Merge branch 'main' into pr/4352

invokeai/app/invocations/latent.py

@@ -34,6 +34,7 @@ from invokeai.app.util.step_callback import stable_diffusion_step_callback
 from invokeai.backend.model_management.models import ModelType, SilenceWarnings
 
 from ...backend.model_management.lora import ModelPatcher
+from ...backend.model_management.seamless import set_seamless
 from ...backend.model_management.models import BaseModelType
 from ...backend.stable_diffusion import PipelineIntermediateState
 from ...backend.stable_diffusion.diffusers_pipeline import (
@@ -456,7 +457,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
             )
             with ExitStack() as exit_stack, ModelPatcher.apply_lora_unet(
                 unet_info.context.model, _lora_loader()
-            ), unet_info as unet:
+            ), set_seamless(unet_info.context.model, self.unet.seamless_axes), unet_info as unet:
                 latents = latents.to(device=unet.device, dtype=unet.dtype)
                 if noise is not None:
                     noise = noise.to(device=unet.device, dtype=unet.dtype)
@@ -549,7 +550,7 @@ class LatentsToImageInvocation(BaseInvocation):
             context=context,
         )
 
-        with vae_info as vae:
+        with set_seamless(vae_info.context.model, self.vae.seamless_axes), vae_info as vae:
             latents = latents.to(vae.device)
             if self.fp32:
                 vae.to(dtype=torch.float32)

invokeai/app/invocations/model.py

@@ -8,8 +8,8 @@ from .baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
     FieldDescriptions,
-    InputField,
     Input,
+    InputField,
     InvocationContext,
     OutputField,
     UIType,
@@ -33,6 +33,7 @@ class UNetField(BaseModel):
     unet: ModelInfo = Field(description="Info to load unet submodel")
     scheduler: ModelInfo = Field(description="Info to load scheduler submodel")
     loras: List[LoraInfo] = Field(description="Loras to apply on model loading")
+    seamless_axes: List[str] = Field(default_factory=list, description='Axes("x" and "y") to which apply seamless')
 
 
 class ClipField(BaseModel):
@@ -45,6 +46,7 @@ class ClipField(BaseModel):
 class VaeField(BaseModel):
     # TODO: better naming?
     vae: ModelInfo = Field(description="Info to load vae submodel")
+    seamless_axes: List[str] = Field(default_factory=list, description='Axes("x" and "y") to which apply seamless')
 
 
 class ModelLoaderOutput(BaseInvocationOutput):
@@ -388,3 +390,50 @@ class VaeLoaderInvocation(BaseInvocation):
                 )
             )
         )
+
+
+class SeamlessModeOutput(BaseInvocationOutput):
+    """Modified Seamless Model output"""
+
+    type: Literal["seamless_output"] = "seamless_output"
+
+    # Outputs
+    unet: Optional[UNetField] = OutputField(description=FieldDescriptions.unet, title="UNet")
+    vae: Optional[VaeField] = OutputField(description=FieldDescriptions.vae, title="VAE")
+
+
+@title("Seamless")
+@tags("seamless", "model")
+class SeamlessModeInvocation(BaseInvocation):
+    """Applies the seamless transformation to the Model UNet and VAE."""
+
+    type: Literal["seamless"] = "seamless"
+
+    # Inputs
+    unet: Optional[UNetField] = InputField(
+        default=None, description=FieldDescriptions.unet, input=Input.Connection, title="UNet"
+    )
+    vae: Optional[VaeField] = InputField(
+        default=None, description=FieldDescriptions.vae_model, input=Input.Connection, title="VAE"
+    )
+    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:
+        # Conditionally append 'x' and 'y' based on seamless_x and seamless_y
+        unet = copy.deepcopy(self.unet)
+        vae = copy.deepcopy(self.vae)
+
+        seamless_axes_list = []
+
+        if self.seamless_x:
+            seamless_axes_list.append("x")
+        if self.seamless_y:
+            seamless_axes_list.append("y")
+
+        if unet is not None:
+            unet.seamless_axes = seamless_axes_list
+        if vae is not None:
+            vae.seamless_axes = seamless_axes_list
+
+        return SeamlessModeOutput(unet=unet, vae=vae)

invokeai/backend/image_util/seamless.py

@@ -20,7 +20,8 @@ def _conv_forward_asymmetric(self, input, weight, bias):
 
 def configure_model_padding(model, seamless, seamless_axes):
     """
-    Modifies the 2D convolution layers to use a circular padding mode based on the `seamless` and `seamless_axes` options.
+    Modifies the 2D convolution layers to use a circular padding mode based on
+    the `seamless` and `seamless_axes` options.
     """
     # TODO: get an explicit interface for this in diffusers: https://github.com/huggingface/diffusers/issues/556
     for m in model.modules():

invokeai/backend/model_management/seamless.py

@@ -0,0 +1,103 @@
+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)):
+                print(f"applied - {m_name}")
+                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(m, "asymmetric_padding_mode"):
+                del m.asymmetric_padding_mode
+            if hasattr(m, "asymmetric_padding"):
+                del m.asymmetric_padding

invokeai/backend/util/hotfixes.py

@@ -761,3 +761,18 @@ class ControlNetModel(ModelMixin, ConfigMixin, FromOriginalControlnetMixin):
 
 diffusers.ControlNetModel = ControlNetModel
 diffusers.models.controlnet.ControlNetModel = ControlNetModel
+
+
+# patch LoRACompatibleConv to use original Conv2D forward function
+# this needed to make work seamless patch
+# NOTE: with this patch, torch.compile crashes on 2.0 torch(already fixed in nightly)
+# https://github.com/huggingface/diffusers/pull/4315
+# https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/lora.py#L96C18-L96C18
+def new_LoRACompatibleConv_forward(self, x):
+    if self.lora_layer is None:
+        return super(diffusers.models.lora.LoRACompatibleConv, self).forward(x)
+    else:
+        return super(diffusers.models.lora.LoRACompatibleConv, self).forward(x) + self.lora_layer(x)
+
+
+diffusers.models.lora.LoRACompatibleConv.forward = new_LoRACompatibleConv_forward

invokeai/frontend/web/src/app/components/App.tsx

@@ -14,6 +14,7 @@ import i18n from 'i18n';
 import { size } from 'lodash-es';
 import { ReactNode, memo, useCallback, useEffect } from 'react';
 import { ErrorBoundary } from 'react-error-boundary';
+import { usePreselectedImage } from '../../features/parameters/hooks/usePreselectedImage';
 import AppErrorBoundaryFallback from './AppErrorBoundaryFallback';
 import GlobalHotkeys from './GlobalHotkeys';
 import Toaster from './Toaster';
@@ -23,13 +24,22 @@ const DEFAULT_CONFIG = {};
 interface Props {
   config?: PartialAppConfig;
   headerComponent?: ReactNode;
+  selectedImage?: {
+    imageName: string;
+    action: 'sendToImg2Img' | 'sendToCanvas' | 'useAllParameters';
+  };
 }
 
-const App = ({ config = DEFAULT_CONFIG, headerComponent }: Props) => {
+const App = ({
+  config = DEFAULT_CONFIG,
+  headerComponent,
+  selectedImage,
+}: Props) => {
   const language = useAppSelector(languageSelector);
 
   const logger = useLogger('system');
   const dispatch = useAppDispatch();
+  const { handlePreselectedImage } = usePreselectedImage();
   const handleReset = useCallback(() => {
     localStorage.clear();
     location.reload();
@@ -51,6 +61,10 @@ const App = ({ config = DEFAULT_CONFIG, headerComponent }: Props) => {
     dispatch(appStarted());
   }, [dispatch]);
 
+  useEffect(() => {
+    handlePreselectedImage(selectedImage);
+  }, [handlePreselectedImage, selectedImage]);
+
   return (
     <ErrorBoundary
       onReset={handleReset}

invokeai/frontend/web/src/app/components/InvokeAIUI.tsx

@@ -26,6 +26,10 @@ interface Props extends PropsWithChildren {
   headerComponent?: ReactNode;
   middleware?: Middleware[];
   projectId?: string;
+  selectedImage?: {
+    imageName: string;
+    action: 'sendToImg2Img' | 'sendToCanvas' | 'useAllParameters';
+  };
 }
 
 const InvokeAIUI = ({
@@ -35,6 +39,7 @@ const InvokeAIUI = ({
   headerComponent,
   middleware,
   projectId,
+  selectedImage,
 }: Props) => {
   useEffect(() => {
     // configure API client token
@@ -81,7 +86,11 @@ const InvokeAIUI = ({
         <React.Suspense fallback={<Loading />}>
           <ThemeLocaleProvider>
             <AppDndContext>
-              <App config={config} headerComponent={headerComponent} />
+              <App
+                config={config}
+                headerComponent={headerComponent}
+                selectedImage={selectedImage}
+              />
             </AppDndContext>
           </ThemeLocaleProvider>
         </React.Suspense>

invokeai/frontend/web/src/features/gallery/components/ImageGrid/GalleryImage.tsx

@@ -8,7 +8,7 @@ import {
   ImageDraggableData,
   TypesafeDraggableData,
 } from 'features/dnd/types';
-import { useMultiselect } from 'features/gallery/hooks/useMultiselect.ts';
+import { useMultiselect } from 'features/gallery/hooks/useMultiselect';
 import { MouseEvent, memo, useCallback, useMemo, useState } from 'react';
 import { FaTrash } from 'react-icons/fa';
 import { MdStar, MdStarBorder } from 'react-icons/md';

invokeai/frontend/web/src/features/nodes/util/graphBuilders/addDynamicPromptsToGraph.ts

@@ -63,7 +63,7 @@ export const addDynamicPromptsToGraph = (
       {
         source: {
           node_id: DYNAMIC_PROMPT,
-          field: 'prompt_collection',
+          field: 'collection',
         },
         destination: {
           node_id: ITERATE,

invokeai/frontend/web/src/features/nodes/util/graphBuilders/addSDXLLoRAstoGraph.ts

@@ -11,9 +11,11 @@ import {
   METADATA_ACCUMULATOR,
   NEGATIVE_CONDITIONING,
   POSITIVE_CONDITIONING,
+  REFINER_SEAMLESS,
   SDXL_CANVAS_INPAINT_GRAPH,
   SDXL_CANVAS_OUTPAINT_GRAPH,
   SDXL_MODEL_LOADER,
+  SEAMLESS,
 } from './constants';
 
 export const addSDXLLoRAsToGraph = (
@@ -36,20 +38,25 @@ export const addSDXLLoRAsToGraph = (
     | MetadataAccumulatorInvocation
     | undefined;
 
+  // Handle Seamless Plugs
+  const unetLoaderId = modelLoaderNodeId;
+  let clipLoaderId = modelLoaderNodeId;
+  if ([SEAMLESS, REFINER_SEAMLESS].includes(modelLoaderNodeId)) {
+    clipLoaderId = SDXL_MODEL_LOADER;
+  }
+
   if (loraCount > 0) {
     // Remove modelLoaderNodeId unet/clip/clip2 connections to feed it to LoRAs
     graph.edges = graph.edges.filter(
       (e) =>
         !(
-          e.source.node_id === modelLoaderNodeId &&
+          e.source.node_id === unetLoaderId && ['unet'].includes(e.source.field)
-          ['unet'].includes(e.source.field)
         ) &&
         !(
-          e.source.node_id === modelLoaderNodeId &&
+          e.source.node_id === clipLoaderId && ['clip'].includes(e.source.field)
-          ['clip'].includes(e.source.field)
         ) &&
         !(
-          e.source.node_id === modelLoaderNodeId &&
+          e.source.node_id === clipLoaderId &&
           ['clip2'].includes(e.source.field)
         )
     );
@@ -88,7 +95,7 @@ export const addSDXLLoRAsToGraph = (
       // first lora = start the lora chain, attach directly to model loader
       graph.edges.push({
         source: {
-          node_id: modelLoaderNodeId,
+          node_id: unetLoaderId,
           field: 'unet',
         },
         destination: {
@@ -99,7 +106,7 @@ export const addSDXLLoRAsToGraph = (
 
       graph.edges.push({
         source: {
-          node_id: modelLoaderNodeId,
+          node_id: clipLoaderId,
           field: 'clip',
         },
         destination: {
@@ -110,7 +117,7 @@ export const addSDXLLoRAsToGraph = (
 
       graph.edges.push({
         source: {
-          node_id: modelLoaderNodeId,
+          node_id: clipLoaderId,
           field: 'clip2',
         },
         destination: {

invokeai/frontend/web/src/features/nodes/util/graphBuilders/addSDXLRefinerToGraph.ts

@@ -1,11 +1,15 @@
 import { RootState } from 'app/store/store';
-import { MetadataAccumulatorInvocation } from 'services/api/types';
+import {
+  MetadataAccumulatorInvocation,
+  SeamlessModeInvocation,
+} from 'services/api/types';
 import { NonNullableGraph } from '../../types/types';
 import {
   CANVAS_OUTPUT,
   LATENTS_TO_IMAGE,
   MASK_BLUR,
   METADATA_ACCUMULATOR,
+  REFINER_SEAMLESS,
   SDXL_CANVAS_IMAGE_TO_IMAGE_GRAPH,
   SDXL_CANVAS_INPAINT_GRAPH,
   SDXL_CANVAS_OUTPAINT_GRAPH,
@@ -21,7 +25,8 @@ import { craftSDXLStylePrompt } from './helpers/craftSDXLStylePrompt';
 export const addSDXLRefinerToGraph = (
   state: RootState,
   graph: NonNullableGraph,
-  baseNodeId: string
+  baseNodeId: string,
+  modelLoaderNodeId?: string
 ): void => {
   const {
     refinerModel,
@@ -33,6 +38,8 @@ export const addSDXLRefinerToGraph = (
     refinerStart,
   } = state.sdxl;
 
+  const { seamlessXAxis, seamlessYAxis } = state.generation;
+
   if (!refinerModel) {
     return;
   }
@@ -53,6 +60,10 @@ export const addSDXLRefinerToGraph = (
     metadataAccumulator.refiner_steps = refinerSteps;
   }
 
+  const modelLoaderId = modelLoaderNodeId
+    ? modelLoaderNodeId
+    : SDXL_MODEL_LOADER;
+
   // Construct Style Prompt
   const { craftedPositiveStylePrompt, craftedNegativeStylePrompt } =
     craftSDXLStylePrompt(state, true);
@@ -65,10 +76,7 @@ export const addSDXLRefinerToGraph = (
 
   graph.edges = graph.edges.filter(
     (e) =>
-      !(
+      !(e.source.node_id === modelLoaderId && ['vae'].includes(e.source.field))
-        e.source.node_id === SDXL_MODEL_LOADER &&
-        ['vae'].includes(e.source.field)
-      )
   );
 
   graph.nodes[SDXL_REFINER_MODEL_LOADER] = {
@@ -98,8 +106,39 @@ export const addSDXLRefinerToGraph = (
     denoising_end: 1,
   };
 
+  // Add Seamless To Refiner
+  if (seamlessXAxis || seamlessYAxis) {
+    graph.nodes[REFINER_SEAMLESS] = {
+      id: REFINER_SEAMLESS,
+      type: 'seamless',
+      seamless_x: seamlessXAxis,
+      seamless_y: seamlessYAxis,
+    } as SeamlessModeInvocation;
+
     graph.edges.push(
       {
+        source: {
+          node_id: SDXL_REFINER_MODEL_LOADER,
+          field: 'unet',
+        },
+        destination: {
+          node_id: REFINER_SEAMLESS,
+          field: 'unet',
+        },
+      },
+      {
+        source: {
+          node_id: REFINER_SEAMLESS,
+          field: 'unet',
+        },
+        destination: {
+          node_id: SDXL_REFINER_DENOISE_LATENTS,
+          field: 'unet',
+        },
+      }
+    );
+  } else {
+    graph.edges.push({
       source: {
         node_id: SDXL_REFINER_MODEL_LOADER,
         field: 'unet',
@@ -108,7 +147,10 @@ export const addSDXLRefinerToGraph = (
         node_id: SDXL_REFINER_DENOISE_LATENTS,
         field: 'unet',
       },
-    },
+    });
+  }
+
+  graph.edges.push(
     {
       source: {
         node_id: SDXL_REFINER_MODEL_LOADER,

invokeai/frontend/web/src/features/nodes/util/graphBuilders/addSeamlessToLinearGraph.ts

@@ -0,0 +1,109 @@
+import { RootState } from 'app/store/store';
+import { SeamlessModeInvocation } from 'services/api/types';
+import { NonNullableGraph } from '../../types/types';
+import {
+  CANVAS_COHERENCE_DENOISE_LATENTS,
+  CANVAS_INPAINT_GRAPH,
+  CANVAS_OUTPAINT_GRAPH,
+  DENOISE_LATENTS,
+  SDXL_CANVAS_IMAGE_TO_IMAGE_GRAPH,
+  SDXL_CANVAS_INPAINT_GRAPH,
+  SDXL_CANVAS_OUTPAINT_GRAPH,
+  SDXL_CANVAS_TEXT_TO_IMAGE_GRAPH,
+  SDXL_DENOISE_LATENTS,
+  SDXL_IMAGE_TO_IMAGE_GRAPH,
+  SDXL_TEXT_TO_IMAGE_GRAPH,
+  SEAMLESS,
+} from './constants';
+
+export const addSeamlessToLinearGraph = (
+  state: RootState,
+  graph: NonNullableGraph,
+  modelLoaderNodeId: string
+): void => {
+  // Remove Existing UNet Connections
+  const { seamlessXAxis, seamlessYAxis } = state.generation;
+
+  graph.nodes[SEAMLESS] = {
+    id: SEAMLESS,
+    type: 'seamless',
+    seamless_x: seamlessXAxis,
+    seamless_y: seamlessYAxis,
+  } as SeamlessModeInvocation;
+
+  let denoisingNodeId = DENOISE_LATENTS;
+
+  if (
+    graph.id === SDXL_TEXT_TO_IMAGE_GRAPH ||
+    graph.id === SDXL_IMAGE_TO_IMAGE_GRAPH ||
+    graph.id === SDXL_CANVAS_TEXT_TO_IMAGE_GRAPH ||
+    graph.id === SDXL_CANVAS_IMAGE_TO_IMAGE_GRAPH ||
+    graph.id === SDXL_CANVAS_INPAINT_GRAPH ||
+    graph.id === SDXL_CANVAS_OUTPAINT_GRAPH
+  ) {
+    denoisingNodeId = SDXL_DENOISE_LATENTS;
+  }
+
+  graph.edges = graph.edges.filter(
+    (e) =>
+      !(
+        e.source.node_id === modelLoaderNodeId &&
+        ['unet'].includes(e.source.field)
+      ) &&
+      !(
+        e.source.node_id === modelLoaderNodeId &&
+        ['vae'].includes(e.source.field)
+      )
+  );
+
+  graph.edges.push(
+    {
+      source: {
+        node_id: modelLoaderNodeId,
+        field: 'unet',
+      },
+      destination: {
+        node_id: SEAMLESS,
+        field: 'unet',
+      },
+    },
+    {
+      source: {
+        node_id: modelLoaderNodeId,
+        field: 'vae',
+      },
+      destination: {
+        node_id: SEAMLESS,
+        field: 'vae',
+      },
+    },
+    {
+      source: {
+        node_id: SEAMLESS,
+        field: 'unet',
+      },
+      destination: {
+        node_id: denoisingNodeId,
+        field: 'unet',
+      },
+    }
+  );
+
+  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',
+      },
+    });
+  }
+};

invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildCanvasImageToImageGraph.ts

@@ -7,6 +7,7 @@ import { addControlNetToLinearGraph } from './addControlNetToLinearGraph';
 import { addDynamicPromptsToGraph } from './addDynamicPromptsToGraph';
 import { addLoRAsToGraph } from './addLoRAsToGraph';
 import { addNSFWCheckerToGraph } from './addNSFWCheckerToGraph';
+import { addSeamlessToLinearGraph } from './addSeamlessToLinearGraph';
 import { addVAEToGraph } from './addVAEToGraph';
 import { addWatermarkerToGraph } from './addWatermarkerToGraph';
 import {
@@ -22,6 +23,7 @@ import {
   NEGATIVE_CONDITIONING,
   NOISE,
   POSITIVE_CONDITIONING,
+  SEAMLESS,
 } from './constants';
 
 /**
@@ -44,6 +46,8 @@ export const buildCanvasImageToImageGraph = (
     clipSkip,
     shouldUseCpuNoise,
     shouldUseNoiseSettings,
+    seamlessXAxis,
+    seamlessYAxis,
   } = state.generation;
 
   // The bounding box determines width and height, not the width and height params
@@ -64,6 +68,8 @@ export const buildCanvasImageToImageGraph = (
     throw new Error('No model found in state');
   }
 
+  let modelLoaderNodeId = MAIN_MODEL_LOADER;
+
   const use_cpu = shouldUseNoiseSettings
     ? shouldUseCpuNoise
     : initialGenerationState.shouldUseCpuNoise;
@@ -81,9 +87,9 @@ export const buildCanvasImageToImageGraph = (
   const graph: NonNullableGraph = {
     id: CANVAS_IMAGE_TO_IMAGE_GRAPH,
     nodes: {
-      [MAIN_MODEL_LOADER]: {
+      [modelLoaderNodeId]: {
         type: 'main_model_loader',
-        id: MAIN_MODEL_LOADER,
+        id: modelLoaderNodeId,
         is_intermediate: true,
         model,
       },
@@ -142,7 +148,7 @@ export const buildCanvasImageToImageGraph = (
       // Connect Model Loader to CLIP Skip and UNet
       {
         source: {
-          node_id: MAIN_MODEL_LOADER,
+          node_id: modelLoaderNodeId,
           field: 'unet',
         },
         destination: {
@@ -152,7 +158,7 @@ export const buildCanvasImageToImageGraph = (
       },
       {
         source: {
-          node_id: MAIN_MODEL_LOADER,
+          node_id: modelLoaderNodeId,
           field: 'clip',
         },
         destination: {
@@ -340,11 +346,17 @@ export const buildCanvasImageToImageGraph = (
     },
   });
 
+  // Add Seamless To Graph
+  if (seamlessXAxis || seamlessYAxis) {
+    addSeamlessToLinearGraph(state, graph, modelLoaderNodeId);
+    modelLoaderNodeId = SEAMLESS;
+  }
+
   // add LoRA support
   addLoRAsToGraph(state, graph, DENOISE_LATENTS);
 
   // optionally add custom VAE
-  addVAEToGraph(state, graph, MAIN_MODEL_LOADER);
+  addVAEToGraph(state, graph, modelLoaderNodeId);
 
   // add dynamic prompts - also sets up core iteration and seed
   addDynamicPromptsToGraph(state, graph);

invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildCanvasInpaintGraph.ts

@@ -13,6 +13,7 @@ import {
 import { addControlNetToLinearGraph } from './addControlNetToLinearGraph';
 import { addLoRAsToGraph } from './addLoRAsToGraph';
 import { addNSFWCheckerToGraph } from './addNSFWCheckerToGraph';
+import { addSeamlessToLinearGraph } from './addSeamlessToLinearGraph';
 import { addVAEToGraph } from './addVAEToGraph';
 import { addWatermarkerToGraph } from './addWatermarkerToGraph';
 import {
@@ -38,6 +39,7 @@ import {
   POSITIVE_CONDITIONING,
   RANDOM_INT,
   RANGE_OF_SIZE,
+  SEAMLESS,
 } from './constants';
 
 /**
@@ -68,6 +70,8 @@ export const buildCanvasInpaintGraph = (
     canvasCoherenceSteps,
     canvasCoherenceStrength,
     clipSkip,
+    seamlessXAxis,
+    seamlessYAxis,
   } = state.generation;
 
   if (!model) {
@@ -85,6 +89,8 @@ export const buildCanvasInpaintGraph = (
     shouldAutoSave,
   } = state.canvas;
 
+  let modelLoaderNodeId = MAIN_MODEL_LOADER;
+
   const use_cpu = shouldUseNoiseSettings
     ? shouldUseCpuNoise
     : shouldUseCpuNoise;
@@ -92,9 +98,9 @@ export const buildCanvasInpaintGraph = (
   const graph: NonNullableGraph = {
     id: CANVAS_INPAINT_GRAPH,
     nodes: {
-      [MAIN_MODEL_LOADER]: {
+      [modelLoaderNodeId]: {
         type: 'main_model_loader',
-        id: MAIN_MODEL_LOADER,
+        id: modelLoaderNodeId,
         is_intermediate: true,
         model,
       },
@@ -204,7 +210,7 @@ export const buildCanvasInpaintGraph = (
       // Connect Model Loader to CLIP Skip and UNet
       {
         source: {
-          node_id: MAIN_MODEL_LOADER,
+          node_id: modelLoaderNodeId,
           field: 'unet',
         },
         destination: {
@@ -214,7 +220,7 @@ export const buildCanvasInpaintGraph = (
       },
       {
         source: {
-          node_id: MAIN_MODEL_LOADER,
+          node_id: modelLoaderNodeId,
           field: 'clip',
         },
         destination: {
@@ -349,7 +355,7 @@ export const buildCanvasInpaintGraph = (
       },
       {
         source: {
-          node_id: MAIN_MODEL_LOADER,
+          node_id: modelLoaderNodeId,
           field: 'unet',
         },
         destination: {
@@ -595,11 +601,17 @@ export const buildCanvasInpaintGraph = (
     (graph.nodes[RANGE_OF_SIZE] as RangeOfSizeInvocation).start = seed;
   }
 
+  // Add Seamless To Graph
+  if (seamlessXAxis || seamlessYAxis) {
+    addSeamlessToLinearGraph(state, graph, modelLoaderNodeId);
+    modelLoaderNodeId = SEAMLESS;
+  }
+
   // Add VAE
-  addVAEToGraph(state, graph, MAIN_MODEL_LOADER);
+  addVAEToGraph(state, graph, modelLoaderNodeId);
 
   // add LoRA support
-  addLoRAsToGraph(state, graph, DENOISE_LATENTS, MAIN_MODEL_LOADER);
+  addLoRAsToGraph(state, graph, DENOISE_LATENTS, modelLoaderNodeId);
 
   // add controlnet, mutating `graph`
   addControlNetToLinearGraph(state, graph, DENOISE_LATENTS);

invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildCanvasOutpaintGraph.ts

@@ -14,6 +14,7 @@ import {
 import { addControlNetToLinearGraph } from './addControlNetToLinearGraph';
 import { addLoRAsToGraph } from './addLoRAsToGraph';
 import { addNSFWCheckerToGraph } from './addNSFWCheckerToGraph';
+import { addSeamlessToLinearGraph } from './addSeamlessToLinearGraph';
 import { addVAEToGraph } from './addVAEToGraph';
 import { addWatermarkerToGraph } from './addWatermarkerToGraph';
 import {
@@ -43,6 +44,7 @@ import {
   POSITIVE_CONDITIONING,
   RANDOM_INT,
   RANGE_OF_SIZE,
+  SEAMLESS,
 } from './constants';
 
 /**
@@ -75,6 +77,8 @@ export const buildCanvasOutpaintGraph = (
     tileSize,
     infillMethod,
     clipSkip,
+    seamlessXAxis,
+    seamlessYAxis,
   } = state.generation;
 
   if (!model) {
@@ -92,6 +96,8 @@ export const buildCanvasOutpaintGraph = (
     shouldAutoSave,
   } = state.canvas;
 
+  let modelLoaderNodeId = MAIN_MODEL_LOADER;
+
   const use_cpu = shouldUseNoiseSettings
     ? shouldUseCpuNoise
     : shouldUseCpuNoise;
@@ -99,9 +105,9 @@ export const buildCanvasOutpaintGraph = (
   const graph: NonNullableGraph = {
     id: CANVAS_OUTPAINT_GRAPH,
     nodes: {
-      [MAIN_MODEL_LOADER]: {
+      [modelLoaderNodeId]: {
         type: 'main_model_loader',
-        id: MAIN_MODEL_LOADER,
+        id: modelLoaderNodeId,
         is_intermediate: true,
         model,
       },
@@ -222,7 +228,7 @@ export const buildCanvasOutpaintGraph = (
       // Connect Model Loader To UNet & Clip Skip
       {
         source: {
-          node_id: MAIN_MODEL_LOADER,
+          node_id: modelLoaderNodeId,
           field: 'unet',
         },
         destination: {
@@ -232,7 +238,7 @@ export const buildCanvasOutpaintGraph = (
       },
       {
         source: {
-          node_id: MAIN_MODEL_LOADER,
+          node_id: modelLoaderNodeId,
           field: 'clip',
         },
         destination: {
@@ -389,7 +395,7 @@ export const buildCanvasOutpaintGraph = (
       },
       {
         source: {
-          node_id: MAIN_MODEL_LOADER,
+          node_id: modelLoaderNodeId,
           field: 'unet',
         },
         destination: {
@@ -732,11 +738,17 @@ export const buildCanvasOutpaintGraph = (
     (graph.nodes[RANGE_OF_SIZE] as RangeOfSizeInvocation).start = seed;
   }
 
+  // Add Seamless To Graph
+  if (seamlessXAxis || seamlessYAxis) {
+    addSeamlessToLinearGraph(state, graph, modelLoaderNodeId);
+    modelLoaderNodeId = SEAMLESS;
+  }
+
   // Add VAE
-  addVAEToGraph(state, graph, MAIN_MODEL_LOADER);
+  addVAEToGraph(state, graph, modelLoaderNodeId);
 
   // add LoRA support
-  addLoRAsToGraph(state, graph, DENOISE_LATENTS, MAIN_MODEL_LOADER);
+  addLoRAsToGraph(state, graph, DENOISE_LATENTS, modelLoaderNodeId);
 
   // add controlnet, mutating `graph`
   addControlNetToLinearGraph(state, graph, DENOISE_LATENTS);

invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildCanvasSDXLImageToImageGraph.ts

@@ -8,6 +8,7 @@ import { addDynamicPromptsToGraph } from './addDynamicPromptsToGraph';
 import { addNSFWCheckerToGraph } from './addNSFWCheckerToGraph';
 import { addSDXLLoRAsToGraph } from './addSDXLLoRAstoGraph';
 import { addSDXLRefinerToGraph } from './addSDXLRefinerToGraph';
+import { addSeamlessToLinearGraph } from './addSeamlessToLinearGraph';
 import { addVAEToGraph } from './addVAEToGraph';
 import { addWatermarkerToGraph } from './addWatermarkerToGraph';
 import {
@@ -19,9 +20,11 @@ import {
   NEGATIVE_CONDITIONING,
   NOISE,
   POSITIVE_CONDITIONING,
+  REFINER_SEAMLESS,
   SDXL_CANVAS_IMAGE_TO_IMAGE_GRAPH,
   SDXL_DENOISE_LATENTS,
   SDXL_MODEL_LOADER,
+  SEAMLESS,
 } from './constants';
 import { craftSDXLStylePrompt } from './helpers/craftSDXLStylePrompt';
 
@@ -44,6 +47,8 @@ export const buildCanvasSDXLImageToImageGraph = (
     clipSkip,
     shouldUseCpuNoise,
     shouldUseNoiseSettings,
+    seamlessXAxis,
+    seamlessYAxis,
   } = state.generation;
 
   const {
@@ -71,6 +76,9 @@ export const buildCanvasSDXLImageToImageGraph = (
     throw new Error('No model found in state');
   }
 
+  // Model Loader ID
+  let modelLoaderNodeId = SDXL_MODEL_LOADER;
+
   const use_cpu = shouldUseNoiseSettings
     ? shouldUseCpuNoise
     : initialGenerationState.shouldUseCpuNoise;
@@ -92,9 +100,9 @@ export const buildCanvasSDXLImageToImageGraph = (
   const graph: NonNullableGraph = {
     id: SDXL_CANVAS_IMAGE_TO_IMAGE_GRAPH,
     nodes: {
-      [SDXL_MODEL_LOADER]: {
+      [modelLoaderNodeId]: {
         type: 'sdxl_model_loader',
-        id: SDXL_MODEL_LOADER,
+        id: modelLoaderNodeId,
         model,
       },
       [POSITIVE_CONDITIONING]: {
@@ -144,7 +152,7 @@ export const buildCanvasSDXLImageToImageGraph = (
       // Connect Model Loader To UNet & CLIP
       {
         source: {
-          node_id: SDXL_MODEL_LOADER,
+          node_id: modelLoaderNodeId,
           field: 'unet',
         },
         destination: {
@@ -154,7 +162,7 @@ export const buildCanvasSDXLImageToImageGraph = (
       },
       {
         source: {
-          node_id: SDXL_MODEL_LOADER,
+          node_id: modelLoaderNodeId,
           field: 'clip',
         },
         destination: {
@@ -164,7 +172,7 @@ export const buildCanvasSDXLImageToImageGraph = (
       },
       {
         source: {
-          node_id: SDXL_MODEL_LOADER,
+          node_id: modelLoaderNodeId,
           field: 'clip2',
         },
         destination: {
@@ -174,7 +182,7 @@ export const buildCanvasSDXLImageToImageGraph = (
       },
       {
         source: {
-          node_id: SDXL_MODEL_LOADER,
+          node_id: modelLoaderNodeId,
           field: 'clip',
         },
         destination: {
@@ -184,7 +192,7 @@ export const buildCanvasSDXLImageToImageGraph = (
       },
       {
         source: {
-          node_id: SDXL_MODEL_LOADER,
+          node_id: modelLoaderNodeId,
           field: 'clip2',
         },
         destination: {
@@ -351,16 +359,23 @@ export const buildCanvasSDXLImageToImageGraph = (
     },
   });
 
-  // add LoRA support
+  // Add Seamless To Graph
-  addSDXLLoRAsToGraph(state, graph, SDXL_DENOISE_LATENTS, SDXL_MODEL_LOADER);
+  if (seamlessXAxis || seamlessYAxis) {
+    addSeamlessToLinearGraph(state, graph, modelLoaderNodeId);
+    modelLoaderNodeId = SEAMLESS;
+  }
 
   // Add Refiner if enabled
   if (shouldUseSDXLRefiner) {
     addSDXLRefinerToGraph(state, graph, SDXL_DENOISE_LATENTS);
+    modelLoaderNodeId = REFINER_SEAMLESS;
   }
 
   // optionally add custom VAE
-  addVAEToGraph(state, graph, SDXL_MODEL_LOADER);
+  addVAEToGraph(state, graph, modelLoaderNodeId);
+
+  // add LoRA support
+  addSDXLLoRAsToGraph(state, graph, SDXL_DENOISE_LATENTS, modelLoaderNodeId);
 
   // add dynamic prompts - also sets up core iteration and seed
   addDynamicPromptsToGraph(state, graph);

invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildCanvasSDXLInpaintGraph.ts

@@ -14,6 +14,7 @@ import { addControlNetToLinearGraph } from './addControlNetToLinearGraph';
 import { addNSFWCheckerToGraph } from './addNSFWCheckerToGraph';
 import { addSDXLLoRAsToGraph } from './addSDXLLoRAstoGraph';
 import { addSDXLRefinerToGraph } from './addSDXLRefinerToGraph';
+import { addSeamlessToLinearGraph } from './addSeamlessToLinearGraph';
 import { addVAEToGraph } from './addVAEToGraph';
 import { addWatermarkerToGraph } from './addWatermarkerToGraph';
 import {
@@ -35,9 +36,11 @@ import {
   POSITIVE_CONDITIONING,
   RANDOM_INT,
   RANGE_OF_SIZE,
+  REFINER_SEAMLESS,
   SDXL_CANVAS_INPAINT_GRAPH,
   SDXL_DENOISE_LATENTS,
   SDXL_MODEL_LOADER,
+  SEAMLESS,
 } from './constants';
 import { craftSDXLStylePrompt } from './helpers/craftSDXLStylePrompt';
 
@@ -67,6 +70,8 @@ export const buildCanvasSDXLInpaintGraph = (
     maskBlurMethod,
     canvasCoherenceSteps,
     canvasCoherenceStrength,
+    seamlessXAxis,
+    seamlessYAxis,
   } = state.generation;
 
   const {
@@ -91,6 +96,8 @@ export const buildCanvasSDXLInpaintGraph = (
     shouldAutoSave,
   } = state.canvas;
 
+  let modelLoaderNodeId = SDXL_MODEL_LOADER;
+
   const use_cpu = shouldUseNoiseSettings
     ? shouldUseCpuNoise
     : shouldUseCpuNoise;
@@ -102,9 +109,9 @@ export const buildCanvasSDXLInpaintGraph = (
   const graph: NonNullableGraph = {
     id: SDXL_CANVAS_INPAINT_GRAPH,
     nodes: {
-      [SDXL_MODEL_LOADER]: {
+      [modelLoaderNodeId]: {
         type: 'sdxl_model_loader',
-        id: SDXL_MODEL_LOADER,
+        id: modelLoaderNodeId,
         model,
       },
       [POSITIVE_CONDITIONING]: {
@@ -209,7 +216,7 @@ export const buildCanvasSDXLInpaintGraph = (
       // Connect Model Loader to UNet and CLIP
       {
         source: {
-          node_id: SDXL_MODEL_LOADER,
+          node_id: modelLoaderNodeId,
           field: 'unet',
         },
         destination: {
@@ -219,7 +226,7 @@ export const buildCanvasSDXLInpaintGraph = (
       },
       {
         source: {
-          node_id: SDXL_MODEL_LOADER,
+          node_id: modelLoaderNodeId,
           field: 'clip',
         },
         destination: {
@@ -229,7 +236,7 @@ export const buildCanvasSDXLInpaintGraph = (
       },
       {
         source: {
-          node_id: SDXL_MODEL_LOADER,
+          node_id: modelLoaderNodeId,
           field: 'clip2',
         },
         destination: {
@@ -239,7 +246,7 @@ export const buildCanvasSDXLInpaintGraph = (
       },
       {
         source: {
-          node_id: SDXL_MODEL_LOADER,
+          node_id: modelLoaderNodeId,
           field: 'clip',
         },
         destination: {
@@ -249,7 +256,7 @@ export const buildCanvasSDXLInpaintGraph = (
       },
       {
         source: {
-          node_id: SDXL_MODEL_LOADER,
+          node_id: modelLoaderNodeId,
           field: 'clip2',
         },
         destination: {
@@ -363,7 +370,7 @@ export const buildCanvasSDXLInpaintGraph = (
       },
       {
         source: {
-          node_id: SDXL_MODEL_LOADER,
+          node_id: modelLoaderNodeId,
           field: 'unet',
         },
         destination: {
@@ -609,16 +616,28 @@ export const buildCanvasSDXLInpaintGraph = (
     (graph.nodes[RANGE_OF_SIZE] as RangeOfSizeInvocation).start = seed;
   }
 
+  // Add Seamless To Graph
+  if (seamlessXAxis || seamlessYAxis) {
+    addSeamlessToLinearGraph(state, graph, modelLoaderNodeId);
+    modelLoaderNodeId = SEAMLESS;
+  }
+
   // Add Refiner if enabled
   if (shouldUseSDXLRefiner) {
-    addSDXLRefinerToGraph(state, graph, CANVAS_COHERENCE_DENOISE_LATENTS);
+    addSDXLRefinerToGraph(
+      state,
+      graph,
+      CANVAS_COHERENCE_DENOISE_LATENTS,
+      modelLoaderNodeId
+    );
+    modelLoaderNodeId = REFINER_SEAMLESS;
   }
 
   // optionally add custom VAE
-  addVAEToGraph(state, graph, SDXL_MODEL_LOADER);
+  addVAEToGraph(state, graph, modelLoaderNodeId);
 
   // add LoRA support
-  addSDXLLoRAsToGraph(state, graph, SDXL_DENOISE_LATENTS, SDXL_MODEL_LOADER);
+  addSDXLLoRAsToGraph(state, graph, SDXL_DENOISE_LATENTS, modelLoaderNodeId);
 
   // add controlnet, mutating `graph`
   addControlNetToLinearGraph(state, graph, SDXL_DENOISE_LATENTS);

invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildCanvasSDXLOutpaintGraph.ts

@@ -15,6 +15,7 @@ import { addControlNetToLinearGraph } from './addControlNetToLinearGraph';
 import { addNSFWCheckerToGraph } from './addNSFWCheckerToGraph';
 import { addSDXLLoRAsToGraph } from './addSDXLLoRAstoGraph';
 import { addSDXLRefinerToGraph } from './addSDXLRefinerToGraph';
+import { addSeamlessToLinearGraph } from './addSeamlessToLinearGraph';
 import { addVAEToGraph } from './addVAEToGraph';
 import { addWatermarkerToGraph } from './addWatermarkerToGraph';
 import {
@@ -40,9 +41,11 @@ import {
   POSITIVE_CONDITIONING,
   RANDOM_INT,
   RANGE_OF_SIZE,
+  REFINER_SEAMLESS,
   SDXL_CANVAS_OUTPAINT_GRAPH,
   SDXL_DENOISE_LATENTS,
   SDXL_MODEL_LOADER,
+  SEAMLESS,
 } from './constants';
 import { craftSDXLStylePrompt } from './helpers/craftSDXLStylePrompt';
 
@@ -74,6 +77,8 @@ export const buildCanvasSDXLOutpaintGraph = (
     canvasCoherenceStrength,
     tileSize,
     infillMethod,
+    seamlessXAxis,
+    seamlessYAxis,
   } = state.generation;
 
   const {
@@ -98,6 +103,8 @@ export const buildCanvasSDXLOutpaintGraph = (
     shouldAutoSave,
   } = state.canvas;
 
+  let modelLoaderNodeId = SDXL_MODEL_LOADER;
+
   const use_cpu = shouldUseNoiseSettings
     ? shouldUseCpuNoise
     : shouldUseCpuNoise;
@@ -747,16 +754,28 @@ export const buildCanvasSDXLOutpaintGraph = (
     (graph.nodes[RANGE_OF_SIZE] as RangeOfSizeInvocation).start = seed;
   }
 
+  // Add Seamless To Graph
+  if (seamlessXAxis || seamlessYAxis) {
+    addSeamlessToLinearGraph(state, graph, modelLoaderNodeId);
+    modelLoaderNodeId = SEAMLESS;
+  }
+
   // Add Refiner if enabled
   if (shouldUseSDXLRefiner) {
-    addSDXLRefinerToGraph(state, graph, CANVAS_COHERENCE_DENOISE_LATENTS);
+    addSDXLRefinerToGraph(
+      state,
+      graph,
+      CANVAS_COHERENCE_DENOISE_LATENTS,
+      modelLoaderNodeId
+    );
+    modelLoaderNodeId = REFINER_SEAMLESS;
   }
 
   // optionally add custom VAE
-  addVAEToGraph(state, graph, SDXL_MODEL_LOADER);
+  addVAEToGraph(state, graph, modelLoaderNodeId);
 
   // add LoRA support
-  addSDXLLoRAsToGraph(state, graph, SDXL_DENOISE_LATENTS, SDXL_MODEL_LOADER);
+  addSDXLLoRAsToGraph(state, graph, SDXL_DENOISE_LATENTS, modelLoaderNodeId);
 
   // add controlnet, mutating `graph`
   addControlNetToLinearGraph(state, graph, SDXL_DENOISE_LATENTS);

invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildCanvasSDXLTextToImageGraph.ts

@@ -11,6 +11,7 @@ import { addDynamicPromptsToGraph } from './addDynamicPromptsToGraph';
 import { addNSFWCheckerToGraph } from './addNSFWCheckerToGraph';
 import { addSDXLLoRAsToGraph } from './addSDXLLoRAstoGraph';
 import { addSDXLRefinerToGraph } from './addSDXLRefinerToGraph';
+import { addSeamlessToLinearGraph } from './addSeamlessToLinearGraph';
 import { addVAEToGraph } from './addVAEToGraph';
 import { addWatermarkerToGraph } from './addWatermarkerToGraph';
 import {
@@ -21,9 +22,11 @@ import {
   NOISE,
   ONNX_MODEL_LOADER,
   POSITIVE_CONDITIONING,
+  REFINER_SEAMLESS,
   SDXL_CANVAS_TEXT_TO_IMAGE_GRAPH,
   SDXL_DENOISE_LATENTS,
   SDXL_MODEL_LOADER,
+  SEAMLESS,
 } from './constants';
 import { craftSDXLStylePrompt } from './helpers/craftSDXLStylePrompt';
 
@@ -45,6 +48,8 @@ export const buildCanvasSDXLTextToImageGraph = (
     clipSkip,
     shouldUseCpuNoise,
     shouldUseNoiseSettings,
+    seamlessXAxis,
+    seamlessYAxis,
   } = state.generation;
 
   // The bounding box determines width and height, not the width and height params
@@ -74,7 +79,7 @@ export const buildCanvasSDXLTextToImageGraph = (
 
   const isUsingOnnxModel = model.model_type === 'onnx';
 
-  const modelLoaderNodeId = isUsingOnnxModel
+  let modelLoaderNodeId = isUsingOnnxModel
     ? ONNX_MODEL_LOADER
     : SDXL_MODEL_LOADER;
 
@@ -334,9 +339,16 @@ export const buildCanvasSDXLTextToImageGraph = (
     },
   });
 
+  // Add Seamless To Graph
+  if (seamlessXAxis || seamlessYAxis) {
+    addSeamlessToLinearGraph(state, graph, modelLoaderNodeId);
+    modelLoaderNodeId = SEAMLESS;
+  }
+
   // Add Refiner if enabled
   if (shouldUseSDXLRefiner) {
     addSDXLRefinerToGraph(state, graph, SDXL_DENOISE_LATENTS);
+    modelLoaderNodeId = REFINER_SEAMLESS;
   }
 
   // add LoRA support

invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildCanvasTextToImageGraph.ts

@@ -10,6 +10,7 @@ import { addControlNetToLinearGraph } from './addControlNetToLinearGraph';
 import { addDynamicPromptsToGraph } from './addDynamicPromptsToGraph';
 import { addLoRAsToGraph } from './addLoRAsToGraph';
 import { addNSFWCheckerToGraph } from './addNSFWCheckerToGraph';
+import { addSeamlessToLinearGraph } from './addSeamlessToLinearGraph';
 import { addVAEToGraph } from './addVAEToGraph';
 import { addWatermarkerToGraph } from './addWatermarkerToGraph';
 import {
@@ -24,6 +25,7 @@ import {
   NOISE,
   ONNX_MODEL_LOADER,
   POSITIVE_CONDITIONING,
+  SEAMLESS,
 } from './constants';
 
 /**
@@ -44,6 +46,8 @@ export const buildCanvasTextToImageGraph = (
     clipSkip,
     shouldUseCpuNoise,
     shouldUseNoiseSettings,
+    seamlessXAxis,
+    seamlessYAxis,
   } = state.generation;
 
   // The bounding box determines width and height, not the width and height params
@@ -70,7 +74,7 @@ export const buildCanvasTextToImageGraph = (
 
   const isUsingOnnxModel = model.model_type === 'onnx';
 
-  const modelLoaderNodeId = isUsingOnnxModel
+  let modelLoaderNodeId = isUsingOnnxModel
     ? ONNX_MODEL_LOADER
     : MAIN_MODEL_LOADER;
 
@@ -321,6 +325,12 @@ export const buildCanvasTextToImageGraph = (
     },
   });
 
+  // Add Seamless To Graph
+  if (seamlessXAxis || seamlessYAxis) {
+    addSeamlessToLinearGraph(state, graph, modelLoaderNodeId);
+    modelLoaderNodeId = SEAMLESS;
+  }
+
   // optionally add custom VAE
   addVAEToGraph(state, graph, modelLoaderNodeId);
 

invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildLinearImageToImageGraph.ts

@@ -10,6 +10,7 @@ import { addControlNetToLinearGraph } from './addControlNetToLinearGraph';
 import { addDynamicPromptsToGraph } from './addDynamicPromptsToGraph';
 import { addLoRAsToGraph } from './addLoRAsToGraph';
 import { addNSFWCheckerToGraph } from './addNSFWCheckerToGraph';
+import { addSeamlessToLinearGraph } from './addSeamlessToLinearGraph';
 import { addVAEToGraph } from './addVAEToGraph';
 import { addWatermarkerToGraph } from './addWatermarkerToGraph';
 import {
@@ -24,6 +25,7 @@ import {
   NOISE,
   POSITIVE_CONDITIONING,
   RESIZE,
+  SEAMLESS,
 } from './constants';
 
 /**
@@ -49,6 +51,8 @@ export const buildLinearImageToImageGraph = (
     shouldUseCpuNoise,
     shouldUseNoiseSettings,
     vaePrecision,
+    seamlessXAxis,
+    seamlessYAxis,
   } = state.generation;
 
   // TODO: add batch functionality
@@ -80,6 +84,8 @@ export const buildLinearImageToImageGraph = (
     throw new Error('No model found in state');
   }
 
+  let modelLoaderNodeId = MAIN_MODEL_LOADER;
+
   const use_cpu = shouldUseNoiseSettings
     ? shouldUseCpuNoise
     : initialGenerationState.shouldUseCpuNoise;
@@ -88,9 +94,9 @@ export const buildLinearImageToImageGraph = (
   const graph: NonNullableGraph = {
     id: IMAGE_TO_IMAGE_GRAPH,
     nodes: {
-      [MAIN_MODEL_LOADER]: {
+      [modelLoaderNodeId]: {
         type: 'main_model_loader',
-        id: MAIN_MODEL_LOADER,
+        id: modelLoaderNodeId,
         model,
       },
       [CLIP_SKIP]: {
@@ -141,7 +147,7 @@ export const buildLinearImageToImageGraph = (
       // Connect Model Loader to UNet and CLIP Skip
       {
         source: {
-          node_id: MAIN_MODEL_LOADER,
+          node_id: modelLoaderNodeId,
           field: 'unet',
         },
         destination: {
@@ -151,7 +157,7 @@ export const buildLinearImageToImageGraph = (
       },
       {
         source: {
-          node_id: MAIN_MODEL_LOADER,
+          node_id: modelLoaderNodeId,
           field: 'clip',
         },
         destination: {
@@ -338,11 +344,17 @@ export const buildLinearImageToImageGraph = (
     },
   });
 
+  // Add Seamless To Graph
+  if (seamlessXAxis || seamlessYAxis) {
+    addSeamlessToLinearGraph(state, graph, modelLoaderNodeId);
+    modelLoaderNodeId = SEAMLESS;
+  }
+
   // optionally add custom VAE
-  addVAEToGraph(state, graph, MAIN_MODEL_LOADER);
+  addVAEToGraph(state, graph, modelLoaderNodeId);
 
   // add LoRA support
-  addLoRAsToGraph(state, graph, DENOISE_LATENTS);
+  addLoRAsToGraph(state, graph, DENOISE_LATENTS, modelLoaderNodeId);
 
   // add dynamic prompts - also sets up core iteration and seed
   addDynamicPromptsToGraph(state, graph);

invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildLinearSDXLImageToImageGraph.ts

@@ -11,6 +11,7 @@ import { addDynamicPromptsToGraph } from './addDynamicPromptsToGraph';
 import { addNSFWCheckerToGraph } from './addNSFWCheckerToGraph';
 import { addSDXLLoRAsToGraph } from './addSDXLLoRAstoGraph';
 import { addSDXLRefinerToGraph } from './addSDXLRefinerToGraph';
+import { addSeamlessToLinearGraph } from './addSeamlessToLinearGraph';
 import { addVAEToGraph } from './addVAEToGraph';
 import { addWatermarkerToGraph } from './addWatermarkerToGraph';
 import {
@@ -20,10 +21,12 @@ import {
   NEGATIVE_CONDITIONING,
   NOISE,
   POSITIVE_CONDITIONING,
+  REFINER_SEAMLESS,
   RESIZE,
   SDXL_DENOISE_LATENTS,
   SDXL_IMAGE_TO_IMAGE_GRAPH,
   SDXL_MODEL_LOADER,
+  SEAMLESS,
 } from './constants';
 import { craftSDXLStylePrompt } from './helpers/craftSDXLStylePrompt';
 
@@ -49,6 +52,8 @@ export const buildLinearSDXLImageToImageGraph = (
     shouldUseCpuNoise,
     shouldUseNoiseSettings,
     vaePrecision,
+    seamlessXAxis,
+    seamlessYAxis,
   } = state.generation;
 
   const {
@@ -79,6 +84,9 @@ export const buildLinearSDXLImageToImageGraph = (
     throw new Error('No model found in state');
   }
 
+  // Model Loader ID
+  let modelLoaderNodeId = SDXL_MODEL_LOADER;
+
   const use_cpu = shouldUseNoiseSettings
     ? shouldUseCpuNoise
     : initialGenerationState.shouldUseCpuNoise;
@@ -91,9 +99,9 @@ export const buildLinearSDXLImageToImageGraph = (
   const graph: NonNullableGraph = {
     id: SDXL_IMAGE_TO_IMAGE_GRAPH,
     nodes: {
-      [SDXL_MODEL_LOADER]: {
+      [modelLoaderNodeId]: {
         type: 'sdxl_model_loader',
-        id: SDXL_MODEL_LOADER,
+        id: modelLoaderNodeId,
         model,
       },
       [POSITIVE_CONDITIONING]: {
@@ -143,7 +151,7 @@ export const buildLinearSDXLImageToImageGraph = (
       // Connect Model Loader to UNet, CLIP & VAE
       {
         source: {
-          node_id: SDXL_MODEL_LOADER,
+          node_id: modelLoaderNodeId,
           field: 'unet',
         },
         destination: {
@@ -153,7 +161,7 @@ export const buildLinearSDXLImageToImageGraph = (
       },
       {
         source: {
-          node_id: SDXL_MODEL_LOADER,
+          node_id: modelLoaderNodeId,
           field: 'clip',
         },
         destination: {
@@ -163,7 +171,7 @@ export const buildLinearSDXLImageToImageGraph = (
       },
       {
         source: {
-          node_id: SDXL_MODEL_LOADER,
+          node_id: modelLoaderNodeId,
           field: 'clip2',
         },
         destination: {
@@ -173,7 +181,7 @@ export const buildLinearSDXLImageToImageGraph = (
       },
       {
         source: {
-          node_id: SDXL_MODEL_LOADER,
+          node_id: modelLoaderNodeId,
           field: 'clip',
         },
         destination: {
@@ -183,7 +191,7 @@ export const buildLinearSDXLImageToImageGraph = (
       },
       {
         source: {
-          node_id: SDXL_MODEL_LOADER,
+          node_id: modelLoaderNodeId,
           field: 'clip2',
         },
         destination: {
@@ -351,15 +359,23 @@ export const buildLinearSDXLImageToImageGraph = (
     },
   });
 
-  addSDXLLoRAsToGraph(state, graph, SDXL_DENOISE_LATENTS, SDXL_MODEL_LOADER);
+  // Add Seamless To Graph
+  if (seamlessXAxis || seamlessYAxis) {
+    addSeamlessToLinearGraph(state, graph, modelLoaderNodeId);
+    modelLoaderNodeId = SEAMLESS;
+  }
 
   // Add Refiner if enabled
   if (shouldUseSDXLRefiner) {
     addSDXLRefinerToGraph(state, graph, SDXL_DENOISE_LATENTS);
+    modelLoaderNodeId = REFINER_SEAMLESS;
   }
 
   // optionally add custom VAE
-  addVAEToGraph(state, graph, SDXL_MODEL_LOADER);
+  addVAEToGraph(state, graph, modelLoaderNodeId);
+
+  // Add LoRA Support
+  addSDXLLoRAsToGraph(state, graph, SDXL_DENOISE_LATENTS, modelLoaderNodeId);
 
   // add controlnet, mutating `graph`
   addControlNetToLinearGraph(state, graph, SDXL_DENOISE_LATENTS);

invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildLinearSDXLTextToImageGraph.ts

@@ -7,6 +7,7 @@ import { addDynamicPromptsToGraph } from './addDynamicPromptsToGraph';
 import { addNSFWCheckerToGraph } from './addNSFWCheckerToGraph';
 import { addSDXLLoRAsToGraph } from './addSDXLLoRAstoGraph';
 import { addSDXLRefinerToGraph } from './addSDXLRefinerToGraph';
+import { addSeamlessToLinearGraph } from './addSeamlessToLinearGraph';
 import { addVAEToGraph } from './addVAEToGraph';
 import { addWatermarkerToGraph } from './addWatermarkerToGraph';
 import {
@@ -15,9 +16,11 @@ import {
   NEGATIVE_CONDITIONING,
   NOISE,
   POSITIVE_CONDITIONING,
+  REFINER_SEAMLESS,
   SDXL_DENOISE_LATENTS,
   SDXL_MODEL_LOADER,
   SDXL_TEXT_TO_IMAGE_GRAPH,
+  SEAMLESS,
 } from './constants';
 import { craftSDXLStylePrompt } from './helpers/craftSDXLStylePrompt';
 
@@ -38,6 +41,8 @@ export const buildLinearSDXLTextToImageGraph = (
     shouldUseCpuNoise,
     shouldUseNoiseSettings,
     vaePrecision,
+    seamlessXAxis,
+    seamlessYAxis,
   } = state.generation;
 
   const {
@@ -61,6 +66,9 @@ export const buildLinearSDXLTextToImageGraph = (
   const { craftedPositiveStylePrompt, craftedNegativeStylePrompt } =
     craftSDXLStylePrompt(state, shouldConcatSDXLStylePrompt);
 
+  // Model Loader ID
+  let modelLoaderNodeId = SDXL_MODEL_LOADER;
+
   /**
    * The easiest way to build linear graphs is to do it in the node editor, then copy and paste the
    * full graph here as a template. Then use the parameters from app state and set friendlier node
@@ -74,9 +82,9 @@ export const buildLinearSDXLTextToImageGraph = (
   const graph: NonNullableGraph = {
     id: SDXL_TEXT_TO_IMAGE_GRAPH,
     nodes: {
-      [SDXL_MODEL_LOADER]: {
+      [modelLoaderNodeId]: {
         type: 'sdxl_model_loader',
-        id: SDXL_MODEL_LOADER,
+        id: modelLoaderNodeId,
         model,
       },
       [POSITIVE_CONDITIONING]: {
@@ -117,7 +125,7 @@ export const buildLinearSDXLTextToImageGraph = (
       // Connect Model Loader to UNet, VAE & CLIP
       {
         source: {
-          node_id: SDXL_MODEL_LOADER,
+          node_id: modelLoaderNodeId,
           field: 'unet',
         },
         destination: {
@@ -127,7 +135,7 @@ export const buildLinearSDXLTextToImageGraph = (
       },
       {
         source: {
-          node_id: SDXL_MODEL_LOADER,
+          node_id: modelLoaderNodeId,
           field: 'clip',
         },
         destination: {
@@ -137,7 +145,7 @@ export const buildLinearSDXLTextToImageGraph = (
       },
       {
         source: {
-          node_id: SDXL_MODEL_LOADER,
+          node_id: modelLoaderNodeId,
           field: 'clip2',
         },
         destination: {
@@ -147,7 +155,7 @@ export const buildLinearSDXLTextToImageGraph = (
       },
       {
         source: {
-          node_id: SDXL_MODEL_LOADER,
+          node_id: modelLoaderNodeId,
           field: 'clip',
         },
         destination: {
@@ -157,7 +165,7 @@ export const buildLinearSDXLTextToImageGraph = (
       },
       {
         source: {
-          node_id: SDXL_MODEL_LOADER,
+          node_id: modelLoaderNodeId,
           field: 'clip2',
         },
         destination: {
@@ -244,16 +252,23 @@ export const buildLinearSDXLTextToImageGraph = (
     },
   });
 
+  // Add Seamless To Graph
+  if (seamlessXAxis || seamlessYAxis) {
+    addSeamlessToLinearGraph(state, graph, modelLoaderNodeId);
+    modelLoaderNodeId = SEAMLESS;
+  }
+
   // Add Refiner if enabled
   if (shouldUseSDXLRefiner) {
     addSDXLRefinerToGraph(state, graph, SDXL_DENOISE_LATENTS);
+    modelLoaderNodeId = REFINER_SEAMLESS;
   }
 
   // optionally add custom VAE
-  addVAEToGraph(state, graph, SDXL_MODEL_LOADER);
+  addVAEToGraph(state, graph, modelLoaderNodeId);
 
   // add LoRA support
-  addSDXLLoRAsToGraph(state, graph, SDXL_DENOISE_LATENTS, SDXL_MODEL_LOADER);
+  addSDXLLoRAsToGraph(state, graph, SDXL_DENOISE_LATENTS, modelLoaderNodeId);
 
   // add controlnet, mutating `graph`
   addControlNetToLinearGraph(state, graph, SDXL_DENOISE_LATENTS);

invokeai/frontend/web/src/features/nodes/util/graphBuilders/buildLinearTextToImageGraph.ts

@@ -10,6 +10,7 @@ import { addControlNetToLinearGraph } from './addControlNetToLinearGraph';
 import { addDynamicPromptsToGraph } from './addDynamicPromptsToGraph';
 import { addLoRAsToGraph } from './addLoRAsToGraph';
 import { addNSFWCheckerToGraph } from './addNSFWCheckerToGraph';
+import { addSeamlessToLinearGraph } from './addSeamlessToLinearGraph';
 import { addVAEToGraph } from './addVAEToGraph';
 import { addWatermarkerToGraph } from './addWatermarkerToGraph';
 import {
@@ -22,6 +23,7 @@ import {
   NOISE,
   ONNX_MODEL_LOADER,
   POSITIVE_CONDITIONING,
+  SEAMLESS,
   TEXT_TO_IMAGE_GRAPH,
 } from './constants';
 
@@ -42,6 +44,8 @@ export const buildLinearTextToImageGraph = (
     shouldUseCpuNoise,
     shouldUseNoiseSettings,
     vaePrecision,
+    seamlessXAxis,
+    seamlessYAxis,
   } = state.generation;
 
   const use_cpu = shouldUseNoiseSettings
@@ -55,7 +59,7 @@ export const buildLinearTextToImageGraph = (
 
   const isUsingOnnxModel = model.model_type === 'onnx';
 
-  const modelLoaderNodeId = isUsingOnnxModel
+  let modelLoaderNodeId = isUsingOnnxModel
     ? ONNX_MODEL_LOADER
     : MAIN_MODEL_LOADER;
 
@@ -258,6 +262,12 @@ export const buildLinearTextToImageGraph = (
     },
   });
 
+  // Add Seamless To Graph
+  if (seamlessXAxis || seamlessYAxis) {
+    addSeamlessToLinearGraph(state, graph, modelLoaderNodeId);
+    modelLoaderNodeId = SEAMLESS;
+  }
+
   // optionally add custom VAE
   addVAEToGraph(state, graph, modelLoaderNodeId);
 

invokeai/frontend/web/src/features/nodes/util/graphBuilders/constants.ts

@@ -56,6 +56,8 @@ export const SDXL_REFINER_POSITIVE_CONDITIONING =
 export const SDXL_REFINER_NEGATIVE_CONDITIONING =
   'sdxl_refiner_negative_conditioning';
 export const SDXL_REFINER_DENOISE_LATENTS = 'sdxl_refiner_denoise_latents';
+export const SEAMLESS = 'seamless';
+export const REFINER_SEAMLESS = 'refiner_seamless';
 
 // friendly graph ids
 export const TEXT_TO_IMAGE_GRAPH = 'text_to_image_graph';

invokeai/frontend/web/src/features/parameters/hooks/usePreselectedImage.ts

@@ -0,0 +1,81 @@
+import { skipToken } from '@reduxjs/toolkit/dist/query';
+import { t } from 'i18next';
+import { useCallback, useState } from 'react';
+import { useAppToaster } from '../../../app/components/Toaster';
+import { useAppDispatch } from '../../../app/store/storeHooks';
+import {
+  useGetImageDTOQuery,
+  useGetImageMetadataQuery,
+} from '../../../services/api/endpoints/images';
+import { setInitialCanvasImage } from '../../canvas/store/canvasSlice';
+import { setActiveTab } from '../../ui/store/uiSlice';
+import { initialImageSelected } from '../store/actions';
+import { useRecallParameters } from './useRecallParameters';
+
+type SelectedImage = {
+  imageName: string;
+  action: 'sendToImg2Img' | 'sendToCanvas' | 'useAllParameters';
+};
+
+export const usePreselectedImage = () => {
+  const dispatch = useAppDispatch();
+  const [imageNameForDto, setImageNameForDto] = useState<string | undefined>();
+  const [imageNameForMetadata, setImageNameForMetadata] = useState<
+    string | undefined
+  >();
+  const { recallAllParameters } = useRecallParameters();
+  const toaster = useAppToaster();
+
+  const { currentData: selectedImageDto } = useGetImageDTOQuery(
+    imageNameForDto ?? skipToken
+  );
+
+  const { currentData: selectedImageMetadata } = useGetImageMetadataQuery(
+    imageNameForMetadata ?? skipToken
+  );
+
+  const handlePreselectedImage = useCallback(
+    (selectedImage?: SelectedImage) => {
+      if (!selectedImage) {
+        return;
+      }
+
+      if (selectedImage.action === 'sendToCanvas') {
+        setImageNameForDto(selectedImage?.imageName);
+        if (selectedImageDto) {
+          dispatch(setInitialCanvasImage(selectedImageDto));
+          dispatch(setActiveTab('unifiedCanvas'));
+          toaster({
+            title: t('toast.sentToUnifiedCanvas'),
+            status: 'info',
+            duration: 2500,
+            isClosable: true,
+          });
+        }
+      }
+
+      if (selectedImage.action === 'sendToImg2Img') {
+        setImageNameForDto(selectedImage?.imageName);
+        if (selectedImageDto) {
+          dispatch(initialImageSelected(selectedImageDto));
+        }
+      }
+
+      if (selectedImage.action === 'useAllParameters') {
+        setImageNameForMetadata(selectedImage?.imageName);
+        if (selectedImageMetadata) {
+          recallAllParameters(selectedImageMetadata.metadata);
+        }
+      }
+    },
+    [
+      dispatch,
+      selectedImageDto,
+      selectedImageMetadata,
+      recallAllParameters,
+      toaster,
+    ]
+  );
+
+  return { handlePreselectedImage };
+};

invokeai/frontend/web/src/features/sdxl/components/SDXLImageToImageTabParameters.tsx

@@ -2,6 +2,7 @@ import ParamDynamicPromptsCollapse from 'features/dynamicPrompts/components/Para
 import ParamLoraCollapse from 'features/lora/components/ParamLoraCollapse';
 import ParamControlNetCollapse from 'features/parameters/components/Parameters/ControlNet/ParamControlNetCollapse';
 import ParamNoiseCollapse from 'features/parameters/components/Parameters/Noise/ParamNoiseCollapse';
+import ParamSeamlessCollapse from 'features/parameters/components/Parameters/Seamless/ParamSeamlessCollapse';
 import { memo } from 'react';
 import ParamSDXLPromptArea from './ParamSDXLPromptArea';
 import ParamSDXLRefinerCollapse from './ParamSDXLRefinerCollapse';
@@ -17,6 +18,7 @@ const SDXLImageToImageTabParameters = () => {
       <ParamLoraCollapse />
       <ParamDynamicPromptsCollapse />
       <ParamNoiseCollapse />
+      <ParamSeamlessCollapse />
     </>
   );
 };

invokeai/frontend/web/src/features/sdxl/components/SDXLTextToImageTabParameters.tsx

@@ -2,6 +2,7 @@ import ParamDynamicPromptsCollapse from 'features/dynamicPrompts/components/Para
 import ParamLoraCollapse from 'features/lora/components/ParamLoraCollapse';
 import ParamControlNetCollapse from 'features/parameters/components/Parameters/ControlNet/ParamControlNetCollapse';
 import ParamNoiseCollapse from 'features/parameters/components/Parameters/Noise/ParamNoiseCollapse';
+import ParamSeamlessCollapse from 'features/parameters/components/Parameters/Seamless/ParamSeamlessCollapse';
 import TextToImageTabCoreParameters from 'features/ui/components/tabs/TextToImage/TextToImageTabCoreParameters';
 import { memo } from 'react';
 import ParamSDXLPromptArea from './ParamSDXLPromptArea';
@@ -17,6 +18,7 @@ const SDXLTextToImageTabParameters = () => {
       <ParamLoraCollapse />
       <ParamDynamicPromptsCollapse />
       <ParamNoiseCollapse />
+      <ParamSeamlessCollapse />
     </>
   );
 };

invokeai/frontend/web/src/features/sdxl/components/SDXLUnifiedCanvasTabParameters.tsx

@@ -5,6 +5,7 @@ import ParamMaskAdjustmentCollapse from 'features/parameters/components/Paramete
 import ParamCanvasCoherencePassCollapse from 'features/parameters/components/Parameters/Canvas/SeamPainting/ParamCanvasCoherencePassCollapse';
 import ParamControlNetCollapse from 'features/parameters/components/Parameters/ControlNet/ParamControlNetCollapse';
 import ParamNoiseCollapse from 'features/parameters/components/Parameters/Noise/ParamNoiseCollapse';
+import ParamSeamlessCollapse from 'features/parameters/components/Parameters/Seamless/ParamSeamlessCollapse';
 import ParamSDXLPromptArea from './ParamSDXLPromptArea';
 import ParamSDXLRefinerCollapse from './ParamSDXLRefinerCollapse';
 import SDXLUnifiedCanvasTabCoreParameters from './SDXLUnifiedCanvasTabCoreParameters';
@@ -22,6 +23,7 @@ export default function SDXLUnifiedCanvasTabParameters() {
       <ParamMaskAdjustmentCollapse />
       <ParamInfillAndScalingCollapse />
       <ParamCanvasCoherencePassCollapse />
+      <ParamSeamlessCollapse />
     </>
   );
 }

invokeai/frontend/web/src/features/system/store/configSlice.ts

@@ -9,7 +9,6 @@ export const initialConfigState: AppConfig = {
   disabledFeatures: ['lightbox', 'faceRestore', 'batches'],
   disabledSDFeatures: [
     'variation',
-    'seamless',
     'symmetry',
     'hires',
     'perlinNoise',

invokeai/frontend/web/src/features/ui/components/tabs/UnifiedCanvas/UnifiedCanvasParameters.tsx

@@ -6,6 +6,7 @@ import ParamMaskAdjustmentCollapse from 'features/parameters/components/Paramete
 import ParamCanvasCoherencePassCollapse from 'features/parameters/components/Parameters/Canvas/SeamPainting/ParamCanvasCoherencePassCollapse';
 import ParamControlNetCollapse from 'features/parameters/components/Parameters/ControlNet/ParamControlNetCollapse';
 import ParamPromptArea from 'features/parameters/components/Parameters/Prompt/ParamPromptArea';
+import ParamSeamlessCollapse from 'features/parameters/components/Parameters/Seamless/ParamSeamlessCollapse';
 import ParamSymmetryCollapse from 'features/parameters/components/Parameters/Symmetry/ParamSymmetryCollapse';
 import { memo } from 'react';
 import UnifiedCanvasCoreParameters from './UnifiedCanvasCoreParameters';
@@ -22,6 +23,7 @@ const UnifiedCanvasParameters = () => {
       <ParamMaskAdjustmentCollapse />
       <ParamInfillAndScalingCollapse />
       <ParamCanvasCoherencePassCollapse />
+      <ParamSeamlessCollapse />
       <ParamAdvancedCollapse />
     </>
   );

invokeai/frontend/web/src/services/api/types.ts

@@ -130,6 +130,7 @@ 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'];
 
 // ControlNet Nodes
 export type ControlNetInvocation = s['ControlNetInvocation'];