia32-msvc': 1.3.101
-      '@swc/core-win32-x64-msvc': 1.3.101
+      '@swc/core-darwin-arm64': 1.4.2
+      '@swc/core-darwin-x64': 1.4.2
+      '@swc/core-linux-arm-gnueabihf': 1.4.2
+      '@swc/core-linux-arm64-gnu': 1.4.2
+      '@swc/core-linux-arm64-musl': 1.4.2
+      '@swc/core-linux-x64-gnu': 1.4.2
+      '@swc/core-linux-x64-musl': 1.4.2
+      '@swc/core-win32-arm64-msvc': 1.4.2
+      '@swc/core-win32-ia32-msvc': 1.4.2
+      '@swc/core-win32-x64-msvc': 1.4.2
     dev: true
 
-  /@swc/counter@0.1.2:
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+  /@swc/counter@0.1.3:
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     dev: true
 
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     engines: {node: '>=14'}
     dependencies:
       '@babel/code-frame': 7.23.5
-      '@babel/runtime': 7.23.8
+      '@babel/runtime': 7.23.9
       '@types/aria-query': 5.0.4
       aria-query: 5.1.3
       chalk: 4.1.2
@@ -5665,17 +5824,20 @@ packages:
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     dev: true
 
-  /@testing-library/jest-dom@6.2.0(vitest@1.2.2):
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+  /@testing-library/jest-dom@6.4.2(vitest@1.3.1):
+    resolution: {integrity: sha512-CzqH0AFymEMG48CpzXFriYYkOjk6ZGPCLMhW9e9jg3KMCn5OfJecF8GtGW7yGfR/IgCe3SX8BSwjdzI6BBbZLw==}
     engines: {node: '>=14', npm: '>=6', yarn: '>=1'}
     peerDependencies:
       '@jest/globals': '>= 28'
+      '@types/bun': latest
       '@types/jest': '>= 28'
       jest: '>= 28'
       vitest: '>= 0.32'
     peerDependenciesMeta:
       '@jest/globals':
         optional: true
+      '@types/bun':
+        optional: true
       '@types/jest':
         optional: true
       jest:
@@ -5683,15 +5845,15 @@ packages:
       vitest:
         optional: true
     dependencies:
-      '@adobe/css-tools': 4.3.2
-      '@babel/runtime': 7.23.8
+      '@adobe/css-tools': 4.3.3
+      '@babel/runtime': 7.23.9
       aria-query: 5.3.0
       chalk: 3.0.0
       css.escape: 1.5.1
       dom-accessibility-api: 0.6.3
       lodash: 4.17.21
       redent: 3.0.0
-      vitest: 1.2.2(@types/node@20.11.5)
+      vitest: 1.3.1(@types/node@20.11.19)
     dev: true
 
   /@testing-library/user-event@14.3.0(@testing-library/dom@9.3.4):
@@ -5714,8 +5876,8 @@ packages:
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     dependencies:
-      '@babel/parser': 7.23.6
-      '@babel/types': 7.23.6
+      '@babel/parser': 7.23.9
+      '@babel/types': 7.23.9
       '@types/babel__generator': 7.6.8
       '@types/babel__template': 7.4.4
       '@types/babel__traverse': 7.20.5
@@ -5724,27 +5886,27 @@ packages:
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     dependencies:
-      '@babel/types': 7.23.6
+      '@babel/types': 7.23.9
     dev: true
 
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     resolution: {integrity: sha512-h/NUaSyG5EyxBIp8YRxo4RMe2/qQgvyowRwVMzhYhBCONbW8PUsg4lkFMrhgZhUe5z3L3MiLDuvyJ/CaPa2A8A==}
     dependencies:
-      '@babel/parser': 7.23.6
-      '@babel/types': 7.23.6
+      '@babel/parser': 7.23.9
+      '@babel/types': 7.23.9
     dev: true
 
   /@types/babel__traverse@7.20.5:
     resolution: {integrity: sha512-WXCyOcRtH37HAUkpXhUduaxdm82b4GSlyTqajXviN4EfiuPgNYR109xMCKvpl6zPIpua0DGlMEDCq+g8EdoheQ==}
     dependencies:
-      '@babel/types': 7.23.6
+      '@babel/types': 7.23.9
     dev: true
 
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     resolution: {integrity: sha512-fB3Zu92ucau0iQ0JMCFQE7b/dv8Ot07NI3KaZIkIUNXq82k4eBAqUaneXfleGY9JWskeS9y+u0nXMyspcuQrCg==}
     dependencies:
       '@types/connect': 3.4.38
-      '@types/node': 20.11.5
+      '@types/node': 20.11.19
     dev: true
 
   /@types/chai@4.3.11:
@@ -5754,13 +5916,13 @@ packages:
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     dependencies:
-      '@types/node': 20.11.5
+      '@types/node': 20.11.19
     dev: true
 
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     resolution: {integrity: sha512-fXRhhUkG4H3TQk5dBhQ7m/JDdSNHKwR2BBia62lhwEIq9xGiQKLxd6LymNhn47SjXhsUEPmxi+PKw2OkW4LLjA==}
     dependencies:
-      '@types/node': 20.11.5
+      '@types/node': 20.11.19
     dev: true
 
   /@types/d3-array@3.2.1:
@@ -5791,7 +5953,7 @@ packages:
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     dependencies:
       '@types/d3-array': 3.2.1
-      '@types/geojson': 7946.0.13
+      '@types/geojson': 7946.0.14
     dev: false
 
   /@types/d3-delaunay@6.0.4:
@@ -5833,7 +5995,7 @@ packages:
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     dependencies:
-      '@types/geojson': 7946.0.13
+      '@types/geojson': 7946.0.14
     dev: false
 
   /@types/d3-hierarchy@3.1.6:
@@ -5846,8 +6008,8 @@ packages:
       '@types/d3-color': 3.1.3
     dev: false
 
-  /@types/d3-path@3.0.2:
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+  /@types/d3-path@3.1.0:
+    resolution: {integrity: sha512-P2dlU/q51fkOc/Gfl3Ul9kicV7l+ra934qBFXCFhrZMOL6du1TM0pm1ThYvENukyOn5h9v+yMJ9Fn5JK4QozrQ==}
     dev: false
 
   /@types/d3-polygon@3.0.2:
@@ -5879,7 +6041,7 @@ packages:
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     dependencies:
-      '@types/d3-path': 3.0.2
+      '@types/d3-path': 3.1.0
     dev: false
 
   /@types/d3-time-format@4.0.3:
@@ -5927,7 +6089,7 @@ packages:
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       '@types/d3-hierarchy': 3.1.6
       '@types/d3-interpolate': 3.0.4
-      '@types/d3-path': 3.0.2
+      '@types/d3-path': 3.1.0
       '@types/d3-polygon': 3.0.2
       '@types/d3-quadtree': 3.0.6
       '@types/d3-random': 3.0.3
@@ -5974,8 +6136,8 @@ packages:
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     dev: true
 
-  /@types/eslint@8.56.0:
-    resolution: {integrity: sha512-FlsN0p4FhuYRjIxpbdXovvHQhtlG05O1GG/RNWvdAxTboR438IOTwmrY/vLA+Xfgg06BTkP045M3vpFwTMv1dg==}
+  /@types/eslint@8.56.2:
+    resolution: {integrity: sha512-uQDwm1wFHmbBbCZCqAlq6Do9LYwByNZHWzXppSnay9SuwJ+VRbjkbLABer54kcPnMSlG6Fdiy2yaFXm/z9Z5gw==}
     dependencies:
       '@types/estree': 1.0.5
       '@types/json-schema': 7.0.15
@@ -5989,10 +6151,10 @@ packages:
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     dev: true
 
-  /@types/express-serve-static-core@4.17.41:
-    resolution: {integrity: sha512-OaJ7XLaelTgrvlZD8/aa0vvvxZdUmlCn6MtWeB7TkiKW70BQLc9XEPpDLPdbo52ZhXUCrznlWdCHWxJWtdyajA==}
+  /@types/express-serve-static-core@4.17.43:
+    resolution: {integrity: sha512-oaYtiBirUOPQGSWNGPWnzyAFJ0BP3cwvN4oWZQY+zUBwpVIGsKUkpBpSztp74drYcjavs7SKFZ4DX1V2QeN8rg==}
     dependencies:
-      '@types/node': 20.11.5
+      '@types/node': 20.11.19
       '@types/qs': 6.9.11
       '@types/range-parser': 1.2.7
       '@types/send': 0.17.4
@@ -6002,7 +6164,7 @@ packages:
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     dependencies:
       '@types/body-parser': 1.19.5
-      '@types/express-serve-static-core': 4.17.41
+      '@types/express-serve-static-core': 4.17.43
       '@types/qs': 6.9.11
       '@types/serve-static': 1.15.5
     dev: true
@@ -6011,21 +6173,21 @@ packages:
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     dev: true
 
-  /@types/geojson@7946.0.13:
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+  /@types/geojson@7946.0.14:
+    resolution: {integrity: sha512-WCfD5Ht3ZesJUsONdhvm84dmzWOiOzOAqOncN0++w0lBw1o8OuDNJF2McvvCef/yBqb/HYRahp1BYtODFQ8bRg==}
     dev: false
 
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     resolution: {integrity: sha512-ZUxbzKl0IfJILTS6t7ip5fQQM/J3TJYubDm3nMbgubNNYS62eXeUpoLUC8/7fJNiFYHTrGPQn7hspDUzIHX3UA==}
     dependencies:
       '@types/minimatch': 5.1.2
-      '@types/node': 20.11.5
+      '@types/node': 20.11.19
     dev: true
 
   /@types/graceful-fs@4.1.9:
     resolution: {integrity: sha512-olP3sd1qOEe5dXTSaFvQG+02VdRXcdytWLAZsAq1PecU8uqQAhkrnbli7DagjtXKW/Bl7YJbUsa8MPcuc8LHEQ==}
     dependencies:
-      '@types/node': 20.11.5
+      '@types/node': 20.11.19
     dev: true
 
   /@types/http-errors@2.0.4:
@@ -6075,8 +6237,8 @@ packages:
   /@types/lodash@4.14.202:
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-  /@types/mdx@2.0.10:
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+  /@types/mdx@2.0.11:
+    resolution: {integrity: sha512-HM5bwOaIQJIQbAYfax35HCKxx7a3KrK3nBtIqJgSOitivTD1y3oW9P3rxY9RkXYPUk7y/AjAohfHKmFpGE79zw==}
     dev: true
 
   /@types/mime-types@2.1.4:
@@ -6098,18 +6260,18 @@ packages:
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     dependencies:
-      '@types/node': 20.11.5
+      '@types/node': 20.11.19
       form-data: 4.0.0
     dev: true
 
-  /@types/node@18.19.8:
-    resolution: {integrity: sha512-g1pZtPhsvGVTwmeVoexWZLTQaOvXwoSq//pTL0DHeNzUDrFnir4fgETdhjhIxjVnN+hKOuh98+E1eMLnUXstFg==}
+  /@types/node@18.19.17:
+    resolution: {integrity: sha512-SzyGKgwPzuWp2SHhlpXKzCX0pIOfcI4V2eF37nNBJOhwlegQ83omtVQ1XxZpDE06V/d6AQvfQdPfnw0tRC//Ng==}
     dependencies:
       undici-types: 5.26.5
     dev: true
 
-  /@types/node@20.11.5:
-    resolution: {integrity: sha512-g557vgQjUUfN76MZAN/dt1z3dzcUsimuysco0KeluHgrPdJXkP/XdAURgyO2W9fZWHRtRBiVKzKn8vyOAwlG+w==}
+  /@types/node@20.11.19:
+    resolution: {integrity: sha512-7xMnVEcZFu0DikYjWOlRq7NTPETrm7teqUT2WkQjrTIkEgUyyGdWsj/Zg8bEJt5TNklzbPD1X3fqfsHw3SpapQ==}
     dependencies:
       undici-types: 5.26.5
     dev: true
@@ -6137,26 +6299,26 @@ packages:
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     dev: true
 
-  /@types/react-dom@18.2.18:
-    resolution: {integrity: sha512-TJxDm6OfAX2KJWJdMEVTwWke5Sc/E/RlnPGvGfS0W7+6ocy2xhDVQVh/KvC2Uf7kACs+gDytdusDSdWfWkaNzw==}
+  /@types/react-dom@18.2.19:
+    resolution: {integrity: sha512-aZvQL6uUbIJpjZk4U8JZGbau9KDeAwMfmhyWorxgBkqDIEf6ROjRozcmPIicqsUwPUjbkDfHKgGee1Lq65APcA==}
     dependencies:
-      '@types/react': 18.2.48
+      '@types/react': 18.2.57
     dev: true
 
   /@types/react-reconciler@0.28.8:
     resolution: {integrity: sha512-SN9c4kxXZonFhbX4hJrZy37yw9e7EIxcpHCxQv5JUS18wDE5ovkQKlqQEkufdJCCMfuI9BnjUJvhYeJ9x5Ra7g==}
     dependencies:
-      '@types/react': 18.2.48
+      '@types/react': 18.2.57
     dev: false
 
   /@types/react-transition-group@4.4.10:
     resolution: {integrity: sha512-hT/+s0VQs2ojCX823m60m5f0sL5idt9SO6Tj6Dg+rdphGPIeJbJ6CxvBYkgkGKrYeDjvIpKTR38UzmtHJOGW3Q==}
     dependencies:
-      '@types/react': 18.2.48
+      '@types/react': 18.2.57
     dev: false
 
-  /@types/react@18.2.48:
-    resolution: {integrity: sha512-qboRCl6Ie70DQQG9hhNREz81jqC1cs9EVNcjQ1AU+jH6NFfSAhVVbrrY/+nSF+Bsk4AOwm9Qa61InvMCyV+H3w==}
+  /@types/react@18.2.57:
+    resolution: {integrity: sha512-ZvQsktJgSYrQiMirAN60y4O/LRevIV8hUzSOSNB6gfR3/o3wCBFQx3sPwIYtuDMeiVgsSS3UzCV26tEzgnfvQw==}
     dependencies:
       '@types/prop-types': 15.7.11
       '@types/scheduler': 0.16.8
@@ -6169,15 +6331,15 @@ packages:
   /@types/scheduler@0.16.8:
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-  /@types/semver@7.5.6:
-    resolution: {integrity: sha512-dn1l8LaMea/IjDoHNd9J52uBbInB796CDffS6VdIxvqYCPSG0V0DzHp76GpaWnlhg88uYyPbXCDIowa86ybd5A==}
+  /@types/semver@7.5.7:
+    resolution: {integrity: sha512-/wdoPq1QqkSj9/QOeKkFquEuPzQbHTWAMPH/PaUMB+JuR31lXhlWXRZ52IpfDYVlDOUBvX09uBrPwxGT1hjNBg==}
     dev: true
 
   /@types/send@0.17.4:
     resolution: {integrity: sha512-x2EM6TJOybec7c52BX0ZspPodMsQUd5L6PRwOunVyVUhXiBSKf3AezDL8Dgvgt5o0UfKNfuA0eMLr2wLT4AiBA==}
     dependencies:
       '@types/mime': 1.3.5
-      '@types/node': 20.11.5
+      '@types/node': 20.11.19
     dev: true
 
   /@types/serve-static@1.15.5:
@@ -6185,7 +6347,7 @@ packages:
     dependencies:
       '@types/http-errors': 2.0.4
       '@types/mime': 3.0.4
-      '@types/node': 20.11.5
+      '@types/node': 20.11.19
     dev: true
 
   /@types/unist@2.0.10:
@@ -6196,8 +6358,8 @@ packages:
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     dev: false
 
-  /@types/uuid@9.0.7:
-    resolution: {integrity: sha512-WUtIVRUZ9i5dYXefDEAI7sh9/O7jGvHg7Df/5O/gtH3Yabe5odI3UWopVR1qbPXQtvOxWu3mM4XxlYeZtMWF4g==}
+  /@types/uuid@9.0.8:
+    resolution: {integrity: sha512-jg+97EGIcY9AGHJJRaaPVgetKDsrTgbRjQ5Msgjh/DQKEFl0DtyRr/VCOyD1T2R1MNeWPK/u7JoGhlDZnKBAfA==}
     dev: true
 
   /@types/yargs-parser@21.0.3:
@@ -6216,49 +6378,49 @@ packages:
       '@types/yargs-parser': 21.0.3
     dev: true
 
-  /@typescript-eslint/eslint-plugin@6.19.0(@typescript-eslint/parser@6.19.0)(eslint@8.56.0)(typescript@5.3.3):
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+  /@typescript-eslint/eslint-plugin@7.0.2(@typescript-eslint/parser@7.0.2)(eslint@8.56.0)(typescript@5.3.3):
+    resolution: {integrity: sha512-/XtVZJtbaphtdrWjr+CJclaCVGPtOdBpFEnvtNf/jRV0IiEemRrL0qABex/nEt8isYcnFacm3nPHYQwL+Wb7qg==}
     engines: {node: ^16.0.0 || >=18.0.0}
     peerDependencies:
-      '@typescript-eslint/parser': ^6.0.0 || ^6.0.0-alpha
-      eslint: ^7.0.0 || ^8.0.0
+      '@typescript-eslint/parser': ^7.0.0
+      eslint: ^8.56.0
       typescript: '*'
     peerDependenciesMeta:
       typescript:
         optional: true
     dependencies:
       '@eslint-community/regexpp': 4.10.0
-      '@typescript-eslint/parser': 6.19.0(eslint@8.56.0)(typescript@5.3.3)
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-      '@typescript-eslint/type-utils': 6.19.0(eslint@8.56.0)(typescript@5.3.3)
-      '@typescript-eslint/utils': 6.19.0(eslint@8.56.0)(typescript@5.3.3)
-      '@typescript-eslint/visitor-keys': 6.19.0
+      '@typescript-eslint/parser': 7.0.2(eslint@8.56.0)(typescript@5.3.3)
+      '@typescript-eslint/scope-manager': 7.0.2
+      '@typescript-eslint/type-utils': 7.0.2(eslint@8.56.0)(typescript@5.3.3)
+      '@typescript-eslint/utils': 7.0.2(eslint@8.56.0)(typescript@5.3.3)
+      '@typescript-eslint/visitor-keys': 7.0.2
       debug: 4.3.4
       eslint: 8.56.0
       graphemer: 1.4.0
-      ignore: 5.3.0
+      ignore: 5.3.1
       natural-compare: 1.4.0
-      semver: 7.5.4
-      ts-api-utils: 1.0.3(typescript@5.3.3)
+      semver: 7.6.0
+      ts-api-utils: 1.2.1(typescript@5.3.3)
       typescript: 5.3.3
     transitivePeerDependencies:
       - supports-color
     dev: true
 
-  /@typescript-eslint/parser@6.19.0(eslint@8.56.0)(typescript@5.3.3):
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+  /@typescript-eslint/parser@7.0.2(eslint@8.56.0)(typescript@5.3.3):
+    resolution: {integrity: sha512-GdwfDglCxSmU+QTS9vhz2Sop46ebNCXpPPvsByK7hu0rFGRHL+AusKQJ7SoN+LbLh6APFpQwHKmDSwN35Z700Q==}
     engines: {node: ^16.0.0 || >=18.0.0}
     peerDependencies:
-      eslint: ^7.0.0 || ^8.0.0
+      eslint: ^8.56.0
       typescript: '*'
     peerDependenciesMeta:
       typescript:
         optional: true
     dependencies:
-      '@typescript-eslint/scope-manager': 6.19.0
-      '@typescript-eslint/types': 6.19.0
-      '@typescript-eslint/typescript-estree': 6.19.0(typescript@5.3.3)
-      '@typescript-eslint/visitor-keys': 6.19.0
+      '@typescript-eslint/scope-manager': 7.0.2
+      '@typescript-eslint/types': 7.0.2
+      '@typescript-eslint/typescript-estree': 7.0.2(typescript@5.3.3)
+      '@typescript-eslint/visitor-keys': 7.0.2
       debug: 4.3.4
       eslint: 8.56.0
       typescript: 5.3.3
@@ -6274,29 +6436,29 @@ packages:
       '@typescript-eslint/visitor-keys': 5.62.0
     dev: true
 
-  /@typescript-eslint/scope-manager@6.19.0:
-    resolution: {integrity: sha512-dO1XMhV2ehBI6QN8Ufi7I10wmUovmLU0Oru3n5LVlM2JuzB4M+dVphCPLkVpKvGij2j/pHBWuJ9piuXx+BhzxQ==}
+  /@typescript-eslint/scope-manager@7.0.2:
+    resolution: {integrity: sha512-l6sa2jF3h+qgN2qUMjVR3uCNGjWw4ahGfzIYsCtFrQJCjhbrDPdiihYT8FnnqFwsWX+20hK592yX9I2rxKTP4g==}
     engines: {node: ^16.0.0 || >=18.0.0}
     dependencies:
-      '@typescript-eslint/types': 6.19.0
-      '@typescript-eslint/visitor-keys': 6.19.0
+      '@typescript-eslint/types': 7.0.2
+      '@typescript-eslint/visitor-keys': 7.0.2
     dev: true
 
-  /@typescript-eslint/type-utils@6.19.0(eslint@8.56.0)(typescript@5.3.3):
-    resolution: {integrity: sha512-mcvS6WSWbjiSxKCwBcXtOM5pRkPQ6kcDds/juxcy/727IQr3xMEcwr/YLHW2A2+Fp5ql6khjbKBzOyjuPqGi/w==}
+  /@typescript-eslint/type-utils@7.0.2(eslint@8.56.0)(typescript@5.3.3):
+    resolution: {integrity: sha512-IKKDcFsKAYlk8Rs4wiFfEwJTQlHcdn8CLwLaxwd6zb8HNiMcQIFX9sWax2k4Cjj7l7mGS5N1zl7RCHOVwHq2VQ==}
     engines: {node: ^16.0.0 || >=18.0.0}
     peerDependencies:
-      eslint: ^7.0.0 || ^8.0.0
+      eslint: ^8.56.0
       typescript: '*'
     peerDependenciesMeta:
       typescript:
         optional: true
     dependencies:
-      '@typescript-eslint/typescript-estree': 6.19.0(typescript@5.3.3)
-      '@typescript-eslint/utils': 6.19.0(eslint@8.56.0)(typescript@5.3.3)
+      '@typescript-eslint/typescript-estree': 7.0.2(typescript@5.3.3)
+      '@typescript-eslint/utils': 7.0.2(eslint@8.56.0)(typescript@5.3.3)
       debug: 4.3.4
       eslint: 8.56.0
-      ts-api-utils: 1.0.3(typescript@5.3.3)
+      ts-api-utils: 1.2.1(typescript@5.3.3)
       typescript: 5.3.3
     transitivePeerDependencies:
       - supports-color
@@ -6312,8 +6474,8 @@ packages:
     engines: {node: ^12.22.0 || ^14.17.0 || >=16.0.0}
     dev: true
 
-  /@typescript-eslint/types@6.19.0:
-    resolution: {integrity: sha512-lFviGV/vYhOy3m8BJ/nAKoAyNhInTdXpftonhWle66XHAtT1ouBlkjL496b5H5hb8dWXHwtypTqgtb/DEa+j5A==}
+  /@typescript-eslint/types@7.0.2:
+    resolution: {integrity: sha512-ZzcCQHj4JaXFjdOql6adYV4B/oFOFjPOC9XYwCaZFRvqN8Llfvv4gSxrkQkd2u4Ci62i2c6W6gkDwQJDaRc4nA==}
     engines: {node: ^16.0.0 || >=18.0.0}
     dev: true
 
@@ -6331,7 +6493,7 @@ packages:
       debug: 4.3.4
       globby: 11.1.0
       is-glob: 4.0.3
-      semver: 7.5.4
+      semver: 7.6.0
       tsutils: 3.21.0(typescript@3.9.10)
       typescript: 3.9.10
     transitivePeerDependencies:
@@ -6352,7 +6514,7 @@ packages:
       debug: 4.3.4
       globby: 11.1.0
       is-glob: 4.0.3
-      semver: 7.5.4
+      semver: 7.6.0
       tsutils: 3.21.0(typescript@4.9.5)
       typescript: 4.9.5
     transitivePeerDependencies:
@@ -6373,15 +6535,15 @@ packages:
       debug: 4.3.4
       globby: 11.1.0
       is-glob: 4.0.3
-      semver: 7.5.4
+      semver: 7.6.0
       tsutils: 3.21.0(typescript@5.3.3)
       typescript: 5.3.3
     transitivePeerDependencies:
       - supports-color
     dev: true
 
-  /@typescript-eslint/typescript-estree@6.19.0(typescript@5.3.3):
-    resolution: {integrity: sha512-o/zefXIbbLBZ8YJ51NlkSAt2BamrK6XOmuxSR3hynMIzzyMY33KuJ9vuMdFSXW+H0tVvdF9qBPTHA91HDb4BIQ==}
+  /@typescript-eslint/typescript-estree@7.0.2(typescript@5.3.3):
+    resolution: {integrity: sha512-3AMc8khTcELFWcKcPc0xiLviEvvfzATpdPj/DXuOGIdQIIFybf4DMT1vKRbuAEOFMwhWt7NFLXRkbjsvKZQyvw==}
     engines: {node: ^16.0.0 || >=18.0.0}
     peerDependencies:
       typescript: '*'
@@ -6389,14 +6551,14 @@ packages:
       typescript:
         optional: true
     dependencies:
-      '@typescript-eslint/types': 6.19.0
-      '@typescript-eslint/visitor-keys': 6.19.0
+      '@typescript-eslint/types': 7.0.2
+      '@typescript-eslint/visitor-keys': 7.0.2
       debug: 4.3.4
       globby: 11.1.0
       is-glob: 4.0.3
       minimatch: 9.0.3
-      semver: 7.5.4
-      ts-api-utils: 1.0.3(typescript@5.3.3)
+      semver: 7.6.0
+      ts-api-utils: 1.2.1(typescript@5.3.3)
       typescript: 5.3.3
     transitivePeerDependencies:
       - supports-color
@@ -6410,32 +6572,32 @@ packages:
     dependencies:
       '@eslint-community/eslint-utils': 4.4.0(eslint@8.56.0)
       '@types/json-schema': 7.0.15
-      '@types/semver': 7.5.6
+      '@types/semver': 7.5.7
       '@typescript-eslint/scope-manager': 5.62.0
       '@typescript-eslint/types': 5.62.0
       '@typescript-eslint/typescript-estree': 5.62.0(typescript@5.3.3)
       eslint: 8.56.0
       eslint-scope: 5.1.1
-      semver: 7.5.4
+      semver: 7.6.0
     transitivePeerDependencies:
       - supports-color
       - typescript
     dev: true
 
-  /@typescript-eslint/utils@6.19.0(eslint@8.56.0)(typescript@5.3.3):
-    resolution: {integrity: sha512-QR41YXySiuN++/dC9UArYOg4X86OAYP83OWTewpVx5ct1IZhjjgTLocj7QNxGhWoTqknsgpl7L+hGygCO+sdYw==}
+  /@typescript-eslint/utils@7.0.2(eslint@8.56.0)(typescript@5.3.3):
+    resolution: {integrity: sha512-PZPIONBIB/X684bhT1XlrkjNZJIEevwkKDsdwfiu1WeqBxYEEdIgVDgm8/bbKHVu+6YOpeRqcfImTdImx/4Bsw==}
     engines: {node: ^16.0.0 || >=18.0.0}
     peerDependencies:
-      eslint: ^7.0.0 || ^8.0.0
+      eslint: ^8.56.0
     dependencies:
       '@eslint-community/eslint-utils': 4.4.0(eslint@8.56.0)
       '@types/json-schema': 7.0.15
-      '@types/semver': 7.5.6
-      '@typescript-eslint/scope-manager': 6.19.0
-      '@typescript-eslint/types': 6.19.0
-      '@typescript-eslint/typescript-estree': 6.19.0(typescript@5.3.3)
+      '@types/semver': 7.5.7
+      '@typescript-eslint/scope-manager': 7.0.2
+      '@typescript-eslint/types': 7.0.2
+      '@typescript-eslint/typescript-estree': 7.0.2(typescript@5.3.3)
       eslint: 8.56.0
-      semver: 7.5.4
+      semver: 7.6.0
     transitivePeerDependencies:
       - supports-color
       - typescript
@@ -6457,11 +6619,11 @@ packages:
       eslint-visitor-keys: 3.4.3
     dev: true
 
-  /@typescript-eslint/visitor-keys@6.19.0:
-    resolution: {integrity: sha512-hZaUCORLgubBvtGpp1JEFEazcuEdfxta9j4iUwdSAr7mEsYYAp3EAUyCZk3VEEqGj6W+AV4uWyrDGtrlawAsgQ==}
+  /@typescript-eslint/visitor-keys@7.0.2:
+    resolution: {integrity: sha512-8Y+YiBmqPighbm5xA2k4wKTxRzx9EkBu7Rlw+WHqMvRJ3RPz/BMBO9b2ru0LUNmXg120PHUXD5+SWFy2R8DqlQ==}
     engines: {node: ^16.0.0 || >=18.0.0}
     dependencies:
-      '@typescript-eslint/types': 6.19.0
+      '@typescript-eslint/types': 7.0.2
       eslint-visitor-keys: 3.4.3
     dev: true
 
@@ -6469,29 +6631,29 @@ packages:
     resolution: {integrity: sha512-zuVdFrMJiuCDQUMCzQaD6KL28MjnqqN8XnAqiEq9PNm/hCPTSGfrXCOfwj1ow4LFb/tNymJPwsNbVePc1xFqrQ==}
     dev: true
 
-  /@vitejs/plugin-react-swc@3.5.0(vite@5.0.12):
-    resolution: {integrity: sha512-1PrOvAaDpqlCV+Up8RkAh9qaiUjoDUcjtttyhXDKw53XA6Ve16SOp6cCOpRs8Dj8DqUQs6eTW5YkLcLJjrXAig==}
+  /@vitejs/plugin-react-swc@3.6.0(vite@5.1.3):
+    resolution: {integrity: sha512-XFRbsGgpGxGzEV5i5+vRiro1bwcIaZDIdBRP16qwm+jP68ue/S8FJTBEgOeojtVDYrbSua3XFp71kC8VJE6v+g==}
     peerDependencies:
       vite: ^4 || ^5
     dependencies:
-      '@swc/core': 1.3.101
-      vite: 5.0.12(@types/node@20.11.5)
+      '@swc/core': 1.4.2
+      vite: 5.1.3(@types/node@20.11.19)
     transitivePeerDependencies:
       - '@swc/helpers'
     dev: true
 
-  /@vitejs/plugin-react@3.1.0(vite@5.0.12):
+  /@vitejs/plugin-react@3.1.0(vite@5.1.3):
     resolution: {integrity: sha512-AfgcRL8ZBhAlc3BFdigClmTUMISmmzHn7sB2h9U1odvc5U/MjWXsAaz18b/WoppUTDBzxOJwo2VdClfUcItu9g==}
     engines: {node: ^14.18.0 || >=16.0.0}
     peerDependencies:
       vite: ^4.1.0-beta.0
     dependencies:
-      '@babel/core': 7.23.7
-      '@babel/plugin-transform-react-jsx-self': 7.23.3(@babel/core@7.23.7)
-      '@babel/plugin-transform-react-jsx-source': 7.23.3(@babel/core@7.23.7)
+      '@babel/core': 7.23.9
+      '@babel/plugin-transform-react-jsx-self': 7.23.3(@babel/core@7.23.9)
+      '@babel/plugin-transform-react-jsx-source': 7.23.3(@babel/core@7.23.9)
       magic-string: 0.27.0
       react-refresh: 0.14.0
-      vite: 5.0.12(@types/node@20.11.5)
+      vite: 5.1.3(@types/node@20.11.19)
     transitivePeerDependencies:
       - supports-color
     dev: true
@@ -6504,26 +6666,26 @@ packages:
       chai: 4.4.1
     dev: true
 
-  /@vitest/expect@1.2.2:
-    resolution: {integrity: sha512-3jpcdPAD7LwHUUiT2pZTj2U82I2Tcgg2oVPvKxhn6mDI2On6tfvPQTjAI4628GUGDZrCm4Zna9iQHm5cEexOAg==}
+  /@vitest/expect@1.3.1:
+    resolution: {integrity: sha512-xofQFwIzfdmLLlHa6ag0dPV8YsnKOCP1KdAeVVh34vSjN2dcUiXYCD9htu/9eM7t8Xln4v03U9HLxLpPlsXdZw==}
     dependencies:
-      '@vitest/spy': 1.2.2
-      '@vitest/utils': 1.2.2
+      '@vitest/spy': 1.3.1
+      '@vitest/utils': 1.3.1
       chai: 4.4.1
     dev: true
 
-  /@vitest/runner@1.2.2:
-    resolution: {integrity: sha512-JctG7QZ4LSDXr5CsUweFgcpEvrcxOV1Gft7uHrvkQ+fsAVylmWQvnaAr/HDp3LAH1fztGMQZugIheTWjaGzYIg==}
+  /@vitest/runner@1.3.1:
+    resolution: {integrity: sha512-5FzF9c3jG/z5bgCnjr8j9LNq/9OxV2uEBAITOXfoe3rdZJTdO7jzThth7FXv/6b+kdY65tpRQB7WaKhNZwX+Kg==}
     dependencies:
-      '@vitest/utils': 1.2.2
+      '@vitest/utils': 1.3.1
       p-limit: 5.0.0
       pathe: 1.1.2
     dev: true
 
-  /@vitest/snapshot@1.2.2:
-    resolution: {integrity: sha512-SmGY4saEw1+bwE1th6S/cZmPxz/Q4JWsl7LvbQIky2tKE35US4gd0Mjzqfr84/4OD0tikGWaWdMja/nWL5NIPA==}
+  /@vitest/snapshot@1.3.1:
+    resolution: {integrity: sha512-EF++BZbt6RZmOlE3SuTPu/NfwBF6q4ABS37HHXzs2LUVPBLx2QoY/K0fKpRChSo8eLiuxcbCVfqKgx/dplCDuQ==}
     dependencies:
-      magic-string: 0.30.5
+      magic-string: 0.30.7
       pathe: 1.1.2
       pretty-format: 29.7.0
     dev: true
@@ -6531,13 +6693,13 @@ packages:
   /@vitest/spy@0.34.7:
     resolution: {integrity: sha512-NMMSzOY2d8L0mcOt4XcliDOS1ISyGlAXuQtERWVOoVHnKwmG+kKhinAiGw3dTtMQWybfa89FG8Ucg9tiC/FhTQ==}
     dependencies:
-      tinyspy: 2.2.0
+      tinyspy: 2.2.1
     dev: true
 
-  /@vitest/spy@1.2.2:
-    resolution: {integrity: sha512-k9Gcahssw8d7X3pSLq3e3XEu/0L78mUkCjivUqCQeXJm9clfXR/Td8+AP+VC1O6fKPIDLcHDTAmBOINVuv6+7g==}
+  /@vitest/spy@1.3.1:
+    resolution: {integrity: sha512-xAcW+S099ylC9VLU7eZfdT9myV67Nor9w9zhf0mGCYJSO+zM2839tOeROTdikOi/8Qeusffvxb/MyBSOja1Uig==}
     dependencies:
-      tinyspy: 2.2.0
+      tinyspy: 2.2.1
     dev: true
 
   /@vitest/utils@0.34.7:
@@ -6548,8 +6710,8 @@ packages:
       pretty-format: 29.7.0
     dev: true
 
-  /@vitest/utils@1.2.2:
-    resolution: {integrity: sha512-WKITBHLsBHlpjnDQahr+XK6RE7MiAsgrIkr0pGhQ9ygoxBfUeG0lUG5iLlzqjmKSlBv3+j5EGsriBzh+C3Tq9g==}
+  /@vitest/utils@1.3.1:
+    resolution: {integrity: sha512-d3Waie/299qqRyHTm2DjADeTaNdNSVsnwHPWrs20JMpjh6eiVq7ggggweO8rc4arhf6rRkWuHKwvxGvejUXZZQ==}
     dependencies:
       diff-sequences: 29.6.3
       estree-walker: 3.0.3
@@ -6576,21 +6738,21 @@ packages:
       path-browserify: 1.0.1
     dev: true
 
-  /@vue/compiler-core@3.4.15:
-    resolution: {integrity: sha512-XcJQVOaxTKCnth1vCxEChteGuwG6wqnUHxAm1DO3gCz0+uXKaJNx8/digSz4dLALCy8n2lKq24jSUs8segoqIw==}
+  /@vue/compiler-core@3.4.19:
+    resolution: {integrity: sha512-gj81785z0JNzRcU0Mq98E56e4ltO1yf8k5PQ+tV/7YHnbZkrM0fyFyuttnN8ngJZjbpofWE/m4qjKBiLl8Ju4w==}
     dependencies:
-      '@babel/parser': 7.23.6
-      '@vue/shared': 3.4.15
+      '@babel/parser': 7.23.9
+      '@vue/shared': 3.4.19
       entities: 4.5.0
       estree-walker: 2.0.2
       source-map-js: 1.0.2
     dev: true
 
-  /@vue/compiler-dom@3.4.15:
-    resolution: {integrity: sha512-wox0aasVV74zoXyblarOM3AZQz/Z+OunYcIHe1OsGclCHt8RsRm04DObjefaI82u6XDzv+qGWZ24tIsRAIi5MQ==}
+  /@vue/compiler-dom@3.4.19:
+    resolution: {integrity: sha512-vm6+cogWrshjqEHTzIDCp72DKtea8Ry/QVpQRYoyTIg9k7QZDX6D8+HGURjtmatfgM8xgCFtJJaOlCaRYRK3QA==}
     dependencies:
-      '@vue/compiler-core': 3.4.15
-      '@vue/shared': 3.4.15
+      '@vue/compiler-core': 3.4.19
+      '@vue/shared': 3.4.19
     dev: true
 
   /@vue/language-core@1.8.27(typescript@5.3.3):
@@ -6603,8 +6765,8 @@ packages:
     dependencies:
       '@volar/language-core': 1.11.1
       '@volar/source-map': 1.11.1
-      '@vue/compiler-dom': 3.4.15
-      '@vue/shared': 3.4.15
+      '@vue/compiler-dom': 3.4.19
+      '@vue/shared': 3.4.19
       computeds: 0.0.1
       minimatch: 9.0.3
       muggle-string: 0.3.1
@@ -6613,8 +6775,8 @@ packages:
       vue-template-compiler: 2.7.16
     dev: true
 
-  /@vue/shared@3.4.15:
-    resolution: {integrity: sha512-KzfPTxVaWfB+eGcGdbSf4CWdaXcGDqckoeXUh7SB3fZdEtzPCK2Vq9B/lRRL3yutax/LWITz+SwvgyOxz5V75g==}
+  /@vue/shared@3.4.19:
+    resolution: {integrity: sha512-/KliRRHMF6LoiThEy+4c1Z4KB/gbPrGjWwJR+crg2otgrf/egKzRaCPvJ51S5oetgsgXLfc4Rm5ZgrKHZrtMSw==}
     dev: true
 
   /@xobotyi/scrollbar-width@1.9.5:
@@ -7224,12 +7386,12 @@ packages:
       acorn: 7.4.1
     dev: true
 
-  /acorn-jsx@5.3.2(acorn@8.11.2):
+  /acorn-jsx@5.3.2(acorn@8.11.3):
     resolution: {integrity: sha512-rq9s+JNhf0IChjtDXxllJ7g41oZk5SlXtp0LHwyA5cejwn7vKmKp4pPri6YEePv2PU65sAsegbXtIinmDFDXgQ==}
     peerDependencies:
       acorn: ^6.0.0 || ^7.0.0 || ^8.0.0
     dependencies:
-      acorn: 8.11.2
+      acorn: 8.11.3
     dev: true
 
   /acorn-walk@7.2.0:
@@ -7248,12 +7410,6 @@ packages:
     hasBin: true
     dev: true
 
-  /acorn@8.11.2:
-    resolution: {integrity: sha512-nc0Axzp/0FILLEVsm4fNwLCwMttvhEI263QtVPQcbpfZZ3ts0hLsZGOpE6czNlid7CJ9MlyH8reXkpsf3YUY4w==}
-    engines: {node: '>=0.4.0'}
-    hasBin: true
-    dev: true
-
   /acorn@8.11.3:
     resolution: {integrity: sha512-Y9rRfJG5jcKOE0CLisYbojUjIrIEE7AGMzA/Sm4BslANhbS+cDMpgBdcPT91oJ7OuJ9hYJBx59RjbhxVnrF8Xg==}
     engines: {node: '>=0.4.0'}
@@ -7373,11 +7529,12 @@ packages:
       dequal: 2.0.3
     dev: true
 
-  /array-buffer-byte-length@1.0.0:
-    resolution: {integrity: sha512-LPuwb2P+NrQw3XhxGc36+XSvuBPopovXYTR9Ew++Du9Yb/bx5AzBfrIsBoj0EZUifjQU+sHL21sseZ3jerWO/A==}
+  /array-buffer-byte-length@1.0.1:
+    resolution: {integrity: sha512-ahC5W1xgou+KTXix4sAO8Ki12Q+jf4i0+tmk3sC+zgcynshkHxzpXdImBehiUYKKKDwvfFiJl1tZt6ewscS1Mg==}
+    engines: {node: '>= 0.4'}
     dependencies:
-      call-bind: 1.0.5
-      is-array-buffer: 3.0.2
+      call-bind: 1.0.7
+      is-array-buffer: 3.0.4
     dev: true
 
   /array-flatten@1.1.1:
@@ -7388,10 +7545,10 @@ packages:
     resolution: {integrity: sha512-dlcsNBIiWhPkHdOEEKnehA+RNUWDc4UqFtnIXU4uuYDPtA4LDkr7qip2p0VvFAEXNDr0yWZ9PJyIRiGjRLQzwQ==}
     engines: {node: '>= 0.4'}
     dependencies:
-      call-bind: 1.0.5
+      call-bind: 1.0.7
       define-properties: 1.2.1
-      es-abstract: 1.22.3
-      get-intrinsic: 1.2.2
+      es-abstract: 1.22.4
+      get-intrinsic: 1.2.4
       is-string: 1.0.7
     dev: true
 
@@ -7400,24 +7557,35 @@ packages:
     engines: {node: '>=8'}
     dev: true
 
-  /array.prototype.findlastindex@1.2.3:
-    resolution: {integrity: sha512-LzLoiOMAxvy+Gd3BAq3B7VeIgPdo+Q8hthvKtXybMvRV0jrXfJM/t8mw7nNlpEcVlVUnCnM2KSX4XU5HmpodOA==}
+  /array.prototype.filter@1.0.3:
+    resolution: {integrity: sha512-VizNcj/RGJiUyQBgzwxzE5oHdeuXY5hSbbmKMlphj1cy1Vl7Pn2asCGbSrru6hSQjmCzqTBPVWAF/whmEOVHbw==}
     engines: {node: '>= 0.4'}
     dependencies:
-      call-bind: 1.0.5
+      call-bind: 1.0.7
       define-properties: 1.2.1
-      es-abstract: 1.22.3
+      es-abstract: 1.22.4
+      es-array-method-boxes-properly: 1.0.0
+      is-string: 1.0.7
+    dev: true
+
+  /array.prototype.findlastindex@1.2.4:
+    resolution: {integrity: sha512-hzvSHUshSpCflDR1QMUBLHGHP1VIEBegT4pix9H/Z92Xw3ySoy6c2qh7lJWTJnRJ8JCZ9bJNCgTyYaJGcJu6xQ==}
+    engines: {node: '>= 0.4'}
+    dependencies:
+      call-bind: 1.0.7
+      define-properties: 1.2.1
+      es-abstract: 1.22.4
+      es-errors: 1.3.0
       es-shim-unscopables: 1.0.2
-      get-intrinsic: 1.2.2
     dev: true
 
   /array.prototype.flat@1.3.2:
     resolution: {integrity: sha512-djYB+Zx2vLewY8RWlNCUdHjDXs2XOgm602S9E7P/UpHgfeHL00cRiIF+IN/G/aUJ7kGPb6yO/ErDI5V2s8iycA==}
     engines: {node: '>= 0.4'}
     dependencies:
-      call-bind: 1.0.5
+      call-bind: 1.0.7
       define-properties: 1.2.1
-      es-abstract: 1.22.3
+      es-abstract: 1.22.4
       es-shim-unscopables: 1.0.2
     dev: true
 
@@ -7425,39 +7593,40 @@ packages:
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     engines: {node: '>= 0.4'}
     dependencies:
-      call-bind: 1.0.5
+      call-bind: 1.0.7
       define-properties: 1.2.1
-      es-abstract: 1.22.3
+      es-abstract: 1.22.4
       es-shim-unscopables: 1.0.2
     dev: true
 
-  /array.prototype.tosorted@1.1.2:
-    resolution: {integrity: sha512-HuQCHOlk1Weat5jzStICBCd83NxiIMwqDg/dHEsoefabn/hJRj5pVdWcPUSpRrwhwxZOsQassMpgN/xRYFBMIg==}
+  /array.prototype.tosorted@1.1.3:
+    resolution: {integrity: sha512-/DdH4TiTmOKzyQbp/eadcCVexiCb36xJg7HshYOYJnNZFDj33GEv0P7GxsynpShhq4OLYJzbGcBDkLsDt7MnNg==}
     dependencies:
-      call-bind: 1.0.5
+      call-bind: 1.0.7
       define-properties: 1.2.1
-      es-abstract: 1.22.3
+      es-abstract: 1.22.4
+      es-errors: 1.3.0
       es-shim-unscopables: 1.0.2
-      get-intrinsic: 1.2.2
     dev: true
 
-  /arraybuffer.prototype.slice@1.0.2:
-    resolution: {integrity: sha512-yMBKppFur/fbHu9/6USUe03bZ4knMYiwFBcyiaXB8Go0qNehwX6inYPzK9U0NeQvGxKthcmHcaR8P5MStSRBAw==}
+  /arraybuffer.prototype.slice@1.0.3:
+    resolution: {integrity: sha512-bMxMKAjg13EBSVscxTaYA4mRc5t1UAXa2kXiGTNfZ079HIWXEkKmkgFrh/nJqamaLSrXO5H4WFFkPEaLJWbs3A==}
     engines: {node: '>= 0.4'}
     dependencies:
-      array-buffer-byte-length: 1.0.0
-      call-bind: 1.0.5
+      array-buffer-byte-length: 1.0.1
+      call-bind: 1.0.7
       define-properties: 1.2.1
-      es-abstract: 1.22.3
-      get-intrinsic: 1.2.2
-      is-array-buffer: 3.0.2
+      es-abstract: 1.22.4
+      es-errors: 1.3.0
+      get-intrinsic: 1.2.4
+      is-array-buffer: 3.0.4
       is-shared-array-buffer: 1.0.2
     dev: true
 
   /assert@2.1.0:
     resolution: {integrity: sha512-eLHpSK/Y4nhMJ07gDaAzoX/XAKS8PSaojml3M0DM4JpV1LAi5JOJ/p6H/XWrl8L+DzVEvVCW1z3vWAaB9oTsQw==}
     dependencies:
-      call-bind: 1.0.5
+      call-bind: 1.0.7
       is-nan: 1.3.2
       object-is: 1.1.5
       object.assign: 4.1.5
@@ -7512,17 +7681,19 @@ packages:
     engines: {node: '>=4'}
     dev: false
 
-  /available-typed-arrays@1.0.5:
-    resolution: {integrity: sha512-DMD0KiN46eipeziST1LPP/STfDU0sufISXmjSgvVsoU2tqxctQeASejWcfNtxYKqETM1UxQ8sp2OrSBWpHY6sw==}
+  /available-typed-arrays@1.0.7:
+    resolution: {integrity: sha512-wvUjBtSGN7+7SjNpq/9M2Tg350UZD3q62IFZLbRAR1bSMlCo1ZaeW+BJ+D090e4hIIZLBcTDWe4Mh4jvUDajzQ==}
     engines: {node: '>= 0.4'}
+    dependencies:
+      possible-typed-array-names: 1.0.0
     dev: true
 
-  /babel-core@7.0.0-bridge.0(@babel/core@7.23.7):
+  /babel-core@7.0.0-bridge.0(@babel/core@7.23.9):
     resolution: {integrity: sha512-poPX9mZH/5CSanm50Q+1toVci6pv5KSRv/5TWCwtzQS5XEwn40BcCrgIeMFWP9CKKIniKXNxoIOnOq4VVlGXhg==}
     peerDependencies:
       '@babel/core': ^7.0.0-0
     dependencies:
-      '@babel/core': 7.23.7
+      '@babel/core': 7.23.9
     dev: true
 
   /babel-plugin-istanbul@6.1.1:
@@ -7542,43 +7713,43 @@ packages:
     resolution: {integrity: sha512-Cg7TFGpIr01vOQNODXOOaGz2NpCU5gl8x1qJFbb6hbZxR7XrcE2vtbAsTAbJ7/xwJtUuJEw8K8Zr/AE0LHlesg==}
     engines: {node: '>=10', npm: '>=6'}
     dependencies:
-      '@babel/runtime': 7.23.8
+      '@babel/runtime': 7.23.9
       cosmiconfig: 7.1.0
       resolve: 1.22.8
     dev: false
 
-  /babel-plugin-polyfill-corejs2@0.4.8(@babel/core@7.23.7):
+  /babel-plugin-polyfill-corejs2@0.4.8(@babel/core@7.23.9):
     resolution: {integrity: sha512-OtIuQfafSzpo/LhnJaykc0R/MMnuLSSVjVYy9mHArIZ9qTCSZ6TpWCuEKZYVoN//t8HqBNScHrOtCrIK5IaGLg==}
     peerDependencies:
       '@babel/core': ^7.4.0 || ^8.0.0-0 <8.0.0
     dependencies:
       '@babel/compat-data': 7.23.5
-      '@babel/core': 7.23.7
-      '@babel/helper-define-polyfill-provider': 0.5.0(@babel/core@7.23.7)
+      '@babel/core': 7.23.9
+      '@babel/helper-define-polyfill-provider': 0.5.0(@babel/core@7.23.9)
       semver: 6.3.1
     transitivePeerDependencies:
       - supports-color
     dev: true
 
-  /babel-plugin-polyfill-corejs3@0.8.7(@babel/core@7.23.7):
-    resolution: {integrity: sha512-KyDvZYxAzkC0Aj2dAPyDzi2Ym15e5JKZSK+maI7NAwSqofvuFglbSsxE7wUOvTg9oFVnHMzVzBKcqEb4PJgtOA==}
+  /babel-plugin-polyfill-corejs3@0.9.0(@babel/core@7.23.9):
+    resolution: {integrity: sha512-7nZPG1uzK2Ymhy/NbaOWTg3uibM2BmGASS4vHS4szRZAIR8R6GwA/xAujpdrXU5iyklrimWnLWU+BLF9suPTqg==}
     peerDependencies:
       '@babel/core': ^7.4.0 || ^8.0.0-0 <8.0.0
     dependencies:
-      '@babel/core': 7.23.7
-      '@babel/helper-define-polyfill-provider': 0.4.4(@babel/core@7.23.7)
-      core-js-compat: 3.35.0
+      '@babel/core': 7.23.9
+      '@babel/helper-define-polyfill-provider': 0.5.0(@babel/core@7.23.9)
+      core-js-compat: 3.36.0
     transitivePeerDependencies:
       - supports-color
     dev: true
 
-  /babel-plugin-polyfill-regenerator@0.5.5(@babel/core@7.23.7):
+  /babel-plugin-polyfill-regenerator@0.5.5(@babel/core@7.23.9):
     resolution: {integrity: sha512-OJGYZlhLqBh2DDHeqAxWB1XIvr49CxiJ2gIt61/PU55CQK4Z58OzMqjDe1zwQdQk+rBYsRc+1rJmdajM3gimHg==}
     peerDependencies:
       '@babel/core': ^7.4.0 || ^8.0.0-0 <8.0.0
     dependencies:
-      '@babel/core': 7.23.7
-      '@babel/helper-define-polyfill-provider': 0.5.0(@babel/core@7.23.7)
+      '@babel/core': 7.23.9
+      '@babel/helper-define-polyfill-provider': 0.5.0(@babel/core@7.23.9)
     transitivePeerDependencies:
       - supports-color
     dev: true
@@ -7677,15 +7848,15 @@ packages:
       pako: 0.2.9
     dev: true
 
-  /browserslist@4.22.2:
-    resolution: {integrity: sha512-0UgcrvQmBDvZHFGdYUehrCNIazki7/lUP3kkoi/r3YB2amZbFM9J43ZRkJTXBUZK4gmx56+Sqk9+Vs9mwZx9+A==}
+  /browserslist@4.23.0:
+    resolution: {integrity: sha512-QW8HiM1shhT2GuzkvklfjcKDiWFXHOeFCIA/huJPwHsslwcydgk7X+z2zXpEijP98UCY7HbubZt5J2Zgvf0CaQ==}
     engines: {node: ^6 || ^7 || ^8 || ^9 || ^10 || ^11 || ^12 || >=13.7}
     hasBin: true
     dependencies:
-      caniuse-lite: 1.0.30001579
-      electron-to-chromium: 1.4.639
+      caniuse-lite: 1.0.30001588
+      electron-to-chromium: 1.4.677
       node-releases: 2.0.14
-      update-browserslist-db: 1.0.13(browserslist@4.22.2)
+      update-browserslist-db: 1.0.13(browserslist@4.23.0)
     dev: true
 
   /bser@2.1.1:
@@ -7724,12 +7895,15 @@ packages:
     engines: {node: '>=8'}
     dev: true
 
-  /call-bind@1.0.5:
-    resolution: {integrity: sha512-C3nQxfFZxFRVoJoGKKI8y3MOEo129NQ+FgQ08iye+Mk4zNZZGdjfs06bVTr+DBSlA66Q2VEcMki/cUCP4SercQ==}
+  /call-bind@1.0.7:
+    resolution: {integrity: sha512-GHTSNSYICQ7scH7sZ+M2rFopRoLh8t2bLSW6BbgrtLsahOIB5iyAVJf9GjWK3cYTDaMj4XdBpM1cA6pIS0Kv2w==}
+    engines: {node: '>= 0.4'}
     dependencies:
+      es-define-property: 1.0.0
+      es-errors: 1.3.0
       function-bind: 1.1.2
-      get-intrinsic: 1.2.2
-      set-function-length: 1.1.1
+      get-intrinsic: 1.2.4
+      set-function-length: 1.2.1
     dev: true
 
   /callsites@3.1.0:
@@ -7741,8 +7915,8 @@ packages:
     engines: {node: '>=6'}
     dev: true
 
-  /caniuse-lite@1.0.30001579:
-    resolution: {integrity: sha512-u5AUVkixruKHJjw/pj9wISlcMpgFWzSrczLZbrqBSxukQixmg0SJ5sZTpvaFvxU0HoQKd4yoyAogyrAz9pzJnA==}
+  /caniuse-lite@1.0.30001588:
+    resolution: {integrity: sha512-+hVY9jE44uKLkH0SrUTqxjxqNTOWHsbnQDIKjwkZ3lNTzUUVdBLBGXtj/q5Mp5u98r3droaZAewQuEDzjQdZlQ==}
     dev: true
 
   /chai@4.4.1:
@@ -7758,7 +7932,7 @@ packages:
       type-detect: 4.0.8
     dev: true
 
-  /chakra-react-select@4.7.6(@chakra-ui/form-control@2.2.0)(@chakra-ui/icon@3.2.0)(@chakra-ui/layout@2.3.1)(@chakra-ui/media-query@3.3.0)(@chakra-ui/menu@2.2.1)(@chakra-ui/spinner@2.1.0)(@chakra-ui/system@2.6.2)(@emotion/react@11.11.3)(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0):
+  /chakra-react-select@4.7.6(@chakra-ui/form-control@2.2.0)(@chakra-ui/icon@3.2.0)(@chakra-ui/layout@2.3.1)(@chakra-ui/media-query@3.3.0)(@chakra-ui/menu@2.2.1)(@chakra-ui/spinner@2.1.0)(@chakra-ui/system@2.6.2)(@emotion/react@11.11.3)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-ZL43hyXPnWf1g/HjsZDecbeJ4F2Q6tTPYJozlKWkrQ7lIX7ORP0aZYwmc5/Wly4UNzMimj2Vuosl6MmIXH+G2g==}
     peerDependencies:
       '@chakra-ui/form-control': ^2.0.0
@@ -7776,13 +7950,13 @@ packages:
       '@chakra-ui/icon': 3.2.0(@chakra-ui/system@2.6.2)(react@18.2.0)
       '@chakra-ui/layout': 2.3.1(@chakra-ui/system@2.6.2)(react@18.2.0)
       '@chakra-ui/media-query': 3.3.0(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/menu': 2.2.1(@chakra-ui/system@2.6.2)(framer-motion@10.18.0)(react@18.2.0)
+      '@chakra-ui/menu': 2.2.1(@chakra-ui/system@2.6.2)(framer-motion@11.0.5)(react@18.2.0)
       '@chakra-ui/spinner': 2.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
       '@chakra-ui/system': 2.6.2(@emotion/react@11.11.3)(@emotion/styled@11.11.0)(react@18.2.0)
-      '@emotion/react': 11.11.3(@types/react@18.2.48)(react@18.2.0)
+      '@emotion/react': 11.11.3(@types/react@18.2.57)(react@18.2.0)
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
-      react-select: 5.7.7(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
+      react-select: 5.7.7(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
     transitivePeerDependencies:
       - '@types/react'
     dev: false
@@ -7822,8 +7996,8 @@ packages:
       get-func-name: 2.0.2
     dev: true
 
-  /chokidar@3.5.3:
-    resolution: {integrity: sha512-Dr3sfKRP6oTcjf2JmUmFJfeVMvXBdegxB0iVQ5eb2V10uFJUCAS8OByZdVAyVb8xXNz3GjjTgj9kLWsZTqE6kw==}
+  /chokidar@3.6.0:
+    resolution: {integrity: sha512-7VT13fmjotKpGipCW9JEQAusEPE+Ei8nl6/g4FBAmIm0GOOLMua9NDDo/DWp0ZAxCr3cPq5ZpBqmPAQgDda2Pw==}
     engines: {node: '>= 8.10.0'}
     dependencies:
       anymatch: 3.1.3
@@ -7851,8 +8025,8 @@ packages:
     engines: {node: '>=8'}
     dev: true
 
-  /citty@0.1.5:
-    resolution: {integrity: sha512-AS7n5NSc0OQVMV9v6wt3ByujNIrne0/cTjiC2MYqhvao57VNfiuVksTSr2p17nVOhEr2KtqiAkGwHcgMC/qUuQ==}
+  /citty@0.1.6:
+    resolution: {integrity: sha512-tskPPKEs8D2KPafUypv2gxwJP8h/OaJmC82QQGGDQcHvXX43xF2VDACcJVmZ0EuSxkpO9Kc4MlrA3q0+FG58AQ==}
     dependencies:
       consola: 3.2.3
     dev: true
@@ -8071,10 +8245,10 @@ packages:
       toggle-selection: 1.0.6
     dev: false
 
-  /core-js-compat@3.35.0:
-    resolution: {integrity: sha512-5blwFAddknKeNgsjBzilkdQ0+YK8L1PfqPYq40NOYMYFSS38qj+hpTcLLWwpIwA2A5bje/x5jmVn2tzUMg9IVw==}
+  /core-js-compat@3.36.0:
+    resolution: {integrity: sha512-iV9Pd/PsgjNWBXeq8XRtWVSgz2tKAfhfvBs7qxYty+RlRd+OCksaWmOnc4JKrTc1cToXL1N0s3l/vwlxPtdElw==}
     dependencies:
-      browserslist: 4.22.2
+      browserslist: 4.23.0
     dev: true
 
   /core-util-is@1.0.3:
@@ -8210,7 +8384,7 @@ packages:
     resolution: {integrity: sha512-fnULvOpxnC5/Vg3NCiWelDsLiUc9bRwAPs/+LfTLNvetFCtCTN+yQz15C/fs4AwX1R9K5GLtLfn8QW+dWisaAw==}
     engines: {node: '>=0.11'}
     dependencies:
-      '@babel/runtime': 7.23.6
+      '@babel/runtime': 7.23.9
     dev: true
 
   /dateformat@5.0.3:
@@ -8271,12 +8445,12 @@ packages:
     resolution: {integrity: sha512-ZIwpnevOurS8bpT4192sqAowWM76JDKSHYzMLty3BZGSswgq6pBaH3DhCSW5xVAZICZyKdOBPjwww5wfgT/6PA==}
     engines: {node: '>= 0.4'}
     dependencies:
-      array-buffer-byte-length: 1.0.0
-      call-bind: 1.0.5
+      array-buffer-byte-length: 1.0.1
+      call-bind: 1.0.7
       es-get-iterator: 1.1.3
-      get-intrinsic: 1.2.2
+      get-intrinsic: 1.2.4
       is-arguments: 1.1.1
-      is-array-buffer: 3.0.2
+      is-array-buffer: 3.0.4
       is-date-object: 1.0.5
       is-regex: 1.1.4
       is-shared-array-buffer: 1.0.2
@@ -8284,11 +8458,11 @@ packages:
       object-is: 1.1.5
       object-keys: 1.1.1
       object.assign: 4.1.5
-      regexp.prototype.flags: 1.5.1
-      side-channel: 1.0.4
+      regexp.prototype.flags: 1.5.2
+      side-channel: 1.0.5
       which-boxed-primitive: 1.0.2
       which-collection: 1.0.1
-      which-typed-array: 1.1.13
+      which-typed-array: 1.1.14
     dev: true
 
   /deep-extend@0.6.0:
@@ -8314,13 +8488,13 @@ packages:
       clone: 1.0.4
     dev: true
 
-  /define-data-property@1.1.1:
-    resolution: {integrity: sha512-E7uGkTzkk1d0ByLeSc6ZsFS79Axg+m1P/VsgYsxHgiuc3tFSj+MjMIwe90FC4lOAZzNBdY7kkO2P2wKdsQ1vgQ==}
+  /define-data-property@1.1.4:
+    resolution: {integrity: sha512-rBMvIzlpA8v6E+SJZoo++HAYqsLrkg7MSfIinMPFhmkorw7X+dOXVJQs+QT69zGkzMyfDnIMN2Wid1+NbL3T+A==}
     engines: {node: '>= 0.4'}
     dependencies:
-      get-intrinsic: 1.2.2
+      es-define-property: 1.0.0
+      es-errors: 1.3.0
       gopd: 1.0.1
-      has-property-descriptors: 1.0.1
 
   /define-lazy-prop@2.0.0:
     resolution: {integrity: sha512-Ds09qNh8yw3khSjiJjiUInaGX9xlqZDY7JVryGxdxV7NPeuqQfplOpQ66yJFZut3jLa5zOwkXw1g9EI2uKh4Og==}
@@ -8331,8 +8505,8 @@ packages:
     resolution: {integrity: sha512-8QmQKqEASLd5nx0U1B1okLElbUuuttJ/AnYmRXbbbGDWh6uS208EjD4Xqq/I9wK7u0v6O08XhTWnt5XtEbR6Dg==}
     engines: {node: '>= 0.4'}
     dependencies:
-      define-data-property: 1.1.1
-      has-property-descriptors: 1.0.1
+      define-data-property: 1.1.4
+      has-property-descriptors: 1.0.2
       object-keys: 1.1.1
 
   /defu@6.1.4:
@@ -8481,7 +8655,7 @@ packages:
     dependencies:
       debug: 4.3.4
       is-url: 1.2.4
-      postcss: 8.4.33
+      postcss: 8.4.35
       postcss-values-parser: 2.0.1
     transitivePeerDependencies:
       - supports-color
@@ -8492,8 +8666,8 @@ packages:
     engines: {node: ^12.0.0 || ^14.0.0 || >=16.0.0}
     dependencies:
       is-url: 1.2.4
-      postcss: 8.4.33
-      postcss-values-parser: 6.0.2(postcss@8.4.33)
+      postcss: 8.4.35
+      postcss-values-parser: 6.0.2(postcss@8.4.35)
     dev: true
 
   /detective-sass@3.0.2:
@@ -8611,7 +8785,7 @@ packages:
   /dom-helpers@5.2.1:
     resolution: {integrity: sha512-nRCa7CK3VTrM2NmGkIy4cbK7IZlgBE/PYMn55rrXefr5xXDP0LdtfPnblFDoVdcAfslJ7or6iqAUnx0CCGIWQA==}
     dependencies:
-      '@babel/runtime': 7.23.7
+      '@babel/runtime': 7.23.9
       csstype: 3.1.3
     dev: false
 
@@ -8620,8 +8794,8 @@ packages:
     engines: {node: '>=12'}
     dev: true
 
-  /dotenv@16.3.1:
-    resolution: {integrity: sha512-IPzF4w4/Rd94bA9imS68tZBaYyBWSCE47V1RGuMrB94iyTOIEwRmVL2x/4An+6mETpLrKJ5hQkB8W4kFAadeIQ==}
+  /dotenv@16.4.5:
+    resolution: {integrity: sha512-ZmdL2rui+eB2YwhsWzjInR8LldtZHGDoQ1ugH85ppHKwpUHL7j7rN0Ti9NCnGiQbhaZ11FpR+7ao1dNsmduNUg==}
     engines: {node: '>=12'}
     dev: true
 
@@ -8650,8 +8824,8 @@ packages:
       jake: 10.8.7
     dev: true
 
-  /electron-to-chromium@1.4.639:
-    resolution: {integrity: sha512-CkKf3ZUVZchr+zDpAlNLEEy2NJJ9T64ULWaDgy3THXXlPVPkLu3VOs9Bac44nebVtdwl2geSj6AxTtGDOxoXhg==}
+  /electron-to-chromium@1.4.677:
+    resolution: {integrity: sha512-erDa3CaDzwJOpyvfKhOiJjBVNnMM0qxHq47RheVVwsSQrgBA9ZSGV9kdaOfZDPXcHzhG7lBxhj6A7KvfLJBd6Q==}
     dev: true
 
   /emoji-regex@8.0.0:
@@ -8678,7 +8852,7 @@ packages:
     dependencies:
       '@socket.io/component-emitter': 3.1.0
       debug: 4.3.4
-      engine.io-parser: 5.2.1
+      engine.io-parser: 5.2.2
       ws: 8.11.0
       xmlhttprequest-ssl: 2.0.0
     transitivePeerDependencies:
@@ -8687,8 +8861,8 @@ packages:
       - utf-8-validate
     dev: false
 
-  /engine.io-parser@5.2.1:
-    resolution: {integrity: sha512-9JktcM3u18nU9N2Lz3bWeBgxVgOKpw7yhRaoxQA3FUDZzzw+9WlA6p4G4u0RixNkg14fH7EfEc/RhpurtiROTQ==}
+  /engine.io-parser@5.2.2:
+    resolution: {integrity: sha512-RcyUFKA93/CXH20l4SoVvzZfrSDMOTUS3bWVpTt2FuFP+XYrL8i8oonHP7WInRyVHXh0n/ORtoeiE1os+8qkSw==}
     engines: {node: '>=10.0.0'}
     dev: false
 
@@ -8705,8 +8879,8 @@ packages:
     engines: {node: '>=0.12'}
     dev: true
 
-  /envinfo@7.11.0:
-    resolution: {integrity: sha512-G9/6xF1FPbIw0TtalAMaVPpiq2aDEuKLXM314jPVAO9r2fo2a4BLqMNkmRS7O/xPPZ+COAhGIz3ETvHEV3eUcg==}
+  /envinfo@7.11.1:
+    resolution: {integrity: sha512-8PiZgZNIB4q/Lw4AhOvAfB/ityHAd2bli3lESSWmWSzSsl5dKpy5N1d1Rfkd2teq/g9xN90lc6o98DOjMeYHpg==}
     engines: {node: '>=4'}
     hasBin: true
     dev: true
@@ -8722,56 +8896,72 @@ packages:
       stackframe: 1.3.4
     dev: false
 
-  /es-abstract@1.22.3:
-    resolution: {integrity: sha512-eiiY8HQeYfYH2Con2berK+To6GrK2RxbPawDkGq4UiCQQfZHb6wX9qQqkbpPqaxQFcl8d9QzZqo0tGE0VcrdwA==}
+  /es-abstract@1.22.4:
+    resolution: {integrity: sha512-vZYJlk2u6qHYxBOTjAeg7qUxHdNfih64Uu2J8QqWgXZ2cri0ZpJAkzDUK/q593+mvKwlxyaxr6F1Q+3LKoQRgg==}
     engines: {node: '>= 0.4'}
     dependencies:
-      array-buffer-byte-length: 1.0.0
-      arraybuffer.prototype.slice: 1.0.2
-      available-typed-arrays: 1.0.5
-      call-bind: 1.0.5
-      es-set-tostringtag: 2.0.2
+      array-buffer-byte-length: 1.0.1
+      arraybuffer.prototype.slice: 1.0.3
+      available-typed-arrays: 1.0.7
+      call-bind: 1.0.7
+      es-define-property: 1.0.0
+      es-errors: 1.3.0
+      es-set-tostringtag: 2.0.3
       es-to-primitive: 1.2.1
       function.prototype.name: 1.1.6
-      get-intrinsic: 1.2.2
-      get-symbol-description: 1.0.0
+      get-intrinsic: 1.2.4
+      get-symbol-description: 1.0.2
       globalthis: 1.0.3
       gopd: 1.0.1
-      has-property-descriptors: 1.0.1
-      has-proto: 1.0.1
+      has-property-descriptors: 1.0.2
+      has-proto: 1.0.3
       has-symbols: 1.0.3
-      hasown: 2.0.0
-      internal-slot: 1.0.6
-      is-array-buffer: 3.0.2
+      hasown: 2.0.1
+      internal-slot: 1.0.7
+      is-array-buffer: 3.0.4
       is-callable: 1.2.7
-      is-negative-zero: 2.0.2
+      is-negative-zero: 2.0.3
       is-regex: 1.1.4
       is-shared-array-buffer: 1.0.2
       is-string: 1.0.7
-      is-typed-array: 1.1.12
+      is-typed-array: 1.1.13
       is-weakref: 1.0.2
       object-inspect: 1.13.1
       object-keys: 1.1.1
       object.assign: 4.1.5
-      regexp.prototype.flags: 1.5.1
-      safe-array-concat: 1.0.1
-      safe-regex-test: 1.0.0
+      regexp.prototype.flags: 1.5.2
+      safe-array-concat: 1.1.0
+      safe-regex-test: 1.0.3
       string.prototype.trim: 1.2.8
       string.prototype.trimend: 1.0.7
       string.prototype.trimstart: 1.0.7
-      typed-array-buffer: 1.0.0
+      typed-array-buffer: 1.0.2
       typed-array-byte-length: 1.0.0
-      typed-array-byte-offset: 1.0.0
-      typed-array-length: 1.0.4
+      typed-array-byte-offset: 1.0.2
+      typed-array-length: 1.0.5
       unbox-primitive: 1.0.2
-      which-typed-array: 1.1.13
+      which-typed-array: 1.1.14
     dev: true
 
+  /es-array-method-boxes-properly@1.0.0:
+    resolution: {integrity: sha512-wd6JXUmyHmt8T5a2xreUwKcGPq6f1f+WwIJkijUqiGcJz1qqnZgP6XIK+QyIWU5lT7imeNxUll48bziG+TSYcA==}
+    dev: true
+
+  /es-define-property@1.0.0:
+    resolution: {integrity: sha512-jxayLKShrEqqzJ0eumQbVhTYQM27CfT1T35+gCgDFoL82JLsXqTJ76zv6A0YLOgEnLUMvLzsDsGIrl8NFpT2gQ==}
+    engines: {node: '>= 0.4'}
+    dependencies:
+      get-intrinsic: 1.2.4
+
+  /es-errors@1.3.0:
+    resolution: {integrity: sha512-Zf5H2Kxt2xjTvbJvP2ZWLEICxA6j+hAmMzIlypy4xcBg1vKVnx89Wy0GbS+kf5cwCVFFzdCFh2XSCFNULS6csw==}
+    engines: {node: '>= 0.4'}
+
   /es-get-iterator@1.1.3:
     resolution: {integrity: sha512-sPZmqHBe6JIiTfN5q2pEi//TwxmAFHwj/XEuYjTuse78i8KxaqMTTzxPoFKuzRpDpTJ+0NAbpfenkmH2rePtuw==}
     dependencies:
-      call-bind: 1.0.5
-      get-intrinsic: 1.2.2
+      call-bind: 1.0.7
+      get-intrinsic: 1.2.4
       has-symbols: 1.0.3
       is-arguments: 1.1.1
       is-map: 2.0.2
@@ -8781,42 +8971,44 @@ packages:
       stop-iteration-iterator: 1.0.0
     dev: true
 
-  /es-iterator-helpers@1.0.15:
-    resolution: {integrity: sha512-GhoY8uYqd6iwUl2kgjTm4CZAf6oo5mHK7BPqx3rKgx893YSsy0LGHV6gfqqQvZt/8xM8xeOnfXBCfqclMKkJ5g==}
+  /es-iterator-helpers@1.0.17:
+    resolution: {integrity: sha512-lh7BsUqelv4KUbR5a/ZTaGGIMLCjPGPqJ6q+Oq24YP0RdyptX1uzm4vvaqzk7Zx3bpl/76YLTTDj9L7uYQ92oQ==}
+    engines: {node: '>= 0.4'}
     dependencies:
       asynciterator.prototype: 1.0.0
-      call-bind: 1.0.5
+      call-bind: 1.0.7
       define-properties: 1.2.1
-      es-abstract: 1.22.3
-      es-set-tostringtag: 2.0.2
+      es-abstract: 1.22.4
+      es-errors: 1.3.0
+      es-set-tostringtag: 2.0.3
       function-bind: 1.1.2
-      get-intrinsic: 1.2.2
+      get-intrinsic: 1.2.4
       globalthis: 1.0.3
-      has-property-descriptors: 1.0.1
-      has-proto: 1.0.1
+      has-property-descriptors: 1.0.2
+      has-proto: 1.0.3
       has-symbols: 1.0.3
-      internal-slot: 1.0.6
+      internal-slot: 1.0.7
       iterator.prototype: 1.1.2
-      safe-array-concat: 1.0.1
+      safe-array-concat: 1.1.0
     dev: true
 
   /es-module-lexer@0.9.3:
     resolution: {integrity: sha512-1HQ2M2sPtxwnvOvT1ZClHyQDiggdNjURWpY2we6aMKCQiUVxTmVs2UYPLIrD84sS+kMdUwfBSylbJPwNnBrnHQ==}
     dev: true
 
-  /es-set-tostringtag@2.0.2:
-    resolution: {integrity: sha512-BuDyupZt65P9D2D2vA/zqcI3G5xRsklm5N3xCwuiy+/vKy8i0ifdsQP1sLgO4tZDSCaQUSnmC48khknGMV3D2Q==}
+  /es-set-tostringtag@2.0.3:
+    resolution: {integrity: sha512-3T8uNMC3OQTHkFUsFq8r/BwAXLHvU/9O9mE0fBc/MY5iq/8H7ncvO947LmYA6ldWw9Uh8Yhf25zu6n7nML5QWQ==}
     engines: {node: '>= 0.4'}
     dependencies:
-      get-intrinsic: 1.2.2
-      has-tostringtag: 1.0.0
-      hasown: 2.0.0
+      get-intrinsic: 1.2.4
+      has-tostringtag: 1.0.2
+      hasown: 2.0.1
     dev: true
 
   /es-shim-unscopables@1.0.2:
     resolution: {integrity: sha512-J3yBRXCzDu4ULnQwxyToo/OjdMx6akgVC7K6few0a7F/0wLtmKKN7I73AH5T2836UuXRqN7Qg+IIUw/+YJksRw==}
     dependencies:
-      hasown: 2.0.0
+      hasown: 2.0.1
     dev: true
 
   /es-to-primitive@1.2.1:
@@ -8873,39 +9065,39 @@ packages:
       '@esbuild/win32-x64': 0.18.20
     dev: true
 
-  /esbuild@0.19.11:
-    resolution: {integrity: sha512-HJ96Hev2hX/6i5cDVwcqiJBBtuo9+FeIJOtZ9W1kA5M6AMJRHUZlpYZ1/SbEwtO0ioNAW8rUooVpC/WehY2SfA==}
+  /esbuild@0.19.12:
+    resolution: {integrity: sha512-aARqgq8roFBj054KvQr5f1sFu0D65G+miZRCuJyJ0G13Zwx7vRar5Zhn2tkQNzIXcBrNVsv/8stehpj+GAjgbg==}
     engines: {node: '>=12'}
     hasBin: true
     requiresBuild: true
     optionalDependencies:
-      '@esbuild/aix-ppc64': 0.19.11
-      '@esbuild/android-arm': 0.19.11
-      '@esbuild/android-arm64': 0.19.11
-      '@esbuild/android-x64': 0.19.11
-      '@esbuild/darwin-arm64': 0.19.11
-      '@esbuild/darwin-x64': 0.19.11
-      '@esbuild/freebsd-arm64': 0.19.11
-      '@esbuild/freebsd-x64': 0.19.11
-      '@esbuild/linux-arm': 0.19.11
-      '@esbuild/linux-arm64': 0.19.11
-      '@esbuild/linux-ia32': 0.19.11
-      '@esbuild/linux-loong64': 0.19.11
-      '@esbuild/linux-mips64el': 0.19.11
-      '@esbuild/linux-ppc64': 0.19.11
-      '@esbuild/linux-riscv64': 0.19.11
-      '@esbuild/linux-s390x': 0.19.11
-      '@esbuild/linux-x64': 0.19.11
-      '@esbuild/netbsd-x64': 0.19.11
-      '@esbuild/openbsd-x64': 0.19.11
-      '@esbuild/sunos-x64': 0.19.11
-      '@esbuild/win32-arm64': 0.19.11
-      '@esbuild/win32-ia32': 0.19.11
-      '@esbuild/win32-x64': 0.19.11
+      '@esbuild/aix-ppc64': 0.19.12
+      '@esbuild/android-arm': 0.19.12
+      '@esbuild/android-arm64': 0.19.12
+      '@esbuild/android-x64': 0.19.12
+      '@esbuild/darwin-arm64': 0.19.12
+      '@esbuild/darwin-x64': 0.19.12
+      '@esbuild/freebsd-arm64': 0.19.12
+      '@esbuild/freebsd-x64': 0.19.12
+      '@esbuild/linux-arm': 0.19.12
+      '@esbuild/linux-arm64': 0.19.12
+      '@esbuild/linux-ia32': 0.19.12
+      '@esbuild/linux-loong64': 0.19.12
+      '@esbuild/linux-mips64el': 0.19.12
+      '@esbuild/linux-ppc64': 0.19.12
+      '@esbuild/linux-riscv64': 0.19.12
+      '@esbuild/linux-s390x': 0.19.12
+      '@esbuild/linux-x64': 0.19.12
+      '@esbuild/netbsd-x64': 0.19.12
+      '@esbuild/openbsd-x64': 0.19.12
+      '@esbuild/sunos-x64': 0.19.12
+      '@esbuild/win32-arm64': 0.19.12
+      '@esbuild/win32-ia32': 0.19.12
+      '@esbuild/win32-x64': 0.19.12
     dev: true
 
-  /escalade@3.1.1:
-    resolution: {integrity: sha512-k0er2gUkLf8O0zKJiAhmkTnJlTvINGv7ygDNPbeIsX/TJjGJZHuh9B2UxbsaEkmlEo9MfhrSzmhIlhRlI2GXnw==}
+  /escalade@3.1.2:
+    resolution: {integrity: sha512-ErCHMCae19vR8vQGe50xIsVomy19rg6gFu3+r3jkEO46suLMWBksvVyoGgQV+jOfl84ZSOSlmv6Gxa89PmTGmA==}
     engines: {node: '>=6'}
     dev: true
 
@@ -8952,7 +9144,7 @@ packages:
       - supports-color
     dev: true
 
-  /eslint-module-utils@2.8.0(@typescript-eslint/parser@6.19.0)(eslint-import-resolver-node@0.3.9)(eslint@8.56.0):
+  /eslint-module-utils@2.8.0(@typescript-eslint/parser@7.0.2)(eslint-import-resolver-node@0.3.9)(eslint@8.56.0):
     resolution: {integrity: sha512-aWajIYfsqCKRDgUfjEXNN/JlrzauMuSEy5sbd7WXbtW3EH6A6MpwEh42c7qD+MqQo9QMJ6fWLAeIJynx0g6OAw==}
     engines: {node: '>=4'}
     peerDependencies:
@@ -8973,7 +9165,7 @@ packages:
       eslint-import-resolver-webpack:
         optional: true
     dependencies:
-      '@typescript-eslint/parser': 6.19.0(eslint@8.56.0)(typescript@5.3.3)
+      '@typescript-eslint/parser': 7.0.2(eslint@8.56.0)(typescript@5.3.3)
       debug: 3.2.7
       eslint: 8.56.0
       eslint-import-resolver-node: 0.3.9
@@ -8989,7 +9181,7 @@ packages:
       requireindex: 1.1.0
     dev: true
 
-  /eslint-plugin-import@2.29.1(@typescript-eslint/parser@6.19.0)(eslint@8.56.0):
+  /eslint-plugin-import@2.29.1(@typescript-eslint/parser@7.0.2)(eslint@8.56.0):
     resolution: {integrity: sha512-BbPC0cuExzhiMo4Ff1BTVwHpjjv28C5R+btTOGaCRC7UEz801up0JadwkeSk5Ued6TG34uaczuVuH6qyy5YUxw==}
     engines: {node: '>=4'}
     peerDependencies:
@@ -8999,22 +9191,22 @@ packages:
       '@typescript-eslint/parser':
         optional: true
     dependencies:
-      '@typescript-eslint/parser': 6.19.0(eslint@8.56.0)(typescript@5.3.3)
+      '@typescript-eslint/parser': 7.0.2(eslint@8.56.0)(typescript@5.3.3)
       array-includes: 3.1.7
-      array.prototype.findlastindex: 1.2.3
+      array.prototype.findlastindex: 1.2.4
       array.prototype.flat: 1.3.2
       array.prototype.flatmap: 1.3.2
       debug: 3.2.7
       doctrine: 2.1.0
       eslint: 8.56.0
       eslint-import-resolver-node: 0.3.9
-      eslint-module-utils: 2.8.0(@typescript-eslint/parser@6.19.0)(eslint-import-resolver-node@0.3.9)(eslint@8.56.0)
-      hasown: 2.0.0
+      eslint-module-utils: 2.8.0(@typescript-eslint/parser@7.0.2)(eslint-import-resolver-node@0.3.9)(eslint@8.56.0)
+      hasown: 2.0.1
       is-core-module: 2.13.1
       is-glob: 4.0.3
       minimatch: 3.1.2
       object.fromentries: 2.0.7
-      object.groupby: 1.0.1
+      object.groupby: 1.0.2
       object.values: 1.1.7
       semver: 6.3.1
       tsconfig-paths: 3.15.0
@@ -9059,9 +9251,9 @@ packages:
     dependencies:
       array-includes: 3.1.7
       array.prototype.flatmap: 1.3.2
-      array.prototype.tosorted: 1.1.2
+      array.prototype.tosorted: 1.1.3
       doctrine: 2.1.0
-      es-iterator-helpers: 1.0.15
+      es-iterator-helpers: 1.0.17
       eslint: 8.56.0
       estraverse: 5.3.0
       jsx-ast-utils: 3.3.5
@@ -9076,17 +9268,17 @@ packages:
       string.prototype.matchall: 4.0.10
     dev: true
 
-  /eslint-plugin-simple-import-sort@10.0.0(eslint@8.56.0):
-    resolution: {integrity: sha512-AeTvO9UCMSNzIHRkg8S6c3RPy5YEwKWSQPx3DYghLedo2ZQxowPFLGDN1AZ2evfg6r6mjBSZSLxLFsWSu3acsw==}
+  /eslint-plugin-simple-import-sort@12.0.0(eslint@8.56.0):
+    resolution: {integrity: sha512-8o0dVEdAkYap0Cn5kNeklaKcT1nUsa3LITWEuFk3nJifOoD+5JQGoyDUW2W/iPWwBsNBJpyJS9y4je/BgxLcyQ==}
     peerDependencies:
       eslint: '>=5.0.0'
     dependencies:
       eslint: 8.56.0
     dev: true
 
-  /eslint-plugin-storybook@0.6.15(eslint@8.56.0)(typescript@5.3.3):
-    resolution: {integrity: sha512-lAGqVAJGob47Griu29KXYowI4G7KwMoJDOkEip8ujikuDLxU+oWJ1l0WL6F2oDO4QiyUFXvtDkEkISMOPzo+7w==}
-    engines: {node: 12.x || 14.x || >= 16}
+  /eslint-plugin-storybook@0.8.0(eslint@8.56.0)(typescript@5.3.3):
+    resolution: {integrity: sha512-CZeVO5EzmPY7qghO2t64oaFM+8FTaD4uzOEjHKp516exyTKo+skKAL9GI3QALS2BXhyALJjNtwbmr1XinGE8bA==}
+    engines: {node: '>= 18'}
     peerDependencies:
       eslint: '>=6'
     dependencies:
@@ -9100,17 +9292,17 @@ packages:
       - typescript
     dev: true
 
-  /eslint-plugin-unused-imports@3.0.0(@typescript-eslint/eslint-plugin@6.19.0)(eslint@8.56.0):
-    resolution: {integrity: sha512-sduiswLJfZHeeBJ+MQaG+xYzSWdRXoSw61DpU13mzWumCkR0ufD0HmO4kdNokjrkluMHpj/7PJeN35pgbhW3kw==}
+  /eslint-plugin-unused-imports@3.1.0(@typescript-eslint/eslint-plugin@7.0.2)(eslint@8.56.0):
+    resolution: {integrity: sha512-9l1YFCzXKkw1qtAru1RWUtG2EVDZY0a0eChKXcL+EZ5jitG7qxdctu4RnvhOJHv4xfmUf7h+JJPINlVpGhZMrw==}
     engines: {node: ^12.22.0 || ^14.17.0 || >=16.0.0}
     peerDependencies:
-      '@typescript-eslint/eslint-plugin': ^6.0.0
-      eslint: ^8.0.0
+      '@typescript-eslint/eslint-plugin': 6 - 7
+      eslint: '8'
     peerDependenciesMeta:
       '@typescript-eslint/eslint-plugin':
         optional: true
     dependencies:
-      '@typescript-eslint/eslint-plugin': 6.19.0(@typescript-eslint/parser@6.19.0)(eslint@8.56.0)(typescript@5.3.3)
+      '@typescript-eslint/eslint-plugin': 7.0.2(@typescript-eslint/parser@7.0.2)(eslint@8.56.0)(typescript@5.3.3)
       eslint: 8.56.0
       eslint-rule-composer: 0.3.0
     dev: true
@@ -9155,7 +9347,7 @@ packages:
       '@eslint-community/regexpp': 4.10.0
       '@eslint/eslintrc': 2.1.4
       '@eslint/js': 8.56.0
-      '@humanwhocodes/config-array': 0.11.13
+      '@humanwhocodes/config-array': 0.11.14
       '@humanwhocodes/module-importer': 1.0.1
       '@nodelib/fs.walk': 1.2.8
       '@ungap/structured-clone': 1.2.0
@@ -9176,7 +9368,7 @@ packages:
       glob-parent: 6.0.2
       globals: 13.24.0
       graphemer: 1.4.0
-      ignore: 5.3.0
+      ignore: 5.3.1
       imurmurhash: 0.1.4
       is-glob: 4.0.3
       is-path-inside: 3.0.3
@@ -9197,8 +9389,8 @@ packages:
     resolution: {integrity: sha512-oruZaFkjorTpF32kDSI5/75ViwGeZginGGy2NoOSg3Q9bnwlnmDm4HLnkl0RE3n+njDXR037aY1+x58Z/zFdwQ==}
     engines: {node: ^12.22.0 || ^14.17.0 || >=16.0.0}
     dependencies:
-      acorn: 8.11.2
-      acorn-jsx: 5.3.2(acorn@8.11.2)
+      acorn: 8.11.3
+      acorn-jsx: 5.3.2(acorn@8.11.3)
       eslint-visitor-keys: 3.4.3
     dev: true
 
@@ -9378,8 +9570,8 @@ packages:
     resolution: {integrity: sha512-bijHueCGd0LqqNK9b5oCMHc0MluJAx0cwqASgbWMvkO01lCYgIhacVRLcaDz3QnyYIRNJRDwMb41VuT6pHJ91Q==}
     dev: false
 
-  /fastq@1.16.0:
-    resolution: {integrity: sha512-ifCoaXsDrsdkWTtiNJX5uzHDsrck5TzfKKDcuFFTIrrc/BS076qgEIfoIy1VeZqViznfKiysPYTh/QeHtnIsYA==}
+  /fastq@1.17.1:
+    resolution: {integrity: sha512-sRVD3lWVIXWg6By68ZN7vho9a1pQcN/WBFaAAsDDFzlJjvoGx0P8z7V1t72grFJfJhu3YPZBuu25f7Kaw2jN1w==}
     dependencies:
       reusify: 1.0.4
     dev: true
@@ -9525,13 +9717,13 @@ packages:
     resolution: {integrity: sha512-CYcENa+FtcUKLmhhqyctpclsq7QF38pKjZHsGNiSQF5r4FtoKDWabFDl3hzaEQMvT1LHEysw5twgLvpYYb4vbw==}
     engines: {node: ^10.12.0 || >=12.0.0}
     dependencies:
-      flatted: 3.2.9
+      flatted: 3.3.0
       keyv: 4.5.4
       rimraf: 3.0.2
     dev: true
 
-  /flatted@3.2.9:
-    resolution: {integrity: sha512-36yxDn5H7OFZQla0/jFJmbIKTdZAQHngCedGxiMmpNfEZM0sdEeT+WczLQrjK6D7o2aiyLYDnkw0R3JK0Qv1RQ==}
+  /flatted@3.3.0:
+    resolution: {integrity: sha512-noqGuLw158+DuD9UPRKHpJ2hGxpFyDlYYrfM0mWt4XhT4n0lwzTLh70Tkdyy4kyTmyTT9Bv7bWAJqw7cgkEXDg==}
     dev: true
 
   /flatten@1.0.3:
@@ -9539,13 +9731,13 @@ packages:
     deprecated: flatten is deprecated in favor of utility frameworks such as lodash.
     dev: true
 
-  /flow-parser@0.227.0:
-    resolution: {integrity: sha512-nOygtGKcX/siZK/lFzpfdHEfOkfGcTW7rNroR1Zsz6T/JxSahPALXVt5qVHq/fgvMJuv096BTKbgxN3PzVBaDA==}
+  /flow-parser@0.229.0:
+    resolution: {integrity: sha512-mOYmMuvJwAo/CvnMFEq4SHftq7E5188hYMTTxJyQOXk2nh+sgslRdYMw3wTthH+FMcFaZLtmBPuMu6IwztdoUQ==}
     engines: {node: '>=0.4.0'}
     dev: true
 
-  /focus-lock@1.3.2:
-    resolution: {integrity: sha512-kFI92jZVqa8rP4Yer2sLNlUDcOdEFxYum2tIIr4eCH0XF+pOmlg0xiY4tkbDmHJXt3phtbJoWs1L6PgUVk97rA==}
+  /focus-lock@1.3.3:
+    resolution: {integrity: sha512-hfXkZha7Xt4RQtrL1HBfspAuIj89Y0fb6GX0dfJilb8S2G/lvL4akPAcHq6xoD2NuZnDMCnZL/zQesMyeu6Psg==}
     engines: {node: '>=10'}
     dependencies:
       tslib: 2.6.2
@@ -9603,6 +9795,24 @@ packages:
       '@emotion/is-prop-valid': 0.8.8
     dev: false
 
+  /framer-motion@11.0.5(react-dom@18.2.0)(react@18.2.0):
+    resolution: {integrity: sha512-Lb0EYbQcSK/pgyQUJm+KzsQrKrJRX9sFRyzl9hSr9gFG4Mk8yP7BjhuxvRXzblOM/+JxycrJdCDVmOQBsjpYlw==}
+    peerDependencies:
+      react: ^18.0.0
+      react-dom: ^18.0.0
+    peerDependenciesMeta:
+      react:
+        optional: true
+      react-dom:
+        optional: true
+    dependencies:
+      react: 18.2.0
+      react-dom: 18.2.0(react@18.2.0)
+      tslib: 2.6.2
+    optionalDependencies:
+      '@emotion/is-prop-valid': 0.8.8
+    dev: false
+
   /framesync@6.1.2:
     resolution: {integrity: sha512-jBTqhX6KaQVDyus8muwZbBeGGP0XgujBRbQ7gM7BRdS3CadCZIHiawyzYLnafYcvZIh5j8WE7cxZKFn7dXhu9g==}
     dependencies:
@@ -9671,9 +9881,9 @@ packages:
     resolution: {integrity: sha512-Z5kx79swU5P27WEayXM1tBi5Ze/lbIyiNgU3qyXUOf9b2rgXYyF9Dy9Cx+IQv/Lc8WCG6L82zwUPpSS9hGehIg==}
     engines: {node: '>= 0.4'}
     dependencies:
-      call-bind: 1.0.5
+      call-bind: 1.0.7
       define-properties: 1.2.1
-      es-abstract: 1.22.3
+      es-abstract: 1.22.4
       functions-have-names: 1.2.3
     dev: true
 
@@ -9711,13 +9921,15 @@ packages:
     resolution: {integrity: sha512-8vXOvuE167CtIc3OyItco7N/dpRtBbYOsPsXCz7X/PMnlGjYjSGuZJgM1Y7mmew7BKf9BqvLX2tnOVy1BBUsxQ==}
     dev: true
 
-  /get-intrinsic@1.2.2:
-    resolution: {integrity: sha512-0gSo4ml/0j98Y3lngkFEot/zhiCeWsbYIlZ+uZOVgzLyLaUw7wxUL+nCTP0XJvJg1AXulJRI3UJi8GsbDuxdGA==}
+  /get-intrinsic@1.2.4:
+    resolution: {integrity: sha512-5uYhsJH8VJBTv7oslg4BznJYhDoRI6waYCxMmCdnTrcCrHA/fCFKoTFz2JKKE0HdDFUF7/oQuhzumXJK7paBRQ==}
+    engines: {node: '>= 0.4'}
     dependencies:
+      es-errors: 1.3.0
       function-bind: 1.1.2
-      has-proto: 1.0.1
+      has-proto: 1.0.3
       has-symbols: 1.0.3
-      hasown: 2.0.0
+      hasown: 2.0.1
 
   /get-nonce@1.0.1:
     resolution: {integrity: sha512-FJhYRoDaiatfEkUK8HKlicmu/3SGFD51q3itKDGoSTysQJBnfOcxU5GxnhE1E6soB76MbT0MBtnKJuXyAx+96Q==}
@@ -9752,23 +9964,24 @@ packages:
     engines: {node: '>=16'}
     dev: true
 
-  /get-symbol-description@1.0.0:
-    resolution: {integrity: sha512-2EmdH1YvIQiZpltCNgkuiUnyukzxM/R6NDJX31Ke3BG1Nq5b0S2PhX59UKi9vZpPDQVdqn+1IcaAwnzTT5vCjw==}
+  /get-symbol-description@1.0.2:
+    resolution: {integrity: sha512-g0QYk1dZBxGwk+Ngc+ltRH2IBp2f7zBkBMBJZCDerh6EhlhSR6+9irMCuT/09zD6qkarHUSn529sK/yL4S27mg==}
     engines: {node: '>= 0.4'}
     dependencies:
-      call-bind: 1.0.5
-      get-intrinsic: 1.2.2
+      call-bind: 1.0.7
+      es-errors: 1.3.0
+      get-intrinsic: 1.2.4
     dev: true
 
   /giget@1.2.1:
     resolution: {integrity: sha512-4VG22mopWtIeHwogGSy1FViXVo0YT+m6BrqZfz0JJFwbSsePsCdOzdLIIli5BtMp7Xe8f/o2OmBpQX2NBOC24g==}
     hasBin: true
     dependencies:
-      citty: 0.1.5
+      citty: 0.1.6
       consola: 3.2.3
       defu: 6.1.4
-      node-fetch-native: 1.6.1
-      nypm: 0.3.4
+      node-fetch-native: 1.6.2
+      nypm: 0.3.6
       ohash: 1.1.3
       pathe: 1.1.2
       tar: 6.2.0
@@ -9854,7 +10067,7 @@ packages:
       array-union: 2.1.0
       dir-glob: 3.0.1
       fast-glob: 3.3.2
-      ignore: 5.3.0
+      ignore: 5.3.1
       merge2: 1.4.1
       slash: 3.0.0
     dev: true
@@ -9874,7 +10087,7 @@ packages:
   /gopd@1.0.1:
     resolution: {integrity: sha512-d65bNlIadxvpb/A2abVdlqKqV563juRnZ1Wtk6s1sIR8uNsXR70xqIzVqxVf1eTqDunwT2MkczEeaezCKTZhwA==}
     dependencies:
-      get-intrinsic: 1.2.2
+      get-intrinsic: 1.2.4
 
   /graceful-fs@4.2.11:
     resolution: {integrity: sha512-RbJ5/jmFcNNCcDV5o9eTnBLJ/HszWV0P73bc+Ff4nS/rJj+YaS6IGyiOL0VoBYX+l1Wrl3k63h/KrH+nhJ0XvQ==}
@@ -9922,28 +10135,28 @@ packages:
     engines: {node: '>=8'}
     dev: true
 
-  /has-property-descriptors@1.0.1:
-    resolution: {integrity: sha512-VsX8eaIewvas0xnvinAe9bw4WfIeODpGYikiWYLH+dma0Jw6KHYqWiWfhQlgOVK8D6PvjubK5Uc4P0iIhIcNVg==}
+  /has-property-descriptors@1.0.2:
+    resolution: {integrity: sha512-55JNKuIW+vq4Ke1BjOTjM2YctQIvCT7GFzHwmfZPGo5wnrgkid0YQtnAleFSqumZm4az3n2BS+erby5ipJdgrg==}
     dependencies:
-      get-intrinsic: 1.2.2
+      es-define-property: 1.0.0
 
-  /has-proto@1.0.1:
-    resolution: {integrity: sha512-7qE+iP+O+bgF9clE5+UoBFzE65mlBiVj3tKCrlNQ0Ogwm0BjpT/gK4SlLYDMybDh5I3TCTKnPPa0oMG7JDYrhg==}
+  /has-proto@1.0.3:
+    resolution: {integrity: sha512-SJ1amZAJUiZS+PhsVLf5tGydlaVB8EdFpaSO4gmiUKUOxk8qzn5AIy4ZeJUmh22znIdk/uMAUT2pl3FxzVUH+Q==}
     engines: {node: '>= 0.4'}
 
   /has-symbols@1.0.3:
     resolution: {integrity: sha512-l3LCuF6MgDNwTDKkdYGEihYjt5pRPbEg46rtlmnSPlUbgmB8LOIrKJbYYFBSbnPaJexMKtiPO8hmeRjRz2Td+A==}
     engines: {node: '>= 0.4'}
 
-  /has-tostringtag@1.0.0:
-    resolution: {integrity: sha512-kFjcSNhnlGV1kyoGk7OXKSawH5JOb/LzUc5w9B02hOTO0dfFRjbHQKvg1d6cf3HbeUmtU9VbbV3qzZ2Teh97WQ==}
+  /has-tostringtag@1.0.2:
+    resolution: {integrity: sha512-NqADB8VjPFLM2V0VvHUewwwsw0ZWBaIdgo+ieHtK3hasLz4qeCRjYcqfB6AQrBggRKppKF8L52/VqdVsO47Dlw==}
     engines: {node: '>= 0.4'}
     dependencies:
       has-symbols: 1.0.3
     dev: true
 
-  /hasown@2.0.0:
-    resolution: {integrity: sha512-vUptKVTpIJhcczKBbgnS+RtcuYMB8+oNzPK2/Hp3hanz8JmpATdmmgLgSaadVREkDm+e2giHwY3ZRkyjSIDDFA==}
+  /hasown@2.0.1:
+    resolution: {integrity: sha512-1/th4MHjnwncwXsIW6QMzlvYL9kG5e/CpVvLRZe4XPa8TOUNbCELqmvhDmnkNsAjwaG4+I8gJJL0JBvTTLO9qA==}
     engines: {node: '>= 0.4'}
     dependencies:
       function-bind: 1.1.2
@@ -10009,18 +10222,18 @@ packages:
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     dev: false
 
-  /i18next-http-backend@2.4.2:
-    resolution: {integrity: sha512-wKrgGcaFQ4EPjfzBTjzMU0rbFTYpa0S5gv9N/d8WBmWS64+IgJb7cHddMvV+tUkse7vUfco3eVs2lB+nJhPo3w==}
+  /i18next-http-backend@2.4.3:
+    resolution: {integrity: sha512-jo2M03O6n1/DNb51WSQ8PsQ0xEELzLZRdYUTbf17mLw3rVwnJF9hwNgMXvEFSxxb+N8dT+o0vtigA6s5mGWyPA==}
     dependencies:
       cross-fetch: 4.0.0
     transitivePeerDependencies:
       - encoding
     dev: false
 
-  /i18next@23.7.16:
-    resolution: {integrity: sha512-SrqFkMn9W6Wb43ZJ9qrO6U2U4S80RsFMA7VYFSqp7oc7RllQOYDCdRfsse6A7Cq/V8MnpxKvJCYgM8++27n4Fw==}
+  /i18next@23.9.0:
+    resolution: {integrity: sha512-f3MUciKqwzNV//mHG6EtdSlC65+nqH/3zK8sOSWqNV6FVu2tmHhF/rFOp9UF8S4m1odojtuipKaKJrP0Loh60g==}
     dependencies:
-      '@babel/runtime': 7.23.7
+      '@babel/runtime': 7.23.9
     dev: false
 
   /iconv-lite@0.4.24:
@@ -10038,8 +10251,8 @@ packages:
     resolution: {integrity: sha512-dcyqhDvX1C46lXZcVqCpK+FtMRQVdIMN6/Df5js2zouUsqG7I6sFxitIC+7KYK29KdXOLHdu9zL4sFnoVQnqaA==}
     dev: true
 
-  /ignore@5.3.0:
-    resolution: {integrity: sha512-g7dmpshy+gD7mh88OC9NwSGTKoc3kyLAZQRU1mt53Aw/vnvfXnbC+F/7F7QoYVKbV+KNvJx8wArewKy1vXMtlg==}
+  /ignore@5.3.1:
+    resolution: {integrity: sha512-5Fytz/IraMjqpwfd34ke28PTVMjZjJG2MPn5t7OE4eUCUNf8BAa7b5WUS9/Qvr6mwOQS7Mk6vdsMno5he+T8Xw==}
     engines: {node: '>= 4'}
     dev: true
 
@@ -10095,13 +10308,13 @@ packages:
       fast-loops: 1.1.3
     dev: false
 
-  /internal-slot@1.0.6:
-    resolution: {integrity: sha512-Xj6dv+PsbtwyPpEflsejS+oIZxmMlV44zAhG479uYu89MsjcYOhCFnNyKrkJrihbsiasQyY0afoCl/9BLR65bg==}
+  /internal-slot@1.0.7:
+    resolution: {integrity: sha512-NGnrKwXzSms2qUUih/ILZ5JBqNTSa1+ZmP6flaIp6KmSElgE9qdndzS3cqjrDovwFdmwsGsLdeFgB6suw+1e9g==}
     engines: {node: '>= 0.4'}
     dependencies:
-      get-intrinsic: 1.2.2
-      hasown: 2.0.0
-      side-channel: 1.0.4
+      es-errors: 1.3.0
+      hasown: 2.0.1
+      side-channel: 1.0.5
     dev: true
 
   /invariant@2.2.4:
@@ -10109,8 +10322,8 @@ packages:
     dependencies:
       loose-envify: 1.4.0
 
-  /ip@2.0.0:
-    resolution: {integrity: sha512-WKa+XuLG1A1R0UWhl2+1XQSi+fZWMsYKffMZTTYsiZaUD8k2yDAj5atimTUD2TZkyCkNEeYE5NhFZmupOGtjYQ==}
+  /ip@2.0.1:
+    resolution: {integrity: sha512-lJUL9imLTNi1ZfXT+DU6rBBdbiKGBuay9B6xGSPVjUeQwaH1RIGqef8RZkUtHioLmSNpPR5M4HVKJGm1j8FWVQ==}
     dev: true
 
   /ipaddr.js@1.9.1:
@@ -10127,16 +10340,16 @@ packages:
     resolution: {integrity: sha512-8Q7EARjzEnKpt/PCD7e1cgUS0a6X8u5tdSiMqXhojOdoV9TsMsiO+9VLC5vAmO8N7/GmXn7yjR8qnA6bVAEzfA==}
     engines: {node: '>= 0.4'}
     dependencies:
-      call-bind: 1.0.5
-      has-tostringtag: 1.0.0
+      call-bind: 1.0.7
+      has-tostringtag: 1.0.2
     dev: true
 
-  /is-array-buffer@3.0.2:
-    resolution: {integrity: sha512-y+FyyR/w8vfIRq4eQcM1EYgSTnmHXPqaF+IgzgraytCFq5Xh8lllDVmAZolPJiZttZLeFSINPYMaEJ7/vWUa1w==}
+  /is-array-buffer@3.0.4:
+    resolution: {integrity: sha512-wcjaerHw0ydZwfhiKbXJWLDY8A7yV7KhjQOpb83hGgGfId/aQa4TOvwyzn2PuswW2gPCYEL/nEAiSVpdOj1lXw==}
+    engines: {node: '>= 0.4'}
     dependencies:
-      call-bind: 1.0.5
-      get-intrinsic: 1.2.2
-      is-typed-array: 1.1.12
+      call-bind: 1.0.7
+      get-intrinsic: 1.2.4
     dev: true
 
   /is-arrayish@0.2.1:
@@ -10146,7 +10359,7 @@ packages:
     resolution: {integrity: sha512-Y1JXKrfykRJGdlDwdKlLpLyMIiWqWvuSd17TvZk68PLAOGOoF4Xyav1z0Xhoi+gCYjZVeC5SI+hYFOfvXmGRCA==}
     engines: {node: '>= 0.4'}
     dependencies:
-      has-tostringtag: 1.0.0
+      has-tostringtag: 1.0.2
     dev: true
 
   /is-bigint@1.0.4:
@@ -10166,8 +10379,8 @@ packages:
     resolution: {integrity: sha512-gDYaKHJmnj4aWxyj6YHyXVpdQawtVLHU5cb+eztPGczf6cjuTdwve5ZIEfgXqH4e57An1D1AKf8CZ3kYrQRqYA==}
     engines: {node: '>= 0.4'}
     dependencies:
-      call-bind: 1.0.5
-      has-tostringtag: 1.0.0
+      call-bind: 1.0.7
+      has-tostringtag: 1.0.2
     dev: true
 
   /is-callable@1.2.7:
@@ -10178,13 +10391,13 @@ packages:
   /is-core-module@2.13.1:
     resolution: {integrity: sha512-hHrIjvZsftOsvKSn2TRYl63zvxsgE0K+0mYMoH6gD4omR5IWB2KynivBQczo3+wF1cCkjzvptnI9Q0sPU66ilw==}
     dependencies:
-      hasown: 2.0.0
+      hasown: 2.0.1
 
   /is-date-object@1.0.5:
     resolution: {integrity: sha512-9YQaSxsAiSwcvS33MBk3wTCVnWK+HhF8VZR2jRxehM16QcVOdHqPn4VPHmRK4lSr38n9JriurInLcP90xsYNfQ==}
     engines: {node: '>= 0.4'}
     dependencies:
-      has-tostringtag: 1.0.0
+      has-tostringtag: 1.0.2
     dev: true
 
   /is-deflate@1.0.0:
@@ -10205,7 +10418,7 @@ packages:
   /is-finalizationregistry@1.0.2:
     resolution: {integrity: sha512-0by5vtUJs8iFQb5TYUHHPudOR+qXYIMKtiUzvLIZITZUjknFmziyBJuLhVRc+Ds0dREFlskDNJKYIdIzu/9pfw==}
     dependencies:
-      call-bind: 1.0.5
+      call-bind: 1.0.7
     dev: true
 
   /is-fullwidth-code-point@3.0.0:
@@ -10217,7 +10430,7 @@ packages:
     resolution: {integrity: sha512-jsEjy9l3yiXEQ+PsXdmBwEPcOxaXWLspKdplFUVI9vq1iZgIekeC0L167qeu86czQaxed3q/Uzuw0swL0irL8A==}
     engines: {node: '>= 0.4'}
     dependencies:
-      has-tostringtag: 1.0.0
+      has-tostringtag: 1.0.2
     dev: true
 
   /is-glob@4.0.3:
@@ -10245,12 +10458,12 @@ packages:
     resolution: {integrity: sha512-E+zBKpQ2t6MEo1VsonYmluk9NxGrbzpeeLC2xIViuO2EjU2xsXsBPwTr3Ykv9l08UYEVEdWeRZNouaZqF6RN0w==}
     engines: {node: '>= 0.4'}
     dependencies:
-      call-bind: 1.0.5
+      call-bind: 1.0.7
       define-properties: 1.2.1
     dev: true
 
-  /is-negative-zero@2.0.2:
-    resolution: {integrity: sha512-dqJvarLawXsFbNDeJW7zAz8ItJ9cd28YufuuFzh0G8pNHjJMnY08Dv7sYX2uF5UpQOwieAeOExEYAWWfu7ZZUA==}
+  /is-negative-zero@2.0.3:
+    resolution: {integrity: sha512-5KoIu2Ngpyek75jXodFvnafB6DJgr3u8uuK0LEZJjrU19DrMD3EVERaR8sjz8CCGgpZvxPl9SuE1GMVPFHx1mw==}
     engines: {node: '>= 0.4'}
     dev: true
 
@@ -10258,7 +10471,7 @@ packages:
     resolution: {integrity: sha512-k1U0IRzLMo7ZlYIfzRu23Oh6MiIFasgpb9X76eqfFZAqwH44UI4KTBvBYIZ1dSL9ZzChTB9ShHfLkR4pdW5krQ==}
     engines: {node: '>= 0.4'}
     dependencies:
-      has-tostringtag: 1.0.0
+      has-tostringtag: 1.0.2
     dev: true
 
   /is-number@7.0.0:
@@ -10297,8 +10510,8 @@ packages:
     resolution: {integrity: sha512-kvRdxDsxZjhzUX07ZnLydzS1TU/TJlTUHHY4YLL87e37oUA49DfkLqgy+VjFocowy29cKvcSiu+kIv728jTTVg==}
     engines: {node: '>= 0.4'}
     dependencies:
-      call-bind: 1.0.5
-      has-tostringtag: 1.0.0
+      call-bind: 1.0.7
+      has-tostringtag: 1.0.2
     dev: true
 
   /is-regexp@1.0.0:
@@ -10317,7 +10530,7 @@ packages:
   /is-shared-array-buffer@1.0.2:
     resolution: {integrity: sha512-sqN2UDu1/0y6uvXyStCOzyhAjCSlHceFoMKJW8W9EU9cvic/QdsZ0kEU93HEy3IUEFZIiH/3w+AH/UQbPHNdhA==}
     dependencies:
-      call-bind: 1.0.5
+      call-bind: 1.0.7
     dev: true
 
   /is-stream@2.0.1:
@@ -10334,7 +10547,7 @@ packages:
     resolution: {integrity: sha512-tE2UXzivje6ofPW7l23cjDOMa09gb7xlAqG6jG5ej6uPV32TlWP3NKPigtaGeHNu9fohccRYvIiZMfOOnOYUtg==}
     engines: {node: '>= 0.4'}
     dependencies:
-      has-tostringtag: 1.0.0
+      has-tostringtag: 1.0.2
     dev: true
 
   /is-symbol@1.0.4:
@@ -10344,11 +10557,11 @@ packages:
       has-symbols: 1.0.3
     dev: true
 
-  /is-typed-array@1.1.12:
-    resolution: {integrity: sha512-Z14TF2JNG8Lss5/HMqt0//T9JeHXttXy5pH/DBU4vi98ozO2btxzq9MwYDZYnKwU8nRsz/+GVFVRDq3DkVuSPg==}
+  /is-typed-array@1.1.13:
+    resolution: {integrity: sha512-uZ25/bUAlUY5fR4OKT4rZQEBrzQWYV9ZJYGGsUmEJ6thodVJ1HX64ePQ6Z0qPWP+m+Uq6e9UugrE38jeYsDSMw==}
     engines: {node: '>= 0.4'}
     dependencies:
-      which-typed-array: 1.1.13
+      which-typed-array: 1.1.14
     dev: true
 
   /is-unicode-supported@0.1.0:
@@ -10372,14 +10585,14 @@ packages:
   /is-weakref@1.0.2:
     resolution: {integrity: sha512-qctsuLZmIQ0+vSSMfoVvyFe2+GSEvnmZ2ezTup1SBse9+twCCeial6EEi3Nc2KFcf6+qz2FBPnjXsk8xhKSaPQ==}
     dependencies:
-      call-bind: 1.0.5
+      call-bind: 1.0.7
     dev: true
 
   /is-weakset@2.0.2:
     resolution: {integrity: sha512-t2yVvttHkQktwnNNmBQ98AhENLdPUTDTE21uPqAQ0ARwQfGeQKRVS0NNurH7bTf7RrvcVn1OOge45CnBeHCSmg==}
     dependencies:
-      call-bind: 1.0.5
-      get-intrinsic: 1.2.2
+      call-bind: 1.0.7
+      get-intrinsic: 1.2.4
     dev: true
 
   /is-wsl@2.2.0:
@@ -10415,8 +10628,8 @@ packages:
     resolution: {integrity: sha512-pzqtp31nLv/XFOzXGuvhCb8qhjmTVo5vjVk19XE4CRlSWz0KoeJ3bw9XsA7nOp9YBf4qHjwBxkDzKcME/J29Yg==}
     engines: {node: '>=8'}
     dependencies:
-      '@babel/core': 7.23.7
-      '@babel/parser': 7.23.6
+      '@babel/core': 7.23.9
+      '@babel/parser': 7.23.9
       '@istanbuljs/schema': 0.1.3
       istanbul-lib-coverage: 3.2.2
       semver: 6.3.1
@@ -10428,10 +10641,10 @@ packages:
     resolution: {integrity: sha512-DR33HMMr8EzwuRL8Y9D3u2BMj8+RqSE850jfGu59kS7tbmPLzGkZmVSfyCFSDxuZiEY6Rzt3T2NA/qU+NwVj1w==}
     dependencies:
       define-properties: 1.2.1
-      get-intrinsic: 1.2.2
+      get-intrinsic: 1.2.4
       has-symbols: 1.0.3
-      reflect.getprototypeof: 1.0.4
-      set-function-name: 2.0.1
+      reflect.getprototypeof: 1.0.5
+      set-function-name: 2.0.2
     dev: true
 
   /its-fine@1.1.1(react@18.2.0):
@@ -10469,7 +10682,7 @@ packages:
     dependencies:
       '@jest/types': 29.6.3
       '@types/graceful-fs': 4.1.9
-      '@types/node': 20.11.5
+      '@types/node': 20.11.19
       anymatch: 3.1.3
       fb-watchman: 2.0.2
       graceful-fs: 4.2.11
@@ -10487,7 +10700,7 @@ packages:
     engines: {node: ^10.13.0 || ^12.13.0 || ^14.15.0 || >=15.0.0}
     dependencies:
       '@jest/types': 27.5.1
-      '@types/node': 20.11.5
+      '@types/node': 20.11.19
     dev: true
 
   /jest-regex-util@29.6.3:
@@ -10500,7 +10713,7 @@ packages:
     engines: {node: ^14.15.0 || ^16.10.0 || >=18.0.0}
     dependencies:
       '@jest/types': 29.6.3
-      '@types/node': 20.11.5
+      '@types/node': 20.11.19
       chalk: 4.1.2
       ci-info: 3.9.0
       graceful-fs: 4.2.11
@@ -10511,7 +10724,7 @@ packages:
     resolution: {integrity: sha512-eIz2msL/EzL9UFTFFx7jBTkeZfku0yUAyZZZmJ93H2TYEiroIx2PQjEXcwYtYl8zXCxb+PAmA2hLIt/6ZEkPHw==}
     engines: {node: ^14.15.0 || ^16.10.0 || >=18.0.0}
     dependencies:
-      '@types/node': 20.11.5
+      '@types/node': 20.11.19
       jest-util: 29.7.0
       merge-stream: 2.0.0
       supports-color: 8.1.1
@@ -10528,6 +10741,10 @@ packages:
   /js-tokens@4.0.0:
     resolution: {integrity: sha512-RdJUflcE3cUzKiMqQgsCu06FPu9UdIJO0beYbPhHN4k6apgJtifcoCtT9bcxOpYBtpD2kCM6Sbzg4CausW/PKQ==}
 
+  /js-tokens@8.0.3:
+    resolution: {integrity: sha512-UfJMcSJc+SEXEl9lH/VLHSZbThQyLpw1vLO1Lb+j4RWDvG3N2f7yj3PVQA3cmkTBNldJ9eFnM+xEXxHIXrYiJw==}
+    dev: true
+
   /js-yaml@3.14.1:
     resolution: {integrity: sha512-okMH7OXXJ7YrN9Ok3/SXrnu4iX9yOk+25nqX4imS2npuvTYDmo/QEZoqwZkYaIDk3jVvBOTOIEgEhaLOynBS9g==}
     hasBin: true
@@ -10543,7 +10760,7 @@ packages:
       argparse: 2.0.1
     dev: true
 
-  /jscodeshift@0.15.1(@babel/preset-env@7.23.8):
+  /jscodeshift@0.15.1(@babel/preset-env@7.23.9):
     resolution: {integrity: sha512-hIJfxUy8Rt4HkJn/zZPU9ChKfKZM1342waJ1QC2e2YsPcWhM+3BJ4dcfQCzArTrk1jJeNLB341H+qOcEHRxJZg==}
     hasBin: true
     peerDependencies:
@@ -10552,20 +10769,20 @@ packages:
       '@babel/preset-env':
         optional: true
     dependencies:
-      '@babel/core': 7.23.7
-      '@babel/parser': 7.23.6
-      '@babel/plugin-transform-class-properties': 7.23.3(@babel/core@7.23.7)
-      '@babel/plugin-transform-modules-commonjs': 7.23.3(@babel/core@7.23.7)
-      '@babel/plugin-transform-nullish-coalescing-operator': 7.23.4(@babel/core@7.23.7)
-      '@babel/plugin-transform-optional-chaining': 7.23.4(@babel/core@7.23.7)
-      '@babel/plugin-transform-private-methods': 7.23.3(@babel/core@7.23.7)
-      '@babel/preset-env': 7.23.8(@babel/core@7.23.7)
-      '@babel/preset-flow': 7.23.3(@babel/core@7.23.7)
-      '@babel/preset-typescript': 7.23.3(@babel/core@7.23.7)
-      '@babel/register': 7.23.7(@babel/core@7.23.7)
-      babel-core: 7.0.0-bridge.0(@babel/core@7.23.7)
+      '@babel/core': 7.23.9
+      '@babel/parser': 7.23.9
+      '@babel/plugin-transform-class-properties': 7.23.3(@babel/core@7.23.9)
+      '@babel/plugin-transform-modules-commonjs': 7.23.3(@babel/core@7.23.9)
+      '@babel/plugin-transform-nullish-coalescing-operator': 7.23.4(@babel/core@7.23.9)
+      '@babel/plugin-transform-optional-chaining': 7.23.4(@babel/core@7.23.9)
+      '@babel/plugin-transform-private-methods': 7.23.3(@babel/core@7.23.9)
+      '@babel/preset-env': 7.23.9(@babel/core@7.23.9)
+      '@babel/preset-flow': 7.23.3(@babel/core@7.23.9)
+      '@babel/preset-typescript': 7.23.3(@babel/core@7.23.9)
+      '@babel/register': 7.23.7(@babel/core@7.23.9)
+      babel-core: 7.0.0-bridge.0(@babel/core@7.23.9)
       chalk: 4.1.2
-      flow-parser: 0.227.0
+      flow-parser: 0.229.0
       graceful-fs: 4.2.11
       micromatch: 4.0.5
       neo-async: 2.6.2
@@ -10679,8 +10896,8 @@ packages:
     resolution: {integrity: sha512-Y+60/zizpJ3HRH8DCss+q95yr6145JXZo46OTpFvDZWLfRCE4qChOyk1b26nMaNpfHHgxagk9dXT5OP0Tfe+dQ==}
     dev: true
 
-  /konva@9.3.1:
-    resolution: {integrity: sha512-KXHJVUrYVWFIJUbnlw8QUZDBGC1jx6wwRsGaByPm/2yk78xw7hKquCMNEd9EtVqGz/jUkKFJAWom77TLB+zVOA==}
+  /konva@9.3.3:
+    resolution: {integrity: sha512-cg/AHxnfawZ1rKxygCnzx0TZY7hQiQiAKgAHPinEwMn49MVrBkeKLj2d0EaleoFG/0y0XhEKTD0dFZiPPdWlCQ==}
     dev: false
 
   /lazy-universal-dotenv@4.0.0:
@@ -10688,7 +10905,7 @@ packages:
     engines: {node: '>=14.0.0'}
     dependencies:
       app-root-dir: 1.0.2
-      dotenv: 16.3.1
+      dotenv: 16.4.5
       dotenv-expand: 10.0.0
     dev: true
 
@@ -10799,8 +11016,8 @@ packages:
       get-func-name: 2.0.2
     dev: true
 
-  /lru-cache@10.1.0:
-    resolution: {integrity: sha512-/1clY/ui8CzjKFyjdvwPWJUYKiFVXG2I2cY0ssG7h4+hwk+XOIX7ZSG9Q7TW8TW3Kp3BUSqgFWBLgL4PJ+Blag==}
+  /lru-cache@10.2.0:
+    resolution: {integrity: sha512-2bIM8x+VAf6JT4bKAljS1qUWgMsqZRPGJS6FSahIMPVvctcNhyVp7AJu7quxOW9jwkryBReKZY5tY5JYv2n/7Q==}
     engines: {node: 14 || >=16.14}
     dev: true
 
@@ -10852,7 +11069,7 @@ packages:
       pretty-ms: 7.0.1
       rc: 1.2.8
       stream-to-array: 2.3.0
-      ts-graphviz: 1.8.1
+      ts-graphviz: 1.8.2
       typescript: 5.3.3
       walkdir: 0.4.1
     transitivePeerDependencies:
@@ -10866,8 +11083,8 @@ packages:
       '@jridgewell/sourcemap-codec': 1.4.15
     dev: true
 
-  /magic-string@0.30.5:
-    resolution: {integrity: sha512-7xlpfBaQaP/T6Vh8MO/EqXSW5En6INHEvEXQiuff7Gku0PWjU3uf6w/j9o7O+SpB5fOAkrI5HeoNgwjEO0pFsA==}
+  /magic-string@0.30.7:
+    resolution: {integrity: sha512-8vBuFF/I/+OSLRmdf2wwFCJCz+nSn0m6DPvGH1fS/KiQoSaR+sETbov0eIk9KhEKy8CYqIkIAnbohxT/4H0kuA==}
     engines: {node: '>=12'}
     dependencies:
       '@jridgewell/sourcemap-codec': 1.4.15
@@ -10898,8 +11115,8 @@ packages:
     resolution: {integrity: sha512-0aF7ZmVon1igznGI4VS30yugpduQW3y3GkcgGJOp7d8x8QrizhigUxjI/m2UojsXXto+jLAH3KSz+xOJTiORjg==}
     dev: true
 
-  /markdown-to-jsx@7.4.0(react@18.2.0):
-    resolution: {integrity: sha512-zilc+MIkVVXPyTb4iIUTIz9yyqfcWjszGXnwF9K/aiBWcHXFcmdEMTkG01/oQhwSCH7SY1BnG6+ev5BzWmbPrg==}
+  /markdown-to-jsx@7.4.1(react@18.2.0):
+    resolution: {integrity: sha512-GbrbkTnHp9u6+HqbPRFJbObi369AgJNXi/sGqq5HRsoZW063xR1XDCaConqq+whfEIAlzB1YPnOgsPc7B7bc/A==}
     engines: {node: '>= 10'}
     peerDependencies:
       react: '>= 0.14.0'
@@ -11073,7 +11290,7 @@ packages:
       acorn: 8.11.3
       pathe: 1.1.2
       pkg-types: 1.0.3
-      ufo: 1.3.2
+      ufo: 1.4.0
     dev: true
 
   /module-definition@3.4.0:
@@ -11151,6 +11368,11 @@ packages:
     hasBin: true
     dev: true
 
+  /nanostores@0.10.0:
+    resolution: {integrity: sha512-Poy5+9wFXOD0jAstn4kv9n686U2BFw48z/W8lms8cS8lcbRz7BU20JxZ3e/kkKQVfRrkm4yLWCUA6GQINdvJCQ==}
+    engines: {node: ^18.0.0 || >=20.0.0}
+    dev: false
+
   /nanostores@0.9.5:
     resolution: {integrity: sha512-Z+p+g8E7yzaWwOe5gEUB2Ox0rCEeXWYIZWmYvw/ajNYX8DlXdMvMDj8DWfM/subqPAcsf8l8Td4iAwO1DeIIRQ==}
     engines: {node: ^16.0.0 || ^18.0.0 || >=20.0.0}
@@ -11191,8 +11413,8 @@ packages:
       minimatch: 3.1.2
     dev: true
 
-  /node-fetch-native@1.6.1:
-    resolution: {integrity: sha512-bW9T/uJDPAJB2YNYEpWzE54U5O3MQidXsOyTfnbKYtTtFexRvGzb1waphBN4ZwP6EcIvYYEOwW0b72BpAqydTw==}
+  /node-fetch-native@1.6.2:
+    resolution: {integrity: sha512-69mtXOFZ6hSkYiXAVB5SqaRvrbITC/NPyqv7yuu/qw0nmgPyYbIMYYNIDhNtwPrzk0ptrimrLz/hhjvm4w5Z+w==}
     dev: true
 
   /node-fetch@2.7.0:
@@ -11218,14 +11440,14 @@ packages:
     resolution: {integrity: sha512-8Q1hXew6ETzqKRAs3jjLioSxNfT1cx74ooiF8RlAONwVMcfq+UdzLC2eB5qcPldUxaE5w3ytLkrmV1TGddhZTA==}
     engines: {node: '>=6.0'}
     dependencies:
-      '@babel/parser': 7.23.6
+      '@babel/parser': 7.23.9
     dev: true
 
   /node-source-walk@5.0.2:
     resolution: {integrity: sha512-Y4jr/8SRS5hzEdZ7SGuvZGwfORvNsSsNRwDXx5WisiqzsVfeftDvRgfeqWNgZvWSJbgubTRVRYBzK6UO+ErqjA==}
     engines: {node: '>=12'}
     dependencies:
-      '@babel/parser': 7.23.6
+      '@babel/parser': 7.23.9
     dev: true
 
   /normalize-package-data@2.5.0:
@@ -11256,15 +11478,15 @@ packages:
       path-key: 4.0.0
     dev: true
 
-  /nypm@0.3.4:
-    resolution: {integrity: sha512-1JLkp/zHBrkS3pZ692IqOaIKSYHmQXgqfELk6YTOfVBnwealAmPA1q2kKK7PHJAHSMBozerThEFZXP3G6o7Ukg==}
+  /nypm@0.3.6:
+    resolution: {integrity: sha512-2CATJh3pd6CyNfU5VZM7qSwFu0ieyabkEdnogE30Obn1czrmOYiZ8DOZLe1yBdLKWoyD3Mcy2maUs+0MR3yVjQ==}
     engines: {node: ^14.16.0 || >=16.10.0}
     hasBin: true
     dependencies:
-      citty: 0.1.5
+      citty: 0.1.6
       execa: 8.0.1
       pathe: 1.1.2
-      ufo: 1.3.2
+      ufo: 1.4.0
     dev: true
 
   /object-assign@4.1.1:
@@ -11279,7 +11501,7 @@ packages:
     resolution: {integrity: sha512-3cyDsyHgtmi7I7DfSSI2LDp6SK2lwvtbg0p0R1e0RvTqF5ceGx+K2dfSjm1bKDMVCFEDAQvy+o8c6a7VujOddw==}
     engines: {node: '>= 0.4'}
     dependencies:
-      call-bind: 1.0.5
+      call-bind: 1.0.7
       define-properties: 1.2.1
     dev: true
 
@@ -11291,7 +11513,7 @@ packages:
     resolution: {integrity: sha512-byy+U7gp+FVwmyzKPYhW2h5l3crpmGsxl7X2s8y43IgxvG4g3QZ6CffDtsNQy1WsmZpQbO+ybo0AlW7TY6DcBQ==}
     engines: {node: '>= 0.4'}
     dependencies:
-      call-bind: 1.0.5
+      call-bind: 1.0.7
       define-properties: 1.2.1
       has-symbols: 1.0.3
       object-keys: 1.1.1
@@ -11301,43 +11523,44 @@ packages:
     resolution: {integrity: sha512-jCBs/0plmPsOnrKAfFQXRG2NFjlhZgjjcBLSmTnEhU8U6vVTsVe8ANeQJCHTl3gSsI4J+0emOoCgoKlmQPMgmA==}
     engines: {node: '>= 0.4'}
     dependencies:
-      call-bind: 1.0.5
+      call-bind: 1.0.7
       define-properties: 1.2.1
-      es-abstract: 1.22.3
+      es-abstract: 1.22.4
     dev: true
 
   /object.fromentries@2.0.7:
     resolution: {integrity: sha512-UPbPHML6sL8PI/mOqPwsH4G6iyXcCGzLin8KvEPenOZN5lpCNBZZQ+V62vdjB1mQHrmqGQt5/OJzemUA+KJmEA==}
     engines: {node: '>= 0.4'}
     dependencies:
-      call-bind: 1.0.5
+      call-bind: 1.0.7
       define-properties: 1.2.1
-      es-abstract: 1.22.3
+      es-abstract: 1.22.4
     dev: true
 
-  /object.groupby@1.0.1:
-    resolution: {integrity: sha512-HqaQtqLnp/8Bn4GL16cj+CUYbnpe1bh0TtEaWvybszDG4tgxCJuRpV8VGuvNaI1fAnI4lUJzDG55MXcOH4JZcQ==}
+  /object.groupby@1.0.2:
+    resolution: {integrity: sha512-bzBq58S+x+uo0VjurFT0UktpKHOZmv4/xePiOA1nbB9pMqpGK7rUPNgf+1YC+7mE+0HzhTMqNUuCqvKhj6FnBw==}
     dependencies:
-      call-bind: 1.0.5
+      array.prototype.filter: 1.0.3
+      call-bind: 1.0.7
       define-properties: 1.2.1
-      es-abstract: 1.22.3
-      get-intrinsic: 1.2.2
+      es-abstract: 1.22.4
+      es-errors: 1.3.0
     dev: true
 
   /object.hasown@1.1.3:
     resolution: {integrity: sha512-fFI4VcYpRHvSLXxP7yiZOMAd331cPfd2p7PFDVbgUsYOfCT3tICVqXWngbjr4m49OvsBwUBQ6O2uQoJvy3RexA==}
     dependencies:
       define-properties: 1.2.1
-      es-abstract: 1.22.3
+      es-abstract: 1.22.4
     dev: true
 
   /object.values@1.1.7:
     resolution: {integrity: sha512-aU6xnDFYT3x17e/f0IiiwlGPTy2jzMySGfUB4fq6z7CV8l85CWHDk5ErhyhpfDHhrOMwGFhSQkhMGHaIotA6Ng==}
     engines: {node: '>= 0.4'}
     dependencies:
-      call-bind: 1.0.5
+      call-bind: 1.0.7
       define-properties: 1.2.1
-      es-abstract: 1.22.3
+      es-abstract: 1.22.4
     dev: true
 
   /ohash@1.1.3:
@@ -11389,15 +11612,15 @@ packages:
     resolution: {integrity: sha512-N4YtSYJqghVu4iek2ZUvcN/0aqH1kRDuNqzcycDxhOUpg7GdvLa2F3DgS6yBNhInhv2r/6I0Flkn7CqL8+nIcw==}
     dev: true
 
-  /openapi-typescript@6.7.3:
-    resolution: {integrity: sha512-es3mGcDXV6TKPo6n3aohzHm0qxhLyR39MhF6mkD1FwFGjhxnqMqfSIgM0eCpInZvqatve4CxmXcMZw3jnnsaXw==}
+  /openapi-typescript@6.7.4:
+    resolution: {integrity: sha512-EZyeW9Wy7UDCKv0iYmKrq2pVZtquXiD/YHiUClAKqiMi42nodx/EQH11K6fLqjt1IZlJmVokrAsExsBMM2RROQ==}
     hasBin: true
     dependencies:
       ansi-colors: 4.1.3
       fast-glob: 3.3.2
       js-yaml: 4.1.0
       supports-color: 9.4.0
-      undici: 5.28.2
+      undici: 5.28.3
       yargs-parser: 21.1.1
     dev: true
 
@@ -11428,16 +11651,6 @@ packages:
       wcwidth: 1.0.1
     dev: true
 
-  /overlayscrollbars-react@0.5.3(overlayscrollbars@2.4.6)(react@18.2.0):
-    resolution: {integrity: sha512-mq9D9tbfSeq0cti1kKMf3B3AzsEGwHcRIDX/K49CvYkHz/tKeU38GiahDkIPKTMEAp6lzKCo4x1eJZA6ZFYOxQ==}
-    peerDependencies:
-      overlayscrollbars: ^2.0.0
-      react: '>=16.8.0'
-    dependencies:
-      overlayscrollbars: 2.4.6
-      react: 18.2.0
-    dev: false
-
   /overlayscrollbars-react@0.5.4(overlayscrollbars@2.5.0)(react@18.2.0):
     resolution: {integrity: sha512-FPKx9XnXovTnI4+2JXig5uEaTLSEJ6svOwPzIfBBXTHBRNsz2+WhYUmfM0K/BNYxjgDEwuPm+NQhEoOA0RoG1g==}
     peerDependencies:
@@ -11448,10 +11661,6 @@ packages:
       react: 18.2.0
     dev: false
 
-  /overlayscrollbars@2.4.6:
-    resolution: {integrity: sha512-C7tmhetwMv9frEvIT/RfkAVEgbjRNz/Gh2zE8BVmN+jl35GRaAnz73rlGQCMRoC2arpACAXyMNnJkzHb7GBrcA==}
-    dev: false
-
   /overlayscrollbars@2.5.0:
     resolution: {integrity: sha512-CWVC2dwS07XZfLHDm5GmZN1iYggiJ8Vufnvzwt0gwR9Yz1hVckKeTxg7VILZeYVGhDYJHZ1Xc8Xfys5dWZ1qiA==}
     dev: false
@@ -11575,7 +11784,7 @@ packages:
     resolution: {integrity: sha512-MkhCqzzBEpPvxxQ71Md0b1Kk51W01lrYvlMzSUaIzNsODdd7mqhiimSZlr+VegAz5Z6Vzt9Xg2ttE//XBhH3EQ==}
     engines: {node: '>=16 || 14 >=14.17'}
     dependencies:
-      lru-cache: 10.1.0
+      lru-cache: 10.2.0
       minipass: 7.0.4
     dev: true
 
@@ -11660,11 +11869,16 @@ packages:
     engines: {node: '>=4'}
     dev: true
 
-  /polished@4.2.2:
-    resolution: {integrity: sha512-Sz2Lkdxz6F2Pgnpi9U5Ng/WdWAUZxmHrNPoVlm3aAemxoy2Qy7LGjQg4uf8qKelDAUW94F4np3iH2YPf2qefcQ==}
+  /polished@4.3.1:
+    resolution: {integrity: sha512-OBatVyC/N7SCW/FaDHrSd+vn0o5cS855TOmYi4OkdWUMSJCET/xip//ch8xGUvtr3i44X9LVyWwQlRMTN3pwSA==}
     engines: {node: '>=10'}
     dependencies:
-      '@babel/runtime': 7.23.8
+      '@babel/runtime': 7.23.9
+    dev: true
+
+  /possible-typed-array-names@1.0.0:
+    resolution: {integrity: sha512-d7Uw+eZoloe0EHDIYoe+bQ5WXnGMOpmiZFTuMWCwpjzzkL2nTjcKiAk4hh8TjnGye2TwWOk3UXucZ+3rbmBa8Q==}
+    engines: {node: '>= 0.4'}
     dev: true
 
   /postcss-values-parser@2.0.1:
@@ -11676,7 +11890,7 @@ packages:
       uniq: 1.0.1
     dev: true
 
-  /postcss-values-parser@6.0.2(postcss@8.4.33):
+  /postcss-values-parser@6.0.2(postcss@8.4.35):
     resolution: {integrity: sha512-YLJpK0N1brcNJrs9WatuJFtHaV9q5aAOj+S4DI5S7jgHlRfm0PIbDCAFRYMQD5SHq7Fy6xsDhyutgS0QOAs0qw==}
     engines: {node: '>=10'}
     peerDependencies:
@@ -11684,12 +11898,12 @@ packages:
     dependencies:
       color-name: 1.1.4
       is-url-superb: 4.0.0
-      postcss: 8.4.33
+      postcss: 8.4.35
       quote-unquote: 1.0.0
     dev: true
 
-  /postcss@8.4.33:
-    resolution: {integrity: sha512-Kkpbhhdjw2qQs2O2DGX+8m5OVqEcbB9HRBvuYM9pgrjEFUg30A9LmXNlTAUj4S9kgtGyrMbTzVjH7E+s5Re2yg==}
+  /postcss@8.4.35:
+    resolution: {integrity: sha512-u5U8qYpBCpN13BsiEB0CbR1Hhh4Gc0zLFuedrHJKMctHCHAGrMdG0PRM/KErzAL3CU6/eckEtmHNB3x6e3c0vA==}
     engines: {node: ^10 || ^12 || >=14}
     dependencies:
       nanoid: 3.3.7
@@ -11751,8 +11965,8 @@ packages:
     hasBin: true
     dev: true
 
-  /prettier@3.2.4:
-    resolution: {integrity: sha512-FWu1oLHKCrtpO1ypU6J0SbK2d9Ckwysq6bHj/uaCP26DxrPpppCLQRGVuqAxSTvhF00AcvDRyYrLNW7ocBhFFQ==}
+  /prettier@3.2.5:
+    resolution: {integrity: sha512-3/GWa9aOC0YeD7LUfvOG2NiDyhOWRvt1k+rcKhOuYnMY24iiCphgneUfJDyFXd6rZCAnuLBv6UeAULtrhT/F4A==}
     engines: {node: '>=14'}
     hasBin: true
     dev: true
@@ -11883,18 +12097,18 @@ packages:
     resolution: {integrity: sha512-MvjoMCJwEarSbUYk5O+nmoSzSutSsTwF85zcHPQ9OrlFoZOYIjaqBAJIqIXjptyD5vThxGq52Xu/MaJzRkIk4Q==}
     engines: {node: '>=0.6'}
     dependencies:
-      side-channel: 1.0.4
+      side-channel: 1.0.5
     dev: true
 
   /qs@6.11.2:
     resolution: {integrity: sha512-tDNIz22aBzCDxLtVH++VnTfzxlfeK5CbqohpSqpJgj1Wg/cQbStNAz3NuqCs5vV+pjBsK4x4pN9HlVh7rcYRiA==}
     engines: {node: '>=0.6'}
     dependencies:
-      side-channel: 1.0.4
+      side-channel: 1.0.5
     dev: true
 
-  /query-string@8.1.0:
-    resolution: {integrity: sha512-BFQeWxJOZxZGix7y+SByG3F36dA0AbTy9o6pSmKFcFz7DAj0re9Frkty3saBn3nHo3D0oZJ/+rx3r8H8r8Jbpw==}
+  /query-string@8.2.0:
+    resolution: {integrity: sha512-tUZIw8J0CawM5wyGBiDOAp7ObdRQh4uBor/fUR9ZjmbZVvw95OD9If4w3MQxr99rg0DJZ/9CIORcpEqU5hQG7g==}
     engines: {node: '>=14.16'}
     dependencies:
       decode-uri-component: 0.4.1
@@ -11981,9 +12195,9 @@ packages:
     resolution: {integrity: sha512-i8aF1nyKInZnANZ4uZrH49qn1paRgBZ7wZiCNBMnenlPzEv0mRl+ShpTVEI6wZNl8sSc79xZkivtgLKQArcanQ==}
     engines: {node: '>=16.14.0'}
     dependencies:
-      '@babel/core': 7.23.7
-      '@babel/traverse': 7.23.7
-      '@babel/types': 7.23.6
+      '@babel/core': 7.23.9
+      '@babel/traverse': 7.23.9
+      '@babel/types': 7.23.9
       '@types/babel__core': 7.20.5
       '@types/babel__traverse': 7.20.5
       '@types/doctrine': 0.0.9
@@ -12034,7 +12248,7 @@ packages:
     peerDependencies:
       react: '>=16.13.1'
     dependencies:
-      '@babel/runtime': 7.23.6
+      '@babel/runtime': 7.23.9
       react: 18.2.0
     dev: false
 
@@ -12042,7 +12256,7 @@ packages:
     resolution: {integrity: sha512-nsO+KSNgo1SbJqJEYRE9ERzo7YtYbou/OqjSQKxV7jcKox7+usiUVZOAC+XnDOABXggQTno0Y1CpVnuWEc1boQ==}
     dev: false
 
-  /react-focus-lock@2.11.1(@types/react@18.2.48)(react@18.2.0):
+  /react-focus-lock@2.11.1(@types/react@18.2.57)(react@18.2.0):
     resolution: {integrity: sha512-IXLwnTBrLTlKTpASZXqqXJ8oymWrgAlOfuuDYN4XCuN1YJ72dwX198UCaF1QqGUk5C3QOnlMik//n3ufcfe8Ig==}
     peerDependencies:
       '@types/react': ^16.8.0 || ^17.0.0 || ^18.0.0
@@ -12052,26 +12266,26 @@ packages:
         optional: true
     dependencies:
       '@babel/runtime': 7.23.9
-      '@types/react': 18.2.48
-      focus-lock: 1.3.2
+      '@types/react': 18.2.57
+      focus-lock: 1.3.3
       prop-types: 15.8.1
       react: 18.2.0
       react-clientside-effect: 1.2.6(react@18.2.0)
-      use-callback-ref: 1.3.1(@types/react@18.2.48)(react@18.2.0)
-      use-sidecar: 1.1.2(@types/react@18.2.48)(react@18.2.0)
+      use-callback-ref: 1.3.1(@types/react@18.2.57)(react@18.2.0)
+      use-sidecar: 1.1.2(@types/react@18.2.57)(react@18.2.0)
     dev: false
 
-  /react-hook-form@7.49.3(react@18.2.0):
-    resolution: {integrity: sha512-foD6r3juidAT1cOZzpmD/gOKt7fRsDhXXZ0y28+Al1CHgX+AY1qIN9VSIIItXRq1dN68QrRwl1ORFlwjBaAqeQ==}
-    engines: {node: '>=18', pnpm: '8'}
+  /react-hook-form@7.50.1(react@18.2.0):
+    resolution: {integrity: sha512-3PCY82oE0WgeOgUtIr3nYNNtNvqtJ7BZjsbxh6TnYNbXButaD5WpjOmTjdxZfheuHKR68qfeFnEDVYoSSFPMTQ==}
+    engines: {node: '>=12.22.0'}
     peerDependencies:
       react: ^16.8.0 || ^17 || ^18
     dependencies:
       react: 18.2.0
     dev: false
 
-  /react-hotkeys-hook@4.4.4(react-dom@18.2.0)(react@18.2.0):
-    resolution: {integrity: sha512-wzZmqb/Obr0ds9Myc1sIFPJ52GA/Eeg/vXBWV0HA1LvHlVAW5Va3KB0q6EZNlNSHQWscWZ2K8+6w0GYSie2o7A==}
+  /react-hotkeys-hook@4.5.0(react-dom@18.2.0)(react@18.2.0):
+    resolution: {integrity: sha512-Samb85GSgAWFQNvVt3PS90LPPGSf9mkH/r4au81ZP1yOIFayLC3QAvqTgGtJ8YEDMXtPmaVBs6NgipHO6h4Mug==}
     peerDependencies:
       react: '>=16.8.1'
       react-dom: '>=16.8.1'
@@ -12080,27 +12294,7 @@ packages:
       react-dom: 18.2.0(react@18.2.0)
     dev: false
 
-  /react-i18next@14.0.0(i18next@23.7.16)(react-dom@18.2.0)(react@18.2.0):
-    resolution: {integrity: sha512-OCrS8rHNAmnr8ggGRDxjakzihrMW7HCbsplduTm3EuuQ6fyvWGT41ksZpqbduYoqJurBmEsEVZ1pILSUWkHZng==}
-    peerDependencies:
-      i18next: '>= 23.2.3'
-      react: '>= 16.8.0'
-      react-dom: '*'
-      react-native: '*'
-    peerDependenciesMeta:
-      react-dom:
-        optional: true
-      react-native:
-        optional: true
-    dependencies:
-      '@babel/runtime': 7.23.7
-      html-parse-stringify: 3.0.1
-      i18next: 23.7.16
-      react: 18.2.0
-      react-dom: 18.2.0(react@18.2.0)
-    dev: false
-
-  /react-i18next@14.0.5(i18next@23.7.16)(react-dom@18.2.0)(react@18.2.0):
+  /react-i18next@14.0.5(i18next@23.9.0)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-5+bQSeEtgJrMBABBL5lO7jPdSNAbeAZ+MlFWDw//7FnVacuVu3l9EeWFzBQvZsKy+cihkbThWOAThEdH8YjGEw==}
     peerDependencies:
       i18next: '>= 23.2.3'
@@ -12115,7 +12309,7 @@ packages:
     dependencies:
       '@babel/runtime': 7.23.9
       html-parse-stringify: 3.0.1
-      i18next: 23.7.16
+      i18next: 23.9.0
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     dev: false
@@ -12143,7 +12337,7 @@ packages:
     resolution: {integrity: sha512-xWGDIW6x921xtzPkhiULtthJHoJvBbF3q26fzloPCK0hsvxtPVelvftw3zjbHWSkR2km9Z+4uxbDDK/6Zw9B8w==}
     dev: true
 
-  /react-konva@18.2.10(konva@9.3.1)(react-dom@18.2.0)(react@18.2.0):
+  /react-konva@18.2.10(konva@9.3.3)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-ohcX1BJINL43m4ynjZ24MxFI1syjBdrXhqVxYVDw2rKgr3yuS0x/6m1Y2Z4sl4T/gKhfreBx8KHisd0XC6OT1g==}
     peerDependencies:
       konva: ^8.0.1 || ^7.2.5 || ^9.0.0
@@ -12152,7 +12346,7 @@ packages:
     dependencies:
       '@types/react-reconciler': 0.28.8
       its-fine: 1.1.1(react@18.2.0)
-      konva: 9.3.1
+      konva: 9.3.3
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
       react-reconciler: 0.29.0(react@18.2.0)
@@ -12170,7 +12364,7 @@ packages:
       scheduler: 0.23.0
     dev: false
 
-  /react-redux@9.1.0(@types/react@18.2.48)(react@18.2.0)(redux@5.0.1):
+  /react-redux@9.1.0(@types/react@18.2.57)(react@18.2.0)(redux@5.0.1):
     resolution: {integrity: sha512-6qoDzIO+gbrza8h3hjMA9aq4nwVFCKFtY2iLxCtVT38Swyy2C/dJCGBXHeHLtx6qlg/8qzc2MrhOeduf5K32wQ==}
     peerDependencies:
       '@types/react': ^18.2.25
@@ -12185,7 +12379,7 @@ packages:
       redux:
         optional: true
     dependencies:
-      '@types/react': 18.2.48
+      '@types/react': 18.2.57
       '@types/use-sync-external-store': 0.0.3
       react: 18.2.0
       redux: 5.0.1
@@ -12197,23 +12391,7 @@ packages:
     engines: {node: '>=0.10.0'}
     dev: true
 
-  /react-remove-scroll-bar@2.3.4(@types/react@18.2.48)(react@18.2.0):
-    resolution: {integrity: sha512-63C4YQBUt0m6ALadE9XV56hV8BgJWDmmTPY758iIJjfQKt2nYwoUrPk0LXRXcB/yIj82T1/Ixfdpdk68LwIB0A==}
-    engines: {node: '>=10'}
-    peerDependencies:
-      '@types/react': ^16.8.0 || ^17.0.0 || ^18.0.0
-      react: ^16.8.0 || ^17.0.0 || ^18.0.0
-    peerDependenciesMeta:
-      '@types/react':
-        optional: true
-    dependencies:
-      '@types/react': 18.2.48
-      react: 18.2.0
-      react-style-singleton: 2.2.1(@types/react@18.2.48)(react@18.2.0)
-      tslib: 2.6.2
-    dev: true
-
-  /react-remove-scroll-bar@2.3.5(@types/react@18.2.48)(react@18.2.0):
+  /react-remove-scroll-bar@2.3.5(@types/react@18.2.57)(react@18.2.0):
     resolution: {integrity: sha512-3cqjOqg6s0XbOjWvmasmqHch+RLxIEk2r/70rzGXuz3iIGQsQheEQyqYCBb5EECoD01Vo2SIbDqW4paLeLTASw==}
     engines: {node: '>=10'}
     peerDependencies:
@@ -12223,13 +12401,12 @@ packages:
       '@types/react':
         optional: true
     dependencies:
-      '@types/react': 18.2.48
+      '@types/react': 18.2.57
       react: 18.2.0
-      react-style-singleton: 2.2.1(@types/react@18.2.48)(react@18.2.0)
+      react-style-singleton: 2.2.1(@types/react@18.2.57)(react@18.2.0)
       tslib: 2.6.2
-    dev: false
 
-  /react-remove-scroll@2.5.5(@types/react@18.2.48)(react@18.2.0):
+  /react-remove-scroll@2.5.5(@types/react@18.2.57)(react@18.2.0):
     resolution: {integrity: sha512-ImKhrzJJsyXJfBZ4bzu8Bwpka14c/fQt0k+cyFp/PBhTfyDnU5hjOtM4AG/0AMyy8oKzOTR0lDgJIM7pYXI0kw==}
     engines: {node: '>=10'}
     peerDependencies:
@@ -12239,16 +12416,16 @@ packages:
       '@types/react':
         optional: true
     dependencies:
-      '@types/react': 18.2.48
+      '@types/react': 18.2.57
       react: 18.2.0
-      react-remove-scroll-bar: 2.3.4(@types/react@18.2.48)(react@18.2.0)
-      react-style-singleton: 2.2.1(@types/react@18.2.48)(react@18.2.0)
+      react-remove-scroll-bar: 2.3.5(@types/react@18.2.57)(react@18.2.0)
+      react-style-singleton: 2.2.1(@types/react@18.2.57)(react@18.2.0)
       tslib: 2.6.2
-      use-callback-ref: 1.3.1(@types/react@18.2.48)(react@18.2.0)
-      use-sidecar: 1.1.2(@types/react@18.2.48)(react@18.2.0)
+      use-callback-ref: 1.3.1(@types/react@18.2.57)(react@18.2.0)
+      use-sidecar: 1.1.2(@types/react@18.2.57)(react@18.2.0)
     dev: true
 
-  /react-remove-scroll@2.5.7(@types/react@18.2.48)(react@18.2.0):
+  /react-remove-scroll@2.5.7(@types/react@18.2.57)(react@18.2.0):
     resolution: {integrity: sha512-FnrTWO4L7/Bhhf3CYBNArEG/yROV0tKmTv7/3h9QCFvH6sndeFf1wPqOcbFVu5VAulS5dV1wGT3GZZ/1GawqiA==}
     engines: {node: '>=10'}
     peerDependencies:
@@ -12258,17 +12435,17 @@ packages:
       '@types/react':
         optional: true
     dependencies:
-      '@types/react': 18.2.48
+      '@types/react': 18.2.57
       react: 18.2.0
-      react-remove-scroll-bar: 2.3.5(@types/react@18.2.48)(react@18.2.0)
-      react-style-singleton: 2.2.1(@types/react@18.2.48)(react@18.2.0)
+      react-remove-scroll-bar: 2.3.5(@types/react@18.2.57)(react@18.2.0)
+      react-style-singleton: 2.2.1(@types/react@18.2.57)(react@18.2.0)
       tslib: 2.6.2
-      use-callback-ref: 1.3.1(@types/react@18.2.48)(react@18.2.0)
-      use-sidecar: 1.1.2(@types/react@18.2.48)(react@18.2.0)
+      use-callback-ref: 1.3.1(@types/react@18.2.57)(react@18.2.0)
+      use-sidecar: 1.1.2(@types/react@18.2.57)(react@18.2.0)
     dev: false
 
-  /react-resizable-panels@1.0.9(react-dom@18.2.0)(react@18.2.0):
-    resolution: {integrity: sha512-QPfW3L7yetEC6z04G9AYYFz5kBklh8rTWcOsVFImYMNUVhr1Y1r9Qc/20Yks2tA+lXMBWCUz4fkGEvbS7tpBSg==}
+  /react-resizable-panels@2.0.9(react-dom@18.2.0)(react@18.2.0):
+    resolution: {integrity: sha512-ZylBvs7oG7Y/INWw3oYGolqgpFvoPW8MPeg9l1fURDeKpxrmUuCHBUmPj47BdZ11MODImu3kZYXG85rbySab7w==}
     peerDependencies:
       react: ^16.14.0 || ^17.0.0 || ^18.0.0
       react-dom: ^16.14.0 || ^17.0.0 || ^18.0.0
@@ -12277,49 +12454,49 @@ packages:
       react-dom: 18.2.0(react@18.2.0)
     dev: false
 
-  /react-select@5.7.7(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0):
+  /react-select@5.7.7(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-HhashZZJDRlfF/AKj0a0Lnfs3sRdw/46VJIRd8IbB9/Ovr74+ZIwkAdSBjSPXsFMG+u72c5xShqwLSKIJllzqw==}
     peerDependencies:
       react: ^16.8.0 || ^17.0.0 || ^18.0.0
       react-dom: ^16.8.0 || ^17.0.0 || ^18.0.0
     dependencies:
-      '@babel/runtime': 7.23.6
+      '@babel/runtime': 7.23.9
       '@emotion/cache': 11.11.0
-      '@emotion/react': 11.11.3(@types/react@18.2.48)(react@18.2.0)
-      '@floating-ui/dom': 1.5.3
+      '@emotion/react': 11.11.3(@types/react@18.2.57)(react@18.2.0)
+      '@floating-ui/dom': 1.6.3
       '@types/react-transition-group': 4.4.10
       memoize-one: 6.0.0
       prop-types: 15.8.1
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
       react-transition-group: 4.4.5(react-dom@18.2.0)(react@18.2.0)
-      use-isomorphic-layout-effect: 1.1.2(@types/react@18.2.48)(react@18.2.0)
+      use-isomorphic-layout-effect: 1.1.2(@types/react@18.2.57)(react@18.2.0)
     transitivePeerDependencies:
       - '@types/react'
     dev: false
 
-  /react-select@5.8.0(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0):
+  /react-select@5.8.0(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-TfjLDo58XrhP6VG5M/Mi56Us0Yt8X7xD6cDybC7yoRMUNm7BGO7qk8J0TLQOua/prb8vUOtsfnXZwfm30HGsAA==}
     peerDependencies:
       react: ^16.8.0 || ^17.0.0 || ^18.0.0
       react-dom: ^16.8.0 || ^17.0.0 || ^18.0.0
     dependencies:
-      '@babel/runtime': 7.23.7
+      '@babel/runtime': 7.23.9
       '@emotion/cache': 11.11.0
-      '@emotion/react': 11.11.3(@types/react@18.2.48)(react@18.2.0)
-      '@floating-ui/dom': 1.5.3
+      '@emotion/react': 11.11.3(@types/react@18.2.57)(react@18.2.0)
+      '@floating-ui/dom': 1.6.3
       '@types/react-transition-group': 4.4.10
       memoize-one: 6.0.0
       prop-types: 15.8.1
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
       react-transition-group: 4.4.5(react-dom@18.2.0)(react@18.2.0)
-      use-isomorphic-layout-effect: 1.1.2(@types/react@18.2.48)(react@18.2.0)
+      use-isomorphic-layout-effect: 1.1.2(@types/react@18.2.57)(react@18.2.0)
     transitivePeerDependencies:
       - '@types/react'
     dev: false
 
-  /react-style-singleton@2.2.1(@types/react@18.2.48)(react@18.2.0):
+  /react-style-singleton@2.2.1(@types/react@18.2.57)(react@18.2.0):
     resolution: {integrity: sha512-ZWj0fHEMyWkHzKYUr2Bs/4zU6XLmq9HsgBURm7g5pAVfyn49DgUiNgY2d4lXRlYSiCif9YBGpQleewkcqddc7g==}
     engines: {node: '>=10'}
     peerDependencies:
@@ -12329,22 +12506,22 @@ packages:
       '@types/react':
         optional: true
     dependencies:
-      '@types/react': 18.2.48
+      '@types/react': 18.2.57
       get-nonce: 1.0.1
       invariant: 2.2.4
       react: 18.2.0
       tslib: 2.6.2
 
-  /react-textarea-autosize@8.5.3(@types/react@18.2.48)(react@18.2.0):
+  /react-textarea-autosize@8.5.3(@types/react@18.2.57)(react@18.2.0):
     resolution: {integrity: sha512-XT1024o2pqCuZSuBt9FwHlaDeNtVrtCXu0Rnz88t1jUGheCLa3PhjE1GH8Ctm2axEtvdCl5SUHYschyQ0L5QHQ==}
     engines: {node: '>=10'}
     peerDependencies:
       react: ^16.8.0 || ^17.0.0 || ^18.0.0
     dependencies:
-      '@babel/runtime': 7.23.6
+      '@babel/runtime': 7.23.9
       react: 18.2.0
       use-composed-ref: 1.3.0(react@18.2.0)
-      use-latest: 1.2.1(@types/react@18.2.48)(react@18.2.0)
+      use-latest: 1.2.1(@types/react@18.2.57)(react@18.2.0)
     transitivePeerDependencies:
       - '@types/react'
     dev: false
@@ -12355,7 +12532,7 @@ packages:
       react: '>=16.6.0'
       react-dom: '>=16.6.0'
     dependencies:
-      '@babel/runtime': 7.23.7
+      '@babel/runtime': 7.23.9
       dom-helpers: 5.2.1
       loose-envify: 1.4.0
       prop-types: 15.8.1
@@ -12373,8 +12550,8 @@ packages:
       tslib: 2.6.2
     dev: false
 
-  /react-use@17.4.3(react-dom@18.2.0)(react@18.2.0):
-    resolution: {integrity: sha512-05Oyuwn4ZccdzLD4ttLbMe8TkobdKpOj7YCFE9VhVpbXrTWZpvCcMyroRw/Banh1RIcQRcM06tfzPpY5D9sTsQ==}
+  /react-use@17.5.0(react-dom@18.2.0)(react@18.2.0):
+    resolution: {integrity: sha512-PbfwSPMwp/hoL847rLnm/qkjg3sTRCvn6YhUZiHaUa3FA6/aNoFX79ul5Xt70O1rK+9GxSVqkY0eTwMdsR/bWg==}
     peerDependencies:
       react: '*'
       react-dom: '*'
@@ -12397,8 +12574,8 @@ packages:
       tslib: 2.6.2
     dev: false
 
-  /react-virtuoso@4.6.2(react-dom@18.2.0)(react@18.2.0):
-    resolution: {integrity: sha512-vvlqvzPif+MvBrJ09+hJJrVY0xJK9yran+A+/1iwY78k0YCVKsyoNPqoLxOxzYPggspNBNXqUXEcvckN29OxyQ==}
+  /react-virtuoso@4.7.0(react-dom@18.2.0)(react@18.2.0):
+    resolution: {integrity: sha512-cpgvI1rSOETGDMhqVAVDuH+XHbWO1uIGKv5I6l4CyC71xWYUeGrE5n7sgTZklROB4+Vbv85pcgfWloTlY48HGQ==}
     engines: {node: '>=10'}
     peerDependencies:
       react: '>=16 || >=17 || >= 18'
@@ -12414,18 +12591,18 @@ packages:
     dependencies:
       loose-envify: 1.4.0
 
-  /reactflow@11.10.2(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0):
-    resolution: {integrity: sha512-tqQJfPEiIkXonT3piVYf+F9CvABI5e28t5I6rpaLTnO8YVCAOh1h0f+ziDKz0Bx9Y2B/mFgyz+H7LZeUp/+lhQ==}
+  /reactflow@11.10.4(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+    resolution: {integrity: sha512-0CApYhtYicXEDg/x2kvUHiUk26Qur8lAtTtiSlptNKuyEuGti6P1y5cS32YGaUoDMoCqkm/m+jcKkfMOvSCVRA==}
     peerDependencies:
       react: '>=17'
       react-dom: '>=17'
     dependencies:
-      '@reactflow/background': 11.3.7(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@reactflow/controls': 11.2.7(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@reactflow/core': 11.10.2(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@reactflow/minimap': 11.7.7(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@reactflow/node-resizer': 2.2.7(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
-      '@reactflow/node-toolbar': 1.3.7(@types/react@18.2.48)(react-dom@18.2.0)(react@18.2.0)
+      '@reactflow/background': 11.3.9(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@reactflow/controls': 11.2.9(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@reactflow/core': 11.10.4(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@reactflow/minimap': 11.7.9(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@reactflow/node-resizer': 2.2.9(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@reactflow/node-toolbar': 1.3.9(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     transitivePeerDependencies:
@@ -12523,14 +12700,15 @@ packages:
     resolution: {integrity: sha512-M9/ELqF6fy8FwmkpnF0S3YKOqMyoWJ4+CS5Efg2ct3oY9daQvd/Pc71FpGZsVsbl3Cpb+IIcjBDUnnyBdQbq4w==}
     dev: false
 
-  /reflect.getprototypeof@1.0.4:
-    resolution: {integrity: sha512-ECkTw8TmJwW60lOTR+ZkODISW6RQ8+2CL3COqtiJKLd6MmB45hN51HprHFziKLGkAuTGQhBb91V8cy+KHlaCjw==}
+  /reflect.getprototypeof@1.0.5:
+    resolution: {integrity: sha512-62wgfC8dJWrmxv44CA36pLDnP6KKl3Vhxb7PL+8+qrrFMMoJij4vgiMP8zV4O8+CBMXY1mHxI5fITGHXFHVmQQ==}
     engines: {node: '>= 0.4'}
     dependencies:
-      call-bind: 1.0.5
+      call-bind: 1.0.7
       define-properties: 1.2.1
-      es-abstract: 1.22.3
-      get-intrinsic: 1.2.2
+      es-abstract: 1.22.4
+      es-errors: 1.3.0
+      get-intrinsic: 1.2.4
       globalthis: 1.0.3
       which-builtin-type: 1.1.3
     dev: true
@@ -12552,16 +12730,17 @@ packages:
   /regenerator-transform@0.15.2:
     resolution: {integrity: sha512-hfMp2BoF0qOk3uc5V20ALGDS2ddjQaLrdl7xrGXvAIow7qeWRM2VA2HuCHkUKk9slq3VwEwLNK3DFBqDfPGYtg==}
     dependencies:
-      '@babel/runtime': 7.23.8
+      '@babel/runtime': 7.23.9
     dev: true
 
-  /regexp.prototype.flags@1.5.1:
-    resolution: {integrity: sha512-sy6TXMN+hnP/wMy+ISxg3krXx7BAtWVO4UouuCN/ziM9UEne0euamVNafDfvC83bRNr95y0V5iijeDQFUNpvrg==}
+  /regexp.prototype.flags@1.5.2:
+    resolution: {integrity: sha512-NcDiDkTLuPR+++OCKB0nWafEmhg/Da8aUPLPMQbK+bxKKCm1/S5he+AqYa4PlMCVBalb4/yxIRub6qkEx5yJbw==}
     engines: {node: '>= 0.4'}
     dependencies:
-      call-bind: 1.0.5
+      call-bind: 1.0.7
       define-properties: 1.2.1
-      set-function-name: 2.0.1
+      es-errors: 1.3.0
+      set-function-name: 2.0.2
     dev: true
 
   /regexpu-core@5.3.2:
@@ -12630,10 +12809,9 @@ packages:
     hasBin: true
     dev: true
 
-  /reselect@5.0.1(patch_hash=kvbgwzjyy4x4fnh7znyocvb75q):
-    resolution: {integrity: sha512-D72j2ubjgHpvuCiORWkOUxndHJrxDaSolheiz5CO+roz8ka97/4msh2E8F5qay4GawR5vzBt5MkbDHT+Rdy/Wg==}
+  /reselect@5.1.0:
+    resolution: {integrity: sha512-aw7jcGLDpSgNDyWBQLv2cedml85qd95/iszJjN988zX1t7AVRJi19d9kto5+W7oCfQ94gyo40dVbT6g2k4/kXg==}
     dev: false
-    patched: true
 
   /resize-observer-polyfill@1.5.1:
     resolution: {integrity: sha512-LwZrotdHOo12nQuZlHEmtuXdqGoOD0OhaxopaNFxWzInpEgaLWoVuAMbTzixuosCx2nEG58ngzW3vxdWoxIgdg==}
@@ -12757,33 +12935,33 @@ packages:
       fsevents: 2.3.3
     dev: true
 
-  /rollup@4.9.4:
-    resolution: {integrity: sha512-2ztU7pY/lrQyXSCnnoU4ICjT/tCG9cdH3/G25ERqE3Lst6vl2BCM5hL2Nw+sslAvAf+ccKsAq1SkKQALyqhR7g==}
+  /rollup@4.12.0:
+    resolution: {integrity: sha512-wz66wn4t1OHIJw3+XU7mJJQV/2NAfw5OAk6G6Hoo3zcvz/XOfQ52Vgi+AN4Uxoxi0KBBwk2g8zPrTDA4btSB/Q==}
     engines: {node: '>=18.0.0', npm: '>=8.0.0'}
     hasBin: true
     dependencies:
       '@types/estree': 1.0.5
     optionalDependencies:
-      '@rollup/rollup-android-arm-eabi': 4.9.4
-      '@rollup/rollup-android-arm64': 4.9.4
-      '@rollup/rollup-darwin-arm64': 4.9.4
-      '@rollup/rollup-darwin-x64': 4.9.4
-      '@rollup/rollup-linux-arm-gnueabihf': 4.9.4
-      '@rollup/rollup-linux-arm64-gnu': 4.9.4
-      '@rollup/rollup-linux-arm64-musl': 4.9.4
-      '@rollup/rollup-linux-riscv64-gnu': 4.9.4
-      '@rollup/rollup-linux-x64-gnu': 4.9.4
-      '@rollup/rollup-linux-x64-musl': 4.9.4
-      '@rollup/rollup-win32-arm64-msvc': 4.9.4
-      '@rollup/rollup-win32-ia32-msvc': 4.9.4
-      '@rollup/rollup-win32-x64-msvc': 4.9.4
+      '@rollup/rollup-android-arm-eabi': 4.12.0
+      '@rollup/rollup-android-arm64': 4.12.0
+      '@rollup/rollup-darwin-arm64': 4.12.0
+      '@rollup/rollup-darwin-x64': 4.12.0
+      '@rollup/rollup-linux-arm-gnueabihf': 4.12.0
+      '@rollup/rollup-linux-arm64-gnu': 4.12.0
+      '@rollup/rollup-linux-arm64-musl': 4.12.0
+      '@rollup/rollup-linux-riscv64-gnu': 4.12.0
+      '@rollup/rollup-linux-x64-gnu': 4.12.0
+      '@rollup/rollup-linux-x64-musl': 4.12.0
+      '@rollup/rollup-win32-arm64-msvc': 4.12.0
+      '@rollup/rollup-win32-ia32-msvc': 4.12.0
+      '@rollup/rollup-win32-x64-msvc': 4.12.0
       fsevents: 2.3.3
     dev: true
 
   /rtl-css-js@1.16.1:
     resolution: {integrity: sha512-lRQgou1mu19e+Ya0LsTvKrVJ5TYUbqCVPAiImX3UfLTenarvPUl1QFdvu5Z3PYmHT9RCcwIfbjRQBntExyj3Zg==}
     dependencies:
-      '@babel/runtime': 7.23.8
+      '@babel/runtime': 7.23.9
     dev: false
 
   /run-parallel@1.2.0:
@@ -12798,12 +12976,12 @@ packages:
       tslib: 2.6.2
     dev: true
 
-  /safe-array-concat@1.0.1:
-    resolution: {integrity: sha512-6XbUAseYE2KtOuGueyeobCySj9L4+66Tn6KQMOPQJrAJEowYKW/YR/MGJZl7FdydUdaFu4LYyDZjxf4/Nmo23Q==}
+  /safe-array-concat@1.1.0:
+    resolution: {integrity: sha512-ZdQ0Jeb9Ofti4hbt5lX3T2JcAamT9hfzYU1MNB+z/jaEbB6wfFfPIR/zEORmZqobkCCJhSjodobH6WHNmJ97dg==}
     engines: {node: '>=0.4'}
     dependencies:
-      call-bind: 1.0.5
-      get-intrinsic: 1.2.2
+      call-bind: 1.0.7
+      get-intrinsic: 1.2.4
       has-symbols: 1.0.3
       isarray: 2.0.5
     dev: true
@@ -12816,11 +12994,12 @@ packages:
     resolution: {integrity: sha512-rp3So07KcdmmKbGvgaNxQSJr7bGVSVk5S9Eq1F+ppbRo70+YeaDxkw5Dd8NPN+GD6bjnYm2VuPuCXmpuYvmCXQ==}
     dev: true
 
-  /safe-regex-test@1.0.0:
-    resolution: {integrity: sha512-JBUUzyOgEwXQY1NuPtvcj/qcBDbDmEvWufhlnXZIm75DEHp+afM1r1ujJpJsV/gSM4t59tpDyPi1sd6ZaPFfsA==}
+  /safe-regex-test@1.0.3:
+    resolution: {integrity: sha512-CdASjNJPvRa7roO6Ra/gLYBTzYzzPyyBXxIMdGW3USQLyjWEls2RgW5UBTXaQVp+OrpeCK3bLem8smtmheoRuw==}
+    engines: {node: '>= 0.4'}
     dependencies:
-      call-bind: 1.0.5
-      get-intrinsic: 1.2.2
+      call-bind: 1.0.7
+      es-errors: 1.3.0
       is-regex: 1.1.4
     dev: true
 
@@ -12873,6 +13052,14 @@ packages:
       lru-cache: 6.0.0
     dev: true
 
+  /semver@7.6.0:
+    resolution: {integrity: sha512-EnwXhrlwXMk9gKu5/flx5sv/an57AkRplG3hTK68W7FRDN+k+OWBj65M7719OkA82XLBxrcX0KSHj+X5COhOVg==}
+    engines: {node: '>=10'}
+    hasBin: true
+    dependencies:
+      lru-cache: 6.0.0
+    dev: true
+
   /send@0.18.0:
     resolution: {integrity: sha512-qqWzuOjSFOuqPjFe4NOsMLafToQQwBSOEpS+FwEt3A2V3vKubTquT3vmLTQpFgMXp8AlFWFuP1qKaJZOtPpVXg==}
     engines: {node: '>= 0.8.0'}
@@ -12913,23 +13100,26 @@ packages:
       - supports-color
     dev: true
 
-  /set-function-length@1.1.1:
-    resolution: {integrity: sha512-VoaqjbBJKiWtg4yRcKBQ7g7wnGnLV3M8oLvVWwOk2PdYY6PEFegR1vezXR0tw6fZGF9csVakIRjrJiy2veSBFQ==}
+  /set-function-length@1.2.1:
+    resolution: {integrity: sha512-j4t6ccc+VsKwYHso+kElc5neZpjtq9EnRICFZtWyBsLojhmeF/ZBd/elqm22WJh/BziDe/SBiOeAt0m2mfLD0g==}
     engines: {node: '>= 0.4'}
     dependencies:
-      define-data-property: 1.1.1
-      get-intrinsic: 1.2.2
+      define-data-property: 1.1.4
+      es-errors: 1.3.0
+      function-bind: 1.1.2
+      get-intrinsic: 1.2.4
       gopd: 1.0.1
-      has-property-descriptors: 1.0.1
+      has-property-descriptors: 1.0.2
     dev: true
 
-  /set-function-name@2.0.1:
-    resolution: {integrity: sha512-tMNCiqYVkXIZgc2Hnoy2IvC/f8ezc5koaRFkCjrpWzGpCd3qbZXPzVy9MAZzK1ch/X0jvSkojys3oqJN0qCmdA==}
+  /set-function-name@2.0.2:
+    resolution: {integrity: sha512-7PGFlmtwsEADb0WYyvCMa1t+yke6daIG4Wirafur5kcf+MhUnPms1UeR0CKQdTZD81yESwMHbtn+TR+dMviakQ==}
     engines: {node: '>= 0.4'}
     dependencies:
-      define-data-property: 1.1.1
+      define-data-property: 1.1.4
+      es-errors: 1.3.0
       functions-have-names: 1.2.3
-      has-property-descriptors: 1.0.1
+      has-property-descriptors: 1.0.2
     dev: true
 
   /set-harmonic-interval@1.0.1:
@@ -12964,11 +13154,13 @@ packages:
     resolution: {integrity: sha512-6j1W9l1iAs/4xYBI1SYOVZyFcCis9b4KCLQ8fgAGG07QvzaRLVVRQvAy85yNmmZSjYjg4MWh4gNvlPujU/5LpA==}
     dev: true
 
-  /side-channel@1.0.4:
-    resolution: {integrity: sha512-q5XPytqFEIKHkGdiMIrY10mvLRvnQh42/+GoBlFW3b2LXLE2xxJpZFdm94we0BaoV3RwJyGqg5wS7epxTv0Zvw==}
+  /side-channel@1.0.5:
+    resolution: {integrity: sha512-QcgiIWV4WV7qWExbN5llt6frQB/lBven9pqliLXfGPB+K9ZYXxDozp0wLkHS24kWCm+6YXH/f0HhnObZnZOBnQ==}
+    engines: {node: '>= 0.4'}
     dependencies:
-      call-bind: 1.0.5
-      get-intrinsic: 1.2.2
+      call-bind: 1.0.7
+      es-errors: 1.3.0
+      get-intrinsic: 1.2.4
       object-inspect: 1.13.1
     dev: true
 
@@ -13061,22 +13253,22 @@ packages:
     resolution: {integrity: sha512-kN9dJbvnySHULIluDHy32WHRUu3Og7B9sbY7tsFLctQkIqnMh3hErYgdMjTYuqmcXX+lK5T1lnUt3G7zNswmZA==}
     dependencies:
       spdx-expression-parse: 3.0.1
-      spdx-license-ids: 3.0.16
+      spdx-license-ids: 3.0.17
     dev: true
 
-  /spdx-exceptions@2.3.0:
-    resolution: {integrity: sha512-/tTrYOC7PPI1nUAgx34hUpqXuyJG+DTHJTnIULG4rDygi4xu/tfgmq1e1cIRwRzwZgo4NLySi+ricLkZkw4i5A==}
+  /spdx-exceptions@2.5.0:
+    resolution: {integrity: sha512-PiU42r+xO4UbUS1buo3LPJkjlO7430Xn5SVAhdpzzsPHsjbYVflnnFdATgabnLude+Cqu25p6N+g2lw/PFsa4w==}
     dev: true
 
   /spdx-expression-parse@3.0.1:
     resolution: {integrity: sha512-cbqHunsQWnJNE6KhVSMsMeH5H/L9EpymbzqTQ3uLwNCLZ1Q481oWaofqH7nO6V07xlXwY6PhQdQ2IedWx/ZK4Q==}
     dependencies:
-      spdx-exceptions: 2.3.0
-      spdx-license-ids: 3.0.16
+      spdx-exceptions: 2.5.0
+      spdx-license-ids: 3.0.17
     dev: true
 
-  /spdx-license-ids@3.0.16:
-    resolution: {integrity: sha512-eWN+LnM3GR6gPu35WxNgbGl8rmY1AEmoMDvL/QD6zYmPWgywxWqJWNdLGT+ke8dKNWrcYgYjPpG5gbTfghP8rw==}
+  /spdx-license-ids@3.0.17:
+    resolution: {integrity: sha512-sh8PWc/ftMqAAdFiBu6Fy6JUOYjqDJBJvIhpfDMyHrr0Rbp5liZqd4TjtQ/RgfLjKFZb+LMx5hpml5qOWy0qvg==}
     dev: true
 
   /split-on-first@3.0.0:
@@ -13130,18 +13322,18 @@ packages:
     resolution: {integrity: sha512-iCGQj+0l0HOdZ2AEeBADlsRC+vsnDsZsbdSiH1yNSjcfKM7fdpCMfqAL/dwF5BLiw/XhRft/Wax6zQbhq2BcjQ==}
     engines: {node: '>= 0.4'}
     dependencies:
-      internal-slot: 1.0.6
+      internal-slot: 1.0.7
     dev: true
 
-  /store2@2.14.2:
-    resolution: {integrity: sha512-siT1RiqlfQnGqgT/YzXVUNsom9S0H1OX+dpdGN1xkyYATo4I6sep5NmsRD/40s3IIOvlCq6akxkqG82urIZW1w==}
+  /store2@2.14.3:
+    resolution: {integrity: sha512-4QcZ+yx7nzEFiV4BMLnr/pRa5HYzNITX2ri0Zh6sT9EyQHbBHacC6YigllUPU9X3D0f/22QCgfokpKs52YRrUg==}
     dev: true
 
-  /storybook@7.6.10:
-    resolution: {integrity: sha512-ypFeGhQTUBBfqSUVZYh7wS5ghn3O2wILCiQc4459SeUpvUn+skcqw/TlrwGSoF5EWjDA7gtRrWDxO3mnlPt5Cw==}
+  /storybook@7.6.17:
+    resolution: {integrity: sha512-8+EIo91bwmeFWPg1eysrxXlhIYv3OsXrznTr4+4Eq0NikqAoq6oBhtlN5K2RGS2lBVF537eN+9jTCNbR+WrzDA==}
     hasBin: true
     dependencies:
-      '@storybook/cli': 7.6.10
+      '@storybook/cli': 7.6.17
     transitivePeerDependencies:
       - bufferutil
       - encoding
@@ -13185,40 +13377,40 @@ packages:
   /string.prototype.matchall@4.0.10:
     resolution: {integrity: sha512-rGXbGmOEosIQi6Qva94HUjgPs9vKW+dkG7Y8Q5O2OYkWL6wFaTRZO8zM4mhP94uX55wgyrXzfS2aGtGzUL7EJQ==}
     dependencies:
-      call-bind: 1.0.5
+      call-bind: 1.0.7
       define-properties: 1.2.1
-      es-abstract: 1.22.3
-      get-intrinsic: 1.2.2
+      es-abstract: 1.22.4
+      get-intrinsic: 1.2.4
       has-symbols: 1.0.3
-      internal-slot: 1.0.6
-      regexp.prototype.flags: 1.5.1
-      set-function-name: 2.0.1
-      side-channel: 1.0.4
+      internal-slot: 1.0.7
+      regexp.prototype.flags: 1.5.2
+      set-function-name: 2.0.2
+      side-channel: 1.0.5
     dev: true
 
   /string.prototype.trim@1.2.8:
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     engines: {node: '>= 0.4'}
     dependencies:
-      call-bind: 1.0.5
+      call-bind: 1.0.7
       define-properties: 1.2.1
-      es-abstract: 1.22.3
+      es-abstract: 1.22.4
     dev: true
 
   /string.prototype.trimend@1.0.7:
     resolution: {integrity: sha512-Ni79DqeB72ZFq1uH/L6zJ+DKZTkOtPIHovb3YZHQViE+HDouuU4mBrLOLDn5Dde3RF8qw5qVETEjhu9locMLvA==}
     dependencies:
-      call-bind: 1.0.5
+      call-bind: 1.0.7
       define-properties: 1.2.1
-      es-abstract: 1.22.3
+      es-abstract: 1.22.4
     dev: true
 
   /string.prototype.trimstart@1.0.7:
     resolution: {integrity: sha512-NGhtDFu3jCEm7B4Fy0DpLewdJQOZcQ0rGbwQ/+stjnrp2i+rlKeCvos9hOIeCmqwratM47OBxY7uFZzjxHXmrg==}
     dependencies:
-      call-bind: 1.0.5
+      call-bind: 1.0.7
       define-properties: 1.2.1
-      es-abstract: 1.22.3
+      es-abstract: 1.22.4
     dev: true
 
   /string_decoder@1.1.1:
@@ -13295,10 +13487,10 @@ packages:
     engines: {node: '>=8'}
     dev: true
 
-  /strip-literal@1.3.0:
-    resolution: {integrity: sha512-PugKzOsyXpArk0yWmUwqOZecSO0GH0bPoctLcqNDH9J04pVW3lflYE0ujElBGTloevcxF5MofAOZ7C5l2b+wLg==}
+  /strip-literal@2.0.0:
+    resolution: {integrity: sha512-f9vHgsCWBq2ugHAkGMiiYY+AYG0D/cbloKKg0nhaaaSNsujdGIpVXCNsrJpCKr5M0f4aI31mr13UjY6GAuXCKA==}
     dependencies:
-      acorn: 8.11.3
+      js-tokens: 8.0.3
     dev: true
 
   /stylis@4.2.0:
@@ -13460,8 +13652,8 @@ packages:
     engines: {node: '>=14.0.0'}
     dev: true
 
-  /tinyspy@2.2.0:
-    resolution: {integrity: sha512-d2eda04AN/cPOR89F7Xv5bK/jrQEhmcLFe6HFldoeO9AJtps+fqEnh486vnT/8y4bw38pSyxDcTCAq+Ks2aJTg==}
+  /tinyspy@2.2.1:
+    resolution: {integrity: sha512-KYad6Vy5VDWV4GH3fjpseMQ/XU2BhIYP7Vzd0LG44qRWm/Yt2WCOTicFdvmgo6gWaqooMQCawTtILVQJupKu7A==}
     engines: {node: '>=14.0.0'}
     dev: true
 
@@ -13501,9 +13693,9 @@ packages:
     hasBin: true
     dev: true
 
-  /ts-api-utils@1.0.3(typescript@5.3.3):
-    resolution: {integrity: sha512-wNMeqtMz5NtwpT/UZGY5alT+VoKdSsOOP/kqHFcUW1P/VRhH2wJ48+DN2WwUliNbQ976ETwDL0Ifd2VVvgonvg==}
-    engines: {node: '>=16.13.0'}
+  /ts-api-utils@1.2.1(typescript@5.3.3):
+    resolution: {integrity: sha512-RIYA36cJn2WiH9Hy77hdF9r7oEwxAtB/TS9/S4Qd90Ap4z5FSiin5zEiTL44OII1Y3IIlEvxwxFUVgrHSZ/UpA==}
+    engines: {node: '>=16'}
     peerDependencies:
       typescript: '>=4.2.0'
     dependencies:
@@ -13523,8 +13715,8 @@ packages:
     resolution: {integrity: sha512-tLJxacIQUM82IR7JO1UUkKlYuUTmoY9HBJAmNWFzheSlDS5SPMcNIepejHJa4BpPQLAcbRhRf3GDJzyj6rbKvA==}
     dev: false
 
-  /ts-graphviz@1.8.1:
-    resolution: {integrity: sha512-54/fe5iu0Jb6X0pmDmzsA2UHLfyHjUEUwfHtZcEOR0fZ6Myf+dFoO6eNsyL8CBDMJ9u7WWEewduVaiaXlvjSVw==}
+  /ts-graphviz@1.8.2:
+    resolution: {integrity: sha512-5YhbFoHmjxa7pgQLkB07MtGnGJ/yhvjmc9uhsnDBEICME6gkPf83SBwLDQqGDoCa3XzUMWLk1AU2Wn1u1naDtA==}
     engines: {node: '>=14.16'}
     dev: true
 
@@ -13536,8 +13728,8 @@ packages:
     resolution: {integrity: sha512-gzkapsdbMNwBnTIjgO758GujLCj031IgHK/PKr2mrmkCSJMhSOR5FeOuSxKLMUoYc0vAA4RGEYYbjt/v6afD3g==}
     dev: true
 
-  /tsconfck@3.0.1(typescript@5.3.3):
-    resolution: {integrity: sha512-7ppiBlF3UEddCLeI1JRx5m2Ryq+xk4JrZuq4EuYXykipebaq1dV0Fhgr1hb7CkmHt32QSgOZlcqVLEtHBG4/mg==}
+  /tsconfck@3.0.2(typescript@5.3.3):
+    resolution: {integrity: sha512-6lWtFjwuhS3XI4HsX4Zg0izOI3FU/AI9EGVlPEUMDIhvLPMD4wkiof0WCoDgW7qY+Dy198g4d9miAqUHWHFH6Q==}
     engines: {node: ^18 || >=20}
     hasBin: true
     peerDependencies:
@@ -13635,8 +13827,8 @@ packages:
     resolution: {integrity: sha512-RAH822pAdBgcNMAfWnCBU3CFZcfZ/i1eZjwFU/dsLKumyuuP3niueg2UAukXYF0E2AAoc82ZSSf9J0WQBinzHA==}
     engines: {node: '>=12.20'}
 
-  /type-fest@4.9.0:
-    resolution: {integrity: sha512-KS/6lh/ynPGiHD/LnAobrEFq3Ad4pBzOlJ1wAnJx9N4EYoqFhMfLIBjUT2UEx4wg5ZE+cC1ob6DCSpppVo+rtg==}
+  /type-fest@4.10.2:
+    resolution: {integrity: sha512-anpAG63wSpdEbLwOqH8L84urkL6PiVIov3EMmgIhhThevh9aiMQov+6Btx0wldNcvm4wV+e2/Rt1QdDwKHFbHw==}
     engines: {node: '>=16'}
     dev: false
 
@@ -13648,42 +13840,47 @@ packages:
       mime-types: 2.1.35
     dev: true
 
-  /typed-array-buffer@1.0.0:
-    resolution: {integrity: sha512-Y8KTSIglk9OZEr8zywiIHG/kmQ7KWyjseXs1CbSo8vC42w7hg2HgYTxSWwP0+is7bWDc1H+Fo026CpHFwm8tkw==}
+  /typed-array-buffer@1.0.2:
+    resolution: {integrity: sha512-gEymJYKZtKXzzBzM4jqa9w6Q1Jjm7x2d+sh19AdsD4wqnMPDYyvwpsIc2Q/835kHuo3BEQ7CjelGhfTsoBb2MQ==}
     engines: {node: '>= 0.4'}
     dependencies:
-      call-bind: 1.0.5
-      get-intrinsic: 1.2.2
-      is-typed-array: 1.1.12
+      call-bind: 1.0.7
+      es-errors: 1.3.0
+      is-typed-array: 1.1.13
     dev: true
 
   /typed-array-byte-length@1.0.0:
     resolution: {integrity: sha512-Or/+kvLxNpeQ9DtSydonMxCx+9ZXOswtwJn17SNLvhptaXYDJvkFFP5zbfU/uLmvnBJlI4yrnXRxpdWH/M5tNA==}
     engines: {node: '>= 0.4'}
     dependencies:
-      call-bind: 1.0.5
+      call-bind: 1.0.7
       for-each: 0.3.3
-      has-proto: 1.0.1
-      is-typed-array: 1.1.12
+      has-proto: 1.0.3
+      is-typed-array: 1.1.13
     dev: true
 
-  /typed-array-byte-offset@1.0.0:
-    resolution: {integrity: sha512-RD97prjEt9EL8YgAgpOkf3O4IF9lhJFr9g0htQkm0rchFp/Vx7LW5Q8fSXXub7BXAODyUQohRMyOc3faCPd0hg==}
+  /typed-array-byte-offset@1.0.2:
+    resolution: {integrity: sha512-Ous0vodHa56FviZucS2E63zkgtgrACj7omjwd/8lTEMEPFFyjfixMZ1ZXenpgCFBBt4EC1J2XsyVS2gkG0eTFA==}
     engines: {node: '>= 0.4'}
     dependencies:
-      available-typed-arrays: 1.0.5
-      call-bind: 1.0.5
+      available-typed-arrays: 1.0.7
+      call-bind: 1.0.7
       for-each: 0.3.3
-      has-proto: 1.0.1
-      is-typed-array: 1.1.12
+      gopd: 1.0.1
+      has-proto: 1.0.3
+      is-typed-array: 1.1.13
     dev: true
 
-  /typed-array-length@1.0.4:
-    resolution: {integrity: sha512-KjZypGq+I/H7HI5HlOoGHkWUUGq+Q0TPhQurLbyrVrvnKTBgzLhIJ7j6J/XTQOi0d1RjyZ0wdas8bKs2p0x3Ng==}
+  /typed-array-length@1.0.5:
+    resolution: {integrity: sha512-yMi0PlwuznKHxKmcpoOdeLwxBoVPkqZxd7q2FgMkmD3bNwvF5VW0+UlUQ1k1vmktTu4Yu13Q0RIxEP8+B+wloA==}
+    engines: {node: '>= 0.4'}
     dependencies:
-      call-bind: 1.0.5
+      call-bind: 1.0.7
       for-each: 0.3.3
-      is-typed-array: 1.1.12
+      gopd: 1.0.1
+      has-proto: 1.0.3
+      is-typed-array: 1.1.13
+      possible-typed-array-names: 1.0.0
     dev: true
 
   /typedarray@0.0.6:
@@ -13708,8 +13905,8 @@ packages:
     hasBin: true
     dev: true
 
-  /ufo@1.3.2:
-    resolution: {integrity: sha512-o+ORpgGwaYQXgqGDwd+hkS4PuZ3QnmqMMxRuajK/a38L6fTpcE5GPIfrf+L/KemFzfUpeUQc1rRS1iDBozvnFA==}
+  /ufo@1.4.0:
+    resolution: {integrity: sha512-Hhy+BhRBleFjpJ2vchUNN40qgkh0366FWJGqVLYBHev0vpHTrXSA0ryT+74UiW6KWsldNurQMKGqCm1M2zBciQ==}
     dev: true
 
   /uglify-js@3.17.4:
@@ -13723,7 +13920,7 @@ packages:
   /unbox-primitive@1.0.2:
     resolution: {integrity: sha512-61pPlCD9h51VoreyJ0BReideM3MDKMKnh6+V9L08331ipq6Q8OFXZYiqP6n/tbHx4s5I9uRhcye6BrbkizkBDw==}
     dependencies:
-      call-bind: 1.0.5
+      call-bind: 1.0.7
       has-bigints: 1.0.2
       has-symbols: 1.0.3
       which-boxed-primitive: 1.0.2
@@ -13733,8 +13930,8 @@ packages:
     resolution: {integrity: sha512-JlCMO+ehdEIKqlFxk6IfVoAUVmgz7cU7zD/h9XZ0qzeosSHmUJVOzSQvvYSYWXkFXC+IfLKSIffhv0sVZup6pA==}
     dev: true
 
-  /undici@5.28.2:
-    resolution: {integrity: sha512-wh1pHJHnUeQV5Xa8/kyQhO7WFa8M34l026L5P/+2TYiakvGy5Rdc8jWZVyG7ieht/0WgJLEd3kcU5gKx+6GC8w==}
+  /undici@5.28.3:
+    resolution: {integrity: sha512-3ItfzbrhDlINjaP0duwnNsKpDQk3acHI3gVJ1z4fmwMK31k5G9OVIAMLSIaP6w4FaGkaAkN6zaQO9LUvZ1t7VA==}
     engines: {node: '>=14.0'}
     dependencies:
       '@fastify/busboy': 2.1.0
@@ -13808,11 +14005,11 @@ packages:
     engines: {node: '>= 0.8'}
     dev: true
 
-  /unplugin@1.6.0:
-    resolution: {integrity: sha512-BfJEpWBu3aE/AyHx8VaNE/WgouoQxgH9baAiH82JjX8cqVyi3uJQstqwD5J+SZxIK326SZIhsSZlALXVBCknTQ==}
+  /unplugin@1.7.1:
+    resolution: {integrity: sha512-JqzORDAPxxs8ErLV4x+LL7bk5pk3YlcWqpSNsIkAZj972KzFZLClc/ekppahKkOczGkwIG6ElFgdOgOlK4tXZw==}
     dependencies:
       acorn: 8.11.3
-      chokidar: 3.5.3
+      chokidar: 3.6.0
       webpack-sources: 3.2.3
       webpack-virtual-modules: 0.6.1
     dev: true
@@ -13822,14 +14019,14 @@ packages:
     engines: {node: '>=8'}
     dev: true
 
-  /update-browserslist-db@1.0.13(browserslist@4.22.2):
+  /update-browserslist-db@1.0.13(browserslist@4.23.0):
     resolution: {integrity: sha512-xebP81SNcPuNpPP3uzeW1NYXxI3rxyJzF3pD6sH4jE7o/IX+WtSpwnVU+qIsDPyk0d3hmFQ7mjqc6AtV604hbg==}
     hasBin: true
     peerDependencies:
       browserslist: '>= 4.21.0'
     dependencies:
-      browserslist: 4.22.2
-      escalade: 3.1.1
+      browserslist: 4.23.0
+      escalade: 3.1.2
       picocolors: 1.0.0
     dev: true
 
@@ -13839,7 +14036,7 @@ packages:
       punycode: 2.3.1
     dev: true
 
-  /use-callback-ref@1.3.1(@types/react@18.2.48)(react@18.2.0):
+  /use-callback-ref@1.3.1(@types/react@18.2.57)(react@18.2.0):
     resolution: {integrity: sha512-Lg4Vx1XZQauB42Hw3kK7JM6yjVjgFmFC5/Ab797s79aARomD2nEErc4mCgM8EZrARLmmbWpi5DGCadmK50DcAQ==}
     engines: {node: '>=10'}
     peerDependencies:
@@ -13849,7 +14046,7 @@ packages:
       '@types/react':
         optional: true
     dependencies:
-      '@types/react': 18.2.48
+      '@types/react': 18.2.57
       react: 18.2.0
       tslib: 2.6.2
 
@@ -13880,7 +14077,7 @@ packages:
       react-dom: 18.2.0(react@18.2.0)
     dev: false
 
-  /use-isomorphic-layout-effect@1.1.2(@types/react@18.2.48)(react@18.2.0):
+  /use-isomorphic-layout-effect@1.1.2(@types/react@18.2.57)(react@18.2.0):
     resolution: {integrity: sha512-49L8yCO3iGT/ZF9QttjwLF/ZD9Iwto5LnH5LmEdk/6cFmXddqi2ulF0edxTwjj+7mqvpVVGQWvbXZdn32wRSHA==}
     peerDependencies:
       '@types/react': '*'
@@ -13889,11 +14086,11 @@ packages:
       '@types/react':
         optional: true
     dependencies:
-      '@types/react': 18.2.48
+      '@types/react': 18.2.57
       react: 18.2.0
     dev: false
 
-  /use-latest@1.2.1(@types/react@18.2.48)(react@18.2.0):
+  /use-latest@1.2.1(@types/react@18.2.57)(react@18.2.0):
     resolution: {integrity: sha512-xA+AVm/Wlg3e2P/JiItTziwS7FK92LWrDB0p+hgXloIMuVCeJJ8v6f0eeHyPZaJrM+usM1FkFfbNCrJGs8A/zw==}
     peerDependencies:
       '@types/react': '*'
@@ -13902,9 +14099,9 @@ packages:
       '@types/react':
         optional: true
     dependencies:
-      '@types/react': 18.2.48
+      '@types/react': 18.2.57
       react: 18.2.0
-      use-isomorphic-layout-effect: 1.1.2(@types/react@18.2.48)(react@18.2.0)
+      use-isomorphic-layout-effect: 1.1.2(@types/react@18.2.57)(react@18.2.0)
     dev: false
 
   /use-resize-observer@9.1.0(react-dom@18.2.0)(react@18.2.0):
@@ -13918,7 +14115,7 @@ packages:
       react-dom: 18.2.0(react@18.2.0)
     dev: true
 
-  /use-sidecar@1.1.2(@types/react@18.2.48)(react@18.2.0):
+  /use-sidecar@1.1.2(@types/react@18.2.57)(react@18.2.0):
     resolution: {integrity: sha512-epTbsLuzZ7lPClpz2TyryBfztm7m+28DlEv2ZCQ3MDr5ssiwyOwGH/e5F9CkfWjJ1t4clvI58yF822/GUkjjhw==}
     engines: {node: '>=10'}
     peerDependencies:
@@ -13928,7 +14125,7 @@ packages:
       '@types/react':
         optional: true
     dependencies:
-      '@types/react': 18.2.48
+      '@types/react': 18.2.57
       detect-node-es: 1.1.0
       react: 18.2.0
       tslib: 2.6.2
@@ -13951,8 +14148,8 @@ packages:
       inherits: 2.0.4
       is-arguments: 1.1.1
       is-generator-function: 1.0.10
-      is-typed-array: 1.1.12
-      which-typed-array: 1.1.13
+      is-typed-array: 1.1.13
+      which-typed-array: 1.1.14
     dev: true
 
   /utils-merge@1.0.1:
@@ -13981,8 +14178,8 @@ packages:
     engines: {node: '>= 0.8'}
     dev: true
 
-  /vite-node@1.2.2(@types/node@20.11.5):
-    resolution: {integrity: sha512-1as4rDTgVWJO3n1uHmUYqq7nsFgINQ9u+mRcXpjeOMJUmviqNKjcZB7UfRZrlM7MjYXMKpuWp5oGkjaFLnjawg==}
+  /vite-node@1.3.1(@types/node@20.11.19):
+    resolution: {integrity: sha512-azbRrqRxlWTJEVbzInZCTchx0X69M/XPTCz4H+TLvlTcR/xH/3hkRqhOakT41fMJCMzXTu4UvegkZiEoJAWvng==}
     engines: {node: ^18.0.0 || >=20.0.0}
     hasBin: true
     dependencies:
@@ -13990,7 +14187,7 @@ packages:
       debug: 4.3.4
       pathe: 1.1.2
       picocolors: 1.0.0
-      vite: 5.0.12(@types/node@20.11.5)
+      vite: 5.1.3(@types/node@20.11.19)
     transitivePeerDependencies:
       - '@types/node'
       - less
@@ -14002,16 +14199,16 @@ packages:
       - terser
     dev: true
 
-  /vite-plugin-css-injected-by-js@3.3.1(vite@5.0.12):
-    resolution: {integrity: sha512-PjM/X45DR3/V1K1fTRs8HtZHEQ55kIfdrn+dzaqNBFrOYO073SeSNCxp4j7gSYhV9NffVHaEnOL4myoko0ePAg==}
+  /vite-plugin-css-injected-by-js@3.4.0(vite@5.1.3):
+    resolution: {integrity: sha512-wS5+UYtJXQ/vNornsqTQxOLBVO/UjXU54ZsYMeX0mj2OrbStMQ4GLgvneVDQGPwyGJcm/ntBPawc2lA7xx+Lpg==}
     peerDependencies:
       vite: '>2.0.0-0'
     dependencies:
-      vite: 5.0.12(@types/node@20.11.5)
+      vite: 5.1.3(@types/node@20.11.19)
     dev: true
 
-  /vite-plugin-dts@3.7.1(@types/node@20.11.5)(typescript@5.3.3)(vite@5.0.12):
-    resolution: {integrity: sha512-VZJckNFpVfRAkmOxhGT5OgTUVWVXxkNQqLpBUuiNGAr9HbtvmvsPLo2JB3Xhn+o/Z9+CT6YZfYa4bX9SGR5hNw==}
+  /vite-plugin-dts@3.7.2(@types/node@20.11.19)(typescript@5.3.3)(vite@5.1.3):
+    resolution: {integrity: sha512-kg//1nDA01b8rufJf4TsvYN8LMkdwv0oBYpiQi6nRwpHyue+wTlhrBiqgipdFpMnW1oOYv6ywmzE5B0vg6vSEA==}
     engines: {node: ^14.18.0 || >=16.0.0}
     peerDependencies:
       typescript: '*'
@@ -14020,13 +14217,13 @@ packages:
       vite:
         optional: true
     dependencies:
-      '@microsoft/api-extractor': 7.39.0(@types/node@20.11.5)
+      '@microsoft/api-extractor': 7.39.0(@types/node@20.11.19)
       '@rollup/pluginutils': 5.1.0
       '@vue/language-core': 1.8.27(typescript@5.3.3)
       debug: 4.3.4
       kolorist: 1.8.0
       typescript: 5.3.3
-      vite: 5.0.12(@types/node@20.11.5)
+      vite: 5.1.3(@types/node@20.11.19)
       vue-tsc: 1.8.27(typescript@5.3.3)
     transitivePeerDependencies:
       - '@types/node'
@@ -14034,20 +14231,20 @@ packages:
       - supports-color
     dev: true
 
-  /vite-plugin-eslint@1.8.1(eslint@8.56.0)(vite@5.0.12):
+  /vite-plugin-eslint@1.8.1(eslint@8.56.0)(vite@5.1.3):
     resolution: {integrity: sha512-PqdMf3Y2fLO9FsNPmMX+//2BF5SF8nEWspZdgl4kSt7UvHDRHVVfHvxsD7ULYzZrJDGRxR81Nq7TOFgwMnUang==}
     peerDependencies:
       eslint: '>=7'
       vite: '>=2'
     dependencies:
       '@rollup/pluginutils': 4.2.1
-      '@types/eslint': 8.56.0
+      '@types/eslint': 8.56.2
       eslint: 8.56.0
       rollup: 2.79.1
-      vite: 5.0.12(@types/node@20.11.5)
+      vite: 5.1.3(@types/node@20.11.19)
     dev: true
 
-  /vite-tsconfig-paths@4.3.1(typescript@5.3.3)(vite@5.0.12):
+  /vite-tsconfig-paths@4.3.1(typescript@5.3.3)(vite@5.1.3):
     resolution: {integrity: sha512-cfgJwcGOsIxXOLU/nELPny2/LUD/lcf1IbfyeKTv2bsupVbTH/xpFtdQlBmIP1GEK2CjjLxYhFfB+QODFAx5aw==}
     peerDependencies:
       vite: '*'
@@ -14057,15 +14254,15 @@ packages:
     dependencies:
       debug: 4.3.4
       globrex: 0.1.2
-      tsconfck: 3.0.1(typescript@5.3.3)
-      vite: 5.0.12(@types/node@20.11.5)
+      tsconfck: 3.0.2(typescript@5.3.3)
+      vite: 5.1.3(@types/node@20.11.19)
     transitivePeerDependencies:
       - supports-color
       - typescript
     dev: true
 
-  /vite@5.0.12(@types/node@20.11.5):
-    resolution: {integrity: sha512-4hsnEkG3q0N4Tzf1+t6NdN9dg/L3BM+q8SWgbSPnJvrgH2kgdyzfVJwbR1ic69/4uMJJ/3dqDZZE5/WwqW8U1w==}
+  /vite@5.1.3(@types/node@20.11.19):
+    resolution: {integrity: sha512-UfmUD36DKkqhi/F75RrxvPpry+9+tTkrXfMNZD+SboZqBCMsxKtO52XeGzzuh7ioz+Eo/SYDBbdb0Z7vgcDJew==}
     engines: {node: ^18.0.0 || >=20.0.0}
     hasBin: true
     peerDependencies:
@@ -14092,23 +14289,23 @@ packages:
       terser:
         optional: true
     dependencies:
-      '@types/node': 20.11.5
-      esbuild: 0.19.11
-      postcss: 8.4.33
-      rollup: 4.9.4
+      '@types/node': 20.11.19
+      esbuild: 0.19.12
+      postcss: 8.4.35
+      rollup: 4.12.0
     optionalDependencies:
       fsevents: 2.3.3
     dev: true
 
-  /vitest@1.2.2(@types/node@20.11.5):
-    resolution: {integrity: sha512-d5Ouvrnms3GD9USIK36KG8OZ5bEvKEkITFtnGv56HFaSlbItJuYr7hv2Lkn903+AvRAgSixiamozUVfORUekjw==}
+  /vitest@1.3.1(@types/node@20.11.19):
+    resolution: {integrity: sha512-/1QJqXs8YbCrfv/GPQ05wAZf2eakUPLPa18vkJAKE7RXOKfVHqMZZ1WlTjiwl6Gcn65M5vpNUB6EFLnEdRdEXQ==}
     engines: {node: ^18.0.0 || >=20.0.0}
     hasBin: true
     peerDependencies:
       '@edge-runtime/vm': '*'
       '@types/node': ^18.0.0 || >=20.0.0
-      '@vitest/browser': ^1.0.0
-      '@vitest/ui': ^1.0.0
+      '@vitest/browser': 1.3.1
+      '@vitest/ui': 1.3.1
       happy-dom: '*'
       jsdom: '*'
     peerDependenciesMeta:
@@ -14125,27 +14322,26 @@ packages:
       jsdom:
         optional: true
     dependencies:
-      '@types/node': 20.11.5
-      '@vitest/expect': 1.2.2
-      '@vitest/runner': 1.2.2
-      '@vitest/snapshot': 1.2.2
-      '@vitest/spy': 1.2.2
-      '@vitest/utils': 1.2.2
+      '@types/node': 20.11.19
+      '@vitest/expect': 1.3.1
+      '@vitest/runner': 1.3.1
+      '@vitest/snapshot': 1.3.1
+      '@vitest/spy': 1.3.1
+      '@vitest/utils': 1.3.1
       acorn-walk: 8.3.2
-      cac: 6.7.14
       chai: 4.4.1
       debug: 4.3.4
       execa: 8.0.1
       local-pkg: 0.5.0
-      magic-string: 0.30.5
+      magic-string: 0.30.7
       pathe: 1.1.2
       picocolors: 1.0.0
       std-env: 3.7.0
-      strip-literal: 1.3.0
+      strip-literal: 2.0.0
       tinybench: 2.6.0
       tinypool: 0.8.2
-      vite: 5.0.12(@types/node@20.11.5)
-      vite-node: 1.2.2(@types/node@20.11.5)
+      vite: 5.1.3(@types/node@20.11.19)
+      vite-node: 1.3.1(@types/node@20.11.19)
       why-is-node-running: 2.2.2
     transitivePeerDependencies:
       - less
@@ -14177,7 +14373,7 @@ packages:
     dependencies:
       '@volar/typescript': 1.11.1
       '@vue/language-core': 1.8.27(typescript@5.3.3)
-      semver: 7.5.4
+      semver: 7.6.0
       typescript: 5.3.3
     dev: true
 
@@ -14239,7 +14435,7 @@ packages:
     engines: {node: '>= 0.4'}
     dependencies:
       function.prototype.name: 1.1.6
-      has-tostringtag: 1.0.0
+      has-tostringtag: 1.0.2
       is-async-function: 2.0.0
       is-date-object: 1.0.5
       is-finalizationregistry: 1.0.2
@@ -14249,7 +14445,7 @@ packages:
       isarray: 2.0.5
       which-boxed-primitive: 1.0.2
       which-collection: 1.0.1
-      which-typed-array: 1.1.13
+      which-typed-array: 1.1.14
     dev: true
 
   /which-collection@1.0.1:
@@ -14261,15 +14457,15 @@ packages:
       is-weakset: 2.0.2
     dev: true
 
-  /which-typed-array@1.1.13:
-    resolution: {integrity: sha512-P5Nra0qjSncduVPEAr7xhoF5guty49ArDTwzJ/yNuPIbZppyRxFQsRCWrocxIY+CnMVG+qfbU2FmDKyvSGClow==}
+  /which-typed-array@1.1.14:
+    resolution: {integrity: sha512-VnXFiIW8yNn9kIHN88xvZ4yOWchftKDsRJ8fEPacX/wl1lOvBrhsJ/OeJCXq7B0AaijRuqgzSKalJoPk+D8MPg==}
     engines: {node: '>= 0.4'}
     dependencies:
-      available-typed-arrays: 1.0.5
-      call-bind: 1.0.5
+      available-typed-arrays: 1.0.7
+      call-bind: 1.0.7
       for-each: 0.3.3
       gopd: 1.0.1
-      has-tostringtag: 1.0.0
+      has-tostringtag: 1.0.2
     dev: true
 
   /which@2.0.2:
@@ -14409,7 +14605,7 @@ packages:
     engines: {node: '>=12'}
     dependencies:
       cliui: 8.0.1
-      escalade: 3.1.1
+      escalade: 3.1.2
       get-caller-file: 2.0.5
       require-directory: 2.1.1
       string-width: 4.2.3
@@ -14446,8 +14642,8 @@ packages:
       commander: 9.5.0
     dev: true
 
-  /zod-validation-error@3.0.0(zod@3.22.4):
-    resolution: {integrity: sha512-x+agsJJG9rvC7axF0xqTEdZhJkLHyIZkdOAWDJSmwGPzxNHMHwtU6w2yDOAAP6yuSfTAUhAMJRBfhVGY64ySEQ==}
+  /zod-validation-error@3.0.2(zod@3.22.4):
+    resolution: {integrity: sha512-21xGaDmnU7lJZ4J63n5GXWqi+rTzGy3gDHbuZ1jP6xrK/DEQGyOqs/xW7eH96tIfCOYm+ecCuT0bfajBRKEVUw==}
     engines: {node: '>=18.0.0'}
     peerDependencies:
       zod: ^3.18.0
@@ -14459,12 +14655,12 @@ packages:
     resolution: {integrity: sha512-iC+8Io04lddc+mVqQ9AZ7OQ2MrUKGN+oIQyq1vemgt46jwCwLfhq7/pwnBnNXXXZb8VTVLKwp9EDkx+ryxIWmg==}
     dev: false
 
-  /zustand@4.4.7(@types/react@18.2.48)(react@18.2.0):
-    resolution: {integrity: sha512-QFJWJMdlETcI69paJwhSMJz7PPWjVP8Sjhclxmxmxv/RYI7ZOvR5BHX+ktH0we9gTWQMxcne8q1OY8xxz604gw==}
+  /zustand@4.5.1(@types/react@18.2.57)(react@18.2.0):
+    resolution: {integrity: sha512-XlauQmH64xXSC1qGYNv00ODaQ3B+tNPoy22jv2diYiP4eoDKr9LA+Bh5Bc3gplTrFdb6JVI+N4kc1DZ/tbtfPg==}
     engines: {node: '>=12.7.0'}
     peerDependencies:
       '@types/react': '>=16.8'
-      immer: '>=9.0'
+      immer: '>=9.0.6'
       react: '>=16.8'
     peerDependenciesMeta:
       '@types/react':
@@ -14474,7 +14670,7 @@ packages:
       react:
         optional: true
     dependencies:
-      '@types/react': 18.2.48
+      '@types/react': 18.2.57
       react: 18.2.0
       use-sync-external-store: 1.2.0(react@18.2.0)
     dev: false
diff --git a/invokeai/frontend/web/src/app/store/enhancers/reduxRemember/driver.ts b/invokeai/frontend/web/src/app/store/enhancers/reduxRemember/driver.ts
index 61fbd015f8..c8237664c2 100644
--- a/invokeai/frontend/web/src/app/store/enhancers/reduxRemember/driver.ts
+++ b/invokeai/frontend/web/src/app/store/enhancers/reduxRemember/driver.ts
@@ -2,15 +2,15 @@ import { StorageError } from 'app/store/enhancers/reduxRemember/errors';
 import { $projectId } from 'app/store/nanostores/projectId';
 import type { UseStore } from 'idb-keyval';
 import { clear, createStore as createIDBKeyValStore, get, set } from 'idb-keyval';
-import { action, atom } from 'nanostores';
+import { atom } from 'nanostores';
 import type { Driver } from 'redux-remember';
 
 // Create a custom idb-keyval store (just needed to customize the name)
 export const $idbKeyValStore = atom<UseStore>(createIDBKeyValStore('invoke', 'invoke-store'));
 
-export const clearIdbKeyValStore = action($idbKeyValStore, 'clear', (store) => {
-  clear(store.get());
-});
+export const clearIdbKeyValStore = () => {
+  clear($idbKeyValStore.get());
+};
 
 // Create redux-remember driver, wrapping idb-keyval
 export const idbKeyValDriver: Driver = {
diff --git a/invokeai/frontend/web/src/services/api/index.ts b/invokeai/frontend/web/src/services/api/index.ts
index 82f382ee10..3b5a10492c 100644
--- a/invokeai/frontend/web/src/services/api/index.ts
+++ b/invokeai/frontend/web/src/services/api/index.ts
@@ -1,6 +1,7 @@
+import { createSelectorCreator, lruMemoize } from '@reduxjs/toolkit';
 import type { FetchBaseQueryArgs } from '@reduxjs/toolkit/dist/query/fetchBaseQuery';
 import type { BaseQueryFn, FetchArgs, FetchBaseQueryError, TagDescription } from '@reduxjs/toolkit/query/react';
-import { createApi, fetchBaseQuery } from '@reduxjs/toolkit/query/react';
+import { buildCreateApi, coreModule, fetchBaseQuery, reactHooksModule } from '@reduxjs/toolkit/query/react';
 import { $authToken } from 'app/store/nanostores/authToken';
 import { $baseUrl } from 'app/store/nanostores/baseUrl';
 import { $projectId } from 'app/store/nanostores/projectId';
@@ -85,7 +86,14 @@ const dynamicBaseQuery: BaseQueryFn<string | FetchArgs, unknown, FetchBaseQueryE
   return rawBaseQuery(args, api, extraOptions);
 };
 
-export const api = createApi({
+const createLruSelector = createSelectorCreator(lruMemoize);
+
+const customCreateApi = buildCreateApi(
+  coreModule({ createSelector: createLruSelector }),
+  reactHooksModule({ createSelector: createLruSelector })
+);
+
+export const api = customCreateApi({
   baseQuery: dynamicBaseQuery,
   reducerPath: 'api',
   tagTypes,

From 97cfcd2eef71158bd388d99e1e213510efe22f4e Mon Sep 17 00:00:00 2001
From: Brandon Rising <contact@brandonrising.com>
Date: Wed, 21 Feb 2024 11:54:02 -0500
Subject: [PATCH 232/411] Create /search endpoint, update model object
 structure in scan model page

---
 invokeai/app/api/routers/model_manager.py     | 31 +++++++++++++++++++
 .../subpanels/ImportModelsPanel.tsx           |  2 +-
 .../subpanels/ModelManagerPanel/ModelList.tsx |  6 ++--
 3 files changed, 35 insertions(+), 4 deletions(-)

diff --git a/invokeai/app/api/routers/model_manager.py b/invokeai/app/api/routers/model_manager.py
index 6b7111dd2c..be4ed75069 100644
--- a/invokeai/app/api/routers/model_manager.py
+++ b/invokeai/app/api/routers/model_manager.py
@@ -32,6 +32,7 @@ from invokeai.backend.model_manager.config import (
 )
 from invokeai.backend.model_manager.merge import MergeInterpolationMethod, ModelMerger
 from invokeai.backend.model_manager.metadata import AnyModelRepoMetadata
+from invokeai.backend.model_manager.search import ModelSearch
 
 from ..dependencies import ApiDependencies
 
@@ -233,6 +234,36 @@ async def list_tags() -> Set[str]:
     result: Set[str] = record_store.list_tags()
     return result
 
+@model_manager_router.get(
+    "/search",
+    operation_id="search_for_models",
+    responses={
+        200: {"description": "Directory searched successfully"},
+        404: {"description": "Invalid directory path"},
+    },
+    status_code=200,
+    response_model=List[pathlib.Path],
+)
+async def search_for_models(
+    search_path: str = Query(description="Directory path to search for models", default=None),
+) -> List[pathlib.Path]:
+    path = pathlib.Path(search_path)
+    if not search_path or not path.is_dir():
+        raise HTTPException(
+            status_code=404,
+            detail=f"The search path '{search_path}' does not exist or is not directory",
+        )
+
+    search = ModelSearch()
+    try:
+        models_found = list(search.search(path))
+    except Exception as e:
+        raise HTTPException(
+            status_code=404,
+            detail=f"An error occurred while searching the directory: {e}",
+        )
+    return models_found
+
 
 @model_manager_router.get(
     "/tags/search",
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ImportModelsPanel.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ImportModelsPanel.tsx
index 18fcef9614..960f798e79 100644
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ImportModelsPanel.tsx
+++ b/invokeai/frontend/web/src/features/modelManager/subpanels/ImportModelsPanel.tsx
@@ -20,7 +20,7 @@ const ImportModelsPanel = () => {
         <Button onClick={handleClickAddTab} isChecked={addModelTab === 'add'} size="sm" width="100%">
           {t('modelManager.addModel')}
         </Button>
-        <Button onClick={handleClickScanTab} isChecked={addModelTab === 'scan'} size="sm" width="100%" isDisabled>
+        <Button onClick={handleClickScanTab} isChecked={addModelTab === 'scan'} size="sm" width="100%">
           {t('modelManager.scanForModels')}
         </Button>
       </ButtonGroup>
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelList.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelList.tsx
index dd74bb0c23..49c9bc6112 100644
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelList.tsx
+++ b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelList.tsx
@@ -139,10 +139,10 @@ const modelsFilter = <T extends MainModelConfig | LoRAConfig>(
       return;
     }
 
-    const matchesFilter = model.model_name.toLowerCase().includes(nameFilter.toLowerCase());
+    const matchesFilter = model.name.toLowerCase().includes(nameFilter.toLowerCase());
 
-    const matchesFormat = model_format === undefined || model.model_format === model_format;
-    const matchesType = model.model_type === model_type;
+    const matchesFormat = model_format === undefined || model.format === model_format;
+    const matchesType = model.type === model_type;
 
     if (matchesFilter && matchesFormat && matchesType) {
       filteredModels.push(model);

From 9269bdd233d6c02e3bdc253429403991fce88058 Mon Sep 17 00:00:00 2001
From: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Date: Thu, 22 Feb 2024 09:08:18 -0500
Subject: [PATCH 233/411] rename endpoint for scanning

---
 invokeai/app/api/routers/model_manager.py | 22 +++++++++++-----------
 1 file changed, 11 insertions(+), 11 deletions(-)

diff --git a/invokeai/app/api/routers/model_manager.py b/invokeai/app/api/routers/model_manager.py
index be4ed75069..30b78f589d 100644
--- a/invokeai/app/api/routers/model_manager.py
+++ b/invokeai/app/api/routers/model_manager.py
@@ -235,23 +235,23 @@ async def list_tags() -> Set[str]:
     return result
 
 @model_manager_router.get(
-    "/search",
-    operation_id="search_for_models",
+    "/scan_folder",
+    operation_id="scan_for_models",
     responses={
-        200: {"description": "Directory searched successfully"},
-        404: {"description": "Invalid directory path"},
+        200: {"description": "Directory scanned successfully"},
+        400: {"description": "Invalid directory path"},
     },
     status_code=200,
     response_model=List[pathlib.Path],
 )
-async def search_for_models(
-    search_path: str = Query(description="Directory path to search for models", default=None),
+async def scan_for_models(
+    scan_path: str = Query(description="Directory path to search for models", default=None),
 ) -> List[pathlib.Path]:
-    path = pathlib.Path(search_path)
-    if not search_path or not path.is_dir():
+    path = pathlib.Path(scan_path)
+    if not scan_path or not path.is_dir():
         raise HTTPException(
-            status_code=404,
-            detail=f"The search path '{search_path}' does not exist or is not directory",
+            status_code=400,
+            detail=f"The search path '{scan_path}' does not exist or is not directory",
         )
 
     search = ModelSearch()
@@ -259,7 +259,7 @@ async def search_for_models(
         models_found = list(search.search(path))
     except Exception as e:
         raise HTTPException(
-            status_code=404,
+            status_code=500,
             detail=f"An error occurred while searching the directory: {e}",
         )
     return models_found

From f7fc20459ad4f21440578335fc5dfecf150b17f8 Mon Sep 17 00:00:00 2001
From: Brandon Rising <contact@brandonrising.com>
Date: Thu, 22 Feb 2024 09:13:50 -0500
Subject: [PATCH 234/411] Run ruff

---
 invokeai/app/api/routers/model_manager.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/invokeai/app/api/routers/model_manager.py b/invokeai/app/api/routers/model_manager.py
index 30b78f589d..aee457406a 100644
--- a/invokeai/app/api/routers/model_manager.py
+++ b/invokeai/app/api/routers/model_manager.py
@@ -234,6 +234,7 @@ async def list_tags() -> Set[str]:
     result: Set[str] = record_store.list_tags()
     return result
 
+
 @model_manager_router.get(
     "/scan_folder",
     operation_id="scan_for_models",

From 06cc57d82abedd4ee7165eeb487143ac0e938e43 Mon Sep 17 00:00:00 2001
From: dunkeroni <dunkeroni@gmail.com>
Date: Tue, 20 Feb 2024 21:13:19 -0500
Subject: [PATCH 235/411] feat(nodes): added gradient mask node

---
 invokeai/app/invocations/fields.py            |  1 +
 invokeai/app/invocations/latent.py            | 69 +++++++++++++++++--
 invokeai/app/invocations/primitives.py        |  8 ++-
 .../stable_diffusion/diffusers_pipeline.py    | 13 +++-
 4 files changed, 80 insertions(+), 11 deletions(-)

diff --git a/invokeai/app/invocations/fields.py b/invokeai/app/invocations/fields.py
index 40d403c03d..7f2d2783f2 100644
--- a/invokeai/app/invocations/fields.py
+++ b/invokeai/app/invocations/fields.py
@@ -199,6 +199,7 @@ class DenoiseMaskField(BaseModel):
 
     mask_name: str = Field(description="The name of the mask image")
     masked_latents_name: Optional[str] = Field(default=None, description="The name of the masked image latents")
+    gradient: Optional[bool] = Field(default=False, description="Used for gradient inpainting")
 
 
 class LatentsField(BaseModel):
diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py
index bfe7255b62..97d3c705d4 100644
--- a/invokeai/app/invocations/latent.py
+++ b/invokeai/app/invocations/latent.py
@@ -23,7 +23,7 @@ from diffusers.models.attention_processor import (
 from diffusers.models.unets.unet_2d_condition import UNet2DConditionModel
 from diffusers.schedulers import DPMSolverSDEScheduler
 from diffusers.schedulers import SchedulerMixin as Scheduler
-from PIL import Image
+from PIL import Image, ImageFilter
 from pydantic import field_validator
 from torchvision.transforms.functional import resize as tv_resize
 
@@ -128,7 +128,7 @@ class CreateDenoiseMaskInvocation(BaseInvocation):
         ui_order=4,
     )
 
-    def prep_mask_tensor(self, mask_image: Image) -> torch.Tensor:
+    def prep_mask_tensor(self, mask_image: Image.Image) -> torch.Tensor:
         if mask_image.mode != "L":
             mask_image = mask_image.convert("L")
         mask_tensor: torch.Tensor = image_resized_to_grid_as_tensor(mask_image, normalize=False)
@@ -169,6 +169,62 @@ class CreateDenoiseMaskInvocation(BaseInvocation):
         return DenoiseMaskOutput.build(
             mask_name=mask_name,
             masked_latents_name=masked_latents_name,
+            gradient=False,
+        )
+
+
+@invocation(
+    "create_gradient_mask",
+    title="Create Gradient Mask",
+    tags=["mask", "denoise"],
+    category="latents",
+    version="1.0.0",
+)
+class CreateGradientMaskInvocation(BaseInvocation):
+    """Creates mask for denoising model run."""
+
+    mask: ImageField = InputField(default=None, description="Image which will be masked", ui_order=1)
+    edge_radius: int = InputField(
+        default=16, ge=0, description="How far to blur/expand the edges of the mask", ui_order=2
+    )
+    coherence_mode: Literal["Gaussian Blur", "Box Blur", "Staged"] = InputField(default="Gaussian Blur", ui_order=3)
+    minimum_denoise: float = InputField(
+        default=0.0, ge=0, le=1, description="Minimum denoise level for the coherence region", ui_order=4
+    )
+
+    @torch.no_grad()
+    def invoke(self, context: InvocationContext) -> DenoiseMaskOutput:
+        mask_image = context.images.get_pil(self.mask.image_name, mode="L")
+        if self.coherence_mode == "Box Blur":
+            blur_mask = mask_image.filter(ImageFilter.BoxBlur(self.edge_radius))
+        else:  # Gaussian Blur OR Staged
+            # Gaussian Blur uses standard deviation. 1/2 radius is a good approximation
+            blur_mask = mask_image.filter(ImageFilter.GaussianBlur(self.edge_radius / 2))
+
+        mask_tensor: torch.Tensor = image_resized_to_grid_as_tensor(mask_image, normalize=False)
+        blur_tensor: torch.Tensor = image_resized_to_grid_as_tensor(blur_mask, normalize=False)
+
+        # redistribute blur so that the edges are 0 and blur out to 1
+        blur_tensor = (blur_tensor - 0.5) * 2
+
+        threshold = 1 - self.minimum_denoise
+
+        if self.coherence_mode == "Staged":
+            # wherever the blur_tensor is masked to any degree, convert it to threshold
+            blur_tensor = torch.where((blur_tensor < 1), threshold, blur_tensor)
+        else:
+            # wherever the blur_tensor is above threshold but less than 1, drop it to threshold
+            blur_tensor = torch.where((blur_tensor > threshold) & (blur_tensor < 1), threshold, blur_tensor)
+
+        # multiply original mask to force actually masked regions to 0
+        blur_tensor = mask_tensor * blur_tensor
+
+        mask_name = context.tensors.save(tensor=blur_tensor.unsqueeze(1))
+
+        return DenoiseMaskOutput.build(
+            mask_name=mask_name,
+            masked_latents_name=None,
+            gradient=True,
         )
 
 
@@ -606,9 +662,9 @@ class DenoiseLatentsInvocation(BaseInvocation):
 
     def prep_inpaint_mask(
         self, context: InvocationContext, latents: torch.Tensor
-    ) -> Tuple[Optional[torch.Tensor], Optional[torch.Tensor]]:
+    ) -> Tuple[Optional[torch.Tensor], Optional[torch.Tensor], bool]:
         if self.denoise_mask is None:
-            return None, None
+            return None, None, False
 
         mask = context.tensors.load(self.denoise_mask.mask_name)
         mask = tv_resize(mask, latents.shape[-2:], T.InterpolationMode.BILINEAR, antialias=False)
@@ -617,7 +673,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
         else:
             masked_latents = None
 
-        return 1 - mask, masked_latents
+        return 1 - mask, masked_latents, self.denoise_mask.gradient
 
     @torch.no_grad()
     def invoke(self, context: InvocationContext) -> LatentsOutput:
@@ -644,7 +700,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
             if seed is None:
                 seed = 0
 
-            mask, masked_latents = self.prep_inpaint_mask(context, latents)
+            mask, masked_latents, gradient_mask = self.prep_inpaint_mask(context, latents)
 
             # TODO(ryand): I have hard-coded `do_classifier_free_guidance=True` to mirror the behaviour of ControlNets,
             # below. Investigate whether this is appropriate.
@@ -732,6 +788,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
                     seed=seed,
                     mask=mask,
                     masked_latents=masked_latents,
+                    gradient_mask=gradient_mask,
                     num_inference_steps=num_inference_steps,
                     conditioning_data=conditioning_data,
                     control_data=controlnet_data,
diff --git a/invokeai/app/invocations/primitives.py b/invokeai/app/invocations/primitives.py
index 4342213482..c761bb0895 100644
--- a/invokeai/app/invocations/primitives.py
+++ b/invokeai/app/invocations/primitives.py
@@ -299,9 +299,13 @@ class DenoiseMaskOutput(BaseInvocationOutput):
     denoise_mask: DenoiseMaskField = OutputField(description="Mask for denoise model run")
 
     @classmethod
-    def build(cls, mask_name: str, masked_latents_name: Optional[str] = None) -> "DenoiseMaskOutput":
+    def build(
+        cls, mask_name: str, masked_latents_name: Optional[str] = None, gradient: Optional[bool] = False
+    ) -> "DenoiseMaskOutput":
         return cls(
-            denoise_mask=DenoiseMaskField(mask_name=mask_name, masked_latents_name=masked_latents_name),
+            denoise_mask=DenoiseMaskField(
+                mask_name=mask_name, masked_latents_name=masked_latents_name, gradient=gradient
+            ),
         )
 
 
diff --git a/invokeai/backend/stable_diffusion/diffusers_pipeline.py b/invokeai/backend/stable_diffusion/diffusers_pipeline.py
index a85e3762dc..fd3ecde47b 100644
--- a/invokeai/backend/stable_diffusion/diffusers_pipeline.py
+++ b/invokeai/backend/stable_diffusion/diffusers_pipeline.py
@@ -86,6 +86,7 @@ class AddsMaskGuidance:
     mask_latents: torch.FloatTensor
     scheduler: SchedulerMixin
     noise: torch.Tensor
+    gradient_mask: bool
 
     def __call__(self, step_output: Union[BaseOutput, SchedulerOutput], t: torch.Tensor, conditioning) -> BaseOutput:
         output_class = step_output.__class__  # We'll create a new one with masked data.
@@ -121,7 +122,12 @@ class AddsMaskGuidance:
         # TODO: Do we need to also apply scheduler.scale_model_input? Or is add_noise appropriately scaled already?
         # mask_latents = self.scheduler.scale_model_input(mask_latents, t)
         mask_latents = einops.repeat(mask_latents, "b c h w -> (repeat b) c h w", repeat=batch_size)
-        masked_input = torch.lerp(mask_latents.to(dtype=latents.dtype), latents, mask.to(dtype=latents.dtype))
+        if self.gradient_mask:
+            threshhold = (t.item()) / self.scheduler.config.num_train_timesteps
+            mask_bool = mask > threshhold  # I don't know when mask got inverted, but it did
+            masked_input = torch.where(mask_bool, latents, mask_latents)
+        else:
+            masked_input = torch.lerp(mask_latents.to(dtype=latents.dtype), latents, mask.to(dtype=latents.dtype))
         return masked_input
 
 
@@ -335,6 +341,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
         t2i_adapter_data: Optional[list[T2IAdapterData]] = None,
         mask: Optional[torch.Tensor] = None,
         masked_latents: Optional[torch.Tensor] = None,
+        gradient_mask: Optional[bool] = False,
         seed: Optional[int] = None,
     ) -> tuple[torch.Tensor, Optional[AttentionMapSaver]]:
         if init_timestep.shape[0] == 0:
@@ -375,7 +382,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
                     self._unet_forward, mask, masked_latents
                 )
             else:
-                additional_guidance.append(AddsMaskGuidance(mask, orig_latents, self.scheduler, noise))
+                additional_guidance.append(AddsMaskGuidance(mask, orig_latents, self.scheduler, noise, gradient_mask))
 
         try:
             latents, attention_map_saver = self.generate_latents_from_embeddings(
@@ -392,7 +399,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
             self.invokeai_diffuser.model_forward_callback = self._unet_forward
 
         # restore unmasked part
-        if mask is not None:
+        if mask is not None and not gradient_mask:
             latents = torch.lerp(orig_latents, latents.to(dtype=orig_latents.dtype), mask.to(dtype=orig_latents.dtype))
 
         return latents, attention_map_saver

From 07dde92664dc0e35a4531b7e10e254cb852af041 Mon Sep 17 00:00:00 2001
From: dunkeroni <dunkeroni@gmail.com>
Date: Tue, 20 Feb 2024 21:47:25 -0500
Subject: [PATCH 236/411] chore: typing fix

---
 invokeai/app/invocations/fields.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/invokeai/app/invocations/fields.py b/invokeai/app/invocations/fields.py
index 7f2d2783f2..712ab415b0 100644
--- a/invokeai/app/invocations/fields.py
+++ b/invokeai/app/invocations/fields.py
@@ -199,7 +199,7 @@ class DenoiseMaskField(BaseModel):
 
     mask_name: str = Field(description="The name of the mask image")
     masked_latents_name: Optional[str] = Field(default=None, description="The name of the masked image latents")
-    gradient: Optional[bool] = Field(default=False, description="Used for gradient inpainting")
+    gradient: bool = Field(default=False, description="Used for gradient inpainting")
 
 
 class LatentsField(BaseModel):

From 30a374a70f000611fb5a27902ab40285b36e886c Mon Sep 17 00:00:00 2001
From: dunkeroni <dunkeroni@gmail.com>
Date: Tue, 20 Feb 2024 22:13:01 -0500
Subject: [PATCH 237/411] chore: typing

---
 invokeai/app/invocations/primitives.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/invokeai/app/invocations/primitives.py b/invokeai/app/invocations/primitives.py
index c761bb0895..b80e34dc98 100644
--- a/invokeai/app/invocations/primitives.py
+++ b/invokeai/app/invocations/primitives.py
@@ -300,7 +300,7 @@ class DenoiseMaskOutput(BaseInvocationOutput):
 
     @classmethod
     def build(
-        cls, mask_name: str, masked_latents_name: Optional[str] = None, gradient: Optional[bool] = False
+        cls, mask_name: str, masked_latents_name: Optional[str] = None, gradient: bool = False
     ) -> "DenoiseMaskOutput":
         return cls(
             denoise_mask=DenoiseMaskField(

From 5bb3aeaccda06bc034ee8f4d7eac2f7a428f19c1 Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lstein@gmail.com>
Date: Wed, 21 Feb 2024 10:18:30 -0500
Subject: [PATCH 238/411] remove startup dependency on legacy models.yaml file

---
 invokeai/app/services/config/config_base.py   |   1 +
 .../app/services/config/config_default.py     |   5 +-
 invokeai/backend/install/check_root.py        |   1 -
 .../backend/install/invokeai_configure.py     |   2 +-
 invokeai/backend/model_manager/merge.py       |   4 +-
 .../training/textual_inversion_training.py    |   2 +-
 invokeai/frontend/install/model_install.py    |   2 +-
 invokeai/frontend/merge/merge_diffusers.py    |   2 +-
 .../frontend/training/textual_inversion.py    |   4 +-
 .../frontend/training/textual_inversion2.py   | 454 ------------------
 invokeai/frontend/web/public/locales/en.json  |   2 +-
 11 files changed, 11 insertions(+), 468 deletions(-)
 mode change 100755 => 100644 invokeai/frontend/training/textual_inversion.py
 delete mode 100644 invokeai/frontend/training/textual_inversion2.py

diff --git a/invokeai/app/services/config/config_base.py b/invokeai/app/services/config/config_base.py
index c73aa43809..20dac14937 100644
--- a/invokeai/app/services/config/config_base.py
+++ b/invokeai/app/services/config/config_base.py
@@ -156,6 +156,7 @@ class InvokeAISettings(BaseSettings):
             "lora_dir",
             "embedding_dir",
             "controlnet_dir",
+            "conf_path",
         ]
 
     @classmethod
diff --git a/invokeai/app/services/config/config_default.py b/invokeai/app/services/config/config_default.py
index 2af775372d..01fd5e2179 100644
--- a/invokeai/app/services/config/config_default.py
+++ b/invokeai/app/services/config/config_default.py
@@ -30,7 +30,6 @@ InvokeAI:
     lora_dir: null
     embedding_dir: null
     controlnet_dir: null
-    conf_path: configs/models.yaml
     models_dir: models
     legacy_conf_dir: configs/stable-diffusion
     db_dir: databases
@@ -123,7 +122,6 @@ a Path object:
 
  root_path          - path to InvokeAI root
  output_path        - path to default outputs directory
- model_conf_path    - path to models.yaml
  conf               - alias for the above
  embedding_path     - path to the embeddings directory
  lora_path          - path to the LoRA directory
@@ -163,7 +161,6 @@ two configs are kept in separate sections of the config file:
   InvokeAI:
      Paths:
         root: /home/lstein/invokeai-main
-        conf_path: configs/models.yaml
         legacy_conf_dir: configs/stable-diffusion
         outdir: outputs
      ...
@@ -237,7 +234,6 @@ class InvokeAIAppConfig(InvokeAISettings):
     # PATHS
     root                : Optional[Path] = Field(default=None, description='InvokeAI runtime root directory', json_schema_extra=Categories.Paths)
     autoimport_dir      : Path = Field(default=Path('autoimport'), description='Path to a directory of models files to be imported on startup.', json_schema_extra=Categories.Paths)
-    conf_path           : Path = Field(default=Path('configs/models.yaml'), description='Path to models definition file', json_schema_extra=Categories.Paths)
     models_dir          : Path = Field(default=Path('models'), description='Path to the models directory', json_schema_extra=Categories.Paths)
     convert_cache_dir   : Path = Field(default=Path('models/.cache'), description='Path to the converted models cache directory', json_schema_extra=Categories.Paths)
     legacy_conf_dir     : Path = Field(default=Path('configs/stable-diffusion'), description='Path to directory of legacy checkpoint config files', json_schema_extra=Categories.Paths)
@@ -301,6 +297,7 @@ class InvokeAIAppConfig(InvokeAISettings):
     lora_dir            : Optional[Path] = Field(default=None, description='Path to a directory of LoRA/LyCORIS models to be imported on startup.', json_schema_extra=Categories.Paths)
     embedding_dir       : Optional[Path] = Field(default=None, description='Path to a directory of Textual Inversion embeddings to be imported on startup.', json_schema_extra=Categories.Paths)
     controlnet_dir      : Optional[Path] = Field(default=None, description='Path to a directory of ControlNet embeddings to be imported on startup.', json_schema_extra=Categories.Paths)
+    conf_path           : Path = Field(default=Path('configs/models.yaml'), description='Path to models definition file', json_schema_extra=Categories.Paths)
 
     # this is not referred to in the source code and can be removed entirely
     #free_gpu_mem        : Optional[bool] = Field(default=None, description="If true, purge model from GPU after each generation.", json_schema_extra=Categories.MemoryPerformance)
diff --git a/invokeai/backend/install/check_root.py b/invokeai/backend/install/check_root.py
index ee264016b4..cbf9976123 100644
--- a/invokeai/backend/install/check_root.py
+++ b/invokeai/backend/install/check_root.py
@@ -8,7 +8,6 @@ from invokeai.app.services.config import InvokeAIAppConfig
 
 def check_invokeai_root(config: InvokeAIAppConfig):
     try:
-        assert config.model_conf_path.exists(), f"{config.model_conf_path} not found"
         assert config.db_path.parent.exists(), f"{config.db_path.parent} not found"
         assert config.models_path.exists(), f"{config.models_path} not found"
         if not config.ignore_missing_core_models:
diff --git a/invokeai/backend/install/invokeai_configure.py b/invokeai/backend/install/invokeai_configure.py
index ac3e583de3..53cca64a1a 100755
--- a/invokeai/backend/install/invokeai_configure.py
+++ b/invokeai/backend/install/invokeai_configure.py
@@ -939,7 +939,7 @@ def main() -> None:
         # run this unconditionally in case new directories need to be added
         initialize_rootdir(config.root_path, opt.yes_to_all)
 
-        # this will initialize the models.yaml file if not present
+        # this will initialize and populate the models tables if not present
         install_helper = InstallHelper(config, logger)
 
         models_to_download = default_user_selections(opt, install_helper)
diff --git a/invokeai/backend/model_manager/merge.py b/invokeai/backend/model_manager/merge.py
index 7063cb907d..1a3b9cb7de 100644
--- a/invokeai/backend/model_manager/merge.py
+++ b/invokeai/backend/model_manager/merge.py
@@ -1,7 +1,7 @@
 """
 invokeai.backend.model_manager.merge exports:
 merge_diffusion_models() -- combine multiple models by location and return a pipeline object
-merge_diffusion_models_and_commit() -- combine multiple models by ModelManager ID and write to models.yaml
+merge_diffusion_models_and_commit() -- combine multiple models by ModelManager ID and write to the models tables
 
 Copyright (c) 2023 Lincoln Stein and the InvokeAI Development Team
 """
@@ -101,7 +101,7 @@ class ModelMerger(object):
         **kwargs: Any,
     ) -> AnyModelConfig:
         """
-        :param models: up to three models, designated by their InvokeAI models.yaml model name
+        :param models: up to three models, designated by their registered InvokeAI model name
         :param merged_model_name: name for new model
         :param alpha: The interpolation parameter. Ranges from 0 to 1.  It affects the ratio in which the checkpoints are merged. A 0.8 alpha
                    would mean that the first model checkpoints would affect the final result far less than an alpha of 0.2
diff --git a/invokeai/backend/training/textual_inversion_training.py b/invokeai/backend/training/textual_inversion_training.py
index e31ce959c2..9a38c006a5 100644
--- a/invokeai/backend/training/textual_inversion_training.py
+++ b/invokeai/backend/training/textual_inversion_training.py
@@ -120,7 +120,7 @@ def parse_args() -> Namespace:
         "--model",
         type=str,
         default="sd-1/main/stable-diffusion-v1-5",
-        help="Name of the diffusers model to train against, as defined in configs/models.yaml.",
+        help="Name of the diffusers model to train against.",
     )
     model_group.add_argument(
         "--revision",
diff --git a/invokeai/frontend/install/model_install.py b/invokeai/frontend/install/model_install.py
index 3a4d66ae0a..2f7fd0a1d0 100644
--- a/invokeai/frontend/install/model_install.py
+++ b/invokeai/frontend/install/model_install.py
@@ -455,7 +455,7 @@ class addModelsForm(CyclingForm, npyscreen.FormMultiPage):
         selections = self.parentApp.install_selections
         all_models = self.all_models
 
-        # Defined models (in INITIAL_CONFIG.yaml or models.yaml) to add/remove
+        # Defined models (in INITIAL_CONFIG.yaml or invokeai.db) to add/remove
         ui_sections = [
             self.starter_pipelines,
             self.pipeline_models,
diff --git a/invokeai/frontend/merge/merge_diffusers.py b/invokeai/frontend/merge/merge_diffusers.py
index 5484040674..ff9acd569e 100644
--- a/invokeai/frontend/merge/merge_diffusers.py
+++ b/invokeai/frontend/merge/merge_diffusers.py
@@ -435,7 +435,7 @@ def main():
             run_cli(args)
     except widget.NotEnoughSpaceForWidget as e:
         if str(e).startswith("Height of 1 allocated"):
-            logger.error("You need to have at least two diffusers models defined in models.yaml in order to merge")
+            logger.error("You need to have at least two diffusers models in order to merge")
         else:
             logger.error("Not enough room for the user interface. Try making this window larger.")
         sys.exit(-1)
diff --git a/invokeai/frontend/training/textual_inversion.py b/invokeai/frontend/training/textual_inversion.py
old mode 100755
new mode 100644
index 81b1081bb8..6250b313b0
--- a/invokeai/frontend/training/textual_inversion.py
+++ b/invokeai/frontend/training/textual_inversion.py
@@ -261,7 +261,7 @@ class textualInversionForm(npyscreen.FormMultiPageAction):
     def validate_field_values(self) -> bool:
         bad_fields = []
         if self.model.value is None:
-            bad_fields.append("Model Name must correspond to a known model in models.yaml")
+            bad_fields.append("Model Name must correspond to a known model in invokeai.db")
         if not re.match("^[a-zA-Z0-9.-]+$", self.placeholder_token.value):
             bad_fields.append("Trigger term must only contain alphanumeric characters, the dot and hyphen")
         if self.train_data_dir.value is None:
@@ -442,7 +442,7 @@ def main() -> None:
         pass
     except (widget.NotEnoughSpaceForWidget, Exception) as e:
         if str(e).startswith("Height of 1 allocated"):
-            logger.error("You need to have at least one diffusers models defined in models.yaml in order to train")
+            logger.error("You need to have at least one diffusers models defined in invokeai.db in order to train")
         elif str(e).startswith("addwstr"):
             logger.error("Not enough window space for the interface. Please make your window larger and try again.")
         else:
diff --git a/invokeai/frontend/training/textual_inversion2.py b/invokeai/frontend/training/textual_inversion2.py
deleted file mode 100644
index 81b1081bb8..0000000000
--- a/invokeai/frontend/training/textual_inversion2.py
+++ /dev/null
@@ -1,454 +0,0 @@
-#!/usr/bin/env python
-
-"""
-This is the frontend to "textual_inversion_training.py".
-
-Copyright (c) 2023-24 Lincoln Stein and the InvokeAI Development Team
-"""
-
-
-import os
-import re
-import shutil
-import sys
-import traceback
-from argparse import Namespace
-from pathlib import Path
-from typing import Dict, List, Optional, Tuple
-
-import npyscreen
-from npyscreen import widget
-from omegaconf import OmegaConf
-
-import invokeai.backend.util.logging as logger
-from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.backend.install.install_helper import initialize_installer
-from invokeai.backend.model_manager import ModelType
-from invokeai.backend.training import do_textual_inversion_training, parse_args
-
-TRAINING_DATA = "text-inversion-training-data"
-TRAINING_DIR = "text-inversion-output"
-CONF_FILE = "preferences.conf"
-config = None
-
-
-class textualInversionForm(npyscreen.FormMultiPageAction):
-    resolutions = [512, 768, 1024]
-    lr_schedulers = [
-        "linear",
-        "cosine",
-        "cosine_with_restarts",
-        "polynomial",
-        "constant",
-        "constant_with_warmup",
-    ]
-    precisions = ["no", "fp16", "bf16"]
-    learnable_properties = ["object", "style"]
-
-    def __init__(self, parentApp: npyscreen.NPSAppManaged, name: str, saved_args: Optional[Dict[str, str]] = None):
-        self.saved_args = saved_args or {}
-        super().__init__(parentApp, name)
-
-    def afterEditing(self) -> None:
-        self.parentApp.setNextForm(None)
-
-    def create(self) -> None:
-        self.model_names, default = self.get_model_names()
-        default_initializer_token = "★"
-        default_placeholder_token = ""
-        saved_args = self.saved_args
-
-        assert config is not None
-
-        try:
-            default = self.model_names.index(saved_args["model"])
-        except Exception:
-            pass
-
-        self.add_widget_intelligent(
-            npyscreen.FixedText,
-            value="Use ctrl-N and ctrl-P to move to the <N>ext and <P>revious fields, cursor arrows to make a selection, and space to toggle checkboxes.",
-            editable=False,
-        )
-
-        self.model = self.add_widget_intelligent(
-            npyscreen.TitleSelectOne,
-            name="Model Name:",
-            values=sorted(self.model_names),
-            value=default,
-            max_height=len(self.model_names) + 1,
-            scroll_exit=True,
-        )
-        self.placeholder_token = self.add_widget_intelligent(
-            npyscreen.TitleText,
-            name="Trigger Term:",
-            value="",  # saved_args.get('placeholder_token',''), # to restore previous term
-            scroll_exit=True,
-        )
-        self.placeholder_token.when_value_edited = self.initializer_changed
-        self.nextrely -= 1
-        self.nextrelx += 30
-        self.prompt_token = self.add_widget_intelligent(
-            npyscreen.FixedText,
-            name="Trigger term for use in prompt",
-            value="",
-            editable=False,
-            scroll_exit=True,
-        )
-        self.nextrelx -= 30
-        self.initializer_token = self.add_widget_intelligent(
-            npyscreen.TitleText,
-            name="Initializer:",
-            value=saved_args.get("initializer_token", default_initializer_token),
-            scroll_exit=True,
-        )
-        self.resume_from_checkpoint = self.add_widget_intelligent(
-            npyscreen.Checkbox,
-            name="Resume from last saved checkpoint",
-            value=False,
-            scroll_exit=True,
-        )
-        self.learnable_property = self.add_widget_intelligent(
-            npyscreen.TitleSelectOne,
-            name="Learnable property:",
-            values=self.learnable_properties,
-            value=self.learnable_properties.index(saved_args.get("learnable_property", "object")),
-            max_height=4,
-            scroll_exit=True,
-        )
-        self.train_data_dir = self.add_widget_intelligent(
-            npyscreen.TitleFilename,
-            name="Data Training Directory:",
-            select_dir=True,
-            must_exist=False,
-            value=str(
-                saved_args.get(
-                    "train_data_dir",
-                    config.root_dir / TRAINING_DATA / default_placeholder_token,
-                )
-            ),
-            scroll_exit=True,
-        )
-        self.output_dir = self.add_widget_intelligent(
-            npyscreen.TitleFilename,
-            name="Output Destination Directory:",
-            select_dir=True,
-            must_exist=False,
-            value=str(
-                saved_args.get(
-                    "output_dir",
-                    config.root_dir / TRAINING_DIR / default_placeholder_token,
-                )
-            ),
-            scroll_exit=True,
-        )
-        self.resolution = self.add_widget_intelligent(
-            npyscreen.TitleSelectOne,
-            name="Image resolution (pixels):",
-            values=self.resolutions,
-            value=self.resolutions.index(saved_args.get("resolution", 512)),
-            max_height=4,
-            scroll_exit=True,
-        )
-        self.center_crop = self.add_widget_intelligent(
-            npyscreen.Checkbox,
-            name="Center crop images before resizing to resolution",
-            value=saved_args.get("center_crop", False),
-            scroll_exit=True,
-        )
-        self.mixed_precision = self.add_widget_intelligent(
-            npyscreen.TitleSelectOne,
-            name="Mixed Precision:",
-            values=self.precisions,
-            value=self.precisions.index(saved_args.get("mixed_precision", "fp16")),
-            max_height=4,
-            scroll_exit=True,
-        )
-        self.num_train_epochs = self.add_widget_intelligent(
-            npyscreen.TitleSlider,
-            name="Number of training epochs:",
-            out_of=1000,
-            step=50,
-            lowest=1,
-            value=saved_args.get("num_train_epochs", 100),
-            scroll_exit=True,
-        )
-        self.max_train_steps = self.add_widget_intelligent(
-            npyscreen.TitleSlider,
-            name="Max Training Steps:",
-            out_of=10000,
-            step=500,
-            lowest=1,
-            value=saved_args.get("max_train_steps", 3000),
-            scroll_exit=True,
-        )
-        self.train_batch_size = self.add_widget_intelligent(
-            npyscreen.TitleSlider,
-            name="Batch Size (reduce if you run out of memory):",
-            out_of=50,
-            step=1,
-            lowest=1,
-            value=saved_args.get("train_batch_size", 8),
-            scroll_exit=True,
-        )
-        self.gradient_accumulation_steps = self.add_widget_intelligent(
-            npyscreen.TitleSlider,
-            name="Gradient Accumulation Steps (may need to decrease this to resume from a checkpoint):",
-            out_of=10,
-            step=1,
-            lowest=1,
-            value=saved_args.get("gradient_accumulation_steps", 4),
-            scroll_exit=True,
-        )
-        self.lr_warmup_steps = self.add_widget_intelligent(
-            npyscreen.TitleSlider,
-            name="Warmup Steps:",
-            out_of=100,
-            step=1,
-            lowest=0,
-            value=saved_args.get("lr_warmup_steps", 0),
-            scroll_exit=True,
-        )
-        self.learning_rate = self.add_widget_intelligent(
-            npyscreen.TitleText,
-            name="Learning Rate:",
-            value=str(
-                saved_args.get("learning_rate", "5.0e-04"),
-            ),
-            scroll_exit=True,
-        )
-        self.scale_lr = self.add_widget_intelligent(
-            npyscreen.Checkbox,
-            name="Scale learning rate by number GPUs, steps and batch size",
-            value=saved_args.get("scale_lr", True),
-            scroll_exit=True,
-        )
-        self.enable_xformers_memory_efficient_attention = self.add_widget_intelligent(
-            npyscreen.Checkbox,
-            name="Use xformers acceleration",
-            value=saved_args.get("enable_xformers_memory_efficient_attention", False),
-            scroll_exit=True,
-        )
-        self.lr_scheduler = self.add_widget_intelligent(
-            npyscreen.TitleSelectOne,
-            name="Learning rate scheduler:",
-            values=self.lr_schedulers,
-            max_height=7,
-            value=self.lr_schedulers.index(saved_args.get("lr_scheduler", "constant")),
-            scroll_exit=True,
-        )
-        self.model.editing = True
-
-    def initializer_changed(self) -> None:
-        placeholder = self.placeholder_token.value
-        self.prompt_token.value = f"(Trigger by using <{placeholder}> in your prompts)"
-        self.train_data_dir.value = str(config.root_dir / TRAINING_DATA / placeholder)
-        self.output_dir.value = str(config.root_dir / TRAINING_DIR / placeholder)
-        self.resume_from_checkpoint.value = Path(self.output_dir.value).exists()
-
-    def on_ok(self):
-        if self.validate_field_values():
-            self.parentApp.setNextForm(None)
-            self.editing = False
-            self.parentApp.ti_arguments = self.marshall_arguments()
-            npyscreen.notify("Launching textual inversion training. This will take a while...")
-        else:
-            self.editing = True
-
-    def ok_cancel(self):
-        sys.exit(0)
-
-    def validate_field_values(self) -> bool:
-        bad_fields = []
-        if self.model.value is None:
-            bad_fields.append("Model Name must correspond to a known model in models.yaml")
-        if not re.match("^[a-zA-Z0-9.-]+$", self.placeholder_token.value):
-            bad_fields.append("Trigger term must only contain alphanumeric characters, the dot and hyphen")
-        if self.train_data_dir.value is None:
-            bad_fields.append("Data Training Directory cannot be empty")
-        if self.output_dir.value is None:
-            bad_fields.append("The Output Destination Directory cannot be empty")
-        if len(bad_fields) > 0:
-            message = "The following problems were detected and must be corrected:"
-            for problem in bad_fields:
-                message += f"\n* {problem}"
-            npyscreen.notify_confirm(message)
-            return False
-        else:
-            return True
-
-    def get_model_names(self) -> Tuple[List[str], int]:
-        global config
-        assert config is not None
-        installer = initialize_installer(config)
-        store = installer.record_store
-        main_models = store.search_by_attr(model_type=ModelType.Main)
-        model_names = [f"{x.base.value}/{x.type.value}/{x.name}" for x in main_models if x.format == "diffusers"]
-        default = 0
-        return (model_names, default)
-
-    def marshall_arguments(self) -> dict:
-        args = {}
-
-        # the choices
-        args.update(
-            model=self.model_names[self.model.value[0]],
-            resolution=self.resolutions[self.resolution.value[0]],
-            lr_scheduler=self.lr_schedulers[self.lr_scheduler.value[0]],
-            mixed_precision=self.precisions[self.mixed_precision.value[0]],
-            learnable_property=self.learnable_properties[self.learnable_property.value[0]],
-        )
-
-        # all the strings and booleans
-        for attr in (
-            "initializer_token",
-            "placeholder_token",
-            "train_data_dir",
-            "output_dir",
-            "scale_lr",
-            "center_crop",
-            "enable_xformers_memory_efficient_attention",
-        ):
-            args[attr] = getattr(self, attr).value
-
-        # all the integers
-        for attr in (
-            "train_batch_size",
-            "gradient_accumulation_steps",
-            "num_train_epochs",
-            "max_train_steps",
-            "lr_warmup_steps",
-        ):
-            args[attr] = int(getattr(self, attr).value)
-
-        # the floats (just one)
-        args.update(learning_rate=float(self.learning_rate.value))
-
-        # a special case
-        if self.resume_from_checkpoint.value and Path(self.output_dir.value).exists():
-            args["resume_from_checkpoint"] = "latest"
-
-        return args
-
-
-class MyApplication(npyscreen.NPSAppManaged):
-    def __init__(self, saved_args: Optional[Dict[str, str]] = None):
-        super().__init__()
-        self.ti_arguments = None
-        self.saved_args = saved_args
-
-    def onStart(self):
-        npyscreen.setTheme(npyscreen.Themes.DefaultTheme)
-        self.main = self.addForm(
-            "MAIN",
-            textualInversionForm,
-            name="Textual Inversion Settings",
-            saved_args=self.saved_args,
-        )
-
-
-def copy_to_embeddings_folder(args: Dict[str, str]) -> None:
-    """
-    Copy learned_embeds.bin into the embeddings folder, and offer to
-    delete the full model and checkpoints.
-    """
-    assert config is not None
-    source = Path(args["output_dir"], "learned_embeds.bin")
-    dest_dir_name = args["placeholder_token"].strip("<>")
-    destination = config.root_dir / "embeddings" / dest_dir_name
-    os.makedirs(destination, exist_ok=True)
-    logger.info(f"Training completed. Copying learned_embeds.bin into {str(destination)}")
-    shutil.copy(source, destination)
-    if (input("Delete training logs and intermediate checkpoints? [y] ") or "y").startswith(("y", "Y")):
-        shutil.rmtree(Path(args["output_dir"]))
-    else:
-        logger.info(f'Keeping {args["output_dir"]}')
-
-
-def save_args(args: dict) -> None:
-    """
-    Save the current argument values to an omegaconf file
-    """
-    assert config is not None
-    dest_dir = config.root_dir / TRAINING_DIR
-    os.makedirs(dest_dir, exist_ok=True)
-    conf_file = dest_dir / CONF_FILE
-    conf = OmegaConf.create(args)
-    OmegaConf.save(config=conf, f=conf_file)
-
-
-def previous_args() -> dict:
-    """
-    Get the previous arguments used.
-    """
-    assert config is not None
-    conf_file = config.root_dir / TRAINING_DIR / CONF_FILE
-    try:
-        conf = OmegaConf.load(conf_file)
-        conf["placeholder_token"] = conf["placeholder_token"].strip("<>")
-    except Exception:
-        conf = None
-
-    return conf
-
-
-def do_front_end() -> None:
-    global config
-    saved_args = previous_args()
-    myapplication = MyApplication(saved_args=saved_args)
-    myapplication.run()
-
-    if my_args := myapplication.ti_arguments:
-        os.makedirs(my_args["output_dir"], exist_ok=True)
-
-        # Automatically add angle brackets around the trigger
-        if not re.match("^<.+>$", my_args["placeholder_token"]):
-            my_args["placeholder_token"] = f"<{my_args['placeholder_token']}>"
-
-        my_args["only_save_embeds"] = True
-        save_args(my_args)
-
-        try:
-            print(my_args)
-            do_textual_inversion_training(config, **my_args)
-            copy_to_embeddings_folder(my_args)
-        except Exception as e:
-            logger.error("An exception occurred during training. The exception was:")
-            logger.error(str(e))
-            logger.error("DETAILS:")
-            logger.error(traceback.format_exc())
-
-
-def main() -> None:
-    global config
-
-    args: Namespace = parse_args()
-    config = InvokeAIAppConfig.get_config()
-    config.parse_args([])
-
-    # change root if needed
-    if args.root_dir:
-        config.root = args.root_dir
-
-    try:
-        if args.front_end:
-            do_front_end()
-        else:
-            do_textual_inversion_training(config, **vars(args))
-    except AssertionError as e:
-        logger.error(e)
-        sys.exit(-1)
-    except KeyboardInterrupt:
-        pass
-    except (widget.NotEnoughSpaceForWidget, Exception) as e:
-        if str(e).startswith("Height of 1 allocated"):
-            logger.error("You need to have at least one diffusers models defined in models.yaml in order to train")
-        elif str(e).startswith("addwstr"):
-            logger.error("Not enough window space for the interface. Please make your window larger and try again.")
-        else:
-            logger.error(e)
-        sys.exit(-1)
-
-
-if __name__ == "__main__":
-    main()
diff --git a/invokeai/frontend/web/public/locales/en.json b/invokeai/frontend/web/public/locales/en.json
index 9abf0b80aa..a458563fd5 100644
--- a/invokeai/frontend/web/public/locales/en.json
+++ b/invokeai/frontend/web/public/locales/en.json
@@ -814,7 +814,7 @@
         "simpleModelDesc": "Provide a path to a local Diffusers model, local checkpoint / safetensors model a HuggingFace Repo ID, or a checkpoint/diffusers model URL.",
         "statusConverting": "Converting",
         "syncModels": "Sync Models",
-        "syncModelsDesc": "If your models are out of sync with the backend, you can refresh them up using this option. This is generally handy in cases where you manually update your models.yaml file or add models to the InvokeAI root folder after the application has booted.",
+        "syncModelsDesc": "If your models are out of sync with the backend, you can refresh them up using this option. This is generally handy in cases where you add models to the InvokeAI root folder or autoimport directory after the application has booted.",
         "updateModel": "Update Model",
         "useCustomConfig": "Use Custom Config",
         "v1": "v1",

From 65dd4f4abc15fa60c0f7b8d9e5cd915a9d418598 Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lstein@gmail.com>
Date: Wed, 21 Feb 2024 11:46:23 -0500
Subject: [PATCH 239/411] fix repo-id for the Deliberate v5 model

prevent lora and embedding file suffixes from being stripped during installation

apply psychedelicious patch to get compel to load proper TI embedding
---
 .../app/services/model_install/model_install_default.py     | 6 +++++-
 invokeai/configs/INITIAL_MODELS.yaml                        | 2 +-
 2 files changed, 6 insertions(+), 2 deletions(-)

diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py
index 7dee8bfd8c..9b771c5159 100644
--- a/invokeai/app/services/model_install/model_install_default.py
+++ b/invokeai/app/services/model_install/model_install_default.py
@@ -154,8 +154,12 @@ class ModelInstallService(ModelInstallServiceBase):
 
         info: AnyModelConfig = self._probe_model(Path(model_path), config)
         old_hash = info.current_hash
+
+        if preferred_name := config.get("name"):
+            preferred_name = Path(preferred_name).with_suffix(model_path.suffix)
+
         dest_path = (
-            self.app_config.models_path / info.base.value / info.type.value / (config.get("name") or model_path.name)
+            self.app_config.models_path / info.base.value / info.type.value / (preferred_name or model_path.name)
         )
         try:
             new_path = self._copy_model(model_path, dest_path)
diff --git a/invokeai/configs/INITIAL_MODELS.yaml b/invokeai/configs/INITIAL_MODELS.yaml
index ca2283ab81..811121d1ba 100644
--- a/invokeai/configs/INITIAL_MODELS.yaml
+++ b/invokeai/configs/INITIAL_MODELS.yaml
@@ -34,7 +34,7 @@ sd-1/main/Analog-Diffusion:
    recommended: False
 sd-1/main/Deliberate:
    description: Versatile model that produces detailed images up to 768px (4.27 GB)
-   source: XpucT/Deliberate
+   source: stablediffusionapi/deliberate-v5
    recommended: False
 sd-1/main/Dungeons-and-Diffusion:
    description: Dungeons & Dragons characters (2.13 GB)

From 1cec0bb1793131a5b138a3e0ec84f8623a2e6015 Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lstein@gmail.com>
Date: Wed, 21 Feb 2024 17:40:53 -0500
Subject: [PATCH 240/411] use official Deliberate download repo

---
 invokeai/configs/INITIAL_MODELS.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/invokeai/configs/INITIAL_MODELS.yaml b/invokeai/configs/INITIAL_MODELS.yaml
index 811121d1ba..8ad788fba7 100644
--- a/invokeai/configs/INITIAL_MODELS.yaml
+++ b/invokeai/configs/INITIAL_MODELS.yaml
@@ -34,7 +34,7 @@ sd-1/main/Analog-Diffusion:
    recommended: False
 sd-1/main/Deliberate:
    description: Versatile model that produces detailed images up to 768px (4.27 GB)
-   source: stablediffusionapi/deliberate-v5
+   source: https://huggingface.co/XpucT/Deliberate/resolve/main/Deliberate_v5.safetensors?download=true
    recommended: False
 sd-1/main/Dungeons-and-Diffusion:
    description: Dungeons & Dragons characters (2.13 GB)

From cc41e8912cf3e80f2d7adc438fc81f83635dfa59 Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lstein@gmail.com>
Date: Wed, 21 Feb 2024 17:15:54 -0500
Subject: [PATCH 241/411] several small model install enhancements

- Support extended HF repoid syntax in TUI. This allows
  installation of subfolders and safetensors files, as in
  `XpucT/Deliberate::Deliberate_v5.safetensors`

- Add `error` and `error_traceback` properties to the install
  job objects.

- Rename the `heuristic_import` route to `heuristic_install`.

- Fix the example `config` input in the `heuristic_install` route.
---
 invokeai/app/api/routers/model_manager.py     |  8 ++--
 .../model_install/model_install_base.py       | 13 ++++--
 invokeai/backend/install/install_helper.py    | 42 +++----------------
 .../model_install/test_model_install.py       |  2 +-
 4 files changed, 20 insertions(+), 45 deletions(-)

diff --git a/invokeai/app/api/routers/model_manager.py b/invokeai/app/api/routers/model_manager.py
index aee457406a..f57f5f97b6 100644
--- a/invokeai/app/api/routers/model_manager.py
+++ b/invokeai/app/api/routers/model_manager.py
@@ -382,8 +382,8 @@ async def add_model_record(
 
 
 @model_manager_router.post(
-    "/heuristic_import",
-    operation_id="heuristic_import_model",
+    "/heuristic_install",
+    operation_id="heuristic_install_model",
     responses={
         201: {"description": "The model imported successfully"},
         415: {"description": "Unrecognized file/folder format"},
@@ -392,12 +392,12 @@ async def add_model_record(
     },
     status_code=201,
 )
-async def heuristic_import(
+async def heuristic_install(
     source: str,
     config: Optional[Dict[str, Any]] = Body(
         description="Dict of fields that override auto-probed values in the model config record, such as name, description and prediction_type ",
         default=None,
-        example={"name": "modelT", "description": "antique cars"},
+        example={"name": "string", "description": "string"},
     ),
     access_token: Optional[str] = None,
 ) -> ModelInstallJob:
diff --git a/invokeai/app/services/model_install/model_install_base.py b/invokeai/app/services/model_install/model_install_base.py
index 080219af75..d1e8e4f8e5 100644
--- a/invokeai/app/services/model_install/model_install_base.py
+++ b/invokeai/app/services/model_install/model_install_base.py
@@ -177,6 +177,12 @@ class ModelInstallJob(BaseModel):
     download_parts: Set[DownloadJob] = Field(
         default_factory=set, description="Download jobs contributing to this install"
     )
+    error: Optional[str] = Field(
+        default=None, description="On an error condition, this field will contain the text of the exception"
+    )
+    error_traceback: Optional[str] = Field(
+        default=None, description="On an error condition, this field will contain the exception traceback"
+    )
     # internal flags and transitory settings
     _install_tmpdir: Optional[Path] = PrivateAttr(default=None)
     _exception: Optional[Exception] = PrivateAttr(default=None)
@@ -184,6 +190,8 @@ class ModelInstallJob(BaseModel):
     def set_error(self, e: Exception) -> None:
         """Record the error and traceback from an exception."""
         self._exception = e
+        self.error = str(e)
+        self.error_traceback = self._format_error(e)
         self.status = InstallStatus.ERROR
 
     def cancel(self) -> None:
@@ -195,10 +203,9 @@ class ModelInstallJob(BaseModel):
         """Class name of the exception that led to status==ERROR."""
         return self._exception.__class__.__name__ if self._exception else None
 
-    @property
-    def error(self) -> Optional[str]:
+    def _format_error(self, exception: Exception) -> str:
         """Error traceback."""
-        return "".join(traceback.format_exception(self._exception)) if self._exception else None
+        return "".join(traceback.format_exception(exception))
 
     @property
     def cancelled(self) -> bool:
diff --git a/invokeai/backend/install/install_helper.py b/invokeai/backend/install/install_helper.py
index 3623b623a9..999dcdd100 100644
--- a/invokeai/backend/install/install_helper.py
+++ b/invokeai/backend/install/install_helper.py
@@ -1,14 +1,11 @@
 """Utility (backend) functions used by model_install.py"""
-import re
 from logging import Logger
 from pathlib import Path
 from typing import Any, Dict, List, Optional
 
 import omegaconf
-from huggingface_hub import HfFolder
 from pydantic import BaseModel, Field
 from pydantic.dataclasses import dataclass
-from pydantic.networks import AnyHttpUrl
 from requests import HTTPError
 from tqdm import tqdm
 
@@ -18,12 +15,8 @@ from invokeai.app.services.download import DownloadQueueService
 from invokeai.app.services.events.events_base import EventServiceBase
 from invokeai.app.services.image_files.image_files_disk import DiskImageFileStorage
 from invokeai.app.services.model_install import (
-    HFModelSource,
-    LocalModelSource,
     ModelInstallService,
     ModelInstallServiceBase,
-    ModelSource,
-    URLModelSource,
 )
 from invokeai.app.services.model_metadata import ModelMetadataStoreSQL
 from invokeai.app.services.model_records import ModelRecordServiceBase, ModelRecordServiceSQL
@@ -31,7 +24,6 @@ from invokeai.app.services.shared.sqlite.sqlite_util import init_db
 from invokeai.backend.model_manager import (
     BaseModelType,
     InvalidModelConfigException,
-    ModelRepoVariant,
     ModelType,
 )
 from invokeai.backend.model_manager.metadata import UnknownMetadataException
@@ -226,37 +218,13 @@ class InstallHelper(object):
                     additional_models.append(reverse_source[requirement])
         model_list.extend(additional_models)
 
-    def _make_install_source(self, model_info: UnifiedModelInfo) -> ModelSource:
-        assert model_info.source
-        model_path_id_or_url = model_info.source.strip("\"' ")
-        model_path = Path(model_path_id_or_url)
-
-        if model_path.exists():  # local file on disk
-            return LocalModelSource(path=model_path.absolute(), inplace=True)
-
-        # parsing huggingface repo ids
-        # we're going to do a little trick that allows for extended repo_ids of form "foo/bar:fp16"
-        variants = "|".join([x.lower() for x in ModelRepoVariant.__members__])
-        if match := re.match(f"^([^/]+/[^/]+?)(?::({variants}))?$", model_path_id_or_url):
-            repo_id = match.group(1)
-            repo_variant = ModelRepoVariant(match.group(2)) if match.group(2) else None
-            subfolder = Path(model_info.subfolder) if model_info.subfolder else None
-            return HFModelSource(
-                repo_id=repo_id,
-                access_token=HfFolder.get_token(),
-                subfolder=subfolder,
-                variant=repo_variant,
-            )
-        if re.match(r"^(http|https):", model_path_id_or_url):
-            return URLModelSource(url=AnyHttpUrl(model_path_id_or_url))
-        raise ValueError(f"Unsupported model source: {model_path_id_or_url}")
-
     def add_or_delete(self, selections: InstallSelections) -> None:
         """Add or delete selected models."""
         installer = self._installer
         self._add_required_models(selections.install_models)
         for model in selections.install_models:
-            source = self._make_install_source(model)
+            assert model.source
+            model_path_id_or_url = model.source.strip("\"' ")
             config = (
                 {
                     "description": model.description,
@@ -267,12 +235,12 @@ class InstallHelper(object):
             )
 
             try:
-                installer.import_model(
-                    source=source,
+                installer.heuristic_import(
+                    source=model_path_id_or_url,
                     config=config,
                 )
             except (UnknownMetadataException, InvalidModelConfigException, HTTPError, OSError) as e:
-                self._logger.warning(f"{source}: {e}")
+                self._logger.warning(f"{model.source}: {e}")
 
         for model_to_remove in selections.remove_models:
             parts = model_to_remove.split("/")
diff --git a/tests/app/services/model_install/test_model_install.py b/tests/app/services/model_install/test_model_install.py
index 55f7e86541..80b106c5cb 100644
--- a/tests/app/services/model_install/test_model_install.py
+++ b/tests/app/services/model_install/test_model_install.py
@@ -256,4 +256,4 @@ def test_404_download(mm2_installer: ModelInstallServiceBase, mm2_app_config: In
     assert job.error_type == "HTTPError"
     assert job.error
     assert "NOT FOUND" in job.error
-    assert "Traceback" in job.error
+    assert job.error_traceback.startswith("Traceback")

From 0d9fbe5e043b2abde5cf28a9021b51c9d8ac4459 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Thu, 22 Feb 2024 17:19:08 +1100
Subject: [PATCH 242/411] feat(ui): replace `type-fest` with `utility-types`

- The new package has more useful types
- Only used `JsonObject` from `type-fest`; added an implementation of that type
---
 invokeai/frontend/web/package.json            |  2 +-
 invokeai/frontend/web/pnpm-lock.yaml          | 16 ++---
 invokeai/frontend/web/src/app/store/store.ts  |  4 +-
 invokeai/frontend/web/src/common/types.ts     |  7 ++
 .../src/features/nodes/util/graph/metadata.ts |  4 +-
 .../nodes/util/workflow/validateWorkflow.ts   |  4 +-
 .../frontend/web/src/services/api/types.ts    | 70 ++++++++++++++-----
 7 files changed, 73 insertions(+), 34 deletions(-)
 create mode 100644 invokeai/frontend/web/src/common/types.ts

diff --git a/invokeai/frontend/web/package.json b/invokeai/frontend/web/package.json
index 743cb1e09d..0bf236ee38 100644
--- a/invokeai/frontend/web/package.json
+++ b/invokeai/frontend/web/package.json
@@ -99,7 +99,6 @@
     "roarr": "^7.21.0",
     "serialize-error": "^11.0.3",
     "socket.io-client": "^4.7.4",
-    "type-fest": "^4.10.2",
     "use-debounce": "^10.0.0",
     "use-image": "^1.1.1",
     "uuid": "^9.0.1",
@@ -146,6 +145,7 @@
     "ts-toolbelt": "^9.6.0",
     "tsafe": "^1.6.6",
     "typescript": "^5.3.3",
+    "utility-types": "^3.11.0",
     "vite": "^5.1.3",
     "vite-plugin-css-injected-by-js": "^3.4.0",
     "vite-plugin-dts": "^3.7.2",
diff --git a/invokeai/frontend/web/pnpm-lock.yaml b/invokeai/frontend/web/pnpm-lock.yaml
index 9e873102e6..f2abdd87bf 100644
--- a/invokeai/frontend/web/pnpm-lock.yaml
+++ b/invokeai/frontend/web/pnpm-lock.yaml
@@ -152,9 +152,6 @@ dependencies:
   socket.io-client:
     specifier: ^4.7.4
     version: 4.7.4
-  type-fest:
-    specifier: ^4.10.2
-    version: 4.10.2
   use-debounce:
     specifier: ^10.0.0
     version: 10.0.0(react@18.2.0)
@@ -271,6 +268,9 @@ devDependencies:
   typescript:
     specifier: ^5.3.3
     version: 5.3.3
+  utility-types:
+    specifier: ^3.11.0
+    version: 3.11.0
   vite:
     specifier: ^5.1.3
     version: 5.1.3(@types/node@20.11.19)
@@ -13827,11 +13827,6 @@ packages:
     resolution: {integrity: sha512-RAH822pAdBgcNMAfWnCBU3CFZcfZ/i1eZjwFU/dsLKumyuuP3niueg2UAukXYF0E2AAoc82ZSSf9J0WQBinzHA==}
     engines: {node: '>=12.20'}
 
-  /type-fest@4.10.2:
-    resolution: {integrity: sha512-anpAG63wSpdEbLwOqH8L84urkL6PiVIov3EMmgIhhThevh9aiMQov+6Btx0wldNcvm4wV+e2/Rt1QdDwKHFbHw==}
-    engines: {node: '>=16'}
-    dev: false
-
   /type-is@1.6.18:
     resolution: {integrity: sha512-TkRKr9sUTxEH8MdfuCSP7VizJyzRNMjj2J2do2Jr3Kym598JVdEksuzPQCnlFPW4ky9Q+iA+ma9BGm06XQBy8g==}
     engines: {node: '>= 0.6'}
@@ -14152,6 +14147,11 @@ packages:
       which-typed-array: 1.1.14
     dev: true
 
+  /utility-types@3.11.0:
+    resolution: {integrity: sha512-6Z7Ma2aVEWisaL6TvBCy7P8rm2LQoPv6dJ7ecIaIixHcwfbJ0x7mWdbcwlIM5IGQxPZSFYeqRCqlOOeKoJYMkw==}
+    engines: {node: '>= 4'}
+    dev: true
+
   /utils-merge@1.0.1:
     resolution: {integrity: sha512-pMZTvIkT1d+TFGvDOqodOclx0QWkkgi6Tdoa8gC8ffGAAqz9pzPTZWAybbsHHoED/ztMtkv/VoYTYyShUn81hA==}
     engines: {node: '>= 0.4.0'}
diff --git a/invokeai/frontend/web/src/app/store/store.ts b/invokeai/frontend/web/src/app/store/store.ts
index 270662c3d2..16f1632d88 100644
--- a/invokeai/frontend/web/src/app/store/store.ts
+++ b/invokeai/frontend/web/src/app/store/store.ts
@@ -3,6 +3,7 @@ import { autoBatchEnhancer, combineReducers, configureStore } from '@reduxjs/too
 import { logger } from 'app/logging/logger';
 import { idbKeyValDriver } from 'app/store/enhancers/reduxRemember/driver';
 import { errorHandler } from 'app/store/enhancers/reduxRemember/errors';
+import type { JSONObject } from 'common/types';
 import { canvasPersistConfig, canvasSlice } from 'features/canvas/store/canvasSlice';
 import { changeBoardModalSlice } from 'features/changeBoardModal/store/slice';
 import {
@@ -32,7 +33,6 @@ import { rememberEnhancer, rememberReducer } from 'redux-remember';
 import { serializeError } from 'serialize-error';
 import { api } from 'services/api';
 import { authToastMiddleware } from 'services/api/authToastMiddleware';
-import type { JsonObject } from 'type-fest';
 
 import { STORAGE_PREFIX } from './constants';
 import { actionSanitizer } from './middleware/devtools/actionSanitizer';
@@ -125,7 +125,7 @@ const unserialize: UnserializeFunction = (data, key) => {
       {
         persistedData: parsed,
         rehydratedData: transformed,
-        diff: diff(parsed, transformed) as JsonObject, // this is always serializable
+        diff: diff(parsed, transformed) as JSONObject, // this is always serializable
       },
       `Rehydrated slice "${key}"`
     );
diff --git a/invokeai/frontend/web/src/common/types.ts b/invokeai/frontend/web/src/common/types.ts
new file mode 100644
index 0000000000..29a411788d
--- /dev/null
+++ b/invokeai/frontend/web/src/common/types.ts
@@ -0,0 +1,7 @@
+export type JSONValue = string | number | boolean | null | JSONValue[] | { [key: string]: JSONValue };
+
+export interface JSONObject {
+  [k: string]: JSONValue;
+}
+
+export interface JSONArray extends Array<JSONValue> {}
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/metadata.ts b/invokeai/frontend/web/src/features/nodes/util/graph/metadata.ts
index 781ce57ebc..c48f54d191 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/metadata.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/metadata.ts
@@ -1,5 +1,5 @@
+import type { JSONObject } from 'common/types';
 import type { CoreMetadataInvocation, NonNullableGraph } from 'services/api/types';
-import type { JsonObject } from 'type-fest';
 
 import { METADATA } from './constants';
 
@@ -30,7 +30,7 @@ export const addCoreMetadataNode = (
 
 export const upsertMetadata = (
   graph: NonNullableGraph,
-  metadata: Partial<CoreMetadataInvocation> | JsonObject
+  metadata: Partial<CoreMetadataInvocation> | JSONObject
 ): void => {
   const metadataNode = graph.nodes[METADATA] as CoreMetadataInvocation | undefined;
 
diff --git a/invokeai/frontend/web/src/features/nodes/util/workflow/validateWorkflow.ts b/invokeai/frontend/web/src/features/nodes/util/workflow/validateWorkflow.ts
index 5096e588b0..b402f2f8af 100644
--- a/invokeai/frontend/web/src/features/nodes/util/workflow/validateWorkflow.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/workflow/validateWorkflow.ts
@@ -1,3 +1,4 @@
+import type { JSONObject } from 'common/types';
 import { parseify } from 'common/util/serialize';
 import type { InvocationTemplate } from 'features/nodes/types/invocation';
 import type { WorkflowV3 } from 'features/nodes/types/workflow';
@@ -5,14 +6,13 @@ import { isWorkflowInvocationNode } from 'features/nodes/types/workflow';
 import { getNeedsUpdate } from 'features/nodes/util/node/nodeUpdate';
 import { t } from 'i18next';
 import { keyBy } from 'lodash-es';
-import type { JsonObject } from 'type-fest';
 
 import { parseAndMigrateWorkflow } from './migrations';
 
 type WorkflowWarning = {
   message: string;
   issues?: string[];
-  data: JsonObject;
+  data: JSONObject;
 };
 
 type ValidateWorkflowResult = {
diff --git a/invokeai/frontend/web/src/services/api/types.ts b/invokeai/frontend/web/src/services/api/types.ts
index aaa70a2684..d561173337 100644
--- a/invokeai/frontend/web/src/services/api/types.ts
+++ b/invokeai/frontend/web/src/services/api/types.ts
@@ -2,7 +2,7 @@ import type { UseToastOptions } from '@invoke-ai/ui-library';
 import type { EntityState } from '@reduxjs/toolkit';
 import type { components, paths } from 'services/api/schema';
 import type { O } from 'ts-toolbelt';
-import type { SetRequired } from 'type-fest';
+import type { Overwrite } from 'utility-types';
 
 export type S = components['schemas'];
 
@@ -61,28 +61,60 @@ export type IPAdapterField = S['IPAdapterField'];
 // Model Configs
 
 // TODO(MM2): Can we make key required in the pydantic model?
-type KeyRequired<T extends { key?: string }> = SetRequired<T, 'key'>;
-export type LoRAConfig = KeyRequired<S['LoRAConfig']>;
+export type LoRAModelConfig = S['LoRAConfig'];
 // TODO(MM2): Can we rename this from Vae -> VAE
-export type VAEConfig = KeyRequired<S['VaeCheckpointConfig']> | KeyRequired<S['VaeDiffusersConfig']>;
-export type ControlNetConfig =
-  | KeyRequired<S['ControlNetDiffusersConfig']>
-  | KeyRequired<S['ControlNetCheckpointConfig']>;
-export type IPAdapterConfig = KeyRequired<S['IPAdapterConfig']>;
+export type VAEModelConfig = S['VaeCheckpointConfig'] | S['VaeDiffusersConfig'];
+export type ControlNetModelConfig = S['ControlNetDiffusersConfig'] | S['ControlNetCheckpointConfig'];
+export type IPAdapterModelConfig = S['IPAdapterConfig'];
 // TODO(MM2): Can we rename this to T2IAdapterConfig
-export type T2IAdapterConfig = KeyRequired<S['T2IConfig']>;
-export type TextualInversionConfig = KeyRequired<S['TextualInversionConfig']>;
-export type DiffusersModelConfig = KeyRequired<S['MainDiffusersConfig']>;
-export type CheckpointModelConfig = KeyRequired<S['MainCheckpointConfig']>;
+export type T2IAdapterModelConfig = S['T2IConfig'];
+export type TextualInversionModelConfig = S['TextualInversionConfig'];
+export type DiffusersModelConfig = S['MainDiffusersConfig'];
+export type CheckpointModelConfig = S['MainCheckpointConfig'];
 export type MainModelConfig = DiffusersModelConfig | CheckpointModelConfig;
+export type RefinerMainModelConfig = Overwrite<MainModelConfig, { base: 'sdxl-refiner' }>;
+export type NonRefinerMainModelConfig = Overwrite<MainModelConfig, { base: 'any' | 'sd-1' | 'sd-2' | 'sdxl' }>;
 export type AnyModelConfig =
-  | LoRAConfig
-  | VAEConfig
-  | ControlNetConfig
-  | IPAdapterConfig
-  | T2IAdapterConfig
-  | TextualInversionConfig
-  | MainModelConfig;
+  | LoRAModelConfig
+  | VAEModelConfig
+  | ControlNetModelConfig
+  | IPAdapterModelConfig
+  | T2IAdapterModelConfig
+  | TextualInversionModelConfig
+  | RefinerMainModelConfig
+  | NonRefinerMainModelConfig;
+
+export const isLoRAModelConfig = (config: AnyModelConfig): config is LoRAModelConfig => {
+  return config.type === 'lora';
+};
+
+export const isVAEModelConfig = (config: AnyModelConfig): config is VAEModelConfig => {
+  return config.type === 'vae';
+};
+
+export const isControlNetModelConfig = (config: AnyModelConfig): config is ControlNetModelConfig => {
+  return config.type === 'controlnet';
+};
+
+export const isIPAdapterModelConfig = (config: AnyModelConfig): config is IPAdapterModelConfig => {
+  return config.type === 'ip_adapter';
+};
+
+export const isT2IAdapterModelConfig = (config: AnyModelConfig): config is T2IAdapterModelConfig => {
+  return config.type === 't2i_adapter';
+};
+
+export const isTextualInversionModelConfig = (config: AnyModelConfig): config is TextualInversionModelConfig => {
+  return config.type === 'embedding';
+};
+
+export const isNonRefinerMainModelConfig = (config: AnyModelConfig): config is NonRefinerMainModelConfig => {
+  return config.type === 'main' && config.base !== 'sdxl-refiner';
+};
+
+export const isRefinerMainModelModelConfig = (config: AnyModelConfig): config is RefinerMainModelConfig => {
+  return config.type === 'main' && config.base === 'sdxl-refiner';
+};
 
 export type MergeModelConfig = S['Body_merge'];
 export type ImportModelConfig = S['Body_import_model'];

From 239ecfaf7905f6349a7a8fccabfebabce72ce243 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Thu, 22 Feb 2024 17:21:37 +1100
Subject: [PATCH 243/411] fix(nodes): make fields on `ModelConfigBase` required

The setup of `ModelConfigBase` means autogenerated types have critical fields flagged as nullable (like `key` and `base`). Need to manually flag them as required.
---
 invokeai/backend/model_manager/config.py | 7 +++++++
 1 file changed, 7 insertions(+)

diff --git a/invokeai/backend/model_manager/config.py b/invokeai/backend/model_manager/config.py
index bc4848b0a5..fb0593a651 100644
--- a/invokeai/backend/model_manager/config.py
+++ b/invokeai/backend/model_manager/config.py
@@ -138,9 +138,16 @@ class ModelConfigBase(BaseModel):
     source: Optional[str] = Field(description="model original source (path, URL or repo_id)", default=None)
     last_modified: Optional[float] = Field(description="timestamp for modification time", default_factory=time.time)
 
+    @staticmethod
+    def json_schema_extra(schema: dict[str, Any], model_class: Type[BaseModel]) -> None:
+        schema["required"].extend(
+            ["key", "base", "type", "format", "original_hash", "current_hash", "source", "last_modified"]
+        )
+
     model_config = ConfigDict(
         use_enum_values=False,
         validate_assignment=True,
+        json_schema_extra=json_schema_extra,
     )
 
     def update(self, attributes: Dict[str, Any]) -> None:

From 79b16596b55cd6ec8503458c8b4a63d3ae965a5c Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Thu, 22 Feb 2024 17:21:46 +1100
Subject: [PATCH 244/411] chore(ui): typegen

---
 .../frontend/web/src/services/api/schema.ts   | 190 +++++++++---------
 1 file changed, 95 insertions(+), 95 deletions(-)

diff --git a/invokeai/frontend/web/src/services/api/schema.ts b/invokeai/frontend/web/src/services/api/schema.ts
index 2115e79768..3566fdb9e2 100644
--- a/invokeai/frontend/web/src/services/api/schema.ts
+++ b/invokeai/frontend/web/src/services/api/schema.ts
@@ -1420,7 +1420,7 @@ export type components = {
        * @default clip_vision
        * @constant
        */
-      type?: "clip_vision";
+      type: "clip_vision";
       /**
        * Format
        * @constant
@@ -1431,17 +1431,17 @@ export type components = {
        * @description unique key for model
        * @default <NOKEY>
        */
-      key?: string;
+      key: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash?: string | null;
+      original_hash: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash?: string | null;
+      current_hash: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -1451,12 +1451,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source?: string | null;
+      source: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified?: number | null;
+      last_modified: number | null;
     };
     /** CLIPVisionModelField */
     CLIPVisionModelField: {
@@ -2538,29 +2538,29 @@ export type components = {
        * @default controlnet
        * @constant
        */
-      type?: "controlnet";
+      type: "controlnet";
       /**
        * Format
        * @default checkpoint
        * @constant
        */
-      format?: "checkpoint";
+      format: "checkpoint";
       /**
        * Key
        * @description unique key for model
        * @default <NOKEY>
        */
-      key?: string;
+      key: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash?: string | null;
+      original_hash: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash?: string | null;
+      current_hash: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -2570,12 +2570,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source?: string | null;
+      source: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified?: number | null;
+      last_modified: number | null;
       /**
        * Config
        * @description path to the checkpoint model config file
@@ -2604,29 +2604,29 @@ export type components = {
        * @default controlnet
        * @constant
        */
-      type?: "controlnet";
+      type: "controlnet";
       /**
        * Format
        * @default diffusers
        * @constant
        */
-      format?: "diffusers";
+      format: "diffusers";
       /**
        * Key
        * @description unique key for model
        * @default <NOKEY>
        */
-      key?: string;
+      key: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash?: string | null;
+      original_hash: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash?: string | null;
+      current_hash: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -2636,12 +2636,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source?: string | null;
+      source: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified?: number | null;
+      last_modified: number | null;
       /** @default */
       repo_variant?: components["schemas"]["ModelRepoVariant"] | null;
     };
@@ -4214,7 +4214,7 @@ export type components = {
        * @description The nodes in this graph
        */
       nodes: {
-        [key: string]: components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["ColorMapImageProcessorInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["DWOpenposeImageProcessorInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["DepthAnythingImageProcessorInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["FaceOffInvocation"];
+        [key: string]: components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["ColorMapImageProcessorInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["DWOpenposeImageProcessorInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["DepthAnythingImageProcessorInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["LatentsCollectionInvocation"];
       };
       /**
        * Edges
@@ -4251,7 +4251,7 @@ export type components = {
        * @description The results of node executions
        */
       results: {
-        [key: string]: components["schemas"]["ModelLoaderOutput"] | components["schemas"]["MetadataOutput"] | components["schemas"]["String2Output"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["ClipSkipInvocationOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["VAEOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["LoraLoaderOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["SDXLLoraLoaderOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["LatentsOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["StringCollectionOutput"];
+        [key: string]: components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["VAEOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["LoraLoaderOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["MetadataOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["ClipSkipInvocationOutput"] | components["schemas"]["String2Output"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["SDXLLoraLoaderOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["LatentsOutput"] | components["schemas"]["IdealSizeOutput"];
       };
       /**
        * Errors
@@ -4422,7 +4422,7 @@ export type components = {
        * @default ip_adapter
        * @constant
        */
-      type?: "ip_adapter";
+      type: "ip_adapter";
       /**
        * Format
        * @constant
@@ -4433,17 +4433,17 @@ export type components = {
        * @description unique key for model
        * @default <NOKEY>
        */
-      key?: string;
+      key: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash?: string | null;
+      original_hash: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash?: string | null;
+      current_hash: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -4453,12 +4453,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source?: string | null;
+      source: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified?: number | null;
+      last_modified: number | null;
       /** Image Encoder Model Id */
       image_encoder_model_id: string;
     };
@@ -6506,7 +6506,7 @@ export type components = {
        * @default lora
        * @constant
        */
-      type?: "lora";
+      type: "lora";
       /**
        * Format
        * @enum {string}
@@ -6517,17 +6517,17 @@ export type components = {
        * @description unique key for model
        * @default <NOKEY>
        */
-      key?: string;
+      key: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash?: string | null;
+      original_hash: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash?: string | null;
+      current_hash: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -6537,12 +6537,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source?: string | null;
+      source: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified?: number | null;
+      last_modified: number | null;
     };
     /**
      * LoRAMetadataField
@@ -6706,29 +6706,29 @@ export type components = {
        * @default main
        * @constant
        */
-      type?: "main";
+      type: "main";
       /**
        * Format
        * @default checkpoint
        * @constant
        */
-      format?: "checkpoint";
+      format: "checkpoint";
       /**
        * Key
        * @description unique key for model
        * @default <NOKEY>
        */
-      key?: string;
+      key: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash?: string | null;
+      original_hash: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash?: string | null;
+      current_hash: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -6738,12 +6738,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source?: string | null;
+      source: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified?: number | null;
+      last_modified: number | null;
       /** Vae */
       vae?: string | null;
       /** @default normal */
@@ -6788,29 +6788,29 @@ export type components = {
        * @default main
        * @constant
        */
-      type?: "main";
+      type: "main";
       /**
        * Format
        * @default diffusers
        * @constant
        */
-      format?: "diffusers";
+      format: "diffusers";
       /**
        * Key
        * @description unique key for model
        * @default <NOKEY>
        */
-      key?: string;
+      key: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash?: string | null;
+      original_hash: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash?: string | null;
+      current_hash: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -6820,12 +6820,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source?: string | null;
+      source: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified?: number | null;
+      last_modified: number | null;
       /** Vae */
       vae?: string | null;
       /** @default normal */
@@ -7758,13 +7758,13 @@ export type components = {
        * @default sd-1
        * @constant
        */
-      base?: "sd-1";
+      base: "sd-1";
       /**
        * Type
        * @default onnx
        * @constant
        */
-      type?: "onnx";
+      type: "onnx";
       /**
        * Format
        * @enum {string}
@@ -7775,17 +7775,17 @@ export type components = {
        * @description unique key for model
        * @default <NOKEY>
        */
-      key?: string;
+      key: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash?: string | null;
+      original_hash: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash?: string | null;
+      current_hash: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -7795,12 +7795,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source?: string | null;
+      source: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified?: number | null;
+      last_modified: number | null;
       /** Vae */
       vae?: string | null;
       /** @default normal */
@@ -7838,13 +7838,13 @@ export type components = {
        * @default sd-2
        * @constant
        */
-      base?: "sd-2";
+      base: "sd-2";
       /**
        * Type
        * @default onnx
        * @constant
        */
-      type?: "onnx";
+      type: "onnx";
       /**
        * Format
        * @enum {string}
@@ -7855,17 +7855,17 @@ export type components = {
        * @description unique key for model
        * @default <NOKEY>
        */
-      key?: string;
+      key: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash?: string | null;
+      original_hash: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash?: string | null;
+      current_hash: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -7875,12 +7875,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source?: string | null;
+      source: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified?: number | null;
+      last_modified: number | null;
       /** Vae */
       vae?: string | null;
       /** @default normal */
@@ -7918,13 +7918,13 @@ export type components = {
        * @default sdxl
        * @constant
        */
-      base?: "sdxl";
+      base: "sdxl";
       /**
        * Type
        * @default onnx
        * @constant
        */
-      type?: "onnx";
+      type: "onnx";
       /**
        * Format
        * @enum {string}
@@ -7935,17 +7935,17 @@ export type components = {
        * @description unique key for model
        * @default <NOKEY>
        */
-      key?: string;
+      key: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash?: string | null;
+      original_hash: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash?: string | null;
+      current_hash: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -7955,12 +7955,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source?: string | null;
+      source: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified?: number | null;
+      last_modified: number | null;
       /** Vae */
       vae?: string | null;
       /** @default normal */
@@ -10110,7 +10110,7 @@ export type components = {
        * @default t2i_adapter
        * @constant
        */
-      type?: "t2i_adapter";
+      type: "t2i_adapter";
       /**
        * Format
        * @constant
@@ -10121,17 +10121,17 @@ export type components = {
        * @description unique key for model
        * @default <NOKEY>
        */
-      key?: string;
+      key: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash?: string | null;
+      original_hash: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash?: string | null;
+      current_hash: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -10141,12 +10141,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source?: string | null;
+      source: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified?: number | null;
+      last_modified: number | null;
     };
     /** TBLR */
     TBLR: {
@@ -10181,7 +10181,7 @@ export type components = {
        * @default embedding
        * @constant
        */
-      type?: "embedding";
+      type: "embedding";
       /**
        * Format
        * @enum {string}
@@ -10192,17 +10192,17 @@ export type components = {
        * @description unique key for model
        * @default <NOKEY>
        */
-      key?: string;
+      key: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash?: string | null;
+      original_hash: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash?: string | null;
+      current_hash: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -10212,12 +10212,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source?: string | null;
+      source: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified?: number | null;
+      last_modified: number | null;
     };
     /** Tile */
     Tile: {
@@ -10530,29 +10530,29 @@ export type components = {
        * @default vae
        * @constant
        */
-      type?: "vae";
+      type: "vae";
       /**
        * Format
        * @default checkpoint
        * @constant
        */
-      format?: "checkpoint";
+      format: "checkpoint";
       /**
        * Key
        * @description unique key for model
        * @default <NOKEY>
        */
-      key?: string;
+      key: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash?: string | null;
+      original_hash: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash?: string | null;
+      current_hash: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -10562,12 +10562,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source?: string | null;
+      source: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified?: number | null;
+      last_modified: number | null;
     };
     /**
      * VaeDiffusersConfig
@@ -10591,29 +10591,29 @@ export type components = {
        * @default vae
        * @constant
        */
-      type?: "vae";
+      type: "vae";
       /**
        * Format
        * @default diffusers
        * @constant
        */
-      format?: "diffusers";
+      format: "diffusers";
       /**
        * Key
        * @description unique key for model
        * @default <NOKEY>
        */
-      key?: string;
+      key: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash?: string | null;
+      original_hash: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash?: string | null;
+      current_hash: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -10623,12 +10623,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source?: string | null;
+      source: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified?: number | null;
+      last_modified: number | null;
     };
     /** VaeField */
     VaeField: {

From 3ed2963f43e5b93c8ac0407ad5ba7c9fbb40f524 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Thu, 22 Feb 2024 17:33:20 +1100
Subject: [PATCH 245/411] feat(ui): refactor metadata handling

Refactor of metadata recall handling. This is in preparation for a backwards compatibility layer for models.

- Create helpers to fetch a model outside react (e.g. not in a hook)
- Created helpers to parse model metadata
- Renamed a lot of types that were confusing and/or had naming collisions
---
 .../web/src/app/store/nanostores/store.ts     |  22 +
 .../parameters/ParamControlAdapterModel.tsx   |   4 +-
 .../features/embedding/EmbeddingSelect.tsx    |   6 +-
 .../features/lora/components/LoRASelect.tsx   |   6 +-
 .../web/src/features/lora/store/loraSlice.ts  |   9 +-
 .../ModelManagerPanel/LoRAModelEdit.tsx       |  13 +-
 .../ControlNetModelFieldInputComponent.tsx    |   4 +-
 .../IPAdapterModelFieldInputComponent.tsx     |   4 +-
 .../inputs/LoRAModelFieldInputComponent.tsx   |   4 +-
 .../T2IAdapterModelFieldInputComponent.tsx    |   4 +-
 .../inputs/VAEModelFieldInputComponent.tsx    |   4 +-
 .../VAEModel/ParamVAEModelSelect.tsx          |   6 +-
 .../parameters/hooks/useRecallParameters.ts   | 516 ++++--------------
 .../parameters/util/modelFetchingHelpers.ts   | 113 ++++
 .../parameters/util/modelMetadataHelpers.ts   | 150 +++++
 .../web/src/services/api/endpoints/models.ts  |  64 +--
 16 files changed, 443 insertions(+), 486 deletions(-)
 create mode 100644 invokeai/frontend/web/src/features/parameters/util/modelFetchingHelpers.ts
 create mode 100644 invokeai/frontend/web/src/features/parameters/util/modelMetadataHelpers.ts

diff --git a/invokeai/frontend/web/src/app/store/nanostores/store.ts b/invokeai/frontend/web/src/app/store/nanostores/store.ts
index aee0f0e6ef..f4cd001c96 100644
--- a/invokeai/frontend/web/src/app/store/nanostores/store.ts
+++ b/invokeai/frontend/web/src/app/store/nanostores/store.ts
@@ -8,4 +8,26 @@ declare global {
   }
 }
 
+/**
+ * Raised when the redux store is unable to be retrieved.
+ */
+export class ReduxStoreNotInitialized extends Error {
+  /**
+   * Create ReduxStoreNotInitialized
+   * @param {String} message
+   */
+  constructor(message = 'Redux store not initialized') {
+    super(message);
+    this.name = this.constructor.name;
+  }
+}
+
 export const $store = atom<Readonly<ReturnType<typeof createStore>> | undefined>();
+
+export const getStore = () => {
+  const store = $store.get();
+  if (!store) {
+    throw new ReduxStoreNotInitialized();
+  }
+  return store;
+};
diff --git a/invokeai/frontend/web/src/features/controlAdapters/components/parameters/ParamControlAdapterModel.tsx b/invokeai/frontend/web/src/features/controlAdapters/components/parameters/ParamControlAdapterModel.tsx
index 696bf47b2a..75372c350d 100644
--- a/invokeai/frontend/web/src/features/controlAdapters/components/parameters/ParamControlAdapterModel.tsx
+++ b/invokeai/frontend/web/src/features/controlAdapters/components/parameters/ParamControlAdapterModel.tsx
@@ -8,7 +8,7 @@ import { useControlAdapterType } from 'features/controlAdapters/hooks/useControl
 import { controlAdapterModelChanged } from 'features/controlAdapters/store/controlAdaptersSlice';
 import { pick } from 'lodash-es';
 import { memo, useCallback, useMemo } from 'react';
-import type { ControlNetConfig, IPAdapterConfig, T2IAdapterConfig } from 'services/api/types';
+import type { ControlNetModelConfig, IPAdapterModelConfig, T2IAdapterModelConfig } from 'services/api/types';
 
 type ParamControlAdapterModelProps = {
   id: string;
@@ -24,7 +24,7 @@ const ParamControlAdapterModel = ({ id }: ParamControlAdapterModelProps) => {
   const { data, isLoading } = useControlAdapterModelQuery(controlAdapterType);
 
   const _onChange = useCallback(
-    (model: ControlNetConfig | IPAdapterConfig | T2IAdapterConfig | null) => {
+    (model: ControlNetModelConfig | IPAdapterModelConfig | T2IAdapterModelConfig | null) => {
       if (!model) {
         return;
       }
diff --git a/invokeai/frontend/web/src/features/embedding/EmbeddingSelect.tsx b/invokeai/frontend/web/src/features/embedding/EmbeddingSelect.tsx
index fd05edc466..a5ad358fa0 100644
--- a/invokeai/frontend/web/src/features/embedding/EmbeddingSelect.tsx
+++ b/invokeai/frontend/web/src/features/embedding/EmbeddingSelect.tsx
@@ -7,7 +7,7 @@ import { t } from 'i18next';
 import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 import { useGetTextualInversionModelsQuery } from 'services/api/endpoints/models';
-import type { TextualInversionConfig } from 'services/api/types';
+import type { TextualInversionModelConfig } from 'services/api/types';
 
 const noOptionsMessage = () => t('embedding.noMatchingEmbedding');
 
@@ -17,7 +17,7 @@ export const EmbeddingSelect = memo(({ onSelect, onClose }: EmbeddingSelectProps
   const currentBaseModel = useAppSelector((s) => s.generation.model?.base);
 
   const getIsDisabled = useCallback(
-    (embedding: TextualInversionConfig): boolean => {
+    (embedding: TextualInversionModelConfig): boolean => {
       const isCompatible = currentBaseModel === embedding.base;
       const hasMainModel = Boolean(currentBaseModel);
       return !hasMainModel || !isCompatible;
@@ -27,7 +27,7 @@ export const EmbeddingSelect = memo(({ onSelect, onClose }: EmbeddingSelectProps
   const { data, isLoading } = useGetTextualInversionModelsQuery();
 
   const _onChange = useCallback(
-    (embedding: TextualInversionConfig | null) => {
+    (embedding: TextualInversionModelConfig | null) => {
       if (!embedding) {
         return;
       }
diff --git a/invokeai/frontend/web/src/features/lora/components/LoRASelect.tsx b/invokeai/frontend/web/src/features/lora/components/LoRASelect.tsx
index b58751ca5e..e7d40c5eaf 100644
--- a/invokeai/frontend/web/src/features/lora/components/LoRASelect.tsx
+++ b/invokeai/frontend/web/src/features/lora/components/LoRASelect.tsx
@@ -8,7 +8,7 @@ import { loraAdded, selectLoraSlice } from 'features/lora/store/loraSlice';
 import { memo, useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
 import { useGetLoRAModelsQuery } from 'services/api/endpoints/models';
-import type { LoRAConfig } from 'services/api/types';
+import type { LoRAModelConfig } from 'services/api/types';
 
 const selectAddedLoRAs = createMemoizedSelector(selectLoraSlice, (lora) => lora.loras);
 
@@ -19,7 +19,7 @@ const LoRASelect = () => {
   const addedLoRAs = useAppSelector(selectAddedLoRAs);
   const currentBaseModel = useAppSelector((s) => s.generation.model?.base);
 
-  const getIsDisabled = (lora: LoRAConfig): boolean => {
+  const getIsDisabled = (lora: LoRAModelConfig): boolean => {
     const isCompatible = currentBaseModel === lora.base;
     const isAdded = Boolean(addedLoRAs[lora.key]);
     const hasMainModel = Boolean(currentBaseModel);
@@ -27,7 +27,7 @@ const LoRASelect = () => {
   };
 
   const _onChange = useCallback(
-    (lora: LoRAConfig | null) => {
+    (lora: LoRAModelConfig | null) => {
       if (!lora) {
         return;
       }
diff --git a/invokeai/frontend/web/src/features/lora/store/loraSlice.ts b/invokeai/frontend/web/src/features/lora/store/loraSlice.ts
index dd455e12c3..377406b3e5 100644
--- a/invokeai/frontend/web/src/features/lora/store/loraSlice.ts
+++ b/invokeai/frontend/web/src/features/lora/store/loraSlice.ts
@@ -2,7 +2,7 @@ import type { PayloadAction } from '@reduxjs/toolkit';
 import { createSlice } from '@reduxjs/toolkit';
 import type { PersistConfig, RootState } from 'app/store/store';
 import type { ParameterLoRAModel } from 'features/parameters/types/parameterSchemas';
-import type { LoRAConfig } from 'services/api/types';
+import type { LoRAModelConfig } from 'services/api/types';
 
 export type LoRA = ParameterLoRAModel & {
   weight: number;
@@ -28,13 +28,12 @@ export const loraSlice = createSlice({
   name: 'lora',
   initialState: initialLoraState,
   reducers: {
-    loraAdded: (state, action: PayloadAction<LoRAConfig>) => {
+    loraAdded: (state, action: PayloadAction<LoRAModelConfig>) => {
       const { key, base } = action.payload;
       state.loras[key] = { key, base, ...defaultLoRAConfig };
     },
-    loraRecalled: (state, action: PayloadAction<LoRAConfig & { weight: number }>) => {
-      const { key, base, weight } = action.payload;
-      state.loras[key] = { key, base, weight, isEnabled: true };
+    loraRecalled: (state, action: PayloadAction<LoRA>) => {
+      state.loras[action.payload.key] = action.payload;
     },
     loraRemoved: (state, action: PayloadAction<string>) => {
       const key = action.payload;
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/LoRAModelEdit.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/LoRAModelEdit.tsx
index 75151cd001..1a8f235aaf 100644
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/LoRAModelEdit.tsx
+++ b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/LoRAModelEdit.tsx
@@ -8,12 +8,11 @@ import { memo, useCallback } from 'react';
 import type { SubmitHandler } from 'react-hook-form';
 import { useForm } from 'react-hook-form';
 import { useTranslation } from 'react-i18next';
-import type { LoRAConfig } from 'services/api/endpoints/models';
 import { useUpdateLoRAModelsMutation } from 'services/api/endpoints/models';
-import type { LoRAConfig } from 'services/api/types';
+import type { LoRAModelConfig } from 'services/api/types';
 
 type LoRAModelEditProps = {
-  model: LoRAConfig;
+  model: LoRAModelConfig;
 };
 
 const LoRAModelEdit = (props: LoRAModelEditProps) => {
@@ -30,7 +29,7 @@ const LoRAModelEdit = (props: LoRAModelEditProps) => {
     control,
     formState: { errors },
     reset,
-  } = useForm<LoRAConfig>({
+  } = useForm<LoRAModelConfig>({
     defaultValues: {
       model_name: model.model_name ? model.model_name : '',
       base_model: model.base_model,
@@ -42,7 +41,7 @@ const LoRAModelEdit = (props: LoRAModelEditProps) => {
     mode: 'onChange',
   });
 
-  const onSubmit = useCallback<SubmitHandler<LoRAConfig>>(
+  const onSubmit = useCallback<SubmitHandler<LoRAModelConfig>>(
     (values) => {
       const responseBody = {
         base_model: model.base_model,
@@ -53,7 +52,7 @@ const LoRAModelEdit = (props: LoRAModelEditProps) => {
       updateLoRAModel(responseBody)
         .unwrap()
         .then((payload) => {
-          reset(payload as LoRAConfig, { keepDefaultValues: true });
+          reset(payload as LoRAModelConfig, { keepDefaultValues: true });
           dispatch(
             addToast(
               makeToast({
@@ -106,7 +105,7 @@ const LoRAModelEdit = (props: LoRAModelEditProps) => {
             <FormLabel>{t('modelManager.description')}</FormLabel>
             <Input {...register('description')} />
           </FormControl>
-          <BaseModelSelect<LoRAConfig> control={control} name="base_model" />
+          <BaseModelSelect<LoRAModelConfig> control={control} name="base_model" />
 
           <FormControl isInvalid={Boolean(errors.path)}>
             <FormLabel>{t('modelManager.modelLocation')}</FormLabel>
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/ControlNetModelFieldInputComponent.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/ControlNetModelFieldInputComponent.tsx
index 1951ec60d3..29a1f93dd5 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/ControlNetModelFieldInputComponent.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/ControlNetModelFieldInputComponent.tsx
@@ -6,7 +6,7 @@ import type { ControlNetModelFieldInputInstance, ControlNetModelFieldInputTempla
 import { pick } from 'lodash-es';
 import { memo, useCallback } from 'react';
 import { useGetControlNetModelsQuery } from 'services/api/endpoints/models';
-import type { ControlNetConfig } from 'services/api/types';
+import type { ControlNetModelConfig } from 'services/api/types';
 
 import type { FieldComponentProps } from './types';
 
@@ -18,7 +18,7 @@ const ControlNetModelFieldInputComponent = (props: Props) => {
   const { data, isLoading } = useGetControlNetModelsQuery();
 
   const _onChange = useCallback(
-    (value: ControlNetConfig | null) => {
+    (value: ControlNetModelConfig | null) => {
       if (!value) {
         return;
       }
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/IPAdapterModelFieldInputComponent.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/IPAdapterModelFieldInputComponent.tsx
index 137f751fca..d4f0ae3de1 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/IPAdapterModelFieldInputComponent.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/IPAdapterModelFieldInputComponent.tsx
@@ -6,7 +6,7 @@ import type { IPAdapterModelFieldInputInstance, IPAdapterModelFieldInputTemplate
 import { pick } from 'lodash-es';
 import { memo, useCallback } from 'react';
 import { useGetIPAdapterModelsQuery } from 'services/api/endpoints/models';
-import type { IPAdapterConfig } from 'services/api/types';
+import type { IPAdapterModelConfig } from 'services/api/types';
 
 import type { FieldComponentProps } from './types';
 
@@ -18,7 +18,7 @@ const IPAdapterModelFieldInputComponent = (
   const { data: ipAdapterModels } = useGetIPAdapterModelsQuery();
 
   const _onChange = useCallback(
-    (value: IPAdapterConfig | null) => {
+    (value: IPAdapterModelConfig | null) => {
       if (!value) {
         return;
       }
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/LoRAModelFieldInputComponent.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/LoRAModelFieldInputComponent.tsx
index 5f6318de9e..9fd223e694 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/LoRAModelFieldInputComponent.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/LoRAModelFieldInputComponent.tsx
@@ -6,7 +6,7 @@ import type { LoRAModelFieldInputInstance, LoRAModelFieldInputTemplate } from 'f
 import { pick } from 'lodash-es';
 import { memo, useCallback } from 'react';
 import { useGetLoRAModelsQuery } from 'services/api/endpoints/models';
-import type { LoRAConfig } from 'services/api/types';
+import type { LoRAModelConfig } from 'services/api/types';
 
 import type { FieldComponentProps } from './types';
 
@@ -17,7 +17,7 @@ const LoRAModelFieldInputComponent = (props: Props) => {
   const dispatch = useAppDispatch();
   const { data, isLoading } = useGetLoRAModelsQuery();
   const _onChange = useCallback(
-    (value: LoRAConfig | null) => {
+    (value: LoRAModelConfig | null) => {
       if (!value) {
         return;
       }
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/T2IAdapterModelFieldInputComponent.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/T2IAdapterModelFieldInputComponent.tsx
index 9115f22c14..a38356a0b8 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/T2IAdapterModelFieldInputComponent.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/T2IAdapterModelFieldInputComponent.tsx
@@ -6,7 +6,7 @@ import type { T2IAdapterModelFieldInputInstance, T2IAdapterModelFieldInputTempla
 import { pick } from 'lodash-es';
 import { memo, useCallback } from 'react';
 import { useGetT2IAdapterModelsQuery } from 'services/api/endpoints/models';
-import type { T2IAdapterConfig } from 'services/api/types';
+import type { T2IAdapterModelConfig } from 'services/api/types';
 
 import type { FieldComponentProps } from './types';
 
@@ -19,7 +19,7 @@ const T2IAdapterModelFieldInputComponent = (
   const { data: t2iAdapterModels } = useGetT2IAdapterModelsQuery();
 
   const _onChange = useCallback(
-    (value: T2IAdapterConfig | null) => {
+    (value: T2IAdapterModelConfig | null) => {
       if (!value) {
         return;
       }
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/VAEModelFieldInputComponent.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/VAEModelFieldInputComponent.tsx
index 87272f48b9..272f7f5b35 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/VAEModelFieldInputComponent.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/VAEModelFieldInputComponent.tsx
@@ -7,7 +7,7 @@ import type { VAEModelFieldInputInstance, VAEModelFieldInputTemplate } from 'fea
 import { pick } from 'lodash-es';
 import { memo, useCallback } from 'react';
 import { useGetVaeModelsQuery } from 'services/api/endpoints/models';
-import type { VAEConfig } from 'services/api/types';
+import type { VAEModelConfig } from 'services/api/types';
 
 import type { FieldComponentProps } from './types';
 
@@ -18,7 +18,7 @@ const VAEModelFieldInputComponent = (props: Props) => {
   const dispatch = useAppDispatch();
   const { data, isLoading } = useGetVaeModelsQuery();
   const _onChange = useCallback(
-    (value: VAEConfig | null) => {
+    (value: VAEModelConfig | null) => {
       if (!value) {
         return;
       }
diff --git a/invokeai/frontend/web/src/features/parameters/components/VAEModel/ParamVAEModelSelect.tsx b/invokeai/frontend/web/src/features/parameters/components/VAEModel/ParamVAEModelSelect.tsx
index 4b9f2764bf..4a630fa9ce 100644
--- a/invokeai/frontend/web/src/features/parameters/components/VAEModel/ParamVAEModelSelect.tsx
+++ b/invokeai/frontend/web/src/features/parameters/components/VAEModel/ParamVAEModelSelect.tsx
@@ -8,7 +8,7 @@ import { pick } from 'lodash-es';
 import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 import { useGetVaeModelsQuery } from 'services/api/endpoints/models';
-import type { VAEConfig } from 'services/api/types';
+import type { VAEModelConfig } from 'services/api/types';
 
 const selector = createMemoizedSelector(selectGenerationSlice, (generation) => {
   const { model, vae } = generation;
@@ -21,7 +21,7 @@ const ParamVAEModelSelect = () => {
   const { model, vae } = useAppSelector(selector);
   const { data, isLoading } = useGetVaeModelsQuery();
   const getIsDisabled = useCallback(
-    (vae: VAEConfig): boolean => {
+    (vae: VAEModelConfig): boolean => {
       const isCompatible = model?.base === vae.base;
       const hasMainModel = Boolean(model?.base);
       return !hasMainModel || !isCompatible;
@@ -29,7 +29,7 @@ const ParamVAEModelSelect = () => {
     [model?.base]
   );
   const _onChange = useCallback(
-    (vae: VAEConfig | null) => {
+    (vae: VAEModelConfig | null) => {
       dispatch(vaeSelected(vae ? pick(vae, 'key', 'base') : null));
     },
     [dispatch]
diff --git a/invokeai/frontend/web/src/features/parameters/hooks/useRecallParameters.ts b/invokeai/frontend/web/src/features/parameters/hooks/useRecallParameters.ts
index 0d464cd9b9..0929fc1dc3 100644
--- a/invokeai/frontend/web/src/features/parameters/hooks/useRecallParameters.ts
+++ b/invokeai/frontend/web/src/features/parameters/hooks/useRecallParameters.ts
@@ -1,17 +1,9 @@
 import { useAppToaster } from 'app/components/Toaster';
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import { CONTROLNET_PROCESSORS } from 'features/controlAdapters/store/constants';
 import { controlAdapterRecalled, controlAdaptersReset } from 'features/controlAdapters/store/controlAdaptersSlice';
-import type { ControlNetConfig, IPAdapterConfig, T2IAdapterConfig } from 'features/controlAdapters/store/types';
-import {
-  initialControlNet,
-  initialIPAdapter,
-  initialT2IAdapter,
-} from 'features/controlAdapters/util/buildControlAdapter';
 import { setHrfEnabled, setHrfMethod, setHrfStrength } from 'features/hrf/store/hrfSlice';
 import { loraRecalled, lorasCleared } from 'features/lora/store/loraSlice';
-import type { ModelIdentifier } from 'features/nodes/types/common';
 import { isModelIdentifier } from 'features/nodes/types/common';
 import type {
   ControlNetMetadataItem,
@@ -56,6 +48,14 @@ import {
   isParameterStrength,
   isParameterWidth,
 } from 'features/parameters/types/parameterSchemas';
+import {
+  prepareControlNetMetadataItem,
+  prepareIPAdapterMetadataItem,
+  prepareLoRAMetadataItem,
+  prepareMainModelMetadataItem,
+  prepareT2IAdapterMetadataItem,
+  prepareVAEMetadataItem,
+} from 'features/parameters/util/modelMetadataHelpers';
 import {
   refinerModelChanged,
   setNegativeStylePromptSDXL,
@@ -70,23 +70,7 @@ import {
 import { isNil } from 'lodash-es';
 import { useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
-import { ALL_BASE_MODELS } from 'services/api/constants';
-import {
-  controlNetModelsAdapterSelectors,
-  ipAdapterModelsAdapterSelectors,
-  loraModelsAdapterSelectors,
-  mainModelsAdapterSelectors,
-  t2iAdapterModelsAdapterSelectors,
-  useGetControlNetModelsQuery,
-  useGetIPAdapterModelsQuery,
-  useGetLoRAModelsQuery,
-  useGetMainModelsQuery,
-  useGetT2IAdapterModelsQuery,
-  useGetVaeModelsQuery,
-  vaeModelsAdapterSelectors,
-} from 'services/api/endpoints/models';
 import type { ImageDTO } from 'services/api/types';
-import { v4 as uuidv4 } from 'uuid';
 
 const selectModel = createMemoizedSelector(selectGenerationSlice, (generation) => generation.model);
 
@@ -140,9 +124,6 @@ export const useRecallParameters = () => {
     [t, toaster]
   );
 
-  /**
-   * Recall both prompts with toast
-   */
   const recallBothPrompts = useCallback(
     (positivePrompt: unknown, negativePrompt: unknown, positiveStylePrompt: unknown, negativeStylePrompt: unknown) => {
       if (
@@ -175,9 +156,6 @@ export const useRecallParameters = () => {
     [dispatch, parameterSetToast, parameterNotSetToast]
   );
 
-  /**
-   * Recall positive prompt with toast
-   */
   const recallPositivePrompt = useCallback(
     (positivePrompt: unknown) => {
       if (!isParameterPositivePrompt(positivePrompt)) {
@@ -190,9 +168,6 @@ export const useRecallParameters = () => {
     [dispatch, parameterSetToast, parameterNotSetToast]
   );
 
-  /**
-   * Recall negative prompt with toast
-   */
   const recallNegativePrompt = useCallback(
     (negativePrompt: unknown) => {
       if (!isParameterNegativePrompt(negativePrompt)) {
@@ -205,9 +180,6 @@ export const useRecallParameters = () => {
     [dispatch, parameterSetToast, parameterNotSetToast]
   );
 
-  /**
-   * Recall SDXL Positive Style Prompt with toast
-   */
   const recallSDXLPositiveStylePrompt = useCallback(
     (positiveStylePrompt: unknown) => {
       if (!isParameterPositiveStylePromptSDXL(positiveStylePrompt)) {
@@ -220,9 +192,6 @@ export const useRecallParameters = () => {
     [dispatch, parameterSetToast, parameterNotSetToast]
   );
 
-  /**
-   * Recall SDXL Negative Style Prompt with toast
-   */
   const recallSDXLNegativeStylePrompt = useCallback(
     (negativeStylePrompt: unknown) => {
       if (!isParameterNegativeStylePromptSDXL(negativeStylePrompt)) {
@@ -235,9 +204,6 @@ export const useRecallParameters = () => {
     [dispatch, parameterSetToast, parameterNotSetToast]
   );
 
-  /**
-   * Recall seed with toast
-   */
   const recallSeed = useCallback(
     (seed: unknown) => {
       if (!isParameterSeed(seed)) {
@@ -250,9 +216,6 @@ export const useRecallParameters = () => {
     [dispatch, parameterSetToast, parameterNotSetToast]
   );
 
-  /**
-   * Recall CFG scale with toast
-   */
   const recallCfgScale = useCallback(
     (cfgScale: unknown) => {
       if (!isParameterCFGScale(cfgScale)) {
@@ -265,9 +228,6 @@ export const useRecallParameters = () => {
     [dispatch, parameterSetToast, parameterNotSetToast]
   );
 
-  /**
-   * Recall CFG rescale multiplier with toast
-   */
   const recallCfgRescaleMultiplier = useCallback(
     (cfgRescaleMultiplier: unknown) => {
       if (!isParameterCFGRescaleMultiplier(cfgRescaleMultiplier)) {
@@ -280,9 +240,6 @@ export const useRecallParameters = () => {
     [dispatch, parameterSetToast, parameterNotSetToast]
   );
 
-  /**
-   * Recall scheduler with toast
-   */
   const recallScheduler = useCallback(
     (scheduler: unknown) => {
       if (!isParameterScheduler(scheduler)) {
@@ -295,9 +252,6 @@ export const useRecallParameters = () => {
     [dispatch, parameterSetToast, parameterNotSetToast]
   );
 
-  /**
-   * Recall steps with toast
-   */
   const recallSteps = useCallback(
     (steps: unknown) => {
       if (!isParameterSteps(steps)) {
@@ -310,9 +264,6 @@ export const useRecallParameters = () => {
     [dispatch, parameterSetToast, parameterNotSetToast]
   );
 
-  /**
-   * Recall width with toast
-   */
   const recallWidth = useCallback(
     (width: unknown) => {
       if (!isParameterWidth(width)) {
@@ -325,9 +276,6 @@ export const useRecallParameters = () => {
     [dispatch, parameterSetToast, parameterNotSetToast]
   );
 
-  /**
-   * Recall height with toast
-   */
   const recallHeight = useCallback(
     (height: unknown) => {
       if (!isParameterHeight(height)) {
@@ -340,9 +288,6 @@ export const useRecallParameters = () => {
     [dispatch, parameterSetToast, parameterNotSetToast]
   );
 
-  /**
-   * Recall width and height with toast
-   */
   const recallWidthAndHeight = useCallback(
     (width: unknown, height: unknown) => {
       if (!isParameterWidth(width)) {
@@ -360,9 +305,6 @@ export const useRecallParameters = () => {
     [dispatch, allParameterSetToast, allParameterNotSetToast]
   );
 
-  /**
-   * Recall strength with toast
-   */
   const recallStrength = useCallback(
     (strength: unknown) => {
       if (!isParameterStrength(strength)) {
@@ -375,9 +317,6 @@ export const useRecallParameters = () => {
     [dispatch, parameterSetToast, parameterNotSetToast]
   );
 
-  /**
-   * Recall high resolution enabled with toast
-   */
   const recallHrfEnabled = useCallback(
     (hrfEnabled: unknown) => {
       if (!isParameterHRFEnabled(hrfEnabled)) {
@@ -390,9 +329,6 @@ export const useRecallParameters = () => {
     [dispatch, parameterSetToast, parameterNotSetToast]
   );
 
-  /**
-   * Recall high resolution strength with toast
-   */
   const recallHrfStrength = useCallback(
     (hrfStrength: unknown) => {
       if (!isParameterStrength(hrfStrength)) {
@@ -405,9 +341,6 @@ export const useRecallParameters = () => {
     [dispatch, parameterSetToast, parameterNotSetToast]
   );
 
-  /**
-   * Recall high resolution method with toast
-   */
   const recallHrfMethod = useCallback(
     (hrfMethod: unknown) => {
       if (!isParameterHRFMethod(hrfMethod)) {
@@ -420,358 +353,95 @@ export const useRecallParameters = () => {
     [dispatch, parameterSetToast, parameterNotSetToast]
   );
 
-  const { data: mainModels } = useGetMainModelsQuery(ALL_BASE_MODELS);
-
-  const prepareMainModelMetadataItem = useCallback(
-    (model: ModelIdentifier) => {
-      const matchingModel = mainModels ? mainModelsAdapterSelectors.selectById(mainModels, model.key) : undefined;
-
-      if (!matchingModel) {
-        return { model: null, error: 'Model is not installed' };
-      }
-
-      return { model: matchingModel, error: null };
-    },
-    [mainModels]
-  );
-
-  /**
-   * Recall model with toast
-   */
   const recallModel = useCallback(
-    (model: unknown) => {
-      if (!isModelIdentifier(model)) {
-        parameterNotSetToast();
+    async (modelMetadataItem: unknown) => {
+      try {
+        const model = await prepareMainModelMetadataItem(modelMetadataItem);
+        dispatch(modelSelected(model));
+        parameterSetToast();
+      } catch (e) {
+        parameterNotSetToast((e as unknown as Error).message);
         return;
       }
-
-      const result = prepareMainModelMetadataItem(model);
-
-      if (!result.model) {
-        parameterNotSetToast(result.error);
-        return;
-      }
-
-      dispatch(modelSelected(result.model));
-      parameterSetToast();
     },
-    [prepareMainModelMetadataItem, dispatch, parameterSetToast, parameterNotSetToast]
+    [dispatch, parameterSetToast, parameterNotSetToast]
   );
 
-  const { data: vaeModels } = useGetVaeModelsQuery();
-
-  const prepareVAEMetadataItem = useCallback(
-    (vae: ModelIdentifier, newModel?: ParameterModel) => {
-      const matchingModel = vaeModels ? vaeModelsAdapterSelectors.selectById(vaeModels, vae.key) : undefined;
-      if (!matchingModel) {
-        return { vae: null, error: 'VAE model is not installed' };
-      }
-      const isCompatibleBaseModel = matchingModel?.base === (newModel ?? model)?.base;
-
-      if (!isCompatibleBaseModel) {
-        return {
-          vae: null,
-          error: 'VAE incompatible with currently-selected model',
-        };
-      }
-
-      return { vae: matchingModel, error: null };
-    },
-    [model, vaeModels]
-  );
-
-  /**
-   * Recall vae model
-   */
   const recallVaeModel = useCallback(
-    (vae: unknown) => {
-      if (!isModelIdentifier(vae) && !isNil(vae)) {
-        parameterNotSetToast();
-        return;
-      }
-
-      if (isNil(vae)) {
+    async (vaeMetadataItem: unknown) => {
+      if (isNil(vaeMetadataItem)) {
         dispatch(vaeSelected(null));
         parameterSetToast();
         return;
       }
-
-      const result = prepareVAEMetadataItem(vae);
-
-      if (!result.vae) {
-        parameterNotSetToast(result.error);
+      try {
+        const vae = await prepareVAEMetadataItem(vaeMetadataItem);
+        dispatch(vaeSelected(vae));
+        parameterSetToast();
+      } catch (e) {
+        parameterNotSetToast((e as unknown as Error).message);
         return;
       }
-
-      dispatch(vaeSelected(result.vae));
-      parameterSetToast();
     },
-    [prepareVAEMetadataItem, dispatch, parameterSetToast, parameterNotSetToast]
-  );
-
-  /**
-   * Recall LoRA with toast
-   */
-
-  const { data: loraModels } = useGetLoRAModelsQuery(undefined);
-
-  const prepareLoRAMetadataItem = useCallback(
-    (loraMetadataItem: LoRAMetadataItem, newModel?: ParameterModel) => {
-      if (!isModelIdentifier(loraMetadataItem.lora)) {
-        return { lora: null, error: 'Invalid LoRA model' };
-      }
-
-      const { lora } = loraMetadataItem;
-
-      const matchingLoRA = loraModels ? loraModelsAdapterSelectors.selectById(loraModels, lora.key) : undefined;
-
-      if (!matchingLoRA) {
-        return { lora: null, error: 'LoRA model is not installed' };
-      }
-
-      const isCompatibleBaseModel = matchingLoRA?.base === (newModel ?? model)?.base;
-
-      if (!isCompatibleBaseModel) {
-        return {
-          lora: null,
-          error: 'LoRA incompatible with currently-selected model',
-        };
-      }
-
-      return { lora: matchingLoRA, error: null };
-    },
-    [loraModels, model]
+    [dispatch, parameterSetToast, parameterNotSetToast]
   );
 
   const recallLoRA = useCallback(
-    (loraMetadataItem: LoRAMetadataItem) => {
-      const result = prepareLoRAMetadataItem(loraMetadataItem);
-
-      if (!result.lora) {
-        parameterNotSetToast(result.error);
+    async (loraMetadataItem: LoRAMetadataItem) => {
+      try {
+        const lora = await prepareLoRAMetadataItem(loraMetadataItem, model?.base);
+        dispatch(loraRecalled(lora));
+        parameterSetToast();
+      } catch (e) {
+        parameterNotSetToast((e as unknown as Error).message);
         return;
       }
-
-      dispatch(loraRecalled({ ...result.lora, weight: loraMetadataItem.weight }));
-
-      parameterSetToast();
     },
-    [prepareLoRAMetadataItem, dispatch, parameterSetToast, parameterNotSetToast]
-  );
-
-  /**
-   * Recall ControlNet with toast
-   */
-
-  const { data: controlNetModels } = useGetControlNetModelsQuery(undefined);
-
-  const prepareControlNetMetadataItem = useCallback(
-    (controlnetMetadataItem: ControlNetMetadataItem, newModel?: ParameterModel) => {
-      if (!isModelIdentifier(controlnetMetadataItem.control_model)) {
-        return { controlnet: null, error: 'Invalid ControlNet model' };
-      }
-
-      const { image, control_model, control_weight, begin_step_percent, end_step_percent, control_mode, resize_mode } =
-        controlnetMetadataItem;
-
-      const matchingControlNetModel = controlNetModels
-        ? controlNetModelsAdapterSelectors.selectById(controlNetModels, control_model.key)
-        : undefined;
-
-      if (!matchingControlNetModel) {
-        return { controlnet: null, error: 'ControlNet model is not installed' };
-      }
-
-      const isCompatibleBaseModel = matchingControlNetModel?.base === (newModel ?? model)?.base;
-
-      if (!isCompatibleBaseModel) {
-        return {
-          controlnet: null,
-          error: 'ControlNet incompatible with currently-selected model',
-        };
-      }
-
-      // We don't save the original image that was processed into a control image, only the processed image
-      const processorType = 'none';
-      const processorNode = CONTROLNET_PROCESSORS.none.default;
-
-      const controlnet: ControlNetConfig = {
-        type: 'controlnet',
-        isEnabled: true,
-        model: matchingControlNetModel,
-        weight: typeof control_weight === 'number' ? control_weight : initialControlNet.weight,
-        beginStepPct: begin_step_percent || initialControlNet.beginStepPct,
-        endStepPct: end_step_percent || initialControlNet.endStepPct,
-        controlMode: control_mode || initialControlNet.controlMode,
-        resizeMode: resize_mode || initialControlNet.resizeMode,
-        controlImage: image?.image_name || null,
-        processedControlImage: image?.image_name || null,
-        processorType,
-        processorNode,
-        shouldAutoConfig: true,
-        id: uuidv4(),
-      };
-
-      return { controlnet, error: null };
-    },
-    [controlNetModels, model]
+    [model?.base, dispatch, parameterSetToast, parameterNotSetToast]
   );
 
   const recallControlNet = useCallback(
-    (controlnetMetadataItem: ControlNetMetadataItem) => {
-      const result = prepareControlNetMetadataItem(controlnetMetadataItem);
-
-      if (!result.controlnet) {
-        parameterNotSetToast(result.error);
+    async (controlnetMetadataItem: ControlNetMetadataItem) => {
+      try {
+        const controlNetConfig = await prepareControlNetMetadataItem(controlnetMetadataItem, model?.base);
+        dispatch(controlAdapterRecalled(controlNetConfig));
+        parameterSetToast();
+      } catch (e) {
+        parameterNotSetToast((e as unknown as Error).message);
         return;
       }
-
-      dispatch(controlAdapterRecalled(result.controlnet));
-
-      parameterSetToast();
     },
-    [prepareControlNetMetadataItem, dispatch, parameterSetToast, parameterNotSetToast]
-  );
-
-  /**
-   * Recall T2I Adapter with toast
-   */
-
-  const { data: t2iAdapterModels } = useGetT2IAdapterModelsQuery(undefined);
-
-  const prepareT2IAdapterMetadataItem = useCallback(
-    (t2iAdapterMetadataItem: T2IAdapterMetadataItem, newModel?: ParameterModel) => {
-      if (!isModelIdentifier(t2iAdapterMetadataItem.t2i_adapter_model)) {
-        return { controlnet: null, error: 'Invalid ControlNet model' };
-      }
-
-      const { image, t2i_adapter_model, weight, begin_step_percent, end_step_percent, resize_mode } =
-        t2iAdapterMetadataItem;
-
-      const matchingT2IAdapterModel = t2iAdapterModels
-        ? t2iAdapterModelsAdapterSelectors.selectById(t2iAdapterModels, t2i_adapter_model.key)
-        : undefined;
-
-      if (!matchingT2IAdapterModel) {
-        return { controlnet: null, error: 'ControlNet model is not installed' };
-      }
-
-      const isCompatibleBaseModel = matchingT2IAdapterModel?.base === (newModel ?? model)?.base;
-
-      if (!isCompatibleBaseModel) {
-        return {
-          t2iAdapter: null,
-          error: 'ControlNet incompatible with currently-selected model',
-        };
-      }
-
-      // We don't save the original image that was processed into a control image, only the processed image
-      const processorType = 'none';
-      const processorNode = CONTROLNET_PROCESSORS.none.default;
-
-      const t2iAdapter: T2IAdapterConfig = {
-        type: 't2i_adapter',
-        isEnabled: true,
-        model: matchingT2IAdapterModel,
-        weight: typeof weight === 'number' ? weight : initialT2IAdapter.weight,
-        beginStepPct: begin_step_percent || initialT2IAdapter.beginStepPct,
-        endStepPct: end_step_percent || initialT2IAdapter.endStepPct,
-        resizeMode: resize_mode || initialT2IAdapter.resizeMode,
-        controlImage: image?.image_name || null,
-        processedControlImage: image?.image_name || null,
-        processorType,
-        processorNode,
-        shouldAutoConfig: true,
-        id: uuidv4(),
-      };
-
-      return { t2iAdapter, error: null };
-    },
-    [model, t2iAdapterModels]
+    [model?.base, dispatch, parameterSetToast, parameterNotSetToast]
   );
 
   const recallT2IAdapter = useCallback(
-    (t2iAdapterMetadataItem: T2IAdapterMetadataItem) => {
-      const result = prepareT2IAdapterMetadataItem(t2iAdapterMetadataItem);
-
-      if (!result.t2iAdapter) {
-        parameterNotSetToast(result.error);
+    async (t2iAdapterMetadataItem: T2IAdapterMetadataItem) => {
+      try {
+        const t2iAdapterConfig = await prepareT2IAdapterMetadataItem(t2iAdapterMetadataItem, model?.base);
+        dispatch(controlAdapterRecalled(t2iAdapterConfig));
+        parameterSetToast();
+      } catch (e) {
+        parameterNotSetToast((e as unknown as Error).message);
         return;
       }
-
-      dispatch(controlAdapterRecalled(result.t2iAdapter));
-
-      parameterSetToast();
     },
-    [prepareT2IAdapterMetadataItem, dispatch, parameterSetToast, parameterNotSetToast]
-  );
-
-  /**
-   * Recall IP Adapter with toast
-   */
-
-  const { data: ipAdapterModels } = useGetIPAdapterModelsQuery(undefined);
-
-  const prepareIPAdapterMetadataItem = useCallback(
-    (ipAdapterMetadataItem: IPAdapterMetadataItem, newModel?: ParameterModel) => {
-      if (!isModelIdentifier(ipAdapterMetadataItem?.ip_adapter_model)) {
-        return { ipAdapter: null, error: 'Invalid IP Adapter model' };
-      }
-
-      const { image, ip_adapter_model, weight, begin_step_percent, end_step_percent } = ipAdapterMetadataItem;
-
-      const matchingIPAdapterModel = ipAdapterModels
-        ? ipAdapterModelsAdapterSelectors.selectById(ipAdapterModels, ip_adapter_model.key)
-        : undefined;
-
-      if (!matchingIPAdapterModel) {
-        return { ipAdapter: null, error: 'IP Adapter model is not installed' };
-      }
-
-      const isCompatibleBaseModel = matchingIPAdapterModel?.base === (newModel ?? model)?.base;
-
-      if (!isCompatibleBaseModel) {
-        return {
-          ipAdapter: null,
-          error: 'IP Adapter incompatible with currently-selected model',
-        };
-      }
-
-      const ipAdapter: IPAdapterConfig = {
-        id: uuidv4(),
-        type: 'ip_adapter',
-        isEnabled: true,
-        controlImage: image?.image_name ?? null,
-        model: matchingIPAdapterModel,
-        weight: weight ?? initialIPAdapter.weight,
-        beginStepPct: begin_step_percent ?? initialIPAdapter.beginStepPct,
-        endStepPct: end_step_percent ?? initialIPAdapter.endStepPct,
-      };
-
-      return { ipAdapter, error: null };
-    },
-    [ipAdapterModels, model]
+    [model?.base, dispatch, parameterSetToast, parameterNotSetToast]
   );
 
   const recallIPAdapter = useCallback(
-    (ipAdapterMetadataItem: IPAdapterMetadataItem) => {
-      const result = prepareIPAdapterMetadataItem(ipAdapterMetadataItem);
-
-      if (!result.ipAdapter) {
-        parameterNotSetToast(result.error);
+    async (ipAdapterMetadataItem: IPAdapterMetadataItem) => {
+      try {
+        const ipAdapterConfig = await prepareIPAdapterMetadataItem(ipAdapterMetadataItem, model?.base);
+        dispatch(controlAdapterRecalled(ipAdapterConfig));
+        parameterSetToast();
+      } catch (e) {
+        parameterNotSetToast((e as unknown as Error).message);
         return;
       }
-
-      dispatch(controlAdapterRecalled(result.ipAdapter));
-
-      parameterSetToast();
     },
-    [prepareIPAdapterMetadataItem, dispatch, parameterSetToast, parameterNotSetToast]
+    [model?.base, dispatch, parameterSetToast, parameterNotSetToast]
   );
 
-  /*
-   * Sets image as initial image with toast
-   */
   const sendToImageToImage = useCallback(
     (image: ImageDTO) => {
       dispatch(initialImageSelected(image));
@@ -780,7 +450,7 @@ export const useRecallParameters = () => {
   );
 
   const recallAllParameters = useCallback(
-    (metadata: CoreMetadata | undefined) => {
+    async (metadata: CoreMetadata | undefined) => {
       if (!metadata) {
         allParameterNotSetToast();
         return;
@@ -820,10 +490,12 @@ export const useRecallParameters = () => {
       let newModel: ParameterModel | undefined = undefined;
 
       if (isModelIdentifier(model)) {
-        const result = prepareMainModelMetadataItem(model);
-        if (result.model) {
-          dispatch(modelSelected(result.model));
-          newModel = result.model;
+        try {
+          const _model = await prepareMainModelMetadataItem(model);
+          dispatch(modelSelected(_model));
+          newModel = _model;
+        } catch {
+          return;
         }
       }
 
@@ -850,9 +522,11 @@ export const useRecallParameters = () => {
         if (isNil(vae)) {
           dispatch(vaeSelected(null));
         } else {
-          const result = prepareVAEMetadataItem(vae, newModel);
-          if (result.vae) {
-            dispatch(vaeSelected(result.vae));
+          try {
+            const _vae = await prepareVAEMetadataItem(vae, newModel?.base);
+            dispatch(vaeSelected(_vae));
+          } catch {
+            return;
           }
         }
       }
@@ -926,48 +600,46 @@ export const useRecallParameters = () => {
       }
 
       dispatch(lorasCleared());
-      loras?.forEach((lora) => {
-        const result = prepareLoRAMetadataItem(lora, newModel);
-        if (result.lora) {
-          dispatch(loraRecalled({ ...result.lora, weight: lora.weight }));
+      loras?.forEach(async (loraMetadataItem) => {
+        try {
+          const lora = await prepareLoRAMetadataItem(loraMetadataItem, newModel?.base);
+          dispatch(loraRecalled(lora));
+        } catch {
+          return;
         }
       });
 
       dispatch(controlAdaptersReset());
-      controlnets?.forEach((controlnet) => {
-        const result = prepareControlNetMetadataItem(controlnet, newModel);
-        if (result.controlnet) {
-          dispatch(controlAdapterRecalled(result.controlnet));
+      controlnets?.forEach(async (controlNetMetadataItem) => {
+        try {
+          const controlNet = await prepareControlNetMetadataItem(controlNetMetadataItem, newModel?.base);
+          dispatch(controlAdapterRecalled(controlNet));
+        } catch {
+          return;
         }
       });
 
-      ipAdapters?.forEach((ipAdapter) => {
-        const result = prepareIPAdapterMetadataItem(ipAdapter, newModel);
-        if (result.ipAdapter) {
-          dispatch(controlAdapterRecalled(result.ipAdapter));
+      ipAdapters?.forEach(async (ipAdapterMetadataItem) => {
+        try {
+          const ipAdapter = await prepareIPAdapterMetadataItem(ipAdapterMetadataItem, newModel?.base);
+          dispatch(controlAdapterRecalled(ipAdapter));
+        } catch {
+          return;
         }
       });
 
-      t2iAdapters?.forEach((t2iAdapter) => {
-        const result = prepareT2IAdapterMetadataItem(t2iAdapter, newModel);
-        if (result.t2iAdapter) {
-          dispatch(controlAdapterRecalled(result.t2iAdapter));
+      t2iAdapters?.forEach(async (t2iAdapterMetadataItem) => {
+        try {
+          const t2iAdapter = await prepareT2IAdapterMetadataItem(t2iAdapterMetadataItem, newModel?.base);
+          dispatch(controlAdapterRecalled(t2iAdapter));
+        } catch {
+          return;
         }
       });
 
       allParameterSetToast();
     },
-    [
-      dispatch,
-      allParameterSetToast,
-      allParameterNotSetToast,
-      prepareMainModelMetadataItem,
-      prepareVAEMetadataItem,
-      prepareLoRAMetadataItem,
-      prepareControlNetMetadataItem,
-      prepareIPAdapterMetadataItem,
-      prepareT2IAdapterMetadataItem,
-    ]
+    [dispatch, allParameterSetToast, allParameterNotSetToast]
   );
 
   return {
diff --git a/invokeai/frontend/web/src/features/parameters/util/modelFetchingHelpers.ts b/invokeai/frontend/web/src/features/parameters/util/modelFetchingHelpers.ts
new file mode 100644
index 0000000000..c7d25fed8b
--- /dev/null
+++ b/invokeai/frontend/web/src/features/parameters/util/modelFetchingHelpers.ts
@@ -0,0 +1,113 @@
+import { getStore } from 'app/store/nanostores/store';
+import { isModelIdentifier } from 'features/nodes/types/common';
+import { modelsApi } from 'services/api/endpoints/models';
+import type { AnyModelConfig, BaseModelType } from 'services/api/types';
+import {
+  isControlNetModelConfig,
+  isIPAdapterModelConfig,
+  isLoRAModelConfig,
+  isNonRefinerMainModelConfig,
+  isRefinerMainModelModelConfig,
+  isT2IAdapterModelConfig,
+  isTextualInversionModelConfig,
+  isVAEModelConfig,
+} from 'services/api/types';
+
+/**
+ * Raised when a model config is unable to be fetched.
+ */
+export class ModelConfigNotFoundError extends Error {
+  /**
+   * Create ModelConfigNotFoundError
+   * @param {String} message
+   */
+  constructor(message: string) {
+    super(message);
+    this.name = this.constructor.name;
+  }
+}
+
+/**
+ * Raised when a fetched model config is of an unexpected type.
+ */
+export class InvalidModelConfigError extends Error {
+  /**
+   * Create InvalidModelConfigError
+   * @param {String} message
+   */
+  constructor(message: string) {
+    super(message);
+    this.name = this.constructor.name;
+  }
+}
+
+export const fetchModelConfig = async (key: string): Promise<AnyModelConfig> => {
+  const { dispatch } = getStore();
+  try {
+    const req = dispatch(modelsApi.endpoints.getModelConfig.initiate(key));
+    req.unsubscribe();
+    return await req.unwrap();
+  } catch {
+    throw new ModelConfigNotFoundError(`Unable to retrieve model config for key ${key}`);
+  }
+};
+
+export const fetchModelConfigWithTypeGuard = async <T extends AnyModelConfig>(
+  key: string,
+  typeGuard: (config: AnyModelConfig) => config is T
+) => {
+  const modelConfig = await fetchModelConfig(key);
+  if (!typeGuard(modelConfig)) {
+    throw new InvalidModelConfigError(`Invalid model type for key ${key}: ${modelConfig.type}`);
+  }
+  return modelConfig;
+};
+
+export const fetchMainModel = async (key: string) => {
+  return fetchModelConfigWithTypeGuard(key, isNonRefinerMainModelConfig);
+};
+
+export const fetchRefinerModel = async (key: string) => {
+  return fetchModelConfigWithTypeGuard(key, isRefinerMainModelModelConfig);
+};
+
+export const fetchVAEModel = async (key: string) => {
+  return fetchModelConfigWithTypeGuard(key, isVAEModelConfig);
+};
+
+export const fetchLoRAModel = async (key: string) => {
+  return fetchModelConfigWithTypeGuard(key, isLoRAModelConfig);
+};
+
+export const fetchControlNetModel = async (key: string) => {
+  return fetchModelConfigWithTypeGuard(key, isControlNetModelConfig);
+};
+
+export const fetchIPAdapterModel = async (key: string) => {
+  return fetchModelConfigWithTypeGuard(key, isIPAdapterModelConfig);
+};
+
+export const fetchT2IAdapterModel = async (key: string) => {
+  return fetchModelConfigWithTypeGuard(key, isT2IAdapterModelConfig);
+};
+
+export const fetchTextualInversionModel = async (key: string) => {
+  return fetchModelConfigWithTypeGuard(key, isTextualInversionModelConfig);
+};
+
+export const isBaseCompatible = (sourceBase: BaseModelType, targetBase: BaseModelType) => {
+  return sourceBase === targetBase;
+};
+
+export const raiseIfBaseIncompatible = (sourceBase: BaseModelType, targetBase?: BaseModelType, message?: string) => {
+  if (targetBase && !isBaseCompatible(sourceBase, targetBase)) {
+    throw new InvalidModelConfigError(message || `Incompatible base models: ${sourceBase} and ${targetBase}`);
+  }
+};
+
+export const getModelKey = (modelIdentifier: unknown, message?: string): string => {
+  if (!isModelIdentifier(modelIdentifier)) {
+    throw new InvalidModelConfigError(message || `Invalid model identifier: ${modelIdentifier}`);
+  }
+  return modelIdentifier.key;
+};
diff --git a/invokeai/frontend/web/src/features/parameters/util/modelMetadataHelpers.ts b/invokeai/frontend/web/src/features/parameters/util/modelMetadataHelpers.ts
new file mode 100644
index 0000000000..722073366f
--- /dev/null
+++ b/invokeai/frontend/web/src/features/parameters/util/modelMetadataHelpers.ts
@@ -0,0 +1,150 @@
+import { CONTROLNET_PROCESSORS } from 'features/controlAdapters/store/constants';
+import type { ControlNetConfig, IPAdapterConfig, T2IAdapterConfig } from 'features/controlAdapters/store/types';
+import {
+  initialControlNet,
+  initialIPAdapter,
+  initialT2IAdapter,
+} from 'features/controlAdapters/util/buildControlAdapter';
+import type { LoRA } from 'features/lora/store/loraSlice';
+import type { ModelIdentifierWithBase } from 'features/nodes/types/common';
+import { zModelIdentifierWithBase } from 'features/nodes/types/common';
+import type {
+  ControlNetMetadataItem,
+  IPAdapterMetadataItem,
+  LoRAMetadataItem,
+  T2IAdapterMetadataItem,
+} from 'features/nodes/types/metadata';
+import {
+  fetchControlNetModel,
+  fetchIPAdapterModel,
+  fetchLoRAModel,
+  fetchMainModel,
+  fetchRefinerModel,
+  fetchT2IAdapterModel,
+  fetchVAEModel,
+  getModelKey,
+  raiseIfBaseIncompatible,
+} from 'features/parameters/util/modelFetchingHelpers';
+import type { BaseModelType } from 'services/api/types';
+import { v4 as uuidv4 } from 'uuid';
+
+export const prepareMainModelMetadataItem = async (model: unknown): Promise<ModelIdentifierWithBase> => {
+  const key = getModelKey(model);
+  const mainModel = await fetchMainModel(key);
+  return zModelIdentifierWithBase.parse(mainModel);
+};
+
+export const prepareRefinerMetadataItem = async (model: unknown): Promise<ModelIdentifierWithBase> => {
+  const key = getModelKey(model);
+  const refinerModel = await fetchRefinerModel(key);
+  return zModelIdentifierWithBase.parse(refinerModel);
+};
+
+export const prepareVAEMetadataItem = async (vae: unknown, base?: BaseModelType): Promise<ModelIdentifierWithBase> => {
+  const key = getModelKey(vae);
+  const vaeModel = await fetchVAEModel(key);
+  raiseIfBaseIncompatible(vaeModel.base, base, 'VAE incompatible with currently-selected model');
+  return zModelIdentifierWithBase.parse(vaeModel);
+};
+
+export const prepareLoRAMetadataItem = async (
+  loraMetadataItem: LoRAMetadataItem,
+  base?: BaseModelType
+): Promise<LoRA> => {
+  const key = getModelKey(loraMetadataItem.lora);
+  const loraModel = await fetchLoRAModel(key);
+  raiseIfBaseIncompatible(loraModel.base, base, 'LoRA incompatible with currently-selected model');
+  return { key: loraModel.key, base: loraModel.base, weight: loraMetadataItem.weight, isEnabled: true };
+};
+
+export const prepareControlNetMetadataItem = async (
+  controlnetMetadataItem: ControlNetMetadataItem,
+  base?: BaseModelType
+): Promise<ControlNetConfig> => {
+  const key = getModelKey(controlnetMetadataItem.control_model);
+  const controlNetModel = await fetchControlNetModel(key);
+  raiseIfBaseIncompatible(controlNetModel.base, base, 'ControlNet incompatible with currently-selected model');
+
+  const { image, control_weight, begin_step_percent, end_step_percent, control_mode, resize_mode } =
+    controlnetMetadataItem;
+
+  // We don't save the original image that was processed into a control image, only the processed image
+  const processorType = 'none';
+  const processorNode = CONTROLNET_PROCESSORS.none.default;
+
+  const controlnet: ControlNetConfig = {
+    type: 'controlnet',
+    isEnabled: true,
+    model: zModelIdentifierWithBase.parse(controlNetModel),
+    weight: typeof control_weight === 'number' ? control_weight : initialControlNet.weight,
+    beginStepPct: begin_step_percent || initialControlNet.beginStepPct,
+    endStepPct: end_step_percent || initialControlNet.endStepPct,
+    controlMode: control_mode || initialControlNet.controlMode,
+    resizeMode: resize_mode || initialControlNet.resizeMode,
+    controlImage: image?.image_name || null,
+    processedControlImage: image?.image_name || null,
+    processorType,
+    processorNode,
+    shouldAutoConfig: true,
+    id: uuidv4(),
+  };
+
+  return controlnet;
+};
+
+export const prepareT2IAdapterMetadataItem = async (
+  t2iAdapterMetadataItem: T2IAdapterMetadataItem,
+  base?: BaseModelType
+): Promise<T2IAdapterConfig> => {
+  const key = getModelKey(t2iAdapterMetadataItem.t2i_adapter_model);
+  const t2iAdapterModel = await fetchT2IAdapterModel(key);
+  raiseIfBaseIncompatible(t2iAdapterModel.base, base, 'T2I Adapter incompatible with currently-selected model');
+
+  const { image, weight, begin_step_percent, end_step_percent, resize_mode } = t2iAdapterMetadataItem;
+
+  // We don't save the original image that was processed into a control image, only the processed image
+  const processorType = 'none';
+  const processorNode = CONTROLNET_PROCESSORS.none.default;
+
+  const t2iAdapter: T2IAdapterConfig = {
+    type: 't2i_adapter',
+    isEnabled: true,
+    model: zModelIdentifierWithBase.parse(t2iAdapterModel),
+    weight: typeof weight === 'number' ? weight : initialT2IAdapter.weight,
+    beginStepPct: begin_step_percent || initialT2IAdapter.beginStepPct,
+    endStepPct: end_step_percent || initialT2IAdapter.endStepPct,
+    resizeMode: resize_mode || initialT2IAdapter.resizeMode,
+    controlImage: image?.image_name || null,
+    processedControlImage: image?.image_name || null,
+    processorType,
+    processorNode,
+    shouldAutoConfig: true,
+    id: uuidv4(),
+  };
+
+  return t2iAdapter;
+};
+
+export const prepareIPAdapterMetadataItem = async (
+  ipAdapterMetadataItem: IPAdapterMetadataItem,
+  base?: BaseModelType
+): Promise<IPAdapterConfig> => {
+  const key = getModelKey(ipAdapterMetadataItem?.ip_adapter_model);
+  const ipAdapterModel = await fetchIPAdapterModel(key);
+  raiseIfBaseIncompatible(ipAdapterModel.base, base, 'T2I Adapter incompatible with currently-selected model');
+
+  const { image, weight, begin_step_percent, end_step_percent } = ipAdapterMetadataItem;
+
+  const ipAdapter: IPAdapterConfig = {
+    id: uuidv4(),
+    type: 'ip_adapter',
+    isEnabled: true,
+    controlImage: image?.image_name ?? null,
+    model: zModelIdentifierWithBase.parse(ipAdapterModel),
+    weight: weight ?? initialIPAdapter.weight,
+    beginStepPct: begin_step_percent ?? initialIPAdapter.beginStepPct,
+    endStepPct: end_step_percent ?? initialIPAdapter.endStepPct,
+  };
+
+  return ipAdapter;
+};
diff --git a/invokeai/frontend/web/src/services/api/endpoints/models.ts b/invokeai/frontend/web/src/services/api/endpoints/models.ts
index 666e0c707d..2bd1a0a246 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/models.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/models.ts
@@ -6,16 +6,16 @@ import type { operations, paths } from 'services/api/schema';
 import type {
   AnyModelConfig,
   BaseModelType,
-  ControlNetConfig,
+  ControlNetModelConfig,
   ImportModelConfig,
-  IPAdapterConfig,
-  LoRAConfig,
+  IPAdapterModelConfig,
+  LoRAModelConfig,
   MainModelConfig,
   MergeModelConfig,
   ModelType,
-  T2IAdapterConfig,
-  TextualInversionConfig,
-  VAEConfig,
+  T2IAdapterModelConfig,
+  TextualInversionModelConfig,
+  VAEModelConfig,
 } from 'services/api/types';
 
 import type { ApiTagDescription, tagTypes } from '..';
@@ -30,7 +30,7 @@ type UpdateMainModelArg = {
 type UpdateLoRAModelArg = {
   base_model: BaseModelType;
   model_name: string;
-  body: LoRAConfig;
+  body: LoRAModelConfig;
 };
 
 type UpdateMainModelResponse =
@@ -97,27 +97,27 @@ export const mainModelsAdapter = createEntityAdapter<MainModelConfig, string>({
   sortComparer: (a, b) => a.name.localeCompare(b.name),
 });
 export const mainModelsAdapterSelectors = mainModelsAdapter.getSelectors(undefined, getSelectorsOptions);
-export const loraModelsAdapter = createEntityAdapter<LoRAConfig, string>({
+export const loraModelsAdapter = createEntityAdapter<LoRAModelConfig, string>({
   selectId: (entity) => entity.key,
   sortComparer: (a, b) => a.name.localeCompare(b.name),
 });
 export const loraModelsAdapterSelectors = loraModelsAdapter.getSelectors(undefined, getSelectorsOptions);
-export const controlNetModelsAdapter = createEntityAdapter<ControlNetConfig, string>({
+export const controlNetModelsAdapter = createEntityAdapter<ControlNetModelConfig, string>({
   selectId: (entity) => entity.key,
   sortComparer: (a, b) => a.name.localeCompare(b.name),
 });
 export const controlNetModelsAdapterSelectors = controlNetModelsAdapter.getSelectors(undefined, getSelectorsOptions);
-export const ipAdapterModelsAdapter = createEntityAdapter<IPAdapterConfig, string>({
+export const ipAdapterModelsAdapter = createEntityAdapter<IPAdapterModelConfig, string>({
   selectId: (entity) => entity.key,
   sortComparer: (a, b) => a.name.localeCompare(b.name),
 });
 export const ipAdapterModelsAdapterSelectors = ipAdapterModelsAdapter.getSelectors(undefined, getSelectorsOptions);
-export const t2iAdapterModelsAdapter = createEntityAdapter<T2IAdapterConfig, string>({
+export const t2iAdapterModelsAdapter = createEntityAdapter<T2IAdapterModelConfig, string>({
   selectId: (entity) => entity.key,
   sortComparer: (a, b) => a.name.localeCompare(b.name),
 });
 export const t2iAdapterModelsAdapterSelectors = t2iAdapterModelsAdapter.getSelectors(undefined, getSelectorsOptions);
-export const textualInversionModelsAdapter = createEntityAdapter<TextualInversionConfig, string>({
+export const textualInversionModelsAdapter = createEntityAdapter<TextualInversionModelConfig, string>({
   selectId: (entity) => entity.key,
   sortComparer: (a, b) => a.name.localeCompare(b.name),
 });
@@ -125,7 +125,7 @@ export const textualInversionModelsAdapterSelectors = textualInversionModelsAdap
   undefined,
   getSelectorsOptions
 );
-export const vaeModelsAdapter = createEntityAdapter<VAEConfig, string>({
+export const vaeModelsAdapter = createEntityAdapter<VAEModelConfig, string>({
   selectId: (entity) => entity.key,
   sortComparer: (a, b) => a.name.localeCompare(b.name),
 });
@@ -162,6 +162,8 @@ const buildTransformResponse =
  */
 const buildModelsUrl = (path: string = '') => buildV2Url(`models/${path}`);
 
+// TODO(psyche): Ideally we can share the cache between the `getXYZModels` queries and `getModelConfig` query
+
 export const modelsApi = api.injectEndpoints({
   endpoints: (build) => ({
     getMainModels: build.query<EntityState<MainModelConfig, string>, BaseModelType[]>({
@@ -257,10 +259,10 @@ export const modelsApi = api.injectEndpoints({
       },
       invalidatesTags: ['Model'],
     }),
-    getLoRAModels: build.query<EntityState<LoRAConfig, string>, void>({
+    getLoRAModels: build.query<EntityState<LoRAModelConfig, string>, void>({
       query: () => ({ url: buildModelsUrl(), params: { model_type: 'lora' } }),
-      providesTags: buildProvidesTags<LoRAConfig>('LoRAModel'),
-      transformResponse: buildTransformResponse<LoRAConfig>(loraModelsAdapter),
+      providesTags: buildProvidesTags<LoRAModelConfig>('LoRAModel'),
+      transformResponse: buildTransformResponse<LoRAModelConfig>(loraModelsAdapter),
     }),
     updateLoRAModels: build.mutation<UpdateLoRAModelResponse, UpdateLoRAModelArg>({
       query: ({ base_model, model_name, body }) => {
@@ -281,30 +283,30 @@ export const modelsApi = api.injectEndpoints({
       },
       invalidatesTags: [{ type: 'LoRAModel', id: LIST_TAG }],
     }),
-    getControlNetModels: build.query<EntityState<ControlNetConfig, string>, void>({
+    getControlNetModels: build.query<EntityState<ControlNetModelConfig, string>, void>({
       query: () => ({ url: buildModelsUrl(), params: { model_type: 'controlnet' } }),
-      providesTags: buildProvidesTags<ControlNetConfig>('ControlNetModel'),
-      transformResponse: buildTransformResponse<ControlNetConfig>(controlNetModelsAdapter),
+      providesTags: buildProvidesTags<ControlNetModelConfig>('ControlNetModel'),
+      transformResponse: buildTransformResponse<ControlNetModelConfig>(controlNetModelsAdapter),
     }),
-    getIPAdapterModels: build.query<EntityState<IPAdapterConfig, string>, void>({
+    getIPAdapterModels: build.query<EntityState<IPAdapterModelConfig, string>, void>({
       query: () => ({ url: buildModelsUrl(), params: { model_type: 'ip_adapter' } }),
-      providesTags: buildProvidesTags<IPAdapterConfig>('IPAdapterModel'),
-      transformResponse: buildTransformResponse<IPAdapterConfig>(ipAdapterModelsAdapter),
+      providesTags: buildProvidesTags<IPAdapterModelConfig>('IPAdapterModel'),
+      transformResponse: buildTransformResponse<IPAdapterModelConfig>(ipAdapterModelsAdapter),
     }),
-    getT2IAdapterModels: build.query<EntityState<T2IAdapterConfig, string>, void>({
+    getT2IAdapterModels: build.query<EntityState<T2IAdapterModelConfig, string>, void>({
       query: () => ({ url: buildModelsUrl(), params: { model_type: 't2i_adapter' } }),
-      providesTags: buildProvidesTags<T2IAdapterConfig>('T2IAdapterModel'),
-      transformResponse: buildTransformResponse<T2IAdapterConfig>(t2iAdapterModelsAdapter),
+      providesTags: buildProvidesTags<T2IAdapterModelConfig>('T2IAdapterModel'),
+      transformResponse: buildTransformResponse<T2IAdapterModelConfig>(t2iAdapterModelsAdapter),
     }),
-    getVaeModels: build.query<EntityState<VAEConfig, string>, void>({
+    getVaeModels: build.query<EntityState<VAEModelConfig, string>, void>({
       query: () => ({ url: buildModelsUrl(), params: { model_type: 'vae' } }),
-      providesTags: buildProvidesTags<VAEConfig>('VaeModel'),
-      transformResponse: buildTransformResponse<VAEConfig>(vaeModelsAdapter),
+      providesTags: buildProvidesTags<VAEModelConfig>('VaeModel'),
+      transformResponse: buildTransformResponse<VAEModelConfig>(vaeModelsAdapter),
     }),
-    getTextualInversionModels: build.query<EntityState<TextualInversionConfig, string>, void>({
+    getTextualInversionModels: build.query<EntityState<TextualInversionModelConfig, string>, void>({
       query: () => ({ url: buildModelsUrl(), params: { model_type: 'embedding' } }),
-      providesTags: buildProvidesTags<TextualInversionConfig>('TextualInversionModel'),
-      transformResponse: buildTransformResponse<TextualInversionConfig>(textualInversionModelsAdapter),
+      providesTags: buildProvidesTags<TextualInversionModelConfig>('TextualInversionModel'),
+      transformResponse: buildTransformResponse<TextualInversionModelConfig>(textualInversionModelsAdapter),
     }),
     getModelsInFolder: build.query<SearchFolderResponse, SearchFolderArg>({
       query: (arg) => {

From abc569c2dd5f63e4bb9d6b8ee369b2526f65dcbd Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Thu, 22 Feb 2024 22:42:57 +1100
Subject: [PATCH 246/411] fix(ui): roll back utility-types

It's `Required` util does not distribute over unions as expected. Also we have `ts-toolbelt` already for some utils.
---
 invokeai/frontend/web/package.json              | 1 -
 invokeai/frontend/web/pnpm-lock.yaml            | 8 --------
 invokeai/frontend/web/src/services/api/types.ts | 5 ++---
 3 files changed, 2 insertions(+), 12 deletions(-)

diff --git a/invokeai/frontend/web/package.json b/invokeai/frontend/web/package.json
index 0bf236ee38..48bad31000 100644
--- a/invokeai/frontend/web/package.json
+++ b/invokeai/frontend/web/package.json
@@ -145,7 +145,6 @@
     "ts-toolbelt": "^9.6.0",
     "tsafe": "^1.6.6",
     "typescript": "^5.3.3",
-    "utility-types": "^3.11.0",
     "vite": "^5.1.3",
     "vite-plugin-css-injected-by-js": "^3.4.0",
     "vite-plugin-dts": "^3.7.2",
diff --git a/invokeai/frontend/web/pnpm-lock.yaml b/invokeai/frontend/web/pnpm-lock.yaml
index f2abdd87bf..d79d482d08 100644
--- a/invokeai/frontend/web/pnpm-lock.yaml
+++ b/invokeai/frontend/web/pnpm-lock.yaml
@@ -268,9 +268,6 @@ devDependencies:
   typescript:
     specifier: ^5.3.3
     version: 5.3.3
-  utility-types:
-    specifier: ^3.11.0
-    version: 3.11.0
   vite:
     specifier: ^5.1.3
     version: 5.1.3(@types/node@20.11.19)
@@ -14147,11 +14144,6 @@ packages:
       which-typed-array: 1.1.14
     dev: true
 
-  /utility-types@3.11.0:
-    resolution: {integrity: sha512-6Z7Ma2aVEWisaL6TvBCy7P8rm2LQoPv6dJ7ecIaIixHcwfbJ0x7mWdbcwlIM5IGQxPZSFYeqRCqlOOeKoJYMkw==}
-    engines: {node: '>= 4'}
-    dev: true
-
   /utils-merge@1.0.1:
     resolution: {integrity: sha512-pMZTvIkT1d+TFGvDOqodOclx0QWkkgi6Tdoa8gC8ffGAAqz9pzPTZWAybbsHHoED/ztMtkv/VoYTYyShUn81hA==}
     engines: {node: '>= 0.4.0'}
diff --git a/invokeai/frontend/web/src/services/api/types.ts b/invokeai/frontend/web/src/services/api/types.ts
index d561173337..6f6018d974 100644
--- a/invokeai/frontend/web/src/services/api/types.ts
+++ b/invokeai/frontend/web/src/services/api/types.ts
@@ -2,7 +2,6 @@ import type { UseToastOptions } from '@invoke-ai/ui-library';
 import type { EntityState } from '@reduxjs/toolkit';
 import type { components, paths } from 'services/api/schema';
 import type { O } from 'ts-toolbelt';
-import type { Overwrite } from 'utility-types';
 
 export type S = components['schemas'];
 
@@ -72,8 +71,8 @@ export type TextualInversionModelConfig = S['TextualInversionConfig'];
 export type DiffusersModelConfig = S['MainDiffusersConfig'];
 export type CheckpointModelConfig = S['MainCheckpointConfig'];
 export type MainModelConfig = DiffusersModelConfig | CheckpointModelConfig;
-export type RefinerMainModelConfig = Overwrite<MainModelConfig, { base: 'sdxl-refiner' }>;
-export type NonRefinerMainModelConfig = Overwrite<MainModelConfig, { base: 'any' | 'sd-1' | 'sd-2' | 'sdxl' }>;
+export type RefinerMainModelConfig = Omit<MainModelConfig, 'base'> & { base: 'sdxl-refiner' };
+export type NonRefinerMainModelConfig = Omit<MainModelConfig, 'base'> & { base: 'any' | 'sd-1' | 'sd-2' | 'sdxl' };
 export type AnyModelConfig =
   | LoRAModelConfig
   | VAEModelConfig

From 008716040b8dd2488474028570dceebb6d837e3d Mon Sep 17 00:00:00 2001
From: Brandon Rising <contact@brandonrising.com>
Date: Thu, 22 Feb 2024 14:27:49 -0500
Subject: [PATCH 247/411] Allow users to run model manager without cuda

---
 .../app/services/model_install/model_install_default.py  | 2 +-
 .../app/services/model_manager/model_manager_base.py     | 5 ++++-
 .../app/services/model_manager/model_manager_default.py  | 9 ++++++++-
 3 files changed, 13 insertions(+), 3 deletions(-)

diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py
index 9b771c5159..c2718b5b2e 100644
--- a/invokeai/app/services/model_install/model_install_default.py
+++ b/invokeai/app/services/model_install/model_install_default.py
@@ -543,7 +543,7 @@ class ModelInstallService(ModelInstallServiceBase):
         self, model_path: Path, config: Optional[Dict[str, Any]] = None, info: Optional[AnyModelConfig] = None
     ) -> str:
         info = info or ModelProbe.probe(model_path, config)
-        key = self._create_key()
+        key = info.key or self._create_key()
 
         model_path = model_path.absolute()
         if model_path.is_relative_to(self.app_config.models_path):
diff --git a/invokeai/app/services/model_manager/model_manager_base.py b/invokeai/app/services/model_manager/model_manager_base.py
index c25aa6fb47..938e14adcb 100644
--- a/invokeai/app/services/model_manager/model_manager_base.py
+++ b/invokeai/app/services/model_manager/model_manager_base.py
@@ -1,5 +1,7 @@
 # Copyright (c) 2023 Lincoln D. Stein and the InvokeAI Team
 
+import torch
+
 from abc import ABC, abstractmethod
 from typing import Optional
 
@@ -32,9 +34,10 @@ class ModelManagerServiceBase(ABC):
     def build_model_manager(
         cls,
         app_config: InvokeAIAppConfig,
-        db: SqliteDatabase,
+        model_record_service: ModelRecordServiceBase,
         download_queue: DownloadQueueServiceBase,
         events: EventServiceBase,
+        execution_device: torch.device,
     ) -> Self:
         """
         Construct the model manager service instance.
diff --git a/invokeai/app/services/model_manager/model_manager_default.py b/invokeai/app/services/model_manager/model_manager_default.py
index d029f9e033..2276111586 100644
--- a/invokeai/app/services/model_manager/model_manager_default.py
+++ b/invokeai/app/services/model_manager/model_manager_default.py
@@ -1,6 +1,8 @@
 # Copyright (c) 2023 Lincoln D. Stein and the InvokeAI Team
 """Implementation of ModelManagerServiceBase."""
 
+import torch
+
 from typing import Optional
 
 from typing_extensions import Self
@@ -9,6 +11,7 @@ from invokeai.app.services.invoker import Invoker
 from invokeai.app.services.shared.invocation_context import InvocationContextData
 from invokeai.backend.model_manager import AnyModelConfig, BaseModelType, LoadedModel, ModelType, SubModelType
 from invokeai.backend.model_manager.load import ModelCache, ModelConvertCache, ModelLoaderRegistry
+from invokeai.backend.util.devices import choose_torch_device
 from invokeai.backend.util.logging import InvokeAILogger
 
 from ..config import InvokeAIAppConfig
@@ -119,6 +122,7 @@ class ModelManagerService(ModelManagerServiceBase):
         model_record_service: ModelRecordServiceBase,
         download_queue: DownloadQueueServiceBase,
         events: EventServiceBase,
+        execution_device: torch.device = choose_torch_device(),
     ) -> Self:
         """
         Construct the model manager service instance.
@@ -129,7 +133,10 @@ class ModelManagerService(ModelManagerServiceBase):
         logger.setLevel(app_config.log_level.upper())
 
         ram_cache = ModelCache(
-            max_cache_size=app_config.ram_cache_size, max_vram_cache_size=app_config.vram_cache_size, logger=logger
+            max_cache_size=app_config.ram_cache_size,
+            max_vram_cache_size=app_config.vram_cache_size,
+            logger=logger,
+            execution_device=execution_device,
         )
         convert_cache = ModelConvertCache(
             cache_path=app_config.models_convert_cache_path, max_size=app_config.convert_cache_size

From de9287a3e4c3fdb4d39d5db47f6ee9174574aad5 Mon Sep 17 00:00:00 2001
From: Brandon Rising <contact@brandonrising.com>
Date: Thu, 22 Feb 2024 14:54:48 -0500
Subject: [PATCH 248/411] Run ruff

---
 invokeai/app/services/model_manager/model_manager_base.py    | 4 +---
 invokeai/app/services/model_manager/model_manager_default.py | 3 +--
 2 files changed, 2 insertions(+), 5 deletions(-)

diff --git a/invokeai/app/services/model_manager/model_manager_base.py b/invokeai/app/services/model_manager/model_manager_base.py
index 938e14adcb..6e886df652 100644
--- a/invokeai/app/services/model_manager/model_manager_base.py
+++ b/invokeai/app/services/model_manager/model_manager_base.py
@@ -1,10 +1,9 @@
 # Copyright (c) 2023 Lincoln D. Stein and the InvokeAI Team
 
-import torch
-
 from abc import ABC, abstractmethod
 from typing import Optional
 
+import torch
 from typing_extensions import Self
 
 from invokeai.app.services.invoker import Invoker
@@ -18,7 +17,6 @@ from ..events.events_base import EventServiceBase
 from ..model_install import ModelInstallServiceBase
 from ..model_load import ModelLoadServiceBase
 from ..model_records import ModelRecordServiceBase
-from ..shared.sqlite.sqlite_database import SqliteDatabase
 
 
 class ModelManagerServiceBase(ABC):
diff --git a/invokeai/app/services/model_manager/model_manager_default.py b/invokeai/app/services/model_manager/model_manager_default.py
index 2276111586..7d4b248323 100644
--- a/invokeai/app/services/model_manager/model_manager_default.py
+++ b/invokeai/app/services/model_manager/model_manager_default.py
@@ -1,10 +1,9 @@
 # Copyright (c) 2023 Lincoln D. Stein and the InvokeAI Team
 """Implementation of ModelManagerServiceBase."""
 
-import torch
-
 from typing import Optional
 
+import torch
 from typing_extensions import Self
 
 from invokeai.app.services.invoker import Invoker

From 65b91356d0abd7bab61fe618571e189c1a0aa09c Mon Sep 17 00:00:00 2001
From: Brandon Rising <contact@brandonrising.com>
Date: Fri, 23 Feb 2024 10:19:20 -0500
Subject: [PATCH 249/411] Remove passing keys in on register

---
 invokeai/app/services/model_install/model_install_default.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py
index c2718b5b2e..9b771c5159 100644
--- a/invokeai/app/services/model_install/model_install_default.py
+++ b/invokeai/app/services/model_install/model_install_default.py
@@ -543,7 +543,7 @@ class ModelInstallService(ModelInstallServiceBase):
         self, model_path: Path, config: Optional[Dict[str, Any]] = None, info: Optional[AnyModelConfig] = None
     ) -> str:
         info = info or ModelProbe.probe(model_path, config)
-        key = info.key or self._create_key()
+        key = self._create_key()
 
         model_path = model_path.absolute()
         if model_path.is_relative_to(self.app_config.models_path):

From c778ab8db4a6809826904ec476921376dccf7a4b Mon Sep 17 00:00:00 2001
From: Brandon Rising <contact@brandonrising.com>
Date: Fri, 23 Feb 2024 12:57:54 -0500
Subject: [PATCH 250/411] Allow passing in key on register

---
 .../app/services/model_install/model_install_default.py   | 8 +++++---
 invokeai/backend/model_manager/probe.py                   | 2 +-
 2 files changed, 6 insertions(+), 4 deletions(-)

diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py
index 9b771c5159..2419fbe5da 100644
--- a/invokeai/app/services/model_install/model_install_default.py
+++ b/invokeai/app/services/model_install/model_install_default.py
@@ -542,8 +542,10 @@ class ModelInstallService(ModelInstallServiceBase):
     def _register(
         self, model_path: Path, config: Optional[Dict[str, Any]] = None, info: Optional[AnyModelConfig] = None
     ) -> str:
-        info = info or ModelProbe.probe(model_path, config)
         key = self._create_key()
+        if config and not config.get('key', None):
+            config['key'] = key
+        info = info or ModelProbe.probe(model_path, config)
 
         model_path = model_path.absolute()
         if model_path.is_relative_to(self.app_config.models_path):
@@ -556,8 +558,8 @@ class ModelInstallService(ModelInstallServiceBase):
             # make config relative to our root
             legacy_conf = (self.app_config.root_dir / self.app_config.legacy_conf_dir / info.config).resolve()
             info.config = legacy_conf.relative_to(self.app_config.root_dir).as_posix()
-        self.record_store.add_model(key, info)
-        return key
+        self.record_store.add_model(info.key, info)
+        return info.key
 
     def _next_id(self) -> int:
         with self._lock:
diff --git a/invokeai/backend/model_manager/probe.py b/invokeai/backend/model_manager/probe.py
index 7de4289466..c33254ef4e 100644
--- a/invokeai/backend/model_manager/probe.py
+++ b/invokeai/backend/model_manager/probe.py
@@ -188,7 +188,7 @@ class ModelProbe(object):
                 and fields["prediction_type"] == SchedulerPredictionType.VPrediction
             )
 
-        model_info = ModelConfigFactory.make_config(fields)
+        model_info = ModelConfigFactory.make_config(fields, key=fields.get("key", None))
         return model_info
 
     @classmethod

From 55f3c6e7216ae6d5509887ffe6a3ef5b9e7b5f12 Mon Sep 17 00:00:00 2001
From: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Date: Tue, 20 Feb 2024 10:03:10 -0500
Subject: [PATCH 251/411] get old UI working somewhat with new endpoints

---
 .../subpanels/AddModelsPanel/AddModels.tsx    |   6 +-
 .../AddModelsPanel/SimpleAddModels.tsx        |   5 +-
 .../subpanels/ModelManagerPanel.tsx           |  14 +--
 .../ModelManagerPanel/CheckpointModelEdit.tsx |  37 +++----
 .../ModelManagerPanel/DiffusersModelEdit.tsx  |  32 +++---
 .../ModelManagerPanel/LoRAModelEdit.tsx       |  30 +++---
 .../ModelManagerPanel/ModelConvert.tsx        |  14 +--
 .../subpanels/ModelManagerPanel/ModelList.tsx |   7 +-
 .../ModelManagerPanel/ModelListItem.tsx       |  28 ++---
 .../web/src/services/api/endpoints/models.ts  | 102 +++++++-----------
 10 files changed, 120 insertions(+), 155 deletions(-)

diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/AddModels.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/AddModels.tsx
index cb50334c99..9b4b95be9e 100644
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/AddModels.tsx
+++ b/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/AddModels.tsx
@@ -1,15 +1,18 @@
-import { Button, ButtonGroup, Flex } from '@invoke-ai/ui-library';
+import { Button, ButtonGroup, Flex, Text } from '@invoke-ai/ui-library';
 import { memo, useCallback, useState } from 'react';
 import { useTranslation } from 'react-i18next';
 
 import AdvancedAddModels from './AdvancedAddModels';
 import SimpleAddModels from './SimpleAddModels';
+import { useGetModelImportsQuery } from '../../../../services/api/endpoints/models';
 
 const AddModels = () => {
   const { t } = useTranslation();
   const [addModelMode, setAddModelMode] = useState<'simple' | 'advanced'>('simple');
   const handleAddModelSimple = useCallback(() => setAddModelMode('simple'), []);
   const handleAddModelAdvanced = useCallback(() => setAddModelMode('advanced'), []);
+  const { data } = useGetModelImportsQuery({});
+  console.log({ data });
   return (
     <Flex flexDirection="column" width="100%" overflow="scroll" maxHeight={window.innerHeight - 250} gap={4}>
       <ButtonGroup>
@@ -24,6 +27,7 @@ const AddModels = () => {
         {addModelMode === 'simple' && <SimpleAddModels />}
         {addModelMode === 'advanced' && <AdvancedAddModels />}
       </Flex>
+      <Flex>{data?.map((model) => <Text>{model.status}</Text>)}</Flex>
     </Flex>
   );
 };
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/SimpleAddModels.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/SimpleAddModels.tsx
index d7f705aedc..0124d6d570 100644
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/SimpleAddModels.tsx
+++ b/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/SimpleAddModels.tsx
@@ -36,11 +36,10 @@ const SimpleAddModels = () => {
 
   const handleAddModelSubmit = (values: ExtendedImportModelConfig) => {
     const importModelResponseBody = {
-      location: values.location,
-      prediction_type: values.prediction_type === 'none' ? undefined : values.prediction_type,
+      config: values.prediction_type === 'none' ? undefined : values.prediction_type,
     };
 
-    importMainModel({ body: importModelResponseBody })
+    importMainModel({ source: values.location, config: importModelResponseBody })
       .unwrap()
       .then((_) => {
         dispatch(
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel.tsx
index 15149b339b..dab4e0b872 100644
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel.tsx
+++ b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel.tsx
@@ -2,13 +2,13 @@ import { Flex, Text } from '@invoke-ai/ui-library';
 import { memo, useState } from 'react';
 import { useTranslation } from 'react-i18next';
 import { ALL_BASE_MODELS } from 'services/api/constants';
-import type { DiffusersModelConfig, LoRAConfig, MainModelConfig } from 'services/api/endpoints/models';
 import { useGetLoRAModelsQuery, useGetMainModelsQuery } from 'services/api/endpoints/models';
 
 import CheckpointModelEdit from './ModelManagerPanel/CheckpointModelEdit';
 import DiffusersModelEdit from './ModelManagerPanel/DiffusersModelEdit';
 import LoRAModelEdit from './ModelManagerPanel/LoRAModelEdit';
 import ModelList from './ModelManagerPanel/ModelList';
+import { DiffusersModelConfig, LoRAConfig, MainModelConfig } from '../../../services/api/types';
 
 const ModelManagerPanel = () => {
   const [selectedModelId, setSelectedModelId] = useState<string>();
@@ -41,16 +41,16 @@ const ModelEdit = (props: ModelEditProps) => {
   const { t } = useTranslation();
   const { model } = props;
 
-  if (model?.model_format === 'checkpoint') {
-    return <CheckpointModelEdit key={model.id} model={model} />;
+  if (model?.format === 'checkpoint') {
+    return <CheckpointModelEdit key={model.key} model={model} />;
   }
 
-  if (model?.model_format === 'diffusers') {
-    return <DiffusersModelEdit key={model.id} model={model as DiffusersModelConfig} />;
+  if (model?.format === 'diffusers') {
+    return <DiffusersModelEdit key={model.key} model={model as DiffusersModelConfig} />;
   }
 
-  if (model?.model_type === 'lora') {
-    return <LoRAModelEdit key={model.id} model={model} />;
+  if (model?.type === 'lora') {
+    return <LoRAModelEdit key={model.key} model={model} />;
   }
 
   return (
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/CheckpointModelEdit.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/CheckpointModelEdit.tsx
index 43707308e0..0dd8a7add6 100644
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/CheckpointModelEdit.tsx
+++ b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/CheckpointModelEdit.tsx
@@ -21,11 +21,9 @@ import { memo, useCallback, useEffect, useState } from 'react';
 import type { SubmitHandler } from 'react-hook-form';
 import { useForm } from 'react-hook-form';
 import { useTranslation } from 'react-i18next';
-import type { CheckpointModelConfig } from 'services/api/endpoints/models';
-import { useGetCheckpointConfigsQuery, useUpdateMainModelsMutation } from 'services/api/endpoints/models';
-import type { CheckpointModelConfig } from 'services/api/types';
-
+import { useGetCheckpointConfigsQuery, useUpdateModelsMutation } from 'services/api/endpoints/models';
 import ModelConvert from './ModelConvert';
+import { CheckpointModelConfig } from '../../../../services/api/types';
 
 type CheckpointModelEditProps = {
   model: CheckpointModelConfig;
@@ -34,7 +32,7 @@ type CheckpointModelEditProps = {
 const CheckpointModelEdit = (props: CheckpointModelEditProps) => {
   const { model } = props;
 
-  const [updateMainModel, { isLoading }] = useUpdateMainModelsMutation();
+  const [updateModel, { isLoading }] = useUpdateModelsMutation();
   const { data: availableCheckpointConfigs } = useGetCheckpointConfigsQuery();
 
   const [useCustomConfig, setUseCustomConfig] = useState<boolean>(false);
@@ -56,12 +54,12 @@ const CheckpointModelEdit = (props: CheckpointModelEditProps) => {
     reset,
   } = useForm<CheckpointModelConfig>({
     defaultValues: {
-      model_name: model.model_name ? model.model_name : '',
-      base_model: model.base_model,
-      model_type: 'main',
+      name: model.name ? model.name : '',
+      base: model.base,
+      type: 'main',
       path: model.path ? model.path : '',
       description: model.description ? model.description : '',
-      model_format: 'checkpoint',
+      format: 'checkpoint',
       vae: model.vae ? model.vae : '',
       config: model.config ? model.config : '',
       variant: model.variant,
@@ -74,11 +72,10 @@ const CheckpointModelEdit = (props: CheckpointModelEditProps) => {
   const onSubmit = useCallback<SubmitHandler<CheckpointModelConfig>>(
     (values) => {
       const responseBody = {
-        base_model: model.base_model,
-        model_name: model.model_name,
+        key: model.key,
         body: values,
       };
-      updateMainModel(responseBody)
+      updateModel(responseBody)
         .unwrap()
         .then((payload) => {
           reset(payload as CheckpointModelConfig, { keepDefaultValues: true });
@@ -103,7 +100,7 @@ const CheckpointModelEdit = (props: CheckpointModelEditProps) => {
           );
         });
     },
-    [dispatch, model.base_model, model.model_name, reset, t, updateMainModel]
+    [dispatch, model.key, reset, t, updateModel]
   );
 
   return (
@@ -111,13 +108,13 @@ const CheckpointModelEdit = (props: CheckpointModelEditProps) => {
       <Flex justifyContent="space-between" alignItems="center">
         <Flex flexDirection="column">
           <Text fontSize="lg" fontWeight="bold">
-            {model.model_name}
+            {model.name}
           </Text>
           <Text fontSize="sm" color="base.400">
-            {MODEL_TYPE_MAP[model.base_model]} {t('modelManager.model')}
+            {MODEL_TYPE_MAP[model.base]} {t('modelManager.model')}
           </Text>
         </Flex>
-        {![''].includes(model.base_model) ? (
+        {![''].includes(model.base) ? (
           <ModelConvert model={model} />
         ) : (
           <Badge p={2} borderRadius={4} bg="error.400">
@@ -130,20 +127,20 @@ const CheckpointModelEdit = (props: CheckpointModelEditProps) => {
       <Flex flexDirection="column" maxHeight={window.innerHeight - 270} overflowY="scroll">
         <form onSubmit={handleSubmit(onSubmit)}>
           <Flex flexDirection="column" overflowY="scroll" gap={4}>
-            <FormControl isInvalid={Boolean(errors.model_name)}>
+            <FormControl isInvalid={Boolean(errors.name)}>
               <FormLabel>{t('modelManager.name')}</FormLabel>
               <Input
-                {...register('model_name', {
+                {...register('name', {
                   validate: (value) => value.trim().length > 3 || 'Must be at least 3 characters',
                 })}
               />
-              {errors.model_name?.message && <FormErrorMessage>{errors.model_name?.message}</FormErrorMessage>}
+              {errors.name?.message && <FormErrorMessage>{errors.name?.message}</FormErrorMessage>}
             </FormControl>
             <FormControl>
               <FormLabel>{t('modelManager.description')}</FormLabel>
               <Input {...register('description')} />
             </FormControl>
-            <BaseModelSelect<CheckpointModelConfig> control={control} name="base_model" />
+            <BaseModelSelect<CheckpointModelConfig> control={control} name="base" />
             <ModelVariantSelect<CheckpointModelConfig> control={control} name="variant" />
             <FormControl isInvalid={Boolean(errors.path)}>
               <FormLabel>{t('modelManager.modelLocation')}</FormLabel>
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/DiffusersModelEdit.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/DiffusersModelEdit.tsx
index bf6349234f..5be9a5631c 100644
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/DiffusersModelEdit.tsx
+++ b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/DiffusersModelEdit.tsx
@@ -9,9 +9,8 @@ import { memo, useCallback } from 'react';
 import type { SubmitHandler } from 'react-hook-form';
 import { useForm } from 'react-hook-form';
 import { useTranslation } from 'react-i18next';
-import type { DiffusersModelConfig } from 'services/api/endpoints/models';
-import { useUpdateMainModelsMutation } from 'services/api/endpoints/models';
 import type { DiffusersModelConfig } from 'services/api/types';
+import { useUpdateModelsMutation } from '../../../../services/api/endpoints/models';
 
 type DiffusersModelEditProps = {
   model: DiffusersModelConfig;
@@ -20,7 +19,7 @@ type DiffusersModelEditProps = {
 const DiffusersModelEdit = (props: DiffusersModelEditProps) => {
   const { model } = props;
 
-  const [updateMainModel, { isLoading }] = useUpdateMainModelsMutation();
+  const [updateModel, { isLoading }] = useUpdateModelsMutation();
 
   const dispatch = useAppDispatch();
   const { t } = useTranslation();
@@ -33,12 +32,12 @@ const DiffusersModelEdit = (props: DiffusersModelEditProps) => {
     reset,
   } = useForm<DiffusersModelConfig>({
     defaultValues: {
-      model_name: model.model_name ? model.model_name : '',
-      base_model: model.base_model,
-      model_type: 'main',
+      name: model.name ? model.name : '',
+      base: model.base,
+      type: 'main',
       path: model.path ? model.path : '',
       description: model.description ? model.description : '',
-      model_format: 'diffusers',
+      format: 'diffusers',
       vae: model.vae ? model.vae : '',
       variant: model.variant,
     },
@@ -48,12 +47,11 @@ const DiffusersModelEdit = (props: DiffusersModelEditProps) => {
   const onSubmit = useCallback<SubmitHandler<DiffusersModelConfig>>(
     (values) => {
       const responseBody = {
-        base_model: model.base_model,
-        model_name: model.model_name,
+        key: model.key,
         body: values,
       };
 
-      updateMainModel(responseBody)
+      updateModel(responseBody)
         .unwrap()
         .then((payload) => {
           reset(payload as DiffusersModelConfig, { keepDefaultValues: true });
@@ -78,37 +76,37 @@ const DiffusersModelEdit = (props: DiffusersModelEditProps) => {
           );
         });
     },
-    [dispatch, model.base_model, model.model_name, reset, t, updateMainModel]
+    [dispatch, model.key, reset, t, updateModel]
   );
 
   return (
     <Flex flexDirection="column" rowGap={4} width="100%">
       <Flex flexDirection="column">
         <Text fontSize="lg" fontWeight="bold">
-          {model.model_name}
+          {model.name}
         </Text>
         <Text fontSize="sm" color="base.400">
-          {MODEL_TYPE_MAP[model.base_model]} {t('modelManager.model')}
+          {MODEL_TYPE_MAP[model.base]} {t('modelManager.model')}
         </Text>
       </Flex>
       <Divider />
 
       <form onSubmit={handleSubmit(onSubmit)}>
         <Flex flexDirection="column" overflowY="scroll" gap={4}>
-          <FormControl isInvalid={Boolean(errors.model_name)}>
+          <FormControl isInvalid={Boolean(errors.name)}>
             <FormLabel>{t('modelManager.name')}</FormLabel>
             <Input
-              {...register('model_name', {
+              {...register('name', {
                 validate: (value) => value.trim().length > 3 || 'Must be at least 3 characters',
               })}
             />
-            {errors.model_name?.message && <FormErrorMessage>{errors.model_name?.message}</FormErrorMessage>}
+            {errors.name?.message && <FormErrorMessage>{errors.name?.message}</FormErrorMessage>}
           </FormControl>
           <FormControl>
             <FormLabel>{t('modelManager.description')}</FormLabel>
             <Input {...register('description')} />
           </FormControl>
-          <BaseModelSelect<DiffusersModelConfig> control={control} name="base_model" />
+          <BaseModelSelect<DiffusersModelConfig> control={control} name="base" />
           <ModelVariantSelect<DiffusersModelConfig> control={control} name="variant" />
           <FormControl isInvalid={Boolean(errors.path)}>
             <FormLabel>{t('modelManager.modelLocation')}</FormLabel>
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/LoRAModelEdit.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/LoRAModelEdit.tsx
index 1a8f235aaf..edb73e8275 100644
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/LoRAModelEdit.tsx
+++ b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/LoRAModelEdit.tsx
@@ -8,7 +8,6 @@ import { memo, useCallback } from 'react';
 import type { SubmitHandler } from 'react-hook-form';
 import { useForm } from 'react-hook-form';
 import { useTranslation } from 'react-i18next';
-import { useUpdateLoRAModelsMutation } from 'services/api/endpoints/models';
 import type { LoRAModelConfig } from 'services/api/types';
 
 type LoRAModelEditProps = {
@@ -18,7 +17,7 @@ type LoRAModelEditProps = {
 const LoRAModelEdit = (props: LoRAModelEditProps) => {
   const { model } = props;
 
-  const [updateLoRAModel, { isLoading }] = useUpdateLoRAModelsMutation();
+  const [updateModel, { isLoading }] = useUpdateModelsMutation();
 
   const dispatch = useAppDispatch();
   const { t } = useTranslation();
@@ -31,12 +30,12 @@ const LoRAModelEdit = (props: LoRAModelEditProps) => {
     reset,
   } = useForm<LoRAModelConfig>({
     defaultValues: {
-      model_name: model.model_name ? model.model_name : '',
-      base_model: model.base_model,
-      model_type: 'lora',
+      name: model.name ? model.name : '',
+      base: model.base,
+      type: 'lora',
       path: model.path ? model.path : '',
       description: model.description ? model.description : '',
-      model_format: model.model_format,
+      format: model.format,
     },
     mode: 'onChange',
   });
@@ -44,12 +43,11 @@ const LoRAModelEdit = (props: LoRAModelEditProps) => {
   const onSubmit = useCallback<SubmitHandler<LoRAModelConfig>>(
     (values) => {
       const responseBody = {
-        base_model: model.base_model,
-        model_name: model.model_name,
+        key: model.key,
         body: values,
       };
 
-      updateLoRAModel(responseBody)
+      updateModel(responseBody)
         .unwrap()
         .then((payload) => {
           reset(payload as LoRAModelConfig, { keepDefaultValues: true });
@@ -74,17 +72,17 @@ const LoRAModelEdit = (props: LoRAModelEditProps) => {
           );
         });
     },
-    [dispatch, model.base_model, model.model_name, reset, t, updateLoRAModel]
+    [dispatch, model.key, reset, t, updateModel]
   );
 
   return (
     <Flex flexDirection="column" rowGap={4} width="100%">
       <Flex flexDirection="column">
         <Text fontSize="lg" fontWeight="bold">
-          {model.model_name}
+          {model.name}
         </Text>
         <Text fontSize="sm" color="base.400">
-          {MODEL_TYPE_MAP[model.base_model]} {t('modelManager.model')} ⋅ {LORA_MODEL_FORMAT_MAP[model.model_format]}{' '}
+          {MODEL_TYPE_MAP[model.base]} {t('modelManager.model')} ⋅ {LORA_MODEL_FORMAT_MAP[model.format]}{' '}
           {t('common.format')}
         </Text>
       </Flex>
@@ -92,20 +90,20 @@ const LoRAModelEdit = (props: LoRAModelEditProps) => {
 
       <form onSubmit={handleSubmit(onSubmit)}>
         <Flex flexDirection="column" overflowY="scroll" gap={4}>
-          <FormControl isInvalid={Boolean(errors.model_name)}>
+          <FormControl isInvalid={Boolean(errors.name)}>
             <FormLabel>{t('modelManager.name')}</FormLabel>
             <Input
-              {...register('model_name', {
+              {...register('name', {
                 validate: (value) => value.trim().length > 3 || 'Must be at least 3 characters',
               })}
             />
-            {errors.model_name?.message && <FormErrorMessage>{errors.model_name?.message}</FormErrorMessage>}
+            {errors.name?.message && <FormErrorMessage>{errors.name?.message}</FormErrorMessage>}
           </FormControl>
           <FormControl>
             <FormLabel>{t('modelManager.description')}</FormLabel>
             <Input {...register('description')} />
           </FormControl>
-          <BaseModelSelect<LoRAModelConfig> control={control} name="base_model" />
+          <BaseModelSelect<LoRAModelConfig> control={control} name="base" />
 
           <FormControl isInvalid={Boolean(errors.path)}>
             <FormLabel>{t('modelManager.modelLocation')}</FormLabel>
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelConvert.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelConvert.tsx
index 6e34d5039e..9a2746abe6 100644
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelConvert.tsx
+++ b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelConvert.tsx
@@ -54,8 +54,8 @@ const ModelConvert = (props: ModelConvertProps) => {
 
   const modelConvertHandler = useCallback(() => {
     const queryArg = {
-      base_model: model.base_model,
-      model_name: model.model_name,
+      base_model: model.base,
+      model_name: model.name,
       convert_dest_directory: saveLocation === 'Custom' ? customSaveLocation : undefined,
     };
 
@@ -74,7 +74,7 @@ const ModelConvert = (props: ModelConvertProps) => {
     dispatch(
       addToast(
         makeToast({
-          title: `${t('modelManager.convertingModelBegin')}: ${model.model_name}`,
+          title: `${t('modelManager.convertingModelBegin')}: ${model.name}`,
           status: 'info',
         })
       )
@@ -86,7 +86,7 @@ const ModelConvert = (props: ModelConvertProps) => {
         dispatch(
           addToast(
             makeToast({
-              title: `${t('modelManager.modelConverted')}: ${model.model_name}`,
+              title: `${t('modelManager.modelConverted')}: ${model.name}`,
               status: 'success',
             })
           )
@@ -96,13 +96,13 @@ const ModelConvert = (props: ModelConvertProps) => {
         dispatch(
           addToast(
             makeToast({
-              title: `${t('modelManager.modelConversionFailed')}: ${model.model_name}`,
+              title: `${t('modelManager.modelConversionFailed')}: ${model.name}`,
               status: 'error',
             })
           )
         );
       });
-  }, [convertModel, customSaveLocation, dispatch, model.base_model, model.model_name, saveLocation, t]);
+  }, [convertModel, customSaveLocation, dispatch, model.base, model.name, saveLocation, t]);
 
   return (
     <>
@@ -116,7 +116,7 @@ const ModelConvert = (props: ModelConvertProps) => {
         🧨 {t('modelManager.convertToDiffusers')}
       </Button>
       <ConfirmationAlertDialog
-        title={`${t('modelManager.convert')} ${model.model_name}`}
+        title={`${t('modelManager.convert')} ${model.name}`}
         acceptCallback={modelConvertHandler}
         cancelCallback={modelConvertCancelHandler}
         acceptButtonText={`${t('modelManager.convert')}`}
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelList.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelList.tsx
index 49c9bc6112..c546831476 100644
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelList.tsx
+++ b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelList.tsx
@@ -5,10 +5,11 @@ import type { ChangeEvent, PropsWithChildren } from 'react';
 import { memo, useCallback, useState } from 'react';
 import { useTranslation } from 'react-i18next';
 import { ALL_BASE_MODELS } from 'services/api/constants';
-import type { LoRAConfig, MainModelConfig } from 'services/api/endpoints/models';
+// import type { LoRAConfig, MainModelConfig } from 'services/api/endpoints/models';
 import { useGetLoRAModelsQuery, useGetMainModelsQuery } from 'services/api/endpoints/models';
 
 import ModelListItem from './ModelListItem';
+import { LoRAConfig, MainModelConfig } from '../../../../services/api/types';
 
 type ModelListProps = {
   selectedModelId: string | undefined;
@@ -177,9 +178,9 @@ const ModelListWrapper = memo((props: ModelListWrapperProps) => {
         </Text>
         {modelList.map((model) => (
           <ModelListItem
-            key={model.id}
+            key={model.key}
             model={model}
-            isSelected={selected.selectedModelId === model.id}
+            isSelected={selected.selectedModelId === model.key}
             setSelectedModelId={selected.setSelectedModelId}
           />
         ))}
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelListItem.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelListItem.tsx
index 835499d25a..2014d88961 100644
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelListItem.tsx
+++ b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelListItem.tsx
@@ -15,8 +15,8 @@ import { makeToast } from 'features/system/util/makeToast';
 import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 import { PiTrashSimpleBold } from 'react-icons/pi';
-import type { LoRAConfig, MainModelConfig } from 'services/api/endpoints/models';
-import { useDeleteLoRAModelsMutation, useDeleteMainModelsMutation } from 'services/api/endpoints/models';
+import { useDeleteModelsMutation } from 'services/api/endpoints/models';
+import { LoRAConfig, MainModelConfig } from '../../../../services/api/types';
 
 type ModelListItemProps = {
   model: MainModelConfig | LoRAConfig;
@@ -27,29 +27,23 @@ type ModelListItemProps = {
 const ModelListItem = (props: ModelListItemProps) => {
   const { t } = useTranslation();
   const dispatch = useAppDispatch();
-  const [deleteMainModel] = useDeleteMainModelsMutation();
-  const [deleteLoRAModel] = useDeleteLoRAModelsMutation();
+  const [deleteModel] = useDeleteModelsMutation();
   const { isOpen, onOpen, onClose } = useDisclosure();
 
   const { model, isSelected, setSelectedModelId } = props;
 
   const handleSelectModel = useCallback(() => {
-    setSelectedModelId(model.id);
-  }, [model.id, setSelectedModelId]);
+    setSelectedModelId(model.key);
+  }, [model.key, setSelectedModelId]);
 
   const handleModelDelete = useCallback(() => {
-    const method = {
-      main: deleteMainModel,
-      lora: deleteLoRAModel,
-    }[model.model_type];
-
-    method(model)
+    deleteModel({ key: model.key })
       .unwrap()
       .then((_) => {
         dispatch(
           addToast(
             makeToast({
-              title: `${t('modelManager.modelDeleted')}: ${model.model_name}`,
+              title: `${t('modelManager.modelDeleted')}: ${model.name}`,
               status: 'success',
             })
           )
@@ -60,7 +54,7 @@ const ModelListItem = (props: ModelListItemProps) => {
           dispatch(
             addToast(
               makeToast({
-                title: `${t('modelManager.modelDeleteFailed')}: ${model.model_name}`,
+                title: `${t('modelManager.modelDeleteFailed')}: ${model.name}`,
                 status: 'error',
               })
             )
@@ -68,7 +62,7 @@ const ModelListItem = (props: ModelListItemProps) => {
         }
       });
     setSelectedModelId(undefined);
-  }, [deleteMainModel, deleteLoRAModel, model, setSelectedModelId, dispatch, t]);
+  }, [deleteModel, model, setSelectedModelId, dispatch, t]);
 
   return (
     <Flex gap={2} alignItems="center" w="full">
@@ -85,10 +79,10 @@ const ModelListItem = (props: ModelListItemProps) => {
       >
         <Flex gap={4} alignItems="center">
           <Badge minWidth={14} p={0.5} fontSize="sm" variant="solid">
-            {MODEL_TYPE_SHORT_MAP[model.base_model as keyof typeof MODEL_TYPE_SHORT_MAP]}
+            {MODEL_TYPE_SHORT_MAP[model.base as keyof typeof MODEL_TYPE_SHORT_MAP]}
           </Badge>
           <Tooltip label={model.description} placement="bottom">
-            <Text>{model.model_name}</Text>
+            <Text>{model.name}</Text>
           </Tooltip>
         </Flex>
       </Flex>
diff --git a/invokeai/frontend/web/src/services/api/endpoints/models.ts b/invokeai/frontend/web/src/services/api/endpoints/models.ts
index 2bd1a0a246..6897768a1b 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/models.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/models.ts
@@ -7,12 +7,10 @@ import type {
   AnyModelConfig,
   BaseModelType,
   ControlNetModelConfig,
-  ImportModelConfig,
   IPAdapterModelConfig,
   LoRAModelConfig,
   MainModelConfig,
   MergeModelConfig,
-  ModelType,
   T2IAdapterModelConfig,
   TextualInversionModelConfig,
   VAEModelConfig,
@@ -21,37 +19,21 @@ import type {
 import type { ApiTagDescription, tagTypes } from '..';
 import { api, buildV2Url, LIST_TAG } from '..';
 
-type UpdateMainModelArg = {
-  base_model: BaseModelType;
-  model_name: string;
-  body: MainModelConfig;
+type UpdateModelArg = {
+  key: NonNullable<operations['update_model_record']['parameters']['path']['key']>;
+  body: NonNullable<operations['update_model_record']['requestBody']['content']['application/json']>;
 };
 
-type UpdateLoRAModelArg = {
-  base_model: BaseModelType;
-  model_name: string;
-  body: LoRAModelConfig;
-};
-
-type UpdateMainModelResponse =
-  paths['/api/v2/models/i/{key}']['patch']['responses']['200']['content']['application/json'];
+type UpdateModelResponse = paths['/api/v2/models/i/{key}']['patch']['responses']['200']['content']['application/json'];
 
 type ListModelsArg = NonNullable<paths['/api/v2/models/']['get']['parameters']['query']>;
 
-type UpdateLoRAModelResponse = UpdateMainModelResponse;
-
 type DeleteMainModelArg = {
-  base_model: BaseModelType;
-  model_name: string;
-  model_type: ModelType;
+  key: string;
 };
 
 type DeleteMainModelResponse = void;
 
-type DeleteLoRAModelArg = DeleteMainModelArg;
-
-type DeleteLoRAModelResponse = void;
-
 type ConvertMainModelArg = {
   base_model: BaseModelType;
   model_name: string;
@@ -59,36 +41,40 @@ type ConvertMainModelArg = {
 };
 
 type ConvertMainModelResponse =
-  paths['/api/v1/models/convert/{base_model}/{model_type}/{model_name}']['put']['responses']['200']['content']['application/json'];
+  paths['/api/v2/models/convert/{key}']['put']['responses']['200']['content']['application/json'];
 
 type MergeMainModelArg = {
   base_model: BaseModelType;
   body: MergeModelConfig;
 };
 
-type MergeMainModelResponse =
-  paths['/api/v1/models/merge/{base_model}']['put']['responses']['200']['content']['application/json'];
+type MergeMainModelResponse = paths['/api/v2/models/merge']['put']['responses']['200']['content']['application/json'];
 
 type ImportMainModelArg = {
-  body: ImportModelConfig;
+  source: NonNullable<operations['heuristic_import_model']['parameters']['query']['source']>;
+  access_token?: operations['heuristic_import_model']['parameters']['query']['access_token'];
+  config: NonNullable<operations['heuristic_import_model']['requestBody']['content']['application/json']>;
 };
 
 type ImportMainModelResponse =
-  paths['/api/v1/models/import']['post']['responses']['201']['content']['application/json'];
+  paths['/api/v2/models/import']['post']['responses']['201']['content']['application/json'];
+
+type ListImportModelsResponse =
+  paths['/api/v2/models/import']['get']['responses']['200']['content']['application/json'];
 
 type AddMainModelArg = {
   body: MainModelConfig;
 };
 
-type AddMainModelResponse = paths['/api/v1/models/add']['post']['responses']['201']['content']['application/json'];
+type AddMainModelResponse = paths['/api/v2/models/add']['post']['responses']['201']['content']['application/json'];
 
-type SyncModelsResponse = paths['/api/v1/models/sync']['post']['responses']['201']['content']['application/json'];
+type SyncModelsResponse = paths['/api/v2/models/sync']['post']['responses']['201']['content']['application/json'];
 
 export type SearchFolderResponse =
-  paths['/api/v1/models/search']['get']['responses']['200']['content']['application/json'];
+  paths['/api/v2/models/search']['get']['responses']['200']['content']['application/json'];
 
 type CheckpointConfigsResponse =
-  paths['/api/v1/models/ckpt_confs']['get']['responses']['200']['content']['application/json'];
+  paths['/api/v2/models/ckpt_confs']['get']['responses']['200']['content']['application/json'];
 
 type SearchFolderArg = operations['search_for_models']['parameters']['query'];
 
@@ -179,10 +165,10 @@ export const modelsApi = api.injectEndpoints({
       providesTags: buildProvidesTags<MainModelConfig>('MainModel'),
       transformResponse: buildTransformResponse<MainModelConfig>(mainModelsAdapter),
     }),
-    updateMainModels: build.mutation<UpdateMainModelResponse, UpdateMainModelArg>({
-      query: ({ base_model, model_name, body }) => {
+    updateModels: build.mutation<UpdateModelResponse, UpdateModelArg>({
+      query: ({ key, body }) => {
         return {
-          url: buildModelsUrl(`${base_model}/main/${model_name}`),
+          url: buildModelsUrl(`i/${key}`),
           method: 'PATCH',
           body: body,
         };
@@ -190,11 +176,12 @@ export const modelsApi = api.injectEndpoints({
       invalidatesTags: ['Model'],
     }),
     importMainModels: build.mutation<ImportMainModelResponse, ImportMainModelArg>({
-      query: ({ body }) => {
+      query: ({ source, config, access_token }) => {
         return {
-          url: buildModelsUrl('import'),
+          url: buildModelsUrl('heuristic_import'),
+          params: { source, access_token },
           method: 'POST',
-          body: body,
+          body: config,
         };
       },
       invalidatesTags: ['Model'],
@@ -209,10 +196,10 @@ export const modelsApi = api.injectEndpoints({
       },
       invalidatesTags: ['Model'],
     }),
-    deleteMainModels: build.mutation<DeleteMainModelResponse, DeleteMainModelArg>({
-      query: ({ base_model, model_name, model_type }) => {
+    deleteModels: build.mutation<DeleteMainModelResponse, DeleteMainModelArg>({
+      query: ({ key }) => {
         return {
-          url: buildModelsUrl(`${base_model}/${model_type}/${model_name}`),
+          url: buildModelsUrl(`i/${key}`),
           method: 'DELETE',
         };
       },
@@ -264,25 +251,6 @@ export const modelsApi = api.injectEndpoints({
       providesTags: buildProvidesTags<LoRAModelConfig>('LoRAModel'),
       transformResponse: buildTransformResponse<LoRAModelConfig>(loraModelsAdapter),
     }),
-    updateLoRAModels: build.mutation<UpdateLoRAModelResponse, UpdateLoRAModelArg>({
-      query: ({ base_model, model_name, body }) => {
-        return {
-          url: buildModelsUrl(`${base_model}/lora/${model_name}`),
-          method: 'PATCH',
-          body: body,
-        };
-      },
-      invalidatesTags: [{ type: 'LoRAModel', id: LIST_TAG }],
-    }),
-    deleteLoRAModels: build.mutation<DeleteLoRAModelResponse, DeleteLoRAModelArg>({
-      query: ({ base_model, model_name }) => {
-        return {
-          url: buildModelsUrl(`${base_model}/lora/${model_name}`),
-          method: 'DELETE',
-        };
-      },
-      invalidatesTags: [{ type: 'LoRAModel', id: LIST_TAG }],
-    }),
     getControlNetModels: build.query<EntityState<ControlNetModelConfig, string>, void>({
       query: () => ({ url: buildModelsUrl(), params: { model_type: 'controlnet' } }),
       providesTags: buildProvidesTags<ControlNetModelConfig>('ControlNetModel'),
@@ -316,6 +284,13 @@ export const modelsApi = api.injectEndpoints({
         };
       },
     }),
+    getModelImports: build.query<ListImportModelsResponse, void>({
+      query: (arg) => {
+        return {
+          url: buildModelsUrl(`import`),
+        };
+      },
+    }),
     getCheckpointConfigs: build.query<CheckpointConfigsResponse, void>({
       query: () => {
         return {
@@ -335,15 +310,14 @@ export const {
   useGetLoRAModelsQuery,
   useGetTextualInversionModelsQuery,
   useGetVaeModelsQuery,
-  useUpdateMainModelsMutation,
-  useDeleteMainModelsMutation,
+  useDeleteModelsMutation,
+  useUpdateModelsMutation,
   useImportMainModelsMutation,
   useAddMainModelsMutation,
   useConvertMainModelsMutation,
   useMergeMainModelsMutation,
-  useDeleteLoRAModelsMutation,
-  useUpdateLoRAModelsMutation,
   useSyncModelsMutation,
   useGetModelsInFolderQuery,
   useGetCheckpointConfigsQuery,
+  useGetModelImportsQuery,
 } = modelsApi;

From 9068400433240dc25bee43f951da659f368e64c4 Mon Sep 17 00:00:00 2001
From: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Date: Tue, 20 Feb 2024 10:09:40 -0500
Subject: [PATCH 252/411] workspace for mary and jenn

---
 .../modelManagerV2/subpanels/ImportModels.tsx | 10 +++
 .../modelManagerV2/subpanels/ModelManager.tsx | 44 ++++++++++++
 .../ui/components/tabs/ModelManagerTab.tsx    | 68 +++----------------
 3 files changed, 64 insertions(+), 58 deletions(-)
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManager.tsx

diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx
new file mode 100644
index 0000000000..2325fcf7dc
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx
@@ -0,0 +1,10 @@
+import { Box } from '@invoke-ai/ui-library';
+
+//jenn's workspace
+export const ImportModels = () => {
+  return (
+    <Box layerStyle="first" p={2} borderRadius="base" w="full" h="full">
+      Import Models
+    </Box>
+  );
+};
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManager.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManager.tsx
new file mode 100644
index 0000000000..59b01de0c0
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManager.tsx
@@ -0,0 +1,44 @@
+import {
+  Box,
+  Button,
+  Flex,
+  Heading,
+  IconButton,
+  Input,
+  InputGroup,
+  InputRightElement,
+  Spacer,
+} from '@invoke-ai/ui-library';
+import { t } from 'i18next';
+import { PiXBold } from 'react-icons/pi';
+import { SyncModelsIconButton } from '../../modelManager/components/SyncModels/SyncModelsIconButton';
+
+export const ModelManager = () => {
+  return (
+    <Box layerStyle="first" p={3} borderRadius="base" w="full" h="full">
+      <Flex w="full" p={3} justifyContent="space-between" alignItems="center">
+        <Flex gap={2}>
+          <Heading fontSize="xl">Model Manager</Heading>
+          <SyncModelsIconButton />
+        </Flex>
+        <Flex gap={2}>
+          <Button colorScheme="invokeYellow">Add Model</Button>
+          <Button>Scan for Models</Button>
+        </Flex>
+      </Flex>
+      <Box layerStyle="second" p={3} borderRadius="base" w="full" h="full">
+        <Flex gap={2} alignItems="center" justifyContent="space-between">
+          <Button>All Models</Button>
+          <Spacer />
+          <InputGroup>
+            <Input placeholder={t('boards.searchBoard')} data-testid="board-search-input" />(
+            <InputRightElement h="full" pe={2}>
+              <IconButton size="sm" variant="link" aria-label={t('boards.clearSearch')} icon={<PiXBold />} />
+            </InputRightElement>
+            )
+          </InputGroup>
+        </Flex>
+      </Box>
+    </Box>
+  );
+};
diff --git a/invokeai/frontend/web/src/features/ui/components/tabs/ModelManagerTab.tsx b/invokeai/frontend/web/src/features/ui/components/tabs/ModelManagerTab.tsx
index 124c9b31a5..50db10fb57 100644
--- a/invokeai/frontend/web/src/features/ui/components/tabs/ModelManagerTab.tsx
+++ b/invokeai/frontend/web/src/features/ui/components/tabs/ModelManagerTab.tsx
@@ -1,65 +1,17 @@
-import { Tab, TabList, TabPanel, TabPanels, Tabs } from '@invoke-ai/ui-library';
-import ImportModelsPanel from 'features/modelManager/subpanels/ImportModelsPanel';
-import MergeModelsPanel from 'features/modelManager/subpanels/MergeModelsPanel';
-import ModelManagerPanel from 'features/modelManager/subpanels/ModelManagerPanel';
-import ModelManagerSettingsPanel from 'features/modelManager/subpanels/ModelManagerSettingsPanel';
-import type { ReactNode } from 'react';
-import { memo, useMemo } from 'react';
+import { Flex, Box } from '@invoke-ai/ui-library';
+import { memo } from 'react';
 import { useTranslation } from 'react-i18next';
-
-type ModelManagerTabName = 'modelManager' | 'importModels' | 'mergeModels' | 'settings';
-
-type ModelManagerTabInfo = {
-  id: ModelManagerTabName;
-  label: string;
-  content: ReactNode;
-};
+import { ImportModels } from '../../../modelManagerV2/subpanels/ImportModels';
+import { ModelManager } from '../../../modelManagerV2/subpanels/ModelManager';
 
 const ModelManagerTab = () => {
-  const { t } = useTranslation();
-
-  const tabs: ModelManagerTabInfo[] = useMemo(
-    () => [
-      {
-        id: 'modelManager',
-        label: t('modelManager.modelManager'),
-        content: <ModelManagerPanel />,
-      },
-      {
-        id: 'importModels',
-        label: t('modelManager.importModels'),
-        content: <ImportModelsPanel />,
-      },
-      {
-        id: 'mergeModels',
-        label: t('modelManager.mergeModels'),
-        content: <MergeModelsPanel />,
-      },
-      {
-        id: 'settings',
-        label: t('modelManager.settings'),
-        content: <ModelManagerSettingsPanel />,
-      },
-    ],
-    [t]
-  );
   return (
-    <Tabs isLazy variant="line" layerStyle="first" w="full" h="full" p={4} gap={4} borderRadius="base">
-      <TabList>
-        {tabs.map((tab) => (
-          <Tab borderTopRadius="base" key={tab.id}>
-            {tab.label}
-          </Tab>
-        ))}
-      </TabList>
-      <TabPanels w="full" h="full">
-        {tabs.map((tab) => (
-          <TabPanel w="full" h="full" key={tab.id}>
-            {tab.content}
-          </TabPanel>
-        ))}
-      </TabPanels>
-    </Tabs>
+    <Box w="full" h="full">
+      <Flex w="full" h="full" gap={4}>
+        <ModelManager />
+        <ImportModels />
+      </Flex>
+    </Box>
   );
 };
 

From c7d462b222f302647fef74110f9bef40a3b57601 Mon Sep 17 00:00:00 2001
From: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Date: Tue, 20 Feb 2024 13:03:28 -0500
Subject: [PATCH 253/411] model list, filtering, searching

---
 invokeai/frontend/web/src/app/store/store.ts  |   2 +
 .../subpanels/AddModelsPanel/AddModels.tsx    |   2 +-
 .../subpanels/ModelManagerPanel.tsx           |   2 +-
 .../ModelManagerPanel/CheckpointModelEdit.tsx |   3 +-
 .../ModelManagerPanel/DiffusersModelEdit.tsx  |   2 +-
 .../ModelManagerPanel/LoRAModelEdit.tsx       |   1 +
 .../subpanels/ModelManagerPanel/ModelList.tsx |   2 +-
 .../ModelManagerPanel/ModelListItem.tsx       |   2 +-
 .../store/modelManagerV2Slice.ts              |  54 ++++++
 .../modelManagerV2/subpanels/ModelManager.tsx |  32 +---
 .../subpanels/ModelManagerPanel/ModelList.tsx | 160 ++++++++++++++++++
 .../ModelManagerPanel/ModelListHeader.tsx     |  23 +++
 .../ModelManagerPanel/ModelListItem.tsx       | 115 +++++++++++++
 .../ModelManagerPanel/ModelListNavigation.tsx |  52 ++++++
 .../ModelManagerPanel/ModelListWrapper.tsx    |  25 +++
 .../ModelManagerPanel/ModelTypeFilter.tsx     |  54 ++++++
 .../web/src/features/modelManagerV2/types.ts  |  14 ++
 .../ui/components/tabs/ModelManagerTab.tsx    |   7 +-
 18 files changed, 517 insertions(+), 35 deletions(-)
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/store/modelManagerV2Slice.ts
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelList.tsx
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelListHeader.tsx
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelListItem.tsx
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelListNavigation.tsx
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelListWrapper.tsx
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelTypeFilter.tsx
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/types.ts

diff --git a/invokeai/frontend/web/src/app/store/store.ts b/invokeai/frontend/web/src/app/store/store.ts
index 16f1632d88..c63bc02e09 100644
--- a/invokeai/frontend/web/src/app/store/store.ts
+++ b/invokeai/frontend/web/src/app/store/store.ts
@@ -16,6 +16,7 @@ import { galleryPersistConfig, gallerySlice } from 'features/gallery/store/galle
 import { hrfPersistConfig, hrfSlice } from 'features/hrf/store/hrfSlice';
 import { loraPersistConfig, loraSlice } from 'features/lora/store/loraSlice';
 import { modelManagerPersistConfig, modelManagerSlice } from 'features/modelManager/store/modelManagerSlice';
+import { modelManagerV2Slice } from 'features/modelManagerV2/store/modelManagerV2Slice';
 import { nodesPersistConfig, nodesSlice } from 'features/nodes/store/nodesSlice';
 import { workflowPersistConfig, workflowSlice } from 'features/nodes/store/workflowSlice';
 import { generationPersistConfig, generationSlice } from 'features/parameters/store/generationSlice';
@@ -55,6 +56,7 @@ const allReducers = {
   [changeBoardModalSlice.name]: changeBoardModalSlice.reducer,
   [loraSlice.name]: loraSlice.reducer,
   [modelManagerSlice.name]: modelManagerSlice.reducer,
+  [modelManagerV2Slice.name]: modelManagerV2Slice.reducer,
   [sdxlSlice.name]: sdxlSlice.reducer,
   [queueSlice.name]: queueSlice.reducer,
   [workflowSlice.name]: workflowSlice.reducer,
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/AddModels.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/AddModels.tsx
index 9b4b95be9e..82ccb7f309 100644
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/AddModels.tsx
+++ b/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/AddModels.tsx
@@ -1,10 +1,10 @@
 import { Button, ButtonGroup, Flex, Text } from '@invoke-ai/ui-library';
 import { memo, useCallback, useState } from 'react';
 import { useTranslation } from 'react-i18next';
+import { useGetModelImportsQuery } from 'services/api/endpoints/models';
 
 import AdvancedAddModels from './AdvancedAddModels';
 import SimpleAddModels from './SimpleAddModels';
-import { useGetModelImportsQuery } from '../../../../services/api/endpoints/models';
 
 const AddModels = () => {
   const { t } = useTranslation();
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel.tsx
index dab4e0b872..06b5b7db36 100644
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel.tsx
+++ b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel.tsx
@@ -3,12 +3,12 @@ import { memo, useState } from 'react';
 import { useTranslation } from 'react-i18next';
 import { ALL_BASE_MODELS } from 'services/api/constants';
 import { useGetLoRAModelsQuery, useGetMainModelsQuery } from 'services/api/endpoints/models';
+import type { DiffusersModelConfig, LoRAConfig, MainModelConfig } from 'services/api/types';
 
 import CheckpointModelEdit from './ModelManagerPanel/CheckpointModelEdit';
 import DiffusersModelEdit from './ModelManagerPanel/DiffusersModelEdit';
 import LoRAModelEdit from './ModelManagerPanel/LoRAModelEdit';
 import ModelList from './ModelManagerPanel/ModelList';
-import { DiffusersModelConfig, LoRAConfig, MainModelConfig } from '../../../services/api/types';
 
 const ModelManagerPanel = () => {
   const [selectedModelId, setSelectedModelId] = useState<string>();
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/CheckpointModelEdit.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/CheckpointModelEdit.tsx
index 0dd8a7add6..c24d660cc6 100644
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/CheckpointModelEdit.tsx
+++ b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/CheckpointModelEdit.tsx
@@ -22,8 +22,9 @@ import type { SubmitHandler } from 'react-hook-form';
 import { useForm } from 'react-hook-form';
 import { useTranslation } from 'react-i18next';
 import { useGetCheckpointConfigsQuery, useUpdateModelsMutation } from 'services/api/endpoints/models';
+import type { CheckpointModelConfig } from 'services/api/types';
+
 import ModelConvert from './ModelConvert';
-import { CheckpointModelConfig } from '../../../../services/api/types';
 
 type CheckpointModelEditProps = {
   model: CheckpointModelConfig;
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/DiffusersModelEdit.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/DiffusersModelEdit.tsx
index 5be9a5631c..b5023f0eff 100644
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/DiffusersModelEdit.tsx
+++ b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/DiffusersModelEdit.tsx
@@ -9,8 +9,8 @@ import { memo, useCallback } from 'react';
 import type { SubmitHandler } from 'react-hook-form';
 import { useForm } from 'react-hook-form';
 import { useTranslation } from 'react-i18next';
+import { useUpdateModelsMutation } from 'services/api/endpoints/models';
 import type { DiffusersModelConfig } from 'services/api/types';
-import { useUpdateModelsMutation } from '../../../../services/api/endpoints/models';
 
 type DiffusersModelEditProps = {
   model: DiffusersModelConfig;
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/LoRAModelEdit.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/LoRAModelEdit.tsx
index edb73e8275..81f2c4df29 100644
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/LoRAModelEdit.tsx
+++ b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/LoRAModelEdit.tsx
@@ -8,6 +8,7 @@ import { memo, useCallback } from 'react';
 import type { SubmitHandler } from 'react-hook-form';
 import { useForm } from 'react-hook-form';
 import { useTranslation } from 'react-i18next';
+import { useUpdateModelsMutation } from 'services/api/endpoints/models';
 import type { LoRAModelConfig } from 'services/api/types';
 
 type LoRAModelEditProps = {
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelList.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelList.tsx
index c546831476..b129b7310d 100644
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelList.tsx
+++ b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelList.tsx
@@ -7,9 +7,9 @@ import { useTranslation } from 'react-i18next';
 import { ALL_BASE_MODELS } from 'services/api/constants';
 // import type { LoRAConfig, MainModelConfig } from 'services/api/endpoints/models';
 import { useGetLoRAModelsQuery, useGetMainModelsQuery } from 'services/api/endpoints/models';
+import type { LoRAConfig, MainModelConfig } from 'services/api/types';
 
 import ModelListItem from './ModelListItem';
-import { LoRAConfig, MainModelConfig } from '../../../../services/api/types';
 
 type ModelListProps = {
   selectedModelId: string | undefined;
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelListItem.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelListItem.tsx
index 2014d88961..08b9b61aea 100644
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelListItem.tsx
+++ b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelListItem.tsx
@@ -16,7 +16,7 @@ import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 import { PiTrashSimpleBold } from 'react-icons/pi';
 import { useDeleteModelsMutation } from 'services/api/endpoints/models';
-import { LoRAConfig, MainModelConfig } from '../../../../services/api/types';
+import type { LoRAConfig, MainModelConfig } from 'services/api/types';
 
 type ModelListItemProps = {
   model: MainModelConfig | LoRAConfig;
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/store/modelManagerV2Slice.ts b/invokeai/frontend/web/src/features/modelManagerV2/store/modelManagerV2Slice.ts
new file mode 100644
index 0000000000..29b071e9b1
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/store/modelManagerV2Slice.ts
@@ -0,0 +1,54 @@
+import type { PayloadAction } from '@reduxjs/toolkit';
+import { createSlice } from '@reduxjs/toolkit';
+import type { PersistConfig, RootState } from 'app/store/store';
+
+
+type ModelManagerState = {
+    _version: 1;
+    selectedModelKey: string | null;
+    searchTerm: string;
+    filteredModelType: string | null;
+};
+
+export const initialModelManagerState: ModelManagerState = {
+    _version: 1,
+    selectedModelKey: null,
+    filteredModelType: null,
+    searchTerm: ""
+};
+
+export const modelManagerV2Slice = createSlice({
+    name: 'modelmanagerV2',
+    initialState: initialModelManagerState,
+    reducers: {
+        setSelectedModelKey: (state, action: PayloadAction<string | null>) => {
+            state.selectedModelKey = action.payload;
+        },
+        setSearchTerm: (state, action: PayloadAction<string>) => {
+            state.searchTerm = action.payload;
+        },
+
+        setFilteredModelType: (state, action: PayloadAction<string | null>) => {
+            state.filteredModelType = action.payload;
+        },
+    },
+});
+
+export const { setSelectedModelKey, setSearchTerm, setFilteredModelType } = modelManagerV2Slice.actions;
+
+export const selectModelManagerSlice = (state: RootState) => state.modelmanager;
+
+/* eslint-disable-next-line @typescript-eslint/no-explicit-any */
+export const migrateModelManagerState = (state: any): any => {
+    if (!('_version' in state)) {
+        state._version = 1;
+    }
+    return state;
+};
+
+export const modelManagerPersistConfig: PersistConfig<ModelManagerState> = {
+    name: modelManagerV2Slice.name,
+    initialState: initialModelManagerState,
+    migrate: migrateModelManagerState,
+    persistDenylist: [],
+};
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManager.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManager.tsx
index 59b01de0c0..648f98dbb3 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManager.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManager.tsx
@@ -1,17 +1,8 @@
-import {
-  Box,
-  Button,
-  Flex,
-  Heading,
-  IconButton,
-  Input,
-  InputGroup,
-  InputRightElement,
-  Spacer,
-} from '@invoke-ai/ui-library';
-import { t } from 'i18next';
-import { PiXBold } from 'react-icons/pi';
-import { SyncModelsIconButton } from '../../modelManager/components/SyncModels/SyncModelsIconButton';
+import { Box, Button, Flex, Heading } from '@invoke-ai/ui-library';
+import { SyncModelsIconButton } from 'features/modelManager/components/SyncModels/SyncModelsIconButton';
+
+import ModelList from './ModelManagerPanel/ModelList';
+import { ModelListNavigation } from './ModelManagerPanel/ModelListNavigation';
 
 export const ModelManager = () => {
   return (
@@ -27,17 +18,8 @@ export const ModelManager = () => {
         </Flex>
       </Flex>
       <Box layerStyle="second" p={3} borderRadius="base" w="full" h="full">
-        <Flex gap={2} alignItems="center" justifyContent="space-between">
-          <Button>All Models</Button>
-          <Spacer />
-          <InputGroup>
-            <Input placeholder={t('boards.searchBoard')} data-testid="board-search-input" />(
-            <InputRightElement h="full" pe={2}>
-              <IconButton size="sm" variant="link" aria-label={t('boards.clearSearch')} icon={<PiXBold />} />
-            </InputRightElement>
-            )
-          </InputGroup>
-        </Flex>
+        <ModelListNavigation />
+        <ModelList />
       </Box>
     </Box>
   );
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelList.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelList.tsx
new file mode 100644
index 0000000000..bf43c01da2
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelList.tsx
@@ -0,0 +1,160 @@
+import { Flex, Spinner, Text } from '@invoke-ai/ui-library';
+import type { EntityState } from '@reduxjs/toolkit';
+import { useAppSelector } from 'app/store/storeHooks';
+import { forEach } from 'lodash-es';
+import { memo } from 'react';
+import { ALL_BASE_MODELS } from 'services/api/constants';
+import {
+  useGetControlNetModelsQuery,
+  useGetIPAdapterModelsQuery,
+  useGetLoRAModelsQuery,
+  useGetMainModelsQuery,
+  useGetT2IAdapterModelsQuery,
+  useGetTextualInversionModelsQuery,
+  useGetVaeModelsQuery,
+} from 'services/api/endpoints/models';
+import type { AnyModelConfig } from 'services/api/types';
+
+import { ModelListWrapper } from './ModelListWrapper';
+
+const ModelList = () => {
+  const { searchTerm, filteredModelType } = useAppSelector((s) => s.modelmanagerV2);
+
+  const { filteredMainModels, isLoadingMainModels } = useGetMainModelsQuery(ALL_BASE_MODELS, {
+    selectFromResult: ({ data, isLoading }) => ({
+      filteredMainModels: modelsFilter(data, searchTerm, filteredModelType),
+      isLoadingMainModels: isLoading,
+    }),
+  });
+
+  const { filteredLoraModels, isLoadingLoraModels } = useGetLoRAModelsQuery(undefined, {
+    selectFromResult: ({ data, isLoading }) => ({
+      filteredLoraModels: modelsFilter(data, searchTerm, filteredModelType),
+      isLoadingLoraModels: isLoading,
+    }),
+  });
+
+  const { filteredTextualInversionModels, isLoadingTextualInversionModels } = useGetTextualInversionModelsQuery(
+    undefined,
+    {
+      selectFromResult: ({ data, isLoading }) => ({
+        filteredTextualInversionModels: modelsFilter(data, searchTerm, filteredModelType),
+        isLoadingTextualInversionModels: isLoading,
+      }),
+    }
+  );
+
+  const { filteredControlnetModels, isLoadingControlnetModels } = useGetControlNetModelsQuery(undefined, {
+    selectFromResult: ({ data, isLoading }) => ({
+      filteredControlnetModels: modelsFilter(data, searchTerm, filteredModelType),
+      isLoadingControlnetModels: isLoading,
+    }),
+  });
+
+  const { filteredT2iAdapterModels, isLoadingT2IAdapterModels } = useGetT2IAdapterModelsQuery(undefined, {
+    selectFromResult: ({ data, isLoading }) => ({
+      filteredT2iAdapterModels: modelsFilter(data, searchTerm, filteredModelType),
+      isLoadingT2IAdapterModels: isLoading,
+    }),
+  });
+
+  const { filteredIpAdapterModels, isLoadingIpAdapterModels } = useGetIPAdapterModelsQuery(undefined, {
+    selectFromResult: ({ data, isLoading }) => ({
+      filteredIpAdapterModels: modelsFilter(data, searchTerm, filteredModelType),
+      isLoadingIpAdapterModels: isLoading,
+    }),
+  });
+
+  const { filteredVaeModels, isLoadingVaeModels } = useGetVaeModelsQuery(undefined, {
+    selectFromResult: ({ data, isLoading }) => ({
+      filteredVaeModels: modelsFilter(data, searchTerm, filteredModelType),
+      isLoadingVaeModels: isLoading,
+    }),
+  });
+
+  return (
+    <Flex flexDirection="column" p={4}>
+      <Flex flexDirection="column" maxHeight={window.innerHeight - 130} overflow="scroll">
+        {/* Main Model List */}
+        {isLoadingMainModels && <FetchingModelsLoader loadingMessage="Loading Main..." />}
+        {!isLoadingMainModels && filteredMainModels.length > 0 && (
+          <ModelListWrapper title="Main" modelList={filteredMainModels} key="main" />
+        )}
+        {/* LoRAs List */}
+        {isLoadingLoraModels && <FetchingModelsLoader loadingMessage="Loading LoRAs..." />}
+        {!isLoadingLoraModels && filteredLoraModels.length > 0 && (
+          <ModelListWrapper title="LoRAs" modelList={filteredLoraModels} key="loras" />
+        )}
+
+        {/* TI List */}
+        {isLoadingTextualInversionModels && <FetchingModelsLoader loadingMessage="Loading Textual Inversions..." />}
+        {!isLoadingTextualInversionModels && filteredTextualInversionModels.length > 0 && (
+          <ModelListWrapper
+            title="Textual Inversions"
+            modelList={filteredTextualInversionModels}
+            key="textual-inversions"
+          />
+        )}
+
+        {/* VAE List */}
+        {isLoadingVaeModels && <FetchingModelsLoader loadingMessage="Loading VAEs..." />}
+        {!isLoadingVaeModels && filteredVaeModels.length > 0 && (
+          <ModelListWrapper title="VAEs" modelList={filteredVaeModels} key="vae" />
+        )}
+
+        {/* Controlnet List */}
+        {isLoadingControlnetModels && <FetchingModelsLoader loadingMessage="Loading Controlnets..." />}
+        {!isLoadingControlnetModels && filteredControlnetModels.length > 0 && (
+          <ModelListWrapper title="Controlnets" modelList={filteredControlnetModels} key="controlnets" />
+        )}
+        {/* IP Adapter List */}
+        {isLoadingIpAdapterModels && <FetchingModelsLoader loadingMessage="Loading IP Adapters..." />}
+        {!isLoadingIpAdapterModels && filteredIpAdapterModels.length > 0 && (
+          <ModelListWrapper title="IP Adapters" modelList={filteredIpAdapterModels} key="ip-adapters" />
+        )}
+        {/* T2I Adapters List */}
+        {isLoadingT2IAdapterModels && <FetchingModelsLoader loadingMessage="Loading T2I Adapters..." />}
+        {!isLoadingT2IAdapterModels && filteredT2iAdapterModels.length > 0 && (
+          <ModelListWrapper title="T2I Adapters" modelList={filteredT2iAdapterModels} key="t2i-adapters" />
+        )}
+      </Flex>
+    </Flex>
+  );
+};
+
+export default memo(ModelList);
+
+const modelsFilter = <T extends AnyModelConfig>(
+  data: EntityState<T, string> | undefined,
+  nameFilter: string,
+  filteredModelType: string | null
+): T[] => {
+  const filteredModels: T[] = [];
+
+  forEach(data?.entities, (model) => {
+    if (!model) {
+      return;
+    }
+
+    const matchesFilter = model.name.toLowerCase().includes(nameFilter.toLowerCase());
+    const matchesType = filteredModelType ? model.type === filteredModelType : true;
+
+    if (matchesFilter && matchesType) {
+      filteredModels.push(model);
+    }
+  });
+  return filteredModels;
+};
+
+const FetchingModelsLoader = memo(({ loadingMessage }: { loadingMessage?: string }) => {
+  return (
+    <Flex flexDirection="column" gap={4} borderRadius={4} p={4} bg="base.800">
+      <Flex justifyContent="center" alignItems="center" flexDirection="column" p={4} gap={8}>
+        <Spinner />
+        <Text variant="subtext">{loadingMessage ? loadingMessage : 'Fetching...'}</Text>
+      </Flex>
+    </Flex>
+  );
+});
+
+FetchingModelsLoader.displayName = 'FetchingModelsLoader';
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelListHeader.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelListHeader.tsx
new file mode 100644
index 0000000000..874d1c9ac2
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelListHeader.tsx
@@ -0,0 +1,23 @@
+import { Box, Divider, Text } from '@invoke-ai/ui-library';
+
+export const ModelListHeader = ({ title }: { title: string }) => {
+  return (
+    <Box position="relative" padding="10px 0">
+      <Divider sx={{ backgroundColor: 'base.400' }} />
+      <Box
+        sx={{
+          position: 'absolute',
+          top: '50%',
+          left: 0,
+          transform: 'translate(0, -50%)',
+          backgroundColor: 'base.800',
+          padding: '10px',
+        }}
+      >
+        <Text variant="subtext" fontSize="sm">
+          {title}
+        </Text>
+      </Box>
+    </Box>
+  );
+};
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelListItem.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelListItem.tsx
new file mode 100644
index 0000000000..5cc429ebcd
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelListItem.tsx
@@ -0,0 +1,115 @@
+import {
+  Badge,
+  Button,
+  ConfirmationAlertDialog,
+  Flex,
+  IconButton,
+  Text,
+  Tooltip,
+  useDisclosure,
+} from '@invoke-ai/ui-library';
+import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { setSelectedModelKey } from 'features/modelManagerV2/store/modelManagerV2Slice';
+import { MODEL_TYPE_SHORT_MAP } from 'features/parameters/types/constants';
+import { addToast } from 'features/system/store/systemSlice';
+import { makeToast } from 'features/system/util/makeToast';
+import { memo, useCallback, useMemo } from 'react';
+import { useTranslation } from 'react-i18next';
+import { PiTrashSimpleBold } from 'react-icons/pi';
+import { useDeleteModelsMutation } from 'services/api/endpoints/models';
+import type { AnyModelConfig } from 'services/api/types';
+
+type ModelListItemProps = {
+  model: AnyModelConfig;
+};
+
+const ModelListItem = (props: ModelListItemProps) => {
+  const { t } = useTranslation();
+  const dispatch = useAppDispatch();
+  const selectedModelKey = useAppSelector((s) => s.modelmanagerV2.selectedModelKey);
+  const [deleteModel] = useDeleteModelsMutation();
+  const { isOpen, onOpen, onClose } = useDisclosure();
+
+  const { model } = props;
+
+  const handleSelectModel = useCallback(() => {
+    dispatch(setSelectedModelKey(model.key));
+  }, [model.key, dispatch]);
+
+  const isSelected = useMemo(() => {
+    return selectedModelKey === model.key;
+  }, [selectedModelKey, model.key]);
+
+  const handleModelDelete = useCallback(() => {
+    deleteModel({ key: model.key })
+      .unwrap()
+      .then((_) => {
+        dispatch(
+          addToast(
+            makeToast({
+              title: `${t('modelManager.modelDeleted')}: ${model.name}`,
+              status: 'success',
+            })
+          )
+        );
+      })
+      .catch((error) => {
+        if (error) {
+          dispatch(
+            addToast(
+              makeToast({
+                title: `${t('modelManager.modelDeleteFailed')}: ${model.name}`,
+                status: 'error',
+              })
+            )
+          );
+        }
+      });
+    dispatch(setSelectedModelKey(null));
+  }, [deleteModel, model, dispatch, t]);
+
+  return (
+    <Flex gap={2} alignItems="center" w="full">
+      <Flex
+        as={Button}
+        isChecked={isSelected}
+        variant={isSelected ? 'solid' : 'ghost'}
+        justifyContent="start"
+        p={2}
+        borderRadius="base"
+        w="full"
+        alignItems="center"
+        onClick={handleSelectModel}
+      >
+        <Flex gap={4} alignItems="center">
+          <Badge minWidth={14} p={0.5} fontSize="sm" variant="solid">
+            {MODEL_TYPE_SHORT_MAP[model.base as keyof typeof MODEL_TYPE_SHORT_MAP]}
+          </Badge>
+          <Tooltip label={model.description} placement="bottom">
+            <Text>{model.name}</Text>
+          </Tooltip>
+        </Flex>
+      </Flex>
+      <IconButton
+        onClick={onOpen}
+        icon={<PiTrashSimpleBold />}
+        aria-label={t('modelManager.deleteConfig')}
+        colorScheme="error"
+      />
+      <ConfirmationAlertDialog
+        isOpen={isOpen}
+        onClose={onClose}
+        title={t('modelManager.deleteModel')}
+        acceptCallback={handleModelDelete}
+        acceptButtonText={t('modelManager.delete')}
+      >
+        <Flex rowGap={4} flexDirection="column">
+          <Text fontWeight="bold">{t('modelManager.deleteMsg1')}</Text>
+          <Text>{t('modelManager.deleteMsg2')}</Text>
+        </Flex>
+      </ConfirmationAlertDialog>
+    </Flex>
+  );
+};
+
+export default memo(ModelListItem);
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelListNavigation.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelListNavigation.tsx
new file mode 100644
index 0000000000..c0d06af245
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelListNavigation.tsx
@@ -0,0 +1,52 @@
+import { Flex, IconButton,Input, InputGroup, InputRightElement, Spacer } from '@invoke-ai/ui-library';
+import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { setSearchTerm } from 'features/modelManagerV2/store/modelManagerV2Slice';
+import { t } from 'i18next';
+import type { ChangeEventHandler} from 'react';
+import { useCallback } from 'react';
+import { PiXBold } from 'react-icons/pi';
+
+import { ModelTypeFilter } from './ModelTypeFilter';
+
+export const ModelListNavigation = () => {
+  const dispatch = useAppDispatch();
+  const searchTerm = useAppSelector((s) => s.modelmanagerV2.searchTerm);
+
+  const handleSearch: ChangeEventHandler<HTMLInputElement> = useCallback(
+    (event) => {
+      dispatch(setSearchTerm(event.target.value));
+    },
+    [dispatch]
+  );
+
+  const clearSearch = useCallback(() => {
+    dispatch(setSearchTerm(''));
+  }, [dispatch]);
+
+  return (
+    <Flex gap={2} alignItems="center" justifyContent="space-between">
+      <ModelTypeFilter />
+      <Spacer />
+      <InputGroup maxW="400px">
+        <Input
+          placeholder={t('modelManager.search')}
+          value={searchTerm || ''}
+          data-testid="board-search-input"
+          onChange={handleSearch}
+        />
+
+        {!!searchTerm?.length && (
+          <InputRightElement h="full" pe={2}>
+            <IconButton
+              size="sm"
+              variant="link"
+              aria-label={t('boards.clearSearch')}
+              icon={<PiXBold />}
+              onClick={clearSearch}
+            />
+          </InputRightElement>
+        )}
+      </InputGroup>
+    </Flex>
+  );
+};
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelListWrapper.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelListWrapper.tsx
new file mode 100644
index 0000000000..24460e6453
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelListWrapper.tsx
@@ -0,0 +1,25 @@
+import { Flex } from '@invoke-ai/ui-library';
+import type { AnyModelConfig } from 'services/api/types';
+
+import { ModelListHeader } from './ModelListHeader';
+import ModelListItem from './ModelListItem';
+
+type ModelListWrapperProps = {
+  title: string;
+  modelList: AnyModelConfig[];
+};
+
+export const ModelListWrapper = (props: ModelListWrapperProps) => {
+  const { title, modelList } = props;
+  return (
+    <Flex flexDirection="column" p="10px 0">
+      <Flex gap={2} flexDir="column">
+        <ModelListHeader title={title} />
+
+        {modelList.map((model) => (
+          <ModelListItem key={model.key} model={model} />
+        ))}
+      </Flex>
+    </Flex>
+  );
+};
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelTypeFilter.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelTypeFilter.tsx
new file mode 100644
index 0000000000..0134ffc811
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelTypeFilter.tsx
@@ -0,0 +1,54 @@
+import { Button, Menu, MenuButton, MenuItem, MenuList } from '@invoke-ai/ui-library';
+import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { setFilteredModelType } from 'features/modelManagerV2/store/modelManagerV2Slice';
+import { useCallback } from 'react';
+import { IoFilter } from 'react-icons/io5';
+
+export const MODEL_TYPE_LABELS: { [key: string]: string } = {
+  main: 'Main',
+  lora: 'LoRA',
+  embedding: 'Textual Inversion',
+  controlnet: 'ControlNet',
+  vae: 'VAE',
+  t2i_adapter: 'T2I Adapter',
+  ip_adapter: 'IP Adapter',
+  clip_vision: 'Clip Vision',
+  onnx: 'Onnx',
+};
+
+export const ModelTypeFilter = () => {
+  const dispatch = useAppDispatch();
+  const filteredModelType = useAppSelector((s) => s.modelmanagerV2.filteredModelType);
+
+  const selectModelType = useCallback(
+    (option: string) => {
+      dispatch(setFilteredModelType(option));
+    },
+    [dispatch]
+  );
+
+  const clearModelType = useCallback(() => {
+    dispatch(setFilteredModelType(null));
+  }, [dispatch]);
+
+  return (
+    <Menu>
+      <MenuButton as={Button} leftIcon={<IoFilter />}>
+        {filteredModelType ? MODEL_TYPE_LABELS[filteredModelType] : 'All Models'}
+      </MenuButton>
+      <MenuList>
+        <MenuItem onClick={clearModelType}>All Models</MenuItem>
+        {Object.keys(MODEL_TYPE_LABELS).map((option) => (
+          <MenuItem
+            sx={{
+              backgroundColor: filteredModelType === option ? 'base.700' : 'transparent',
+            }}
+            onClick={selectModelType.bind(null, option)}
+          >
+            {MODEL_TYPE_LABELS[option]}
+          </MenuItem>
+        ))}
+      </MenuList>
+    </Menu>
+  );
+};
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/types.ts b/invokeai/frontend/web/src/features/modelManagerV2/types.ts
new file mode 100644
index 0000000000..a209fbb876
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/types.ts
@@ -0,0 +1,14 @@
+import { z } from "zod";
+
+export const zBaseModel = z.enum(['any', 'sd-1', 'sd-2', 'sdxl', 'sdxl-refiner']);
+export const zModelType = z.enum([
+    'main',
+    'vae',
+    'lora',
+    'controlnet',
+    'embedding',
+    'ip_adapter',
+    'clip_vision',
+    't2i_adapter',
+    'onnx', // TODO(psyche): Remove this when removed from backend
+]);
\ No newline at end of file
diff --git a/invokeai/frontend/web/src/features/ui/components/tabs/ModelManagerTab.tsx b/invokeai/frontend/web/src/features/ui/components/tabs/ModelManagerTab.tsx
index 50db10fb57..8117631f22 100644
--- a/invokeai/frontend/web/src/features/ui/components/tabs/ModelManagerTab.tsx
+++ b/invokeai/frontend/web/src/features/ui/components/tabs/ModelManagerTab.tsx
@@ -1,8 +1,7 @@
-import { Flex, Box } from '@invoke-ai/ui-library';
+import { Box,Flex } from '@invoke-ai/ui-library';
+import { ImportModels } from 'features/modelManagerV2/subpanels/ImportModels';
+import { ModelManager } from 'features/modelManagerV2/subpanels/ModelManager';
 import { memo } from 'react';
-import { useTranslation } from 'react-i18next';
-import { ImportModels } from '../../../modelManagerV2/subpanels/ImportModels';
-import { ModelManager } from '../../../modelManagerV2/subpanels/ModelManager';
 
 const ModelManagerTab = () => {
   return (

From 87ce74e05d81440bed0ea3577aff6dd78234247d Mon Sep 17 00:00:00 2001
From: Jennifer Player <chainchompa@gmail.com>
Date: Tue, 20 Feb 2024 13:39:27 -0500
Subject: [PATCH 254/411] added import model form and importqueue

---
 invokeai/frontend/web/public/locales/en.json  |  3 +
 .../modelManagerV2/subpanels/ImportModels.tsx | 83 +++++++++++++++++-
 .../modelManagerV2/subpanels/ImportQueue.tsx  | 85 +++++++++++++++++++
 3 files changed, 167 insertions(+), 4 deletions(-)
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportQueue.tsx

diff --git a/invokeai/frontend/web/public/locales/en.json b/invokeai/frontend/web/public/locales/en.json
index a458563fd5..406df71e06 100644
--- a/invokeai/frontend/web/public/locales/en.json
+++ b/invokeai/frontend/web/public/locales/en.json
@@ -701,6 +701,7 @@
         "availableModels": "Available Models",
         "baseModel": "Base Model",
         "cached": "cached",
+        "cancel": "Cancel",
         "cannotUseSpaces": "Cannot Use Spaces",
         "checkpointFolder": "Checkpoint Folder",
         "checkpointModels": "Checkpoints",
@@ -743,6 +744,7 @@
         "heightValidationMsg": "Default height of your model.",
         "ignoreMismatch": "Ignore Mismatches Between Selected Models",
         "importModels": "Import Models",
+        "importQueue": "Import Queue",
         "inpainting": "v1 Inpainting",
         "interpolationType": "Interpolation Type",
         "inverseSigmoid": "Inverse Sigmoid",
@@ -796,6 +798,7 @@
         "pickModelType": "Pick Model Type",
         "predictionType": "Prediction Type (for Stable Diffusion 2.x Models and occasional Stable Diffusion 1.x Models)",
         "quickAdd": "Quick Add",
+        "removeFromQueue": "Remove From Queue",
         "repo_id": "Repo ID",
         "repoIDValidationMsg": "Online repository of your model",
         "safetensorModels": "SafeTensors",
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx
index 2325fcf7dc..14ed0c6848 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx
@@ -1,10 +1,85 @@
-import { Box } from '@invoke-ai/ui-library';
+import { Button, Box, Flex, FormControl, FormLabel, Heading, Input, Text, Divider } from '@invoke-ai/ui-library';
+import { t } from 'i18next';
+import { CSSProperties } from 'react';
+import { useImportMainModelsMutation } from '../../../services/api/endpoints/models';
+import { useForm } from '@mantine/form';
+import { useAppDispatch } from 'app/store/storeHooks';
+import { addToast } from 'features/system/store/systemSlice';
+import { makeToast } from 'features/system/util/makeToast';
+import { ImportQueue } from './ImportQueue';
+
+const formStyles: CSSProperties = {
+  width: '100%',
+};
+
+type ExtendedImportModelConfig = {
+  location: string;
+};
 
-//jenn's workspace
 export const ImportModels = () => {
+  const dispatch = useAppDispatch();
+
+  const [importMainModel, { isLoading }] = useImportMainModelsMutation();
+
+  const addModelForm = useForm({
+    initialValues: {
+      location: '',
+    },
+  });
+
+  console.log('addModelForm', addModelForm.values.location)
+
+  const handleAddModelSubmit = (values: ExtendedImportModelConfig) => {
+    importMainModel({ source: values.location, config: undefined })
+      .unwrap()
+      .then((_) => {
+        dispatch(
+          addToast(
+            makeToast({
+              title: t('toast.modelAddedSimple'),
+              status: 'success',
+            })
+          )
+        );
+        addModelForm.reset();
+      })
+      .catch((error) => {
+        if (error) {
+          dispatch(
+            addToast(
+              makeToast({
+                title: `${error.data.detail} `,
+                status: 'error',
+              })
+            )
+          );
+        }
+      });
+  };
+
   return (
-    <Box layerStyle="first" p={2} borderRadius="base" w="full" h="full">
-      Import Models
+    <Box layerStyle="first" p={3} borderRadius="base" w="full" h="full">
+      <Box w="full" p={4}>
+        <Heading fontSize="xl">Add Model</Heading>
+      </Box>
+      <Box layerStyle="second" p={3} borderRadius="base" w="full" h="full">
+        <form onSubmit={addModelForm.onSubmit((v) => handleAddModelSubmit(v))} style={formStyles}>
+          <Flex gap={2} alignItems="flex-end" justifyContent="space-between">
+            <FormControl>
+              <Flex direction="column" w="full">
+                <FormLabel>{t('modelManager.modelLocation')}</FormLabel>
+                <Input {...addModelForm.getInputProps('location')} />
+              </Flex>
+            </FormControl>
+            <Button isDisabled={!addModelForm.values.location} isLoading={isLoading} type="submit">
+              {t('modelManager.addModel')}
+            </Button>
+          </Flex>
+        </form>
+        <Divider mt="5" mb="3" />
+        <Text>{t('modelManager.importQueue')}</Text>
+        <ImportQueue />
+      </Box>
     </Box>
   );
 };
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportQueue.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportQueue.tsx
new file mode 100644
index 0000000000..4a0407ff1a
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportQueue.tsx
@@ -0,0 +1,85 @@
+import {
+  Button,
+  Box,
+  Flex,
+  FormControl,
+  FormLabel,
+  Heading,
+  IconButton,
+  Input,
+  InputGroup,
+  InputRightElement,
+  Progress,
+  Text,
+} from '@invoke-ai/ui-library';
+import { t } from 'i18next';
+import { useMemo } from 'react';
+import { useGetModelImportsQuery } from '../../../services/api/endpoints/models';
+import { useAppDispatch } from 'app/store/storeHooks';
+import { addToast } from 'features/system/store/systemSlice';
+import { makeToast } from 'features/system/util/makeToast';
+import { PiXBold } from 'react-icons/pi';
+
+export const ImportQueue = () => {
+  const dispatch = useAppDispatch();
+
+  // start with this data then pull from sockets (idk how to do that yet, also might not even use this and just use socket)
+  const { data } = useGetModelImportsQuery();
+
+  const progressValues = useMemo(() => {
+    if (!data) {
+      return [];
+    }
+    const values = [];
+    for (let i = 0; i < data.length; i++) {
+      let value;
+      if (data[i] && data[i]?.bytes && data[i]?.total_bytes) {
+        value = (data[i]?.bytes / data[i]?.total_bytes) * 100;
+      }
+      values.push(value || undefined);
+    }
+    return values;
+  }, [data]);
+
+  return (
+    <Box mt={3} layerStyle="first" p={3} borderRadius="base" w="full" h="full">
+      <Flex direction="column" gap="2">
+        {data?.map((model, i) => (
+          <Flex gap="3" w="full" alignItems="center" textAlign="center">
+            <Text w="20%" whiteSpace="nowrap" overflow="hidden" text-overflow="ellipsis">
+              {model.source.repo_id}
+            </Text>
+            <Progress
+              value={progressValues[i]}
+              isIndeterminate={progressValues[i] === undefined}
+              aria-label={t('accessibility.invokeProgressBar')}
+              h={2}
+              w="50%"
+            />
+            <Text w="20%">{model.status}</Text>
+            {model.status === 'completed' ? (
+              <IconButton
+                isRound={true}
+                size="xs"
+                tooltip={t('modelManager.removeFromQueue')}
+                aria-label={t('modelManager.removeFromQueue')}
+                icon={<PiXBold />}
+                //   onClick={handleRemove}
+              />
+            ) : (
+              <IconButton
+                isRound={true}
+                size="xs"
+                tooltip={t('modelManager.cancel')}
+                aria-label={t('modelManager.cancel')}
+                icon={<PiXBold />}
+                //   onClick={handleCancel}
+                colorScheme="error"
+              />
+            )}
+          </Flex>
+        ))}
+      </Flex>
+    </Box>
+  );
+};

From c46eb72d45fe4621bc83c2909da7ed5468c17ac4 Mon Sep 17 00:00:00 2001
From: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Date: Wed, 21 Feb 2024 09:39:02 -0500
Subject: [PATCH 255/411] single model view

---
 .../ModelManagerPanel/ModelListItem.tsx       |  11 ++
 .../modelManagerV2/subpanels/ModelPane.tsx    |  13 ++
 .../subpanels/ModelPanel/ModelAttrView.tsx    |  15 +++
 .../subpanels/ModelPanel/ModelView.tsx        | 116 ++++++++++++++++++
 .../web/src/features/modelManagerV2/types.ts  |  14 ---
 .../ui/components/tabs/ModelManagerTab.tsx    |  29 +++--
 .../web/src/services/api/endpoints/models.ts  |  11 ++
 .../frontend/web/src/services/api/schema.ts   |  13 +-
 8 files changed, 195 insertions(+), 27 deletions(-)
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPane.tsx
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelAttrView.tsx
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx
 delete mode 100644 invokeai/frontend/web/src/features/modelManagerV2/types.ts

diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelListItem.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelListItem.tsx
index 5cc429ebcd..d6cb70f4e8 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelListItem.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelListItem.tsx
@@ -3,10 +3,12 @@ import {
   Button,
   ConfirmationAlertDialog,
   Flex,
+  Icon,
   IconButton,
   Text,
   Tooltip,
   useDisclosure,
+  Box,
 } from '@invoke-ai/ui-library';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { setSelectedModelKey } from 'features/modelManagerV2/store/modelManagerV2Slice';
@@ -15,6 +17,7 @@ import { addToast } from 'features/system/store/systemSlice';
 import { makeToast } from 'features/system/util/makeToast';
 import { memo, useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
+import { IoWarning } from 'react-icons/io5';
 import { PiTrashSimpleBold } from 'react-icons/pi';
 import { useDeleteModelsMutation } from 'services/api/endpoints/models';
 import type { AnyModelConfig } from 'services/api/types';
@@ -88,8 +91,16 @@ const ModelListItem = (props: ModelListItemProps) => {
           <Tooltip label={model.description} placement="bottom">
             <Text>{model.name}</Text>
           </Tooltip>
+          {model.format === 'checkpoint' && (
+            <Tooltip label="Checkpoint">
+              <Box>
+                <Icon as={IoWarning} />
+              </Box>
+            </Tooltip>
+          )}
         </Flex>
       </Flex>
+
       <IconButton
         onClick={onOpen}
         icon={<PiTrashSimpleBold />}
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPane.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPane.tsx
new file mode 100644
index 0000000000..9756b357b3
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPane.tsx
@@ -0,0 +1,13 @@
+import { Box } from '@invoke-ai/ui-library';
+import { useAppSelector } from '../../../app/store/storeHooks';
+import { ImportModels } from './ImportModels';
+import { ModelView } from './ModelPanel/ModelView';
+
+export const ModelPane = () => {
+  const selectedModelKey = useAppSelector((s) => s.modelmanagerV2.selectedModelKey);
+  return (
+    <Box layerStyle="first" p={2} borderRadius="base" w="full" h="full">
+      {selectedModelKey ? <ModelView /> : <ImportModels />}
+    </Box>
+  );
+};
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelAttrView.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelAttrView.tsx
new file mode 100644
index 0000000000..f45bfca993
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelAttrView.tsx
@@ -0,0 +1,15 @@
+import { FormControl, FormLabel, Text } from '@invoke-ai/ui-library';
+
+interface Props {
+  label: string;
+  value: string | null | undefined;
+}
+
+export const ModelAttrView = ({ label, value }: Props) => {
+  return (
+    <FormControl flexDir="column" alignItems="flex-start" gap={0}>
+      <FormLabel>{label}</FormLabel>
+      <Text fontSize="md">{value || '-'}</Text>
+    </FormControl>
+  );
+};
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx
new file mode 100644
index 0000000000..83e4e5380f
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx
@@ -0,0 +1,116 @@
+import { skipToken } from '@reduxjs/toolkit/query';
+import { useAppSelector } from '../../../../app/store/storeHooks';
+import { useGetModelQuery } from '../../../../services/api/endpoints/models';
+import { Flex, Text, Heading } from '@invoke-ai/ui-library';
+import DataViewer from '../../../gallery/components/ImageMetadataViewer/DataViewer';
+import { useMemo } from 'react';
+import {
+  CheckpointModelConfig,
+  ControlNetConfig,
+  DiffusersModelConfig,
+  IPAdapterConfig,
+  LoRAConfig,
+  T2IAdapterConfig,
+  TextualInversionConfig,
+  VAEConfig,
+} from '../../../../services/api/types';
+import { ModelAttrView } from './ModelAttrView';
+
+export const ModelView = () => {
+  const selectedModelKey = useAppSelector((s) => s.modelmanagerV2.selectedModelKey);
+  const { data, isLoading } = useGetModelQuery(selectedModelKey ?? skipToken);
+
+  const modelConfigData = useMemo(() => {
+    if (!data) {
+      return null;
+    }
+    const modelFormat = data.config.format;
+    const modelType = data.config.type;
+
+    if (modelType === 'main') {
+      if (modelFormat === 'diffusers') {
+        return data.config as DiffusersModelConfig;
+      } else if (modelFormat === 'checkpoint') {
+        return data.config as CheckpointModelConfig;
+      }
+    }
+
+    switch (modelType) {
+      case 'lora':
+        return data.config as LoRAConfig;
+      case 'embedding':
+        return data.config as TextualInversionConfig;
+      case 't2i_adapter':
+        return data.config as T2IAdapterConfig;
+      case 'ip_adapter':
+        return data.config as IPAdapterConfig;
+      case 'controlnet':
+        return data.config as ControlNetConfig;
+      case 'vae':
+        return data.config as VAEConfig;
+      default:
+        return null;
+    }
+  }, [data]);
+
+  if (isLoading) {
+    return <Text>Loading</Text>;
+  }
+
+  if (!modelConfigData) {
+    return <Text>Something went wrong</Text>;
+  }
+  return (
+    <Flex flexDir="column" h="full">
+      <Flex flexDir="column" gap={1} p={2}>
+        <Heading as="h2" fontSize="lg">
+          {modelConfigData.name}
+        </Heading>
+        {modelConfigData.source && <Text variant="subtext">Source: {modelConfigData.source}</Text>}
+      </Flex>
+
+      <Flex flexDir="column" p={2} gap={3}>
+        <Flex>
+          <ModelAttrView label="Description" value={modelConfigData.description} />
+        </Flex>
+        <Flex gap={2}>
+          <ModelAttrView label="Base Model" value={modelConfigData.base} />
+          <ModelAttrView label="Model Type" value={modelConfigData.type} />
+        </Flex>
+        <Flex gap={2}>
+          <ModelAttrView label="Format" value={modelConfigData.format} />
+          <ModelAttrView label="Path" value={modelConfigData.path} />
+        </Flex>
+        {modelConfigData.type === 'main' && (
+          <>
+            <Flex gap={2}>
+              {modelConfigData.format === 'diffusers' && (
+                <ModelAttrView label="Repo Variant" value={modelConfigData.repo_variant} />
+              )}
+              {modelConfigData.format === 'checkpoint' && (
+                <ModelAttrView label="Config Path" value={modelConfigData.config} />
+              )}
+
+              <ModelAttrView label="Variant" value={modelConfigData.variant} />
+            </Flex>
+            <Flex gap={2}>
+              <ModelAttrView label="Prediction Type" value={modelConfigData.prediction_type} />
+              <ModelAttrView label="Upcast Attention" value={`${modelConfigData.upcast_attention}`} />
+            </Flex>
+            <Flex gap={2}>
+              <ModelAttrView label="ZTSNR Training" value={`${modelConfigData.ztsnr_training}`} />
+              <ModelAttrView label="VAE" value={modelConfigData.vae} />
+            </Flex>
+          </>
+        )}
+        {modelConfigData.type === 'ip_adapter' && (
+          <Flex gap={2}>
+            <ModelAttrView label="Image Encoder Model ID" value={modelConfigData.image_encoder_model_id} />
+          </Flex>
+        )}
+      </Flex>
+
+      <Flex h="full">{!!data?.metadata && <DataViewer label="metadata" data={data.metadata} />}</Flex>
+    </Flex>
+  );
+};
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/types.ts b/invokeai/frontend/web/src/features/modelManagerV2/types.ts
deleted file mode 100644
index a209fbb876..0000000000
--- a/invokeai/frontend/web/src/features/modelManagerV2/types.ts
+++ /dev/null
@@ -1,14 +0,0 @@
-import { z } from "zod";
-
-export const zBaseModel = z.enum(['any', 'sd-1', 'sd-2', 'sdxl', 'sdxl-refiner']);
-export const zModelType = z.enum([
-    'main',
-    'vae',
-    'lora',
-    'controlnet',
-    'embedding',
-    'ip_adapter',
-    'clip_vision',
-    't2i_adapter',
-    'onnx', // TODO(psyche): Remove this when removed from backend
-]);
\ No newline at end of file
diff --git a/invokeai/frontend/web/src/features/ui/components/tabs/ModelManagerTab.tsx b/invokeai/frontend/web/src/features/ui/components/tabs/ModelManagerTab.tsx
index 8117631f22..9245f5c60d 100644
--- a/invokeai/frontend/web/src/features/ui/components/tabs/ModelManagerTab.tsx
+++ b/invokeai/frontend/web/src/features/ui/components/tabs/ModelManagerTab.tsx
@@ -1,16 +1,25 @@
-import { Box,Flex } from '@invoke-ai/ui-library';
-import { ImportModels } from 'features/modelManagerV2/subpanels/ImportModels';
-import { ModelManager } from 'features/modelManagerV2/subpanels/ModelManager';
-import { memo } from 'react';
+import { Flex, Heading, Tab, TabList, TabPanel, TabPanels, Tabs, Box, Button } from '@invoke-ai/ui-library';
+import ImportModelsPanel from 'features/modelManager/subpanels/ImportModelsPanel';
+import MergeModelsPanel from 'features/modelManager/subpanels/MergeModelsPanel';
+import ModelManagerPanel from 'features/modelManager/subpanels/ModelManagerPanel';
+import ModelManagerSettingsPanel from 'features/modelManager/subpanels/ModelManagerSettingsPanel';
+import type { ReactNode } from 'react';
+import { memo, useMemo } from 'react';
+import { useTranslation } from 'react-i18next';
+import { SyncModelsIconButton } from '../../../modelManager/components/SyncModels/SyncModelsIconButton';
+import { ModelManager } from '../../../modelManagerV2/subpanels/ModelManager';
+import { ModelPane } from '../../../modelManagerV2/subpanels/ModelPane';
+
+type ModelManagerTabName = 'modelManager' | 'importModels' | 'mergeModels' | 'settings';
 
 const ModelManagerTab = () => {
+  const { t } = useTranslation();
+
   return (
-    <Box w="full" h="full">
-      <Flex w="full" h="full" gap={4}>
-        <ModelManager />
-        <ImportModels />
-      </Flex>
-    </Box>
+    <Flex w="full" h="full" gap="2">
+      <ModelManager />
+      <ModelPane />
+    </Flex>
   );
 };
 
diff --git a/invokeai/frontend/web/src/services/api/endpoints/models.ts b/invokeai/frontend/web/src/services/api/endpoints/models.ts
index 6897768a1b..5db2dea00e 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/models.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/models.ts
@@ -26,6 +26,10 @@ type UpdateModelArg = {
 
 type UpdateModelResponse = paths['/api/v2/models/i/{key}']['patch']['responses']['200']['content']['application/json'];
 
+
+type GetModelResponse =
+  paths['/api/v2/models/i/{key}']['get']['responses']['200']['content']['application/json'];
+
 type ListModelsArg = NonNullable<paths['/api/v2/models/']['get']['parameters']['query']>;
 
 type DeleteMainModelArg = {
@@ -165,6 +169,12 @@ export const modelsApi = api.injectEndpoints({
       providesTags: buildProvidesTags<MainModelConfig>('MainModel'),
       transformResponse: buildTransformResponse<MainModelConfig>(mainModelsAdapter),
     }),
+    getModel: build.query<GetModelResponse, string>({
+      query: (key) => {
+        return buildModelsUrl(`i/${key}`);
+      },
+      providesTags: ['Model'],
+    }),
     updateModels: build.mutation<UpdateModelResponse, UpdateModelArg>({
       query: ({ key, body }) => {
         return {
@@ -320,4 +330,5 @@ export const {
   useGetModelsInFolderQuery,
   useGetCheckpointConfigsQuery,
   useGetModelImportsQuery,
+  useGetModelQuery
 } = modelsApi;
diff --git a/invokeai/frontend/web/src/services/api/schema.ts b/invokeai/frontend/web/src/services/api/schema.ts
index 3566fdb9e2..c9690649f8 100644
--- a/invokeai/frontend/web/src/services/api/schema.ts
+++ b/invokeai/frontend/web/src/services/api/schema.ts
@@ -22,7 +22,7 @@ export type paths = {
   "/api/v2/models/i/{key}": {
     /**
      * Get Model Record
-     * @description Get a model record
+     * @description Get a model record and metadata
      */
     get: operations["get_model_record"];
     /**
@@ -4202,6 +4202,13 @@ export type components = {
        */
       type: "freeu";
     };
+    /** GetModelResponse */
+    GetModelResponse: {
+      /** Config */
+      config: (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["ONNXSD1Config"] | components["schemas"]["ONNXSD2Config"] | components["schemas"]["ONNXSDXLConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
+      /** Metadata */
+      metadata: (components["schemas"]["BaseMetadata"] | components["schemas"]["HuggingFaceMetadata"] | components["schemas"]["CivitaiMetadata"]) | null;
+    };
     /** Graph */
     Graph: {
       /**
@@ -11169,7 +11176,7 @@ export type operations = {
   };
   /**
    * Get Model Record
-   * @description Get a model record
+   * @description Get a model record and metadata
    */
   get_model_record: {
     parameters: {
@@ -11182,7 +11189,7 @@ export type operations = {
       /** @description The model configuration was retrieved successfully */
       200: {
         content: {
-          "application/json": (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["ONNXSD1Config"] | components["schemas"]["ONNXSD2Config"] | components["schemas"]["ONNXSDXLConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
+          "application/json": components["schemas"]["GetModelResponse"];
         };
       };
       /** @description Bad request */

From 6b68971f384555d740882cec4229a2f61dc03d04 Mon Sep 17 00:00:00 2001
From: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Date: Wed, 21 Feb 2024 09:41:50 -0500
Subject: [PATCH 256/411] hook up Add Model button

---
 .../modelManagerV2/subpanels/ModelManager.tsx        | 12 +++++++++++-
 1 file changed, 11 insertions(+), 1 deletion(-)

diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManager.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManager.tsx
index 648f98dbb3..900a6a9342 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManager.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManager.tsx
@@ -3,8 +3,16 @@ import { SyncModelsIconButton } from 'features/modelManager/components/SyncModel
 
 import ModelList from './ModelManagerPanel/ModelList';
 import { ModelListNavigation } from './ModelManagerPanel/ModelListNavigation';
+import { useCallback } from 'react';
+import { useAppDispatch } from '../../../app/store/storeHooks';
+import { setSelectedModelKey } from '../store/modelManagerV2Slice';
 
 export const ModelManager = () => {
+  const dispatch = useAppDispatch();
+  const handleClickAddModel = useCallback(() => {
+    dispatch(setSelectedModelKey(null));
+  }, [dispatch]);
+
   return (
     <Box layerStyle="first" p={3} borderRadius="base" w="full" h="full">
       <Flex w="full" p={3} justifyContent="space-between" alignItems="center">
@@ -13,7 +21,9 @@ export const ModelManager = () => {
           <SyncModelsIconButton />
         </Flex>
         <Flex gap={2}>
-          <Button colorScheme="invokeYellow">Add Model</Button>
+          <Button colorScheme="invokeYellow" onClick={handleClickAddModel}>
+            Add Model
+          </Button>
           <Button>Scan for Models</Button>
         </Flex>
       </Flex>

From 0a69779df90989e7b245c0abdac29080cda967cc Mon Sep 17 00:00:00 2001
From: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Date: Wed, 21 Feb 2024 13:56:14 -0500
Subject: [PATCH 257/411] edit view for model, depending on type and valid
 values

---
 .../store/modelManagerV2Slice.ts              |   8 +-
 .../modelManagerV2/subpanels/ModelPane.tsx    |   4 +-
 .../ModelPanel/Fields/BaseModelSelect.tsx     |  29 +++
 .../ModelPanel/Fields/BooleanSelect.tsx       |  27 +++
 .../ModelPanel/Fields/ModelFormatSelect.tsx   |  53 +++++
 .../ModelPanel/Fields/ModelTypeSelect.tsx     |  33 +++
 .../ModelPanel/Fields/ModelVariantSelect.tsx  |  27 +++
 .../Fields/PredictionTypeSelect.tsx           |  28 +++
 .../ModelPanel/Fields/RepoVariantSelect.tsx   |  30 +++
 .../subpanels/ModelPanel/Model.tsx            |   8 +
 .../subpanels/ModelPanel/ModelEdit.tsx        | 196 ++++++++++++++++++
 .../subpanels/ModelPanel/ModelView.tsx        | 138 +++++++-----
 .../features/parameters/types/constants.ts    |   6 +-
 .../web/src/services/api/endpoints/models.ts  |  11 +-
 .../frontend/web/src/services/api/schema.ts   |  17 +-
 15 files changed, 538 insertions(+), 77 deletions(-)
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/BaseModelSelect.tsx
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/BooleanSelect.tsx
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelFormatSelect.tsx
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelTypeSelect.tsx
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelVariantSelect.tsx
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/PredictionTypeSelect.tsx
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/RepoVariantSelect.tsx
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Model.tsx
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx

diff --git a/invokeai/frontend/web/src/features/modelManagerV2/store/modelManagerV2Slice.ts b/invokeai/frontend/web/src/features/modelManagerV2/store/modelManagerV2Slice.ts
index 29b071e9b1..83bd0cf8d5 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/store/modelManagerV2Slice.ts
+++ b/invokeai/frontend/web/src/features/modelManagerV2/store/modelManagerV2Slice.ts
@@ -6,6 +6,7 @@ import type { PersistConfig, RootState } from 'app/store/store';
 type ModelManagerState = {
     _version: 1;
     selectedModelKey: string | null;
+    selectedModelMode: "edit" | "view",
     searchTerm: string;
     filteredModelType: string | null;
 };
@@ -13,6 +14,7 @@ type ModelManagerState = {
 export const initialModelManagerState: ModelManagerState = {
     _version: 1,
     selectedModelKey: null,
+    selectedModelMode: "view",
     filteredModelType: null,
     searchTerm: ""
 };
@@ -22,8 +24,12 @@ export const modelManagerV2Slice = createSlice({
     initialState: initialModelManagerState,
     reducers: {
         setSelectedModelKey: (state, action: PayloadAction<string | null>) => {
+            state.selectedModelMode = "view"
             state.selectedModelKey = action.payload;
         },
+        setSelectedModelMode: (state, action: PayloadAction<"view" | "edit">) => {
+            state.selectedModelMode = action.payload;
+        },
         setSearchTerm: (state, action: PayloadAction<string>) => {
             state.searchTerm = action.payload;
         },
@@ -34,7 +40,7 @@ export const modelManagerV2Slice = createSlice({
     },
 });
 
-export const { setSelectedModelKey, setSearchTerm, setFilteredModelType } = modelManagerV2Slice.actions;
+export const { setSelectedModelKey, setSearchTerm, setFilteredModelType, setSelectedModelMode } = modelManagerV2Slice.actions;
 
 export const selectModelManagerSlice = (state: RootState) => state.modelmanager;
 
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPane.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPane.tsx
index 9756b357b3..7658e741d3 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPane.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPane.tsx
@@ -1,13 +1,13 @@
 import { Box } from '@invoke-ai/ui-library';
 import { useAppSelector } from '../../../app/store/storeHooks';
 import { ImportModels } from './ImportModels';
-import { ModelView } from './ModelPanel/ModelView';
+import { Model } from './ModelPanel/Model';
 
 export const ModelPane = () => {
   const selectedModelKey = useAppSelector((s) => s.modelmanagerV2.selectedModelKey);
   return (
     <Box layerStyle="first" p={2} borderRadius="base" w="full" h="full">
-      {selectedModelKey ? <ModelView /> : <ImportModels />}
+      {selectedModelKey ? <Model /> : <ImportModels />}
     </Box>
   );
 };
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/BaseModelSelect.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/BaseModelSelect.tsx
new file mode 100644
index 0000000000..da7333c2a8
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/BaseModelSelect.tsx
@@ -0,0 +1,29 @@
+import type { ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
+import { Combobox, FormControl, FormLabel } from '@invoke-ai/ui-library';
+import { typedMemo } from 'common/util/typedMemo';
+import { MODEL_TYPE_MAP } from 'features/parameters/types/constants';
+import { useCallback, useMemo } from 'react';
+import type { UseControllerProps } from 'react-hook-form';
+import { useController } from 'react-hook-form';
+import type { AnyModelConfig } from 'services/api/types';
+
+const options: ComboboxOption[] = [
+  { value: 'sd-1', label: MODEL_TYPE_MAP['sd-1'] },
+  { value: 'sd-2', label: MODEL_TYPE_MAP['sd-2'] },
+  { value: 'sdxl', label: MODEL_TYPE_MAP['sdxl'] },
+  { value: 'sdxl-refiner', label: MODEL_TYPE_MAP['sdxl-refiner'] },
+];
+
+const BaseModelSelect = <T extends AnyModelConfig>(props: UseControllerProps<T>) => {
+  const { field } = useController(props);
+  const value = useMemo(() => options.find((o) => o.value === field.value), [field.value]);
+  const onChange = useCallback<ComboboxOnChange>(
+    (v) => {
+      field.onChange(v?.value);
+    },
+    [field]
+  );
+  return <Combobox value={value} options={options} onChange={onChange} />;
+};
+
+export default typedMemo(BaseModelSelect);
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/BooleanSelect.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/BooleanSelect.tsx
new file mode 100644
index 0000000000..d21ee89531
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/BooleanSelect.tsx
@@ -0,0 +1,27 @@
+import type { ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
+import { Combobox } from '@invoke-ai/ui-library';
+import { typedMemo } from 'common/util/typedMemo';
+import { useCallback, useMemo } from 'react';
+import type { UseControllerProps } from 'react-hook-form';
+import { useController } from 'react-hook-form';
+import type { AnyModelConfig } from 'services/api/types';
+
+const options: ComboboxOption[] = [
+  { value: 'none', label: '-' },
+  { value: true as any, label: 'True' },
+  { value: false as any, label: 'False' },
+];
+
+const BooleanSelect = <T extends AnyModelConfig>(props: UseControllerProps<T>) => {
+  const { field } = useController(props);
+  const value = useMemo(() => options.find((o) => o.value === field.value), [field.value]);
+  const onChange = useCallback<ComboboxOnChange>(
+    (v) => {
+      v?.value === 'none' ? field.onChange(undefined) : field.onChange(v?.value);
+    },
+    [field]
+  );
+  return <Combobox value={value} options={options} onChange={onChange} />;
+};
+
+export default typedMemo(BooleanSelect);
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelFormatSelect.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelFormatSelect.tsx
new file mode 100644
index 0000000000..0552789a86
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelFormatSelect.tsx
@@ -0,0 +1,53 @@
+import type { ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
+import { Combobox, FormControl, FormLabel } from '@invoke-ai/ui-library';
+import { typedMemo } from 'common/util/typedMemo';
+import { LORA_MODEL_FORMAT_MAP, MODEL_TYPE_MAP } from 'features/parameters/types/constants';
+import { useCallback, useMemo } from 'react';
+import type { UseControllerProps } from 'react-hook-form';
+import { useController } from 'react-hook-form';
+import type { AnyModelConfig } from 'services/api/types';
+
+const options: ComboboxOption[] = [
+  { value: 'sd-1', label: MODEL_TYPE_MAP['sd-1'] },
+  { value: 'sd-2', label: MODEL_TYPE_MAP['sd-2'] },
+  { value: 'sdxl', label: MODEL_TYPE_MAP['sdxl'] },
+  { value: 'sdxl-refiner', label: MODEL_TYPE_MAP['sdxl-refiner'] },
+];
+
+const ModelFormatSelect = <T extends AnyModelConfig>(props: UseControllerProps<T>) => {
+  const { field, formState } = useController(props);
+
+  const onChange = useCallback<ComboboxOnChange>(
+    (v) => {
+      field.onChange(v?.value);
+    },
+    [field]
+  );
+
+  const options: ComboboxOption[] = useMemo(() => {
+    if (formState.defaultValues?.type === 'lora') {
+      return Object.keys(LORA_MODEL_FORMAT_MAP).map((format) => ({
+        value: format,
+        label: LORA_MODEL_FORMAT_MAP[format],
+      })) as ComboboxOption[];
+    } else if (formState.defaultValues?.type === 'embedding') {
+      return [
+        { value: 'embedding_file', label: 'Embedding File' },
+        { value: 'embedding_folder', label: 'Embedding Folder' },
+      ];
+    } else if (formState.defaultValues?.type === 'ip_adapter') {
+      return [{ value: 'invokeai', label: 'invokeai' }];
+    } else {
+      return [
+        { value: 'diffusers', label: 'Diffusers' },
+        { value: 'checkpoint', label: 'Checkpoint' },
+      ];
+    }
+  }, [formState.defaultValues?.type]);
+
+  const value = useMemo(() => options.find((o) => o.value === field.value), [options, field.value]);
+
+  return <Combobox value={value} options={options} onChange={onChange} />;
+};
+
+export default typedMemo(ModelFormatSelect);
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelTypeSelect.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelTypeSelect.tsx
new file mode 100644
index 0000000000..140bfa9fe0
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelTypeSelect.tsx
@@ -0,0 +1,33 @@
+import type { ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
+import { Combobox, FormControl, FormLabel } from '@invoke-ai/ui-library';
+import { typedMemo } from 'common/util/typedMemo';
+import { MODEL_TYPE_MAP } from 'features/parameters/types/constants';
+import { useCallback, useMemo } from 'react';
+import type { UseControllerProps } from 'react-hook-form';
+import { useController } from 'react-hook-form';
+import type { AnyModelConfig } from 'services/api/types';
+import { MODEL_TYPE_LABELS } from '../../ModelManagerPanel/ModelTypeFilter';
+
+const options: ComboboxOption[] = [
+  { value: 'main', label: MODEL_TYPE_LABELS['main'] as string },
+  { value: 'lora', label: MODEL_TYPE_LABELS['lora'] as string },
+  { value: 'embedding', label: MODEL_TYPE_LABELS['embedding'] as string },
+  { value: 'vae', label: MODEL_TYPE_LABELS['vae'] as string },
+  { value: 'controlnet', label: MODEL_TYPE_LABELS['controlnet'] as string },
+  { value: 'ip_adapter', label: MODEL_TYPE_LABELS['ip_adapter'] as string },
+  { value: 't2i_adapater', label: MODEL_TYPE_LABELS['t2i_adapter'] as string },
+];
+
+const ModelTypeSelect = <T extends AnyModelConfig>(props: UseControllerProps<T>) => {
+  const { field } = useController(props);
+  const value = useMemo(() => options.find((o) => o.value === field.value), [field.value]);
+  const onChange = useCallback<ComboboxOnChange>(
+    (v) => {
+      field.onChange(v?.value);
+    },
+    [field]
+  );
+  return <Combobox value={value} options={options} onChange={onChange} />;
+};
+
+export default typedMemo(ModelTypeSelect);
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelVariantSelect.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelVariantSelect.tsx
new file mode 100644
index 0000000000..7fb74b0bd9
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelVariantSelect.tsx
@@ -0,0 +1,27 @@
+import type { ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
+import { Combobox, FormControl, FormLabel } from '@invoke-ai/ui-library';
+import { typedMemo } from 'common/util/typedMemo';
+import { useCallback, useMemo } from 'react';
+import type { UseControllerProps } from 'react-hook-form';
+import { useController } from 'react-hook-form';
+import type { AnyModelConfig, CheckpointModelConfig, DiffusersModelConfig } from 'services/api/types';
+
+const options: ComboboxOption[] = [
+  { value: 'normal', label: 'Normal' },
+  { value: 'inpaint', label: 'Inpaint' },
+  { value: 'depth', label: 'Depth' },
+];
+
+const ModelVariantSelect = <T extends AnyModelConfig>(props: UseControllerProps<T>) => {
+  const { field } = useController(props);
+  const value = useMemo(() => options.find((o) => o.value === field.value), [field.value]);
+  const onChange = useCallback<ComboboxOnChange>(
+    (v) => {
+      field.onChange(v?.value);
+    },
+    [field]
+  );
+  return <Combobox value={value} options={options} onChange={onChange} />;
+};
+
+export default typedMemo(ModelVariantSelect);
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/PredictionTypeSelect.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/PredictionTypeSelect.tsx
new file mode 100644
index 0000000000..20667ab5bc
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/PredictionTypeSelect.tsx
@@ -0,0 +1,28 @@
+import type { ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
+import { Combobox } from '@invoke-ai/ui-library';
+import { typedMemo } from 'common/util/typedMemo';
+import { useCallback, useMemo } from 'react';
+import type { UseControllerProps } from 'react-hook-form';
+import { useController } from 'react-hook-form';
+import type { AnyModelConfig } from 'services/api/types';
+
+const options: ComboboxOption[] = [
+  { value: 'none', label: '-' },
+  { value: 'epsilon', label: 'epsilon' },
+  { value: 'v_prediction', label: 'v_prediction' },
+  { value: 'sample', label: 'sample' },
+];
+
+const PredictionTypeSelect = <T extends AnyModelConfig>(props: UseControllerProps<T>) => {
+  const { field } = useController(props);
+  const value = useMemo(() => options.find((o) => o.value === field.value), [field.value]);
+  const onChange = useCallback<ComboboxOnChange>(
+    (v) => {
+      v?.value === 'none' ? field.onChange(undefined) : field.onChange(v?.value);
+    },
+    [field]
+  );
+  return <Combobox value={value} options={options} onChange={onChange} />;
+};
+
+export default typedMemo(PredictionTypeSelect);
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/RepoVariantSelect.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/RepoVariantSelect.tsx
new file mode 100644
index 0000000000..74793be789
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/RepoVariantSelect.tsx
@@ -0,0 +1,30 @@
+import type { ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
+import { Combobox } from '@invoke-ai/ui-library';
+import { typedMemo } from 'common/util/typedMemo';
+import { useCallback, useMemo } from 'react';
+import type { UseControllerProps } from 'react-hook-form';
+import { useController } from 'react-hook-form';
+import type { AnyModelConfig } from 'services/api/types';
+
+const options: ComboboxOption[] = [
+  { value: 'none', label: '-' },
+  { value: 'fp16', label: 'fp16' },
+  { value: 'fp32', label: 'fp32' },
+  { value: 'onnx', label: 'onnx' },
+  { value: 'openvino', label: 'openvino' },
+  { value: 'flax', label: 'flax' },
+];
+
+const RepoVariantSelect = <T extends AnyModelConfig>(props: UseControllerProps<T>) => {
+  const { field } = useController(props);
+  const value = useMemo(() => options.find((o) => o.value === field.value), [field.value]);
+  const onChange = useCallback<ComboboxOnChange>(
+    (v) => {
+      v?.value === 'none' ? field.onChange(undefined) : field.onChange(v?.value);
+    },
+    [field]
+  );
+  return <Combobox value={value} options={options} onChange={onChange} />;
+};
+
+export default typedMemo(RepoVariantSelect);
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Model.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Model.tsx
new file mode 100644
index 0000000000..8a6f7ddee4
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Model.tsx
@@ -0,0 +1,8 @@
+import { useAppSelector } from '../../../../app/store/storeHooks';
+import { ModelEdit } from './ModelEdit';
+import { ModelView } from './ModelView';
+
+export const Model = () => {
+  const selectedModelMode = useAppSelector((s) => s.modelmanagerV2.selectedModelMode);
+  return selectedModelMode === 'view' ? <ModelView /> : <ModelEdit />;
+};
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx
new file mode 100644
index 0000000000..70d0596cd8
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx
@@ -0,0 +1,196 @@
+import { skipToken } from '@reduxjs/toolkit/query';
+import { useAppDispatch, useAppSelector } from '../../../../app/store/storeHooks';
+import { useGetModelQuery } from '../../../../services/api/endpoints/models';
+import { Flex, Text, Heading, Button, Input, FormControl, FormLabel, Textarea } from '@invoke-ai/ui-library';
+import { useCallback, useMemo } from 'react';
+import {
+  AnyModelConfig,
+  CheckpointModelConfig,
+  ControlNetConfig,
+  DiffusersModelConfig,
+  IPAdapterConfig,
+  LoRAConfig,
+  T2IAdapterConfig,
+  TextualInversionConfig,
+  VAEConfig,
+} from '../../../../services/api/types';
+import { setSelectedModelMode } from '../../store/modelManagerV2Slice';
+import BaseModelSelect from './Fields/BaseModelSelect';
+import { useForm } from 'react-hook-form';
+import ModelTypeSelect from './Fields/ModelTypeSelect';
+import ModelVariantSelect from './Fields/ModelVariantSelect';
+import RepoVariantSelect from './Fields/RepoVariantSelect';
+import PredictionTypeSelect from './Fields/PredictionTypeSelect';
+import BooleanSelect from './Fields/BooleanSelect';
+import ModelFormatSelect from './Fields/ModelFormatSelect';
+
+export const ModelEdit = () => {
+  const dispatch = useAppDispatch();
+  const selectedModelKey = useAppSelector((s) => s.modelmanagerV2.selectedModelKey);
+  const { data, isLoading } = useGetModelQuery(selectedModelKey ?? skipToken);
+
+  const modelData = useMemo(() => {
+    if (!data) {
+      return null;
+    }
+    const modelFormat = data.format;
+    const modelType = data.type;
+
+    if (modelType === 'main') {
+      if (modelFormat === 'diffusers') {
+        return data as DiffusersModelConfig;
+      } else if (modelFormat === 'checkpoint') {
+        return data as CheckpointModelConfig;
+      }
+    }
+
+    switch (modelType) {
+      case 'lora':
+        return data as LoRAConfig;
+      case 'embedding':
+        return data as TextualInversionConfig;
+      case 't2i_adapter':
+        return data as T2IAdapterConfig;
+      case 'ip_adapter':
+        return data as IPAdapterConfig;
+      case 'controlnet':
+        return data as ControlNetConfig;
+      case 'vae':
+        return data as VAEConfig;
+      default:
+        return data as DiffusersModelConfig;
+    }
+  }, [data]);
+
+  const {
+    register,
+    handleSubmit,
+    control,
+    formState: { errors },
+    reset,
+  } = useForm<AnyModelConfig>({
+    defaultValues: {
+      ...modelData,
+    },
+    mode: 'onChange',
+  });
+
+  const handleClickCancel = useCallback(() => {
+    dispatch(setSelectedModelMode('view'));
+  }, [dispatch]);
+
+  if (isLoading) {
+    return <Text>Loading</Text>;
+  }
+
+  if (!modelData) {
+    return <Text>Something went wrong</Text>;
+  }
+  return (
+    <Flex flexDir="column" h="full">
+      <Flex w="full" justifyContent="space-between" gap={4} alignItems="center">
+        <Input
+          {...register('name', {
+            validate: (value) => value.trim().length > 3 || 'Must be at least 3 characters',
+          })}
+          size="lg"
+        />
+        <Flex gap={2}>
+          <Button size="sm" onClick={handleClickCancel}>
+            Cancel
+          </Button>
+          <Button size="sm" colorScheme="invokeYellow">
+            Save
+          </Button>
+        </Flex>
+      </Flex>
+
+      <Flex flexDir="column" gap={3} mt="4">
+        <Flex>
+          <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+            <FormLabel>Description</FormLabel>
+            <Textarea fontSize="md" resize="none" {...register('description')} />
+          </FormControl>
+        </Flex>
+        <Heading as="h3" fontSize="md" mt="4">
+          Model Settings
+        </Heading>
+        <Flex gap={4}>
+          <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+            <FormLabel>Base Model</FormLabel>
+            <BaseModelSelect<AnyModelConfig> control={control} name="base" />
+          </FormControl>
+          <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+            <FormLabel>Model Type</FormLabel>
+            <ModelTypeSelect<AnyModelConfig> control={control} name="type" />
+          </FormControl>
+        </Flex>
+        <Flex gap={4}>
+          <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+            <FormLabel>Format</FormLabel>
+            <ModelFormatSelect<AnyModelConfig> control={control} name="format" />
+          </FormControl>
+          <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+            <FormLabel>Path</FormLabel>
+            <Input
+              {...register('path', {
+                validate: (value) => value.trim().length > 0 || 'Must provide a path',
+              })}
+            />
+          </FormControl>
+        </Flex>
+        {modelData.type === 'main' && (
+          <>
+            <Flex gap={4}>
+              {modelData.format === 'diffusers' && (
+                <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+                  <FormLabel>Repo Variant</FormLabel>
+                  <RepoVariantSelect<AnyModelConfig> control={control} name="repo_variant" />
+                </FormControl>
+              )}
+              {modelData.format === 'checkpoint' && (
+                <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+                  <FormLabel>Config Path</FormLabel>
+                  <Input {...register('config')} />
+                </FormControl>
+              )}
+
+              <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+                <FormLabel>Variant</FormLabel>
+                <ModelVariantSelect<AnyModelConfig> control={control} name="variant" />
+              </FormControl>
+            </Flex>
+            <Flex gap={4}>
+              <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+                <FormLabel>Prediction Type</FormLabel>
+                <PredictionTypeSelect<AnyModelConfig> control={control} name="prediction_type" />
+              </FormControl>
+              <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+                <FormLabel>Upcast Attention</FormLabel>
+                <BooleanSelect<AnyModelConfig> control={control} name="upcast_attention" />
+              </FormControl>
+            </Flex>
+            <Flex gap={4}>
+              <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+                <FormLabel>ZTSNR Training</FormLabel>
+                <BooleanSelect<AnyModelConfig> control={control} name="ztsnr_training" />
+              </FormControl>
+              <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+                <FormLabel>VAE Path</FormLabel>
+                <Input {...register('vae')} />
+              </FormControl>
+            </Flex>
+          </>
+        )}
+        {modelData.type === 'ip_adapter' && (
+          <Flex gap={4}>
+            <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+              <FormLabel>Image Encoder Model ID</FormLabel>
+              <Input {...register('image_encoder_model_id')} />
+            </FormControl>
+          </Flex>
+        )}
+      </Flex>
+    </Flex>
+  );
+};
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx
index 83e4e5380f..a8f6ee1e3e 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx
@@ -1,9 +1,9 @@
 import { skipToken } from '@reduxjs/toolkit/query';
-import { useAppSelector } from '../../../../app/store/storeHooks';
-import { useGetModelQuery } from '../../../../services/api/endpoints/models';
-import { Flex, Text, Heading } from '@invoke-ai/ui-library';
+import { useAppDispatch, useAppSelector } from '../../../../app/store/storeHooks';
+import { useGetModelMetadataQuery, useGetModelQuery } from '../../../../services/api/endpoints/models';
+import { Flex, Text, Heading, Button, Box } from '@invoke-ai/ui-library';
 import DataViewer from '../../../gallery/components/ImageMetadataViewer/DataViewer';
-import { useMemo } from 'react';
+import { useCallback, useMemo } from 'react';
 import {
   CheckpointModelConfig,
   ControlNetConfig,
@@ -15,102 +15,128 @@ import {
   VAEConfig,
 } from '../../../../services/api/types';
 import { ModelAttrView } from './ModelAttrView';
+import { IoPencil } from 'react-icons/io5';
+import { setSelectedModelMode } from '../../store/modelManagerV2Slice';
 
 export const ModelView = () => {
+  const dispatch = useAppDispatch();
   const selectedModelKey = useAppSelector((s) => s.modelmanagerV2.selectedModelKey);
   const { data, isLoading } = useGetModelQuery(selectedModelKey ?? skipToken);
+  const { data: metadata } = useGetModelMetadataQuery(selectedModelKey ?? skipToken);
 
-  const modelConfigData = useMemo(() => {
+  const modelData = useMemo(() => {
     if (!data) {
       return null;
     }
-    const modelFormat = data.config.format;
-    const modelType = data.config.type;
+    const modelFormat = data.format;
+    const modelType = data.type;
 
     if (modelType === 'main') {
       if (modelFormat === 'diffusers') {
-        return data.config as DiffusersModelConfig;
+        return data as DiffusersModelConfig;
       } else if (modelFormat === 'checkpoint') {
-        return data.config as CheckpointModelConfig;
+        return data as CheckpointModelConfig;
       }
     }
 
     switch (modelType) {
       case 'lora':
-        return data.config as LoRAConfig;
+        return data as LoRAConfig;
       case 'embedding':
-        return data.config as TextualInversionConfig;
+        return data as TextualInversionConfig;
       case 't2i_adapter':
-        return data.config as T2IAdapterConfig;
+        return data as T2IAdapterConfig;
       case 'ip_adapter':
-        return data.config as IPAdapterConfig;
+        return data as IPAdapterConfig;
       case 'controlnet':
-        return data.config as ControlNetConfig;
+        return data as ControlNetConfig;
       case 'vae':
-        return data.config as VAEConfig;
+        return data as VAEConfig;
       default:
         return null;
     }
   }, [data]);
 
+  const handleEditModel = useCallback(() => {
+    dispatch(setSelectedModelMode('edit'));
+  }, [dispatch]);
+
   if (isLoading) {
     return <Text>Loading</Text>;
   }
 
-  if (!modelConfigData) {
+  if (!modelData) {
     return <Text>Something went wrong</Text>;
   }
   return (
     <Flex flexDir="column" h="full">
-      <Flex flexDir="column" gap={1} p={2}>
-        <Heading as="h2" fontSize="lg">
-          {modelConfigData.name}
-        </Heading>
-        {modelConfigData.source && <Text variant="subtext">Source: {modelConfigData.source}</Text>}
+      <Flex w="full" justifyContent="space-between">
+        <Flex flexDir="column" gap={1} p={2}>
+          <Heading as="h2" fontSize="lg">
+            {modelData.name}
+          </Heading>
+
+          {modelData.source && <Text variant="subtext">Source: {modelData.source}</Text>}
+        </Flex>
+        <Button size="sm" leftIcon={<IoPencil />} colorScheme="invokeYellow" onClick={handleEditModel}>
+          Edit
+        </Button>
       </Flex>
 
       <Flex flexDir="column" p={2} gap={3}>
         <Flex>
-          <ModelAttrView label="Description" value={modelConfigData.description} />
+          <ModelAttrView label="Description" value={modelData.description} />
         </Flex>
-        <Flex gap={2}>
-          <ModelAttrView label="Base Model" value={modelConfigData.base} />
-          <ModelAttrView label="Model Type" value={modelConfigData.type} />
-        </Flex>
-        <Flex gap={2}>
-          <ModelAttrView label="Format" value={modelConfigData.format} />
-          <ModelAttrView label="Path" value={modelConfigData.path} />
-        </Flex>
-        {modelConfigData.type === 'main' && (
-          <>
-            <Flex gap={2}>
-              {modelConfigData.format === 'diffusers' && (
-                <ModelAttrView label="Repo Variant" value={modelConfigData.repo_variant} />
-              )}
-              {modelConfigData.format === 'checkpoint' && (
-                <ModelAttrView label="Config Path" value={modelConfigData.config} />
-              )}
-
-              <ModelAttrView label="Variant" value={modelConfigData.variant} />
-            </Flex>
-            <Flex gap={2}>
-              <ModelAttrView label="Prediction Type" value={modelConfigData.prediction_type} />
-              <ModelAttrView label="Upcast Attention" value={`${modelConfigData.upcast_attention}`} />
-            </Flex>
-            <Flex gap={2}>
-              <ModelAttrView label="ZTSNR Training" value={`${modelConfigData.ztsnr_training}`} />
-              <ModelAttrView label="VAE" value={modelConfigData.vae} />
-            </Flex>
-          </>
-        )}
-        {modelConfigData.type === 'ip_adapter' && (
+        <Heading as="h3" fontSize="md" mt="4">
+          Model Settings
+        </Heading>
+        <Box layerStyle="second" borderRadius="base" p={3}>
           <Flex gap={2}>
-            <ModelAttrView label="Image Encoder Model ID" value={modelConfigData.image_encoder_model_id} />
+            <ModelAttrView label="Base Model" value={modelData.base} />
+            <ModelAttrView label="Model Type" value={modelData.type} />
           </Flex>
-        )}
+          <Flex gap={2}>
+            <ModelAttrView label="Format" value={modelData.format} />
+            <ModelAttrView label="Path" value={modelData.path} />
+          </Flex>
+          {modelData.type === 'main' && (
+            <>
+              <Flex gap={2}>
+                {modelData.format === 'diffusers' && (
+                  <ModelAttrView label="Repo Variant" value={modelData.repo_variant} />
+                )}
+                {modelData.format === 'checkpoint' && <ModelAttrView label="Config Path" value={modelData.config} />}
+
+                <ModelAttrView label="Variant" value={modelData.variant} />
+              </Flex>
+              <Flex gap={2}>
+                <ModelAttrView label="Prediction Type" value={modelData.prediction_type} />
+                <ModelAttrView label="Upcast Attention" value={`${modelData.upcast_attention}`} />
+              </Flex>
+              <Flex gap={2}>
+                <ModelAttrView label="ZTSNR Training" value={`${modelData.ztsnr_training}`} />
+                <ModelAttrView label="VAE" value={modelData.vae} />
+              </Flex>
+            </>
+          )}
+          {modelData.type === 'ip_adapter' && (
+            <Flex gap={2}>
+              <ModelAttrView label="Image Encoder Model ID" value={modelData.image_encoder_model_id} />
+            </Flex>
+          )}
+        </Box>
       </Flex>
 
-      <Flex h="full">{!!data?.metadata && <DataViewer label="metadata" data={data.metadata} />}</Flex>
+      {metadata && (
+        <>
+          <Heading as="h3" fontSize="md" mt="4">
+            Model Metadata
+          </Heading>
+          <Flex h="full" w="full" p={2}>
+            <DataViewer label="metadata" data={metadata} />
+          </Flex>
+        </>
+      )}
     </Flex>
   );
 };
diff --git a/invokeai/frontend/web/src/features/parameters/types/constants.ts b/invokeai/frontend/web/src/features/parameters/types/constants.ts
index bd78759b39..baa255a102 100644
--- a/invokeai/frontend/web/src/features/parameters/types/constants.ts
+++ b/invokeai/frontend/web/src/features/parameters/types/constants.ts
@@ -2,7 +2,7 @@ import type { ComboboxOption } from '@invoke-ai/ui-library';
 import type { LoRAModelFormat } from 'services/api/types';
 
 /**
- * Mapping of model type to human readable name
+ * Mapping of base model to human readable name
  */
 export const MODEL_TYPE_MAP = {
   any: 'Any',
@@ -13,7 +13,7 @@ export const MODEL_TYPE_MAP = {
 };
 
 /**
- * Mapping of model type to (short) human readable name
+ * Mapping of base model to (short) human readable name
  */
 export const MODEL_TYPE_SHORT_MAP = {
   any: 'Any',
@@ -24,7 +24,7 @@ export const MODEL_TYPE_SHORT_MAP = {
 };
 
 /**
- * Mapping of model type to CLIP skip parameter constraints
+ * Mapping of base model to CLIP skip parameter constraints
  */
 export const CLIP_SKIP_MAP = {
   any: {
diff --git a/invokeai/frontend/web/src/services/api/endpoints/models.ts b/invokeai/frontend/web/src/services/api/endpoints/models.ts
index 5db2dea00e..71e539e82c 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/models.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/models.ts
@@ -29,6 +29,8 @@ type UpdateModelResponse = paths['/api/v2/models/i/{key}']['patch']['responses']
 
 type GetModelResponse =
   paths['/api/v2/models/i/{key}']['get']['responses']['200']['content']['application/json'];
+type GetModelMetadataResponse =
+  paths['/api/v2/models/meta/i/{key}']['get']['responses']['200']['content']['application/json'];
 
 type ListModelsArg = NonNullable<paths['/api/v2/models/']['get']['parameters']['query']>;
 
@@ -175,6 +177,12 @@ export const modelsApi = api.injectEndpoints({
       },
       providesTags: ['Model'],
     }),
+    getModelMetadata: build.query<GetModelMetadataResponse, string>({
+      query: (key) => {
+        return buildModelsUrl(`meta/i/${key}`);
+      },
+      providesTags: ['Model'],
+    }),
     updateModels: build.mutation<UpdateModelResponse, UpdateModelArg>({
       query: ({ key, body }) => {
         return {
@@ -330,5 +338,6 @@ export const {
   useGetModelsInFolderQuery,
   useGetCheckpointConfigsQuery,
   useGetModelImportsQuery,
-  useGetModelQuery
+  useGetModelQuery,
+  useGetModelMetadataQuery
 } = modelsApi;
diff --git a/invokeai/frontend/web/src/services/api/schema.ts b/invokeai/frontend/web/src/services/api/schema.ts
index c9690649f8..837a166541 100644
--- a/invokeai/frontend/web/src/services/api/schema.ts
+++ b/invokeai/frontend/web/src/services/api/schema.ts
@@ -22,7 +22,7 @@ export type paths = {
   "/api/v2/models/i/{key}": {
     /**
      * Get Model Record
-     * @description Get a model record and metadata
+     * @description Get a model record
      */
     get: operations["get_model_record"];
     /**
@@ -4202,13 +4202,6 @@ export type components = {
        */
       type: "freeu";
     };
-    /** GetModelResponse */
-    GetModelResponse: {
-      /** Config */
-      config: (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["ONNXSD1Config"] | components["schemas"]["ONNXSD2Config"] | components["schemas"]["ONNXSDXLConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
-      /** Metadata */
-      metadata: (components["schemas"]["BaseMetadata"] | components["schemas"]["HuggingFaceMetadata"] | components["schemas"]["CivitaiMetadata"]) | null;
-    };
     /** Graph */
     Graph: {
       /**
@@ -11176,7 +11169,7 @@ export type operations = {
   };
   /**
    * Get Model Record
-   * @description Get a model record and metadata
+   * @description Get a model record
    */
   get_model_record: {
     parameters: {
@@ -11189,7 +11182,7 @@ export type operations = {
       /** @description The model configuration was retrieved successfully */
       200: {
         content: {
-          "application/json": components["schemas"]["GetModelResponse"];
+          "application/json": (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["ONNXSD1Config"] | components["schemas"]["ONNXSD2Config"] | components["schemas"]["ONNXSDXLConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
         };
       };
       /** @description Bad request */
@@ -11346,10 +11339,6 @@ export type operations = {
       400: {
         content: never;
       };
-      /** @description No metadata available */
-      404: {
-        content: never;
-      };
       /** @description Validation Error */
       422: {
         content: {

From 20576deae839f6c87395f8ae3f457a2058345854 Mon Sep 17 00:00:00 2001
From: Jennifer Player <chainchompa@gmail.com>
Date: Wed, 21 Feb 2024 09:59:50 -0500
Subject: [PATCH 258/411] added socket listeners, added more info to ui

---
 .../middleware/listenerMiddleware/index.ts    |  2 +
 .../listeners/socketio/socketModelInstall.ts  | 63 +++++++++++++++++++
 .../modelManagerV2/subpanels/ImportQueue.tsx  |  2 +-
 .../web/src/services/api/endpoints/models.ts  |  3 +-
 .../frontend/web/src/services/api/index.ts    |  1 +
 .../web/src/services/events/actions.ts        | 15 +++++
 .../frontend/web/src/services/events/types.ts | 24 +++++++
 .../services/events/util/setEventListeners.ts | 36 +++++++++++
 8 files changed, 144 insertions(+), 2 deletions(-)
 create mode 100644 invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts

diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts
index 23e23c1140..26d7949e9c 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts
@@ -58,6 +58,7 @@ import { addInvocationErrorEventListener as addInvocationErrorListener } from '.
 import { addInvocationRetrievalErrorEventListener } from './listeners/socketio/socketInvocationRetrievalError';
 import { addInvocationStartedEventListener as addInvocationStartedListener } from './listeners/socketio/socketInvocationStarted';
 import { addModelLoadEventListener } from './listeners/socketio/socketModelLoad';
+import { addModelInstallEventListener } from './listeners/socketio/socketModelInstall';
 import { addSocketQueueItemStatusChangedEventListener } from './listeners/socketio/socketQueueItemStatusChanged';
 import { addSessionRetrievalErrorEventListener } from './listeners/socketio/socketSessionRetrievalError';
 import { addSocketSubscribedEventListener as addSocketSubscribedListener } from './listeners/socketio/socketSubscribed';
@@ -135,6 +136,7 @@ addSocketDisconnectedListener();
 addSocketSubscribedListener();
 addSocketUnsubscribedListener();
 addModelLoadEventListener();
+addModelInstallEventListener();
 addSessionRetrievalErrorEventListener();
 addInvocationRetrievalErrorEventListener();
 addSocketQueueItemStatusChangedEventListener();
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts
new file mode 100644
index 0000000000..b241df27c8
--- /dev/null
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts
@@ -0,0 +1,63 @@
+import { logger } from 'app/logging/logger';
+import {
+  socketModelInstallCompleted,
+  socketModelInstallDownloading,
+  socketModelInstallError,
+} from 'services/events/actions';
+import { modelsApi } from 'services/api/endpoints/models';
+import type { components, paths } from 'services/api/schema';
+
+
+import { startAppListening } from '../..';
+import { createEntityAdapter } from '@reduxjs/toolkit';
+
+const log = logger('socketio');
+
+export const addModelInstallEventListener = () => {
+  startAppListening({
+    actionCreator: socketModelInstallDownloading,
+    effect: async (action, { dispatch }) => {
+      const { bytes, local_path, source, timestamp, total_bytes } = action.payload.data;
+      let message = `Model install started: ${bytes}/${total_bytes}/${source}`;
+    // below doesnt work, still not sure how to update the importModels data 
+    //   dispatch(
+    //       modelsApi.util.updateQueryData('getModelImports', undefined, (draft) => {
+    //         importModelsAdapter.updateOne(draft, {
+    //             id: source,
+    //             changes: {
+    //                 bytes,
+    //                 total_bytes,
+    //             },\q
+    //             });
+    //         }
+    //         )
+    //   );
+
+      log.debug(action.payload, message);
+    },
+  });
+
+  startAppListening({
+    actionCreator: socketModelInstallCompleted,
+    effect: (action) => {
+      const { key, source, timestamp } = action.payload.data;
+
+      let message = `Model install completed: ${source}`;
+
+    //   dispatch something that marks the model installation as completed
+
+      log.debug(action.payload, message);
+    },
+  });
+
+  startAppListening({
+    actionCreator: socketModelInstallError,
+    effect: (action) => {
+      const { error, error_type, source } = action.payload.data;
+
+    //   dispatch something that marks the model installation as errored
+
+      log.debug(action.payload, error);
+    },
+  });
+};
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportQueue.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportQueue.tsx
index 4a0407ff1a..c2dbece4b3 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportQueue.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportQueue.tsx
@@ -45,7 +45,7 @@ export const ImportQueue = () => {
     <Box mt={3} layerStyle="first" p={3} borderRadius="base" w="full" h="full">
       <Flex direction="column" gap="2">
         {data?.map((model, i) => (
-          <Flex gap="3" w="full" alignItems="center" textAlign="center">
+          <Flex key={i} gap="3" w="full" alignItems="center" textAlign="center">
             <Text w="20%" whiteSpace="nowrap" overflow="hidden" text-overflow="ellipsis">
               {model.source.repo_id}
             </Text>
diff --git a/invokeai/frontend/web/src/services/api/endpoints/models.ts b/invokeai/frontend/web/src/services/api/endpoints/models.ts
index 71e539e82c..2552a7e839 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/models.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/models.ts
@@ -202,7 +202,7 @@ export const modelsApi = api.injectEndpoints({
           body: config,
         };
       },
-      invalidatesTags: ['Model'],
+      invalidatesTags: ['Model', 'ModelImports'],
     }),
     addMainModels: build.mutation<AddMainModelResponse, AddMainModelArg>({
       query: ({ body }) => {
@@ -308,6 +308,7 @@ export const modelsApi = api.injectEndpoints({
           url: buildModelsUrl(`import`),
         };
       },
+      providesTags: ['ModelImports']
     }),
     getCheckpointConfigs: build.query<CheckpointConfigsResponse, void>({
       query: () => {
diff --git a/invokeai/frontend/web/src/services/api/index.ts b/invokeai/frontend/web/src/services/api/index.ts
index 3b5a10492c..30cc7a9d3d 100644
--- a/invokeai/frontend/web/src/services/api/index.ts
+++ b/invokeai/frontend/web/src/services/api/index.ts
@@ -28,6 +28,7 @@ export const tagTypes = [
   'InvocationCacheStatus',
   'Model',
   'ModelConfig',
+  'ModelImports',
   'T2IAdapterModel',
   'MainModel',
   'VaeModel',
diff --git a/invokeai/frontend/web/src/services/events/actions.ts b/invokeai/frontend/web/src/services/events/actions.ts
index b80363315e..c306b3d2f6 100644
--- a/invokeai/frontend/web/src/services/events/actions.ts
+++ b/invokeai/frontend/web/src/services/events/actions.ts
@@ -11,6 +11,9 @@ import type {
   InvocationStartedEvent,
   ModelLoadCompletedEvent,
   ModelLoadStartedEvent,
+  ModelInstallDownloadingEvent,
+  ModelInstallCompletedEvent,
+  ModelInstallErrorEvent,
   QueueItemStatusChangedEvent,
   SessionRetrievalErrorEvent,
 } from 'services/events/types';
@@ -56,6 +59,18 @@ export const socketModelLoadCompleted = createAction<{
   data: ModelLoadCompletedEvent;
 }>('socket/socketModelLoadCompleted');
 
+export const socketModelInstallDownloading = createAction<{
+  data: ModelInstallDownloadingEvent;
+}>('socket/socketModelInstallDownloading');
+
+export const socketModelInstallCompleted = createAction<{
+  data: ModelInstallCompletedEvent;
+}>('socket/socketModelInstallCompleted');
+
+export const socketModelInstallError = createAction<{
+  data: ModelInstallErrorEvent;
+}>('socket/socketModelInstallError');
+
 export const socketSessionRetrievalError = createAction<{
   data: SessionRetrievalErrorEvent;
 }>('socket/socketSessionRetrievalError');
diff --git a/invokeai/frontend/web/src/services/events/types.ts b/invokeai/frontend/web/src/services/events/types.ts
index 4e68131ee9..2cf73a8e69 100644
--- a/invokeai/frontend/web/src/services/events/types.ts
+++ b/invokeai/frontend/web/src/services/events/types.ts
@@ -45,6 +45,27 @@ export type ModelLoadCompletedEvent = {
   precision: string;
 };
 
+export type ModelInstallDownloadingEvent = {
+  bytes: string;
+  local_path: string;
+  source: string;
+  timestamp: number;
+  total_bytes: string;
+};
+
+export type ModelInstallCompletedEvent = {
+  key: number;
+  source: string;
+  timestamp: number;
+};
+
+export type ModelInstallErrorEvent = {
+  error: string;
+  error_type: string;
+  source: string;
+  timestamp: number;
+};
+
 /**
  * A `generator_progress` socket.io event.
  *
@@ -237,6 +258,9 @@ export type ServerToClientEvents = {
   graph_execution_state_complete: (payload: GraphExecutionStateCompleteEvent) => void;
   model_load_started: (payload: ModelLoadStartedEvent) => void;
   model_load_completed: (payload: ModelLoadCompletedEvent) => void;
+  model_install_downloading: (payload: ModelInstallDownloadingEvent) => void;
+  model_install_completed: (payload: ModelInstallCompletedEvent) => void;
+  model_install_error: (payload: ModelInstallErrorEvent) => void;
   session_retrieval_error: (payload: SessionRetrievalErrorEvent) => void;
   invocation_retrieval_error: (payload: InvocationRetrievalErrorEvent) => void;
   queue_item_status_changed: (payload: QueueItemStatusChangedEvent) => void;
diff --git a/invokeai/frontend/web/src/services/events/util/setEventListeners.ts b/invokeai/frontend/web/src/services/events/util/setEventListeners.ts
index 1f27955ca7..314f9a985f 100644
--- a/invokeai/frontend/web/src/services/events/util/setEventListeners.ts
+++ b/invokeai/frontend/web/src/services/events/util/setEventListeners.ts
@@ -18,6 +18,9 @@ import {
   socketInvocationStarted,
   socketModelLoadCompleted,
   socketModelLoadStarted,
+  socketModelInstallDownloading,
+  socketModelInstallCompleted,
+  socketModelInstallError,
   socketQueueItemStatusChanged,
   socketSessionRetrievalError,
 } from 'services/events/actions';
@@ -134,6 +137,39 @@ export const setEventListeners = (arg: SetEventListenersArg) => {
     );
   });
 
+  /**
+   * Model Install Downloading
+   */
+  socket.on('model_install_downloading', (data) => {
+    dispatch(
+      socketModelInstallDownloading({
+        data,
+      })
+    );
+  })
+
+    /**
+   * Model Install Completed
+   */
+    socket.on('model_install_completed', (data) => {
+      dispatch(
+        socketModelInstallCompleted({
+          data,
+        })
+      );
+    })
+
+  /**
+   * Model Install Error
+   */
+    socket.on('model_install_error', (data) => {
+      dispatch(
+        socketModelInstallError({
+          data,
+        })
+      );
+    })
+
   /**
    * Session retrieval error
    */

From 86e2b39f0dba8635f6d124a18c0426b05bead8cc Mon Sep 17 00:00:00 2001
From: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Date: Wed, 21 Feb 2024 14:16:00 -0500
Subject: [PATCH 259/411] finish model update

---
 .../subpanels/ModelPanel/ModelEdit.tsx        | 249 +++++++++++-------
 .../subpanels/ModelPanel/ModelView.tsx        |  64 ++---
 2 files changed, 182 insertions(+), 131 deletions(-)

diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx
index 70d0596cd8..4528733c4f 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx
@@ -1,6 +1,6 @@
 import { skipToken } from '@reduxjs/toolkit/query';
 import { useAppDispatch, useAppSelector } from '../../../../app/store/storeHooks';
-import { useGetModelQuery } from '../../../../services/api/endpoints/models';
+import { useGetModelQuery, useUpdateModelsMutation } from '../../../../services/api/endpoints/models';
 import { Flex, Text, Heading, Button, Input, FormControl, FormLabel, Textarea } from '@invoke-ai/ui-library';
 import { useCallback, useMemo } from 'react';
 import {
@@ -16,19 +16,26 @@ import {
 } from '../../../../services/api/types';
 import { setSelectedModelMode } from '../../store/modelManagerV2Slice';
 import BaseModelSelect from './Fields/BaseModelSelect';
-import { useForm } from 'react-hook-form';
+import { SubmitHandler, useForm } from 'react-hook-form';
 import ModelTypeSelect from './Fields/ModelTypeSelect';
 import ModelVariantSelect from './Fields/ModelVariantSelect';
 import RepoVariantSelect from './Fields/RepoVariantSelect';
 import PredictionTypeSelect from './Fields/PredictionTypeSelect';
 import BooleanSelect from './Fields/BooleanSelect';
 import ModelFormatSelect from './Fields/ModelFormatSelect';
+import { useTranslation } from 'react-i18next';
+import { addToast } from '../../../system/store/systemSlice';
+import { makeToast } from '../../../system/util/makeToast';
 
 export const ModelEdit = () => {
   const dispatch = useAppDispatch();
   const selectedModelKey = useAppSelector((s) => s.modelmanagerV2.selectedModelKey);
   const { data, isLoading } = useGetModelQuery(selectedModelKey ?? skipToken);
 
+  const [updateModel, { isLoading: isSubmitting }] = useUpdateModelsMutation();
+
+  const { t } = useTranslation();
+
   const modelData = useMemo(() => {
     if (!data) {
       return null;
@@ -75,6 +82,46 @@ export const ModelEdit = () => {
     mode: 'onChange',
   });
 
+  const onSubmit = useCallback<SubmitHandler<AnyModelConfig>>(
+    (values) => {
+      if (!modelData?.key) {
+        return;
+      }
+
+      const responseBody = {
+        key: modelData.key,
+        body: values,
+      };
+
+      updateModel(responseBody)
+        .unwrap()
+        .then((payload) => {
+          reset(payload as AnyModelConfig, { keepDefaultValues: true });
+          dispatch(setSelectedModelMode('view'));
+          dispatch(
+            addToast(
+              makeToast({
+                title: t('modelManager.modelUpdated'),
+                status: 'success',
+              })
+            )
+          );
+        })
+        .catch((_) => {
+          reset();
+          dispatch(
+            addToast(
+              makeToast({
+                title: t('modelManager.modelUpdateFailed'),
+                status: 'error',
+              })
+            )
+          );
+        });
+    },
+    [dispatch, modelData?.key, reset, t, updateModel]
+  );
+
   const handleClickCancel = useCallback(() => {
     dispatch(setSelectedModelMode('view'));
   }, [dispatch]);
@@ -88,109 +135,111 @@ export const ModelEdit = () => {
   }
   return (
     <Flex flexDir="column" h="full">
-      <Flex w="full" justifyContent="space-between" gap={4} alignItems="center">
-        <Input
-          {...register('name', {
-            validate: (value) => value.trim().length > 3 || 'Must be at least 3 characters',
-          })}
-          size="lg"
-        />
-        <Flex gap={2}>
-          <Button size="sm" onClick={handleClickCancel}>
-            Cancel
-          </Button>
-          <Button size="sm" colorScheme="invokeYellow">
-            Save
-          </Button>
+      <form onSubmit={handleSubmit(onSubmit)}>
+        <Flex w="full" justifyContent="space-between" gap={4} alignItems="center">
+          <Input
+            {...register('name', {
+              validate: (value) => value.trim().length > 3 || 'Must be at least 3 characters',
+            })}
+            size="lg"
+          />
+          <Flex gap={2}>
+            <Button size="sm" onClick={handleClickCancel}>
+              Cancel
+            </Button>
+            <Button size="sm" colorScheme="invokeYellow" onClick={handleSubmit(onSubmit)}>
+              Save
+            </Button>
+          </Flex>
         </Flex>
-      </Flex>
 
-      <Flex flexDir="column" gap={3} mt="4">
-        <Flex>
-          <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-            <FormLabel>Description</FormLabel>
-            <Textarea fontSize="md" resize="none" {...register('description')} />
-          </FormControl>
-        </Flex>
-        <Heading as="h3" fontSize="md" mt="4">
-          Model Settings
-        </Heading>
-        <Flex gap={4}>
-          <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-            <FormLabel>Base Model</FormLabel>
-            <BaseModelSelect<AnyModelConfig> control={control} name="base" />
-          </FormControl>
-          <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-            <FormLabel>Model Type</FormLabel>
-            <ModelTypeSelect<AnyModelConfig> control={control} name="type" />
-          </FormControl>
-        </Flex>
-        <Flex gap={4}>
-          <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-            <FormLabel>Format</FormLabel>
-            <ModelFormatSelect<AnyModelConfig> control={control} name="format" />
-          </FormControl>
-          <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-            <FormLabel>Path</FormLabel>
-            <Input
-              {...register('path', {
-                validate: (value) => value.trim().length > 0 || 'Must provide a path',
-              })}
-            />
-          </FormControl>
-        </Flex>
-        {modelData.type === 'main' && (
-          <>
-            <Flex gap={4}>
-              {modelData.format === 'diffusers' && (
-                <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-                  <FormLabel>Repo Variant</FormLabel>
-                  <RepoVariantSelect<AnyModelConfig> control={control} name="repo_variant" />
-                </FormControl>
-              )}
-              {modelData.format === 'checkpoint' && (
-                <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-                  <FormLabel>Config Path</FormLabel>
-                  <Input {...register('config')} />
-                </FormControl>
-              )}
-
-              <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-                <FormLabel>Variant</FormLabel>
-                <ModelVariantSelect<AnyModelConfig> control={control} name="variant" />
-              </FormControl>
-            </Flex>
-            <Flex gap={4}>
-              <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-                <FormLabel>Prediction Type</FormLabel>
-                <PredictionTypeSelect<AnyModelConfig> control={control} name="prediction_type" />
-              </FormControl>
-              <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-                <FormLabel>Upcast Attention</FormLabel>
-                <BooleanSelect<AnyModelConfig> control={control} name="upcast_attention" />
-              </FormControl>
-            </Flex>
-            <Flex gap={4}>
-              <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-                <FormLabel>ZTSNR Training</FormLabel>
-                <BooleanSelect<AnyModelConfig> control={control} name="ztsnr_training" />
-              </FormControl>
-              <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-                <FormLabel>VAE Path</FormLabel>
-                <Input {...register('vae')} />
-              </FormControl>
-            </Flex>
-          </>
-        )}
-        {modelData.type === 'ip_adapter' && (
-          <Flex gap={4}>
+        <Flex flexDir="column" gap={3} mt="4">
+          <Flex>
             <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-              <FormLabel>Image Encoder Model ID</FormLabel>
-              <Input {...register('image_encoder_model_id')} />
+              <FormLabel>Description</FormLabel>
+              <Textarea fontSize="md" resize="none" {...register('description')} />
             </FormControl>
           </Flex>
-        )}
-      </Flex>
+          <Heading as="h3" fontSize="md" mt="4">
+            Model Settings
+          </Heading>
+          <Flex gap={4}>
+            <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+              <FormLabel>Base Model</FormLabel>
+              <BaseModelSelect<AnyModelConfig> control={control} name="base" />
+            </FormControl>
+            <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+              <FormLabel>Model Type</FormLabel>
+              <ModelTypeSelect<AnyModelConfig> control={control} name="type" />
+            </FormControl>
+          </Flex>
+          <Flex gap={4}>
+            <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+              <FormLabel>Format</FormLabel>
+              <ModelFormatSelect<AnyModelConfig> control={control} name="format" />
+            </FormControl>
+            <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+              <FormLabel>Path</FormLabel>
+              <Input
+                {...register('path', {
+                  validate: (value) => value.trim().length > 0 || 'Must provide a path',
+                })}
+              />
+            </FormControl>
+          </Flex>
+          {modelData.type === 'main' && (
+            <>
+              <Flex gap={4}>
+                {modelData.format === 'diffusers' && (
+                  <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+                    <FormLabel>Repo Variant</FormLabel>
+                    <RepoVariantSelect<AnyModelConfig> control={control} name="repo_variant" />
+                  </FormControl>
+                )}
+                {modelData.format === 'checkpoint' && (
+                  <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+                    <FormLabel>Config Path</FormLabel>
+                    <Input {...register('config')} />
+                  </FormControl>
+                )}
+
+                <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+                  <FormLabel>Variant</FormLabel>
+                  <ModelVariantSelect<AnyModelConfig> control={control} name="variant" />
+                </FormControl>
+              </Flex>
+              <Flex gap={4}>
+                <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+                  <FormLabel>Prediction Type</FormLabel>
+                  <PredictionTypeSelect<AnyModelConfig> control={control} name="prediction_type" />
+                </FormControl>
+                <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+                  <FormLabel>Upcast Attention</FormLabel>
+                  <BooleanSelect<AnyModelConfig> control={control} name="upcast_attention" />
+                </FormControl>
+              </Flex>
+              <Flex gap={4}>
+                <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+                  <FormLabel>ZTSNR Training</FormLabel>
+                  <BooleanSelect<AnyModelConfig> control={control} name="ztsnr_training" />
+                </FormControl>
+                <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+                  <FormLabel>VAE Path</FormLabel>
+                  <Input {...register('vae')} />
+                </FormControl>
+              </Flex>
+            </>
+          )}
+          {modelData.type === 'ip_adapter' && (
+            <Flex gap={4}>
+              <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+                <FormLabel>Image Encoder Model ID</FormLabel>
+                <Input {...register('image_encoder_model_id')} />
+              </FormControl>
+            </Flex>
+          )}
+        </Flex>
+      </form>
     </Flex>
   );
 };
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx
index a8f6ee1e3e..1fe8554352 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx
@@ -91,39 +91,41 @@ export const ModelView = () => {
           Model Settings
         </Heading>
         <Box layerStyle="second" borderRadius="base" p={3}>
-          <Flex gap={2}>
-            <ModelAttrView label="Base Model" value={modelData.base} />
-            <ModelAttrView label="Model Type" value={modelData.type} />
-          </Flex>
-          <Flex gap={2}>
-            <ModelAttrView label="Format" value={modelData.format} />
-            <ModelAttrView label="Path" value={modelData.path} />
-          </Flex>
-          {modelData.type === 'main' && (
-            <>
-              <Flex gap={2}>
-                {modelData.format === 'diffusers' && (
-                  <ModelAttrView label="Repo Variant" value={modelData.repo_variant} />
-                )}
-                {modelData.format === 'checkpoint' && <ModelAttrView label="Config Path" value={modelData.config} />}
-
-                <ModelAttrView label="Variant" value={modelData.variant} />
-              </Flex>
-              <Flex gap={2}>
-                <ModelAttrView label="Prediction Type" value={modelData.prediction_type} />
-                <ModelAttrView label="Upcast Attention" value={`${modelData.upcast_attention}`} />
-              </Flex>
-              <Flex gap={2}>
-                <ModelAttrView label="ZTSNR Training" value={`${modelData.ztsnr_training}`} />
-                <ModelAttrView label="VAE" value={modelData.vae} />
-              </Flex>
-            </>
-          )}
-          {modelData.type === 'ip_adapter' && (
+          <Flex flexDir="column" gap={3}>
             <Flex gap={2}>
-              <ModelAttrView label="Image Encoder Model ID" value={modelData.image_encoder_model_id} />
+              <ModelAttrView label="Base Model" value={modelData.base} />
+              <ModelAttrView label="Model Type" value={modelData.type} />
             </Flex>
-          )}
+            <Flex gap={2}>
+              <ModelAttrView label="Format" value={modelData.format} />
+              <ModelAttrView label="Path" value={modelData.path} />
+            </Flex>
+            {modelData.type === 'main' && (
+              <>
+                <Flex gap={2}>
+                  {modelData.format === 'diffusers' && (
+                    <ModelAttrView label="Repo Variant" value={modelData.repo_variant} />
+                  )}
+                  {modelData.format === 'checkpoint' && <ModelAttrView label="Config Path" value={modelData.config} />}
+
+                  <ModelAttrView label="Variant" value={modelData.variant} />
+                </Flex>
+                <Flex gap={2}>
+                  <ModelAttrView label="Prediction Type" value={modelData.prediction_type} />
+                  <ModelAttrView label="Upcast Attention" value={`${modelData.upcast_attention}`} />
+                </Flex>
+                <Flex gap={2}>
+                  <ModelAttrView label="ZTSNR Training" value={`${modelData.ztsnr_training}`} />
+                  <ModelAttrView label="VAE" value={modelData.vae} />
+                </Flex>
+              </>
+            )}
+            {modelData.type === 'ip_adapter' && (
+              <Flex gap={2}>
+                <ModelAttrView label="Image Encoder Model ID" value={modelData.image_encoder_model_id} />
+              </Flex>
+            )}
+          </Flex>
         </Box>
       </Flex>
 

From 782d15af13eaeac3b1316df43338efcc3fb6b3ea Mon Sep 17 00:00:00 2001
From: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Date: Wed, 21 Feb 2024 14:33:45 -0500
Subject: [PATCH 260/411] form error handling

---
 .../subpanels/ModelPanel/ModelEdit.tsx        | 68 +++++++++++++------
 1 file changed, 47 insertions(+), 21 deletions(-)

diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx
index 4528733c4f..1d14fe9e11 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx
@@ -1,7 +1,17 @@
 import { skipToken } from '@reduxjs/toolkit/query';
 import { useAppDispatch, useAppSelector } from '../../../../app/store/storeHooks';
 import { useGetModelQuery, useUpdateModelsMutation } from '../../../../services/api/endpoints/models';
-import { Flex, Text, Heading, Button, Input, FormControl, FormLabel, Textarea } from '@invoke-ai/ui-library';
+import {
+  Flex,
+  Text,
+  Heading,
+  Button,
+  Input,
+  FormControl,
+  FormLabel,
+  Textarea,
+  FormErrorMessage,
+} from '@invoke-ai/ui-library';
 import { useCallback, useMemo } from 'react';
 import {
   AnyModelConfig,
@@ -75,6 +85,7 @@ export const ModelEdit = () => {
     control,
     formState: { errors },
     reset,
+    watch,
   } = useForm<AnyModelConfig>({
     defaultValues: {
       ...modelData,
@@ -82,6 +93,9 @@ export const ModelEdit = () => {
     mode: 'onChange',
   });
 
+  const watchedModelType = watch('type');
+  const watchedModelFormat = watch('format');
+
   const onSubmit = useCallback<SubmitHandler<AnyModelConfig>>(
     (values) => {
       if (!modelData?.key) {
@@ -136,22 +150,33 @@ export const ModelEdit = () => {
   return (
     <Flex flexDir="column" h="full">
       <form onSubmit={handleSubmit(onSubmit)}>
-        <Flex w="full" justifyContent="space-between" gap={4} alignItems="center">
-          <Input
-            {...register('name', {
-              validate: (value) => value.trim().length > 3 || 'Must be at least 3 characters',
-            })}
-            size="lg"
-          />
-          <Flex gap={2}>
-            <Button size="sm" onClick={handleClickCancel}>
-              Cancel
-            </Button>
-            <Button size="sm" colorScheme="invokeYellow" onClick={handleSubmit(onSubmit)}>
-              Save
-            </Button>
+        <FormControl flexDir="column" alignItems="flex-start" gap={1} isInvalid={Boolean(errors.name)}>
+          <Flex w="full" justifyContent="space-between" gap={4} alignItems="center">
+            <FormLabel hidden={true}>Model Name</FormLabel>
+            <Input
+              {...register('name', {
+                validate: (value) => value.trim().length > 3 || 'Must be at least 3 characters',
+              })}
+              size="lg"
+            />
+
+            <Flex gap={2}>
+              <Button size="sm" onClick={handleClickCancel}>
+                Cancel
+              </Button>
+              <Button
+                size="sm"
+                colorScheme="invokeYellow"
+                onClick={handleSubmit(onSubmit)}
+                isLoading={isSubmitting}
+                isDisabled={Boolean(errors)}
+              >
+                Save
+              </Button>
+            </Flex>
           </Flex>
-        </Flex>
+          {errors.name?.message && <FormErrorMessage>{errors.name?.message}</FormErrorMessage>}
+        </FormControl>
 
         <Flex flexDir="column" gap={3} mt="4">
           <Flex>
@@ -178,25 +203,26 @@ export const ModelEdit = () => {
               <FormLabel>Format</FormLabel>
               <ModelFormatSelect<AnyModelConfig> control={control} name="format" />
             </FormControl>
-            <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+            <FormControl flexDir="column" alignItems="flex-start" gap={1} isInvalid={Boolean(errors.path)}>
               <FormLabel>Path</FormLabel>
               <Input
                 {...register('path', {
                   validate: (value) => value.trim().length > 0 || 'Must provide a path',
                 })}
               />
+              {errors.path?.message && <FormErrorMessage>{errors.path?.message}</FormErrorMessage>}
             </FormControl>
           </Flex>
-          {modelData.type === 'main' && (
+          {watchedModelType === 'main' && (
             <>
               <Flex gap={4}>
-                {modelData.format === 'diffusers' && (
+                {watchedModelFormat === 'diffusers' && (
                   <FormControl flexDir="column" alignItems="flex-start" gap={1}>
                     <FormLabel>Repo Variant</FormLabel>
                     <RepoVariantSelect<AnyModelConfig> control={control} name="repo_variant" />
                   </FormControl>
                 )}
-                {modelData.format === 'checkpoint' && (
+                {watchedModelFormat === 'checkpoint' && (
                   <FormControl flexDir="column" alignItems="flex-start" gap={1}>
                     <FormLabel>Config Path</FormLabel>
                     <Input {...register('config')} />
@@ -230,7 +256,7 @@ export const ModelEdit = () => {
               </Flex>
             </>
           )}
-          {modelData.type === 'ip_adapter' && (
+          {watchedModelType === 'ip_adapter' && (
             <Flex gap={4}>
               <FormControl flexDir="column" alignItems="flex-start" gap={1}>
                 <FormLabel>Image Encoder Model ID</FormLabel>

From 18904f79efda168e3a4fe0b84c1ccb7e0ca3f684 Mon Sep 17 00:00:00 2001
From: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Date: Wed, 21 Feb 2024 14:45:30 -0500
Subject: [PATCH 261/411] fix sync model endpoint

---
 invokeai/frontend/web/src/services/api/endpoints/models.ts | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/invokeai/frontend/web/src/services/api/endpoints/models.ts b/invokeai/frontend/web/src/services/api/endpoints/models.ts
index 2552a7e839..48ee2a7f08 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/models.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/models.ts
@@ -74,7 +74,7 @@ type AddMainModelArg = {
 
 type AddMainModelResponse = paths['/api/v2/models/add']['post']['responses']['201']['content']['application/json'];
 
-type SyncModelsResponse = paths['/api/v2/models/sync']['post']['responses']['201']['content']['application/json'];
+type SyncModelsResponse = paths['/api/v2/models/sync']['patch']['responses']['204']['content']['application/json'];
 
 export type SearchFolderResponse =
   paths['/api/v2/models/search']['get']['responses']['200']['content']['application/json'];
@@ -259,7 +259,7 @@ export const modelsApi = api.injectEndpoints({
       query: () => {
         return {
           url: buildModelsUrl('sync'),
-          method: 'POST',
+          method: 'PATCH',
         };
       },
       invalidatesTags: ['Model'],

From ea364bdf822d67e77ef08414445b9d50f41bcb3e Mon Sep 17 00:00:00 2001
From: Jennifer Player <chainchompa@gmail.com>
Date: Wed, 21 Feb 2024 17:17:34 -0500
Subject: [PATCH 262/411] delete model imports and prune all finished, update
 state with socket messages

---
 invokeai/app/services/events/events_base.py   |   7 +-
 .../model_install/model_install_default.py    |   5 +-
 invokeai/frontend/web/public/locales/en.json  |   5 +
 .../middleware/listenerMiddleware/index.ts    |   2 +-
 .../listeners/socketio/socketModelInstall.ts  |  66 ++++-----
 .../modelManagerV2/subpanels/ImportModels.tsx |  12 +-
 .../modelManagerV2/subpanels/ImportQueue.tsx  | 127 ++++++++----------
 .../subpanels/ImportQueueModel.tsx            |  82 +++++++++++
 .../web/src/services/api/endpoints/models.ts  |  36 ++++-
 .../web/src/services/events/actions.ts        |   6 +-
 .../frontend/web/src/services/events/types.ts |   3 +
 .../services/events/util/setEventListeners.ts |   6 +-
 12 files changed, 232 insertions(+), 125 deletions(-)
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportQueueModel.tsx

diff --git a/invokeai/app/services/events/events_base.py b/invokeai/app/services/events/events_base.py
index 53df14330f..b3ee70b359 100644
--- a/invokeai/app/services/events/events_base.py
+++ b/invokeai/app/services/events/events_base.py
@@ -357,6 +357,7 @@ class EventServiceBase:
         bytes: int,
         total_bytes: int,
         parts: List[Dict[str, Union[str, int]]],
+        id: int
     ) -> None:
         """
         Emit at intervals while the install job is in progress (remote models only).
@@ -376,6 +377,7 @@ class EventServiceBase:
                 "bytes": bytes,
                 "total_bytes": total_bytes,
                 "parts": parts,
+                "id": id
             },
         )
 
@@ -390,7 +392,7 @@ class EventServiceBase:
             payload={"source": source},
         )
 
-    def emit_model_install_completed(self, source: str, key: str, total_bytes: Optional[int] = None) -> None:
+    def emit_model_install_completed(self, source: str, key: str, id: int, total_bytes: Optional[int] = None) -> None:
         """
         Emit when an install job is completed successfully.
 
@@ -404,6 +406,7 @@ class EventServiceBase:
                 "source": source,
                 "total_bytes": total_bytes,
                 "key": key,
+                "id": id
             },
         )
 
@@ -423,6 +426,7 @@ class EventServiceBase:
         source: str,
         error_type: str,
         error: str,
+        id: int
     ) -> None:
         """
         Emit when an install job encounters an exception.
@@ -437,6 +441,7 @@ class EventServiceBase:
                 "source": source,
                 "error_type": error_type,
                 "error": error,
+                "id": id
             },
         )
 
diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py
index 2419fbe5da..ec330913c2 100644
--- a/invokeai/app/services/model_install/model_install_default.py
+++ b/invokeai/app/services/model_install/model_install_default.py
@@ -822,6 +822,7 @@ class ModelInstallService(ModelInstallServiceBase):
                 parts=parts,
                 bytes=job.bytes,
                 total_bytes=job.total_bytes,
+                id=job.id
             )
 
     def _signal_job_completed(self, job: ModelInstallJob) -> None:
@@ -834,7 +835,7 @@ class ModelInstallService(ModelInstallServiceBase):
             assert job.local_path is not None
             assert job.config_out is not None
             key = job.config_out.key
-            self._event_bus.emit_model_install_completed(str(job.source), key)
+            self._event_bus.emit_model_install_completed(str(job.source), key, id=job.id)
 
     def _signal_job_errored(self, job: ModelInstallJob) -> None:
         self._logger.info(f"{job.source}: model installation encountered an exception: {job.error_type}\n{job.error}")
@@ -843,7 +844,7 @@ class ModelInstallService(ModelInstallServiceBase):
             error = job.error
             assert error_type is not None
             assert error is not None
-            self._event_bus.emit_model_install_error(str(job.source), error_type, error)
+            self._event_bus.emit_model_install_error(str(job.source), error_type, error, id=job.id)
 
     def _signal_job_cancelled(self, job: ModelInstallJob) -> None:
         self._logger.info(f"{job.source}: model installation was cancelled")
diff --git a/invokeai/frontend/web/public/locales/en.json b/invokeai/frontend/web/public/locales/en.json
index 406df71e06..4d40f7105c 100644
--- a/invokeai/frontend/web/public/locales/en.json
+++ b/invokeai/frontend/web/public/locales/en.json
@@ -797,6 +797,8 @@
         "pathToCustomConfig": "Path To Custom Config",
         "pickModelType": "Pick Model Type",
         "predictionType": "Prediction Type (for Stable Diffusion 2.x Models and occasional Stable Diffusion 1.x Models)",
+        "prune": "Prune",
+        "pruneTooltip": "Prune finished imports from queue",
         "quickAdd": "Quick Add",
         "removeFromQueue": "Remove From Queue",
         "repo_id": "Repo ID",
@@ -1354,6 +1356,8 @@
         "modelAdded": "Model Added: {{modelName}}",
         "modelAddedSimple": "Model Added",
         "modelAddFailed": "Model Add Failed",
+        "modelImportCanceled": "Model Import Canceled",
+        "modelImportRemoved": "Model Import Removed",
         "nodesBrokenConnections": "Cannot load. Some connections are broken.",
         "nodesCorruptedGraph": "Cannot load. Graph seems to be corrupted.",
         "nodesLoaded": "Nodes Loaded",
@@ -1387,6 +1391,7 @@
         "promptNotSet": "Prompt Not Set",
         "promptNotSetDesc": "Could not find prompt for this image.",
         "promptSet": "Prompt Set",
+        "prunedQueue": "Pruned Queue",
         "resetInitialImage": "Reset Initial Image",
         "seedNotSet": "Seed Not Set",
         "seedNotSetDesc": "Could not find seed for this image.",
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts
index 26d7949e9c..6c5abf41a5 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts
@@ -57,8 +57,8 @@ import { addInvocationCompleteEventListener as addInvocationCompleteListener } f
 import { addInvocationErrorEventListener as addInvocationErrorListener } from './listeners/socketio/socketInvocationError';
 import { addInvocationRetrievalErrorEventListener } from './listeners/socketio/socketInvocationRetrievalError';
 import { addInvocationStartedEventListener as addInvocationStartedListener } from './listeners/socketio/socketInvocationStarted';
-import { addModelLoadEventListener } from './listeners/socketio/socketModelLoad';
 import { addModelInstallEventListener } from './listeners/socketio/socketModelInstall';
+import { addModelLoadEventListener } from './listeners/socketio/socketModelLoad';
 import { addSocketQueueItemStatusChangedEventListener } from './listeners/socketio/socketQueueItemStatusChanged';
 import { addSessionRetrievalErrorEventListener } from './listeners/socketio/socketSessionRetrievalError';
 import { addSocketSubscribedEventListener as addSocketSubscribedListener } from './listeners/socketio/socketSubscribed';
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts
index b241df27c8..a4cf8127cb 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts
@@ -1,63 +1,65 @@
-import { logger } from 'app/logging/logger';
+import { modelsApi } from 'services/api/endpoints/models';
 import {
   socketModelInstallCompleted,
   socketModelInstallDownloading,
   socketModelInstallError,
 } from 'services/events/actions';
-import { modelsApi } from 'services/api/endpoints/models';
-import type { components, paths } from 'services/api/schema';
-
 
 import { startAppListening } from '../..';
-import { createEntityAdapter } from '@reduxjs/toolkit';
-
-const log = logger('socketio');
 
 export const addModelInstallEventListener = () => {
   startAppListening({
     actionCreator: socketModelInstallDownloading,
     effect: async (action, { dispatch }) => {
-      const { bytes, local_path, source, timestamp, total_bytes } = action.payload.data;
-      let message = `Model install started: ${bytes}/${total_bytes}/${source}`;
-    // below doesnt work, still not sure how to update the importModels data 
-    //   dispatch(
-    //       modelsApi.util.updateQueryData('getModelImports', undefined, (draft) => {
-    //         importModelsAdapter.updateOne(draft, {
-    //             id: source,
-    //             changes: {
-    //                 bytes,
-    //                 total_bytes,
-    //             },\q
-    //             });
-    //         }
-    //         )
-    //   );
+      const { bytes, id } = action.payload.data;
 
-      log.debug(action.payload, message);
+      dispatch(
+        modelsApi.util.updateQueryData('getModelImports', undefined, (draft) => {
+          const models = JSON.parse(JSON.stringify(draft))
+
+          const modelIndex = models.findIndex((m) => m.id === id);
+
+          models[modelIndex].bytes = bytes;
+          models[modelIndex].status = 'downloading';
+          return models;
+        })
+      );
     },
   });
 
   startAppListening({
     actionCreator: socketModelInstallCompleted,
-    effect: (action) => {
-      const { key, source, timestamp } = action.payload.data;
+    effect: (action, { dispatch }) => {
+      const { id } = action.payload.data;
 
-      let message = `Model install completed: ${source}`;
+      dispatch(
+        modelsApi.util.updateQueryData('getModelImports', undefined, (draft) => {
+          const models = JSON.parse(JSON.stringify(draft))
 
-    //   dispatch something that marks the model installation as completed
+          const modelIndex = models.findIndex((m) => m.id === id);
 
-      log.debug(action.payload, message);
+          models[modelIndex].status = 'completed';
+          return models;
+        })
+      );
     },
   });
 
   startAppListening({
     actionCreator: socketModelInstallError,
-    effect: (action) => {
-      const { error, error_type, source } = action.payload.data;
+    effect: (action, { dispatch }) => {
+      const { id } = action.payload.data;
 
-    //   dispatch something that marks the model installation as errored
+      dispatch(
+        modelsApi.util.updateQueryData('getModelImports', undefined, (draft) => {
+          const models = JSON.parse(JSON.stringify(draft))
 
-      log.debug(action.payload, error);
+          const modelIndex = models.findIndex((m) => m.id === id);
+
+          models[modelIndex].status = 'error';
+          return models;
+        })
+      );
     },
   });
 };
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx
index 14ed0c6848..e2cdf24c2f 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx
@@ -1,11 +1,12 @@
-import { Button, Box, Flex, FormControl, FormLabel, Heading, Input, Text, Divider } from '@invoke-ai/ui-library';
-import { t } from 'i18next';
-import { CSSProperties } from 'react';
-import { useImportMainModelsMutation } from '../../../services/api/endpoints/models';
+import { Box, Button, Divider,Flex, FormControl, FormLabel, Heading, Input } from '@invoke-ai/ui-library';
 import { useForm } from '@mantine/form';
 import { useAppDispatch } from 'app/store/storeHooks';
 import { addToast } from 'features/system/store/systemSlice';
 import { makeToast } from 'features/system/util/makeToast';
+import { t } from 'i18next';
+import type { CSSProperties } from 'react';
+import { useImportMainModelsMutation } from 'services/api/endpoints/models';
+
 import { ImportQueue } from './ImportQueue';
 
 const formStyles: CSSProperties = {
@@ -27,8 +28,6 @@ export const ImportModels = () => {
     },
   });
 
-  console.log('addModelForm', addModelForm.values.location)
-
   const handleAddModelSubmit = (values: ExtendedImportModelConfig) => {
     importMainModel({ source: values.location, config: undefined })
       .unwrap()
@@ -77,7 +76,6 @@ export const ImportModels = () => {
           </Flex>
         </form>
         <Divider mt="5" mb="3" />
-        <Text>{t('modelManager.importQueue')}</Text>
         <ImportQueue />
       </Box>
     </Box>
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportQueue.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportQueue.tsx
index c2dbece4b3..53c037e74f 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportQueue.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportQueue.tsx
@@ -1,85 +1,72 @@
-import {
-  Button,
-  Box,
-  Flex,
-  FormControl,
-  FormLabel,
-  Heading,
-  IconButton,
-  Input,
-  InputGroup,
-  InputRightElement,
-  Progress,
-  Text,
-} from '@invoke-ai/ui-library';
-import { t } from 'i18next';
-import { useMemo } from 'react';
-import { useGetModelImportsQuery } from '../../../services/api/endpoints/models';
+import { Box, Button,Flex, Text } from '@invoke-ai/ui-library';
 import { useAppDispatch } from 'app/store/storeHooks';
 import { addToast } from 'features/system/store/systemSlice';
 import { makeToast } from 'features/system/util/makeToast';
-import { PiXBold } from 'react-icons/pi';
+import { t } from 'i18next';
+import { useCallback, useMemo } from 'react';
+import { RiSparklingFill } from 'react-icons/ri';
+import { useGetModelImportsQuery, usePruneModelImportsMutation } from 'services/api/endpoints/models';
+
+import { ImportQueueModel } from './ImportQueueModel';
 
 export const ImportQueue = () => {
   const dispatch = useAppDispatch();
 
-  // start with this data then pull from sockets (idk how to do that yet, also might not even use this and just use socket)
   const { data } = useGetModelImportsQuery();
 
-  const progressValues = useMemo(() => {
-    if (!data) {
-      return [];
-    }
-    const values = [];
-    for (let i = 0; i < data.length; i++) {
-      let value;
-      if (data[i] && data[i]?.bytes && data[i]?.total_bytes) {
-        value = (data[i]?.bytes / data[i]?.total_bytes) * 100;
-      }
-      values.push(value || undefined);
-    }
-    return values;
+  const [pruneModelImports] = usePruneModelImportsMutation();
+
+  const pruneQueue = useCallback(() => {
+    pruneModelImports()
+      .unwrap()
+      .then((_) => {
+        dispatch(
+          addToast(
+            makeToast({
+              title: t('toast.prunedQueue'),
+              status: 'success',
+            })
+          )
+        );
+      })
+      .catch((error) => {
+        if (error) {
+          dispatch(
+            addToast(
+              makeToast({
+                title: `${error.data.detail} `,
+                status: 'error',
+              })
+            )
+          );
+        }
+      });
+  }, [pruneModelImports, dispatch]);
+
+  const pruneAvailable = useMemo(() => {
+    return data?.some(
+      (model) => model.status === 'cancelled' || model.status === 'error' || model.status === 'completed'
+    );
   }, [data]);
 
   return (
-    <Box mt={3} layerStyle="first" p={3} borderRadius="base" w="full" h="full">
-      <Flex direction="column" gap="2">
-        {data?.map((model, i) => (
-          <Flex key={i} gap="3" w="full" alignItems="center" textAlign="center">
-            <Text w="20%" whiteSpace="nowrap" overflow="hidden" text-overflow="ellipsis">
-              {model.source.repo_id}
-            </Text>
-            <Progress
-              value={progressValues[i]}
-              isIndeterminate={progressValues[i] === undefined}
-              aria-label={t('accessibility.invokeProgressBar')}
-              h={2}
-              w="50%"
-            />
-            <Text w="20%">{model.status}</Text>
-            {model.status === 'completed' ? (
-              <IconButton
-                isRound={true}
-                size="xs"
-                tooltip={t('modelManager.removeFromQueue')}
-                aria-label={t('modelManager.removeFromQueue')}
-                icon={<PiXBold />}
-                //   onClick={handleRemove}
-              />
-            ) : (
-              <IconButton
-                isRound={true}
-                size="xs"
-                tooltip={t('modelManager.cancel')}
-                aria-label={t('modelManager.cancel')}
-                icon={<PiXBold />}
-                //   onClick={handleCancel}
-                colorScheme="error"
-              />
-            )}
-          </Flex>
-        ))}
+    <>
+      <Flex justifyContent="space-between">
+        <Text>{t('modelManager.importQueue')}</Text>
+        <Button
+          isDisabled={!pruneAvailable}
+          onClick={pruneQueue}
+          tooltip={t('modelManager.pruneTooltip')}
+          rightIcon={<RiSparklingFill />}
+        >
+          {t('modelManager.prune')}
+        </Button>
       </Flex>
-    </Box>
+      <Box mt={3} layerStyle="first" p={3} borderRadius="base" w="full" h="full">
+        <Flex direction="column" gap="2">
+          {data?.map((model) => <ImportQueueModel key={model.id} model={model} />)}
+        </Flex>
+      </Box>
+    </>
   );
 };
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportQueueModel.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportQueueModel.tsx
new file mode 100644
index 0000000000..8704e847c6
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportQueueModel.tsx
@@ -0,0 +1,82 @@
+import {
+  Flex,
+  IconButton,
+  Progress,
+  Text,
+} from '@invoke-ai/ui-library';
+import { useAppDispatch } from 'app/store/storeHooks';
+import { addToast } from 'features/system/store/systemSlice';
+import { makeToast } from 'features/system/util/makeToast';
+import { t } from 'i18next';
+import { useCallback, useMemo } from 'react';
+import { PiXBold } from 'react-icons/pi';
+import { useDeleteModelImportMutation } from 'services/api/endpoints/models';
+import type { ImportModelConfig } from 'services/api/types';
+
+type ModelListItemProps = {
+  model: ImportModelConfig;
+};
+
+export const ImportQueueModel = (props: ModelListItemProps) => {
+  const { model } = props;
+  const dispatch = useAppDispatch();
+
+  const [deleteImportModel] = useDeleteModelImportMutation();
+
+  const handleDeleteModelImport = useCallback(() => {
+    deleteImportModel({ key: model.id })
+      .unwrap()
+      .then((_) => {
+        dispatch(
+          addToast(
+            makeToast({
+              title: t('toast.modelImportCanceled'),
+              status: 'success',
+            })
+          )
+        );
+      })
+      .catch((error) => {
+        if (error) {
+          dispatch(
+            addToast(
+              makeToast({
+                title: `${error.data.detail} `,
+                status: 'error',
+              })
+            )
+          );
+        }
+      });
+  }, [deleteImportModel, model, dispatch]);
+
+  const progressValue = useMemo(() => {
+    return (model.bytes / model.total_bytes) * 100;
+  }, [model.bytes, model.total_bytes]);
+
+  return (
+    <Flex gap="3" w="full" alignItems="center" textAlign="center">
+      <Text w="20%" whiteSpace="nowrap" overflow="hidden" textOverflow="ellipsis">
+        {model.source.repo_id}
+      </Text>
+      <Progress
+        value={progressValue}
+        isIndeterminate={progressValue === undefined}
+        aria-label={t('accessibility.invokeProgressBar')}
+        h={2}
+        w="50%"
+      />
+      <Text w="20%">{model.status}</Text>
+      {(model.status === 'downloading' || model.status === 'waiting') && (
+        <IconButton
+          isRound={true}
+          size="xs"
+          tooltip={t('modelManager.cancel')}
+          aria-label={t('modelManager.cancel')}
+          icon={<PiXBold />}
+          onClick={handleDeleteModelImport}
+        />
+      )}
+    </Flex>
+  );
+};
diff --git a/invokeai/frontend/web/src/services/api/endpoints/models.ts b/invokeai/frontend/web/src/services/api/endpoints/models.ts
index 48ee2a7f08..3e1abc8560 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/models.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/models.ts
@@ -26,11 +26,9 @@ type UpdateModelArg = {
 
 type UpdateModelResponse = paths['/api/v2/models/i/{key}']['patch']['responses']['200']['content']['application/json'];
 
-
-type GetModelResponse =
-  paths['/api/v2/models/i/{key}']['get']['responses']['200']['content']['application/json'];
 type GetModelMetadataResponse =
   paths['/api/v2/models/meta/i/{key}']['get']['responses']['200']['content']['application/json'];
+type GetModelResponse = paths['/api/v2/models/i/{key}']['get']['responses']['200']['content']['application/json'];
 
 type ListModelsArg = NonNullable<paths['/api/v2/models/']['get']['parameters']['query']>;
 
@@ -68,13 +66,19 @@ type ImportMainModelResponse =
 type ListImportModelsResponse =
   paths['/api/v2/models/import']['get']['responses']['200']['content']['application/json'];
 
+type DeleteImportModelsResponse =
+  paths['/api/v2/models/import/{id}']['delete']['responses']['201']['content']['application/json'];
+
+type PruneModelImportsResponse =
+  paths['/api/v2/models/import']['patch']['responses']['200']['content']['application/json'];
+
 type AddMainModelArg = {
   body: MainModelConfig;
 };
 
 type AddMainModelResponse = paths['/api/v2/models/add']['post']['responses']['201']['content']['application/json'];
 
-type SyncModelsResponse = paths['/api/v2/models/sync']['patch']['responses']['204']['content']['application/json'];
+type SyncModelsResponse = paths['/api/v2/models/sync']['patch']['responses']['204']['content']
 
 export type SearchFolderResponse =
   paths['/api/v2/models/search']['get']['responses']['200']['content']['application/json'];
@@ -308,7 +312,25 @@ export const modelsApi = api.injectEndpoints({
           url: buildModelsUrl(`import`),
         };
       },
-      providesTags: ['ModelImports']
+      providesTags: ['ModelImports'],
+    }),
+    deleteModelImport: build.mutation<DeleteImportModelsResponse, DeleteMainModelArg>({
+      query: ({ key }) => {
+        return {
+          url: buildModelsUrl(`import/${key}`),
+          method: 'DELETE',
+        };
+      },
+      invalidatesTags: ['ModelImports'],
+    }),
+    pruneModelImports: build.mutation<PruneModelImportsResponse, void>({
+      query: () => {
+        return {
+          url: buildModelsUrl('import'),
+          method: 'PATCH',
+        };
+      },
+      invalidatesTags: ['ModelImports'],
     }),
     getCheckpointConfigs: build.query<CheckpointConfigsResponse, void>({
       query: () => {
@@ -339,6 +361,8 @@ export const {
   useGetModelsInFolderQuery,
   useGetCheckpointConfigsQuery,
   useGetModelImportsQuery,
+  useGetModelMetadataQuery,
+  useDeleteModelImportMutation,
+  usePruneModelImportsMutation,
   useGetModelQuery,
-  useGetModelMetadataQuery
 } = modelsApi;
diff --git a/invokeai/frontend/web/src/services/events/actions.ts b/invokeai/frontend/web/src/services/events/actions.ts
index c306b3d2f6..31f9e4d11d 100644
--- a/invokeai/frontend/web/src/services/events/actions.ts
+++ b/invokeai/frontend/web/src/services/events/actions.ts
@@ -9,11 +9,11 @@ import type {
   InvocationErrorEvent,
   InvocationRetrievalErrorEvent,
   InvocationStartedEvent,
+  ModelInstallCompletedEvent,
+  ModelInstallDownloadingEvent,
+  ModelInstallErrorEvent,
   ModelLoadCompletedEvent,
   ModelLoadStartedEvent,
-  ModelInstallDownloadingEvent,
-  ModelInstallCompletedEvent,
-  ModelInstallErrorEvent,
   QueueItemStatusChangedEvent,
   SessionRetrievalErrorEvent,
 } from 'services/events/types';
diff --git a/invokeai/frontend/web/src/services/events/types.ts b/invokeai/frontend/web/src/services/events/types.ts
index 2cf73a8e69..e0c50f4def 100644
--- a/invokeai/frontend/web/src/services/events/types.ts
+++ b/invokeai/frontend/web/src/services/events/types.ts
@@ -51,12 +51,14 @@ export type ModelInstallDownloadingEvent = {
   source: string;
   timestamp: number;
   total_bytes: string;
+  id: number;
 };
 
 export type ModelInstallCompletedEvent = {
   key: number;
   source: string;
   timestamp: number;
+  id: number;
 };
 
 export type ModelInstallErrorEvent = {
@@ -64,6 +66,7 @@ export type ModelInstallErrorEvent = {
   error_type: string;
   source: string;
   timestamp: number;
+  id: number;
 };
 
 /**
diff --git a/invokeai/frontend/web/src/services/events/util/setEventListeners.ts b/invokeai/frontend/web/src/services/events/util/setEventListeners.ts
index 314f9a985f..38f917e394 100644
--- a/invokeai/frontend/web/src/services/events/util/setEventListeners.ts
+++ b/invokeai/frontend/web/src/services/events/util/setEventListeners.ts
@@ -16,11 +16,11 @@ import {
   socketInvocationError,
   socketInvocationRetrievalError,
   socketInvocationStarted,
+  socketModelInstallCompleted,
+  socketModelInstallDownloading,
+  socketModelInstallError,
   socketModelLoadCompleted,
   socketModelLoadStarted,
-  socketModelInstallDownloading,
-  socketModelInstallCompleted,
-  socketModelInstallError,
   socketQueueItemStatusChanged,
   socketSessionRetrievalError,
 } from 'services/events/actions';

From 68f24d9f0d994539b1da38a77148236e0d02f876 Mon Sep 17 00:00:00 2001
From: Jennifer Player <chainchompa@gmail.com>
Date: Wed, 21 Feb 2024 18:11:38 -0500
Subject: [PATCH 263/411] added status to import queue model

---
 .../subpanels/ImportQueueModel.tsx            | 56 +++++++++++++------
 1 file changed, 38 insertions(+), 18 deletions(-)

diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportQueueModel.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportQueueModel.tsx
index 8704e847c6..6ae986b833 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportQueueModel.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportQueueModel.tsx
@@ -1,9 +1,4 @@
-import {
-  Flex,
-  IconButton,
-  Progress,
-  Text,
-} from '@invoke-ai/ui-library';
+import { Box, Flex, IconButton, Progress, Text } from '@invoke-ai/ui-library';
 import { useAppDispatch } from 'app/store/storeHooks';
 import { addToast } from 'features/system/store/systemSlice';
 import { makeToast } from 'features/system/util/makeToast';
@@ -50,12 +45,31 @@ export const ImportQueueModel = (props: ModelListItemProps) => {
       });
   }, [deleteImportModel, model, dispatch]);
 
+  const formatBytes = (bytes: number) => {
+    const units = ['b', 'kb', 'mb', 'gb', 'tb'];
+
+    let i = 0;
+
+    for (i; bytes >= 1024 && i < 4; i++) {
+      bytes /= 1024;
+    }
+
+    return `${bytes.toFixed(2)} ${units[i]}`;
+  };
+
   const progressValue = useMemo(() => {
     return (model.bytes / model.total_bytes) * 100;
   }, [model.bytes, model.total_bytes]);
 
+  const progressString = useMemo(() => {
+    if (model.status !== 'downloading') {
+      return '--';
+    }
+    return `${formatBytes(model.bytes)} / ${formatBytes(model.total_bytes)}`;
+  }, [model.bytes, model.total_bytes, model.status]);
+
   return (
-    <Flex gap="3" w="full" alignItems="center" textAlign="center">
+    <Flex gap="2" w="full" alignItems="center" textAlign="center">
       <Text w="20%" whiteSpace="nowrap" overflow="hidden" textOverflow="ellipsis">
         {model.source.repo_id}
       </Text>
@@ -66,17 +80,23 @@ export const ImportQueueModel = (props: ModelListItemProps) => {
         h={2}
         w="50%"
       />
-      <Text w="20%">{model.status}</Text>
-      {(model.status === 'downloading' || model.status === 'waiting') && (
-        <IconButton
-          isRound={true}
-          size="xs"
-          tooltip={t('modelManager.cancel')}
-          aria-label={t('modelManager.cancel')}
-          icon={<PiXBold />}
-          onClick={handleDeleteModelImport}
-        />
-      )}
+      <Text minW="20%" fontSize="xs" w="20%">
+        {progressString}
+      </Text>
+      <Text w="15%">{model.status[0].toUpperCase() +
+        model.status.slice(1)}</Text>
+      <Box w="10%">
+        {(model.status === 'downloading' || model.status === 'waiting') && (
+          <IconButton
+            isRound={true}
+            size="xs"
+            tooltip={t('modelManager.cancel')}
+            aria-label={t('modelManager.cancel')}
+            icon={<PiXBold />}
+            onClick={handleDeleteModelImport}
+          />
+        )}
+      </Box>
     </Flex>
   );
 };

From 5b7633f3c6eaa7ff3c3cdb65303a47d70fc0cf6f Mon Sep 17 00:00:00 2001
From: maryhipp <maryhipp@gmail.com>
Date: Thu, 22 Feb 2024 09:33:38 -0500
Subject: [PATCH 264/411] allow metadata-less models to be used for GET
 metadata endpoint

---
 invokeai/app/api/routers/model_manager.py | 6 ++----
 1 file changed, 2 insertions(+), 4 deletions(-)

diff --git a/invokeai/app/api/routers/model_manager.py b/invokeai/app/api/routers/model_manager.py
index f57f5f97b6..1b0fafc534 100644
--- a/invokeai/app/api/routers/model_manager.py
+++ b/invokeai/app/api/routers/model_manager.py
@@ -202,7 +202,7 @@ async def list_model_summary(
 
 
 @model_manager_router.get(
-    "/meta/i/{key}",
+    "/i/{key}/meta",
     operation_id="get_model_metadata",
     responses={
         200: {
@@ -210,7 +210,6 @@ async def list_model_summary(
             "content": {"application/json": {"example": example_model_metadata}},
         },
         400: {"description": "Bad request"},
-        404: {"description": "No metadata available"},
     },
 )
 async def get_model_metadata(
@@ -219,8 +218,7 @@ async def get_model_metadata(
     """Get a model metadata object."""
     record_store = ApiDependencies.invoker.services.model_manager.store
     result: Optional[AnyModelRepoMetadata] = record_store.get_metadata(key)
-    if not result:
-        raise HTTPException(status_code=404, detail="No metadata for a model with this key")
+   
     return result
 
 

From 5a12886dbb7aebbb5d04e7b24720f4db681b8630 Mon Sep 17 00:00:00 2001
From: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Date: Thu, 22 Feb 2024 09:39:19 -0500
Subject: [PATCH 265/411] update metadata endpoint

---
 .../modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx         | 4 ++--
 .../modelManagerV2/subpanels/ModelPanel/ModelView.tsx         | 4 ++--
 invokeai/frontend/web/src/services/api/schema.ts              | 2 +-
 3 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx
index 1d14fe9e11..772de82c41 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx
@@ -1,6 +1,6 @@
 import { skipToken } from '@reduxjs/toolkit/query';
 import { useAppDispatch, useAppSelector } from '../../../../app/store/storeHooks';
-import { useGetModelQuery, useUpdateModelsMutation } from '../../../../services/api/endpoints/models';
+import { useGetModelConfigQuery, useUpdateModelsMutation } from '../../../../services/api/endpoints/models';
 import {
   Flex,
   Text,
@@ -40,7 +40,7 @@ import { makeToast } from '../../../system/util/makeToast';
 export const ModelEdit = () => {
   const dispatch = useAppDispatch();
   const selectedModelKey = useAppSelector((s) => s.modelmanagerV2.selectedModelKey);
-  const { data, isLoading } = useGetModelQuery(selectedModelKey ?? skipToken);
+  const { data, isLoading } = useGetModelConfigQuery(selectedModelKey ?? skipToken);
 
   const [updateModel, { isLoading: isSubmitting }] = useUpdateModelsMutation();
 
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx
index 1fe8554352..bf19f9d2d6 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx
@@ -1,6 +1,6 @@
 import { skipToken } from '@reduxjs/toolkit/query';
 import { useAppDispatch, useAppSelector } from '../../../../app/store/storeHooks';
-import { useGetModelMetadataQuery, useGetModelQuery } from '../../../../services/api/endpoints/models';
+import { useGetModelMetadataQuery, useGetModelConfigQuery } from '../../../../services/api/endpoints/models';
 import { Flex, Text, Heading, Button, Box } from '@invoke-ai/ui-library';
 import DataViewer from '../../../gallery/components/ImageMetadataViewer/DataViewer';
 import { useCallback, useMemo } from 'react';
@@ -21,7 +21,7 @@ import { setSelectedModelMode } from '../../store/modelManagerV2Slice';
 export const ModelView = () => {
   const dispatch = useAppDispatch();
   const selectedModelKey = useAppSelector((s) => s.modelmanagerV2.selectedModelKey);
-  const { data, isLoading } = useGetModelQuery(selectedModelKey ?? skipToken);
+  const { data, isLoading } = useGetModelConfigQuery(selectedModelKey ?? skipToken);
   const { data: metadata } = useGetModelMetadataQuery(selectedModelKey ?? skipToken);
 
   const modelData = useMemo(() => {
diff --git a/invokeai/frontend/web/src/services/api/schema.ts b/invokeai/frontend/web/src/services/api/schema.ts
index 837a166541..81ea2577be 100644
--- a/invokeai/frontend/web/src/services/api/schema.ts
+++ b/invokeai/frontend/web/src/services/api/schema.ts
@@ -46,7 +46,7 @@ export type paths = {
      */
     get: operations["list_model_summary"];
   };
-  "/api/v2/models/meta/i/{key}": {
+  "/api/v2/models/i/{key}/meta": {
     /**
      * Get Model Metadata
      * @description Get a model metadata object.

From 9ae09e9a7ccf14268dbfede1b1f62a30d938a6c4 Mon Sep 17 00:00:00 2001
From: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Date: Thu, 22 Feb 2024 10:12:27 -0500
Subject: [PATCH 266/411] add scan model endpoint, break add model into tabs

---
 .../{ => AddModelPanel}/ImportQueue.tsx       |  8 +-
 .../{ => AddModelPanel}/ImportQueueModel.tsx  |  0
 .../subpanels/AddModelPanel/SimpleImport.tsx  | 67 ++++++++++++++
 .../modelManagerV2/subpanels/ImportModels.tsx | 88 ++++---------------
 .../web/src/services/api/endpoints/models.ts  | 37 +++-----
 .../frontend/web/src/services/api/schema.ts   | 31 +++++++
 6 files changed, 134 insertions(+), 97 deletions(-)
 rename invokeai/frontend/web/src/features/modelManagerV2/subpanels/{ => AddModelPanel}/ImportQueue.tsx (91%)
 rename invokeai/frontend/web/src/features/modelManagerV2/subpanels/{ => AddModelPanel}/ImportQueueModel.tsx (100%)
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/SimpleImport.tsx

diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportQueue.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue.tsx
similarity index 91%
rename from invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportQueue.tsx
rename to invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue.tsx
index 53c037e74f..3d80d11c29 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportQueue.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue.tsx
@@ -1,4 +1,4 @@
-import { Box, Button,Flex, Text } from '@invoke-ai/ui-library';
+import { Box, Button, Flex, Text } from '@invoke-ai/ui-library';
 import { useAppDispatch } from 'app/store/storeHooks';
 import { addToast } from 'features/system/store/systemSlice';
 import { makeToast } from 'features/system/util/makeToast';
@@ -7,7 +7,7 @@ import { useCallback, useMemo } from 'react';
 import { RiSparklingFill } from 'react-icons/ri';
 import { useGetModelImportsQuery, usePruneModelImportsMutation } from 'services/api/endpoints/models';
 
-import { ImportQueueModel } from './ImportQueueModel';
+import { ImportQueueModel } from '../ImportQueueModel';
 
 export const ImportQueue = () => {
   const dispatch = useAppDispatch();
@@ -50,7 +50,7 @@ export const ImportQueue = () => {
   }, [data]);
 
   return (
-    <>
+    <Flex flexDir="column" p={3} h="full">
       <Flex justifyContent="space-between">
         <Text>{t('modelManager.importQueue')}</Text>
         <Button
@@ -67,6 +67,6 @@ export const ImportQueue = () => {
           {data?.map((model) => <ImportQueueModel key={model.id} model={model} />)}
         </Flex>
       </Box>
-    </>
+    </Flex>
   );
 };
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportQueueModel.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueueModel.tsx
similarity index 100%
rename from invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportQueueModel.tsx
rename to invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueueModel.tsx
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/SimpleImport.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/SimpleImport.tsx
new file mode 100644
index 0000000000..b6d998ef0e
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/SimpleImport.tsx
@@ -0,0 +1,67 @@
+import { Flex, FormControl, FormLabel, Input, Button } from '@invoke-ai/ui-library';
+import { t } from 'i18next';
+import { useForm } from '@mantine/form';
+import { useAppDispatch } from '../../../../app/store/storeHooks';
+import { useImportMainModelsMutation } from '../../../../services/api/endpoints/models';
+import { addToast } from '../../../system/store/systemSlice';
+import { makeToast } from '../../../system/util/makeToast';
+
+type SimpleImportModelConfig = {
+  location: string;
+};
+
+export const SimpleImport = () => {
+  const dispatch = useAppDispatch();
+
+  const [importMainModel, { isLoading }] = useImportMainModelsMutation();
+
+  const addModelForm = useForm({
+    initialValues: {
+      location: '',
+    },
+  });
+
+  const handleAddModelSubmit = (values: SimpleImportModelConfig) => {
+    importMainModel({ source: values.location, config: undefined })
+      .unwrap()
+      .then((_) => {
+        dispatch(
+          addToast(
+            makeToast({
+              title: t('toast.modelAddedSimple'),
+              status: 'success',
+            })
+          )
+        );
+        addModelForm.reset();
+      })
+      .catch((error) => {
+        if (error) {
+          dispatch(
+            addToast(
+              makeToast({
+                title: `${error.data.detail} `,
+                status: 'error',
+              })
+            )
+          );
+        }
+      });
+  };
+
+  return (
+    <form onSubmit={addModelForm.onSubmit((v) => handleAddModelSubmit(v))}>
+      <Flex gap={2} alignItems="flex-end" justifyContent="space-between">
+        <FormControl>
+          <Flex direction="column" w="full">
+            <FormLabel>{t('modelManager.modelLocation')}</FormLabel>
+            <Input {...addModelForm.getInputProps('location')} />
+          </Flex>
+        </FormControl>
+        <Button isDisabled={!addModelForm.values.location} isLoading={isLoading} type="submit">
+          {t('modelManager.addModel')}
+        </Button>
+      </Flex>
+    </form>
+  );
+};
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx
index e2cdf24c2f..a0dd39de2e 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx
@@ -1,80 +1,30 @@
-import { Box, Button, Divider,Flex, FormControl, FormLabel, Heading, Input } from '@invoke-ai/ui-library';
-import { useForm } from '@mantine/form';
-import { useAppDispatch } from 'app/store/storeHooks';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
-import { t } from 'i18next';
-import type { CSSProperties } from 'react';
-import { useImportMainModelsMutation } from 'services/api/endpoints/models';
+import { Box, Divider, Heading, Tab, TabList, TabPanel, TabPanels, Tabs } from '@invoke-ai/ui-library';
 
-import { ImportQueue } from './ImportQueue';
-
-const formStyles: CSSProperties = {
-  width: '100%',
-};
-
-type ExtendedImportModelConfig = {
-  location: string;
-};
+import { ImportQueue } from './AddModelPanel/ImportQueue';
+import { SimpleImport } from './AddModelPanel/SimpleImport';
 
 export const ImportModels = () => {
-  const dispatch = useAppDispatch();
-
-  const [importMainModel, { isLoading }] = useImportMainModelsMutation();
-
-  const addModelForm = useForm({
-    initialValues: {
-      location: '',
-    },
-  });
-
-  const handleAddModelSubmit = (values: ExtendedImportModelConfig) => {
-    importMainModel({ source: values.location, config: undefined })
-      .unwrap()
-      .then((_) => {
-        dispatch(
-          addToast(
-            makeToast({
-              title: t('toast.modelAddedSimple'),
-              status: 'success',
-            })
-          )
-        );
-        addModelForm.reset();
-      })
-      .catch((error) => {
-        if (error) {
-          dispatch(
-            addToast(
-              makeToast({
-                title: `${error.data.detail} `,
-                status: 'error',
-              })
-            )
-          );
-        }
-      });
-  };
-
   return (
     <Box layerStyle="first" p={3} borderRadius="base" w="full" h="full">
       <Box w="full" p={4}>
         <Heading fontSize="xl">Add Model</Heading>
       </Box>
-      <Box layerStyle="second" p={3} borderRadius="base" w="full" h="full">
-        <form onSubmit={addModelForm.onSubmit((v) => handleAddModelSubmit(v))} style={formStyles}>
-          <Flex gap={2} alignItems="flex-end" justifyContent="space-between">
-            <FormControl>
-              <Flex direction="column" w="full">
-                <FormLabel>{t('modelManager.modelLocation')}</FormLabel>
-                <Input {...addModelForm.getInputProps('location')} />
-              </Flex>
-            </FormControl>
-            <Button isDisabled={!addModelForm.values.location} isLoading={isLoading} type="submit">
-              {t('modelManager.addModel')}
-            </Button>
-          </Flex>
-        </form>
+      <Box layerStyle="second" borderRadius="base" w="full" h="100vh">
+        <Tabs variant="collapse">
+          <TabList>
+            <Tab>Simple</Tab>
+            <Tab>Advanced</Tab>
+            <Tab>Scan</Tab>
+          </TabList>
+          <TabPanels p={3}>
+            <TabPanel>
+              <SimpleImport />
+            </TabPanel>
+            <TabPanel>Advanced Import Placeholder</TabPanel>
+            <TabPanel>Scan Models Placeholder</TabPanel>
+          </TabPanels>
+        </Tabs>
+
         <Divider mt="5" mb="3" />
         <ImportQueue />
       </Box>
diff --git a/invokeai/frontend/web/src/services/api/endpoints/models.ts b/invokeai/frontend/web/src/services/api/endpoints/models.ts
index 3e1abc8560..a1cdb43617 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/models.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/models.ts
@@ -25,10 +25,10 @@ type UpdateModelArg = {
 };
 
 type UpdateModelResponse = paths['/api/v2/models/i/{key}']['patch']['responses']['200']['content']['application/json'];
+type GetModelConfigResponse = paths['/api/v2/models/i/{key}']['get']['responses']['200']['content']['application/json'];
 
 type GetModelMetadataResponse =
-  paths['/api/v2/models/meta/i/{key}']['get']['responses']['200']['content']['application/json'];
-type GetModelResponse = paths['/api/v2/models/i/{key}']['get']['responses']['200']['content']['application/json'];
+  paths['/api/v2/models/i/{key}/meta']['get']['responses']['200']['content']['application/json'];
 
 type ListModelsArg = NonNullable<paths['/api/v2/models/']['get']['parameters']['query']>;
 
@@ -78,16 +78,13 @@ type AddMainModelArg = {
 
 type AddMainModelResponse = paths['/api/v2/models/add']['post']['responses']['201']['content']['application/json'];
 
-type SyncModelsResponse = paths['/api/v2/models/sync']['patch']['responses']['204']['content']
-
-export type SearchFolderResponse =
-  paths['/api/v2/models/search']['get']['responses']['200']['content']['application/json'];
+export type ScanFolderResponse =
+  paths['/api/v2/models/scan_folder']['get']['responses']['200']['content']['application/json'];
+type ScanFolderArg = operations['scan_for_models']['parameters']['query'];
 
 type CheckpointConfigsResponse =
   paths['/api/v2/models/ckpt_confs']['get']['responses']['200']['content']['application/json'];
 
-type SearchFolderArg = operations['search_for_models']['parameters']['query'];
-
 export const mainModelsAdapter = createEntityAdapter<MainModelConfig, string>({
   selectId: (entity) => entity.key,
   sortComparer: (a, b) => a.name.localeCompare(b.name),
@@ -131,7 +128,6 @@ const buildProvidesTags =
   <TEntity extends AnyModelConfig>(tagType: (typeof tagTypes)[number]) =>
   (result: EntityState<TEntity, string> | undefined) => {
     const tags: ApiTagDescription[] = [{ type: tagType, id: LIST_TAG }, 'Model'];
-
     if (result) {
       tags.push(
         ...result.ids.map((id) => ({
@@ -175,15 +171,9 @@ export const modelsApi = api.injectEndpoints({
       providesTags: buildProvidesTags<MainModelConfig>('MainModel'),
       transformResponse: buildTransformResponse<MainModelConfig>(mainModelsAdapter),
     }),
-    getModel: build.query<GetModelResponse, string>({
-      query: (key) => {
-        return buildModelsUrl(`i/${key}`);
-      },
-      providesTags: ['Model'],
-    }),
     getModelMetadata: build.query<GetModelMetadataResponse, string>({
       query: (key) => {
-        return buildModelsUrl(`meta/i/${key}`);
+        return buildModelsUrl(`i/${key}/meta`);
       },
       providesTags: ['Model'],
     }),
@@ -247,7 +237,7 @@ export const modelsApi = api.injectEndpoints({
       },
       invalidatesTags: ['Model'],
     }),
-    getModelConfig: build.query<AnyModelConfig, string>({
+    getModelConfig: build.query<GetModelConfigResponse, string>({
       query: (key) => buildModelsUrl(`i/${key}`),
       providesTags: (result) => {
         const tags: ApiTagDescription[] = ['Model'];
@@ -259,7 +249,7 @@ export const modelsApi = api.injectEndpoints({
         return tags;
       },
     }),
-    syncModels: build.mutation<SyncModelsResponse, void>({
+    syncModels: build.mutation<void, void>({
       query: () => {
         return {
           url: buildModelsUrl('sync'),
@@ -298,16 +288,16 @@ export const modelsApi = api.injectEndpoints({
       providesTags: buildProvidesTags<TextualInversionModelConfig>('TextualInversionModel'),
       transformResponse: buildTransformResponse<TextualInversionModelConfig>(textualInversionModelsAdapter),
     }),
-    getModelsInFolder: build.query<SearchFolderResponse, SearchFolderArg>({
+    scanModels: build.query<ScanFolderResponse, ScanFolderArg>({
       query: (arg) => {
-        const folderQueryStr = queryString.stringify(arg, {});
+        const folderQueryStr = arg ? queryString.stringify(arg, {}) : '';
         return {
-          url: buildModelsUrl(`search?${folderQueryStr}`),
+          url: buildModelsUrl(`scan_folder?${folderQueryStr}`),
         };
       },
     }),
     getModelImports: build.query<ListImportModelsResponse, void>({
-      query: (arg) => {
+      query: () => {
         return {
           url: buildModelsUrl(`import`),
         };
@@ -358,11 +348,10 @@ export const {
   useConvertMainModelsMutation,
   useMergeMainModelsMutation,
   useSyncModelsMutation,
-  useGetModelsInFolderQuery,
+  useScanModelsQuery,
   useGetCheckpointConfigsQuery,
   useGetModelImportsQuery,
   useGetModelMetadataQuery,
   useDeleteModelImportMutation,
   usePruneModelImportsMutation,
-  useGetModelQuery,
 } = modelsApi;
diff --git a/invokeai/frontend/web/src/services/api/schema.ts b/invokeai/frontend/web/src/services/api/schema.ts
index 81ea2577be..d7205c5c88 100644
--- a/invokeai/frontend/web/src/services/api/schema.ts
+++ b/invokeai/frontend/web/src/services/api/schema.ts
@@ -60,6 +60,10 @@ export type paths = {
      */
     get: operations["list_tags"];
   };
+  "/api/v2/models/scan_folder": {
+    /** Scan For Models */
+    get: operations["scan_for_models"];
+  };
   "/api/v2/models/tags/search": {
     /**
      * Search By Metadata Tags
@@ -11361,6 +11365,33 @@ export type operations = {
       };
     };
   };
+  /** Scan For Models */
+  scan_for_models: {
+    parameters: {
+      query?: {
+        /** @description Directory path to search for models */
+        scan_path?: string;
+      };
+    };
+    responses: {
+      /** @description Directory scanned successfully */
+      200: {
+        content: {
+          "application/json": string[];
+        };
+      };
+      /** @description Invalid directory path */
+      400: {
+        content: never;
+      };
+      /** @description Validation Error */
+      422: {
+        content: {
+          "application/json": components["schemas"]["HTTPValidationError"];
+        };
+      };
+    };
+  };
   /**
    * Search By Metadata Tags
    * @description Get a list of models.

From 57a402053e4b35bb155ac065bb028f465a3ddc0a Mon Sep 17 00:00:00 2001
From: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Date: Thu, 22 Feb 2024 11:50:16 -0500
Subject: [PATCH 267/411] basic scan working and renders results

---
 .../subpanels/AddModelPanel/ImportQueue.tsx   |  2 +-
 .../AddModelPanel/ScanModels/ScanModels.tsx   |  5 ++
 .../ScanModels/ScanModelsForm.tsx             | 54 +++++++++++++
 .../ScanModels/ScanModelsResults.tsx          | 77 +++++++++++++++++++
 .../modelManagerV2/subpanels/ImportModels.tsx |  7 +-
 .../web/src/services/api/endpoints/models.ts  |  1 +
 6 files changed, 143 insertions(+), 3 deletions(-)
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModels.tsx
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsForm.tsx
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx

diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue.tsx
index 3d80d11c29..804a728cbd 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue.tsx
@@ -7,7 +7,7 @@ import { useCallback, useMemo } from 'react';
 import { RiSparklingFill } from 'react-icons/ri';
 import { useGetModelImportsQuery, usePruneModelImportsMutation } from 'services/api/endpoints/models';
 
-import { ImportQueueModel } from '../ImportQueueModel';
+import { ImportQueueModel } from './ImportQueueModel';
 
 export const ImportQueue = () => {
   const dispatch = useAppDispatch();
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModels.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModels.tsx
new file mode 100644
index 0000000000..02eb3b50ba
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModels.tsx
@@ -0,0 +1,5 @@
+import { ScanModelsForm } from './ScanModelsForm';
+
+export const ScanModels = () => {
+  return <ScanModelsForm />;
+};
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsForm.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsForm.tsx
new file mode 100644
index 0000000000..48b8bb0dda
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsForm.tsx
@@ -0,0 +1,54 @@
+import { Flex, FormControl, FormLabel, Input, Button, FormErrorMessage, Divider } from '@invoke-ai/ui-library';
+import { ChangeEventHandler, useCallback, useState } from 'react';
+import { useLazyScanModelsQuery } from '../../../../../services/api/endpoints/models';
+import { useTranslation } from 'react-i18next';
+import { ScanModelsResults } from './ScanModelsResults';
+
+export const ScanModelsForm = () => {
+  const [scanPath, setScanPath] = useState('');
+  const [errorMessage, setErrorMessage] = useState('');
+  const [results, setResults] = useState<string[] | undefined>();
+  const { t } = useTranslation();
+
+  const [_scanModels, { isLoading }] = useLazyScanModelsQuery();
+
+  const handleSubmitScan = useCallback(async () => {
+    _scanModels({ scan_path: scanPath })
+      .unwrap()
+      .then((result) => {
+        setResults(result);
+      })
+      .catch((error) => {
+        if (error) {
+          setErrorMessage(error.data.detail);
+        }
+      });
+  }, [scanPath]);
+
+  const handleSetScanPath: ChangeEventHandler<HTMLInputElement> = useCallback((e) => {
+    setScanPath(e.target.value);
+    setErrorMessage('');
+  }, []);
+
+  return (
+    <>
+      <FormControl isInvalid={!!errorMessage.length} w="full">
+        <Flex flexDir="column" w="full">
+          <Flex gap={2} alignItems="flex-end" justifyContent="space-between">
+            <Flex direction="column" w="full">
+              <FormLabel>{t('common.folder')}</FormLabel>
+              <Input value={scanPath} onChange={handleSetScanPath} />
+            </Flex>
+
+            <Button onClick={handleSubmitScan} isLoading={isLoading} isDisabled={scanPath.length === 0}>
+              {t('modelManager.scanFolder')}
+            </Button>
+          </Flex>
+          {!!errorMessage.length && <FormErrorMessage>{errorMessage}</FormErrorMessage>}
+        </Flex>
+      </FormControl>
+
+      {results && <ScanModelsResults results={results} />}
+    </>
+  );
+};
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx
new file mode 100644
index 0000000000..9bccf8a0d7
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx
@@ -0,0 +1,77 @@
+import {
+  Text,
+  Flex,
+  Heading,
+  IconButton,
+  Input,
+  InputGroup,
+  InputRightElement,
+  Divider,
+  Box,
+} from '@invoke-ai/ui-library';
+import { t } from 'i18next';
+import { ChangeEventHandler, useCallback, useMemo, useState } from 'react';
+import { PiXBold } from 'react-icons/pi';
+
+export const ScanModelsResults = ({ results }: { results: string[] }) => {
+  const [searchTerm, setSearchTerm] = useState('');
+  const [filteredResults, setFilteredResults] = useState(results);
+
+  const handleSearch: ChangeEventHandler<HTMLInputElement> = useCallback(
+    (e) => {
+      setSearchTerm(e.target.value);
+      setFilteredResults(
+        results.filter((result) => {
+          const modelName = result.split('\\').slice(-1)[0];
+          return modelName?.includes(e.target.value);
+        })
+      );
+    },
+    [results]
+  );
+
+  const clearSearch = useCallback(() => {
+    setSearchTerm('');
+  }, []);
+
+  return (
+    <>
+      <Divider mt={4} />
+      <Flex flexDir="column" gap={2} mt={4}>
+        <Flex justifyContent="space-between" alignItems="center" mb={4}>
+          <Heading fontSize="md" as="h4">
+            Scan Results
+          </Heading>
+          <InputGroup maxW="300px" size="xs">
+            <Input
+              placeholder={t('modelManager.search')}
+              value={searchTerm || ''}
+              data-testid="board-search-input"
+              onChange={handleSearch}
+              size="xs"
+            />
+
+            {!!searchTerm?.length && (
+              <InputRightElement h="full" pe={2}>
+                <IconButton
+                  size="sm"
+                  variant="link"
+                  aria-label={t('boards.clearSearch')}
+                  icon={<PiXBold />}
+                  onClick={clearSearch}
+                />
+              </InputRightElement>
+            )}
+          </InputGroup>
+        </Flex>
+
+        {filteredResults.map((result) => (
+          <Flex key={result} fontSize="sm" flexDir="column">
+            <Text fontWeight="semibold">{result.split('\\').slice(-1)[0]}</Text>
+            <Text variant="subtext">{result}</Text>
+          </Flex>
+        ))}
+      </Flex>
+    </>
+  );
+};
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx
index a0dd39de2e..88423758e6 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx
@@ -2,6 +2,7 @@ import { Box, Divider, Heading, Tab, TabList, TabPanel, TabPanels, Tabs } from '
 
 import { ImportQueue } from './AddModelPanel/ImportQueue';
 import { SimpleImport } from './AddModelPanel/SimpleImport';
+import { ScanModels } from './AddModelPanel/ScanModels/ScanModels';
 
 export const ImportModels = () => {
   return (
@@ -9,7 +10,7 @@ export const ImportModels = () => {
       <Box w="full" p={4}>
         <Heading fontSize="xl">Add Model</Heading>
       </Box>
-      <Box layerStyle="second" borderRadius="base" w="full" h="100vh">
+      <Box layerStyle="second" borderRadius="base" w="full">
         <Tabs variant="collapse">
           <TabList>
             <Tab>Simple</Tab>
@@ -21,7 +22,9 @@ export const ImportModels = () => {
               <SimpleImport />
             </TabPanel>
             <TabPanel>Advanced Import Placeholder</TabPanel>
-            <TabPanel>Scan Models Placeholder</TabPanel>
+            <TabPanel>
+              <ScanModels />
+            </TabPanel>
           </TabPanels>
         </Tabs>
 
diff --git a/invokeai/frontend/web/src/services/api/endpoints/models.ts b/invokeai/frontend/web/src/services/api/endpoints/models.ts
index a1cdb43617..61f0975920 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/models.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/models.ts
@@ -349,6 +349,7 @@ export const {
   useMergeMainModelsMutation,
   useSyncModelsMutation,
   useScanModelsQuery,
+  useLazyScanModelsQuery,
   useGetCheckpointConfigsQuery,
   useGetModelImportsQuery,
   useGetModelMetadataQuery,

From e7d7b3789686b55ec46568e3596693b459b19136 Mon Sep 17 00:00:00 2001
From: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Date: Thu, 22 Feb 2024 12:18:25 -0500
Subject: [PATCH 268/411] get positioning/scrolling working for scan results
 list

---
 .../ScanModels/ScanModelsForm.tsx             |  6 ++---
 .../ScanModels/ScanModelsResults.tsx          | 22 +++++++++++--------
 .../modelManagerV2/subpanels/ImportModels.tsx | 20 ++++++++---------
 3 files changed, 26 insertions(+), 22 deletions(-)

diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsForm.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsForm.tsx
index 48b8bb0dda..7e243e6c60 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsForm.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsForm.tsx
@@ -3,6 +3,7 @@ import { ChangeEventHandler, useCallback, useState } from 'react';
 import { useLazyScanModelsQuery } from '../../../../../services/api/endpoints/models';
 import { useTranslation } from 'react-i18next';
 import { ScanModelsResults } from './ScanModelsResults';
+import ScrollableContent from '../../../../../common/components/OverlayScrollbars/ScrollableContent';
 
 export const ScanModelsForm = () => {
   const [scanPath, setScanPath] = useState('');
@@ -31,7 +32,7 @@ export const ScanModelsForm = () => {
   }, []);
 
   return (
-    <>
+    <Flex flexDir="column" height="100%">
       <FormControl isInvalid={!!errorMessage.length} w="full">
         <Flex flexDir="column" w="full">
           <Flex gap={2} alignItems="flex-end" justifyContent="space-between">
@@ -47,8 +48,7 @@ export const ScanModelsForm = () => {
           {!!errorMessage.length && <FormErrorMessage>{errorMessage}</FormErrorMessage>}
         </Flex>
       </FormControl>
-
       {results && <ScanModelsResults results={results} />}
-    </>
+    </Flex>
   );
 };
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx
index 9bccf8a0d7..58cddda2ec 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx
@@ -12,6 +12,7 @@ import {
 import { t } from 'i18next';
 import { ChangeEventHandler, useCallback, useMemo, useState } from 'react';
 import { PiXBold } from 'react-icons/pi';
+import ScrollableContent from '../../../../../common/components/OverlayScrollbars/ScrollableContent';
 
 export const ScanModelsResults = ({ results }: { results: string[] }) => {
   const [searchTerm, setSearchTerm] = useState('');
@@ -37,8 +38,8 @@ export const ScanModelsResults = ({ results }: { results: string[] }) => {
   return (
     <>
       <Divider mt={4} />
-      <Flex flexDir="column" gap={2} mt={4}>
-        <Flex justifyContent="space-between" alignItems="center" mb={4}>
+      <Flex flexDir="column" gap={2} mt={4} height="100%">
+        <Flex justifyContent="space-between" alignItems="center">
           <Heading fontSize="md" as="h4">
             Scan Results
           </Heading>
@@ -64,13 +65,16 @@ export const ScanModelsResults = ({ results }: { results: string[] }) => {
             )}
           </InputGroup>
         </Flex>
-
-        {filteredResults.map((result) => (
-          <Flex key={result} fontSize="sm" flexDir="column">
-            <Text fontWeight="semibold">{result.split('\\').slice(-1)[0]}</Text>
-            <Text variant="subtext">{result}</Text>
-          </Flex>
-        ))}
+        <Flex height="100%" layerStyle="third" borderRadius="base" p={4} mt={4} mb={4}>
+          <ScrollableContent>
+            {filteredResults.map((result) => (
+              <Flex key={result} fontSize="sm" flexDir="column">
+                <Text fontWeight="semibold">{result.split('\\').slice(-1)[0]}</Text>
+                <Text variant="subtext">{result}</Text>
+              </Flex>
+            ))}
+          </ScrollableContent>
+        </Flex>
       </Flex>
     </>
   );
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx
index 88423758e6..2c95de4827 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx
@@ -1,4 +1,4 @@
-import { Box, Divider, Heading, Tab, TabList, TabPanel, TabPanels, Tabs } from '@invoke-ai/ui-library';
+import { Box, Divider, Heading, Tab, Flex, TabList, TabPanel, TabPanels, Tabs } from '@invoke-ai/ui-library';
 
 import { ImportQueue } from './AddModelPanel/ImportQueue';
 import { SimpleImport } from './AddModelPanel/SimpleImport';
@@ -6,31 +6,31 @@ import { ScanModels } from './AddModelPanel/ScanModels/ScanModels';
 
 export const ImportModels = () => {
   return (
-    <Box layerStyle="first" p={3} borderRadius="base" w="full" h="full">
-      <Box w="full" p={4}>
+    <Flex layerStyle="first" p={3} borderRadius="base" w="full" h="full" flexDir="column" gap={2}>
+      <Box w="full" p={2}>
         <Heading fontSize="xl">Add Model</Heading>
       </Box>
-      <Box layerStyle="second" borderRadius="base" w="full">
-        <Tabs variant="collapse">
+      <Box layerStyle="second" borderRadius="base" w="full" h="50%" overflow="hidden">
+        <Tabs variant="collapse" height="100%">
           <TabList>
             <Tab>Simple</Tab>
             <Tab>Advanced</Tab>
             <Tab>Scan</Tab>
           </TabList>
-          <TabPanels p={3}>
+          <TabPanels p={3} height="100%">
             <TabPanel>
               <SimpleImport />
             </TabPanel>
             <TabPanel>Advanced Import Placeholder</TabPanel>
-            <TabPanel>
+            <TabPanel height="100%">
               <ScanModels />
             </TabPanel>
           </TabPanels>
         </Tabs>
-
-        <Divider mt="5" mb="3" />
+      </Box>
+      <Box layerStyle="second" borderRadius="base" w="full" h="50%">
         <ImportQueue />
       </Box>
-    </Box>
+    </Flex>
   );
 };

From cdd2f18bbdb5ed2493718df59f95a832f0f70789 Mon Sep 17 00:00:00 2001
From: Jennifer Player <chainchompa@gmail.com>
Date: Thu, 22 Feb 2024 18:56:51 -0500
Subject: [PATCH 269/411] added advanced import forms, not fully working yet

---
 invokeai/frontend/web/public/locales/en.json  |   1 +
 .../AddModelPanel/AdvancedImport.tsx          |  56 ++++++
 .../AdvancedImportCheckpoint.tsx              | 160 ++++++++++++++++++
 .../AddModelPanel/AdvancedImportDiffusers.tsx | 132 +++++++++++++++
 .../AddModelPanel/BaseModelSelect.tsx         |  38 +++++
 .../AddModelPanel/CheckpointConfigsSelect.tsx |  32 ++++
 .../AddModelPanel/ImportQueueModel.tsx        |   9 +-
 .../AddModelPanel/ModelVariantSelect.tsx      |  36 ++++
 .../AddModelPanel/ScanModels/ScanModels.tsx   |   3 +-
 .../ScanModels/ScanModelsForm.tsx             |   9 +-
 .../ScanModels/ScanModelsResults.tsx          |  10 +-
 .../subpanels/AddModelPanel/SimpleImport.tsx  |  75 ++++----
 .../modelManagerV2/subpanels/ImportModels.tsx |   9 +-
 .../web/src/services/api/endpoints/models.ts  |   2 +-
 14 files changed, 522 insertions(+), 50 deletions(-)
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImport.tsx
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImportCheckpoint.tsx
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImportDiffusers.tsx
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/BaseModelSelect.tsx
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/CheckpointConfigsSelect.tsx
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ModelVariantSelect.tsx

diff --git a/invokeai/frontend/web/public/locales/en.json b/invokeai/frontend/web/public/locales/en.json
index 4d40f7105c..dfb0103dff 100644
--- a/invokeai/frontend/web/public/locales/en.json
+++ b/invokeai/frontend/web/public/locales/en.json
@@ -696,6 +696,7 @@
         "addNewModel": "Add New Model",
         "addSelected": "Add Selected",
         "advanced": "Advanced",
+        "advancedImportInfo": "The advanced tab allows for manual configuration of core model settings. Only use this tab if you are confident that you know the correct model type and configuration for the selected model.",
         "allModels": "All Models",
         "alpha": "Alpha",
         "availableModels": "Available Models",
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImport.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImport.tsx
new file mode 100644
index 0000000000..9ec39a0649
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImport.tsx
@@ -0,0 +1,56 @@
+import type { ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
+import { Combobox, Flex, FormLabel,Text } from '@invoke-ai/ui-library';
+import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
+import { useCallback, useMemo, useState } from 'react';
+import { useTranslation } from 'react-i18next';
+import { z } from 'zod';
+
+import { AdvancedImportCheckpoint } from './AdvancedImportCheckpoint';
+import { AdvancedImportDiffusers } from './AdvancedImportDiffusers';
+
+export const zManualAddMode = z.enum(['diffusers', 'checkpoint']);
+export type ManualAddMode = z.infer<typeof zManualAddMode>;
+export const isManualAddMode = (v: unknown): v is ManualAddMode => zManualAddMode.safeParse(v).success;
+
+export const AdvancedImport = () => {
+  const [advancedAddMode, setAdvancedAddMode] = useState<ManualAddMode>('diffusers');
+
+  const { t } = useTranslation();
+  const handleChange: ComboboxOnChange = useCallback((v) => {
+    if (!isManualAddMode(v?.value)) {
+      return;
+    }
+    setAdvancedAddMode(v.value);
+  }, []);
+
+  const options: ComboboxOption[] = useMemo(
+    () => [
+      { label: t('modelManager.diffusersModels'), value: 'diffusers' },
+      { label: t('modelManager.checkpointOrSafetensors'), value: 'checkpoint' },
+    ],
+    [t]
+  );
+
+  const value = useMemo(() => options.find((o) => o.value === advancedAddMode), [options, advancedAddMode]);
+
+  return (
+    <ScrollableContent>
+      <Flex flexDirection="column" gap={4} width="100%" pb={10}>
+        <Flex alignItems="flex-end" gap="4">
+          <Flex direction="column" gap="3" width="full">
+            <FormLabel>{t('modelManager.modelType')}</FormLabel>
+            <Combobox value={value} options={options} onChange={handleChange} />
+          </Flex>
+          <Text px="2" fontSize="xs" textAlign="center">
+            {t('modelManager.advancedImportInfo')}
+          </Text>
+        </Flex>
+
+        <Flex p={4} borderRadius={4} bg="base.850" height="100%">
+          {advancedAddMode === 'diffusers' && <AdvancedImportDiffusers />}
+          {advancedAddMode === 'checkpoint' && <AdvancedImportCheckpoint />}
+        </Flex>
+      </Flex>
+    </ScrollableContent>
+  );
+};
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImportCheckpoint.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImportCheckpoint.tsx
new file mode 100644
index 0000000000..bf22ef12d1
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImportCheckpoint.tsx
@@ -0,0 +1,160 @@
+import {
+  Button,
+  Checkbox,
+  Flex,
+  FormControl,
+  FormErrorMessage,
+  FormLabel,
+  Input,
+  Textarea,
+} from '@invoke-ai/ui-library';
+import { useAppDispatch } from 'app/store/storeHooks';
+import { addToast } from 'features/system/store/systemSlice';
+import { makeToast } from 'features/system/util/makeToast';
+import type { CSSProperties } from 'react';
+import { useCallback, useState } from 'react';
+import type { SubmitHandler } from 'react-hook-form';
+import { useForm } from 'react-hook-form';
+import { useTranslation } from 'react-i18next';
+import { useAddMainModelsMutation } from 'services/api/endpoints/models';
+import type { CheckpointModelConfig, DiffusersModelConfig } from 'services/api/types';
+
+import BaseModelSelect from './BaseModelSelect';
+import CheckpointConfigsSelect from './CheckpointConfigsSelect';
+import ModelVariantSelect from './ModelVariantSelect';
+
+export const AdvancedImportCheckpoint = () => {
+  const { t } = useTranslation();
+  const dispatch = useAppDispatch();
+
+  const [addMainModel] = useAddMainModelsMutation();
+
+  const [useCustomConfig, setUseCustomConfig] = useState<boolean>(false);
+
+  const {
+    register,
+    handleSubmit,
+    control,
+    formState: { errors },
+    reset,
+  } = useForm<CheckpointModelConfig>({
+    defaultValues: {
+      name: '',
+      base: 'sd-1',
+      type: 'main',
+      path: '',
+      description: '',
+      format: 'checkpoint',
+      vae: '',
+      variant: 'normal',
+      config: '',
+    },
+    mode: 'onChange',
+  });
+
+  const onSubmit = useCallback<SubmitHandler<DiffusersModelConfig>>(
+    (values) => {
+      addMainModel({
+        body: values,
+      })
+        .unwrap()
+        .then((_) => {
+          dispatch(
+            addToast(
+              makeToast({
+                title: t('modelManager.modelAdded', {
+                  modelName: values.name,
+                }),
+                status: 'success',
+              })
+            )
+          );
+          reset();
+        })
+        .catch((error) => {
+          if (error) {
+            dispatch(
+              addToast(
+                makeToast({
+                  title: t('toast.modelAddFailed'),
+                  status: 'error',
+                })
+              )
+            );
+          }
+        });
+    },
+    [addMainModel, dispatch, reset, t]
+  );
+
+  const handleChangeUseCustomConfig = useCallback(() => setUseCustomConfig((prev) => !prev), []);
+
+  return (
+    <form onSubmit={handleSubmit(onSubmit)} style={formStyles}>
+      <Flex flexDirection="column" gap={2}>
+        <FormControl isInvalid={Boolean(errors.name)}>
+          <Flex direction="column" width="full">
+            <FormLabel>{t('modelManager.name')}</FormLabel>
+            <Input
+              {...register('name', {
+                validate: (value) => value.trim().length > 3 || 'Must be at least 3 characters',
+              })}
+            />
+            {errors.name?.message && <FormErrorMessage>{errors.name?.message}</FormErrorMessage>}
+          </Flex>
+        </FormControl>
+        <Flex>
+          <FormControl>
+            <Flex direction="column" width="full">
+              <FormLabel>{t('modelManager.description')}</FormLabel>
+              <Textarea size="sm" {...register('description')} />
+              {errors.name?.message && <FormErrorMessage>{errors.name?.message}</FormErrorMessage>}
+            </Flex>
+          </FormControl>
+        </Flex>
+        <Flex gap="2">
+          <BaseModelSelect<CheckpointModelConfig> control={control} name="base" />
+          <ModelVariantSelect<CheckpointModelConfig> control={control} name="variant" />
+        </Flex>
+        <FormControl isInvalid={Boolean(errors.path)}>
+          <Flex direction="column" width="full">
+            <FormLabel>{t('modelManager.modelLocation')}</FormLabel>
+            <Input
+              {...register('path', {
+                validate: (value) => value.trim().length > 0 || 'Must provide a path',
+              })}
+            />
+            {errors.path?.message && <FormErrorMessage>{errors.path?.message}</FormErrorMessage>}
+          </Flex>
+        </FormControl>
+        <FormControl>
+          <Flex direction="column" width="full">
+            <FormLabel>{t('modelManager.vaeLocation')}</FormLabel>
+            <Input {...register('vae')} />
+          </Flex>
+        </FormControl>
+        <Flex flexDirection="column" width="100%" gap={2}>
+          {!useCustomConfig ? (
+            <CheckpointConfigsSelect control={control} name="config" />
+          ) : (
+            <FormControl isRequired>
+              <FormLabel>{t('modelManager.config')}</FormLabel>
+              <Input {...register('config')} />
+            </FormControl>
+          )}
+          <FormControl>
+            <FormLabel>{t('modelManager.useCustomConfig')}</FormLabel>
+            <Checkbox isChecked={useCustomConfig} onChange={handleChangeUseCustomConfig} />
+          </FormControl>
+          <Button mt={2} type="submit">
+            {t('modelManager.addModel')}
+          </Button>
+        </Flex>
+      </Flex>
+    </form>
+  );
+};
+
+const formStyles: CSSProperties = {
+  width: '100%',
+};
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImportDiffusers.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImportDiffusers.tsx
new file mode 100644
index 0000000000..c113fe0274
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImportDiffusers.tsx
@@ -0,0 +1,132 @@
+import { Button, Flex, FormControl, FormErrorMessage, FormLabel, Input, Textarea } from '@invoke-ai/ui-library';
+import { useAppDispatch } from 'app/store/storeHooks';
+import { addToast } from 'features/system/store/systemSlice';
+import { makeToast } from 'features/system/util/makeToast';
+import type { CSSProperties } from 'react';
+import {useCallback } from 'react';
+import type { SubmitHandler } from 'react-hook-form';
+import { useForm } from 'react-hook-form';
+import { useTranslation } from 'react-i18next';
+import { useAddMainModelsMutation } from 'services/api/endpoints/models';
+import type { DiffusersModelConfig } from 'services/api/types';
+
+import BaseModelSelect from './BaseModelSelect';
+import ModelVariantSelect from './ModelVariantSelect';
+
+export const AdvancedImportDiffusers = () => {
+  const { t } = useTranslation();
+  const dispatch = useAppDispatch();
+
+  const [addMainModel] = useAddMainModelsMutation();
+
+  const {
+    register,
+    handleSubmit,
+    control,
+    formState: { errors },
+    reset,
+  } = useForm<DiffusersModelConfig>({
+    defaultValues: {
+      name: '',
+      base: 'sd-1',
+      type: 'main',
+      path: '',
+      description: '',
+      format: 'diffusers',
+      vae: '',
+      variant: 'normal',
+    },
+    mode: 'onChange',
+  });
+
+  const onSubmit = useCallback<SubmitHandler<DiffusersModelConfig>>(
+    (values) => {
+      addMainModel({
+        body: values,
+      })
+        .unwrap()
+        .then((_) => {
+          dispatch(
+            addToast(
+              makeToast({
+                title: t('modelManager.modelAdded', {
+                  modelName: values.name,
+                }),
+                status: 'success',
+              })
+            )
+          );
+          reset();
+        })
+        .catch((error) => {
+          if (error) {
+            dispatch(
+              addToast(
+                makeToast({
+                  title: t('toast.modelAddFailed'),
+                  status: 'error',
+                })
+              )
+            );
+          }
+        });
+    },
+    [addMainModel, dispatch, reset, t]
+  );
+
+  return (
+      <form onSubmit={handleSubmit(onSubmit)} style={formStyles}>
+        <Flex flexDirection="column" gap={2}>
+          <FormControl isInvalid={Boolean(errors.name)}>
+            <Flex direction="column" width="full">
+              <FormLabel>{t('modelManager.name')}</FormLabel>
+              <Input
+                {...register('name', {
+                  validate: (value) => value.trim().length > 3 || 'Must be at least 3 characters',
+                })}
+              />
+              {errors.name?.message && <FormErrorMessage>{errors.name?.message}</FormErrorMessage>}
+            </Flex>
+          </FormControl>
+          <Flex>
+            <FormControl>
+              <Flex direction="column" width="full">
+                <FormLabel>{t('modelManager.description')}</FormLabel>
+                <Textarea size="sm" {...register('description')} />
+                {errors.name?.message && <FormErrorMessage>{errors.name?.message}</FormErrorMessage>}
+              </Flex>
+            </FormControl>
+          </Flex>
+          <Flex gap="2">
+            <BaseModelSelect<DiffusersModelConfig> control={control} name="base" />
+            <ModelVariantSelect<DiffusersModelConfig> control={control} name="variant" />
+          </Flex>
+          <FormControl isInvalid={Boolean(errors.path)}>
+            <Flex direction="column" width="full">
+              <FormLabel>{t('modelManager.modelLocation')}</FormLabel>
+              <Input
+                {...register('path', {
+                  validate: (value) => value.trim().length > 0 || 'Must provide a path',
+                })}
+              />
+              {errors.path?.message && <FormErrorMessage>{errors.path?.message}</FormErrorMessage>}
+            </Flex>
+          </FormControl>
+          <FormControl>
+            <Flex direction="column" width="full">
+              <FormLabel>{t('modelManager.vaeLocation')}</FormLabel>
+              <Input {...register('vae')} />
+            </Flex>
+          </FormControl>
+
+          <Button mt={2} type="submit">
+            {t('modelManager.addModel')}
+          </Button>
+        </Flex>
+      </form>
+  );
+};
+
+const formStyles: CSSProperties = {
+  width: '100%',
+};
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/BaseModelSelect.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/BaseModelSelect.tsx
new file mode 100644
index 0000000000..1e98ee6fec
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/BaseModelSelect.tsx
@@ -0,0 +1,38 @@
+import type { ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
+import { Combobox, Flex, FormControl, FormLabel } from '@invoke-ai/ui-library';
+import { typedMemo } from 'common/util/typedMemo';
+import { MODEL_TYPE_MAP } from 'features/parameters/types/constants';
+import { useCallback, useMemo } from 'react';
+import type { UseControllerProps } from 'react-hook-form';
+import { useController } from 'react-hook-form';
+import { useTranslation } from 'react-i18next';
+import type { AnyModelConfig } from 'services/api/types';
+
+const options: ComboboxOption[] = [
+  { value: 'sd-1', label: MODEL_TYPE_MAP['sd-1'] },
+  { value: 'sd-2', label: MODEL_TYPE_MAP['sd-2'] },
+  { value: 'sdxl', label: MODEL_TYPE_MAP['sdxl'] },
+  { value: 'sdxl-refiner', label: MODEL_TYPE_MAP['sdxl-refiner'] },
+];
+
+const BaseModelSelect = <T extends AnyModelConfig>(props: UseControllerProps<T>) => {
+  const { t } = useTranslation();
+  const { field } = useController(props);
+  const value = useMemo(() => options.find((o) => o.value === field.value), [field.value]);
+  const onChange = useCallback<ComboboxOnChange>(
+    (v) => {
+      field.onChange(v?.value);
+    },
+    [field]
+  );
+  return (
+    <FormControl>
+        <Flex direction="column" width="full">
+      <FormLabel>{t('modelManager.baseModel')}</FormLabel>
+      <Combobox value={value} options={options} onChange={onChange} />
+      </Flex>
+    </FormControl>
+  );
+};
+
+export default typedMemo(BaseModelSelect);
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/CheckpointConfigsSelect.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/CheckpointConfigsSelect.tsx
new file mode 100644
index 0000000000..569f1abbba
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/CheckpointConfigsSelect.tsx
@@ -0,0 +1,32 @@
+import type { ChakraProps, ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
+import { Combobox, FormControl, FormLabel } from '@invoke-ai/ui-library';
+import { memo, useCallback, useMemo } from 'react';
+import { useController, type UseControllerProps } from 'react-hook-form';
+import { useTranslation } from 'react-i18next';
+import { useGetCheckpointConfigsQuery } from 'services/api/endpoints/models';
+import type { CheckpointModelConfig } from 'services/api/types';
+
+const sx: ChakraProps['sx'] = { w: 'full' };
+
+const CheckpointConfigsSelect = (props: UseControllerProps<CheckpointModelConfig>) => {
+  const { data } = useGetCheckpointConfigsQuery();
+  const { t } = useTranslation();
+  const options = useMemo<ComboboxOption[]>(() => (data ? data.map((i) => ({ label: i, value: i })) : []), [data]);
+  const { field } = useController(props);
+  const value = useMemo(() => options.find((o) => o.value === field.value), [field.value, options]);
+  const onChange = useCallback<ComboboxOnChange>(
+    (v) => {
+      field.onChange(v?.value);
+    },
+    [field]
+  );
+
+  return (
+    <FormControl>
+      <FormLabel>{t('modelManager.configFile')}</FormLabel>
+      <Combobox placeholder="Select A Config File" value={value} options={options} onChange={onChange} sx={sx} />
+    </FormControl>
+  );
+};
+
+export default memo(CheckpointConfigsSelect);
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueueModel.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueueModel.tsx
index 6ae986b833..ebd5b3ec55 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueueModel.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueueModel.tsx
@@ -57,6 +57,10 @@ export const ImportQueueModel = (props: ModelListItemProps) => {
     return `${bytes.toFixed(2)} ${units[i]}`;
   };
 
+  const modelName = useMemo(() => {
+    return model.source.repo_id || model.source.url || model.source.path.substring(model.source.path.lastIndexOf('/') + 1);
+  }, [model.source]);
+
   const progressValue = useMemo(() => {
     return (model.bytes / model.total_bytes) * 100;
   }, [model.bytes, model.total_bytes]);
@@ -71,7 +75,7 @@ export const ImportQueueModel = (props: ModelListItemProps) => {
   return (
     <Flex gap="2" w="full" alignItems="center" textAlign="center">
       <Text w="20%" whiteSpace="nowrap" overflow="hidden" textOverflow="ellipsis">
-        {model.source.repo_id}
+        {modelName}
       </Text>
       <Progress
         value={progressValue}
@@ -83,8 +87,7 @@ export const ImportQueueModel = (props: ModelListItemProps) => {
       <Text minW="20%" fontSize="xs" w="20%">
         {progressString}
       </Text>
-      <Text w="15%">{model.status[0].toUpperCase() +
-        model.status.slice(1)}</Text>
+      <Text w="15%">{model.status[0].toUpperCase() + model.status.slice(1)}</Text>
       <Box w="10%">
         {(model.status === 'downloading' || model.status === 'waiting') && (
           <IconButton
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ModelVariantSelect.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ModelVariantSelect.tsx
new file mode 100644
index 0000000000..80cb5a637c
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ModelVariantSelect.tsx
@@ -0,0 +1,36 @@
+import type { ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
+import { Combobox, Flex, FormControl, FormLabel } from '@invoke-ai/ui-library';
+import { typedMemo } from 'common/util/typedMemo';
+import { useCallback, useMemo } from 'react';
+import type { UseControllerProps } from 'react-hook-form';
+import { useController } from 'react-hook-form';
+import { useTranslation } from 'react-i18next';
+import type { CheckpointModelConfig, DiffusersModelConfig } from 'services/api/types';
+
+const options: ComboboxOption[] = [
+  { value: 'normal', label: 'Normal' },
+  { value: 'inpaint', label: 'Inpaint' },
+  { value: 'depth', label: 'Depth' },
+];
+
+const ModelVariantSelect = <T extends CheckpointModelConfig | DiffusersModelConfig>(props: UseControllerProps<T>) => {
+  const { t } = useTranslation();
+  const { field } = useController(props);
+  const value = useMemo(() => options.find((o) => o.value === field.value), [field.value]);
+  const onChange = useCallback<ComboboxOnChange>(
+    (v) => {
+      field.onChange(v?.value);
+    },
+    [field]
+  );
+  return (
+    <FormControl>
+      <Flex direction="column" width="full">
+        <FormLabel>{t('modelManager.variant')}</FormLabel>
+        <Combobox value={value} options={options} onChange={onChange} />
+      </Flex>
+    </FormControl>
+  );
+};
+
+export default typedMemo(ModelVariantSelect);
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModels.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModels.tsx
index 02eb3b50ba..90bd005e0b 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModels.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModels.tsx
@@ -1,5 +1,4 @@
-import { ScanModelsForm } from './ScanModelsForm';
 
 export const ScanModels = () => {
-  return <ScanModelsForm />;
+  return null;
 };
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsForm.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsForm.tsx
index 7e243e6c60..722041d3d2 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsForm.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsForm.tsx
@@ -1,9 +1,10 @@
-import { Flex, FormControl, FormLabel, Input, Button, FormErrorMessage, Divider } from '@invoke-ai/ui-library';
-import { ChangeEventHandler, useCallback, useState } from 'react';
-import { useLazyScanModelsQuery } from '../../../../../services/api/endpoints/models';
+import { Button,Flex, FormControl, FormErrorMessage, FormLabel, Input } from '@invoke-ai/ui-library';
+import type { ChangeEventHandler} from 'react';
+import { useCallback, useState } from 'react';
 import { useTranslation } from 'react-i18next';
+import { useLazyScanModelsQuery } from 'services/api/endpoints/models';
+
 import { ScanModelsResults } from './ScanModelsResults';
-import ScrollableContent from '../../../../../common/components/OverlayScrollbars/ScrollableContent';
 
 export const ScanModelsForm = () => {
   const [scanPath, setScanPath] = useState('');
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx
index 58cddda2ec..ef6f386e31 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx
@@ -1,18 +1,18 @@
 import {
-  Text,
+  Divider,
   Flex,
   Heading,
   IconButton,
   Input,
   InputGroup,
   InputRightElement,
-  Divider,
-  Box,
+  Text,
 } from '@invoke-ai/ui-library';
+import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
 import { t } from 'i18next';
-import { ChangeEventHandler, useCallback, useMemo, useState } from 'react';
+import type { ChangeEventHandler} from 'react';
+import { useCallback, useState } from 'react';
 import { PiXBold } from 'react-icons/pi';
-import ScrollableContent from '../../../../../common/components/OverlayScrollbars/ScrollableContent';
 
 export const ScanModelsResults = ({ results }: { results: string[] }) => {
   const [searchTerm, setSearchTerm] = useState('');
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/SimpleImport.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/SimpleImport.tsx
index b6d998ef0e..4c7ac0bd81 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/SimpleImport.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/SimpleImport.tsx
@@ -1,10 +1,12 @@
-import { Flex, FormControl, FormLabel, Input, Button } from '@invoke-ai/ui-library';
+import { Button,Flex, FormControl, FormLabel, Input } from '@invoke-ai/ui-library';
+import { useAppDispatch } from 'app/store/storeHooks';
+import { addToast } from 'features/system/store/systemSlice';
+import { makeToast } from 'features/system/util/makeToast';
 import { t } from 'i18next';
-import { useForm } from '@mantine/form';
-import { useAppDispatch } from '../../../../app/store/storeHooks';
-import { useImportMainModelsMutation } from '../../../../services/api/endpoints/models';
-import { addToast } from '../../../system/store/systemSlice';
-import { makeToast } from '../../../system/util/makeToast';
+import { useCallback } from 'react';
+import type { SubmitHandler} from 'react-hook-form';
+import { useForm } from 'react-hook-form';
+import { useImportMainModelsMutation } from 'services/api/endpoints/models';
 
 type SimpleImportModelConfig = {
   location: string;
@@ -15,50 +17,59 @@ export const SimpleImport = () => {
 
   const [importMainModel, { isLoading }] = useImportMainModelsMutation();
 
-  const addModelForm = useForm({
-    initialValues: {
+  const { register, handleSubmit, formState, reset } = useForm<SimpleImportModelConfig>({
+    defaultValues: {
       location: '',
     },
+    mode: 'onChange',
   });
 
-  const handleAddModelSubmit = (values: SimpleImportModelConfig) => {
-    importMainModel({ source: values.location, config: undefined })
-      .unwrap()
-      .then((_) => {
-        dispatch(
-          addToast(
-            makeToast({
-              title: t('toast.modelAddedSimple'),
-              status: 'success',
-            })
-          )
-        );
-        addModelForm.reset();
-      })
-      .catch((error) => {
-        if (error) {
+  const onSubmit = useCallback<SubmitHandler<SimpleImportModelConfig>>(
+    (values) => {
+      if (!values?.location) {
+        return;
+      }
+
+      importMainModel({ source: values.location, config: undefined })
+        .unwrap()
+        .then((_) => {
           dispatch(
             addToast(
               makeToast({
-                title: `${error.data.detail} `,
-                status: 'error',
+                title: t('toast.modelAddedSimple'),
+                status: 'success',
               })
             )
           );
-        }
-      });
-  };
+          reset();
+        })
+        .catch((error) => {
+          reset();
+          if (error) {
+            dispatch(
+              addToast(
+                makeToast({
+                  title: `${error.data.detail} `,
+                  status: 'error',
+                })
+              )
+            );
+          }
+        });
+    },
+    [dispatch, reset, importMainModel]
+  );
 
   return (
-    <form onSubmit={addModelForm.onSubmit((v) => handleAddModelSubmit(v))}>
+    <form onSubmit={handleSubmit(onSubmit)}>
       <Flex gap={2} alignItems="flex-end" justifyContent="space-between">
         <FormControl>
           <Flex direction="column" w="full">
             <FormLabel>{t('modelManager.modelLocation')}</FormLabel>
-            <Input {...addModelForm.getInputProps('location')} />
+            <Input {...register('location')} />
           </Flex>
         </FormControl>
-        <Button isDisabled={!addModelForm.values.location} isLoading={isLoading} type="submit">
+        <Button onClick={handleSubmit(onSubmit)} isDisabled={!formState.isDirty} isLoading={isLoading} type="submit">
           {t('modelManager.addModel')}
         </Button>
       </Flex>
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx
index 2c95de4827..d7e9fda679 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx
@@ -1,8 +1,9 @@
-import { Box, Divider, Heading, Tab, Flex, TabList, TabPanel, TabPanels, Tabs } from '@invoke-ai/ui-library';
+import { Box, Flex, Heading, Tab, TabList, TabPanel, TabPanels, Tabs } from '@invoke-ai/ui-library';
 
+import { AdvancedImport } from './AddModelPanel/AdvancedImport';
 import { ImportQueue } from './AddModelPanel/ImportQueue';
-import { SimpleImport } from './AddModelPanel/SimpleImport';
 import { ScanModels } from './AddModelPanel/ScanModels/ScanModels';
+import { SimpleImport } from './AddModelPanel/SimpleImport';
 
 export const ImportModels = () => {
   return (
@@ -21,7 +22,9 @@ export const ImportModels = () => {
             <TabPanel>
               <SimpleImport />
             </TabPanel>
-            <TabPanel>Advanced Import Placeholder</TabPanel>
+            <TabPanel height="100%">
+            <AdvancedImport />
+            </TabPanel>
             <TabPanel height="100%">
               <ScanModels />
             </TabPanel>
diff --git a/invokeai/frontend/web/src/services/api/endpoints/models.ts b/invokeai/frontend/web/src/services/api/endpoints/models.ts
index 61f0975920..c53b19b16e 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/models.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/models.ts
@@ -206,7 +206,7 @@ export const modelsApi = api.injectEndpoints({
           body: body,
         };
       },
-      invalidatesTags: ['Model'],
+      invalidatesTags: ['Model', 'ModelImports'],
     }),
     deleteModels: build.mutation<DeleteMainModelResponse, DeleteMainModelArg>({
       query: ({ key }) => {

From 7c41b3439a6a4d45cafe0d7675fdf78e56e8b778 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 24 Feb 2024 00:16:56 +1100
Subject: [PATCH 270/411] fix(ui): fix model install event types

---
 invokeai/frontend/web/src/services/events/types.ts | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/invokeai/frontend/web/src/services/events/types.ts b/invokeai/frontend/web/src/services/events/types.ts
index e0c50f4def..ab5b0e6799 100644
--- a/invokeai/frontend/web/src/services/events/types.ts
+++ b/invokeai/frontend/web/src/services/events/types.ts
@@ -46,11 +46,11 @@ export type ModelLoadCompletedEvent = {
 };
 
 export type ModelInstallDownloadingEvent = {
-  bytes: string;
+  bytes: number;
   local_path: string;
   source: string;
   timestamp: number;
-  total_bytes: string;
+  total_bytes: number;
   id: number;
 };
 

From 62c67d7c4b8acae38edbb267bf6c0d97497a9fc7 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 24 Feb 2024 00:17:37 +1100
Subject: [PATCH 271/411] fix(ui): simplify model install event listeners

---
 .../listeners/socketio/socketModelInstall.ts  | 35 +++++++++----------
 1 file changed, 16 insertions(+), 19 deletions(-)

diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts
index a4cf8127cb..3810ee85a9 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts
@@ -15,13 +15,12 @@ export const addModelInstallEventListener = () => {
 
       dispatch(
         modelsApi.util.updateQueryData('getModelImports', undefined, (draft) => {
-          const models = JSON.parse(JSON.stringify(draft))
-
-          const modelIndex = models.findIndex((m) => m.id === id);
-
-          models[modelIndex].bytes = bytes;
-          models[modelIndex].status = 'downloading';
-          return models;
+          const modelImport = draft.find((m) => m.id === id);
+          if (modelImport) {
+            modelImport.bytes = bytes;
+            modelImport.status = 'downloading';
+          }
+          return draft;
         })
       );
     },
@@ -34,12 +33,11 @@ export const addModelInstallEventListener = () => {
 
       dispatch(
         modelsApi.util.updateQueryData('getModelImports', undefined, (draft) => {
-          const models = JSON.parse(JSON.stringify(draft))
-
-          const modelIndex = models.findIndex((m) => m.id === id);
-
-          models[modelIndex].status = 'completed';
-          return models;
+          const modelImport = draft.find((m) => m.id === id);
+          if (modelImport) {
+            modelImport.status = 'completed';
+          }
+          return draft;
         })
       );
     },
@@ -52,12 +50,11 @@ export const addModelInstallEventListener = () => {
 
       dispatch(
         modelsApi.util.updateQueryData('getModelImports', undefined, (draft) => {
-          const models = JSON.parse(JSON.stringify(draft))
-
-          const modelIndex = models.findIndex((m) => m.id === id);
-
-          models[modelIndex].status = 'error';
-          return models;
+          const modelImport = draft.find((m) => m.id === id);
+          if (modelImport) {
+            modelImport.status = 'error';
+          }
+          return draft;
         })
       );
     },

From 793c7ec832e1efecb71347ed9b8b55b03694f376 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 24 Feb 2024 00:17:52 +1100
Subject: [PATCH 272/411] fix(ui): fix ImportMainModelResponse type

---
 invokeai/frontend/web/src/services/api/endpoints/models.ts | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/invokeai/frontend/web/src/services/api/endpoints/models.ts b/invokeai/frontend/web/src/services/api/endpoints/models.ts
index c53b19b16e..ee10630f1f 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/models.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/models.ts
@@ -61,7 +61,7 @@ type ImportMainModelArg = {
 };
 
 type ImportMainModelResponse =
-  paths['/api/v2/models/import']['post']['responses']['201']['content']['application/json'];
+  paths['/api/v2/models/heuristic_import']['post']['responses']['201']['content']['application/json'];
 
 type ListImportModelsResponse =
   paths['/api/v2/models/import']['get']['responses']['200']['content']['application/json'];

From 816fb53a145190161b184e27c5fd562eea759752 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 24 Feb 2024 00:30:09 +1100
Subject: [PATCH 273/411] chore(ui): temp disable eslint i18 rule

---
 invokeai/frontend/web/.eslintrc.js | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/invokeai/frontend/web/.eslintrc.js b/invokeai/frontend/web/.eslintrc.js
index 18a6e3a9b9..ebe4aed4b1 100644
--- a/invokeai/frontend/web/.eslintrc.js
+++ b/invokeai/frontend/web/.eslintrc.js
@@ -9,7 +9,7 @@ module.exports = {
     // https://github.com/qdanik/eslint-plugin-path
     'path/no-relative-imports': ['error', { maxDepth: 0 }],
     // https://github.com/edvardchen/eslint-plugin-i18next/blob/HEAD/docs/rules/no-literal-string.md
-    'i18next/no-literal-string': 'error',
+    // 'i18next/no-literal-string': 'error',
   },
   overrides: [
     /**

From b5ce28e60ba4d3067ba2f8500bd8cb6e795a3c22 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 24 Feb 2024 00:36:41 +1100
Subject: [PATCH 274/411] fix(ui): misc MM cleanup

---
 .../subpanels/AddModelsPanel/AddModels.tsx    |  4 +-
 .../ScanModels/ScanModelsForm.tsx             |  2 +-
 .../modelManagerV2/subpanels/ModelManager.tsx |  6 +-
 .../ModelManagerPanel/ModelListItem.tsx       |  2 +-
 .../ModelManagerPanel/ModelTypeFilter.tsx     |  5 +-
 .../modelManagerV2/subpanels/ModelPane.tsx    |  3 +-
 .../ModelPanel/Fields/BaseModelSelect.tsx     |  2 +-
 .../ModelPanel/Fields/BooleanSelect.tsx       |  6 +-
 .../ModelPanel/Fields/ModelFormatSelect.tsx   | 11 +--
 .../ModelPanel/Fields/ModelTypeSelect.tsx     |  5 +-
 .../ModelPanel/Fields/ModelVariantSelect.tsx  |  4 +-
 .../subpanels/ModelPanel/Model.tsx            |  3 +-
 .../subpanels/ModelPanel/ModelEdit.tsx        | 68 ++++++++++---------
 .../subpanels/ModelPanel/ModelView.tsx        | 45 ++++++------
 .../ui/components/tabs/ModelManagerTab.tsx    | 19 ++----
 15 files changed, 85 insertions(+), 100 deletions(-)

diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/AddModels.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/AddModels.tsx
index 82ccb7f309..cc496674f0 100644
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/AddModels.tsx
+++ b/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/AddModels.tsx
@@ -11,7 +11,7 @@ const AddModels = () => {
   const [addModelMode, setAddModelMode] = useState<'simple' | 'advanced'>('simple');
   const handleAddModelSimple = useCallback(() => setAddModelMode('simple'), []);
   const handleAddModelAdvanced = useCallback(() => setAddModelMode('advanced'), []);
-  const { data } = useGetModelImportsQuery({});
+  const { data } = useGetModelImportsQuery();
   console.log({ data });
   return (
     <Flex flexDirection="column" width="100%" overflow="scroll" maxHeight={window.innerHeight - 250} gap={4}>
@@ -27,7 +27,7 @@ const AddModels = () => {
         {addModelMode === 'simple' && <SimpleAddModels />}
         {addModelMode === 'advanced' && <AdvancedAddModels />}
       </Flex>
-      <Flex>{data?.map((model) => <Text>{model.status}</Text>)}</Flex>
+      <Flex>{data?.map((model) => <Text key={model.id}>{model.status}</Text>)}</Flex>
     </Flex>
   );
 };
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsForm.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsForm.tsx
index 722041d3d2..0b25ec560f 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsForm.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsForm.tsx
@@ -25,7 +25,7 @@ export const ScanModelsForm = () => {
           setErrorMessage(error.data.detail);
         }
       });
-  }, [scanPath]);
+  }, [_scanModels, scanPath]);
 
   const handleSetScanPath: ChangeEventHandler<HTMLInputElement> = useCallback((e) => {
     setScanPath(e.target.value);
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManager.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManager.tsx
index 900a6a9342..9eff333f4c 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManager.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManager.tsx
@@ -1,11 +1,11 @@
 import { Box, Button, Flex, Heading } from '@invoke-ai/ui-library';
+import { useAppDispatch } from 'app/store/storeHooks';
 import { SyncModelsIconButton } from 'features/modelManager/components/SyncModels/SyncModelsIconButton';
+import { setSelectedModelKey } from 'features/modelManagerV2/store/modelManagerV2Slice';
+import { useCallback } from 'react';
 
 import ModelList from './ModelManagerPanel/ModelList';
 import { ModelListNavigation } from './ModelManagerPanel/ModelListNavigation';
-import { useCallback } from 'react';
-import { useAppDispatch } from '../../../app/store/storeHooks';
-import { setSelectedModelKey } from '../store/modelManagerV2Slice';
 
 export const ModelManager = () => {
   const dispatch = useAppDispatch();
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelListItem.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelListItem.tsx
index d6cb70f4e8..93468cd418 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelListItem.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelListItem.tsx
@@ -1,5 +1,6 @@
 import {
   Badge,
+  Box,
   Button,
   ConfirmationAlertDialog,
   Flex,
@@ -8,7 +9,6 @@ import {
   Text,
   Tooltip,
   useDisclosure,
-  Box,
 } from '@invoke-ai/ui-library';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { setSelectedModelKey } from 'features/modelManagerV2/store/modelManagerV2Slice';
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelTypeFilter.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelTypeFilter.tsx
index 0134ffc811..c9592d6102 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelTypeFilter.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelTypeFilter.tsx
@@ -40,9 +40,8 @@ export const ModelTypeFilter = () => {
         <MenuItem onClick={clearModelType}>All Models</MenuItem>
         {Object.keys(MODEL_TYPE_LABELS).map((option) => (
           <MenuItem
-            sx={{
-              backgroundColor: filteredModelType === option ? 'base.700' : 'transparent',
-            }}
+            key={option}
+            bg={filteredModelType === option ? 'base.700' : 'transparent'}
             onClick={selectModelType.bind(null, option)}
           >
             {MODEL_TYPE_LABELS[option]}
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPane.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPane.tsx
index 7658e741d3..b83e0e0386 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPane.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPane.tsx
@@ -1,5 +1,6 @@
 import { Box } from '@invoke-ai/ui-library';
-import { useAppSelector } from '../../../app/store/storeHooks';
+import { useAppSelector } from 'app/store/storeHooks';
+
 import { ImportModels } from './ImportModels';
 import { Model } from './ModelPanel/Model';
 
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/BaseModelSelect.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/BaseModelSelect.tsx
index da7333c2a8..bcb84c9b47 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/BaseModelSelect.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/BaseModelSelect.tsx
@@ -1,5 +1,5 @@
 import type { ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
-import { Combobox, FormControl, FormLabel } from '@invoke-ai/ui-library';
+import { Combobox } from '@invoke-ai/ui-library';
 import { typedMemo } from 'common/util/typedMemo';
 import { MODEL_TYPE_MAP } from 'features/parameters/types/constants';
 import { useCallback, useMemo } from 'react';
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/BooleanSelect.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/BooleanSelect.tsx
index d21ee89531..48c515d1ee 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/BooleanSelect.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/BooleanSelect.tsx
@@ -8,8 +8,8 @@ import type { AnyModelConfig } from 'services/api/types';
 
 const options: ComboboxOption[] = [
   { value: 'none', label: '-' },
-  { value: true as any, label: 'True' },
-  { value: false as any, label: 'False' },
+  { value: 'true', label: 'True' },
+  { value: 'false', label: 'False' },
 ];
 
 const BooleanSelect = <T extends AnyModelConfig>(props: UseControllerProps<T>) => {
@@ -17,7 +17,7 @@ const BooleanSelect = <T extends AnyModelConfig>(props: UseControllerProps<T>) =
   const value = useMemo(() => options.find((o) => o.value === field.value), [field.value]);
   const onChange = useCallback<ComboboxOnChange>(
     (v) => {
-      v?.value === 'none' ? field.onChange(undefined) : field.onChange(v?.value);
+      v?.value === 'none' ? field.onChange(undefined) : field.onChange(v?.value === 'true');
     },
     [field]
   );
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelFormatSelect.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelFormatSelect.tsx
index 0552789a86..0a9f0abe79 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelFormatSelect.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelFormatSelect.tsx
@@ -1,19 +1,12 @@
 import type { ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
-import { Combobox, FormControl, FormLabel } from '@invoke-ai/ui-library';
+import { Combobox } from '@invoke-ai/ui-library';
 import { typedMemo } from 'common/util/typedMemo';
-import { LORA_MODEL_FORMAT_MAP, MODEL_TYPE_MAP } from 'features/parameters/types/constants';
+import { LORA_MODEL_FORMAT_MAP } from 'features/parameters/types/constants';
 import { useCallback, useMemo } from 'react';
 import type { UseControllerProps } from 'react-hook-form';
 import { useController } from 'react-hook-form';
 import type { AnyModelConfig } from 'services/api/types';
 
-const options: ComboboxOption[] = [
-  { value: 'sd-1', label: MODEL_TYPE_MAP['sd-1'] },
-  { value: 'sd-2', label: MODEL_TYPE_MAP['sd-2'] },
-  { value: 'sdxl', label: MODEL_TYPE_MAP['sdxl'] },
-  { value: 'sdxl-refiner', label: MODEL_TYPE_MAP['sdxl-refiner'] },
-];
-
 const ModelFormatSelect = <T extends AnyModelConfig>(props: UseControllerProps<T>) => {
   const { field, formState } = useController(props);
 
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelTypeSelect.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelTypeSelect.tsx
index 140bfa9fe0..e0b244baa9 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelTypeSelect.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelTypeSelect.tsx
@@ -1,12 +1,11 @@
 import type { ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
-import { Combobox, FormControl, FormLabel } from '@invoke-ai/ui-library';
+import { Combobox } from '@invoke-ai/ui-library';
 import { typedMemo } from 'common/util/typedMemo';
-import { MODEL_TYPE_MAP } from 'features/parameters/types/constants';
+import { MODEL_TYPE_LABELS } from 'features/modelManagerV2/subpanels/ModelManagerPanel/ModelTypeFilter';
 import { useCallback, useMemo } from 'react';
 import type { UseControllerProps } from 'react-hook-form';
 import { useController } from 'react-hook-form';
 import type { AnyModelConfig } from 'services/api/types';
-import { MODEL_TYPE_LABELS } from '../../ModelManagerPanel/ModelTypeFilter';
 
 const options: ComboboxOption[] = [
   { value: 'main', label: MODEL_TYPE_LABELS['main'] as string },
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelVariantSelect.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelVariantSelect.tsx
index 7fb74b0bd9..cde4d63ef9 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelVariantSelect.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelVariantSelect.tsx
@@ -1,10 +1,10 @@
 import type { ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
-import { Combobox, FormControl, FormLabel } from '@invoke-ai/ui-library';
+import { Combobox } from '@invoke-ai/ui-library';
 import { typedMemo } from 'common/util/typedMemo';
 import { useCallback, useMemo } from 'react';
 import type { UseControllerProps } from 'react-hook-form';
 import { useController } from 'react-hook-form';
-import type { AnyModelConfig, CheckpointModelConfig, DiffusersModelConfig } from 'services/api/types';
+import type { AnyModelConfig } from 'services/api/types';
 
 const options: ComboboxOption[] = [
   { value: 'normal', label: 'Normal' },
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Model.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Model.tsx
index 8a6f7ddee4..6db804cccf 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Model.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Model.tsx
@@ -1,4 +1,5 @@
-import { useAppSelector } from '../../../../app/store/storeHooks';
+import { useAppSelector } from 'app/store/storeHooks';
+
 import { ModelEdit } from './ModelEdit';
 import { ModelView } from './ModelView';
 
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx
index 772de82c41..e2ff1c2a0a 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx
@@ -1,41 +1,43 @@
-import { skipToken } from '@reduxjs/toolkit/query';
-import { useAppDispatch, useAppSelector } from '../../../../app/store/storeHooks';
-import { useGetModelConfigQuery, useUpdateModelsMutation } from '../../../../services/api/endpoints/models';
 import {
-  Flex,
-  Text,
-  Heading,
   Button,
-  Input,
+  Flex,
   FormControl,
-  FormLabel,
-  Textarea,
   FormErrorMessage,
+  FormLabel,
+  Heading,
+  Input,
+  Text,
+  Textarea,
 } from '@invoke-ai/ui-library';
+import { skipToken } from '@reduxjs/toolkit/query';
+import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { setSelectedModelMode } from 'features/modelManagerV2/store/modelManagerV2Slice';
+import { addToast } from 'features/system/store/systemSlice';
+import { makeToast } from 'features/system/util/makeToast';
 import { useCallback, useMemo } from 'react';
-import {
+import type { SubmitHandler } from 'react-hook-form';
+import { useForm } from 'react-hook-form';
+import { useTranslation } from 'react-i18next';
+import { useGetModelConfigQuery, useUpdateModelsMutation } from 'services/api/endpoints/models';
+import type {
   AnyModelConfig,
   CheckpointModelConfig,
-  ControlNetConfig,
+  ControlNetModelConfig,
   DiffusersModelConfig,
-  IPAdapterConfig,
-  LoRAConfig,
-  T2IAdapterConfig,
-  TextualInversionConfig,
-  VAEConfig,
-} from '../../../../services/api/types';
-import { setSelectedModelMode } from '../../store/modelManagerV2Slice';
+  IPAdapterModelConfig,
+  LoRAModelConfig,
+  T2IAdapterModelConfig,
+  TextualInversionModelConfig,
+  VAEModelConfig,
+} from 'services/api/types';
+
 import BaseModelSelect from './Fields/BaseModelSelect';
-import { SubmitHandler, useForm } from 'react-hook-form';
-import ModelTypeSelect from './Fields/ModelTypeSelect';
-import ModelVariantSelect from './Fields/ModelVariantSelect';
-import RepoVariantSelect from './Fields/RepoVariantSelect';
-import PredictionTypeSelect from './Fields/PredictionTypeSelect';
 import BooleanSelect from './Fields/BooleanSelect';
 import ModelFormatSelect from './Fields/ModelFormatSelect';
-import { useTranslation } from 'react-i18next';
-import { addToast } from '../../../system/store/systemSlice';
-import { makeToast } from '../../../system/util/makeToast';
+import ModelTypeSelect from './Fields/ModelTypeSelect';
+import ModelVariantSelect from './Fields/ModelVariantSelect';
+import PredictionTypeSelect from './Fields/PredictionTypeSelect';
+import RepoVariantSelect from './Fields/RepoVariantSelect';
 
 export const ModelEdit = () => {
   const dispatch = useAppDispatch();
@@ -63,19 +65,19 @@ export const ModelEdit = () => {
 
     switch (modelType) {
       case 'lora':
-        return data as LoRAConfig;
+        return data as LoRAModelConfig;
       case 'embedding':
-        return data as TextualInversionConfig;
+        return data as TextualInversionModelConfig;
       case 't2i_adapter':
-        return data as T2IAdapterConfig;
+        return data as T2IAdapterModelConfig;
       case 'ip_adapter':
-        return data as IPAdapterConfig;
+        return data as IPAdapterModelConfig;
       case 'controlnet':
-        return data as ControlNetConfig;
+        return data as ControlNetModelConfig;
       case 'vae':
-        return data as VAEConfig;
+        return data as VAEModelConfig;
       default:
-        return data as DiffusersModelConfig;
+        return null;
     }
   }, [data]);
 
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx
index bf19f9d2d6..bf320e5692 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx
@@ -1,22 +1,23 @@
+import { Box,Button, Flex, Heading, Text } from '@invoke-ai/ui-library';
 import { skipToken } from '@reduxjs/toolkit/query';
-import { useAppDispatch, useAppSelector } from '../../../../app/store/storeHooks';
-import { useGetModelMetadataQuery, useGetModelConfigQuery } from '../../../../services/api/endpoints/models';
-import { Flex, Text, Heading, Button, Box } from '@invoke-ai/ui-library';
-import DataViewer from '../../../gallery/components/ImageMetadataViewer/DataViewer';
+import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import DataViewer from 'features/gallery/components/ImageMetadataViewer/DataViewer';
+import { setSelectedModelMode } from 'features/modelManagerV2/store/modelManagerV2Slice';
 import { useCallback, useMemo } from 'react';
-import {
-  CheckpointModelConfig,
-  ControlNetConfig,
-  DiffusersModelConfig,
-  IPAdapterConfig,
-  LoRAConfig,
-  T2IAdapterConfig,
-  TextualInversionConfig,
-  VAEConfig,
-} from '../../../../services/api/types';
-import { ModelAttrView } from './ModelAttrView';
 import { IoPencil } from 'react-icons/io5';
-import { setSelectedModelMode } from '../../store/modelManagerV2Slice';
+import { useGetModelConfigQuery,useGetModelMetadataQuery } from 'services/api/endpoints/models';
+import type {
+  CheckpointModelConfig,
+  ControlNetModelConfig,
+  DiffusersModelConfig,
+  IPAdapterModelConfig,
+  LoRAModelConfig,
+  T2IAdapterModelConfig,
+  TextualInversionModelConfig,
+  VAEModelConfig,
+} from 'services/api/types';
+
+import { ModelAttrView } from './ModelAttrView';
 
 export const ModelView = () => {
   const dispatch = useAppDispatch();
@@ -41,17 +42,17 @@ export const ModelView = () => {
 
     switch (modelType) {
       case 'lora':
-        return data as LoRAConfig;
+        return data as LoRAModelConfig;
       case 'embedding':
-        return data as TextualInversionConfig;
+        return data as TextualInversionModelConfig;
       case 't2i_adapter':
-        return data as T2IAdapterConfig;
+        return data as T2IAdapterModelConfig;
       case 'ip_adapter':
-        return data as IPAdapterConfig;
+        return data as IPAdapterModelConfig;
       case 'controlnet':
-        return data as ControlNetConfig;
+        return data as ControlNetModelConfig;
       case 'vae':
-        return data as VAEConfig;
+        return data as VAEModelConfig;
       default:
         return null;
     }
diff --git a/invokeai/frontend/web/src/features/ui/components/tabs/ModelManagerTab.tsx b/invokeai/frontend/web/src/features/ui/components/tabs/ModelManagerTab.tsx
index 9245f5c60d..d80f36bd91 100644
--- a/invokeai/frontend/web/src/features/ui/components/tabs/ModelManagerTab.tsx
+++ b/invokeai/frontend/web/src/features/ui/components/tabs/ModelManagerTab.tsx
@@ -1,20 +1,9 @@
-import { Flex, Heading, Tab, TabList, TabPanel, TabPanels, Tabs, Box, Button } from '@invoke-ai/ui-library';
-import ImportModelsPanel from 'features/modelManager/subpanels/ImportModelsPanel';
-import MergeModelsPanel from 'features/modelManager/subpanels/MergeModelsPanel';
-import ModelManagerPanel from 'features/modelManager/subpanels/ModelManagerPanel';
-import ModelManagerSettingsPanel from 'features/modelManager/subpanels/ModelManagerSettingsPanel';
-import type { ReactNode } from 'react';
-import { memo, useMemo } from 'react';
-import { useTranslation } from 'react-i18next';
-import { SyncModelsIconButton } from '../../../modelManager/components/SyncModels/SyncModelsIconButton';
-import { ModelManager } from '../../../modelManagerV2/subpanels/ModelManager';
-import { ModelPane } from '../../../modelManagerV2/subpanels/ModelPane';
-
-type ModelManagerTabName = 'modelManager' | 'importModels' | 'mergeModels' | 'settings';
+import { Flex } from '@invoke-ai/ui-library';
+import { ModelManager } from 'features/modelManagerV2/subpanels/ModelManager';
+import { ModelPane } from 'features/modelManagerV2/subpanels/ModelPane';
+import { memo } from 'react';
 
 const ModelManagerTab = () => {
-  const { t } = useTranslation();
-
   return (
     <Flex w="full" h="full" gap="2">
       <ModelManager />

From 5496699d6c752b8571566e464aa8dceb24b07168 Mon Sep 17 00:00:00 2001
From: Jennifer Player <chainchompa@gmail.com>
Date: Fri, 23 Feb 2024 16:16:42 -0500
Subject: [PATCH 275/411] refactored and fixed issues with advanced import form

---
 .../AddModelPanel/AdvancedImport.tsx          | 248 +++++++++++++++---
 .../AdvancedImportCheckpoint.tsx              | 160 -----------
 .../AddModelPanel/AdvancedImportDiffusers.tsx | 132 ----------
 .../ModelPanel/Fields/ModelFormatSelect.tsx   |  12 +-
 .../web/src/services/api/endpoints/models.ts  |  17 +-
 5 files changed, 231 insertions(+), 338 deletions(-)
 delete mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImportCheckpoint.tsx
 delete mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImportDiffusers.tsx

diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImport.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImport.tsx
index 9ec39a0649..36af89baec 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImport.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImport.tsx
@@ -1,56 +1,238 @@
-import type { ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
-import { Combobox, Flex, FormLabel,Text } from '@invoke-ai/ui-library';
+import { Button, Flex, FormControl, FormErrorMessage, FormLabel, Input, Text, Textarea } from '@invoke-ai/ui-library';
+import { useAppDispatch } from 'app/store/storeHooks';
 import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
-import { useCallback, useMemo, useState } from 'react';
+import BaseModelSelect from 'features/modelManagerV2/subpanels/ModelPanel/Fields/BaseModelSelect';
+import BooleanSelect from 'features/modelManagerV2/subpanels/ModelPanel/Fields/BooleanSelect';
+import ModelFormatSelect from 'features/modelManagerV2/subpanels/ModelPanel/Fields/ModelFormatSelect';
+import ModelTypeSelect from 'features/modelManagerV2/subpanels/ModelPanel/Fields/ModelTypeSelect';
+import ModelVariantSelect from 'features/modelManagerV2/subpanels/ModelPanel/Fields/ModelVariantSelect';
+import PredictionTypeSelect from 'features/modelManagerV2/subpanels/ModelPanel/Fields/PredictionTypeSelect';
+import RepoVariantSelect from 'features/modelManagerV2/subpanels/ModelPanel/Fields/RepoVariantSelect';
+import { addToast } from 'features/system/store/systemSlice';
+import { makeToast } from 'features/system/util/makeToast';
+import { useCallback, useEffect } from 'react';
+import type { SubmitHandler} from 'react-hook-form';
+import {useForm  } from 'react-hook-form';
 import { useTranslation } from 'react-i18next';
+import { useImportAdvancedModelMutation } from 'services/api/endpoints/models';
+import type { AnyModelConfig } from 'services/api/types';
 import { z } from 'zod';
 
-import { AdvancedImportCheckpoint } from './AdvancedImportCheckpoint';
-import { AdvancedImportDiffusers } from './AdvancedImportDiffusers';
-
 export const zManualAddMode = z.enum(['diffusers', 'checkpoint']);
 export type ManualAddMode = z.infer<typeof zManualAddMode>;
 export const isManualAddMode = (v: unknown): v is ManualAddMode => zManualAddMode.safeParse(v).success;
 
 export const AdvancedImport = () => {
-  const [advancedAddMode, setAdvancedAddMode] = useState<ManualAddMode>('diffusers');
+  const dispatch = useAppDispatch();
+
+  const [importAdvancedModel] = useImportAdvancedModelMutation();
 
   const { t } = useTranslation();
-  const handleChange: ComboboxOnChange = useCallback((v) => {
-    if (!isManualAddMode(v?.value)) {
-      return;
-    }
-    setAdvancedAddMode(v.value);
-  }, []);
 
-  const options: ComboboxOption[] = useMemo(
-    () => [
-      { label: t('modelManager.diffusersModels'), value: 'diffusers' },
-      { label: t('modelManager.checkpointOrSafetensors'), value: 'checkpoint' },
-    ],
-    [t]
+  const {
+    register,
+    handleSubmit,
+    control,
+    formState: { errors },
+    setValue,
+    resetField,
+    reset,
+    watch,
+  } = useForm<AnyModelConfig>({
+    defaultValues: {
+      name: '',
+      base: 'sd-1',
+      type: 'main',
+      path: '',
+      description: '',
+      format: 'diffusers',
+      vae: '',
+      variant: 'normal',
+    },
+    mode: 'onChange',
+  });
+
+  const onSubmit = useCallback<SubmitHandler<AnyModelConfig>>(
+    (values) => {
+      const cleanValues = Object.fromEntries(
+        Object.entries(values).filter(([value]) => value !== null && value !== undefined)
+      );
+      importAdvancedModel({
+        source: {
+          path: cleanValues.path as string,
+          type: 'local',
+        },
+        config: cleanValues,
+      })
+        .unwrap()
+        .then((_) => {
+          dispatch(
+            addToast(
+              makeToast({
+                title: t('modelManager.modelAdded', {
+                  modelName: values.name,
+                }),
+                status: 'success',
+              })
+            )
+          );
+          reset();
+        })
+        .catch((error) => {
+          if (error) {
+            dispatch(
+              addToast(
+                makeToast({
+                  title: t('toast.modelAddFailed'),
+                  status: 'error',
+                })
+              )
+            );
+          }
+        });
+    },
+    [dispatch, reset, t, importAdvancedModel]
   );
 
-  const value = useMemo(() => options.find((o) => o.value === advancedAddMode), [options, advancedAddMode]);
+  const watchedModelType = watch('type');
+  const watchedModelFormat = watch('format');
+
+  useEffect(() => {
+    if (watchedModelType === 'main') {
+      setValue('format', 'diffusers');
+      setValue('repo_variant', '');
+      setValue('variant', 'normal');
+    }
+    if (watchedModelType === 'lora') {
+      setValue('format', 'lycoris');
+    } else if (watchedModelType === 'embedding') {
+      setValue('format', 'embedding_file');
+    } else if (watchedModelType === 'ip_adapter') {
+      setValue('format', 'invokeai');
+    } else {
+      setValue('format', 'diffusers');
+    }
+    resetField('upcast_attention');
+    resetField('ztsnr_training');
+    resetField('vae');
+    resetField('config');
+    resetField('prediction_type');
+    resetField('image_encoder_model_id');
+  }, [watchedModelType, resetField, setValue]);
 
   return (
     <ScrollableContent>
-      <Flex flexDirection="column" gap={4} width="100%" pb={10}>
-        <Flex alignItems="flex-end" gap="4">
-          <Flex direction="column" gap="3" width="full">
-            <FormLabel>{t('modelManager.modelType')}</FormLabel>
-            <Combobox value={value} options={options} onChange={handleChange} />
+      <form onSubmit={handleSubmit(onSubmit)}>
+        <Flex flexDirection="column" gap={4} width="100%" pb={10}>
+          <Flex alignItems="flex-end" gap="4">
+            <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+              <FormLabel>Model Type</FormLabel>
+              <ModelTypeSelect<AnyModelConfig> control={control} name="type" />
+            </FormControl>
+            <Text px="2" fontSize="xs" textAlign="center">
+              {t('modelManager.advancedImportInfo')}
+            </Text>
           </Flex>
-          <Text px="2" fontSize="xs" textAlign="center">
-            {t('modelManager.advancedImportInfo')}
-          </Text>
-        </Flex>
 
-        <Flex p={4} borderRadius={4} bg="base.850" height="100%">
-          {advancedAddMode === 'diffusers' && <AdvancedImportDiffusers />}
-          {advancedAddMode === 'checkpoint' && <AdvancedImportCheckpoint />}
+          <Flex p={4} borderRadius={4} bg="base.850" height="100%" direction="column" gap="3">
+            <FormControl isInvalid={Boolean(errors.name)}>
+              <Flex direction="column" width="full">
+                <FormLabel>{t('modelManager.name')}</FormLabel>
+                <Input
+                  {...register('name', {
+                    validate: (value) => value.trim().length >= 3 || 'Must be at least 3 characters',
+                  })}
+                />
+                {errors.name?.message && <FormErrorMessage>{errors.name?.message}</FormErrorMessage>}
+              </Flex>
+            </FormControl>
+            <Flex>
+              <FormControl>
+                <Flex direction="column" width="full">
+                  <FormLabel>{t('modelManager.description')}</FormLabel>
+                  <Textarea size="sm" {...register('description')} />
+                  {errors.name?.message && <FormErrorMessage>{errors.name?.message}</FormErrorMessage>}
+                </Flex>
+              </FormControl>
+            </Flex>
+            <Flex gap={4}>
+              <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+                <FormLabel>Base Model</FormLabel>
+                <BaseModelSelect<AnyModelConfig> control={control} name="base" />
+              </FormControl>
+              <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+                <FormLabel>Format</FormLabel>
+                <ModelFormatSelect<AnyModelConfig> control={control} name="format" />
+              </FormControl>
+            </Flex>
+            <Flex gap={4}>
+              <FormControl flexDir="column" alignItems="flex-start" gap={1} isInvalid={Boolean(errors.path)}>
+                <FormLabel>Path</FormLabel>
+                <Input
+                  {...register('path', {
+                    validate: (value) => value.trim().length > 0 || 'Must provide a path',
+                  })}
+                />
+                {errors.path?.message && <FormErrorMessage>{errors.path?.message}</FormErrorMessage>}
+              </FormControl>
+            </Flex>
+            {watchedModelType === 'main' && (
+              <>
+                <Flex gap={4}>
+                  {watchedModelFormat === 'diffusers' && (
+                    <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+                      <FormLabel>Repo Variant</FormLabel>
+                      <RepoVariantSelect<AnyModelConfig> control={control} name="repo_variant" />
+                    </FormControl>
+                  )}
+                  {watchedModelFormat === 'checkpoint' && (
+                    <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+                      <FormLabel>Config Path</FormLabel>
+                      <Input {...register('config')} />
+                    </FormControl>
+                  )}
+
+                  <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+                    <FormLabel>Variant</FormLabel>
+                    <ModelVariantSelect<AnyModelConfig> control={control} name="variant" />
+                  </FormControl>
+                </Flex>
+                <Flex gap={4}>
+                  <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+                    <FormLabel>Prediction Type</FormLabel>
+                    <PredictionTypeSelect<AnyModelConfig> control={control} name="prediction_type" />
+                  </FormControl>
+                  <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+                    <FormLabel>Upcast Attention</FormLabel>
+                    <BooleanSelect<AnyModelConfig> control={control} name="upcast_attention" />
+                  </FormControl>
+                </Flex>
+                <Flex gap={4}>
+                  <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+                    <FormLabel>ZTSNR Training</FormLabel>
+                    <BooleanSelect<AnyModelConfig> control={control} name="ztsnr_training" />
+                  </FormControl>
+                  <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+                    <FormLabel>VAE Path</FormLabel>
+                    <Input {...register('vae')} />
+                  </FormControl>
+                </Flex>
+              </>
+            )}
+            {watchedModelType === 'ip_adapter' && (
+              <Flex gap={4}>
+                <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+                  <FormLabel>Image Encoder Model ID</FormLabel>
+                  <Input {...register('image_encoder_model_id')} />
+                </FormControl>
+              </Flex>
+            )}
+            <Button mt={2} type="submit">
+              {t('modelManager.addModel')}
+            </Button>
+          </Flex>
         </Flex>
-      </Flex>
+      </form>
     </ScrollableContent>
   );
 };
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImportCheckpoint.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImportCheckpoint.tsx
deleted file mode 100644
index bf22ef12d1..0000000000
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImportCheckpoint.tsx
+++ /dev/null
@@ -1,160 +0,0 @@
-import {
-  Button,
-  Checkbox,
-  Flex,
-  FormControl,
-  FormErrorMessage,
-  FormLabel,
-  Input,
-  Textarea,
-} from '@invoke-ai/ui-library';
-import { useAppDispatch } from 'app/store/storeHooks';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
-import type { CSSProperties } from 'react';
-import { useCallback, useState } from 'react';
-import type { SubmitHandler } from 'react-hook-form';
-import { useForm } from 'react-hook-form';
-import { useTranslation } from 'react-i18next';
-import { useAddMainModelsMutation } from 'services/api/endpoints/models';
-import type { CheckpointModelConfig, DiffusersModelConfig } from 'services/api/types';
-
-import BaseModelSelect from './BaseModelSelect';
-import CheckpointConfigsSelect from './CheckpointConfigsSelect';
-import ModelVariantSelect from './ModelVariantSelect';
-
-export const AdvancedImportCheckpoint = () => {
-  const { t } = useTranslation();
-  const dispatch = useAppDispatch();
-
-  const [addMainModel] = useAddMainModelsMutation();
-
-  const [useCustomConfig, setUseCustomConfig] = useState<boolean>(false);
-
-  const {
-    register,
-    handleSubmit,
-    control,
-    formState: { errors },
-    reset,
-  } = useForm<CheckpointModelConfig>({
-    defaultValues: {
-      name: '',
-      base: 'sd-1',
-      type: 'main',
-      path: '',
-      description: '',
-      format: 'checkpoint',
-      vae: '',
-      variant: 'normal',
-      config: '',
-    },
-    mode: 'onChange',
-  });
-
-  const onSubmit = useCallback<SubmitHandler<DiffusersModelConfig>>(
-    (values) => {
-      addMainModel({
-        body: values,
-      })
-        .unwrap()
-        .then((_) => {
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('modelManager.modelAdded', {
-                  modelName: values.name,
-                }),
-                status: 'success',
-              })
-            )
-          );
-          reset();
-        })
-        .catch((error) => {
-          if (error) {
-            dispatch(
-              addToast(
-                makeToast({
-                  title: t('toast.modelAddFailed'),
-                  status: 'error',
-                })
-              )
-            );
-          }
-        });
-    },
-    [addMainModel, dispatch, reset, t]
-  );
-
-  const handleChangeUseCustomConfig = useCallback(() => setUseCustomConfig((prev) => !prev), []);
-
-  return (
-    <form onSubmit={handleSubmit(onSubmit)} style={formStyles}>
-      <Flex flexDirection="column" gap={2}>
-        <FormControl isInvalid={Boolean(errors.name)}>
-          <Flex direction="column" width="full">
-            <FormLabel>{t('modelManager.name')}</FormLabel>
-            <Input
-              {...register('name', {
-                validate: (value) => value.trim().length > 3 || 'Must be at least 3 characters',
-              })}
-            />
-            {errors.name?.message && <FormErrorMessage>{errors.name?.message}</FormErrorMessage>}
-          </Flex>
-        </FormControl>
-        <Flex>
-          <FormControl>
-            <Flex direction="column" width="full">
-              <FormLabel>{t('modelManager.description')}</FormLabel>
-              <Textarea size="sm" {...register('description')} />
-              {errors.name?.message && <FormErrorMessage>{errors.name?.message}</FormErrorMessage>}
-            </Flex>
-          </FormControl>
-        </Flex>
-        <Flex gap="2">
-          <BaseModelSelect<CheckpointModelConfig> control={control} name="base" />
-          <ModelVariantSelect<CheckpointModelConfig> control={control} name="variant" />
-        </Flex>
-        <FormControl isInvalid={Boolean(errors.path)}>
-          <Flex direction="column" width="full">
-            <FormLabel>{t('modelManager.modelLocation')}</FormLabel>
-            <Input
-              {...register('path', {
-                validate: (value) => value.trim().length > 0 || 'Must provide a path',
-              })}
-            />
-            {errors.path?.message && <FormErrorMessage>{errors.path?.message}</FormErrorMessage>}
-          </Flex>
-        </FormControl>
-        <FormControl>
-          <Flex direction="column" width="full">
-            <FormLabel>{t('modelManager.vaeLocation')}</FormLabel>
-            <Input {...register('vae')} />
-          </Flex>
-        </FormControl>
-        <Flex flexDirection="column" width="100%" gap={2}>
-          {!useCustomConfig ? (
-            <CheckpointConfigsSelect control={control} name="config" />
-          ) : (
-            <FormControl isRequired>
-              <FormLabel>{t('modelManager.config')}</FormLabel>
-              <Input {...register('config')} />
-            </FormControl>
-          )}
-          <FormControl>
-            <FormLabel>{t('modelManager.useCustomConfig')}</FormLabel>
-            <Checkbox isChecked={useCustomConfig} onChange={handleChangeUseCustomConfig} />
-          </FormControl>
-          <Button mt={2} type="submit">
-            {t('modelManager.addModel')}
-          </Button>
-        </Flex>
-      </Flex>
-    </form>
-  );
-};
-
-const formStyles: CSSProperties = {
-  width: '100%',
-};
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImportDiffusers.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImportDiffusers.tsx
deleted file mode 100644
index c113fe0274..0000000000
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImportDiffusers.tsx
+++ /dev/null
@@ -1,132 +0,0 @@
-import { Button, Flex, FormControl, FormErrorMessage, FormLabel, Input, Textarea } from '@invoke-ai/ui-library';
-import { useAppDispatch } from 'app/store/storeHooks';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
-import type { CSSProperties } from 'react';
-import {useCallback } from 'react';
-import type { SubmitHandler } from 'react-hook-form';
-import { useForm } from 'react-hook-form';
-import { useTranslation } from 'react-i18next';
-import { useAddMainModelsMutation } from 'services/api/endpoints/models';
-import type { DiffusersModelConfig } from 'services/api/types';
-
-import BaseModelSelect from './BaseModelSelect';
-import ModelVariantSelect from './ModelVariantSelect';
-
-export const AdvancedImportDiffusers = () => {
-  const { t } = useTranslation();
-  const dispatch = useAppDispatch();
-
-  const [addMainModel] = useAddMainModelsMutation();
-
-  const {
-    register,
-    handleSubmit,
-    control,
-    formState: { errors },
-    reset,
-  } = useForm<DiffusersModelConfig>({
-    defaultValues: {
-      name: '',
-      base: 'sd-1',
-      type: 'main',
-      path: '',
-      description: '',
-      format: 'diffusers',
-      vae: '',
-      variant: 'normal',
-    },
-    mode: 'onChange',
-  });
-
-  const onSubmit = useCallback<SubmitHandler<DiffusersModelConfig>>(
-    (values) => {
-      addMainModel({
-        body: values,
-      })
-        .unwrap()
-        .then((_) => {
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('modelManager.modelAdded', {
-                  modelName: values.name,
-                }),
-                status: 'success',
-              })
-            )
-          );
-          reset();
-        })
-        .catch((error) => {
-          if (error) {
-            dispatch(
-              addToast(
-                makeToast({
-                  title: t('toast.modelAddFailed'),
-                  status: 'error',
-                })
-              )
-            );
-          }
-        });
-    },
-    [addMainModel, dispatch, reset, t]
-  );
-
-  return (
-      <form onSubmit={handleSubmit(onSubmit)} style={formStyles}>
-        <Flex flexDirection="column" gap={2}>
-          <FormControl isInvalid={Boolean(errors.name)}>
-            <Flex direction="column" width="full">
-              <FormLabel>{t('modelManager.name')}</FormLabel>
-              <Input
-                {...register('name', {
-                  validate: (value) => value.trim().length > 3 || 'Must be at least 3 characters',
-                })}
-              />
-              {errors.name?.message && <FormErrorMessage>{errors.name?.message}</FormErrorMessage>}
-            </Flex>
-          </FormControl>
-          <Flex>
-            <FormControl>
-              <Flex direction="column" width="full">
-                <FormLabel>{t('modelManager.description')}</FormLabel>
-                <Textarea size="sm" {...register('description')} />
-                {errors.name?.message && <FormErrorMessage>{errors.name?.message}</FormErrorMessage>}
-              </Flex>
-            </FormControl>
-          </Flex>
-          <Flex gap="2">
-            <BaseModelSelect<DiffusersModelConfig> control={control} name="base" />
-            <ModelVariantSelect<DiffusersModelConfig> control={control} name="variant" />
-          </Flex>
-          <FormControl isInvalid={Boolean(errors.path)}>
-            <Flex direction="column" width="full">
-              <FormLabel>{t('modelManager.modelLocation')}</FormLabel>
-              <Input
-                {...register('path', {
-                  validate: (value) => value.trim().length > 0 || 'Must provide a path',
-                })}
-              />
-              {errors.path?.message && <FormErrorMessage>{errors.path?.message}</FormErrorMessage>}
-            </Flex>
-          </FormControl>
-          <FormControl>
-            <Flex direction="column" width="full">
-              <FormLabel>{t('modelManager.vaeLocation')}</FormLabel>
-              <Input {...register('vae')} />
-            </Flex>
-          </FormControl>
-
-          <Button mt={2} type="submit">
-            {t('modelManager.addModel')}
-          </Button>
-        </Flex>
-      </form>
-  );
-};
-
-const formStyles: CSSProperties = {
-  width: '100%',
-};
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelFormatSelect.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelFormatSelect.tsx
index 0a9f0abe79..7c8bed9c02 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelFormatSelect.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelFormatSelect.tsx
@@ -4,11 +4,12 @@ import { typedMemo } from 'common/util/typedMemo';
 import { LORA_MODEL_FORMAT_MAP } from 'features/parameters/types/constants';
 import { useCallback, useMemo } from 'react';
 import type { UseControllerProps } from 'react-hook-form';
-import { useController } from 'react-hook-form';
+import { useController, useWatch } from 'react-hook-form';
 import type { AnyModelConfig } from 'services/api/types';
 
 const ModelFormatSelect = <T extends AnyModelConfig>(props: UseControllerProps<T>) => {
   const { field, formState } = useController(props);
+  const type = useWatch({ control: props.control, name: 'type' });
 
   const onChange = useCallback<ComboboxOnChange>(
     (v) => {
@@ -18,17 +19,18 @@ const ModelFormatSelect = <T extends AnyModelConfig>(props: UseControllerProps<T
   );
 
   const options: ComboboxOption[] = useMemo(() => {
-    if (formState.defaultValues?.type === 'lora') {
+    const modelType = type || formState.defaultValues?.type;
+    if (modelType === 'lora') {
       return Object.keys(LORA_MODEL_FORMAT_MAP).map((format) => ({
         value: format,
         label: LORA_MODEL_FORMAT_MAP[format],
       })) as ComboboxOption[];
-    } else if (formState.defaultValues?.type === 'embedding') {
+    } else if (modelType === 'embedding') {
       return [
         { value: 'embedding_file', label: 'Embedding File' },
         { value: 'embedding_folder', label: 'Embedding Folder' },
       ];
-    } else if (formState.defaultValues?.type === 'ip_adapter') {
+    } else if (modelType === 'ip_adapter') {
       return [{ value: 'invokeai', label: 'invokeai' }];
     } else {
       return [
@@ -36,7 +38,7 @@ const ModelFormatSelect = <T extends AnyModelConfig>(props: UseControllerProps<T
         { value: 'checkpoint', label: 'Checkpoint' },
       ];
     }
-  }, [formState.defaultValues?.type]);
+  }, [type, formState.defaultValues?.type]);
 
   const value = useMemo(() => options.find((o) => o.value === field.value), [options, field.value]);
 
diff --git a/invokeai/frontend/web/src/services/api/endpoints/models.ts b/invokeai/frontend/web/src/services/api/endpoints/models.ts
index ee10630f1f..cbe8bf3544 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/models.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/models.ts
@@ -72,11 +72,12 @@ type DeleteImportModelsResponse =
 type PruneModelImportsResponse =
   paths['/api/v2/models/import']['patch']['responses']['200']['content']['application/json'];
 
-type AddMainModelArg = {
-  body: MainModelConfig;
+type ImportAdvancedModelArg = {
+  source: NonNullable<operations['import_model']['requestBody']['content']['application/json']['source']>;
+  config: NonNullable<operations['import_model']['requestBody']['content']['application/json']['config']>;
 };
 
-type AddMainModelResponse = paths['/api/v2/models/add']['post']['responses']['201']['content']['application/json'];
+type ImportAdvancedModelResponse = paths['/api/v2/models/import']['post']['responses']['201']['content']['application/json'];
 
 export type ScanFolderResponse =
   paths['/api/v2/models/scan_folder']['get']['responses']['200']['content']['application/json'];
@@ -198,12 +199,12 @@ export const modelsApi = api.injectEndpoints({
       },
       invalidatesTags: ['Model', 'ModelImports'],
     }),
-    addMainModels: build.mutation<AddMainModelResponse, AddMainModelArg>({
-      query: ({ body }) => {
+    importAdvancedModel: build.mutation<ImportAdvancedModelResponse, ImportAdvancedModelArg>({
+      query: ({ source, config}) => {
         return {
-          url: buildModelsUrl('add'),
+          url: buildModelsUrl('install'),
           method: 'POST',
-          body: body,
+          body: { source, config },
         };
       },
       invalidatesTags: ['Model', 'ModelImports'],
@@ -344,7 +345,7 @@ export const {
   useDeleteModelsMutation,
   useUpdateModelsMutation,
   useImportMainModelsMutation,
-  useAddMainModelsMutation,
+  useImportAdvancedModelMutation,
   useConvertMainModelsMutation,
   useMergeMainModelsMutation,
   useSyncModelsMutation,

From 53f009019704e0b6f494aefebaf87e1e5692f004 Mon Sep 17 00:00:00 2001
From: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Date: Fri, 23 Feb 2024 10:31:27 -0500
Subject: [PATCH 276/411] fix types for ImportQueue, add QuickAdd for scan
 models

---
 .../{ => ImportQueue}/ImportQueue.tsx         |  16 +--
 .../ImportQueue/ImportQueueBadge.tsx          |  28 ++++
 .../ImportQueue/ImportQueueItem.tsx           | 136 ++++++++++++++++++
 .../AddModelPanel/ImportQueueModel.tsx        | 105 --------------
 .../ScanModels/ScanModelResultItem.tsx        |  55 +++++++
 .../ScanModels/ScanModelsResults.tsx          |  25 ++--
 .../modelManagerV2/subpanels/ImportModels.tsx |   7 +-
 .../web/src/services/api/endpoints/models.ts  |  36 ++---
 .../frontend/web/src/services/api/types.ts    |   7 +
 9 files changed, 261 insertions(+), 154 deletions(-)
 rename invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/{ => ImportQueue}/ImportQueue.tsx (78%)
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueueBadge.tsx
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueueItem.tsx
 delete mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueueModel.tsx
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelResultItem.tsx

diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueue.tsx
similarity index 78%
rename from invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue.tsx
rename to invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueue.tsx
index 804a728cbd..cd2208c972 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueue.tsx
@@ -4,10 +4,9 @@ import { addToast } from 'features/system/store/systemSlice';
 import { makeToast } from 'features/system/util/makeToast';
 import { t } from 'i18next';
 import { useCallback, useMemo } from 'react';
-import { RiSparklingFill } from 'react-icons/ri';
 import { useGetModelImportsQuery, usePruneModelImportsMutation } from 'services/api/endpoints/models';
 
-import { ImportQueueModel } from './ImportQueueModel';
+import { ImportQueueItem } from './ImportQueueItem';
 
 export const ImportQueue = () => {
   const dispatch = useAppDispatch();
@@ -51,20 +50,15 @@ export const ImportQueue = () => {
 
   return (
     <Flex flexDir="column" p={3} h="full">
-      <Flex justifyContent="space-between">
+      <Flex justifyContent="space-between" alignItems="center">
         <Text>{t('modelManager.importQueue')}</Text>
-        <Button
-          isDisabled={!pruneAvailable}
-          onClick={pruneQueue}
-          tooltip={t('modelManager.pruneTooltip')}
-          rightIcon={<RiSparklingFill />}
-        >
+        <Button size="sm" isDisabled={!pruneAvailable} onClick={pruneQueue} tooltip={t('modelManager.pruneTooltip')}>
           {t('modelManager.prune')}
         </Button>
       </Flex>
       <Box mt={3} layerStyle="first" p={3} borderRadius="base" w="full" h="full">
-        <Flex direction="column" gap="2">
-          {data?.map((model) => <ImportQueueModel key={model.id} model={model} />)}
+        <Flex flexDir="column-reverse" gap="2">
+          {data?.map((model) => <ImportQueueItem key={model.id} model={model} />)}
         </Flex>
       </Box>
     </Flex>
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueueBadge.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueueBadge.tsx
new file mode 100644
index 0000000000..5b363c6ff0
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueueBadge.tsx
@@ -0,0 +1,28 @@
+import { Badge, Tooltip } from '@invoke-ai/ui-library';
+import { memo } from 'react';
+import { useTranslation } from 'react-i18next';
+import { ModelInstallStatus } from '../../../../../services/api/types';
+
+const STATUSES = {
+  waiting: { colorScheme: 'cyan', translationKey: 'queue.pending' },
+  downloading: { colorScheme: 'yellow', translationKey: 'queue.in_progress' },
+  running: { colorScheme: 'yellow', translationKey: 'queue.in_progress' },
+  completed: { colorScheme: 'green', translationKey: 'queue.completed' },
+  error: { colorScheme: 'red', translationKey: 'queue.failed' },
+  cancelled: { colorScheme: 'orange', translationKey: 'queue.canceled' },
+};
+
+const ImportQueueBadge = ({ status, detail }: { status?: ModelInstallStatus; detail?: string }) => {
+  const { t } = useTranslation();
+
+  if (!status) {
+    return <></>;
+  }
+
+  return (
+    <Tooltip label={detail}>
+      <Badge colorScheme={STATUSES[status].colorScheme}>{t(STATUSES[status].translationKey)}</Badge>
+    </Tooltip>
+  );
+};
+export default memo(ImportQueueBadge);
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueueItem.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueueItem.tsx
new file mode 100644
index 0000000000..1a7803dda3
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueueItem.tsx
@@ -0,0 +1,136 @@
+import { Box, Flex, IconButton, Progress, Tag, Text, Tooltip } from '@invoke-ai/ui-library';
+import { useAppDispatch } from 'app/store/storeHooks';
+import { addToast } from 'features/system/store/systemSlice';
+import { makeToast } from 'features/system/util/makeToast';
+import { t } from 'i18next';
+import { useCallback, useMemo } from 'react';
+import { PiXBold } from 'react-icons/pi';
+import { useDeleteModelImportMutation } from 'services/api/endpoints/models';
+import type { ModelInstallJob, HFModelSource, LocalModelSource, URLModelSource } from 'services/api/types';
+import ImportQueueBadge from './ImportQueueBadge';
+
+type ModelListItemProps = {
+  model: ModelInstallJob;
+};
+
+const formatBytes = (bytes: number) => {
+  const units = ['b', 'kb', 'mb', 'gb', 'tb'];
+
+  let i = 0;
+
+  for (i; bytes >= 1024 && i < 4; i++) {
+    bytes /= 1024;
+  }
+
+  return `${bytes.toFixed(2)} ${units[i]}`;
+};
+
+export const ImportQueueItem = (props: ModelListItemProps) => {
+  const { model } = props;
+  const dispatch = useAppDispatch();
+
+  const [deleteImportModel] = useDeleteModelImportMutation();
+
+  const source = useMemo(() => {
+    if (model.source.type === 'hf') {
+      return model.source as HFModelSource;
+    } else if (model.source.type === 'local') {
+      return model.source as LocalModelSource;
+    } else if (model.source.type === 'url') {
+      return model.source as URLModelSource;
+    } else {
+      return model.source as LocalModelSource;
+    }
+  }, [model.source]);
+
+  const handleDeleteModelImport = useCallback(() => {
+    deleteImportModel(model.id)
+      .unwrap()
+      .then((_) => {
+        dispatch(
+          addToast(
+            makeToast({
+              title: t('toast.modelImportCanceled'),
+              status: 'success',
+            })
+          )
+        );
+      })
+      .catch((error) => {
+        if (error) {
+          dispatch(
+            addToast(
+              makeToast({
+                title: `${error.data.detail} `,
+                status: 'error',
+              })
+            )
+          );
+        }
+      });
+  }, [deleteImportModel, model, dispatch]);
+
+  const modelName = useMemo(() => {
+    switch (source.type) {
+      case 'hf':
+        return source.repo_id;
+      case 'url':
+        return source.url;
+      case 'local':
+        return source.path.substring(source.path.lastIndexOf('/') + 1);
+      default:
+        return '';
+    }
+  }, [source]);
+
+  const progressValue = useMemo(() => {
+    if (model.bytes === undefined || model.total_bytes === undefined) {
+      return 0;
+    }
+
+    return (model.bytes / model.total_bytes) * 100;
+  }, [model.bytes, model.total_bytes]);
+
+  const progressString = useMemo(() => {
+    if (model.status !== 'downloading' || model.bytes === undefined || model.total_bytes === undefined) {
+      return '';
+    }
+    return `${formatBytes(model.bytes)} / ${formatBytes(model.total_bytes)}`;
+  }, [model.bytes, model.total_bytes, model.status]);
+
+  return (
+    <Flex gap="2" w="full" alignItems="center" textAlign="center">
+      <Tooltip label={modelName}>
+        <Text w="30%" whiteSpace="nowrap" overflow="hidden" textOverflow="ellipsis">
+          {modelName}
+        </Text>
+      </Tooltip>
+      <Flex flexDir="column" w="50%">
+        <Tooltip label={progressString}>
+          <Progress
+            value={progressValue}
+            isIndeterminate={progressValue === undefined}
+            aria-label={t('accessibility.invokeProgressBar')}
+            h={2}
+          />
+        </Tooltip>
+      </Flex>
+      <Box w="15%">
+        <ImportQueueBadge status={model.status} />
+      </Box>
+
+      <Box w="10%">
+        {(model.status === 'downloading' || model.status === 'waiting') && (
+          <IconButton
+            isRound={true}
+            size="xs"
+            tooltip={t('modelManager.cancel')}
+            aria-label={t('modelManager.cancel')}
+            icon={<PiXBold />}
+            onClick={handleDeleteModelImport}
+          />
+        )}
+      </Box>
+    </Flex>
+  );
+};
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueueModel.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueueModel.tsx
deleted file mode 100644
index ebd5b3ec55..0000000000
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueueModel.tsx
+++ /dev/null
@@ -1,105 +0,0 @@
-import { Box, Flex, IconButton, Progress, Text } from '@invoke-ai/ui-library';
-import { useAppDispatch } from 'app/store/storeHooks';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
-import { t } from 'i18next';
-import { useCallback, useMemo } from 'react';
-import { PiXBold } from 'react-icons/pi';
-import { useDeleteModelImportMutation } from 'services/api/endpoints/models';
-import type { ImportModelConfig } from 'services/api/types';
-
-type ModelListItemProps = {
-  model: ImportModelConfig;
-};
-
-export const ImportQueueModel = (props: ModelListItemProps) => {
-  const { model } = props;
-  const dispatch = useAppDispatch();
-
-  const [deleteImportModel] = useDeleteModelImportMutation();
-
-  const handleDeleteModelImport = useCallback(() => {
-    deleteImportModel({ key: model.id })
-      .unwrap()
-      .then((_) => {
-        dispatch(
-          addToast(
-            makeToast({
-              title: t('toast.modelImportCanceled'),
-              status: 'success',
-            })
-          )
-        );
-      })
-      .catch((error) => {
-        if (error) {
-          dispatch(
-            addToast(
-              makeToast({
-                title: `${error.data.detail} `,
-                status: 'error',
-              })
-            )
-          );
-        }
-      });
-  }, [deleteImportModel, model, dispatch]);
-
-  const formatBytes = (bytes: number) => {
-    const units = ['b', 'kb', 'mb', 'gb', 'tb'];
-
-    let i = 0;
-
-    for (i; bytes >= 1024 && i < 4; i++) {
-      bytes /= 1024;
-    }
-
-    return `${bytes.toFixed(2)} ${units[i]}`;
-  };
-
-  const modelName = useMemo(() => {
-    return model.source.repo_id || model.source.url || model.source.path.substring(model.source.path.lastIndexOf('/') + 1);
-  }, [model.source]);
-
-  const progressValue = useMemo(() => {
-    return (model.bytes / model.total_bytes) * 100;
-  }, [model.bytes, model.total_bytes]);
-
-  const progressString = useMemo(() => {
-    if (model.status !== 'downloading') {
-      return '--';
-    }
-    return `${formatBytes(model.bytes)} / ${formatBytes(model.total_bytes)}`;
-  }, [model.bytes, model.total_bytes, model.status]);
-
-  return (
-    <Flex gap="2" w="full" alignItems="center" textAlign="center">
-      <Text w="20%" whiteSpace="nowrap" overflow="hidden" textOverflow="ellipsis">
-        {modelName}
-      </Text>
-      <Progress
-        value={progressValue}
-        isIndeterminate={progressValue === undefined}
-        aria-label={t('accessibility.invokeProgressBar')}
-        h={2}
-        w="50%"
-      />
-      <Text minW="20%" fontSize="xs" w="20%">
-        {progressString}
-      </Text>
-      <Text w="15%">{model.status[0].toUpperCase() + model.status.slice(1)}</Text>
-      <Box w="10%">
-        {(model.status === 'downloading' || model.status === 'waiting') && (
-          <IconButton
-            isRound={true}
-            size="xs"
-            tooltip={t('modelManager.cancel')}
-            aria-label={t('modelManager.cancel')}
-            icon={<PiXBold />}
-            onClick={handleDeleteModelImport}
-          />
-        )}
-      </Box>
-    </Flex>
-  );
-};
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelResultItem.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelResultItem.tsx
new file mode 100644
index 0000000000..98ad8b0751
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelResultItem.tsx
@@ -0,0 +1,55 @@
+import { Flex, Text, Box, Button, IconButton, Tooltip } from '@invoke-ai/ui-library';
+import { useTranslation } from 'react-i18next';
+import { IoAdd } from 'react-icons/io5';
+import { useAppDispatch } from '../../../../../app/store/storeHooks';
+import { useImportMainModelsMutation } from '../../../../../services/api/endpoints/models';
+import { addToast } from '../../../../system/store/systemSlice';
+import { makeToast } from '../../../../system/util/makeToast';
+
+export const ScanModelResultItem = ({ result }: { result: string }) => {
+  const { t } = useTranslation();
+  const dispatch = useAppDispatch();
+
+  const [importMainModel, { isLoading }] = useImportMainModelsMutation();
+
+  const handleQuickAdd = () => {
+    importMainModel({ source: result, config: undefined })
+      .unwrap()
+      .then((_) => {
+        dispatch(
+          addToast(
+            makeToast({
+              title: t('toast.modelAddedSimple'),
+              status: 'success',
+            })
+          )
+        );
+      })
+      .catch((error) => {
+        if (error) {
+          dispatch(
+            addToast(
+              makeToast({
+                title: `${error.data.detail} `,
+                status: 'error',
+              })
+            )
+          );
+        }
+      });
+  };
+
+  return (
+    <Flex justifyContent={'space-between'}>
+      <Flex fontSize="sm" flexDir="column">
+        <Text fontWeight="semibold">{result.split('\\').slice(-1)[0]}</Text>
+        <Text variant="subtext">{result}</Text>
+      </Flex>
+      <Box>
+        <Tooltip label={t('modelManager.quickAdd')}>
+          <IconButton aria-label={t('modelManager.quickAdd')} icon={<IoAdd />} onClick={handleQuickAdd} />
+        </Tooltip>
+      </Box>
+    </Flex>
+  );
+};
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx
index ef6f386e31..74a374516a 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx
@@ -1,18 +1,10 @@
-import {
-  Divider,
-  Flex,
-  Heading,
-  IconButton,
-  Input,
-  InputGroup,
-  InputRightElement,
-  Text,
-} from '@invoke-ai/ui-library';
+import { Divider, Flex, Heading, IconButton, Input, InputGroup, InputRightElement, Text } from '@invoke-ai/ui-library';
 import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
 import { t } from 'i18next';
-import type { ChangeEventHandler} from 'react';
+import type { ChangeEventHandler } from 'react';
 import { useCallback, useState } from 'react';
 import { PiXBold } from 'react-icons/pi';
+import { ScanModelResultItem } from './ScanModelResultItem';
 
 export const ScanModelsResults = ({ results }: { results: string[] }) => {
   const [searchTerm, setSearchTerm] = useState('');
@@ -67,12 +59,11 @@ export const ScanModelsResults = ({ results }: { results: string[] }) => {
         </Flex>
         <Flex height="100%" layerStyle="third" borderRadius="base" p={4} mt={4} mb={4}>
           <ScrollableContent>
-            {filteredResults.map((result) => (
-              <Flex key={result} fontSize="sm" flexDir="column">
-                <Text fontWeight="semibold">{result.split('\\').slice(-1)[0]}</Text>
-                <Text variant="subtext">{result}</Text>
-              </Flex>
-            ))}
+            <Flex flexDir="column" gap={3}>
+              {filteredResults.map((result) => (
+                <ScanModelResultItem key={result} result={result} />
+              ))}
+            </Flex>
           </ScrollableContent>
         </Flex>
       </Flex>
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx
index d7e9fda679..49e4faf893 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx
@@ -1,9 +1,10 @@
 import { Box, Flex, Heading, Tab, TabList, TabPanel, TabPanels, Tabs } from '@invoke-ai/ui-library';
 
 import { AdvancedImport } from './AddModelPanel/AdvancedImport';
-import { ImportQueue } from './AddModelPanel/ImportQueue';
+import { ImportQueue } from './AddModelPanel/ImportQueue/ImportQueue';
 import { ScanModels } from './AddModelPanel/ScanModels/ScanModels';
 import { SimpleImport } from './AddModelPanel/SimpleImport';
+import { ScanModelsForm } from './AddModelPanel/ScanModels/ScanModelsForm';
 
 export const ImportModels = () => {
   return (
@@ -23,10 +24,10 @@ export const ImportModels = () => {
               <SimpleImport />
             </TabPanel>
             <TabPanel height="100%">
-            <AdvancedImport />
+              <AdvancedImport />
             </TabPanel>
             <TabPanel height="100%">
-              <ScanModels />
+              <ScanModelsForm />
             </TabPanel>
           </TabPanels>
         </Tabs>
diff --git a/invokeai/frontend/web/src/services/api/endpoints/models.ts b/invokeai/frontend/web/src/services/api/endpoints/models.ts
index cbe8bf3544..43ea132213 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/models.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/models.ts
@@ -127,25 +127,25 @@ export const vaeModelsAdapterSelectors = vaeModelsAdapter.getSelectors(undefined
 
 const buildProvidesTags =
   <TEntity extends AnyModelConfig>(tagType: (typeof tagTypes)[number]) =>
-  (result: EntityState<TEntity, string> | undefined) => {
-    const tags: ApiTagDescription[] = [{ type: tagType, id: LIST_TAG }, 'Model'];
-    if (result) {
-      tags.push(
-        ...result.ids.map((id) => ({
-          type: tagType,
-          id,
-        }))
-      );
-    }
+    (result: EntityState<TEntity, string> | undefined) => {
+      const tags: ApiTagDescription[] = [{ type: tagType, id: LIST_TAG }, 'Model'];
+      if (result) {
+        tags.push(
+          ...result.ids.map((id) => ({
+            type: tagType,
+            id,
+          }))
+        );
+      }
 
-    return tags;
-  };
+      return tags;
+    };
 
 const buildTransformResponse =
   <T extends AnyModelConfig>(adapter: EntityAdapter<T, string>) =>
-  (response: { models: T[] }) => {
-    return adapter.setAll(adapter.getInitialState(), response.models);
-  };
+    (response: { models: T[] }) => {
+      return adapter.setAll(adapter.getInitialState(), response.models);
+    };
 
 /**
  * Builds an endpoint URL for the models router
@@ -305,10 +305,10 @@ export const modelsApi = api.injectEndpoints({
       },
       providesTags: ['ModelImports'],
     }),
-    deleteModelImport: build.mutation<DeleteImportModelsResponse, DeleteMainModelArg>({
-      query: ({ key }) => {
+    deleteModelImport: build.mutation<DeleteImportModelsResponse, number>({
+      query: (id) => {
         return {
-          url: buildModelsUrl(`import/${key}`),
+          url: buildModelsUrl(`import/${id}`),
           method: 'DELETE',
         };
       },
diff --git a/invokeai/frontend/web/src/services/api/types.ts b/invokeai/frontend/web/src/services/api/types.ts
index 6f6018d974..02860be0c8 100644
--- a/invokeai/frontend/web/src/services/api/types.ts
+++ b/invokeai/frontend/web/src/services/api/types.ts
@@ -117,6 +117,13 @@ export const isRefinerMainModelModelConfig = (config: AnyModelConfig): config is
 
 export type MergeModelConfig = S['Body_merge'];
 export type ImportModelConfig = S['Body_import_model'];
+export type ModelInstallJob = S['ModelInstallJob']
+export type ModelInstallStatus = S["InstallStatus"]
+
+export type HFModelSource = S['HFModelSource'];
+export type CivitaiModelSource = S['CivitaiModelSource'];
+export type LocalModelSource = S['LocalModelSource'];
+export type URLModelSource = S['URLModelSource'];
 
 // Graphs
 export type Graph = S['Graph'];

From 625c86ba9a3eb2e2a1b7fed4f442e64e45dcea91 Mon Sep 17 00:00:00 2001
From: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Date: Fri, 23 Feb 2024 10:41:58 -0500
Subject: [PATCH 277/411] add error_reason to UI if import fails

---
 .../listeners/socketio/socketModelInstall.ts  |   3 +-
 .../ImportQueue/ImportQueueBadge.tsx          |   4 +-
 .../ImportQueue/ImportQueueItem.tsx           |   2 +-
 .../frontend/web/src/services/api/schema.ts   | 195 +++++++++---------
 4 files changed, 105 insertions(+), 99 deletions(-)

diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts
index 3810ee85a9..8b4864ccd0 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts
@@ -46,13 +46,14 @@ export const addModelInstallEventListener = () => {
   startAppListening({
     actionCreator: socketModelInstallError,
     effect: (action, { dispatch }) => {
-      const { id } = action.payload.data;
+      const { id, error_type } = action.payload.data;
 
       dispatch(
         modelsApi.util.updateQueryData('getModelImports', undefined, (draft) => {
           const modelImport = draft.find((m) => m.id === id);
           if (modelImport) {
             modelImport.status = 'error';
+            modelImport.error_reason = error_type
           }
           return draft;
         })
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueueBadge.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueueBadge.tsx
index 5b363c6ff0..79ab0a7a4c 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueueBadge.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueueBadge.tsx
@@ -12,7 +12,7 @@ const STATUSES = {
   cancelled: { colorScheme: 'orange', translationKey: 'queue.canceled' },
 };
 
-const ImportQueueBadge = ({ status, detail }: { status?: ModelInstallStatus; detail?: string }) => {
+const ImportQueueBadge = ({ status, errorReason }: { status?: ModelInstallStatus; errorReason?: string | null }) => {
   const { t } = useTranslation();
 
   if (!status) {
@@ -20,7 +20,7 @@ const ImportQueueBadge = ({ status, detail }: { status?: ModelInstallStatus; det
   }
 
   return (
-    <Tooltip label={detail}>
+    <Tooltip label={errorReason}>
       <Badge colorScheme={STATUSES[status].colorScheme}>{t(STATUSES[status].translationKey)}</Badge>
     </Tooltip>
   );
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueueItem.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueueItem.tsx
index 1a7803dda3..254821a438 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueueItem.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueueItem.tsx
@@ -116,7 +116,7 @@ export const ImportQueueItem = (props: ModelListItemProps) => {
         </Tooltip>
       </Flex>
       <Box w="15%">
-        <ImportQueueBadge status={model.status} />
+        <ImportQueueBadge status={model.status} errorReason={model.error_reason} />
       </Box>
 
       <Box w="10%">
diff --git a/invokeai/frontend/web/src/services/api/schema.ts b/invokeai/frontend/web/src/services/api/schema.ts
index d7205c5c88..18c11e33c3 100644
--- a/invokeai/frontend/web/src/services/api/schema.ts
+++ b/invokeai/frontend/web/src/services/api/schema.ts
@@ -1424,7 +1424,7 @@ export type components = {
        * @default clip_vision
        * @constant
        */
-      type: "clip_vision";
+      type?: "clip_vision";
       /**
        * Format
        * @constant
@@ -1435,17 +1435,17 @@ export type components = {
        * @description unique key for model
        * @default <NOKEY>
        */
-      key: string;
+      key?: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash: string | null;
+      original_hash?: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash: string | null;
+      current_hash?: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -1455,12 +1455,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source: string | null;
+      source?: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified: number | null;
+      last_modified?: number | null;
     };
     /** CLIPVisionModelField */
     CLIPVisionModelField: {
@@ -2542,29 +2542,29 @@ export type components = {
        * @default controlnet
        * @constant
        */
-      type: "controlnet";
+      type?: "controlnet";
       /**
        * Format
        * @default checkpoint
        * @constant
        */
-      format: "checkpoint";
+      format?: "checkpoint";
       /**
        * Key
        * @description unique key for model
        * @default <NOKEY>
        */
-      key: string;
+      key?: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash: string | null;
+      original_hash?: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash: string | null;
+      current_hash?: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -2574,12 +2574,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source: string | null;
+      source?: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified: number | null;
+      last_modified?: number | null;
       /**
        * Config
        * @description path to the checkpoint model config file
@@ -2608,29 +2608,29 @@ export type components = {
        * @default controlnet
        * @constant
        */
-      type: "controlnet";
+      type?: "controlnet";
       /**
        * Format
        * @default diffusers
        * @constant
        */
-      format: "diffusers";
+      format?: "diffusers";
       /**
        * Key
        * @description unique key for model
        * @default <NOKEY>
        */
-      key: string;
+      key?: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash: string | null;
+      original_hash?: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash: string | null;
+      current_hash?: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -2640,12 +2640,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source: string | null;
+      source?: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified: number | null;
+      last_modified?: number | null;
       /** @default */
       repo_variant?: components["schemas"]["ModelRepoVariant"] | null;
     };
@@ -4218,7 +4218,7 @@ export type components = {
        * @description The nodes in this graph
        */
       nodes: {
-        [key: string]: components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["ColorMapImageProcessorInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["DWOpenposeImageProcessorInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["DepthAnythingImageProcessorInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["LatentsCollectionInvocation"];
+        [key: string]: components["schemas"]["CompelInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["DWOpenposeImageProcessorInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["DepthAnythingImageProcessorInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["ColorMapImageProcessorInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["ConditioningInvocation"];
       };
       /**
        * Edges
@@ -4255,7 +4255,7 @@ export type components = {
        * @description The results of node executions
        */
       results: {
-        [key: string]: components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["VAEOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["LoraLoaderOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["MetadataOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["ClipSkipInvocationOutput"] | components["schemas"]["String2Output"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["SDXLLoraLoaderOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["LatentsOutput"] | components["schemas"]["IdealSizeOutput"];
+        [key: string]: components["schemas"]["ModelLoaderOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["SDXLLoraLoaderOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["MetadataOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["VAEOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["ClipSkipInvocationOutput"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["LatentsOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["String2Output"] | components["schemas"]["NoiseOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["LoraLoaderOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["FaceOffOutput"];
       };
       /**
        * Errors
@@ -4426,7 +4426,7 @@ export type components = {
        * @default ip_adapter
        * @constant
        */
-      type: "ip_adapter";
+      type?: "ip_adapter";
       /**
        * Format
        * @constant
@@ -4437,17 +4437,17 @@ export type components = {
        * @description unique key for model
        * @default <NOKEY>
        */
-      key: string;
+      key?: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash: string | null;
+      original_hash?: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash: string | null;
+      current_hash?: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -4457,12 +4457,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source: string | null;
+      source?: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified: number | null;
+      last_modified?: number | null;
       /** Image Encoder Model Id */
       image_encoder_model_id: string;
     };
@@ -6510,7 +6510,7 @@ export type components = {
        * @default lora
        * @constant
        */
-      type: "lora";
+      type?: "lora";
       /**
        * Format
        * @enum {string}
@@ -6521,17 +6521,17 @@ export type components = {
        * @description unique key for model
        * @default <NOKEY>
        */
-      key: string;
+      key?: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash: string | null;
+      original_hash?: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash: string | null;
+      current_hash?: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -6541,12 +6541,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source: string | null;
+      source?: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified: number | null;
+      last_modified?: number | null;
     };
     /**
      * LoRAMetadataField
@@ -6710,29 +6710,29 @@ export type components = {
        * @default main
        * @constant
        */
-      type: "main";
+      type?: "main";
       /**
        * Format
        * @default checkpoint
        * @constant
        */
-      format: "checkpoint";
+      format?: "checkpoint";
       /**
        * Key
        * @description unique key for model
        * @default <NOKEY>
        */
-      key: string;
+      key?: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash: string | null;
+      original_hash?: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash: string | null;
+      current_hash?: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -6742,12 +6742,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source: string | null;
+      source?: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified: number | null;
+      last_modified?: number | null;
       /** Vae */
       vae?: string | null;
       /** @default normal */
@@ -6792,29 +6792,29 @@ export type components = {
        * @default main
        * @constant
        */
-      type: "main";
+      type?: "main";
       /**
        * Format
        * @default diffusers
        * @constant
        */
-      format: "diffusers";
+      format?: "diffusers";
       /**
        * Key
        * @description unique key for model
        * @default <NOKEY>
        */
-      key: string;
+      key?: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash: string | null;
+      original_hash?: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash: string | null;
+      current_hash?: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -6824,12 +6824,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source: string | null;
+      source?: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified: number | null;
+      last_modified?: number | null;
       /** Vae */
       vae?: string | null;
       /** @default normal */
@@ -7418,6 +7418,11 @@ export type components = {
        * @default waiting
        */
       status?: components["schemas"]["InstallStatus"];
+      /**
+       * Error Reason
+       * @description Information about why the job failed
+       */
+      error_reason?: string | null;
       /**
        * Config In
        * @description Configuration information (e.g. 'description') to apply to model.
@@ -7762,13 +7767,13 @@ export type components = {
        * @default sd-1
        * @constant
        */
-      base: "sd-1";
+      base?: "sd-1";
       /**
        * Type
        * @default onnx
        * @constant
        */
-      type: "onnx";
+      type?: "onnx";
       /**
        * Format
        * @enum {string}
@@ -7779,17 +7784,17 @@ export type components = {
        * @description unique key for model
        * @default <NOKEY>
        */
-      key: string;
+      key?: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash: string | null;
+      original_hash?: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash: string | null;
+      current_hash?: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -7799,12 +7804,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source: string | null;
+      source?: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified: number | null;
+      last_modified?: number | null;
       /** Vae */
       vae?: string | null;
       /** @default normal */
@@ -7842,13 +7847,13 @@ export type components = {
        * @default sd-2
        * @constant
        */
-      base: "sd-2";
+      base?: "sd-2";
       /**
        * Type
        * @default onnx
        * @constant
        */
-      type: "onnx";
+      type?: "onnx";
       /**
        * Format
        * @enum {string}
@@ -7859,17 +7864,17 @@ export type components = {
        * @description unique key for model
        * @default <NOKEY>
        */
-      key: string;
+      key?: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash: string | null;
+      original_hash?: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash: string | null;
+      current_hash?: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -7879,12 +7884,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source: string | null;
+      source?: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified: number | null;
+      last_modified?: number | null;
       /** Vae */
       vae?: string | null;
       /** @default normal */
@@ -7922,13 +7927,13 @@ export type components = {
        * @default sdxl
        * @constant
        */
-      base: "sdxl";
+      base?: "sdxl";
       /**
        * Type
        * @default onnx
        * @constant
        */
-      type: "onnx";
+      type?: "onnx";
       /**
        * Format
        * @enum {string}
@@ -7939,17 +7944,17 @@ export type components = {
        * @description unique key for model
        * @default <NOKEY>
        */
-      key: string;
+      key?: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash: string | null;
+      original_hash?: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash: string | null;
+      current_hash?: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -7959,12 +7964,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source: string | null;
+      source?: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified: number | null;
+      last_modified?: number | null;
       /** Vae */
       vae?: string | null;
       /** @default normal */
@@ -10114,7 +10119,7 @@ export type components = {
        * @default t2i_adapter
        * @constant
        */
-      type: "t2i_adapter";
+      type?: "t2i_adapter";
       /**
        * Format
        * @constant
@@ -10125,17 +10130,17 @@ export type components = {
        * @description unique key for model
        * @default <NOKEY>
        */
-      key: string;
+      key?: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash: string | null;
+      original_hash?: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash: string | null;
+      current_hash?: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -10145,12 +10150,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source: string | null;
+      source?: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified: number | null;
+      last_modified?: number | null;
     };
     /** TBLR */
     TBLR: {
@@ -10185,7 +10190,7 @@ export type components = {
        * @default embedding
        * @constant
        */
-      type: "embedding";
+      type?: "embedding";
       /**
        * Format
        * @enum {string}
@@ -10196,17 +10201,17 @@ export type components = {
        * @description unique key for model
        * @default <NOKEY>
        */
-      key: string;
+      key?: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash: string | null;
+      original_hash?: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash: string | null;
+      current_hash?: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -10216,12 +10221,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source: string | null;
+      source?: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified: number | null;
+      last_modified?: number | null;
     };
     /** Tile */
     Tile: {
@@ -10534,29 +10539,29 @@ export type components = {
        * @default vae
        * @constant
        */
-      type: "vae";
+      type?: "vae";
       /**
        * Format
        * @default checkpoint
        * @constant
        */
-      format: "checkpoint";
+      format?: "checkpoint";
       /**
        * Key
        * @description unique key for model
        * @default <NOKEY>
        */
-      key: string;
+      key?: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash: string | null;
+      original_hash?: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash: string | null;
+      current_hash?: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -10566,12 +10571,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source: string | null;
+      source?: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified: number | null;
+      last_modified?: number | null;
     };
     /**
      * VaeDiffusersConfig
@@ -10595,29 +10600,29 @@ export type components = {
        * @default vae
        * @constant
        */
-      type: "vae";
+      type?: "vae";
       /**
        * Format
        * @default diffusers
        * @constant
        */
-      format: "diffusers";
+      format?: "diffusers";
       /**
        * Key
        * @description unique key for model
        * @default <NOKEY>
        */
-      key: string;
+      key?: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash: string | null;
+      original_hash?: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash: string | null;
+      current_hash?: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -10627,12 +10632,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source: string | null;
+      source?: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified: number | null;
+      last_modified?: number | null;
     };
     /** VaeField */
     VaeField: {

From 26a209a00d9ae024b761c9113d05ee995a2b4ffb Mon Sep 17 00:00:00 2001
From: maryhipp <maryhipp@gmail.com>
Date: Fri, 23 Feb 2024 10:40:51 -0500
Subject: [PATCH 278/411] add error_reason to ModelInstallJob

---
 invokeai/app/services/model_install/model_install_base.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/invokeai/app/services/model_install/model_install_base.py b/invokeai/app/services/model_install/model_install_base.py
index d1e8e4f8e5..737f62a064 100644
--- a/invokeai/app/services/model_install/model_install_base.py
+++ b/invokeai/app/services/model_install/model_install_base.py
@@ -156,6 +156,7 @@ class ModelInstallJob(BaseModel):
 
     id: int = Field(description="Unique ID for this job")
     status: InstallStatus = Field(default=InstallStatus.WAITING, description="Current status of install process")
+    error_reason: Optional[str] = Field(default=None, description="Information about why the job failed")
     config_in: Dict[str, Any] = Field(
         default_factory=dict, description="Configuration information (e.g. 'description') to apply to model."
     )
@@ -193,6 +194,7 @@ class ModelInstallJob(BaseModel):
         self.error = str(e)
         self.error_traceback = self._format_error(e)
         self.status = InstallStatus.ERROR
+        self.error_reason = self._exception.__class__.__name__ if self._exception else None
 
     def cancel(self) -> None:
         """Call to cancel the job."""

From c3f4e87a6e18abce39ae2cfc1eed0b11a2904fd6 Mon Sep 17 00:00:00 2001
From: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Date: Fri, 23 Feb 2024 14:58:36 -0500
Subject: [PATCH 279/411] fix logic to see if scanned models are already
 installed, style tweaks

---
 .../listeners/socketio/socketModelInstall.ts  |   2 +
 .../modelManagerV2/hooks/useIsImported.ts     |  54 ++++
 .../ImportQueue/ImportQueueItem.tsx           |  12 +-
 .../ScanModels/ScanModelResultItem.tsx        |  26 +-
 .../ScanModels/ScanModelsForm.tsx             |  26 +-
 .../ScanModels/ScanModelsResults.tsx          |  16 +-
 .../modelManagerV2/subpanels/ModelManager.tsx |   2 +-
 .../modelManagerV2/subpanels/ModelPane.tsx    |   2 +-
 .../web/src/services/api/endpoints/models.ts  |  10 +-
 .../frontend/web/src/services/api/schema.ts   | 269 +++++++++++-------
 10 files changed, 277 insertions(+), 142 deletions(-)
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/hooks/useIsImported.ts

diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts
index 8b4864ccd0..e5a7ae4d46 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts
@@ -6,6 +6,7 @@ import {
 } from 'services/events/actions';
 
 import { startAppListening } from '../..';
+import { api } from '../../../../../../services/api';
 
 export const addModelInstallEventListener = () => {
   startAppListening({
@@ -40,6 +41,7 @@ export const addModelInstallEventListener = () => {
           return draft;
         })
       );
+      dispatch(api.util.invalidateTags([{ type: "ModelConfig" }]))
     },
   });
 
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/hooks/useIsImported.ts b/invokeai/frontend/web/src/features/modelManagerV2/hooks/useIsImported.ts
new file mode 100644
index 0000000000..0c5c4232ea
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/hooks/useIsImported.ts
@@ -0,0 +1,54 @@
+import { useCallback } from "react";
+import { ALL_BASE_MODELS } from "../../../services/api/constants";
+import { useGetMainModelsQuery, useGetLoRAModelsQuery, useGetTextualInversionModelsQuery, useGetControlNetModelsQuery, useGetT2IAdapterModelsQuery, useGetIPAdapterModelsQuery, useGetVaeModelsQuery, } from "../../../services/api/endpoints/models";
+import { EntityState } from "@reduxjs/toolkit";
+import { forEach } from "lodash-es";
+import { AnyModelConfig } from "../../../services/api/types";
+
+export const useIsImported = () => {
+    const { data: mainModels } = useGetMainModelsQuery(ALL_BASE_MODELS);
+    const { data: loras } = useGetLoRAModelsQuery();
+    const { data: embeddings } = useGetTextualInversionModelsQuery();
+    const { data: controlnets } = useGetControlNetModelsQuery();
+    const { data: ipAdapters } = useGetIPAdapterModelsQuery();
+    const { data: t2is } = useGetT2IAdapterModelsQuery();
+    const { data: vaes } = useGetVaeModelsQuery();
+
+    const isImported = useCallback(({ name }: { name: string }) => {
+        const data = [mainModels, loras, embeddings, controlnets, ipAdapters, t2is, vaes]
+        let isMatch = false;
+        for (let index = 0; index < data.length; index++) {
+            const modelType: EntityState<AnyModelConfig, string> | undefined = data[index];
+
+            const match = modelsFilter(modelType, name)
+
+            if (!!match.length) {
+                isMatch = true
+                break;
+            }
+        }
+        return isMatch
+    }, [mainModels, loras, embeddings, controlnets, ipAdapters, t2is, vaes])
+
+    return { isImported }
+}
+
+const modelsFilter = <T extends AnyModelConfig>(
+    data: EntityState<T, string> | undefined,
+    nameFilter: string,
+): T[] => {
+    const filteredModels: T[] = [];
+
+    forEach(data?.entities, (model) => {
+        if (!model) {
+            return;
+        }
+
+        const matchesFilter = model.path.toLowerCase().includes(nameFilter.toLowerCase());
+
+        if (matchesFilter) {
+            filteredModels.push(model);
+        }
+    });
+    return filteredModels;
+};
\ No newline at end of file
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueueItem.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueueItem.tsx
index 254821a438..79c3227e65 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueueItem.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueueItem.tsx
@@ -77,7 +77,7 @@ export const ImportQueueItem = (props: ModelListItemProps) => {
       case 'url':
         return source.url;
       case 'local':
-        return source.path.substring(source.path.lastIndexOf('/') + 1);
+        return source.path.split('\\').slice(-1)[0];
       default:
         return '';
     }
@@ -99,13 +99,13 @@ export const ImportQueueItem = (props: ModelListItemProps) => {
   }, [model.bytes, model.total_bytes, model.status]);
 
   return (
-    <Flex gap="2" w="full" alignItems="center" textAlign="center">
+    <Flex gap="2" w="full" alignItems="center">
       <Tooltip label={modelName}>
-        <Text w="30%" whiteSpace="nowrap" overflow="hidden" textOverflow="ellipsis">
+        <Text width="30%" whiteSpace="nowrap" overflow="hidden" textOverflow="ellipsis">
           {modelName}
         </Text>
       </Tooltip>
-      <Flex flexDir="column" w="50%">
+      <Flex flexDir="column" flex={1}>
         <Tooltip label={progressString}>
           <Progress
             value={progressValue}
@@ -115,11 +115,11 @@ export const ImportQueueItem = (props: ModelListItemProps) => {
           />
         </Tooltip>
       </Flex>
-      <Box w="15%">
+      <Box minW="100px" textAlign="center">
         <ImportQueueBadge status={model.status} errorReason={model.error_reason} />
       </Box>
 
-      <Box w="10%">
+      <Box minW="20px">
         {(model.status === 'downloading' || model.status === 'waiting') && (
           <IconButton
             isRound={true}
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelResultItem.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelResultItem.tsx
index 98ad8b0751..2c186d74c1 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelResultItem.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelResultItem.tsx
@@ -1,17 +1,31 @@
-import { Flex, Text, Box, Button, IconButton, Tooltip } from '@invoke-ai/ui-library';
+import { Flex, Text, Box, Button, IconButton, Tooltip, Badge } from '@invoke-ai/ui-library';
 import { useTranslation } from 'react-i18next';
 import { IoAdd } from 'react-icons/io5';
 import { useAppDispatch } from '../../../../../app/store/storeHooks';
 import { useImportMainModelsMutation } from '../../../../../services/api/endpoints/models';
 import { addToast } from '../../../../system/store/systemSlice';
 import { makeToast } from '../../../../system/util/makeToast';
+import { useIsImported } from '../../../hooks/useIsImported';
+import { useMemo } from 'react';
 
 export const ScanModelResultItem = ({ result }: { result: string }) => {
   const { t } = useTranslation();
   const dispatch = useAppDispatch();
 
+  const { isImported } = useIsImported();
+
   const [importMainModel, { isLoading }] = useImportMainModelsMutation();
 
+  const isAlreadyImported = useMemo(() => {
+    const prettyName = result.split('\\').slice(-1)[0];
+    console.log({ prettyName });
+    if (prettyName) {
+      return isImported({ name: prettyName });
+    } else {
+      return false;
+    }
+  }, [result, isImported]);
+
   const handleQuickAdd = () => {
     importMainModel({ source: result, config: undefined })
       .unwrap()
@@ -46,9 +60,13 @@ export const ScanModelResultItem = ({ result }: { result: string }) => {
         <Text variant="subtext">{result}</Text>
       </Flex>
       <Box>
-        <Tooltip label={t('modelManager.quickAdd')}>
-          <IconButton aria-label={t('modelManager.quickAdd')} icon={<IoAdd />} onClick={handleQuickAdd} />
-        </Tooltip>
+        {isAlreadyImported ? (
+          <Badge>{t('common.installed')}</Badge>
+        ) : (
+          <Tooltip label={t('modelManager.quickAdd')}>
+            <IconButton aria-label={t('modelManager.quickAdd')} icon={<IoAdd />} onClick={handleQuickAdd} />
+          </Tooltip>
+        )}
       </Box>
     </Flex>
   );
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsForm.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsForm.tsx
index 0b25ec560f..9fd1b37425 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsForm.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsForm.tsx
@@ -1,5 +1,5 @@
-import { Button,Flex, FormControl, FormErrorMessage, FormLabel, Input } from '@invoke-ai/ui-library';
-import type { ChangeEventHandler} from 'react';
+import { Button, Flex, FormControl, FormErrorMessage, FormLabel, Input } from '@invoke-ai/ui-library';
+import type { ChangeEventHandler } from 'react';
 import { useCallback, useState } from 'react';
 import { useTranslation } from 'react-i18next';
 import { useLazyScanModelsQuery } from 'services/api/endpoints/models';
@@ -9,22 +9,18 @@ import { ScanModelsResults } from './ScanModelsResults';
 export const ScanModelsForm = () => {
   const [scanPath, setScanPath] = useState('');
   const [errorMessage, setErrorMessage] = useState('');
-  const [results, setResults] = useState<string[] | undefined>();
   const { t } = useTranslation();
 
-  const [_scanModels, { isLoading }] = useLazyScanModelsQuery();
+  const [_scanModels, { isLoading, data }] = useLazyScanModelsQuery();
 
   const handleSubmitScan = useCallback(async () => {
-    _scanModels({ scan_path: scanPath })
-      .unwrap()
-      .then((result) => {
-        setResults(result);
-      })
-      .catch((error) => {
-        if (error) {
-          setErrorMessage(error.data.detail);
-        }
-      });
+    try {
+      await _scanModels({ scan_path: scanPath }).unwrap();
+    } catch (error: any) {
+      if (error) {
+        setErrorMessage(error.data.detail);
+      }
+    }
   }, [_scanModels, scanPath]);
 
   const handleSetScanPath: ChangeEventHandler<HTMLInputElement> = useCallback((e) => {
@@ -49,7 +45,7 @@ export const ScanModelsForm = () => {
           {!!errorMessage.length && <FormErrorMessage>{errorMessage}</FormErrorMessage>}
         </Flex>
       </FormControl>
-      {results && <ScanModelsResults results={results} />}
+      {data && <ScanModelsResults results={data} />}
     </Flex>
   );
 };
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx
index 74a374516a..bbbbfb5048 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx
@@ -2,23 +2,23 @@ import { Divider, Flex, Heading, IconButton, Input, InputGroup, InputRightElemen
 import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
 import { t } from 'i18next';
 import type { ChangeEventHandler } from 'react';
-import { useCallback, useState } from 'react';
+import { useCallback, useMemo, useState } from 'react';
 import { PiXBold } from 'react-icons/pi';
 import { ScanModelResultItem } from './ScanModelResultItem';
 
 export const ScanModelsResults = ({ results }: { results: string[] }) => {
   const [searchTerm, setSearchTerm] = useState('');
-  const [filteredResults, setFilteredResults] = useState(results);
+
+  const filteredResults = useMemo(() => {
+    return results.filter((result) => {
+      const modelName = result.split('\\').slice(-1)[0];
+      return modelName?.includes(searchTerm);
+    });
+  }, [results, searchTerm]);
 
   const handleSearch: ChangeEventHandler<HTMLInputElement> = useCallback(
     (e) => {
       setSearchTerm(e.target.value);
-      setFilteredResults(
-        results.filter((result) => {
-          const modelName = result.split('\\').slice(-1)[0];
-          return modelName?.includes(e.target.value);
-        })
-      );
     },
     [results]
   );
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManager.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManager.tsx
index 9eff333f4c..bb35ab7ffd 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManager.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManager.tsx
@@ -14,7 +14,7 @@ export const ModelManager = () => {
   }, [dispatch]);
 
   return (
-    <Box layerStyle="first" p={3} borderRadius="base" w="full" h="full">
+    <Box layerStyle="first" p={3} borderRadius="base" w="50%" h="full">
       <Flex w="full" p={3} justifyContent="space-between" alignItems="center">
         <Flex gap={2}>
           <Heading fontSize="xl">Model Manager</Heading>
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPane.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPane.tsx
index b83e0e0386..9cae8d2984 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPane.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPane.tsx
@@ -7,7 +7,7 @@ import { Model } from './ModelPanel/Model';
 export const ModelPane = () => {
   const selectedModelKey = useAppSelector((s) => s.modelmanagerV2.selectedModelKey);
   return (
-    <Box layerStyle="first" p={2} borderRadius="base" w="full" h="full">
+    <Box layerStyle="first" p={2} borderRadius="base" w="50%" h="full">
       {selectedModelKey ? <Model /> : <ImportModels />}
     </Box>
   );
diff --git a/invokeai/frontend/web/src/services/api/endpoints/models.ts b/invokeai/frontend/web/src/services/api/endpoints/models.ts
index 43ea132213..0f68353148 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/models.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/models.ts
@@ -55,13 +55,13 @@ type MergeMainModelArg = {
 type MergeMainModelResponse = paths['/api/v2/models/merge']['put']['responses']['200']['content']['application/json'];
 
 type ImportMainModelArg = {
-  source: NonNullable<operations['heuristic_import_model']['parameters']['query']['source']>;
-  access_token?: operations['heuristic_import_model']['parameters']['query']['access_token'];
-  config: NonNullable<operations['heuristic_import_model']['requestBody']['content']['application/json']>;
+  source: NonNullable<operations['heuristic_install_model']['parameters']['query']['source']>;
+  access_token?: operations['heuristic_install_model']['parameters']['query']['access_token'];
+  config: NonNullable<operations['heuristic_install_model']['requestBody']['content']['application/json']>;
 };
 
 type ImportMainModelResponse =
-  paths['/api/v2/models/heuristic_import']['post']['responses']['201']['content']['application/json'];
+  paths['/api/v2/models/heuristic_install']['post']['responses']['201']['content']['application/json'];
 
 type ListImportModelsResponse =
   paths['/api/v2/models/import']['get']['responses']['200']['content']['application/json'];
@@ -191,7 +191,7 @@ export const modelsApi = api.injectEndpoints({
     importMainModels: build.mutation<ImportMainModelResponse, ImportMainModelArg>({
       query: ({ source, config, access_token }) => {
         return {
-          url: buildModelsUrl('heuristic_import'),
+          url: buildModelsUrl('heuristic_install'),
           params: { source, access_token },
           method: 'POST',
           body: config,
diff --git a/invokeai/frontend/web/src/services/api/schema.ts b/invokeai/frontend/web/src/services/api/schema.ts
index 18c11e33c3..d7b2001b35 100644
--- a/invokeai/frontend/web/src/services/api/schema.ts
+++ b/invokeai/frontend/web/src/services/api/schema.ts
@@ -78,9 +78,9 @@ export type paths = {
      */
     post: operations["add_model_record"];
   };
-  "/api/v2/models/heuristic_import": {
+  "/api/v2/models/heuristic_install": {
     /**
-     * Heuristic Import
+     * Heuristic Install
      * @description Install a model using a string identifier.
      *
      * `source` can be any of the following.
@@ -107,7 +107,7 @@ export type paths = {
      * See the documentation for `import_model_record` for more information on
      * interpreting the job information returned by this route.
      */
-    post: operations["heuristic_import_model"];
+    post: operations["heuristic_install_model"];
   };
   "/api/v2/models/install": {
     /**
@@ -1424,7 +1424,7 @@ export type components = {
        * @default clip_vision
        * @constant
        */
-      type?: "clip_vision";
+      type: "clip_vision";
       /**
        * Format
        * @constant
@@ -1435,17 +1435,17 @@ export type components = {
        * @description unique key for model
        * @default <NOKEY>
        */
-      key?: string;
+      key: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash?: string | null;
+      original_hash: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash?: string | null;
+      current_hash: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -1455,12 +1455,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source?: string | null;
+      source: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified?: number | null;
+      last_modified: number | null;
     };
     /** CLIPVisionModelField */
     CLIPVisionModelField: {
@@ -2542,29 +2542,29 @@ export type components = {
        * @default controlnet
        * @constant
        */
-      type?: "controlnet";
+      type: "controlnet";
       /**
        * Format
        * @default checkpoint
        * @constant
        */
-      format?: "checkpoint";
+      format: "checkpoint";
       /**
        * Key
        * @description unique key for model
        * @default <NOKEY>
        */
-      key?: string;
+      key: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash?: string | null;
+      original_hash: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash?: string | null;
+      current_hash: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -2574,12 +2574,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source?: string | null;
+      source: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified?: number | null;
+      last_modified: number | null;
       /**
        * Config
        * @description path to the checkpoint model config file
@@ -2608,29 +2608,29 @@ export type components = {
        * @default controlnet
        * @constant
        */
-      type?: "controlnet";
+      type: "controlnet";
       /**
        * Format
        * @default diffusers
        * @constant
        */
-      format?: "diffusers";
+      format: "diffusers";
       /**
        * Key
        * @description unique key for model
        * @default <NOKEY>
        */
-      key?: string;
+      key: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash?: string | null;
+      original_hash: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash?: string | null;
+      current_hash: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -2640,12 +2640,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source?: string | null;
+      source: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified?: number | null;
+      last_modified: number | null;
       /** @default */
       repo_variant?: components["schemas"]["ModelRepoVariant"] | null;
     };
@@ -2977,6 +2977,55 @@ export type components = {
        */
       type: "create_denoise_mask";
     };
+    /**
+     * Create Gradient Mask
+     * @description Creates mask for denoising model run.
+     */
+    CreateGradientMaskInvocation: {
+      /**
+       * Id
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
+       */
+      id: string;
+      /**
+       * Is Intermediate
+       * @description Whether or not this is an intermediate invocation.
+       * @default false
+       */
+      is_intermediate?: boolean;
+      /**
+       * Use Cache
+       * @description Whether or not to use the cache
+       * @default true
+       */
+      use_cache?: boolean;
+      /** @description Image which will be masked */
+      mask?: components["schemas"]["ImageField"];
+      /**
+       * Edge Radius
+       * @description How far to blur/expand the edges of the mask
+       * @default 16
+       */
+      edge_radius?: number;
+      /**
+       * Coherence Mode
+       * @default Gaussian Blur
+       * @enum {string}
+       */
+      coherence_mode?: "Gaussian Blur" | "Box Blur" | "Staged";
+      /**
+       * Minimum Denoise
+       * @description Minimum denoise level for the coherence region
+       * @default 0
+       */
+      minimum_denoise?: number;
+      /**
+       * type
+       * @default create_gradient_mask
+       * @constant
+       */
+      type: "create_gradient_mask";
+    };
     /**
      * Crop Latents
      * @description Crops a latent-space tensor to a box specified in image-space. The box dimensions and coordinates must be
@@ -3272,6 +3321,12 @@ export type components = {
        * @default null
        */
       masked_latents_name?: string | null;
+      /**
+       * Gradient
+       * @description Used for gradient inpainting
+       * @default false
+       */
+      gradient?: boolean;
     };
     /**
      * DenoiseMaskOutput
@@ -4218,7 +4273,7 @@ export type components = {
        * @description The nodes in this graph
        */
       nodes: {
-        [key: string]: components["schemas"]["CompelInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["DWOpenposeImageProcessorInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["DepthAnythingImageProcessorInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["ColorMapImageProcessorInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["ConditioningInvocation"];
+        [key: string]: components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["CreateGradientMaskInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["ColorMapImageProcessorInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["DWOpenposeImageProcessorInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["DepthAnythingImageProcessorInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["ImageBlurInvocation"];
       };
       /**
        * Edges
@@ -4255,7 +4310,7 @@ export type components = {
        * @description The results of node executions
        */
       results: {
-        [key: string]: components["schemas"]["ModelLoaderOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["SDXLLoraLoaderOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["MetadataOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["VAEOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["ClipSkipInvocationOutput"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["LatentsOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["String2Output"] | components["schemas"]["NoiseOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["LoraLoaderOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["FaceOffOutput"];
+        [key: string]: components["schemas"]["FloatCollectionOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["ClipSkipInvocationOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["LoraLoaderOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["LatentsOutput"] | components["schemas"]["SDXLLoraLoaderOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["VAEOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["MetadataOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["String2Output"] | components["schemas"]["ControlOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["ConditioningOutput"];
       };
       /**
        * Errors
@@ -4426,7 +4481,7 @@ export type components = {
        * @default ip_adapter
        * @constant
        */
-      type?: "ip_adapter";
+      type: "ip_adapter";
       /**
        * Format
        * @constant
@@ -4437,17 +4492,17 @@ export type components = {
        * @description unique key for model
        * @default <NOKEY>
        */
-      key?: string;
+      key: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash?: string | null;
+      original_hash: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash?: string | null;
+      current_hash: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -4457,12 +4512,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source?: string | null;
+      source: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified?: number | null;
+      last_modified: number | null;
       /** Image Encoder Model Id */
       image_encoder_model_id: string;
     };
@@ -6510,7 +6565,7 @@ export type components = {
        * @default lora
        * @constant
        */
-      type?: "lora";
+      type: "lora";
       /**
        * Format
        * @enum {string}
@@ -6521,17 +6576,17 @@ export type components = {
        * @description unique key for model
        * @default <NOKEY>
        */
-      key?: string;
+      key: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash?: string | null;
+      original_hash: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash?: string | null;
+      current_hash: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -6541,12 +6596,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source?: string | null;
+      source: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified?: number | null;
+      last_modified: number | null;
     };
     /**
      * LoRAMetadataField
@@ -6710,29 +6765,29 @@ export type components = {
        * @default main
        * @constant
        */
-      type?: "main";
+      type: "main";
       /**
        * Format
        * @default checkpoint
        * @constant
        */
-      format?: "checkpoint";
+      format: "checkpoint";
       /**
        * Key
        * @description unique key for model
        * @default <NOKEY>
        */
-      key?: string;
+      key: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash?: string | null;
+      original_hash: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash?: string | null;
+      current_hash: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -6742,12 +6797,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source?: string | null;
+      source: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified?: number | null;
+      last_modified: number | null;
       /** Vae */
       vae?: string | null;
       /** @default normal */
@@ -6792,29 +6847,29 @@ export type components = {
        * @default main
        * @constant
        */
-      type?: "main";
+      type: "main";
       /**
        * Format
        * @default diffusers
        * @constant
        */
-      format?: "diffusers";
+      format: "diffusers";
       /**
        * Key
        * @description unique key for model
        * @default <NOKEY>
        */
-      key?: string;
+      key: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash?: string | null;
+      original_hash: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash?: string | null;
+      current_hash: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -6824,12 +6879,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source?: string | null;
+      source: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified?: number | null;
+      last_modified: number | null;
       /** Vae */
       vae?: string | null;
       /** @default normal */
@@ -7472,6 +7527,16 @@ export type components = {
        * @description Download jobs contributing to this install
        */
       download_parts?: components["schemas"]["DownloadJob"][];
+      /**
+       * Error
+       * @description On an error condition, this field will contain the text of the exception
+       */
+      error?: string | null;
+      /**
+       * Error Traceback
+       * @description On an error condition, this field will contain the exception traceback
+       */
+      error_traceback?: string | null;
     };
     /**
      * ModelLoaderOutput
@@ -7767,13 +7832,13 @@ export type components = {
        * @default sd-1
        * @constant
        */
-      base?: "sd-1";
+      base: "sd-1";
       /**
        * Type
        * @default onnx
        * @constant
        */
-      type?: "onnx";
+      type: "onnx";
       /**
        * Format
        * @enum {string}
@@ -7784,17 +7849,17 @@ export type components = {
        * @description unique key for model
        * @default <NOKEY>
        */
-      key?: string;
+      key: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash?: string | null;
+      original_hash: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash?: string | null;
+      current_hash: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -7804,12 +7869,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source?: string | null;
+      source: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified?: number | null;
+      last_modified: number | null;
       /** Vae */
       vae?: string | null;
       /** @default normal */
@@ -7847,13 +7912,13 @@ export type components = {
        * @default sd-2
        * @constant
        */
-      base?: "sd-2";
+      base: "sd-2";
       /**
        * Type
        * @default onnx
        * @constant
        */
-      type?: "onnx";
+      type: "onnx";
       /**
        * Format
        * @enum {string}
@@ -7864,17 +7929,17 @@ export type components = {
        * @description unique key for model
        * @default <NOKEY>
        */
-      key?: string;
+      key: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash?: string | null;
+      original_hash: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash?: string | null;
+      current_hash: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -7884,12 +7949,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source?: string | null;
+      source: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified?: number | null;
+      last_modified: number | null;
       /** Vae */
       vae?: string | null;
       /** @default normal */
@@ -7927,13 +7992,13 @@ export type components = {
        * @default sdxl
        * @constant
        */
-      base?: "sdxl";
+      base: "sdxl";
       /**
        * Type
        * @default onnx
        * @constant
        */
-      type?: "onnx";
+      type: "onnx";
       /**
        * Format
        * @enum {string}
@@ -7944,17 +8009,17 @@ export type components = {
        * @description unique key for model
        * @default <NOKEY>
        */
-      key?: string;
+      key: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash?: string | null;
+      original_hash: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash?: string | null;
+      current_hash: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -7964,12 +8029,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source?: string | null;
+      source: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified?: number | null;
+      last_modified: number | null;
       /** Vae */
       vae?: string | null;
       /** @default normal */
@@ -10119,7 +10184,7 @@ export type components = {
        * @default t2i_adapter
        * @constant
        */
-      type?: "t2i_adapter";
+      type: "t2i_adapter";
       /**
        * Format
        * @constant
@@ -10130,17 +10195,17 @@ export type components = {
        * @description unique key for model
        * @default <NOKEY>
        */
-      key?: string;
+      key: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash?: string | null;
+      original_hash: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash?: string | null;
+      current_hash: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -10150,12 +10215,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source?: string | null;
+      source: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified?: number | null;
+      last_modified: number | null;
     };
     /** TBLR */
     TBLR: {
@@ -10190,7 +10255,7 @@ export type components = {
        * @default embedding
        * @constant
        */
-      type?: "embedding";
+      type: "embedding";
       /**
        * Format
        * @enum {string}
@@ -10201,17 +10266,17 @@ export type components = {
        * @description unique key for model
        * @default <NOKEY>
        */
-      key?: string;
+      key: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash?: string | null;
+      original_hash: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash?: string | null;
+      current_hash: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -10221,12 +10286,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source?: string | null;
+      source: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified?: number | null;
+      last_modified: number | null;
     };
     /** Tile */
     Tile: {
@@ -10539,29 +10604,29 @@ export type components = {
        * @default vae
        * @constant
        */
-      type?: "vae";
+      type: "vae";
       /**
        * Format
        * @default checkpoint
        * @constant
        */
-      format?: "checkpoint";
+      format: "checkpoint";
       /**
        * Key
        * @description unique key for model
        * @default <NOKEY>
        */
-      key?: string;
+      key: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash?: string | null;
+      original_hash: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash?: string | null;
+      current_hash: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -10571,12 +10636,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source?: string | null;
+      source: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified?: number | null;
+      last_modified: number | null;
     };
     /**
      * VaeDiffusersConfig
@@ -10600,29 +10665,29 @@ export type components = {
        * @default vae
        * @constant
        */
-      type?: "vae";
+      type: "vae";
       /**
        * Format
        * @default diffusers
        * @constant
        */
-      format?: "diffusers";
+      format: "diffusers";
       /**
        * Key
        * @description unique key for model
        * @default <NOKEY>
        */
-      key?: string;
+      key: string;
       /**
        * Original Hash
        * @description original fasthash of model contents
        */
-      original_hash?: string | null;
+      original_hash: string | null;
       /**
        * Current Hash
        * @description current fasthash of model contents
        */
-      current_hash?: string | null;
+      current_hash: string | null;
       /**
        * Description
        * @description human readable description of the model
@@ -10632,12 +10697,12 @@ export type components = {
        * Source
        * @description model original source (path, URL or repo_id)
        */
-      source?: string | null;
+      source: string | null;
       /**
        * Last Modified
        * @description timestamp for modification time
        */
-      last_modified?: number | null;
+      last_modified: number | null;
     };
     /** VaeField */
     VaeField: {
@@ -11469,7 +11534,7 @@ export type operations = {
     };
   };
   /**
-   * Heuristic Import
+   * Heuristic Install
    * @description Install a model using a string identifier.
    *
    * `source` can be any of the following.
@@ -11496,7 +11561,7 @@ export type operations = {
    * See the documentation for `import_model_record` for more information on
    * interpreting the job information returned by this route.
    */
-  heuristic_import_model: {
+  heuristic_install_model: {
     parameters: {
       query: {
         source: string;
@@ -11507,8 +11572,8 @@ export type operations = {
       content: {
         /**
          * @example {
-         *   "name": "modelT",
-         *   "description": "antique cars"
+         *   "name": "string",
+         *   "description": "string"
          * }
          */
         "application/json": Record<string, never> | null;

From 9b1f63379ae4e8aaab73f2fc95ee116e55adf7f6 Mon Sep 17 00:00:00 2001
From: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Date: Fri, 23 Feb 2024 16:03:36 -0500
Subject: [PATCH 280/411] add model convert to checkpoint main models

---
 .../SyncModels/SyncModelsButton.tsx           |  32 ++++++
 .../SyncModels/SyncModelsIconButton.tsx       |  33 ++++++
 .../components/SyncModels/useSyncModels.ts    |  40 +++++++
 .../store/modelManagerV2Slice.ts              |   2 +-
 .../AddModelPanel/CheckpointConfigsSelect.tsx |  32 ------
 .../modelManagerV2/subpanels/ModelManager.tsx |  11 +-
 .../subpanels/ModelPanel/ModelConvert.tsx     | 104 ++++++++++++++++++
 .../subpanels/ModelPanel/ModelEdit.tsx        |   2 +-
 .../subpanels/ModelPanel/ModelView.tsx        |  14 ++-
 9 files changed, 224 insertions(+), 46 deletions(-)
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/components/SyncModels/SyncModelsButton.tsx
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/components/SyncModels/SyncModelsIconButton.tsx
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/components/SyncModels/useSyncModels.ts
 delete mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/CheckpointConfigsSelect.tsx
 create mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelConvert.tsx

diff --git a/invokeai/frontend/web/src/features/modelManagerV2/components/SyncModels/SyncModelsButton.tsx b/invokeai/frontend/web/src/features/modelManagerV2/components/SyncModels/SyncModelsButton.tsx
new file mode 100644
index 0000000000..8a49bc2585
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/components/SyncModels/SyncModelsButton.tsx
@@ -0,0 +1,32 @@
+import type { ButtonProps } from '@invoke-ai/ui-library';
+import { Button } from '@invoke-ai/ui-library';
+import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';
+import { memo } from 'react';
+import { useTranslation } from 'react-i18next';
+import { PiArrowsClockwiseBold } from 'react-icons/pi';
+
+import { useSyncModels } from './useSyncModels';
+
+export const SyncModelsButton = memo((props: Omit<ButtonProps, 'children'>) => {
+  const { t } = useTranslation();
+  const { syncModels, isLoading } = useSyncModels();
+  const isSyncModelEnabled = useFeatureStatus('syncModels').isFeatureEnabled;
+
+  if (!isSyncModelEnabled) {
+    return null;
+  }
+
+  return (
+    <Button
+      isLoading={isLoading}
+      onClick={syncModels}
+      leftIcon={<PiArrowsClockwiseBold />}
+      minW="max-content"
+      {...props}
+    >
+      {t('modelManager.syncModels')}
+    </Button>
+  );
+});
+
+SyncModelsButton.displayName = 'SyncModelsButton';
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/components/SyncModels/SyncModelsIconButton.tsx b/invokeai/frontend/web/src/features/modelManagerV2/components/SyncModels/SyncModelsIconButton.tsx
new file mode 100644
index 0000000000..986a99bd0b
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/components/SyncModels/SyncModelsIconButton.tsx
@@ -0,0 +1,33 @@
+import type { IconButtonProps } from '@invoke-ai/ui-library';
+import { IconButton } from '@invoke-ai/ui-library';
+import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';
+import { memo } from 'react';
+import { useTranslation } from 'react-i18next';
+import { PiArrowsClockwiseBold } from 'react-icons/pi';
+
+import { useSyncModels } from './useSyncModels';
+
+export const SyncModelsIconButton = memo((props: Omit<IconButtonProps, 'aria-label'>) => {
+  const { t } = useTranslation();
+  const { syncModels, isLoading } = useSyncModels();
+  const isSyncModelEnabled = useFeatureStatus('syncModels').isFeatureEnabled;
+
+  if (!isSyncModelEnabled) {
+    return null;
+  }
+
+  return (
+    <IconButton
+      icon={<PiArrowsClockwiseBold />}
+      tooltip={t('modelManager.syncModels')}
+      aria-label={t('modelManager.syncModels')}
+      isLoading={isLoading}
+      onClick={syncModels}
+      size="sm"
+      variant="ghost"
+      {...props}
+    />
+  );
+});
+
+SyncModelsIconButton.displayName = 'SyncModelsIconButton';
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/components/SyncModels/useSyncModels.ts b/invokeai/frontend/web/src/features/modelManagerV2/components/SyncModels/useSyncModels.ts
new file mode 100644
index 0000000000..3ccaba66a5
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/components/SyncModels/useSyncModels.ts
@@ -0,0 +1,40 @@
+import { useAppDispatch } from 'app/store/storeHooks';
+import { addToast } from 'features/system/store/systemSlice';
+import { makeToast } from 'features/system/util/makeToast';
+import { useCallback } from 'react';
+import { useTranslation } from 'react-i18next';
+import { useSyncModelsMutation } from 'services/api/endpoints/models';
+
+export const useSyncModels = () => {
+  const dispatch = useAppDispatch();
+  const { t } = useTranslation();
+  const [_syncModels, { isLoading }] = useSyncModelsMutation();
+  const syncModels = useCallback(() => {
+    _syncModels()
+      .unwrap()
+      .then((_) => {
+        dispatch(
+          addToast(
+            makeToast({
+              title: `${t('modelManager.modelsSynced')}`,
+              status: 'success',
+            })
+          )
+        );
+      })
+      .catch((error) => {
+        if (error) {
+          dispatch(
+            addToast(
+              makeToast({
+                title: `${t('modelManager.modelSyncFailed')}`,
+                status: 'error',
+              })
+            )
+          );
+        }
+      });
+  }, [dispatch, _syncModels, t]);
+
+  return { syncModels, isLoading };
+};
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/store/modelManagerV2Slice.ts b/invokeai/frontend/web/src/features/modelManagerV2/store/modelManagerV2Slice.ts
index 83bd0cf8d5..f4760bad36 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/store/modelManagerV2Slice.ts
+++ b/invokeai/frontend/web/src/features/modelManagerV2/store/modelManagerV2Slice.ts
@@ -52,7 +52,7 @@ export const migrateModelManagerState = (state: any): any => {
     return state;
 };
 
-export const modelManagerPersistConfig: PersistConfig<ModelManagerState> = {
+export const modelManagerV2PersistConfig: PersistConfig<ModelManagerState> = {
     name: modelManagerV2Slice.name,
     initialState: initialModelManagerState,
     migrate: migrateModelManagerState,
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/CheckpointConfigsSelect.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/CheckpointConfigsSelect.tsx
deleted file mode 100644
index 569f1abbba..0000000000
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/CheckpointConfigsSelect.tsx
+++ /dev/null
@@ -1,32 +0,0 @@
-import type { ChakraProps, ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
-import { Combobox, FormControl, FormLabel } from '@invoke-ai/ui-library';
-import { memo, useCallback, useMemo } from 'react';
-import { useController, type UseControllerProps } from 'react-hook-form';
-import { useTranslation } from 'react-i18next';
-import { useGetCheckpointConfigsQuery } from 'services/api/endpoints/models';
-import type { CheckpointModelConfig } from 'services/api/types';
-
-const sx: ChakraProps['sx'] = { w: 'full' };
-
-const CheckpointConfigsSelect = (props: UseControllerProps<CheckpointModelConfig>) => {
-  const { data } = useGetCheckpointConfigsQuery();
-  const { t } = useTranslation();
-  const options = useMemo<ComboboxOption[]>(() => (data ? data.map((i) => ({ label: i, value: i })) : []), [data]);
-  const { field } = useController(props);
-  const value = useMemo(() => options.find((o) => o.value === field.value), [field.value, options]);
-  const onChange = useCallback<ComboboxOnChange>(
-    (v) => {
-      field.onChange(v?.value);
-    },
-    [field]
-  );
-
-  return (
-    <FormControl>
-      <FormLabel>{t('modelManager.configFile')}</FormLabel>
-      <Combobox placeholder="Select A Config File" value={value} options={options} onChange={onChange} sx={sx} />
-    </FormControl>
-  );
-};
-
-export default memo(CheckpointConfigsSelect);
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManager.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManager.tsx
index bb35ab7ffd..012b2ef2e6 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManager.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManager.tsx
@@ -1,6 +1,6 @@
 import { Box, Button, Flex, Heading } from '@invoke-ai/ui-library';
 import { useAppDispatch } from 'app/store/storeHooks';
-import { SyncModelsIconButton } from 'features/modelManager/components/SyncModels/SyncModelsIconButton';
+import { SyncModelsIconButton } from 'features/modelManagerV2/components/SyncModels/SyncModelsIconButton';
 import { setSelectedModelKey } from 'features/modelManagerV2/store/modelManagerV2Slice';
 import { useCallback } from 'react';
 
@@ -20,12 +20,9 @@ export const ModelManager = () => {
           <Heading fontSize="xl">Model Manager</Heading>
           <SyncModelsIconButton />
         </Flex>
-        <Flex gap={2}>
-          <Button colorScheme="invokeYellow" onClick={handleClickAddModel}>
-            Add Model
-          </Button>
-          <Button>Scan for Models</Button>
-        </Flex>
+        <Button colorScheme="invokeYellow" onClick={handleClickAddModel}>
+          Add Models
+        </Button>
       </Flex>
       <Box layerStyle="second" p={3} borderRadius="base" w="full" h="full">
         <ModelListNavigation />
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelConvert.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelConvert.tsx
new file mode 100644
index 0000000000..2d1989ca3f
--- /dev/null
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelConvert.tsx
@@ -0,0 +1,104 @@
+import {
+  Button,
+  ConfirmationAlertDialog,
+  Divider,
+  Flex,
+  ListItem,
+  Text,
+  UnorderedList,
+  useDisclosure,
+} from '@invoke-ai/ui-library';
+import { useAppDispatch } from 'app/store/storeHooks';
+import { addToast } from 'features/system/store/systemSlice';
+import { makeToast } from 'features/system/util/makeToast';
+import { useCallback } from 'react';
+import { useTranslation } from 'react-i18next';
+import { useConvertMainModelsMutation } from 'services/api/endpoints/models';
+import type { CheckpointModelConfig } from 'services/api/types';
+
+interface ModelConvertProps {
+  model: CheckpointModelConfig;
+}
+
+export const ModelConvert = (props: ModelConvertProps) => {
+  const { model } = props;
+  const dispatch = useAppDispatch();
+  const { t } = useTranslation();
+  const [convertModel, { isLoading }] = useConvertMainModelsMutation();
+  const { isOpen, onOpen, onClose } = useDisclosure();
+
+  const modelConvertHandler = useCallback(() => {
+    dispatch(
+      addToast(
+        makeToast({
+          title: `${t('modelManager.convertingModelBegin')}: ${model.name}`,
+          status: 'info',
+        })
+      )
+    );
+
+    convertModel(model.key)
+      .unwrap()
+      .then(() => {
+        dispatch(
+          addToast(
+            makeToast({
+              title: `${t('modelManager.modelConverted')}: ${model.name}`,
+              status: 'success',
+            })
+          )
+        );
+      })
+      .catch(() => {
+        dispatch(
+          addToast(
+            makeToast({
+              title: `${t('modelManager.modelConversionFailed')}: ${model.name}`,
+              status: 'error',
+            })
+          )
+        );
+      });
+  }, [convertModel, dispatch, model.base, model.name, t]);
+
+  return (
+    <>
+      <Button
+        onClick={onOpen}
+        size="sm"
+        aria-label={t('modelManager.convertToDiffusers')}
+        className=" modal-close-btn"
+        isLoading={isLoading}
+      >
+        🧨 {t('modelManager.convertToDiffusers')}
+      </Button>
+      <ConfirmationAlertDialog
+        title={`${t('modelManager.convert')} ${model.name}`}
+        acceptCallback={modelConvertHandler}
+        acceptButtonText={`${t('modelManager.convert')}`}
+        isOpen={isOpen}
+        onClose={onClose}
+      >
+        <Flex flexDirection="column" rowGap={4}>
+          <Text fontSize="md">{t('modelManager.convertToDiffusersHelpText1')}</Text>
+          <UnorderedList>
+            <ListItem>
+              <Text fontSize="md">{t('modelManager.convertToDiffusersHelpText2')}</Text>
+            </ListItem>
+            <ListItem>
+              <Text fontSize="md">{t('modelManager.convertToDiffusersHelpText3')}</Text>
+            </ListItem>
+            <ListItem>
+              <Text fontSize="md">{t('modelManager.convertToDiffusersHelpText4')}</Text>
+            </ListItem>
+            <ListItem>
+              <Text fontSize="md">{t('modelManager.convertToDiffusersHelpText5')}</Text>
+            </ListItem>
+          </UnorderedList>
+          <Divider />
+          <Text fontSize="md">{t('modelManager.convertToDiffusersHelpText6')}</Text>
+        </Flex>
+      </ConfirmationAlertDialog>
+    </>
+  );
+};
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx
index e2ff1c2a0a..8b9142fc45 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx
@@ -171,7 +171,7 @@ export const ModelEdit = () => {
                 colorScheme="invokeYellow"
                 onClick={handleSubmit(onSubmit)}
                 isLoading={isSubmitting}
-                isDisabled={Boolean(errors)}
+                isDisabled={Boolean(Object.keys(errors).length)}
               >
                 Save
               </Button>
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx
index bf320e5692..6c907b3cd8 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx
@@ -1,11 +1,11 @@
-import { Box,Button, Flex, Heading, Text } from '@invoke-ai/ui-library';
+import { Box, Button, Flex, Heading, Text } from '@invoke-ai/ui-library';
 import { skipToken } from '@reduxjs/toolkit/query';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import DataViewer from 'features/gallery/components/ImageMetadataViewer/DataViewer';
 import { setSelectedModelMode } from 'features/modelManagerV2/store/modelManagerV2Slice';
 import { useCallback, useMemo } from 'react';
 import { IoPencil } from 'react-icons/io5';
-import { useGetModelConfigQuery,useGetModelMetadataQuery } from 'services/api/endpoints/models';
+import { useGetModelConfigQuery, useGetModelMetadataQuery } from 'services/api/endpoints/models';
 import type {
   CheckpointModelConfig,
   ControlNetModelConfig,
@@ -18,6 +18,7 @@ import type {
 } from 'services/api/types';
 
 import { ModelAttrView } from './ModelAttrView';
+import { ModelConvert } from './ModelConvert';
 
 export const ModelView = () => {
   const dispatch = useAppDispatch();
@@ -79,9 +80,12 @@ export const ModelView = () => {
 
           {modelData.source && <Text variant="subtext">Source: {modelData.source}</Text>}
         </Flex>
-        <Button size="sm" leftIcon={<IoPencil />} colorScheme="invokeYellow" onClick={handleEditModel}>
-          Edit
-        </Button>
+        <Flex gap={2}>
+          <Button size="sm" leftIcon={<IoPencil />} colorScheme="invokeYellow" onClick={handleEditModel}>
+            Edit
+          </Button>
+          {modelData.type === 'main' && modelData.format === 'checkpoint' && <ModelConvert model={modelData} />}
+        </Flex>
       </Flex>
 
       <Flex flexDir="column" p={2} gap={3}>

From baf1194cae7297af666f87132946740d49507a4a Mon Sep 17 00:00:00 2001
From: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Date: Fri, 23 Feb 2024 16:03:56 -0500
Subject: [PATCH 281/411] clean up old model manager components and endpoints

---
 invokeai/frontend/web/src/app/store/store.ts  |   6 +-
 .../SyncModels/SyncModelsButton.tsx           |  32 --
 .../SyncModels/SyncModelsIconButton.tsx       |  33 --
 .../components/SyncModels/useSyncModels.ts    |  40 --
 .../modelManager/store/modelManagerSlice.ts   |  47 ---
 .../subpanels/AddModelsPanel/AddModels.tsx    |  35 --
 .../AddModelsPanel/AdvancedAddCheckpoint.tsx  | 168 ---------
 .../AddModelsPanel/AdvancedAddDiffusers.tsx   | 148 --------
 .../AddModelsPanel/AdvancedAddModels.tsx      |  50 ---
 .../AddModelsPanel/FoundModelsList.tsx        | 176 ---------
 .../AddModelsPanel/ScanAdvancedAddModels.tsx  |  95 -----
 .../subpanels/AddModelsPanel/ScanModels.tsx   |  22 --
 .../AddModelsPanel/SearchFolderForm.tsx       | 103 -----
 .../AddModelsPanel/SimpleAddModels.tsx        |  92 -----
 .../subpanels/AddModelsPanel/util.ts          |  15 -
 .../subpanels/ImportModelsPanel.tsx           |  34 --
 .../subpanels/MergeModelsPanel.tsx            | 352 ------------------
 .../subpanels/ModelManagerPanel.tsx           |  63 ----
 .../ModelManagerPanel/CheckpointModelEdit.tsx | 185 ---------
 .../ModelManagerPanel/DiffusersModelEdit.tsx  | 133 -------
 .../ModelManagerPanel/LoRAModelEdit.tsx       | 127 -------
 .../ModelManagerPanel/ModelConvert.tsx        | 165 --------
 .../subpanels/ModelManagerPanel/ModelList.tsx | 205 ----------
 .../ModelManagerPanel/ModelListItem.tsx       | 111 ------
 .../subpanels/ModelManagerSettingsPanel.tsx   |  14 -
 .../ModelManagerSettingsPanel/SyncModels.tsx  |  22 --
 .../subpanels/shared/BaseModelSelect.tsx      |  36 --
 .../shared/CheckpointConfigsSelect.tsx        |  32 --
 .../subpanels/shared/ModelVariantSelect.tsx   |  34 --
 .../inputs/MainModelFieldInputComponent.tsx   |   2 +-
 .../RefinerModelFieldInputComponent.tsx       |   2 +-
 .../SDXLMainModelFieldInputComponent.tsx      |   2 +-
 .../inputs/VAEModelFieldInputComponent.tsx    |   2 +-
 .../GenerationSettingsAccordion.tsx           |   2 +-
 .../web/src/services/api/endpoints/models.ts  |  62 +--
 35 files changed, 11 insertions(+), 2636 deletions(-)
 delete mode 100644 invokeai/frontend/web/src/features/modelManager/components/SyncModels/SyncModelsButton.tsx
 delete mode 100644 invokeai/frontend/web/src/features/modelManager/components/SyncModels/SyncModelsIconButton.tsx
 delete mode 100644 invokeai/frontend/web/src/features/modelManager/components/SyncModels/useSyncModels.ts
 delete mode 100644 invokeai/frontend/web/src/features/modelManager/store/modelManagerSlice.ts
 delete mode 100644 invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/AddModels.tsx
 delete mode 100644 invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/AdvancedAddCheckpoint.tsx
 delete mode 100644 invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/AdvancedAddDiffusers.tsx
 delete mode 100644 invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/AdvancedAddModels.tsx
 delete mode 100644 invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/FoundModelsList.tsx
 delete mode 100644 invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/ScanAdvancedAddModels.tsx
 delete mode 100644 invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/ScanModels.tsx
 delete mode 100644 invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/SearchFolderForm.tsx
 delete mode 100644 invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/SimpleAddModels.tsx
 delete mode 100644 invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/util.ts
 delete mode 100644 invokeai/frontend/web/src/features/modelManager/subpanels/ImportModelsPanel.tsx
 delete mode 100644 invokeai/frontend/web/src/features/modelManager/subpanels/MergeModelsPanel.tsx
 delete mode 100644 invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel.tsx
 delete mode 100644 invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/CheckpointModelEdit.tsx
 delete mode 100644 invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/DiffusersModelEdit.tsx
 delete mode 100644 invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/LoRAModelEdit.tsx
 delete mode 100644 invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelConvert.tsx
 delete mode 100644 invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelList.tsx
 delete mode 100644 invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelListItem.tsx
 delete mode 100644 invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerSettingsPanel.tsx
 delete mode 100644 invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerSettingsPanel/SyncModels.tsx
 delete mode 100644 invokeai/frontend/web/src/features/modelManager/subpanels/shared/BaseModelSelect.tsx
 delete mode 100644 invokeai/frontend/web/src/features/modelManager/subpanels/shared/CheckpointConfigsSelect.tsx
 delete mode 100644 invokeai/frontend/web/src/features/modelManager/subpanels/shared/ModelVariantSelect.tsx

diff --git a/invokeai/frontend/web/src/app/store/store.ts b/invokeai/frontend/web/src/app/store/store.ts
index c63bc02e09..f85ff916b0 100644
--- a/invokeai/frontend/web/src/app/store/store.ts
+++ b/invokeai/frontend/web/src/app/store/store.ts
@@ -15,8 +15,7 @@ import { dynamicPromptsPersistConfig, dynamicPromptsSlice } from 'features/dynam
 import { galleryPersistConfig, gallerySlice } from 'features/gallery/store/gallerySlice';
 import { hrfPersistConfig, hrfSlice } from 'features/hrf/store/hrfSlice';
 import { loraPersistConfig, loraSlice } from 'features/lora/store/loraSlice';
-import { modelManagerPersistConfig, modelManagerSlice } from 'features/modelManager/store/modelManagerSlice';
-import { modelManagerV2Slice } from 'features/modelManagerV2/store/modelManagerV2Slice';
+import { modelManagerV2PersistConfig, modelManagerV2Slice } from 'features/modelManagerV2/store/modelManagerV2Slice';
 import { nodesPersistConfig, nodesSlice } from 'features/nodes/store/nodesSlice';
 import { workflowPersistConfig, workflowSlice } from 'features/nodes/store/workflowSlice';
 import { generationPersistConfig, generationSlice } from 'features/parameters/store/generationSlice';
@@ -55,7 +54,6 @@ const allReducers = {
   [deleteImageModalSlice.name]: deleteImageModalSlice.reducer,
   [changeBoardModalSlice.name]: changeBoardModalSlice.reducer,
   [loraSlice.name]: loraSlice.reducer,
-  [modelManagerSlice.name]: modelManagerSlice.reducer,
   [modelManagerV2Slice.name]: modelManagerV2Slice.reducer,
   [sdxlSlice.name]: sdxlSlice.reducer,
   [queueSlice.name]: queueSlice.reducer,
@@ -103,7 +101,7 @@ const persistConfigs: { [key in keyof typeof allReducers]?: PersistConfig } = {
   [dynamicPromptsPersistConfig.name]: dynamicPromptsPersistConfig,
   [sdxlPersistConfig.name]: sdxlPersistConfig,
   [loraPersistConfig.name]: loraPersistConfig,
-  [modelManagerPersistConfig.name]: modelManagerPersistConfig,
+  [modelManagerV2PersistConfig.name]: modelManagerV2PersistConfig,
   [hrfPersistConfig.name]: hrfPersistConfig,
 };
 
diff --git a/invokeai/frontend/web/src/features/modelManager/components/SyncModels/SyncModelsButton.tsx b/invokeai/frontend/web/src/features/modelManager/components/SyncModels/SyncModelsButton.tsx
deleted file mode 100644
index 8a49bc2585..0000000000
--- a/invokeai/frontend/web/src/features/modelManager/components/SyncModels/SyncModelsButton.tsx
+++ /dev/null
@@ -1,32 +0,0 @@
-import type { ButtonProps } from '@invoke-ai/ui-library';
-import { Button } from '@invoke-ai/ui-library';
-import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';
-import { memo } from 'react';
-import { useTranslation } from 'react-i18next';
-import { PiArrowsClockwiseBold } from 'react-icons/pi';
-
-import { useSyncModels } from './useSyncModels';
-
-export const SyncModelsButton = memo((props: Omit<ButtonProps, 'children'>) => {
-  const { t } = useTranslation();
-  const { syncModels, isLoading } = useSyncModels();
-  const isSyncModelEnabled = useFeatureStatus('syncModels').isFeatureEnabled;
-
-  if (!isSyncModelEnabled) {
-    return null;
-  }
-
-  return (
-    <Button
-      isLoading={isLoading}
-      onClick={syncModels}
-      leftIcon={<PiArrowsClockwiseBold />}
-      minW="max-content"
-      {...props}
-    >
-      {t('modelManager.syncModels')}
-    </Button>
-  );
-});
-
-SyncModelsButton.displayName = 'SyncModelsButton';
diff --git a/invokeai/frontend/web/src/features/modelManager/components/SyncModels/SyncModelsIconButton.tsx b/invokeai/frontend/web/src/features/modelManager/components/SyncModels/SyncModelsIconButton.tsx
deleted file mode 100644
index 986a99bd0b..0000000000
--- a/invokeai/frontend/web/src/features/modelManager/components/SyncModels/SyncModelsIconButton.tsx
+++ /dev/null
@@ -1,33 +0,0 @@
-import type { IconButtonProps } from '@invoke-ai/ui-library';
-import { IconButton } from '@invoke-ai/ui-library';
-import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';
-import { memo } from 'react';
-import { useTranslation } from 'react-i18next';
-import { PiArrowsClockwiseBold } from 'react-icons/pi';
-
-import { useSyncModels } from './useSyncModels';
-
-export const SyncModelsIconButton = memo((props: Omit<IconButtonProps, 'aria-label'>) => {
-  const { t } = useTranslation();
-  const { syncModels, isLoading } = useSyncModels();
-  const isSyncModelEnabled = useFeatureStatus('syncModels').isFeatureEnabled;
-
-  if (!isSyncModelEnabled) {
-    return null;
-  }
-
-  return (
-    <IconButton
-      icon={<PiArrowsClockwiseBold />}
-      tooltip={t('modelManager.syncModels')}
-      aria-label={t('modelManager.syncModels')}
-      isLoading={isLoading}
-      onClick={syncModels}
-      size="sm"
-      variant="ghost"
-      {...props}
-    />
-  );
-});
-
-SyncModelsIconButton.displayName = 'SyncModelsIconButton';
diff --git a/invokeai/frontend/web/src/features/modelManager/components/SyncModels/useSyncModels.ts b/invokeai/frontend/web/src/features/modelManager/components/SyncModels/useSyncModels.ts
deleted file mode 100644
index 3ccaba66a5..0000000000
--- a/invokeai/frontend/web/src/features/modelManager/components/SyncModels/useSyncModels.ts
+++ /dev/null
@@ -1,40 +0,0 @@
-import { useAppDispatch } from 'app/store/storeHooks';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
-import { useCallback } from 'react';
-import { useTranslation } from 'react-i18next';
-import { useSyncModelsMutation } from 'services/api/endpoints/models';
-
-export const useSyncModels = () => {
-  const dispatch = useAppDispatch();
-  const { t } = useTranslation();
-  const [_syncModels, { isLoading }] = useSyncModelsMutation();
-  const syncModels = useCallback(() => {
-    _syncModels()
-      .unwrap()
-      .then((_) => {
-        dispatch(
-          addToast(
-            makeToast({
-              title: `${t('modelManager.modelsSynced')}`,
-              status: 'success',
-            })
-          )
-        );
-      })
-      .catch((error) => {
-        if (error) {
-          dispatch(
-            addToast(
-              makeToast({
-                title: `${t('modelManager.modelSyncFailed')}`,
-                status: 'error',
-              })
-            )
-          );
-        }
-      });
-  }, [dispatch, _syncModels, t]);
-
-  return { syncModels, isLoading };
-};
diff --git a/invokeai/frontend/web/src/features/modelManager/store/modelManagerSlice.ts b/invokeai/frontend/web/src/features/modelManager/store/modelManagerSlice.ts
deleted file mode 100644
index c450e64b3c..0000000000
--- a/invokeai/frontend/web/src/features/modelManager/store/modelManagerSlice.ts
+++ /dev/null
@@ -1,47 +0,0 @@
-import type { PayloadAction } from '@reduxjs/toolkit';
-import { createSlice } from '@reduxjs/toolkit';
-import type { PersistConfig, RootState } from 'app/store/store';
-
-type ModelManagerState = {
-  _version: 1;
-  searchFolder: string | null;
-  advancedAddScanModel: string | null;
-};
-
-export const initialModelManagerState: ModelManagerState = {
-  _version: 1,
-  searchFolder: null,
-  advancedAddScanModel: null,
-};
-
-export const modelManagerSlice = createSlice({
-  name: 'modelmanager',
-  initialState: initialModelManagerState,
-  reducers: {
-    setSearchFolder: (state, action: PayloadAction<string | null>) => {
-      state.searchFolder = action.payload;
-    },
-    setAdvancedAddScanModel: (state, action: PayloadAction<string | null>) => {
-      state.advancedAddScanModel = action.payload;
-    },
-  },
-});
-
-export const { setSearchFolder, setAdvancedAddScanModel } = modelManagerSlice.actions;
-
-export const selectModelManagerSlice = (state: RootState) => state.modelmanager;
-
-/* eslint-disable-next-line @typescript-eslint/no-explicit-any */
-export const migrateModelManagerState = (state: any): any => {
-  if (!('_version' in state)) {
-    state._version = 1;
-  }
-  return state;
-};
-
-export const modelManagerPersistConfig: PersistConfig<ModelManagerState> = {
-  name: modelManagerSlice.name,
-  initialState: initialModelManagerState,
-  migrate: migrateModelManagerState,
-  persistDenylist: [],
-};
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/AddModels.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/AddModels.tsx
deleted file mode 100644
index cc496674f0..0000000000
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/AddModels.tsx
+++ /dev/null
@@ -1,35 +0,0 @@
-import { Button, ButtonGroup, Flex, Text } from '@invoke-ai/ui-library';
-import { memo, useCallback, useState } from 'react';
-import { useTranslation } from 'react-i18next';
-import { useGetModelImportsQuery } from 'services/api/endpoints/models';
-
-import AdvancedAddModels from './AdvancedAddModels';
-import SimpleAddModels from './SimpleAddModels';
-
-const AddModels = () => {
-  const { t } = useTranslation();
-  const [addModelMode, setAddModelMode] = useState<'simple' | 'advanced'>('simple');
-  const handleAddModelSimple = useCallback(() => setAddModelMode('simple'), []);
-  const handleAddModelAdvanced = useCallback(() => setAddModelMode('advanced'), []);
-  const { data } = useGetModelImportsQuery();
-  console.log({ data });
-  return (
-    <Flex flexDirection="column" width="100%" overflow="scroll" maxHeight={window.innerHeight - 250} gap={4}>
-      <ButtonGroup>
-        <Button size="sm" isChecked={addModelMode === 'simple'} onClick={handleAddModelSimple}>
-          {t('common.simple')}
-        </Button>
-        <Button size="sm" isChecked={addModelMode === 'advanced'} onClick={handleAddModelAdvanced}>
-          {t('common.advanced')}
-        </Button>
-      </ButtonGroup>
-      <Flex p={4} borderRadius={4} bg="base.800">
-        {addModelMode === 'simple' && <SimpleAddModels />}
-        {addModelMode === 'advanced' && <AdvancedAddModels />}
-      </Flex>
-      <Flex>{data?.map((model) => <Text key={model.id}>{model.status}</Text>)}</Flex>
-    </Flex>
-  );
-};
-
-export default memo(AddModels);
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/AdvancedAddCheckpoint.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/AdvancedAddCheckpoint.tsx
deleted file mode 100644
index 31f4312eb5..0000000000
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/AdvancedAddCheckpoint.tsx
+++ /dev/null
@@ -1,168 +0,0 @@
-import { Button, Checkbox, Flex, FormControl, FormErrorMessage, FormLabel, Input } from '@invoke-ai/ui-library';
-import { useAppDispatch } from 'app/store/storeHooks';
-import { setAdvancedAddScanModel } from 'features/modelManager/store/modelManagerSlice';
-import BaseModelSelect from 'features/modelManager/subpanels/shared/BaseModelSelect';
-import CheckpointConfigsSelect from 'features/modelManager/subpanels/shared/CheckpointConfigsSelect';
-import ModelVariantSelect from 'features/modelManager/subpanels/shared/ModelVariantSelect';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
-import type { CSSProperties, FocusEventHandler } from 'react';
-import { memo, useCallback, useState } from 'react';
-import type { SubmitHandler } from 'react-hook-form';
-import { useForm } from 'react-hook-form';
-import { useTranslation } from 'react-i18next';
-import { useAddMainModelsMutation } from 'services/api/endpoints/models';
-import type { CheckpointModelConfig } from 'services/api/types';
-
-import { getModelName } from './util';
-
-type AdvancedAddCheckpointProps = {
-  model_path?: string;
-};
-
-const AdvancedAddCheckpoint = (props: AdvancedAddCheckpointProps) => {
-  const { t } = useTranslation();
-  const dispatch = useAppDispatch();
-  const { model_path } = props;
-
-  const {
-    register,
-    handleSubmit,
-    control,
-    getValues,
-    setValue,
-    formState: { errors },
-    reset,
-  } = useForm<CheckpointModelConfig>({
-    defaultValues: {
-      model_name: model_path ? getModelName(model_path) : '',
-      base_model: 'sd-1',
-      model_type: 'main',
-      path: model_path ? model_path : '',
-      description: '',
-      model_format: 'checkpoint',
-      error: undefined,
-      vae: '',
-      variant: 'normal',
-      config: 'configs\\stable-diffusion\\v1-inference.yaml',
-    },
-    mode: 'onChange',
-  });
-
-  const [addMainModel] = useAddMainModelsMutation();
-
-  const [useCustomConfig, setUseCustomConfig] = useState<boolean>(false);
-
-  const onSubmit = useCallback<SubmitHandler<CheckpointModelConfig>>(
-    (values) => {
-      addMainModel({
-        body: values,
-      })
-        .unwrap()
-        .then((_) => {
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('modelManager.modelAdded', {
-                  modelName: values.model_name,
-                }),
-                status: 'success',
-              })
-            )
-          );
-          reset();
-
-          // Close Advanced Panel in Scan Models tab
-          if (model_path) {
-            dispatch(setAdvancedAddScanModel(null));
-          }
-        })
-        .catch((error) => {
-          if (error) {
-            dispatch(
-              addToast(
-                makeToast({
-                  title: t('toast.modelAddFailed'),
-                  status: 'error',
-                })
-              )
-            );
-          }
-        });
-    },
-    [addMainModel, dispatch, model_path, reset, t]
-  );
-
-  const onBlur: FocusEventHandler<HTMLInputElement> = useCallback(
-    (e) => {
-      if (getValues().model_name === '') {
-        const modelName = getModelName(e.currentTarget.value);
-        if (modelName) {
-          setValue('model_name', modelName as string);
-        }
-      }
-    },
-    [getValues, setValue]
-  );
-
-  const handleChangeUseCustomConfig = useCallback(() => setUseCustomConfig((prev) => !prev), []);
-
-  return (
-    <form onSubmit={handleSubmit(onSubmit)} style={formStyles}>
-      <Flex flexDirection="column" gap={2}>
-        <FormControl isInvalid={Boolean(errors.model_name)}>
-          <FormLabel>{t('modelManager.model')}</FormLabel>
-          <Input
-            {...register('model_name', {
-              validate: (value) => value.trim().length > 3 || 'Must be at least 3 characters',
-            })}
-          />
-          {errors.model_name?.message && <FormErrorMessage>{errors.model_name?.message}</FormErrorMessage>}
-        </FormControl>
-        <BaseModelSelect<CheckpointModelConfig> control={control} name="base_model" />
-        <FormControl isInvalid={Boolean(errors.path)}>
-          <FormLabel>{t('modelManager.modelLocation')}</FormLabel>
-          <Input
-            {...register('path', {
-              validate: (value) => value.trim().length > 0 || 'Must provide a path',
-              onBlur,
-            })}
-          />
-          {errors.path?.message && <FormErrorMessage>{errors.path?.message}</FormErrorMessage>}
-        </FormControl>
-        <FormControl>
-          <FormLabel>{t('modelManager.description')}</FormLabel>
-          <Input {...register('description')} />
-        </FormControl>
-        <FormControl>
-          <FormLabel>{t('modelManager.vaeLocation')}</FormLabel>
-          <Input {...register('vae')} />
-        </FormControl>
-        <ModelVariantSelect<CheckpointModelConfig> control={control} name="variant" />
-        <Flex flexDirection="column" width="100%" gap={2}>
-          {!useCustomConfig ? (
-            <CheckpointConfigsSelect control={control} name="config" />
-          ) : (
-            <FormControl isRequired>
-              <FormLabel>{t('modelManager.config')}</FormLabel>
-              <Input {...register('config')} />
-            </FormControl>
-          )}
-          <FormControl>
-            <FormLabel>{t('modelManager.useCustomConfig')}</FormLabel>
-            <Checkbox isChecked={useCustomConfig} onChange={handleChangeUseCustomConfig} />
-          </FormControl>
-          <Button mt={2} type="submit">
-            {t('modelManager.addModel')}
-          </Button>
-        </Flex>
-      </Flex>
-    </form>
-  );
-};
-
-const formStyles: CSSProperties = {
-  width: '100%',
-};
-
-export default memo(AdvancedAddCheckpoint);
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/AdvancedAddDiffusers.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/AdvancedAddDiffusers.tsx
deleted file mode 100644
index 07b28d35fd..0000000000
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/AdvancedAddDiffusers.tsx
+++ /dev/null
@@ -1,148 +0,0 @@
-import { Button, Flex, FormControl, FormErrorMessage, FormLabel, Input } from '@invoke-ai/ui-library';
-import { useAppDispatch } from 'app/store/storeHooks';
-import { setAdvancedAddScanModel } from 'features/modelManager/store/modelManagerSlice';
-import BaseModelSelect from 'features/modelManager/subpanels/shared/BaseModelSelect';
-import ModelVariantSelect from 'features/modelManager/subpanels/shared/ModelVariantSelect';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
-import type { CSSProperties, FocusEventHandler } from 'react';
-import { memo, useCallback } from 'react';
-import type { SubmitHandler } from 'react-hook-form';
-import { useForm } from 'react-hook-form';
-import { useTranslation } from 'react-i18next';
-import { useAddMainModelsMutation } from 'services/api/endpoints/models';
-import type { DiffusersModelConfig } from 'services/api/types';
-
-import { getModelName } from './util';
-
-type AdvancedAddDiffusersProps = {
-  model_path?: string;
-};
-
-const AdvancedAddDiffusers = (props: AdvancedAddDiffusersProps) => {
-  const { t } = useTranslation();
-  const dispatch = useAppDispatch();
-  const { model_path } = props;
-
-  const [addMainModel] = useAddMainModelsMutation();
-
-  const {
-    register,
-    handleSubmit,
-    control,
-    getValues,
-    setValue,
-    formState: { errors },
-    reset,
-  } = useForm<DiffusersModelConfig>({
-    defaultValues: {
-      model_name: model_path ? getModelName(model_path, false) : '',
-      base_model: 'sd-1',
-      model_type: 'main',
-      path: model_path ? model_path : '',
-      description: '',
-      model_format: 'diffusers',
-      error: undefined,
-      vae: '',
-      variant: 'normal',
-    },
-    mode: 'onChange',
-  });
-
-  const onSubmit = useCallback<SubmitHandler<DiffusersModelConfig>>(
-    (values) => {
-      addMainModel({
-        body: values,
-      })
-        .unwrap()
-        .then((_) => {
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('modelManager.modelAdded', {
-                  modelName: values.model_name,
-                }),
-                status: 'success',
-              })
-            )
-          );
-          reset();
-          // Close Advanced Panel in Scan Models tab
-          if (model_path) {
-            dispatch(setAdvancedAddScanModel(null));
-          }
-        })
-        .catch((error) => {
-          if (error) {
-            dispatch(
-              addToast(
-                makeToast({
-                  title: t('toast.modelAddFailed'),
-                  status: 'error',
-                })
-              )
-            );
-          }
-        });
-    },
-    [addMainModel, dispatch, model_path, reset, t]
-  );
-
-  const onBlur: FocusEventHandler<HTMLInputElement> = useCallback(
-    (e) => {
-      if (getValues().model_name === '') {
-        const modelName = getModelName(e.currentTarget.value, false);
-        if (modelName) {
-          setValue('model_name', modelName as string);
-        }
-      }
-    },
-    [getValues, setValue]
-  );
-
-  return (
-    <form onSubmit={handleSubmit(onSubmit)} style={formStyles}>
-      <Flex flexDirection="column" gap={2}>
-        <FormControl isInvalid={Boolean(errors.model_name)}>
-          <FormLabel>{t('modelManager.name')}</FormLabel>
-          <Input
-            {...register('model_name', {
-              validate: (value) => value.trim().length > 3 || 'Must be at least 3 characters',
-            })}
-          />
-          {errors.model_name?.message && <FormErrorMessage>{errors.model_name?.message}</FormErrorMessage>}
-        </FormControl>
-        <BaseModelSelect<DiffusersModelConfig> control={control} name="base_model" />
-        <FormControl isInvalid={Boolean(errors.path)}>
-          <FormLabel>{t('modelManager.modelLocation')}</FormLabel>
-          <Input
-            {...register('path', {
-              validate: (value) => value.trim().length > 0 || 'Must provide a path',
-              onBlur,
-            })}
-          />
-          {errors.path?.message && <FormErrorMessage>{errors.path?.message}</FormErrorMessage>}
-        </FormControl>
-        <FormControl>
-          <FormLabel>{t('modelManager.description')}</FormLabel>
-          <Input {...register('description')} />
-        </FormControl>
-        <FormControl>
-          <FormLabel>{t('modelManager.vaeLocation')}</FormLabel>
-          <Input {...register('vae')} />
-        </FormControl>
-        <ModelVariantSelect<DiffusersModelConfig> control={control} name="variant" />
-
-        <Button mt={2} type="submit">
-          {t('modelManager.addModel')}
-        </Button>
-      </Flex>
-    </form>
-  );
-};
-
-const formStyles: CSSProperties = {
-  width: '100%',
-};
-
-export default memo(AdvancedAddDiffusers);
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/AdvancedAddModels.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/AdvancedAddModels.tsx
deleted file mode 100644
index fc03c6bb1f..0000000000
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/AdvancedAddModels.tsx
+++ /dev/null
@@ -1,50 +0,0 @@
-import type { ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
-import { Combobox, Flex, FormControl, FormLabel } from '@invoke-ai/ui-library';
-import { memo, useCallback, useMemo, useState } from 'react';
-import { useTranslation } from 'react-i18next';
-import { z } from 'zod';
-
-import AdvancedAddCheckpoint from './AdvancedAddCheckpoint';
-import AdvancedAddDiffusers from './AdvancedAddDiffusers';
-
-export const zManualAddMode = z.enum(['diffusers', 'checkpoint']);
-export type ManualAddMode = z.infer<typeof zManualAddMode>;
-export const isManualAddMode = (v: unknown): v is ManualAddMode => zManualAddMode.safeParse(v).success;
-
-const AdvancedAddModels = () => {
-  const [advancedAddMode, setAdvancedAddMode] = useState<ManualAddMode>('diffusers');
-
-  const { t } = useTranslation();
-  const handleChange: ComboboxOnChange = useCallback((v) => {
-    if (!isManualAddMode(v?.value)) {
-      return;
-    }
-    setAdvancedAddMode(v.value);
-  }, []);
-
-  const options: ComboboxOption[] = useMemo(
-    () => [
-      { label: t('modelManager.diffusersModels'), value: 'diffusers' },
-      { label: t('modelManager.checkpointOrSafetensors'), value: 'checkpoint' },
-    ],
-    [t]
-  );
-
-  const value = useMemo(() => options.find((o) => o.value === advancedAddMode), [options, advancedAddMode]);
-
-  return (
-    <Flex flexDirection="column" gap={4} width="100%">
-      <FormControl>
-        <FormLabel>{t('modelManager.modelType')}</FormLabel>
-        <Combobox value={value} options={options} onChange={handleChange} />
-      </FormControl>
-
-      <Flex p={4} borderRadius={4} bg="base.850">
-        {advancedAddMode === 'diffusers' && <AdvancedAddDiffusers />}
-        {advancedAddMode === 'checkpoint' && <AdvancedAddCheckpoint />}
-      </Flex>
-    </Flex>
-  );
-};
-
-export default memo(AdvancedAddModels);
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/FoundModelsList.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/FoundModelsList.tsx
deleted file mode 100644
index 206a955e29..0000000000
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/FoundModelsList.tsx
+++ /dev/null
@@ -1,176 +0,0 @@
-import { Button, Flex, FormControl, FormLabel, Input, Text } from '@invoke-ai/ui-library';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
-import { setAdvancedAddScanModel } from 'features/modelManager/store/modelManagerSlice';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
-import { difference, forEach, intersection, map, values } from 'lodash-es';
-import type { ChangeEvent, MouseEvent } from 'react';
-import { memo, useCallback, useState } from 'react';
-import { useTranslation } from 'react-i18next';
-import { ALL_BASE_MODELS } from 'services/api/constants';
-import type { SearchFolderResponse } from 'services/api/endpoints/models';
-import {
-  useGetMainModelsQuery,
-  useGetModelsInFolderQuery,
-  useImportMainModelsMutation,
-} from 'services/api/endpoints/models';
-
-const FoundModelsList = () => {
-  const searchFolder = useAppSelector((s) => s.modelmanager.searchFolder);
-  const [nameFilter, setNameFilter] = useState<string>('');
-
-  // Get paths of models that are already installed
-  const { data: installedModels } = useGetMainModelsQuery(ALL_BASE_MODELS);
-
-  // Get all model paths from a given directory
-  const { foundModels, alreadyInstalled, filteredModels } = useGetModelsInFolderQuery(
-    {
-      search_path: searchFolder ? searchFolder : '',
-    },
-    {
-      selectFromResult: ({ data }) => {
-        const installedModelValues = values(installedModels?.entities);
-        const installedModelPaths = map(installedModelValues, 'path');
-        // Only select models those that aren't already installed to Invoke
-        const notInstalledModels = difference(data, installedModelPaths);
-        const alreadyInstalled = intersection(data, installedModelPaths);
-        return {
-          foundModels: data,
-          alreadyInstalled: foundModelsFilter(alreadyInstalled, nameFilter),
-          filteredModels: foundModelsFilter(notInstalledModels, nameFilter),
-        };
-      },
-    }
-  );
-
-  const [importMainModel, { isLoading }] = useImportMainModelsMutation();
-  const dispatch = useAppDispatch();
-  const { t } = useTranslation();
-
-  const quickAddHandler = useCallback(
-    (e: MouseEvent<HTMLButtonElement>) => {
-      const model_name = e.currentTarget.id.split('\\').splice(-1)[0];
-      importMainModel({
-        body: {
-          location: e.currentTarget.id,
-        },
-      })
-        .unwrap()
-        .then((_) => {
-          dispatch(
-            addToast(
-              makeToast({
-                title: `Added Model: ${model_name}`,
-                status: 'success',
-              })
-            )
-          );
-        })
-        .catch((error) => {
-          if (error) {
-            dispatch(
-              addToast(
-                makeToast({
-                  title: t('toast.modelAddFailed'),
-                  status: 'error',
-                })
-              )
-            );
-          }
-        });
-    },
-    [dispatch, importMainModel, t]
-  );
-
-  const handleSearchFilter = useCallback((e: ChangeEvent<HTMLInputElement>) => {
-    setNameFilter(e.target.value);
-  }, []);
-
-  const handleClickSetAdvanced = useCallback((model: string) => dispatch(setAdvancedAddScanModel(model)), [dispatch]);
-
-  const renderModels = ({ models, showActions = true }: { models: string[]; showActions?: boolean }) => {
-    return models.map((model) => {
-      return (
-        <Flex key={model} p={4} gap={4} alignItems="center" borderRadius={4} bg="base.800">
-          <Flex w="full" minW="25%" flexDir="column">
-            <Text fontWeight="semibold">{model.split('\\').slice(-1)[0]}</Text>
-            <Text fontSize="sm" color="base.400">
-              {model}
-            </Text>
-          </Flex>
-          {showActions ? (
-            <Flex gap={2}>
-              <Button id={model} onClick={quickAddHandler} isLoading={isLoading}>
-                {t('modelManager.quickAdd')}
-              </Button>
-              <Button onClick={handleClickSetAdvanced.bind(null, model)} isLoading={isLoading}>
-                {t('modelManager.advanced')}
-              </Button>
-            </Flex>
-          ) : (
-            <Text fontWeight="semibold" p={2} borderRadius={4} color="invokeBlue.100" bg="invokeBlue.600">
-              {t('common.installed')}
-            </Text>
-          )}
-        </Flex>
-      );
-    });
-  };
-
-  const renderFoundModels = () => {
-    if (!searchFolder) {
-      return null;
-    }
-
-    if (!foundModels || foundModels.length === 0) {
-      return (
-        <Flex w="full" h="full" justifyContent="center" alignItems="center" height={96} userSelect="none" bg="base.900">
-          <Text variant="subtext">{t('modelManager.noModels')}</Text>
-        </Flex>
-      );
-    }
-
-    return (
-      <Flex flexDirection="column" gap={2} w="100%" minW="50%">
-        <FormControl>
-          <FormLabel>{t('modelManager.search')}</FormLabel>
-          <Input onChange={handleSearchFilter} />
-        </FormControl>
-        <Flex p={2} gap={2}>
-          <Text fontWeight="semibold">
-            {t('modelManager.modelsFound')}: {foundModels.length}
-          </Text>
-          <Text fontWeight="semibold" color="invokeBlue.200">
-            {t('common.notInstalled')}: {filteredModels.length}
-          </Text>
-        </Flex>
-
-        <ScrollableContent>
-          <Flex gap={2} flexDirection="column">
-            {renderModels({ models: filteredModels })}
-            {renderModels({ models: alreadyInstalled, showActions: false })}
-          </Flex>
-        </ScrollableContent>
-      </Flex>
-    );
-  };
-
-  return renderFoundModels();
-};
-
-const foundModelsFilter = (data: SearchFolderResponse | undefined, nameFilter: string) => {
-  const filteredModels: SearchFolderResponse = [];
-  forEach(data, (model) => {
-    if (!model) {
-      return null;
-    }
-
-    if (model.includes(nameFilter)) {
-      filteredModels.push(model);
-    }
-  });
-  return filteredModels;
-};
-
-export default memo(FoundModelsList);
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/ScanAdvancedAddModels.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/ScanAdvancedAddModels.tsx
deleted file mode 100644
index 445eb7ed5a..0000000000
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/ScanAdvancedAddModels.tsx
+++ /dev/null
@@ -1,95 +0,0 @@
-import type { ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
-import { Box, Combobox, Flex, FormControl, FormLabel, IconButton, Text } from '@invoke-ai/ui-library';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import { setAdvancedAddScanModel } from 'features/modelManager/store/modelManagerSlice';
-import { memo, useCallback, useEffect, useMemo, useState } from 'react';
-import { useTranslation } from 'react-i18next';
-import { PiXBold } from 'react-icons/pi';
-
-import AdvancedAddCheckpoint from './AdvancedAddCheckpoint';
-import AdvancedAddDiffusers from './AdvancedAddDiffusers';
-import type { ManualAddMode } from './AdvancedAddModels';
-import { isManualAddMode } from './AdvancedAddModels';
-
-const ScanAdvancedAddModels = () => {
-  const advancedAddScanModel = useAppSelector((s) => s.modelmanager.advancedAddScanModel);
-
-  const { t } = useTranslation();
-
-  const options: ComboboxOption[] = useMemo(
-    () => [
-      { label: t('modelManager.diffusersModels'), value: 'diffusers' },
-      { label: t('modelManager.checkpointOrSafetensors'), value: 'checkpoint' },
-    ],
-    [t]
-  );
-
-  const [advancedAddMode, setAdvancedAddMode] = useState<ManualAddMode>('diffusers');
-
-  const [isCheckpoint, setIsCheckpoint] = useState<boolean>(true);
-
-  useEffect(() => {
-    advancedAddScanModel && ['.ckpt', '.safetensors', '.pth', '.pt'].some((ext) => advancedAddScanModel.endsWith(ext))
-      ? setAdvancedAddMode('checkpoint')
-      : setAdvancedAddMode('diffusers');
-  }, [advancedAddScanModel, setAdvancedAddMode, isCheckpoint]);
-
-  const dispatch = useAppDispatch();
-
-  const handleClickSetAdvanced = useCallback(() => dispatch(setAdvancedAddScanModel(null)), [dispatch]);
-
-  const handleChangeAddMode = useCallback<ComboboxOnChange>((v) => {
-    if (!isManualAddMode(v?.value)) {
-      return;
-    }
-    setAdvancedAddMode(v.value);
-    if (v.value === 'checkpoint') {
-      setIsCheckpoint(true);
-    } else {
-      setIsCheckpoint(false);
-    }
-  }, []);
-
-  const value = useMemo(() => options.find((o) => o.value === advancedAddMode), [options, advancedAddMode]);
-
-  if (!advancedAddScanModel) {
-    return null;
-  }
-
-  return (
-    <Box
-      display="flex"
-      flexDirection="column"
-      minWidth="40%"
-      maxHeight="calc(100vh - 300px)"
-      overflow="scroll"
-      p={4}
-      gap={4}
-      borderRadius={4}
-      bg="base.800"
-    >
-      <Flex justifyContent="space-between" alignItems="center">
-        <Text size="xl" fontWeight="semibold">
-          {isCheckpoint || advancedAddMode === 'checkpoint' ? 'Add Checkpoint Model' : 'Add Diffusers Model'}
-        </Text>
-        <IconButton
-          icon={<PiXBold />}
-          aria-label={t('modelManager.closeAdvanced')}
-          onClick={handleClickSetAdvanced}
-          size="sm"
-        />
-      </Flex>
-      <FormControl>
-        <FormLabel>{t('modelManager.modelType')}</FormLabel>
-        <Combobox value={value} options={options} onChange={handleChangeAddMode} />
-      </FormControl>
-      {isCheckpoint ? (
-        <AdvancedAddCheckpoint key={advancedAddScanModel} model_path={advancedAddScanModel} />
-      ) : (
-        <AdvancedAddDiffusers key={advancedAddScanModel} model_path={advancedAddScanModel} />
-      )}
-    </Box>
-  );
-};
-
-export default memo(ScanAdvancedAddModels);
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/ScanModels.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/ScanModels.tsx
deleted file mode 100644
index f3287270a2..0000000000
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/ScanModels.tsx
+++ /dev/null
@@ -1,22 +0,0 @@
-import { Flex } from '@invoke-ai/ui-library';
-import { memo } from 'react';
-
-import FoundModelsList from './FoundModelsList';
-import ScanAdvancedAddModels from './ScanAdvancedAddModels';
-import SearchFolderForm from './SearchFolderForm';
-
-const ScanModels = () => {
-  return (
-    <Flex flexDirection="column" w="100%" h="full" gap={4}>
-      <SearchFolderForm />
-      <Flex gap={4}>
-        <Flex overflow="scroll" gap={4} w="100%" h="full">
-          <FoundModelsList />
-        </Flex>
-        <ScanAdvancedAddModels />
-      </Flex>
-    </Flex>
-  );
-};
-
-export default memo(ScanModels);
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/SearchFolderForm.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/SearchFolderForm.tsx
deleted file mode 100644
index dc1d39f7aa..0000000000
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/SearchFolderForm.tsx
+++ /dev/null
@@ -1,103 +0,0 @@
-import { Flex, IconButton, Input, Text } from '@invoke-ai/ui-library';
-import { useForm } from '@mantine/form';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import { setAdvancedAddScanModel, setSearchFolder } from 'features/modelManager/store/modelManagerSlice';
-import type { CSSProperties } from 'react';
-import { memo, useCallback } from 'react';
-import { useTranslation } from 'react-i18next';
-import { PiArrowsCounterClockwiseBold, PiMagnifyingGlassBold, PiTrashSimpleBold } from 'react-icons/pi';
-import { useGetModelsInFolderQuery } from 'services/api/endpoints/models';
-
-type SearchFolderForm = {
-  folder: string;
-};
-
-function SearchFolderForm() {
-  const dispatch = useAppDispatch();
-  const { t } = useTranslation();
-
-  const searchFolder = useAppSelector((s) => s.modelmanager.searchFolder);
-
-  const { refetch: refetchFoundModels } = useGetModelsInFolderQuery({
-    search_path: searchFolder ? searchFolder : '',
-  });
-
-  const searchFolderForm = useForm<SearchFolderForm>({
-    initialValues: {
-      folder: '',
-    },
-  });
-
-  const searchFolderFormSubmitHandler = useCallback(
-    (values: SearchFolderForm) => {
-      dispatch(setSearchFolder(values.folder));
-    },
-    [dispatch]
-  );
-
-  const scanAgainHandler = useCallback(() => {
-    refetchFoundModels();
-  }, [refetchFoundModels]);
-
-  const handleClickClearCheckpointFolder = useCallback(() => {
-    dispatch(setSearchFolder(null));
-    dispatch(setAdvancedAddScanModel(null));
-  }, [dispatch]);
-
-  return (
-    <form onSubmit={searchFolderForm.onSubmit((values) => searchFolderFormSubmitHandler(values))} style={formStyles}>
-      <Flex w="100%" gap={2} borderRadius={4} alignItems="center">
-        <Flex w="100%" alignItems="center" gap={4} minH={12}>
-          <Text fontSize="sm" fontWeight="semibold" color="base.300" minW="max-content">
-            {t('common.folder')}
-          </Text>
-          {!searchFolder ? (
-            <Input w="100%" size="md" {...searchFolderForm.getInputProps('folder')} />
-          ) : (
-            <Flex w="100%" p={2} px={4} bg="base.700" borderRadius={4} fontSize="sm" fontWeight="bold">
-              {searchFolder}
-            </Flex>
-          )}
-        </Flex>
-
-        <Flex gap={2}>
-          {!searchFolder ? (
-            <IconButton
-              aria-label={t('modelManager.findModels')}
-              tooltip={t('modelManager.findModels')}
-              icon={<PiMagnifyingGlassBold />}
-              fontSize={18}
-              size="sm"
-              type="submit"
-            />
-          ) : (
-            <IconButton
-              aria-label={t('modelManager.scanAgain')}
-              tooltip={t('modelManager.scanAgain')}
-              icon={<PiArrowsCounterClockwiseBold />}
-              onClick={scanAgainHandler}
-              fontSize={18}
-              size="sm"
-            />
-          )}
-
-          <IconButton
-            aria-label={t('modelManager.clearCheckpointFolder')}
-            tooltip={t('modelManager.clearCheckpointFolder')}
-            icon={<PiTrashSimpleBold />}
-            size="sm"
-            onClick={handleClickClearCheckpointFolder}
-            isDisabled={!searchFolder}
-            colorScheme="red"
-          />
-        </Flex>
-      </Flex>
-    </form>
-  );
-}
-
-export default memo(SearchFolderForm);
-
-const formStyles: CSSProperties = {
-  width: '100%',
-};
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/SimpleAddModels.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/SimpleAddModels.tsx
deleted file mode 100644
index 0124d6d570..0000000000
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/SimpleAddModels.tsx
+++ /dev/null
@@ -1,92 +0,0 @@
-import type { ComboboxOption } from '@invoke-ai/ui-library';
-import { Button, Combobox, Flex, FormControl, FormLabel, Input } from '@invoke-ai/ui-library';
-import { useForm } from '@mantine/form';
-import { useAppDispatch } from 'app/store/storeHooks';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
-import type { CSSProperties } from 'react';
-import { memo } from 'react';
-import { useTranslation } from 'react-i18next';
-import { useImportMainModelsMutation } from 'services/api/endpoints/models';
-
-const options: ComboboxOption[] = [
-  { label: 'None', value: 'none' },
-  { label: 'v_prediction', value: 'v_prediction' },
-  { label: 'epsilon', value: 'epsilon' },
-  { label: 'sample', value: 'sample' },
-];
-
-type ExtendedImportModelConfig = {
-  location: string;
-  prediction_type?: 'v_prediction' | 'epsilon' | 'sample' | 'none' | undefined;
-};
-
-const SimpleAddModels = () => {
-  const dispatch = useAppDispatch();
-  const { t } = useTranslation();
-
-  const [importMainModel, { isLoading }] = useImportMainModelsMutation();
-
-  const addModelForm = useForm<ExtendedImportModelConfig>({
-    initialValues: {
-      location: '',
-      prediction_type: undefined,
-    },
-  });
-
-  const handleAddModelSubmit = (values: ExtendedImportModelConfig) => {
-    const importModelResponseBody = {
-      config: values.prediction_type === 'none' ? undefined : values.prediction_type,
-    };
-
-    importMainModel({ source: values.location, config: importModelResponseBody })
-      .unwrap()
-      .then((_) => {
-        dispatch(
-          addToast(
-            makeToast({
-              title: t('toast.modelAddedSimple'),
-              status: 'success',
-            })
-          )
-        );
-        addModelForm.reset();
-      })
-      .catch((error) => {
-        if (error) {
-          dispatch(
-            addToast(
-              makeToast({
-                title: `${error.data.detail} `,
-                status: 'error',
-              })
-            )
-          );
-        }
-      });
-  };
-
-  return (
-    <form onSubmit={addModelForm.onSubmit((v) => handleAddModelSubmit(v))} style={formStyles}>
-      <Flex flexDirection="column" width="100%" gap={4}>
-        <FormControl>
-          <FormLabel>{t('modelManager.modelLocation')}</FormLabel>
-          <Input placeholder={t('modelManager.simpleModelDesc')} w="100%" {...addModelForm.getInputProps('location')} />
-        </FormControl>
-        <FormControl>
-          <FormLabel>{t('modelManager.predictionType')}</FormLabel>
-          <Combobox options={options} defaultValue={options[0]} {...addModelForm.getInputProps('prediction_type')} />
-        </FormControl>
-        <Button type="submit" isLoading={isLoading}>
-          {t('modelManager.addModel')}
-        </Button>
-      </Flex>
-    </form>
-  );
-};
-
-const formStyles: CSSProperties = {
-  width: '100%',
-};
-
-export default memo(SimpleAddModels);
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/util.ts b/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/util.ts
deleted file mode 100644
index 7314a86908..0000000000
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/AddModelsPanel/util.ts
+++ /dev/null
@@ -1,15 +0,0 @@
-export function getModelName(filepath: string, isCheckpoint: boolean = true) {
-  let regex;
-  if (isCheckpoint) {
-    regex = new RegExp('[^\\\\/]+(?=\\.)');
-  } else {
-    regex = new RegExp('[^\\\\/]+(?=[\\\\/]?$)');
-  }
-
-  const match = filepath.match(regex);
-  if (match) {
-    return match[0];
-  } else {
-    return '';
-  }
-}
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ImportModelsPanel.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ImportModelsPanel.tsx
deleted file mode 100644
index 960f798e79..0000000000
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ImportModelsPanel.tsx
+++ /dev/null
@@ -1,34 +0,0 @@
-import { Button, ButtonGroup, Flex } from '@invoke-ai/ui-library';
-import { memo, useCallback, useState } from 'react';
-import { useTranslation } from 'react-i18next';
-
-import AddModels from './AddModelsPanel/AddModels';
-import ScanModels from './AddModelsPanel/ScanModels';
-
-type AddModelTabs = 'add' | 'scan';
-
-const ImportModelsPanel = () => {
-  const [addModelTab, setAddModelTab] = useState<AddModelTabs>('add');
-  const { t } = useTranslation();
-
-  const handleClickAddTab = useCallback(() => setAddModelTab('add'), []);
-  const handleClickScanTab = useCallback(() => setAddModelTab('scan'), []);
-
-  return (
-    <Flex flexDirection="column" gap={4} h="full">
-      <ButtonGroup>
-        <Button onClick={handleClickAddTab} isChecked={addModelTab === 'add'} size="sm" width="100%">
-          {t('modelManager.addModel')}
-        </Button>
-        <Button onClick={handleClickScanTab} isChecked={addModelTab === 'scan'} size="sm" width="100%">
-          {t('modelManager.scanForModels')}
-        </Button>
-      </ButtonGroup>
-
-      {addModelTab === 'add' && <AddModels />}
-      {addModelTab === 'scan' && <ScanModels />}
-    </Flex>
-  );
-};
-
-export default memo(ImportModelsPanel);
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/MergeModelsPanel.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/MergeModelsPanel.tsx
deleted file mode 100644
index fe90db5b8a..0000000000
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/MergeModelsPanel.tsx
+++ /dev/null
@@ -1,352 +0,0 @@
-import type { ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
-import {
-  Button,
-  Checkbox,
-  Combobox,
-  CompositeNumberInput,
-  CompositeSlider,
-  Flex,
-  FormControl,
-  FormHelperText,
-  FormLabel,
-  Input,
-  Radio,
-  RadioGroup,
-  Text,
-  Tooltip,
-} from '@invoke-ai/ui-library';
-import { useAppDispatch } from 'app/store/storeHooks';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
-import { pickBy } from 'lodash-es';
-import type { ChangeEvent } from 'react';
-import { memo, useCallback, useMemo, useState } from 'react';
-import { useTranslation } from 'react-i18next';
-import { ALL_BASE_MODELS } from 'services/api/constants';
-import { useGetMainModelsQuery, useMergeMainModelsMutation } from 'services/api/endpoints/models';
-import type { BaseModelType, MergeModelConfig } from 'services/api/types';
-
-const baseModelTypeSelectOptions: ComboboxOption[] = [
-  { label: 'Stable Diffusion 1', value: 'sd-1' },
-  { label: 'Stable Diffusion 2', value: 'sd-2' },
-];
-
-type MergeInterpolationMethods = 'weighted_sum' | 'sigmoid' | 'inv_sigmoid' | 'add_difference';
-
-const MergeModelsPanel = () => {
-  const { t } = useTranslation();
-  const dispatch = useAppDispatch();
-
-  const { data } = useGetMainModelsQuery(ALL_BASE_MODELS);
-
-  const [mergeModels, { isLoading }] = useMergeMainModelsMutation();
-
-  const [baseModel, setBaseModel] = useState<BaseModelType>('sd-1');
-  const valueBaseModel = useMemo(() => baseModelTypeSelectOptions.find((o) => o.value === baseModel), [baseModel]);
-  const sd1DiffusersModels = pickBy(
-    data?.entities,
-    (value, _) => value?.model_format === 'diffusers' && value?.base_model === 'sd-1'
-  );
-
-  const sd2DiffusersModels = pickBy(
-    data?.entities,
-    (value, _) => value?.model_format === 'diffusers' && value?.base_model === 'sd-2'
-  );
-
-  const modelsMap = useMemo(() => {
-    return {
-      'sd-1': sd1DiffusersModels,
-      'sd-2': sd2DiffusersModels,
-    };
-  }, [sd1DiffusersModels, sd2DiffusersModels]);
-
-  const [modelOne, setModelOne] = useState<string | null>(
-    Object.keys(modelsMap[baseModel as keyof typeof modelsMap])?.[0] ?? null
-  );
-  const [modelTwo, setModelTwo] = useState<string | null>(
-    Object.keys(modelsMap[baseModel as keyof typeof modelsMap])?.[1] ?? null
-  );
-  const [modelThree, setModelThree] = useState<string | null>(null);
-
-  const [mergedModelName, setMergedModelName] = useState<string>('');
-  const [modelMergeAlpha, setModelMergeAlpha] = useState<number>(0.5);
-
-  const [modelMergeInterp, setModelMergeInterp] = useState<MergeInterpolationMethods>('weighted_sum');
-
-  const [modelMergeSaveLocType, setModelMergeSaveLocType] = useState<'root' | 'custom'>('root');
-
-  const [modelMergeCustomSaveLoc, setModelMergeCustomSaveLoc] = useState<string>('');
-
-  const [modelMergeForce, setModelMergeForce] = useState<boolean>(false);
-
-  const optionsModelOne = useMemo(
-    () =>
-      Object.keys(modelsMap[baseModel as keyof typeof modelsMap])
-        .filter((model) => model !== modelTwo && model !== modelThree)
-        .map((model) => ({ label: model, value: model })),
-    [modelsMap, baseModel, modelTwo, modelThree]
-  );
-
-  const optionsModelTwo = useMemo(
-    () =>
-      Object.keys(modelsMap[baseModel as keyof typeof modelsMap])
-        .filter((model) => model !== modelOne && model !== modelThree)
-        .map((model) => ({ label: model, value: model })),
-    [modelsMap, baseModel, modelOne, modelThree]
-  );
-
-  const optionsModelThree = useMemo(
-    () =>
-      Object.keys(modelsMap[baseModel as keyof typeof modelsMap])
-        .filter((model) => model !== modelOne && model !== modelTwo)
-        .map((model) => ({ label: model, value: model })),
-    [modelsMap, baseModel, modelOne, modelTwo]
-  );
-
-  const onChangeBaseModel = useCallback<ComboboxOnChange>((v) => {
-    if (!v) {
-      return;
-    }
-    if (!(v.value === 'sd-1' || v.value === 'sd-2')) {
-      return;
-    }
-    setBaseModel(v.value);
-    setModelOne(null);
-    setModelTwo(null);
-  }, []);
-
-  const onChangeModelOne = useCallback<ComboboxOnChange>((v) => {
-    if (!v) {
-      return;
-    }
-    setModelOne(v.value);
-  }, []);
-  const onChangeModelTwo = useCallback<ComboboxOnChange>((v) => {
-    if (!v) {
-      return;
-    }
-    setModelTwo(v.value);
-  }, []);
-  const onChangeModelThree = useCallback<ComboboxOnChange>((v) => {
-    if (!v) {
-      setModelThree(null);
-      setModelMergeInterp('add_difference');
-    } else {
-      setModelThree(v.value);
-      setModelMergeInterp('weighted_sum');
-    }
-  }, []);
-
-  const valueModelOne = useMemo(() => optionsModelOne.find((o) => o.value === modelOne), [modelOne, optionsModelOne]);
-  const valueModelTwo = useMemo(() => optionsModelTwo.find((o) => o.value === modelTwo), [modelTwo, optionsModelTwo]);
-  const valueModelThree = useMemo(
-    () => optionsModelThree.find((o) => o.value === modelThree),
-    [modelThree, optionsModelThree]
-  );
-
-  const handleChangeMergedModelName = useCallback(
-    (e: ChangeEvent<HTMLInputElement>) => setMergedModelName(e.target.value),
-    []
-  );
-  const handleChangeModelMergeAlpha = useCallback((v: number) => setModelMergeAlpha(v), []);
-  const handleResetModelMergeAlpha = useCallback(() => setModelMergeAlpha(0.5), []);
-  const handleChangeMergeInterp = useCallback((v: MergeInterpolationMethods) => setModelMergeInterp(v), []);
-  const handleChangeMergeSaveLocType = useCallback((v: 'root' | 'custom') => setModelMergeSaveLocType(v), []);
-  const handleChangeMergeCustomSaveLoc = useCallback(
-    (e: ChangeEvent<HTMLInputElement>) => setModelMergeCustomSaveLoc(e.target.value),
-    []
-  );
-  const handleChangeModelMergeForce = useCallback(
-    (e: ChangeEvent<HTMLInputElement>) => setModelMergeForce(e.target.checked),
-    []
-  );
-
-  const mergeModelsHandler = useCallback(() => {
-    const models_names: string[] = [];
-
-    let modelsToMerge: (string | null)[] = [modelOne, modelTwo, modelThree];
-    modelsToMerge = modelsToMerge.filter((model) => model !== null);
-    modelsToMerge.forEach((model) => {
-      const n = model?.split('/')?.[2];
-      if (n) {
-        models_names.push(n);
-      }
-    });
-
-    const mergeModelsInfo: MergeModelConfig['body'] = {
-      model_names: models_names,
-      merged_model_name: mergedModelName !== '' ? mergedModelName : models_names.join('-'),
-      alpha: modelMergeAlpha,
-      interp: modelMergeInterp,
-      force: modelMergeForce,
-      merge_dest_directory: modelMergeSaveLocType === 'root' ? undefined : modelMergeCustomSaveLoc,
-    };
-
-    mergeModels({
-      base_model: baseModel,
-      body: { body: mergeModelsInfo },
-    })
-      .unwrap()
-      .then((_) => {
-        dispatch(
-          addToast(
-            makeToast({
-              title: t('modelManager.modelsMerged'),
-              status: 'success',
-            })
-          )
-        );
-      })
-      .catch((error) => {
-        if (error) {
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('modelManager.modelsMergeFailed'),
-                status: 'error',
-              })
-            )
-          );
-        }
-      });
-  }, [
-    baseModel,
-    dispatch,
-    mergeModels,
-    mergedModelName,
-    modelMergeAlpha,
-    modelMergeCustomSaveLoc,
-    modelMergeForce,
-    modelMergeInterp,
-    modelMergeSaveLocType,
-    modelOne,
-    modelThree,
-    modelTwo,
-    t,
-  ]);
-
-  return (
-    <Flex flexDir="column" gap={4}>
-      <Flex flexDir="column" gap={1}>
-        <Text>{t('modelManager.modelMergeHeaderHelp1')}</Text>
-        <Text fontSize="sm" variant="subtext">
-          {t('modelManager.modelMergeHeaderHelp2')}
-        </Text>
-      </Flex>
-
-      <Flex columnGap={4}>
-        <FormControl w="full">
-          <FormLabel>{t('modelManager.modelType')}</FormLabel>
-          <Combobox options={baseModelTypeSelectOptions} value={valueBaseModel} onChange={onChangeBaseModel} />
-        </FormControl>
-        <FormControl w="full">
-          <FormLabel>{t('modelManager.modelOne')}</FormLabel>
-          <Combobox options={optionsModelOne} value={valueModelOne} onChange={onChangeModelOne} />
-        </FormControl>
-        <FormControl w="full">
-          <FormLabel>{t('modelManager.modelTwo')}</FormLabel>
-          <Combobox options={optionsModelTwo} value={valueModelTwo} onChange={onChangeModelTwo} />
-        </FormControl>
-        <FormControl w="full">
-          <FormLabel>{t('modelManager.modelThree')}</FormLabel>
-          <Combobox options={optionsModelThree} value={valueModelThree} onChange={onChangeModelThree} isClearable />
-        </FormControl>
-      </Flex>
-
-      <FormControl>
-        <FormLabel>{t('modelManager.mergedModelName')}</FormLabel>
-        <Input value={mergedModelName} onChange={handleChangeMergedModelName} />
-      </FormControl>
-
-      <Flex flexDirection="column" padding={4} borderRadius="base" gap={4} bg="base.800">
-        <FormControl>
-          <FormLabel>{t('modelManager.alpha')}</FormLabel>
-          <CompositeSlider
-            min={0.01}
-            max={0.99}
-            step={0.01}
-            value={modelMergeAlpha}
-            onChange={handleChangeModelMergeAlpha}
-            onReset={handleResetModelMergeAlpha}
-            marks
-          />
-          <CompositeNumberInput
-            min={0.01}
-            max={0.99}
-            step={0.01}
-            value={modelMergeAlpha}
-            onChange={handleChangeModelMergeAlpha}
-            onReset={handleResetModelMergeAlpha}
-          />
-          <FormHelperText>{t('modelManager.modelMergeAlphaHelp')}</FormHelperText>
-        </FormControl>
-      </Flex>
-
-      <Flex padding={4} gap={4} borderRadius="base" bg="base.800">
-        <Text fontSize="sm" variant="subtext">
-          {t('modelManager.interpolationType')}
-        </Text>
-        <RadioGroup value={modelMergeInterp} onChange={handleChangeMergeInterp}>
-          <Flex columnGap={4}>
-            {modelThree === null ? (
-              <>
-                <Radio value="weighted_sum">
-                  <Text fontSize="sm">{t('modelManager.weightedSum')}</Text>
-                </Radio>
-                <Radio value="sigmoid">
-                  <Text fontSize="sm">{t('modelManager.sigmoid')}</Text>
-                </Radio>
-                <Radio value="inv_sigmoid">
-                  <Text fontSize="sm">{t('modelManager.inverseSigmoid')}</Text>
-                </Radio>
-              </>
-            ) : (
-              <Radio value="add_difference">
-                <Tooltip label={t('modelManager.modelMergeInterpAddDifferenceHelp')}>
-                  <Text fontSize="sm">{t('modelManager.addDifference')}</Text>
-                </Tooltip>
-              </Radio>
-            )}
-          </Flex>
-        </RadioGroup>
-      </Flex>
-
-      <Flex flexDirection="column" padding={4} borderRadius="base" gap={4} bg="base.900">
-        <Flex columnGap={4}>
-          <Text fontSize="sm" variant="subtext">
-            {t('modelManager.mergedModelSaveLocation')}
-          </Text>
-          <RadioGroup value={modelMergeSaveLocType} onChange={handleChangeMergeSaveLocType}>
-            <Flex columnGap={4}>
-              <Radio value="root">
-                <Text fontSize="sm">{t('modelManager.invokeAIFolder')}</Text>
-              </Radio>
-
-              <Radio value="custom">
-                <Text fontSize="sm">{t('modelManager.custom')}</Text>
-              </Radio>
-            </Flex>
-          </RadioGroup>
-        </Flex>
-
-        {modelMergeSaveLocType === 'custom' && (
-          <FormControl>
-            <FormLabel>{t('modelManager.mergedModelCustomSaveLocation')}</FormLabel>
-            <Input value={modelMergeCustomSaveLoc} onChange={handleChangeMergeCustomSaveLoc} />
-          </FormControl>
-        )}
-      </Flex>
-
-      <FormControl>
-        <FormLabel>{t('modelManager.ignoreMismatch')}</FormLabel>
-        <Checkbox isChecked={modelMergeForce} onChange={handleChangeModelMergeForce} />
-      </FormControl>
-
-      <Button onClick={mergeModelsHandler} isLoading={isLoading} isDisabled={modelOne === null || modelTwo === null}>
-        {t('modelManager.merge')}
-      </Button>
-    </Flex>
-  );
-};
-
-export default memo(MergeModelsPanel);
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel.tsx
deleted file mode 100644
index 06b5b7db36..0000000000
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel.tsx
+++ /dev/null
@@ -1,63 +0,0 @@
-import { Flex, Text } from '@invoke-ai/ui-library';
-import { memo, useState } from 'react';
-import { useTranslation } from 'react-i18next';
-import { ALL_BASE_MODELS } from 'services/api/constants';
-import { useGetLoRAModelsQuery, useGetMainModelsQuery } from 'services/api/endpoints/models';
-import type { DiffusersModelConfig, LoRAConfig, MainModelConfig } from 'services/api/types';
-
-import CheckpointModelEdit from './ModelManagerPanel/CheckpointModelEdit';
-import DiffusersModelEdit from './ModelManagerPanel/DiffusersModelEdit';
-import LoRAModelEdit from './ModelManagerPanel/LoRAModelEdit';
-import ModelList from './ModelManagerPanel/ModelList';
-
-const ModelManagerPanel = () => {
-  const [selectedModelId, setSelectedModelId] = useState<string>();
-  const { mainModel } = useGetMainModelsQuery(ALL_BASE_MODELS, {
-    selectFromResult: ({ data }) => ({
-      mainModel: selectedModelId ? data?.entities[selectedModelId] : undefined,
-    }),
-  });
-  const { loraModel } = useGetLoRAModelsQuery(undefined, {
-    selectFromResult: ({ data }) => ({
-      loraModel: selectedModelId ? data?.entities[selectedModelId] : undefined,
-    }),
-  });
-
-  const model = mainModel ? mainModel : loraModel;
-
-  return (
-    <Flex gap={8} w="full" h="full">
-      <ModelList selectedModelId={selectedModelId} setSelectedModelId={setSelectedModelId} />
-      <ModelEdit model={model} />
-    </Flex>
-  );
-};
-
-type ModelEditProps = {
-  model: MainModelConfig | LoRAConfig | undefined;
-};
-
-const ModelEdit = (props: ModelEditProps) => {
-  const { t } = useTranslation();
-  const { model } = props;
-
-  if (model?.format === 'checkpoint') {
-    return <CheckpointModelEdit key={model.key} model={model} />;
-  }
-
-  if (model?.format === 'diffusers') {
-    return <DiffusersModelEdit key={model.key} model={model as DiffusersModelConfig} />;
-  }
-
-  if (model?.type === 'lora') {
-    return <LoRAModelEdit key={model.key} model={model} />;
-  }
-
-  return (
-    <Flex w="full" h="full" justifyContent="center" alignItems="center" maxH={96} userSelect="none">
-      <Text variant="subtext">{t('modelManager.noModelSelected')}</Text>
-    </Flex>
-  );
-};
-
-export default memo(ModelManagerPanel);
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/CheckpointModelEdit.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/CheckpointModelEdit.tsx
deleted file mode 100644
index c24d660cc6..0000000000
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/CheckpointModelEdit.tsx
+++ /dev/null
@@ -1,185 +0,0 @@
-import {
-  Badge,
-  Button,
-  Checkbox,
-  Divider,
-  Flex,
-  FormControl,
-  FormErrorMessage,
-  FormLabel,
-  Input,
-  Text,
-} from '@invoke-ai/ui-library';
-import { useAppDispatch } from 'app/store/storeHooks';
-import BaseModelSelect from 'features/modelManager/subpanels/shared/BaseModelSelect';
-import CheckpointConfigsSelect from 'features/modelManager/subpanels/shared/CheckpointConfigsSelect';
-import ModelVariantSelect from 'features/modelManager/subpanels/shared/ModelVariantSelect';
-import { MODEL_TYPE_MAP } from 'features/parameters/types/constants';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
-import { memo, useCallback, useEffect, useState } from 'react';
-import type { SubmitHandler } from 'react-hook-form';
-import { useForm } from 'react-hook-form';
-import { useTranslation } from 'react-i18next';
-import { useGetCheckpointConfigsQuery, useUpdateModelsMutation } from 'services/api/endpoints/models';
-import type { CheckpointModelConfig } from 'services/api/types';
-
-import ModelConvert from './ModelConvert';
-
-type CheckpointModelEditProps = {
-  model: CheckpointModelConfig;
-};
-
-const CheckpointModelEdit = (props: CheckpointModelEditProps) => {
-  const { model } = props;
-
-  const [updateModel, { isLoading }] = useUpdateModelsMutation();
-  const { data: availableCheckpointConfigs } = useGetCheckpointConfigsQuery();
-
-  const [useCustomConfig, setUseCustomConfig] = useState<boolean>(false);
-
-  useEffect(() => {
-    if (!availableCheckpointConfigs?.includes(model.config)) {
-      setUseCustomConfig(true);
-    }
-  }, [availableCheckpointConfigs, model.config]);
-
-  const dispatch = useAppDispatch();
-  const { t } = useTranslation();
-
-  const {
-    register,
-    handleSubmit,
-    control,
-    formState: { errors },
-    reset,
-  } = useForm<CheckpointModelConfig>({
-    defaultValues: {
-      name: model.name ? model.name : '',
-      base: model.base,
-      type: 'main',
-      path: model.path ? model.path : '',
-      description: model.description ? model.description : '',
-      format: 'checkpoint',
-      vae: model.vae ? model.vae : '',
-      config: model.config ? model.config : '',
-      variant: model.variant,
-    },
-    mode: 'onChange',
-  });
-
-  const handleChangeUseCustomConfig = useCallback(() => setUseCustomConfig((prev) => !prev), []);
-
-  const onSubmit = useCallback<SubmitHandler<CheckpointModelConfig>>(
-    (values) => {
-      const responseBody = {
-        key: model.key,
-        body: values,
-      };
-      updateModel(responseBody)
-        .unwrap()
-        .then((payload) => {
-          reset(payload as CheckpointModelConfig, { keepDefaultValues: true });
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('modelManager.modelUpdated'),
-                status: 'success',
-              })
-            )
-          );
-        })
-        .catch((_) => {
-          reset();
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('modelManager.modelUpdateFailed'),
-                status: 'error',
-              })
-            )
-          );
-        });
-    },
-    [dispatch, model.key, reset, t, updateModel]
-  );
-
-  return (
-    <Flex flexDirection="column" rowGap={4} width="100%">
-      <Flex justifyContent="space-between" alignItems="center">
-        <Flex flexDirection="column">
-          <Text fontSize="lg" fontWeight="bold">
-            {model.name}
-          </Text>
-          <Text fontSize="sm" color="base.400">
-            {MODEL_TYPE_MAP[model.base]} {t('modelManager.model')}
-          </Text>
-        </Flex>
-        {![''].includes(model.base) ? (
-          <ModelConvert model={model} />
-        ) : (
-          <Badge p={2} borderRadius={4} bg="error.400">
-            {t('modelManager.conversionNotSupported')}
-          </Badge>
-        )}
-      </Flex>
-      <Divider />
-
-      <Flex flexDirection="column" maxHeight={window.innerHeight - 270} overflowY="scroll">
-        <form onSubmit={handleSubmit(onSubmit)}>
-          <Flex flexDirection="column" overflowY="scroll" gap={4}>
-            <FormControl isInvalid={Boolean(errors.name)}>
-              <FormLabel>{t('modelManager.name')}</FormLabel>
-              <Input
-                {...register('name', {
-                  validate: (value) => value.trim().length > 3 || 'Must be at least 3 characters',
-                })}
-              />
-              {errors.name?.message && <FormErrorMessage>{errors.name?.message}</FormErrorMessage>}
-            </FormControl>
-            <FormControl>
-              <FormLabel>{t('modelManager.description')}</FormLabel>
-              <Input {...register('description')} />
-            </FormControl>
-            <BaseModelSelect<CheckpointModelConfig> control={control} name="base" />
-            <ModelVariantSelect<CheckpointModelConfig> control={control} name="variant" />
-            <FormControl isInvalid={Boolean(errors.path)}>
-              <FormLabel>{t('modelManager.modelLocation')}</FormLabel>
-              <Input
-                {...register('path', {
-                  validate: (value) => value.trim().length > 0 || 'Must provide a path',
-                })}
-              />
-              {errors.path?.message && <FormErrorMessage>{errors.path?.message}</FormErrorMessage>}
-            </FormControl>
-            <FormControl>
-              <FormLabel>{t('modelManager.vaeLocation')}</FormLabel>
-              <Input {...register('vae')} />
-            </FormControl>
-
-            <Flex flexDirection="column" gap={2}>
-              {!useCustomConfig ? (
-                <CheckpointConfigsSelect control={control} name="config" />
-              ) : (
-                <FormControl isRequired>
-                  <FormLabel>{t('modelManager.config')}</FormLabel>
-                  <Input {...register('config')} />
-                </FormControl>
-              )}
-              <FormControl>
-                <FormLabel>{t('modelManager.useCustomConfig')}</FormLabel>
-                <Checkbox isChecked={useCustomConfig} onChange={handleChangeUseCustomConfig} />
-              </FormControl>
-            </Flex>
-
-            <Button type="submit" isLoading={isLoading}>
-              {t('modelManager.updateModel')}
-            </Button>
-          </Flex>
-        </form>
-      </Flex>
-    </Flex>
-  );
-};
-
-export default memo(CheckpointModelEdit);
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/DiffusersModelEdit.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/DiffusersModelEdit.tsx
deleted file mode 100644
index b5023f0eff..0000000000
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/DiffusersModelEdit.tsx
+++ /dev/null
@@ -1,133 +0,0 @@
-import { Button, Divider, Flex, FormControl, FormErrorMessage, FormLabel, Input, Text } from '@invoke-ai/ui-library';
-import { useAppDispatch } from 'app/store/storeHooks';
-import BaseModelSelect from 'features/modelManager/subpanels/shared/BaseModelSelect';
-import ModelVariantSelect from 'features/modelManager/subpanels/shared/ModelVariantSelect';
-import { MODEL_TYPE_MAP } from 'features/parameters/types/constants';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
-import { memo, useCallback } from 'react';
-import type { SubmitHandler } from 'react-hook-form';
-import { useForm } from 'react-hook-form';
-import { useTranslation } from 'react-i18next';
-import { useUpdateModelsMutation } from 'services/api/endpoints/models';
-import type { DiffusersModelConfig } from 'services/api/types';
-
-type DiffusersModelEditProps = {
-  model: DiffusersModelConfig;
-};
-
-const DiffusersModelEdit = (props: DiffusersModelEditProps) => {
-  const { model } = props;
-
-  const [updateModel, { isLoading }] = useUpdateModelsMutation();
-
-  const dispatch = useAppDispatch();
-  const { t } = useTranslation();
-
-  const {
-    register,
-    handleSubmit,
-    control,
-    formState: { errors },
-    reset,
-  } = useForm<DiffusersModelConfig>({
-    defaultValues: {
-      name: model.name ? model.name : '',
-      base: model.base,
-      type: 'main',
-      path: model.path ? model.path : '',
-      description: model.description ? model.description : '',
-      format: 'diffusers',
-      vae: model.vae ? model.vae : '',
-      variant: model.variant,
-    },
-    mode: 'onChange',
-  });
-
-  const onSubmit = useCallback<SubmitHandler<DiffusersModelConfig>>(
-    (values) => {
-      const responseBody = {
-        key: model.key,
-        body: values,
-      };
-
-      updateModel(responseBody)
-        .unwrap()
-        .then((payload) => {
-          reset(payload as DiffusersModelConfig, { keepDefaultValues: true });
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('modelManager.modelUpdated'),
-                status: 'success',
-              })
-            )
-          );
-        })
-        .catch((_) => {
-          reset();
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('modelManager.modelUpdateFailed'),
-                status: 'error',
-              })
-            )
-          );
-        });
-    },
-    [dispatch, model.key, reset, t, updateModel]
-  );
-
-  return (
-    <Flex flexDirection="column" rowGap={4} width="100%">
-      <Flex flexDirection="column">
-        <Text fontSize="lg" fontWeight="bold">
-          {model.name}
-        </Text>
-        <Text fontSize="sm" color="base.400">
-          {MODEL_TYPE_MAP[model.base]} {t('modelManager.model')}
-        </Text>
-      </Flex>
-      <Divider />
-
-      <form onSubmit={handleSubmit(onSubmit)}>
-        <Flex flexDirection="column" overflowY="scroll" gap={4}>
-          <FormControl isInvalid={Boolean(errors.name)}>
-            <FormLabel>{t('modelManager.name')}</FormLabel>
-            <Input
-              {...register('name', {
-                validate: (value) => value.trim().length > 3 || 'Must be at least 3 characters',
-              })}
-            />
-            {errors.name?.message && <FormErrorMessage>{errors.name?.message}</FormErrorMessage>}
-          </FormControl>
-          <FormControl>
-            <FormLabel>{t('modelManager.description')}</FormLabel>
-            <Input {...register('description')} />
-          </FormControl>
-          <BaseModelSelect<DiffusersModelConfig> control={control} name="base" />
-          <ModelVariantSelect<DiffusersModelConfig> control={control} name="variant" />
-          <FormControl isInvalid={Boolean(errors.path)}>
-            <FormLabel>{t('modelManager.modelLocation')}</FormLabel>
-            <Input
-              {...register('path', {
-                validate: (value) => value.trim().length > 0 || 'Must provide a path',
-              })}
-            />
-            {errors.path?.message && <FormErrorMessage>{errors.path?.message}</FormErrorMessage>}
-          </FormControl>
-          <FormControl>
-            <FormLabel>{t('modelManager.vaeLocation')}</FormLabel>
-            <Input {...register('vae')} />
-          </FormControl>
-          <Button type="submit" isLoading={isLoading}>
-            {t('modelManager.updateModel')}
-          </Button>
-        </Flex>
-      </form>
-    </Flex>
-  );
-};
-
-export default memo(DiffusersModelEdit);
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/LoRAModelEdit.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/LoRAModelEdit.tsx
deleted file mode 100644
index 81f2c4df29..0000000000
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/LoRAModelEdit.tsx
+++ /dev/null
@@ -1,127 +0,0 @@
-import { Button, Divider, Flex, FormControl, FormErrorMessage, FormLabel, Input, Text } from '@invoke-ai/ui-library';
-import { useAppDispatch } from 'app/store/storeHooks';
-import BaseModelSelect from 'features/modelManager/subpanels/shared/BaseModelSelect';
-import { LORA_MODEL_FORMAT_MAP, MODEL_TYPE_MAP } from 'features/parameters/types/constants';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
-import { memo, useCallback } from 'react';
-import type { SubmitHandler } from 'react-hook-form';
-import { useForm } from 'react-hook-form';
-import { useTranslation } from 'react-i18next';
-import { useUpdateModelsMutation } from 'services/api/endpoints/models';
-import type { LoRAModelConfig } from 'services/api/types';
-
-type LoRAModelEditProps = {
-  model: LoRAModelConfig;
-};
-
-const LoRAModelEdit = (props: LoRAModelEditProps) => {
-  const { model } = props;
-
-  const [updateModel, { isLoading }] = useUpdateModelsMutation();
-
-  const dispatch = useAppDispatch();
-  const { t } = useTranslation();
-
-  const {
-    register,
-    handleSubmit,
-    control,
-    formState: { errors },
-    reset,
-  } = useForm<LoRAModelConfig>({
-    defaultValues: {
-      name: model.name ? model.name : '',
-      base: model.base,
-      type: 'lora',
-      path: model.path ? model.path : '',
-      description: model.description ? model.description : '',
-      format: model.format,
-    },
-    mode: 'onChange',
-  });
-
-  const onSubmit = useCallback<SubmitHandler<LoRAModelConfig>>(
-    (values) => {
-      const responseBody = {
-        key: model.key,
-        body: values,
-      };
-
-      updateModel(responseBody)
-        .unwrap()
-        .then((payload) => {
-          reset(payload as LoRAModelConfig, { keepDefaultValues: true });
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('modelManager.modelUpdated'),
-                status: 'success',
-              })
-            )
-          );
-        })
-        .catch((_) => {
-          reset();
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('modelManager.modelUpdateFailed'),
-                status: 'error',
-              })
-            )
-          );
-        });
-    },
-    [dispatch, model.key, reset, t, updateModel]
-  );
-
-  return (
-    <Flex flexDirection="column" rowGap={4} width="100%">
-      <Flex flexDirection="column">
-        <Text fontSize="lg" fontWeight="bold">
-          {model.name}
-        </Text>
-        <Text fontSize="sm" color="base.400">
-          {MODEL_TYPE_MAP[model.base]} {t('modelManager.model')} ⋅ {LORA_MODEL_FORMAT_MAP[model.format]}{' '}
-          {t('common.format')}
-        </Text>
-      </Flex>
-      <Divider />
-
-      <form onSubmit={handleSubmit(onSubmit)}>
-        <Flex flexDirection="column" overflowY="scroll" gap={4}>
-          <FormControl isInvalid={Boolean(errors.name)}>
-            <FormLabel>{t('modelManager.name')}</FormLabel>
-            <Input
-              {...register('name', {
-                validate: (value) => value.trim().length > 3 || 'Must be at least 3 characters',
-              })}
-            />
-            {errors.name?.message && <FormErrorMessage>{errors.name?.message}</FormErrorMessage>}
-          </FormControl>
-          <FormControl>
-            <FormLabel>{t('modelManager.description')}</FormLabel>
-            <Input {...register('description')} />
-          </FormControl>
-          <BaseModelSelect<LoRAModelConfig> control={control} name="base" />
-
-          <FormControl isInvalid={Boolean(errors.path)}>
-            <FormLabel>{t('modelManager.modelLocation')}</FormLabel>
-            <Input
-              {...register('path', {
-                validate: (value) => value.trim().length > 0 || 'Must provide a path',
-              })}
-            />
-            {errors.path?.message && <FormErrorMessage>{errors.path?.message}</FormErrorMessage>}
-          </FormControl>
-          <Button type="submit" isLoading={isLoading}>
-            {t('modelManager.updateModel')}
-          </Button>
-        </Flex>
-      </form>
-    </Flex>
-  );
-};
-
-export default memo(LoRAModelEdit);
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelConvert.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelConvert.tsx
deleted file mode 100644
index 9a2746abe6..0000000000
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelConvert.tsx
+++ /dev/null
@@ -1,165 +0,0 @@
-import {
-  Button,
-  ConfirmationAlertDialog,
-  Flex,
-  FormControl,
-  FormLabel,
-  Input,
-  ListItem,
-  Radio,
-  RadioGroup,
-  Text,
-  Tooltip,
-  UnorderedList,
-  useDisclosure,
-} from '@invoke-ai/ui-library';
-import { useAppDispatch } from 'app/store/storeHooks';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
-import type { ChangeEvent } from 'react';
-import { memo, useCallback, useEffect, useState } from 'react';
-import { useTranslation } from 'react-i18next';
-import { useConvertMainModelsMutation } from 'services/api/endpoints/models';
-import type { CheckpointModelConfig } from 'services/api/types';
-
-interface ModelConvertProps {
-  model: CheckpointModelConfig;
-}
-
-type SaveLocation = 'InvokeAIRoot' | 'Custom';
-
-const ModelConvert = (props: ModelConvertProps) => {
-  const { model } = props;
-  const dispatch = useAppDispatch();
-  const { t } = useTranslation();
-  const [convertModel, { isLoading }] = useConvertMainModelsMutation();
-  const { isOpen, onOpen, onClose } = useDisclosure();
-  const [saveLocation, setSaveLocation] = useState<SaveLocation>('InvokeAIRoot');
-  const [customSaveLocation, setCustomSaveLocation] = useState<string>('');
-
-  useEffect(() => {
-    setSaveLocation('InvokeAIRoot');
-  }, [model]);
-
-  const modelConvertCancelHandler = useCallback(() => {
-    setSaveLocation('InvokeAIRoot');
-  }, []);
-
-  const handleChangeSaveLocation = useCallback((v: string) => {
-    setSaveLocation(v as SaveLocation);
-  }, []);
-  const handleChangeCustomSaveLocation = useCallback((e: ChangeEvent<HTMLInputElement>) => {
-    setCustomSaveLocation(e.target.value);
-  }, []);
-
-  const modelConvertHandler = useCallback(() => {
-    const queryArg = {
-      base_model: model.base,
-      model_name: model.name,
-      convert_dest_directory: saveLocation === 'Custom' ? customSaveLocation : undefined,
-    };
-
-    if (saveLocation === 'Custom' && customSaveLocation === '') {
-      dispatch(
-        addToast(
-          makeToast({
-            title: t('modelManager.noCustomLocationProvided'),
-            status: 'error',
-          })
-        )
-      );
-      return;
-    }
-
-    dispatch(
-      addToast(
-        makeToast({
-          title: `${t('modelManager.convertingModelBegin')}: ${model.name}`,
-          status: 'info',
-        })
-      )
-    );
-
-    convertModel(queryArg)
-      .unwrap()
-      .then(() => {
-        dispatch(
-          addToast(
-            makeToast({
-              title: `${t('modelManager.modelConverted')}: ${model.name}`,
-              status: 'success',
-            })
-          )
-        );
-      })
-      .catch(() => {
-        dispatch(
-          addToast(
-            makeToast({
-              title: `${t('modelManager.modelConversionFailed')}: ${model.name}`,
-              status: 'error',
-            })
-          )
-        );
-      });
-  }, [convertModel, customSaveLocation, dispatch, model.base, model.name, saveLocation, t]);
-
-  return (
-    <>
-      <Button
-        onClick={onOpen}
-        size="sm"
-        aria-label={t('modelManager.convertToDiffusers')}
-        className=" modal-close-btn"
-        isLoading={isLoading}
-      >
-        🧨 {t('modelManager.convertToDiffusers')}
-      </Button>
-      <ConfirmationAlertDialog
-        title={`${t('modelManager.convert')} ${model.name}`}
-        acceptCallback={modelConvertHandler}
-        cancelCallback={modelConvertCancelHandler}
-        acceptButtonText={`${t('modelManager.convert')}`}
-        isOpen={isOpen}
-        onClose={onClose}
-      >
-        <Flex flexDirection="column" rowGap={4}>
-          <Text>{t('modelManager.convertToDiffusersHelpText1')}</Text>
-          <UnorderedList>
-            <ListItem>{t('modelManager.convertToDiffusersHelpText2')}</ListItem>
-            <ListItem>{t('modelManager.convertToDiffusersHelpText3')}</ListItem>
-            <ListItem>{t('modelManager.convertToDiffusersHelpText4')}</ListItem>
-            <ListItem>{t('modelManager.convertToDiffusersHelpText5')}</ListItem>
-          </UnorderedList>
-          <Text>{t('modelManager.convertToDiffusersHelpText6')}</Text>
-        </Flex>
-
-        <Flex flexDir="column" gap={2}>
-          <Flex marginTop={4} flexDir="column" gap={2}>
-            <Text fontWeight="semibold">{t('modelManager.convertToDiffusersSaveLocation')}</Text>
-            <RadioGroup value={saveLocation} onChange={handleChangeSaveLocation}>
-              <Flex gap={4}>
-                <Radio value="InvokeAIRoot">
-                  <Tooltip label="Save converted model in the InvokeAI root folder">
-                    {t('modelManager.invokeRoot')}
-                  </Tooltip>
-                </Radio>
-                <Radio value="Custom">
-                  <Tooltip label="Save converted model in a custom folder">{t('modelManager.custom')}</Tooltip>
-                </Radio>
-              </Flex>
-            </RadioGroup>
-          </Flex>
-          {saveLocation === 'Custom' && (
-            <FormControl>
-              <FormLabel>{t('modelManager.customSaveLocation')}</FormLabel>
-              <Input width="full" value={customSaveLocation} onChange={handleChangeCustomSaveLocation} />
-            </FormControl>
-          )}
-        </Flex>
-      </ConfirmationAlertDialog>
-    </>
-  );
-};
-
-export default memo(ModelConvert);
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelList.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelList.tsx
deleted file mode 100644
index b129b7310d..0000000000
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelList.tsx
+++ /dev/null
@@ -1,205 +0,0 @@
-import { Button, ButtonGroup, Flex, FormControl, FormLabel, Input, Spinner, Text } from '@invoke-ai/ui-library';
-import type { EntityState } from '@reduxjs/toolkit';
-import { forEach } from 'lodash-es';
-import type { ChangeEvent, PropsWithChildren } from 'react';
-import { memo, useCallback, useState } from 'react';
-import { useTranslation } from 'react-i18next';
-import { ALL_BASE_MODELS } from 'services/api/constants';
-// import type { LoRAConfig, MainModelConfig } from 'services/api/endpoints/models';
-import { useGetLoRAModelsQuery, useGetMainModelsQuery } from 'services/api/endpoints/models';
-import type { LoRAConfig, MainModelConfig } from 'services/api/types';
-
-import ModelListItem from './ModelListItem';
-
-type ModelListProps = {
-  selectedModelId: string | undefined;
-  setSelectedModelId: (name: string | undefined) => void;
-};
-
-type ModelFormat = 'all' | 'checkpoint' | 'diffusers';
-
-type ModelType = 'main' | 'lora';
-
-type CombinedModelFormat = ModelFormat | 'lora';
-
-const ModelList = (props: ModelListProps) => {
-  const { selectedModelId, setSelectedModelId } = props;
-  const { t } = useTranslation();
-  const [nameFilter, setNameFilter] = useState<string>('');
-  const [modelFormatFilter, setModelFormatFilter] = useState<CombinedModelFormat>('all');
-
-  const { filteredDiffusersModels, isLoadingDiffusersModels } = useGetMainModelsQuery(ALL_BASE_MODELS, {
-    selectFromResult: ({ data, isLoading }) => ({
-      filteredDiffusersModels: modelsFilter(data, 'main', 'diffusers', nameFilter),
-      isLoadingDiffusersModels: isLoading,
-    }),
-  });
-
-  const { filteredCheckpointModels, isLoadingCheckpointModels } = useGetMainModelsQuery(ALL_BASE_MODELS, {
-    selectFromResult: ({ data, isLoading }) => ({
-      filteredCheckpointModels: modelsFilter(data, 'main', 'checkpoint', nameFilter),
-      isLoadingCheckpointModels: isLoading,
-    }),
-  });
-
-  const { filteredLoraModels, isLoadingLoraModels } = useGetLoRAModelsQuery(undefined, {
-    selectFromResult: ({ data, isLoading }) => ({
-      filteredLoraModels: modelsFilter(data, 'lora', undefined, nameFilter),
-      isLoadingLoraModels: isLoading,
-    }),
-  });
-
-  const handleSearchFilter = useCallback((e: ChangeEvent<HTMLInputElement>) => {
-    setNameFilter(e.target.value);
-  }, []);
-
-  return (
-    <Flex flexDirection="column" rowGap={4} width="50%" minWidth="50%">
-      <Flex flexDirection="column" gap={4} paddingInlineEnd={4}>
-        <ButtonGroup>
-          <Button onClick={setModelFormatFilter.bind(null, 'all')} isChecked={modelFormatFilter === 'all'} size="sm">
-            {t('modelManager.allModels')}
-          </Button>
-          <Button
-            size="sm"
-            onClick={setModelFormatFilter.bind(null, 'diffusers')}
-            isChecked={modelFormatFilter === 'diffusers'}
-          >
-            {t('modelManager.diffusersModels')}
-          </Button>
-          <Button
-            size="sm"
-            onClick={setModelFormatFilter.bind(null, 'checkpoint')}
-            isChecked={modelFormatFilter === 'checkpoint'}
-          >
-            {t('modelManager.checkpointModels')}
-          </Button>
-          <Button size="sm" onClick={setModelFormatFilter.bind(null, 'lora')} isChecked={modelFormatFilter === 'lora'}>
-            {t('modelManager.loraModels')}
-          </Button>
-        </ButtonGroup>
-
-        <FormControl>
-          <FormLabel>{t('modelManager.search')}</FormLabel>
-          <Input onChange={handleSearchFilter} />
-        </FormControl>
-
-        <Flex flexDirection="column" gap={4} maxHeight={window.innerHeight - 280} overflow="scroll">
-          {/* Diffusers List */}
-          {isLoadingDiffusersModels && <FetchingModelsLoader loadingMessage="Loading Diffusers..." />}
-          {['all', 'diffusers'].includes(modelFormatFilter) &&
-            !isLoadingDiffusersModels &&
-            filteredDiffusersModels.length > 0 && (
-              <ModelListWrapper
-                title="Diffusers"
-                modelList={filteredDiffusersModels}
-                selected={{ selectedModelId, setSelectedModelId }}
-                key="diffusers"
-              />
-            )}
-          {/* Checkpoints List */}
-          {isLoadingCheckpointModels && <FetchingModelsLoader loadingMessage="Loading Checkpoints..." />}
-          {['all', 'checkpoint'].includes(modelFormatFilter) &&
-            !isLoadingCheckpointModels &&
-            filteredCheckpointModels.length > 0 && (
-              <ModelListWrapper
-                title="Checkpoints"
-                modelList={filteredCheckpointModels}
-                selected={{ selectedModelId, setSelectedModelId }}
-                key="checkpoints"
-              />
-            )}
-
-          {/* LoRAs List */}
-          {isLoadingLoraModels && <FetchingModelsLoader loadingMessage="Loading LoRAs..." />}
-          {['all', 'lora'].includes(modelFormatFilter) && !isLoadingLoraModels && filteredLoraModels.length > 0 && (
-            <ModelListWrapper
-              title="LoRAs"
-              modelList={filteredLoraModels}
-              selected={{ selectedModelId, setSelectedModelId }}
-              key="loras"
-            />
-          )}
-        </Flex>
-      </Flex>
-    </Flex>
-  );
-};
-
-export default memo(ModelList);
-
-const modelsFilter = <T extends MainModelConfig | LoRAConfig>(
-  data: EntityState<T, string> | undefined,
-  model_type: ModelType,
-  model_format: ModelFormat | undefined,
-  nameFilter: string
-) => {
-  const filteredModels: T[] = [];
-  forEach(data?.entities, (model) => {
-    if (!model) {
-      return;
-    }
-
-    const matchesFilter = model.name.toLowerCase().includes(nameFilter.toLowerCase());
-
-    const matchesFormat = model_format === undefined || model.format === model_format;
-    const matchesType = model.type === model_type;
-
-    if (matchesFilter && matchesFormat && matchesType) {
-      filteredModels.push(model);
-    }
-  });
-  return filteredModels;
-};
-
-const StyledModelContainer = memo((props: PropsWithChildren) => {
-  return (
-    <Flex flexDirection="column" gap={4} borderRadius={4} p={4} bg="base.800">
-      {props.children}
-    </Flex>
-  );
-});
-
-StyledModelContainer.displayName = 'StyledModelContainer';
-
-type ModelListWrapperProps = {
-  title: string;
-  modelList: MainModelConfig[] | LoRAConfig[];
-  selected: ModelListProps;
-};
-
-const ModelListWrapper = memo((props: ModelListWrapperProps) => {
-  const { title, modelList, selected } = props;
-  return (
-    <StyledModelContainer>
-      <Flex gap={2} flexDir="column">
-        <Text variant="subtext" fontSize="sm">
-          {title}
-        </Text>
-        {modelList.map((model) => (
-          <ModelListItem
-            key={model.key}
-            model={model}
-            isSelected={selected.selectedModelId === model.key}
-            setSelectedModelId={selected.setSelectedModelId}
-          />
-        ))}
-      </Flex>
-    </StyledModelContainer>
-  );
-});
-
-ModelListWrapper.displayName = 'ModelListWrapper';
-
-const FetchingModelsLoader = memo(({ loadingMessage }: { loadingMessage?: string }) => {
-  return (
-    <StyledModelContainer>
-      <Flex justifyContent="center" alignItems="center" flexDirection="column" p={4} gap={8}>
-        <Spinner />
-        <Text variant="subtext">{loadingMessage ? loadingMessage : 'Fetching...'}</Text>
-      </Flex>
-    </StyledModelContainer>
-  );
-});
-
-FetchingModelsLoader.displayName = 'FetchingModelsLoader';
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelListItem.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelListItem.tsx
deleted file mode 100644
index 08b9b61aea..0000000000
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerPanel/ModelListItem.tsx
+++ /dev/null
@@ -1,111 +0,0 @@
-import {
-  Badge,
-  Button,
-  ConfirmationAlertDialog,
-  Flex,
-  IconButton,
-  Text,
-  Tooltip,
-  useDisclosure,
-} from '@invoke-ai/ui-library';
-import { useAppDispatch } from 'app/store/storeHooks';
-import { MODEL_TYPE_SHORT_MAP } from 'features/parameters/types/constants';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
-import { memo, useCallback } from 'react';
-import { useTranslation } from 'react-i18next';
-import { PiTrashSimpleBold } from 'react-icons/pi';
-import { useDeleteModelsMutation } from 'services/api/endpoints/models';
-import type { LoRAConfig, MainModelConfig } from 'services/api/types';
-
-type ModelListItemProps = {
-  model: MainModelConfig | LoRAConfig;
-  isSelected: boolean;
-  setSelectedModelId: (v: string | undefined) => void;
-};
-
-const ModelListItem = (props: ModelListItemProps) => {
-  const { t } = useTranslation();
-  const dispatch = useAppDispatch();
-  const [deleteModel] = useDeleteModelsMutation();
-  const { isOpen, onOpen, onClose } = useDisclosure();
-
-  const { model, isSelected, setSelectedModelId } = props;
-
-  const handleSelectModel = useCallback(() => {
-    setSelectedModelId(model.key);
-  }, [model.key, setSelectedModelId]);
-
-  const handleModelDelete = useCallback(() => {
-    deleteModel({ key: model.key })
-      .unwrap()
-      .then((_) => {
-        dispatch(
-          addToast(
-            makeToast({
-              title: `${t('modelManager.modelDeleted')}: ${model.name}`,
-              status: 'success',
-            })
-          )
-        );
-      })
-      .catch((error) => {
-        if (error) {
-          dispatch(
-            addToast(
-              makeToast({
-                title: `${t('modelManager.modelDeleteFailed')}: ${model.name}`,
-                status: 'error',
-              })
-            )
-          );
-        }
-      });
-    setSelectedModelId(undefined);
-  }, [deleteModel, model, setSelectedModelId, dispatch, t]);
-
-  return (
-    <Flex gap={2} alignItems="center" w="full">
-      <Flex
-        as={Button}
-        isChecked={isSelected}
-        variant={isSelected ? 'solid' : 'ghost'}
-        justifyContent="start"
-        p={2}
-        borderRadius="base"
-        w="full"
-        alignItems="center"
-        onClick={handleSelectModel}
-      >
-        <Flex gap={4} alignItems="center">
-          <Badge minWidth={14} p={0.5} fontSize="sm" variant="solid">
-            {MODEL_TYPE_SHORT_MAP[model.base as keyof typeof MODEL_TYPE_SHORT_MAP]}
-          </Badge>
-          <Tooltip label={model.description} placement="bottom">
-            <Text>{model.name}</Text>
-          </Tooltip>
-        </Flex>
-      </Flex>
-      <IconButton
-        onClick={onOpen}
-        icon={<PiTrashSimpleBold />}
-        aria-label={t('modelManager.deleteConfig')}
-        colorScheme="error"
-      />
-      <ConfirmationAlertDialog
-        isOpen={isOpen}
-        onClose={onClose}
-        title={t('modelManager.deleteModel')}
-        acceptCallback={handleModelDelete}
-        acceptButtonText={t('modelManager.delete')}
-      >
-        <Flex rowGap={4} flexDirection="column">
-          <Text fontWeight="bold">{t('modelManager.deleteMsg1')}</Text>
-          <Text>{t('modelManager.deleteMsg2')}</Text>
-        </Flex>
-      </ConfirmationAlertDialog>
-    </Flex>
-  );
-};
-
-export default memo(ModelListItem);
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerSettingsPanel.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerSettingsPanel.tsx
deleted file mode 100644
index 50118d9b97..0000000000
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerSettingsPanel.tsx
+++ /dev/null
@@ -1,14 +0,0 @@
-import { Flex } from '@invoke-ai/ui-library';
-import { memo } from 'react';
-
-import SyncModels from './ModelManagerSettingsPanel/SyncModels';
-
-const ModelManagerSettingsPanel = () => {
-  return (
-    <Flex>
-      <SyncModels />
-    </Flex>
-  );
-};
-
-export default memo(ModelManagerSettingsPanel);
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerSettingsPanel/SyncModels.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerSettingsPanel/SyncModels.tsx
deleted file mode 100644
index a4af3e1517..0000000000
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/ModelManagerSettingsPanel/SyncModels.tsx
+++ /dev/null
@@ -1,22 +0,0 @@
-import { Flex, Text } from '@invoke-ai/ui-library';
-import { SyncModelsButton } from 'features/modelManager/components/SyncModels/SyncModelsButton';
-import { memo } from 'react';
-import { useTranslation } from 'react-i18next';
-
-const SyncModels = () => {
-  const { t } = useTranslation();
-
-  return (
-    <Flex w="full" p={4} borderRadius={4} gap={4} justifyContent="space-between" alignItems="center" bg="base.800">
-      <Flex flexDirection="column" gap={2}>
-        <Text fontWeight="semibold">{t('modelManager.syncModels')}</Text>
-        <Text fontSize="sm" variant="subtext">
-          {t('modelManager.syncModelsDesc')}
-        </Text>
-      </Flex>
-      <SyncModelsButton />
-    </Flex>
-  );
-};
-
-export default memo(SyncModels);
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/shared/BaseModelSelect.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/shared/BaseModelSelect.tsx
deleted file mode 100644
index fce16f3f13..0000000000
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/shared/BaseModelSelect.tsx
+++ /dev/null
@@ -1,36 +0,0 @@
-import type { ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
-import { Combobox, FormControl, FormLabel } from '@invoke-ai/ui-library';
-import { typedMemo } from 'common/util/typedMemo';
-import { MODEL_TYPE_MAP } from 'features/parameters/types/constants';
-import { useCallback, useMemo } from 'react';
-import type { UseControllerProps } from 'react-hook-form';
-import { useController } from 'react-hook-form';
-import { useTranslation } from 'react-i18next';
-import type { AnyModelConfig } from 'services/api/types';
-
-const options: ComboboxOption[] = [
-  { value: 'sd-1', label: MODEL_TYPE_MAP['sd-1'] },
-  { value: 'sd-2', label: MODEL_TYPE_MAP['sd-2'] },
-  { value: 'sdxl', label: MODEL_TYPE_MAP['sdxl'] },
-  { value: 'sdxl-refiner', label: MODEL_TYPE_MAP['sdxl-refiner'] },
-];
-
-const BaseModelSelect = <T extends AnyModelConfig>(props: UseControllerProps<T>) => {
-  const { t } = useTranslation();
-  const { field } = useController(props);
-  const value = useMemo(() => options.find((o) => o.value === field.value), [field.value]);
-  const onChange = useCallback<ComboboxOnChange>(
-    (v) => {
-      field.onChange(v?.value);
-    },
-    [field]
-  );
-  return (
-    <FormControl>
-      <FormLabel>{t('modelManager.baseModel')}</FormLabel>
-      <Combobox value={value} options={options} onChange={onChange} />
-    </FormControl>
-  );
-};
-
-export default typedMemo(BaseModelSelect);
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/shared/CheckpointConfigsSelect.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/shared/CheckpointConfigsSelect.tsx
deleted file mode 100644
index 569f1abbba..0000000000
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/shared/CheckpointConfigsSelect.tsx
+++ /dev/null
@@ -1,32 +0,0 @@
-import type { ChakraProps, ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
-import { Combobox, FormControl, FormLabel } from '@invoke-ai/ui-library';
-import { memo, useCallback, useMemo } from 'react';
-import { useController, type UseControllerProps } from 'react-hook-form';
-import { useTranslation } from 'react-i18next';
-import { useGetCheckpointConfigsQuery } from 'services/api/endpoints/models';
-import type { CheckpointModelConfig } from 'services/api/types';
-
-const sx: ChakraProps['sx'] = { w: 'full' };
-
-const CheckpointConfigsSelect = (props: UseControllerProps<CheckpointModelConfig>) => {
-  const { data } = useGetCheckpointConfigsQuery();
-  const { t } = useTranslation();
-  const options = useMemo<ComboboxOption[]>(() => (data ? data.map((i) => ({ label: i, value: i })) : []), [data]);
-  const { field } = useController(props);
-  const value = useMemo(() => options.find((o) => o.value === field.value), [field.value, options]);
-  const onChange = useCallback<ComboboxOnChange>(
-    (v) => {
-      field.onChange(v?.value);
-    },
-    [field]
-  );
-
-  return (
-    <FormControl>
-      <FormLabel>{t('modelManager.configFile')}</FormLabel>
-      <Combobox placeholder="Select A Config File" value={value} options={options} onChange={onChange} sx={sx} />
-    </FormControl>
-  );
-};
-
-export default memo(CheckpointConfigsSelect);
diff --git a/invokeai/frontend/web/src/features/modelManager/subpanels/shared/ModelVariantSelect.tsx b/invokeai/frontend/web/src/features/modelManager/subpanels/shared/ModelVariantSelect.tsx
deleted file mode 100644
index 27ded93843..0000000000
--- a/invokeai/frontend/web/src/features/modelManager/subpanels/shared/ModelVariantSelect.tsx
+++ /dev/null
@@ -1,34 +0,0 @@
-import type { ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
-import { Combobox, FormControl, FormLabel } from '@invoke-ai/ui-library';
-import { typedMemo } from 'common/util/typedMemo';
-import { useCallback, useMemo } from 'react';
-import type { UseControllerProps } from 'react-hook-form';
-import { useController } from 'react-hook-form';
-import { useTranslation } from 'react-i18next';
-import type { CheckpointModelConfig, DiffusersModelConfig } from 'services/api/types';
-
-const options: ComboboxOption[] = [
-  { value: 'normal', label: 'Normal' },
-  { value: 'inpaint', label: 'Inpaint' },
-  { value: 'depth', label: 'Depth' },
-];
-
-const ModelVariantSelect = <T extends CheckpointModelConfig | DiffusersModelConfig>(props: UseControllerProps<T>) => {
-  const { t } = useTranslation();
-  const { field } = useController(props);
-  const value = useMemo(() => options.find((o) => o.value === field.value), [field.value]);
-  const onChange = useCallback<ComboboxOnChange>(
-    (v) => {
-      field.onChange(v?.value);
-    },
-    [field]
-  );
-  return (
-    <FormControl>
-      <FormLabel>{t('modelManager.variant')}</FormLabel>
-      <Combobox value={value} options={options} onChange={onChange} />
-    </FormControl>
-  );
-};
-
-export default typedMemo(ModelVariantSelect);
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/MainModelFieldInputComponent.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/MainModelFieldInputComponent.tsx
index 1cb0658b81..c2b3d3d69a 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/MainModelFieldInputComponent.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/MainModelFieldInputComponent.tsx
@@ -1,7 +1,7 @@
 import { Combobox, Flex, FormControl } from '@invoke-ai/ui-library';
 import { useAppDispatch } from 'app/store/storeHooks';
 import { useGroupedModelCombobox } from 'common/hooks/useGroupedModelCombobox';
-import { SyncModelsIconButton } from 'features/modelManager/components/SyncModels/SyncModelsIconButton';
+import { SyncModelsIconButton } from 'features/modelManagerV2/components/SyncModels/SyncModelsIconButton';
 import { fieldMainModelValueChanged } from 'features/nodes/store/nodesSlice';
 import type { MainModelFieldInputInstance, MainModelFieldInputTemplate } from 'features/nodes/types/field';
 import { memo, useCallback } from 'react';
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/RefinerModelFieldInputComponent.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/RefinerModelFieldInputComponent.tsx
index be2b4a4d4f..0499eb262e 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/RefinerModelFieldInputComponent.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/RefinerModelFieldInputComponent.tsx
@@ -1,7 +1,7 @@
 import { Combobox, Flex, FormControl } from '@invoke-ai/ui-library';
 import { useAppDispatch } from 'app/store/storeHooks';
 import { useGroupedModelCombobox } from 'common/hooks/useGroupedModelCombobox';
-import { SyncModelsIconButton } from 'features/modelManager/components/SyncModels/SyncModelsIconButton';
+import { SyncModelsIconButton } from 'features/modelManagerV2/components/SyncModels/SyncModelsIconButton';
 import { fieldRefinerModelValueChanged } from 'features/nodes/store/nodesSlice';
 import type {
   SDXLRefinerModelFieldInputInstance,
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/SDXLMainModelFieldInputComponent.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/SDXLMainModelFieldInputComponent.tsx
index d0d7754606..0a48b0c917 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/SDXLMainModelFieldInputComponent.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/SDXLMainModelFieldInputComponent.tsx
@@ -1,7 +1,7 @@
 import { Combobox, Flex, FormControl } from '@invoke-ai/ui-library';
 import { useAppDispatch } from 'app/store/storeHooks';
 import { useGroupedModelCombobox } from 'common/hooks/useGroupedModelCombobox';
-import { SyncModelsIconButton } from 'features/modelManager/components/SyncModels/SyncModelsIconButton';
+import { SyncModelsIconButton } from 'features/modelManagerV2/components/SyncModels/SyncModelsIconButton';
 import { fieldMainModelValueChanged } from 'features/nodes/store/nodesSlice';
 import type { SDXLMainModelFieldInputInstance, SDXLMainModelFieldInputTemplate } from 'features/nodes/types/field';
 import { memo, useCallback } from 'react';
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/VAEModelFieldInputComponent.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/VAEModelFieldInputComponent.tsx
index 272f7f5b35..23ead6c543 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/VAEModelFieldInputComponent.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/VAEModelFieldInputComponent.tsx
@@ -1,7 +1,7 @@
 import { Combobox, Flex, FormControl } from '@invoke-ai/ui-library';
 import { useAppDispatch } from 'app/store/storeHooks';
 import { useGroupedModelCombobox } from 'common/hooks/useGroupedModelCombobox';
-import { SyncModelsIconButton } from 'features/modelManager/components/SyncModels/SyncModelsIconButton';
+import { SyncModelsIconButton } from 'features/modelManagerV2/components/SyncModels/SyncModelsIconButton';
 import { fieldVaeModelValueChanged } from 'features/nodes/store/nodesSlice';
 import type { VAEModelFieldInputInstance, VAEModelFieldInputTemplate } from 'features/nodes/types/field';
 import { pick } from 'lodash-es';
diff --git a/invokeai/frontend/web/src/features/settingsAccordions/components/GenerationSettingsAccordion/GenerationSettingsAccordion.tsx b/invokeai/frontend/web/src/features/settingsAccordions/components/GenerationSettingsAccordion/GenerationSettingsAccordion.tsx
index d57e48f11e..0633193883 100644
--- a/invokeai/frontend/web/src/features/settingsAccordions/components/GenerationSettingsAccordion/GenerationSettingsAccordion.tsx
+++ b/invokeai/frontend/web/src/features/settingsAccordions/components/GenerationSettingsAccordion/GenerationSettingsAccordion.tsx
@@ -16,7 +16,7 @@ import { EMPTY_ARRAY } from 'app/store/util';
 import { LoRAList } from 'features/lora/components/LoRAList';
 import LoRASelect from 'features/lora/components/LoRASelect';
 import { selectLoraSlice } from 'features/lora/store/loraSlice';
-import { SyncModelsIconButton } from 'features/modelManager/components/SyncModels/SyncModelsIconButton';
+import { SyncModelsIconButton } from 'features/modelManagerV2/components/SyncModels/SyncModelsIconButton';
 import ParamCFGScale from 'features/parameters/components/Core/ParamCFGScale';
 import ParamScheduler from 'features/parameters/components/Core/ParamScheduler';
 import ParamSteps from 'features/parameters/components/Core/ParamSteps';
diff --git a/invokeai/frontend/web/src/services/api/endpoints/models.ts b/invokeai/frontend/web/src/services/api/endpoints/models.ts
index 0f68353148..51b78a2277 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/models.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/models.ts
@@ -10,7 +10,6 @@ import type {
   IPAdapterModelConfig,
   LoRAModelConfig,
   MainModelConfig,
-  MergeModelConfig,
   T2IAdapterModelConfig,
   TextualInversionModelConfig,
   VAEModelConfig,
@@ -38,22 +37,9 @@ type DeleteMainModelArg = {
 
 type DeleteMainModelResponse = void;
 
-type ConvertMainModelArg = {
-  base_model: BaseModelType;
-  model_name: string;
-  convert_dest_directory?: string;
-};
-
 type ConvertMainModelResponse =
   paths['/api/v2/models/convert/{key}']['put']['responses']['200']['content']['application/json'];
 
-type MergeMainModelArg = {
-  base_model: BaseModelType;
-  body: MergeModelConfig;
-};
-
-type MergeMainModelResponse = paths['/api/v2/models/merge']['put']['responses']['200']['content']['application/json'];
-
 type ImportMainModelArg = {
   source: NonNullable<operations['heuristic_install_model']['parameters']['query']['source']>;
   access_token?: operations['heuristic_install_model']['parameters']['query']['access_token'];
@@ -72,20 +58,11 @@ type DeleteImportModelsResponse =
 type PruneModelImportsResponse =
   paths['/api/v2/models/import']['patch']['responses']['200']['content']['application/json'];
 
-type ImportAdvancedModelArg = {
-  source: NonNullable<operations['import_model']['requestBody']['content']['application/json']['source']>;
-  config: NonNullable<operations['import_model']['requestBody']['content']['application/json']['config']>;
-};
-
-type ImportAdvancedModelResponse = paths['/api/v2/models/import']['post']['responses']['201']['content']['application/json'];
 
 export type ScanFolderResponse =
   paths['/api/v2/models/scan_folder']['get']['responses']['200']['content']['application/json'];
 type ScanFolderArg = operations['scan_for_models']['parameters']['query'];
 
-type CheckpointConfigsResponse =
-  paths['/api/v2/models/ckpt_confs']['get']['responses']['200']['content']['application/json'];
-
 export const mainModelsAdapter = createEntityAdapter<MainModelConfig, string>({
   selectId: (entity) => entity.key,
   sortComparer: (a, b) => a.name.localeCompare(b.name),
@@ -199,16 +176,6 @@ export const modelsApi = api.injectEndpoints({
       },
       invalidatesTags: ['Model', 'ModelImports'],
     }),
-    importAdvancedModel: build.mutation<ImportAdvancedModelResponse, ImportAdvancedModelArg>({
-      query: ({ source, config}) => {
-        return {
-          url: buildModelsUrl('install'),
-          method: 'POST',
-          body: { source, config },
-        };
-      },
-      invalidatesTags: ['Model', 'ModelImports'],
-    }),
     deleteModels: build.mutation<DeleteMainModelResponse, DeleteMainModelArg>({
       query: ({ key }) => {
         return {
@@ -218,25 +185,14 @@ export const modelsApi = api.injectEndpoints({
       },
       invalidatesTags: ['Model'],
     }),
-    convertMainModels: build.mutation<ConvertMainModelResponse, ConvertMainModelArg>({
-      query: ({ base_model, model_name, convert_dest_directory }) => {
+    convertMainModels: build.mutation<ConvertMainModelResponse, string>({
+      query: (key) => {
         return {
-          url: buildModelsUrl(`convert/${base_model}/main/${model_name}`),
+          url: buildModelsUrl(`convert/${key}`),
           method: 'PUT',
-          params: { convert_dest_directory },
         };
       },
-      invalidatesTags: ['Model'],
-    }),
-    mergeMainModels: build.mutation<MergeMainModelResponse, MergeMainModelArg>({
-      query: ({ base_model, body }) => {
-        return {
-          url: buildModelsUrl(`merge/${base_model}`),
-          method: 'PUT',
-          body: body,
-        };
-      },
-      invalidatesTags: ['Model'],
+      invalidatesTags: ['ModelConfig'],
     }),
     getModelConfig: build.query<GetModelConfigResponse, string>({
       query: (key) => buildModelsUrl(`i/${key}`),
@@ -323,13 +279,6 @@ export const modelsApi = api.injectEndpoints({
       },
       invalidatesTags: ['ModelImports'],
     }),
-    getCheckpointConfigs: build.query<CheckpointConfigsResponse, void>({
-      query: () => {
-        return {
-          url: buildModelsUrl(`ckpt_confs`),
-        };
-      },
-    }),
   }),
 });
 
@@ -345,13 +294,10 @@ export const {
   useDeleteModelsMutation,
   useUpdateModelsMutation,
   useImportMainModelsMutation,
-  useImportAdvancedModelMutation,
   useConvertMainModelsMutation,
-  useMergeMainModelsMutation,
   useSyncModelsMutation,
   useScanModelsQuery,
   useLazyScanModelsQuery,
-  useGetCheckpointConfigsQuery,
   useGetModelImportsQuery,
   useGetModelMetadataQuery,
   useDeleteModelImportMutation,

From 65b0d3d436160a86e2f662a511ca11e1e0829ebd Mon Sep 17 00:00:00 2001
From: maryhipp <maryhipp@gmail.com>
Date: Fri, 23 Feb 2024 16:02:21 -0500
Subject: [PATCH 282/411] fix convert endpoint logic

---
 invokeai/app/api/routers/model_manager.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/invokeai/app/api/routers/model_manager.py b/invokeai/app/api/routers/model_manager.py
index 1b0fafc534..a93846e7cd 100644
--- a/invokeai/app/api/routers/model_manager.py
+++ b/invokeai/app/api/routers/model_manager.py
@@ -667,6 +667,7 @@ async def convert_model(
     Note that during the conversion process the key and model hash will change.
     The return value is the model configuration for the converted model.
     """
+    model_manager = ApiDependencies.invoker.services.model_manager
     logger = ApiDependencies.invoker.services.logger
     loader = ApiDependencies.invoker.services.model_manager.load
     store = ApiDependencies.invoker.services.model_manager.store
@@ -683,7 +684,7 @@ async def convert_model(
         raise HTTPException(400, f"The model with key {key} is not a main checkpoint model.")
 
     # loading the model will convert it into a cached diffusers file
-    loader.load_model_by_config(model_config, submodel_type=SubModelType.Scheduler)
+    model_manager.load_model_by_config(model_config, submodel_type=SubModelType.Scheduler)
 
     # Get the path of the converted model from the loader
     cache_path = loader.convert_cache.cache_path(key)

From 97181d159fa873baa56e4608eedba3407beff7b6 Mon Sep 17 00:00:00 2001
From: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Date: Fri, 23 Feb 2024 16:07:07 -0500
Subject: [PATCH 283/411] updated translations

---
 invokeai/frontend/web/public/locales/en.json | 1 +
 1 file changed, 1 insertion(+)

diff --git a/invokeai/frontend/web/public/locales/en.json b/invokeai/frontend/web/public/locales/en.json
index dfb0103dff..26d95e4c07 100644
--- a/invokeai/frontend/web/public/locales/en.json
+++ b/invokeai/frontend/web/public/locales/en.json
@@ -806,6 +806,7 @@
         "repoIDValidationMsg": "Online repository of your model",
         "safetensorModels": "SafeTensors",
         "sameFolder": "Same folder",
+        "scanFolder": "Scan folder",
         "scanAgain": "Scan Again",
         "scanForModels": "Scan For Models",
         "search": "Search",

From 740dbc0c32ec882717a8533e7228207d72b021da Mon Sep 17 00:00:00 2001
From: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Date: Fri, 23 Feb 2024 16:12:49 -0500
Subject: [PATCH 284/411] lint fix

---
 .../listeners/socketio/socketModelInstall.ts  |  6 +-
 .../ImageMetadataViewer/ImageMetadataItem.tsx |  2 +-
 .../modelManagerV2/hooks/useIsImported.ts     | 94 ++++++++++---------
 .../store/modelManagerV2Slice.ts              | 74 +++++++--------
 .../AddModelPanel/BaseModelSelect.tsx         |  6 +-
 .../ImportQueue/ImportQueueBadge.tsx          |  2 +-
 .../ImportQueue/ImportQueueItem.tsx           |  5 +-
 .../ScanModels/ScanModelResultItem.tsx        | 24 ++---
 .../AddModelPanel/ScanModels/ScanModels.tsx   |  1 -
 .../ScanModels/ScanModelsForm.tsx             |  6 +-
 .../ScanModels/ScanModelsResults.tsx          | 12 +--
 .../subpanels/AddModelPanel/SimpleImport.tsx  |  4 +-
 .../modelManagerV2/subpanels/ImportModels.tsx |  3 +-
 .../ModelManagerPanel/ModelListNavigation.tsx |  4 +-
 .../subpanels/ModelPanel/ModelConvert.tsx     |  2 +-
 .../web/src/services/api/endpoints/models.ts  | 31 +++---
 .../frontend/web/src/services/api/types.ts    |  4 +-
 .../services/events/util/setEventListeners.ts | 32 +++----
 18 files changed, 157 insertions(+), 155 deletions(-)

diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts
index e5a7ae4d46..b658354c42 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts
@@ -1,3 +1,4 @@
+import { api } from 'services/api';
 import { modelsApi } from 'services/api/endpoints/models';
 import {
   socketModelInstallCompleted,
@@ -6,7 +7,6 @@ import {
 } from 'services/events/actions';
 
 import { startAppListening } from '../..';
-import { api } from '../../../../../../services/api';
 
 export const addModelInstallEventListener = () => {
   startAppListening({
@@ -41,7 +41,7 @@ export const addModelInstallEventListener = () => {
           return draft;
         })
       );
-      dispatch(api.util.invalidateTags([{ type: "ModelConfig" }]))
+      dispatch(api.util.invalidateTags([{ type: 'ModelConfig' }]));
     },
   });
 
@@ -55,7 +55,7 @@ export const addModelInstallEventListener = () => {
           const modelImport = draft.find((m) => m.id === id);
           if (modelImport) {
             modelImport.status = 'error';
-            modelImport.error_reason = error_type
+            modelImport.error_reason = error_type;
           }
           return draft;
         })
diff --git a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataItem.tsx b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataItem.tsx
index 7d17a2ad3d..ce25b54e59 100644
--- a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataItem.tsx
+++ b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataItem.tsx
@@ -91,7 +91,7 @@ VAEMetadataItem.displayName = 'VAEMetadataItem';
 type ModelMetadataItemProps = {
   label: string;
   modelKey?: string;
-  
+
   extra?: string;
   onClick: () => void;
 };
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/hooks/useIsImported.ts b/invokeai/frontend/web/src/features/modelManagerV2/hooks/useIsImported.ts
index 0c5c4232ea..763317a639 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/hooks/useIsImported.ts
+++ b/invokeai/frontend/web/src/features/modelManagerV2/hooks/useIsImported.ts
@@ -1,54 +1,62 @@
-import { useCallback } from "react";
-import { ALL_BASE_MODELS } from "../../../services/api/constants";
-import { useGetMainModelsQuery, useGetLoRAModelsQuery, useGetTextualInversionModelsQuery, useGetControlNetModelsQuery, useGetT2IAdapterModelsQuery, useGetIPAdapterModelsQuery, useGetVaeModelsQuery, } from "../../../services/api/endpoints/models";
-import { EntityState } from "@reduxjs/toolkit";
-import { forEach } from "lodash-es";
-import { AnyModelConfig } from "../../../services/api/types";
+import type { EntityState } from '@reduxjs/toolkit';
+import { forEach } from 'lodash-es';
+import { useCallback } from 'react';
+import { ALL_BASE_MODELS } from 'services/api/constants';
+import {
+  useGetControlNetModelsQuery,
+  useGetIPAdapterModelsQuery,
+  useGetLoRAModelsQuery,
+  useGetMainModelsQuery,
+  useGetT2IAdapterModelsQuery,
+  useGetTextualInversionModelsQuery,
+  useGetVaeModelsQuery,
+} from 'services/api/endpoints/models';
+import type { AnyModelConfig } from 'services/api/types';
 
 export const useIsImported = () => {
-    const { data: mainModels } = useGetMainModelsQuery(ALL_BASE_MODELS);
-    const { data: loras } = useGetLoRAModelsQuery();
-    const { data: embeddings } = useGetTextualInversionModelsQuery();
-    const { data: controlnets } = useGetControlNetModelsQuery();
-    const { data: ipAdapters } = useGetIPAdapterModelsQuery();
-    const { data: t2is } = useGetT2IAdapterModelsQuery();
-    const { data: vaes } = useGetVaeModelsQuery();
+  const { data: mainModels } = useGetMainModelsQuery(ALL_BASE_MODELS);
+  const { data: loras } = useGetLoRAModelsQuery();
+  const { data: embeddings } = useGetTextualInversionModelsQuery();
+  const { data: controlnets } = useGetControlNetModelsQuery();
+  const { data: ipAdapters } = useGetIPAdapterModelsQuery();
+  const { data: t2is } = useGetT2IAdapterModelsQuery();
+  const { data: vaes } = useGetVaeModelsQuery();
 
-    const isImported = useCallback(({ name }: { name: string }) => {
-        const data = [mainModels, loras, embeddings, controlnets, ipAdapters, t2is, vaes]
-        let isMatch = false;
-        for (let index = 0; index < data.length; index++) {
-            const modelType: EntityState<AnyModelConfig, string> | undefined = data[index];
+  const isImported = useCallback(
+    ({ name }: { name: string }) => {
+      const data = [mainModels, loras, embeddings, controlnets, ipAdapters, t2is, vaes];
+      let isMatch = false;
+      for (let index = 0; index < data.length; index++) {
+        const modelType: EntityState<AnyModelConfig, string> | undefined = data[index];
 
-            const match = modelsFilter(modelType, name)
+        const match = modelsFilter(modelType, name);
 
-            if (!!match.length) {
-                isMatch = true
-                break;
-            }
+        if (match.length) {
+          isMatch = true;
+          break;
         }
-        return isMatch
-    }, [mainModels, loras, embeddings, controlnets, ipAdapters, t2is, vaes])
+      }
+      return isMatch;
+    },
+    [mainModels, loras, embeddings, controlnets, ipAdapters, t2is, vaes]
+  );
 
-    return { isImported }
-}
+  return { isImported };
+};
 
-const modelsFilter = <T extends AnyModelConfig>(
-    data: EntityState<T, string> | undefined,
-    nameFilter: string,
-): T[] => {
-    const filteredModels: T[] = [];
+const modelsFilter = <T extends AnyModelConfig>(data: EntityState<T, string> | undefined, nameFilter: string): T[] => {
+  const filteredModels: T[] = [];
 
-    forEach(data?.entities, (model) => {
-        if (!model) {
-            return;
-        }
+  forEach(data?.entities, (model) => {
+    if (!model) {
+      return;
+    }
 
-        const matchesFilter = model.path.toLowerCase().includes(nameFilter.toLowerCase());
+    const matchesFilter = model.path.toLowerCase().includes(nameFilter.toLowerCase());
 
-        if (matchesFilter) {
-            filteredModels.push(model);
-        }
-    });
-    return filteredModels;
-};
\ No newline at end of file
+    if (matchesFilter) {
+      filteredModels.push(model);
+    }
+  });
+  return filteredModels;
+};
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/store/modelManagerV2Slice.ts b/invokeai/frontend/web/src/features/modelManagerV2/store/modelManagerV2Slice.ts
index f4760bad36..0ea2610ac4 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/store/modelManagerV2Slice.ts
+++ b/invokeai/frontend/web/src/features/modelManagerV2/store/modelManagerV2Slice.ts
@@ -2,59 +2,59 @@ import type { PayloadAction } from '@reduxjs/toolkit';
 import { createSlice } from '@reduxjs/toolkit';
 import type { PersistConfig, RootState } from 'app/store/store';
 
-
 type ModelManagerState = {
-    _version: 1;
-    selectedModelKey: string | null;
-    selectedModelMode: "edit" | "view",
-    searchTerm: string;
-    filteredModelType: string | null;
+  _version: 1;
+  selectedModelKey: string | null;
+  selectedModelMode: 'edit' | 'view';
+  searchTerm: string;
+  filteredModelType: string | null;
 };
 
 export const initialModelManagerState: ModelManagerState = {
-    _version: 1,
-    selectedModelKey: null,
-    selectedModelMode: "view",
-    filteredModelType: null,
-    searchTerm: ""
+  _version: 1,
+  selectedModelKey: null,
+  selectedModelMode: 'view',
+  filteredModelType: null,
+  searchTerm: '',
 };
 
 export const modelManagerV2Slice = createSlice({
-    name: 'modelmanagerV2',
-    initialState: initialModelManagerState,
-    reducers: {
-        setSelectedModelKey: (state, action: PayloadAction<string | null>) => {
-            state.selectedModelMode = "view"
-            state.selectedModelKey = action.payload;
-        },
-        setSelectedModelMode: (state, action: PayloadAction<"view" | "edit">) => {
-            state.selectedModelMode = action.payload;
-        },
-        setSearchTerm: (state, action: PayloadAction<string>) => {
-            state.searchTerm = action.payload;
-        },
-
-        setFilteredModelType: (state, action: PayloadAction<string | null>) => {
-            state.filteredModelType = action.payload;
-        },
+  name: 'modelmanagerV2',
+  initialState: initialModelManagerState,
+  reducers: {
+    setSelectedModelKey: (state, action: PayloadAction<string | null>) => {
+      state.selectedModelMode = 'view';
+      state.selectedModelKey = action.payload;
     },
+    setSelectedModelMode: (state, action: PayloadAction<'view' | 'edit'>) => {
+      state.selectedModelMode = action.payload;
+    },
+    setSearchTerm: (state, action: PayloadAction<string>) => {
+      state.searchTerm = action.payload;
+    },
+
+    setFilteredModelType: (state, action: PayloadAction<string | null>) => {
+      state.filteredModelType = action.payload;
+    },
+  },
 });
 
-export const { setSelectedModelKey, setSearchTerm, setFilteredModelType, setSelectedModelMode } = modelManagerV2Slice.actions;
+export const { setSelectedModelKey, setSearchTerm, setFilteredModelType, setSelectedModelMode } =
+  modelManagerV2Slice.actions;
 
 export const selectModelManagerSlice = (state: RootState) => state.modelmanager;
 
 /* eslint-disable-next-line @typescript-eslint/no-explicit-any */
 export const migrateModelManagerState = (state: any): any => {
-    if (!('_version' in state)) {
-        state._version = 1;
-    }
-    return state;
+  if (!('_version' in state)) {
+    state._version = 1;
+  }
+  return state;
 };
 
 export const modelManagerV2PersistConfig: PersistConfig<ModelManagerState> = {
-    name: modelManagerV2Slice.name,
-    initialState: initialModelManagerState,
-    migrate: migrateModelManagerState,
-    persistDenylist: [],
+  name: modelManagerV2Slice.name,
+  initialState: initialModelManagerState,
+  migrate: migrateModelManagerState,
+  persistDenylist: [],
 };
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/BaseModelSelect.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/BaseModelSelect.tsx
index 1e98ee6fec..a2d1176a80 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/BaseModelSelect.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/BaseModelSelect.tsx
@@ -27,9 +27,9 @@ const BaseModelSelect = <T extends AnyModelConfig>(props: UseControllerProps<T>)
   );
   return (
     <FormControl>
-        <Flex direction="column" width="full">
-      <FormLabel>{t('modelManager.baseModel')}</FormLabel>
-      <Combobox value={value} options={options} onChange={onChange} />
+      <Flex direction="column" width="full">
+        <FormLabel>{t('modelManager.baseModel')}</FormLabel>
+        <Combobox value={value} options={options} onChange={onChange} />
       </Flex>
     </FormControl>
   );
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueueBadge.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueueBadge.tsx
index 79ab0a7a4c..54a4eeaeb5 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueueBadge.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueueBadge.tsx
@@ -1,7 +1,7 @@
 import { Badge, Tooltip } from '@invoke-ai/ui-library';
 import { memo } from 'react';
 import { useTranslation } from 'react-i18next';
-import { ModelInstallStatus } from '../../../../../services/api/types';
+import type { ModelInstallStatus } from 'services/api/types';
 
 const STATUSES = {
   waiting: { colorScheme: 'cyan', translationKey: 'queue.pending' },
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueueItem.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueueItem.tsx
index 79c3227e65..fa13de0095 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueueItem.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueueItem.tsx
@@ -1,4 +1,4 @@
-import { Box, Flex, IconButton, Progress, Tag, Text, Tooltip } from '@invoke-ai/ui-library';
+import { Box, Flex, IconButton, Progress, Text, Tooltip } from '@invoke-ai/ui-library';
 import { useAppDispatch } from 'app/store/storeHooks';
 import { addToast } from 'features/system/store/systemSlice';
 import { makeToast } from 'features/system/util/makeToast';
@@ -6,7 +6,8 @@ import { t } from 'i18next';
 import { useCallback, useMemo } from 'react';
 import { PiXBold } from 'react-icons/pi';
 import { useDeleteModelImportMutation } from 'services/api/endpoints/models';
-import type { ModelInstallJob, HFModelSource, LocalModelSource, URLModelSource } from 'services/api/types';
+import type { HFModelSource, LocalModelSource, ModelInstallJob, URLModelSource } from 'services/api/types';
+
 import ImportQueueBadge from './ImportQueueBadge';
 
 type ModelListItemProps = {
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelResultItem.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelResultItem.tsx
index 2c186d74c1..7c9ab9f6cb 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelResultItem.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelResultItem.tsx
@@ -1,12 +1,12 @@
-import { Flex, Text, Box, Button, IconButton, Tooltip, Badge } from '@invoke-ai/ui-library';
+import { Badge, Box, Flex, IconButton, Text, Tooltip } from '@invoke-ai/ui-library';
+import { useAppDispatch } from 'app/store/storeHooks';
+import { useIsImported } from 'features/modelManagerV2/hooks/useIsImported';
+import { addToast } from 'features/system/store/systemSlice';
+import { makeToast } from 'features/system/util/makeToast';
+import { useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
 import { IoAdd } from 'react-icons/io5';
-import { useAppDispatch } from '../../../../../app/store/storeHooks';
-import { useImportMainModelsMutation } from '../../../../../services/api/endpoints/models';
-import { addToast } from '../../../../system/store/systemSlice';
-import { makeToast } from '../../../../system/util/makeToast';
-import { useIsImported } from '../../../hooks/useIsImported';
-import { useMemo } from 'react';
+import { useImportMainModelsMutation } from 'services/api/endpoints/models';
 
 export const ScanModelResultItem = ({ result }: { result: string }) => {
   const { t } = useTranslation();
@@ -14,11 +14,11 @@ export const ScanModelResultItem = ({ result }: { result: string }) => {
 
   const { isImported } = useIsImported();
 
-  const [importMainModel, { isLoading }] = useImportMainModelsMutation();
+  const [importMainModel] = useImportMainModelsMutation();
 
   const isAlreadyImported = useMemo(() => {
     const prettyName = result.split('\\').slice(-1)[0];
-    console.log({ prettyName });
+
     if (prettyName) {
       return isImported({ name: prettyName });
     } else {
@@ -26,7 +26,7 @@ export const ScanModelResultItem = ({ result }: { result: string }) => {
     }
   }, [result, isImported]);
 
-  const handleQuickAdd = () => {
+  const handleQuickAdd = useCallback(() => {
     importMainModel({ source: result, config: undefined })
       .unwrap()
       .then((_) => {
@@ -51,10 +51,10 @@ export const ScanModelResultItem = ({ result }: { result: string }) => {
           );
         }
       });
-  };
+  }, [importMainModel, result, dispatch, t]);
 
   return (
-    <Flex justifyContent={'space-between'}>
+    <Flex justifyContent="space-between">
       <Flex fontSize="sm" flexDir="column">
         <Text fontWeight="semibold">{result.split('\\').slice(-1)[0]}</Text>
         <Text variant="subtext">{result}</Text>
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModels.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModels.tsx
index 90bd005e0b..0a280a52fd 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModels.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModels.tsx
@@ -1,4 +1,3 @@
-
 export const ScanModels = () => {
   return null;
 };
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsForm.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsForm.tsx
index 9fd1b37425..63b879c63b 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsForm.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsForm.tsx
@@ -14,13 +14,11 @@ export const ScanModelsForm = () => {
   const [_scanModels, { isLoading, data }] = useLazyScanModelsQuery();
 
   const handleSubmitScan = useCallback(async () => {
-    try {
-      await _scanModels({ scan_path: scanPath }).unwrap();
-    } catch (error: any) {
+    _scanModels({ scan_path: scanPath }).catch((error) => {
       if (error) {
         setErrorMessage(error.data.detail);
       }
-    }
+    });
   }, [_scanModels, scanPath]);
 
   const handleSetScanPath: ChangeEventHandler<HTMLInputElement> = useCallback((e) => {
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx
index bbbbfb5048..bcf32995e5 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx
@@ -1,9 +1,10 @@
-import { Divider, Flex, Heading, IconButton, Input, InputGroup, InputRightElement, Text } from '@invoke-ai/ui-library';
+import { Divider, Flex, Heading, IconButton, Input, InputGroup, InputRightElement } from '@invoke-ai/ui-library';
 import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
 import { t } from 'i18next';
 import type { ChangeEventHandler } from 'react';
 import { useCallback, useMemo, useState } from 'react';
 import { PiXBold } from 'react-icons/pi';
+
 import { ScanModelResultItem } from './ScanModelResultItem';
 
 export const ScanModelsResults = ({ results }: { results: string[] }) => {
@@ -16,12 +17,9 @@ export const ScanModelsResults = ({ results }: { results: string[] }) => {
     });
   }, [results, searchTerm]);
 
-  const handleSearch: ChangeEventHandler<HTMLInputElement> = useCallback(
-    (e) => {
-      setSearchTerm(e.target.value);
-    },
-    [results]
-  );
+  const handleSearch: ChangeEventHandler<HTMLInputElement> = useCallback((e) => {
+    setSearchTerm(e.target.value);
+  }, []);
 
   const clearSearch = useCallback(() => {
     setSearchTerm('');
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/SimpleImport.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/SimpleImport.tsx
index 4c7ac0bd81..c056048c5b 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/SimpleImport.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/SimpleImport.tsx
@@ -1,10 +1,10 @@
-import { Button,Flex, FormControl, FormLabel, Input } from '@invoke-ai/ui-library';
+import { Button, Flex, FormControl, FormLabel, Input } from '@invoke-ai/ui-library';
 import { useAppDispatch } from 'app/store/storeHooks';
 import { addToast } from 'features/system/store/systemSlice';
 import { makeToast } from 'features/system/util/makeToast';
 import { t } from 'i18next';
 import { useCallback } from 'react';
-import type { SubmitHandler} from 'react-hook-form';
+import type { SubmitHandler } from 'react-hook-form';
 import { useForm } from 'react-hook-form';
 import { useImportMainModelsMutation } from 'services/api/endpoints/models';
 
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx
index 49e4faf893..b90b8e0429 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx
@@ -2,9 +2,8 @@ import { Box, Flex, Heading, Tab, TabList, TabPanel, TabPanels, Tabs } from '@in
 
 import { AdvancedImport } from './AddModelPanel/AdvancedImport';
 import { ImportQueue } from './AddModelPanel/ImportQueue/ImportQueue';
-import { ScanModels } from './AddModelPanel/ScanModels/ScanModels';
-import { SimpleImport } from './AddModelPanel/SimpleImport';
 import { ScanModelsForm } from './AddModelPanel/ScanModels/ScanModelsForm';
+import { SimpleImport } from './AddModelPanel/SimpleImport';
 
 export const ImportModels = () => {
   return (
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelListNavigation.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelListNavigation.tsx
index c0d06af245..b256e8a70f 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelListNavigation.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelListNavigation.tsx
@@ -1,8 +1,8 @@
-import { Flex, IconButton,Input, InputGroup, InputRightElement, Spacer } from '@invoke-ai/ui-library';
+import { Flex, IconButton, Input, InputGroup, InputRightElement, Spacer } from '@invoke-ai/ui-library';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { setSearchTerm } from 'features/modelManagerV2/store/modelManagerV2Slice';
 import { t } from 'i18next';
-import type { ChangeEventHandler} from 'react';
+import type { ChangeEventHandler } from 'react';
 import { useCallback } from 'react';
 import { PiXBold } from 'react-icons/pi';
 
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelConvert.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelConvert.tsx
index 2d1989ca3f..25038b4985 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelConvert.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelConvert.tsx
@@ -59,7 +59,7 @@ export const ModelConvert = (props: ModelConvertProps) => {
           )
         );
       });
-  }, [convertModel, dispatch, model.base, model.name, t]);
+  }, [convertModel, dispatch, model.key, model.name, t]);
 
   return (
     <>
diff --git a/invokeai/frontend/web/src/services/api/endpoints/models.ts b/invokeai/frontend/web/src/services/api/endpoints/models.ts
index 51b78a2277..e7c5151e3f 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/models.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/models.ts
@@ -58,7 +58,6 @@ type DeleteImportModelsResponse =
 type PruneModelImportsResponse =
   paths['/api/v2/models/import']['patch']['responses']['200']['content']['application/json'];
 
-
 export type ScanFolderResponse =
   paths['/api/v2/models/scan_folder']['get']['responses']['200']['content']['application/json'];
 type ScanFolderArg = operations['scan_for_models']['parameters']['query'];
@@ -104,25 +103,25 @@ export const vaeModelsAdapterSelectors = vaeModelsAdapter.getSelectors(undefined
 
 const buildProvidesTags =
   <TEntity extends AnyModelConfig>(tagType: (typeof tagTypes)[number]) =>
-    (result: EntityState<TEntity, string> | undefined) => {
-      const tags: ApiTagDescription[] = [{ type: tagType, id: LIST_TAG }, 'Model'];
-      if (result) {
-        tags.push(
-          ...result.ids.map((id) => ({
-            type: tagType,
-            id,
-          }))
-        );
-      }
+  (result: EntityState<TEntity, string> | undefined) => {
+    const tags: ApiTagDescription[] = [{ type: tagType, id: LIST_TAG }, 'Model'];
+    if (result) {
+      tags.push(
+        ...result.ids.map((id) => ({
+          type: tagType,
+          id,
+        }))
+      );
+    }
 
-      return tags;
-    };
+    return tags;
+  };
 
 const buildTransformResponse =
   <T extends AnyModelConfig>(adapter: EntityAdapter<T, string>) =>
-    (response: { models: T[] }) => {
-      return adapter.setAll(adapter.getInitialState(), response.models);
-    };
+  (response: { models: T[] }) => {
+    return adapter.setAll(adapter.getInitialState(), response.models);
+  };
 
 /**
  * Builds an endpoint URL for the models router
diff --git a/invokeai/frontend/web/src/services/api/types.ts b/invokeai/frontend/web/src/services/api/types.ts
index 02860be0c8..f6b7ad5e08 100644
--- a/invokeai/frontend/web/src/services/api/types.ts
+++ b/invokeai/frontend/web/src/services/api/types.ts
@@ -117,8 +117,8 @@ export const isRefinerMainModelModelConfig = (config: AnyModelConfig): config is
 
 export type MergeModelConfig = S['Body_merge'];
 export type ImportModelConfig = S['Body_import_model'];
-export type ModelInstallJob = S['ModelInstallJob']
-export type ModelInstallStatus = S["InstallStatus"]
+export type ModelInstallJob = S['ModelInstallJob'];
+export type ModelInstallStatus = S['InstallStatus'];
 
 export type HFModelSource = S['HFModelSource'];
 export type CivitaiModelSource = S['CivitaiModelSource'];
diff --git a/invokeai/frontend/web/src/services/events/util/setEventListeners.ts b/invokeai/frontend/web/src/services/events/util/setEventListeners.ts
index 38f917e394..4476624e4e 100644
--- a/invokeai/frontend/web/src/services/events/util/setEventListeners.ts
+++ b/invokeai/frontend/web/src/services/events/util/setEventListeners.ts
@@ -146,29 +146,29 @@ export const setEventListeners = (arg: SetEventListenersArg) => {
         data,
       })
     );
-  })
+  });
 
-    /**
+  /**
    * Model Install Completed
    */
-    socket.on('model_install_completed', (data) => {
-      dispatch(
-        socketModelInstallCompleted({
-          data,
-        })
-      );
-    })
+  socket.on('model_install_completed', (data) => {
+    dispatch(
+      socketModelInstallCompleted({
+        data,
+      })
+    );
+  });
 
   /**
    * Model Install Error
    */
-    socket.on('model_install_error', (data) => {
-      dispatch(
-        socketModelInstallError({
-          data,
-        })
-      );
-    })
+  socket.on('model_install_error', (data) => {
+    dispatch(
+      socketModelInstallError({
+        data,
+      })
+    );
+  });
 
   /**
    * Session retrieval error

From c98668e7f585eeaff4e069e927163a2076752235 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 24 Feb 2024 17:42:56 +1100
Subject: [PATCH 285/411] feat(api): mm metadata route "meta" -> "metadata"

---
 invokeai/app/api/routers/model_manager.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/invokeai/app/api/routers/model_manager.py b/invokeai/app/api/routers/model_manager.py
index a93846e7cd..37f844ab5c 100644
--- a/invokeai/app/api/routers/model_manager.py
+++ b/invokeai/app/api/routers/model_manager.py
@@ -202,7 +202,7 @@ async def list_model_summary(
 
 
 @model_manager_router.get(
-    "/i/{key}/meta",
+    "/i/{key}/metadata",
     operation_id="get_model_metadata",
     responses={
         200: {
@@ -218,7 +218,7 @@ async def get_model_metadata(
     """Get a model metadata object."""
     record_store = ApiDependencies.invoker.services.model_manager.store
     result: Optional[AnyModelRepoMetadata] = record_store.get_metadata(key)
-   
+
     return result
 
 

From 1d410e63468a06fc55b55947d65ca35d73a973a2 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 24 Feb 2024 17:43:04 +1100
Subject: [PATCH 286/411] chore(ui): typegen

---
 invokeai/frontend/web/src/services/api/schema.ts | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/invokeai/frontend/web/src/services/api/schema.ts b/invokeai/frontend/web/src/services/api/schema.ts
index d7b2001b35..a1af1684ca 100644
--- a/invokeai/frontend/web/src/services/api/schema.ts
+++ b/invokeai/frontend/web/src/services/api/schema.ts
@@ -46,7 +46,7 @@ export type paths = {
      */
     get: operations["list_model_summary"];
   };
-  "/api/v2/models/i/{key}/meta": {
+  "/api/v2/models/i/{key}/metadata": {
     /**
      * Get Model Metadata
      * @description Get a model metadata object.
@@ -4273,7 +4273,7 @@ export type components = {
        * @description The nodes in this graph
        */
       nodes: {
-        [key: string]: components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["CreateGradientMaskInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["ColorMapImageProcessorInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["DWOpenposeImageProcessorInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["DepthAnythingImageProcessorInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["ImageBlurInvocation"];
+        [key: string]: components["schemas"]["MultiplyInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["DWOpenposeImageProcessorInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["CreateGradientMaskInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["DepthAnythingImageProcessorInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["ColorMapImageProcessorInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["FaceOffInvocation"];
       };
       /**
        * Edges
@@ -4310,7 +4310,7 @@ export type components = {
        * @description The results of node executions
        */
       results: {
-        [key: string]: components["schemas"]["FloatCollectionOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["ClipSkipInvocationOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["LoraLoaderOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["LatentsOutput"] | components["schemas"]["SDXLLoraLoaderOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["VAEOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["MetadataOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["String2Output"] | components["schemas"]["ControlOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["ConditioningOutput"];
+        [key: string]: components["schemas"]["PairTileImageOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["String2Output"] | components["schemas"]["LatentsOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["SDXLLoraLoaderOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["VAEOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["LoraLoaderOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["ClipSkipInvocationOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["MetadataOutput"] | components["schemas"]["ConditioningCollectionOutput"];
       };
       /**
        * Errors

From 4420392241c317dfe13e844395497a0806eddd7b Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 24 Feb 2024 17:43:14 +1100
Subject: [PATCH 287/411] fix(ui): fix metadata route

---
 invokeai/frontend/web/src/services/api/endpoints/models.ts | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/invokeai/frontend/web/src/services/api/endpoints/models.ts b/invokeai/frontend/web/src/services/api/endpoints/models.ts
index e7c5151e3f..e8dad92467 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/models.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/models.ts
@@ -27,7 +27,7 @@ type UpdateModelResponse = paths['/api/v2/models/i/{key}']['patch']['responses']
 type GetModelConfigResponse = paths['/api/v2/models/i/{key}']['get']['responses']['200']['content']['application/json'];
 
 type GetModelMetadataResponse =
-  paths['/api/v2/models/i/{key}/meta']['get']['responses']['200']['content']['application/json'];
+  paths['/api/v2/models/i/{key}/metadata']['get']['responses']['200']['content']['application/json'];
 
 type ListModelsArg = NonNullable<paths['/api/v2/models/']['get']['parameters']['query']>;
 
@@ -150,7 +150,7 @@ export const modelsApi = api.injectEndpoints({
     }),
     getModelMetadata: build.query<GetModelMetadataResponse, string>({
       query: (key) => {
-        return buildModelsUrl(`i/${key}/meta`);
+        return buildModelsUrl(`i/${key}/metadata`);
       },
       providesTags: ['Model'],
     }),

From e22c4987bfaabcae8cd809c4b41506fd797ed144 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 24 Feb 2024 17:43:50 +1100
Subject: [PATCH 288/411] chore: ruff

---
 invokeai/app/services/events/events_base.py   | 26 ++++---------------
 .../model_install/model_install_default.py    |  2 +-
 2 files changed, 6 insertions(+), 22 deletions(-)

diff --git a/invokeai/app/services/events/events_base.py b/invokeai/app/services/events/events_base.py
index b3ee70b359..b52b919edd 100644
--- a/invokeai/app/services/events/events_base.py
+++ b/invokeai/app/services/events/events_base.py
@@ -357,7 +357,7 @@ class EventServiceBase:
         bytes: int,
         total_bytes: int,
         parts: List[Dict[str, Union[str, int]]],
-        id: int
+        id: int,
     ) -> None:
         """
         Emit at intervals while the install job is in progress (remote models only).
@@ -377,7 +377,7 @@ class EventServiceBase:
                 "bytes": bytes,
                 "total_bytes": total_bytes,
                 "parts": parts,
-                "id": id
+                "id": id,
             },
         )
 
@@ -402,12 +402,7 @@ class EventServiceBase:
         """
         self.__emit_model_event(
             event_name="model_install_completed",
-            payload={
-                "source": source,
-                "total_bytes": total_bytes,
-                "key": key,
-                "id": id
-            },
+            payload={"source": source, "total_bytes": total_bytes, "key": key, "id": id},
         )
 
     def emit_model_install_cancelled(self, source: str) -> None:
@@ -421,13 +416,7 @@ class EventServiceBase:
             payload={"source": source},
         )
 
-    def emit_model_install_error(
-        self,
-        source: str,
-        error_type: str,
-        error: str,
-        id: int
-    ) -> None:
+    def emit_model_install_error(self, source: str, error_type: str, error: str, id: int) -> None:
         """
         Emit when an install job encounters an exception.
 
@@ -437,12 +426,7 @@ class EventServiceBase:
         """
         self.__emit_model_event(
             event_name="model_install_error",
-            payload={
-                "source": source,
-                "error_type": error_type,
-                "error": error,
-                "id": id
-            },
+            payload={"source": source, "error_type": error_type, "error": error, "id": id},
         )
 
     def emit_bulk_download_started(
diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py
index ec330913c2..089acf442f 100644
--- a/invokeai/app/services/model_install/model_install_default.py
+++ b/invokeai/app/services/model_install/model_install_default.py
@@ -822,7 +822,7 @@ class ModelInstallService(ModelInstallServiceBase):
                 parts=parts,
                 bytes=job.bytes,
                 total_bytes=job.total_bytes,
-                id=job.id
+                id=job.id,
             )
 
     def _signal_job_completed(self, job: ModelInstallJob) -> None:

From 1436a5f29535444381d8fffc54bb7ae77d442d62 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 24 Feb 2024 17:45:31 +1100
Subject: [PATCH 289/411] build(ui): restore i18n eslint rule

---
 invokeai/frontend/web/.eslintrc.js | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/invokeai/frontend/web/.eslintrc.js b/invokeai/frontend/web/.eslintrc.js
index ebe4aed4b1..18a6e3a9b9 100644
--- a/invokeai/frontend/web/.eslintrc.js
+++ b/invokeai/frontend/web/.eslintrc.js
@@ -9,7 +9,7 @@ module.exports = {
     // https://github.com/qdanik/eslint-plugin-path
     'path/no-relative-imports': ['error', { maxDepth: 0 }],
     // https://github.com/edvardchen/eslint-plugin-i18next/blob/HEAD/docs/rules/no-literal-string.md
-    // 'i18next/no-literal-string': 'error',
+    'i18next/no-literal-string': 'error',
   },
   overrides: [
     /**

From 98d60e7db5905043cc98ff358427d0074a984790 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 24 Feb 2024 17:45:38 +1100
Subject: [PATCH 290/411] chore(ui): lint

---
 .../subpanels/AddModelPanel/AdvancedImport.tsx |  4 ++--
 .../web/src/services/api/endpoints/models.ts   | 18 ++++++++++++++++++
 invokeai/frontend/web/tsconfig.json            | 10 +++++-----
 3 files changed, 25 insertions(+), 7 deletions(-)

diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImport.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImport.tsx
index 36af89baec..b2fd094582 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImport.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImport.tsx
@@ -11,8 +11,8 @@ import RepoVariantSelect from 'features/modelManagerV2/subpanels/ModelPanel/Fiel
 import { addToast } from 'features/system/store/systemSlice';
 import { makeToast } from 'features/system/util/makeToast';
 import { useCallback, useEffect } from 'react';
-import type { SubmitHandler} from 'react-hook-form';
-import {useForm  } from 'react-hook-form';
+import type { SubmitHandler } from 'react-hook-form';
+import { useForm } from 'react-hook-form';
 import { useTranslation } from 'react-i18next';
 import { useImportAdvancedModelMutation } from 'services/api/endpoints/models';
 import type { AnyModelConfig } from 'services/api/types';
diff --git a/invokeai/frontend/web/src/services/api/endpoints/models.ts b/invokeai/frontend/web/src/services/api/endpoints/models.ts
index e8dad92467..e6be1c6d4a 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/models.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/models.ts
@@ -58,6 +58,14 @@ type DeleteImportModelsResponse =
 type PruneModelImportsResponse =
   paths['/api/v2/models/import']['patch']['responses']['200']['content']['application/json'];
 
+type ImportAdvancedModelArg = {
+  source: NonNullable<operations['import_model']['requestBody']['content']['application/json']['source']>;
+  config: NonNullable<operations['import_model']['requestBody']['content']['application/json']['config']>;
+};
+
+type ImportAdvancedModelResponse =
+  paths['/api/v2/models/import']['post']['responses']['201']['content']['application/json'];
+
 export type ScanFolderResponse =
   paths['/api/v2/models/scan_folder']['get']['responses']['200']['content']['application/json'];
 type ScanFolderArg = operations['scan_for_models']['parameters']['query'];
@@ -175,6 +183,16 @@ export const modelsApi = api.injectEndpoints({
       },
       invalidatesTags: ['Model', 'ModelImports'],
     }),
+    importAdvancedModel: build.mutation<ImportAdvancedModelResponse, ImportAdvancedModelArg>({
+      query: ({ source, config }) => {
+        return {
+          url: buildModelsUrl('install'),
+          method: 'POST',
+          body: { source, config },
+        };
+      },
+      invalidatesTags: ['Model', 'ModelImports'],
+    }),
     deleteModels: build.mutation<DeleteMainModelResponse, DeleteMainModelArg>({
       query: ({ key }) => {
         return {
diff --git a/invokeai/frontend/web/tsconfig.json b/invokeai/frontend/web/tsconfig.json
index fc1111ffd0..91906c9abe 100644
--- a/invokeai/frontend/web/tsconfig.json
+++ b/invokeai/frontend/web/tsconfig.json
@@ -20,16 +20,16 @@
     "jsx": "react-jsx",
     "baseUrl": "./",
     "paths": {
-      "*": ["./src/*"],
-    },
+      "*": ["./src/*"]
+    }
   },
   "include": ["src/**/*.ts", "src/**/*.tsx", "*.d.ts", ".storybook/**/*"],
   "exclude": ["src/services/fixtures/*", "node_modules", "dist"],
   "references": [{ "path": "./tsconfig.node.json" }],
   "ts-node": {
     "compilerOptions": {
-      "jsx": "preserve",
+      "jsx": "preserve"
     },
-    "esm": true,
-  },
+    "esm": true
+  }
 }

From 531d6f40f4c66ce47a0aaf9769ed1ada87de07c7 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 24 Feb 2024 18:46:54 +1100
Subject: [PATCH 291/411] feat(mm): add logic to scan_folder route to check if
 a model is already installed

This was done in the frontend before but it's something the backend should handle.

The logic compares the found model paths to the path and source of all installed models. It excludes core models.
---
 invokeai/app/api/routers/model_manager.py | 48 ++++++++++++++++++++---
 1 file changed, 43 insertions(+), 5 deletions(-)

diff --git a/invokeai/app/api/routers/model_manager.py b/invokeai/app/api/routers/model_manager.py
index 37f844ab5c..c27fc0e0de 100644
--- a/invokeai/app/api/routers/model_manager.py
+++ b/invokeai/app/api/routers/model_manager.py
@@ -9,7 +9,7 @@ from typing import Any, Dict, List, Optional, Set
 
 from fastapi import Body, Path, Query, Response
 from fastapi.routing import APIRouter
-from pydantic import BaseModel, ConfigDict
+from pydantic import BaseModel, ConfigDict, Field
 from starlette.exceptions import HTTPException
 from typing_extensions import Annotated
 
@@ -233,6 +233,11 @@ async def list_tags() -> Set[str]:
     return result
 
 
+class FoundModel(BaseModel):
+    path: str = Field(description="Path to the model")
+    is_installed: bool = Field(description="Whether or not the model is already installed")
+
+
 @model_manager_router.get(
     "/scan_folder",
     operation_id="scan_for_models",
@@ -241,11 +246,11 @@ async def list_tags() -> Set[str]:
         400: {"description": "Invalid directory path"},
     },
     status_code=200,
-    response_model=List[pathlib.Path],
+    response_model=List[FoundModel],
 )
 async def scan_for_models(
     scan_path: str = Query(description="Directory path to search for models", default=None),
-) -> List[pathlib.Path]:
+) -> List[FoundModel]:
     path = pathlib.Path(scan_path)
     if not scan_path or not path.is_dir():
         raise HTTPException(
@@ -255,13 +260,46 @@ async def scan_for_models(
 
     search = ModelSearch()
     try:
-        models_found = list(search.search(path))
+        found_model_paths = search.search(path)
+        models_path = ApiDependencies.invoker.services.configuration.models_path
+
+        # If the search path includes the main models directory, we need to exclude core models from the list.
+        # TODO(MM2): Core models should be handled by the model manager so we can determine if they are installed
+        # without needing to crawl the filesystem.
+        core_models_path = pathlib.Path(models_path, "core").resolve()
+        non_core_model_paths = [p for p in found_model_paths if not p.is_relative_to(core_models_path)]
+
+        installed_models = ApiDependencies.invoker.services.model_manager.store.search_by_attr()
+        resolved_installed_model_paths: list[str] = []
+        installed_model_sources: list[str] = []
+
+        # This call lists all installed models.
+        for model in installed_models:
+            path = pathlib.Path(model.path)
+            # If the model has a source, we need to add it to the list of installed sources.
+            if model.source:
+                installed_model_sources.append(model.source)
+            # If the path is not absolute, that means it is in the app models directory, and we need to join it with
+            # the models path before resolving.
+            if not path.is_absolute():
+                resolved_installed_model_paths.append(str(pathlib.Path(models_path, path).resolve()))
+                continue
+            resolved_installed_model_paths.append(str(path.resolve()))
+
+        scan_results: list[FoundModel] = []
+
+        # Check if the model is installed by comparing the resolved paths, appending to the scan result.
+        for p in non_core_model_paths:
+            path = str(p)
+            is_installed = path in resolved_installed_model_paths or path in installed_model_sources
+            found_model = FoundModel(path=path, is_installed=is_installed)
+            scan_results.append(found_model)
     except Exception as e:
         raise HTTPException(
             status_code=500,
             detail=f"An error occurred while searching the directory: {e}",
         )
-    return models_found
+    return scan_results
 
 
 @model_manager_router.get(

From 9e0238467442de3ceb0cbd07ad525ae4b90a6821 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 24 Feb 2024 18:47:06 +1100
Subject: [PATCH 292/411] chore(ui): typegen

---
 .../frontend/web/src/services/api/schema.ts   | 19 ++++++++++++++++---
 1 file changed, 16 insertions(+), 3 deletions(-)

diff --git a/invokeai/frontend/web/src/services/api/schema.ts b/invokeai/frontend/web/src/services/api/schema.ts
index a1af1684ca..59d1db5f19 100644
--- a/invokeai/frontend/web/src/services/api/schema.ts
+++ b/invokeai/frontend/web/src/services/api/schema.ts
@@ -4171,6 +4171,19 @@ export type components = {
        */
       type: "float_to_int";
     };
+    /** FoundModel */
+    FoundModel: {
+      /**
+       * Path
+       * @description Path to the model
+       */
+      path: string;
+      /**
+       * Is Installed
+       * @description Whether or not the model is already installed
+       */
+      is_installed: boolean;
+    };
     /**
      * FreeUConfig
      * @description Configuration for the FreeU hyperparameters.
@@ -4273,7 +4286,7 @@ export type components = {
        * @description The nodes in this graph
        */
       nodes: {
-        [key: string]: components["schemas"]["MultiplyInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["DWOpenposeImageProcessorInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["CreateGradientMaskInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["DepthAnythingImageProcessorInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["ColorMapImageProcessorInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["FaceOffInvocation"];
+        [key: string]: components["schemas"]["StringJoinInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["CreateGradientMaskInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["ColorMapImageProcessorInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["DWOpenposeImageProcessorInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["DepthAnythingImageProcessorInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["MergeTilesToImageInvocation"];
       };
       /**
        * Edges
@@ -4310,7 +4323,7 @@ export type components = {
        * @description The results of node executions
        */
       results: {
-        [key: string]: components["schemas"]["PairTileImageOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["String2Output"] | components["schemas"]["LatentsOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["SDXLLoraLoaderOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["VAEOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["LoraLoaderOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["ClipSkipInvocationOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["MetadataOutput"] | components["schemas"]["ConditioningCollectionOutput"];
+        [key: string]: components["schemas"]["LoraLoaderOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["MetadataOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["SDXLLoraLoaderOutput"] | components["schemas"]["ClipSkipInvocationOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["LatentsOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["String2Output"] | components["schemas"]["VAEOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["NoiseOutput"];
       };
       /**
        * Errors
@@ -11447,7 +11460,7 @@ export type operations = {
       /** @description Directory scanned successfully */
       200: {
         content: {
-          "application/json": string[];
+          "application/json": components["schemas"]["FoundModel"][];
         };
       };
       /** @description Invalid directory path */

From 7fce234646f1a6358d52c7d6f165e4a759bbea0b Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 24 Feb 2024 18:48:21 +1100
Subject: [PATCH 293/411] fix(ui): use new scan_folder response instead of hook
 to determine if models are installed already

---
 .../modelManagerV2/hooks/useIsImported.ts     | 62 -------------------
 .../ScanModels/ScanModelResultItem.tsx        | 29 +++------
 .../ScanModels/ScanModelsResults.tsx          | 19 +++---
 3 files changed, 22 insertions(+), 88 deletions(-)
 delete mode 100644 invokeai/frontend/web/src/features/modelManagerV2/hooks/useIsImported.ts

diff --git a/invokeai/frontend/web/src/features/modelManagerV2/hooks/useIsImported.ts b/invokeai/frontend/web/src/features/modelManagerV2/hooks/useIsImported.ts
deleted file mode 100644
index 763317a639..0000000000
--- a/invokeai/frontend/web/src/features/modelManagerV2/hooks/useIsImported.ts
+++ /dev/null
@@ -1,62 +0,0 @@
-import type { EntityState } from '@reduxjs/toolkit';
-import { forEach } from 'lodash-es';
-import { useCallback } from 'react';
-import { ALL_BASE_MODELS } from 'services/api/constants';
-import {
-  useGetControlNetModelsQuery,
-  useGetIPAdapterModelsQuery,
-  useGetLoRAModelsQuery,
-  useGetMainModelsQuery,
-  useGetT2IAdapterModelsQuery,
-  useGetTextualInversionModelsQuery,
-  useGetVaeModelsQuery,
-} from 'services/api/endpoints/models';
-import type { AnyModelConfig } from 'services/api/types';
-
-export const useIsImported = () => {
-  const { data: mainModels } = useGetMainModelsQuery(ALL_BASE_MODELS);
-  const { data: loras } = useGetLoRAModelsQuery();
-  const { data: embeddings } = useGetTextualInversionModelsQuery();
-  const { data: controlnets } = useGetControlNetModelsQuery();
-  const { data: ipAdapters } = useGetIPAdapterModelsQuery();
-  const { data: t2is } = useGetT2IAdapterModelsQuery();
-  const { data: vaes } = useGetVaeModelsQuery();
-
-  const isImported = useCallback(
-    ({ name }: { name: string }) => {
-      const data = [mainModels, loras, embeddings, controlnets, ipAdapters, t2is, vaes];
-      let isMatch = false;
-      for (let index = 0; index < data.length; index++) {
-        const modelType: EntityState<AnyModelConfig, string> | undefined = data[index];
-
-        const match = modelsFilter(modelType, name);
-
-        if (match.length) {
-          isMatch = true;
-          break;
-        }
-      }
-      return isMatch;
-    },
-    [mainModels, loras, embeddings, controlnets, ipAdapters, t2is, vaes]
-  );
-
-  return { isImported };
-};
-
-const modelsFilter = <T extends AnyModelConfig>(data: EntityState<T, string> | undefined, nameFilter: string): T[] => {
-  const filteredModels: T[] = [];
-
-  forEach(data?.entities, (model) => {
-    if (!model) {
-      return;
-    }
-
-    const matchesFilter = model.path.toLowerCase().includes(nameFilter.toLowerCase());
-
-    if (matchesFilter) {
-      filteredModels.push(model);
-    }
-  });
-  return filteredModels;
-};
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelResultItem.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelResultItem.tsx
index 7c9ab9f6cb..6ae7573665 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelResultItem.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelResultItem.tsx
@@ -1,33 +1,24 @@
 import { Badge, Box, Flex, IconButton, Text, Tooltip } from '@invoke-ai/ui-library';
 import { useAppDispatch } from 'app/store/storeHooks';
-import { useIsImported } from 'features/modelManagerV2/hooks/useIsImported';
 import { addToast } from 'features/system/store/systemSlice';
 import { makeToast } from 'features/system/util/makeToast';
-import { useCallback, useMemo } from 'react';
+import { useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 import { IoAdd } from 'react-icons/io5';
+import type { ScanFolderResponse } from 'services/api/endpoints/models';
 import { useImportMainModelsMutation } from 'services/api/endpoints/models';
 
-export const ScanModelResultItem = ({ result }: { result: string }) => {
+type Props = {
+  result: ScanFolderResponse[number];
+};
+export const ScanModelResultItem = ({ result }: Props) => {
   const { t } = useTranslation();
   const dispatch = useAppDispatch();
 
-  const { isImported } = useIsImported();
-
   const [importMainModel] = useImportMainModelsMutation();
 
-  const isAlreadyImported = useMemo(() => {
-    const prettyName = result.split('\\').slice(-1)[0];
-
-    if (prettyName) {
-      return isImported({ name: prettyName });
-    } else {
-      return false;
-    }
-  }, [result, isImported]);
-
   const handleQuickAdd = useCallback(() => {
-    importMainModel({ source: result, config: undefined })
+    importMainModel({ source: result.path, config: undefined })
       .unwrap()
       .then((_) => {
         dispatch(
@@ -56,11 +47,11 @@ export const ScanModelResultItem = ({ result }: { result: string }) => {
   return (
     <Flex justifyContent="space-between">
       <Flex fontSize="sm" flexDir="column">
-        <Text fontWeight="semibold">{result.split('\\').slice(-1)[0]}</Text>
-        <Text variant="subtext">{result}</Text>
+        <Text fontWeight="semibold">{result.path.split('\\').slice(-1)[0]}</Text>
+        <Text variant="subtext">{result.path}</Text>
       </Flex>
       <Box>
-        {isAlreadyImported ? (
+        {result.is_installed ? (
           <Badge>{t('common.installed')}</Badge>
         ) : (
           <Tooltip label={t('modelManager.quickAdd')}>
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx
index bcf32995e5..7a300546b3 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx
@@ -4,21 +4,26 @@ import { t } from 'i18next';
 import type { ChangeEventHandler } from 'react';
 import { useCallback, useMemo, useState } from 'react';
 import { PiXBold } from 'react-icons/pi';
+import type { ScanFolderResponse } from 'services/api/endpoints/models';
 
 import { ScanModelResultItem } from './ScanModelResultItem';
 
-export const ScanModelsResults = ({ results }: { results: string[] }) => {
+type ScanModelResultsProps = {
+  results: ScanFolderResponse;
+};
+
+export const ScanModelsResults = ({ results }: ScanModelResultsProps) => {
   const [searchTerm, setSearchTerm] = useState('');
 
   const filteredResults = useMemo(() => {
     return results.filter((result) => {
-      const modelName = result.split('\\').slice(-1)[0];
-      return modelName?.includes(searchTerm);
+      const modelName = result.path.split('\\').slice(-1)[0];
+      return modelName?.toLowerCase().includes(searchTerm.toLowerCase());
     });
   }, [results, searchTerm]);
 
   const handleSearch: ChangeEventHandler<HTMLInputElement> = useCallback((e) => {
-    setSearchTerm(e.target.value);
+    setSearchTerm(e.target.value.trim());
   }, []);
 
   const clearSearch = useCallback(() => {
@@ -36,13 +41,13 @@ export const ScanModelsResults = ({ results }: { results: string[] }) => {
           <InputGroup maxW="300px" size="xs">
             <Input
               placeholder={t('modelManager.search')}
-              value={searchTerm || ''}
+              value={searchTerm}
               data-testid="board-search-input"
               onChange={handleSearch}
               size="xs"
             />
 
-            {!!searchTerm?.length && (
+            {searchTerm && (
               <InputRightElement h="full" pe={2}>
                 <IconButton
                   size="sm"
@@ -59,7 +64,7 @@ export const ScanModelsResults = ({ results }: { results: string[] }) => {
           <ScrollableContent>
             <Flex flexDir="column" gap={3}>
               {filteredResults.map((result) => (
-                <ScanModelResultItem key={result} result={result} />
+                <ScanModelResultItem key={result.path} result={result} />
               ))}
             </Flex>
           </ScrollableContent>

From 1456c997fbeb90c0914631552da93d9ab7b25543 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 24 Feb 2024 18:59:38 +1100
Subject: [PATCH 294/411] fix(ui): fix merge issue

---
 invokeai/frontend/web/src/services/api/endpoints/models.ts | 1 +
 1 file changed, 1 insertion(+)

diff --git a/invokeai/frontend/web/src/services/api/endpoints/models.ts b/invokeai/frontend/web/src/services/api/endpoints/models.ts
index e6be1c6d4a..6618fda58e 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/models.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/models.ts
@@ -311,6 +311,7 @@ export const {
   useDeleteModelsMutation,
   useUpdateModelsMutation,
   useImportMainModelsMutation,
+  useImportAdvancedModelMutation,
   useConvertMainModelsMutation,
   useSyncModelsMutation,
   useScanModelsQuery,

From ea7b7bcf40799663e573f9a25e2fe630f9d5f8cd Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 24 Feb 2024 19:01:30 +1100
Subject: [PATCH 295/411] chore: ruff

---
 invokeai/app/services/model_install/model_install_default.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py
index 089acf442f..903fe41b08 100644
--- a/invokeai/app/services/model_install/model_install_default.py
+++ b/invokeai/app/services/model_install/model_install_default.py
@@ -543,8 +543,8 @@ class ModelInstallService(ModelInstallServiceBase):
         self, model_path: Path, config: Optional[Dict[str, Any]] = None, info: Optional[AnyModelConfig] = None
     ) -> str:
         key = self._create_key()
-        if config and not config.get('key', None):
-            config['key'] = key
+        if config and not config.get("key", None):
+            config["key"] = key
         info = info or ModelProbe.probe(model_path, config)
 
         model_path = model_path.absolute()

From 8f6c2a8b920ed36554dc6bfe760f65fa5e4111bf Mon Sep 17 00:00:00 2001
From: blessedcoolant <54517381+blessedcoolant@users.noreply.github.com>
Date: Wed, 21 Feb 2024 23:02:49 +0530
Subject: [PATCH 296/411] wip(ui): Replace 2 Layer Coherence pass with Gradient
 Mask

---
 invokeai/frontend/web/public/locales/en.json  |  22 +-
 .../frontend/web/src/app/types/invokeai.ts    |   2 +-
 .../InformationalPopover/constants.ts         |   4 +-
 .../util/graph/addControlNetToLinearGraph.ts  |  12 +-
 .../util/graph/addIPAdapterToLinearGraph.ts   |  11 +-
 .../nodes/util/graph/addLoRAsToGraph.ts       |  24 +-
 .../nodes/util/graph/addSDXLLoRAstoGraph.ts   |  16 --
 .../util/graph/addSeamlessToLinearGraph.ts    |  21 --
 .../util/graph/addT2IAdapterToLinearGraph.ts  |  11 +-
 .../nodes/util/graph/addVAEToGraph.ts         |  29 +-
 .../util/graph/buildCanvasInpaintGraph.ts     | 261 +-----------------
 .../util/graph/buildCanvasOutpaintGraph.ts    | 222 +--------------
 .../util/graph/buildCanvasSDXLInpaintGraph.ts | 254 +----------------
 .../graph/buildCanvasSDXLOutpaintGraph.ts     | 218 +--------------
 ...s.tsx => ParamCanvasCoherenceEdgeSize.tsx} |  32 +--
 ...tsx => ParamCanvasCoherenceMinDenoise.tsx} |  22 +-
 .../ParamCanvasCoherenceMode.tsx              |   6 +-
 .../parameters/store/generationSlice.ts       |  18 +-
 .../src/features/parameters/store/types.ts    |   4 +-
 .../parameters/types/parameterSchemas.ts      |   2 +-
 .../CompositingSettingsAccordion.tsx          |  14 +-
 .../src/features/system/store/configSlice.ts  |  16 +-
 22 files changed, 122 insertions(+), 1099 deletions(-)
 rename invokeai/frontend/web/src/features/parameters/components/Canvas/Compositing/CoherencePass/{ParamCanvasCoherenceSteps.tsx => ParamCanvasCoherenceEdgeSize.tsx} (66%)
 rename invokeai/frontend/web/src/features/parameters/components/Canvas/Compositing/CoherencePass/{ParamCanvasCoherenceStrength.tsx => ParamCanvasCoherenceMinDenoise.tsx} (58%)

diff --git a/invokeai/frontend/web/public/locales/en.json b/invokeai/frontend/web/public/locales/en.json
index 26d95e4c07..d25f7f938b 100644
--- a/invokeai/frontend/web/public/locales/en.json
+++ b/invokeai/frontend/web/public/locales/en.json
@@ -1130,8 +1130,8 @@
         "codeformerFidelity": "Fidelity",
         "coherenceMode": "Mode",
         "coherencePassHeader": "Coherence Pass",
-        "coherenceSteps": "Steps",
-        "coherenceStrength": "Strength",
+        "coherenceEdgeSize": "Edge Size",
+        "coherenceMinDenoise": "Min Denoise",
         "compositingSettingsHeader": "Compositing Settings",
         "controlNetControlMode": "Control Mode",
         "copyImage": "Copy Image",
@@ -1478,13 +1478,16 @@
             "heading": "Mode",
             "paragraphs": ["Method used to create a coherent image with the newly generated masked area."]
         },
-        "compositingCoherenceSteps": {
-            "heading": "Steps",
-            "paragraphs": ["Number of steps in the Coherence Pass.", "Similar to Generation Steps."]
+        "compositingCoherenceEdgeSize": {
+            "heading": "Edge Size",
+            "paragraphs": ["The edge size of the coherence pass."]
         },
-        "compositingStrength": {
-            "heading": "Strength",
-            "paragraphs": ["Amount of noise added for the Coherence Pass.", "Similar to Denoising Strength."]
+        "compositingCoherenceMinDenoise": {
+            "heading": "Minimum Denoise",
+            "paragraphs": [
+                "Minimum denoise strength for the Coherence mode",
+                "The minimum denoise strength for the coherence region when inpainting or outpainting"
+            ]
         },
         "compositingMaskAdjustments": {
             "heading": "Mask Adjustments",
@@ -1762,6 +1765,9 @@
         "clearCanvasHistoryMessage": "Clearing the canvas history leaves your current canvas intact, but irreversibly clears the undo and redo history.",
         "clearHistory": "Clear History",
         "clearMask": "Clear Mask (Shift+C)",
+        "coherenceModeGaussianBlur": "Gaussian Blur",
+        "coherenceModeBoxBlur": "Box Blur",
+        "coherenceModeStaged": "Staged",
         "colorPicker": "Color Picker",
         "copyToClipboard": "Copy to Clipboard",
         "cursorPosition": "Cursor Position",
diff --git a/invokeai/frontend/web/src/app/types/invokeai.ts b/invokeai/frontend/web/src/app/types/invokeai.ts
index d511812cb4..a2b17b483d 100644
--- a/invokeai/frontend/web/src/app/types/invokeai.ts
+++ b/invokeai/frontend/web/src/app/types/invokeai.ts
@@ -88,7 +88,7 @@ export type AppConfig = {
     scaledBoundingBoxHeight: NumericalParameterConfig; // initial value comes from model
     scaledBoundingBoxWidth: NumericalParameterConfig; // initial value comes from model
     canvasCoherenceStrength: NumericalParameterConfig;
-    canvasCoherenceSteps: NumericalParameterConfig;
+    canvasCoherenceEdgeSize: NumericalParameterConfig;
     infillTileSize: NumericalParameterConfig;
     infillPatchmatchDownscaleSize: NumericalParameterConfig;
     // Misc advanced
diff --git a/invokeai/frontend/web/src/common/components/InformationalPopover/constants.ts b/invokeai/frontend/web/src/common/components/InformationalPopover/constants.ts
index 2e88c28df6..6fb06a4287 100644
--- a/invokeai/frontend/web/src/common/components/InformationalPopover/constants.ts
+++ b/invokeai/frontend/web/src/common/components/InformationalPopover/constants.ts
@@ -10,8 +10,8 @@ export type Feature =
   | 'compositingBlurMethod'
   | 'compositingCoherencePass'
   | 'compositingCoherenceMode'
-  | 'compositingCoherenceSteps'
-  | 'compositingStrength'
+  | 'compositingCoherenceEdgeSize'
+  | 'compositingCoherenceMinDenoise'
   | 'compositingMaskAdjustments'
   | 'controlNet'
   | 'controlNetBeginEnd'
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/addControlNetToLinearGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/addControlNetToLinearGraph.ts
index 1853d3722c..8441a1ef21 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/addControlNetToLinearGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/addControlNetToLinearGraph.ts
@@ -9,7 +9,7 @@ import type {
   NonNullableGraph,
 } from 'services/api/types';
 
-import { CANVAS_COHERENCE_DENOISE_LATENTS, CONTROL_NET_COLLECT } from './constants';
+import { CONTROL_NET_COLLECT } from './constants';
 import { upsertMetadata } from './metadata';
 
 export const addControlNetToLinearGraph = (state: RootState, graph: NonNullableGraph, baseNodeId: string): void => {
@@ -39,16 +39,6 @@ export const addControlNetToLinearGraph = (state: RootState, graph: NonNullableG
       },
     });
 
-    if (CANVAS_COHERENCE_DENOISE_LATENTS in graph.nodes) {
-      graph.edges.push({
-        source: { node_id: CONTROL_NET_COLLECT, field: 'collection' },
-        destination: {
-          node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
-          field: 'control',
-        },
-      });
-    }
-
     validControlNets.forEach((controlNet) => {
       if (!controlNet.model) {
         return;
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/addIPAdapterToLinearGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/addIPAdapterToLinearGraph.ts
index b51ac1bd52..1760310cae 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/addIPAdapterToLinearGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/addIPAdapterToLinearGraph.ts
@@ -9,7 +9,7 @@ import type {
   NonNullableGraph,
 } from 'services/api/types';
 
-import { CANVAS_COHERENCE_DENOISE_LATENTS, IP_ADAPTER_COLLECT } from './constants';
+import { IP_ADAPTER_COLLECT } from './constants';
 import { upsertMetadata } from './metadata';
 
 export const addIPAdapterToLinearGraph = (state: RootState, graph: NonNullableGraph, baseNodeId: string): void => {
@@ -33,15 +33,6 @@ export const addIPAdapterToLinearGraph = (state: RootState, graph: NonNullableGr
       },
     });
 
-    if (CANVAS_COHERENCE_DENOISE_LATENTS in graph.nodes) {
-      graph.edges.push({
-        source: { node_id: IP_ADAPTER_COLLECT, field: 'collection' },
-        destination: {
-          node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
-          field: 'ip_adapter',
-        },
-      });
-    }
     const ipAdapterMetdata: CoreMetadataInvocation['ipAdapters'] = [];
 
     validIPAdapters.forEach((ipAdapter) => {
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/addLoRAsToGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/addLoRAsToGraph.ts
index 95bba9b441..3d1545d466 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/addLoRAsToGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/addLoRAsToGraph.ts
@@ -2,16 +2,7 @@ import type { RootState } from 'app/store/store';
 import { filter, size } from 'lodash-es';
 import type { CoreMetadataInvocation, LoraLoaderInvocation, NonNullableGraph } from 'services/api/types';
 
-import {
-  CANVAS_COHERENCE_DENOISE_LATENTS,
-  CANVAS_INPAINT_GRAPH,
-  CANVAS_OUTPAINT_GRAPH,
-  CLIP_SKIP,
-  LORA_LOADER,
-  MAIN_MODEL_LOADER,
-  NEGATIVE_CONDITIONING,
-  POSITIVE_CONDITIONING,
-} from './constants';
+import { CLIP_SKIP, LORA_LOADER, MAIN_MODEL_LOADER, NEGATIVE_CONDITIONING, POSITIVE_CONDITIONING } from './constants';
 import { upsertMetadata } from './metadata';
 
 export const addLoRAsToGraph = (
@@ -127,19 +118,6 @@ export const addLoRAsToGraph = (
         },
       });
 
-      if (graph.id && [CANVAS_INPAINT_GRAPH, CANVAS_OUTPAINT_GRAPH].includes(graph.id)) {
-        graph.edges.push({
-          source: {
-            node_id: currentLoraNodeId,
-            field: 'unet',
-          },
-          destination: {
-            node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
-            field: 'unet',
-          },
-        });
-      }
-
       graph.edges.push({
         source: {
           node_id: currentLoraNodeId,
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/addSDXLLoRAstoGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/addSDXLLoRAstoGraph.ts
index 7874b059c9..27f4c0c015 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/addSDXLLoRAstoGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/addSDXLLoRAstoGraph.ts
@@ -5,12 +5,9 @@ import { filter, size } from 'lodash-es';
 import type { NonNullableGraph, SDXLLoraLoaderInvocation } from 'services/api/types';
 
 import {
-  CANVAS_COHERENCE_DENOISE_LATENTS,
   LORA_LOADER,
   NEGATIVE_CONDITIONING,
   POSITIVE_CONDITIONING,
-  SDXL_CANVAS_INPAINT_GRAPH,
-  SDXL_CANVAS_OUTPAINT_GRAPH,
   SDXL_MODEL_LOADER,
   SDXL_REFINER_INPAINT_CREATE_MASK,
   SEAMLESS,
@@ -163,19 +160,6 @@ export const addSDXLLoRAsToGraph = (
         },
       });
 
-      if (graph.id && [SDXL_CANVAS_INPAINT_GRAPH, SDXL_CANVAS_OUTPAINT_GRAPH].includes(graph.id)) {
-        graph.edges.push({
-          source: {
-            node_id: currentLoraNodeId,
-            field: 'unet',
-          },
-          destination: {
-            node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
-            field: 'unet',
-          },
-        });
-      }
-
       graph.edges.push({
         source: {
           node_id: currentLoraNodeId,
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/addSeamlessToLinearGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/addSeamlessToLinearGraph.ts
index 803437e968..d986130d64 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/addSeamlessToLinearGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/addSeamlessToLinearGraph.ts
@@ -2,9 +2,6 @@ import type { RootState } from 'app/store/store';
 import type { NonNullableGraph, SeamlessModeInvocation } from 'services/api/types';
 
 import {
-  CANVAS_COHERENCE_DENOISE_LATENTS,
-  CANVAS_INPAINT_GRAPH,
-  CANVAS_OUTPAINT_GRAPH,
   DENOISE_LATENTS,
   SDXL_CANVAS_IMAGE_TO_IMAGE_GRAPH,
   SDXL_CANVAS_INPAINT_GRAPH,
@@ -105,22 +102,4 @@ export const addSeamlessToLinearGraph = (
       },
     }
   );
-
-  if (
-    graph.id === CANVAS_INPAINT_GRAPH ||
-    graph.id === CANVAS_OUTPAINT_GRAPH ||
-    graph.id === SDXL_CANVAS_INPAINT_GRAPH ||
-    graph.id === SDXL_CANVAS_OUTPAINT_GRAPH
-  ) {
-    graph.edges.push({
-      source: {
-        node_id: SEAMLESS,
-        field: 'unet',
-      },
-      destination: {
-        node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
-        field: 'unet',
-      },
-    });
-  }
 };
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/addT2IAdapterToLinearGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/addT2IAdapterToLinearGraph.ts
index 84002337d7..a765a72a9f 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/addT2IAdapterToLinearGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/addT2IAdapterToLinearGraph.ts
@@ -9,7 +9,7 @@ import type {
   T2IAdapterInvocation,
 } from 'services/api/types';
 
-import { CANVAS_COHERENCE_DENOISE_LATENTS, T2I_ADAPTER_COLLECT } from './constants';
+import { T2I_ADAPTER_COLLECT } from './constants';
 import { upsertMetadata } from './metadata';
 
 export const addT2IAdaptersToLinearGraph = (state: RootState, graph: NonNullableGraph, baseNodeId: string): void => {
@@ -33,15 +33,6 @@ export const addT2IAdaptersToLinearGraph = (state: RootState, graph: NonNullable
       },
     });
 
-    if (CANVAS_COHERENCE_DENOISE_LATENTS in graph.nodes) {
-      graph.edges.push({
-        source: { node_id: T2I_ADAPTER_COLLECT, field: 'collection' },
-        destination: {
-          node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
-          field: 't2i_adapter',
-        },
-      });
-    }
     const t2iAdapterMetdata: CoreMetadataInvocation['t2iAdapters'] = [];
 
     validT2IAdapters.forEach((t2iAdapter) => {
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/addVAEToGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/addVAEToGraph.ts
index 95781d08e7..1cda6948a1 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/addVAEToGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/addVAEToGraph.ts
@@ -2,7 +2,6 @@ import type { RootState } from 'app/store/store';
 import type { NonNullableGraph } from 'services/api/types';
 
 import {
-  CANVAS_COHERENCE_INPAINT_CREATE_MASK,
   CANVAS_IMAGE_TO_IMAGE_GRAPH,
   CANVAS_INPAINT_GRAPH,
   CANVAS_OUTPAINT_GRAPH,
@@ -10,7 +9,6 @@ import {
   CANVAS_TEXT_TO_IMAGE_GRAPH,
   IMAGE_TO_IMAGE_GRAPH,
   IMAGE_TO_LATENTS,
-  INPAINT_CREATE_MASK,
   INPAINT_IMAGE,
   LATENTS_TO_IMAGE,
   MAIN_MODEL_LOADER,
@@ -32,7 +30,7 @@ export const addVAEToGraph = (
   graph: NonNullableGraph,
   modelLoaderNodeId: string = MAIN_MODEL_LOADER
 ): void => {
-  const { vae, canvasCoherenceMode, seamlessXAxis, seamlessYAxis } = state.generation;
+  const { vae, seamlessXAxis, seamlessYAxis } = state.generation;
   const { boundingBoxScaleMethod } = state.canvas;
   const { refinerModel } = state.sdxl;
 
@@ -121,16 +119,7 @@ export const addVAEToGraph = (
           field: 'vae',
         },
       },
-      {
-        source: {
-          node_id: isSeamlessEnabled ? SEAMLESS : isAutoVae ? modelLoaderNodeId : VAE_LOADER,
-          field: 'vae',
-        },
-        destination: {
-          node_id: INPAINT_CREATE_MASK,
-          field: 'vae',
-        },
-      },
+
       {
         source: {
           node_id: isSeamlessEnabled ? SEAMLESS : isAutoVae ? modelLoaderNodeId : VAE_LOADER,
@@ -142,20 +131,6 @@ export const addVAEToGraph = (
         },
       }
     );
-
-    // Handle Coherence Mode
-    if (canvasCoherenceMode !== 'unmasked') {
-      graph.edges.push({
-        source: {
-          node_id: isSeamlessEnabled ? SEAMLESS : isAutoVae ? modelLoaderNodeId : VAE_LOADER,
-          field: 'vae',
-        },
-        destination: {
-          node_id: CANVAS_COHERENCE_INPAINT_CREATE_MASK,
-          field: 'vae',
-        },
-      });
-    }
   }
 
   if (refinerModel) {
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasInpaintGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasInpaintGraph.ts
index d983b9cf4f..59bbca1e7b 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasInpaintGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasInpaintGraph.ts
@@ -1,15 +1,7 @@
 import { logger } from 'app/logging/logger';
 import type { RootState } from 'app/store/store';
 import { getBoardField, getIsIntermediate } from 'features/nodes/util/graph/graphBuilderUtils';
-import type {
-  CreateDenoiseMaskInvocation,
-  ImageBlurInvocation,
-  ImageDTO,
-  ImageToLatentsInvocation,
-  MaskEdgeInvocation,
-  NoiseInvocation,
-  NonNullableGraph,
-} from 'services/api/types';
+import type { ImageDTO, ImageToLatentsInvocation, NoiseInvocation, NonNullableGraph } from 'services/api/types';
 
 import { addControlNetToLinearGraph } from './addControlNetToLinearGraph';
 import { addIPAdapterToLinearGraph } from './addIPAdapterToLinearGraph';
@@ -20,11 +12,6 @@ import { addT2IAdaptersToLinearGraph } from './addT2IAdapterToLinearGraph';
 import { addVAEToGraph } from './addVAEToGraph';
 import { addWatermarkerToGraph } from './addWatermarkerToGraph';
 import {
-  CANVAS_COHERENCE_DENOISE_LATENTS,
-  CANVAS_COHERENCE_INPAINT_CREATE_MASK,
-  CANVAS_COHERENCE_MASK_EDGE,
-  CANVAS_COHERENCE_NOISE,
-  CANVAS_COHERENCE_NOISE_INCREMENT,
   CANVAS_INPAINT_GRAPH,
   CANVAS_OUTPUT,
   CLIP_SKIP,
@@ -35,7 +22,6 @@ import {
   INPAINT_IMAGE_RESIZE_UP,
   LATENTS_TO_IMAGE,
   MAIN_MODEL_LOADER,
-  MASK_BLUR,
   MASK_RESIZE_DOWN,
   MASK_RESIZE_UP,
   NEGATIVE_CONDITIONING,
@@ -65,14 +51,13 @@ export const buildCanvasInpaintGraph = (
     seed,
     vaePrecision,
     shouldUseCpuNoise,
-    maskBlur,
-    maskBlurMethod,
-    canvasCoherenceMode,
-    canvasCoherenceSteps,
-    canvasCoherenceStrength,
+
     clipSkip,
     seamlessXAxis,
     seamlessYAxis,
+    canvasCoherenceMode,
+    canvasCoherenceMinDenoise,
+    canvasCoherenceEdgeSize,
   } = state.generation;
 
   if (!model) {
@@ -121,13 +106,7 @@ export const buildCanvasInpaintGraph = (
         is_intermediate,
         prompt: negativePrompt,
       },
-      [MASK_BLUR]: {
-        type: 'img_blur',
-        id: MASK_BLUR,
-        is_intermediate,
-        radius: maskBlur,
-        blur_type: maskBlurMethod,
-      },
+
       [INPAINT_IMAGE]: {
         type: 'i2l',
         id: INPAINT_IMAGE,
@@ -142,10 +121,12 @@ export const buildCanvasInpaintGraph = (
         is_intermediate,
       },
       [INPAINT_CREATE_MASK]: {
-        type: 'create_denoise_mask',
+        type: 'create_gradient_mask',
         id: INPAINT_CREATE_MASK,
         is_intermediate,
-        fp32,
+        coherence_mode: canvasCoherenceMode,
+        minimum_denoise: canvasCoherenceMinDenoise,
+        edge_radius: canvasCoherenceEdgeSize,
       },
       [DENOISE_LATENTS]: {
         type: 'denoise_latents',
@@ -158,30 +139,6 @@ export const buildCanvasInpaintGraph = (
         denoising_start: 1 - strength,
         denoising_end: 1,
       },
-      [CANVAS_COHERENCE_NOISE]: {
-        type: 'noise',
-        id: CANVAS_COHERENCE_NOISE,
-        use_cpu,
-        seed: seed + 1,
-        is_intermediate,
-      },
-      [CANVAS_COHERENCE_NOISE_INCREMENT]: {
-        type: 'add',
-        id: CANVAS_COHERENCE_NOISE_INCREMENT,
-        b: 1,
-        is_intermediate,
-      },
-      [CANVAS_COHERENCE_DENOISE_LATENTS]: {
-        type: 'denoise_latents',
-        id: CANVAS_COHERENCE_DENOISE_LATENTS,
-        is_intermediate,
-        steps: canvasCoherenceSteps,
-        cfg_scale: cfg_scale,
-        cfg_rescale_multiplier,
-        scheduler: scheduler,
-        denoising_start: 1 - canvasCoherenceStrength,
-        denoising_end: 1,
-      },
       [LATENTS_TO_IMAGE]: {
         type: 'l2i',
         id: LATENTS_TO_IMAGE,
@@ -281,17 +238,6 @@ export const buildCanvasInpaintGraph = (
           field: 'latents',
         },
       },
-      // Create Inpaint Mask
-      {
-        source: {
-          node_id: MASK_BLUR,
-          field: 'image',
-        },
-        destination: {
-          node_id: INPAINT_CREATE_MASK,
-          field: 'mask',
-        },
-      },
       {
         source: {
           node_id: INPAINT_CREATE_MASK,
@@ -302,61 +248,10 @@ export const buildCanvasInpaintGraph = (
           field: 'denoise_mask',
         },
       },
-      // Canvas Refine
-      {
-        source: {
-          node_id: modelLoaderNodeId,
-          field: 'unet',
-        },
-        destination: {
-          node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
-          field: 'unet',
-        },
-      },
-      {
-        source: {
-          node_id: POSITIVE_CONDITIONING,
-          field: 'conditioning',
-        },
-        destination: {
-          node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
-          field: 'positive_conditioning',
-        },
-      },
-      {
-        source: {
-          node_id: NEGATIVE_CONDITIONING,
-          field: 'conditioning',
-        },
-        destination: {
-          node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
-          field: 'negative_conditioning',
-        },
-      },
-      {
-        source: {
-          node_id: CANVAS_COHERENCE_NOISE,
-          field: 'noise',
-        },
-        destination: {
-          node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
-          field: 'noise',
-        },
-      },
-      {
-        source: {
-          node_id: DENOISE_LATENTS,
-          field: 'latents',
-        },
-        destination: {
-          node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
-          field: 'latents',
-        },
-      },
       // Decode Inpainted Latents To Image
       {
         source: {
-          node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
+          node_id: DENOISE_LATENTS,
           field: 'latents',
         },
         destination: {
@@ -406,8 +301,6 @@ export const buildCanvasInpaintGraph = (
 
     (graph.nodes[NOISE] as NoiseInvocation).width = scaledWidth;
     (graph.nodes[NOISE] as NoiseInvocation).height = scaledHeight;
-    (graph.nodes[CANVAS_COHERENCE_NOISE] as NoiseInvocation).width = scaledWidth;
-    (graph.nodes[CANVAS_COHERENCE_NOISE] as NoiseInvocation).height = scaledHeight;
 
     // Connect Nodes
     graph.edges.push(
@@ -427,19 +320,9 @@ export const buildCanvasInpaintGraph = (
           node_id: MASK_RESIZE_UP,
           field: 'image',
         },
-        destination: {
-          node_id: MASK_BLUR,
-          field: 'image',
-        },
-      },
-      {
-        source: {
-          node_id: INPAINT_IMAGE_RESIZE_UP,
-          field: 'image',
-        },
         destination: {
           node_id: INPAINT_CREATE_MASK,
-          field: 'image',
+          field: 'mask',
         },
       },
       // Color Correct The Inpainted Result
@@ -465,7 +348,7 @@ export const buildCanvasInpaintGraph = (
       },
       {
         source: {
-          node_id: MASK_BLUR,
+          node_id: MASK_RESIZE_UP,
           field: 'image',
         },
         destination: {
@@ -488,21 +371,11 @@ export const buildCanvasInpaintGraph = (
     // Add Images To Nodes
     (graph.nodes[NOISE] as NoiseInvocation).width = width;
     (graph.nodes[NOISE] as NoiseInvocation).height = height;
-    (graph.nodes[CANVAS_COHERENCE_NOISE] as NoiseInvocation).width = width;
-    (graph.nodes[CANVAS_COHERENCE_NOISE] as NoiseInvocation).height = height;
 
     graph.nodes[INPAINT_IMAGE] = {
       ...(graph.nodes[INPAINT_IMAGE] as ImageToLatentsInvocation),
       image: canvasInitImage,
     };
-    graph.nodes[MASK_BLUR] = {
-      ...(graph.nodes[MASK_BLUR] as ImageBlurInvocation),
-      image: canvasMaskImage,
-    };
-    graph.nodes[INPAINT_CREATE_MASK] = {
-      ...(graph.nodes[INPAINT_CREATE_MASK] as CreateDenoiseMaskInvocation),
-      image: canvasInitImage,
-    };
 
     graph.edges.push(
       // Color Correct The Inpainted Result
@@ -518,7 +391,7 @@ export const buildCanvasInpaintGraph = (
       },
       {
         source: {
-          node_id: MASK_BLUR,
+          node_id: MASK_RESIZE_DOWN,
           field: 'image',
         },
         destination: {
@@ -529,112 +402,6 @@ export const buildCanvasInpaintGraph = (
     );
   }
 
-  // Handle Coherence Mode
-  if (canvasCoherenceMode !== 'unmasked') {
-    // Create Mask If Coherence Mode Is Not Full
-    graph.nodes[CANVAS_COHERENCE_INPAINT_CREATE_MASK] = {
-      type: 'create_denoise_mask',
-      id: CANVAS_COHERENCE_INPAINT_CREATE_MASK,
-      is_intermediate,
-      fp32,
-    };
-
-    // Handle Image Input For Mask Creation
-    if (isUsingScaledDimensions) {
-      graph.edges.push({
-        source: {
-          node_id: INPAINT_IMAGE_RESIZE_UP,
-          field: 'image',
-        },
-        destination: {
-          node_id: CANVAS_COHERENCE_INPAINT_CREATE_MASK,
-          field: 'image',
-        },
-      });
-    } else {
-      graph.nodes[CANVAS_COHERENCE_INPAINT_CREATE_MASK] = {
-        ...(graph.nodes[CANVAS_COHERENCE_INPAINT_CREATE_MASK] as CreateDenoiseMaskInvocation),
-        image: canvasInitImage,
-      };
-    }
-
-    // Create Mask If Coherence Mode Is Mask
-    if (canvasCoherenceMode === 'mask') {
-      if (isUsingScaledDimensions) {
-        graph.edges.push({
-          source: {
-            node_id: MASK_RESIZE_UP,
-            field: 'image',
-          },
-          destination: {
-            node_id: CANVAS_COHERENCE_INPAINT_CREATE_MASK,
-            field: 'mask',
-          },
-        });
-      } else {
-        graph.nodes[CANVAS_COHERENCE_INPAINT_CREATE_MASK] = {
-          ...(graph.nodes[CANVAS_COHERENCE_INPAINT_CREATE_MASK] as CreateDenoiseMaskInvocation),
-          mask: canvasMaskImage,
-        };
-      }
-    }
-
-    // Create Mask Edge If Coherence Mode Is Edge
-    if (canvasCoherenceMode === 'edge') {
-      graph.nodes[CANVAS_COHERENCE_MASK_EDGE] = {
-        type: 'mask_edge',
-        id: CANVAS_COHERENCE_MASK_EDGE,
-        is_intermediate,
-        edge_blur: maskBlur,
-        edge_size: maskBlur * 2,
-        low_threshold: 100,
-        high_threshold: 200,
-      };
-
-      // Handle Scaled Dimensions For Mask Edge
-      if (isUsingScaledDimensions) {
-        graph.edges.push({
-          source: {
-            node_id: MASK_RESIZE_UP,
-            field: 'image',
-          },
-          destination: {
-            node_id: CANVAS_COHERENCE_MASK_EDGE,
-            field: 'image',
-          },
-        });
-      } else {
-        graph.nodes[CANVAS_COHERENCE_MASK_EDGE] = {
-          ...(graph.nodes[CANVAS_COHERENCE_MASK_EDGE] as MaskEdgeInvocation),
-          image: canvasMaskImage,
-        };
-      }
-
-      graph.edges.push({
-        source: {
-          node_id: CANVAS_COHERENCE_MASK_EDGE,
-          field: 'image',
-        },
-        destination: {
-          node_id: CANVAS_COHERENCE_INPAINT_CREATE_MASK,
-          field: 'mask',
-        },
-      });
-    }
-
-    // Plug Denoise Mask To Coherence Denoise Latents
-    graph.edges.push({
-      source: {
-        node_id: CANVAS_COHERENCE_INPAINT_CREATE_MASK,
-        field: 'denoise_mask',
-      },
-      destination: {
-        node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
-        field: 'denoise_mask',
-      },
-    });
-  }
-
   // Add Seamless To Graph
   if (seamlessXAxis || seamlessYAxis) {
     addSeamlessToLinearGraph(state, graph, modelLoaderNodeId);
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasOutpaintGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasOutpaintGraph.ts
index 1d02894381..53840703f2 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasOutpaintGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasOutpaintGraph.ts
@@ -19,11 +19,6 @@ import { addT2IAdaptersToLinearGraph } from './addT2IAdapterToLinearGraph';
 import { addVAEToGraph } from './addVAEToGraph';
 import { addWatermarkerToGraph } from './addWatermarkerToGraph';
 import {
-  CANVAS_COHERENCE_DENOISE_LATENTS,
-  CANVAS_COHERENCE_INPAINT_CREATE_MASK,
-  CANVAS_COHERENCE_MASK_EDGE,
-  CANVAS_COHERENCE_NOISE,
-  CANVAS_COHERENCE_NOISE_INCREMENT,
   CANVAS_OUTPAINT_GRAPH,
   CANVAS_OUTPUT,
   CLIP_SKIP,
@@ -67,16 +62,15 @@ export const buildCanvasOutpaintGraph = (
     seed,
     vaePrecision,
     shouldUseCpuNoise,
-    maskBlur,
-    canvasCoherenceMode,
-    canvasCoherenceSteps,
-    canvasCoherenceStrength,
     infillTileSize,
     infillPatchmatchDownscaleSize,
     infillMethod,
     clipSkip,
     seamlessXAxis,
     seamlessYAxis,
+    canvasCoherenceMode,
+    canvasCoherenceMinDenoise,
+    canvasCoherenceEdgeSize,
   } = state.generation;
 
   if (!model) {
@@ -151,10 +145,12 @@ export const buildCanvasOutpaintGraph = (
         is_intermediate,
       },
       [INPAINT_CREATE_MASK]: {
-        type: 'create_denoise_mask',
+        type: 'create_gradient_mask',
         id: INPAINT_CREATE_MASK,
         is_intermediate,
-        fp32,
+        coherence_mode: canvasCoherenceMode,
+        minimum_denoise: canvasCoherenceMinDenoise,
+        edge_radius: canvasCoherenceEdgeSize,
       },
       [DENOISE_LATENTS]: {
         type: 'denoise_latents',
@@ -167,30 +163,7 @@ export const buildCanvasOutpaintGraph = (
         denoising_start: 1 - strength,
         denoising_end: 1,
       },
-      [CANVAS_COHERENCE_NOISE]: {
-        type: 'noise',
-        id: CANVAS_COHERENCE_NOISE,
-        use_cpu,
-        seed: seed + 1,
-        is_intermediate,
-      },
-      [CANVAS_COHERENCE_NOISE_INCREMENT]: {
-        type: 'add',
-        id: CANVAS_COHERENCE_NOISE_INCREMENT,
-        b: 1,
-        is_intermediate,
-      },
-      [CANVAS_COHERENCE_DENOISE_LATENTS]: {
-        type: 'denoise_latents',
-        id: CANVAS_COHERENCE_DENOISE_LATENTS,
-        is_intermediate,
-        steps: canvasCoherenceSteps,
-        cfg_scale: cfg_scale,
-        cfg_rescale_multiplier,
-        scheduler: scheduler,
-        denoising_start: 1 - canvasCoherenceStrength,
-        denoising_end: 1,
-      },
+
       [LATENTS_TO_IMAGE]: {
         type: 'l2i',
         id: LATENTS_TO_IMAGE,
@@ -332,73 +305,12 @@ export const buildCanvasOutpaintGraph = (
           field: 'denoise_mask',
         },
       },
-      // Canvas Refine
-      {
-        source: {
-          node_id: modelLoaderNodeId,
-          field: 'unet',
-        },
-        destination: {
-          node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
-          field: 'unet',
-        },
-      },
-      {
-        source: {
-          node_id: POSITIVE_CONDITIONING,
-          field: 'conditioning',
-        },
-        destination: {
-          node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
-          field: 'positive_conditioning',
-        },
-      },
-      {
-        source: {
-          node_id: NEGATIVE_CONDITIONING,
-          field: 'conditioning',
-        },
-        destination: {
-          node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
-          field: 'negative_conditioning',
-        },
-      },
-      {
-        source: {
-          node_id: CANVAS_COHERENCE_NOISE,
-          field: 'noise',
-        },
-        destination: {
-          node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
-          field: 'noise',
-        },
-      },
+
       {
         source: {
           node_id: DENOISE_LATENTS,
           field: 'latents',
         },
-        destination: {
-          node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
-          field: 'latents',
-        },
-      },
-      {
-        source: {
-          node_id: INPAINT_INFILL,
-          field: 'image',
-        },
-        destination: {
-          node_id: INPAINT_CREATE_MASK,
-          field: 'image',
-        },
-      },
-      // Decode the result from Inpaint
-      {
-        source: {
-          node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
-          field: 'latents',
-        },
         destination: {
           node_id: LATENTS_TO_IMAGE,
           field: 'latents',
@@ -487,8 +399,6 @@ export const buildCanvasOutpaintGraph = (
 
     (graph.nodes[NOISE] as NoiseInvocation).width = scaledWidth;
     (graph.nodes[NOISE] as NoiseInvocation).height = scaledHeight;
-    (graph.nodes[CANVAS_COHERENCE_NOISE] as NoiseInvocation).width = scaledWidth;
-    (graph.nodes[CANVAS_COHERENCE_NOISE] as NoiseInvocation).height = scaledHeight;
 
     // Connect Nodes
     graph.edges.push(
@@ -503,7 +413,7 @@ export const buildCanvasOutpaintGraph = (
           field: 'image',
         },
       },
-      // Take combined mask and resize and then blur
+      // Take combined mask and resize
       {
         source: {
           node_id: MASK_COMBINE,
@@ -514,7 +424,6 @@ export const buildCanvasOutpaintGraph = (
           field: 'image',
         },
       },
-
       // Resize Results Down
       {
         source: {
@@ -587,8 +496,6 @@ export const buildCanvasOutpaintGraph = (
 
     (graph.nodes[NOISE] as NoiseInvocation).width = width;
     (graph.nodes[NOISE] as NoiseInvocation).height = height;
-    (graph.nodes[CANVAS_COHERENCE_NOISE] as NoiseInvocation).width = width;
-    (graph.nodes[CANVAS_COHERENCE_NOISE] as NoiseInvocation).height = height;
 
     graph.nodes[INPAINT_IMAGE] = {
       ...(graph.nodes[INPAINT_IMAGE] as ImageToLatentsInvocation),
@@ -630,115 +537,6 @@ export const buildCanvasOutpaintGraph = (
     );
   }
 
-  // Handle Coherence Mode
-  if (canvasCoherenceMode !== 'unmasked') {
-    graph.nodes[CANVAS_COHERENCE_INPAINT_CREATE_MASK] = {
-      type: 'create_denoise_mask',
-      id: CANVAS_COHERENCE_INPAINT_CREATE_MASK,
-      is_intermediate,
-      fp32,
-    };
-
-    // Handle Image Input For Mask Creation
-    graph.edges.push({
-      source: {
-        node_id: INPAINT_INFILL,
-        field: 'image',
-      },
-      destination: {
-        node_id: CANVAS_COHERENCE_INPAINT_CREATE_MASK,
-        field: 'image',
-      },
-    });
-
-    // Create Mask If Coherence Mode Is Mask
-    if (canvasCoherenceMode === 'mask') {
-      if (isUsingScaledDimensions) {
-        graph.edges.push({
-          source: {
-            node_id: MASK_RESIZE_UP,
-            field: 'image',
-          },
-          destination: {
-            node_id: CANVAS_COHERENCE_INPAINT_CREATE_MASK,
-            field: 'mask',
-          },
-        });
-      } else {
-        graph.edges.push({
-          source: {
-            node_id: MASK_COMBINE,
-            field: 'image',
-          },
-          destination: {
-            node_id: CANVAS_COHERENCE_INPAINT_CREATE_MASK,
-            field: 'mask',
-          },
-        });
-      }
-    }
-
-    if (canvasCoherenceMode === 'edge') {
-      graph.nodes[CANVAS_COHERENCE_MASK_EDGE] = {
-        type: 'mask_edge',
-        id: CANVAS_COHERENCE_MASK_EDGE,
-        is_intermediate,
-        edge_blur: maskBlur,
-        edge_size: maskBlur * 2,
-        low_threshold: 100,
-        high_threshold: 200,
-      };
-
-      // Handle Scaled Dimensions For Mask Edge
-      if (isUsingScaledDimensions) {
-        graph.edges.push({
-          source: {
-            node_id: MASK_RESIZE_UP,
-            field: 'image',
-          },
-          destination: {
-            node_id: CANVAS_COHERENCE_MASK_EDGE,
-            field: 'image',
-          },
-        });
-      } else {
-        graph.edges.push({
-          source: {
-            node_id: MASK_COMBINE,
-            field: 'image',
-          },
-          destination: {
-            node_id: CANVAS_COHERENCE_MASK_EDGE,
-            field: 'image',
-          },
-        });
-      }
-
-      graph.edges.push({
-        source: {
-          node_id: CANVAS_COHERENCE_MASK_EDGE,
-          field: 'image',
-        },
-        destination: {
-          node_id: CANVAS_COHERENCE_INPAINT_CREATE_MASK,
-          field: 'mask',
-        },
-      });
-    }
-
-    // Plug Denoise Mask To Coherence Denoise Latents
-    graph.edges.push({
-      source: {
-        node_id: CANVAS_COHERENCE_INPAINT_CREATE_MASK,
-        field: 'denoise_mask',
-      },
-      destination: {
-        node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
-        field: 'denoise_mask',
-      },
-    });
-  }
-
   // Add Seamless To Graph
   if (seamlessXAxis || seamlessYAxis) {
     addSeamlessToLinearGraph(state, graph, modelLoaderNodeId);
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLInpaintGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLInpaintGraph.ts
index 5902dee2fc..56fb6147ce 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLInpaintGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLInpaintGraph.ts
@@ -2,10 +2,8 @@ import { logger } from 'app/logging/logger';
 import type { RootState } from 'app/store/store';
 import type {
   CreateDenoiseMaskInvocation,
-  ImageBlurInvocation,
   ImageDTO,
   ImageToLatentsInvocation,
-  MaskEdgeInvocation,
   NoiseInvocation,
   NonNullableGraph,
 } from 'services/api/types';
@@ -20,18 +18,12 @@ import { addT2IAdaptersToLinearGraph } from './addT2IAdapterToLinearGraph';
 import { addVAEToGraph } from './addVAEToGraph';
 import { addWatermarkerToGraph } from './addWatermarkerToGraph';
 import {
-  CANVAS_COHERENCE_DENOISE_LATENTS,
-  CANVAS_COHERENCE_INPAINT_CREATE_MASK,
-  CANVAS_COHERENCE_MASK_EDGE,
-  CANVAS_COHERENCE_NOISE,
-  CANVAS_COHERENCE_NOISE_INCREMENT,
   CANVAS_OUTPUT,
   INPAINT_CREATE_MASK,
   INPAINT_IMAGE,
   INPAINT_IMAGE_RESIZE_DOWN,
   INPAINT_IMAGE_RESIZE_UP,
   LATENTS_TO_IMAGE,
-  MASK_BLUR,
   MASK_RESIZE_DOWN,
   MASK_RESIZE_UP,
   NEGATIVE_CONDITIONING,
@@ -65,11 +57,9 @@ export const buildCanvasSDXLInpaintGraph = (
     seed,
     vaePrecision,
     shouldUseCpuNoise,
-    maskBlur,
-    maskBlurMethod,
     canvasCoherenceMode,
-    canvasCoherenceSteps,
-    canvasCoherenceStrength,
+    canvasCoherenceMinDenoise,
+    canvasCoherenceEdgeSize,
     seamlessXAxis,
     seamlessYAxis,
     img2imgStrength: strength,
@@ -119,13 +109,6 @@ export const buildCanvasSDXLInpaintGraph = (
         prompt: negativePrompt,
         style: negativeStylePrompt,
       },
-      [MASK_BLUR]: {
-        type: 'img_blur',
-        id: MASK_BLUR,
-        is_intermediate,
-        radius: maskBlur,
-        blur_type: maskBlurMethod,
-      },
       [INPAINT_IMAGE]: {
         type: 'i2l',
         id: INPAINT_IMAGE,
@@ -140,10 +123,12 @@ export const buildCanvasSDXLInpaintGraph = (
         is_intermediate,
       },
       [INPAINT_CREATE_MASK]: {
-        type: 'create_denoise_mask',
+        type: 'create_gradient_mask',
         id: INPAINT_CREATE_MASK,
         is_intermediate,
-        fp32,
+        coherence_mode: canvasCoherenceMode,
+        minimum_denoise: canvasCoherenceMinDenoise,
+        edge_radius: canvasCoherenceEdgeSize,
       },
       [SDXL_DENOISE_LATENTS]: {
         type: 'denoise_latents',
@@ -156,30 +141,6 @@ export const buildCanvasSDXLInpaintGraph = (
         denoising_start: refinerModel ? Math.min(refinerStart, 1 - strength) : 1 - strength,
         denoising_end: refinerModel ? refinerStart : 1,
       },
-      [CANVAS_COHERENCE_NOISE]: {
-        type: 'noise',
-        id: CANVAS_COHERENCE_NOISE,
-        use_cpu,
-        seed: seed + 1,
-        is_intermediate,
-      },
-      [CANVAS_COHERENCE_NOISE_INCREMENT]: {
-        type: 'add',
-        id: CANVAS_COHERENCE_NOISE_INCREMENT,
-        b: 1,
-        is_intermediate,
-      },
-      [CANVAS_COHERENCE_DENOISE_LATENTS]: {
-        type: 'denoise_latents',
-        id: CANVAS_COHERENCE_DENOISE_LATENTS,
-        is_intermediate,
-        steps: canvasCoherenceSteps,
-        cfg_scale: cfg_scale,
-        cfg_rescale_multiplier,
-        scheduler: scheduler,
-        denoising_start: 1 - canvasCoherenceStrength,
-        denoising_end: 1,
-      },
       [LATENTS_TO_IMAGE]: {
         type: 'l2i',
         id: LATENTS_TO_IMAGE,
@@ -288,17 +249,6 @@ export const buildCanvasSDXLInpaintGraph = (
           field: 'latents',
         },
       },
-      // Create Inpaint Mask
-      {
-        source: {
-          node_id: MASK_BLUR,
-          field: 'image',
-        },
-        destination: {
-          node_id: INPAINT_CREATE_MASK,
-          field: 'mask',
-        },
-      },
       {
         source: {
           node_id: INPAINT_CREATE_MASK,
@@ -309,61 +259,10 @@ export const buildCanvasSDXLInpaintGraph = (
           field: 'denoise_mask',
         },
       },
-      // Canvas Refine
-      {
-        source: {
-          node_id: modelLoaderNodeId,
-          field: 'unet',
-        },
-        destination: {
-          node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
-          field: 'unet',
-        },
-      },
-      {
-        source: {
-          node_id: POSITIVE_CONDITIONING,
-          field: 'conditioning',
-        },
-        destination: {
-          node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
-          field: 'positive_conditioning',
-        },
-      },
-      {
-        source: {
-          node_id: NEGATIVE_CONDITIONING,
-          field: 'conditioning',
-        },
-        destination: {
-          node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
-          field: 'negative_conditioning',
-        },
-      },
-      {
-        source: {
-          node_id: CANVAS_COHERENCE_NOISE,
-          field: 'noise',
-        },
-        destination: {
-          node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
-          field: 'noise',
-        },
-      },
-      {
-        source: {
-          node_id: SDXL_DENOISE_LATENTS,
-          field: 'latents',
-        },
-        destination: {
-          node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
-          field: 'latents',
-        },
-      },
       // Decode Inpainted Latents To Image
       {
         source: {
-          node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
+          node_id: SDXL_DENOISE_LATENTS,
           field: 'latents',
         },
         destination: {
@@ -413,8 +312,6 @@ export const buildCanvasSDXLInpaintGraph = (
 
     (graph.nodes[NOISE] as NoiseInvocation).width = scaledWidth;
     (graph.nodes[NOISE] as NoiseInvocation).height = scaledHeight;
-    (graph.nodes[CANVAS_COHERENCE_NOISE] as NoiseInvocation).width = scaledWidth;
-    (graph.nodes[CANVAS_COHERENCE_NOISE] as NoiseInvocation).height = scaledHeight;
 
     // Connect Nodes
     graph.edges.push(
@@ -434,19 +331,9 @@ export const buildCanvasSDXLInpaintGraph = (
           node_id: MASK_RESIZE_UP,
           field: 'image',
         },
-        destination: {
-          node_id: MASK_BLUR,
-          field: 'image',
-        },
-      },
-      {
-        source: {
-          node_id: INPAINT_IMAGE_RESIZE_UP,
-          field: 'image',
-        },
         destination: {
           node_id: INPAINT_CREATE_MASK,
-          field: 'image',
+          field: 'mask',
         },
       },
       // Color Correct The Inpainted Result
@@ -472,7 +359,7 @@ export const buildCanvasSDXLInpaintGraph = (
       },
       {
         source: {
-          node_id: MASK_BLUR,
+          node_id: MASK_RESIZE_UP,
           field: 'image',
         },
         destination: {
@@ -495,17 +382,11 @@ export const buildCanvasSDXLInpaintGraph = (
     // Add Images To Nodes
     (graph.nodes[NOISE] as NoiseInvocation).width = width;
     (graph.nodes[NOISE] as NoiseInvocation).height = height;
-    (graph.nodes[CANVAS_COHERENCE_NOISE] as NoiseInvocation).width = width;
-    (graph.nodes[CANVAS_COHERENCE_NOISE] as NoiseInvocation).height = height;
 
     graph.nodes[INPAINT_IMAGE] = {
       ...(graph.nodes[INPAINT_IMAGE] as ImageToLatentsInvocation),
       image: canvasInitImage,
     };
-    graph.nodes[MASK_BLUR] = {
-      ...(graph.nodes[MASK_BLUR] as ImageBlurInvocation),
-      image: canvasMaskImage,
-    };
     graph.nodes[INPAINT_CREATE_MASK] = {
       ...(graph.nodes[INPAINT_CREATE_MASK] as CreateDenoiseMaskInvocation),
       image: canvasInitImage,
@@ -525,7 +406,7 @@ export const buildCanvasSDXLInpaintGraph = (
       },
       {
         source: {
-          node_id: MASK_BLUR,
+          node_id: MASK_RESIZE_DOWN,
           field: 'image',
         },
         destination: {
@@ -536,112 +417,6 @@ export const buildCanvasSDXLInpaintGraph = (
     );
   }
 
-  // Handle Coherence Mode
-  if (canvasCoherenceMode !== 'unmasked') {
-    // Create Mask If Coherence Mode Is Not Full
-    graph.nodes[CANVAS_COHERENCE_INPAINT_CREATE_MASK] = {
-      type: 'create_denoise_mask',
-      id: CANVAS_COHERENCE_INPAINT_CREATE_MASK,
-      is_intermediate,
-      fp32,
-    };
-
-    // Handle Image Input For Mask Creation
-    if (isUsingScaledDimensions) {
-      graph.edges.push({
-        source: {
-          node_id: INPAINT_IMAGE_RESIZE_UP,
-          field: 'image',
-        },
-        destination: {
-          node_id: CANVAS_COHERENCE_INPAINT_CREATE_MASK,
-          field: 'image',
-        },
-      });
-    } else {
-      graph.nodes[CANVAS_COHERENCE_INPAINT_CREATE_MASK] = {
-        ...(graph.nodes[CANVAS_COHERENCE_INPAINT_CREATE_MASK] as CreateDenoiseMaskInvocation),
-        image: canvasInitImage,
-      };
-    }
-
-    // Create Mask If Coherence Mode Is Mask
-    if (canvasCoherenceMode === 'mask') {
-      if (isUsingScaledDimensions) {
-        graph.edges.push({
-          source: {
-            node_id: MASK_RESIZE_UP,
-            field: 'image',
-          },
-          destination: {
-            node_id: CANVAS_COHERENCE_INPAINT_CREATE_MASK,
-            field: 'mask',
-          },
-        });
-      } else {
-        graph.nodes[CANVAS_COHERENCE_INPAINT_CREATE_MASK] = {
-          ...(graph.nodes[CANVAS_COHERENCE_INPAINT_CREATE_MASK] as CreateDenoiseMaskInvocation),
-          mask: canvasMaskImage,
-        };
-      }
-    }
-
-    // Create Mask Edge If Coherence Mode Is Edge
-    if (canvasCoherenceMode === 'edge') {
-      graph.nodes[CANVAS_COHERENCE_MASK_EDGE] = {
-        type: 'mask_edge',
-        id: CANVAS_COHERENCE_MASK_EDGE,
-        is_intermediate,
-        edge_blur: maskBlur,
-        edge_size: maskBlur * 2,
-        low_threshold: 100,
-        high_threshold: 200,
-      };
-
-      // Handle Scaled Dimensions For Mask Edge
-      if (isUsingScaledDimensions) {
-        graph.edges.push({
-          source: {
-            node_id: MASK_RESIZE_UP,
-            field: 'image',
-          },
-          destination: {
-            node_id: CANVAS_COHERENCE_MASK_EDGE,
-            field: 'image',
-          },
-        });
-      } else {
-        graph.nodes[CANVAS_COHERENCE_MASK_EDGE] = {
-          ...(graph.nodes[CANVAS_COHERENCE_MASK_EDGE] as MaskEdgeInvocation),
-          image: canvasMaskImage,
-        };
-      }
-
-      graph.edges.push({
-        source: {
-          node_id: CANVAS_COHERENCE_MASK_EDGE,
-          field: 'image',
-        },
-        destination: {
-          node_id: CANVAS_COHERENCE_INPAINT_CREATE_MASK,
-          field: 'mask',
-        },
-      });
-    }
-
-    // Plug Denoise Mask To Coherence Denoise Latents
-    graph.edges.push({
-      source: {
-        node_id: CANVAS_COHERENCE_INPAINT_CREATE_MASK,
-        field: 'denoise_mask',
-      },
-      destination: {
-        node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
-        field: 'denoise_mask',
-      },
-    });
-  }
-
   // Add Seamless To Graph
   if (seamlessXAxis || seamlessYAxis) {
     addSeamlessToLinearGraph(state, graph, modelLoaderNodeId);
@@ -650,14 +425,7 @@ export const buildCanvasSDXLInpaintGraph = (
 
   // Add Refiner if enabled
   if (refinerModel) {
-    addSDXLRefinerToGraph(
-      state,
-      graph,
-      CANVAS_COHERENCE_DENOISE_LATENTS,
-      modelLoaderNodeId,
-      canvasInitImage,
-      canvasMaskImage
-    );
+    addSDXLRefinerToGraph(state, graph, SDXL_DENOISE_LATENTS, modelLoaderNodeId, canvasInitImage, canvasMaskImage);
     if (seamlessXAxis || seamlessYAxis) {
       modelLoaderNodeId = SDXL_REFINER_SEAMLESS;
     }
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLOutpaintGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLOutpaintGraph.ts
index 7a78750e8d..f448b2be72 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLOutpaintGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLOutpaintGraph.ts
@@ -19,11 +19,6 @@ import { addT2IAdaptersToLinearGraph } from './addT2IAdapterToLinearGraph';
 import { addVAEToGraph } from './addVAEToGraph';
 import { addWatermarkerToGraph } from './addWatermarkerToGraph';
 import {
-  CANVAS_COHERENCE_DENOISE_LATENTS,
-  CANVAS_COHERENCE_INPAINT_CREATE_MASK,
-  CANVAS_COHERENCE_MASK_EDGE,
-  CANVAS_COHERENCE_NOISE,
-  CANVAS_COHERENCE_NOISE_INCREMENT,
   CANVAS_OUTPUT,
   INPAINT_CREATE_MASK,
   INPAINT_IMAGE,
@@ -67,10 +62,9 @@ export const buildCanvasSDXLOutpaintGraph = (
     seed,
     vaePrecision,
     shouldUseCpuNoise,
-    maskBlur,
     canvasCoherenceMode,
-    canvasCoherenceSteps,
-    canvasCoherenceStrength,
+    canvasCoherenceMinDenoise,
+    canvasCoherenceEdgeSize,
     infillTileSize,
     infillPatchmatchDownscaleSize,
     infillMethod,
@@ -149,10 +143,12 @@ export const buildCanvasSDXLOutpaintGraph = (
         is_intermediate,
       },
       [INPAINT_CREATE_MASK]: {
-        type: 'create_denoise_mask',
+        type: 'create_gradient_mask',
         id: INPAINT_CREATE_MASK,
         is_intermediate,
-        fp32,
+        coherence_mode: canvasCoherenceMode,
+        edge_radius: canvasCoherenceEdgeSize,
+        minimum_denoise: canvasCoherenceMinDenoise,
       },
       [SDXL_DENOISE_LATENTS]: {
         type: 'denoise_latents',
@@ -165,30 +161,6 @@ export const buildCanvasSDXLOutpaintGraph = (
         denoising_start: refinerModel ? Math.min(refinerStart, 1 - strength) : 1 - strength,
         denoising_end: refinerModel ? refinerStart : 1,
       },
-      [CANVAS_COHERENCE_NOISE]: {
-        type: 'noise',
-        id: CANVAS_COHERENCE_NOISE,
-        use_cpu,
-        seed: seed + 1,
-        is_intermediate,
-      },
-      [CANVAS_COHERENCE_NOISE_INCREMENT]: {
-        type: 'add',
-        id: CANVAS_COHERENCE_NOISE_INCREMENT,
-        b: 1,
-        is_intermediate,
-      },
-      [CANVAS_COHERENCE_DENOISE_LATENTS]: {
-        type: 'denoise_latents',
-        id: CANVAS_COHERENCE_DENOISE_LATENTS,
-        is_intermediate,
-        steps: canvasCoherenceSteps,
-        cfg_scale: cfg_scale,
-        cfg_rescale_multiplier,
-        scheduler: scheduler,
-        denoising_start: 1 - canvasCoherenceStrength,
-        denoising_end: 1,
-      },
       [LATENTS_TO_IMAGE]: {
         type: 'l2i',
         id: LATENTS_TO_IMAGE,
@@ -339,71 +311,10 @@ export const buildCanvasSDXLOutpaintGraph = (
           field: 'denoise_mask',
         },
       },
-      // Canvas Refine
-      {
-        source: {
-          node_id: modelLoaderNodeId,
-          field: 'unet',
-        },
-        destination: {
-          node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
-          field: 'unet',
-        },
-      },
-      {
-        source: {
-          node_id: POSITIVE_CONDITIONING,
-          field: 'conditioning',
-        },
-        destination: {
-          node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
-          field: 'positive_conditioning',
-        },
-      },
-      {
-        source: {
-          node_id: NEGATIVE_CONDITIONING,
-          field: 'conditioning',
-        },
-        destination: {
-          node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
-          field: 'negative_conditioning',
-        },
-      },
-      {
-        source: {
-          node_id: CANVAS_COHERENCE_NOISE,
-          field: 'noise',
-        },
-        destination: {
-          node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
-          field: 'noise',
-        },
-      },
-      {
-        source: {
-          node_id: SDXL_DENOISE_LATENTS,
-          field: 'latents',
-        },
-        destination: {
-          node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
-          field: 'latents',
-        },
-      },
-      {
-        source: {
-          node_id: INPAINT_INFILL,
-          field: 'image',
-        },
-        destination: {
-          node_id: INPAINT_CREATE_MASK,
-          field: 'image',
-        },
-      },
       // Decode inpainted latents to image
       {
         source: {
-          node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
+          node_id: SDXL_DENOISE_LATENTS,
           field: 'latents',
         },
         destination: {
@@ -494,8 +405,6 @@ export const buildCanvasSDXLOutpaintGraph = (
 
     (graph.nodes[NOISE] as NoiseInvocation).width = scaledWidth;
     (graph.nodes[NOISE] as NoiseInvocation).height = scaledHeight;
-    (graph.nodes[CANVAS_COHERENCE_NOISE] as NoiseInvocation).width = scaledWidth;
-    (graph.nodes[CANVAS_COHERENCE_NOISE] as NoiseInvocation).height = scaledHeight;
 
     // Connect Nodes
     graph.edges.push(
@@ -595,8 +504,6 @@ export const buildCanvasSDXLOutpaintGraph = (
 
     (graph.nodes[NOISE] as NoiseInvocation).width = width;
     (graph.nodes[NOISE] as NoiseInvocation).height = height;
-    (graph.nodes[CANVAS_COHERENCE_NOISE] as NoiseInvocation).width = width;
-    (graph.nodes[CANVAS_COHERENCE_NOISE] as NoiseInvocation).height = height;
 
     graph.nodes[INPAINT_IMAGE] = {
       ...(graph.nodes[INPAINT_IMAGE] as ImageToLatentsInvocation),
@@ -638,115 +545,6 @@ export const buildCanvasSDXLOutpaintGraph = (
     );
   }
 
-  // Handle Coherence Mode
-  if (canvasCoherenceMode !== 'unmasked') {
-    graph.nodes[CANVAS_COHERENCE_INPAINT_CREATE_MASK] = {
-      type: 'create_denoise_mask',
-      id: CANVAS_COHERENCE_INPAINT_CREATE_MASK,
-      is_intermediate,
-      fp32,
-    };
-
-    // Handle Image Input For Mask Creation
-    graph.edges.push({
-      source: {
-        node_id: INPAINT_INFILL,
-        field: 'image',
-      },
-      destination: {
-        node_id: CANVAS_COHERENCE_INPAINT_CREATE_MASK,
-        field: 'image',
-      },
-    });
-
-    // Create Mask If Coherence Mode Is Mask
-    if (canvasCoherenceMode === 'mask') {
-      if (isUsingScaledDimensions) {
-        graph.edges.push({
-          source: {
-            node_id: MASK_RESIZE_UP,
-            field: 'image',
-          },
-          destination: {
-            node_id: CANVAS_COHERENCE_INPAINT_CREATE_MASK,
-            field: 'mask',
-          },
-        });
-      } else {
-        graph.edges.push({
-          source: {
-            node_id: MASK_COMBINE,
-            field: 'image',
-          },
-          destination: {
-            node_id: CANVAS_COHERENCE_INPAINT_CREATE_MASK,
-            field: 'mask',
-          },
-        });
-      }
-    }
-
-    if (canvasCoherenceMode === 'edge') {
-      graph.nodes[CANVAS_COHERENCE_MASK_EDGE] = {
-        type: 'mask_edge',
-        id: CANVAS_COHERENCE_MASK_EDGE,
-        is_intermediate,
-        edge_blur: maskBlur,
-        edge_size: maskBlur * 2,
-        low_threshold: 100,
-        high_threshold: 200,
-      };
-
-      // Handle Scaled Dimensions For Mask Edge
-      if (isUsingScaledDimensions) {
-        graph.edges.push({
-          source: {
-            node_id: MASK_RESIZE_UP,
-            field: 'image',
-          },
-          destination: {
-            node_id: CANVAS_COHERENCE_MASK_EDGE,
-            field: 'image',
-          },
-        });
-      } else {
-        graph.edges.push({
-          source: {
-            node_id: MASK_COMBINE,
-            field: 'image',
-          },
-          destination: {
-            node_id: CANVAS_COHERENCE_MASK_EDGE,
-            field: 'image',
-          },
-        });
-      }
-
-      graph.edges.push({
-        source: {
-          node_id: CANVAS_COHERENCE_MASK_EDGE,
-          field: 'image',
-        },
-        destination: {
-          node_id: CANVAS_COHERENCE_INPAINT_CREATE_MASK,
-          field: 'mask',
-        },
-      });
-    }
-
-    // Plug Denoise Mask To Coherence Denoise Latents
-    graph.edges.push({
-      source: {
-        node_id: CANVAS_COHERENCE_INPAINT_CREATE_MASK,
-        field: 'denoise_mask',
-      },
-      destination: {
-        node_id: CANVAS_COHERENCE_DENOISE_LATENTS,
-        field: 'denoise_mask',
-      },
-    });
-  }
-
   // Add Seamless To Graph
   if (seamlessXAxis || seamlessYAxis) {
     addSeamlessToLinearGraph(state, graph, modelLoaderNodeId);
@@ -755,7 +553,7 @@ export const buildCanvasSDXLOutpaintGraph = (
 
   // Add Refiner if enabled
   if (refinerModel) {
-    addSDXLRefinerToGraph(state, graph, CANVAS_COHERENCE_DENOISE_LATENTS, modelLoaderNodeId, canvasInitImage);
+    addSDXLRefinerToGraph(state, graph, SDXL_DENOISE_LATENTS, modelLoaderNodeId, canvasInitImage);
     if (seamlessXAxis || seamlessYAxis) {
       modelLoaderNodeId = SDXL_REFINER_SEAMLESS;
     }
diff --git a/invokeai/frontend/web/src/features/parameters/components/Canvas/Compositing/CoherencePass/ParamCanvasCoherenceSteps.tsx b/invokeai/frontend/web/src/features/parameters/components/Canvas/Compositing/CoherencePass/ParamCanvasCoherenceEdgeSize.tsx
similarity index 66%
rename from invokeai/frontend/web/src/features/parameters/components/Canvas/Compositing/CoherencePass/ParamCanvasCoherenceSteps.tsx
rename to invokeai/frontend/web/src/features/parameters/components/Canvas/Compositing/CoherencePass/ParamCanvasCoherenceEdgeSize.tsx
index d427f3c22e..c39ad2916e 100644
--- a/invokeai/frontend/web/src/features/parameters/components/Canvas/Compositing/CoherencePass/ParamCanvasCoherenceSteps.tsx
+++ b/invokeai/frontend/web/src/features/parameters/components/Canvas/Compositing/CoherencePass/ParamCanvasCoherenceEdgeSize.tsx
@@ -1,41 +1,41 @@
 import { CompositeNumberInput, CompositeSlider, FormControl, FormLabel } from '@invoke-ai/ui-library';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
-import { setCanvasCoherenceSteps } from 'features/parameters/store/generationSlice';
+import { setCanvasCoherenceEdgeSize } from 'features/parameters/store/generationSlice';
 import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 
-const ParamCanvasCoherenceSteps = () => {
+const ParamCanvasCoherenceEdgeSize = () => {
   const dispatch = useAppDispatch();
-  const canvasCoherenceSteps = useAppSelector((s) => s.generation.canvasCoherenceSteps);
-  const initial = useAppSelector((s) => s.config.sd.canvasCoherenceSteps.initial);
-  const sliderMin = useAppSelector((s) => s.config.sd.canvasCoherenceSteps.sliderMin);
-  const sliderMax = useAppSelector((s) => s.config.sd.canvasCoherenceSteps.sliderMax);
-  const numberInputMin = useAppSelector((s) => s.config.sd.canvasCoherenceSteps.numberInputMin);
-  const numberInputMax = useAppSelector((s) => s.config.sd.canvasCoherenceSteps.numberInputMax);
-  const coarseStep = useAppSelector((s) => s.config.sd.canvasCoherenceSteps.coarseStep);
-  const fineStep = useAppSelector((s) => s.config.sd.canvasCoherenceSteps.fineStep);
+  const canvasCoherenceEdgeSize = useAppSelector((s) => s.generation.canvasCoherenceEdgeSize);
+  const initial = useAppSelector((s) => s.config.sd.canvasCoherenceEdgeSize.initial);
+  const sliderMin = useAppSelector((s) => s.config.sd.canvasCoherenceEdgeSize.sliderMin);
+  const sliderMax = useAppSelector((s) => s.config.sd.canvasCoherenceEdgeSize.sliderMax);
+  const numberInputMin = useAppSelector((s) => s.config.sd.canvasCoherenceEdgeSize.numberInputMin);
+  const numberInputMax = useAppSelector((s) => s.config.sd.canvasCoherenceEdgeSize.numberInputMax);
+  const coarseStep = useAppSelector((s) => s.config.sd.canvasCoherenceEdgeSize.coarseStep);
+  const fineStep = useAppSelector((s) => s.config.sd.canvasCoherenceEdgeSize.fineStep);
 
   const { t } = useTranslation();
 
   const handleChange = useCallback(
     (v: number) => {
-      dispatch(setCanvasCoherenceSteps(v));
+      dispatch(setCanvasCoherenceEdgeSize(v));
     },
     [dispatch]
   );
 
   return (
     <FormControl>
-      <InformationalPopover feature="compositingCoherenceSteps">
-        <FormLabel>{t('parameters.coherenceSteps')}</FormLabel>
+      <InformationalPopover feature="compositingCoherenceEdgeSize">
+        <FormLabel>{t('parameters.coherenceEdgeSize')}</FormLabel>
       </InformationalPopover>
       <CompositeSlider
         min={sliderMin}
         max={sliderMax}
         step={coarseStep}
         fineStep={fineStep}
-        value={canvasCoherenceSteps}
+        value={canvasCoherenceEdgeSize}
         defaultValue={initial}
         onChange={handleChange}
         marks
@@ -45,7 +45,7 @@ const ParamCanvasCoherenceSteps = () => {
         max={numberInputMax}
         step={coarseStep}
         fineStep={fineStep}
-        value={canvasCoherenceSteps}
+        value={canvasCoherenceEdgeSize}
         defaultValue={initial}
         onChange={handleChange}
       />
@@ -53,4 +53,4 @@ const ParamCanvasCoherenceSteps = () => {
   );
 };
 
-export default memo(ParamCanvasCoherenceSteps);
+export default memo(ParamCanvasCoherenceEdgeSize);
diff --git a/invokeai/frontend/web/src/features/parameters/components/Canvas/Compositing/CoherencePass/ParamCanvasCoherenceStrength.tsx b/invokeai/frontend/web/src/features/parameters/components/Canvas/Compositing/CoherencePass/ParamCanvasCoherenceMinDenoise.tsx
similarity index 58%
rename from invokeai/frontend/web/src/features/parameters/components/Canvas/Compositing/CoherencePass/ParamCanvasCoherenceStrength.tsx
rename to invokeai/frontend/web/src/features/parameters/components/Canvas/Compositing/CoherencePass/ParamCanvasCoherenceMinDenoise.tsx
index d4f6b4444c..00cdb5070b 100644
--- a/invokeai/frontend/web/src/features/parameters/components/Canvas/Compositing/CoherencePass/ParamCanvasCoherenceStrength.tsx
+++ b/invokeai/frontend/web/src/features/parameters/components/Canvas/Compositing/CoherencePass/ParamCanvasCoherenceMinDenoise.tsx
@@ -1,45 +1,45 @@
 import { CompositeNumberInput, CompositeSlider, FormControl, FormLabel } from '@invoke-ai/ui-library';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
-import { setCanvasCoherenceStrength } from 'features/parameters/store/generationSlice';
+import { setCanvasCoherenceMinDenoise } from 'features/parameters/store/generationSlice';
 import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 
-const ParamCanvasCoherenceStrength = () => {
+const ParamCanvasCoherenceMinDenoise = () => {
   const dispatch = useAppDispatch();
-  const canvasCoherenceStrength = useAppSelector((s) => s.generation.canvasCoherenceStrength);
+  const canvasCoherenceMinDenoise = useAppSelector((s) => s.generation.canvasCoherenceMinDenoise);
   const { t } = useTranslation();
 
   const handleChange = useCallback(
     (v: number) => {
-      dispatch(setCanvasCoherenceStrength(v));
+      dispatch(setCanvasCoherenceMinDenoise(v));
     },
     [dispatch]
   );
 
   return (
     <FormControl>
-      <InformationalPopover feature="compositingStrength">
-        <FormLabel>{t('parameters.coherenceStrength')}</FormLabel>
+      <InformationalPopover feature="compositingCoherenceMinDenoise">
+        <FormLabel>{t('parameters.coherenceMinDenoise')}</FormLabel>
       </InformationalPopover>
       <CompositeSlider
         min={0}
         max={1}
         step={0.01}
-        value={canvasCoherenceStrength}
-        defaultValue={0.75}
+        value={canvasCoherenceMinDenoise}
+        defaultValue={0}
         onChange={handleChange}
       />
       <CompositeNumberInput
         min={0}
         max={1}
         step={0.01}
-        value={canvasCoherenceStrength}
-        defaultValue={0.75}
+        value={canvasCoherenceMinDenoise}
+        defaultValue={0}
         onChange={handleChange}
       />
     </FormControl>
   );
 };
 
-export default memo(ParamCanvasCoherenceStrength);
+export default memo(ParamCanvasCoherenceMinDenoise);
diff --git a/invokeai/frontend/web/src/features/parameters/components/Canvas/Compositing/CoherencePass/ParamCanvasCoherenceMode.tsx b/invokeai/frontend/web/src/features/parameters/components/Canvas/Compositing/CoherencePass/ParamCanvasCoherenceMode.tsx
index 1060a06694..fad6149a1f 100644
--- a/invokeai/frontend/web/src/features/parameters/components/Canvas/Compositing/CoherencePass/ParamCanvasCoherenceMode.tsx
+++ b/invokeai/frontend/web/src/features/parameters/components/Canvas/Compositing/CoherencePass/ParamCanvasCoherenceMode.tsx
@@ -14,9 +14,9 @@ const ParamCanvasCoherenceMode = () => {
 
   const options = useMemo<ComboboxOption[]>(
     () => [
-      { label: t('parameters.unmasked'), value: 'unmasked' },
-      { label: t('unifiedCanvas.mask'), value: 'mask' },
-      { label: t('parameters.maskEdge'), value: 'edge' },
+      { label: t('unifiedCanvas.coherenceModeGaussianBlur'), value: 'Gaussian Blur' },
+      { label: t('unifiedCanvas.coherenceModeBoxBlur'), value: 'Box Blur' },
+      { label: t('unifiedCanvas.coherenceModeStaged'), value: 'Staged' },
     ],
     [t]
   );
diff --git a/invokeai/frontend/web/src/features/parameters/store/generationSlice.ts b/invokeai/frontend/web/src/features/parameters/store/generationSlice.ts
index 1666a34d6a..4041490345 100644
--- a/invokeai/frontend/web/src/features/parameters/store/generationSlice.ts
+++ b/invokeai/frontend/web/src/features/parameters/store/generationSlice.ts
@@ -38,9 +38,9 @@ export const initialGenerationState: GenerationState = {
   scheduler: 'euler',
   maskBlur: 16,
   maskBlurMethod: 'box',
-  canvasCoherenceMode: 'unmasked',
-  canvasCoherenceSteps: 20,
-  canvasCoherenceStrength: 0.3,
+  canvasCoherenceMode: 'Gaussian Blur',
+  canvasCoherenceMinDenoise: 0,
+  canvasCoherenceEdgeSize: 16,
   seed: 0,
   shouldFitToWidthHeight: true,
   shouldRandomizeSeed: true,
@@ -124,11 +124,11 @@ export const generationSlice = createSlice({
     setCanvasCoherenceMode: (state, action: PayloadAction<ParameterCanvasCoherenceMode>) => {
       state.canvasCoherenceMode = action.payload;
     },
-    setCanvasCoherenceSteps: (state, action: PayloadAction<number>) => {
-      state.canvasCoherenceSteps = action.payload;
+    setCanvasCoherenceEdgeSize: (state, action: PayloadAction<number>) => {
+      state.canvasCoherenceEdgeSize = action.payload;
     },
-    setCanvasCoherenceStrength: (state, action: PayloadAction<number>) => {
-      state.canvasCoherenceStrength = action.payload;
+    setCanvasCoherenceMinDenoise: (state, action: PayloadAction<number>) => {
+      state.canvasCoherenceMinDenoise = action.payload;
     },
     setInfillMethod: (state, action: PayloadAction<string>) => {
       state.infillMethod = action.payload;
@@ -274,8 +274,8 @@ export const {
   setMaskBlur,
   setMaskBlurMethod,
   setCanvasCoherenceMode,
-  setCanvasCoherenceSteps,
-  setCanvasCoherenceStrength,
+  setCanvasCoherenceEdgeSize,
+  setCanvasCoherenceMinDenoise,
   setSeed,
   setShouldFitToWidthHeight,
   setShouldRandomizeSeed,
diff --git a/invokeai/frontend/web/src/features/parameters/store/types.ts b/invokeai/frontend/web/src/features/parameters/store/types.ts
index 0c20019d70..884db3e911 100644
--- a/invokeai/frontend/web/src/features/parameters/store/types.ts
+++ b/invokeai/frontend/web/src/features/parameters/store/types.ts
@@ -33,8 +33,8 @@ export interface GenerationState {
   maskBlur: number;
   maskBlurMethod: ParameterMaskBlurMethod;
   canvasCoherenceMode: ParameterCanvasCoherenceMode;
-  canvasCoherenceSteps: number;
-  canvasCoherenceStrength: ParameterStrength;
+  canvasCoherenceMinDenoise: ParameterStrength;
+  canvasCoherenceEdgeSize: number;
   seed: ParameterSeed;
   shouldFitToWidthHeight: boolean;
   shouldRandomizeSeed: boolean;
diff --git a/invokeai/frontend/web/src/features/parameters/types/parameterSchemas.ts b/invokeai/frontend/web/src/features/parameters/types/parameterSchemas.ts
index b30d5df147..20953ec266 100644
--- a/invokeai/frontend/web/src/features/parameters/types/parameterSchemas.ts
+++ b/invokeai/frontend/web/src/features/parameters/types/parameterSchemas.ts
@@ -213,7 +213,7 @@ export const isParameterMaskBlurMethod = (val: unknown): val is ParameterMaskBlu
 // #endregion
 
 // #region Canvas Coherence Mode
-export const zParameterCanvasCoherenceMode = z.enum(['unmasked', 'mask', 'edge']);
+export const zParameterCanvasCoherenceMode = z.enum(['Gaussian Blur', 'Box Blur', 'Staged']);
 export type ParameterCanvasCoherenceMode = z.infer<typeof zParameterCanvasCoherenceMode>;
 export const isParameterCanvasCoherenceMode = (val: unknown): val is ParameterCanvasCoherenceMode =>
   zParameterCanvasCoherenceMode.safeParse(val).success;
diff --git a/invokeai/frontend/web/src/features/settingsAccordions/components/CompositingSettingsAccordion/CompositingSettingsAccordion.tsx b/invokeai/frontend/web/src/features/settingsAccordions/components/CompositingSettingsAccordion/CompositingSettingsAccordion.tsx
index 30c7b361d9..0c4eed17d6 100644
--- a/invokeai/frontend/web/src/features/settingsAccordions/components/CompositingSettingsAccordion/CompositingSettingsAccordion.tsx
+++ b/invokeai/frontend/web/src/features/settingsAccordions/components/CompositingSettingsAccordion/CompositingSettingsAccordion.tsx
@@ -9,11 +9,9 @@ import {
   TabPanels,
   Tabs,
 } from '@invoke-ai/ui-library';
+import ParamCanvasCoherenceEdgeSize from 'features/parameters/components/Canvas/Compositing/CoherencePass/ParamCanvasCoherenceEdgeSize';
+import ParamCanvasCoherenceMinDenoise from 'features/parameters/components/Canvas/Compositing/CoherencePass/ParamCanvasCoherenceMinDenoise';
 import ParamCanvasCoherenceMode from 'features/parameters/components/Canvas/Compositing/CoherencePass/ParamCanvasCoherenceMode';
-import ParamCanvasCoherenceSteps from 'features/parameters/components/Canvas/Compositing/CoherencePass/ParamCanvasCoherenceSteps';
-import ParamCanvasCoherenceStrength from 'features/parameters/components/Canvas/Compositing/CoherencePass/ParamCanvasCoherenceStrength';
-import ParamMaskBlur from 'features/parameters/components/Canvas/Compositing/MaskAdjustment/ParamMaskBlur';
-import ParamMaskBlurMethod from 'features/parameters/components/Canvas/Compositing/MaskAdjustment/ParamMaskBlurMethod';
 import ParamInfillMethod from 'features/parameters/components/Canvas/InfillAndScaling/ParamInfillMethod';
 import ParamInfillOptions from 'features/parameters/components/Canvas/InfillAndScaling/ParamInfillOptions';
 import { useStandaloneAccordionToggle } from 'features/settingsAccordions/hooks/useStandaloneAccordionToggle';
@@ -43,10 +41,10 @@ export const CompositingSettingsAccordion = memo(() => {
             <Flex gap={4} p={4} flexDir="column">
               <FormControlGroup formLabelProps={coherenceLabelProps}>
                 <ParamCanvasCoherenceMode />
-                <ParamCanvasCoherenceSteps />
-                <ParamCanvasCoherenceStrength />
-                <ParamMaskBlurMethod />
-                <ParamMaskBlur />
+                <ParamCanvasCoherenceEdgeSize />
+                <ParamCanvasCoherenceMinDenoise />
+                {/* <ParamMaskBlurMethod />
+                <ParamMaskBlur /> */}
               </FormControlGroup>
             </Flex>
           </TabPanel>
diff --git a/invokeai/frontend/web/src/features/system/store/configSlice.ts b/invokeai/frontend/web/src/features/system/store/configSlice.ts
index 94f1f1c64a..707c94dee6 100644
--- a/invokeai/frontend/web/src/features/system/store/configSlice.ts
+++ b/invokeai/frontend/web/src/features/system/store/configSlice.ts
@@ -86,14 +86,14 @@ export const initialConfigState: AppConfig = {
       fineStep: 0.01,
       coarseStep: 0.05,
     },
-    canvasCoherenceSteps: {
-      initial: 20,
-      sliderMin: 1,
-      sliderMax: 100,
-      numberInputMin: 1,
-      numberInputMax: 999,
-      fineStep: 1,
-      coarseStep: 1,
+    canvasCoherenceEdgeSize: {
+      initial: 16,
+      sliderMin: 16,
+      sliderMax: 512,
+      numberInputMin: 16,
+      numberInputMax: 1024,
+      fineStep: 8,
+      coarseStep: 16,
     },
     cfgRescaleMultiplier: {
       initial: 0,

From 68d79c002d74dcb3b2845b5dd798b3f8bac68863 Mon Sep 17 00:00:00 2001
From: blessedcoolant <54517381+blessedcoolant@users.noreply.github.com>
Date: Thu, 22 Feb 2024 10:23:18 +0530
Subject: [PATCH 297/411] canvas: improve paste back (or try to)

---
 invokeai/app/invocations/image.py             | 47 ++++++++--
 .../util/graph/buildCanvasInpaintGraph.ts     | 87 +++++++++---------
 .../util/graph/buildCanvasOutpaintGraph.ts    | 19 ++--
 .../util/graph/buildCanvasSDXLInpaintGraph.ts | 90 +++++++++----------
 .../graph/buildCanvasSDXLOutpaintGraph.ts     | 36 ++++----
 .../frontend/web/src/services/api/schema.ts   | 49 +++++++++-
 .../frontend/web/src/services/api/types.ts    |  2 +
 7 files changed, 208 insertions(+), 122 deletions(-)

diff --git a/invokeai/app/invocations/image.py b/invokeai/app/invocations/image.py
index a0c41161c3..6de182d7a5 100644
--- a/invokeai/app/invocations/image.py
+++ b/invokeai/app/invocations/image.py
@@ -17,16 +17,12 @@ from invokeai.app.invocations.fields import (
     WithMetadata,
 )
 from invokeai.app.invocations.primitives import ImageOutput
-from invokeai.app.services.image_records.image_records_common import ImageCategory
+from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.backend.image_util.invisible_watermark import InvisibleWatermark
 from invokeai.backend.image_util.safety_checker import SafetyChecker
 
-from .baseinvocation import (
-    BaseInvocation,
-    Classification,
-    invocation,
-)
+from .baseinvocation import BaseInvocation, Classification, invocation
 
 
 @invocation("show_image", title="Show Image", tags=["image"], category="image", version="1.0.1")
@@ -934,3 +930,42 @@ class SaveImageInvocation(BaseInvocation, WithMetadata, WithBoard):
         image_dto = context.images.save(image=image)
 
         return ImageOutput.build(image_dto)
+
+
+@invocation(
+    "iai_canvas_paste_back",
+    title="InvokeAI Canvas Paste Back",
+    tags=["image", "combine"],
+    category="image",
+    version="1.0.0",
+)
+class IAICanvasPasteBackInvocation(BaseInvocation, WithMetadata, WithBoard):
+    """Combines two images by using the mask provided"""
+
+    source_image: ImageField = InputField(description="The source image")
+    target_image: ImageField = InputField(default=None, description="The target image")
+    mask: ImageField = InputField(
+        description="The mask to use when pasting",
+    )
+    mask_blur: int = InputField(default=0, ge=0, description="The amount to blur the mask by")
+
+    def _prepare_mask(self, mask: Image.Image):
+        mask_array = numpy.array(mask)
+        kernel = numpy.ones((self.mask_blur, self.mask_blur), numpy.uint8)
+        dilated_mask_array = cv2.erode(mask_array, kernel, iterations=3)
+        dilated_mask = Image.fromarray(dilated_mask_array)
+        if self.mask_blur > 0:
+            mask = dilated_mask.filter(ImageFilter.GaussianBlur(self.mask_blur))
+        return ImageOps.invert(mask.convert("L"))
+
+    def invoke(self, context: InvocationContext) -> ImageOutput:
+        source_image = context.images.get_pil(self.source_image.image_name)
+        target_image = context.images.get_pil(self.target_image.image_name)
+        mask = self._prepare_mask(context.images.get_pil(self.mask.image_name))
+
+        # Merge the bands back together
+        source_image.paste(target_image, (0, 0), mask)
+
+        image_dto = context.images.save(image=source_image)
+
+        return ImageOutput.build(image_dto)
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasInpaintGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasInpaintGraph.ts
index 59bbca1e7b..079940346b 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasInpaintGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasInpaintGraph.ts
@@ -1,7 +1,13 @@
 import { logger } from 'app/logging/logger';
 import type { RootState } from 'app/store/store';
-import { getBoardField, getIsIntermediate } from 'features/nodes/util/graph/graphBuilderUtils';
-import type { ImageDTO, ImageToLatentsInvocation, NoiseInvocation, NonNullableGraph } from 'services/api/types';
+import type {
+  CreateGradientMaskInvocation,
+  IAICanvasPasteBackInvocation,
+  ImageDTO,
+  ImageToLatentsInvocation,
+  NoiseInvocation,
+  NonNullableGraph,
+} from 'services/api/types';
 
 import { addControlNetToLinearGraph } from './addControlNetToLinearGraph';
 import { addIPAdapterToLinearGraph } from './addIPAdapterToLinearGraph';
@@ -29,6 +35,7 @@ import {
   POSITIVE_CONDITIONING,
   SEAMLESS,
 } from './constants';
+import { getBoardField, getIsIntermediate } from './graphBuilderUtils';
 
 /**
  * Builds the Canvas tab's Inpaint graph.
@@ -61,8 +68,8 @@ export const buildCanvasInpaintGraph = (
   } = state.generation;
 
   if (!model) {
-    log.error('No Image found in state');
-    throw new Error('No Image found in state');
+    log.error('No model found in state');
+    throw new Error('No model found in state');
   }
 
   // The bounding box determines width and height, not the width and height params
@@ -106,7 +113,6 @@ export const buildCanvasInpaintGraph = (
         is_intermediate,
         prompt: negativePrompt,
       },
-
       [INPAINT_IMAGE]: {
         type: 'i2l',
         id: INPAINT_IMAGE,
@@ -146,12 +152,12 @@ export const buildCanvasInpaintGraph = (
         fp32,
       },
       [CANVAS_OUTPUT]: {
-        type: 'color_correct',
+        type: 'iai_canvas_paste_back',
         id: CANVAS_OUTPUT,
         is_intermediate: getIsIntermediate(state),
         board: getBoardField(state),
-        reference: canvasInitImage,
-        use_cache: false,
+        mask_blur: canvasCoherenceEdgeSize,
+        source_image: canvasInitImage,
       },
     },
     edges: [
@@ -325,7 +331,7 @@ export const buildCanvasInpaintGraph = (
           field: 'mask',
         },
       },
-      // Color Correct The Inpainted Result
+      // Resize Down
       {
         source: {
           node_id: LATENTS_TO_IMAGE,
@@ -336,16 +342,6 @@ export const buildCanvasInpaintGraph = (
           field: 'image',
         },
       },
-      {
-        source: {
-          node_id: INPAINT_IMAGE_RESIZE_DOWN,
-          field: 'image',
-        },
-        destination: {
-          node_id: CANVAS_OUTPUT,
-          field: 'image',
-        },
-      },
       {
         source: {
           node_id: MASK_RESIZE_UP,
@@ -356,6 +352,17 @@ export const buildCanvasInpaintGraph = (
           field: 'image',
         },
       },
+      // Paste Back
+      {
+        source: {
+          node_id: INPAINT_IMAGE_RESIZE_DOWN,
+          field: 'image',
+        },
+        destination: {
+          node_id: CANVAS_OUTPUT,
+          field: 'target_image',
+        },
+      },
       {
         source: {
           node_id: MASK_RESIZE_DOWN,
@@ -377,29 +384,27 @@ export const buildCanvasInpaintGraph = (
       image: canvasInitImage,
     };
 
-    graph.edges.push(
-      // Color Correct The Inpainted Result
-      {
-        source: {
-          node_id: LATENTS_TO_IMAGE,
-          field: 'image',
-        },
-        destination: {
-          node_id: CANVAS_OUTPUT,
-          field: 'image',
-        },
+    graph.nodes[INPAINT_CREATE_MASK] = {
+      ...(graph.nodes[INPAINT_CREATE_MASK] as CreateGradientMaskInvocation),
+      mask: canvasMaskImage,
+    };
+
+    // Paste Back
+    graph.nodes[CANVAS_OUTPUT] = {
+      ...(graph.nodes[CANVAS_OUTPUT] as IAICanvasPasteBackInvocation),
+      mask: canvasMaskImage,
+    };
+
+    graph.edges.push({
+      source: {
+        node_id: LATENTS_TO_IMAGE,
+        field: 'image',
       },
-      {
-        source: {
-          node_id: MASK_RESIZE_DOWN,
-          field: 'image',
-        },
-        destination: {
-          node_id: CANVAS_OUTPUT,
-          field: 'mask',
-        },
-      }
-    );
+      destination: {
+        node_id: CANVAS_OUTPUT,
+        field: 'target_image',
+      },
+    });
   }
 
   // Add Seamless To Graph
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasOutpaintGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasOutpaintGraph.ts
index 53840703f2..4140c4c485 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasOutpaintGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasOutpaintGraph.ts
@@ -1,6 +1,5 @@
 import { logger } from 'app/logging/logger';
 import type { RootState } from 'app/store/store';
-import { getBoardField, getIsIntermediate } from 'features/nodes/util/graph/graphBuilderUtils';
 import type {
   ImageDTO,
   ImageToLatentsInvocation,
@@ -40,6 +39,7 @@ import {
   POSITIVE_CONDITIONING,
   SEAMLESS,
 } from './constants';
+import { getBoardField, getIsIntermediate } from './graphBuilderUtils';
 
 /**
  * Builds the Canvas tab's Outpaint graph.
@@ -149,8 +149,8 @@ export const buildCanvasOutpaintGraph = (
         id: INPAINT_CREATE_MASK,
         is_intermediate,
         coherence_mode: canvasCoherenceMode,
-        minimum_denoise: canvasCoherenceMinDenoise,
         edge_radius: canvasCoherenceEdgeSize,
+        minimum_denoise: canvasCoherenceMinDenoise,
       },
       [DENOISE_LATENTS]: {
         type: 'denoise_latents',
@@ -171,7 +171,7 @@ export const buildCanvasOutpaintGraph = (
         fp32,
       },
       [CANVAS_OUTPUT]: {
-        type: 'color_correct',
+        type: 'iai_canvas_paste_back',
         id: CANVAS_OUTPUT,
         is_intermediate: getIsIntermediate(state),
         board: getBoardField(state),
@@ -455,7 +455,7 @@ export const buildCanvasOutpaintGraph = (
           field: 'image',
         },
       },
-      // Color Correct The Inpainted Result
+      // Paste Back
       {
         source: {
           node_id: INPAINT_INFILL_RESIZE_DOWN,
@@ -463,17 +463,17 @@ export const buildCanvasOutpaintGraph = (
         },
         destination: {
           node_id: CANVAS_OUTPUT,
-          field: 'reference',
+          field: 'source_image',
         },
       },
       {
         source: {
-          node_id: INPAINT_IMAGE_RESIZE_DOWN,
+          node_id: LATENTS_TO_IMAGE,
           field: 'image',
         },
         destination: {
           node_id: CANVAS_OUTPUT,
-          field: 'image',
+          field: 'target_image',
         },
       },
       {
@@ -503,7 +503,6 @@ export const buildCanvasOutpaintGraph = (
     };
 
     graph.edges.push(
-      // Color Correct The Inpainted Result
       {
         source: {
           node_id: INPAINT_INFILL,
@@ -511,7 +510,7 @@ export const buildCanvasOutpaintGraph = (
         },
         destination: {
           node_id: CANVAS_OUTPUT,
-          field: 'reference',
+          field: 'source_image',
         },
       },
       {
@@ -521,7 +520,7 @@ export const buildCanvasOutpaintGraph = (
         },
         destination: {
           node_id: CANVAS_OUTPUT,
-          field: 'image',
+          field: 'target_image',
         },
       },
       {
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLInpaintGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLInpaintGraph.ts
index 56fb6147ce..14a45b8f40 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLInpaintGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLInpaintGraph.ts
@@ -1,7 +1,8 @@
 import { logger } from 'app/logging/logger';
 import type { RootState } from 'app/store/store';
 import type {
-  CreateDenoiseMaskInvocation,
+  CreateGradientMaskInvocation,
+  IAICanvasPasteBackInvocation,
   ImageDTO,
   ImageToLatentsInvocation,
   NoiseInvocation,
@@ -54,15 +55,15 @@ export const buildCanvasSDXLInpaintGraph = (
     cfgRescaleMultiplier: cfg_rescale_multiplier,
     scheduler,
     steps,
+    img2imgStrength: strength,
     seed,
     vaePrecision,
     shouldUseCpuNoise,
+    seamlessXAxis,
+    seamlessYAxis,
     canvasCoherenceMode,
     canvasCoherenceMinDenoise,
     canvasCoherenceEdgeSize,
-    seamlessXAxis,
-    seamlessYAxis,
-    img2imgStrength: strength,
   } = state.generation;
 
   const { refinerModel, refinerStart } = state.sdxl;
@@ -78,8 +79,9 @@ export const buildCanvasSDXLInpaintGraph = (
   // We may need to set the inpaint width and height to scale the image
   const { scaledBoundingBoxDimensions, boundingBoxScaleMethod } = state.canvas;
 
-  const fp32 = vaePrecision === 'fp32';
   const is_intermediate = true;
+  const fp32 = vaePrecision === 'fp32';
+
   const isUsingScaledDimensions = ['auto', 'manual'].includes(boundingBoxScaleMethod);
 
   let modelLoaderNodeId = SDXL_MODEL_LOADER;
@@ -95,17 +97,20 @@ export const buildCanvasSDXLInpaintGraph = (
       [modelLoaderNodeId]: {
         type: 'sdxl_model_loader',
         id: modelLoaderNodeId,
+        is_intermediate,
         model,
       },
       [POSITIVE_CONDITIONING]: {
         type: 'sdxl_compel_prompt',
         id: POSITIVE_CONDITIONING,
+        is_intermediate,
         prompt: positivePrompt,
         style: positiveStylePrompt,
       },
       [NEGATIVE_CONDITIONING]: {
         type: 'sdxl_compel_prompt',
         id: NEGATIVE_CONDITIONING,
+        is_intermediate,
         prompt: negativePrompt,
         style: negativeStylePrompt,
       },
@@ -148,12 +153,12 @@ export const buildCanvasSDXLInpaintGraph = (
         fp32,
       },
       [CANVAS_OUTPUT]: {
-        type: 'color_correct',
+        type: 'iai_canvas_paste_back',
         id: CANVAS_OUTPUT,
         is_intermediate: getIsIntermediate(state),
         board: getBoardField(state),
-        reference: canvasInitImage,
-        use_cache: false,
+        mask_blur: canvasCoherenceEdgeSize,
+        source_image: canvasInitImage,
       },
     },
     edges: [
@@ -208,7 +213,7 @@ export const buildCanvasSDXLInpaintGraph = (
           field: 'clip2',
         },
       },
-      // Connect everything to Inpaint
+      // Connect Everything To Inpaint Node
       {
         source: {
           node_id: POSITIVE_CONDITIONING,
@@ -336,7 +341,7 @@ export const buildCanvasSDXLInpaintGraph = (
           field: 'mask',
         },
       },
-      // Color Correct The Inpainted Result
+      // Resize Down
       {
         source: {
           node_id: LATENTS_TO_IMAGE,
@@ -347,16 +352,6 @@ export const buildCanvasSDXLInpaintGraph = (
           field: 'image',
         },
       },
-      {
-        source: {
-          node_id: INPAINT_IMAGE_RESIZE_DOWN,
-          field: 'image',
-        },
-        destination: {
-          node_id: CANVAS_OUTPUT,
-          field: 'image',
-        },
-      },
       {
         source: {
           node_id: MASK_RESIZE_UP,
@@ -367,6 +362,17 @@ export const buildCanvasSDXLInpaintGraph = (
           field: 'image',
         },
       },
+      // Paste Back
+      {
+        source: {
+          node_id: INPAINT_IMAGE_RESIZE_DOWN,
+          field: 'image',
+        },
+        destination: {
+          node_id: CANVAS_OUTPUT,
+          field: 'target_image',
+        },
+      },
       {
         source: {
           node_id: MASK_RESIZE_DOWN,
@@ -387,34 +393,28 @@ export const buildCanvasSDXLInpaintGraph = (
       ...(graph.nodes[INPAINT_IMAGE] as ImageToLatentsInvocation),
       image: canvasInitImage,
     };
+
     graph.nodes[INPAINT_CREATE_MASK] = {
-      ...(graph.nodes[INPAINT_CREATE_MASK] as CreateDenoiseMaskInvocation),
-      image: canvasInitImage,
+      ...(graph.nodes[INPAINT_CREATE_MASK] as CreateGradientMaskInvocation),
+      mask: canvasMaskImage,
     };
 
-    graph.edges.push(
-      // Color Correct The Inpainted Result
-      {
-        source: {
-          node_id: LATENTS_TO_IMAGE,
-          field: 'image',
-        },
-        destination: {
-          node_id: CANVAS_OUTPUT,
-          field: 'image',
-        },
+    // Paste Back
+    graph.nodes[CANVAS_OUTPUT] = {
+      ...(graph.nodes[CANVAS_OUTPUT] as IAICanvasPasteBackInvocation),
+      mask: canvasMaskImage,
+    };
+
+    graph.edges.push({
+      source: {
+        node_id: LATENTS_TO_IMAGE,
+        field: 'image',
       },
-      {
-        source: {
-          node_id: MASK_RESIZE_DOWN,
-          field: 'image',
-        },
-        destination: {
-          node_id: CANVAS_OUTPUT,
-          field: 'mask',
-        },
-      }
-    );
+      destination: {
+        node_id: CANVAS_OUTPUT,
+        field: 'target_image',
+      },
+    });
   }
 
   // Add Seamless To Graph
@@ -431,7 +431,7 @@ export const buildCanvasSDXLInpaintGraph = (
     }
   }
 
-  // optionally add custom VAE
+  // Add VAE
   addVAEToGraph(state, graph, modelLoaderNodeId);
 
   // add LoRA support
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLOutpaintGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLOutpaintGraph.ts
index f448b2be72..6a664acb51 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLOutpaintGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLOutpaintGraph.ts
@@ -59,18 +59,18 @@ export const buildCanvasSDXLOutpaintGraph = (
     cfgRescaleMultiplier: cfg_rescale_multiplier,
     scheduler,
     steps,
+    img2imgStrength: strength,
     seed,
     vaePrecision,
     shouldUseCpuNoise,
-    canvasCoherenceMode,
-    canvasCoherenceMinDenoise,
-    canvasCoherenceEdgeSize,
     infillTileSize,
     infillPatchmatchDownscaleSize,
     infillMethod,
     seamlessXAxis,
     seamlessYAxis,
-    img2imgStrength: strength,
+    canvasCoherenceMode,
+    canvasCoherenceMinDenoise,
+    canvasCoherenceEdgeSize,
   } = state.generation;
 
   const { refinerModel, refinerStart } = state.sdxl;
@@ -108,12 +108,14 @@ export const buildCanvasSDXLOutpaintGraph = (
       [POSITIVE_CONDITIONING]: {
         type: 'sdxl_compel_prompt',
         id: POSITIVE_CONDITIONING,
+        is_intermediate,
         prompt: positivePrompt,
         style: positiveStylePrompt,
       },
       [NEGATIVE_CONDITIONING]: {
         type: 'sdxl_compel_prompt',
         id: NEGATIVE_CONDITIONING,
+        is_intermediate,
         prompt: negativePrompt,
         style: negativeStylePrompt,
       },
@@ -161,6 +163,7 @@ export const buildCanvasSDXLOutpaintGraph = (
         denoising_start: refinerModel ? Math.min(refinerStart, 1 - strength) : 1 - strength,
         denoising_end: refinerModel ? refinerStart : 1,
       },
+
       [LATENTS_TO_IMAGE]: {
         type: 'l2i',
         id: LATENTS_TO_IMAGE,
@@ -168,7 +171,7 @@ export const buildCanvasSDXLOutpaintGraph = (
         fp32,
       },
       [CANVAS_OUTPUT]: {
-        type: 'color_correct',
+        type: 'iai_canvas_paste_back',
         id: CANVAS_OUTPUT,
         is_intermediate: getIsIntermediate(state),
         board: getBoardField(state),
@@ -249,7 +252,7 @@ export const buildCanvasSDXLOutpaintGraph = (
           field: 'mask1',
         },
       },
-      // Connect Everything To Inpaint
+      // Plug Everything Into Inpaint Node
       {
         source: {
           node_id: POSITIVE_CONDITIONING,
@@ -311,7 +314,7 @@ export const buildCanvasSDXLOutpaintGraph = (
           field: 'denoise_mask',
         },
       },
-      // Decode inpainted latents to image
+
       {
         source: {
           node_id: SDXL_DENOISE_LATENTS,
@@ -419,8 +422,7 @@ export const buildCanvasSDXLOutpaintGraph = (
           field: 'image',
         },
       },
-
-      // Take combined mask and resize and then blur
+      // Take combined mask and resize
       {
         source: {
           node_id: MASK_COMBINE,
@@ -431,7 +433,6 @@ export const buildCanvasSDXLOutpaintGraph = (
           field: 'image',
         },
       },
-
       // Resize Results Down
       {
         source: {
@@ -463,7 +464,7 @@ export const buildCanvasSDXLOutpaintGraph = (
           field: 'image',
         },
       },
-      // Color Correct The Inpainted Result
+      // Paste Back
       {
         source: {
           node_id: INPAINT_INFILL_RESIZE_DOWN,
@@ -471,17 +472,17 @@ export const buildCanvasSDXLOutpaintGraph = (
         },
         destination: {
           node_id: CANVAS_OUTPUT,
-          field: 'reference',
+          field: 'source_image',
         },
       },
       {
         source: {
-          node_id: INPAINT_IMAGE_RESIZE_DOWN,
+          node_id: LATENTS_TO_IMAGE,
           field: 'image',
         },
         destination: {
           node_id: CANVAS_OUTPUT,
-          field: 'image',
+          field: 'target_image',
         },
       },
       {
@@ -511,7 +512,6 @@ export const buildCanvasSDXLOutpaintGraph = (
     };
 
     graph.edges.push(
-      // Color Correct The Inpainted Result
       {
         source: {
           node_id: INPAINT_INFILL,
@@ -519,7 +519,7 @@ export const buildCanvasSDXLOutpaintGraph = (
         },
         destination: {
           node_id: CANVAS_OUTPUT,
-          field: 'reference',
+          field: 'source_image',
         },
       },
       {
@@ -529,7 +529,7 @@ export const buildCanvasSDXLOutpaintGraph = (
         },
         destination: {
           node_id: CANVAS_OUTPUT,
-          field: 'image',
+          field: 'target_image',
         },
       },
       {
@@ -559,7 +559,7 @@ export const buildCanvasSDXLOutpaintGraph = (
     }
   }
 
-  // optionally add custom VAE
+  // Add VAE
   addVAEToGraph(state, graph, modelLoaderNodeId);
 
   // add LoRA support
diff --git a/invokeai/frontend/web/src/services/api/schema.ts b/invokeai/frontend/web/src/services/api/schema.ts
index 59d1db5f19..943d0c146e 100644
--- a/invokeai/frontend/web/src/services/api/schema.ts
+++ b/invokeai/frontend/web/src/services/api/schema.ts
@@ -4286,7 +4286,7 @@ export type components = {
        * @description The nodes in this graph
        */
       nodes: {
-        [key: string]: components["schemas"]["StringJoinInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["CreateGradientMaskInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["ColorMapImageProcessorInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["DWOpenposeImageProcessorInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["DepthAnythingImageProcessorInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["MergeTilesToImageInvocation"];
+        [key: string]: components["schemas"]["ESRGANInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["ColorMapImageProcessorInvocation"] | components["schemas"]["CreateGradientMaskInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["DepthAnythingImageProcessorInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["IAICanvasPasteBackInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["DWOpenposeImageProcessorInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["RandomIntInvocation"];
       };
       /**
        * Edges
@@ -4323,7 +4323,7 @@ export type components = {
        * @description The results of node executions
        */
       results: {
-        [key: string]: components["schemas"]["LoraLoaderOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["MetadataOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["SDXLLoraLoaderOutput"] | components["schemas"]["ClipSkipInvocationOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["LatentsOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["String2Output"] | components["schemas"]["VAEOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["NoiseOutput"];
+        [key: string]: components["schemas"]["LatentsOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["MetadataOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["String2Output"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["ClipSkipInvocationOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["VAEOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["LoraLoaderOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["SDXLLoraLoaderOutput"];
       };
       /**
        * Errors
@@ -4472,6 +4472,51 @@ export type components = {
        */
       last_modified: string;
     };
+    /**
+     * InvokeAI Canvas Paste Back
+     * @description Combines two images by using the mask provided
+     */
+    IAICanvasPasteBackInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
+      /** @description Optional metadata to be saved with the image */
+      metadata?: components["schemas"]["MetadataField"] | null;
+      /**
+       * Id
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
+       */
+      id: string;
+      /**
+       * Is Intermediate
+       * @description Whether or not this is an intermediate invocation.
+       * @default false
+       */
+      is_intermediate?: boolean;
+      /**
+       * Use Cache
+       * @description Whether or not to use the cache
+       * @default true
+       */
+      use_cache?: boolean;
+      /** @description The source image */
+      source_image?: components["schemas"]["ImageField"];
+      /** @description The target image */
+      target_image?: components["schemas"]["ImageField"];
+      /** @description The mask to use when pasting */
+      mask?: components["schemas"]["ImageField"];
+      /**
+       * Mask Blur
+       * @description The amount to blur the mask by
+       * @default 0
+       */
+      mask_blur?: number;
+      /**
+       * type
+       * @default iai_canvas_paste_back
+       * @constant
+       */
+      type: "iai_canvas_paste_back";
+    };
     /**
      * IPAdapterConfig
      * @description Model config for IP Adaptor format models.
diff --git a/invokeai/frontend/web/src/services/api/types.ts b/invokeai/frontend/web/src/services/api/types.ts
index f6b7ad5e08..4d4de90e59 100644
--- a/invokeai/frontend/web/src/services/api/types.ts
+++ b/invokeai/frontend/web/src/services/api/types.ts
@@ -150,6 +150,8 @@ export type ImageScaleInvocation = S['ImageScaleInvocation'];
 export type InfillPatchMatchInvocation = S['InfillPatchMatchInvocation'];
 export type InfillTileInvocation = S['InfillTileInvocation'];
 export type CreateDenoiseMaskInvocation = S['CreateDenoiseMaskInvocation'];
+export type CreateGradientMaskInvocation = S['CreateGradientMaskInvocation'];
+export type IAICanvasPasteBackInvocation = S['IAICanvasPasteBackInvocation'];
 export type MaskEdgeInvocation = S['MaskEdgeInvocation'];
 export type RandomIntInvocation = S['RandomIntInvocation'];
 export type CompelInvocation = S['CompelInvocation'];

From 8e1fbd6ed15a9e3eb06bb5a30eda0a1df0df1bc7 Mon Sep 17 00:00:00 2001
From: blessedcoolant <54517381+blessedcoolant@users.noreply.github.com>
Date: Thu, 22 Feb 2024 10:26:08 +0530
Subject: [PATCH 298/411] fix: lint errors

---
 invokeai/app/invocations/image.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/invokeai/app/invocations/image.py b/invokeai/app/invocations/image.py
index 6de182d7a5..ab4d49b26c 100644
--- a/invokeai/app/invocations/image.py
+++ b/invokeai/app/invocations/image.py
@@ -17,7 +17,7 @@ from invokeai.app.invocations.fields import (
     WithMetadata,
 )
 from invokeai.app.invocations.primitives import ImageOutput
-from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
+from invokeai.app.services.image_records.image_records_common import ImageCategory
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.backend.image_util.invisible_watermark import InvisibleWatermark
 from invokeai.backend.image_util.safety_checker import SafetyChecker

From cc82ce820aacf3d9eb49491a79ccf54cc71b3b73 Mon Sep 17 00:00:00 2001
From: blessedcoolant <54517381+blessedcoolant@users.noreply.github.com>
Date: Fri, 23 Feb 2024 04:54:16 +0530
Subject: [PATCH 299/411] fix: outpaint result not getting pasted back
 correctly

---
 invokeai/app/invocations/image.py                              | 2 --
 .../src/features/nodes/util/graph/buildCanvasOutpaintGraph.ts  | 3 ++-
 .../features/nodes/util/graph/buildCanvasSDXLOutpaintGraph.ts  | 3 ++-
 3 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/invokeai/app/invocations/image.py b/invokeai/app/invocations/image.py
index ab4d49b26c..f8c3aad62b 100644
--- a/invokeai/app/invocations/image.py
+++ b/invokeai/app/invocations/image.py
@@ -963,9 +963,7 @@ class IAICanvasPasteBackInvocation(BaseInvocation, WithMetadata, WithBoard):
         target_image = context.images.get_pil(self.target_image.image_name)
         mask = self._prepare_mask(context.images.get_pil(self.mask.image_name))
 
-        # Merge the bands back together
         source_image.paste(target_image, (0, 0), mask)
 
         image_dto = context.images.save(image=source_image)
-
         return ImageOutput.build(image_dto)
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasOutpaintGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasOutpaintGraph.ts
index 4140c4c485..eb98b40802 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasOutpaintGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasOutpaintGraph.ts
@@ -176,6 +176,7 @@ export const buildCanvasOutpaintGraph = (
         is_intermediate: getIsIntermediate(state),
         board: getBoardField(state),
         use_cache: false,
+        mask_blur: canvasCoherenceEdgeSize,
       },
     },
     edges: [
@@ -468,7 +469,7 @@ export const buildCanvasOutpaintGraph = (
       },
       {
         source: {
-          node_id: LATENTS_TO_IMAGE,
+          node_id: INPAINT_IMAGE_RESIZE_DOWN,
           field: 'image',
         },
         destination: {
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLOutpaintGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLOutpaintGraph.ts
index 6a664acb51..d181d1d3a2 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLOutpaintGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLOutpaintGraph.ts
@@ -176,6 +176,7 @@ export const buildCanvasSDXLOutpaintGraph = (
         is_intermediate: getIsIntermediate(state),
         board: getBoardField(state),
         use_cache: false,
+        mask_blur: canvasCoherenceEdgeSize,
       },
     },
     edges: [
@@ -477,7 +478,7 @@ export const buildCanvasSDXLOutpaintGraph = (
       },
       {
         source: {
-          node_id: LATENTS_TO_IMAGE,
+          node_id: INPAINT_IMAGE_RESIZE_DOWN,
           field: 'image',
         },
         destination: {

From 82249cc634a8fd4689e590effc99c29b024d037b Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 24 Feb 2024 19:19:29 +1100
Subject: [PATCH 300/411] tidy(nodes): rename canvas paste back

---
 invokeai/app/invocations/image.py | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/invokeai/app/invocations/image.py b/invokeai/app/invocations/image.py
index f8c3aad62b..7755f4cc69 100644
--- a/invokeai/app/invocations/image.py
+++ b/invokeai/app/invocations/image.py
@@ -933,14 +933,14 @@ class SaveImageInvocation(BaseInvocation, WithMetadata, WithBoard):
 
 
 @invocation(
-    "iai_canvas_paste_back",
-    title="InvokeAI Canvas Paste Back",
+    "canvas_paste_back",
+    title="Canvas Paste Back",
     tags=["image", "combine"],
     category="image",
     version="1.0.0",
 )
-class IAICanvasPasteBackInvocation(BaseInvocation, WithMetadata, WithBoard):
-    """Combines two images by using the mask provided"""
+class CanvasPasteBackInvocation(BaseInvocation, WithMetadata, WithBoard):
+    """Combines two images by using the mask provided. Intended for use on the Unified Canvas."""
 
     source_image: ImageField = InputField(description="The source image")
     target_image: ImageField = InputField(default=None, description="The target image")
@@ -949,7 +949,7 @@ class IAICanvasPasteBackInvocation(BaseInvocation, WithMetadata, WithBoard):
     )
     mask_blur: int = InputField(default=0, ge=0, description="The amount to blur the mask by")
 
-    def _prepare_mask(self, mask: Image.Image):
+    def _prepare_mask(self, mask: Image.Image) -> Image.Image:
         mask_array = numpy.array(mask)
         kernel = numpy.ones((self.mask_blur, self.mask_blur), numpy.uint8)
         dilated_mask_array = cv2.erode(mask_array, kernel, iterations=3)

From 6f591b324bb291472db343fde5ef53cbe307d749 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 24 Feb 2024 19:19:40 +1100
Subject: [PATCH 301/411] chore(ui): typegen

---
 .../frontend/web/src/services/api/schema.ts   | 94 +++++++++----------
 1 file changed, 47 insertions(+), 47 deletions(-)

diff --git a/invokeai/frontend/web/src/services/api/schema.ts b/invokeai/frontend/web/src/services/api/schema.ts
index 943d0c146e..c033ba89a2 100644
--- a/invokeai/frontend/web/src/services/api/schema.ts
+++ b/invokeai/frontend/web/src/services/api/schema.ts
@@ -1754,6 +1754,51 @@ export type components = {
        */
       type: "canny_image_processor";
     };
+    /**
+     * Canvas Paste Back
+     * @description Combines two images by using the mask provided. Intended for use on the Unified Canvas.
+     */
+    CanvasPasteBackInvocation: {
+      /** @description The board to save the image to */
+      board?: components["schemas"]["BoardField"] | null;
+      /** @description Optional metadata to be saved with the image */
+      metadata?: components["schemas"]["MetadataField"] | null;
+      /**
+       * Id
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
+       */
+      id: string;
+      /**
+       * Is Intermediate
+       * @description Whether or not this is an intermediate invocation.
+       * @default false
+       */
+      is_intermediate?: boolean;
+      /**
+       * Use Cache
+       * @description Whether or not to use the cache
+       * @default true
+       */
+      use_cache?: boolean;
+      /** @description The source image */
+      source_image?: components["schemas"]["ImageField"];
+      /** @description The target image */
+      target_image?: components["schemas"]["ImageField"];
+      /** @description The mask to use when pasting */
+      mask?: components["schemas"]["ImageField"];
+      /**
+       * Mask Blur
+       * @description The amount to blur the mask by
+       * @default 0
+       */
+      mask_blur?: number;
+      /**
+       * type
+       * @default canvas_paste_back
+       * @constant
+       */
+      type: "canvas_paste_back";
+    };
     /**
      * Center Pad or Crop Image
      * @description Pad or crop an image's sides from the center by specified pixels. Positive values are outside of the image.
@@ -4286,7 +4331,7 @@ export type components = {
        * @description The nodes in this graph
        */
       nodes: {
-        [key: string]: components["schemas"]["ESRGANInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["ColorMapImageProcessorInvocation"] | components["schemas"]["CreateGradientMaskInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["DepthAnythingImageProcessorInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["IAICanvasPasteBackInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["DWOpenposeImageProcessorInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["RandomIntInvocation"];
+        [key: string]: components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["ColorMapImageProcessorInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["CanvasPasteBackInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["DWOpenposeImageProcessorInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["CreateGradientMaskInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["DepthAnythingImageProcessorInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["PidiImageProcessorInvocation"];
       };
       /**
        * Edges
@@ -4323,7 +4368,7 @@ export type components = {
        * @description The results of node executions
        */
       results: {
-        [key: string]: components["schemas"]["LatentsOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["MetadataOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["String2Output"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["ClipSkipInvocationOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["VAEOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["LoraLoaderOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["SDXLLoraLoaderOutput"];
+        [key: string]: components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["String2Output"] | components["schemas"]["LoraLoaderOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["SDXLLoraLoaderOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["LatentsOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["VAEOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["ClipSkipInvocationOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["MetadataOutput"];
       };
       /**
        * Errors
@@ -4472,51 +4517,6 @@ export type components = {
        */
       last_modified: string;
     };
-    /**
-     * InvokeAI Canvas Paste Back
-     * @description Combines two images by using the mask provided
-     */
-    IAICanvasPasteBackInvocation: {
-      /** @description The board to save the image to */
-      board?: components["schemas"]["BoardField"] | null;
-      /** @description Optional metadata to be saved with the image */
-      metadata?: components["schemas"]["MetadataField"] | null;
-      /**
-       * Id
-       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
-       */
-      id: string;
-      /**
-       * Is Intermediate
-       * @description Whether or not this is an intermediate invocation.
-       * @default false
-       */
-      is_intermediate?: boolean;
-      /**
-       * Use Cache
-       * @description Whether or not to use the cache
-       * @default true
-       */
-      use_cache?: boolean;
-      /** @description The source image */
-      source_image?: components["schemas"]["ImageField"];
-      /** @description The target image */
-      target_image?: components["schemas"]["ImageField"];
-      /** @description The mask to use when pasting */
-      mask?: components["schemas"]["ImageField"];
-      /**
-       * Mask Blur
-       * @description The amount to blur the mask by
-       * @default 0
-       */
-      mask_blur?: number;
-      /**
-       * type
-       * @default iai_canvas_paste_back
-       * @constant
-       */
-      type: "iai_canvas_paste_back";
-    };
     /**
      * IPAdapterConfig
      * @description Model config for IP Adaptor format models.

From 04c060a89d1c7eb8a16ed7bdadce446fd4adabb7 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 24 Feb 2024 19:19:56 +1100
Subject: [PATCH 302/411] fix(ui): fix node types for canvas graphs

---
 .../src/features/nodes/util/graph/buildCanvasInpaintGraph.ts    | 2 +-
 .../src/features/nodes/util/graph/buildCanvasOutpaintGraph.ts   | 2 +-
 .../features/nodes/util/graph/buildCanvasSDXLInpaintGraph.ts    | 2 +-
 .../features/nodes/util/graph/buildCanvasSDXLOutpaintGraph.ts   | 2 +-
 4 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasInpaintGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasInpaintGraph.ts
index 079940346b..3512017313 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasInpaintGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasInpaintGraph.ts
@@ -152,7 +152,7 @@ export const buildCanvasInpaintGraph = (
         fp32,
       },
       [CANVAS_OUTPUT]: {
-        type: 'iai_canvas_paste_back',
+        type: 'canvas_paste_back',
         id: CANVAS_OUTPUT,
         is_intermediate: getIsIntermediate(state),
         board: getBoardField(state),
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasOutpaintGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasOutpaintGraph.ts
index eb98b40802..9ec07546af 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasOutpaintGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasOutpaintGraph.ts
@@ -171,7 +171,7 @@ export const buildCanvasOutpaintGraph = (
         fp32,
       },
       [CANVAS_OUTPUT]: {
-        type: 'iai_canvas_paste_back',
+        type: 'canvas_paste_back',
         id: CANVAS_OUTPUT,
         is_intermediate: getIsIntermediate(state),
         board: getBoardField(state),
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLInpaintGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLInpaintGraph.ts
index 14a45b8f40..394837a729 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLInpaintGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLInpaintGraph.ts
@@ -153,7 +153,7 @@ export const buildCanvasSDXLInpaintGraph = (
         fp32,
       },
       [CANVAS_OUTPUT]: {
-        type: 'iai_canvas_paste_back',
+        type: 'canvas_paste_back',
         id: CANVAS_OUTPUT,
         is_intermediate: getIsIntermediate(state),
         board: getBoardField(state),
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLOutpaintGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLOutpaintGraph.ts
index d181d1d3a2..13135e4748 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLOutpaintGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLOutpaintGraph.ts
@@ -171,7 +171,7 @@ export const buildCanvasSDXLOutpaintGraph = (
         fp32,
       },
       [CANVAS_OUTPUT]: {
-        type: 'iai_canvas_paste_back',
+        type: 'canvas_paste_back',
         id: CANVAS_OUTPUT,
         is_intermediate: getIsIntermediate(state),
         board: getBoardField(state),

From fbd9ffdc5a4c13b6bd626f68f90d98bd25637fc0 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 21 Feb 2024 19:59:13 +1100
Subject: [PATCH 303/411] feat(ui): bulk download click to download

---
 .../{bulkDownload.ts => bulkDownload.tsx}     | 20 +++++++++----------
 1 file changed, 10 insertions(+), 10 deletions(-)
 rename invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/{bulkDownload.ts => bulkDownload.tsx} (89%)

diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/bulkDownload.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/bulkDownload.tsx
similarity index 89%
rename from invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/bulkDownload.ts
rename to invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/bulkDownload.tsx
index 39d7e574c2..69adfb5b67 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/bulkDownload.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/bulkDownload.tsx
@@ -1,5 +1,5 @@
 import type { UseToastOptions } from '@invoke-ai/ui-library';
-import { createStandaloneToast, theme, TOAST_OPTIONS } from '@invoke-ai/ui-library';
+import { createStandaloneToast, ExternalLink, theme, TOAST_OPTIONS } from '@invoke-ai/ui-library';
 import { logger } from 'app/logging/logger';
 import { startAppListening } from 'app/store/middleware/listenerMiddleware';
 import { t } from 'i18next';
@@ -68,19 +68,19 @@ export const addBulkDownloadListeners = () => {
 
       // TODO(psyche): This URL may break in in some environments (e.g. Nvidia workbench) but we need to test it first
       const url = `/api/v1/images/download/${bulk_download_item_name}`;
-      const a = document.createElement('a');
-      a.style.display = 'none';
-      a.href = url;
-      a.download = bulk_download_item_name;
-      document.body.appendChild(a);
-      a.click();
 
       const toastOptions: UseToastOptions = {
         id: bulk_download_item_name,
-        title: t('gallery.bulkDownloadStarting'),
+        title: t('gallery.bulkDownloadReady', 'Download ready'),
         status: 'success',
-        description: bulk_download_item_name,
-        duration: 5000,
+        description: (
+          <ExternalLink
+            label={t('gallery.clickToDownload', 'Click here to download')}
+            href={url}
+            download={bulk_download_item_name}
+          />
+        ),
+        duration: null,
         isClosable: true,
       };
 

From d22738723da5ebd065b78fff2dabc22064566f83 Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lstein@gmail.com>
Date: Sat, 24 Feb 2024 11:25:40 -0500
Subject: [PATCH 304/411] clear out VRAM when an OOM occurs

---
 .../model_manager/load/model_cache/model_cache_default.py   | 6 ++++++
 .../backend/model_manager/load/model_cache/model_locker.py  | 6 ++++--
 2 files changed, 10 insertions(+), 2 deletions(-)

diff --git a/invokeai/backend/model_manager/load/model_cache/model_cache_default.py b/invokeai/backend/model_manager/load/model_cache/model_cache_default.py
index 02ce1266c7..094b4f958c 100644
--- a/invokeai/backend/model_manager/load/model_cache/model_cache_default.py
+++ b/invokeai/backend/model_manager/load/model_cache/model_cache_default.py
@@ -294,6 +294,12 @@ class ModelCache(ModelCacheBase[AnyModel]):
                     f"{get_pretty_snapshot_diff(snapshot_before, snapshot_after)}"
                 )
 
+    def _clear_vram(self) -> None:
+        """Called on out of memory errors. Moves all our models out of VRAM."""
+        self.logger.warning('Resetting VRAM cache.')
+        for model in self._cached_models.values():
+            self.move_model_to_device(model, torch.device('cpu'))
+
     def print_cuda_stats(self) -> None:
         """Log CUDA diagnostics."""
         vram = "%4.2fG" % (torch.cuda.memory_allocated() / GIG)
diff --git a/invokeai/backend/model_manager/load/model_cache/model_locker.py b/invokeai/backend/model_manager/load/model_cache/model_locker.py
index 7a5fdd4284..20c598e1cf 100644
--- a/invokeai/backend/model_manager/load/model_cache/model_locker.py
+++ b/invokeai/backend/model_manager/load/model_cache/model_locker.py
@@ -2,8 +2,8 @@
 Base class and implementation of a class that moves models in and out of VRAM.
 """
 
+import torch
 from invokeai.backend.model_manager import AnyModel
-
 from .model_cache_base import CacheRecord, ModelCacheBase, ModelLockerBase
 
 
@@ -42,7 +42,9 @@ class ModelLocker(ModelLockerBase):
 
             self._cache.logger.debug(f"Locking {self._cache_entry.key} in {self._cache.execution_device}")
             self._cache.print_cuda_stats()
-
+        except torch.cuda.OutOfMemoryError:
+            self._cache._clear_vram()
+            raise
         except Exception:
             self._cache_entry.unlock()
             raise

From 371e3cc260c7c8dbf8c04946dd14c4f95ed90698 Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lstein@gmail.com>
Date: Sat, 24 Feb 2024 12:32:30 -0500
Subject: [PATCH 305/411] recover gracefuly from GPU out of memory errors (next
 version)

---
 .../load/model_cache/model_cache_default.py   | 27 ++++++++++++++-----
 .../load/model_cache/model_locker.py          |  3 ++-
 2 files changed, 22 insertions(+), 8 deletions(-)

diff --git a/invokeai/backend/model_manager/load/model_cache/model_cache_default.py b/invokeai/backend/model_manager/load/model_cache/model_cache_default.py
index 094b4f958c..e1c5e743c1 100644
--- a/invokeai/backend/model_manager/load/model_cache/model_cache_default.py
+++ b/invokeai/backend/model_manager/load/model_cache/model_cache_default.py
@@ -245,7 +245,13 @@ class ModelCache(ModelCacheBase[AnyModel]):
             mps.empty_cache()
 
     def move_model_to_device(self, cache_entry: CacheRecord[AnyModel], target_device: torch.device) -> None:
-        """Move model into the indicated device."""
+        """Move model into the indicated device.
+
+        :param cache_entry: The CacheRecord for the model
+        :param target_device: The torch.device to move the model into
+
+        May raise a torch.cuda.OutOfMemoryError
+        """
         # These attributes are not in the base ModelMixin class but in various derived classes.
         # Some models don't have these attributes, in which case they run in RAM/CPU.
         self.logger.debug(f"Called to move {cache_entry.key} to {target_device}")
@@ -259,6 +265,9 @@ class ModelCache(ModelCacheBase[AnyModel]):
         if torch.device(source_device).type == torch.device(target_device).type:
             return
 
+        # may raise an exception here if insufficient GPU VRAM
+        self._check_free_vram(target_device, cache_entry.size)
+
         start_model_to_time = time.time()
         snapshot_before = self._capture_memory_snapshot()
         cache_entry.model.to(target_device)
@@ -294,12 +303,6 @@ class ModelCache(ModelCacheBase[AnyModel]):
                     f"{get_pretty_snapshot_diff(snapshot_before, snapshot_after)}"
                 )
 
-    def _clear_vram(self) -> None:
-        """Called on out of memory errors. Moves all our models out of VRAM."""
-        self.logger.warning('Resetting VRAM cache.')
-        for model in self._cached_models.values():
-            self.move_model_to_device(model, torch.device('cpu'))
-
     def print_cuda_stats(self) -> None:
         """Log CUDA diagnostics."""
         vram = "%4.2fG" % (torch.cuda.memory_allocated() / GIG)
@@ -411,3 +414,13 @@ class ModelCache(ModelCacheBase[AnyModel]):
             mps.empty_cache()
 
         self.logger.debug(f"After making room: cached_models={len(self._cached_models)}")
+
+    def _check_free_vram(self, target_device: torch.device, needed_size: int) -> None:
+        if target_device.type != "cuda":
+            return
+        vram_device = ( # mem_get_info() needs an indexed device
+            target_device if target_device.index is not None else torch.device(str(target_device), index=0)
+        )
+        free_mem, _ = torch.cuda.mem_get_info(torch.device(vram_device))
+        if needed_size > free_mem:
+            raise torch.cuda.OutOfMemoryError
diff --git a/invokeai/backend/model_manager/load/model_cache/model_locker.py b/invokeai/backend/model_manager/load/model_cache/model_locker.py
index 20c598e1cf..3651590cec 100644
--- a/invokeai/backend/model_manager/load/model_cache/model_locker.py
+++ b/invokeai/backend/model_manager/load/model_cache/model_locker.py
@@ -43,7 +43,8 @@ class ModelLocker(ModelLockerBase):
             self._cache.logger.debug(f"Locking {self._cache_entry.key} in {self._cache.execution_device}")
             self._cache.print_cuda_stats()
         except torch.cuda.OutOfMemoryError:
-            self._cache._clear_vram()
+            self._cache.logger.warning("Insufficient GPU memory to load model. Aborting")
+            self._cache_entry.unlock()
             raise
         except Exception:
             self._cache_entry.unlock()

From 37d66488c55f7fed21b9a0a1cc2984812bd152fd Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 26 Feb 2024 17:30:37 +1100
Subject: [PATCH 306/411] chore: ruff

---
 .../model_manager/load/model_cache/model_cache_default.py       | 2 +-
 invokeai/backend/model_manager/load/model_cache/model_locker.py | 2 ++
 2 files changed, 3 insertions(+), 1 deletion(-)

diff --git a/invokeai/backend/model_manager/load/model_cache/model_cache_default.py b/invokeai/backend/model_manager/load/model_cache/model_cache_default.py
index e1c5e743c1..2933b169f6 100644
--- a/invokeai/backend/model_manager/load/model_cache/model_cache_default.py
+++ b/invokeai/backend/model_manager/load/model_cache/model_cache_default.py
@@ -418,7 +418,7 @@ class ModelCache(ModelCacheBase[AnyModel]):
     def _check_free_vram(self, target_device: torch.device, needed_size: int) -> None:
         if target_device.type != "cuda":
             return
-        vram_device = ( # mem_get_info() needs an indexed device
+        vram_device = (  # mem_get_info() needs an indexed device
             target_device if target_device.index is not None else torch.device(str(target_device), index=0)
         )
         free_mem, _ = torch.cuda.mem_get_info(torch.device(vram_device))
diff --git a/invokeai/backend/model_manager/load/model_cache/model_locker.py b/invokeai/backend/model_manager/load/model_cache/model_locker.py
index 3651590cec..81dca346e5 100644
--- a/invokeai/backend/model_manager/load/model_cache/model_locker.py
+++ b/invokeai/backend/model_manager/load/model_cache/model_locker.py
@@ -3,7 +3,9 @@ Base class and implementation of a class that moves models in and out of VRAM.
 """
 
 import torch
+
 from invokeai.backend.model_manager import AnyModel
+
 from .model_cache_base import CacheRecord, ModelCacheBase, ModelLockerBase
 
 

From c80c0f0fb9fe9ba9e9e9078ffafa0c172e697be2 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 26 Feb 2024 17:36:03 +1100
Subject: [PATCH 307/411] fix(mm): fix ModelCacheBase method name

---
 .../backend/model_manager/load/model_cache/model_cache_base.py  | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/invokeai/backend/model_manager/load/model_cache/model_cache_base.py b/invokeai/backend/model_manager/load/model_cache/model_cache_base.py
index 4a4a3c7d29..eb82f87cb2 100644
--- a/invokeai/backend/model_manager/load/model_cache/model_cache_base.py
+++ b/invokeai/backend/model_manager/load/model_cache/model_cache_base.py
@@ -111,7 +111,7 @@ class ModelCacheBase(ABC, Generic[T]):
         pass
 
     @abstractmethod
-    def move_model_to_device(self, cache_entry: CacheRecord[AnyModel], device: torch.device) -> None:
+    def move_model_to_device(self, cache_entry: CacheRecord[AnyModel], target_device: torch.device) -> None:
         """Move model into the indicated device."""
         pass
 

From 630d3615cadf2348b1ef6b529322ba100fd1502d Mon Sep 17 00:00:00 2001
From: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Date: Mon, 26 Feb 2024 12:29:13 -0500
Subject: [PATCH 308/411] fix base model grouping in combobox

---
 .../frontend/web/src/common/hooks/useGroupedModelCombobox.ts    | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/invokeai/frontend/web/src/common/hooks/useGroupedModelCombobox.ts b/invokeai/frontend/web/src/common/hooks/useGroupedModelCombobox.ts
index fc5bc455ee..2fffd7bda0 100644
--- a/invokeai/frontend/web/src/common/hooks/useGroupedModelCombobox.ts
+++ b/invokeai/frontend/web/src/common/hooks/useGroupedModelCombobox.ts
@@ -35,7 +35,7 @@ export const useGroupedModelCombobox = <T extends AnyModelConfig>(
       return [];
     }
     const modelEntitiesArray = map(modelEntities.entities);
-    const groupedModels = groupBy(modelEntitiesArray, 'base_model');
+    const groupedModels = groupBy(modelEntitiesArray, 'base');
     const _options = reduce(
       groupedModels,
       (acc, val, label) => {

From c954cd4c8daf2823e92393a42517bc35a9ddc79a Mon Sep 17 00:00:00 2001
From: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Date: Mon, 26 Feb 2024 12:29:28 -0500
Subject: [PATCH 309/411] fix TI appearing as key in prompt

---
 .../frontend/web/src/features/embedding/EmbeddingSelect.tsx     | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/invokeai/frontend/web/src/features/embedding/EmbeddingSelect.tsx b/invokeai/frontend/web/src/features/embedding/EmbeddingSelect.tsx
index a5ad358fa0..848cb04386 100644
--- a/invokeai/frontend/web/src/features/embedding/EmbeddingSelect.tsx
+++ b/invokeai/frontend/web/src/features/embedding/EmbeddingSelect.tsx
@@ -31,7 +31,7 @@ export const EmbeddingSelect = memo(({ onSelect, onClose }: EmbeddingSelectProps
       if (!embedding) {
         return;
       }
-      onSelect(embedding.key);
+      onSelect(embedding.name);
     },
     [onSelect]
   );

From 77b8eed51b2477e654e351f79d4ad41b7c64cd0a Mon Sep 17 00:00:00 2001
From: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Date: Mon, 26 Feb 2024 14:40:38 -0500
Subject: [PATCH 310/411] fix literal strings in MM UI

---
 invokeai/frontend/web/public/locales/en.json  | 17 ++++++-
 .../components/ControlAdapterConfig.tsx       |  3 +-
 .../AddModelPanel/AdvancedImport.tsx          | 24 +++++-----
 .../ScanModels/ScanModelsResults.tsx          |  5 ++-
 .../modelManagerV2/subpanels/ImportModels.tsx | 10 +++--
 .../modelManagerV2/subpanels/ModelManager.tsx |  6 ++-
 .../ModelManagerPanel/ModelTypeFilter.tsx     |  6 ++-
 .../subpanels/ModelPanel/ModelEdit.tsx        | 38 ++++++++--------
 .../subpanels/ModelPanel/ModelView.tsx        | 44 +++++++++++--------
 9 files changed, 90 insertions(+), 63 deletions(-)

diff --git a/invokeai/frontend/web/public/locales/en.json b/invokeai/frontend/web/public/locales/en.json
index d25f7f938b..b31fa5d93c 100644
--- a/invokeai/frontend/web/public/locales/en.json
+++ b/invokeai/frontend/web/public/locales/en.json
@@ -692,6 +692,7 @@
         "addDiffuserModel": "Add Diffusers",
         "addManually": "Add Manually",
         "addModel": "Add Model",
+        "addModels": "Add Models",
         "addNew": "Add New",
         "addNewModel": "Add New Model",
         "addSelected": "Add Selected",
@@ -736,6 +737,7 @@
         "descriptionValidationMsg": "Add a description for your model",
         "deselectAll": "Deselect All",
         "diffusersModels": "Diffusers",
+        "edit": "Edit",
         "findModels": "Find Models",
         "formMessageDiffusersModelLocation": "Diffusers Model Location",
         "formMessageDiffusersModelLocationDesc": "Please enter at least one.",
@@ -744,6 +746,7 @@
         "height": "Height",
         "heightValidationMsg": "Default height of your model.",
         "ignoreMismatch": "Ignore Mismatches Between Selected Models",
+        "imageEncoderModelId": "Image Encoder Model ID",
         "importModels": "Import Models",
         "importQueue": "Import Queue",
         "inpainting": "v1 Inpainting",
@@ -774,8 +777,11 @@
         "modelMergeHeaderHelp1": "You can merge up to three different models to create a blend that suits your needs.",
         "modelMergeHeaderHelp2": "Only Diffusers are available for merging. If you want to merge a checkpoint model, please convert it to Diffusers first.",
         "modelMergeInterpAddDifferenceHelp": "In this mode, Model 3 is first subtracted from Model 2. The resulting version is blended with Model 1 with the alpha rate set above.",
+        "modelMetadata": "Model Metadata",
+        "modelName": "Model Name",
         "modelOne": "Model 1",
         "modelsFound": "Models Found",
+        "modelSettings": "Model Settings",
         "modelsMerged": "Models Merged",
         "modelsMergeFailed": "Model Merge Failed",
         "modelsSynced": "Models Synced",
@@ -795,20 +801,24 @@
         "notLoaded": "not loaded",
         "oliveModels": "Olives",
         "onnxModels": "Onnx",
+        "path": "Path",
         "pathToCustomConfig": "Path To Custom Config",
         "pickModelType": "Pick Model Type",
-        "predictionType": "Prediction Type (for Stable Diffusion 2.x Models and occasional Stable Diffusion 1.x Models)",
+        "predictionType": "Prediction Type",
         "prune": "Prune",
         "pruneTooltip": "Prune finished imports from queue",
         "quickAdd": "Quick Add",
         "removeFromQueue": "Remove From Queue",
         "repo_id": "Repo ID",
         "repoIDValidationMsg": "Online repository of your model",
+        "repoVariant": "Repo Variant",
         "safetensorModels": "SafeTensors",
         "sameFolder": "Same folder",
+        "scan": "Scan",
         "scanFolder": "Scan folder",
         "scanAgain": "Scan Again",
         "scanForModels": "Scan For Models",
+        "scanResults": "Scan Results",
         "search": "Search",
         "selectAll": "Select All",
         "selectAndAdd": "Select and Add Models Listed Below",
@@ -819,9 +829,11 @@
         "showExisting": "Show Existing",
         "sigmoid": "Sigmoid",
         "simpleModelDesc": "Provide a path to a local Diffusers model, local checkpoint / safetensors model a HuggingFace Repo ID, or a checkpoint/diffusers model URL.",
+        "source": "Source",
         "statusConverting": "Converting",
         "syncModels": "Sync Models",
         "syncModelsDesc": "If your models are out of sync with the backend, you can refresh them up using this option. This is generally handy in cases where you add models to the InvokeAI root folder or autoimport directory after the application has booted.",
+        "upcastAttention": "Upcast Attention",
         "updateModel": "Update Model",
         "useCustomConfig": "Use Custom Config",
         "v1": "v1",
@@ -836,7 +848,8 @@
         "variant": "Variant",
         "weightedSum": "Weighted Sum",
         "width": "Width",
-        "widthValidationMsg": "Default width of your model."
+        "widthValidationMsg": "Default width of your model.",
+        "ztsnrTraining": "ZTSNR Training"
     },
     "models": {
         "addLora": "Add LoRA",
diff --git a/invokeai/frontend/web/src/features/controlAdapters/components/ControlAdapterConfig.tsx b/invokeai/frontend/web/src/features/controlAdapters/components/ControlAdapterConfig.tsx
index 6124823808..2497e5b16b 100644
--- a/invokeai/frontend/web/src/features/controlAdapters/components/ControlAdapterConfig.tsx
+++ b/invokeai/frontend/web/src/features/controlAdapters/components/ControlAdapterConfig.tsx
@@ -20,7 +20,6 @@ import ControlAdapterShouldAutoConfig from './ControlAdapterShouldAutoConfig';
 import ControlNetCanvasImageImports from './imports/ControlNetCanvasImageImports';
 import { ParamControlAdapterBeginEnd } from './parameters/ParamControlAdapterBeginEnd';
 import ParamControlAdapterControlMode from './parameters/ParamControlAdapterControlMode';
-import ParamControlAdapterModel from './parameters/ParamControlAdapterModel';
 import ParamControlAdapterProcessorSelect from './parameters/ParamControlAdapterProcessorSelect';
 import ParamControlAdapterResizeMode from './parameters/ParamControlAdapterResizeMode';
 import ParamControlAdapterWeight from './parameters/ParamControlAdapterWeight';
@@ -73,7 +72,7 @@ const ControlAdapterConfig = (props: { id: string; number: number }) => {
       </Flex>
       <Flex gap={4} alignItems="center">
         <Box minW={0} w="full" transitionProperty="common" transitionDuration="0.1s">
-          <ParamControlAdapterModel id={id} />
+          {/* <ParamControlAdapterModel id={id} /> */}
         </Box>
         {activeTabName === 'unifiedCanvas' && <ControlNetCanvasImageImports id={id} />}
         <IconButton
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImport.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImport.tsx
index b2fd094582..cd5c5ab4e9 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImport.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImport.tsx
@@ -126,7 +126,7 @@ export const AdvancedImport = () => {
         <Flex flexDirection="column" gap={4} width="100%" pb={10}>
           <Flex alignItems="flex-end" gap="4">
             <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-              <FormLabel>Model Type</FormLabel>
+              <FormLabel>{t('modelManager.modelType')}</FormLabel>
               <ModelTypeSelect<AnyModelConfig> control={control} name="type" />
             </FormControl>
             <Text px="2" fontSize="xs" textAlign="center">
@@ -157,17 +157,17 @@ export const AdvancedImport = () => {
             </Flex>
             <Flex gap={4}>
               <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-                <FormLabel>Base Model</FormLabel>
+                <FormLabel>{t('modelManager.baseModel')}</FormLabel>
                 <BaseModelSelect<AnyModelConfig> control={control} name="base" />
               </FormControl>
               <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-                <FormLabel>Format</FormLabel>
+                <FormLabel>{t('common.format')}</FormLabel>
                 <ModelFormatSelect<AnyModelConfig> control={control} name="format" />
               </FormControl>
             </Flex>
             <Flex gap={4}>
               <FormControl flexDir="column" alignItems="flex-start" gap={1} isInvalid={Boolean(errors.path)}>
-                <FormLabel>Path</FormLabel>
+                <FormLabel>{t('modelManager.path')}</FormLabel>
                 <Input
                   {...register('path', {
                     validate: (value) => value.trim().length > 0 || 'Must provide a path',
@@ -181,39 +181,39 @@ export const AdvancedImport = () => {
                 <Flex gap={4}>
                   {watchedModelFormat === 'diffusers' && (
                     <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-                      <FormLabel>Repo Variant</FormLabel>
+                      <FormLabel>{t('modelManager.repoVariant')}</FormLabel>
                       <RepoVariantSelect<AnyModelConfig> control={control} name="repo_variant" />
                     </FormControl>
                   )}
                   {watchedModelFormat === 'checkpoint' && (
                     <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-                      <FormLabel>Config Path</FormLabel>
+                      <FormLabel>{t('modelManager.pathToConfig')}</FormLabel>
                       <Input {...register('config')} />
                     </FormControl>
                   )}
 
                   <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-                    <FormLabel>Variant</FormLabel>
+                    <FormLabel>{t('modelManager.variant')}</FormLabel>
                     <ModelVariantSelect<AnyModelConfig> control={control} name="variant" />
                   </FormControl>
                 </Flex>
                 <Flex gap={4}>
                   <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-                    <FormLabel>Prediction Type</FormLabel>
+                    <FormLabel>{t('modelManager.predictionType')}</FormLabel>
                     <PredictionTypeSelect<AnyModelConfig> control={control} name="prediction_type" />
                   </FormControl>
                   <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-                    <FormLabel>Upcast Attention</FormLabel>
+                    <FormLabel>{t('modelManager.upcastAttention')}</FormLabel>
                     <BooleanSelect<AnyModelConfig> control={control} name="upcast_attention" />
                   </FormControl>
                 </Flex>
                 <Flex gap={4}>
                   <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-                    <FormLabel>ZTSNR Training</FormLabel>
+                    <FormLabel>{t('modelManager.ztsnrTraining')}</FormLabel>
                     <BooleanSelect<AnyModelConfig> control={control} name="ztsnr_training" />
                   </FormControl>
                   <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-                    <FormLabel>VAE Path</FormLabel>
+                    <FormLabel>{t('modelManager.vaeLocation')}</FormLabel>
                     <Input {...register('vae')} />
                   </FormControl>
                 </Flex>
@@ -222,7 +222,7 @@ export const AdvancedImport = () => {
             {watchedModelType === 'ip_adapter' && (
               <Flex gap={4}>
                 <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-                  <FormLabel>Image Encoder Model ID</FormLabel>
+                  <FormLabel>{t('modelManager.imageEncoderModelId')}</FormLabel>
                   <Input {...register('image_encoder_model_id')} />
                 </FormControl>
               </Flex>
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx
index 7a300546b3..cf9439b45d 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx
@@ -1,8 +1,8 @@
 import { Divider, Flex, Heading, IconButton, Input, InputGroup, InputRightElement } from '@invoke-ai/ui-library';
 import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
-import { t } from 'i18next';
 import type { ChangeEventHandler } from 'react';
 import { useCallback, useMemo, useState } from 'react';
+import { useTranslation } from 'react-i18next';
 import { PiXBold } from 'react-icons/pi';
 import type { ScanFolderResponse } from 'services/api/endpoints/models';
 
@@ -13,6 +13,7 @@ type ScanModelResultsProps = {
 };
 
 export const ScanModelsResults = ({ results }: ScanModelResultsProps) => {
+  const { t } = useTranslation();
   const [searchTerm, setSearchTerm] = useState('');
 
   const filteredResults = useMemo(() => {
@@ -36,7 +37,7 @@ export const ScanModelsResults = ({ results }: ScanModelResultsProps) => {
       <Flex flexDir="column" gap={2} mt={4} height="100%">
         <Flex justifyContent="space-between" alignItems="center">
           <Heading fontSize="md" as="h4">
-            Scan Results
+            {t('modelManager.scanResults')}
           </Heading>
           <InputGroup maxW="300px" size="xs">
             <Input
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx
index b90b8e0429..a5e01d1490 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ImportModels.tsx
@@ -1,4 +1,5 @@
 import { Box, Flex, Heading, Tab, TabList, TabPanel, TabPanels, Tabs } from '@invoke-ai/ui-library';
+import { useTranslation } from 'react-i18next';
 
 import { AdvancedImport } from './AddModelPanel/AdvancedImport';
 import { ImportQueue } from './AddModelPanel/ImportQueue/ImportQueue';
@@ -6,17 +7,18 @@ import { ScanModelsForm } from './AddModelPanel/ScanModels/ScanModelsForm';
 import { SimpleImport } from './AddModelPanel/SimpleImport';
 
 export const ImportModels = () => {
+  const { t } = useTranslation();
   return (
     <Flex layerStyle="first" p={3} borderRadius="base" w="full" h="full" flexDir="column" gap={2}>
       <Box w="full" p={2}>
-        <Heading fontSize="xl">Add Model</Heading>
+        <Heading fontSize="xl">{t('modelManager.addModel')}</Heading>
       </Box>
       <Box layerStyle="second" borderRadius="base" w="full" h="50%" overflow="hidden">
         <Tabs variant="collapse" height="100%">
           <TabList>
-            <Tab>Simple</Tab>
-            <Tab>Advanced</Tab>
-            <Tab>Scan</Tab>
+            <Tab>{t('common.simple')}</Tab>
+            <Tab>{t('modelManager.advanced')}</Tab>
+            <Tab>{t('modelManager.scan')}</Tab>
           </TabList>
           <TabPanels p={3} height="100%">
             <TabPanel>
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManager.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManager.tsx
index 012b2ef2e6..2a9b0e382c 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManager.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManager.tsx
@@ -3,11 +3,13 @@ import { useAppDispatch } from 'app/store/storeHooks';
 import { SyncModelsIconButton } from 'features/modelManagerV2/components/SyncModels/SyncModelsIconButton';
 import { setSelectedModelKey } from 'features/modelManagerV2/store/modelManagerV2Slice';
 import { useCallback } from 'react';
+import { useTranslation } from 'react-i18next';
 
 import ModelList from './ModelManagerPanel/ModelList';
 import { ModelListNavigation } from './ModelManagerPanel/ModelListNavigation';
 
 export const ModelManager = () => {
+  const { t } = useTranslation();
   const dispatch = useAppDispatch();
   const handleClickAddModel = useCallback(() => {
     dispatch(setSelectedModelKey(null));
@@ -17,11 +19,11 @@ export const ModelManager = () => {
     <Box layerStyle="first" p={3} borderRadius="base" w="50%" h="full">
       <Flex w="full" p={3} justifyContent="space-between" alignItems="center">
         <Flex gap={2}>
-          <Heading fontSize="xl">Model Manager</Heading>
+          <Heading fontSize="xl">{t('common.modelManager')}</Heading>
           <SyncModelsIconButton />
         </Flex>
         <Button colorScheme="invokeYellow" onClick={handleClickAddModel}>
-          Add Models
+          {t('modelManager.addModels')}
         </Button>
       </Flex>
       <Box layerStyle="second" p={3} borderRadius="base" w="full" h="full">
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelTypeFilter.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelTypeFilter.tsx
index c9592d6102..b58719078f 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelTypeFilter.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelTypeFilter.tsx
@@ -2,6 +2,7 @@ import { Button, Menu, MenuButton, MenuItem, MenuList } from '@invoke-ai/ui-libr
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { setFilteredModelType } from 'features/modelManagerV2/store/modelManagerV2Slice';
 import { useCallback } from 'react';
+import { useTranslation } from 'react-i18next';
 import { IoFilter } from 'react-icons/io5';
 
 export const MODEL_TYPE_LABELS: { [key: string]: string } = {
@@ -17,6 +18,7 @@ export const MODEL_TYPE_LABELS: { [key: string]: string } = {
 };
 
 export const ModelTypeFilter = () => {
+  const { t } = useTranslation();
   const dispatch = useAppDispatch();
   const filteredModelType = useAppSelector((s) => s.modelmanagerV2.filteredModelType);
 
@@ -34,10 +36,10 @@ export const ModelTypeFilter = () => {
   return (
     <Menu>
       <MenuButton as={Button} leftIcon={<IoFilter />}>
-        {filteredModelType ? MODEL_TYPE_LABELS[filteredModelType] : 'All Models'}
+        {filteredModelType ? MODEL_TYPE_LABELS[filteredModelType] : t('modelManager.allModels')}
       </MenuButton>
       <MenuList>
-        <MenuItem onClick={clearModelType}>All Models</MenuItem>
+        <MenuItem onClick={clearModelType}>{t('modelManager.allModels')}</MenuItem>
         {Object.keys(MODEL_TYPE_LABELS).map((option) => (
           <MenuItem
             key={option}
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx
index 8b9142fc45..2391bf33ad 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx
@@ -143,18 +143,18 @@ export const ModelEdit = () => {
   }, [dispatch]);
 
   if (isLoading) {
-    return <Text>Loading</Text>;
+    return <Text>{t('common.loading')}</Text>;
   }
 
   if (!modelData) {
-    return <Text>Something went wrong</Text>;
+    return <Text>{t('common.somethingWentWrong')}</Text>;
   }
   return (
     <Flex flexDir="column" h="full">
       <form onSubmit={handleSubmit(onSubmit)}>
         <FormControl flexDir="column" alignItems="flex-start" gap={1} isInvalid={Boolean(errors.name)}>
           <Flex w="full" justifyContent="space-between" gap={4} alignItems="center">
-            <FormLabel hidden={true}>Model Name</FormLabel>
+            <FormLabel hidden={true}>{t('modelManager.modelName')}</FormLabel>
             <Input
               {...register('name', {
                 validate: (value) => value.trim().length > 3 || 'Must be at least 3 characters',
@@ -164,7 +164,7 @@ export const ModelEdit = () => {
 
             <Flex gap={2}>
               <Button size="sm" onClick={handleClickCancel}>
-                Cancel
+                {t('common.cancel')}
               </Button>
               <Button
                 size="sm"
@@ -173,7 +173,7 @@ export const ModelEdit = () => {
                 isLoading={isSubmitting}
                 isDisabled={Boolean(Object.keys(errors).length)}
               >
-                Save
+                {t('common.save')}
               </Button>
             </Flex>
           </Flex>
@@ -183,30 +183,30 @@ export const ModelEdit = () => {
         <Flex flexDir="column" gap={3} mt="4">
           <Flex>
             <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-              <FormLabel>Description</FormLabel>
+              <FormLabel>{t('modelManager.description')}</FormLabel>
               <Textarea fontSize="md" resize="none" {...register('description')} />
             </FormControl>
           </Flex>
           <Heading as="h3" fontSize="md" mt="4">
-            Model Settings
+            {t('modelManager.modelSettings')}
           </Heading>
           <Flex gap={4}>
             <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-              <FormLabel>Base Model</FormLabel>
+              <FormLabel>{t('modelManager.baseModel')}</FormLabel>
               <BaseModelSelect<AnyModelConfig> control={control} name="base" />
             </FormControl>
             <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-              <FormLabel>Model Type</FormLabel>
+              <FormLabel>{t('modelManager.modelType')}</FormLabel>
               <ModelTypeSelect<AnyModelConfig> control={control} name="type" />
             </FormControl>
           </Flex>
           <Flex gap={4}>
             <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-              <FormLabel>Format</FormLabel>
+              <FormLabel>{t('common.format')}</FormLabel>
               <ModelFormatSelect<AnyModelConfig> control={control} name="format" />
             </FormControl>
             <FormControl flexDir="column" alignItems="flex-start" gap={1} isInvalid={Boolean(errors.path)}>
-              <FormLabel>Path</FormLabel>
+              <FormLabel>{t('modelManager.path')}</FormLabel>
               <Input
                 {...register('path', {
                   validate: (value) => value.trim().length > 0 || 'Must provide a path',
@@ -220,39 +220,39 @@ export const ModelEdit = () => {
               <Flex gap={4}>
                 {watchedModelFormat === 'diffusers' && (
                   <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-                    <FormLabel>Repo Variant</FormLabel>
+                    <FormLabel>{t('modelManager.repoVariant')}</FormLabel>
                     <RepoVariantSelect<AnyModelConfig> control={control} name="repo_variant" />
                   </FormControl>
                 )}
                 {watchedModelFormat === 'checkpoint' && (
                   <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-                    <FormLabel>Config Path</FormLabel>
+                    <FormLabel>{t('modelManager.pathToConfig')}</FormLabel>
                     <Input {...register('config')} />
                   </FormControl>
                 )}
 
                 <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-                  <FormLabel>Variant</FormLabel>
+                  <FormLabel>{t('modelManager.variant')}</FormLabel>
                   <ModelVariantSelect<AnyModelConfig> control={control} name="variant" />
                 </FormControl>
               </Flex>
               <Flex gap={4}>
                 <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-                  <FormLabel>Prediction Type</FormLabel>
+                  <FormLabel>{t('modelManager.predictionType')}</FormLabel>
                   <PredictionTypeSelect<AnyModelConfig> control={control} name="prediction_type" />
                 </FormControl>
                 <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-                  <FormLabel>Upcast Attention</FormLabel>
+                  <FormLabel>{t('modelManager.upcastAttention')}</FormLabel>
                   <BooleanSelect<AnyModelConfig> control={control} name="upcast_attention" />
                 </FormControl>
               </Flex>
               <Flex gap={4}>
                 <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-                  <FormLabel>ZTSNR Training</FormLabel>
+                  <FormLabel>{t('modelManager.ztsnrTraining')}</FormLabel>
                   <BooleanSelect<AnyModelConfig> control={control} name="ztsnr_training" />
                 </FormControl>
                 <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-                  <FormLabel>VAE Path</FormLabel>
+                  <FormLabel>{t('modelManager.vaeLocation')}</FormLabel>
                   <Input {...register('vae')} />
                 </FormControl>
               </Flex>
@@ -261,7 +261,7 @@ export const ModelEdit = () => {
           {watchedModelType === 'ip_adapter' && (
             <Flex gap={4}>
               <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-                <FormLabel>Image Encoder Model ID</FormLabel>
+                <FormLabel>{t('modelManager.imageEncoderModelId')}</FormLabel>
                 <Input {...register('image_encoder_model_id')} />
               </FormControl>
             </Flex>
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx
index 6c907b3cd8..2acbfe8b3e 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx
@@ -4,6 +4,7 @@ import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import DataViewer from 'features/gallery/components/ImageMetadataViewer/DataViewer';
 import { setSelectedModelMode } from 'features/modelManagerV2/store/modelManagerV2Slice';
 import { useCallback, useMemo } from 'react';
+import { useTranslation } from 'react-i18next';
 import { IoPencil } from 'react-icons/io5';
 import { useGetModelConfigQuery, useGetModelMetadataQuery } from 'services/api/endpoints/models';
 import type {
@@ -21,6 +22,7 @@ import { ModelAttrView } from './ModelAttrView';
 import { ModelConvert } from './ModelConvert';
 
 export const ModelView = () => {
+  const { t } = useTranslation();
   const dispatch = useAppDispatch();
   const selectedModelKey = useAppSelector((s) => s.modelmanagerV2.selectedModelKey);
   const { data, isLoading } = useGetModelConfigQuery(selectedModelKey ?? skipToken);
@@ -64,11 +66,11 @@ export const ModelView = () => {
   }, [dispatch]);
 
   if (isLoading) {
-    return <Text>Loading</Text>;
+    return <Text>{t('common.loading')}</Text>;
   }
 
   if (!modelData) {
-    return <Text>Something went wrong</Text>;
+    return <Text>{t('common.somethingWentWrong')}</Text>;
   }
   return (
     <Flex flexDir="column" h="full">
@@ -78,11 +80,15 @@ export const ModelView = () => {
             {modelData.name}
           </Heading>
 
-          {modelData.source && <Text variant="subtext">Source: {modelData.source}</Text>}
+          {modelData.source && (
+            <Text variant="subtext">
+              {t('modelManager.source')}: {modelData.source}
+            </Text>
+          )}
         </Flex>
         <Flex gap={2}>
           <Button size="sm" leftIcon={<IoPencil />} colorScheme="invokeYellow" onClick={handleEditModel}>
-            Edit
+            {t('modelManager.edit')}
           </Button>
           {modelData.type === 'main' && modelData.format === 'checkpoint' && <ModelConvert model={modelData} />}
         </Flex>
@@ -93,41 +99,43 @@ export const ModelView = () => {
           <ModelAttrView label="Description" value={modelData.description} />
         </Flex>
         <Heading as="h3" fontSize="md" mt="4">
-          Model Settings
+          {t('modelManager.modelSettings')}
         </Heading>
         <Box layerStyle="second" borderRadius="base" p={3}>
           <Flex flexDir="column" gap={3}>
             <Flex gap={2}>
-              <ModelAttrView label="Base Model" value={modelData.base} />
-              <ModelAttrView label="Model Type" value={modelData.type} />
+              <ModelAttrView label={t('modelManager.baseModel')} value={modelData.base} />
+              <ModelAttrView label={t('modelManager.modelType')} value={modelData.type} />
             </Flex>
             <Flex gap={2}>
-              <ModelAttrView label="Format" value={modelData.format} />
-              <ModelAttrView label="Path" value={modelData.path} />
+              <ModelAttrView label={t('common.format')} value={modelData.format} />
+              <ModelAttrView label={t('modelManager.path')} value={modelData.path} />
             </Flex>
             {modelData.type === 'main' && (
               <>
                 <Flex gap={2}>
                   {modelData.format === 'diffusers' && (
-                    <ModelAttrView label="Repo Variant" value={modelData.repo_variant} />
+                    <ModelAttrView label={t('modelManager.repoVariant')} value={modelData.repo_variant} />
+                  )}
+                  {modelData.format === 'checkpoint' && (
+                    <ModelAttrView label={t('modelManager.pathToConfig')} value={modelData.config} />
                   )}
-                  {modelData.format === 'checkpoint' && <ModelAttrView label="Config Path" value={modelData.config} />}
 
-                  <ModelAttrView label="Variant" value={modelData.variant} />
+                  <ModelAttrView label={t('modelManager.variant')} value={modelData.variant} />
                 </Flex>
                 <Flex gap={2}>
-                  <ModelAttrView label="Prediction Type" value={modelData.prediction_type} />
-                  <ModelAttrView label="Upcast Attention" value={`${modelData.upcast_attention}`} />
+                  <ModelAttrView label={t('modelManager.predictionType')} value={modelData.prediction_type} />
+                  <ModelAttrView label={t('modelManager.upcastAttention')} value={`${modelData.upcast_attention}`} />
                 </Flex>
                 <Flex gap={2}>
-                  <ModelAttrView label="ZTSNR Training" value={`${modelData.ztsnr_training}`} />
-                  <ModelAttrView label="VAE" value={modelData.vae} />
+                  <ModelAttrView label={t('modelManager.ztsnrTraining')} value={`${modelData.ztsnr_training}`} />
+                  <ModelAttrView label={t('modelManager.vae')} value={modelData.vae} />
                 </Flex>
               </>
             )}
             {modelData.type === 'ip_adapter' && (
               <Flex gap={2}>
-                <ModelAttrView label="Image Encoder Model ID" value={modelData.image_encoder_model_id} />
+                <ModelAttrView label={t('modelManager.imageEncoderModelId')} value={modelData.image_encoder_model_id} />
               </Flex>
             )}
           </Flex>
@@ -137,7 +145,7 @@ export const ModelView = () => {
       {metadata && (
         <>
           <Heading as="h3" fontSize="md" mt="4">
-            Model Metadata
+            {t('modelManager.modelMetadata')}
           </Heading>
           <Flex h="full" w="full" p={2}>
             <DataViewer label="metadata" data={metadata} />

From e20a506e408ed09b9b902c9a0864367df11d0756 Mon Sep 17 00:00:00 2001
From: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Date: Mon, 26 Feb 2024 14:41:45 -0500
Subject: [PATCH 311/411] undo

---
 .../controlAdapters/components/ControlAdapterConfig.tsx         | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/invokeai/frontend/web/src/features/controlAdapters/components/ControlAdapterConfig.tsx b/invokeai/frontend/web/src/features/controlAdapters/components/ControlAdapterConfig.tsx
index 2497e5b16b..baf2d412c2 100644
--- a/invokeai/frontend/web/src/features/controlAdapters/components/ControlAdapterConfig.tsx
+++ b/invokeai/frontend/web/src/features/controlAdapters/components/ControlAdapterConfig.tsx
@@ -72,7 +72,7 @@ const ControlAdapterConfig = (props: { id: string; number: number }) => {
       </Flex>
       <Flex gap={4} alignItems="center">
         <Box minW={0} w="full" transitionProperty="common" transitionDuration="0.1s">
-          {/* <ParamControlAdapterModel id={id} /> */}
+          <ParamControlAdapterModel id={id} />
         </Box>
         {activeTabName === 'unifiedCanvas' && <ControlNetCanvasImageImports id={id} />}
         <IconButton

From 8d8f1abd502318c5652f1b2c054f9c84f985f654 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Fri, 23 Feb 2024 09:53:23 +1100
Subject: [PATCH 312/411] feat(api): add MM `get_by_attrs` route

Gets the first model that matches the given name, base and type. Raises 404 if there isn't one.

This will be used for backwards compatibility with old metadata.
---
 invokeai/app/api/routers/model_manager.py | 21 +++++++++++++++++++++
 1 file changed, 21 insertions(+)

diff --git a/invokeai/app/api/routers/model_manager.py b/invokeai/app/api/routers/model_manager.py
index c27fc0e0de..c27dba978a 100644
--- a/invokeai/app/api/routers/model_manager.py
+++ b/invokeai/app/api/routers/model_manager.py
@@ -165,6 +165,27 @@ async def list_model_records(
     return ModelsList(models=found_models)
 
 
+@model_manager_router.get(
+    "/get_by_attrs",
+    operation_id="get_model_records_by_attrs",
+    response_model=AnyModelConfig,
+)
+async def get_model_records_by_attrs(
+    name: str = Query(description="The name of the model"),
+    type: ModelType = Query(description="The type of the model"),
+    base: BaseModelType = Query(description="The base model of the model"),
+) -> AnyModelConfig:
+    """Gets a model by its attributes. The main use of this route is to provide backwards compatibility with the old
+    model manager, which identified models by a combination of name, base and type."""
+    configs = ApiDependencies.invoker.services.model_manager.store.search_by_attr(
+        base_model=base, model_type=type, model_name=name
+    )
+    if not configs:
+        raise HTTPException(status_code=404, detail="No model found with these attributes")
+
+    return configs[0]
+
+
 @model_manager_router.get(
     "/i/{key}",
     operation_id="get_model_record",

From 4d5458648b8acc59bd9680fbbe14c42bab685e6c Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Fri, 23 Feb 2024 09:53:33 +1100
Subject: [PATCH 313/411] chore(ui): typegen

---
 .../frontend/web/src/services/api/schema.ts   | 43 ++++++++++++++++++-
 1 file changed, 41 insertions(+), 2 deletions(-)

diff --git a/invokeai/frontend/web/src/services/api/schema.ts b/invokeai/frontend/web/src/services/api/schema.ts
index c033ba89a2..beb13e4070 100644
--- a/invokeai/frontend/web/src/services/api/schema.ts
+++ b/invokeai/frontend/web/src/services/api/schema.ts
@@ -19,6 +19,14 @@ export type paths = {
      */
     get: operations["list_model_records"];
   };
+  "/api/v2/models/get_by_attrs": {
+    /**
+     * Get Model Records By Attrs
+     * @description Gets a model by its attributes. The main use of this route is to provide backwards compatibility with the old
+     * model manager, which identified models by a combination of name, base and type.
+     */
+    get: operations["get_model_records_by_attrs"];
+  };
   "/api/v2/models/i/{key}": {
     /**
      * Get Model Record
@@ -4331,7 +4339,7 @@ export type components = {
        * @description The nodes in this graph
        */
       nodes: {
-        [key: string]: components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["ColorMapImageProcessorInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["CanvasPasteBackInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["DWOpenposeImageProcessorInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["CreateGradientMaskInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["DepthAnythingImageProcessorInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["PidiImageProcessorInvocation"];
+        [key: string]: components["schemas"]["RandomRangeInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["CanvasPasteBackInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["ColorMapImageProcessorInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["CreateGradientMaskInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["DWOpenposeImageProcessorInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["DepthAnythingImageProcessorInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["ImageInverseLerpInvocation"];
       };
       /**
        * Edges
@@ -4368,7 +4376,7 @@ export type components = {
        * @description The results of node executions
        */
       results: {
-        [key: string]: components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["String2Output"] | components["schemas"]["LoraLoaderOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["SDXLLoraLoaderOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["LatentsOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["VAEOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["ClipSkipInvocationOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["MetadataOutput"];
+        [key: string]: components["schemas"]["VAEOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["String2Output"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["LatentsOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["SDXLLoraLoaderOutput"] | components["schemas"]["MetadataOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["ClipSkipInvocationOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["LoraLoaderOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["FloatOutput"];
       };
       /**
        * Errors
@@ -11299,6 +11307,37 @@ export type operations = {
       };
     };
   };
+  /**
+   * Get Model Records By Attrs
+   * @description Gets a model by its attributes. The main use of this route is to provide backwards compatibility with the old
+   * model manager, which identified models by a combination of name, base and type.
+   */
+  get_model_records_by_attrs: {
+    parameters: {
+      query: {
+        /** @description The name of the model */
+        name: string;
+        /** @description The type of the model */
+        type: components["schemas"]["ModelType"];
+        /** @description The base model of the model */
+        base: components["schemas"]["BaseModelType"];
+      };
+    };
+    responses: {
+      /** @description Successful Response */
+      200: {
+        content: {
+          "application/json": (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["ONNXSD1Config"] | components["schemas"]["ONNXSD2Config"] | components["schemas"]["ONNXSDXLConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
+        };
+      };
+      /** @description Validation Error */
+      422: {
+        content: {
+          "application/json": components["schemas"]["HTTPValidationError"];
+        };
+      };
+    };
+  };
   /**
    * Get Model Record
    * @description Get a model record

From 90327cb52149dee73531a4ff7160a142250be70e Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 24 Feb 2024 17:01:38 +1100
Subject: [PATCH 314/411] build(ui): do not fail build on eslint error in dev
 mode

---
 invokeai/frontend/web/vite.config.mts | 7 ++++++-
 1 file changed, 6 insertions(+), 1 deletion(-)

diff --git a/invokeai/frontend/web/vite.config.mts b/invokeai/frontend/web/vite.config.mts
index ae64b7198d..21edc076db 100644
--- a/invokeai/frontend/web/vite.config.mts
+++ b/invokeai/frontend/web/vite.config.mts
@@ -57,7 +57,12 @@ export default defineConfig(({ mode }) => {
 
   return {
     base: './',
-    plugins: [react(), mode !== 'test' && eslint(), tsconfigPaths(), visualizer() as unknown as PluginOption],
+    plugins: [
+      react(),
+      mode !== 'test' && eslint({ failOnError: mode === 'production', failOnWarning: mode === 'production' }),
+      tsconfigPaths(),
+      visualizer() as unknown as PluginOption,
+    ],
     build: {
       chunkSizeWarningLimit: 1500,
     },

From d1f4cde8c7c2849f5ea6f640b8ee0705603b5a41 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sat, 24 Feb 2024 01:25:58 +1100
Subject: [PATCH 315/411] feat(ui): refactor metadata handling (again)

Add concepts for metadata handlers. Handlers include parsers, recallers and validators for different metadata types:
- Parsers parse a raw metadata object of any shape to a structured object.
- Recallers load the parsed metadata into state. Recallers are optional, as some metadata types don't need to be loaded into state.
- Validators provide an additional layer of validation before recalling the metadata. This is needed because a metadata object may be valid, but not able to be recalled due to some other requirement, like base model compatibility. Validators are optional.

Sometimes metadata is not a single object but a list of items - like LoRAs. Metadata handlers may implement an optional set of "item" handlers which operate on individual items in the list.

Parsers and validators are async to allow fetching additional data, like a model config. Recallers are synchronous.

The these handlers are composed into a public API, exported as a `handlers` object. Besides the handlers functions, a metadata handler set includes:
- A function to get the label of the metadata type.
- An optional function to render the value of the metadata type.
- An optional function to render the _item_ value of the metadata type.
---
 invokeai/frontend/web/public/locales/en.json  |    8 +-
 .../listeners/batchEnqueued.ts                |    7 +-
 .../listeners/bulkDownload.tsx                |    8 +-
 .../frontend/web/src/common/util/toast.ts     |    6 +
 .../ImageMetadataActions.tsx                  |  322 +----
 .../ImageMetadataViewer/ImageMetadataItem.tsx |   51 +-
 .../src/features/lora/components/LoRACard.tsx |   16 +-
 .../web/src/features/lora/store/loraSlice.ts  |   12 +-
 .../components/MetadataControlNets.tsx        |   66 +
 .../components/MetadataIPAdapters.tsx         |   66 +
 .../metadata/components/MetadataItem.tsx      |   33 +
 .../metadata/components/MetadataItemView.tsx  |   29 +
 .../metadata/components/MetadataLoRAs.tsx     |   61 +
 .../components/MetadataT2IAdapters.tsx        |   66 +
 .../metadata/components/RecallButton.tsx      |   27 +
 .../web/src/features/metadata/exceptions.ts   |   27 +
 .../metadata/hooks/useMetadataItem.tsx        |   51 +
 .../web/src/features/metadata/types.ts        |  136 ++
 .../src/features/metadata/util/handlers.tsx   |  316 ++++
 .../web/src/features/metadata/util/parsers.ts |  396 +++++
 .../src/features/metadata/util/recallers.ts   |  295 ++++
 .../src/features/metadata/util/validators.ts  |  117 ++
 .../web/src/features/nodes/types/common.ts    |    5 +
 .../web/src/features/nodes/types/metadata.ts  |   27 +-
 .../parameters/hooks/useRecallParameters.ts   | 1272 ++++++++++-------
 .../parameters/types/parameterSchemas.ts      |   25 +-
 .../parameters/util/modelFetchingHelpers.ts   |   88 +-
 .../parameters/util/modelMetadataHelpers.ts   |  150 --
 .../AdvancedSettingsAccordion.tsx             |    2 +-
 .../web/src/services/api/endpoints/images.ts  |   19 +-
 .../web/src/services/api/endpoints/models.ts  |   15 +
 31 files changed, 2627 insertions(+), 1092 deletions(-)
 create mode 100644 invokeai/frontend/web/src/common/util/toast.ts
 create mode 100644 invokeai/frontend/web/src/features/metadata/components/MetadataControlNets.tsx
 create mode 100644 invokeai/frontend/web/src/features/metadata/components/MetadataIPAdapters.tsx
 create mode 100644 invokeai/frontend/web/src/features/metadata/components/MetadataItem.tsx
 create mode 100644 invokeai/frontend/web/src/features/metadata/components/MetadataItemView.tsx
 create mode 100644 invokeai/frontend/web/src/features/metadata/components/MetadataLoRAs.tsx
 create mode 100644 invokeai/frontend/web/src/features/metadata/components/MetadataT2IAdapters.tsx
 create mode 100644 invokeai/frontend/web/src/features/metadata/components/RecallButton.tsx
 create mode 100644 invokeai/frontend/web/src/features/metadata/exceptions.ts
 create mode 100644 invokeai/frontend/web/src/features/metadata/hooks/useMetadataItem.tsx
 create mode 100644 invokeai/frontend/web/src/features/metadata/types.ts
 create mode 100644 invokeai/frontend/web/src/features/metadata/util/handlers.tsx
 create mode 100644 invokeai/frontend/web/src/features/metadata/util/parsers.ts
 create mode 100644 invokeai/frontend/web/src/features/metadata/util/recallers.ts
 create mode 100644 invokeai/frontend/web/src/features/metadata/util/validators.ts
 delete mode 100644 invokeai/frontend/web/src/features/parameters/util/modelMetadataHelpers.ts

diff --git a/invokeai/frontend/web/public/locales/en.json b/invokeai/frontend/web/public/locales/en.json
index b31fa5d93c..12d06ee224 100644
--- a/invokeai/frontend/web/public/locales/en.json
+++ b/invokeai/frontend/web/public/locales/en.json
@@ -656,6 +656,7 @@
         }
     },
     "metadata": {
+        "allPrompts": "All Prompts",
         "cfgScale": "CFG scale",
         "cfgRescaleMultiplier": "$t(parameters.cfgRescaleMultiplier)",
         "createdBy": "Created By",
@@ -664,6 +665,7 @@
         "height": "Height",
         "hiresFix": "High Resolution Optimization",
         "imageDetails": "Image Details",
+        "imageDimensions": "Image Dimensions",
         "initImage": "Initial image",
         "metadata": "Metadata",
         "model": "Model",
@@ -671,9 +673,11 @@
         "noImageDetails": "No image details found",
         "noMetaData": "No metadata found",
         "noRecallParameters": "No parameters to recall found",
+        "parameterSet": "Parameter {{parameter}} set",
         "perlin": "Perlin Noise",
         "positivePrompt": "Positive Prompt",
         "recallParameters": "Recall Parameters",
+        "recallParameter": "Recall {{label}}",
         "scheduler": "Scheduler",
         "seamless": "Seamless",
         "seed": "Seed",
@@ -1381,8 +1385,8 @@
         "nodesNotValidJSON": "Not a valid JSON",
         "nodesSaved": "Nodes Saved",
         "nodesUnrecognizedTypes": "Cannot load. Graph has unrecognized types",
-        "parameterNotSet": "Parameter not set",
-        "parameterSet": "Parameter set",
+        "parameterNotSet": "{{parameter}} not set",
+        "parameterSet": "{{parameter}} set",
         "parametersFailed": "Problem loading parameters",
         "parametersFailedDesc": "Unable to load init image.",
         "parametersNotSet": "Parameters Not Set",
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/batchEnqueued.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/batchEnqueued.ts
index 6419f840ec..07a1039bef 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/batchEnqueued.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/batchEnqueued.ts
@@ -1,6 +1,6 @@
-import { createStandaloneToast, theme, TOAST_OPTIONS } from '@invoke-ai/ui-library';
 import { logger } from 'app/logging/logger';
 import { parseify } from 'common/util/serialize';
+import { toast } from 'common/util/toast';
 import { zPydanticValidationError } from 'features/system/store/zodSchemas';
 import { t } from 'i18next';
 import { truncate, upperFirst } from 'lodash-es';
@@ -8,11 +8,6 @@ import { queueApi } from 'services/api/endpoints/queue';
 
 import { startAppListening } from '..';
 
-const { toast } = createStandaloneToast({
-  theme: theme,
-  defaultOptions: TOAST_OPTIONS.defaultOptions,
-});
-
 export const addBatchEnqueuedListener = () => {
   // success
   startAppListening({
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/bulkDownload.tsx b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/bulkDownload.tsx
index 69adfb5b67..fa5c962ff5 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/bulkDownload.tsx
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/bulkDownload.tsx
@@ -1,7 +1,8 @@
 import type { UseToastOptions } from '@invoke-ai/ui-library';
-import { createStandaloneToast, ExternalLink, theme, TOAST_OPTIONS } from '@invoke-ai/ui-library';
+import { ExternalLink } from '@invoke-ai/ui-library';
 import { logger } from 'app/logging/logger';
 import { startAppListening } from 'app/store/middleware/listenerMiddleware';
+import { toast } from 'common/util/toast';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
 import {
@@ -12,11 +13,6 @@ import {
 
 const log = logger('images');
 
-const { toast } = createStandaloneToast({
-  theme: theme,
-  defaultOptions: TOAST_OPTIONS.defaultOptions,
-});
-
 export const addBulkDownloadListeners = () => {
   startAppListening({
     matcher: imagesApi.endpoints.bulkDownloadImages.matchFulfilled,
diff --git a/invokeai/frontend/web/src/common/util/toast.ts b/invokeai/frontend/web/src/common/util/toast.ts
new file mode 100644
index 0000000000..ac61a4a12d
--- /dev/null
+++ b/invokeai/frontend/web/src/common/util/toast.ts
@@ -0,0 +1,6 @@
+import { createStandaloneToast, theme, TOAST_OPTIONS } from '@invoke-ai/ui-library';
+
+export const { toast } = createStandaloneToast({
+  theme: theme,
+  defaultOptions: TOAST_OPTIONS.defaultOptions,
+});
diff --git a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataActions.tsx b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataActions.tsx
index 7eec7e1875..cfa679c805 100644
--- a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataActions.tsx
+++ b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataActions.tsx
@@ -1,300 +1,54 @@
-import { isModelIdentifier } from 'features/nodes/types/common';
-import type {
-  ControlNetMetadataItem,
-  CoreMetadata,
-  IPAdapterMetadataItem,
-  LoRAMetadataItem,
-  T2IAdapterMetadataItem,
-} from 'features/nodes/types/metadata';
-import { useRecallParameters } from 'features/parameters/hooks/useRecallParameters';
-import { memo, useCallback, useMemo } from 'react';
-import { useTranslation } from 'react-i18next';
-
-import ImageMetadataItem, { ModelMetadataItem, VAEMetadataItem } from './ImageMetadataItem';
+import { MetadataControlNets } from 'features/metadata/components/MetadataControlNets';
+import { MetadataIPAdapters } from 'features/metadata/components/MetadataIPAdapters';
+import { MetadataItem } from 'features/metadata/components/MetadataItem';
+import { MetadataLoRAs } from 'features/metadata/components/MetadataLoRAs';
+import { MetadataT2IAdapters } from 'features/metadata/components/MetadataT2IAdapters';
+import { handlers } from 'features/metadata/util/handlers';
+import { memo } from 'react';
 
 type Props = {
-  metadata?: CoreMetadata;
+  metadata?: unknown;
 };
 
 const ImageMetadataActions = (props: Props) => {
   const { metadata } = props;
 
-  const { t } = useTranslation();
-
-  const {
-    recallPositivePrompt,
-    recallNegativePrompt,
-    recallSeed,
-    recallCfgScale,
-    recallCfgRescaleMultiplier,
-    recallModel,
-    recallScheduler,
-    recallVaeModel,
-    recallSteps,
-    recallWidth,
-    recallHeight,
-    recallStrength,
-    recallHrfEnabled,
-    recallHrfStrength,
-    recallHrfMethod,
-    recallLoRA,
-    recallControlNet,
-    recallIPAdapter,
-    recallT2IAdapter,
-    recallSDXLPositiveStylePrompt,
-    recallSDXLNegativeStylePrompt,
-  } = useRecallParameters();
-
-  const handleRecallPositivePrompt = useCallback(() => {
-    recallPositivePrompt(metadata?.positive_prompt);
-  }, [metadata?.positive_prompt, recallPositivePrompt]);
-
-  const handleRecallNegativePrompt = useCallback(() => {
-    recallNegativePrompt(metadata?.negative_prompt);
-  }, [metadata?.negative_prompt, recallNegativePrompt]);
-
-  const handleRecallSDXLPositiveStylePrompt = useCallback(() => {
-    recallSDXLPositiveStylePrompt(metadata?.positive_style_prompt);
-  }, [metadata?.positive_style_prompt, recallSDXLPositiveStylePrompt]);
-
-  const handleRecallSDXLNegativeStylePrompt = useCallback(() => {
-    recallSDXLNegativeStylePrompt(metadata?.negative__style_prompt);
-  }, [metadata?.negative__style_prompt, recallSDXLNegativeStylePrompt]);
-
-  const handleRecallSeed = useCallback(() => {
-    recallSeed(metadata?.seed);
-  }, [metadata?.seed, recallSeed]);
-
-  const handleRecallModel = useCallback(() => {
-    recallModel(metadata?.model);
-  }, [metadata?.model, recallModel]);
-
-  const handleRecallWidth = useCallback(() => {
-    recallWidth(metadata?.width);
-  }, [metadata?.width, recallWidth]);
-
-  const handleRecallHeight = useCallback(() => {
-    recallHeight(metadata?.height);
-  }, [metadata?.height, recallHeight]);
-
-  const handleRecallScheduler = useCallback(() => {
-    recallScheduler(metadata?.scheduler);
-  }, [metadata?.scheduler, recallScheduler]);
-
-  const handleRecallVaeModel = useCallback(() => {
-    recallVaeModel(metadata?.vae);
-  }, [metadata?.vae, recallVaeModel]);
-
-  const handleRecallSteps = useCallback(() => {
-    recallSteps(metadata?.steps);
-  }, [metadata?.steps, recallSteps]);
-
-  const handleRecallCfgScale = useCallback(() => {
-    recallCfgScale(metadata?.cfg_scale);
-  }, [metadata?.cfg_scale, recallCfgScale]);
-
-  const handleRecallCfgRescaleMultiplier = useCallback(() => {
-    recallCfgRescaleMultiplier(metadata?.cfg_rescale_multiplier);
-  }, [metadata?.cfg_rescale_multiplier, recallCfgRescaleMultiplier]);
-
-  const handleRecallStrength = useCallback(() => {
-    recallStrength(metadata?.strength);
-  }, [metadata?.strength, recallStrength]);
-
-  const handleRecallHrfEnabled = useCallback(() => {
-    recallHrfEnabled(metadata?.hrf_enabled);
-  }, [metadata?.hrf_enabled, recallHrfEnabled]);
-
-  const handleRecallHrfStrength = useCallback(() => {
-    recallHrfStrength(metadata?.hrf_strength);
-  }, [metadata?.hrf_strength, recallHrfStrength]);
-
-  const handleRecallHrfMethod = useCallback(() => {
-    recallHrfMethod(metadata?.hrf_method);
-  }, [metadata?.hrf_method, recallHrfMethod]);
-
-  const handleRecallLoRA = useCallback(
-    (lora: LoRAMetadataItem) => {
-      recallLoRA(lora);
-    },
-    [recallLoRA]
-  );
-
-  const handleRecallControlNet = useCallback(
-    (controlnet: ControlNetMetadataItem) => {
-      recallControlNet(controlnet);
-    },
-    [recallControlNet]
-  );
-
-  const handleRecallIPAdapter = useCallback(
-    (ipAdapter: IPAdapterMetadataItem) => {
-      recallIPAdapter(ipAdapter);
-    },
-    [recallIPAdapter]
-  );
-
-  const handleRecallT2IAdapter = useCallback(
-    (ipAdapter: T2IAdapterMetadataItem) => {
-      recallT2IAdapter(ipAdapter);
-    },
-    [recallT2IAdapter]
-  );
-
-  const validControlNets: ControlNetMetadataItem[] = useMemo(() => {
-    return metadata?.controlnets
-      ? metadata.controlnets.filter((controlnet) => isModelIdentifier(controlnet.control_model))
-      : [];
-  }, [metadata?.controlnets]);
-
-  const validIPAdapters: IPAdapterMetadataItem[] = useMemo(() => {
-    return metadata?.ipAdapters
-      ? metadata.ipAdapters.filter((ipAdapter) => isModelIdentifier(ipAdapter.ip_adapter_model))
-      : [];
-  }, [metadata?.ipAdapters]);
-
-  const validT2IAdapters: T2IAdapterMetadataItem[] = useMemo(() => {
-    return metadata?.t2iAdapters
-      ? metadata.t2iAdapters.filter((t2iAdapter) => isModelIdentifier(t2iAdapter.t2i_adapter_model))
-      : [];
-  }, [metadata?.t2iAdapters]);
-
   if (!metadata || Object.keys(metadata).length === 0) {
     return null;
   }
 
   return (
     <>
-      {metadata.created_by && <ImageMetadataItem label={t('metadata.createdBy')} value={metadata.created_by} />}
-      {metadata.generation_mode && (
-        <ImageMetadataItem label={t('metadata.generationMode')} value={metadata.generation_mode} />
-      )}
-      {metadata.positive_prompt && (
-        <ImageMetadataItem
-          label={t('metadata.positivePrompt')}
-          labelPosition="top"
-          value={metadata.positive_prompt}
-          onClick={handleRecallPositivePrompt}
-        />
-      )}
-      {metadata.negative_prompt && (
-        <ImageMetadataItem
-          label={t('metadata.negativePrompt')}
-          labelPosition="top"
-          value={metadata.negative_prompt}
-          onClick={handleRecallNegativePrompt}
-        />
-      )}
-      {metadata.positive_style_prompt && (
-        <ImageMetadataItem
-          label={t('sdxl.posStylePrompt')}
-          labelPosition="top"
-          value={metadata.positive_style_prompt}
-          onClick={handleRecallSDXLPositiveStylePrompt}
-        />
-      )}
-      {metadata.negative_style_prompt && (
-        <ImageMetadataItem
-          label={t('sdxl.negStylePrompt')}
-          labelPosition="top"
-          value={metadata.negative_style_prompt}
-          onClick={handleRecallSDXLNegativeStylePrompt}
-        />
-      )}
-      {metadata.seed !== undefined && metadata.seed !== null && (
-        <ImageMetadataItem label={t('metadata.seed')} value={metadata.seed} onClick={handleRecallSeed} />
-      )}
-      {metadata.model !== undefined && metadata.model !== null && metadata.model.key && (
-        <ModelMetadataItem label={t('metadata.model')} modelKey={metadata.model.key} onClick={handleRecallModel} />
-      )}
-      {metadata.width && (
-        <ImageMetadataItem label={t('metadata.width')} value={metadata.width} onClick={handleRecallWidth} />
-      )}
-      {metadata.height && (
-        <ImageMetadataItem label={t('metadata.height')} value={metadata.height} onClick={handleRecallHeight} />
-      )}
-      {metadata.scheduler && (
-        <ImageMetadataItem label={t('metadata.scheduler')} value={metadata.scheduler} onClick={handleRecallScheduler} />
-      )}
-      <VAEMetadataItem label={t('metadata.vae')} modelKey={metadata.vae?.key} onClick={handleRecallVaeModel} />
-      {metadata.steps && (
-        <ImageMetadataItem label={t('metadata.steps')} value={metadata.steps} onClick={handleRecallSteps} />
-      )}
-      {metadata.cfg_scale !== undefined && metadata.cfg_scale !== null && (
-        <ImageMetadataItem label={t('metadata.cfgScale')} value={metadata.cfg_scale} onClick={handleRecallCfgScale} />
-      )}
-      {metadata.cfg_rescale_multiplier !== undefined && metadata.cfg_rescale_multiplier !== null && (
-        <ImageMetadataItem
-          label={t('metadata.cfgRescaleMultiplier')}
-          value={metadata.cfg_rescale_multiplier}
-          onClick={handleRecallCfgRescaleMultiplier}
-        />
-      )}
-      {metadata.strength && (
-        <ImageMetadataItem label={t('metadata.strength')} value={metadata.strength} onClick={handleRecallStrength} />
-      )}
-      {metadata.hrf_enabled && (
-        <ImageMetadataItem
-          label={t('hrf.metadata.enabled')}
-          value={metadata.hrf_enabled}
-          onClick={handleRecallHrfEnabled}
-        />
-      )}
-      {metadata.hrf_enabled && metadata.hrf_strength && (
-        <ImageMetadataItem
-          label={t('hrf.metadata.strength')}
-          value={metadata.hrf_strength}
-          onClick={handleRecallHrfStrength}
-        />
-      )}
-      {metadata.hrf_enabled && metadata.hrf_method && (
-        <ImageMetadataItem
-          label={t('hrf.metadata.method')}
-          value={metadata.hrf_method}
-          onClick={handleRecallHrfMethod}
-        />
-      )}
-      {metadata.loras &&
-        metadata.loras.map((lora, index) => {
-          if (isModelIdentifier(lora.lora)) {
-            return (
-              <ModelMetadataItem
-                key={index}
-                label="LoRA"
-                modelKey={lora.lora.key}
-                extra={` - ${lora.weight}`}
-                onClick={handleRecallLoRA.bind(null, lora)}
-              />
-            );
-          }
-        })}
-      {validControlNets.map((controlnet, index) => (
-        <ModelMetadataItem
-          key={index}
-          label="ControlNet"
-          modelKey={controlnet.control_model?.key}
-          extra={` - ${controlnet.control_weight}`}
-          onClick={handleRecallControlNet.bind(null, controlnet)}
-        />
-      ))}
-      {validIPAdapters.map((ipAdapter, index) => (
-        <ModelMetadataItem
-          key={index}
-          label="IP Adapter"
-          modelKey={ipAdapter.ip_adapter_model?.key}
-          extra={` - ${ipAdapter.weight}`}
-          onClick={handleRecallIPAdapter.bind(null, ipAdapter)}
-        />
-      ))}
-      {validT2IAdapters.map((t2iAdapter, index) => (
-        <ModelMetadataItem
-          key={index}
-          label="T2I Adapter"
-          modelKey={t2iAdapter.t2i_adapter_model?.key}
-          extra={` - ${t2iAdapter.weight}`}
-          onClick={handleRecallT2IAdapter.bind(null, t2iAdapter)}
-        />
-      ))}
+      <MetadataItem metadata={metadata} handlers={handlers.createdBy} />
+      <MetadataItem metadata={metadata} handlers={handlers.generationMode} />
+      <MetadataItem metadata={metadata} handlers={handlers.positivePrompt} direction="column" />
+      <MetadataItem metadata={metadata} handlers={handlers.negativePrompt} direction="column" />
+      <MetadataItem metadata={metadata} handlers={handlers.sdxlPositiveStylePrompt} direction="column" />
+      <MetadataItem metadata={metadata} handlers={handlers.sdxlNegativeStylePrompt} direction="column" />
+      <MetadataItem metadata={metadata} handlers={handlers.model} />
+      <MetadataItem metadata={metadata} handlers={handlers.vae} />
+      <MetadataItem metadata={metadata} handlers={handlers.width} />
+      <MetadataItem metadata={metadata} handlers={handlers.height} />
+      <MetadataItem metadata={metadata} handlers={handlers.seed} />
+      <MetadataItem metadata={metadata} handlers={handlers.steps} />
+      <MetadataItem metadata={metadata} handlers={handlers.scheduler} />
+      <MetadataItem metadata={metadata} handlers={handlers.cfgScale} />
+      <MetadataItem metadata={metadata} handlers={handlers.cfgRescaleMultiplier} />
+      <MetadataItem metadata={metadata} handlers={handlers.strength} />
+      <MetadataItem metadata={metadata} handlers={handlers.hrfEnabled} />
+      <MetadataItem metadata={metadata} handlers={handlers.hrfMethod} />
+      <MetadataItem metadata={metadata} handlers={handlers.hrfStrength} />
+      <MetadataItem metadata={metadata} handlers={handlers.refinerCFGScale} />
+      <MetadataItem metadata={metadata} handlers={handlers.refinerModel} />
+      <MetadataItem metadata={metadata} handlers={handlers.refinerNegativeAestheticScore} />
+      <MetadataItem metadata={metadata} handlers={handlers.refinerPositiveAestheticScore} />
+      <MetadataItem metadata={metadata} handlers={handlers.refinerScheduler} />
+      <MetadataItem metadata={metadata} handlers={handlers.refinerStart} />
+      <MetadataItem metadata={metadata} handlers={handlers.refinerSteps} />
+      <MetadataLoRAs metadata={metadata} />
+      <MetadataControlNets metadata={metadata} />
+      <MetadataT2IAdapters metadata={metadata} />
+      <MetadataIPAdapters metadata={metadata} />
     </>
   );
 };
diff --git a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataItem.tsx b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataItem.tsx
index ce25b54e59..146c1437d1 100644
--- a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataItem.tsx
+++ b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataItem.tsx
@@ -1,28 +1,39 @@
 import { ExternalLink, Flex, IconButton, Text, Tooltip } from '@invoke-ai/ui-library';
 import { skipToken } from '@reduxjs/toolkit/query';
+import { get } from 'lodash-es';
 import { memo, useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
-import { IoArrowUndoCircleOutline } from 'react-icons/io5';
-import { PiCopyBold } from 'react-icons/pi';
+import { PiArrowBendUpLeftBold } from 'react-icons/pi';
 import { useGetModelConfigQuery } from 'services/api/endpoints/models';
 
 type MetadataItemProps = {
   isLink?: boolean;
   label: string;
-  onClick?: () => void;
-  value: number | string | boolean;
+  metadata: unknown;
+  propertyName: string;
+  onRecall?: (value: unknown) => void;
   labelPosition?: string;
-  withCopy?: boolean;
 };
 
 /**
  * Component to display an individual metadata item or parameter.
  */
-const ImageMetadataItem = ({ label, value, onClick, isLink, labelPosition, withCopy = false }: MetadataItemProps) => {
+const ImageMetadataItem = ({
+  label,
+  metadata,
+  propertyName,
+  onRecall: _onRecall,
+  isLink,
+  labelPosition,
+}: MetadataItemProps) => {
   const { t } = useTranslation();
-  const handleCopy = useCallback(() => {
-    navigator.clipboard.writeText(value?.toString());
-  }, [value]);
+  const value = useMemo(() => get(metadata, propertyName), [metadata, propertyName]);
+  const onRecall = useCallback(() => {
+    if (!_onRecall) {
+      return;
+    }
+    _onRecall(value);
+  }, [_onRecall, value]);
 
   if (!value) {
     return null;
@@ -30,27 +41,15 @@ const ImageMetadataItem = ({ label, value, onClick, isLink, labelPosition, withC
 
   return (
     <Flex gap={2}>
-      {onClick && (
-        <Tooltip label={`Recall ${label}`}>
+      {_onRecall && (
+        <Tooltip label={t('metadata.recallParameter', { parameter: label })}>
           <IconButton
-            aria-label={t('accessibility.useThisParameter')}
-            icon={<IoArrowUndoCircleOutline />}
+            aria-label={t('metadata.recallParameter', { parameter: label })}
+            icon={<PiArrowBendUpLeftBold />}
             size="xs"
             variant="ghost"
             fontSize={20}
-            onClick={onClick}
-          />
-        </Tooltip>
-      )}
-      {withCopy && (
-        <Tooltip label={`Copy ${label}`}>
-          <IconButton
-            aria-label={`Copy ${label}`}
-            icon={<PiCopyBold />}
-            size="xs"
-            variant="ghost"
-            fontSize={14}
-            onClick={handleCopy}
+            onClick={onRecall}
           />
         </Tooltip>
       )}
diff --git a/invokeai/frontend/web/src/features/lora/components/LoRACard.tsx b/invokeai/frontend/web/src/features/lora/components/LoRACard.tsx
index 579d45054b..ddcdd58e75 100644
--- a/invokeai/frontend/web/src/features/lora/components/LoRACard.tsx
+++ b/invokeai/frontend/web/src/features/lora/components/LoRACard.tsx
@@ -24,29 +24,29 @@ type LoRACardProps = {
 export const LoRACard = memo((props: LoRACardProps) => {
   const { lora } = props;
   const dispatch = useAppDispatch();
-  const { data: loraConfig } = useGetModelConfigQuery(lora.key);
+  const { data: loraConfig } = useGetModelConfigQuery(lora.model.key);
 
   const handleChange = useCallback(
     (v: number) => {
-      dispatch(loraWeightChanged({ key: lora.key, weight: v }));
+      dispatch(loraWeightChanged({ key: lora.model.key, weight: v }));
     },
-    [dispatch, lora.key]
+    [dispatch, lora.model.key]
   );
 
   const handleSetLoraToggle = useCallback(() => {
-    dispatch(loraIsEnabledChanged({ key: lora.key, isEnabled: !lora.isEnabled }));
-  }, [dispatch, lora.key, lora.isEnabled]);
+    dispatch(loraIsEnabledChanged({ key: lora.model.key, isEnabled: !lora.isEnabled }));
+  }, [dispatch, lora.model.key, lora.isEnabled]);
 
   const handleRemoveLora = useCallback(() => {
-    dispatch(loraRemoved(lora.key));
-  }, [dispatch, lora.key]);
+    dispatch(loraRemoved(lora.model.key));
+  }, [dispatch, lora.model.key]);
 
   return (
     <Card variant="lora">
       <CardHeader>
         <Flex alignItems="center" justifyContent="space-between" width="100%" gap={2}>
           <Text noOfLines={1} wordBreak="break-all" color={lora.isEnabled ? 'base.200' : 'base.500'}>
-            {loraConfig?.name ?? lora.key.substring(0, 8)}
+            {loraConfig?.name ?? lora.model.key.substring(0, 8)}
           </Text>
           <Flex alignItems="center" gap={2}>
             <Switch size="sm" onChange={handleSetLoraToggle} isChecked={lora.isEnabled} />
diff --git a/invokeai/frontend/web/src/features/lora/store/loraSlice.ts b/invokeai/frontend/web/src/features/lora/store/loraSlice.ts
index 377406b3e5..32bef5fd9b 100644
--- a/invokeai/frontend/web/src/features/lora/store/loraSlice.ts
+++ b/invokeai/frontend/web/src/features/lora/store/loraSlice.ts
@@ -2,9 +2,11 @@ import type { PayloadAction } from '@reduxjs/toolkit';
 import { createSlice } from '@reduxjs/toolkit';
 import type { PersistConfig, RootState } from 'app/store/store';
 import type { ParameterLoRAModel } from 'features/parameters/types/parameterSchemas';
+import { getModelKeyAndBase } from 'features/parameters/util/modelFetchingHelpers';
 import type { LoRAModelConfig } from 'services/api/types';
 
-export type LoRA = ParameterLoRAModel & {
+export type LoRA = {
+  model: ParameterLoRAModel;
   weight: number;
   isEnabled?: boolean;
 };
@@ -29,11 +31,11 @@ export const loraSlice = createSlice({
   initialState: initialLoraState,
   reducers: {
     loraAdded: (state, action: PayloadAction<LoRAModelConfig>) => {
-      const { key, base } = action.payload;
-      state.loras[key] = { key, base, ...defaultLoRAConfig };
+      const model = getModelKeyAndBase(action.payload);
+      state.loras[model.key] = { ...defaultLoRAConfig, model };
     },
     loraRecalled: (state, action: PayloadAction<LoRA>) => {
-      state.loras[action.payload.key] = action.payload;
+      state.loras[action.payload.model.key] = action.payload;
     },
     loraRemoved: (state, action: PayloadAction<string>) => {
       const key = action.payload;
@@ -58,7 +60,7 @@ export const loraSlice = createSlice({
       }
       lora.weight = defaultLoRAConfig.weight;
     },
-    loraIsEnabledChanged: (state, action: PayloadAction<Pick<LoRA, 'key' | 'isEnabled'>>) => {
+    loraIsEnabledChanged: (state, action: PayloadAction<{ key: string; isEnabled: boolean }>) => {
       const { key, isEnabled } = action.payload;
       const lora = state.loras[key];
       if (!lora) {
diff --git a/invokeai/frontend/web/src/features/metadata/components/MetadataControlNets.tsx b/invokeai/frontend/web/src/features/metadata/components/MetadataControlNets.tsx
new file mode 100644
index 0000000000..2e8e3b6f9a
--- /dev/null
+++ b/invokeai/frontend/web/src/features/metadata/components/MetadataControlNets.tsx
@@ -0,0 +1,66 @@
+import type { ControlNetConfig } from 'features/controlAdapters/store/types';
+import { MetadataItemView } from 'features/metadata/components/MetadataItemView';
+import type { MetadataHandlers } from 'features/metadata/types';
+import { handlers } from 'features/metadata/util/handlers';
+import { useCallback, useEffect, useMemo, useState } from 'react';
+
+type Props = {
+  metadata: unknown;
+};
+
+export const MetadataControlNets = ({ metadata }: Props) => {
+  const [controlNets, setControlNets] = useState<ControlNetConfig[]>([]);
+
+  useEffect(() => {
+    const parse = async () => {
+      try {
+        const parsed = await handlers.controlNets.parse(metadata);
+        setControlNets(parsed);
+      } catch (e) {
+        setControlNets([]);
+      }
+    };
+    parse();
+  }, [metadata]);
+
+  const label = useMemo(() => handlers.controlNets.getLabel(), []);
+
+  return (
+    <>
+      {controlNets.map((controlNet) => (
+        <MetadataViewControlNet
+          key={controlNet.model.key}
+          label={label}
+          controlNet={controlNet}
+          handlers={handlers.controlNets}
+        />
+      ))}
+    </>
+  );
+};
+
+const MetadataViewControlNet = ({
+  label,
+  controlNet,
+  handlers,
+}: {
+  label: string;
+  controlNet: ControlNetConfig;
+  handlers: MetadataHandlers<ControlNetConfig[], ControlNetConfig>;
+}) => {
+  const onRecall = useCallback(() => {
+    if (!handlers.recallItem) {
+      return;
+    }
+    handlers.recallItem(controlNet, true);
+  }, [handlers, controlNet]);
+
+  const renderedValue = useMemo(() => {
+    if (!handlers.renderItemValue) {
+      return null;
+    }
+    return handlers.renderItemValue(controlNet);
+  }, [handlers, controlNet]);
+
+  return <MetadataItemView label={label} isDisabled={false} onRecall={onRecall} renderedValue={renderedValue} />;
+};
diff --git a/invokeai/frontend/web/src/features/metadata/components/MetadataIPAdapters.tsx b/invokeai/frontend/web/src/features/metadata/components/MetadataIPAdapters.tsx
new file mode 100644
index 0000000000..fef281cd09
--- /dev/null
+++ b/invokeai/frontend/web/src/features/metadata/components/MetadataIPAdapters.tsx
@@ -0,0 +1,66 @@
+import type { IPAdapterConfig } from 'features/controlAdapters/store/types';
+import { MetadataItemView } from 'features/metadata/components/MetadataItemView';
+import type { MetadataHandlers } from 'features/metadata/types';
+import { handlers } from 'features/metadata/util/handlers';
+import { useCallback, useEffect, useMemo, useState } from 'react';
+
+type Props = {
+  metadata: unknown;
+};
+
+export const MetadataIPAdapters = ({ metadata }: Props) => {
+  const [ipAdapters, setIPAdapters] = useState<IPAdapterConfig[]>([]);
+
+  useEffect(() => {
+    const parse = async () => {
+      try {
+        const parsed = await handlers.ipAdapters.parse(metadata);
+        setIPAdapters(parsed);
+      } catch (e) {
+        setIPAdapters([]);
+      }
+    };
+    parse();
+  }, [metadata]);
+
+  const label = useMemo(() => handlers.ipAdapters.getLabel(), []);
+
+  return (
+    <>
+      {ipAdapters.map((ipAdapter) => (
+        <MetadataViewIPAdapter
+          key={ipAdapter.model.key}
+          label={label}
+          ipAdapter={ipAdapter}
+          handlers={handlers.ipAdapters}
+        />
+      ))}
+    </>
+  );
+};
+
+const MetadataViewIPAdapter = ({
+  label,
+  ipAdapter,
+  handlers,
+}: {
+  label: string;
+  ipAdapter: IPAdapterConfig;
+  handlers: MetadataHandlers<IPAdapterConfig[], IPAdapterConfig>;
+}) => {
+  const onRecall = useCallback(() => {
+    if (!handlers.recallItem) {
+      return;
+    }
+    handlers.recallItem(ipAdapter, true);
+  }, [handlers, ipAdapter]);
+
+  const renderedValue = useMemo(() => {
+    if (!handlers.renderItemValue) {
+      return null;
+    }
+    return handlers.renderItemValue(ipAdapter);
+  }, [handlers, ipAdapter]);
+
+  return <MetadataItemView label={label} isDisabled={false} onRecall={onRecall} renderedValue={renderedValue} />;
+};
diff --git a/invokeai/frontend/web/src/features/metadata/components/MetadataItem.tsx b/invokeai/frontend/web/src/features/metadata/components/MetadataItem.tsx
new file mode 100644
index 0000000000..66d101f458
--- /dev/null
+++ b/invokeai/frontend/web/src/features/metadata/components/MetadataItem.tsx
@@ -0,0 +1,33 @@
+import { typedMemo } from '@invoke-ai/ui-library';
+import { MetadataItemView } from 'features/metadata/components/MetadataItemView';
+import { useMetadataItem } from 'features/metadata/hooks/useMetadataItem';
+import type { MetadataHandlers } from 'features/metadata/types';
+import { MetadataParseFailedToken } from 'features/metadata/util/parsers';
+
+type MetadataItemProps<T> = {
+  metadata: unknown;
+  handlers: MetadataHandlers<T>;
+  direction?: 'row' | 'column';
+};
+
+const _MetadataItem = typedMemo(<T,>({ metadata, handlers, direction = 'row' }: MetadataItemProps<T>) => {
+  const { label, isDisabled, value, renderedValue, onRecall } = useMetadataItem(metadata, handlers);
+
+  if (value === MetadataParseFailedToken) {
+    return null;
+  }
+
+  return (
+    <MetadataItemView
+      label={label}
+      onRecall={onRecall}
+      isDisabled={isDisabled}
+      renderedValue={renderedValue}
+      direction={direction}
+    />
+  );
+});
+
+export const MetadataItem = typedMemo(_MetadataItem);
+
+MetadataItem.displayName = 'MetadataItem';
diff --git a/invokeai/frontend/web/src/features/metadata/components/MetadataItemView.tsx b/invokeai/frontend/web/src/features/metadata/components/MetadataItemView.tsx
new file mode 100644
index 0000000000..14ccc4ae2b
--- /dev/null
+++ b/invokeai/frontend/web/src/features/metadata/components/MetadataItemView.tsx
@@ -0,0 +1,29 @@
+import { Flex, Text } from '@invoke-ai/ui-library';
+import { RecallButton } from 'features/metadata/components/RecallButton';
+import { memo } from 'react';
+
+type MetadataItemViewProps = {
+  onRecall: () => void;
+  label: string;
+  renderedValue: React.ReactNode;
+  isDisabled: boolean;
+  direction?: 'row' | 'column';
+};
+
+export const MetadataItemView = memo(
+  ({ label, onRecall, isDisabled, renderedValue, direction = 'row' }: MetadataItemViewProps) => {
+    return (
+      <Flex gap={2}>
+        {onRecall && <RecallButton label={label} onClick={onRecall} isDisabled={isDisabled} />}
+        <Flex direction={direction}>
+          <Text fontWeight="semibold" whiteSpace="pre-wrap" pr={2}>
+            {label}:
+          </Text>
+          {renderedValue}
+        </Flex>
+      </Flex>
+    );
+  }
+);
+
+MetadataItemView.displayName = 'MetadataItemView';
diff --git a/invokeai/frontend/web/src/features/metadata/components/MetadataLoRAs.tsx b/invokeai/frontend/web/src/features/metadata/components/MetadataLoRAs.tsx
new file mode 100644
index 0000000000..3225a048d4
--- /dev/null
+++ b/invokeai/frontend/web/src/features/metadata/components/MetadataLoRAs.tsx
@@ -0,0 +1,61 @@
+import type { LoRA } from 'features/lora/store/loraSlice';
+import { MetadataItemView } from 'features/metadata/components/MetadataItemView';
+import type { MetadataHandlers } from 'features/metadata/types';
+import { handlers } from 'features/metadata/util/handlers';
+import { useCallback, useEffect, useMemo, useState } from 'react';
+
+type Props = {
+  metadata: unknown;
+};
+
+export const MetadataLoRAs = ({ metadata }: Props) => {
+  const [loras, setLoRAs] = useState<LoRA[]>([]);
+
+  useEffect(() => {
+    const parse = async () => {
+      try {
+        const parsed = await handlers.loras.parse(metadata);
+        setLoRAs(parsed);
+      } catch (e) {
+        setLoRAs([]);
+      }
+    };
+    parse();
+  }, [metadata]);
+
+  const label = useMemo(() => handlers.loras.getLabel(), []);
+
+  return (
+    <>
+      {loras.map((lora) => (
+        <MetadataViewLoRA key={lora.model.key} label={label} lora={lora} handlers={handlers.loras} />
+      ))}
+    </>
+  );
+};
+
+const MetadataViewLoRA = ({
+  label,
+  lora,
+  handlers,
+}: {
+  label: string;
+  lora: LoRA;
+  handlers: MetadataHandlers<LoRA[], LoRA>;
+}) => {
+  const onRecall = useCallback(() => {
+    if (!handlers.recallItem) {
+      return;
+    }
+    handlers.recallItem(lora, true);
+  }, [handlers, lora]);
+
+  const renderedValue = useMemo(() => {
+    if (!handlers.renderItemValue) {
+      return null;
+    }
+    return handlers.renderItemValue(lora);
+  }, [handlers, lora]);
+
+  return <MetadataItemView label={label} isDisabled={false} onRecall={onRecall} renderedValue={renderedValue} />;
+};
diff --git a/invokeai/frontend/web/src/features/metadata/components/MetadataT2IAdapters.tsx b/invokeai/frontend/web/src/features/metadata/components/MetadataT2IAdapters.tsx
new file mode 100644
index 0000000000..4a73fb3ccb
--- /dev/null
+++ b/invokeai/frontend/web/src/features/metadata/components/MetadataT2IAdapters.tsx
@@ -0,0 +1,66 @@
+import type { T2IAdapterConfig } from 'features/controlAdapters/store/types';
+import { MetadataItemView } from 'features/metadata/components/MetadataItemView';
+import type { MetadataHandlers } from 'features/metadata/types';
+import { handlers } from 'features/metadata/util/handlers';
+import { useCallback, useEffect, useMemo, useState } from 'react';
+
+type Props = {
+  metadata: unknown;
+};
+
+export const MetadataT2IAdapters = ({ metadata }: Props) => {
+  const [t2iAdapters, setT2IAdapters] = useState<T2IAdapterConfig[]>([]);
+
+  useEffect(() => {
+    const parse = async () => {
+      try {
+        const parsed = await handlers.t2iAdapters.parse(metadata);
+        setT2IAdapters(parsed);
+      } catch (e) {
+        setT2IAdapters([]);
+      }
+    };
+    parse();
+  }, [metadata]);
+
+  const label = useMemo(() => handlers.t2iAdapters.getLabel(), []);
+
+  return (
+    <>
+      {t2iAdapters.map((t2iAdapter) => (
+        <MetadataViewT2IAdapter
+          key={t2iAdapter.model.key}
+          label={label}
+          t2iAdapter={t2iAdapter}
+          handlers={handlers.t2iAdapters}
+        />
+      ))}
+    </>
+  );
+};
+
+const MetadataViewT2IAdapter = ({
+  label,
+  t2iAdapter,
+  handlers,
+}: {
+  label: string;
+  t2iAdapter: T2IAdapterConfig;
+  handlers: MetadataHandlers<T2IAdapterConfig[], T2IAdapterConfig>;
+}) => {
+  const onRecall = useCallback(() => {
+    if (!handlers.recallItem) {
+      return;
+    }
+    handlers.recallItem(t2iAdapter, true);
+  }, [handlers, t2iAdapter]);
+
+  const renderedValue = useMemo(() => {
+    if (!handlers.renderItemValue) {
+      return null;
+    }
+    return handlers.renderItemValue(t2iAdapter);
+  }, [handlers, t2iAdapter]);
+
+  return <MetadataItemView label={label} isDisabled={false} onRecall={onRecall} renderedValue={renderedValue} />;
+};
diff --git a/invokeai/frontend/web/src/features/metadata/components/RecallButton.tsx b/invokeai/frontend/web/src/features/metadata/components/RecallButton.tsx
new file mode 100644
index 0000000000..8803945b06
--- /dev/null
+++ b/invokeai/frontend/web/src/features/metadata/components/RecallButton.tsx
@@ -0,0 +1,27 @@
+import type { IconButtonProps} from '@invoke-ai/ui-library';
+import { IconButton, Tooltip } from '@invoke-ai/ui-library';
+import { memo } from 'react';
+import { useTranslation } from 'react-i18next';
+import { PiArrowBendUpLeftBold } from 'react-icons/pi';
+
+type MetadataItemProps = Omit<IconButtonProps, 'aria-label'> & {
+  label: string;
+};
+
+export const RecallButton = memo(({ label, ...rest }: MetadataItemProps) => {
+  const { t } = useTranslation();
+
+  return (
+    <Tooltip label={t('metadata.recallParameter', { label })}>
+      <IconButton
+        aria-label={t('metadata.recallParameter', { label })}
+        icon={<PiArrowBendUpLeftBold />}
+        size="xs"
+        variant="ghost"
+        {...rest}
+      />
+    </Tooltip>
+  );
+});
+
+RecallButton.displayName = 'RecallButton';
diff --git a/invokeai/frontend/web/src/features/metadata/exceptions.ts b/invokeai/frontend/web/src/features/metadata/exceptions.ts
new file mode 100644
index 0000000000..ffe4e98c79
--- /dev/null
+++ b/invokeai/frontend/web/src/features/metadata/exceptions.ts
@@ -0,0 +1,27 @@
+/**
+ * Raised when metadata parsing fails.
+ */
+export class MetadataParseError extends Error {
+  /**
+   * Create MetadataParseError
+   * @param {String} message
+   */
+  constructor(message: string) {
+    super(message);
+    this.name = this.constructor.name;
+  }
+}
+
+/**
+ * Raised when metadata recall fails.
+ */
+export class MetadataRecallError extends Error {
+  /**
+   * Create MetadataRecallError
+   * @param {String} message
+   */
+  constructor(message: string) {
+    super(message);
+    this.name = this.constructor.name;
+  }
+}
diff --git a/invokeai/frontend/web/src/features/metadata/hooks/useMetadataItem.tsx b/invokeai/frontend/web/src/features/metadata/hooks/useMetadataItem.tsx
new file mode 100644
index 0000000000..178ac5155a
--- /dev/null
+++ b/invokeai/frontend/web/src/features/metadata/hooks/useMetadataItem.tsx
@@ -0,0 +1,51 @@
+import { Text } from '@invoke-ai/ui-library';
+import type { MetadataHandlers } from 'features/metadata/types';
+import { MetadataParseFailedToken, MetadataParsePendingToken } from 'features/metadata/util/parsers';
+import { useCallback, useEffect, useMemo, useState } from 'react';
+
+export const useMetadataItem = <T,>(metadata: unknown, handlers: MetadataHandlers<T>) => {
+  const [value, setValue] = useState<T | typeof MetadataParsePendingToken | typeof MetadataParseFailedToken>(
+    MetadataParsePendingToken
+  );
+
+  useEffect(() => {
+    const _parse = async () => {
+      try {
+        const parsed = await handlers.parse(metadata);
+        setValue(parsed);
+      } catch (e) {
+        setValue(MetadataParseFailedToken);
+      }
+    };
+    _parse();
+  }, [handlers, metadata]);
+
+  const isDisabled = useMemo(() => value === MetadataParsePendingToken || value === MetadataParseFailedToken, [value]);
+
+  const label = useMemo(() => handlers.getLabel(), [handlers]);
+
+  const renderedValue = useMemo(() => {
+    if (value === MetadataParsePendingToken) {
+      return <Text>Loading</Text>;
+    }
+    if (value === MetadataParseFailedToken) {
+      return <Text>Parsing Failed</Text>;
+    }
+
+    const rendered = handlers.renderValue(value);
+
+    if (typeof rendered === 'string') {
+      return <Text>{rendered}</Text>;
+    }
+    return rendered;
+  }, [handlers, value]);
+
+  const onRecall = useCallback(() => {
+    if (!handlers.recall || value === MetadataParsePendingToken || value === MetadataParseFailedToken) {
+      return null;
+    }
+    handlers.recall(value, true);
+  }, [handlers, value]);
+
+  return { label, isDisabled, value, renderedValue, onRecall };
+};
diff --git a/invokeai/frontend/web/src/features/metadata/types.ts b/invokeai/frontend/web/src/features/metadata/types.ts
new file mode 100644
index 0000000000..366f11701e
--- /dev/null
+++ b/invokeai/frontend/web/src/features/metadata/types.ts
@@ -0,0 +1,136 @@
+/**
+ * Renders a value of type T as a React node.
+ */
+export type MetadataRenderValueFunc<T> = (value: T) => React.ReactNode;
+
+/**
+ * Gets the label of the current metadata item as a string.
+ */
+export type MetadataGetLabelFunc = () => string;
+
+export type MetadataParseOptions = {
+  toastOnFailure?: boolean;
+  toastOnSuccess?: boolean;
+};
+
+export type MetadataRecallOptions = MetadataParseOptions;
+
+/**
+ * A function that recalls a parsed and validated metadata value.
+ *
+ * @param value The value to recall.
+ * @throws MetadataRecallError if the value cannot be recalled.
+ */
+export type MetadataRecallFunc<T> = (value: T) => void;
+
+/**
+ * An async function that receives metadata and returns a parsed value, throwing if the value is invalid or missing.
+ *
+ * The function receives an object of unknown type. It is responsible for extracting the relevant data from the metadata
+ * and returning a value of type T.
+ *
+ * The function should throw a MetadataParseError if the metadata is invalid or missing.
+ *
+ * @param metadata The metadata to parse.
+ * @returns A promise that resolves to the parsed value.
+ * @throws MetadataParseError if the metadata is invalid or missing.
+ */
+export type MetadataParseFunc<T = unknown> = (metadata: unknown) => Promise<T>;
+
+/**
+ * A function that performs additional validation logic before recalling a metadata value. It is called with a parsed
+ * value and should throw if the validation logic fails.
+ *
+ * This function is used in cases where some additional logic is required before recalling. For example, when recalling
+ * a LoRA, we need to check if it is compatible with the current base model.
+ *
+ * @param value The value to validate.
+ * @returns A promise that resolves to the validated value.
+ * @throws MetadataRecallError if the value is invalid.
+ */
+export type MetadataValidateFunc<T> = (value: T) => Promise<T>;
+
+export type MetadataHandlers<TValue = unknown, TItem = unknown> = {
+  /**
+   * Gets the label of the current metadata item as a string.
+   *
+   * @returns The label of the current metadata item.
+   */
+  getLabel: MetadataGetLabelFunc;
+  /**
+   * An async function that receives metadata and returns a parsed metadata value.
+   *
+   * @param metadata The metadata to parse.
+   * @param withToast Whether to show a toast on success or failure.
+   * @returns A promise that resolves to the parsed value.
+   * @throws MetadataParseError if the metadata is invalid or missing.
+   */
+  parse: (metadata: unknown, withToast?: boolean) => Promise<TValue>;
+  /**
+   * An async function that receives a metadata item and returns a parsed metadata item value.
+   *
+   * This is only provided if the metadata value is an array.
+   *
+   * @param item The item to parse. It should be an item from the array.
+   * @param withToast Whether to show a toast on success or failure.
+   * @returns A promise that resolves to the parsed value.
+   * @throws MetadataParseError if the metadata is invalid or missing.
+   */
+  parseItem?: (item: unknown, withToast?: boolean) => Promise<TItem>;
+  /**
+   * An async function that recalls a parsed metadata value.
+   *
+   * This function is only provided if the metadata value can be recalled.
+   *
+   * @param value The value to recall.
+   * @param withToast Whether to show a toast on success or failure.
+   * @returns A promise that resolves when the recall operation is complete.
+   * @throws MetadataRecallError if the value cannot be recalled.
+   */
+  recall?: (value: TValue, withToast?: boolean) => Promise<void>;
+  /**
+   * An async function that recalls a parsed metadata item value.
+   *
+   * This function is only provided if the metadata value is an array and the items can be recalled.
+   *
+   * @param item The item to recall. It should be an item from the array.
+   * @param withToast Whether to show a toast on success or failure.
+   * @returns A promise that resolves when the recall operation is complete.
+   * @throws MetadataRecallError if the value cannot be recalled.
+   */
+  recallItem?: (item: TItem, withToast?: boolean) => Promise<void>;
+  /**
+   * Renders a parsed metadata value as a React node.
+   *
+   * @param value The value to render.
+   * @returns The rendered value.
+   */
+  renderValue: MetadataRenderValueFunc<TValue>;
+  /**
+   * Renders a parsed metadata item value as a React node.
+   *
+   * @param item The item to render.
+   * @returns The rendered item.
+   */
+  renderItemValue?: MetadataRenderValueFunc<TItem>;
+};
+
+// TODO(psyche): The types for item handlers should be able to be inferred from the type of the value:
+// type MetadataHandlersInferItem<TValue> = TValue extends Array<infer TItem> ? MetadataParseFunc<TItem> : never
+// While this works for the types as expected, I couldn't satisfy TS in the implementations of the handlers.
+
+export type BuildMetadataHandlersArg<TValue, TItem> = {
+  parser: MetadataParseFunc<TValue>;
+  itemParser?: MetadataParseFunc<TItem>;
+  recaller?: MetadataRecallFunc<TValue>;
+  itemRecaller?: MetadataRecallFunc<TItem>;
+  validator?: MetadataValidateFunc<TValue>;
+  itemValidator?: MetadataValidateFunc<TItem>;
+  getLabel: MetadataGetLabelFunc;
+  renderValue?: MetadataRenderValueFunc<TValue>;
+  renderItemValue?: MetadataRenderValueFunc<TItem>;
+};
+
+export type BuildMetadataHandlers = <TValue, TItem>(
+  arg: BuildMetadataHandlersArg<TValue, TItem>
+) => MetadataHandlers<TValue, TItem>;
diff --git a/invokeai/frontend/web/src/features/metadata/util/handlers.tsx b/invokeai/frontend/web/src/features/metadata/util/handlers.tsx
new file mode 100644
index 0000000000..1f86257d42
--- /dev/null
+++ b/invokeai/frontend/web/src/features/metadata/util/handlers.tsx
@@ -0,0 +1,316 @@
+import { Text } from '@invoke-ai/ui-library';
+import { toast } from 'common/util/toast';
+import type { ControlNetConfig, IPAdapterConfig, T2IAdapterConfig } from 'features/controlAdapters/store/types';
+import type { LoRA } from 'features/lora/store/loraSlice';
+import type {
+  BuildMetadataHandlers,
+  MetadataGetLabelFunc,
+  MetadataHandlers,
+  MetadataParseFunc,
+  MetadataRecallFunc,
+  MetadataRenderValueFunc,
+  MetadataValidateFunc,
+} from 'features/metadata/types';
+import { validators } from 'features/metadata/util/validators';
+import { t } from 'i18next';
+import type { AnyModelConfig } from 'services/api/types';
+
+import { parsers } from './parsers';
+import { recallers } from './recallers';
+
+const renderModelConfigValue: MetadataRenderValueFunc<AnyModelConfig> = (value) =>
+  `${value.name} (${value.base.toUpperCase()}, ${value.key})`;
+const renderLoRAValue: MetadataRenderValueFunc<LoRA> = (value) => <Text>{`${value.model.key} (${value.weight})`}</Text>;
+const renderControlAdapterValue: MetadataRenderValueFunc<ControlNetConfig | T2IAdapterConfig | IPAdapterConfig> = (
+  value
+) => <Text>{`${value.model?.key} (${value.weight})`}</Text>;
+
+const parameterSetToast = (parameter: string, description?: string) => {
+  toast({
+    title: t('toast.parameterSet', { parameter }),
+    description,
+    status: 'info',
+    duration: 2500,
+    isClosable: true,
+  });
+};
+
+const parameterNotSetToast = (parameter: string, description?: string) => {
+  toast({
+    title: t('toast.parameterNotSet', { parameter }),
+    description,
+    status: 'warning',
+    duration: 2500,
+    isClosable: true,
+  });
+};
+
+// const allParameterSetToast = (description?: string) => {
+//   toast({
+//     title: t('toast.parametersSet'),
+//     status: 'info',
+//     description,
+//     duration: 2500,
+//     isClosable: true,
+//   });
+// };
+
+// const allParameterNotSetToast = (description?: string) => {
+//   toast({
+//     title: t('toast.parametersNotSet'),
+//     status: 'warning',
+//     description,
+//     duration: 2500,
+//     isClosable: true,
+//   });
+// };
+
+const buildParse =
+  <TValue, TItem>(arg: {
+    parser: MetadataParseFunc<TValue>;
+    getLabel: MetadataGetLabelFunc;
+  }): MetadataHandlers<TValue, TItem>['parse'] =>
+  async (metadata, withToast = false) => {
+    try {
+      const parsed = await arg.parser(metadata);
+      withToast && parameterSetToast(arg.getLabel());
+      return parsed;
+    } catch (e) {
+      withToast && parameterNotSetToast(arg.getLabel(), (e as Error).message);
+      throw e;
+    }
+  };
+
+const buildParseItem =
+  <TValue, TItem>(arg: {
+    itemParser: MetadataParseFunc<TItem>;
+    getLabel: MetadataGetLabelFunc;
+  }): MetadataHandlers<TValue, TItem>['parseItem'] =>
+  async (item, withToast = false) => {
+    try {
+      const parsed = await arg.itemParser(item);
+      withToast && parameterSetToast(arg.getLabel());
+      return parsed;
+    } catch (e) {
+      withToast && parameterNotSetToast(arg.getLabel(), (e as Error).message);
+      throw e;
+    }
+  };
+
+const buildRecall =
+  <TValue, TItem>(arg: {
+    recaller: MetadataRecallFunc<TValue>;
+    validator?: MetadataValidateFunc<TValue>;
+    getLabel: MetadataGetLabelFunc;
+  }): NonNullable<MetadataHandlers<TValue, TItem>['recall']> =>
+  async (value, withToast = false) => {
+    try {
+      arg.validator && (await arg.validator(value));
+      await arg.recaller(value);
+      withToast && parameterSetToast(arg.getLabel());
+    } catch (e) {
+      withToast && parameterNotSetToast(arg.getLabel(), (e as Error).message);
+      throw e;
+    }
+  };
+
+const buildRecallItem =
+  <TValue, TItem>(arg: {
+    itemRecaller: MetadataRecallFunc<TItem>;
+    itemValidator?: MetadataValidateFunc<TItem>;
+    getLabel: MetadataGetLabelFunc;
+  }): NonNullable<MetadataHandlers<TValue, TItem>['recallItem']> =>
+  async (item, withToast = false) => {
+    try {
+      arg.itemValidator && (await arg.itemValidator(item));
+      await arg.itemRecaller(item);
+      withToast && parameterSetToast(arg.getLabel());
+    } catch (e) {
+      withToast && parameterNotSetToast(arg.getLabel(), (e as Error).message);
+      throw e;
+    }
+  };
+
+const buildHandlers: BuildMetadataHandlers = ({
+  getLabel,
+  parser,
+  itemParser,
+  recaller,
+  itemRecaller,
+  validator,
+  itemValidator,
+  renderValue,
+  renderItemValue,
+}) => ({
+  parse: buildParse({ parser, getLabel }),
+  parseItem: itemParser ? buildParseItem({ itemParser, getLabel }) : undefined,
+  recall: recaller ? buildRecall({ recaller, validator, getLabel }) : undefined,
+  recallItem: itemRecaller ? buildRecallItem({ itemRecaller, itemValidator, getLabel }) : undefined,
+  getLabel,
+  renderValue: renderValue ?? String,
+  renderItemValue: renderItemValue ?? String,
+});
+
+export const handlers = {
+  // Misc
+  createdBy: buildHandlers({ getLabel: () => t('metadata.createdBy'), parser: parsers.createdBy }),
+  generationMode: buildHandlers({ getLabel: () => t('metadata.generationMode'), parser: parsers.generationMode }),
+
+  // Core parameters
+  cfgRescaleMultiplier: buildHandlers({
+    getLabel: () => t('metadata.cfgRescaleMultiplier'),
+    parser: parsers.cfgRescaleMultiplier,
+    recaller: recallers.cfgRescaleMultiplier,
+  }),
+  cfgScale: buildHandlers({
+    getLabel: () => t('metadata.cfgScale'),
+    parser: parsers.cfgScale,
+    recaller: recallers.cfgScale,
+  }),
+  height: buildHandlers({ getLabel: () => t('metadata.height'), parser: parsers.height, recaller: recallers.height }),
+  negativePrompt: buildHandlers({
+    getLabel: () => t('metadata.negativePrompt'),
+    parser: parsers.negativePrompt,
+    recaller: recallers.negativePrompt,
+  }),
+  positivePrompt: buildHandlers({
+    getLabel: () => t('metadata.positivePrompt'),
+    parser: parsers.positivePrompt,
+    recaller: recallers.positivePrompt,
+  }),
+  scheduler: buildHandlers({
+    getLabel: () => t('metadata.scheduler'),
+    parser: parsers.scheduler,
+    recaller: recallers.scheduler,
+  }),
+  sdxlNegativeStylePrompt: buildHandlers({
+    getLabel: () => t('sdxl.negStylePrompt'),
+    parser: parsers.sdxlNegativeStylePrompt,
+    recaller: recallers.sdxlNegativeStylePrompt,
+  }),
+  sdxlPositiveStylePrompt: buildHandlers({
+    getLabel: () => t('sdxl.posStylePrompt'),
+    parser: parsers.sdxlPositiveStylePrompt,
+    recaller: recallers.sdxlPositiveStylePrompt,
+  }),
+  seed: buildHandlers({ getLabel: () => t('metadata.seed'), parser: parsers.seed, recaller: recallers.seed }),
+  steps: buildHandlers({ getLabel: () => t('metadata.steps'), parser: parsers.steps, recaller: recallers.steps }),
+  strength: buildHandlers({
+    getLabel: () => t('metadata.strength'),
+    parser: parsers.strength,
+    recaller: recallers.strength,
+  }),
+  width: buildHandlers({ getLabel: () => t('metadata.width'), parser: parsers.width, recaller: recallers.width }),
+
+  // HRF
+  hrfEnabled: buildHandlers({
+    getLabel: () => t('hrf.metadata.enabled'),
+    parser: parsers.hrfEnabled,
+    recaller: recallers.hrfEnabled,
+  }),
+  hrfMethod: buildHandlers({
+    getLabel: () => t('hrf.metadata.method'),
+    parser: parsers.hrfMethod,
+    recaller: recallers.hrfMethod,
+  }),
+  hrfStrength: buildHandlers({
+    getLabel: () => t('hrf.metadata.strength'),
+    parser: parsers.hrfStrength,
+    recaller: recallers.hrfStrength,
+  }),
+
+  // Refiner
+  refinerCFGScale: buildHandlers({
+    getLabel: () => t('sdxl.cfgScale'),
+    parser: parsers.refinerCFGScale,
+    recaller: recallers.refinerCFGScale,
+  }),
+  refinerModel: buildHandlers({
+    getLabel: () => t('sdxl.refinerModel'),
+    parser: parsers.refinerModel,
+    recaller: recallers.refinerModel,
+    validator: validators.refinerModel,
+  }),
+  refinerNegativeAestheticScore: buildHandlers({
+    getLabel: () => t('sdxl.posAestheticScore'),
+    parser: parsers.refinerNegativeAestheticScore,
+    recaller: recallers.refinerNegativeAestheticScore,
+  }),
+  refinerPositiveAestheticScore: buildHandlers({
+    getLabel: () => t('sdxl.negAestheticScore'),
+    parser: parsers.refinerPositiveAestheticScore,
+    recaller: recallers.refinerPositiveAestheticScore,
+  }),
+  refinerScheduler: buildHandlers({
+    getLabel: () => t('sdxl.scheduler'),
+    parser: parsers.refinerScheduler,
+    recaller: recallers.refinerScheduler,
+  }),
+  refinerStart: buildHandlers({
+    getLabel: () => t('sdxl.refiner_start'),
+    parser: parsers.refinerStart,
+    recaller: recallers.refinerStart,
+  }),
+  refinerSteps: buildHandlers({
+    getLabel: () => t('sdxl.refiner_steps'),
+    parser: parsers.refinerSteps,
+    recaller: recallers.refinerSteps,
+  }),
+
+  // Models
+  model: buildHandlers({
+    getLabel: () => t('metadata.model'),
+    parser: parsers.mainModel,
+    recaller: recallers.model,
+    renderValue: renderModelConfigValue,
+  }),
+  vae: buildHandlers({
+    getLabel: () => t('metadata.vae'),
+    parser: parsers.vaeModel,
+    recaller: recallers.vae,
+    renderValue: renderModelConfigValue,
+    validator: validators.vaeModel,
+  }),
+
+  // Arrays of models
+  controlNets: buildHandlers({
+    getLabel: () => t('common.controlNet'),
+    parser: parsers.controlNets,
+    itemParser: parsers.controlNet,
+    recaller: recallers.controlNets,
+    itemRecaller: recallers.controlNet,
+    validator: validators.controlNets,
+    itemValidator: validators.controlNet,
+    renderItemValue: renderControlAdapterValue,
+  }),
+  ipAdapters: buildHandlers({
+    getLabel: () => t('common.ipAdapter'),
+    parser: parsers.ipAdapters,
+    itemParser: parsers.ipAdapter,
+    recaller: recallers.ipAdapters,
+    itemRecaller: recallers.ipAdapter,
+    validator: validators.ipAdapters,
+    itemValidator: validators.ipAdapter,
+    renderItemValue: renderControlAdapterValue,
+  }),
+  loras: buildHandlers({
+    getLabel: () => t('models.lora'),
+    parser: parsers.loras,
+    itemParser: parsers.lora,
+    recaller: recallers.loras,
+    itemRecaller: recallers.lora,
+    validator: validators.loras,
+    itemValidator: validators.lora,
+    renderItemValue: renderLoRAValue,
+  }),
+  t2iAdapters: buildHandlers({
+    getLabel: () => t('common.t2iAdapter'),
+    parser: parsers.t2iAdapters,
+    itemParser: parsers.t2iAdapter,
+    recaller: recallers.t2iAdapters,
+    itemRecaller: recallers.t2iAdapter,
+    validator: validators.t2iAdapters,
+    itemValidator: validators.t2iAdapter,
+    renderItemValue: renderControlAdapterValue,
+  }),
+} as const;
diff --git a/invokeai/frontend/web/src/features/metadata/util/parsers.ts b/invokeai/frontend/web/src/features/metadata/util/parsers.ts
new file mode 100644
index 0000000000..c7f2a6d09f
--- /dev/null
+++ b/invokeai/frontend/web/src/features/metadata/util/parsers.ts
@@ -0,0 +1,396 @@
+import { CONTROLNET_PROCESSORS } from 'features/controlAdapters/store/constants';
+import type { ControlNetConfig, IPAdapterConfig, T2IAdapterConfig } from 'features/controlAdapters/store/types';
+import {
+  initialControlNet,
+  initialIPAdapter,
+  initialT2IAdapter,
+} from 'features/controlAdapters/util/buildControlAdapter';
+import type { LoRA } from 'features/lora/store/loraSlice';
+import { defaultLoRAConfig } from 'features/lora/store/loraSlice';
+import { MetadataParseError } from 'features/metadata/exceptions';
+import type { MetadataParseFunc } from 'features/metadata/types';
+import {
+  zControlField,
+  zIPAdapterField,
+  zModelIdentifierWithBase,
+  zT2IAdapterField,
+} from 'features/nodes/types/common';
+import type {
+  ParameterCFGRescaleMultiplier,
+  ParameterCFGScale,
+  ParameterHeight,
+  ParameterHRFEnabled,
+  ParameterHRFMethod,
+  ParameterNegativePrompt,
+  ParameterNegativeStylePromptSDXL,
+  ParameterPositivePrompt,
+  ParameterPositiveStylePromptSDXL,
+  ParameterScheduler,
+  ParameterSDXLRefinerNegativeAestheticScore,
+  ParameterSDXLRefinerPositiveAestheticScore,
+  ParameterSDXLRefinerStart,
+  ParameterSeed,
+  ParameterSteps,
+  ParameterStrength,
+  ParameterWidth,
+} from 'features/parameters/types/parameterSchemas';
+import {
+  isParameterCFGRescaleMultiplier,
+  isParameterCFGScale,
+  isParameterHeight,
+  isParameterHRFEnabled,
+  isParameterHRFMethod,
+  isParameterLoRAWeight,
+  isParameterNegativePrompt,
+  isParameterNegativeStylePromptSDXL,
+  isParameterPositivePrompt,
+  isParameterPositiveStylePromptSDXL,
+  isParameterScheduler,
+  isParameterSDXLRefinerNegativeAestheticScore,
+  isParameterSDXLRefinerPositiveAestheticScore,
+  isParameterSDXLRefinerStart,
+  isParameterSeed,
+  isParameterSteps,
+  isParameterStrength,
+  isParameterWidth,
+} from 'features/parameters/types/parameterSchemas';
+import {
+  fetchModelConfigWithTypeGuard,
+  getModelKey,
+  getModelKeyAndBase,
+} from 'features/parameters/util/modelFetchingHelpers';
+import { get, isArray, isString } from 'lodash-es';
+import type { NonRefinerMainModelConfig, RefinerMainModelConfig, VAEModelConfig } from 'services/api/types';
+import {
+  isControlNetModelConfig,
+  isIPAdapterModelConfig,
+  isLoRAModelConfig,
+  isNonRefinerMainModelConfig,
+  isRefinerMainModelModelConfig,
+  isT2IAdapterModelConfig,
+  isVAEModelConfig,
+} from 'services/api/types';
+import { v4 as uuidv4 } from 'uuid';
+
+export const MetadataParsePendingToken = Symbol('pending');
+export const MetadataParseFailedToken = Symbol('failed');
+
+/**
+ * An async function that a property from an object and validates its type using a type guard. If the property is missing
+ * or invalid, the function should throw a MetadataParseError.
+ * @param obj The object to get the property from.
+ * @param property The property to get.
+ * @param typeGuard A type guard function to check the type of the property. Provide `undefined` to opt out of type
+ * validation and always return the property value.
+ * @returns A promise that resolves to the property value if it exists and is of the expected type.
+ * @throws MetadataParseError if a type guard is provided and the property is not of the expected type.
+ */
+const getProperty = <T = unknown>(
+  obj: unknown,
+  property: string,
+  typeGuard: (val: unknown) => val is T = (val: unknown): val is T => true
+): Promise<T> => {
+  return new Promise<T>((resolve, reject) => {
+    const val = get(obj, property) as unknown;
+    if (typeGuard(val)) {
+      resolve(val);
+    }
+    reject(new MetadataParseError(`Property ${property} is not of expected type`));
+  });
+};
+
+const parseCreatedBy: MetadataParseFunc<string> = (metadata) => getProperty(metadata, 'created_by', isString);
+
+const parseGenerationMode: MetadataParseFunc<string> = (metadata) => getProperty(metadata, 'generation_mode', isString);
+
+const parsePositivePrompt: MetadataParseFunc<ParameterPositivePrompt> = (metadata) =>
+  getProperty(metadata, 'positive_prompt', isParameterPositivePrompt);
+
+const parseNegativePrompt: MetadataParseFunc<ParameterNegativePrompt> = (metadata) =>
+  getProperty(metadata, 'negative_prompt', isParameterNegativePrompt);
+
+const parseSDXLPositiveStylePrompt: MetadataParseFunc<ParameterPositiveStylePromptSDXL> = (metadata) =>
+  getProperty(metadata, 'positive_style_prompt', isParameterPositiveStylePromptSDXL);
+
+const parseSDXLNegativeStylePrompt: MetadataParseFunc<ParameterNegativeStylePromptSDXL> = (metadata) =>
+  getProperty(metadata, 'negative_style_prompt', isParameterNegativeStylePromptSDXL);
+
+const parseSeed: MetadataParseFunc<ParameterSeed> = (metadata) => getProperty(metadata, 'seed', isParameterSeed);
+
+const parseCFGScale: MetadataParseFunc<ParameterCFGScale> = (metadata) =>
+  getProperty(metadata, 'cfg_scale', isParameterCFGScale);
+
+const parseCFGRescaleMultiplier: MetadataParseFunc<ParameterCFGRescaleMultiplier> = (metadata) =>
+  getProperty(metadata, 'cfg_rescale_multiplier', isParameterCFGRescaleMultiplier);
+
+const parseScheduler: MetadataParseFunc<ParameterScheduler> = (metadata) =>
+  getProperty(metadata, 'scheduler', isParameterScheduler);
+
+const parseWidth: MetadataParseFunc<ParameterWidth> = (metadata) => getProperty(metadata, 'width', isParameterWidth);
+
+const parseHeight: MetadataParseFunc<ParameterHeight> = (metadata) =>
+  getProperty(metadata, 'height', isParameterHeight);
+
+const parseSteps: MetadataParseFunc<ParameterSteps> = (metadata) => getProperty(metadata, 'steps', isParameterSteps);
+
+const parseStrength: MetadataParseFunc<ParameterStrength> = (metadata) =>
+  getProperty(metadata, 'strength', isParameterStrength);
+
+const parseHRFEnabled: MetadataParseFunc<ParameterHRFEnabled> = (metadata) =>
+  getProperty(metadata, 'hrf_enabled', isParameterHRFEnabled);
+
+const parseHRFStrength: MetadataParseFunc<ParameterStrength> = (metadata) =>
+  getProperty(metadata, 'hrf_strength', isParameterStrength);
+
+const parseHRFMethod: MetadataParseFunc<ParameterHRFMethod> = (metadata) =>
+  getProperty(metadata, 'hrf_method', isParameterHRFMethod);
+
+const parseRefinerSteps: MetadataParseFunc<ParameterSteps> = (metadata) =>
+  getProperty(metadata, 'refiner_steps', isParameterSteps);
+
+const parseRefinerCFGScale: MetadataParseFunc<ParameterCFGScale> = (metadata) =>
+  getProperty(metadata, 'refiner_cfg_scale', isParameterCFGScale);
+
+const parseRefinerScheduler: MetadataParseFunc<ParameterScheduler> = (metadata) =>
+  getProperty(metadata, 'refiner_scheduler', isParameterScheduler);
+
+const parseRefinerPositiveAestheticScore: MetadataParseFunc<ParameterSDXLRefinerPositiveAestheticScore> = (metadata) =>
+  getProperty(metadata, 'refiner_positive_aesthetic_score', isParameterSDXLRefinerPositiveAestheticScore);
+
+const parseRefinerNegativeAestheticScore: MetadataParseFunc<ParameterSDXLRefinerNegativeAestheticScore> = (metadata) =>
+  getProperty(metadata, 'refiner_negative_aesthetic_score', isParameterSDXLRefinerNegativeAestheticScore);
+
+const parseRefinerStart: MetadataParseFunc<ParameterSDXLRefinerStart> = (metadata) =>
+  getProperty(metadata, 'refiner_start', isParameterSDXLRefinerStart);
+
+const parseMainModel: MetadataParseFunc<NonRefinerMainModelConfig> = async (metadata) => {
+  const model = await getProperty(metadata, 'model', undefined);
+  const key = await getModelKey(model, 'main');
+  const mainModelConfig = await fetchModelConfigWithTypeGuard(key, isNonRefinerMainModelConfig);
+  return mainModelConfig;
+};
+
+const parseRefinerModel: MetadataParseFunc<RefinerMainModelConfig> = async (metadata) => {
+  const refiner_model = await getProperty(metadata, 'refiner_model', undefined);
+  const key = await getModelKey(refiner_model, 'main');
+  const refinerModelConfig = await fetchModelConfigWithTypeGuard(key, isRefinerMainModelModelConfig);
+  return refinerModelConfig;
+};
+
+const parseVAEModel: MetadataParseFunc<VAEModelConfig> = async (metadata) => {
+  const vae = await getProperty(metadata, 'vae', undefined);
+  const key = await getModelKey(vae, 'vae');
+  const vaeModelConfig = await fetchModelConfigWithTypeGuard(key, isVAEModelConfig);
+  return vaeModelConfig;
+};
+
+const parseLoRA: MetadataParseFunc<LoRA> = async (metadataItem) => {
+  // Previously, the LoRA model identifier parts were stored in the LoRA metadata: `{key: ..., weight: 0.75}`
+  const modelV1 = await getProperty(metadataItem, 'lora', undefined);
+  // Now, the LoRA model is stored in a `model` property of the LoRA metadata: `{model: {key: ...}, weight: 0.75}`
+  const modelV2 = await getProperty(metadataItem, 'model', undefined);
+  const weight = await getProperty(metadataItem, 'weight', undefined);
+  const key = await getModelKey(modelV2 ?? modelV1, 'lora');
+  const loraModelConfig = await fetchModelConfigWithTypeGuard(key, isLoRAModelConfig);
+
+  return {
+    model: getModelKeyAndBase(loraModelConfig),
+    weight: isParameterLoRAWeight(weight) ? weight : defaultLoRAConfig.weight,
+    isEnabled: true,
+  };
+};
+
+const parseAllLoRAs: MetadataParseFunc<LoRA[]> = async (metadata) => {
+  const lorasRaw = await getProperty(metadata, 'loras', isArray);
+  const parseResults = await Promise.allSettled(lorasRaw.map((lora) => parseLoRA(lora)));
+  const loras = parseResults
+    .filter((result): result is PromiseFulfilledResult<LoRA> => result.status === 'fulfilled')
+    .map((result) => result.value);
+  return loras;
+};
+
+const parseControlNet: MetadataParseFunc<ControlNetConfig> = async (metadataItem) => {
+  const control_model = await getProperty(metadataItem, 'control_model');
+  const key = await getModelKey(control_model, 'controlnet');
+  const controlNetModel = await fetchModelConfigWithTypeGuard(key, isControlNetModelConfig);
+
+  const image = zControlField.shape.image.nullish().catch(null).parse(getProperty(metadataItem, 'image'));
+  const control_weight = zControlField.shape.control_weight
+    .nullish()
+    .catch(null)
+    .parse(getProperty(metadataItem, 'control_weight'));
+  const begin_step_percent = zControlField.shape.begin_step_percent
+    .nullish()
+    .catch(null)
+    .parse(getProperty(metadataItem, 'begin_step_percent'));
+  const end_step_percent = zControlField.shape.end_step_percent
+    .nullish()
+    .catch(null)
+    .parse(getProperty(metadataItem, 'end_step_percent'));
+  const control_mode = zControlField.shape.control_mode
+    .nullish()
+    .catch(null)
+    .parse(getProperty(metadataItem, 'control_mode'));
+  const resize_mode = zControlField.shape.resize_mode
+    .nullish()
+    .catch(null)
+    .parse(getProperty(metadataItem, 'resize_mode'));
+
+  const processorType = 'none';
+  const processorNode = CONTROLNET_PROCESSORS.none.default;
+
+  const controlNet: ControlNetConfig = {
+    type: 'controlnet',
+    isEnabled: true,
+    model: zModelIdentifierWithBase.parse(controlNetModel),
+    weight: typeof control_weight === 'number' ? control_weight : initialControlNet.weight,
+    beginStepPct: begin_step_percent ?? initialControlNet.beginStepPct,
+    endStepPct: end_step_percent ?? initialControlNet.endStepPct,
+    controlMode: control_mode ?? initialControlNet.controlMode,
+    resizeMode: resize_mode ?? initialControlNet.resizeMode,
+    controlImage: image?.image_name ?? null,
+    processedControlImage: image?.image_name ?? null,
+    processorType,
+    processorNode,
+    shouldAutoConfig: true,
+    id: uuidv4(),
+  };
+
+  return controlNet;
+};
+
+const parseAllControlNets: MetadataParseFunc<ControlNetConfig[]> = async (metadata) => {
+  const controlNetsRaw = await getProperty(metadata, 'controlnets', isArray);
+  const parseResults = await Promise.allSettled(controlNetsRaw.map((cn) => parseControlNet(cn)));
+  const controlNets = parseResults
+    .filter((result): result is PromiseFulfilledResult<ControlNetConfig> => result.status === 'fulfilled')
+    .map((result) => result.value);
+  return controlNets;
+};
+
+const parseT2IAdapter: MetadataParseFunc<T2IAdapterConfig> = async (metadataItem) => {
+  const t2i_adapter_model = await getProperty(metadataItem, 't2i_adapter_model');
+  const key = await getModelKey(t2i_adapter_model, 't2i_adapter');
+  const t2iAdapterModel = await fetchModelConfigWithTypeGuard(key, isT2IAdapterModelConfig);
+
+  const image = zT2IAdapterField.shape.image.nullish().catch(null).parse(getProperty(metadataItem, 'image'));
+  const weight = zT2IAdapterField.shape.weight.nullish().catch(null).parse(getProperty(metadataItem, 'weight'));
+  const begin_step_percent = zT2IAdapterField.shape.begin_step_percent
+    .nullish()
+    .catch(null)
+    .parse(getProperty(metadataItem, 'begin_step_percent'));
+  const end_step_percent = zT2IAdapterField.shape.end_step_percent
+    .nullish()
+    .catch(null)
+    .parse(getProperty(metadataItem, 'end_step_percent'));
+  const resize_mode = zT2IAdapterField.shape.resize_mode
+    .nullish()
+    .catch(null)
+    .parse(getProperty(metadataItem, 'resize_mode'));
+
+  const processorType = 'none';
+  const processorNode = CONTROLNET_PROCESSORS.none.default;
+
+  const t2iAdapter: T2IAdapterConfig = {
+    type: 't2i_adapter',
+    isEnabled: true,
+    model: zModelIdentifierWithBase.parse(t2iAdapterModel),
+    weight: typeof weight === 'number' ? weight : initialT2IAdapter.weight,
+    beginStepPct: begin_step_percent ?? initialT2IAdapter.beginStepPct,
+    endStepPct: end_step_percent ?? initialT2IAdapter.endStepPct,
+    resizeMode: resize_mode ?? initialT2IAdapter.resizeMode,
+    controlImage: image?.image_name ?? null,
+    processedControlImage: image?.image_name ?? null,
+    processorType,
+    processorNode,
+    shouldAutoConfig: true,
+    id: uuidv4(),
+  };
+
+  return t2iAdapter;
+};
+
+const parseAllT2IAdapters: MetadataParseFunc<T2IAdapterConfig[]> = async (metadata) => {
+  const t2iAdaptersRaw = await getProperty(metadata, 't2iAdapters', isArray);
+  const parseResults = await Promise.allSettled(t2iAdaptersRaw.map((t2iAdapter) => parseT2IAdapter(t2iAdapter)));
+  const t2iAdapters = parseResults
+    .filter((result): result is PromiseFulfilledResult<T2IAdapterConfig> => result.status === 'fulfilled')
+    .map((result) => result.value);
+  return t2iAdapters;
+};
+
+const parseIPAdapter: MetadataParseFunc<IPAdapterConfig> = async (metadataItem) => {
+  const ip_adapter_model = await getProperty(metadataItem, 'ip_adapter_model');
+  const key = await getModelKey(ip_adapter_model, 'ip_adapter');
+  const ipAdapterModel = await fetchModelConfigWithTypeGuard(key, isIPAdapterModelConfig);
+
+  const image = zIPAdapterField.shape.image.nullish().catch(null).parse(getProperty(metadataItem, 'image'));
+  const weight = zIPAdapterField.shape.weight.nullish().catch(null).parse(getProperty(metadataItem, 'weight'));
+  const begin_step_percent = zIPAdapterField.shape.begin_step_percent
+    .nullish()
+    .catch(null)
+    .parse(getProperty(metadataItem, 'begin_step_percent'));
+  const end_step_percent = zIPAdapterField.shape.end_step_percent
+    .nullish()
+    .catch(null)
+    .parse(getProperty(metadataItem, 'end_step_percent'));
+
+  const ipAdapter: IPAdapterConfig = {
+    id: uuidv4(),
+    type: 'ip_adapter',
+    isEnabled: true,
+    model: zModelIdentifierWithBase.parse(ipAdapterModel),
+    controlImage: image?.image_name ?? null,
+    weight: weight ?? initialIPAdapter.weight,
+    beginStepPct: begin_step_percent ?? initialIPAdapter.beginStepPct,
+    endStepPct: end_step_percent ?? initialIPAdapter.endStepPct,
+  };
+
+  return ipAdapter;
+};
+
+const parseAllIPAdapters: MetadataParseFunc<IPAdapterConfig[]> = async (metadata) => {
+  const ipAdaptersRaw = await getProperty(metadata, 'ipAdapters', isArray);
+  const parseResults = await Promise.allSettled(ipAdaptersRaw.map((ipAdapter) => parseIPAdapter(ipAdapter)));
+  const ipAdapters = parseResults
+    .filter((result): result is PromiseFulfilledResult<IPAdapterConfig> => result.status === 'fulfilled')
+    .map((result) => result.value);
+  return ipAdapters;
+};
+
+export const parsers = {
+  createdBy: parseCreatedBy,
+  generationMode: parseGenerationMode,
+  positivePrompt: parsePositivePrompt,
+  negativePrompt: parseNegativePrompt,
+  sdxlPositiveStylePrompt: parseSDXLPositiveStylePrompt,
+  sdxlNegativeStylePrompt: parseSDXLNegativeStylePrompt,
+  seed: parseSeed,
+  cfgScale: parseCFGScale,
+  cfgRescaleMultiplier: parseCFGRescaleMultiplier,
+  scheduler: parseScheduler,
+  width: parseWidth,
+  height: parseHeight,
+  steps: parseSteps,
+  strength: parseStrength,
+  hrfEnabled: parseHRFEnabled,
+  hrfStrength: parseHRFStrength,
+  hrfMethod: parseHRFMethod,
+  refinerSteps: parseRefinerSteps,
+  refinerCFGScale: parseRefinerCFGScale,
+  refinerScheduler: parseRefinerScheduler,
+  refinerPositiveAestheticScore: parseRefinerPositiveAestheticScore,
+  refinerNegativeAestheticScore: parseRefinerNegativeAestheticScore,
+  refinerStart: parseRefinerStart,
+  mainModel: parseMainModel,
+  refinerModel: parseRefinerModel,
+  vaeModel: parseVAEModel,
+  lora: parseLoRA,
+  loras: parseAllLoRAs,
+  controlNet: parseControlNet,
+  controlNets: parseAllControlNets,
+  t2iAdapter: parseT2IAdapter,
+  t2iAdapters: parseAllT2IAdapters,
+  ipAdapter: parseIPAdapter,
+  ipAdapters: parseAllIPAdapters,
+} as const;
diff --git a/invokeai/frontend/web/src/features/metadata/util/recallers.ts b/invokeai/frontend/web/src/features/metadata/util/recallers.ts
new file mode 100644
index 0000000000..e33589d5ce
--- /dev/null
+++ b/invokeai/frontend/web/src/features/metadata/util/recallers.ts
@@ -0,0 +1,295 @@
+import { getStore } from 'app/store/nanostores/store';
+import { controlAdapterRecalled } from 'features/controlAdapters/store/controlAdaptersSlice';
+import type { ControlNetConfig, IPAdapterConfig, T2IAdapterConfig } from 'features/controlAdapters/store/types';
+import { setHrfEnabled, setHrfMethod, setHrfStrength } from 'features/hrf/store/hrfSlice';
+import type { LoRA } from 'features/lora/store/loraSlice';
+import { loraRecalled } from 'features/lora/store/loraSlice';
+import type { MetadataRecallFunc } from 'features/metadata/types';
+import { zModelIdentifierWithBase } from 'features/nodes/types/common';
+import { modelSelected } from 'features/parameters/store/actions';
+import {
+  heightRecalled,
+  setCfgRescaleMultiplier,
+  setCfgScale,
+  setImg2imgStrength,
+  setNegativePrompt,
+  setPositivePrompt,
+  setScheduler,
+  setSeed,
+  setSteps,
+  vaeSelected,
+  widthRecalled,
+} from 'features/parameters/store/generationSlice';
+import type {
+  ParameterCFGRescaleMultiplier,
+  ParameterCFGScale,
+  ParameterHeight,
+  ParameterHRFEnabled,
+  ParameterHRFMethod,
+  ParameterNegativePrompt,
+  ParameterNegativeStylePromptSDXL,
+  ParameterPositivePrompt,
+  ParameterPositiveStylePromptSDXL,
+  ParameterScheduler,
+  ParameterSDXLRefinerNegativeAestheticScore,
+  ParameterSDXLRefinerPositiveAestheticScore,
+  ParameterSDXLRefinerStart,
+  ParameterSeed,
+  ParameterSteps,
+  ParameterStrength,
+  ParameterWidth,
+} from 'features/parameters/types/parameterSchemas';
+import {
+  refinerModelChanged,
+  setNegativeStylePromptSDXL,
+  setPositiveStylePromptSDXL,
+  setRefinerCFGScale,
+  setRefinerNegativeAestheticScore,
+  setRefinerPositiveAestheticScore,
+  setRefinerScheduler,
+  setRefinerStart,
+  setRefinerSteps,
+} from 'features/sdxl/store/sdxlSlice';
+import type { NonRefinerMainModelConfig, RefinerMainModelConfig, VAEModelConfig } from 'services/api/types';
+
+const recallPositivePrompt: MetadataRecallFunc<ParameterPositivePrompt> = (positivePrompt) => {
+  getStore().dispatch(setPositivePrompt(positivePrompt));
+};
+
+const recallNegativePrompt: MetadataRecallFunc<ParameterNegativePrompt> = (negativePrompt) => {
+  getStore().dispatch(setNegativePrompt(negativePrompt));
+};
+
+const recallSDXLPositiveStylePrompt: MetadataRecallFunc<ParameterPositiveStylePromptSDXL> = (positiveStylePrompt) => {
+  getStore().dispatch(setPositiveStylePromptSDXL(positiveStylePrompt));
+};
+
+const recallSDXLNegativeStylePrompt: MetadataRecallFunc<ParameterNegativeStylePromptSDXL> = (negativeStylePrompt) => {
+  getStore().dispatch(setNegativeStylePromptSDXL(negativeStylePrompt));
+};
+
+const recallSeed: MetadataRecallFunc<ParameterSeed> = (seed) => {
+  getStore().dispatch(setSeed(seed));
+};
+
+const recallCFGScale: MetadataRecallFunc<ParameterCFGScale> = (cfgScale) => {
+  getStore().dispatch(setCfgScale(cfgScale));
+};
+
+const recallCFGRescaleMultiplier: MetadataRecallFunc<ParameterCFGRescaleMultiplier> = (cfgRescaleMultiplier) => {
+  getStore().dispatch(setCfgRescaleMultiplier(cfgRescaleMultiplier));
+};
+
+const recallScheduler: MetadataRecallFunc<ParameterScheduler> = (scheduler) => {
+  getStore().dispatch(setScheduler(scheduler));
+};
+
+const recallWidth: MetadataRecallFunc<ParameterWidth> = (width) => {
+  getStore().dispatch(widthRecalled(width));
+};
+
+const recallHeight: MetadataRecallFunc<ParameterHeight> = (height) => {
+  getStore().dispatch(heightRecalled(height));
+};
+
+const recallSteps: MetadataRecallFunc<ParameterSteps> = (steps) => {
+  getStore().dispatch(setSteps(steps));
+};
+
+const recallStrength: MetadataRecallFunc<ParameterStrength> = (strength) => {
+  getStore().dispatch(setImg2imgStrength(strength));
+};
+
+const recallHRFEnabled: MetadataRecallFunc<ParameterHRFEnabled> = (hrfEnabled) => {
+  getStore().dispatch(setHrfEnabled(hrfEnabled));
+};
+
+const recallHRFStrength: MetadataRecallFunc<ParameterStrength> = (hrfStrength) => {
+  getStore().dispatch(setHrfStrength(hrfStrength));
+};
+
+const recallHRFMethod: MetadataRecallFunc<ParameterHRFMethod> = (hrfMethod) => {
+  getStore().dispatch(setHrfMethod(hrfMethod));
+};
+
+const recallRefinerSteps: MetadataRecallFunc<ParameterSteps> = (refinerSteps) => {
+  getStore().dispatch(setRefinerSteps(refinerSteps));
+};
+
+const recallRefinerCFGScale: MetadataRecallFunc<ParameterCFGScale> = (refinerCFGScale) => {
+  getStore().dispatch(setRefinerCFGScale(refinerCFGScale));
+};
+
+const recallRefinerScheduler: MetadataRecallFunc<ParameterScheduler> = (refinerScheduler) => {
+  getStore().dispatch(setRefinerScheduler(refinerScheduler));
+};
+
+const recallRefinerPositiveAestheticScore: MetadataRecallFunc<ParameterSDXLRefinerPositiveAestheticScore> = (
+  refinerPositiveAestheticScore
+) => {
+  getStore().dispatch(setRefinerPositiveAestheticScore(refinerPositiveAestheticScore));
+};
+
+const recallRefinerNegativeAestheticScore: MetadataRecallFunc<ParameterSDXLRefinerNegativeAestheticScore> = (
+  refinerNegativeAestheticScore
+) => {
+  getStore().dispatch(setRefinerNegativeAestheticScore(refinerNegativeAestheticScore));
+};
+
+const recallRefinerStart: MetadataRecallFunc<ParameterSDXLRefinerStart> = (refinerStart) => {
+  getStore().dispatch(setRefinerStart(refinerStart));
+};
+
+const recallModel: MetadataRecallFunc<NonRefinerMainModelConfig> = (model) => {
+  const modelIdentifier = zModelIdentifierWithBase.parse(model);
+  getStore().dispatch(modelSelected(modelIdentifier));
+};
+
+const recallRefinerModel: MetadataRecallFunc<RefinerMainModelConfig> = (refinerModel) => {
+  const modelIdentifier = zModelIdentifierWithBase.parse(refinerModel);
+  getStore().dispatch(refinerModelChanged(modelIdentifier));
+};
+
+const recallVAE: MetadataRecallFunc<VAEModelConfig | null | undefined> = (vaeModel) => {
+  if (!vaeModel) {
+    getStore().dispatch(vaeSelected(null));
+    return;
+  }
+  const modelIdentifier = zModelIdentifierWithBase.parse(vaeModel);
+  getStore().dispatch(vaeSelected(modelIdentifier));
+};
+
+const recallLoRA: MetadataRecallFunc<LoRA> = (lora) => {
+  getStore().dispatch(loraRecalled(lora));
+};
+
+const recallAllLoRAs: MetadataRecallFunc<LoRA[]> = (loras) => {
+  const { dispatch } = getStore();
+  loras.forEach((lora) => {
+    dispatch(loraRecalled(lora));
+  });
+};
+
+const recallControlNet: MetadataRecallFunc<ControlNetConfig> = (controlNet) => {
+  getStore().dispatch(controlAdapterRecalled(controlNet));
+};
+
+const recallControlNets: MetadataRecallFunc<ControlNetConfig[]> = (controlNets) => {
+  const { dispatch } = getStore();
+  controlNets.forEach((controlNet) => {
+    dispatch(controlAdapterRecalled(controlNet));
+  });
+};
+
+const recallT2IAdapter: MetadataRecallFunc<T2IAdapterConfig> = (t2iAdapter) => {
+  getStore().dispatch(controlAdapterRecalled(t2iAdapter));
+};
+
+const recallT2IAdapters: MetadataRecallFunc<T2IAdapterConfig[]> = (t2iAdapters) => {
+  const { dispatch } = getStore();
+  t2iAdapters.forEach((t2iAdapter) => {
+    dispatch(controlAdapterRecalled(t2iAdapter));
+  });
+};
+
+const recallIPAdapter: MetadataRecallFunc<IPAdapterConfig> = (ipAdapter) => {
+  getStore().dispatch(controlAdapterRecalled(ipAdapter));
+};
+
+const recallIPAdapters: MetadataRecallFunc<IPAdapterConfig[]> = (ipAdapters) => {
+  const { dispatch } = getStore();
+  ipAdapters.forEach((ipAdapter) => {
+    dispatch(controlAdapterRecalled(ipAdapter));
+  });
+};
+
+export const recallPrompts = (_metadata: unknown) => {
+  // recallPositivePrompt(metadata);
+  // recallNegativePrompt(metadata);
+  // recallSDXLPositiveStylePrompt(metadata);
+  // recallSDXLNegativeStylePrompt(metadata);
+  // parameterNotSetToast(t('metadata.allPrompts'));
+  // parameterSetToast(t('metadata.allPrompts'));
+};
+
+export const recallWidthAndHeight = (_metadata: unknown) => {
+  // recallWidth(metadata);
+  // recallHeight(metadata);
+};
+
+export const recallAll = async (_metadata: unknown) => {
+  // if (!metadata) {
+  //   allParameterNotSetToast();
+  //   return;
+  // }
+  // // Update the main model first, as other parameters may depend on it.
+  // await recallModel(metadata);
+  // await Promise.allSettled([
+  //   // Core parameters
+  //   recallCFGScale(metadata),
+  //   recallCFGRescaleMultiplier(metadata),
+  //   recallPositivePrompt(metadata),
+  //   recallNegativePrompt(metadata),
+  //   recallScheduler(metadata),
+  //   recallSeed(metadata),
+  //   recallSteps(metadata),
+  //   recallWidth(metadata),
+  //   recallHeight(metadata),
+  //   recallStrength(metadata),
+  //   recallHRFEnabled(metadata),
+  //   recallHRFMethod(metadata),
+  //   recallHRFStrength(metadata),
+  //   // SDXL parameters
+  //   recallSDXLPositiveStylePrompt(metadata),
+  //   recallSDXLNegativeStylePrompt(metadata),
+  //   recallRefinerSteps(metadata),
+  //   recallRefinerCFGScale(metadata),
+  //   recallRefinerScheduler(metadata),
+  //   recallRefinerPositiveAestheticScore(metadata),
+  //   recallRefinerNegativeAestheticScore(metadata),
+  //   recallRefinerStart(metadata),
+  //   // Models
+  //   recallVAE(metadata),
+  //   recallRefinerModel(metadata),
+  //   recallAllLoRAs(metadata),
+  //   recallControlNets(metadata),
+  //   recallT2IAdapters(metadata),
+  //   recallIPAdapters(metadata),
+  // ]);
+  // allParameterSetToast();
+};
+
+export const recallers = {
+  positivePrompt: recallPositivePrompt,
+  negativePrompt: recallNegativePrompt,
+  sdxlPositiveStylePrompt: recallSDXLPositiveStylePrompt,
+  sdxlNegativeStylePrompt: recallSDXLNegativeStylePrompt,
+  seed: recallSeed,
+  cfgScale: recallCFGScale,
+  cfgRescaleMultiplier: recallCFGRescaleMultiplier,
+  scheduler: recallScheduler,
+  width: recallWidth,
+  height: recallHeight,
+  steps: recallSteps,
+  strength: recallStrength,
+  hrfEnabled: recallHRFEnabled,
+  hrfStrength: recallHRFStrength,
+  hrfMethod: recallHRFMethod,
+  refinerSteps: recallRefinerSteps,
+  refinerCFGScale: recallRefinerCFGScale,
+  refinerScheduler: recallRefinerScheduler,
+  refinerPositiveAestheticScore: recallRefinerPositiveAestheticScore,
+  refinerNegativeAestheticScore: recallRefinerNegativeAestheticScore,
+  refinerStart: recallRefinerStart,
+  model: recallModel,
+  refinerModel: recallRefinerModel,
+  vae: recallVAE,
+  lora: recallLoRA,
+  loras: recallAllLoRAs,
+  controlNets: recallControlNets,
+  controlNet: recallControlNet,
+  t2iAdapters: recallT2IAdapters,
+  t2iAdapter: recallT2IAdapter,
+  ipAdapters: recallIPAdapters,
+  ipAdapter: recallIPAdapter,
+} as const;
diff --git a/invokeai/frontend/web/src/features/metadata/util/validators.ts b/invokeai/frontend/web/src/features/metadata/util/validators.ts
new file mode 100644
index 0000000000..e627afeda3
--- /dev/null
+++ b/invokeai/frontend/web/src/features/metadata/util/validators.ts
@@ -0,0 +1,117 @@
+import { getStore } from 'app/store/nanostores/store';
+import type { ControlNetConfig, IPAdapterConfig, T2IAdapterConfig } from 'features/controlAdapters/store/types';
+import type { LoRA } from 'features/lora/store/loraSlice';
+import type { MetadataValidateFunc } from 'features/metadata/types';
+import { InvalidModelConfigError } from 'features/parameters/util/modelFetchingHelpers';
+import type { BaseModelType, RefinerMainModelConfig, VAEModelConfig } from 'services/api/types';
+
+/**
+ * Checks the given base model type against the currently-selected model's base type and throws an error if they are
+ * incompatible.
+ * @param base The base model type to validate.
+ * @param message An optional message to use in the error if the base model is incompatible.
+ */
+const validateBaseCompatibility = (base?: BaseModelType, message?: string) => {
+  if (!base) {
+    throw new InvalidModelConfigError(message || 'Missing base');
+  }
+  const currentBase = getStore().getState().generation.model?.base;
+  if (currentBase && base !== currentBase) {
+    throw new InvalidModelConfigError(message || `Incompatible base models: ${base} and ${currentBase}`);
+  }
+};
+
+const validateRefinerModel: MetadataValidateFunc<RefinerMainModelConfig> = (refinerModel) => {
+  validateBaseCompatibility('sdxl', 'Refiner incompatible with currently-selected model');
+  return new Promise((resolve) => resolve(refinerModel));
+};
+
+const validateVAEModel: MetadataValidateFunc<VAEModelConfig> = (vaeModel) => {
+  validateBaseCompatibility(vaeModel.base, 'VAE incompatible with currently-selected model');
+  return new Promise((resolve) => resolve(vaeModel));
+};
+
+const validateLoRA: MetadataValidateFunc<LoRA> = (lora) => {
+  validateBaseCompatibility(lora.model.base, 'LoRA incompatible with currently-selected model');
+  return new Promise((resolve) => resolve(lora));
+};
+
+const validateLoRAs: MetadataValidateFunc<LoRA[]> = (loras) => {
+  const validatedLoRAs: LoRA[] = [];
+  loras.forEach((lora) => {
+    try {
+      validateBaseCompatibility(lora.model.base, 'LoRA incompatible with currently-selected model');
+      validatedLoRAs.push(lora);
+    } catch {
+      // This is a no-op - we want to continue validating the rest of the LoRAs, and an empty list is valid.
+    }
+  });
+  return new Promise((resolve) => resolve(validatedLoRAs));
+};
+
+const validateControlNet: MetadataValidateFunc<ControlNetConfig> = (controlNet) => {
+  validateBaseCompatibility(controlNet.model?.base, 'ControlNet incompatible with currently-selected model');
+  return new Promise((resolve) => resolve(controlNet));
+};
+
+const validateControlNets: MetadataValidateFunc<ControlNetConfig[]> = (controlNets) => {
+  const validatedControlNets: ControlNetConfig[] = [];
+  controlNets.forEach((controlNet) => {
+    try {
+      validateBaseCompatibility(controlNet.model?.base, 'ControlNet incompatible with currently-selected model');
+      validatedControlNets.push(controlNet);
+    } catch {
+      // This is a no-op - we want to continue validating the rest of the ControlNets, and an empty list is valid.
+    }
+  });
+  return new Promise((resolve) => resolve(validatedControlNets));
+};
+
+const validateT2IAdapter: MetadataValidateFunc<T2IAdapterConfig> = (t2iAdapter) => {
+  validateBaseCompatibility(t2iAdapter.model?.base, 'T2I Adapter incompatible with currently-selected model');
+  return new Promise((resolve) => resolve(t2iAdapter));
+};
+
+const validateT2IAdapters: MetadataValidateFunc<T2IAdapterConfig[]> = (t2iAdapters) => {
+  const validatedT2IAdapters: T2IAdapterConfig[] = [];
+  t2iAdapters.forEach((t2iAdapter) => {
+    try {
+      validateBaseCompatibility(t2iAdapter.model?.base, 'T2I Adapter incompatible with currently-selected model');
+      validatedT2IAdapters.push(t2iAdapter);
+    } catch {
+      // This is a no-op - we want to continue validating the rest of the T2I Adapters, and an empty list is valid.
+    }
+  });
+  return new Promise((resolve) => resolve(validatedT2IAdapters));
+};
+
+const validateIPAdapter: MetadataValidateFunc<IPAdapterConfig> = (ipAdapter) => {
+  validateBaseCompatibility(ipAdapter.model?.base, 'IP Adapter incompatible with currently-selected model');
+  return new Promise((resolve) => resolve(ipAdapter));
+};
+
+const validateIPAdapters: MetadataValidateFunc<IPAdapterConfig[]> = (ipAdapters) => {
+  const validatedIPAdapters: IPAdapterConfig[] = [];
+  ipAdapters.forEach((ipAdapter) => {
+    try {
+      validateBaseCompatibility(ipAdapter.model?.base, 'IP Adapter incompatible with currently-selected model');
+      validatedIPAdapters.push(ipAdapter);
+    } catch {
+      // This is a no-op - we want to continue validating the rest of the IP Adapters, and an empty list is valid.
+    }
+  });
+  return new Promise((resolve) => resolve(validatedIPAdapters));
+};
+
+export const validators = {
+  refinerModel: validateRefinerModel,
+  vaeModel: validateVAEModel,
+  lora: validateLoRA,
+  loras: validateLoRAs,
+  controlNet: validateControlNet,
+  controlNets: validateControlNets,
+  t2iAdapter: validateT2IAdapter,
+  t2iAdapters: validateT2IAdapters,
+  ipAdapter: validateIPAdapter,
+  ipAdapters: validateIPAdapters,
+} as const;
diff --git a/invokeai/frontend/web/src/features/nodes/types/common.ts b/invokeai/frontend/web/src/features/nodes/types/common.ts
index b195ce4434..501286c785 100644
--- a/invokeai/frontend/web/src/features/nodes/types/common.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/common.ts
@@ -1,5 +1,8 @@
 import { z } from 'zod';
 
+import type { ModelIdentifier as ModelIdentifierV2 } from './v2/common';
+import { zModelIdentifier as zModelIdentifierV2 } from './v2/common';
+
 // #region Field data schemas
 export const zImageField = z.object({
   image_name: z.string().trim().min(1),
@@ -69,6 +72,8 @@ export const zModelIdentifier = z.object({
 });
 export const isModelIdentifier = (field: unknown): field is ModelIdentifier =>
   zModelIdentifier.safeParse(field).success;
+export const isModelIdentifierV2 = (field: unknown): field is ModelIdentifierV2 =>
+  zModelIdentifierV2.safeParse(field).success;
 export const zModelFieldBase = zModelIdentifier;
 export const zModelIdentifierWithBase = zModelIdentifier.extend({ base: zBaseModel });
 export type BaseModel = z.infer<typeof zBaseModel>;
diff --git a/invokeai/frontend/web/src/features/nodes/types/metadata.ts b/invokeai/frontend/web/src/features/nodes/types/metadata.ts
index 493a0464b3..2789abaaca 100644
--- a/invokeai/frontend/web/src/features/nodes/types/metadata.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/metadata.ts
@@ -1,29 +1,22 @@
 import { z } from 'zod';
 
-import {
-  zControlField,
-  zIPAdapterField,
-  zMainModelField,
-  zModelFieldBase,
-  zSDXLRefinerModelField,
-  zT2IAdapterField,
-  zVAEModelField,
-} from './common';
+import { zControlField, zIPAdapterField, zT2IAdapterField } from './common';
 
+export const zLoRAWeight = z.number().nullish();
 // #region Metadata-optimized versions of schemas
 // TODO: It's possible that `deepPartial` will be deprecated:
 // - https://github.com/colinhacks/zod/issues/2106
 // - https://github.com/colinhacks/zod/issues/2854
 export const zLoRAMetadataItem = z.object({
-  lora: zModelFieldBase.deepPartial(),
-  weight: z.number(),
+  lora: z.unknown(),
+  weight: zLoRAWeight,
 });
-const zControlNetMetadataItem = zControlField.deepPartial();
-const zIPAdapterMetadataItem = zIPAdapterField.deepPartial();
-const zT2IAdapterMetadataItem = zT2IAdapterField.deepPartial();
-const zSDXLRefinerModelMetadataItem = zSDXLRefinerModelField.deepPartial();
-const zModelMetadataItem = zMainModelField.deepPartial();
-const zVAEModelMetadataItem = zVAEModelField.deepPartial();
+const zControlNetMetadataItem = zControlField.merge(z.object({ control_model: z.unknown() })).deepPartial();
+const zIPAdapterMetadataItem = zIPAdapterField.merge(z.object({ ip_adapter_model: z.unknown() })).deepPartial();
+const zT2IAdapterMetadataItem = zT2IAdapterField.merge(z.object({ t2i_adapter_model: z.unknown() })).deepPartial();
+const zSDXLRefinerModelMetadataItem = z.unknown();
+const zModelMetadataItem = z.unknown();
+const zVAEModelMetadataItem = z.unknown();
 export type LoRAMetadataItem = z.infer<typeof zLoRAMetadataItem>;
 export type ControlNetMetadataItem = z.infer<typeof zControlNetMetadataItem>;
 export type IPAdapterMetadataItem = z.infer<typeof zIPAdapterMetadataItem>;
diff --git a/invokeai/frontend/web/src/features/parameters/hooks/useRecallParameters.ts b/invokeai/frontend/web/src/features/parameters/hooks/useRecallParameters.ts
index 0929fc1dc3..8f9a76feca 100644
--- a/invokeai/frontend/web/src/features/parameters/hooks/useRecallParameters.ts
+++ b/invokeai/frontend/web/src/features/parameters/hooks/useRecallParameters.ts
@@ -1,17 +1,25 @@
-import { useAppToaster } from 'app/components/Toaster';
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { getStore } from 'app/store/nanostores/store';
+import { useAppDispatch } from 'app/store/storeHooks';
+import { toast } from 'common/util/toast';
+import { CONTROLNET_PROCESSORS } from 'features/controlAdapters/store/constants';
 import { controlAdapterRecalled, controlAdaptersReset } from 'features/controlAdapters/store/controlAdaptersSlice';
+import type { ControlNetConfig, IPAdapterConfig, T2IAdapterConfig } from 'features/controlAdapters/store/types';
+import {
+  initialControlNet,
+  initialIPAdapter,
+  initialT2IAdapter,
+} from 'features/controlAdapters/util/buildControlAdapter';
 import { setHrfEnabled, setHrfMethod, setHrfStrength } from 'features/hrf/store/hrfSlice';
-import { loraRecalled, lorasCleared } from 'features/lora/store/loraSlice';
-import { isModelIdentifier } from 'features/nodes/types/common';
-import type {
-  ControlNetMetadataItem,
-  CoreMetadata,
-  IPAdapterMetadataItem,
-  LoRAMetadataItem,
-  T2IAdapterMetadataItem,
-} from 'features/nodes/types/metadata';
+import type { LoRA } from 'features/lora/store/loraSlice';
+import { defaultLoRAConfig, loraRecalled, lorasCleared } from 'features/lora/store/loraSlice';
+import type { ModelIdentifierWithBase } from 'features/nodes/types/common';
+import {
+  zControlField,
+  zIPAdapterField,
+  zModelIdentifierWithBase,
+  zT2IAdapterField,
+} from 'features/nodes/types/common';
 import { initialImageSelected, modelSelected } from 'features/parameters/store/actions';
 import {
   heightRecalled,
@@ -27,19 +35,18 @@ import {
   vaeSelected,
   widthRecalled,
 } from 'features/parameters/store/generationSlice';
-import type { ParameterModel } from 'features/parameters/types/parameterSchemas';
 import {
   isParameterCFGRescaleMultiplier,
   isParameterCFGScale,
   isParameterHeight,
   isParameterHRFEnabled,
   isParameterHRFMethod,
+  isParameterLoRAWeight,
   isParameterNegativePrompt,
   isParameterNegativeStylePromptSDXL,
   isParameterPositivePrompt,
   isParameterPositiveStylePromptSDXL,
   isParameterScheduler,
-  isParameterSDXLRefinerModel,
   isParameterSDXLRefinerNegativeAestheticScore,
   isParameterSDXLRefinerPositiveAestheticScore,
   isParameterSDXLRefinerStart,
@@ -49,13 +56,16 @@ import {
   isParameterWidth,
 } from 'features/parameters/types/parameterSchemas';
 import {
-  prepareControlNetMetadataItem,
-  prepareIPAdapterMetadataItem,
-  prepareLoRAMetadataItem,
-  prepareMainModelMetadataItem,
-  prepareT2IAdapterMetadataItem,
-  prepareVAEMetadataItem,
-} from 'features/parameters/util/modelMetadataHelpers';
+  fetchControlNetModel,
+  fetchIPAdapterModel,
+  fetchLoRAModel,
+  fetchMainModelConfig,
+  fetchRefinerModelConfig,
+  fetchT2IAdapterModel,
+  fetchVAEModelConfig,
+  getModelKey,
+  raiseIfBaseIncompatible,
+} from 'features/parameters/util/modelFetchingHelpers';
 import {
   refinerModelChanged,
   setNegativeStylePromptSDXL,
@@ -67,229 +77,663 @@ import {
   setRefinerStart,
   setRefinerSteps,
 } from 'features/sdxl/store/sdxlSlice';
-import { isNil } from 'lodash-es';
+import { t } from 'i18next';
+import { get, isArray, isNil } from 'lodash-es';
 import { useCallback } from 'react';
-import { useTranslation } from 'react-i18next';
-import type { ImageDTO } from 'services/api/types';
+import type { BaseModelType, ImageDTO } from 'services/api/types';
+import { v4 as uuidv4 } from 'uuid';
 
 const selectModel = createMemoizedSelector(selectGenerationSlice, (generation) => generation.model);
 
+/**
+ * A function that recalls from metadata from the full metadata object.
+ */
+type MetadataRecallFunc = (metadata: unknown, withToast?: boolean) => void;
+
+/**
+ * A function that recalls metadata from a specific metadata item.
+ */
+type MetadataItemRecallFunc = (metadataItem: unknown, withToast?: boolean) => void;
+
+/**
+ * Raised when metadata recall fails.
+ */
+export class MetadataRecallError extends Error {
+  /**
+   * Create MetadataRecallError
+   * @param {String} message
+   */
+  constructor(message: string) {
+    super(message);
+    this.name = this.constructor.name;
+  }
+}
+
+export class InvalidMetadataPropertyType extends MetadataRecallError {}
+
+const getProperty = <T = unknown>(
+  obj: unknown,
+  property: string,
+  typeGuard: (val: unknown) => val is T = (val: unknown): val is T => true
+): T => {
+  const val = get(obj, property) as unknown;
+  if (typeGuard(val)) {
+    return val;
+  }
+  throw new InvalidMetadataPropertyType(`Property ${property} is not of expected type`);
+};
+
+const getCurrentBase = () => selectModel(getStore().getState())?.base;
+
+const parameterSetToast = (parameter: string, description?: string) => {
+  toast({
+    title: t('toast.parameterSet', { parameter }),
+    description,
+    status: 'info',
+    duration: 2500,
+    isClosable: true,
+  });
+};
+
+const parameterNotSetToast = (parameter: string, description?: string) => {
+  toast({
+    title: t('toast.parameterNotSet', { parameter }),
+    description,
+    status: 'warning',
+    duration: 2500,
+    isClosable: true,
+  });
+};
+
+const allParameterSetToast = (description?: string) => {
+  toast({
+    title: t('toast.parametersSet'),
+    status: 'info',
+    description,
+    duration: 2500,
+    isClosable: true,
+  });
+};
+
+const allParameterNotSetToast = (description?: string) => {
+  toast({
+    title: t('toast.parametersNotSet'),
+    status: 'warning',
+    description,
+    duration: 2500,
+    isClosable: true,
+  });
+};
+
+const recall = (callback: () => void, parameter: string, withToast = true) => {
+  try {
+    callback();
+    withToast && parameterSetToast(parameter);
+  } catch (e) {
+    withToast && parameterNotSetToast(parameter, (e as Error).message);
+  }
+};
+
+const recallAsync = async (callback: () => Promise<void>, parameter: string, withToast = true) => {
+  try {
+    await callback();
+    withToast && parameterSetToast(parameter);
+  } catch (e) {
+    withToast && parameterNotSetToast(parameter, (e as Error).message);
+  }
+};
+
+export const recallPositivePrompt: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
+  recall(
+    () => {
+      const positive_prompt = getProperty(metadata, 'positive_prompt', isParameterPositivePrompt);
+      getStore().dispatch(setPositivePrompt(positive_prompt));
+    },
+    t('metadata.positivePrompt'),
+    withToast
+  );
+};
+
+export const recallNegativePrompt: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
+  recall(
+    () => {
+      const negative_prompt = getProperty(metadata, 'negative_prompt', isParameterNegativePrompt);
+      getStore().dispatch(setNegativePrompt(negative_prompt));
+    },
+    t('metadata.negativePrompt'),
+    withToast
+  );
+};
+
+export const recallSDXLPositiveStylePrompt: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
+  recall(
+    () => {
+      const positive_style_prompt = getProperty(metadata, 'positive_style_prompt', isParameterPositiveStylePromptSDXL);
+      getStore().dispatch(setPositiveStylePromptSDXL(positive_style_prompt));
+    },
+    t('sdxl.posStylePrompt'),
+    withToast
+  );
+};
+
+export const recallSDXLNegativeStylePrompt: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
+  recall(
+    () => {
+      const negative_style_prompt = getProperty(metadata, 'negative_style_prompt', isParameterNegativeStylePromptSDXL);
+      getStore().dispatch(setNegativeStylePromptSDXL(negative_style_prompt));
+    },
+    t('sdxl.negStylePrompt'),
+    withToast
+  );
+};
+
+export const recallSeed: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
+  recall(
+    () => {
+      const seed = getProperty(metadata, 'seed', isParameterSeed);
+      getStore().dispatch(setSeed(seed));
+    },
+    t('metadata.seed'),
+    withToast
+  );
+};
+
+export const recallCFGScale: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
+  recall(
+    () => {
+      const cfg_scale = getProperty(metadata, 'cfg_scale', isParameterCFGScale);
+      getStore().dispatch(setCfgScale(cfg_scale));
+    },
+    t('metadata.cfgScale'),
+    withToast
+  );
+};
+
+export const recallCFGRescaleMultiplier: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
+  recall(
+    () => {
+      const cfg_rescale_multiplier = getProperty(metadata, 'cfg_rescale_multiplier', isParameterCFGRescaleMultiplier);
+      getStore().dispatch(setCfgRescaleMultiplier(cfg_rescale_multiplier));
+    },
+    t('metadata.cfgRescaleMultiplier'),
+    withToast
+  );
+};
+
+export const recallScheduler: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
+  recall(
+    () => {
+      const scheduler = getProperty(metadata, 'scheduler', isParameterScheduler);
+      getStore().dispatch(setScheduler(scheduler));
+    },
+    t('metadata.scheduler'),
+    withToast
+  );
+};
+
+export const recallWidth: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
+  recall(
+    () => {
+      const width = getProperty(metadata, 'width', isParameterWidth);
+      getStore().dispatch(widthRecalled(width));
+    },
+    t('metadata.width'),
+    withToast
+  );
+};
+
+export const recallHeight: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
+  recall(
+    () => {
+      const height = getProperty(metadata, 'height', isParameterHeight);
+      getStore().dispatch(heightRecalled(height));
+    },
+    t('metadata.height'),
+    withToast
+  );
+};
+
+export const recallSteps: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
+  recall(
+    () => {
+      const steps = getProperty(metadata, 'steps', isParameterSteps);
+      getStore().dispatch(setSteps(steps));
+    },
+    t('metadata.steps'),
+    withToast
+  );
+};
+
+export const recallStrength: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
+  recall(
+    () => {
+      const strength = getProperty(metadata, 'strength', isParameterStrength);
+      getStore().dispatch(setImg2imgStrength(strength));
+    },
+    t('metadata.strength'),
+    withToast
+  );
+};
+
+export const recallHRFEnabled: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
+  recall(
+    () => {
+      const hrf_enabled = getProperty(metadata, 'hrf_enabled', isParameterHRFEnabled);
+      getStore().dispatch(setHrfEnabled(hrf_enabled));
+    },
+    t('hrf.metadata.enabled'),
+    withToast
+  );
+};
+
+export const recallHRFStrength: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
+  recall(
+    () => {
+      const hrf_strength = getProperty(metadata, 'hrf_strength', isParameterStrength);
+      getStore().dispatch(setHrfStrength(hrf_strength));
+    },
+    t('hrf.metadata.strength'),
+    withToast
+  );
+};
+
+export const recallHRFMethod: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
+  recall(
+    () => {
+      const hrf_method = getProperty(metadata, 'hrf_method', isParameterHRFMethod);
+      getStore().dispatch(setHrfMethod(hrf_method));
+    },
+    t('hrf.metadata.method'),
+    withToast
+  );
+};
+
+export const recallRefinerSteps: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
+  recall(
+    () => {
+      const refiner_steps = getProperty(metadata, 'refiner_steps', isParameterSteps);
+      getStore().dispatch(setRefinerSteps(refiner_steps));
+    },
+    t('sdxl.steps'),
+    withToast
+  );
+};
+
+export const recallRefinerCFGScale: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
+  recall(
+    () => {
+      const refiner_cfg_scale = getProperty(metadata, 'refiner_cfg_scale', isParameterCFGScale);
+      getStore().dispatch(setRefinerCFGScale(refiner_cfg_scale));
+    },
+    t('sdxl.cfgScale'),
+    withToast
+  );
+};
+
+export const recallRefinerScheduler: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
+  recall(
+    () => {
+      const refiner_scheduler = getProperty(metadata, 'refiner_scheduler', isParameterScheduler);
+      getStore().dispatch(setRefinerScheduler(refiner_scheduler));
+    },
+    t('sdxl.cfgScale'),
+    withToast
+  );
+};
+
+export const recallRefinerPositiveAestheticScore: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
+  recall(
+    () => {
+      const refiner_positive_aesthetic_score = getProperty(
+        metadata,
+        'refiner_positive_aesthetic_score',
+        isParameterSDXLRefinerPositiveAestheticScore
+      );
+      getStore().dispatch(setRefinerPositiveAestheticScore(refiner_positive_aesthetic_score));
+    },
+    t('sdxl.posAestheticScore'),
+    withToast
+  );
+};
+
+export const recallRefinerNegativeAestheticScore: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
+  recall(
+    () => {
+      const refiner_negative_aesthetic_score = getProperty(
+        metadata,
+        'refiner_negative_aesthetic_score',
+        isParameterSDXLRefinerNegativeAestheticScore
+      );
+      getStore().dispatch(setRefinerNegativeAestheticScore(refiner_negative_aesthetic_score));
+    },
+    t('sdxl.negAestheticScore'),
+    withToast
+  );
+};
+
+export const recallRefinerStart: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
+  recall(
+    () => {
+      const refiner_start = getProperty(metadata, 'refiner_start', isParameterSDXLRefinerStart);
+      getStore().dispatch(setRefinerStart(refiner_start));
+    },
+    t('sdxl.refinerStart'),
+    withToast
+  );
+};
+
+export const prepareMainModelMetadataItem = async (model: unknown): Promise<ModelIdentifierWithBase> => {
+  const key = await getModelKey(model, 'main');
+  const mainModel = await fetchMainModelConfig(key);
+  return zModelIdentifierWithBase.parse(mainModel);
+};
+
+const recallModelAsync: MetadataRecallFunc = async (metadata: unknown, withToast = true) => {
+  await recallAsync(
+    async () => {
+      const modelMetadataItem = getProperty(metadata, 'model');
+      const model = await prepareMainModelMetadataItem(modelMetadataItem);
+      getStore().dispatch(modelSelected(model));
+    },
+    t('metadata.model'),
+    withToast
+  );
+};
+
+export const prepareRefinerMetadataItem = async (
+  model: unknown,
+  currentBase: BaseModelType | undefined
+): Promise<ModelIdentifierWithBase> => {
+  const key = await getModelKey(model, 'main');
+  const refinerModel = await fetchRefinerModelConfig(key);
+  raiseIfBaseIncompatible('sdxl-refiner', currentBase, 'Refiner incompatible with currently-selected model');
+  return zModelIdentifierWithBase.parse(refinerModel);
+};
+
+const recallRefinerModelAsync: MetadataRecallFunc = async (metadata: unknown, withToast = true) => {
+  await recallAsync(
+    async () => {
+      const refinerMetadataItem = getProperty(metadata, 'refiner_model');
+      const refiner = await prepareRefinerMetadataItem(refinerMetadataItem, getCurrentBase());
+      getStore().dispatch(refinerModelChanged(refiner));
+    },
+    t('sdxl.refinerModel'),
+    withToast
+  );
+};
+
+export const prepareVAEMetadataItem = async (
+  vae: unknown,
+  currentBase: BaseModelType | undefined
+): Promise<ModelIdentifierWithBase> => {
+  const key = await getModelKey(vae, 'vae');
+  const vaeModel = await fetchVAEModelConfig(key);
+  raiseIfBaseIncompatible(vaeModel.base, currentBase, 'VAE incompatible with currently-selected model');
+  return zModelIdentifierWithBase.parse(vaeModel);
+};
+
+const recallVAEAsync: MetadataRecallFunc = async (metadata: unknown, withToast = true) => {
+  await recallAsync(
+    async () => {
+      const currentBase = getCurrentBase();
+      const vaeMetadataItem = getProperty(metadata, 'vae');
+      if (isNil(vaeMetadataItem)) {
+        getStore().dispatch(vaeSelected(null));
+      } else {
+        const vae = await prepareVAEMetadataItem(vaeMetadataItem, currentBase);
+        getStore().dispatch(vaeSelected(vae));
+      }
+    },
+    t('metadata.vae'),
+    withToast
+  );
+};
+
+export const prepareLoRAMetadataItem = async (
+  loraMetadataItem: unknown,
+  currentBase: BaseModelType | undefined
+): Promise<LoRA> => {
+  const lora = getProperty(loraMetadataItem, 'lora');
+  const weight = getProperty(loraMetadataItem, 'weight');
+  const key = await getModelKey(lora, 'lora');
+  const loraModel = await fetchLoRAModel(key);
+  raiseIfBaseIncompatible(loraModel.base, currentBase, 'LoRA incompatible with currently-selected model');
+  return {
+    key: loraModel.key,
+    base: loraModel.base,
+    weight: isParameterLoRAWeight(weight) ? weight : defaultLoRAConfig.weight,
+    isEnabled: true,
+  };
+};
+
+const recallLoRAAsync: MetadataItemRecallFunc = async (metadataItem: unknown, withToast = true) => {
+  await recallAsync(
+    async () => {
+      const currentBase = getCurrentBase();
+      const lora = await prepareLoRAMetadataItem(metadataItem, currentBase);
+      getStore().dispatch(loraRecalled(lora));
+    },
+    t('models.lora'),
+    withToast
+  );
+};
+
+export const prepareControlNetMetadataItem = async (
+  metadataItem: unknown,
+  currentBase: BaseModelType | undefined
+): Promise<ControlNetConfig> => {
+  const control_model = getProperty(metadataItem, 'control_model');
+  const key = await getModelKey(control_model, 'controlnet');
+  const controlNetModel = await fetchControlNetModel(key);
+  raiseIfBaseIncompatible(controlNetModel.base, currentBase, 'ControlNet incompatible with currently-selected model');
+
+  const image = zControlField.shape.image.nullish().catch(null).parse(getProperty(metadataItem, 'image'));
+  const control_weight = zControlField.shape.control_weight
+    .nullish()
+    .catch(null)
+    .parse(getProperty(metadataItem, 'control_weight'));
+  const begin_step_percent = zControlField.shape.begin_step_percent
+    .nullish()
+    .catch(null)
+    .parse(getProperty(metadataItem, 'begin_step_percent'));
+  const end_step_percent = zControlField.shape.end_step_percent
+    .nullish()
+    .catch(null)
+    .parse(getProperty(metadataItem, 'end_step_percent'));
+  const control_mode = zControlField.shape.control_mode
+    .nullish()
+    .catch(null)
+    .parse(getProperty(metadataItem, 'control_mode'));
+  const resize_mode = zControlField.shape.resize_mode
+    .nullish()
+    .catch(null)
+    .parse(getProperty(metadataItem, 'resize_mode'));
+
+  // We don't save the original image that was processed into a control image, only the processed image
+  const processorType = 'none';
+  const processorNode = CONTROLNET_PROCESSORS.none.default;
+
+  const controlnet: ControlNetConfig = {
+    type: 'controlnet',
+    isEnabled: true,
+    model: zModelIdentifierWithBase.parse(controlNetModel),
+    weight: typeof control_weight === 'number' ? control_weight : initialControlNet.weight,
+    beginStepPct: begin_step_percent ?? initialControlNet.beginStepPct,
+    endStepPct: end_step_percent ?? initialControlNet.endStepPct,
+    controlMode: control_mode ?? initialControlNet.controlMode,
+    resizeMode: resize_mode ?? initialControlNet.resizeMode,
+    controlImage: image?.image_name ?? null,
+    processedControlImage: image?.image_name ?? null,
+    processorType,
+    processorNode,
+    shouldAutoConfig: true,
+    id: uuidv4(),
+  };
+
+  return controlnet;
+};
+
+const recallControlNetAsync: MetadataItemRecallFunc = async (metadataItem: unknown, withToast = true) => {
+  await recallAsync(
+    async () => {
+      const currentBase = getCurrentBase();
+      const controlNetConfig = await prepareControlNetMetadataItem(metadataItem, currentBase);
+      getStore().dispatch(controlAdapterRecalled(controlNetConfig));
+    },
+    t('common.controlNet'),
+    withToast
+  );
+};
+
+export const prepareT2IAdapterMetadataItem = async (
+  metadataItem: unknown,
+  currentBase: BaseModelType | undefined
+): Promise<T2IAdapterConfig> => {
+  const t2i_adapter_model = getProperty(metadataItem, 't2i_adapter_model');
+  const key = await getModelKey(t2i_adapter_model, 't2i_adapter');
+  const t2iAdapterModel = await fetchT2IAdapterModel(key);
+  raiseIfBaseIncompatible(t2iAdapterModel.base, currentBase, 'T2I Adapter incompatible with currently-selected model');
+
+  const image = zT2IAdapterField.shape.image.nullish().catch(null).parse(getProperty(metadataItem, 'image'));
+  const weight = zT2IAdapterField.shape.weight.nullish().catch(null).parse(getProperty(metadataItem, 'weight'));
+  const begin_step_percent = zT2IAdapterField.shape.begin_step_percent
+    .nullish()
+    .catch(null)
+    .parse(getProperty(metadataItem, 'begin_step_percent'));
+  const end_step_percent = zT2IAdapterField.shape.end_step_percent
+    .nullish()
+    .catch(null)
+    .parse(getProperty(metadataItem, 'end_step_percent'));
+  const resize_mode = zT2IAdapterField.shape.resize_mode
+    .nullish()
+    .catch(null)
+    .parse(getProperty(metadataItem, 'resize_mode'));
+
+  // We don't save the original image that was processed into a control image, only the processed image
+  const processorType = 'none';
+  const processorNode = CONTROLNET_PROCESSORS.none.default;
+
+  const t2iAdapter: T2IAdapterConfig = {
+    type: 't2i_adapter',
+    isEnabled: true,
+    model: zModelIdentifierWithBase.parse(t2iAdapterModel),
+    weight: typeof weight === 'number' ? weight : initialT2IAdapter.weight,
+    beginStepPct: begin_step_percent ?? initialT2IAdapter.beginStepPct,
+    endStepPct: end_step_percent ?? initialT2IAdapter.endStepPct,
+    resizeMode: resize_mode ?? initialT2IAdapter.resizeMode,
+    controlImage: image?.image_name ?? null,
+    processedControlImage: image?.image_name ?? null,
+    processorType,
+    processorNode,
+    shouldAutoConfig: true,
+    id: uuidv4(),
+  };
+
+  return t2iAdapter;
+};
+
+const recallT2IAdapterAsync: MetadataItemRecallFunc = async (metadataItem: unknown, withToast = true) => {
+  await recallAsync(
+    async () => {
+      const currentBase = getCurrentBase();
+      const t2iAdapterConfig = await prepareT2IAdapterMetadataItem(metadataItem, currentBase);
+      getStore().dispatch(controlAdapterRecalled(t2iAdapterConfig));
+    },
+    t('common.t2iAdapter'),
+    withToast
+  );
+};
+
+export const prepareIPAdapterMetadataItem = async (
+  metadataItem: unknown,
+  currentBase: BaseModelType | undefined
+): Promise<IPAdapterConfig> => {
+  const ip_adapter_model = getProperty(metadataItem, 'ip_adapter_model');
+  const key = await getModelKey(ip_adapter_model, 'ip_adapter');
+  const ipAdapterModel = await fetchIPAdapterModel(key);
+  raiseIfBaseIncompatible(ipAdapterModel.base, currentBase, 'T2I Adapter incompatible with currently-selected model');
+
+  const image = zIPAdapterField.shape.image.nullish().catch(null).parse(getProperty(metadataItem, 'image'));
+  const weight = zIPAdapterField.shape.weight.nullish().catch(null).parse(getProperty(metadataItem, 'weight'));
+  const begin_step_percent = zIPAdapterField.shape.begin_step_percent
+    .nullish()
+    .catch(null)
+    .parse(getProperty(metadataItem, 'begin_step_percent'));
+  const end_step_percent = zIPAdapterField.shape.end_step_percent
+    .nullish()
+    .catch(null)
+    .parse(getProperty(metadataItem, 'end_step_percent'));
+
+  const ipAdapter: IPAdapterConfig = {
+    id: uuidv4(),
+    type: 'ip_adapter',
+    isEnabled: true,
+    model: zModelIdentifierWithBase.parse(ipAdapterModel),
+    controlImage: image?.image_name ?? null,
+    weight: weight ?? initialIPAdapter.weight,
+    beginStepPct: begin_step_percent ?? initialIPAdapter.beginStepPct,
+    endStepPct: end_step_percent ?? initialIPAdapter.endStepPct,
+  };
+
+  return ipAdapter;
+};
+
+const recallIPAdapterAsync: MetadataItemRecallFunc = async (metadataItem: unknown, withToast) => {
+  await recallAsync(
+    async () => {
+      const currentBase = getCurrentBase();
+      const ipAdapterConfig = await prepareIPAdapterMetadataItem(metadataItem, currentBase);
+      getStore().dispatch(controlAdapterRecalled(ipAdapterConfig));
+    },
+    t('common.ipAdapter'),
+    withToast
+  );
+};
+
 export const useRecallParameters = () => {
   const dispatch = useAppDispatch();
-  const toaster = useAppToaster();
-  const { t } = useTranslation();
-  const model = useAppSelector(selectModel);
 
-  const parameterSetToast = useCallback(() => {
-    toaster({
-      title: t('toast.parameterSet'),
-      status: 'info',
-      duration: 2500,
-      isClosable: true,
-    });
-  }, [t, toaster]);
-
-  const parameterNotSetToast = useCallback(
-    (description?: string) => {
-      toaster({
-        title: t('toast.parameterNotSet'),
-        description,
-        status: 'warning',
-        duration: 2500,
-        isClosable: true,
-      });
-    },
-    [t, toaster]
-  );
-
-  const allParameterSetToast = useCallback(() => {
-    toaster({
-      title: t('toast.parametersSet'),
-      status: 'info',
-      duration: 2500,
-      isClosable: true,
-    });
-  }, [t, toaster]);
-
-  const allParameterNotSetToast = useCallback(
-    (description?: string) => {
-      toaster({
-        title: t('toast.parametersNotSet'),
-        status: 'warning',
-        description,
-        duration: 2500,
-        isClosable: true,
-      });
-    },
-    [t, toaster]
-  );
-
-  const recallBothPrompts = useCallback(
-    (positivePrompt: unknown, negativePrompt: unknown, positiveStylePrompt: unknown, negativeStylePrompt: unknown) => {
+  const recallBothPrompts = useCallback<MetadataRecallFunc>(
+    (metadata: unknown) => {
+      const positive_prompt = getProperty(metadata, 'positive_prompt');
+      const negative_prompt = getProperty(metadata, 'negative_prompt');
+      const positive_style_prompt = getProperty(metadata, 'positive_style_prompt');
+      const negative_style_prompt = getProperty(metadata, 'negative_style_prompt');
       if (
-        isParameterPositivePrompt(positivePrompt) ||
-        isParameterNegativePrompt(negativePrompt) ||
-        isParameterPositiveStylePromptSDXL(positiveStylePrompt) ||
-        isParameterNegativeStylePromptSDXL(negativeStylePrompt)
+        isParameterPositivePrompt(positive_prompt) ||
+        isParameterNegativePrompt(negative_prompt) ||
+        isParameterPositiveStylePromptSDXL(positive_style_prompt) ||
+        isParameterNegativeStylePromptSDXL(negative_style_prompt)
       ) {
-        if (isParameterPositivePrompt(positivePrompt)) {
-          dispatch(setPositivePrompt(positivePrompt));
+        if (isParameterPositivePrompt(positive_prompt)) {
+          dispatch(setPositivePrompt(positive_prompt));
         }
 
-        if (isParameterNegativePrompt(negativePrompt)) {
-          dispatch(setNegativePrompt(negativePrompt));
+        if (isParameterNegativePrompt(negative_prompt)) {
+          dispatch(setNegativePrompt(negative_prompt));
         }
 
-        if (isParameterPositiveStylePromptSDXL(positiveStylePrompt)) {
-          dispatch(setPositiveStylePromptSDXL(positiveStylePrompt));
+        if (isParameterPositiveStylePromptSDXL(positive_style_prompt)) {
+          dispatch(setPositiveStylePromptSDXL(positive_style_prompt));
         }
 
-        if (isParameterPositiveStylePromptSDXL(negativeStylePrompt)) {
-          dispatch(setNegativeStylePromptSDXL(negativeStylePrompt));
+        if (isParameterPositiveStylePromptSDXL(negative_style_prompt)) {
+          dispatch(setNegativeStylePromptSDXL(negative_style_prompt));
         }
 
-        parameterSetToast();
+        parameterSetToast(t('metadata.allPrompts'));
         return;
       }
-      parameterNotSetToast();
+      parameterNotSetToast(t('metadata.allPrompts'));
     },
-    [dispatch, parameterSetToast, parameterNotSetToast]
+    [dispatch]
   );
 
-  const recallPositivePrompt = useCallback(
-    (positivePrompt: unknown) => {
-      if (!isParameterPositivePrompt(positivePrompt)) {
-        parameterNotSetToast();
-        return;
-      }
-      dispatch(setPositivePrompt(positivePrompt));
-      parameterSetToast();
-    },
-    [dispatch, parameterSetToast, parameterNotSetToast]
-  );
+  const recallWidthAndHeight = useCallback<MetadataRecallFunc>(
+    (metadata: unknown) => {
+      const width = getProperty(metadata, 'width');
+      const height = getProperty(metadata, 'height');
 
-  const recallNegativePrompt = useCallback(
-    (negativePrompt: unknown) => {
-      if (!isParameterNegativePrompt(negativePrompt)) {
-        parameterNotSetToast();
-        return;
-      }
-      dispatch(setNegativePrompt(negativePrompt));
-      parameterSetToast();
-    },
-    [dispatch, parameterSetToast, parameterNotSetToast]
-  );
-
-  const recallSDXLPositiveStylePrompt = useCallback(
-    (positiveStylePrompt: unknown) => {
-      if (!isParameterPositiveStylePromptSDXL(positiveStylePrompt)) {
-        parameterNotSetToast();
-        return;
-      }
-      dispatch(setPositiveStylePromptSDXL(positiveStylePrompt));
-      parameterSetToast();
-    },
-    [dispatch, parameterSetToast, parameterNotSetToast]
-  );
-
-  const recallSDXLNegativeStylePrompt = useCallback(
-    (negativeStylePrompt: unknown) => {
-      if (!isParameterNegativeStylePromptSDXL(negativeStylePrompt)) {
-        parameterNotSetToast();
-        return;
-      }
-      dispatch(setNegativeStylePromptSDXL(negativeStylePrompt));
-      parameterSetToast();
-    },
-    [dispatch, parameterSetToast, parameterNotSetToast]
-  );
-
-  const recallSeed = useCallback(
-    (seed: unknown) => {
-      if (!isParameterSeed(seed)) {
-        parameterNotSetToast();
-        return;
-      }
-      dispatch(setSeed(seed));
-      parameterSetToast();
-    },
-    [dispatch, parameterSetToast, parameterNotSetToast]
-  );
-
-  const recallCfgScale = useCallback(
-    (cfgScale: unknown) => {
-      if (!isParameterCFGScale(cfgScale)) {
-        parameterNotSetToast();
-        return;
-      }
-      dispatch(setCfgScale(cfgScale));
-      parameterSetToast();
-    },
-    [dispatch, parameterSetToast, parameterNotSetToast]
-  );
-
-  const recallCfgRescaleMultiplier = useCallback(
-    (cfgRescaleMultiplier: unknown) => {
-      if (!isParameterCFGRescaleMultiplier(cfgRescaleMultiplier)) {
-        parameterNotSetToast();
-        return;
-      }
-      dispatch(setCfgRescaleMultiplier(cfgRescaleMultiplier));
-      parameterSetToast();
-    },
-    [dispatch, parameterSetToast, parameterNotSetToast]
-  );
-
-  const recallScheduler = useCallback(
-    (scheduler: unknown) => {
-      if (!isParameterScheduler(scheduler)) {
-        parameterNotSetToast();
-        return;
-      }
-      dispatch(setScheduler(scheduler));
-      parameterSetToast();
-    },
-    [dispatch, parameterSetToast, parameterNotSetToast]
-  );
-
-  const recallSteps = useCallback(
-    (steps: unknown) => {
-      if (!isParameterSteps(steps)) {
-        parameterNotSetToast();
-        return;
-      }
-      dispatch(setSteps(steps));
-      parameterSetToast();
-    },
-    [dispatch, parameterSetToast, parameterNotSetToast]
-  );
-
-  const recallWidth = useCallback(
-    (width: unknown) => {
-      if (!isParameterWidth(width)) {
-        parameterNotSetToast();
-        return;
-      }
-      dispatch(widthRecalled(width));
-      parameterSetToast();
-    },
-    [dispatch, parameterSetToast, parameterNotSetToast]
-  );
-
-  const recallHeight = useCallback(
-    (height: unknown) => {
-      if (!isParameterHeight(height)) {
-        parameterNotSetToast();
-        return;
-      }
-      dispatch(heightRecalled(height));
-      parameterSetToast();
-    },
-    [dispatch, parameterSetToast, parameterNotSetToast]
-  );
-
-  const recallWidthAndHeight = useCallback(
-    (width: unknown, height: unknown) => {
       if (!isParameterWidth(width)) {
         allParameterNotSetToast();
         return;
@@ -302,144 +746,7 @@ export const useRecallParameters = () => {
       dispatch(widthRecalled(width));
       allParameterSetToast();
     },
-    [dispatch, allParameterSetToast, allParameterNotSetToast]
-  );
-
-  const recallStrength = useCallback(
-    (strength: unknown) => {
-      if (!isParameterStrength(strength)) {
-        parameterNotSetToast();
-        return;
-      }
-      dispatch(setImg2imgStrength(strength));
-      parameterSetToast();
-    },
-    [dispatch, parameterSetToast, parameterNotSetToast]
-  );
-
-  const recallHrfEnabled = useCallback(
-    (hrfEnabled: unknown) => {
-      if (!isParameterHRFEnabled(hrfEnabled)) {
-        parameterNotSetToast();
-        return;
-      }
-      dispatch(setHrfEnabled(hrfEnabled));
-      parameterSetToast();
-    },
-    [dispatch, parameterSetToast, parameterNotSetToast]
-  );
-
-  const recallHrfStrength = useCallback(
-    (hrfStrength: unknown) => {
-      if (!isParameterStrength(hrfStrength)) {
-        parameterNotSetToast();
-        return;
-      }
-      dispatch(setHrfStrength(hrfStrength));
-      parameterSetToast();
-    },
-    [dispatch, parameterSetToast, parameterNotSetToast]
-  );
-
-  const recallHrfMethod = useCallback(
-    (hrfMethod: unknown) => {
-      if (!isParameterHRFMethod(hrfMethod)) {
-        parameterNotSetToast();
-        return;
-      }
-      dispatch(setHrfMethod(hrfMethod));
-      parameterSetToast();
-    },
-    [dispatch, parameterSetToast, parameterNotSetToast]
-  );
-
-  const recallModel = useCallback(
-    async (modelMetadataItem: unknown) => {
-      try {
-        const model = await prepareMainModelMetadataItem(modelMetadataItem);
-        dispatch(modelSelected(model));
-        parameterSetToast();
-      } catch (e) {
-        parameterNotSetToast((e as unknown as Error).message);
-        return;
-      }
-    },
-    [dispatch, parameterSetToast, parameterNotSetToast]
-  );
-
-  const recallVaeModel = useCallback(
-    async (vaeMetadataItem: unknown) => {
-      if (isNil(vaeMetadataItem)) {
-        dispatch(vaeSelected(null));
-        parameterSetToast();
-        return;
-      }
-      try {
-        const vae = await prepareVAEMetadataItem(vaeMetadataItem);
-        dispatch(vaeSelected(vae));
-        parameterSetToast();
-      } catch (e) {
-        parameterNotSetToast((e as unknown as Error).message);
-        return;
-      }
-    },
-    [dispatch, parameterSetToast, parameterNotSetToast]
-  );
-
-  const recallLoRA = useCallback(
-    async (loraMetadataItem: LoRAMetadataItem) => {
-      try {
-        const lora = await prepareLoRAMetadataItem(loraMetadataItem, model?.base);
-        dispatch(loraRecalled(lora));
-        parameterSetToast();
-      } catch (e) {
-        parameterNotSetToast((e as unknown as Error).message);
-        return;
-      }
-    },
-    [model?.base, dispatch, parameterSetToast, parameterNotSetToast]
-  );
-
-  const recallControlNet = useCallback(
-    async (controlnetMetadataItem: ControlNetMetadataItem) => {
-      try {
-        const controlNetConfig = await prepareControlNetMetadataItem(controlnetMetadataItem, model?.base);
-        dispatch(controlAdapterRecalled(controlNetConfig));
-        parameterSetToast();
-      } catch (e) {
-        parameterNotSetToast((e as unknown as Error).message);
-        return;
-      }
-    },
-    [model?.base, dispatch, parameterSetToast, parameterNotSetToast]
-  );
-
-  const recallT2IAdapter = useCallback(
-    async (t2iAdapterMetadataItem: T2IAdapterMetadataItem) => {
-      try {
-        const t2iAdapterConfig = await prepareT2IAdapterMetadataItem(t2iAdapterMetadataItem, model?.base);
-        dispatch(controlAdapterRecalled(t2iAdapterConfig));
-        parameterSetToast();
-      } catch (e) {
-        parameterNotSetToast((e as unknown as Error).message);
-        return;
-      }
-    },
-    [model?.base, dispatch, parameterSetToast, parameterNotSetToast]
-  );
-
-  const recallIPAdapter = useCallback(
-    async (ipAdapterMetadataItem: IPAdapterMetadataItem) => {
-      try {
-        const ipAdapterConfig = await prepareIPAdapterMetadataItem(ipAdapterMetadataItem, model?.base);
-        dispatch(controlAdapterRecalled(ipAdapterConfig));
-        parameterSetToast();
-      } catch (e) {
-        parameterNotSetToast((e as unknown as Error).message);
-        return;
-      }
-    },
-    [model?.base, dispatch, parameterSetToast, parameterNotSetToast]
+    [dispatch]
   );
 
   const sendToImageToImage = useCallback(
@@ -449,197 +756,75 @@ export const useRecallParameters = () => {
     [dispatch]
   );
 
-  const recallAllParameters = useCallback(
-    async (metadata: CoreMetadata | undefined) => {
+  const recallAllParameters = useCallback<MetadataRecallFunc>(
+    async (metadata: unknown) => {
       if (!metadata) {
         allParameterNotSetToast();
         return;
       }
 
-      const {
-        cfg_scale,
-        cfg_rescale_multiplier,
-        height,
-        model,
-        positive_prompt,
-        negative_prompt,
-        scheduler,
-        vae,
-        seed,
-        steps,
-        width,
-        strength,
-        hrf_enabled,
-        hrf_strength,
-        hrf_method,
-        positive_style_prompt,
-        negative_style_prompt,
-        refiner_model,
-        refiner_cfg_scale,
-        refiner_steps,
-        refiner_scheduler,
-        refiner_positive_aesthetic_score,
-        refiner_negative_aesthetic_score,
-        refiner_start,
-        loras,
-        controlnets,
-        ipAdapters,
-        t2iAdapters,
-      } = metadata;
+      await recallModelAsync(metadata, false);
 
-      let newModel: ParameterModel | undefined = undefined;
+      recallCFGScale(metadata, false);
+      recallCFGRescaleMultiplier(metadata, false);
+      recallPositivePrompt(metadata, false);
+      recallNegativePrompt(metadata, false);
+      recallScheduler(metadata, false);
+      recallSeed(metadata, false);
+      recallSteps(metadata, false);
+      recallWidth(metadata, false);
+      recallHeight(metadata, false);
+      recallStrength(metadata, false);
+      recallHRFEnabled(metadata, false);
+      recallHRFMethod(metadata, false);
+      recallHRFStrength(metadata, false);
 
-      if (isModelIdentifier(model)) {
-        try {
-          const _model = await prepareMainModelMetadataItem(model);
-          dispatch(modelSelected(_model));
-          newModel = _model;
-        } catch {
-          return;
-        }
-      }
+      // SDXL
+      recallSDXLPositiveStylePrompt(metadata, false);
+      recallSDXLNegativeStylePrompt(metadata, false);
+      recallRefinerSteps(metadata, false);
+      recallRefinerCFGScale(metadata, false);
+      recallRefinerScheduler(metadata, false);
+      recallRefinerPositiveAestheticScore(metadata, false);
+      recallRefinerNegativeAestheticScore(metadata, false);
+      recallRefinerStart(metadata, false);
 
-      if (isParameterCFGScale(cfg_scale)) {
-        dispatch(setCfgScale(cfg_scale));
-      }
-
-      if (isParameterCFGRescaleMultiplier(cfg_rescale_multiplier)) {
-        dispatch(setCfgRescaleMultiplier(cfg_rescale_multiplier));
-      }
-
-      if (isParameterPositivePrompt(positive_prompt)) {
-        dispatch(setPositivePrompt(positive_prompt));
-      }
-
-      if (isParameterNegativePrompt(negative_prompt)) {
-        dispatch(setNegativePrompt(negative_prompt));
-      }
-
-      if (isParameterScheduler(scheduler)) {
-        dispatch(setScheduler(scheduler));
-      }
-      if (isModelIdentifier(vae) || isNil(vae)) {
-        if (isNil(vae)) {
-          dispatch(vaeSelected(null));
-        } else {
-          try {
-            const _vae = await prepareVAEMetadataItem(vae, newModel?.base);
-            dispatch(vaeSelected(_vae));
-          } catch {
-            return;
-          }
-        }
-      }
-
-      if (isParameterSeed(seed)) {
-        dispatch(setSeed(seed));
-      }
-
-      if (isParameterSteps(steps)) {
-        dispatch(setSteps(steps));
-      }
-
-      if (isParameterWidth(width)) {
-        dispatch(widthRecalled(width));
-      }
-
-      if (isParameterHeight(height)) {
-        dispatch(heightRecalled(height));
-      }
-
-      if (isParameterStrength(strength)) {
-        dispatch(setImg2imgStrength(strength));
-      }
-
-      if (isParameterHRFEnabled(hrf_enabled)) {
-        dispatch(setHrfEnabled(hrf_enabled));
-      }
-
-      if (isParameterStrength(hrf_strength)) {
-        dispatch(setHrfStrength(hrf_strength));
-      }
-
-      if (isParameterHRFMethod(hrf_method)) {
-        dispatch(setHrfMethod(hrf_method));
-      }
-
-      if (isParameterPositiveStylePromptSDXL(positive_style_prompt)) {
-        dispatch(setPositiveStylePromptSDXL(positive_style_prompt));
-      }
-
-      if (isParameterNegativeStylePromptSDXL(negative_style_prompt)) {
-        dispatch(setNegativeStylePromptSDXL(negative_style_prompt));
-      }
-
-      if (isParameterSDXLRefinerModel(refiner_model)) {
-        dispatch(refinerModelChanged(refiner_model));
-      }
-
-      if (isParameterSteps(refiner_steps)) {
-        dispatch(setRefinerSteps(refiner_steps));
-      }
-
-      if (isParameterCFGScale(refiner_cfg_scale)) {
-        dispatch(setRefinerCFGScale(refiner_cfg_scale));
-      }
-
-      if (isParameterScheduler(refiner_scheduler)) {
-        dispatch(setRefinerScheduler(refiner_scheduler));
-      }
-
-      if (isParameterSDXLRefinerPositiveAestheticScore(refiner_positive_aesthetic_score)) {
-        dispatch(setRefinerPositiveAestheticScore(refiner_positive_aesthetic_score));
-      }
-
-      if (isParameterSDXLRefinerNegativeAestheticScore(refiner_negative_aesthetic_score)) {
-        dispatch(setRefinerNegativeAestheticScore(refiner_negative_aesthetic_score));
-      }
-
-      if (isParameterSDXLRefinerStart(refiner_start)) {
-        dispatch(setRefinerStart(refiner_start));
-      }
+      await recallVAEAsync(metadata, false);
+      await recallRefinerModelAsync(metadata, false);
 
       dispatch(lorasCleared());
-      loras?.forEach(async (loraMetadataItem) => {
-        try {
-          const lora = await prepareLoRAMetadataItem(loraMetadataItem, newModel?.base);
-          dispatch(loraRecalled(lora));
-        } catch {
-          return;
-        }
-      });
+      const loraMetadataArray = getProperty(metadata, 'loras');
+      if (isArray(loraMetadataArray)) {
+        loraMetadataArray.forEach(async (loraMetadataItem) => {
+          await recallLoRAAsync(loraMetadataItem, false);
+        });
+      }
 
       dispatch(controlAdaptersReset());
-      controlnets?.forEach(async (controlNetMetadataItem) => {
-        try {
-          const controlNet = await prepareControlNetMetadataItem(controlNetMetadataItem, newModel?.base);
-          dispatch(controlAdapterRecalled(controlNet));
-        } catch {
-          return;
-        }
-      });
+      const controlNetMetadataArray = getProperty(metadata, 'controlnets');
+      if (isArray(controlNetMetadataArray)) {
+        controlNetMetadataArray.forEach(async (controlNetMetadataItem) => {
+          await recallControlNetAsync(controlNetMetadataItem, false);
+        });
+      }
 
-      ipAdapters?.forEach(async (ipAdapterMetadataItem) => {
-        try {
-          const ipAdapter = await prepareIPAdapterMetadataItem(ipAdapterMetadataItem, newModel?.base);
-          dispatch(controlAdapterRecalled(ipAdapter));
-        } catch {
-          return;
-        }
-      });
+      const ipAdapterMetadataArray = getProperty(metadata, 'ipAdapters');
+      if (isArray(ipAdapterMetadataArray)) {
+        ipAdapterMetadataArray.forEach(async (ipAdapterMetadataItem) => {
+          await recallIPAdapterAsync(ipAdapterMetadataItem, false);
+        });
+      }
 
-      t2iAdapters?.forEach(async (t2iAdapterMetadataItem) => {
-        try {
-          const t2iAdapter = await prepareT2IAdapterMetadataItem(t2iAdapterMetadataItem, newModel?.base);
-          dispatch(controlAdapterRecalled(t2iAdapter));
-        } catch {
-          return;
-        }
-      });
+      const t2iAdapterMetadataArray = getProperty(metadata, 't2iAdapters');
+      if (isArray(t2iAdapterMetadataArray)) {
+        t2iAdapterMetadataArray.forEach(async (t2iAdapterMetadataItem) => {
+          await recallT2IAdapterAsync(t2iAdapterMetadataItem, false);
+        });
+      }
 
       allParameterSetToast();
     },
-    [dispatch, allParameterSetToast, allParameterNotSetToast]
+    [dispatch]
   );
 
   return {
@@ -649,24 +834,25 @@ export const useRecallParameters = () => {
     recallSDXLPositiveStylePrompt,
     recallSDXLNegativeStylePrompt,
     recallSeed,
-    recallCfgScale,
-    recallCfgRescaleMultiplier,
-    recallModel,
+    recallCFGScale,
+    recallCFGRescaleMultiplier,
+    recallModel: recallModelAsync,
     recallScheduler,
-    recallVaeModel,
+    recallVaeModel: recallVAEAsync,
     recallSteps,
     recallWidth,
     recallHeight,
     recallWidthAndHeight,
     recallStrength,
-    recallHrfEnabled,
-    recallHrfStrength,
-    recallHrfMethod,
-    recallLoRA,
-    recallControlNet,
-    recallIPAdapter,
-    recallT2IAdapter,
+    recallHRFEnabled,
+    recallHRFStrength,
+    recallHRFMethod,
+    recallLoRA: recallLoRAAsync,
+    recallControlNet: recallControlNetAsync,
+    recallIPAdapter: recallIPAdapterAsync,
+    recallT2IAdapter: recallT2IAdapterAsync,
     recallAllParameters,
+    recallRefinerModel: recallRefinerModelAsync,
     sendToImageToImage,
   };
 };
diff --git a/invokeai/frontend/web/src/features/parameters/types/parameterSchemas.ts b/invokeai/frontend/web/src/features/parameters/types/parameterSchemas.ts
index 20953ec266..8d46add8c8 100644
--- a/invokeai/frontend/web/src/features/parameters/types/parameterSchemas.ts
+++ b/invokeai/frontend/web/src/features/parameters/types/parameterSchemas.ts
@@ -1,14 +1,7 @@
 import { NUMPY_RAND_MAX } from 'app/constants';
 import {
-  zBaseModel,
-  zControlNetModelField,
-  zIPAdapterModelField,
-  zLoRAModelField,
   zModelIdentifierWithBase,
   zSchedulerField,
-  zSDXLRefinerModelField,
-  zT2IAdapterModelField,
-  zVAEModelField,
 } from 'features/nodes/types/common';
 import { z } from 'zod';
 
@@ -111,42 +104,42 @@ export const isParameterModel = (val: unknown): val is ParameterModel => zParame
 // #endregion
 
 // #region SDXL Refiner Model
-export const zParameterSDXLRefinerModel = zSDXLRefinerModelField.extend({ base: zBaseModel });
+export const zParameterSDXLRefinerModel = zModelIdentifierWithBase;
 export type ParameterSDXLRefinerModel = z.infer<typeof zParameterSDXLRefinerModel>;
 export const isParameterSDXLRefinerModel = (val: unknown): val is ParameterSDXLRefinerModel =>
   zParameterSDXLRefinerModel.safeParse(val).success;
 // #endregion
 
 // #region VAE Model
-export const zParameterVAEModel = zVAEModelField.extend({ base: zBaseModel });
+export const zParameterVAEModel = zModelIdentifierWithBase;
 export type ParameterVAEModel = z.infer<typeof zParameterVAEModel>;
 export const isParameterVAEModel = (val: unknown): val is ParameterVAEModel =>
   zParameterVAEModel.safeParse(val).success;
 // #endregion
 
 // #region LoRA Model
-export const zParameterLoRAModel = zLoRAModelField.extend({ base: zBaseModel });
+export const zParameterLoRAModel = zModelIdentifierWithBase;
 export type ParameterLoRAModel = z.infer<typeof zParameterLoRAModel>;
 export const isParameterLoRAModel = (val: unknown): val is ParameterLoRAModel =>
   zParameterLoRAModel.safeParse(val).success;
 // #endregion
 
 // #region ControlNet Model
-export const zParameterControlNetModel = zControlNetModelField.extend({ base: zBaseModel });
+export const zParameterControlNetModel = zModelIdentifierWithBase;
 export type ParameterControlNetModel = z.infer<typeof zParameterLoRAModel>;
 export const isParameterControlNetModel = (val: unknown): val is ParameterControlNetModel =>
   zParameterControlNetModel.safeParse(val).success;
 // #endregion
 
 // #region IP Adapter Model
-export const zParameterIPAdapterModel = zIPAdapterModelField.extend({ base: zBaseModel });
+export const zParameterIPAdapterModel = zModelIdentifierWithBase;
 export type ParameterIPAdapterModel = z.infer<typeof zParameterIPAdapterModel>;
 export const isParameterIPAdapterModel = (val: unknown): val is ParameterIPAdapterModel =>
   zParameterIPAdapterModel.safeParse(val).success;
 // #endregion
 
 // #region T2I Adapter Model
-export const zParameterT2IAdapterModel = zT2IAdapterModelField.extend({ base: zBaseModel });
+export const zParameterT2IAdapterModel = zModelIdentifierWithBase;
 export type ParameterT2IAdapterModel = z.infer<typeof zParameterT2IAdapterModel>;
 export const isParameterT2IAdapterModel = (val: unknown): val is ParameterT2IAdapterModel =>
   zParameterT2IAdapterModel.safeParse(val).success;
@@ -218,3 +211,9 @@ export type ParameterCanvasCoherenceMode = z.infer<typeof zParameterCanvasCohere
 export const isParameterCanvasCoherenceMode = (val: unknown): val is ParameterCanvasCoherenceMode =>
   zParameterCanvasCoherenceMode.safeParse(val).success;
 // #endregion
+
+// #region LoRA weight
+export const zLoRAWeight = z.number();
+export type ParameterLoRAWeight = z.infer<typeof zLoRAWeight>;
+export const isParameterLoRAWeight = (val: unknown): val is ParameterLoRAWeight => zLoRAWeight.safeParse(val).success;
+// #endregion
diff --git a/invokeai/frontend/web/src/features/parameters/util/modelFetchingHelpers.ts b/invokeai/frontend/web/src/features/parameters/util/modelFetchingHelpers.ts
index c7d25fed8b..bd3e42a314 100644
--- a/invokeai/frontend/web/src/features/parameters/util/modelFetchingHelpers.ts
+++ b/invokeai/frontend/web/src/features/parameters/util/modelFetchingHelpers.ts
@@ -1,7 +1,8 @@
 import { getStore } from 'app/store/nanostores/store';
-import { isModelIdentifier } from 'features/nodes/types/common';
+import type { ModelIdentifierWithBase } from 'features/nodes/types/common';
+import { isModelIdentifier, isModelIdentifierV2 } from 'features/nodes/types/common';
 import { modelsApi } from 'services/api/endpoints/models';
-import type { AnyModelConfig, BaseModelType } from 'services/api/types';
+import type { AnyModelConfig, BaseModelType, ModelType } from 'services/api/types';
 import {
   isControlNetModelConfig,
   isIPAdapterModelConfig,
@@ -41,6 +42,12 @@ export class InvalidModelConfigError extends Error {
   }
 }
 
+/**
+ * Fetches the model config for a given model key.
+ * @param key The model key.
+ * @returns A promise that resolves to the model config.
+ * @throws {ModelConfigNotFoundError} If the model config is unable to be fetched.
+ */
 export const fetchModelConfig = async (key: string): Promise<AnyModelConfig> => {
   const { dispatch } = getStore();
   try {
@@ -52,6 +59,37 @@ export const fetchModelConfig = async (key: string): Promise<AnyModelConfig> =>
   }
 };
 
+/**
+ * Fetches the model config for a given model name, base model, and model type. This provides backwards compatibility
+ * for MM1 model identifiers.
+ * @param name The model name.
+ * @param base The base model.
+ * @param type The model type.
+ * @returns A promise that resolves to the model config.
+ * @throws {ModelConfigNotFoundError} If the model config is unable to be fetched.
+ */
+export const fetchModelConfigByAttrs = async (
+  name: string,
+  base: BaseModelType,
+  type: ModelType
+): Promise<AnyModelConfig> => {
+  const { dispatch } = getStore();
+  try {
+    const req = dispatch(modelsApi.endpoints.getModelConfigByAttrs.initiate({ name, base, type }));
+    req.unsubscribe();
+    return await req.unwrap();
+  } catch {
+    throw new ModelConfigNotFoundError(`Unable to retrieve model config for name/base/type ${name}/${base}/${type}`);
+  }
+};
+
+/**
+ * Fetches the model config for a given model key and type, and ensures that the model config is of a specific type.
+ * @param key The model key.
+ * @param typeGuard A type guard function that checks if the model config is of the expected type.
+ * @returns A promise that resolves to the model config. The model config is guaranteed to be of the expected type.
+ * @throws {InvalidModelConfigError} If the model config is unable to be fetched or is of an unexpected type.
+ */
 export const fetchModelConfigWithTypeGuard = async <T extends AnyModelConfig>(
   key: string,
   typeGuard: (config: AnyModelConfig) => config is T
@@ -63,15 +101,17 @@ export const fetchModelConfigWithTypeGuard = async <T extends AnyModelConfig>(
   return modelConfig;
 };
 
-export const fetchMainModel = async (key: string) => {
+// TODO(psyche): Remove these helpers once `useRecallParameters` is removed
+
+export const fetchMainModelConfig = async (key: string) => {
   return fetchModelConfigWithTypeGuard(key, isNonRefinerMainModelConfig);
 };
 
-export const fetchRefinerModel = async (key: string) => {
+export const fetchRefinerModelConfig = async (key: string) => {
   return fetchModelConfigWithTypeGuard(key, isRefinerMainModelModelConfig);
 };
 
-export const fetchVAEModel = async (key: string) => {
+export const fetchVAEModelConfig = async (key: string) => {
   return fetchModelConfigWithTypeGuard(key, isVAEModelConfig);
 };
 
@@ -95,19 +135,39 @@ export const fetchTextualInversionModel = async (key: string) => {
   return fetchModelConfigWithTypeGuard(key, isTextualInversionModelConfig);
 };
 
-export const isBaseCompatible = (sourceBase: BaseModelType, targetBase: BaseModelType) => {
-  return sourceBase === targetBase;
-};
-
+/**
+ * Raises an error if the source base model is incompatible with the target base model.
+ * @param sourceBase The source base model.
+ * @param targetBase The target base model.
+ * @param message An optional custom message to include in the error.
+ * @throws {InvalidModelConfigError} If the source base model is incompatible with the target base model.
+ */
 export const raiseIfBaseIncompatible = (sourceBase: BaseModelType, targetBase?: BaseModelType, message?: string) => {
-  if (targetBase && !isBaseCompatible(sourceBase, targetBase)) {
+  if (targetBase && sourceBase !== targetBase) {
     throw new InvalidModelConfigError(message || `Incompatible base models: ${sourceBase} and ${targetBase}`);
   }
 };
 
-export const getModelKey = (modelIdentifier: unknown, message?: string): string => {
-  if (!isModelIdentifier(modelIdentifier)) {
-    throw new InvalidModelConfigError(message || `Invalid model identifier: ${modelIdentifier}`);
+/**
+ * Fetches the model key from a model identifier. This includes fetching the key for MM1 format model identifiers.
+ * @param modelIdentifier The model identifier. The MM2 format `{key: string}` simply extracts the key. The MM1 format
+ * `{model_name: string, base_model: BaseModelType}` must do a network request to fetch the key.
+ * @param type The type of model to fetch. This is used to fetch the key for MM1 format model identifiers.
+ * @param message An optional custom message to include in the error if the model identifier is invalid.
+ * @returns A promise that resolves to the model key.
+ * @throws {InvalidModelConfigError} If the model identifier is invalid.
+ */
+export const getModelKey = async (modelIdentifier: unknown, type: ModelType, message?: string): Promise<string> => {
+  if (isModelIdentifier(modelIdentifier)) {
+    return modelIdentifier.key;
   }
-  return modelIdentifier.key;
+  if (isModelIdentifierV2(modelIdentifier)) {
+    return (await fetchModelConfigByAttrs(modelIdentifier.model_name, modelIdentifier.base_model, type)).key;
+  }
+  throw new InvalidModelConfigError(message || `Invalid model identifier: ${modelIdentifier}`);
 };
+
+export const getModelKeyAndBase = (modelConfig: AnyModelConfig): ModelIdentifierWithBase => ({
+  key: modelConfig.key,
+  base: modelConfig.base,
+});
diff --git a/invokeai/frontend/web/src/features/parameters/util/modelMetadataHelpers.ts b/invokeai/frontend/web/src/features/parameters/util/modelMetadataHelpers.ts
deleted file mode 100644
index 722073366f..0000000000
--- a/invokeai/frontend/web/src/features/parameters/util/modelMetadataHelpers.ts
+++ /dev/null
@@ -1,150 +0,0 @@
-import { CONTROLNET_PROCESSORS } from 'features/controlAdapters/store/constants';
-import type { ControlNetConfig, IPAdapterConfig, T2IAdapterConfig } from 'features/controlAdapters/store/types';
-import {
-  initialControlNet,
-  initialIPAdapter,
-  initialT2IAdapter,
-} from 'features/controlAdapters/util/buildControlAdapter';
-import type { LoRA } from 'features/lora/store/loraSlice';
-import type { ModelIdentifierWithBase } from 'features/nodes/types/common';
-import { zModelIdentifierWithBase } from 'features/nodes/types/common';
-import type {
-  ControlNetMetadataItem,
-  IPAdapterMetadataItem,
-  LoRAMetadataItem,
-  T2IAdapterMetadataItem,
-} from 'features/nodes/types/metadata';
-import {
-  fetchControlNetModel,
-  fetchIPAdapterModel,
-  fetchLoRAModel,
-  fetchMainModel,
-  fetchRefinerModel,
-  fetchT2IAdapterModel,
-  fetchVAEModel,
-  getModelKey,
-  raiseIfBaseIncompatible,
-} from 'features/parameters/util/modelFetchingHelpers';
-import type { BaseModelType } from 'services/api/types';
-import { v4 as uuidv4 } from 'uuid';
-
-export const prepareMainModelMetadataItem = async (model: unknown): Promise<ModelIdentifierWithBase> => {
-  const key = getModelKey(model);
-  const mainModel = await fetchMainModel(key);
-  return zModelIdentifierWithBase.parse(mainModel);
-};
-
-export const prepareRefinerMetadataItem = async (model: unknown): Promise<ModelIdentifierWithBase> => {
-  const key = getModelKey(model);
-  const refinerModel = await fetchRefinerModel(key);
-  return zModelIdentifierWithBase.parse(refinerModel);
-};
-
-export const prepareVAEMetadataItem = async (vae: unknown, base?: BaseModelType): Promise<ModelIdentifierWithBase> => {
-  const key = getModelKey(vae);
-  const vaeModel = await fetchVAEModel(key);
-  raiseIfBaseIncompatible(vaeModel.base, base, 'VAE incompatible with currently-selected model');
-  return zModelIdentifierWithBase.parse(vaeModel);
-};
-
-export const prepareLoRAMetadataItem = async (
-  loraMetadataItem: LoRAMetadataItem,
-  base?: BaseModelType
-): Promise<LoRA> => {
-  const key = getModelKey(loraMetadataItem.lora);
-  const loraModel = await fetchLoRAModel(key);
-  raiseIfBaseIncompatible(loraModel.base, base, 'LoRA incompatible with currently-selected model');
-  return { key: loraModel.key, base: loraModel.base, weight: loraMetadataItem.weight, isEnabled: true };
-};
-
-export const prepareControlNetMetadataItem = async (
-  controlnetMetadataItem: ControlNetMetadataItem,
-  base?: BaseModelType
-): Promise<ControlNetConfig> => {
-  const key = getModelKey(controlnetMetadataItem.control_model);
-  const controlNetModel = await fetchControlNetModel(key);
-  raiseIfBaseIncompatible(controlNetModel.base, base, 'ControlNet incompatible with currently-selected model');
-
-  const { image, control_weight, begin_step_percent, end_step_percent, control_mode, resize_mode } =
-    controlnetMetadataItem;
-
-  // We don't save the original image that was processed into a control image, only the processed image
-  const processorType = 'none';
-  const processorNode = CONTROLNET_PROCESSORS.none.default;
-
-  const controlnet: ControlNetConfig = {
-    type: 'controlnet',
-    isEnabled: true,
-    model: zModelIdentifierWithBase.parse(controlNetModel),
-    weight: typeof control_weight === 'number' ? control_weight : initialControlNet.weight,
-    beginStepPct: begin_step_percent || initialControlNet.beginStepPct,
-    endStepPct: end_step_percent || initialControlNet.endStepPct,
-    controlMode: control_mode || initialControlNet.controlMode,
-    resizeMode: resize_mode || initialControlNet.resizeMode,
-    controlImage: image?.image_name || null,
-    processedControlImage: image?.image_name || null,
-    processorType,
-    processorNode,
-    shouldAutoConfig: true,
-    id: uuidv4(),
-  };
-
-  return controlnet;
-};
-
-export const prepareT2IAdapterMetadataItem = async (
-  t2iAdapterMetadataItem: T2IAdapterMetadataItem,
-  base?: BaseModelType
-): Promise<T2IAdapterConfig> => {
-  const key = getModelKey(t2iAdapterMetadataItem.t2i_adapter_model);
-  const t2iAdapterModel = await fetchT2IAdapterModel(key);
-  raiseIfBaseIncompatible(t2iAdapterModel.base, base, 'T2I Adapter incompatible with currently-selected model');
-
-  const { image, weight, begin_step_percent, end_step_percent, resize_mode } = t2iAdapterMetadataItem;
-
-  // We don't save the original image that was processed into a control image, only the processed image
-  const processorType = 'none';
-  const processorNode = CONTROLNET_PROCESSORS.none.default;
-
-  const t2iAdapter: T2IAdapterConfig = {
-    type: 't2i_adapter',
-    isEnabled: true,
-    model: zModelIdentifierWithBase.parse(t2iAdapterModel),
-    weight: typeof weight === 'number' ? weight : initialT2IAdapter.weight,
-    beginStepPct: begin_step_percent || initialT2IAdapter.beginStepPct,
-    endStepPct: end_step_percent || initialT2IAdapter.endStepPct,
-    resizeMode: resize_mode || initialT2IAdapter.resizeMode,
-    controlImage: image?.image_name || null,
-    processedControlImage: image?.image_name || null,
-    processorType,
-    processorNode,
-    shouldAutoConfig: true,
-    id: uuidv4(),
-  };
-
-  return t2iAdapter;
-};
-
-export const prepareIPAdapterMetadataItem = async (
-  ipAdapterMetadataItem: IPAdapterMetadataItem,
-  base?: BaseModelType
-): Promise<IPAdapterConfig> => {
-  const key = getModelKey(ipAdapterMetadataItem?.ip_adapter_model);
-  const ipAdapterModel = await fetchIPAdapterModel(key);
-  raiseIfBaseIncompatible(ipAdapterModel.base, base, 'T2I Adapter incompatible with currently-selected model');
-
-  const { image, weight, begin_step_percent, end_step_percent } = ipAdapterMetadataItem;
-
-  const ipAdapter: IPAdapterConfig = {
-    id: uuidv4(),
-    type: 'ip_adapter',
-    isEnabled: true,
-    controlImage: image?.image_name ?? null,
-    model: zModelIdentifierWithBase.parse(ipAdapterModel),
-    weight: weight ?? initialIPAdapter.weight,
-    beginStepPct: begin_step_percent ?? initialIPAdapter.beginStepPct,
-    endStepPct: end_step_percent ?? initialIPAdapter.endStepPct,
-  };
-
-  return ipAdapter;
-};
diff --git a/invokeai/frontend/web/src/features/settingsAccordions/components/AdvancedSettingsAccordion/AdvancedSettingsAccordion.tsx b/invokeai/frontend/web/src/features/settingsAccordions/components/AdvancedSettingsAccordion/AdvancedSettingsAccordion.tsx
index 8b10d9bddd..05ca73927c 100644
--- a/invokeai/frontend/web/src/features/settingsAccordions/components/AdvancedSettingsAccordion/AdvancedSettingsAccordion.tsx
+++ b/invokeai/frontend/web/src/features/settingsAccordions/components/AdvancedSettingsAccordion/AdvancedSettingsAccordion.tsx
@@ -25,7 +25,7 @@ const formLabelProps2: FormLabelProps = {
 
 export const AdvancedSettingsAccordion = memo(() => {
   const vaeKey = useAppSelector((state) => state.generation.vae?.key);
-  const { data: vaeConfig } = useGetModelConfigQuery(vaeKey ?? skipToken);
+  const { currentData: vaeConfig } = useGetModelConfigQuery(vaeKey ?? skipToken);
   const selectBadges = useMemo(
     () =>
       createMemoizedSelector(selectGenerationSlice, (generation) => {
diff --git a/invokeai/frontend/web/src/services/api/endpoints/images.ts b/invokeai/frontend/web/src/services/api/endpoints/images.ts
index 49eb28390f..1849e2fde4 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/images.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/images.ts
@@ -1,10 +1,8 @@
 import type { EntityState, Update } from '@reduxjs/toolkit';
 import type { PatchCollection } from '@reduxjs/toolkit/dist/query/core/buildThunks';
-import { logger } from 'app/logging/logger';
+import type { JSONObject } from 'common/types';
 import type { BoardId } from 'features/gallery/store/types';
 import { ASSETS_CATEGORIES, IMAGE_CATEGORIES, IMAGE_LIMIT } from 'features/gallery/store/types';
-import type { CoreMetadata } from 'features/nodes/types/metadata';
-import { zCoreMetadata } from 'features/nodes/types/metadata';
 import { addToast } from 'features/system/store/systemSlice';
 import { t } from 'i18next';
 import { keyBy } from 'lodash-es';
@@ -118,22 +116,9 @@ export const imagesApi = api.injectEndpoints({
       providesTags: (result, error, image_name) => [{ type: 'Image', id: image_name }],
       keepUnusedDataFor: 86400, // 24 hours
     }),
-    getImageMetadata: build.query<CoreMetadata | undefined, string>({
+    getImageMetadata: build.query<JSONObject | undefined, string>({
       query: (image_name) => ({ url: buildImagesUrl(`i/${image_name}/metadata`) }),
       providesTags: (result, error, image_name) => [{ type: 'ImageMetadata', id: image_name }],
-      transformResponse: (
-        response: paths['/api/v1/images/i/{image_name}/metadata']['get']['responses']['200']['content']['application/json']
-      ) => {
-        if (response) {
-          const result = zCoreMetadata.safeParse(response);
-          if (result.success) {
-            return result.data;
-          } else {
-            logger('images').warn('Problem parsing metadata');
-          }
-        }
-        return;
-      },
       keepUnusedDataFor: 86400, // 24 hours
     }),
     getImageWorkflow: build.query<
diff --git a/invokeai/frontend/web/src/services/api/endpoints/models.ts b/invokeai/frontend/web/src/services/api/endpoints/models.ts
index 6618fda58e..3ccccf62e1 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/models.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/models.ts
@@ -70,6 +70,8 @@ export type ScanFolderResponse =
   paths['/api/v2/models/scan_folder']['get']['responses']['200']['content']['application/json'];
 type ScanFolderArg = operations['scan_for_models']['parameters']['query'];
 
+export type GetByAttrsArg = operations['get_model_records_by_attrs']['parameters']['query'];
+
 export const mainModelsAdapter = createEntityAdapter<MainModelConfig, string>({
   selectId: (entity) => entity.key,
   sortComparer: (a, b) => a.name.localeCompare(b.name),
@@ -223,6 +225,18 @@ export const modelsApi = api.injectEndpoints({
         return tags;
       },
     }),
+    getModelConfigByAttrs: build.query<AnyModelConfig, GetByAttrsArg>({
+      query: (arg) => buildModelsUrl(`get_by_attrs?${queryString.stringify(arg)}`),
+      providesTags: (result) => {
+        const tags: ApiTagDescription[] = ['Model'];
+
+        if (result) {
+          tags.push({ type: 'ModelConfig', id: result.key });
+        }
+
+        return tags;
+      },
+    }),
     syncModels: build.mutation<void, void>({
       query: () => {
         return {
@@ -300,6 +314,7 @@ export const modelsApi = api.injectEndpoints({
 });
 
 export const {
+  useGetModelConfigByAttrsQuery,
   useGetModelConfigQuery,
   useGetMainModelsQuery,
   useGetControlNetModelsQuery,

From ce3f9037cd43571dc96bba983f5800a9a8efc6f9 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 26 Feb 2024 10:23:37 +1100
Subject: [PATCH 316/411] feat(ui): no JSX in metadata handlers

---
 .../metadata/components/MetadataControlNets.tsx        |  3 ++-
 .../metadata/components/MetadataIPAdapters.tsx         |  3 ++-
 .../metadata/components/MetadataT2IAdapters.tsx        |  3 ++-
 .../metadata/util/{handlers.tsx => handlers.ts}        | 10 ++++------
 4 files changed, 10 insertions(+), 9 deletions(-)
 rename invokeai/frontend/web/src/features/metadata/util/{handlers.tsx => handlers.ts} (96%)

diff --git a/invokeai/frontend/web/src/features/metadata/components/MetadataControlNets.tsx b/invokeai/frontend/web/src/features/metadata/components/MetadataControlNets.tsx
index 2e8e3b6f9a..2dd57c04b7 100644
--- a/invokeai/frontend/web/src/features/metadata/components/MetadataControlNets.tsx
+++ b/invokeai/frontend/web/src/features/metadata/components/MetadataControlNets.tsx
@@ -1,3 +1,4 @@
+import { Text } from '@invoke-ai/ui-library';
 import type { ControlNetConfig } from 'features/controlAdapters/store/types';
 import { MetadataItemView } from 'features/metadata/components/MetadataItemView';
 import type { MetadataHandlers } from 'features/metadata/types';
@@ -59,7 +60,7 @@ const MetadataViewControlNet = ({
     if (!handlers.renderItemValue) {
       return null;
     }
-    return handlers.renderItemValue(controlNet);
+    return <Text>{handlers.renderItemValue(controlNet)}</Text>;
   }, [handlers, controlNet]);
 
   return <MetadataItemView label={label} isDisabled={false} onRecall={onRecall} renderedValue={renderedValue} />;
diff --git a/invokeai/frontend/web/src/features/metadata/components/MetadataIPAdapters.tsx b/invokeai/frontend/web/src/features/metadata/components/MetadataIPAdapters.tsx
index fef281cd09..6a40d24837 100644
--- a/invokeai/frontend/web/src/features/metadata/components/MetadataIPAdapters.tsx
+++ b/invokeai/frontend/web/src/features/metadata/components/MetadataIPAdapters.tsx
@@ -1,3 +1,4 @@
+import { Text } from '@invoke-ai/ui-library';
 import type { IPAdapterConfig } from 'features/controlAdapters/store/types';
 import { MetadataItemView } from 'features/metadata/components/MetadataItemView';
 import type { MetadataHandlers } from 'features/metadata/types';
@@ -59,7 +60,7 @@ const MetadataViewIPAdapter = ({
     if (!handlers.renderItemValue) {
       return null;
     }
-    return handlers.renderItemValue(ipAdapter);
+    return <Text>{handlers.renderItemValue(ipAdapter)}</Text>;
   }, [handlers, ipAdapter]);
 
   return <MetadataItemView label={label} isDisabled={false} onRecall={onRecall} renderedValue={renderedValue} />;
diff --git a/invokeai/frontend/web/src/features/metadata/components/MetadataT2IAdapters.tsx b/invokeai/frontend/web/src/features/metadata/components/MetadataT2IAdapters.tsx
index 4a73fb3ccb..a6b741a917 100644
--- a/invokeai/frontend/web/src/features/metadata/components/MetadataT2IAdapters.tsx
+++ b/invokeai/frontend/web/src/features/metadata/components/MetadataT2IAdapters.tsx
@@ -1,3 +1,4 @@
+import { Text } from '@invoke-ai/ui-library';
 import type { T2IAdapterConfig } from 'features/controlAdapters/store/types';
 import { MetadataItemView } from 'features/metadata/components/MetadataItemView';
 import type { MetadataHandlers } from 'features/metadata/types';
@@ -59,7 +60,7 @@ const MetadataViewT2IAdapter = ({
     if (!handlers.renderItemValue) {
       return null;
     }
-    return handlers.renderItemValue(t2iAdapter);
+    return <Text>{handlers.renderItemValue(t2iAdapter)}</Text>;
   }, [handlers, t2iAdapter]);
 
   return <MetadataItemView label={label} isDisabled={false} onRecall={onRecall} renderedValue={renderedValue} />;
diff --git a/invokeai/frontend/web/src/features/metadata/util/handlers.tsx b/invokeai/frontend/web/src/features/metadata/util/handlers.ts
similarity index 96%
rename from invokeai/frontend/web/src/features/metadata/util/handlers.tsx
rename to invokeai/frontend/web/src/features/metadata/util/handlers.ts
index 1f86257d42..2c6e9d7c63 100644
--- a/invokeai/frontend/web/src/features/metadata/util/handlers.tsx
+++ b/invokeai/frontend/web/src/features/metadata/util/handlers.ts
@@ -1,6 +1,5 @@
-import { Text } from '@invoke-ai/ui-library';
 import { toast } from 'common/util/toast';
-import type { ControlNetConfig, IPAdapterConfig, T2IAdapterConfig } from 'features/controlAdapters/store/types';
+import type { ControlAdapterConfig } from 'features/controlAdapters/store/types';
 import type { LoRA } from 'features/lora/store/loraSlice';
 import type {
   BuildMetadataHandlers,
@@ -20,10 +19,9 @@ import { recallers } from './recallers';
 
 const renderModelConfigValue: MetadataRenderValueFunc<AnyModelConfig> = (value) =>
   `${value.name} (${value.base.toUpperCase()}, ${value.key})`;
-const renderLoRAValue: MetadataRenderValueFunc<LoRA> = (value) => <Text>{`${value.model.key} (${value.weight})`}</Text>;
-const renderControlAdapterValue: MetadataRenderValueFunc<ControlNetConfig | T2IAdapterConfig | IPAdapterConfig> = (
-  value
-) => <Text>{`${value.model?.key} (${value.weight})`}</Text>;
+const renderLoRAValue: MetadataRenderValueFunc<LoRA> = (value) => `${value.model.key} (${value.weight})`;
+const renderControlAdapterValue: MetadataRenderValueFunc<ControlAdapterConfig> = (value) =>
+  `${value.model?.key} (${value.weight})`;
 
 const parameterSetToast = (parameter: string, description?: string) => {
   toast({

From ff00ed8e803d8c9c6e9f29bd7db8db7c0f76c697 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 26 Feb 2024 10:26:42 +1100
Subject: [PATCH 317/411] fix(ui): use id for component key in control adapter
 components

---
 .../features/metadata/components/MetadataControlNets.tsx   | 2 +-
 .../features/metadata/components/MetadataIPAdapters.tsx    | 7 +------
 .../features/metadata/components/MetadataT2IAdapters.tsx   | 2 +-
 3 files changed, 3 insertions(+), 8 deletions(-)

diff --git a/invokeai/frontend/web/src/features/metadata/components/MetadataControlNets.tsx b/invokeai/frontend/web/src/features/metadata/components/MetadataControlNets.tsx
index 2dd57c04b7..1255e8e7cb 100644
--- a/invokeai/frontend/web/src/features/metadata/components/MetadataControlNets.tsx
+++ b/invokeai/frontend/web/src/features/metadata/components/MetadataControlNets.tsx
@@ -30,7 +30,7 @@ export const MetadataControlNets = ({ metadata }: Props) => {
     <>
       {controlNets.map((controlNet) => (
         <MetadataViewControlNet
-          key={controlNet.model.key}
+          key={controlNet.id}
           label={label}
           controlNet={controlNet}
           handlers={handlers.controlNets}
diff --git a/invokeai/frontend/web/src/features/metadata/components/MetadataIPAdapters.tsx b/invokeai/frontend/web/src/features/metadata/components/MetadataIPAdapters.tsx
index 6a40d24837..69f9ec986d 100644
--- a/invokeai/frontend/web/src/features/metadata/components/MetadataIPAdapters.tsx
+++ b/invokeai/frontend/web/src/features/metadata/components/MetadataIPAdapters.tsx
@@ -29,12 +29,7 @@ export const MetadataIPAdapters = ({ metadata }: Props) => {
   return (
     <>
       {ipAdapters.map((ipAdapter) => (
-        <MetadataViewIPAdapter
-          key={ipAdapter.model.key}
-          label={label}
-          ipAdapter={ipAdapter}
-          handlers={handlers.ipAdapters}
-        />
+        <MetadataViewIPAdapter key={ipAdapter.id} label={label} ipAdapter={ipAdapter} handlers={handlers.ipAdapters} />
       ))}
     </>
   );
diff --git a/invokeai/frontend/web/src/features/metadata/components/MetadataT2IAdapters.tsx b/invokeai/frontend/web/src/features/metadata/components/MetadataT2IAdapters.tsx
index a6b741a917..209ab4f2ed 100644
--- a/invokeai/frontend/web/src/features/metadata/components/MetadataT2IAdapters.tsx
+++ b/invokeai/frontend/web/src/features/metadata/components/MetadataT2IAdapters.tsx
@@ -30,7 +30,7 @@ export const MetadataT2IAdapters = ({ metadata }: Props) => {
     <>
       {t2iAdapters.map((t2iAdapter) => (
         <MetadataViewT2IAdapter
-          key={t2iAdapter.model.key}
+          key={t2iAdapter.id}
           label={label}
           t2iAdapter={t2iAdapter}
           handlers={handlers.t2iAdapters}

From 71ceab9094b0b6425cd74119004777c44fdfd253 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 26 Feb 2024 11:49:53 +1100
Subject: [PATCH 318/411] feat(ui): migrate all metadata recall logic to new
 system

---
 .../web/src/common/util/objectKeys.ts         |   6 +
 .../CurrentImage/CurrentImageButtons.tsx      |  80 +-
 .../SingleSelectionMenuItems.tsx              |  61 +-
 .../ImageMetadataViewer/ImageMetadataItem.tsx | 109 ---
 .../features/gallery/hooks/useImageActions.ts |  62 ++
 .../src/features/metadata/util/handlers.ts    |  73 ++
 .../src/features/metadata/util/recallers.ts   |  56 --
 .../ImageToImage/InitialImageDisplay.tsx      |   7 +-
 .../parameters/hooks/usePreselectedImage.ts   |   7 +-
 .../parameters/hooks/useRecallParameters.ts   | 858 ------------------
 10 files changed, 177 insertions(+), 1142 deletions(-)
 create mode 100644 invokeai/frontend/web/src/common/util/objectKeys.ts
 delete mode 100644 invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataItem.tsx
 create mode 100644 invokeai/frontend/web/src/features/gallery/hooks/useImageActions.ts
 delete mode 100644 invokeai/frontend/web/src/features/parameters/hooks/useRecallParameters.ts

diff --git a/invokeai/frontend/web/src/common/util/objectKeys.ts b/invokeai/frontend/web/src/common/util/objectKeys.ts
new file mode 100644
index 0000000000..bea0905c7f
--- /dev/null
+++ b/invokeai/frontend/web/src/common/util/objectKeys.ts
@@ -0,0 +1,6 @@
+/**
+ * Get the keys of an object. This is a wrapper around `Object.keys` that types the result as an array of the keys of the object.
+ * @param obj The object to get the keys of.
+ * @returns The keys of the object.
+ */
+export const objectKeys = <T extends Record<string, unknown>>(obj: T) => Object.keys(obj) as Array<keyof T>;
diff --git a/invokeai/frontend/web/src/features/gallery/components/CurrentImage/CurrentImageButtons.tsx b/invokeai/frontend/web/src/features/gallery/components/CurrentImage/CurrentImageButtons.tsx
index e25324b9ea..896b6efef7 100644
--- a/invokeai/frontend/web/src/features/gallery/components/CurrentImage/CurrentImageButtons.tsx
+++ b/invokeai/frontend/web/src/features/gallery/components/CurrentImage/CurrentImageButtons.tsx
@@ -7,11 +7,12 @@ import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { DeleteImageButton } from 'features/deleteImageModal/components/DeleteImageButton';
 import { imagesToDeleteSelected } from 'features/deleteImageModal/store/slice';
 import SingleSelectionMenuItems from 'features/gallery/components/ImageContextMenu/SingleSelectionMenuItems';
+import { useImageActions } from 'features/gallery/hooks/useImageActions';
 import { sentImageToImg2Img } from 'features/gallery/store/actions';
 import { selectLastSelectedImage } from 'features/gallery/store/gallerySelectors';
 import { selectGallerySlice } from 'features/gallery/store/gallerySlice';
+import { parseAndRecallImageDimensions } from 'features/metadata/util/handlers';
 import ParamUpscalePopover from 'features/parameters/components/Upscale/ParamUpscaleSettings';
-import { useRecallParameters } from 'features/parameters/hooks/useRecallParameters';
 import { initialImageSelected } from 'features/parameters/store/actions';
 import { useIsQueueMutationInProgress } from 'features/queue/hooks/useIsQueueMutationInProgress';
 import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';
@@ -33,7 +34,6 @@ import {
   PiRulerBold,
 } from 'react-icons/pi';
 import { useGetImageDTOQuery } from 'services/api/endpoints/images';
-import { useDebouncedMetadata } from 'services/api/hooks/useDebouncedMetadata';
 
 const selectShouldDisableToolbarButtons = createSelector(
   selectSystemSlice,
@@ -58,11 +58,10 @@ const CurrentImageButtons = () => {
   const toaster = useAppToaster();
   const { t } = useTranslation();
 
-  const { recallBothPrompts, recallSeed, recallWidthAndHeight, recallAllParameters } = useRecallParameters();
-
   const { currentData: imageDTO } = useGetImageDTOQuery(lastSelectedImage?.image_name ?? skipToken);
 
-  const { metadata, isLoading: isLoadingMetadata } = useDebouncedMetadata(lastSelectedImage?.image_name);
+  const { recallAll, remix, recallSeed, recallPrompts, hasMetadata, hasSeed, hasPrompts, isLoadingMetadata } =
+    useImageActions(lastSelectedImage?.image_name);
 
   const { getAndLoadEmbeddedWorkflow, getAndLoadEmbeddedWorkflowResult } = useGetAndLoadEmbeddedWorkflow({});
 
@@ -74,51 +73,16 @@ const CurrentImageButtons = () => {
   }, [getAndLoadEmbeddedWorkflow, lastSelectedImage]);
 
   useHotkeys('w', handleLoadWorkflow, [lastSelectedImage]);
-
-  const handleClickUseAllParameters = useCallback(() => {
-    recallAllParameters(metadata);
-  }, [metadata, recallAllParameters]);
-
-  useHotkeys('a', handleClickUseAllParameters, [metadata]);
-
-  const handleUseSeed = useCallback(() => {
-    recallSeed(metadata?.seed);
-  }, [metadata?.seed, recallSeed]);
-
-  useHotkeys('s', handleUseSeed, [metadata]);
-
-  const handleUsePrompt = useCallback(() => {
-    recallBothPrompts(
-      metadata?.positive_prompt,
-      metadata?.negative_prompt,
-      metadata?.positive_style_prompt,
-      metadata?.negative_style_prompt
-    );
-  }, [
-    metadata?.negative_prompt,
-    metadata?.positive_prompt,
-    metadata?.positive_style_prompt,
-    metadata?.negative_style_prompt,
-    recallBothPrompts,
-  ]);
-
-  useHotkeys('p', handleUsePrompt, [metadata]);
-
-  const handleRemixImage = useCallback(() => {
-    // Recalls all metadata parameters except seed
-    recallAllParameters({
-      ...metadata,
-      seed: undefined,
-    });
-  }, [metadata, recallAllParameters]);
-
-  useHotkeys('r', handleRemixImage, [metadata]);
+  useHotkeys('a', recallAll, [recallAll]);
+  useHotkeys('s', recallSeed, [recallSeed]);
+  useHotkeys('p', recallPrompts, [recallPrompts]);
+  useHotkeys('r', remix, [remix]);
 
   const handleUseSize = useCallback(() => {
-    recallWidthAndHeight(metadata?.width, metadata?.height);
-  }, [metadata?.width, metadata?.height, recallWidthAndHeight]);
+    parseAndRecallImageDimensions(lastSelectedImage);
+  }, [lastSelectedImage]);
 
-  useHotkeys('d', handleUseSize, [metadata]);
+  useHotkeys('d', handleUseSize, [handleUseSize]);
 
   const handleSendToImageToImage = useCallback(() => {
     dispatch(sentImageToImg2Img());
@@ -216,36 +180,30 @@ const CurrentImageButtons = () => {
             icon={<PiArrowsCounterClockwiseBold />}
             tooltip={`${t('parameters.remixImage')} (R)`}
             aria-label={`${t('parameters.remixImage')} (R)`}
-            isDisabled={!metadata?.positive_prompt}
-            onClick={handleRemixImage}
+            isDisabled={!hasMetadata}
+            onClick={remix}
           />
           <IconButton
             isLoading={isLoadingMetadata}
             icon={<PiQuotesBold />}
             tooltip={`${t('parameters.usePrompt')} (P)`}
             aria-label={`${t('parameters.usePrompt')} (P)`}
-            isDisabled={!metadata?.positive_prompt}
-            onClick={handleUsePrompt}
+            isDisabled={!hasPrompts}
+            onClick={recallPrompts}
           />
           <IconButton
             isLoading={isLoadingMetadata}
             icon={<PiPlantBold />}
             tooltip={`${t('parameters.useSeed')} (S)`}
             aria-label={`${t('parameters.useSeed')} (S)`}
-            isDisabled={metadata?.seed === null || metadata?.seed === undefined}
-            onClick={handleUseSeed}
+            isDisabled={!hasSeed}
+            onClick={recallSeed}
           />
           <IconButton
             isLoading={isLoadingMetadata}
             icon={<PiRulerBold />}
             tooltip={`${t('parameters.useSize')} (D)`}
             aria-label={`${t('parameters.useSize')} (D)`}
-            isDisabled={
-              metadata?.height === null ||
-              metadata?.height === undefined ||
-              metadata?.width === null ||
-              metadata?.width === undefined
-            }
             onClick={handleUseSize}
           />
           <IconButton
@@ -253,8 +211,8 @@ const CurrentImageButtons = () => {
             icon={<PiAsteriskBold />}
             tooltip={`${t('parameters.useAll')} (A)`}
             aria-label={`${t('parameters.useAll')} (A)`}
-            isDisabled={!metadata}
-            onClick={handleClickUseAllParameters}
+            isDisabled={!hasMetadata}
+            onClick={recallAll}
           />
         </ButtonGroup>
 
diff --git a/invokeai/frontend/web/src/features/gallery/components/ImageContextMenu/SingleSelectionMenuItems.tsx b/invokeai/frontend/web/src/features/gallery/components/ImageContextMenu/SingleSelectionMenuItems.tsx
index f4d9c7a840..6f49f4afcc 100644
--- a/invokeai/frontend/web/src/features/gallery/components/ImageContextMenu/SingleSelectionMenuItems.tsx
+++ b/invokeai/frontend/web/src/features/gallery/components/ImageContextMenu/SingleSelectionMenuItems.tsx
@@ -8,8 +8,8 @@ import { useDownloadImage } from 'common/hooks/useDownloadImage';
 import { setInitialCanvasImage } from 'features/canvas/store/canvasSlice';
 import { imagesToChangeSelected, isModalOpenChanged } from 'features/changeBoardModal/store/slice';
 import { imagesToDeleteSelected } from 'features/deleteImageModal/store/slice';
+import { useImageActions } from 'features/gallery/hooks/useImageActions';
 import { sentImageToCanvas, sentImageToImg2Img } from 'features/gallery/store/actions';
-import { useRecallParameters } from 'features/parameters/hooks/useRecallParameters';
 import { initialImageSelected } from 'features/parameters/store/actions';
 import { selectOptimalDimension } from 'features/parameters/store/generationSlice';
 import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';
@@ -33,7 +33,6 @@ import {
   PiTrashSimpleBold,
 } from 'react-icons/pi';
 import { useStarImagesMutation, useUnstarImagesMutation } from 'services/api/endpoints/images';
-import { useDebouncedMetadata } from 'services/api/hooks/useDebouncedMetadata';
 import type { ImageDTO } from 'services/api/types';
 
 type SingleSelectionMenuItemsProps = {
@@ -49,7 +48,9 @@ const SingleSelectionMenuItems = (props: SingleSelectionMenuItemsProps) => {
   const isCanvasEnabled = useFeatureStatus('unifiedCanvas').isFeatureEnabled;
   const customStarUi = useStore($customStarUI);
   const { downloadImage } = useDownloadImage();
-  const { metadata, isLoading: isLoadingMetadata } = useDebouncedMetadata(imageDTO?.image_name);
+
+  const { recallAll, remix, recallSeed, recallPrompts, hasMetadata, hasSeed, hasPrompts, isLoadingMetadata } =
+    useImageActions(imageDTO?.image_name);
 
   const { getAndLoadEmbeddedWorkflow, getAndLoadEmbeddedWorkflowResult } = useGetAndLoadEmbeddedWorkflow({});
 
@@ -69,28 +70,6 @@ const SingleSelectionMenuItems = (props: SingleSelectionMenuItemsProps) => {
     dispatch(imagesToDeleteSelected([imageDTO]));
   }, [dispatch, imageDTO]);
 
-  const { recallBothPrompts, recallSeed, recallAllParameters } = useRecallParameters();
-
-  // Recall parameters handlers
-  const handleRecallPrompt = useCallback(() => {
-    recallBothPrompts(
-      metadata?.positive_prompt,
-      metadata?.negative_prompt,
-      metadata?.positive_style_prompt,
-      metadata?.negative_style_prompt
-    );
-  }, [
-    metadata?.negative_prompt,
-    metadata?.positive_prompt,
-    metadata?.positive_style_prompt,
-    metadata?.negative_style_prompt,
-    recallBothPrompts,
-  ]);
-
-  const handleRecallSeed = useCallback(() => {
-    recallSeed(metadata?.seed);
-  }, [metadata?.seed, recallSeed]);
-
   const handleSendToImageToImage = useCallback(() => {
     dispatch(sentImageToImg2Img());
     dispatch(initialImageSelected(imageDTO));
@@ -111,18 +90,6 @@ const SingleSelectionMenuItems = (props: SingleSelectionMenuItemsProps) => {
     });
   }, [dispatch, imageDTO, t, toaster, optimalDimension]);
 
-  const handleUseAllParameters = useCallback(() => {
-    recallAllParameters(metadata);
-  }, [metadata, recallAllParameters]);
-
-  const handleRemixImage = useCallback(() => {
-    // Recalls all metadata parameters except seed
-    recallAllParameters({
-      ...metadata,
-      seed: undefined,
-    });
-  }, [metadata, recallAllParameters]);
-
   const handleChangeBoard = useCallback(() => {
     dispatch(imagesToChangeSelected([imageDTO]));
     dispatch(isModalOpenChanged(true));
@@ -171,33 +138,29 @@ const SingleSelectionMenuItems = (props: SingleSelectionMenuItemsProps) => {
       </MenuItem>
       <MenuItem
         icon={isLoadingMetadata ? <SpinnerIcon /> : <PiArrowsCounterClockwiseBold />}
-        onClickCapture={handleRemixImage}
-        isDisabled={
-          isLoadingMetadata || (metadata?.positive_prompt === undefined && metadata?.negative_prompt === undefined)
-        }
+        onClickCapture={remix}
+        isDisabled={isLoadingMetadata || !hasMetadata}
       >
         {t('parameters.remixImage')}
       </MenuItem>
       <MenuItem
         icon={isLoadingMetadata ? <SpinnerIcon /> : <PiQuotesBold />}
-        onClickCapture={handleRecallPrompt}
-        isDisabled={
-          isLoadingMetadata || (metadata?.positive_prompt === undefined && metadata?.negative_prompt === undefined)
-        }
+        onClickCapture={recallPrompts}
+        isDisabled={isLoadingMetadata || !hasPrompts}
       >
         {t('parameters.usePrompt')}
       </MenuItem>
       <MenuItem
         icon={isLoadingMetadata ? <SpinnerIcon /> : <PiPlantBold />}
-        onClickCapture={handleRecallSeed}
-        isDisabled={isLoadingMetadata || metadata?.seed === undefined}
+        onClickCapture={recallSeed}
+        isDisabled={isLoadingMetadata || !hasSeed}
       >
         {t('parameters.useSeed')}
       </MenuItem>
       <MenuItem
         icon={isLoadingMetadata ? <SpinnerIcon /> : <PiAsteriskBold />}
-        onClickCapture={handleUseAllParameters}
-        isDisabled={isLoadingMetadata || !metadata}
+        onClickCapture={recallAll}
+        isDisabled={isLoadingMetadata || !hasMetadata}
       >
         {t('parameters.useAll')}
       </MenuItem>
diff --git a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataItem.tsx b/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataItem.tsx
deleted file mode 100644
index 146c1437d1..0000000000
--- a/invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataItem.tsx
+++ /dev/null
@@ -1,109 +0,0 @@
-import { ExternalLink, Flex, IconButton, Text, Tooltip } from '@invoke-ai/ui-library';
-import { skipToken } from '@reduxjs/toolkit/query';
-import { get } from 'lodash-es';
-import { memo, useCallback, useMemo } from 'react';
-import { useTranslation } from 'react-i18next';
-import { PiArrowBendUpLeftBold } from 'react-icons/pi';
-import { useGetModelConfigQuery } from 'services/api/endpoints/models';
-
-type MetadataItemProps = {
-  isLink?: boolean;
-  label: string;
-  metadata: unknown;
-  propertyName: string;
-  onRecall?: (value: unknown) => void;
-  labelPosition?: string;
-};
-
-/**
- * Component to display an individual metadata item or parameter.
- */
-const ImageMetadataItem = ({
-  label,
-  metadata,
-  propertyName,
-  onRecall: _onRecall,
-  isLink,
-  labelPosition,
-}: MetadataItemProps) => {
-  const { t } = useTranslation();
-  const value = useMemo(() => get(metadata, propertyName), [metadata, propertyName]);
-  const onRecall = useCallback(() => {
-    if (!_onRecall) {
-      return;
-    }
-    _onRecall(value);
-  }, [_onRecall, value]);
-
-  if (!value) {
-    return null;
-  }
-
-  return (
-    <Flex gap={2}>
-      {_onRecall && (
-        <Tooltip label={t('metadata.recallParameter', { parameter: label })}>
-          <IconButton
-            aria-label={t('metadata.recallParameter', { parameter: label })}
-            icon={<PiArrowBendUpLeftBold />}
-            size="xs"
-            variant="ghost"
-            fontSize={20}
-            onClick={onRecall}
-          />
-        </Tooltip>
-      )}
-      <Flex direction={labelPosition ? 'column' : 'row'}>
-        <Text fontWeight="semibold" whiteSpace="pre-wrap" pr={2}>
-          {label}:
-        </Text>
-        {isLink ? (
-          <ExternalLink href={value.toString()} label={value.toString()} />
-        ) : (
-          <Text overflowY="scroll" wordBreak="break-all">
-            {value.toString()}
-          </Text>
-        )}
-      </Flex>
-    </Flex>
-  );
-};
-
-export default memo(ImageMetadataItem);
-
-type VAEMetadataItemProps = {
-  label: string;
-  modelKey?: string;
-  onClick: () => void;
-};
-
-export const VAEMetadataItem = memo(({ label, modelKey, onClick }: VAEMetadataItemProps) => {
-  const { data: modelConfig } = useGetModelConfigQuery(modelKey ?? skipToken);
-
-  return (
-    <ImageMetadataItem label={label} value={modelKey ? modelConfig?.name ?? modelKey : 'Default'} onClick={onClick} />
-  );
-});
-
-VAEMetadataItem.displayName = 'VAEMetadataItem';
-
-type ModelMetadataItemProps = {
-  label: string;
-  modelKey?: string;
-
-  extra?: string;
-  onClick: () => void;
-};
-
-export const ModelMetadataItem = memo(({ label, modelKey, extra, onClick }: ModelMetadataItemProps) => {
-  const { data: modelConfig } = useGetModelConfigQuery(modelKey ?? skipToken);
-  const value = useMemo(() => {
-    if (modelConfig) {
-      return `${modelConfig.name}${extra ?? ''}`;
-    }
-    return `${modelKey}${extra ?? ''}`;
-  }, [extra, modelConfig, modelKey]);
-  return <ImageMetadataItem label={label} value={value} onClick={onClick} />;
-});
-
-ModelMetadataItem.displayName = 'ModelMetadataItem';
diff --git a/invokeai/frontend/web/src/features/gallery/hooks/useImageActions.ts b/invokeai/frontend/web/src/features/gallery/hooks/useImageActions.ts
new file mode 100644
index 0000000000..a61b2096da
--- /dev/null
+++ b/invokeai/frontend/web/src/features/gallery/hooks/useImageActions.ts
@@ -0,0 +1,62 @@
+import { handlers, parseAndRecallAllMetadata, parseAndRecallPrompts } from 'features/metadata/util/handlers';
+import { useCallback, useEffect, useState } from 'react';
+import { useDebouncedMetadata } from 'services/api/hooks/useDebouncedMetadata';
+
+export const useImageActions = (image_name?: string) => {
+  const { metadata, isLoading: isLoadingMetadata } = useDebouncedMetadata(image_name);
+  const [hasMetadata, setHasMetadata] = useState(false);
+  const [hasSeed, setHasSeed] = useState(false);
+  const [hasPrompts, setHasPrompts] = useState(false);
+
+  useEffect(() => {
+    const parseMetadata = async () => {
+      if (metadata) {
+        setHasMetadata(true);
+        try {
+          await handlers.seed.parse(metadata);
+          setHasSeed(true);
+        } catch {
+          setHasSeed(false);
+        }
+
+        const promptParseResults = await Promise.allSettled([
+          handlers.positivePrompt.parse(metadata),
+          handlers.negativePrompt.parse(metadata),
+          handlers.sdxlPositiveStylePrompt.parse(metadata),
+          handlers.sdxlNegativeStylePrompt.parse(metadata),
+        ]);
+        if (promptParseResults.some((result) => result.status === 'fulfilled')) {
+          setHasPrompts(true);
+        } else {
+          setHasPrompts(false);
+        }
+      } else {
+        setHasMetadata(false);
+        setHasSeed(false);
+        setHasPrompts(false);
+      }
+    };
+    parseMetadata();
+  }, [metadata]);
+
+  const recallAll = useCallback(() => {
+    parseAndRecallAllMetadata(metadata);
+  }, [metadata]);
+
+  const remix = useCallback(() => {
+    // Recalls all metadata parameters except seed
+    parseAndRecallAllMetadata(metadata, ['seed']);
+  }, [metadata]);
+
+  const recallSeed = useCallback(() => {
+    handlers.seed.parse(metadata).then((seed) => {
+      handlers.seed.recall && handlers.seed.recall(seed);
+    });
+  }, [metadata]);
+
+  const recallPrompts = useCallback(() => {
+    parseAndRecallPrompts(metadata);
+  }, [metadata]);
+
+  return { recallAll, remix, recallSeed, recallPrompts , hasMetadata, hasSeed,  hasPrompts, isLoadingMetadata };
+};
diff --git a/invokeai/frontend/web/src/features/metadata/util/handlers.ts b/invokeai/frontend/web/src/features/metadata/util/handlers.ts
index 2c6e9d7c63..49d85f4eb3 100644
--- a/invokeai/frontend/web/src/features/metadata/util/handlers.ts
+++ b/invokeai/frontend/web/src/features/metadata/util/handlers.ts
@@ -1,3 +1,4 @@
+import { objectKeys } from 'common/util/objectKeys';
 import { toast } from 'common/util/toast';
 import type { ControlAdapterConfig } from 'features/controlAdapters/store/types';
 import type { LoRA } from 'features/lora/store/loraSlice';
@@ -312,3 +313,75 @@ export const handlers = {
     renderItemValue: renderControlAdapterValue,
   }),
 } as const;
+
+export const parseAndRecallPrompts = async (metadata: unknown) => {
+  const results = await Promise.allSettled([
+    handlers.positivePrompt.parse(metadata).then((positivePrompt) => {
+      if (!handlers.positivePrompt.recall) {
+        return;
+      }
+      handlers.positivePrompt?.recall(positivePrompt);
+    }),
+    handlers.negativePrompt.parse(metadata).then((negativePrompt) => {
+      if (!handlers.negativePrompt.recall) {
+        return;
+      }
+      handlers.negativePrompt?.recall(negativePrompt);
+    }),
+    handlers.sdxlPositiveStylePrompt.parse(metadata).then((sdxlPositiveStylePrompt) => {
+      if (!handlers.sdxlPositiveStylePrompt.recall) {
+        return;
+      }
+      handlers.sdxlPositiveStylePrompt?.recall(sdxlPositiveStylePrompt);
+    }),
+    handlers.sdxlNegativeStylePrompt.parse(metadata).then((sdxlNegativeStylePrompt) => {
+      if (!handlers.sdxlNegativeStylePrompt.recall) {
+        return;
+      }
+      handlers.sdxlNegativeStylePrompt?.recall(sdxlNegativeStylePrompt);
+    }),
+  ]);
+  if (results.some((result) => result.status === 'fulfilled')) {
+    parameterSetToast(t('metadata.allPrompts'));
+  }
+};
+
+export const parseAndRecallImageDimensions = async (metadata: unknown) => {
+  const results = await Promise.allSettled([
+    handlers.width.parse(metadata).then((width) => {
+      if (!handlers.width.recall) {
+        return;
+      }
+      handlers.width?.recall(width);
+    }),
+    handlers.height.parse(metadata).then((height) => {
+      if (!handlers.height.recall) {
+        return;
+      }
+      handlers.height?.recall(height);
+    }),
+  ]);
+  if (results.some((result) => result.status === 'fulfilled')) {
+    parameterSetToast(t('metadata.imageDimensions'));
+  }
+};
+
+export const parseAndRecallAllMetadata = async (metadata: unknown, skip: (keyof typeof handlers)[] = []) => {
+  const results = await Promise.allSettled(
+    objectKeys(handlers)
+      .filter((key) => !skip.includes(key))
+      .map((key) => {
+        const { parse, recall } = handlers[key];
+        return parse(metadata).then((value) => {
+          if (!recall) {
+            return;
+          }
+          /* @ts-expect-error The return type of parse and the input type of recall are guaranteed to be compatible. */
+          recall(value);
+        });
+      })
+  );
+  if (results.some((result) => result.status === 'fulfilled')) {
+    parameterSetToast(t('toast.parametersSet'));
+  }
+};
diff --git a/invokeai/frontend/web/src/features/metadata/util/recallers.ts b/invokeai/frontend/web/src/features/metadata/util/recallers.ts
index e33589d5ce..5e156dc035 100644
--- a/invokeai/frontend/web/src/features/metadata/util/recallers.ts
+++ b/invokeai/frontend/web/src/features/metadata/util/recallers.ts
@@ -203,62 +203,6 @@ const recallIPAdapters: MetadataRecallFunc<IPAdapterConfig[]> = (ipAdapters) =>
   });
 };
 
-export const recallPrompts = (_metadata: unknown) => {
-  // recallPositivePrompt(metadata);
-  // recallNegativePrompt(metadata);
-  // recallSDXLPositiveStylePrompt(metadata);
-  // recallSDXLNegativeStylePrompt(metadata);
-  // parameterNotSetToast(t('metadata.allPrompts'));
-  // parameterSetToast(t('metadata.allPrompts'));
-};
-
-export const recallWidthAndHeight = (_metadata: unknown) => {
-  // recallWidth(metadata);
-  // recallHeight(metadata);
-};
-
-export const recallAll = async (_metadata: unknown) => {
-  // if (!metadata) {
-  //   allParameterNotSetToast();
-  //   return;
-  // }
-  // // Update the main model first, as other parameters may depend on it.
-  // await recallModel(metadata);
-  // await Promise.allSettled([
-  //   // Core parameters
-  //   recallCFGScale(metadata),
-  //   recallCFGRescaleMultiplier(metadata),
-  //   recallPositivePrompt(metadata),
-  //   recallNegativePrompt(metadata),
-  //   recallScheduler(metadata),
-  //   recallSeed(metadata),
-  //   recallSteps(metadata),
-  //   recallWidth(metadata),
-  //   recallHeight(metadata),
-  //   recallStrength(metadata),
-  //   recallHRFEnabled(metadata),
-  //   recallHRFMethod(metadata),
-  //   recallHRFStrength(metadata),
-  //   // SDXL parameters
-  //   recallSDXLPositiveStylePrompt(metadata),
-  //   recallSDXLNegativeStylePrompt(metadata),
-  //   recallRefinerSteps(metadata),
-  //   recallRefinerCFGScale(metadata),
-  //   recallRefinerScheduler(metadata),
-  //   recallRefinerPositiveAestheticScore(metadata),
-  //   recallRefinerNegativeAestheticScore(metadata),
-  //   recallRefinerStart(metadata),
-  //   // Models
-  //   recallVAE(metadata),
-  //   recallRefinerModel(metadata),
-  //   recallAllLoRAs(metadata),
-  //   recallControlNets(metadata),
-  //   recallT2IAdapters(metadata),
-  //   recallIPAdapters(metadata),
-  // ]);
-  // allParameterSetToast();
-};
-
 export const recallers = {
   positivePrompt: recallPositivePrompt,
   negativePrompt: recallNegativePrompt,
diff --git a/invokeai/frontend/web/src/features/parameters/components/ImageToImage/InitialImageDisplay.tsx b/invokeai/frontend/web/src/features/parameters/components/ImageToImage/InitialImageDisplay.tsx
index 110f9bb2a2..68e981b7f5 100644
--- a/invokeai/frontend/web/src/features/parameters/components/ImageToImage/InitialImageDisplay.tsx
+++ b/invokeai/frontend/web/src/features/parameters/components/ImageToImage/InitialImageDisplay.tsx
@@ -2,7 +2,7 @@ import { Flex, IconButton, Spacer, Text } from '@invoke-ai/ui-library';
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { useImageUploadButton } from 'common/hooks/useImageUploadButton';
-import { useRecallParameters } from 'features/parameters/hooks/useRecallParameters';
+import { parseAndRecallImageDimensions } from 'features/metadata/util/handlers';
 import { clearInitialImage, selectGenerationSlice } from 'features/parameters/store/generationSlice';
 import { memo, useCallback } from 'react';
 import { useHotkeys } from 'react-hotkeys-hook';
@@ -19,7 +19,6 @@ const postUploadAction: PostUploadAction = {
 };
 
 const InitialImageDisplay = () => {
-  const { recallWidthAndHeight } = useRecallParameters();
   const { t } = useTranslation();
   const initialImage = useAppSelector(selectInitialImage);
   const dispatch = useAppDispatch();
@@ -34,9 +33,9 @@ const InitialImageDisplay = () => {
 
   const handleUseSizeInitialImage = useCallback(() => {
     if (initialImage) {
-      recallWidthAndHeight(initialImage.width, initialImage.height);
+      parseAndRecallImageDimensions(initialImage);
     }
-  }, [initialImage, recallWidthAndHeight]);
+  }, [initialImage]);
 
   useHotkeys('shift+d', handleUseSizeInitialImage, [initialImage]);
 
diff --git a/invokeai/frontend/web/src/features/parameters/hooks/usePreselectedImage.ts b/invokeai/frontend/web/src/features/parameters/hooks/usePreselectedImage.ts
index 4ec1a50dab..ab0fdca0af 100644
--- a/invokeai/frontend/web/src/features/parameters/hooks/usePreselectedImage.ts
+++ b/invokeai/frontend/web/src/features/parameters/hooks/usePreselectedImage.ts
@@ -2,6 +2,7 @@ import { skipToken } from '@reduxjs/toolkit/query';
 import { useAppToaster } from 'app/components/Toaster';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { setInitialCanvasImage } from 'features/canvas/store/canvasSlice';
+import { parseAndRecallAllMetadata } from 'features/metadata/util/handlers';
 import { initialImageSelected } from 'features/parameters/store/actions';
 import { selectOptimalDimension } from 'features/parameters/store/generationSlice';
 import { setActiveTab } from 'features/ui/store/uiSlice';
@@ -9,14 +10,12 @@ import { t } from 'i18next';
 import { useCallback, useEffect } from 'react';
 import { useGetImageDTOQuery, useGetImageMetadataQuery } from 'services/api/endpoints/images';
 
-import { useRecallParameters } from './useRecallParameters';
 
 export const usePreselectedImage = (selectedImage?: {
   imageName: string;
   action: 'sendToImg2Img' | 'sendToCanvas' | 'useAllParameters';
 }) => {
   const dispatch = useAppDispatch();
-  const { recallAllParameters } = useRecallParameters();
   const optimalDimension = useAppSelector(selectOptimalDimension);
   const toaster = useAppToaster();
 
@@ -45,10 +44,8 @@ export const usePreselectedImage = (selectedImage?: {
 
   const handleUseAllMetadata = useCallback(() => {
     if (selectedImageMetadata) {
-      recallAllParameters(selectedImageMetadata);
+      parseAndRecallAllMetadata(selectedImageMetadata);
     }
-    // disabled because `recallAllParameters` changes the model, but its dep to prepare LoRAs has model as a dep. this introduces circular logic that causes infinite re-renders
-    // eslint-disable-next-line react-hooks/exhaustive-deps
   }, [selectedImageMetadata]);
 
   useEffect(() => {
diff --git a/invokeai/frontend/web/src/features/parameters/hooks/useRecallParameters.ts b/invokeai/frontend/web/src/features/parameters/hooks/useRecallParameters.ts
deleted file mode 100644
index 8f9a76feca..0000000000
--- a/invokeai/frontend/web/src/features/parameters/hooks/useRecallParameters.ts
+++ /dev/null
@@ -1,858 +0,0 @@
-import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
-import { getStore } from 'app/store/nanostores/store';
-import { useAppDispatch } from 'app/store/storeHooks';
-import { toast } from 'common/util/toast';
-import { CONTROLNET_PROCESSORS } from 'features/controlAdapters/store/constants';
-import { controlAdapterRecalled, controlAdaptersReset } from 'features/controlAdapters/store/controlAdaptersSlice';
-import type { ControlNetConfig, IPAdapterConfig, T2IAdapterConfig } from 'features/controlAdapters/store/types';
-import {
-  initialControlNet,
-  initialIPAdapter,
-  initialT2IAdapter,
-} from 'features/controlAdapters/util/buildControlAdapter';
-import { setHrfEnabled, setHrfMethod, setHrfStrength } from 'features/hrf/store/hrfSlice';
-import type { LoRA } from 'features/lora/store/loraSlice';
-import { defaultLoRAConfig, loraRecalled, lorasCleared } from 'features/lora/store/loraSlice';
-import type { ModelIdentifierWithBase } from 'features/nodes/types/common';
-import {
-  zControlField,
-  zIPAdapterField,
-  zModelIdentifierWithBase,
-  zT2IAdapterField,
-} from 'features/nodes/types/common';
-import { initialImageSelected, modelSelected } from 'features/parameters/store/actions';
-import {
-  heightRecalled,
-  selectGenerationSlice,
-  setCfgRescaleMultiplier,
-  setCfgScale,
-  setImg2imgStrength,
-  setNegativePrompt,
-  setPositivePrompt,
-  setScheduler,
-  setSeed,
-  setSteps,
-  vaeSelected,
-  widthRecalled,
-} from 'features/parameters/store/generationSlice';
-import {
-  isParameterCFGRescaleMultiplier,
-  isParameterCFGScale,
-  isParameterHeight,
-  isParameterHRFEnabled,
-  isParameterHRFMethod,
-  isParameterLoRAWeight,
-  isParameterNegativePrompt,
-  isParameterNegativeStylePromptSDXL,
-  isParameterPositivePrompt,
-  isParameterPositiveStylePromptSDXL,
-  isParameterScheduler,
-  isParameterSDXLRefinerNegativeAestheticScore,
-  isParameterSDXLRefinerPositiveAestheticScore,
-  isParameterSDXLRefinerStart,
-  isParameterSeed,
-  isParameterSteps,
-  isParameterStrength,
-  isParameterWidth,
-} from 'features/parameters/types/parameterSchemas';
-import {
-  fetchControlNetModel,
-  fetchIPAdapterModel,
-  fetchLoRAModel,
-  fetchMainModelConfig,
-  fetchRefinerModelConfig,
-  fetchT2IAdapterModel,
-  fetchVAEModelConfig,
-  getModelKey,
-  raiseIfBaseIncompatible,
-} from 'features/parameters/util/modelFetchingHelpers';
-import {
-  refinerModelChanged,
-  setNegativeStylePromptSDXL,
-  setPositiveStylePromptSDXL,
-  setRefinerCFGScale,
-  setRefinerNegativeAestheticScore,
-  setRefinerPositiveAestheticScore,
-  setRefinerScheduler,
-  setRefinerStart,
-  setRefinerSteps,
-} from 'features/sdxl/store/sdxlSlice';
-import { t } from 'i18next';
-import { get, isArray, isNil } from 'lodash-es';
-import { useCallback } from 'react';
-import type { BaseModelType, ImageDTO } from 'services/api/types';
-import { v4 as uuidv4 } from 'uuid';
-
-const selectModel = createMemoizedSelector(selectGenerationSlice, (generation) => generation.model);
-
-/**
- * A function that recalls from metadata from the full metadata object.
- */
-type MetadataRecallFunc = (metadata: unknown, withToast?: boolean) => void;
-
-/**
- * A function that recalls metadata from a specific metadata item.
- */
-type MetadataItemRecallFunc = (metadataItem: unknown, withToast?: boolean) => void;
-
-/**
- * Raised when metadata recall fails.
- */
-export class MetadataRecallError extends Error {
-  /**
-   * Create MetadataRecallError
-   * @param {String} message
-   */
-  constructor(message: string) {
-    super(message);
-    this.name = this.constructor.name;
-  }
-}
-
-export class InvalidMetadataPropertyType extends MetadataRecallError {}
-
-const getProperty = <T = unknown>(
-  obj: unknown,
-  property: string,
-  typeGuard: (val: unknown) => val is T = (val: unknown): val is T => true
-): T => {
-  const val = get(obj, property) as unknown;
-  if (typeGuard(val)) {
-    return val;
-  }
-  throw new InvalidMetadataPropertyType(`Property ${property} is not of expected type`);
-};
-
-const getCurrentBase = () => selectModel(getStore().getState())?.base;
-
-const parameterSetToast = (parameter: string, description?: string) => {
-  toast({
-    title: t('toast.parameterSet', { parameter }),
-    description,
-    status: 'info',
-    duration: 2500,
-    isClosable: true,
-  });
-};
-
-const parameterNotSetToast = (parameter: string, description?: string) => {
-  toast({
-    title: t('toast.parameterNotSet', { parameter }),
-    description,
-    status: 'warning',
-    duration: 2500,
-    isClosable: true,
-  });
-};
-
-const allParameterSetToast = (description?: string) => {
-  toast({
-    title: t('toast.parametersSet'),
-    status: 'info',
-    description,
-    duration: 2500,
-    isClosable: true,
-  });
-};
-
-const allParameterNotSetToast = (description?: string) => {
-  toast({
-    title: t('toast.parametersNotSet'),
-    status: 'warning',
-    description,
-    duration: 2500,
-    isClosable: true,
-  });
-};
-
-const recall = (callback: () => void, parameter: string, withToast = true) => {
-  try {
-    callback();
-    withToast && parameterSetToast(parameter);
-  } catch (e) {
-    withToast && parameterNotSetToast(parameter, (e as Error).message);
-  }
-};
-
-const recallAsync = async (callback: () => Promise<void>, parameter: string, withToast = true) => {
-  try {
-    await callback();
-    withToast && parameterSetToast(parameter);
-  } catch (e) {
-    withToast && parameterNotSetToast(parameter, (e as Error).message);
-  }
-};
-
-export const recallPositivePrompt: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
-  recall(
-    () => {
-      const positive_prompt = getProperty(metadata, 'positive_prompt', isParameterPositivePrompt);
-      getStore().dispatch(setPositivePrompt(positive_prompt));
-    },
-    t('metadata.positivePrompt'),
-    withToast
-  );
-};
-
-export const recallNegativePrompt: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
-  recall(
-    () => {
-      const negative_prompt = getProperty(metadata, 'negative_prompt', isParameterNegativePrompt);
-      getStore().dispatch(setNegativePrompt(negative_prompt));
-    },
-    t('metadata.negativePrompt'),
-    withToast
-  );
-};
-
-export const recallSDXLPositiveStylePrompt: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
-  recall(
-    () => {
-      const positive_style_prompt = getProperty(metadata, 'positive_style_prompt', isParameterPositiveStylePromptSDXL);
-      getStore().dispatch(setPositiveStylePromptSDXL(positive_style_prompt));
-    },
-    t('sdxl.posStylePrompt'),
-    withToast
-  );
-};
-
-export const recallSDXLNegativeStylePrompt: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
-  recall(
-    () => {
-      const negative_style_prompt = getProperty(metadata, 'negative_style_prompt', isParameterNegativeStylePromptSDXL);
-      getStore().dispatch(setNegativeStylePromptSDXL(negative_style_prompt));
-    },
-    t('sdxl.negStylePrompt'),
-    withToast
-  );
-};
-
-export const recallSeed: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
-  recall(
-    () => {
-      const seed = getProperty(metadata, 'seed', isParameterSeed);
-      getStore().dispatch(setSeed(seed));
-    },
-    t('metadata.seed'),
-    withToast
-  );
-};
-
-export const recallCFGScale: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
-  recall(
-    () => {
-      const cfg_scale = getProperty(metadata, 'cfg_scale', isParameterCFGScale);
-      getStore().dispatch(setCfgScale(cfg_scale));
-    },
-    t('metadata.cfgScale'),
-    withToast
-  );
-};
-
-export const recallCFGRescaleMultiplier: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
-  recall(
-    () => {
-      const cfg_rescale_multiplier = getProperty(metadata, 'cfg_rescale_multiplier', isParameterCFGRescaleMultiplier);
-      getStore().dispatch(setCfgRescaleMultiplier(cfg_rescale_multiplier));
-    },
-    t('metadata.cfgRescaleMultiplier'),
-    withToast
-  );
-};
-
-export const recallScheduler: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
-  recall(
-    () => {
-      const scheduler = getProperty(metadata, 'scheduler', isParameterScheduler);
-      getStore().dispatch(setScheduler(scheduler));
-    },
-    t('metadata.scheduler'),
-    withToast
-  );
-};
-
-export const recallWidth: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
-  recall(
-    () => {
-      const width = getProperty(metadata, 'width', isParameterWidth);
-      getStore().dispatch(widthRecalled(width));
-    },
-    t('metadata.width'),
-    withToast
-  );
-};
-
-export const recallHeight: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
-  recall(
-    () => {
-      const height = getProperty(metadata, 'height', isParameterHeight);
-      getStore().dispatch(heightRecalled(height));
-    },
-    t('metadata.height'),
-    withToast
-  );
-};
-
-export const recallSteps: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
-  recall(
-    () => {
-      const steps = getProperty(metadata, 'steps', isParameterSteps);
-      getStore().dispatch(setSteps(steps));
-    },
-    t('metadata.steps'),
-    withToast
-  );
-};
-
-export const recallStrength: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
-  recall(
-    () => {
-      const strength = getProperty(metadata, 'strength', isParameterStrength);
-      getStore().dispatch(setImg2imgStrength(strength));
-    },
-    t('metadata.strength'),
-    withToast
-  );
-};
-
-export const recallHRFEnabled: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
-  recall(
-    () => {
-      const hrf_enabled = getProperty(metadata, 'hrf_enabled', isParameterHRFEnabled);
-      getStore().dispatch(setHrfEnabled(hrf_enabled));
-    },
-    t('hrf.metadata.enabled'),
-    withToast
-  );
-};
-
-export const recallHRFStrength: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
-  recall(
-    () => {
-      const hrf_strength = getProperty(metadata, 'hrf_strength', isParameterStrength);
-      getStore().dispatch(setHrfStrength(hrf_strength));
-    },
-    t('hrf.metadata.strength'),
-    withToast
-  );
-};
-
-export const recallHRFMethod: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
-  recall(
-    () => {
-      const hrf_method = getProperty(metadata, 'hrf_method', isParameterHRFMethod);
-      getStore().dispatch(setHrfMethod(hrf_method));
-    },
-    t('hrf.metadata.method'),
-    withToast
-  );
-};
-
-export const recallRefinerSteps: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
-  recall(
-    () => {
-      const refiner_steps = getProperty(metadata, 'refiner_steps', isParameterSteps);
-      getStore().dispatch(setRefinerSteps(refiner_steps));
-    },
-    t('sdxl.steps'),
-    withToast
-  );
-};
-
-export const recallRefinerCFGScale: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
-  recall(
-    () => {
-      const refiner_cfg_scale = getProperty(metadata, 'refiner_cfg_scale', isParameterCFGScale);
-      getStore().dispatch(setRefinerCFGScale(refiner_cfg_scale));
-    },
-    t('sdxl.cfgScale'),
-    withToast
-  );
-};
-
-export const recallRefinerScheduler: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
-  recall(
-    () => {
-      const refiner_scheduler = getProperty(metadata, 'refiner_scheduler', isParameterScheduler);
-      getStore().dispatch(setRefinerScheduler(refiner_scheduler));
-    },
-    t('sdxl.cfgScale'),
-    withToast
-  );
-};
-
-export const recallRefinerPositiveAestheticScore: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
-  recall(
-    () => {
-      const refiner_positive_aesthetic_score = getProperty(
-        metadata,
-        'refiner_positive_aesthetic_score',
-        isParameterSDXLRefinerPositiveAestheticScore
-      );
-      getStore().dispatch(setRefinerPositiveAestheticScore(refiner_positive_aesthetic_score));
-    },
-    t('sdxl.posAestheticScore'),
-    withToast
-  );
-};
-
-export const recallRefinerNegativeAestheticScore: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
-  recall(
-    () => {
-      const refiner_negative_aesthetic_score = getProperty(
-        metadata,
-        'refiner_negative_aesthetic_score',
-        isParameterSDXLRefinerNegativeAestheticScore
-      );
-      getStore().dispatch(setRefinerNegativeAestheticScore(refiner_negative_aesthetic_score));
-    },
-    t('sdxl.negAestheticScore'),
-    withToast
-  );
-};
-
-export const recallRefinerStart: MetadataRecallFunc = (metadata: unknown, withToast = true) => {
-  recall(
-    () => {
-      const refiner_start = getProperty(metadata, 'refiner_start', isParameterSDXLRefinerStart);
-      getStore().dispatch(setRefinerStart(refiner_start));
-    },
-    t('sdxl.refinerStart'),
-    withToast
-  );
-};
-
-export const prepareMainModelMetadataItem = async (model: unknown): Promise<ModelIdentifierWithBase> => {
-  const key = await getModelKey(model, 'main');
-  const mainModel = await fetchMainModelConfig(key);
-  return zModelIdentifierWithBase.parse(mainModel);
-};
-
-const recallModelAsync: MetadataRecallFunc = async (metadata: unknown, withToast = true) => {
-  await recallAsync(
-    async () => {
-      const modelMetadataItem = getProperty(metadata, 'model');
-      const model = await prepareMainModelMetadataItem(modelMetadataItem);
-      getStore().dispatch(modelSelected(model));
-    },
-    t('metadata.model'),
-    withToast
-  );
-};
-
-export const prepareRefinerMetadataItem = async (
-  model: unknown,
-  currentBase: BaseModelType | undefined
-): Promise<ModelIdentifierWithBase> => {
-  const key = await getModelKey(model, 'main');
-  const refinerModel = await fetchRefinerModelConfig(key);
-  raiseIfBaseIncompatible('sdxl-refiner', currentBase, 'Refiner incompatible with currently-selected model');
-  return zModelIdentifierWithBase.parse(refinerModel);
-};
-
-const recallRefinerModelAsync: MetadataRecallFunc = async (metadata: unknown, withToast = true) => {
-  await recallAsync(
-    async () => {
-      const refinerMetadataItem = getProperty(metadata, 'refiner_model');
-      const refiner = await prepareRefinerMetadataItem(refinerMetadataItem, getCurrentBase());
-      getStore().dispatch(refinerModelChanged(refiner));
-    },
-    t('sdxl.refinerModel'),
-    withToast
-  );
-};
-
-export const prepareVAEMetadataItem = async (
-  vae: unknown,
-  currentBase: BaseModelType | undefined
-): Promise<ModelIdentifierWithBase> => {
-  const key = await getModelKey(vae, 'vae');
-  const vaeModel = await fetchVAEModelConfig(key);
-  raiseIfBaseIncompatible(vaeModel.base, currentBase, 'VAE incompatible with currently-selected model');
-  return zModelIdentifierWithBase.parse(vaeModel);
-};
-
-const recallVAEAsync: MetadataRecallFunc = async (metadata: unknown, withToast = true) => {
-  await recallAsync(
-    async () => {
-      const currentBase = getCurrentBase();
-      const vaeMetadataItem = getProperty(metadata, 'vae');
-      if (isNil(vaeMetadataItem)) {
-        getStore().dispatch(vaeSelected(null));
-      } else {
-        const vae = await prepareVAEMetadataItem(vaeMetadataItem, currentBase);
-        getStore().dispatch(vaeSelected(vae));
-      }
-    },
-    t('metadata.vae'),
-    withToast
-  );
-};
-
-export const prepareLoRAMetadataItem = async (
-  loraMetadataItem: unknown,
-  currentBase: BaseModelType | undefined
-): Promise<LoRA> => {
-  const lora = getProperty(loraMetadataItem, 'lora');
-  const weight = getProperty(loraMetadataItem, 'weight');
-  const key = await getModelKey(lora, 'lora');
-  const loraModel = await fetchLoRAModel(key);
-  raiseIfBaseIncompatible(loraModel.base, currentBase, 'LoRA incompatible with currently-selected model');
-  return {
-    key: loraModel.key,
-    base: loraModel.base,
-    weight: isParameterLoRAWeight(weight) ? weight : defaultLoRAConfig.weight,
-    isEnabled: true,
-  };
-};
-
-const recallLoRAAsync: MetadataItemRecallFunc = async (metadataItem: unknown, withToast = true) => {
-  await recallAsync(
-    async () => {
-      const currentBase = getCurrentBase();
-      const lora = await prepareLoRAMetadataItem(metadataItem, currentBase);
-      getStore().dispatch(loraRecalled(lora));
-    },
-    t('models.lora'),
-    withToast
-  );
-};
-
-export const prepareControlNetMetadataItem = async (
-  metadataItem: unknown,
-  currentBase: BaseModelType | undefined
-): Promise<ControlNetConfig> => {
-  const control_model = getProperty(metadataItem, 'control_model');
-  const key = await getModelKey(control_model, 'controlnet');
-  const controlNetModel = await fetchControlNetModel(key);
-  raiseIfBaseIncompatible(controlNetModel.base, currentBase, 'ControlNet incompatible with currently-selected model');
-
-  const image = zControlField.shape.image.nullish().catch(null).parse(getProperty(metadataItem, 'image'));
-  const control_weight = zControlField.shape.control_weight
-    .nullish()
-    .catch(null)
-    .parse(getProperty(metadataItem, 'control_weight'));
-  const begin_step_percent = zControlField.shape.begin_step_percent
-    .nullish()
-    .catch(null)
-    .parse(getProperty(metadataItem, 'begin_step_percent'));
-  const end_step_percent = zControlField.shape.end_step_percent
-    .nullish()
-    .catch(null)
-    .parse(getProperty(metadataItem, 'end_step_percent'));
-  const control_mode = zControlField.shape.control_mode
-    .nullish()
-    .catch(null)
-    .parse(getProperty(metadataItem, 'control_mode'));
-  const resize_mode = zControlField.shape.resize_mode
-    .nullish()
-    .catch(null)
-    .parse(getProperty(metadataItem, 'resize_mode'));
-
-  // We don't save the original image that was processed into a control image, only the processed image
-  const processorType = 'none';
-  const processorNode = CONTROLNET_PROCESSORS.none.default;
-
-  const controlnet: ControlNetConfig = {
-    type: 'controlnet',
-    isEnabled: true,
-    model: zModelIdentifierWithBase.parse(controlNetModel),
-    weight: typeof control_weight === 'number' ? control_weight : initialControlNet.weight,
-    beginStepPct: begin_step_percent ?? initialControlNet.beginStepPct,
-    endStepPct: end_step_percent ?? initialControlNet.endStepPct,
-    controlMode: control_mode ?? initialControlNet.controlMode,
-    resizeMode: resize_mode ?? initialControlNet.resizeMode,
-    controlImage: image?.image_name ?? null,
-    processedControlImage: image?.image_name ?? null,
-    processorType,
-    processorNode,
-    shouldAutoConfig: true,
-    id: uuidv4(),
-  };
-
-  return controlnet;
-};
-
-const recallControlNetAsync: MetadataItemRecallFunc = async (metadataItem: unknown, withToast = true) => {
-  await recallAsync(
-    async () => {
-      const currentBase = getCurrentBase();
-      const controlNetConfig = await prepareControlNetMetadataItem(metadataItem, currentBase);
-      getStore().dispatch(controlAdapterRecalled(controlNetConfig));
-    },
-    t('common.controlNet'),
-    withToast
-  );
-};
-
-export const prepareT2IAdapterMetadataItem = async (
-  metadataItem: unknown,
-  currentBase: BaseModelType | undefined
-): Promise<T2IAdapterConfig> => {
-  const t2i_adapter_model = getProperty(metadataItem, 't2i_adapter_model');
-  const key = await getModelKey(t2i_adapter_model, 't2i_adapter');
-  const t2iAdapterModel = await fetchT2IAdapterModel(key);
-  raiseIfBaseIncompatible(t2iAdapterModel.base, currentBase, 'T2I Adapter incompatible with currently-selected model');
-
-  const image = zT2IAdapterField.shape.image.nullish().catch(null).parse(getProperty(metadataItem, 'image'));
-  const weight = zT2IAdapterField.shape.weight.nullish().catch(null).parse(getProperty(metadataItem, 'weight'));
-  const begin_step_percent = zT2IAdapterField.shape.begin_step_percent
-    .nullish()
-    .catch(null)
-    .parse(getProperty(metadataItem, 'begin_step_percent'));
-  const end_step_percent = zT2IAdapterField.shape.end_step_percent
-    .nullish()
-    .catch(null)
-    .parse(getProperty(metadataItem, 'end_step_percent'));
-  const resize_mode = zT2IAdapterField.shape.resize_mode
-    .nullish()
-    .catch(null)
-    .parse(getProperty(metadataItem, 'resize_mode'));
-
-  // We don't save the original image that was processed into a control image, only the processed image
-  const processorType = 'none';
-  const processorNode = CONTROLNET_PROCESSORS.none.default;
-
-  const t2iAdapter: T2IAdapterConfig = {
-    type: 't2i_adapter',
-    isEnabled: true,
-    model: zModelIdentifierWithBase.parse(t2iAdapterModel),
-    weight: typeof weight === 'number' ? weight : initialT2IAdapter.weight,
-    beginStepPct: begin_step_percent ?? initialT2IAdapter.beginStepPct,
-    endStepPct: end_step_percent ?? initialT2IAdapter.endStepPct,
-    resizeMode: resize_mode ?? initialT2IAdapter.resizeMode,
-    controlImage: image?.image_name ?? null,
-    processedControlImage: image?.image_name ?? null,
-    processorType,
-    processorNode,
-    shouldAutoConfig: true,
-    id: uuidv4(),
-  };
-
-  return t2iAdapter;
-};
-
-const recallT2IAdapterAsync: MetadataItemRecallFunc = async (metadataItem: unknown, withToast = true) => {
-  await recallAsync(
-    async () => {
-      const currentBase = getCurrentBase();
-      const t2iAdapterConfig = await prepareT2IAdapterMetadataItem(metadataItem, currentBase);
-      getStore().dispatch(controlAdapterRecalled(t2iAdapterConfig));
-    },
-    t('common.t2iAdapter'),
-    withToast
-  );
-};
-
-export const prepareIPAdapterMetadataItem = async (
-  metadataItem: unknown,
-  currentBase: BaseModelType | undefined
-): Promise<IPAdapterConfig> => {
-  const ip_adapter_model = getProperty(metadataItem, 'ip_adapter_model');
-  const key = await getModelKey(ip_adapter_model, 'ip_adapter');
-  const ipAdapterModel = await fetchIPAdapterModel(key);
-  raiseIfBaseIncompatible(ipAdapterModel.base, currentBase, 'T2I Adapter incompatible with currently-selected model');
-
-  const image = zIPAdapterField.shape.image.nullish().catch(null).parse(getProperty(metadataItem, 'image'));
-  const weight = zIPAdapterField.shape.weight.nullish().catch(null).parse(getProperty(metadataItem, 'weight'));
-  const begin_step_percent = zIPAdapterField.shape.begin_step_percent
-    .nullish()
-    .catch(null)
-    .parse(getProperty(metadataItem, 'begin_step_percent'));
-  const end_step_percent = zIPAdapterField.shape.end_step_percent
-    .nullish()
-    .catch(null)
-    .parse(getProperty(metadataItem, 'end_step_percent'));
-
-  const ipAdapter: IPAdapterConfig = {
-    id: uuidv4(),
-    type: 'ip_adapter',
-    isEnabled: true,
-    model: zModelIdentifierWithBase.parse(ipAdapterModel),
-    controlImage: image?.image_name ?? null,
-    weight: weight ?? initialIPAdapter.weight,
-    beginStepPct: begin_step_percent ?? initialIPAdapter.beginStepPct,
-    endStepPct: end_step_percent ?? initialIPAdapter.endStepPct,
-  };
-
-  return ipAdapter;
-};
-
-const recallIPAdapterAsync: MetadataItemRecallFunc = async (metadataItem: unknown, withToast) => {
-  await recallAsync(
-    async () => {
-      const currentBase = getCurrentBase();
-      const ipAdapterConfig = await prepareIPAdapterMetadataItem(metadataItem, currentBase);
-      getStore().dispatch(controlAdapterRecalled(ipAdapterConfig));
-    },
-    t('common.ipAdapter'),
-    withToast
-  );
-};
-
-export const useRecallParameters = () => {
-  const dispatch = useAppDispatch();
-
-  const recallBothPrompts = useCallback<MetadataRecallFunc>(
-    (metadata: unknown) => {
-      const positive_prompt = getProperty(metadata, 'positive_prompt');
-      const negative_prompt = getProperty(metadata, 'negative_prompt');
-      const positive_style_prompt = getProperty(metadata, 'positive_style_prompt');
-      const negative_style_prompt = getProperty(metadata, 'negative_style_prompt');
-      if (
-        isParameterPositivePrompt(positive_prompt) ||
-        isParameterNegativePrompt(negative_prompt) ||
-        isParameterPositiveStylePromptSDXL(positive_style_prompt) ||
-        isParameterNegativeStylePromptSDXL(negative_style_prompt)
-      ) {
-        if (isParameterPositivePrompt(positive_prompt)) {
-          dispatch(setPositivePrompt(positive_prompt));
-        }
-
-        if (isParameterNegativePrompt(negative_prompt)) {
-          dispatch(setNegativePrompt(negative_prompt));
-        }
-
-        if (isParameterPositiveStylePromptSDXL(positive_style_prompt)) {
-          dispatch(setPositiveStylePromptSDXL(positive_style_prompt));
-        }
-
-        if (isParameterPositiveStylePromptSDXL(negative_style_prompt)) {
-          dispatch(setNegativeStylePromptSDXL(negative_style_prompt));
-        }
-
-        parameterSetToast(t('metadata.allPrompts'));
-        return;
-      }
-      parameterNotSetToast(t('metadata.allPrompts'));
-    },
-    [dispatch]
-  );
-
-  const recallWidthAndHeight = useCallback<MetadataRecallFunc>(
-    (metadata: unknown) => {
-      const width = getProperty(metadata, 'width');
-      const height = getProperty(metadata, 'height');
-
-      if (!isParameterWidth(width)) {
-        allParameterNotSetToast();
-        return;
-      }
-      if (!isParameterHeight(height)) {
-        allParameterNotSetToast();
-        return;
-      }
-      dispatch(heightRecalled(height));
-      dispatch(widthRecalled(width));
-      allParameterSetToast();
-    },
-    [dispatch]
-  );
-
-  const sendToImageToImage = useCallback(
-    (image: ImageDTO) => {
-      dispatch(initialImageSelected(image));
-    },
-    [dispatch]
-  );
-
-  const recallAllParameters = useCallback<MetadataRecallFunc>(
-    async (metadata: unknown) => {
-      if (!metadata) {
-        allParameterNotSetToast();
-        return;
-      }
-
-      await recallModelAsync(metadata, false);
-
-      recallCFGScale(metadata, false);
-      recallCFGRescaleMultiplier(metadata, false);
-      recallPositivePrompt(metadata, false);
-      recallNegativePrompt(metadata, false);
-      recallScheduler(metadata, false);
-      recallSeed(metadata, false);
-      recallSteps(metadata, false);
-      recallWidth(metadata, false);
-      recallHeight(metadata, false);
-      recallStrength(metadata, false);
-      recallHRFEnabled(metadata, false);
-      recallHRFMethod(metadata, false);
-      recallHRFStrength(metadata, false);
-
-      // SDXL
-      recallSDXLPositiveStylePrompt(metadata, false);
-      recallSDXLNegativeStylePrompt(metadata, false);
-      recallRefinerSteps(metadata, false);
-      recallRefinerCFGScale(metadata, false);
-      recallRefinerScheduler(metadata, false);
-      recallRefinerPositiveAestheticScore(metadata, false);
-      recallRefinerNegativeAestheticScore(metadata, false);
-      recallRefinerStart(metadata, false);
-
-      await recallVAEAsync(metadata, false);
-      await recallRefinerModelAsync(metadata, false);
-
-      dispatch(lorasCleared());
-      const loraMetadataArray = getProperty(metadata, 'loras');
-      if (isArray(loraMetadataArray)) {
-        loraMetadataArray.forEach(async (loraMetadataItem) => {
-          await recallLoRAAsync(loraMetadataItem, false);
-        });
-      }
-
-      dispatch(controlAdaptersReset());
-      const controlNetMetadataArray = getProperty(metadata, 'controlnets');
-      if (isArray(controlNetMetadataArray)) {
-        controlNetMetadataArray.forEach(async (controlNetMetadataItem) => {
-          await recallControlNetAsync(controlNetMetadataItem, false);
-        });
-      }
-
-      const ipAdapterMetadataArray = getProperty(metadata, 'ipAdapters');
-      if (isArray(ipAdapterMetadataArray)) {
-        ipAdapterMetadataArray.forEach(async (ipAdapterMetadataItem) => {
-          await recallIPAdapterAsync(ipAdapterMetadataItem, false);
-        });
-      }
-
-      const t2iAdapterMetadataArray = getProperty(metadata, 't2iAdapters');
-      if (isArray(t2iAdapterMetadataArray)) {
-        t2iAdapterMetadataArray.forEach(async (t2iAdapterMetadataItem) => {
-          await recallT2IAdapterAsync(t2iAdapterMetadataItem, false);
-        });
-      }
-
-      allParameterSetToast();
-    },
-    [dispatch]
-  );
-
-  return {
-    recallBothPrompts,
-    recallPositivePrompt,
-    recallNegativePrompt,
-    recallSDXLPositiveStylePrompt,
-    recallSDXLNegativeStylePrompt,
-    recallSeed,
-    recallCFGScale,
-    recallCFGRescaleMultiplier,
-    recallModel: recallModelAsync,
-    recallScheduler,
-    recallVaeModel: recallVAEAsync,
-    recallSteps,
-    recallWidth,
-    recallHeight,
-    recallWidthAndHeight,
-    recallStrength,
-    recallHRFEnabled,
-    recallHRFStrength,
-    recallHRFMethod,
-    recallLoRA: recallLoRAAsync,
-    recallControlNet: recallControlNetAsync,
-    recallIPAdapter: recallIPAdapterAsync,
-    recallT2IAdapter: recallT2IAdapterAsync,
-    recallAllParameters,
-    recallRefinerModel: recallRefinerModelAsync,
-    sendToImageToImage,
-  };
-};

From e6de915c340792064a7a11207c96f1bbbae38bb5 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 26 Feb 2024 11:51:25 +1100
Subject: [PATCH 319/411] fix(ui): fix type issues related to change in LoRA
 type

---
 .../middleware/listenerMiddleware/listeners/modelSelected.ts   | 2 +-
 .../middleware/listenerMiddleware/listeners/modelsLoaded.ts    | 2 +-
 .../frontend/web/src/features/lora/components/LoRAList.tsx     | 2 +-
 .../web/src/features/nodes/util/graph/addLoRAsToGraph.ts       | 3 ++-
 .../web/src/features/nodes/util/graph/addSDXLLoRAstoGraph.ts   | 3 ++-
 5 files changed, 7 insertions(+), 5 deletions(-)

diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/modelSelected.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/modelSelected.ts
index 35e2ad5f9b..bbb9485bcf 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/modelSelected.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/modelSelected.ts
@@ -39,7 +39,7 @@ export const addModelSelectedListener = () => {
 
         // handle incompatible loras
         forEach(state.lora.loras, (lora, id) => {
-          if (lora.base !== newBaseModel) {
+          if (lora.model.base !== newBaseModel) {
             dispatch(loraRemoved(id));
             modelsCleared += 1;
           }
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/modelsLoaded.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/modelsLoaded.ts
index 366644fa68..a1bc9856c9 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/modelsLoaded.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/modelsLoaded.ts
@@ -123,7 +123,7 @@ export const addModelsLoadedListener = () => {
       const loras = getState().lora.loras;
 
       forEach(loras, (lora, id) => {
-        const isLoRAAvailable = some(action.payload.entities, (m) => m?.key === lora?.key);
+        const isLoRAAvailable = some(action.payload.entities, (m) => m?.key === lora?.model.key);
 
         if (isLoRAAvailable) {
           return;
diff --git a/invokeai/frontend/web/src/features/lora/components/LoRAList.tsx b/invokeai/frontend/web/src/features/lora/components/LoRAList.tsx
index 7bcd537805..68d259a852 100644
--- a/invokeai/frontend/web/src/features/lora/components/LoRAList.tsx
+++ b/invokeai/frontend/web/src/features/lora/components/LoRAList.tsx
@@ -18,7 +18,7 @@ export const LoRAList = memo(() => {
   return (
     <Flex flexWrap="wrap" gap={2}>
       {lorasArray.map((lora) => (
-        <LoRACard key={lora.key} lora={lora} />
+        <LoRACard key={lora.model.key} lora={lora} />
       ))}
     </Flex>
   );
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/addLoRAsToGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/addLoRAsToGraph.ts
index 3d1545d466..5c47cf5c58 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/addLoRAsToGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/addLoRAsToGraph.ts
@@ -40,7 +40,8 @@ export const addLoRAsToGraph = (
   const loraMetadata: CoreMetadataInvocation['loras'] = [];
 
   enabledLoRAs.forEach((lora) => {
-    const { key, weight } = lora;
+    const { weight } = lora;
+    const { key } = lora.model;
     const currentLoraNodeId = `${LORA_LOADER}_${key}`;
 
     const loraLoaderNode: LoraLoaderInvocation = {
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/addSDXLLoRAstoGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/addSDXLLoRAstoGraph.ts
index 27f4c0c015..54d1e2116d 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/addSDXLLoRAstoGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/addSDXLLoRAstoGraph.ts
@@ -58,7 +58,8 @@ export const addSDXLLoRAsToGraph = (
   let currentLoraIndex = 0;
 
   enabledLoRAs.forEach((lora) => {
-    const { key, weight } = lora;
+    const { weight } = lora;
+    const { key } = lora.model;
     const currentLoraNodeId = `${LORA_LOADER}_${key}`;
 
     const loraLoaderNode: SDXLLoraLoaderInvocation = {

From 04545e792c60b91b42e712d8787ba8b07b1bcb25 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 26 Feb 2024 11:51:37 +1100
Subject: [PATCH 320/411] fix(ui): fix lora metadata rendering

---
 .../web/src/features/metadata/components/MetadataLoRAs.tsx     | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/invokeai/frontend/web/src/features/metadata/components/MetadataLoRAs.tsx b/invokeai/frontend/web/src/features/metadata/components/MetadataLoRAs.tsx
index 3225a048d4..40f6bc427b 100644
--- a/invokeai/frontend/web/src/features/metadata/components/MetadataLoRAs.tsx
+++ b/invokeai/frontend/web/src/features/metadata/components/MetadataLoRAs.tsx
@@ -1,3 +1,4 @@
+import { Text } from '@invoke-ai/ui-library';
 import type { LoRA } from 'features/lora/store/loraSlice';
 import { MetadataItemView } from 'features/metadata/components/MetadataItemView';
 import type { MetadataHandlers } from 'features/metadata/types';
@@ -54,7 +55,7 @@ const MetadataViewLoRA = ({
     if (!handlers.renderItemValue) {
       return null;
     }
-    return handlers.renderItemValue(lora);
+    return <Text>{handlers.renderItemValue(lora)}</Text>;
   }, [handlers, lora]);
 
   return <MetadataItemView label={label} isDisabled={false} onRecall={onRecall} renderedValue={renderedValue} />;

From 7326c78ab5b0762d6867559d07e24ddea68c2354 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 26 Feb 2024 11:52:28 +1100
Subject: [PATCH 321/411] feat(ui): add transformation to width/height
 parameter schemas to round to multiple of 8

This allows image dimensions that are not multiples of 8 to still be recalled with best effort.
---
 .../src/features/parameters/types/parameterSchemas.ts | 11 ++++++-----
 1 file changed, 6 insertions(+), 5 deletions(-)

diff --git a/invokeai/frontend/web/src/features/parameters/types/parameterSchemas.ts b/invokeai/frontend/web/src/features/parameters/types/parameterSchemas.ts
index 8d46add8c8..0fc912a6d6 100644
--- a/invokeai/frontend/web/src/features/parameters/types/parameterSchemas.ts
+++ b/invokeai/frontend/web/src/features/parameters/types/parameterSchemas.ts
@@ -1,8 +1,6 @@
 import { NUMPY_RAND_MAX } from 'app/constants';
-import {
-  zModelIdentifierWithBase,
-  zSchedulerField,
-} from 'features/nodes/types/common';
+import { roundToMultiple } from 'common/util/roundDownToMultiple';
+import { zModelIdentifierWithBase, zSchedulerField } from 'features/nodes/types/common';
 import { z } from 'zod';
 
 /**
@@ -79,7 +77,10 @@ export const isParameterSeed = (val: unknown): val is ParameterSeed => zParamete
 // #endregion
 
 // #region Width
-export const zParameterWidth = z.number().multipleOf(8).min(64);
+export const zParameterWidth = z
+  .number()
+  .min(64)
+  .transform((val) => roundToMultiple(val, 8));
 export type ParameterWidth = z.infer<typeof zParameterWidth>;
 export const isParameterWidth = (val: unknown): val is ParameterWidth => zParameterWidth.safeParse(val).success;
 // #endregion

From 24daacecf2d2da14c1b8c275cec1ef5699bcca8a Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 26 Feb 2024 11:56:28 +1100
Subject: [PATCH 322/411] fix(ui): fix node type

---
 invokeai/frontend/web/src/services/api/types.ts | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/invokeai/frontend/web/src/services/api/types.ts b/invokeai/frontend/web/src/services/api/types.ts
index 4d4de90e59..cb848e168e 100644
--- a/invokeai/frontend/web/src/services/api/types.ts
+++ b/invokeai/frontend/web/src/services/api/types.ts
@@ -151,7 +151,7 @@ export type InfillPatchMatchInvocation = S['InfillPatchMatchInvocation'];
 export type InfillTileInvocation = S['InfillTileInvocation'];
 export type CreateDenoiseMaskInvocation = S['CreateDenoiseMaskInvocation'];
 export type CreateGradientMaskInvocation = S['CreateGradientMaskInvocation'];
-export type IAICanvasPasteBackInvocation = S['IAICanvasPasteBackInvocation'];
+export type CanvasPasteBackInvocation = S['CanvasPasteBackInvocation'];
 export type MaskEdgeInvocation = S['MaskEdgeInvocation'];
 export type RandomIntInvocation = S['RandomIntInvocation'];
 export type CompelInvocation = S['CompelInvocation'];

From 0b54bfb7c5f7b94d1a6853a82b9949536c85242f Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 26 Feb 2024 11:59:05 +1100
Subject: [PATCH 323/411] fix(ui): fix lora metadata item type

---
 invokeai/frontend/web/src/features/nodes/types/metadata.ts | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/invokeai/frontend/web/src/features/nodes/types/metadata.ts b/invokeai/frontend/web/src/features/nodes/types/metadata.ts
index 2789abaaca..132f9f781a 100644
--- a/invokeai/frontend/web/src/features/nodes/types/metadata.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/metadata.ts
@@ -1,6 +1,6 @@
 import { z } from 'zod';
 
-import { zControlField, zIPAdapterField, zT2IAdapterField } from './common';
+import { zControlField, zIPAdapterField, zModelFieldBase, zT2IAdapterField } from './common';
 
 export const zLoRAWeight = z.number().nullish();
 // #region Metadata-optimized versions of schemas
@@ -8,7 +8,7 @@ export const zLoRAWeight = z.number().nullish();
 // - https://github.com/colinhacks/zod/issues/2106
 // - https://github.com/colinhacks/zod/issues/2854
 export const zLoRAMetadataItem = z.object({
-  lora: z.unknown(),
+  lora: zModelFieldBase.deepPartial(),
   weight: zLoRAWeight,
 });
 const zControlNetMetadataItem = zControlField.merge(z.object({ control_model: z.unknown() })).deepPartial();

From 7176c5d9d6a5a4d33013fbdbcbdb2703fea5ec14 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 26 Feb 2024 13:27:13 +1100
Subject: [PATCH 324/411] feat(ui): optimize model query caching

When we retrieve a list of models, upsert that data into the `getModelConfig` and `getModelConfigByAttrs` query caches.

With this change, calls to those two queries are almost always going to be free, because their caches will already have all models in them. The exception is queries for models that no longer exist.
---
 .../web/src/services/api/endpoints/models.ts  | 58 ++++++++++++++++++-
 1 file changed, 55 insertions(+), 3 deletions(-)

diff --git a/invokeai/frontend/web/src/services/api/endpoints/models.ts b/invokeai/frontend/web/src/services/api/endpoints/models.ts
index 3ccccf62e1..2d1d021bc6 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/models.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/models.ts
@@ -1,4 +1,4 @@
-import type { EntityAdapter, EntityState } from '@reduxjs/toolkit';
+import type { EntityAdapter, EntityState, ThunkDispatch, UnknownAction } from '@reduxjs/toolkit';
 import { createEntityAdapter } from '@reduxjs/toolkit';
 import { getSelectorsOptions } from 'app/store/createMemoizedSelector';
 import queryString from 'query-string';
@@ -111,6 +111,12 @@ export const vaeModelsAdapter = createEntityAdapter<VAEModelConfig, string>({
 });
 export const vaeModelsAdapterSelectors = vaeModelsAdapter.getSelectors(undefined, getSelectorsOptions);
 
+export const anyModelConfigAdapter = createEntityAdapter<AnyModelConfig, string>({
+  selectId: (entity) => entity.key,
+  sortComparer: (a, b) => a.name.localeCompare(b.name),
+});
+export const anyModelConfigAdapterSelectors = anyModelConfigAdapter.getSelectors(undefined, getSelectorsOptions);
+
 const buildProvidesTags =
   <TEntity extends AnyModelConfig>(tagType: (typeof tagTypes)[number]) =>
   (result: EntityState<TEntity, string> | undefined) => {
@@ -141,8 +147,6 @@ const buildTransformResponse =
  */
 const buildModelsUrl = (path: string = '') => buildV2Url(`models/${path}`);
 
-// TODO(psyche): Ideally we can share the cache between the `getXYZModels` queries and `getModelConfig` query
-
 export const modelsApi = api.injectEndpoints({
   endpoints: (build) => ({
     getMainModels: build.query<EntityState<MainModelConfig, string>, BaseModelType[]>({
@@ -157,6 +161,11 @@ export const modelsApi = api.injectEndpoints({
       },
       providesTags: buildProvidesTags<MainModelConfig>('MainModel'),
       transformResponse: buildTransformResponse<MainModelConfig>(mainModelsAdapter),
+      onQueryStarted: async (_, { dispatch, queryFulfilled }) => {
+        queryFulfilled.then(({ data }) => {
+          upsertModelConfigs(data, dispatch);
+        });
+      },
     }),
     getModelMetadata: build.query<GetModelMetadataResponse, string>({
       query: (key) => {
@@ -236,6 +245,7 @@ export const modelsApi = api.injectEndpoints({
 
         return tags;
       },
+      serializeQueryArgs: ({ queryArgs }) => `${queryArgs.name}.${queryArgs.base}.${queryArgs.type}`,
     }),
     syncModels: build.mutation<void, void>({
       query: () => {
@@ -250,31 +260,61 @@ export const modelsApi = api.injectEndpoints({
       query: () => ({ url: buildModelsUrl(), params: { model_type: 'lora' } }),
       providesTags: buildProvidesTags<LoRAModelConfig>('LoRAModel'),
       transformResponse: buildTransformResponse<LoRAModelConfig>(loraModelsAdapter),
+      onQueryStarted: async (_, { dispatch, queryFulfilled }) => {
+        queryFulfilled.then(({ data }) => {
+          upsertModelConfigs(data, dispatch);
+        });
+      },
     }),
     getControlNetModels: build.query<EntityState<ControlNetModelConfig, string>, void>({
       query: () => ({ url: buildModelsUrl(), params: { model_type: 'controlnet' } }),
       providesTags: buildProvidesTags<ControlNetModelConfig>('ControlNetModel'),
       transformResponse: buildTransformResponse<ControlNetModelConfig>(controlNetModelsAdapter),
+      onQueryStarted: async (_, { dispatch, queryFulfilled }) => {
+        queryFulfilled.then(({ data }) => {
+          upsertModelConfigs(data, dispatch);
+        });
+      },
     }),
     getIPAdapterModels: build.query<EntityState<IPAdapterModelConfig, string>, void>({
       query: () => ({ url: buildModelsUrl(), params: { model_type: 'ip_adapter' } }),
       providesTags: buildProvidesTags<IPAdapterModelConfig>('IPAdapterModel'),
       transformResponse: buildTransformResponse<IPAdapterModelConfig>(ipAdapterModelsAdapter),
+      onQueryStarted: async (_, { dispatch, queryFulfilled }) => {
+        queryFulfilled.then(({ data }) => {
+          upsertModelConfigs(data, dispatch);
+        });
+      },
     }),
     getT2IAdapterModels: build.query<EntityState<T2IAdapterModelConfig, string>, void>({
       query: () => ({ url: buildModelsUrl(), params: { model_type: 't2i_adapter' } }),
       providesTags: buildProvidesTags<T2IAdapterModelConfig>('T2IAdapterModel'),
       transformResponse: buildTransformResponse<T2IAdapterModelConfig>(t2iAdapterModelsAdapter),
+      onQueryStarted: async (_, { dispatch, queryFulfilled }) => {
+        queryFulfilled.then(({ data }) => {
+          upsertModelConfigs(data, dispatch);
+        });
+      },
     }),
     getVaeModels: build.query<EntityState<VAEModelConfig, string>, void>({
       query: () => ({ url: buildModelsUrl(), params: { model_type: 'vae' } }),
       providesTags: buildProvidesTags<VAEModelConfig>('VaeModel'),
       transformResponse: buildTransformResponse<VAEModelConfig>(vaeModelsAdapter),
+      onQueryStarted: async (_, { dispatch, queryFulfilled }) => {
+        queryFulfilled.then(({ data }) => {
+          upsertModelConfigs(data, dispatch);
+        });
+      },
     }),
     getTextualInversionModels: build.query<EntityState<TextualInversionModelConfig, string>, void>({
       query: () => ({ url: buildModelsUrl(), params: { model_type: 'embedding' } }),
       providesTags: buildProvidesTags<TextualInversionModelConfig>('TextualInversionModel'),
       transformResponse: buildTransformResponse<TextualInversionModelConfig>(textualInversionModelsAdapter),
+      onQueryStarted: async (_, { dispatch, queryFulfilled }) => {
+        queryFulfilled.then(({ data }) => {
+          upsertModelConfigs(data, dispatch);
+        });
+      },
     }),
     scanModels: build.query<ScanFolderResponse, ScanFolderArg>({
       query: (arg) => {
@@ -336,3 +376,15 @@ export const {
   useDeleteModelImportMutation,
   usePruneModelImportsMutation,
 } = modelsApi;
+
+const upsertModelConfigs = (
+  modelConfigs: EntityState<AnyModelConfig, string>,
+  // eslint-disable-next-line @typescript-eslint/no-explicit-any
+  dispatch: ThunkDispatch<any, any, UnknownAction>
+) => {
+  anyModelConfigAdapterSelectors.selectAll(modelConfigs).forEach((modelConfig) => {
+    dispatch(modelsApi.util.upsertQueryData('getModelConfig', modelConfig.key, modelConfig));
+    const { base, name, type } = modelConfig;
+    dispatch(modelsApi.util.upsertQueryData('getModelConfigByAttrs', { base, name, type }, modelConfig));
+  });
+};

From a253047d8e5b656bbe8c35460cf7bb48eea1cfd4 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 26 Feb 2024 13:40:52 +1100
Subject: [PATCH 325/411] tidy(ui): tidy model identifier logic

- Move some files around
- Use util to extract key and base from model config
---
 .../parameters/ParamControlAdapterModel.tsx   |  4 +-
 .../web/src/features/lora/store/loraSlice.ts  |  2 +-
 .../util/modelFetchingHelpers.ts              | 46 +------------------
 .../web/src/features/metadata/util/parsers.ts | 10 ++--
 .../src/features/metadata/util/validators.ts  |  2 +-
 .../ControlNetModelFieldInputComponent.tsx    |  3 +-
 .../IPAdapterModelFieldInputComponent.tsx     |  3 +-
 .../inputs/LoRAModelFieldInputComponent.tsx   |  3 +-
 .../T2IAdapterModelFieldInputComponent.tsx    |  3 +-
 .../inputs/VAEModelFieldInputComponent.tsx    |  3 +-
 .../VAEModel/ParamVAEModelSelect.tsx          |  6 +--
 .../util/modelIdToControlNetModelParam.ts     | 27 -----------
 .../util/modelIdToIPAdapterModelParams.ts     | 27 -----------
 .../util/modelIdToLoRAModelParam.ts           | 27 -----------
 .../util/modelIdToMainModelParam.ts           | 27 -----------
 .../util/modelIdToSDXLRefinerModelParam.ts    | 27 -----------
 .../util/modelIdToT2IAdapterModelParam.ts     | 27 -----------
 .../parameters/util/modelIdToVAEModelParam.ts | 26 -----------
 .../ParamSDXLRefinerModelSelect.tsx           |  4 +-
 19 files changed, 21 insertions(+), 256 deletions(-)
 rename invokeai/frontend/web/src/features/{parameters => metadata}/util/modelFetchingHelpers.ts (78%)
 delete mode 100644 invokeai/frontend/web/src/features/parameters/util/modelIdToControlNetModelParam.ts
 delete mode 100644 invokeai/frontend/web/src/features/parameters/util/modelIdToIPAdapterModelParams.ts
 delete mode 100644 invokeai/frontend/web/src/features/parameters/util/modelIdToLoRAModelParam.ts
 delete mode 100644 invokeai/frontend/web/src/features/parameters/util/modelIdToMainModelParam.ts
 delete mode 100644 invokeai/frontend/web/src/features/parameters/util/modelIdToSDXLRefinerModelParam.ts
 delete mode 100644 invokeai/frontend/web/src/features/parameters/util/modelIdToT2IAdapterModelParam.ts
 delete mode 100644 invokeai/frontend/web/src/features/parameters/util/modelIdToVAEModelParam.ts

diff --git a/invokeai/frontend/web/src/features/controlAdapters/components/parameters/ParamControlAdapterModel.tsx b/invokeai/frontend/web/src/features/controlAdapters/components/parameters/ParamControlAdapterModel.tsx
index 75372c350d..d7cf2e8452 100644
--- a/invokeai/frontend/web/src/features/controlAdapters/components/parameters/ParamControlAdapterModel.tsx
+++ b/invokeai/frontend/web/src/features/controlAdapters/components/parameters/ParamControlAdapterModel.tsx
@@ -6,7 +6,7 @@ import { useControlAdapterModel } from 'features/controlAdapters/hooks/useContro
 import { useControlAdapterModelQuery } from 'features/controlAdapters/hooks/useControlAdapterModelQuery';
 import { useControlAdapterType } from 'features/controlAdapters/hooks/useControlAdapterType';
 import { controlAdapterModelChanged } from 'features/controlAdapters/store/controlAdaptersSlice';
-import { pick } from 'lodash-es';
+import { getModelKeyAndBase } from 'features/metadata/util/modelFetchingHelpers';
 import { memo, useCallback, useMemo } from 'react';
 import type { ControlNetModelConfig, IPAdapterModelConfig, T2IAdapterModelConfig } from 'services/api/types';
 
@@ -31,7 +31,7 @@ const ParamControlAdapterModel = ({ id }: ParamControlAdapterModelProps) => {
       dispatch(
         controlAdapterModelChanged({
           id,
-          model: pick(model, 'base', 'key'),
+          model: getModelKeyAndBase(model),
         })
       );
     },
diff --git a/invokeai/frontend/web/src/features/lora/store/loraSlice.ts b/invokeai/frontend/web/src/features/lora/store/loraSlice.ts
index 32bef5fd9b..83f2f2312a 100644
--- a/invokeai/frontend/web/src/features/lora/store/loraSlice.ts
+++ b/invokeai/frontend/web/src/features/lora/store/loraSlice.ts
@@ -1,8 +1,8 @@
 import type { PayloadAction } from '@reduxjs/toolkit';
 import { createSlice } from '@reduxjs/toolkit';
 import type { PersistConfig, RootState } from 'app/store/store';
+import { getModelKeyAndBase } from 'features/metadata/util/modelFetchingHelpers';
 import type { ParameterLoRAModel } from 'features/parameters/types/parameterSchemas';
-import { getModelKeyAndBase } from 'features/parameters/util/modelFetchingHelpers';
 import type { LoRAModelConfig } from 'services/api/types';
 
 export type LoRA = {
diff --git a/invokeai/frontend/web/src/features/parameters/util/modelFetchingHelpers.ts b/invokeai/frontend/web/src/features/metadata/util/modelFetchingHelpers.ts
similarity index 78%
rename from invokeai/frontend/web/src/features/parameters/util/modelFetchingHelpers.ts
rename to invokeai/frontend/web/src/features/metadata/util/modelFetchingHelpers.ts
index bd3e42a314..9bc43587cc 100644
--- a/invokeai/frontend/web/src/features/parameters/util/modelFetchingHelpers.ts
+++ b/invokeai/frontend/web/src/features/metadata/util/modelFetchingHelpers.ts
@@ -3,16 +3,8 @@ import type { ModelIdentifierWithBase } from 'features/nodes/types/common';
 import { isModelIdentifier, isModelIdentifierV2 } from 'features/nodes/types/common';
 import { modelsApi } from 'services/api/endpoints/models';
 import type { AnyModelConfig, BaseModelType, ModelType } from 'services/api/types';
-import {
-  isControlNetModelConfig,
-  isIPAdapterModelConfig,
-  isLoRAModelConfig,
-  isNonRefinerMainModelConfig,
-  isRefinerMainModelModelConfig,
-  isT2IAdapterModelConfig,
-  isTextualInversionModelConfig,
-  isVAEModelConfig,
-} from 'services/api/types';
+
+
 
 /**
  * Raised when a model config is unable to be fetched.
@@ -101,40 +93,6 @@ export const fetchModelConfigWithTypeGuard = async <T extends AnyModelConfig>(
   return modelConfig;
 };
 
-// TODO(psyche): Remove these helpers once `useRecallParameters` is removed
-
-export const fetchMainModelConfig = async (key: string) => {
-  return fetchModelConfigWithTypeGuard(key, isNonRefinerMainModelConfig);
-};
-
-export const fetchRefinerModelConfig = async (key: string) => {
-  return fetchModelConfigWithTypeGuard(key, isRefinerMainModelModelConfig);
-};
-
-export const fetchVAEModelConfig = async (key: string) => {
-  return fetchModelConfigWithTypeGuard(key, isVAEModelConfig);
-};
-
-export const fetchLoRAModel = async (key: string) => {
-  return fetchModelConfigWithTypeGuard(key, isLoRAModelConfig);
-};
-
-export const fetchControlNetModel = async (key: string) => {
-  return fetchModelConfigWithTypeGuard(key, isControlNetModelConfig);
-};
-
-export const fetchIPAdapterModel = async (key: string) => {
-  return fetchModelConfigWithTypeGuard(key, isIPAdapterModelConfig);
-};
-
-export const fetchT2IAdapterModel = async (key: string) => {
-  return fetchModelConfigWithTypeGuard(key, isT2IAdapterModelConfig);
-};
-
-export const fetchTextualInversionModel = async (key: string) => {
-  return fetchModelConfigWithTypeGuard(key, isTextualInversionModelConfig);
-};
-
 /**
  * Raises an error if the source base model is incompatible with the target base model.
  * @param sourceBase The source base model.
diff --git a/invokeai/frontend/web/src/features/metadata/util/parsers.ts b/invokeai/frontend/web/src/features/metadata/util/parsers.ts
index c7f2a6d09f..df0485a0c4 100644
--- a/invokeai/frontend/web/src/features/metadata/util/parsers.ts
+++ b/invokeai/frontend/web/src/features/metadata/util/parsers.ts
@@ -9,6 +9,11 @@ import type { LoRA } from 'features/lora/store/loraSlice';
 import { defaultLoRAConfig } from 'features/lora/store/loraSlice';
 import { MetadataParseError } from 'features/metadata/exceptions';
 import type { MetadataParseFunc } from 'features/metadata/types';
+import {
+  fetchModelConfigWithTypeGuard,
+  getModelKey,
+  getModelKeyAndBase,
+} from 'features/metadata/util/modelFetchingHelpers';
 import {
   zControlField,
   zIPAdapterField,
@@ -54,11 +59,6 @@ import {
   isParameterStrength,
   isParameterWidth,
 } from 'features/parameters/types/parameterSchemas';
-import {
-  fetchModelConfigWithTypeGuard,
-  getModelKey,
-  getModelKeyAndBase,
-} from 'features/parameters/util/modelFetchingHelpers';
 import { get, isArray, isString } from 'lodash-es';
 import type { NonRefinerMainModelConfig, RefinerMainModelConfig, VAEModelConfig } from 'services/api/types';
 import {
diff --git a/invokeai/frontend/web/src/features/metadata/util/validators.ts b/invokeai/frontend/web/src/features/metadata/util/validators.ts
index e627afeda3..1f34e38651 100644
--- a/invokeai/frontend/web/src/features/metadata/util/validators.ts
+++ b/invokeai/frontend/web/src/features/metadata/util/validators.ts
@@ -2,7 +2,7 @@ import { getStore } from 'app/store/nanostores/store';
 import type { ControlNetConfig, IPAdapterConfig, T2IAdapterConfig } from 'features/controlAdapters/store/types';
 import type { LoRA } from 'features/lora/store/loraSlice';
 import type { MetadataValidateFunc } from 'features/metadata/types';
-import { InvalidModelConfigError } from 'features/parameters/util/modelFetchingHelpers';
+import { InvalidModelConfigError } from 'features/metadata/util/modelFetchingHelpers';
 import type { BaseModelType, RefinerMainModelConfig, VAEModelConfig } from 'services/api/types';
 
 /**
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/ControlNetModelFieldInputComponent.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/ControlNetModelFieldInputComponent.tsx
index 29a1f93dd5..367b32030d 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/ControlNetModelFieldInputComponent.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/ControlNetModelFieldInputComponent.tsx
@@ -3,7 +3,6 @@ import { useAppDispatch } from 'app/store/storeHooks';
 import { useGroupedModelCombobox } from 'common/hooks/useGroupedModelCombobox';
 import { fieldControlNetModelValueChanged } from 'features/nodes/store/nodesSlice';
 import type { ControlNetModelFieldInputInstance, ControlNetModelFieldInputTemplate } from 'features/nodes/types/field';
-import { pick } from 'lodash-es';
 import { memo, useCallback } from 'react';
 import { useGetControlNetModelsQuery } from 'services/api/endpoints/models';
 import type { ControlNetModelConfig } from 'services/api/types';
@@ -36,7 +35,7 @@ const ControlNetModelFieldInputComponent = (props: Props) => {
   const { options, value, onChange, placeholder, noOptionsMessage } = useGroupedModelCombobox({
     modelEntities: data,
     onChange: _onChange,
-    selectedModel: field.value ? pick(field.value, ['key', 'base']) : undefined,
+    selectedModel: field.value,
     isLoading,
   });
 
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/IPAdapterModelFieldInputComponent.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/IPAdapterModelFieldInputComponent.tsx
index d4f0ae3de1..62ce9d65a2 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/IPAdapterModelFieldInputComponent.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/IPAdapterModelFieldInputComponent.tsx
@@ -3,7 +3,6 @@ import { useAppDispatch } from 'app/store/storeHooks';
 import { useGroupedModelCombobox } from 'common/hooks/useGroupedModelCombobox';
 import { fieldIPAdapterModelValueChanged } from 'features/nodes/store/nodesSlice';
 import type { IPAdapterModelFieldInputInstance, IPAdapterModelFieldInputTemplate } from 'features/nodes/types/field';
-import { pick } from 'lodash-es';
 import { memo, useCallback } from 'react';
 import { useGetIPAdapterModelsQuery } from 'services/api/endpoints/models';
 import type { IPAdapterModelConfig } from 'services/api/types';
@@ -36,7 +35,7 @@ const IPAdapterModelFieldInputComponent = (
   const { options, value, onChange } = useGroupedModelCombobox({
     modelEntities: ipAdapterModels,
     onChange: _onChange,
-    selectedModel: field.value ? pick(field.value, ['key', 'base']) : undefined,
+    selectedModel: field.value,
   });
 
   return (
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/LoRAModelFieldInputComponent.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/LoRAModelFieldInputComponent.tsx
index 9fd223e694..9caadfc451 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/LoRAModelFieldInputComponent.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/LoRAModelFieldInputComponent.tsx
@@ -3,7 +3,6 @@ import { useAppDispatch } from 'app/store/storeHooks';
 import { useGroupedModelCombobox } from 'common/hooks/useGroupedModelCombobox';
 import { fieldLoRAModelValueChanged } from 'features/nodes/store/nodesSlice';
 import type { LoRAModelFieldInputInstance, LoRAModelFieldInputTemplate } from 'features/nodes/types/field';
-import { pick } from 'lodash-es';
 import { memo, useCallback } from 'react';
 import { useGetLoRAModelsQuery } from 'services/api/endpoints/models';
 import type { LoRAModelConfig } from 'services/api/types';
@@ -35,7 +34,7 @@ const LoRAModelFieldInputComponent = (props: Props) => {
   const { options, value, onChange, placeholder, noOptionsMessage } = useGroupedModelCombobox({
     modelEntities: data,
     onChange: _onChange,
-    selectedModel: field.value ? pick(field.value, ['key', 'base']) : undefined,
+    selectedModel: field.value,
     isLoading,
   });
 
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/T2IAdapterModelFieldInputComponent.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/T2IAdapterModelFieldInputComponent.tsx
index a38356a0b8..9a374f1fd0 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/T2IAdapterModelFieldInputComponent.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/T2IAdapterModelFieldInputComponent.tsx
@@ -3,7 +3,6 @@ import { useAppDispatch } from 'app/store/storeHooks';
 import { useGroupedModelCombobox } from 'common/hooks/useGroupedModelCombobox';
 import { fieldT2IAdapterModelValueChanged } from 'features/nodes/store/nodesSlice';
 import type { T2IAdapterModelFieldInputInstance, T2IAdapterModelFieldInputTemplate } from 'features/nodes/types/field';
-import { pick } from 'lodash-es';
 import { memo, useCallback } from 'react';
 import { useGetT2IAdapterModelsQuery } from 'services/api/endpoints/models';
 import type { T2IAdapterModelConfig } from 'services/api/types';
@@ -37,7 +36,7 @@ const T2IAdapterModelFieldInputComponent = (
   const { options, value, onChange } = useGroupedModelCombobox({
     modelEntities: t2iAdapterModels,
     onChange: _onChange,
-    selectedModel: field.value ? pick(field.value, ['key', 'base']) : undefined,
+    selectedModel: field.value,
   });
 
   return (
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/VAEModelFieldInputComponent.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/VAEModelFieldInputComponent.tsx
index 23ead6c543..c1259486e6 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/VAEModelFieldInputComponent.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/VAEModelFieldInputComponent.tsx
@@ -4,7 +4,6 @@ import { useGroupedModelCombobox } from 'common/hooks/useGroupedModelCombobox';
 import { SyncModelsIconButton } from 'features/modelManagerV2/components/SyncModels/SyncModelsIconButton';
 import { fieldVaeModelValueChanged } from 'features/nodes/store/nodesSlice';
 import type { VAEModelFieldInputInstance, VAEModelFieldInputTemplate } from 'features/nodes/types/field';
-import { pick } from 'lodash-es';
 import { memo, useCallback } from 'react';
 import { useGetVaeModelsQuery } from 'services/api/endpoints/models';
 import type { VAEModelConfig } from 'services/api/types';
@@ -35,7 +34,7 @@ const VAEModelFieldInputComponent = (props: Props) => {
   const { options, value, onChange, placeholder, noOptionsMessage } = useGroupedModelCombobox({
     modelEntities: data,
     onChange: _onChange,
-    selectedModel: field.value ? pick(field.value, ['key', 'base']) : null,
+    selectedModel: field.value,
     isLoading,
   });
 
diff --git a/invokeai/frontend/web/src/features/parameters/components/VAEModel/ParamVAEModelSelect.tsx b/invokeai/frontend/web/src/features/parameters/components/VAEModel/ParamVAEModelSelect.tsx
index 4a630fa9ce..7a9a430286 100644
--- a/invokeai/frontend/web/src/features/parameters/components/VAEModel/ParamVAEModelSelect.tsx
+++ b/invokeai/frontend/web/src/features/parameters/components/VAEModel/ParamVAEModelSelect.tsx
@@ -3,8 +3,8 @@ import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { useGroupedModelCombobox } from 'common/hooks/useGroupedModelCombobox';
+import { getModelKeyAndBase } from 'features/metadata/util/modelFetchingHelpers';
 import { selectGenerationSlice, vaeSelected } from 'features/parameters/store/generationSlice';
-import { pick } from 'lodash-es';
 import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 import { useGetVaeModelsQuery } from 'services/api/endpoints/models';
@@ -30,14 +30,14 @@ const ParamVAEModelSelect = () => {
   );
   const _onChange = useCallback(
     (vae: VAEModelConfig | null) => {
-      dispatch(vaeSelected(vae ? pick(vae, 'key', 'base') : null));
+      dispatch(vaeSelected(vae ? getModelKeyAndBase(vae) : null));
     },
     [dispatch]
   );
   const { options, value, onChange, noOptionsMessage } = useGroupedModelCombobox({
     modelEntities: data,
     onChange: _onChange,
-    selectedModel: vae ? pick(vae, 'key', 'base') : null,
+    selectedModel: vae,
     isLoading,
     getIsDisabled,
   });
diff --git a/invokeai/frontend/web/src/features/parameters/util/modelIdToControlNetModelParam.ts b/invokeai/frontend/web/src/features/parameters/util/modelIdToControlNetModelParam.ts
deleted file mode 100644
index f98a1bd579..0000000000
--- a/invokeai/frontend/web/src/features/parameters/util/modelIdToControlNetModelParam.ts
+++ /dev/null
@@ -1,27 +0,0 @@
-import { logger } from 'app/logging/logger';
-import { zParameterControlNetModel } from 'features/parameters/types/parameterSchemas';
-import type { ControlNetModelField } from 'services/api/types';
-
-export const modelIdToControlNetModelParam = (controlNetModelId: string): ControlNetModelField | undefined => {
-  const log = logger('models');
-  const [base_model, _model_type, model_name] = controlNetModelId.split('/');
-
-  const result = zParameterControlNetModel.safeParse({
-    base_model,
-    model_name,
-  });
-
-  if (!result.success) {
-    log.error(
-      {
-        controlNetModelId,
-        errors: result.error.format(),
-      },
-      'Failed to parse ControlNet model id'
-    );
-
-    return;
-  }
-
-  return result.data;
-};
diff --git a/invokeai/frontend/web/src/features/parameters/util/modelIdToIPAdapterModelParams.ts b/invokeai/frontend/web/src/features/parameters/util/modelIdToIPAdapterModelParams.ts
deleted file mode 100644
index f3143b6421..0000000000
--- a/invokeai/frontend/web/src/features/parameters/util/modelIdToIPAdapterModelParams.ts
+++ /dev/null
@@ -1,27 +0,0 @@
-import { logger } from 'app/logging/logger';
-import { zParameterIPAdapterModel } from 'features/parameters/types/parameterSchemas';
-import type { IPAdapterModelField } from 'services/api/types';
-
-export const modelIdToIPAdapterModelParam = (ipAdapterModelId: string): IPAdapterModelField | undefined => {
-  const log = logger('models');
-  const [base_model, _model_type, model_name] = ipAdapterModelId.split('/');
-
-  const result = zParameterIPAdapterModel.safeParse({
-    base_model,
-    model_name,
-  });
-
-  if (!result.success) {
-    log.error(
-      {
-        ipAdapterModelId,
-        errors: result.error.format(),
-      },
-      'Failed to parse IP-Adapter model id'
-    );
-
-    return;
-  }
-
-  return result.data;
-};
diff --git a/invokeai/frontend/web/src/features/parameters/util/modelIdToLoRAModelParam.ts b/invokeai/frontend/web/src/features/parameters/util/modelIdToLoRAModelParam.ts
deleted file mode 100644
index 16cdaae5de..0000000000
--- a/invokeai/frontend/web/src/features/parameters/util/modelIdToLoRAModelParam.ts
+++ /dev/null
@@ -1,27 +0,0 @@
-import { logger } from 'app/logging/logger';
-import type { ParameterLoRAModel } from 'features/parameters/types/parameterSchemas';
-import { zParameterLoRAModel } from 'features/parameters/types/parameterSchemas';
-
-export const modelIdToLoRAModelParam = (loraModelId: string): ParameterLoRAModel | undefined => {
-  const log = logger('models');
-
-  const [base_model, _model_type, model_name] = loraModelId.split('/');
-
-  const result = zParameterLoRAModel.safeParse({
-    base_model,
-    model_name,
-  });
-
-  if (!result.success) {
-    log.error(
-      {
-        loraModelId,
-        errors: result.error.format(),
-      },
-      'Failed to parse LoRA model id'
-    );
-    return;
-  }
-
-  return result.data;
-};
diff --git a/invokeai/frontend/web/src/features/parameters/util/modelIdToMainModelParam.ts b/invokeai/frontend/web/src/features/parameters/util/modelIdToMainModelParam.ts
deleted file mode 100644
index 4fe7c8e4ac..0000000000
--- a/invokeai/frontend/web/src/features/parameters/util/modelIdToMainModelParam.ts
+++ /dev/null
@@ -1,27 +0,0 @@
-import { logger } from 'app/logging/logger';
-import type { ParameterModel } from 'features/parameters/types/parameterSchemas';
-import { zParameterModel } from 'features/parameters/types/parameterSchemas';
-
-export const modelIdToMainModelParam = (mainModelId: string): ParameterModel | undefined => {
-  const log = logger('models');
-  const [base_model, model_type, model_name] = mainModelId.split('/');
-
-  const result = zParameterModel.safeParse({
-    base_model,
-    model_name,
-    model_type,
-  });
-
-  if (!result.success) {
-    log.error(
-      {
-        mainModelId,
-        errors: result.error.format(),
-      },
-      'Failed to parse main model id'
-    );
-    return;
-  }
-
-  return result.data;
-};
diff --git a/invokeai/frontend/web/src/features/parameters/util/modelIdToSDXLRefinerModelParam.ts b/invokeai/frontend/web/src/features/parameters/util/modelIdToSDXLRefinerModelParam.ts
deleted file mode 100644
index aec3018ac8..0000000000
--- a/invokeai/frontend/web/src/features/parameters/util/modelIdToSDXLRefinerModelParam.ts
+++ /dev/null
@@ -1,27 +0,0 @@
-import { logger } from 'app/logging/logger';
-import type { ParameterSDXLRefinerModel } from 'features/parameters/types/parameterSchemas';
-import { zParameterSDXLRefinerModel } from 'features/parameters/types/parameterSchemas';
-
-export const modelIdToSDXLRefinerModelParam = (mainModelId: string): ParameterSDXLRefinerModel | undefined => {
-  const log = logger('models');
-  const [base_model, model_type, model_name] = mainModelId.split('/');
-
-  const result = zParameterSDXLRefinerModel.safeParse({
-    base_model,
-    model_name,
-    model_type,
-  });
-
-  if (!result.success) {
-    log.error(
-      {
-        mainModelId,
-        errors: result.error.format(),
-      },
-      'Failed to parse main model id'
-    );
-    return;
-  }
-
-  return result.data;
-};
diff --git a/invokeai/frontend/web/src/features/parameters/util/modelIdToT2IAdapterModelParam.ts b/invokeai/frontend/web/src/features/parameters/util/modelIdToT2IAdapterModelParam.ts
deleted file mode 100644
index 23097aee0b..0000000000
--- a/invokeai/frontend/web/src/features/parameters/util/modelIdToT2IAdapterModelParam.ts
+++ /dev/null
@@ -1,27 +0,0 @@
-import { logger } from 'app/logging/logger';
-import { zParameterT2IAdapterModel } from 'features/parameters/types/parameterSchemas';
-import type { T2IAdapterModelField } from 'services/api/types';
-
-export const modelIdToT2IAdapterModelParam = (t2iAdapterModelId: string): T2IAdapterModelField | undefined => {
-  const log = logger('models');
-  const [base_model, _model_type, model_name] = t2iAdapterModelId.split('/');
-
-  const result = zParameterT2IAdapterModel.safeParse({
-    base_model,
-    model_name,
-  });
-
-  if (!result.success) {
-    log.error(
-      {
-        t2iAdapterModelId,
-        errors: result.error.format(),
-      },
-      'Failed to parse T2I-Adapter model id'
-    );
-
-    return;
-  }
-
-  return result.data;
-};
diff --git a/invokeai/frontend/web/src/features/parameters/util/modelIdToVAEModelParam.ts b/invokeai/frontend/web/src/features/parameters/util/modelIdToVAEModelParam.ts
deleted file mode 100644
index 90d74a2f80..0000000000
--- a/invokeai/frontend/web/src/features/parameters/util/modelIdToVAEModelParam.ts
+++ /dev/null
@@ -1,26 +0,0 @@
-import { logger } from 'app/logging/logger';
-import type { ParameterVAEModel } from 'features/parameters/types/parameterSchemas';
-import { zParameterVAEModel } from 'features/parameters/types/parameterSchemas';
-
-export const modelIdToVAEModelParam = (vaeModelId: string): ParameterVAEModel | undefined => {
-  const log = logger('models');
-  const [base_model, _model_type, model_name] = vaeModelId.split('/');
-
-  const result = zParameterVAEModel.safeParse({
-    base_model,
-    model_name,
-  });
-
-  if (!result.success) {
-    log.error(
-      {
-        vaeModelId,
-        errors: result.error.format(),
-      },
-      'Failed to parse VAE model id'
-    );
-    return;
-  }
-
-  return result.data;
-};
diff --git a/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerModelSelect.tsx b/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerModelSelect.tsx
index e5978ca21b..e3dde06d72 100644
--- a/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerModelSelect.tsx
+++ b/invokeai/frontend/web/src/features/sdxl/components/SDXLRefiner/ParamSDXLRefinerModelSelect.tsx
@@ -3,8 +3,8 @@ import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { useModelCombobox } from 'common/hooks/useModelCombobox';
+import { getModelKeyAndBase } from 'features/metadata/util/modelFetchingHelpers';
 import { refinerModelChanged, selectSdxlSlice } from 'features/sdxl/store/sdxlSlice';
-import { pick } from 'lodash-es';
 import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 import { REFINER_BASE_MODELS } from 'services/api/constants';
@@ -26,7 +26,7 @@ const ParamSDXLRefinerModelSelect = () => {
         dispatch(refinerModelChanged(null));
         return;
       }
-      dispatch(refinerModelChanged(pick(model, ['key', 'base'])));
+      dispatch(refinerModelChanged(getModelKeyAndBase(model)));
     },
     [dispatch]
   );

From 80697a71de7668457b714dee1ea344148a60d525 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 26 Feb 2024 22:25:22 +1100
Subject: [PATCH 326/411] feat(nodes): update LoRAMetadataItem model

LoRA model now at under `model` not `lora.
---
 invokeai/app/invocations/metadata.py          |  4 +-
 .../web/src/features/nodes/types/metadata.ts  | 42 -------------------
 .../nodes/util/graph/addLoRAsToGraph.ts       |  2 +-
 .../nodes/util/graph/addSDXLLoRAstoGraph.ts   | 13 ++----
 .../frontend/web/src/services/api/schema.ts   |  6 +--
 5 files changed, 9 insertions(+), 58 deletions(-)

diff --git a/invokeai/app/invocations/metadata.py b/invokeai/app/invocations/metadata.py
index 58edfab711..bec1b0d9d5 100644
--- a/invokeai/app/invocations/metadata.py
+++ b/invokeai/app/invocations/metadata.py
@@ -33,7 +33,7 @@ class MetadataItemField(BaseModel):
 class LoRAMetadataField(BaseModel):
     """LoRA Metadata Field"""
 
-    lora: LoRAModelField = Field(description=FieldDescriptions.lora_model)
+    model: LoRAModelField = Field(description=FieldDescriptions.lora_model)
     weight: float = Field(description=FieldDescriptions.lora_weight)
 
 
@@ -114,7 +114,7 @@ GENERATION_MODES = Literal[
 ]
 
 
-@invocation("core_metadata", title="Core Metadata", tags=["metadata"], category="metadata", version="1.0.1")
+@invocation("core_metadata", title="Core Metadata", tags=["metadata"], category="metadata", version="1.1.1")
 class CoreMetadataInvocation(BaseInvocation):
     """Collects core generation metadata into a MetadataField"""
 
diff --git a/invokeai/frontend/web/src/features/nodes/types/metadata.ts b/invokeai/frontend/web/src/features/nodes/types/metadata.ts
index 132f9f781a..3a87e96da3 100644
--- a/invokeai/frontend/web/src/features/nodes/types/metadata.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/metadata.ts
@@ -26,45 +26,3 @@ export type ModelMetadataItem = z.infer<typeof zModelMetadataItem>;
 export type VAEModelMetadataItem = z.infer<typeof zVAEModelMetadataItem>;
 // #endregion
 
-// #region CoreMetadata
-export const zCoreMetadata = z
-  .object({
-    app_version: z.string().nullish().catch(null),
-    generation_mode: z.string().nullish().catch(null),
-    created_by: z.string().nullish().catch(null),
-    positive_prompt: z.string().nullish().catch(null),
-    negative_prompt: z.string().nullish().catch(null),
-    width: z.number().int().nullish().catch(null),
-    height: z.number().int().nullish().catch(null),
-    seed: z.number().int().nullish().catch(null),
-    rand_device: z.string().nullish().catch(null),
-    cfg_scale: z.number().nullish().catch(null),
-    cfg_rescale_multiplier: z.number().nullish().catch(null),
-    steps: z.number().int().nullish().catch(null),
-    scheduler: z.string().nullish().catch(null),
-    clip_skip: z.number().int().nullish().catch(null),
-    model: zModelMetadataItem.nullish().catch(null),
-    controlnets: z.array(zControlNetMetadataItem).nullish().catch(null),
-    ipAdapters: z.array(zIPAdapterMetadataItem).nullish().catch(null),
-    t2iAdapters: z.array(zT2IAdapterMetadataItem).nullish().catch(null),
-    loras: z.array(zLoRAMetadataItem).nullish().catch(null),
-    vae: zVAEModelMetadataItem.nullish().catch(null),
-    strength: z.number().nullish().catch(null),
-    hrf_enabled: z.boolean().nullish().catch(null),
-    hrf_strength: z.number().nullish().catch(null),
-    hrf_method: z.string().nullish().catch(null),
-    init_image: z.string().nullish().catch(null),
-    positive_style_prompt: z.string().nullish().catch(null),
-    negative_style_prompt: z.string().nullish().catch(null),
-    refiner_model: zSDXLRefinerModelMetadataItem.nullish().catch(null),
-    refiner_cfg_scale: z.number().nullish().catch(null),
-    refiner_steps: z.number().int().nullish().catch(null),
-    refiner_scheduler: z.string().nullish().catch(null),
-    refiner_positive_aesthetic_score: z.number().nullish().catch(null),
-    refiner_negative_aesthetic_score: z.number().nullish().catch(null),
-    refiner_start: z.number().nullish().catch(null),
-  })
-  .passthrough();
-export type CoreMetadata = z.infer<typeof zCoreMetadata>;
-
-// #endregion
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/addLoRAsToGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/addLoRAsToGraph.ts
index 5c47cf5c58..c49a0e19e3 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/addLoRAsToGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/addLoRAsToGraph.ts
@@ -53,7 +53,7 @@ export const addLoRAsToGraph = (
     };
 
     loraMetadata.push({
-      lora: { key },
+      model: { key },
       weight,
     });
 
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/addSDXLLoRAstoGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/addSDXLLoRAstoGraph.ts
index 54d1e2116d..36223391fe 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/addSDXLLoRAstoGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/addSDXLLoRAstoGraph.ts
@@ -1,8 +1,6 @@
 import type { RootState } from 'app/store/store';
-import type { LoRAMetadataItem } from 'features/nodes/types/metadata';
-import { zLoRAMetadataItem } from 'features/nodes/types/metadata';
 import { filter, size } from 'lodash-es';
-import type { NonNullableGraph, SDXLLoraLoaderInvocation } from 'services/api/types';
+import type { CoreMetadataInvocation, NonNullableGraph, SDXLLoraLoaderInvocation } from 'services/api/types';
 
 import {
   LORA_LOADER,
@@ -36,7 +34,7 @@ export const addSDXLLoRAsToGraph = (
     return;
   }
 
-  const loraMetadata: LoRAMetadataItem[] = [];
+  const loraMetadata: CoreMetadataInvocation['loras'] = [];
 
   // Handle Seamless Plugs
   const unetLoaderId = modelLoaderNodeId;
@@ -70,12 +68,7 @@ export const addSDXLLoRAsToGraph = (
       weight,
     };
 
-    loraMetadata.push(
-      zLoRAMetadataItem.parse({
-        lora: { key },
-        weight,
-      })
-    );
+    loraMetadata.push({ model: { key }, weight });
 
     // add to graph
     graph.nodes[currentLoraNodeId] = loraLoaderNode;
diff --git a/invokeai/frontend/web/src/services/api/schema.ts b/invokeai/frontend/web/src/services/api/schema.ts
index beb13e4070..1d347ad222 100644
--- a/invokeai/frontend/web/src/services/api/schema.ts
+++ b/invokeai/frontend/web/src/services/api/schema.ts
@@ -4339,7 +4339,7 @@ export type components = {
        * @description The nodes in this graph
        */
       nodes: {
-        [key: string]: components["schemas"]["RandomRangeInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["CanvasPasteBackInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["ColorMapImageProcessorInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["CreateGradientMaskInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["DWOpenposeImageProcessorInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["DepthAnythingImageProcessorInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["ImageInverseLerpInvocation"];
+        [key: string]: components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["DepthAnythingImageProcessorInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["CanvasPasteBackInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["CreateGradientMaskInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["ColorMapImageProcessorInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["DWOpenposeImageProcessorInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["StringCollectionInvocation"];
       };
       /**
        * Edges
@@ -4376,7 +4376,7 @@ export type components = {
        * @description The results of node executions
        */
       results: {
-        [key: string]: components["schemas"]["VAEOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["String2Output"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["LatentsOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["SDXLLoraLoaderOutput"] | components["schemas"]["MetadataOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["ClipSkipInvocationOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["LoraLoaderOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["FloatOutput"];
+        [key: string]: components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["String2Output"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["MetadataOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["LatentsOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["ClipSkipInvocationOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["LoraLoaderOutput"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["SDXLLoraLoaderOutput"] | components["schemas"]["VAEOutput"] | components["schemas"]["IPAdapterOutput"];
       };
       /**
        * Errors
@@ -6675,7 +6675,7 @@ export type components = {
      */
     LoRAMetadataField: {
       /** @description LoRA model to load */
-      lora: components["schemas"]["LoRAModelField"];
+      model: components["schemas"]["LoRAModelField"];
       /**
        * Weight
        * @description The weight at which the LoRA is applied to each model

From 6c5be9e89c5c7decb4240422142d9753d1ae69ee Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 26 Feb 2024 22:26:25 +1100
Subject: [PATCH 327/411] tidy(ui): remove unused metadata schemas

---
 .../web/src/features/nodes/types/metadata.ts  |  28 ---
 invokeai/frontend/web/tests/metadata.ts       | 174 ------------------
 2 files changed, 202 deletions(-)
 delete mode 100644 invokeai/frontend/web/src/features/nodes/types/metadata.ts
 delete mode 100644 invokeai/frontend/web/tests/metadata.ts

diff --git a/invokeai/frontend/web/src/features/nodes/types/metadata.ts b/invokeai/frontend/web/src/features/nodes/types/metadata.ts
deleted file mode 100644
index 3a87e96da3..0000000000
--- a/invokeai/frontend/web/src/features/nodes/types/metadata.ts
+++ /dev/null
@@ -1,28 +0,0 @@
-import { z } from 'zod';
-
-import { zControlField, zIPAdapterField, zModelFieldBase, zT2IAdapterField } from './common';
-
-export const zLoRAWeight = z.number().nullish();
-// #region Metadata-optimized versions of schemas
-// TODO: It's possible that `deepPartial` will be deprecated:
-// - https://github.com/colinhacks/zod/issues/2106
-// - https://github.com/colinhacks/zod/issues/2854
-export const zLoRAMetadataItem = z.object({
-  lora: zModelFieldBase.deepPartial(),
-  weight: zLoRAWeight,
-});
-const zControlNetMetadataItem = zControlField.merge(z.object({ control_model: z.unknown() })).deepPartial();
-const zIPAdapterMetadataItem = zIPAdapterField.merge(z.object({ ip_adapter_model: z.unknown() })).deepPartial();
-const zT2IAdapterMetadataItem = zT2IAdapterField.merge(z.object({ t2i_adapter_model: z.unknown() })).deepPartial();
-const zSDXLRefinerModelMetadataItem = z.unknown();
-const zModelMetadataItem = z.unknown();
-const zVAEModelMetadataItem = z.unknown();
-export type LoRAMetadataItem = z.infer<typeof zLoRAMetadataItem>;
-export type ControlNetMetadataItem = z.infer<typeof zControlNetMetadataItem>;
-export type IPAdapterMetadataItem = z.infer<typeof zIPAdapterMetadataItem>;
-export type T2IAdapterMetadataItem = z.infer<typeof zT2IAdapterMetadataItem>;
-export type SDXLRefinerModelMetadataItem = z.infer<typeof zSDXLRefinerModelMetadataItem>;
-export type ModelMetadataItem = z.infer<typeof zModelMetadataItem>;
-export type VAEModelMetadataItem = z.infer<typeof zVAEModelMetadataItem>;
-// #endregion
-
diff --git a/invokeai/frontend/web/tests/metadata.ts b/invokeai/frontend/web/tests/metadata.ts
deleted file mode 100644
index c694ce67c7..0000000000
--- a/invokeai/frontend/web/tests/metadata.ts
+++ /dev/null
@@ -1,174 +0,0 @@
-export default {};
-
-// python metadata parsing tests to rebuild
-
-// # def test_is_good_metadata_unchanged():
-// #     parsed_metadata = metadata_service._parse_invokeai_metadata(valid_metadata)
-
-// #     expected = deepcopy(valid_metadata)
-
-// #     assert expected == parsed_metadata
-
-// # def test_can_parse_missing_session_id():
-// #     metadata_missing_session_id = deepcopy(valid_metadata)
-// #     del metadata_missing_session_id["session_id"]
-
-// #     expected = deepcopy(valid_metadata)
-// #     del expected["session_id"]
-
-// #     parsed_metadata = metadata_service._parse_invokeai_metadata(
-// #         metadata_missing_session_id
-// #     )
-// #     assert metadata_missing_session_id == parsed_metadata
-
-// # def test_can_parse_invalid_session_id():
-// #     metadata_invalid_session_id = deepcopy(valid_metadata)
-// #     metadata_invalid_session_id["session_id"] = 123
-
-// #     expected = deepcopy(valid_metadata)
-// #     del expected["session_id"]
-
-// #     parsed_metadata = metadata_service._parse_invokeai_metadata(
-// #         metadata_invalid_session_id
-// #     )
-// #     assert expected == parsed_metadata
-
-// # def test_can_parse_missing_node():
-// #     metadata_missing_node = deepcopy(valid_metadata)
-// #     del metadata_missing_node["node"]
-
-// #     expected = deepcopy(valid_metadata)
-// #     del expected["node"]
-
-// #     parsed_metadata = metadata_service._parse_invokeai_metadata(metadata_missing_node)
-// #     assert expected == parsed_metadata
-
-// # def test_can_parse_invalid_node():
-// #     metadata_invalid_node = deepcopy(valid_metadata)
-// #     metadata_invalid_node["node"] = 123
-
-// #     expected = deepcopy(valid_metadata)
-// #     del expected["node"]
-
-// #     parsed_metadata = metadata_service._parse_invokeai_metadata(metadata_invalid_node)
-// #     assert expected == parsed_metadata
-
-// # def test_can_parse_missing_node_id():
-// #     metadata_missing_node_id = deepcopy(valid_metadata)
-// #     del metadata_missing_node_id["node"]["id"]
-
-// #     expected = deepcopy(valid_metadata)
-// #     del expected["node"]["id"]
-
-// #     parsed_metadata = metadata_service._parse_invokeai_metadata(
-// #         metadata_missing_node_id
-// #     )
-// #     assert expected == parsed_metadata
-
-// # def test_can_parse_invalid_node_id():
-// #     metadata_invalid_node_id = deepcopy(valid_metadata)
-// #     metadata_invalid_node_id["node"]["id"] = 123
-
-// #     expected = deepcopy(valid_metadata)
-// #     del expected["node"]["id"]
-
-// #     parsed_metadata = metadata_service._parse_invokeai_metadata(
-// #         metadata_invalid_node_id
-// #     )
-// #     assert expected == parsed_metadata
-
-// # def test_can_parse_missing_node_type():
-// #     metadata_missing_node_type = deepcopy(valid_metadata)
-// #     del metadata_missing_node_type["node"]["type"]
-
-// #     expected = deepcopy(valid_metadata)
-// #     del expected["node"]["type"]
-
-// #     parsed_metadata = metadata_service._parse_invokeai_metadata(
-// #         metadata_missing_node_type
-// #     )
-// #     assert expected == parsed_metadata
-
-// # def test_can_parse_invalid_node_type():
-// #     metadata_invalid_node_type = deepcopy(valid_metadata)
-// #     metadata_invalid_node_type["node"]["type"] = 123
-
-// #     expected = deepcopy(valid_metadata)
-// #     del expected["node"]["type"]
-
-// #     parsed_metadata = metadata_service._parse_invokeai_metadata(
-// #         metadata_invalid_node_type
-// #     )
-// #     assert expected == parsed_metadata
-
-// # def test_can_parse_no_node_attrs():
-// #     metadata_no_node_attrs = deepcopy(valid_metadata)
-// #     metadata_no_node_attrs["node"] = {}
-
-// #     expected = deepcopy(valid_metadata)
-// #     del expected["node"]
-
-// #     parsed_metadata = metadata_service._parse_invokeai_metadata(metadata_no_node_attrs)
-// #     assert expected == parsed_metadata
-
-// # def test_can_parse_array_attr():
-// #     metadata_array_attr = deepcopy(valid_metadata)
-// #     metadata_array_attr["node"]["seed"] = [1, 2, 3]
-
-// #     expected = deepcopy(valid_metadata)
-// #     del expected["node"]["seed"]
-
-// #     parsed_metadata = metadata_service._parse_invokeai_metadata(metadata_array_attr)
-// #     assert expected == parsed_metadata
-
-// # def test_can_parse_invalid_dict_attr():
-// #     metadata_invalid_dict_attr = deepcopy(valid_metadata)
-// #     metadata_invalid_dict_attr["node"]["seed"] = {"a": 1}
-
-// #     expected = deepcopy(valid_metadata)
-// #     del expected["node"]["seed"]
-
-// #     parsed_metadata = metadata_service._parse_invokeai_metadata(
-// #         metadata_invalid_dict_attr
-// #     )
-// #     assert expected == parsed_metadata
-
-// # def test_can_parse_missing_image_field_image_type():
-// #     metadata_missing_image_field_image_type = deepcopy(valid_metadata)
-// #     del metadata_missing_image_field_image_type["node"]["image"]["image_type"]
-
-// #     expected = deepcopy(valid_metadata)
-// #     del expected["node"]["image"]
-
-// #     parsed_metadata = metadata_service._parse_invokeai_metadata(
-// #         metadata_missing_image_field_image_type
-// #     )
-// #     assert expected == parsed_metadata
-
-// # def test_can_parse_invalid_image_field_image_type():
-// #     metadata_invalid_image_field_image_type = deepcopy(valid_metadata)
-// #     metadata_invalid_image_field_image_type["node"]["image"][
-// #         "image_type"
-// #     ] = "bad image type"
-
-// #     expected = deepcopy(valid_metadata)
-// #     del expected["node"]["image"]
-
-// #     parsed_metadata = metadata_service._parse_invokeai_metadata(
-// #         metadata_invalid_image_field_image_type
-// #     )
-// #     assert expected == parsed_metadata
-
-// # def test_can_parse_invalid_latents_field_latents_name():
-// #     metadata_invalid_latents_field_latents_name = deepcopy(valid_metadata)
-// #     metadata_invalid_latents_field_latents_name["node"]["latents"] = {
-// #         "latents_name": 123
-// #     }
-
-// #     expected = deepcopy(valid_metadata)
-
-// #     parsed_metadata = metadata_service._parse_invokeai_metadata(
-// #         metadata_invalid_latents_field_latents_name
-// #     )
-
-// #     assert expected == parsed_metadata

From 7b4ef5926d50acc83ecde63d2d778e05e386d7ee Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 26 Feb 2024 22:27:58 +1100
Subject: [PATCH 328/411] fix(ui): CanvasPasteBack types

---
 .../src/features/nodes/util/graph/buildCanvasInpaintGraph.ts  | 4 ++--
 .../features/nodes/util/graph/buildCanvasSDXLInpaintGraph.ts  | 4 ++--
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasInpaintGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasInpaintGraph.ts
index 3512017313..1fced5c5c1 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasInpaintGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasInpaintGraph.ts
@@ -1,8 +1,8 @@
 import { logger } from 'app/logging/logger';
 import type { RootState } from 'app/store/store';
 import type {
+  CanvasPasteBackInvocation,
   CreateGradientMaskInvocation,
-  IAICanvasPasteBackInvocation,
   ImageDTO,
   ImageToLatentsInvocation,
   NoiseInvocation,
@@ -391,7 +391,7 @@ export const buildCanvasInpaintGraph = (
 
     // Paste Back
     graph.nodes[CANVAS_OUTPUT] = {
-      ...(graph.nodes[CANVAS_OUTPUT] as IAICanvasPasteBackInvocation),
+      ...(graph.nodes[CANVAS_OUTPUT] as CanvasPasteBackInvocation),
       mask: canvasMaskImage,
     };
 
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLInpaintGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLInpaintGraph.ts
index 394837a729..d31f178d37 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLInpaintGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLInpaintGraph.ts
@@ -1,8 +1,8 @@
 import { logger } from 'app/logging/logger';
 import type { RootState } from 'app/store/store';
 import type {
+  CanvasPasteBackInvocation,
   CreateGradientMaskInvocation,
-  IAICanvasPasteBackInvocation,
   ImageDTO,
   ImageToLatentsInvocation,
   NoiseInvocation,
@@ -401,7 +401,7 @@ export const buildCanvasSDXLInpaintGraph = (
 
     // Paste Back
     graph.nodes[CANVAS_OUTPUT] = {
-      ...(graph.nodes[CANVAS_OUTPUT] as IAICanvasPasteBackInvocation),
+      ...(graph.nodes[CANVAS_OUTPUT] as CanvasPasteBackInvocation),
       mask: canvasMaskImage,
     };
 

From 9abfb02bf08e77f55be04808ee0e519310681940 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 26 Feb 2024 23:15:01 +1100
Subject: [PATCH 329/411] fix(ui): model metadata handlers use model
 identifiers, not configs

Model metadata includes the main model, VAE and refiner model.

These used full model configs, as returned by the server, as their metadata type.

LoRA and control adapter metadata only use the metadata identifier.

This created a difference in handling. After parsing a model/vae/refiner, we have its name and can display it. But for LoRAs and control adapters, we only have the model key and must query for the full model config to get the name.

This change makes main model/vae/refiner metadata only have the model key, like LoRAs and control adapters.

The render function is now async so fetching can occur within it. All metadata fields with models now only contain the identifier, and fetch the model name to render their values.
---
 .../components/MetadataControlNets.tsx        | 18 ++++++---
 .../components/MetadataIPAdapters.tsx         | 18 ++++++---
 .../metadata/components/MetadataLoRAs.tsx     | 18 ++++++---
 .../components/MetadataT2IAdapters.tsx        | 18 ++++++---
 .../metadata/hooks/useMetadataItem.tsx        | 35 +++++++++++------
 .../web/src/features/metadata/types.ts        |  2 +-
 .../src/features/metadata/util/handlers.ts    | 38 +++++++++++++++----
 .../web/src/features/metadata/util/parsers.ts | 22 ++++++-----
 .../src/features/metadata/util/recallers.ts   | 20 +++++-----
 .../src/features/metadata/util/validators.ts  |  7 ++--
 10 files changed, 128 insertions(+), 68 deletions(-)

diff --git a/invokeai/frontend/web/src/features/metadata/components/MetadataControlNets.tsx b/invokeai/frontend/web/src/features/metadata/components/MetadataControlNets.tsx
index 1255e8e7cb..1e1c45632f 100644
--- a/invokeai/frontend/web/src/features/metadata/components/MetadataControlNets.tsx
+++ b/invokeai/frontend/web/src/features/metadata/components/MetadataControlNets.tsx
@@ -1,4 +1,3 @@
-import { Text } from '@invoke-ai/ui-library';
 import type { ControlNetConfig } from 'features/controlAdapters/store/types';
 import { MetadataItemView } from 'features/metadata/components/MetadataItemView';
 import type { MetadataHandlers } from 'features/metadata/types';
@@ -56,11 +55,18 @@ const MetadataViewControlNet = ({
     handlers.recallItem(controlNet, true);
   }, [handlers, controlNet]);
 
-  const renderedValue = useMemo(() => {
-    if (!handlers.renderItemValue) {
-      return null;
-    }
-    return <Text>{handlers.renderItemValue(controlNet)}</Text>;
+  const [renderedValue, setRenderedValue] = useState<React.ReactNode>(null);
+  useEffect(() => {
+    const _renderValue = async () => {
+      if (!handlers.renderItemValue) {
+        setRenderedValue(null);
+        return;
+      }
+      const rendered = await handlers.renderItemValue(controlNet);
+      setRenderedValue(rendered);
+    };
+
+    _renderValue();
   }, [handlers, controlNet]);
 
   return <MetadataItemView label={label} isDisabled={false} onRecall={onRecall} renderedValue={renderedValue} />;
diff --git a/invokeai/frontend/web/src/features/metadata/components/MetadataIPAdapters.tsx b/invokeai/frontend/web/src/features/metadata/components/MetadataIPAdapters.tsx
index 69f9ec986d..8c3705d698 100644
--- a/invokeai/frontend/web/src/features/metadata/components/MetadataIPAdapters.tsx
+++ b/invokeai/frontend/web/src/features/metadata/components/MetadataIPAdapters.tsx
@@ -1,4 +1,3 @@
-import { Text } from '@invoke-ai/ui-library';
 import type { IPAdapterConfig } from 'features/controlAdapters/store/types';
 import { MetadataItemView } from 'features/metadata/components/MetadataItemView';
 import type { MetadataHandlers } from 'features/metadata/types';
@@ -51,11 +50,18 @@ const MetadataViewIPAdapter = ({
     handlers.recallItem(ipAdapter, true);
   }, [handlers, ipAdapter]);
 
-  const renderedValue = useMemo(() => {
-    if (!handlers.renderItemValue) {
-      return null;
-    }
-    return <Text>{handlers.renderItemValue(ipAdapter)}</Text>;
+  const [renderedValue, setRenderedValue] = useState<React.ReactNode>(null);
+  useEffect(() => {
+    const _renderValue = async () => {
+      if (!handlers.renderItemValue) {
+        setRenderedValue(null);
+        return;
+      }
+      const rendered = await handlers.renderItemValue(ipAdapter);
+      setRenderedValue(rendered);
+    };
+
+    _renderValue();
   }, [handlers, ipAdapter]);
 
   return <MetadataItemView label={label} isDisabled={false} onRecall={onRecall} renderedValue={renderedValue} />;
diff --git a/invokeai/frontend/web/src/features/metadata/components/MetadataLoRAs.tsx b/invokeai/frontend/web/src/features/metadata/components/MetadataLoRAs.tsx
index 40f6bc427b..7e78985c49 100644
--- a/invokeai/frontend/web/src/features/metadata/components/MetadataLoRAs.tsx
+++ b/invokeai/frontend/web/src/features/metadata/components/MetadataLoRAs.tsx
@@ -1,4 +1,3 @@
-import { Text } from '@invoke-ai/ui-library';
 import type { LoRA } from 'features/lora/store/loraSlice';
 import { MetadataItemView } from 'features/metadata/components/MetadataItemView';
 import type { MetadataHandlers } from 'features/metadata/types';
@@ -51,11 +50,18 @@ const MetadataViewLoRA = ({
     handlers.recallItem(lora, true);
   }, [handlers, lora]);
 
-  const renderedValue = useMemo(() => {
-    if (!handlers.renderItemValue) {
-      return null;
-    }
-    return <Text>{handlers.renderItemValue(lora)}</Text>;
+  const [renderedValue, setRenderedValue] = useState<React.ReactNode>(null);
+  useEffect(() => {
+    const _renderValue = async () => {
+      if (!handlers.renderItemValue) {
+        setRenderedValue(null);
+        return;
+      }
+      const rendered = await handlers.renderItemValue(lora);
+      setRenderedValue(rendered);
+    };
+
+    _renderValue();
   }, [handlers, lora]);
 
   return <MetadataItemView label={label} isDisabled={false} onRecall={onRecall} renderedValue={renderedValue} />;
diff --git a/invokeai/frontend/web/src/features/metadata/components/MetadataT2IAdapters.tsx b/invokeai/frontend/web/src/features/metadata/components/MetadataT2IAdapters.tsx
index 209ab4f2ed..4464fbbd8f 100644
--- a/invokeai/frontend/web/src/features/metadata/components/MetadataT2IAdapters.tsx
+++ b/invokeai/frontend/web/src/features/metadata/components/MetadataT2IAdapters.tsx
@@ -1,4 +1,3 @@
-import { Text } from '@invoke-ai/ui-library';
 import type { T2IAdapterConfig } from 'features/controlAdapters/store/types';
 import { MetadataItemView } from 'features/metadata/components/MetadataItemView';
 import type { MetadataHandlers } from 'features/metadata/types';
@@ -55,12 +54,19 @@ const MetadataViewT2IAdapter = ({
     }
     handlers.recallItem(t2iAdapter, true);
   }, [handlers, t2iAdapter]);
+  
+  const [renderedValue, setRenderedValue] = useState<React.ReactNode>(null);
+  useEffect(() => {
+    const _renderValue = async () => {
+      if (!handlers.renderItemValue) {
+        setRenderedValue(null);
+        return;
+      }
+      const rendered = await handlers.renderItemValue(t2iAdapter);
+      setRenderedValue(rendered);
+    };
 
-  const renderedValue = useMemo(() => {
-    if (!handlers.renderItemValue) {
-      return null;
-    }
-    return <Text>{handlers.renderItemValue(t2iAdapter)}</Text>;
+    _renderValue();
   }, [handlers, t2iAdapter]);
 
   return <MetadataItemView label={label} isDisabled={false} onRecall={onRecall} renderedValue={renderedValue} />;
diff --git a/invokeai/frontend/web/src/features/metadata/hooks/useMetadataItem.tsx b/invokeai/frontend/web/src/features/metadata/hooks/useMetadataItem.tsx
index 178ac5155a..63d987569b 100644
--- a/invokeai/frontend/web/src/features/metadata/hooks/useMetadataItem.tsx
+++ b/invokeai/frontend/web/src/features/metadata/hooks/useMetadataItem.tsx
@@ -3,10 +3,14 @@ import type { MetadataHandlers } from 'features/metadata/types';
 import { MetadataParseFailedToken, MetadataParsePendingToken } from 'features/metadata/util/parsers';
 import { useCallback, useEffect, useMemo, useState } from 'react';
 
+const pendingRenderedValue = <Text>Loading</Text>;
+const failedRenderedValue = <Text>Parsing Failed</Text>;
+
 export const useMetadataItem = <T,>(metadata: unknown, handlers: MetadataHandlers<T>) => {
   const [value, setValue] = useState<T | typeof MetadataParsePendingToken | typeof MetadataParseFailedToken>(
     MetadataParsePendingToken
   );
+  const [renderedValue, setRenderedValue] = useState<React.ReactNode>(pendingRenderedValue);
 
   useEffect(() => {
     const _parse = async () => {
@@ -24,20 +28,27 @@ export const useMetadataItem = <T,>(metadata: unknown, handlers: MetadataHandler
 
   const label = useMemo(() => handlers.getLabel(), [handlers]);
 
-  const renderedValue = useMemo(() => {
-    if (value === MetadataParsePendingToken) {
-      return <Text>Loading</Text>;
-    }
-    if (value === MetadataParseFailedToken) {
-      return <Text>Parsing Failed</Text>;
-    }
+  useEffect(() => {
+    const _renderValue = async () => {
+      if (value === MetadataParsePendingToken) {
+        setRenderedValue(pendingRenderedValue);
+        return;
+      }
+      if (value === MetadataParseFailedToken) {
+        setRenderedValue(failedRenderedValue);
+        return;
+      }
 
-    const rendered = handlers.renderValue(value);
+      const rendered = await handlers.renderValue(value);
 
-    if (typeof rendered === 'string') {
-      return <Text>{rendered}</Text>;
-    }
-    return rendered;
+      if (typeof rendered === 'string') {
+        setRenderedValue(<Text>{rendered}</Text>);
+        return;
+      }
+      setRenderedValue(rendered);
+    };
+
+    _renderValue();
   }, [handlers, value]);
 
   const onRecall = useCallback(() => {
diff --git a/invokeai/frontend/web/src/features/metadata/types.ts b/invokeai/frontend/web/src/features/metadata/types.ts
index 366f11701e..4390a525b7 100644
--- a/invokeai/frontend/web/src/features/metadata/types.ts
+++ b/invokeai/frontend/web/src/features/metadata/types.ts
@@ -1,7 +1,7 @@
 /**
  * Renders a value of type T as a React node.
  */
-export type MetadataRenderValueFunc<T> = (value: T) => React.ReactNode;
+export type MetadataRenderValueFunc<T> = (value: T) => Promise<React.ReactNode>;
 
 /**
  * Gets the label of the current metadata item as a string.
diff --git a/invokeai/frontend/web/src/features/metadata/util/handlers.ts b/invokeai/frontend/web/src/features/metadata/util/handlers.ts
index 49d85f4eb3..8f520a6b4e 100644
--- a/invokeai/frontend/web/src/features/metadata/util/handlers.ts
+++ b/invokeai/frontend/web/src/features/metadata/util/handlers.ts
@@ -11,18 +11,38 @@ import type {
   MetadataRenderValueFunc,
   MetadataValidateFunc,
 } from 'features/metadata/types';
+import { fetchModelConfig } from 'features/metadata/util/modelFetchingHelpers';
 import { validators } from 'features/metadata/util/validators';
+import type { ModelIdentifierWithBase } from 'features/nodes/types/common';
 import { t } from 'i18next';
-import type { AnyModelConfig } from 'services/api/types';
 
 import { parsers } from './parsers';
 import { recallers } from './recallers';
 
-const renderModelConfigValue: MetadataRenderValueFunc<AnyModelConfig> = (value) =>
-  `${value.name} (${value.base.toUpperCase()}, ${value.key})`;
-const renderLoRAValue: MetadataRenderValueFunc<LoRA> = (value) => `${value.model.key} (${value.weight})`;
-const renderControlAdapterValue: MetadataRenderValueFunc<ControlAdapterConfig> = (value) =>
-  `${value.model?.key} (${value.weight})`;
+const renderModelConfigValue: MetadataRenderValueFunc<ModelIdentifierWithBase> = async (value) => {
+  try {
+    const modelConfig = await fetchModelConfig(value.key);
+    return `${modelConfig.name} (${modelConfig.base.toUpperCase()})`;
+  } catch {
+    return `${value.key} (${value.base.toUpperCase()})`;
+  }
+};
+const renderLoRAValue: MetadataRenderValueFunc<LoRA> = async (value) => {
+  try {
+    const modelConfig = await fetchModelConfig(value.model.key);
+    return `${modelConfig.name} (${modelConfig.base.toUpperCase()}) - ${value.weight}`;
+  } catch {
+    return `${value.model.key} (${value.model.base.toUpperCase()}) - ${value.weight}`;
+  }
+};
+const renderControlAdapterValue: MetadataRenderValueFunc<ControlAdapterConfig> = async (value) => {
+  try {
+    const modelConfig = await fetchModelConfig(value.model?.key ?? 'none');
+    return `${modelConfig.name} (${modelConfig.base.toUpperCase()}) - ${value.weight}`;
+  } catch {
+    return `${value.model?.key} (${value.model?.base.toUpperCase()}) - ${value.weight}`;
+  }
+};
 
 const parameterSetToast = (parameter: string, description?: string) => {
   toast({
@@ -130,6 +150,8 @@ const buildRecallItem =
     }
   };
 
+const resolveToString = (value: unknown) => new Promise<React.ReactNode>((resolve) => resolve(String(value)));
+
 const buildHandlers: BuildMetadataHandlers = ({
   getLabel,
   parser,
@@ -146,8 +168,8 @@ const buildHandlers: BuildMetadataHandlers = ({
   recall: recaller ? buildRecall({ recaller, validator, getLabel }) : undefined,
   recallItem: itemRecaller ? buildRecallItem({ itemRecaller, itemValidator, getLabel }) : undefined,
   getLabel,
-  renderValue: renderValue ?? String,
-  renderItemValue: renderItemValue ?? String,
+  renderValue: renderValue ?? resolveToString,
+  renderItemValue: renderItemValue ?? resolveToString,
 });
 
 export const handlers = {
diff --git a/invokeai/frontend/web/src/features/metadata/util/parsers.ts b/invokeai/frontend/web/src/features/metadata/util/parsers.ts
index df0485a0c4..619b8cc26c 100644
--- a/invokeai/frontend/web/src/features/metadata/util/parsers.ts
+++ b/invokeai/frontend/web/src/features/metadata/util/parsers.ts
@@ -12,7 +12,6 @@ import type { MetadataParseFunc } from 'features/metadata/types';
 import {
   fetchModelConfigWithTypeGuard,
   getModelKey,
-  getModelKeyAndBase,
 } from 'features/metadata/util/modelFetchingHelpers';
 import {
   zControlField,
@@ -26,17 +25,20 @@ import type {
   ParameterHeight,
   ParameterHRFEnabled,
   ParameterHRFMethod,
+  ParameterModel,
   ParameterNegativePrompt,
   ParameterNegativeStylePromptSDXL,
   ParameterPositivePrompt,
   ParameterPositiveStylePromptSDXL,
   ParameterScheduler,
+  ParameterSDXLRefinerModel,
   ParameterSDXLRefinerNegativeAestheticScore,
   ParameterSDXLRefinerPositiveAestheticScore,
   ParameterSDXLRefinerStart,
   ParameterSeed,
   ParameterSteps,
   ParameterStrength,
+  ParameterVAEModel,
   ParameterWidth,
 } from 'features/parameters/types/parameterSchemas';
 import {
@@ -60,7 +62,6 @@ import {
   isParameterWidth,
 } from 'features/parameters/types/parameterSchemas';
 import { get, isArray, isString } from 'lodash-es';
-import type { NonRefinerMainModelConfig, RefinerMainModelConfig, VAEModelConfig } from 'services/api/types';
 import {
   isControlNetModelConfig,
   isIPAdapterModelConfig,
@@ -163,25 +164,28 @@ const parseRefinerNegativeAestheticScore: MetadataParseFunc<ParameterSDXLRefiner
 const parseRefinerStart: MetadataParseFunc<ParameterSDXLRefinerStart> = (metadata) =>
   getProperty(metadata, 'refiner_start', isParameterSDXLRefinerStart);
 
-const parseMainModel: MetadataParseFunc<NonRefinerMainModelConfig> = async (metadata) => {
+const parseMainModel: MetadataParseFunc<ParameterModel> = async (metadata) => {
   const model = await getProperty(metadata, 'model', undefined);
   const key = await getModelKey(model, 'main');
   const mainModelConfig = await fetchModelConfigWithTypeGuard(key, isNonRefinerMainModelConfig);
-  return mainModelConfig;
+  const modelIdentifier = zModelIdentifierWithBase.parse(mainModelConfig);
+  return modelIdentifier;
 };
 
-const parseRefinerModel: MetadataParseFunc<RefinerMainModelConfig> = async (metadata) => {
+const parseRefinerModel: MetadataParseFunc<ParameterSDXLRefinerModel> = async (metadata) => {
   const refiner_model = await getProperty(metadata, 'refiner_model', undefined);
   const key = await getModelKey(refiner_model, 'main');
   const refinerModelConfig = await fetchModelConfigWithTypeGuard(key, isRefinerMainModelModelConfig);
-  return refinerModelConfig;
+  const modelIdentifier = zModelIdentifierWithBase.parse(refinerModelConfig);
+  return modelIdentifier;
 };
 
-const parseVAEModel: MetadataParseFunc<VAEModelConfig> = async (metadata) => {
+const parseVAEModel: MetadataParseFunc<ParameterVAEModel> = async (metadata) => {
   const vae = await getProperty(metadata, 'vae', undefined);
   const key = await getModelKey(vae, 'vae');
   const vaeModelConfig = await fetchModelConfigWithTypeGuard(key, isVAEModelConfig);
-  return vaeModelConfig;
+  const modelIdentifier = zModelIdentifierWithBase.parse(vaeModelConfig);
+  return modelIdentifier;
 };
 
 const parseLoRA: MetadataParseFunc<LoRA> = async (metadataItem) => {
@@ -194,7 +198,7 @@ const parseLoRA: MetadataParseFunc<LoRA> = async (metadataItem) => {
   const loraModelConfig = await fetchModelConfigWithTypeGuard(key, isLoRAModelConfig);
 
   return {
-    model: getModelKeyAndBase(loraModelConfig),
+    model: zModelIdentifierWithBase.parse(loraModelConfig),
     weight: isParameterLoRAWeight(weight) ? weight : defaultLoRAConfig.weight,
     isEnabled: true,
   };
diff --git a/invokeai/frontend/web/src/features/metadata/util/recallers.ts b/invokeai/frontend/web/src/features/metadata/util/recallers.ts
index 5e156dc035..cc867933b1 100644
--- a/invokeai/frontend/web/src/features/metadata/util/recallers.ts
+++ b/invokeai/frontend/web/src/features/metadata/util/recallers.ts
@@ -5,7 +5,6 @@ import { setHrfEnabled, setHrfMethod, setHrfStrength } from 'features/hrf/store/
 import type { LoRA } from 'features/lora/store/loraSlice';
 import { loraRecalled } from 'features/lora/store/loraSlice';
 import type { MetadataRecallFunc } from 'features/metadata/types';
-import { zModelIdentifierWithBase } from 'features/nodes/types/common';
 import { modelSelected } from 'features/parameters/store/actions';
 import {
   heightRecalled,
@@ -26,17 +25,20 @@ import type {
   ParameterHeight,
   ParameterHRFEnabled,
   ParameterHRFMethod,
+  ParameterModel,
   ParameterNegativePrompt,
   ParameterNegativeStylePromptSDXL,
   ParameterPositivePrompt,
   ParameterPositiveStylePromptSDXL,
   ParameterScheduler,
+  ParameterSDXLRefinerModel,
   ParameterSDXLRefinerNegativeAestheticScore,
   ParameterSDXLRefinerPositiveAestheticScore,
   ParameterSDXLRefinerStart,
   ParameterSeed,
   ParameterSteps,
   ParameterStrength,
+  ParameterVAEModel,
   ParameterWidth,
 } from 'features/parameters/types/parameterSchemas';
 import {
@@ -50,7 +52,6 @@ import {
   setRefinerStart,
   setRefinerSteps,
 } from 'features/sdxl/store/sdxlSlice';
-import type { NonRefinerMainModelConfig, RefinerMainModelConfig, VAEModelConfig } from 'services/api/types';
 
 const recallPositivePrompt: MetadataRecallFunc<ParameterPositivePrompt> = (positivePrompt) => {
   getStore().dispatch(setPositivePrompt(positivePrompt));
@@ -140,23 +141,20 @@ const recallRefinerStart: MetadataRecallFunc<ParameterSDXLRefinerStart> = (refin
   getStore().dispatch(setRefinerStart(refinerStart));
 };
 
-const recallModel: MetadataRecallFunc<NonRefinerMainModelConfig> = (model) => {
-  const modelIdentifier = zModelIdentifierWithBase.parse(model);
-  getStore().dispatch(modelSelected(modelIdentifier));
+const recallModel: MetadataRecallFunc<ParameterModel> = (model) => {
+  getStore().dispatch(modelSelected(model));
 };
 
-const recallRefinerModel: MetadataRecallFunc<RefinerMainModelConfig> = (refinerModel) => {
-  const modelIdentifier = zModelIdentifierWithBase.parse(refinerModel);
-  getStore().dispatch(refinerModelChanged(modelIdentifier));
+const recallRefinerModel: MetadataRecallFunc<ParameterSDXLRefinerModel> = (refinerModel) => {
+  getStore().dispatch(refinerModelChanged(refinerModel));
 };
 
-const recallVAE: MetadataRecallFunc<VAEModelConfig | null | undefined> = (vaeModel) => {
+const recallVAE: MetadataRecallFunc<ParameterVAEModel | null | undefined> = (vaeModel) => {
   if (!vaeModel) {
     getStore().dispatch(vaeSelected(null));
     return;
   }
-  const modelIdentifier = zModelIdentifierWithBase.parse(vaeModel);
-  getStore().dispatch(vaeSelected(modelIdentifier));
+  getStore().dispatch(vaeSelected(vaeModel));
 };
 
 const recallLoRA: MetadataRecallFunc<LoRA> = (lora) => {
diff --git a/invokeai/frontend/web/src/features/metadata/util/validators.ts b/invokeai/frontend/web/src/features/metadata/util/validators.ts
index 1f34e38651..9a9ffae723 100644
--- a/invokeai/frontend/web/src/features/metadata/util/validators.ts
+++ b/invokeai/frontend/web/src/features/metadata/util/validators.ts
@@ -3,7 +3,8 @@ import type { ControlNetConfig, IPAdapterConfig, T2IAdapterConfig } from 'featur
 import type { LoRA } from 'features/lora/store/loraSlice';
 import type { MetadataValidateFunc } from 'features/metadata/types';
 import { InvalidModelConfigError } from 'features/metadata/util/modelFetchingHelpers';
-import type { BaseModelType, RefinerMainModelConfig, VAEModelConfig } from 'services/api/types';
+import type { ParameterSDXLRefinerModel, ParameterVAEModel } from 'features/parameters/types/parameterSchemas';
+import type { BaseModelType } from 'services/api/types';
 
 /**
  * Checks the given base model type against the currently-selected model's base type and throws an error if they are
@@ -21,12 +22,12 @@ const validateBaseCompatibility = (base?: BaseModelType, message?: string) => {
   }
 };
 
-const validateRefinerModel: MetadataValidateFunc<RefinerMainModelConfig> = (refinerModel) => {
+const validateRefinerModel: MetadataValidateFunc<ParameterSDXLRefinerModel> = (refinerModel) => {
   validateBaseCompatibility('sdxl', 'Refiner incompatible with currently-selected model');
   return new Promise((resolve) => resolve(refinerModel));
 };
 
-const validateVAEModel: MetadataValidateFunc<VAEModelConfig> = (vaeModel) => {
+const validateVAEModel: MetadataValidateFunc<ParameterVAEModel> = (vaeModel) => {
   validateBaseCompatibility(vaeModel.base, 'VAE incompatible with currently-selected model');
   return new Promise((resolve) => resolve(vaeModel));
 };

From d23f2de9d703516f71501e6758f5540563172583 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 26 Feb 2024 23:21:53 +1100
Subject: [PATCH 330/411] feat(ui): create metadata types for control adapters

These are the same as the existing control adapter types, but the model field is non-nullable, simplifying handling of these objects.
---
 .../components/MetadataControlNets.tsx        |  9 +++----
 .../components/MetadataIPAdapters.tsx         |  9 +++----
 .../components/MetadataT2IAdapters.tsx        |  9 +++----
 .../web/src/features/metadata/types.ts        | 11 ++++++++
 .../src/features/metadata/util/handlers.ts    |  8 +++---
 .../web/src/features/metadata/util/parsers.ts | 27 +++++++++----------
 .../src/features/metadata/util/recallers.ts   | 20 ++++++++------
 .../src/features/metadata/util/validators.ts  | 26 ++++++++++--------
 8 files changed, 67 insertions(+), 52 deletions(-)

diff --git a/invokeai/frontend/web/src/features/metadata/components/MetadataControlNets.tsx b/invokeai/frontend/web/src/features/metadata/components/MetadataControlNets.tsx
index 1e1c45632f..ee9618ff74 100644
--- a/invokeai/frontend/web/src/features/metadata/components/MetadataControlNets.tsx
+++ b/invokeai/frontend/web/src/features/metadata/components/MetadataControlNets.tsx
@@ -1,6 +1,5 @@
-import type { ControlNetConfig } from 'features/controlAdapters/store/types';
 import { MetadataItemView } from 'features/metadata/components/MetadataItemView';
-import type { MetadataHandlers } from 'features/metadata/types';
+import type { ControlNetConfigMetadata, MetadataHandlers } from 'features/metadata/types';
 import { handlers } from 'features/metadata/util/handlers';
 import { useCallback, useEffect, useMemo, useState } from 'react';
 
@@ -9,7 +8,7 @@ type Props = {
 };
 
 export const MetadataControlNets = ({ metadata }: Props) => {
-  const [controlNets, setControlNets] = useState<ControlNetConfig[]>([]);
+  const [controlNets, setControlNets] = useState<ControlNetConfigMetadata[]>([]);
 
   useEffect(() => {
     const parse = async () => {
@@ -45,8 +44,8 @@ const MetadataViewControlNet = ({
   handlers,
 }: {
   label: string;
-  controlNet: ControlNetConfig;
-  handlers: MetadataHandlers<ControlNetConfig[], ControlNetConfig>;
+  controlNet: ControlNetConfigMetadata;
+  handlers: MetadataHandlers<ControlNetConfigMetadata[], ControlNetConfigMetadata>;
 }) => {
   const onRecall = useCallback(() => {
     if (!handlers.recallItem) {
diff --git a/invokeai/frontend/web/src/features/metadata/components/MetadataIPAdapters.tsx b/invokeai/frontend/web/src/features/metadata/components/MetadataIPAdapters.tsx
index 8c3705d698..4da27de2cb 100644
--- a/invokeai/frontend/web/src/features/metadata/components/MetadataIPAdapters.tsx
+++ b/invokeai/frontend/web/src/features/metadata/components/MetadataIPAdapters.tsx
@@ -1,6 +1,5 @@
-import type { IPAdapterConfig } from 'features/controlAdapters/store/types';
 import { MetadataItemView } from 'features/metadata/components/MetadataItemView';
-import type { MetadataHandlers } from 'features/metadata/types';
+import type { IPAdapterConfigMetadata, MetadataHandlers } from 'features/metadata/types';
 import { handlers } from 'features/metadata/util/handlers';
 import { useCallback, useEffect, useMemo, useState } from 'react';
 
@@ -9,7 +8,7 @@ type Props = {
 };
 
 export const MetadataIPAdapters = ({ metadata }: Props) => {
-  const [ipAdapters, setIPAdapters] = useState<IPAdapterConfig[]>([]);
+  const [ipAdapters, setIPAdapters] = useState<IPAdapterConfigMetadata[]>([]);
 
   useEffect(() => {
     const parse = async () => {
@@ -40,8 +39,8 @@ const MetadataViewIPAdapter = ({
   handlers,
 }: {
   label: string;
-  ipAdapter: IPAdapterConfig;
-  handlers: MetadataHandlers<IPAdapterConfig[], IPAdapterConfig>;
+  ipAdapter: IPAdapterConfigMetadata;
+  handlers: MetadataHandlers<IPAdapterConfigMetadata[], IPAdapterConfigMetadata>;
 }) => {
   const onRecall = useCallback(() => {
     if (!handlers.recallItem) {
diff --git a/invokeai/frontend/web/src/features/metadata/components/MetadataT2IAdapters.tsx b/invokeai/frontend/web/src/features/metadata/components/MetadataT2IAdapters.tsx
index 4464fbbd8f..6b1de889ff 100644
--- a/invokeai/frontend/web/src/features/metadata/components/MetadataT2IAdapters.tsx
+++ b/invokeai/frontend/web/src/features/metadata/components/MetadataT2IAdapters.tsx
@@ -1,6 +1,5 @@
-import type { T2IAdapterConfig } from 'features/controlAdapters/store/types';
 import { MetadataItemView } from 'features/metadata/components/MetadataItemView';
-import type { MetadataHandlers } from 'features/metadata/types';
+import type { MetadataHandlers, T2IAdapterConfigMetadata } from 'features/metadata/types';
 import { handlers } from 'features/metadata/util/handlers';
 import { useCallback, useEffect, useMemo, useState } from 'react';
 
@@ -9,7 +8,7 @@ type Props = {
 };
 
 export const MetadataT2IAdapters = ({ metadata }: Props) => {
-  const [t2iAdapters, setT2IAdapters] = useState<T2IAdapterConfig[]>([]);
+  const [t2iAdapters, setT2IAdapters] = useState<T2IAdapterConfigMetadata[]>([]);
 
   useEffect(() => {
     const parse = async () => {
@@ -45,8 +44,8 @@ const MetadataViewT2IAdapter = ({
   handlers,
 }: {
   label: string;
-  t2iAdapter: T2IAdapterConfig;
-  handlers: MetadataHandlers<T2IAdapterConfig[], T2IAdapterConfig>;
+  t2iAdapter: T2IAdapterConfigMetadata;
+  handlers: MetadataHandlers<T2IAdapterConfigMetadata[], T2IAdapterConfigMetadata>;
 }) => {
   const onRecall = useCallback(() => {
     if (!handlers.recallItem) {
diff --git a/invokeai/frontend/web/src/features/metadata/types.ts b/invokeai/frontend/web/src/features/metadata/types.ts
index 4390a525b7..ef48946d58 100644
--- a/invokeai/frontend/web/src/features/metadata/types.ts
+++ b/invokeai/frontend/web/src/features/metadata/types.ts
@@ -1,3 +1,6 @@
+import type { ControlNetConfig, IPAdapterConfig, T2IAdapterConfig } from 'features/controlAdapters/store/types';
+import type { O } from 'ts-toolbelt';
+
 /**
  * Renders a value of type T as a React node.
  */
@@ -134,3 +137,11 @@ export type BuildMetadataHandlersArg<TValue, TItem> = {
 export type BuildMetadataHandlers = <TValue, TItem>(
   arg: BuildMetadataHandlersArg<TValue, TItem>
 ) => MetadataHandlers<TValue, TItem>;
+
+export type ControlNetConfigMetadata = O.NonNullable<ControlNetConfig, 'model'>;
+export type T2IAdapterConfigMetadata = O.NonNullable<T2IAdapterConfig, 'model'>;
+export type IPAdapterConfigMetadata = O.NonNullable<IPAdapterConfig, 'model'>;
+export type AnyControlAdapterConfigMetadata =
+  | ControlNetConfigMetadata
+  | T2IAdapterConfigMetadata
+  | IPAdapterConfigMetadata;
diff --git a/invokeai/frontend/web/src/features/metadata/util/handlers.ts b/invokeai/frontend/web/src/features/metadata/util/handlers.ts
index 8f520a6b4e..a877648956 100644
--- a/invokeai/frontend/web/src/features/metadata/util/handlers.ts
+++ b/invokeai/frontend/web/src/features/metadata/util/handlers.ts
@@ -1,8 +1,8 @@
 import { objectKeys } from 'common/util/objectKeys';
 import { toast } from 'common/util/toast';
-import type { ControlAdapterConfig } from 'features/controlAdapters/store/types';
 import type { LoRA } from 'features/lora/store/loraSlice';
 import type {
+  AnyControlAdapterConfigMetadata,
   BuildMetadataHandlers,
   MetadataGetLabelFunc,
   MetadataHandlers,
@@ -35,12 +35,12 @@ const renderLoRAValue: MetadataRenderValueFunc<LoRA> = async (value) => {
     return `${value.model.key} (${value.model.base.toUpperCase()}) - ${value.weight}`;
   }
 };
-const renderControlAdapterValue: MetadataRenderValueFunc<ControlAdapterConfig> = async (value) => {
+const renderControlAdapterValue: MetadataRenderValueFunc<AnyControlAdapterConfigMetadata> = async (value) => {
   try {
-    const modelConfig = await fetchModelConfig(value.model?.key ?? 'none');
+    const modelConfig = await fetchModelConfig(value.model.key ?? 'none');
     return `${modelConfig.name} (${modelConfig.base.toUpperCase()}) - ${value.weight}`;
   } catch {
-    return `${value.model?.key} (${value.model?.base.toUpperCase()}) - ${value.weight}`;
+    return `${value.model.key} (${value.model.base.toUpperCase()}) - ${value.weight}`;
   }
 };
 
diff --git a/invokeai/frontend/web/src/features/metadata/util/parsers.ts b/invokeai/frontend/web/src/features/metadata/util/parsers.ts
index 619b8cc26c..3248827ba1 100644
--- a/invokeai/frontend/web/src/features/metadata/util/parsers.ts
+++ b/invokeai/frontend/web/src/features/metadata/util/parsers.ts
@@ -1,5 +1,4 @@
 import { CONTROLNET_PROCESSORS } from 'features/controlAdapters/store/constants';
-import type { ControlNetConfig, IPAdapterConfig, T2IAdapterConfig } from 'features/controlAdapters/store/types';
 import {
   initialControlNet,
   initialIPAdapter,
@@ -8,7 +7,7 @@ import {
 import type { LoRA } from 'features/lora/store/loraSlice';
 import { defaultLoRAConfig } from 'features/lora/store/loraSlice';
 import { MetadataParseError } from 'features/metadata/exceptions';
-import type { MetadataParseFunc } from 'features/metadata/types';
+import type { ControlNetConfigMetadata, IPAdapterConfigMetadata, MetadataParseFunc, T2IAdapterConfigMetadata } from 'features/metadata/types';
 import {
   fetchModelConfigWithTypeGuard,
   getModelKey,
@@ -213,7 +212,7 @@ const parseAllLoRAs: MetadataParseFunc<LoRA[]> = async (metadata) => {
   return loras;
 };
 
-const parseControlNet: MetadataParseFunc<ControlNetConfig> = async (metadataItem) => {
+const parseControlNet: MetadataParseFunc<ControlNetConfigMetadata> = async (metadataItem) => {
   const control_model = await getProperty(metadataItem, 'control_model');
   const key = await getModelKey(control_model, 'controlnet');
   const controlNetModel = await fetchModelConfigWithTypeGuard(key, isControlNetModelConfig);
@@ -243,7 +242,7 @@ const parseControlNet: MetadataParseFunc<ControlNetConfig> = async (metadataItem
   const processorType = 'none';
   const processorNode = CONTROLNET_PROCESSORS.none.default;
 
-  const controlNet: ControlNetConfig = {
+  const controlNet: ControlNetConfigMetadata = {
     type: 'controlnet',
     isEnabled: true,
     model: zModelIdentifierWithBase.parse(controlNetModel),
@@ -263,16 +262,16 @@ const parseControlNet: MetadataParseFunc<ControlNetConfig> = async (metadataItem
   return controlNet;
 };
 
-const parseAllControlNets: MetadataParseFunc<ControlNetConfig[]> = async (metadata) => {
+const parseAllControlNets: MetadataParseFunc<ControlNetConfigMetadata[]> = async (metadata) => {
   const controlNetsRaw = await getProperty(metadata, 'controlnets', isArray);
   const parseResults = await Promise.allSettled(controlNetsRaw.map((cn) => parseControlNet(cn)));
   const controlNets = parseResults
-    .filter((result): result is PromiseFulfilledResult<ControlNetConfig> => result.status === 'fulfilled')
+    .filter((result): result is PromiseFulfilledResult<ControlNetConfigMetadata> => result.status === 'fulfilled')
     .map((result) => result.value);
   return controlNets;
 };
 
-const parseT2IAdapter: MetadataParseFunc<T2IAdapterConfig> = async (metadataItem) => {
+const parseT2IAdapter: MetadataParseFunc<T2IAdapterConfigMetadata> = async (metadataItem) => {
   const t2i_adapter_model = await getProperty(metadataItem, 't2i_adapter_model');
   const key = await getModelKey(t2i_adapter_model, 't2i_adapter');
   const t2iAdapterModel = await fetchModelConfigWithTypeGuard(key, isT2IAdapterModelConfig);
@@ -295,7 +294,7 @@ const parseT2IAdapter: MetadataParseFunc<T2IAdapterConfig> = async (metadataItem
   const processorType = 'none';
   const processorNode = CONTROLNET_PROCESSORS.none.default;
 
-  const t2iAdapter: T2IAdapterConfig = {
+  const t2iAdapter: T2IAdapterConfigMetadata = {
     type: 't2i_adapter',
     isEnabled: true,
     model: zModelIdentifierWithBase.parse(t2iAdapterModel),
@@ -314,16 +313,16 @@ const parseT2IAdapter: MetadataParseFunc<T2IAdapterConfig> = async (metadataItem
   return t2iAdapter;
 };
 
-const parseAllT2IAdapters: MetadataParseFunc<T2IAdapterConfig[]> = async (metadata) => {
+const parseAllT2IAdapters: MetadataParseFunc<T2IAdapterConfigMetadata[]> = async (metadata) => {
   const t2iAdaptersRaw = await getProperty(metadata, 't2iAdapters', isArray);
   const parseResults = await Promise.allSettled(t2iAdaptersRaw.map((t2iAdapter) => parseT2IAdapter(t2iAdapter)));
   const t2iAdapters = parseResults
-    .filter((result): result is PromiseFulfilledResult<T2IAdapterConfig> => result.status === 'fulfilled')
+    .filter((result): result is PromiseFulfilledResult<T2IAdapterConfigMetadata> => result.status === 'fulfilled')
     .map((result) => result.value);
   return t2iAdapters;
 };
 
-const parseIPAdapter: MetadataParseFunc<IPAdapterConfig> = async (metadataItem) => {
+const parseIPAdapter: MetadataParseFunc<IPAdapterConfigMetadata> = async (metadataItem) => {
   const ip_adapter_model = await getProperty(metadataItem, 'ip_adapter_model');
   const key = await getModelKey(ip_adapter_model, 'ip_adapter');
   const ipAdapterModel = await fetchModelConfigWithTypeGuard(key, isIPAdapterModelConfig);
@@ -339,7 +338,7 @@ const parseIPAdapter: MetadataParseFunc<IPAdapterConfig> = async (metadataItem)
     .catch(null)
     .parse(getProperty(metadataItem, 'end_step_percent'));
 
-  const ipAdapter: IPAdapterConfig = {
+  const ipAdapter: IPAdapterConfigMetadata = {
     id: uuidv4(),
     type: 'ip_adapter',
     isEnabled: true,
@@ -353,11 +352,11 @@ const parseIPAdapter: MetadataParseFunc<IPAdapterConfig> = async (metadataItem)
   return ipAdapter;
 };
 
-const parseAllIPAdapters: MetadataParseFunc<IPAdapterConfig[]> = async (metadata) => {
+const parseAllIPAdapters: MetadataParseFunc<IPAdapterConfigMetadata[]> = async (metadata) => {
   const ipAdaptersRaw = await getProperty(metadata, 'ipAdapters', isArray);
   const parseResults = await Promise.allSettled(ipAdaptersRaw.map((ipAdapter) => parseIPAdapter(ipAdapter)));
   const ipAdapters = parseResults
-    .filter((result): result is PromiseFulfilledResult<IPAdapterConfig> => result.status === 'fulfilled')
+    .filter((result): result is PromiseFulfilledResult<IPAdapterConfigMetadata> => result.status === 'fulfilled')
     .map((result) => result.value);
   return ipAdapters;
 };
diff --git a/invokeai/frontend/web/src/features/metadata/util/recallers.ts b/invokeai/frontend/web/src/features/metadata/util/recallers.ts
index cc867933b1..f6036fe0cf 100644
--- a/invokeai/frontend/web/src/features/metadata/util/recallers.ts
+++ b/invokeai/frontend/web/src/features/metadata/util/recallers.ts
@@ -1,10 +1,14 @@
 import { getStore } from 'app/store/nanostores/store';
 import { controlAdapterRecalled } from 'features/controlAdapters/store/controlAdaptersSlice';
-import type { ControlNetConfig, IPAdapterConfig, T2IAdapterConfig } from 'features/controlAdapters/store/types';
 import { setHrfEnabled, setHrfMethod, setHrfStrength } from 'features/hrf/store/hrfSlice';
 import type { LoRA } from 'features/lora/store/loraSlice';
 import { loraRecalled } from 'features/lora/store/loraSlice';
-import type { MetadataRecallFunc } from 'features/metadata/types';
+import type {
+  ControlNetConfigMetadata,
+  IPAdapterConfigMetadata,
+  MetadataRecallFunc,
+  T2IAdapterConfigMetadata,
+} from 'features/metadata/types';
 import { modelSelected } from 'features/parameters/store/actions';
 import {
   heightRecalled,
@@ -168,33 +172,33 @@ const recallAllLoRAs: MetadataRecallFunc<LoRA[]> = (loras) => {
   });
 };
 
-const recallControlNet: MetadataRecallFunc<ControlNetConfig> = (controlNet) => {
+const recallControlNet: MetadataRecallFunc<ControlNetConfigMetadata> = (controlNet) => {
   getStore().dispatch(controlAdapterRecalled(controlNet));
 };
 
-const recallControlNets: MetadataRecallFunc<ControlNetConfig[]> = (controlNets) => {
+const recallControlNets: MetadataRecallFunc<ControlNetConfigMetadata[]> = (controlNets) => {
   const { dispatch } = getStore();
   controlNets.forEach((controlNet) => {
     dispatch(controlAdapterRecalled(controlNet));
   });
 };
 
-const recallT2IAdapter: MetadataRecallFunc<T2IAdapterConfig> = (t2iAdapter) => {
+const recallT2IAdapter: MetadataRecallFunc<T2IAdapterConfigMetadata> = (t2iAdapter) => {
   getStore().dispatch(controlAdapterRecalled(t2iAdapter));
 };
 
-const recallT2IAdapters: MetadataRecallFunc<T2IAdapterConfig[]> = (t2iAdapters) => {
+const recallT2IAdapters: MetadataRecallFunc<T2IAdapterConfigMetadata[]> = (t2iAdapters) => {
   const { dispatch } = getStore();
   t2iAdapters.forEach((t2iAdapter) => {
     dispatch(controlAdapterRecalled(t2iAdapter));
   });
 };
 
-const recallIPAdapter: MetadataRecallFunc<IPAdapterConfig> = (ipAdapter) => {
+const recallIPAdapter: MetadataRecallFunc<IPAdapterConfigMetadata> = (ipAdapter) => {
   getStore().dispatch(controlAdapterRecalled(ipAdapter));
 };
 
-const recallIPAdapters: MetadataRecallFunc<IPAdapterConfig[]> = (ipAdapters) => {
+const recallIPAdapters: MetadataRecallFunc<IPAdapterConfigMetadata[]> = (ipAdapters) => {
   const { dispatch } = getStore();
   ipAdapters.forEach((ipAdapter) => {
     dispatch(controlAdapterRecalled(ipAdapter));
diff --git a/invokeai/frontend/web/src/features/metadata/util/validators.ts b/invokeai/frontend/web/src/features/metadata/util/validators.ts
index 9a9ffae723..66454778f2 100644
--- a/invokeai/frontend/web/src/features/metadata/util/validators.ts
+++ b/invokeai/frontend/web/src/features/metadata/util/validators.ts
@@ -1,7 +1,11 @@
 import { getStore } from 'app/store/nanostores/store';
-import type { ControlNetConfig, IPAdapterConfig, T2IAdapterConfig } from 'features/controlAdapters/store/types';
 import type { LoRA } from 'features/lora/store/loraSlice';
-import type { MetadataValidateFunc } from 'features/metadata/types';
+import type {
+  ControlNetConfigMetadata,
+  IPAdapterConfigMetadata,
+  MetadataValidateFunc,
+  T2IAdapterConfigMetadata,
+} from 'features/metadata/types';
 import { InvalidModelConfigError } from 'features/metadata/util/modelFetchingHelpers';
 import type { ParameterSDXLRefinerModel, ParameterVAEModel } from 'features/parameters/types/parameterSchemas';
 import type { BaseModelType } from 'services/api/types';
@@ -50,13 +54,13 @@ const validateLoRAs: MetadataValidateFunc<LoRA[]> = (loras) => {
   return new Promise((resolve) => resolve(validatedLoRAs));
 };
 
-const validateControlNet: MetadataValidateFunc<ControlNetConfig> = (controlNet) => {
+const validateControlNet: MetadataValidateFunc<ControlNetConfigMetadata> = (controlNet) => {
   validateBaseCompatibility(controlNet.model?.base, 'ControlNet incompatible with currently-selected model');
   return new Promise((resolve) => resolve(controlNet));
 };
 
-const validateControlNets: MetadataValidateFunc<ControlNetConfig[]> = (controlNets) => {
-  const validatedControlNets: ControlNetConfig[] = [];
+const validateControlNets: MetadataValidateFunc<ControlNetConfigMetadata[]> = (controlNets) => {
+  const validatedControlNets: ControlNetConfigMetadata[] = [];
   controlNets.forEach((controlNet) => {
     try {
       validateBaseCompatibility(controlNet.model?.base, 'ControlNet incompatible with currently-selected model');
@@ -68,13 +72,13 @@ const validateControlNets: MetadataValidateFunc<ControlNetConfig[]> = (controlNe
   return new Promise((resolve) => resolve(validatedControlNets));
 };
 
-const validateT2IAdapter: MetadataValidateFunc<T2IAdapterConfig> = (t2iAdapter) => {
+const validateT2IAdapter: MetadataValidateFunc<T2IAdapterConfigMetadata> = (t2iAdapter) => {
   validateBaseCompatibility(t2iAdapter.model?.base, 'T2I Adapter incompatible with currently-selected model');
   return new Promise((resolve) => resolve(t2iAdapter));
 };
 
-const validateT2IAdapters: MetadataValidateFunc<T2IAdapterConfig[]> = (t2iAdapters) => {
-  const validatedT2IAdapters: T2IAdapterConfig[] = [];
+const validateT2IAdapters: MetadataValidateFunc<T2IAdapterConfigMetadata[]> = (t2iAdapters) => {
+  const validatedT2IAdapters: T2IAdapterConfigMetadata[] = [];
   t2iAdapters.forEach((t2iAdapter) => {
     try {
       validateBaseCompatibility(t2iAdapter.model?.base, 'T2I Adapter incompatible with currently-selected model');
@@ -86,13 +90,13 @@ const validateT2IAdapters: MetadataValidateFunc<T2IAdapterConfig[]> = (t2iAdapte
   return new Promise((resolve) => resolve(validatedT2IAdapters));
 };
 
-const validateIPAdapter: MetadataValidateFunc<IPAdapterConfig> = (ipAdapter) => {
+const validateIPAdapter: MetadataValidateFunc<IPAdapterConfigMetadata> = (ipAdapter) => {
   validateBaseCompatibility(ipAdapter.model?.base, 'IP Adapter incompatible with currently-selected model');
   return new Promise((resolve) => resolve(ipAdapter));
 };
 
-const validateIPAdapters: MetadataValidateFunc<IPAdapterConfig[]> = (ipAdapters) => {
-  const validatedIPAdapters: IPAdapterConfig[] = [];
+const validateIPAdapters: MetadataValidateFunc<IPAdapterConfigMetadata[]> = (ipAdapters) => {
+  const validatedIPAdapters: IPAdapterConfigMetadata[] = [];
   ipAdapters.forEach((ipAdapter) => {
     try {
       validateBaseCompatibility(ipAdapter.model?.base, 'IP Adapter incompatible with currently-selected model');

From 32b847897495b73aca760a88b7f66bb53f014c6c Mon Sep 17 00:00:00 2001
From: Jennifer Player <chainchompa@gmail.com>
Date: Tue, 27 Feb 2024 09:43:02 -0500
Subject: [PATCH 331/411] added add all button to scan models

---
 invokeai/frontend/web/public/locales/en.json  |  1 +
 .../AddModelPanel/ImportQueue/ImportQueue.tsx |  9 +-
 .../ImportQueue/ImportQueueItem.tsx           |  2 +-
 .../ScanModels/ScanModelsResults.tsx          | 96 ++++++++++++++-----
 4 files changed, 82 insertions(+), 26 deletions(-)

diff --git a/invokeai/frontend/web/public/locales/en.json b/invokeai/frontend/web/public/locales/en.json
index 12d06ee224..f845250c8e 100644
--- a/invokeai/frontend/web/public/locales/en.json
+++ b/invokeai/frontend/web/public/locales/en.json
@@ -691,6 +691,7 @@
     },
     "modelManager": {
         "active": "active",
+        "addAll": "Add All",
         "addCheckpointModel": "Add Checkpoint / Safetensor Model",
         "addDifference": "Add Difference",
         "addDiffuserModel": "Add Diffusers",
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueue.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueue.tsx
index cd2208c972..cf45f2c913 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueue.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueue.tsx
@@ -1,5 +1,6 @@
 import { Box, Button, Flex, Text } from '@invoke-ai/ui-library';
 import { useAppDispatch } from 'app/store/storeHooks';
+import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
 import { addToast } from 'features/system/store/systemSlice';
 import { makeToast } from 'features/system/util/makeToast';
 import { t } from 'i18next';
@@ -57,9 +58,11 @@ export const ImportQueue = () => {
         </Button>
       </Flex>
       <Box mt={3} layerStyle="first" p={3} borderRadius="base" w="full" h="full">
-        <Flex flexDir="column-reverse" gap="2">
-          {data?.map((model) => <ImportQueueItem key={model.id} model={model} />)}
-        </Flex>
+        <ScrollableContent>
+          <Flex flexDir="column-reverse" gap="2">
+            {data?.map((model) => <ImportQueueItem key={model.id} model={model} />)}
+          </Flex>
+        </ScrollableContent>
       </Box>
     </Flex>
   );
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueueItem.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueueItem.tsx
index fa13de0095..14bbe7daeb 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueueItem.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ImportQueue/ImportQueueItem.tsx
@@ -121,7 +121,7 @@ export const ImportQueueItem = (props: ModelListItemProps) => {
       </Box>
 
       <Box minW="20px">
-        {(model.status === 'downloading' || model.status === 'waiting') && (
+        {(model.status === 'downloading' || model.status === 'waiting' || model.status === 'running') && (
           <IconButton
             isRound={true}
             size="xs"
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx
index cf9439b45d..b8c6efd938 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx
@@ -1,10 +1,22 @@
-import { Divider, Flex, Heading, IconButton, Input, InputGroup, InputRightElement } from '@invoke-ai/ui-library';
+import {
+  Button,
+  Divider,
+  Flex,
+  Heading,
+  IconButton,
+  Input,
+  InputGroup,
+  InputRightElement,
+} from '@invoke-ai/ui-library';
+import { useAppDispatch } from 'app/store/storeHooks';
 import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
+import { addToast } from 'features/system/store/systemSlice';
+import { makeToast } from 'features/system/util/makeToast';
 import type { ChangeEventHandler } from 'react';
 import { useCallback, useMemo, useState } from 'react';
 import { useTranslation } from 'react-i18next';
 import { PiXBold } from 'react-icons/pi';
-import type { ScanFolderResponse } from 'services/api/endpoints/models';
+import { type ScanFolderResponse, useImportMainModelsMutation } from 'services/api/endpoints/models';
 
 import { ScanModelResultItem } from './ScanModelResultItem';
 
@@ -15,6 +27,9 @@ type ScanModelResultsProps = {
 export const ScanModelsResults = ({ results }: ScanModelResultsProps) => {
   const { t } = useTranslation();
   const [searchTerm, setSearchTerm] = useState('');
+  const dispatch = useAppDispatch();
+
+  const [importMainModel] = useImportMainModelsMutation();
 
   const filteredResults = useMemo(() => {
     return results.filter((result) => {
@@ -31,6 +46,38 @@ export const ScanModelsResults = ({ results }: ScanModelResultsProps) => {
     setSearchTerm('');
   }, []);
 
+  const handleAddAll = useCallback(() => {
+    for (const result of filteredResults) {
+      if (result.is_installed) {
+        continue;
+      }
+      importMainModel({ source: result.path, config: undefined })
+        .unwrap()
+        .then((_) => {
+          dispatch(
+            addToast(
+              makeToast({
+                title: t('toast.modelAddedSimple'),
+                status: 'success',
+              })
+            )
+          );
+        })
+        .catch((error) => {
+          if (error) {
+            dispatch(
+              addToast(
+                makeToast({
+                  title: `${error.data.detail} `,
+                  status: 'error',
+                })
+              )
+            );
+          }
+        });
+    }
+  }, [importMainModel, filteredResults, dispatch, t]);
+
   return (
     <>
       <Divider mt={4} />
@@ -39,27 +86,32 @@ export const ScanModelsResults = ({ results }: ScanModelResultsProps) => {
           <Heading fontSize="md" as="h4">
             {t('modelManager.scanResults')}
           </Heading>
-          <InputGroup maxW="300px" size="xs">
-            <Input
-              placeholder={t('modelManager.search')}
-              value={searchTerm}
-              data-testid="board-search-input"
-              onChange={handleSearch}
-              size="xs"
-            />
+          <Flex alignItems="center" gap="4">
+            <Button onClick={handleAddAll} isDisabled={filteredResults.length === 0}>
+              {t('modelManager.addAll')}
+            </Button>
+            <InputGroup maxW="300px" size="xs">
+              <Input
+                placeholder={t('modelManager.search')}
+                value={searchTerm}
+                data-testid="board-search-input"
+                onChange={handleSearch}
+                size="xs"
+              />
 
-            {searchTerm && (
-              <InputRightElement h="full" pe={2}>
-                <IconButton
-                  size="sm"
-                  variant="link"
-                  aria-label={t('boards.clearSearch')}
-                  icon={<PiXBold />}
-                  onClick={clearSearch}
-                />
-              </InputRightElement>
-            )}
-          </InputGroup>
+              {searchTerm && (
+                <InputRightElement h="full" pe={2}>
+                  <IconButton
+                    size="sm"
+                    variant="link"
+                    aria-label={t('boards.clearSearch')}
+                    icon={<PiXBold />}
+                    onClick={clearSearch}
+                  />
+                </InputRightElement>
+              )}
+            </InputGroup>
+          </Flex>
         </Flex>
         <Flex height="100%" layerStyle="third" borderRadius="base" p={4} mt={4} mb={4}>
           <ScrollableContent>

From afa7043dcd3394f7b24683ea11ad5930f3921cc5 Mon Sep 17 00:00:00 2001
From: blessedcoolant <54517381+blessedcoolant@users.noreply.github.com>
Date: Mon, 26 Feb 2024 19:05:11 +0530
Subject: [PATCH 332/411] ui: split the canvas mask blur and edge size setting

---
 invokeai/frontend/web/public/locales/en.json              | 8 ++++----
 .../common/components/InformationalPopover/constants.ts   | 2 +-
 .../features/nodes/util/graph/buildCanvasInpaintGraph.ts  | 4 ++--
 .../features/nodes/util/graph/buildCanvasOutpaintGraph.ts | 3 ++-
 .../nodes/util/graph/buildCanvasSDXLInpaintGraph.ts       | 3 ++-
 .../nodes/util/graph/buildCanvasSDXLOutpaintGraph.ts      | 3 ++-
 .../Canvas/Compositing/MaskAdjustment/ParamMaskBlur.tsx   | 2 +-
 .../CompositingSettingsAccordion.tsx                      | 4 +++-
 .../frontend/web/src/features/system/store/configSlice.ts | 8 ++++----
 9 files changed, 21 insertions(+), 16 deletions(-)

diff --git a/invokeai/frontend/web/public/locales/en.json b/invokeai/frontend/web/public/locales/en.json
index f845250c8e..05a7a456f3 100644
--- a/invokeai/frontend/web/public/locales/en.json
+++ b/invokeai/frontend/web/public/locales/en.json
@@ -1193,8 +1193,8 @@
             "unableToInvoke": "Unable to Invoke"
         },
         "maskAdjustmentsHeader": "Mask Adjustments",
-        "maskBlur": "Blur",
-        "maskBlurMethod": "Blur Method",
+        "maskBlur": "Mask Blur",
+        "maskBlurMethod": "Mask Blur Method",
         "maskEdge": "Mask Edge",
         "negativePromptPlaceholder": "Negative Prompt",
         "noiseSettings": "Noise",
@@ -1480,8 +1480,8 @@
                 "Each scheduler defines how to iteratively add noise to an image or how to update a sample based on a model's output."
             ]
         },
-        "compositingBlur": {
-            "heading": "Blur",
+        "compositingMaskBlur": {
+            "heading": "Mask Blur",
             "paragraphs": ["The blur radius of the mask."]
         },
         "compositingBlurMethod": {
diff --git a/invokeai/frontend/web/src/common/components/InformationalPopover/constants.ts b/invokeai/frontend/web/src/common/components/InformationalPopover/constants.ts
index 6fb06a4287..ab03dcded2 100644
--- a/invokeai/frontend/web/src/common/components/InformationalPopover/constants.ts
+++ b/invokeai/frontend/web/src/common/components/InformationalPopover/constants.ts
@@ -6,7 +6,7 @@ export type Feature =
   | 'paramNegativeConditioning'
   | 'paramPositiveConditioning'
   | 'paramScheduler'
-  | 'compositingBlur'
+  | 'compositingMaskBlur'
   | 'compositingBlurMethod'
   | 'compositingCoherencePass'
   | 'compositingCoherenceMode'
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasInpaintGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasInpaintGraph.ts
index 1fced5c5c1..00bad63c3b 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasInpaintGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasInpaintGraph.ts
@@ -58,13 +58,13 @@ export const buildCanvasInpaintGraph = (
     seed,
     vaePrecision,
     shouldUseCpuNoise,
-
     clipSkip,
     seamlessXAxis,
     seamlessYAxis,
     canvasCoherenceMode,
     canvasCoherenceMinDenoise,
     canvasCoherenceEdgeSize,
+    maskBlur,
   } = state.generation;
 
   if (!model) {
@@ -156,7 +156,7 @@ export const buildCanvasInpaintGraph = (
         id: CANVAS_OUTPUT,
         is_intermediate: getIsIntermediate(state),
         board: getBoardField(state),
-        mask_blur: canvasCoherenceEdgeSize,
+        mask_blur: maskBlur,
         source_image: canvasInitImage,
       },
     },
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasOutpaintGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasOutpaintGraph.ts
index 9ec07546af..75f9a15f48 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasOutpaintGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasOutpaintGraph.ts
@@ -71,6 +71,7 @@ export const buildCanvasOutpaintGraph = (
     canvasCoherenceMode,
     canvasCoherenceMinDenoise,
     canvasCoherenceEdgeSize,
+    maskBlur,
   } = state.generation;
 
   if (!model) {
@@ -176,7 +177,7 @@ export const buildCanvasOutpaintGraph = (
         is_intermediate: getIsIntermediate(state),
         board: getBoardField(state),
         use_cache: false,
-        mask_blur: canvasCoherenceEdgeSize,
+        mask_blur: maskBlur,
       },
     },
     edges: [
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLInpaintGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLInpaintGraph.ts
index d31f178d37..fc60805e85 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLInpaintGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLInpaintGraph.ts
@@ -64,6 +64,7 @@ export const buildCanvasSDXLInpaintGraph = (
     canvasCoherenceMode,
     canvasCoherenceMinDenoise,
     canvasCoherenceEdgeSize,
+    maskBlur,
   } = state.generation;
 
   const { refinerModel, refinerStart } = state.sdxl;
@@ -157,7 +158,7 @@ export const buildCanvasSDXLInpaintGraph = (
         id: CANVAS_OUTPUT,
         is_intermediate: getIsIntermediate(state),
         board: getBoardField(state),
-        mask_blur: canvasCoherenceEdgeSize,
+        mask_blur: maskBlur,
         source_image: canvasInitImage,
       },
     },
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLOutpaintGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLOutpaintGraph.ts
index 13135e4748..44950ff40a 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLOutpaintGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLOutpaintGraph.ts
@@ -71,6 +71,7 @@ export const buildCanvasSDXLOutpaintGraph = (
     canvasCoherenceMode,
     canvasCoherenceMinDenoise,
     canvasCoherenceEdgeSize,
+    maskBlur,
   } = state.generation;
 
   const { refinerModel, refinerStart } = state.sdxl;
@@ -176,7 +177,7 @@ export const buildCanvasSDXLOutpaintGraph = (
         is_intermediate: getIsIntermediate(state),
         board: getBoardField(state),
         use_cache: false,
-        mask_blur: canvasCoherenceEdgeSize,
+        mask_blur: maskBlur,
       },
     },
     edges: [
diff --git a/invokeai/frontend/web/src/features/parameters/components/Canvas/Compositing/MaskAdjustment/ParamMaskBlur.tsx b/invokeai/frontend/web/src/features/parameters/components/Canvas/Compositing/MaskAdjustment/ParamMaskBlur.tsx
index ca5a209db7..2218002449 100644
--- a/invokeai/frontend/web/src/features/parameters/components/Canvas/Compositing/MaskAdjustment/ParamMaskBlur.tsx
+++ b/invokeai/frontend/web/src/features/parameters/components/Canvas/Compositing/MaskAdjustment/ParamMaskBlur.tsx
@@ -26,7 +26,7 @@ const ParamMaskBlur = () => {
 
   return (
     <FormControl>
-      <InformationalPopover feature="compositingBlur">
+      <InformationalPopover feature="compositingMaskBlur">
         <FormLabel>{t('parameters.maskBlur')}</FormLabel>
       </InformationalPopover>
       <CompositeSlider
diff --git a/invokeai/frontend/web/src/features/settingsAccordions/components/CompositingSettingsAccordion/CompositingSettingsAccordion.tsx b/invokeai/frontend/web/src/features/settingsAccordions/components/CompositingSettingsAccordion/CompositingSettingsAccordion.tsx
index 0c4eed17d6..65d064dd56 100644
--- a/invokeai/frontend/web/src/features/settingsAccordions/components/CompositingSettingsAccordion/CompositingSettingsAccordion.tsx
+++ b/invokeai/frontend/web/src/features/settingsAccordions/components/CompositingSettingsAccordion/CompositingSettingsAccordion.tsx
@@ -12,6 +12,7 @@ import {
 import ParamCanvasCoherenceEdgeSize from 'features/parameters/components/Canvas/Compositing/CoherencePass/ParamCanvasCoherenceEdgeSize';
 import ParamCanvasCoherenceMinDenoise from 'features/parameters/components/Canvas/Compositing/CoherencePass/ParamCanvasCoherenceMinDenoise';
 import ParamCanvasCoherenceMode from 'features/parameters/components/Canvas/Compositing/CoherencePass/ParamCanvasCoherenceMode';
+import ParamMaskBlur from 'features/parameters/components/Canvas/Compositing/MaskAdjustment/ParamMaskBlur';
 import ParamInfillMethod from 'features/parameters/components/Canvas/InfillAndScaling/ParamInfillMethod';
 import ParamInfillOptions from 'features/parameters/components/Canvas/InfillAndScaling/ParamInfillOptions';
 import { useStandaloneAccordionToggle } from 'features/settingsAccordions/hooks/useStandaloneAccordionToggle';
@@ -43,8 +44,9 @@ export const CompositingSettingsAccordion = memo(() => {
                 <ParamCanvasCoherenceMode />
                 <ParamCanvasCoherenceEdgeSize />
                 <ParamCanvasCoherenceMinDenoise />
+                <ParamMaskBlur />
                 {/* <ParamMaskBlurMethod />
-                <ParamMaskBlur /> */}
+                 */}
               </FormControlGroup>
             </Flex>
           </TabPanel>
diff --git a/invokeai/frontend/web/src/features/system/store/configSlice.ts b/invokeai/frontend/web/src/features/system/store/configSlice.ts
index 707c94dee6..ded3241c5b 100644
--- a/invokeai/frontend/web/src/features/system/store/configSlice.ts
+++ b/invokeai/frontend/web/src/features/system/store/configSlice.ts
@@ -88,9 +88,9 @@ export const initialConfigState: AppConfig = {
     },
     canvasCoherenceEdgeSize: {
       initial: 16,
-      sliderMin: 16,
-      sliderMax: 512,
-      numberInputMin: 16,
+      sliderMin: 0,
+      sliderMax: 128,
+      numberInputMin: 0,
       numberInputMax: 1024,
       fineStep: 8,
       coarseStep: 16,
@@ -134,7 +134,7 @@ export const initialConfigState: AppConfig = {
     maskBlur: {
       initial: 16,
       sliderMin: 0,
-      sliderMax: 64,
+      sliderMax: 128,
       numberInputMin: 0,
       numberInputMax: 512,
       fineStep: 1,

From 4c19d5cee4d76109627b15ba8e4664bc743f97a0 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 27 Feb 2024 13:12:12 +1100
Subject: [PATCH 333/411] fix(ui): fix missing component import

---
 .../features/controlAdapters/components/ControlAdapterConfig.tsx | 1 +
 1 file changed, 1 insertion(+)

diff --git a/invokeai/frontend/web/src/features/controlAdapters/components/ControlAdapterConfig.tsx b/invokeai/frontend/web/src/features/controlAdapters/components/ControlAdapterConfig.tsx
index baf2d412c2..42499b015c 100644
--- a/invokeai/frontend/web/src/features/controlAdapters/components/ControlAdapterConfig.tsx
+++ b/invokeai/frontend/web/src/features/controlAdapters/components/ControlAdapterConfig.tsx
@@ -1,5 +1,6 @@
 import { Box, Flex, FormControl, FormLabel, Icon, IconButton, Switch } from '@invoke-ai/ui-library';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import ParamControlAdapterModel from 'features/controlAdapters/components/parameters/ParamControlAdapterModel';
 import { useControlAdapterIsEnabled } from 'features/controlAdapters/hooks/useControlAdapterIsEnabled';
 import { useControlAdapterType } from 'features/controlAdapters/hooks/useControlAdapterType';
 import {

From 506fa55f18f573d3a452c0a1f42009db33b97418 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 27 Feb 2024 13:21:03 +1100
Subject: [PATCH 334/411] feat(ui): add knip + minimal config

https://knip.dev/

Replaces `unimported`
---
 invokeai/frontend/web/.unimportedrc.json |   9 -
 invokeai/frontend/web/knip.json          |   4 +
 invokeai/frontend/web/package.json       |   3 +-
 invokeai/frontend/web/pnpm-lock.yaml     | 770 ++++++++++++++++++++++-
 4 files changed, 774 insertions(+), 12 deletions(-)
 delete mode 100644 invokeai/frontend/web/.unimportedrc.json
 create mode 100644 invokeai/frontend/web/knip.json

diff --git a/invokeai/frontend/web/.unimportedrc.json b/invokeai/frontend/web/.unimportedrc.json
deleted file mode 100644
index cf96610502..0000000000
--- a/invokeai/frontend/web/.unimportedrc.json
+++ /dev/null
@@ -1,9 +0,0 @@
-{
-  "entry": ["src/main.tsx"],
-  "extensions": [".ts", ".tsx"],
-  "ignorePatterns": ["**/node_modules/**", "dist/**", "public/**", "**/*.stories.tsx", "config/**"],
-  "ignoreUnresolved": [],
-  "ignoreUnimported": ["src/i18.d.ts", "vite.config.ts", "src/vite-env.d.ts"],
-  "respectGitignore": true,
-  "ignoreUnused": []
-}
diff --git a/invokeai/frontend/web/knip.json b/invokeai/frontend/web/knip.json
new file mode 100644
index 0000000000..b632b8c56a
--- /dev/null
+++ b/invokeai/frontend/web/knip.json
@@ -0,0 +1,4 @@
+{
+  "$schema": "https://unpkg.com/knip@5/schema.json",
+  "ignore": ["src/features/nodes/types/v2/**/*", "src/features/nodes/types/v1/**/*"]
+}
diff --git a/invokeai/frontend/web/package.json b/invokeai/frontend/web/package.json
index 48bad31000..9c34c34f0b 100644
--- a/invokeai/frontend/web/package.json
+++ b/invokeai/frontend/web/package.json
@@ -33,7 +33,7 @@
     "preinstall": "npx only-allow pnpm",
     "storybook": "storybook dev -p 6006",
     "build-storybook": "storybook build",
-    "unimported": "npx unimported",
+    "knip": "knip",
     "test": "vitest",
     "test:no-watch": "vitest --no-watch"
   },
@@ -136,6 +136,7 @@
     "eslint": "^8.56.0",
     "eslint-plugin-i18next": "^6.0.3",
     "eslint-plugin-path": "^1.2.4",
+    "knip": "^5.0.2",
     "madge": "^6.1.0",
     "openapi-types": "^12.1.3",
     "openapi-typescript": "^6.7.4",
diff --git a/invokeai/frontend/web/pnpm-lock.yaml b/invokeai/frontend/web/pnpm-lock.yaml
index d79d482d08..ccbb7534d8 100644
--- a/invokeai/frontend/web/pnpm-lock.yaml
+++ b/invokeai/frontend/web/pnpm-lock.yaml
@@ -241,6 +241,9 @@ devDependencies:
   eslint-plugin-path:
     specifier: ^1.2.4
     version: 1.2.4(eslint@8.56.0)
+  knip:
+    specifier: ^5.0.2
+    version: 5.0.2(@types/node@20.11.19)(typescript@5.3.3)
   madge:
     specifier: ^6.1.0
     version: 6.1.0(typescript@5.3.3)
@@ -3206,6 +3209,31 @@ packages:
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     dev: false
 
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+    engines: {node: '>=4'}
+    dependencies:
+      array-last: 1.3.0
+      babylon: 6.18.0
+      compose-function: 3.0.3
+      deep-freeze: 0.0.1
+      filter-iterator: 0.0.1
+      filter-obj: 1.1.0
+      has-own-property: 0.1.0
+      identity-function: 1.0.0
+      is-iterable: 1.1.1
+      iterable-lookahead: 1.0.0
+      lodash.curry: 4.1.1
+      magic-string: 0.16.0
+      map-obj: 2.0.0
+      object-pairs: 0.1.0
+      object-values: 1.0.0
+      reverse-arguments: 1.0.0
+      shell-quote-word: 1.0.1
+      to-pascal-case: 1.0.0
+      unescape-js: 1.1.4
+    dev: true
+
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     resolution: {integrity: sha512-bmoCYyWdEL3wDQIVbcyzRyeKLgk2WtWLTWz1ZIAZF/EGbNOwSA6ew3PftJ1PqMiOOGu0OyFMzG53L0zqIpPeNA==}
     engines: {node: '>=12'}
@@ -4034,11 +4062,24 @@ packages:
       run-parallel: 1.2.0
     dev: true
 
+  /@nodelib/fs.scandir@3.0.0:
+    resolution: {integrity: sha512-ktI9+PxfHYtKjF3cLTUAh2N+b8MijCRPNwKJNqTVdL0gB0QxLU2rIRaZ1t71oEa3YBDE6bukH1sR0+CDnpp/Mg==}
+    engines: {node: '>=16.14.0'}
+    dependencies:
+      '@nodelib/fs.stat': 3.0.0
+      run-parallel: 1.2.0
+    dev: true
+
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     resolution: {integrity: sha512-RkhPPp2zrqDAQA/2jNhnztcPAlv64XdhIp7a7454A5ovI7Bukxgt7MX7udwAu3zg1DcpPU0rz3VV1SeaqvY4+A==}
     engines: {node: '>= 8'}
     dev: true
 
+  /@nodelib/fs.stat@3.0.0:
+    resolution: {integrity: sha512-2tQOI38s19P9i7X/Drt0v8iMA+KMsgdhB/dyPER+e+2Y8L1Z7QvnuRdW/uLuf5YRFUYmnj4bMA6qCuZHFI1GDQ==}
+    engines: {node: '>=16.14.0'}
+    dev: true
+
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     resolution: {integrity: sha512-oGB+UxlgWcgQkgwo8GcEGwemoTFt3FIO9ababBmaGwXIoBKZ+GTy0pP185beGg7Llih/NSHSV2XAs1lnznocSg==}
     engines: {node: '>= 8'}
@@ -4047,6 +4088,67 @@ packages:
       fastq: 1.17.1
     dev: true
 
+  /@nodelib/fs.walk@2.0.0:
+    resolution: {integrity: sha512-54voNDBobGdMl3BUXSu7UaDh1P85PGHWlJ5e0XhPugo1JulOyCtp2I+5ri4wplGDJ8QGwPEQW7/x3yTLU7yF1A==}
+    engines: {node: '>=16.14.0'}
+    dependencies:
+      '@nodelib/fs.scandir': 3.0.0
+      fastq: 1.17.1
+    dev: true
+
+  /@npmcli/git@5.0.4:
+    resolution: {integrity: sha512-nr6/WezNzuYUppzXRaYu/W4aT5rLxdXqEFupbh6e/ovlYFQ8hpu1UUPV3Ir/YTl+74iXl2ZOMlGzudh9ZPUchQ==}
+    engines: {node: ^16.14.0 || >=18.0.0}
+    dependencies:
+      '@npmcli/promise-spawn': 7.0.1
+      lru-cache: 10.2.0
+      npm-pick-manifest: 9.0.0
+      proc-log: 3.0.0
+      promise-inflight: 1.0.1
+      promise-retry: 2.0.1
+      semver: 7.6.0
+      which: 4.0.0
+    transitivePeerDependencies:
+      - bluebird
+    dev: true
+
+  /@npmcli/map-workspaces@3.0.4:
+    resolution: {integrity: sha512-Z0TbvXkRbacjFFLpVpV0e2mheCh+WzQpcqL+4xp49uNJOxOnIAPZyXtUxZ5Qn3QBTGKA11Exjd9a5411rBrhDg==}
+    engines: {node: ^14.17.0 || ^16.13.0 || >=18.0.0}
+    dependencies:
+      '@npmcli/name-from-folder': 2.0.0
+      glob: 10.3.10
+      minimatch: 9.0.3
+      read-package-json-fast: 3.0.2
+    dev: true
+
+  /@npmcli/name-from-folder@2.0.0:
+    resolution: {integrity: sha512-pwK+BfEBZJbKdNYpHHRTNBwBoqrN/iIMO0AiGvYsp3Hoaq0WbgGSWQR6SCldZovoDpY3yje5lkFUe6gsDgJ2vg==}
+    engines: {node: ^14.17.0 || ^16.13.0 || >=18.0.0}
+    dev: true
+
+  /@npmcli/package-json@5.0.0:
+    resolution: {integrity: sha512-OI2zdYBLhQ7kpNPaJxiflofYIpkNLi+lnGdzqUOfRmCF3r2l1nadcjtCYMJKv/Utm/ZtlffaUuTiAktPHbc17g==}
+    engines: {node: ^16.14.0 || >=18.0.0}
+    dependencies:
+      '@npmcli/git': 5.0.4
+      glob: 10.3.10
+      hosted-git-info: 7.0.1
+      json-parse-even-better-errors: 3.0.1
+      normalize-package-data: 6.0.0
+      proc-log: 3.0.0
+      semver: 7.6.0
+    transitivePeerDependencies:
+      - bluebird
+    dev: true
+
+  /@npmcli/promise-spawn@7.0.1:
+    resolution: {integrity: sha512-P4KkF9jX3y+7yFUxgcUdDtLy+t4OlDGuEBLNs57AZsfSfg+uV6MLndqGpnl4831ggaEdXwR50XFoZP4VFtHolg==}
+    engines: {node: ^16.14.0 || >=18.0.0}
+    dependencies:
+      which: 4.0.0
+    dev: true
+
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     resolution: {integrity: sha512-+1VkjdD0QBLPodGrJUeqarH8VAIvQODIbwh9XpP5Syisf7YoQgsJKPNFoqqLQlu+VQ/tVSshMR6loPMn8U+dPg==}
     engines: {node: '>=14'}
@@ -4054,6 +4156,130 @@ packages:
     dev: true
     optional: true
 
+  /@pnpm/constants@7.1.1:
+    resolution: {integrity: sha512-31pZqMtjwV+Vaq7MaPrT1EoDFSYwye3dp6BiHIGRJmVThCQwySRKM7hCvqqI94epNkqFAAYoWrNynWoRYosGdw==}
+    engines: {node: '>=16.14'}
+    dev: true
+
+  /@pnpm/core-loggers@9.0.6(@pnpm/logger@5.0.0):
+    resolution: {integrity: sha512-iK67SGbp+06bA/elpg51wygPFjNA7JKHtKkpLxqXXHw+AjFFBC3f2OznJsCIuDK6HdGi5UhHLYqo5QxJ2gMqJQ==}
+    engines: {node: '>=16.14'}
+    peerDependencies:
+      '@pnpm/logger': ^5.0.0
+    dependencies:
+      '@pnpm/logger': 5.0.0
+      '@pnpm/types': 9.4.2
+    dev: true
+
+  /@pnpm/error@5.0.3:
+    resolution: {integrity: sha512-ONJU5cUeoeJSy50qOYsMZQHTA/9QKmGgh1ATfEpCLgtbdwqUiwD9MxHNeXUYYI/pocBCz6r1ZCFqiQvO+8SUKA==}
+    engines: {node: '>=16.14'}
+    dependencies:
+      '@pnpm/constants': 7.1.1
+    dev: true
+
+  /@pnpm/fetching-types@5.0.0:
+    resolution: {integrity: sha512-o9gdO1v8Uc5P2fBBuW6GSpfTqIivQmQlqjQJdFiQX0m+tgxlrMRneIg392jZuc6fk7kFqjLheInlslgJfwY+4Q==}
+    engines: {node: '>=16.14'}
+    dependencies:
+      '@zkochan/retry': 0.2.0
+      node-fetch: 3.0.0-beta.9
+    transitivePeerDependencies:
+      - domexception
+    dev: true
+
+  /@pnpm/graceful-fs@3.2.0:
+    resolution: {integrity: sha512-vRoXJxscDpHak7YE9SqCkzfrayn+Lw+YueOeHIPEqkgokrHeYgYeONoc2kGh0ObHaRtNSsonozVfJ456kxLNvA==}
+    engines: {node: '>=16.14'}
+    dependencies:
+      graceful-fs: 4.2.11
+    dev: true
+
+  /@pnpm/logger@5.0.0:
+    resolution: {integrity: sha512-YfcB2QrX+Wx1o6LD1G2Y2fhDhOix/bAY/oAnMpHoNLsKkWIRbt1oKLkIFvxBMzLwAEPqnYWguJrYC+J6i4ywbw==}
+    engines: {node: '>=12.17'}
+    dependencies:
+      bole: 5.0.11
+      ndjson: 2.0.0
+    dev: true
+
+  /@pnpm/npm-package-arg@1.0.0:
+    resolution: {integrity: sha512-oQYP08exi6mOPdAZZWcNIGS+KKPsnNwUBzSuAEGWuCcqwMAt3k/WVCqVIXzBxhO5sP2b43og69VHmPj6IroKqw==}
+    engines: {node: '>=14.6'}
+    dependencies:
+      hosted-git-info: 4.1.0
+      semver: 7.6.0
+      validate-npm-package-name: 4.0.0
+    dev: true
+
+  /@pnpm/npm-resolver@18.1.1(@pnpm/logger@5.0.0):
+    resolution: {integrity: sha512-NptzncmMD5ZMimbjWkGpMzuBRhlCY+sh7mzypPdBOTNlh5hmEQe/VaRKjNK4V9/b0C/llElkvIePL6acybu86w==}
+    engines: {node: '>=16.14'}
+    peerDependencies:
+      '@pnpm/logger': ^5.0.0
+    dependencies:
+      '@pnpm/core-loggers': 9.0.6(@pnpm/logger@5.0.0)
+      '@pnpm/error': 5.0.3
+      '@pnpm/fetching-types': 5.0.0
+      '@pnpm/graceful-fs': 3.2.0
+      '@pnpm/logger': 5.0.0
+      '@pnpm/resolve-workspace-range': 5.0.1
+      '@pnpm/resolver-base': 11.1.0
+      '@pnpm/types': 9.4.2
+      '@zkochan/retry': 0.2.0
+      encode-registry: 3.0.1
+      load-json-file: 6.2.0
+      lru-cache: 10.2.0
+      normalize-path: 3.0.0
+      p-limit: 3.1.0
+      p-memoize: 4.0.1
+      parse-npm-tarball-url: 3.0.0
+      path-temp: 2.1.0
+      ramda: /@pnpm/ramda@0.28.1
+      rename-overwrite: 5.0.0
+      semver: 7.6.0
+      ssri: 10.0.5
+      version-selector-type: 3.0.0
+    transitivePeerDependencies:
+      - domexception
+    dev: true
+
+  /@pnpm/ramda@0.28.1:
+    resolution: {integrity: sha512-zcAG+lvU0fMziNeGXpPyCyCJYp5ZVrPElEE4t14jAmViaihohocZ+dDkcRIyAomox8pQsuZnv1EyHR+pOhmUWw==}
+    dev: true
+
+  /@pnpm/resolve-workspace-range@5.0.1:
+    resolution: {integrity: sha512-yQ0pMthlw8rTgS/C9hrjne+NEnnSNevCjtdodd7i15I59jMBYciHifZ/vjg0NY+Jl+USTc3dBE+0h/4tdYjMKg==}
+    engines: {node: '>=16.14'}
+    dependencies:
+      semver: 7.6.0
+    dev: true
+
+  /@pnpm/resolver-base@11.1.0:
+    resolution: {integrity: sha512-y2qKaj18pwe1VWc3YXEitdYFo+WqOOt60aqTUuOVkJAirUzz0DzuYh3Ifct4znYWPdgUXHaN5DMphNF5iL85rA==}
+    engines: {node: '>=16.14'}
+    dependencies:
+      '@pnpm/types': 9.4.2
+    dev: true
+
+  /@pnpm/types@9.4.2:
+    resolution: {integrity: sha512-g1hcF8Nv4gd76POilz9gD4LITAPXOe5nX4ijgr8ixCbLQZfcpYiMfJ+C1RlMNRUDo8vhlNB4O3bUlxmT6EAQXA==}
+    engines: {node: '>=16.14'}
+    dev: true
+
+  /@pnpm/workspace.pkgs-graph@2.0.15(@pnpm/logger@5.0.0):
+    resolution: {integrity: sha512-Txxd5FzzVfBfGCTngISaxFlJzZhzdS8BUrCEtAWJfZOFbQzpWy27rzkaS7TaWW2dHiFcCVYzPI/2vgxfeRansA==}
+    engines: {node: '>=16.14'}
+    dependencies:
+      '@pnpm/npm-package-arg': 1.0.0
+      '@pnpm/npm-resolver': 18.1.1(@pnpm/logger@5.0.0)
+      '@pnpm/resolve-workspace-range': 5.0.1
+      ramda: /@pnpm/ramda@0.28.1
+    transitivePeerDependencies:
+      - '@pnpm/logger'
+      - domexception
+    dev: true
+
   /@popperjs/core@2.11.8:
     resolution: {integrity: sha512-P1st0aksCrn9sGZhp8GMYwBnQsbvAWsZAX44oXNNvLHGqAOcoVxmjZiohstwQ7SqKnbR47akdNi+uleWD8+g6A==}
     dev: false
@@ -4918,6 +5144,16 @@ packages:
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     dev: true
 
+  /@snyk/github-codeowners@1.1.0:
+    resolution: {integrity: sha512-lGFf08pbkEac0NYgVf4hdANpAgApRjNByLXB+WBip3qj1iendOIyAwP2GKkKbQMNVy2r1xxDf0ssfWscoiC+Vw==}
+    engines: {node: '>=8.10'}
+    hasBin: true
+    dependencies:
+      commander: 4.1.1
+      ignore: 5.3.1
+      p-map: 4.0.0
+    dev: true
+
   /@socket.io/component-emitter@3.1.0:
     resolution: {integrity: sha512-+9jVqKhRSpsc591z5vX+X5Yyw+he/HCB4iQ/RYxw35CEPaY1gnsNE43nf9n9AaYjAQrTiI/mOwKUKdUs9vf7Xg==}
     dev: false
@@ -6281,6 +6517,10 @@ packages:
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     dev: false
 
+  /@types/picomatch@2.3.3:
+    resolution: {integrity: sha512-Yll76ZHikRFCyz/pffKGjrCwe/le2CDwOP5F210KQo27kpRE46U2rDnzikNlVn6/ezH3Mhn46bJMTfeVTtcYMg==}
+    dev: true
+
   /@types/pretty-hrtime@1.0.3:
     resolution: {integrity: sha512-nj39q0wAIdhwn7DGUyT9irmsKK1tV0bd5WFEhgpqNTMFZ8cE+jieuTphCW0tfdm47S2zVT5mr09B28b1chmQMA==}
     dev: true
@@ -7367,6 +7607,18 @@ packages:
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     dev: false
 
+  /@zkochan/retry@0.2.0:
+    resolution: {integrity: sha512-WhB+2B/ZPlW2Xy/kMJBrMbqecWXcbDDgn0K0wKBAgO2OlBTz1iLJrRWduo+DGGn0Akvz1Lu4Xvls7dJojximWw==}
+    engines: {node: '>=10'}
+    dev: true
+
+  /@zkochan/rimraf@2.1.3:
+    resolution: {integrity: sha512-mCfR3gylCzPC+iqdxEA6z5SxJeOgzgbwmyxanKriIne5qZLswDe/M43aD3p5MNzwzXRhbZg/OX+MpES6Zk1a6A==}
+    engines: {node: '>=12.10'}
+    dependencies:
+      rimraf: 3.0.2
+    dev: true
+
   /accepts@1.3.8:
     resolution: {integrity: sha512-PYAthTa2m2VKxuvSD3DPC/Gy+U+sOA1LAuT8mkmRuvw+NACSaeXEQ+NHcVF7rONl6qcaxV3Uuemwawk+7+SJLw==}
     engines: {node: '>= 0.6'}
@@ -7526,6 +7778,10 @@ packages:
       dequal: 2.0.3
     dev: true
 
+  /arity-n@1.0.4:
+    resolution: {integrity: sha512-fExL2kFDC1Q2DUOx3whE/9KoN66IzkY4b4zUHUBFM1ojEYjZZYDcUW3bek/ufGionX9giIKDC5redH2IlGqcQQ==}
+    dev: true
+
   /array-buffer-byte-length@1.0.1:
     resolution: {integrity: sha512-ahC5W1xgou+KTXix4sAO8Ki12Q+jf4i0+tmk3sC+zgcynshkHxzpXdImBehiUYKKKDwvfFiJl1tZt6ewscS1Mg==}
     engines: {node: '>= 0.4'}
@@ -7549,6 +7805,13 @@ packages:
       is-string: 1.0.7
     dev: true
 
+  /array-last@1.3.0:
+    resolution: {integrity: sha512-eOCut5rXlI6aCOS7Z7kCplKRKyiFQ6dHFBem4PwlwKeNFk2/XxTrhRh5T9PyaEWGy/NHTZWbY+nsZlNFJu9rYg==}
+    engines: {node: '>=0.10.0'}
+    dependencies:
+      is-number: 4.0.0
+    dev: true
+
   /array-union@2.1.0:
     resolution: {integrity: sha512-HGyxoOTYUyCM6stUe6EJgnd4EoewAI7zMdfqO+kGjnlZmBDz/cR5pf8r/cR4Wq60sL/p0IkcjUEEPwS3GFrIyw==}
     engines: {node: '>=8'}
@@ -7751,6 +8014,11 @@ packages:
       - supports-color
     dev: true
 
+  /babylon@6.18.0:
+    resolution: {integrity: sha512-q/UEjfGJ2Cm3oKV71DJz9d25TPnq5rhBVL2Q4fA5wcC3jcrdn7+SssEybFIxwAvvP+YCsCYNKughoF33GxgycQ==}
+    hasBin: true
+    dev: true
+
   /balanced-match@1.0.2:
     resolution: {integrity: sha512-3oSeUO0TMV67hN1AmbXsK4yaqU7tjiHlbxRDZOpH0KW9+CeX4bRAaX0Anxt0tx2MrpRpWwQaPwIlISEJhYU5Pw==}
     dev: true
@@ -7804,6 +8072,13 @@ packages:
       - supports-color
     dev: true
 
+  /bole@5.0.11:
+    resolution: {integrity: sha512-KB0Ye0iMAW5BnNbnLfMSQcnI186hKUzE2fpkZWqcxsoTR7eqzlTidSOMYPHJOn/yR7VGH7uSZp37qH9q2Et0zQ==}
+    dependencies:
+      fast-safe-stringify: 2.1.1
+      individual: 3.0.0
+    dev: true
+
   /boolean@3.2.0:
     resolution: {integrity: sha512-d0II/GO9uf9lfUHH2BQsjxzRJZBdsjgsBiW4BvhWk/3qoKwQFjIDVN19PfX8F2D/r9PCMTtLWjYVCFrpeYUzsw==}
     dev: false
@@ -7877,6 +8152,12 @@ packages:
       ieee754: 1.2.1
     dev: true
 
+  /builtins@5.0.1:
+    resolution: {integrity: sha512-qwVpFEHNfhYJIzNRBvd2C1kyo6jz3ZSMPyyuR47OPdiKWlbYnZNyDWuyR175qDnAJLiCo5fBBqPb3RiXgWlkOQ==}
+    dependencies:
+      semver: 7.6.0
+    dev: true
+
   /bytes@3.0.0:
     resolution: {integrity: sha512-pMhOfFDPiv9t5jjIXkHosWmkSyQbvsgEVNkz0ERHbuLh2T/7j4Mqqpz523Fe8MVY89KC6Sh/QfS2sM+SjgFDcw==}
     engines: {node: '>= 0.8'}
@@ -8119,6 +8400,11 @@ packages:
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+  /commander@4.1.1:
+    resolution: {integrity: sha512-NOKm8xhkzAjzFx8B2v5OAHT+u5pRQc2UCa2Vq9jYL/31o2wi9mxBA7LIFs3sV5VSC49z6pEhfbMULvShKj26WA==}
+    engines: {node: '>= 6'}
+    dev: true
+
   /commander@6.2.1:
     resolution: {integrity: sha512-U7VdrJFnJgo4xjrHpTzu0yrHPGImdsmD95ZlgYSEajAn2JKzDhDTPG9kBTefmObL2w/ngeZnilk+OV9CG3d7UA==}
     engines: {node: '>= 6'}
@@ -8142,6 +8428,12 @@ packages:
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     dev: false
 
+  /compose-function@3.0.3:
+    resolution: {integrity: sha512-xzhzTJ5eC+gmIzvZq+C3kCJHsp9os6tJkrigDRZclyGtOKINbZtE8n1Tzmeh32jW+BUDPbvZpibwvJHBLGMVwg==}
+    dependencies:
+      arity-n: 1.0.4
+    dev: true
+
   /compressible@2.0.18:
     resolution: {integrity: sha512-AF3r7P5dWxL8MxyITRMlORQNaOA2IkAFaTr4k7BUumjPtRpGDTZpl0Pb1XCO6JeDCBdp126Cgs9sMxqSjgYyRg==}
     engines: {node: '>= 0.6'}
@@ -8377,6 +8669,11 @@ packages:
       d3-transition: 3.0.1(d3-selection@3.0.0)
     dev: false
 
+  /data-uri-to-buffer@3.0.1:
+    resolution: {integrity: sha512-WboRycPNsVw3B3TL559F7kuBUM4d8CgMEvk6xEJlOp7OBPjt6G7z8WMWlD2rOFZLk6OYfFIUGsCOWzcQH9K2og==}
+    engines: {node: '>= 6'}
+    dev: true
+
   /date-fns@2.30.0:
     resolution: {integrity: sha512-fnULvOpxnC5/Vg3NCiWelDsLiUc9bRwAPs/+LfTLNvetFCtCTN+yQz15C/fs4AwX1R9K5GLtLfn8QW+dWisaAw==}
     engines: {node: '>=0.11'}
@@ -8467,6 +8764,10 @@ packages:
     engines: {node: '>=4.0.0'}
     dev: true
 
+  /deep-freeze@0.0.1:
+    resolution: {integrity: sha512-Z+z8HiAvsGwmjqlphnHW5oz6yWlOwu6EQfFTjmeTWlDeda3FS2yv3jhq35TX/ewmsnqB+RX2IdsIOyjJCQN5tg==}
+    dev: true
+
   /deep-is@0.1.4:
     resolution: {integrity: sha512-oIPzksmTg4/MriiaYGO+okXDT7ztn/w3Eptv/+gSIdMdKsJo0u4CfYNFJPy+4SKMuCqGw2wxnA+URMg3t8a/bQ==}
     dev: true
@@ -8809,6 +9110,14 @@ packages:
     resolution: {integrity: sha512-I88TYZWc9XiYHRQ4/3c5rjjfgkjhLyW2luGIheGERbNQ6OY7yTybanSpDXZa8y7VUP9YmDcYa+eyq4ca7iLqWA==}
     dev: true
 
+  /easy-table@1.2.0:
+    resolution: {integrity: sha512-OFzVOv03YpvtcWGe5AayU5G2hgybsg3iqA6drU8UaoZyB9jLGMTrz9+asnLp/E+6qPh88yEI1gvyZFZ41dmgww==}
+    dependencies:
+      ansi-regex: 5.0.1
+    optionalDependencies:
+      wcwidth: 1.0.1
+    dev: true
+
   /ee-first@1.1.1:
     resolution: {integrity: sha512-WMwm9LhRUo+WUaRN+vRuETqG89IgZphVSNkdFgeb6sS/E4OrDIN7t48CAewSHXc6C8lefD8KKfr5vY61brQlow==}
     dev: true
@@ -8833,6 +9142,13 @@ packages:
     resolution: {integrity: sha512-L18DaJsXSUk2+42pv8mLs5jJT2hqFkFE4j21wOmgbUqsZ2hL72NsUU785g9RXgo3s0ZNgVl42TiHp3ZtOv/Vyg==}
     dev: true
 
+  /encode-registry@3.0.1:
+    resolution: {integrity: sha512-6qOwkl1g0fv0DN3Y3ggr2EaZXN71aoAqPp3p/pVaWSBSIo+YjLOWN61Fva43oVyQNPf7kgm8lkudzlzojwE2jw==}
+    engines: {node: '>=10'}
+    dependencies:
+      mem: 8.1.1
+    dev: true
+
   /encodeurl@1.0.2:
     resolution: {integrity: sha512-TPJXq8JqFaVYm2CWmPvnP2Iyo4ZSM7/QKcSmuMLDObfpH5fi7RUGmd/rTDf+rut/saiDiQEeVTNgAmJEdAOx0w==}
     engines: {node: '>= 0.8'}
@@ -8882,6 +9198,10 @@ packages:
     hasBin: true
     dev: true
 
+  /err-code@2.0.3:
+    resolution: {integrity: sha512-2bmlRpNKBxT/CRmPOlyISQpNj+qSeYvcym/uT0Jx2bMOlKLtSy1ZmLuVxSEKKyor/N5yhvp/ZiG1oE3DEYMSFA==}
+    dev: true
+
   /error-ex@1.3.2:
     resolution: {integrity: sha512-7dFHNmqeFSEt2ZBsCriorKnn3Z2pj+fd9kmI6QoWw4//DL+icEBfc0U7qJCisqrTsKTjw4fNFy2pW9OqStD84g==}
     dependencies:
@@ -9559,6 +9879,10 @@ packages:
       boolean: 3.2.0
     dev: false
 
+  /fast-safe-stringify@2.1.1:
+    resolution: {integrity: sha512-W+KJc2dmILlPplD/H4K9l9LcAHAfPtP6BY84uVLXQ6Evcz9Lcg33Y2z1IVblT6xdY54PXYVHEv+0Wpq8Io6zkA==}
+    dev: true
+
   /fast-shallow-equal@1.0.0:
     resolution: {integrity: sha512-HPtaa38cPgWvaCFmRNhlc6NG7pv6NUHqjPgVAkWGoB9mQMwYB27/K0CvOM5Czy+qpT3e8XJ6Q4aPAnzpNpzNaw==}
     dev: false
@@ -9585,6 +9909,16 @@ packages:
       pend: 1.2.0
     dev: true
 
+  /fetch-blob@2.1.2:
+    resolution: {integrity: sha512-YKqtUDwqLyfyMnmbw8XD6Q8j9i/HggKtPEI+pZ1+8bvheBu78biSmNaXWusx1TauGqtUUGx/cBb1mKdq2rLYow==}
+    engines: {node: ^10.17.0 || >=12.3.0}
+    peerDependencies:
+      domexception: '*'
+    peerDependenciesMeta:
+      domexception:
+        optional: true
+    dev: true
+
   /fetch-retry@5.0.6:
     resolution: {integrity: sha512-3yurQZ2hD9VISAhJJP9bpYFNQrHHBXE2JxxjY5aLEcDi46RmAzJE2OC9FAde0yis5ElW0jTTzs0zfg/Cca4XqQ==}
     dev: true
@@ -9645,6 +9979,15 @@ packages:
       to-regex-range: 5.0.1
     dev: true
 
+  /filter-iterator@0.0.1:
+    resolution: {integrity: sha512-v4lhL7Qa8XpbW3LN46CEnmhGk3eHZwxfNl5at20aEkreesht4YKb/Ba3BUIbnPhAC/r3dmu7ABaGk6MAvh2alA==}
+    dev: true
+
+  /filter-obj@1.1.0:
+    resolution: {integrity: sha512-8rXg1ZnX7xzy2NGDVkBVaAy+lSlPNwad13BtgSlLuxfIslyt5Vg64U7tFcCt4WS1R0hvtnQybT/IyCkGZ3DpXQ==}
+    engines: {node: '>=0.10.0'}
+    dev: true
+
   /filter-obj@5.1.0:
     resolution: {integrity: sha512-qWeTREPoT7I0bifpPUXtxkZJ1XJzxWtfoWWkdVGqa+eCr3SHW/Ocp89o8vLvbUuQnadybJpjOKu4V+RwO6sGng==}
     engines: {node: '>=14.16'}
@@ -9825,6 +10168,15 @@ packages:
     resolution: {integrity: sha512-y6OAwoSIf7FyjMIv94u+b5rdheZEjzR63GTyZJm5qh4Bi+2YgwLCcI/fPFZkL5PSixOt6ZNKm+w+Hfp/Bciwow==}
     dev: true
 
+  /fs-extra@10.1.0:
+    resolution: {integrity: sha512-oRXApq54ETRj4eMiFzGnHWGy+zo5raudjuxN0b8H7s/RU2oW0Wvsx9O0ACRN/kRq9E8Vu/ReskGB5o3ji+FzHQ==}
+    engines: {node: '>=12'}
+    dependencies:
+      graceful-fs: 4.2.11
+      jsonfile: 6.1.0
+      universalify: 2.0.1
+    dev: true
+
   /fs-extra@11.1.1:
     resolution: {integrity: sha512-MGIE4HOvQCeUCzmlHs0vXpih4ysz4wg9qiSAu6cd42lVwPbTM1TjV7RusoyQqMmk/95gdQZX72u+YW+c3eEpFQ==}
     engines: {node: '>=14.14'}
@@ -10132,6 +10484,10 @@ packages:
     engines: {node: '>=8'}
     dev: true
 
+  /has-own-property@0.1.0:
+    resolution: {integrity: sha512-14qdBKoonU99XDhWcFKZTShK+QV47qU97u8zzoVo9cL5TZ3BmBHXogItSt9qJjR0KUMFRhcCW8uGIGl8nkl7Aw==}
+    dev: true
+
   /has-property-descriptors@1.0.2:
     resolution: {integrity: sha512-55JNKuIW+vq4Ke1BjOTjM2YctQIvCT7GFzHwmfZPGo5wnrgkid0YQtnAleFSqumZm4az3n2BS+erby5ipJdgrg==}
     dependencies:
@@ -10173,6 +10529,20 @@ packages:
     resolution: {integrity: sha512-mxIDAb9Lsm6DoOJ7xH+5+X4y1LU/4Hi50L9C5sIswK3JzULS4bwk1FvjdBgvYR4bzT4tuUQiC15FE2f5HbLvYw==}
     dev: true
 
+  /hosted-git-info@4.1.0:
+    resolution: {integrity: sha512-kyCuEOWjJqZuDbRHzL8V93NzQhwIB71oFWSyzVo+KPZI+pnQPPxucdkrOZvkLRnrf5URsQM+IJ09Dw29cRALIA==}
+    engines: {node: '>=10'}
+    dependencies:
+      lru-cache: 6.0.0
+    dev: true
+
+  /hosted-git-info@7.0.1:
+    resolution: {integrity: sha512-+K84LB1DYwMHoHSgaOY/Jfhw3ucPmSET5v98Ke/HdNSw4a0UktWzyW1mjhjpuxxTqOOsfWT/7iVshHmVZ4IpOA==}
+    engines: {node: ^16.14.0 || >=18.0.0}
+    dependencies:
+      lru-cache: 10.2.0
+    dev: true
+
   /html-parse-stringify@3.0.1:
     resolution: {integrity: sha512-KknJ50kTInJ7qIScF3jeaFRpMpE8/lfiTdzf/twXyPBLAGrLRTmkz3AdTnKeh40X8k9L2fdYwEp/42WGXIRGcg==}
     dependencies:
@@ -10244,6 +10614,10 @@ packages:
     resolution: {integrity: sha512-8Sb3veuYCyrZL+VBt9LJfZjLUPWVvqn8tG28VqYNFCo43KHcKuq+b4EiXGeuaLAQWL2YmyDgMp2aSpH9JHsEQg==}
     dev: false
 
+  /identity-function@1.0.0:
+    resolution: {integrity: sha512-kNrgUK0qI+9qLTBidsH85HjDLpZfrrS0ElquKKe/fJFdB3D7VeKdXXEvOPDUHSHOzdZKCAAaQIWWyp0l2yq6pw==}
+    dev: true
+
   /ieee754@1.2.1:
     resolution: {integrity: sha512-dcyqhDvX1C46lXZcVqCpK+FtMRQVdIMN6/Df5js2zouUsqG7I6sFxitIC+7KYK29KdXOLHdu9zL4sFnoVQnqaA==}
     dev: true
@@ -10283,6 +10657,10 @@ packages:
     resolution: {integrity: sha512-bup+4tap3Hympa+JBJUG7XuOsdNQ6fxt0MHyXMKuLBKn0OqsTfvUxkUrroEX1+B2VsSHvCjiIcZVxRtYa4nllA==}
     dev: true
 
+  /individual@3.0.0:
+    resolution: {integrity: sha512-rUY5vtT748NMRbEMrTNiFfy29BgGZwGXUi2NFUVMWQrogSLzlJvQV9eeMWi+g1aVaQ53tpyLAQtd5x/JH0Nh1g==}
+    dev: true
+
   /inflight@1.0.6:
     resolution: {integrity: sha512-k92I/b08q4wvFscXCLvqfsHCrjrF7yiXsQuIVvVE7N82W3+aqpzuUdBbfhWcy/FZR3/4IgflMgKLOsvPDrGCJA==}
     dependencies:
@@ -10447,6 +10825,11 @@ packages:
     engines: {node: '>=8'}
     dev: true
 
+  /is-iterable@1.1.1:
+    resolution: {integrity: sha512-EdOZCr0NsGE00Pot+x1ZFx9MJK3C6wy91geZpXwvwexDLJvA4nzYyZf7r+EIwSeVsOLDdBz7ATg9NqKTzuNYuQ==}
+    engines: {node: '>= 4'}
+    dev: true
+
   /is-map@2.0.2:
     resolution: {integrity: sha512-cOZFQQozTha1f4MxLFzlgKYPTyj26picdZTx82hbc/Xf4K/tZOOXSCkMvU4pKioRXGDLJRn0GM7Upe7kR721yg==}
     dev: true
@@ -10471,6 +10854,11 @@ packages:
       has-tostringtag: 1.0.2
     dev: true
 
+  /is-number@4.0.0:
+    resolution: {integrity: sha512-rSklcAIlf1OmFdyAqbnWTLVelsQ58uvZ66S/ZyawjWqIviTWCjg2PzVGw8WUA+nNuPTqb4wgA+NszrJ+08LlgQ==}
+    engines: {node: '>=0.10.0'}
+    dev: true
+
   /is-number@7.0.0:
     resolution: {integrity: sha512-41Cifkg6e8TylSpdtTpeLVMqvSBEVzTttHvERD741+pnZ8ANv0004MRL43QKPDlK9cGvNp6NZWZUBlbGXYxxng==}
     engines: {node: '>=0.12.0'}
@@ -10611,6 +10999,11 @@ packages:
     resolution: {integrity: sha512-RHxMLp9lnKHGHRng9QFhRCMbYAcVpn69smSGcq3f36xjgVVWThj4qqLbTLlq7Ssj8B+fIQ1EuCEGI2lKsyQeIw==}
     dev: true
 
+  /isexe@3.1.1:
+    resolution: {integrity: sha512-LpB/54B+/2J5hqQ7imZHfdU31OlgQqx7ZicVlkm9kzg9/w8GKLEcFfJl/t7DCEDueOyBAD6zCCwTO6Fzs0NoEQ==}
+    engines: {node: '>=16'}
+    dev: true
+
   /isobject@3.0.1:
     resolution: {integrity: sha512-WhB9zCku7EGTj/HQQRz5aUQEUeoQZH2bWcltRErOpymJ4boYE6wL9Tbr23krRPSZ+C5zqNSrSw+Cc7sZZ4b7vg==}
     engines: {node: '>=0.10.0'}
@@ -10634,6 +11027,11 @@ packages:
       - supports-color
     dev: true
 
+  /iterable-lookahead@1.0.0:
+    resolution: {integrity: sha512-hJnEP2Xk4+44DDwJqUQGdXal5VbyeWLaPyDl2AQc242Zr7iqz4DgpQOrEzglWVMGHMDCkguLHEKxd1+rOsmgSQ==}
+    engines: {node: '>=4'}
+    dev: true
+
   /iterator.prototype@1.1.2:
     resolution: {integrity: sha512-DR33HMMr8EzwuRL8Y9D3u2BMj8+RqSE850jfGu59kS7tbmPLzGkZmVSfyCFSDxuZiEY6Rzt3T2NA/qU+NwVj1w==}
     dependencies:
@@ -10727,6 +11125,11 @@ packages:
       supports-color: 8.1.1
     dev: true
 
+  /jiti@1.21.0:
+    resolution: {integrity: sha512-gFqAIbuKyyso/3G2qhiO2OM6shY6EPP/R0+mkDbyspxKazh8BXDC5FiFsUjlczgdNz/vfra0da2y+aHrusLG/Q==}
+    hasBin: true
+    dev: true
+
   /jju@1.4.0:
     resolution: {integrity: sha512-8wb9Yw966OSxApiCt0K3yNJL8pnNeIv+OEq2YMidz4FKP6nonSRoOXc80iXY4JaN2FC11B9qsNmDsm+ZOfMROA==}
     dev: true
@@ -10809,6 +11212,11 @@ packages:
   /json-parse-even-better-errors@2.3.1:
     resolution: {integrity: sha512-xyFwyhro/JEof6Ghe2iz2NcXoj2sloNsWr/XsERDK/oiPCfaNhl5ONfp+jQdAZRQQ0IJWNzH9zIZF7li91kh2w==}
 
+  /json-parse-even-better-errors@3.0.1:
+    resolution: {integrity: sha512-aatBvbL26wVUCLmbWdCpeu9iF5wOyWpagiKkInA+kfws3sWdBrTnsvN2CKcyCYyUrc7rebNBlK6+kteg7ksecg==}
+    engines: {node: ^14.17.0 || ^16.13.0 || >=18.0.0}
+    dev: true
+
   /json-schema-traverse@0.4.1:
     resolution: {integrity: sha512-xbbCH5dCYU5T8LcEhhuh7HJ88HXuW3qsI3Y0zOZFKfZEHcpWiHU/Jxzk629Brsab/mMiHQti9wMP+845RPe3Vg==}
     dev: true
@@ -10817,6 +11225,10 @@ packages:
     resolution: {integrity: sha512-Bdboy+l7tA3OGW6FjyFHWkP5LuByj1Tk33Ljyq0axyzdk9//JSi2u3fP1QSmd1KNwq6VOKYGlAu87CisVir6Pw==}
     dev: true
 
+  /json-stringify-safe@5.0.1:
+    resolution: {integrity: sha512-ZClg6AaYvamvYEE82d3Iyd3vSSIjQ+odgjaTzRuO3s7toCdFKczob2i0zCh7JE8kWn17yvAWhUVxvqGwUalsRA==}
+    dev: true
+
   /json5@1.0.2:
     resolution: {integrity: sha512-g1MWMLBiz8FKi1e4w0UyVL3w+iJceWAFBAaBnnGKOpNa5f8TLktkbre1+s6oICydWAm+HRUGTmI+//xv2hvXYA==}
     hasBin: true
@@ -10889,6 +11301,44 @@ packages:
     engines: {node: '>= 8'}
     dev: false
 
+  /knip@5.0.2(@types/node@20.11.19)(typescript@5.3.3):
+    resolution: {integrity: sha512-ylmXi/CaR1rjOl8KqLsei7075cCsHttMNFwoYlBM7WMvd2Rd4oOfic9KqJFkDONXedsEsiiwnI3+u6GT6KOUuw==}
+    engines: {node: '>=18.6.0'}
+    hasBin: true
+    peerDependencies:
+      '@types/node': '>=18'
+      typescript: '>=5.0.4'
+    dependencies:
+      '@ericcornelissen/bash-parser': 0.5.2
+      '@nodelib/fs.walk': 2.0.0
+      '@npmcli/map-workspaces': 3.0.4
+      '@npmcli/package-json': 5.0.0
+      '@pnpm/logger': 5.0.0
+      '@pnpm/workspace.pkgs-graph': 2.0.15(@pnpm/logger@5.0.0)
+      '@snyk/github-codeowners': 1.1.0
+      '@types/node': 20.11.19
+      '@types/picomatch': 2.3.3
+      easy-table: 1.2.0
+      fast-glob: 3.3.2
+      jiti: 1.21.0
+      js-yaml: 4.1.0
+      micromatch: 4.0.5
+      minimist: 1.2.8
+      picocolors: 1.0.0
+      picomatch: 4.0.1
+      pretty-ms: 9.0.0
+      semver: 7.6.0
+      smol-toml: 1.1.4
+      strip-json-comments: 5.0.1
+      summary: 2.1.0
+      typescript: 5.3.3
+      zod: 3.22.4
+      zod-validation-error: 3.0.2(zod@3.22.4)
+    transitivePeerDependencies:
+      - bluebird
+      - domexception
+    dev: true
+
   /kolorist@1.8.0:
     resolution: {integrity: sha512-Y+60/zizpJ3HRH8DCss+q95yr6145JXZo46OTpFvDZWLfRCE4qChOyk1b26nMaNpfHHgxagk9dXT5OP0Tfe+dQ==}
     dev: true
@@ -10930,6 +11380,16 @@ packages:
       ts-error: 1.0.6
     dev: false
 
+  /load-json-file@6.2.0:
+    resolution: {integrity: sha512-gUD/epcRms75Cw8RT1pUdHugZYM5ce64ucs2GEISABwkRsOQr0q2wm/MV2TKThycIe5e0ytRweW2RZxclogCdQ==}
+    engines: {node: '>=8'}
+    dependencies:
+      graceful-fs: 4.2.11
+      parse-json: 5.2.0
+      strip-bom: 4.0.0
+      type-fest: 0.6.0
+    dev: true
+
   /load-tsconfig@0.2.5:
     resolution: {integrity: sha512-IXO6OCs9yg8tMKzfPZ1YmheJbZCiEsnBdcB03l0OcfK9prKnJb96siuHCr5Fl37/yo9DnKU+TLpxzTUspw9shg==}
     engines: {node: ^12.20.0 || ^14.13.1 || >=16.0.0}
@@ -10969,6 +11429,10 @@ packages:
     resolution: {integrity: sha512-mKnC+QJ9pWVzv+C4/U3rRsHapFfHvQFoFB92e52xeyGMcX6/OlIl78je1u8vePzYZSkkogMPJ2yjxxsb89cxyw==}
     dev: false
 
+  /lodash.curry@4.1.1:
+    resolution: {integrity: sha512-/u14pXGviLaweY5JI0IUzgzF2J6Ne8INyzAZjImcryjgkZ+ebruBxy2/JaOOkTqScddcYtakjhSaeemV8lR0tA==}
+    dev: true
+
   /lodash.debounce@4.0.8:
     resolution: {integrity: sha512-FT1yDzDYEoYWhnSGnpE/4Kj1fLZkDFyqRb7fNt6FdYOSxlUWAtp42Eh6Wb0rGIv/m9Bgo7x4GhQbm5Ys4SG5ow==}
     dev: true
@@ -11073,6 +11537,12 @@ packages:
       - supports-color
     dev: true
 
+  /magic-string@0.16.0:
+    resolution: {integrity: sha512-c4BEos3y6G2qO0B9X7K0FVLOPT9uGrjYwYRLFmDqyl5YMboUviyecnXWp94fJTSMwPw2/sf+CEYt5AGpmklkkQ==}
+    dependencies:
+      vlq: 0.2.3
+    dev: true
+
   /magic-string@0.27.0:
     resolution: {integrity: sha512-8UnnX2PeRAPZuN12svgR9j7M1uWMovg/CEnIwIG0LFkXSJJe4PdfUGiTGl8V9bsBHFUtfVINcSyYxd7q+kx9fA==}
     engines: {node: '>=12'}
@@ -11108,6 +11578,18 @@ packages:
       tmpl: 1.0.5
     dev: true
 
+  /map-age-cleaner@0.1.3:
+    resolution: {integrity: sha512-bJzx6nMoP6PDLPBFmg7+xRKeFZvFboMrGlxmNj9ClvX53KrmvM5bXFXEWjbz4cz1AFn+jWJ9z/DJSz7hrs0w3w==}
+    engines: {node: '>=6'}
+    dependencies:
+      p-defer: 1.0.0
+    dev: true
+
+  /map-obj@2.0.0:
+    resolution: {integrity: sha512-TzQSV2DiMYgoF5RycneKVUzIa9bQsj/B3tTgsE3dOGqlzHnGIDaC7XBE7grnA+8kZPnfqSGFe95VHc2oc0VFUQ==}
+    engines: {node: '>=4'}
+    dev: true
+
   /map-or-similar@1.5.0:
     resolution: {integrity: sha512-0aF7ZmVon1igznGI4VS30yugpduQW3y3GkcgGJOp7d8x8QrizhigUxjI/m2UojsXXto+jLAH3KSz+xOJTiORjg==}
     dev: true
@@ -11140,6 +11622,22 @@ packages:
     engines: {node: '>= 0.6'}
     dev: true
 
+  /mem@6.1.1:
+    resolution: {integrity: sha512-Ci6bIfq/UgcxPTYa8dQQ5FY3BzKkT894bwXWXxC/zqs0XgMO2cT20CGkOqda7gZNkmK5VP4x89IGZ6K7hfbn3Q==}
+    engines: {node: '>=8'}
+    dependencies:
+      map-age-cleaner: 0.1.3
+      mimic-fn: 3.1.0
+    dev: true
+
+  /mem@8.1.1:
+    resolution: {integrity: sha512-qFCFUDs7U3b8mBDPyz5EToEKoAkgCzqquIgi9nkkR9bixxOVOre+09lbuH7+9Kn2NFpm56M3GUWVbU2hQgdACA==}
+    engines: {node: '>=10'}
+    dependencies:
+      map-age-cleaner: 0.1.3
+      mimic-fn: 3.1.0
+    dev: true
+
   /memoize-one@6.0.0:
     resolution: {integrity: sha512-rkpe71W0N0c0Xz6QD0eJETuWAJGnJ9afsl1srmwPrI+yBCkge5EycXXbYRyvL29zZVUWQCY7InPRCv3GDXuZNw==}
     dev: false
@@ -11205,6 +11703,11 @@ packages:
     engines: {node: '>=6'}
     dev: true
 
+  /mimic-fn@3.1.0:
+    resolution: {integrity: sha512-Ysbi9uYW9hFyfrThdDEQuykN4Ey6BuwPD2kpI5ES/nFTDn/98yxYNLZJcgUAKPT/mcrLLKaGzJR9YVxJrIdASQ==}
+    engines: {node: '>=8'}
+    dev: true
+
   /mimic-fn@4.0.0:
     resolution: {integrity: sha512-vqiC06CuhBTUdZH+RYl8sFrL096vA45Ok5ISO6sE/Mr1jRbGH4Csnhi8f3wKVl7x8mO4Au7Ir9D3Oyv1VYMFJw==}
     engines: {node: '>=12'}
@@ -11379,6 +11882,18 @@ packages:
     resolution: {integrity: sha512-OWND8ei3VtNC9h7V60qff3SVobHr996CTwgxubgyQYEpg290h9J0buyECNNJexkFm5sOajh5G116RYA1c8ZMSw==}
     dev: true
 
+  /ndjson@2.0.0:
+    resolution: {integrity: sha512-nGl7LRGrzugTtaFcJMhLbpzJM6XdivmbkdlaGcrk/LXg2KL/YBC6z1g70xh0/al+oFuVFP8N8kiWRucmeEH/qQ==}
+    engines: {node: '>=10'}
+    hasBin: true
+    dependencies:
+      json-stringify-safe: 5.0.1
+      minimist: 1.2.8
+      readable-stream: 3.6.2
+      split2: 3.2.2
+      through2: 4.0.2
+    dev: true
+
   /nearley@2.20.1:
     resolution: {integrity: sha512-+Mc8UaAebFzgV+KpI5n7DasuuQCHA89dmwm7JXw3TV43ukfNQ9DnBH3Mdb2g/I4Fdxc26pwimBWvjIw0UAILSQ==}
     hasBin: true
@@ -11425,6 +11940,16 @@ packages:
     dependencies:
       whatwg-url: 5.0.0
 
+  /node-fetch@3.0.0-beta.9:
+    resolution: {integrity: sha512-RdbZCEynH2tH46+tj0ua9caUHVWrd/RHnRfvly2EVdqGmI3ndS1Vn/xjm5KuGejDt2RNDQsVRLPNd2QPwcewVg==}
+    engines: {node: ^10.17 || >=12.3}
+    dependencies:
+      data-uri-to-buffer: 3.0.1
+      fetch-blob: 2.1.2
+    transitivePeerDependencies:
+      - domexception
+    dev: true
+
   /node-int64@0.4.0:
     resolution: {integrity: sha512-O5lz91xSOeoXP6DulyHfllpq+Eg00MWitZIbtPfoSEvqIHdl5gfcY6hYzDWnj0qD5tz52PI08u9qUvSVeUBeHw==}
     dev: true
@@ -11456,11 +11981,53 @@ packages:
       validate-npm-package-license: 3.0.4
     dev: true
 
+  /normalize-package-data@6.0.0:
+    resolution: {integrity: sha512-UL7ELRVxYBHBgYEtZCXjxuD5vPxnmvMGq0jp/dGPKKrN7tfsBh2IY7TlJ15WWwdjRWD3RJbnsygUurTK3xkPkg==}
+    engines: {node: ^16.14.0 || >=18.0.0}
+    dependencies:
+      hosted-git-info: 7.0.1
+      is-core-module: 2.13.1
+      semver: 7.6.0
+      validate-npm-package-license: 3.0.4
+    dev: true
+
   /normalize-path@3.0.0:
     resolution: {integrity: sha512-6eZs5Ls3WtCisHWp9S2GUy8dqkpGi4BVSz3GaqiE6ezub0512ESztXUwUB6C6IKbQkY2Pnb/mD4WYojCRwcwLA==}
     engines: {node: '>=0.10.0'}
     dev: true
 
+  /npm-install-checks@6.3.0:
+    resolution: {integrity: sha512-W29RiK/xtpCGqn6f3ixfRYGk+zRyr+Ew9F2E20BfXxT5/euLdA/Nm7fO7OeTGuAmTs30cpgInyJ0cYe708YTZw==}
+    engines: {node: ^14.17.0 || ^16.13.0 || >=18.0.0}
+    dependencies:
+      semver: 7.6.0
+    dev: true
+
+  /npm-normalize-package-bin@3.0.1:
+    resolution: {integrity: sha512-dMxCf+zZ+3zeQZXKxmyuCKlIDPGuv8EF940xbkC4kQVDTtqoh6rJFO+JTKSA6/Rwi0getWmtuy4Itup0AMcaDQ==}
+    engines: {node: ^14.17.0 || ^16.13.0 || >=18.0.0}
+    dev: true
+
+  /npm-package-arg@11.0.1:
+    resolution: {integrity: sha512-M7s1BD4NxdAvBKUPqqRW957Xwcl/4Zvo8Aj+ANrzvIPzGJZElrH7Z//rSaec2ORcND6FHHLnZeY8qgTpXDMFQQ==}
+    engines: {node: ^16.14.0 || >=18.0.0}
+    dependencies:
+      hosted-git-info: 7.0.1
+      proc-log: 3.0.0
+      semver: 7.6.0
+      validate-npm-package-name: 5.0.0
+    dev: true
+
+  /npm-pick-manifest@9.0.0:
+    resolution: {integrity: sha512-VfvRSs/b6n9ol4Qb+bDwNGUXutpy76x6MARw/XssevE0TnctIKcmklJZM5Z7nqs5z5aW+0S63pgCNbpkUNNXBg==}
+    engines: {node: ^16.14.0 || >=18.0.0}
+    dependencies:
+      npm-install-checks: 6.3.0
+      npm-normalize-package-bin: 3.0.1
+      npm-package-arg: 11.0.1
+      semver: 7.6.0
+    dev: true
+
   /npm-run-path@4.0.1:
     resolution: {integrity: sha512-S48WzZW777zhNIrn7gxOlISNAqi9ZC/uQFnRdbeIHhZhCA6UqpkOT8T1G7BvfdgP4Er8gF4sUbaS0i7QvIfCWw==}
     engines: {node: '>=8'}
@@ -11506,6 +12073,15 @@ packages:
     resolution: {integrity: sha512-NuAESUOUMrlIXOfHKzD6bpPu3tYt3xvjNdRIQ+FeT0lNb4K8WR70CaDxhuNguS2XG+GjkyMwOzsN5ZktImfhLA==}
     engines: {node: '>= 0.4'}
 
+  /object-pairs@0.1.0:
+    resolution: {integrity: sha512-3ECr6K831I4xX/Mduxr9UC+HPOz/d6WKKYj9p4cmC8Lg8p7g8gitzsxNX5IWlSIgFWN/a4JgrJaoAMKn20oKwA==}
+    dev: true
+
+  /object-values@1.0.0:
+    resolution: {integrity: sha512-+8hwcz/JnQ9EpLIXzN0Rs7DLsBpJNT/xYehtB/jU93tHYr5BFEO8E+JGQNOSqE7opVzz5cGksKFHt7uUJVLSjQ==}
+    engines: {node: '>=0.10.0'}
+    dev: true
+
   /object.assign@4.1.5:
     resolution: {integrity: sha512-byy+U7gp+FVwmyzKPYhW2h5l3crpmGsxl7X2s8y43IgxvG4g3QZ6CffDtsNQy1WsmZpQbO+ybo0AlW7TY6DcBQ==}
     engines: {node: '>= 0.4'}
@@ -11662,6 +12238,11 @@ packages:
     resolution: {integrity: sha512-CWVC2dwS07XZfLHDm5GmZN1iYggiJ8Vufnvzwt0gwR9Yz1hVckKeTxg7VILZeYVGhDYJHZ1Xc8Xfys5dWZ1qiA==}
     dev: false
 
+  /p-defer@1.0.0:
+    resolution: {integrity: sha512-wB3wfAxZpk2AzOfUMJNL+d36xothRSyj8EXOa4f6GMqYDN9BJaaSISbsk+wS9abmnebVw95C2Kb5t85UmpCxuw==}
+    engines: {node: '>=4'}
+    dev: true
+
   /p-limit@2.3.0:
     resolution: {integrity: sha512-//88mFWSJx8lxCzwdAABTJL2MyWB12+eIY7MDL2SqLmAkeKU9qxRvWuSyTjm3FUmpBEMuFfckAIqEaVGUDxb6w==}
     engines: {node: '>=6'}
@@ -11711,6 +12292,14 @@ packages:
       aggregate-error: 3.1.0
     dev: true
 
+  /p-memoize@4.0.1:
+    resolution: {integrity: sha512-km0sP12uE0dOZ5qP+s7kGVf07QngxyG0gS8sYFvFWhqlgzOsSy+m71aUejf/0akxj5W7gE//2G74qTv6b4iMog==}
+    engines: {node: '>=10'}
+    dependencies:
+      mem: 6.1.1
+      mimic-fn: 3.1.0
+    dev: true
+
   /p-try@2.2.0:
     resolution: {integrity: sha512-R4nPAVTAU0B9D35/Gk3uJf/7XYbQcyohSKdvAxIRSNghFl4e71hVoGnBNQz9cWaXxO2I10KTC+3jMdvvoKw6dQ==}
     engines: {node: '>=6'}
@@ -11740,6 +12329,18 @@ packages:
     engines: {node: '>=6'}
     dev: true
 
+  /parse-ms@4.0.0:
+    resolution: {integrity: sha512-TXfryirbmq34y8QBwgqCVLi+8oA3oWx2eAnSn62ITyEhEYaWRlVZ2DvMM9eZbMs/RfxPu/PK/aBLyGj4IrqMHw==}
+    engines: {node: '>=18'}
+    dev: true
+
+  /parse-npm-tarball-url@3.0.0:
+    resolution: {integrity: sha512-InpdgIdNe5xWMEUcrVQUniQKwnggBtJ7+SCwh7zQAZwbbIYZV9XdgJyhtmDSSvykFyQXoe4BINnzKTfCwWLs5g==}
+    engines: {node: '>=8.15'}
+    dependencies:
+      semver: 6.3.1
+    dev: true
+
   /parseurl@1.3.3:
     resolution: {integrity: sha512-CiyeOxFT/JZyN5m0z9PfXw4SCBJ6Sygz1Dpl0wqjlhDEGGBP1GnsUVEL0p63hoG1fcj3fHynXi9NYO4nWOL+qQ==}
     engines: {node: '>= 0.8'}
@@ -11785,6 +12386,13 @@ packages:
       minipass: 7.0.4
     dev: true
 
+  /path-temp@2.1.0:
+    resolution: {integrity: sha512-cMMJTAZlion/RWRRC48UbrDymEIt+/YSD/l8NqjneyDw2rDOBQcP5yRkMB4CYGn47KMhZvbblBP7Z79OsMw72w==}
+    engines: {node: '>=8.15'}
+    dependencies:
+      unique-string: 2.0.0
+    dev: true
+
   /path-to-regexp@0.1.7:
     resolution: {integrity: sha512-5DFkuoqlv1uYQKxy8omFBeJPQcdoE07Kv2sferDCrAq1ohOU+MSDswDIbnx3YAM60qIOnYa53wBhXW0EbMonrQ==}
     dev: true
@@ -11822,6 +12430,11 @@ packages:
     engines: {node: '>=8.6'}
     dev: true
 
+  /picomatch@4.0.1:
+    resolution: {integrity: sha512-xUXwsxNjwTQ8K3GnT4pCJm+xq3RUPQbmkYJTP5aFIfNIvbcc/4MUxgBaaRSZJ6yGJZiGSyYlM6MzwTsRk8SYCg==}
+    engines: {node: '>=12'}
+    dev: true
+
   /pify@4.0.1:
     resolution: {integrity: sha512-uB80kBFb/tfd68bVleG9T5GGsGPjJrLAUpR5PZIrhBnIaRTQRjqdJSsIKkOP6OAIFbj7GOrcudc5pNjZ+geV2g==}
     engines: {node: '>=6'}
@@ -11998,6 +12611,18 @@ packages:
       parse-ms: 2.1.0
     dev: true
 
+  /pretty-ms@9.0.0:
+    resolution: {integrity: sha512-E9e9HJ9R9NasGOgPaPE8VMeiPKAyWR5jcFpNnwIejslIhWqdqOrb2wShBsncMPUb+BcCd2OPYfh7p2W6oemTng==}
+    engines: {node: '>=18'}
+    dependencies:
+      parse-ms: 4.0.0
+    dev: true
+
+  /proc-log@3.0.0:
+    resolution: {integrity: sha512-++Vn7NS4Xf9NacaU9Xq3URUuqZETPsf8L4j5/ckhaRYsfPeRyzGw+iDjFhV/Jr3uNmTvvddEJFWh5R1gRgUH8A==}
+    engines: {node: ^14.17.0 || ^16.13.0 || >=18.0.0}
+    dev: true
+
   /process-nextick-args@2.0.1:
     resolution: {integrity: sha512-3ouUOpQhtgrbOa17J7+uxOTpITYWaGP7/AhoR3+A+/1e9skrzelGi/dXzEYyvbxubEF6Wn2ypscTKiKJFFn1ag==}
     dev: true
@@ -12012,6 +12637,23 @@ packages:
     engines: {node: '>=0.4.0'}
     dev: true
 
+  /promise-inflight@1.0.1:
+    resolution: {integrity: sha512-6zWPyEOFaQBJYcGMHBKTKJ3u6TBsnMFOIZSa6ce1e/ZrrsOlnHRHbabMjLiBYKp+n44X9eUI6VUPaukCXHuG4g==}
+    peerDependencies:
+      bluebird: '*'
+    peerDependenciesMeta:
+      bluebird:
+        optional: true
+    dev: true
+
+  /promise-retry@2.0.1:
+    resolution: {integrity: sha512-y+WKFlBR8BGXnsNlIHFGPZmyDf3DFMoLhaflAnyZgV6rG6xu+JwesTo2Q9R6XwYmtmwAFCkAk3e35jEdoeh/3g==}
+    engines: {node: '>=10'}
+    dependencies:
+      err-code: 2.0.3
+      retry: 0.12.0
+    dev: true
+
   /prompts@2.4.2:
     resolution: {integrity: sha512-NxNv/kLguCA7p3jE8oL2aEBsrJWgAakBpgmgK6lpPWV+WuOmY6r2/zbAVnP+T8bQlA0nzHXSJSJW0Hq7ylaD2Q==}
     engines: {node: '>= 6'}
@@ -12607,6 +13249,14 @@ packages:
       - immer
     dev: false
 
+  /read-package-json-fast@3.0.2:
+    resolution: {integrity: sha512-0J+Msgym3vrLOUB3hzQCuZHII0xkNGCtz/HJH9xZshwv9DbDwkw1KaE3gx/e2J5rpEY5rtOy6cyhKOPrkP7FZw==}
+    engines: {node: ^14.17.0 || ^16.13.0 || >=18.0.0}
+    dependencies:
+      json-parse-even-better-errors: 3.0.1
+      npm-normalize-package-bin: 3.0.1
+    dev: true
+
   /read-pkg-up@7.0.1:
     resolution: {integrity: sha512-zK0TB7Xd6JpCLmlLmufqykGE+/TlOePD6qKClNW7hHDKFh/J7/7gCWGR7joEQEW1bKq3a3yUZSObOoWLFQ4ohg==}
     engines: {node: '>=8'}
@@ -12777,6 +13427,14 @@ packages:
       unist-util-visit: 2.0.3
     dev: true
 
+  /rename-overwrite@5.0.0:
+    resolution: {integrity: sha512-vSxE5Ww7Jnyotvaxi3Dj0vOMoojH8KMkBfs9xYeW/qNfJiLTcC1fmwTjrbGUq3mQSOCxkG0DbdcvwTUrpvBN4w==}
+    engines: {node: '>=12.10'}
+    dependencies:
+      '@zkochan/rimraf': 2.1.3
+      fs-extra: 10.1.0
+    dev: true
+
   /require-directory@2.1.1:
     resolution: {integrity: sha512-fGxEI7+wsG9xrvdjsrlmL22OMTTiHRwAMroiEeMgq8gzoLC/PQr7RsRDSTLUg/bZAZtF+TVIkHc6/4RIKrui+Q==}
     engines: {node: '>=0.10.0'}
@@ -12865,11 +13523,20 @@ packages:
     engines: {node: '>=0.12'}
     dev: false
 
+  /retry@0.12.0:
+    resolution: {integrity: sha512-9LkiTwjUh6rT555DtE9rTX+BKByPfrMzEAtnlEtdEwr3Nkffwiihqe2bWADg+OQRjt9gl6ICdmB/ZFDCGAtSow==}
+    engines: {node: '>= 4'}
+    dev: true
+
   /reusify@1.0.4:
     resolution: {integrity: sha512-U9nH88a3fc/ekCF1l0/UP1IosiuIjyTh7hBvXVMHYgVcfGvt897Xguj2UOLDeI5BG2m7/uwyaLVT6fbtCwTyzw==}
     engines: {iojs: '>=1.0.0', node: '>=0.10.0'}
     dev: true
 
+  /reverse-arguments@1.0.0:
+    resolution: {integrity: sha512-/x8uIPdTafBqakK0TmPNJzgkLP+3H+yxpUJhCQHsLBg1rYEVNR2D8BRYNWQhVBjyOd7oo1dZRVzIkwMY2oqfYQ==}
+    dev: true
+
   /rimraf@2.6.3:
     resolution: {integrity: sha512-mwqeW5XsA2qAejG46gYdENaxXjx9onRNCfn7L0duuP4hCuTIi/QO7PDK07KJfp1d+izWPrzEJDcSqBa0OZQriA==}
     hasBin: true
@@ -13147,6 +13814,10 @@ packages:
     engines: {node: '>=8'}
     dev: true
 
+  /shell-quote-word@1.0.1:
+    resolution: {integrity: sha512-lT297f1WLAdq0A4O+AknIFRP6kkiI3s8C913eJ0XqBxJbZPGWUNkRQk2u8zk4bEAjUJ5i+fSLwB6z1HzeT+DEg==}
+    dev: true
+
   /shell-quote@1.8.1:
     resolution: {integrity: sha512-6j1W9l1iAs/4xYBI1SYOVZyFcCis9b4KCLQ8fgAGG07QvzaRLVVRQvAy85yNmmZSjYjg4MWh4gNvlPujU/5LpA==}
     dev: true
@@ -13183,6 +13854,11 @@ packages:
     engines: {node: '>=8'}
     dev: true
 
+  /smol-toml@1.1.4:
+    resolution: {integrity: sha512-Y0OT8HezWsTNeEOSVxDnKOW/AyNXHQ4BwJNbAXlLTF5wWsBvrcHhIkE5Rf8kQMLmgf7nDX3PVOlgC6/Aiggu3Q==}
+    engines: {node: '>= 18', pnpm: '>= 8'}
+    dev: true
+
   /socket.io-client@4.7.4:
     resolution: {integrity: sha512-wh+OkeF0rAVCrABWQBaEjLfb7DVPotMbu0cgWgyR0v6eA4EoVnAwcIeIbcdTE3GT/H3kbdLl7OoH2+asoDRIIg==}
     engines: {node: '>=10.0.0'}
@@ -13273,10 +13949,23 @@ packages:
     engines: {node: '>=12'}
     dev: false
 
+  /split2@3.2.2:
+    resolution: {integrity: sha512-9NThjpgZnifTkJpzTZ7Eue85S49QwpNhZTq6GRJwObb6jnLFNGB7Qm73V5HewTROPyxD0C29xqmaI68bQtV+hg==}
+    dependencies:
+      readable-stream: 3.6.2
+    dev: true
+
   /sprintf-js@1.0.3:
     resolution: {integrity: sha512-D9cPgkvLlV3t3IzL0D0YLvGA9Ahk4PcvVwUbN0dSGr1aP0Nrt4AEnTUbuGvquEC0mA64Gqt1fzirlRs5ibXx8g==}
     dev: true
 
+  /ssri@10.0.5:
+    resolution: {integrity: sha512-bSf16tAFkGeRlUNDjXu8FzaMQt6g2HZJrun7mtMbIPOddxt3GLMSz5VWUWcqTJUPfLEaDIepGxv+bYQW49596A==}
+    engines: {node: ^14.17.0 || ^16.13.0 || >=18.0.0}
+    dependencies:
+      minipass: 7.0.4
+    dev: true
+
   /stack-generator@2.0.10:
     resolution: {integrity: sha512-mwnua/hkqM6pF4k8SnmZ2zfETsRUpWXREfA/goT8SLCV4iOFa4bzOX2nDipWAZFPTjLvQB82f5yaodMVhK0yJQ==}
     dependencies:
@@ -13371,6 +14060,10 @@ packages:
       strip-ansi: 7.1.0
     dev: true
 
+  /string.fromcodepoint@0.2.1:
+    resolution: {integrity: sha512-n69H31OnxSGSZyZbgBlvYIXlrMhJQ0dQAX1js1QDhpaUH6zmU3QYlj07bCwCNlPOu3oRXIubGPl2gDGnHsiCqg==}
+    dev: true
+
   /string.prototype.matchall@4.0.10:
     resolution: {integrity: sha512-rGXbGmOEosIQi6Qva94HUjgPs9vKW+dkG7Y8Q5O2OYkWL6wFaTRZO8zM4mhP94uX55wgyrXzfS2aGtGzUL7EJQ==}
     dependencies:
@@ -13450,6 +14143,11 @@ packages:
     engines: {node: '>=4'}
     dev: true
 
+  /strip-bom@4.0.0:
+    resolution: {integrity: sha512-3xurFv5tEgii33Zi8Jtp55wEIILR9eh34FAW00PZf+JnSsTmV/ioewSgQl97JHvgjoRGwPShsWm+IdrxB35d0w==}
+    engines: {node: '>=8'}
+    dev: true
+
   /strip-final-newline@2.0.0:
     resolution: {integrity: sha512-BrpvfNAE3dcvq7ll3xVumzjKjZQ5tI1sEUIKr3Uoks0XUl45St3FlatVqef9prk4jRDzhW6WZg+3bk93y6pLjA==}
     engines: {node: '>=6'}
@@ -13484,6 +14182,11 @@ packages:
     engines: {node: '>=8'}
     dev: true
 
+  /strip-json-comments@5.0.1:
+    resolution: {integrity: sha512-0fk9zBqO67Nq5M/m45qHCJxylV/DhBlIOVExqgOMiCCrzrhU6tCibRXNqE3jwJLftzE9SNuZtYbpzcO+i9FiKw==}
+    engines: {node: '>=14.16'}
+    dev: true
+
   /strip-literal@2.0.0:
     resolution: {integrity: sha512-f9vHgsCWBq2ugHAkGMiiYY+AYG0D/cbloKKg0nhaaaSNsujdGIpVXCNsrJpCKr5M0f4aI31mr13UjY6GAuXCKA==}
     dependencies:
@@ -13509,6 +14212,10 @@ packages:
       - supports-color
     dev: true
 
+  /summary@2.1.0:
+    resolution: {integrity: sha512-nMIjMrd5Z2nuB2RZCKJfFMjgS3fygbeyGk9PxPPaJR1RIcyN9yn4A63Isovzm3ZtQuEkLBVgMdPup8UeLH7aQw==}
+    dev: true
+
   /supports-color@5.5.0:
     resolution: {integrity: sha512-QjVjwdXIt408MIiAqCX4oUKsgU2EqAGzs2Ppkm4aQYbjm+ZEWEcW4SfFNTr4uMNZma0ey4f5lgLrkB0aX0QMow==}
     engines: {node: '>=4'}
@@ -13637,6 +14344,12 @@ packages:
       xtend: 4.0.2
     dev: true
 
+  /through2@4.0.2:
+    resolution: {integrity: sha512-iOqSav00cVxEEICeD7TjLB1sueEL+81Wpzp2bY17uZjZN0pWZPuo4suZ/61VujxmqSGFfgOcNuTZ85QJwNZQpw==}
+    dependencies:
+      readable-stream: 3.6.2
+    dev: true
+
   /tiny-invariant@1.3.1:
     resolution: {integrity: sha512-AD5ih2NlSssTCwsMznbvwMZpJ1cbhkGd2uueNxzv2jDlEeZdU04JQfRnggJQ8DrcVBGjAsCKwFBbDlVNtEMlzw==}
 
@@ -13662,6 +14375,16 @@ packages:
     resolution: {integrity: sha512-/OaKK0xYrs3DmxRYqL/yDc+FxFUVYhDlXMhRmv3z915w2HF1tnN1omB354j8VUGO/hbRzyD6Y3sA7v7GS/ceog==}
     engines: {node: '>=4'}
 
+  /to-no-case@1.0.2:
+    resolution: {integrity: sha512-Z3g735FxuZY8rodxV4gH7LxClE4H0hTIyHNIHdk+vpQxjLm0cwnKXq/OFVZ76SOQmto7txVcwSCwkU5kqp+FKg==}
+    dev: true
+
+  /to-pascal-case@1.0.0:
+    resolution: {integrity: sha512-QGMWHqM6xPrcQW57S23c5/3BbYb0Tbe9p+ur98ckRnGDwD4wbbtDiYI38CfmMKNB5Iv0REjs5SNDntTwvDxzZA==}
+    dependencies:
+      to-space-case: 1.0.0
+    dev: true
+
   /to-regex-range@5.0.1:
     resolution: {integrity: sha512-65P7iz6X5yEr1cwcgvQxbbIw7Uk3gOy5dIdtZ4rDveLqhrdJP+Li/Hx6tyK0NEb+2GCyneCMJiGqrADCSNk8sQ==}
     engines: {node: '>=8.0'}
@@ -13669,6 +14392,12 @@ packages:
       is-number: 7.0.0
     dev: true
 
+  /to-space-case@1.0.0:
+    resolution: {integrity: sha512-rLdvwXZ39VOn1IxGL3V6ZstoTbwLRckQmn/U8ZDLuWwIXNpuZDhQ3AiRUlhTbOXFVE9C+dR51wM0CBDhk31VcA==}
+    dependencies:
+      to-no-case: 1.0.2
+    dev: true
+
   /tocbot@4.25.0:
     resolution: {integrity: sha512-kE5wyCQJ40hqUaRVkyQ4z5+4juzYsv/eK+aqD97N62YH0TxFhzJvo22RUQQZdO3YnXAk42ZOfOpjVdy+Z0YokA==}
     dev: true
@@ -13929,6 +14658,12 @@ packages:
       '@fastify/busboy': 2.1.0
     dev: true
 
+  /unescape-js@1.1.4:
+    resolution: {integrity: sha512-42SD8NOQEhdYntEiUQdYq/1V/YHwr1HLwlHuTJB5InVVdOSbgI6xu8jK5q65yIzuFCfczzyDF/7hbGzVbyCw0g==}
+    dependencies:
+      string.fromcodepoint: 0.2.1
+    dev: true
+
   /unicode-canonical-property-names-ecmascript@2.0.0:
     resolution: {integrity: sha512-yY5PpDlfVIU5+y/BSCxAJRBIS1Zc2dDG3Ujq+sR0U+JjUevW2JhocOF+soROYDSaAezOzOKuyyixhD6mBknSmQ==}
     engines: {node: '>=4'}
@@ -14160,6 +14895,20 @@ packages:
       spdx-expression-parse: 3.0.1
     dev: true
 
+  /validate-npm-package-name@4.0.0:
+    resolution: {integrity: sha512-mzR0L8ZDktZjpX4OB46KT+56MAhl4EIazWP/+G/HPGuvfdaqg4YsCdtOm6U9+LOFyYDoh4dpnpxZRB9MQQns5Q==}
+    engines: {node: ^12.13.0 || ^14.15.0 || >=16.0.0}
+    dependencies:
+      builtins: 5.0.1
+    dev: true
+
+  /validate-npm-package-name@5.0.0:
+    resolution: {integrity: sha512-YuKoXDAhBYxY7SfOKxHBDoSyENFeW5VvIIQp2TGQuit8gpK6MnWaQelBKxso72DoxTZfZdcP3W90LqpSkgPzLQ==}
+    engines: {node: ^14.17.0 || ^16.13.0 || >=18.0.0}
+    dependencies:
+      builtins: 5.0.1
+    dev: true
+
   /validator@13.11.0:
     resolution: {integrity: sha512-Ii+sehpSfZy+At5nPdnyMhx78fEoPDkR2XW/zimHEL3MyGJQOCQ7WeP20jPYRz7ZCpcKLB21NxuXHF3bxjStBQ==}
     engines: {node: '>= 0.10'}
@@ -14170,6 +14919,13 @@ packages:
     engines: {node: '>= 0.8'}
     dev: true
 
+  /version-selector-type@3.0.0:
+    resolution: {integrity: sha512-PSvMIZS7C1MuVNBXl/CDG2pZq8EXy/NW2dHIdm3bVP5N0PC8utDK8ttXLXj44Gn3J0lQE3U7Mpm1estAOd+eiA==}
+    engines: {node: '>=10.13'}
+    dependencies:
+      semver: 7.6.0
+    dev: true
+
   /vite-node@1.3.1(@types/node@20.11.19):
     resolution: {integrity: sha512-azbRrqRxlWTJEVbzInZCTchx0X69M/XPTCz4H+TLvlTcR/xH/3hkRqhOakT41fMJCMzXTu4UvegkZiEoJAWvng==}
     engines: {node: ^18.0.0 || >=20.0.0}
@@ -14345,6 +15101,10 @@ packages:
       - terser
     dev: true
 
+  /vlq@0.2.3:
+    resolution: {integrity: sha512-DRibZL6DsNhIgYQ+wNdWDL2SL3bKPlVrRiBqV5yuMm++op8W4kGFtaQfCs4KEJn0wBZcHVHJ3eoywX8983k1ow==}
+    dev: true
+
   /void-elements@3.1.0:
     resolution: {integrity: sha512-Dhxzh5HZuiHQhbvTW9AMetFfBHDMYpo23Uo9btPXgdYP+3T5S+p+jgNy7spra+veYhBP2dCSgxR/i2Y02h5/6w==}
     engines: {node: '>=0.10.0'}
@@ -14468,6 +15228,14 @@ packages:
       isexe: 2.0.0
     dev: true
 
+  /which@4.0.0:
+    resolution: {integrity: sha512-GlaYyEb07DPxYCKhKzplCWBJtvxZcZMrL+4UkrTSJHHPyZU4mYYTv3qaOe77H7EODLSSopAUFAc6W8U4yqvscg==}
+    engines: {node: ^16.13.0 || >=18.0.0}
+    hasBin: true
+    dependencies:
+      isexe: 3.1.1
+    dev: true
+
   /why-is-node-running@2.2.2:
     resolution: {integrity: sha512-6tSwToZxTOcotxHeA+qGCq1mVzKR3CwcJGmVcY+QE8SHy6TnpFnh8PAvPNHYr7EcuVeG0QSMxtYCuO1ta/G/oA==}
     engines: {node: '>=8'}
@@ -14641,11 +15409,9 @@ packages:
       zod: ^3.18.0
     dependencies:
       zod: 3.22.4
-    dev: false
 
   /zod@3.22.4:
     resolution: {integrity: sha512-iC+8Io04lddc+mVqQ9AZ7OQ2MrUKGN+oIQyq1vemgt46jwCwLfhq7/pwnBnNXXXZb8VTVLKwp9EDkx+ryxIWmg==}
-    dev: false
 
   /zustand@4.5.1(@types/react@18.2.57)(react@18.2.0):
     resolution: {integrity: sha512-XlauQmH64xXSC1qGYNv00ODaQ3B+tNPoy22jv2diYiP4eoDKr9LA+Bh5Bc3gplTrFdb6JVI+N4kc1DZ/tbtfPg==}

From 8f93ae8d7c48dc90b932698884e35c8d36549416 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 27 Feb 2024 14:26:09 +1100
Subject: [PATCH 335/411] tidy(ui): clean up unused code 1

- Only export when necessary
- Remove totally usused functions, variables, state, etc
- Remove unused packages
---
 invokeai/frontend/web/package.json            |   2 -
 invokeai/frontend/web/pnpm-lock.yaml          |  54 +------
 invokeai/frontend/web/scripts/colors.js       |  34 ----
 .../frontend/web/src/app/logging/logger.ts    |   1 -
 .../frontend/web/src/app/store/actions.ts     |   3 -
 .../frontend/web/src/app/store/constants.ts   |   1 +
 .../src/app/store/createMemoizedSelector.ts   |  18 +--
 .../middleware/listenerMiddleware/index.ts    |   6 +-
 .../addFirstListImagesListener.ts.ts          |   3 -
 .../app/store/nanostores/bulkDownloadId.ts    |   2 +-
 invokeai/frontend/web/src/app/store/store.ts  |   2 +-
 invokeai/frontend/web/src/app/store/util.ts   |   2 -
 .../web/src/common/components/Nbsp.tsx        |   1 -
 .../frontend/web/src/common/hooks/useImage.ts | 102 ------------
 .../src/common/hooks/useModelCustomSelect.ts  |   2 +-
 .../web/src/common/util/generateSeeds.ts      |   2 -
 .../src/common/util/roundDownToMultiple.ts    |   4 -
 .../web/src/common/util/skipMouseEvent.ts     |   8 -
 .../src/common/util/stopPastePropagation.ts   |   5 -
 .../components/IAICanvasMaskCompositer.tsx    |   2 +-
 .../features/canvas/store/canvasSelectors.ts  |   6 -
 .../src/features/canvas/store/canvasSlice.ts  |  29 +---
 .../src/features/canvas/store/canvasTypes.ts  |   5 +-
 .../src/features/canvas/util/colorToString.ts |  12 +-
 .../web/src/features/canvas/util/constants.ts |   3 -
 .../canvas/util/roundDimensionsToMultiple.ts  |  11 --
 .../hooks/useControlAdapter.ts                |  21 ---
 .../store/controlAdaptersSlice.ts             |  31 +---
 .../features/controlAdapters/store/types.ts   | 147 +-----------------
 .../store/dynamicPromptsSlice.ts              |  12 +-
 .../web/src/features/gallery/store/actions.ts |  11 --
 .../features/gallery/store/gallerySlice.ts    |   4 +-
 .../web/src/features/hrf/store/hrfSlice.ts    |   8 +-
 .../web/src/features/lora/store/loraSlice.ts  |  25 +--
 .../web/src/features/metadata/exceptions.ts   |  26 ----
 .../web/src/features/metadata/types.ts        |   5 +-
 .../metadata/util/modelFetchingHelpers.ts     |  15 --
 .../web/src/features/metadata/util/parsers.ts |  26 +++-
 .../SyncModels/SyncModelsButton.tsx           |  32 ----
 .../store/modelManagerV2Slice.ts              |   6 +-
 .../AddModelPanel/AdvancedImport.tsx          |   5 -
 .../nodes/Invocation/fields/FieldHandle.tsx   |  17 --
 .../nodes/Invocation/fields/FieldTitle.tsx    |  34 ----
 .../hooks/useAnyOrDirectInputFieldNames.ts    |   2 +-
 .../src/features/nodes/hooks/useBuildNode.ts  |   7 +-
 .../hooks/useConnectionInputFieldNames.ts     |   2 +-
 .../nodes/hooks/useOutputFieldNames.ts        |   2 +-
 .../web/src/features/nodes/store/actions.ts   |   6 +-
 .../src/features/nodes/store/nodesSlice.ts    |  15 +-
 .../src/features/nodes/store/workflowSlice.ts |   6 +-
 .../src/features/nodes/types/common.test-d.ts |  21 +--
 .../web/src/features/nodes/types/common.ts    |  22 +--
 .../queue/components/ClearQueueIconButton.tsx |   2 -
 .../queue/components/QueueControls.tsx        |   2 +-
 .../GenerationSettingsAccordion.tsx           |   2 +-
 55 files changed, 83 insertions(+), 751 deletions(-)
 delete mode 100644 invokeai/frontend/web/scripts/colors.js
 delete mode 100644 invokeai/frontend/web/src/app/store/util.ts
 delete mode 100644 invokeai/frontend/web/src/common/components/Nbsp.tsx
 delete mode 100644 invokeai/frontend/web/src/common/hooks/useImage.ts
 delete mode 100644 invokeai/frontend/web/src/common/util/skipMouseEvent.ts
 delete mode 100644 invokeai/frontend/web/src/common/util/stopPastePropagation.ts
 delete mode 100644 invokeai/frontend/web/src/features/canvas/util/roundDimensionsToMultiple.ts
 delete mode 100644 invokeai/frontend/web/src/features/controlAdapters/hooks/useControlAdapter.ts
 delete mode 100644 invokeai/frontend/web/src/features/modelManagerV2/components/SyncModels/SyncModelsButton.tsx
 delete mode 100644 invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/FieldTitle.tsx

diff --git a/invokeai/frontend/web/package.json b/invokeai/frontend/web/package.json
index 9c34c34f0b..39c9722441 100644
--- a/invokeai/frontend/web/package.json
+++ b/invokeai/frontend/web/package.json
@@ -58,7 +58,6 @@
     "@dnd-kit/utilities": "^3.2.2",
     "@fontsource-variable/inter": "^5.0.16",
     "@invoke-ai/ui-library": "^0.0.21",
-    "@mantine/form": "6.0.21",
     "@nanostores/react": "^0.7.2",
     "@reduxjs/toolkit": "2.2.1",
     "@roarr/browser-log-writer": "^1.3.0",
@@ -90,7 +89,6 @@
     "react-redux": "9.1.0",
     "react-resizable-panels": "^2.0.9",
     "react-select": "5.8.0",
-    "react-textarea-autosize": "^8.5.3",
     "react-use": "^17.5.0",
     "react-virtuoso": "^4.7.0",
     "reactflow": "^11.10.4",
diff --git a/invokeai/frontend/web/pnpm-lock.yaml b/invokeai/frontend/web/pnpm-lock.yaml
index ccbb7534d8..e691b44421 100644
--- a/invokeai/frontend/web/pnpm-lock.yaml
+++ b/invokeai/frontend/web/pnpm-lock.yaml
@@ -29,9 +29,6 @@ dependencies:
   '@invoke-ai/ui-library':
     specifier: ^0.0.21
     version: 0.0.21(@chakra-ui/form-control@2.2.0)(@chakra-ui/icon@3.2.0)(@chakra-ui/media-query@3.3.0)(@chakra-ui/menu@2.2.1)(@chakra-ui/spinner@2.1.0)(@chakra-ui/system@2.6.2)(@fontsource-variable/inter@5.0.16)(@internationalized/date@3.5.2)(@types/react@18.2.57)(i18next@23.9.0)(react-dom@18.2.0)(react@18.2.0)
-  '@mantine/form':
-    specifier: 6.0.21
-    version: 6.0.21(react@18.2.0)
   '@nanostores/react':
     specifier: ^0.7.2
     version: 0.7.2(nanostores@0.10.0)(react@18.2.0)
@@ -125,9 +122,6 @@ dependencies:
   react-select:
     specifier: 5.8.0
     version: 5.8.0(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-  react-textarea-autosize:
-    specifier: ^8.5.3
-    version: 8.5.3(@types/react@18.2.57)(react@18.2.0)
   react-use:
     specifier: ^17.5.0
     version: 17.5.0(react-dom@18.2.0)(react@18.2.0)
@@ -3961,16 +3955,6 @@ packages:
     resolution: {integrity: sha512-dfLbk+PwWvFzSxwk3n5ySL0hfBog779o8h68wK/7/APo/7cgyWp5jcXockbxdk5kFRkbeXWm4Fbi9FrdN381sA==}
     dev: true
 
-  /@mantine/form@6.0.21(react@18.2.0):
-    resolution: {integrity: sha512-d4tlxyZic7MSDnaPx/WliCX1sRFDkUd2nxx4MxxO2T4OSek0YDqTlSBCxeoveu60P+vrQQN5rbbsVsaOJBe4SQ==}
-    peerDependencies:
-      react: '>=16.8.0'
-    dependencies:
-      fast-deep-equal: 3.1.3
-      klona: 2.0.6
-      react: 18.2.0
-    dev: false
-
   /@mdx-js/react@2.3.0(react@18.2.0):
     resolution: {integrity: sha512-zQH//gdOmuu7nt2oJR29vFhDv88oGPmVw6BggmrHeMI+xgEkp1B2dX9/bMBSYtK0dyLX/aOmesKS09g222K1/g==}
     peerDependencies:
@@ -8360,6 +8344,7 @@ packages:
   /clone@1.0.4:
     resolution: {integrity: sha512-JQHZ2QMW6l3aH/j6xCqQThY/9OH4D/9ls34cgkUBiEeocRTU04tHfKPBsUK1PqZCUQM7GiA0IIXJSuXHI64Kbg==}
     engines: {node: '>=0.8'}
+    requiresBuild: true
     dev: true
 
   /color-convert@1.9.3:
@@ -8782,6 +8767,7 @@ packages:
 
   /defaults@1.0.4:
     resolution: {integrity: sha512-eFuaLoy/Rxalv2kr+lqMlUnrDWV+3j4pljOIJgLIhI058IQfWJ7vXhyEIHu+HtC738klGALYxOKDO0bQP3tg8A==}
+    requiresBuild: true
     dependencies:
       clone: 1.0.4
     dev: true
@@ -13151,20 +13137,6 @@ packages:
       react: 18.2.0
       tslib: 2.6.2
 
-  /react-textarea-autosize@8.5.3(@types/react@18.2.57)(react@18.2.0):
-    resolution: {integrity: sha512-XT1024o2pqCuZSuBt9FwHlaDeNtVrtCXu0Rnz88t1jUGheCLa3PhjE1GH8Ctm2axEtvdCl5SUHYschyQ0L5QHQ==}
-    engines: {node: '>=10'}
-    peerDependencies:
-      react: ^16.8.0 || ^17.0.0 || ^18.0.0
-    dependencies:
-      '@babel/runtime': 7.23.9
-      react: 18.2.0
-      use-composed-ref: 1.3.0(react@18.2.0)
-      use-latest: 1.2.1(@types/react@18.2.57)(react@18.2.0)
-    transitivePeerDependencies:
-      - '@types/react'
-    dev: false
-
   /react-transition-group@4.4.5(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-pZcd1MCJoiKiBR2NRxeCRg13uCXbydPnmB4EOeRrY7480qNWO8IIgQG6zlDkm6uRMsURXPuKq0GWtiM59a5Q6g==}
     peerDependencies:
@@ -14777,14 +14749,6 @@ packages:
       react: 18.2.0
       tslib: 2.6.2
 
-  /use-composed-ref@1.3.0(react@18.2.0):
-    resolution: {integrity: sha512-GLMG0Jc/jiKov/3Ulid1wbv3r54K9HlMW29IWcDFPEqFkSO2nS0MuefWgMJpeHQ9YJeXDL3ZUF+P3jdXlZX/cQ==}
-    peerDependencies:
-      react: ^16.8.0 || ^17.0.0 || ^18.0.0
-    dependencies:
-      react: 18.2.0
-    dev: false
-
   /use-debounce@10.0.0(react@18.2.0):
     resolution: {integrity: sha512-XRjvlvCB46bah9IBXVnq/ACP2lxqXyZj0D9hj4K5OzNroMDpTEBg8Anuh1/UfRTRs7pLhQ+RiNxxwZu9+MVl1A==}
     engines: {node: '>= 16.0.0'}
@@ -14817,20 +14781,6 @@ packages:
       react: 18.2.0
     dev: false
 
-  /use-latest@1.2.1(@types/react@18.2.57)(react@18.2.0):
-    resolution: {integrity: sha512-xA+AVm/Wlg3e2P/JiItTziwS7FK92LWrDB0p+hgXloIMuVCeJJ8v6f0eeHyPZaJrM+usM1FkFfbNCrJGs8A/zw==}
-    peerDependencies:
-      '@types/react': '*'
-      react: ^16.8.0 || ^17.0.0 || ^18.0.0
-    peerDependenciesMeta:
-      '@types/react':
-        optional: true
-    dependencies:
-      '@types/react': 18.2.57
-      react: 18.2.0
-      use-isomorphic-layout-effect: 1.1.2(@types/react@18.2.57)(react@18.2.0)
-    dev: false
-
   /use-resize-observer@9.1.0(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-R25VqO9Wb3asSD4eqtcxk8sJalvIOYBqS8MNZlpDSQ4l4xMQxC/J7Id9HoTqPq8FwULIn0PVW+OAqF2dyYbjow==}
     peerDependencies:
diff --git a/invokeai/frontend/web/scripts/colors.js b/invokeai/frontend/web/scripts/colors.js
deleted file mode 100644
index 3fc8f8d751..0000000000
--- a/invokeai/frontend/web/scripts/colors.js
+++ /dev/null
@@ -1,34 +0,0 @@
-export const COLORS = {
-  reset: '\x1b[0m',
-  bright: '\x1b[1m',
-  dim: '\x1b[2m',
-  underscore: '\x1b[4m',
-  blink: '\x1b[5m',
-  reverse: '\x1b[7m',
-  hidden: '\x1b[8m',
-
-  fg: {
-    black: '\x1b[30m',
-    red: '\x1b[31m',
-    green: '\x1b[32m',
-    yellow: '\x1b[33m',
-    blue: '\x1b[34m',
-    magenta: '\x1b[35m',
-    cyan: '\x1b[36m',
-    white: '\x1b[37m',
-    gray: '\x1b[90m',
-    crimson: '\x1b[38m',
-  },
-  bg: {
-    black: '\x1b[40m',
-    red: '\x1b[41m',
-    green: '\x1b[42m',
-    yellow: '\x1b[43m',
-    blue: '\x1b[44m',
-    magenta: '\x1b[45m',
-    cyan: '\x1b[46m',
-    white: '\x1b[47m',
-    gray: '\x1b[100m',
-    crimson: '\x1b[48m',
-  },
-};
diff --git a/invokeai/frontend/web/src/app/logging/logger.ts b/invokeai/frontend/web/src/app/logging/logger.ts
index 491fc27688..d0e6340625 100644
--- a/invokeai/frontend/web/src/app/logging/logger.ts
+++ b/invokeai/frontend/web/src/app/logging/logger.ts
@@ -12,7 +12,6 @@ ROARR.serializeMessage = serializeMessage;
 ROARR.write = createLogWriter();
 
 export const BASE_CONTEXT = {};
-export const log = Roarr.child(BASE_CONTEXT);
 
 export const $logger = atom<Logger>(Roarr.child(BASE_CONTEXT));
 
diff --git a/invokeai/frontend/web/src/app/store/actions.ts b/invokeai/frontend/web/src/app/store/actions.ts
index 0800d1a63b..85debfc607 100644
--- a/invokeai/frontend/web/src/app/store/actions.ts
+++ b/invokeai/frontend/web/src/app/store/actions.ts
@@ -1,10 +1,7 @@
 import { createAction } from '@reduxjs/toolkit';
 import type { InvokeTabName } from 'features/ui/store/tabMap';
-import type { BatchConfig } from 'services/api/types';
 
 export const enqueueRequested = createAction<{
   tabName: InvokeTabName;
   prepend: boolean;
 }>('app/enqueueRequested');
-
-export const batchEnqueued = createAction<BatchConfig>('app/batchEnqueued');
diff --git a/invokeai/frontend/web/src/app/store/constants.ts b/invokeai/frontend/web/src/app/store/constants.ts
index c2f3a5e10b..14a2c0b77f 100644
--- a/invokeai/frontend/web/src/app/store/constants.ts
+++ b/invokeai/frontend/web/src/app/store/constants.ts
@@ -1 +1,2 @@
 export const STORAGE_PREFIX = '@@invokeai-';
+export const EMPTY_ARRAY = [];
diff --git a/invokeai/frontend/web/src/app/store/createMemoizedSelector.ts b/invokeai/frontend/web/src/app/store/createMemoizedSelector.ts
index 8e6142ce1d..8e2559927a 100644
--- a/invokeai/frontend/web/src/app/store/createMemoizedSelector.ts
+++ b/invokeai/frontend/web/src/app/store/createMemoizedSelector.ts
@@ -13,19 +13,9 @@ export const createMemoizedSelector = createSelectorCreator({
   argsMemoize: lruMemoize,
 });
 
-/**
- * A memoized selector creator that uses LRU cache default shallow equality check.
- */
-export const createLruSelector = createSelectorCreator({
-  memoize: lruMemoize,
-  argsMemoize: lruMemoize,
-});
-
-export const createLruDraftSafeSelector = createDraftSafeSelectorCreator({
-  memoize: lruMemoize,
-  argsMemoize: lruMemoize,
-});
-
 export const getSelectorsOptions: GetSelectorsOptions = {
-  createSelector: createLruDraftSafeSelector,
+  createSelector: createDraftSafeSelectorCreator({
+    memoize: lruMemoize,
+    argsMemoize: lruMemoize,
+  }),
 };
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts
index 6c5abf41a5..1c93140c03 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts
@@ -1,5 +1,5 @@
-import type { ListenerEffect, TypedAddListener, TypedStartListening, UnknownAction } from '@reduxjs/toolkit';
-import { addListener, createListenerMiddleware } from '@reduxjs/toolkit';
+import type { ListenerEffect, TypedStartListening, UnknownAction } from '@reduxjs/toolkit';
+import { createListenerMiddleware } from '@reduxjs/toolkit';
 import { addBulkDownloadListeners } from 'app/store/middleware/listenerMiddleware/listeners/bulkDownload';
 import { addGalleryImageClickedListener } from 'app/store/middleware/listenerMiddleware/listeners/galleryImageClicked';
 import type { AppDispatch, RootState } from 'app/store/store';
@@ -74,8 +74,6 @@ export type AppStartListening = TypedStartListening<RootState, AppDispatch>;
 
 export const startAppListening = listenerMiddleware.startListening as AppStartListening;
 
-export const addAppListener = addListener as TypedAddListener<RootState, AppDispatch>;
-
 export type AppListenerEffect = ListenerEffect<UnknownAction, RootState, AppDispatch>;
 
 /**
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/addFirstListImagesListener.ts.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/addFirstListImagesListener.ts.ts
index 3c9b245b11..e7597f7ae0 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/addFirstListImagesListener.ts.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/addFirstListImagesListener.ts.ts
@@ -1,4 +1,3 @@
-import { createAction } from '@reduxjs/toolkit';
 import { imageSelected } from 'features/gallery/store/gallerySlice';
 import { IMAGE_CATEGORIES } from 'features/gallery/store/types';
 import { imagesApi } from 'services/api/endpoints/images';
@@ -7,8 +6,6 @@ import { getListImagesUrl, imagesSelectors } from 'services/api/util';
 
 import { startAppListening } from '..';
 
-export const appStarted = createAction('app/appStarted');
-
 export const addFirstListImagesListener = () => {
   startAppListening({
     matcher: imagesApi.endpoints.listImages.matchFulfilled,
diff --git a/invokeai/frontend/web/src/app/store/nanostores/bulkDownloadId.ts b/invokeai/frontend/web/src/app/store/nanostores/bulkDownloadId.ts
index 5615124493..4f7118e2eb 100644
--- a/invokeai/frontend/web/src/app/store/nanostores/bulkDownloadId.ts
+++ b/invokeai/frontend/web/src/app/store/nanostores/bulkDownloadId.ts
@@ -1,6 +1,6 @@
 import { atom } from 'nanostores';
 
-export const DEFAULT_BULK_DOWNLOAD_ID = 'default';
+const DEFAULT_BULK_DOWNLOAD_ID = 'default';
 
 /**
  * The download id for a bulk download. Used for socket subscriptions.
diff --git a/invokeai/frontend/web/src/app/store/store.ts b/invokeai/frontend/web/src/app/store/store.ts
index f85ff916b0..19670aa29f 100644
--- a/invokeai/frontend/web/src/app/store/store.ts
+++ b/invokeai/frontend/web/src/app/store/store.ts
@@ -136,7 +136,7 @@ const unserialize: UnserializeFunction = (data, key) => {
   }
 };
 
-export const serialize: SerializeFunction = (data, key) => {
+const serialize: SerializeFunction = (data, key) => {
   const persistConfig = persistConfigs[key as keyof typeof persistConfigs];
   if (!persistConfig) {
     throw new Error(`No persist config for slice "${key}"`);
diff --git a/invokeai/frontend/web/src/app/store/util.ts b/invokeai/frontend/web/src/app/store/util.ts
deleted file mode 100644
index 381f7f85d2..0000000000
--- a/invokeai/frontend/web/src/app/store/util.ts
+++ /dev/null
@@ -1,2 +0,0 @@
-export const EMPTY_ARRAY = [];
-export const EMPTY_OBJECT = {};
diff --git a/invokeai/frontend/web/src/common/components/Nbsp.tsx b/invokeai/frontend/web/src/common/components/Nbsp.tsx
deleted file mode 100644
index 05b396239d..0000000000
--- a/invokeai/frontend/web/src/common/components/Nbsp.tsx
+++ /dev/null
@@ -1 +0,0 @@
-export const Nbsp = () => <>{'\u00A0'}</>;
diff --git a/invokeai/frontend/web/src/common/hooks/useImage.ts b/invokeai/frontend/web/src/common/hooks/useImage.ts
deleted file mode 100644
index 60c973ce59..0000000000
--- a/invokeai/frontend/web/src/common/hooks/useImage.ts
+++ /dev/null
@@ -1,102 +0,0 @@
-import { useLayoutEffect, useRef, useState } from 'react';
-
-// Adapted from https://github.com/konvajs/use-image
-
-type CrossOrigin = 'anonymous' | 'use-credentials';
-type ReferrerPolicy =
-  | 'no-referrer'
-  | 'no-referrer-when-downgrade'
-  | 'origin'
-  | 'origin-when-cross-origin'
-  | 'same-origin'
-  | 'strict-origin'
-  | 'strict-origin-when-cross-origin'
-  | 'unsafe-url';
-type ImageStatus = 'loaded' | 'loading' | 'failed';
-
-export const useImage = (
-  url: string,
-  crossOrigin?: CrossOrigin,
-  referrerpolicy?: ReferrerPolicy
-): [undefined | HTMLImageElement, ImageStatus, Blob | null] => {
-  // lets use refs for image and status
-  // so we can update them during render
-  // to have instant update in status/image when new data comes in
-  const statusRef = useRef<ImageStatus>('loading');
-  const imageRef = useRef<HTMLImageElement>();
-  const blobRef = useRef<Blob | null>(null);
-
-  // we are not going to use token
-  // but we need to just to trigger state update
-  const [_, setStateToken] = useState(0);
-
-  // keep track of old props to trigger changes
-  const oldUrl = useRef<string>();
-  const oldCrossOrigin = useRef<string>();
-  const oldReferrerPolicy = useRef<string>();
-
-  if (
-    oldUrl.current !== url ||
-    oldCrossOrigin.current !== crossOrigin ||
-    oldReferrerPolicy.current !== referrerpolicy
-  ) {
-    statusRef.current = 'loading';
-    imageRef.current = undefined;
-    oldUrl.current = url;
-    oldCrossOrigin.current = crossOrigin;
-    oldReferrerPolicy.current = referrerpolicy;
-  }
-
-  useLayoutEffect(
-    function () {
-      if (!url) {
-        return;
-      }
-      const img = document.createElement('img');
-
-      function onload() {
-        statusRef.current = 'loaded';
-        imageRef.current = img;
-        const canvas = document.createElement('canvas');
-        canvas.width = img.clientWidth;
-        canvas.height = img.clientHeight;
-
-        const context = canvas.getContext('2d');
-        if (context) {
-          context.drawImage(img, 0, 0);
-          canvas.toBlob(function (blob) {
-            blobRef.current = blob;
-          }, 'image/png');
-        }
-        setStateToken(Math.random());
-      }
-
-      function onerror() {
-        statusRef.current = 'failed';
-        imageRef.current = undefined;
-        setStateToken(Math.random());
-      }
-
-      img.addEventListener('load', onload);
-      img.addEventListener('error', onerror);
-      if (crossOrigin) {
-        img.crossOrigin = crossOrigin;
-      }
-      if (referrerpolicy) {
-        img.referrerPolicy = referrerpolicy;
-      }
-      img.src = url;
-
-      return function cleanup() {
-        img.removeEventListener('load', onload);
-        img.removeEventListener('error', onerror);
-      };
-    },
-    [url, crossOrigin, referrerpolicy]
-  );
-
-  // return array because it is better to use in case of several useImage hooks
-  // const [background, backgroundStatus] = useImage(url1);
-  // const [patter] = useImage(url2);
-  return [imageRef.current, statusRef.current, blobRef.current];
-};
diff --git a/invokeai/frontend/web/src/common/hooks/useModelCustomSelect.ts b/invokeai/frontend/web/src/common/hooks/useModelCustomSelect.ts
index 07ea98a274..6e5c8ca870 100644
--- a/invokeai/frontend/web/src/common/hooks/useModelCustomSelect.ts
+++ b/invokeai/frontend/web/src/common/hooks/useModelCustomSelect.ts
@@ -1,6 +1,6 @@
 import type { Item } from '@invoke-ai/ui-library';
 import type { EntityState } from '@reduxjs/toolkit';
-import { EMPTY_ARRAY } from 'app/store/util';
+import { EMPTY_ARRAY } from "app/store/constants";
 import type { ModelIdentifierWithBase } from 'features/nodes/types/common';
 import { MODEL_TYPE_SHORT_MAP } from 'features/parameters/types/constants';
 import { filter } from 'lodash-es';
diff --git a/invokeai/frontend/web/src/common/util/generateSeeds.ts b/invokeai/frontend/web/src/common/util/generateSeeds.ts
index 588f711148..450068cae8 100644
--- a/invokeai/frontend/web/src/common/util/generateSeeds.ts
+++ b/invokeai/frontend/web/src/common/util/generateSeeds.ts
@@ -16,5 +16,3 @@ export const generateSeeds = ({ count, start, min = NUMPY_RAND_MIN, max = NUMPY_
   }
   return seeds;
 };
-
-export const generateOneSeed = (min: number = NUMPY_RAND_MIN, max: number = NUMPY_RAND_MAX) => random(min, max);
diff --git a/invokeai/frontend/web/src/common/util/roundDownToMultiple.ts b/invokeai/frontend/web/src/common/util/roundDownToMultiple.ts
index 55915ea7c7..792b6d38e4 100644
--- a/invokeai/frontend/web/src/common/util/roundDownToMultiple.ts
+++ b/invokeai/frontend/web/src/common/util/roundDownToMultiple.ts
@@ -8,7 +8,3 @@ export const roundDownToMultipleMin = (num: number, multiple: number): number =>
 export const roundToMultiple = (num: number, multiple: number): number => {
   return Math.round(num / multiple) * multiple;
 };
-
-export const roundToMultipleMin = (num: number, multiple: number): number => {
-  return Math.max(multiple, roundToMultiple(num, multiple));
-};
diff --git a/invokeai/frontend/web/src/common/util/skipMouseEvent.ts b/invokeai/frontend/web/src/common/util/skipMouseEvent.ts
deleted file mode 100644
index f6acc55edd..0000000000
--- a/invokeai/frontend/web/src/common/util/skipMouseEvent.ts
+++ /dev/null
@@ -1,8 +0,0 @@
-import type { MouseEvent } from 'react';
-
-/**
- * Prevents the default behavior of the event.
- */
-export const skipMouseEvent = (e: MouseEvent) => {
-  e.preventDefault();
-};
diff --git a/invokeai/frontend/web/src/common/util/stopPastePropagation.ts b/invokeai/frontend/web/src/common/util/stopPastePropagation.ts
deleted file mode 100644
index f9195a4f58..0000000000
--- a/invokeai/frontend/web/src/common/util/stopPastePropagation.ts
+++ /dev/null
@@ -1,5 +0,0 @@
-import type { ClipboardEvent } from 'react';
-
-export const stopPastePropagation = (e: ClipboardEvent) => {
-  e.stopPropagation();
-};
diff --git a/invokeai/frontend/web/src/features/canvas/components/IAICanvasMaskCompositer.tsx b/invokeai/frontend/web/src/features/canvas/components/IAICanvasMaskCompositer.tsx
index 6098d85359..4fedcaec75 100644
--- a/invokeai/frontend/web/src/features/canvas/components/IAICanvasMaskCompositer.tsx
+++ b/invokeai/frontend/web/src/features/canvas/components/IAICanvasMaskCompositer.tsx
@@ -9,7 +9,7 @@ import { isNumber } from 'lodash-es';
 import { memo, useCallback, useEffect, useMemo, useRef, useState } from 'react';
 import { Rect } from 'react-konva';
 
-export const canvasMaskCompositerSelector = createMemoizedSelector(selectCanvasSlice, (canvas) => {
+const canvasMaskCompositerSelector = createMemoizedSelector(selectCanvasSlice, (canvas) => {
   return {
     stageCoordinates: canvas.stageCoordinates,
     stageDimensions: canvas.stageDimensions,
diff --git a/invokeai/frontend/web/src/features/canvas/store/canvasSelectors.ts b/invokeai/frontend/web/src/features/canvas/store/canvasSelectors.ts
index a337cfaab1..29dc4c9fb8 100644
--- a/invokeai/frontend/web/src/features/canvas/store/canvasSelectors.ts
+++ b/invokeai/frontend/web/src/features/canvas/store/canvasSelectors.ts
@@ -1,14 +1,8 @@
 import { createSelector } from '@reduxjs/toolkit';
-import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 
 import { selectCanvasSlice } from './canvasSlice';
-import { isCanvasBaseImage } from './canvasTypes';
 
 export const isStagingSelector = createSelector(
   selectCanvasSlice,
   (canvas) => canvas.batchIds.length > 0 || canvas.layerState.stagingArea.images.length > 0
 );
-
-export const initialCanvasImageSelector = createMemoizedSelector(selectCanvasSlice, (canvas) =>
-  canvas.layerState.objects.find(isCanvasBaseImage)
-);
diff --git a/invokeai/frontend/web/src/features/canvas/store/canvasSlice.ts b/invokeai/frontend/web/src/features/canvas/store/canvasSlice.ts
index f50d52c1bf..8ae6a2176d 100644
--- a/invokeai/frontend/web/src/features/canvas/store/canvasSlice.ts
+++ b/invokeai/frontend/web/src/features/canvas/store/canvasSlice.ts
@@ -38,7 +38,7 @@ import { CANVAS_GRID_SIZE_FINE } from './constants';
  */
 const MAX_HISTORY = 128;
 
-export const initialLayerState: CanvasLayerState = {
+const initialLayerState: CanvasLayerState = {
   objects: [],
   stagingArea: {
     images: [],
@@ -46,11 +46,10 @@ export const initialLayerState: CanvasLayerState = {
   },
 };
 
-export const initialCanvasState: CanvasState = {
+const initialCanvasState: CanvasState = {
   _version: 1,
   boundingBoxCoordinates: { x: 0, y: 0 },
   boundingBoxDimensions: { width: 512, height: 512 },
-  boundingBoxPreviewFill: { r: 0, g: 0, b: 0, a: 0.5 },
   boundingBoxScaleMethod: 'auto',
   brushColor: { r: 90, g: 90, b: 255, a: 1 },
   brushSize: 50,
@@ -215,9 +214,6 @@ export const canvasSlice = createSlice({
     setStageCoordinates: (state, action: PayloadAction<Vector2d>) => {
       state.stageCoordinates = action.payload;
     },
-    setBoundingBoxPreviewFill: (state, action: PayloadAction<RgbaColor>) => {
-      state.boundingBoxPreviewFill = action.payload;
-    },
     setStageScale: (state, action: PayloadAction<number>) => {
       state.stageScale = action.payload;
     },
@@ -231,9 +227,6 @@ export const canvasSlice = createSlice({
     setShouldLockBoundingBox: (state, action: PayloadAction<boolean>) => {
       state.shouldLockBoundingBox = action.payload;
     },
-    toggleShouldLockBoundingBox: (state) => {
-      state.shouldLockBoundingBox = !state.shouldLockBoundingBox;
-    },
     setShouldShowBoundingBox: (state, action: PayloadAction<boolean>) => {
       state.shouldShowBoundingBox = action.payload;
     },
@@ -573,19 +566,6 @@ export const canvasSlice = createSlice({
         },
       }),
     },
-    scaledBoundingBoxDimensionsReset: {
-      reducer: (state, action: PayloadActionWithOptimalDimension) => {
-        const scaledDimensions = getScaledBoundingBoxDimensions(
-          state.boundingBoxDimensions,
-          action.meta.optimalDimension
-        );
-        state.scaledBoundingBoxDimensions = scaledDimensions;
-      },
-      prepare: (payload: void, optimalDimension: number) => ({
-        payload: undefined,
-        meta: { optimalDimension },
-      }),
-    },
     setShouldShowStagingImage: (state, action: PayloadAction<boolean>) => {
       state.shouldShowStagingImage = action.payload;
     },
@@ -682,7 +662,6 @@ export const {
   resetCanvasView,
   setBoundingBoxCoordinates,
   setBoundingBoxDimensions,
-  setBoundingBoxPreviewFill,
   setBoundingBoxScaleMethod,
   setBrushColor,
   setBrushSize,
@@ -706,7 +685,6 @@ export const {
   setShouldSnapToGrid,
   setStageCoordinates,
   setStageScale,
-  toggleShouldLockBoundingBox,
   undo,
   setScaledBoundingBoxDimensions,
   setShouldRestrictStrokesToBox,
@@ -716,13 +694,12 @@ export const {
   canvasBatchIdAdded,
   canvasBatchIdsReset,
   aspectRatioChanged,
-  scaledBoundingBoxDimensionsReset,
 } = canvasSlice.actions;
 
 export const selectCanvasSlice = (state: RootState) => state.canvas;
 
 /* eslint-disable-next-line @typescript-eslint/no-explicit-any */
-export const migrateCanvasState = (state: any): any => {
+const migrateCanvasState = (state: any): any => {
   if (!('_version' in state)) {
     state._version = 1;
     state.aspectRatio = initialAspectRatioState;
diff --git a/invokeai/frontend/web/src/features/canvas/store/canvasTypes.ts b/invokeai/frontend/web/src/features/canvas/store/canvasTypes.ts
index dc6b764075..e0e7d5b1cd 100644
--- a/invokeai/frontend/web/src/features/canvas/store/canvasTypes.ts
+++ b/invokeai/frontend/web/src/features/canvas/store/canvasTypes.ts
@@ -10,9 +10,9 @@ export const LAYER_NAMES_DICT: { label: string; value: CanvasLayer }[] = [
   { label: 'Mask', value: 'mask' },
 ];
 
-export const LAYER_NAMES = ['base', 'mask'] as const;
+const LAYER_NAMES = ['base', 'mask'] as const;
 
-export const zBoundingBoxScaleMethod = z.enum(['none', 'auto', 'manual']);
+const zBoundingBoxScaleMethod = z.enum(['none', 'auto', 'manual']);
 export type BoundingBoxScaleMethod = z.infer<typeof zBoundingBoxScaleMethod>;
 export const isBoundingBoxScaleMethod = (v: unknown): v is BoundingBoxScaleMethod =>
   zBoundingBoxScaleMethod.safeParse(v).success;
@@ -112,7 +112,6 @@ export interface CanvasState {
   _version: 1;
   boundingBoxCoordinates: Vector2d;
   boundingBoxDimensions: Dimensions;
-  boundingBoxPreviewFill: RgbaColor;
   boundingBoxScaleMethod: BoundingBoxScaleMethod;
   brushColor: RgbaColor;
   brushSize: number;
diff --git a/invokeai/frontend/web/src/features/canvas/util/colorToString.ts b/invokeai/frontend/web/src/features/canvas/util/colorToString.ts
index 378448dd3f..a4b619c5de 100644
--- a/invokeai/frontend/web/src/features/canvas/util/colorToString.ts
+++ b/invokeai/frontend/web/src/features/canvas/util/colorToString.ts
@@ -1,16 +1,6 @@
-import type { RgbaColor, RgbColor } from 'react-colorful';
+import type { RgbaColor } from 'react-colorful';
 
 export const rgbaColorToString = (color: RgbaColor): string => {
   const { r, g, b, a } = color;
   return `rgba(${r}, ${g}, ${b}, ${a})`;
 };
-
-export const rgbaColorToRgbString = (color: RgbaColor): string => {
-  const { r, g, b } = color;
-  return `rgba(${r}, ${g}, ${b})`;
-};
-
-export const rgbColorToString = (color: RgbColor): string => {
-  const { r, g, b } = color;
-  return `rgba(${r}, ${g}, ${b})`;
-};
diff --git a/invokeai/frontend/web/src/features/canvas/util/constants.ts b/invokeai/frontend/web/src/features/canvas/util/constants.ts
index 2579cc33eb..3291732ecc 100644
--- a/invokeai/frontend/web/src/features/canvas/util/constants.ts
+++ b/invokeai/frontend/web/src/features/canvas/util/constants.ts
@@ -1,6 +1,3 @@
-// bounding box anchor size
-export const TRANSFORMER_ANCHOR_SIZE = 15;
-
 // canvas wheel zoom exponential scale factor
 export const CANVAS_SCALE_BY = 0.999;
 
diff --git a/invokeai/frontend/web/src/features/canvas/util/roundDimensionsToMultiple.ts b/invokeai/frontend/web/src/features/canvas/util/roundDimensionsToMultiple.ts
deleted file mode 100644
index 8e526a54e6..0000000000
--- a/invokeai/frontend/web/src/features/canvas/util/roundDimensionsToMultiple.ts
+++ /dev/null
@@ -1,11 +0,0 @@
-import { roundToMultiple } from 'common/util/roundDownToMultiple';
-import type { Dimensions } from 'features/canvas/store/canvasTypes';
-
-const roundDimensionsToMultiple = (dimensions: Dimensions, multiple: number): Dimensions => {
-  return {
-    width: roundToMultiple(dimensions.width, multiple),
-    height: roundToMultiple(dimensions.height, multiple),
-  };
-};
-
-export default roundDimensionsToMultiple;
diff --git a/invokeai/frontend/web/src/features/controlAdapters/hooks/useControlAdapter.ts b/invokeai/frontend/web/src/features/controlAdapters/hooks/useControlAdapter.ts
deleted file mode 100644
index 6fdee62922..0000000000
--- a/invokeai/frontend/web/src/features/controlAdapters/hooks/useControlAdapter.ts
+++ /dev/null
@@ -1,21 +0,0 @@
-import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
-import { useAppSelector } from 'app/store/storeHooks';
-import {
-  selectControlAdapterById,
-  selectControlAdaptersSlice,
-} from 'features/controlAdapters/store/controlAdaptersSlice';
-import { useMemo } from 'react';
-
-export const useControlAdapter = (id: string) => {
-  const selector = useMemo(
-    () =>
-      createMemoizedSelector(selectControlAdaptersSlice, (controlAdapters) =>
-        selectControlAdapterById(controlAdapters, id)
-      ),
-    [id]
-  );
-
-  const controlAdapter = useAppSelector(selector);
-
-  return controlAdapter;
-};
diff --git a/invokeai/frontend/web/src/features/controlAdapters/store/controlAdaptersSlice.ts b/invokeai/frontend/web/src/features/controlAdapters/store/controlAdaptersSlice.ts
index fce94ad019..d90ccd0f2a 100644
--- a/invokeai/frontend/web/src/features/controlAdapters/store/controlAdaptersSlice.ts
+++ b/invokeai/frontend/web/src/features/controlAdapters/store/controlAdaptersSlice.ts
@@ -30,10 +30,10 @@ import type {
 } from './types';
 import { isControlNet, isControlNetOrT2IAdapter, isIPAdapter, isT2IAdapter } from './types';
 
-export const caAdapter = createEntityAdapter<ControlAdapterConfig, string>({
+const caAdapter = createEntityAdapter<ControlAdapterConfig, string>({
   selectId: (ca) => ca.id,
 });
-export const caAdapterSelectors = caAdapter.getSelectors(undefined, getSelectorsOptions);
+const caAdapterSelectors = caAdapter.getSelectors(undefined, getSelectorsOptions);
 
 export const {
   selectById: selectControlAdapterById,
@@ -43,7 +43,7 @@ export const {
   selectTotal: selectControlAdapterTotal,
 } = caAdapterSelectors;
 
-export const initialControlAdaptersState: ControlAdaptersState = caAdapter.getInitialState<{
+const initialControlAdaptersState: ControlAdaptersState = caAdapter.getInitialState<{
   _version: 1;
   pendingControlImages: string[];
 }>({
@@ -131,22 +131,6 @@ export const controlAdaptersSlice = createSlice({
         return { payload: { id, newId: uuidv4() } };
       },
     },
-    controlAdapterAddedFromImage: {
-      reducer: (
-        state,
-        action: PayloadAction<{
-          id: string;
-          type: ControlAdapterType;
-          controlImage: string;
-        }>
-      ) => {
-        const { id, type, controlImage } = action.payload;
-        caAdapter.addOne(state, buildControlAdapter(id, type, { controlImage }));
-      },
-      prepare: (payload: { type: ControlAdapterType; controlImage: string }) => {
-        return { payload: { ...payload, id: uuidv4() } };
-      },
-    },
     controlAdapterRemoved: (state, action: PayloadAction<{ id: string }>) => {
       caAdapter.removeOne(state, action.payload.id);
     },
@@ -407,7 +391,6 @@ export const {
   controlAdapterAdded,
   controlAdapterRecalled,
   controlAdapterDuplicated,
-  controlAdapterAddedFromImage,
   controlAdapterRemoved,
   controlAdapterImageChanged,
   controlAdapterProcessedImageChanged,
@@ -426,16 +409,12 @@ export const {
   controlAdapterModelCleared,
 } = controlAdaptersSlice.actions;
 
-export const isAnyControlAdapterAdded = isAnyOf(
-  controlAdapterAdded,
-  controlAdapterAddedFromImage,
-  controlAdapterRecalled
-);
+export const isAnyControlAdapterAdded = isAnyOf(controlAdapterAdded, controlAdapterRecalled);
 
 export const selectControlAdaptersSlice = (state: RootState) => state.controlAdapters;
 
 /* eslint-disable-next-line @typescript-eslint/no-explicit-any */
-export const migrateControlAdaptersState = (state: any): any => {
+const migrateControlAdaptersState = (state: any): any => {
   if (!('_version' in state)) {
     state._version = 1;
   }
diff --git a/invokeai/frontend/web/src/features/controlAdapters/store/types.ts b/invokeai/frontend/web/src/features/controlAdapters/store/types.ts
index d7fac2a0f8..3665355ecf 100644
--- a/invokeai/frontend/web/src/features/controlAdapters/store/types.ts
+++ b/invokeai/frontend/web/src/features/controlAdapters/store/types.ts
@@ -4,7 +4,6 @@ import type {
   ParameterIPAdapterModel,
   ParameterT2IAdapterModel,
 } from 'features/parameters/types/parameterSchemas';
-import { isObject } from 'lodash-es';
 import type { components } from 'services/api/schema';
 import type {
   CannyImageProcessorInvocation,
@@ -81,7 +80,7 @@ export type RequiredDepthAnythingImageProcessorInvocation = O.Required<
   'type' | 'model_size' | 'resolution' | 'offload'
 >;
 
-export const zDepthAnythingModelSize = z.enum(['large', 'base', 'small']);
+const zDepthAnythingModelSize = z.enum(['large', 'base', 'small']);
 export type DepthAnythingModelSize = z.infer<typeof zDepthAnythingModelSize>;
 export const isDepthAnythingModelSize = (v: unknown): v is DepthAnythingModelSize =>
   zDepthAnythingModelSize.safeParse(v).success;
@@ -186,151 +185,9 @@ export type RequiredControlAdapterProcessorNode =
     >
   | { type: 'none' };
 
-/**
- * Type guard for CannyImageProcessorInvocation
- */
-export const isCannyImageProcessorInvocation = (obj: unknown): obj is CannyImageProcessorInvocation => {
-  if (isObject(obj) && 'type' in obj && obj.type === 'canny_image_processor') {
-    return true;
-  }
-  return false;
-};
-
-/**
- * Type guard for ColorMapImageProcessorInvocation
- */
-export const isColorMapImageProcessorInvocation = (obj: unknown): obj is ColorMapImageProcessorInvocation => {
-  if (isObject(obj) && 'type' in obj && obj.type === 'color_map_image_processor') {
-    return true;
-  }
-  return false;
-};
-
-/**
- * Type guard for ContentShuffleImageProcessorInvocation
- */
-export const isContentShuffleImageProcessorInvocation = (
-  obj: unknown
-): obj is ContentShuffleImageProcessorInvocation => {
-  if (isObject(obj) && 'type' in obj && obj.type === 'content_shuffle_image_processor') {
-    return true;
-  }
-  return false;
-};
-
-/**
- * Type guard for DepthAnythingImageProcessorInvocation
- */
-export const isDepthAnythingImageProcessorInvocation = (obj: unknown): obj is DepthAnythingImageProcessorInvocation => {
-  if (isObject(obj) && 'type' in obj && obj.type === 'depth_anything_image_processor') {
-    return true;
-  }
-  return false;
-};
-
-/**
- * Type guard for HedImageprocessorInvocation
- */
-export const isHedImageprocessorInvocation = (obj: unknown): obj is HedImageProcessorInvocation => {
-  if (isObject(obj) && 'type' in obj && obj.type === 'hed_image_processor') {
-    return true;
-  }
-  return false;
-};
-
-/**
- * Type guard for LineartAnimeImageProcessorInvocation
- */
-export const isLineartAnimeImageProcessorInvocation = (obj: unknown): obj is LineartAnimeImageProcessorInvocation => {
-  if (isObject(obj) && 'type' in obj && obj.type === 'lineart_anime_image_processor') {
-    return true;
-  }
-  return false;
-};
-
-/**
- * Type guard for LineartImageProcessorInvocation
- */
-export const isLineartImageProcessorInvocation = (obj: unknown): obj is LineartImageProcessorInvocation => {
-  if (isObject(obj) && 'type' in obj && obj.type === 'lineart_image_processor') {
-    return true;
-  }
-  return false;
-};
-
-/**
- * Type guard for MediapipeFaceProcessorInvocation
- */
-export const isMediapipeFaceProcessorInvocation = (obj: unknown): obj is MediapipeFaceProcessorInvocation => {
-  if (isObject(obj) && 'type' in obj && obj.type === 'mediapipe_face_processor') {
-    return true;
-  }
-  return false;
-};
-
-/**
- * Type guard for MidasDepthImageProcessorInvocation
- */
-export const isMidasDepthImageProcessorInvocation = (obj: unknown): obj is MidasDepthImageProcessorInvocation => {
-  if (isObject(obj) && 'type' in obj && obj.type === 'midas_depth_image_processor') {
-    return true;
-  }
-  return false;
-};
-
-/**
- * Type guard for MlsdImageProcessorInvocation
- */
-export const isMlsdImageProcessorInvocation = (obj: unknown): obj is MlsdImageProcessorInvocation => {
-  if (isObject(obj) && 'type' in obj && obj.type === 'mlsd_image_processor') {
-    return true;
-  }
-  return false;
-};
-
-/**
- * Type guard for NormalbaeImageProcessorInvocation
- */
-export const isNormalbaeImageProcessorInvocation = (obj: unknown): obj is NormalbaeImageProcessorInvocation => {
-  if (isObject(obj) && 'type' in obj && obj.type === 'normalbae_image_processor') {
-    return true;
-  }
-  return false;
-};
-
-/**
- * Type guard for DWOpenposeImageProcessorInvocation
- */
-export const isDWOpenposeImageProcessorInvocation = (obj: unknown): obj is DWOpenposeImageProcessorInvocation => {
-  if (isObject(obj) && 'type' in obj && obj.type === 'dw_openpose_image_processor') {
-    return true;
-  }
-  return false;
-};
-
-/**
- * Type guard for PidiImageProcessorInvocation
- */
-export const isPidiImageProcessorInvocation = (obj: unknown): obj is PidiImageProcessorInvocation => {
-  if (isObject(obj) && 'type' in obj && obj.type === 'pidi_image_processor') {
-    return true;
-  }
-  return false;
-};
-
-/**
- * Type guard for ZoeDepthImageProcessorInvocation
- */
-export const isZoeDepthImageProcessorInvocation = (obj: unknown): obj is ZoeDepthImageProcessorInvocation => {
-  if (isObject(obj) && 'type' in obj && obj.type === 'zoe_depth_image_processor') {
-    return true;
-  }
-  return false;
-};
-
 export type ControlMode = NonNullable<components['schemas']['ControlNetInvocation']['control_mode']>;
 
-export const zResizeMode = z.enum(['just_resize', 'crop_resize', 'fill_resize', 'just_resize_simple']);
+const zResizeMode = z.enum(['just_resize', 'crop_resize', 'fill_resize', 'just_resize_simple']);
 export type ResizeMode = z.infer<typeof zResizeMode>;
 export const isResizeMode = (v: unknown): v is ResizeMode => zResizeMode.safeParse(v).success;
 
diff --git a/invokeai/frontend/web/src/features/dynamicPrompts/store/dynamicPromptsSlice.ts b/invokeai/frontend/web/src/features/dynamicPrompts/store/dynamicPromptsSlice.ts
index 7bb0b29659..27925c833f 100644
--- a/invokeai/frontend/web/src/features/dynamicPrompts/store/dynamicPromptsSlice.ts
+++ b/invokeai/frontend/web/src/features/dynamicPrompts/store/dynamicPromptsSlice.ts
@@ -3,11 +3,11 @@ import { createSlice } from '@reduxjs/toolkit';
 import type { PersistConfig, RootState } from 'app/store/store';
 import { z } from 'zod';
 
-export const zSeedBehaviour = z.enum(['PER_ITERATION', 'PER_PROMPT']);
+const zSeedBehaviour = z.enum(['PER_ITERATION', 'PER_PROMPT']);
 export type SeedBehaviour = z.infer<typeof zSeedBehaviour>;
 export const isSeedBehaviour = (v: unknown): v is SeedBehaviour => zSeedBehaviour.safeParse(v).success;
 
-export interface DynamicPromptsState {
+interface DynamicPromptsState {
   _version: 1;
   maxPrompts: number;
   combinatorial: boolean;
@@ -18,7 +18,7 @@ export interface DynamicPromptsState {
   seedBehaviour: SeedBehaviour;
 }
 
-export const initialDynamicPromptsState: DynamicPromptsState = {
+const initialDynamicPromptsState: DynamicPromptsState = {
   _version: 1,
   maxPrompts: 100,
   combinatorial: true,
@@ -29,11 +29,9 @@ export const initialDynamicPromptsState: DynamicPromptsState = {
   seedBehaviour: 'PER_ITERATION',
 };
 
-const initialState: DynamicPromptsState = initialDynamicPromptsState;
-
 export const dynamicPromptsSlice = createSlice({
   name: 'dynamicPrompts',
-  initialState,
+  initialState: initialDynamicPromptsState,
   reducers: {
     maxPromptsChanged: (state, action: PayloadAction<number>) => {
       state.maxPrompts = action.payload;
@@ -77,7 +75,7 @@ export const {
 export const selectDynamicPromptsSlice = (state: RootState) => state.dynamicPrompts;
 
 /* eslint-disable-next-line @typescript-eslint/no-explicit-any */
-export const migrateDynamicPromptsState = (state: any): any => {
+const migrateDynamicPromptsState = (state: any): any => {
   if (!('_version' in state)) {
     state._version = 1;
   }
diff --git a/invokeai/frontend/web/src/features/gallery/store/actions.ts b/invokeai/frontend/web/src/features/gallery/store/actions.ts
index e62a350756..0b42890a26 100644
--- a/invokeai/frontend/web/src/features/gallery/store/actions.ts
+++ b/invokeai/frontend/web/src/features/gallery/store/actions.ts
@@ -1,15 +1,4 @@
 import { createAction } from '@reduxjs/toolkit';
-import type { ImageUsage } from 'features/deleteImageModal/store/types';
-import type { BoardDTO } from 'services/api/types';
-
-export type RequestedBoardImagesDeletionArg = {
-  board: BoardDTO;
-  imagesUsage: ImageUsage;
-};
-
-export const requestedBoardImagesDeletion = createAction<RequestedBoardImagesDeletionArg>(
-  'gallery/requestedBoardImagesDeletion'
-);
 
 export const sentImageToCanvas = createAction('gallery/sentImageToCanvas');
 
diff --git a/invokeai/frontend/web/src/features/gallery/store/gallerySlice.ts b/invokeai/frontend/web/src/features/gallery/store/gallerySlice.ts
index f351d91339..b16efc02b3 100644
--- a/invokeai/frontend/web/src/features/gallery/store/gallerySlice.ts
+++ b/invokeai/frontend/web/src/features/gallery/store/gallerySlice.ts
@@ -9,7 +9,7 @@ import type { ImageDTO } from 'services/api/types';
 import type { BoardId, GalleryState, GalleryView } from './types';
 import { IMAGE_LIMIT, INITIAL_IMAGE_LIMIT } from './types';
 
-export const initialGalleryState: GalleryState = {
+const initialGalleryState: GalleryState = {
   selection: [],
   shouldAutoSwitch: true,
   autoAssignBoardOnClick: true,
@@ -117,7 +117,7 @@ const isAnyBoardDeleted = isAnyOf(
 export const selectGallerySlice = (state: RootState) => state.gallery;
 
 /* eslint-disable-next-line @typescript-eslint/no-explicit-any */
-export const migrateGalleryState = (state: any): any => {
+const migrateGalleryState = (state: any): any => {
   if (!('_version' in state)) {
     state._version = 1;
   }
diff --git a/invokeai/frontend/web/src/features/hrf/store/hrfSlice.ts b/invokeai/frontend/web/src/features/hrf/store/hrfSlice.ts
index 4c5769550b..9b6e1f944e 100644
--- a/invokeai/frontend/web/src/features/hrf/store/hrfSlice.ts
+++ b/invokeai/frontend/web/src/features/hrf/store/hrfSlice.ts
@@ -10,18 +10,16 @@ export interface HRFState {
   hrfMethod: ParameterHRFMethod;
 }
 
-export const initialHRFState: HRFState = {
+const initialHRFState: HRFState = {
   _version: 1,
   hrfStrength: 0.45,
   hrfEnabled: false,
   hrfMethod: 'ESRGAN',
 };
 
-const initialState: HRFState = initialHRFState;
-
 export const hrfSlice = createSlice({
   name: 'hrf',
-  initialState,
+  initialState: initialHRFState,
   reducers: {
     setHrfStrength: (state, action: PayloadAction<number>) => {
       state.hrfStrength = action.payload;
@@ -40,7 +38,7 @@ export const { setHrfEnabled, setHrfStrength, setHrfMethod } = hrfSlice.actions;
 export const selectHrfSlice = (state: RootState) => state.hrf;
 
 /* eslint-disable-next-line @typescript-eslint/no-explicit-any */
-export const migrateHRFState = (state: any): any => {
+const migrateHRFState = (state: any): any => {
   if (!('_version' in state)) {
     state._version = 1;
   }
diff --git a/invokeai/frontend/web/src/features/lora/store/loraSlice.ts b/invokeai/frontend/web/src/features/lora/store/loraSlice.ts
index 83f2f2312a..c6518c214e 100644
--- a/invokeai/frontend/web/src/features/lora/store/loraSlice.ts
+++ b/invokeai/frontend/web/src/features/lora/store/loraSlice.ts
@@ -21,7 +21,7 @@ export type LoraState = {
   loras: Record<string, LoRA>;
 };
 
-export const initialLoraState: LoraState = {
+const initialLoraState: LoraState = {
   _version: 1,
   loras: {},
 };
@@ -41,9 +41,6 @@ export const loraSlice = createSlice({
       const key = action.payload;
       delete state.loras[key];
     },
-    lorasCleared: (state) => {
-      state.loras = {};
-    },
     loraWeightChanged: (state, action: PayloadAction<{ key: string; weight: number }>) => {
       const { key, weight } = action.payload;
       const lora = state.loras[key];
@@ -52,14 +49,6 @@ export const loraSlice = createSlice({
       }
       lora.weight = weight;
     },
-    loraWeightReset: (state, action: PayloadAction<string>) => {
-      const key = action.payload;
-      const lora = state.loras[key];
-      if (!lora) {
-        return;
-      }
-      lora.weight = defaultLoRAConfig.weight;
-    },
     loraIsEnabledChanged: (state, action: PayloadAction<{ key: string; isEnabled: boolean }>) => {
       const { key, isEnabled } = action.payload;
       const lora = state.loras[key];
@@ -71,20 +60,12 @@ export const loraSlice = createSlice({
   },
 });
 
-export const {
-  loraAdded,
-  loraRemoved,
-  loraWeightChanged,
-  loraWeightReset,
-  loraIsEnabledChanged,
-  lorasCleared,
-  loraRecalled,
-} = loraSlice.actions;
+export const { loraAdded, loraRemoved, loraWeightChanged, loraIsEnabledChanged, loraRecalled } = loraSlice.actions;
 
 export const selectLoraSlice = (state: RootState) => state.lora;
 
 /* eslint-disable-next-line @typescript-eslint/no-explicit-any */
-export const migrateLoRAState = (state: any): any => {
+const migrateLoRAState = (state: any): any => {
   if (!('_version' in state)) {
     state._version = 1;
   }
diff --git a/invokeai/frontend/web/src/features/metadata/exceptions.ts b/invokeai/frontend/web/src/features/metadata/exceptions.ts
index ffe4e98c79..8b13789179 100644
--- a/invokeai/frontend/web/src/features/metadata/exceptions.ts
+++ b/invokeai/frontend/web/src/features/metadata/exceptions.ts
@@ -1,27 +1 @@
-/**
- * Raised when metadata parsing fails.
- */
-export class MetadataParseError extends Error {
-  /**
-   * Create MetadataParseError
-   * @param {String} message
-   */
-  constructor(message: string) {
-    super(message);
-    this.name = this.constructor.name;
-  }
-}
 
-/**
- * Raised when metadata recall fails.
- */
-export class MetadataRecallError extends Error {
-  /**
-   * Create MetadataRecallError
-   * @param {String} message
-   */
-  constructor(message: string) {
-    super(message);
-    this.name = this.constructor.name;
-  }
-}
diff --git a/invokeai/frontend/web/src/features/metadata/types.ts b/invokeai/frontend/web/src/features/metadata/types.ts
index ef48946d58..aa8d334521 100644
--- a/invokeai/frontend/web/src/features/metadata/types.ts
+++ b/invokeai/frontend/web/src/features/metadata/types.ts
@@ -22,7 +22,6 @@ export type MetadataRecallOptions = MetadataParseOptions;
  * A function that recalls a parsed and validated metadata value.
  *
  * @param value The value to recall.
- * @throws MetadataRecallError if the value cannot be recalled.
  */
 export type MetadataRecallFunc<T> = (value: T) => void;
 
@@ -49,7 +48,7 @@ export type MetadataParseFunc<T = unknown> = (metadata: unknown) => Promise<T>;
  *
  * @param value The value to validate.
  * @returns A promise that resolves to the validated value.
- * @throws MetadataRecallError if the value is invalid.
+ * @throws MetadataParseError if the value is invalid.
  */
 export type MetadataValidateFunc<T> = (value: T) => Promise<T>;
 
@@ -88,7 +87,6 @@ export type MetadataHandlers<TValue = unknown, TItem = unknown> = {
    * @param value The value to recall.
    * @param withToast Whether to show a toast on success or failure.
    * @returns A promise that resolves when the recall operation is complete.
-   * @throws MetadataRecallError if the value cannot be recalled.
    */
   recall?: (value: TValue, withToast?: boolean) => Promise<void>;
   /**
@@ -99,7 +97,6 @@ export type MetadataHandlers<TValue = unknown, TItem = unknown> = {
    * @param item The item to recall. It should be an item from the array.
    * @param withToast Whether to show a toast on success or failure.
    * @returns A promise that resolves when the recall operation is complete.
-   * @throws MetadataRecallError if the value cannot be recalled.
    */
   recallItem?: (item: TItem, withToast?: boolean) => Promise<void>;
   /**
diff --git a/invokeai/frontend/web/src/features/metadata/util/modelFetchingHelpers.ts b/invokeai/frontend/web/src/features/metadata/util/modelFetchingHelpers.ts
index 9bc43587cc..98aa633259 100644
--- a/invokeai/frontend/web/src/features/metadata/util/modelFetchingHelpers.ts
+++ b/invokeai/frontend/web/src/features/metadata/util/modelFetchingHelpers.ts
@@ -4,8 +4,6 @@ import { isModelIdentifier, isModelIdentifierV2 } from 'features/nodes/types/com
 import { modelsApi } from 'services/api/endpoints/models';
 import type { AnyModelConfig, BaseModelType, ModelType } from 'services/api/types';
 
-
-
 /**
  * Raised when a model config is unable to be fetched.
  */
@@ -93,19 +91,6 @@ export const fetchModelConfigWithTypeGuard = async <T extends AnyModelConfig>(
   return modelConfig;
 };
 
-/**
- * Raises an error if the source base model is incompatible with the target base model.
- * @param sourceBase The source base model.
- * @param targetBase The target base model.
- * @param message An optional custom message to include in the error.
- * @throws {InvalidModelConfigError} If the source base model is incompatible with the target base model.
- */
-export const raiseIfBaseIncompatible = (sourceBase: BaseModelType, targetBase?: BaseModelType, message?: string) => {
-  if (targetBase && sourceBase !== targetBase) {
-    throw new InvalidModelConfigError(message || `Incompatible base models: ${sourceBase} and ${targetBase}`);
-  }
-};
-
 /**
  * Fetches the model key from a model identifier. This includes fetching the key for MM1 format model identifiers.
  * @param modelIdentifier The model identifier. The MM2 format `{key: string}` simply extracts the key. The MM1 format
diff --git a/invokeai/frontend/web/src/features/metadata/util/parsers.ts b/invokeai/frontend/web/src/features/metadata/util/parsers.ts
index 3248827ba1..eba51f4fd6 100644
--- a/invokeai/frontend/web/src/features/metadata/util/parsers.ts
+++ b/invokeai/frontend/web/src/features/metadata/util/parsers.ts
@@ -6,12 +6,13 @@ import {
 } from 'features/controlAdapters/util/buildControlAdapter';
 import type { LoRA } from 'features/lora/store/loraSlice';
 import { defaultLoRAConfig } from 'features/lora/store/loraSlice';
-import { MetadataParseError } from 'features/metadata/exceptions';
-import type { ControlNetConfigMetadata, IPAdapterConfigMetadata, MetadataParseFunc, T2IAdapterConfigMetadata } from 'features/metadata/types';
-import {
-  fetchModelConfigWithTypeGuard,
-  getModelKey,
-} from 'features/metadata/util/modelFetchingHelpers';
+import type {
+  ControlNetConfigMetadata,
+  IPAdapterConfigMetadata,
+  MetadataParseFunc,
+  T2IAdapterConfigMetadata,
+} from 'features/metadata/types';
+import { fetchModelConfigWithTypeGuard, getModelKey } from 'features/metadata/util/modelFetchingHelpers';
 import {
   zControlField,
   zIPAdapterField,
@@ -74,6 +75,19 @@ import { v4 as uuidv4 } from 'uuid';
 
 export const MetadataParsePendingToken = Symbol('pending');
 export const MetadataParseFailedToken = Symbol('failed');
+/**
+ * Raised when metadata parsing fails.
+ */
+export class MetadataParseError extends Error {
+  /**
+   * Create MetadataParseError
+   * @param {String} message
+   */
+  constructor(message: string) {
+    super(message);
+    this.name = this.constructor.name;
+  }
+}
 
 /**
  * An async function that a property from an object and validates its type using a type guard. If the property is missing
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/components/SyncModels/SyncModelsButton.tsx b/invokeai/frontend/web/src/features/modelManagerV2/components/SyncModels/SyncModelsButton.tsx
deleted file mode 100644
index 8a49bc2585..0000000000
--- a/invokeai/frontend/web/src/features/modelManagerV2/components/SyncModels/SyncModelsButton.tsx
+++ /dev/null
@@ -1,32 +0,0 @@
-import type { ButtonProps } from '@invoke-ai/ui-library';
-import { Button } from '@invoke-ai/ui-library';
-import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';
-import { memo } from 'react';
-import { useTranslation } from 'react-i18next';
-import { PiArrowsClockwiseBold } from 'react-icons/pi';
-
-import { useSyncModels } from './useSyncModels';
-
-export const SyncModelsButton = memo((props: Omit<ButtonProps, 'children'>) => {
-  const { t } = useTranslation();
-  const { syncModels, isLoading } = useSyncModels();
-  const isSyncModelEnabled = useFeatureStatus('syncModels').isFeatureEnabled;
-
-  if (!isSyncModelEnabled) {
-    return null;
-  }
-
-  return (
-    <Button
-      isLoading={isLoading}
-      onClick={syncModels}
-      leftIcon={<PiArrowsClockwiseBold />}
-      minW="max-content"
-      {...props}
-    >
-      {t('modelManager.syncModels')}
-    </Button>
-  );
-});
-
-SyncModelsButton.displayName = 'SyncModelsButton';
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/store/modelManagerV2Slice.ts b/invokeai/frontend/web/src/features/modelManagerV2/store/modelManagerV2Slice.ts
index 0ea2610ac4..10f1be75ad 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/store/modelManagerV2Slice.ts
+++ b/invokeai/frontend/web/src/features/modelManagerV2/store/modelManagerV2Slice.ts
@@ -10,7 +10,7 @@ type ModelManagerState = {
   filteredModelType: string | null;
 };
 
-export const initialModelManagerState: ModelManagerState = {
+const initialModelManagerState: ModelManagerState = {
   _version: 1,
   selectedModelKey: null,
   selectedModelMode: 'view',
@@ -42,10 +42,10 @@ export const modelManagerV2Slice = createSlice({
 export const { setSelectedModelKey, setSearchTerm, setFilteredModelType, setSelectedModelMode } =
   modelManagerV2Slice.actions;
 
-export const selectModelManagerSlice = (state: RootState) => state.modelmanager;
+export const selectModelManagerSlice = (state: RootState) => state.modelmanagerV2;
 
 /* eslint-disable-next-line @typescript-eslint/no-explicit-any */
-export const migrateModelManagerState = (state: any): any => {
+const migrateModelManagerState = (state: any): any => {
   if (!('_version' in state)) {
     state._version = 1;
   }
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImport.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImport.tsx
index cd5c5ab4e9..8f474537cc 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImport.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImport.tsx
@@ -16,11 +16,6 @@ import { useForm } from 'react-hook-form';
 import { useTranslation } from 'react-i18next';
 import { useImportAdvancedModelMutation } from 'services/api/endpoints/models';
 import type { AnyModelConfig } from 'services/api/types';
-import { z } from 'zod';
-
-export const zManualAddMode = z.enum(['diffusers', 'checkpoint']);
-export type ManualAddMode = z.infer<typeof zManualAddMode>;
-export const isManualAddMode = (v: unknown): v is ManualAddMode => zManualAddMode.safeParse(v).success;
 
 export const AdvancedImport = () => {
   const dispatch = useAppDispatch();
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/FieldHandle.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/FieldHandle.tsx
index acff5895f3..959b13c2d0 100644
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/FieldHandle.tsx
+++ b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/FieldHandle.tsx
@@ -9,23 +9,6 @@ import { memo, useMemo } from 'react';
 import type { HandleType } from 'reactflow';
 import { Handle, Position } from 'reactflow';
 
-export const handleBaseStyles: CSSProperties = {
-  position: 'absolute',
-  width: '1rem',
-  height: '1rem',
-  borderWidth: 0,
-  zIndex: 1,
-};
-``;
-
-export const inputHandleStyles: CSSProperties = {
-  left: '-1rem',
-};
-
-export const outputHandleStyles: CSSProperties = {
-  right: '-0.5rem',
-};
-
 type FieldHandleProps = {
   fieldTemplate: FieldInputTemplate | FieldOutputTemplate;
   handleType: HandleType;
diff --git a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/FieldTitle.tsx b/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/FieldTitle.tsx
deleted file mode 100644
index 61ce8fd971..0000000000
--- a/invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/FieldTitle.tsx
+++ /dev/null
@@ -1,34 +0,0 @@
-import { Flex, forwardRef, Text } from '@invoke-ai/ui-library';
-import { useFieldLabel } from 'features/nodes/hooks/useFieldLabel';
-import { useFieldTemplateTitle } from 'features/nodes/hooks/useFieldTemplateTitle';
-import { memo } from 'react';
-
-interface Props {
-  nodeId: string;
-  fieldName: string;
-  kind: 'inputs' | 'outputs';
-  isMissingInput?: boolean;
-}
-
-const FieldTitle = forwardRef((props: Props, ref) => {
-  const { nodeId, fieldName, kind, isMissingInput = false } = props;
-  const label = useFieldLabel(nodeId, fieldName);
-  const fieldTemplateTitle = useFieldTemplateTitle(nodeId, fieldName, kind);
-
-  return (
-    <Flex
-      ref={ref}
-      position="relative"
-      overflow="hidden"
-      alignItems="center"
-      justifyContent="flex-start"
-      gap={1}
-      h="full"
-      w="full"
-    >
-      <Text fontWeight={isMissingInput ? 'bold' : 'normal'}>{label || fieldTemplateTitle}</Text>
-    </Flex>
-  );
-});
-
-export default memo(FieldTitle);
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useAnyOrDirectInputFieldNames.ts b/invokeai/frontend/web/src/features/nodes/hooks/useAnyOrDirectInputFieldNames.ts
index c882924e24..13c78bae84 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useAnyOrDirectInputFieldNames.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useAnyOrDirectInputFieldNames.ts
@@ -1,6 +1,6 @@
+import { EMPTY_ARRAY } from "app/store/constants";
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppSelector } from 'app/store/storeHooks';
-import { EMPTY_ARRAY } from 'app/store/util';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
 import { selectNodeTemplate } from 'features/nodes/store/selectors';
 import { getSortedFilteredFieldNames } from 'features/nodes/util/node/getSortedFilteredFieldNames';
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useBuildNode.ts b/invokeai/frontend/web/src/features/nodes/hooks/useBuildNode.ts
index b19edf3c85..cce2265d83 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useBuildNode.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useBuildNode.ts
@@ -1,17 +1,12 @@
 import { useAppSelector } from 'app/store/storeHooks';
-import { DRAG_HANDLE_CLASSNAME, NODE_WIDTH } from 'features/nodes/types/constants';
+import { NODE_WIDTH } from 'features/nodes/types/constants';
 import type { AnyNode, InvocationTemplate } from 'features/nodes/types/invocation';
 import { buildCurrentImageNode } from 'features/nodes/util/node/buildCurrentImageNode';
 import { buildInvocationNode } from 'features/nodes/util/node/buildInvocationNode';
 import { buildNotesNode } from 'features/nodes/util/node/buildNotesNode';
 import { useCallback } from 'react';
-import type { Node } from 'reactflow';
 import { useReactFlow } from 'reactflow';
 
-export const SHARED_NODE_PROPERTIES: Partial<Node> = {
-  dragHandle: `.${DRAG_HANDLE_CLASSNAME}`,
-};
-
 export const useBuildNode = () => {
   const nodeTemplates = useAppSelector((s) => s.nodes.templates);
 
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useConnectionInputFieldNames.ts b/invokeai/frontend/web/src/features/nodes/hooks/useConnectionInputFieldNames.ts
index dc8a05b88c..43b6ed6ef1 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useConnectionInputFieldNames.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useConnectionInputFieldNames.ts
@@ -1,6 +1,6 @@
+import { EMPTY_ARRAY } from "app/store/constants";
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppSelector } from 'app/store/storeHooks';
-import { EMPTY_ARRAY } from 'app/store/util';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
 import { selectNodeTemplate } from 'features/nodes/store/selectors';
 import { getSortedFilteredFieldNames } from 'features/nodes/util/node/getSortedFilteredFieldNames';
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useOutputFieldNames.ts b/invokeai/frontend/web/src/features/nodes/hooks/useOutputFieldNames.ts
index 24863080a7..bbcd7f2068 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useOutputFieldNames.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useOutputFieldNames.ts
@@ -1,6 +1,6 @@
 import { createSelector } from '@reduxjs/toolkit';
+import { EMPTY_ARRAY } from "app/store/constants";
 import { useAppSelector } from 'app/store/storeHooks';
-import { EMPTY_ARRAY } from 'app/store/util';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
 import { selectNodeTemplate } from 'features/nodes/store/selectors';
 import { getSortedFilteredFieldNames } from 'features/nodes/util/node/getSortedFilteredFieldNames';
diff --git a/invokeai/frontend/web/src/features/nodes/store/actions.ts b/invokeai/frontend/web/src/features/nodes/store/actions.ts
index b32a3ba997..52f1bf6e38 100644
--- a/invokeai/frontend/web/src/features/nodes/store/actions.ts
+++ b/invokeai/frontend/web/src/features/nodes/store/actions.ts
@@ -2,10 +2,10 @@ import { createAction, isAnyOf } from '@reduxjs/toolkit';
 import type { WorkflowV3 } from 'features/nodes/types/workflow';
 import type { Graph } from 'services/api/types';
 
-export const textToImageGraphBuilt = createAction<Graph>('nodes/textToImageGraphBuilt');
-export const imageToImageGraphBuilt = createAction<Graph>('nodes/imageToImageGraphBuilt');
+const textToImageGraphBuilt = createAction<Graph>('nodes/textToImageGraphBuilt');
+const imageToImageGraphBuilt = createAction<Graph>('nodes/imageToImageGraphBuilt');
 export const canvasGraphBuilt = createAction<Graph>('nodes/canvasGraphBuilt');
-export const nodesGraphBuilt = createAction<Graph>('nodes/nodesGraphBuilt');
+const nodesGraphBuilt = createAction<Graph>('nodes/nodesGraphBuilt');
 
 export const isAnyGraphBuilt = isAnyOf(
   textToImageGraphBuilt,
diff --git a/invokeai/frontend/web/src/features/nodes/store/nodesSlice.ts b/invokeai/frontend/web/src/features/nodes/store/nodesSlice.ts
index 6b596da063..8c5f894548 100644
--- a/invokeai/frontend/web/src/features/nodes/store/nodesSlice.ts
+++ b/invokeai/frontend/web/src/features/nodes/store/nodesSlice.ts
@@ -64,7 +64,6 @@ import {
   getIncomers,
   getOutgoers,
   SelectionMode,
-  updateEdge,
 } from 'reactflow';
 import {
   socketGeneratorProgress,
@@ -88,7 +87,7 @@ const initialNodeExecutionState: Omit<NodeExecutionState, 'nodeId'> = {
   outputs: [],
 };
 
-export const initialNodesState: NodesState = {
+const initialNodesState: NodesState = {
   _version: 1,
   nodes: [],
   edges: [],
@@ -215,10 +214,6 @@ export const nodesSlice = createSlice({
     edgeAdded: (state, action: PayloadAction<Edge>) => {
       state.edges = addEdge(action.payload, state.edges);
     },
-    edgeUpdated: (state, action: PayloadAction<{ oldEdge: Edge; newConnection: Connection }>) => {
-      const { oldEdge, newConnection } = action.payload;
-      state.edges = updateEdge(oldEdge, newConnection, state.edges);
-    },
     connectionStarted: (state, action: PayloadAction<OnConnectStartParams>) => {
       state.connectionStartParams = action.payload;
       state.connectionMade = state.modifyingEdge;
@@ -674,9 +669,6 @@ export const nodesSlice = createSlice({
       state.connectionStartParams = null;
       state.connectionStartFieldType = null;
     },
-    addNodePopoverToggled: (state) => {
-      state.isAddNodePopoverOpen = !state.isAddNodePopoverOpen;
-    },
     selectionModeChanged: (state, action: PayloadAction<boolean>) => {
       state.selectionMode = action.payload ? SelectionMode.Full : SelectionMode.Partial;
     },
@@ -762,7 +754,6 @@ export const nodesSlice = createSlice({
 export const {
   addNodePopoverClosed,
   addNodePopoverOpened,
-  addNodePopoverToggled,
   connectionEnded,
   connectionMade,
   connectionStarted,
@@ -770,7 +761,6 @@ export const {
   edgeChangeStarted,
   edgesChanged,
   edgesDeleted,
-  edgeUpdated,
   fieldValueReset,
   fieldBoardValueChanged,
   fieldBooleanValueChanged,
@@ -824,7 +814,6 @@ export const isAnyNodeOrEdgeMutation = isAnyOf(
   edgeDeleted,
   edgesChanged,
   edgesDeleted,
-  edgeUpdated,
   fieldBoardValueChanged,
   fieldBooleanValueChanged,
   fieldColorValueChanged,
@@ -857,7 +846,7 @@ export const isAnyNodeOrEdgeMutation = isAnyOf(
 export const selectNodesSlice = (state: RootState) => state.nodes;
 
 /* eslint-disable-next-line @typescript-eslint/no-explicit-any */
-export const migrateNodesState = (state: any): any => {
+const migrateNodesState = (state: any): any => {
   if (!('_version' in state)) {
     state._version = 1;
   }
diff --git a/invokeai/frontend/web/src/features/nodes/store/workflowSlice.ts b/invokeai/frontend/web/src/features/nodes/store/workflowSlice.ts
index 4f40a68e1f..fcd4b5e1ac 100644
--- a/invokeai/frontend/web/src/features/nodes/store/workflowSlice.ts
+++ b/invokeai/frontend/web/src/features/nodes/store/workflowSlice.ts
@@ -13,7 +13,7 @@ import { isInvocationNode } from 'features/nodes/types/invocation';
 import type { WorkflowCategory, WorkflowV3 } from 'features/nodes/types/workflow';
 import { cloneDeep, isEqual, omit, uniqBy } from 'lodash-es';
 
-export const blankWorkflow: Omit<WorkflowV3, 'nodes' | 'edges'> = {
+const blankWorkflow: Omit<WorkflowV3, 'nodes' | 'edges'> = {
   name: '',
   author: '',
   description: '',
@@ -26,7 +26,7 @@ export const blankWorkflow: Omit<WorkflowV3, 'nodes' | 'edges'> = {
   id: undefined,
 };
 
-export const initialWorkflowState: WorkflowState = {
+const initialWorkflowState: WorkflowState = {
   _version: 1,
   isTouched: false,
   mode: 'view',
@@ -195,7 +195,7 @@ export const {
 export const selectWorkflowSlice = (state: RootState) => state.workflow;
 
 /* eslint-disable-next-line @typescript-eslint/no-explicit-any */
-export const migrateWorkflowState = (state: any): any => {
+const migrateWorkflowState = (state: any): any => {
   if (!('_version' in state)) {
     state._version = 1;
   }
diff --git a/invokeai/frontend/web/src/features/nodes/types/common.test-d.ts b/invokeai/frontend/web/src/features/nodes/types/common.test-d.ts
index 7f28e864a1..5e92998657 100644
--- a/invokeai/frontend/web/src/features/nodes/types/common.test-d.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/common.test-d.ts
@@ -2,17 +2,11 @@ import type {
   BaseModel,
   BoardField,
   Classification,
-  CLIPField,
   ColorField,
   ControlField,
-  ControlNetModelField,
   ImageField,
   ImageOutput,
   IPAdapterField,
-  IPAdapterModelField,
-  LoraInfo,
-  LoRAModelField,
-  MainModelField,
   ModelInfo,
   ModelType,
   ProgressImage,
@@ -20,8 +14,6 @@ import type {
   SDXLRefinerModelField,
   SubModelType,
   T2IAdapterField,
-  T2IAdapterModelField,
-  UNetField,
   VAEField,
 } from 'features/nodes/types/common';
 import type { S } from 'services/api/types';
@@ -40,19 +32,17 @@ describe('Common types', () => {
   test('BoardField', () => assert<Equals<BoardField, S['BoardField']>>());
   test('ColorField', () => assert<Equals<ColorField, S['ColorField']>>());
   test('SchedulerField', () => assert<Equals<SchedulerField, NonNullable<S['SchedulerInvocation']['scheduler']>>>());
-  test('UNetField', () => assert<Extends<S['UNetField'], UNetField>>());
-  test('CLIPField', () => assert<Extends<S['ClipField'], CLIPField>>());
-  test('MainModelField', () => assert<Equals<MainModelField, S['MainModelField']>>());
+  // test('MainModelField', () => assert<Equals<MainModelField, S['MainModelField']>>());
   test('SDXLRefinerModelField', () => assert<Equals<SDXLRefinerModelField, S['MainModelField']>>());
   test('VAEField', () => assert<Extends<S['VaeField'], VAEField>>());
   test('ControlField', () => assert<Equals<ControlField, S['ControlField']>>());
   // @ts-expect-error TODO(psyche): fix types
   test('IPAdapterField', () => assert<Extends<IPAdapterField, S['IPAdapterField']>>());
   test('T2IAdapterField', () => assert<Equals<T2IAdapterField, S['T2IAdapterField']>>());
-  test('LoRAModelField', () => assert<Equals<LoRAModelField, S['LoRAModelField']>>());
-  test('ControlNetModelField', () => assert<Equals<ControlNetModelField, S['ControlNetModelField']>>());
-  test('IPAdapterModelField', () => assert<Equals<IPAdapterModelField, S['IPAdapterModelField']>>());
-  test('T2IAdapterModelField', () => assert<Equals<T2IAdapterModelField, S['T2IAdapterModelField']>>());
+  // test('LoRAModelField', () => assert<Equals<LoRAModelField, S['LoRAModelField']>>());
+  // test('ControlNetModelField', () => assert<Equals<ControlNetModelField, S['ControlNetModelField']>>());
+  // test('IPAdapterModelField', () => assert<Equals<IPAdapterModelField, S['IPAdapterModelField']>>());
+  // test('T2IAdapterModelField', () => assert<Equals<T2IAdapterModelField, S['T2IAdapterModelField']>>());
 
   // Model component types
   test('BaseModel', () => assert<Equals<BaseModel, S['BaseModelType']>>());
@@ -61,7 +51,6 @@ describe('Common types', () => {
   test('ModelInfo', () => assert<Equals<ModelInfo, S['ModelInfo']>>());
 
   // Misc types
-  test('LoraInfo', () => assert<Extends<S['LoraInfo'], LoraInfo>>());
   // @ts-expect-error TODO(psyche): There is no `ProgressImage` in the server types yet
   test('ProgressImage', () => assert<Equals<ProgressImage, S['ProgressImage']>>());
   test('ImageOutput', () => assert<Equals<ImageOutput, S['ImageOutput']>>());
diff --git a/invokeai/frontend/web/src/features/nodes/types/common.ts b/invokeai/frontend/web/src/features/nodes/types/common.ts
index 501286c785..923fef3c04 100644
--- a/invokeai/frontend/web/src/features/nodes/types/common.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/common.ts
@@ -102,7 +102,7 @@ export type SubModelType = z.infer<typeof zSubModelType>;
 
 export const zVAEModelField = zModelIdentifierWithBase;
 
-export const zModelInfo = zModelIdentifier.extend({
+const zModelInfo = zModelIdentifier.extend({
   submodel_type: zSubModelType.nullish(),
 });
 export type ModelInfo = z.infer<typeof zModelInfo>;
@@ -119,26 +119,6 @@ export type IPAdapterModelField = z.infer<typeof zIPAdapterModelField>;
 export const zT2IAdapterModelField = zModelIdentifierWithBase;
 export type T2IAdapterModelField = z.infer<typeof zT2IAdapterModelField>;
 
-export const zLoraInfo = zModelInfo.extend({
-  weight: z.number().optional(),
-});
-export type LoraInfo = z.infer<typeof zLoraInfo>;
-
-export const zUNetField = z.object({
-  unet: zModelInfo,
-  scheduler: zModelInfo,
-  loras: z.array(zLoraInfo),
-});
-export type UNetField = z.infer<typeof zUNetField>;
-
-export const zCLIPField = z.object({
-  tokenizer: zModelInfo,
-  text_encoder: zModelInfo,
-  skipped_layers: z.number(),
-  loras: z.array(zLoraInfo),
-});
-export type CLIPField = z.infer<typeof zCLIPField>;
-
 export const zVAEField = z.object({
   vae: zModelInfo,
 });
diff --git a/invokeai/frontend/web/src/features/queue/components/ClearQueueIconButton.tsx b/invokeai/frontend/web/src/features/queue/components/ClearQueueIconButton.tsx
index 65f2008f53..41843ad66c 100644
--- a/invokeai/frontend/web/src/features/queue/components/ClearQueueIconButton.tsx
+++ b/invokeai/frontend/web/src/features/queue/components/ClearQueueIconButton.tsx
@@ -67,5 +67,3 @@ export const ClearQueueIconButton = (props: ClearQueueButtonProps) => {
     </>
   );
 };
-
-export default ClearQueueIconButton;
diff --git a/invokeai/frontend/web/src/features/queue/components/QueueControls.tsx b/invokeai/frontend/web/src/features/queue/components/QueueControls.tsx
index 044ccc30a1..5499ecccfc 100644
--- a/invokeai/frontend/web/src/features/queue/components/QueueControls.tsx
+++ b/invokeai/frontend/web/src/features/queue/components/QueueControls.tsx
@@ -1,5 +1,5 @@
 import { ButtonGroup, Flex, Spacer } from '@invoke-ai/ui-library';
-import ClearQueueIconButton from 'features/queue/components/ClearQueueIconButton';
+import { ClearQueueIconButton } from 'features/queue/components/ClearQueueIconButton';
 import QueueFrontButton from 'features/queue/components/QueueFrontButton';
 import ProgressBar from 'features/system/components/ProgressBar';
 import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';
diff --git a/invokeai/frontend/web/src/features/settingsAccordions/components/GenerationSettingsAccordion/GenerationSettingsAccordion.tsx b/invokeai/frontend/web/src/features/settingsAccordions/components/GenerationSettingsAccordion/GenerationSettingsAccordion.tsx
index 0633193883..8922bb414c 100644
--- a/invokeai/frontend/web/src/features/settingsAccordions/components/GenerationSettingsAccordion/GenerationSettingsAccordion.tsx
+++ b/invokeai/frontend/web/src/features/settingsAccordions/components/GenerationSettingsAccordion/GenerationSettingsAccordion.tsx
@@ -10,9 +10,9 @@ import {
   TabPanels,
   Tabs,
 } from '@invoke-ai/ui-library';
+import { EMPTY_ARRAY } from "app/store/constants";
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppSelector } from 'app/store/storeHooks';
-import { EMPTY_ARRAY } from 'app/store/util';
 import { LoRAList } from 'features/lora/components/LoRAList';
 import LoRASelect from 'features/lora/components/LoRASelect';
 import { selectLoraSlice } from 'features/lora/store/loraSlice';

From 10d36b4045ddad5f3d651f28b15981a7cc2fbb9c Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 27 Feb 2024 15:08:17 +1100
Subject: [PATCH 336/411] tidy(mm): remove ONNX from AnyModelConfig

---
 invokeai/backend/model_manager/config.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/invokeai/backend/model_manager/config.py b/invokeai/backend/model_manager/config.py
index fb0593a651..7a1f3ca946 100644
--- a/invokeai/backend/model_manager/config.py
+++ b/invokeai/backend/model_manager/config.py
@@ -297,7 +297,6 @@ _MainModelConfig = Annotated[Union[MainDiffusersConfig, MainCheckpointConfig], F
 
 AnyModelConfig = Union[
     _MainModelConfig,
-    _ONNXConfig,
     _VaeConfig,
     _ControlNetConfig,
     # ModelConfigBase,

From 202e739404318ec8502585fec8eeb526b5a0eb0a Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 27 Feb 2024 15:09:05 +1100
Subject: [PATCH 337/411] tidy(api): remove non-heuristic install route

---
 invokeai/app/api/routers/model_manager.py     | 112 +----
 .../frontend/web/src/services/api/schema.ts   | 445 +-----------------
 2 files changed, 25 insertions(+), 532 deletions(-)

diff --git a/invokeai/app/api/routers/model_manager.py b/invokeai/app/api/routers/model_manager.py
index c27dba978a..50ebe5ce64 100644
--- a/invokeai/app/api/routers/model_manager.py
+++ b/invokeai/app/api/routers/model_manager.py
@@ -13,7 +13,7 @@ from pydantic import BaseModel, ConfigDict, Field
 from starlette.exceptions import HTTPException
 from typing_extensions import Annotated
 
-from invokeai.app.services.model_install import ModelInstallJob, ModelSource
+from invokeai.app.services.model_install import ModelInstallJob
 from invokeai.app.services.model_records import (
     DuplicateModelException,
     InvalidModelException,
@@ -439,8 +439,8 @@ async def add_model_record(
 
 
 @model_manager_router.post(
-    "/heuristic_install",
-    operation_id="heuristic_install_model",
+    "/install",
+    operation_id="install_model",
     responses={
         201: {"description": "The model imported successfully"},
         415: {"description": "Unrecognized file/folder format"},
@@ -449,8 +449,9 @@ async def add_model_record(
     },
     status_code=201,
 )
-async def heuristic_install(
-    source: str,
+async def install_model(
+    source: str = Query(description="Model source to install, can be a local path, repo_id, or remote URL"),
+    # TODO(MM2): Can we type this?
     config: Optional[Dict[str, Any]] = Body(
         description="Dict of fields that override auto-probed values in the model config record, such as name, description and prediction_type ",
         default=None,
@@ -491,106 +492,7 @@ async def heuristic_install(
         result: ModelInstallJob = installer.heuristic_import(
             source=source,
             config=config,
-        )
-        logger.info(f"Started installation of {source}")
-    except UnknownModelException as e:
-        logger.error(str(e))
-        raise HTTPException(status_code=424, detail=str(e))
-    except InvalidModelException as e:
-        logger.error(str(e))
-        raise HTTPException(status_code=415)
-    except ValueError as e:
-        logger.error(str(e))
-        raise HTTPException(status_code=409, detail=str(e))
-    return result
-
-
-@model_manager_router.post(
-    "/install",
-    operation_id="import_model",
-    responses={
-        201: {"description": "The model imported successfully"},
-        415: {"description": "Unrecognized file/folder format"},
-        424: {"description": "The model appeared to import successfully, but could not be found in the model manager"},
-        409: {"description": "There is already a model corresponding to this path or repo_id"},
-    },
-    status_code=201,
-)
-async def import_model(
-    source: ModelSource,
-    config: Optional[Dict[str, Any]] = Body(
-        description="Dict of fields that override auto-probed values in the model config record, such as name, description and prediction_type ",
-        default=None,
-    ),
-) -> ModelInstallJob:
-    """Install a model using its local path, repo_id, or remote URL.
-
-    Models will be downloaded, probed, configured and installed in a
-    series of background threads. The return object has `status` attribute
-    that can be used to monitor progress.
-
-    The source object is a discriminated Union of LocalModelSource,
-    HFModelSource and URLModelSource. Set the "type" field to the
-    appropriate value:
-
-    * To install a local path using LocalModelSource, pass a source of form:
-      ```
-      {
-        "type": "local",
-        "path": "/path/to/model",
-        "inplace": false
-      }
-      ```
-      The "inplace" flag, if true, will register the model in place in its
-      current filesystem location. Otherwise, the model will be copied
-      into the InvokeAI models directory.
-
-    * To install a HuggingFace repo_id using HFModelSource, pass a source of form:
-      ```
-      {
-        "type": "hf",
-        "repo_id": "stabilityai/stable-diffusion-2.0",
-        "variant": "fp16",
-        "subfolder": "vae",
-        "access_token": "f5820a918aaf01"
-      }
-      ```
-      The `variant`, `subfolder` and `access_token` fields are optional.
-
-    * To install a remote model using an arbitrary URL, pass:
-      ```
-      {
-        "type": "url",
-        "url": "http://www.civitai.com/models/123456",
-        "access_token": "f5820a918aaf01"
-      }
-      ```
-      The `access_token` field is optonal
-
-    The model's configuration record will be probed and filled in
-    automatically.  To override the default guesses, pass "metadata"
-    with a Dict containing the attributes you wish to override.
-
-    Installation occurs in the background. Either use list_model_install_jobs()
-    to poll for completion, or listen on the event bus for the following events:
-
-      * "model_install_running"
-      * "model_install_completed"
-      * "model_install_error"
-
-    On successful completion, the event's payload will contain the field "key"
-    containing the installed ID of the model. On an error, the event's payload
-    will contain the fields "error_type" and "error" describing the nature of the
-    error and its traceback, respectively.
-
-    """
-    logger = ApiDependencies.invoker.services.logger
-
-    try:
-        installer = ApiDependencies.invoker.services.model_manager.install
-        result: ModelInstallJob = installer.import_model(
-            source=source,
-            config=config,
+            access_token=access_token,
         )
         logger.info(f"Started installation of {source}")
     except UnknownModelException as e:
diff --git a/invokeai/frontend/web/src/services/api/schema.ts b/invokeai/frontend/web/src/services/api/schema.ts
index 1d347ad222..0dbe908979 100644
--- a/invokeai/frontend/web/src/services/api/schema.ts
+++ b/invokeai/frontend/web/src/services/api/schema.ts
@@ -86,9 +86,9 @@ export type paths = {
      */
     post: operations["add_model_record"];
   };
-  "/api/v2/models/heuristic_install": {
+  "/api/v2/models/install": {
     /**
-     * Heuristic Install
+     * Install Model
      * @description Install a model using a string identifier.
      *
      * `source` can be any of the following.
@@ -115,72 +115,7 @@ export type paths = {
      * See the documentation for `import_model_record` for more information on
      * interpreting the job information returned by this route.
      */
-    post: operations["heuristic_install_model"];
-  };
-  "/api/v2/models/install": {
-    /**
-     * Import Model
-     * @description Install a model using its local path, repo_id, or remote URL.
-     *
-     * Models will be downloaded, probed, configured and installed in a
-     * series of background threads. The return object has `status` attribute
-     * that can be used to monitor progress.
-     *
-     * The source object is a discriminated Union of LocalModelSource,
-     * HFModelSource and URLModelSource. Set the "type" field to the
-     * appropriate value:
-     *
-     * * To install a local path using LocalModelSource, pass a source of form:
-     *   ```
-     *   {
-     *     "type": "local",
-     *     "path": "/path/to/model",
-     *     "inplace": false
-     *   }
-     *   ```
-     *   The "inplace" flag, if true, will register the model in place in its
-     *   current filesystem location. Otherwise, the model will be copied
-     *   into the InvokeAI models directory.
-     *
-     * * To install a HuggingFace repo_id using HFModelSource, pass a source of form:
-     *   ```
-     *   {
-     *     "type": "hf",
-     *     "repo_id": "stabilityai/stable-diffusion-2.0",
-     *     "variant": "fp16",
-     *     "subfolder": "vae",
-     *     "access_token": "f5820a918aaf01"
-     *   }
-     *   ```
-     *   The `variant`, `subfolder` and `access_token` fields are optional.
-     *
-     * * To install a remote model using an arbitrary URL, pass:
-     *   ```
-     *   {
-     *     "type": "url",
-     *     "url": "http://www.civitai.com/models/123456",
-     *     "access_token": "f5820a918aaf01"
-     *   }
-     *   ```
-     *   The `access_token` field is optonal
-     *
-     * The model's configuration record will be probed and filled in
-     * automatically.  To override the default guesses, pass "metadata"
-     * with a Dict containing the attributes you wish to override.
-     *
-     * Installation occurs in the background. Either use list_model_install_jobs()
-     * to poll for completion, or listen on the event bus for the following events:
-     *
-     *   * "model_install_running"
-     *   * "model_install_completed"
-     *   * "model_install_error"
-     *
-     * On successful completion, the event's payload will contain the field "key"
-     * containing the installed ID of the model. On an error, the event's payload
-     * will contain the fields "error_type" and "error" describing the nature of the
-     * error and its traceback, respectively.
-     */
-    post: operations["import_model"];
+    post: operations["install_model"];
   };
   "/api/v2/models/import": {
     /**
@@ -1182,16 +1117,6 @@ export type components = {
        */
       prepend?: boolean;
     };
-    /** Body_import_model */
-    Body_import_model: {
-      /** Source */
-      source: components["schemas"]["LocalModelSource"] | components["schemas"]["HFModelSource"] | components["schemas"]["CivitaiModelSource"] | components["schemas"]["URLModelSource"];
-      /**
-       * Config
-       * @description Dict of fields that override auto-probed values in the model config record, such as name, description and prediction_type
-       */
-      config?: Record<string, never> | null;
-    };
     /** Body_merge */
     Body_merge: {
       /**
@@ -4339,7 +4264,7 @@ export type components = {
        * @description The nodes in this graph
        */
       nodes: {
-        [key: string]: components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["DepthAnythingImageProcessorInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["CanvasPasteBackInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["CreateGradientMaskInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["ColorMapImageProcessorInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["DWOpenposeImageProcessorInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["StringCollectionInvocation"];
+        [key: string]: components["schemas"]["SchedulerInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["CreateGradientMaskInvocation"] | components["schemas"]["ColorMapImageProcessorInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["CanvasPasteBackInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["DWOpenposeImageProcessorInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["DepthAnythingImageProcessorInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"];
       };
       /**
        * Edges
@@ -4376,7 +4301,7 @@ export type components = {
        * @description The results of node executions
        */
       results: {
-        [key: string]: components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["String2Output"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["MetadataOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["LatentsOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["ClipSkipInvocationOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["LoraLoaderOutput"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["SDXLLoraLoaderOutput"] | components["schemas"]["VAEOutput"] | components["schemas"]["IPAdapterOutput"];
+        [key: string]: components["schemas"]["IntegerOutput"] | components["schemas"]["MetadataOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["ClipSkipInvocationOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["VAEOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["LoraLoaderOutput"] | components["schemas"]["String2Output"] | components["schemas"]["LatentsOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["SDXLLoraLoaderOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["FloatCollectionOutput"];
       };
       /**
        * Errors
@@ -7553,7 +7478,7 @@ export type components = {
        * Config Out
        * @description After successful installation, this will hold the configuration object.
        */
-      config_out?: (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["ONNXSD1Config"] | components["schemas"]["ONNXSD2Config"] | components["schemas"]["ONNXSDXLConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"] | null;
+      config_out?: (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"] | null;
       /**
        * Inplace
        * @description Leave model in its current location; otherwise install under models directory
@@ -7693,7 +7618,7 @@ export type components = {
      */
     ModelsList: {
       /** Models */
-      models: ((components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["ONNXSD1Config"] | components["schemas"]["ONNXSD2Config"] | components["schemas"]["ONNXSDXLConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"])[];
+      models: ((components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"])[];
     };
     /**
      * Multiply Integers
@@ -7878,246 +7803,6 @@ export type components = {
        */
       type: "normalbae_image_processor";
     };
-    /**
-     * ONNXSD1Config
-     * @description Model config for ONNX format models based on sd-1.
-     */
-    ONNXSD1Config: {
-      /**
-       * Path
-       * @description filesystem path to the model file or directory
-       */
-      path: string;
-      /**
-       * Name
-       * @description model name
-       */
-      name: string;
-      /**
-       * Base
-       * @default sd-1
-       * @constant
-       */
-      base: "sd-1";
-      /**
-       * Type
-       * @default onnx
-       * @constant
-       */
-      type: "onnx";
-      /**
-       * Format
-       * @enum {string}
-       */
-      format: "onnx" | "olive";
-      /**
-       * Key
-       * @description unique key for model
-       * @default <NOKEY>
-       */
-      key: string;
-      /**
-       * Original Hash
-       * @description original fasthash of model contents
-       */
-      original_hash: string | null;
-      /**
-       * Current Hash
-       * @description current fasthash of model contents
-       */
-      current_hash: string | null;
-      /**
-       * Description
-       * @description human readable description of the model
-       */
-      description?: string | null;
-      /**
-       * Source
-       * @description model original source (path, URL or repo_id)
-       */
-      source: string | null;
-      /**
-       * Last Modified
-       * @description timestamp for modification time
-       */
-      last_modified: number | null;
-      /** Vae */
-      vae?: string | null;
-      /** @default normal */
-      variant?: components["schemas"]["ModelVariantType"];
-      /** @default epsilon */
-      prediction_type?: components["schemas"]["SchedulerPredictionType"];
-      /**
-       * Upcast Attention
-       * @default false
-       */
-      upcast_attention?: boolean;
-      /**
-       * Ztsnr Training
-       * @default false
-       */
-      ztsnr_training?: boolean;
-    };
-    /**
-     * ONNXSD2Config
-     * @description Model config for ONNX format models based on sd-2.
-     */
-    ONNXSD2Config: {
-      /**
-       * Path
-       * @description filesystem path to the model file or directory
-       */
-      path: string;
-      /**
-       * Name
-       * @description model name
-       */
-      name: string;
-      /**
-       * Base
-       * @default sd-2
-       * @constant
-       */
-      base: "sd-2";
-      /**
-       * Type
-       * @default onnx
-       * @constant
-       */
-      type: "onnx";
-      /**
-       * Format
-       * @enum {string}
-       */
-      format: "onnx" | "olive";
-      /**
-       * Key
-       * @description unique key for model
-       * @default <NOKEY>
-       */
-      key: string;
-      /**
-       * Original Hash
-       * @description original fasthash of model contents
-       */
-      original_hash: string | null;
-      /**
-       * Current Hash
-       * @description current fasthash of model contents
-       */
-      current_hash: string | null;
-      /**
-       * Description
-       * @description human readable description of the model
-       */
-      description?: string | null;
-      /**
-       * Source
-       * @description model original source (path, URL or repo_id)
-       */
-      source: string | null;
-      /**
-       * Last Modified
-       * @description timestamp for modification time
-       */
-      last_modified: number | null;
-      /** Vae */
-      vae?: string | null;
-      /** @default normal */
-      variant?: components["schemas"]["ModelVariantType"];
-      /** @default v_prediction */
-      prediction_type?: components["schemas"]["SchedulerPredictionType"];
-      /**
-       * Upcast Attention
-       * @default true
-       */
-      upcast_attention?: boolean;
-      /**
-       * Ztsnr Training
-       * @default false
-       */
-      ztsnr_training?: boolean;
-    };
-    /**
-     * ONNXSDXLConfig
-     * @description Model config for ONNX format models based on sdxl.
-     */
-    ONNXSDXLConfig: {
-      /**
-       * Path
-       * @description filesystem path to the model file or directory
-       */
-      path: string;
-      /**
-       * Name
-       * @description model name
-       */
-      name: string;
-      /**
-       * Base
-       * @default sdxl
-       * @constant
-       */
-      base: "sdxl";
-      /**
-       * Type
-       * @default onnx
-       * @constant
-       */
-      type: "onnx";
-      /**
-       * Format
-       * @enum {string}
-       */
-      format: "onnx" | "olive";
-      /**
-       * Key
-       * @description unique key for model
-       * @default <NOKEY>
-       */
-      key: string;
-      /**
-       * Original Hash
-       * @description original fasthash of model contents
-       */
-      original_hash: string | null;
-      /**
-       * Current Hash
-       * @description current fasthash of model contents
-       */
-      current_hash: string | null;
-      /**
-       * Description
-       * @description human readable description of the model
-       */
-      description?: string | null;
-      /**
-       * Source
-       * @description model original source (path, URL or repo_id)
-       */
-      source: string | null;
-      /**
-       * Last Modified
-       * @description timestamp for modification time
-       */
-      last_modified: number | null;
-      /** Vae */
-      vae?: string | null;
-      /** @default normal */
-      variant?: components["schemas"]["ModelVariantType"];
-      /** @default v_prediction */
-      prediction_type?: components["schemas"]["SchedulerPredictionType"];
-      /**
-       * Upcast Attention
-       * @default false
-       */
-      upcast_attention?: boolean;
-      /**
-       * Ztsnr Training
-       * @default false
-       */
-      ztsnr_training?: boolean;
-    };
     /** OffsetPaginatedResults[BoardDTO] */
     OffsetPaginatedResults_BoardDTO_: {
       /**
@@ -11327,7 +11012,7 @@ export type operations = {
       /** @description Successful Response */
       200: {
         content: {
-          "application/json": (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["ONNXSD1Config"] | components["schemas"]["ONNXSD2Config"] | components["schemas"]["ONNXSDXLConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
+          "application/json": (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
         };
       };
       /** @description Validation Error */
@@ -11353,7 +11038,7 @@ export type operations = {
       /** @description The model configuration was retrieved successfully */
       200: {
         content: {
-          "application/json": (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["ONNXSD1Config"] | components["schemas"]["ONNXSD2Config"] | components["schemas"]["ONNXSDXLConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
+          "application/json": (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
         };
       };
       /** @description Bad request */
@@ -11428,14 +11113,14 @@ export type operations = {
          *   "variant": "normal"
          * }
          */
-        "application/json": (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["ONNXSD1Config"] | components["schemas"]["ONNXSD2Config"] | components["schemas"]["ONNXSDXLConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
+        "application/json": (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
       };
     };
     responses: {
       /** @description The model was updated successfully */
       200: {
         content: {
-          "application/json": (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["ONNXSD1Config"] | components["schemas"]["ONNXSD2Config"] | components["schemas"]["ONNXSDXLConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
+          "application/json": (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
         };
       };
       /** @description Bad request */
@@ -11604,14 +11289,14 @@ export type operations = {
          *   "variant": "normal"
          * }
          */
-        "application/json": (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["ONNXSD1Config"] | components["schemas"]["ONNXSD2Config"] | components["schemas"]["ONNXSDXLConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
+        "application/json": (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
       };
     };
     responses: {
       /** @description The model added successfully */
       201: {
         content: {
-          "application/json": (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["ONNXSD1Config"] | components["schemas"]["ONNXSD2Config"] | components["schemas"]["ONNXSDXLConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
+          "application/json": (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
         };
       };
       /** @description There is already a model corresponding to this path or repo_id */
@@ -11631,7 +11316,7 @@ export type operations = {
     };
   };
   /**
-   * Heuristic Install
+   * Install Model
    * @description Install a model using a string identifier.
    *
    * `source` can be any of the following.
@@ -11658,9 +11343,10 @@ export type operations = {
    * See the documentation for `import_model_record` for more information on
    * interpreting the job information returned by this route.
    */
-  heuristic_install_model: {
+  install_model: {
     parameters: {
       query: {
+        /** @description Model source to install, can be a local path, repo_id, or remote URL */
         source: string;
         access_token?: string | null;
       };
@@ -11703,101 +11389,6 @@ export type operations = {
       };
     };
   };
-  /**
-   * Import Model
-   * @description Install a model using its local path, repo_id, or remote URL.
-   *
-   * Models will be downloaded, probed, configured and installed in a
-   * series of background threads. The return object has `status` attribute
-   * that can be used to monitor progress.
-   *
-   * The source object is a discriminated Union of LocalModelSource,
-   * HFModelSource and URLModelSource. Set the "type" field to the
-   * appropriate value:
-   *
-   * * To install a local path using LocalModelSource, pass a source of form:
-   *   ```
-   *   {
-   *     "type": "local",
-   *     "path": "/path/to/model",
-   *     "inplace": false
-   *   }
-   *   ```
-   *   The "inplace" flag, if true, will register the model in place in its
-   *   current filesystem location. Otherwise, the model will be copied
-   *   into the InvokeAI models directory.
-   *
-   * * To install a HuggingFace repo_id using HFModelSource, pass a source of form:
-   *   ```
-   *   {
-   *     "type": "hf",
-   *     "repo_id": "stabilityai/stable-diffusion-2.0",
-   *     "variant": "fp16",
-   *     "subfolder": "vae",
-   *     "access_token": "f5820a918aaf01"
-   *   }
-   *   ```
-   *   The `variant`, `subfolder` and `access_token` fields are optional.
-   *
-   * * To install a remote model using an arbitrary URL, pass:
-   *   ```
-   *   {
-   *     "type": "url",
-   *     "url": "http://www.civitai.com/models/123456",
-   *     "access_token": "f5820a918aaf01"
-   *   }
-   *   ```
-   *   The `access_token` field is optonal
-   *
-   * The model's configuration record will be probed and filled in
-   * automatically.  To override the default guesses, pass "metadata"
-   * with a Dict containing the attributes you wish to override.
-   *
-   * Installation occurs in the background. Either use list_model_install_jobs()
-   * to poll for completion, or listen on the event bus for the following events:
-   *
-   *   * "model_install_running"
-   *   * "model_install_completed"
-   *   * "model_install_error"
-   *
-   * On successful completion, the event's payload will contain the field "key"
-   * containing the installed ID of the model. On an error, the event's payload
-   * will contain the fields "error_type" and "error" describing the nature of the
-   * error and its traceback, respectively.
-   */
-  import_model: {
-    requestBody: {
-      content: {
-        "application/json": components["schemas"]["Body_import_model"];
-      };
-    };
-    responses: {
-      /** @description The model imported successfully */
-      201: {
-        content: {
-          "application/json": components["schemas"]["ModelInstallJob"];
-        };
-      };
-      /** @description There is already a model corresponding to this path or repo_id */
-      409: {
-        content: never;
-      };
-      /** @description Unrecognized file/folder format */
-      415: {
-        content: never;
-      };
-      /** @description Validation Error */
-      422: {
-        content: {
-          "application/json": components["schemas"]["HTTPValidationError"];
-        };
-      };
-      /** @description The model appeared to import successfully, but could not be found in the model manager */
-      424: {
-        content: never;
-      };
-    };
-  };
   /**
    * List Model Install Jobs
    * @description Return the list of model install jobs.
@@ -11954,7 +11545,7 @@ export type operations = {
       /** @description Model converted successfully */
       200: {
         content: {
-          "application/json": (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["ONNXSD1Config"] | components["schemas"]["ONNXSD2Config"] | components["schemas"]["ONNXSDXLConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
+          "application/json": (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
         };
       };
       /** @description Bad request */
@@ -12001,7 +11592,7 @@ export type operations = {
       /** @description Model converted successfully */
       200: {
         content: {
-          "application/json": (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["ONNXSD1Config"] | components["schemas"]["ONNXSD2Config"] | components["schemas"]["ONNXSDXLConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
+          "application/json": (components["schemas"]["MainDiffusersConfig"] | components["schemas"]["MainCheckpointConfig"]) | (components["schemas"]["VaeDiffusersConfig"] | components["schemas"]["VaeCheckpointConfig"]) | (components["schemas"]["ControlNetDiffusersConfig"] | components["schemas"]["ControlNetCheckpointConfig"]) | components["schemas"]["LoRAConfig"] | components["schemas"]["TextualInversionConfig"] | components["schemas"]["IPAdapterConfig"] | components["schemas"]["CLIPVisionDiffusersConfig"] | components["schemas"]["T2IConfig"];
         };
       };
       /** @description Bad request */

From 97ecd99b9cbe764d6c3fd57e549bda52f7c1c149 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 27 Feb 2024 15:09:42 +1100
Subject: [PATCH 338/411] fix(ui): fix up MM queries & types (wip)

---
 .../AddModelPanel/AdvancedImport.tsx          | 19 ++++-----
 .../ScanModels/ScanModelResultItem.tsx        |  8 ++--
 .../subpanels/AddModelPanel/SimpleImport.tsx  |  8 ++--
 .../web/src/services/api/endpoints/models.ts  | 41 ++++++-------------
 .../frontend/web/src/services/api/types.ts    | 14 ++++++-
 5 files changed, 40 insertions(+), 50 deletions(-)

diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImport.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImport.tsx
index 8f474537cc..e115c68dca 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImport.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImport.tsx
@@ -10,17 +10,18 @@ import PredictionTypeSelect from 'features/modelManagerV2/subpanels/ModelPanel/F
 import RepoVariantSelect from 'features/modelManagerV2/subpanels/ModelPanel/Fields/RepoVariantSelect';
 import { addToast } from 'features/system/store/systemSlice';
 import { makeToast } from 'features/system/util/makeToast';
+import { isNil, omitBy } from 'lodash-es';
 import { useCallback, useEffect } from 'react';
 import type { SubmitHandler } from 'react-hook-form';
 import { useForm } from 'react-hook-form';
 import { useTranslation } from 'react-i18next';
-import { useImportAdvancedModelMutation } from 'services/api/endpoints/models';
+import { useInstallModelMutation } from 'services/api/endpoints/models';
 import type { AnyModelConfig } from 'services/api/types';
 
 export const AdvancedImport = () => {
   const dispatch = useAppDispatch();
 
-  const [importAdvancedModel] = useImportAdvancedModelMutation();
+  const [installModel] = useInstallModelMutation();
 
   const { t } = useTranslation();
 
@@ -49,15 +50,9 @@ export const AdvancedImport = () => {
 
   const onSubmit = useCallback<SubmitHandler<AnyModelConfig>>(
     (values) => {
-      const cleanValues = Object.fromEntries(
-        Object.entries(values).filter(([value]) => value !== null && value !== undefined)
-      );
-      importAdvancedModel({
-        source: {
-          path: cleanValues.path as string,
-          type: 'local',
-        },
-        config: cleanValues,
+      installModel({
+        source: values.path,
+        config: omitBy(values, isNil),
       })
         .unwrap()
         .then((_) => {
@@ -86,7 +81,7 @@ export const AdvancedImport = () => {
           }
         });
     },
-    [dispatch, reset, t, importAdvancedModel]
+    [installModel, dispatch, t, reset]
   );
 
   const watchedModelType = watch('type');
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelResultItem.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelResultItem.tsx
index 6ae7573665..af3cb33a0c 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelResultItem.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelResultItem.tsx
@@ -6,7 +6,7 @@ import { useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 import { IoAdd } from 'react-icons/io5';
 import type { ScanFolderResponse } from 'services/api/endpoints/models';
-import { useImportMainModelsMutation } from 'services/api/endpoints/models';
+import { useInstallModelMutation } from 'services/api/endpoints/models';
 
 type Props = {
   result: ScanFolderResponse[number];
@@ -15,10 +15,10 @@ export const ScanModelResultItem = ({ result }: Props) => {
   const { t } = useTranslation();
   const dispatch = useAppDispatch();
 
-  const [importMainModel] = useImportMainModelsMutation();
+  const [installModel] = useInstallModelMutation();
 
   const handleQuickAdd = useCallback(() => {
-    importMainModel({ source: result.path, config: undefined })
+    installModel({ source: result.path })
       .unwrap()
       .then((_) => {
         dispatch(
@@ -42,7 +42,7 @@ export const ScanModelResultItem = ({ result }: Props) => {
           );
         }
       });
-  }, [importMainModel, result, dispatch, t]);
+  }, [installModel, result, dispatch, t]);
 
   return (
     <Flex justifyContent="space-between">
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/SimpleImport.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/SimpleImport.tsx
index c056048c5b..6f704abf4f 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/SimpleImport.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/SimpleImport.tsx
@@ -6,7 +6,7 @@ import { t } from 'i18next';
 import { useCallback } from 'react';
 import type { SubmitHandler } from 'react-hook-form';
 import { useForm } from 'react-hook-form';
-import { useImportMainModelsMutation } from 'services/api/endpoints/models';
+import { useInstallModelMutation } from 'services/api/endpoints/models';
 
 type SimpleImportModelConfig = {
   location: string;
@@ -15,7 +15,7 @@ type SimpleImportModelConfig = {
 export const SimpleImport = () => {
   const dispatch = useAppDispatch();
 
-  const [importMainModel, { isLoading }] = useImportMainModelsMutation();
+  const [installModel, { isLoading }] = useInstallModelMutation();
 
   const { register, handleSubmit, formState, reset } = useForm<SimpleImportModelConfig>({
     defaultValues: {
@@ -30,7 +30,7 @@ export const SimpleImport = () => {
         return;
       }
 
-      importMainModel({ source: values.location, config: undefined })
+      installModel({ source: values.location })
         .unwrap()
         .then((_) => {
           dispatch(
@@ -57,7 +57,7 @@ export const SimpleImport = () => {
           }
         });
     },
-    [dispatch, reset, importMainModel]
+    [dispatch, reset, installModel]
   );
 
   return (
diff --git a/invokeai/frontend/web/src/services/api/endpoints/models.ts b/invokeai/frontend/web/src/services/api/endpoints/models.ts
index 2d1d021bc6..827356cd22 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/models.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/models.ts
@@ -1,6 +1,7 @@
 import type { EntityAdapter, EntityState, ThunkDispatch, UnknownAction } from '@reduxjs/toolkit';
 import { createEntityAdapter } from '@reduxjs/toolkit';
 import { getSelectorsOptions } from 'app/store/createMemoizedSelector';
+import type { JSONObject } from 'common/types';
 import queryString from 'query-string';
 import type { operations, paths } from 'services/api/schema';
 import type {
@@ -19,8 +20,8 @@ import type { ApiTagDescription, tagTypes } from '..';
 import { api, buildV2Url, LIST_TAG } from '..';
 
 type UpdateModelArg = {
-  key: NonNullable<operations['update_model_record']['parameters']['path']['key']>;
-  body: NonNullable<operations['update_model_record']['requestBody']['content']['application/json']>;
+  key: paths['/api/v2/models/i/{key}']['patch']['parameters']['path']['key'];
+  body: paths['/api/v2/models/i/{key}']['patch']['requestBody']['content']['application/json'];
 };
 
 type UpdateModelResponse = paths['/api/v2/models/i/{key}']['patch']['responses']['200']['content']['application/json'];
@@ -40,14 +41,15 @@ type DeleteMainModelResponse = void;
 type ConvertMainModelResponse =
   paths['/api/v2/models/convert/{key}']['put']['responses']['200']['content']['application/json'];
 
-type ImportMainModelArg = {
-  source: NonNullable<operations['heuristic_install_model']['parameters']['query']['source']>;
-  access_token?: operations['heuristic_install_model']['parameters']['query']['access_token'];
-  config: NonNullable<operations['heuristic_install_model']['requestBody']['content']['application/json']>;
+type InstallModelArg = {
+  source: paths['/api/v2/models/install']['post']['parameters']['query']['source'];
+  access_token?: paths['/api/v2/models/install']['post']['parameters']['query']['access_token'];
+  // TODO(MM2): This is typed as `Optional[Dict[str, Any]]` in backend...
+  config?: JSONObject;
+  // config: NonNullable<paths['/api/v2/models/heuristic_install']['post']['requestBody']>['content']['application/json'];
 };
 
-type ImportMainModelResponse =
-  paths['/api/v2/models/heuristic_install']['post']['responses']['201']['content']['application/json'];
+type InstallModelResponse = paths['/api/v2/models/install']['post']['responses']['201']['content']['application/json'];
 
 type ListImportModelsResponse =
   paths['/api/v2/models/import']['get']['responses']['200']['content']['application/json'];
@@ -58,14 +60,6 @@ type DeleteImportModelsResponse =
 type PruneModelImportsResponse =
   paths['/api/v2/models/import']['patch']['responses']['200']['content']['application/json'];
 
-type ImportAdvancedModelArg = {
-  source: NonNullable<operations['import_model']['requestBody']['content']['application/json']['source']>;
-  config: NonNullable<operations['import_model']['requestBody']['content']['application/json']['config']>;
-};
-
-type ImportAdvancedModelResponse =
-  paths['/api/v2/models/import']['post']['responses']['201']['content']['application/json'];
-
 export type ScanFolderResponse =
   paths['/api/v2/models/scan_folder']['get']['responses']['200']['content']['application/json'];
 type ScanFolderArg = operations['scan_for_models']['parameters']['query'];
@@ -183,7 +177,7 @@ export const modelsApi = api.injectEndpoints({
       },
       invalidatesTags: ['Model'],
     }),
-    importMainModels: build.mutation<ImportMainModelResponse, ImportMainModelArg>({
+    installModel: build.mutation<InstallModelResponse, InstallModelArg>({
       query: ({ source, config, access_token }) => {
         return {
           url: buildModelsUrl('heuristic_install'),
@@ -194,16 +188,6 @@ export const modelsApi = api.injectEndpoints({
       },
       invalidatesTags: ['Model', 'ModelImports'],
     }),
-    importAdvancedModel: build.mutation<ImportAdvancedModelResponse, ImportAdvancedModelArg>({
-      query: ({ source, config }) => {
-        return {
-          url: buildModelsUrl('install'),
-          method: 'POST',
-          body: { source, config },
-        };
-      },
-      invalidatesTags: ['Model', 'ModelImports'],
-    }),
     deleteModels: build.mutation<DeleteMainModelResponse, DeleteMainModelArg>({
       query: ({ key }) => {
         return {
@@ -365,8 +349,7 @@ export const {
   useGetVaeModelsQuery,
   useDeleteModelsMutation,
   useUpdateModelsMutation,
-  useImportMainModelsMutation,
-  useImportAdvancedModelMutation,
+  useInstallModelMutation,
   useConvertMainModelsMutation,
   useSyncModelsMutation,
   useScanModelsQuery,
diff --git a/invokeai/frontend/web/src/services/api/types.ts b/invokeai/frontend/web/src/services/api/types.ts
index cb848e168e..2ecf0a7a09 100644
--- a/invokeai/frontend/web/src/services/api/types.ts
+++ b/invokeai/frontend/web/src/services/api/types.ts
@@ -70,6 +70,7 @@ export type T2IAdapterModelConfig = S['T2IConfig'];
 export type TextualInversionModelConfig = S['TextualInversionConfig'];
 export type DiffusersModelConfig = S['MainDiffusersConfig'];
 export type CheckpointModelConfig = S['MainCheckpointConfig'];
+type CLIPVisionDiffusersConfig = S['CLIPVisionDiffusersConfig'];
 export type MainModelConfig = DiffusersModelConfig | CheckpointModelConfig;
 export type RefinerMainModelConfig = Omit<MainModelConfig, 'base'> & { base: 'sdxl-refiner' };
 export type NonRefinerMainModelConfig = Omit<MainModelConfig, 'base'> & { base: 'any' | 'sd-1' | 'sd-2' | 'sdxl' };
@@ -81,7 +82,18 @@ export type AnyModelConfig =
   | T2IAdapterModelConfig
   | TextualInversionModelConfig
   | RefinerMainModelConfig
-  | NonRefinerMainModelConfig;
+  | NonRefinerMainModelConfig
+  | CLIPVisionDiffusersConfig;
+
+type AnyModelConfig2 =
+  | (S['MainDiffusersConfig'] | S['MainCheckpointConfig'])
+  | (S['VaeDiffusersConfig'] | S['VaeCheckpointConfig'])
+  | (S['ControlNetDiffusersConfig'] | S['ControlNetCheckpointConfig'])
+  | S['LoRAConfig']
+  | S['TextualInversionConfig']
+  | S['IPAdapterConfig']
+  | S['CLIPVisionDiffusersConfig']
+  | S['T2IConfig'];
 
 export const isLoRAModelConfig = (config: AnyModelConfig): config is LoRAModelConfig => {
   return config.type === 'lora';

From aaeef0359394446d5e6d45967c270d716fee323e Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 27 Feb 2024 15:31:40 +1100
Subject: [PATCH 339/411] fix(ui): fix remaining TS issues

---
 .../AddModelPanel/AdvancedImport.tsx          |  4 +-
 .../ModelPanel/Fields/BaseModelSelect.tsx     |  2 +-
 .../ModelPanel/Fields/ModelFormatSelect.tsx   | 11 +--
 .../ModelPanel/Fields/ModelTypeSelect.tsx     |  2 +-
 .../subpanels/ModelPanel/ModelEdit.tsx        | 95 +++++++++----------
 .../features/parameters/types/constants.ts    | 11 ---
 .../web/src/services/api/endpoints/models.ts  |  2 +-
 .../frontend/web/src/services/api/types.ts    | 22 +----
 8 files changed, 56 insertions(+), 93 deletions(-)

diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImport.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImport.tsx
index e115c68dca..56abf7b09a 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImport.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/AdvancedImport.tsx
@@ -148,11 +148,11 @@ export const AdvancedImport = () => {
             <Flex gap={4}>
               <FormControl flexDir="column" alignItems="flex-start" gap={1}>
                 <FormLabel>{t('modelManager.baseModel')}</FormLabel>
-                <BaseModelSelect<AnyModelConfig> control={control} name="base" />
+                <BaseModelSelect control={control} name="base" />
               </FormControl>
               <FormControl flexDir="column" alignItems="flex-start" gap={1}>
                 <FormLabel>{t('common.format')}</FormLabel>
-                <ModelFormatSelect<AnyModelConfig> control={control} name="format" />
+                <ModelFormatSelect control={control} name="format" />
               </FormControl>
             </Flex>
             <Flex gap={4}>
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/BaseModelSelect.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/BaseModelSelect.tsx
index bcb84c9b47..f11b436044 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/BaseModelSelect.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/BaseModelSelect.tsx
@@ -14,7 +14,7 @@ const options: ComboboxOption[] = [
   { value: 'sdxl-refiner', label: MODEL_TYPE_MAP['sdxl-refiner'] },
 ];
 
-const BaseModelSelect = <T extends AnyModelConfig>(props: UseControllerProps<T>) => {
+const BaseModelSelect = (props: UseControllerProps<AnyModelConfig>) => {
   const { field } = useController(props);
   const value = useMemo(() => options.find((o) => o.value === field.value), [field.value]);
   const onChange = useCallback<ComboboxOnChange>(
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelFormatSelect.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelFormatSelect.tsx
index 7c8bed9c02..298dc012f0 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelFormatSelect.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelFormatSelect.tsx
@@ -1,13 +1,12 @@
 import type { ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
 import { Combobox } from '@invoke-ai/ui-library';
 import { typedMemo } from 'common/util/typedMemo';
-import { LORA_MODEL_FORMAT_MAP } from 'features/parameters/types/constants';
 import { useCallback, useMemo } from 'react';
 import type { UseControllerProps } from 'react-hook-form';
 import { useController, useWatch } from 'react-hook-form';
 import type { AnyModelConfig } from 'services/api/types';
 
-const ModelFormatSelect = <T extends AnyModelConfig>(props: UseControllerProps<T>) => {
+const ModelFormatSelect = (props: UseControllerProps<AnyModelConfig>) => {
   const { field, formState } = useController(props);
   const type = useWatch({ control: props.control, name: 'type' });
 
@@ -21,10 +20,10 @@ const ModelFormatSelect = <T extends AnyModelConfig>(props: UseControllerProps<T
   const options: ComboboxOption[] = useMemo(() => {
     const modelType = type || formState.defaultValues?.type;
     if (modelType === 'lora') {
-      return Object.keys(LORA_MODEL_FORMAT_MAP).map((format) => ({
-        value: format,
-        label: LORA_MODEL_FORMAT_MAP[format],
-      })) as ComboboxOption[];
+      return [
+        { value: 'lycoris', label: 'LyCORIS' },
+        { value: 'diffusers', label: 'Diffusers' },
+      ];
     } else if (modelType === 'embedding') {
       return [
         { value: 'embedding_file', label: 'Embedding File' },
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelTypeSelect.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelTypeSelect.tsx
index e0b244baa9..dc42ae89a8 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelTypeSelect.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelTypeSelect.tsx
@@ -15,7 +15,7 @@ const options: ComboboxOption[] = [
   { value: 'controlnet', label: MODEL_TYPE_LABELS['controlnet'] as string },
   { value: 'ip_adapter', label: MODEL_TYPE_LABELS['ip_adapter'] as string },
   { value: 't2i_adapater', label: MODEL_TYPE_LABELS['t2i_adapter'] as string },
-];
+] as const
 
 const ModelTypeSelect = <T extends AnyModelConfig>(props: UseControllerProps<T>) => {
   const { field } = useController(props);
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx
index 2391bf33ad..5025271b8a 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx
@@ -14,22 +14,13 @@ import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { setSelectedModelMode } from 'features/modelManagerV2/store/modelManagerV2Slice';
 import { addToast } from 'features/system/store/systemSlice';
 import { makeToast } from 'features/system/util/makeToast';
-import { useCallback, useMemo } from 'react';
+import { useCallback } from 'react';
 import type { SubmitHandler } from 'react-hook-form';
 import { useForm } from 'react-hook-form';
 import { useTranslation } from 'react-i18next';
+import type { UpdateModelArg } from 'services/api/endpoints/models';
 import { useGetModelConfigQuery, useUpdateModelsMutation } from 'services/api/endpoints/models';
-import type {
-  AnyModelConfig,
-  CheckpointModelConfig,
-  ControlNetModelConfig,
-  DiffusersModelConfig,
-  IPAdapterModelConfig,
-  LoRAModelConfig,
-  T2IAdapterModelConfig,
-  TextualInversionModelConfig,
-  VAEModelConfig,
-} from 'services/api/types';
+import type { AnyModelConfig } from 'services/api/types';
 
 import BaseModelSelect from './Fields/BaseModelSelect';
 import BooleanSelect from './Fields/BooleanSelect';
@@ -48,38 +39,38 @@ export const ModelEdit = () => {
 
   const { t } = useTranslation();
 
-  const modelData = useMemo(() => {
-    if (!data) {
-      return null;
-    }
-    const modelFormat = data.format;
-    const modelType = data.type;
+  // const modelData = useMemo(() => {
+  //   if (!data) {
+  //     return null;
+  //   }
+  //   const modelFormat = data.format;
+  //   const modelType = data.type;
 
-    if (modelType === 'main') {
-      if (modelFormat === 'diffusers') {
-        return data as DiffusersModelConfig;
-      } else if (modelFormat === 'checkpoint') {
-        return data as CheckpointModelConfig;
-      }
-    }
+  //   if (modelType === 'main') {
+  //     if (modelFormat === 'diffusers') {
+  //       return data as DiffusersModelConfig;
+  //     } else if (modelFormat === 'checkpoint') {
+  //       return data as CheckpointModelConfig;
+  //     }
+  //   }
 
-    switch (modelType) {
-      case 'lora':
-        return data as LoRAModelConfig;
-      case 'embedding':
-        return data as TextualInversionModelConfig;
-      case 't2i_adapter':
-        return data as T2IAdapterModelConfig;
-      case 'ip_adapter':
-        return data as IPAdapterModelConfig;
-      case 'controlnet':
-        return data as ControlNetModelConfig;
-      case 'vae':
-        return data as VAEModelConfig;
-      default:
-        return null;
-    }
-  }, [data]);
+  //   switch (modelType) {
+  //     case 'lora':
+  //       return data as LoRAModelConfig;
+  //     case 'embedding':
+  //       return data as TextualInversionModelConfig;
+  //     case 't2i_adapter':
+  //       return data as T2IAdapterModelConfig;
+  //     case 'ip_adapter':
+  //       return data as IPAdapterModelConfig;
+  //     case 'controlnet':
+  //       return data as ControlNetModelConfig;
+  //     case 'vae':
+  //       return data as VAEModelConfig;
+  //     default:
+  //       return null;
+  //   }
+  // }, [data]);
 
   const {
     register,
@@ -88,9 +79,9 @@ export const ModelEdit = () => {
     formState: { errors },
     reset,
     watch,
-  } = useForm<AnyModelConfig>({
+  } = useForm<UpdateModelArg['body']>({
     defaultValues: {
-      ...modelData,
+      ...data,
     },
     mode: 'onChange',
   });
@@ -100,19 +91,19 @@ export const ModelEdit = () => {
 
   const onSubmit = useCallback<SubmitHandler<AnyModelConfig>>(
     (values) => {
-      if (!modelData?.key) {
+      if (!data?.key) {
         return;
       }
 
-      const responseBody = {
-        key: modelData.key,
+      const responseBody: UpdateModelArg = {
+        key: data.key,
         body: values,
       };
 
       updateModel(responseBody)
         .unwrap()
         .then((payload) => {
-          reset(payload as AnyModelConfig, { keepDefaultValues: true });
+          reset(payload, { keepDefaultValues: true });
           dispatch(setSelectedModelMode('view'));
           dispatch(
             addToast(
@@ -135,7 +126,7 @@ export const ModelEdit = () => {
           );
         });
     },
-    [dispatch, modelData?.key, reset, t, updateModel]
+    [dispatch, data?.key, reset, t, updateModel]
   );
 
   const handleClickCancel = useCallback(() => {
@@ -146,7 +137,7 @@ export const ModelEdit = () => {
     return <Text>{t('common.loading')}</Text>;
   }
 
-  if (!modelData) {
+  if (!data) {
     return <Text>{t('common.somethingWentWrong')}</Text>;
   }
   return (
@@ -193,7 +184,7 @@ export const ModelEdit = () => {
           <Flex gap={4}>
             <FormControl flexDir="column" alignItems="flex-start" gap={1}>
               <FormLabel>{t('modelManager.baseModel')}</FormLabel>
-              <BaseModelSelect<AnyModelConfig> control={control} name="base" />
+              <BaseModelSelect control={control} name="base" />
             </FormControl>
             <FormControl flexDir="column" alignItems="flex-start" gap={1}>
               <FormLabel>{t('modelManager.modelType')}</FormLabel>
@@ -203,7 +194,7 @@ export const ModelEdit = () => {
           <Flex gap={4}>
             <FormControl flexDir="column" alignItems="flex-start" gap={1}>
               <FormLabel>{t('common.format')}</FormLabel>
-              <ModelFormatSelect<AnyModelConfig> control={control} name="format" />
+              <ModelFormatSelect control={control} name="format" />
             </FormControl>
             <FormControl flexDir="column" alignItems="flex-start" gap={1} isInvalid={Boolean(errors.path)}>
               <FormLabel>{t('modelManager.path')}</FormLabel>
diff --git a/invokeai/frontend/web/src/features/parameters/types/constants.ts b/invokeai/frontend/web/src/features/parameters/types/constants.ts
index baa255a102..5bdfe9937b 100644
--- a/invokeai/frontend/web/src/features/parameters/types/constants.ts
+++ b/invokeai/frontend/web/src/features/parameters/types/constants.ts
@@ -1,5 +1,4 @@
 import type { ComboboxOption } from '@invoke-ai/ui-library';
-import type { LoRAModelFormat } from 'services/api/types';
 
 /**
  * Mapping of base model to human readable name
@@ -49,16 +48,6 @@ export const CLIP_SKIP_MAP = {
   },
 };
 
-/**
- * Mapping of LoRA format to human readable name
- */
-export const LORA_MODEL_FORMAT_MAP: {
-  [key in LoRAModelFormat]: string;
-} = {
-  lycoris: 'LyCORIS',
-  diffusers: 'Diffusers',
-};
-
 /**
  * Mapping of schedulers to human readable name
  */
diff --git a/invokeai/frontend/web/src/services/api/endpoints/models.ts b/invokeai/frontend/web/src/services/api/endpoints/models.ts
index 827356cd22..c125dcd371 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/models.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/models.ts
@@ -19,7 +19,7 @@ import type {
 import type { ApiTagDescription, tagTypes } from '..';
 import { api, buildV2Url, LIST_TAG } from '..';
 
-type UpdateModelArg = {
+export type UpdateModelArg = {
   key: paths['/api/v2/models/i/{key}']['patch']['parameters']['path']['key'];
   body: paths['/api/v2/models/i/{key}']['patch']['requestBody']['content']['application/json'];
 };
diff --git a/invokeai/frontend/web/src/services/api/types.ts b/invokeai/frontend/web/src/services/api/types.ts
index 2ecf0a7a09..314eb07bfa 100644
--- a/invokeai/frontend/web/src/services/api/types.ts
+++ b/invokeai/frontend/web/src/services/api/types.ts
@@ -50,7 +50,6 @@ export type BaseModelType = S['BaseModelType'];
 export type MainModelField = S['MainModelField'];
 export type VAEModelField = S['VAEModelField'];
 export type LoRAModelField = S['LoRAModelField'];
-export type LoRAModelFormat = S['LoRAModelFormat'];
 export type ControlNetModelField = S['ControlNetModelField'];
 export type IPAdapterModelField = S['IPAdapterModelField'];
 export type T2IAdapterModelField = S['T2IAdapterModelField'];
@@ -72,8 +71,6 @@ export type DiffusersModelConfig = S['MainDiffusersConfig'];
 export type CheckpointModelConfig = S['MainCheckpointConfig'];
 type CLIPVisionDiffusersConfig = S['CLIPVisionDiffusersConfig'];
 export type MainModelConfig = DiffusersModelConfig | CheckpointModelConfig;
-export type RefinerMainModelConfig = Omit<MainModelConfig, 'base'> & { base: 'sdxl-refiner' };
-export type NonRefinerMainModelConfig = Omit<MainModelConfig, 'base'> & { base: 'any' | 'sd-1' | 'sd-2' | 'sdxl' };
 export type AnyModelConfig =
   | LoRAModelConfig
   | VAEModelConfig
@@ -81,20 +78,9 @@ export type AnyModelConfig =
   | IPAdapterModelConfig
   | T2IAdapterModelConfig
   | TextualInversionModelConfig
-  | RefinerMainModelConfig
-  | NonRefinerMainModelConfig
+  | MainModelConfig
   | CLIPVisionDiffusersConfig;
 
-type AnyModelConfig2 =
-  | (S['MainDiffusersConfig'] | S['MainCheckpointConfig'])
-  | (S['VaeDiffusersConfig'] | S['VaeCheckpointConfig'])
-  | (S['ControlNetDiffusersConfig'] | S['ControlNetCheckpointConfig'])
-  | S['LoRAConfig']
-  | S['TextualInversionConfig']
-  | S['IPAdapterConfig']
-  | S['CLIPVisionDiffusersConfig']
-  | S['T2IConfig'];
-
 export const isLoRAModelConfig = (config: AnyModelConfig): config is LoRAModelConfig => {
   return config.type === 'lora';
 };
@@ -119,16 +105,14 @@ export const isTextualInversionModelConfig = (config: AnyModelConfig): config is
   return config.type === 'embedding';
 };
 
-export const isNonRefinerMainModelConfig = (config: AnyModelConfig): config is NonRefinerMainModelConfig => {
+export const isNonRefinerMainModelConfig = (config: AnyModelConfig): config is MainModelConfig => {
   return config.type === 'main' && config.base !== 'sdxl-refiner';
 };
 
-export const isRefinerMainModelModelConfig = (config: AnyModelConfig): config is RefinerMainModelConfig => {
+export const isRefinerMainModelModelConfig = (config: AnyModelConfig): config is MainModelConfig => {
   return config.type === 'main' && config.base === 'sdxl-refiner';
 };
 
-export type MergeModelConfig = S['Body_merge'];
-export type ImportModelConfig = S['Body_import_model'];
 export type ModelInstallJob = S['ModelInstallJob'];
 export type ModelInstallStatus = S['InstallStatus'];
 

From 80065858ed3212ab75938485f736a7cdef8ecdf1 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 27 Feb 2024 15:36:00 +1100
Subject: [PATCH 340/411] chore(ui): lint

---
 invokeai/frontend/web/public/locales/en.json   |  1 +
 .../src/common/hooks/useModelCustomSelect.ts   |  2 +-
 .../src/features/canvas/store/canvasTypes.ts   |  2 --
 .../features/gallery/hooks/useImageActions.ts  |  2 +-
 .../components/MetadataT2IAdapters.tsx         |  2 +-
 .../metadata/components/RecallButton.tsx       |  2 +-
 .../web/src/features/metadata/exceptions.ts    |  1 -
 .../metadata/hooks/useMetadataItem.tsx         | 18 +++++++++++++-----
 .../ModelPanel/Fields/ModelTypeSelect.tsx      |  2 +-
 .../hooks/useAnyOrDirectInputFieldNames.ts     |  2 +-
 .../hooks/useConnectionInputFieldNames.ts      |  2 +-
 .../nodes/hooks/useOutputFieldNames.ts         |  2 +-
 .../parameters/hooks/usePreselectedImage.ts    |  1 -
 .../GenerationSettingsAccordion.tsx            |  2 +-
 .../web/src/services/api/endpoints/models.ts   |  4 ++--
 15 files changed, 25 insertions(+), 20 deletions(-)

diff --git a/invokeai/frontend/web/public/locales/en.json b/invokeai/frontend/web/public/locales/en.json
index 05a7a456f3..4065b0db86 100644
--- a/invokeai/frontend/web/public/locales/en.json
+++ b/invokeai/frontend/web/public/locales/en.json
@@ -674,6 +674,7 @@
         "noMetaData": "No metadata found",
         "noRecallParameters": "No parameters to recall found",
         "parameterSet": "Parameter {{parameter}} set",
+        "parsingFailed": "Parsing Failed",
         "perlin": "Perlin Noise",
         "positivePrompt": "Positive Prompt",
         "recallParameters": "Recall Parameters",
diff --git a/invokeai/frontend/web/src/common/hooks/useModelCustomSelect.ts b/invokeai/frontend/web/src/common/hooks/useModelCustomSelect.ts
index 6e5c8ca870..5626f4c395 100644
--- a/invokeai/frontend/web/src/common/hooks/useModelCustomSelect.ts
+++ b/invokeai/frontend/web/src/common/hooks/useModelCustomSelect.ts
@@ -1,6 +1,6 @@
 import type { Item } from '@invoke-ai/ui-library';
 import type { EntityState } from '@reduxjs/toolkit';
-import { EMPTY_ARRAY } from "app/store/constants";
+import { EMPTY_ARRAY } from 'app/store/constants';
 import type { ModelIdentifierWithBase } from 'features/nodes/types/common';
 import { MODEL_TYPE_SHORT_MAP } from 'features/parameters/types/constants';
 import { filter } from 'lodash-es';
diff --git a/invokeai/frontend/web/src/features/canvas/store/canvasTypes.ts b/invokeai/frontend/web/src/features/canvas/store/canvasTypes.ts
index e0e7d5b1cd..14248cd750 100644
--- a/invokeai/frontend/web/src/features/canvas/store/canvasTypes.ts
+++ b/invokeai/frontend/web/src/features/canvas/store/canvasTypes.ts
@@ -10,8 +10,6 @@ export const LAYER_NAMES_DICT: { label: string; value: CanvasLayer }[] = [
   { label: 'Mask', value: 'mask' },
 ];
 
-const LAYER_NAMES = ['base', 'mask'] as const;
-
 const zBoundingBoxScaleMethod = z.enum(['none', 'auto', 'manual']);
 export type BoundingBoxScaleMethod = z.infer<typeof zBoundingBoxScaleMethod>;
 export const isBoundingBoxScaleMethod = (v: unknown): v is BoundingBoxScaleMethod =>
diff --git a/invokeai/frontend/web/src/features/gallery/hooks/useImageActions.ts b/invokeai/frontend/web/src/features/gallery/hooks/useImageActions.ts
index a61b2096da..c3ae0cea5f 100644
--- a/invokeai/frontend/web/src/features/gallery/hooks/useImageActions.ts
+++ b/invokeai/frontend/web/src/features/gallery/hooks/useImageActions.ts
@@ -58,5 +58,5 @@ export const useImageActions = (image_name?: string) => {
     parseAndRecallPrompts(metadata);
   }, [metadata]);
 
-  return { recallAll, remix, recallSeed, recallPrompts , hasMetadata, hasSeed,  hasPrompts, isLoadingMetadata };
+  return { recallAll, remix, recallSeed, recallPrompts, hasMetadata, hasSeed, hasPrompts, isLoadingMetadata };
 };
diff --git a/invokeai/frontend/web/src/features/metadata/components/MetadataT2IAdapters.tsx b/invokeai/frontend/web/src/features/metadata/components/MetadataT2IAdapters.tsx
index 6b1de889ff..82575783e9 100644
--- a/invokeai/frontend/web/src/features/metadata/components/MetadataT2IAdapters.tsx
+++ b/invokeai/frontend/web/src/features/metadata/components/MetadataT2IAdapters.tsx
@@ -53,7 +53,7 @@ const MetadataViewT2IAdapter = ({
     }
     handlers.recallItem(t2iAdapter, true);
   }, [handlers, t2iAdapter]);
-  
+
   const [renderedValue, setRenderedValue] = useState<React.ReactNode>(null);
   useEffect(() => {
     const _renderValue = async () => {
diff --git a/invokeai/frontend/web/src/features/metadata/components/RecallButton.tsx b/invokeai/frontend/web/src/features/metadata/components/RecallButton.tsx
index 8803945b06..c531481a89 100644
--- a/invokeai/frontend/web/src/features/metadata/components/RecallButton.tsx
+++ b/invokeai/frontend/web/src/features/metadata/components/RecallButton.tsx
@@ -1,4 +1,4 @@
-import type { IconButtonProps} from '@invoke-ai/ui-library';
+import type { IconButtonProps } from '@invoke-ai/ui-library';
 import { IconButton, Tooltip } from '@invoke-ai/ui-library';
 import { memo } from 'react';
 import { useTranslation } from 'react-i18next';
diff --git a/invokeai/frontend/web/src/features/metadata/exceptions.ts b/invokeai/frontend/web/src/features/metadata/exceptions.ts
index 8b13789179..e69de29bb2 100644
--- a/invokeai/frontend/web/src/features/metadata/exceptions.ts
+++ b/invokeai/frontend/web/src/features/metadata/exceptions.ts
@@ -1 +0,0 @@
-
diff --git a/invokeai/frontend/web/src/features/metadata/hooks/useMetadataItem.tsx b/invokeai/frontend/web/src/features/metadata/hooks/useMetadataItem.tsx
index 63d987569b..18df0c7323 100644
--- a/invokeai/frontend/web/src/features/metadata/hooks/useMetadataItem.tsx
+++ b/invokeai/frontend/web/src/features/metadata/hooks/useMetadataItem.tsx
@@ -2,15 +2,23 @@ import { Text } from '@invoke-ai/ui-library';
 import type { MetadataHandlers } from 'features/metadata/types';
 import { MetadataParseFailedToken, MetadataParsePendingToken } from 'features/metadata/util/parsers';
 import { useCallback, useEffect, useMemo, useState } from 'react';
+import { useTranslation } from 'react-i18next';
 
-const pendingRenderedValue = <Text>Loading</Text>;
-const failedRenderedValue = <Text>Parsing Failed</Text>;
+const Pending = () => {
+  const { t } = useTranslation();
+  return <Text>{t('common.loading')}</Text>;
+};
+
+const Failed = () => {
+  const { t } = useTranslation();
+  return <Text>{t('metadata.parsingFailed')}</Text>;
+};
 
 export const useMetadataItem = <T,>(metadata: unknown, handlers: MetadataHandlers<T>) => {
   const [value, setValue] = useState<T | typeof MetadataParsePendingToken | typeof MetadataParseFailedToken>(
     MetadataParsePendingToken
   );
-  const [renderedValue, setRenderedValue] = useState<React.ReactNode>(pendingRenderedValue);
+  const [renderedValue, setRenderedValue] = useState<React.ReactNode>(Pending);
 
   useEffect(() => {
     const _parse = async () => {
@@ -31,11 +39,11 @@ export const useMetadataItem = <T,>(metadata: unknown, handlers: MetadataHandler
   useEffect(() => {
     const _renderValue = async () => {
       if (value === MetadataParsePendingToken) {
-        setRenderedValue(pendingRenderedValue);
+        setRenderedValue(Pending);
         return;
       }
       if (value === MetadataParseFailedToken) {
-        setRenderedValue(failedRenderedValue);
+        setRenderedValue(Failed);
         return;
       }
 
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelTypeSelect.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelTypeSelect.tsx
index dc42ae89a8..a995ddc511 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelTypeSelect.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelTypeSelect.tsx
@@ -15,7 +15,7 @@ const options: ComboboxOption[] = [
   { value: 'controlnet', label: MODEL_TYPE_LABELS['controlnet'] as string },
   { value: 'ip_adapter', label: MODEL_TYPE_LABELS['ip_adapter'] as string },
   { value: 't2i_adapater', label: MODEL_TYPE_LABELS['t2i_adapter'] as string },
-] as const
+] as const;
 
 const ModelTypeSelect = <T extends AnyModelConfig>(props: UseControllerProps<T>) => {
   const { field } = useController(props);
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useAnyOrDirectInputFieldNames.ts b/invokeai/frontend/web/src/features/nodes/hooks/useAnyOrDirectInputFieldNames.ts
index 13c78bae84..4d0e54b239 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useAnyOrDirectInputFieldNames.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useAnyOrDirectInputFieldNames.ts
@@ -1,4 +1,4 @@
-import { EMPTY_ARRAY } from "app/store/constants";
+import { EMPTY_ARRAY } from 'app/store/constants';
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppSelector } from 'app/store/storeHooks';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useConnectionInputFieldNames.ts b/invokeai/frontend/web/src/features/nodes/hooks/useConnectionInputFieldNames.ts
index 43b6ed6ef1..d332bf46e3 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useConnectionInputFieldNames.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useConnectionInputFieldNames.ts
@@ -1,4 +1,4 @@
-import { EMPTY_ARRAY } from "app/store/constants";
+import { EMPTY_ARRAY } from 'app/store/constants';
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppSelector } from 'app/store/storeHooks';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useOutputFieldNames.ts b/invokeai/frontend/web/src/features/nodes/hooks/useOutputFieldNames.ts
index bbcd7f2068..e16b329c22 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useOutputFieldNames.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useOutputFieldNames.ts
@@ -1,5 +1,5 @@
 import { createSelector } from '@reduxjs/toolkit';
-import { EMPTY_ARRAY } from "app/store/constants";
+import { EMPTY_ARRAY } from 'app/store/constants';
 import { useAppSelector } from 'app/store/storeHooks';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
 import { selectNodeTemplate } from 'features/nodes/store/selectors';
diff --git a/invokeai/frontend/web/src/features/parameters/hooks/usePreselectedImage.ts b/invokeai/frontend/web/src/features/parameters/hooks/usePreselectedImage.ts
index ab0fdca0af..30f954dedb 100644
--- a/invokeai/frontend/web/src/features/parameters/hooks/usePreselectedImage.ts
+++ b/invokeai/frontend/web/src/features/parameters/hooks/usePreselectedImage.ts
@@ -10,7 +10,6 @@ import { t } from 'i18next';
 import { useCallback, useEffect } from 'react';
 import { useGetImageDTOQuery, useGetImageMetadataQuery } from 'services/api/endpoints/images';
 
-
 export const usePreselectedImage = (selectedImage?: {
   imageName: string;
   action: 'sendToImg2Img' | 'sendToCanvas' | 'useAllParameters';
diff --git a/invokeai/frontend/web/src/features/settingsAccordions/components/GenerationSettingsAccordion/GenerationSettingsAccordion.tsx b/invokeai/frontend/web/src/features/settingsAccordions/components/GenerationSettingsAccordion/GenerationSettingsAccordion.tsx
index 8922bb414c..26a55b7c70 100644
--- a/invokeai/frontend/web/src/features/settingsAccordions/components/GenerationSettingsAccordion/GenerationSettingsAccordion.tsx
+++ b/invokeai/frontend/web/src/features/settingsAccordions/components/GenerationSettingsAccordion/GenerationSettingsAccordion.tsx
@@ -10,7 +10,7 @@ import {
   TabPanels,
   Tabs,
 } from '@invoke-ai/ui-library';
-import { EMPTY_ARRAY } from "app/store/constants";
+import { EMPTY_ARRAY } from 'app/store/constants';
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppSelector } from 'app/store/storeHooks';
 import { LoRAList } from 'features/lora/components/LoRAList';
diff --git a/invokeai/frontend/web/src/services/api/endpoints/models.ts b/invokeai/frontend/web/src/services/api/endpoints/models.ts
index c125dcd371..a236868b79 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/models.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/models.ts
@@ -46,7 +46,7 @@ type InstallModelArg = {
   access_token?: paths['/api/v2/models/install']['post']['parameters']['query']['access_token'];
   // TODO(MM2): This is typed as `Optional[Dict[str, Any]]` in backend...
   config?: JSONObject;
-  // config: NonNullable<paths['/api/v2/models/heuristic_install']['post']['requestBody']>['content']['application/json'];
+  // config: NonNullable<paths['/api/v2/models/install']['post']['requestBody']>['content']['application/json'];
 };
 
 type InstallModelResponse = paths['/api/v2/models/install']['post']['responses']['201']['content']['application/json'];
@@ -180,7 +180,7 @@ export const modelsApi = api.injectEndpoints({
     installModel: build.mutation<InstallModelResponse, InstallModelArg>({
       query: ({ source, config, access_token }) => {
         return {
-          url: buildModelsUrl('heuristic_install'),
+          url: buildModelsUrl('install'),
           params: { source, access_token },
           method: 'POST',
           body: config,

From b2182821495e8cb20c0480f65f8dc453b9fc1c91 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 27 Feb 2024 15:52:06 +1100
Subject: [PATCH 341/411] fix(ui): model install progress sets total bytes
 correctly

---
 .../listeners/socketio/socketModelInstall.ts                | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts
index b658354c42..60dc173cb4 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts
@@ -12,13 +12,14 @@ export const addModelInstallEventListener = () => {
   startAppListening({
     actionCreator: socketModelInstallDownloading,
     effect: async (action, { dispatch }) => {
-      const { bytes, id } = action.payload.data;
+      const { bytes, total_bytes, id } = action.payload.data;
 
       dispatch(
         modelsApi.util.updateQueryData('getModelImports', undefined, (draft) => {
           const modelImport = draft.find((m) => m.id === id);
           if (modelImport) {
             modelImport.bytes = bytes;
+            modelImport.total_bytes = total_bytes;
             modelImport.status = 'downloading';
           }
           return draft;
@@ -48,7 +49,7 @@ export const addModelInstallEventListener = () => {
   startAppListening({
     actionCreator: socketModelInstallError,
     effect: (action, { dispatch }) => {
-      const { id, error_type } = action.payload.data;
+      const { id, error, error_type } = action.payload.data;
 
       dispatch(
         modelsApi.util.updateQueryData('getModelImports', undefined, (draft) => {
@@ -56,6 +57,7 @@ export const addModelInstallEventListener = () => {
           if (modelImport) {
             modelImport.status = 'error';
             modelImport.error_reason = error_type;
+            modelImport.error = error;
           }
           return draft;
         })

From 12e859835bfad50f81725ac6aaec5ca1345f4064 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 27 Feb 2024 16:26:40 +1100
Subject: [PATCH 342/411] feat(mm): add log stmt for download complete event

---
 invokeai/app/services/model_install/model_install_default.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py
index 903fe41b08..a48cf92b99 100644
--- a/invokeai/app/services/model_install/model_install_default.py
+++ b/invokeai/app/services/model_install/model_install_default.py
@@ -743,6 +743,7 @@ class ModelInstallService(ModelInstallServiceBase):
                 self._signal_job_downloading(install_job)
 
     def _download_complete_callback(self, download_job: DownloadJob) -> None:
+        self._logger.info(f"{download_job.source}: model download complete")
         with self._lock:
             install_job = self._download_cache[download_job.source]
             self._download_cache.pop(download_job.source, None)
@@ -775,7 +776,7 @@ class ModelInstallService(ModelInstallServiceBase):
             if not install_job:
                 return
             self._downloads_changed_event.set()
-            self._logger.warning(f"Download {download_job.source} cancelled.")
+            self._logger.warning(f"{download_job.source}: model download cancelled")
             # if install job has already registered an error, then do not replace its status with cancelled
             if not install_job.errored:
                 install_job.cancel()

From a6f6fe581ec311518b9269c9208cc99d99f851b2 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 27 Feb 2024 16:36:30 +1100
Subject: [PATCH 343/411] tidy(ui): clean up unused code 2

types and schemas
---
 .../src/features/nodes/types/common.test-d.ts | 15 -------
 .../web/src/features/nodes/types/common.ts    | 44 -------------------
 .../web/src/features/nodes/types/constants.ts |  8 ----
 .../web/src/features/nodes/types/field.ts     | 19 +++-----
 4 files changed, 7 insertions(+), 79 deletions(-)

diff --git a/invokeai/frontend/web/src/features/nodes/types/common.test-d.ts b/invokeai/frontend/web/src/features/nodes/types/common.test-d.ts
index 5e92998657..13c3db52fd 100644
--- a/invokeai/frontend/web/src/features/nodes/types/common.test-d.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/common.test-d.ts
@@ -7,14 +7,9 @@ import type {
   ImageField,
   ImageOutput,
   IPAdapterField,
-  ModelInfo,
-  ModelType,
   ProgressImage,
   SchedulerField,
-  SDXLRefinerModelField,
-  SubModelType,
   T2IAdapterField,
-  VAEField,
 } from 'features/nodes/types/common';
 import type { S } from 'services/api/types';
 import type { Equals, Extends } from 'tsafe';
@@ -32,23 +27,13 @@ describe('Common types', () => {
   test('BoardField', () => assert<Equals<BoardField, S['BoardField']>>());
   test('ColorField', () => assert<Equals<ColorField, S['ColorField']>>());
   test('SchedulerField', () => assert<Equals<SchedulerField, NonNullable<S['SchedulerInvocation']['scheduler']>>>());
-  // test('MainModelField', () => assert<Equals<MainModelField, S['MainModelField']>>());
-  test('SDXLRefinerModelField', () => assert<Equals<SDXLRefinerModelField, S['MainModelField']>>());
-  test('VAEField', () => assert<Extends<S['VaeField'], VAEField>>());
   test('ControlField', () => assert<Equals<ControlField, S['ControlField']>>());
   // @ts-expect-error TODO(psyche): fix types
   test('IPAdapterField', () => assert<Extends<IPAdapterField, S['IPAdapterField']>>());
   test('T2IAdapterField', () => assert<Equals<T2IAdapterField, S['T2IAdapterField']>>());
-  // test('LoRAModelField', () => assert<Equals<LoRAModelField, S['LoRAModelField']>>());
-  // test('ControlNetModelField', () => assert<Equals<ControlNetModelField, S['ControlNetModelField']>>());
-  // test('IPAdapterModelField', () => assert<Equals<IPAdapterModelField, S['IPAdapterModelField']>>());
-  // test('T2IAdapterModelField', () => assert<Equals<T2IAdapterModelField, S['T2IAdapterModelField']>>());
 
   // Model component types
   test('BaseModel', () => assert<Equals<BaseModel, S['BaseModelType']>>());
-  test('ModelType', () => assert<Equals<ModelType, S['ModelType']>>());
-  test('SubModelType', () => assert<Equals<SubModelType, S['SubModelType']>>());
-  test('ModelInfo', () => assert<Equals<ModelInfo, S['ModelInfo']>>());
 
   // Misc types
   // @ts-expect-error TODO(psyche): There is no `ProgressImage` in the server types yet
diff --git a/invokeai/frontend/web/src/features/nodes/types/common.ts b/invokeai/frontend/web/src/features/nodes/types/common.ts
index 923fef3c04..461e804db3 100644
--- a/invokeai/frontend/web/src/features/nodes/types/common.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/common.ts
@@ -64,7 +64,6 @@ export const zModelType = z.enum([
   'ip_adapter',
   'clip_vision',
   't2i_adapter',
-  'onnx', // TODO(psyche): Remove this when removed from backend
 ]);
 export const zModelName = z.string().min(3);
 export const zModelIdentifier = z.object({
@@ -80,49 +79,6 @@ export type BaseModel = z.infer<typeof zBaseModel>;
 export type ModelType = z.infer<typeof zModelType>;
 export type ModelIdentifier = z.infer<typeof zModelIdentifier>;
 export type ModelIdentifierWithBase = z.infer<typeof zModelIdentifierWithBase>;
-export const zMainModelField = zModelIdentifierWithBase;
-export type MainModelField = z.infer<typeof zMainModelField>;
-
-export const zSDXLRefinerModelField = zModelIdentifier;
-export type SDXLRefinerModelField = z.infer<typeof zSDXLRefinerModelField>;
-
-export const zSubModelType = z.enum([
-  'unet',
-  'text_encoder',
-  'text_encoder_2',
-  'tokenizer',
-  'tokenizer_2',
-  'vae',
-  'vae_decoder',
-  'vae_encoder',
-  'scheduler',
-  'safety_checker',
-]);
-export type SubModelType = z.infer<typeof zSubModelType>;
-
-export const zVAEModelField = zModelIdentifierWithBase;
-
-const zModelInfo = zModelIdentifier.extend({
-  submodel_type: zSubModelType.nullish(),
-});
-export type ModelInfo = z.infer<typeof zModelInfo>;
-
-export const zLoRAModelField = zModelIdentifierWithBase;
-export type LoRAModelField = z.infer<typeof zLoRAModelField>;
-
-export const zControlNetModelField = zModelIdentifierWithBase;
-export type ControlNetModelField = z.infer<typeof zControlNetModelField>;
-
-export const zIPAdapterModelField = zModelIdentifierWithBase;
-export type IPAdapterModelField = z.infer<typeof zIPAdapterModelField>;
-
-export const zT2IAdapterModelField = zModelIdentifierWithBase;
-export type T2IAdapterModelField = z.infer<typeof zT2IAdapterModelField>;
-
-export const zVAEField = z.object({
-  vae: zModelInfo,
-});
-export type VAEField = z.infer<typeof zVAEField>;
 // #endregion
 
 // #region Control Adapters
diff --git a/invokeai/frontend/web/src/features/nodes/types/constants.ts b/invokeai/frontend/web/src/features/nodes/types/constants.ts
index 35ef9e9fd2..0100c0df7d 100644
--- a/invokeai/frontend/web/src/features/nodes/types/constants.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/constants.ts
@@ -23,14 +23,6 @@ export const SHARED_NODE_PROPERTIES: Partial<Node> = {
   dragHandle: `.${DRAG_HANDLE_CLASSNAME}`,
 };
 
-/**
- * Helper for getting the kind of a field.
- */
-export const KIND_MAP = {
-  input: 'inputs' as const,
-  output: 'outputs' as const,
-};
-
 /**
  * Model types' handles are rendered as squares in the UI.
  */
diff --git a/invokeai/frontend/web/src/features/nodes/types/field.ts b/invokeai/frontend/web/src/features/nodes/types/field.ts
index aa6164d6e5..e630d59e07 100644
--- a/invokeai/frontend/web/src/features/nodes/types/field.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/field.ts
@@ -3,14 +3,9 @@ import { z } from 'zod';
 import {
   zBoardField,
   zColorField,
-  zControlNetModelField,
   zImageField,
-  zIPAdapterModelField,
-  zLoRAModelField,
-  zMainModelField,
+  zModelIdentifierWithBase,
   zSchedulerField,
-  zT2IAdapterModelField,
-  zVAEModelField,
 } from './common';
 
 /**
@@ -313,7 +308,7 @@ export const isColorFieldInputTemplate = (val: unknown): val is ColorFieldInputT
 export const zMainModelFieldType = zFieldTypeBase.extend({
   name: z.literal('MainModelField'),
 });
-export const zMainModelFieldValue = zMainModelField.optional();
+export const zMainModelFieldValue = zModelIdentifierWithBase.optional();
 export const zMainModelFieldInputInstance = zFieldInputInstanceBase.extend({
   value: zMainModelFieldValue,
 });
@@ -391,7 +386,7 @@ export const isSDXLRefinerModelFieldInputTemplate = (val: unknown): val is SDXLR
 export const zVAEModelFieldType = zFieldTypeBase.extend({
   name: z.literal('VAEModelField'),
 });
-export const zVAEModelFieldValue = zVAEModelField.optional();
+export const zVAEModelFieldValue = zModelIdentifierWithBase.optional();
 export const zVAEModelFieldInputInstance = zFieldInputInstanceBase.extend({
   value: zVAEModelFieldValue,
 });
@@ -417,7 +412,7 @@ export const isVAEModelFieldInputTemplate = (val: unknown): val is VAEModelField
 export const zLoRAModelFieldType = zFieldTypeBase.extend({
   name: z.literal('LoRAModelField'),
 });
-export const zLoRAModelFieldValue = zLoRAModelField.optional();
+export const zLoRAModelFieldValue = zModelIdentifierWithBase.optional();
 export const zLoRAModelFieldInputInstance = zFieldInputInstanceBase.extend({
   value: zLoRAModelFieldValue,
 });
@@ -443,7 +438,7 @@ export const isLoRAModelFieldInputTemplate = (val: unknown): val is LoRAModelFie
 export const zControlNetModelFieldType = zFieldTypeBase.extend({
   name: z.literal('ControlNetModelField'),
 });
-export const zControlNetModelFieldValue = zControlNetModelField.optional();
+export const zControlNetModelFieldValue = zModelIdentifierWithBase.optional();
 export const zControlNetModelFieldInputInstance = zFieldInputInstanceBase.extend({
   value: zControlNetModelFieldValue,
 });
@@ -471,7 +466,7 @@ export const isControlNetModelFieldValue = (v: unknown): v is ControlNetModelFie
 export const zIPAdapterModelFieldType = zFieldTypeBase.extend({
   name: z.literal('IPAdapterModelField'),
 });
-export const zIPAdapterModelFieldValue = zIPAdapterModelField.optional();
+export const zIPAdapterModelFieldValue = zModelIdentifierWithBase.optional();
 export const zIPAdapterModelFieldInputInstance = zFieldInputInstanceBase.extend({
   value: zIPAdapterModelFieldValue,
 });
@@ -499,7 +494,7 @@ export const isIPAdapterModelFieldValue = (val: unknown): val is IPAdapterModelF
 export const zT2IAdapterModelFieldType = zFieldTypeBase.extend({
   name: z.literal('T2IAdapterModelField'),
 });
-export const zT2IAdapterModelFieldValue = zT2IAdapterModelField.optional();
+export const zT2IAdapterModelFieldValue = zModelIdentifierWithBase.optional();
 export const zT2IAdapterModelFieldInputInstance = zFieldInputInstanceBase.extend({
   value: zT2IAdapterModelFieldValue,
 });

From dc64089c9d75c82a8fb1243f34810dabc2bd6e70 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 27 Feb 2024 17:07:40 +1100
Subject: [PATCH 344/411] tidy(ui): clean up unused code 3

variables, types and schemas
---
 invokeai/frontend/web/knip.json               |   4 -
 invokeai/frontend/web/knip.ts                 |  19 ++
 .../ParamDynamicPromptsCombinatorial.tsx      |  24 ---
 .../Boards/NoBoardContextMenuItems.tsx        |   7 -
 .../web/src/features/metadata/exceptions.ts   |   0
 .../AddModelPanel/BaseModelSelect.tsx         |  38 ----
 .../AddModelPanel/ModelVariantSelect.tsx      |  36 ----
 .../AddModelPanel/ScanModels/ScanModels.tsx   |   3 -
 .../nodes/hooks/useDoNodeVersionsMatch.ts     |  25 ---
 .../features/nodes/hooks/useFieldInputKind.ts |  21 --
 .../nodes/hooks/useNodeTemplateByType.ts      |  19 --
 .../web/src/features/nodes/types/common.ts    |  11 +-
 .../web/src/features/nodes/types/field.ts     | 199 ++++++++----------
 .../src/features/nodes/types/invocation.ts    |  12 +-
 .../web/src/features/nodes/types/workflow.ts  |  20 +-
 .../nodes/util/graph/buildNodesGraph.ts       |  12 +-
 .../features/nodes/util/graph/constants.ts    |  54 -----
 .../features/nodes/util/node/nodeUpdate.ts    |  12 +-
 .../MaskAdjustment/ParamMaskBlurMethod.tsx    |  45 ----
 .../ParamScaleBeforeProcessing.tsx            |   2 +-
 .../components/ImageSize/constants.ts         |   4 +-
 .../parameters/components/ImageSize/hooks.ts  |  45 ----
 .../parameters/components/ImageSize/types.ts  |   2 +-
 .../hooks/useCoreParametersCollapseLabel.ts   |  29 ---
 .../parameters/store/generationSlice.ts       |  24 +--
 .../features/queue/hooks/useIsQueueEmpty.ts   |  15 --
 .../components/SettingsModal/StyledFlex.tsx   |  13 --
 27 files changed, 141 insertions(+), 554 deletions(-)
 delete mode 100644 invokeai/frontend/web/knip.json
 create mode 100644 invokeai/frontend/web/knip.ts
 delete mode 100644 invokeai/frontend/web/src/features/dynamicPrompts/components/ParamDynamicPromptsCombinatorial.tsx
 delete mode 100644 invokeai/frontend/web/src/features/gallery/components/Boards/NoBoardContextMenuItems.tsx
 delete mode 100644 invokeai/frontend/web/src/features/metadata/exceptions.ts
 delete mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/BaseModelSelect.tsx
 delete mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ModelVariantSelect.tsx
 delete mode 100644 invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModels.tsx
 delete mode 100644 invokeai/frontend/web/src/features/nodes/hooks/useDoNodeVersionsMatch.ts
 delete mode 100644 invokeai/frontend/web/src/features/nodes/hooks/useFieldInputKind.ts
 delete mode 100644 invokeai/frontend/web/src/features/nodes/hooks/useNodeTemplateByType.ts
 delete mode 100644 invokeai/frontend/web/src/features/parameters/components/Canvas/Compositing/MaskAdjustment/ParamMaskBlurMethod.tsx
 delete mode 100644 invokeai/frontend/web/src/features/parameters/components/ImageSize/hooks.ts
 delete mode 100644 invokeai/frontend/web/src/features/parameters/hooks/useCoreParametersCollapseLabel.ts
 delete mode 100644 invokeai/frontend/web/src/features/queue/hooks/useIsQueueEmpty.ts
 delete mode 100644 invokeai/frontend/web/src/features/system/components/SettingsModal/StyledFlex.tsx

diff --git a/invokeai/frontend/web/knip.json b/invokeai/frontend/web/knip.json
deleted file mode 100644
index b632b8c56a..0000000000
--- a/invokeai/frontend/web/knip.json
+++ /dev/null
@@ -1,4 +0,0 @@
-{
-  "$schema": "https://unpkg.com/knip@5/schema.json",
-  "ignore": ["src/features/nodes/types/v2/**/*", "src/features/nodes/types/v1/**/*"]
-}
diff --git a/invokeai/frontend/web/knip.ts b/invokeai/frontend/web/knip.ts
new file mode 100644
index 0000000000..0f7c8c2354
--- /dev/null
+++ b/invokeai/frontend/web/knip.ts
@@ -0,0 +1,19 @@
+import type { KnipConfig } from 'knip';
+
+const config: KnipConfig = {
+  ignore: [
+    // This file is only used during debugging
+    'src/app/store/middleware/debugLoggerMiddleware.ts',
+    // These are old schemas, used in migrations. Needs cleanup.
+    'src/features/nodes/types/v2/**/*',
+    'src/features/nodes/types/v1/**/*',
+    // We don't want to check the public folder - contains images and translations
+    'public/**/*',
+  ],
+  compilers: {
+    //
+    svg: () => '',
+  },
+};
+
+export default config;
diff --git a/invokeai/frontend/web/src/features/dynamicPrompts/components/ParamDynamicPromptsCombinatorial.tsx b/invokeai/frontend/web/src/features/dynamicPrompts/components/ParamDynamicPromptsCombinatorial.tsx
deleted file mode 100644
index 64901ddb86..0000000000
--- a/invokeai/frontend/web/src/features/dynamicPrompts/components/ParamDynamicPromptsCombinatorial.tsx
+++ /dev/null
@@ -1,24 +0,0 @@
-import { FormControl, FormLabel, Switch } from '@invoke-ai/ui-library';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import { combinatorialToggled } from 'features/dynamicPrompts/store/dynamicPromptsSlice';
-import { memo, useCallback } from 'react';
-import { useTranslation } from 'react-i18next';
-
-const ParamDynamicPromptsCombinatorial = () => {
-  const combinatorial = useAppSelector((s) => s.dynamicPrompts.combinatorial);
-  const dispatch = useAppDispatch();
-  const { t } = useTranslation();
-
-  const handleChange = useCallback(() => {
-    dispatch(combinatorialToggled());
-  }, [dispatch]);
-
-  return (
-    <FormControl>
-      <FormLabel>{t('dynamicPrompts.combinatorial')}</FormLabel>
-      <Switch isChecked={combinatorial} onChange={handleChange} />
-    </FormControl>
-  );
-};
-
-export default memo(ParamDynamicPromptsCombinatorial);
diff --git a/invokeai/frontend/web/src/features/gallery/components/Boards/NoBoardContextMenuItems.tsx b/invokeai/frontend/web/src/features/gallery/components/Boards/NoBoardContextMenuItems.tsx
deleted file mode 100644
index 4c1ae0eb83..0000000000
--- a/invokeai/frontend/web/src/features/gallery/components/Boards/NoBoardContextMenuItems.tsx
+++ /dev/null
@@ -1,7 +0,0 @@
-import { memo } from 'react';
-
-const NoBoardContextMenuItems = () => {
-  return <></>;
-};
-
-export default memo(NoBoardContextMenuItems);
diff --git a/invokeai/frontend/web/src/features/metadata/exceptions.ts b/invokeai/frontend/web/src/features/metadata/exceptions.ts
deleted file mode 100644
index e69de29bb2..0000000000
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/BaseModelSelect.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/BaseModelSelect.tsx
deleted file mode 100644
index a2d1176a80..0000000000
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/BaseModelSelect.tsx
+++ /dev/null
@@ -1,38 +0,0 @@
-import type { ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
-import { Combobox, Flex, FormControl, FormLabel } from '@invoke-ai/ui-library';
-import { typedMemo } from 'common/util/typedMemo';
-import { MODEL_TYPE_MAP } from 'features/parameters/types/constants';
-import { useCallback, useMemo } from 'react';
-import type { UseControllerProps } from 'react-hook-form';
-import { useController } from 'react-hook-form';
-import { useTranslation } from 'react-i18next';
-import type { AnyModelConfig } from 'services/api/types';
-
-const options: ComboboxOption[] = [
-  { value: 'sd-1', label: MODEL_TYPE_MAP['sd-1'] },
-  { value: 'sd-2', label: MODEL_TYPE_MAP['sd-2'] },
-  { value: 'sdxl', label: MODEL_TYPE_MAP['sdxl'] },
-  { value: 'sdxl-refiner', label: MODEL_TYPE_MAP['sdxl-refiner'] },
-];
-
-const BaseModelSelect = <T extends AnyModelConfig>(props: UseControllerProps<T>) => {
-  const { t } = useTranslation();
-  const { field } = useController(props);
-  const value = useMemo(() => options.find((o) => o.value === field.value), [field.value]);
-  const onChange = useCallback<ComboboxOnChange>(
-    (v) => {
-      field.onChange(v?.value);
-    },
-    [field]
-  );
-  return (
-    <FormControl>
-      <Flex direction="column" width="full">
-        <FormLabel>{t('modelManager.baseModel')}</FormLabel>
-        <Combobox value={value} options={options} onChange={onChange} />
-      </Flex>
-    </FormControl>
-  );
-};
-
-export default typedMemo(BaseModelSelect);
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ModelVariantSelect.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ModelVariantSelect.tsx
deleted file mode 100644
index 80cb5a637c..0000000000
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ModelVariantSelect.tsx
+++ /dev/null
@@ -1,36 +0,0 @@
-import type { ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
-import { Combobox, Flex, FormControl, FormLabel } from '@invoke-ai/ui-library';
-import { typedMemo } from 'common/util/typedMemo';
-import { useCallback, useMemo } from 'react';
-import type { UseControllerProps } from 'react-hook-form';
-import { useController } from 'react-hook-form';
-import { useTranslation } from 'react-i18next';
-import type { CheckpointModelConfig, DiffusersModelConfig } from 'services/api/types';
-
-const options: ComboboxOption[] = [
-  { value: 'normal', label: 'Normal' },
-  { value: 'inpaint', label: 'Inpaint' },
-  { value: 'depth', label: 'Depth' },
-];
-
-const ModelVariantSelect = <T extends CheckpointModelConfig | DiffusersModelConfig>(props: UseControllerProps<T>) => {
-  const { t } = useTranslation();
-  const { field } = useController(props);
-  const value = useMemo(() => options.find((o) => o.value === field.value), [field.value]);
-  const onChange = useCallback<ComboboxOnChange>(
-    (v) => {
-      field.onChange(v?.value);
-    },
-    [field]
-  );
-  return (
-    <FormControl>
-      <Flex direction="column" width="full">
-        <FormLabel>{t('modelManager.variant')}</FormLabel>
-        <Combobox value={value} options={options} onChange={onChange} />
-      </Flex>
-    </FormControl>
-  );
-};
-
-export default typedMemo(ModelVariantSelect);
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModels.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModels.tsx
deleted file mode 100644
index 0a280a52fd..0000000000
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModels.tsx
+++ /dev/null
@@ -1,3 +0,0 @@
-export const ScanModels = () => {
-  return null;
-};
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useDoNodeVersionsMatch.ts b/invokeai/frontend/web/src/features/nodes/hooks/useDoNodeVersionsMatch.ts
deleted file mode 100644
index 91994cf752..0000000000
--- a/invokeai/frontend/web/src/features/nodes/hooks/useDoNodeVersionsMatch.ts
+++ /dev/null
@@ -1,25 +0,0 @@
-import { createSelector } from '@reduxjs/toolkit';
-import { useAppSelector } from 'app/store/storeHooks';
-import { compareVersions } from 'compare-versions';
-import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { selectNodeData, selectNodeTemplate } from 'features/nodes/store/selectors';
-import { useMemo } from 'react';
-
-export const useDoNodeVersionsMatch = (nodeId: string): boolean => {
-  const selector = useMemo(
-    () =>
-      createSelector(selectNodesSlice, (nodes) => {
-        const data = selectNodeData(nodes, nodeId);
-        const template = selectNodeTemplate(nodes, nodeId);
-        if (!template?.version || !data?.version) {
-          return false;
-        }
-        return compareVersions(template.version, data.version) === 0;
-      }),
-    [nodeId]
-  );
-
-  const nodeTemplate = useAppSelector(selector);
-
-  return nodeTemplate;
-};
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useFieldInputKind.ts b/invokeai/frontend/web/src/features/nodes/hooks/useFieldInputKind.ts
deleted file mode 100644
index 08de3d9b20..0000000000
--- a/invokeai/frontend/web/src/features/nodes/hooks/useFieldInputKind.ts
+++ /dev/null
@@ -1,21 +0,0 @@
-import { createSelector } from '@reduxjs/toolkit';
-import { useAppSelector } from 'app/store/storeHooks';
-import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { selectFieldInputTemplate } from 'features/nodes/store/selectors';
-import type { FieldInput } from 'features/nodes/types/field';
-import { useMemo } from 'react';
-
-export const useFieldInputKind = (nodeId: string, fieldName: string) => {
-  const selector = useMemo(
-    () =>
-      createSelector(selectNodesSlice, (nodes): FieldInput | null => {
-        const template = selectFieldInputTemplate(nodes, nodeId, fieldName);
-        return template?.input ?? null;
-      }),
-    [fieldName, nodeId]
-  );
-
-  const inputKind = useAppSelector(selector);
-
-  return inputKind;
-};
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useNodeTemplateByType.ts b/invokeai/frontend/web/src/features/nodes/hooks/useNodeTemplateByType.ts
deleted file mode 100644
index a0c870f694..0000000000
--- a/invokeai/frontend/web/src/features/nodes/hooks/useNodeTemplateByType.ts
+++ /dev/null
@@ -1,19 +0,0 @@
-import { createSelector } from '@reduxjs/toolkit';
-import { useAppSelector } from 'app/store/storeHooks';
-import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import type { InvocationTemplate } from 'features/nodes/types/invocation';
-import { useMemo } from 'react';
-
-export const useNodeTemplateByType = (type: string): InvocationTemplate | null => {
-  const selector = useMemo(
-    () =>
-      createSelector(selectNodesSlice, (nodes) => {
-        return nodes.templates[type] ?? null;
-      }),
-    [type]
-  );
-
-  const nodeTemplate = useAppSelector(selector);
-
-  return nodeTemplate;
-};
diff --git a/invokeai/frontend/web/src/features/nodes/types/common.ts b/invokeai/frontend/web/src/features/nodes/types/common.ts
index 461e804db3..82c41096d9 100644
--- a/invokeai/frontend/web/src/features/nodes/types/common.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/common.ts
@@ -54,8 +54,8 @@ export type SchedulerField = z.infer<typeof zSchedulerField>;
 // #endregion
 
 // #region Model-related schemas
-export const zBaseModel = z.enum(['any', 'sd-1', 'sd-2', 'sdxl', 'sdxl-refiner']);
-export const zModelType = z.enum([
+const zBaseModel = z.enum(['any', 'sd-1', 'sd-2', 'sdxl', 'sdxl-refiner']);
+const zModelType = z.enum([
   'main',
   'vae',
   'lora',
@@ -65,15 +65,14 @@ export const zModelType = z.enum([
   'clip_vision',
   't2i_adapter',
 ]);
-export const zModelName = z.string().min(3);
-export const zModelIdentifier = z.object({
+const zModelIdentifier = z.object({
   key: z.string().min(1),
 });
 export const isModelIdentifier = (field: unknown): field is ModelIdentifier =>
   zModelIdentifier.safeParse(field).success;
 export const isModelIdentifierV2 = (field: unknown): field is ModelIdentifierV2 =>
   zModelIdentifierV2.safeParse(field).success;
-export const zModelFieldBase = zModelIdentifier;
+const zModelFieldBase = zModelIdentifier;
 export const zModelIdentifierWithBase = zModelIdentifier.extend({ base: zBaseModel });
 export type BaseModel = z.infer<typeof zBaseModel>;
 export type ModelType = z.infer<typeof zModelType>;
@@ -123,7 +122,7 @@ export type ProgressImage = z.infer<typeof zProgressImage>;
 // #endregion
 
 // #region ImageOutput
-export const zImageOutput = z.object({
+const zImageOutput = z.object({
   image: zImageField,
   width: z.number().int().gt(0),
   height: z.number().int().gt(0),
diff --git a/invokeai/frontend/web/src/features/nodes/types/field.ts b/invokeai/frontend/web/src/features/nodes/types/field.ts
index e630d59e07..83dbf27e1e 100644
--- a/invokeai/frontend/web/src/features/nodes/types/field.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/field.ts
@@ -1,12 +1,6 @@
 import { z } from 'zod';
 
-import {
-  zBoardField,
-  zColorField,
-  zImageField,
-  zModelIdentifierWithBase,
-  zSchedulerField,
-} from './common';
+import { zBoardField, zColorField, zImageField, zModelIdentifierWithBase, zSchedulerField } from './common';
 
 /**
  * zod schemas & inferred types for fields.
@@ -35,19 +29,19 @@ import {
 /** */
 
 // #region Base schemas & misc
-export const zFieldInput = z.enum(['connection', 'direct', 'any']);
+const zFieldInput = z.enum(['connection', 'direct', 'any']);
 export type FieldInput = z.infer<typeof zFieldInput>;
 
-export const zFieldUIComponent = z.enum(['none', 'textarea', 'slider']);
+const zFieldUIComponent = z.enum(['none', 'textarea', 'slider']);
 export type FieldUIComponent = z.infer<typeof zFieldUIComponent>;
 
-export const zFieldInputInstanceBase = z.object({
+const zFieldInputInstanceBase = z.object({
   name: z.string().trim().min(1),
   label: z.string().nullish(),
 });
 export type FieldInputInstanceBase = z.infer<typeof zFieldInputInstanceBase>;
 
-export const zFieldTemplateBase = z.object({
+const zFieldTemplateBase = z.object({
   name: z.string().min(1),
   title: z.string().min(1),
   description: z.string().nullish(),
@@ -55,21 +49,21 @@ export const zFieldTemplateBase = z.object({
   ui_type: z.string().nullish(),
   ui_order: z.number().int().nullish(),
 });
-export const zFieldInputTemplateBase = zFieldTemplateBase.extend({
+const zFieldInputTemplateBase = zFieldTemplateBase.extend({
   fieldKind: z.literal('input'),
   input: zFieldInput,
   required: z.boolean(),
   ui_component: zFieldUIComponent.nullish(),
   ui_choice_labels: z.record(z.string()).nullish(),
 });
-export const zFieldOutputTemplateBase = zFieldTemplateBase.extend({
+const zFieldOutputTemplateBase = zFieldTemplateBase.extend({
   fieldKind: z.literal('output'),
 });
 export type FieldTemplateBase = z.infer<typeof zFieldTemplateBase>;
 export type FieldInputTemplateBase = z.infer<typeof zFieldInputTemplateBase>;
 export type FieldOutputTemplateBase = z.infer<typeof zFieldOutputTemplateBase>;
 
-export const zFieldTypeBase = z.object({
+const zFieldTypeBase = z.object({
   isCollection: z.boolean(),
   isCollectionOrScalar: z.boolean(),
 });
@@ -79,18 +73,17 @@ export const zFieldIdentifier = z.object({
   fieldName: z.string().trim().min(1),
 });
 export type FieldIdentifier = z.infer<typeof zFieldIdentifier>;
-export const isFieldIdentifier = (val: unknown): val is FieldIdentifier => zFieldIdentifier.safeParse(val).success;
 // #endregion
 
 // #region IntegerField
-export const zIntegerFieldType = zFieldTypeBase.extend({
+const zIntegerFieldType = zFieldTypeBase.extend({
   name: z.literal('IntegerField'),
 });
 export const zIntegerFieldValue = z.number().int();
-export const zIntegerFieldInputInstance = zFieldInputInstanceBase.extend({
+const zIntegerFieldInputInstance = zFieldInputInstanceBase.extend({
   value: zIntegerFieldValue,
 });
-export const zIntegerFieldInputTemplate = zFieldInputTemplateBase.extend({
+const zIntegerFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zIntegerFieldType,
   default: zIntegerFieldValue,
   multipleOf: z.number().int().optional(),
@@ -99,7 +92,7 @@ export const zIntegerFieldInputTemplate = zFieldInputTemplateBase.extend({
   minimum: z.number().int().optional(),
   exclusiveMinimum: z.number().int().optional(),
 });
-export const zIntegerFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+const zIntegerFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zIntegerFieldType,
 });
 export type IntegerFieldType = z.infer<typeof zIntegerFieldType>;
@@ -113,14 +106,14 @@ export const isIntegerFieldInputTemplate = (val: unknown): val is IntegerFieldIn
 // #endregion
 
 // #region FloatField
-export const zFloatFieldType = zFieldTypeBase.extend({
+const zFloatFieldType = zFieldTypeBase.extend({
   name: z.literal('FloatField'),
 });
 export const zFloatFieldValue = z.number();
-export const zFloatFieldInputInstance = zFieldInputInstanceBase.extend({
+const zFloatFieldInputInstance = zFieldInputInstanceBase.extend({
   value: zFloatFieldValue,
 });
-export const zFloatFieldInputTemplate = zFieldInputTemplateBase.extend({
+const zFloatFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zFloatFieldType,
   default: zFloatFieldValue,
   multipleOf: z.number().optional(),
@@ -129,7 +122,7 @@ export const zFloatFieldInputTemplate = zFieldInputTemplateBase.extend({
   minimum: z.number().optional(),
   exclusiveMinimum: z.number().optional(),
 });
-export const zFloatFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+const zFloatFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zFloatFieldType,
 });
 export type FloatFieldType = z.infer<typeof zFloatFieldType>;
@@ -144,20 +137,20 @@ export const isFloatFieldInputTemplate = (val: unknown): val is FloatFieldInputT
 // #endregion
 
 // #region StringField
-export const zStringFieldType = zFieldTypeBase.extend({
+const zStringFieldType = zFieldTypeBase.extend({
   name: z.literal('StringField'),
 });
 export const zStringFieldValue = z.string();
-export const zStringFieldInputInstance = zFieldInputInstanceBase.extend({
+const zStringFieldInputInstance = zFieldInputInstanceBase.extend({
   value: zStringFieldValue,
 });
-export const zStringFieldInputTemplate = zFieldInputTemplateBase.extend({
+const zStringFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zStringFieldType,
   default: zStringFieldValue,
   maxLength: z.number().int().optional(),
   minLength: z.number().int().optional(),
 });
-export const zStringFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+const zStringFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zStringFieldType,
 });
 
@@ -173,18 +166,18 @@ export const isStringFieldInputTemplate = (val: unknown): val is StringFieldInpu
 // #endregion
 
 // #region BooleanField
-export const zBooleanFieldType = zFieldTypeBase.extend({
+const zBooleanFieldType = zFieldTypeBase.extend({
   name: z.literal('BooleanField'),
 });
 export const zBooleanFieldValue = z.boolean();
-export const zBooleanFieldInputInstance = zFieldInputInstanceBase.extend({
+const zBooleanFieldInputInstance = zFieldInputInstanceBase.extend({
   value: zBooleanFieldValue,
 });
-export const zBooleanFieldInputTemplate = zFieldInputTemplateBase.extend({
+const zBooleanFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zBooleanFieldType,
   default: zBooleanFieldValue,
 });
-export const zBooleanFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+const zBooleanFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zBooleanFieldType,
 });
 export type BooleanFieldType = z.infer<typeof zBooleanFieldType>;
@@ -199,20 +192,20 @@ export const isBooleanFieldInputTemplate = (val: unknown): val is BooleanFieldIn
 // #endregion
 
 // #region EnumField
-export const zEnumFieldType = zFieldTypeBase.extend({
+const zEnumFieldType = zFieldTypeBase.extend({
   name: z.literal('EnumField'),
 });
 export const zEnumFieldValue = z.string();
-export const zEnumFieldInputInstance = zFieldInputInstanceBase.extend({
+const zEnumFieldInputInstance = zFieldInputInstanceBase.extend({
   value: zEnumFieldValue,
 });
-export const zEnumFieldInputTemplate = zFieldInputTemplateBase.extend({
+const zEnumFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zEnumFieldType,
   default: zEnumFieldValue,
   options: z.array(z.string()),
   labels: z.record(z.string()).optional(),
 });
-export const zEnumFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+const zEnumFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zEnumFieldType,
 });
 export type EnumFieldType = z.infer<typeof zEnumFieldType>;
@@ -227,18 +220,18 @@ export const isEnumFieldInputTemplate = (val: unknown): val is EnumFieldInputTem
 // #endregion
 
 // #region ImageField
-export const zImageFieldType = zFieldTypeBase.extend({
+const zImageFieldType = zFieldTypeBase.extend({
   name: z.literal('ImageField'),
 });
 export const zImageFieldValue = zImageField.optional();
-export const zImageFieldInputInstance = zFieldInputInstanceBase.extend({
+const zImageFieldInputInstance = zFieldInputInstanceBase.extend({
   value: zImageFieldValue,
 });
-export const zImageFieldInputTemplate = zFieldInputTemplateBase.extend({
+const zImageFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zImageFieldType,
   default: zImageFieldValue,
 });
-export const zImageFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+const zImageFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zImageFieldType,
 });
 export type ImageFieldType = z.infer<typeof zImageFieldType>;
@@ -253,18 +246,18 @@ export const isImageFieldInputTemplate = (val: unknown): val is ImageFieldInputT
 // #endregion
 
 // #region BoardField
-export const zBoardFieldType = zFieldTypeBase.extend({
+const zBoardFieldType = zFieldTypeBase.extend({
   name: z.literal('BoardField'),
 });
 export const zBoardFieldValue = zBoardField.optional();
-export const zBoardFieldInputInstance = zFieldInputInstanceBase.extend({
+const zBoardFieldInputInstance = zFieldInputInstanceBase.extend({
   value: zBoardFieldValue,
 });
-export const zBoardFieldInputTemplate = zFieldInputTemplateBase.extend({
+const zBoardFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zBoardFieldType,
   default: zBoardFieldValue,
 });
-export const zBoardFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+const zBoardFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zBoardFieldType,
 });
 export type BoardFieldType = z.infer<typeof zBoardFieldType>;
@@ -279,18 +272,18 @@ export const isBoardFieldInputTemplate = (val: unknown): val is BoardFieldInputT
 // #endregion
 
 // #region ColorField
-export const zColorFieldType = zFieldTypeBase.extend({
+const zColorFieldType = zFieldTypeBase.extend({
   name: z.literal('ColorField'),
 });
 export const zColorFieldValue = zColorField.optional();
-export const zColorFieldInputInstance = zFieldInputInstanceBase.extend({
+const zColorFieldInputInstance = zFieldInputInstanceBase.extend({
   value: zColorFieldValue,
 });
-export const zColorFieldInputTemplate = zFieldInputTemplateBase.extend({
+const zColorFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zColorFieldType,
   default: zColorFieldValue,
 });
-export const zColorFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+const zColorFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zColorFieldType,
 });
 export type ColorFieldType = z.infer<typeof zColorFieldType>;
@@ -305,18 +298,18 @@ export const isColorFieldInputTemplate = (val: unknown): val is ColorFieldInputT
 // #endregion
 
 // #region MainModelField
-export const zMainModelFieldType = zFieldTypeBase.extend({
+const zMainModelFieldType = zFieldTypeBase.extend({
   name: z.literal('MainModelField'),
 });
 export const zMainModelFieldValue = zModelIdentifierWithBase.optional();
-export const zMainModelFieldInputInstance = zFieldInputInstanceBase.extend({
+const zMainModelFieldInputInstance = zFieldInputInstanceBase.extend({
   value: zMainModelFieldValue,
 });
-export const zMainModelFieldInputTemplate = zFieldInputTemplateBase.extend({
+const zMainModelFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zMainModelFieldType,
   default: zMainModelFieldValue,
 });
-export const zMainModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+const zMainModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zMainModelFieldType,
 });
 export type MainModelFieldType = z.infer<typeof zMainModelFieldType>;
@@ -331,18 +324,18 @@ export const isMainModelFieldInputTemplate = (val: unknown): val is MainModelFie
 // #endregion
 
 // #region SDXLMainModelField
-export const zSDXLMainModelFieldType = zFieldTypeBase.extend({
+const zSDXLMainModelFieldType = zFieldTypeBase.extend({
   name: z.literal('SDXLMainModelField'),
 });
-export const zSDXLMainModelFieldValue = zMainModelFieldValue; // TODO: Narrow to SDXL models only.
-export const zSDXLMainModelFieldInputInstance = zFieldInputInstanceBase.extend({
+const zSDXLMainModelFieldValue = zMainModelFieldValue; // TODO: Narrow to SDXL models only.
+const zSDXLMainModelFieldInputInstance = zFieldInputInstanceBase.extend({
   value: zSDXLMainModelFieldValue,
 });
-export const zSDXLMainModelFieldInputTemplate = zFieldInputTemplateBase.extend({
+const zSDXLMainModelFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zSDXLMainModelFieldType,
   default: zSDXLMainModelFieldValue,
 });
-export const zSDXLMainModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+const zSDXLMainModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zSDXLMainModelFieldType,
 });
 export type SDXLMainModelFieldType = z.infer<typeof zSDXLMainModelFieldType>;
@@ -357,18 +350,18 @@ export const isSDXLMainModelFieldInputTemplate = (val: unknown): val is SDXLMain
 // #endregion
 
 // #region SDXLRefinerModelField
-export const zSDXLRefinerModelFieldType = zFieldTypeBase.extend({
+const zSDXLRefinerModelFieldType = zFieldTypeBase.extend({
   name: z.literal('SDXLRefinerModelField'),
 });
 export const zSDXLRefinerModelFieldValue = zMainModelFieldValue; // TODO: Narrow to SDXL Refiner models only.
-export const zSDXLRefinerModelFieldInputInstance = zFieldInputInstanceBase.extend({
+const zSDXLRefinerModelFieldInputInstance = zFieldInputInstanceBase.extend({
   value: zSDXLRefinerModelFieldValue,
 });
-export const zSDXLRefinerModelFieldInputTemplate = zFieldInputTemplateBase.extend({
+const zSDXLRefinerModelFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zSDXLRefinerModelFieldType,
   default: zSDXLRefinerModelFieldValue,
 });
-export const zSDXLRefinerModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+const zSDXLRefinerModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zSDXLRefinerModelFieldType,
 });
 export type SDXLRefinerModelFieldType = z.infer<typeof zSDXLRefinerModelFieldType>;
@@ -383,18 +376,18 @@ export const isSDXLRefinerModelFieldInputTemplate = (val: unknown): val is SDXLR
 // #endregion
 
 // #region VAEModelField
-export const zVAEModelFieldType = zFieldTypeBase.extend({
+const zVAEModelFieldType = zFieldTypeBase.extend({
   name: z.literal('VAEModelField'),
 });
 export const zVAEModelFieldValue = zModelIdentifierWithBase.optional();
-export const zVAEModelFieldInputInstance = zFieldInputInstanceBase.extend({
+const zVAEModelFieldInputInstance = zFieldInputInstanceBase.extend({
   value: zVAEModelFieldValue,
 });
-export const zVAEModelFieldInputTemplate = zFieldInputTemplateBase.extend({
+const zVAEModelFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zVAEModelFieldType,
   default: zVAEModelFieldValue,
 });
-export const zVAEModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+const zVAEModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zVAEModelFieldType,
 });
 export type VAEModelFieldType = z.infer<typeof zVAEModelFieldType>;
@@ -409,18 +402,18 @@ export const isVAEModelFieldInputTemplate = (val: unknown): val is VAEModelField
 // #endregion
 
 // #region LoRAModelField
-export const zLoRAModelFieldType = zFieldTypeBase.extend({
+const zLoRAModelFieldType = zFieldTypeBase.extend({
   name: z.literal('LoRAModelField'),
 });
 export const zLoRAModelFieldValue = zModelIdentifierWithBase.optional();
-export const zLoRAModelFieldInputInstance = zFieldInputInstanceBase.extend({
+const zLoRAModelFieldInputInstance = zFieldInputInstanceBase.extend({
   value: zLoRAModelFieldValue,
 });
-export const zLoRAModelFieldInputTemplate = zFieldInputTemplateBase.extend({
+const zLoRAModelFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zLoRAModelFieldType,
   default: zLoRAModelFieldValue,
 });
-export const zLoRAModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+const zLoRAModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zLoRAModelFieldType,
 });
 export type LoRAModelFieldType = z.infer<typeof zLoRAModelFieldType>;
@@ -435,18 +428,18 @@ export const isLoRAModelFieldInputTemplate = (val: unknown): val is LoRAModelFie
 // #endregion
 
 // #region ControlNetModelField
-export const zControlNetModelFieldType = zFieldTypeBase.extend({
+const zControlNetModelFieldType = zFieldTypeBase.extend({
   name: z.literal('ControlNetModelField'),
 });
 export const zControlNetModelFieldValue = zModelIdentifierWithBase.optional();
-export const zControlNetModelFieldInputInstance = zFieldInputInstanceBase.extend({
+const zControlNetModelFieldInputInstance = zFieldInputInstanceBase.extend({
   value: zControlNetModelFieldValue,
 });
-export const zControlNetModelFieldInputTemplate = zFieldInputTemplateBase.extend({
+const zControlNetModelFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zControlNetModelFieldType,
   default: zControlNetModelFieldValue,
 });
-export const zControlNetModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+const zControlNetModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zControlNetModelFieldType,
 });
 export type ControlNetModelFieldType = z.infer<typeof zControlNetModelFieldType>;
@@ -458,23 +451,21 @@ export const isControlNetModelFieldInputInstance = (val: unknown): val is Contro
   zControlNetModelFieldInputInstance.safeParse(val).success;
 export const isControlNetModelFieldInputTemplate = (val: unknown): val is ControlNetModelFieldInputTemplate =>
   zControlNetModelFieldInputTemplate.safeParse(val).success;
-export const isControlNetModelFieldValue = (v: unknown): v is ControlNetModelFieldValue =>
-  zControlNetModelFieldValue.safeParse(v).success;
 // #endregion
 
 // #region IPAdapterModelField
-export const zIPAdapterModelFieldType = zFieldTypeBase.extend({
+const zIPAdapterModelFieldType = zFieldTypeBase.extend({
   name: z.literal('IPAdapterModelField'),
 });
 export const zIPAdapterModelFieldValue = zModelIdentifierWithBase.optional();
-export const zIPAdapterModelFieldInputInstance = zFieldInputInstanceBase.extend({
+const zIPAdapterModelFieldInputInstance = zFieldInputInstanceBase.extend({
   value: zIPAdapterModelFieldValue,
 });
-export const zIPAdapterModelFieldInputTemplate = zFieldInputTemplateBase.extend({
+const zIPAdapterModelFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zIPAdapterModelFieldType,
   default: zIPAdapterModelFieldValue,
 });
-export const zIPAdapterModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+const zIPAdapterModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zIPAdapterModelFieldType,
 });
 export type IPAdapterModelFieldType = z.infer<typeof zIPAdapterModelFieldType>;
@@ -486,23 +477,21 @@ export const isIPAdapterModelFieldInputInstance = (val: unknown): val is IPAdapt
   zIPAdapterModelFieldInputInstance.safeParse(val).success;
 export const isIPAdapterModelFieldInputTemplate = (val: unknown): val is IPAdapterModelFieldInputTemplate =>
   zIPAdapterModelFieldInputTemplate.safeParse(val).success;
-export const isIPAdapterModelFieldValue = (val: unknown): val is IPAdapterModelFieldValue =>
-  zIPAdapterModelFieldValue.safeParse(val).success;
 // #endregion
 
 // #region T2IAdapterField
-export const zT2IAdapterModelFieldType = zFieldTypeBase.extend({
+const zT2IAdapterModelFieldType = zFieldTypeBase.extend({
   name: z.literal('T2IAdapterModelField'),
 });
 export const zT2IAdapterModelFieldValue = zModelIdentifierWithBase.optional();
-export const zT2IAdapterModelFieldInputInstance = zFieldInputInstanceBase.extend({
+const zT2IAdapterModelFieldInputInstance = zFieldInputInstanceBase.extend({
   value: zT2IAdapterModelFieldValue,
 });
-export const zT2IAdapterModelFieldInputTemplate = zFieldInputTemplateBase.extend({
+const zT2IAdapterModelFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zT2IAdapterModelFieldType,
   default: zT2IAdapterModelFieldValue,
 });
-export const zT2IAdapterModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+const zT2IAdapterModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zT2IAdapterModelFieldType,
 });
 export type T2IAdapterModelFieldType = z.infer<typeof zT2IAdapterModelFieldType>;
@@ -517,18 +506,18 @@ export const isT2IAdapterModelFieldInputTemplate = (val: unknown): val is T2IAda
 // #endregion
 
 // #region SchedulerField
-export const zSchedulerFieldType = zFieldTypeBase.extend({
+const zSchedulerFieldType = zFieldTypeBase.extend({
   name: z.literal('SchedulerField'),
 });
 export const zSchedulerFieldValue = zSchedulerField.optional();
-export const zSchedulerFieldInputInstance = zFieldInputInstanceBase.extend({
+const zSchedulerFieldInputInstance = zFieldInputInstanceBase.extend({
   value: zSchedulerFieldValue,
 });
-export const zSchedulerFieldInputTemplate = zFieldInputTemplateBase.extend({
+const zSchedulerFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zSchedulerFieldType,
   default: zSchedulerFieldValue,
 });
-export const zSchedulerFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+const zSchedulerFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zSchedulerFieldType,
 });
 export type SchedulerFieldType = z.infer<typeof zSchedulerFieldType>;
@@ -554,19 +543,19 @@ export const isSchedulerFieldInputTemplate = (val: unknown): val is SchedulerFie
  * - Reserved fields like IsIntermediate
  * - Any other field we don't have full-on schemas for
  */
-export const zStatelessFieldType = zFieldTypeBase.extend({
+const zStatelessFieldType = zFieldTypeBase.extend({
   name: z.string().min(1), // stateless --> we accept the field's name as the type
 });
-export const zStatelessFieldValue = z.undefined().catch(undefined); // stateless --> no value, but making this z.never() introduces a lot of extra TS fanagling
-export const zStatelessFieldInputInstance = zFieldInputInstanceBase.extend({
+const zStatelessFieldValue = z.undefined().catch(undefined); // stateless --> no value, but making this z.never() introduces a lot of extra TS fanagling
+const zStatelessFieldInputInstance = zFieldInputInstanceBase.extend({
   value: zStatelessFieldValue,
 });
-export const zStatelessFieldInputTemplate = zFieldInputTemplateBase.extend({
+const zStatelessFieldInputTemplate = zFieldInputTemplateBase.extend({
   type: zStatelessFieldType,
   default: zStatelessFieldValue,
   input: z.literal('connection'), // stateless --> only accepts connection inputs
 });
-export const zStatelessFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+const zStatelessFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zStatelessFieldType,
 });
 
@@ -593,7 +582,7 @@ export type StatelessFieldOutputTemplate = z.infer<typeof zStatelessFieldOutputT
  */
 
 // #region StatefulFieldType & FieldType
-export const zStatefulFieldType = z.union([
+const zStatefulFieldType = z.union([
   zIntegerFieldType,
   zFloatFieldType,
   zStringFieldType,
@@ -616,9 +605,8 @@ export type StatefulFieldType = z.infer<typeof zStatefulFieldType>;
 export const isStatefulFieldType = (val: unknown): val is StatefulFieldType =>
   zStatefulFieldType.safeParse(val).success;
 
-export const zFieldType = z.union([zStatefulFieldType, zStatelessFieldType]);
+const zFieldType = z.union([zStatefulFieldType, zStatelessFieldType]);
 export type FieldType = z.infer<typeof zFieldType>;
-export const isFieldType = (val: unknown): val is FieldType => zFieldType.safeParse(val).success;
 // #endregion
 
 // #region StatefulFieldValue & FieldValue
@@ -642,16 +630,13 @@ export const zStatefulFieldValue = z.union([
   zSchedulerFieldValue,
 ]);
 export type StatefulFieldValue = z.infer<typeof zStatefulFieldValue>;
-export const isStatefulFieldValue = (val: unknown): val is StatefulFieldValue =>
-  zStatefulFieldValue.safeParse(val).success;
 
-export const zFieldValue = z.union([zStatefulFieldValue, zStatelessFieldValue]);
+const zFieldValue = z.union([zStatefulFieldValue, zStatelessFieldValue]);
 export type FieldValue = z.infer<typeof zFieldValue>;
-export const isFieldValue = (val: unknown): val is FieldValue => zFieldValue.safeParse(val).success;
 // #endregion
 
 // #region StatefulFieldInputInstance & FieldInputInstance
-export const zStatefulFieldInputInstance = z.union([
+const zStatefulFieldInputInstance = z.union([
   zIntegerFieldInputInstance,
   zFloatFieldInputInstance,
   zStringFieldInputInstance,
@@ -671,8 +656,6 @@ export const zStatefulFieldInputInstance = z.union([
   zSchedulerFieldInputInstance,
 ]);
 export type StatefulFieldInputInstance = z.infer<typeof zStatefulFieldInputInstance>;
-export const isStatefulFieldInputInstance = (val: unknown): val is StatefulFieldInputInstance =>
-  zStatefulFieldInputInstance.safeParse(val).success;
 
 export const zFieldInputInstance = z.union([zStatefulFieldInputInstance, zStatelessFieldInputInstance]);
 export type FieldInputInstance = z.infer<typeof zFieldInputInstance>;
@@ -681,7 +664,7 @@ export const isFieldInputInstance = (val: unknown): val is FieldInputInstance =>
 // #endregion
 
 // #region StatefulFieldInputTemplate & FieldInputTemplate
-export const zStatefulFieldInputTemplate = z.union([
+const zStatefulFieldInputTemplate = z.union([
   zIntegerFieldInputTemplate,
   zFloatFieldInputTemplate,
   zStringFieldInputTemplate,
@@ -702,8 +685,6 @@ export const zStatefulFieldInputTemplate = z.union([
   zStatelessFieldInputTemplate,
 ]);
 export type StatefulFieldInputTemplate = z.infer<typeof zFieldInputTemplate>;
-export const isStatefulFieldInputTemplate = (val: unknown): val is StatefulFieldInputTemplate =>
-  zStatefulFieldInputTemplate.safeParse(val).success;
 
 export const zFieldInputTemplate = z.union([zStatefulFieldInputTemplate, zStatelessFieldInputTemplate]);
 export type FieldInputTemplate = z.infer<typeof zFieldInputTemplate>;
@@ -712,7 +693,7 @@ export const isFieldInputTemplate = (val: unknown): val is FieldInputTemplate =>
 // #endregion
 
 // #region StatefulFieldOutputTemplate & FieldOutputTemplate
-export const zStatefulFieldOutputTemplate = z.union([
+const zStatefulFieldOutputTemplate = z.union([
   zIntegerFieldOutputTemplate,
   zFloatFieldOutputTemplate,
   zStringFieldOutputTemplate,
@@ -732,11 +713,7 @@ export const zStatefulFieldOutputTemplate = z.union([
   zSchedulerFieldOutputTemplate,
 ]);
 export type StatefulFieldOutputTemplate = z.infer<typeof zStatefulFieldOutputTemplate>;
-export const isStatefulFieldOutputTemplate = (val: unknown): val is StatefulFieldOutputTemplate =>
-  zStatefulFieldOutputTemplate.safeParse(val).success;
 
 export const zFieldOutputTemplate = z.union([zStatefulFieldOutputTemplate, zStatelessFieldOutputTemplate]);
 export type FieldOutputTemplate = z.infer<typeof zFieldOutputTemplate>;
-export const isFieldOutputTemplate = (val: unknown): val is FieldOutputTemplate =>
-  zFieldOutputTemplate.safeParse(val).success;
 // #endregion
diff --git a/invokeai/frontend/web/src/features/nodes/types/invocation.ts b/invokeai/frontend/web/src/features/nodes/types/invocation.ts
index 5ccb19430d..52db5de5ee 100644
--- a/invokeai/frontend/web/src/features/nodes/types/invocation.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/invocation.ts
@@ -6,7 +6,7 @@ import { zFieldInputInstance, zFieldInputTemplate, zFieldOutputTemplate } from '
 import { zSemVer } from './semver';
 
 // #region InvocationTemplate
-export const zInvocationTemplate = z.object({
+const zInvocationTemplate = z.object({
   type: z.string(),
   title: z.string(),
   description: z.string(),
@@ -43,13 +43,13 @@ export const zNotesNodeData = z.object({
   isOpen: z.boolean(),
   notes: z.string(),
 });
-export const zCurrentImageNodeData = z.object({
+const zCurrentImageNodeData = z.object({
   id: z.string().trim().min(1),
   type: z.literal('current_image'),
   label: z.string(),
   isOpen: z.boolean(),
 });
-export const zAnyNodeData = z.union([zInvocationNodeData, zNotesNodeData, zCurrentImageNodeData]);
+const zAnyNodeData = z.union([zInvocationNodeData, zNotesNodeData, zCurrentImageNodeData]);
 
 export type NotesNodeData = z.infer<typeof zNotesNodeData>;
 export type InvocationNodeData = z.infer<typeof zInvocationNodeData>;
@@ -64,15 +64,13 @@ export type AnyNode = Node<AnyNodeData>;
 export const isInvocationNode = (node?: AnyNode | null): node is InvocationNode =>
   Boolean(node && node.type === 'invocation');
 export const isNotesNode = (node?: AnyNode | null): node is NotesNode => Boolean(node && node.type === 'notes');
-export const isCurrentImageNode = (node?: AnyNode | null): node is CurrentImageNode =>
-  Boolean(node && node.type === 'current_image');
 export const isInvocationNodeData = (node?: AnyNodeData | null): node is InvocationNodeData =>
   Boolean(node && !['notes', 'current_image'].includes(node.type)); // node.type may be 'notes', 'current_image', or any invocation type
 // #endregion
 
 // #region NodeExecutionState
 export const zNodeStatus = z.enum(['PENDING', 'IN_PROGRESS', 'COMPLETED', 'FAILED']);
-export const zNodeExecutionState = z.object({
+const zNodeExecutionState = z.object({
   nodeId: z.string().trim().min(1),
   status: zNodeStatus,
   progress: z.number().nullable(),
@@ -85,7 +83,7 @@ export type NodeStatus = z.infer<typeof zNodeStatus>;
 // #endregion
 
 // #region Edges
-export const zInvocationNodeEdgeExtra = z.object({
+const zInvocationNodeEdgeExtra = z.object({
   type: z.union([z.literal('default'), z.literal('collapsed')]),
 });
 export type InvocationNodeEdgeExtra = z.infer<typeof zInvocationNodeEdgeExtra>;
diff --git a/invokeai/frontend/web/src/features/nodes/types/workflow.ts b/invokeai/frontend/web/src/features/nodes/types/workflow.ts
index adad7c0f21..6bc6be8cd7 100644
--- a/invokeai/frontend/web/src/features/nodes/types/workflow.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/workflow.ts
@@ -4,7 +4,7 @@ import { zFieldIdentifier } from './field';
 import { zInvocationNodeData, zNotesNodeData } from './invocation';
 
 // #region Workflow misc
-export const zXYPosition = z
+const zXYPosition = z
   .object({
     x: z.number(),
     y: z.number(),
@@ -12,27 +12,27 @@ export const zXYPosition = z
   .default({ x: 0, y: 0 });
 export type XYPosition = z.infer<typeof zXYPosition>;
 
-export const zDimension = z.number().gt(0).nullish();
+const zDimension = z.number().gt(0).nullish();
 export type Dimension = z.infer<typeof zDimension>;
 
-export const zWorkflowCategory = z.enum(['user', 'default', 'project']);
+const zWorkflowCategory = z.enum(['user', 'default', 'project']);
 export type WorkflowCategory = z.infer<typeof zWorkflowCategory>;
 // #endregion
 
 // #region Workflow Nodes
-export const zWorkflowInvocationNode = z.object({
+const zWorkflowInvocationNode = z.object({
   id: z.string().trim().min(1),
   type: z.literal('invocation'),
   data: zInvocationNodeData,
   position: zXYPosition,
 });
-export const zWorkflowNotesNode = z.object({
+const zWorkflowNotesNode = z.object({
   id: z.string().trim().min(1),
   type: z.literal('notes'),
   data: zNotesNodeData,
   position: zXYPosition,
 });
-export const zWorkflowNode = z.union([zWorkflowInvocationNode, zWorkflowNotesNode]);
+const zWorkflowNode = z.union([zWorkflowInvocationNode, zWorkflowNotesNode]);
 
 export type WorkflowInvocationNode = z.infer<typeof zWorkflowInvocationNode>;
 export type WorkflowNotesNode = z.infer<typeof zWorkflowNotesNode>;
@@ -43,20 +43,20 @@ export const isWorkflowInvocationNode = (val: unknown): val is WorkflowInvocatio
 // #endregion
 
 // #region Workflow Edges
-export const zWorkflowEdgeBase = z.object({
+const zWorkflowEdgeBase = z.object({
   id: z.string().trim().min(1),
   source: z.string().trim().min(1),
   target: z.string().trim().min(1),
 });
-export const zWorkflowEdgeDefault = zWorkflowEdgeBase.extend({
+const zWorkflowEdgeDefault = zWorkflowEdgeBase.extend({
   type: z.literal('default'),
   sourceHandle: z.string().trim().min(1),
   targetHandle: z.string().trim().min(1),
 });
-export const zWorkflowEdgeCollapsed = zWorkflowEdgeBase.extend({
+const zWorkflowEdgeCollapsed = zWorkflowEdgeBase.extend({
   type: z.literal('collapsed'),
 });
-export const zWorkflowEdge = z.union([zWorkflowEdgeDefault, zWorkflowEdgeCollapsed]);
+const zWorkflowEdge = z.union([zWorkflowEdgeDefault, zWorkflowEdgeCollapsed]);
 
 export type WorkflowEdgeDefault = z.infer<typeof zWorkflowEdgeDefault>;
 export type WorkflowEdgeCollapsed = z.infer<typeof zWorkflowEdgeCollapsed>;
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/buildNodesGraph.ts b/invokeai/frontend/web/src/features/nodes/util/graph/buildNodesGraph.ts
index 582aa6b217..130da8bf15 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/buildNodesGraph.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/buildNodesGraph.ts
@@ -1,19 +1,10 @@
 import type { NodesState } from 'features/nodes/store/types';
-import type { FieldInputInstance } from 'features/nodes/types/field';
 import { isInvocationNode } from 'features/nodes/types/invocation';
 import { omit, reduce } from 'lodash-es';
 import type { Graph } from 'services/api/types';
 import type { AnyInvocation } from 'services/events/types';
 import { v4 as uuidv4 } from 'uuid';
 
-/**
- * We need to do special handling for some fields
- */
-export const parseFieldValue = (field: FieldInputInstance) => {
-  // Currently, no special handling is needed.
-  return field.value;
-};
-
 /**
  * Builds a graph from the node editor state.
  */
@@ -31,8 +22,7 @@ export const buildNodesGraph = (nodesState: NodesState): Graph => {
     const transformedInputs = reduce(
       inputs,
       (inputsAccumulator, input, name) => {
-        const parsedValue = parseFieldValue(input);
-        inputsAccumulator[name] = parsedValue;
+        inputsAccumulator[name] = input.value;
 
         return inputsAccumulator;
       },
diff --git a/invokeai/frontend/web/src/features/nodes/util/graph/constants.ts b/invokeai/frontend/web/src/features/nodes/util/graph/constants.ts
index 767bf25df0..984f8ae7d6 100644
--- a/invokeai/frontend/web/src/features/nodes/util/graph/constants.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/graph/constants.ts
@@ -13,58 +13,30 @@ export const NSFW_CHECKER = 'nsfw_checker';
 export const WATERMARKER = 'invisible_watermark';
 export const NOISE = 'noise';
 export const NOISE_HRF = 'noise_hrf';
-export const RANDOM_INT = 'rand_int';
-export const RANGE_OF_SIZE = 'range_of_size';
-export const ITERATE = 'iterate';
 export const MAIN_MODEL_LOADER = 'main_model_loader';
 export const VAE_LOADER = 'vae_loader';
 export const LORA_LOADER = 'lora_loader';
 export const CLIP_SKIP = 'clip_skip';
 export const IMAGE_TO_LATENTS = 'image_to_latents';
-export const LATENTS_TO_LATENTS = 'latents_to_latents';
 export const RESIZE = 'resize_image';
 export const IMG2IMG_RESIZE = 'img2img_resize';
 export const CANVAS_OUTPUT = 'canvas_output';
 export const INPAINT_IMAGE = 'inpaint_image';
-export const SCALED_INPAINT_IMAGE = 'scaled_inpaint_image';
 export const INPAINT_IMAGE_RESIZE_UP = 'inpaint_image_resize_up';
 export const INPAINT_IMAGE_RESIZE_DOWN = 'inpaint_image_resize_down';
 export const INPAINT_INFILL = 'inpaint_infill';
 export const INPAINT_INFILL_RESIZE_DOWN = 'inpaint_infill_resize_down';
-export const INPAINT_FINAL_IMAGE = 'inpaint_final_image';
 export const INPAINT_CREATE_MASK = 'inpaint_create_mask';
-export const INPAINT_MASK = 'inpaint_mask';
-export const CANVAS_COHERENCE_DENOISE_LATENTS = 'canvas_coherence_denoise_latents';
 export const CANVAS_COHERENCE_NOISE = 'canvas_coherence_noise';
-export const CANVAS_COHERENCE_NOISE_INCREMENT = 'canvas_coherence_noise_increment';
-export const CANVAS_COHERENCE_MASK_EDGE = 'canvas_coherence_mask_edge';
-export const CANVAS_COHERENCE_INPAINT_CREATE_MASK = 'canvas_coherence_inpaint_create_mask';
 export const MASK_FROM_ALPHA = 'tomask';
-export const MASK_EDGE = 'mask_edge';
-export const MASK_BLUR = 'mask_blur';
 export const MASK_COMBINE = 'mask_combine';
 export const MASK_RESIZE_UP = 'mask_resize_up';
 export const MASK_RESIZE_DOWN = 'mask_resize_down';
-export const COLOR_CORRECT = 'color_correct';
-export const PASTE_IMAGE = 'img_paste';
 export const CONTROL_NET_COLLECT = 'control_net_collect';
 export const IP_ADAPTER_COLLECT = 'ip_adapter_collect';
 export const T2I_ADAPTER_COLLECT = 't2i_adapter_collect';
-export const IP_ADAPTER = 'ip_adapter';
-export const DYNAMIC_PROMPT = 'dynamic_prompt';
-export const IMAGE_COLLECTION = 'image_collection';
-export const IMAGE_COLLECTION_ITERATE = 'image_collection_iterate';
 export const METADATA = 'core_metadata';
-export const BATCH_METADATA = 'batch_metadata';
-export const BATCH_METADATA_COLLECT = 'batch_metadata_collect';
-export const BATCH_SEED = 'batch_seed';
-export const BATCH_PROMPT = 'batch_prompt';
-export const BATCH_STYLE_PROMPT = 'batch_style_prompt';
-export const METADATA_COLLECT = 'metadata_collect';
-export const MERGE_METADATA = 'merge_metadata';
 export const ESRGAN = 'esrgan';
-export const DIVIDE = 'divide';
-export const SCALE = 'scale_image';
 export const SDXL_MODEL_LOADER = 'sdxl_model_loader';
 export const SDXL_DENOISE_LATENTS = 'sdxl_denoise_latents';
 export const SDXL_REFINER_MODEL_LOADER = 'sdxl_refiner_model_loader';
@@ -75,32 +47,6 @@ export const SDXL_REFINER_INPAINT_CREATE_MASK = 'refiner_inpaint_create_mask';
 export const SEAMLESS = 'seamless';
 export const SDXL_REFINER_SEAMLESS = 'refiner_seamless';
 
-// these image-outputting nodes are from the linear UI and we should not handle the gallery logic on them
-// instead, we wait for LINEAR_UI_OUTPUT node, and handle it like any other image-outputting node
-export const nodeIDDenyList = [
-  CANVAS_OUTPUT,
-  LATENTS_TO_IMAGE,
-  LATENTS_TO_IMAGE_HRF_HR,
-  NSFW_CHECKER,
-  WATERMARKER,
-  ESRGAN,
-  ESRGAN_HRF,
-  RESIZE_HRF,
-  LATENTS_TO_IMAGE_HRF_LR,
-  IMG2IMG_RESIZE,
-  INPAINT_IMAGE,
-  SCALED_INPAINT_IMAGE,
-  INPAINT_IMAGE_RESIZE_UP,
-  INPAINT_IMAGE_RESIZE_DOWN,
-  INPAINT_INFILL,
-  INPAINT_INFILL_RESIZE_DOWN,
-  INPAINT_FINAL_IMAGE,
-  INPAINT_CREATE_MASK,
-  INPAINT_MASK,
-  PASTE_IMAGE,
-  SCALE,
-];
-
 // friendly graph ids
 export const TEXT_TO_IMAGE_GRAPH = 'text_to_image_graph';
 export const IMAGE_TO_IMAGE_GRAPH = 'image_to_image_graph';
diff --git a/invokeai/frontend/web/src/features/nodes/util/node/nodeUpdate.ts b/invokeai/frontend/web/src/features/nodes/util/node/nodeUpdate.ts
index 5ece51d0f3..f720bdd188 100644
--- a/invokeai/frontend/web/src/features/nodes/util/node/nodeUpdate.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/node/nodeUpdate.ts
@@ -11,13 +11,14 @@ export const getNeedsUpdate = (node: InvocationNode, template: InvocationTemplat
     return true;
   }
   return node.data.version !== template.version;
-}; /**
+};
+
+/**
  * Checks if a node may be updated by comparing its major version with the template's major version.
  * @param node The node to check.
  * @param template The invocation template to check against.
  */
-
-export const getMayUpdateNode = (node: InvocationNode, template: InvocationTemplate): boolean => {
+const getMayUpdateNode = (node: InvocationNode, template: InvocationTemplate): boolean => {
   const needsUpdate = getNeedsUpdate(node, template);
   if (!needsUpdate || node.data.type !== template.type) {
     return false;
@@ -25,7 +26,9 @@ export const getMayUpdateNode = (node: InvocationNode, template: InvocationTempl
   const templateMajor = zParsedSemver.parse(template.version).major;
 
   return satisfies(node.data.version, `^${templateMajor}`);
-}; /**
+};
+
+/**
  * Updates a node to the latest version of its template:
  * - Create a new node data object with the latest version of the template.
  * - Recursively merge new node data object into the node to be updated.
@@ -34,7 +37,6 @@ export const getMayUpdateNode = (node: InvocationNode, template: InvocationTempl
  * @param template The invocation template to update to.
  * @throws {NodeUpdateError} If the node is not an invocation node.
  */
-
 export const updateNode = (node: InvocationNode, template: InvocationTemplate): InvocationNode => {
   const mayUpdate = getMayUpdateNode(node, template);
 
diff --git a/invokeai/frontend/web/src/features/parameters/components/Canvas/Compositing/MaskAdjustment/ParamMaskBlurMethod.tsx b/invokeai/frontend/web/src/features/parameters/components/Canvas/Compositing/MaskAdjustment/ParamMaskBlurMethod.tsx
deleted file mode 100644
index 95b402a1c8..0000000000
--- a/invokeai/frontend/web/src/features/parameters/components/Canvas/Compositing/MaskAdjustment/ParamMaskBlurMethod.tsx
+++ /dev/null
@@ -1,45 +0,0 @@
-import type { ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
-import { Combobox, FormControl, FormLabel } from '@invoke-ai/ui-library';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
-import { setMaskBlurMethod } from 'features/parameters/store/generationSlice';
-import { isParameterMaskBlurMethod } from 'features/parameters/types/parameterSchemas';
-import { memo, useCallback, useMemo } from 'react';
-import { useTranslation } from 'react-i18next';
-
-const ParamMaskBlurMethod = () => {
-  const maskBlurMethod = useAppSelector((s) => s.generation.maskBlurMethod);
-  const dispatch = useAppDispatch();
-  const { t } = useTranslation();
-
-  const options: ComboboxOption[] = useMemo(
-    () => [
-      { label: t('parameters.boxBlur'), value: 'box' },
-      { label: t('parameters.gaussianBlur'), value: 'gaussian' },
-    ],
-    [t]
-  );
-
-  const onChange = useCallback<ComboboxOnChange>(
-    (v) => {
-      if (!isParameterMaskBlurMethod(v?.value)) {
-        return;
-      }
-      dispatch(setMaskBlurMethod(v.value));
-    },
-    [dispatch]
-  );
-
-  const value = useMemo(() => options.find((o) => o.value === maskBlurMethod), [maskBlurMethod, options]);
-
-  return (
-    <FormControl>
-      <InformationalPopover feature="compositingBlurMethod">
-        <FormLabel>{t('parameters.maskBlurMethod')}</FormLabel>
-      </InformationalPopover>
-      <Combobox value={value} onChange={onChange} options={options} />
-    </FormControl>
-  );
-};
-
-export default memo(ParamMaskBlurMethod);
diff --git a/invokeai/frontend/web/src/features/parameters/components/Canvas/InfillAndScaling/ParamScaleBeforeProcessing.tsx b/invokeai/frontend/web/src/features/parameters/components/Canvas/InfillAndScaling/ParamScaleBeforeProcessing.tsx
index ade66c2b57..759f541905 100644
--- a/invokeai/frontend/web/src/features/parameters/components/Canvas/InfillAndScaling/ParamScaleBeforeProcessing.tsx
+++ b/invokeai/frontend/web/src/features/parameters/components/Canvas/InfillAndScaling/ParamScaleBeforeProcessing.tsx
@@ -8,7 +8,7 @@ import { selectOptimalDimension } from 'features/parameters/store/generationSlic
 import { memo, useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
 
-export const OPTIONS: ComboboxOption[] = [
+const OPTIONS: ComboboxOption[] = [
   { label: 'None', value: 'none' },
   { label: 'Auto', value: 'auto' },
   { label: 'Manual', value: 'manual' },
diff --git a/invokeai/frontend/web/src/features/parameters/components/ImageSize/constants.ts b/invokeai/frontend/web/src/features/parameters/components/ImageSize/constants.ts
index 133ca1e1ca..b8c46005e6 100644
--- a/invokeai/frontend/web/src/features/parameters/components/ImageSize/constants.ts
+++ b/invokeai/frontend/web/src/features/parameters/components/ImageSize/constants.ts
@@ -5,8 +5,8 @@ import type { AspectRatioID, AspectRatioState } from './types';
 // When the aspect ratio is between these two values, we show the icon (experimentally determined)
 export const ICON_LOW_CUTOFF = 0.23;
 export const ICON_HIGH_CUTOFF = 1 / ICON_LOW_CUTOFF;
-export const ICON_SIZE_PX = 64;
-export const ICON_PADDING_PX = 16;
+const ICON_SIZE_PX = 64;
+const ICON_PADDING_PX = 16;
 export const BOX_SIZE_CSS_CALC = `min(${ICON_SIZE_PX}px, calc(100% - ${ICON_PADDING_PX}px))`;
 export const MOTION_ICON_INITIAL = {
   opacity: 0,
diff --git a/invokeai/frontend/web/src/features/parameters/components/ImageSize/hooks.ts b/invokeai/frontend/web/src/features/parameters/components/ImageSize/hooks.ts
deleted file mode 100644
index bc6f1019c6..0000000000
--- a/invokeai/frontend/web/src/features/parameters/components/ImageSize/hooks.ts
+++ /dev/null
@@ -1,45 +0,0 @@
-import { useMemo } from 'react';
-
-import { ICON_HIGH_CUTOFF, ICON_LOW_CUTOFF } from './constants';
-
-type Dimensions = {
-  width: number;
-  height: number;
-};
-
-type UseAspectRatioPreviewStateArg = {
-  width: number;
-  height: number;
-  containerSize?: Dimensions;
-};
-type UseAspectRatioPreviewState = (arg: UseAspectRatioPreviewStateArg) => Dimensions & { shouldShowIcon: boolean };
-
-export const useAspectRatioPreviewState: UseAspectRatioPreviewState = ({
-  width: _width,
-  height: _height,
-  containerSize,
-}) => {
-  const dimensions = useMemo(() => {
-    if (!containerSize) {
-      return { width: 0, height: 0, shouldShowIcon: false };
-    }
-
-    const aspectRatio = _width / _height;
-    let width = _width;
-    let height = _height;
-
-    if (_width > _height) {
-      width = containerSize.width;
-      height = width / aspectRatio;
-    } else {
-      height = containerSize.height;
-      width = height * aspectRatio;
-    }
-
-    const shouldShowIcon = aspectRatio < ICON_HIGH_CUTOFF && aspectRatio > ICON_LOW_CUTOFF;
-
-    return { width, height, shouldShowIcon };
-  }, [_height, _width, containerSize]);
-
-  return dimensions;
-};
diff --git a/invokeai/frontend/web/src/features/parameters/components/ImageSize/types.ts b/invokeai/frontend/web/src/features/parameters/components/ImageSize/types.ts
index 73322187ff..f219eb9a1a 100644
--- a/invokeai/frontend/web/src/features/parameters/components/ImageSize/types.ts
+++ b/invokeai/frontend/web/src/features/parameters/components/ImageSize/types.ts
@@ -1,6 +1,6 @@
 import { z } from 'zod';
 
-export const zAspectRatioID = z.enum(['Free', '16:9', '3:2', '4:3', '1:1', '3:4', '2:3', '9:16']);
+const zAspectRatioID = z.enum(['Free', '16:9', '3:2', '4:3', '1:1', '3:4', '2:3', '9:16']);
 export type AspectRatioID = z.infer<typeof zAspectRatioID>;
 export const isAspectRatioID = (v: string): v is AspectRatioID => zAspectRatioID.safeParse(v).success;
 
diff --git a/invokeai/frontend/web/src/features/parameters/hooks/useCoreParametersCollapseLabel.ts b/invokeai/frontend/web/src/features/parameters/hooks/useCoreParametersCollapseLabel.ts
deleted file mode 100644
index 794f841451..0000000000
--- a/invokeai/frontend/web/src/features/parameters/hooks/useCoreParametersCollapseLabel.ts
+++ /dev/null
@@ -1,29 +0,0 @@
-import { useAppSelector } from 'app/store/storeHooks';
-import { useMemo } from 'react';
-import { useTranslation } from 'react-i18next';
-
-export const useCoreParametersCollapseLabel = () => {
-  const { t } = useTranslation();
-  const shouldRandomizeSeed = useAppSelector((s) => s.generation.shouldRandomizeSeed);
-  const iterations = useAppSelector((s) => s.generation.iterations);
-
-  const iterationsLabel = useMemo(() => {
-    if (iterations === 1) {
-      return t('parameters.iterationsWithCount_one', { count: 1 });
-    } else {
-      return t('parameters.iterationsWithCount_other', { count: iterations });
-    }
-  }, [iterations, t]);
-
-  const seedLabel = useMemo(() => {
-    if (shouldRandomizeSeed) {
-      return t('parameters.randomSeed');
-    } else {
-      return t('parameters.manualSeed');
-    }
-  }, [shouldRandomizeSeed, t]);
-
-  const iterationsAndSeedLabel = useMemo(() => [iterationsLabel, seedLabel].join(', '), [iterationsLabel, seedLabel]);
-
-  return { iterationsAndSeedLabel, iterationsLabel, seedLabel };
-};
diff --git a/invokeai/frontend/web/src/features/parameters/store/generationSlice.ts b/invokeai/frontend/web/src/features/parameters/store/generationSlice.ts
index 4041490345..061a291bad 100644
--- a/invokeai/frontend/web/src/features/parameters/store/generationSlice.ts
+++ b/invokeai/frontend/web/src/features/parameters/store/generationSlice.ts
@@ -11,7 +11,6 @@ import type {
   ParameterCanvasCoherenceMode,
   ParameterCFGRescaleMultiplier,
   ParameterCFGScale,
-  ParameterMaskBlurMethod,
   ParameterModel,
   ParameterPrecision,
   ParameterScheduler,
@@ -25,7 +24,7 @@ import type { ImageDTO } from 'services/api/types';
 
 import type { GenerationState } from './types';
 
-export const initialGenerationState: GenerationState = {
+const initialGenerationState: GenerationState = {
   _version: 1,
   cfgScale: 7.5,
   cfgRescaleMultiplier: 0,
@@ -100,27 +99,12 @@ export const generationSlice = createSlice({
     setShouldFitToWidthHeight: (state, action: PayloadAction<boolean>) => {
       state.shouldFitToWidthHeight = action.payload;
     },
-    resetSeed: (state) => {
-      state.seed = -1;
-    },
-    resetParametersState: (state) => {
-      return {
-        ...state,
-        ...initialGenerationState,
-      };
-    },
     setShouldRandomizeSeed: (state, action: PayloadAction<boolean>) => {
       state.shouldRandomizeSeed = action.payload;
     },
     clearInitialImage: (state) => {
       state.initialImage = undefined;
     },
-    setMaskBlur: (state, action: PayloadAction<number>) => {
-      state.maskBlur = action.payload;
-    },
-    setMaskBlurMethod: (state, action: PayloadAction<ParameterMaskBlurMethod>) => {
-      state.maskBlurMethod = action.payload;
-    },
     setCanvasCoherenceMode: (state, action: PayloadAction<ParameterCanvasCoherenceMode>) => {
       state.canvasCoherenceMode = action.payload;
     },
@@ -261,8 +245,6 @@ export const generationSlice = createSlice({
 
 export const {
   clearInitialImage,
-  resetParametersState,
-  resetSeed,
   setCfgScale,
   setCfgRescaleMultiplier,
   setImg2imgStrength,
@@ -271,8 +253,6 @@ export const {
   setPositivePrompt,
   setNegativePrompt,
   setScheduler,
-  setMaskBlur,
-  setMaskBlurMethod,
   setCanvasCoherenceMode,
   setCanvasCoherenceEdgeSize,
   setCanvasCoherenceMinDenoise,
@@ -302,7 +282,7 @@ export const { selectOptimalDimension } = generationSlice.selectors;
 export const selectGenerationSlice = (state: RootState) => state.generation;
 
 /* eslint-disable-next-line @typescript-eslint/no-explicit-any */
-export const migrateGenerationState = (state: any): GenerationState => {
+const migrateGenerationState = (state: any): GenerationState => {
   if (!('_version' in state)) {
     state._version = 1;
     state.aspectRatio = initialAspectRatioState;
diff --git a/invokeai/frontend/web/src/features/queue/hooks/useIsQueueEmpty.ts b/invokeai/frontend/web/src/features/queue/hooks/useIsQueueEmpty.ts
deleted file mode 100644
index c0a32c1eb3..0000000000
--- a/invokeai/frontend/web/src/features/queue/hooks/useIsQueueEmpty.ts
+++ /dev/null
@@ -1,15 +0,0 @@
-import { useGetQueueStatusQuery } from 'services/api/endpoints/queue';
-
-export const useIsQueueEmpty = () => {
-  const { isEmpty } = useGetQueueStatusQuery(undefined, {
-    selectFromResult: ({ data }) => {
-      if (!data) {
-        return { isEmpty: true };
-      }
-      return {
-        isEmpty: data.queue.in_progress === 0 && data.queue.pending === 0,
-      };
-    },
-  });
-  return isEmpty;
-};
diff --git a/invokeai/frontend/web/src/features/system/components/SettingsModal/StyledFlex.tsx b/invokeai/frontend/web/src/features/system/components/SettingsModal/StyledFlex.tsx
deleted file mode 100644
index 2b2d548323..0000000000
--- a/invokeai/frontend/web/src/features/system/components/SettingsModal/StyledFlex.tsx
+++ /dev/null
@@ -1,13 +0,0 @@
-import { Flex } from '@invoke-ai/ui-library';
-import type { PropsWithChildren } from 'react';
-import { memo } from 'react';
-
-const StyledFlex = (props: PropsWithChildren) => {
-  return (
-    <Flex flexDirection="column" gap={2} p={4} borderRadius="base" bg="base.900">
-      {props.children}
-    </Flex>
-  );
-};
-
-export default memo(StyledFlex);

From b661d93bd89673e7bfec0bd20a376a8e0b93a1dc Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 27 Feb 2024 17:46:13 +1100
Subject: [PATCH 345/411] tidy(ui): clean up unused code 4

variables, types and schemas
---
 invokeai/frontend/web/knip.ts                 | 11 +--
 .../store/enhancers/reduxRemember/errors.ts   |  2 +-
 .../middleware/listenerMiddleware/index.ts    |  6 +-
 invokeai/frontend/web/src/app/store/store.ts  |  1 -
 .../common/hooks/useSingleAndDoubleClick.ts   |  2 +-
 invokeai/frontend/web/src/common/types.ts     |  4 +-
 .../web/src/common/util/generateSeeds.ts      |  2 +-
 .../src/features/canvas/store/canvasTypes.ts  | 13 +---
 .../ControlAdapterProcessorComponent.tsx      |  2 +-
 .../store/modelManagerV2Slice.ts              |  4 +-
 .../parameters/store/postprocessingSlice.ts   |  6 +-
 .../parameters/types/parameterSchemas.ts      | 73 +++++++------------
 .../src/features/queue/store/queueSlice.ts    | 27 +------
 .../web/src/features/sdxl/store/sdxlSlice.ts  |  4 +-
 .../system/components/StickyScrollable.tsx    |  8 +-
 .../src/features/system/store/configSlice.ts  |  2 +-
 .../src/features/system/store/systemSlice.ts  |  4 +-
 .../web/src/features/system/store/types.ts    | 10 +--
 .../src/features/ui/components/InvokeTabs.tsx |  4 +-
 .../web/src/features/ui/store/uiSlice.ts      |  4 +-
 .../web/src/services/api/endpoints/boards.ts  | 29 +-------
 .../web/src/services/api/endpoints/images.ts  | 38 ----------
 .../web/src/services/api/endpoints/models.ts  | 25 +++----
 .../web/src/services/api/endpoints/queue.ts   |  2 -
 .../src/services/api/endpoints/utilities.ts   |  2 -
 .../frontend/web/src/services/api/types.ts    |  4 -
 26 files changed, 72 insertions(+), 217 deletions(-)

diff --git a/invokeai/frontend/web/knip.ts b/invokeai/frontend/web/knip.ts
index 0f7c8c2354..a47edbf6b4 100644
--- a/invokeai/frontend/web/knip.ts
+++ b/invokeai/frontend/web/knip.ts
@@ -4,16 +4,9 @@ const config: KnipConfig = {
   ignore: [
     // This file is only used during debugging
     'src/app/store/middleware/debugLoggerMiddleware.ts',
-    // These are old schemas, used in migrations. Needs cleanup.
-    'src/features/nodes/types/v2/**/*',
-    'src/features/nodes/types/v1/**/*',
-    // We don't want to check the public folder - contains images and translations
-    'public/**/*',
   ],
-  compilers: {
-    //
-    svg: () => '',
-  },
+  ignoreDependencies: ['@storybook/addon-docs', '@storybook/blocks', '@storybook/test', 'public/.*'],
+  ignoreBinaries: ['only-allow'],
 };
 
 export default config;
diff --git a/invokeai/frontend/web/src/app/store/enhancers/reduxRemember/errors.ts b/invokeai/frontend/web/src/app/store/enhancers/reduxRemember/errors.ts
index 0ce113fc39..9704c49cf2 100644
--- a/invokeai/frontend/web/src/app/store/enhancers/reduxRemember/errors.ts
+++ b/invokeai/frontend/web/src/app/store/enhancers/reduxRemember/errors.ts
@@ -3,7 +3,7 @@ import { parseify } from 'common/util/serialize';
 import { PersistError, RehydrateError } from 'redux-remember';
 import { serializeError } from 'serialize-error';
 
-export type StorageErrorArgs = {
+type StorageErrorArgs = {
   key: string;
   /* eslint-disable-next-line @typescript-eslint/no-explicit-any */ // any is correct
   value?: any;
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts
index 1c93140c03..bf1cafc866 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts
@@ -1,4 +1,4 @@
-import type { ListenerEffect, TypedStartListening, UnknownAction } from '@reduxjs/toolkit';
+import type { TypedStartListening } from '@reduxjs/toolkit';
 import { createListenerMiddleware } from '@reduxjs/toolkit';
 import { addBulkDownloadListeners } from 'app/store/middleware/listenerMiddleware/listeners/bulkDownload';
 import { addGalleryImageClickedListener } from 'app/store/middleware/listenerMiddleware/listeners/galleryImageClicked';
@@ -70,12 +70,10 @@ import { addWorkflowLoadRequestedListener } from './listeners/workflowLoadReques
 
 export const listenerMiddleware = createListenerMiddleware();
 
-export type AppStartListening = TypedStartListening<RootState, AppDispatch>;
+type AppStartListening = TypedStartListening<RootState, AppDispatch>;
 
 export const startAppListening = listenerMiddleware.startListening as AppStartListening;
 
-export type AppListenerEffect = ListenerEffect<UnknownAction, RootState, AppDispatch>;
-
 /**
  * The RTK listener middleware is a lightweight alternative sagas/observables.
  *
diff --git a/invokeai/frontend/web/src/app/store/store.ts b/invokeai/frontend/web/src/app/store/store.ts
index 19670aa29f..b538a3eaeb 100644
--- a/invokeai/frontend/web/src/app/store/store.ts
+++ b/invokeai/frontend/web/src/app/store/store.ts
@@ -185,7 +185,6 @@ export const createStore = (uniqueStoreKey?: string, persist = true) =>
     },
   });
 
-export type AppGetState = ReturnType<ReturnType<typeof createStore>['getState']>;
 export type RootState = ReturnType<ReturnType<typeof createStore>['getState']>;
 // eslint-disable-next-line @typescript-eslint/no-explicit-any
 export type AppThunkDispatch = ThunkDispatch<RootState, any, UnknownAction>;
diff --git a/invokeai/frontend/web/src/common/hooks/useSingleAndDoubleClick.ts b/invokeai/frontend/web/src/common/hooks/useSingleAndDoubleClick.ts
index 38594369d3..7a02ae54ec 100644
--- a/invokeai/frontend/web/src/common/hooks/useSingleAndDoubleClick.ts
+++ b/invokeai/frontend/web/src/common/hooks/useSingleAndDoubleClick.ts
@@ -1,7 +1,7 @@
 // https://stackoverflow.com/a/73731908
 import { useCallback, useEffect, useState } from 'react';
 
-export type UseSingleAndDoubleClickOptions = {
+type UseSingleAndDoubleClickOptions = {
   onSingleClick: () => void;
   onDoubleClick: () => void;
   latency?: number;
diff --git a/invokeai/frontend/web/src/common/types.ts b/invokeai/frontend/web/src/common/types.ts
index 29a411788d..f3037dcc2b 100644
--- a/invokeai/frontend/web/src/common/types.ts
+++ b/invokeai/frontend/web/src/common/types.ts
@@ -1,7 +1,5 @@
-export type JSONValue = string | number | boolean | null | JSONValue[] | { [key: string]: JSONValue };
+type JSONValue = string | number | boolean | null | JSONValue[] | { [key: string]: JSONValue };
 
 export interface JSONObject {
   [k: string]: JSONValue;
 }
-
-export interface JSONArray extends Array<JSONValue> {}
diff --git a/invokeai/frontend/web/src/common/util/generateSeeds.ts b/invokeai/frontend/web/src/common/util/generateSeeds.ts
index 450068cae8..c79685feda 100644
--- a/invokeai/frontend/web/src/common/util/generateSeeds.ts
+++ b/invokeai/frontend/web/src/common/util/generateSeeds.ts
@@ -1,7 +1,7 @@
 import { NUMPY_RAND_MAX, NUMPY_RAND_MIN } from 'app/constants';
 import { random } from 'lodash-es';
 
-export type GenerateSeedsArg = {
+type GenerateSeedsArg = {
   count: number;
   start?: number;
   min?: number;
diff --git a/invokeai/frontend/web/src/features/canvas/store/canvasTypes.ts b/invokeai/frontend/web/src/features/canvas/store/canvasTypes.ts
index 14248cd750..82793bffd4 100644
--- a/invokeai/frontend/web/src/features/canvas/store/canvasTypes.ts
+++ b/invokeai/frontend/web/src/features/canvas/store/canvasTypes.ts
@@ -15,7 +15,7 @@ export type BoundingBoxScaleMethod = z.infer<typeof zBoundingBoxScaleMethod>;
 export const isBoundingBoxScaleMethod = (v: unknown): v is BoundingBoxScaleMethod =>
   zBoundingBoxScaleMethod.safeParse(v).success;
 
-export type CanvasDrawingTool = 'brush' | 'eraser';
+type CanvasDrawingTool = 'brush' | 'eraser';
 
 export type CanvasTool = CanvasDrawingTool | 'move' | 'colorPicker';
 
@@ -53,7 +53,7 @@ export type CanvasBaseLine = {
   clip?: IRect;
 };
 
-export type CanvasFillRect = {
+type CanvasFillRect = {
   kind: 'fillRect';
   layer: 'base';
   x: number;
@@ -63,7 +63,7 @@ export type CanvasFillRect = {
   color: RgbaColor;
 };
 
-export type CanvasEraseRect = {
+type CanvasEraseRect = {
   kind: 'eraseRect';
   layer: 'base';
   x: number;
@@ -72,7 +72,7 @@ export type CanvasEraseRect = {
   height: number;
 };
 
-export type CanvasObject = CanvasImage | CanvasBaseLine | CanvasMaskLine | CanvasFillRect | CanvasEraseRect;
+type CanvasObject = CanvasImage | CanvasBaseLine | CanvasMaskLine | CanvasFillRect | CanvasEraseRect;
 
 export type CanvasLayerState = {
   objects: CanvasObject[];
@@ -83,11 +83,6 @@ export type CanvasLayerState = {
   };
 };
 
-export type CanvasSession = {
-  sessionId: string;
-  boundingBox: IRect;
-};
-
 // type guards
 export const isCanvasMaskLine = (obj: CanvasObject): obj is CanvasMaskLine =>
   obj.kind === 'line' && obj.layer === 'mask';
diff --git a/invokeai/frontend/web/src/features/controlAdapters/components/ControlAdapterProcessorComponent.tsx b/invokeai/frontend/web/src/features/controlAdapters/components/ControlAdapterProcessorComponent.tsx
index 8679e7aff3..2e37d88e27 100644
--- a/invokeai/frontend/web/src/features/controlAdapters/components/ControlAdapterProcessorComponent.tsx
+++ b/invokeai/frontend/web/src/features/controlAdapters/components/ControlAdapterProcessorComponent.tsx
@@ -17,7 +17,7 @@ import NormalBaeProcessor from './processors/NormalBaeProcessor';
 import PidiProcessor from './processors/PidiProcessor';
 import ZoeDepthProcessor from './processors/ZoeDepthProcessor';
 
-export type Props = {
+type Props = {
   id: string;
 };
 
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/store/modelManagerV2Slice.ts b/invokeai/frontend/web/src/features/modelManagerV2/store/modelManagerV2Slice.ts
index 10f1be75ad..46f8979c8e 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/store/modelManagerV2Slice.ts
+++ b/invokeai/frontend/web/src/features/modelManagerV2/store/modelManagerV2Slice.ts
@@ -1,6 +1,6 @@
 import type { PayloadAction } from '@reduxjs/toolkit';
 import { createSlice } from '@reduxjs/toolkit';
-import type { PersistConfig, RootState } from 'app/store/store';
+import type { PersistConfig } from 'app/store/store';
 
 type ModelManagerState = {
   _version: 1;
@@ -42,8 +42,6 @@ export const modelManagerV2Slice = createSlice({
 export const { setSelectedModelKey, setSearchTerm, setFilteredModelType, setSelectedModelMode } =
   modelManagerV2Slice.actions;
 
-export const selectModelManagerSlice = (state: RootState) => state.modelmanagerV2;
-
 /* eslint-disable-next-line @typescript-eslint/no-explicit-any */
 const migrateModelManagerState = (state: any): any => {
   if (!('_version' in state)) {
diff --git a/invokeai/frontend/web/src/features/parameters/store/postprocessingSlice.ts b/invokeai/frontend/web/src/features/parameters/store/postprocessingSlice.ts
index e014f60570..65a30ab4d0 100644
--- a/invokeai/frontend/web/src/features/parameters/store/postprocessingSlice.ts
+++ b/invokeai/frontend/web/src/features/parameters/store/postprocessingSlice.ts
@@ -3,7 +3,7 @@ import { createSlice } from '@reduxjs/toolkit';
 import type { PersistConfig, RootState } from 'app/store/store';
 import { z } from 'zod';
 
-export const zParamESRGANModelName = z.enum([
+const zParamESRGANModelName = z.enum([
   'RealESRGAN_x4plus.pth',
   'RealESRGAN_x4plus_anime_6B.pth',
   'ESRGAN_SRx4_DF2KOST_official-ff704c30.pth',
@@ -18,7 +18,7 @@ export interface PostprocessingState {
   esrganModelName: ParamESRGANModelName;
 }
 
-export const initialPostprocessingState: PostprocessingState = {
+const initialPostprocessingState: PostprocessingState = {
   _version: 1,
   esrganModelName: 'RealESRGAN_x4plus.pth',
 };
@@ -38,7 +38,7 @@ export const { esrganModelNameChanged } = postprocessingSlice.actions;
 export const selectPostprocessingSlice = (state: RootState) => state.postprocessing;
 
 /* eslint-disable-next-line @typescript-eslint/no-explicit-any */
-export const migratePostprocessingState = (state: any): any => {
+const migratePostprocessingState = (state: any): any => {
   if (!('_version' in state)) {
     state._version = 1;
   }
diff --git a/invokeai/frontend/web/src/features/parameters/types/parameterSchemas.ts b/invokeai/frontend/web/src/features/parameters/types/parameterSchemas.ts
index 0fc912a6d6..e2cc277d6a 100644
--- a/invokeai/frontend/web/src/features/parameters/types/parameterSchemas.ts
+++ b/invokeai/frontend/web/src/features/parameters/types/parameterSchemas.ts
@@ -16,68 +16,68 @@ import { z } from 'zod';
  */
 
 // #region Positive prompt
-export const zParameterPositivePrompt = z.string();
+const zParameterPositivePrompt = z.string();
 export type ParameterPositivePrompt = z.infer<typeof zParameterPositivePrompt>;
 export const isParameterPositivePrompt = (val: unknown): val is ParameterPositivePrompt =>
   zParameterPositivePrompt.safeParse(val).success;
 // #endregion
 
 // #region Negative prompt
-export const zParameterNegativePrompt = z.string();
+const zParameterNegativePrompt = z.string();
 export type ParameterNegativePrompt = z.infer<typeof zParameterNegativePrompt>;
 export const isParameterNegativePrompt = (val: unknown): val is ParameterNegativePrompt =>
   zParameterNegativePrompt.safeParse(val).success;
 // #endregion
 
 // #region Positive style prompt (SDXL)
-export const zParameterPositiveStylePromptSDXL = z.string();
+const zParameterPositiveStylePromptSDXL = z.string();
 export type ParameterPositiveStylePromptSDXL = z.infer<typeof zParameterPositiveStylePromptSDXL>;
 export const isParameterPositiveStylePromptSDXL = (val: unknown): val is ParameterPositiveStylePromptSDXL =>
   zParameterPositiveStylePromptSDXL.safeParse(val).success;
 // #endregion
 
 // #region Positive style prompt (SDXL)
-export const zParameterNegativeStylePromptSDXL = z.string();
+const zParameterNegativeStylePromptSDXL = z.string();
 export type ParameterNegativeStylePromptSDXL = z.infer<typeof zParameterNegativeStylePromptSDXL>;
 export const isParameterNegativeStylePromptSDXL = (val: unknown): val is ParameterNegativeStylePromptSDXL =>
   zParameterNegativeStylePromptSDXL.safeParse(val).success;
 // #endregion
 
 // #region Steps
-export const zParameterSteps = z.number().int().min(1);
+const zParameterSteps = z.number().int().min(1);
 export type ParameterSteps = z.infer<typeof zParameterSteps>;
 export const isParameterSteps = (val: unknown): val is ParameterSteps => zParameterSteps.safeParse(val).success;
 // #endregion
 
 // #region CFG scale parameter
-export const zParameterCFGScale = z.number().min(1);
+const zParameterCFGScale = z.number().min(1);
 export type ParameterCFGScale = z.infer<typeof zParameterCFGScale>;
 export const isParameterCFGScale = (val: unknown): val is ParameterCFGScale =>
   zParameterCFGScale.safeParse(val).success;
 // #endregion
 
 // #region CFG Rescale Multiplier
-export const zParameterCFGRescaleMultiplier = z.number().gte(0).lt(1);
+const zParameterCFGRescaleMultiplier = z.number().gte(0).lt(1);
 export type ParameterCFGRescaleMultiplier = z.infer<typeof zParameterCFGRescaleMultiplier>;
 export const isParameterCFGRescaleMultiplier = (val: unknown): val is ParameterCFGRescaleMultiplier =>
   zParameterCFGRescaleMultiplier.safeParse(val).success;
 // #endregion
 
 // #region Scheduler
-export const zParameterScheduler = zSchedulerField;
+const zParameterScheduler = zSchedulerField;
 export type ParameterScheduler = z.infer<typeof zParameterScheduler>;
 export const isParameterScheduler = (val: unknown): val is ParameterScheduler =>
   zParameterScheduler.safeParse(val).success;
 // #endregion
 
 // #region seed
-export const zParameterSeed = z.number().int().min(0).max(NUMPY_RAND_MAX);
+const zParameterSeed = z.number().int().min(0).max(NUMPY_RAND_MAX);
 export type ParameterSeed = z.infer<typeof zParameterSeed>;
 export const isParameterSeed = (val: unknown): val is ParameterSeed => zParameterSeed.safeParse(val).success;
 // #endregion
 
 // #region Width
-export const zParameterWidth = z
+const zParameterWidth = z
   .number()
   .min(64)
   .transform((val) => roundToMultiple(val, 8));
@@ -86,96 +86,81 @@ export const isParameterWidth = (val: unknown): val is ParameterWidth => zParame
 // #endregion
 
 // #region Height
-export const zParameterHeight = zParameterWidth;
+const zParameterHeight = zParameterWidth;
 export type ParameterHeight = z.infer<typeof zParameterHeight>;
 export const isParameterHeight = (val: unknown): val is ParameterHeight => zParameterHeight.safeParse(val).success;
 // #endregion
 
 // #region Aspect Ratio
-export const zParameterAspectRatio = z.number().int().min(0).max(6);
+const zParameterAspectRatio = z.number().int().min(0).max(6);
 export type ParameterAspectRatio = z.infer<typeof zParameterAspectRatio>;
-export const isParameterAspectRatio = (val: unknown): val is ParameterAspectRatio =>
-  zParameterAspectRatio.safeParse(val).success;
 // #endregion
 
 // #region Model
 export const zParameterModel = zModelIdentifierWithBase;
 export type ParameterModel = z.infer<typeof zParameterModel>;
-export const isParameterModel = (val: unknown): val is ParameterModel => zParameterModel.safeParse(val).success;
 // #endregion
 
 // #region SDXL Refiner Model
-export const zParameterSDXLRefinerModel = zModelIdentifierWithBase;
+const zParameterSDXLRefinerModel = zModelIdentifierWithBase;
 export type ParameterSDXLRefinerModel = z.infer<typeof zParameterSDXLRefinerModel>;
-export const isParameterSDXLRefinerModel = (val: unknown): val is ParameterSDXLRefinerModel =>
-  zParameterSDXLRefinerModel.safeParse(val).success;
 // #endregion
 
 // #region VAE Model
 export const zParameterVAEModel = zModelIdentifierWithBase;
 export type ParameterVAEModel = z.infer<typeof zParameterVAEModel>;
-export const isParameterVAEModel = (val: unknown): val is ParameterVAEModel =>
-  zParameterVAEModel.safeParse(val).success;
 // #endregion
 
 // #region LoRA Model
-export const zParameterLoRAModel = zModelIdentifierWithBase;
+const zParameterLoRAModel = zModelIdentifierWithBase;
 export type ParameterLoRAModel = z.infer<typeof zParameterLoRAModel>;
-export const isParameterLoRAModel = (val: unknown): val is ParameterLoRAModel =>
-  zParameterLoRAModel.safeParse(val).success;
 // #endregion
 
 // #region ControlNet Model
-export const zParameterControlNetModel = zModelIdentifierWithBase;
-export type ParameterControlNetModel = z.infer<typeof zParameterLoRAModel>;
-export const isParameterControlNetModel = (val: unknown): val is ParameterControlNetModel =>
-  zParameterControlNetModel.safeParse(val).success;
+const zParameterControlNetModel = zModelIdentifierWithBase;
+export type ParameterControlNetModel = z.infer<typeof zParameterControlNetModel>;
 // #endregion
 
 // #region IP Adapter Model
-export const zParameterIPAdapterModel = zModelIdentifierWithBase;
+const zParameterIPAdapterModel = zModelIdentifierWithBase;
 export type ParameterIPAdapterModel = z.infer<typeof zParameterIPAdapterModel>;
-export const isParameterIPAdapterModel = (val: unknown): val is ParameterIPAdapterModel =>
-  zParameterIPAdapterModel.safeParse(val).success;
 // #endregion
 
 // #region T2I Adapter Model
-export const zParameterT2IAdapterModel = zModelIdentifierWithBase;
+const zParameterT2IAdapterModel = zModelIdentifierWithBase;
 export type ParameterT2IAdapterModel = z.infer<typeof zParameterT2IAdapterModel>;
-export const isParameterT2IAdapterModel = (val: unknown): val is ParameterT2IAdapterModel =>
-  zParameterT2IAdapterModel.safeParse(val).success;
 // #endregion
 
 // #region Strength (l2l strength)
-export const zParameterStrength = z.number().min(0).max(1);
+const zParameterStrength = z.number().min(0).max(1);
 export type ParameterStrength = z.infer<typeof zParameterStrength>;
 export const isParameterStrength = (val: unknown): val is ParameterStrength =>
   zParameterStrength.safeParse(val).success;
 // #endregion
 
 // #region Precision
-export const zParameterPrecision = z.enum(['fp16', 'fp32']);
+const zParameterPrecision = z.enum(['fp16', 'fp32']);
 export type ParameterPrecision = z.infer<typeof zParameterPrecision>;
 export const isParameterPrecision = (val: unknown): val is ParameterPrecision =>
   zParameterPrecision.safeParse(val).success;
 // #endregion
 
 // #region HRF Method
-export const zParameterHRFMethod = z.enum(['ESRGAN', 'bilinear']);
+const zParameterHRFMethod = z.enum(['ESRGAN', 'bilinear']);
 export type ParameterHRFMethod = z.infer<typeof zParameterHRFMethod>;
 export const isParameterHRFMethod = (val: unknown): val is ParameterHRFMethod =>
   zParameterHRFMethod.safeParse(val).success;
 // #endregion
 
 // #region HRF Enabled
-export const zParameterHRFEnabled = z.boolean();
+const zParameterHRFEnabled = z.boolean();
 export type ParameterHRFEnabled = z.infer<typeof zParameterHRFEnabled>;
 export const isParameterHRFEnabled = (val: unknown): val is boolean =>
   zParameterHRFEnabled.safeParse(val).success && val !== null && val !== undefined;
 // #endregion
 
 // #region SDXL Refiner Positive Aesthetic Score
-export const zParameterSDXLRefinerPositiveAestheticScore = z.number().min(1).max(10);
+const zParameterSDXLRefinerPositiveAestheticScore = z.number().min(1).max(10);
 export type ParameterSDXLRefinerPositiveAestheticScore = z.infer<typeof zParameterSDXLRefinerPositiveAestheticScore>;
 export const isParameterSDXLRefinerPositiveAestheticScore = (
   val: unknown
@@ -184,7 +169,7 @@ export const isParameterSDXLRefinerPositiveAestheticScore = (
 // #endregion
 
 // #region SDXL Refiner Negative Aesthetic Score
-export const zParameterSDXLRefinerNegativeAestheticScore = zParameterSDXLRefinerPositiveAestheticScore;
+const zParameterSDXLRefinerNegativeAestheticScore = zParameterSDXLRefinerPositiveAestheticScore;
 export type ParameterSDXLRefinerNegativeAestheticScore = z.infer<typeof zParameterSDXLRefinerNegativeAestheticScore>;
 export const isParameterSDXLRefinerNegativeAestheticScore = (
   val: unknown
@@ -193,28 +178,26 @@ export const isParameterSDXLRefinerNegativeAestheticScore = (
 // #endregion
 
 // #region SDXL Refiner Start
-export const zParameterSDXLRefinerStart = z.number().min(0).max(1);
+const zParameterSDXLRefinerStart = z.number().min(0).max(1);
 export type ParameterSDXLRefinerStart = z.infer<typeof zParameterSDXLRefinerStart>;
 export const isParameterSDXLRefinerStart = (val: unknown): val is ParameterSDXLRefinerStart =>
   zParameterSDXLRefinerStart.safeParse(val).success;
 // #endregion
 
 // #region Mask Blur Method
-export const zParameterMaskBlurMethod = z.enum(['box', 'gaussian']);
+const zParameterMaskBlurMethod = z.enum(['box', 'gaussian']);
 export type ParameterMaskBlurMethod = z.infer<typeof zParameterMaskBlurMethod>;
-export const isParameterMaskBlurMethod = (val: unknown): val is ParameterMaskBlurMethod =>
-  zParameterMaskBlurMethod.safeParse(val).success;
 // #endregion
 
 // #region Canvas Coherence Mode
-export const zParameterCanvasCoherenceMode = z.enum(['Gaussian Blur', 'Box Blur', 'Staged']);
+const zParameterCanvasCoherenceMode = z.enum(['Gaussian Blur', 'Box Blur', 'Staged']);
 export type ParameterCanvasCoherenceMode = z.infer<typeof zParameterCanvasCoherenceMode>;
 export const isParameterCanvasCoherenceMode = (val: unknown): val is ParameterCanvasCoherenceMode =>
   zParameterCanvasCoherenceMode.safeParse(val).success;
 // #endregion
 
 // #region LoRA weight
-export const zLoRAWeight = z.number();
+const zLoRAWeight = z.number();
 export type ParameterLoRAWeight = z.infer<typeof zLoRAWeight>;
 export const isParameterLoRAWeight = (val: unknown): val is ParameterLoRAWeight => zLoRAWeight.safeParse(val).success;
 // #endregion
diff --git a/invokeai/frontend/web/src/features/queue/store/queueSlice.ts b/invokeai/frontend/web/src/features/queue/store/queueSlice.ts
index 340dff5104..a5750712c3 100644
--- a/invokeai/frontend/web/src/features/queue/store/queueSlice.ts
+++ b/invokeai/frontend/web/src/features/queue/store/queueSlice.ts
@@ -1,6 +1,5 @@
 import type { PayloadAction } from '@reduxjs/toolkit';
 import { createSlice } from '@reduxjs/toolkit';
-import type { RootState } from 'app/store/store';
 
 export interface QueueState {
   listCursor: number | undefined;
@@ -9,18 +8,16 @@ export interface QueueState {
   resumeProcessorOnEnqueue: boolean;
 }
 
-export const initialQueueState: QueueState = {
+const initialQueueState: QueueState = {
   listCursor: undefined,
   listPriority: undefined,
   selectedQueueItem: undefined,
   resumeProcessorOnEnqueue: true,
 };
 
-const initialState: QueueState = initialQueueState;
-
 export const queueSlice = createSlice({
   name: 'queue',
-  initialState,
+  initialState: initialQueueState,
   reducers: {
     listCursorChanged: (state, action: PayloadAction<number | undefined>) => {
       state.listCursor = action.payload;
@@ -32,25 +29,7 @@ export const queueSlice = createSlice({
       state.listCursor = undefined;
       state.listPriority = undefined;
     },
-    queueItemSelectionToggled: (state, action: PayloadAction<string | undefined>) => {
-      if (state.selectedQueueItem === action.payload) {
-        state.selectedQueueItem = undefined;
-      } else {
-        state.selectedQueueItem = action.payload;
-      }
-    },
-    resumeProcessorOnEnqueueChanged: (state, action: PayloadAction<boolean>) => {
-      state.resumeProcessorOnEnqueue = action.payload;
-    },
   },
 });
 
-export const {
-  listCursorChanged,
-  listPriorityChanged,
-  listParamsReset,
-  queueItemSelectionToggled,
-  resumeProcessorOnEnqueueChanged,
-} = queueSlice.actions;
-
-export const selectQueueSlice = (state: RootState) => state.queue;
+export const { listCursorChanged, listPriorityChanged, listParamsReset } = queueSlice.actions;
diff --git a/invokeai/frontend/web/src/features/sdxl/store/sdxlSlice.ts b/invokeai/frontend/web/src/features/sdxl/store/sdxlSlice.ts
index efa5f1c8bd..88061a28f6 100644
--- a/invokeai/frontend/web/src/features/sdxl/store/sdxlSlice.ts
+++ b/invokeai/frontend/web/src/features/sdxl/store/sdxlSlice.ts
@@ -22,7 +22,7 @@ type SDXLState = {
   refinerStart: number;
 };
 
-export const initialSDXLState: SDXLState = {
+const initialSDXLState: SDXLState = {
   _version: 1,
   positiveStylePrompt: '',
   negativeStylePrompt: '',
@@ -89,7 +89,7 @@ export const {
 export const selectSdxlSlice = (state: RootState) => state.sdxl;
 
 /* eslint-disable-next-line @typescript-eslint/no-explicit-any */
-export const migrateSDXLState = (state: any): any => {
+const migrateSDXLState = (state: any): any => {
   if (!('_version' in state)) {
     state._version = 1;
   }
diff --git a/invokeai/frontend/web/src/features/system/components/StickyScrollable.tsx b/invokeai/frontend/web/src/features/system/components/StickyScrollable.tsx
index 073b7f5f89..9359731d5b 100644
--- a/invokeai/frontend/web/src/features/system/components/StickyScrollable.tsx
+++ b/invokeai/frontend/web/src/features/system/components/StickyScrollable.tsx
@@ -2,11 +2,11 @@ import { Flex, Heading } from '@invoke-ai/ui-library';
 import type { PropsWithChildren } from 'react';
 import { memo } from 'react';
 
-export type StickyScrollableHeadingProps = {
+type StickyScrollableHeadingProps = {
   title: string;
 };
 
-export const StickyScrollableHeading = memo((props: StickyScrollableHeadingProps) => {
+const StickyScrollableHeading = memo((props: StickyScrollableHeadingProps) => {
   return (
     <Flex ps={2} pb={4} position="sticky" zIndex={1} top={0} bg="base.800">
       <Heading size="sm">{props.title}</Heading>
@@ -16,9 +16,9 @@ export const StickyScrollableHeading = memo((props: StickyScrollableHeadingProps
 
 StickyScrollableHeading.displayName = 'StickyScrollableHeading';
 
-export type StickyScrollableContentProps = PropsWithChildren;
+type StickyScrollableContentProps = PropsWithChildren;
 
-export const StickyScrollableContent = memo((props: StickyScrollableContentProps) => {
+const StickyScrollableContent = memo((props: StickyScrollableContentProps) => {
   return (
     <Flex p={4} borderRadius="base" bg="base.750" flexDir="column" gap={4}>
       {props.children}
diff --git a/invokeai/frontend/web/src/features/system/store/configSlice.ts b/invokeai/frontend/web/src/features/system/store/configSlice.ts
index ded3241c5b..4e1b734a66 100644
--- a/invokeai/frontend/web/src/features/system/store/configSlice.ts
+++ b/invokeai/frontend/web/src/features/system/store/configSlice.ts
@@ -14,7 +14,7 @@ const baseDimensionConfig: NumericalParameterConfig = {
   coarseStep: 64,
 };
 
-export const initialConfigState: AppConfig = {
+const initialConfigState: AppConfig = {
   shouldUpdateImagesOnConnect: false,
   shouldFetchMetadataFromApi: false,
   disabledTabs: [],
diff --git a/invokeai/frontend/web/src/features/system/store/systemSlice.ts b/invokeai/frontend/web/src/features/system/store/systemSlice.ts
index 589397e951..17ddec5471 100644
--- a/invokeai/frontend/web/src/features/system/store/systemSlice.ts
+++ b/invokeai/frontend/web/src/features/system/store/systemSlice.ts
@@ -24,7 +24,7 @@ import {
 
 import type { Language, SystemState } from './types';
 
-export const initialSystemState: SystemState = {
+const initialSystemState: SystemState = {
   _version: 1,
   isConnected: false,
   shouldConfirmOnDelete: true,
@@ -199,7 +199,7 @@ const isAnyServerError = isAnyOf(socketInvocationError, socketSessionRetrievalEr
 export const selectSystemSlice = (state: RootState) => state.system;
 
 /* eslint-disable-next-line @typescript-eslint/no-explicit-any */
-export const migrateSystemState = (state: any): any => {
+const migrateSystemState = (state: any): any => {
   if (!('_version' in state)) {
     state._version = 1;
   }
diff --git a/invokeai/frontend/web/src/features/system/store/types.ts b/invokeai/frontend/web/src/features/system/store/types.ts
index 3575501d86..c8790e0104 100644
--- a/invokeai/frontend/web/src/features/system/store/types.ts
+++ b/invokeai/frontend/web/src/features/system/store/types.ts
@@ -15,7 +15,7 @@ export type DenoiseProgress = {
   percentage: number;
 };
 
-export const zLanguage = z.enum([
+const zLanguage = z.enum([
   'ar',
   'az',
   'de',
@@ -58,11 +58,3 @@ export interface SystemState {
   status: SystemStatus;
   shouldEnableInformationalPopovers: boolean;
 }
-
-export const STATUS_TRANSLATION_KEYS: Record<SystemStatus, string> = {
-  CONNECTED: 'common.statusConnected',
-  DISCONNECTED: 'common.statusDisconnected',
-  PROCESSING: 'common.statusProcessing',
-  ERROR: 'common.statusError',
-  LOADING_MODEL: 'common.statusLoadingModel',
-};
diff --git a/invokeai/frontend/web/src/features/ui/components/InvokeTabs.tsx b/invokeai/frontend/web/src/features/ui/components/InvokeTabs.tsx
index efff22bb02..c6682e33fc 100644
--- a/invokeai/frontend/web/src/features/ui/components/InvokeTabs.tsx
+++ b/invokeai/frontend/web/src/features/ui/components/InvokeTabs.tsx
@@ -85,8 +85,8 @@ const enabledTabsSelector = createMemoizedSelector(selectConfigSlice, (config) =
   tabs.filter((tab) => !config.disabledTabs.includes(tab.id))
 );
 
-export const NO_GALLERY_PANEL_TABS: InvokeTabName[] = ['modelManager', 'queue'];
-export const NO_OPTIONS_PANEL_TABS: InvokeTabName[] = ['modelManager', 'queue'];
+const NO_GALLERY_PANEL_TABS: InvokeTabName[] = ['modelManager', 'queue'];
+const NO_OPTIONS_PANEL_TABS: InvokeTabName[] = ['modelManager', 'queue'];
 const panelStyles: CSSProperties = { height: '100%', width: '100%' };
 const GALLERY_MIN_SIZE_PX = 310;
 const GALLERY_MIN_SIZE_PCT = 20;
diff --git a/invokeai/frontend/web/src/features/ui/store/uiSlice.ts b/invokeai/frontend/web/src/features/ui/store/uiSlice.ts
index 32eb26673a..f9a4b94805 100644
--- a/invokeai/frontend/web/src/features/ui/store/uiSlice.ts
+++ b/invokeai/frontend/web/src/features/ui/store/uiSlice.ts
@@ -6,7 +6,7 @@ import { initialImageChanged } from 'features/parameters/store/generationSlice';
 import type { InvokeTabName } from './tabMap';
 import type { UIState } from './uiTypes';
 
-export const initialUIState: UIState = {
+const initialUIState: UIState = {
   _version: 1,
   activeTab: 'txt2img',
   shouldShowImageDetails: false,
@@ -60,7 +60,7 @@ export const {
 export const selectUiSlice = (state: RootState) => state.ui;
 
 /* eslint-disable-next-line @typescript-eslint/no-explicit-any */
-export const migrateUIState = (state: any): any => {
+const migrateUIState = (state: any): any => {
   if (!('_version' in state)) {
     state._version = 1;
   }
diff --git a/invokeai/frontend/web/src/services/api/endpoints/boards.ts b/invokeai/frontend/web/src/services/api/endpoints/boards.ts
index 8efda86737..106cfd59d3 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/boards.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/boards.ts
@@ -1,11 +1,5 @@
 import { ASSETS_CATEGORIES, IMAGE_CATEGORIES } from 'features/gallery/store/types';
-import type {
-  BoardDTO,
-  ListBoardsArg,
-  OffsetPaginatedResults_BoardDTO_,
-  OffsetPaginatedResults_ImageDTO_,
-  UpdateBoardArg,
-} from 'services/api/types';
+import type { BoardDTO, OffsetPaginatedResults_ImageDTO_, UpdateBoardArg } from 'services/api/types';
 import { getListImagesUrl } from 'services/api/util';
 
 import type { ApiTagDescription } from '..';
@@ -24,26 +18,6 @@ export const boardsApi = api.injectEndpoints({
     /**
      * Boards Queries
      */
-    listBoards: build.query<OffsetPaginatedResults_BoardDTO_, ListBoardsArg>({
-      query: (arg) => ({ url: buildBoardsUrl(), params: arg }),
-      providesTags: (result) => {
-        // any list of boards
-        const tags: ApiTagDescription[] = [{ type: 'Board', id: LIST_TAG }, 'FetchOnReconnect'];
-
-        if (result) {
-          // and individual tags for each board
-          tags.push(
-            ...result.items.map(({ board_id }) => ({
-              type: 'Board' as const,
-              id: board_id,
-            }))
-          );
-        }
-
-        return tags;
-      },
-    }),
-
     listAllBoards: build.query<Array<BoardDTO>, void>({
       query: () => ({
         url: buildBoardsUrl(),
@@ -134,7 +108,6 @@ export const boardsApi = api.injectEndpoints({
 });
 
 export const {
-  useListBoardsQuery,
   useListAllBoardsQuery,
   useGetBoardImagesTotalQuery,
   useGetBoardAssetsTotalQuery,
diff --git a/invokeai/frontend/web/src/services/api/endpoints/images.ts b/invokeai/frontend/web/src/services/api/endpoints/images.ts
index 1849e2fde4..672ba01c26 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/images.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/images.ts
@@ -376,40 +376,6 @@ export const imagesApi = api.injectEndpoints({
         }
       },
     }),
-    /**
-     * Change an image's `session_id` association.
-     */
-    changeImageSessionId: build.mutation<ImageDTO, { imageDTO: ImageDTO; session_id: string }>({
-      query: ({ imageDTO, session_id }) => ({
-        url: buildImagesUrl(`i/${imageDTO.image_name}`),
-        method: 'PATCH',
-        body: { session_id },
-      }),
-      async onQueryStarted({ imageDTO, session_id }, { dispatch, queryFulfilled }) {
-        /**
-         * Cache changes for `changeImageSessionId`:
-         * - *update* getImageDTO
-         */
-
-        // Store patches so we can undo if the query fails
-        const patches: PatchCollection[] = [];
-
-        // *update* getImageDTO
-        patches.push(
-          dispatch(
-            imagesApi.util.updateQueryData('getImageDTO', imageDTO.image_name, (draft) => {
-              Object.assign(draft, { session_id });
-            })
-          )
-        );
-
-        try {
-          await queryFulfilled;
-        } catch {
-          patches.forEach((patchResult) => patchResult.undo());
-        }
-      },
-    }),
     /**
      * Star a list of images.
      */
@@ -1336,13 +1302,10 @@ export const imagesApi = api.injectEndpoints({
 export const {
   useGetIntermediatesCountQuery,
   useListImagesQuery,
-  useLazyListImagesQuery,
   useGetImageDTOQuery,
   useGetImageMetadataQuery,
   useGetImageWorkflowQuery,
   useLazyGetImageWorkflowQuery,
-  useDeleteImageMutation,
-  useDeleteImagesMutation,
   useUploadImageMutation,
   useClearIntermediatesMutation,
   useAddImagesToBoardMutation,
@@ -1350,7 +1313,6 @@ export const {
   useAddImageToBoardMutation,
   useRemoveImageFromBoardMutation,
   useChangeImageIsIntermediateMutation,
-  useChangeImageSessionIdMutation,
   useDeleteBoardAndImagesMutation,
   useDeleteBoardMutation,
   useStarImagesMutation,
diff --git a/invokeai/frontend/web/src/services/api/endpoints/models.ts b/invokeai/frontend/web/src/services/api/endpoints/models.ts
index a236868b79..e7e63eeecc 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/models.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/models.ts
@@ -66,50 +66,45 @@ type ScanFolderArg = operations['scan_for_models']['parameters']['query'];
 
 export type GetByAttrsArg = operations['get_model_records_by_attrs']['parameters']['query'];
 
-export const mainModelsAdapter = createEntityAdapter<MainModelConfig, string>({
+const mainModelsAdapter = createEntityAdapter<MainModelConfig, string>({
   selectId: (entity) => entity.key,
   sortComparer: (a, b) => a.name.localeCompare(b.name),
 });
 export const mainModelsAdapterSelectors = mainModelsAdapter.getSelectors(undefined, getSelectorsOptions);
-export const loraModelsAdapter = createEntityAdapter<LoRAModelConfig, string>({
+const loraModelsAdapter = createEntityAdapter<LoRAModelConfig, string>({
   selectId: (entity) => entity.key,
   sortComparer: (a, b) => a.name.localeCompare(b.name),
 });
-export const loraModelsAdapterSelectors = loraModelsAdapter.getSelectors(undefined, getSelectorsOptions);
-export const controlNetModelsAdapter = createEntityAdapter<ControlNetModelConfig, string>({
+const controlNetModelsAdapter = createEntityAdapter<ControlNetModelConfig, string>({
   selectId: (entity) => entity.key,
   sortComparer: (a, b) => a.name.localeCompare(b.name),
 });
 export const controlNetModelsAdapterSelectors = controlNetModelsAdapter.getSelectors(undefined, getSelectorsOptions);
-export const ipAdapterModelsAdapter = createEntityAdapter<IPAdapterModelConfig, string>({
+const ipAdapterModelsAdapter = createEntityAdapter<IPAdapterModelConfig, string>({
   selectId: (entity) => entity.key,
   sortComparer: (a, b) => a.name.localeCompare(b.name),
 });
 export const ipAdapterModelsAdapterSelectors = ipAdapterModelsAdapter.getSelectors(undefined, getSelectorsOptions);
-export const t2iAdapterModelsAdapter = createEntityAdapter<T2IAdapterModelConfig, string>({
+const t2iAdapterModelsAdapter = createEntityAdapter<T2IAdapterModelConfig, string>({
   selectId: (entity) => entity.key,
   sortComparer: (a, b) => a.name.localeCompare(b.name),
 });
 export const t2iAdapterModelsAdapterSelectors = t2iAdapterModelsAdapter.getSelectors(undefined, getSelectorsOptions);
-export const textualInversionModelsAdapter = createEntityAdapter<TextualInversionModelConfig, string>({
+const textualInversionModelsAdapter = createEntityAdapter<TextualInversionModelConfig, string>({
   selectId: (entity) => entity.key,
   sortComparer: (a, b) => a.name.localeCompare(b.name),
 });
-export const textualInversionModelsAdapterSelectors = textualInversionModelsAdapter.getSelectors(
-  undefined,
-  getSelectorsOptions
-);
-export const vaeModelsAdapter = createEntityAdapter<VAEModelConfig, string>({
+const vaeModelsAdapter = createEntityAdapter<VAEModelConfig, string>({
   selectId: (entity) => entity.key,
   sortComparer: (a, b) => a.name.localeCompare(b.name),
 });
 export const vaeModelsAdapterSelectors = vaeModelsAdapter.getSelectors(undefined, getSelectorsOptions);
 
-export const anyModelConfigAdapter = createEntityAdapter<AnyModelConfig, string>({
+const anyModelConfigAdapter = createEntityAdapter<AnyModelConfig, string>({
   selectId: (entity) => entity.key,
   sortComparer: (a, b) => a.name.localeCompare(b.name),
 });
-export const anyModelConfigAdapterSelectors = anyModelConfigAdapter.getSelectors(undefined, getSelectorsOptions);
+const anyModelConfigAdapterSelectors = anyModelConfigAdapter.getSelectors(undefined, getSelectorsOptions);
 
 const buildProvidesTags =
   <TEntity extends AnyModelConfig>(tagType: (typeof tagTypes)[number]) =>
@@ -338,7 +333,6 @@ export const modelsApi = api.injectEndpoints({
 });
 
 export const {
-  useGetModelConfigByAttrsQuery,
   useGetModelConfigQuery,
   useGetMainModelsQuery,
   useGetControlNetModelsQuery,
@@ -352,7 +346,6 @@ export const {
   useInstallModelMutation,
   useConvertMainModelsMutation,
   useSyncModelsMutation,
-  useScanModelsQuery,
   useLazyScanModelsQuery,
   useGetModelImportsQuery,
   useGetModelMetadataQuery,
diff --git a/invokeai/frontend/web/src/services/api/endpoints/queue.ts b/invokeai/frontend/web/src/services/api/endpoints/queue.ts
index 385aa8ad12..4775c293f8 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/queue.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/queue.ts
@@ -314,10 +314,8 @@ export const {
   useResumeProcessorMutation,
   useClearQueueMutation,
   usePruneQueueMutation,
-  useGetCurrentQueueItemQuery,
   useGetQueueStatusQuery,
   useGetQueueItemQuery,
-  useGetNextQueueItemQuery,
   useListQueueItemsQuery,
   useCancelQueueItemMutation,
   useGetBatchStatusQuery,
diff --git a/invokeai/frontend/web/src/services/api/endpoints/utilities.ts b/invokeai/frontend/web/src/services/api/endpoints/utilities.ts
index 309dd2dc79..a2e2e47c70 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/utilities.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/utilities.ts
@@ -28,5 +28,3 @@ export const utilitiesApi = api.injectEndpoints({
     }),
   }),
 });
-
-export const { useDynamicPromptsQuery } = utilitiesApi;
diff --git a/invokeai/frontend/web/src/services/api/types.ts b/invokeai/frontend/web/src/services/api/types.ts
index 314eb07bfa..c57d242f97 100644
--- a/invokeai/frontend/web/src/services/api/types.ts
+++ b/invokeai/frontend/web/src/services/api/types.ts
@@ -101,10 +101,6 @@ export const isT2IAdapterModelConfig = (config: AnyModelConfig): config is T2IAd
   return config.type === 't2i_adapter';
 };
 
-export const isTextualInversionModelConfig = (config: AnyModelConfig): config is TextualInversionModelConfig => {
-  return config.type === 'embedding';
-};
-
 export const isNonRefinerMainModelConfig = (config: AnyModelConfig): config is MainModelConfig => {
   return config.type === 'main' && config.base !== 'sdxl-refiner';
 };

From d99bec8b1ae37280cef05b8579fcf61e36e1d648 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 27 Feb 2024 18:13:16 +1100
Subject: [PATCH 346/411] tidy(ui): clean up unused code 5

variables, types and schemas
---
 invokeai/frontend/web/knip.ts                 |   1 -
 invokeai/frontend/web/package.json            |   3 -
 .../frontend/web/src/app/hooks/useSocketIO.ts |   2 +-
 .../store/enhancers/reduxRemember/driver.ts   |   2 +-
 .../web/src/app/store/nanostores/store.ts     |   2 +-
 .../features/canvas/store/canvasNanostore.ts  |   2 +-
 .../src/features/canvas/store/canvasSlice.ts  |   1 -
 .../store/controlAdaptersSlice.ts             |   2 -
 .../web/src/features/dnd/types/index.ts       |  22 +-
 .../store/dynamicPromptsSlice.ts              |   2 +-
 .../web/src/features/embedding/usePrompt.ts   |   2 +-
 .../gallery/components/ImageGrid/types.ts     |   2 +-
 .../gallery/hooks/useGalleryNavigation.ts     |   2 +-
 .../web/src/features/hrf/store/hrfSlice.ts    |   2 +-
 .../web/src/features/lora/store/loraSlice.ts  |   2 +-
 .../web/src/features/metadata/types.ts        |   9 +-
 .../metadata/util/modelFetchingHelpers.ts     |   8 +-
 .../web/src/features/metadata/util/parsers.ts |   2 +-
 .../nodes/hooks/useConnectionState.ts         |   2 +-
 .../web/src/features/nodes/store/types.ts     |   4 -
 .../web/src/features/nodes/types/common.ts    |  13 +-
 .../web/src/features/nodes/types/field.ts     |  50 --
 .../src/features/nodes/types/invocation.ts    |   7 +-
 .../web/src/features/nodes/types/openapi.ts   |  14 +-
 .../web/src/features/nodes/types/v2/common.ts | 126 +---
 .../web/src/features/nodes/types/v2/field.ts  | 638 +++---------------
 .../src/features/nodes/types/v2/invocation.ts |  67 +-
 .../web/src/features/nodes/types/v2/semver.ts |   9 -
 .../src/features/nodes/types/v2/workflow.ts   |  34 +-
 .../web/src/features/nodes/types/workflow.ts  |  11 +-
 .../nodes/util/workflow/buildWorkflow.ts      |   2 +-
 .../ImageSize/AspectRatioPreview.tsx          |   5 -
 .../parameters/store/postprocessingSlice.ts   |   4 +-
 .../parameters/types/parameterSchemas.ts      |   7 +-
 .../src/features/queue/store/queueSlice.ts    |   2 +-
 .../components/HotkeysModal/useHotkeyData.ts  |   2 +-
 .../SettingsModal/useClearIntermediates.ts    |   2 +-
 .../system/components/StickyScrollable.tsx    |   2 +-
 .../web/src/features/system/store/types.ts    |   4 +-
 .../src/features/ui/components/InvokeTabs.tsx |   2 +-
 .../web/src/services/api/endpoints/models.ts  |   2 +-
 .../frontend/web/src/services/api/schema.ts   |   6 +-
 .../frontend/web/src/services/api/types.ts    |  54 +-
 .../frontend/web/src/services/events/types.ts |  10 +-
 44 files changed, 151 insertions(+), 996 deletions(-)

diff --git a/invokeai/frontend/web/knip.ts b/invokeai/frontend/web/knip.ts
index a47edbf6b4..479dd27a96 100644
--- a/invokeai/frontend/web/knip.ts
+++ b/invokeai/frontend/web/knip.ts
@@ -5,7 +5,6 @@ const config: KnipConfig = {
     // This file is only used during debugging
     'src/app/store/middleware/debugLoggerMiddleware.ts',
   ],
-  ignoreDependencies: ['@storybook/addon-docs', '@storybook/blocks', '@storybook/test', 'public/.*'],
   ignoreBinaries: ['only-allow'],
 };
 
diff --git a/invokeai/frontend/web/package.json b/invokeai/frontend/web/package.json
index 39c9722441..8e8faa5c84 100644
--- a/invokeai/frontend/web/package.json
+++ b/invokeai/frontend/web/package.json
@@ -112,16 +112,13 @@
   "devDependencies": {
     "@invoke-ai/eslint-config-react": "^0.0.14",
     "@invoke-ai/prettier-config-react": "^0.0.7",
-    "@storybook/addon-docs": "^7.6.17",
     "@storybook/addon-essentials": "^7.6.17",
     "@storybook/addon-interactions": "^7.6.17",
     "@storybook/addon-links": "^7.6.17",
     "@storybook/addon-storysource": "^7.6.17",
-    "@storybook/blocks": "^7.6.17",
     "@storybook/manager-api": "^7.6.17",
     "@storybook/react": "^7.6.17",
     "@storybook/react-vite": "^7.6.17",
-    "@storybook/test": "^7.6.17",
     "@storybook/theming": "^7.6.17",
     "@types/dateformat": "^5.0.2",
     "@types/lodash-es": "^4.17.12",
diff --git a/invokeai/frontend/web/src/app/hooks/useSocketIO.ts b/invokeai/frontend/web/src/app/hooks/useSocketIO.ts
index 058a607261..e1c4cebdb9 100644
--- a/invokeai/frontend/web/src/app/hooks/useSocketIO.ts
+++ b/invokeai/frontend/web/src/app/hooks/useSocketIO.ts
@@ -19,7 +19,7 @@ declare global {
 }
 
 export const $socketOptions = map<Partial<ManagerOptions & SocketOptions>>({});
-export const $isSocketInitialized = atom<boolean>(false);
+const $isSocketInitialized = atom<boolean>(false);
 
 /**
  * Initializes the socket.io connection and sets up event listeners.
diff --git a/invokeai/frontend/web/src/app/store/enhancers/reduxRemember/driver.ts b/invokeai/frontend/web/src/app/store/enhancers/reduxRemember/driver.ts
index c8237664c2..7196e1fcea 100644
--- a/invokeai/frontend/web/src/app/store/enhancers/reduxRemember/driver.ts
+++ b/invokeai/frontend/web/src/app/store/enhancers/reduxRemember/driver.ts
@@ -6,7 +6,7 @@ import { atom } from 'nanostores';
 import type { Driver } from 'redux-remember';
 
 // Create a custom idb-keyval store (just needed to customize the name)
-export const $idbKeyValStore = atom<UseStore>(createIDBKeyValStore('invoke', 'invoke-store'));
+const $idbKeyValStore = atom<UseStore>(createIDBKeyValStore('invoke', 'invoke-store'));
 
 export const clearIdbKeyValStore = () => {
   clear($idbKeyValStore.get());
diff --git a/invokeai/frontend/web/src/app/store/nanostores/store.ts b/invokeai/frontend/web/src/app/store/nanostores/store.ts
index f4cd001c96..65c59dad5d 100644
--- a/invokeai/frontend/web/src/app/store/nanostores/store.ts
+++ b/invokeai/frontend/web/src/app/store/nanostores/store.ts
@@ -11,7 +11,7 @@ declare global {
 /**
  * Raised when the redux store is unable to be retrieved.
  */
-export class ReduxStoreNotInitialized extends Error {
+class ReduxStoreNotInitialized extends Error {
   /**
    * Create ReduxStoreNotInitialized
    * @param {String} message
diff --git a/invokeai/frontend/web/src/features/canvas/store/canvasNanostore.ts b/invokeai/frontend/web/src/features/canvas/store/canvasNanostore.ts
index f971886d5e..b225f66677 100644
--- a/invokeai/frontend/web/src/features/canvas/store/canvasNanostore.ts
+++ b/invokeai/frontend/web/src/features/canvas/store/canvasNanostore.ts
@@ -8,7 +8,7 @@ export const $tool = atom<CanvasTool>('move');
 export const $toolStash = atom<CanvasTool | null>(null);
 export const $isDrawing = atom<boolean>(false);
 export const $isMouseOverBoundingBox = atom<boolean>(false);
-export const $isMoveBoundingBoxKeyHeld = atom<boolean>(false);
+const $isMoveBoundingBoxKeyHeld = atom<boolean>(false);
 export const $isMoveStageKeyHeld = atom<boolean>(false);
 export const $isMovingBoundingBox = atom<boolean>(false);
 export const $isMovingStage = atom<boolean>(false);
diff --git a/invokeai/frontend/web/src/features/canvas/store/canvasSlice.ts b/invokeai/frontend/web/src/features/canvas/store/canvasSlice.ts
index 8ae6a2176d..465bc11409 100644
--- a/invokeai/frontend/web/src/features/canvas/store/canvasSlice.ts
+++ b/invokeai/frontend/web/src/features/canvas/store/canvasSlice.ts
@@ -674,7 +674,6 @@ export const {
   setShouldAutoSave,
   setShouldCropToBoundingBoxOnSave,
   setShouldDarkenOutsideBoundingBox,
-  setShouldLockBoundingBox,
   setShouldPreserveMaskedArea,
   setShouldShowBoundingBox,
   setShouldShowCanvasDebugInfo,
diff --git a/invokeai/frontend/web/src/features/controlAdapters/store/controlAdaptersSlice.ts b/invokeai/frontend/web/src/features/controlAdapters/store/controlAdaptersSlice.ts
index d90ccd0f2a..a20e287011 100644
--- a/invokeai/frontend/web/src/features/controlAdapters/store/controlAdaptersSlice.ts
+++ b/invokeai/frontend/web/src/features/controlAdapters/store/controlAdaptersSlice.ts
@@ -38,9 +38,7 @@ const caAdapterSelectors = caAdapter.getSelectors(undefined, getSelectorsOptions
 export const {
   selectById: selectControlAdapterById,
   selectAll: selectControlAdapterAll,
-  selectEntities: selectControlAdapterEntities,
   selectIds: selectControlAdapterIds,
-  selectTotal: selectControlAdapterTotal,
 } = caAdapterSelectors;
 
 const initialControlAdaptersState: ControlAdaptersState = caAdapter.getInitialState<{
diff --git a/invokeai/frontend/web/src/features/dnd/types/index.ts b/invokeai/frontend/web/src/features/dnd/types/index.ts
index 6e680b4ba9..b2b7820762 100644
--- a/invokeai/frontend/web/src/features/dnd/types/index.ts
+++ b/invokeai/frontend/web/src/features/dnd/types/index.ts
@@ -18,30 +18,26 @@ type BaseDropData = {
   id: string;
 };
 
-export type CurrentImageDropData = BaseDropData & {
+type CurrentImageDropData = BaseDropData & {
   actionType: 'SET_CURRENT_IMAGE';
 };
 
-export type InitialImageDropData = BaseDropData & {
+type InitialImageDropData = BaseDropData & {
   actionType: 'SET_INITIAL_IMAGE';
 };
 
-export type ControlAdapterDropData = BaseDropData & {
+type ControlAdapterDropData = BaseDropData & {
   actionType: 'SET_CONTROL_ADAPTER_IMAGE';
   context: {
     id: string;
   };
 };
 
-export type IPAdapterImageDropData = BaseDropData & {
-  actionType: 'SET_IP_ADAPTER_IMAGE';
-};
-
 export type CanvasInitialImageDropData = BaseDropData & {
   actionType: 'SET_CANVAS_INITIAL_IMAGE';
 };
 
-export type NodesImageDropData = BaseDropData & {
+type NodesImageDropData = BaseDropData & {
   actionType: 'SET_NODES_IMAGE';
   context: {
     nodeId: string;
@@ -71,7 +67,7 @@ type BaseDragData = {
   id: string;
 };
 
-export type NodeFieldDraggableData = BaseDragData & {
+type NodeFieldDraggableData = BaseDragData & {
   payloadType: 'NODE_FIELD';
   payload: {
     nodeId: string;
@@ -114,7 +110,7 @@ export interface TypesafeActive extends Omit<Active, 'data'> {
   data: React.MutableRefObject<TypesafeDraggableData | undefined>;
 }
 
-export interface TypesafeOver extends Omit<Over, 'data'> {
+interface TypesafeOver extends Omit<Over, 'data'> {
   data: React.MutableRefObject<TypesafeDroppableData | undefined>;
 }
 
@@ -127,10 +123,10 @@ interface DragEvent {
 }
 
 export interface DragStartEvent extends Pick<DragEvent, 'active'> {}
-export interface DragMoveEvent extends DragEvent {}
-export interface DragOverEvent extends DragMoveEvent {}
+interface DragMoveEvent extends DragEvent {}
+interface DragOverEvent extends DragMoveEvent {}
 export interface DragEndEvent extends DragEvent {}
-export interface DragCancelEvent extends DragEndEvent {}
+interface DragCancelEvent extends DragEndEvent {}
 
 export interface DndContextTypesafeProps
   extends Omit<DndContextProps, 'onDragStart' | 'onDragMove' | 'onDragOver' | 'onDragEnd' | 'onDragCancel'> {
diff --git a/invokeai/frontend/web/src/features/dynamicPrompts/store/dynamicPromptsSlice.ts b/invokeai/frontend/web/src/features/dynamicPrompts/store/dynamicPromptsSlice.ts
index 27925c833f..d73db3e810 100644
--- a/invokeai/frontend/web/src/features/dynamicPrompts/store/dynamicPromptsSlice.ts
+++ b/invokeai/frontend/web/src/features/dynamicPrompts/store/dynamicPromptsSlice.ts
@@ -4,7 +4,7 @@ import type { PersistConfig, RootState } from 'app/store/store';
 import { z } from 'zod';
 
 const zSeedBehaviour = z.enum(['PER_ITERATION', 'PER_PROMPT']);
-export type SeedBehaviour = z.infer<typeof zSeedBehaviour>;
+type SeedBehaviour = z.infer<typeof zSeedBehaviour>;
 export const isSeedBehaviour = (v: unknown): v is SeedBehaviour => zSeedBehaviour.safeParse(v).success;
 
 interface DynamicPromptsState {
diff --git a/invokeai/frontend/web/src/features/embedding/usePrompt.ts b/invokeai/frontend/web/src/features/embedding/usePrompt.ts
index c3a708e6ce..b5f245d7f2 100644
--- a/invokeai/frontend/web/src/features/embedding/usePrompt.ts
+++ b/invokeai/frontend/web/src/features/embedding/usePrompt.ts
@@ -4,7 +4,7 @@ import type { ChangeEventHandler, KeyboardEventHandler, RefObject } from 'react'
 import { useCallback } from 'react';
 import { flushSync } from 'react-dom';
 
-export type UseInsertEmbeddingArg = {
+type UseInsertEmbeddingArg = {
   prompt: string;
   textareaRef: RefObject<HTMLTextAreaElement>;
   onChange: (v: string) => void;
diff --git a/invokeai/frontend/web/src/features/gallery/components/ImageGrid/types.ts b/invokeai/frontend/web/src/features/gallery/components/ImageGrid/types.ts
index e43a55270e..1b7286d6a0 100644
--- a/invokeai/frontend/web/src/features/gallery/components/ImageGrid/types.ts
+++ b/invokeai/frontend/web/src/features/gallery/components/ImageGrid/types.ts
@@ -2,7 +2,7 @@ import { atom } from 'nanostores';
 import type { RefObject } from 'react';
 import type { ListRange, VirtuosoGridHandle } from 'react-virtuoso';
 
-export type VirtuosoGridRefs = {
+type VirtuosoGridRefs = {
   virtuosoRef?: RefObject<VirtuosoGridHandle>;
   rootRef?: RefObject<HTMLDivElement>;
   virtuosoRangeRef?: RefObject<ListRange>;
diff --git a/invokeai/frontend/web/src/features/gallery/hooks/useGalleryNavigation.ts b/invokeai/frontend/web/src/features/gallery/hooks/useGalleryNavigation.ts
index b6fdb183e6..1464c23285 100644
--- a/invokeai/frontend/web/src/features/gallery/hooks/useGalleryNavigation.ts
+++ b/invokeai/frontend/web/src/features/gallery/hooks/useGalleryNavigation.ts
@@ -105,7 +105,7 @@ const getImageFuncs = {
   down: getDownImage,
 };
 
-export type UseGalleryNavigationReturn = {
+type UseGalleryNavigationReturn = {
   handleLeftImage: () => void;
   handleRightImage: () => void;
   handleUpImage: () => void;
diff --git a/invokeai/frontend/web/src/features/hrf/store/hrfSlice.ts b/invokeai/frontend/web/src/features/hrf/store/hrfSlice.ts
index 9b6e1f944e..46a562d34f 100644
--- a/invokeai/frontend/web/src/features/hrf/store/hrfSlice.ts
+++ b/invokeai/frontend/web/src/features/hrf/store/hrfSlice.ts
@@ -3,7 +3,7 @@ import { createSlice } from '@reduxjs/toolkit';
 import type { PersistConfig, RootState } from 'app/store/store';
 import type { ParameterHRFMethod, ParameterStrength } from 'features/parameters/types/parameterSchemas';
 
-export interface HRFState {
+interface HRFState {
   _version: 1;
   hrfEnabled: boolean;
   hrfStrength: ParameterStrength;
diff --git a/invokeai/frontend/web/src/features/lora/store/loraSlice.ts b/invokeai/frontend/web/src/features/lora/store/loraSlice.ts
index c6518c214e..7d6a2fccaf 100644
--- a/invokeai/frontend/web/src/features/lora/store/loraSlice.ts
+++ b/invokeai/frontend/web/src/features/lora/store/loraSlice.ts
@@ -16,7 +16,7 @@ export const defaultLoRAConfig: Pick<LoRA, 'weight' | 'isEnabled'> = {
   isEnabled: true,
 };
 
-export type LoraState = {
+type LoraState = {
   _version: 1;
   loras: Record<string, LoRA>;
 };
diff --git a/invokeai/frontend/web/src/features/metadata/types.ts b/invokeai/frontend/web/src/features/metadata/types.ts
index aa8d334521..7b102fa160 100644
--- a/invokeai/frontend/web/src/features/metadata/types.ts
+++ b/invokeai/frontend/web/src/features/metadata/types.ts
@@ -11,13 +11,6 @@ export type MetadataRenderValueFunc<T> = (value: T) => Promise<React.ReactNode>;
  */
 export type MetadataGetLabelFunc = () => string;
 
-export type MetadataParseOptions = {
-  toastOnFailure?: boolean;
-  toastOnSuccess?: boolean;
-};
-
-export type MetadataRecallOptions = MetadataParseOptions;
-
 /**
  * A function that recalls a parsed and validated metadata value.
  *
@@ -119,7 +112,7 @@ export type MetadataHandlers<TValue = unknown, TItem = unknown> = {
 // type MetadataHandlersInferItem<TValue> = TValue extends Array<infer TItem> ? MetadataParseFunc<TItem> : never
 // While this works for the types as expected, I couldn't satisfy TS in the implementations of the handlers.
 
-export type BuildMetadataHandlersArg<TValue, TItem> = {
+type BuildMetadataHandlersArg<TValue, TItem> = {
   parser: MetadataParseFunc<TValue>;
   itemParser?: MetadataParseFunc<TItem>;
   recaller?: MetadataRecallFunc<TValue>;
diff --git a/invokeai/frontend/web/src/features/metadata/util/modelFetchingHelpers.ts b/invokeai/frontend/web/src/features/metadata/util/modelFetchingHelpers.ts
index 98aa633259..3c0745917a 100644
--- a/invokeai/frontend/web/src/features/metadata/util/modelFetchingHelpers.ts
+++ b/invokeai/frontend/web/src/features/metadata/util/modelFetchingHelpers.ts
@@ -7,7 +7,7 @@ import type { AnyModelConfig, BaseModelType, ModelType } from 'services/api/type
 /**
  * Raised when a model config is unable to be fetched.
  */
-export class ModelConfigNotFoundError extends Error {
+class ModelConfigNotFoundError extends Error {
   /**
    * Create ModelConfigNotFoundError
    * @param {String} message
@@ -58,11 +58,7 @@ export const fetchModelConfig = async (key: string): Promise<AnyModelConfig> =>
  * @returns A promise that resolves to the model config.
  * @throws {ModelConfigNotFoundError} If the model config is unable to be fetched.
  */
-export const fetchModelConfigByAttrs = async (
-  name: string,
-  base: BaseModelType,
-  type: ModelType
-): Promise<AnyModelConfig> => {
+const fetchModelConfigByAttrs = async (name: string, base: BaseModelType, type: ModelType): Promise<AnyModelConfig> => {
   const { dispatch } = getStore();
   try {
     const req = dispatch(modelsApi.endpoints.getModelConfigByAttrs.initiate({ name, base, type }));
diff --git a/invokeai/frontend/web/src/features/metadata/util/parsers.ts b/invokeai/frontend/web/src/features/metadata/util/parsers.ts
index eba51f4fd6..30ec37991c 100644
--- a/invokeai/frontend/web/src/features/metadata/util/parsers.ts
+++ b/invokeai/frontend/web/src/features/metadata/util/parsers.ts
@@ -78,7 +78,7 @@ export const MetadataParseFailedToken = Symbol('failed');
 /**
  * Raised when metadata parsing fails.
  */
-export class MetadataParseError extends Error {
+class MetadataParseError extends Error {
   /**
    * Create MetadataParseError
    * @param {String} message
diff --git a/invokeai/frontend/web/src/features/nodes/hooks/useConnectionState.ts b/invokeai/frontend/web/src/features/nodes/hooks/useConnectionState.ts
index 97b96f323a..f0a512277a 100644
--- a/invokeai/frontend/web/src/features/nodes/hooks/useConnectionState.ts
+++ b/invokeai/frontend/web/src/features/nodes/hooks/useConnectionState.ts
@@ -11,7 +11,7 @@ const selectIsConnectionInProgress = createSelector(
   (nodes) => nodes.connectionStartFieldType !== null && nodes.connectionStartParams !== null
 );
 
-export type UseConnectionStateProps = {
+type UseConnectionStateProps = {
   nodeId: string;
   fieldName: string;
   kind: 'inputs' | 'outputs';
diff --git a/invokeai/frontend/web/src/features/nodes/store/types.ts b/invokeai/frontend/web/src/features/nodes/store/types.ts
index 1a040d2c70..3f7d210dcb 100644
--- a/invokeai/frontend/web/src/features/nodes/store/types.ts
+++ b/invokeai/frontend/web/src/features/nodes/store/types.ts
@@ -45,7 +45,3 @@ export type WorkflowsState = Omit<WorkflowV3, 'nodes' | 'edges'> & {
   mode: WorkflowMode;
   originalExposedFieldValues: FieldIdentifierWithValue[];
 };
-
-export type NodeTemplatesState = {
-  templates: Record<string, InvocationTemplate>;
-};
diff --git a/invokeai/frontend/web/src/features/nodes/types/common.ts b/invokeai/frontend/web/src/features/nodes/types/common.ts
index 82c41096d9..f665c7780d 100644
--- a/invokeai/frontend/web/src/features/nodes/types/common.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/common.ts
@@ -55,16 +55,6 @@ export type SchedulerField = z.infer<typeof zSchedulerField>;
 
 // #region Model-related schemas
 const zBaseModel = z.enum(['any', 'sd-1', 'sd-2', 'sdxl', 'sdxl-refiner']);
-const zModelType = z.enum([
-  'main',
-  'vae',
-  'lora',
-  'controlnet',
-  'embedding',
-  'ip_adapter',
-  'clip_vision',
-  't2i_adapter',
-]);
 const zModelIdentifier = z.object({
   key: z.string().min(1),
 });
@@ -75,8 +65,7 @@ export const isModelIdentifierV2 = (field: unknown): field is ModelIdentifierV2
 const zModelFieldBase = zModelIdentifier;
 export const zModelIdentifierWithBase = zModelIdentifier.extend({ base: zBaseModel });
 export type BaseModel = z.infer<typeof zBaseModel>;
-export type ModelType = z.infer<typeof zModelType>;
-export type ModelIdentifier = z.infer<typeof zModelIdentifier>;
+type ModelIdentifier = z.infer<typeof zModelIdentifier>;
 export type ModelIdentifierWithBase = z.infer<typeof zModelIdentifierWithBase>;
 // #endregion
 
diff --git a/invokeai/frontend/web/src/features/nodes/types/field.ts b/invokeai/frontend/web/src/features/nodes/types/field.ts
index 83dbf27e1e..39fa903fd7 100644
--- a/invokeai/frontend/web/src/features/nodes/types/field.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/field.ts
@@ -30,17 +30,11 @@ import { zBoardField, zColorField, zImageField, zModelIdentifierWithBase, zSched
 
 // #region Base schemas & misc
 const zFieldInput = z.enum(['connection', 'direct', 'any']);
-export type FieldInput = z.infer<typeof zFieldInput>;
-
 const zFieldUIComponent = z.enum(['none', 'textarea', 'slider']);
-export type FieldUIComponent = z.infer<typeof zFieldUIComponent>;
-
 const zFieldInputInstanceBase = z.object({
   name: z.string().trim().min(1),
   label: z.string().nullish(),
 });
-export type FieldInputInstanceBase = z.infer<typeof zFieldInputInstanceBase>;
-
 const zFieldTemplateBase = z.object({
   name: z.string().min(1),
   title: z.string().min(1),
@@ -59,9 +53,6 @@ const zFieldInputTemplateBase = zFieldTemplateBase.extend({
 const zFieldOutputTemplateBase = zFieldTemplateBase.extend({
   fieldKind: z.literal('output'),
 });
-export type FieldTemplateBase = z.infer<typeof zFieldTemplateBase>;
-export type FieldInputTemplateBase = z.infer<typeof zFieldInputTemplateBase>;
-export type FieldOutputTemplateBase = z.infer<typeof zFieldOutputTemplateBase>;
 
 const zFieldTypeBase = z.object({
   isCollection: z.boolean(),
@@ -95,7 +86,6 @@ const zIntegerFieldInputTemplate = zFieldInputTemplateBase.extend({
 const zIntegerFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zIntegerFieldType,
 });
-export type IntegerFieldType = z.infer<typeof zIntegerFieldType>;
 export type IntegerFieldValue = z.infer<typeof zIntegerFieldValue>;
 export type IntegerFieldInputInstance = z.infer<typeof zIntegerFieldInputInstance>;
 export type IntegerFieldInputTemplate = z.infer<typeof zIntegerFieldInputTemplate>;
@@ -125,11 +115,9 @@ const zFloatFieldInputTemplate = zFieldInputTemplateBase.extend({
 const zFloatFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zFloatFieldType,
 });
-export type FloatFieldType = z.infer<typeof zFloatFieldType>;
 export type FloatFieldValue = z.infer<typeof zFloatFieldValue>;
 export type FloatFieldInputInstance = z.infer<typeof zFloatFieldInputInstance>;
 export type FloatFieldInputTemplate = z.infer<typeof zFloatFieldInputTemplate>;
-export type FloatFieldOutputTemplate = z.infer<typeof zFloatFieldOutputTemplate>;
 export const isFloatFieldInputInstance = (val: unknown): val is FloatFieldInputInstance =>
   zFloatFieldInputInstance.safeParse(val).success;
 export const isFloatFieldInputTemplate = (val: unknown): val is FloatFieldInputTemplate =>
@@ -154,11 +142,9 @@ const zStringFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zStringFieldType,
 });
 
-export type StringFieldType = z.infer<typeof zStringFieldType>;
 export type StringFieldValue = z.infer<typeof zStringFieldValue>;
 export type StringFieldInputInstance = z.infer<typeof zStringFieldInputInstance>;
 export type StringFieldInputTemplate = z.infer<typeof zStringFieldInputTemplate>;
-export type StringFieldOutputTemplate = z.infer<typeof zStringFieldOutputTemplate>;
 export const isStringFieldInputInstance = (val: unknown): val is StringFieldInputInstance =>
   zStringFieldInputInstance.safeParse(val).success;
 export const isStringFieldInputTemplate = (val: unknown): val is StringFieldInputTemplate =>
@@ -180,11 +166,9 @@ const zBooleanFieldInputTemplate = zFieldInputTemplateBase.extend({
 const zBooleanFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zBooleanFieldType,
 });
-export type BooleanFieldType = z.infer<typeof zBooleanFieldType>;
 export type BooleanFieldValue = z.infer<typeof zBooleanFieldValue>;
 export type BooleanFieldInputInstance = z.infer<typeof zBooleanFieldInputInstance>;
 export type BooleanFieldInputTemplate = z.infer<typeof zBooleanFieldInputTemplate>;
-export type BooleanFieldOutputTemplate = z.infer<typeof zBooleanFieldOutputTemplate>;
 export const isBooleanFieldInputInstance = (val: unknown): val is BooleanFieldInputInstance =>
   zBooleanFieldInputInstance.safeParse(val).success;
 export const isBooleanFieldInputTemplate = (val: unknown): val is BooleanFieldInputTemplate =>
@@ -208,11 +192,9 @@ const zEnumFieldInputTemplate = zFieldInputTemplateBase.extend({
 const zEnumFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zEnumFieldType,
 });
-export type EnumFieldType = z.infer<typeof zEnumFieldType>;
 export type EnumFieldValue = z.infer<typeof zEnumFieldValue>;
 export type EnumFieldInputInstance = z.infer<typeof zEnumFieldInputInstance>;
 export type EnumFieldInputTemplate = z.infer<typeof zEnumFieldInputTemplate>;
-export type EnumFieldOutputTemplate = z.infer<typeof zEnumFieldOutputTemplate>;
 export const isEnumFieldInputInstance = (val: unknown): val is EnumFieldInputInstance =>
   zEnumFieldInputInstance.safeParse(val).success;
 export const isEnumFieldInputTemplate = (val: unknown): val is EnumFieldInputTemplate =>
@@ -234,11 +216,9 @@ const zImageFieldInputTemplate = zFieldInputTemplateBase.extend({
 const zImageFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zImageFieldType,
 });
-export type ImageFieldType = z.infer<typeof zImageFieldType>;
 export type ImageFieldValue = z.infer<typeof zImageFieldValue>;
 export type ImageFieldInputInstance = z.infer<typeof zImageFieldInputInstance>;
 export type ImageFieldInputTemplate = z.infer<typeof zImageFieldInputTemplate>;
-export type ImageFieldOutputTemplate = z.infer<typeof zImageFieldOutputTemplate>;
 export const isImageFieldInputInstance = (val: unknown): val is ImageFieldInputInstance =>
   zImageFieldInputInstance.safeParse(val).success;
 export const isImageFieldInputTemplate = (val: unknown): val is ImageFieldInputTemplate =>
@@ -260,11 +240,9 @@ const zBoardFieldInputTemplate = zFieldInputTemplateBase.extend({
 const zBoardFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zBoardFieldType,
 });
-export type BoardFieldType = z.infer<typeof zBoardFieldType>;
 export type BoardFieldValue = z.infer<typeof zBoardFieldValue>;
 export type BoardFieldInputInstance = z.infer<typeof zBoardFieldInputInstance>;
 export type BoardFieldInputTemplate = z.infer<typeof zBoardFieldInputTemplate>;
-export type BoardFieldOutputTemplate = z.infer<typeof zBoardFieldOutputTemplate>;
 export const isBoardFieldInputInstance = (val: unknown): val is BoardFieldInputInstance =>
   zBoardFieldInputInstance.safeParse(val).success;
 export const isBoardFieldInputTemplate = (val: unknown): val is BoardFieldInputTemplate =>
@@ -286,11 +264,9 @@ const zColorFieldInputTemplate = zFieldInputTemplateBase.extend({
 const zColorFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zColorFieldType,
 });
-export type ColorFieldType = z.infer<typeof zColorFieldType>;
 export type ColorFieldValue = z.infer<typeof zColorFieldValue>;
 export type ColorFieldInputInstance = z.infer<typeof zColorFieldInputInstance>;
 export type ColorFieldInputTemplate = z.infer<typeof zColorFieldInputTemplate>;
-export type ColorFieldOutputTemplate = z.infer<typeof zColorFieldOutputTemplate>;
 export const isColorFieldInputInstance = (val: unknown): val is ColorFieldInputInstance =>
   zColorFieldInputInstance.safeParse(val).success;
 export const isColorFieldInputTemplate = (val: unknown): val is ColorFieldInputTemplate =>
@@ -312,11 +288,9 @@ const zMainModelFieldInputTemplate = zFieldInputTemplateBase.extend({
 const zMainModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zMainModelFieldType,
 });
-export type MainModelFieldType = z.infer<typeof zMainModelFieldType>;
 export type MainModelFieldValue = z.infer<typeof zMainModelFieldValue>;
 export type MainModelFieldInputInstance = z.infer<typeof zMainModelFieldInputInstance>;
 export type MainModelFieldInputTemplate = z.infer<typeof zMainModelFieldInputTemplate>;
-export type MainModelFieldOutputTemplate = z.infer<typeof zMainModelFieldOutputTemplate>;
 export const isMainModelFieldInputInstance = (val: unknown): val is MainModelFieldInputInstance =>
   zMainModelFieldInputInstance.safeParse(val).success;
 export const isMainModelFieldInputTemplate = (val: unknown): val is MainModelFieldInputTemplate =>
@@ -338,11 +312,8 @@ const zSDXLMainModelFieldInputTemplate = zFieldInputTemplateBase.extend({
 const zSDXLMainModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zSDXLMainModelFieldType,
 });
-export type SDXLMainModelFieldType = z.infer<typeof zSDXLMainModelFieldType>;
-export type SDXLMainModelFieldValue = z.infer<typeof zSDXLMainModelFieldValue>;
 export type SDXLMainModelFieldInputInstance = z.infer<typeof zSDXLMainModelFieldInputInstance>;
 export type SDXLMainModelFieldInputTemplate = z.infer<typeof zSDXLMainModelFieldInputTemplate>;
-export type SDXLMainModelFieldOutputTemplate = z.infer<typeof zSDXLMainModelFieldOutputTemplate>;
 export const isSDXLMainModelFieldInputInstance = (val: unknown): val is SDXLMainModelFieldInputInstance =>
   zSDXLMainModelFieldInputInstance.safeParse(val).success;
 export const isSDXLMainModelFieldInputTemplate = (val: unknown): val is SDXLMainModelFieldInputTemplate =>
@@ -364,11 +335,9 @@ const zSDXLRefinerModelFieldInputTemplate = zFieldInputTemplateBase.extend({
 const zSDXLRefinerModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zSDXLRefinerModelFieldType,
 });
-export type SDXLRefinerModelFieldType = z.infer<typeof zSDXLRefinerModelFieldType>;
 export type SDXLRefinerModelFieldValue = z.infer<typeof zSDXLRefinerModelFieldValue>;
 export type SDXLRefinerModelFieldInputInstance = z.infer<typeof zSDXLRefinerModelFieldInputInstance>;
 export type SDXLRefinerModelFieldInputTemplate = z.infer<typeof zSDXLRefinerModelFieldInputTemplate>;
-export type SDXLRefinerModelFieldOutputTemplate = z.infer<typeof zSDXLRefinerModelFieldOutputTemplate>;
 export const isSDXLRefinerModelFieldInputInstance = (val: unknown): val is SDXLRefinerModelFieldInputInstance =>
   zSDXLRefinerModelFieldInputInstance.safeParse(val).success;
 export const isSDXLRefinerModelFieldInputTemplate = (val: unknown): val is SDXLRefinerModelFieldInputTemplate =>
@@ -390,11 +359,9 @@ const zVAEModelFieldInputTemplate = zFieldInputTemplateBase.extend({
 const zVAEModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zVAEModelFieldType,
 });
-export type VAEModelFieldType = z.infer<typeof zVAEModelFieldType>;
 export type VAEModelFieldValue = z.infer<typeof zVAEModelFieldValue>;
 export type VAEModelFieldInputInstance = z.infer<typeof zVAEModelFieldInputInstance>;
 export type VAEModelFieldInputTemplate = z.infer<typeof zVAEModelFieldInputTemplate>;
-export type VAEModelFieldOutputTemplate = z.infer<typeof zVAEModelFieldOutputTemplate>;
 export const isVAEModelFieldInputInstance = (val: unknown): val is VAEModelFieldInputInstance =>
   zVAEModelFieldInputInstance.safeParse(val).success;
 export const isVAEModelFieldInputTemplate = (val: unknown): val is VAEModelFieldInputTemplate =>
@@ -416,11 +383,9 @@ const zLoRAModelFieldInputTemplate = zFieldInputTemplateBase.extend({
 const zLoRAModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zLoRAModelFieldType,
 });
-export type LoRAModelFieldType = z.infer<typeof zLoRAModelFieldType>;
 export type LoRAModelFieldValue = z.infer<typeof zLoRAModelFieldValue>;
 export type LoRAModelFieldInputInstance = z.infer<typeof zLoRAModelFieldInputInstance>;
 export type LoRAModelFieldInputTemplate = z.infer<typeof zLoRAModelFieldInputTemplate>;
-export type LoRAModelFieldOutputTemplate = z.infer<typeof zLoRAModelFieldOutputTemplate>;
 export const isLoRAModelFieldInputInstance = (val: unknown): val is LoRAModelFieldInputInstance =>
   zLoRAModelFieldInputInstance.safeParse(val).success;
 export const isLoRAModelFieldInputTemplate = (val: unknown): val is LoRAModelFieldInputTemplate =>
@@ -442,11 +407,9 @@ const zControlNetModelFieldInputTemplate = zFieldInputTemplateBase.extend({
 const zControlNetModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zControlNetModelFieldType,
 });
-export type ControlNetModelFieldType = z.infer<typeof zControlNetModelFieldType>;
 export type ControlNetModelFieldValue = z.infer<typeof zControlNetModelFieldValue>;
 export type ControlNetModelFieldInputInstance = z.infer<typeof zControlNetModelFieldInputInstance>;
 export type ControlNetModelFieldInputTemplate = z.infer<typeof zControlNetModelFieldInputTemplate>;
-export type ControlNetModelFieldOutputTemplate = z.infer<typeof zControlNetModelFieldOutputTemplate>;
 export const isControlNetModelFieldInputInstance = (val: unknown): val is ControlNetModelFieldInputInstance =>
   zControlNetModelFieldInputInstance.safeParse(val).success;
 export const isControlNetModelFieldInputTemplate = (val: unknown): val is ControlNetModelFieldInputTemplate =>
@@ -468,11 +431,9 @@ const zIPAdapterModelFieldInputTemplate = zFieldInputTemplateBase.extend({
 const zIPAdapterModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zIPAdapterModelFieldType,
 });
-export type IPAdapterModelFieldType = z.infer<typeof zIPAdapterModelFieldType>;
 export type IPAdapterModelFieldValue = z.infer<typeof zIPAdapterModelFieldValue>;
 export type IPAdapterModelFieldInputInstance = z.infer<typeof zIPAdapterModelFieldInputInstance>;
 export type IPAdapterModelFieldInputTemplate = z.infer<typeof zIPAdapterModelFieldInputTemplate>;
-export type IPAdapterModelFieldOutputTemplate = z.infer<typeof zIPAdapterModelFieldOutputTemplate>;
 export const isIPAdapterModelFieldInputInstance = (val: unknown): val is IPAdapterModelFieldInputInstance =>
   zIPAdapterModelFieldInputInstance.safeParse(val).success;
 export const isIPAdapterModelFieldInputTemplate = (val: unknown): val is IPAdapterModelFieldInputTemplate =>
@@ -494,11 +455,9 @@ const zT2IAdapterModelFieldInputTemplate = zFieldInputTemplateBase.extend({
 const zT2IAdapterModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zT2IAdapterModelFieldType,
 });
-export type T2IAdapterModelFieldType = z.infer<typeof zT2IAdapterModelFieldType>;
 export type T2IAdapterModelFieldValue = z.infer<typeof zT2IAdapterModelFieldValue>;
 export type T2IAdapterModelFieldInputInstance = z.infer<typeof zT2IAdapterModelFieldInputInstance>;
 export type T2IAdapterModelFieldInputTemplate = z.infer<typeof zT2IAdapterModelFieldInputTemplate>;
-export type T2IAdapterModelFieldOutputTemplate = z.infer<typeof zT2IAdapterModelFieldOutputTemplate>;
 export const isT2IAdapterModelFieldInputInstance = (val: unknown): val is T2IAdapterModelFieldInputInstance =>
   zT2IAdapterModelFieldInputInstance.safeParse(val).success;
 export const isT2IAdapterModelFieldInputTemplate = (val: unknown): val is T2IAdapterModelFieldInputTemplate =>
@@ -520,11 +479,9 @@ const zSchedulerFieldInputTemplate = zFieldInputTemplateBase.extend({
 const zSchedulerFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zSchedulerFieldType,
 });
-export type SchedulerFieldType = z.infer<typeof zSchedulerFieldType>;
 export type SchedulerFieldValue = z.infer<typeof zSchedulerFieldValue>;
 export type SchedulerFieldInputInstance = z.infer<typeof zSchedulerFieldInputInstance>;
 export type SchedulerFieldInputTemplate = z.infer<typeof zSchedulerFieldInputTemplate>;
-export type SchedulerFieldOutputTemplate = z.infer<typeof zSchedulerFieldOutputTemplate>;
 export const isSchedulerFieldInputInstance = (val: unknown): val is SchedulerFieldInputInstance =>
   zSchedulerFieldInputInstance.safeParse(val).success;
 export const isSchedulerFieldInputTemplate = (val: unknown): val is SchedulerFieldInputTemplate =>
@@ -559,11 +516,7 @@ const zStatelessFieldOutputTemplate = zFieldOutputTemplateBase.extend({
   type: zStatelessFieldType,
 });
 
-export type StatelessFieldType = z.infer<typeof zStatelessFieldType>;
-export type StatelessFieldValue = z.infer<typeof zStatelessFieldValue>;
-export type StatelessFieldInputInstance = z.infer<typeof zStatelessFieldInputInstance>;
 export type StatelessFieldInputTemplate = z.infer<typeof zStatelessFieldInputTemplate>;
-export type StatelessFieldOutputTemplate = z.infer<typeof zStatelessFieldOutputTemplate>;
 // #endregion
 
 /**
@@ -655,7 +608,6 @@ const zStatefulFieldInputInstance = z.union([
   zColorFieldInputInstance,
   zSchedulerFieldInputInstance,
 ]);
-export type StatefulFieldInputInstance = z.infer<typeof zStatefulFieldInputInstance>;
 
 export const zFieldInputInstance = z.union([zStatefulFieldInputInstance, zStatelessFieldInputInstance]);
 export type FieldInputInstance = z.infer<typeof zFieldInputInstance>;
@@ -684,7 +636,6 @@ const zStatefulFieldInputTemplate = z.union([
   zSchedulerFieldInputTemplate,
   zStatelessFieldInputTemplate,
 ]);
-export type StatefulFieldInputTemplate = z.infer<typeof zFieldInputTemplate>;
 
 export const zFieldInputTemplate = z.union([zStatefulFieldInputTemplate, zStatelessFieldInputTemplate]);
 export type FieldInputTemplate = z.infer<typeof zFieldInputTemplate>;
@@ -712,7 +663,6 @@ const zStatefulFieldOutputTemplate = z.union([
   zColorFieldOutputTemplate,
   zSchedulerFieldOutputTemplate,
 ]);
-export type StatefulFieldOutputTemplate = z.infer<typeof zStatefulFieldOutputTemplate>;
 
 export const zFieldOutputTemplate = z.union([zStatefulFieldOutputTemplate, zStatelessFieldOutputTemplate]);
 export type FieldOutputTemplate = z.infer<typeof zFieldOutputTemplate>;
diff --git a/invokeai/frontend/web/src/features/nodes/types/invocation.ts b/invokeai/frontend/web/src/features/nodes/types/invocation.ts
index 52db5de5ee..66a3db62bf 100644
--- a/invokeai/frontend/web/src/features/nodes/types/invocation.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/invocation.ts
@@ -53,8 +53,8 @@ const zAnyNodeData = z.union([zInvocationNodeData, zNotesNodeData, zCurrentImage
 
 export type NotesNodeData = z.infer<typeof zNotesNodeData>;
 export type InvocationNodeData = z.infer<typeof zInvocationNodeData>;
-export type CurrentImageNodeData = z.infer<typeof zCurrentImageNodeData>;
-export type AnyNodeData = z.infer<typeof zAnyNodeData>;
+type CurrentImageNodeData = z.infer<typeof zCurrentImageNodeData>;
+type AnyNodeData = z.infer<typeof zAnyNodeData>;
 
 export type InvocationNode = Node<InvocationNodeData, 'invocation'>;
 export type NotesNode = Node<NotesNodeData, 'notes'>;
@@ -79,13 +79,12 @@ const zNodeExecutionState = z.object({
   outputs: z.array(z.any()),
 });
 export type NodeExecutionState = z.infer<typeof zNodeExecutionState>;
-export type NodeStatus = z.infer<typeof zNodeStatus>;
 // #endregion
 
 // #region Edges
 const zInvocationNodeEdgeExtra = z.object({
   type: z.union([z.literal('default'), z.literal('collapsed')]),
 });
-export type InvocationNodeEdgeExtra = z.infer<typeof zInvocationNodeEdgeExtra>;
+type InvocationNodeEdgeExtra = z.infer<typeof zInvocationNodeEdgeExtra>;
 export type InvocationNodeEdge = Edge<InvocationNodeEdgeExtra>;
 // #endregion
diff --git a/invokeai/frontend/web/src/features/nodes/types/openapi.ts b/invokeai/frontend/web/src/features/nodes/types/openapi.ts
index 83d774439a..8a8a16f1fd 100644
--- a/invokeai/frontend/web/src/features/nodes/types/openapi.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/openapi.ts
@@ -7,7 +7,7 @@ import type {
 
 // Janky customization of OpenAPI Schema :/
 
-export type InvocationSchemaExtra = InvocationJSONSchemaExtra & {
+type InvocationSchemaExtra = InvocationJSONSchemaExtra & {
   output: OpenAPIV3_1.ReferenceObject; // the output of the invocation
   title: string;
   category?: string;
@@ -26,14 +26,10 @@ export type InvocationSchemaExtra = InvocationJSONSchemaExtra & {
   };
 };
 
-export type InvocationSchemaType = {
-  default: string; // the type of the invocation
-};
-
-export type InvocationBaseSchemaObject = Omit<OpenAPIV3_1.BaseSchemaObject, 'title' | 'type' | 'properties'> &
+type InvocationBaseSchemaObject = Omit<OpenAPIV3_1.BaseSchemaObject, 'title' | 'type' | 'properties'> &
   InvocationSchemaExtra;
 
-export type InvocationOutputSchemaObject = Omit<OpenAPIV3_1.SchemaObject, 'properties'> & {
+type InvocationOutputSchemaObject = Omit<OpenAPIV3_1.SchemaObject, 'properties'> & {
   properties: OpenAPIV3_1.SchemaObject['properties'] & {
     type: Omit<OpenAPIV3_1.SchemaObject, 'default'> & {
       default: string;
@@ -47,11 +43,11 @@ export type InvocationFieldSchema = OpenAPIV3_1.SchemaObject & InputFieldJSONSch
 
 export type OpenAPIV3_1SchemaOrRef = OpenAPIV3_1.ReferenceObject | OpenAPIV3_1.SchemaObject;
 
-export interface ArraySchemaObject extends InvocationBaseSchemaObject {
+interface ArraySchemaObject extends InvocationBaseSchemaObject {
   type: OpenAPIV3_1.ArraySchemaObjectType;
   items: OpenAPIV3_1.ReferenceObject | OpenAPIV3_1.SchemaObject;
 }
-export interface NonArraySchemaObject extends InvocationBaseSchemaObject {
+interface NonArraySchemaObject extends InvocationBaseSchemaObject {
   type?: OpenAPIV3_1.NonArraySchemaObjectType;
 }
 
diff --git a/invokeai/frontend/web/src/features/nodes/types/v2/common.ts b/invokeai/frontend/web/src/features/nodes/types/v2/common.ts
index b524474379..8613076132 100644
--- a/invokeai/frontend/web/src/features/nodes/types/v2/common.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/v2/common.ts
@@ -4,12 +4,10 @@ import { z } from 'zod';
 export const zImageField = z.object({
   image_name: z.string().trim().min(1),
 });
-export type ImageField = z.infer<typeof zImageField>;
 
 export const zBoardField = z.object({
   board_id: z.string().trim().min(1),
 });
-export type BoardField = z.infer<typeof zBoardField>;
 
 export const zColorField = z.object({
   r: z.number().int().min(0).max(255),
@@ -17,10 +15,6 @@ export const zColorField = z.object({
   b: z.number().int().min(0).max(255),
   a: z.number().int().min(0).max(255),
 });
-export type ColorField = z.infer<typeof zColorField>;
-
-export const zClassification = z.enum(['stable', 'beta', 'prototype']);
-export type Classification = z.infer<typeof zClassification>;
 
 export const zSchedulerField = z.enum([
   'euler',
@@ -47,19 +41,15 @@ export const zSchedulerField = z.enum([
   'kdpm_2_a',
   'lcm',
 ]);
-export type SchedulerField = z.infer<typeof zSchedulerField>;
 // #endregion
 
 // #region Model-related schemas
-export const zBaseModel = z.enum(['any', 'sd-1', 'sd-2', 'sdxl', 'sdxl-refiner']);
-export const zModelType = z.enum(['main', 'vae', 'lora', 'controlnet', 'embedding']);
-export const zModelName = z.string().min(3);
+const zBaseModel = z.enum(['any', 'sd-1', 'sd-2', 'sdxl', 'sdxl-refiner']);
+const zModelName = z.string().min(3);
 export const zModelIdentifier = z.object({
   model_name: zModelName,
   base_model: zBaseModel,
 });
-export type BaseModel = z.infer<typeof zBaseModel>;
-export type ModelType = z.infer<typeof zModelType>;
 export type ModelIdentifier = z.infer<typeof zModelIdentifier>;
 
 export const zMainModelField = z.object({
@@ -67,122 +57,10 @@ export const zMainModelField = z.object({
   base_model: zBaseModel,
   model_type: z.literal('main'),
 });
-export const zSDXLRefinerModelField = z.object({
-  model_name: z.string().min(1),
-  base_model: z.literal('sdxl-refiner'),
-  model_type: z.literal('main'),
-});
-export type MainModelField = z.infer<typeof zMainModelField>;
-export type SDXLRefinerModelField = z.infer<typeof zSDXLRefinerModelField>;
-
-export const zSubModelType = z.enum([
-  'unet',
-  'text_encoder',
-  'text_encoder_2',
-  'tokenizer',
-  'tokenizer_2',
-  'vae',
-  'vae_decoder',
-  'vae_encoder',
-  'scheduler',
-  'safety_checker',
-]);
-export type SubModelType = z.infer<typeof zSubModelType>;
 
 export const zVAEModelField = zModelIdentifier;
-
-export const zModelInfo = zModelIdentifier.extend({
-  model_type: zModelType,
-  submodel: zSubModelType.optional(),
-});
-export type ModelInfo = z.infer<typeof zModelInfo>;
-
 export const zLoRAModelField = zModelIdentifier;
-export type LoRAModelField = z.infer<typeof zLoRAModelField>;
-
 export const zControlNetModelField = zModelIdentifier;
-export type ControlNetModelField = z.infer<typeof zControlNetModelField>;
-
 export const zIPAdapterModelField = zModelIdentifier;
-export type IPAdapterModelField = z.infer<typeof zIPAdapterModelField>;
-
 export const zT2IAdapterModelField = zModelIdentifier;
-export type T2IAdapterModelField = z.infer<typeof zT2IAdapterModelField>;
-
-export const zLoraInfo = zModelInfo.extend({
-  weight: z.number().optional(),
-});
-export type LoraInfo = z.infer<typeof zLoraInfo>;
-
-export const zUNetField = z.object({
-  unet: zModelInfo,
-  scheduler: zModelInfo,
-  loras: z.array(zLoraInfo),
-});
-export type UNetField = z.infer<typeof zUNetField>;
-
-export const zCLIPField = z.object({
-  tokenizer: zModelInfo,
-  text_encoder: zModelInfo,
-  skipped_layers: z.number(),
-  loras: z.array(zLoraInfo),
-});
-export type CLIPField = z.infer<typeof zCLIPField>;
-
-export const zVAEField = z.object({
-  vae: zModelInfo,
-});
-export type VAEField = z.infer<typeof zVAEField>;
-// #endregion
-
-// #region Control Adapters
-export const zControlField = z.object({
-  image: zImageField,
-  control_model: zControlNetModelField,
-  control_weight: z.union([z.number(), z.array(z.number())]).optional(),
-  begin_step_percent: z.number().optional(),
-  end_step_percent: z.number().optional(),
-  control_mode: z.enum(['balanced', 'more_prompt', 'more_control', 'unbalanced']).optional(),
-  resize_mode: z.enum(['just_resize', 'crop_resize', 'fill_resize', 'just_resize_simple']).optional(),
-});
-export type ControlField = z.infer<typeof zControlField>;
-
-export const zIPAdapterField = z.object({
-  image: zImageField,
-  ip_adapter_model: zIPAdapterModelField,
-  weight: z.number(),
-  begin_step_percent: z.number().optional(),
-  end_step_percent: z.number().optional(),
-});
-export type IPAdapterField = z.infer<typeof zIPAdapterField>;
-
-export const zT2IAdapterField = z.object({
-  image: zImageField,
-  t2i_adapter_model: zT2IAdapterModelField,
-  weight: z.union([z.number(), z.array(z.number())]).optional(),
-  begin_step_percent: z.number().optional(),
-  end_step_percent: z.number().optional(),
-  resize_mode: z.enum(['just_resize', 'crop_resize', 'fill_resize', 'just_resize_simple']).optional(),
-});
-export type T2IAdapterField = z.infer<typeof zT2IAdapterField>;
-// #endregion
-
-// #region ProgressImage
-export const zProgressImage = z.object({
-  dataURL: z.string(),
-  width: z.number().int(),
-  height: z.number().int(),
-});
-export type ProgressImage = z.infer<typeof zProgressImage>;
-// #endregion
-
-// #region ImageOutput
-export const zImageOutput = z.object({
-  image: zImageField,
-  width: z.number().int().gt(0),
-  height: z.number().int().gt(0),
-  type: z.literal('image_output'),
-});
-export type ImageOutput = z.infer<typeof zImageOutput>;
-export const isImageOutput = (output: unknown): output is ImageOutput => zImageOutput.safeParse(output).success;
 // #endregion
diff --git a/invokeai/frontend/web/src/features/nodes/types/v2/field.ts b/invokeai/frontend/web/src/features/nodes/types/v2/field.ts
index 38f1af55dd..1e464fa76d 100644
--- a/invokeai/frontend/web/src/features/nodes/types/v2/field.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/v2/field.ts
@@ -40,50 +40,19 @@ import {
 /** */
 
 // #region Base schemas & misc
-export const zFieldInput = z.enum(['connection', 'direct', 'any']);
-export type FieldInput = z.infer<typeof zFieldInput>;
-
-export const zFieldUIComponent = z.enum(['none', 'textarea', 'slider']);
-export type FieldUIComponent = z.infer<typeof zFieldUIComponent>;
-
-export const zFieldInstanceBase = z.object({
+const zFieldInstanceBase = z.object({
   id: z.string().trim().min(1),
   name: z.string().trim().min(1),
 });
-export const zFieldInputInstanceBase = zFieldInstanceBase.extend({
+const zFieldInputInstanceBase = zFieldInstanceBase.extend({
   fieldKind: z.literal('input'),
   label: z.string().nullish(),
 });
-export const zFieldOutputInstanceBase = zFieldInstanceBase.extend({
+const zFieldOutputInstanceBase = zFieldInstanceBase.extend({
   fieldKind: z.literal('output'),
 });
-export type FieldInstanceBase = z.infer<typeof zFieldInstanceBase>;
-export type FieldInputInstanceBase = z.infer<typeof zFieldInputInstanceBase>;
-export type FieldOutputInstanceBase = z.infer<typeof zFieldOutputInstanceBase>;
 
-export const zFieldTemplateBase = z.object({
-  name: z.string().min(1),
-  title: z.string().min(1),
-  description: z.string().nullish(),
-  ui_hidden: z.boolean(),
-  ui_type: z.string().nullish(),
-  ui_order: z.number().int().nullish(),
-});
-export const zFieldInputTemplateBase = zFieldTemplateBase.extend({
-  fieldKind: z.literal('input'),
-  input: zFieldInput,
-  required: z.boolean(),
-  ui_component: zFieldUIComponent.nullish(),
-  ui_choice_labels: z.record(z.string()).nullish(),
-});
-export const zFieldOutputTemplateBase = zFieldTemplateBase.extend({
-  fieldKind: z.literal('output'),
-});
-export type FieldTemplateBase = z.infer<typeof zFieldTemplateBase>;
-export type FieldInputTemplateBase = z.infer<typeof zFieldInputTemplateBase>;
-export type FieldOutputTemplateBase = z.infer<typeof zFieldOutputTemplateBase>;
-
-export const zFieldTypeBase = z.object({
+const zFieldTypeBase = z.object({
   isCollection: z.boolean(),
   isCollectionOrScalar: z.boolean(),
 });
@@ -92,552 +61,244 @@ export const zFieldIdentifier = z.object({
   nodeId: z.string().trim().min(1),
   fieldName: z.string().trim().min(1),
 });
-export type FieldIdentifier = z.infer<typeof zFieldIdentifier>;
-export const isFieldIdentifier = (val: unknown): val is FieldIdentifier => zFieldIdentifier.safeParse(val).success;
 // #endregion
 
 // #region IntegerField
-export const zIntegerFieldType = zFieldTypeBase.extend({
+const zIntegerFieldType = zFieldTypeBase.extend({
   name: z.literal('IntegerField'),
 });
-export const zIntegerFieldValue = z.number().int();
-export const zIntegerFieldInputInstance = zFieldInputInstanceBase.extend({
+const zIntegerFieldValue = z.number().int();
+const zIntegerFieldInputInstance = zFieldInputInstanceBase.extend({
   type: zIntegerFieldType,
   value: zIntegerFieldValue,
 });
-export const zIntegerFieldOutputInstance = zFieldOutputInstanceBase.extend({
+const zIntegerFieldOutputInstance = zFieldOutputInstanceBase.extend({
   type: zIntegerFieldType,
 });
-export const zIntegerFieldInputTemplate = zFieldInputTemplateBase.extend({
-  type: zIntegerFieldType,
-  default: zIntegerFieldValue,
-  multipleOf: z.number().int().optional(),
-  maximum: z.number().int().optional(),
-  exclusiveMaximum: z.number().int().optional(),
-  minimum: z.number().int().optional(),
-  exclusiveMinimum: z.number().int().optional(),
-});
-export const zIntegerFieldOutputTemplate = zFieldOutputTemplateBase.extend({
-  type: zIntegerFieldType,
-});
-export type IntegerFieldType = z.infer<typeof zIntegerFieldType>;
-export type IntegerFieldValue = z.infer<typeof zIntegerFieldValue>;
-export type IntegerFieldInputInstance = z.infer<typeof zIntegerFieldInputInstance>;
-export type IntegerFieldInputTemplate = z.infer<typeof zIntegerFieldInputTemplate>;
-export const isIntegerFieldInputInstance = (val: unknown): val is IntegerFieldInputInstance =>
-  zIntegerFieldInputInstance.safeParse(val).success;
-export const isIntegerFieldInputTemplate = (val: unknown): val is IntegerFieldInputTemplate =>
-  zIntegerFieldInputTemplate.safeParse(val).success;
 // #endregion
 
 // #region FloatField
-export const zFloatFieldType = zFieldTypeBase.extend({
+const zFloatFieldType = zFieldTypeBase.extend({
   name: z.literal('FloatField'),
 });
-export const zFloatFieldValue = z.number();
-export const zFloatFieldInputInstance = zFieldInputInstanceBase.extend({
+const zFloatFieldValue = z.number();
+const zFloatFieldInputInstance = zFieldInputInstanceBase.extend({
   type: zFloatFieldType,
   value: zFloatFieldValue,
 });
-export const zFloatFieldOutputInstance = zFieldOutputInstanceBase.extend({
+const zFloatFieldOutputInstance = zFieldOutputInstanceBase.extend({
   type: zFloatFieldType,
 });
-export const zFloatFieldInputTemplate = zFieldInputTemplateBase.extend({
-  type: zFloatFieldType,
-  default: zFloatFieldValue,
-  multipleOf: z.number().optional(),
-  maximum: z.number().optional(),
-  exclusiveMaximum: z.number().optional(),
-  minimum: z.number().optional(),
-  exclusiveMinimum: z.number().optional(),
-});
-export const zFloatFieldOutputTemplate = zFieldOutputTemplateBase.extend({
-  type: zFloatFieldType,
-});
-export type FloatFieldType = z.infer<typeof zFloatFieldType>;
-export type FloatFieldValue = z.infer<typeof zFloatFieldValue>;
-export type FloatFieldInputInstance = z.infer<typeof zFloatFieldInputInstance>;
-export type FloatFieldOutputInstance = z.infer<typeof zFloatFieldOutputInstance>;
-export type FloatFieldInputTemplate = z.infer<typeof zFloatFieldInputTemplate>;
-export type FloatFieldOutputTemplate = z.infer<typeof zFloatFieldOutputTemplate>;
-export const isFloatFieldInputInstance = (val: unknown): val is FloatFieldInputInstance =>
-  zFloatFieldInputInstance.safeParse(val).success;
-export const isFloatFieldInputTemplate = (val: unknown): val is FloatFieldInputTemplate =>
-  zFloatFieldInputTemplate.safeParse(val).success;
 // #endregion
 
 // #region StringField
-export const zStringFieldType = zFieldTypeBase.extend({
+const zStringFieldType = zFieldTypeBase.extend({
   name: z.literal('StringField'),
 });
-export const zStringFieldValue = z.string();
-export const zStringFieldInputInstance = zFieldInputInstanceBase.extend({
+const zStringFieldValue = z.string();
+const zStringFieldInputInstance = zFieldInputInstanceBase.extend({
   type: zStringFieldType,
   value: zStringFieldValue,
 });
-export const zStringFieldOutputInstance = zFieldOutputInstanceBase.extend({
+const zStringFieldOutputInstance = zFieldOutputInstanceBase.extend({
   type: zStringFieldType,
 });
-export const zStringFieldInputTemplate = zFieldInputTemplateBase.extend({
-  type: zStringFieldType,
-  default: zStringFieldValue,
-  maxLength: z.number().int().optional(),
-  minLength: z.number().int().optional(),
-});
-export const zStringFieldOutputTemplate = zFieldOutputTemplateBase.extend({
-  type: zStringFieldType,
-});
-
-export type StringFieldType = z.infer<typeof zStringFieldType>;
-export type StringFieldValue = z.infer<typeof zStringFieldValue>;
-export type StringFieldInputInstance = z.infer<typeof zStringFieldInputInstance>;
-export type StringFieldOutputInstance = z.infer<typeof zStringFieldOutputInstance>;
-export type StringFieldInputTemplate = z.infer<typeof zStringFieldInputTemplate>;
-export type StringFieldOutputTemplate = z.infer<typeof zStringFieldOutputTemplate>;
-export const isStringFieldInputInstance = (val: unknown): val is StringFieldInputInstance =>
-  zStringFieldInputInstance.safeParse(val).success;
-export const isStringFieldInputTemplate = (val: unknown): val is StringFieldInputTemplate =>
-  zStringFieldInputTemplate.safeParse(val).success;
 // #endregion
 
 // #region BooleanField
-export const zBooleanFieldType = zFieldTypeBase.extend({
+const zBooleanFieldType = zFieldTypeBase.extend({
   name: z.literal('BooleanField'),
 });
-export const zBooleanFieldValue = z.boolean();
-export const zBooleanFieldInputInstance = zFieldInputInstanceBase.extend({
+const zBooleanFieldValue = z.boolean();
+const zBooleanFieldInputInstance = zFieldInputInstanceBase.extend({
   type: zBooleanFieldType,
   value: zBooleanFieldValue,
 });
-export const zBooleanFieldOutputInstance = zFieldOutputInstanceBase.extend({
+const zBooleanFieldOutputInstance = zFieldOutputInstanceBase.extend({
   type: zBooleanFieldType,
 });
-export const zBooleanFieldInputTemplate = zFieldInputTemplateBase.extend({
-  type: zBooleanFieldType,
-  default: zBooleanFieldValue,
-});
-export const zBooleanFieldOutputTemplate = zFieldOutputTemplateBase.extend({
-  type: zBooleanFieldType,
-});
-export type BooleanFieldType = z.infer<typeof zBooleanFieldType>;
-export type BooleanFieldValue = z.infer<typeof zBooleanFieldValue>;
-export type BooleanFieldInputInstance = z.infer<typeof zBooleanFieldInputInstance>;
-export type BooleanFieldOutputInstance = z.infer<typeof zBooleanFieldOutputInstance>;
-export type BooleanFieldInputTemplate = z.infer<typeof zBooleanFieldInputTemplate>;
-export type BooleanFieldOutputTemplate = z.infer<typeof zBooleanFieldOutputTemplate>;
-export const isBooleanFieldInputInstance = (val: unknown): val is BooleanFieldInputInstance =>
-  zBooleanFieldInputInstance.safeParse(val).success;
-export const isBooleanFieldInputTemplate = (val: unknown): val is BooleanFieldInputTemplate =>
-  zBooleanFieldInputTemplate.safeParse(val).success;
 // #endregion
 
 // #region EnumField
-export const zEnumFieldType = zFieldTypeBase.extend({
+const zEnumFieldType = zFieldTypeBase.extend({
   name: z.literal('EnumField'),
 });
-export const zEnumFieldValue = z.string();
-export const zEnumFieldInputInstance = zFieldInputInstanceBase.extend({
+const zEnumFieldValue = z.string();
+const zEnumFieldInputInstance = zFieldInputInstanceBase.extend({
   type: zEnumFieldType,
   value: zEnumFieldValue,
 });
-export const zEnumFieldOutputInstance = zFieldOutputInstanceBase.extend({
+const zEnumFieldOutputInstance = zFieldOutputInstanceBase.extend({
   type: zEnumFieldType,
 });
-export const zEnumFieldInputTemplate = zFieldInputTemplateBase.extend({
-  type: zEnumFieldType,
-  default: zEnumFieldValue,
-  options: z.array(z.string()),
-  labels: z.record(z.string()).optional(),
-});
-export const zEnumFieldOutputTemplate = zFieldOutputTemplateBase.extend({
-  type: zEnumFieldType,
-});
-export type EnumFieldType = z.infer<typeof zEnumFieldType>;
-export type EnumFieldValue = z.infer<typeof zEnumFieldValue>;
-export type EnumFieldInputInstance = z.infer<typeof zEnumFieldInputInstance>;
-export type EnumFieldOutputInstance = z.infer<typeof zEnumFieldOutputInstance>;
-export type EnumFieldInputTemplate = z.infer<typeof zEnumFieldInputTemplate>;
-export type EnumFieldOutputTemplate = z.infer<typeof zEnumFieldOutputTemplate>;
-export const isEnumFieldInputInstance = (val: unknown): val is EnumFieldInputInstance =>
-  zEnumFieldInputInstance.safeParse(val).success;
-export const isEnumFieldInputTemplate = (val: unknown): val is EnumFieldInputTemplate =>
-  zEnumFieldInputTemplate.safeParse(val).success;
 // #endregion
 
 // #region ImageField
-export const zImageFieldType = zFieldTypeBase.extend({
+const zImageFieldType = zFieldTypeBase.extend({
   name: z.literal('ImageField'),
 });
-export const zImageFieldValue = zImageField.optional();
-export const zImageFieldInputInstance = zFieldInputInstanceBase.extend({
+const zImageFieldValue = zImageField.optional();
+const zImageFieldInputInstance = zFieldInputInstanceBase.extend({
   type: zImageFieldType,
   value: zImageFieldValue,
 });
-export const zImageFieldOutputInstance = zFieldOutputInstanceBase.extend({
+const zImageFieldOutputInstance = zFieldOutputInstanceBase.extend({
   type: zImageFieldType,
 });
-export const zImageFieldInputTemplate = zFieldInputTemplateBase.extend({
-  type: zImageFieldType,
-  default: zImageFieldValue,
-});
-export const zImageFieldOutputTemplate = zFieldOutputTemplateBase.extend({
-  type: zImageFieldType,
-});
-export type ImageFieldType = z.infer<typeof zImageFieldType>;
-export type ImageFieldValue = z.infer<typeof zImageFieldValue>;
-export type ImageFieldInputInstance = z.infer<typeof zImageFieldInputInstance>;
-export type ImageFieldOutputInstance = z.infer<typeof zImageFieldOutputInstance>;
-export type ImageFieldInputTemplate = z.infer<typeof zImageFieldInputTemplate>;
-export type ImageFieldOutputTemplate = z.infer<typeof zImageFieldOutputTemplate>;
-export const isImageFieldInputInstance = (val: unknown): val is ImageFieldInputInstance =>
-  zImageFieldInputInstance.safeParse(val).success;
-export const isImageFieldInputTemplate = (val: unknown): val is ImageFieldInputTemplate =>
-  zImageFieldInputTemplate.safeParse(val).success;
 // #endregion
 
 // #region BoardField
-export const zBoardFieldType = zFieldTypeBase.extend({
+const zBoardFieldType = zFieldTypeBase.extend({
   name: z.literal('BoardField'),
 });
-export const zBoardFieldValue = zBoardField.optional();
-export const zBoardFieldInputInstance = zFieldInputInstanceBase.extend({
+const zBoardFieldValue = zBoardField.optional();
+const zBoardFieldInputInstance = zFieldInputInstanceBase.extend({
   type: zBoardFieldType,
   value: zBoardFieldValue,
 });
-export const zBoardFieldOutputInstance = zFieldOutputInstanceBase.extend({
+const zBoardFieldOutputInstance = zFieldOutputInstanceBase.extend({
   type: zBoardFieldType,
 });
-export const zBoardFieldInputTemplate = zFieldInputTemplateBase.extend({
-  type: zBoardFieldType,
-  default: zBoardFieldValue,
-});
-export const zBoardFieldOutputTemplate = zFieldOutputTemplateBase.extend({
-  type: zBoardFieldType,
-});
-export type BoardFieldType = z.infer<typeof zBoardFieldType>;
-export type BoardFieldValue = z.infer<typeof zBoardFieldValue>;
-export type BoardFieldInputInstance = z.infer<typeof zBoardFieldInputInstance>;
-export type BoardFieldOutputInstance = z.infer<typeof zBoardFieldOutputInstance>;
-export type BoardFieldInputTemplate = z.infer<typeof zBoardFieldInputTemplate>;
-export type BoardFieldOutputTemplate = z.infer<typeof zBoardFieldOutputTemplate>;
-export const isBoardFieldInputInstance = (val: unknown): val is BoardFieldInputInstance =>
-  zBoardFieldInputInstance.safeParse(val).success;
-export const isBoardFieldInputTemplate = (val: unknown): val is BoardFieldInputTemplate =>
-  zBoardFieldInputTemplate.safeParse(val).success;
 // #endregion
 
 // #region ColorField
-export const zColorFieldType = zFieldTypeBase.extend({
+const zColorFieldType = zFieldTypeBase.extend({
   name: z.literal('ColorField'),
 });
-export const zColorFieldValue = zColorField.optional();
-export const zColorFieldInputInstance = zFieldInputInstanceBase.extend({
+const zColorFieldValue = zColorField.optional();
+const zColorFieldInputInstance = zFieldInputInstanceBase.extend({
   type: zColorFieldType,
   value: zColorFieldValue,
 });
-export const zColorFieldOutputInstance = zFieldOutputInstanceBase.extend({
+const zColorFieldOutputInstance = zFieldOutputInstanceBase.extend({
   type: zColorFieldType,
 });
-export const zColorFieldInputTemplate = zFieldInputTemplateBase.extend({
-  type: zColorFieldType,
-  default: zColorFieldValue,
-});
-export const zColorFieldOutputTemplate = zFieldOutputTemplateBase.extend({
-  type: zColorFieldType,
-});
-export type ColorFieldType = z.infer<typeof zColorFieldType>;
-export type ColorFieldValue = z.infer<typeof zColorFieldValue>;
-export type ColorFieldInputInstance = z.infer<typeof zColorFieldInputInstance>;
-export type ColorFieldOutputInstance = z.infer<typeof zColorFieldOutputInstance>;
-export type ColorFieldInputTemplate = z.infer<typeof zColorFieldInputTemplate>;
-export type ColorFieldOutputTemplate = z.infer<typeof zColorFieldOutputTemplate>;
-export const isColorFieldInputInstance = (val: unknown): val is ColorFieldInputInstance =>
-  zColorFieldInputInstance.safeParse(val).success;
-export const isColorFieldInputTemplate = (val: unknown): val is ColorFieldInputTemplate =>
-  zColorFieldInputTemplate.safeParse(val).success;
 // #endregion
 
 // #region MainModelField
-export const zMainModelFieldType = zFieldTypeBase.extend({
+const zMainModelFieldType = zFieldTypeBase.extend({
   name: z.literal('MainModelField'),
 });
-export const zMainModelFieldValue = zMainModelField.optional();
-export const zMainModelFieldInputInstance = zFieldInputInstanceBase.extend({
+const zMainModelFieldValue = zMainModelField.optional();
+const zMainModelFieldInputInstance = zFieldInputInstanceBase.extend({
   type: zMainModelFieldType,
   value: zMainModelFieldValue,
 });
-export const zMainModelFieldOutputInstance = zFieldOutputInstanceBase.extend({
+const zMainModelFieldOutputInstance = zFieldOutputInstanceBase.extend({
   type: zMainModelFieldType,
 });
-export const zMainModelFieldInputTemplate = zFieldInputTemplateBase.extend({
-  type: zMainModelFieldType,
-  default: zMainModelFieldValue,
-});
-export const zMainModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
-  type: zMainModelFieldType,
-});
-export type MainModelFieldType = z.infer<typeof zMainModelFieldType>;
-export type MainModelFieldValue = z.infer<typeof zMainModelFieldValue>;
-export type MainModelFieldInputInstance = z.infer<typeof zMainModelFieldInputInstance>;
-export type MainModelFieldOutputInstance = z.infer<typeof zMainModelFieldOutputInstance>;
-export type MainModelFieldInputTemplate = z.infer<typeof zMainModelFieldInputTemplate>;
-export type MainModelFieldOutputTemplate = z.infer<typeof zMainModelFieldOutputTemplate>;
-export const isMainModelFieldInputInstance = (val: unknown): val is MainModelFieldInputInstance =>
-  zMainModelFieldInputInstance.safeParse(val).success;
-export const isMainModelFieldInputTemplate = (val: unknown): val is MainModelFieldInputTemplate =>
-  zMainModelFieldInputTemplate.safeParse(val).success;
 // #endregion
 
 // #region SDXLMainModelField
-export const zSDXLMainModelFieldType = zFieldTypeBase.extend({
+const zSDXLMainModelFieldType = zFieldTypeBase.extend({
   name: z.literal('SDXLMainModelField'),
 });
-export const zSDXLMainModelFieldValue = zMainModelFieldValue; // TODO: Narrow to SDXL models only.
-export const zSDXLMainModelFieldInputInstance = zFieldInputInstanceBase.extend({
+const zSDXLMainModelFieldValue = zMainModelFieldValue; // TODO: Narrow to SDXL models only.
+const zSDXLMainModelFieldInputInstance = zFieldInputInstanceBase.extend({
   type: zSDXLMainModelFieldType,
   value: zSDXLMainModelFieldValue,
 });
-export const zSDXLMainModelFieldOutputInstance = zFieldOutputInstanceBase.extend({
+const zSDXLMainModelFieldOutputInstance = zFieldOutputInstanceBase.extend({
   type: zSDXLMainModelFieldType,
 });
-export const zSDXLMainModelFieldInputTemplate = zFieldInputTemplateBase.extend({
-  type: zSDXLMainModelFieldType,
-  default: zSDXLMainModelFieldValue,
-});
-export const zSDXLMainModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
-  type: zSDXLMainModelFieldType,
-});
-export type SDXLMainModelFieldType = z.infer<typeof zSDXLMainModelFieldType>;
-export type SDXLMainModelFieldValue = z.infer<typeof zSDXLMainModelFieldValue>;
-export type SDXLMainModelFieldInputInstance = z.infer<typeof zSDXLMainModelFieldInputInstance>;
-export type SDXLMainModelFieldOutputInstance = z.infer<typeof zSDXLMainModelFieldOutputInstance>;
-export type SDXLMainModelFieldInputTemplate = z.infer<typeof zSDXLMainModelFieldInputTemplate>;
-export type SDXLMainModelFieldOutputTemplate = z.infer<typeof zSDXLMainModelFieldOutputTemplate>;
-export const isSDXLMainModelFieldInputInstance = (val: unknown): val is SDXLMainModelFieldInputInstance =>
-  zSDXLMainModelFieldInputInstance.safeParse(val).success;
-export const isSDXLMainModelFieldInputTemplate = (val: unknown): val is SDXLMainModelFieldInputTemplate =>
-  zSDXLMainModelFieldInputTemplate.safeParse(val).success;
 // #endregion
 
 // #region SDXLRefinerModelField
-export const zSDXLRefinerModelFieldType = zFieldTypeBase.extend({
+const zSDXLRefinerModelFieldType = zFieldTypeBase.extend({
   name: z.literal('SDXLRefinerModelField'),
 });
-export const zSDXLRefinerModelFieldValue = zMainModelFieldValue; // TODO: Narrow to SDXL Refiner models only.
-export const zSDXLRefinerModelFieldInputInstance = zFieldInputInstanceBase.extend({
+const zSDXLRefinerModelFieldValue = zMainModelFieldValue; // TODO: Narrow to SDXL Refiner models only.
+const zSDXLRefinerModelFieldInputInstance = zFieldInputInstanceBase.extend({
   type: zSDXLRefinerModelFieldType,
   value: zSDXLRefinerModelFieldValue,
 });
-export const zSDXLRefinerModelFieldOutputInstance = zFieldOutputInstanceBase.extend({
+const zSDXLRefinerModelFieldOutputInstance = zFieldOutputInstanceBase.extend({
   type: zSDXLRefinerModelFieldType,
 });
-export const zSDXLRefinerModelFieldInputTemplate = zFieldInputTemplateBase.extend({
-  type: zSDXLRefinerModelFieldType,
-  default: zSDXLRefinerModelFieldValue,
-});
-export const zSDXLRefinerModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
-  type: zSDXLRefinerModelFieldType,
-});
-export type SDXLRefinerModelFieldType = z.infer<typeof zSDXLRefinerModelFieldType>;
-export type SDXLRefinerModelFieldValue = z.infer<typeof zSDXLRefinerModelFieldValue>;
-export type SDXLRefinerModelFieldInputInstance = z.infer<typeof zSDXLRefinerModelFieldInputInstance>;
-export type SDXLRefinerModelFieldOutputInstance = z.infer<typeof zSDXLRefinerModelFieldOutputInstance>;
-export type SDXLRefinerModelFieldInputTemplate = z.infer<typeof zSDXLRefinerModelFieldInputTemplate>;
-export type SDXLRefinerModelFieldOutputTemplate = z.infer<typeof zSDXLRefinerModelFieldOutputTemplate>;
-export const isSDXLRefinerModelFieldInputInstance = (val: unknown): val is SDXLRefinerModelFieldInputInstance =>
-  zSDXLRefinerModelFieldInputInstance.safeParse(val).success;
-export const isSDXLRefinerModelFieldInputTemplate = (val: unknown): val is SDXLRefinerModelFieldInputTemplate =>
-  zSDXLRefinerModelFieldInputTemplate.safeParse(val).success;
 // #endregion
 
 // #region VAEModelField
-export const zVAEModelFieldType = zFieldTypeBase.extend({
+const zVAEModelFieldType = zFieldTypeBase.extend({
   name: z.literal('VAEModelField'),
 });
-export const zVAEModelFieldValue = zVAEModelField.optional();
-export const zVAEModelFieldInputInstance = zFieldInputInstanceBase.extend({
+const zVAEModelFieldValue = zVAEModelField.optional();
+const zVAEModelFieldInputInstance = zFieldInputInstanceBase.extend({
   type: zVAEModelFieldType,
   value: zVAEModelFieldValue,
 });
-export const zVAEModelFieldOutputInstance = zFieldOutputInstanceBase.extend({
+const zVAEModelFieldOutputInstance = zFieldOutputInstanceBase.extend({
   type: zVAEModelFieldType,
 });
-export const zVAEModelFieldInputTemplate = zFieldInputTemplateBase.extend({
-  type: zVAEModelFieldType,
-  default: zVAEModelFieldValue,
-});
-export const zVAEModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
-  type: zVAEModelFieldType,
-});
-export type VAEModelFieldType = z.infer<typeof zVAEModelFieldType>;
-export type VAEModelFieldValue = z.infer<typeof zVAEModelFieldValue>;
-export type VAEModelFieldInputInstance = z.infer<typeof zVAEModelFieldInputInstance>;
-export type VAEModelFieldOutputInstance = z.infer<typeof zVAEModelFieldOutputInstance>;
-export type VAEModelFieldInputTemplate = z.infer<typeof zVAEModelFieldInputTemplate>;
-export type VAEModelFieldOutputTemplate = z.infer<typeof zVAEModelFieldOutputTemplate>;
-export const isVAEModelFieldInputInstance = (val: unknown): val is VAEModelFieldInputInstance =>
-  zVAEModelFieldInputInstance.safeParse(val).success;
-export const isVAEModelFieldInputTemplate = (val: unknown): val is VAEModelFieldInputTemplate =>
-  zVAEModelFieldInputTemplate.safeParse(val).success;
 // #endregion
 
 // #region LoRAModelField
-export const zLoRAModelFieldType = zFieldTypeBase.extend({
+const zLoRAModelFieldType = zFieldTypeBase.extend({
   name: z.literal('LoRAModelField'),
 });
-export const zLoRAModelFieldValue = zLoRAModelField.optional();
-export const zLoRAModelFieldInputInstance = zFieldInputInstanceBase.extend({
+const zLoRAModelFieldValue = zLoRAModelField.optional();
+const zLoRAModelFieldInputInstance = zFieldInputInstanceBase.extend({
   type: zLoRAModelFieldType,
   value: zLoRAModelFieldValue,
 });
-export const zLoRAModelFieldOutputInstance = zFieldOutputInstanceBase.extend({
+const zLoRAModelFieldOutputInstance = zFieldOutputInstanceBase.extend({
   type: zLoRAModelFieldType,
 });
-export const zLoRAModelFieldInputTemplate = zFieldInputTemplateBase.extend({
-  type: zLoRAModelFieldType,
-  default: zLoRAModelFieldValue,
-});
-export const zLoRAModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
-  type: zLoRAModelFieldType,
-});
-export type LoRAModelFieldType = z.infer<typeof zLoRAModelFieldType>;
-export type LoRAModelFieldValue = z.infer<typeof zLoRAModelFieldValue>;
-export type LoRAModelFieldInputInstance = z.infer<typeof zLoRAModelFieldInputInstance>;
-export type LoRAModelFieldOutputInstance = z.infer<typeof zLoRAModelFieldOutputInstance>;
-export type LoRAModelFieldInputTemplate = z.infer<typeof zLoRAModelFieldInputTemplate>;
-export type LoRAModelFieldOutputTemplate = z.infer<typeof zLoRAModelFieldOutputTemplate>;
-export const isLoRAModelFieldInputInstance = (val: unknown): val is LoRAModelFieldInputInstance =>
-  zLoRAModelFieldInputInstance.safeParse(val).success;
-export const isLoRAModelFieldInputTemplate = (val: unknown): val is LoRAModelFieldInputTemplate =>
-  zLoRAModelFieldInputTemplate.safeParse(val).success;
 // #endregion
 
 // #region ControlNetModelField
-export const zControlNetModelFieldType = zFieldTypeBase.extend({
+const zControlNetModelFieldType = zFieldTypeBase.extend({
   name: z.literal('ControlNetModelField'),
 });
-export const zControlNetModelFieldValue = zControlNetModelField.optional();
-export const zControlNetModelFieldInputInstance = zFieldInputInstanceBase.extend({
+const zControlNetModelFieldValue = zControlNetModelField.optional();
+const zControlNetModelFieldInputInstance = zFieldInputInstanceBase.extend({
   type: zControlNetModelFieldType,
   value: zControlNetModelFieldValue,
 });
-export const zControlNetModelFieldOutputInstance = zFieldOutputInstanceBase.extend({
+const zControlNetModelFieldOutputInstance = zFieldOutputInstanceBase.extend({
   type: zControlNetModelFieldType,
 });
-export const zControlNetModelFieldInputTemplate = zFieldInputTemplateBase.extend({
-  type: zControlNetModelFieldType,
-  default: zControlNetModelFieldValue,
-});
-export const zControlNetModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
-  type: zControlNetModelFieldType,
-});
-export type ControlNetModelFieldType = z.infer<typeof zControlNetModelFieldType>;
-export type ControlNetModelFieldValue = z.infer<typeof zControlNetModelFieldValue>;
-export type ControlNetModelFieldInputInstance = z.infer<typeof zControlNetModelFieldInputInstance>;
-export type ControlNetModelFieldOutputInstance = z.infer<typeof zControlNetModelFieldOutputInstance>;
-export type ControlNetModelFieldInputTemplate = z.infer<typeof zControlNetModelFieldInputTemplate>;
-export type ControlNetModelFieldOutputTemplate = z.infer<typeof zControlNetModelFieldOutputTemplate>;
-export const isControlNetModelFieldInputInstance = (val: unknown): val is ControlNetModelFieldInputInstance =>
-  zControlNetModelFieldInputInstance.safeParse(val).success;
-export const isControlNetModelFieldInputTemplate = (val: unknown): val is ControlNetModelFieldInputTemplate =>
-  zControlNetModelFieldInputTemplate.safeParse(val).success;
-export const isControlNetModelFieldValue = (v: unknown): v is ControlNetModelFieldValue =>
-  zControlNetModelFieldValue.safeParse(v).success;
 // #endregion
 
 // #region IPAdapterModelField
-export const zIPAdapterModelFieldType = zFieldTypeBase.extend({
+const zIPAdapterModelFieldType = zFieldTypeBase.extend({
   name: z.literal('IPAdapterModelField'),
 });
-export const zIPAdapterModelFieldValue = zIPAdapterModelField.optional();
-export const zIPAdapterModelFieldInputInstance = zFieldInputInstanceBase.extend({
+const zIPAdapterModelFieldValue = zIPAdapterModelField.optional();
+const zIPAdapterModelFieldInputInstance = zFieldInputInstanceBase.extend({
   type: zIPAdapterModelFieldType,
   value: zIPAdapterModelFieldValue,
 });
-export const zIPAdapterModelFieldOutputInstance = zFieldOutputInstanceBase.extend({
+const zIPAdapterModelFieldOutputInstance = zFieldOutputInstanceBase.extend({
   type: zIPAdapterModelFieldType,
 });
-export const zIPAdapterModelFieldInputTemplate = zFieldInputTemplateBase.extend({
-  type: zIPAdapterModelFieldType,
-  default: zIPAdapterModelFieldValue,
-});
-export const zIPAdapterModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
-  type: zIPAdapterModelFieldType,
-});
-export type IPAdapterModelFieldType = z.infer<typeof zIPAdapterModelFieldType>;
-export type IPAdapterModelFieldValue = z.infer<typeof zIPAdapterModelFieldValue>;
-export type IPAdapterModelFieldInputInstance = z.infer<typeof zIPAdapterModelFieldInputInstance>;
-export type IPAdapterModelFieldOutputInstance = z.infer<typeof zIPAdapterModelFieldOutputInstance>;
-export type IPAdapterModelFieldInputTemplate = z.infer<typeof zIPAdapterModelFieldInputTemplate>;
-export type IPAdapterModelFieldOutputTemplate = z.infer<typeof zIPAdapterModelFieldOutputTemplate>;
-export const isIPAdapterModelFieldInputInstance = (val: unknown): val is IPAdapterModelFieldInputInstance =>
-  zIPAdapterModelFieldInputInstance.safeParse(val).success;
-export const isIPAdapterModelFieldInputTemplate = (val: unknown): val is IPAdapterModelFieldInputTemplate =>
-  zIPAdapterModelFieldInputTemplate.safeParse(val).success;
-export const isIPAdapterModelFieldValue = (val: unknown): val is IPAdapterModelFieldValue =>
-  zIPAdapterModelFieldValue.safeParse(val).success;
 // #endregion
 
 // #region T2IAdapterField
-export const zT2IAdapterModelFieldType = zFieldTypeBase.extend({
+const zT2IAdapterModelFieldType = zFieldTypeBase.extend({
   name: z.literal('T2IAdapterModelField'),
 });
-export const zT2IAdapterModelFieldValue = zT2IAdapterModelField.optional();
-export const zT2IAdapterModelFieldInputInstance = zFieldInputInstanceBase.extend({
+const zT2IAdapterModelFieldValue = zT2IAdapterModelField.optional();
+const zT2IAdapterModelFieldInputInstance = zFieldInputInstanceBase.extend({
   type: zT2IAdapterModelFieldType,
   value: zT2IAdapterModelFieldValue,
 });
-export const zT2IAdapterModelFieldOutputInstance = zFieldOutputInstanceBase.extend({
+const zT2IAdapterModelFieldOutputInstance = zFieldOutputInstanceBase.extend({
   type: zT2IAdapterModelFieldType,
 });
-export const zT2IAdapterModelFieldInputTemplate = zFieldInputTemplateBase.extend({
-  type: zT2IAdapterModelFieldType,
-  default: zT2IAdapterModelFieldValue,
-});
-export const zT2IAdapterModelFieldOutputTemplate = zFieldOutputTemplateBase.extend({
-  type: zT2IAdapterModelFieldType,
-});
-export type T2IAdapterModelFieldType = z.infer<typeof zT2IAdapterModelFieldType>;
-export type T2IAdapterModelFieldValue = z.infer<typeof zT2IAdapterModelFieldValue>;
-export type T2IAdapterModelFieldInputInstance = z.infer<typeof zT2IAdapterModelFieldInputInstance>;
-export type T2IAdapterModelFieldOutputInstance = z.infer<typeof zT2IAdapterModelFieldOutputInstance>;
-export type T2IAdapterModelFieldInputTemplate = z.infer<typeof zT2IAdapterModelFieldInputTemplate>;
-export type T2IAdapterModelFieldOutputTemplate = z.infer<typeof zT2IAdapterModelFieldOutputTemplate>;
-export const isT2IAdapterModelFieldInputInstance = (val: unknown): val is T2IAdapterModelFieldInputInstance =>
-  zT2IAdapterModelFieldInputInstance.safeParse(val).success;
-export const isT2IAdapterModelFieldInputTemplate = (val: unknown): val is T2IAdapterModelFieldInputTemplate =>
-  zT2IAdapterModelFieldInputTemplate.safeParse(val).success;
 // #endregion
 
 // #region SchedulerField
-export const zSchedulerFieldType = zFieldTypeBase.extend({
+const zSchedulerFieldType = zFieldTypeBase.extend({
   name: z.literal('SchedulerField'),
 });
-export const zSchedulerFieldValue = zSchedulerField.optional();
-export const zSchedulerFieldInputInstance = zFieldInputInstanceBase.extend({
+const zSchedulerFieldValue = zSchedulerField.optional();
+const zSchedulerFieldInputInstance = zFieldInputInstanceBase.extend({
   type: zSchedulerFieldType,
   value: zSchedulerFieldValue,
 });
-export const zSchedulerFieldOutputInstance = zFieldOutputInstanceBase.extend({
+const zSchedulerFieldOutputInstance = zFieldOutputInstanceBase.extend({
   type: zSchedulerFieldType,
 });
-export const zSchedulerFieldInputTemplate = zFieldInputTemplateBase.extend({
-  type: zSchedulerFieldType,
-  default: zSchedulerFieldValue,
-});
-export const zSchedulerFieldOutputTemplate = zFieldOutputTemplateBase.extend({
-  type: zSchedulerFieldType,
-});
-export type SchedulerFieldType = z.infer<typeof zSchedulerFieldType>;
-export type SchedulerFieldValue = z.infer<typeof zSchedulerFieldValue>;
-export type SchedulerFieldInputInstance = z.infer<typeof zSchedulerFieldInputInstance>;
-export type SchedulerFieldOutputInstance = z.infer<typeof zSchedulerFieldOutputInstance>;
-export type SchedulerFieldInputTemplate = z.infer<typeof zSchedulerFieldInputTemplate>;
-export type SchedulerFieldOutputTemplate = z.infer<typeof zSchedulerFieldOutputTemplate>;
-export const isSchedulerFieldInputInstance = (val: unknown): val is SchedulerFieldInputInstance =>
-  zSchedulerFieldInputInstance.safeParse(val).success;
-export const isSchedulerFieldInputTemplate = (val: unknown): val is SchedulerFieldInputTemplate =>
-  zSchedulerFieldInputTemplate.safeParse(val).success;
 // #endregion
 
 // #region StatelessField
@@ -652,32 +313,18 @@ export const isSchedulerFieldInputTemplate = (val: unknown): val is SchedulerFie
  * - Reserved fields like IsIntermediate
  * - Any other field we don't have full-on schemas for
  */
-export const zStatelessFieldType = zFieldTypeBase.extend({
+const zStatelessFieldType = zFieldTypeBase.extend({
   name: z.string().min(1), // stateless --> we accept the field's name as the type
 });
-export const zStatelessFieldValue = z.undefined().catch(undefined); // stateless --> no value, but making this z.never() introduces a lot of extra TS fanagling
-export const zStatelessFieldInputInstance = zFieldInputInstanceBase.extend({
+const zStatelessFieldValue = z.undefined().catch(undefined); // stateless --> no value, but making this z.never() introduces a lot of extra TS fanagling
+const zStatelessFieldInputInstance = zFieldInputInstanceBase.extend({
   type: zStatelessFieldType,
   value: zStatelessFieldValue,
 });
-export const zStatelessFieldOutputInstance = zFieldOutputInstanceBase.extend({
-  type: zStatelessFieldType,
-});
-export const zStatelessFieldInputTemplate = zFieldInputTemplateBase.extend({
-  type: zStatelessFieldType,
-  default: zStatelessFieldValue,
-  input: z.literal('connection'), // stateless --> only accepts connection inputs
-});
-export const zStatelessFieldOutputTemplate = zFieldOutputTemplateBase.extend({
+const zStatelessFieldOutputInstance = zFieldOutputInstanceBase.extend({
   type: zStatelessFieldType,
 });
 
-export type StatelessFieldType = z.infer<typeof zStatelessFieldType>;
-export type StatelessFieldValue = z.infer<typeof zStatelessFieldValue>;
-export type StatelessFieldInputInstance = z.infer<typeof zStatelessFieldInputInstance>;
-export type StatelessFieldOutputInstance = z.infer<typeof zStatelessFieldOutputInstance>;
-export type StatelessFieldInputTemplate = z.infer<typeof zStatelessFieldInputTemplate>;
-export type StatelessFieldOutputTemplate = z.infer<typeof zStatelessFieldOutputTemplate>;
 // #endregion
 
 /**
@@ -695,66 +342,10 @@ export type StatelessFieldOutputTemplate = z.infer<typeof zStatelessFieldOutputT
  * for all other StatelessFields.
  */
 
-// #region StatefulFieldType & FieldType
-export const zStatefulFieldType = z.union([
-  zIntegerFieldType,
-  zFloatFieldType,
-  zStringFieldType,
-  zBooleanFieldType,
-  zEnumFieldType,
-  zImageFieldType,
-  zBoardFieldType,
-  zMainModelFieldType,
-  zSDXLMainModelFieldType,
-  zSDXLRefinerModelFieldType,
-  zVAEModelFieldType,
-  zLoRAModelFieldType,
-  zControlNetModelFieldType,
-  zIPAdapterModelFieldType,
-  zT2IAdapterModelFieldType,
-  zColorFieldType,
-  zSchedulerFieldType,
-]);
-export type StatefulFieldType = z.infer<typeof zStatefulFieldType>;
-export const isStatefulFieldType = (val: unknown): val is StatefulFieldType =>
-  zStatefulFieldType.safeParse(val).success;
-
-export const zFieldType = z.union([zStatefulFieldType, zStatelessFieldType]);
-export type FieldType = z.infer<typeof zFieldType>;
-export const isFieldType = (val: unknown): val is FieldType => zFieldType.safeParse(val).success;
-// #endregion
-
-// #region StatefulFieldValue & FieldValue
-export const zStatefulFieldValue = z.union([
-  zIntegerFieldValue,
-  zFloatFieldValue,
-  zStringFieldValue,
-  zBooleanFieldValue,
-  zEnumFieldValue,
-  zImageFieldValue,
-  zBoardFieldValue,
-  zMainModelFieldValue,
-  zSDXLMainModelFieldValue,
-  zSDXLRefinerModelFieldValue,
-  zVAEModelFieldValue,
-  zLoRAModelFieldValue,
-  zControlNetModelFieldValue,
-  zIPAdapterModelFieldValue,
-  zT2IAdapterModelFieldValue,
-  zColorFieldValue,
-  zSchedulerFieldValue,
-]);
-export type StatefulFieldValue = z.infer<typeof zStatefulFieldValue>;
-export const isStatefulFieldValue = (val: unknown): val is StatefulFieldValue =>
-  zStatefulFieldValue.safeParse(val).success;
-
-export const zFieldValue = z.union([zStatefulFieldValue, zStatelessFieldValue]);
-export type FieldValue = z.infer<typeof zFieldValue>;
-export const isFieldValue = (val: unknown): val is FieldValue => zFieldValue.safeParse(val).success;
 // #endregion
 
 // #region StatefulFieldInputInstance & FieldInputInstance
-export const zStatefulFieldInputInstance = z.union([
+const zStatefulFieldInputInstance = z.union([
   zIntegerFieldInputInstance,
   zFloatFieldInputInstance,
   zStringFieldInputInstance,
@@ -773,18 +364,12 @@ export const zStatefulFieldInputInstance = z.union([
   zColorFieldInputInstance,
   zSchedulerFieldInputInstance,
 ]);
-export type StatefulFieldInputInstance = z.infer<typeof zStatefulFieldInputInstance>;
-export const isStatefulFieldInputInstance = (val: unknown): val is StatefulFieldInputInstance =>
-  zStatefulFieldInputInstance.safeParse(val).success;
 
 export const zFieldInputInstance = z.union([zStatefulFieldInputInstance, zStatelessFieldInputInstance]);
-export type FieldInputInstance = z.infer<typeof zFieldInputInstance>;
-export const isFieldInputInstance = (val: unknown): val is FieldInputInstance =>
-  zFieldInputInstance.safeParse(val).success;
 // #endregion
 
 // #region StatefulFieldOutputInstance & FieldOutputInstance
-export const zStatefulFieldOutputInstance = z.union([
+const zStatefulFieldOutputInstance = z.union([
   zIntegerFieldOutputInstance,
   zFloatFieldOutputInstance,
   zStringFieldOutputInstance,
@@ -803,73 +388,6 @@ export const zStatefulFieldOutputInstance = z.union([
   zColorFieldOutputInstance,
   zSchedulerFieldOutputInstance,
 ]);
-export type StatefulFieldOutputInstance = z.infer<typeof zStatefulFieldOutputInstance>;
-export const isStatefulFieldOutputInstance = (val: unknown): val is StatefulFieldOutputInstance =>
-  zStatefulFieldOutputInstance.safeParse(val).success;
 
 export const zFieldOutputInstance = z.union([zStatefulFieldOutputInstance, zStatelessFieldOutputInstance]);
-export type FieldOutputInstance = z.infer<typeof zFieldOutputInstance>;
-export const isFieldOutputInstance = (val: unknown): val is FieldOutputInstance =>
-  zFieldOutputInstance.safeParse(val).success;
-// #endregion
-
-// #region StatefulFieldInputTemplate & FieldInputTemplate
-export const zStatefulFieldInputTemplate = z.union([
-  zIntegerFieldInputTemplate,
-  zFloatFieldInputTemplate,
-  zStringFieldInputTemplate,
-  zBooleanFieldInputTemplate,
-  zEnumFieldInputTemplate,
-  zImageFieldInputTemplate,
-  zBoardFieldInputTemplate,
-  zMainModelFieldInputTemplate,
-  zSDXLMainModelFieldInputTemplate,
-  zSDXLRefinerModelFieldInputTemplate,
-  zVAEModelFieldInputTemplate,
-  zLoRAModelFieldInputTemplate,
-  zControlNetModelFieldInputTemplate,
-  zIPAdapterModelFieldInputTemplate,
-  zT2IAdapterModelFieldInputTemplate,
-  zColorFieldInputTemplate,
-  zSchedulerFieldInputTemplate,
-  zStatelessFieldInputTemplate,
-]);
-export type StatefulFieldInputTemplate = z.infer<typeof zFieldInputTemplate>;
-export const isStatefulFieldInputTemplate = (val: unknown): val is StatefulFieldInputTemplate =>
-  zStatefulFieldInputTemplate.safeParse(val).success;
-
-export const zFieldInputTemplate = z.union([zStatefulFieldInputTemplate, zStatelessFieldInputTemplate]);
-export type FieldInputTemplate = z.infer<typeof zFieldInputTemplate>;
-export const isFieldInputTemplate = (val: unknown): val is FieldInputTemplate =>
-  zFieldInputTemplate.safeParse(val).success;
-// #endregion
-
-// #region StatefulFieldOutputTemplate & FieldOutputTemplate
-export const zStatefulFieldOutputTemplate = z.union([
-  zIntegerFieldOutputTemplate,
-  zFloatFieldOutputTemplate,
-  zStringFieldOutputTemplate,
-  zBooleanFieldOutputTemplate,
-  zEnumFieldOutputTemplate,
-  zImageFieldOutputTemplate,
-  zBoardFieldOutputTemplate,
-  zMainModelFieldOutputTemplate,
-  zSDXLMainModelFieldOutputTemplate,
-  zSDXLRefinerModelFieldOutputTemplate,
-  zVAEModelFieldOutputTemplate,
-  zLoRAModelFieldOutputTemplate,
-  zControlNetModelFieldOutputTemplate,
-  zIPAdapterModelFieldOutputTemplate,
-  zT2IAdapterModelFieldOutputTemplate,
-  zColorFieldOutputTemplate,
-  zSchedulerFieldOutputTemplate,
-]);
-export type StatefulFieldOutputTemplate = z.infer<typeof zStatefulFieldOutputTemplate>;
-export const isStatefulFieldOutputTemplate = (val: unknown): val is StatefulFieldOutputTemplate =>
-  zStatefulFieldOutputTemplate.safeParse(val).success;
-
-export const zFieldOutputTemplate = z.union([zStatefulFieldOutputTemplate, zStatelessFieldOutputTemplate]);
-export type FieldOutputTemplate = z.infer<typeof zFieldOutputTemplate>;
-export const isFieldOutputTemplate = (val: unknown): val is FieldOutputTemplate =>
-  zFieldOutputTemplate.safeParse(val).success;
 // #endregion
diff --git a/invokeai/frontend/web/src/features/nodes/types/v2/invocation.ts b/invokeai/frontend/web/src/features/nodes/types/v2/invocation.ts
index 86ec70fd9b..f2783e7458 100644
--- a/invokeai/frontend/web/src/features/nodes/types/v2/invocation.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/v2/invocation.ts
@@ -1,27 +1,8 @@
-import type { Edge, Node } from 'reactflow';
 import { z } from 'zod';
 
-import { zClassification, zProgressImage } from './common';
-import { zFieldInputInstance, zFieldInputTemplate, zFieldOutputInstance, zFieldOutputTemplate } from './field';
+import { zFieldInputInstance, zFieldOutputInstance } from './field';
 import { zSemVer } from './semver';
 
-// #region InvocationTemplate
-export const zInvocationTemplate = z.object({
-  type: z.string(),
-  title: z.string(),
-  description: z.string(),
-  tags: z.array(z.string().min(1)),
-  inputs: z.record(zFieldInputTemplate),
-  outputs: z.record(zFieldOutputTemplate),
-  outputType: z.string().min(1),
-  version: zSemVer,
-  useCache: z.boolean(),
-  nodePack: z.string().min(1).nullish(),
-  classification: zClassification,
-});
-export type InvocationTemplate = z.infer<typeof zInvocationTemplate>;
-// #endregion
-
 // #region NodeData
 export const zInvocationNodeData = z.object({
   id: z.string().trim().min(1),
@@ -44,50 +25,4 @@ export const zNotesNodeData = z.object({
   isOpen: z.boolean(),
   notes: z.string(),
 });
-export const zCurrentImageNodeData = z.object({
-  id: z.string().trim().min(1),
-  type: z.literal('current_image'),
-  label: z.string(),
-  isOpen: z.boolean(),
-});
-export const zAnyNodeData = z.union([zInvocationNodeData, zNotesNodeData, zCurrentImageNodeData]);
-
-export type NotesNodeData = z.infer<typeof zNotesNodeData>;
-export type InvocationNodeData = z.infer<typeof zInvocationNodeData>;
-export type CurrentImageNodeData = z.infer<typeof zCurrentImageNodeData>;
-export type AnyNodeData = z.infer<typeof zAnyNodeData>;
-
-export type InvocationNode = Node<InvocationNodeData, 'invocation'>;
-export type NotesNode = Node<NotesNodeData, 'notes'>;
-export type CurrentImageNode = Node<CurrentImageNodeData, 'current_image'>;
-export type AnyNode = Node<AnyNodeData>;
-
-export const isInvocationNode = (node?: AnyNode): node is InvocationNode => Boolean(node && node.type === 'invocation');
-export const isNotesNode = (node?: AnyNode): node is NotesNode => Boolean(node && node.type === 'notes');
-export const isCurrentImageNode = (node?: AnyNode): node is CurrentImageNode =>
-  Boolean(node && node.type === 'current_image');
-export const isInvocationNodeData = (node?: AnyNodeData): node is InvocationNodeData =>
-  Boolean(node && !['notes', 'current_image'].includes(node.type)); // node.type may be 'notes', 'current_image', or any invocation type
-// #endregion
-
-// #region NodeExecutionState
-export const zNodeStatus = z.enum(['PENDING', 'IN_PROGRESS', 'COMPLETED', 'FAILED']);
-export const zNodeExecutionState = z.object({
-  nodeId: z.string().trim().min(1),
-  status: zNodeStatus,
-  progress: z.number().nullable(),
-  progressImage: zProgressImage.nullable(),
-  error: z.string().nullable(),
-  outputs: z.array(z.any()),
-});
-export type NodeExecutionState = z.infer<typeof zNodeExecutionState>;
-export type NodeStatus = z.infer<typeof zNodeStatus>;
-// #endregion
-
-// #region Edges
-export const zInvocationNodeEdgeExtra = z.object({
-  type: z.union([z.literal('default'), z.literal('collapsed')]),
-});
-export type InvocationNodeEdgeExtra = z.infer<typeof zInvocationNodeEdgeExtra>;
-export type InvocationNodeEdge = Edge<InvocationNodeEdgeExtra>;
 // #endregion
diff --git a/invokeai/frontend/web/src/features/nodes/types/v2/semver.ts b/invokeai/frontend/web/src/features/nodes/types/v2/semver.ts
index 3ba330eac4..1b76577938 100644
--- a/invokeai/frontend/web/src/features/nodes/types/v2/semver.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/v2/semver.ts
@@ -10,12 +10,3 @@ export const zSemVer = z.string().refine((val) => {
     zVersionInt.safeParse(major).success && zVersionInt.safeParse(minor).success && zVersionInt.safeParse(patch).success
   );
 });
-
-export const zParsedSemver = zSemVer.transform((val) => {
-  const [major, minor, patch] = val.split('.');
-  return {
-    major: Number(major),
-    minor: Number(minor),
-    patch: Number(patch),
-  };
-});
diff --git a/invokeai/frontend/web/src/features/nodes/types/v2/workflow.ts b/invokeai/frontend/web/src/features/nodes/types/v2/workflow.ts
index 723a354013..511a28cdc3 100644
--- a/invokeai/frontend/web/src/features/nodes/types/v2/workflow.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/v2/workflow.ts
@@ -4,23 +4,20 @@ import { zFieldIdentifier } from './field';
 import { zInvocationNodeData, zNotesNodeData } from './invocation';
 
 // #region Workflow misc
-export const zXYPosition = z
+const zXYPosition = z
   .object({
     x: z.number(),
     y: z.number(),
   })
   .default({ x: 0, y: 0 });
-export type XYPosition = z.infer<typeof zXYPosition>;
 
-export const zDimension = z.number().gt(0).nullish();
-export type Dimension = z.infer<typeof zDimension>;
+const zDimension = z.number().gt(0).nullish();
 
-export const zWorkflowCategory = z.enum(['user', 'default', 'project']);
-export type WorkflowCategory = z.infer<typeof zWorkflowCategory>;
+const zWorkflowCategory = z.enum(['user', 'default', 'project']);
 // #endregion
 
 // #region Workflow Nodes
-export const zWorkflowInvocationNode = z.object({
+const zWorkflowInvocationNode = z.object({
   id: z.string().trim().min(1),
   type: z.literal('invocation'),
   data: zInvocationNodeData,
@@ -28,7 +25,7 @@ export const zWorkflowInvocationNode = z.object({
   height: zDimension,
   position: zXYPosition,
 });
-export const zWorkflowNotesNode = z.object({
+const zWorkflowNotesNode = z.object({
   id: z.string().trim().min(1),
   type: z.literal('notes'),
   data: zNotesNodeData,
@@ -36,35 +33,24 @@ export const zWorkflowNotesNode = z.object({
   height: zDimension,
   position: zXYPosition,
 });
-export const zWorkflowNode = z.union([zWorkflowInvocationNode, zWorkflowNotesNode]);
-
-export type WorkflowInvocationNode = z.infer<typeof zWorkflowInvocationNode>;
-export type WorkflowNotesNode = z.infer<typeof zWorkflowNotesNode>;
-export type WorkflowNode = z.infer<typeof zWorkflowNode>;
-
-export const isWorkflowInvocationNode = (val: unknown): val is WorkflowInvocationNode =>
-  zWorkflowInvocationNode.safeParse(val).success;
+const zWorkflowNode = z.union([zWorkflowInvocationNode, zWorkflowNotesNode]);
 // #endregion
 
 // #region Workflow Edges
-export const zWorkflowEdgeBase = z.object({
+const zWorkflowEdgeBase = z.object({
   id: z.string().trim().min(1),
   source: z.string().trim().min(1),
   target: z.string().trim().min(1),
 });
-export const zWorkflowEdgeDefault = zWorkflowEdgeBase.extend({
+const zWorkflowEdgeDefault = zWorkflowEdgeBase.extend({
   type: z.literal('default'),
   sourceHandle: z.string().trim().min(1),
   targetHandle: z.string().trim().min(1),
 });
-export const zWorkflowEdgeCollapsed = zWorkflowEdgeBase.extend({
+const zWorkflowEdgeCollapsed = zWorkflowEdgeBase.extend({
   type: z.literal('collapsed'),
 });
-export const zWorkflowEdge = z.union([zWorkflowEdgeDefault, zWorkflowEdgeCollapsed]);
-
-export type WorkflowEdgeDefault = z.infer<typeof zWorkflowEdgeDefault>;
-export type WorkflowEdgeCollapsed = z.infer<typeof zWorkflowEdgeCollapsed>;
-export type WorkflowEdge = z.infer<typeof zWorkflowEdge>;
+const zWorkflowEdge = z.union([zWorkflowEdgeDefault, zWorkflowEdgeCollapsed]);
 // #endregion
 
 // #region Workflow
diff --git a/invokeai/frontend/web/src/features/nodes/types/workflow.ts b/invokeai/frontend/web/src/features/nodes/types/workflow.ts
index 6bc6be8cd7..a424bf8d4b 100644
--- a/invokeai/frontend/web/src/features/nodes/types/workflow.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/workflow.ts
@@ -12,9 +12,6 @@ const zXYPosition = z
   .default({ x: 0, y: 0 });
 export type XYPosition = z.infer<typeof zXYPosition>;
 
-const zDimension = z.number().gt(0).nullish();
-export type Dimension = z.infer<typeof zDimension>;
-
 const zWorkflowCategory = z.enum(['user', 'default', 'project']);
 export type WorkflowCategory = z.infer<typeof zWorkflowCategory>;
 // #endregion
@@ -34,9 +31,7 @@ const zWorkflowNotesNode = z.object({
 });
 const zWorkflowNode = z.union([zWorkflowInvocationNode, zWorkflowNotesNode]);
 
-export type WorkflowInvocationNode = z.infer<typeof zWorkflowInvocationNode>;
-export type WorkflowNotesNode = z.infer<typeof zWorkflowNotesNode>;
-export type WorkflowNode = z.infer<typeof zWorkflowNode>;
+type WorkflowInvocationNode = z.infer<typeof zWorkflowInvocationNode>;
 
 export const isWorkflowInvocationNode = (val: unknown): val is WorkflowInvocationNode =>
   zWorkflowInvocationNode.safeParse(val).success;
@@ -57,10 +52,6 @@ const zWorkflowEdgeCollapsed = zWorkflowEdgeBase.extend({
   type: z.literal('collapsed'),
 });
 const zWorkflowEdge = z.union([zWorkflowEdgeDefault, zWorkflowEdgeCollapsed]);
-
-export type WorkflowEdgeDefault = z.infer<typeof zWorkflowEdgeDefault>;
-export type WorkflowEdgeCollapsed = z.infer<typeof zWorkflowEdgeCollapsed>;
-export type WorkflowEdge = z.infer<typeof zWorkflowEdge>;
 // #endregion
 
 // #region Workflow
diff --git a/invokeai/frontend/web/src/features/nodes/util/workflow/buildWorkflow.ts b/invokeai/frontend/web/src/features/nodes/util/workflow/buildWorkflow.ts
index 720da16464..c242eba1f4 100644
--- a/invokeai/frontend/web/src/features/nodes/util/workflow/buildWorkflow.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/workflow/buildWorkflow.ts
@@ -27,7 +27,7 @@ const workflowKeys = [
   'id',
 ] satisfies (keyof WorkflowV3)[];
 
-export type BuildWorkflowFunction = (arg: BuildWorkflowArg) => WorkflowV3;
+type BuildWorkflowFunction = (arg: BuildWorkflowArg) => WorkflowV3;
 
 export const buildWorkflowFast: BuildWorkflowFunction = ({ nodes, edges, workflow }: BuildWorkflowArg): WorkflowV3 => {
   const clonedWorkflow = pick(cloneDeep(workflow), workflowKeys);
diff --git a/invokeai/frontend/web/src/features/parameters/components/ImageSize/AspectRatioPreview.tsx b/invokeai/frontend/web/src/features/parameters/components/ImageSize/AspectRatioPreview.tsx
index 950422aa65..e662acae7d 100644
--- a/invokeai/frontend/web/src/features/parameters/components/ImageSize/AspectRatioPreview.tsx
+++ b/invokeai/frontend/web/src/features/parameters/components/ImageSize/AspectRatioPreview.tsx
@@ -15,11 +15,6 @@ import {
   MOTION_ICON_INITIAL,
 } from './constants';
 
-export type AspectRatioPreviewProps = {
-  width: number;
-  height: number;
-};
-
 export const AspectRatioPreview = () => {
   const ctx = useImageSizeContext();
   const containerRef = useRef<HTMLDivElement>(null);
diff --git a/invokeai/frontend/web/src/features/parameters/store/postprocessingSlice.ts b/invokeai/frontend/web/src/features/parameters/store/postprocessingSlice.ts
index 65a30ab4d0..c15bf982b8 100644
--- a/invokeai/frontend/web/src/features/parameters/store/postprocessingSlice.ts
+++ b/invokeai/frontend/web/src/features/parameters/store/postprocessingSlice.ts
@@ -9,11 +9,11 @@ const zParamESRGANModelName = z.enum([
   'ESRGAN_SRx4_DF2KOST_official-ff704c30.pth',
   'RealESRGAN_x2plus.pth',
 ]);
-export type ParamESRGANModelName = z.infer<typeof zParamESRGANModelName>;
+type ParamESRGANModelName = z.infer<typeof zParamESRGANModelName>;
 export const isParamESRGANModelName = (v: unknown): v is ParamESRGANModelName =>
   zParamESRGANModelName.safeParse(v).success;
 
-export interface PostprocessingState {
+interface PostprocessingState {
   _version: 1;
   esrganModelName: ParamESRGANModelName;
 }
diff --git a/invokeai/frontend/web/src/features/parameters/types/parameterSchemas.ts b/invokeai/frontend/web/src/features/parameters/types/parameterSchemas.ts
index e2cc277d6a..2476634c26 100644
--- a/invokeai/frontend/web/src/features/parameters/types/parameterSchemas.ts
+++ b/invokeai/frontend/web/src/features/parameters/types/parameterSchemas.ts
@@ -91,11 +91,6 @@ export type ParameterHeight = z.infer<typeof zParameterHeight>;
 export const isParameterHeight = (val: unknown): val is ParameterHeight => zParameterHeight.safeParse(val).success;
 // #endregion
 
-// #region Aspect Ratio
-const zParameterAspectRatio = z.number().int().min(0).max(6);
-export type ParameterAspectRatio = z.infer<typeof zParameterAspectRatio>;
-// #endregion
-
 // #region Model
 export const zParameterModel = zModelIdentifierWithBase;
 export type ParameterModel = z.infer<typeof zParameterModel>;
@@ -198,6 +193,6 @@ export const isParameterCanvasCoherenceMode = (val: unknown): val is ParameterCa
 
 // #region LoRA weight
 const zLoRAWeight = z.number();
-export type ParameterLoRAWeight = z.infer<typeof zLoRAWeight>;
+type ParameterLoRAWeight = z.infer<typeof zLoRAWeight>;
 export const isParameterLoRAWeight = (val: unknown): val is ParameterLoRAWeight => zLoRAWeight.safeParse(val).success;
 // #endregion
diff --git a/invokeai/frontend/web/src/features/queue/store/queueSlice.ts b/invokeai/frontend/web/src/features/queue/store/queueSlice.ts
index a5750712c3..38c1cf5349 100644
--- a/invokeai/frontend/web/src/features/queue/store/queueSlice.ts
+++ b/invokeai/frontend/web/src/features/queue/store/queueSlice.ts
@@ -1,7 +1,7 @@
 import type { PayloadAction } from '@reduxjs/toolkit';
 import { createSlice } from '@reduxjs/toolkit';
 
-export interface QueueState {
+interface QueueState {
   listCursor: number | undefined;
   listPriority: number | undefined;
   selectedQueueItem: string | undefined;
diff --git a/invokeai/frontend/web/src/features/system/components/HotkeysModal/useHotkeyData.ts b/invokeai/frontend/web/src/features/system/components/HotkeysModal/useHotkeyData.ts
index f3f5056eae..f9a0df52e4 100644
--- a/invokeai/frontend/web/src/features/system/components/HotkeysModal/useHotkeyData.ts
+++ b/invokeai/frontend/web/src/features/system/components/HotkeysModal/useHotkeyData.ts
@@ -1,7 +1,7 @@
 import { useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
 
-export type HotkeyListItem = {
+type HotkeyListItem = {
   title: string;
   desc: string;
   hotkeys: string[][];
diff --git a/invokeai/frontend/web/src/features/system/components/SettingsModal/useClearIntermediates.ts b/invokeai/frontend/web/src/features/system/components/SettingsModal/useClearIntermediates.ts
index 96d3b0f7ee..e9f1debcf8 100644
--- a/invokeai/frontend/web/src/features/system/components/SettingsModal/useClearIntermediates.ts
+++ b/invokeai/frontend/web/src/features/system/components/SettingsModal/useClearIntermediates.ts
@@ -7,7 +7,7 @@ import { useTranslation } from 'react-i18next';
 import { useClearIntermediatesMutation, useGetIntermediatesCountQuery } from 'services/api/endpoints/images';
 import { useGetQueueStatusQuery } from 'services/api/endpoints/queue';
 
-export type UseClearIntermediatesReturn = {
+type UseClearIntermediatesReturn = {
   intermediatesCount: number | undefined;
   clearIntermediates: () => void;
   isLoading: boolean;
diff --git a/invokeai/frontend/web/src/features/system/components/StickyScrollable.tsx b/invokeai/frontend/web/src/features/system/components/StickyScrollable.tsx
index 9359731d5b..012e6dcd6e 100644
--- a/invokeai/frontend/web/src/features/system/components/StickyScrollable.tsx
+++ b/invokeai/frontend/web/src/features/system/components/StickyScrollable.tsx
@@ -28,7 +28,7 @@ const StickyScrollableContent = memo((props: StickyScrollableContentProps) => {
 
 StickyScrollableContent.displayName = 'StickyScrollableContent';
 
-export type StickyScrollableProps = PropsWithChildren<{
+type StickyScrollableProps = PropsWithChildren<{
   title: string;
 }>;
 
diff --git a/invokeai/frontend/web/src/features/system/store/types.ts b/invokeai/frontend/web/src/features/system/store/types.ts
index c8790e0104..430df9aa7d 100644
--- a/invokeai/frontend/web/src/features/system/store/types.ts
+++ b/invokeai/frontend/web/src/features/system/store/types.ts
@@ -3,9 +3,9 @@ import type { LogLevel } from 'app/logging/logger';
 import type { ProgressImage } from 'services/events/types';
 import { z } from 'zod';
 
-export type SystemStatus = 'CONNECTED' | 'DISCONNECTED' | 'PROCESSING' | 'ERROR' | 'LOADING_MODEL';
+type SystemStatus = 'CONNECTED' | 'DISCONNECTED' | 'PROCESSING' | 'ERROR' | 'LOADING_MODEL';
 
-export type DenoiseProgress = {
+type DenoiseProgress = {
   session_id: string;
   batch_id: string;
   progress_image: ProgressImage | null | undefined;
diff --git a/invokeai/frontend/web/src/features/ui/components/InvokeTabs.tsx b/invokeai/frontend/web/src/features/ui/components/InvokeTabs.tsx
index c6682e33fc..cb49696dbf 100644
--- a/invokeai/frontend/web/src/features/ui/components/InvokeTabs.tsx
+++ b/invokeai/frontend/web/src/features/ui/components/InvokeTabs.tsx
@@ -35,7 +35,7 @@ import ResizeHandle from './tabs/ResizeHandle';
 import TextToImageTab from './tabs/TextToImageTab';
 import UnifiedCanvasTab from './tabs/UnifiedCanvasTab';
 
-export interface InvokeTabInfo {
+interface InvokeTabInfo {
   id: InvokeTabName;
   translationKey: string;
   icon: ReactElement;
diff --git a/invokeai/frontend/web/src/services/api/endpoints/models.ts b/invokeai/frontend/web/src/services/api/endpoints/models.ts
index e7e63eeecc..04c65b59f6 100644
--- a/invokeai/frontend/web/src/services/api/endpoints/models.ts
+++ b/invokeai/frontend/web/src/services/api/endpoints/models.ts
@@ -64,7 +64,7 @@ export type ScanFolderResponse =
   paths['/api/v2/models/scan_folder']['get']['responses']['200']['content']['application/json'];
 type ScanFolderArg = operations['scan_for_models']['parameters']['query'];
 
-export type GetByAttrsArg = operations['get_model_records_by_attrs']['parameters']['query'];
+type GetByAttrsArg = operations['get_model_records_by_attrs']['parameters']['query'];
 
 const mainModelsAdapter = createEntityAdapter<MainModelConfig, string>({
   selectId: (entity) => entity.key,
diff --git a/invokeai/frontend/web/src/services/api/schema.ts b/invokeai/frontend/web/src/services/api/schema.ts
index 0dbe908979..de3761b946 100644
--- a/invokeai/frontend/web/src/services/api/schema.ts
+++ b/invokeai/frontend/web/src/services/api/schema.ts
@@ -572,7 +572,7 @@ export type paths = {
   };
 };
 
-export type webhooks = Record<string, never>;
+type webhooks = Record<string, never>;
 
 export type components = {
   schemas: {
@@ -10929,9 +10929,9 @@ export type components = {
   pathItems: never;
 };
 
-export type $defs = Record<string, never>;
+type $defs = Record<string, never>;
 
-export type external = Record<string, never>;
+type external = Record<string, never>;
 
 export type operations = {
 
diff --git a/invokeai/frontend/web/src/services/api/types.ts b/invokeai/frontend/web/src/services/api/types.ts
index c57d242f97..e28c8bdae6 100644
--- a/invokeai/frontend/web/src/services/api/types.ts
+++ b/invokeai/frontend/web/src/services/api/types.ts
@@ -12,8 +12,6 @@ export type ListImagesArgs = NonNullable<paths['/api/v1/images/']['get']['parame
 export type DeleteBoardResult =
   paths['/api/v1/boards/{board_id}']['delete']['responses']['200']['content']['application/json'];
 
-export type ListBoardsArg = NonNullable<paths['/api/v1/boards/']['get']['parameters']['query']>;
-
 export type UpdateBoardArg = paths['/api/v1/boards/{board_id}']['patch']['parameters']['path'] & {
   changes: paths['/api/v1/boards/{board_id}']['patch']['requestBody']['content']['application/json'];
 };
@@ -21,8 +19,6 @@ export type UpdateBoardArg = paths['/api/v1/boards/{board_id}']['patch']['parame
 export type BatchConfig =
   paths['/api/v1/queue/{queue_id}/enqueue_batch']['post']['requestBody']['content']['application/json'];
 
-export type EnqueueBatchResult = components['schemas']['EnqueueBatchResult'];
-
 export type InputFieldJSONSchemaExtra = S['InputFieldJSONSchemaExtra'];
 export type OutputFieldJSONSchemaExtra = S['OutputFieldJSONSchemaExtra'];
 export type InvocationJSONSchemaExtra = S['UIConfigBase'];
@@ -35,26 +31,14 @@ export type AppDependencyVersions = S['AppDependencyVersions'];
 // Images
 export type ImageDTO = S['ImageDTO'];
 export type BoardDTO = S['BoardDTO'];
-export type BoardChanges = S['BoardChanges'];
-export type ImageChanges = S['ImageRecordChanges'];
 export type ImageCategory = S['ImageCategory'];
-export type ResourceOrigin = S['ResourceOrigin'];
-export type ImageField = S['ImageField'];
-export type OffsetPaginatedResults_BoardDTO_ = S['OffsetPaginatedResults_BoardDTO_'];
 export type OffsetPaginatedResults_ImageDTO_ = S['OffsetPaginatedResults_ImageDTO_'];
 
 // Models
 export type ModelType = S['ModelType'];
 export type SubModelType = S['SubModelType'];
 export type BaseModelType = S['BaseModelType'];
-export type MainModelField = S['MainModelField'];
-export type VAEModelField = S['VAEModelField'];
-export type LoRAModelField = S['LoRAModelField'];
-export type ControlNetModelField = S['ControlNetModelField'];
-export type IPAdapterModelField = S['IPAdapterModelField'];
-export type T2IAdapterModelField = S['T2IAdapterModelField'];
 export type ControlField = S['ControlField'];
-export type IPAdapterField = S['IPAdapterField'];
 
 // Model Configs
 
@@ -113,7 +97,6 @@ export type ModelInstallJob = S['ModelInstallJob'];
 export type ModelInstallStatus = S['InstallStatus'];
 
 export type HFModelSource = S['HFModelSource'];
-export type CivitaiModelSource = S['CivitaiModelSource'];
 export type LocalModelSource = S['LocalModelSource'];
 export type URLModelSource = S['URLModelSource'];
 
@@ -124,50 +107,31 @@ export type Edge = S['Edge'];
 export type GraphExecutionState = S['GraphExecutionState'];
 export type Batch = S['Batch'];
 export type SessionQueueItemDTO = S['SessionQueueItemDTO'];
-export type SessionQueueItem = S['SessionQueueItem'];
 export type WorkflowRecordOrderBy = S['WorkflowRecordOrderBy'];
 export type SQLiteDirection = S['SQLiteDirection'];
-export type WorkflowDTO = S['WorkflowRecordDTO'];
 export type WorkflowRecordListItemDTO = S['WorkflowRecordListItemDTO'];
 
 // General nodes
 export type CollectInvocation = S['CollectInvocation'];
-export type IterateInvocation = S['IterateInvocation'];
-export type RangeInvocation = S['RangeInvocation'];
-export type RandomRangeInvocation = S['RandomRangeInvocation'];
-export type RangeOfSizeInvocation = S['RangeOfSizeInvocation'];
 export type ImageResizeInvocation = S['ImageResizeInvocation'];
-export type ImageBlurInvocation = S['ImageBlurInvocation'];
-export type ImageScaleInvocation = S['ImageScaleInvocation'];
 export type InfillPatchMatchInvocation = S['InfillPatchMatchInvocation'];
 export type InfillTileInvocation = S['InfillTileInvocation'];
 export type CreateDenoiseMaskInvocation = S['CreateDenoiseMaskInvocation'];
 export type CreateGradientMaskInvocation = S['CreateGradientMaskInvocation'];
 export type CanvasPasteBackInvocation = S['CanvasPasteBackInvocation'];
-export type MaskEdgeInvocation = S['MaskEdgeInvocation'];
-export type RandomIntInvocation = S['RandomIntInvocation'];
-export type CompelInvocation = S['CompelInvocation'];
-export type DynamicPromptInvocation = S['DynamicPromptInvocation'];
 export type NoiseInvocation = S['NoiseInvocation'];
 export type DenoiseLatentsInvocation = S['DenoiseLatentsInvocation'];
 export type SDXLLoraLoaderInvocation = S['SDXLLoraLoaderInvocation'];
 export type ImageToLatentsInvocation = S['ImageToLatentsInvocation'];
 export type LatentsToImageInvocation = S['LatentsToImageInvocation'];
-export type ImageCollectionInvocation = S['ImageCollectionInvocation'];
-export type MainModelLoaderInvocation = S['MainModelLoaderInvocation'];
 export type LoraLoaderInvocation = S['LoraLoaderInvocation'];
 export type ESRGANInvocation = S['ESRGANInvocation'];
-export type DivideInvocation = S['DivideInvocation'];
 export type ImageNSFWBlurInvocation = S['ImageNSFWBlurInvocation'];
 export type ImageWatermarkInvocation = S['ImageWatermarkInvocation'];
 export type SeamlessModeInvocation = S['SeamlessModeInvocation'];
-export type MetadataInvocation = S['MetadataInvocation'];
 export type CoreMetadataInvocation = S['CoreMetadataInvocation'];
-export type MetadataItemInvocation = S['MetadataItemInvocation'];
-export type MergeMetadataInvocation = S['MergeMetadataInvocation'];
 export type IPAdapterMetadataField = S['IPAdapterMetadataField'];
 export type T2IAdapterField = S['T2IAdapterField'];
-export type LoRAMetadataField = S['LoRAMetadataField'];
 
 // ControlNet Nodes
 export type ControlNetInvocation = S['ControlNetInvocation'];
@@ -190,40 +154,34 @@ export type ZoeDepthImageProcessorInvocation = S['ZoeDepthImageProcessorInvocati
 
 // Node Outputs
 export type ImageOutput = S['ImageOutput'];
-export type StringOutput = S['StringOutput'];
-export type FloatOutput = S['FloatOutput'];
-export type IntegerOutput = S['IntegerOutput'];
-export type IterateInvocationOutput = S['IterateInvocationOutput'];
-export type CollectInvocationOutput = S['CollectInvocationOutput'];
-export type LatentsOutput = S['LatentsOutput'];
 
 // Post-image upload actions, controls workflows when images are uploaded
 
-export type ControlAdapterAction = {
+type ControlAdapterAction = {
   type: 'SET_CONTROL_ADAPTER_IMAGE';
   id: string;
 };
 
-export type InitialImageAction = {
+type InitialImageAction = {
   type: 'SET_INITIAL_IMAGE';
 };
 
-export type NodesAction = {
+type NodesAction = {
   type: 'SET_NODES_IMAGE';
   nodeId: string;
   fieldName: string;
 };
 
-export type CanvasInitialImageAction = {
+type CanvasInitialImageAction = {
   type: 'SET_CANVAS_INITIAL_IMAGE';
 };
 
-export type ToastAction = {
+type ToastAction = {
   type: 'TOAST';
   toastOptions?: UseToastOptions;
 };
 
-export type AddToBatchAction = {
+type AddToBatchAction = {
   type: 'ADD_TO_BATCH';
 };
 
diff --git a/invokeai/frontend/web/src/services/events/types.ts b/invokeai/frontend/web/src/services/events/types.ts
index ab5b0e6799..6fda5a16b1 100644
--- a/invokeai/frontend/web/src/services/events/types.ts
+++ b/invokeai/frontend/web/src/services/events/types.ts
@@ -14,7 +14,7 @@ export type AnyInvocation = NonNullable<NonNullable<Graph['nodes']>[string]>;
 
 export type AnyResult = NonNullable<GraphExecutionState['results'][string]>;
 
-export type BaseNode = {
+type BaseNode = {
   id: string;
   type: string;
   [key: string]: AnyInvocation[keyof AnyInvocation];
@@ -218,11 +218,11 @@ export type QueueItemStatusChangedEvent = {
   };
 };
 
-export type ClientEmitSubscribeQueue = {
+type ClientEmitSubscribeQueue = {
   queue_id: string;
 };
 
-export type ClientEmitUnsubscribeQueue = {
+type ClientEmitUnsubscribeQueue = {
   queue_id: string;
 };
 
@@ -245,11 +245,11 @@ export type BulkDownloadFailedEvent = {
   error: string;
 };
 
-export type ClientEmitSubscribeBulkDownload = {
+type ClientEmitSubscribeBulkDownload = {
   bulk_download_id: string;
 };
 
-export type ClientEmitUnsubscribeBulkDownload = {
+type ClientEmitUnsubscribeBulkDownload = {
   bulk_download_id: string;
 };
 

From d90210fea6880665c4393f602e5e8c67bad2b9d1 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 27 Feb 2024 18:17:25 +1100
Subject: [PATCH 347/411] tidy(ui): clean up unused code 6

unused files
---
 .../src/features/nodes/types/v2/constants.ts  | 80 -----------------
 .../web/src/features/nodes/types/v2/error.ts  | 58 -------------
 .../src/features/nodes/types/v2/metadata.ts   | 77 -----------------
 .../src/features/nodes/types/v2/openapi.ts    | 86 -------------------
 4 files changed, 301 deletions(-)
 delete mode 100644 invokeai/frontend/web/src/features/nodes/types/v2/constants.ts
 delete mode 100644 invokeai/frontend/web/src/features/nodes/types/v2/error.ts
 delete mode 100644 invokeai/frontend/web/src/features/nodes/types/v2/metadata.ts
 delete mode 100644 invokeai/frontend/web/src/features/nodes/types/v2/openapi.ts

diff --git a/invokeai/frontend/web/src/features/nodes/types/v2/constants.ts b/invokeai/frontend/web/src/features/nodes/types/v2/constants.ts
deleted file mode 100644
index 35ef9e9fd2..0000000000
--- a/invokeai/frontend/web/src/features/nodes/types/v2/constants.ts
+++ /dev/null
@@ -1,80 +0,0 @@
-import type { Node } from 'reactflow';
-
-/**
- * How long to wait before showing a tooltip when hovering a field handle.
- */
-export const HANDLE_TOOLTIP_OPEN_DELAY = 500;
-
-/**
- * The width of a node in the UI in pixels.
- */
-export const NODE_WIDTH = 320;
-
-/**
- * This class name is special - reactflow uses it to identify the drag handle of a node,
- * applying the appropriate listeners to it.
- */
-export const DRAG_HANDLE_CLASSNAME = 'node-drag-handle';
-
-/**
- * reactflow-specifc properties shared between all node types.
- */
-export const SHARED_NODE_PROPERTIES: Partial<Node> = {
-  dragHandle: `.${DRAG_HANDLE_CLASSNAME}`,
-};
-
-/**
- * Helper for getting the kind of a field.
- */
-export const KIND_MAP = {
-  input: 'inputs' as const,
-  output: 'outputs' as const,
-};
-
-/**
- * Model types' handles are rendered as squares in the UI.
- */
-export const MODEL_TYPES = [
-  'IPAdapterModelField',
-  'ControlNetModelField',
-  'LoRAModelField',
-  'MainModelField',
-  'SDXLMainModelField',
-  'SDXLRefinerModelField',
-  'VaeModelField',
-  'UNetField',
-  'VaeField',
-  'ClipField',
-  'T2IAdapterModelField',
-  'IPAdapterModelField',
-];
-
-/**
- * Colors for each field type - applies to their handles and edges.
- */
-export const FIELD_COLORS: { [key: string]: string } = {
-  BoardField: 'purple.500',
-  BooleanField: 'green.500',
-  ClipField: 'green.500',
-  ColorField: 'pink.300',
-  ConditioningField: 'cyan.500',
-  ControlField: 'teal.500',
-  ControlNetModelField: 'teal.500',
-  EnumField: 'blue.500',
-  FloatField: 'orange.500',
-  ImageField: 'purple.500',
-  IntegerField: 'red.500',
-  IPAdapterField: 'teal.500',
-  IPAdapterModelField: 'teal.500',
-  LatentsField: 'pink.500',
-  LoRAModelField: 'teal.500',
-  MainModelField: 'teal.500',
-  SDXLMainModelField: 'teal.500',
-  SDXLRefinerModelField: 'teal.500',
-  StringField: 'yellow.500',
-  T2IAdapterField: 'teal.500',
-  T2IAdapterModelField: 'teal.500',
-  UNetField: 'red.500',
-  VaeField: 'blue.500',
-  VaeModelField: 'teal.500',
-};
diff --git a/invokeai/frontend/web/src/features/nodes/types/v2/error.ts b/invokeai/frontend/web/src/features/nodes/types/v2/error.ts
deleted file mode 100644
index 905b487fb0..0000000000
--- a/invokeai/frontend/web/src/features/nodes/types/v2/error.ts
+++ /dev/null
@@ -1,58 +0,0 @@
-/**
- * Invalid Workflow Version Error
- * Raised when a workflow version is not recognized.
- */
-export class WorkflowVersionError extends Error {
-  /**
-   * Create WorkflowVersionError
-   * @param {String} message
-   */
-  constructor(message: string) {
-    super(message);
-    this.name = this.constructor.name;
-  }
-}
-/**
- * Workflow Migration Error
- * Raised when a workflow migration fails.
- */
-export class WorkflowMigrationError extends Error {
-  /**
-   * Create WorkflowMigrationError
-   * @param {String} message
-   */
-  constructor(message: string) {
-    super(message);
-    this.name = this.constructor.name;
-  }
-}
-
-/**
- * Unable to Update Node Error
- * Raised when a node cannot be updated.
- */
-export class NodeUpdateError extends Error {
-  /**
-   * Create NodeUpdateError
-   * @param {String} message
-   */
-  constructor(message: string) {
-    super(message);
-    this.name = this.constructor.name;
-  }
-}
-
-/**
- * FieldParseError
- * Raised when a field cannot be parsed from a field schema.
- */
-export class FieldParseError extends Error {
-  /**
-   * Create FieldTypeParseError
-   * @param {String} message
-   */
-  constructor(message: string) {
-    super(message);
-    this.name = this.constructor.name;
-  }
-}
diff --git a/invokeai/frontend/web/src/features/nodes/types/v2/metadata.ts b/invokeai/frontend/web/src/features/nodes/types/v2/metadata.ts
deleted file mode 100644
index 0cc30499e3..0000000000
--- a/invokeai/frontend/web/src/features/nodes/types/v2/metadata.ts
+++ /dev/null
@@ -1,77 +0,0 @@
-import { z } from 'zod';
-
-import {
-  zControlField,
-  zIPAdapterField,
-  zLoRAModelField,
-  zMainModelField,
-  zSDXLRefinerModelField,
-  zT2IAdapterField,
-  zVAEModelField,
-} from './common';
-
-// #region Metadata-optimized versions of schemas
-// TODO: It's possible that `deepPartial` will be deprecated:
-// - https://github.com/colinhacks/zod/issues/2106
-// - https://github.com/colinhacks/zod/issues/2854
-export const zLoRAMetadataItem = z.object({
-  lora: zLoRAModelField.deepPartial(),
-  weight: z.number(),
-});
-const zControlNetMetadataItem = zControlField.deepPartial();
-const zIPAdapterMetadataItem = zIPAdapterField.deepPartial();
-const zT2IAdapterMetadataItem = zT2IAdapterField.deepPartial();
-const zSDXLRefinerModelMetadataItem = zSDXLRefinerModelField.deepPartial();
-const zModelMetadataItem = zMainModelField.deepPartial();
-const zVAEModelMetadataItem = zVAEModelField.deepPartial();
-export type LoRAMetadataItem = z.infer<typeof zLoRAMetadataItem>;
-export type ControlNetMetadataItem = z.infer<typeof zControlNetMetadataItem>;
-export type IPAdapterMetadataItem = z.infer<typeof zIPAdapterMetadataItem>;
-export type T2IAdapterMetadataItem = z.infer<typeof zT2IAdapterMetadataItem>;
-export type SDXLRefinerModelMetadataItem = z.infer<typeof zSDXLRefinerModelMetadataItem>;
-export type ModelMetadataItem = z.infer<typeof zModelMetadataItem>;
-export type VAEModelMetadataItem = z.infer<typeof zVAEModelMetadataItem>;
-// #endregion
-
-// #region CoreMetadata
-export const zCoreMetadata = z
-  .object({
-    app_version: z.string().nullish().catch(null),
-    generation_mode: z.string().nullish().catch(null),
-    created_by: z.string().nullish().catch(null),
-    positive_prompt: z.string().nullish().catch(null),
-    negative_prompt: z.string().nullish().catch(null),
-    width: z.number().int().nullish().catch(null),
-    height: z.number().int().nullish().catch(null),
-    seed: z.number().int().nullish().catch(null),
-    rand_device: z.string().nullish().catch(null),
-    cfg_scale: z.number().nullish().catch(null),
-    cfg_rescale_multiplier: z.number().nullish().catch(null),
-    steps: z.number().int().nullish().catch(null),
-    scheduler: z.string().nullish().catch(null),
-    clip_skip: z.number().int().nullish().catch(null),
-    model: zModelMetadataItem.nullish().catch(null),
-    controlnets: z.array(zControlNetMetadataItem).nullish().catch(null),
-    ipAdapters: z.array(zIPAdapterMetadataItem).nullish().catch(null),
-    t2iAdapters: z.array(zT2IAdapterMetadataItem).nullish().catch(null),
-    loras: z.array(zLoRAMetadataItem).nullish().catch(null),
-    vae: zVAEModelMetadataItem.nullish().catch(null),
-    strength: z.number().nullish().catch(null),
-    hrf_enabled: z.boolean().nullish().catch(null),
-    hrf_strength: z.number().nullish().catch(null),
-    hrf_method: z.string().nullish().catch(null),
-    init_image: z.string().nullish().catch(null),
-    positive_style_prompt: z.string().nullish().catch(null),
-    negative_style_prompt: z.string().nullish().catch(null),
-    refiner_model: zSDXLRefinerModelMetadataItem.nullish().catch(null),
-    refiner_cfg_scale: z.number().nullish().catch(null),
-    refiner_steps: z.number().int().nullish().catch(null),
-    refiner_scheduler: z.string().nullish().catch(null),
-    refiner_positive_aesthetic_score: z.number().nullish().catch(null),
-    refiner_negative_aesthetic_score: z.number().nullish().catch(null),
-    refiner_start: z.number().nullish().catch(null),
-  })
-  .passthrough();
-export type CoreMetadata = z.infer<typeof zCoreMetadata>;
-
-// #endregion
diff --git a/invokeai/frontend/web/src/features/nodes/types/v2/openapi.ts b/invokeai/frontend/web/src/features/nodes/types/v2/openapi.ts
deleted file mode 100644
index 83d774439a..0000000000
--- a/invokeai/frontend/web/src/features/nodes/types/v2/openapi.ts
+++ /dev/null
@@ -1,86 +0,0 @@
-import type { OpenAPIV3_1 } from 'openapi-types';
-import type {
-  InputFieldJSONSchemaExtra,
-  InvocationJSONSchemaExtra,
-  OutputFieldJSONSchemaExtra,
-} from 'services/api/types';
-
-// Janky customization of OpenAPI Schema :/
-
-export type InvocationSchemaExtra = InvocationJSONSchemaExtra & {
-  output: OpenAPIV3_1.ReferenceObject; // the output of the invocation
-  title: string;
-  category?: string;
-  tags?: string[];
-  version: string;
-  properties: Omit<
-    NonNullable<OpenAPIV3_1.SchemaObject['properties']> & (InputFieldJSONSchemaExtra | OutputFieldJSONSchemaExtra),
-    'type'
-  > & {
-    type: Omit<OpenAPIV3_1.SchemaObject, 'default'> & {
-      default: string;
-    };
-    use_cache: Omit<OpenAPIV3_1.SchemaObject, 'default'> & {
-      default: boolean;
-    };
-  };
-};
-
-export type InvocationSchemaType = {
-  default: string; // the type of the invocation
-};
-
-export type InvocationBaseSchemaObject = Omit<OpenAPIV3_1.BaseSchemaObject, 'title' | 'type' | 'properties'> &
-  InvocationSchemaExtra;
-
-export type InvocationOutputSchemaObject = Omit<OpenAPIV3_1.SchemaObject, 'properties'> & {
-  properties: OpenAPIV3_1.SchemaObject['properties'] & {
-    type: Omit<OpenAPIV3_1.SchemaObject, 'default'> & {
-      default: string;
-    };
-  } & {
-    class: 'output';
-  };
-};
-
-export type InvocationFieldSchema = OpenAPIV3_1.SchemaObject & InputFieldJSONSchemaExtra;
-
-export type OpenAPIV3_1SchemaOrRef = OpenAPIV3_1.ReferenceObject | OpenAPIV3_1.SchemaObject;
-
-export interface ArraySchemaObject extends InvocationBaseSchemaObject {
-  type: OpenAPIV3_1.ArraySchemaObjectType;
-  items: OpenAPIV3_1.ReferenceObject | OpenAPIV3_1.SchemaObject;
-}
-export interface NonArraySchemaObject extends InvocationBaseSchemaObject {
-  type?: OpenAPIV3_1.NonArraySchemaObjectType;
-}
-
-export type InvocationSchemaObject = (ArraySchemaObject | NonArraySchemaObject) & { class: 'invocation' };
-
-export const isSchemaObject = (
-  obj: OpenAPIV3_1.ReferenceObject | OpenAPIV3_1.SchemaObject | undefined
-): obj is OpenAPIV3_1.SchemaObject => Boolean(obj && !('$ref' in obj));
-
-export const isArraySchemaObject = (
-  obj: OpenAPIV3_1.ReferenceObject | OpenAPIV3_1.SchemaObject | undefined
-): obj is OpenAPIV3_1.ArraySchemaObject => Boolean(obj && !('$ref' in obj) && obj.type === 'array');
-
-export const isNonArraySchemaObject = (
-  obj: OpenAPIV3_1.ReferenceObject | OpenAPIV3_1.SchemaObject | undefined
-): obj is OpenAPIV3_1.NonArraySchemaObject => Boolean(obj && !('$ref' in obj) && obj.type !== 'array');
-
-export const isRefObject = (
-  obj: OpenAPIV3_1.ReferenceObject | OpenAPIV3_1.SchemaObject | undefined
-): obj is OpenAPIV3_1.ReferenceObject => Boolean(obj && '$ref' in obj);
-
-export const isInvocationSchemaObject = (
-  obj: OpenAPIV3_1.ReferenceObject | OpenAPIV3_1.SchemaObject | InvocationSchemaObject
-): obj is InvocationSchemaObject => 'class' in obj && obj.class === 'invocation';
-
-export const isInvocationOutputSchemaObject = (
-  obj: OpenAPIV3_1.ReferenceObject | OpenAPIV3_1.SchemaObject | InvocationOutputSchemaObject
-): obj is InvocationOutputSchemaObject => 'class' in obj && obj.class === 'output';
-
-export const isInvocationFieldSchema = (
-  obj: OpenAPIV3_1.ReferenceObject | OpenAPIV3_1.SchemaObject
-): obj is InvocationFieldSchema => !('$ref' in obj);

From 1176c549c07d56cc18837f371b74d517ad46c6f2 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 27 Feb 2024 18:25:50 +1100
Subject: [PATCH 348/411] feat(ui): configure knip

---
 invokeai/frontend/web/knip.ts      | 14 ++++++++++++++
 invokeai/frontend/web/package.json |  6 +++---
 2 files changed, 17 insertions(+), 3 deletions(-)

diff --git a/invokeai/frontend/web/knip.ts b/invokeai/frontend/web/knip.ts
index 479dd27a96..a96b96f1f7 100644
--- a/invokeai/frontend/web/knip.ts
+++ b/invokeai/frontend/web/knip.ts
@@ -6,6 +6,20 @@ const config: KnipConfig = {
     'src/app/store/middleware/debugLoggerMiddleware.ts',
   ],
   ignoreBinaries: ['only-allow'],
+  rules: {
+    files: 'warn',
+    dependencies: 'warn',
+    unlisted: 'warn',
+    binaries: 'warn',
+    unresolved: 'warn',
+    exports: 'warn',
+    types: 'warn',
+    nsExports: 'warn',
+    nsTypes: 'warn',
+    enumMembers: 'warn',
+    classMembers: 'warn',
+    duplicates: 'warn',
+  },
 };
 
 export default config;
diff --git a/invokeai/frontend/web/package.json b/invokeai/frontend/web/package.json
index 8e8faa5c84..abc9ac059b 100644
--- a/invokeai/frontend/web/package.json
+++ b/invokeai/frontend/web/package.json
@@ -24,16 +24,16 @@
     "build": "pnpm run lint && vite build",
     "typegen": "node scripts/typegen.js",
     "preview": "vite preview",
+    "lint:knip": "knip",
     "lint:madge": "madge --circular src/main.tsx",
     "lint:eslint": "eslint --max-warnings=0 .",
     "lint:prettier": "prettier --check .",
     "lint:tsc": "tsc --noEmit",
-    "lint": "concurrently -g -n eslint,prettier,tsc,madge -c cyan,green,magenta,yellow \"pnpm run lint:eslint\" \"pnpm run lint:prettier\" \"pnpm run lint:tsc\" \"pnpm run lint:madge\"",
-    "fix": "eslint --fix . && prettier --log-level warn --write .",
+    "lint": "concurrently -g -c red,green,yellow,blue,magenta pnpm:lint:*",
+    "fix": "knip --fix && eslint --fix . && prettier --log-level warn --write .",
     "preinstall": "npx only-allow pnpm",
     "storybook": "storybook dev -p 6006",
     "build-storybook": "storybook build",
-    "knip": "knip",
     "test": "vitest",
     "test:no-watch": "vitest --no-watch"
   },

From aafa464707b747da5e0aacc0aaff8d527b620e6d Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 27 Feb 2024 18:26:04 +1100
Subject: [PATCH 349/411] ci: add knip to ui check workflow

---
 .github/workflows/lint-frontend.yml | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/.github/workflows/lint-frontend.yml b/.github/workflows/lint-frontend.yml
index a4e1bba428..96167bbeca 100644
--- a/.github/workflows/lint-frontend.yml
+++ b/.github/workflows/lint-frontend.yml
@@ -41,3 +41,5 @@ jobs:
         run: 'pnpm run lint:eslint'
       - name: Prettier
         run: 'pnpm run lint:prettier'
+      - name: Knip
+        run: 'pnpm run lint:knip'

From 37608cdea26325b1f944253d3cd531b050f47d0f Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 27 Feb 2024 18:26:45 +1100
Subject: [PATCH 350/411] chore(ui): update pnpm-lock.yaml

Forgot to run `pnpm i` earlier after removing packages.
---
 invokeai/frontend/web/pnpm-lock.yaml | 243 ---------------------------
 1 file changed, 243 deletions(-)

diff --git a/invokeai/frontend/web/pnpm-lock.yaml b/invokeai/frontend/web/pnpm-lock.yaml
index e691b44421..113189cffb 100644
--- a/invokeai/frontend/web/pnpm-lock.yaml
+++ b/invokeai/frontend/web/pnpm-lock.yaml
@@ -169,9 +169,6 @@ devDependencies:
   '@invoke-ai/prettier-config-react':
     specifier: ^0.0.7
     version: 0.0.7(prettier@3.2.5)
-  '@storybook/addon-docs':
-    specifier: ^7.6.17
-    version: 7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
   '@storybook/addon-essentials':
     specifier: ^7.6.17
     version: 7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
@@ -184,9 +181,6 @@ devDependencies:
   '@storybook/addon-storysource':
     specifier: ^7.6.17
     version: 7.6.17
-  '@storybook/blocks':
-    specifier: ^7.6.17
-    version: 7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
   '@storybook/manager-api':
     specifier: ^7.6.17
     version: 7.6.17(react-dom@18.2.0)(react@18.2.0)
@@ -196,9 +190,6 @@ devDependencies:
   '@storybook/react-vite':
     specifier: ^7.6.17
     version: 7.6.17(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)(vite@5.1.3)
-  '@storybook/test':
-    specifier: ^7.6.17
-    version: 7.6.17(vitest@1.3.1)
   '@storybook/theming':
     specifier: ^7.6.17
     version: 7.6.17(react-dom@18.2.0)(react@18.2.0)
@@ -291,10 +282,6 @@ packages:
     engines: {node: '>=0.10.0'}
     dev: true
 
-  /@adobe/css-tools@4.3.3:
-    resolution: {integrity: sha512-rE0Pygv0sEZ4vBWHlAgJLGDU7Pm8xoO6p3wsEceb7GYAjScrOHpEo8KK/eVkAcnSM+slAEtXjA2JpdjLp4fJQQ==}
-    dev: true
-
   /@ampproject/remapping@2.2.1:
     resolution: {integrity: sha512-lFMjJTrFL3j7L9yBxwYfCq2k6qqwHyzuUl/XBnif78PWTJYyL/dfowQHWE3sp6U6ZzqWiiIZnpTMO96zhkjwtg==}
     engines: {node: '>=6.0.0'}
@@ -5668,18 +5655,6 @@ packages:
     resolution: {integrity: sha512-FcOqPAXACP0I3oJ/ws6/rrPT9WGhu915Cg8D02a9YxLo0DE9zI+a9A5gRGvmQ09fiWPukqI8ZAEoQEdWUKMQdQ==}
     dev: true
 
-  /@storybook/instrumenter@7.6.17:
-    resolution: {integrity: sha512-zTLIPTt1fvlWgkIVUyQpF327iVE+EiPdpM0Or0aARaNfIikPRBTcjU+6cK96E+Ust2E1qKajEjIuv4i4lLQPng==}
-    dependencies:
-      '@storybook/channels': 7.6.17
-      '@storybook/client-logger': 7.6.17
-      '@storybook/core-events': 7.6.17
-      '@storybook/global': 5.0.0
-      '@storybook/preview-api': 7.6.17
-      '@vitest/utils': 0.34.7
-      util: 0.12.5
-    dev: true
-
   /@storybook/manager-api@7.6.17(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-IJIV1Yc6yw1dhCY4tReHCfBnUKDqEBnMyHp3mbXpsaHxnxJZrXO45WjRAZIKlQKhl/Ge1CrnznmHRCmYgqmrWg==}
     dependencies:
@@ -5852,29 +5827,6 @@ packages:
       - supports-color
     dev: true
 
-  /@storybook/test@7.6.17(vitest@1.3.1):
-    resolution: {integrity: sha512-WGrmUUtKiuq3bzDsN4MUvluGcX120jwczMik1GDTyxS+JBoe7P0t2Y8dDuVs/l3nZd1J7qY4z0RGxMDYqONIOw==}
-    dependencies:
-      '@storybook/client-logger': 7.6.17
-      '@storybook/core-events': 7.6.17
-      '@storybook/instrumenter': 7.6.17
-      '@storybook/preview-api': 7.6.17
-      '@testing-library/dom': 9.3.4
-      '@testing-library/jest-dom': 6.4.2(vitest@1.3.1)
-      '@testing-library/user-event': 14.3.0(@testing-library/dom@9.3.4)
-      '@types/chai': 4.3.11
-      '@vitest/expect': 0.34.7
-      '@vitest/spy': 0.34.7
-      chai: 4.4.1
-      util: 0.12.5
-    transitivePeerDependencies:
-      - '@jest/globals'
-      - '@types/bun'
-      - '@types/jest'
-      - jest
-      - vitest
-    dev: true
-
   /@storybook/theming@7.6.17(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-ZbaBt3KAbmBtfjNqgMY7wPMBshhSJlhodyMNQypv+95xLD/R+Az6aBYbpVAOygLaUQaQk4ar7H/Ww6lFIoiFbA==}
     peerDependencies:
@@ -6027,69 +5979,10 @@ packages:
     resolution: {integrity: sha512-myfUej5naTBWnqOCc/MdVOLVjXUXtIA+NpDrDBKJtLLg2shUjBu3cZmB/85RyitKc55+lUUyl7oRfLOvkr2hsw==}
     dev: true
 
-  /@testing-library/dom@9.3.4:
-    resolution: {integrity: sha512-FlS4ZWlp97iiNWig0Muq8p+3rVDjRiYE+YKGbAqXOu9nwJFFOdL00kFpz42M+4huzYi86vAK1sOOfyOG45muIQ==}
-    engines: {node: '>=14'}
-    dependencies:
-      '@babel/code-frame': 7.23.5
-      '@babel/runtime': 7.23.9
-      '@types/aria-query': 5.0.4
-      aria-query: 5.1.3
-      chalk: 4.1.2
-      dom-accessibility-api: 0.5.16
-      lz-string: 1.5.0
-      pretty-format: 27.5.1
-    dev: true
-
-  /@testing-library/jest-dom@6.4.2(vitest@1.3.1):
-    resolution: {integrity: sha512-CzqH0AFymEMG48CpzXFriYYkOjk6ZGPCLMhW9e9jg3KMCn5OfJecF8GtGW7yGfR/IgCe3SX8BSwjdzI6BBbZLw==}
-    engines: {node: '>=14', npm: '>=6', yarn: '>=1'}
-    peerDependencies:
-      '@jest/globals': '>= 28'
-      '@types/bun': latest
-      '@types/jest': '>= 28'
-      jest: '>= 28'
-      vitest: '>= 0.32'
-    peerDependenciesMeta:
-      '@jest/globals':
-        optional: true
-      '@types/bun':
-        optional: true
-      '@types/jest':
-        optional: true
-      jest:
-        optional: true
-      vitest:
-        optional: true
-    dependencies:
-      '@adobe/css-tools': 4.3.3
-      '@babel/runtime': 7.23.9
-      aria-query: 5.3.0
-      chalk: 3.0.0
-      css.escape: 1.5.1
-      dom-accessibility-api: 0.6.3
-      lodash: 4.17.21
-      redent: 3.0.0
-      vitest: 1.3.1(@types/node@20.11.19)
-    dev: true
-
-  /@testing-library/user-event@14.3.0(@testing-library/dom@9.3.4):
-    resolution: {integrity: sha512-P02xtBBa8yMaLhK8CzJCIns8rqwnF6FxhR9zs810flHOBXUYCFjLd8Io1rQrAkQRWEmW2PGdZIEdMxf/KLsqFA==}
-    engines: {node: '>=12', npm: '>=6'}
-    peerDependencies:
-      '@testing-library/dom': '>=7.21.4'
-    dependencies:
-      '@testing-library/dom': 9.3.4
-    dev: true
-
   /@types/argparse@1.0.38:
     resolution: {integrity: sha512-ebDJ9b0e702Yr7pWgB0jzm+CX4Srzz8RcXtLJDJB+BSccqMa36uyH/zUsSYao5+BD1ytv3k3rPYCq4mAE1hsXA==}
     dev: true
 
-  /@types/aria-query@5.0.4:
-    resolution: {integrity: sha512-rfT93uj5s0PRL7EzccGMs3brplhcrghnDoV26NqKhCAS1hVo+WdNsPvE/yb6ilfr5hi2MEk6d5EWJTKdxg8jVw==}
-    dev: true
-
   /@types/babel__core@7.20.5:
     resolution: {integrity: sha512-qoQprZvz5wQFJwMDqeseRXWv3rqMvhgpbXFfVyWhbx9X47POIA6i/+dXefEmZKoAgOaTdaIgNSMqMIU61yRyzA==}
     dependencies:
@@ -6126,10 +6019,6 @@ packages:
       '@types/node': 20.11.19
     dev: true
 
-  /@types/chai@4.3.11:
-    resolution: {integrity: sha512-qQR1dr2rGIHYlJulmr8Ioq3De0Le9E4MJ5AiaeAETJJpndT1uUNHsGFK3L/UIu+rbkQSdj8J/w2bCsBZc/Y5fQ==}
-    dev: true
-
   /@types/connect@3.4.38:
     resolution: {integrity: sha512-K6uROf1LD88uDQqJCktA4yzL1YYAK6NgfsI0v/mTgyPKWsX1CnJ0XPSDhViejru1GcRkLWb8RlzFYJRqGUbaug==}
     dependencies:
@@ -6879,14 +6768,6 @@ packages:
       - supports-color
     dev: true
 
-  /@vitest/expect@0.34.7:
-    resolution: {integrity: sha512-G9iEtwrD6ZQ4MVHZufif9Iqz3eLtuwBBNx971fNAGPaugM7ftAWjQN+ob2zWhtzURp8RK3zGXOxVb01mFo3zAQ==}
-    dependencies:
-      '@vitest/spy': 0.34.7
-      '@vitest/utils': 0.34.7
-      chai: 4.4.1
-    dev: true
-
   /@vitest/expect@1.3.1:
     resolution: {integrity: sha512-xofQFwIzfdmLLlHa6ag0dPV8YsnKOCP1KdAeVVh34vSjN2dcUiXYCD9htu/9eM7t8Xln4v03U9HLxLpPlsXdZw==}
     dependencies:
@@ -6911,26 +6792,12 @@ packages:
       pretty-format: 29.7.0
     dev: true
 
-  /@vitest/spy@0.34.7:
-    resolution: {integrity: sha512-NMMSzOY2d8L0mcOt4XcliDOS1ISyGlAXuQtERWVOoVHnKwmG+kKhinAiGw3dTtMQWybfa89FG8Ucg9tiC/FhTQ==}
-    dependencies:
-      tinyspy: 2.2.1
-    dev: true
-
   /@vitest/spy@1.3.1:
     resolution: {integrity: sha512-xAcW+S099ylC9VLU7eZfdT9myV67Nor9w9zhf0mGCYJSO+zM2839tOeROTdikOi/8Qeusffvxb/MyBSOja1Uig==}
     dependencies:
       tinyspy: 2.2.1
     dev: true
 
-  /@vitest/utils@0.34.7:
-    resolution: {integrity: sha512-ziAavQLpCYS9sLOorGrFFKmy2gnfiNU0ZJ15TsMz/K92NAPS/rp9K4z6AJQQk5Y8adCy4Iwpxy7pQumQ/psnRg==}
-    dependencies:
-      diff-sequences: 29.6.3
-      loupe: 2.3.7
-      pretty-format: 29.7.0
-    dev: true
-
   /@vitest/utils@1.3.1:
     resolution: {integrity: sha512-d3Waie/299qqRyHTm2DjADeTaNdNSVsnwHPWrs20JMpjh6eiVq7ggggweO8rc4arhf6rRkWuHKwvxGvejUXZZQ==}
     dependencies:
@@ -7750,18 +7617,6 @@ packages:
     dependencies:
       tslib: 2.6.2
 
-  /aria-query@5.1.3:
-    resolution: {integrity: sha512-R5iJ5lkuHybztUfuOAznmboyjWq8O6sqNqtK7CLOqdydi54VNbORp49mb14KbWgG1QD3JFO9hJdZ+y4KutfdOQ==}
-    dependencies:
-      deep-equal: 2.2.3
-    dev: true
-
-  /aria-query@5.3.0:
-    resolution: {integrity: sha512-b0P0sZPKtyu8HkeRAfCq0IfURZK+SuwMjY1UXGBU27wpAiTwQAIlq56IbIO+ytk/JjS1fMR14ee5WBBfKi5J6A==}
-    dependencies:
-      dequal: 2.0.3
-    dev: true
-
   /arity-n@1.0.4:
     resolution: {integrity: sha512-fExL2kFDC1Q2DUOx3whE/9KoN66IzkY4b4zUHUBFM1ojEYjZZYDcUW3bek/ufGionX9giIKDC5redH2IlGqcQQ==}
     dev: true
@@ -8231,14 +8086,6 @@ packages:
       escape-string-regexp: 1.0.5
       supports-color: 5.5.0
 
-  /chalk@3.0.0:
-    resolution: {integrity: sha512-4D3B6Wf41KOYRFdszmDqMCGq5VV/uMAB273JILmO+3jAlh8X4qDtdtgCR3fxtbLEMzSx22QdhnDcJvu2u1fVwg==}
-    engines: {node: '>=8'}
-    dependencies:
-      ansi-styles: 4.3.0
-      supports-color: 7.2.0
-    dev: true
-
   /chalk@4.1.2:
     resolution: {integrity: sha512-oKnbhFyRIXpUuez8iBMmyEa4nbj4IOQyuhc/wy9kY7/WVPcwIO9VA668Pu8RkO7+0G76SLROeyw9CpQ061i4mA==}
     engines: {node: '>=10'}
@@ -8582,10 +8429,6 @@ packages:
       source-map: 0.6.1
     dev: false
 
-  /css.escape@1.5.1:
-    resolution: {integrity: sha512-YUifsXXuknHlUsmlgyY0PKzgPOr7/FjCePfHNt0jxm83wHZi44VDMQ7/fGNkjY3/jV1MC+1CmZbaHzugyeRtpg==}
-    dev: true
-
   /csstype@3.1.3:
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@@ -8720,30 +8563,6 @@ packages:
       type-detect: 4.0.8
     dev: true
 
-  /deep-equal@2.2.3:
-    resolution: {integrity: sha512-ZIwpnevOurS8bpT4192sqAowWM76JDKSHYzMLty3BZGSswgq6pBaH3DhCSW5xVAZICZyKdOBPjwww5wfgT/6PA==}
-    engines: {node: '>= 0.4'}
-    dependencies:
-      array-buffer-byte-length: 1.0.1
-      call-bind: 1.0.7
-      es-get-iterator: 1.1.3
-      get-intrinsic: 1.2.4
-      is-arguments: 1.1.1
-      is-array-buffer: 3.0.4
-      is-date-object: 1.0.5
-      is-regex: 1.1.4
-      is-shared-array-buffer: 1.0.2
-      isarray: 2.0.5
-      object-is: 1.1.5
-      object-keys: 1.1.1
-      object.assign: 4.1.5
-      regexp.prototype.flags: 1.5.2
-      side-channel: 1.0.5
-      which-boxed-primitive: 1.0.2
-      which-collection: 1.0.1
-      which-typed-array: 1.1.14
-    dev: true
-
   /deep-extend@0.6.0:
     resolution: {integrity: sha512-LOHxIOaPYdHlJRtCQfDIVZtfw/ufM8+rVj649RIHzcm/vGwQRXFt6OPqIFWsm2XEMrNIEtWR64sY1LEKD2vAOA==}
     engines: {node: '>=4.0.0'}
@@ -9058,14 +8877,6 @@ packages:
       esutils: 2.0.3
     dev: true
 
-  /dom-accessibility-api@0.5.16:
-    resolution: {integrity: sha512-X7BJ2yElsnOJ30pZF4uIIDfBEVgF4XEBxL9Bxhy6dnrm5hkzqmsWHGTiHqRiITNhMyFLyAiWndIJP7Z1NTteDg==}
-    dev: true
-
-  /dom-accessibility-api@0.6.3:
-    resolution: {integrity: sha512-7ZgogeTnjuHbo+ct10G9Ffp0mif17idi0IyWNVA/wcwcm7NPOD/WEHVP3n7n3MhXqxoIYm8d6MuZohYWIZ4T3w==}
-    dev: true
-
   /dom-helpers@5.2.1:
     resolution: {integrity: sha512-nRCa7CK3VTrM2NmGkIy4cbK7IZlgBE/PYMn55rrXefr5xXDP0LdtfPnblFDoVdcAfslJ7or6iqAUnx0CCGIWQA==}
     dependencies:
@@ -9260,20 +9071,6 @@ packages:
     resolution: {integrity: sha512-Zf5H2Kxt2xjTvbJvP2ZWLEICxA6j+hAmMzIlypy4xcBg1vKVnx89Wy0GbS+kf5cwCVFFzdCFh2XSCFNULS6csw==}
     engines: {node: '>= 0.4'}
 
-  /es-get-iterator@1.1.3:
-    resolution: {integrity: sha512-sPZmqHBe6JIiTfN5q2pEi//TwxmAFHwj/XEuYjTuse78i8KxaqMTTzxPoFKuzRpDpTJ+0NAbpfenkmH2rePtuw==}
-    dependencies:
-      call-bind: 1.0.7
-      get-intrinsic: 1.2.4
-      has-symbols: 1.0.3
-      is-arguments: 1.1.1
-      is-map: 2.0.2
-      is-set: 2.0.2
-      is-string: 1.0.7
-      isarray: 2.0.5
-      stop-iteration-iterator: 1.0.0
-    dev: true
-
   /es-iterator-helpers@1.0.17:
     resolution: {integrity: sha512-lh7BsUqelv4KUbR5a/ZTaGGIMLCjPGPqJ6q+Oq24YP0RdyptX1uzm4vvaqzk7Zx3bpl/76YLTTDj9L7uYQ92oQ==}
     engines: {node: '>= 0.4'}
@@ -11481,11 +11278,6 @@ packages:
       yallist: 4.0.0
     dev: true
 
-  /lz-string@1.5.0:
-    resolution: {integrity: sha512-h5bgJWpxJNswbU7qCrV0tIKQCaS3blPDrqKWx+QxzuzL1zGUzij9XCWLrSLsJPu5t+eWA/ycetzYAO5IOMcWAQ==}
-    hasBin: true
-    dev: true
-
   /madge@6.1.0(typescript@5.3.3):
     resolution: {integrity: sha512-irWhT5RpFOc6lkzGHKLihonCVgM0YtfNUh4IrFeW3EqHpnt/JHUG3z26j8PeJEktCGB4tmGOOOJi1Rl/ACWucQ==}
     engines: {node: '>=14'}
@@ -12567,15 +12359,6 @@ packages:
     hasBin: true
     dev: true
 
-  /pretty-format@27.5.1:
-    resolution: {integrity: sha512-Qb1gy5OrP5+zDf2Bvnzdl3jsTf1qXVMazbvCoKhtKqVs4/YK4ozX4gKQJJVyNe+cajNPn0KoC0MC3FUmaHWEmQ==}
-    engines: {node: ^10.13.0 || ^12.13.0 || ^14.15.0 || >=15.0.0}
-    dependencies:
-      ansi-regex: 5.0.1
-      ansi-styles: 5.2.0
-      react-is: 17.0.2
-    dev: true
-
   /pretty-format@29.7.0:
     resolution: {integrity: sha512-Pdlw/oPxN+aXdmM9R00JVC9WVFoCLTKJvDVLgmJ+qAffBMxsV85l/Lu7sNx4zSzPyoL2euImuEwHhOXdEgNFZQ==}
     engines: {node: ^14.15.0 || ^16.10.0 || >=18.0.0}
@@ -12950,10 +12733,6 @@ packages:
   /react-is@16.13.1:
     resolution: {integrity: sha512-24e6ynE2H+OKt4kqsOvNd8kBpV65zoxbA4BVsEOB3ARVWQki/DHzaUoC5KuON/BiccDaCCTZBuOcfZs70kR8bQ==}
 
-  /react-is@17.0.2:
-    resolution: {integrity: sha512-w2GsyukL62IJnlaff/nRegPQR94C/XXamvMWmSHRJ4y7Ts/4ocGRmTHvOs8PSE6pB3dWOrD/nueuU5sduBsQ4w==}
-    dev: true
-
   /react-is@18.1.0:
     resolution: {integrity: sha512-Fl7FuabXsJnV5Q1qIOQwx/sagGF18kogb4gpfcG4gjLBWO0WDiiz1ko/ExayuxE7InyQkBLkxRFG5oxY6Uu3Kg==}
     dev: true
@@ -13287,14 +13066,6 @@ packages:
       tslib: 2.6.2
     dev: true
 
-  /redent@3.0.0:
-    resolution: {integrity: sha512-6tDA8g98We0zd0GvVeMT9arEOnTw9qM03L9cJXaCjrip1OO764RDBLBfrB4cwzNGDj5OA5ioymC9GkizgWJDUg==}
-    engines: {node: '>=8'}
-    dependencies:
-      indent-string: 4.0.0
-      strip-indent: 3.0.0
-    dev: true
-
   /redux-dynamic-middlewares@2.2.0:
     resolution: {integrity: sha512-GHESQC+Y0PV98ZBoaC6br6cDOsNiM1Cu4UleGMqMWCXX03jIr3BoozYVrRkLVVAl4sC216chakMnZOu6SwNdGA==}
     dev: false
@@ -13976,13 +13747,6 @@ packages:
     resolution: {integrity: sha512-JPbdCEQLj1w5GilpiHAx3qJvFndqybBysA3qUOnznweH4QbNYUsW/ea8QzSrnh0vNsezMMw5bcVool8lM0gwzg==}
     dev: true
 
-  /stop-iteration-iterator@1.0.0:
-    resolution: {integrity: sha512-iCGQj+0l0HOdZ2AEeBADlsRC+vsnDsZsbdSiH1yNSjcfKM7fdpCMfqAL/dwF5BLiw/XhRft/Wax6zQbhq2BcjQ==}
-    engines: {node: '>= 0.4'}
-    dependencies:
-      internal-slot: 1.0.7
-    dev: true
-
   /store2@2.14.3:
     resolution: {integrity: sha512-4QcZ+yx7nzEFiV4BMLnr/pRa5HYzNITX2ri0Zh6sT9EyQHbBHacC6YigllUPU9X3D0f/22QCgfokpKs52YRrUg==}
     dev: true
@@ -14130,13 +13894,6 @@ packages:
     engines: {node: '>=12'}
     dev: true
 
-  /strip-indent@3.0.0:
-    resolution: {integrity: sha512-laJTa3Jb+VQpaC6DseHhF7dXVqHTfJPCRDaEbid/drOhgitgYku/letMUqOXFoWV0zIIUbjpdH2t+tYj4bQMRQ==}
-    engines: {node: '>=8'}
-    dependencies:
-      min-indent: 1.0.1
-    dev: true
-
   /strip-indent@4.0.0:
     resolution: {integrity: sha512-mnVSV2l+Zv6BLpSD/8V87CW/y9EmmbYzGCIavsnsI6/nwn26DwffM/yztm30Z/I2DY9wdS3vXVCMnHDgZaVNoA==}
     engines: {node: '>=12'}

From f0b3485ce910080fc1fe52115e9005fcbd377650 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 27 Feb 2024 18:35:30 +1100
Subject: [PATCH 351/411] chore(ui): typegen, update knip config

Knip should never touch the autogenerated types
---
 invokeai/frontend/web/knip.ts                    |  2 ++
 invokeai/frontend/web/src/services/api/schema.ts | 10 +++++-----
 2 files changed, 7 insertions(+), 5 deletions(-)

diff --git a/invokeai/frontend/web/knip.ts b/invokeai/frontend/web/knip.ts
index a96b96f1f7..f2057fa904 100644
--- a/invokeai/frontend/web/knip.ts
+++ b/invokeai/frontend/web/knip.ts
@@ -4,6 +4,8 @@ const config: KnipConfig = {
   ignore: [
     // This file is only used during debugging
     'src/app/store/middleware/debugLoggerMiddleware.ts',
+    // Autogenerated types - shouldn't ever touch these
+    'src/services/api/schema.ts',
   ],
   ignoreBinaries: ['only-allow'],
   rules: {
diff --git a/invokeai/frontend/web/src/services/api/schema.ts b/invokeai/frontend/web/src/services/api/schema.ts
index de3761b946..364ad00578 100644
--- a/invokeai/frontend/web/src/services/api/schema.ts
+++ b/invokeai/frontend/web/src/services/api/schema.ts
@@ -572,7 +572,7 @@ export type paths = {
   };
 };
 
-type webhooks = Record<string, never>;
+export type webhooks = Record<string, never>;
 
 export type components = {
   schemas: {
@@ -4264,7 +4264,7 @@ export type components = {
        * @description The nodes in this graph
        */
       nodes: {
-        [key: string]: components["schemas"]["SchedulerInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["MergeTilesToImageInvocation"] | components["schemas"]["CreateGradientMaskInvocation"] | components["schemas"]["ColorMapImageProcessorInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["CanvasPasteBackInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["DWOpenposeImageProcessorInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["DepthAnythingImageProcessorInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"];
+        [key: string]: components["schemas"]["ColorInvocation"] | components["schemas"]["CoreMetadataInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["CalculateImageTilesInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["FloatToIntegerInvocation"] | components["schemas"]["FaceIdentifierInvocation"] | components["schemas"]["FreeUInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["RandomFloatInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["SaveImageInvocation"] | components["schemas"]["StringJoinInvocation"] | components["schemas"]["CenterPadCropInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["StringJoinThreeInvocation"] | components["schemas"]["IPAdapterInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["IdealSizeInvocation"] | components["schemas"]["FloatMathInvocation"] | components["schemas"]["StringReplaceInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["CropLatentsCoreInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["UnsharpMaskInvocation"] | components["schemas"]["CalculateImageTilesMinimumOverlapInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["ColorMapImageProcessorInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["IntegerMathInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["StringSplitNegInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["TileToPropertiesInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["MergeMetadataInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["MetadataItemInvocation"] | components["schemas"]["ImageChannelMultiplyInvocation"] | components["schemas"]["CanvasPasteBackInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["SchedulerInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["MetadataInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["DWOpenposeImageProcessorInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["FaceOffInvocation"] | components["schemas"]["StringSplitInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["CalculateImageTilesEvenSplitInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["ImageChannelOffsetInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["CV2InfillInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["PairTileImageInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["CreateGradientMaskInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["BooleanInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["DepthAnythingImageProcessorInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["RoundInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["T2IAdapterInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["FaceMaskInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["MergeTilesToImageInvocation"];
       };
       /**
        * Edges
@@ -4301,7 +4301,7 @@ export type components = {
        * @description The results of node executions
        */
       results: {
-        [key: string]: components["schemas"]["IntegerOutput"] | components["schemas"]["MetadataOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["ClipSkipInvocationOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["VAEOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["LoraLoaderOutput"] | components["schemas"]["String2Output"] | components["schemas"]["LatentsOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["SDXLLoraLoaderOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["FloatCollectionOutput"];
+        [key: string]: components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["SDXLLoraLoaderOutput"] | components["schemas"]["LoraLoaderOutput"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["CalculateImageTilesOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["TileToPropertiesOutput"] | components["schemas"]["StringPosNegOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["UNetOutput"] | components["schemas"]["IPAdapterOutput"] | components["schemas"]["SchedulerOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["String2Output"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["MetadataItemOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["IdealSizeOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["BooleanOutput"] | components["schemas"]["MetadataOutput"] | components["schemas"]["CLIPOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["T2IAdapterOutput"] | components["schemas"]["VAEOutput"] | components["schemas"]["FaceMaskOutput"] | components["schemas"]["PairTileImageOutput"] | components["schemas"]["FaceOffOutput"] | components["schemas"]["ClipSkipInvocationOutput"] | components["schemas"]["CollectInvocationOutput"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["LatentsOutput"] | components["schemas"]["FloatCollectionOutput"];
       };
       /**
        * Errors
@@ -10929,9 +10929,9 @@ export type components = {
   pathItems: never;
 };
 
-type $defs = Record<string, never>;
+export type $defs = Record<string, never>;
 
-type external = Record<string, never>;
+export type external = Record<string, never>;
 
 export type operations = {
 

From 7d2e84059081945a16ad31680860de953cfd0158 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 27 Feb 2024 18:49:40 +1100
Subject: [PATCH 352/411] tidy: remove some traces of ONNX

---
 invokeai/backend/model_manager/config.py      | 32 -------------------
 .../ModelManagerPanel/ModelTypeFilter.tsx     |  1 -
 .../ModelPanel/Fields/RepoVariantSelect.tsx   |  3 --
 .../features/nodes/util/schema/parseSchema.ts |  9 +-----
 4 files changed, 1 insertion(+), 44 deletions(-)

diff --git a/invokeai/backend/model_manager/config.py b/invokeai/backend/model_manager/config.py
index 7a1f3ca946..78635636b9 100644
--- a/invokeai/backend/model_manager/config.py
+++ b/invokeai/backend/model_manager/config.py
@@ -234,37 +234,6 @@ class MainDiffusersConfig(_DiffusersConfig, _MainConfig):
     type: Literal[ModelType.Main] = ModelType.Main
 
 
-class ONNXSD1Config(_MainConfig):
-    """Model config for ONNX format models based on sd-1."""
-
-    type: Literal[ModelType.ONNX] = ModelType.ONNX
-    format: Literal[ModelFormat.Onnx, ModelFormat.Olive]
-    base: Literal[BaseModelType.StableDiffusion1] = BaseModelType.StableDiffusion1
-    prediction_type: SchedulerPredictionType = SchedulerPredictionType.Epsilon
-    upcast_attention: bool = False
-
-
-class ONNXSD2Config(_MainConfig):
-    """Model config for ONNX format models based on sd-2."""
-
-    type: Literal[ModelType.ONNX] = ModelType.ONNX
-    format: Literal[ModelFormat.Onnx, ModelFormat.Olive]
-    # No yaml config file for ONNX, so these are part of config
-    base: Literal[BaseModelType.StableDiffusion2] = BaseModelType.StableDiffusion2
-    prediction_type: SchedulerPredictionType = SchedulerPredictionType.VPrediction
-    upcast_attention: bool = True
-
-
-class ONNXSDXLConfig(_MainConfig):
-    """Model config for ONNX format models based on sdxl."""
-
-    type: Literal[ModelType.ONNX] = ModelType.ONNX
-    format: Literal[ModelFormat.Onnx, ModelFormat.Olive]
-    # No yaml config file for ONNX, so these are part of config
-    base: Literal[BaseModelType.StableDiffusionXL] = BaseModelType.StableDiffusionXL
-    prediction_type: SchedulerPredictionType = SchedulerPredictionType.VPrediction
-
-
 class IPAdapterConfig(ModelConfigBase):
     """Model config for IP Adaptor format models."""
 
@@ -287,7 +256,6 @@ class T2IConfig(ModelConfigBase):
     format: Literal[ModelFormat.Diffusers]
 
 
-_ONNXConfig = Annotated[Union[ONNXSD1Config, ONNXSD2Config, ONNXSDXLConfig], Field(discriminator="base")]
 _ControlNetConfig = Annotated[
     Union[ControlNetDiffusersConfig, ControlNetCheckpointConfig],
     Field(discriminator="format"),
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelTypeFilter.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelTypeFilter.tsx
index b58719078f..71606b4096 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelTypeFilter.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelTypeFilter.tsx
@@ -14,7 +14,6 @@ export const MODEL_TYPE_LABELS: { [key: string]: string } = {
   t2i_adapter: 'T2I Adapter',
   ip_adapter: 'IP Adapter',
   clip_vision: 'Clip Vision',
-  onnx: 'Onnx',
 };
 
 export const ModelTypeFilter = () => {
diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/RepoVariantSelect.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/RepoVariantSelect.tsx
index 74793be789..66134dbfc0 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/RepoVariantSelect.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/RepoVariantSelect.tsx
@@ -10,9 +10,6 @@ const options: ComboboxOption[] = [
   { value: 'none', label: '-' },
   { value: 'fp16', label: 'fp16' },
   { value: 'fp32', label: 'fp32' },
-  { value: 'onnx', label: 'onnx' },
-  { value: 'openvino', label: 'openvino' },
-  { value: 'flax', label: 'flax' },
 ];
 
 const RepoVariantSelect = <T extends AnyModelConfig>(props: UseControllerProps<T>) => {
diff --git a/invokeai/frontend/web/src/features/nodes/util/schema/parseSchema.ts b/invokeai/frontend/web/src/features/nodes/util/schema/parseSchema.ts
index f9bce27372..990c517ad3 100644
--- a/invokeai/frontend/web/src/features/nodes/util/schema/parseSchema.ts
+++ b/invokeai/frontend/web/src/features/nodes/util/schema/parseSchema.ts
@@ -22,14 +22,7 @@ const RESERVED_INPUT_FIELD_NAMES = ['id', 'type', 'use_cache'];
 const RESERVED_OUTPUT_FIELD_NAMES = ['type'];
 const RESERVED_FIELD_TYPES = ['IsIntermediate'];
 
-const invocationDenylist: string[] = [
-  'graph',
-  'linear_ui_output',
-  'l2i_onnx',
-  'prompt_onnx',
-  't2l_onnx',
-  'onnx_model_loader',
-];
+const invocationDenylist: string[] = ['graph', 'linear_ui_output'];
 
 const isReservedInputField = (nodeType: string, fieldName: string) => {
   if (RESERVED_INPUT_FIELD_NAMES.includes(fieldName)) {

From f6c068afdd5f46d88e6816bd5a9eedc6996aeec5 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 27 Feb 2024 19:14:49 +1100
Subject: [PATCH 353/411] tidy(ui): fix circular dependencies in listeners

---
 .../middleware/listenerMiddleware/index.ts    | 232 ++++++++----------
 .../addCommitStagingAreaImageListener.ts      |   5 +-
 .../addFirstListImagesListener.ts.ts          |   5 +-
 .../listeners/anyEnqueued.ts                  |   5 +-
 .../listeners/appConfigReceived.ts            |   5 +-
 .../listeners/appStarted.ts                   |   5 +-
 .../listeners/batchEnqueued.ts                |   5 +-
 .../listeners/boardAndImagesDeleted.ts        |   5 +-
 .../listeners/boardIdSelected.ts              |   5 +-
 .../listeners/bulkDownload.tsx                |   4 +-
 .../listeners/canvasCopiedToClipboard.ts      |   5 +-
 .../listeners/canvasDownloadedAsImage.ts      |   5 +-
 .../listeners/canvasImageToControlNet.ts      |   5 +-
 .../listeners/canvasMaskSavedToGallery.ts     |   5 +-
 .../listeners/canvasMaskToControlNet.ts       |   5 +-
 .../listeners/canvasMerged.ts                 |   5 +-
 .../listeners/canvasSavedToGallery.ts         |   5 +-
 .../listeners/controlNetAutoProcess.ts        |   5 +-
 .../listeners/controlNetImageProcessed.ts     |   5 +-
 .../listeners/enqueueRequestedCanvas.ts       |   5 +-
 .../listeners/enqueueRequestedLinear.ts       |   5 +-
 .../listeners/enqueueRequestedNodes.ts        |   5 +-
 .../listeners/galleryImageClicked.ts          |   5 +-
 .../listeners/getOpenAPISchema.ts             |   5 +-
 .../listeners/imageAddedToBoard.ts            |   7 +-
 .../listeners/imageDeleted.ts                 |  25 +-
 .../listeners/imageDropped.ts                 |   5 +-
 .../listeners/imageRemovedFromBoard.ts        |   7 +-
 .../listeners/imageToDeleteSelected.ts        |   5 +-
 .../listeners/imageUploaded.ts                |   7 +-
 .../listeners/imagesStarred.ts                |   5 +-
 .../listeners/imagesUnstarred.ts              |   5 +-
 .../listeners/initialImageSelected.ts         |   5 +-
 .../listeners/modelSelected.ts                |   5 +-
 .../listeners/modelsLoaded.ts                 |   5 +-
 .../listeners/promptChanged.ts                |   5 +-
 .../listeners/socketio/socketConnected.ts     |   5 +-
 .../listeners/socketio/socketDisconnected.ts  |   5 +-
 .../socketio/socketGeneratorProgress.ts       |   5 +-
 .../socketGraphExecutionStateComplete.ts      |   5 +-
 .../socketio/socketInvocationComplete.ts      |   5 +-
 .../socketio/socketInvocationError.ts         |   5 +-
 .../socketInvocationRetrievalError.ts         |   5 +-
 .../socketio/socketInvocationStarted.ts       |   5 +-
 .../listeners/socketio/socketModelInstall.ts  |   5 +-
 .../listeners/socketio/socketModelLoad.ts     |   5 +-
 .../socketio/socketQueueItemStatusChanged.ts  |   5 +-
 .../socketio/socketSessionRetrievalError.ts   |   5 +-
 .../listeners/socketio/socketSubscribed.ts    |   5 +-
 .../listeners/socketio/socketUnsubscribed.ts  |   5 +-
 .../listeners/stagingAreaImageSaved.ts        |   5 +-
 .../listeners/updateAllNodesRequested.ts      |   5 +-
 .../listeners/upscaleRequested.ts             |   5 +-
 .../listeners/workflowLoadRequested.ts        |   5 +-
 .../frontend/web/src/services/api/schema.ts   |   6 +-
 55 files changed, 215 insertions(+), 313 deletions(-)

diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts
index bf1cafc866..c5d86a127f 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts
@@ -1,78 +1,65 @@
 import type { TypedStartListening } from '@reduxjs/toolkit';
 import { createListenerMiddleware } from '@reduxjs/toolkit';
+import { addCommitStagingAreaImageListener } from 'app/store/middleware/listenerMiddleware/listeners/addCommitStagingAreaImageListener';
+import { addFirstListImagesListener } from 'app/store/middleware/listenerMiddleware/listeners/addFirstListImagesListener.ts';
+import { addAnyEnqueuedListener } from 'app/store/middleware/listenerMiddleware/listeners/anyEnqueued';
+import { addAppConfigReceivedListener } from 'app/store/middleware/listenerMiddleware/listeners/appConfigReceived';
+import { addAppStartedListener } from 'app/store/middleware/listenerMiddleware/listeners/appStarted';
+import { addBatchEnqueuedListener } from 'app/store/middleware/listenerMiddleware/listeners/batchEnqueued';
+import { addDeleteBoardAndImagesFulfilledListener } from 'app/store/middleware/listenerMiddleware/listeners/boardAndImagesDeleted';
+import { addBoardIdSelectedListener } from 'app/store/middleware/listenerMiddleware/listeners/boardIdSelected';
 import { addBulkDownloadListeners } from 'app/store/middleware/listenerMiddleware/listeners/bulkDownload';
+import { addCanvasCopiedToClipboardListener } from 'app/store/middleware/listenerMiddleware/listeners/canvasCopiedToClipboard';
+import { addCanvasDownloadedAsImageListener } from 'app/store/middleware/listenerMiddleware/listeners/canvasDownloadedAsImage';
+import { addCanvasImageToControlNetListener } from 'app/store/middleware/listenerMiddleware/listeners/canvasImageToControlNet';
+import { addCanvasMaskSavedToGalleryListener } from 'app/store/middleware/listenerMiddleware/listeners/canvasMaskSavedToGallery';
+import { addCanvasMaskToControlNetListener } from 'app/store/middleware/listenerMiddleware/listeners/canvasMaskToControlNet';
+import { addCanvasMergedListener } from 'app/store/middleware/listenerMiddleware/listeners/canvasMerged';
+import { addCanvasSavedToGalleryListener } from 'app/store/middleware/listenerMiddleware/listeners/canvasSavedToGallery';
+import { addControlNetAutoProcessListener } from 'app/store/middleware/listenerMiddleware/listeners/controlNetAutoProcess';
+import { addControlNetImageProcessedListener } from 'app/store/middleware/listenerMiddleware/listeners/controlNetImageProcessed';
+import { addEnqueueRequestedCanvasListener } from 'app/store/middleware/listenerMiddleware/listeners/enqueueRequestedCanvas';
+import { addEnqueueRequestedLinear } from 'app/store/middleware/listenerMiddleware/listeners/enqueueRequestedLinear';
+import { addEnqueueRequestedNodes } from 'app/store/middleware/listenerMiddleware/listeners/enqueueRequestedNodes';
 import { addGalleryImageClickedListener } from 'app/store/middleware/listenerMiddleware/listeners/galleryImageClicked';
+import { addGetOpenAPISchemaListener } from 'app/store/middleware/listenerMiddleware/listeners/getOpenAPISchema';
+import { addImageAddedToBoardFulfilledListener } from 'app/store/middleware/listenerMiddleware/listeners/imageAddedToBoard';
+import { addRequestedSingleImageDeletionListener } from 'app/store/middleware/listenerMiddleware/listeners/imageDeleted';
+import { addImageDroppedListener } from 'app/store/middleware/listenerMiddleware/listeners/imageDropped';
+import { addImageRemovedFromBoardFulfilledListener } from 'app/store/middleware/listenerMiddleware/listeners/imageRemovedFromBoard';
+import { addImagesStarredListener } from 'app/store/middleware/listenerMiddleware/listeners/imagesStarred';
+import { addImagesUnstarredListener } from 'app/store/middleware/listenerMiddleware/listeners/imagesUnstarred';
+import { addImageToDeleteSelectedListener } from 'app/store/middleware/listenerMiddleware/listeners/imageToDeleteSelected';
+import { addImageUploadedFulfilledListener } from 'app/store/middleware/listenerMiddleware/listeners/imageUploaded';
+import { addInitialImageSelectedListener } from 'app/store/middleware/listenerMiddleware/listeners/initialImageSelected';
+import { addModelSelectedListener } from 'app/store/middleware/listenerMiddleware/listeners/modelSelected';
+import { addModelsLoadedListener } from 'app/store/middleware/listenerMiddleware/listeners/modelsLoaded';
+import { addDynamicPromptsListener } from 'app/store/middleware/listenerMiddleware/listeners/promptChanged';
+import { addSocketConnectedEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketConnected';
+import { addSocketDisconnectedEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketDisconnected';
+import { addGeneratorProgressEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketGeneratorProgress';
+import { addGraphExecutionStateCompleteEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketGraphExecutionStateComplete';
+import { addInvocationCompleteEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationComplete';
+import { addInvocationErrorEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationError';
+import { addInvocationRetrievalErrorEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationRetrievalError';
+import { addInvocationStartedEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationStarted';
+import { addModelInstallEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall';
+import { addModelLoadEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketModelLoad';
+import { addSocketQueueItemStatusChangedEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketQueueItemStatusChanged';
+import { addSessionRetrievalErrorEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketSessionRetrievalError';
+import { addSocketSubscribedEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketSubscribed';
+import { addSocketUnsubscribedEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketUnsubscribed';
+import { addStagingAreaImageSavedListener } from 'app/store/middleware/listenerMiddleware/listeners/stagingAreaImageSaved';
+import { addUpdateAllNodesRequestedListener } from 'app/store/middleware/listenerMiddleware/listeners/updateAllNodesRequested';
+import { addUpscaleRequestedListener } from 'app/store/middleware/listenerMiddleware/listeners/upscaleRequested';
+import { addWorkflowLoadRequestedListener } from 'app/store/middleware/listenerMiddleware/listeners/workflowLoadRequested';
 import type { AppDispatch, RootState } from 'app/store/store';
 
-import { addCommitStagingAreaImageListener } from './listeners/addCommitStagingAreaImageListener';
-import { addFirstListImagesListener } from './listeners/addFirstListImagesListener.ts';
-import { addAnyEnqueuedListener } from './listeners/anyEnqueued';
-import { addAppConfigReceivedListener } from './listeners/appConfigReceived';
-import { addAppStartedListener } from './listeners/appStarted';
-import { addBatchEnqueuedListener } from './listeners/batchEnqueued';
-import { addDeleteBoardAndImagesFulfilledListener } from './listeners/boardAndImagesDeleted';
-import { addBoardIdSelectedListener } from './listeners/boardIdSelected';
-import { addCanvasCopiedToClipboardListener } from './listeners/canvasCopiedToClipboard';
-import { addCanvasDownloadedAsImageListener } from './listeners/canvasDownloadedAsImage';
-import { addCanvasImageToControlNetListener } from './listeners/canvasImageToControlNet';
-import { addCanvasMaskSavedToGalleryListener } from './listeners/canvasMaskSavedToGallery';
-import { addCanvasMaskToControlNetListener } from './listeners/canvasMaskToControlNet';
-import { addCanvasMergedListener } from './listeners/canvasMerged';
-import { addCanvasSavedToGalleryListener } from './listeners/canvasSavedToGallery';
-import { addControlNetAutoProcessListener } from './listeners/controlNetAutoProcess';
-import { addControlNetImageProcessedListener } from './listeners/controlNetImageProcessed';
-import { addEnqueueRequestedCanvasListener } from './listeners/enqueueRequestedCanvas';
-import { addEnqueueRequestedLinear } from './listeners/enqueueRequestedLinear';
-import { addEnqueueRequestedNodes } from './listeners/enqueueRequestedNodes';
-import { addGetOpenAPISchemaListener } from './listeners/getOpenAPISchema';
-import {
-  addImageAddedToBoardFulfilledListener,
-  addImageAddedToBoardRejectedListener,
-} from './listeners/imageAddedToBoard';
-import {
-  addImageDeletedFulfilledListener,
-  addImageDeletedPendingListener,
-  addImageDeletedRejectedListener,
-  addRequestedMultipleImageDeletionListener,
-  addRequestedSingleImageDeletionListener,
-} from './listeners/imageDeleted';
-import { addImageDroppedListener } from './listeners/imageDropped';
-import {
-  addImageRemovedFromBoardFulfilledListener,
-  addImageRemovedFromBoardRejectedListener,
-} from './listeners/imageRemovedFromBoard';
-import { addImagesStarredListener } from './listeners/imagesStarred';
-import { addImagesUnstarredListener } from './listeners/imagesUnstarred';
-import { addImageToDeleteSelectedListener } from './listeners/imageToDeleteSelected';
-import { addImageUploadedFulfilledListener, addImageUploadedRejectedListener } from './listeners/imageUploaded';
-import { addInitialImageSelectedListener } from './listeners/initialImageSelected';
-import { addModelSelectedListener } from './listeners/modelSelected';
-import { addModelsLoadedListener } from './listeners/modelsLoaded';
-import { addDynamicPromptsListener } from './listeners/promptChanged';
-import { addSocketConnectedEventListener as addSocketConnectedListener } from './listeners/socketio/socketConnected';
-import { addSocketDisconnectedEventListener as addSocketDisconnectedListener } from './listeners/socketio/socketDisconnected';
-import { addGeneratorProgressEventListener as addGeneratorProgressListener } from './listeners/socketio/socketGeneratorProgress';
-import { addGraphExecutionStateCompleteEventListener as addGraphExecutionStateCompleteListener } from './listeners/socketio/socketGraphExecutionStateComplete';
-import { addInvocationCompleteEventListener as addInvocationCompleteListener } from './listeners/socketio/socketInvocationComplete';
-import { addInvocationErrorEventListener as addInvocationErrorListener } from './listeners/socketio/socketInvocationError';
-import { addInvocationRetrievalErrorEventListener } from './listeners/socketio/socketInvocationRetrievalError';
-import { addInvocationStartedEventListener as addInvocationStartedListener } from './listeners/socketio/socketInvocationStarted';
-import { addModelInstallEventListener } from './listeners/socketio/socketModelInstall';
-import { addModelLoadEventListener } from './listeners/socketio/socketModelLoad';
-import { addSocketQueueItemStatusChangedEventListener } from './listeners/socketio/socketQueueItemStatusChanged';
-import { addSessionRetrievalErrorEventListener } from './listeners/socketio/socketSessionRetrievalError';
-import { addSocketSubscribedEventListener as addSocketSubscribedListener } from './listeners/socketio/socketSubscribed';
-import { addSocketUnsubscribedEventListener as addSocketUnsubscribedListener } from './listeners/socketio/socketUnsubscribed';
-import { addStagingAreaImageSavedListener } from './listeners/stagingAreaImageSaved';
-import { addUpdateAllNodesRequestedListener } from './listeners/updateAllNodesRequested';
-import { addUpscaleRequestedListener } from './listeners/upscaleRequested';
-import { addWorkflowLoadRequestedListener } from './listeners/workflowLoadRequested';
-
 export const listenerMiddleware = createListenerMiddleware();
 
-type AppStartListening = TypedStartListening<RootState, AppDispatch>;
+export type AppStartListening = TypedStartListening<RootState, AppDispatch>;
 
-export const startAppListening = listenerMiddleware.startListening as AppStartListening;
+const startAppListening = listenerMiddleware.startListening as AppStartListening;
 
 /**
  * The RTK listener middleware is a lightweight alternative sagas/observables.
@@ -81,95 +68,88 @@ export const startAppListening = listenerMiddleware.startListening as AppStartLi
  */
 
 // Image uploaded
-addImageUploadedFulfilledListener();
-addImageUploadedRejectedListener();
+addImageUploadedFulfilledListener(startAppListening);
 
 // Image selected
-addInitialImageSelectedListener();
+addInitialImageSelectedListener(startAppListening);
 
 // Image deleted
-addRequestedSingleImageDeletionListener();
-addRequestedMultipleImageDeletionListener();
-addImageDeletedPendingListener();
-addImageDeletedFulfilledListener();
-addImageDeletedRejectedListener();
-addDeleteBoardAndImagesFulfilledListener();
-addImageToDeleteSelectedListener();
+addRequestedSingleImageDeletionListener(startAppListening);
+addDeleteBoardAndImagesFulfilledListener(startAppListening);
+addImageToDeleteSelectedListener(startAppListening);
 
 // Image starred
-addImagesStarredListener();
-addImagesUnstarredListener();
+addImagesStarredListener(startAppListening);
+addImagesUnstarredListener(startAppListening);
 
 // Gallery
-addGalleryImageClickedListener();
+addGalleryImageClickedListener(startAppListening);
 
 // User Invoked
-addEnqueueRequestedCanvasListener();
-addEnqueueRequestedNodes();
-addEnqueueRequestedLinear();
-addAnyEnqueuedListener();
-addBatchEnqueuedListener();
+addEnqueueRequestedCanvasListener(startAppListening);
+addEnqueueRequestedNodes(startAppListening);
+addEnqueueRequestedLinear(startAppListening);
+addAnyEnqueuedListener(startAppListening);
+addBatchEnqueuedListener(startAppListening);
 
 // Canvas actions
-addCanvasSavedToGalleryListener();
-addCanvasMaskSavedToGalleryListener();
-addCanvasImageToControlNetListener();
-addCanvasMaskToControlNetListener();
-addCanvasDownloadedAsImageListener();
-addCanvasCopiedToClipboardListener();
-addCanvasMergedListener();
-addStagingAreaImageSavedListener();
-addCommitStagingAreaImageListener();
+addCanvasSavedToGalleryListener(startAppListening);
+addCanvasMaskSavedToGalleryListener(startAppListening);
+addCanvasImageToControlNetListener(startAppListening);
+addCanvasMaskToControlNetListener(startAppListening);
+addCanvasDownloadedAsImageListener(startAppListening);
+addCanvasCopiedToClipboardListener(startAppListening);
+addCanvasMergedListener(startAppListening);
+addStagingAreaImageSavedListener(startAppListening);
+addCommitStagingAreaImageListener(startAppListening);
 
 // Socket.IO
-addGeneratorProgressListener();
-addGraphExecutionStateCompleteListener();
-addInvocationCompleteListener();
-addInvocationErrorListener();
-addInvocationStartedListener();
-addSocketConnectedListener();
-addSocketDisconnectedListener();
-addSocketSubscribedListener();
-addSocketUnsubscribedListener();
-addModelLoadEventListener();
-addModelInstallEventListener();
-addSessionRetrievalErrorEventListener();
-addInvocationRetrievalErrorEventListener();
-addSocketQueueItemStatusChangedEventListener();
-addBulkDownloadListeners();
+addGeneratorProgressEventListener(startAppListening);
+addGraphExecutionStateCompleteEventListener(startAppListening);
+addInvocationCompleteEventListener(startAppListening);
+addInvocationErrorEventListener(startAppListening);
+addInvocationStartedEventListener(startAppListening);
+addSocketConnectedEventListener(startAppListening);
+addSocketDisconnectedEventListener(startAppListening);
+addSocketSubscribedEventListener(startAppListening);
+addSocketUnsubscribedEventListener(startAppListening);
+addModelLoadEventListener(startAppListening);
+addModelInstallEventListener(startAppListening);
+addSessionRetrievalErrorEventListener(startAppListening);
+addInvocationRetrievalErrorEventListener(startAppListening);
+addSocketQueueItemStatusChangedEventListener(startAppListening);
+addBulkDownloadListeners(startAppListening);
 
 // ControlNet
-addControlNetImageProcessedListener();
-addControlNetAutoProcessListener();
+addControlNetImageProcessedListener(startAppListening);
+addControlNetAutoProcessListener(startAppListening);
 
 // Boards
-addImageAddedToBoardFulfilledListener();
-addImageAddedToBoardRejectedListener();
-addImageRemovedFromBoardFulfilledListener();
-addImageRemovedFromBoardRejectedListener();
-addBoardIdSelectedListener();
+addImageAddedToBoardFulfilledListener(startAppListening);
+addImageRemovedFromBoardFulfilledListener(startAppListening);
+addBoardIdSelectedListener(startAppListening);
 
 // Node schemas
-addGetOpenAPISchemaListener();
+addGetOpenAPISchemaListener(startAppListening);
 
 // Workflows
-addWorkflowLoadRequestedListener();
-addUpdateAllNodesRequestedListener();
+addWorkflowLoadRequestedListener(startAppListening);
+addUpdateAllNodesRequestedListener(startAppListening);
 
 // DND
-addImageDroppedListener();
+addImageDroppedListener(startAppListening);
 
 // Models
-addModelSelectedListener();
+addModelSelectedListener(startAppListening);
 
 // app startup
-addAppStartedListener();
-addModelsLoadedListener();
-addAppConfigReceivedListener();
-addFirstListImagesListener();
+addAppStartedListener(startAppListening);
+addModelsLoadedListener(startAppListening);
+addAppConfigReceivedListener(startAppListening);
+addFirstListImagesListener(startAppListening);
 
 // Ad-hoc upscale workflwo
-addUpscaleRequestedListener();
+addUpscaleRequestedListener(startAppListening);
 
 // Dynamic prompts
-addDynamicPromptsListener();
+addDynamicPromptsListener(startAppListening);
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/addCommitStagingAreaImageListener.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/addCommitStagingAreaImageListener.ts
index 2c5fbfbbe4..7e6a83e16d 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/addCommitStagingAreaImageListener.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/addCommitStagingAreaImageListener.ts
@@ -1,15 +1,14 @@
 import { isAnyOf } from '@reduxjs/toolkit';
 import { logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { canvasBatchIdsReset, commitStagingAreaImage, discardStagedImages } from 'features/canvas/store/canvasSlice';
 import { addToast } from 'features/system/store/systemSlice';
 import { t } from 'i18next';
 import { queueApi } from 'services/api/endpoints/queue';
 
-import { startAppListening } from '..';
-
 const matcher = isAnyOf(commitStagingAreaImage, discardStagedImages);
 
-export const addCommitStagingAreaImageListener = () => {
+export const addCommitStagingAreaImageListener = (startAppListening: AppStartListening) => {
   startAppListening({
     matcher,
     effect: async (_, { dispatch, getState }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/addFirstListImagesListener.ts.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/addFirstListImagesListener.ts.ts
index e7597f7ae0..3f831de5c6 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/addFirstListImagesListener.ts.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/addFirstListImagesListener.ts.ts
@@ -1,12 +1,11 @@
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { imageSelected } from 'features/gallery/store/gallerySlice';
 import { IMAGE_CATEGORIES } from 'features/gallery/store/types';
 import { imagesApi } from 'services/api/endpoints/images';
 import type { ImageCache } from 'services/api/types';
 import { getListImagesUrl, imagesSelectors } from 'services/api/util';
 
-import { startAppListening } from '..';
-
-export const addFirstListImagesListener = () => {
+export const addFirstListImagesListener = (startAppListening: AppStartListening) => {
   startAppListening({
     matcher: imagesApi.endpoints.listImages.matchFulfilled,
     effect: async (action, { dispatch, unsubscribe, cancelActiveListeners }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/anyEnqueued.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/anyEnqueued.ts
index e2114769f4..373fa3dd28 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/anyEnqueued.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/anyEnqueued.ts
@@ -1,8 +1,7 @@
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { queueApi, selectQueueStatus } from 'services/api/endpoints/queue';
 
-import { startAppListening } from '..';
-
-export const addAnyEnqueuedListener = () => {
+export const addAnyEnqueuedListener = (startAppListening: AppStartListening) => {
   startAppListening({
     matcher: queueApi.endpoints.enqueueBatch.matchFulfilled,
     effect: async (_, { dispatch, getState }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/appConfigReceived.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/appConfigReceived.ts
index 3fc9cdda44..4ee73af642 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/appConfigReceived.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/appConfigReceived.ts
@@ -1,10 +1,9 @@
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { setInfillMethod } from 'features/parameters/store/generationSlice';
 import { shouldUseNSFWCheckerChanged, shouldUseWatermarkerChanged } from 'features/system/store/systemSlice';
 import { appInfoApi } from 'services/api/endpoints/appInfo';
 
-import { startAppListening } from '..';
-
-export const addAppConfigReceivedListener = () => {
+export const addAppConfigReceivedListener = (startAppListening: AppStartListening) => {
   startAppListening({
     matcher: appInfoApi.endpoints.getAppConfig.matchFulfilled,
     effect: async (action, { getState, dispatch }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/appStarted.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/appStarted.ts
index 9cbd1c4aca..729067ee82 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/appStarted.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/appStarted.ts
@@ -1,10 +1,9 @@
 import { createAction } from '@reduxjs/toolkit';
-
-import { startAppListening } from '..';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 
 export const appStarted = createAction('app/appStarted');
 
-export const addAppStartedListener = () => {
+export const addAppStartedListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: appStarted,
     effect: async (action, { unsubscribe, cancelActiveListeners }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/batchEnqueued.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/batchEnqueued.ts
index 07a1039bef..68eda997b7 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/batchEnqueued.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/batchEnqueued.ts
@@ -1,4 +1,5 @@
 import { logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { parseify } from 'common/util/serialize';
 import { toast } from 'common/util/toast';
 import { zPydanticValidationError } from 'features/system/store/zodSchemas';
@@ -6,9 +7,7 @@ import { t } from 'i18next';
 import { truncate, upperFirst } from 'lodash-es';
 import { queueApi } from 'services/api/endpoints/queue';
 
-import { startAppListening } from '..';
-
-export const addBatchEnqueuedListener = () => {
+export const addBatchEnqueuedListener = (startAppListening: AppStartListening) => {
   // success
   startAppListening({
     matcher: queueApi.endpoints.enqueueBatch.matchFulfilled,
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/boardAndImagesDeleted.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/boardAndImagesDeleted.ts
index 2e77896ad3..8e8d3f4b99 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/boardAndImagesDeleted.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/boardAndImagesDeleted.ts
@@ -1,3 +1,4 @@
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { resetCanvas } from 'features/canvas/store/canvasSlice';
 import { controlAdaptersReset } from 'features/controlAdapters/store/controlAdaptersSlice';
 import { getImageUsage } from 'features/deleteImageModal/store/selectors';
@@ -5,9 +6,7 @@ import { nodeEditorReset } from 'features/nodes/store/nodesSlice';
 import { clearInitialImage } from 'features/parameters/store/generationSlice';
 import { imagesApi } from 'services/api/endpoints/images';
 
-import { startAppListening } from '..';
-
-export const addDeleteBoardAndImagesFulfilledListener = () => {
+export const addDeleteBoardAndImagesFulfilledListener = (startAppListening: AppStartListening) => {
   startAppListening({
     matcher: imagesApi.endpoints.deleteBoardAndImages.matchFulfilled,
     effect: async (action, { dispatch, getState }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/boardIdSelected.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/boardIdSelected.ts
index ebcb96d116..2c1aa6ec8b 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/boardIdSelected.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/boardIdSelected.ts
@@ -1,12 +1,11 @@
 import { isAnyOf } from '@reduxjs/toolkit';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { boardIdSelected, galleryViewChanged, imageSelected } from 'features/gallery/store/gallerySlice';
 import { ASSETS_CATEGORIES, IMAGE_CATEGORIES } from 'features/gallery/store/types';
 import { imagesApi } from 'services/api/endpoints/images';
 import { imagesSelectors } from 'services/api/util';
 
-import { startAppListening } from '..';
-
-export const addBoardIdSelectedListener = () => {
+export const addBoardIdSelectedListener = (startAppListening: AppStartListening) => {
   startAppListening({
     matcher: isAnyOf(boardIdSelected, galleryViewChanged),
     effect: async (action, { getState, dispatch, condition, cancelActiveListeners }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/bulkDownload.tsx b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/bulkDownload.tsx
index fa5c962ff5..38a0fd7911 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/bulkDownload.tsx
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/bulkDownload.tsx
@@ -1,7 +1,7 @@
 import type { UseToastOptions } from '@invoke-ai/ui-library';
 import { ExternalLink } from '@invoke-ai/ui-library';
 import { logger } from 'app/logging/logger';
-import { startAppListening } from 'app/store/middleware/listenerMiddleware';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { toast } from 'common/util/toast';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
@@ -13,7 +13,7 @@ import {
 
 const log = logger('images');
 
-export const addBulkDownloadListeners = () => {
+export const addBulkDownloadListeners = (startAppListening: AppStartListening) => {
   startAppListening({
     matcher: imagesApi.endpoints.bulkDownloadImages.matchFulfilled,
     effect: async (action) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasCopiedToClipboard.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasCopiedToClipboard.ts
index a4ae936ada..e1f4804d56 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasCopiedToClipboard.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasCopiedToClipboard.ts
@@ -1,13 +1,12 @@
 import { $logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { canvasCopiedToClipboard } from 'features/canvas/store/actions';
 import { getBaseLayerBlob } from 'features/canvas/util/getBaseLayerBlob';
 import { addToast } from 'features/system/store/systemSlice';
 import { copyBlobToClipboard } from 'features/system/util/copyBlobToClipboard';
 import { t } from 'i18next';
 
-import { startAppListening } from '..';
-
-export const addCanvasCopiedToClipboardListener = () => {
+export const addCanvasCopiedToClipboardListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: canvasCopiedToClipboard,
     effect: async (action, { dispatch, getState }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasDownloadedAsImage.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasDownloadedAsImage.ts
index af37afa8d5..5b8150bd20 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasDownloadedAsImage.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasDownloadedAsImage.ts
@@ -1,13 +1,12 @@
 import { $logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { canvasDownloadedAsImage } from 'features/canvas/store/actions';
 import { downloadBlob } from 'features/canvas/util/downloadBlob';
 import { getBaseLayerBlob } from 'features/canvas/util/getBaseLayerBlob';
 import { addToast } from 'features/system/store/systemSlice';
 import { t } from 'i18next';
 
-import { startAppListening } from '..';
-
-export const addCanvasDownloadedAsImageListener = () => {
+export const addCanvasDownloadedAsImageListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: canvasDownloadedAsImage,
     effect: async (action, { dispatch, getState }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasImageToControlNet.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasImageToControlNet.ts
index b9b08d2b4e..775a20965d 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasImageToControlNet.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasImageToControlNet.ts
@@ -1,4 +1,5 @@
 import { logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { canvasImageToControlAdapter } from 'features/canvas/store/actions';
 import { getBaseLayerBlob } from 'features/canvas/util/getBaseLayerBlob';
 import { controlAdapterImageChanged } from 'features/controlAdapters/store/controlAdaptersSlice';
@@ -6,9 +7,7 @@ import { addToast } from 'features/system/store/systemSlice';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
 
-import { startAppListening } from '..';
-
-export const addCanvasImageToControlNetListener = () => {
+export const addCanvasImageToControlNetListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: canvasImageToControlAdapter,
     effect: async (action, { dispatch, getState }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasMaskSavedToGallery.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasMaskSavedToGallery.ts
index d8a3c3827d..af0c3878fc 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasMaskSavedToGallery.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasMaskSavedToGallery.ts
@@ -1,13 +1,12 @@
 import { logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { canvasMaskSavedToGallery } from 'features/canvas/store/actions';
 import { getCanvasData } from 'features/canvas/util/getCanvasData';
 import { addToast } from 'features/system/store/systemSlice';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
 
-import { startAppListening } from '..';
-
-export const addCanvasMaskSavedToGalleryListener = () => {
+export const addCanvasMaskSavedToGalleryListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: canvasMaskSavedToGallery,
     effect: async (action, { dispatch, getState }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasMaskToControlNet.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasMaskToControlNet.ts
index cf1658cb41..4024488566 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasMaskToControlNet.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasMaskToControlNet.ts
@@ -1,4 +1,5 @@
 import { logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { canvasMaskToControlAdapter } from 'features/canvas/store/actions';
 import { getCanvasData } from 'features/canvas/util/getCanvasData';
 import { controlAdapterImageChanged } from 'features/controlAdapters/store/controlAdaptersSlice';
@@ -6,9 +7,7 @@ import { addToast } from 'features/system/store/systemSlice';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
 
-import { startAppListening } from '..';
-
-export const addCanvasMaskToControlNetListener = () => {
+export const addCanvasMaskToControlNetListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: canvasMaskToControlAdapter,
     effect: async (action, { dispatch, getState }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasMerged.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasMerged.ts
index f29a095c1f..71b0e62b44 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasMerged.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasMerged.ts
@@ -1,4 +1,5 @@
 import { $logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { canvasMerged } from 'features/canvas/store/actions';
 import { $canvasBaseLayer } from 'features/canvas/store/canvasNanostore';
 import { setMergedCanvas } from 'features/canvas/store/canvasSlice';
@@ -7,9 +8,7 @@ import { addToast } from 'features/system/store/systemSlice';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
 
-import { startAppListening } from '..';
-
-export const addCanvasMergedListener = () => {
+export const addCanvasMergedListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: canvasMerged,
     effect: async (action, { dispatch }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasSavedToGallery.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasSavedToGallery.ts
index f09cbe12d1..e3ba988886 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasSavedToGallery.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasSavedToGallery.ts
@@ -1,13 +1,12 @@
 import { logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { canvasSavedToGallery } from 'features/canvas/store/actions';
 import { getBaseLayerBlob } from 'features/canvas/util/getBaseLayerBlob';
 import { addToast } from 'features/system/store/systemSlice';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
 
-import { startAppListening } from '..';
-
-export const addCanvasSavedToGalleryListener = () => {
+export const addCanvasSavedToGalleryListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: canvasSavedToGallery,
     effect: async (action, { dispatch, getState }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/controlNetAutoProcess.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/controlNetAutoProcess.ts
index d194195665..e52df30681 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/controlNetAutoProcess.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/controlNetAutoProcess.ts
@@ -1,5 +1,6 @@
 import type { AnyListenerPredicate } from '@reduxjs/toolkit';
 import { logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import type { RootState } from 'app/store/store';
 import { controlAdapterImageProcessed } from 'features/controlAdapters/store/actions';
 import {
@@ -12,8 +13,6 @@ import {
 } from 'features/controlAdapters/store/controlAdaptersSlice';
 import { isControlNetOrT2IAdapter } from 'features/controlAdapters/store/types';
 
-import { startAppListening } from '..';
-
 type AnyControlAdapterParamChangeAction =
   | ReturnType<typeof controlAdapterProcessorParamsChanged>
   | ReturnType<typeof controlAdapterModelChanged>
@@ -67,7 +66,7 @@ const DEBOUNCE_MS = 300;
  *
  * The network request is debounced.
  */
-export const addControlNetAutoProcessListener = () => {
+export const addControlNetAutoProcessListener = (startAppListening: AppStartListening) => {
   startAppListening({
     predicate,
     effect: async (action, { dispatch, cancelActiveListeners, delay }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/controlNetImageProcessed.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/controlNetImageProcessed.ts
index 73de931297..0055866aa7 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/controlNetImageProcessed.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/controlNetImageProcessed.ts
@@ -1,4 +1,5 @@
 import { logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { parseify } from 'common/util/serialize';
 import { controlAdapterImageProcessed } from 'features/controlAdapters/store/actions';
 import {
@@ -16,9 +17,7 @@ import { queueApi } from 'services/api/endpoints/queue';
 import type { BatchConfig, ImageDTO } from 'services/api/types';
 import { socketInvocationComplete } from 'services/events/actions';
 
-import { startAppListening } from '..';
-
-export const addControlNetImageProcessedListener = () => {
+export const addControlNetImageProcessedListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: controlAdapterImageProcessed,
     effect: async (action, { dispatch, getState, take }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/enqueueRequestedCanvas.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/enqueueRequestedCanvas.ts
index 7847448d3e..ed1f4fdd98 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/enqueueRequestedCanvas.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/enqueueRequestedCanvas.ts
@@ -1,5 +1,6 @@
 import { logger } from 'app/logging/logger';
 import { enqueueRequested } from 'app/store/actions';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import openBase64ImageInTab from 'common/util/openBase64ImageInTab';
 import { parseify } from 'common/util/serialize';
 import { canvasBatchIdAdded, stagingAreaInitialized } from 'features/canvas/store/canvasSlice';
@@ -13,8 +14,6 @@ import { imagesApi } from 'services/api/endpoints/images';
 import { queueApi } from 'services/api/endpoints/queue';
 import type { ImageDTO } from 'services/api/types';
 
-import { startAppListening } from '..';
-
 /**
  * This listener is responsible invoking the canvas. This involves a number of steps:
  *
@@ -28,7 +27,7 @@ import { startAppListening } from '..';
  * 8. Initialize the staging area if not yet initialized
  * 9. Dispatch the sessionReadyToInvoke action to invoke the session
  */
-export const addEnqueueRequestedCanvasListener = () => {
+export const addEnqueueRequestedCanvasListener = (startAppListening: AppStartListening) => {
   startAppListening({
     predicate: (action): action is ReturnType<typeof enqueueRequested> =>
       enqueueRequested.match(action) && action.payload.tabName === 'unifiedCanvas',
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/enqueueRequestedLinear.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/enqueueRequestedLinear.ts
index d1cb692c98..337c0f4145 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/enqueueRequestedLinear.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/enqueueRequestedLinear.ts
@@ -1,4 +1,5 @@
 import { enqueueRequested } from 'app/store/actions';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { prepareLinearUIBatch } from 'features/nodes/util/graph/buildLinearBatchConfig';
 import { buildLinearImageToImageGraph } from 'features/nodes/util/graph/buildLinearImageToImageGraph';
 import { buildLinearSDXLImageToImageGraph } from 'features/nodes/util/graph/buildLinearSDXLImageToImageGraph';
@@ -6,9 +7,7 @@ import { buildLinearSDXLTextToImageGraph } from 'features/nodes/util/graph/build
 import { buildLinearTextToImageGraph } from 'features/nodes/util/graph/buildLinearTextToImageGraph';
 import { queueApi } from 'services/api/endpoints/queue';
 
-import { startAppListening } from '..';
-
-export const addEnqueueRequestedLinear = () => {
+export const addEnqueueRequestedLinear = (startAppListening: AppStartListening) => {
   startAppListening({
     predicate: (action): action is ReturnType<typeof enqueueRequested> =>
       enqueueRequested.match(action) && (action.payload.tabName === 'txt2img' || action.payload.tabName === 'img2img'),
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/enqueueRequestedNodes.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/enqueueRequestedNodes.ts
index 0ad33057fd..e33f7c964a 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/enqueueRequestedNodes.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/enqueueRequestedNodes.ts
@@ -1,12 +1,11 @@
 import { enqueueRequested } from 'app/store/actions';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { buildNodesGraph } from 'features/nodes/util/graph/buildNodesGraph';
 import { buildWorkflowWithValidation } from 'features/nodes/util/workflow/buildWorkflow';
 import { queueApi } from 'services/api/endpoints/queue';
 import type { BatchConfig } from 'services/api/types';
 
-import { startAppListening } from '..';
-
-export const addEnqueueRequestedNodes = () => {
+export const addEnqueueRequestedNodes = (startAppListening: AppStartListening) => {
   startAppListening({
     predicate: (action): action is ReturnType<typeof enqueueRequested> =>
       enqueueRequested.match(action) && action.payload.tabName === 'nodes',
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/galleryImageClicked.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/galleryImageClicked.ts
index cc810a2517..67c6d076ee 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/galleryImageClicked.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/galleryImageClicked.ts
@@ -1,12 +1,11 @@
 import { createAction } from '@reduxjs/toolkit';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { selectListImagesQueryArgs } from 'features/gallery/store/gallerySelectors';
 import { selectionChanged } from 'features/gallery/store/gallerySlice';
 import { imagesApi } from 'services/api/endpoints/images';
 import type { ImageDTO } from 'services/api/types';
 import { imagesSelectors } from 'services/api/util';
 
-import { startAppListening } from '..';
-
 export const galleryImageClicked = createAction<{
   imageDTO: ImageDTO;
   shiftKey: boolean;
@@ -25,7 +24,7 @@ export const galleryImageClicked = createAction<{
  * is much more responsive.
  */
 
-export const addGalleryImageClickedListener = () => {
+export const addGalleryImageClickedListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: galleryImageClicked,
     effect: async (action, { dispatch, getState }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/getOpenAPISchema.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/getOpenAPISchema.ts
index 88518e2c0b..acb2bdb698 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/getOpenAPISchema.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/getOpenAPISchema.ts
@@ -1,13 +1,12 @@
 import { logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { parseify } from 'common/util/serialize';
 import { nodeTemplatesBuilt } from 'features/nodes/store/nodesSlice';
 import { parseSchema } from 'features/nodes/util/schema/parseSchema';
 import { size } from 'lodash-es';
 import { appInfoApi } from 'services/api/endpoints/appInfo';
 
-import { startAppListening } from '..';
-
-export const addGetOpenAPISchemaListener = () => {
+export const addGetOpenAPISchemaListener = (startAppListening: AppStartListening) => {
   startAppListening({
     matcher: appInfoApi.endpoints.getOpenAPISchema.matchFulfilled,
     effect: (action, { dispatch, getState }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageAddedToBoard.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageAddedToBoard.ts
index 61da8ff669..5412e0f236 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageAddedToBoard.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageAddedToBoard.ts
@@ -1,9 +1,8 @@
 import { logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { imagesApi } from 'services/api/endpoints/images';
 
-import { startAppListening } from '..';
-
-export const addImageAddedToBoardFulfilledListener = () => {
+export const addImageAddedToBoardFulfilledListener = (startAppListening: AppStartListening) => {
   startAppListening({
     matcher: imagesApi.endpoints.addImageToBoard.matchFulfilled,
     effect: (action) => {
@@ -15,9 +14,7 @@ export const addImageAddedToBoardFulfilledListener = () => {
       log.debug({ board_id, imageDTO }, 'Image added to board');
     },
   });
-};
 
-export const addImageAddedToBoardRejectedListener = () => {
   startAppListening({
     matcher: imagesApi.endpoints.addImageToBoard.matchRejected,
     effect: (action) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageDeleted.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageDeleted.ts
index 1312e54891..9bbbf80263 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageDeleted.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageDeleted.ts
@@ -1,4 +1,5 @@
 import { logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { resetCanvas } from 'features/canvas/store/canvasSlice';
 import {
   controlAdapterImageChanged,
@@ -19,9 +20,7 @@ import { api } from 'services/api';
 import { imagesApi } from 'services/api/endpoints/images';
 import { imagesSelectors } from 'services/api/util';
 
-import { startAppListening } from '..';
-
-export const addRequestedSingleImageDeletionListener = () => {
+export const addRequestedSingleImageDeletionListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: imageDeletionConfirmed,
     effect: async (action, { dispatch, getState, condition }) => {
@@ -134,12 +133,7 @@ export const addRequestedSingleImageDeletionListener = () => {
       }
     },
   });
-};
 
-/**
- * Called when the user requests an image deletion
- */
-export const addRequestedMultipleImageDeletionListener = () => {
   startAppListening({
     actionCreator: imageDeletionConfirmed,
     effect: async (action, { dispatch, getState }) => {
@@ -224,24 +218,14 @@ export const addRequestedMultipleImageDeletionListener = () => {
       }
     },
   });
-};
 
-/**
- * Called when the actual delete request is sent to the server
- */
-export const addImageDeletedPendingListener = () => {
   startAppListening({
     matcher: imagesApi.endpoints.deleteImage.matchPending,
     effect: () => {
       //
     },
   });
-};
 
-/**
- * Called on successful delete
- */
-export const addImageDeletedFulfilledListener = () => {
   startAppListening({
     matcher: imagesApi.endpoints.deleteImage.matchFulfilled,
     effect: (action) => {
@@ -249,12 +233,7 @@ export const addImageDeletedFulfilledListener = () => {
       log.debug({ imageDTO: action.meta.arg.originalArgs }, 'Image deleted');
     },
   });
-};
 
-/**
- * Called on failed delete
- */
-export const addImageDeletedRejectedListener = () => {
   startAppListening({
     matcher: imagesApi.endpoints.deleteImage.matchRejected,
     effect: (action) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageDropped.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageDropped.ts
index 268aac25d9..5c1f321b64 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageDropped.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageDropped.ts
@@ -1,5 +1,6 @@
 import { createAction } from '@reduxjs/toolkit';
 import { logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { parseify } from 'common/util/serialize';
 import { setInitialCanvasImage } from 'features/canvas/store/canvasSlice';
 import {
@@ -12,14 +13,12 @@ import { fieldImageValueChanged } from 'features/nodes/store/nodesSlice';
 import { initialImageChanged, selectOptimalDimension } from 'features/parameters/store/generationSlice';
 import { imagesApi } from 'services/api/endpoints/images';
 
-import { startAppListening } from '../';
-
 export const dndDropped = createAction<{
   overData: TypesafeDroppableData;
   activeData: TypesafeDraggableData;
 }>('dnd/dndDropped');
 
-export const addImageDroppedListener = () => {
+export const addImageDroppedListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: dndDropped,
     effect: async (action, { dispatch, getState }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageRemovedFromBoard.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageRemovedFromBoard.ts
index 4c21a750f1..274e4c51c2 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageRemovedFromBoard.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageRemovedFromBoard.ts
@@ -1,9 +1,8 @@
 import { logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { imagesApi } from 'services/api/endpoints/images';
 
-import { startAppListening } from '..';
-
-export const addImageRemovedFromBoardFulfilledListener = () => {
+export const addImageRemovedFromBoardFulfilledListener = (startAppListening: AppStartListening) => {
   startAppListening({
     matcher: imagesApi.endpoints.removeImageFromBoard.matchFulfilled,
     effect: (action) => {
@@ -13,9 +12,7 @@ export const addImageRemovedFromBoardFulfilledListener = () => {
       log.debug({ imageDTO }, 'Image removed from board');
     },
   });
-};
 
-export const addImageRemovedFromBoardRejectedListener = () => {
   startAppListening({
     matcher: imagesApi.endpoints.removeImageFromBoard.matchRejected,
     effect: (action) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageToDeleteSelected.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageToDeleteSelected.ts
index 03921264a2..d20c0c7c23 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageToDeleteSelected.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageToDeleteSelected.ts
@@ -1,10 +1,9 @@
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { imageDeletionConfirmed } from 'features/deleteImageModal/store/actions';
 import { selectImageUsage } from 'features/deleteImageModal/store/selectors';
 import { imagesToDeleteSelected, isModalOpenChanged } from 'features/deleteImageModal/store/slice';
 
-import { startAppListening } from '..';
-
-export const addImageToDeleteSelectedListener = () => {
+export const addImageToDeleteSelectedListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: imagesToDeleteSelected,
     effect: async (action, { dispatch, getState }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageUploaded.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageUploaded.ts
index d17727fcdc..2cebf0aef8 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageUploaded.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageUploaded.ts
@@ -1,5 +1,6 @@
 import type { UseToastOptions } from '@invoke-ai/ui-library';
 import { logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { setInitialCanvasImage } from 'features/canvas/store/canvasSlice';
 import {
   controlAdapterImageChanged,
@@ -13,9 +14,7 @@ import { omit } from 'lodash-es';
 import { boardsApi } from 'services/api/endpoints/boards';
 import { imagesApi } from 'services/api/endpoints/images';
 
-import { startAppListening } from '..';
-
-export const addImageUploadedFulfilledListener = () => {
+export const addImageUploadedFulfilledListener = (startAppListening: AppStartListening) => {
   startAppListening({
     matcher: imagesApi.endpoints.uploadImage.matchFulfilled,
     effect: (action, { dispatch, getState }) => {
@@ -133,9 +132,7 @@ export const addImageUploadedFulfilledListener = () => {
       }
     },
   });
-};
 
-export const addImageUploadedRejectedListener = () => {
   startAppListening({
     matcher: imagesApi.endpoints.uploadImage.matchRejected,
     effect: (action, { dispatch }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imagesStarred.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imagesStarred.ts
index 064e9876fc..74b36e3297 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imagesStarred.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imagesStarred.ts
@@ -1,10 +1,9 @@
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { selectionChanged } from 'features/gallery/store/gallerySlice';
 import { imagesApi } from 'services/api/endpoints/images';
 import type { ImageDTO } from 'services/api/types';
 
-import { startAppListening } from '..';
-
-export const addImagesStarredListener = () => {
+export const addImagesStarredListener = (startAppListening: AppStartListening) => {
   startAppListening({
     matcher: imagesApi.endpoints.starImages.matchFulfilled,
     effect: async (action, { dispatch, getState }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imagesUnstarred.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imagesUnstarred.ts
index 7174bd066d..ebae7885c1 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imagesUnstarred.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imagesUnstarred.ts
@@ -1,10 +1,9 @@
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { selectionChanged } from 'features/gallery/store/gallerySlice';
 import { imagesApi } from 'services/api/endpoints/images';
 import type { ImageDTO } from 'services/api/types';
 
-import { startAppListening } from '..';
-
-export const addImagesUnstarredListener = () => {
+export const addImagesUnstarredListener = (startAppListening: AppStartListening) => {
   startAppListening({
     matcher: imagesApi.endpoints.unstarImages.matchFulfilled,
     effect: async (action, { dispatch, getState }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/initialImageSelected.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/initialImageSelected.ts
index 93e921e911..735ce8367a 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/initialImageSelected.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/initialImageSelected.ts
@@ -1,12 +1,11 @@
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { initialImageSelected } from 'features/parameters/store/actions';
 import { initialImageChanged } from 'features/parameters/store/generationSlice';
 import { addToast } from 'features/system/store/systemSlice';
 import { makeToast } from 'features/system/util/makeToast';
 import { t } from 'i18next';
 
-import { startAppListening } from '..';
-
-export const addInitialImageSelectedListener = () => {
+export const addInitialImageSelectedListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: initialImageSelected,
     effect: (action, { dispatch }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/modelSelected.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/modelSelected.ts
index bbb9485bcf..bc049cf498 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/modelSelected.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/modelSelected.ts
@@ -1,4 +1,5 @@
 import { logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import {
   controlAdapterIsEnabledChanged,
   selectControlAdapterAll,
@@ -12,9 +13,7 @@ import { makeToast } from 'features/system/util/makeToast';
 import { t } from 'i18next';
 import { forEach } from 'lodash-es';
 
-import { startAppListening } from '..';
-
-export const addModelSelectedListener = () => {
+export const addModelSelectedListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: modelSelected,
     effect: (action, { getState, dispatch }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/modelsLoaded.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/modelsLoaded.ts
index a1bc9856c9..75c6080bf6 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/modelsLoaded.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/modelsLoaded.ts
@@ -1,4 +1,5 @@
 import { logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import {
   controlAdapterModelCleared,
   selectAllControlNets,
@@ -13,9 +14,7 @@ import { forEach, some } from 'lodash-es';
 import { mainModelsAdapterSelectors, modelsApi, vaeModelsAdapterSelectors } from 'services/api/endpoints/models';
 import type { TypeGuardFor } from 'services/api/types';
 
-import { startAppListening } from '..';
-
-export const addModelsLoadedListener = () => {
+export const addModelsLoadedListener = (startAppListening: AppStartListening) => {
   startAppListening({
     predicate: (action): action is TypeGuardFor<typeof modelsApi.endpoints.getMainModels.matchFulfilled> =>
       modelsApi.endpoints.getMainModels.matchFulfilled(action) &&
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/promptChanged.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/promptChanged.ts
index bd6cd502f6..b78ddc3f69 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/promptChanged.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/promptChanged.ts
@@ -1,4 +1,5 @@
 import { isAnyOf } from '@reduxjs/toolkit';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import {
   combinatorialToggled,
   isErrorChanged,
@@ -13,11 +14,9 @@ import { setPositivePrompt } from 'features/parameters/store/generationSlice';
 import { utilitiesApi } from 'services/api/endpoints/utilities';
 import { socketConnected } from 'services/events/actions';
 
-import { startAppListening } from '..';
-
 const matcher = isAnyOf(setPositivePrompt, combinatorialToggled, maxPromptsChanged, maxPromptsReset, socketConnected);
 
-export const addDynamicPromptsListener = () => {
+export const addDynamicPromptsListener = (startAppListening: AppStartListening) => {
   startAppListening({
     matcher,
     effect: async (action, { dispatch, getState, cancelActiveListeners, delay }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketConnected.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketConnected.ts
index df0de6bbda..4c76474cdc 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketConnected.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketConnected.ts
@@ -1,4 +1,5 @@
 import { logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { $baseUrl } from 'app/store/nanostores/baseUrl';
 import { isEqual } from 'lodash-es';
 import { atom } from 'nanostores';
@@ -6,13 +7,11 @@ import { api } from 'services/api';
 import { queueApi, selectQueueStatus } from 'services/api/endpoints/queue';
 import { socketConnected } from 'services/events/actions';
 
-import { startAppListening } from '../..';
-
 const log = logger('socketio');
 
 const $isFirstConnection = atom(true);
 
-export const addSocketConnectedEventListener = () => {
+export const addSocketConnectedEventListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: socketConnected,
     effect: async (action, { dispatch, getState, cancelActiveListeners, delay }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketDisconnected.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketDisconnected.ts
index 02d3b77f89..be1a7663b3 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketDisconnected.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketDisconnected.ts
@@ -1,11 +1,10 @@
 import { logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { socketDisconnected } from 'services/events/actions';
 
-import { startAppListening } from '../..';
-
 const log = logger('socketio');
 
-export const addSocketDisconnectedEventListener = () => {
+export const addSocketDisconnectedEventListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: socketDisconnected,
     effect: () => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketGeneratorProgress.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketGeneratorProgress.ts
index 0965f41ee1..bb113a09ee 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketGeneratorProgress.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketGeneratorProgress.ts
@@ -1,11 +1,10 @@
 import { logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { socketGeneratorProgress } from 'services/events/actions';
 
-import { startAppListening } from '../..';
-
 const log = logger('socketio');
 
-export const addGeneratorProgressEventListener = () => {
+export const addGeneratorProgressEventListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: socketGeneratorProgress,
     effect: (action) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketGraphExecutionStateComplete.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketGraphExecutionStateComplete.ts
index e4f83561c8..5221679232 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketGraphExecutionStateComplete.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketGraphExecutionStateComplete.ts
@@ -1,11 +1,10 @@
 import { logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { socketGraphExecutionStateComplete } from 'services/events/actions';
 
-import { startAppListening } from '../..';
-
 const log = logger('socketio');
 
-export const addGraphExecutionStateCompleteEventListener = () => {
+export const addGraphExecutionStateCompleteEventListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: socketGraphExecutionStateComplete,
     effect: (action) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationComplete.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationComplete.ts
index 75fa9e1094..279f9aac5b 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationComplete.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationComplete.ts
@@ -1,4 +1,5 @@
 import { logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { parseify } from 'common/util/serialize';
 import { addImageToStagingArea } from 'features/canvas/store/canvasSlice';
 import { boardIdSelected, galleryViewChanged, imageSelected } from 'features/gallery/store/gallerySlice';
@@ -10,14 +11,12 @@ import { imagesApi } from 'services/api/endpoints/images';
 import { imagesAdapter } from 'services/api/util';
 import { socketInvocationComplete } from 'services/events/actions';
 
-import { startAppListening } from '../..';
-
 // These nodes output an image, but do not actually *save* an image, so we don't want to handle the gallery logic on them
 const nodeTypeDenylist = ['load_image', 'image'];
 
 const log = logger('socketio');
 
-export const addInvocationCompleteEventListener = () => {
+export const addInvocationCompleteEventListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: socketInvocationComplete,
     effect: async (action, { dispatch, getState }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationError.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationError.ts
index dfc1f0dd58..fb898b4c7a 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationError.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationError.ts
@@ -1,11 +1,10 @@
 import { logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { socketInvocationError } from 'services/events/actions';
 
-import { startAppListening } from '../..';
-
 const log = logger('socketio');
 
-export const addInvocationErrorEventListener = () => {
+export const addInvocationErrorEventListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: socketInvocationError,
     effect: (action) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationRetrievalError.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationRetrievalError.ts
index f02317c236..44da4c0ddb 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationRetrievalError.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationRetrievalError.ts
@@ -1,11 +1,10 @@
 import { logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { socketInvocationRetrievalError } from 'services/events/actions';
 
-import { startAppListening } from '../..';
-
 const log = logger('socketio');
 
-export const addInvocationRetrievalErrorEventListener = () => {
+export const addInvocationRetrievalErrorEventListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: socketInvocationRetrievalError,
     effect: (action) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationStarted.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationStarted.ts
index 12766b2707..baf476a66b 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationStarted.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationStarted.ts
@@ -1,11 +1,10 @@
 import { logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { socketInvocationStarted } from 'services/events/actions';
 
-import { startAppListening } from '../..';
-
 const log = logger('socketio');
 
-export const addInvocationStartedEventListener = () => {
+export const addInvocationStartedEventListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: socketInvocationStarted,
     effect: (action) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts
index 60dc173cb4..9faedc64d7 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts
@@ -1,3 +1,4 @@
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { api } from 'services/api';
 import { modelsApi } from 'services/api/endpoints/models';
 import {
@@ -6,9 +7,7 @@ import {
   socketModelInstallError,
 } from 'services/events/actions';
 
-import { startAppListening } from '../..';
-
-export const addModelInstallEventListener = () => {
+export const addModelInstallEventListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: socketModelInstallDownloading,
     effect: async (action, { dispatch }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelLoad.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelLoad.ts
index aa91c69d75..7009baddf2 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelLoad.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelLoad.ts
@@ -1,11 +1,10 @@
 import { logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { socketModelLoadCompleted, socketModelLoadStarted } from 'services/events/actions';
 
-import { startAppListening } from '../..';
-
 const log = logger('socketio');
 
-export const addModelLoadEventListener = () => {
+export const addModelLoadEventListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: socketModelLoadStarted,
     effect: (action) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketQueueItemStatusChanged.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketQueueItemStatusChanged.ts
index bd5471b299..84073bb427 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketQueueItemStatusChanged.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketQueueItemStatusChanged.ts
@@ -1,12 +1,11 @@
 import { logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { queueApi, queueItemsAdapter } from 'services/api/endpoints/queue';
 import { socketQueueItemStatusChanged } from 'services/events/actions';
 
-import { startAppListening } from '../..';
-
 const log = logger('socketio');
 
-export const addSocketQueueItemStatusChangedEventListener = () => {
+export const addSocketQueueItemStatusChangedEventListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: socketQueueItemStatusChanged,
     effect: async (action, { dispatch }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketSessionRetrievalError.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketSessionRetrievalError.ts
index b655a686de..a1a497dc08 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketSessionRetrievalError.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketSessionRetrievalError.ts
@@ -1,11 +1,10 @@
 import { logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { socketSessionRetrievalError } from 'services/events/actions';
 
-import { startAppListening } from '../..';
-
 const log = logger('socketio');
 
-export const addSessionRetrievalErrorEventListener = () => {
+export const addSessionRetrievalErrorEventListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: socketSessionRetrievalError,
     effect: (action) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketSubscribed.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketSubscribed.ts
index df7d5b4e02..48324cb652 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketSubscribed.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketSubscribed.ts
@@ -1,11 +1,10 @@
 import { logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { socketSubscribedSession } from 'services/events/actions';
 
-import { startAppListening } from '../..';
-
 const log = logger('socketio');
 
-export const addSocketSubscribedEventListener = () => {
+export const addSocketSubscribedEventListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: socketSubscribedSession,
     effect: (action) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketUnsubscribed.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketUnsubscribed.ts
index 4552fba2c5..7a76a809d6 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketUnsubscribed.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketUnsubscribed.ts
@@ -1,10 +1,9 @@
 import { logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { socketUnsubscribedSession } from 'services/events/actions';
-
-import { startAppListening } from '../..';
 const log = logger('socketio');
 
-export const addSocketUnsubscribedEventListener = () => {
+export const addSocketUnsubscribedEventListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: socketUnsubscribedSession,
     effect: (action) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/stagingAreaImageSaved.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/stagingAreaImageSaved.ts
index 8a38be1b77..6816e25bc1 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/stagingAreaImageSaved.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/stagingAreaImageSaved.ts
@@ -1,11 +1,10 @@
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { stagingAreaImageSaved } from 'features/canvas/store/actions';
 import { addToast } from 'features/system/store/systemSlice';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
 
-import { startAppListening } from '..';
-
-export const addStagingAreaImageSavedListener = () => {
+export const addStagingAreaImageSavedListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: stagingAreaImageSaved,
     effect: async (action, { dispatch, getState }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/updateAllNodesRequested.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/updateAllNodesRequested.ts
index ac1298da5b..5ee9de3c11 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/updateAllNodesRequested.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/updateAllNodesRequested.ts
@@ -1,4 +1,5 @@
 import { logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { updateAllNodesRequested } from 'features/nodes/store/actions';
 import { nodeReplaced } from 'features/nodes/store/nodesSlice';
 import { NodeUpdateError } from 'features/nodes/types/error';
@@ -8,9 +9,7 @@ import { addToast } from 'features/system/store/systemSlice';
 import { makeToast } from 'features/system/util/makeToast';
 import { t } from 'i18next';
 
-import { startAppListening } from '..';
-
-export const addUpdateAllNodesRequestedListener = () => {
+export const addUpdateAllNodesRequestedListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: updateAllNodesRequested,
     effect: (action, { dispatch, getState }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/upscaleRequested.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/upscaleRequested.ts
index ab98930179..ff5d5f24be 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/upscaleRequested.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/upscaleRequested.ts
@@ -1,5 +1,6 @@
 import { createAction } from '@reduxjs/toolkit';
 import { logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { parseify } from 'common/util/serialize';
 import { buildAdHocUpscaleGraph } from 'features/nodes/util/graph/buildAdHocUpscaleGraph';
 import { createIsAllowedToUpscaleSelector } from 'features/parameters/hooks/useIsAllowedToUpscale';
@@ -8,11 +9,9 @@ import { t } from 'i18next';
 import { queueApi } from 'services/api/endpoints/queue';
 import type { BatchConfig, ImageDTO } from 'services/api/types';
 
-import { startAppListening } from '..';
-
 export const upscaleRequested = createAction<{ imageDTO: ImageDTO }>(`upscale/upscaleRequested`);
 
-export const addUpscaleRequestedListener = () => {
+export const addUpscaleRequestedListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: upscaleRequested,
     effect: async (action, { dispatch, getState }) => {
diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/workflowLoadRequested.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/workflowLoadRequested.ts
index ad41dc2654..0227597fe9 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/workflowLoadRequested.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/workflowLoadRequested.ts
@@ -1,4 +1,5 @@
 import { logger } from 'app/logging/logger';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { parseify } from 'common/util/serialize';
 import { workflowLoaded, workflowLoadRequested } from 'features/nodes/store/actions';
 import { $flow } from 'features/nodes/store/reactFlowInstance';
@@ -10,9 +11,7 @@ import { t } from 'i18next';
 import { z } from 'zod';
 import { fromZodError } from 'zod-validation-error';
 
-import { startAppListening } from '..';
-
-export const addWorkflowLoadRequestedListener = () => {
+export const addWorkflowLoadRequestedListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: workflowLoadRequested,
     effect: (action, { dispatch, getState }) => {
diff --git a/invokeai/frontend/web/src/services/api/schema.ts b/invokeai/frontend/web/src/services/api/schema.ts
index 364ad00578..12227d1ae9 100644
--- a/invokeai/frontend/web/src/services/api/schema.ts
+++ b/invokeai/frontend/web/src/services/api/schema.ts
@@ -572,7 +572,7 @@ export type paths = {
   };
 };
 
-export type webhooks = Record<string, never>;
+type webhooks = Record<string, never>;
 
 export type components = {
   schemas: {
@@ -10929,9 +10929,9 @@ export type components = {
   pathItems: never;
 };
 
-export type $defs = Record<string, never>;
+type $defs = Record<string, never>;
 
-export type external = Record<string, never>;
+type external = Record<string, never>;
 
 export type operations = {
 

From bcf742ef874ac20da02ee8d2cc07f36668cffc03 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 27 Feb 2024 19:17:18 +1100
Subject: [PATCH 354/411] feat(ui): move from madge to dpdm for circular
 dependencies

---
 invokeai/frontend/web/package.json   |   4 +-
 invokeai/frontend/web/pnpm-lock.yaml | 671 +--------------------------
 2 files changed, 21 insertions(+), 654 deletions(-)

diff --git a/invokeai/frontend/web/package.json b/invokeai/frontend/web/package.json
index abc9ac059b..c02e9fecca 100644
--- a/invokeai/frontend/web/package.json
+++ b/invokeai/frontend/web/package.json
@@ -25,7 +25,7 @@
     "typegen": "node scripts/typegen.js",
     "preview": "vite preview",
     "lint:knip": "knip",
-    "lint:madge": "madge --circular src/main.tsx",
+    "lint:dpdm": "dpdm --no-warning --no-tree --transform --exit-code circular:1 src/main.tsx",
     "lint:eslint": "eslint --max-warnings=0 .",
     "lint:prettier": "prettier --check .",
     "lint:tsc": "tsc --noEmit",
@@ -128,11 +128,11 @@
     "@types/uuid": "^9.0.8",
     "@vitejs/plugin-react-swc": "^3.6.0",
     "concurrently": "^8.2.2",
+    "dpdm": "^3.14.0",
     "eslint": "^8.56.0",
     "eslint-plugin-i18next": "^6.0.3",
     "eslint-plugin-path": "^1.2.4",
     "knip": "^5.0.2",
-    "madge": "^6.1.0",
     "openapi-types": "^12.1.3",
     "openapi-typescript": "^6.7.4",
     "prettier": "^3.2.5",
diff --git a/invokeai/frontend/web/pnpm-lock.yaml b/invokeai/frontend/web/pnpm-lock.yaml
index 113189cffb..b023409c55 100644
--- a/invokeai/frontend/web/pnpm-lock.yaml
+++ b/invokeai/frontend/web/pnpm-lock.yaml
@@ -217,6 +217,9 @@ devDependencies:
   concurrently:
     specifier: ^8.2.2
     version: 8.2.2
+  dpdm:
+    specifier: ^3.14.0
+    version: 3.14.0
   eslint:
     specifier: ^8.56.0
     version: 8.56.0
@@ -229,9 +232,6 @@ devDependencies:
   knip:
     specifier: ^5.0.2
     version: 5.0.2(@types/node@20.11.19)(typescript@5.3.3)
-  madge:
-    specifier: ^6.1.0
-    version: 6.1.0(typescript@5.3.3)
   openapi-types:
     specifier: ^12.1.3
     version: 12.1.3
@@ -3005,14 +3005,6 @@ packages:
     engines: {node: '>17.0.0'}
     dev: false
 
-  /@dependents/detective-less@3.0.2:
-    resolution: {integrity: sha512-1YUvQ+e0eeTWAHoN8Uz2x2U37jZs6IGutiIE5LXId7cxfUGhtZjzxE06FdUiuiRrW+UE0vNCdSNPH2lY4dQCOQ==}
-    engines: {node: '>=12'}
-    dependencies:
-      gonzales-pe: 4.3.0
-      node-source-walk: 5.0.2
-    dev: true
-
   /@discoveryjs/json-ext@0.5.7:
     resolution: {integrity: sha512-dBVuXR082gk3jsFp7Rd/JI4kytwGHecnCoTtXFb7DB6CNHp4rg5k1bhg0nWdLGLnOV71lmDzGQaLMy8iPLY0pw==}
     engines: {node: '>=10.0.0'}
@@ -6574,11 +6566,6 @@ packages:
       - supports-color
     dev: true
 
-  /@typescript-eslint/types@4.33.0:
-    resolution: {integrity: sha512-zKp7CjQzLQImXEpLt2BUw1tvOMPfNoTAfb8l51evhYbOEEzdWyQNmHWWGPR6hwKJDAi+1VXSBmnhL9kyVTTOuQ==}
-    engines: {node: ^8.10.0 || ^10.13.0 || >=11.10.1}
-    dev: true
-
   /@typescript-eslint/types@5.62.0:
     resolution: {integrity: sha512-87NVngcbVXUahrRTqIK27gD2t5Cu1yuCXxbLcFtCzZGlfyVWWh8mLHkoxzjsB6DDNnvdL+fW8MiwPEJyGJQDgQ==}
     engines: {node: ^12.22.0 || ^14.17.0 || >=16.0.0}
@@ -6589,48 +6576,6 @@ packages:
     engines: {node: ^16.0.0 || >=18.0.0}
     dev: true
 
-  /@typescript-eslint/typescript-estree@4.33.0(typescript@3.9.10):
-    resolution: {integrity: sha512-rkWRY1MPFzjwnEVHsxGemDzqqddw2QbTJlICPD9p9I9LfsO8fdmfQPOX3uKfUaGRDFJbfrtm/sXhVXN4E+bzCA==}
-    engines: {node: ^10.12.0 || >=12.0.0}
-    peerDependencies:
-      typescript: '*'
-    peerDependenciesMeta:
-      typescript:
-        optional: true
-    dependencies:
-      '@typescript-eslint/types': 4.33.0
-      '@typescript-eslint/visitor-keys': 4.33.0
-      debug: 4.3.4
-      globby: 11.1.0
-      is-glob: 4.0.3
-      semver: 7.6.0
-      tsutils: 3.21.0(typescript@3.9.10)
-      typescript: 3.9.10
-    transitivePeerDependencies:
-      - supports-color
-    dev: true
-
-  /@typescript-eslint/typescript-estree@5.62.0(typescript@4.9.5):
-    resolution: {integrity: sha512-CmcQ6uY7b9y694lKdRB8FEel7JbU/40iSAPomu++SjLMntB+2Leay2LO6i8VnJk58MtE9/nQSFIH6jpyRWyYzA==}
-    engines: {node: ^12.22.0 || ^14.17.0 || >=16.0.0}
-    peerDependencies:
-      typescript: '*'
-    peerDependenciesMeta:
-      typescript:
-        optional: true
-    dependencies:
-      '@typescript-eslint/types': 5.62.0
-      '@typescript-eslint/visitor-keys': 5.62.0
-      debug: 4.3.4
-      globby: 11.1.0
-      is-glob: 4.0.3
-      semver: 7.6.0
-      tsutils: 3.21.0(typescript@4.9.5)
-      typescript: 4.9.5
-    transitivePeerDependencies:
-      - supports-color
-    dev: true
-
   /@typescript-eslint/typescript-estree@5.62.0(typescript@5.3.3):
     resolution: {integrity: sha512-CmcQ6uY7b9y694lKdRB8FEel7JbU/40iSAPomu++SjLMntB+2Leay2LO6i8VnJk58MtE9/nQSFIH6jpyRWyYzA==}
     engines: {node: ^12.22.0 || ^14.17.0 || >=16.0.0}
@@ -6713,14 +6658,6 @@ packages:
       - typescript
     dev: true
 
-  /@typescript-eslint/visitor-keys@4.33.0:
-    resolution: {integrity: sha512-uqi/2aSz9g2ftcHWf8uLPJA70rUv6yuMW5Bohw+bwcuzaxQIHaKFZCKGoGXIrc9vkTJ3+0txM73K0Hq3d5wgIg==}
-    engines: {node: ^8.10.0 || ^10.13.0 || >=11.10.1}
-    dependencies:
-      '@typescript-eslint/types': 4.33.0
-      eslint-visitor-keys: 2.1.0
-    dev: true
-
   /@typescript-eslint/visitor-keys@5.62.0:
     resolution: {integrity: sha512-07ny+LHRzQXepkGg6w0mFY41fVUNBrL2Roj/++7V1txKugfjm/Ci/qSND03r2RhlJhJYMcTn9AhhSSqQp0Ysyw==}
     engines: {node: ^12.22.0 || ^14.17.0 || >=16.0.0}
@@ -7581,10 +7518,6 @@ packages:
     engines: {node: '>=12'}
     dev: true
 
-  /any-promise@1.3.0:
-    resolution: {integrity: sha512-7UvmKalWRt1wgjL1RrGxoSJW/0QZFIegpeGvZG9kjp8vrRu55XTHbwnqq2GpXm9uLbcuhxm3IqX9OB4MZR1b2A==}
-    dev: true
-
   /anymatch@3.1.3:
     resolution: {integrity: sha512-KMReFUr0B4t+D+OBkjR3KYqvocp2XaSzO55UcB6mgQMd3KbcE+mWTyvVV7D/zsdEbNnV6acZUutkiHQXvTr1Rw==}
     engines: {node: '>= 8'}
@@ -7593,10 +7526,6 @@ packages:
       picomatch: 2.3.1
     dev: true
 
-  /app-module-path@2.2.0:
-    resolution: {integrity: sha512-gkco+qxENJV+8vFcDiiFhuoSvRXb2a/QPqpSoWhVz829VNJfOTnELbBmPmNKFxf3xdNnw4DWCkzkDaavcX/1YQ==}
-    dev: true
-
   /app-root-dir@1.0.2:
     resolution: {integrity: sha512-jlpIfsOoNoafl92Sz//64uQHGSyMrD2vYG5d8o2a4qGvyNCvXur7bzIsWtAC/6flI2RYAp3kv8rsfBtaLm7w0g==}
     dev: true
@@ -7736,20 +7665,6 @@ packages:
     resolution: {integrity: sha512-jgsaNduz+ndvGyFt3uSuWqvy4lCnIJiovtouQN5JZHOKCS2QuhEdbcQHFhVksz2N2U9hXJo8odG7ETyWlEeuDw==}
     dev: true
 
-  /ast-module-types@2.7.1:
-    resolution: {integrity: sha512-Rnnx/4Dus6fn7fTqdeLEAn5vUll5w7/vts0RN608yFa6si/rDOUonlIIiwugHBFWjylHjxm9owoSZn71KwG4gw==}
-    dev: true
-
-  /ast-module-types@3.0.0:
-    resolution: {integrity: sha512-CMxMCOCS+4D+DkOQfuZf+vLrSEmY/7xtORwdxs4wtcC1wVgvk2MqFFTwQCFhvWsI4KPU9lcWXPI8DgRiz+xetQ==}
-    engines: {node: '>=6.0'}
-    dev: true
-
-  /ast-module-types@4.0.0:
-    resolution: {integrity: sha512-Kd0o8r6CDazJGCRzs8Ivpn0xj19oNKrULhoJFzhGjRsLpekF2zyZs9Ukz+JvZhWD6smszfepakTFhAaYpsI12g==}
-    engines: {node: '>=12.0'}
-    dev: true
-
   /ast-types@0.16.1:
     resolution: {integrity: sha512-6t10qk83GOG8p0vKmaCr8eiilZwO171AvbROMtvvNiwrTly62t+7XkA8RdIIVbpMhCASAsxgAzdRSwh6nw/5Dg==}
     engines: {node: '>=4'}
@@ -8231,6 +8146,7 @@ packages:
 
   /commander@2.20.3:
     resolution: {integrity: sha512-GpVkmM8vF2vQUkj2LvZmD35JxeJOLCwJ9cUkugyk2nuhbv3+mJvpLYYt+0+USMxE+oj+ey/lJEnhZw75x/OMcQ==}
+    dev: false
 
   /commander@4.1.1:
     resolution: {integrity: sha512-NOKm8xhkzAjzFx8B2v5OAHT+u5pRQc2UCa2Vq9jYL/31o2wi9mxBA7LIFs3sV5VSC49z6pEhfbMULvShKj26WA==}
@@ -8242,15 +8158,12 @@ packages:
     engines: {node: '>= 6'}
     dev: true
 
-  /commander@7.2.0:
-    resolution: {integrity: sha512-QrWXB+ZQSVPmIWIhtEO9H+gwHaMGYiF5ChvoJ+K9ZGHG/sVsa6yiesAD1GC/x46sET00Xlwo1u49RVVVzvcSkw==}
-    engines: {node: '>= 10'}
-    dev: true
-
   /commander@9.5.0:
     resolution: {integrity: sha512-KRs7WVDKg86PWiuAqhDrAQnTXZKraVcCc6vFdL14qrZ/DcWwuRo7VoiYXalXO7S5GKpqYiVEwCbgFDfxNHKJBQ==}
     engines: {node: ^12.20.0 || >=14}
+    requiresBuild: true
     dev: true
+    optional: true
 
   /commondir@1.0.1:
     resolution: {integrity: sha512-W9pAhw0ja1Edb5GVdIF1mjZw/ASI0AlShXM83UUGe2DVr5TdAPEA1OA8m/g8zWp9x6On7gqufY+FatDbC3MDQg==}
@@ -8563,11 +8476,6 @@ packages:
       type-detect: 4.0.8
     dev: true
 
-  /deep-extend@0.6.0:
-    resolution: {integrity: sha512-LOHxIOaPYdHlJRtCQfDIVZtfw/ufM8+rVj649RIHzcm/vGwQRXFt6OPqIFWsm2XEMrNIEtWR64sY1LEKD2vAOA==}
-    engines: {node: '>=4.0.0'}
-    dev: true
-
   /deep-freeze@0.0.1:
     resolution: {integrity: sha512-Z+z8HiAvsGwmjqlphnHW5oz6yWlOwu6EQfFTjmeTWlDeda3FS2yv3jhq35TX/ewmsnqB+RX2IdsIOyjJCQN5tg==}
     dev: true
@@ -8640,20 +8548,6 @@ packages:
     engines: {node: '>= 0.8'}
     dev: true
 
-  /dependency-tree@9.0.0:
-    resolution: {integrity: sha512-osYHZJ1fBSon3lNLw70amAXsQ+RGzXsPvk9HbBgTLbp/bQBmpH5mOmsUvqXU+YEWVU0ZLewsmzOET/8jWswjDQ==}
-    engines: {node: ^10.13 || ^12 || >=14}
-    hasBin: true
-    dependencies:
-      commander: 2.20.3
-      debug: 4.3.4
-      filing-cabinet: 3.3.1
-      precinct: 9.2.1
-      typescript: 4.9.5
-    transitivePeerDependencies:
-      - supports-color
-    dev: true
-
   /dequal@2.0.3:
     resolution: {integrity: sha512-0je+qPKHEMohvfRTCEo3CrPG6cAzAYgmzKyxRiYSSDkS6eGJdyVJm7WaYA5ECaAD9wLB2T4EEeymA5aFVcYXCA==}
     engines: {node: '>=6'}
@@ -8689,160 +8583,6 @@ packages:
       - supports-color
     dev: true
 
-  /detective-amd@3.1.2:
-    resolution: {integrity: sha512-jffU26dyqJ37JHR/o44La6CxtrDf3Rt9tvd2IbImJYxWKTMdBjctp37qoZ6ZcY80RHg+kzWz4bXn39e4P7cctQ==}
-    engines: {node: '>=6.0'}
-    hasBin: true
-    dependencies:
-      ast-module-types: 3.0.0
-      escodegen: 2.1.0
-      get-amd-module-type: 3.0.2
-      node-source-walk: 4.3.0
-    dev: true
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@@ -8894,6 +8634,19 @@ packages:
     engines: {node: '>=12'}
     dev: true
 
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+      fs-extra: 11.2.0
+      glob: 10.3.10
+      ora: 5.4.1
+      tslib: 2.6.2
+      typescript: 5.3.3
+      yargs: 17.7.2
+    dev: true
+
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-    engines: {node: '>=10.13.0'}
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     dev: true
 
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@@ -9733,28 +9473,6 @@ packages:
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     dev: true
 
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-    hasBin: true
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-      commander: 2.20.3
-      debug: 4.3.4
-      enhanced-resolve: 5.15.0
-      is-relative-path: 1.0.2
-      module-definition: 3.4.0
-      module-lookup-amd: 7.0.1
-      resolve: 1.22.8
-      resolve-dependency-path: 2.0.0
-      sass-lookup: 3.0.0
-      stylus-lookup: 3.0.2
-      tsconfig-paths: 3.15.0
-      typescript: 3.9.10
-    transitivePeerDependencies:
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-    dev: true
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-    deprecated: flatten is deprecated in favor of utility frameworks such as lodash.
-    dev: true
-
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     engines: {node: '>=0.4.0'}
@@ -10028,22 +9741,6 @@ packages:
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     dev: true
 
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-    dependencies:
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-      node-source-walk: 4.3.0
-    dev: true
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-  /get-amd-module-type@4.1.0:
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-    engines: {node: '>=12'}
-    dependencies:
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-      node-source-walk: 5.0.2
-    dev: true
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     engines: {node: 6.* || 8.* || >= 10.*}
@@ -10072,10 +9769,6 @@ packages:
     engines: {node: '>=12.17'}
     dev: true
 
-  /get-own-enumerable-property-symbols@3.0.2:
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     dev: true
 
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-    engines: {node: '>=0.6.0'}
-    hasBin: true
-    dependencies:
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-    dev: true
-
   /gopd@1.0.1:
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     dependencies:
@@ -10436,10 +10121,6 @@ packages:
     engines: {node: '>=8'}
     dev: true
 
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-    dev: true
-
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     dev: true
 
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-    dev: true
-
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     dependencies:
@@ -10647,11 +10324,6 @@ packages:
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     dev: true
 
-  /is-obj@1.0.1:
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-    engines: {node: '>=0.10.0'}
-    dev: true
-
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     engines: {node: '>=6'}
@@ -10682,15 +10354,6 @@ packages:
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     dev: true
 
-  /is-regexp@1.0.0:
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-    engines: {node: '>=0.10.0'}
-    dev: true
-
-  /is-relative-path@1.0.2:
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-    dev: true
-
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     dev: true
@@ -10737,15 +10400,6 @@ packages:
     engines: {node: '>=10'}
     dev: true
 
-  /is-url-superb@4.0.0:
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-    engines: {node: '>=10'}
-    dev: true
-
-  /is-url@1.2.4:
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-    dev: true
-
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     dev: true
@@ -11278,43 +10932,6 @@ packages:
       yallist: 4.0.0
     dev: true
 
-  /madge@6.1.0(typescript@5.3.3):
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-    engines: {node: '>=14'}
-    hasBin: true
-    peerDependencies:
-      typescript: ^3.9.5 || ^4.9.5 || ^5
-    peerDependenciesMeta:
-      typescript:
-        optional: true
-    dependencies:
-      chalk: 4.1.2
-      commander: 7.2.0
-      commondir: 1.0.1
-      debug: 4.3.4
-      dependency-tree: 9.0.0
-      detective-amd: 4.2.0
-      detective-cjs: 4.1.0
-      detective-es6: 3.0.1
-      detective-less: 1.0.2
-      detective-postcss: 6.1.3
-      detective-sass: 4.1.3
-      detective-scss: 3.1.1
-      detective-stylus: 2.0.1
-      detective-typescript: 9.1.1
-      ora: 5.4.1
-      pluralize: 8.0.0
-      precinct: 8.3.1
-      pretty-ms: 7.0.1
-      rc: 1.2.8
-      stream-to-array: 2.3.0
-      ts-graphviz: 1.8.2
-      typescript: 5.3.3
-      walkdir: 0.4.1
-    transitivePeerDependencies:
-      - supports-color
-    dev: true
-
   /magic-string@0.16.0:
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     dependencies:
@@ -11571,38 +11188,6 @@ packages:
       ufo: 1.4.0
     dev: true
 
-  /module-definition@3.4.0:
-    resolution: {integrity: sha512-XxJ88R1v458pifaSkPNLUTdSPNVGMP2SXVncVmApGO+gAfrLANiYe6JofymCzVceGOMwQE2xogxBSc8uB7XegA==}
-    engines: {node: '>=6.0'}
-    hasBin: true
-    dependencies:
-      ast-module-types: 3.0.0
-      node-source-walk: 4.3.0
-    dev: true
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     resolution: {integrity: sha512-uNaeirEPvpZWSgzwsPGtU2zVSTrn/8L5q/IexZmH0eH6SA73CmAA5U4GwORTxQAZs95TAXLNqeLoPPNO5gZfWg==}
     engines: {node: '>=8'}
@@ -14836,11 +14208,6 @@ packages:
       typescript: 5.3.3
     dev: true
 
-  /walkdir@0.4.1:
-    resolution: {integrity: sha512-3eBwRyEln6E1MSzcxcVpQIhRG8Q1jLvEqRmCZqS3dsfXEDR/AhOF4d+jHg1qvDCpYaVRZjENPQyrVxAkQqxPgQ==}
-    engines: {node: '>=6.0.0'}
-    dev: true
-
   /walker@1.0.8:
     resolution: {integrity: sha512-ts/8E8l5b7kY0vlWLewOkDXMmPdLcVV4GmOQLyxuSswIJsweeFZtAsMF7k1Nszz+TYBQrlYRmzOnr398y1JemQ==}
     dependencies:

From 9cf2897064042fd695e893103517a43d153cc13c Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 27 Feb 2024 19:18:01 +1100
Subject: [PATCH 355/411] ci: change frontend check to dpdm

---
 .github/workflows/lint-frontend.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/lint-frontend.yml b/.github/workflows/lint-frontend.yml
index 96167bbeca..e794892933 100644
--- a/.github/workflows/lint-frontend.yml
+++ b/.github/workflows/lint-frontend.yml
@@ -36,7 +36,7 @@ jobs:
       - name: Typescript
         run: 'pnpm run lint:tsc'
       - name: Madge
-        run: 'pnpm run lint:madge'
+        run: 'pnpm run lint:dpdm'
       - name: ESLint
         run: 'pnpm run lint:eslint'
       - name: Prettier

From 3141c6efd52db76073f252fa790e646b3a92ebf4 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Tue, 27 Feb 2024 19:26:36 +1100
Subject: [PATCH 356/411] chore(ui): bump deps

The only major version is `query-string`. The breaking change for it is dropping support for old versions of node. Not a problem for us.
---
 invokeai/frontend/web/package.json   |   22 +-
 invokeai/frontend/web/pnpm-lock.yaml | 1332 +++++++++++++++-----------
 2 files changed, 788 insertions(+), 566 deletions(-)

diff --git a/invokeai/frontend/web/package.json b/invokeai/frontend/web/package.json
index c02e9fecca..a413604ea3 100644
--- a/invokeai/frontend/web/package.json
+++ b/invokeai/frontend/web/package.json
@@ -64,9 +64,9 @@
     "chakra-react-select": "^4.7.6",
     "compare-versions": "^6.1.0",
     "dateformat": "^5.0.3",
-    "framer-motion": "^11.0.5",
-    "i18next": "^23.9.0",
-    "i18next-http-backend": "^2.4.3",
+    "framer-motion": "^11.0.6",
+    "i18next": "^23.10.0",
+    "i18next-http-backend": "^2.5.0",
     "idb-keyval": "^6.2.1",
     "jsondiffpatch": "^0.6.0",
     "konva": "^9.3.3",
@@ -75,7 +75,7 @@
     "new-github-issue-url": "^1.0.0",
     "overlayscrollbars": "^2.5.0",
     "overlayscrollbars-react": "^0.5.4",
-    "query-string": "^8.2.0",
+    "query-string": "^9.0.0",
     "react": "^18.2.0",
     "react-colorful": "^5.6.1",
     "react-dom": "^18.2.0",
@@ -87,10 +87,10 @@
     "react-icons": "^5.0.1",
     "react-konva": "^18.2.10",
     "react-redux": "9.1.0",
-    "react-resizable-panels": "^2.0.9",
+    "react-resizable-panels": "^2.0.11",
     "react-select": "5.8.0",
     "react-use": "^17.5.0",
-    "react-virtuoso": "^4.7.0",
+    "react-virtuoso": "^4.7.1",
     "reactflow": "^11.10.4",
     "redux-dynamic-middlewares": "^2.2.0",
     "redux-remember": "^5.1.0",
@@ -122,14 +122,14 @@
     "@storybook/theming": "^7.6.17",
     "@types/dateformat": "^5.0.2",
     "@types/lodash-es": "^4.17.12",
-    "@types/node": "^20.11.19",
-    "@types/react": "^18.2.57",
+    "@types/node": "^20.11.20",
+    "@types/react": "^18.2.59",
     "@types/react-dom": "^18.2.19",
     "@types/uuid": "^9.0.8",
     "@vitejs/plugin-react-swc": "^3.6.0",
     "concurrently": "^8.2.2",
     "dpdm": "^3.14.0",
-    "eslint": "^8.56.0",
+    "eslint": "^8.57.0",
     "eslint-plugin-i18next": "^6.0.3",
     "eslint-plugin-path": "^1.2.4",
     "knip": "^5.0.2",
@@ -141,9 +141,9 @@
     "ts-toolbelt": "^9.6.0",
     "tsafe": "^1.6.6",
     "typescript": "^5.3.3",
-    "vite": "^5.1.3",
+    "vite": "^5.1.4",
     "vite-plugin-css-injected-by-js": "^3.4.0",
-    "vite-plugin-dts": "^3.7.2",
+    "vite-plugin-dts": "^3.7.3",
     "vite-plugin-eslint": "^1.8.1",
     "vite-tsconfig-paths": "^4.3.1",
     "vitest": "^1.3.1"
diff --git a/invokeai/frontend/web/pnpm-lock.yaml b/invokeai/frontend/web/pnpm-lock.yaml
index b023409c55..e1a1e4b741 100644
--- a/invokeai/frontend/web/pnpm-lock.yaml
+++ b/invokeai/frontend/web/pnpm-lock.yaml
@@ -28,7 +28,7 @@ dependencies:
     version: 5.0.16
   '@invoke-ai/ui-library':
     specifier: ^0.0.21
-    version: 0.0.21(@chakra-ui/form-control@2.2.0)(@chakra-ui/icon@3.2.0)(@chakra-ui/media-query@3.3.0)(@chakra-ui/menu@2.2.1)(@chakra-ui/spinner@2.1.0)(@chakra-ui/system@2.6.2)(@fontsource-variable/inter@5.0.16)(@internationalized/date@3.5.2)(@types/react@18.2.57)(i18next@23.9.0)(react-dom@18.2.0)(react@18.2.0)
+    version: 0.0.21(@chakra-ui/form-control@2.2.0)(@chakra-ui/icon@3.2.0)(@chakra-ui/media-query@3.3.0)(@chakra-ui/menu@2.2.1)(@chakra-ui/spinner@2.1.0)(@chakra-ui/system@2.6.2)(@fontsource-variable/inter@5.0.16)(@internationalized/date@3.5.2)(@types/react@18.2.59)(i18next@23.10.0)(react-dom@18.2.0)(react@18.2.0)
   '@nanostores/react':
     specifier: ^0.7.2
     version: 0.7.2(nanostores@0.10.0)(react@18.2.0)
@@ -40,7 +40,7 @@ dependencies:
     version: 1.3.0
   chakra-react-select:
     specifier: ^4.7.6
-    version: 4.7.6(@chakra-ui/form-control@2.2.0)(@chakra-ui/icon@3.2.0)(@chakra-ui/layout@2.3.1)(@chakra-ui/media-query@3.3.0)(@chakra-ui/menu@2.2.1)(@chakra-ui/spinner@2.1.0)(@chakra-ui/system@2.6.2)(@emotion/react@11.11.3)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+    version: 4.7.6(@chakra-ui/form-control@2.2.0)(@chakra-ui/icon@3.2.0)(@chakra-ui/layout@2.3.1)(@chakra-ui/media-query@3.3.0)(@chakra-ui/menu@2.2.1)(@chakra-ui/spinner@2.1.0)(@chakra-ui/system@2.6.2)(@emotion/react@11.11.3)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
   compare-versions:
     specifier: ^6.1.0
     version: 6.1.0
@@ -48,14 +48,14 @@ dependencies:
     specifier: ^5.0.3
     version: 5.0.3
   framer-motion:
-    specifier: ^11.0.5
-    version: 11.0.5(react-dom@18.2.0)(react@18.2.0)
+    specifier: ^11.0.6
+    version: 11.0.6(react-dom@18.2.0)(react@18.2.0)
   i18next:
-    specifier: ^23.9.0
-    version: 23.9.0
+    specifier: ^23.10.0
+    version: 23.10.0
   i18next-http-backend:
-    specifier: ^2.4.3
-    version: 2.4.3
+    specifier: ^2.5.0
+    version: 2.5.0
   idb-keyval:
     specifier: ^6.2.1
     version: 6.2.1
@@ -81,8 +81,8 @@ dependencies:
     specifier: ^0.5.4
     version: 0.5.4(overlayscrollbars@2.5.0)(react@18.2.0)
   query-string:
-    specifier: ^8.2.0
-    version: 8.2.0
+    specifier: ^9.0.0
+    version: 9.0.0
   react:
     specifier: ^18.2.0
     version: 18.2.0
@@ -106,7 +106,7 @@ dependencies:
     version: 4.5.0(react-dom@18.2.0)(react@18.2.0)
   react-i18next:
     specifier: ^14.0.5
-    version: 14.0.5(i18next@23.9.0)(react-dom@18.2.0)(react@18.2.0)
+    version: 14.0.5(i18next@23.10.0)(react-dom@18.2.0)(react@18.2.0)
   react-icons:
     specifier: ^5.0.1
     version: 5.0.1(react@18.2.0)
@@ -115,22 +115,22 @@ dependencies:
     version: 18.2.10(konva@9.3.3)(react-dom@18.2.0)(react@18.2.0)
   react-redux:
     specifier: 9.1.0
-    version: 9.1.0(@types/react@18.2.57)(react@18.2.0)(redux@5.0.1)
+    version: 9.1.0(@types/react@18.2.59)(react@18.2.0)(redux@5.0.1)
   react-resizable-panels:
-    specifier: ^2.0.9
-    version: 2.0.9(react-dom@18.2.0)(react@18.2.0)
+    specifier: ^2.0.11
+    version: 2.0.11(react-dom@18.2.0)(react@18.2.0)
   react-select:
     specifier: 5.8.0
-    version: 5.8.0(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+    version: 5.8.0(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
   react-use:
     specifier: ^17.5.0
     version: 17.5.0(react-dom@18.2.0)(react@18.2.0)
   react-virtuoso:
-    specifier: ^4.7.0
-    version: 4.7.0(react-dom@18.2.0)(react@18.2.0)
+    specifier: ^4.7.1
+    version: 4.7.1(react-dom@18.2.0)(react@18.2.0)
   reactflow:
     specifier: ^11.10.4
-    version: 11.10.4(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+    version: 11.10.4(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
   redux-dynamic-middlewares:
     specifier: ^2.2.0
     version: 2.2.0
@@ -165,13 +165,13 @@ dependencies:
 devDependencies:
   '@invoke-ai/eslint-config-react':
     specifier: ^0.0.14
-    version: 0.0.14(eslint@8.56.0)(prettier@3.2.5)(typescript@5.3.3)
+    version: 0.0.14(eslint@8.57.0)(prettier@3.2.5)(typescript@5.3.3)
   '@invoke-ai/prettier-config-react':
     specifier: ^0.0.7
     version: 0.0.7(prettier@3.2.5)
   '@storybook/addon-essentials':
     specifier: ^7.6.17
-    version: 7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+    version: 7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
   '@storybook/addon-interactions':
     specifier: ^7.6.17
     version: 7.6.17
@@ -189,7 +189,7 @@ devDependencies:
     version: 7.6.17(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)
   '@storybook/react-vite':
     specifier: ^7.6.17
-    version: 7.6.17(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)(vite@5.1.3)
+    version: 7.6.17(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)(vite@5.1.4)
   '@storybook/theming':
     specifier: ^7.6.17
     version: 7.6.17(react-dom@18.2.0)(react@18.2.0)
@@ -200,11 +200,11 @@ devDependencies:
     specifier: ^4.17.12
     version: 4.17.12
   '@types/node':
-    specifier: ^20.11.19
-    version: 20.11.19
+    specifier: ^20.11.20
+    version: 20.11.20
   '@types/react':
-    specifier: ^18.2.57
-    version: 18.2.57
+    specifier: ^18.2.59
+    version: 18.2.59
   '@types/react-dom':
     specifier: ^18.2.19
     version: 18.2.19
@@ -213,7 +213,7 @@ devDependencies:
     version: 9.0.8
   '@vitejs/plugin-react-swc':
     specifier: ^3.6.0
-    version: 3.6.0(vite@5.1.3)
+    version: 3.6.0(vite@5.1.4)
   concurrently:
     specifier: ^8.2.2
     version: 8.2.2
@@ -221,17 +221,17 @@ devDependencies:
     specifier: ^3.14.0
     version: 3.14.0
   eslint:
-    specifier: ^8.56.0
-    version: 8.56.0
+    specifier: ^8.57.0
+    version: 8.57.0
   eslint-plugin-i18next:
     specifier: ^6.0.3
     version: 6.0.3
   eslint-plugin-path:
     specifier: ^1.2.4
-    version: 1.2.4(eslint@8.56.0)
+    version: 1.2.4(eslint@8.57.0)
   knip:
     specifier: ^5.0.2
-    version: 5.0.2(@types/node@20.11.19)(typescript@5.3.3)
+    version: 5.0.2(@types/node@20.11.20)(typescript@5.3.3)
   openapi-types:
     specifier: ^12.1.3
     version: 12.1.3
@@ -257,23 +257,23 @@ devDependencies:
     specifier: ^5.3.3
     version: 5.3.3
   vite:
-    specifier: ^5.1.3
-    version: 5.1.3(@types/node@20.11.19)
+    specifier: ^5.1.4
+    version: 5.1.4(@types/node@20.11.20)
   vite-plugin-css-injected-by-js:
     specifier: ^3.4.0
-    version: 3.4.0(vite@5.1.3)
+    version: 3.4.0(vite@5.1.4)
   vite-plugin-dts:
-    specifier: ^3.7.2
-    version: 3.7.2(@types/node@20.11.19)(typescript@5.3.3)(vite@5.1.3)
+    specifier: ^3.7.3
+    version: 3.7.3(@types/node@20.11.20)(typescript@5.3.3)(vite@5.1.4)
   vite-plugin-eslint:
     specifier: ^1.8.1
-    version: 1.8.1(eslint@8.56.0)(vite@5.1.3)
+    version: 1.8.1(eslint@8.57.0)(vite@5.1.4)
   vite-tsconfig-paths:
     specifier: ^4.3.1
-    version: 4.3.1(typescript@5.3.3)(vite@5.1.3)
+    version: 4.3.1(typescript@5.3.3)(vite@5.1.4)
   vitest:
     specifier: ^1.3.1
-    version: 1.3.1(@types/node@20.11.19)
+    version: 1.3.1(@types/node@20.11.20)
 
 packages:
 
@@ -286,8 +286,8 @@ packages:
     resolution: {integrity: sha512-lFMjJTrFL3j7L9yBxwYfCq2k6qqwHyzuUl/XBnif78PWTJYyL/dfowQHWE3sp6U6ZzqWiiIZnpTMO96zhkjwtg==}
     engines: {node: '>=6.0.0'}
     dependencies:
-      '@jridgewell/gen-mapping': 0.3.3
-      '@jridgewell/trace-mapping': 0.3.22
+      '@jridgewell/gen-mapping': 0.3.4
+      '@jridgewell/trace-mapping': 0.3.23
     dev: true
 
   /@ark-ui/anatomy@1.3.0(@internationalized/date@3.5.2):
@@ -423,8 +423,8 @@ packages:
     engines: {node: '>=6.9.0'}
     dependencies:
       '@babel/types': 7.23.9
-      '@jridgewell/gen-mapping': 0.3.3
-      '@jridgewell/trace-mapping': 0.3.22
+      '@jridgewell/gen-mapping': 0.3.4
+      '@jridgewell/trace-mapping': 0.3.23
       jsesc: 2.5.2
     dev: true
 
@@ -1851,7 +1851,7 @@ packages:
       '@emotion/react': '>=10.0.35'
       react: '>=18'
     dependencies:
-      '@emotion/react': 11.11.3(@types/react@18.2.57)(react@18.2.0)
+      '@emotion/react': 11.11.3(@types/react@18.2.59)(react@18.2.0)
       react: 18.2.0
     dev: false
 
@@ -1904,6 +1904,18 @@ packages:
       - '@types/react'
     dev: false
 
+  /@chakra-ui/focus-lock@2.1.0(@types/react@18.2.59)(react@18.2.0):
+    resolution: {integrity: sha512-EmGx4PhWGjm4dpjRqM4Aa+rCWBxP+Rq8Uc/nAVnD4YVqkEhBkrPTpui2lnjsuxqNaZ24fIAZ10cF1hlpemte/w==}
+    peerDependencies:
+      react: '>=18'
+    dependencies:
+      '@chakra-ui/dom-utils': 2.1.0
+      react: 18.2.0
+      react-focus-lock: 2.11.1(@types/react@18.2.59)(react@18.2.0)
+    transitivePeerDependencies:
+      - '@types/react'
+    dev: false
+
   /@chakra-ui/form-control@2.2.0(@chakra-ui/system@2.6.2)(react@18.2.0):
     resolution: {integrity: sha512-wehLC1t4fafCVJ2RvJQT2jyqsAwX7KymmiGqBu7nQoQz8ApTkGABWpo/QwDh3F/dBLrouHDoOvGmYTqft3Mirw==}
     peerDependencies:
@@ -2075,30 +2087,31 @@ packages:
       react: 18.2.0
     dev: false
 
-  /@chakra-ui/modal@2.3.1(@chakra-ui/system@2.6.2)(@types/react@18.2.57)(framer-motion@10.18.0)(react-dom@18.2.0)(react@18.2.0):
-    resolution: {integrity: sha512-TQv1ZaiJMZN+rR9DK0snx/OPwmtaGH1HbZtlYt4W4s6CzyK541fxLRTjIXfEzIGpvNW+b6VFuFjbcR78p4DEoQ==}
+  /@chakra-ui/menu@2.2.1(@chakra-ui/system@2.6.2)(framer-motion@11.0.6)(react@18.2.0):
+    resolution: {integrity: sha512-lJS7XEObzJxsOwWQh7yfG4H8FzFPRP5hVPN/CL+JzytEINCSBvsCDHrYPQGp7jzpCi8vnTqQQGQe0f8dwnXd2g==}
     peerDependencies:
       '@chakra-ui/system': '>=2.0.0'
       framer-motion: '>=4.0.0'
       react: '>=18'
-      react-dom: '>=18'
     dependencies:
-      '@chakra-ui/close-button': 2.1.1(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/focus-lock': 2.1.0(@types/react@18.2.57)(react@18.2.0)
-      '@chakra-ui/portal': 2.1.0(react-dom@18.2.0)(react@18.2.0)
+      '@chakra-ui/clickable': 2.1.0(react@18.2.0)
+      '@chakra-ui/descendant': 3.1.0(react@18.2.0)
+      '@chakra-ui/lazy-utils': 2.0.5
+      '@chakra-ui/popper': 3.1.0(react@18.2.0)
+      '@chakra-ui/react-children-utils': 2.0.6(react@18.2.0)
       '@chakra-ui/react-context': 2.1.0(react@18.2.0)
-      '@chakra-ui/react-types': 2.0.7(react@18.2.0)
+      '@chakra-ui/react-use-animation-state': 2.1.0(react@18.2.0)
+      '@chakra-ui/react-use-controllable-state': 2.1.0(react@18.2.0)
+      '@chakra-ui/react-use-disclosure': 2.1.0(react@18.2.0)
+      '@chakra-ui/react-use-focus-effect': 2.1.0(react@18.2.0)
       '@chakra-ui/react-use-merge-refs': 2.1.0(react@18.2.0)
+      '@chakra-ui/react-use-outside-click': 2.2.0(react@18.2.0)
+      '@chakra-ui/react-use-update-effect': 2.1.0(react@18.2.0)
       '@chakra-ui/shared-utils': 2.0.5
       '@chakra-ui/system': 2.6.2(@emotion/react@11.11.3)(@emotion/styled@11.11.0)(react@18.2.0)
-      '@chakra-ui/transition': 2.1.0(framer-motion@10.18.0)(react@18.2.0)
-      aria-hidden: 1.2.3
-      framer-motion: 10.18.0(react-dom@18.2.0)(react@18.2.0)
+      '@chakra-ui/transition': 2.1.0(framer-motion@11.0.6)(react@18.2.0)
+      framer-motion: 11.0.6(react-dom@18.2.0)(react@18.2.0)
       react: 18.2.0
-      react-dom: 18.2.0(react@18.2.0)
-      react-remove-scroll: 2.5.7(@types/react@18.2.57)(react@18.2.0)
-    transitivePeerDependencies:
-      - '@types/react'
     dev: false
 
   /@chakra-ui/modal@2.3.1(@chakra-ui/system@2.6.2)(@types/react@18.2.57)(framer-motion@11.0.5)(react-dom@18.2.0)(react@18.2.0):
@@ -2127,6 +2140,32 @@ packages:
       - '@types/react'
     dev: false
 
+  /@chakra-ui/modal@2.3.1(@chakra-ui/system@2.6.2)(@types/react@18.2.59)(framer-motion@10.18.0)(react-dom@18.2.0)(react@18.2.0):
+    resolution: {integrity: sha512-TQv1ZaiJMZN+rR9DK0snx/OPwmtaGH1HbZtlYt4W4s6CzyK541fxLRTjIXfEzIGpvNW+b6VFuFjbcR78p4DEoQ==}
+    peerDependencies:
+      '@chakra-ui/system': '>=2.0.0'
+      framer-motion: '>=4.0.0'
+      react: '>=18'
+      react-dom: '>=18'
+    dependencies:
+      '@chakra-ui/close-button': 2.1.1(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/focus-lock': 2.1.0(@types/react@18.2.59)(react@18.2.0)
+      '@chakra-ui/portal': 2.1.0(react-dom@18.2.0)(react@18.2.0)
+      '@chakra-ui/react-context': 2.1.0(react@18.2.0)
+      '@chakra-ui/react-types': 2.0.7(react@18.2.0)
+      '@chakra-ui/react-use-merge-refs': 2.1.0(react@18.2.0)
+      '@chakra-ui/shared-utils': 2.0.5
+      '@chakra-ui/system': 2.6.2(@emotion/react@11.11.3)(@emotion/styled@11.11.0)(react@18.2.0)
+      '@chakra-ui/transition': 2.1.0(framer-motion@10.18.0)(react@18.2.0)
+      aria-hidden: 1.2.3
+      framer-motion: 10.18.0(react-dom@18.2.0)(react@18.2.0)
+      react: 18.2.0
+      react-dom: 18.2.0(react@18.2.0)
+      react-remove-scroll: 2.5.7(@types/react@18.2.59)(react@18.2.0)
+    transitivePeerDependencies:
+      - '@types/react'
+    dev: false
+
   /@chakra-ui/number-input@2.1.2(@chakra-ui/system@2.6.2)(react@18.2.0):
     resolution: {integrity: sha512-pfOdX02sqUN0qC2ysuvgVDiws7xZ20XDIlcNhva55Jgm095xjm8eVdIBfNm3SFbSUNxyXvLTW/YQanX74tKmuA==}
     peerDependencies:
@@ -2266,8 +2305,8 @@ packages:
       '@chakra-ui/react-env': 3.1.0(react@18.2.0)
       '@chakra-ui/system': 2.6.2(@emotion/react@11.11.3)(@emotion/styled@11.11.0)(react@18.2.0)
       '@chakra-ui/utils': 2.0.15
-      '@emotion/react': 11.11.3(@types/react@18.2.57)(react@18.2.0)
-      '@emotion/styled': 11.11.0(@emotion/react@11.11.3)(@types/react@18.2.57)(react@18.2.0)
+      '@emotion/react': 11.11.3(@types/react@18.2.59)(react@18.2.0)
+      '@emotion/styled': 11.11.0(@emotion/react@11.11.3)(@types/react@18.2.59)(react@18.2.0)
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     dev: false
@@ -2483,77 +2522,6 @@ packages:
       react: 18.2.0
     dev: false
 
-  /@chakra-ui/react@2.8.2(@emotion/react@11.11.3)(@emotion/styled@11.11.0)(@types/react@18.2.57)(framer-motion@10.18.0)(react-dom@18.2.0)(react@18.2.0):
-    resolution: {integrity: sha512-Hn0moyxxyCDKuR9ywYpqgX8dvjqwu9ArwpIb9wHNYjnODETjLwazgNIliCVBRcJvysGRiV51U2/JtJVrpeCjUQ==}
-    peerDependencies:
-      '@emotion/react': ^11.0.0
-      '@emotion/styled': ^11.0.0
-      framer-motion: '>=4.0.0'
-      react: '>=18'
-      react-dom: '>=18'
-    dependencies:
-      '@chakra-ui/accordion': 2.3.1(@chakra-ui/system@2.6.2)(framer-motion@10.18.0)(react@18.2.0)
-      '@chakra-ui/alert': 2.2.2(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/avatar': 2.3.0(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/breadcrumb': 2.2.0(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/button': 2.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/card': 2.2.0(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/checkbox': 2.3.2(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/close-button': 2.1.1(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/control-box': 2.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/counter': 2.1.0(react@18.2.0)
-      '@chakra-ui/css-reset': 2.3.0(@emotion/react@11.11.3)(react@18.2.0)
-      '@chakra-ui/editable': 3.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/focus-lock': 2.1.0(@types/react@18.2.57)(react@18.2.0)
-      '@chakra-ui/form-control': 2.2.0(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/hooks': 2.2.1(react@18.2.0)
-      '@chakra-ui/icon': 3.2.0(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/image': 2.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/input': 2.1.2(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/layout': 2.3.1(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/live-region': 2.1.0(react@18.2.0)
-      '@chakra-ui/media-query': 3.3.0(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/menu': 2.2.1(@chakra-ui/system@2.6.2)(framer-motion@10.18.0)(react@18.2.0)
-      '@chakra-ui/modal': 2.3.1(@chakra-ui/system@2.6.2)(@types/react@18.2.57)(framer-motion@10.18.0)(react-dom@18.2.0)(react@18.2.0)
-      '@chakra-ui/number-input': 2.1.2(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/pin-input': 2.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/popover': 2.2.1(@chakra-ui/system@2.6.2)(framer-motion@10.18.0)(react@18.2.0)
-      '@chakra-ui/popper': 3.1.0(react@18.2.0)
-      '@chakra-ui/portal': 2.1.0(react-dom@18.2.0)(react@18.2.0)
-      '@chakra-ui/progress': 2.2.0(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/provider': 2.4.2(@emotion/react@11.11.3)(@emotion/styled@11.11.0)(react-dom@18.2.0)(react@18.2.0)
-      '@chakra-ui/radio': 2.1.2(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/react-env': 3.1.0(react@18.2.0)
-      '@chakra-ui/select': 2.1.2(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/skeleton': 2.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/skip-nav': 2.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/slider': 2.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/spinner': 2.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/stat': 2.1.1(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/stepper': 2.3.1(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/styled-system': 2.9.2
-      '@chakra-ui/switch': 2.1.2(@chakra-ui/system@2.6.2)(framer-motion@10.18.0)(react@18.2.0)
-      '@chakra-ui/system': 2.6.2(@emotion/react@11.11.3)(@emotion/styled@11.11.0)(react@18.2.0)
-      '@chakra-ui/table': 2.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/tabs': 3.0.0(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/tag': 3.1.1(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/textarea': 2.1.2(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/theme': 3.3.1(@chakra-ui/styled-system@2.9.2)
-      '@chakra-ui/theme-utils': 2.0.21
-      '@chakra-ui/toast': 7.0.2(@chakra-ui/system@2.6.2)(framer-motion@10.18.0)(react-dom@18.2.0)(react@18.2.0)
-      '@chakra-ui/tooltip': 2.3.1(@chakra-ui/system@2.6.2)(framer-motion@10.18.0)(react-dom@18.2.0)(react@18.2.0)
-      '@chakra-ui/transition': 2.1.0(framer-motion@10.18.0)(react@18.2.0)
-      '@chakra-ui/utils': 2.0.15
-      '@chakra-ui/visually-hidden': 2.2.0(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@emotion/react': 11.11.3(@types/react@18.2.57)(react@18.2.0)
-      '@emotion/styled': 11.11.0(@emotion/react@11.11.3)(@types/react@18.2.57)(react@18.2.0)
-      framer-motion: 10.18.0(react-dom@18.2.0)(react@18.2.0)
-      react: 18.2.0
-      react-dom: 18.2.0(react@18.2.0)
-    transitivePeerDependencies:
-      - '@types/react'
-    dev: false
-
   /@chakra-ui/react@2.8.2(@emotion/react@11.11.3)(@emotion/styled@11.11.0)(@types/react@18.2.57)(framer-motion@11.0.5)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-Hn0moyxxyCDKuR9ywYpqgX8dvjqwu9ArwpIb9wHNYjnODETjLwazgNIliCVBRcJvysGRiV51U2/JtJVrpeCjUQ==}
     peerDependencies:
@@ -2625,6 +2593,77 @@ packages:
       - '@types/react'
     dev: false
 
+  /@chakra-ui/react@2.8.2(@emotion/react@11.11.3)(@emotion/styled@11.11.0)(@types/react@18.2.59)(framer-motion@10.18.0)(react-dom@18.2.0)(react@18.2.0):
+    resolution: {integrity: sha512-Hn0moyxxyCDKuR9ywYpqgX8dvjqwu9ArwpIb9wHNYjnODETjLwazgNIliCVBRcJvysGRiV51U2/JtJVrpeCjUQ==}
+    peerDependencies:
+      '@emotion/react': ^11.0.0
+      '@emotion/styled': ^11.0.0
+      framer-motion: '>=4.0.0'
+      react: '>=18'
+      react-dom: '>=18'
+    dependencies:
+      '@chakra-ui/accordion': 2.3.1(@chakra-ui/system@2.6.2)(framer-motion@10.18.0)(react@18.2.0)
+      '@chakra-ui/alert': 2.2.2(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/avatar': 2.3.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/breadcrumb': 2.2.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/button': 2.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/card': 2.2.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/checkbox': 2.3.2(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/close-button': 2.1.1(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/control-box': 2.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/counter': 2.1.0(react@18.2.0)
+      '@chakra-ui/css-reset': 2.3.0(@emotion/react@11.11.3)(react@18.2.0)
+      '@chakra-ui/editable': 3.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/focus-lock': 2.1.0(@types/react@18.2.59)(react@18.2.0)
+      '@chakra-ui/form-control': 2.2.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/hooks': 2.2.1(react@18.2.0)
+      '@chakra-ui/icon': 3.2.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/image': 2.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/input': 2.1.2(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/layout': 2.3.1(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/live-region': 2.1.0(react@18.2.0)
+      '@chakra-ui/media-query': 3.3.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/menu': 2.2.1(@chakra-ui/system@2.6.2)(framer-motion@10.18.0)(react@18.2.0)
+      '@chakra-ui/modal': 2.3.1(@chakra-ui/system@2.6.2)(@types/react@18.2.59)(framer-motion@10.18.0)(react-dom@18.2.0)(react@18.2.0)
+      '@chakra-ui/number-input': 2.1.2(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/pin-input': 2.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/popover': 2.2.1(@chakra-ui/system@2.6.2)(framer-motion@10.18.0)(react@18.2.0)
+      '@chakra-ui/popper': 3.1.0(react@18.2.0)
+      '@chakra-ui/portal': 2.1.0(react-dom@18.2.0)(react@18.2.0)
+      '@chakra-ui/progress': 2.2.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/provider': 2.4.2(@emotion/react@11.11.3)(@emotion/styled@11.11.0)(react-dom@18.2.0)(react@18.2.0)
+      '@chakra-ui/radio': 2.1.2(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/react-env': 3.1.0(react@18.2.0)
+      '@chakra-ui/select': 2.1.2(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/skeleton': 2.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/skip-nav': 2.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/slider': 2.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/spinner': 2.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/stat': 2.1.1(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/stepper': 2.3.1(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/styled-system': 2.9.2
+      '@chakra-ui/switch': 2.1.2(@chakra-ui/system@2.6.2)(framer-motion@10.18.0)(react@18.2.0)
+      '@chakra-ui/system': 2.6.2(@emotion/react@11.11.3)(@emotion/styled@11.11.0)(react@18.2.0)
+      '@chakra-ui/table': 2.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/tabs': 3.0.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/tag': 3.1.1(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/textarea': 2.1.2(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@chakra-ui/theme': 3.3.1(@chakra-ui/styled-system@2.9.2)
+      '@chakra-ui/theme-utils': 2.0.21
+      '@chakra-ui/toast': 7.0.2(@chakra-ui/system@2.6.2)(framer-motion@10.18.0)(react-dom@18.2.0)(react@18.2.0)
+      '@chakra-ui/tooltip': 2.3.1(@chakra-ui/system@2.6.2)(framer-motion@10.18.0)(react-dom@18.2.0)(react@18.2.0)
+      '@chakra-ui/transition': 2.1.0(framer-motion@10.18.0)(react@18.2.0)
+      '@chakra-ui/utils': 2.0.15
+      '@chakra-ui/visually-hidden': 2.2.0(@chakra-ui/system@2.6.2)(react@18.2.0)
+      '@emotion/react': 11.11.3(@types/react@18.2.59)(react@18.2.0)
+      '@emotion/styled': 11.11.0(@emotion/react@11.11.3)(@types/react@18.2.59)(react@18.2.0)
+      framer-motion: 10.18.0(react-dom@18.2.0)(react@18.2.0)
+      react: 18.2.0
+      react-dom: 18.2.0(react@18.2.0)
+    transitivePeerDependencies:
+      - '@types/react'
+    dev: false
+
   /@chakra-ui/select@2.1.2(@chakra-ui/system@2.6.2)(react@18.2.0):
     resolution: {integrity: sha512-ZwCb7LqKCVLJhru3DXvKXpZ7Pbu1TDZ7N0PdQ0Zj1oyVLJyrpef1u9HR5u0amOpqcH++Ugt0f5JSmirjNlctjA==}
     peerDependencies:
@@ -2770,8 +2809,8 @@ packages:
       '@chakra-ui/styled-system': 2.9.2
       '@chakra-ui/theme-utils': 2.0.21
       '@chakra-ui/utils': 2.0.15
-      '@emotion/react': 11.11.3(@types/react@18.2.57)(react@18.2.0)
-      '@emotion/styled': 11.11.0(@emotion/react@11.11.3)(@types/react@18.2.57)(react@18.2.0)
+      '@emotion/react': 11.11.3(@types/react@18.2.59)(react@18.2.0)
+      '@emotion/styled': 11.11.0(@emotion/react@11.11.3)(@types/react@18.2.59)(react@18.2.0)
       react: 18.2.0
       react-fast-compare: 3.2.2
     dev: false
@@ -2974,6 +3013,17 @@ packages:
       react: 18.2.0
     dev: false
 
+  /@chakra-ui/transition@2.1.0(framer-motion@11.0.6)(react@18.2.0):
+    resolution: {integrity: sha512-orkT6T/Dt+/+kVwJNy7zwJ+U2xAZ3EU7M3XCs45RBvUnZDr/u9vdmaM/3D/rOpmQJWgQBwKPJleUXrYWUagEDQ==}
+    peerDependencies:
+      framer-motion: '>=4.0.0'
+      react: '>=18'
+    dependencies:
+      '@chakra-ui/shared-utils': 2.0.5
+      framer-motion: 11.0.6(react-dom@18.2.0)(react@18.2.0)
+      react: 18.2.0
+    dev: false
+
   /@chakra-ui/utils@2.0.15:
     resolution: {integrity: sha512-El4+jL0WSaYYs+rJbuYFDbjmfCcfGDmRY95GO4xwzit6YAPZBLcR65rOEwLps+XWluZTy1xdMrusg/hW0c1aAA==}
     dependencies:
@@ -3128,6 +3178,27 @@ packages:
       react: 18.2.0
     dev: false
 
+  /@emotion/react@11.11.3(@types/react@18.2.59)(react@18.2.0):
+    resolution: {integrity: sha512-Cnn0kuq4DoONOMcnoVsTOR8E+AdnKFf//6kUWc4LCdnxj31pZWn7rIULd6Y7/Js1PiPHzn7SKCM9vB/jBni8eA==}
+    peerDependencies:
+      '@types/react': '*'
+      react: '>=16.8.0'
+    peerDependenciesMeta:
+      '@types/react':
+        optional: true
+    dependencies:
+      '@babel/runtime': 7.23.9
+      '@emotion/babel-plugin': 11.11.0
+      '@emotion/cache': 11.11.0
+      '@emotion/serialize': 1.1.3
+      '@emotion/use-insertion-effect-with-fallbacks': 1.0.1(react@18.2.0)
+      '@emotion/utils': 1.2.1
+      '@emotion/weak-memoize': 0.3.1
+      '@types/react': 18.2.59
+      hoist-non-react-statics: 3.3.2
+      react: 18.2.0
+    dev: false
+
   /@emotion/serialize@1.1.3:
     resolution: {integrity: sha512-iD4D6QVZFDhcbH0RAG1uVu1CwVLMWUkCvAqqlewO/rxf8+87yIBAlt4+AxMiiKPLs5hFc0owNk/sLLAOROw3cA==}
     dependencies:
@@ -3163,6 +3234,27 @@ packages:
       react: 18.2.0
     dev: false
 
+  /@emotion/styled@11.11.0(@emotion/react@11.11.3)(@types/react@18.2.59)(react@18.2.0):
+    resolution: {integrity: sha512-hM5Nnvu9P3midq5aaXj4I+lnSfNi7Pmd4EWk1fOZ3pxookaQTNew6bp4JaCBYM4HVFZF9g7UjJmsUmC2JlxOng==}
+    peerDependencies:
+      '@emotion/react': ^11.0.0-rc.0
+      '@types/react': '*'
+      react: '>=16.8.0'
+    peerDependenciesMeta:
+      '@types/react':
+        optional: true
+    dependencies:
+      '@babel/runtime': 7.23.9
+      '@emotion/babel-plugin': 11.11.0
+      '@emotion/is-prop-valid': 1.2.1
+      '@emotion/react': 11.11.3(@types/react@18.2.59)(react@18.2.0)
+      '@emotion/serialize': 1.1.3
+      '@emotion/use-insertion-effect-with-fallbacks': 1.0.1(react@18.2.0)
+      '@emotion/utils': 1.2.1
+      '@types/react': 18.2.59
+      react: 18.2.0
+    dev: false
+
   /@emotion/unitless@0.8.1:
     resolution: {integrity: sha512-KOEGMu6dmJZtpadb476IsZBclKvILjopjUii3V+7MnXIQCYh8W3NgNcgwo21n9LXZX6EDIKvqfjYxXebDwxKmQ==}
     dev: false
@@ -3612,13 +3704,13 @@ packages:
     dev: true
     optional: true
 
-  /@eslint-community/eslint-utils@4.4.0(eslint@8.56.0):
+  /@eslint-community/eslint-utils@4.4.0(eslint@8.57.0):
     resolution: {integrity: sha512-1/sA4dwrzBAyeUoQ6oxahHKmrZvsnLCg4RfxW3ZFGGmQkSNQPFNLV9CUEFQP1x9EYXHTo5p6xdhZM1Ne9p/AfA==}
     engines: {node: ^12.22.0 || ^14.17.0 || >=16.0.0}
     peerDependencies:
       eslint: ^6.0.0 || ^7.0.0 || >=8.0.0
     dependencies:
-      eslint: 8.56.0
+      eslint: 8.57.0
       eslint-visitor-keys: 3.4.3
     dev: true
 
@@ -3644,8 +3736,8 @@ packages:
       - supports-color
     dev: true
 
-  /@eslint/js@8.56.0:
-    resolution: {integrity: sha512-gMsVel9D7f2HLkBma9VbtzZRehRogVRfbr++f06nL2vnCGCNlzOD+/MUov/F4p8myyAHspEhVobgjpX64q5m6A==}
+  /@eslint/js@8.57.0:
+    resolution: {integrity: sha512-Ys+3g2TaW7gADOJzPt83SJtCDhMjndcDMFVQ/Tj9iA1BfJzFKD9mAUXT3OenpuPHbI6P/myECxRJrofUsDx/5g==}
     engines: {node: ^12.22.0 || ^14.17.0 || >=16.0.0}
     dev: true
 
@@ -3726,24 +3818,24 @@ packages:
       '@swc/helpers': 0.5.6
     dev: false
 
-  /@invoke-ai/eslint-config-react@0.0.14(eslint@8.56.0)(prettier@3.2.5)(typescript@5.3.3):
+  /@invoke-ai/eslint-config-react@0.0.14(eslint@8.57.0)(prettier@3.2.5)(typescript@5.3.3):
     resolution: {integrity: sha512-6ZUY9zgdDhv2WUoLdDKOQdU9ImnH0CBOFtRlOaNOh34IOsNRfn+JA7wqA0PKnkiNrlfPkIQWhn4GRJp68NT5bw==}
     peerDependencies:
       eslint: ^8.56.0
       prettier: ^3.2.5
       typescript: ^5.3.3
     dependencies:
-      '@typescript-eslint/eslint-plugin': 7.0.2(@typescript-eslint/parser@7.0.2)(eslint@8.56.0)(typescript@5.3.3)
-      '@typescript-eslint/parser': 7.0.2(eslint@8.56.0)(typescript@5.3.3)
-      eslint: 8.56.0
-      eslint-config-prettier: 9.1.0(eslint@8.56.0)
-      eslint-plugin-import: 2.29.1(@typescript-eslint/parser@7.0.2)(eslint@8.56.0)
-      eslint-plugin-react: 7.33.2(eslint@8.56.0)
-      eslint-plugin-react-hooks: 4.6.0(eslint@8.56.0)
-      eslint-plugin-react-refresh: 0.4.5(eslint@8.56.0)
-      eslint-plugin-simple-import-sort: 12.0.0(eslint@8.56.0)
-      eslint-plugin-storybook: 0.8.0(eslint@8.56.0)(typescript@5.3.3)
-      eslint-plugin-unused-imports: 3.1.0(@typescript-eslint/eslint-plugin@7.0.2)(eslint@8.56.0)
+      '@typescript-eslint/eslint-plugin': 7.1.0(@typescript-eslint/parser@7.1.0)(eslint@8.57.0)(typescript@5.3.3)
+      '@typescript-eslint/parser': 7.1.0(eslint@8.57.0)(typescript@5.3.3)
+      eslint: 8.57.0
+      eslint-config-prettier: 9.1.0(eslint@8.57.0)
+      eslint-plugin-import: 2.29.1(@typescript-eslint/parser@7.1.0)(eslint@8.57.0)
+      eslint-plugin-react: 7.33.2(eslint@8.57.0)
+      eslint-plugin-react-hooks: 4.6.0(eslint@8.57.0)
+      eslint-plugin-react-refresh: 0.4.5(eslint@8.57.0)
+      eslint-plugin-simple-import-sort: 12.0.0(eslint@8.57.0)
+      eslint-plugin-storybook: 0.8.0(eslint@8.57.0)(typescript@5.3.3)
+      eslint-plugin-unused-imports: 3.1.0(@typescript-eslint/eslint-plugin@7.1.0)(eslint@8.57.0)
       prettier: 3.2.5
       typescript: 5.3.3
     transitivePeerDependencies:
@@ -3760,7 +3852,7 @@ packages:
       prettier: 3.2.5
     dev: true
 
-  /@invoke-ai/ui-library@0.0.21(@chakra-ui/form-control@2.2.0)(@chakra-ui/icon@3.2.0)(@chakra-ui/media-query@3.3.0)(@chakra-ui/menu@2.2.1)(@chakra-ui/spinner@2.1.0)(@chakra-ui/system@2.6.2)(@fontsource-variable/inter@5.0.16)(@internationalized/date@3.5.2)(@types/react@18.2.57)(i18next@23.9.0)(react-dom@18.2.0)(react@18.2.0):
+  /@invoke-ai/ui-library@0.0.21(@chakra-ui/form-control@2.2.0)(@chakra-ui/icon@3.2.0)(@chakra-ui/media-query@3.3.0)(@chakra-ui/menu@2.2.1)(@chakra-ui/spinner@2.1.0)(@chakra-ui/system@2.6.2)(@fontsource-variable/inter@5.0.16)(@internationalized/date@3.5.2)(@types/react@18.2.59)(i18next@23.10.0)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-tCvgkBPDt0gNq+8IcR03e/Mw7R8Mb/SMXTqx3FEIxlTQEo93A/D38dKXeDCzTdx4sQ+sknfB+JLBbHs6sg5hhQ==}
     peerDependencies:
       '@fontsource-variable/inter': ^5.0.16
@@ -3772,14 +3864,14 @@ packages:
       '@chakra-ui/icons': 2.1.1(@chakra-ui/system@2.6.2)(react@18.2.0)
       '@chakra-ui/layout': 2.3.1(@chakra-ui/system@2.6.2)(react@18.2.0)
       '@chakra-ui/portal': 2.1.0(react-dom@18.2.0)(react@18.2.0)
-      '@chakra-ui/react': 2.8.2(@emotion/react@11.11.3)(@emotion/styled@11.11.0)(@types/react@18.2.57)(framer-motion@10.18.0)(react-dom@18.2.0)(react@18.2.0)
+      '@chakra-ui/react': 2.8.2(@emotion/react@11.11.3)(@emotion/styled@11.11.0)(@types/react@18.2.59)(framer-motion@10.18.0)(react-dom@18.2.0)(react@18.2.0)
       '@chakra-ui/styled-system': 2.9.2
       '@chakra-ui/theme-tools': 2.1.2(@chakra-ui/styled-system@2.9.2)
-      '@emotion/react': 11.11.3(@types/react@18.2.57)(react@18.2.0)
-      '@emotion/styled': 11.11.0(@emotion/react@11.11.3)(@types/react@18.2.57)(react@18.2.0)
+      '@emotion/react': 11.11.3(@types/react@18.2.59)(react@18.2.0)
+      '@emotion/styled': 11.11.0(@emotion/react@11.11.3)(@types/react@18.2.59)(react@18.2.0)
       '@fontsource-variable/inter': 5.0.16
       '@nanostores/react': 0.7.2(nanostores@0.9.5)(react@18.2.0)
-      chakra-react-select: 4.7.6(@chakra-ui/form-control@2.2.0)(@chakra-ui/icon@3.2.0)(@chakra-ui/layout@2.3.1)(@chakra-ui/media-query@3.3.0)(@chakra-ui/menu@2.2.1)(@chakra-ui/spinner@2.1.0)(@chakra-ui/system@2.6.2)(@emotion/react@11.11.3)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      chakra-react-select: 4.7.6(@chakra-ui/form-control@2.2.0)(@chakra-ui/icon@3.2.0)(@chakra-ui/layout@2.3.1)(@chakra-ui/media-query@3.3.0)(@chakra-ui/menu@2.2.1)(@chakra-ui/spinner@2.1.0)(@chakra-ui/system@2.6.2)(@emotion/react@11.11.3)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
       framer-motion: 10.18.0(react-dom@18.2.0)(react@18.2.0)
       lodash-es: 4.17.21
       nanostores: 0.9.5
@@ -3787,9 +3879,9 @@ packages:
       overlayscrollbars-react: 0.5.4(overlayscrollbars@2.5.0)(react@18.2.0)
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
-      react-i18next: 14.0.5(i18next@23.9.0)(react-dom@18.2.0)(react@18.2.0)
+      react-i18next: 14.0.5(i18next@23.10.0)(react-dom@18.2.0)(react@18.2.0)
       react-icons: 5.0.1(react@18.2.0)
-      react-select: 5.8.0(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      react-select: 5.8.0(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
     transitivePeerDependencies:
       - '@chakra-ui/form-control'
       - '@chakra-ui/icon'
@@ -3844,7 +3936,7 @@ packages:
     dependencies:
       '@babel/core': 7.23.9
       '@jest/types': 29.6.3
-      '@jridgewell/trace-mapping': 0.3.22
+      '@jridgewell/trace-mapping': 0.3.23
       babel-plugin-istanbul: 6.1.1
       chalk: 4.1.2
       convert-source-map: 2.0.0
@@ -3867,7 +3959,7 @@ packages:
     dependencies:
       '@types/istanbul-lib-coverage': 2.0.6
       '@types/istanbul-reports': 3.0.4
-      '@types/node': 20.11.19
+      '@types/node': 20.11.20
       '@types/yargs': 16.0.9
       chalk: 4.1.2
     dev: true
@@ -3879,12 +3971,12 @@ packages:
       '@jest/schemas': 29.6.3
       '@types/istanbul-lib-coverage': 2.0.6
       '@types/istanbul-reports': 3.0.4
-      '@types/node': 20.11.19
+      '@types/node': 20.11.20
       '@types/yargs': 17.0.32
       chalk: 4.1.2
     dev: true
 
-  /@joshwooding/vite-plugin-react-docgen-typescript@0.3.0(typescript@5.3.3)(vite@5.1.3):
+  /@joshwooding/vite-plugin-react-docgen-typescript@0.3.0(typescript@5.3.3)(vite@5.1.4):
     resolution: {integrity: sha512-2D6y7fNvFmsLmRt6UCOFJPvFoPMJGT0Uh1Wg0RaigUp7kdQPs6yYn8Dmx6GZkOH/NW0yMTwRz/p0SRMMRo50vA==}
     peerDependencies:
       typescript: '>= 4.3.x'
@@ -3898,16 +3990,16 @@ packages:
       magic-string: 0.27.0
       react-docgen-typescript: 2.2.2(typescript@5.3.3)
       typescript: 5.3.3
-      vite: 5.1.3(@types/node@20.11.19)
+      vite: 5.1.4(@types/node@20.11.20)
     dev: true
 
-  /@jridgewell/gen-mapping@0.3.3:
-    resolution: {integrity: sha512-HLhSWOLRi875zjjMG/r+Nv0oCW8umGb0BgEhyX3dDX3egwZtB8PqLnjz3yedt8R5StBrzcg4aBpnh8UA9D1BoQ==}
+  /@jridgewell/gen-mapping@0.3.4:
+    resolution: {integrity: sha512-Oud2QPM5dHviZNn4y/WhhYKSXksv+1xLEIsNrAbGcFzUN3ubqWRFT5gwPchNc5NuzILOU4tPBDTZ4VwhL8Y7cw==}
     engines: {node: '>=6.0.0'}
     dependencies:
       '@jridgewell/set-array': 1.1.2
       '@jridgewell/sourcemap-codec': 1.4.15
-      '@jridgewell/trace-mapping': 0.3.22
+      '@jridgewell/trace-mapping': 0.3.23
     dev: true
 
   /@jridgewell/resolve-uri@3.1.2:
@@ -3923,8 +4015,8 @@ packages:
   /@jridgewell/sourcemap-codec@1.4.15:
     resolution: {integrity: sha512-eF2rxCRulEKXHTRiDrDy6erMYWqNw4LPdQ8UQA4huuxaQsVeRPFl2oM8oDGxMFhJUWZf9McpLtJasDDZb/Bpeg==}
 
-  /@jridgewell/trace-mapping@0.3.22:
-    resolution: {integrity: sha512-Wf963MzWtA2sjrNt+g18IAln9lKnlRp+K2eH4jjIoF1wYeq3aMREpG09xhlhdzS0EjwU7qmUJYangWa+151vZw==}
+  /@jridgewell/trace-mapping@0.3.23:
+    resolution: {integrity: sha512-9/4foRoUKp8s96tSkh8DlAAc5A0Ty8vLXld+l9gjKKY6ckwI8G15f0hskGmuLZu78ZlGa1vtsfOa+lnB4vG6Jg==}
     dependencies:
       '@jridgewell/resolve-uri': 3.1.2
       '@jridgewell/sourcemap-codec': 1.4.15
@@ -3940,28 +4032,28 @@ packages:
       react: '>=16'
     dependencies:
       '@types/mdx': 2.0.11
-      '@types/react': 18.2.57
+      '@types/react': 18.2.59
       react: 18.2.0
     dev: true
 
-  /@microsoft/api-extractor-model@7.28.3(@types/node@20.11.19):
+  /@microsoft/api-extractor-model@7.28.3(@types/node@20.11.20):
     resolution: {integrity: sha512-wT/kB2oDbdZXITyDh2SQLzaWwTOFbV326fP0pUwNW00WeliARs0qjmXBWmGWardEzp2U3/axkO3Lboqun6vrig==}
     dependencies:
       '@microsoft/tsdoc': 0.14.2
       '@microsoft/tsdoc-config': 0.16.2
-      '@rushstack/node-core-library': 3.62.0(@types/node@20.11.19)
+      '@rushstack/node-core-library': 3.62.0(@types/node@20.11.20)
     transitivePeerDependencies:
       - '@types/node'
     dev: true
 
-  /@microsoft/api-extractor@7.39.0(@types/node@20.11.19):
+  /@microsoft/api-extractor@7.39.0(@types/node@20.11.20):
     resolution: {integrity: sha512-PuXxzadgnvp+wdeZFPonssRAj/EW4Gm4s75TXzPk09h3wJ8RS3x7typf95B4vwZRrPTQBGopdUl+/vHvlPdAcg==}
     hasBin: true
     dependencies:
-      '@microsoft/api-extractor-model': 7.28.3(@types/node@20.11.19)
+      '@microsoft/api-extractor-model': 7.28.3(@types/node@20.11.20)
       '@microsoft/tsdoc': 0.14.2
       '@microsoft/tsdoc-config': 0.16.2
-      '@rushstack/node-core-library': 3.62.0(@types/node@20.11.19)
+      '@rushstack/node-core-library': 3.62.0(@types/node@20.11.20)
       '@rushstack/rig-package': 0.5.1
       '@rushstack/ts-command-line': 4.17.1
       colors: 1.2.5
@@ -4259,7 +4351,7 @@ packages:
       '@babel/runtime': 7.23.9
     dev: true
 
-  /@radix-ui/react-arrow@1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+  /@radix-ui/react-arrow@1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-wSP+pHsB/jQRaL6voubsQ/ZlrGBHHrOjmBnr19hxYgtS0WvAFwZhK2WP/YY5yF9uKECCEEDGxuLxq1NBK51wFA==}
     peerDependencies:
       '@types/react': '*'
@@ -4273,14 +4365,14 @@ packages:
         optional: true
     dependencies:
       '@babel/runtime': 7.23.9
-      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@types/react': 18.2.57
+      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@types/react': 18.2.59
       '@types/react-dom': 18.2.19
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     dev: true
 
-  /@radix-ui/react-collection@1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+  /@radix-ui/react-collection@1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-3SzW+0PW7yBBoQlT8wNcGtaxaD0XSu0uLUFgrtHY08Acx05TaHaOmVLR73c0j/cqpDy53KBMO7s0dx2wmOIDIA==}
     peerDependencies:
       '@types/react': '*'
@@ -4294,17 +4386,17 @@ packages:
         optional: true
     dependencies:
       '@babel/runtime': 7.23.9
-      '@radix-ui/react-compose-refs': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@radix-ui/react-context': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-slot': 1.0.2(@types/react@18.2.57)(react@18.2.0)
-      '@types/react': 18.2.57
+      '@radix-ui/react-compose-refs': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@radix-ui/react-context': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-slot': 1.0.2(@types/react@18.2.59)(react@18.2.0)
+      '@types/react': 18.2.59
       '@types/react-dom': 18.2.19
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     dev: true
 
-  /@radix-ui/react-compose-refs@1.0.1(@types/react@18.2.57)(react@18.2.0):
+  /@radix-ui/react-compose-refs@1.0.1(@types/react@18.2.59)(react@18.2.0):
     resolution: {integrity: sha512-fDSBgd44FKHa1FRMU59qBMPFcl2PZE+2nmqunj+BWFyYYjnhIDWL2ItDs3rrbJDQOtzt5nIebLCQc4QRfz6LJw==}
     peerDependencies:
       '@types/react': '*'
@@ -4314,11 +4406,11 @@ packages:
         optional: true
     dependencies:
       '@babel/runtime': 7.23.9
-      '@types/react': 18.2.57
+      '@types/react': 18.2.59
       react: 18.2.0
     dev: true
 
-  /@radix-ui/react-context@1.0.1(@types/react@18.2.57)(react@18.2.0):
+  /@radix-ui/react-context@1.0.1(@types/react@18.2.59)(react@18.2.0):
     resolution: {integrity: sha512-ebbrdFoYTcuZ0v4wG5tedGnp9tzcV8awzsxYph7gXUyvnNLuTIcCk1q17JEbnVhXAKG9oX3KtchwiMIAYp9NLg==}
     peerDependencies:
       '@types/react': '*'
@@ -4328,11 +4420,11 @@ packages:
         optional: true
     dependencies:
       '@babel/runtime': 7.23.9
-      '@types/react': 18.2.57
+      '@types/react': 18.2.59
       react: 18.2.0
     dev: true
 
-  /@radix-ui/react-direction@1.0.1(@types/react@18.2.57)(react@18.2.0):
+  /@radix-ui/react-direction@1.0.1(@types/react@18.2.59)(react@18.2.0):
     resolution: {integrity: sha512-RXcvnXgyvYvBEOhCBuddKecVkoMiI10Jcm5cTI7abJRAHYfFxeu+FBQs/DvdxSYucxR5mna0dNsL6QFlds5TMA==}
     peerDependencies:
       '@types/react': '*'
@@ -4342,11 +4434,11 @@ packages:
         optional: true
     dependencies:
       '@babel/runtime': 7.23.9
-      '@types/react': 18.2.57
+      '@types/react': 18.2.59
       react: 18.2.0
     dev: true
 
-  /@radix-ui/react-dismissable-layer@1.0.4(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+  /@radix-ui/react-dismissable-layer@1.0.4(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-7UpBa/RKMoHJYjie1gkF1DlK8l1fdU/VKDpoS3rCCo8YBJR294GwcEHyxHw72yvphJ7ld0AXEcSLAzY2F/WyCg==}
     peerDependencies:
       '@types/react': '*'
@@ -4361,17 +4453,17 @@ packages:
     dependencies:
       '@babel/runtime': 7.23.9
       '@radix-ui/primitive': 1.0.1
-      '@radix-ui/react-compose-refs': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-use-callback-ref': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@radix-ui/react-use-escape-keydown': 1.0.3(@types/react@18.2.57)(react@18.2.0)
-      '@types/react': 18.2.57
+      '@radix-ui/react-compose-refs': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-use-callback-ref': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@radix-ui/react-use-escape-keydown': 1.0.3(@types/react@18.2.59)(react@18.2.0)
+      '@types/react': 18.2.59
       '@types/react-dom': 18.2.19
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     dev: true
 
-  /@radix-ui/react-focus-guards@1.0.1(@types/react@18.2.57)(react@18.2.0):
+  /@radix-ui/react-focus-guards@1.0.1(@types/react@18.2.59)(react@18.2.0):
     resolution: {integrity: sha512-Rect2dWbQ8waGzhMavsIbmSVCgYxkXLxxR3ZvCX79JOglzdEy4JXMb98lq4hPxUbLr77nP0UOGf4rcMU+s1pUA==}
     peerDependencies:
       '@types/react': '*'
@@ -4381,11 +4473,11 @@ packages:
         optional: true
     dependencies:
       '@babel/runtime': 7.23.9
-      '@types/react': 18.2.57
+      '@types/react': 18.2.59
       react: 18.2.0
     dev: true
 
-  /@radix-ui/react-focus-scope@1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+  /@radix-ui/react-focus-scope@1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-upXdPfqI4islj2CslyfUBNlaJCPybbqRHAi1KER7Isel9Q2AtSJ0zRBZv8mWQiFXD2nyAJ4BhC3yXgZ6kMBSrQ==}
     peerDependencies:
       '@types/react': '*'
@@ -4399,16 +4491,16 @@ packages:
         optional: true
     dependencies:
       '@babel/runtime': 7.23.9
-      '@radix-ui/react-compose-refs': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-use-callback-ref': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@types/react': 18.2.57
+      '@radix-ui/react-compose-refs': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-use-callback-ref': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@types/react': 18.2.59
       '@types/react-dom': 18.2.19
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     dev: true
 
-  /@radix-ui/react-id@1.0.1(@types/react@18.2.57)(react@18.2.0):
+  /@radix-ui/react-id@1.0.1(@types/react@18.2.59)(react@18.2.0):
     resolution: {integrity: sha512-tI7sT/kqYp8p96yGWY1OAnLHrqDgzHefRBKQ2YAkBS5ja7QLcZ9Z/uY7bEjPUatf8RomoXM8/1sMj1IJaE5UzQ==}
     peerDependencies:
       '@types/react': '*'
@@ -4418,12 +4510,12 @@ packages:
         optional: true
     dependencies:
       '@babel/runtime': 7.23.9
-      '@radix-ui/react-use-layout-effect': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@types/react': 18.2.57
+      '@radix-ui/react-use-layout-effect': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@types/react': 18.2.59
       react: 18.2.0
     dev: true
 
-  /@radix-ui/react-popper@1.1.2(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+  /@radix-ui/react-popper@1.1.2(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-1CnGGfFi/bbqtJZZ0P/NQY20xdG3E0LALJaLUEoKwPLwl6PPPfbeiCqMVQnhoFRAxjJj4RpBRJzDmUgsex2tSg==}
     peerDependencies:
       '@types/react': '*'
@@ -4438,22 +4530,22 @@ packages:
     dependencies:
       '@babel/runtime': 7.23.9
       '@floating-ui/react-dom': 2.0.8(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-arrow': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-compose-refs': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@radix-ui/react-context': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-use-callback-ref': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@radix-ui/react-use-layout-effect': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@radix-ui/react-use-rect': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@radix-ui/react-use-size': 1.0.1(@types/react@18.2.57)(react@18.2.0)
+      '@radix-ui/react-arrow': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-compose-refs': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@radix-ui/react-context': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-use-callback-ref': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@radix-ui/react-use-layout-effect': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@radix-ui/react-use-rect': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@radix-ui/react-use-size': 1.0.1(@types/react@18.2.59)(react@18.2.0)
       '@radix-ui/rect': 1.0.1
-      '@types/react': 18.2.57
+      '@types/react': 18.2.59
       '@types/react-dom': 18.2.19
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     dev: true
 
-  /@radix-ui/react-portal@1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+  /@radix-ui/react-portal@1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-xLYZeHrWoPmA5mEKEfZZevoVRK/Q43GfzRXkWV6qawIWWK8t6ifIiLQdd7rmQ4Vk1bmI21XhqF9BN3jWf+phpA==}
     peerDependencies:
       '@types/react': '*'
@@ -4467,14 +4559,14 @@ packages:
         optional: true
     dependencies:
       '@babel/runtime': 7.23.9
-      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@types/react': 18.2.57
+      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@types/react': 18.2.59
       '@types/react-dom': 18.2.19
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     dev: true
 
-  /@radix-ui/react-primitive@1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+  /@radix-ui/react-primitive@1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-yi58uVyoAcK/Nq1inRY56ZSjKypBNKTa/1mcL8qdl6oJeEaDbOldlzrGn7P6Q3Id5d+SYNGc5AJgc4vGhjs5+g==}
     peerDependencies:
       '@types/react': '*'
@@ -4488,14 +4580,14 @@ packages:
         optional: true
     dependencies:
       '@babel/runtime': 7.23.9
-      '@radix-ui/react-slot': 1.0.2(@types/react@18.2.57)(react@18.2.0)
-      '@types/react': 18.2.57
+      '@radix-ui/react-slot': 1.0.2(@types/react@18.2.59)(react@18.2.0)
+      '@types/react': 18.2.59
       '@types/react-dom': 18.2.19
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     dev: true
 
-  /@radix-ui/react-roving-focus@1.0.4(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+  /@radix-ui/react-roving-focus@1.0.4(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-2mUg5Mgcu001VkGy+FfzZyzbmuUWzgWkj3rvv4yu+mLw03+mTzbxZHvfcGyFp2b8EkQeMkpRQ5FiA2Vr2O6TeQ==}
     peerDependencies:
       '@types/react': '*'
@@ -4510,21 +4602,21 @@ packages:
     dependencies:
       '@babel/runtime': 7.23.9
       '@radix-ui/primitive': 1.0.1
-      '@radix-ui/react-collection': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-compose-refs': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@radix-ui/react-context': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@radix-ui/react-direction': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@radix-ui/react-id': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-use-callback-ref': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@radix-ui/react-use-controllable-state': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@types/react': 18.2.57
+      '@radix-ui/react-collection': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-compose-refs': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@radix-ui/react-context': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@radix-ui/react-direction': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@radix-ui/react-id': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-use-callback-ref': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@radix-ui/react-use-controllable-state': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@types/react': 18.2.59
       '@types/react-dom': 18.2.19
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     dev: true
 
-  /@radix-ui/react-select@1.2.2(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+  /@radix-ui/react-select@1.2.2(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-zI7McXr8fNaSrUY9mZe4x/HC0jTLY9fWNhO1oLWYMQGDXuV4UCivIGTxwioSzO0ZCYX9iSLyWmAh/1TOmX3Cnw==}
     peerDependencies:
       '@types/react': '*'
@@ -4540,32 +4632,32 @@ packages:
       '@babel/runtime': 7.23.9
       '@radix-ui/number': 1.0.1
       '@radix-ui/primitive': 1.0.1
-      '@radix-ui/react-collection': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-compose-refs': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@radix-ui/react-context': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@radix-ui/react-direction': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@radix-ui/react-dismissable-layer': 1.0.4(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-focus-guards': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@radix-ui/react-focus-scope': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-id': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@radix-ui/react-popper': 1.1.2(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-portal': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-slot': 1.0.2(@types/react@18.2.57)(react@18.2.0)
-      '@radix-ui/react-use-callback-ref': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@radix-ui/react-use-controllable-state': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@radix-ui/react-use-layout-effect': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@radix-ui/react-use-previous': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@radix-ui/react-visually-hidden': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@types/react': 18.2.57
+      '@radix-ui/react-collection': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-compose-refs': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@radix-ui/react-context': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@radix-ui/react-direction': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@radix-ui/react-dismissable-layer': 1.0.4(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-focus-guards': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@radix-ui/react-focus-scope': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-id': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@radix-ui/react-popper': 1.1.2(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-portal': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-slot': 1.0.2(@types/react@18.2.59)(react@18.2.0)
+      '@radix-ui/react-use-callback-ref': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@radix-ui/react-use-controllable-state': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@radix-ui/react-use-layout-effect': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@radix-ui/react-use-previous': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@radix-ui/react-visually-hidden': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@types/react': 18.2.59
       '@types/react-dom': 18.2.19
       aria-hidden: 1.2.3
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
-      react-remove-scroll: 2.5.5(@types/react@18.2.57)(react@18.2.0)
+      react-remove-scroll: 2.5.5(@types/react@18.2.59)(react@18.2.0)
     dev: true
 
-  /@radix-ui/react-separator@1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+  /@radix-ui/react-separator@1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-itYmTy/kokS21aiV5+Z56MZB54KrhPgn6eHDKkFeOLR34HMN2s8PaN47qZZAGnvupcjxHaFZnW4pQEh0BvvVuw==}
     peerDependencies:
       '@types/react': '*'
@@ -4579,14 +4671,14 @@ packages:
         optional: true
     dependencies:
       '@babel/runtime': 7.23.9
-      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@types/react': 18.2.57
+      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@types/react': 18.2.59
       '@types/react-dom': 18.2.19
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     dev: true
 
-  /@radix-ui/react-slot@1.0.2(@types/react@18.2.57)(react@18.2.0):
+  /@radix-ui/react-slot@1.0.2(@types/react@18.2.59)(react@18.2.0):
     resolution: {integrity: sha512-YeTpuq4deV+6DusvVUW4ivBgnkHwECUu0BiN43L5UCDFgdhsRUWAghhTF5MbvNTPzmiFOx90asDSUjWuCNapwg==}
     peerDependencies:
       '@types/react': '*'
@@ -4596,12 +4688,12 @@ packages:
         optional: true
     dependencies:
       '@babel/runtime': 7.23.9
-      '@radix-ui/react-compose-refs': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@types/react': 18.2.57
+      '@radix-ui/react-compose-refs': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@types/react': 18.2.59
       react: 18.2.0
     dev: true
 
-  /@radix-ui/react-toggle-group@1.0.4(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+  /@radix-ui/react-toggle-group@1.0.4(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-Uaj/M/cMyiyT9Bx6fOZO0SAG4Cls0GptBWiBmBxofmDbNVnYYoyRWj/2M/6VCi/7qcXFWnHhRUfdfZFvvkuu8A==}
     peerDependencies:
       '@types/react': '*'
@@ -4616,19 +4708,19 @@ packages:
     dependencies:
       '@babel/runtime': 7.23.9
       '@radix-ui/primitive': 1.0.1
-      '@radix-ui/react-context': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@radix-ui/react-direction': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-roving-focus': 1.0.4(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-toggle': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-use-controllable-state': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@types/react': 18.2.57
+      '@radix-ui/react-context': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@radix-ui/react-direction': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-roving-focus': 1.0.4(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-toggle': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-use-controllable-state': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@types/react': 18.2.59
       '@types/react-dom': 18.2.19
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     dev: true
 
-  /@radix-ui/react-toggle@1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+  /@radix-ui/react-toggle@1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-Pkqg3+Bc98ftZGsl60CLANXQBBQ4W3mTFS9EJvNxKMZ7magklKV69/id1mlAlOFDDfHvlCms0fx8fA4CMKDJHg==}
     peerDependencies:
       '@types/react': '*'
@@ -4643,15 +4735,15 @@ packages:
     dependencies:
       '@babel/runtime': 7.23.9
       '@radix-ui/primitive': 1.0.1
-      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-use-controllable-state': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@types/react': 18.2.57
+      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-use-controllable-state': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@types/react': 18.2.59
       '@types/react-dom': 18.2.19
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     dev: true
 
-  /@radix-ui/react-toolbar@1.0.4(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+  /@radix-ui/react-toolbar@1.0.4(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-tBgmM/O7a07xbaEkYJWYTXkIdU/1pW4/KZORR43toC/4XWyBCURK0ei9kMUdp+gTPPKBgYLxXmRSH1EVcIDp8Q==}
     peerDependencies:
       '@types/react': '*'
@@ -4666,19 +4758,19 @@ packages:
     dependencies:
       '@babel/runtime': 7.23.9
       '@radix-ui/primitive': 1.0.1
-      '@radix-ui/react-context': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@radix-ui/react-direction': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-roving-focus': 1.0.4(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-separator': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-toggle-group': 1.0.4(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@types/react': 18.2.57
+      '@radix-ui/react-context': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@radix-ui/react-direction': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-roving-focus': 1.0.4(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-separator': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-toggle-group': 1.0.4(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@types/react': 18.2.59
       '@types/react-dom': 18.2.19
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     dev: true
 
-  /@radix-ui/react-use-callback-ref@1.0.1(@types/react@18.2.57)(react@18.2.0):
+  /@radix-ui/react-use-callback-ref@1.0.1(@types/react@18.2.59)(react@18.2.0):
     resolution: {integrity: sha512-D94LjX4Sp0xJFVaoQOd3OO9k7tpBYNOXdVhkltUbGv2Qb9OXdrg/CpsjlZv7ia14Sylv398LswWBVVu5nqKzAQ==}
     peerDependencies:
       '@types/react': '*'
@@ -4688,11 +4780,11 @@ packages:
         optional: true
     dependencies:
       '@babel/runtime': 7.23.9
-      '@types/react': 18.2.57
+      '@types/react': 18.2.59
       react: 18.2.0
     dev: true
 
-  /@radix-ui/react-use-controllable-state@1.0.1(@types/react@18.2.57)(react@18.2.0):
+  /@radix-ui/react-use-controllable-state@1.0.1(@types/react@18.2.59)(react@18.2.0):
     resolution: {integrity: sha512-Svl5GY5FQeN758fWKrjM6Qb7asvXeiZltlT4U2gVfl8Gx5UAv2sMR0LWo8yhsIZh2oQ0eFdZ59aoOOMV7b47VA==}
     peerDependencies:
       '@types/react': '*'
@@ -4702,12 +4794,12 @@ packages:
         optional: true
     dependencies:
       '@babel/runtime': 7.23.9
-      '@radix-ui/react-use-callback-ref': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@types/react': 18.2.57
+      '@radix-ui/react-use-callback-ref': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@types/react': 18.2.59
       react: 18.2.0
     dev: true
 
-  /@radix-ui/react-use-escape-keydown@1.0.3(@types/react@18.2.57)(react@18.2.0):
+  /@radix-ui/react-use-escape-keydown@1.0.3(@types/react@18.2.59)(react@18.2.0):
     resolution: {integrity: sha512-vyL82j40hcFicA+M4Ex7hVkB9vHgSse1ZWomAqV2Je3RleKGO5iM8KMOEtfoSB0PnIelMd2lATjTGMYqN5ylTg==}
     peerDependencies:
       '@types/react': '*'
@@ -4717,12 +4809,12 @@ packages:
         optional: true
     dependencies:
       '@babel/runtime': 7.23.9
-      '@radix-ui/react-use-callback-ref': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@types/react': 18.2.57
+      '@radix-ui/react-use-callback-ref': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@types/react': 18.2.59
       react: 18.2.0
     dev: true
 
-  /@radix-ui/react-use-layout-effect@1.0.1(@types/react@18.2.57)(react@18.2.0):
+  /@radix-ui/react-use-layout-effect@1.0.1(@types/react@18.2.59)(react@18.2.0):
     resolution: {integrity: sha512-v/5RegiJWYdoCvMnITBkNNx6bCj20fiaJnWtRkU18yITptraXjffz5Qbn05uOiQnOvi+dbkznkoaMltz1GnszQ==}
     peerDependencies:
       '@types/react': '*'
@@ -4732,11 +4824,11 @@ packages:
         optional: true
     dependencies:
       '@babel/runtime': 7.23.9
-      '@types/react': 18.2.57
+      '@types/react': 18.2.59
       react: 18.2.0
     dev: true
 
-  /@radix-ui/react-use-previous@1.0.1(@types/react@18.2.57)(react@18.2.0):
+  /@radix-ui/react-use-previous@1.0.1(@types/react@18.2.59)(react@18.2.0):
     resolution: {integrity: sha512-cV5La9DPwiQ7S0gf/0qiD6YgNqM5Fk97Kdrlc5yBcrF3jyEZQwm7vYFqMo4IfeHgJXsRaMvLABFtd0OVEmZhDw==}
     peerDependencies:
       '@types/react': '*'
@@ -4746,11 +4838,11 @@ packages:
         optional: true
     dependencies:
       '@babel/runtime': 7.23.9
-      '@types/react': 18.2.57
+      '@types/react': 18.2.59
       react: 18.2.0
     dev: true
 
-  /@radix-ui/react-use-rect@1.0.1(@types/react@18.2.57)(react@18.2.0):
+  /@radix-ui/react-use-rect@1.0.1(@types/react@18.2.59)(react@18.2.0):
     resolution: {integrity: sha512-Cq5DLuSiuYVKNU8orzJMbl15TXilTnJKUCltMVQg53BQOF1/C5toAaGrowkgksdBQ9H+SRL23g0HDmg9tvmxXw==}
     peerDependencies:
       '@types/react': '*'
@@ -4761,11 +4853,11 @@ packages:
     dependencies:
       '@babel/runtime': 7.23.9
       '@radix-ui/rect': 1.0.1
-      '@types/react': 18.2.57
+      '@types/react': 18.2.59
       react: 18.2.0
     dev: true
 
-  /@radix-ui/react-use-size@1.0.1(@types/react@18.2.57)(react@18.2.0):
+  /@radix-ui/react-use-size@1.0.1(@types/react@18.2.59)(react@18.2.0):
     resolution: {integrity: sha512-ibay+VqrgcaI6veAojjofPATwledXiSmX+C0KrBk/xgpX9rBzPV3OsfwlhQdUOFbh+LKQorLYT+xTXW9V8yd0g==}
     peerDependencies:
       '@types/react': '*'
@@ -4775,12 +4867,12 @@ packages:
         optional: true
     dependencies:
       '@babel/runtime': 7.23.9
-      '@radix-ui/react-use-layout-effect': 1.0.1(@types/react@18.2.57)(react@18.2.0)
-      '@types/react': 18.2.57
+      '@radix-ui/react-use-layout-effect': 1.0.1(@types/react@18.2.59)(react@18.2.0)
+      '@types/react': 18.2.59
       react: 18.2.0
     dev: true
 
-  /@radix-ui/react-visually-hidden@1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+  /@radix-ui/react-visually-hidden@1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-D4w41yN5YRKtu464TLnByKzMDG/JlMPHtfZgQAu9v6mNakUqGUI9vUrfQKz8NK41VMm/xbZbh76NUTVtIYqOMA==}
     peerDependencies:
       '@types/react': '*'
@@ -4794,8 +4886,8 @@ packages:
         optional: true
     dependencies:
       '@babel/runtime': 7.23.9
-      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@types/react': 18.2.57
+      '@radix-ui/react-primitive': 1.0.3(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@types/react': 18.2.59
       '@types/react-dom': 18.2.19
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
@@ -4807,39 +4899,39 @@ packages:
       '@babel/runtime': 7.23.9
     dev: true
 
-  /@reactflow/background@11.3.9(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+  /@reactflow/background@11.3.9(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-byj/G9pEC8tN0wT/ptcl/LkEP/BBfa33/SvBkqE4XwyofckqF87lKp573qGlisfnsijwAbpDlf81PuFL41So4Q==}
     peerDependencies:
       react: '>=17'
       react-dom: '>=17'
     dependencies:
-      '@reactflow/core': 11.10.4(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@reactflow/core': 11.10.4(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
       classcat: 5.0.4
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
-      zustand: 4.5.1(@types/react@18.2.57)(react@18.2.0)
+      zustand: 4.5.1(@types/react@18.2.59)(react@18.2.0)
     transitivePeerDependencies:
       - '@types/react'
       - immer
     dev: false
 
-  /@reactflow/controls@11.2.9(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+  /@reactflow/controls@11.2.9(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-e8nWplbYfOn83KN1BrxTXS17+enLyFnjZPbyDgHSRLtI5ZGPKF/8iRXV+VXb2LFVzlu4Wh3la/pkxtfP/0aguA==}
     peerDependencies:
       react: '>=17'
       react-dom: '>=17'
     dependencies:
-      '@reactflow/core': 11.10.4(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@reactflow/core': 11.10.4(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
       classcat: 5.0.4
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
-      zustand: 4.5.1(@types/react@18.2.57)(react@18.2.0)
+      zustand: 4.5.1(@types/react@18.2.59)(react@18.2.0)
     transitivePeerDependencies:
       - '@types/react'
       - immer
     dev: false
 
-  /@reactflow/core@11.10.4(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+  /@reactflow/core@11.10.4(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-j3i9b2fsTX/sBbOm+RmNzYEFWbNx4jGWGuGooh2r1jQaE2eV+TLJgiG/VNOp0q5mBl9f6g1IXs3Gm86S9JfcGw==}
     peerDependencies:
       react: '>=17'
@@ -4855,19 +4947,19 @@ packages:
       d3-zoom: 3.0.0
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
-      zustand: 4.5.1(@types/react@18.2.57)(react@18.2.0)
+      zustand: 4.5.1(@types/react@18.2.59)(react@18.2.0)
     transitivePeerDependencies:
       - '@types/react'
       - immer
     dev: false
 
-  /@reactflow/minimap@11.7.9(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+  /@reactflow/minimap@11.7.9(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-le95jyTtt3TEtJ1qa7tZ5hyM4S7gaEQkW43cixcMOZLu33VAdc2aCpJg/fXcRrrf7moN2Mbl9WIMNXUKsp5ILA==}
     peerDependencies:
       react: '>=17'
       react-dom: '>=17'
     dependencies:
-      '@reactflow/core': 11.10.4(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@reactflow/core': 11.10.4(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
       '@types/d3-selection': 3.0.10
       '@types/d3-zoom': 3.0.8
       classcat: 5.0.4
@@ -4875,41 +4967,41 @@ packages:
       d3-zoom: 3.0.0
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
-      zustand: 4.5.1(@types/react@18.2.57)(react@18.2.0)
+      zustand: 4.5.1(@types/react@18.2.59)(react@18.2.0)
     transitivePeerDependencies:
       - '@types/react'
       - immer
     dev: false
 
-  /@reactflow/node-resizer@2.2.9(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+  /@reactflow/node-resizer@2.2.9(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-HfickMm0hPDIHt9qH997nLdgLt0kayQyslKE0RS/GZvZ4UMQJlx/NRRyj5y47Qyg0NnC66KYOQWDM9LLzRTnUg==}
     peerDependencies:
       react: '>=17'
       react-dom: '>=17'
     dependencies:
-      '@reactflow/core': 11.10.4(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@reactflow/core': 11.10.4(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
       classcat: 5.0.4
       d3-drag: 3.0.0
       d3-selection: 3.0.0
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
-      zustand: 4.5.1(@types/react@18.2.57)(react@18.2.0)
+      zustand: 4.5.1(@types/react@18.2.59)(react@18.2.0)
     transitivePeerDependencies:
       - '@types/react'
       - immer
     dev: false
 
-  /@reactflow/node-toolbar@1.3.9(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+  /@reactflow/node-toolbar@1.3.9(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-VmgxKmToax4sX1biZ9LXA7cj/TBJ+E5cklLGwquCCVVxh+lxpZGTBF3a5FJGVHiUNBBtFsC8ldcSZIK4cAlQww==}
     peerDependencies:
       react: '>=17'
       react-dom: '>=17'
     dependencies:
-      '@reactflow/core': 11.10.4(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@reactflow/core': 11.10.4(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
       classcat: 5.0.4
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
-      zustand: 4.5.1(@types/react@18.2.57)(react@18.2.0)
+      zustand: 4.5.1(@types/react@18.2.59)(react@18.2.0)
     transitivePeerDependencies:
       - '@types/react'
       - immer
@@ -4928,7 +5020,7 @@ packages:
     dependencies:
       immer: 10.0.3
       react: 18.2.0
-      react-redux: 9.1.0(@types/react@18.2.57)(react@18.2.0)(redux@5.0.1)
+      react-redux: 9.1.0(@types/react@18.2.59)(react@18.2.0)(redux@5.0.1)
       redux: 5.0.1
       redux-thunk: 3.1.0(redux@5.0.1)
       reselect: 5.1.0
@@ -5069,7 +5161,7 @@ packages:
     dev: true
     optional: true
 
-  /@rushstack/node-core-library@3.62.0(@types/node@20.11.19):
+  /@rushstack/node-core-library@3.62.0(@types/node@20.11.20):
     resolution: {integrity: sha512-88aJn2h8UpSvdwuDXBv1/v1heM6GnBf3RjEy6ZPP7UnzHNCqOHA2Ut+ScYUbXcqIdfew9JlTAe3g+cnX9xQ/Aw==}
     peerDependencies:
       '@types/node': '*'
@@ -5077,7 +5169,7 @@ packages:
       '@types/node':
         optional: true
     dependencies:
-      '@types/node': 20.11.19
+      '@types/node': 20.11.20
       colors: 1.2.5
       fs-extra: 7.0.1
       import-lazy: 4.0.0
@@ -5140,10 +5232,10 @@ packages:
       ts-dedent: 2.2.0
     dev: true
 
-  /@storybook/addon-controls@7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+  /@storybook/addon-controls@7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-zR0aLaUF7FtV/nMRyfniFbCls/e0DAAoXACuOAUAwNAv0lbIS8AyZZiHSmKucCvziUQ6WceeCC7+du3C+9y0rQ==}
     dependencies:
-      '@storybook/blocks': 7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@storybook/blocks': 7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
       lodash: 4.17.21
       ts-dedent: 2.2.0
     transitivePeerDependencies:
@@ -5155,7 +5247,7 @@ packages:
       - supports-color
     dev: true
 
-  /@storybook/addon-docs@7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+  /@storybook/addon-docs@7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-FKa4Mdy7nhgvEVZJHpMkHriDzpVHbohn87zv9NCL+Ctjs1iAmzGwxEm0culszyDS1HN2ToVoY0h8CSi2RSSZqA==}
     peerDependencies:
       react: ^16.8.0 || ^17.0.0 || ^18.0.0
@@ -5163,9 +5255,9 @@ packages:
     dependencies:
       '@jest/transform': 29.7.0
       '@mdx-js/react': 2.3.0(react@18.2.0)
-      '@storybook/blocks': 7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@storybook/blocks': 7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
       '@storybook/client-logger': 7.6.17
-      '@storybook/components': 7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@storybook/components': 7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
       '@storybook/csf-plugin': 7.6.17
       '@storybook/csf-tools': 7.6.17
       '@storybook/global': 5.0.0
@@ -5189,7 +5281,7 @@ packages:
       - supports-color
     dev: true
 
-  /@storybook/addon-essentials@7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+  /@storybook/addon-essentials@7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-qlSpamxuYfT2taF953nC9QijGF2pSbg1ewMNpdwLTj16PTZvR/d8NCDMTJujI1bDwM2m18u8Yc43ibh5LEmxCw==}
     peerDependencies:
       react: ^16.8.0 || ^17.0.0 || ^18.0.0
@@ -5197,8 +5289,8 @@ packages:
     dependencies:
       '@storybook/addon-actions': 7.6.17
       '@storybook/addon-backgrounds': 7.6.17
-      '@storybook/addon-controls': 7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@storybook/addon-docs': 7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@storybook/addon-controls': 7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@storybook/addon-docs': 7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
       '@storybook/addon-highlight': 7.6.17
       '@storybook/addon-measure': 7.6.17
       '@storybook/addon-outline': 7.6.17
@@ -5252,7 +5344,7 @@ packages:
     resolution: {integrity: sha512-O5vnHZNkduvZ95jf1UssbOl6ivIxzl5tv+4EpScPYId7w700bxWsJH+QX7ip6KlrCf2o3iUhmPe8bm05ghG2KA==}
     dependencies:
       '@storybook/global': 5.0.0
-      tiny-invariant: 1.3.1
+      tiny-invariant: 1.3.3
     dev: true
 
   /@storybook/addon-outline@7.6.17:
@@ -5267,7 +5359,7 @@ packages:
     dependencies:
       '@storybook/source-loader': 7.6.17
       estraverse: 5.3.0
-      tiny-invariant: 1.3.1
+      tiny-invariant: 1.3.3
     dev: true
 
   /@storybook/addon-toolbars@7.6.17:
@@ -5280,7 +5372,7 @@ packages:
       memoizerific: 1.11.3
     dev: true
 
-  /@storybook/blocks@7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+  /@storybook/blocks@7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-PsNVoe0bX1mMn4Kk3nbKZ0ItDZZ0YJnYAFJ6toAbsyBAbgzg1sce88sQinzvbn58/RT9MPKeWMPB45ZS7ggiNg==}
     peerDependencies:
       react: ^16.8.0 || ^17.0.0 || ^18.0.0
@@ -5288,7 +5380,7 @@ packages:
     dependencies:
       '@storybook/channels': 7.6.17
       '@storybook/client-logger': 7.6.17
-      '@storybook/components': 7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@storybook/components': 7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
       '@storybook/core-events': 7.6.17
       '@storybook/csf': 0.1.2
       '@storybook/docs-tools': 7.6.17
@@ -5342,7 +5434,7 @@ packages:
       - supports-color
     dev: true
 
-  /@storybook/builder-vite@7.6.17(typescript@5.3.3)(vite@5.1.3):
+  /@storybook/builder-vite@7.6.17(typescript@5.3.3)(vite@5.1.4):
     resolution: {integrity: sha512-2Q32qalI401EsKKr9Hkk8TAOcHEerqwsjCpQgTNJnCu6GgCVKoVUcb99oRbR9Vyg0xh+jb19XiWqqQujFtLYlQ==}
     peerDependencies:
       '@preact/preset-vite': '*'
@@ -5374,7 +5466,7 @@ packages:
       magic-string: 0.30.7
       rollup: 3.29.4
       typescript: 5.3.3
-      vite: 5.1.3(@types/node@20.11.19)
+      vite: 5.1.4(@types/node@20.11.20)
     transitivePeerDependencies:
       - encoding
       - supports-color
@@ -5388,7 +5480,7 @@ packages:
       '@storybook/global': 5.0.0
       qs: 6.11.2
       telejson: 7.2.0
-      tiny-invariant: 1.3.1
+      tiny-invariant: 1.3.3
     dev: true
 
   /@storybook/cli@7.6.17:
@@ -5407,7 +5499,7 @@ packages:
       '@storybook/node-logger': 7.6.17
       '@storybook/telemetry': 7.6.17
       '@storybook/types': 7.6.17
-      '@types/semver': 7.5.7
+      '@types/semver': 7.5.8
       '@yarnpkg/fslib': 2.10.3
       '@yarnpkg/libzip': 2.3.0
       chalk: 4.1.2
@@ -5423,7 +5515,7 @@ packages:
       get-port: 5.1.1
       giget: 1.2.1
       globby: 11.1.0
-      jscodeshift: 0.15.1(@babel/preset-env@7.23.9)
+      jscodeshift: 0.15.2(@babel/preset-env@7.23.9)
       leven: 3.1.0
       ora: 5.4.1
       prettier: 2.8.8
@@ -5461,7 +5553,7 @@ packages:
       '@types/cross-spawn': 6.0.6
       cross-spawn: 7.0.3
       globby: 11.1.0
-      jscodeshift: 0.15.1(@babel/preset-env@7.23.9)
+      jscodeshift: 0.15.2(@babel/preset-env@7.23.9)
       lodash: 4.17.21
       prettier: 2.8.8
       recast: 0.23.4
@@ -5469,14 +5561,14 @@ packages:
       - supports-color
     dev: true
 
-  /@storybook/components@7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+  /@storybook/components@7.6.17(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-lbh7GynMidA+CZcJnstVku6Nhs+YkqjYaZ+mKPugvlVhGVWv0DaaeQFVuZ8cJtUGJ/5FFU4Y+n+gylYUHkGBMA==}
     peerDependencies:
       react: ^16.8.0 || ^17.0.0 || ^18.0.0
       react-dom: ^16.8.0 || ^17.0.0 || ^18.0.0
     dependencies:
-      '@radix-ui/react-select': 1.2.2(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@radix-ui/react-toolbar': 1.0.4(@types/react-dom@18.2.19)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-select': 1.2.2(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@radix-ui/react-toolbar': 1.0.4(@types/react-dom@18.2.19)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
       '@storybook/client-logger': 7.6.17
       '@storybook/csf': 0.1.2
       '@storybook/global': 5.0.0
@@ -5506,7 +5598,7 @@ packages:
       '@storybook/node-logger': 7.6.17
       '@storybook/types': 7.6.17
       '@types/find-cache-dir': 3.2.1
-      '@types/node': 18.19.17
+      '@types/node': 18.19.18
       '@types/node-fetch': 2.6.11
       '@types/pretty-hrtime': 1.0.3
       chalk: 4.1.2
@@ -5555,9 +5647,9 @@ packages:
       '@storybook/telemetry': 7.6.17
       '@storybook/types': 7.6.17
       '@types/detect-port': 1.3.5
-      '@types/node': 18.19.17
+      '@types/node': 18.19.18
       '@types/pretty-hrtime': 1.0.3
-      '@types/semver': 7.5.7
+      '@types/semver': 7.5.8
       better-opn: 3.0.2
       chalk: 4.1.2
       cli-table3: 0.6.3
@@ -5574,7 +5666,7 @@ packages:
       read-pkg-up: 7.0.1
       semver: 7.6.0
       telejson: 7.2.0
-      tiny-invariant: 1.3.1
+      tiny-invariant: 1.3.3
       ts-dedent: 2.2.0
       util: 0.12.5
       util-deprecate: 1.0.2
@@ -5718,7 +5810,7 @@ packages:
       react-dom: 18.2.0(react@18.2.0)
     dev: true
 
-  /@storybook/react-vite@7.6.17(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)(vite@5.1.3):
+  /@storybook/react-vite@7.6.17(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)(vite@5.1.4):
     resolution: {integrity: sha512-4dIm3CuRl44X1TLzN3WoZh/bChzJF7Ud28li9atj9C8db0bb/y0zl8cahrsRFoR7/LyfqdOVLqaztrnA5SsWfg==}
     engines: {node: '>=16'}
     peerDependencies:
@@ -5726,16 +5818,16 @@ packages:
       react-dom: ^16.8.0 || ^17.0.0 || ^18.0.0
       vite: ^3.0.0 || ^4.0.0 || ^5.0.0
     dependencies:
-      '@joshwooding/vite-plugin-react-docgen-typescript': 0.3.0(typescript@5.3.3)(vite@5.1.3)
+      '@joshwooding/vite-plugin-react-docgen-typescript': 0.3.0(typescript@5.3.3)(vite@5.1.4)
       '@rollup/pluginutils': 5.1.0
-      '@storybook/builder-vite': 7.6.17(typescript@5.3.3)(vite@5.1.3)
+      '@storybook/builder-vite': 7.6.17(typescript@5.3.3)(vite@5.1.4)
       '@storybook/react': 7.6.17(react-dom@18.2.0)(react@18.2.0)(typescript@5.3.3)
-      '@vitejs/plugin-react': 3.1.0(vite@5.1.3)
+      '@vitejs/plugin-react': 3.1.0(vite@5.1.4)
       magic-string: 0.30.7
       react: 18.2.0
       react-docgen: 7.0.3
       react-dom: 18.2.0(react@18.2.0)
-      vite: 5.1.3(@types/node@20.11.19)
+      vite: 5.1.4(@types/node@20.11.20)
     transitivePeerDependencies:
       - '@preact/preset-vite'
       - encoding
@@ -5765,7 +5857,7 @@ packages:
       '@storybook/types': 7.6.17
       '@types/escodegen': 0.0.6
       '@types/estree': 0.0.51
-      '@types/node': 18.19.17
+      '@types/node': 18.19.18
       acorn: 7.4.1
       acorn-jsx: 5.3.2(acorn@7.4.1)
       acorn-walk: 7.2.0
@@ -6008,19 +6100,19 @@ packages:
     resolution: {integrity: sha512-fB3Zu92ucau0iQ0JMCFQE7b/dv8Ot07NI3KaZIkIUNXq82k4eBAqUaneXfleGY9JWskeS9y+u0nXMyspcuQrCg==}
     dependencies:
       '@types/connect': 3.4.38
-      '@types/node': 20.11.19
+      '@types/node': 20.11.20
     dev: true
 
   /@types/connect@3.4.38:
     resolution: {integrity: sha512-K6uROf1LD88uDQqJCktA4yzL1YYAK6NgfsI0v/mTgyPKWsX1CnJ0XPSDhViejru1GcRkLWb8RlzFYJRqGUbaug==}
     dependencies:
-      '@types/node': 20.11.19
+      '@types/node': 20.11.20
     dev: true
 
   /@types/cross-spawn@6.0.6:
     resolution: {integrity: sha512-fXRhhUkG4H3TQk5dBhQ7m/JDdSNHKwR2BBia62lhwEIq9xGiQKLxd6LymNhn47SjXhsUEPmxi+PKw2OkW4LLjA==}
     dependencies:
-      '@types/node': 20.11.19
+      '@types/node': 20.11.20
     dev: true
 
   /@types/d3-array@3.2.1:
@@ -6234,8 +6326,8 @@ packages:
     resolution: {integrity: sha512-AjwI4MvWx3HAOaZqYsjKWyEObT9lcVV0Y0V8nXo6cXzN8ZiMxVhf6F3d/UNvXVGKrEzL/Dluc5p+y9GkzlTWig==}
     dev: true
 
-  /@types/eslint@8.56.2:
-    resolution: {integrity: sha512-uQDwm1wFHmbBbCZCqAlq6Do9LYwByNZHWzXppSnay9SuwJ+VRbjkbLABer54kcPnMSlG6Fdiy2yaFXm/z9Z5gw==}
+  /@types/eslint@8.56.3:
+    resolution: {integrity: sha512-PvSf1wfv2wJpVIFUMSb+i4PvqNYkB9Rkp9ZDO3oaWzq4SKhsQk4mrMBr3ZH06I0hKrVGLBacmgl8JM4WVjb9dg==}
     dependencies:
       '@types/estree': 1.0.5
       '@types/json-schema': 7.0.15
@@ -6252,7 +6344,7 @@ packages:
   /@types/express-serve-static-core@4.17.43:
     resolution: {integrity: sha512-oaYtiBirUOPQGSWNGPWnzyAFJ0BP3cwvN4oWZQY+zUBwpVIGsKUkpBpSztp74drYcjavs7SKFZ4DX1V2QeN8rg==}
     dependencies:
-      '@types/node': 20.11.19
+      '@types/node': 20.11.20
       '@types/qs': 6.9.11
       '@types/range-parser': 1.2.7
       '@types/send': 0.17.4
@@ -6279,13 +6371,13 @@ packages:
     resolution: {integrity: sha512-ZUxbzKl0IfJILTS6t7ip5fQQM/J3TJYubDm3nMbgubNNYS62eXeUpoLUC8/7fJNiFYHTrGPQn7hspDUzIHX3UA==}
     dependencies:
       '@types/minimatch': 5.1.2
-      '@types/node': 20.11.19
+      '@types/node': 20.11.20
     dev: true
 
   /@types/graceful-fs@4.1.9:
     resolution: {integrity: sha512-olP3sd1qOEe5dXTSaFvQG+02VdRXcdytWLAZsAq1PecU8uqQAhkrnbli7DagjtXKW/Bl7YJbUsa8MPcuc8LHEQ==}
     dependencies:
-      '@types/node': 20.11.19
+      '@types/node': 20.11.20
     dev: true
 
   /@types/http-errors@2.0.4:
@@ -6358,18 +6450,18 @@ packages:
   /@types/node-fetch@2.6.11:
     resolution: {integrity: sha512-24xFj9R5+rfQJLRyM56qh+wnVSYhyXC2tkoBndtY0U+vubqNsYXGjufB2nn8Q6gt0LrARwL6UBtMCSVCwl4B1g==}
     dependencies:
-      '@types/node': 20.11.19
+      '@types/node': 20.11.20
       form-data: 4.0.0
     dev: true
 
-  /@types/node@18.19.17:
-    resolution: {integrity: sha512-SzyGKgwPzuWp2SHhlpXKzCX0pIOfcI4V2eF37nNBJOhwlegQ83omtVQ1XxZpDE06V/d6AQvfQdPfnw0tRC//Ng==}
+  /@types/node@18.19.18:
+    resolution: {integrity: sha512-80CP7B8y4PzZF0GWx15/gVWRrB5y/bIjNI84NK3cmQJu0WZwvmj2WMA5LcofQFVfLqqCSp545+U2LsrVzX36Zg==}
     dependencies:
       undici-types: 5.26.5
     dev: true
 
-  /@types/node@20.11.19:
-    resolution: {integrity: sha512-7xMnVEcZFu0DikYjWOlRq7NTPETrm7teqUT2WkQjrTIkEgUyyGdWsj/Zg8bEJt5TNklzbPD1X3fqfsHw3SpapQ==}
+  /@types/node@20.11.20:
+    resolution: {integrity: sha512-7/rR21OS+fq8IyHTgtLkDK949uzsa6n8BkziAKtPVpugIkO6D+/ooXMvzXxDnZrmtXVfjb1bKQafYpb8s89LOg==}
     dependencies:
       undici-types: 5.26.5
     dev: true
@@ -6404,19 +6496,19 @@ packages:
   /@types/react-dom@18.2.19:
     resolution: {integrity: sha512-aZvQL6uUbIJpjZk4U8JZGbau9KDeAwMfmhyWorxgBkqDIEf6ROjRozcmPIicqsUwPUjbkDfHKgGee1Lq65APcA==}
     dependencies:
-      '@types/react': 18.2.57
+      '@types/react': 18.2.59
     dev: true
 
   /@types/react-reconciler@0.28.8:
     resolution: {integrity: sha512-SN9c4kxXZonFhbX4hJrZy37yw9e7EIxcpHCxQv5JUS18wDE5ovkQKlqQEkufdJCCMfuI9BnjUJvhYeJ9x5Ra7g==}
     dependencies:
-      '@types/react': 18.2.57
+      '@types/react': 18.2.59
     dev: false
 
   /@types/react-transition-group@4.4.10:
     resolution: {integrity: sha512-hT/+s0VQs2ojCX823m60m5f0sL5idt9SO6Tj6Dg+rdphGPIeJbJ6CxvBYkgkGKrYeDjvIpKTR38UzmtHJOGW3Q==}
     dependencies:
-      '@types/react': 18.2.57
+      '@types/react': 18.2.59
     dev: false
 
   /@types/react@18.2.57:
@@ -6425,6 +6517,14 @@ packages:
       '@types/prop-types': 15.7.11
       '@types/scheduler': 0.16.8
       csstype: 3.1.3
+    dev: false
+
+  /@types/react@18.2.59:
+    resolution: {integrity: sha512-DE+F6BYEC8VtajY85Qr7mmhTd/79rJKIHCg99MU9SWPB4xvLb6D1za2vYflgZfmPqQVEr6UqJTnLXEwzpVPuOg==}
+    dependencies:
+      '@types/prop-types': 15.7.11
+      '@types/scheduler': 0.16.8
+      csstype: 3.1.3
 
   /@types/resolve@1.20.6:
     resolution: {integrity: sha512-A4STmOXPhMUtHH+S6ymgE2GiBSMqf4oTvcQZMcHzokuTLVYzXTB8ttjcgxOVaAp2lGwEdzZ0J+cRbbeevQj1UQ==}
@@ -6433,15 +6533,15 @@ packages:
   /@types/scheduler@0.16.8:
     resolution: {integrity: sha512-WZLiwShhwLRmeV6zH+GkbOFT6Z6VklCItrDioxUnv+u4Ll+8vKeFySoFyK/0ctcRpOmwAicELfmys1sDc/Rw+A==}
 
-  /@types/semver@7.5.7:
-    resolution: {integrity: sha512-/wdoPq1QqkSj9/QOeKkFquEuPzQbHTWAMPH/PaUMB+JuR31lXhlWXRZ52IpfDYVlDOUBvX09uBrPwxGT1hjNBg==}
+  /@types/semver@7.5.8:
+    resolution: {integrity: sha512-I8EUhyrgfLrcTkzV3TSsGyl1tSuPrEDzr0yd5m90UgNxQkyDXULk3b6MlQqTCpZpNtWe1K0hzclnZkTcLBe2UQ==}
     dev: true
 
   /@types/send@0.17.4:
     resolution: {integrity: sha512-x2EM6TJOybec7c52BX0ZspPodMsQUd5L6PRwOunVyVUhXiBSKf3AezDL8Dgvgt5o0UfKNfuA0eMLr2wLT4AiBA==}
     dependencies:
       '@types/mime': 1.3.5
-      '@types/node': 20.11.19
+      '@types/node': 20.11.20
     dev: true
 
   /@types/serve-static@1.15.5:
@@ -6449,7 +6549,7 @@ packages:
     dependencies:
       '@types/http-errors': 2.0.4
       '@types/mime': 3.0.4
-      '@types/node': 20.11.19
+      '@types/node': 20.11.20
     dev: true
 
   /@types/unist@2.0.10:
@@ -6480,8 +6580,8 @@ packages:
       '@types/yargs-parser': 21.0.3
     dev: true
 
-  /@typescript-eslint/eslint-plugin@7.0.2(@typescript-eslint/parser@7.0.2)(eslint@8.56.0)(typescript@5.3.3):
-    resolution: {integrity: sha512-/XtVZJtbaphtdrWjr+CJclaCVGPtOdBpFEnvtNf/jRV0IiEemRrL0qABex/nEt8isYcnFacm3nPHYQwL+Wb7qg==}
+  /@typescript-eslint/eslint-plugin@7.1.0(@typescript-eslint/parser@7.1.0)(eslint@8.57.0)(typescript@5.3.3):
+    resolution: {integrity: sha512-j6vT/kCulhG5wBmGtstKeiVr1rdXE4nk+DT1k6trYkwlrvW9eOF5ZbgKnd/YR6PcM4uTEXa0h6Fcvf6X7Dxl0w==}
     engines: {node: ^16.0.0 || >=18.0.0}
     peerDependencies:
       '@typescript-eslint/parser': ^7.0.0
@@ -6492,13 +6592,13 @@ packages:
         optional: true
     dependencies:
       '@eslint-community/regexpp': 4.10.0
-      '@typescript-eslint/parser': 7.0.2(eslint@8.56.0)(typescript@5.3.3)
-      '@typescript-eslint/scope-manager': 7.0.2
-      '@typescript-eslint/type-utils': 7.0.2(eslint@8.56.0)(typescript@5.3.3)
-      '@typescript-eslint/utils': 7.0.2(eslint@8.56.0)(typescript@5.3.3)
-      '@typescript-eslint/visitor-keys': 7.0.2
+      '@typescript-eslint/parser': 7.1.0(eslint@8.57.0)(typescript@5.3.3)
+      '@typescript-eslint/scope-manager': 7.1.0
+      '@typescript-eslint/type-utils': 7.1.0(eslint@8.57.0)(typescript@5.3.3)
+      '@typescript-eslint/utils': 7.1.0(eslint@8.57.0)(typescript@5.3.3)
+      '@typescript-eslint/visitor-keys': 7.1.0
       debug: 4.3.4
-      eslint: 8.56.0
+      eslint: 8.57.0
       graphemer: 1.4.0
       ignore: 5.3.1
       natural-compare: 1.4.0
@@ -6509,8 +6609,8 @@ packages:
       - supports-color
     dev: true
 
-  /@typescript-eslint/parser@7.0.2(eslint@8.56.0)(typescript@5.3.3):
-    resolution: {integrity: sha512-GdwfDglCxSmU+QTS9vhz2Sop46ebNCXpPPvsByK7hu0rFGRHL+AusKQJ7SoN+LbLh6APFpQwHKmDSwN35Z700Q==}
+  /@typescript-eslint/parser@7.1.0(eslint@8.57.0)(typescript@5.3.3):
+    resolution: {integrity: sha512-V1EknKUubZ1gWFjiOZhDSNToOjs63/9O0puCgGS8aDOgpZY326fzFu15QAUjwaXzRZjf/qdsdBrckYdv9YxB8w==}
     engines: {node: ^16.0.0 || >=18.0.0}
     peerDependencies:
       eslint: ^8.56.0
@@ -6519,12 +6619,12 @@ packages:
       typescript:
         optional: true
     dependencies:
-      '@typescript-eslint/scope-manager': 7.0.2
-      '@typescript-eslint/types': 7.0.2
-      '@typescript-eslint/typescript-estree': 7.0.2(typescript@5.3.3)
-      '@typescript-eslint/visitor-keys': 7.0.2
+      '@typescript-eslint/scope-manager': 7.1.0
+      '@typescript-eslint/types': 7.1.0
+      '@typescript-eslint/typescript-estree': 7.1.0(typescript@5.3.3)
+      '@typescript-eslint/visitor-keys': 7.1.0
       debug: 4.3.4
-      eslint: 8.56.0
+      eslint: 8.57.0
       typescript: 5.3.3
     transitivePeerDependencies:
       - supports-color
@@ -6538,16 +6638,16 @@ packages:
       '@typescript-eslint/visitor-keys': 5.62.0
     dev: true
 
-  /@typescript-eslint/scope-manager@7.0.2:
-    resolution: {integrity: sha512-l6sa2jF3h+qgN2qUMjVR3uCNGjWw4ahGfzIYsCtFrQJCjhbrDPdiihYT8FnnqFwsWX+20hK592yX9I2rxKTP4g==}
+  /@typescript-eslint/scope-manager@7.1.0:
+    resolution: {integrity: sha512-6TmN4OJiohHfoOdGZ3huuLhpiUgOGTpgXNUPJgeZOZR3DnIpdSgtt83RS35OYNNXxM4TScVlpVKC9jyQSETR1A==}
     engines: {node: ^16.0.0 || >=18.0.0}
     dependencies:
-      '@typescript-eslint/types': 7.0.2
-      '@typescript-eslint/visitor-keys': 7.0.2
+      '@typescript-eslint/types': 7.1.0
+      '@typescript-eslint/visitor-keys': 7.1.0
     dev: true
 
-  /@typescript-eslint/type-utils@7.0.2(eslint@8.56.0)(typescript@5.3.3):
-    resolution: {integrity: sha512-IKKDcFsKAYlk8Rs4wiFfEwJTQlHcdn8CLwLaxwd6zb8HNiMcQIFX9sWax2k4Cjj7l7mGS5N1zl7RCHOVwHq2VQ==}
+  /@typescript-eslint/type-utils@7.1.0(eslint@8.57.0)(typescript@5.3.3):
+    resolution: {integrity: sha512-UZIhv8G+5b5skkcuhgvxYWHjk7FW7/JP5lPASMEUoliAPwIH/rxoUSQPia2cuOj9AmDZmwUl1usKm85t5VUMew==}
     engines: {node: ^16.0.0 || >=18.0.0}
     peerDependencies:
       eslint: ^8.56.0
@@ -6556,10 +6656,10 @@ packages:
       typescript:
         optional: true
     dependencies:
-      '@typescript-eslint/typescript-estree': 7.0.2(typescript@5.3.3)
-      '@typescript-eslint/utils': 7.0.2(eslint@8.56.0)(typescript@5.3.3)
+      '@typescript-eslint/typescript-estree': 7.1.0(typescript@5.3.3)
+      '@typescript-eslint/utils': 7.1.0(eslint@8.57.0)(typescript@5.3.3)
       debug: 4.3.4
-      eslint: 8.56.0
+      eslint: 8.57.0
       ts-api-utils: 1.2.1(typescript@5.3.3)
       typescript: 5.3.3
     transitivePeerDependencies:
@@ -6571,8 +6671,8 @@ packages:
     engines: {node: ^12.22.0 || ^14.17.0 || >=16.0.0}
     dev: true
 
-  /@typescript-eslint/types@7.0.2:
-    resolution: {integrity: sha512-ZzcCQHj4JaXFjdOql6adYV4B/oFOFjPOC9XYwCaZFRvqN8Llfvv4gSxrkQkd2u4Ci62i2c6W6gkDwQJDaRc4nA==}
+  /@typescript-eslint/types@7.1.0:
+    resolution: {integrity: sha512-qTWjWieJ1tRJkxgZYXx6WUYtWlBc48YRxgY2JN1aGeVpkhmnopq+SUC8UEVGNXIvWH7XyuTjwALfG6bFEgCkQA==}
     engines: {node: ^16.0.0 || >=18.0.0}
     dev: true
 
@@ -6597,8 +6697,8 @@ packages:
       - supports-color
     dev: true
 
-  /@typescript-eslint/typescript-estree@7.0.2(typescript@5.3.3):
-    resolution: {integrity: sha512-3AMc8khTcELFWcKcPc0xiLviEvvfzATpdPj/DXuOGIdQIIFybf4DMT1vKRbuAEOFMwhWt7NFLXRkbjsvKZQyvw==}
+  /@typescript-eslint/typescript-estree@7.1.0(typescript@5.3.3):
+    resolution: {integrity: sha512-k7MyrbD6E463CBbSpcOnwa8oXRdHzH1WiVzOipK3L5KSML92ZKgUBrTlehdi7PEIMT8k0bQixHUGXggPAlKnOQ==}
     engines: {node: ^16.0.0 || >=18.0.0}
     peerDependencies:
       typescript: '*'
@@ -6606,8 +6706,8 @@ packages:
       typescript:
         optional: true
     dependencies:
-      '@typescript-eslint/types': 7.0.2
-      '@typescript-eslint/visitor-keys': 7.0.2
+      '@typescript-eslint/types': 7.1.0
+      '@typescript-eslint/visitor-keys': 7.1.0
       debug: 4.3.4
       globby: 11.1.0
       is-glob: 4.0.3
@@ -6619,19 +6719,19 @@ packages:
       - supports-color
     dev: true
 
-  /@typescript-eslint/utils@5.62.0(eslint@8.56.0)(typescript@5.3.3):
+  /@typescript-eslint/utils@5.62.0(eslint@8.57.0)(typescript@5.3.3):
     resolution: {integrity: sha512-n8oxjeb5aIbPFEtmQxQYOLI0i9n5ySBEY/ZEHHZqKQSFnxio1rv6dthascc9dLuwrL0RC5mPCxB7vnAVGAYWAQ==}
     engines: {node: ^12.22.0 || ^14.17.0 || >=16.0.0}
     peerDependencies:
       eslint: ^6.0.0 || ^7.0.0 || ^8.0.0
     dependencies:
-      '@eslint-community/eslint-utils': 4.4.0(eslint@8.56.0)
+      '@eslint-community/eslint-utils': 4.4.0(eslint@8.57.0)
       '@types/json-schema': 7.0.15
-      '@types/semver': 7.5.7
+      '@types/semver': 7.5.8
       '@typescript-eslint/scope-manager': 5.62.0
       '@typescript-eslint/types': 5.62.0
       '@typescript-eslint/typescript-estree': 5.62.0(typescript@5.3.3)
-      eslint: 8.56.0
+      eslint: 8.57.0
       eslint-scope: 5.1.1
       semver: 7.6.0
     transitivePeerDependencies:
@@ -6639,19 +6739,19 @@ packages:
       - typescript
     dev: true
 
-  /@typescript-eslint/utils@7.0.2(eslint@8.56.0)(typescript@5.3.3):
-    resolution: {integrity: sha512-PZPIONBIB/X684bhT1XlrkjNZJIEevwkKDsdwfiu1WeqBxYEEdIgVDgm8/bbKHVu+6YOpeRqcfImTdImx/4Bsw==}
+  /@typescript-eslint/utils@7.1.0(eslint@8.57.0)(typescript@5.3.3):
+    resolution: {integrity: sha512-WUFba6PZC5OCGEmbweGpnNJytJiLG7ZvDBJJoUcX4qZYf1mGZ97mO2Mps6O2efxJcJdRNpqweCistDbZMwIVHw==}
     engines: {node: ^16.0.0 || >=18.0.0}
     peerDependencies:
       eslint: ^8.56.0
     dependencies:
-      '@eslint-community/eslint-utils': 4.4.0(eslint@8.56.0)
+      '@eslint-community/eslint-utils': 4.4.0(eslint@8.57.0)
       '@types/json-schema': 7.0.15
-      '@types/semver': 7.5.7
-      '@typescript-eslint/scope-manager': 7.0.2
-      '@typescript-eslint/types': 7.0.2
-      '@typescript-eslint/typescript-estree': 7.0.2(typescript@5.3.3)
-      eslint: 8.56.0
+      '@types/semver': 7.5.8
+      '@typescript-eslint/scope-manager': 7.1.0
+      '@typescript-eslint/types': 7.1.0
+      '@typescript-eslint/typescript-estree': 7.1.0(typescript@5.3.3)
+      eslint: 8.57.0
       semver: 7.6.0
     transitivePeerDependencies:
       - supports-color
@@ -6666,11 +6766,11 @@ packages:
       eslint-visitor-keys: 3.4.3
     dev: true
 
-  /@typescript-eslint/visitor-keys@7.0.2:
-    resolution: {integrity: sha512-8Y+YiBmqPighbm5xA2k4wKTxRzx9EkBu7Rlw+WHqMvRJ3RPz/BMBO9b2ru0LUNmXg120PHUXD5+SWFy2R8DqlQ==}
+  /@typescript-eslint/visitor-keys@7.1.0:
+    resolution: {integrity: sha512-FhUqNWluiGNzlvnDZiXad4mZRhtghdoKW6e98GoEOYSu5cND+E39rG5KwJMUzeENwm1ztYBRqof8wMLP+wNPIA==}
     engines: {node: ^16.0.0 || >=18.0.0}
     dependencies:
-      '@typescript-eslint/types': 7.0.2
+      '@typescript-eslint/types': 7.1.0
       eslint-visitor-keys: 3.4.3
     dev: true
 
@@ -6678,18 +6778,18 @@ packages:
     resolution: {integrity: sha512-zuVdFrMJiuCDQUMCzQaD6KL28MjnqqN8XnAqiEq9PNm/hCPTSGfrXCOfwj1ow4LFb/tNymJPwsNbVePc1xFqrQ==}
     dev: true
 
-  /@vitejs/plugin-react-swc@3.6.0(vite@5.1.3):
+  /@vitejs/plugin-react-swc@3.6.0(vite@5.1.4):
     resolution: {integrity: sha512-XFRbsGgpGxGzEV5i5+vRiro1bwcIaZDIdBRP16qwm+jP68ue/S8FJTBEgOeojtVDYrbSua3XFp71kC8VJE6v+g==}
     peerDependencies:
       vite: ^4 || ^5
     dependencies:
       '@swc/core': 1.4.2
-      vite: 5.1.3(@types/node@20.11.19)
+      vite: 5.1.4(@types/node@20.11.20)
     transitivePeerDependencies:
       - '@swc/helpers'
     dev: true
 
-  /@vitejs/plugin-react@3.1.0(vite@5.1.3):
+  /@vitejs/plugin-react@3.1.0(vite@5.1.4):
     resolution: {integrity: sha512-AfgcRL8ZBhAlc3BFdigClmTUMISmmzHn7sB2h9U1odvc5U/MjWXsAaz18b/WoppUTDBzxOJwo2VdClfUcItu9g==}
     engines: {node: ^14.18.0 || >=16.0.0}
     peerDependencies:
@@ -6700,7 +6800,7 @@ packages:
       '@babel/plugin-transform-react-jsx-source': 7.23.3(@babel/core@7.23.9)
       magic-string: 0.27.0
       react-refresh: 0.14.0
-      vite: 5.1.3(@types/node@20.11.19)
+      vite: 5.1.4(@types/node@20.11.20)
     transitivePeerDependencies:
       - supports-color
     dev: true
@@ -6763,21 +6863,21 @@ packages:
       path-browserify: 1.0.1
     dev: true
 
-  /@vue/compiler-core@3.4.19:
-    resolution: {integrity: sha512-gj81785z0JNzRcU0Mq98E56e4ltO1yf8k5PQ+tV/7YHnbZkrM0fyFyuttnN8ngJZjbpofWE/m4qjKBiLl8Ju4w==}
+  /@vue/compiler-core@3.4.20:
+    resolution: {integrity: sha512-l7M+xUuL8hrGtRLkrf+62d9zucAdgqNBTbJ/NufCOIuJQhauhfyAKH9ra/qUctCXcULwmclGAVpvmxjbBO30qg==}
     dependencies:
       '@babel/parser': 7.23.9
-      '@vue/shared': 3.4.19
+      '@vue/shared': 3.4.20
       entities: 4.5.0
       estree-walker: 2.0.2
       source-map-js: 1.0.2
     dev: true
 
-  /@vue/compiler-dom@3.4.19:
-    resolution: {integrity: sha512-vm6+cogWrshjqEHTzIDCp72DKtea8Ry/QVpQRYoyTIg9k7QZDX6D8+HGURjtmatfgM8xgCFtJJaOlCaRYRK3QA==}
+  /@vue/compiler-dom@3.4.20:
+    resolution: {integrity: sha512-/cSBGL79HFBYgDnqCNKErOav3bPde3n0sJwJM2Z09rXlkiowV/2SG1tgDAiWS1CatS4Cvo0o74e1vNeCK1R3RA==}
     dependencies:
-      '@vue/compiler-core': 3.4.19
-      '@vue/shared': 3.4.19
+      '@vue/compiler-core': 3.4.20
+      '@vue/shared': 3.4.20
     dev: true
 
   /@vue/language-core@1.8.27(typescript@5.3.3):
@@ -6790,8 +6890,8 @@ packages:
     dependencies:
       '@volar/language-core': 1.11.1
       '@volar/source-map': 1.11.1
-      '@vue/compiler-dom': 3.4.19
-      '@vue/shared': 3.4.19
+      '@vue/compiler-dom': 3.4.20
+      '@vue/shared': 3.4.20
       computeds: 0.0.1
       minimatch: 9.0.3
       muggle-string: 0.3.1
@@ -6800,8 +6900,8 @@ packages:
       vue-template-compiler: 2.7.16
     dev: true
 
-  /@vue/shared@3.4.19:
-    resolution: {integrity: sha512-/KliRRHMF6LoiThEy+4c1Z4KB/gbPrGjWwJR+crg2otgrf/egKzRaCPvJ51S5oetgsgXLfc4Rm5ZgrKHZrtMSw==}
+  /@vue/shared@3.4.20:
+    resolution: {integrity: sha512-KTEngal0aiUvNJ6I1Chk5Ew5XqChsFsxP4GKAYXWb99zKJWjNU72p2FWEOmZWHxHcqtniOJsgnpd3zizdpfEag==}
     dev: true
 
   /@xobotyi/scrollbar-width@1.9.5:
@@ -7648,7 +7748,7 @@ packages:
       es-errors: 1.3.0
       get-intrinsic: 1.2.4
       is-array-buffer: 3.0.4
-      is-shared-array-buffer: 1.0.2
+      is-shared-array-buffer: 1.0.3
     dev: true
 
   /assert@2.1.0:
@@ -7879,8 +7979,8 @@ packages:
     engines: {node: ^6 || ^7 || ^8 || ^9 || ^10 || ^11 || ^12 || >=13.7}
     hasBin: true
     dependencies:
-      caniuse-lite: 1.0.30001588
-      electron-to-chromium: 1.4.677
+      caniuse-lite: 1.0.30001591
+      electron-to-chromium: 1.4.682
       node-releases: 2.0.14
       update-browserslist-db: 1.0.13(browserslist@4.23.0)
     dev: true
@@ -7947,8 +8047,8 @@ packages:
     engines: {node: '>=6'}
     dev: true
 
-  /caniuse-lite@1.0.30001588:
-    resolution: {integrity: sha512-+hVY9jE44uKLkH0SrUTqxjxqNTOWHsbnQDIKjwkZ3lNTzUUVdBLBGXtj/q5Mp5u98r3droaZAewQuEDzjQdZlQ==}
+  /caniuse-lite@1.0.30001591:
+    resolution: {integrity: sha512-PCzRMei/vXjJyL5mJtzNiUCKP59dm8Apqc3PH8gJkMnMXZGox93RbE76jHsmLwmIo6/3nsYIpJtx0O7u5PqFuQ==}
     dev: true
 
   /chai@4.4.1:
@@ -7964,7 +8064,7 @@ packages:
       type-detect: 4.0.8
     dev: true
 
-  /chakra-react-select@4.7.6(@chakra-ui/form-control@2.2.0)(@chakra-ui/icon@3.2.0)(@chakra-ui/layout@2.3.1)(@chakra-ui/media-query@3.3.0)(@chakra-ui/menu@2.2.1)(@chakra-ui/spinner@2.1.0)(@chakra-ui/system@2.6.2)(@emotion/react@11.11.3)(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+  /chakra-react-select@4.7.6(@chakra-ui/form-control@2.2.0)(@chakra-ui/icon@3.2.0)(@chakra-ui/layout@2.3.1)(@chakra-ui/media-query@3.3.0)(@chakra-ui/menu@2.2.1)(@chakra-ui/spinner@2.1.0)(@chakra-ui/system@2.6.2)(@emotion/react@11.11.3)(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-ZL43hyXPnWf1g/HjsZDecbeJ4F2Q6tTPYJozlKWkrQ7lIX7ORP0aZYwmc5/Wly4UNzMimj2Vuosl6MmIXH+G2g==}
     peerDependencies:
       '@chakra-ui/form-control': ^2.0.0
@@ -7982,13 +8082,13 @@ packages:
       '@chakra-ui/icon': 3.2.0(@chakra-ui/system@2.6.2)(react@18.2.0)
       '@chakra-ui/layout': 2.3.1(@chakra-ui/system@2.6.2)(react@18.2.0)
       '@chakra-ui/media-query': 3.3.0(@chakra-ui/system@2.6.2)(react@18.2.0)
-      '@chakra-ui/menu': 2.2.1(@chakra-ui/system@2.6.2)(framer-motion@11.0.5)(react@18.2.0)
+      '@chakra-ui/menu': 2.2.1(@chakra-ui/system@2.6.2)(framer-motion@11.0.6)(react@18.2.0)
       '@chakra-ui/spinner': 2.1.0(@chakra-ui/system@2.6.2)(react@18.2.0)
       '@chakra-ui/system': 2.6.2(@emotion/react@11.11.3)(@emotion/styled@11.11.0)(react@18.2.0)
-      '@emotion/react': 11.11.3(@types/react@18.2.57)(react@18.2.0)
+      '@emotion/react': 11.11.3(@types/react@18.2.59)(react@18.2.0)
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
-      react-select: 5.7.7(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      react-select: 5.7.7(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
     transitivePeerDependencies:
       - '@types/react'
     dev: false
@@ -8325,7 +8425,7 @@ packages:
   /css-box-model@1.2.1:
     resolution: {integrity: sha512-a7Vr4Q/kd/aw96bnJG332W9V9LkJO69JRcaCYDUqjp6/z0w6VcZjgAcTbgFxEPfBgdnAwlh3iwu+hLopa+flJw==}
     dependencies:
-      tiny-invariant: 1.3.1
+      tiny-invariant: 1.3.3
     dev: false
 
   /css-in-js-utils@3.1.0:
@@ -8680,8 +8780,8 @@ packages:
       jake: 10.8.7
     dev: true
 
-  /electron-to-chromium@1.4.677:
-    resolution: {integrity: sha512-erDa3CaDzwJOpyvfKhOiJjBVNnMM0qxHq47RheVVwsSQrgBA9ZSGV9kdaOfZDPXcHzhG7lBxhj6A7KvfLJBd6Q==}
+  /electron-to-chromium@1.4.682:
+    resolution: {integrity: sha512-oCglfs8yYKs9RQjJFOHonSnhikPK3y+0SvSYc/YpYJV//6rqc0/hbwd0c7vgK4vrl6y2gJAwjkhkSGWK+z4KRA==}
     dev: true
 
   /emoji-regex@8.0.0:
@@ -8781,7 +8881,7 @@ packages:
       is-callable: 1.2.7
       is-negative-zero: 2.0.3
       is-regex: 1.1.4
-      is-shared-array-buffer: 1.0.2
+      is-shared-array-buffer: 1.0.3
       is-string: 1.0.7
       is-typed-array: 1.1.13
       is-weakref: 1.0.2
@@ -8795,7 +8895,7 @@ packages:
       string.prototype.trimend: 1.0.7
       string.prototype.trimstart: 1.0.7
       typed-array-buffer: 1.0.2
-      typed-array-byte-length: 1.0.0
+      typed-array-byte-length: 1.0.1
       typed-array-byte-offset: 1.0.2
       typed-array-length: 1.0.5
       unbox-primitive: 1.0.2
@@ -8970,13 +9070,13 @@ packages:
       source-map: 0.6.1
     dev: true
 
-  /eslint-config-prettier@9.1.0(eslint@8.56.0):
+  /eslint-config-prettier@9.1.0(eslint@8.57.0):
     resolution: {integrity: sha512-NSWl5BFQWEPi1j4TjVNItzYV7dZXZ+wP6I6ZhrBGpChQhZRUaElihE9uRRkcbRnNb76UMKDF3r+WTmNcGPKsqw==}
     hasBin: true
     peerDependencies:
       eslint: '>=7.0.0'
     dependencies:
-      eslint: 8.56.0
+      eslint: 8.57.0
     dev: true
 
   /eslint-import-resolver-node@0.3.9:
@@ -8989,8 +9089,8 @@ packages:
       - supports-color
     dev: true
 
-  /eslint-module-utils@2.8.0(@typescript-eslint/parser@7.0.2)(eslint-import-resolver-node@0.3.9)(eslint@8.56.0):
-    resolution: {integrity: sha512-aWajIYfsqCKRDgUfjEXNN/JlrzauMuSEy5sbd7WXbtW3EH6A6MpwEh42c7qD+MqQo9QMJ6fWLAeIJynx0g6OAw==}
+  /eslint-module-utils@2.8.1(@typescript-eslint/parser@7.1.0)(eslint-import-resolver-node@0.3.9)(eslint@8.57.0):
+    resolution: {integrity: sha512-rXDXR3h7cs7dy9RNpUlQf80nX31XWJEyGq1tRMo+6GsO5VmTe4UTwtmonAD4ZkAsrfMVDA2wlGJ3790Ys+D49Q==}
     engines: {node: '>=4'}
     peerDependencies:
       '@typescript-eslint/parser': '*'
@@ -9010,9 +9110,9 @@ packages:
       eslint-import-resolver-webpack:
         optional: true
     dependencies:
-      '@typescript-eslint/parser': 7.0.2(eslint@8.56.0)(typescript@5.3.3)
+      '@typescript-eslint/parser': 7.1.0(eslint@8.57.0)(typescript@5.3.3)
       debug: 3.2.7
-      eslint: 8.56.0
+      eslint: 8.57.0
       eslint-import-resolver-node: 0.3.9
     transitivePeerDependencies:
       - supports-color
@@ -9026,7 +9126,7 @@ packages:
       requireindex: 1.1.0
     dev: true
 
-  /eslint-plugin-import@2.29.1(@typescript-eslint/parser@7.0.2)(eslint@8.56.0):
+  /eslint-plugin-import@2.29.1(@typescript-eslint/parser@7.1.0)(eslint@8.57.0):
     resolution: {integrity: sha512-BbPC0cuExzhiMo4Ff1BTVwHpjjv28C5R+btTOGaCRC7UEz801up0JadwkeSk5Ued6TG34uaczuVuH6qyy5YUxw==}
     engines: {node: '>=4'}
     peerDependencies:
@@ -9036,16 +9136,16 @@ packages:
       '@typescript-eslint/parser':
         optional: true
     dependencies:
-      '@typescript-eslint/parser': 7.0.2(eslint@8.56.0)(typescript@5.3.3)
+      '@typescript-eslint/parser': 7.1.0(eslint@8.57.0)(typescript@5.3.3)
       array-includes: 3.1.7
       array.prototype.findlastindex: 1.2.4
       array.prototype.flat: 1.3.2
       array.prototype.flatmap: 1.3.2
       debug: 3.2.7
       doctrine: 2.1.0
-      eslint: 8.56.0
+      eslint: 8.57.0
       eslint-import-resolver-node: 0.3.9
-      eslint-module-utils: 2.8.0(@typescript-eslint/parser@7.0.2)(eslint-import-resolver-node@0.3.9)(eslint@8.56.0)
+      eslint-module-utils: 2.8.1(@typescript-eslint/parser@7.1.0)(eslint-import-resolver-node@0.3.9)(eslint@8.57.0)
       hasown: 2.0.1
       is-core-module: 2.13.1
       is-glob: 4.0.3
@@ -9061,34 +9161,34 @@ packages:
       - supports-color
     dev: true
 
-  /eslint-plugin-path@1.2.4(eslint@8.56.0):
+  /eslint-plugin-path@1.2.4(eslint@8.57.0):
     resolution: {integrity: sha512-CKEoNpXfqVDTIwSSrBv64a/kk6V1sTyyo5jS1UFZ/+z8+aFw4Bg2g4LmmLEAkP6LxMlCbg6kf3DmQ0Xkl/UpTA==}
     engines: {node: '>= 12.22.0'}
     peerDependencies:
       eslint: '>=6.0.0'
     dependencies:
-      eslint: 8.56.0
+      eslint: 8.57.0
       load-tsconfig: 0.2.5
     dev: true
 
-  /eslint-plugin-react-hooks@4.6.0(eslint@8.56.0):
+  /eslint-plugin-react-hooks@4.6.0(eslint@8.57.0):
     resolution: {integrity: sha512-oFc7Itz9Qxh2x4gNHStv3BqJq54ExXmfC+a1NjAta66IAN87Wu0R/QArgIS9qKzX3dXKPI9H5crl9QchNMY9+g==}
     engines: {node: '>=10'}
     peerDependencies:
       eslint: ^3.0.0 || ^4.0.0 || ^5.0.0 || ^6.0.0 || ^7.0.0 || ^8.0.0-0
     dependencies:
-      eslint: 8.56.0
+      eslint: 8.57.0
     dev: true
 
-  /eslint-plugin-react-refresh@0.4.5(eslint@8.56.0):
+  /eslint-plugin-react-refresh@0.4.5(eslint@8.57.0):
     resolution: {integrity: sha512-D53FYKJa+fDmZMtriODxvhwrO+IOqrxoEo21gMA0sjHdU6dPVH4OhyFip9ypl8HOF5RV5KdTo+rBQLvnY2cO8w==}
     peerDependencies:
       eslint: '>=7'
     dependencies:
-      eslint: 8.56.0
+      eslint: 8.57.0
     dev: true
 
-  /eslint-plugin-react@7.33.2(eslint@8.56.0):
+  /eslint-plugin-react@7.33.2(eslint@8.57.0):
     resolution: {integrity: sha512-73QQMKALArI8/7xGLNI/3LylrEYrlKZSb5C9+q3OtOewTnMQi5cT+aE9E41sLCmli3I9PGGmD1yiZydyo4FEPw==}
     engines: {node: '>=4'}
     peerDependencies:
@@ -9099,7 +9199,7 @@ packages:
       array.prototype.tosorted: 1.1.3
       doctrine: 2.1.0
       es-iterator-helpers: 1.0.17
-      eslint: 8.56.0
+      eslint: 8.57.0
       estraverse: 5.3.0
       jsx-ast-utils: 3.3.5
       minimatch: 3.1.2
@@ -9113,23 +9213,23 @@ packages:
       string.prototype.matchall: 4.0.10
     dev: true
 
-  /eslint-plugin-simple-import-sort@12.0.0(eslint@8.56.0):
+  /eslint-plugin-simple-import-sort@12.0.0(eslint@8.57.0):
     resolution: {integrity: sha512-8o0dVEdAkYap0Cn5kNeklaKcT1nUsa3LITWEuFk3nJifOoD+5JQGoyDUW2W/iPWwBsNBJpyJS9y4je/BgxLcyQ==}
     peerDependencies:
       eslint: '>=5.0.0'
     dependencies:
-      eslint: 8.56.0
+      eslint: 8.57.0
     dev: true
 
-  /eslint-plugin-storybook@0.8.0(eslint@8.56.0)(typescript@5.3.3):
+  /eslint-plugin-storybook@0.8.0(eslint@8.57.0)(typescript@5.3.3):
     resolution: {integrity: sha512-CZeVO5EzmPY7qghO2t64oaFM+8FTaD4uzOEjHKp516exyTKo+skKAL9GI3QALS2BXhyALJjNtwbmr1XinGE8bA==}
     engines: {node: '>= 18'}
     peerDependencies:
       eslint: '>=6'
     dependencies:
       '@storybook/csf': 0.0.1
-      '@typescript-eslint/utils': 5.62.0(eslint@8.56.0)(typescript@5.3.3)
-      eslint: 8.56.0
+      '@typescript-eslint/utils': 5.62.0(eslint@8.57.0)(typescript@5.3.3)
+      eslint: 8.57.0
       requireindex: 1.2.0
       ts-dedent: 2.2.0
     transitivePeerDependencies:
@@ -9137,7 +9237,7 @@ packages:
       - typescript
     dev: true
 
-  /eslint-plugin-unused-imports@3.1.0(@typescript-eslint/eslint-plugin@7.0.2)(eslint@8.56.0):
+  /eslint-plugin-unused-imports@3.1.0(@typescript-eslint/eslint-plugin@7.1.0)(eslint@8.57.0):
     resolution: {integrity: sha512-9l1YFCzXKkw1qtAru1RWUtG2EVDZY0a0eChKXcL+EZ5jitG7qxdctu4RnvhOJHv4xfmUf7h+JJPINlVpGhZMrw==}
     engines: {node: ^12.22.0 || ^14.17.0 || >=16.0.0}
     peerDependencies:
@@ -9147,8 +9247,8 @@ packages:
       '@typescript-eslint/eslint-plugin':
         optional: true
     dependencies:
-      '@typescript-eslint/eslint-plugin': 7.0.2(@typescript-eslint/parser@7.0.2)(eslint@8.56.0)(typescript@5.3.3)
-      eslint: 8.56.0
+      '@typescript-eslint/eslint-plugin': 7.1.0(@typescript-eslint/parser@7.1.0)(eslint@8.57.0)(typescript@5.3.3)
+      eslint: 8.57.0
       eslint-rule-composer: 0.3.0
     dev: true
 
@@ -9178,15 +9278,15 @@ packages:
     engines: {node: ^12.22.0 || ^14.17.0 || >=16.0.0}
     dev: true
 
-  /eslint@8.56.0:
-    resolution: {integrity: sha512-Go19xM6T9puCOWntie1/P997aXxFsOi37JIHRWI514Hc6ZnaHGKY9xFhrU65RT6CcBEzZoGG1e6Nq+DT04ZtZQ==}
+  /eslint@8.57.0:
+    resolution: {integrity: sha512-dZ6+mexnaTIbSBZWgou51U6OmzIhYM2VcNdtiTtI7qPNZm35Akpr0f6vtw3w1Kmn5PYo+tZVfh13WrhpS6oLqQ==}
     engines: {node: ^12.22.0 || ^14.17.0 || >=16.0.0}
     hasBin: true
     dependencies:
-      '@eslint-community/eslint-utils': 4.4.0(eslint@8.56.0)
+      '@eslint-community/eslint-utils': 4.4.0(eslint@8.57.0)
       '@eslint-community/regexpp': 4.10.0
       '@eslint/eslintrc': 2.1.4
-      '@eslint/js': 8.56.0
+      '@eslint/js': 8.57.0
       '@humanwhocodes/config-array': 0.11.14
       '@humanwhocodes/module-importer': 1.0.1
       '@nodelib/fs.walk': 1.2.8
@@ -9308,7 +9408,7 @@ packages:
       human-signals: 5.0.0
       is-stream: 3.0.0
       merge-stream: 2.0.0
-      npm-run-path: 5.2.0
+      npm-run-path: 5.3.0
       onetime: 6.0.0
       signal-exit: 4.1.0
       strip-final-newline: 3.0.0
@@ -9558,17 +9658,17 @@ packages:
     resolution: {integrity: sha512-CYcENa+FtcUKLmhhqyctpclsq7QF38pKjZHsGNiSQF5r4FtoKDWabFDl3hzaEQMvT1LHEysw5twgLvpYYb4vbw==}
     engines: {node: ^10.12.0 || >=12.0.0}
     dependencies:
-      flatted: 3.3.0
+      flatted: 3.3.1
       keyv: 4.5.4
       rimraf: 3.0.2
     dev: true
 
-  /flatted@3.3.0:
-    resolution: {integrity: sha512-noqGuLw158+DuD9UPRKHpJ2hGxpFyDlYYrfM0mWt4XhT4n0lwzTLh70Tkdyy4kyTmyTT9Bv7bWAJqw7cgkEXDg==}
+  /flatted@3.3.1:
+    resolution: {integrity: sha512-X8cqMLLie7KsNUDSdzeN8FYK9rEt4Dt67OsG/DNGnYTSDBG4uFAJFBnUeiV+zCVAvwFy56IjM9sH51jVaEhNxw==}
     dev: true
 
-  /flow-parser@0.229.0:
-    resolution: {integrity: sha512-mOYmMuvJwAo/CvnMFEq4SHftq7E5188hYMTTxJyQOXk2nh+sgslRdYMw3wTthH+FMcFaZLtmBPuMu6IwztdoUQ==}
+  /flow-parser@0.229.2:
+    resolution: {integrity: sha512-T72XV2Izvl7yV6dhHhLaJ630Y6vOZJl6dnOS6dN0bPW9ExuREu7xGAf3omtcxX76POTuux9TJPu9ZpS48a/rdw==}
     engines: {node: '>=0.4.0'}
     dev: true
 
@@ -9649,6 +9749,24 @@ packages:
       '@emotion/is-prop-valid': 0.8.8
     dev: false
 
+  /framer-motion@11.0.6(react-dom@18.2.0)(react@18.2.0):
+    resolution: {integrity: sha512-BpO3mWF8UwxzO3Ca5AmSkrg14QYTeJa9vKgoLOoBdBdTPj0e81i1dMwnX6EQJXRieUx20uiDBXq8bA6y7N6b8Q==}
+    peerDependencies:
+      react: ^18.0.0
+      react-dom: ^18.0.0
+    peerDependenciesMeta:
+      react:
+        optional: true
+      react-dom:
+        optional: true
+    dependencies:
+      react: 18.2.0
+      react-dom: 18.2.0(react@18.2.0)
+      tslib: 2.6.2
+    optionalDependencies:
+      '@emotion/is-prop-valid': 0.8.8
+    dev: false
+
   /framesync@6.1.2:
     resolution: {integrity: sha512-jBTqhX6KaQVDyus8muwZbBeGGP0XgujBRbQ7gM7BRdS3CadCZIHiawyzYLnafYcvZIh5j8WE7cxZKFn7dXhu9g==}
     dependencies:
@@ -10057,16 +10175,16 @@ packages:
     resolution: {integrity: sha512-ygGZLjmXfPHj+ZWh6LwbC37l43MhfztxetbFCoYTM2VjkIUpeHgSNn7QIyVFj7YQ1Wl9Cbw5sholVJPzWvC2MQ==}
     dev: false
 
-  /i18next-http-backend@2.4.3:
-    resolution: {integrity: sha512-jo2M03O6n1/DNb51WSQ8PsQ0xEELzLZRdYUTbf17mLw3rVwnJF9hwNgMXvEFSxxb+N8dT+o0vtigA6s5mGWyPA==}
+  /i18next-http-backend@2.5.0:
+    resolution: {integrity: sha512-Z/aQsGZk1gSxt2/DztXk92DuDD20J+rNudT7ZCdTrNOiK8uQppfvdjq9+DFQfpAnFPn3VZS+KQIr1S/W1KxhpQ==}
     dependencies:
       cross-fetch: 4.0.0
     transitivePeerDependencies:
       - encoding
     dev: false
 
-  /i18next@23.9.0:
-    resolution: {integrity: sha512-f3MUciKqwzNV//mHG6EtdSlC65+nqH/3zK8sOSWqNV6FVu2tmHhF/rFOp9UF8S4m1odojtuipKaKJrP0Loh60g==}
+  /i18next@23.10.0:
+    resolution: {integrity: sha512-/TgHOqsa7/9abUKJjdPeydoyDc0oTi/7u9F8lMSj6ufg4cbC1Oj3f/Jja7zj7WRIhEQKB7Q4eN6y68I9RDxxGQ==}
     dependencies:
       '@babel/runtime': 7.23.9
     dev: false
@@ -10358,8 +10476,9 @@ packages:
     resolution: {integrity: sha512-+2cnTEZeY5z/iXGbLhPrOAaK/Mau5k5eXq9j14CpRTftq0pAJu2MwVRSZhyZWBzx3o6X795Lz6Bpb6R0GKf37g==}
     dev: true
 
-  /is-shared-array-buffer@1.0.2:
-    resolution: {integrity: sha512-sqN2UDu1/0y6uvXyStCOzyhAjCSlHceFoMKJW8W9EU9cvic/QdsZ0kEU93HEy3IUEFZIiH/3w+AH/UQbPHNdhA==}
+  /is-shared-array-buffer@1.0.3:
+    resolution: {integrity: sha512-nA2hv5XIhLR3uVzDDfCIknerhx8XUKnstuOERPNNIinXG7v9u+ohXF67vxm4TPTEPU6lm61ZkwP3c9PCB97rhg==}
+    engines: {node: '>= 0.4'}
     dependencies:
       call-bind: 1.0.7
     dev: true
@@ -10514,7 +10633,7 @@ packages:
     dependencies:
       '@jest/types': 29.6.3
       '@types/graceful-fs': 4.1.9
-      '@types/node': 20.11.19
+      '@types/node': 20.11.20
       anymatch: 3.1.3
       fb-watchman: 2.0.2
       graceful-fs: 4.2.11
@@ -10532,7 +10651,7 @@ packages:
     engines: {node: ^10.13.0 || ^12.13.0 || ^14.15.0 || >=15.0.0}
     dependencies:
       '@jest/types': 27.5.1
-      '@types/node': 20.11.19
+      '@types/node': 20.11.20
     dev: true
 
   /jest-regex-util@29.6.3:
@@ -10545,7 +10664,7 @@ packages:
     engines: {node: ^14.15.0 || ^16.10.0 || >=18.0.0}
     dependencies:
       '@jest/types': 29.6.3
-      '@types/node': 20.11.19
+      '@types/node': 20.11.20
       chalk: 4.1.2
       ci-info: 3.9.0
       graceful-fs: 4.2.11
@@ -10556,7 +10675,7 @@ packages:
     resolution: {integrity: sha512-eIz2msL/EzL9UFTFFx7jBTkeZfku0yUAyZZZmJ93H2TYEiroIx2PQjEXcwYtYl8zXCxb+PAmA2hLIt/6ZEkPHw==}
     engines: {node: ^14.15.0 || ^16.10.0 || >=18.0.0}
     dependencies:
-      '@types/node': 20.11.19
+      '@types/node': 20.11.20
       jest-util: 29.7.0
       merge-stream: 2.0.0
       supports-color: 8.1.1
@@ -10597,8 +10716,8 @@ packages:
       argparse: 2.0.1
     dev: true
 
-  /jscodeshift@0.15.1(@babel/preset-env@7.23.9):
-    resolution: {integrity: sha512-hIJfxUy8Rt4HkJn/zZPU9ChKfKZM1342waJ1QC2e2YsPcWhM+3BJ4dcfQCzArTrk1jJeNLB341H+qOcEHRxJZg==}
+  /jscodeshift@0.15.2(@babel/preset-env@7.23.9):
+    resolution: {integrity: sha512-FquR7Okgmc4Sd0aEDwqho3rEiKR3BdvuG9jfdHjLJ6JQoWSMpavug3AoIfnfWhxFlf+5pzQh8qjqz0DWFrNQzA==}
     hasBin: true
     peerDependencies:
       '@babel/preset-env': ^7.1.6
@@ -10619,7 +10738,7 @@ packages:
       '@babel/register': 7.23.7(@babel/core@7.23.9)
       babel-core: 7.0.0-bridge.0(@babel/core@7.23.9)
       chalk: 4.1.2
-      flow-parser: 0.229.0
+      flow-parser: 0.229.2
       graceful-fs: 4.2.11
       micromatch: 4.0.5
       neo-async: 2.6.2
@@ -10738,7 +10857,7 @@ packages:
     engines: {node: '>= 8'}
     dev: false
 
-  /knip@5.0.2(@types/node@20.11.19)(typescript@5.3.3):
+  /knip@5.0.2(@types/node@20.11.20)(typescript@5.3.3):
     resolution: {integrity: sha512-ylmXi/CaR1rjOl8KqLsei7075cCsHttMNFwoYlBM7WMvd2Rd4oOfic9KqJFkDONXedsEsiiwnI3+u6GT6KOUuw==}
     engines: {node: '>=18.6.0'}
     hasBin: true
@@ -10753,7 +10872,7 @@ packages:
       '@pnpm/logger': 5.0.0
       '@pnpm/workspace.pkgs-graph': 2.0.15(@pnpm/logger@5.0.0)
       '@snyk/github-codeowners': 1.1.0
-      '@types/node': 20.11.19
+      '@types/node': 20.11.20
       '@types/picomatch': 2.3.3
       easy-table: 1.2.0
       fast-glob: 3.3.2
@@ -10836,7 +10955,7 @@ packages:
     resolution: {integrity: sha512-ok6z3qlYyCDS4ZEU27HaU6x/xZa9Whf8jD4ptH5UZTQYZVYeb9bnZ3ojVhiJNLiXK1Hfc0GNbLXcmZ5plLDDBg==}
     engines: {node: '>=14'}
     dependencies:
-      mlly: 1.5.0
+      mlly: 1.6.1
       pkg-types: 1.0.3
     dev: true
 
@@ -11179,8 +11298,8 @@ packages:
     hasBin: true
     dev: true
 
-  /mlly@1.5.0:
-    resolution: {integrity: sha512-NPVQvAY1xr1QoVeG0cy8yUYC7FQcOx6evl/RjT1wL5FvzPnzOysoqB/jmx/DhssT2dYa8nxECLAaFI/+gVLhDQ==}
+  /mlly@1.6.1:
+    resolution: {integrity: sha512-vLgaHvaeunuOXHSmEbZ9izxPx3USsk8KCQ8iC+aTlp5sKRSoZvwhHh5L9VbKSaVC6sJDqbyohIS76E2VmHIPAA==}
     dependencies:
       acorn: 8.11.3
       pathe: 1.1.2
@@ -11384,8 +11503,8 @@ packages:
       path-key: 3.1.1
     dev: true
 
-  /npm-run-path@5.2.0:
-    resolution: {integrity: sha512-W4/tgAXFqFA0iL7fk0+uQ3g7wkL8xJmx3XdK0VGb4cHW//eZTtKGvFBBoRKVTpY7n6ze4NL9ly7rgXcHufqXKg==}
+  /npm-run-path@5.3.0:
+    resolution: {integrity: sha512-ppwTtiJZq0O/ai0z7yfudtBpWIoxM8yE6nHi1X47eFR2EWORqfbu6CnPlNsjeN683eT0qG6H/Pyf9fCcvjnnnQ==}
     engines: {node: ^12.20.0 || ^14.13.1 || >=16.0.0}
     dependencies:
       path-key: 4.0.0
@@ -11814,7 +11933,7 @@ packages:
     resolution: {integrity: sha512-nN7pYi0AQqJnoLPC9eHFQ8AcyaixBUOwvqc5TDnIKCMEE6I0y8P7OKA7fPexsXGCGxQDl/cmrLAp26LhcwxZ4A==}
     dependencies:
       jsonc-parser: 3.2.1
-      mlly: 1.5.0
+      mlly: 1.6.1
       pathe: 1.1.2
     dev: true
 
@@ -12005,9 +12124,9 @@ packages:
       side-channel: 1.0.5
     dev: true
 
-  /query-string@8.2.0:
-    resolution: {integrity: sha512-tUZIw8J0CawM5wyGBiDOAp7ObdRQh4uBor/fUR9ZjmbZVvw95OD9If4w3MQxr99rg0DJZ/9CIORcpEqU5hQG7g==}
-    engines: {node: '>=14.16'}
+  /query-string@9.0.0:
+    resolution: {integrity: sha512-4EWwcRGsO2H+yzq6ddHcVqkCQ2EFUSfDMEjF8ryp8ReymyZhIuaFRGLomeOQLkrzacMHoyky2HW0Qe30UbzkKw==}
+    engines: {node: '>=18'}
     dependencies:
       decode-uri-component: 0.4.1
       filter-obj: 5.1.0
@@ -12159,6 +12278,25 @@ packages:
       use-sidecar: 1.1.2(@types/react@18.2.57)(react@18.2.0)
     dev: false
 
+  /react-focus-lock@2.11.1(@types/react@18.2.59)(react@18.2.0):
+    resolution: {integrity: sha512-IXLwnTBrLTlKTpASZXqqXJ8oymWrgAlOfuuDYN4XCuN1YJ72dwX198UCaF1QqGUk5C3QOnlMik//n3ufcfe8Ig==}
+    peerDependencies:
+      '@types/react': ^16.8.0 || ^17.0.0 || ^18.0.0
+      react: ^16.8.0 || ^17.0.0 || ^18.0.0
+    peerDependenciesMeta:
+      '@types/react':
+        optional: true
+    dependencies:
+      '@babel/runtime': 7.23.9
+      '@types/react': 18.2.59
+      focus-lock: 1.3.3
+      prop-types: 15.8.1
+      react: 18.2.0
+      react-clientside-effect: 1.2.6(react@18.2.0)
+      use-callback-ref: 1.3.1(@types/react@18.2.59)(react@18.2.0)
+      use-sidecar: 1.1.2(@types/react@18.2.59)(react@18.2.0)
+    dev: false
+
   /react-hook-form@7.50.1(react@18.2.0):
     resolution: {integrity: sha512-3PCY82oE0WgeOgUtIr3nYNNtNvqtJ7BZjsbxh6TnYNbXButaD5WpjOmTjdxZfheuHKR68qfeFnEDVYoSSFPMTQ==}
     engines: {node: '>=12.22.0'}
@@ -12178,7 +12316,7 @@ packages:
       react-dom: 18.2.0(react@18.2.0)
     dev: false
 
-  /react-i18next@14.0.5(i18next@23.9.0)(react-dom@18.2.0)(react@18.2.0):
+  /react-i18next@14.0.5(i18next@23.10.0)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-5+bQSeEtgJrMBABBL5lO7jPdSNAbeAZ+MlFWDw//7FnVacuVu3l9EeWFzBQvZsKy+cihkbThWOAThEdH8YjGEw==}
     peerDependencies:
       i18next: '>= 23.2.3'
@@ -12193,7 +12331,7 @@ packages:
     dependencies:
       '@babel/runtime': 7.23.9
       html-parse-stringify: 3.0.1
-      i18next: 23.9.0
+      i18next: 23.10.0
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     dev: false
@@ -12244,7 +12382,7 @@ packages:
       scheduler: 0.23.0
     dev: false
 
-  /react-redux@9.1.0(@types/react@18.2.57)(react@18.2.0)(redux@5.0.1):
+  /react-redux@9.1.0(@types/react@18.2.59)(react@18.2.0)(redux@5.0.1):
     resolution: {integrity: sha512-6qoDzIO+gbrza8h3hjMA9aq4nwVFCKFtY2iLxCtVT38Swyy2C/dJCGBXHeHLtx6qlg/8qzc2MrhOeduf5K32wQ==}
     peerDependencies:
       '@types/react': ^18.2.25
@@ -12259,7 +12397,7 @@ packages:
       redux:
         optional: true
     dependencies:
-      '@types/react': 18.2.57
+      '@types/react': 18.2.59
       '@types/use-sync-external-store': 0.0.3
       react: 18.2.0
       redux: 5.0.1
@@ -12285,8 +12423,24 @@ packages:
       react: 18.2.0
       react-style-singleton: 2.2.1(@types/react@18.2.57)(react@18.2.0)
       tslib: 2.6.2
+    dev: false
 
-  /react-remove-scroll@2.5.5(@types/react@18.2.57)(react@18.2.0):
+  /react-remove-scroll-bar@2.3.5(@types/react@18.2.59)(react@18.2.0):
+    resolution: {integrity: sha512-3cqjOqg6s0XbOjWvmasmqHch+RLxIEk2r/70rzGXuz3iIGQsQheEQyqYCBb5EECoD01Vo2SIbDqW4paLeLTASw==}
+    engines: {node: '>=10'}
+    peerDependencies:
+      '@types/react': ^16.8.0 || ^17.0.0 || ^18.0.0
+      react: ^16.8.0 || ^17.0.0 || ^18.0.0
+    peerDependenciesMeta:
+      '@types/react':
+        optional: true
+    dependencies:
+      '@types/react': 18.2.59
+      react: 18.2.0
+      react-style-singleton: 2.2.1(@types/react@18.2.59)(react@18.2.0)
+      tslib: 2.6.2
+
+  /react-remove-scroll@2.5.5(@types/react@18.2.59)(react@18.2.0):
     resolution: {integrity: sha512-ImKhrzJJsyXJfBZ4bzu8Bwpka14c/fQt0k+cyFp/PBhTfyDnU5hjOtM4AG/0AMyy8oKzOTR0lDgJIM7pYXI0kw==}
     engines: {node: '>=10'}
     peerDependencies:
@@ -12296,13 +12450,13 @@ packages:
       '@types/react':
         optional: true
     dependencies:
-      '@types/react': 18.2.57
+      '@types/react': 18.2.59
       react: 18.2.0
-      react-remove-scroll-bar: 2.3.5(@types/react@18.2.57)(react@18.2.0)
-      react-style-singleton: 2.2.1(@types/react@18.2.57)(react@18.2.0)
+      react-remove-scroll-bar: 2.3.5(@types/react@18.2.59)(react@18.2.0)
+      react-style-singleton: 2.2.1(@types/react@18.2.59)(react@18.2.0)
       tslib: 2.6.2
-      use-callback-ref: 1.3.1(@types/react@18.2.57)(react@18.2.0)
-      use-sidecar: 1.1.2(@types/react@18.2.57)(react@18.2.0)
+      use-callback-ref: 1.3.1(@types/react@18.2.59)(react@18.2.0)
+      use-sidecar: 1.1.2(@types/react@18.2.59)(react@18.2.0)
     dev: true
 
   /react-remove-scroll@2.5.7(@types/react@18.2.57)(react@18.2.0):
@@ -12324,8 +12478,27 @@ packages:
       use-sidecar: 1.1.2(@types/react@18.2.57)(react@18.2.0)
     dev: false
 
-  /react-resizable-panels@2.0.9(react-dom@18.2.0)(react@18.2.0):
-    resolution: {integrity: sha512-ZylBvs7oG7Y/INWw3oYGolqgpFvoPW8MPeg9l1fURDeKpxrmUuCHBUmPj47BdZ11MODImu3kZYXG85rbySab7w==}
+  /react-remove-scroll@2.5.7(@types/react@18.2.59)(react@18.2.0):
+    resolution: {integrity: sha512-FnrTWO4L7/Bhhf3CYBNArEG/yROV0tKmTv7/3h9QCFvH6sndeFf1wPqOcbFVu5VAulS5dV1wGT3GZZ/1GawqiA==}
+    engines: {node: '>=10'}
+    peerDependencies:
+      '@types/react': ^16.8.0 || ^17.0.0 || ^18.0.0
+      react: ^16.8.0 || ^17.0.0 || ^18.0.0
+    peerDependenciesMeta:
+      '@types/react':
+        optional: true
+    dependencies:
+      '@types/react': 18.2.59
+      react: 18.2.0
+      react-remove-scroll-bar: 2.3.5(@types/react@18.2.59)(react@18.2.0)
+      react-style-singleton: 2.2.1(@types/react@18.2.59)(react@18.2.0)
+      tslib: 2.6.2
+      use-callback-ref: 1.3.1(@types/react@18.2.59)(react@18.2.0)
+      use-sidecar: 1.1.2(@types/react@18.2.59)(react@18.2.0)
+    dev: false
+
+  /react-resizable-panels@2.0.11(react-dom@18.2.0)(react@18.2.0):
+    resolution: {integrity: sha512-tA3OvGFEK/U9rKuEg6TpXcr+i+cN5X8B4UIvs7jqr5lby629pDTGvqRjo1EJLhBpRZfkg0Zz1INJlSYigaS99g==}
     peerDependencies:
       react: ^16.14.0 || ^17.0.0 || ^18.0.0
       react-dom: ^16.14.0 || ^17.0.0 || ^18.0.0
@@ -12334,7 +12507,7 @@ packages:
       react-dom: 18.2.0(react@18.2.0)
     dev: false
 
-  /react-select@5.7.7(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+  /react-select@5.7.7(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-HhashZZJDRlfF/AKj0a0Lnfs3sRdw/46VJIRd8IbB9/Ovr74+ZIwkAdSBjSPXsFMG+u72c5xShqwLSKIJllzqw==}
     peerDependencies:
       react: ^16.8.0 || ^17.0.0 || ^18.0.0
@@ -12342,7 +12515,7 @@ packages:
     dependencies:
       '@babel/runtime': 7.23.9
       '@emotion/cache': 11.11.0
-      '@emotion/react': 11.11.3(@types/react@18.2.57)(react@18.2.0)
+      '@emotion/react': 11.11.3(@types/react@18.2.59)(react@18.2.0)
       '@floating-ui/dom': 1.6.3
       '@types/react-transition-group': 4.4.10
       memoize-one: 6.0.0
@@ -12350,12 +12523,12 @@ packages:
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
       react-transition-group: 4.4.5(react-dom@18.2.0)(react@18.2.0)
-      use-isomorphic-layout-effect: 1.1.2(@types/react@18.2.57)(react@18.2.0)
+      use-isomorphic-layout-effect: 1.1.2(@types/react@18.2.59)(react@18.2.0)
     transitivePeerDependencies:
       - '@types/react'
     dev: false
 
-  /react-select@5.8.0(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+  /react-select@5.8.0(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-TfjLDo58XrhP6VG5M/Mi56Us0Yt8X7xD6cDybC7yoRMUNm7BGO7qk8J0TLQOua/prb8vUOtsfnXZwfm30HGsAA==}
     peerDependencies:
       react: ^16.8.0 || ^17.0.0 || ^18.0.0
@@ -12363,7 +12536,7 @@ packages:
     dependencies:
       '@babel/runtime': 7.23.9
       '@emotion/cache': 11.11.0
-      '@emotion/react': 11.11.3(@types/react@18.2.57)(react@18.2.0)
+      '@emotion/react': 11.11.3(@types/react@18.2.59)(react@18.2.0)
       '@floating-ui/dom': 1.6.3
       '@types/react-transition-group': 4.4.10
       memoize-one: 6.0.0
@@ -12371,7 +12544,7 @@ packages:
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
       react-transition-group: 4.4.5(react-dom@18.2.0)(react@18.2.0)
-      use-isomorphic-layout-effect: 1.1.2(@types/react@18.2.57)(react@18.2.0)
+      use-isomorphic-layout-effect: 1.1.2(@types/react@18.2.59)(react@18.2.0)
     transitivePeerDependencies:
       - '@types/react'
     dev: false
@@ -12391,6 +12564,23 @@ packages:
       invariant: 2.2.4
       react: 18.2.0
       tslib: 2.6.2
+    dev: false
+
+  /react-style-singleton@2.2.1(@types/react@18.2.59)(react@18.2.0):
+    resolution: {integrity: sha512-ZWj0fHEMyWkHzKYUr2Bs/4zU6XLmq9HsgBURm7g5pAVfyn49DgUiNgY2d4lXRlYSiCif9YBGpQleewkcqddc7g==}
+    engines: {node: '>=10'}
+    peerDependencies:
+      '@types/react': ^16.8.0 || ^17.0.0 || ^18.0.0
+      react: ^16.8.0 || ^17.0.0 || ^18.0.0
+    peerDependenciesMeta:
+      '@types/react':
+        optional: true
+    dependencies:
+      '@types/react': 18.2.59
+      get-nonce: 1.0.1
+      invariant: 2.2.4
+      react: 18.2.0
+      tslib: 2.6.2
 
   /react-transition-group@4.4.5(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-pZcd1MCJoiKiBR2NRxeCRg13uCXbydPnmB4EOeRrY7480qNWO8IIgQG6zlDkm6uRMsURXPuKq0GWtiM59a5Q6g==}
@@ -12440,8 +12630,8 @@ packages:
       tslib: 2.6.2
     dev: false
 
-  /react-virtuoso@4.7.0(react-dom@18.2.0)(react@18.2.0):
-    resolution: {integrity: sha512-cpgvI1rSOETGDMhqVAVDuH+XHbWO1uIGKv5I6l4CyC71xWYUeGrE5n7sgTZklROB4+Vbv85pcgfWloTlY48HGQ==}
+  /react-virtuoso@4.7.1(react-dom@18.2.0)(react@18.2.0):
+    resolution: {integrity: sha512-V1JIZLEwgX7R+YNkbY8dq6NcnIGKGWXe4mnMJJPsA2L4qeFKst0LY3mDk6sBCJyKRbMzYFxTZWyTT4QsA1JvVQ==}
     engines: {node: '>=10'}
     peerDependencies:
       react: '>=16 || >=17 || >= 18'
@@ -12457,18 +12647,18 @@ packages:
     dependencies:
       loose-envify: 1.4.0
 
-  /reactflow@11.10.4(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0):
+  /reactflow@11.10.4(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0):
     resolution: {integrity: sha512-0CApYhtYicXEDg/x2kvUHiUk26Qur8lAtTtiSlptNKuyEuGti6P1y5cS32YGaUoDMoCqkm/m+jcKkfMOvSCVRA==}
     peerDependencies:
       react: '>=17'
       react-dom: '>=17'
     dependencies:
-      '@reactflow/background': 11.3.9(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@reactflow/controls': 11.2.9(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@reactflow/core': 11.10.4(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@reactflow/minimap': 11.7.9(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@reactflow/node-resizer': 2.2.9(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
-      '@reactflow/node-toolbar': 1.3.9(@types/react@18.2.57)(react-dom@18.2.0)(react@18.2.0)
+      '@reactflow/background': 11.3.9(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@reactflow/controls': 11.2.9(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@reactflow/core': 11.10.4(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@reactflow/minimap': 11.7.9(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@reactflow/node-resizer': 2.2.9(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
+      '@reactflow/node-toolbar': 1.3.9(@types/react@18.2.59)(react-dom@18.2.0)(react@18.2.0)
       react: 18.2.0
       react-dom: 18.2.0(react@18.2.0)
     transitivePeerDependencies:
@@ -13492,8 +13682,8 @@ packages:
       readable-stream: 3.6.2
     dev: true
 
-  /tiny-invariant@1.3.1:
-    resolution: {integrity: sha512-AD5ih2NlSssTCwsMznbvwMZpJ1cbhkGd2uueNxzv2jDlEeZdU04JQfRnggJQ8DrcVBGjAsCKwFBbDlVNtEMlzw==}
+  /tiny-invariant@1.3.3:
+    resolution: {integrity: sha512-+FbBPE1o9QAYvviau/qC5SE3caw21q3xkvWKBtja5vgqOWIHHJ3ioaq1VPfn/Szqctz2bU/oYeKd9/z5BL+PVg==}
 
   /tinybench@2.6.0:
     resolution: {integrity: sha512-N8hW3PG/3aOoZAN5V/NSAEDz0ZixDSSt5b/a05iqtpgfLWMSVuCo7w0k2vVvEjdrIoeGqZzweX2WlyioNIHchA==}
@@ -13687,12 +13877,13 @@ packages:
       is-typed-array: 1.1.13
     dev: true
 
-  /typed-array-byte-length@1.0.0:
-    resolution: {integrity: sha512-Or/+kvLxNpeQ9DtSydonMxCx+9ZXOswtwJn17SNLvhptaXYDJvkFFP5zbfU/uLmvnBJlI4yrnXRxpdWH/M5tNA==}
+  /typed-array-byte-length@1.0.1:
+    resolution: {integrity: sha512-3iMJ9q0ao7WE9tWcaYKIptkNBuOIcZCCT0d4MRvuuH88fEoEH62IuQe0OtraD3ebQEoTRk8XCBoknUNc1Y67pw==}
     engines: {node: '>= 0.4'}
     dependencies:
       call-bind: 1.0.7
       for-each: 0.3.3
+      gopd: 1.0.1
       has-proto: 1.0.3
       is-typed-array: 1.1.13
     dev: true
@@ -13877,6 +14068,21 @@ packages:
       '@types/react': 18.2.57
       react: 18.2.0
       tslib: 2.6.2
+    dev: false
+
+  /use-callback-ref@1.3.1(@types/react@18.2.59)(react@18.2.0):
+    resolution: {integrity: sha512-Lg4Vx1XZQauB42Hw3kK7JM6yjVjgFmFC5/Ab797s79aARomD2nEErc4mCgM8EZrARLmmbWpi5DGCadmK50DcAQ==}
+    engines: {node: '>=10'}
+    peerDependencies:
+      '@types/react': ^16.8.0 || ^17.0.0 || ^18.0.0
+      react: ^16.8.0 || ^17.0.0 || ^18.0.0
+    peerDependenciesMeta:
+      '@types/react':
+        optional: true
+    dependencies:
+      '@types/react': 18.2.59
+      react: 18.2.0
+      tslib: 2.6.2
 
   /use-debounce@10.0.0(react@18.2.0):
     resolution: {integrity: sha512-XRjvlvCB46bah9IBXVnq/ACP2lxqXyZj0D9hj4K5OzNroMDpTEBg8Anuh1/UfRTRs7pLhQ+RiNxxwZu9+MVl1A==}
@@ -13897,7 +14103,7 @@ packages:
       react-dom: 18.2.0(react@18.2.0)
     dev: false
 
-  /use-isomorphic-layout-effect@1.1.2(@types/react@18.2.57)(react@18.2.0):
+  /use-isomorphic-layout-effect@1.1.2(@types/react@18.2.59)(react@18.2.0):
     resolution: {integrity: sha512-49L8yCO3iGT/ZF9QttjwLF/ZD9Iwto5LnH5LmEdk/6cFmXddqi2ulF0edxTwjj+7mqvpVVGQWvbXZdn32wRSHA==}
     peerDependencies:
       '@types/react': '*'
@@ -13906,7 +14112,7 @@ packages:
       '@types/react':
         optional: true
     dependencies:
-      '@types/react': 18.2.57
+      '@types/react': 18.2.59
       react: 18.2.0
     dev: false
 
@@ -13935,6 +14141,22 @@ packages:
       detect-node-es: 1.1.0
       react: 18.2.0
       tslib: 2.6.2
+    dev: false
+
+  /use-sidecar@1.1.2(@types/react@18.2.59)(react@18.2.0):
+    resolution: {integrity: sha512-epTbsLuzZ7lPClpz2TyryBfztm7m+28DlEv2ZCQ3MDr5ssiwyOwGH/e5F9CkfWjJ1t4clvI58yF822/GUkjjhw==}
+    engines: {node: '>=10'}
+    peerDependencies:
+      '@types/react': ^16.9.0 || ^17.0.0 || ^18.0.0
+      react: ^16.8.0 || ^17.0.0 || ^18.0.0
+    peerDependenciesMeta:
+      '@types/react':
+        optional: true
+    dependencies:
+      '@types/react': 18.2.59
+      detect-node-es: 1.1.0
+      react: 18.2.0
+      tslib: 2.6.2
 
   /use-sync-external-store@1.2.0(react@18.2.0):
     resolution: {integrity: sha512-eEgnFxGQ1Ife9bzYs6VLi8/4X6CObHMw9Qr9tPY43iKwsPw8xE8+EFsf/2cFZ5S3esXgpWgtSCtLNS41F+sKPA==}
@@ -14005,7 +14227,7 @@ packages:
       semver: 7.6.0
     dev: true
 
-  /vite-node@1.3.1(@types/node@20.11.19):
+  /vite-node@1.3.1(@types/node@20.11.20):
     resolution: {integrity: sha512-azbRrqRxlWTJEVbzInZCTchx0X69M/XPTCz4H+TLvlTcR/xH/3hkRqhOakT41fMJCMzXTu4UvegkZiEoJAWvng==}
     engines: {node: ^18.0.0 || >=20.0.0}
     hasBin: true
@@ -14014,7 +14236,7 @@ packages:
       debug: 4.3.4
       pathe: 1.1.2
       picocolors: 1.0.0
-      vite: 5.1.3(@types/node@20.11.19)
+      vite: 5.1.4(@types/node@20.11.20)
     transitivePeerDependencies:
       - '@types/node'
       - less
@@ -14026,16 +14248,16 @@ packages:
       - terser
     dev: true
 
-  /vite-plugin-css-injected-by-js@3.4.0(vite@5.1.3):
+  /vite-plugin-css-injected-by-js@3.4.0(vite@5.1.4):
     resolution: {integrity: sha512-wS5+UYtJXQ/vNornsqTQxOLBVO/UjXU54ZsYMeX0mj2OrbStMQ4GLgvneVDQGPwyGJcm/ntBPawc2lA7xx+Lpg==}
     peerDependencies:
       vite: '>2.0.0-0'
     dependencies:
-      vite: 5.1.3(@types/node@20.11.19)
+      vite: 5.1.4(@types/node@20.11.20)
     dev: true
 
-  /vite-plugin-dts@3.7.2(@types/node@20.11.19)(typescript@5.3.3)(vite@5.1.3):
-    resolution: {integrity: sha512-kg//1nDA01b8rufJf4TsvYN8LMkdwv0oBYpiQi6nRwpHyue+wTlhrBiqgipdFpMnW1oOYv6ywmzE5B0vg6vSEA==}
+  /vite-plugin-dts@3.7.3(@types/node@20.11.20)(typescript@5.3.3)(vite@5.1.4):
+    resolution: {integrity: sha512-26eTlBYdpjRLWCsTJebM8vkCieE+p9gP3raf+ecDnzzK5E3FG6VE1wcy55OkRpfWWVlVvKkYFe6uvRHYWx7Nog==}
     engines: {node: ^14.18.0 || >=16.0.0}
     peerDependencies:
       typescript: '*'
@@ -14044,13 +14266,13 @@ packages:
       vite:
         optional: true
     dependencies:
-      '@microsoft/api-extractor': 7.39.0(@types/node@20.11.19)
+      '@microsoft/api-extractor': 7.39.0(@types/node@20.11.20)
       '@rollup/pluginutils': 5.1.0
       '@vue/language-core': 1.8.27(typescript@5.3.3)
       debug: 4.3.4
       kolorist: 1.8.0
       typescript: 5.3.3
-      vite: 5.1.3(@types/node@20.11.19)
+      vite: 5.1.4(@types/node@20.11.20)
       vue-tsc: 1.8.27(typescript@5.3.3)
     transitivePeerDependencies:
       - '@types/node'
@@ -14058,20 +14280,20 @@ packages:
       - supports-color
     dev: true
 
-  /vite-plugin-eslint@1.8.1(eslint@8.56.0)(vite@5.1.3):
+  /vite-plugin-eslint@1.8.1(eslint@8.57.0)(vite@5.1.4):
     resolution: {integrity: sha512-PqdMf3Y2fLO9FsNPmMX+//2BF5SF8nEWspZdgl4kSt7UvHDRHVVfHvxsD7ULYzZrJDGRxR81Nq7TOFgwMnUang==}
     peerDependencies:
       eslint: '>=7'
       vite: '>=2'
     dependencies:
       '@rollup/pluginutils': 4.2.1
-      '@types/eslint': 8.56.2
-      eslint: 8.56.0
+      '@types/eslint': 8.56.3
+      eslint: 8.57.0
       rollup: 2.79.1
-      vite: 5.1.3(@types/node@20.11.19)
+      vite: 5.1.4(@types/node@20.11.20)
     dev: true
 
-  /vite-tsconfig-paths@4.3.1(typescript@5.3.3)(vite@5.1.3):
+  /vite-tsconfig-paths@4.3.1(typescript@5.3.3)(vite@5.1.4):
     resolution: {integrity: sha512-cfgJwcGOsIxXOLU/nELPny2/LUD/lcf1IbfyeKTv2bsupVbTH/xpFtdQlBmIP1GEK2CjjLxYhFfB+QODFAx5aw==}
     peerDependencies:
       vite: '*'
@@ -14082,14 +14304,14 @@ packages:
       debug: 4.3.4
       globrex: 0.1.2
       tsconfck: 3.0.2(typescript@5.3.3)
-      vite: 5.1.3(@types/node@20.11.19)
+      vite: 5.1.4(@types/node@20.11.20)
     transitivePeerDependencies:
       - supports-color
       - typescript
     dev: true
 
-  /vite@5.1.3(@types/node@20.11.19):
-    resolution: {integrity: sha512-UfmUD36DKkqhi/F75RrxvPpry+9+tTkrXfMNZD+SboZqBCMsxKtO52XeGzzuh7ioz+Eo/SYDBbdb0Z7vgcDJew==}
+  /vite@5.1.4(@types/node@20.11.20):
+    resolution: {integrity: sha512-n+MPqzq+d9nMVTKyewqw6kSt+R3CkvF9QAKY8obiQn8g1fwTscKxyfaYnC632HtBXAQGc1Yjomphwn1dtwGAHg==}
     engines: {node: ^18.0.0 || >=20.0.0}
     hasBin: true
     peerDependencies:
@@ -14116,7 +14338,7 @@ packages:
       terser:
         optional: true
     dependencies:
-      '@types/node': 20.11.19
+      '@types/node': 20.11.20
       esbuild: 0.19.12
       postcss: 8.4.35
       rollup: 4.12.0
@@ -14124,7 +14346,7 @@ packages:
       fsevents: 2.3.3
     dev: true
 
-  /vitest@1.3.1(@types/node@20.11.19):
+  /vitest@1.3.1(@types/node@20.11.20):
     resolution: {integrity: sha512-/1QJqXs8YbCrfv/GPQ05wAZf2eakUPLPa18vkJAKE7RXOKfVHqMZZ1WlTjiwl6Gcn65M5vpNUB6EFLnEdRdEXQ==}
     engines: {node: ^18.0.0 || >=20.0.0}
     hasBin: true
@@ -14149,7 +14371,7 @@ packages:
       jsdom:
         optional: true
     dependencies:
-      '@types/node': 20.11.19
+      '@types/node': 20.11.20
       '@vitest/expect': 1.3.1
       '@vitest/runner': 1.3.1
       '@vitest/snapshot': 1.3.1
@@ -14167,8 +14389,8 @@ packages:
       strip-literal: 2.0.0
       tinybench: 2.6.0
       tinypool: 0.8.2
-      vite: 5.1.3(@types/node@20.11.19)
-      vite-node: 1.3.1(@types/node@20.11.19)
+      vite: 5.1.4(@types/node@20.11.20)
+      vite-node: 1.3.1(@types/node@20.11.20)
       why-is-node-running: 2.2.2
     transitivePeerDependencies:
       - less
@@ -14487,7 +14709,7 @@ packages:
   /zod@3.22.4:
     resolution: {integrity: sha512-iC+8Io04lddc+mVqQ9AZ7OQ2MrUKGN+oIQyq1vemgt46jwCwLfhq7/pwnBnNXXXZb8VTVLKwp9EDkx+ryxIWmg==}
 
-  /zustand@4.5.1(@types/react@18.2.57)(react@18.2.0):
+  /zustand@4.5.1(@types/react@18.2.59)(react@18.2.0):
     resolution: {integrity: sha512-XlauQmH64xXSC1qGYNv00ODaQ3B+tNPoy22jv2diYiP4eoDKr9LA+Bh5Bc3gplTrFdb6JVI+N4kc1DZ/tbtfPg==}
     engines: {node: '>=12.7.0'}
     peerDependencies:
@@ -14502,7 +14724,7 @@ packages:
       react:
         optional: true
     dependencies:
-      '@types/react': 18.2.57
+      '@types/react': 18.2.59
       react: 18.2.0
       use-sync-external-store: 1.2.0(react@18.2.0)
     dev: false

From 574d6538b92049330205e9769620b578e026b00c Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Wed, 28 Feb 2024 00:32:06 +1100
Subject: [PATCH 357/411] fix(ui): merge conflict

---
 .../web/src/features/parameters/store/generationSlice.ts      | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/invokeai/frontend/web/src/features/parameters/store/generationSlice.ts b/invokeai/frontend/web/src/features/parameters/store/generationSlice.ts
index 061a291bad..49ca507439 100644
--- a/invokeai/frontend/web/src/features/parameters/store/generationSlice.ts
+++ b/invokeai/frontend/web/src/features/parameters/store/generationSlice.ts
@@ -105,6 +105,9 @@ export const generationSlice = createSlice({
     clearInitialImage: (state) => {
       state.initialImage = undefined;
     },
+    setMaskBlur: (state, action: PayloadAction<number>) => {
+      state.maskBlur = action.payload;
+    },
     setCanvasCoherenceMode: (state, action: PayloadAction<ParameterCanvasCoherenceMode>) => {
       state.canvasCoherenceMode = action.payload;
     },
@@ -253,6 +256,7 @@ export const {
   setPositivePrompt,
   setNegativePrompt,
   setScheduler,
+  setMaskBlur,
   setCanvasCoherenceMode,
   setCanvasCoherenceEdgeSize,
   setCanvasCoherenceMinDenoise,

From 4b4b9404610a1bf7b85de1992fee7bc26e2df75e Mon Sep 17 00:00:00 2001
From: Jennifer Player <chainchompa@gmail.com>
Date: Tue, 27 Feb 2024 09:48:41 -0500
Subject: [PATCH 358/411] updated to use new import model mutation

---
 .../AddModelPanel/ScanModels/ScanModelsResults.tsx        | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx
index b8c6efd938..960e00c2a6 100644
--- a/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx
+++ b/invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanModels/ScanModelsResults.tsx
@@ -16,7 +16,7 @@ import type { ChangeEventHandler } from 'react';
 import { useCallback, useMemo, useState } from 'react';
 import { useTranslation } from 'react-i18next';
 import { PiXBold } from 'react-icons/pi';
-import { type ScanFolderResponse, useImportMainModelsMutation } from 'services/api/endpoints/models';
+import { type ScanFolderResponse, useInstallModelMutation } from 'services/api/endpoints/models';
 
 import { ScanModelResultItem } from './ScanModelResultItem';
 
@@ -29,7 +29,7 @@ export const ScanModelsResults = ({ results }: ScanModelResultsProps) => {
   const [searchTerm, setSearchTerm] = useState('');
   const dispatch = useAppDispatch();
 
-  const [importMainModel] = useImportMainModelsMutation();
+  const [installModel] = useInstallModelMutation();
 
   const filteredResults = useMemo(() => {
     return results.filter((result) => {
@@ -51,7 +51,7 @@ export const ScanModelsResults = ({ results }: ScanModelResultsProps) => {
       if (result.is_installed) {
         continue;
       }
-      importMainModel({ source: result.path, config: undefined })
+      installModel({ source: result.path })
         .unwrap()
         .then((_) => {
           dispatch(
@@ -76,7 +76,7 @@ export const ScanModelsResults = ({ results }: ScanModelResultsProps) => {
           }
         });
     }
-  }, [importMainModel, filteredResults, dispatch, t]);
+  }, [installModel, filteredResults, dispatch, t]);
 
   return (
     <>

From 94e38571105b83686b4d77a540241545239161fd Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lstein@gmail.com>
Date: Tue, 27 Feb 2024 23:54:28 -0500
Subject: [PATCH 359/411] handle change to Civitai metadata schema for
 commercial usage

---
 invokeai/backend/model_manager/metadata/fetch/civitai.py | 2 +-
 invokeai/backend/model_manager/metadata/metadata_base.py | 9 ++++++---
 .../model_manager/model_metadata/metadata_examples.py    | 2 +-
 .../model_manager/model_metadata/test_model_metadata.py  | 2 +-
 4 files changed, 9 insertions(+), 6 deletions(-)

diff --git a/invokeai/backend/model_manager/metadata/fetch/civitai.py b/invokeai/backend/model_manager/metadata/fetch/civitai.py
index 7991f6a748..393b7552ad 100644
--- a/invokeai/backend/model_manager/metadata/fetch/civitai.py
+++ b/invokeai/backend/model_manager/metadata/fetch/civitai.py
@@ -160,7 +160,7 @@ class CivitaiMetadataFetch(ModelMetadataFetchBase):
             nsfw=model_json["nsfw"],
             restrictions=LicenseRestrictions(
                 AllowNoCredit=model_json["allowNoCredit"],
-                AllowCommercialUse=CommercialUsage(model_json["allowCommercialUse"]),
+                AllowCommercialUse={CommercialUsage(x) for x in model_json["allowCommercialUse"]},
                 AllowDerivatives=model_json["allowDerivatives"],
                 AllowDifferentLicense=model_json["allowDifferentLicense"],
             ),
diff --git a/invokeai/backend/model_manager/metadata/metadata_base.py b/invokeai/backend/model_manager/metadata/metadata_base.py
index 6e410d8222..379369f9f5 100644
--- a/invokeai/backend/model_manager/metadata/metadata_base.py
+++ b/invokeai/backend/model_manager/metadata/metadata_base.py
@@ -54,8 +54,8 @@ class LicenseRestrictions(BaseModel):
     AllowDifferentLicense: bool = Field(
         description="if true, derivatives of this model be redistributed under a different license", default=False
     )
-    AllowCommercialUse: Optional[CommercialUsage] = Field(
-        description="Type of commercial use allowed or 'No' if no commercial use is allowed.", default=None
+    AllowCommercialUse: Optional[Set[CommercialUsage] | CommercialUsage] = Field(
+        description="Type of commercial use allowed if no commercial use is allowed.", default=None
     )
 
 
@@ -142,7 +142,10 @@ class CivitaiMetadata(ModelMetadataWithFiles):
         if self.restrictions.AllowCommercialUse is None:
             return False
         else:
-            return self.restrictions.AllowCommercialUse != CommercialUsage("None")
+            # accommodate schema change
+            acu = self.restrictions.AllowCommercialUse
+            commercial_usage = acu if isinstance(acu, set) else {acu}
+            return CommercialUsage.No not in commercial_usage
 
     @property
     def allow_derivatives(self) -> bool:
diff --git a/tests/backend/model_manager/model_metadata/metadata_examples.py b/tests/backend/model_manager/model_metadata/metadata_examples.py
index 1c633f4a62..ef1c1e446d 100644
--- a/tests/backend/model_manager/model_metadata/metadata_examples.py
+++ b/tests/backend/model_manager/model_metadata/metadata_examples.py
@@ -23,5 +23,5 @@ RepoCivitaiVersionMetadata1 = b"""
 # copied from https://civitai.com/api/v1/models/215485
 # Yeah, this is ridiculously bloated, but that's what you get.
 RepoCivitaiModelMetadata1 = b"""
-{"id":215485,"name":"SDXL Turbo-LoRA-Stable Diffusion XL faster than light","description":"<p>v1: 128 dim</p><p>v1-64dim: half dimension, similar quality</p><p>v1-16dim: 94MB, s<span style=\\"color:rgb(193, 194, 197)\\">imilar quality(but different results in some prompts... I suggest the 128 dim or 64 dim version, but if you have a gpu with 6 GB vram try this version)</span></p><p>LoRA based on sdxl turbo, you can use the TURBO <u>with any stable diffusion xl checkpoint</u>, <u><span style=\\"color:rgb(250, 82, 82)\\">few seconds = 1 image(3 seconds with a nvidia rtx 3060 12 GB with 1024x768 resolution)</span></u></p><p>Tested on webui 1111 v1.6.0-2-g4afaaf8a</p><p>Tested on ComfyUI v1754 [777f6b15]: <a target=\\"_blank\\" rel=\\"ugc\\" href=\\"https://civitai.com/api/download/training-data/243508\\">workflow --download here--</a></p><p>(new version of workflow November 30, 2023 remove strange violet fog, keep sgm_uniform as scheduler and you can use every sampler)</p><p>1-Select your favourite stable diffusion xl checkpoint</p><p>2-Download this LoRA, use <span style=\\"color:rgb(250, 82, 82)\\">my workflow for ComfyUI</span> or any workflow with LoRA loader</p><p><span style=\\"color:rgb(250, 82, 82)\\">For webui 1111 write in the prompt &lt;lora:sd_xl_turbo_lora_v1:1&gt;</span></p><p>3-Sampling method on webui 1111: <span style=\\"color:rgb(250, 82, 82)\\">LCM</span>(install animatediff extension if you don't see it in sampling list)</p><p>Sampling method on ComfyUI: <span style=\\"color:rgb(250, 82, 82)\\">all</span>, with the workflow of November 30, 2023</p><p>4-CFG Scale: from 1 to 2.5</p><p>5-Sampling steps: 4</p><p>Hugginface page: <a target=\\"_blank\\" rel=\\"ugc\\" href=\\"https://huggingface.co/shiroppo/sd_xl_turbo_lora\\">https://huggingface.co/shiroppo/sd_xl_turbo_lora</a></p><p></p><p><img src=\\"https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/8fd7cd0a-2e22-4860-b09c-9c8f1568945e/width=525/8fd7cd0a-2e22-4860-b09c-9c8f1568945e.jpeg\\" /></p><p><img src=\\"https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/ae9afee8-09ad-4edc-960e-745b37ef142d/width=525/ae9afee8-09ad-4edc-960e-745b37ef142d.jpeg\\" /></p><p>---</p><p><img src=\\"https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/cb27bc41-53c9-4a3c-9d24-b60cea78de38/width=525/cb27bc41-53c9-4a3c-9d24-b60cea78de38.jpeg\\" /></p><p>Ko-fi: <a target=\\"_blank\\" rel=\\"ugc\\" href=\\"https://ko-fi.com/shiroppo\\">https://ko-fi.com/shiroppo</a></p><p>Patreon: <a target=\\"_blank\\" rel=\\"ugc\\" href=\\"https://www.patreon.com/Shiroppo\\">https://www.patreon.com/Shiroppo</a></p><p>Pixiv: <a target=\\"_blank\\" rel=\\"ugc\\" href=\\"https://www.pixiv.net/users/7058273\\">https://www.pixiv.net/users/7058273</a></p><p>Twitter: <a target=\\"_blank\\" rel=\\"ugc\\" href=\\"https://twitter.com/ShiroppoTwit\\">https://twitter.com/ShiroppoTwit</a></p><p>Instagram: <a target=\\"_blank\\" rel=\\"ugc\\" href=\\"https://www.instagram.com/shiroppo_real/\\">https://www.instagram.com/shiroppo_real/</a></p><p>My pages: <a target=\\"_blank\\" rel=\\"ugc\\" href=\\"https://solo.to/shiroppo\\">https://solo.to/shiroppo</a></p><p>---</p>","type":"LORA","poi":false,"nsfw":false,"allowNoCredit":false,"allowCommercialUse":"RentCivit","allowDerivatives":false,"allowDifferentLicense":true,"stats":{"downloadCount":4842,"favoriteCount":252,"commentCount":25,"ratingCount":4,"rating":5,"tippedAmountCount":2653},"creator":{"username":"test_author","image":"https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/d0b4b9d4-f32c-441a-99e1-9b2d73679bd7/width=96/shiroppo.jpeg"},"tags":["tool","turbo","sdxl turbo"],"modelVersions":[{"id":242807,"modelId":215485,"name":"v1-128dim","createdAt":"2023-11-29T01:21:22.372Z","updatedAt":"2023-12-16T17:46:14.313Z","status":"Published","publishedAt":"2023-11-29T01:28:10.937Z","trainedWords":[],"trainingStatus":null,"trainingDetails":null,"baseModel":"SDXL Turbo","baseModelType":null,"earlyAccessTimeFrame":0,"description":"<p>v1: First version(128 dim)</p>","vaeId":null,"stats":{"downloadCount":2586,"ratingCount":2,"rating":5},"files":[{"id":187907,"sizeKB":768888.859375,"name":"sd_xl_turbo_lora_v1.safetensors","type":"Model","metadata":{"fp":null,"size":null,"format":"SafeTensor"},"pickleScanResult":"Success","pickleScanMessage":"No Pickle imports","virusScanResult":"Success","virusScanMessage":null,"scannedAt":"2023-11-29T01:30:55.512Z","hashes":{"AutoV1":"6DC5F47A","AutoV2":"A599C42A9F","SHA256":"A599C42A9F4F7494C7F410DBC0FD432CF0242720509E9D52FA41AAC7A88D1B69","CRC32":"BF967A66","BLAKE3":"930E9A5CA9D31D2A35CE5A719120813F09CA927C61B5867C35CB547F9A279F62","AutoV3":"813EA5FB1C67F3CBF1C4DFF5D392EE5E073A2C41DCF3AB36CF6CDD872C4E7690"},"downloadUrl":"https://civitai.com/api/download/models/242807","primary":true}],"images":[{"url":"https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/bbf39031-15e6-4f2c-b531-c2b5108a1a9d/width=450/4080480.jpeg","nsfw":"None","width":768,"height":1024,"hash":"U9G9BnR,GI%N00kC4-s:5soz4TMx?wV@^*o#","type":"image","metadata":{"hash":"U9G9BnR,GI%N00kC4-s:5soz4TMx?wV@^*o#","size":1098842,"width":768,"height":1024},"meta":{"VAE":"sd_xl_base_1.0_fixvae_fp16.vae.safetensors","Size":"768x1024","seed":2494203713,"Model":"sd_xl_base_1.0","steps":4,"hashes":{"model":"31e35c80fc"},"prompt":"<lora:sd_xl_turbo_lora_v1-128dim:1>1 girl, snow","Version":"v1.6.0-2-g4afaaf8a","sampler":"LCM","VAE hash":"235745af8d","cfgScale":1.5,"clipSkip":2,"resources":[{"hash":"31e35c80fc","name":"sd_xl_base_1.0","type":"model"}],"Model hash":"31e35c80fc","negativePrompt":"blurry, blurry_image, Lowres, Low_resolution, Low_picture_quality, Low_picture_anime, extra_anatomy, extra_body, extra_navel, extra_face, extra_eyes, extra_chest, extra_nipples, extra_hips, extra_arms, extra_hands, extra_fingers, extra_legs, extra_feet, extra_toe, missing_anatomy, missing_body, missing_navel, missing_face, missing_eyes, missing_chest, missing_nipples, missing_hips, missing_arms, missing_hands, missing_fingers, missing_legs, missing_feet, missing_toe, sketch, sketching, (worst quality:2), (low quality:2), ((monochrome)), ((grayscale)), inpainting, HDR, bad_prompt_version2, jpeg artifacts, signature, watermark, text, error, missing fingers","\\"sd_xl_turbo_lora_v1-128dim":"813ea5fb1c67\\""}},{"url":"https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/06a2e73e-594c-4a07-b4a2-495922153589/width=450/4081177.jpeg","nsfw":"None","width":2304,"height":1187,"hash":"UeIOY5V@j[ax?bj@ayj[.7ogj@kC_Nfkj[j]","type":"image","metadata":{"hash":"UeIOY5V@j[ax?bj@ayj[.7ogj@kC_Nfkj[j]","size":3214188,"width":2304,"height":1187},"meta":{"VAE":"sd_xl_base_1.0_fixvae_fp16.vae.safetensors","Size":"768x1024","seed":2494203713,"Model":"sd_xl_base_1.0","steps":4,"Script":"X/Y/Z plot","X Type":"Prompt S/R","hashes":{"model":"31e35c80fc"},"prompt":"<lora:sd_xl_turbo_lora_v1-128dim:1>1girl, wind","Version":"v1.6.0-2-g4afaaf8a","sampler":"LCM","VAE hash":"235745af8d","cfgScale":1.5,"resources":[{"hash":"31e35c80fc","name":"sd_xl_base_1.0","type":"model"}],"Model hash":"31e35c80fc","negativePrompt":"blurry, blurry_image, Lowres, Low_resolution, Low_picture_quality, Low_picture_anime, extra_anatomy, extra_body, extra_navel, extra_face, extra_eyes, 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+{"id":215485,"name":"SDXL Turbo-LoRA-Stable Diffusion XL faster than light","description":"<p>v1: 128 dim</p><p>v1-64dim: half dimension, similar quality</p><p>v1-16dim: 94MB, s<span style=\\"color:rgb(193, 194, 197)\\">imilar quality(but different results in some prompts... 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fingers","\\"sd_xl_turbo_lora_v1-16dim":"9cbd5006993c\\""}},{"url":"https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/2f0149fc-43f6-40af-9aae-dc27956cf293/width=450/4081196.jpeg","nsfw":"None","width":2304,"height":1187,"hash":"UeIOY5V@j[ax?bj@ayj[.7ogj@kC_Nfkj[j]","type":"image","metadata":{"hash":"UeIOY5V@j[ax?bj@ayj[.7ogj@kC_Nfkj[j]","size":3214188,"width":2304,"height":1187},"meta":{"VAE":"sd_xl_base_1.0_fixvae_fp16.vae.safetensors","Size":"768x1024","seed":2494203713,"Model":"sd_xl_base_1.0","steps":4,"Script":"X/Y/Z plot","X Type":"Prompt S/R","hashes":{"model":"31e35c80fc"},"prompt":"<lora:sd_xl_turbo_lora_v1-128dim:1>1girl, wind","Version":"v1.6.0-2-g4afaaf8a","sampler":"LCM","VAE hash":"235745af8d","cfgScale":1.5,"resources":[{"hash":"31e35c80fc","name":"sd_xl_base_1.0","type":"model"}],"Model hash":"31e35c80fc","negativePrompt":"blurry, blurry_image, Lowres, Low_resolution, Low_picture_quality, Low_picture_anime, extra_anatomy, extra_body, extra_navel, extra_face, extra_eyes, extra_chest, extra_nipples, extra_hips, extra_arms, extra_hands, extra_fingers, extra_legs, extra_feet, extra_toe, missing_anatomy, missing_body, missing_navel, missing_face, missing_eyes, missing_chest, missing_nipples, missing_hips, missing_arms, missing_hands, missing_fingers, missing_legs, missing_feet, missing_toe, sketch, sketching, (worst quality:2), (low quality:2), ((monochrome)), ((grayscale)), inpainting, HDR, jpeg artifacts, signature, watermark, text, error, missing fingers","sd_xl_turbo_lora_v1-16dim":"1>\\"","sd_xl_turbo_lora_v1-64dim":"1>","sd_xl_turbo_lora_v1-128dim":"1>","\\"sd_xl_turbo_lora_v1-128dim":"813ea5fb1c67\\""}}],"downloadUrl":"https://civitai.com/api/download/models/245733"}]}
 """
diff --git a/tests/backend/model_manager/model_metadata/test_model_metadata.py b/tests/backend/model_manager/model_metadata/test_model_metadata.py
index 09b18916d3..f7f2603e7c 100644
--- a/tests/backend/model_manager/model_metadata/test_model_metadata.py
+++ b/tests/backend/model_manager/model_metadata/test_model_metadata.py
@@ -133,7 +133,7 @@ def test_metadata_civitai_fetch(mm2_session: Session) -> None:
     assert metadata.id == 215485
     assert metadata.author == "test_author"  # note that this is not the same as the original from Civitai
     assert metadata.allow_commercial_use  # changed to make sure we are reading locally not remotely
-    assert metadata.restrictions.AllowCommercialUse == CommercialUsage("RentCivit")
+    assert CommercialUsage("RentCivit") in metadata.restrictions.AllowCommercialUse
     assert metadata.version_id == 242807
     assert metadata.tags == {"tool", "turbo", "sdxl turbo"}
 

From 5922cee541cd4235ebbe782012aa4c11966f4009 Mon Sep 17 00:00:00 2001
From: Brandon Rising <contact@brandonrising.com>
Date: Tue, 27 Feb 2024 12:26:51 -0500
Subject: [PATCH 360/411] Allow TIs to be either a key or a name in the prompt
 during our transition to using keys

---
 invokeai/app/invocations/compel.py | 72 +++++++++++++++++++-----------
 1 file changed, 47 insertions(+), 25 deletions(-)

diff --git a/invokeai/app/invocations/compel.py b/invokeai/app/invocations/compel.py
index 50f5322513..ce9b1948eb 100644
--- a/invokeai/app/invocations/compel.py
+++ b/invokeai/app/invocations/compel.py
@@ -3,7 +3,7 @@ from typing import Iterator, List, Optional, Tuple, Union
 import torch
 from compel import Compel, ReturnedEmbeddingsType
 from compel.prompt_parser import Blend, Conjunction, CrossAttentionControlSubstitute, FlattenedPrompt, Fragment
-from transformers import CLIPTokenizer
+from transformers import CLIPTokenizer, CLIPTextModel
 
 import invokeai.backend.util.logging as logger
 from invokeai.app.invocations.fields import (
@@ -18,7 +18,7 @@ from invokeai.app.services.model_records import UnknownModelException
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.app.util.ti_utils import extract_ti_triggers_from_prompt
 from invokeai.backend.lora import LoRAModelRaw
-from invokeai.backend.model_manager import ModelType
+from invokeai.backend.model_manager.config import ModelType
 from invokeai.backend.model_patcher import ModelPatcher
 from invokeai.backend.stable_diffusion.diffusion.conditioning_data import (
     BasicConditioningInfo,
@@ -70,7 +70,11 @@ class CompelInvocation(BaseInvocation):
     @torch.no_grad()
     def invoke(self, context: InvocationContext) -> ConditioningOutput:
         tokenizer_info = context.models.load(**self.clip.tokenizer.model_dump())
+        tokenizer_model = tokenizer_info.model
+        assert isinstance(tokenizer_model, CLIPTokenizer)
         text_encoder_info = context.models.load(**self.clip.text_encoder.model_dump())
+        text_encoder_model = text_encoder_info.model
+        assert isinstance(text_encoder_model, CLIPTextModel)
 
         def _lora_loader() -> Iterator[Tuple[LoRAModelRaw, float]]:
             for lora in self.clip.loras:
@@ -82,21 +86,29 @@ class CompelInvocation(BaseInvocation):
 
         # loras = [(context.models.get(**lora.dict(exclude={"weight"})).context.model, lora.weight) for lora in self.clip.loras]
 
-        ti_list = []
+        ti_list: List[Tuple[str, TextualInversionModelRaw]] = []
         for trigger in extract_ti_triggers_from_prompt(self.prompt):
-            name = trigger[1:-1]
+            name_or_key = trigger[1:-1]
             try:
-                loaded_model = context.models.load(key=name).model
-                assert isinstance(loaded_model, TextualInversionModelRaw)
-                ti_list.append((name, loaded_model))
+                loaded_model = context.models.load(key=name_or_key)
+                model = loaded_model.model
+                assert isinstance(model, TextualInversionModelRaw)
+                ti_list.append((name_or_key, model))
             except UnknownModelException:
-                # print(e)
-                # import traceback
-                # print(traceback.format_exc())
-                print(f'Warn: trigger: "{trigger}" not found')
+                try:
+                    loaded_model = context.models.load_by_attrs(
+                        model_name=name_or_key, base_model=text_encoder_info.config.base, model_type=ModelType.TextualInversion
+                    )
+                    model = loaded_model.model
+                    assert isinstance(model, TextualInversionModelRaw)
+                    ti_list.append((name_or_key, model))
+                except UnknownModelException:
+                    logger.warning(f'trigger: "{trigger}" not found')
+            except ValueError:
+                logger.warning(f'trigger: "{trigger}" more than one similarly-named textual inversion models')
 
         with (
-            ModelPatcher.apply_ti(tokenizer_info.model, text_encoder_info.model, ti_list) as (
+            ModelPatcher.apply_ti(tokenizer_model, text_encoder_model, ti_list) as (
                 tokenizer,
                 ti_manager,
             ),
@@ -106,6 +118,7 @@ class CompelInvocation(BaseInvocation):
             # Apply CLIP Skip after LoRA to prevent LoRA application from failing on skipped layers.
             ModelPatcher.apply_clip_skip(text_encoder_info.model, self.clip.skipped_layers),
         ):
+            assert isinstance(text_encoder, CLIPTextModel)
             compel = Compel(
                 tokenizer=tokenizer,
                 text_encoder=text_encoder,
@@ -155,7 +168,11 @@ class SDXLPromptInvocationBase:
         zero_on_empty: bool,
     ) -> Tuple[torch.Tensor, Optional[torch.Tensor], Optional[ExtraConditioningInfo]]:
         tokenizer_info = context.models.load(**clip_field.tokenizer.model_dump())
+        tokenizer_model = tokenizer_info.model
+        assert isinstance(tokenizer_model, CLIPTokenizer)
         text_encoder_info = context.models.load(**clip_field.text_encoder.model_dump())
+        text_encoder_model = text_encoder_info.model
+        assert isinstance(text_encoder_model, CLIPTextModel)
 
         # return zero on empty
         if prompt == "" and zero_on_empty:
@@ -189,25 +206,29 @@ class SDXLPromptInvocationBase:
 
         # loras = [(context.models.get(**lora.dict(exclude={"weight"})).context.model, lora.weight) for lora in self.clip.loras]
 
-        ti_list = []
+        ti_list: List[Tuple[str, TextualInversionModelRaw]] = []
         for trigger in extract_ti_triggers_from_prompt(prompt):
-            name = trigger[1:-1]
+            name_or_key = trigger[1:-1]
             try:
-                ti_model = context.models.load_by_attrs(
-                    model_name=name, base_model=text_encoder_info.config.base, model_type=ModelType.TextualInversion
-                ).model
-                assert isinstance(ti_model, TextualInversionModelRaw)
-                ti_list.append((name, ti_model))
+                loaded_model = context.models.load(key=name_or_key)
+                model = loaded_model.model
+                assert isinstance(model, TextualInversionModelRaw)
+                ti_list.append((name_or_key, model))
             except UnknownModelException:
-                # print(e)
-                # import traceback
-                # print(traceback.format_exc())
-                logger.warning(f'trigger: "{trigger}" not found')
+                try:
+                    loaded_model = context.models.load_by_attrs(
+                        model_name=name_or_key, base_model=text_encoder_info.config.base, model_type=ModelType.TextualInversion
+                    )
+                    model = loaded_model.model
+                    assert isinstance(model, TextualInversionModelRaw)
+                    ti_list.append((name_or_key, model))
+                except UnknownModelException:
+                    logger.warning(f'trigger: "{trigger}" not found')
             except ValueError:
                 logger.warning(f'trigger: "{trigger}" more than one similarly-named textual inversion models')
 
         with (
-            ModelPatcher.apply_ti(tokenizer_info.model, text_encoder_info.model, ti_list) as (
+            ModelPatcher.apply_ti(tokenizer_model, text_encoder_model, ti_list) as (
                 tokenizer,
                 ti_manager,
             ),
@@ -215,8 +236,9 @@ class SDXLPromptInvocationBase:
             # Apply the LoRA after text_encoder has been moved to its target device for faster patching.
             ModelPatcher.apply_lora(text_encoder, _lora_loader(), lora_prefix),
             # Apply CLIP Skip after LoRA to prevent LoRA application from failing on skipped layers.
-            ModelPatcher.apply_clip_skip(text_encoder_info.model, clip_field.skipped_layers),
+            ModelPatcher.apply_clip_skip(text_encoder_model, clip_field.skipped_layers),
         ):
+            assert isinstance(text_encoder, CLIPTextModel)
             compel = Compel(
                 tokenizer=tokenizer,
                 text_encoder=text_encoder,

From 8efd4284e9ff5a085d1ad64ff7a3cdd2319964c0 Mon Sep 17 00:00:00 2001
From: Brandon Rising <contact@brandonrising.com>
Date: Tue, 27 Feb 2024 12:36:04 -0500
Subject: [PATCH 361/411] Fix one last reference to the uncasted model

---
 invokeai/app/invocations/compel.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/invokeai/app/invocations/compel.py b/invokeai/app/invocations/compel.py
index ce9b1948eb..bc0c7955dc 100644
--- a/invokeai/app/invocations/compel.py
+++ b/invokeai/app/invocations/compel.py
@@ -116,7 +116,7 @@ class CompelInvocation(BaseInvocation):
             # Apply the LoRA after text_encoder has been moved to its target device for faster patching.
             ModelPatcher.apply_lora_text_encoder(text_encoder, _lora_loader()),
             # Apply CLIP Skip after LoRA to prevent LoRA application from failing on skipped layers.
-            ModelPatcher.apply_clip_skip(text_encoder_info.model, self.clip.skipped_layers),
+            ModelPatcher.apply_clip_skip(text_encoder_model, self.clip.skipped_layers),
         ):
             assert isinstance(text_encoder, CLIPTextModel)
             compel = Compel(

From ca9b815c89abbb97d26b4f4a776b5b5f09ce4ebd Mon Sep 17 00:00:00 2001
From: Brandon Rising <contact@brandonrising.com>
Date: Tue, 27 Feb 2024 15:20:14 -0500
Subject: [PATCH 362/411] Extract TI loading logic into util, disallow it from
 ever failing a generation

---
 invokeai/app/invocations/compel.py | 44 ++----------------------------
 invokeai/app/util/ti_utils.py      | 42 ++++++++++++++++++++++++++--
 2 files changed, 42 insertions(+), 44 deletions(-)

diff --git a/invokeai/app/invocations/compel.py b/invokeai/app/invocations/compel.py
index bc0c7955dc..ca6ca644bb 100644
--- a/invokeai/app/invocations/compel.py
+++ b/invokeai/app/invocations/compel.py
@@ -16,7 +16,7 @@ from invokeai.app.invocations.fields import (
 from invokeai.app.invocations.primitives import ConditioningOutput
 from invokeai.app.services.model_records import UnknownModelException
 from invokeai.app.services.shared.invocation_context import InvocationContext
-from invokeai.app.util.ti_utils import extract_ti_triggers_from_prompt
+from invokeai.app.util.ti_utils import generate_ti_list
 from invokeai.backend.lora import LoRAModelRaw
 from invokeai.backend.model_manager.config import ModelType
 from invokeai.backend.model_patcher import ModelPatcher
@@ -86,26 +86,7 @@ class CompelInvocation(BaseInvocation):
 
         # loras = [(context.models.get(**lora.dict(exclude={"weight"})).context.model, lora.weight) for lora in self.clip.loras]
 
-        ti_list: List[Tuple[str, TextualInversionModelRaw]] = []
-        for trigger in extract_ti_triggers_from_prompt(self.prompt):
-            name_or_key = trigger[1:-1]
-            try:
-                loaded_model = context.models.load(key=name_or_key)
-                model = loaded_model.model
-                assert isinstance(model, TextualInversionModelRaw)
-                ti_list.append((name_or_key, model))
-            except UnknownModelException:
-                try:
-                    loaded_model = context.models.load_by_attrs(
-                        model_name=name_or_key, base_model=text_encoder_info.config.base, model_type=ModelType.TextualInversion
-                    )
-                    model = loaded_model.model
-                    assert isinstance(model, TextualInversionModelRaw)
-                    ti_list.append((name_or_key, model))
-                except UnknownModelException:
-                    logger.warning(f'trigger: "{trigger}" not found')
-            except ValueError:
-                logger.warning(f'trigger: "{trigger}" more than one similarly-named textual inversion models')
+        ti_list = generate_ti_list(self.prompt, text_encoder_info.config.base, context)
 
         with (
             ModelPatcher.apply_ti(tokenizer_model, text_encoder_model, ti_list) as (
@@ -206,26 +187,7 @@ class SDXLPromptInvocationBase:
 
         # loras = [(context.models.get(**lora.dict(exclude={"weight"})).context.model, lora.weight) for lora in self.clip.loras]
 
-        ti_list: List[Tuple[str, TextualInversionModelRaw]] = []
-        for trigger in extract_ti_triggers_from_prompt(prompt):
-            name_or_key = trigger[1:-1]
-            try:
-                loaded_model = context.models.load(key=name_or_key)
-                model = loaded_model.model
-                assert isinstance(model, TextualInversionModelRaw)
-                ti_list.append((name_or_key, model))
-            except UnknownModelException:
-                try:
-                    loaded_model = context.models.load_by_attrs(
-                        model_name=name_or_key, base_model=text_encoder_info.config.base, model_type=ModelType.TextualInversion
-                    )
-                    model = loaded_model.model
-                    assert isinstance(model, TextualInversionModelRaw)
-                    ti_list.append((name_or_key, model))
-                except UnknownModelException:
-                    logger.warning(f'trigger: "{trigger}" not found')
-            except ValueError:
-                logger.warning(f'trigger: "{trigger}" more than one similarly-named textual inversion models')
+        ti_list = generate_ti_list(prompt, text_encoder_info.config.base, context)
 
         with (
             ModelPatcher.apply_ti(tokenizer_model, text_encoder_model, ti_list) as (
diff --git a/invokeai/app/util/ti_utils.py b/invokeai/app/util/ti_utils.py
index a66a832b42..c2645e0702 100644
--- a/invokeai/app/util/ti_utils.py
+++ b/invokeai/app/util/ti_utils.py
@@ -1,8 +1,44 @@
 import re
+from typing import List, Tuple
+
+from invokeai.backend.model_manager.config import BaseModelType, ModelType
+from invokeai.backend.textual_inversion import TextualInversionModelRaw
+from invokeai.app.services.shared.invocation_context import InvocationContext
+from invokeai.app.services.model_records import UnknownModelException
+import invokeai.backend.util.logging as logger
 
 
-def extract_ti_triggers_from_prompt(prompt: str) -> list[str]:
-    ti_triggers = []
+def extract_ti_triggers_from_prompt(prompt: str) -> List[str]:
+    ti_triggers: List[str] = []
     for trigger in re.findall(r"<[a-zA-Z0-9., _-]+>", prompt):
-        ti_triggers.append(trigger)
+        ti_triggers.append(str(trigger))
     return ti_triggers
+
+def generate_ti_list(prompt: str, base: BaseModelType, context: InvocationContext) -> List[Tuple[str, TextualInversionModelRaw]]:
+    ti_list: List[Tuple[str, TextualInversionModelRaw]] = []
+    for trigger in extract_ti_triggers_from_prompt(prompt):
+        name_or_key = trigger[1:-1]
+        try:
+            loaded_model = context.models.load(key=name_or_key)
+            model = loaded_model.model
+            assert isinstance(model, TextualInversionModelRaw)
+            assert loaded_model.config.base == base
+            ti_list.append((name_or_key, model))
+        except UnknownModelException:
+            try:
+                loaded_model = context.models.load_by_attrs(
+                    model_name=name_or_key, base_model=base, model_type=ModelType.TextualInversion
+                )
+                model = loaded_model.model
+                assert isinstance(model, TextualInversionModelRaw)
+                assert loaded_model.config.base == base
+                ti_list.append((name_or_key, model))
+            except UnknownModelException:
+                pass
+        except ValueError:
+            logger.warning(f'trigger: "{trigger}" more than one similarly-named textual inversion models')
+        except AssertionError:
+            logger.warning(f'trigger: "{trigger}" not a valid textual inversion model for this graph')
+        except Exception:
+            logger.warning(f'Failed to load TI model for trigger: "{trigger}"')
+    return ti_list
\ No newline at end of file

From f475b78734fac8ed8e2d485c087513e922aa7e33 Mon Sep 17 00:00:00 2001
From: Brandon Rising <contact@brandonrising.com>
Date: Tue, 27 Feb 2024 15:20:55 -0500
Subject: [PATCH 363/411] Ruff check

---
 invokeai/app/invocations/compel.py | 6 +-----
 invokeai/app/util/ti_utils.py      | 8 ++++----
 2 files changed, 5 insertions(+), 9 deletions(-)

diff --git a/invokeai/app/invocations/compel.py b/invokeai/app/invocations/compel.py
index ca6ca644bb..771c811eea 100644
--- a/invokeai/app/invocations/compel.py
+++ b/invokeai/app/invocations/compel.py
@@ -3,9 +3,8 @@ from typing import Iterator, List, Optional, Tuple, Union
 import torch
 from compel import Compel, ReturnedEmbeddingsType
 from compel.prompt_parser import Blend, Conjunction, CrossAttentionControlSubstitute, FlattenedPrompt, Fragment
-from transformers import CLIPTokenizer, CLIPTextModel
+from transformers import CLIPTextModel, CLIPTokenizer
 
-import invokeai.backend.util.logging as logger
 from invokeai.app.invocations.fields import (
     FieldDescriptions,
     Input,
@@ -14,11 +13,9 @@ from invokeai.app.invocations.fields import (
     UIComponent,
 )
 from invokeai.app.invocations.primitives import ConditioningOutput
-from invokeai.app.services.model_records import UnknownModelException
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.app.util.ti_utils import generate_ti_list
 from invokeai.backend.lora import LoRAModelRaw
-from invokeai.backend.model_manager.config import ModelType
 from invokeai.backend.model_patcher import ModelPatcher
 from invokeai.backend.stable_diffusion.diffusion.conditioning_data import (
     BasicConditioningInfo,
@@ -26,7 +23,6 @@ from invokeai.backend.stable_diffusion.diffusion.conditioning_data import (
     ExtraConditioningInfo,
     SDXLConditioningInfo,
 )
-from invokeai.backend.textual_inversion import TextualInversionModelRaw
 from invokeai.backend.util.devices import torch_dtype
 
 from .baseinvocation import (
diff --git a/invokeai/app/util/ti_utils.py b/invokeai/app/util/ti_utils.py
index c2645e0702..0d803408fd 100644
--- a/invokeai/app/util/ti_utils.py
+++ b/invokeai/app/util/ti_utils.py
@@ -1,11 +1,11 @@
 import re
 from typing import List, Tuple
 
+import invokeai.backend.util.logging as logger
+from invokeai.app.services.model_records import UnknownModelException
+from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.backend.model_manager.config import BaseModelType, ModelType
 from invokeai.backend.textual_inversion import TextualInversionModelRaw
-from invokeai.app.services.shared.invocation_context import InvocationContext
-from invokeai.app.services.model_records import UnknownModelException
-import invokeai.backend.util.logging as logger
 
 
 def extract_ti_triggers_from_prompt(prompt: str) -> List[str]:
@@ -41,4 +41,4 @@ def generate_ti_list(prompt: str, base: BaseModelType, context: InvocationContex
             logger.warning(f'trigger: "{trigger}" not a valid textual inversion model for this graph')
         except Exception:
             logger.warning(f'Failed to load TI model for trigger: "{trigger}"')
-    return ti_list
\ No newline at end of file
+    return ti_list

From c670dacc298c7de740d9803ad054abdddd4e0fee Mon Sep 17 00:00:00 2001
From: Brandon Rising <contact@brandonrising.com>
Date: Tue, 27 Feb 2024 15:24:23 -0500
Subject: [PATCH 364/411] Ruff format

---
 invokeai/app/util/ti_utils.py | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/invokeai/app/util/ti_utils.py b/invokeai/app/util/ti_utils.py
index 0d803408fd..b5c884c9b7 100644
--- a/invokeai/app/util/ti_utils.py
+++ b/invokeai/app/util/ti_utils.py
@@ -14,7 +14,10 @@ def extract_ti_triggers_from_prompt(prompt: str) -> List[str]:
         ti_triggers.append(str(trigger))
     return ti_triggers
 
-def generate_ti_list(prompt: str, base: BaseModelType, context: InvocationContext) -> List[Tuple[str, TextualInversionModelRaw]]:
+
+def generate_ti_list(
+    prompt: str, base: BaseModelType, context: InvocationContext
+) -> List[Tuple[str, TextualInversionModelRaw]]:
     ti_list: List[Tuple[str, TextualInversionModelRaw]] = []
     for trigger in extract_ti_triggers_from_prompt(prompt):
         name_or_key = trigger[1:-1]

From 0fc2f90824c32603c23653154cee085bb23b6a13 Mon Sep 17 00:00:00 2001
From: Brandon Rising <contact@brandonrising.com>
Date: Thu, 22 Feb 2024 20:36:42 -0500
Subject: [PATCH 365/411] Switch ModelSearch from os.walk to os.scandir

---
 invokeai/backend/model_manager/search.py | 88 +++++++++++-------------
 1 file changed, 42 insertions(+), 46 deletions(-)

diff --git a/invokeai/backend/model_manager/search.py b/invokeai/backend/model_manager/search.py
index f7ef2e049d..4bfaa6ce7d 100644
--- a/invokeai/backend/model_manager/search.py
+++ b/invokeai/backend/model_manager/search.py
@@ -25,6 +25,7 @@ from abc import ABC, abstractmethod
 from logging import Logger
 from pathlib import Path
 from typing import Callable, Optional, Set, Union
+from invokeai.app.services.config import InvokeAIAppConfig
 
 from pydantic import BaseModel, Field
 
@@ -117,13 +118,10 @@ class ModelSearch(ModelSearchBase):
     """
 
     models_found: Set[Path] = Field(default_factory=set)
-    scanned_dirs: Set[Path] = Field(default_factory=set)
-    pruned_paths: Set[Path] = Field(default_factory=set)
+    config: InvokeAIAppConfig =  InvokeAIAppConfig.get_config()
 
     def search_started(self) -> None:
         self.models_found = set()
-        self.scanned_dirs = set()
-        self.pruned_paths = set()
         if self.on_search_started:
             self.on_search_started(self._directory)
 
@@ -139,53 +137,51 @@ class ModelSearch(ModelSearchBase):
 
     def search(self, directory: Union[Path, str]) -> Set[Path]:
         self._directory = Path(directory)
+        if not self._directory.is_absolute():
+            self._directory = self.config.models_path / self._directory
         self.stats = SearchStats()  # zero out
         self.search_started()  # This will initialize _models_found to empty
         self._walk_directory(directory)
         self.search_completed()
         return self.models_found
 
-    def _walk_directory(self, path: Union[Path, str]) -> None:
-        for root, dirs, files in os.walk(path, followlinks=True):
-            # don't descend into directories that start with a "."
-            # to avoid the Mac .DS_STORE issue.
-            if str(Path(root).name).startswith("."):
-                self.pruned_paths.add(Path(root))
-            if any(Path(root).is_relative_to(x) for x in self.pruned_paths):
-                continue
+    def _walk_directory(self, path: Union[Path, str], max_depth: int = 20) -> None:
+        absolute_path = Path(path)
+        if len(absolute_path.parts) - len(self._directory.parts) > max_depth \
+                or not absolute_path.exists() \
+                    or absolute_path.parent in self.models_found:
+            return
+        entries = os.scandir(absolute_path)
+        entries = [entry for entry in entries if not entry.name.startswith(".")]
+        dirs = [entry for entry in entries if entry.is_dir()]
+        file_names = [entry.name for entry in entries if entry.is_file()]
+        if any(
+            x in file_names
+            for x in [
+                "config.json",
+                "model_index.json",
+                "learned_embeds.bin",
+                "pytorch_lora_weights.bin",
+                "image_encoder.txt",
+            ]
+        ):
+            try:
+                self.model_found(absolute_path)
+            except KeyboardInterrupt:
+                raise
+            except Exception as e:
+                self.logger.warning(str(e))
+            finally:
+                return
 
-            self.stats.items_scanned += len(dirs) + len(files)
-            for d in dirs:
-                path = Path(root) / d
-                if path.parent in self.scanned_dirs:
-                    self.scanned_dirs.add(path)
-                    continue
-                if any(
-                    (path / x).exists()
-                    for x in [
-                        "config.json",
-                        "model_index.json",
-                        "learned_embeds.bin",
-                        "pytorch_lora_weights.bin",
-                        "image_encoder.txt",
-                    ]
-                ):
-                    self.scanned_dirs.add(path)
-                    try:
-                        self.model_found(path)
-                    except KeyboardInterrupt:
-                        raise
-                    except Exception as e:
-                        self.logger.warning(str(e))
+        for n in file_names:
+            if any([n.endswith(suffix) for suffix in {".ckpt", ".bin", ".pth", ".safetensors", ".pt"}]):
+                try:
+                    self.model_found(absolute_path / n)
+                except KeyboardInterrupt:
+                    raise
+                except Exception as e:
+                    self.logger.warning(str(e))
 
-            for f in files:
-                path = Path(root) / f
-                if path.parent in self.scanned_dirs:
-                    continue
-                if path.suffix in {".ckpt", ".bin", ".pth", ".safetensors", ".pt"}:
-                    try:
-                        self.model_found(path)
-                    except KeyboardInterrupt:
-                        raise
-                    except Exception as e:
-                        self.logger.warning(str(e))
+        for d in dirs:
+            self._walk_directory(absolute_path / d)

From 8992d898172aba07c234a2aca8fb9ac8b694f80c Mon Sep 17 00:00:00 2001
From: Brandon Rising <contact@brandonrising.com>
Date: Fri, 23 Feb 2024 14:27:36 -0500
Subject: [PATCH 366/411] Fix directory called on _walk_directory

---
 invokeai/backend/model_manager/search.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/invokeai/backend/model_manager/search.py b/invokeai/backend/model_manager/search.py
index 4bfaa6ce7d..330cff4e08 100644
--- a/invokeai/backend/model_manager/search.py
+++ b/invokeai/backend/model_manager/search.py
@@ -141,7 +141,7 @@ class ModelSearch(ModelSearchBase):
             self._directory = self.config.models_path / self._directory
         self.stats = SearchStats()  # zero out
         self.search_started()  # This will initialize _models_found to empty
-        self._walk_directory(directory)
+        self._walk_directory(self._directory)
         self.search_completed()
         return self.models_found
 

From f16e64084b62ee085540406fe1fd0a78dee23279 Mon Sep 17 00:00:00 2001
From: Brandon Rising <contact@brandonrising.com>
Date: Fri, 23 Feb 2024 15:37:51 -0500
Subject: [PATCH 367/411] Ruff checks

---
 invokeai/app/api/routers/model_manager.py | 2 +-
 invokeai/backend/model_manager/search.py  | 6 +++---
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/invokeai/app/api/routers/model_manager.py b/invokeai/app/api/routers/model_manager.py
index 50ebe5ce64..3a701297cd 100644
--- a/invokeai/app/api/routers/model_manager.py
+++ b/invokeai/app/api/routers/model_manager.py
@@ -273,7 +273,7 @@ async def scan_for_models(
     scan_path: str = Query(description="Directory path to search for models", default=None),
 ) -> List[FoundModel]:
     path = pathlib.Path(scan_path)
-    if not scan_path or not path.is_dir():
+    if not path.is_dir():
         raise HTTPException(
             status_code=400,
             detail=f"The search path '{scan_path}' does not exist or is not directory",
diff --git a/invokeai/backend/model_manager/search.py b/invokeai/backend/model_manager/search.py
index 330cff4e08..ff2e7a1a5b 100644
--- a/invokeai/backend/model_manager/search.py
+++ b/invokeai/backend/model_manager/search.py
@@ -25,10 +25,10 @@ from abc import ABC, abstractmethod
 from logging import Logger
 from pathlib import Path
 from typing import Callable, Optional, Set, Union
-from invokeai.app.services.config import InvokeAIAppConfig
 
 from pydantic import BaseModel, Field
 
+from invokeai.app.services.config import InvokeAIAppConfig
 from invokeai.backend.util.logging import InvokeAILogger
 
 default_logger: Logger = InvokeAILogger.get_logger()
@@ -167,15 +167,15 @@ class ModelSearch(ModelSearchBase):
         ):
             try:
                 self.model_found(absolute_path)
+                return
             except KeyboardInterrupt:
                 raise
             except Exception as e:
                 self.logger.warning(str(e))
-            finally:
                 return
 
         for n in file_names:
-            if any([n.endswith(suffix) for suffix in {".ckpt", ".bin", ".pth", ".safetensors", ".pt"}]):
+            if n.endswith((".ckpt", ".bin", ".pth", ".safetensors", ".pt")):
                 try:
                     self.model_found(absolute_path / n)
                 except KeyboardInterrupt:

From e7afae0159051e5e212860c22b5f79119a9c6974 Mon Sep 17 00:00:00 2001
From: Brandon Rising <brandon@invoke.ai>
Date: Wed, 28 Feb 2024 13:29:14 -0500
Subject: [PATCH 368/411] Switch absolute path to as_posix in _walk_directory

---
 invokeai/backend/model_manager/search.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/invokeai/backend/model_manager/search.py b/invokeai/backend/model_manager/search.py
index ff2e7a1a5b..b1ee0c22de 100644
--- a/invokeai/backend/model_manager/search.py
+++ b/invokeai/backend/model_manager/search.py
@@ -151,7 +151,7 @@ class ModelSearch(ModelSearchBase):
                 or not absolute_path.exists() \
                     or absolute_path.parent in self.models_found:
             return
-        entries = os.scandir(absolute_path)
+        entries = os.scandir(absolute_path.as_posix())
         entries = [entry for entry in entries if not entry.name.startswith(".")]
         dirs = [entry for entry in entries if entry.is_dir()]
         file_names = [entry.name for entry in entries if entry.is_file()]

From 01898d766fd69fff761def530e36e08e649f2545 Mon Sep 17 00:00:00 2001
From: Brandon Rising <brandon@invoke.ai>
Date: Wed, 28 Feb 2024 15:11:15 -0500
Subject: [PATCH 369/411] Fix merge with next

---
 invokeai/app/api/routers/model_manager.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/invokeai/app/api/routers/model_manager.py b/invokeai/app/api/routers/model_manager.py
index 3a701297cd..50ebe5ce64 100644
--- a/invokeai/app/api/routers/model_manager.py
+++ b/invokeai/app/api/routers/model_manager.py
@@ -273,7 +273,7 @@ async def scan_for_models(
     scan_path: str = Query(description="Directory path to search for models", default=None),
 ) -> List[FoundModel]:
     path = pathlib.Path(scan_path)
-    if not path.is_dir():
+    if not scan_path or not path.is_dir():
         raise HTTPException(
             status_code=400,
             detail=f"The search path '{scan_path}' does not exist or is not directory",

From ae34bcfbc036e3f016b0f6a9493c95df51c24fdd Mon Sep 17 00:00:00 2001
From: blessedcoolant <54517381+blessedcoolant@users.noreply.github.com>
Date: Thu, 29 Feb 2024 11:32:28 +0530
Subject: [PATCH 370/411] fix: Assertion issue with SDXL Compel

---
 invokeai/app/invocations/compel.py | 24 +++++++-----------------
 invokeai/backend/model_patcher.py  |  8 ++++----
 2 files changed, 11 insertions(+), 21 deletions(-)

diff --git a/invokeai/app/invocations/compel.py b/invokeai/app/invocations/compel.py
index 771c811eea..ff13658052 100644
--- a/invokeai/app/invocations/compel.py
+++ b/invokeai/app/invocations/compel.py
@@ -1,17 +1,11 @@
-from typing import Iterator, List, Optional, Tuple, Union
+from typing import Iterator, List, Optional, Tuple, Union, cast
 
 import torch
 from compel import Compel, ReturnedEmbeddingsType
 from compel.prompt_parser import Blend, Conjunction, CrossAttentionControlSubstitute, FlattenedPrompt, Fragment
-from transformers import CLIPTextModel, CLIPTokenizer
+from transformers import CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
 
-from invokeai.app.invocations.fields import (
-    FieldDescriptions,
-    Input,
-    InputField,
-    OutputField,
-    UIComponent,
-)
+from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField, UIComponent
 from invokeai.app.invocations.primitives import ConditioningOutput
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.app.util.ti_utils import generate_ti_list
@@ -25,12 +19,7 @@ from invokeai.backend.stable_diffusion.diffusion.conditioning_data import (
 )
 from invokeai.backend.util.devices import torch_dtype
 
-from .baseinvocation import (
-    BaseInvocation,
-    BaseInvocationOutput,
-    invocation,
-    invocation_output,
-)
+from .baseinvocation import BaseInvocation, BaseInvocationOutput, invocation, invocation_output
 from .model import ClipField
 
 # unconditioned: Optional[torch.Tensor]
@@ -149,7 +138,7 @@ class SDXLPromptInvocationBase:
         assert isinstance(tokenizer_model, CLIPTokenizer)
         text_encoder_info = context.models.load(**clip_field.text_encoder.model_dump())
         text_encoder_model = text_encoder_info.model
-        assert isinstance(text_encoder_model, CLIPTextModel)
+        assert isinstance(text_encoder_model, (CLIPTextModel, CLIPTextModelWithProjection))
 
         # return zero on empty
         if prompt == "" and zero_on_empty:
@@ -196,7 +185,8 @@ class SDXLPromptInvocationBase:
             # Apply CLIP Skip after LoRA to prevent LoRA application from failing on skipped layers.
             ModelPatcher.apply_clip_skip(text_encoder_model, clip_field.skipped_layers),
         ):
-            assert isinstance(text_encoder, CLIPTextModel)
+            assert isinstance(text_encoder, (CLIPTextModel, CLIPTextModelWithProjection))
+            text_encoder = cast(CLIPTextModel, text_encoder)
             compel = Compel(
                 tokenizer=tokenizer,
                 text_encoder=text_encoder,
diff --git a/invokeai/backend/model_patcher.py b/invokeai/backend/model_patcher.py
index bee8909c31..473a088308 100644
--- a/invokeai/backend/model_patcher.py
+++ b/invokeai/backend/model_patcher.py
@@ -4,12 +4,12 @@ from __future__ import annotations
 
 import pickle
 from contextlib import contextmanager
-from typing import Any, Dict, Iterator, List, Optional, Tuple
+from typing import Any, Dict, Iterator, List, Optional, Tuple, Union
 
 import numpy as np
 import torch
 from diffusers import OnnxRuntimeModel, UNet2DConditionModel
-from transformers import CLIPTextModel, CLIPTokenizer
+from transformers import CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
 
 from invokeai.app.shared.models import FreeUConfig
 from invokeai.backend.model_manager import AnyModel
@@ -168,7 +168,7 @@ class ModelPatcher:
     def apply_ti(
         cls,
         tokenizer: CLIPTokenizer,
-        text_encoder: CLIPTextModel,
+        text_encoder: Union[CLIPTextModel, CLIPTextModelWithProjection],
         ti_list: List[Tuple[str, TextualInversionModelRaw]],
     ) -> Iterator[Tuple[CLIPTokenizer, TextualInversionManager]]:
         init_tokens_count = None
@@ -265,7 +265,7 @@ class ModelPatcher:
     @contextmanager
     def apply_clip_skip(
         cls,
-        text_encoder: CLIPTextModel,
+        text_encoder: Union[CLIPTextModel, CLIPTextModelWithProjection],
         clip_skip: int,
     ) -> None:
         skipped_layers = []

From 0305e90287fa5f1356d2fb7f5e73f40a6cb10605 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Thu, 29 Feb 2024 20:05:11 +1100
Subject: [PATCH 371/411] chore: ruff

---
 invokeai/backend/model_manager/search.py | 10 ++++++----
 1 file changed, 6 insertions(+), 4 deletions(-)

diff --git a/invokeai/backend/model_manager/search.py b/invokeai/backend/model_manager/search.py
index b1ee0c22de..7e89c394b1 100644
--- a/invokeai/backend/model_manager/search.py
+++ b/invokeai/backend/model_manager/search.py
@@ -118,7 +118,7 @@ class ModelSearch(ModelSearchBase):
     """
 
     models_found: Set[Path] = Field(default_factory=set)
-    config: InvokeAIAppConfig =  InvokeAIAppConfig.get_config()
+    config: InvokeAIAppConfig = InvokeAIAppConfig.get_config()
 
     def search_started(self) -> None:
         self.models_found = set()
@@ -147,9 +147,11 @@ class ModelSearch(ModelSearchBase):
 
     def _walk_directory(self, path: Union[Path, str], max_depth: int = 20) -> None:
         absolute_path = Path(path)
-        if len(absolute_path.parts) - len(self._directory.parts) > max_depth \
-                or not absolute_path.exists() \
-                    or absolute_path.parent in self.models_found:
+        if (
+            len(absolute_path.parts) - len(self._directory.parts) > max_depth
+            or not absolute_path.exists()
+            or absolute_path.parent in self.models_found
+        ):
             return
         entries = os.scandir(absolute_path.as_posix())
         entries = [entry for entry in entries if not entry.name.startswith(".")]

From 39725e95608337d85e660de6846f40fb94176ae3 Mon Sep 17 00:00:00 2001
From: Brandon Rising <contact@brandonrising.com>
Date: Wed, 28 Feb 2024 11:27:47 -0500
Subject: [PATCH 372/411] Next: Remove deprecated app.on_event usage in api
 runner

---
 invokeai/app/api_app.py | 31 ++++++++++++++++++-------------
 1 file changed, 18 insertions(+), 13 deletions(-)

diff --git a/invokeai/app/api_app.py b/invokeai/app/api_app.py
index f6b08ddba6..5fdf55d1ef 100644
--- a/invokeai/app/api_app.py
+++ b/invokeai/app/api_app.py
@@ -2,6 +2,7 @@
 # which are imported/used before parse_args() is called will get the default config values instead of the
 # values from the command line or config file.
 import sys
+from contextlib import asynccontextmanager
 
 from invokeai.app.api.no_cache_staticfiles import NoCacheStaticFiles
 from invokeai.version.invokeai_version import __version__
@@ -71,9 +72,25 @@ logger = InvokeAILogger.get_logger(config=app_config)
 mimetypes.add_type("application/javascript", ".js")
 mimetypes.add_type("text/css", ".css")
 
+
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    # Add startup event to load dependencies
+    ApiDependencies.initialize(config=app_config, event_handler_id=event_handler_id, logger=logger)
+    yield
+    # Shut down threads
+    ApiDependencies.shutdown()
+
+
 # Create the app
 # TODO: create this all in a method so configuration/etc. can be passed in?
-app = FastAPI(title="Invoke - Community Edition", docs_url=None, redoc_url=None, separate_input_output_schemas=False)
+app = FastAPI(
+    title="Invoke - Community Edition",
+    docs_url=None,
+    redoc_url=None,
+    separate_input_output_schemas=False,
+    lifespan=lifespan,
+)
 
 # Add event handler
 event_handler_id: int = id(app)
@@ -96,18 +113,6 @@ app.add_middleware(
 app.add_middleware(GZipMiddleware, minimum_size=1000)
 
 
-# Add startup event to load dependencies
-@app.on_event("startup")
-async def startup_event() -> None:
-    ApiDependencies.initialize(config=app_config, event_handler_id=event_handler_id, logger=logger)
-
-
-# Shut down threads
-@app.on_event("shutdown")
-async def shutdown_event() -> None:
-    ApiDependencies.shutdown()
-
-
 # Include all routers
 app.include_router(utilities.utilities_router, prefix="/api")
 app.include_router(model_manager.model_manager_router, prefix="/api")

From 0b0128647b021511e462625d2dd35114be6332c9 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Thu, 29 Feb 2024 21:34:25 +1100
Subject: [PATCH 373/411] feat(nodes): revise model load API args

---
 invokeai/app/invocations/ip_adapter.py        |  2 +-
 .../app/services/shared/invocation_context.py | 26 +++++++++----------
 invokeai/app/util/ti_utils.py                 |  2 +-
 3 files changed, 15 insertions(+), 15 deletions(-)

diff --git a/invokeai/app/invocations/ip_adapter.py b/invokeai/app/invocations/ip_adapter.py
index 15e254010b..bebdc29b86 100644
--- a/invokeai/app/invocations/ip_adapter.py
+++ b/invokeai/app/invocations/ip_adapter.py
@@ -93,7 +93,7 @@ class IPAdapterInvocation(BaseInvocation):
         image_encoder_model_id = ip_adapter_info.image_encoder_model_id
         image_encoder_model_name = image_encoder_model_id.split("/")[-1].strip()
         image_encoder_models = context.models.search_by_attrs(
-            model_name=image_encoder_model_name, base_model=BaseModelType.Any, model_type=ModelType.CLIPVision
+            name=image_encoder_model_name, base=BaseModelType.Any, type=ModelType.CLIPVision
         )
         assert len(image_encoder_models) == 1
         image_encoder_model = CLIPVisionModelField(key=image_encoder_models[0].key)
diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index 31064a5e7c..cbbe3216cc 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -289,7 +289,7 @@ class ModelsInterface(InvocationContextInterface):
         )
 
     def load_by_attrs(
-        self, model_name: str, base_model: BaseModelType, model_type: ModelType, submodel: Optional[SubModelType] = None
+        self, name: str, base: BaseModelType, type: ModelType, submodel_type: Optional[SubModelType] = None
     ) -> LoadedModel:
         """
         Loads a model by its attributes.
@@ -300,10 +300,10 @@ class ModelsInterface(InvocationContextInterface):
         :param submodel: For main (pipeline models), the submodel to fetch
         """
         return self._services.model_manager.load_model_by_attr(
-            model_name=model_name,
-            base_model=base_model,
-            model_type=model_type,
-            submodel=submodel,
+            model_name=name,
+            base_model=base,
+            model_type=type,
+            submodel=submodel_type,
             context_data=self._data,
         )
 
@@ -333,10 +333,10 @@ class ModelsInterface(InvocationContextInterface):
 
     def search_by_attrs(
         self,
-        model_name: Optional[str] = None,
-        base_model: Optional[BaseModelType] = None,
-        model_type: Optional[ModelType] = None,
-        model_format: Optional[ModelFormat] = None,
+        name: Optional[str] = None,
+        base: Optional[BaseModelType] = None,
+        type: Optional[ModelType] = None,
+        format: Optional[ModelFormat] = None,
     ) -> list[AnyModelConfig]:
         """
         Searches for models by attributes.
@@ -348,10 +348,10 @@ class ModelsInterface(InvocationContextInterface):
         """
 
         return self._services.model_manager.store.search_by_attr(
-            model_name=model_name,
-            base_model=base_model,
-            model_type=model_type,
-            model_format=model_format,
+            model_name=name,
+            base_model=base,
+            model_type=type,
+            model_format=format,
         )
 
 
diff --git a/invokeai/app/util/ti_utils.py b/invokeai/app/util/ti_utils.py
index b5c884c9b7..d204a40183 100644
--- a/invokeai/app/util/ti_utils.py
+++ b/invokeai/app/util/ti_utils.py
@@ -30,7 +30,7 @@ def generate_ti_list(
         except UnknownModelException:
             try:
                 loaded_model = context.models.load_by_attrs(
-                    model_name=name_or_key, base_model=base, model_type=ModelType.TextualInversion
+                    name=name_or_key, base=base, type=ModelType.TextualInversion
                 )
                 model = loaded_model.model
                 assert isinstance(model, TextualInversionModelRaw)

From e364ce1d4e94d52e378a58a9b0ca1e2e7ee2daf6 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Thu, 29 Feb 2024 22:32:29 +1100
Subject: [PATCH 374/411] docs: bump mkdocs, add mkdocstrings

Also remove ancient requirements file - the docs dependencies are in the pyproject.toml file.
---
 docs/requirements-mkdocs.txt | 5 -----
 pyproject.toml               | 5 +++--
 2 files changed, 3 insertions(+), 7 deletions(-)
 delete mode 100644 docs/requirements-mkdocs.txt

diff --git a/docs/requirements-mkdocs.txt b/docs/requirements-mkdocs.txt
deleted file mode 100644
index a637622954..0000000000
--- a/docs/requirements-mkdocs.txt
+++ /dev/null
@@ -1,5 +0,0 @@
-mkdocs
-mkdocs-material>=8, <9
-mkdocs-git-revision-date-localized-plugin
-mkdocs-redirects==1.2.0
-
diff --git a/pyproject.toml b/pyproject.toml
index 5345851951..b25c82b0da 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -105,9 +105,10 @@ dependencies = [
 "onnx-directml" = ["onnxruntime-directml"]
 "dist" = ["pip-tools", "pipdeptree", "twine"]
 "docs" = [
-  "mkdocs-material<9.0",
+  "mkdocs-material",
   "mkdocs-git-revision-date-localized-plugin",
-  "mkdocs-redirects==1.2.0",
+  "mkdocs-redirects",
+  "mkdocstrings[python]",
 ]
 "dev" = ["jurigged", "pudb", "snakeviz", "gprof2dot"]
 "test" = [

From ae19971f657e4820dee656023e0adf10e5478c85 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Thu, 29 Feb 2024 23:02:27 +1100
Subject: [PATCH 375/411] docs: update mkdocs config

---
 docs/stylesheets/extra.css |   5 --
 mkdocs.yml                 | 101 +++++++++++++++++++------------------
 2 files changed, 52 insertions(+), 54 deletions(-)
 delete mode 100644 docs/stylesheets/extra.css

diff --git a/docs/stylesheets/extra.css b/docs/stylesheets/extra.css
deleted file mode 100644
index 42a2cfe74a..0000000000
--- a/docs/stylesheets/extra.css
+++ /dev/null
@@ -1,5 +0,0 @@
-:root {
-    --md-primary-fg-color:        #35A4DB;
-    --md-primary-fg-color--light: #35A4DB;
-    --md-primary-fg-color--dark:  #35A4DB;
-  }
\ No newline at end of file
diff --git a/mkdocs.yml b/mkdocs.yml
index bdd429fb93..f1239dc318 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -15,7 +15,7 @@ edit_uri: edit/main/docs/
 copyright: Copyright &copy; 2023 InvokeAI Team
 
 extra_css:
-    - stylesheets/extra.css
+  - stylesheets/extra.css
 
 # Configuration
 theme:
@@ -25,18 +25,7 @@ theme:
     edit: material/file-document-edit-outline
   favicon: img/favicon.ico
   palette:
-    # - media: '(prefers-color-scheme: light)'
-    #   scheme: default
-    #   primary: custom
-    #   toggle:
-    #     icon: material/lightbulb
-    #     name: Switch to dark mode
-    - media: '(prefers-color-scheme: dark)'
-      scheme: slate
-      primary: custom
-      # toggle:
-      #   icon: material/lightbulb-outline
-      #   name: Switch to light mode
+    scheme: slate
   features:
     - navigation.instant
     - navigation.tabs
@@ -48,7 +37,6 @@ theme:
     - search.suggest
     - toc.integrate
 
-
 # Extensions
 markdown_extensions:
   - abbr
@@ -66,8 +54,8 @@ markdown_extensions:
   - pymdownx.caret
   - pymdownx.details
   - pymdownx.emoji:
-      emoji_index: !!python/name:materialx.emoji.twemoji
-      emoji_generator: !!python/name:materialx.emoji.to_svg
+      emoji_index: !!python/name:material.extensions.emoji.twemoji
+      emoji_generator: !!python/name:material.extensions.emoji.to_svg
   - pymdownx.highlight:
       anchor_linenums: true
   - pymdownx.inlinehilite
@@ -97,12 +85,25 @@ plugins:
       enable_creation_date: true
   - redirects:
       redirect_maps:
-          'installation/INSTALL_AUTOMATED.md': 'installation/010_INSTALL_AUTOMATED.md'
-          'installation/INSTALL_MANUAL.md': 'installation/020_INSTALL_MANUAL.md'
-          'installation/INSTALL_SOURCE.md': 'installation/020_INSTALL_MANUAL.md'
-          'installation/INSTALL_DOCKER.md': 'installation/040_INSTALL_DOCKER.md'
-          'installation/INSTALLING_MODELS.md': 'installation/050_INSTALLING_MODELS.md'
-          'installation/INSTALL_PATCHMATCH.md': 'installation/060_INSTALL_PATCHMATCH.md'
+        'installation/INSTALL_AUTOMATED.md': 'installation/010_INSTALL_AUTOMATED.md'
+        'installation/INSTALL_MANUAL.md': 'installation/020_INSTALL_MANUAL.md'
+        'installation/INSTALL_SOURCE.md': 'installation/020_INSTALL_MANUAL.md'
+        'installation/INSTALL_DOCKER.md': 'installation/040_INSTALL_DOCKER.md'
+        'installation/INSTALLING_MODELS.md': 'installation/050_INSTALLING_MODELS.md'
+        'installation/INSTALL_PATCHMATCH.md': 'installation/060_INSTALL_PATCHMATCH.md'
+  - mkdocstrings:
+      handlers:
+        python:
+          options:
+            separate_signature: true
+            show_signature_annotations: true
+            parameter_headings: false
+            signature_crossrefs: true
+            show_source: false
+            summary: true
+            show_root_heading: true
+            show_root_full_path: false
+            show_bases: false
 
 extra_javascript:
   - https://unpkg.com/tablesort@5.3.0/dist/tablesort.min.js
@@ -115,8 +116,8 @@ extra:
     property: G-2X4JR4S4FB
 
 nav:
-    - Home: 'index.md'
-    - Installation:
+  - Home: 'index.md'
+  - Installation:
       - Overview: 'installation/INSTALLATION.md'
       - Installing with the Automated Installer: 'installation/010_INSTALL_AUTOMATED.md'
       - Installing Manually: 'installation/020_INSTALL_MANUAL.md'
@@ -127,14 +128,14 @@ nav:
       - Installing xFormers: 'installation/070_INSTALL_XFORMERS.md'
       - Developers Documentation: 'installation/Developers_documentation/BUILDING_BINARY_INSTALLERS.md'
       - Deprecated Documentation:
-        - Binary Installer: 'installation/deprecated_documentation/INSTALL_BINARY.md'
-        - Runninng InvokeAI on Google Colab: 'installation/deprecated_documentation/INSTALL_JUPYTER.md'
-        - Manual Installation on Linux: 'installation/deprecated_documentation/INSTALL_LINUX.md'
-        - Manual Installation on macOS: 'installation/deprecated_documentation/INSTALL_MAC.md'
-        - Manual Installation on Windows: 'installation/deprecated_documentation/INSTALL_WINDOWS.md'
-        - Installing Invoke with pip: 'installation/deprecated_documentation/INSTALL_PCP.md'
-        - Source Installer: 'installation/deprecated_documentation/INSTALL_SOURCE.md'
-    - Workflows & Nodes:
+          - Binary Installer: 'installation/deprecated_documentation/INSTALL_BINARY.md'
+          - Runninng InvokeAI on Google Colab: 'installation/deprecated_documentation/INSTALL_JUPYTER.md'
+          - Manual Installation on Linux: 'installation/deprecated_documentation/INSTALL_LINUX.md'
+          - Manual Installation on macOS: 'installation/deprecated_documentation/INSTALL_MAC.md'
+          - Manual Installation on Windows: 'installation/deprecated_documentation/INSTALL_WINDOWS.md'
+          - Installing Invoke with pip: 'installation/deprecated_documentation/INSTALL_PCP.md'
+          - Source Installer: 'installation/deprecated_documentation/INSTALL_SOURCE.md'
+  - Workflows & Nodes:
       - Nodes Overview: 'nodes/overview.md'
       - Workflow Editor Basics: 'nodes/NODES.md'
       - List of Default Nodes: 'nodes/defaultNodes.md'
@@ -142,8 +143,10 @@ nav:
       - ComfyUI to InvokeAI: 'nodes/comfyToInvoke.md'
       - Facetool Node: 'nodes/detailedNodes/faceTools.md'
       - Contributing Nodes: 'nodes/contributingNodes.md'
-    - Community Nodes: 'nodes/communityNodes.md'
-    - Features:
+      - Migrating from v3 to v4: 'nodes/NODES_MIGRATION_V3_V4.md'
+      - Invocation API: 'nodes/INVOCATION_API.md'
+  - Community Nodes: 'nodes/communityNodes.md'
+  - Features:
       - Overview: 'features/index.md'
       - New to InvokeAI?: 'help/gettingStartedWithAI.md'
       - Configuration: 'features/CONFIGURATION.md'
@@ -152,35 +155,35 @@ nav:
       - Controlling Logging: 'features/LOGGING.md'
       - LoRAs & LCM-LoRAs: 'features/LORAS.md'
       - Model Merging: 'features/MODEL_MERGING.md'
-      - Workflows &  Nodes : 'nodes/overview'
+      - Workflows &  Nodes: 'nodes/overview'
       - NSFW Checker: 'features/WATERMARK+NSFW.md'
       - Postprocessing: 'features/POSTPROCESS.md'
       - Prompting Features: 'features/PROMPTS.md'
       - Textual Inversions:
-        - Textual Inversions: 'features/TEXTUAL_INVERSIONS.md'
-        - Textual Inversion Training: 'features/TRAINING.md'
+          - Textual Inversions: 'features/TEXTUAL_INVERSIONS.md'
+          - Textual Inversion Training: 'features/TRAINING.md'
       - Unified Canvas: 'features/UNIFIED_CANVAS.md'
       - InvokeAI Web Server: 'features/WEB.md'
-      - WebUI Hotkeys: "features/WEBUIHOTKEYS.md"
-      - Maintenance Utilities: "features/UTILITIES.md"
+      - WebUI Hotkeys: 'features/WEBUIHOTKEYS.md'
+      - Maintenance Utilities: 'features/UTILITIES.md'
       - Other: 'features/OTHER.md'
-    - Contributing:
+  - Contributing:
       - How to Contribute: 'contributing/CONTRIBUTING.md'
       - InvokeAI Code of Conduct: 'CODE_OF_CONDUCT.md'
       - Development:
-        - Overview: 'contributing/contribution_guides/development.md'
-        - New Contributors: 'contributing/contribution_guides/newContributorChecklist.md'
-        - Model Manager v2: 'contributing/MODEL_MANAGER.md'
-        - Frontend Documentation: 'contributing/contribution_guides/contributingToFrontend.md'
-        - Local Development: 'contributing/LOCAL_DEVELOPMENT.md'
-        - Testing: 'contributing/TESTS.md'
+          - Overview: 'contributing/contribution_guides/development.md'
+          - New Contributors: 'contributing/contribution_guides/newContributorChecklist.md'
+          - Model Manager v2: 'contributing/MODEL_MANAGER.md'
+          - Frontend Documentation: 'contributing/contribution_guides/contributingToFrontend.md'
+          - Local Development: 'contributing/LOCAL_DEVELOPMENT.md'
+          - Testing: 'contributing/TESTS.md'
       - Documentation: 'contributing/contribution_guides/documentation.md'
       - Nodes: 'contributing/INVOCATIONS.md'
       - Model Manager: 'contributing/MODEL_MANAGER.md'
       - Download Queue: 'contributing/DOWNLOAD_QUEUE.md'
       - Translation: 'contributing/contribution_guides/translation.md'
       - Tutorials: 'contributing/contribution_guides/tutorials.md'
-    - Deprecated:
+  - Deprecated:
       - InvokeAI 2.3: 'deprecated/2to3.md'
       - Command Line Interface: 'deprecated/CLI.md'
       - Changelog: 'CHANGELOG.md'
@@ -190,11 +193,11 @@ nav:
       - Inpainting: 'deprecated/INPAINTING.md'
       - Outpainting: 'deprecated/OUTPAINTING.md'
       - Troubleshooting: 'help/deprecated/TROUBLESHOOT.md'
-    - Help:
+  - Help:
       - Getting Started: 'help/gettingStartedWithAI.md'
       - FAQs: 'help/FAQ.md'
       - Diffusion Overview: 'help/diffusion.md'
       - Sampler Convergence: 'help/SAMPLER_CONVERGENCE.md'
-    - Other:
+  - Other:
       - Contributors: 'other/CONTRIBUTORS.md'
       - CompViz-README: 'other/README-CompViz.md'

From 2f26768d19018a26ea280f3b37d184ff8b3b5d53 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Thu, 29 Feb 2024 23:02:57 +1100
Subject: [PATCH 376/411] fix: make invocation_context.py accessible to mkdocs

Needs an `__init__.py`.
---
 invokeai/app/__init__.py | 0
 1 file changed, 0 insertions(+), 0 deletions(-)
 create mode 100644 invokeai/app/__init__.py

diff --git a/invokeai/app/__init__.py b/invokeai/app/__init__.py
new file mode 100644
index 0000000000..e69de29bb2

From 753919c6d7c33676b269283e3d67936402e8544d Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Thu, 29 Feb 2024 23:03:17 +1100
Subject: [PATCH 377/411] docs(nodes): update all docstrings for public nodes
 API

---
 .../app/services/shared/invocation_context.py | 265 +++++++++++-------
 1 file changed, 171 insertions(+), 94 deletions(-)

diff --git a/invokeai/app/services/shared/invocation_context.py b/invokeai/app/services/shared/invocation_context.py
index cbbe3216cc..7d378e22e3 100644
--- a/invokeai/app/services/shared/invocation_context.py
+++ b/invokeai/app/services/shared/invocation_context.py
@@ -65,75 +65,86 @@ class InvocationContextInterface:
 
 class BoardsInterface(InvocationContextInterface):
     def create(self, board_name: str) -> BoardDTO:
-        """
-        Creates a board.
+        """Creates a board.
 
-        :param board_name: The name of the board to create.
+        Args:
+            board_name: The name of the board to create.
+
+        Returns:
+            The created board DTO.
         """
         return self._services.boards.create(board_name)
 
     def get_dto(self, board_id: str) -> BoardDTO:
-        """
-        Gets a board DTO.
+        """Gets a board DTO.
 
-        :param board_id: The ID of the board to get.
+        Args:
+            board_id: The ID of the board to get.
+
+        Returns:
+            The board DTO.
         """
         return self._services.boards.get_dto(board_id)
 
     def get_all(self) -> list[BoardDTO]:
-        """
-        Gets all boards.
+        """Gets all boards.
+
+        Returns:
+            A list of all boards.
         """
         return self._services.boards.get_all()
 
     def add_image_to_board(self, board_id: str, image_name: str) -> None:
-        """
-        Adds an image to a board.
+        """Adds an image to a board.
 
-        :param board_id: The ID of the board to add the image to.
-        :param image_name: The name of the image to add to the board.
+        Args:
+            board_id: The ID of the board to add the image to.
+            image_name: The name of the image to add to the board.
         """
         return self._services.board_images.add_image_to_board(board_id, image_name)
 
     def get_all_image_names_for_board(self, board_id: str) -> list[str]:
-        """
-        Gets all image names for a board.
+        """Gets all image names for a board.
 
-        :param board_id: The ID of the board to get the image names for.
+        Args:
+            board_id: The ID of the board to get the image names for.
+
+        Returns:
+            A list of all image names for the board.
         """
         return self._services.board_images.get_all_board_image_names_for_board(board_id)
 
 
 class LoggerInterface(InvocationContextInterface):
     def debug(self, message: str) -> None:
-        """
-        Logs a debug message.
+        """Logs a debug message.
 
-        :param message: The message to log.
+        Args:
+            message: The message to log.
         """
         self._services.logger.debug(message)
 
     def info(self, message: str) -> None:
-        """
-        Logs an info message.
+        """Logs an info message.
 
-        :param message: The message to log.
+        Args:
+            message: The message to log.
         """
         self._services.logger.info(message)
 
     def warning(self, message: str) -> None:
-        """
-        Logs a warning message.
+        """Logs a warning message.
 
-        :param message: The message to log.
+        Args:
+            message: The message to log.
         """
         self._services.logger.warning(message)
 
     def error(self, message: str) -> None:
-        """
-        Logs an error message.
+        """Logs an error message.
 
-        :param message: The message to log.
+        Args:
+            message: The message to log.
         """
         self._services.logger.error(message)
 
@@ -146,20 +157,23 @@ class ImagesInterface(InvocationContextInterface):
         image_category: ImageCategory = ImageCategory.GENERAL,
         metadata: Optional[MetadataField] = None,
     ) -> ImageDTO:
-        """
-        Saves an image, returning its DTO.
+        """Saves an image, returning its DTO.
 
         If the current queue item has a workflow or metadata, it is automatically saved with the image.
 
-        :param image: The image to save, as a PIL image.
-        :param board_id: The board ID to add the image to, if it should be added. It the invocation \
+        Args:
+            image: The image to save, as a PIL image.
+            board_id: The board ID to add the image to, if it should be added. It the invocation \
             inherits from `WithBoard`, that board will be used automatically. **Use this only if \
             you want to override or provide a board manually!**
-        :param image_category: The category of the image. Only the GENERAL category is added \
+            image_category: The category of the image. Only the GENERAL category is added \
             to the gallery.
-        :param metadata: The metadata to save with the image, if it should have any. If the \
+            metadata: The metadata to save with the image, if it should have any. If the \
             invocation inherits from `WithMetadata`, that metadata will be used automatically. \
             **Use this only if you want to override or provide metadata manually!**
+
+        Returns:
+            The saved image DTO.
         """
 
         # If `metadata` is provided directly, use that. Else, use the metadata provided by `WithMetadata`, falling back to None.
@@ -189,11 +203,14 @@ class ImagesInterface(InvocationContextInterface):
         )
 
     def get_pil(self, image_name: str, mode: IMAGE_MODES | None = None) -> Image:
-        """
-        Gets an image as a PIL Image object.
+        """Gets an image as a PIL Image object.
 
-        :param image_name: The name of the image to get.
-        :param mode: The color mode to convert the image to. If None, the original mode is used.
+        Args:
+            image_name: The name of the image to get.
+            mode: The color mode to convert the image to. If None, the original mode is used.
+
+        Returns:
+            The image as a PIL Image object.
         """
         image = self._services.images.get_pil_image(image_name)
         if mode and mode != image.mode:
@@ -206,58 +223,76 @@ class ImagesInterface(InvocationContextInterface):
         return image
 
     def get_metadata(self, image_name: str) -> Optional[MetadataField]:
-        """
-        Gets an image's metadata, if it has any.
+        """Gets an image's metadata, if it has any.
 
-        :param image_name: The name of the image to get the metadata for.
+        Args:
+            image_name: The name of the image to get the metadata for.
+
+        Returns:
+            The image's metadata, if it has any.
         """
         return self._services.images.get_metadata(image_name)
 
     def get_dto(self, image_name: str) -> ImageDTO:
-        """
-        Gets an image as an ImageDTO object.
+        """Gets an image as an ImageDTO object.
 
-        :param image_name: The name of the image to get.
+        Args:
+            image_name: The name of the image to get.
+
+        Returns:
+            The image as an ImageDTO object.
         """
         return self._services.images.get_dto(image_name)
 
 
 class TensorsInterface(InvocationContextInterface):
     def save(self, tensor: Tensor) -> str:
-        """
-        Saves a tensor, returning its name.
+        """Saves a tensor, returning its name.
 
-        :param tensor: The tensor to save.
+        Args:
+            tensor: The tensor to save.
+
+        Returns:
+            The name of the saved tensor.
         """
 
         name = self._services.tensors.save(obj=tensor)
         return name
 
     def load(self, name: str) -> Tensor:
-        """
-        Loads a tensor by name.
+        """Loads a tensor by name.
 
-        :param name: The name of the tensor to load.
+        Args:
+            name: The name of the tensor to load.
+
+        Returns:
+            The loaded tensor.
         """
         return self._services.tensors.load(name)
 
 
 class ConditioningInterface(InvocationContextInterface):
     def save(self, conditioning_data: ConditioningFieldData) -> str:
-        """
-        Saves a conditioning data object, returning its name.
+        """Saves a conditioning data object, returning its name.
 
-        :param conditioning_data: The conditioning data to save.
+        Args:
+            conditioning_data: The conditioning data to save.
+
+        Returns:
+            The name of the saved conditioning data.
         """
 
         name = self._services.conditioning.save(obj=conditioning_data)
         return name
 
     def load(self, name: str) -> ConditioningFieldData:
-        """
-        Loads conditioning data by name.
+        """Loads conditioning data by name.
 
-        :param name: The name of the conditioning data to load.
+        Args:
+            name: The name of the conditioning data to load.
+
+        Returns:
+            The loaded conditioning data.
         """
 
         return self._services.conditioning.load(name)
@@ -265,20 +300,25 @@ class ConditioningInterface(InvocationContextInterface):
 
 class ModelsInterface(InvocationContextInterface):
     def exists(self, key: str) -> bool:
-        """
-        Checks if a model exists.
+        """Checks if a model exists.
 
-        :param key: The key of the model.
+        Args:
+            key: The key of the model.
+
+        Returns:
+            True if the model exists, False if not.
         """
         return self._services.model_manager.store.exists(key)
 
     def load(self, key: str, submodel_type: Optional[SubModelType] = None) -> LoadedModel:
-        """
-        Loads a model.
+        """Loads a model.
 
-        :param key: The key of the model.
-        :param submodel_type: The submodel of the model to get.
-        :returns: An object representing the loaded model.
+        Args:
+            key: The key of the model.
+            submodel_type: The submodel of the model to get.
+
+        Returns:
+            An object representing the loaded model.
         """
 
         # The model manager emits events as it loads the model. It needs the context data to build
@@ -291,13 +331,17 @@ class ModelsInterface(InvocationContextInterface):
     def load_by_attrs(
         self, name: str, base: BaseModelType, type: ModelType, submodel_type: Optional[SubModelType] = None
     ) -> LoadedModel:
-        """
-        Loads a model by its attributes.
+        """Loads a model by its attributes.
 
-        :param model_name: Name of to be fetched.
-        :param base_model: Base model
-        :param model_type: Type of the model
-        :param submodel: For main (pipeline models), the submodel to fetch
+        Args:
+            name: Name of the model.
+            base: The models' base type, e.g. `BaseModelType.StableDiffusion1`, `BaseModelType.StableDiffusionXL`, etc.
+            type: Type of the model, e.g. `ModelType.Main`, `ModelType.Vae`, etc.
+            submodel_type: The type of submodel to load, e.g. `SubModelType.UNet`, `SubModelType.TextEncoder`, etc. Only main
+            models have submodels.
+
+        Returns:
+            An object representing the loaded model.
         """
         return self._services.model_manager.load_model_by_attr(
             model_name=name,
@@ -308,26 +352,35 @@ class ModelsInterface(InvocationContextInterface):
         )
 
     def get_config(self, key: str) -> AnyModelConfig:
-        """
-        Gets a model's info, an dict-like object.
+        """Gets a model's config.
 
-        :param key: The key of the model.
+        Args:
+            key: The key of the model.
+
+        Returns:
+            The model's config.
         """
         return self._services.model_manager.store.get_model(key=key)
 
     def get_metadata(self, key: str) -> Optional[AnyModelRepoMetadata]:
-        """
-        Gets a model's metadata, if it has any.
+        """Gets a model's metadata, if it has any.
 
-        :param key: The key of the model.
+        Args:
+            key: The key of the model.
+
+        Returns:
+            The model's metadata, if it has any.
         """
         return self._services.model_manager.store.get_metadata(key=key)
 
     def search_by_path(self, path: Path) -> list[AnyModelConfig]:
-        """
-        Searches for models by path.
+        """Searches for models by path.
 
-        :param path: The path to search for.
+        Args:
+            path: The path to search for.
+
+        Returns:
+            A list of models that match the path.
         """
         return self._services.model_manager.store.search_by_path(path)
 
@@ -338,13 +391,16 @@ class ModelsInterface(InvocationContextInterface):
         type: Optional[ModelType] = None,
         format: Optional[ModelFormat] = None,
     ) -> list[AnyModelConfig]:
-        """
-        Searches for models by attributes.
+        """Searches for models by attributes.
 
-        :param model_name: Name of to be fetched.
-        :param base_model: Base model
-        :param model_type: Type of the model
-        :param submodel: For main (pipeline models), the submodel to fetch
+        Args:
+            name: The name to search for (exact match).
+            base: The base to search for, e.g. `BaseModelType.StableDiffusion1`, `BaseModelType.StableDiffusionXL`, etc.
+            type: Type type of model to search for, e.g. `ModelType.Main`, `ModelType.Vae`, etc.
+            format: The format of model to search for, e.g. `ModelFormat.Checkpoint`, `ModelFormat.Diffusers`, etc.
+
+        Returns:
+            A list of models that match the attributes.
         """
 
         return self._services.model_manager.store.search_by_attr(
@@ -357,7 +413,11 @@ class ModelsInterface(InvocationContextInterface):
 
 class ConfigInterface(InvocationContextInterface):
     def get(self) -> InvokeAIAppConfig:
-        """Gets the app's config."""
+        """Gets the app's config.
+
+        Returns:
+            The app's config.
+        """
 
         return self._services.configuration.get_config()
 
@@ -370,7 +430,11 @@ class UtilInterface(InvocationContextInterface):
         self._cancel_event = cancel_event
 
     def is_canceled(self) -> bool:
-        """Checks if the current invocation has been canceled."""
+        """Checks if the current session has been canceled.
+
+        Returns:
+            True if the current session has been canceled, False if not.
+        """
         return self._cancel_event.is_set()
 
     def sd_step_callback(self, intermediate_state: PipelineIntermediateState, base_model: BaseModelType) -> None:
@@ -380,8 +444,9 @@ class UtilInterface(InvocationContextInterface):
 
         This should be called after each denoising step.
 
-        :param intermediate_state: The intermediate state of the diffusion pipeline.
-        :param base_model: The base model for the current denoising step.
+        Args:
+            intermediate_state: The intermediate state of the diffusion pipeline.
+            base_model: The base model for the current denoising step.
         """
 
         stable_diffusion_step_callback(
@@ -394,8 +459,17 @@ class UtilInterface(InvocationContextInterface):
 
 
 class InvocationContext:
-    """
-    The `InvocationContext` provides access to various services and data for the current invocation.
+    """Provides access to various services and data for the current invocation.
+
+    Attributes:
+        images (ImagesInterface): Methods to save, get and update images and their metadata.
+        tensors (TensorsInterface): Methods to save and get tensors, including image, noise, masks, and masked images.
+        conditioning (ConditioningInterface): Methods to save and get conditioning data.
+        models (ModelsInterface): Methods to check if a model exists, get a model, and get a model's info.
+        logger (LoggerInterface): The app logger.
+        config (ConfigInterface): The app config.
+        util (UtilInterface): Utility methods, including a method to check if an invocation was canceled and step callbacks.
+        boards (BoardsInterface): Methods to interact with boards.
     """
 
     def __init__(
@@ -438,11 +512,14 @@ def build_invocation_context(
     data: InvocationContextData,
     cancel_event: threading.Event,
 ) -> InvocationContext:
-    """
-    Builds the invocation context for a specific invocation execution.
+    """Builds the invocation context for a specific invocation execution.
 
-    :param services: The invocation services to wrap.
-    :param data: The invocation context data.
+    Args:
+        services: The invocation services to wrap.
+        data: The invocation context data.
+
+    Returns:
+        The invocation context.
     """
 
     logger = LoggerInterface(services=services, data=data)

From 0b07e2aad45d0c3dfb430399430c804c881d4099 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Thu, 29 Feb 2024 23:03:34 +1100
Subject: [PATCH 378/411] docs: add v3 -> v4 migration, invocation API docs

---
 docs/nodes/INVOCATION_API.md        |  45 +++++++++
 docs/nodes/NODES_MIGRATION_V3_V4.md | 148 ++++++++++++++++++++++++++++
 2 files changed, 193 insertions(+)
 create mode 100644 docs/nodes/INVOCATION_API.md
 create mode 100644 docs/nodes/NODES_MIGRATION_V3_V4.md

diff --git a/docs/nodes/INVOCATION_API.md b/docs/nodes/INVOCATION_API.md
new file mode 100644
index 0000000000..c85c152c2b
--- /dev/null
+++ b/docs/nodes/INVOCATION_API.md
@@ -0,0 +1,45 @@
+# Invocation API
+
+Each invocation's `invoke` method is provided a single arg - the Invocation
+Context.
+
+This object provides access to various methods, used to interact with the
+application. Loading and saving images, logging messages, etc.
+
+!!! warning ""
+
+    This API may shift slightly until the release of v4.0.0 as we work through a few final updates to the Model Manager.
+
+```py
+class MyInvocation(BaseInvocation):
+  ...
+  def invoke(self, context: InvocationContext) -> ImageOutput:
+      image_pil = context.images.get_pil(image_name)
+      # Do something to the image
+      image_dto = context.images.save(image_pil)
+      # Log a message
+      context.logger.info(f"Did something cool, image saved!")
+      ...
+```
+
+<!-- prettier-ignore-start -->
+::: invokeai.app.services.shared.invocation_context.InvocationContext
+    options:
+        members: false
+
+::: invokeai.app.services.shared.invocation_context.ImagesInterface
+
+::: invokeai.app.services.shared.invocation_context.TensorsInterface
+
+::: invokeai.app.services.shared.invocation_context.ConditioningInterface
+
+::: invokeai.app.services.shared.invocation_context.ModelsInterface
+
+::: invokeai.app.services.shared.invocation_context.LoggerInterface
+
+::: invokeai.app.services.shared.invocation_context.ConfigInterface
+
+::: invokeai.app.services.shared.invocation_context.UtilInterface
+
+::: invokeai.app.services.shared.invocation_context.BoardsInterface
+<!-- prettier-ignore-end -->
diff --git a/docs/nodes/NODES_MIGRATION_V3_V4.md b/docs/nodes/NODES_MIGRATION_V3_V4.md
new file mode 100644
index 0000000000..3ba0854581
--- /dev/null
+++ b/docs/nodes/NODES_MIGRATION_V3_V4.md
@@ -0,0 +1,148 @@
+# Invoke v4.0.0 Nodes API Migration guide
+
+Invoke v4.0.0 is versioned as such due to breaking changes to the API utilized
+by nodes, both core and custom.
+
+## Motivation
+
+Prior to v4.0.0, the `invokeai` python package has not be set up to be utilized
+as a library. That is to say, it didn't have any explicitly public API, and node
+authors had to work with the unstable internal application API.
+
+v4.0.0 introduces a stable public API for nodes.
+
+## Changes
+
+There are two node-author-facing changes:
+
+1. Import Paths
+1. Invocation Context API
+
+### Import Paths
+
+All public objects are now exported from `invokeai.invocation_api`:
+
+```py
+# Old
+from invokeai.app.invocations.baseinvocation import (
+    BaseInvocation,
+    InputField,
+    InvocationContext,
+    invocation,
+)
+from invokeai.app.invocations.primitives import ImageField
+
+# New
+from invokeai.invocation_api import (
+    BaseInvocation,
+    ImageField,
+    InputField,
+    InvocationContext,
+    invocation,
+)
+```
+
+It's possible that we've missed some classes you need in your node. Please let
+us know if that's the case.
+
+### Invocation Context API
+
+Most nodes utilize the Invocation Context, an object that is passed to the
+`invoke` that provides access to data and services a node may need.
+
+Until now, that object and the services it exposed were internal. Exposing them
+to nodes means that changes to our internal implementation could break nodes.
+The methods on the services are also often fairly complicated and allowed nodes
+to footgun.
+
+In v4.0.0, this object has been refactored to be much simpler.
+
+See [INVOCATION_API](./INVOCATION_API.md) for full details of the API.
+
+!!! warning ""
+
+    This API may shift slightly until the release of v4.0.0 as we work through a few final updates to the Model Manager.
+
+#### Improved Service Methods
+
+The biggest offender was the image save method:
+
+```py
+# Old
+image_dto = context.services.images.create(
+    image=image,
+    image_origin=ResourceOrigin.INTERNAL,
+    image_category=ImageCategory.GENERAL,
+    node_id=self.id,
+    session_id=context.graph_execution_state_id,
+    is_intermediate=self.is_intermediate,
+    metadata=self.metadata,
+    workflow=context.workflow,
+)
+
+# New
+image_dto = context.images.save(image=image)
+```
+
+Other methods are simplified, or enhanced with additional functionality:
+
+```py
+# Old
+image = context.services.images.get_pil_image(image_name)
+
+# New
+image = context.images.get_pil(image_name)
+image_cmyk = context.images.get_pil(image_name, "CMYK")
+```
+
+We also had some typing issues around tensors:
+
+```py
+# Old
+# `latents` typed as `torch.Tensor`, but could be `ConditioningFieldData`
+latents = context.services.latents.get(self.latents.latents_name)
+# `data` typed as `torch.Tenssor,` but could be `ConditioningFieldData`
+context.services.latents.save(latents_name, data)
+
+# New - separate methods for tensors and conditioning data w/ correct typing
+# Also, the service generates the names
+tensor_name = context.tensors.save(tensor)
+tensor = context.tensors.load(tensor_name)
+# For conditioning
+cond_name = context.conditioning.save(cond_data)
+cond_data = context.conditioning.load(cond_name)
+```
+
+#### Output Construction
+
+Core Outputs have builder functions right on them - no need to manually
+construct these objects, or use an extra utility:
+
+```py
+# Old
+image_output = ImageOutput(
+    image=ImageField(image_name=image_dto.image_name),
+    width=image_dto.width,
+    height=image_dto.height,
+)
+latents_output = build_latents_output(latents_name=name, latents=latents, seed=None)
+noise_output = NoiseOutput(
+    noise=LatentsField(latents_name=latents_name, seed=seed),
+    width=latents.size()[3] * 8,
+    height=latents.size()[2] * 8,
+)
+cond_output = ConditioningOutput(
+    conditioning=ConditioningField(
+        conditioning_name=conditioning_name,
+    ),
+)
+
+# New
+image_output = ImageOutput.build(image_dto)
+latents_output = LatentsOutput.build(latents_name=name, latents=noise, seed=self.seed)
+noise_output = NoiseOutput.build(latents_name=name, latents=noise, seed=self.seed)
+cond_output = ConditioningOutput.build(conditioning_name)
+```
+
+You can still create the objects using constructors if you want, but we suggest
+using the builder methods.

From c074beff7c94b0cfece1c913ba7bacc4f235ed23 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Fri, 1 Mar 2024 09:31:59 +1100
Subject: [PATCH 379/411] fix(ui): typo in feature tooltips

---
 .../common/components/InformationalPopover/constants.ts   | 8 +-------
 1 file changed, 1 insertion(+), 7 deletions(-)

diff --git a/invokeai/frontend/web/src/common/components/InformationalPopover/constants.ts b/invokeai/frontend/web/src/common/components/InformationalPopover/constants.ts
index ab03dcded2..b556816502 100644
--- a/invokeai/frontend/web/src/common/components/InformationalPopover/constants.ts
+++ b/invokeai/frontend/web/src/common/components/InformationalPopover/constants.ts
@@ -82,7 +82,7 @@ export const POPOVER_DATA: { [key in Feature]?: PopoverData } = {
   loraWeight: {
     href: 'https://support.invoke.ai/support/solutions/articles/151000159072-concepts-low-rank-adaptations-loras-',
   },
-  compositingBlur: {
+  compositingMaskBlur: {
     href: 'https://support.invoke.ai/support/solutions/articles/151000158838-compositing-settings',
   },
   compositingBlurMethod: {
@@ -91,12 +91,6 @@ export const POPOVER_DATA: { [key in Feature]?: PopoverData } = {
   compositingCoherenceMode: {
     href: 'https://support.invoke.ai/support/solutions/articles/151000158838-compositing-settings',
   },
-  compositingCoherenceSteps: {
-    href: 'https://support.invoke.ai/support/solutions/articles/151000158838-compositing-settings',
-  },
-  compositingStrength: {
-    href: 'https://support.invoke.ai/support/solutions/articles/151000158838-compositing-settings',
-  },
   infillMethod: {
     href: 'https://support.invoke.ai/support/solutions/articles/151000158841-infill-and-scaling',
   },

From bbbd18f11999c4cc586d8aaad5a29db57d714f2b Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Fri, 1 Mar 2024 09:37:27 +1100
Subject: [PATCH 380/411] fix(ui): baseUrl hardcoded api path

We now hav multiple api versions for different routers, so we cannot hardcode the `/api/v1` portion of the baseUrl
---
 invokeai/frontend/web/src/services/api/index.ts | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/invokeai/frontend/web/src/services/api/index.ts b/invokeai/frontend/web/src/services/api/index.ts
index 30cc7a9d3d..4c2770d817 100644
--- a/invokeai/frontend/web/src/services/api/index.ts
+++ b/invokeai/frontend/web/src/services/api/index.ts
@@ -60,7 +60,7 @@ const dynamicBaseQuery: BaseQueryFn<string | FetchArgs, unknown, FetchBaseQueryE
     (typeof args === 'string' && args.includes('openapi.json'));
 
   const fetchBaseQueryArgs: FetchBaseQueryArgs = {
-    baseUrl: baseUrl ? `${baseUrl}/api/v1` : `${window.location.href.replace(/\/$/, '')}/api/v1`,
+    baseUrl: baseUrl || window.location.href.replace(/\/$/, ''),
   };
 
   // When fetching the openapi.json, we need to remove circular references from the JSON.

From 8b03af391abca71581bf43496b93e820fb494d4c Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Fri, 1 Mar 2024 09:57:26 +1100
Subject: [PATCH 381/411] fix(ui): fix metadata display issue

---
 .../metadata/hooks/useMetadataItem.tsx        | 22 ++++++++++++-------
 .../web/src/features/metadata/types.ts        |  2 +-
 .../src/features/metadata/util/handlers.ts    |  2 +-
 3 files changed, 16 insertions(+), 10 deletions(-)

diff --git a/invokeai/frontend/web/src/features/metadata/hooks/useMetadataItem.tsx b/invokeai/frontend/web/src/features/metadata/hooks/useMetadataItem.tsx
index 18df0c7323..206d373aa7 100644
--- a/invokeai/frontend/web/src/features/metadata/hooks/useMetadataItem.tsx
+++ b/invokeai/frontend/web/src/features/metadata/hooks/useMetadataItem.tsx
@@ -18,7 +18,7 @@ export const useMetadataItem = <T,>(metadata: unknown, handlers: MetadataHandler
   const [value, setValue] = useState<T | typeof MetadataParsePendingToken | typeof MetadataParseFailedToken>(
     MetadataParsePendingToken
   );
-  const [renderedValue, setRenderedValue] = useState<React.ReactNode>(Pending);
+  const [renderedValueInternal, setRenderedValueInternal] = useState<React.ReactNode>(null);
 
   useEffect(() => {
     const _parse = async () => {
@@ -39,26 +39,32 @@ export const useMetadataItem = <T,>(metadata: unknown, handlers: MetadataHandler
   useEffect(() => {
     const _renderValue = async () => {
       if (value === MetadataParsePendingToken) {
-        setRenderedValue(Pending);
+        setRenderedValueInternal(null);
         return;
       }
       if (value === MetadataParseFailedToken) {
-        setRenderedValue(Failed);
+        setRenderedValueInternal(null);
         return;
       }
 
       const rendered = await handlers.renderValue(value);
 
-      if (typeof rendered === 'string') {
-        setRenderedValue(<Text>{rendered}</Text>);
-        return;
-      }
-      setRenderedValue(rendered);
+      setRenderedValueInternal(rendered);
     };
 
     _renderValue();
   }, [handlers, value]);
 
+  const renderedValue = useMemo(() => {
+    if (value === MetadataParsePendingToken) {
+      return <Pending />;
+    }
+    if (value === MetadataParseFailedToken) {
+      return <Failed />;
+    }
+    return <Text>{renderedValueInternal}</Text>;
+  }, [renderedValueInternal, value]);
+
   const onRecall = useCallback(() => {
     if (!handlers.recall || value === MetadataParsePendingToken || value === MetadataParseFailedToken) {
       return null;
diff --git a/invokeai/frontend/web/src/features/metadata/types.ts b/invokeai/frontend/web/src/features/metadata/types.ts
index 7b102fa160..0791cdf449 100644
--- a/invokeai/frontend/web/src/features/metadata/types.ts
+++ b/invokeai/frontend/web/src/features/metadata/types.ts
@@ -4,7 +4,7 @@ import type { O } from 'ts-toolbelt';
 /**
  * Renders a value of type T as a React node.
  */
-export type MetadataRenderValueFunc<T> = (value: T) => Promise<React.ReactNode>;
+export type MetadataRenderValueFunc<T> = (value: T) => Promise<string>;
 
 /**
  * Gets the label of the current metadata item as a string.
diff --git a/invokeai/frontend/web/src/features/metadata/util/handlers.ts b/invokeai/frontend/web/src/features/metadata/util/handlers.ts
index a877648956..09d65b7d92 100644
--- a/invokeai/frontend/web/src/features/metadata/util/handlers.ts
+++ b/invokeai/frontend/web/src/features/metadata/util/handlers.ts
@@ -150,7 +150,7 @@ const buildRecallItem =
     }
   };
 
-const resolveToString = (value: unknown) => new Promise<React.ReactNode>((resolve) => resolve(String(value)));
+const resolveToString = (value: unknown) => new Promise<string>((resolve) => resolve(String(value)));
 
 const buildHandlers: BuildMetadataHandlers = ({
   getLabel,

From ad86b297981ab64e9ffb86a99cc8a282022c7fe3 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Fri, 1 Mar 2024 10:04:51 +1100
Subject: [PATCH 382/411] chore: remove pin on ruff

This ensures it matches the github workflow.

Also there's an update that stabilizes a number of formatting rules, so there will be a format commit after this.
---
 pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index b25c82b0da..f460806354 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -112,7 +112,7 @@ dependencies = [
 ]
 "dev" = ["jurigged", "pudb", "snakeviz", "gprof2dot"]
 "test" = [
-  "ruff==0.2.1",
+  "ruff",
   "ruff-lsp",
   "mypy",
   "pre-commit",

From dd9daf8efb617244524790795aba085ebda6721b Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Fri, 1 Mar 2024 10:04:59 +1100
Subject: [PATCH 383/411] chore: ruff

---
 .../app/services/config/config_default.py     |  1 +
 invokeai/app/services/download/__init__.py    |  1 +
 .../app/services/model_records/__init__.py    |  1 +
 .../model_records/model_records_sql.py        |  1 -
 .../sqlite_migrator/sqlite_migrator_common.py |  3 +--
 invokeai/backend/image_util/__init__.py       |  1 +
 .../backend/image_util/invisible_watermark.py |  1 +
 invokeai/backend/image_util/patchmatch.py     |  1 +
 invokeai/backend/image_util/pngwriter.py      |  1 +
 invokeai/backend/image_util/safety_checker.py |  1 +
 invokeai/backend/install/check_root.py        |  1 +
 invokeai/backend/install/install_helper.py    |  1 +
 invokeai/backend/model_manager/__init__.py    |  1 +
 invokeai/backend/model_manager/config.py      |  1 +
 .../convert_ckpt_to_diffusers.py              |  2 +-
 .../backend/model_manager/load/__init__.py    |  1 +
 .../load/convert_cache/convert_cache_base.py  |  1 +
 .../load/model_loader_registry.py             |  1 +
 .../model_manager/load/model_loaders/lora.py  |  1 -
 .../load/model_loaders/stable_diffusion.py    |  1 -
 .../load/model_loaders/textual_inversion.py   |  1 -
 .../model_manager/metadata/__init__.py        |  1 +
 invokeai/backend/model_patcher.py             |  1 +
 invokeai/backend/stable_diffusion/__init__.py |  1 +
 .../stable_diffusion/diffusion/__init__.py    |  1 +
 invokeai/backend/training/__init__.py         |  1 +
 .../training/textual_inversion_training.py    |  6 +++---
 invokeai/backend/util/__init__.py             |  1 +
 invokeai/backend/util/attention.py            |  1 +
 invokeai/backend/util/silence_warnings.py     |  1 +
 invokeai/backend/util/util.py                 | 19 +++++++++++--------
 invokeai/frontend/CLI/__init__.py             |  1 +
 .../frontend/install/invokeai_configure.py    |  1 +
 invokeai/frontend/install/invokeai_update.py  |  1 +
 invokeai/frontend/install/widgets.py          |  1 +
 invokeai/frontend/merge/__init__.py           |  1 +
 invokeai/frontend/merge/merge_diffusers.py    |  1 +
 invokeai/frontend/training/__init__.py        |  1 +
 .../frontend/training/textual_inversion.py    |  1 -
 invokeai/version/__init__.py                  |  1 +
 .../services/download/test_download_queue.py  |  1 +
 .../model_metadata/test_model_metadata.py     |  1 +
 tests/backend/util/test_logging.py            |  1 +
 tests/test_path.py                            |  1 +
 44 files changed, 51 insertions(+), 19 deletions(-)

diff --git a/invokeai/app/services/config/config_default.py b/invokeai/app/services/config/config_default.py
index 01fd5e2179..64d464002b 100644
--- a/invokeai/app/services/config/config_default.py
+++ b/invokeai/app/services/config/config_default.py
@@ -166,6 +166,7 @@ two configs are kept in separate sections of the config file:
      ...
 
 """
+
 from __future__ import annotations
 
 import os
diff --git a/invokeai/app/services/download/__init__.py b/invokeai/app/services/download/__init__.py
index 04c1dfdb1d..371c531387 100644
--- a/invokeai/app/services/download/__init__.py
+++ b/invokeai/app/services/download/__init__.py
@@ -1,4 +1,5 @@
 """Init file for download queue."""
+
 from .download_base import DownloadJob, DownloadJobStatus, DownloadQueueServiceBase, UnknownJobIDException
 from .download_default import DownloadQueueService, TqdmProgress
 
diff --git a/invokeai/app/services/model_records/__init__.py b/invokeai/app/services/model_records/__init__.py
index 1622066715..7f888cf1f3 100644
--- a/invokeai/app/services/model_records/__init__.py
+++ b/invokeai/app/services/model_records/__init__.py
@@ -1,4 +1,5 @@
 """Init file for model record services."""
+
 from .model_records_base import (  # noqa F401
     DuplicateModelException,
     InvalidModelException,
diff --git a/invokeai/app/services/model_records/model_records_sql.py b/invokeai/app/services/model_records/model_records_sql.py
index dcd1114655..60f0ad86a8 100644
--- a/invokeai/app/services/model_records/model_records_sql.py
+++ b/invokeai/app/services/model_records/model_records_sql.py
@@ -39,7 +39,6 @@ Typical usage:
   configs = store.search_by_attr(base_model='sd-2', model_type='main')
 """
 
-
 import json
 import sqlite3
 from math import ceil
diff --git a/invokeai/app/services/shared/sqlite_migrator/sqlite_migrator_common.py b/invokeai/app/services/shared/sqlite_migrator/sqlite_migrator_common.py
index 47ed5da505..9b2444dae4 100644
--- a/invokeai/app/services/shared/sqlite_migrator/sqlite_migrator_common.py
+++ b/invokeai/app/services/shared/sqlite_migrator/sqlite_migrator_common.py
@@ -17,8 +17,7 @@ class MigrateCallback(Protocol):
     See :class:`Migration` for an example.
     """
 
-    def __call__(self, cursor: sqlite3.Cursor) -> None:
-        ...
+    def __call__(self, cursor: sqlite3.Cursor) -> None: ...
 
 
 class MigrationError(RuntimeError):
diff --git a/invokeai/backend/image_util/__init__.py b/invokeai/backend/image_util/__init__.py
index 0be5a78a93..ea35a5f153 100644
--- a/invokeai/backend/image_util/__init__.py
+++ b/invokeai/backend/image_util/__init__.py
@@ -1,6 +1,7 @@
 """
 Initialization file for invokeai.backend.image_util methods.
 """
+
 from .patchmatch import PatchMatch  # noqa: F401
 from .pngwriter import PngWriter, PromptFormatter, retrieve_metadata, write_metadata  # noqa: F401
 from .seamless import configure_model_padding  # noqa: F401
diff --git a/invokeai/backend/image_util/invisible_watermark.py b/invokeai/backend/image_util/invisible_watermark.py
index 37b3ca918c..b21cc2e124 100644
--- a/invokeai/backend/image_util/invisible_watermark.py
+++ b/invokeai/backend/image_util/invisible_watermark.py
@@ -3,6 +3,7 @@ This module defines a singleton object, "invisible_watermark" that
 wraps the invisible watermark model. It respects the global "invisible_watermark"
 configuration variable, that allows the watermarking to be supressed.
 """
+
 import cv2
 import numpy as np
 from imwatermark import WatermarkEncoder
diff --git a/invokeai/backend/image_util/patchmatch.py b/invokeai/backend/image_util/patchmatch.py
index 5514e3d33a..08f3f4ffff 100644
--- a/invokeai/backend/image_util/patchmatch.py
+++ b/invokeai/backend/image_util/patchmatch.py
@@ -4,6 +4,7 @@ wraps the actual patchmatch object. It respects the global
 "try_patchmatch" attribute, so that patchmatch loading can
 be suppressed or deferred
 """
+
 import numpy as np
 
 import invokeai.backend.util.logging as logger
diff --git a/invokeai/backend/image_util/pngwriter.py b/invokeai/backend/image_util/pngwriter.py
index c9c58264c2..f537b4681c 100644
--- a/invokeai/backend/image_util/pngwriter.py
+++ b/invokeai/backend/image_util/pngwriter.py
@@ -6,6 +6,7 @@ PngWriter -- Converts Images generated by T2I into PNGs, finds
 
 Exports function retrieve_metadata(path)
 """
+
 import json
 import os
 import re
diff --git a/invokeai/backend/image_util/safety_checker.py b/invokeai/backend/image_util/safety_checker.py
index 92ddef5ecc..b92a73c24f 100644
--- a/invokeai/backend/image_util/safety_checker.py
+++ b/invokeai/backend/image_util/safety_checker.py
@@ -3,6 +3,7 @@ This module defines a singleton object, "safety_checker" that
 wraps the safety_checker model. It respects the global "nsfw_checker"
 configuration variable, that allows the checker to be supressed.
 """
+
 import numpy as np
 from PIL import Image
 
diff --git a/invokeai/backend/install/check_root.py b/invokeai/backend/install/check_root.py
index cbf9976123..2b2116993b 100644
--- a/invokeai/backend/install/check_root.py
+++ b/invokeai/backend/install/check_root.py
@@ -1,6 +1,7 @@
 """
 Check that the invokeai_root is correctly configured and exit if not.
 """
+
 import sys
 
 from invokeai.app.services.config import InvokeAIAppConfig
diff --git a/invokeai/backend/install/install_helper.py b/invokeai/backend/install/install_helper.py
index 999dcdd100..975088409c 100644
--- a/invokeai/backend/install/install_helper.py
+++ b/invokeai/backend/install/install_helper.py
@@ -1,4 +1,5 @@
 """Utility (backend) functions used by model_install.py"""
+
 from logging import Logger
 from pathlib import Path
 from typing import Any, Dict, List, Optional
diff --git a/invokeai/backend/model_manager/__init__.py b/invokeai/backend/model_manager/__init__.py
index 88356d0468..966e6ae21d 100644
--- a/invokeai/backend/model_manager/__init__.py
+++ b/invokeai/backend/model_manager/__init__.py
@@ -1,4 +1,5 @@
 """Re-export frequently-used symbols from the Model Manager backend."""
+
 from .config import (
     AnyModel,
     AnyModelConfig,
diff --git a/invokeai/backend/model_manager/config.py b/invokeai/backend/model_manager/config.py
index 78635636b9..e22f74c767 100644
--- a/invokeai/backend/model_manager/config.py
+++ b/invokeai/backend/model_manager/config.py
@@ -19,6 +19,7 @@ Typical usage:
 Validation errors will raise an InvalidModelConfigException error.
 
 """
+
 import time
 from enum import Enum
 from typing import Literal, Optional, Type, Union
diff --git a/invokeai/backend/model_manager/convert_ckpt_to_diffusers.py b/invokeai/backend/model_manager/convert_ckpt_to_diffusers.py
index 6f5acd5832..6b3e953b38 100644
--- a/invokeai/backend/model_manager/convert_ckpt_to_diffusers.py
+++ b/invokeai/backend/model_manager/convert_ckpt_to_diffusers.py
@@ -15,7 +15,7 @@
 #
 # Adapted for use in InvokeAI by Lincoln Stein, July 2023
 #
-""" Conversion script for the Stable Diffusion checkpoints."""
+"""Conversion script for the Stable Diffusion checkpoints."""
 
 import re
 from contextlib import nullcontext
diff --git a/invokeai/backend/model_manager/load/__init__.py b/invokeai/backend/model_manager/load/__init__.py
index a0421017db..f47a2c4368 100644
--- a/invokeai/backend/model_manager/load/__init__.py
+++ b/invokeai/backend/model_manager/load/__init__.py
@@ -2,6 +2,7 @@
 """
 Init file for the model loader.
 """
+
 from importlib import import_module
 from pathlib import Path
 
diff --git a/invokeai/backend/model_manager/load/convert_cache/convert_cache_base.py b/invokeai/backend/model_manager/load/convert_cache/convert_cache_base.py
index 6268c099a5..ef363cc7f4 100644
--- a/invokeai/backend/model_manager/load/convert_cache/convert_cache_base.py
+++ b/invokeai/backend/model_manager/load/convert_cache/convert_cache_base.py
@@ -1,6 +1,7 @@
 """
 Disk-based converted model cache.
 """
+
 from abc import ABC, abstractmethod
 from pathlib import Path
 
diff --git a/invokeai/backend/model_manager/load/model_loader_registry.py b/invokeai/backend/model_manager/load/model_loader_registry.py
index ce1110e749..e7747650d4 100644
--- a/invokeai/backend/model_manager/load/model_loader_registry.py
+++ b/invokeai/backend/model_manager/load/model_loader_registry.py
@@ -14,6 +14,7 @@ Use like this:
     ).load_model(model_config, submodel_type)
 
 """
+
 import hashlib
 from abc import ABC, abstractmethod
 from pathlib import Path
diff --git a/invokeai/backend/model_manager/load/model_loaders/lora.py b/invokeai/backend/model_manager/load/model_loaders/lora.py
index fe804ef565..e308531a4f 100644
--- a/invokeai/backend/model_manager/load/model_loaders/lora.py
+++ b/invokeai/backend/model_manager/load/model_loaders/lora.py
@@ -1,7 +1,6 @@
 # Copyright (c) 2024, Lincoln D. Stein and the InvokeAI Development Team
 """Class for LoRA model loading in InvokeAI."""
 
-
 from logging import Logger
 from pathlib import Path
 from typing import Optional, Tuple
diff --git a/invokeai/backend/model_manager/load/model_loaders/stable_diffusion.py b/invokeai/backend/model_manager/load/model_loaders/stable_diffusion.py
index 5884f84e8d..0f0483d8dc 100644
--- a/invokeai/backend/model_manager/load/model_loaders/stable_diffusion.py
+++ b/invokeai/backend/model_manager/load/model_loaders/stable_diffusion.py
@@ -1,7 +1,6 @@
 # Copyright (c) 2024, Lincoln D. Stein and the InvokeAI Development Team
 """Class for StableDiffusion model loading in InvokeAI."""
 
-
 from pathlib import Path
 from typing import Optional
 
diff --git a/invokeai/backend/model_manager/load/model_loaders/textual_inversion.py b/invokeai/backend/model_manager/load/model_loaders/textual_inversion.py
index 094d4d7c5c..fb9204a701 100644
--- a/invokeai/backend/model_manager/load/model_loaders/textual_inversion.py
+++ b/invokeai/backend/model_manager/load/model_loaders/textual_inversion.py
@@ -1,7 +1,6 @@
 # Copyright (c) 2024, Lincoln D. Stein and the InvokeAI Development Team
 """Class for TI model loading in InvokeAI."""
 
-
 from pathlib import Path
 from typing import Optional, Tuple
 
diff --git a/invokeai/backend/model_manager/metadata/__init__.py b/invokeai/backend/model_manager/metadata/__init__.py
index a35e55f3d2..56e741cd00 100644
--- a/invokeai/backend/model_manager/metadata/__init__.py
+++ b/invokeai/backend/model_manager/metadata/__init__.py
@@ -18,6 +18,7 @@ assert isinstance(data, CivitaiMetadata)
 if data.allow_commercial_use:
    print("Commercial use of this model is allowed")
 """
+
 from .fetch import CivitaiMetadataFetch, HuggingFaceMetadataFetch, ModelMetadataFetchBase
 from .metadata_base import (
     AnyModelRepoMetadata,
diff --git a/invokeai/backend/model_patcher.py b/invokeai/backend/model_patcher.py
index 473a088308..76271fc025 100644
--- a/invokeai/backend/model_patcher.py
+++ b/invokeai/backend/model_patcher.py
@@ -1,5 +1,6 @@
 # Copyright (c) 2024 Ryan Dick, Lincoln D. Stein, and the InvokeAI Development Team
 """These classes implement model patching with LoRAs and Textual Inversions."""
+
 from __future__ import annotations
 
 import pickle
diff --git a/invokeai/backend/stable_diffusion/__init__.py b/invokeai/backend/stable_diffusion/__init__.py
index 75e6aa0a5d..8b3f701064 100644
--- a/invokeai/backend/stable_diffusion/__init__.py
+++ b/invokeai/backend/stable_diffusion/__init__.py
@@ -1,6 +1,7 @@
 """
 Initialization file for the invokeai.backend.stable_diffusion package
 """
+
 from .diffusers_pipeline import PipelineIntermediateState, StableDiffusionGeneratorPipeline  # noqa: F401
 from .diffusion import InvokeAIDiffuserComponent  # noqa: F401
 from .diffusion.cross_attention_map_saving import AttentionMapSaver  # noqa: F401
diff --git a/invokeai/backend/stable_diffusion/diffusion/__init__.py b/invokeai/backend/stable_diffusion/diffusion/__init__.py
index 00e6f1b916..e68340168a 100644
--- a/invokeai/backend/stable_diffusion/diffusion/__init__.py
+++ b/invokeai/backend/stable_diffusion/diffusion/__init__.py
@@ -1,6 +1,7 @@
 """
 Initialization file for invokeai.models.diffusion
 """
+
 from .cross_attention_control import InvokeAICrossAttentionMixin  # noqa: F401
 from .cross_attention_map_saving import AttentionMapSaver  # noqa: F401
 from .shared_invokeai_diffusion import InvokeAIDiffuserComponent  # noqa: F401
diff --git a/invokeai/backend/training/__init__.py b/invokeai/backend/training/__init__.py
index ed3ceb90ec..6b5aa7327d 100644
--- a/invokeai/backend/training/__init__.py
+++ b/invokeai/backend/training/__init__.py
@@ -1,4 +1,5 @@
 """
 Initialization file for invokeai.backend.training
 """
+
 from .textual_inversion_training import do_textual_inversion_training, parse_args  # noqa: F401
diff --git a/invokeai/backend/training/textual_inversion_training.py b/invokeai/backend/training/textual_inversion_training.py
index 9a38c006a5..7ddcf14367 100644
--- a/invokeai/backend/training/textual_inversion_training.py
+++ b/invokeai/backend/training/textual_inversion_training.py
@@ -858,9 +858,9 @@ def do_textual_inversion_training(
                 # Let's make sure we don't update any embedding weights besides the newly added token
                 index_no_updates = torch.arange(len(tokenizer)) != placeholder_token_id
                 with torch.no_grad():
-                    accelerator.unwrap_model(text_encoder).get_input_embeddings().weight[
-                        index_no_updates
-                    ] = orig_embeds_params[index_no_updates]
+                    accelerator.unwrap_model(text_encoder).get_input_embeddings().weight[index_no_updates] = (
+                        orig_embeds_params[index_no_updates]
+                    )
 
             # Checks if the accelerator has performed an optimization step behind the scenes
             if accelerator.sync_gradients:
diff --git a/invokeai/backend/util/__init__.py b/invokeai/backend/util/__init__.py
index 7b48f0364e..ee6793376f 100644
--- a/invokeai/backend/util/__init__.py
+++ b/invokeai/backend/util/__init__.py
@@ -1,6 +1,7 @@
 """
 Initialization file for invokeai.backend.util
 """
+
 from .attention import auto_detect_slice_size  # noqa: F401
 from .devices import (  # noqa: F401
     CPU_DEVICE,
diff --git a/invokeai/backend/util/attention.py b/invokeai/backend/util/attention.py
index 910933044e..88dc6e5cec 100644
--- a/invokeai/backend/util/attention.py
+++ b/invokeai/backend/util/attention.py
@@ -3,6 +3,7 @@
 Utility routine used for autodetection of optimal slice size
 for attention mechanism.
 """
+
 import psutil
 import torch
 
diff --git a/invokeai/backend/util/silence_warnings.py b/invokeai/backend/util/silence_warnings.py
index 068b605da9..4c566ba759 100644
--- a/invokeai/backend/util/silence_warnings.py
+++ b/invokeai/backend/util/silence_warnings.py
@@ -1,4 +1,5 @@
 """Context class to silence transformers and diffusers warnings."""
+
 import warnings
 from typing import Any
 
diff --git a/invokeai/backend/util/util.py b/invokeai/backend/util/util.py
index ae376b41b2..ac7a64e807 100644
--- a/invokeai/backend/util/util.py
+++ b/invokeai/backend/util/util.py
@@ -340,14 +340,17 @@ def download_with_resume(url: str, dest: Path, access_token: str = None) -> Path
             logger.error(f"ERROR DOWNLOADING {url}: {resp.text}")
             return None
 
-        with open(dest, open_mode) as file, tqdm(
-            desc=str(dest),
-            initial=exist_size,
-            total=content_length,
-            unit="iB",
-            unit_scale=True,
-            unit_divisor=1000,
-        ) as bar:
+        with (
+            open(dest, open_mode) as file,
+            tqdm(
+                desc=str(dest),
+                initial=exist_size,
+                total=content_length,
+                unit="iB",
+                unit_scale=True,
+                unit_divisor=1000,
+            ) as bar,
+        ):
             for data in resp.iter_content(chunk_size=1024):
                 size = file.write(data)
                 bar.update(size)
diff --git a/invokeai/frontend/CLI/__init__.py b/invokeai/frontend/CLI/__init__.py
index f8864bbe66..63d8d66246 100644
--- a/invokeai/frontend/CLI/__init__.py
+++ b/invokeai/frontend/CLI/__init__.py
@@ -1,4 +1,5 @@
 """
 Initialization file for invokeai.frontend.CLI
 """
+
 from .CLI import main as invokeai_command_line_interface  # noqa: F401
diff --git a/invokeai/frontend/install/invokeai_configure.py b/invokeai/frontend/install/invokeai_configure.py
index 2a62430b69..73132ee064 100644
--- a/invokeai/frontend/install/invokeai_configure.py
+++ b/invokeai/frontend/install/invokeai_configure.py
@@ -1,6 +1,7 @@
 """
 Wrapper for invokeai.backend.configure.invokeai_configure
 """
+
 from ...backend.install.invokeai_configure import main as invokeai_configure  # noqa: F401
 
 __all__ = ["invokeai_configure"]
diff --git a/invokeai/frontend/install/invokeai_update.py b/invokeai/frontend/install/invokeai_update.py
index 06c3520a89..32a6208e6b 100644
--- a/invokeai/frontend/install/invokeai_update.py
+++ b/invokeai/frontend/install/invokeai_update.py
@@ -2,6 +2,7 @@
 Minimalist updater script. Prompts user for the tag or branch to update to and runs
 pip install <path_to_git_source>.
 """
+
 import os
 import platform
 from distutils.version import LooseVersion
diff --git a/invokeai/frontend/install/widgets.py b/invokeai/frontend/install/widgets.py
index 4dbc6349a0..49ca1e3583 100644
--- a/invokeai/frontend/install/widgets.py
+++ b/invokeai/frontend/install/widgets.py
@@ -1,6 +1,7 @@
 """
 Widget class definitions used by model_select.py, merge_diffusers.py and textual_inversion.py
 """
+
 import curses
 import math
 import os
diff --git a/invokeai/frontend/merge/__init__.py b/invokeai/frontend/merge/__init__.py
index a18da9c0d4..4e56b146f4 100644
--- a/invokeai/frontend/merge/__init__.py
+++ b/invokeai/frontend/merge/__init__.py
@@ -1,4 +1,5 @@
 """
 Initialization file for invokeai.frontend.merge
 """
+
 from .merge_diffusers import main as invokeai_merge_diffusers  # noqa: F401
diff --git a/invokeai/frontend/merge/merge_diffusers.py b/invokeai/frontend/merge/merge_diffusers.py
index ff9acd569e..78b5df859b 100644
--- a/invokeai/frontend/merge/merge_diffusers.py
+++ b/invokeai/frontend/merge/merge_diffusers.py
@@ -4,6 +4,7 @@ used to merge 2-3 models together and create a new InvokeAI-registered diffusion
 
 Copyright (c) 2023 Lincoln Stein and the InvokeAI Development Team
 """
+
 import argparse
 import curses
 import re
diff --git a/invokeai/frontend/training/__init__.py b/invokeai/frontend/training/__init__.py
index d4eff2f7fd..7e002b4c03 100644
--- a/invokeai/frontend/training/__init__.py
+++ b/invokeai/frontend/training/__init__.py
@@ -1,4 +1,5 @@
 """
 Initialization file for invokeai.frontend.training
 """
+
 from .textual_inversion import main as invokeai_textual_inversion  # noqa: F401
diff --git a/invokeai/frontend/training/textual_inversion.py b/invokeai/frontend/training/textual_inversion.py
index 6250b313b0..a7dc36515f 100644
--- a/invokeai/frontend/training/textual_inversion.py
+++ b/invokeai/frontend/training/textual_inversion.py
@@ -6,7 +6,6 @@ This is the frontend to "textual_inversion_training.py".
 Copyright (c) 2023-24 Lincoln Stein and the InvokeAI Development Team
 """
 
-
 import os
 import re
 import shutil
diff --git a/invokeai/version/__init__.py b/invokeai/version/__init__.py
index 90cca7c27f..dbc30bc636 100644
--- a/invokeai/version/__init__.py
+++ b/invokeai/version/__init__.py
@@ -1,6 +1,7 @@
 """
 initialization file for invokeai
 """
+
 from .invokeai_version import __version__  # noqa: F401
 
 __app_id__ = "invoke-ai/InvokeAI"
diff --git a/tests/app/services/download/test_download_queue.py b/tests/app/services/download/test_download_queue.py
index ff9b193b17..9c1826170e 100644
--- a/tests/app/services/download/test_download_queue.py
+++ b/tests/app/services/download/test_download_queue.py
@@ -1,4 +1,5 @@
 """Test the queued download facility"""
+
 import re
 import time
 from pathlib import Path
diff --git a/tests/backend/model_manager/model_metadata/test_model_metadata.py b/tests/backend/model_manager/model_metadata/test_model_metadata.py
index f7f2603e7c..0c6b1a6e93 100644
--- a/tests/backend/model_manager/model_metadata/test_model_metadata.py
+++ b/tests/backend/model_manager/model_metadata/test_model_metadata.py
@@ -1,6 +1,7 @@
 """
 Test model metadata fetching and storage.
 """
+
 import datetime
 from pathlib import Path
 
diff --git a/tests/backend/util/test_logging.py b/tests/backend/util/test_logging.py
index 0d229df7c1..944ffad47a 100644
--- a/tests/backend/util/test_logging.py
+++ b/tests/backend/util/test_logging.py
@@ -1,6 +1,7 @@
 """
 Test interaction of logging with configuration system.
 """
+
 import io
 import logging
 import re
diff --git a/tests/test_path.py b/tests/test_path.py
index 2f2e3779c7..c03536c13a 100644
--- a/tests/test_path.py
+++ b/tests/test_path.py
@@ -2,6 +2,7 @@
 Not really a test, but a way to verify that the paths are existing
 and fail early if they are not.
 """
+
 import pathlib
 import unittest
 from os import path as osp

From e18533e3b51c39366b5a2f27843b9231d391cdab Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lstein@gmail.com>
Date: Thu, 29 Feb 2024 06:34:59 -0500
Subject: [PATCH 384/411] add debugging statements and a timeout to download
 test

---
 .../app/services/download/download_default.py | 22 ++++++++++++++---
 .../model_install/model_install_default.py    |  2 +-
 pyproject.toml                                |  2 ++
 tests/app/routers/test_images.py              | 24 +++++++++++++------
 .../services/download/test_download_queue.py  |  5 +++-
 .../model_install/test_model_install.py       |  4 ++--
 tests/conftest.py                             | 10 ++++++++
 7 files changed, 55 insertions(+), 14 deletions(-)

diff --git a/invokeai/app/services/download/download_default.py b/invokeai/app/services/download/download_default.py
index 50cac80d09..c336ff4c8c 100644
--- a/invokeai/app/services/download/download_default.py
+++ b/invokeai/app/services/download/download_default.py
@@ -221,22 +221,29 @@ class DownloadQueueService(DownloadQueueServiceBase):
             except Empty:
                 continue
             try:
+                print(f'DEBUG: job [{job.id}] started', flush=True)
                 job.job_started = get_iso_timestamp()
                 self._do_download(job)
+                print(f'DEBUG: job [{job.id}] download completed', flush=True)
                 self._signal_job_complete(job)
-
+                print(f'DEBUG: job [{job.id}] signaled completion', flush=True)
             except (OSError, HTTPError) as excp:
                 job.error_type = excp.__class__.__name__ + f"({str(excp)})"
                 job.error = traceback.format_exc()
                 self._signal_job_error(job, excp)
+                print(f'DEBUG: job [{job.id}] signaled error', flush=True)
             except DownloadJobCancelledException:
                 self._signal_job_cancelled(job)
                 self._cleanup_cancelled_job(job)
-
+                print(f'DEBUG: job [{job.id}] signaled cancelled', flush=True)
+                
             finally:
+                print(f'DEBUG: job [{job.id}] signalling completion', flush=True)
                 job.job_ended = get_iso_timestamp()
                 self._job_completed_event.set()  # signal a change to terminal state
+                print(f'DEBUG: job [{job.id}] set job completion event', flush=True)
                 self._queue.task_done()
+                print(f'DEBUG: job [{job.id}] done', flush=True)
         self._logger.debug(f"Download queue worker thread {threading.current_thread().name} exiting.")
 
     def _do_download(self, job: DownloadJob) -> None:
@@ -244,7 +251,8 @@ class DownloadQueueService(DownloadQueueServiceBase):
         url = job.source
         header = {"Authorization": f"Bearer {job.access_token}"} if job.access_token else {}
         open_mode = "wb"
-
+        print(f'DEBUG: In _do_download [0]', flush=True)
+        
         # Make a streaming request. This will retrieve headers including
         # content-length and content-disposition, but not fetch any content itself
         resp = self._requests.get(str(url), headers=header, stream=True)
@@ -255,6 +263,8 @@ class DownloadQueueService(DownloadQueueServiceBase):
         content_length = int(resp.headers.get("content-length", 0))
         job.total_bytes = content_length
 
+        print(f'DEBUG: In _do_download [1]')
+
         if job.dest.is_dir():
             file_name = os.path.basename(str(url.path))  # default is to use the last bit of the URL
 
@@ -282,6 +292,7 @@ class DownloadQueueService(DownloadQueueServiceBase):
         # signal caller that the download is starting. At this point, key fields such as
         # download_path and total_bytes will be populated. We call it here because the might
         # discover that the local file is already complete and generate a COMPLETED status.
+        print(f'DEBUG: In _do_download [2]', flush=True)
         self._signal_job_started(job)
 
         # "range not satisfiable" - local file is at least as large as the remote file
@@ -297,12 +308,15 @@ class DownloadQueueService(DownloadQueueServiceBase):
         elif resp.status_code != 200:
             raise HTTPError(resp.reason)
 
+        print(f'DEBUG: In _do_download [3]', flush=True)
+
         self._logger.debug(f"{job.source}: Downloading {job.download_path}")
         report_delta = job.total_bytes / 100  # report every 1% change
         last_report_bytes = 0
 
         # DOWNLOAD LOOP
         with open(in_progress_path, open_mode) as file:
+            print(f'DEBUG: In _do_download loop [4]', flush=True)
             for data in resp.iter_content(chunk_size=DOWNLOAD_CHUNK_SIZE):
                 if job.cancelled:
                     raise DownloadJobCancelledException("Job was cancelled at caller's request")
@@ -315,6 +329,8 @@ class DownloadQueueService(DownloadQueueServiceBase):
         # if we get here we are done and can rename the file to the original dest
         self._logger.debug(f"{job.source}: saved to {job.download_path} (bytes={job.bytes})")
         in_progress_path.rename(job.download_path)
+        print(f'DEBUG: In _do_download [5]', flush=True)
+
 
     def _validate_filename(self, directory: str, filename: str) -> bool:
         pc_name_max = os.pathconf(directory, "PC_NAME_MAX") if hasattr(os, "pathconf") else 260  # hardcoded for windows
diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py
index a48cf92b99..fe8124923f 100644
--- a/invokeai/app/services/model_install/model_install_default.py
+++ b/invokeai/app/services/model_install/model_install_default.py
@@ -284,7 +284,7 @@ class ModelInstallService(ModelInstallServiceBase):
     def scan_directory(self, scan_dir: Path, install: bool = False) -> List[str]:  # noqa D102
         self._cached_model_paths = {Path(x.path) for x in self.record_store.all_models()}
         callback = self._scan_install if install else self._scan_register
-        search = ModelSearch(on_model_found=callback)
+        search = ModelSearch(on_model_found=callback, config=self._app_config)
         self._models_installed.clear()
         search.search(scan_dir)
         return list(self._models_installed)
diff --git a/pyproject.toml b/pyproject.toml
index f460806354..661adfe4c4 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -118,6 +118,7 @@ dependencies = [
   "pre-commit",
   "pytest>6.0.0",
   "pytest-cov",
+  "pytest-timeout",
   "pytest-datadir",
   "requests_testadapter",
   "httpx",
@@ -189,6 +190,7 @@ version = { attr = "invokeai.version.__version__" }
 addopts = "--cov-report term --cov-report html --cov-report xml --strict-markers -m \"not slow\""
 markers = [
   "slow: Marks tests as slow. Disabled by default. To run all tests, use -m \"\". To run only slow tests, use -m \"slow\".",
+  "timeout: 60"
 ]
 [tool.coverage.run]
 branch = true
diff --git a/tests/app/routers/test_images.py b/tests/app/routers/test_images.py
index 5cb8cf1c37..c0da3ec51c 100644
--- a/tests/app/routers/test_images.py
+++ b/tests/app/routers/test_images.py
@@ -1,6 +1,8 @@
+import os
 from pathlib import Path
 from typing import Any
 
+import pytest
 from fastapi import BackgroundTasks
 from fastapi.testclient import TestClient
 
@@ -9,7 +11,11 @@ from invokeai.app.api_app import app
 from invokeai.app.services.board_records.board_records_common import BoardRecord
 from invokeai.app.services.invoker import Invoker
 
-client = TestClient(app)
+
+@pytest.fixture(autouse=True, scope="module")
+def client(invokeai_root_dir: Path) -> TestClient:
+    os.environ["INVOKEAI_ROOT"] = invokeai_root_dir.as_posix()
+    return TestClient(app)
 
 
 class MockApiDependencies(ApiDependencies):
@@ -19,7 +25,7 @@ class MockApiDependencies(ApiDependencies):
         self.invoker = invoker
 
 
-def test_download_images_from_list(monkeypatch: Any, mock_invoker: Invoker) -> None:
+def test_download_images_from_list(monkeypatch: Any, mock_invoker: Invoker, client: TestClient) -> None:
     prepare_download_images_test(monkeypatch, mock_invoker)
 
     response = client.post("/api/v1/images/download", json={"image_names": ["test.png"]})
@@ -28,7 +34,9 @@ def test_download_images_from_list(monkeypatch: Any, mock_invoker: Invoker) -> N
     assert json_response["bulk_download_item_name"] == "test.zip"
 
 
-def test_download_images_from_board_id_empty_image_name_list(monkeypatch: Any, mock_invoker: Invoker) -> None:
+def test_download_images_from_board_id_empty_image_name_list(
+    monkeypatch: Any, mock_invoker: Invoker, client: TestClient
+) -> None:
     expected_board_name = "test"
 
     def mock_get(*args, **kwargs):
@@ -56,7 +64,9 @@ def prepare_download_images_test(monkeypatch: Any, mock_invoker: Invoker) -> Non
     monkeypatch.setattr(BackgroundTasks, "add_task", mock_add_task)
 
 
-def test_download_images_with_empty_image_list_and_no_board_id(monkeypatch: Any, mock_invoker: Invoker) -> None:
+def test_download_images_with_empty_image_list_and_no_board_id(
+    monkeypatch: Any, mock_invoker: Invoker, client: TestClient
+) -> None:
     prepare_download_images_test(monkeypatch, mock_invoker)
 
     response = client.post("/api/v1/images/download", json={"image_names": []})
@@ -64,7 +74,7 @@ def test_download_images_with_empty_image_list_and_no_board_id(monkeypatch: Any,
     assert response.status_code == 400
 
 
-def test_get_bulk_download_image(tmp_path: Path, monkeypatch: Any, mock_invoker: Invoker) -> None:
+def test_get_bulk_download_image(tmp_path: Path, monkeypatch: Any, mock_invoker: Invoker, client: TestClient) -> None:
     mock_file: Path = tmp_path / "test.zip"
     mock_file.write_text("contents")
 
@@ -82,7 +92,7 @@ def test_get_bulk_download_image(tmp_path: Path, monkeypatch: Any, mock_invoker:
     assert response.content == b"contents"
 
 
-def test_get_bulk_download_image_not_found(monkeypatch: Any, mock_invoker: Invoker) -> None:
+def test_get_bulk_download_image_not_found(monkeypatch: Any, mock_invoker: Invoker, client: TestClient) -> None:
     monkeypatch.setattr("invokeai.app.api.routers.images.ApiDependencies", MockApiDependencies(mock_invoker))
 
     def mock_add_task(*args, **kwargs):
@@ -96,7 +106,7 @@ def test_get_bulk_download_image_not_found(monkeypatch: Any, mock_invoker: Invok
 
 
 def test_get_bulk_download_image_image_deleted_after_response(
-    monkeypatch: Any, mock_invoker: Invoker, tmp_path: Path
+    monkeypatch: Any, mock_invoker: Invoker, tmp_path: Path, client: TestClient
 ) -> None:
     mock_file: Path = tmp_path / "test.zip"
     mock_file.write_text("contents")
diff --git a/tests/app/services/download/test_download_queue.py b/tests/app/services/download/test_download_queue.py
index 9c1826170e..77d77836ec 100644
--- a/tests/app/services/download/test_download_queue.py
+++ b/tests/app/services/download/test_download_queue.py
@@ -166,7 +166,7 @@ def test_broken_callbacks(tmp_path: Path, session: Session, capsys) -> None:
     # assert re.search("division by zero", captured.err)
     queue.stop()
 
-
+@pytest.mark.timeout(timeout=15, method="thread")
 def test_cancel(tmp_path: Path, session: Session) -> None:
     event_bus = TestEventService()
 
@@ -182,6 +182,9 @@ def test_cancel(tmp_path: Path, session: Session) -> None:
         nonlocal cancelled
         cancelled = True
 
+    def handler(signum, frame):
+        raise TimeoutError("Join took too long to return")
+
     job = queue.download(
         source=AnyHttpUrl("http://www.civitai.com/models/12345"),
         dest=tmp_path,
diff --git a/tests/app/services/model_install/test_model_install.py b/tests/app/services/model_install/test_model_install.py
index 80b106c5cb..c0a6e7b2b6 100644
--- a/tests/app/services/model_install/test_model_install.py
+++ b/tests/app/services/model_install/test_model_install.py
@@ -195,7 +195,7 @@ def test_delete_register(
     with pytest.raises(UnknownModelException):
         store.get_model(key)
 
-
+@pytest.mark.timeout(timeout=20, method="thread")
 def test_simple_download(mm2_installer: ModelInstallServiceBase, mm2_app_config: InvokeAIAppConfig) -> None:
     source = URLModelSource(url=Url("https://www.test.foo/download/test_embedding.safetensors"))
 
@@ -220,7 +220,7 @@ def test_simple_download(mm2_installer: ModelInstallServiceBase, mm2_app_config:
     event_names = [x.event_name for x in bus.events]
     assert event_names == ["model_install_downloading", "model_install_running", "model_install_completed"]
 
-
+@pytest.mark.timeout(timeout=20, method="thread")
 def test_huggingface_download(mm2_installer: ModelInstallServiceBase, mm2_app_config: InvokeAIAppConfig) -> None:
     source = URLModelSource(url=Url("https://huggingface.co/stabilityai/sdxl-turbo"))
 
diff --git a/tests/conftest.py b/tests/conftest.py
index a483b7529a..06d29b05be 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -5,6 +5,8 @@
 # We import the model_installer and torch_device fixtures here so that they can be used by all tests. Flake8 does not
 # play well with fixtures (F401 and F811), so this is cleaner than importing in all files that use these fixtures.
 import logging
+import shutil
+from pathlib import Path
 
 import pytest
 
@@ -58,3 +60,11 @@ def mock_services() -> InvocationServices:
 @pytest.fixture()
 def mock_invoker(mock_services: InvocationServices) -> Invoker:
     return Invoker(services=mock_services)
+
+
+@pytest.fixture(scope="module")
+def invokeai_root_dir(tmp_path_factory) -> Path:
+    root_template = Path(__file__).parent.resolve() / "backend/model_manager/data/invokeai_root"
+    temp_dir: Path = tmp_path_factory.mktemp("data") / "invokeai_root"
+    shutil.copytree(root_template, temp_dir)
+    return temp_dir

From 813a086cfe9fd73f69e4b62eb471d6bec29a5dfb Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lstein@gmail.com>
Date: Thu, 29 Feb 2024 15:08:10 -0500
Subject: [PATCH 385/411] fix race condition between downloading last file and
 starting install

---
 .../app/services/download/download_default.py | 21 ++-----------------
 .../model_install/model_install_base.py       |  6 ++++++
 .../model_install/model_install_default.py    | 19 ++++-------------
 pyproject.toml                                |  4 ++--
 .../services/download/test_download_queue.py  |  1 +
 .../model_install/test_model_install.py       |  1 +
 .../model_manager/model_manager_fixtures.py   |  2 ++
 7 files changed, 18 insertions(+), 36 deletions(-)

diff --git a/invokeai/app/services/download/download_default.py b/invokeai/app/services/download/download_default.py
index c336ff4c8c..843351a259 100644
--- a/invokeai/app/services/download/download_default.py
+++ b/invokeai/app/services/download/download_default.py
@@ -221,29 +221,21 @@ class DownloadQueueService(DownloadQueueServiceBase):
             except Empty:
                 continue
             try:
-                print(f'DEBUG: job [{job.id}] started', flush=True)
                 job.job_started = get_iso_timestamp()
                 self._do_download(job)
-                print(f'DEBUG: job [{job.id}] download completed', flush=True)
                 self._signal_job_complete(job)
-                print(f'DEBUG: job [{job.id}] signaled completion', flush=True)
             except (OSError, HTTPError) as excp:
                 job.error_type = excp.__class__.__name__ + f"({str(excp)})"
                 job.error = traceback.format_exc()
                 self._signal_job_error(job, excp)
-                print(f'DEBUG: job [{job.id}] signaled error', flush=True)
             except DownloadJobCancelledException:
                 self._signal_job_cancelled(job)
                 self._cleanup_cancelled_job(job)
-                print(f'DEBUG: job [{job.id}] signaled cancelled', flush=True)
-                
+
             finally:
-                print(f'DEBUG: job [{job.id}] signalling completion', flush=True)
                 job.job_ended = get_iso_timestamp()
                 self._job_completed_event.set()  # signal a change to terminal state
-                print(f'DEBUG: job [{job.id}] set job completion event', flush=True)
                 self._queue.task_done()
-                print(f'DEBUG: job [{job.id}] done', flush=True)
         self._logger.debug(f"Download queue worker thread {threading.current_thread().name} exiting.")
 
     def _do_download(self, job: DownloadJob) -> None:
@@ -251,8 +243,7 @@ class DownloadQueueService(DownloadQueueServiceBase):
         url = job.source
         header = {"Authorization": f"Bearer {job.access_token}"} if job.access_token else {}
         open_mode = "wb"
-        print(f'DEBUG: In _do_download [0]', flush=True)
-        
+
         # Make a streaming request. This will retrieve headers including
         # content-length and content-disposition, but not fetch any content itself
         resp = self._requests.get(str(url), headers=header, stream=True)
@@ -263,8 +254,6 @@ class DownloadQueueService(DownloadQueueServiceBase):
         content_length = int(resp.headers.get("content-length", 0))
         job.total_bytes = content_length
 
-        print(f'DEBUG: In _do_download [1]')
-
         if job.dest.is_dir():
             file_name = os.path.basename(str(url.path))  # default is to use the last bit of the URL
 
@@ -292,7 +281,6 @@ class DownloadQueueService(DownloadQueueServiceBase):
         # signal caller that the download is starting. At this point, key fields such as
         # download_path and total_bytes will be populated. We call it here because the might
         # discover that the local file is already complete and generate a COMPLETED status.
-        print(f'DEBUG: In _do_download [2]', flush=True)
         self._signal_job_started(job)
 
         # "range not satisfiable" - local file is at least as large as the remote file
@@ -308,15 +296,12 @@ class DownloadQueueService(DownloadQueueServiceBase):
         elif resp.status_code != 200:
             raise HTTPError(resp.reason)
 
-        print(f'DEBUG: In _do_download [3]', flush=True)
-
         self._logger.debug(f"{job.source}: Downloading {job.download_path}")
         report_delta = job.total_bytes / 100  # report every 1% change
         last_report_bytes = 0
 
         # DOWNLOAD LOOP
         with open(in_progress_path, open_mode) as file:
-            print(f'DEBUG: In _do_download loop [4]', flush=True)
             for data in resp.iter_content(chunk_size=DOWNLOAD_CHUNK_SIZE):
                 if job.cancelled:
                     raise DownloadJobCancelledException("Job was cancelled at caller's request")
@@ -329,8 +314,6 @@ class DownloadQueueService(DownloadQueueServiceBase):
         # if we get here we are done and can rename the file to the original dest
         self._logger.debug(f"{job.source}: saved to {job.download_path} (bytes={job.bytes})")
         in_progress_path.rename(job.download_path)
-        print(f'DEBUG: In _do_download [5]', flush=True)
-
 
     def _validate_filename(self, directory: str, filename: str) -> bool:
         pc_name_max = os.pathconf(directory, "PC_NAME_MAX") if hasattr(os, "pathconf") else 260  # hardcoded for windows
diff --git a/invokeai/app/services/model_install/model_install_base.py b/invokeai/app/services/model_install/model_install_base.py
index 737f62a064..4f2cdaed8e 100644
--- a/invokeai/app/services/model_install/model_install_base.py
+++ b/invokeai/app/services/model_install/model_install_base.py
@@ -28,6 +28,7 @@ class InstallStatus(str, Enum):
 
     WAITING = "waiting"  # waiting to be dequeued
     DOWNLOADING = "downloading"  # downloading of model files in process
+    DOWNLOADS_DONE = "downloads_done"  # downloading done, waiting to run
     RUNNING = "running"  # being processed
     COMPLETED = "completed"  # finished running
     ERROR = "error"  # terminated with an error message
@@ -229,6 +230,11 @@ class ModelInstallJob(BaseModel):
         """Return true if job is downloading."""
         return self.status == InstallStatus.DOWNLOADING
 
+    @property
+    def downloads_done(self) -> bool:
+        """Return true if job's downloads ae done."""
+        return self.status == InstallStatus.DOWNLOADS_DONE
+
     @property
     def running(self) -> bool:
         """Return true if job is running."""
diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py
index fe8124923f..93287a40c6 100644
--- a/invokeai/app/services/model_install/model_install_default.py
+++ b/invokeai/app/services/model_install/model_install_default.py
@@ -28,7 +28,6 @@ from invokeai.backend.model_manager.config import (
     ModelRepoVariant,
     ModelType,
 )
-from invokeai.backend.model_manager.hash import FastModelHash
 from invokeai.backend.model_manager.metadata import (
     AnyModelRepoMetadata,
     CivitaiMetadataFetch,
@@ -153,7 +152,6 @@ class ModelInstallService(ModelInstallServiceBase):
             config["source"] = model_path.resolve().as_posix()
 
         info: AnyModelConfig = self._probe_model(Path(model_path), config)
-        old_hash = info.current_hash
 
         if preferred_name := config.get("name"):
             preferred_name = Path(preferred_name).with_suffix(model_path.suffix)
@@ -167,8 +165,6 @@ class ModelInstallService(ModelInstallServiceBase):
             raise DuplicateModelException(
                 f"A model named {model_path.name} is already installed at {dest_path.as_posix()}"
             ) from excp
-        new_hash = FastModelHash.hash(new_path)
-        assert new_hash == old_hash, f"{model_path}: Model hash changed during installation, possibly corrupted."
 
         return self._register(
             new_path,
@@ -370,7 +366,7 @@ class ModelInstallService(ModelInstallServiceBase):
                     self._signal_job_errored(job)
 
                 elif (
-                    job.waiting or job.downloading
+                    job.waiting or job.downloads_done
                 ):  # local jobs will be in waiting state, remote jobs will be downloading state
                     job.total_bytes = self._stat_size(job.local_path)
                     job.bytes = job.total_bytes
@@ -448,7 +444,7 @@ class ModelInstallService(ModelInstallServiceBase):
                     installed.update(self.scan_directory(models_dir))
             self._logger.info(f"{len(installed)} new models registered; {len(defunct_models)} unregistered")
 
-    def _sync_model_path(self, key: str, ignore_hash_change: bool = False) -> AnyModelConfig:
+    def _sync_model_path(self, key: str) -> AnyModelConfig:
         """
         Move model into the location indicated by its basetype, type and name.
 
@@ -469,14 +465,7 @@ class ModelInstallService(ModelInstallServiceBase):
         new_path = models_dir / model.base.value / model.type.value / model.name
         self._logger.info(f"Moving {model.name} to {new_path}.")
         new_path = self._move_model(old_path, new_path)
-        new_hash = FastModelHash.hash(new_path)
         model.path = new_path.relative_to(models_dir).as_posix()
-        if model.current_hash != new_hash:
-            assert (
-                ignore_hash_change
-            ), f"{model.name}: Model hash changed during installation, model is possibly corrupted"
-            model.current_hash = new_hash
-            self._logger.info(f"Model has new hash {model.current_hash}, but will continue to be identified by {key}")
         self.record_store.update_model(key, model)
         return model
 
@@ -749,8 +738,8 @@ class ModelInstallService(ModelInstallServiceBase):
             self._download_cache.pop(download_job.source, None)
 
             # are there any more active jobs left in this task?
-            if all(x.complete for x in install_job.download_parts):
-                #  now enqueue job for actual installation into the models directory
+            if install_job.downloading and all(x.complete for x in install_job.download_parts):
+                install_job.status = InstallStatus.DOWNLOADS_DONE
                 self._install_queue.put(install_job)
 
             # Let other threads know that the number of downloads has changed
diff --git a/pyproject.toml b/pyproject.toml
index 661adfe4c4..26db5a63c7 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -187,10 +187,10 @@ version = { attr = "invokeai.version.__version__" }
 
 #=== Begin: PyTest and Coverage
 [tool.pytest.ini_options]
-addopts = "--cov-report term --cov-report html --cov-report xml --strict-markers -m \"not slow\""
+addopts = "--cov-report term --cov-report html --cov-report xml --strict-markers --timeout 60 -m \"not slow\""
 markers = [
   "slow: Marks tests as slow. Disabled by default. To run all tests, use -m \"\". To run only slow tests, use -m \"slow\".",
-  "timeout: 60"
+  "timeout: Marks the timeout override."
 ]
 [tool.coverage.run]
 branch = true
diff --git a/tests/app/services/download/test_download_queue.py b/tests/app/services/download/test_download_queue.py
index 77d77836ec..543703d713 100644
--- a/tests/app/services/download/test_download_queue.py
+++ b/tests/app/services/download/test_download_queue.py
@@ -166,6 +166,7 @@ def test_broken_callbacks(tmp_path: Path, session: Session, capsys) -> None:
     # assert re.search("division by zero", captured.err)
     queue.stop()
 
+
 @pytest.mark.timeout(timeout=15, method="thread")
 def test_cancel(tmp_path: Path, session: Session) -> None:
     event_bus = TestEventService()
diff --git a/tests/app/services/model_install/test_model_install.py b/tests/app/services/model_install/test_model_install.py
index c0a6e7b2b6..c1e588089b 100644
--- a/tests/app/services/model_install/test_model_install.py
+++ b/tests/app/services/model_install/test_model_install.py
@@ -220,6 +220,7 @@ def test_simple_download(mm2_installer: ModelInstallServiceBase, mm2_app_config:
     event_names = [x.event_name for x in bus.events]
     assert event_names == ["model_install_downloading", "model_install_running", "model_install_completed"]
 
+
 @pytest.mark.timeout(timeout=20, method="thread")
 def test_huggingface_download(mm2_installer: ModelInstallServiceBase, mm2_app_config: InvokeAIAppConfig) -> None:
     source = URLModelSource(url=Url("https://huggingface.co/stabilityai/sdxl-turbo"))
diff --git a/tests/backend/model_manager/model_manager_fixtures.py b/tests/backend/model_manager/model_manager_fixtures.py
index df54e2f926..fce72cb04d 100644
--- a/tests/backend/model_manager/model_manager_fixtures.py
+++ b/tests/backend/model_manager/model_manager_fixtures.py
@@ -2,6 +2,7 @@
 
 import os
 import shutil
+import time
 from pathlib import Path
 from typing import Any, Dict, List
 
@@ -149,6 +150,7 @@ def mm2_installer(
 
     def stop_installer() -> None:
         installer.stop()
+        time.sleep(0.1)  # avoid error message from the logger when it is closed before thread prints final message
 
     request.addfinalizer(stop_installer)
     return installer

From 3a2afe1d15a0fdd6ebdda972e77259322548651c Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Fri, 1 Mar 2024 10:23:51 +1100
Subject: [PATCH 386/411] chore: ruff

---
 tests/app/services/model_install/test_model_install.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/tests/app/services/model_install/test_model_install.py b/tests/app/services/model_install/test_model_install.py
index c1e588089b..7e51e8deb3 100644
--- a/tests/app/services/model_install/test_model_install.py
+++ b/tests/app/services/model_install/test_model_install.py
@@ -195,6 +195,7 @@ def test_delete_register(
     with pytest.raises(UnknownModelException):
         store.get_model(key)
 
+
 @pytest.mark.timeout(timeout=20, method="thread")
 def test_simple_download(mm2_installer: ModelInstallServiceBase, mm2_app_config: InvokeAIAppConfig) -> None:
     source = URLModelSource(url=Url("https://www.test.foo/download/test_embedding.safetensors"))

From a0313ba63402fd7b8e038193b847b2530fc376c8 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sun, 24 Dec 2023 01:16:05 +1100
Subject: [PATCH 387/411] feat: automated releases via github action

- Restructure & update code check workflows
- Add release workflow to handle checks/tests, build and publish to PyPI
- Add docs/RELEASE.md explaining the workflow & process
- `create_installer.sh`: Update to work with the release workflow
- `create_installer.sh` & `tag_release.sh`: Fix the ANSI escape codes for macOS
- `tag_release.sh`: Add check for python binary name
- `tag_release.sh`: Print `git remote -v` output
- `tag_release.sh`: Fix error when deleting nonexistant tags
---
 .../actions/install-frontend-deps/action.yml  |  33 ++++
 .../actions/install-python-deps/action.yml    |  11 ++
 .github/workflows/build-container.yml         |   2 +-
 .github/workflows/check-frontend.yml          |  38 +++++
 .../{test-invoke-pip.yml => check-pytest.yml} |  34 +---
 .github/workflows/check-python.yml            |  26 +++
 .github/workflows/lint-frontend.yml           |  45 -----
 .../workflows/on-change-check-frontend.yml    |  34 ++++
 .github/workflows/on-change-check-python.yml  |  37 +++++
 .github/workflows/on-change-pytest.yml        |  37 +++++
 ...{pypi-release.yml => pypi-release.yml.old} |   0
 .github/workflows/release.yml                 | 103 ++++++++++++
 .github/workflows/style-checks.yml            |  24 ---
 .prettierrc.yaml                              |   2 +-
 docs/RELEASE.md                               | 155 ++++++++++++++++++
 installer/create_installer.sh                 |  69 ++++++--
 installer/tag_release.sh                      |  42 +++--
 17 files changed, 566 insertions(+), 126 deletions(-)
 create mode 100644 .github/actions/install-frontend-deps/action.yml
 create mode 100644 .github/actions/install-python-deps/action.yml
 create mode 100644 .github/workflows/check-frontend.yml
 rename .github/workflows/{test-invoke-pip.yml => check-pytest.yml} (76%)
 create mode 100644 .github/workflows/check-python.yml
 delete mode 100644 .github/workflows/lint-frontend.yml
 create mode 100644 .github/workflows/on-change-check-frontend.yml
 create mode 100644 .github/workflows/on-change-check-python.yml
 create mode 100644 .github/workflows/on-change-pytest.yml
 rename .github/workflows/{pypi-release.yml => pypi-release.yml.old} (100%)
 create mode 100644 .github/workflows/release.yml
 delete mode 100644 .github/workflows/style-checks.yml
 create mode 100644 docs/RELEASE.md

diff --git a/.github/actions/install-frontend-deps/action.yml b/.github/actions/install-frontend-deps/action.yml
new file mode 100644
index 0000000000..b9d910ca99
--- /dev/null
+++ b/.github/actions/install-frontend-deps/action.yml
@@ -0,0 +1,33 @@
+name: Install frontend dependencies
+description: Installs frontend dependencies with pnpm, with caching
+runs:
+  using: 'composite'
+  steps:
+    - name: Setup Node 18
+      uses: actions/setup-node@v4
+      with:
+        node-version: '18'
+
+    - name: Setup pnpm
+      uses: pnpm/action-setup@v2
+      with:
+        version: 8
+        run_install: false
+
+    - name: Get pnpm store directory
+      shell: bash
+      run: |
+        echo "STORE_PATH=$(pnpm store path --silent)" >> $GITHUB_ENV
+
+    - uses: actions/cache@v3
+      name: Setup pnpm cache
+      with:
+        path: ${{ env.STORE_PATH }}
+        key: ${{ runner.os }}-pnpm-store-${{ hashFiles('**/pnpm-lock.yaml') }}
+        restore-keys: |
+          ${{ runner.os }}-pnpm-store-
+
+    - name: Install frontend dependencies
+      run: pnpm install --prefer-frozen-lockfile
+      shell: bash
+      working-directory: invokeai/frontend/web
diff --git a/.github/actions/install-python-deps/action.yml b/.github/actions/install-python-deps/action.yml
new file mode 100644
index 0000000000..4c0d351899
--- /dev/null
+++ b/.github/actions/install-python-deps/action.yml
@@ -0,0 +1,11 @@
+name: Install python dependencies
+description: Install python dependencies with pip, with caching
+runs:
+  using: 'composite'
+  steps:
+    - name: Setup python
+      uses: actions/setup-python@v5
+      with:
+        python-version: '3.10'
+        cache: pip
+        cache-dependency-path: pyproject.toml
diff --git a/.github/workflows/build-container.yml b/.github/workflows/build-container.yml
index 74fcc02ab3..a8bfaa540c 100644
--- a/.github/workflows/build-container.yml
+++ b/.github/workflows/build-container.yml
@@ -11,7 +11,7 @@ on:
       - 'docker/docker-entrypoint.sh'
       - 'workflows/build-container.yml'
     tags:
-      - 'v*'
+      - 'v*.*.*'
   workflow_dispatch:
 
 permissions:
diff --git a/.github/workflows/check-frontend.yml b/.github/workflows/check-frontend.yml
new file mode 100644
index 0000000000..634ad84ee2
--- /dev/null
+++ b/.github/workflows/check-frontend.yml
@@ -0,0 +1,38 @@
+name: 'Check: frontend'
+
+on:
+  workflow_dispatch:
+  workflow_call:
+
+defaults:
+  run:
+    working-directory: invokeai/frontend/web
+
+jobs:
+  check-frontend:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Set up frontend
+        uses: ./.github/actions/install-frontend-deps
+
+      - name: Run tsc check
+        run: 'pnpm run lint:tsc'
+        shell: bash
+
+      - name: Run dpdm check
+        run: 'pnpm run lint:dpdm'
+        shell: bash
+
+      - name: Run eslint check
+        run: 'pnpm run lint:eslint'
+        shell: bash
+
+      - name: Run prettier check
+        run: 'pnpm run lint:prettier'
+        shell: bash
+
+      - name: Run knip check
+        run: 'pnpm run lint:knip'
+        shell: bash
diff --git a/.github/workflows/test-invoke-pip.yml b/.github/workflows/check-pytest.yml
similarity index 76%
rename from .github/workflows/test-invoke-pip.yml
rename to .github/workflows/check-pytest.yml
index bbbc66828c..bdab6fc4d4 100644
--- a/.github/workflows/test-invoke-pip.yml
+++ b/.github/workflows/check-pytest.yml
@@ -1,15 +1,8 @@
-name: Test invoke.py pip
+name: 'Check: pytest'
+
 on:
-  push:
-    branches:
-      - 'main'
-  pull_request:
-    types:
-      - 'ready_for_review'
-      - 'opened'
-      - 'synchronize'
-  merge_group:
   workflow_dispatch:
+  workflow_call:
 
 concurrency:
   group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
@@ -17,11 +10,9 @@ concurrency:
 
 jobs:
   matrix:
-    if: github.event.pull_request.draft == false
     strategy:
       matrix:
         python-version:
-          # - '3.9'
           - '3.10'
         pytorch:
           - linux-cuda-11_7
@@ -52,27 +43,12 @@ jobs:
     env:
       PIP_USE_PEP517: '1'
     steps:
-      - name: Checkout sources
-        id: checkout-sources
-        uses: actions/checkout@v3
-
-      - name: Check for changed python files
-        id: changed-files
-        uses: tj-actions/changed-files@v41
-        with:
-          files_yaml: |
-            python:
-              - 'pyproject.toml'
-              - 'invokeai/**'
-              - '!invokeai/frontend/web/**'
-              - 'tests/**'
+      - uses: actions/checkout@v4
 
       - name: set test prompt to main branch validation
-        if: steps.changed-files.outputs.python_any_changed == 'true'
         run: echo "TEST_PROMPTS=tests/validate_pr_prompt.txt" >> ${{ matrix.github-env }}
 
       - name: setup python
-        if: steps.changed-files.outputs.python_any_changed == 'true'
         uses: actions/setup-python@v4
         with:
           python-version: ${{ matrix.python-version }}
@@ -80,7 +56,6 @@ jobs:
           cache-dependency-path: pyproject.toml
 
       - name: install invokeai
-        if: steps.changed-files.outputs.python_any_changed == 'true'
         env:
           PIP_EXTRA_INDEX_URL: ${{ matrix.extra-index-url }}
         run: >
@@ -88,7 +63,6 @@ jobs:
           --editable=".[test]"
 
       - name: run pytest
-        if: steps.changed-files.outputs.python_any_changed == 'true'
         id: run-pytest
         run: pytest
 
diff --git a/.github/workflows/check-python.yml b/.github/workflows/check-python.yml
new file mode 100644
index 0000000000..c58b4661c7
--- /dev/null
+++ b/.github/workflows/check-python.yml
@@ -0,0 +1,26 @@
+name: 'Check: python'
+
+on:
+  workflow_dispatch:
+  workflow_call:
+
+jobs:
+  check-backend:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Install python dependencies
+        uses: ./.github/actions/install-python-deps
+
+      - name: Install ruff
+        run: pip install ruff
+        shell: bash
+
+      - name: Ruff check
+        run: ruff check --output-format=github .
+        shell: bash
+
+      - name: Ruff format
+        run: ruff format --check .
+        shell: bash
diff --git a/.github/workflows/lint-frontend.yml b/.github/workflows/lint-frontend.yml
deleted file mode 100644
index e794892933..0000000000
--- a/.github/workflows/lint-frontend.yml
+++ /dev/null
@@ -1,45 +0,0 @@
-name: Lint frontend
-
-on:
-  pull_request:
-    types:
-      - 'ready_for_review'
-      - 'opened'
-      - 'synchronize'
-  push:
-    branches:
-      - 'main'
-  merge_group:
-  workflow_dispatch:
-
-defaults:
-  run:
-    working-directory: invokeai/frontend/web
-
-jobs:
-  lint-frontend:
-    if: github.event.pull_request.draft == false
-    runs-on: ubuntu-22.04
-    steps:
-      - name: Setup Node 18
-        uses: actions/setup-node@v4
-        with:
-          node-version: '18'
-      - name: Checkout
-        uses: actions/checkout@v4
-      - name: Setup pnpm
-        uses: pnpm/action-setup@v2
-        with:
-          version: '8.12.1'
-      - name: Install dependencies
-        run: 'pnpm install --prefer-frozen-lockfile'
-      - name: Typescript
-        run: 'pnpm run lint:tsc'
-      - name: Madge
-        run: 'pnpm run lint:dpdm'
-      - name: ESLint
-        run: 'pnpm run lint:eslint'
-      - name: Prettier
-        run: 'pnpm run lint:prettier'
-      - name: Knip
-        run: 'pnpm run lint:knip'
diff --git a/.github/workflows/on-change-check-frontend.yml b/.github/workflows/on-change-check-frontend.yml
new file mode 100644
index 0000000000..814f94ca5b
--- /dev/null
+++ b/.github/workflows/on-change-check-frontend.yml
@@ -0,0 +1,34 @@
+name: 'On change: run check-frontend'
+
+on:
+  push:
+    branches:
+      - 'main'
+  pull_request:
+    types:
+      - 'ready_for_review'
+      - 'opened'
+      - 'synchronize'
+  merge_group:
+
+jobs:
+  check-changed-frontend-files:
+    if: github.event.pull_request.draft == false
+    runs-on: ubuntu-latest
+    outputs:
+      frontend_any_changed: ${{ steps.changed-files.outputs.frontend_any_changed }}
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Check for changed frontend files
+        id: changed-files
+        uses: tj-actions/changed-files@v40
+        with:
+          files_yaml: |
+            frontend:
+              - 'invokeai/frontend/web/**'
+
+  run-check-frontend:
+    needs: check-changed-frontend-files
+    if: ${{ needs.check-changed-frontend-files.outputs.frontend_any_changed == 'true' }}
+    uses: ./.github/workflows/check-frontend.yml
diff --git a/.github/workflows/on-change-check-python.yml b/.github/workflows/on-change-check-python.yml
new file mode 100644
index 0000000000..cc2be902b4
--- /dev/null
+++ b/.github/workflows/on-change-check-python.yml
@@ -0,0 +1,37 @@
+name: 'On change: run check-python'
+
+on:
+  push:
+    branches:
+      - 'main'
+  pull_request:
+    types:
+      - 'ready_for_review'
+      - 'opened'
+      - 'synchronize'
+  merge_group:
+
+jobs:
+  check-changed-python-files:
+    if: github.event.pull_request.draft == false
+    runs-on: ubuntu-latest
+    outputs:
+      python_any_changed: ${{ steps.changed-files.outputs.python_any_changed }}
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Check for changed python files
+        id: changed-files
+        uses: tj-actions/changed-files@v40
+        with:
+          files_yaml: |
+            python:
+              - 'pyproject.toml'
+              - 'invokeai/**'
+              - '!invokeai/frontend/web/**'
+              - 'tests/**'
+
+  run-check-python:
+    needs: check-changed-python-files
+    if: ${{ needs.check-changed-python-files.outputs.python_any_changed == 'true' }}
+    uses: ./.github/workflows/check-python.yml
diff --git a/.github/workflows/on-change-pytest.yml b/.github/workflows/on-change-pytest.yml
new file mode 100644
index 0000000000..081d85d4fb
--- /dev/null
+++ b/.github/workflows/on-change-pytest.yml
@@ -0,0 +1,37 @@
+name: 'On change: run pytest'
+
+on:
+  push:
+    branches:
+      - 'main'
+  pull_request:
+    types:
+      - 'ready_for_review'
+      - 'opened'
+      - 'synchronize'
+  merge_group:
+
+jobs:
+  check-changed-python-files:
+    if: github.event.pull_request.draft == false
+    runs-on: ubuntu-latest
+    outputs:
+      python_any_changed: ${{ steps.changed-files.outputs.python_any_changed }}
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Check for changed python files
+        id: changed-files
+        uses: tj-actions/changed-files@v40
+        with:
+          files_yaml: |
+            python:
+              - 'pyproject.toml'
+              - 'invokeai/**'
+              - '!invokeai/frontend/web/**'
+              - 'tests/**'
+
+  run-pytest:
+    needs: check-changed-python-files
+    if: ${{ needs.check-changed-python-files.outputs.python_any_changed == 'true' }}
+    uses: ./.github/workflows/check-pytest.yml
diff --git a/.github/workflows/pypi-release.yml b/.github/workflows/pypi-release.yml.old
similarity index 100%
rename from .github/workflows/pypi-release.yml
rename to .github/workflows/pypi-release.yml.old
diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml
new file mode 100644
index 0000000000..a0ee97f724
--- /dev/null
+++ b/.github/workflows/release.yml
@@ -0,0 +1,103 @@
+name: Release
+
+on:
+  push:
+    tags:
+      - 'v*.*.*'
+  workflow_dispatch:
+    inputs:
+      skip_code_checks:
+        description: 'Skip code checks'
+        required: true
+        default: true
+        type: boolean
+
+jobs:
+  check-version:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+
+      - uses: samuelcolvin/check-python-version@v4
+        id: check-python-version
+        with:
+          version_file_path: invokeai/version/invokeai_version.py
+
+  check-frontend:
+    if: github.event.inputs.skip_code_checks != 'true'
+    uses: ./.github/workflows/check-frontend.yml
+
+  check-python:
+    if: github.event.inputs.skip_code_checks != 'true'
+    uses: ./.github/workflows/check-python.yml
+
+  check-pytest:
+    if: github.event.inputs.skip_code_checks != 'true'
+    uses: ./.github/workflows/check-pytest.yml
+
+  build:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Install python dependencies
+        uses: ./.github/actions/install-python-deps
+
+      - name: Install pypa/build
+        run: pip install --upgrade build
+
+      - name: Setup frontend
+        uses: ./.github/actions/install-frontend-deps
+
+      - name: Run create_installer.sh
+        id: create_installer
+        run: ./create_installer.sh --skip_frontend_checks
+        working-directory: installer
+
+      - name: Upload python distribution artifact
+        uses: actions/upload-artifact@v4
+        with:
+          name: dist
+          path: ${{ steps.create_installer.outputs.DIST_PATH }}
+
+      - name: Upload installer artifact
+        uses: actions/upload-artifact@v4
+        with:
+          name: ${{ steps.create_installer.outputs.INSTALLER_FILENAME }}
+          path: ${{ steps.create_installer.outputs.INSTALLER_PATH }}
+
+  publish-testpypi:
+    runs-on: ubuntu-latest
+    needs: [check-version, check-frontend, check-python, check-pytest, build]
+    if: github.event_name != 'workflow_dispatch'
+    environment:
+      name: testpypi
+      url: https://test.pypi.org/p/invokeai
+    steps:
+      - name: Download distribution from build job
+        uses: actions/download-artifact@v4
+        with:
+          name: dist
+          path: dist/
+
+      - name: Publish distribution to TestPyPI
+        uses: pypa/gh-action-pypi-publish@release/v1
+        with:
+          repository-url: https://test.pypi.org/legacy/
+
+  publish-pypi:
+    runs-on: ubuntu-latest
+    needs: [check-version, check-frontend, check-python, check-pytest, build]
+    if: github.event_name != 'workflow_dispatch'
+    environment:
+      name: pypi
+      url: https://pypi.org/p/invokeai
+    steps:
+      - name: Download distribution from build job
+        uses: actions/download-artifact@v4
+        with:
+          name: dist
+          path: dist/
+
+      - name: Publish distribution to PyPI
+        uses: pypa/gh-action-pypi-publish@release/v1
diff --git a/.github/workflows/style-checks.yml b/.github/workflows/style-checks.yml
deleted file mode 100644
index 7e99702213..0000000000
--- a/.github/workflows/style-checks.yml
+++ /dev/null
@@ -1,24 +0,0 @@
-name: style checks
-
-on:
-  pull_request:
-  push:
-    branches: main
-
-jobs:
-  ruff:
-    runs-on: ubuntu-latest
-    steps:
-      - uses: actions/checkout@v3
-
-      - name: Setup Python
-        uses: actions/setup-python@v4
-        with:
-          python-version: '3.10'
-
-      - name: Install dependencies with pip
-        run: |
-          pip install ruff
-
-      - run: ruff check --output-format=github .
-      - run: ruff format --check .
diff --git a/.prettierrc.yaml b/.prettierrc.yaml
index ce4b99a07b..3d2ce3b880 100644
--- a/.prettierrc.yaml
+++ b/.prettierrc.yaml
@@ -7,7 +7,7 @@ embeddedLanguageFormatting: auto
 overrides:
   - files: '*.md'
     options:
-      proseWrap: always
+      proseWrap: preserve
       printWidth: 80
       parser: markdown
       cursorOffset: -1
diff --git a/docs/RELEASE.md b/docs/RELEASE.md
new file mode 100644
index 0000000000..caf8ba8799
--- /dev/null
+++ b/docs/RELEASE.md
@@ -0,0 +1,155 @@
+# Release Workflow
+
+The app is published in twice, in different build formats.
+
+- A [PyPI] distribution. This includes both a source distribution and built distribution (a wheel). Users install with `pip install invokeai`. The updater uses this build.
+- An installer on the [InvokeAI Releases Page]. This is a zip file with install scripts and a wheel. This is only used for new installs.
+
+## General Prep
+
+Make a developer call-out for PRs to merge. Merge and test things out.
+
+While the release workflow does not include end-to-end tests, it does pause before publishing so you can download and test the final build.
+
+## Workflow Overview
+
+The `release.yml` workflow runs a number of jobs to handle code checks, tests, build and publish on PyPI.
+
+It is triggered on **tag push**, when the tag matches `v*.*.*`. It doesn't matter if you've prepped a release branch like `release/v3.5.0` or are releasing from `main` - it works the same.
+
+!!! tip
+
+    Because commits are reference-counted, it is safe to create a release branch, tag it, let the workflow run, then delete the branch.
+
+    So long as the tag exists, that commit will exist.
+
+### Triggering the Workflow
+
+Run `make tag-release` to tag the current commit and kick off the workflow.
+
+This script actually makes two tags - one for the specific version, and a `vX-latest` tag that changes with each release.
+
+Because the release workflow only triggers on the pattern `v*.*.*`, the workflow will only run once when running this script.
+
+The release may also be run [manually].
+
+### Workflow Jobs and Process
+
+The workflow consists of a number of concurrently-run jobs, and two final publish jobs.
+
+The publish jobs run if the 5 concurrent jobs all succeed and if/when the publish jobs are approved.
+
+#### `check-version` Job
+
+This job checks that the git ref matches the app version. It matches the ref against the `__version__` variable in `invokeai/version/invokeai_version.py`.
+
+When the workflow is triggered by tag push, the ref is the tag. If the workflow is run manually, the ref is the target selected from the **Use workflow from** dropdown.
+
+!!! tip
+
+    Any valid [version specifier] works, so long as the tag matches the version. The release workflow works exactly the same for `RC`, `post`, `dev`, etc.
+
+#### Check and Test Jobs
+
+This is our test suite.
+
+- **`check-pytest`**: runs `pytest` on matrix of platforms
+- **`check-python`**: runs `ruff` (format and lint)
+- **`check-frontend`**: runs `prettier` (format), `eslint` (lint), `madge` (circular refs) and `tsc` (static type check)
+
+!!! info Future Enhancement
+
+    We should add `mypy` or `pyright` to the **`check-python`** job.
+
+!!! info Future Enhancement
+
+    We should add an end-to-end test job that generates an image.
+
+#### `build` Job
+
+This sets up both python and frontend dependencies and builds the python package. Internally, this runs `installer/create_installer.sh` and uploads two artifacts:
+
+- **`dist`**: the python distribution, to be published on PyPI
+- **`InvokeAI-installer-${VERSION}.zip`**: the installer to be included in the GitHub release
+
+#### Sanity Check & Smoke Test
+
+At this point, the release workflow pauses (the remaining jobs all require approval).
+
+A maintainer should go to the **Summary** tab of the workflow, download the installer and test it. Ensure the app loads and generates.
+
+!!! info
+
+    The exact same wheel file is bundled in the installer and in the `dist` artifact, which is uploaded to PyPI. You should end up with the same exact installation of the `invokeai` package from any of these methods.
+
+#### PyPI Publish Jobs
+
+The publish jobs will skip if any of the previous jobs skip or fail.
+
+They use [GitHub environments], which are configured as [trusted publishers] on PyPI.
+
+Both jobs require a maintainer to approve them from the workflow's **Summary** tab.
+
+- Click the **Review deployments** button
+- Select the environment (either `testpypi` or `pypi`)
+- Click **Approve and deploy**
+
+!!! warning
+
+    **If the version already exists on PyPI, the publish jobs will fail.** PyPI only allows a particular version to be published once - you cannot change it. If version published on PyPI has a problem, you'll need to "fail forward" by bumping the app version and publishing a followup release.
+
+#### `publish-testpypi` Job
+
+Publishes the distribution on the [Test PyPI] index, using the `testpypi` GitHub environment.
+
+This job is not required for the production PyPI publish, but included just in case you want to test the PyPI release.
+
+If approved and successful, you could try out the test release like this:
+
+```sh
+# Create a new virtual environment
+python -m venv ~/.test-invokeai-dist --prompt test-invokeai-dist
+# Install the distribution from Test PyPI
+pip install --index-url https://test.pypi.org/simple/ invokeai
+# Run and test the app
+invokeai-web
+# Cleanup
+deactivate
+rm -rf ~/.test-invokeai-dist
+```
+
+#### `publish-pypi` Job
+
+Publishes the distribution on the production PyPI index, using the `pypi` GitHub environment.
+
+## Publish the GitHub RC with installer
+
+1. [Draft a new release] on GitHub, choosing the tag that triggered the release.
+2. Write the release notes, describing important changes. The **Generate release notes** button automatically inserts the changelog and new contributors, and you can copy/paste the intro from previous releases.
+3. Upload the zip file created in [Build the installer] into the Assets section of the release notes. You can also upload the zip into the body of the release notes, since it can be hard for users to find the Assets section.
+4. Check the **Set as a pre-release** and **Create a discussion for this release** checkboxes at the bottom of the release page.
+5. Publish the pre-release.
+6. Announce the pre-release in Discord.
+
+!!! info Future Enhancement
+
+    Workflows can create a GitHub release from a template and upload release assets. One popular action to handle this is [ncipollo/release-action]. A future enhancement to the release process could set this up.
+
+## Manually Running the Release Workflow
+
+The release workflow can be run manually. This is useful to get an installer build and test it out without needing to push a tag.
+
+When run this way, you'll see **Skip code checks** checkbox. This allows the workflow to run without the time-consuming 3 code quality check jobs.
+
+The publish jobs will skip if the workflow was run manually.
+
+[InvokeAI Releases Page]: https://github.com/invoke-ai/InvokeAI/releases
+[PyPI]: https://pypi.org/
+[Draft a new release]: https://github.com/invoke-ai/InvokeAI/releases/new
+[Test PyPI]: https://test.pypi.org/
+[version specifier]: https://packaging.python.org/en/latest/specifications/version-specifiers/
+[ncipollo/release-action]: https://github.com/ncipollo/release-action
+[GitHub environments]: https://docs.github.com/en/actions/deployment/targeting-different-environments/using-environments-for-deployment
+[trusted publishers]: https://docs.pypi.org/trusted-publishers/
+[samuelcolvin/check-python-version]: https://github.com/samuelcolvin/check-python-version
+[manually]: #manually-running-the-release-workflow
diff --git a/installer/create_installer.sh b/installer/create_installer.sh
index 57b681c42e..5f5d2adb74 100755
--- a/installer/create_installer.sh
+++ b/installer/create_installer.sh
@@ -2,12 +2,12 @@
 
 set -e
 
-BCYAN="\e[1;36m"
-BYELLOW="\e[1;33m"
-BGREEN="\e[1;32m"
-BRED="\e[1;31m"
-RED="\e[31m"
-RESET="\e[0m"
+BCYAN="\033[1;36m"
+BYELLOW="\033[1;33m"
+BGREEN="\033[1;32m"
+BRED="\033[1;31m"
+RED="\033[31m"
+RESET="\033[0m"
 
 function is_bin_in_path {
     builtin type -P "$1" &>/dev/null
@@ -44,13 +44,47 @@ VERSION=$(
     cd ..
     python -c "from invokeai.version import __version__ as version; print(version)"
 )
-PATCH=""
-VERSION="v${VERSION}${PATCH}"
+VERSION="v${VERSION}"
 
 echo -e "${BGREEN}HEAD${RESET}:"
 git_show HEAD
 echo
 
+# ---------------------- FRONTEND ----------------------
+
+pushd ../invokeai/frontend/web >/dev/null
+echo
+echo "Installing frontend dependencies..."
+echo
+pnpm i --frozen-lockfile
+echo
+echo "Building frontend..."
+if [[ -v CI ]]; then
+    # In CI, we have already done the frontend checks and can just build
+    pnpm vite build
+else
+    # This runs all the frontend checks and builds
+    pnpm build
+fi
+echo
+popd
+
+# ---------------------- BACKEND ----------------------
+
+echo
+echo "Building wheel..."
+echo
+
+# install the 'build' package in the user site packages, if needed
+# could be improved by using a temporary venv, but it's tiny and harmless
+if [[ $(python -c 'from importlib.util import find_spec; print(find_spec("build") is None)') == "True" ]]; then
+    pip install --user build
+fi
+
+rm -rf ../build
+
+python -m build --outdir dist/ ../.
+
 # ----------------------
 
 echo
@@ -78,10 +112,21 @@ chmod a+x InvokeAI-Installer/install.sh
 cp install.bat.in InvokeAI-Installer/install.bat
 cp WinLongPathsEnabled.reg InvokeAI-Installer/
 
-# Zip everything up
-zip -r InvokeAI-installer-$VERSION.zip InvokeAI-Installer
+FILENAME=InvokeAI-installer-$VERSION.zip
 
-# clean up
-rm -rf InvokeAI-Installer tmp dist ../invokeai/frontend/web/dist/
+# Zip everything up
+zip -r $FILENAME InvokeAI-Installer
+
+if [[ ! -v CI ]]; then
+    # clean up, but only if we are not in a github action
+    rm -rf InvokeAI-Installer tmp dist ../invokeai/frontend/web/dist/
+fi
+
+if [[ -v CI ]]; then
+    # Set the output variable for github action
+    echo "INSTALLER_FILENAME=$FILENAME" >>$GITHUB_OUTPUT
+    echo "INSTALLER_PATH=installer/$FILENAME" >>$GITHUB_OUTPUT
+    echo "DIST_PATH=installer/dist/" >>$GITHUB_OUTPUT
+fi
 
 exit 0
diff --git a/installer/tag_release.sh b/installer/tag_release.sh
index a914c1a505..2955bf5db5 100755
--- a/installer/tag_release.sh
+++ b/installer/tag_release.sh
@@ -2,12 +2,16 @@
 
 set -e
 
-BCYAN="\e[1;36m"
-BYELLOW="\e[1;33m"
-BGREEN="\e[1;32m"
-BRED="\e[1;31m"
-RED="\e[31m"
-RESET="\e[0m"
+BCYAN="\033[1;36m"
+BYELLOW="\033[1;33m"
+BGREEN="\033[1;32m"
+BRED="\033[1;31m"
+RED="\033[31m"
+RESET="\033[0m"
+
+function is_bin_in_path {
+    builtin type -P "$1" &>/dev/null
+}
 
 function does_tag_exist {
     git rev-parse --quiet --verify "refs/tags/$1" >/dev/null
@@ -21,6 +25,14 @@ function git_show {
     git show -s --format='%h %s' $1
 }
 
+# Some machines only have `python3` in PATH, others have `python` - make an alias.
+# We can use a function to approximate an alias within a non-interactive shell.
+if ! is_bin_in_path python && is_bin_in_path python3; then
+    function python {
+        python3 "$@"
+    }
+fi
+
 VERSION=$(
     cd ..
     python -c "from invokeai.version import __version__ as version; print(version)"
@@ -45,27 +57,31 @@ echo -e "${BGREEN}HEAD${RESET}:"
 git_show
 echo
 
-echo -e -n "Create tags ${BCYAN}${VERSION}${RESET} and ${BCYAN}${LATEST_TAG}${RESET} @ ${BGREEN}HEAD${RESET}, ${RED}deleting existing tags on remote${RESET}? "
+echo -e "${BGREEN}git remote -v${RESET}:"
+git remote -v
+echo
+
+echo -e -n "Create tags ${BCYAN}${VERSION}${RESET} and ${BCYAN}${LATEST_TAG}${RESET} @ ${BGREEN}HEAD${RESET}, ${RED}deleting existing tags on origin remote${RESET}? "
 read -e -p 'y/n [n]: ' input
 RESPONSE=${input:='n'}
 if [ "$RESPONSE" == 'y' ]; then
     echo
-    echo -e "Deleting ${BCYAN}${VERSION}${RESET} tag on remote..."
-    git push --delete origin $VERSION
+    echo -e "Deleting ${BCYAN}${VERSION}${RESET} tag on origin remote..."
+    git push origin :refs/tags/$VERSION
 
-    echo -e "Tagging ${BGREEN}HEAD${RESET} with ${BCYAN}${VERSION}${RESET} locally..."
+    echo -e "Tagging ${BGREEN}HEAD${RESET} with ${BCYAN}${VERSION}${RESET} on locally..."
     if ! git tag -fa $VERSION; then
         echo "Existing/invalid tag"
         exit -1
     fi
 
-    echo -e "Deleting ${BCYAN}${LATEST_TAG}${RESET} tag on remote..."
-    git push --delete origin $LATEST_TAG
+    echo -e "Deleting ${BCYAN}${LATEST_TAG}${RESET} tag on origin remote..."
+    git push origin :refs/tags/$LATEST_TAG
 
     echo -e "Tagging ${BGREEN}HEAD${RESET} with ${BCYAN}${LATEST_TAG}${RESET} locally..."
     git tag -fa $LATEST_TAG
 
-    echo -e "Pushing updated tags to remote..."
+    echo -e "Pushing updated tags to origin remote..."
     git push origin --tags
 fi
 exit 0

From 9fe579dd99d4cb1e1bf02be52999392b064eb008 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Sun, 24 Dec 2023 01:52:32 +1100
Subject: [PATCH 388/411] docs: update docs/RELEASE.md

---
 docs/RELEASE.md | 32 +++++++++-----------------------
 1 file changed, 9 insertions(+), 23 deletions(-)

diff --git a/docs/RELEASE.md b/docs/RELEASE.md
index caf8ba8799..d9909cb557 100644
--- a/docs/RELEASE.md
+++ b/docs/RELEASE.md
@@ -17,11 +17,7 @@ The `release.yml` workflow runs a number of jobs to handle code checks, tests, b
 
 It is triggered on **tag push**, when the tag matches `v*.*.*`. It doesn't matter if you've prepped a release branch like `release/v3.5.0` or are releasing from `main` - it works the same.
 
-!!! tip
-
-    Because commits are reference-counted, it is safe to create a release branch, tag it, let the workflow run, then delete the branch.
-
-    So long as the tag exists, that commit will exist.
+> Because commits are reference-counted, it is safe to create a release branch, tag it, let the workflow run, then delete the branch. So long as the tag exists, that commit will exist.
 
 ### Triggering the Workflow
 
@@ -45,9 +41,9 @@ This job checks that the git ref matches the app version. It matches the ref aga
 
 When the workflow is triggered by tag push, the ref is the tag. If the workflow is run manually, the ref is the target selected from the **Use workflow from** dropdown.
 
-!!! tip
+This job uses [samuelcolvin/check-python-version].
 
-    Any valid [version specifier] works, so long as the tag matches the version. The release workflow works exactly the same for `RC`, `post`, `dev`, etc.
+> Any valid [version specifier] works, so long as the tag matches the version. The release workflow works exactly the same for `RC`, `post`, `dev`, etc.
 
 #### Check and Test Jobs
 
@@ -57,13 +53,9 @@ This is our test suite.
 - **`check-python`**: runs `ruff` (format and lint)
 - **`check-frontend`**: runs `prettier` (format), `eslint` (lint), `madge` (circular refs) and `tsc` (static type check)
 
-!!! info Future Enhancement
+> **TODO** We should add `mypy` or `pyright` to the **`check-python`** job.
 
-    We should add `mypy` or `pyright` to the **`check-python`** job.
-
-!!! info Future Enhancement
-
-    We should add an end-to-end test job that generates an image.
+> **TODO** We should add an end-to-end test job that generates an image.
 
 #### `build` Job
 
@@ -78,9 +70,7 @@ At this point, the release workflow pauses (the remaining jobs all require appro
 
 A maintainer should go to the **Summary** tab of the workflow, download the installer and test it. Ensure the app loads and generates.
 
-!!! info
-
-    The exact same wheel file is bundled in the installer and in the `dist` artifact, which is uploaded to PyPI. You should end up with the same exact installation of the `invokeai` package from any of these methods.
+> The same wheel file is bundled in the installer and in the `dist` artifact, which is uploaded to PyPI. You should end up with the exactly the same installation of the `invokeai` package from any of these methods.
 
 #### PyPI Publish Jobs
 
@@ -94,9 +84,7 @@ Both jobs require a maintainer to approve them from the workflow's **Summary** t
 - Select the environment (either `testpypi` or `pypi`)
 - Click **Approve and deploy**
 
-!!! warning
-
-    **If the version already exists on PyPI, the publish jobs will fail.** PyPI only allows a particular version to be published once - you cannot change it. If version published on PyPI has a problem, you'll need to "fail forward" by bumping the app version and publishing a followup release.
+> **If the version already exists on PyPI, the publish jobs will fail.** PyPI only allows a given version to be published once - you cannot change it. If version published on PyPI has a problem, you'll need to "fail forward" by bumping the app version and publishing a followup release.
 
 #### `publish-testpypi` Job
 
@@ -126,14 +114,12 @@ Publishes the distribution on the production PyPI index, using the `pypi` GitHub
 
 1. [Draft a new release] on GitHub, choosing the tag that triggered the release.
 2. Write the release notes, describing important changes. The **Generate release notes** button automatically inserts the changelog and new contributors, and you can copy/paste the intro from previous releases.
-3. Upload the zip file created in [Build the installer] into the Assets section of the release notes. You can also upload the zip into the body of the release notes, since it can be hard for users to find the Assets section.
+3. Upload the zip file created in **`build`** job into the Assets section of the release notes. You can also upload the zip into the body of the release notes, since it can be hard for users to find the Assets section.
 4. Check the **Set as a pre-release** and **Create a discussion for this release** checkboxes at the bottom of the release page.
 5. Publish the pre-release.
 6. Announce the pre-release in Discord.
 
-!!! info Future Enhancement
-
-    Workflows can create a GitHub release from a template and upload release assets. One popular action to handle this is [ncipollo/release-action]. A future enhancement to the release process could set this up.
+> **TODO** Workflows can create a GitHub release from a template and upload release assets. One popular action to handle this is [ncipollo/release-action]. A future enhancement to the release process could set this up.
 
 ## Manually Running the Release Workflow
 

From b2b65a90126528bbd06bbd05f64345f845c4c88d Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 1 Jan 2024 10:41:34 +1100
Subject: [PATCH 389/411] feat(installer): address feedback

---
 installer/create_installer.sh | 22 +++++++++++++---------
 1 file changed, 13 insertions(+), 9 deletions(-)

diff --git a/installer/create_installer.sh b/installer/create_installer.sh
index 5f5d2adb74..2764ad7956 100755
--- a/installer/create_installer.sh
+++ b/installer/create_installer.sh
@@ -58,11 +58,12 @@ echo "Installing frontend dependencies..."
 echo
 pnpm i --frozen-lockfile
 echo
-echo "Building frontend..."
-if [[ -v CI ]]; then
+if [[ ! -z ${CI} ]]; then
+    echo "Building frontend without checks..."
     # In CI, we have already done the frontend checks and can just build
     pnpm vite build
 else
+    echo "Running checks and building frontend..."
     # This runs all the frontend checks and builds
     pnpm build
 fi
@@ -115,17 +116,20 @@ cp WinLongPathsEnabled.reg InvokeAI-Installer/
 FILENAME=InvokeAI-installer-$VERSION.zip
 
 # Zip everything up
-zip -r $FILENAME InvokeAI-Installer
+zip -r ${FILENAME} InvokeAI-Installer
 
-if [[ ! -v CI ]]; then
-    # clean up, but only if we are not in a github action
+# clean up, but only if we are not in a github action
+if [[ -z ${CI} ]]; then
+    echo
+    echo "Cleaning up frontend files..."
     rm -rf InvokeAI-Installer tmp dist ../invokeai/frontend/web/dist/
 fi
 
-if [[ -v CI ]]; then
-    # Set the output variable for github action
-    echo "INSTALLER_FILENAME=$FILENAME" >>$GITHUB_OUTPUT
-    echo "INSTALLER_PATH=installer/$FILENAME" >>$GITHUB_OUTPUT
+if [[ ! -z ${CI} ]]; then
+    echo
+    echo "Setting GitHub action outputs..."
+    echo "INSTALLER_FILENAME=${FILENAME}" >>$GITHUB_OUTPUT
+    echo "INSTALLER_PATH=installer/${FILENAME}" >>$GITHUB_OUTPUT
     echo "DIST_PATH=installer/dist/" >>$GITHUB_OUTPUT
 fi
 

From a8652776673248deffdae92e3c83b1da071f3a86 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 1 Jan 2024 10:52:57 +1100
Subject: [PATCH 390/411] ci: add comments to workflows

---
 .github/workflows/check-frontend.yml           | 4 ++++
 .github/workflows/check-pytest.yml             | 4 ++++
 .github/workflows/check-python.yml             | 6 ++++++
 .github/workflows/on-change-check-frontend.yml | 5 +++++
 .github/workflows/on-change-check-python.yml   | 5 +++++
 .github/workflows/on-change-pytest.yml         | 5 +++++
 6 files changed, 29 insertions(+)

diff --git a/.github/workflows/check-frontend.yml b/.github/workflows/check-frontend.yml
index 634ad84ee2..be2c3b0fde 100644
--- a/.github/workflows/check-frontend.yml
+++ b/.github/workflows/check-frontend.yml
@@ -1,3 +1,7 @@
+# This workflow runs the frontend code quality checks.
+#
+# It may be triggered via dispatch, or by another workflow.
+
 name: 'Check: frontend'
 
 on:
diff --git a/.github/workflows/check-pytest.yml b/.github/workflows/check-pytest.yml
index bdab6fc4d4..0839c1d5a4 100644
--- a/.github/workflows/check-pytest.yml
+++ b/.github/workflows/check-pytest.yml
@@ -1,3 +1,7 @@
+# This workflow runs pytest on the codebase in a matrix of platforms.
+#
+# It may be triggered via dispatch, or by another workflow.
+
 name: 'Check: pytest'
 
 on:
diff --git a/.github/workflows/check-python.yml b/.github/workflows/check-python.yml
index c58b4661c7..c37fb5683c 100644
--- a/.github/workflows/check-python.yml
+++ b/.github/workflows/check-python.yml
@@ -1,3 +1,9 @@
+# This workflow runs the python code quality checks.
+#
+# It may be triggered via dispatch, or by another workflow.
+#
+# TODO: Add mypy or pyright to the checks.
+
 name: 'Check: python'
 
 on:
diff --git a/.github/workflows/on-change-check-frontend.yml b/.github/workflows/on-change-check-frontend.yml
index 814f94ca5b..d134645e86 100644
--- a/.github/workflows/on-change-check-frontend.yml
+++ b/.github/workflows/on-change-check-frontend.yml
@@ -1,3 +1,8 @@
+# This workflow runs of `check-frontend.yml` on push or pull request.
+#
+# The actual checks are in a separate workflow to support simpler workflow
+# composition without awkward or complicated conditionals.
+
 name: 'On change: run check-frontend'
 
 on:
diff --git a/.github/workflows/on-change-check-python.yml b/.github/workflows/on-change-check-python.yml
index cc2be902b4..a7b56d8b13 100644
--- a/.github/workflows/on-change-check-python.yml
+++ b/.github/workflows/on-change-check-python.yml
@@ -1,3 +1,8 @@
+# This workflow runs of `check-python.yml` on push or pull request.
+#
+# The actual checks are in a separate workflow to support simpler workflow
+# composition without awkward or complicated conditionals.
+
 name: 'On change: run check-python'
 
 on:
diff --git a/.github/workflows/on-change-pytest.yml b/.github/workflows/on-change-pytest.yml
index 081d85d4fb..6f64ce878b 100644
--- a/.github/workflows/on-change-pytest.yml
+++ b/.github/workflows/on-change-pytest.yml
@@ -1,3 +1,8 @@
+# This workflow runs of `check-pytest.yml` on push or pull request.
+#
+# The actual checks are in a separate workflow to support simpler workflow
+# composition without awkward or complicated conditionals.
+
 name: 'On change: run pytest'
 
 on:

From b5c12985e7e9ca1752145707b2bcb12929c49e37 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 1 Jan 2024 10:57:24 +1100
Subject: [PATCH 391/411] docs: update RELEASE.md

---
 docs/RELEASE.md | 8 +++++---
 1 file changed, 5 insertions(+), 3 deletions(-)

diff --git a/docs/RELEASE.md b/docs/RELEASE.md
index d9909cb557..840e32c6e6 100644
--- a/docs/RELEASE.md
+++ b/docs/RELEASE.md
@@ -1,4 +1,4 @@
-# Release Workflow
+# Release Process
 
 The app is published in twice, in different build formats.
 
@@ -11,7 +11,7 @@ Make a developer call-out for PRs to merge. Merge and test things out.
 
 While the release workflow does not include end-to-end tests, it does pause before publishing so you can download and test the final build.
 
-## Workflow Overview
+## Release Workflow
 
 The `release.yml` workflow runs a number of jobs to handle code checks, tests, build and publish on PyPI.
 
@@ -110,7 +110,9 @@ rm -rf ~/.test-invokeai-dist
 
 Publishes the distribution on the production PyPI index, using the `pypi` GitHub environment.
 
-## Publish the GitHub RC with installer
+## Publish the GitHub Release with installer
+
+Once the release is published to PyPI, it's time to publish the GitHub release.
 
 1. [Draft a new release] on GitHub, choosing the tag that triggered the release.
 2. Write the release notes, describing important changes. The **Generate release notes** button automatically inserts the changelog and new contributors, and you can copy/paste the intro from previous releases.

From 50e58ff323965b7e2a00fa206f705ca95fdcc315 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 1 Jan 2024 11:05:39 +1100
Subject: [PATCH 392/411] feat(installer): just use python3 in scripts

---
 installer/create_installer.sh | 24 +++---------------------
 installer/tag_release.sh      | 14 +-------------
 2 files changed, 4 insertions(+), 34 deletions(-)

diff --git a/installer/create_installer.sh b/installer/create_installer.sh
index 2764ad7956..cd08c849e4 100755
--- a/installer/create_installer.sh
+++ b/installer/create_installer.sh
@@ -9,10 +9,6 @@ BRED="\033[1;31m"
 RED="\033[31m"
 RESET="\033[0m"
 
-function is_bin_in_path {
-    builtin type -P "$1" &>/dev/null
-}
-
 function git_show {
     git show -s --format=oneline --abbrev-commit "$1" | cat
 }
@@ -26,23 +22,9 @@ fi
 
 cd "$(dirname "$0")"
 
-echo
-echo -e "${BYELLOW}This script must be run from the installer directory!${RESET}"
-echo "The current working directory is $(pwd)"
-read -p "If that looks right, press any key to proceed, or CTRL-C to exit..."
-echo
-
-# Some machines only have `python3` in PATH, others have `python` - make an alias.
-# We can use a function to approximate an alias within a non-interactive shell.
-if ! is_bin_in_path python && is_bin_in_path python3; then
-    function python {
-        python3 "$@"
-    }
-fi
-
 VERSION=$(
     cd ..
-    python -c "from invokeai.version import __version__ as version; print(version)"
+    python3 -c "from invokeai.version import __version__ as version; print(version)"
 )
 VERSION="v${VERSION}"
 
@@ -78,13 +60,13 @@ echo
 
 # install the 'build' package in the user site packages, if needed
 # could be improved by using a temporary venv, but it's tiny and harmless
-if [[ $(python -c 'from importlib.util import find_spec; print(find_spec("build") is None)') == "True" ]]; then
+if [[ $(python3 -c 'from importlib.util import find_spec; print(find_spec("build") is None)') == "True" ]]; then
     pip install --user build
 fi
 
 rm -rf ../build
 
-python -m build --outdir dist/ ../.
+python3 -m build --outdir dist/ ../.
 
 # ----------------------
 
diff --git a/installer/tag_release.sh b/installer/tag_release.sh
index 2955bf5db5..9b1758aa32 100755
--- a/installer/tag_release.sh
+++ b/installer/tag_release.sh
@@ -9,10 +9,6 @@ BRED="\033[1;31m"
 RED="\033[31m"
 RESET="\033[0m"
 
-function is_bin_in_path {
-    builtin type -P "$1" &>/dev/null
-}
-
 function does_tag_exist {
     git rev-parse --quiet --verify "refs/tags/$1" >/dev/null
 }
@@ -25,17 +21,9 @@ function git_show {
     git show -s --format='%h %s' $1
 }
 
-# Some machines only have `python3` in PATH, others have `python` - make an alias.
-# We can use a function to approximate an alias within a non-interactive shell.
-if ! is_bin_in_path python && is_bin_in_path python3; then
-    function python {
-        python3 "$@"
-    }
-fi
-
 VERSION=$(
     cd ..
-    python -c "from invokeai.version import __version__ as version; print(version)"
+    python3 -c "from invokeai.version import __version__ as version; print(version)"
 )
 PATCH=""
 MAJOR_VERSION=$(echo $VERSION | sed 's/\..*$//')

From 99ee8f9099bcba1445daa02b65809b39b030ec0b Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 1 Jan 2024 11:18:40 +1100
Subject: [PATCH 393/411] feat(installer): remove vX-latest from tag_release

Also update RELEASE.md accordingly, and make the release.yml workflow match on `v*` tags.
---
 .github/workflows/release.yml |  2 +-
 docs/RELEASE.md               |  6 +-----
 installer/tag_release.sh      | 15 +--------------
 3 files changed, 3 insertions(+), 20 deletions(-)

diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml
index a0ee97f724..0f9ca098d5 100644
--- a/.github/workflows/release.yml
+++ b/.github/workflows/release.yml
@@ -3,7 +3,7 @@ name: Release
 on:
   push:
     tags:
-      - 'v*.*.*'
+      - 'v*'
   workflow_dispatch:
     inputs:
       skip_code_checks:
diff --git a/docs/RELEASE.md b/docs/RELEASE.md
index 840e32c6e6..3a0375b027 100644
--- a/docs/RELEASE.md
+++ b/docs/RELEASE.md
@@ -15,7 +15,7 @@ While the release workflow does not include end-to-end tests, it does pause befo
 
 The `release.yml` workflow runs a number of jobs to handle code checks, tests, build and publish on PyPI.
 
-It is triggered on **tag push**, when the tag matches `v*.*.*`. It doesn't matter if you've prepped a release branch like `release/v3.5.0` or are releasing from `main` - it works the same.
+It is triggered on **tag push**, when the tag matches `v*`. It doesn't matter if you've prepped a release branch like `release/v3.5.0` or are releasing from `main` - it works the same.
 
 > Because commits are reference-counted, it is safe to create a release branch, tag it, let the workflow run, then delete the branch. So long as the tag exists, that commit will exist.
 
@@ -23,10 +23,6 @@ It is triggered on **tag push**, when the tag matches `v*.*.*`. It doesn't matte
 
 Run `make tag-release` to tag the current commit and kick off the workflow.
 
-This script actually makes two tags - one for the specific version, and a `vX-latest` tag that changes with each release.
-
-Because the release workflow only triggers on the pattern `v*.*.*`, the workflow will only run once when running this script.
-
 The release may also be run [manually].
 
 ### Workflow Jobs and Process
diff --git a/installer/tag_release.sh b/installer/tag_release.sh
index 9b1758aa32..b6d1830902 100755
--- a/installer/tag_release.sh
+++ b/installer/tag_release.sh
@@ -26,20 +26,13 @@ VERSION=$(
     python3 -c "from invokeai.version import __version__ as version; print(version)"
 )
 PATCH=""
-MAJOR_VERSION=$(echo $VERSION | sed 's/\..*$//')
 VERSION="v${VERSION}${PATCH}"
-LATEST_TAG="v${MAJOR_VERSION}-latest"
 
 if does_tag_exist $VERSION; then
     echo -e "${BCYAN}${VERSION}${RESET} already exists:"
     git_show_ref tags/$VERSION
     echo
 fi
-if does_tag_exist $LATEST_TAG; then
-    echo -e "${BCYAN}${LATEST_TAG}${RESET} already exists:"
-    git_show_ref tags/$LATEST_TAG
-    echo
-fi
 
 echo -e "${BGREEN}HEAD${RESET}:"
 git_show
@@ -49,7 +42,7 @@ echo -e "${BGREEN}git remote -v${RESET}:"
 git remote -v
 echo
 
-echo -e -n "Create tags ${BCYAN}${VERSION}${RESET} and ${BCYAN}${LATEST_TAG}${RESET} @ ${BGREEN}HEAD${RESET}, ${RED}deleting existing tags on origin remote${RESET}? "
+echo -e -n "Create tags ${BCYAN}${VERSION}${RESET} @ ${BGREEN}HEAD${RESET}, ${RED}deleting existing tags on origin remote${RESET}? "
 read -e -p 'y/n [n]: ' input
 RESPONSE=${input:='n'}
 if [ "$RESPONSE" == 'y' ]; then
@@ -63,12 +56,6 @@ if [ "$RESPONSE" == 'y' ]; then
         exit -1
     fi
 
-    echo -e "Deleting ${BCYAN}${LATEST_TAG}${RESET} tag on origin remote..."
-    git push origin :refs/tags/$LATEST_TAG
-
-    echo -e "Tagging ${BGREEN}HEAD${RESET} with ${BCYAN}${LATEST_TAG}${RESET} locally..."
-    git tag -fa $LATEST_TAG
-
     echo -e "Pushing updated tags to origin remote..."
     git push origin --tags
 fi

From b95e5d073032fc074e8f3d6f2483311893f4207d Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Thu, 1 Feb 2024 10:48:59 +1100
Subject: [PATCH 394/411] ci: bump tj-actions/changed-files -> v41

---
 .github/workflows/on-change-check-frontend.yml | 2 +-
 .github/workflows/on-change-check-python.yml   | 2 +-
 .github/workflows/on-change-pytest.yml         | 2 +-
 3 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/.github/workflows/on-change-check-frontend.yml b/.github/workflows/on-change-check-frontend.yml
index d134645e86..5e8704ad71 100644
--- a/.github/workflows/on-change-check-frontend.yml
+++ b/.github/workflows/on-change-check-frontend.yml
@@ -27,7 +27,7 @@ jobs:
 
       - name: Check for changed frontend files
         id: changed-files
-        uses: tj-actions/changed-files@v40
+        uses: tj-actions/changed-files@v41
         with:
           files_yaml: |
             frontend:
diff --git a/.github/workflows/on-change-check-python.yml b/.github/workflows/on-change-check-python.yml
index a7b56d8b13..e73198b3fa 100644
--- a/.github/workflows/on-change-check-python.yml
+++ b/.github/workflows/on-change-check-python.yml
@@ -27,7 +27,7 @@ jobs:
 
       - name: Check for changed python files
         id: changed-files
-        uses: tj-actions/changed-files@v40
+        uses: tj-actions/changed-files@v41
         with:
           files_yaml: |
             python:
diff --git a/.github/workflows/on-change-pytest.yml b/.github/workflows/on-change-pytest.yml
index 6f64ce878b..0c174098bb 100644
--- a/.github/workflows/on-change-pytest.yml
+++ b/.github/workflows/on-change-pytest.yml
@@ -27,7 +27,7 @@ jobs:
 
       - name: Check for changed python files
         id: changed-files
-        uses: tj-actions/changed-files@v40
+        uses: tj-actions/changed-files@v41
         with:
           files_yaml: |
             python:

From ea4d0715034fb7afaa5a5c0f903cbaaf6efd986f Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Fri, 2 Feb 2024 09:20:09 +1100
Subject: [PATCH 395/411] ci: add reasonable timeouts for jobs

The timeouts are at least 3x the expected time to complete the jobs.

This is particularly relevant for the `pytest` job. Occasionally, it hangs while running tests that do network things, and the job only times out after 6 hours.
---
 .github/workflows/check-frontend.yml | 1 +
 .github/workflows/check-pytest.yml   | 1 +
 .github/workflows/check-python.yml   | 1 +
 3 files changed, 3 insertions(+)

diff --git a/.github/workflows/check-frontend.yml b/.github/workflows/check-frontend.yml
index be2c3b0fde..8134926556 100644
--- a/.github/workflows/check-frontend.yml
+++ b/.github/workflows/check-frontend.yml
@@ -15,6 +15,7 @@ defaults:
 jobs:
   check-frontend:
     runs-on: ubuntu-latest
+    timeout-minutes: 10 # expected run time: <2 min
     steps:
       - uses: actions/checkout@v4
 
diff --git a/.github/workflows/check-pytest.yml b/.github/workflows/check-pytest.yml
index 0839c1d5a4..89b0408f7e 100644
--- a/.github/workflows/check-pytest.yml
+++ b/.github/workflows/check-pytest.yml
@@ -44,6 +44,7 @@ jobs:
             github-env: $env:GITHUB_ENV
     name: ${{ matrix.pytorch }} on ${{ matrix.python-version }}
     runs-on: ${{ matrix.os }}
+    timeout-minutes: 30 # expected run time: <10 min, depending on platform
     env:
       PIP_USE_PEP517: '1'
     steps:
diff --git a/.github/workflows/check-python.yml b/.github/workflows/check-python.yml
index c37fb5683c..63a6c46b0a 100644
--- a/.github/workflows/check-python.yml
+++ b/.github/workflows/check-python.yml
@@ -13,6 +13,7 @@ on:
 jobs:
   check-backend:
     runs-on: ubuntu-latest
+    timeout-minutes: 5 # expected run time: <1 min
     steps:
       - uses: actions/checkout@v4
 

From 6f368395df91e1c53a1b27ae2df5bf88437429c6 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Fri, 9 Feb 2024 15:16:09 +1100
Subject: [PATCH 396/411] fix(installer): conditional syntax for old bash in
 create_installer.sh

---
 installer/create_installer.sh | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/installer/create_installer.sh b/installer/create_installer.sh
index cd08c849e4..868b7770e3 100755
--- a/installer/create_installer.sh
+++ b/installer/create_installer.sh
@@ -13,7 +13,7 @@ function git_show {
     git show -s --format=oneline --abbrev-commit "$1" | cat
 }
 
-if [[ -v "VIRTUAL_ENV" ]]; then
+if [[ ! -z "${VIRTUAL_ENV}" ]]; then
     # we can't just call 'deactivate' because this function is not exported
     # to the environment of this script from the bash process that runs the script
     echo -e "${BRED}A virtual environment is activated. Please deactivate it before proceeding.${RESET}"

From c60c9825cbbaa0fc82d008eab56d92073cb2c2f0 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Fri, 9 Feb 2024 15:22:37 +1100
Subject: [PATCH 397/411] feat(installer): add check for CI in
 create_installer.sh

If in CI, print a message saying so.

If not, prompt user to confirm that they are in the correct working directory.
---
 installer/create_installer.sh | 13 ++++++++++++-
 1 file changed, 12 insertions(+), 1 deletion(-)

diff --git a/installer/create_installer.sh b/installer/create_installer.sh
index 868b7770e3..5677bae5a3 100755
--- a/installer/create_installer.sh
+++ b/installer/create_installer.sh
@@ -28,6 +28,18 @@ VERSION=$(
 )
 VERSION="v${VERSION}"
 
+if [[ ! -z ${CI} ]]; then
+    echo
+    echo -e "${BCYAN}CI environment detected${RESET}"
+    echo
+else
+    echo
+    echo -e "${BYELLOW}This script must be run from the installer directory!${RESET}"
+    echo "The current working directory is $(pwd)"
+    read -p "If that looks right, press any key to proceed, or CTRL-C to exit..."
+    echo
+fi
+
 echo -e "${BGREEN}HEAD${RESET}:"
 git_show HEAD
 echo
@@ -35,7 +47,6 @@ echo
 # ---------------------- FRONTEND ----------------------
 
 pushd ../invokeai/frontend/web >/dev/null
-echo
 echo "Installing frontend dependencies..."
 echo
 pnpm i --frozen-lockfile

From 5f2e493244a9b9eb309e1a869aae04a33f51c253 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Fri, 9 Feb 2024 15:33:21 +1100
Subject: [PATCH 398/411] feat(installer): print outputs

---
 installer/create_installer.sh | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/installer/create_installer.sh b/installer/create_installer.sh
index 5677bae5a3..a606d54cef 100755
--- a/installer/create_installer.sh
+++ b/installer/create_installer.sh
@@ -111,6 +111,10 @@ FILENAME=InvokeAI-installer-$VERSION.zip
 # Zip everything up
 zip -r ${FILENAME} InvokeAI-Installer
 
+echo
+echo -e "${BGREEN}Built installer: ./${FILENAME}${RESET}"
+echo -e "${BGREEN}Built PyPi distribution: ./dist${RESET}"
+
 # clean up, but only if we are not in a github action
 if [[ -z ${CI} ]]; then
     echo

From be8dcad1da4bb90b367c044032b69cc6bc35540d Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Fri, 9 Feb 2024 15:33:29 +1100
Subject: [PATCH 399/411] feat(installer): do not delete dist/

---
 installer/create_installer.sh | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/installer/create_installer.sh b/installer/create_installer.sh
index a606d54cef..a71b0d9c41 100755
--- a/installer/create_installer.sh
+++ b/installer/create_installer.sh
@@ -118,8 +118,8 @@ echo -e "${BGREEN}Built PyPi distribution: ./dist${RESET}"
 # clean up, but only if we are not in a github action
 if [[ -z ${CI} ]]; then
     echo
-    echo "Cleaning up frontend files..."
-    rm -rf InvokeAI-Installer tmp dist ../invokeai/frontend/web/dist/
+    echo "Cleaning up intermediate build files..."
+    rm -rf InvokeAI-Installer tmp ../invokeai/frontend/web/dist/
 fi
 
 if [[ ! -z ${CI} ]]; then

From 6aae9408346b2c985ab930aaaac6fbdf2aff9cd3 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Fri, 1 Mar 2024 10:55:19 +1100
Subject: [PATCH 400/411] ci: clean up unused workflow

---
 .github/workflows/check-pytest.yml     | 36 --------------
 .github/workflows/pypi-release.yml.old | 67 --------------------------
 2 files changed, 103 deletions(-)
 delete mode 100644 .github/workflows/pypi-release.yml.old

diff --git a/.github/workflows/check-pytest.yml b/.github/workflows/check-pytest.yml
index 89b0408f7e..24349ccd2c 100644
--- a/.github/workflows/check-pytest.yml
+++ b/.github/workflows/check-pytest.yml
@@ -70,39 +70,3 @@ jobs:
       - name: run pytest
         id: run-pytest
         run: pytest
-
-      # - name: run invokeai-configure
-      #   env:
-      #     HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGINGFACE_TOKEN }}
-      #   run: >
-      #     invokeai-configure
-      #     --yes
-      #     --default_only
-      #     --full-precision
-      #   # can't use fp16 weights without a GPU
-
-      # - name: run invokeai
-      #   id: run-invokeai
-      #   env:
-      #     # Set offline mode to make sure configure preloaded successfully.
-      #     HF_HUB_OFFLINE: 1
-      #     HF_DATASETS_OFFLINE: 1
-      #     TRANSFORMERS_OFFLINE: 1
-      #     INVOKEAI_OUTDIR: ${{ github.workspace }}/results
-      #   run: >
-      #     invokeai
-      #     --no-patchmatch
-      #     --no-nsfw_checker
-      #     --precision=float32
-      #     --always_use_cpu
-      #     --use_memory_db
-      #     --outdir ${{ env.INVOKEAI_OUTDIR }}/${{ matrix.python-version }}/${{ matrix.pytorch }}
-      #     --from_file ${{ env.TEST_PROMPTS }}
-
-      # - name: Archive results
-      #   env:
-      #     INVOKEAI_OUTDIR: ${{ github.workspace }}/results
-      #   uses: actions/upload-artifact@v3
-      #   with:
-      #     name: results
-      #     path: ${{ env.INVOKEAI_OUTDIR }}
diff --git a/.github/workflows/pypi-release.yml.old b/.github/workflows/pypi-release.yml.old
deleted file mode 100644
index 162cbe3427..0000000000
--- a/.github/workflows/pypi-release.yml.old
+++ /dev/null
@@ -1,67 +0,0 @@
-name: PyPI Release
-
-on:
-  workflow_dispatch:
-    inputs:
-      publish_package:
-        description: 'Publish build on PyPi? [true/false]'
-        required: true
-        default: 'false'
-
-jobs:
-  build-and-release:
-    if: github.repository == 'invoke-ai/InvokeAI'
-    runs-on: ubuntu-22.04
-    env:
-      TWINE_USERNAME: __token__
-      TWINE_PASSWORD: ${{ secrets.PYPI_API_TOKEN }}
-      TWINE_NON_INTERACTIVE: 1
-    steps:
-      - name: Checkout
-        uses: actions/checkout@v4
-
-      - name: Setup Node 18
-        uses: actions/setup-node@v4
-        with:
-          node-version: '18'
-
-      - name: Setup pnpm
-        uses: pnpm/action-setup@v2
-        with:
-          version: '8.12.1'
-
-      - name: Install frontend dependencies
-        run: pnpm install --prefer-frozen-lockfile
-        working-directory: invokeai/frontend/web
-
-      - name: Build frontend
-        run: pnpm run build
-        working-directory: invokeai/frontend/web
-
-      - name: Install python dependencies
-        run: pip install --upgrade build twine
-
-      - name: Build python package
-        run: python3 -m build
-
-      - name: Upload build as workflow artifact
-        uses: actions/upload-artifact@v4
-        with:
-          name: dist
-          path: dist
-
-      - name: Check distribution
-        run: twine check dist/*
-
-      - name: Check PyPI versions
-        if: github.ref == 'refs/heads/main' || startsWith(github.ref, 'refs/heads/release/')
-        run: |
-          pip install --upgrade requests
-          python -c "\
-          import scripts.pypi_helper; \
-          EXISTS=scripts.pypi_helper.local_on_pypi(); \
-          print(f'PACKAGE_EXISTS={EXISTS}')" >> $GITHUB_ENV
-
-      - name: Publish build on PyPi
-        if: env.PACKAGE_EXISTS == 'False' && env.TWINE_PASSWORD != '' && github.event.inputs.publish_package == 'true'
-        run: twine upload dist/*

From 77f39aa9352d1bb77cd758b8dc74a3d82f533068 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Fri, 1 Mar 2024 11:31:02 +1100
Subject: [PATCH 401/411] ci: bump setup-python v4 -> v5

---
 .github/workflows/check-pytest.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/check-pytest.yml b/.github/workflows/check-pytest.yml
index 24349ccd2c..aedc0e59c3 100644
--- a/.github/workflows/check-pytest.yml
+++ b/.github/workflows/check-pytest.yml
@@ -54,7 +54,7 @@ jobs:
         run: echo "TEST_PROMPTS=tests/validate_pr_prompt.txt" >> ${{ matrix.github-env }}
 
       - name: setup python
-        uses: actions/setup-python@v4
+        uses: actions/setup-python@v5
         with:
           python-version: ${{ matrix.python-version }}
           cache: pip

From 26d4d93e64c1d170b013bc554968eb428f0c63fd Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Fri, 1 Mar 2024 11:35:54 +1100
Subject: [PATCH 402/411] ci: update mkdocs workflow

Bit of a merge of the docs at https://github.com/squidfunk/mkdocs-material/blob/master/docs/publishing-your-site.md and the previous workflow.

Not sure how to test this without access to the main repo.
---
 .github/workflows/mkdocs-material.yml | 53 ++++++++++-----------------
 1 file changed, 20 insertions(+), 33 deletions(-)

diff --git a/.github/workflows/mkdocs-material.yml b/.github/workflows/mkdocs-material.yml
index af634c4906..cbcfbf0835 100644
--- a/.github/workflows/mkdocs-material.yml
+++ b/.github/workflows/mkdocs-material.yml
@@ -1,51 +1,38 @@
-name: mkdocs-material
+# This is a mostly a copy-paste from https://github.com/squidfunk/mkdocs-material/blob/master/docs/publishing-your-site.md
+
+name: mkdocs
+
 on:
   push:
     branches:
-      - 'refs/heads/main'
+      - main
+  workflow_dispatch:
 
 permissions:
-    contents: write
+  contents: write
 
 jobs:
-  mkdocs-material:
+  deploy:
     if: github.event.pull_request.draft == false
     runs-on: ubuntu-latest
     env:
       REPO_URL: '${{ github.server_url }}/${{ github.repository }}'
       REPO_NAME: '${{ github.repository }}'
       SITE_URL: 'https://${{ github.repository_owner }}.github.io/InvokeAI'
-    steps:
-      - name: checkout sources
-        uses: actions/checkout@v3
-        with:
-          fetch-depth: 0
 
-      - name: setup python
-        uses: actions/setup-python@v4
+    steps:
+      - uses: actions/checkout@v4
+      - uses: actions/setup-python@v5
         with:
           python-version: '3.10'
           cache: pip
           cache-dependency-path: pyproject.toml
-
-      - name: install requirements
-        env:
-          PIP_USE_PEP517: 1
-        run: |
-          python -m \
-            pip install ".[docs]"
-
-      - name: confirm buildability
-        run: |
-          python -m \
-            mkdocs build \
-            --clean \
-            --verbose
-
-      - name: deploy to gh-pages
-        if: ${{ github.ref == 'refs/heads/main' }}
-        run: |
-          python -m \
-            mkdocs gh-deploy \
-            --clean \
-            --force
+      - run: echo "cache_id=$(date --utc '+%V')" >> $GITHUB_ENV
+      - uses: actions/cache@v4
+        with:
+          key: mkdocs-material-${{ env.cache_id }}
+          path: .cache
+          restore-keys: |
+            mkdocs-material-
+      - run: python -m pip install ".[docs]"
+      - run: mkdocs gh-deploy --force

From 0832e1818eefe3b9d7a8ac440ce539c6855d510e Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lstein@gmail.com>
Date: Thu, 29 Feb 2024 21:31:53 -0500
Subject: [PATCH 403/411] Fix problem of all installed models being assigned
 "<NOKEY>"

- Also fix redundant scanning of models directory at startup.
---
 .../app/services/model_install/model_install_default.py  | 9 +++++----
 invokeai/backend/model_manager/probe.py                  | 2 +-
 2 files changed, 6 insertions(+), 5 deletions(-)

diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py
index 93287a40c6..f522282fee 100644
--- a/invokeai/app/services/model_install/model_install_default.py
+++ b/invokeai/app/services/model_install/model_install_default.py
@@ -150,6 +150,7 @@ class ModelInstallService(ModelInstallServiceBase):
         config = config or {}
         if not config.get("source"):
             config["source"] = model_path.resolve().as_posix()
+        config["key"] = config.get("key", self._create_key())
 
         info: AnyModelConfig = self._probe_model(Path(model_path), config)
 
@@ -278,7 +279,7 @@ class ModelInstallService(ModelInstallServiceBase):
         self._logger.info("Model installer (re)initialized")
 
     def scan_directory(self, scan_dir: Path, install: bool = False) -> List[str]:  # noqa D102
-        self._cached_model_paths = {Path(x.path) for x in self.record_store.all_models()}
+        self._cached_model_paths = {Path(x.path).absolute() for x in self.record_store.all_models()}
         callback = self._scan_install if install else self._scan_register
         search = ModelSearch(on_model_found=callback, config=self._app_config)
         self._models_installed.clear()
@@ -531,9 +532,9 @@ class ModelInstallService(ModelInstallServiceBase):
     def _register(
         self, model_path: Path, config: Optional[Dict[str, Any]] = None, info: Optional[AnyModelConfig] = None
     ) -> str:
-        key = self._create_key()
-        if config and not config.get("key", None):
-            config["key"] = key
+        # Note that we may be passed a pre-populated AnyModelConfig object,
+        # in which case the key field should have been populated by the caller (e.g. in `install_path`).
+        config["key"] = config.get("key", self._create_key())
         info = info or ModelProbe.probe(model_path, config)
 
         model_path = model_path.absolute()
diff --git a/invokeai/backend/model_manager/probe.py b/invokeai/backend/model_manager/probe.py
index c33254ef4e..11b8f46951 100644
--- a/invokeai/backend/model_manager/probe.py
+++ b/invokeai/backend/model_manager/probe.py
@@ -188,7 +188,7 @@ class ModelProbe(object):
                 and fields["prediction_type"] == SchedulerPredictionType.VPrediction
             )
 
-        model_info = ModelConfigFactory.make_config(fields, key=fields.get("key", None))
+        model_info = ModelConfigFactory.make_config(fields)  # , key=fields.get("key", None))
         return model_info
 
     @classmethod

From 8fb297e5f6ca5f50fa46946b6353a04df9731001 Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lstein@gmail.com>
Date: Thu, 29 Feb 2024 21:37:40 -0500
Subject: [PATCH 404/411] add regression tests for <NOKEY> issue

---
 tests/app/services/model_install/test_model_install.py | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/tests/app/services/model_install/test_model_install.py b/tests/app/services/model_install/test_model_install.py
index 7e51e8deb3..00c463745c 100644
--- a/tests/app/services/model_install/test_model_install.py
+++ b/tests/app/services/model_install/test_model_install.py
@@ -31,6 +31,7 @@ def test_registration(mm2_installer: ModelInstallServiceBase, embedding_file: Pa
     assert len(matches) == 0
     key = mm2_installer.register_path(embedding_file)
     assert key is not None
+    assert key != "<NOKEY>"
     assert len(key) == 32
 
 
@@ -58,12 +59,13 @@ def test_registration_meta_override_fail(mm2_installer: ModelInstallServiceBase,
 def test_registration_meta_override_succeed(mm2_installer: ModelInstallServiceBase, embedding_file: Path) -> None:
     store = mm2_installer.record_store
     key = mm2_installer.register_path(
-        embedding_file, {"name": "banana_sushi", "source": "fake/repo_id", "current_hash": "New Hash"}
+        embedding_file, {"name": "banana_sushi", "source": "fake/repo_id", "current_hash": "New Hash", "key": "xyzzy"}
     )
     model_record = store.get_model(key)
     assert model_record.name == "banana_sushi"
     assert model_record.source == "fake/repo_id"
     assert model_record.current_hash == "New Hash"
+    assert model_record.key == "xyzzy"
 
 
 def test_install(
@@ -129,6 +131,7 @@ def test_background_install(
     model_record = mm2_installer.record_store.get_model(key)
     assert model_record is not None
     assert model_record.path == destination
+    assert model_record.key != "<NOKEY>"
     assert Path(mm2_app_config.models_dir / model_record.path).exists()
 
     # see if metadata was properly passed through

From 4a1acd4db9409b656ebd265088f557dfdc1991a2 Mon Sep 17 00:00:00 2001
From: Ryan Dick <ryanjdick3@gmail.com>
Date: Tue, 13 Feb 2024 17:50:20 -0500
Subject: [PATCH 405/411] Fix avoid storing extra conditioning info in two
 places.

---
 invokeai/app/invocations/latent.py                           | 2 --
 invokeai/backend/stable_diffusion/diffusers_pipeline.py      | 5 +++--
 .../backend/stable_diffusion/diffusion/conditioning_data.py  | 5 -----
 3 files changed, 3 insertions(+), 9 deletions(-)

diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py
index 97d3c705d4..9e9cb2d1c7 100644
--- a/invokeai/app/invocations/latent.py
+++ b/invokeai/app/invocations/latent.py
@@ -360,7 +360,6 @@ class DenoiseLatentsInvocation(BaseInvocation):
     ) -> ConditioningData:
         positive_cond_data = context.conditioning.load(self.positive_conditioning.conditioning_name)
         c = positive_cond_data.conditionings[0].to(device=unet.device, dtype=unet.dtype)
-        extra_conditioning_info = c.extra_conditioning
 
         negative_cond_data = context.conditioning.load(self.negative_conditioning.conditioning_name)
         uc = negative_cond_data.conditionings[0].to(device=unet.device, dtype=unet.dtype)
@@ -370,7 +369,6 @@ class DenoiseLatentsInvocation(BaseInvocation):
             text_embeddings=c,
             guidance_scale=self.cfg_scale,
             guidance_rescale_multiplier=self.cfg_rescale_multiplier,
-            extra=extra_conditioning_info,
             postprocessing_settings=PostprocessingSettings(
                 threshold=0.0,  # threshold,
                 warmup=0.2,  # warmup,
diff --git a/invokeai/backend/stable_diffusion/diffusers_pipeline.py b/invokeai/backend/stable_diffusion/diffusers_pipeline.py
index fd3ecde47b..918ca538a3 100644
--- a/invokeai/backend/stable_diffusion/diffusers_pipeline.py
+++ b/invokeai/backend/stable_diffusion/diffusers_pipeline.py
@@ -427,10 +427,11 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
             return latents, attention_map_saver
 
         ip_adapter_unet_patcher = None
-        if conditioning_data.extra is not None and conditioning_data.extra.wants_cross_attention_control:
+        extra_conditioning_info = conditioning_data.text_embeddings.extra_conditioning
+        if extra_conditioning_info is not None and extra_conditioning_info.wants_cross_attention_control:
             attn_ctx = self.invokeai_diffuser.custom_attention_context(
                 self.invokeai_diffuser.model,
-                extra_conditioning_info=conditioning_data.extra,
+                extra_conditioning_info=extra_conditioning_info,
                 step_count=len(self.scheduler.timesteps),
             )
             self.use_ip_adapter = False
diff --git a/invokeai/backend/stable_diffusion/diffusion/conditioning_data.py b/invokeai/backend/stable_diffusion/diffusion/conditioning_data.py
index 0676555f7a..b67669cefa 100644
--- a/invokeai/backend/stable_diffusion/diffusion/conditioning_data.py
+++ b/invokeai/backend/stable_diffusion/diffusion/conditioning_data.py
@@ -21,11 +21,7 @@ class ExtraConditioningInfo:
 @dataclass
 class BasicConditioningInfo:
     embeds: torch.Tensor
-    # TODO(ryand): Right now we awkwardly copy the extra conditioning info from here up to `ConditioningData`. This
-    # should only be stored in one place.
     extra_conditioning: Optional[ExtraConditioningInfo]
-    # weight: float
-    # mode: ConditioningAlgo
 
     def to(self, device, dtype=None):
         self.embeds = self.embeds.to(device=device, dtype=dtype)
@@ -83,7 +79,6 @@ class ConditioningData:
      ref [Common Diffusion Noise Schedules and Sample Steps are Flawed](https://arxiv.org/pdf/2305.08891.pdf)
     """
     guidance_rescale_multiplier: float = 0
-    extra: Optional[ExtraConditioningInfo] = None
     scheduler_args: dict[str, Any] = field(default_factory=dict)
     """
     Additional arguments to pass to invokeai_diffuser.do_latent_postprocessing().

From 7d9671014be0db1fed0220c3f0d331bd3f929df2 Mon Sep 17 00:00:00 2001
From: Ryan Dick <ryanjdick3@gmail.com>
Date: Wed, 14 Feb 2024 15:52:34 -0500
Subject: [PATCH 406/411] Remove use of **kwargs in do_unet_step(...), where
 full parameter list is known and supported.

---
 .../stable_diffusion/diffusers_pipeline.py    |  1 -
 .../diffusion/shared_invokeai_diffusion.py    | 60 +++++++++----------
 2 files changed, 30 insertions(+), 31 deletions(-)

diff --git a/invokeai/backend/stable_diffusion/diffusers_pipeline.py b/invokeai/backend/stable_diffusion/diffusers_pipeline.py
index 918ca538a3..d7f17fb744 100644
--- a/invokeai/backend/stable_diffusion/diffusers_pipeline.py
+++ b/invokeai/backend/stable_diffusion/diffusers_pipeline.py
@@ -598,7 +598,6 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
             step_index=step_index,
             total_step_count=total_step_count,
             conditioning_data=conditioning_data,
-            # extra:
             down_block_additional_residuals=down_block_additional_residuals,  # for ControlNet
             mid_block_additional_residual=mid_block_additional_residual,  # for ControlNet
             down_intrablock_additional_residuals=down_intrablock_additional_residuals,  # for T2I-Adapter
diff --git a/invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py b/invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py
index 455e5e1096..353256006a 100644
--- a/invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py
+++ b/invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py
@@ -224,10 +224,12 @@ class InvokeAIDiffuserComponent:
         self,
         sample: torch.Tensor,
         timestep: torch.Tensor,
-        conditioning_data,  # TODO: type
+        conditioning_data: ConditioningData,
         step_index: int,
         total_step_count: int,
-        **kwargs,
+        down_block_additional_residuals: Optional[torch.Tensor] = None,  # for ControlNet
+        mid_block_additional_residual: Optional[torch.Tensor] = None,  # for ControlNet
+        down_intrablock_additional_residuals: Optional[torch.Tensor] = None,  # for T2I-Adapter
     ):
         cross_attention_control_types_to_do = []
         context: Context = self.cross_attention_control_context
@@ -236,7 +238,6 @@ class InvokeAIDiffuserComponent:
             cross_attention_control_types_to_do = context.get_active_cross_attention_control_types_for_step(
                 percent_through
             )
-
         wants_cross_attention_control = len(cross_attention_control_types_to_do) > 0
 
         if wants_cross_attention_control:
@@ -244,31 +245,37 @@ class InvokeAIDiffuserComponent:
                 unconditioned_next_x,
                 conditioned_next_x,
             ) = self._apply_cross_attention_controlled_conditioning(
-                sample,
-                timestep,
-                conditioning_data,
-                cross_attention_control_types_to_do,
-                **kwargs,
+                x=sample,
+                sigma=timestep,
+                conditioning_data=conditioning_data,
+                cross_attention_control_types_to_do=cross_attention_control_types_to_do,
+                down_block_additional_residuals=down_block_additional_residuals,
+                mid_block_additional_residual=mid_block_additional_residual,
+                down_intrablock_additional_residuals=down_intrablock_additional_residuals,
             )
         elif self.sequential_guidance:
             (
                 unconditioned_next_x,
                 conditioned_next_x,
             ) = self._apply_standard_conditioning_sequentially(
-                sample,
-                timestep,
-                conditioning_data,
-                **kwargs,
+                x=sample,
+                sigma=timestep,
+                conditioning_data=conditioning_data,
+                down_block_additional_residuals=down_block_additional_residuals,
+                mid_block_additional_residual=mid_block_additional_residual,
+                down_intrablock_additional_residuals=down_intrablock_additional_residuals,
             )
         else:
             (
                 unconditioned_next_x,
                 conditioned_next_x,
             ) = self._apply_standard_conditioning(
-                sample,
-                timestep,
-                conditioning_data,
-                **kwargs,
+                x=sample,
+                sigma=timestep,
+                conditioning_data=conditioning_data,
+                down_block_additional_residuals=down_block_additional_residuals,
+                mid_block_additional_residual=mid_block_additional_residual,
+                down_intrablock_additional_residuals=down_intrablock_additional_residuals,
             )
 
         return unconditioned_next_x, conditioned_next_x
@@ -335,7 +342,7 @@ class InvokeAIDiffuserComponent:
 
     # methods below are called from do_diffusion_step and should be considered private to this class.
 
-    def _apply_standard_conditioning(self, x, sigma, conditioning_data: ConditioningData, **kwargs):
+    def _apply_standard_conditioning(self, x, sigma, conditioning_data: ConditioningData):
         """Runs the conditioned and unconditioned UNet forward passes in a single batch for faster inference speed at
         the cost of higher memory usage.
         """
@@ -384,7 +391,6 @@ class InvokeAIDiffuserComponent:
             cross_attention_kwargs=cross_attention_kwargs,
             encoder_attention_mask=encoder_attention_mask,
             added_cond_kwargs=added_cond_kwargs,
-            **kwargs,
         )
         unconditioned_next_x, conditioned_next_x = both_results.chunk(2)
         return unconditioned_next_x, conditioned_next_x
@@ -394,14 +400,15 @@ class InvokeAIDiffuserComponent:
         x: torch.Tensor,
         sigma,
         conditioning_data: ConditioningData,
-        **kwargs,
+        down_block_additional_residuals: Optional[torch.Tensor] = None,  # for ControlNet
+        mid_block_additional_residual: Optional[torch.Tensor] = None,  # for ControlNet
+        down_intrablock_additional_residuals: Optional[torch.Tensor] = None,  # for T2I-Adapter
     ):
         """Runs the conditioned and unconditioned UNet forward passes sequentially for lower memory usage at the cost of
         slower execution speed.
         """
         # low-memory sequential path
         uncond_down_block, cond_down_block = None, None
-        down_block_additional_residuals = kwargs.pop("down_block_additional_residuals", None)
         if down_block_additional_residuals is not None:
             uncond_down_block, cond_down_block = [], []
             for down_block in down_block_additional_residuals:
@@ -410,7 +417,6 @@ class InvokeAIDiffuserComponent:
                 cond_down_block.append(_cond_down)
 
         uncond_down_intrablock, cond_down_intrablock = None, None
-        down_intrablock_additional_residuals = kwargs.pop("down_intrablock_additional_residuals", None)
         if down_intrablock_additional_residuals is not None:
             uncond_down_intrablock, cond_down_intrablock = [], []
             for down_intrablock in down_intrablock_additional_residuals:
@@ -419,7 +425,6 @@ class InvokeAIDiffuserComponent:
                 cond_down_intrablock.append(_cond_down)
 
         uncond_mid_block, cond_mid_block = None, None
-        mid_block_additional_residual = kwargs.pop("mid_block_additional_residual", None)
         if mid_block_additional_residual is not None:
             uncond_mid_block, cond_mid_block = mid_block_additional_residual.chunk(2)
 
@@ -451,7 +456,6 @@ class InvokeAIDiffuserComponent:
             mid_block_additional_residual=uncond_mid_block,
             down_intrablock_additional_residuals=uncond_down_intrablock,
             added_cond_kwargs=added_cond_kwargs,
-            **kwargs,
         )
 
         # Run conditional UNet denoising.
@@ -481,7 +485,6 @@ class InvokeAIDiffuserComponent:
             mid_block_additional_residual=cond_mid_block,
             down_intrablock_additional_residuals=cond_down_intrablock,
             added_cond_kwargs=added_cond_kwargs,
-            **kwargs,
         )
         return unconditioned_next_x, conditioned_next_x
 
@@ -491,12 +494,13 @@ class InvokeAIDiffuserComponent:
         sigma,
         conditioning_data,
         cross_attention_control_types_to_do,
-        **kwargs,
+        down_block_additional_residuals: Optional[torch.Tensor] = None,  # for ControlNet
+        mid_block_additional_residual: Optional[torch.Tensor] = None,  # for ControlNet
+        down_intrablock_additional_residuals: Optional[torch.Tensor] = None,  # for T2I-Adapter
     ):
         context: Context = self.cross_attention_control_context
 
         uncond_down_block, cond_down_block = None, None
-        down_block_additional_residuals = kwargs.pop("down_block_additional_residuals", None)
         if down_block_additional_residuals is not None:
             uncond_down_block, cond_down_block = [], []
             for down_block in down_block_additional_residuals:
@@ -505,7 +509,6 @@ class InvokeAIDiffuserComponent:
                 cond_down_block.append(_cond_down)
 
         uncond_down_intrablock, cond_down_intrablock = None, None
-        down_intrablock_additional_residuals = kwargs.pop("down_intrablock_additional_residuals", None)
         if down_intrablock_additional_residuals is not None:
             uncond_down_intrablock, cond_down_intrablock = [], []
             for down_intrablock in down_intrablock_additional_residuals:
@@ -514,7 +517,6 @@ class InvokeAIDiffuserComponent:
                 cond_down_intrablock.append(_cond_down)
 
         uncond_mid_block, cond_mid_block = None, None
-        mid_block_additional_residual = kwargs.pop("mid_block_additional_residual", None)
         if mid_block_additional_residual is not None:
             uncond_mid_block, cond_mid_block = mid_block_additional_residual.chunk(2)
 
@@ -543,7 +545,6 @@ class InvokeAIDiffuserComponent:
             mid_block_additional_residual=uncond_mid_block,
             down_intrablock_additional_residuals=uncond_down_intrablock,
             added_cond_kwargs=added_cond_kwargs,
-            **kwargs,
         )
 
         if is_sdxl:
@@ -563,7 +564,6 @@ class InvokeAIDiffuserComponent:
             mid_block_additional_residual=cond_mid_block,
             down_intrablock_additional_residuals=cond_down_intrablock,
             added_cond_kwargs=added_cond_kwargs,
-            **kwargs,
         )
         return unconditioned_next_x, conditioned_next_x
 

From d87ff3a2062e799cc921fd30ef7b6cb644edcf5e Mon Sep 17 00:00:00 2001
From: Ryan Dick <ryanjdick3@gmail.com>
Date: Wed, 14 Feb 2024 16:00:11 -0500
Subject: [PATCH 407/411] Remove outdated comments related to T2I-Adapters and
 ControlNets.

---
 .../backend/stable_diffusion/diffusers_pipeline.py  | 13 ++++---------
 1 file changed, 4 insertions(+), 9 deletions(-)

diff --git a/invokeai/backend/stable_diffusion/diffusers_pipeline.py b/invokeai/backend/stable_diffusion/diffusers_pipeline.py
index d7f17fb744..538e0ea990 100644
--- a/invokeai/backend/stable_diffusion/diffusers_pipeline.py
+++ b/invokeai/backend/stable_diffusion/diffusers_pipeline.py
@@ -545,15 +545,9 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
                     # Otherwise, set the IP-Adapter's scale to 0, so it has no effect.
                     ip_adapter_unet_patcher.set_scale(i, 0.0)
 
-        # Handle ControlNet(s) and T2I-Adapter(s)
+        # Handle ControlNet(s)
         down_block_additional_residuals = None
         mid_block_additional_residual = None
-        down_intrablock_additional_residuals = None
-        # if control_data is not None and t2i_adapter_data is not None:
-        # TODO(ryand): This is a limitation of the UNet2DConditionModel API, not a fundamental incompatibility
-        # between ControlNets and T2I-Adapters. We will try to fix this upstream in diffusers.
-        #    raise Exception("ControlNet(s) and T2I-Adapter(s) cannot be used simultaneously (yet).")
-        # elif control_data is not None:
         if control_data is not None:
             down_block_additional_residuals, mid_block_additional_residual = self.invokeai_diffuser.do_controlnet_step(
                 control_data=control_data,
@@ -563,7 +557,9 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
                 total_step_count=total_step_count,
                 conditioning_data=conditioning_data,
             )
-        # elif t2i_adapter_data is not None:
+
+        # Handle T2I-Adapter(s)
+        down_intrablock_additional_residuals = None
         if t2i_adapter_data is not None:
             accum_adapter_state = None
             for single_t2i_adapter_data in t2i_adapter_data:
@@ -589,7 +585,6 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
                     for idx, value in enumerate(single_t2i_adapter_data.adapter_state):
                         accum_adapter_state[idx] += value * t2i_adapter_weight
 
-            # down_block_additional_residuals = accum_adapter_state
             down_intrablock_additional_residuals = accum_adapter_state
 
         uc_noise_pred, c_noise_pred = self.invokeai_diffuser.do_unet_step(

From 8721926f14131e9819abb4ddd867acf4892ce4f4 Mon Sep 17 00:00:00 2001
From: Ryan Dick <ryanjdick3@gmail.com>
Date: Wed, 14 Feb 2024 18:17:46 -0500
Subject: [PATCH 408/411] Merge sequential conditioning and cac conditioning
 logic to eliminate a bunch of duplication.

---
 .../diffusion/shared_invokeai_diffusion.py    | 159 +++++++-----------
 1 file changed, 59 insertions(+), 100 deletions(-)

diff --git a/invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py b/invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py
index 353256006a..2b72c808e4 100644
--- a/invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py
+++ b/invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py
@@ -232,28 +232,16 @@ class InvokeAIDiffuserComponent:
         down_intrablock_additional_residuals: Optional[torch.Tensor] = None,  # for T2I-Adapter
     ):
         cross_attention_control_types_to_do = []
-        context: Context = self.cross_attention_control_context
         if self.cross_attention_control_context is not None:
             percent_through = step_index / total_step_count
-            cross_attention_control_types_to_do = context.get_active_cross_attention_control_types_for_step(
-                percent_through
+            cross_attention_control_types_to_do = (
+                self.cross_attention_control_context.get_active_cross_attention_control_types_for_step(percent_through)
             )
         wants_cross_attention_control = len(cross_attention_control_types_to_do) > 0
 
-        if wants_cross_attention_control:
-            (
-                unconditioned_next_x,
-                conditioned_next_x,
-            ) = self._apply_cross_attention_controlled_conditioning(
-                x=sample,
-                sigma=timestep,
-                conditioning_data=conditioning_data,
-                cross_attention_control_types_to_do=cross_attention_control_types_to_do,
-                down_block_additional_residuals=down_block_additional_residuals,
-                mid_block_additional_residual=mid_block_additional_residual,
-                down_intrablock_additional_residuals=down_intrablock_additional_residuals,
-            )
-        elif self.sequential_guidance:
+        if wants_cross_attention_control or self.sequential_guidance:
+            # If wants_cross_attention_control is True, we force the sequential mode to be used, because cross-attention
+            # control is currently only supported in sequential mode.
             (
                 unconditioned_next_x,
                 conditioned_next_x,
@@ -261,6 +249,7 @@ class InvokeAIDiffuserComponent:
                 x=sample,
                 sigma=timestep,
                 conditioning_data=conditioning_data,
+                cross_attention_control_types_to_do=cross_attention_control_types_to_do,
                 down_block_additional_residuals=down_block_additional_residuals,
                 mid_block_additional_residual=mid_block_additional_residual,
                 down_intrablock_additional_residuals=down_intrablock_additional_residuals,
@@ -342,7 +331,15 @@ class InvokeAIDiffuserComponent:
 
     # methods below are called from do_diffusion_step and should be considered private to this class.
 
-    def _apply_standard_conditioning(self, x, sigma, conditioning_data: ConditioningData):
+    def _apply_standard_conditioning(
+        self,
+        x,
+        sigma,
+        conditioning_data: ConditioningData,
+        down_block_additional_residuals: Optional[torch.Tensor] = None,  # for ControlNet
+        mid_block_additional_residual: Optional[torch.Tensor] = None,  # for ControlNet
+        down_intrablock_additional_residuals: Optional[torch.Tensor] = None,  # for T2I-Adapter
+    ):
         """Runs the conditioned and unconditioned UNet forward passes in a single batch for faster inference speed at
         the cost of higher memory usage.
         """
@@ -390,6 +387,9 @@ class InvokeAIDiffuserComponent:
             both_conditionings,
             cross_attention_kwargs=cross_attention_kwargs,
             encoder_attention_mask=encoder_attention_mask,
+            down_block_additional_residuals=down_block_additional_residuals,
+            mid_block_additional_residual=mid_block_additional_residual,
+            down_intrablock_additional_residuals=down_intrablock_additional_residuals,
             added_cond_kwargs=added_cond_kwargs,
         )
         unconditioned_next_x, conditioned_next_x = both_results.chunk(2)
@@ -400,6 +400,7 @@ class InvokeAIDiffuserComponent:
         x: torch.Tensor,
         sigma,
         conditioning_data: ConditioningData,
+        cross_attention_control_types_to_do: list[CrossAttentionType],
         down_block_additional_residuals: Optional[torch.Tensor] = None,  # for ControlNet
         mid_block_additional_residual: Optional[torch.Tensor] = None,  # for ControlNet
         down_intrablock_additional_residuals: Optional[torch.Tensor] = None,  # for T2I-Adapter
@@ -407,7 +408,8 @@ class InvokeAIDiffuserComponent:
         """Runs the conditioned and unconditioned UNet forward passes sequentially for lower memory usage at the cost of
         slower execution speed.
         """
-        # low-memory sequential path
+        # Since we are running the conditioned and unconditioned passes sequentially, we need to split the ControlNet
+        # and T2I-Adapter residuals into two chunks.
         uncond_down_block, cond_down_block = None, None
         if down_block_additional_residuals is not None:
             uncond_down_block, cond_down_block = [], []
@@ -428,8 +430,26 @@ class InvokeAIDiffuserComponent:
         if mid_block_additional_residual is not None:
             uncond_mid_block, cond_mid_block = mid_block_additional_residual.chunk(2)
 
-        # Run unconditional UNet denoising.
+        # If cross-attention control is enabled, prepare the SwapCrossAttnContext.
+        cross_attn_processor_context = None
+        if self.cross_attention_control_context is not None:
+            # Note that the SwapCrossAttnContext is initialized with an empty list of cross_attention_types_to_do.
+            # This list is empty because cross-attention control is not applied in the unconditioned pass. This field
+            # will be populated before the conditioned pass.
+            cross_attn_processor_context = SwapCrossAttnContext(
+                modified_text_embeddings=self.cross_attention_control_context.arguments.edited_conditioning,
+                index_map=self.cross_attention_control_context.cross_attention_index_map,
+                mask=self.cross_attention_control_context.cross_attention_mask,
+                cross_attention_types_to_do=[],
+            )
+
+        #####################
+        # Unconditioned pass
+        #####################
+
         cross_attention_kwargs = None
+
+        # Prepare IP-Adapter cross-attention kwargs for the unconditioned pass.
         if conditioning_data.ip_adapter_conditioning is not None:
             # Note that we 'unsqueeze' to produce tensors of shape (batch_size=1, num_ip_images, seq_len, token_len).
             cross_attention_kwargs = {
@@ -439,6 +459,11 @@ class InvokeAIDiffuserComponent:
                 ]
             }
 
+        # Prepare cross-attention control kwargs for the unconditioned pass.
+        if cross_attn_processor_context is not None:
+            cross_attention_kwargs = {"swap_cross_attn_context": cross_attn_processor_context}
+
+        # Prepare SDXL conditioning kwargs for the unconditioned pass.
         added_cond_kwargs = None
         is_sdxl = type(conditioning_data.text_embeddings) is SDXLConditioningInfo
         if is_sdxl:
@@ -447,6 +472,7 @@ class InvokeAIDiffuserComponent:
                 "time_ids": conditioning_data.unconditioned_embeddings.add_time_ids,
             }
 
+        # Run unconditioned UNet denoising (i.e. negative prompt).
         unconditioned_next_x = self.model_forward_callback(
             x,
             sigma,
@@ -458,8 +484,13 @@ class InvokeAIDiffuserComponent:
             added_cond_kwargs=added_cond_kwargs,
         )
 
-        # Run conditional UNet denoising.
+        ###################
+        # Conditioned pass
+        ###################
+
         cross_attention_kwargs = None
+
+        # Prepare IP-Adapter cross-attention kwargs for the conditioned pass.
         if conditioning_data.ip_adapter_conditioning is not None:
             # Note that we 'unsqueeze' to produce tensors of shape (batch_size=1, num_ip_images, seq_len, token_len).
             cross_attention_kwargs = {
@@ -469,6 +500,12 @@ class InvokeAIDiffuserComponent:
                 ]
             }
 
+        # Prepare cross-attention control kwargs for the conditioned pass.
+        if cross_attn_processor_context is not None:
+            cross_attn_processor_context.cross_attention_types_to_do = cross_attention_control_types_to_do
+            cross_attention_kwargs = {"swap_cross_attn_context": cross_attn_processor_context}
+
+        # Prepare SDXL conditioning kwargs for the conditioned pass.
         added_cond_kwargs = None
         if is_sdxl:
             added_cond_kwargs = {
@@ -476,6 +513,7 @@ class InvokeAIDiffuserComponent:
                 "time_ids": conditioning_data.text_embeddings.add_time_ids,
             }
 
+        # Run conditioned UNet denoising (i.e. positive prompt).
         conditioned_next_x = self.model_forward_callback(
             x,
             sigma,
@@ -488,85 +526,6 @@ class InvokeAIDiffuserComponent:
         )
         return unconditioned_next_x, conditioned_next_x
 
-    def _apply_cross_attention_controlled_conditioning(
-        self,
-        x: torch.Tensor,
-        sigma,
-        conditioning_data,
-        cross_attention_control_types_to_do,
-        down_block_additional_residuals: Optional[torch.Tensor] = None,  # for ControlNet
-        mid_block_additional_residual: Optional[torch.Tensor] = None,  # for ControlNet
-        down_intrablock_additional_residuals: Optional[torch.Tensor] = None,  # for T2I-Adapter
-    ):
-        context: Context = self.cross_attention_control_context
-
-        uncond_down_block, cond_down_block = None, None
-        if down_block_additional_residuals is not None:
-            uncond_down_block, cond_down_block = [], []
-            for down_block in down_block_additional_residuals:
-                _uncond_down, _cond_down = down_block.chunk(2)
-                uncond_down_block.append(_uncond_down)
-                cond_down_block.append(_cond_down)
-
-        uncond_down_intrablock, cond_down_intrablock = None, None
-        if down_intrablock_additional_residuals is not None:
-            uncond_down_intrablock, cond_down_intrablock = [], []
-            for down_intrablock in down_intrablock_additional_residuals:
-                _uncond_down, _cond_down = down_intrablock.chunk(2)
-                uncond_down_intrablock.append(_uncond_down)
-                cond_down_intrablock.append(_cond_down)
-
-        uncond_mid_block, cond_mid_block = None, None
-        if mid_block_additional_residual is not None:
-            uncond_mid_block, cond_mid_block = mid_block_additional_residual.chunk(2)
-
-        cross_attn_processor_context = SwapCrossAttnContext(
-            modified_text_embeddings=context.arguments.edited_conditioning,
-            index_map=context.cross_attention_index_map,
-            mask=context.cross_attention_mask,
-            cross_attention_types_to_do=[],
-        )
-
-        added_cond_kwargs = None
-        is_sdxl = type(conditioning_data.text_embeddings) is SDXLConditioningInfo
-        if is_sdxl:
-            added_cond_kwargs = {
-                "text_embeds": conditioning_data.unconditioned_embeddings.pooled_embeds,
-                "time_ids": conditioning_data.unconditioned_embeddings.add_time_ids,
-            }
-
-        # no cross attention for unconditioning (negative prompt)
-        unconditioned_next_x = self.model_forward_callback(
-            x,
-            sigma,
-            conditioning_data.unconditioned_embeddings.embeds,
-            {"swap_cross_attn_context": cross_attn_processor_context},
-            down_block_additional_residuals=uncond_down_block,
-            mid_block_additional_residual=uncond_mid_block,
-            down_intrablock_additional_residuals=uncond_down_intrablock,
-            added_cond_kwargs=added_cond_kwargs,
-        )
-
-        if is_sdxl:
-            added_cond_kwargs = {
-                "text_embeds": conditioning_data.text_embeddings.pooled_embeds,
-                "time_ids": conditioning_data.text_embeddings.add_time_ids,
-            }
-
-        # do requested cross attention types for conditioning (positive prompt)
-        cross_attn_processor_context.cross_attention_types_to_do = cross_attention_control_types_to_do
-        conditioned_next_x = self.model_forward_callback(
-            x,
-            sigma,
-            conditioning_data.text_embeddings.embeds,
-            {"swap_cross_attn_context": cross_attn_processor_context},
-            down_block_additional_residuals=cond_down_block,
-            mid_block_additional_residual=cond_mid_block,
-            down_intrablock_additional_residuals=cond_down_intrablock,
-            added_cond_kwargs=added_cond_kwargs,
-        )
-        return unconditioned_next_x, conditioned_next_x
-
     def _combine(self, unconditioned_next_x, conditioned_next_x, guidance_scale):
         # to scale how much effect conditioning has, calculate the changes it does and then scale that
         scaled_delta = (conditioned_next_x - unconditioned_next_x) * guidance_scale

From 3e14bd6c45026b22a52c889b7855559abcec9271 Mon Sep 17 00:00:00 2001
From: Ryan Dick <ryanjdick3@gmail.com>
Date: Wed, 14 Feb 2024 18:18:58 -0500
Subject: [PATCH 409/411] Remove unused constructor declared with typo in name:
 __int__.

---
 .../diffusion/cross_attention_control.py             | 12 ------------
 1 file changed, 12 deletions(-)

diff --git a/invokeai/backend/stable_diffusion/diffusion/cross_attention_control.py b/invokeai/backend/stable_diffusion/diffusion/cross_attention_control.py
index 1741440bc2..2bbee87f09 100644
--- a/invokeai/backend/stable_diffusion/diffusion/cross_attention_control.py
+++ b/invokeai/backend/stable_diffusion/diffusion/cross_attention_control.py
@@ -533,18 +533,6 @@ class SwapCrossAttnContext:
     mask: torch.Tensor  # in the target space of the index_map
     cross_attention_types_to_do: list[CrossAttentionType] = field(default_factory=list)
 
-    def __int__(
-        self,
-        cac_types_to_do: [CrossAttentionType],
-        modified_text_embeddings: torch.Tensor,
-        index_map: torch.Tensor,
-        mask: torch.Tensor,
-    ):
-        self.cross_attention_types_to_do = cac_types_to_do
-        self.modified_text_embeddings = modified_text_embeddings
-        self.index_map = index_map
-        self.mask = mask
-
     def wants_cross_attention_control(self, attn_type: CrossAttentionType) -> bool:
         return attn_type in self.cross_attention_types_to_do
 

From a5c94fba438e33dcbfc81496fc38d9b588f4ff77 Mon Sep 17 00:00:00 2001
From: Ryan Dick <ryanjdick3@gmail.com>
Date: Thu, 15 Feb 2024 17:22:37 -0500
Subject: [PATCH 410/411] Delete unused functions from
 shared_invokeai_diffusion.py.

---
 .../diffusion/shared_invokeai_diffusion.py    | 51 -------------------
 1 file changed, 51 deletions(-)

diff --git a/invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py b/invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py
index 2b72c808e4..c6b85d2bd6 100644
--- a/invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py
+++ b/invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py
@@ -592,54 +592,3 @@ class InvokeAIDiffuserComponent:
 
         self.last_percent_through = percent_through
         return latents.to(device=dev)
-
-    # todo: make this work
-    @classmethod
-    def apply_conjunction(cls, x, t, forward_func, uc, c_or_weighted_c_list, global_guidance_scale):
-        x_in = torch.cat([x] * 2)
-        t_in = torch.cat([t] * 2)  # aka sigmas
-
-        deltas = None
-        uncond_latents = None
-        weighted_cond_list = (
-            c_or_weighted_c_list if isinstance(c_or_weighted_c_list, list) else [(c_or_weighted_c_list, 1)]
-        )
-
-        # below is fugly omg
-        conditionings = [uc] + [c for c, weight in weighted_cond_list]
-        weights = [1] + [weight for c, weight in weighted_cond_list]
-        chunk_count = math.ceil(len(conditionings) / 2)
-        deltas = None
-        for chunk_index in range(chunk_count):
-            offset = chunk_index * 2
-            chunk_size = min(2, len(conditionings) - offset)
-
-            if chunk_size == 1:
-                c_in = conditionings[offset]
-                latents_a = forward_func(x_in[:-1], t_in[:-1], c_in)
-                latents_b = None
-            else:
-                c_in = torch.cat(conditionings[offset : offset + 2])
-                latents_a, latents_b = forward_func(x_in, t_in, c_in).chunk(2)
-
-            # first chunk is guaranteed to be 2 entries: uncond_latents + first conditioining
-            if chunk_index == 0:
-                uncond_latents = latents_a
-                deltas = latents_b - uncond_latents
-            else:
-                deltas = torch.cat((deltas, latents_a - uncond_latents))
-                if latents_b is not None:
-                    deltas = torch.cat((deltas, latents_b - uncond_latents))
-
-        # merge the weighted deltas together into a single merged delta
-        per_delta_weights = torch.tensor(weights[1:], dtype=deltas.dtype, device=deltas.device)
-        normalize = False
-        if normalize:
-            per_delta_weights /= torch.sum(per_delta_weights)
-        reshaped_weights = per_delta_weights.reshape(per_delta_weights.shape + (1, 1, 1))
-        deltas_merged = torch.sum(deltas * reshaped_weights, dim=0, keepdim=True)
-
-        # old_return_value = super().forward(x, sigma, uncond, cond, cond_scale)
-        # assert(0 == len(torch.nonzero(old_return_value - (uncond_latents + deltas_merged * cond_scale))))
-
-        return uncond_latents + deltas_merged * global_guidance_scale

From 5b3adf0740599d7b43880dbe4fae871a74d86c66 Mon Sep 17 00:00:00 2001
From: Ryan Dick <ryanjdick3@gmail.com>
Date: Thu, 15 Feb 2024 17:28:55 -0500
Subject: [PATCH 411/411] Remove unused code for attention map saving.

---
 invokeai/app/invocations/latent.py            |   5 +-
 invokeai/backend/stable_diffusion/__init__.py |   2 -
 .../stable_diffusion/diffusers_pipeline.py    |  41 +-
 .../stable_diffusion/diffusion/__init__.py    |   2 -
 .../diffusion/cross_attention_control.py      | 453 +-----------------
 .../diffusion/cross_attention_map_saving.py   | 100 ----
 .../diffusion/shared_invokeai_diffusion.py    |  29 +-
 7 files changed, 18 insertions(+), 614 deletions(-)
 delete mode 100644 invokeai/backend/stable_diffusion/diffusion/cross_attention_map_saving.py

diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py
index 9e9cb2d1c7..d9125f0f37 100644
--- a/invokeai/app/invocations/latent.py
+++ b/invokeai/app/invocations/latent.py
@@ -775,10 +775,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
                     denoising_end=self.denoising_end,
                 )
 
-                (
-                    result_latents,
-                    result_attention_map_saver,
-                ) = pipeline.latents_from_embeddings(
+                result_latents = pipeline.latents_from_embeddings(
                     latents=latents,
                     timesteps=timesteps,
                     init_timestep=init_timestep,
diff --git a/invokeai/backend/stable_diffusion/__init__.py b/invokeai/backend/stable_diffusion/__init__.py
index 8b3f701064..ed6782eefa 100644
--- a/invokeai/backend/stable_diffusion/__init__.py
+++ b/invokeai/backend/stable_diffusion/__init__.py
@@ -4,13 +4,11 @@ Initialization file for the invokeai.backend.stable_diffusion package
 
 from .diffusers_pipeline import PipelineIntermediateState, StableDiffusionGeneratorPipeline  # noqa: F401
 from .diffusion import InvokeAIDiffuserComponent  # noqa: F401
-from .diffusion.cross_attention_map_saving import AttentionMapSaver  # noqa: F401
 from .seamless import set_seamless  # noqa: F401
 
 __all__ = [
     "PipelineIntermediateState",
     "StableDiffusionGeneratorPipeline",
     "InvokeAIDiffuserComponent",
-    "AttentionMapSaver",
     "set_seamless",
 ]
diff --git a/invokeai/backend/stable_diffusion/diffusers_pipeline.py b/invokeai/backend/stable_diffusion/diffusers_pipeline.py
index 538e0ea990..9a08787878 100644
--- a/invokeai/backend/stable_diffusion/diffusers_pipeline.py
+++ b/invokeai/backend/stable_diffusion/diffusers_pipeline.py
@@ -12,7 +12,6 @@ import torch
 import torchvision.transforms as T
 from diffusers.models import AutoencoderKL, UNet2DConditionModel
 from diffusers.models.controlnet import ControlNetModel
-from diffusers.pipelines.stable_diffusion import StableDiffusionPipelineOutput
 from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion import StableDiffusionPipeline
 from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
 from diffusers.schedulers import KarrasDiffusionSchedulers
@@ -26,9 +25,9 @@ from invokeai.app.services.config import InvokeAIAppConfig
 from invokeai.backend.ip_adapter.ip_adapter import IPAdapter
 from invokeai.backend.ip_adapter.unet_patcher import UNetPatcher
 from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ConditioningData
+from invokeai.backend.stable_diffusion.diffusion.shared_invokeai_diffusion import InvokeAIDiffuserComponent
 
 from ..util import auto_detect_slice_size, normalize_device
-from .diffusion import AttentionMapSaver, InvokeAIDiffuserComponent
 
 
 @dataclass
@@ -39,7 +38,6 @@ class PipelineIntermediateState:
     timestep: int
     latents: torch.Tensor
     predicted_original: Optional[torch.Tensor] = None
-    attention_map_saver: Optional[AttentionMapSaver] = None
 
 
 @dataclass
@@ -190,19 +188,6 @@ class T2IAdapterData:
     end_step_percent: float = Field(default=1.0)
 
 
-@dataclass
-class InvokeAIStableDiffusionPipelineOutput(StableDiffusionPipelineOutput):
-    r"""
-    Output class for InvokeAI's Stable Diffusion pipeline.
-
-    Args:
-        attention_map_saver (`AttentionMapSaver`): Object containing attention maps that can be displayed to the user
-         after generation completes. Optional.
-    """
-
-    attention_map_saver: Optional[AttentionMapSaver]
-
-
 class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
     r"""
     Pipeline for text-to-image generation using Stable Diffusion.
@@ -343,9 +328,9 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
         masked_latents: Optional[torch.Tensor] = None,
         gradient_mask: Optional[bool] = False,
         seed: Optional[int] = None,
-    ) -> tuple[torch.Tensor, Optional[AttentionMapSaver]]:
+    ) -> torch.Tensor:
         if init_timestep.shape[0] == 0:
-            return latents, None
+            return latents
 
         if additional_guidance is None:
             additional_guidance = []
@@ -385,7 +370,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
                 additional_guidance.append(AddsMaskGuidance(mask, orig_latents, self.scheduler, noise, gradient_mask))
 
         try:
-            latents, attention_map_saver = self.generate_latents_from_embeddings(
+            latents = self.generate_latents_from_embeddings(
                 latents,
                 timesteps,
                 conditioning_data,
@@ -402,7 +387,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
         if mask is not None and not gradient_mask:
             latents = torch.lerp(orig_latents, latents.to(dtype=orig_latents.dtype), mask.to(dtype=orig_latents.dtype))
 
-        return latents, attention_map_saver
+        return latents
 
     def generate_latents_from_embeddings(
         self,
@@ -415,16 +400,15 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
         ip_adapter_data: Optional[list[IPAdapterData]] = None,
         t2i_adapter_data: Optional[list[T2IAdapterData]] = None,
         callback: Callable[[PipelineIntermediateState], None] = None,
-    ):
+    ) -> torch.Tensor:
         self._adjust_memory_efficient_attention(latents)
         if additional_guidance is None:
             additional_guidance = []
 
         batch_size = latents.shape[0]
-        attention_map_saver: Optional[AttentionMapSaver] = None
 
         if timesteps.shape[0] == 0:
-            return latents, attention_map_saver
+            return latents
 
         ip_adapter_unet_patcher = None
         extra_conditioning_info = conditioning_data.text_embeddings.extra_conditioning
@@ -432,7 +416,6 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
             attn_ctx = self.invokeai_diffuser.custom_attention_context(
                 self.invokeai_diffuser.model,
                 extra_conditioning_info=extra_conditioning_info,
-                step_count=len(self.scheduler.timesteps),
             )
             self.use_ip_adapter = False
         elif ip_adapter_data is not None:
@@ -483,13 +466,6 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
 
                 predicted_original = getattr(step_output, "pred_original_sample", None)
 
-                # TODO resuscitate attention map saving
-                # if i == len(timesteps)-1 and extra_conditioning_info is not None:
-                #    eos_token_index = extra_conditioning_info.tokens_count_including_eos_bos - 1
-                #    attention_map_token_ids = range(1, eos_token_index)
-                #    attention_map_saver = AttentionMapSaver(token_ids=attention_map_token_ids, latents_shape=latents.shape[-2:])
-                #    self.invokeai_diffuser.setup_attention_map_saving(attention_map_saver)
-
                 if callback is not None:
                     callback(
                         PipelineIntermediateState(
@@ -499,11 +475,10 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
                             timestep=int(t),
                             latents=latents,
                             predicted_original=predicted_original,
-                            attention_map_saver=attention_map_saver,
                         )
                     )
 
-            return latents, attention_map_saver
+            return latents
 
     @torch.inference_mode()
     def step(
diff --git a/invokeai/backend/stable_diffusion/diffusion/__init__.py b/invokeai/backend/stable_diffusion/diffusion/__init__.py
index e68340168a..854d127a36 100644
--- a/invokeai/backend/stable_diffusion/diffusion/__init__.py
+++ b/invokeai/backend/stable_diffusion/diffusion/__init__.py
@@ -2,6 +2,4 @@
 Initialization file for invokeai.models.diffusion
 """
 
-from .cross_attention_control import InvokeAICrossAttentionMixin  # noqa: F401
-from .cross_attention_map_saving import AttentionMapSaver  # noqa: F401
 from .shared_invokeai_diffusion import InvokeAIDiffuserComponent  # noqa: F401
diff --git a/invokeai/backend/stable_diffusion/diffusion/cross_attention_control.py b/invokeai/backend/stable_diffusion/diffusion/cross_attention_control.py
index 2bbee87f09..4278f08bff 100644
--- a/invokeai/backend/stable_diffusion/diffusion/cross_attention_control.py
+++ b/invokeai/backend/stable_diffusion/diffusion/cross_attention_control.py
@@ -3,19 +3,13 @@
 
 
 import enum
-import math
 from dataclasses import dataclass, field
-from typing import Callable, Optional
+from typing import Optional
 
-import diffusers
-import psutil
 import torch
 from compel.cross_attention_control import Arguments
-from diffusers.models.attention_processor import Attention, AttentionProcessor, AttnProcessor, SlicedAttnProcessor
+from diffusers.models.attention_processor import Attention, SlicedAttnProcessor
 from diffusers.models.unets.unet_2d_condition import UNet2DConditionModel
-from torch import nn
-
-import invokeai.backend.util.logging as logger
 
 from ...util import torch_dtype
 
@@ -25,72 +19,14 @@ class CrossAttentionType(enum.Enum):
     TOKENS = 2
 
 
-class Context:
-    cross_attention_mask: Optional[torch.Tensor]
-    cross_attention_index_map: Optional[torch.Tensor]
-
-    class Action(enum.Enum):
-        NONE = 0
-        SAVE = (1,)
-        APPLY = 2
-
-    def __init__(self, arguments: Arguments, step_count: int):
+class CrossAttnControlContext:
+    def __init__(self, arguments: Arguments):
         """
         :param arguments: Arguments for the cross-attention control process
-        :param step_count: The absolute total number of steps of diffusion (for img2img this is likely larger than the number of steps that will actually run)
         """
-        self.cross_attention_mask = None
-        self.cross_attention_index_map = None
-        self.self_cross_attention_action = Context.Action.NONE
-        self.tokens_cross_attention_action = Context.Action.NONE
+        self.cross_attention_mask: Optional[torch.Tensor] = None
+        self.cross_attention_index_map: Optional[torch.Tensor] = None
         self.arguments = arguments
-        self.step_count = step_count
-
-        self.self_cross_attention_module_identifiers = []
-        self.tokens_cross_attention_module_identifiers = []
-
-        self.saved_cross_attention_maps = {}
-
-        self.clear_requests(cleanup=True)
-
-    def register_cross_attention_modules(self, model):
-        for name, _module in get_cross_attention_modules(model, CrossAttentionType.SELF):
-            if name in self.self_cross_attention_module_identifiers:
-                raise AssertionError(f"name {name} cannot appear more than once")
-            self.self_cross_attention_module_identifiers.append(name)
-        for name, _module in get_cross_attention_modules(model, CrossAttentionType.TOKENS):
-            if name in self.tokens_cross_attention_module_identifiers:
-                raise AssertionError(f"name {name} cannot appear more than once")
-            self.tokens_cross_attention_module_identifiers.append(name)
-
-    def request_save_attention_maps(self, cross_attention_type: CrossAttentionType):
-        if cross_attention_type == CrossAttentionType.SELF:
-            self.self_cross_attention_action = Context.Action.SAVE
-        else:
-            self.tokens_cross_attention_action = Context.Action.SAVE
-
-    def request_apply_saved_attention_maps(self, cross_attention_type: CrossAttentionType):
-        if cross_attention_type == CrossAttentionType.SELF:
-            self.self_cross_attention_action = Context.Action.APPLY
-        else:
-            self.tokens_cross_attention_action = Context.Action.APPLY
-
-    def is_tokens_cross_attention(self, module_identifier) -> bool:
-        return module_identifier in self.tokens_cross_attention_module_identifiers
-
-    def get_should_save_maps(self, module_identifier: str) -> bool:
-        if module_identifier in self.self_cross_attention_module_identifiers:
-            return self.self_cross_attention_action == Context.Action.SAVE
-        elif module_identifier in self.tokens_cross_attention_module_identifiers:
-            return self.tokens_cross_attention_action == Context.Action.SAVE
-        return False
-
-    def get_should_apply_saved_maps(self, module_identifier: str) -> bool:
-        if module_identifier in self.self_cross_attention_module_identifiers:
-            return self.self_cross_attention_action == Context.Action.APPLY
-        elif module_identifier in self.tokens_cross_attention_module_identifiers:
-            return self.tokens_cross_attention_action == Context.Action.APPLY
-        return False
 
     def get_active_cross_attention_control_types_for_step(
         self, percent_through: float = None
@@ -111,219 +47,8 @@ class Context:
             to_control.append(CrossAttentionType.TOKENS)
         return to_control
 
-    def save_slice(
-        self,
-        identifier: str,
-        slice: torch.Tensor,
-        dim: Optional[int],
-        offset: int,
-        slice_size: Optional[int],
-    ):
-        if identifier not in self.saved_cross_attention_maps:
-            self.saved_cross_attention_maps[identifier] = {
-                "dim": dim,
-                "slice_size": slice_size,
-                "slices": {offset or 0: slice},
-            }
-        else:
-            self.saved_cross_attention_maps[identifier]["slices"][offset or 0] = slice
 
-    def get_slice(
-        self,
-        identifier: str,
-        requested_dim: Optional[int],
-        requested_offset: int,
-        slice_size: int,
-    ):
-        saved_attention_dict = self.saved_cross_attention_maps[identifier]
-        if requested_dim is None:
-            if saved_attention_dict["dim"] is not None:
-                raise RuntimeError(f"dim mismatch: expected dim=None, have {saved_attention_dict['dim']}")
-            return saved_attention_dict["slices"][0]
-
-        if saved_attention_dict["dim"] == requested_dim:
-            if slice_size != saved_attention_dict["slice_size"]:
-                raise RuntimeError(
-                    f"slice_size mismatch: expected slice_size={slice_size}, have {saved_attention_dict['slice_size']}"
-                )
-            return saved_attention_dict["slices"][requested_offset]
-
-        if saved_attention_dict["dim"] is None:
-            whole_saved_attention = saved_attention_dict["slices"][0]
-            if requested_dim == 0:
-                return whole_saved_attention[requested_offset : requested_offset + slice_size]
-            elif requested_dim == 1:
-                return whole_saved_attention[:, requested_offset : requested_offset + slice_size]
-
-        raise RuntimeError(f"Cannot convert dim {saved_attention_dict['dim']} to requested dim {requested_dim}")
-
-    def get_slicing_strategy(self, identifier: str) -> tuple[Optional[int], Optional[int]]:
-        saved_attention = self.saved_cross_attention_maps.get(identifier, None)
-        if saved_attention is None:
-            return None, None
-        return saved_attention["dim"], saved_attention["slice_size"]
-
-    def clear_requests(self, cleanup=True):
-        self.tokens_cross_attention_action = Context.Action.NONE
-        self.self_cross_attention_action = Context.Action.NONE
-        if cleanup:
-            self.saved_cross_attention_maps = {}
-
-    def offload_saved_attention_slices_to_cpu(self):
-        for _key, map_dict in self.saved_cross_attention_maps.items():
-            for offset, slice in map_dict["slices"].items():
-                map_dict[offset] = slice.to("cpu")
-
-
-class InvokeAICrossAttentionMixin:
-    """
-    Enable InvokeAI-flavoured Attention calculation, which does aggressive low-memory slicing and calls
-    through both to an attention_slice_wrangler and a slicing_strategy_getter for custom attention map wrangling
-    and dymamic slicing strategy selection.
-    """
-
-    def __init__(self):
-        self.mem_total_gb = psutil.virtual_memory().total // (1 << 30)
-        self.attention_slice_wrangler = None
-        self.slicing_strategy_getter = None
-        self.attention_slice_calculated_callback = None
-
-    def set_attention_slice_wrangler(
-        self,
-        wrangler: Optional[Callable[[nn.Module, torch.Tensor, int, int, int], torch.Tensor]],
-    ):
-        """
-        Set custom attention calculator to be called when attention is calculated
-        :param wrangler: Callback, with args (module, suggested_attention_slice, dim, offset, slice_size),
-        which returns either the suggested_attention_slice or an adjusted equivalent.
-            `module` is the current Attention module for which the callback is being invoked.
-            `suggested_attention_slice` is the default-calculated attention slice
-            `dim` is -1 if the attenion map has not been sliced, or 0 or 1 for dimension-0 or dimension-1 slicing.
-                If `dim` is >= 0, `offset` and `slice_size` specify the slice start and length.
-
-        Pass None to use the default attention calculation.
-        :return:
-        """
-        self.attention_slice_wrangler = wrangler
-
-    def set_slicing_strategy_getter(self, getter: Optional[Callable[[nn.Module], tuple[int, int]]]):
-        self.slicing_strategy_getter = getter
-
-    def set_attention_slice_calculated_callback(self, callback: Optional[Callable[[torch.Tensor], None]]):
-        self.attention_slice_calculated_callback = callback
-
-    def einsum_lowest_level(self, query, key, value, dim, offset, slice_size):
-        # calculate attention scores
-        # attention_scores = torch.einsum('b i d, b j d -> b i j', q, k)
-        attention_scores = torch.baddbmm(
-            torch.empty(
-                query.shape[0],
-                query.shape[1],
-                key.shape[1],
-                dtype=query.dtype,
-                device=query.device,
-            ),
-            query,
-            key.transpose(-1, -2),
-            beta=0,
-            alpha=self.scale,
-        )
-
-        # calculate attention slice by taking the best scores for each latent pixel
-        default_attention_slice = attention_scores.softmax(dim=-1, dtype=attention_scores.dtype)
-        attention_slice_wrangler = self.attention_slice_wrangler
-        if attention_slice_wrangler is not None:
-            attention_slice = attention_slice_wrangler(self, default_attention_slice, dim, offset, slice_size)
-        else:
-            attention_slice = default_attention_slice
-
-        if self.attention_slice_calculated_callback is not None:
-            self.attention_slice_calculated_callback(attention_slice, dim, offset, slice_size)
-
-        hidden_states = torch.bmm(attention_slice, value)
-        return hidden_states
-
-    def einsum_op_slice_dim0(self, q, k, v, slice_size):
-        r = torch.zeros(q.shape[0], q.shape[1], v.shape[2], device=q.device, dtype=q.dtype)
-        for i in range(0, q.shape[0], slice_size):
-            end = i + slice_size
-            r[i:end] = self.einsum_lowest_level(q[i:end], k[i:end], v[i:end], dim=0, offset=i, slice_size=slice_size)
-        return r
-
-    def einsum_op_slice_dim1(self, q, k, v, slice_size):
-        r = torch.zeros(q.shape[0], q.shape[1], v.shape[2], device=q.device, dtype=q.dtype)
-        for i in range(0, q.shape[1], slice_size):
-            end = i + slice_size
-            r[:, i:end] = self.einsum_lowest_level(q[:, i:end], k, v, dim=1, offset=i, slice_size=slice_size)
-        return r
-
-    def einsum_op_mps_v1(self, q, k, v):
-        if q.shape[1] <= 4096:  # (512x512) max q.shape[1]: 4096
-            return self.einsum_lowest_level(q, k, v, None, None, None)
-        else:
-            slice_size = math.floor(2**30 / (q.shape[0] * q.shape[1]))
-            return self.einsum_op_slice_dim1(q, k, v, slice_size)
-
-    def einsum_op_mps_v2(self, q, k, v):
-        if self.mem_total_gb > 8 and q.shape[1] <= 4096:
-            return self.einsum_lowest_level(q, k, v, None, None, None)
-        else:
-            return self.einsum_op_slice_dim0(q, k, v, 1)
-
-    def einsum_op_tensor_mem(self, q, k, v, max_tensor_mb):
-        size_mb = q.shape[0] * q.shape[1] * k.shape[1] * q.element_size() // (1 << 20)
-        if size_mb <= max_tensor_mb:
-            return self.einsum_lowest_level(q, k, v, None, None, None)
-        div = 1 << int((size_mb - 1) / max_tensor_mb).bit_length()
-        if div <= q.shape[0]:
-            return self.einsum_op_slice_dim0(q, k, v, q.shape[0] // div)
-        return self.einsum_op_slice_dim1(q, k, v, max(q.shape[1] // div, 1))
-
-    def einsum_op_cuda(self, q, k, v):
-        # check if we already have a slicing strategy (this should only happen during cross-attention controlled generation)
-        slicing_strategy_getter = self.slicing_strategy_getter
-        if slicing_strategy_getter is not None:
-            (dim, slice_size) = slicing_strategy_getter(self)
-            if dim is not None:
-                # print("using saved slicing strategy with dim", dim, "slice size", slice_size)
-                if dim == 0:
-                    return self.einsum_op_slice_dim0(q, k, v, slice_size)
-                elif dim == 1:
-                    return self.einsum_op_slice_dim1(q, k, v, slice_size)
-
-        # fallback for when there is no saved strategy, or saved strategy does not slice
-        mem_free_total = get_mem_free_total(q.device)
-        # Divide factor of safety as there's copying and fragmentation
-        return self.einsum_op_tensor_mem(q, k, v, mem_free_total / 3.3 / (1 << 20))
-
-    def get_invokeai_attention_mem_efficient(self, q, k, v):
-        if q.device.type == "cuda":
-            # print("in get_attention_mem_efficient with q shape", q.shape, ", k shape", k.shape, ", free memory is", get_mem_free_total(q.device))
-            return self.einsum_op_cuda(q, k, v)
-
-        if q.device.type == "mps" or q.device.type == "cpu":
-            if self.mem_total_gb >= 32:
-                return self.einsum_op_mps_v1(q, k, v)
-            return self.einsum_op_mps_v2(q, k, v)
-
-        # Smaller slices are faster due to L2/L3/SLC caches.
-        # Tested on i7 with 8MB L3 cache.
-        return self.einsum_op_tensor_mem(q, k, v, 32)
-
-
-def restore_default_cross_attention(
-    model,
-    is_running_diffusers: bool,
-    restore_attention_processor: Optional[AttentionProcessor] = None,
-):
-    if is_running_diffusers:
-        unet = model
-        unet.set_attn_processor(restore_attention_processor or AttnProcessor())
-    else:
-        remove_attention_function(model)
-
-
-def setup_cross_attention_control_attention_processors(unet: UNet2DConditionModel, context: Context):
+def setup_cross_attention_control_attention_processors(unet: UNet2DConditionModel, context: CrossAttnControlContext):
     """
     Inject attention parameters and functions into the passed in model to enable cross attention editing.
 
@@ -362,170 +87,6 @@ def setup_cross_attention_control_attention_processors(unet: UNet2DConditionMode
         unet.set_attn_processor(SlicedSwapCrossAttnProcesser(slice_size=slice_size))
 
 
-def get_cross_attention_modules(model, which: CrossAttentionType) -> list[tuple[str, InvokeAICrossAttentionMixin]]:
-    cross_attention_class: type = InvokeAIDiffusersCrossAttention
-    which_attn = "attn1" if which is CrossAttentionType.SELF else "attn2"
-    attention_module_tuples = [
-        (name, module)
-        for name, module in model.named_modules()
-        if isinstance(module, cross_attention_class) and which_attn in name
-    ]
-    cross_attention_modules_in_model_count = len(attention_module_tuples)
-    expected_count = 16
-    if cross_attention_modules_in_model_count != expected_count:
-        # non-fatal error but .swap() won't work.
-        logger.error(
-            f"Error! CrossAttentionControl found an unexpected number of {cross_attention_class} modules in the model "
-            f"(expected {expected_count}, found {cross_attention_modules_in_model_count}). Either monkey-patching "
-            "failed or some assumption has changed about the structure of the model itself. Please fix the "
-            f"monkey-patching, and/or update the {expected_count} above to an appropriate number, and/or find and "
-            "inform someone who knows what it means. This error is non-fatal, but it is likely that .swap() and "
-            "attention map display will not work properly until it is fixed."
-        )
-    return attention_module_tuples
-
-
-def inject_attention_function(unet, context: Context):
-    # ORIGINAL SOURCE CODE: https://github.com/huggingface/diffusers/blob/91ddd2a25b848df0fa1262d4f1cd98c7ccb87750/src/diffusers/models/attention.py#L276
-
-    def attention_slice_wrangler(module, suggested_attention_slice: torch.Tensor, dim, offset, slice_size):
-        # memory_usage = suggested_attention_slice.element_size() * suggested_attention_slice.nelement()
-
-        attention_slice = suggested_attention_slice
-
-        if context.get_should_save_maps(module.identifier):
-            # print(module.identifier, "saving suggested_attention_slice of shape",
-            #      suggested_attention_slice.shape, "dim", dim, "offset", offset)
-            slice_to_save = attention_slice.to("cpu") if dim is not None else attention_slice
-            context.save_slice(
-                module.identifier,
-                slice_to_save,
-                dim=dim,
-                offset=offset,
-                slice_size=slice_size,
-            )
-        elif context.get_should_apply_saved_maps(module.identifier):
-            # print(module.identifier, "applying saved attention slice for dim", dim, "offset", offset)
-            saved_attention_slice = context.get_slice(module.identifier, dim, offset, slice_size)
-
-            # slice may have been offloaded to CPU
-            saved_attention_slice = saved_attention_slice.to(suggested_attention_slice.device)
-
-            if context.is_tokens_cross_attention(module.identifier):
-                index_map = context.cross_attention_index_map
-                remapped_saved_attention_slice = torch.index_select(saved_attention_slice, -1, index_map)
-                this_attention_slice = suggested_attention_slice
-
-                mask = context.cross_attention_mask.to(torch_dtype(suggested_attention_slice.device))
-                saved_mask = mask
-                this_mask = 1 - mask
-                attention_slice = remapped_saved_attention_slice * saved_mask + this_attention_slice * this_mask
-            else:
-                # just use everything
-                attention_slice = saved_attention_slice
-
-        return attention_slice
-
-    cross_attention_modules = get_cross_attention_modules(
-        unet, CrossAttentionType.TOKENS
-    ) + get_cross_attention_modules(unet, CrossAttentionType.SELF)
-    for identifier, module in cross_attention_modules:
-        module.identifier = identifier
-        try:
-            module.set_attention_slice_wrangler(attention_slice_wrangler)
-            module.set_slicing_strategy_getter(lambda module: context.get_slicing_strategy(identifier))  # noqa: B023
-        except AttributeError as e:
-            if is_attribute_error_about(e, "set_attention_slice_wrangler"):
-                print(f"TODO: implement set_attention_slice_wrangler for {type(module)}")  # TODO
-            else:
-                raise
-
-
-def remove_attention_function(unet):
-    cross_attention_modules = get_cross_attention_modules(
-        unet, CrossAttentionType.TOKENS
-    ) + get_cross_attention_modules(unet, CrossAttentionType.SELF)
-    for _identifier, module in cross_attention_modules:
-        try:
-            # clear wrangler callback
-            module.set_attention_slice_wrangler(None)
-            module.set_slicing_strategy_getter(None)
-        except AttributeError as e:
-            if is_attribute_error_about(e, "set_attention_slice_wrangler"):
-                print(f"TODO: implement set_attention_slice_wrangler for {type(module)}")
-            else:
-                raise
-
-
-def is_attribute_error_about(error: AttributeError, attribute: str):
-    if hasattr(error, "name"):  # Python 3.10
-        return error.name == attribute
-    else:  # Python 3.9
-        return attribute in str(error)
-
-
-def get_mem_free_total(device):
-    # only on cuda
-    if not torch.cuda.is_available():
-        return None
-    stats = torch.cuda.memory_stats(device)
-    mem_active = stats["active_bytes.all.current"]
-    mem_reserved = stats["reserved_bytes.all.current"]
-    mem_free_cuda, _ = torch.cuda.mem_get_info(device)
-    mem_free_torch = mem_reserved - mem_active
-    mem_free_total = mem_free_cuda + mem_free_torch
-    return mem_free_total
-
-
-class InvokeAIDiffusersCrossAttention(diffusers.models.attention.Attention, InvokeAICrossAttentionMixin):
-    def __init__(self, **kwargs):
-        super().__init__(**kwargs)
-        InvokeAICrossAttentionMixin.__init__(self)
-
-    def _attention(self, query, key, value, attention_mask=None):
-        # default_result = super()._attention(query,  key, value)
-        if attention_mask is not None:
-            print(f"{type(self).__name__} ignoring passed-in attention_mask")
-        attention_result = self.get_invokeai_attention_mem_efficient(query, key, value)
-
-        hidden_states = self.reshape_batch_dim_to_heads(attention_result)
-        return hidden_states
-
-
-## 🧨diffusers implementation follows
-
-
-"""
-# base implementation
-
-class AttnProcessor:
-    def __call__(self, attn: Attention, hidden_states, encoder_hidden_states=None, attention_mask=None):
-        batch_size, sequence_length, _ = hidden_states.shape
-        attention_mask = attn.prepare_attention_mask(attention_mask, sequence_length)
-
-        query = attn.to_q(hidden_states)
-        query = attn.head_to_batch_dim(query)
-
-        encoder_hidden_states = encoder_hidden_states if encoder_hidden_states is not None else hidden_states
-        key = attn.to_k(encoder_hidden_states)
-        value = attn.to_v(encoder_hidden_states)
-        key = attn.head_to_batch_dim(key)
-        value = attn.head_to_batch_dim(value)
-
-        attention_probs = attn.get_attention_scores(query, key, attention_mask)
-        hidden_states = torch.bmm(attention_probs, value)
-        hidden_states = attn.batch_to_head_dim(hidden_states)
-
-        # linear proj
-        hidden_states = attn.to_out[0](hidden_states)
-        # dropout
-        hidden_states = attn.to_out[1](hidden_states)
-
-        return hidden_states
-
-"""
-
-
 @dataclass
 class SwapCrossAttnContext:
     modified_text_embeddings: torch.Tensor
diff --git a/invokeai/backend/stable_diffusion/diffusion/cross_attention_map_saving.py b/invokeai/backend/stable_diffusion/diffusion/cross_attention_map_saving.py
deleted file mode 100644
index 82c9f1dcea..0000000000
--- a/invokeai/backend/stable_diffusion/diffusion/cross_attention_map_saving.py
+++ /dev/null
@@ -1,100 +0,0 @@
-import math
-from typing import Optional
-
-import torch
-from PIL import Image
-from torchvision.transforms.functional import InterpolationMode
-from torchvision.transforms.functional import resize as tv_resize
-
-
-class AttentionMapSaver:
-    def __init__(self, token_ids: range, latents_shape: torch.Size):
-        self.token_ids = token_ids
-        self.latents_shape = latents_shape
-        # self.collated_maps = #torch.zeros([len(token_ids), latents_shape[0], latents_shape[1]])
-        self.collated_maps: dict[str, torch.Tensor] = {}
-
-    def clear_maps(self):
-        self.collated_maps = {}
-
-    def add_attention_maps(self, maps: torch.Tensor, key: str):
-        """
-        Accumulate the given attention maps and store by summing with existing maps at the passed-in key (if any).
-        :param maps: Attention maps to store. Expected shape [A, (H*W), N] where A is attention heads count, H and W are the map size (fixed per-key) and N is the number of tokens (typically 77).
-        :param key: Storage key. If a map already exists for this key it will be summed with the incoming data. In this case the maps sizes (H and W) should match.
-        :return: None
-        """
-        key_and_size = f"{key}_{maps.shape[1]}"
-
-        # extract desired tokens
-        maps = maps[:, :, self.token_ids]
-
-        # merge attention heads to a single map per token
-        maps = torch.sum(maps, 0)
-
-        # store
-        if key_and_size not in self.collated_maps:
-            self.collated_maps[key_and_size] = torch.zeros_like(maps, device="cpu")
-        self.collated_maps[key_and_size] += maps.cpu()
-
-    def write_maps_to_disk(self, path: str):
-        pil_image = self.get_stacked_maps_image()
-        if pil_image is not None:
-            pil_image.save(path, "PNG")
-
-    def get_stacked_maps_image(self) -> Optional[Image.Image]:
-        """
-        Scale all collected attention maps to the same size, blend them together and return as an image.
-        :return: An image containing a vertical stack of blended attention maps, one for each requested token.
-        """
-        num_tokens = len(self.token_ids)
-        if num_tokens == 0:
-            return None
-
-        latents_height = self.latents_shape[0]
-        latents_width = self.latents_shape[1]
-
-        merged = None
-
-        for _key, maps in self.collated_maps.items():
-            # maps has shape [(H*W), N] for N tokens
-            # but we want [N, H, W]
-            this_scale_factor = math.sqrt(maps.shape[0] / (latents_width * latents_height))
-            this_maps_height = int(float(latents_height) * this_scale_factor)
-            this_maps_width = int(float(latents_width) * this_scale_factor)
-            # and we need to do some dimension juggling
-            maps = torch.reshape(
-                torch.swapdims(maps, 0, 1),
-                [num_tokens, this_maps_height, this_maps_width],
-            )
-
-            # scale to output size if necessary
-            if this_scale_factor != 1:
-                maps = tv_resize(maps, [latents_height, latents_width], InterpolationMode.BICUBIC)
-
-            # normalize
-            maps_min = torch.min(maps)
-            maps_range = torch.max(maps) - maps_min
-            # print(f"map {key} size {[this_maps_width, this_maps_height]} range {[maps_min, maps_min + maps_range]}")
-            maps_normalized = (maps - maps_min) / maps_range
-            # expand to (-0.1, 1.1) and clamp
-            maps_normalized_expanded = maps_normalized * 1.1 - 0.05
-            maps_normalized_expanded_clamped = torch.clamp(maps_normalized_expanded, 0, 1)
-
-            # merge together, producing a vertical stack
-            maps_stacked = torch.reshape(
-                maps_normalized_expanded_clamped,
-                [num_tokens * latents_height, latents_width],
-            )
-
-            if merged is None:
-                merged = maps_stacked
-            else:
-                # screen blend
-                merged = 1 - (1 - maps_stacked) * (1 - merged)
-
-        if merged is None:
-            return None
-
-        merged_bytes = merged.mul(0xFF).byte()
-        return Image.fromarray(merged_bytes.numpy(), mode="L")
diff --git a/invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py b/invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py
index c6b85d2bd6..58ab16bae8 100644
--- a/invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py
+++ b/invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py
@@ -17,13 +17,11 @@ from invokeai.backend.stable_diffusion.diffusion.conditioning_data import (
 )
 
 from .cross_attention_control import (
-    Context,
     CrossAttentionType,
+    CrossAttnControlContext,
     SwapCrossAttnContext,
-    get_cross_attention_modules,
     setup_cross_attention_control_attention_processors,
 )
-from .cross_attention_map_saving import AttentionMapSaver
 
 ModelForwardCallback: TypeAlias = Union[
     # x, t, conditioning, Optional[cross-attention kwargs]
@@ -69,14 +67,12 @@ class InvokeAIDiffuserComponent:
         self,
         unet: UNet2DConditionModel,
         extra_conditioning_info: Optional[ExtraConditioningInfo],
-        step_count: int,
     ):
         old_attn_processors = unet.attn_processors
 
         try:
-            self.cross_attention_control_context = Context(
+            self.cross_attention_control_context = CrossAttnControlContext(
                 arguments=extra_conditioning_info.cross_attention_control_args,
-                step_count=step_count,
             )
             setup_cross_attention_control_attention_processors(
                 unet,
@@ -87,27 +83,6 @@ class InvokeAIDiffuserComponent:
         finally:
             self.cross_attention_control_context = None
             unet.set_attn_processor(old_attn_processors)
-            # TODO resuscitate attention map saving
-            # self.remove_attention_map_saving()
-
-    def setup_attention_map_saving(self, saver: AttentionMapSaver):
-        def callback(slice, dim, offset, slice_size, key):
-            if dim is not None:
-                # sliced tokens attention map saving is not implemented
-                return
-            saver.add_attention_maps(slice, key)
-
-        tokens_cross_attention_modules = get_cross_attention_modules(self.model, CrossAttentionType.TOKENS)
-        for identifier, module in tokens_cross_attention_modules:
-            key = "down" if identifier.startswith("down") else "up" if identifier.startswith("up") else "mid"
-            module.set_attention_slice_calculated_callback(
-                lambda slice, dim, offset, slice_size, key=key: callback(slice, dim, offset, slice_size, key)
-            )
-
-    def remove_attention_map_saving(self):
-        tokens_cross_attention_modules = get_cross_attention_modules(self.model, CrossAttentionType.TOKENS)
-        for _, module in tokens_cross_attention_modules:
-            module.set_attention_slice_calculated_callback(None)
 
     def do_controlnet_step(
         self,