feat: add 'project' workflow category

* dont set socketURL until socket is initialized

* cleanup

* feat(ui): simplify `socketUrl` memo

no need to mutate the string; just return early if using baseUrl

---------

Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
Co-authored-by: psychedelicious <4822129+psychedelicious@users.noreply.github.com>

docs/features/PROMPTS.md

@@ -120,7 +120,7 @@ Generate an image with a given prompt, record the seed of the image, and then
 use the `prompt2prompt` syntax to substitute words in the original prompt for
 words in a new prompt. This works for `img2img` as well.
 
-For example, consider the prompt `a cat.swap(dog) playing with a ball in the forest`. Normally, because of the word words interact with each other when doing a stable diffusion image generation, these two prompts would generate different compositions:
+For example, consider the prompt `a cat.swap(dog) playing with a ball in the forest`. Normally, because the words interact with each other when doing a stable diffusion image generation, these two prompts would generate different compositions:
   - `a cat playing with a ball in the forest`
   - `a dog playing with a ball in the forest`
 

invokeai/app/api/dependencies.py

@@ -2,7 +2,6 @@
 
 from logging import Logger
 
-from invokeai.app.services.workflow_image_records.workflow_image_records_sqlite import SqliteWorkflowImageRecordsStorage
 from invokeai.backend.util.logging import InvokeAILogger
 from invokeai.version.invokeai_version import __version__
 
@@ -30,7 +29,7 @@ from ..services.session_processor.session_processor_default import DefaultSessio
 from ..services.session_queue.session_queue_sqlite import SqliteSessionQueue
 from ..services.shared.default_graphs import create_system_graphs
 from ..services.shared.graph import GraphExecutionState, LibraryGraph
-from ..services.shared.sqlite import SqliteDatabase
+from ..services.shared.sqlite.sqlite_database import SqliteDatabase
 from ..services.urls.urls_default import LocalUrlService
 from ..services.workflow_records.workflow_records_sqlite import SqliteWorkflowRecordsStorage
 from .events import FastAPIEventService
@@ -94,7 +93,6 @@ class ApiDependencies:
         session_processor = DefaultSessionProcessor()
         session_queue = SqliteSessionQueue(db=db)
         urls = LocalUrlService()
-        workflow_image_records = SqliteWorkflowImageRecordsStorage(db=db)
         workflow_records = SqliteWorkflowRecordsStorage(db=db)
 
         services = InvocationServices(
@@ -121,14 +119,12 @@ class ApiDependencies:
             session_processor=session_processor,
             session_queue=session_queue,
             urls=urls,
-            workflow_image_records=workflow_image_records,
             workflow_records=workflow_records,
         )
 
         create_system_graphs(services.graph_library)
 
         ApiDependencies.invoker = Invoker(services)
-
         db.clean()
 
     @staticmethod

invokeai/app/api/routers/app_info.py

@@ -1,7 +1,11 @@
 import typing
 from enum import Enum
+from importlib.metadata import PackageNotFoundError, version
 from pathlib import Path
+from platform import python_version
+from typing import Optional
 
+import torch
 from fastapi import Body
 from fastapi.routing import APIRouter
 from pydantic import BaseModel, Field
@@ -40,6 +44,24 @@ class AppVersion(BaseModel):
     version: str = Field(description="App version")
 
 
+class AppDependencyVersions(BaseModel):
+    """App depencency Versions Response"""
+
+    accelerate: str = Field(description="accelerate version")
+    compel: str = Field(description="compel version")
+    cuda: Optional[str] = Field(description="CUDA version")
+    diffusers: str = Field(description="diffusers version")
+    numpy: str = Field(description="Numpy version")
+    opencv: str = Field(description="OpenCV version")
+    onnx: str = Field(description="ONNX version")
+    pillow: str = Field(description="Pillow (PIL) version")
+    python: str = Field(description="Python version")
+    torch: str = Field(description="PyTorch version")
+    torchvision: str = Field(description="PyTorch Vision version")
+    transformers: str = Field(description="transformers version")
+    xformers: Optional[str] = Field(description="xformers version")
+
+
 class AppConfig(BaseModel):
     """App Config Response"""
 
@@ -54,6 +76,29 @@ async def get_version() -> AppVersion:
     return AppVersion(version=__version__)
 
 
+@app_router.get("/app_deps", operation_id="get_app_deps", status_code=200, response_model=AppDependencyVersions)
+async def get_app_deps() -> AppDependencyVersions:
+    try:
+        xformers = version("xformers")
+    except PackageNotFoundError:
+        xformers = None
+    return AppDependencyVersions(
+        accelerate=version("accelerate"),
+        compel=version("compel"),
+        cuda=torch.version.cuda,
+        diffusers=version("diffusers"),
+        numpy=version("numpy"),
+        opencv=version("opencv-python"),
+        onnx=version("onnx"),
+        pillow=version("pillow"),
+        python=python_version(),
+        torch=torch.version.__version__,
+        torchvision=version("torchvision"),
+        transformers=version("transformers"),
+        xformers=xformers,
+    )
+
+
 @app_router.get("/config", operation_id="get_config", status_code=200, response_model=AppConfig)
 async def get_config() -> AppConfig:
     infill_methods = ["tile", "lama", "cv2"]

invokeai/app/api/routers/images.py

@@ -8,10 +8,11 @@ from fastapi.routing import APIRouter
 from PIL import Image
 from pydantic import BaseModel, Field, ValidationError
 
-from invokeai.app.invocations.baseinvocation import MetadataField, MetadataFieldValidator, WorkflowFieldValidator
+from invokeai.app.invocations.baseinvocation 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
+from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID, WorkflowWithoutIDValidator
 
 from ..dependencies import ApiDependencies
 
@@ -73,7 +74,7 @@ async def upload_image(
     workflow_raw = pil_image.info.get("invokeai_workflow", None)
     if workflow_raw is not None:
         try:
-            workflow = WorkflowFieldValidator.validate_json(workflow_raw)
+            workflow = WorkflowWithoutIDValidator.validate_json(workflow_raw)
         except ValidationError:
             ApiDependencies.invoker.services.logger.warn("Failed to parse metadata for uploaded image")
             pass
@@ -184,6 +185,18 @@ async def get_image_metadata(
         raise HTTPException(status_code=404)
 
 
+@images_router.get(
+    "/i/{image_name}/workflow", operation_id="get_image_workflow", response_model=Optional[WorkflowWithoutID]
+)
+async def get_image_workflow(
+    image_name: str = Path(description="The name of image whose workflow to get"),
+) -> Optional[WorkflowWithoutID]:
+    try:
+        return ApiDependencies.invoker.services.images.get_workflow(image_name)
+    except Exception:
+        raise HTTPException(status_code=404)
+
+
 @images_router.api_route(
     "/i/{image_name}/full",
     methods=["GET", "HEAD"],

invokeai/app/api/routers/model_records.py

@@ -141,7 +141,7 @@ 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")],
 ) -> AnyModelConfig:
     """
     Add a model using the configuration information appropriate for its type.

invokeai/app/api/routers/workflows.py

@@ -1,7 +1,19 @@
-from fastapi import APIRouter, Path
+from typing import Optional
+
+from fastapi import APIRouter, Body, HTTPException, Path, Query
 
 from invokeai.app.api.dependencies import ApiDependencies
-from invokeai.app.invocations.baseinvocation import WorkflowField
+from invokeai.app.services.shared.pagination import PaginatedResults
+from invokeai.app.services.shared.sqlite.sqlite_common import SQLiteDirection
+from invokeai.app.services.workflow_records.workflow_records_common import (
+    Workflow,
+    WorkflowCategory,
+    WorkflowNotFoundError,
+    WorkflowRecordDTO,
+    WorkflowRecordListItemDTO,
+    WorkflowRecordOrderBy,
+    WorkflowWithoutID,
+)
 
 workflows_router = APIRouter(prefix="/v1/workflows", tags=["workflows"])
 
@@ -10,11 +22,76 @@ workflows_router = APIRouter(prefix="/v1/workflows", tags=["workflows"])
     "/i/{workflow_id}",
     operation_id="get_workflow",
     responses={
-        200: {"model": WorkflowField},
+        200: {"model": WorkflowRecordDTO},
     },
 )
 async def get_workflow(
     workflow_id: str = Path(description="The workflow to get"),
-) -> WorkflowField:
+) -> WorkflowRecordDTO:
     """Gets a workflow"""
-    return ApiDependencies.invoker.services.workflow_records.get(workflow_id)
+    try:
+        return ApiDependencies.invoker.services.workflow_records.get(workflow_id)
+    except WorkflowNotFoundError:
+        raise HTTPException(status_code=404, detail="Workflow not found")
+
+
+@workflows_router.patch(
+    "/i/{workflow_id}",
+    operation_id="update_workflow",
+    responses={
+        200: {"model": WorkflowRecordDTO},
+    },
+)
+async def update_workflow(
+    workflow: Workflow = Body(description="The updated workflow", embed=True),
+) -> WorkflowRecordDTO:
+    """Updates a workflow"""
+    return ApiDependencies.invoker.services.workflow_records.update(workflow=workflow)
+
+
+@workflows_router.delete(
+    "/i/{workflow_id}",
+    operation_id="delete_workflow",
+)
+async def delete_workflow(
+    workflow_id: str = Path(description="The workflow to delete"),
+) -> None:
+    """Deletes a workflow"""
+    ApiDependencies.invoker.services.workflow_records.delete(workflow_id)
+
+
+@workflows_router.post(
+    "/",
+    operation_id="create_workflow",
+    responses={
+        200: {"model": WorkflowRecordDTO},
+    },
+)
+async def create_workflow(
+    workflow: WorkflowWithoutID = Body(description="The workflow to create", embed=True),
+) -> WorkflowRecordDTO:
+    """Creates a workflow"""
+    return ApiDependencies.invoker.services.workflow_records.create(workflow=workflow)
+
+
+@workflows_router.get(
+    "/",
+    operation_id="list_workflows",
+    responses={
+        200: {"model": PaginatedResults[WorkflowRecordListItemDTO]},
+    },
+)
+async def list_workflows(
+    page: int = Query(default=0, description="The page to get"),
+    per_page: int = Query(default=10, description="The number of workflows per page"),
+    order_by: WorkflowRecordOrderBy = Query(
+        default=WorkflowRecordOrderBy.Name, description="The attribute to order by"
+    ),
+    direction: SQLiteDirection = Query(default=SQLiteDirection.Ascending, description="The direction to order by"),
+    category: WorkflowCategory = Query(default=WorkflowCategory.User, description="The category of workflow to get"),
+    query: Optional[str] = Query(default=None, description="The text to query by (matches name and description)"),
+) -> PaginatedResults[WorkflowRecordListItemDTO]:
+    """Gets a page of workflows"""
+    return ApiDependencies.invoker.services.workflow_records.get_many(
+        page=page, per_page=per_page, order_by=order_by, direction=direction, query=query, category=category
+    )

invokeai/app/invocations/baseinvocation.py

@@ -16,6 +16,7 @@ from pydantic.fields import FieldInfo, _Unset
 from pydantic_core import PydanticUndefined
 
 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.util.metaenum import MetaEnum
 from invokeai.app.util.misc import uuid_string
@@ -452,6 +453,7 @@ class InvocationContext:
     queue_id: str
     queue_item_id: int
     queue_batch_id: str
+    workflow: Optional[WorkflowWithoutID]
 
     def __init__(
         self,
@@ -460,12 +462,14 @@ class InvocationContext:
         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):
@@ -807,9 +811,9 @@ def invocation(
         cls.UIConfig.category = category
 
         # Grab the node pack's name from the module name, if it's a custom node
-        module_name = cls.__module__.split(".")[0]
-        if module_name.endswith(CUSTOM_NODE_PACK_SUFFIX):
-            cls.UIConfig.node_pack = module_name.split(CUSTOM_NODE_PACK_SUFFIX)[0]
+        is_custom_node = cls.__module__.rsplit(".", 1)[0] == "invokeai.app.invocations"
+        if is_custom_node:
+            cls.UIConfig.node_pack = cls.__module__.split(".")[0]
         else:
             cls.UIConfig.node_pack = None
 
@@ -903,24 +907,6 @@ def invocation_output(
     return wrapper
 
 
-class WorkflowField(RootModel):
-    """
-    Pydantic model for workflows with custom root of type dict[str, Any].
-    Workflows are stored without a strict schema.
-    """
-
-    root: dict[str, Any] = Field(description="The workflow")
-
-
-WorkflowFieldValidator = TypeAdapter(WorkflowField)
-
-
-class WithWorkflow(BaseModel):
-    workflow: Optional[WorkflowField] = Field(
-        default=None, description=FieldDescriptions.workflow, json_schema_extra={"field_kind": FieldKind.NodeAttribute}
-    )
-
-
 class MetadataField(RootModel):
     """
     Pydantic model for metadata with custom root of type dict[str, Any].
@@ -943,3 +929,13 @@ class WithMetadata(BaseModel):
             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__()

invokeai/app/invocations/controlnet_image_processors.py

@@ -39,7 +39,6 @@ from .baseinvocation import (
     InvocationContext,
     OutputField,
     WithMetadata,
-    WithWorkflow,
     invocation,
     invocation_output,
 )
@@ -129,7 +128,7 @@ class ControlNetInvocation(BaseInvocation):
 
 
 # This invocation exists for other invocations to subclass it - do not register with @invocation!
-class ImageProcessorInvocation(BaseInvocation, WithMetadata, WithWorkflow):
+class ImageProcessorInvocation(BaseInvocation, WithMetadata):
     """Base class for invocations that preprocess images for ControlNet"""
 
     image: ImageField = InputField(description="The image to process")
@@ -153,7 +152,7 @@ class ImageProcessorInvocation(BaseInvocation, WithMetadata, WithWorkflow):
             node_id=self.id,
             is_intermediate=self.is_intermediate,
             metadata=self.metadata,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         """Builds an ImageOutput and its ImageField"""
@@ -173,7 +172,7 @@ class ImageProcessorInvocation(BaseInvocation, WithMetadata, WithWorkflow):
     title="Canny Processor",
     tags=["controlnet", "canny"],
     category="controlnet",
-    version="1.1.0",
+    version="1.2.0",
 )
 class CannyImageProcessorInvocation(ImageProcessorInvocation):
     """Canny edge detection for ControlNet"""
@@ -196,7 +195,7 @@ class CannyImageProcessorInvocation(ImageProcessorInvocation):
     title="HED (softedge) Processor",
     tags=["controlnet", "hed", "softedge"],
     category="controlnet",
-    version="1.1.0",
+    version="1.2.0",
 )
 class HedImageProcessorInvocation(ImageProcessorInvocation):
     """Applies HED edge detection to image"""
@@ -225,7 +224,7 @@ class HedImageProcessorInvocation(ImageProcessorInvocation):
     title="Lineart Processor",
     tags=["controlnet", "lineart"],
     category="controlnet",
-    version="1.1.0",
+    version="1.2.0",
 )
 class LineartImageProcessorInvocation(ImageProcessorInvocation):
     """Applies line art processing to image"""
@@ -247,7 +246,7 @@ class LineartImageProcessorInvocation(ImageProcessorInvocation):
     title="Lineart Anime Processor",
     tags=["controlnet", "lineart", "anime"],
     category="controlnet",
-    version="1.1.0",
+    version="1.2.0",
 )
 class LineartAnimeImageProcessorInvocation(ImageProcessorInvocation):
     """Applies line art anime processing to image"""
@@ -270,7 +269,7 @@ class LineartAnimeImageProcessorInvocation(ImageProcessorInvocation):
     title="Openpose Processor",
     tags=["controlnet", "openpose", "pose"],
     category="controlnet",
-    version="1.1.0",
+    version="1.2.0",
 )
 class OpenposeImageProcessorInvocation(ImageProcessorInvocation):
     """Applies Openpose processing to image"""
@@ -295,7 +294,7 @@ class OpenposeImageProcessorInvocation(ImageProcessorInvocation):
     title="Midas Depth Processor",
     tags=["controlnet", "midas"],
     category="controlnet",
-    version="1.1.0",
+    version="1.2.0",
 )
 class MidasDepthImageProcessorInvocation(ImageProcessorInvocation):
     """Applies Midas depth processing to image"""
@@ -322,7 +321,7 @@ class MidasDepthImageProcessorInvocation(ImageProcessorInvocation):
     title="Normal BAE Processor",
     tags=["controlnet"],
     category="controlnet",
-    version="1.1.0",
+    version="1.2.0",
 )
 class NormalbaeImageProcessorInvocation(ImageProcessorInvocation):
     """Applies NormalBae processing to image"""
@@ -339,7 +338,7 @@ class NormalbaeImageProcessorInvocation(ImageProcessorInvocation):
 
 
 @invocation(
-    "mlsd_image_processor", title="MLSD Processor", tags=["controlnet", "mlsd"], category="controlnet", version="1.1.0"
+    "mlsd_image_processor", title="MLSD Processor", tags=["controlnet", "mlsd"], category="controlnet", version="1.2.0"
 )
 class MlsdImageProcessorInvocation(ImageProcessorInvocation):
     """Applies MLSD processing to image"""
@@ -362,7 +361,7 @@ class MlsdImageProcessorInvocation(ImageProcessorInvocation):
 
 
 @invocation(
-    "pidi_image_processor", title="PIDI Processor", tags=["controlnet", "pidi"], category="controlnet", version="1.1.0"
+    "pidi_image_processor", title="PIDI Processor", tags=["controlnet", "pidi"], category="controlnet", version="1.2.0"
 )
 class PidiImageProcessorInvocation(ImageProcessorInvocation):
     """Applies PIDI processing to image"""
@@ -389,7 +388,7 @@ class PidiImageProcessorInvocation(ImageProcessorInvocation):
     title="Content Shuffle Processor",
     tags=["controlnet", "contentshuffle"],
     category="controlnet",
-    version="1.1.0",
+    version="1.2.0",
 )
 class ContentShuffleImageProcessorInvocation(ImageProcessorInvocation):
     """Applies content shuffle processing to image"""
@@ -419,7 +418,7 @@ class ContentShuffleImageProcessorInvocation(ImageProcessorInvocation):
     title="Zoe (Depth) Processor",
     tags=["controlnet", "zoe", "depth"],
     category="controlnet",
-    version="1.1.0",
+    version="1.2.0",
 )
 class ZoeDepthImageProcessorInvocation(ImageProcessorInvocation):
     """Applies Zoe depth processing to image"""
@@ -435,7 +434,7 @@ class ZoeDepthImageProcessorInvocation(ImageProcessorInvocation):
     title="Mediapipe Face Processor",
     tags=["controlnet", "mediapipe", "face"],
     category="controlnet",
-    version="1.1.0",
+    version="1.2.0",
 )
 class MediapipeFaceProcessorInvocation(ImageProcessorInvocation):
     """Applies mediapipe face processing to image"""
@@ -458,7 +457,7 @@ class MediapipeFaceProcessorInvocation(ImageProcessorInvocation):
     title="Leres (Depth) Processor",
     tags=["controlnet", "leres", "depth"],
     category="controlnet",
-    version="1.1.0",
+    version="1.2.0",
 )
 class LeresImageProcessorInvocation(ImageProcessorInvocation):
     """Applies leres processing to image"""
@@ -487,7 +486,7 @@ class LeresImageProcessorInvocation(ImageProcessorInvocation):
     title="Tile Resample Processor",
     tags=["controlnet", "tile"],
     category="controlnet",
-    version="1.1.0",
+    version="1.2.0",
 )
 class TileResamplerProcessorInvocation(ImageProcessorInvocation):
     """Tile resampler processor"""
@@ -527,7 +526,7 @@ class TileResamplerProcessorInvocation(ImageProcessorInvocation):
     title="Segment Anything Processor",
     tags=["controlnet", "segmentanything"],
     category="controlnet",
-    version="1.1.0",
+    version="1.2.0",
 )
 class SegmentAnythingProcessorInvocation(ImageProcessorInvocation):
     """Applies segment anything processing to image"""
@@ -569,7 +568,7 @@ class SamDetectorReproducibleColors(SamDetector):
     title="Color Map Processor",
     tags=["controlnet"],
     category="controlnet",
-    version="1.1.0",
+    version="1.2.0",
 )
 class ColorMapImageProcessorInvocation(ImageProcessorInvocation):
     """Generates a color map from the provided image"""

invokeai/app/invocations/custom_nodes/init.py

@@ -6,7 +6,6 @@ import sys
 from importlib.util import module_from_spec, spec_from_file_location
 from pathlib import Path
 
-from invokeai.app.invocations.baseinvocation import CUSTOM_NODE_PACK_SUFFIX
 from invokeai.backend.util.logging import InvokeAILogger
 
 logger = InvokeAILogger.get_logger()
@@ -34,7 +33,7 @@ for d in Path(__file__).parent.iterdir():
         continue
 
     # load the module, appending adding a suffix to identify it as a custom node pack
-    spec = spec_from_file_location(f"{module_name}{CUSTOM_NODE_PACK_SUFFIX}", init.absolute())
+    spec = spec_from_file_location(module_name, init.absolute())
 
     if spec is None or spec.loader is None:
         logger.warn(f"Could not load {init}")

invokeai/app/invocations/cv.py

@@ -8,11 +8,11 @@ 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, WithWorkflow, invocation
+from .baseinvocation import BaseInvocation, InputField, InvocationContext, WithMetadata, invocation
 
 
-@invocation("cv_inpaint", title="OpenCV Inpaint", tags=["opencv", "inpaint"], category="inpaint", version="1.1.0")
-class CvInpaintInvocation(BaseInvocation, WithMetadata, WithWorkflow):
+@invocation("cv_inpaint", title="OpenCV Inpaint", tags=["opencv", "inpaint"], category="inpaint", version="1.2.0")
+class CvInpaintInvocation(BaseInvocation, WithMetadata):
     """Simple inpaint using opencv."""
 
     image: ImageField = InputField(description="The image to inpaint")
@@ -41,7 +41,7 @@ class CvInpaintInvocation(BaseInvocation, WithMetadata, WithWorkflow):
             node_id=self.id,
             session_id=context.graph_execution_state_id,
             is_intermediate=self.is_intermediate,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         return ImageOutput(

invokeai/app/invocations/facetools.py

@@ -17,7 +17,6 @@ from invokeai.app.invocations.baseinvocation import (
     InvocationContext,
     OutputField,
     WithMetadata,
-    WithWorkflow,
     invocation,
     invocation_output,
 )
@@ -438,8 +437,8 @@ def get_faces_list(
     return all_faces
 
 
-@invocation("face_off", title="FaceOff", tags=["image", "faceoff", "face", "mask"], category="image", version="1.1.0")
-class FaceOffInvocation(BaseInvocation, WithWorkflow, WithMetadata):
+@invocation("face_off", title="FaceOff", tags=["image", "faceoff", "face", "mask"], category="image", version="1.2.0")
+class FaceOffInvocation(BaseInvocation, WithMetadata):
     """Bound, extract, and mask a face from an image using MediaPipe detection"""
 
     image: ImageField = InputField(description="Image for face detection")
@@ -508,7 +507,7 @@ class FaceOffInvocation(BaseInvocation, WithWorkflow, WithMetadata):
             node_id=self.id,
             session_id=context.graph_execution_state_id,
             is_intermediate=self.is_intermediate,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         mask_dto = context.services.images.create(
@@ -532,8 +531,8 @@ class FaceOffInvocation(BaseInvocation, WithWorkflow, WithMetadata):
         return output
 
 
-@invocation("face_mask_detection", title="FaceMask", tags=["image", "face", "mask"], category="image", version="1.1.0")
-class FaceMaskInvocation(BaseInvocation, WithWorkflow, WithMetadata):
+@invocation("face_mask_detection", title="FaceMask", tags=["image", "face", "mask"], category="image", version="1.2.0")
+class FaceMaskInvocation(BaseInvocation, WithMetadata):
     """Face mask creation using mediapipe face detection"""
 
     image: ImageField = InputField(description="Image to face detect")
@@ -627,7 +626,7 @@ class FaceMaskInvocation(BaseInvocation, WithWorkflow, WithMetadata):
             node_id=self.id,
             session_id=context.graph_execution_state_id,
             is_intermediate=self.is_intermediate,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         mask_dto = context.services.images.create(
@@ -650,9 +649,9 @@ class FaceMaskInvocation(BaseInvocation, WithWorkflow, WithMetadata):
 
 
 @invocation(
-    "face_identifier", title="FaceIdentifier", tags=["image", "face", "identifier"], category="image", version="1.1.0"
+    "face_identifier", title="FaceIdentifier", tags=["image", "face", "identifier"], category="image", version="1.2.0"
 )
-class FaceIdentifierInvocation(BaseInvocation, WithWorkflow, WithMetadata):
+class FaceIdentifierInvocation(BaseInvocation, WithMetadata):
     """Outputs an image with detected face IDs printed on each face. For use with other FaceTools."""
 
     image: ImageField = InputField(description="Image to face detect")
@@ -716,7 +715,7 @@ class FaceIdentifierInvocation(BaseInvocation, WithWorkflow, WithMetadata):
             node_id=self.id,
             session_id=context.graph_execution_state_id,
             is_intermediate=self.is_intermediate,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         return ImageOutput(

invokeai/app/invocations/image.py

@@ -13,7 +13,7 @@ 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, Input, InputField, InvocationContext, WithMetadata, WithWorkflow, invocation
+from .baseinvocation import BaseInvocation, Input, InputField, InvocationContext, WithMetadata, invocation
 
 
 @invocation("show_image", title="Show Image", tags=["image"], category="image", version="1.0.0")
@@ -36,8 +36,14 @@ class ShowImageInvocation(BaseInvocation):
         )
 
 
-@invocation("blank_image", title="Blank Image", tags=["image"], category="image", version="1.1.0")
-class BlankImageInvocation(BaseInvocation, WithMetadata, WithWorkflow):
+@invocation(
+    "blank_image",
+    title="Blank Image",
+    tags=["image"],
+    category="image",
+    version="1.2.0",
+)
+class BlankImageInvocation(BaseInvocation, WithMetadata):
     """Creates a blank image and forwards it to the pipeline"""
 
     width: int = InputField(default=512, description="The width of the image")
@@ -56,7 +62,7 @@ class BlankImageInvocation(BaseInvocation, WithMetadata, WithWorkflow):
             session_id=context.graph_execution_state_id,
             is_intermediate=self.is_intermediate,
             metadata=self.metadata,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         return ImageOutput(
@@ -66,8 +72,14 @@ class BlankImageInvocation(BaseInvocation, WithMetadata, WithWorkflow):
         )
 
 
-@invocation("img_crop", title="Crop Image", tags=["image", "crop"], category="image", version="1.1.0")
-class ImageCropInvocation(BaseInvocation, WithWorkflow, WithMetadata):
+@invocation(
+    "img_crop",
+    title="Crop Image",
+    tags=["image", "crop"],
+    category="image",
+    version="1.2.0",
+)
+class ImageCropInvocation(BaseInvocation, WithMetadata):
     """Crops an image to a specified box. The box can be outside of the image."""
 
     image: ImageField = InputField(description="The image to crop")
@@ -90,7 +102,7 @@ class ImageCropInvocation(BaseInvocation, WithWorkflow, WithMetadata):
             session_id=context.graph_execution_state_id,
             is_intermediate=self.is_intermediate,
             metadata=self.metadata,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         return ImageOutput(
@@ -101,11 +113,11 @@ class ImageCropInvocation(BaseInvocation, WithWorkflow, WithMetadata):
 
 
 @invocation(
-    invocation_type="img_pad_crop",
-    title="Center Pad or Crop Image",
+    "img_paste",
+    title="Paste Image",
+    tags=["image", "paste"],
     category="image",
-    tags=["image", "pad", "crop"],
-    version="1.0.0",
+    version="1.2.0",
 )
 class CenterPadCropInvocation(BaseInvocation):
     """Pad or crop an image's sides from the center by specified pixels. Positive values are outside of the image."""
@@ -155,8 +167,14 @@ class CenterPadCropInvocation(BaseInvocation):
         )
 
 
-@invocation("img_paste", title="Paste Image", tags=["image", "paste"], category="image", version="1.1.0")
-class ImagePasteInvocation(BaseInvocation, WithWorkflow, WithMetadata):
+@invocation(
+    invocation_type="img_pad_crop",
+    title="Center Pad or Crop Image",
+    category="image",
+    tags=["image", "pad", "crop"],
+    version="1.0.0",
+)
+class ImagePasteInvocation(BaseInvocation, WithMetadata):
     """Pastes an image into another image."""
 
     base_image: ImageField = InputField(description="The base image")
@@ -199,7 +217,7 @@ class ImagePasteInvocation(BaseInvocation, WithWorkflow, WithMetadata):
             session_id=context.graph_execution_state_id,
             is_intermediate=self.is_intermediate,
             metadata=self.metadata,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         return ImageOutput(
@@ -209,8 +227,14 @@ class ImagePasteInvocation(BaseInvocation, WithWorkflow, WithMetadata):
         )
 
 
-@invocation("tomask", title="Mask from Alpha", tags=["image", "mask"], category="image", version="1.1.0")
-class MaskFromAlphaInvocation(BaseInvocation, WithWorkflow, WithMetadata):
+@invocation(
+    "tomask",
+    title="Mask from Alpha",
+    tags=["image", "mask"],
+    category="image",
+    version="1.2.0",
+)
+class MaskFromAlphaInvocation(BaseInvocation, WithMetadata):
     """Extracts the alpha channel of an image as a mask."""
 
     image: ImageField = InputField(description="The image to create the mask from")
@@ -231,7 +255,7 @@ class MaskFromAlphaInvocation(BaseInvocation, WithWorkflow, WithMetadata):
             session_id=context.graph_execution_state_id,
             is_intermediate=self.is_intermediate,
             metadata=self.metadata,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         return ImageOutput(
@@ -241,8 +265,14 @@ class MaskFromAlphaInvocation(BaseInvocation, WithWorkflow, WithMetadata):
         )
 
 
-@invocation("img_mul", title="Multiply Images", tags=["image", "multiply"], category="image", version="1.1.0")
-class ImageMultiplyInvocation(BaseInvocation, WithWorkflow, WithMetadata):
+@invocation(
+    "img_mul",
+    title="Multiply Images",
+    tags=["image", "multiply"],
+    category="image",
+    version="1.2.0",
+)
+class ImageMultiplyInvocation(BaseInvocation, WithMetadata):
     """Multiplies two images together using `PIL.ImageChops.multiply()`."""
 
     image1: ImageField = InputField(description="The first image to multiply")
@@ -262,7 +292,7 @@ class ImageMultiplyInvocation(BaseInvocation, WithWorkflow, WithMetadata):
             session_id=context.graph_execution_state_id,
             is_intermediate=self.is_intermediate,
             metadata=self.metadata,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         return ImageOutput(
@@ -275,8 +305,14 @@ class ImageMultiplyInvocation(BaseInvocation, WithWorkflow, WithMetadata):
 IMAGE_CHANNELS = Literal["A", "R", "G", "B"]
 
 
-@invocation("img_chan", title="Extract Image Channel", tags=["image", "channel"], category="image", version="1.1.0")
-class ImageChannelInvocation(BaseInvocation, WithWorkflow, WithMetadata):
+@invocation(
+    "img_chan",
+    title="Extract Image Channel",
+    tags=["image", "channel"],
+    category="image",
+    version="1.2.0",
+)
+class ImageChannelInvocation(BaseInvocation, WithMetadata):
     """Gets a channel from an image."""
 
     image: ImageField = InputField(description="The image to get the channel from")
@@ -295,7 +331,7 @@ class ImageChannelInvocation(BaseInvocation, WithWorkflow, WithMetadata):
             session_id=context.graph_execution_state_id,
             is_intermediate=self.is_intermediate,
             metadata=self.metadata,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         return ImageOutput(
@@ -308,8 +344,14 @@ class ImageChannelInvocation(BaseInvocation, WithWorkflow, WithMetadata):
 IMAGE_MODES = Literal["L", "RGB", "RGBA", "CMYK", "YCbCr", "LAB", "HSV", "I", "F"]
 
 
-@invocation("img_conv", title="Convert Image Mode", tags=["image", "convert"], category="image", version="1.1.0")
-class ImageConvertInvocation(BaseInvocation, WithWorkflow, WithMetadata):
+@invocation(
+    "img_conv",
+    title="Convert Image Mode",
+    tags=["image", "convert"],
+    category="image",
+    version="1.2.0",
+)
+class ImageConvertInvocation(BaseInvocation, WithMetadata):
     """Converts an image to a different mode."""
 
     image: ImageField = InputField(description="The image to convert")
@@ -328,7 +370,7 @@ class ImageConvertInvocation(BaseInvocation, WithWorkflow, WithMetadata):
             session_id=context.graph_execution_state_id,
             is_intermediate=self.is_intermediate,
             metadata=self.metadata,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         return ImageOutput(
@@ -338,8 +380,14 @@ class ImageConvertInvocation(BaseInvocation, WithWorkflow, WithMetadata):
         )
 
 
-@invocation("img_blur", title="Blur Image", tags=["image", "blur"], category="image", version="1.1.0")
-class ImageBlurInvocation(BaseInvocation, WithWorkflow, WithMetadata):
+@invocation(
+    "img_blur",
+    title="Blur Image",
+    tags=["image", "blur"],
+    category="image",
+    version="1.2.0",
+)
+class ImageBlurInvocation(BaseInvocation, WithMetadata):
     """Blurs an image"""
 
     image: ImageField = InputField(description="The image to blur")
@@ -363,7 +411,7 @@ class ImageBlurInvocation(BaseInvocation, WithWorkflow, WithMetadata):
             session_id=context.graph_execution_state_id,
             is_intermediate=self.is_intermediate,
             metadata=self.metadata,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         return ImageOutput(
@@ -393,8 +441,14 @@ PIL_RESAMPLING_MAP = {
 }
 
 
-@invocation("img_resize", title="Resize Image", tags=["image", "resize"], category="image", version="1.1.0")
-class ImageResizeInvocation(BaseInvocation, WithMetadata, WithWorkflow):
+@invocation(
+    "img_resize",
+    title="Resize Image",
+    tags=["image", "resize"],
+    category="image",
+    version="1.2.0",
+)
+class ImageResizeInvocation(BaseInvocation, WithMetadata):
     """Resizes an image to specific dimensions"""
 
     image: ImageField = InputField(description="The image to resize")
@@ -420,7 +474,7 @@ class ImageResizeInvocation(BaseInvocation, WithMetadata, WithWorkflow):
             session_id=context.graph_execution_state_id,
             is_intermediate=self.is_intermediate,
             metadata=self.metadata,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         return ImageOutput(
@@ -430,8 +484,14 @@ class ImageResizeInvocation(BaseInvocation, WithMetadata, WithWorkflow):
         )
 
 
-@invocation("img_scale", title="Scale Image", tags=["image", "scale"], category="image", version="1.1.0")
-class ImageScaleInvocation(BaseInvocation, WithMetadata, WithWorkflow):
+@invocation(
+    "img_scale",
+    title="Scale Image",
+    tags=["image", "scale"],
+    category="image",
+    version="1.2.0",
+)
+class ImageScaleInvocation(BaseInvocation, WithMetadata):
     """Scales an image by a factor"""
 
     image: ImageField = InputField(description="The image to scale")
@@ -462,7 +522,7 @@ class ImageScaleInvocation(BaseInvocation, WithMetadata, WithWorkflow):
             session_id=context.graph_execution_state_id,
             is_intermediate=self.is_intermediate,
             metadata=self.metadata,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         return ImageOutput(
@@ -472,8 +532,14 @@ class ImageScaleInvocation(BaseInvocation, WithMetadata, WithWorkflow):
         )
 
 
-@invocation("img_lerp", title="Lerp Image", tags=["image", "lerp"], category="image", version="1.1.0")
-class ImageLerpInvocation(BaseInvocation, WithWorkflow, WithMetadata):
+@invocation(
+    "img_lerp",
+    title="Lerp Image",
+    tags=["image", "lerp"],
+    category="image",
+    version="1.2.0",
+)
+class ImageLerpInvocation(BaseInvocation, WithMetadata):
     """Linear interpolation of all pixels of an image"""
 
     image: ImageField = InputField(description="The image to lerp")
@@ -496,7 +562,7 @@ class ImageLerpInvocation(BaseInvocation, WithWorkflow, WithMetadata):
             session_id=context.graph_execution_state_id,
             is_intermediate=self.is_intermediate,
             metadata=self.metadata,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         return ImageOutput(
@@ -506,8 +572,14 @@ class ImageLerpInvocation(BaseInvocation, WithWorkflow, WithMetadata):
         )
 
 
-@invocation("img_ilerp", title="Inverse Lerp Image", tags=["image", "ilerp"], category="image", version="1.1.0")
-class ImageInverseLerpInvocation(BaseInvocation, WithWorkflow, WithMetadata):
+@invocation(
+    "img_ilerp",
+    title="Inverse Lerp Image",
+    tags=["image", "ilerp"],
+    category="image",
+    version="1.2.0",
+)
+class ImageInverseLerpInvocation(BaseInvocation, WithMetadata):
     """Inverse linear interpolation of all pixels of an image"""
 
     image: ImageField = InputField(description="The image to lerp")
@@ -530,7 +602,7 @@ class ImageInverseLerpInvocation(BaseInvocation, WithWorkflow, WithMetadata):
             session_id=context.graph_execution_state_id,
             is_intermediate=self.is_intermediate,
             metadata=self.metadata,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         return ImageOutput(
@@ -540,8 +612,14 @@ class ImageInverseLerpInvocation(BaseInvocation, WithWorkflow, WithMetadata):
         )
 
 
-@invocation("img_nsfw", title="Blur NSFW Image", tags=["image", "nsfw"], category="image", version="1.1.0")
-class ImageNSFWBlurInvocation(BaseInvocation, WithMetadata, WithWorkflow):
+@invocation(
+    "img_nsfw",
+    title="Blur NSFW Image",
+    tags=["image", "nsfw"],
+    category="image",
+    version="1.2.0",
+)
+class ImageNSFWBlurInvocation(BaseInvocation, WithMetadata):
     """Add blur to NSFW-flagged images"""
 
     image: ImageField = InputField(description="The image to check")
@@ -566,7 +644,7 @@ class ImageNSFWBlurInvocation(BaseInvocation, WithMetadata, WithWorkflow):
             session_id=context.graph_execution_state_id,
             is_intermediate=self.is_intermediate,
             metadata=self.metadata,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         return ImageOutput(
@@ -587,9 +665,9 @@ class ImageNSFWBlurInvocation(BaseInvocation, WithMetadata, WithWorkflow):
     title="Add Invisible Watermark",
     tags=["image", "watermark"],
     category="image",
-    version="1.1.0",
+    version="1.2.0",
 )
-class ImageWatermarkInvocation(BaseInvocation, WithMetadata, WithWorkflow):
+class ImageWatermarkInvocation(BaseInvocation, WithMetadata):
     """Add an invisible watermark to an image"""
 
     image: ImageField = InputField(description="The image to check")
@@ -606,7 +684,7 @@ class ImageWatermarkInvocation(BaseInvocation, WithMetadata, WithWorkflow):
             session_id=context.graph_execution_state_id,
             is_intermediate=self.is_intermediate,
             metadata=self.metadata,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         return ImageOutput(
@@ -616,8 +694,14 @@ class ImageWatermarkInvocation(BaseInvocation, WithMetadata, WithWorkflow):
         )
 
 
-@invocation("mask_edge", title="Mask Edge", tags=["image", "mask", "inpaint"], category="image", version="1.1.0")
-class MaskEdgeInvocation(BaseInvocation, WithWorkflow, WithMetadata):
+@invocation(
+    "mask_edge",
+    title="Mask Edge",
+    tags=["image", "mask", "inpaint"],
+    category="image",
+    version="1.2.0",
+)
+class MaskEdgeInvocation(BaseInvocation, WithMetadata):
     """Applies an edge mask to an image"""
 
     image: ImageField = InputField(description="The image to apply the mask to")
@@ -652,7 +736,7 @@ class MaskEdgeInvocation(BaseInvocation, WithWorkflow, WithMetadata):
             session_id=context.graph_execution_state_id,
             is_intermediate=self.is_intermediate,
             metadata=self.metadata,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         return ImageOutput(
@@ -667,9 +751,9 @@ class MaskEdgeInvocation(BaseInvocation, WithWorkflow, WithMetadata):
     title="Combine Masks",
     tags=["image", "mask", "multiply"],
     category="image",
-    version="1.1.0",
+    version="1.2.0",
 )
-class MaskCombineInvocation(BaseInvocation, WithWorkflow, WithMetadata):
+class MaskCombineInvocation(BaseInvocation, WithMetadata):
     """Combine two masks together by multiplying them using `PIL.ImageChops.multiply()`."""
 
     mask1: ImageField = InputField(description="The first mask to combine")
@@ -689,7 +773,7 @@ class MaskCombineInvocation(BaseInvocation, WithWorkflow, WithMetadata):
             session_id=context.graph_execution_state_id,
             is_intermediate=self.is_intermediate,
             metadata=self.metadata,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         return ImageOutput(
@@ -699,8 +783,14 @@ class MaskCombineInvocation(BaseInvocation, WithWorkflow, WithMetadata):
         )
 
 
-@invocation("color_correct", title="Color Correct", tags=["image", "color"], category="image", version="1.1.0")
-class ColorCorrectInvocation(BaseInvocation, WithWorkflow, WithMetadata):
+@invocation(
+    "color_correct",
+    title="Color Correct",
+    tags=["image", "color"],
+    category="image",
+    version="1.2.0",
+)
+class ColorCorrectInvocation(BaseInvocation, WithMetadata):
     """
     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.
@@ -800,7 +890,7 @@ class ColorCorrectInvocation(BaseInvocation, WithWorkflow, WithMetadata):
             session_id=context.graph_execution_state_id,
             is_intermediate=self.is_intermediate,
             metadata=self.metadata,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         return ImageOutput(
@@ -810,8 +900,14 @@ class ColorCorrectInvocation(BaseInvocation, WithWorkflow, WithMetadata):
         )
 
 
-@invocation("img_hue_adjust", title="Adjust Image Hue", tags=["image", "hue"], category="image", version="1.1.0")
-class ImageHueAdjustmentInvocation(BaseInvocation, WithWorkflow, WithMetadata):
+@invocation(
+    "img_hue_adjust",
+    title="Adjust Image Hue",
+    tags=["image", "hue"],
+    category="image",
+    version="1.2.0",
+)
+class ImageHueAdjustmentInvocation(BaseInvocation, WithMetadata):
     """Adjusts the Hue of an image."""
 
     image: ImageField = InputField(description="The image to adjust")
@@ -840,7 +936,7 @@ class ImageHueAdjustmentInvocation(BaseInvocation, WithWorkflow, WithMetadata):
             is_intermediate=self.is_intermediate,
             session_id=context.graph_execution_state_id,
             metadata=self.metadata,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         return ImageOutput(
@@ -913,9 +1009,9 @@ CHANNEL_FORMATS = {
         "value",
     ],
     category="image",
-    version="1.1.0",
+    version="1.2.0",
 )
-class ImageChannelOffsetInvocation(BaseInvocation, WithWorkflow, WithMetadata):
+class ImageChannelOffsetInvocation(BaseInvocation, WithMetadata):
     """Add or subtract a value from a specific color channel of an image."""
 
     image: ImageField = InputField(description="The image to adjust")
@@ -950,7 +1046,7 @@ class ImageChannelOffsetInvocation(BaseInvocation, WithWorkflow, WithMetadata):
             is_intermediate=self.is_intermediate,
             session_id=context.graph_execution_state_id,
             metadata=self.metadata,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         return ImageOutput(
@@ -984,9 +1080,9 @@ class ImageChannelOffsetInvocation(BaseInvocation, WithWorkflow, WithMetadata):
         "value",
     ],
     category="image",
-    version="1.1.0",
+    version="1.2.0",
 )
-class ImageChannelMultiplyInvocation(BaseInvocation, WithWorkflow, WithMetadata):
+class ImageChannelMultiplyInvocation(BaseInvocation, WithMetadata):
     """Scale a specific color channel of an image."""
 
     image: ImageField = InputField(description="The image to adjust")
@@ -1025,7 +1121,7 @@ class ImageChannelMultiplyInvocation(BaseInvocation, WithWorkflow, WithMetadata)
             node_id=self.id,
             is_intermediate=self.is_intermediate,
             session_id=context.graph_execution_state_id,
-            workflow=self.workflow,
+            workflow=context.workflow,
             metadata=self.metadata,
         )
 
@@ -1043,10 +1139,10 @@ class ImageChannelMultiplyInvocation(BaseInvocation, WithWorkflow, WithMetadata)
     title="Save Image",
     tags=["primitives", "image"],
     category="primitives",
-    version="1.1.0",
+    version="1.2.0",
     use_cache=False,
 )
-class SaveImageInvocation(BaseInvocation, WithWorkflow, WithMetadata):
+class SaveImageInvocation(BaseInvocation, WithMetadata):
     """Saves an image. Unlike an image primitive, this invocation stores a copy of the image."""
 
     image: ImageField = InputField(description=FieldDescriptions.image)
@@ -1064,7 +1160,7 @@ class SaveImageInvocation(BaseInvocation, WithWorkflow, WithMetadata):
             session_id=context.graph_execution_state_id,
             is_intermediate=self.is_intermediate,
             metadata=self.metadata,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         return ImageOutput(
@@ -1082,7 +1178,7 @@ class SaveImageInvocation(BaseInvocation, WithWorkflow, WithMetadata):
     version="1.0.1",
     use_cache=False,
 )
-class LinearUIOutputInvocation(BaseInvocation, WithWorkflow, WithMetadata):
+class LinearUIOutputInvocation(BaseInvocation, WithMetadata):
     """Handles Linear UI Image Outputting tasks."""
 
     image: ImageField = InputField(description=FieldDescriptions.image)

invokeai/app/invocations/infill.py

@@ -13,7 +13,7 @@ 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, WithWorkflow, invocation
+from .baseinvocation import BaseInvocation, InputField, InvocationContext, WithMetadata, invocation
 from .image import PIL_RESAMPLING_MAP, PIL_RESAMPLING_MODES
 
 
@@ -118,8 +118,8 @@ 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="1.1.0")
-class InfillColorInvocation(BaseInvocation, WithWorkflow, WithMetadata):
+@invocation("infill_rgba", title="Solid Color Infill", tags=["image", "inpaint"], category="inpaint", version="1.2.0")
+class InfillColorInvocation(BaseInvocation, WithMetadata):
     """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, WithWorkflow, WithMetadata):
             session_id=context.graph_execution_state_id,
             is_intermediate=self.is_intermediate,
             metadata=self.metadata,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         return ImageOutput(
@@ -154,8 +154,8 @@ class InfillColorInvocation(BaseInvocation, WithWorkflow, WithMetadata):
         )
 
 
-@invocation("infill_tile", title="Tile Infill", tags=["image", "inpaint"], category="inpaint", version="1.1.1")
-class InfillTileInvocation(BaseInvocation, WithWorkflow, WithMetadata):
+@invocation("infill_tile", title="Tile Infill", tags=["image", "inpaint"], category="inpaint", version="1.2.1")
+class InfillTileInvocation(BaseInvocation, WithMetadata):
     """Infills transparent areas of an image with tiles of the image"""
 
     image: ImageField = InputField(description="The image to infill")
@@ -181,7 +181,7 @@ class InfillTileInvocation(BaseInvocation, WithWorkflow, WithMetadata):
             session_id=context.graph_execution_state_id,
             is_intermediate=self.is_intermediate,
             metadata=self.metadata,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         return ImageOutput(
@@ -192,9 +192,9 @@ class InfillTileInvocation(BaseInvocation, WithWorkflow, WithMetadata):
 
 
 @invocation(
-    "infill_patchmatch", title="PatchMatch Infill", tags=["image", "inpaint"], category="inpaint", version="1.1.0"
+    "infill_patchmatch", title="PatchMatch Infill", tags=["image", "inpaint"], category="inpaint", version="1.2.0"
 )
-class InfillPatchMatchInvocation(BaseInvocation, WithWorkflow, WithMetadata):
+class InfillPatchMatchInvocation(BaseInvocation, WithMetadata):
     """Infills transparent areas of an image using the PatchMatch algorithm"""
 
     image: ImageField = InputField(description="The image to infill")
@@ -235,7 +235,7 @@ class InfillPatchMatchInvocation(BaseInvocation, WithWorkflow, WithMetadata):
             session_id=context.graph_execution_state_id,
             is_intermediate=self.is_intermediate,
             metadata=self.metadata,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         return ImageOutput(
@@ -245,8 +245,8 @@ class InfillPatchMatchInvocation(BaseInvocation, WithWorkflow, WithMetadata):
         )
 
 
-@invocation("infill_lama", title="LaMa Infill", tags=["image", "inpaint"], category="inpaint", version="1.1.0")
-class LaMaInfillInvocation(BaseInvocation, WithWorkflow, WithMetadata):
+@invocation("infill_lama", title="LaMa Infill", tags=["image", "inpaint"], category="inpaint", version="1.2.0")
+class LaMaInfillInvocation(BaseInvocation, WithMetadata):
     """Infills transparent areas of an image using the LaMa model"""
 
     image: ImageField = InputField(description="The image to infill")
@@ -264,7 +264,7 @@ class LaMaInfillInvocation(BaseInvocation, WithWorkflow, WithMetadata):
             session_id=context.graph_execution_state_id,
             is_intermediate=self.is_intermediate,
             metadata=self.metadata,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         return ImageOutput(
@@ -274,8 +274,8 @@ class LaMaInfillInvocation(BaseInvocation, WithWorkflow, WithMetadata):
         )
 
 
-@invocation("infill_cv2", title="CV2 Infill", tags=["image", "inpaint"], category="inpaint", version="1.1.0")
-class CV2InfillInvocation(BaseInvocation, WithWorkflow, WithMetadata):
+@invocation("infill_cv2", title="CV2 Infill", tags=["image", "inpaint"], category="inpaint", version="1.2.0")
+class CV2InfillInvocation(BaseInvocation, WithMetadata):
     """Infills transparent areas of an image using OpenCV Inpainting"""
 
     image: ImageField = InputField(description="The image to infill")
@@ -293,7 +293,7 @@ class CV2InfillInvocation(BaseInvocation, WithWorkflow, WithMetadata):
             session_id=context.graph_execution_state_id,
             is_intermediate=self.is_intermediate,
             metadata=self.metadata,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         return ImageOutput(

invokeai/app/invocations/latent.py

@@ -64,7 +64,6 @@ from .baseinvocation import (
     OutputField,
     UIType,
     WithMetadata,
-    WithWorkflow,
     invocation,
     invocation_output,
 )
@@ -79,6 +78,12 @@ 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):
@@ -394,9 +399,9 @@ class DenoiseLatentsInvocation(BaseInvocation):
         exit_stack: ExitStack,
         do_classifier_free_guidance: bool = True,
     ) -> List[ControlNetData]:
-        # assuming fixed dimensional scaling of 8:1 for image:latents
-        control_height_resize = latents_shape[2] * 8
-        control_width_resize = latents_shape[3] * 8
+        # 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
         if control_input is None:
             control_list = None
         elif isinstance(control_input, list) and len(control_input) == 0:
@@ -796,9 +801,9 @@ class DenoiseLatentsInvocation(BaseInvocation):
     title="Latents to Image",
     tags=["latents", "image", "vae", "l2i"],
     category="latents",
-    version="1.1.0",
+    version="1.2.0",
 )
-class LatentsToImageInvocation(BaseInvocation, WithMetadata, WithWorkflow):
+class LatentsToImageInvocation(BaseInvocation, WithMetadata):
     """Generates an image from latents."""
 
     latents: LatentsField = InputField(
@@ -880,7 +885,7 @@ class LatentsToImageInvocation(BaseInvocation, WithMetadata, WithWorkflow):
             session_id=context.graph_execution_state_id,
             is_intermediate=self.is_intermediate,
             metadata=self.metadata,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         return ImageOutput(
@@ -909,12 +914,12 @@ class ResizeLatentsInvocation(BaseInvocation):
     )
     width: int = InputField(
         ge=64,
-        multiple_of=8,
+        multiple_of=LATENT_SCALE_FACTOR,
         description=FieldDescriptions.width,
     )
     height: int = InputField(
         ge=64,
-        multiple_of=8,
+        multiple_of=LATENT_SCALE_FACTOR,
         description=FieldDescriptions.width,
     )
     mode: LATENTS_INTERPOLATION_MODE = InputField(default="bilinear", description=FieldDescriptions.interp_mode)
@@ -928,7 +933,7 @@ class ResizeLatentsInvocation(BaseInvocation):
 
         resized_latents = torch.nn.functional.interpolate(
             latents.to(device),
-            size=(self.height // 8, self.width // 8),
+            size=(self.height // LATENT_SCALE_FACTOR, self.width // LATENT_SCALE_FACTOR),
             mode=self.mode,
             antialias=self.antialias if self.mode in ["bilinear", "bicubic"] else False,
         )
@@ -1166,3 +1171,60 @@ class BlendLatentsInvocation(BaseInvocation):
         # context.services.latents.set(name, resized_latents)
         context.services.latents.save(name, blended_latents)
         return build_latents_output(latents_name=name, latents=blended_latents)
+
+
+# The Crop Latents node was copied from @skunkworxdark's implementation here:
+# https://github.com/skunkworxdark/XYGrid_nodes/blob/74647fa9c1fa57d317a94bd43ca689af7f0aae5e/images_to_grids.py#L1117C1-L1167C80
+@invocation(
+    "crop_latents",
+    title="Crop Latents",
+    tags=["latents", "crop"],
+    category="latents",
+    version="1.0.0",
+)
+# TODO(ryand): Named `CropLatentsCoreInvocation` to prevent a conflict with custom node `CropLatentsInvocation`.
+# Currently, if the class names conflict then 'GET /openapi.json' fails.
+class CropLatentsCoreInvocation(BaseInvocation):
+    """Crops a latent-space tensor to a box specified in image-space. The box dimensions and coordinates must be
+    divisible by the latent scale factor of 8.
+    """
+
+    latents: LatentsField = InputField(
+        description=FieldDescriptions.latents,
+        input=Input.Connection,
+    )
+    x: int = InputField(
+        ge=0,
+        multiple_of=LATENT_SCALE_FACTOR,
+        description="The left x coordinate (in px) of the crop rectangle in image space. This value will be converted to a dimension in latent space.",
+    )
+    y: int = InputField(
+        ge=0,
+        multiple_of=LATENT_SCALE_FACTOR,
+        description="The top y coordinate (in px) of the crop rectangle in image space. This value will be converted to a dimension in latent space.",
+    )
+    width: int = InputField(
+        ge=1,
+        multiple_of=LATENT_SCALE_FACTOR,
+        description="The width (in px) of the crop rectangle in image space. This value will be converted to a dimension in latent space.",
+    )
+    height: int = InputField(
+        ge=1,
+        multiple_of=LATENT_SCALE_FACTOR,
+        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)
+
+        x1 = self.x // LATENT_SCALE_FACTOR
+        y1 = self.y // LATENT_SCALE_FACTOR
+        x2 = x1 + (self.width // LATENT_SCALE_FACTOR)
+        y2 = y1 + (self.height // LATENT_SCALE_FACTOR)
+
+        cropped_latents = latents[..., y1:y2, x1:x2]
+
+        name = f"{context.graph_execution_state_id}__{self.id}"
+        context.services.latents.save(name, cropped_latents)
+
+        return build_latents_output(latents_name=name, latents=cropped_latents)

invokeai/app/invocations/onnx.py

@@ -31,7 +31,6 @@ from .baseinvocation import (
     UIComponent,
     UIType,
     WithMetadata,
-    WithWorkflow,
     invocation,
     invocation_output,
 )
@@ -326,9 +325,9 @@ class ONNXTextToLatentsInvocation(BaseInvocation):
     title="ONNX Latents to Image",
     tags=["latents", "image", "vae", "onnx"],
     category="image",
-    version="1.1.0",
+    version="1.2.0",
 )
-class ONNXLatentsToImageInvocation(BaseInvocation, WithMetadata, WithWorkflow):
+class ONNXLatentsToImageInvocation(BaseInvocation, WithMetadata):
     """Generates an image from latents."""
 
     latents: LatentsField = InputField(
@@ -378,7 +377,7 @@ class ONNXLatentsToImageInvocation(BaseInvocation, WithMetadata, WithWorkflow):
             session_id=context.graph_execution_state_id,
             is_intermediate=self.is_intermediate,
             metadata=self.metadata,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         return ImageOutput(

invokeai/app/invocations/tiles.py

@@ -0,0 +1,180 @@
+import numpy as np
+from PIL import Image
+from pydantic import BaseModel
+
+from invokeai.app.invocations.baseinvocation import (
+    BaseInvocation,
+    BaseInvocationOutput,
+    InputField,
+    InvocationContext,
+    OutputField,
+    WithMetadata,
+    invocation,
+    invocation_output,
+)
+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 calc_tiles_with_overlap, merge_tiles_with_linear_blending
+from invokeai.backend.tiles.utils import Tile
+
+
+class TileWithImage(BaseModel):
+    tile: Tile
+    image: ImageField
+
+
+@invocation_output("calculate_image_tiles_output")
+class CalculateImageTilesOutput(BaseInvocationOutput):
+    tiles: list[Tile] = OutputField(description="The tiles coordinates that cover a particular image shape.")
+
+
+@invocation("calculate_image_tiles", title="Calculate Image Tiles", tags=["tiles"], category="tiles", version="1.0.0")
+class CalculateImageTilesInvocation(BaseInvocation):
+    """Calculate the coordinates and overlaps of tiles that cover a target image shape."""
+
+    image_width: int = InputField(ge=1, default=1024, description="The image width, in pixels, to calculate tiles for.")
+    image_height: int = InputField(
+        ge=1, default=1024, description="The image height, in pixels, to calculate tiles for."
+    )
+    tile_width: int = InputField(ge=1, default=576, description="The tile width, in pixels.")
+    tile_height: int = InputField(ge=1, default=576, description="The tile height, in pixels.")
+    overlap: int = InputField(
+        ge=0,
+        default=128,
+        description="The target overlap, in pixels, between adjacent tiles. Adjacent tiles will overlap by at least this amount",
+    )
+
+    def invoke(self, context: InvocationContext) -> CalculateImageTilesOutput:
+        tiles = calc_tiles_with_overlap(
+            image_height=self.image_height,
+            image_width=self.image_width,
+            tile_height=self.tile_height,
+            tile_width=self.tile_width,
+            overlap=self.overlap,
+        )
+        return CalculateImageTilesOutput(tiles=tiles)
+
+
+@invocation_output("tile_to_properties_output")
+class TileToPropertiesOutput(BaseInvocationOutput):
+    coords_left: int = OutputField(description="Left coordinate of the tile relative to its parent image.")
+    coords_right: int = OutputField(description="Right coordinate of the tile relative to its parent image.")
+    coords_top: int = OutputField(description="Top coordinate of the tile relative to its parent image.")
+    coords_bottom: int = OutputField(description="Bottom coordinate of the tile relative to its parent image.")
+
+    # HACK: The width and height fields are 'meta' fields that can easily be calculated from the other fields on this
+    # object. Including redundant fields that can cheaply/easily be re-calculated goes against conventional API design
+    # principles. These fields are included, because 1) they are often useful in tiled workflows, and 2) they are
+    # difficult to calculate in a workflow (even though it's just a couple of subtraction nodes the graph gets
+    # surprisingly complicated).
+    width: int = OutputField(description="The width of the tile. Equal to coords_right - coords_left.")
+    height: int = OutputField(description="The height of the tile. Equal to coords_bottom - coords_top.")
+
+    overlap_top: int = OutputField(description="Overlap between this tile and its top neighbor.")
+    overlap_bottom: int = OutputField(description="Overlap between this tile and its bottom neighbor.")
+    overlap_left: int = OutputField(description="Overlap between this tile and its left neighbor.")
+    overlap_right: int = OutputField(description="Overlap between this tile and its right neighbor.")
+
+
+@invocation("tile_to_properties", title="Tile to Properties", tags=["tiles"], category="tiles", version="1.0.0")
+class TileToPropertiesInvocation(BaseInvocation):
+    """Split a Tile into its individual properties."""
+
+    tile: Tile = InputField(description="The tile to split into properties.")
+
+    def invoke(self, context: InvocationContext) -> TileToPropertiesOutput:
+        return TileToPropertiesOutput(
+            coords_left=self.tile.coords.left,
+            coords_right=self.tile.coords.right,
+            coords_top=self.tile.coords.top,
+            coords_bottom=self.tile.coords.bottom,
+            width=self.tile.coords.right - self.tile.coords.left,
+            height=self.tile.coords.bottom - self.tile.coords.top,
+            overlap_top=self.tile.overlap.top,
+            overlap_bottom=self.tile.overlap.bottom,
+            overlap_left=self.tile.overlap.left,
+            overlap_right=self.tile.overlap.right,
+        )
+
+
+@invocation_output("pair_tile_image_output")
+class PairTileImageOutput(BaseInvocationOutput):
+    tile_with_image: TileWithImage = OutputField(description="A tile description with its corresponding image.")
+
+
+@invocation("pair_tile_image", title="Pair Tile with Image", tags=["tiles"], category="tiles", version="1.0.0")
+class PairTileImageInvocation(BaseInvocation):
+    """Pair an image with its tile properties."""
+
+    # TODO(ryand): The only reason that PairTileImage is needed is because the iterate/collect nodes don't preserve
+    # order. Can this be fixed?
+
+    image: ImageField = InputField(description="The tile image.")
+    tile: Tile = InputField(description="The tile properties.")
+
+    def invoke(self, context: InvocationContext) -> PairTileImageOutput:
+        return PairTileImageOutput(
+            tile_with_image=TileWithImage(
+                tile=self.tile,
+                image=self.image,
+            )
+        )
+
+
+@invocation("merge_tiles_to_image", title="Merge Tiles to Image", tags=["tiles"], category="tiles", version="1.1.0")
+class MergeTilesToImageInvocation(BaseInvocation, WithMetadata):
+    """Merge multiple tile images into a single image."""
+
+    # Inputs
+    tiles_with_images: list[TileWithImage] = InputField(description="A list of tile images with tile properties.")
+    blend_amount: int = InputField(
+        ge=0,
+        description="The amount to blend adjacent tiles in pixels. Must be <= the amount of overlap between adjacent tiles.",
+    )
+
+    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]
+
+        # Infer the output image dimensions from the max/min tile limits.
+        height = 0
+        width = 0
+        for tile in tiles:
+            height = max(height, tile.coords.bottom)
+            width = max(width, tile.coords.right)
+
+        # Get all tile images for processing.
+        # TODO(ryand): It pains me that we spend time PNG decoding each tile from disk when they almost certainly
+        # 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 = pil_image.convert("RGB")
+            tile_np_images.append(np.array(pil_image))
+
+        # Prepare the output image buffer.
+        # Check the first tile to determine how many image channels are expected in the output.
+        channels = tile_np_images[0].shape[-1]
+        dtype = tile_np_images[0].dtype
+        np_image = np.zeros(shape=(height, width, channels), dtype=dtype)
+
+        merge_tiles_with_linear_blending(
+            dst_image=np_image, tiles=tiles, tile_images=tile_np_images, blend_amount=self.blend_amount
+        )
+        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,
+        )

invokeai/app/invocations/upscale.py

@@ -14,7 +14,7 @@ from invokeai.app.services.image_records.image_records_common import ImageCatego
 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, WithWorkflow, invocation
+from .baseinvocation import BaseInvocation, InputField, InvocationContext, WithMetadata, invocation
 
 # TODO: Populate this from disk?
 # TODO: Use model manager to load?
@@ -29,8 +29,8 @@ if choose_torch_device() == torch.device("mps"):
     from torch import mps
 
 
-@invocation("esrgan", title="Upscale (RealESRGAN)", tags=["esrgan", "upscale"], category="esrgan", version="1.2.0")
-class ESRGANInvocation(BaseInvocation, WithWorkflow, WithMetadata):
+@invocation("esrgan", title="Upscale (RealESRGAN)", tags=["esrgan", "upscale"], category="esrgan", version="1.3.0")
+class ESRGANInvocation(BaseInvocation, WithMetadata):
     """Upscales an image using RealESRGAN."""
 
     image: ImageField = InputField(description="The input image")
@@ -118,7 +118,7 @@ class ESRGANInvocation(BaseInvocation, WithWorkflow, WithMetadata):
             session_id=context.graph_execution_state_id,
             is_intermediate=self.is_intermediate,
             metadata=self.metadata,
-            workflow=self.workflow,
+            workflow=context.workflow,
         )
 
         return ImageOutput(

invokeai/app/services/board_image_records/board_image_records_sqlite.py

@@ -4,7 +4,7 @@ from typing import Optional, cast
 
 from invokeai.app.services.image_records.image_records_common import ImageRecord, deserialize_image_record
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
-from invokeai.app.services.shared.sqlite import SqliteDatabase
+from invokeai.app.services.shared.sqlite.sqlite_database import SqliteDatabase
 
 from .board_image_records_base import BoardImageRecordStorageBase
 

invokeai/app/services/board_records/board_records_sqlite.py

@@ -3,7 +3,7 @@ import threading
 from typing import Union, cast
 
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
-from invokeai.app.services.shared.sqlite import SqliteDatabase
+from invokeai.app.services.shared.sqlite.sqlite_database import SqliteDatabase
 from invokeai.app.util.misc import uuid_string
 
 from .board_records_base import BoardRecordStorageBase

invokeai/app/services/image_files/image_files_base.py

@@ -4,7 +4,8 @@ from typing import Optional
 
 from PIL.Image import Image as PILImageType
 
-from invokeai.app.invocations.baseinvocation import MetadataField, WorkflowField
+from invokeai.app.invocations.baseinvocation import MetadataField
+from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID
 
 
 class ImageFileStorageBase(ABC):
@@ -33,7 +34,7 @@ class ImageFileStorageBase(ABC):
         image: PILImageType,
         image_name: str,
         metadata: Optional[MetadataField] = None,
-        workflow: Optional[WorkflowField] = None,
+        workflow: Optional[WorkflowWithoutID] = None,
         thumbnail_size: int = 256,
     ) -> None:
         """Saves an image and a 256x256 WEBP thumbnail. Returns a tuple of the image name, thumbnail name, and created timestamp."""
@@ -43,3 +44,8 @@ class ImageFileStorageBase(ABC):
     def delete(self, image_name: str) -> None:
         """Deletes an image and its thumbnail (if one exists)."""
         pass
+
+    @abstractmethod
+    def get_workflow(self, image_name: str) -> Optional[WorkflowWithoutID]:
+        """Gets the workflow of an image."""
+        pass

invokeai/app/services/image_files/image_files_disk.py

@@ -7,8 +7,9 @@ from PIL import Image, PngImagePlugin
 from PIL.Image import Image as PILImageType
 from send2trash import send2trash
 
-from invokeai.app.invocations.baseinvocation import MetadataField, WorkflowField
+from invokeai.app.invocations.baseinvocation 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
 
 from .image_files_base import ImageFileStorageBase
@@ -56,7 +57,7 @@ class DiskImageFileStorage(ImageFileStorageBase):
         image: PILImageType,
         image_name: str,
         metadata: Optional[MetadataField] = None,
-        workflow: Optional[WorkflowField] = None,
+        workflow: Optional[WorkflowWithoutID] = None,
         thumbnail_size: int = 256,
     ) -> None:
         try:
@@ -64,12 +65,19 @@ class DiskImageFileStorage(ImageFileStorageBase):
             image_path = self.get_path(image_name)
 
             pnginfo = PngImagePlugin.PngInfo()
+            info_dict = {}
 
             if metadata is not None:
-                pnginfo.add_text("invokeai_metadata", metadata.model_dump_json())
+                metadata_json = metadata.model_dump_json()
+                info_dict["invokeai_metadata"] = metadata_json
+                pnginfo.add_text("invokeai_metadata", metadata_json)
             if workflow is not None:
-                pnginfo.add_text("invokeai_workflow", workflow.model_dump_json())
+                workflow_json = workflow.model_dump_json()
+                info_dict["invokeai_workflow"] = workflow_json
+                pnginfo.add_text("invokeai_workflow", workflow_json)
 
+            # When saving the image, the image object's info field is not populated. We need to set it
+            image.info = info_dict
             image.save(
                 image_path,
                 "PNG",
@@ -121,6 +129,13 @@ class DiskImageFileStorage(ImageFileStorageBase):
         path = path if isinstance(path, Path) else Path(path)
         return path.exists()
 
+    def get_workflow(self, image_name: str) -> WorkflowWithoutID | None:
+        image = self.get(image_name)
+        workflow = image.info.get("invokeai_workflow", None)
+        if workflow is not None:
+            return WorkflowWithoutID.model_validate_json(workflow)
+        return None
+
     def __validate_storage_folders(self) -> None:
         """Checks if the required output folders exist and create them if they don't"""
         folders: list[Path] = [self.__output_folder, self.__thumbnails_folder]

invokeai/app/services/image_records/image_records_base.py

@@ -75,6 +75,7 @@ class ImageRecordStorageBase(ABC):
         image_category: ImageCategory,
         width: int,
         height: int,
+        has_workflow: bool,
         is_intermediate: Optional[bool] = False,
         starred: Optional[bool] = False,
         session_id: Optional[str] = None,

invokeai/app/services/image_records/image_records_common.py

@@ -100,6 +100,7 @@ IMAGE_DTO_COLS = ", ".join(
             "height",
             "session_id",
             "node_id",
+            "has_workflow",
             "is_intermediate",
             "created_at",
             "updated_at",
@@ -145,6 +146,7 @@ class ImageRecord(BaseModelExcludeNull):
     """The node ID that generated this image, if it is a generated image."""
     starred: bool = Field(description="Whether this image is starred.")
     """Whether this image is starred."""
+    has_workflow: bool = Field(description="Whether this image has a workflow.")
 
 
 class ImageRecordChanges(BaseModelExcludeNull, extra="allow"):
@@ -188,6 +190,7 @@ def deserialize_image_record(image_dict: dict) -> ImageRecord:
     deleted_at = image_dict.get("deleted_at", get_iso_timestamp())
     is_intermediate = image_dict.get("is_intermediate", False)
     starred = image_dict.get("starred", False)
+    has_workflow = image_dict.get("has_workflow", False)
 
     return ImageRecord(
         image_name=image_name,
@@ -202,4 +205,5 @@ def deserialize_image_record(image_dict: dict) -> ImageRecord:
         deleted_at=deleted_at,
         is_intermediate=is_intermediate,
         starred=starred,
+        has_workflow=has_workflow,
     )

invokeai/app/services/image_records/image_records_sqlite.py

@@ -5,7 +5,7 @@ from typing import Optional, Union, cast
 
 from invokeai.app.invocations.baseinvocation import MetadataField, MetadataFieldValidator
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
-from invokeai.app.services.shared.sqlite import SqliteDatabase
+from invokeai.app.services.shared.sqlite.sqlite_database import SqliteDatabase
 
 from .image_records_base import ImageRecordStorageBase
 from .image_records_common import (
@@ -117,6 +117,16 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
             """
         )
 
+        self._cursor.execute("PRAGMA table_info(images)")
+        columns = [column[1] for column in self._cursor.fetchall()]
+        if "has_workflow" not in columns:
+            self._cursor.execute(
+                """--sql
+                ALTER TABLE images
+                ADD COLUMN has_workflow BOOLEAN DEFAULT FALSE;
+                """
+            )
+
     def get(self, image_name: str) -> ImageRecord:
         try:
             self._lock.acquire()
@@ -408,6 +418,7 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
         image_category: ImageCategory,
         width: int,
         height: int,
+        has_workflow: bool,
         is_intermediate: Optional[bool] = False,
         starred: Optional[bool] = False,
         session_id: Optional[str] = None,
@@ -429,9 +440,10 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
                     session_id,
                     metadata,
                     is_intermediate,
-                    starred
+                    starred,
+                    has_workflow
                     )
-                VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?);
+                VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?);
                 """,
                 (
                     image_name,
@@ -444,6 +456,7 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
                     metadata_json,
                     is_intermediate,
                     starred,
+                    has_workflow,
                 ),
             )
             self._conn.commit()

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, WorkflowField
+from invokeai.app.invocations.baseinvocation import MetadataField
 from invokeai.app.services.image_records.image_records_common import (
     ImageCategory,
     ImageRecord,
@@ -12,6 +12,7 @@ from invokeai.app.services.image_records.image_records_common import (
 )
 from invokeai.app.services.images.images_common import ImageDTO
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
+from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID
 
 
 class ImageServiceABC(ABC):
@@ -51,7 +52,7 @@ class ImageServiceABC(ABC):
         board_id: Optional[str] = None,
         is_intermediate: Optional[bool] = False,
         metadata: Optional[MetadataField] = None,
-        workflow: Optional[WorkflowField] = None,
+        workflow: Optional[WorkflowWithoutID] = None,
     ) -> ImageDTO:
         """Creates an image, storing the file and its metadata."""
         pass
@@ -85,6 +86,11 @@ class ImageServiceABC(ABC):
         """Gets an image's metadata."""
         pass
 
+    @abstractmethod
+    def get_workflow(self, image_name: str) -> Optional[WorkflowWithoutID]:
+        """Gets an image's workflow."""
+        pass
+
     @abstractmethod
     def get_path(self, image_name: str, thumbnail: bool = False) -> str:
         """Gets an image's path."""

invokeai/app/services/images/images_common.py

@@ -24,11 +24,6 @@ class ImageDTO(ImageRecord, ImageUrlsDTO):
         default=None, description="The id of the board the image belongs to, if one exists."
     )
     """The id of the board the image belongs to, if one exists."""
-    workflow_id: Optional[str] = Field(
-        default=None,
-        description="The workflow that generated this image.",
-    )
-    """The workflow that generated this image."""
 
 
 def image_record_to_dto(
@@ -36,7 +31,6 @@ def image_record_to_dto(
     image_url: str,
     thumbnail_url: str,
     board_id: Optional[str],
-    workflow_id: Optional[str],
 ) -> ImageDTO:
     """Converts an image record to an image DTO."""
     return ImageDTO(
@@ -44,5 +38,4 @@ def image_record_to_dto(
         image_url=image_url,
         thumbnail_url=thumbnail_url,
         board_id=board_id,
-        workflow_id=workflow_id,
     )

invokeai/app/services/images/images_default.py

@@ -2,9 +2,10 @@ from typing import Optional
 
 from PIL.Image import Image as PILImageType
 
-from invokeai.app.invocations.baseinvocation import MetadataField, WorkflowField
+from invokeai.app.invocations.baseinvocation 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
 
 from ..image_files.image_files_common import (
     ImageFileDeleteException,
@@ -42,7 +43,7 @@ class ImageService(ImageServiceABC):
         board_id: Optional[str] = None,
         is_intermediate: Optional[bool] = False,
         metadata: Optional[MetadataField] = None,
-        workflow: Optional[WorkflowField] = None,
+        workflow: Optional[WorkflowWithoutID] = None,
     ) -> ImageDTO:
         if image_origin not in ResourceOrigin:
             raise InvalidOriginException
@@ -55,12 +56,6 @@ class ImageService(ImageServiceABC):
         (width, height) = image.size
 
         try:
-            if workflow is not None:
-                created_workflow = self.__invoker.services.workflow_records.create(workflow)
-                workflow_id = created_workflow.model_dump()["id"]
-            else:
-                workflow_id = None
-
             # TODO: Consider using a transaction here to ensure consistency between storage and database
             self.__invoker.services.image_records.save(
                 # Non-nullable fields
@@ -69,6 +64,7 @@ class ImageService(ImageServiceABC):
                 image_category=image_category,
                 width=width,
                 height=height,
+                has_workflow=workflow is not None,
                 # Meta fields
                 is_intermediate=is_intermediate,
                 # Nullable fields
@@ -78,8 +74,6 @@ class ImageService(ImageServiceABC):
             )
             if board_id is not None:
                 self.__invoker.services.board_image_records.add_image_to_board(board_id=board_id, image_name=image_name)
-            if workflow_id is not None:
-                self.__invoker.services.workflow_image_records.create(workflow_id=workflow_id, image_name=image_name)
             self.__invoker.services.image_files.save(
                 image_name=image_name, image=image, metadata=metadata, workflow=workflow
             )
@@ -143,7 +137,6 @@ class ImageService(ImageServiceABC):
                 image_url=self.__invoker.services.urls.get_image_url(image_name),
                 thumbnail_url=self.__invoker.services.urls.get_image_url(image_name, True),
                 board_id=self.__invoker.services.board_image_records.get_board_for_image(image_name),
-                workflow_id=self.__invoker.services.workflow_image_records.get_workflow_for_image(image_name),
             )
 
             return image_dto
@@ -164,18 +157,15 @@ class ImageService(ImageServiceABC):
             self.__invoker.services.logger.error("Problem getting image DTO")
             raise e
 
-    def get_workflow(self, image_name: str) -> Optional[WorkflowField]:
+    def get_workflow(self, image_name: str) -> Optional[WorkflowWithoutID]:
         try:
-            workflow_id = self.__invoker.services.workflow_image_records.get_workflow_for_image(image_name)
-            if workflow_id is None:
-                return None
-            return self.__invoker.services.workflow_records.get(workflow_id)
-        except ImageRecordNotFoundException:
-            self.__invoker.services.logger.error("Image record not found")
+            return self.__invoker.services.image_files.get_workflow(image_name)
+        except ImageFileNotFoundException:
+            self.__invoker.services.logger.error("Image file not found")
+            raise
+        except Exception:
+            self.__invoker.services.logger.error("Problem getting image workflow")
             raise
-        except Exception as e:
-            self.__invoker.services.logger.error("Problem getting image DTO")
-            raise e
 
     def get_path(self, image_name: str, thumbnail: bool = False) -> str:
         try:
@@ -223,7 +213,6 @@ class ImageService(ImageServiceABC):
                     image_url=self.__invoker.services.urls.get_image_url(r.image_name),
                     thumbnail_url=self.__invoker.services.urls.get_image_url(r.image_name, True),
                     board_id=self.__invoker.services.board_image_records.get_board_for_image(r.image_name),
-                    workflow_id=self.__invoker.services.workflow_image_records.get_workflow_for_image(r.image_name),
                 )
                 for r in results.items
             ]

invokeai/app/services/invocation_processor/invocation_processor_default.py

@@ -108,6 +108,7 @@ class DefaultInvocationProcessor(InvocationProcessorABC):
                                 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,
                             )
                         )
 
@@ -178,6 +179,7 @@ class DefaultInvocationProcessor(InvocationProcessorABC):
                             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:

invokeai/app/services/invocation_queue/invocation_queue_common.py

@@ -1,9 +1,12 @@
 # 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")
@@ -15,5 +18,6 @@ class InvocationQueueItem(BaseModel):
     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)

invokeai/app/services/invocation_services.py

@@ -28,7 +28,6 @@ if TYPE_CHECKING:
     from .session_queue.session_queue_base import SessionQueueBase
     from .shared.graph import GraphExecutionState, LibraryGraph
     from .urls.urls_base import UrlServiceBase
-    from .workflow_image_records.workflow_image_records_base import WorkflowImageRecordsStorageBase
     from .workflow_records.workflow_records_base import WorkflowRecordsStorageBase
 
 
@@ -59,7 +58,6 @@ class InvocationServices:
     invocation_cache: "InvocationCacheBase"
     names: "NameServiceBase"
     urls: "UrlServiceBase"
-    workflow_image_records: "WorkflowImageRecordsStorageBase"
     workflow_records: "WorkflowRecordsStorageBase"
 
     def __init__(
@@ -87,7 +85,6 @@ class InvocationServices:
         invocation_cache: "InvocationCacheBase",
         names: "NameServiceBase",
         urls: "UrlServiceBase",
-        workflow_image_records: "WorkflowImageRecordsStorageBase",
         workflow_records: "WorkflowRecordsStorageBase",
     ):
         self.board_images = board_images
@@ -113,5 +110,4 @@ class InvocationServices:
         self.invocation_cache = invocation_cache
         self.names = names
         self.urls = urls
-        self.workflow_image_records = workflow_image_records
         self.workflow_records = workflow_records

invokeai/app/services/invoker.py

@@ -2,6 +2,8 @@
 
 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
@@ -22,6 +24,7 @@ class Invoker:
         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.
@@ -43,6 +46,7 @@ class Invoker:
                 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,
             )
         )

invokeai/app/services/item_storage/item_storage_sqlite.py

@@ -5,7 +5,7 @@ from typing import Generic, Optional, TypeVar, get_args
 from pydantic import BaseModel, TypeAdapter
 
 from invokeai.app.services.shared.pagination import PaginatedResults
-from invokeai.app.services.shared.sqlite import SqliteDatabase
+from invokeai.app.services.shared.sqlite.sqlite_database import SqliteDatabase
 
 from .item_storage_base import ItemStorageABC
 

invokeai/app/services/latents_storage/latents_storage_disk.py

@@ -5,6 +5,8 @@ from typing import Union
 
 import torch
 
+from invokeai.app.services.invoker import Invoker
+
 from .latents_storage_base import LatentsStorageBase
 
 
@@ -17,6 +19,10 @@ class DiskLatentsStorage(LatentsStorageBase):
         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)
@@ -32,3 +38,21 @@ class DiskLatentsStorage(LatentsStorageBase):
 
     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)"
+            )

invokeai/app/services/latents_storage/latents_storage_forward_cache.py

@@ -5,6 +5,8 @@ from typing import Dict, Optional
 
 import torch
 
+from invokeai.app.services.invoker import Invoker
+
 from .latents_storage_base import LatentsStorageBase
 
 
@@ -23,6 +25,18 @@ class ForwardCacheLatentsStorage(LatentsStorageBase):
         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:

invokeai/app/services/model_records/model_records_sql.py

@@ -52,7 +52,7 @@ from invokeai.backend.model_manager.config import (
     ModelType,
 )
 
-from ..shared.sqlite import SqliteDatabase
+from ..shared.sqlite.sqlite_database import SqliteDatabase
 from .model_records_base import (
     CONFIG_FILE_VERSION,
     DuplicateModelException,

invokeai/app/services/session_processor/session_processor_default.py

@@ -114,6 +114,7 @@ class DefaultSessionProcessor(SessionProcessorBase):
                                 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,
                             )
                             queue_item = None

invokeai/app/services/session_queue/session_queue_common.py

@@ -8,6 +8,10 @@ from pydantic_core import to_jsonable_python
 
 from invokeai.app.invocations.baseinvocation import BaseInvocation
 from invokeai.app.services.shared.graph import Graph, GraphExecutionState, NodeNotFoundError
+from invokeai.app.services.workflow_records.workflow_records_common import (
+    WorkflowWithoutID,
+    WorkflowWithoutIDValidator,
+)
 from invokeai.app.util.misc import uuid_string
 
 # region Errors
@@ -66,6 +70,9 @@ class Batch(BaseModel):
     batch_id: str = Field(default_factory=uuid_string, description="The ID of the batch")
     data: Optional[BatchDataCollection] = Field(default=None, description="The batch data collection.")
     graph: Graph = Field(description="The graph to initialize the session with")
+    workflow: Optional[WorkflowWithoutID] = Field(
+        default=None, description="The workflow to initialize the session with"
+    )
     runs: int = Field(
         default=1, ge=1, description="Int stating how many times to iterate through all possible batch indices"
     )
@@ -164,6 +171,14 @@ def get_session(queue_item_dict: dict) -> GraphExecutionState:
     return session
 
 
+def get_workflow(queue_item_dict: dict) -> Optional[WorkflowWithoutID]:
+    workflow_raw = queue_item_dict.get("workflow", None)
+    if workflow_raw is not None:
+        workflow = WorkflowWithoutIDValidator.validate_json(workflow_raw, strict=False)
+        return workflow
+    return None
+
+
 class SessionQueueItemWithoutGraph(BaseModel):
     """Session queue item without the full graph. Used for serialization."""
 
@@ -213,12 +228,16 @@ class SessionQueueItemDTO(SessionQueueItemWithoutGraph):
 
 class SessionQueueItem(SessionQueueItemWithoutGraph):
     session: GraphExecutionState = Field(description="The fully-populated session to be executed")
+    workflow: Optional[WorkflowWithoutID] = Field(
+        default=None, description="The workflow associated with this queue item"
+    )
 
     @classmethod
     def queue_item_from_dict(cls, queue_item_dict: dict) -> "SessionQueueItem":
         # must parse these manually
         queue_item_dict["field_values"] = get_field_values(queue_item_dict)
         queue_item_dict["session"] = get_session(queue_item_dict)
+        queue_item_dict["workflow"] = get_workflow(queue_item_dict)
         return SessionQueueItem(**queue_item_dict)
 
     model_config = ConfigDict(
@@ -334,7 +353,7 @@ def populate_graph(graph: Graph, node_field_values: Iterable[NodeFieldValue]) ->
 
 def create_session_nfv_tuples(
     batch: Batch, maximum: int
-) -> Generator[tuple[GraphExecutionState, list[NodeFieldValue]], None, None]:
+) -> Generator[tuple[GraphExecutionState, list[NodeFieldValue], Optional[WorkflowWithoutID]], None, None]:
     """
     Create all graph permutations from the given batch data and graph. Yields tuples
     of the form (graph, batch_data_items) where batch_data_items is the list of BatchDataItems
@@ -365,7 +384,7 @@ def create_session_nfv_tuples(
                 return
             flat_node_field_values = list(chain.from_iterable(d))
             graph = populate_graph(batch.graph, flat_node_field_values)
-            yield (GraphExecutionState(graph=graph), flat_node_field_values)
+            yield (GraphExecutionState(graph=graph), flat_node_field_values, batch.workflow)
             count += 1
 
 
@@ -391,12 +410,14 @@ def calc_session_count(batch: Batch) -> int:
 class SessionQueueValueToInsert(NamedTuple):
     """A tuple of values to insert into the session_queue table"""
 
+    # Careful with the ordering of this - it must match the insert statement
     queue_id: str  # queue_id
     session: str  # session json
     session_id: str  # session_id
     batch_id: str  # batch_id
     field_values: Optional[str]  # field_values json
     priority: int  # priority
+    workflow: Optional[str]  # workflow json
 
 
 ValuesToInsert: TypeAlias = list[SessionQueueValueToInsert]
@@ -404,7 +425,7 @@ ValuesToInsert: TypeAlias = list[SessionQueueValueToInsert]
 
 def prepare_values_to_insert(queue_id: str, batch: Batch, priority: int, max_new_queue_items: int) -> ValuesToInsert:
     values_to_insert: ValuesToInsert = []
-    for session, field_values in create_session_nfv_tuples(batch, max_new_queue_items):
+    for session, field_values, workflow in create_session_nfv_tuples(batch, max_new_queue_items):
         # sessions must have unique id
         session.id = uuid_string()
         values_to_insert.append(
@@ -416,6 +437,7 @@ def prepare_values_to_insert(queue_id: str, batch: Batch, priority: int, max_new
                 # must use pydantic_encoder bc field_values is a list of models
                 json.dumps(field_values, default=to_jsonable_python) if field_values else None,  # field_values (json)
                 priority,  # priority
+                json.dumps(workflow, default=to_jsonable_python) if workflow else None,  # workflow (json)
             )
         )
     return values_to_insert

invokeai/app/services/session_queue/session_queue_sqlite.py

@@ -28,7 +28,7 @@ from invokeai.app.services.session_queue.session_queue_common import (
     prepare_values_to_insert,
 )
 from invokeai.app.services.shared.pagination import CursorPaginatedResults
-from invokeai.app.services.shared.sqlite import SqliteDatabase
+from invokeai.app.services.shared.sqlite.sqlite_database import SqliteDatabase
 
 
 class SqliteSessionQueue(SessionQueueBase):
@@ -42,7 +42,8 @@ class SqliteSessionQueue(SessionQueueBase):
         self._set_in_progress_to_canceled()
         prune_result = self.prune(DEFAULT_QUEUE_ID)
         local_handler.register(event_name=EventServiceBase.queue_event, _func=self._on_session_event)
-        self.__invoker.services.logger.info(f"Pruned {prune_result.deleted} finished queue items")
+        if prune_result.deleted > 0:
+            self.__invoker.services.logger.info(f"Pruned {prune_result.deleted} finished queue items")
 
     def __init__(self, db: SqliteDatabase) -> None:
         super().__init__()
@@ -198,6 +199,15 @@ class SqliteSessionQueue(SessionQueueBase):
                 """
             )
 
+            self.__cursor.execute("PRAGMA table_info(session_queue)")
+            columns = [column[1] for column in self.__cursor.fetchall()]
+            if "workflow" not in columns:
+                self.__cursor.execute(
+                    """--sql
+                    ALTER TABLE session_queue ADD COLUMN workflow TEXT;
+                    """
+                )
+
             self.__conn.commit()
         except Exception:
             self.__conn.rollback()
@@ -280,8 +290,8 @@ class SqliteSessionQueue(SessionQueueBase):
 
             self.__cursor.executemany(
                 """--sql
-                INSERT INTO session_queue (queue_id, session, session_id, batch_id, field_values, priority)
-                VALUES (?, ?, ?, ?, ?, ?)
+                INSERT INTO session_queue (queue_id, session, session_id, batch_id, field_values, priority, workflow)
+                VALUES (?, ?, ?, ?, ?, ?, ?)
                 """,
                 values_to_insert,
             )

invokeai/app/services/shared/graph.py

@@ -207,10 +207,12 @@ class IterateInvocationOutput(BaseInvocationOutput):
     item: Any = OutputField(
         description="The item being iterated over", title="Collection Item", ui_type=UIType._CollectionItem
     )
+    index: int = OutputField(description="The index of the item", title="Index")
+    total: int = OutputField(description="The total number of items", title="Total")
 
 
 # TODO: Fill this out and move to invocations
-@invocation("iterate", version="1.0.0")
+@invocation("iterate", version="1.1.0")
 class IterateInvocation(BaseInvocation):
     """Iterates over a list of items"""
 
@@ -221,7 +223,7 @@ class IterateInvocation(BaseInvocation):
 
     def invoke(self, context: InvocationContext) -> IterateInvocationOutput:
         """Produces the outputs as values"""
-        return IterateInvocationOutput(item=self.collection[self.index])
+        return IterateInvocationOutput(item=self.collection[self.index], index=self.index, total=len(self.collection))
 
 
 @invocation_output("collect_output")

invokeai/app/services/shared/sqlite.py

@@ -1,48 +0,0 @@
-import sqlite3
-import threading
-from logging import Logger
-
-from invokeai.app.services.config import InvokeAIAppConfig
-
-sqlite_memory = ":memory:"
-
-
-class SqliteDatabase:
-    conn: sqlite3.Connection
-    lock: threading.RLock
-    _logger: Logger
-    _config: InvokeAIAppConfig
-
-    def __init__(self, config: InvokeAIAppConfig, logger: Logger):
-        self._logger = logger
-        self._config = config
-
-        if self._config.use_memory_db:
-            location = sqlite_memory
-            logger.info("Using in-memory database")
-        else:
-            db_path = self._config.db_path
-            db_path.parent.mkdir(parents=True, exist_ok=True)
-            location = str(db_path)
-            self._logger.info(f"Using database at {location}")
-
-        self.conn = sqlite3.connect(location, check_same_thread=False)
-        self.lock = threading.RLock()
-        self.conn.row_factory = sqlite3.Row
-
-        if self._config.log_sql:
-            self.conn.set_trace_callback(self._logger.debug)
-
-        self.conn.execute("PRAGMA foreign_keys = ON;")
-
-    def clean(self) -> None:
-        try:
-            self.lock.acquire()
-            self.conn.execute("VACUUM;")
-            self.conn.commit()
-            self._logger.info("Cleaned database")
-        except Exception as e:
-            self._logger.error(f"Error cleaning database: {e}")
-            raise e
-        finally:
-            self.lock.release()

invokeai/app/services/shared/sqlite/sqlite_common.py

@@ -0,0 +1,10 @@
+from enum import Enum
+
+from invokeai.app.util.metaenum import MetaEnum
+
+sqlite_memory = ":memory:"
+
+
+class SQLiteDirection(str, Enum, metaclass=MetaEnum):
+    Ascending = "ASC"
+    Descending = "DESC"

invokeai/app/services/shared/sqlite/sqlite_database.py

@@ -0,0 +1,47 @@
+import sqlite3
+import threading
+from logging import Logger
+from pathlib import Path
+
+from invokeai.app.services.config import InvokeAIAppConfig
+from invokeai.app.services.shared.sqlite.sqlite_common import sqlite_memory
+
+
+class SqliteDatabase:
+    def __init__(self, config: InvokeAIAppConfig, logger: Logger):
+        self._logger = logger
+        self._config = config
+
+        if self._config.use_memory_db:
+            self.db_path = sqlite_memory
+            logger.info("Using in-memory database")
+        else:
+            db_path = self._config.db_path
+            db_path.parent.mkdir(parents=True, exist_ok=True)
+            self.db_path = str(db_path)
+            self._logger.info(f"Using database at {self.db_path}")
+
+        self.conn = sqlite3.connect(self.db_path, check_same_thread=False)
+        self.lock = threading.RLock()
+        self.conn.row_factory = sqlite3.Row
+
+        if self._config.log_sql:
+            self.conn.set_trace_callback(self._logger.debug)
+
+        self.conn.execute("PRAGMA foreign_keys = ON;")
+
+    def clean(self) -> None:
+        with self.lock:
+            try:
+                if self.db_path == sqlite_memory:
+                    return
+                initial_db_size = Path(self.db_path).stat().st_size
+                self.conn.execute("VACUUM;")
+                self.conn.commit()
+                final_db_size = Path(self.db_path).stat().st_size
+                freed_space_in_mb = round((initial_db_size - final_db_size) / 1024 / 1024, 2)
+                if freed_space_in_mb > 0:
+                    self._logger.info(f"Cleaned database (freed {freed_space_in_mb}MB)")
+            except Exception as e:
+                self._logger.error(f"Error cleaning database: {e}")
+                raise

invokeai/app/services/workflow_image_records/workflow_image_records_base.py

@@ -1,23 +0,0 @@
-from abc import ABC, abstractmethod
-from typing import Optional
-
-
-class WorkflowImageRecordsStorageBase(ABC):
-    """Abstract base class for the one-to-many workflow-image relationship record storage."""
-
-    @abstractmethod
-    def create(
-        self,
-        workflow_id: str,
-        image_name: str,
-    ) -> None:
-        """Creates a workflow-image record."""
-        pass
-
-    @abstractmethod
-    def get_workflow_for_image(
-        self,
-        image_name: str,
-    ) -> Optional[str]:
-        """Gets an image's workflow id, if it has one."""
-        pass

invokeai/app/services/workflow_image_records/workflow_image_records_sqlite.py

@@ -1,122 +0,0 @@
-import sqlite3
-import threading
-from typing import Optional, cast
-
-from invokeai.app.services.shared.sqlite import SqliteDatabase
-from invokeai.app.services.workflow_image_records.workflow_image_records_base import WorkflowImageRecordsStorageBase
-
-
-class SqliteWorkflowImageRecordsStorage(WorkflowImageRecordsStorageBase):
-    """SQLite implementation of WorkflowImageRecordsStorageBase."""
-
-    _conn: sqlite3.Connection
-    _cursor: sqlite3.Cursor
-    _lock: threading.RLock
-
-    def __init__(self, db: SqliteDatabase) -> None:
-        super().__init__()
-        self._lock = db.lock
-        self._conn = db.conn
-        self._cursor = self._conn.cursor()
-
-        try:
-            self._lock.acquire()
-            self._create_tables()
-            self._conn.commit()
-        finally:
-            self._lock.release()
-
-    def _create_tables(self) -> None:
-        # Create the `workflow_images` junction table.
-        self._cursor.execute(
-            """--sql
-            CREATE TABLE IF NOT EXISTS workflow_images (
-                workflow_id TEXT NOT NULL,
-                image_name TEXT NOT NULL,
-                created_at DATETIME NOT NULL DEFAULT(STRFTIME('%Y-%m-%d %H:%M:%f', 'NOW')),
-                -- updated via trigger
-                updated_at DATETIME NOT NULL DEFAULT(STRFTIME('%Y-%m-%d %H:%M:%f', 'NOW')),
-                -- Soft delete, currently unused
-                deleted_at DATETIME,
-                -- enforce one-to-many relationship between workflows and images using PK
-                -- (we can extend this to many-to-many later)
-                PRIMARY KEY (image_name),
-                FOREIGN KEY (workflow_id) REFERENCES workflows (workflow_id) ON DELETE CASCADE,
-                FOREIGN KEY (image_name) REFERENCES images (image_name) ON DELETE CASCADE
-            );
-            """
-        )
-
-        # Add index for workflow id
-        self._cursor.execute(
-            """--sql
-            CREATE INDEX IF NOT EXISTS idx_workflow_images_workflow_id ON workflow_images (workflow_id);
-            """
-        )
-
-        # Add index for workflow id, sorted by created_at
-        self._cursor.execute(
-            """--sql
-            CREATE INDEX IF NOT EXISTS idx_workflow_images_workflow_id_created_at ON workflow_images (workflow_id, created_at);
-            """
-        )
-
-        # Add trigger for `updated_at`.
-        self._cursor.execute(
-            """--sql
-            CREATE TRIGGER IF NOT EXISTS tg_workflow_images_updated_at
-            AFTER UPDATE
-            ON workflow_images FOR EACH ROW
-            BEGIN
-                UPDATE workflow_images SET updated_at = STRFTIME('%Y-%m-%d %H:%M:%f', 'NOW')
-                    WHERE workflow_id = old.workflow_id AND image_name = old.image_name;
-            END;
-            """
-        )
-
-    def create(
-        self,
-        workflow_id: str,
-        image_name: str,
-    ) -> None:
-        """Creates a workflow-image record."""
-        try:
-            self._lock.acquire()
-            self._cursor.execute(
-                """--sql
-                INSERT INTO workflow_images (workflow_id, image_name)
-                VALUES (?, ?);
-                """,
-                (workflow_id, image_name),
-            )
-            self._conn.commit()
-        except sqlite3.Error as e:
-            self._conn.rollback()
-            raise e
-        finally:
-            self._lock.release()
-
-    def get_workflow_for_image(
-        self,
-        image_name: str,
-    ) -> Optional[str]:
-        """Gets an image's workflow id, if it has one."""
-        try:
-            self._lock.acquire()
-            self._cursor.execute(
-                """--sql
-                SELECT workflow_id
-                FROM workflow_images
-                WHERE image_name = ?;
-                """,
-                (image_name,),
-            )
-            result = self._cursor.fetchone()
-            if result is None:
-                return None
-            return cast(str, result[0])
-        except sqlite3.Error as e:
-            self._conn.rollback()
-            raise e
-        finally:
-            self._lock.release()

invokeai/app/services/workflow_records/default_workflows/README.md

@@ -0,0 +1,17 @@
+# Default Workflows
+
+Workflows placed in this directory will be synced to the `workflow_library` as
+_default workflows_ on app startup.
+
+- Default workflows are not editable by users. If they are loaded and saved,
+  they will save as a copy of the default workflow.
+- Default workflows must have the `meta.category` property set to `"default"`.
+  An exception will be raised during sync if this is not set correctly.
+- Default workflows appear on the "Default Workflows" tab of the Workflow
+  Library.
+
+After adding or updating default workflows, you **must** start the app up and
+load them to ensure:
+
+- The workflow loads without warning or errors
+- The workflow runs successfully

invokeai/app/services/workflow_records/default_workflows/TextToImage_SD15.json

@@ -0,0 +1,798 @@
+{
+  "name": "Text to Image - SD1.5",
+  "author": "InvokeAI",
+  "description": "Sample text to image workflow for Stable Diffusion 1.5/2",
+  "version": "1.1.0",
+  "contact": "invoke@invoke.ai",
+  "tags": "text2image, SD1.5, SD2, default",
+  "notes": "",
+  "exposedFields": [
+    {
+      "nodeId": "c8d55139-f380-4695-b7f2-8b3d1e1e3db8",
+      "fieldName": "model"
+    },
+    {
+      "nodeId": "7d8bf987-284f-413a-b2fd-d825445a5d6c",
+      "fieldName": "prompt"
+    },
+    {
+      "nodeId": "93dc02a4-d05b-48ed-b99c-c9b616af3402",
+      "fieldName": "prompt"
+    },
+    {
+      "nodeId": "55705012-79b9-4aac-9f26-c0b10309785b",
+      "fieldName": "width"
+    },
+    {
+      "nodeId": "55705012-79b9-4aac-9f26-c0b10309785b",
+      "fieldName": "height"
+    }
+  ],
+  "meta": {
+    "category": "default",
+    "version": "2.0.0"
+  },
+  "nodes": [
+    {
+      "id": "93dc02a4-d05b-48ed-b99c-c9b616af3402",
+      "type": "invocation",
+      "data": {
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+        "type": "compel",
+        "label": "Negative Compel Prompt",
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+        "notes": "",
+        "isIntermediate": true,
+        "useCache": true,
+        "version": "1.0.0",
+        "nodePack": "invokeai",
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+            "name": "prompt",
+            "fieldKind": "input",
+            "label": "Negative Prompt",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "StringField"
+            },
+            "value": ""
+          },
+          "clip": {
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+            "name": "clip",
+            "fieldKind": "input",
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+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "ClipField"
+            }
+          }
+        },
+        "outputs": {
+          "conditioning": {
+            "id": "37cf3a9d-f6b7-4b64-8ff6-2558c5ecc447",
+            "name": "conditioning",
+            "fieldKind": "output",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "ConditioningField"
+            }
+          }
+        }
+      },
+      "width": 320,
+      "height": 259,
+      "position": {
+        "x": 1000,
+        "y": 350
+      }
+    },
+    {
+      "id": "55705012-79b9-4aac-9f26-c0b10309785b",
+      "type": "invocation",
+      "data": {
+        "id": "55705012-79b9-4aac-9f26-c0b10309785b",
+        "type": "noise",
+        "label": "",
+        "isOpen": true,
+        "notes": "",
+        "isIntermediate": true,
+        "useCache": true,
+        "version": "1.0.1",
+        "nodePack": "invokeai",
+        "inputs": {
+          "seed": {
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+            "type": {
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+            },
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+          },
+          "width": {
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+            "fieldKind": "input",
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+            "type": {
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+              "name": "IntegerField"
+            },
+            "value": 512
+          },
+          "height": {
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+            "fieldKind": "input",
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+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "IntegerField"
+            },
+            "value": 512
+          },
+          "use_cpu": {
+            "id": "c7c436d3-7a7a-4e76-91e4-c6deb271623c",
+            "name": "use_cpu",
+            "fieldKind": "input",
+            "label": "",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "BooleanField"
+            },
+            "value": true
+          }
+        },
+        "outputs": {
+          "noise": {
+            "id": "50f650dc-0184-4e23-a927-0497a96fe954",
+            "name": "noise",
+            "fieldKind": "output",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "LatentsField"
+            }
+          },
+          "width": {
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+            "name": "width",
+            "fieldKind": "output",
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+            }
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+            }
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+      }
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+    {
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+      "data": {
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+        "type": "main_model_loader",
+        "label": "",
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+        "notes": "",
+        "isIntermediate": true,
+        "useCache": true,
+        "version": "1.0.0",
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+              "isCollectionOrScalar": false,
+              "name": "MainModelField"
+            },
+            "value": {
+              "model_name": "stable-diffusion-v1-5",
+              "base_model": "sd-1",
+              "model_type": "main"
+            }
+          }
+        },
+        "outputs": {
+          "unet": {
+            "id": "5c18c9db-328d-46d0-8cb9-143391c410be",
+            "name": "unet",
+            "fieldKind": "output",
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+              "name": "UNetField"
+            }
+          },
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+            }
+          },
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+            }
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+      }
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+          }
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+        "outputs": {
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+              "isCollectionOrScalar": true,
+              "name": "FloatField"
+            },
+            "value": 7.5
+          },
+          "denoising_start": {
+            "id": "f369d80f-4931-4740-9bcd-9f0620719fab",
+            "name": "denoising_start",
+            "fieldKind": "input",
+            "label": "",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "FloatField"
+            },
+            "value": 0
+          },
+          "denoising_end": {
+            "id": "747d10e5-6f02-445c-994c-0604d814de8c",
+            "name": "denoising_end",
+            "fieldKind": "input",
+            "label": "",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "FloatField"
+            },
+            "value": 1
+          },
+          "scheduler": {
+            "id": "1de84a4e-3a24-4ec8-862b-16ce49633b9b",
+            "name": "scheduler",
+            "fieldKind": "input",
+            "label": "",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "SchedulerField"
+            },
+            "value": "unipc"
+          },
+          "unet": {
+            "id": "ffa6fef4-3ce2-4bdb-9296-9a834849489b",
+            "name": "unet",
+            "fieldKind": "input",
+            "label": "",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "UNetField"
+            }
+          },
+          "control": {
+            "id": "077b64cb-34be-4fcc-83f2-e399807a02bd",
+            "name": "control",
+            "fieldKind": "input",
+            "label": "",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": true,
+              "name": "ControlField"
+            }
+          },
+          "ip_adapter": {
+            "id": "1d6948f7-3a65-4a65-a20c-768b287251aa",
+            "name": "ip_adapter",
+            "fieldKind": "input",
+            "label": "",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": true,
+              "name": "IPAdapterField"
+            }
+          },
+          "t2i_adapter": {
+            "id": "75e67b09-952f-4083-aaf4-6b804d690412",
+            "name": "t2i_adapter",
+            "fieldKind": "input",
+            "label": "",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": true,
+              "name": "T2IAdapterField"
+            }
+          },
+          "cfg_rescale_multiplier": {
+            "id": "9101f0a6-5fe0-4826-b7b3-47e5d506826c",
+            "name": "cfg_rescale_multiplier",
+            "fieldKind": "input",
+            "label": "",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "FloatField"
+            },
+            "value": 0
+          },
+          "latents": {
+            "id": "334d4ba3-5a99-4195-82c5-86fb3f4f7d43",
+            "name": "latents",
+            "fieldKind": "input",
+            "label": "",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "LatentsField"
+            }
+          },
+          "denoise_mask": {
+            "id": "0d3dbdbf-b014-4e95-8b18-ff2ff9cb0bfa",
+            "name": "denoise_mask",
+            "fieldKind": "input",
+            "label": "",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "DenoiseMaskField"
+            }
+          }
+        },
+        "outputs": {
+          "latents": {
+            "id": "70fa5bbc-0c38-41bb-861a-74d6d78d2f38",
+            "name": "latents",
+            "fieldKind": "output",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "LatentsField"
+            }
+          },
+          "width": {
+            "id": "98ee0e6c-82aa-4e8f-8be5-dc5f00ee47f0",
+            "name": "width",
+            "fieldKind": "output",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "IntegerField"
+            }
+          },
+          "height": {
+            "id": "e8cb184a-5e1a-47c8-9695-4b8979564f5d",
+            "name": "height",
+            "fieldKind": "output",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "IntegerField"
+            }
+          }
+        }
+      },
+      "width": 320,
+      "height": 703,
+      "position": {
+        "x": 1400,
+        "y": 25
+      }
+    },
+    {
+      "id": "58c957f5-0d01-41fc-a803-b2bbf0413d4f",
+      "type": "invocation",
+      "data": {
+        "id": "58c957f5-0d01-41fc-a803-b2bbf0413d4f",
+        "type": "l2i",
+        "label": "",
+        "isOpen": true,
+        "notes": "",
+        "isIntermediate": false,
+        "useCache": true,
+        "version": "1.2.0",
+        "nodePack": "invokeai",
+        "inputs": {
+          "metadata": {
+            "id": "ab375f12-0042-4410-9182-29e30db82c85",
+            "name": "metadata",
+            "fieldKind": "input",
+            "label": "",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "MetadataField"
+            }
+          },
+          "latents": {
+            "id": "3a7e7efd-bff5-47d7-9d48-615127afee78",
+            "name": "latents",
+            "fieldKind": "input",
+            "label": "",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "LatentsField"
+            }
+          },
+          "vae": {
+            "id": "a1f5f7a1-0795-4d58-b036-7820c0b0ef2b",
+            "name": "vae",
+            "fieldKind": "input",
+            "label": "",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "VaeField"
+            }
+          },
+          "tiled": {
+            "id": "da52059a-0cee-4668-942f-519aa794d739",
+            "name": "tiled",
+            "fieldKind": "input",
+            "label": "",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "BooleanField"
+            },
+            "value": false
+          },
+          "fp32": {
+            "id": "c4841df3-b24e-4140-be3b-ccd454c2522c",
+            "name": "fp32",
+            "fieldKind": "input",
+            "label": "",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "BooleanField"
+            },
+            "value": true
+          }
+        },
+        "outputs": {
+          "image": {
+            "id": "72d667d0-cf85-459d-abf2-28bd8b823fe7",
+            "name": "image",
+            "fieldKind": "output",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "ImageField"
+            }
+          },
+          "width": {
+            "id": "c8c907d8-1066-49d1-b9a6-83bdcd53addc",
+            "name": "width",
+            "fieldKind": "output",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "IntegerField"
+            }
+          },
+          "height": {
+            "id": "230f359c-b4ea-436c-b372-332d7dcdca85",
+            "name": "height",
+            "fieldKind": "output",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "IntegerField"
+            }
+          }
+        }
+      },
+      "width": 320,
+      "height": 266,
+      "position": {
+        "x": 1800,
+        "y": 25
+      }
+    }
+  ],
+  "edges": [
+    {
+      "id": "reactflow__edge-ea94bc37-d995-4a83-aa99-4af42479f2f2value-55705012-79b9-4aac-9f26-c0b10309785bseed",
+      "source": "ea94bc37-d995-4a83-aa99-4af42479f2f2",
+      "target": "55705012-79b9-4aac-9f26-c0b10309785b",
+      "type": "default",
+      "sourceHandle": "value",
+      "targetHandle": "seed"
+    },
+    {
+      "id": "reactflow__edge-c8d55139-f380-4695-b7f2-8b3d1e1e3db8clip-7d8bf987-284f-413a-b2fd-d825445a5d6cclip",
+      "source": "c8d55139-f380-4695-b7f2-8b3d1e1e3db8",
+      "target": "7d8bf987-284f-413a-b2fd-d825445a5d6c",
+      "type": "default",
+      "sourceHandle": "clip",
+      "targetHandle": "clip"
+    },
+    {
+      "id": "reactflow__edge-c8d55139-f380-4695-b7f2-8b3d1e1e3db8clip-93dc02a4-d05b-48ed-b99c-c9b616af3402clip",
+      "source": "c8d55139-f380-4695-b7f2-8b3d1e1e3db8",
+      "target": "93dc02a4-d05b-48ed-b99c-c9b616af3402",
+      "type": "default",
+      "sourceHandle": "clip",
+      "targetHandle": "clip"
+    },
+    {
+      "id": "reactflow__edge-55705012-79b9-4aac-9f26-c0b10309785bnoise-eea2702a-19fb-45b5-9d75-56b4211ec03cnoise",
+      "source": "55705012-79b9-4aac-9f26-c0b10309785b",
+      "target": "eea2702a-19fb-45b5-9d75-56b4211ec03c",
+      "type": "default",
+      "sourceHandle": "noise",
+      "targetHandle": "noise"
+    },
+    {
+      "id": "reactflow__edge-7d8bf987-284f-413a-b2fd-d825445a5d6cconditioning-eea2702a-19fb-45b5-9d75-56b4211ec03cpositive_conditioning",
+      "source": "7d8bf987-284f-413a-b2fd-d825445a5d6c",
+      "target": "eea2702a-19fb-45b5-9d75-56b4211ec03c",
+      "type": "default",
+      "sourceHandle": "conditioning",
+      "targetHandle": "positive_conditioning"
+    },
+    {
+      "id": "reactflow__edge-93dc02a4-d05b-48ed-b99c-c9b616af3402conditioning-eea2702a-19fb-45b5-9d75-56b4211ec03cnegative_conditioning",
+      "source": "93dc02a4-d05b-48ed-b99c-c9b616af3402",
+      "target": "eea2702a-19fb-45b5-9d75-56b4211ec03c",
+      "type": "default",
+      "sourceHandle": "conditioning",
+      "targetHandle": "negative_conditioning"
+    },
+    {
+      "id": "reactflow__edge-c8d55139-f380-4695-b7f2-8b3d1e1e3db8unet-eea2702a-19fb-45b5-9d75-56b4211ec03cunet",
+      "source": "c8d55139-f380-4695-b7f2-8b3d1e1e3db8",
+      "target": "eea2702a-19fb-45b5-9d75-56b4211ec03c",
+      "type": "default",
+      "sourceHandle": "unet",
+      "targetHandle": "unet"
+    },
+    {
+      "id": "reactflow__edge-eea2702a-19fb-45b5-9d75-56b4211ec03clatents-58c957f5-0d01-41fc-a803-b2bbf0413d4flatents",
+      "source": "eea2702a-19fb-45b5-9d75-56b4211ec03c",
+      "target": "58c957f5-0d01-41fc-a803-b2bbf0413d4f",
+      "type": "default",
+      "sourceHandle": "latents",
+      "targetHandle": "latents"
+    },
+    {
+      "id": "reactflow__edge-c8d55139-f380-4695-b7f2-8b3d1e1e3db8vae-58c957f5-0d01-41fc-a803-b2bbf0413d4fvae",
+      "source": "c8d55139-f380-4695-b7f2-8b3d1e1e3db8",
+      "target": "58c957f5-0d01-41fc-a803-b2bbf0413d4f",
+      "type": "default",
+      "sourceHandle": "vae",
+      "targetHandle": "vae"
+    }
+  ]
+}

invokeai/app/services/workflow_records/workflow_records_base.py

@@ -1,17 +1,50 @@
 from abc import ABC, abstractmethod
+from typing import Optional
 
-from invokeai.app.invocations.baseinvocation import WorkflowField
+from invokeai.app.services.shared.pagination import PaginatedResults
+from invokeai.app.services.shared.sqlite.sqlite_common import SQLiteDirection
+from invokeai.app.services.workflow_records.workflow_records_common import (
+    Workflow,
+    WorkflowCategory,
+    WorkflowRecordDTO,
+    WorkflowRecordListItemDTO,
+    WorkflowRecordOrderBy,
+    WorkflowWithoutID,
+)
 
 
 class WorkflowRecordsStorageBase(ABC):
     """Base class for workflow storage services."""
 
     @abstractmethod
-    def get(self, workflow_id: str) -> WorkflowField:
+    def get(self, workflow_id: str) -> WorkflowRecordDTO:
         """Get workflow by id."""
         pass
 
     @abstractmethod
-    def create(self, workflow: WorkflowField) -> WorkflowField:
+    def create(self, workflow: WorkflowWithoutID) -> WorkflowRecordDTO:
         """Creates a workflow."""
         pass
+
+    @abstractmethod
+    def update(self, workflow: Workflow) -> WorkflowRecordDTO:
+        """Updates a workflow."""
+        pass
+
+    @abstractmethod
+    def delete(self, workflow_id: str) -> None:
+        """Deletes a workflow."""
+        pass
+
+    @abstractmethod
+    def get_many(
+        self,
+        page: int,
+        per_page: int,
+        order_by: WorkflowRecordOrderBy,
+        direction: SQLiteDirection,
+        category: WorkflowCategory,
+        query: Optional[str],
+    ) -> PaginatedResults[WorkflowRecordListItemDTO]:
+        """Gets many workflows."""
+        pass

invokeai/app/services/workflow_records/workflow_records_common.py

@@ -1,2 +1,104 @@
+import datetime
+from enum import Enum
+from typing import Any, Union
+
+import semver
+from pydantic import BaseModel, Field, JsonValue, TypeAdapter, field_validator
+
+from invokeai.app.util.metaenum import MetaEnum
+from invokeai.app.util.misc import uuid_string
+
+__workflow_meta_version__ = semver.Version.parse("1.0.0")
+
+
+class ExposedField(BaseModel):
+    nodeId: str
+    fieldName: str
+
+
 class WorkflowNotFoundError(Exception):
     """Raised when a workflow is not found"""
+
+
+class WorkflowRecordOrderBy(str, Enum, metaclass=MetaEnum):
+    """The order by options for workflow records"""
+
+    CreatedAt = "created_at"
+    UpdatedAt = "updated_at"
+    OpenedAt = "opened_at"
+    Name = "name"
+
+
+class WorkflowCategory(str, Enum, metaclass=MetaEnum):
+    User = "user"
+    Default = "default"
+    Project = "project"
+
+
+class WorkflowMeta(BaseModel):
+    version: str = Field(description="The version of the workflow schema.")
+    category: WorkflowCategory = Field(description="The category of the workflow (user or default).")
+
+    @field_validator("version")
+    def validate_version(cls, version: str):
+        try:
+            semver.Version.parse(version)
+            return version
+        except Exception:
+            raise ValueError(f"Invalid workflow meta version: {version}")
+
+    def to_semver(self) -> semver.Version:
+        return semver.Version.parse(self.version)
+
+
+class WorkflowWithoutID(BaseModel):
+    name: str = Field(description="The name of the workflow.")
+    author: str = Field(description="The author of the workflow.")
+    description: str = Field(description="The description of the workflow.")
+    version: str = Field(description="The version of the workflow.")
+    contact: str = Field(description="The contact of the workflow.")
+    tags: str = Field(description="The tags of the workflow.")
+    notes: str = Field(description="The notes of the workflow.")
+    exposedFields: list[ExposedField] = Field(description="The exposed fields of the workflow.")
+    meta: WorkflowMeta = Field(description="The meta of the workflow.")
+    # TODO: nodes and edges are very loosely typed
+    nodes: list[dict[str, JsonValue]] = Field(description="The nodes of the workflow.")
+    edges: list[dict[str, JsonValue]] = Field(description="The edges of the workflow.")
+
+
+WorkflowWithoutIDValidator = TypeAdapter(WorkflowWithoutID)
+
+
+class Workflow(WorkflowWithoutID):
+    id: str = Field(default_factory=uuid_string, description="The id of the workflow.")
+
+
+WorkflowValidator = TypeAdapter(Workflow)
+
+
+class WorkflowRecordDTOBase(BaseModel):
+    workflow_id: str = Field(description="The id of the workflow.")
+    name: str = Field(description="The name of the workflow.")
+    created_at: Union[datetime.datetime, str] = Field(description="The created timestamp of the workflow.")
+    updated_at: Union[datetime.datetime, str] = Field(description="The updated timestamp of the workflow.")
+    opened_at: Union[datetime.datetime, str] = Field(description="The opened timestamp of the workflow.")
+
+
+class WorkflowRecordDTO(WorkflowRecordDTOBase):
+    workflow: Workflow = Field(description="The workflow.")
+
+    @classmethod
+    def from_dict(cls, data: dict[str, Any]) -> "WorkflowRecordDTO":
+        data["workflow"] = WorkflowValidator.validate_json(data.get("workflow", ""))
+        return WorkflowRecordDTOValidator.validate_python(data)
+
+
+WorkflowRecordDTOValidator = TypeAdapter(WorkflowRecordDTO)
+
+
+class WorkflowRecordListItemDTO(WorkflowRecordDTOBase):
+    description: str = Field(description="The description of the workflow.")
+    category: WorkflowCategory = Field(description="The description of the workflow.")
+
+
+WorkflowRecordListItemDTOValidator = TypeAdapter(WorkflowRecordListItemDTO)

invokeai/app/services/workflow_records/workflow_records_sqlite.py

@@ -1,20 +1,25 @@
-import sqlite3
-import threading
+from pathlib import Path
+from typing import Optional
 
-from invokeai.app.invocations.baseinvocation import WorkflowField, WorkflowFieldValidator
 from invokeai.app.services.invoker import Invoker
-from invokeai.app.services.shared.sqlite import SqliteDatabase
+from invokeai.app.services.shared.pagination import PaginatedResults
+from invokeai.app.services.shared.sqlite.sqlite_common import SQLiteDirection
+from invokeai.app.services.shared.sqlite.sqlite_database import SqliteDatabase
 from invokeai.app.services.workflow_records.workflow_records_base import WorkflowRecordsStorageBase
-from invokeai.app.services.workflow_records.workflow_records_common import WorkflowNotFoundError
-from invokeai.app.util.misc import uuid_string
+from invokeai.app.services.workflow_records.workflow_records_common import (
+    Workflow,
+    WorkflowCategory,
+    WorkflowNotFoundError,
+    WorkflowRecordDTO,
+    WorkflowRecordListItemDTO,
+    WorkflowRecordListItemDTOValidator,
+    WorkflowRecordOrderBy,
+    WorkflowValidator,
+    WorkflowWithoutID,
+)
 
 
 class SqliteWorkflowRecordsStorage(WorkflowRecordsStorageBase):
-    _invoker: Invoker
-    _conn: sqlite3.Connection
-    _cursor: sqlite3.Cursor
-    _lock: threading.RLock
-
     def __init__(self, db: SqliteDatabase) -> None:
         super().__init__()
         self._lock = db.lock
@@ -24,14 +29,25 @@ class SqliteWorkflowRecordsStorage(WorkflowRecordsStorageBase):
 
     def start(self, invoker: Invoker) -> None:
         self._invoker = invoker
+        self._sync_default_workflows()
 
-    def get(self, workflow_id: str) -> WorkflowField:
+    def get(self, workflow_id: str) -> WorkflowRecordDTO:
+        """Gets a workflow by ID. Updates the opened_at column."""
         try:
             self._lock.acquire()
             self._cursor.execute(
                 """--sql
-                SELECT workflow
-                FROM workflows
+                UPDATE workflow_library
+                SET opened_at = STRFTIME('%Y-%m-%d %H:%M:%f', 'NOW')
+                WHERE workflow_id = ?;
+                """,
+                (workflow_id,),
+            )
+            self._conn.commit()
+            self._cursor.execute(
+                """--sql
+                SELECT workflow_id, workflow, name, created_at, updated_at, opened_at
+                FROM workflow_library
                 WHERE workflow_id = ?;
                 """,
                 (workflow_id,),
@@ -39,25 +55,28 @@ class SqliteWorkflowRecordsStorage(WorkflowRecordsStorageBase):
             row = self._cursor.fetchone()
             if row is None:
                 raise WorkflowNotFoundError(f"Workflow with id {workflow_id} not found")
-            return WorkflowFieldValidator.validate_json(row[0])
+            return WorkflowRecordDTO.from_dict(dict(row))
         except Exception:
             self._conn.rollback()
             raise
         finally:
             self._lock.release()
 
-    def create(self, workflow: WorkflowField) -> WorkflowField:
+    def create(self, workflow: WorkflowWithoutID) -> WorkflowRecordDTO:
         try:
-            # workflows do not have ids until they are saved
-            workflow_id = uuid_string()
-            workflow.root["id"] = workflow_id
+            # Only user workflows may be created by this method
+            assert workflow.meta.category is WorkflowCategory.User
+            workflow_with_id = WorkflowValidator.validate_python(workflow.model_dump())
             self._lock.acquire()
             self._cursor.execute(
                 """--sql
-                INSERT INTO workflows(workflow)
-                VALUES (?);
+                INSERT OR IGNORE INTO workflow_library (
+                    workflow_id,
+                    workflow
+                )
+                VALUES (?, ?);
                 """,
-                (workflow.model_dump_json(),),
+                (workflow_with_id.id, workflow_with_id.model_dump_json()),
             )
             self._conn.commit()
         except Exception:
@@ -65,35 +84,231 @@ class SqliteWorkflowRecordsStorage(WorkflowRecordsStorageBase):
             raise
         finally:
             self._lock.release()
-        return self.get(workflow_id)
+        return self.get(workflow_with_id.id)
+
+    def update(self, workflow: Workflow) -> WorkflowRecordDTO:
+        try:
+            self._lock.acquire()
+            self._cursor.execute(
+                """--sql
+                UPDATE workflow_library
+                SET workflow = ?
+                WHERE workflow_id = ? AND category = 'user';
+                """,
+                (workflow.model_dump_json(), workflow.id),
+            )
+            self._conn.commit()
+        except Exception:
+            self._conn.rollback()
+            raise
+        finally:
+            self._lock.release()
+        return self.get(workflow.id)
+
+    def delete(self, workflow_id: str) -> None:
+        try:
+            self._lock.acquire()
+            self._cursor.execute(
+                """--sql
+                DELETE from workflow_library
+                WHERE workflow_id = ? AND category = 'user';
+                """,
+                (workflow_id,),
+            )
+            self._conn.commit()
+        except Exception:
+            self._conn.rollback()
+            raise
+        finally:
+            self._lock.release()
+        return None
+
+    def get_many(
+        self,
+        page: int,
+        per_page: int,
+        order_by: WorkflowRecordOrderBy,
+        direction: SQLiteDirection,
+        category: WorkflowCategory,
+        query: Optional[str] = None,
+    ) -> PaginatedResults[WorkflowRecordListItemDTO]:
+        try:
+            self._lock.acquire()
+            # sanitize!
+            assert order_by in WorkflowRecordOrderBy
+            assert direction in SQLiteDirection
+            assert category in WorkflowCategory
+            count_query = "SELECT COUNT(*) FROM workflow_library WHERE category = ?"
+            main_query = """
+                SELECT
+                    workflow_id,
+                    category,
+                    name,
+                    description,
+                    created_at,
+                    updated_at,
+                    opened_at
+                FROM workflow_library
+                WHERE category = ?
+                """
+            main_params: list[int | str] = [category.value]
+            count_params: list[int | str] = [category.value]
+            stripped_query = query.strip() if query else None
+            if stripped_query:
+                wildcard_query = "%" + stripped_query + "%"
+                main_query += " AND name LIKE ? OR description LIKE ? "
+                count_query += " AND name LIKE ? OR description LIKE ?;"
+                main_params.extend([wildcard_query, wildcard_query])
+                count_params.extend([wildcard_query, wildcard_query])
+
+            main_query += f" ORDER BY {order_by.value} {direction.value} LIMIT ? OFFSET ?;"
+            main_params.extend([per_page, page * per_page])
+            self._cursor.execute(main_query, main_params)
+            rows = self._cursor.fetchall()
+            workflows = [WorkflowRecordListItemDTOValidator.validate_python(dict(row)) for row in rows]
+
+            self._cursor.execute(count_query, count_params)
+            total = self._cursor.fetchone()[0]
+            pages = int(total / per_page) + 1
+
+            return PaginatedResults(
+                items=workflows,
+                page=page,
+                per_page=per_page,
+                pages=pages,
+                total=total,
+            )
+        except Exception:
+            self._conn.rollback()
+            raise
+        finally:
+            self._lock.release()
+
+    def _sync_default_workflows(self) -> None:
+        """Syncs default workflows to the database. Internal use only."""
+
+        """
+        An enhancement might be to only update workflows that have changed. This would require stable
+        default workflow IDs, and properly incrementing the workflow version.
+
+        It's much simpler to just replace them all with whichever workflows are in the directory.
+
+        The downside is that the `updated_at` and `opened_at` timestamps for default workflows are
+        meaningless, as they are overwritten every time the server starts.
+        """
+
+        try:
+            self._lock.acquire()
+            workflows: list[Workflow] = []
+            workflows_dir = Path(__file__).parent / Path("default_workflows")
+            workflow_paths = workflows_dir.glob("*.json")
+            for path in workflow_paths:
+                bytes_ = path.read_bytes()
+                workflow = WorkflowValidator.validate_json(bytes_)
+                workflows.append(workflow)
+            # Only default workflows may be managed by this method
+            assert all(w.meta.category is WorkflowCategory.Default for w in workflows)
+            self._cursor.execute(
+                """--sql
+                DELETE FROM workflow_library
+                WHERE category = 'default';
+                """
+            )
+            for w in workflows:
+                self._cursor.execute(
+                    """--sql
+                    INSERT OR REPLACE INTO workflow_library (
+                        workflow_id,
+                        workflow
+                    )
+                    VALUES (?, ?);
+                    """,
+                    (w.id, w.model_dump_json()),
+                )
+            self._conn.commit()
+        except Exception:
+            self._conn.rollback()
+            raise
+        finally:
+            self._lock.release()
 
     def _create_tables(self) -> None:
         try:
             self._lock.acquire()
             self._cursor.execute(
                 """--sql
-                CREATE TABLE IF NOT EXISTS workflows (
+                CREATE TABLE IF NOT EXISTS workflow_library (
+                    workflow_id TEXT NOT NULL PRIMARY KEY,
                     workflow TEXT NOT NULL,
-                    workflow_id TEXT GENERATED ALWAYS AS (json_extract(workflow, '$.id')) VIRTUAL NOT NULL UNIQUE, -- gets implicit index
                     created_at DATETIME NOT NULL DEFAULT(STRFTIME('%Y-%m-%d %H:%M:%f', 'NOW')),
-                    updated_at DATETIME NOT NULL DEFAULT(STRFTIME('%Y-%m-%d %H:%M:%f', 'NOW')) -- updated via trigger
+                    -- updated via trigger
+                    updated_at DATETIME NOT NULL DEFAULT(STRFTIME('%Y-%m-%d %H:%M:%f', 'NOW')),
+                    -- updated manually when retrieving workflow
+                    opened_at DATETIME NOT NULL DEFAULT(STRFTIME('%Y-%m-%d %H:%M:%f', 'NOW')),
+                    -- Generated columns, needed for indexing and searching
+                    category TEXT GENERATED ALWAYS as (json_extract(workflow, '$.meta.category')) VIRTUAL NOT NULL,
+                    name TEXT GENERATED ALWAYS as (json_extract(workflow, '$.name')) VIRTUAL NOT NULL,
+                    description TEXT GENERATED ALWAYS as (json_extract(workflow, '$.description')) VIRTUAL NOT NULL
                 );
                 """
             )
 
             self._cursor.execute(
                 """--sql
-                CREATE TRIGGER IF NOT EXISTS tg_workflows_updated_at
+                CREATE TRIGGER IF NOT EXISTS tg_workflow_library_updated_at
                 AFTER UPDATE
-                ON workflows FOR EACH ROW
+                ON workflow_library FOR EACH ROW
                 BEGIN
-                    UPDATE workflows
+                    UPDATE workflow_library
                     SET updated_at = STRFTIME('%Y-%m-%d %H:%M:%f', 'NOW')
                     WHERE workflow_id = old.workflow_id;
                 END;
                 """
             )
 
+            self._cursor.execute(
+                """--sql
+                CREATE INDEX IF NOT EXISTS idx_workflow_library_created_at ON workflow_library(created_at);
+                """
+            )
+            self._cursor.execute(
+                """--sql
+                CREATE INDEX IF NOT EXISTS idx_workflow_library_updated_at ON workflow_library(updated_at);
+                """
+            )
+            self._cursor.execute(
+                """--sql
+                CREATE INDEX IF NOT EXISTS idx_workflow_library_opened_at ON workflow_library(opened_at);
+                """
+            )
+            self._cursor.execute(
+                """--sql
+                CREATE INDEX IF NOT EXISTS idx_workflow_library_category ON workflow_library(category);
+                """
+            )
+            self._cursor.execute(
+                """--sql
+                CREATE INDEX IF NOT EXISTS idx_workflow_library_name ON workflow_library(name);
+                """
+            )
+            self._cursor.execute(
+                """--sql
+                CREATE INDEX IF NOT EXISTS idx_workflow_library_description ON workflow_library(description);
+                """
+            )
+
+            # We do not need the original `workflows` table or `workflow_images` junction table.
+            self._cursor.execute(
+                """--sql
+                DROP TABLE IF EXISTS workflow_images;
+                """
+            )
+            self._cursor.execute(
+                """--sql
+                DROP TABLE IF EXISTS workflows;
+                """
+            )
+
             self._conn.commit()
         except Exception:
             self._conn.rollback()

invokeai/backend/model_management/lora.py

@@ -192,20 +192,33 @@ class ModelPatcher:
                     trigger += f"-!pad-{i}"
                 return f"<{trigger}>"
 
+            def _get_ti_embedding(model_embeddings, ti):
+                # 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:
-                for i in range(ti.embedding.shape[0]):
+                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
             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:
+            for ti_name, _ in ti_list:
                 ti_tokens = []
-                for i in range(ti.embedding.shape[0]):
-                    embedding = ti.embedding[i]
+                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)
@@ -273,6 +286,7 @@ class ModelPatcher:
 
 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(
@@ -296,8 +310,8 @@ class TextualInversionModel:
         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."
+                    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()))
@@ -306,6 +320,11 @@ class TextualInversionModel:
         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()))
@@ -342,6 +361,13 @@ class TextualInversionManager(BaseTextualInversionManager):
             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
 
 
@@ -490,24 +516,31 @@ class ONNXModelPatcher:
                     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:
-                for i in range(ti.embedding.shape[0]):
-                    new_tokens_added += ti_tokenizer.add_tokens(_get_trigger(ti_name, i))
+                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
 
-            # modify text_encoder
-            orig_embeddings = text_encoder.tensors["text_model.embeddings.token_embedding.weight"]
+                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, ti in ti_list:
+            for ti_name, _ in ti_list:
                 ti_tokens = []
-                for i in range(ti.embedding.shape[0]):
-                    embedding = ti.embedding[i].detach().numpy()
+                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)

invokeai/backend/model_management/model_probe.py

@@ -373,12 +373,16 @@ class TextualInversionCheckpointProbe(CheckpointProbeBase):
             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[0]
         if token_dim == 768:
             return BaseModelType.StableDiffusion1
         elif token_dim == 1024:
             return BaseModelType.StableDiffusion2
+        elif token_dim == 1280:
+            return BaseModelType.StableDiffusionXL
         else:
             return None
 

invokeai/backend/model_manager/migrate_to_db.py

@@ -11,7 +11,7 @@ from invokeai.app.services.model_records import (
     DuplicateModelException,
     ModelRecordServiceSQL,
 )
-from invokeai.app.services.shared.sqlite import SqliteDatabase
+from invokeai.app.services.shared.sqlite.sqlite_database import SqliteDatabase
 from invokeai.backend.model_manager.config import (
     AnyModelConfig,
     BaseModelType,

invokeai/backend/tiles/tiles.py

@@ -0,0 +1,201 @@
+import math
+from typing import Union
+
+import numpy as np
+
+from invokeai.backend.tiles.utils import TBLR, Tile, paste
+
+
+def calc_tiles_with_overlap(
+    image_height: int, image_width: int, tile_height: int, tile_width: int, overlap: int = 0
+) -> list[Tile]:
+    """Calculate the tile coordinates for a given image shape under a simple tiling scheme with overlaps.
+
+    Args:
+        image_height (int): The image height in px.
+        image_width (int): The image width in px.
+        tile_height (int): The tile height in px. All tiles will have this height.
+        tile_width (int): The tile width in px. All tiles will have this width.
+        overlap (int, optional): The target overlap between adjacent tiles. If the tiles do not evenly cover the image
+            shape, then the last row/column of tiles will overlap more than this. Defaults to 0.
+
+    Returns:
+        list[Tile]: A list of tiles that cover the image shape. Ordered from left-to-right, top-to-bottom.
+    """
+    assert image_height >= tile_height
+    assert image_width >= tile_width
+    assert overlap < tile_height
+    assert overlap < tile_width
+
+    non_overlap_per_tile_height = tile_height - overlap
+    non_overlap_per_tile_width = tile_width - overlap
+
+    num_tiles_y = math.ceil((image_height - overlap) / non_overlap_per_tile_height)
+    num_tiles_x = math.ceil((image_width - overlap) / non_overlap_per_tile_width)
+
+    # tiles[y * num_tiles_x + x] is the tile for the y'th row, x'th column.
+    tiles: list[Tile] = []
+
+    # Calculate tile coordinates. (Ignore overlap values for now.)
+    for tile_idx_y in range(num_tiles_y):
+        for tile_idx_x in range(num_tiles_x):
+            tile = Tile(
+                coords=TBLR(
+                    top=tile_idx_y * non_overlap_per_tile_height,
+                    bottom=tile_idx_y * non_overlap_per_tile_height + tile_height,
+                    left=tile_idx_x * non_overlap_per_tile_width,
+                    right=tile_idx_x * non_overlap_per_tile_width + tile_width,
+                ),
+                overlap=TBLR(top=0, bottom=0, left=0, right=0),
+            )
+
+            if tile.coords.bottom > image_height:
+                # If this tile would go off the bottom of the image, shift it so that it is aligned with the bottom
+                # of the image.
+                tile.coords.bottom = image_height
+                tile.coords.top = image_height - tile_height
+
+            if tile.coords.right > image_width:
+                # If this tile would go off the right edge of the image, shift it so that it is aligned with the
+                # right edge of the image.
+                tile.coords.right = image_width
+                tile.coords.left = image_width - tile_width
+
+            tiles.append(tile)
+
+    def get_tile_or_none(idx_y: int, idx_x: int) -> Union[Tile, None]:
+        if idx_y < 0 or idx_y > num_tiles_y or idx_x < 0 or idx_x > num_tiles_x:
+            return None
+        return tiles[idx_y * num_tiles_x + idx_x]
+
+    # Iterate over tiles again and calculate overlaps.
+    for tile_idx_y in range(num_tiles_y):
+        for tile_idx_x in range(num_tiles_x):
+            cur_tile = get_tile_or_none(tile_idx_y, tile_idx_x)
+            top_neighbor_tile = get_tile_or_none(tile_idx_y - 1, tile_idx_x)
+            left_neighbor_tile = get_tile_or_none(tile_idx_y, tile_idx_x - 1)
+
+            assert cur_tile is not None
+
+            # Update cur_tile top-overlap and corresponding top-neighbor bottom-overlap.
+            if top_neighbor_tile is not None:
+                cur_tile.overlap.top = max(0, top_neighbor_tile.coords.bottom - cur_tile.coords.top)
+                top_neighbor_tile.overlap.bottom = cur_tile.overlap.top
+
+            # Update cur_tile left-overlap and corresponding left-neighbor right-overlap.
+            if left_neighbor_tile is not None:
+                cur_tile.overlap.left = max(0, left_neighbor_tile.coords.right - cur_tile.coords.left)
+                left_neighbor_tile.overlap.right = cur_tile.overlap.left
+
+    return tiles
+
+
+def merge_tiles_with_linear_blending(
+    dst_image: np.ndarray, tiles: list[Tile], tile_images: list[np.ndarray], blend_amount: int
+):
+    """Merge a set of image tiles into `dst_image` with linear blending between the tiles.
+
+    We expect every tile edge to either:
+    1) have an overlap of 0, because it is aligned with the image edge, or
+    2) have an overlap >= blend_amount.
+    If neither of these conditions are satisfied, we raise an exception.
+
+    The linear blending is centered at the halfway point of the overlap between adjacent tiles.
+
+    Args:
+        dst_image (np.ndarray): The destination image. Shape: (H, W, C).
+        tiles (list[Tile]): The list of tiles describing the locations of the respective `tile_images`.
+        tile_images (list[np.ndarray]): The tile images to merge into `dst_image`.
+        blend_amount (int): The amount of blending (in px) between adjacent overlapping tiles.
+    """
+    # Sort tiles and images first by left x coordinate, then by top y coordinate. During tile processing, we want to
+    # iterate over tiles left-to-right, top-to-bottom.
+    tiles_and_images = list(zip(tiles, tile_images, strict=True))
+    tiles_and_images = sorted(tiles_and_images, key=lambda x: x[0].coords.left)
+    tiles_and_images = sorted(tiles_and_images, key=lambda x: x[0].coords.top)
+
+    # Organize tiles into rows.
+    tile_and_image_rows: list[list[tuple[Tile, np.ndarray]]] = []
+    cur_tile_and_image_row: list[tuple[Tile, np.ndarray]] = []
+    first_tile_in_cur_row, _ = tiles_and_images[0]
+    for tile_and_image in tiles_and_images:
+        tile, _ = tile_and_image
+        if not (
+            tile.coords.top == first_tile_in_cur_row.coords.top
+            and tile.coords.bottom == first_tile_in_cur_row.coords.bottom
+        ):
+            # Store the previous row, and start a new one.
+            tile_and_image_rows.append(cur_tile_and_image_row)
+            cur_tile_and_image_row = []
+            first_tile_in_cur_row, _ = tile_and_image
+
+        cur_tile_and_image_row.append(tile_and_image)
+    tile_and_image_rows.append(cur_tile_and_image_row)
+
+    # Prepare 1D linear gradients for blending.
+    gradient_left_x = np.linspace(start=0.0, stop=1.0, num=blend_amount)
+    gradient_top_y = np.linspace(start=0.0, stop=1.0, num=blend_amount)
+    # Convert shape: (blend_amount, ) -> (blend_amount, 1). The extra dimension enables the gradient to be applied
+    # to a 2D image via broadcasting. Note that no additional dimension is needed on gradient_left_x for
+    # broadcasting to work correctly.
+    gradient_top_y = np.expand_dims(gradient_top_y, axis=1)
+
+    for tile_and_image_row in tile_and_image_rows:
+        first_tile_in_row, _ = tile_and_image_row[0]
+        row_height = first_tile_in_row.coords.bottom - first_tile_in_row.coords.top
+        row_image = np.zeros((row_height, dst_image.shape[1], dst_image.shape[2]), dtype=dst_image.dtype)
+
+        # Blend the tiles in the row horizontally.
+        for tile, tile_image in tile_and_image_row:
+            # We expect the tiles to be ordered left-to-right. For each tile, we construct a mask that applies linear
+            # blending to the left of the current tile. The inverse linear blending is automatically applied to the
+            # right of the tiles that have already been pasted by the paste(...) operation.
+            tile_height, tile_width, _ = tile_image.shape
+            mask = np.ones(shape=(tile_height, tile_width), dtype=np.float64)
+
+            # Left blending:
+            if tile.overlap.left > 0:
+                assert tile.overlap.left >= blend_amount
+                # Center the blending gradient in the middle of the overlap.
+                blend_start_left = tile.overlap.left // 2 - blend_amount // 2
+                # The region left of the blending region is masked completely.
+                mask[:, :blend_start_left] = 0.0
+                # Apply the blend gradient to the mask.
+                mask[:, blend_start_left : blend_start_left + blend_amount] = gradient_left_x
+                # For visual debugging:
+                # tile_image[:, blend_start_left : blend_start_left + blend_amount] = 0
+
+            paste(
+                dst_image=row_image,
+                src_image=tile_image,
+                box=TBLR(
+                    top=0, bottom=tile.coords.bottom - tile.coords.top, left=tile.coords.left, right=tile.coords.right
+                ),
+                mask=mask,
+            )
+
+        # Blend the row into the dst_image vertically.
+        # We construct a mask that applies linear blending to the top of the current row. The inverse linear blending is
+        # automatically applied to the bottom of the tiles that have already been pasted by the paste(...) operation.
+        mask = np.ones(shape=(row_image.shape[0], row_image.shape[1]), dtype=np.float64)
+        # Top blending:
+        # (See comments under 'Left blending' for an explanation of the logic.)
+        # We assume that the entire row has the same vertical overlaps as the first_tile_in_row.
+        if first_tile_in_row.overlap.top > 0:
+            assert first_tile_in_row.overlap.top >= blend_amount
+            blend_start_top = first_tile_in_row.overlap.top // 2 - blend_amount // 2
+            mask[:blend_start_top, :] = 0.0
+            mask[blend_start_top : blend_start_top + blend_amount, :] = gradient_top_y
+            # For visual debugging:
+            # row_image[blend_start_top : blend_start_top + blend_amount, :] = 0
+        paste(
+            dst_image=dst_image,
+            src_image=row_image,
+            box=TBLR(
+                top=first_tile_in_row.coords.top,
+                bottom=first_tile_in_row.coords.bottom,
+                left=0,
+                right=row_image.shape[1],
+            ),
+            mask=mask,
+        )

invokeai/backend/tiles/utils.py

@@ -0,0 +1,47 @@
+from typing import Optional
+
+import numpy as np
+from pydantic import BaseModel, Field
+
+
+class TBLR(BaseModel):
+    top: int
+    bottom: int
+    left: int
+    right: int
+
+    def __eq__(self, other):
+        return (
+            self.top == other.top
+            and self.bottom == other.bottom
+            and self.left == other.left
+            and self.right == other.right
+        )
+
+
+class Tile(BaseModel):
+    coords: TBLR = Field(description="The coordinates of this tile relative to its parent image.")
+    overlap: TBLR = Field(description="The amount of overlap with adjacent tiles on each side of this tile.")
+
+    def __eq__(self, other):
+        return self.coords == other.coords and self.overlap == other.overlap
+
+
+def paste(dst_image: np.ndarray, src_image: np.ndarray, box: TBLR, mask: Optional[np.ndarray] = None):
+    """Paste a source image into a destination image.
+
+    Args:
+        dst_image (torch.Tensor): The destination image to paste into. Shape: (H, W, C).
+        src_image (torch.Tensor): The source image to paste. Shape: (H, W, C). H and W must be compatible with 'box'.
+        box (TBLR): Box defining the region in the 'dst_image' where 'src_image' will be pasted.
+        mask (Optional[torch.Tensor]): A mask that defines the blending between 'src_image' and 'dst_image'.
+            Range: [0.0, 1.0], Shape: (H, W). The output is calculate per-pixel according to
+            `src * mask + dst * (1 - mask)`.
+    """
+
+    if mask is None:
+        dst_image[box.top : box.bottom, box.left : box.right] = src_image
+    else:
+        mask = np.expand_dims(mask, -1)
+        dst_image_box = dst_image[box.top : box.bottom, box.left : box.right]
+        dst_image[box.top : box.bottom, box.left : box.right] = src_image * mask + dst_image_box * (1.0 - mask)

invokeai/frontend/web/.prettierignore

@@ -1,5 +1,6 @@
 dist/
 public/locales/*.json
+!public/locales/en.json
 .husky/
 node_modules/
 patches/

invokeai/frontend/web/package.json

@@ -75,6 +75,7 @@
     "framer-motion": "^10.16.4",
     "i18next": "^23.6.0",
     "i18next-http-backend": "^2.3.1",
+    "idb-keyval": "^6.2.1",
     "konva": "^9.2.3",
     "lodash-es": "^4.17.21",
     "nanostores": "^0.9.4",

invokeai/frontend/web/public/locales/de.json

@@ -803,8 +803,7 @@
         "canny": "Canny",
         "hedDescription": "Ganzheitlich verschachtelte Kantenerkennung",
         "scribble": "Scribble",
-        "maxFaces": "Maximal Anzahl Gesichter",
-        "unstarImage": "Markierung aufheben"
+        "maxFaces": "Maximal Anzahl Gesichter"
     },
     "queue": {
         "status": "Status",

invokeai/frontend/web/public/locales/en.json

@@ -67,7 +67,9 @@
         "controlNet": "ControlNet",
         "controlAdapter": "Control Adapter",
         "data": "Data",
+        "delete": "Delete",
         "details": "Details",
+        "direction": "Direction",
         "ipAdapter": "IP Adapter",
         "t2iAdapter": "T2I Adapter",
         "darkMode": "Dark Mode",
@@ -115,6 +117,7 @@
         "nodesDesc": "A node based system for the generation of images is under development currently. Stay tuned for updates about this amazing feature.",
         "notInstalled": "Not $t(common.installed)",
         "openInNewTab": "Open in New Tab",
+        "orderBy": "Order By",
         "outpaint": "outpaint",
         "outputs": "Outputs",
         "postProcessDesc1": "Invoke AI offers a wide variety of post processing features. Image Upscaling and Face Restoration are already available in the WebUI. You can access them from the Advanced Options menu of the Text To Image and Image To Image tabs. You can also process images directly, using the image action buttons above the current image display or in the viewer.",
@@ -125,6 +128,8 @@
         "random": "Random",
         "reportBugLabel": "Report Bug",
         "safetensors": "Safetensors",
+        "save": "Save",
+        "saveAs": "Save As",
         "settingsLabel": "Settings",
         "simple": "Simple",
         "somethingWentWrong": "Something went wrong",
@@ -161,7 +166,11 @@
         "txt2img": "Text To Image",
         "unifiedCanvas": "Unified Canvas",
         "unknown": "Unknown",
-        "upload": "Upload"
+        "upload": "Upload",
+        "updated": "Updated",
+        "created": "Created",
+        "prevPage": "Previous Page",
+        "nextPage": "Next Page"
     },
     "controlnet": {
         "controlAdapter_one": "Control Adapter",
@@ -243,7 +252,6 @@
         "setControlImageDimensions": "Set Control Image Dimensions To W/H",
         "showAdvanced": "Show Advanced",
         "toggleControlNet": "Toggle this ControlNet",
-        "unstarImage": "Unstar Image",
         "w": "W",
         "weight": "Weight",
         "enableIPAdapter": "Enable IP Adapter",
@@ -378,6 +386,8 @@
         "showGenerations": "Show Generations",
         "showUploads": "Show Uploads",
         "singleColumnLayout": "Single Column Layout",
+        "starImage": "Star Image",
+        "unstarImage": "Unstar Image",
         "unableToLoad": "Unable to load Gallery",
         "uploads": "Uploads",
         "deleteSelection": "Delete Selection",
@@ -936,9 +946,9 @@
         "problemSettingTitle": "Problem Setting Title",
         "reloadNodeTemplates": "Reload Node Templates",
         "removeLinearView": "Remove from Linear View",
-        "resetWorkflow": "Reset Workflow",
-        "resetWorkflowDesc": "Are you sure you want to reset this workflow?",
-        "resetWorkflowDesc2": "Resetting the workflow will clear all nodes, edges and workflow details.",
+        "resetWorkflow": "Reset Workflow Editor",
+        "resetWorkflowDesc": "Are you sure you want to reset the Workflow Editor?",
+        "resetWorkflowDesc2": "Resetting the Workflow Editor will clear all nodes, edges and workflow details. Saved workflows will not be affected.",
         "scheduler": "Scheduler",
         "schedulerDescription": "TODO",
         "sDXLMainModelField": "SDXL Model",
@@ -978,6 +988,7 @@
         "unsupportedAnyOfLength": "too many union members ({{count}})",
         "unsupportedMismatchedUnion": "mismatched CollectionOrScalar type with base types {{firstType}} and {{secondType}}",
         "unableToParseFieldType": "unable to parse field type",
+        "unableToExtractEnumOptions": "unable to extract enum options",
         "uNetField": "UNet",
         "uNetFieldDescription": "UNet submodel.",
         "unhandledInputProperty": "Unhandled input property",
@@ -1264,7 +1275,6 @@
         "modelAddedSimple": "Model Added",
         "modelAddFailed": "Model Add Failed",
         "nodesBrokenConnections": "Cannot load. Some connections are broken.",
-        "nodesCleared": "Nodes Cleared",
         "nodesCorruptedGraph": "Cannot load. Graph seems to be corrupted.",
         "nodesLoaded": "Nodes Loaded",
         "nodesLoadedFailed": "Failed To Load Nodes",
@@ -1313,7 +1323,10 @@
         "uploadFailedInvalidUploadDesc": "Must be single PNG or JPEG image",
         "uploadFailedUnableToLoadDesc": "Unable to load file",
         "upscalingFailed": "Upscaling Failed",
-        "workflowLoaded": "Workflow Loaded"
+        "workflowLoaded": "Workflow Loaded",
+        "problemRetrievingWorkflow": "Problem Retrieving Workflow",
+        "workflowDeleted": "Workflow Deleted",
+        "problemDeletingWorkflow": "Problem Deleting Workflow"
     },
     "tooltip": {
         "feature": {
@@ -1608,5 +1621,32 @@
         "showIntermediates": "Show Intermediates",
         "snapToGrid": "Snap to Grid",
         "undo": "Undo"
+    },
+    "workflows": {
+        "workflows": "Workflows",
+        "workflowLibrary": "Workflow Library",
+        "userWorkflows": "My Workflows",
+        "defaultWorkflows": "Defaults",
+        "projectWorkflows": "Project",
+        "openWorkflow": "Open Workflow",
+        "uploadWorkflow": "Upload Workflow",
+        "deleteWorkflow": "Delete Workflow",
+        "unnamedWorkflow": "Unnamed Workflow",
+        "downloadWorkflow": "Download Workflow",
+        "saveWorkflow": "Save Workflow",
+        "saveWorkflowAs": "Save Workflow As",
+        "problemSavingWorkflow": "Problem Saving Workflow",
+        "workflowSaved": "Workflow Saved",
+        "noWorkflows": "No Workflows",
+        "problemLoading": "Problem Loading Workflows",
+        "loading": "Loading Workflows",
+        "noDescription": "No description",
+        "searchWorkflows": "Search Workflows",
+        "clearWorkflowSearchFilter": "Clear Workflow Search Filter",
+        "workflowName": "Workflow Name",
+        "workflowEditorReset": "Workflow Editor Reset"
+    },
+    "app": {
+        "storeNotInitialized": "Store is not initialized"
     }
 }

invokeai/frontend/web/public/locales/it.json

@@ -91,7 +91,19 @@
         "controlNet": "ControlNet",
         "auto": "Automatico",
         "simple": "Semplice",
-        "details": "Dettagli"
+        "details": "Dettagli",
+        "format": "formato",
+        "unknown": "Sconosciuto",
+        "folder": "Cartella",
+        "error": "Errore",
+        "installed": "Installato",
+        "template": "Schema",
+        "outputs": "Uscite",
+        "data": "Dati",
+        "somethingWentWrong": "Qualcosa è andato storto",
+        "copyError": "$t(gallery.copy) Errore",
+        "input": "Ingresso",
+        "notInstalled": "Non $t(common.installed)"
     },
     "gallery": {
         "generations": "Generazioni",
@@ -122,7 +134,14 @@
         "preparingDownload": "Preparazione del download",
         "preparingDownloadFailed": "Problema durante la preparazione del download",
         "downloadSelection": "Scarica gli elementi selezionati",
-        "noImageSelected": "Nessuna immagine selezionata"
+        "noImageSelected": "Nessuna immagine selezionata",
+        "deleteSelection": "Elimina la selezione",
+        "image": "immagine",
+        "drop": "Rilascia",
+        "unstarImage": "Rimuovi preferenza immagine",
+        "dropOrUpload": "$t(gallery.drop) o carica",
+        "starImage": "Immagine preferita",
+        "dropToUpload": "$t(gallery.drop) per aggiornare"
     },
     "hotkeys": {
         "keyboardShortcuts": "Tasti rapidi",
@@ -477,7 +496,8 @@
         "modelType": "Tipo di modello",
         "customConfigFileLocation": "Posizione del file di configurazione personalizzato",
         "vaePrecision": "Precisione VAE",
-        "noModelSelected": "Nessun modello selezionato"
+        "noModelSelected": "Nessun modello selezionato",
+        "conversionNotSupported": "Conversione non supportata"
     },
     "parameters": {
         "images": "Immagini",
@@ -838,7 +858,8 @@
         "menu": "Menu",
         "showGalleryPanel": "Mostra il pannello Galleria",
         "loadMore": "Carica altro",
-        "mode": "Modalità"
+        "mode": "Modalità",
+        "resetUI": "$t(accessibility.reset) l'Interfaccia Utente"
     },
     "ui": {
         "hideProgressImages": "Nascondi avanzamento immagini",
@@ -1040,7 +1061,15 @@
         "updateAllNodes": "Aggiorna tutti i nodi",
         "unableToUpdateNodes_one": "Impossibile aggiornare {{count}} nodo",
         "unableToUpdateNodes_many": "Impossibile aggiornare {{count}} nodi",
-        "unableToUpdateNodes_other": "Impossibile aggiornare {{count}} nodi"
+        "unableToUpdateNodes_other": "Impossibile aggiornare {{count}} nodi",
+        "addLinearView": "Aggiungi alla vista Lineare",
+        "outputFieldInInput": "Campo di uscita in ingresso",
+        "unableToMigrateWorkflow": "Impossibile migrare il flusso di lavoro",
+        "unableToUpdateNode": "Impossibile aggiornare nodo",
+        "unknownErrorValidatingWorkflow": "Errore sconosciuto durante la convalida del flusso di lavoro",
+        "collectionFieldType": "{{name}} Raccolta",
+        "collectionOrScalarFieldType": "{{name}} Raccolta|Scalare",
+        "nodeVersion": "Versione Nodo"
     },
     "boards": {
         "autoAddBoard": "Aggiungi automaticamente bacheca",
@@ -1062,7 +1091,10 @@
         "deleteBoardOnly": "Elimina solo la Bacheca",
         "deleteBoard": "Elimina Bacheca",
         "deleteBoardAndImages": "Elimina Bacheca e Immagini",
-        "deletedBoardsCannotbeRestored": "Le bacheche eliminate non possono essere ripristinate"
+        "deletedBoardsCannotbeRestored": "Le bacheche eliminate non possono essere ripristinate",
+        "movingImagesToBoard_one": "Spostare {{count}} immagine nella bacheca:",
+        "movingImagesToBoard_many": "Spostare {{count}} immagini nella bacheca:",
+        "movingImagesToBoard_other": "Spostare {{count}} immagini nella bacheca:"
     },
     "controlnet": {
         "contentShuffleDescription": "Rimescola il contenuto di un'immagine",
@@ -1136,7 +1168,8 @@
         "megaControl": "Mega ControlNet",
         "minConfidence": "Confidenza minima",
         "scribble": "Scribble",
-        "amult": "Angolo di illuminazione"
+        "amult": "Angolo di illuminazione",
+        "coarse": "Approssimativo"
     },
     "queue": {
         "queueFront": "Aggiungi all'inizio della coda",
@@ -1204,7 +1237,8 @@
     "embedding": {
         "noMatchingEmbedding": "Nessun Incorporamento corrispondente",
         "addEmbedding": "Aggiungi Incorporamento",
-        "incompatibleModel": "Modello base incompatibile:"
+        "incompatibleModel": "Modello base incompatibile:",
+        "noEmbeddingsLoaded": "Nessun incorporamento caricato"
     },
     "models": {
         "noMatchingModels": "Nessun modello corrispondente",
@@ -1217,7 +1251,8 @@
         "noRefinerModelsInstalled": "Nessun modello SDXL Refiner installato",
         "noLoRAsInstalled": "Nessun LoRA installato",
         "esrganModel": "Modello ESRGAN",
-        "addLora": "Aggiungi LoRA"
+        "addLora": "Aggiungi LoRA",
+        "noLoRAsLoaded": "Nessuna LoRA caricata"
     },
     "invocationCache": {
         "disable": "Disabilita",
@@ -1233,7 +1268,8 @@
         "enable": "Abilita",
         "clear": "Svuota",
         "maxCacheSize": "Dimensione max cache",
-        "cacheSize": "Dimensione cache"
+        "cacheSize": "Dimensione cache",
+        "useCache": "Usa Cache"
     },
     "dynamicPrompts": {
         "seedBehaviour": {

invokeai/frontend/web/public/locales/zh_CN.json

@@ -1137,8 +1137,7 @@
         "openPose": "Openpose",
         "controlAdapter_other": "Control Adapters",
         "lineartAnime": "Lineart Anime",
-        "canny": "Canny",
-        "unstarImage": "取消收藏图像"
+        "canny": "Canny"
     },
     "queue": {
         "status": "状态",

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

@@ -21,6 +21,7 @@ import GlobalHotkeys from './GlobalHotkeys';
 import PreselectedImage from './PreselectedImage';
 import Toaster from './Toaster';
 import { useSocketIO } from 'app/hooks/useSocketIO';
+import { useClearStorage } from 'common/hooks/useClearStorage';
 
 const DEFAULT_CONFIG = {};
 
@@ -36,15 +37,16 @@ const App = ({ config = DEFAULT_CONFIG, selectedImage }: Props) => {
   const language = useAppSelector(languageSelector);
   const logger = useLogger('system');
   const dispatch = useAppDispatch();
+  const clearStorage = useClearStorage();
 
   // singleton!
   useSocketIO();
 
   const handleReset = useCallback(() => {
-    localStorage.clear();
+    clearStorage();
     location.reload();
     return false;
-  }, []);
+  }, [clearStorage]);
 
   useEffect(() => {
     i18n.changeLanguage(language);

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

@@ -7,21 +7,23 @@ import { $headerComponent } from 'app/store/nanostores/headerComponent';
 import { $isDebugging } from 'app/store/nanostores/isDebugging';
 import { $projectId } from 'app/store/nanostores/projectId';
 import { $queueId, DEFAULT_QUEUE_ID } from 'app/store/nanostores/queueId';
-import { store } from 'app/store/store';
+import { $store } from 'app/store/nanostores/store';
+import { createStore } from 'app/store/store';
 import { PartialAppConfig } from 'app/types/invokeai';
+import Loading from 'common/components/Loading/Loading';
+import AppDndContext from 'features/dnd/components/AppDndContext';
+import 'i18n';
 import React, {
   PropsWithChildren,
   ReactNode,
   lazy,
   memo,
   useEffect,
+  useMemo,
 } from 'react';
 import { Provider } from 'react-redux';
 import { addMiddleware, resetMiddlewares } from 'redux-dynamic-middlewares';
 import { ManagerOptions, SocketOptions } from 'socket.io-client';
-import Loading from 'common/components/Loading/Loading';
-import AppDndContext from 'features/dnd/components/AppDndContext';
-import 'i18n';
 
 const App = lazy(() => import('./App'));
 const ThemeLocaleProvider = lazy(() => import('./ThemeLocaleProvider'));
@@ -137,6 +139,14 @@ const InvokeAIUI = ({
     };
   }, [isDebugging]);
 
+  const store = useMemo(() => {
+    return createStore(projectId);
+  }, [projectId]);
+
+  useEffect(() => {
+    $store.set(store);
+  }, [store]);
+
   return (
     <React.StrictMode>
       <Provider store={store}>

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

@@ -9,9 +9,9 @@ import { TOAST_OPTIONS, theme as invokeAITheme } from 'theme/theme';
 
 import '@fontsource-variable/inter';
 import { MantineProvider } from '@mantine/core';
+import { useMantineTheme } from 'mantine-theme/theme';
 import 'overlayscrollbars/overlayscrollbars.css';
 import 'theme/css/overlayscrollbars.css';
-import { useMantineTheme } from 'mantine-theme/theme';
 
 type ThemeLocaleProviderProps = {
   children: ReactNode;

invokeai/frontend/web/src/app/hooks/useSocketIO.ts

@@ -3,8 +3,8 @@ import { $authToken } from 'app/store/nanostores/authToken';
 import { $baseUrl } from 'app/store/nanostores/baseUrl';
 import { $isDebugging } from 'app/store/nanostores/isDebugging';
 import { useAppDispatch } from 'app/store/storeHooks';
-import { MapStore, WritableAtom, atom, map } from 'nanostores';
-import { useEffect } from 'react';
+import { MapStore, atom, map } from 'nanostores';
+import { useEffect, useMemo } from 'react';
 import {
   ClientToServerEvents,
   ServerToClientEvents,
@@ -16,57 +16,10 @@ import { ManagerOptions, Socket, SocketOptions, io } from 'socket.io-client';
 declare global {
   interface Window {
     $socketOptions?: MapStore<Partial<ManagerOptions & SocketOptions>>;
-    $socketUrl?: WritableAtom<string>;
   }
 }
 
-const makeSocketOptions = (): Partial<ManagerOptions & SocketOptions> => {
-  const socketOptions: Parameters<typeof io>[0] = {
-    timeout: 60000,
-    path: '/ws/socket.io',
-    autoConnect: false, // achtung! removing this breaks the dynamic middleware
-    forceNew: true,
-  };
-
-  // if building in package mode, replace socket url with open api base url minus the http protocol
-  if (['nodes', 'package'].includes(import.meta.env.MODE)) {
-    const authToken = $authToken.get();
-    if (authToken) {
-      // TODO: handle providing jwt to socket.io
-      socketOptions.auth = { token: authToken };
-    }
-
-    socketOptions.transports = ['websocket', 'polling'];
-  }
-
-  return socketOptions;
-};
-
-const makeSocketUrl = (): string => {
-  const wsProtocol = window.location.protocol === 'https:' ? 'wss' : 'ws';
-  let socketUrl = `${wsProtocol}://${window.location.host}`;
-  if (['nodes', 'package'].includes(import.meta.env.MODE)) {
-    const baseUrl = $baseUrl.get();
-    if (baseUrl) {
-      //eslint-disable-next-line
-      socketUrl = baseUrl.replace(/^https?\:\/\//i, '');
-    }
-  }
-  return socketUrl;
-};
-
-const makeSocket = (): Socket<ServerToClientEvents, ClientToServerEvents> => {
-  const socketOptions = makeSocketOptions();
-  const socketUrl = $socketUrl.get();
-  const socket: Socket<ServerToClientEvents, ClientToServerEvents> = io(
-    socketUrl,
-    { ...socketOptions, ...$socketOptions.get() }
-  );
-  return socket;
-};
-
 export const $socketOptions = map<Partial<ManagerOptions & SocketOptions>>({});
-export const $socketUrl = atom<string>(makeSocketUrl());
 export const $isSocketInitialized = atom<boolean>(false);
 
 /**
@@ -74,23 +27,50 @@ export const $isSocketInitialized = atom<boolean>(false);
  */
 export const useSocketIO = () => {
   const dispatch = useAppDispatch();
-  const socketOptions = useStore($socketOptions);
-  const socketUrl = useStore($socketUrl);
   const baseUrl = useStore($baseUrl);
   const authToken = useStore($authToken);
+  const addlSocketOptions = useStore($socketOptions);
+
+  const socketUrl = useMemo(() => {
+    const wsProtocol = window.location.protocol === 'https:' ? 'wss' : 'ws';
+    if (baseUrl) {
+      return baseUrl.replace(/^https?:\/\//i, '');
+    }
+
+    return `${wsProtocol}://${window.location.host}`;
+  }, [baseUrl]);
+
+  const socketOptions = useMemo(() => {
+    const options: Parameters<typeof io>[0] = {
+      timeout: 60000,
+      path: '/ws/socket.io',
+      autoConnect: false, // achtung! removing this breaks the dynamic middleware
+      forceNew: true,
+    };
+
+    if (authToken) {
+      options.auth = { token: authToken };
+      options.transports = ['websocket', 'polling'];
+    }
+
+    return { ...options, ...addlSocketOptions };
+  }, [authToken, addlSocketOptions]);
 
   useEffect(() => {
     if ($isSocketInitialized.get()) {
       // Singleton!
       return;
     }
-    const socket = makeSocket();
+
+    const socket: Socket<ServerToClientEvents, ClientToServerEvents> = io(
+      socketUrl,
+      socketOptions
+    );
     setEventListeners({ dispatch, socket });
     socket.connect();
 
     if ($isDebugging.get()) {
       window.$socketOptions = $socketOptions;
-      window.$socketUrl = $socketUrl;
       console.log('Socket initialized', socket);
     }
 
@@ -99,11 +79,10 @@ export const useSocketIO = () => {
     return () => {
       if ($isDebugging.get()) {
         window.$socketOptions = undefined;
-        window.$socketUrl = undefined;
         console.log('Socket teardown', socket);
       }
       socket.disconnect();
       $isSocketInitialized.set(false);
     };
-  }, [dispatch, socketOptions, socketUrl, baseUrl, authToken]);
+  }, [dispatch, socketOptions, socketUrl]);
 };

invokeai/frontend/web/src/app/store/constants.ts

@@ -1,8 +1 @@
-export const LOCALSTORAGE_KEYS = [
-  'chakra-ui-color-mode',
-  'i18nextLng',
-  'ROARR_FILTER',
-  'ROARR_LOG',
-];
-
-export const LOCALSTORAGE_PREFIX = '@@invokeai-';
+export const STORAGE_PREFIX = '@@invokeai-';

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/enqueueRequestedNodes.ts

@@ -3,6 +3,7 @@ import { buildNodesGraph } from 'features/nodes/util/graph/buildNodesGraph';
 import { queueApi } from 'services/api/endpoints/queue';
 import { BatchConfig } from 'services/api/types';
 import { startAppListening } from '..';
+import { buildWorkflow } from 'features/nodes/util/workflow/buildWorkflow';
 
 export const addEnqueueRequestedNodes = () => {
   startAppListening({
@@ -10,10 +11,18 @@ export const addEnqueueRequestedNodes = () => {
       enqueueRequested.match(action) && action.payload.tabName === 'nodes',
     effect: async (action, { getState, dispatch }) => {
       const state = getState();
+      const { nodes, edges } = state.nodes;
+      const workflow = state.workflow;
       const graph = buildNodesGraph(state.nodes);
+      const builtWorkflow = buildWorkflow({
+        nodes,
+        edges,
+        workflow,
+      });
       const batchConfig: BatchConfig = {
         batch: {
           graph,
+          workflow: builtWorkflow,
           runs: state.generation.iterations,
         },
         prepend: action.payload.prepend,

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageDropped.ts

@@ -11,13 +11,11 @@ import {
   TypesafeDroppableData,
 } from 'features/dnd/types';
 import { imageSelected } from 'features/gallery/store/gallerySlice';
-import {
-  fieldImageValueChanged,
-  workflowExposedFieldAdded,
-} from 'features/nodes/store/nodesSlice';
+import { fieldImageValueChanged } from 'features/nodes/store/nodesSlice';
 import { initialImageChanged } from 'features/parameters/store/generationSlice';
 import { imagesApi } from 'services/api/endpoints/images';
 import { startAppListening } from '../';
+import { workflowExposedFieldAdded } from 'features/nodes/store/workflowSlice';
 
 export const dndDropped = createAction<{
   overData: TypesafeDroppableData;

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/workflowLoadRequested.ts

@@ -1,7 +1,7 @@
 import { logger } from 'app/logging/logger';
 import { parseify } from 'common/util/serialize';
 import { workflowLoadRequested } from 'features/nodes/store/actions';
-import { workflowLoaded } from 'features/nodes/store/nodesSlice';
+import { workflowLoaded } from 'features/nodes/store/actions';
 import { $flow } from 'features/nodes/store/reactFlowInstance';
 import {
   WorkflowMigrationError,
@@ -21,7 +21,7 @@ export const addWorkflowLoadRequestedListener = () => {
     actionCreator: workflowLoadRequested,
     effect: (action, { dispatch, getState }) => {
       const log = logger('nodes');
-      const workflow = action.payload;
+      const { workflow, asCopy } = action.payload;
       const nodeTemplates = getState().nodes.nodeTemplates;
 
       try {
@@ -29,6 +29,12 @@ export const addWorkflowLoadRequestedListener = () => {
           workflow,
           nodeTemplates
         );
+
+        if (asCopy) {
+          // If we're loading a copy, we need to remove the ID so that the backend will create a new workflow
+          delete validatedWorkflow.id;
+        }
+
         dispatch(workflowLoaded(validatedWorkflow));
         if (!warnings.length) {
           dispatch(
@@ -99,7 +105,6 @@ export const addWorkflowLoadRequestedListener = () => {
           );
         } else {
           // Some other error occurred
-          console.log(e);
           log.error(
             { error: parseify(e) },
             t('nodes.unknownErrorValidatingWorkflow')

invokeai/frontend/web/src/app/store/nanostores/store.ts

@@ -1,5 +1,6 @@
-import { Store } from '@reduxjs/toolkit';
+import { createStore } from 'app/store/store';
 import { atom } from 'nanostores';
 
-// eslint-disable-next-line @typescript-eslint/no-explicit-any
-export const $store = atom<Store<any> | undefined>();
+export const $store = atom<
+  Readonly<ReturnType<typeof createStore>> | undefined
+>();

invokeai/frontend/web/src/app/store/store.ts

@@ -14,6 +14,7 @@ import galleryReducer from 'features/gallery/store/gallerySlice';
 import loraReducer from 'features/lora/store/loraSlice';
 import modelmanagerReducer from 'features/modelManager/store/modelManagerSlice';
 import nodesReducer from 'features/nodes/store/nodesSlice';
+import workflowReducer from 'features/nodes/store/workflowSlice';
 import generationReducer from 'features/parameters/store/generationSlice';
 import postprocessingReducer from 'features/parameters/store/postprocessingSlice';
 import queueReducer from 'features/queue/store/queueSlice';
@@ -22,17 +23,17 @@ import configReducer from 'features/system/store/configSlice';
 import systemReducer from 'features/system/store/systemSlice';
 import hotkeysReducer from 'features/ui/store/hotkeysSlice';
 import uiReducer from 'features/ui/store/uiSlice';
+import { createStore as createIDBKeyValStore, get, set } from 'idb-keyval';
 import dynamicMiddlewares from 'redux-dynamic-middlewares';
-import { rememberEnhancer, rememberReducer } from 'redux-remember';
+import { Driver, rememberEnhancer, rememberReducer } from 'redux-remember';
 import { api } from 'services/api';
-import { LOCALSTORAGE_PREFIX } from './constants';
+import { STORAGE_PREFIX } from './constants';
 import { serialize } from './enhancers/reduxRemember/serialize';
 import { unserialize } from './enhancers/reduxRemember/unserialize';
 import { actionSanitizer } from './middleware/devtools/actionSanitizer';
 import { actionsDenylist } from './middleware/devtools/actionsDenylist';
 import { stateSanitizer } from './middleware/devtools/stateSanitizer';
 import { listenerMiddleware } from './middleware/listenerMiddleware';
-import { $store } from './nanostores/store';
 
 const allReducers = {
   canvas: canvasReducer,
@@ -52,6 +53,7 @@ const allReducers = {
   modelmanager: modelmanagerReducer,
   sdxl: sdxlReducer,
   queue: queueReducer,
+  workflow: workflowReducer,
   [api.reducerPath]: api.reducer,
 };
 
@@ -65,6 +67,7 @@ const rememberedKeys: (keyof typeof allReducers)[] = [
   'generation',
   'sdxl',
   'nodes',
+  'workflow',
   'postprocessing',
   'system',
   'ui',
@@ -74,57 +77,70 @@ const rememberedKeys: (keyof typeof allReducers)[] = [
   'modelmanager',
 ];
 
-export const store = configureStore({
-  reducer: rememberedRootReducer,
-  enhancers: (existingEnhancers) => {
-    return existingEnhancers
-      .concat(
-        rememberEnhancer(window.localStorage, rememberedKeys, {
-          persistDebounce: 300,
-          serialize,
-          unserialize,
-          prefix: LOCALSTORAGE_PREFIX,
-        })
-      )
-      .concat(autoBatchEnhancer());
-  },
-  middleware: (getDefaultMiddleware) =>
-    getDefaultMiddleware({
-      serializableCheck: false,
-      immutableCheck: false,
-    })
-      .concat(api.middleware)
-      .concat(dynamicMiddlewares)
-      .prepend(listenerMiddleware.middleware),
-  devTools: {
-    actionSanitizer,
-    stateSanitizer,
-    trace: true,
-    predicate: (state, action) => {
-      // TODO: hook up to the log level param in system slice
-      // manually type state, cannot type the arg
-      // const typedState = state as ReturnType<typeof rootReducer>;
+// Create a custom idb-keyval store (just needed to customize the name)
+export const idbKeyValStore = createIDBKeyValStore('invoke', 'invoke-store');
 
-      // TODO: doing this breaks the rtk query devtools, commenting out for now
-      // if (action.type.startsWith('api/')) {
-      //   // don't log api actions, with manual cache updates they are extremely noisy
-      //   return false;
-      // }
+// Create redux-remember driver, wrapping idb-keyval
+const idbKeyValDriver: Driver = {
+  getItem: (key) => get(key, idbKeyValStore),
+  setItem: (key, value) => set(key, value, idbKeyValStore),
+};
 
-      if (actionsDenylist.includes(action.type)) {
-        // don't log other noisy actions
-        return false;
-      }
-
-      return true;
+export const createStore = (uniqueStoreKey?: string) =>
+  configureStore({
+    reducer: rememberedRootReducer,
+    enhancers: (existingEnhancers) => {
+      return existingEnhancers
+        .concat(
+          rememberEnhancer(idbKeyValDriver, rememberedKeys, {
+            persistDebounce: 300,
+            serialize,
+            unserialize,
+            prefix: uniqueStoreKey
+              ? `${STORAGE_PREFIX}${uniqueStoreKey}-`
+              : STORAGE_PREFIX,
+          })
+        )
+        .concat(autoBatchEnhancer());
     },
-  },
-});
+    middleware: (getDefaultMiddleware) =>
+      getDefaultMiddleware({
+        serializableCheck: false,
+        immutableCheck: false,
+      })
+        .concat(api.middleware)
+        .concat(dynamicMiddlewares)
+        .prepend(listenerMiddleware.middleware),
+    devTools: {
+      actionSanitizer,
+      stateSanitizer,
+      trace: true,
+      predicate: (state, action) => {
+        // TODO: hook up to the log level param in system slice
+        // manually type state, cannot type the arg
+        // const typedState = state as ReturnType<typeof rootReducer>;
 
-export type AppGetState = typeof store.getState;
-export type RootState = ReturnType<typeof store.getState>;
+        // TODO: doing this breaks the rtk query devtools, commenting out for now
+        // if (action.type.startsWith('api/')) {
+        //   // don't log api actions, with manual cache updates they are extremely noisy
+        //   return false;
+        // }
+
+        if (actionsDenylist.includes(action.type)) {
+          // don't log other noisy actions
+          return false;
+        }
+
+        return 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, AnyAction>;
-export type AppDispatch = typeof store.dispatch;
+export type AppDispatch = ReturnType<typeof createStore>['dispatch'];
 export const stateSelector = (state: RootState) => state;
-$store.set(store);

invokeai/frontend/web/src/common/components/IAIMantineSelect.tsx

@@ -1,4 +1,10 @@
-import { FormControl, FormLabel, Tooltip, forwardRef } from '@chakra-ui/react';
+import {
+  FormControl,
+  FormControlProps,
+  FormLabel,
+  Tooltip,
+  forwardRef,
+} from '@chakra-ui/react';
 import { Select, SelectProps } from '@mantine/core';
 import { useMantineSelectStyles } from 'mantine-theme/hooks/useMantineSelectStyles';
 import { RefObject, memo } from 'react';
@@ -13,10 +19,19 @@ export type IAISelectProps = Omit<SelectProps, 'label'> & {
   tooltip?: string | null;
   inputRef?: RefObject<HTMLInputElement>;
   label?: string;
+  formControlProps?: FormControlProps;
 };
 
 const IAIMantineSelect = forwardRef((props: IAISelectProps, ref) => {
-  const { tooltip, inputRef, label, disabled, required, ...rest } = props;
+  const {
+    tooltip,
+    formControlProps,
+    inputRef,
+    label,
+    disabled,
+    required,
+    ...rest
+  } = props;
 
   const styles = useMantineSelectStyles();
 
@@ -28,6 +43,7 @@ const IAIMantineSelect = forwardRef((props: IAISelectProps, ref) => {
         isDisabled={disabled}
         position="static"
         data-testid={`select-${label || props.placeholder}`}
+        {...formControlProps}
       >
         <FormLabel>{label}</FormLabel>
         <Select disabled={disabled} ref={inputRef} styles={styles} {...rest} />

invokeai/frontend/web/src/common/components/Nbsp.tsx

@@ -0,0 +1 @@
+export const Nbsp = () => <>{'\u00A0'}</>;

invokeai/frontend/web/src/common/hooks/useClearStorage.ts

@@ -0,0 +1,12 @@
+import { idbKeyValStore } from 'app/store/store';
+import { clear } from 'idb-keyval';
+import { useCallback } from 'react';
+
+export const useClearStorage = () => {
+  const clearStorage = useCallback(() => {
+    clear(idbKeyValStore);
+    localStorage.clear();
+  }, []);
+
+  return clearStorage;
+};

invokeai/frontend/web/src/features/controlAdapters/components/ControlAdapterImagePreview.tsx

@@ -5,14 +5,19 @@ import { stateSelector } from 'app/store/store';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { defaultSelectorOptions } from 'app/store/util/defaultMemoizeOptions';
 import IAIDndImage from 'common/components/IAIDndImage';
+import IAIDndImageIcon from 'common/components/IAIDndImageIcon';
 import { setBoundingBoxDimensions } from 'features/canvas/store/canvasSlice';
+import { useControlAdapterControlImage } from 'features/controlAdapters/hooks/useControlAdapterControlImage';
+import { useControlAdapterProcessedControlImage } from 'features/controlAdapters/hooks/useControlAdapterProcessedControlImage';
+import { useControlAdapterProcessorType } from 'features/controlAdapters/hooks/useControlAdapterProcessorType';
+import { controlAdapterImageChanged } from 'features/controlAdapters/store/controlAdaptersSlice';
 import {
   TypesafeDraggableData,
   TypesafeDroppableData,
 } from 'features/dnd/types';
 import { setHeight, setWidth } from 'features/parameters/store/generationSlice';
 import { activeTabNameSelector } from 'features/ui/store/uiSelectors';
-import { memo, useCallback, useMemo, useState } from 'react';
+import { memo, useCallback, useEffect, useMemo, useState } from 'react';
 import { useTranslation } from 'react-i18next';
 import { FaRulerVertical, FaSave, FaUndo } from 'react-icons/fa';
 import {
@@ -22,11 +27,6 @@ import {
   useRemoveImageFromBoardMutation,
 } from 'services/api/endpoints/images';
 import { PostUploadAction } from 'services/api/types';
-import IAIDndImageIcon from 'common/components/IAIDndImageIcon';
-import { controlAdapterImageChanged } from 'features/controlAdapters/store/controlAdaptersSlice';
-import { useControlAdapterControlImage } from 'features/controlAdapters/hooks/useControlAdapterControlImage';
-import { useControlAdapterProcessedControlImage } from 'features/controlAdapters/hooks/useControlAdapterProcessedControlImage';
-import { useControlAdapterProcessorType } from 'features/controlAdapters/hooks/useControlAdapterProcessorType';
 
 type Props = {
   id: string;
@@ -35,13 +35,15 @@ type Props = {
 
 const selector = createSelector(
   stateSelector,
-  ({ controlAdapters, gallery }) => {
+  ({ controlAdapters, gallery, system }) => {
     const { pendingControlImages } = controlAdapters;
     const { autoAddBoardId } = gallery;
+    const { isConnected } = system;
 
     return {
       pendingControlImages,
       autoAddBoardId,
+      isConnected,
     };
   },
   defaultSelectorOptions
@@ -55,18 +57,19 @@ const ControlAdapterImagePreview = ({ isSmall, id }: Props) => {
   const dispatch = useAppDispatch();
   const { t } = useTranslation();
 
-  const { pendingControlImages, autoAddBoardId } = useAppSelector(selector);
+  const { pendingControlImages, autoAddBoardId, isConnected } =
+    useAppSelector(selector);
   const activeTabName = useAppSelector(activeTabNameSelector);
 
   const [isMouseOverImage, setIsMouseOverImage] = useState(false);
 
-  const { currentData: controlImage } = useGetImageDTOQuery(
-    controlImageName ?? skipToken
-  );
+  const { currentData: controlImage, isError: isErrorControlImage } =
+    useGetImageDTOQuery(controlImageName ?? skipToken);
 
-  const { currentData: processedControlImage } = useGetImageDTOQuery(
-    processedControlImageName ?? skipToken
-  );
+  const {
+    currentData: processedControlImage,
+    isError: isErrorProcessedControlImage,
+  } = useGetImageDTOQuery(processedControlImageName ?? skipToken);
 
   const [changeIsIntermediate] = useChangeImageIsIntermediateMutation();
   const [addToBoard] = useAddImageToBoardMutation();
@@ -158,6 +161,17 @@ const ControlAdapterImagePreview = ({ isSmall, id }: Props) => {
     !pendingControlImages.includes(id) &&
     processorType !== 'none';
 
+  useEffect(() => {
+    if (isConnected && (isErrorControlImage || isErrorProcessedControlImage)) {
+      handleResetControlImage();
+    }
+  }, [
+    handleResetControlImage,
+    isConnected,
+    isErrorControlImage,
+    isErrorProcessedControlImage,
+  ]);
+
   return (
     <Flex
       onMouseEnter={handleMouseEnter}

invokeai/frontend/web/src/features/gallery/components/Boards/BoardContextMenu.tsx

@@ -73,7 +73,13 @@ const BoardContextMenu = ({
         addToast({
           title: t('gallery.preparingDownload'),
           status: 'success',
-          ...(response.response ? { description: response.response } : {}),
+          ...(response.response
+            ? {
+                description: response.response,
+                duration: null,
+                isClosable: true,
+              }
+            : {}),
         })
       );
     } catch {

invokeai/frontend/web/src/features/gallery/components/CurrentImage/CurrentImageButtons.tsx

@@ -16,7 +16,8 @@ import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import IAIIconButton from 'common/components/IAIIconButton';
 import { DeleteImageButton } from 'features/deleteImageModal/components/DeleteImageButton';
 import { imagesToDeleteSelected } from 'features/deleteImageModal/store/slice';
-import { workflowLoadRequested } from 'features/nodes/store/actions';
+import SingleSelectionMenuItems from 'features/gallery/components/ImageContextMenu/SingleSelectionMenuItems';
+import { sentImageToImg2Img } from 'features/gallery/store/actions';
 import ParamUpscalePopover from 'features/parameters/components/Parameters/Upscale/ParamUpscaleSettings';
 import { useRecallParameters } from 'features/parameters/hooks/useRecallParameters';
 import { initialImageSelected } from 'features/parameters/store/actions';
@@ -27,6 +28,7 @@ import {
   setShouldShowImageDetails,
   setShouldShowProgressInViewer,
 } from 'features/ui/store/uiSlice';
+import { useGetAndLoadEmbeddedWorkflow } from 'features/workflowLibrary/hooks/useGetAndLoadEmbeddedWorkflow';
 import { memo, useCallback } from 'react';
 import { useHotkeys } from 'react-hotkeys-hook';
 import { useTranslation } from 'react-i18next';
@@ -41,10 +43,7 @@ import {
 import { FaCircleNodes, FaEllipsis } from 'react-icons/fa6';
 import { useGetImageDTOQuery } from 'services/api/endpoints/images';
 import { useDebouncedMetadata } from 'services/api/hooks/useDebouncedMetadata';
-import { useDebouncedWorkflow } from 'services/api/hooks/useDebouncedWorkflow';
 import { menuListMotionProps } from 'theme/components/menu';
-import { sentImageToImg2Img } from 'features/gallery/store/actions';
-import SingleSelectionMenuItems from 'features/gallery/components/ImageContextMenu/SingleSelectionMenuItems';
 
 const currentImageButtonsSelector = createSelector(
   [stateSelector, activeTabNameSelector],
@@ -111,18 +110,17 @@ const CurrentImageButtons = () => {
     lastSelectedImage?.image_name
   );
 
-  const { workflow, isLoading: isLoadingWorkflow } = useDebouncedWorkflow(
-    lastSelectedImage?.workflow_id
-  );
+  const { getAndLoadEmbeddedWorkflow, getAndLoadEmbeddedWorkflowResult } =
+    useGetAndLoadEmbeddedWorkflow({});
 
   const handleLoadWorkflow = useCallback(() => {
-    if (!workflow) {
+    if (!lastSelectedImage || !lastSelectedImage.has_workflow) {
       return;
     }
-    dispatch(workflowLoadRequested(workflow));
-  }, [dispatch, workflow]);
+    getAndLoadEmbeddedWorkflow(lastSelectedImage.image_name);
+  }, [getAndLoadEmbeddedWorkflow, lastSelectedImage]);
 
-  useHotkeys('w', handleLoadWorkflow, [workflow]);
+  useHotkeys('w', handleLoadWorkflow, [lastSelectedImage]);
 
   const handleClickUseAllParameters = useCallback(() => {
     recallAllParameters(metadata);
@@ -255,12 +253,12 @@ const CurrentImageButtons = () => {
 
         <ButtonGroup isAttached={true} isDisabled={shouldDisableToolbarButtons}>
           <IAIIconButton
-            isLoading={isLoadingWorkflow}
             icon={<FaCircleNodes />}
             tooltip={`${t('nodes.loadWorkflow')} (W)`}
             aria-label={`${t('nodes.loadWorkflow')} (W)`}
-            isDisabled={!workflow}
+            isDisabled={!imageDTO?.has_workflow}
             onClick={handleLoadWorkflow}
+            isLoading={getAndLoadEmbeddedWorkflowResult.isLoading}
           />
           <IAIIconButton
             isLoading={isLoadingMetadata}

invokeai/frontend/web/src/features/gallery/components/ImageContextMenu/MultipleSelectionMenuItems.tsx

@@ -59,7 +59,13 @@ const MultipleSelectionMenuItems = () => {
         addToast({
           title: t('gallery.preparingDownload'),
           status: 'success',
-          ...(response.response ? { description: response.response } : {}),
+          ...(response.response
+            ? {
+                description: response.response,
+                duration: null,
+                isClosable: true,
+              }
+            : {}),
         })
       );
     } catch {

invokeai/frontend/web/src/features/gallery/components/ImageContextMenu/SingleSelectionMenuItems.tsx

@@ -3,18 +3,22 @@ import { useStore } from '@nanostores/react';
 import { useAppToaster } from 'app/components/Toaster';
 import { $customStarUI } from 'app/store/nanostores/customStarUI';
 import { useAppDispatch } from 'app/store/storeHooks';
+import { useCopyImageToClipboard } from 'common/hooks/useCopyImageToClipboard';
 import { setInitialCanvasImage } from 'features/canvas/store/canvasSlice';
 import {
   imagesToChangeSelected,
   isModalOpenChanged,
 } from 'features/changeBoardModal/store/slice';
 import { imagesToDeleteSelected } from 'features/deleteImageModal/store/slice';
-import { workflowLoadRequested } from 'features/nodes/store/actions';
+import {
+  sentImageToCanvas,
+  sentImageToImg2Img,
+} from 'features/gallery/store/actions';
 import { useRecallParameters } from 'features/parameters/hooks/useRecallParameters';
 import { initialImageSelected } from 'features/parameters/store/actions';
 import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';
-import { useCopyImageToClipboard } from 'common/hooks/useCopyImageToClipboard';
 import { setActiveTab } from 'features/ui/store/uiSlice';
+import { useGetAndLoadEmbeddedWorkflow } from 'features/workflowLibrary/hooks/useGetAndLoadEmbeddedWorkflow';
 import { memo, useCallback } from 'react';
 import { flushSync } from 'react-dom';
 import { useTranslation } from 'react-i18next';
@@ -36,12 +40,7 @@ import {
   useUnstarImagesMutation,
 } from 'services/api/endpoints/images';
 import { useDebouncedMetadata } from 'services/api/hooks/useDebouncedMetadata';
-import { useDebouncedWorkflow } from 'services/api/hooks/useDebouncedWorkflow';
 import { ImageDTO } from 'services/api/types';
-import {
-  sentImageToCanvas,
-  sentImageToImg2Img,
-} from 'features/gallery/store/actions';
 
 type SingleSelectionMenuItemsProps = {
   imageDTO: ImageDTO;
@@ -61,9 +60,13 @@ const SingleSelectionMenuItems = (props: SingleSelectionMenuItemsProps) => {
   const { metadata, isLoading: isLoadingMetadata } = useDebouncedMetadata(
     imageDTO?.image_name
   );
-  const { workflow, isLoading: isLoadingWorkflow } = useDebouncedWorkflow(
-    imageDTO?.workflow_id
-  );
+
+  const { getAndLoadEmbeddedWorkflow, getAndLoadEmbeddedWorkflowResult } =
+    useGetAndLoadEmbeddedWorkflow({});
+
+  const handleLoadWorkflow = useCallback(() => {
+    getAndLoadEmbeddedWorkflow(imageDTO.image_name);
+  }, [getAndLoadEmbeddedWorkflow, imageDTO.image_name]);
 
   const [starImages] = useStarImagesMutation();
   const [unstarImages] = useUnstarImagesMutation();
@@ -101,13 +104,6 @@ const SingleSelectionMenuItems = (props: SingleSelectionMenuItemsProps) => {
     recallSeed(metadata?.seed);
   }, [metadata?.seed, recallSeed]);
 
-  const handleLoadWorkflow = useCallback(() => {
-    if (!workflow) {
-      return;
-    }
-    dispatch(workflowLoadRequested(workflow));
-  }, [dispatch, workflow]);
-
   const handleSendToImageToImage = useCallback(() => {
     dispatch(sentImageToImg2Img());
     dispatch(initialImageSelected(imageDTO));
@@ -179,9 +175,15 @@ const SingleSelectionMenuItems = (props: SingleSelectionMenuItemsProps) => {
         {t('parameters.downloadImage')}
       </MenuItem>
       <MenuItem
-        icon={isLoadingWorkflow ? <SpinnerIcon /> : <FaCircleNodes />}
+        icon={
+          getAndLoadEmbeddedWorkflowResult.isLoading ? (
+            <SpinnerIcon />
+          ) : (
+            <FaCircleNodes />
+          )
+        }
         onClickCapture={handleLoadWorkflow}
-        isDisabled={isLoadingWorkflow || !workflow}
+        isDisabled={!imageDTO.has_workflow}
       >
         {t('nodes.loadWorkflow')}
       </MenuItem>
@@ -234,14 +236,14 @@ const SingleSelectionMenuItems = (props: SingleSelectionMenuItemsProps) => {
           icon={customStarUi ? customStarUi.off.icon : <MdStar />}
           onClickCapture={handleUnstarImage}
         >
-          {customStarUi ? customStarUi.off.text : t('controlnet.unstarImage')}
+          {customStarUi ? customStarUi.off.text : t('gallery.unstarImage')}
         </MenuItem>
       ) : (
         <MenuItem
           icon={customStarUi ? customStarUi.on.icon : <MdStarBorder />}
           onClickCapture={handleStarImage}
         >
-          {customStarUi ? customStarUi.on.text : `Star Image`}
+          {customStarUi ? customStarUi.on.text : t('gallery.starImage')}
         </MenuItem>
       )}
       <MenuItem

invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataViewer.tsx

@@ -14,10 +14,10 @@ import ScrollableContent from 'features/nodes/components/sidePanel/ScrollableCon
 import { memo } from 'react';
 import { useTranslation } from 'react-i18next';
 import { useDebouncedMetadata } from 'services/api/hooks/useDebouncedMetadata';
-import { useDebouncedWorkflow } from 'services/api/hooks/useDebouncedWorkflow';
 import { ImageDTO } from 'services/api/types';
 import DataViewer from './DataViewer';
 import ImageMetadataActions from './ImageMetadataActions';
+import ImageMetadataWorkflowTabContent from './ImageMetadataWorkflowTabContent';
 
 type ImageMetadataViewerProps = {
   image: ImageDTO;
@@ -32,7 +32,6 @@ const ImageMetadataViewer = ({ image }: ImageMetadataViewerProps) => {
   const { t } = useTranslation();
 
   const { metadata } = useDebouncedMetadata(image.image_name);
-  const { workflow } = useDebouncedWorkflow(image.workflow_id);
 
   return (
     <Flex
@@ -67,9 +66,9 @@ const ImageMetadataViewer = ({ image }: ImageMetadataViewerProps) => {
       >
         <TabList>
           <Tab>{t('metadata.recallParameters')}</Tab>
-          <Tab>{t('metadata.metadata')}</Tab>
+          <Tab isDisabled={!metadata}>{t('metadata.metadata')}</Tab>
           <Tab>{t('metadata.imageDetails')}</Tab>
-          <Tab>{t('metadata.workflow')}</Tab>
+          <Tab isDisabled={!image.has_workflow}>{t('metadata.workflow')}</Tab>
         </TabList>
 
         <TabPanels>
@@ -97,11 +96,7 @@ const ImageMetadataViewer = ({ image }: ImageMetadataViewerProps) => {
             )}
           </TabPanel>
           <TabPanel>
-            {workflow ? (
-              <DataViewer data={workflow} label={t('metadata.workflow')} />
-            ) : (
-              <IAINoContentFallback label={t('nodes.noWorkflow')} />
-            )}
+            <ImageMetadataWorkflowTabContent image={image} />
           </TabPanel>
         </TabPanels>
       </Tabs>

invokeai/frontend/web/src/features/gallery/components/ImageMetadataViewer/ImageMetadataWorkflowTabContent.tsx

@@ -0,0 +1,23 @@
+import { IAINoContentFallback } from 'common/components/IAIImageFallback';
+import { memo } from 'react';
+import { useTranslation } from 'react-i18next';
+import { useGetImageWorkflowQuery } from 'services/api/endpoints/images';
+import { ImageDTO } from 'services/api/types';
+import DataViewer from './DataViewer';
+
+type Props = {
+  image: ImageDTO;
+};
+
+const ImageMetadataWorkflowTabContent = ({ image }: Props) => {
+  const { t } = useTranslation();
+  const { currentData: workflow } = useGetImageWorkflowQuery(image.image_name);
+
+  if (!workflow) {
+    return <IAINoContentFallback label={t('nodes.noWorkflow')} />;
+  }
+
+  return <DataViewer data={workflow} label={t('metadata.workflow')} />;
+};
+
+export default memo(ImageMetadataWorkflowTabContent);

invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/EmbedWorkflowCheckbox.tsx

@@ -1,45 +0,0 @@
-import { Checkbox, Flex, FormControl, FormLabel } from '@chakra-ui/react';
-import { useAppDispatch } from 'app/store/storeHooks';
-import { useEmbedWorkflow } from 'features/nodes/hooks/useEmbedWorkflow';
-import { useWithWorkflow } from 'features/nodes/hooks/useWithWorkflow';
-import { nodeEmbedWorkflowChanged } from 'features/nodes/store/nodesSlice';
-import { ChangeEvent, memo, useCallback } from 'react';
-import { useTranslation } from 'react-i18next';
-
-const EmbedWorkflowCheckbox = ({ nodeId }: { nodeId: string }) => {
-  const { t } = useTranslation();
-  const dispatch = useAppDispatch();
-  const withWorkflow = useWithWorkflow(nodeId);
-  const embedWorkflow = useEmbedWorkflow(nodeId);
-  const handleChange = useCallback(
-    (e: ChangeEvent<HTMLInputElement>) => {
-      dispatch(
-        nodeEmbedWorkflowChanged({
-          nodeId,
-          embedWorkflow: e.target.checked,
-        })
-      );
-    },
-    [dispatch, nodeId]
-  );
-
-  if (!withWorkflow) {
-    return null;
-  }
-
-  return (
-    <FormControl as={Flex} sx={{ alignItems: 'center', gap: 2, w: 'auto' }}>
-      <FormLabel sx={{ fontSize: 'xs', mb: '1px' }}>
-        {t('metadata.workflow')}
-      </FormLabel>
-      <Checkbox
-        className="nopan"
-        size="sm"
-        onChange={handleChange}
-        isChecked={embedWorkflow}
-      />
-    </FormControl>
-  );
-};
-
-export default memo(EmbedWorkflowCheckbox);

invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/InvocationNodeFooter.tsx

@@ -1,9 +1,8 @@
 import { Flex } from '@chakra-ui/react';
 import { useHasImageOutput } from 'features/nodes/hooks/useHasImageOutput';
 import { DRAG_HANDLE_CLASSNAME } from 'features/nodes/types/constants';
-import { memo } from 'react';
 import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';
-import EmbedWorkflowCheckbox from './EmbedWorkflowCheckbox';
+import { memo } from 'react';
 import SaveToGalleryCheckbox from './SaveToGalleryCheckbox';
 import UseCacheCheckbox from './UseCacheCheckbox';
 
@@ -28,7 +27,6 @@ const InvocationNodeFooter = ({ nodeId }: Props) => {
       }}
     >
       {isCacheEnabled && <UseCacheCheckbox nodeId={nodeId} />}
-      {hasImageOutput && <EmbedWorkflowCheckbox nodeId={nodeId} />}
       {hasImageOutput && <SaveToGalleryCheckbox nodeId={nodeId} />}
     </Flex>
   );

invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/FieldContextMenu.tsx

@@ -13,7 +13,7 @@ import { useFieldTemplateTitle } from 'features/nodes/hooks/useFieldTemplateTitl
 import {
   workflowExposedFieldAdded,
   workflowExposedFieldRemoved,
-} from 'features/nodes/store/nodesSlice';
+} from 'features/nodes/store/workflowSlice';
 import { MouseEvent, ReactNode, memo, useCallback, useMemo } from 'react';
 import { FaMinus, FaPlus } from 'react-icons/fa';
 import { menuListMotionProps } from 'theme/components/menu';
@@ -41,9 +41,9 @@ const FieldContextMenu = ({ nodeId, fieldName, kind, children }: Props) => {
     () =>
       createSelector(
         stateSelector,
-        ({ nodes }) => {
+        ({ workflow }) => {
           const isExposed = Boolean(
-            nodes.workflow.exposedFields.find(
+            workflow.exposedFields.find(
               (f) => f.nodeId === nodeId && f.fieldName === fieldName
             )
           );

invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/LinearViewField.tsx

@@ -10,7 +10,7 @@ import { useAppDispatch } from 'app/store/storeHooks';
 import IAIIconButton from 'common/components/IAIIconButton';
 import NodeSelectionOverlay from 'common/components/NodeSelectionOverlay';
 import { useMouseOverNode } from 'features/nodes/hooks/useMouseOverNode';
-import { workflowExposedFieldRemoved } from 'features/nodes/store/nodesSlice';
+import { workflowExposedFieldRemoved } from 'features/nodes/store/workflowSlice';
 import { HANDLE_TOOLTIP_OPEN_DELAY } from 'features/nodes/types/constants';
 import { memo, useCallback } from 'react';
 import { FaInfoCircle, FaTrash } from 'react-icons/fa';

invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/ImageFieldInputComponent.tsx

@@ -1,6 +1,6 @@
 import { Flex, Text } from '@chakra-ui/react';
 import { skipToken } from '@reduxjs/toolkit/dist/query';
-import { useAppDispatch } from 'app/store/storeHooks';
+import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import IAIDndImage from 'common/components/IAIDndImage';
 import IAIDndImageIcon from 'common/components/IAIDndImageIcon';
 import {
@@ -13,7 +13,7 @@ import {
   ImageFieldInputTemplate,
 } from 'features/nodes/types/field';
 import { FieldComponentProps } from './types';
-import { memo, useCallback, useMemo } from 'react';
+import { memo, useCallback, useEffect, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
 import { FaUndo } from 'react-icons/fa';
 import { useGetImageDTOQuery } from 'services/api/endpoints/images';
@@ -24,8 +24,8 @@ const ImageFieldInputComponent = (
 ) => {
   const { nodeId, field } = props;
   const dispatch = useAppDispatch();
-
-  const { currentData: imageDTO } = useGetImageDTOQuery(
+  const isConnected = useAppSelector((state) => state.system.isConnected);
+  const { currentData: imageDTO, isError } = useGetImageDTOQuery(
     field.value?.image_name ?? skipToken
   );
 
@@ -67,6 +67,12 @@ const ImageFieldInputComponent = (
     [nodeId, field.name]
   );
 
+  useEffect(() => {
+    if (isConnected && isError) {
+      handleReset();
+    }
+  }, [handleReset, isConnected, isError]);
+
   return (
     <Flex
       className="nodrag"

invokeai/frontend/web/src/features/nodes/components/flow/panels/TopCenterPanel/TopCenterPanel.tsx

@@ -1,8 +1,10 @@
 import { Flex } from '@chakra-ui/layout';
 import { memo } from 'react';
-import LoadWorkflowButton from './LoadWorkflowButton';
-import ResetWorkflowButton from './ResetWorkflowButton';
-import DownloadWorkflowButton from './DownloadWorkflowButton';
+import DownloadWorkflowButton from 'features/workflowLibrary/components/DownloadWorkflowButton';
+import UploadWorkflowButton from 'features/workflowLibrary/components/LoadWorkflowFromFileButton';
+import ResetWorkflowEditorButton from 'features/workflowLibrary/components/ResetWorkflowButton';
+import SaveWorkflowButton from 'features/workflowLibrary/components/SaveWorkflowButton';
+import SaveWorkflowAsButton from 'features/workflowLibrary/components/SaveWorkflowAsButton';
 
 const TopCenterPanel = () => {
   return (
@@ -16,8 +18,10 @@ const TopCenterPanel = () => {
       }}
     >
       <DownloadWorkflowButton />
-      <LoadWorkflowButton />
-      <ResetWorkflowButton />
+      <UploadWorkflowButton />
+      <SaveWorkflowButton />
+      <SaveWorkflowAsButton />
+      <ResetWorkflowEditorButton />
     </Flex>
   );
 };

invokeai/frontend/web/src/features/nodes/components/flow/panels/TopRightPanel/TopRightPanel.tsx

@@ -1,10 +1,12 @@
-import { Flex } from '@chakra-ui/layout';
+import { Flex } from '@chakra-ui/react';
+import WorkflowLibraryButton from 'features/workflowLibrary/components/WorkflowLibraryButton';
 import { memo } from 'react';
 import WorkflowEditorSettings from './WorkflowEditorSettings';
 
 const TopRightPanel = () => {
   return (
     <Flex sx={{ gap: 2, position: 'absolute', top: 2, insetInlineEnd: 2 }}>
+      <WorkflowLibraryButton />
       <WorkflowEditorSettings />
     </Flex>
   );

invokeai/frontend/web/src/features/nodes/components/sidePanel/inspector/InspectorDetailsTab.tsx

@@ -11,17 +11,16 @@ import { stateSelector } from 'app/store/store';
 import { useAppSelector } from 'app/store/storeHooks';
 import { defaultSelectorOptions } from 'app/store/util/defaultMemoizeOptions';
 import { IAINoContentFallback } from 'common/components/IAIImageFallback';
-import { getNeedsUpdate } from 'features/nodes/util/node/nodeUpdate';
+import NotesTextarea from 'features/nodes/components/flow/nodes/Invocation/NotesTextarea';
+import ScrollableContent from 'features/nodes/components/sidePanel/ScrollableContent';
 import {
-  InvocationNodeData,
+  InvocationNode,
   InvocationTemplate,
   isInvocationNode,
 } from 'features/nodes/types/invocation';
+import { getNeedsUpdate } from 'features/nodes/util/node/nodeUpdate';
 import { memo, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
-import { Node } from 'reactflow';
-import NotesTextarea from 'features/nodes/components/flow/nodes/Invocation/NotesTextarea';
-import ScrollableContent from 'features/nodes/components/sidePanel/ScrollableContent';
 import EditableNodeTitle from './details/EditableNodeTitle';
 
 const selector = createSelector(
@@ -62,7 +61,7 @@ const InspectorDetailsTab = () => {
 export default memo(InspectorDetailsTab);
 
 type ContentProps = {
-  node: Node<InvocationNodeData>;
+  node: InvocationNode;
   template: InvocationTemplate;
 };
 

invokeai/frontend/web/src/features/nodes/components/sidePanel/workflow/WorkflowGeneralTab.tsx

@@ -5,6 +5,7 @@ import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { defaultSelectorOptions } from 'app/store/util/defaultMemoizeOptions';
 import IAIInput from 'common/components/IAIInput';
 import IAITextarea from 'common/components/IAITextarea';
+import ScrollableContent from 'features/nodes/components/sidePanel/ScrollableContent';
 import {
   workflowAuthorChanged,
   workflowContactChanged,
@@ -13,16 +14,15 @@ import {
   workflowNotesChanged,
   workflowTagsChanged,
   workflowVersionChanged,
-} from 'features/nodes/store/nodesSlice';
+} from 'features/nodes/store/workflowSlice';
 import { ChangeEvent, memo, useCallback } from 'react';
-import ScrollableContent from 'features/nodes/components/sidePanel/ScrollableContent';
 import { useTranslation } from 'react-i18next';
 
 const selector = createSelector(
   stateSelector,
-  ({ nodes }) => {
+  ({ workflow }) => {
     const { author, name, description, tags, version, contact, notes } =
-      nodes.workflow;
+      workflow;
 
     return {
       name,

invokeai/frontend/web/src/features/nodes/components/sidePanel/workflow/WorkflowLinearTab.tsx

@@ -11,9 +11,9 @@ import { useTranslation } from 'react-i18next';
 
 const selector = createSelector(
   stateSelector,
-  ({ nodes }) => {
+  ({ workflow }) => {
     return {
-      fields: nodes.workflow.exposedFields,
+      fields: workflow.exposedFields,
     };
   },
   defaultSelectorOptions

invokeai/frontend/web/src/features/nodes/hooks/useDownloadWorkflow.ts

@@ -0,0 +1,17 @@
+import { useWorkflow } from 'features/nodes/hooks/useWorkflow';
+import { useCallback } from 'react';
+
+export const useDownloadWorkflow = () => {
+  const workflow = useWorkflow();
+  const downloadWorkflow = useCallback(() => {
+    const blob = new Blob([JSON.stringify(workflow, null, 2)]);
+    const a = document.createElement('a');
+    a.href = URL.createObjectURL(blob);
+    a.download = `${workflow.name || 'My Workflow'}.json`;
+    document.body.appendChild(a);
+    a.click();
+    a.remove();
+  }, [workflow]);
+
+  return downloadWorkflow;
+};

invokeai/frontend/web/src/features/nodes/hooks/useEmbedWorkflow.ts

@@ -1,27 +0,0 @@
-import { createSelector } from '@reduxjs/toolkit';
-import { stateSelector } from 'app/store/store';
-import { useAppSelector } from 'app/store/storeHooks';
-import { defaultSelectorOptions } from 'app/store/util/defaultMemoizeOptions';
-import { useMemo } from 'react';
-import { isInvocationNode } from 'features/nodes/types/invocation';
-
-export const useEmbedWorkflow = (nodeId: string) => {
-  const selector = useMemo(
-    () =>
-      createSelector(
-        stateSelector,
-        ({ nodes }) => {
-          const node = nodes.nodes.find((node) => node.id === nodeId);
-          if (!isInvocationNode(node)) {
-            return false;
-          }
-          return node.data.embedWorkflow;
-        },
-        defaultSelectorOptions
-      ),
-    [nodeId]
-  );
-
-  const embedWorkflow = useAppSelector(selector);
-  return embedWorkflow;
-};

invokeai/frontend/web/src/features/nodes/hooks/useWithWorkflow.ts

@@ -1,31 +0,0 @@
-import { createSelector } from '@reduxjs/toolkit';
-import { stateSelector } from 'app/store/store';
-import { useAppSelector } from 'app/store/storeHooks';
-import { defaultSelectorOptions } from 'app/store/util/defaultMemoizeOptions';
-import { useMemo } from 'react';
-import { isInvocationNode } from 'features/nodes/types/invocation';
-
-export const useWithWorkflow = (nodeId: string) => {
-  const selector = useMemo(
-    () =>
-      createSelector(
-        stateSelector,
-        ({ nodes }) => {
-          const node = nodes.nodes.find((node) => node.id === nodeId);
-          if (!isInvocationNode(node)) {
-            return false;
-          }
-          const nodeTemplate = nodes.nodeTemplates[node?.data.type ?? ''];
-          if (!nodeTemplate) {
-            return false;
-          }
-          return nodeTemplate.withWorkflow;
-        },
-        defaultSelectorOptions
-      ),
-    [nodeId]
-  );
-
-  const withWorkflow = useAppSelector(selector);
-  return withWorkflow;
-};

invokeai/frontend/web/src/features/nodes/hooks/useWorkflow.ts

@@ -5,12 +5,16 @@ import { useMemo } from 'react';
 import { useDebounce } from 'use-debounce';
 
 export const useWorkflow = () => {
-  const nodes = useAppSelector((state: RootState) => state.nodes);
-  const [debouncedNodes] = useDebounce(nodes, 300);
-  const workflow = useMemo(
-    () => buildWorkflow(debouncedNodes),
-    [debouncedNodes]
+  const nodes_ = useAppSelector((state: RootState) => state.nodes.nodes);
+  const edges_ = useAppSelector((state: RootState) => state.nodes.edges);
+  const workflow_ = useAppSelector((state: RootState) => state.workflow);
+  const [nodes] = useDebounce(nodes_, 300);
+  const [edges] = useDebounce(edges_, 300);
+  const [workflow] = useDebounce(workflow_, 300);
+  const builtWorkflow = useMemo(
+    () => buildWorkflow({ nodes, edges, workflow }),
+    [nodes, edges, workflow]
   );
 
-  return workflow;
+  return builtWorkflow;
 };

invokeai/frontend/web/src/features/nodes/store/actions.ts

@@ -1,4 +1,5 @@
 import { createAction, isAnyOf } from '@reduxjs/toolkit';
+import { WorkflowV2 } from 'features/nodes/types/workflow';
 import { Graph } from 'services/api/types';
 
 export const textToImageGraphBuilt = createAction<Graph>(
@@ -17,10 +18,15 @@ export const isAnyGraphBuilt = isAnyOf(
   nodesGraphBuilt
 );
 
-export const workflowLoadRequested = createAction<unknown>(
-  'nodes/workflowLoadRequested'
-);
+export const workflowLoadRequested = createAction<{
+  workflow: unknown;
+  asCopy: boolean;
+}>('nodes/workflowLoadRequested');
 
 export const updateAllNodesRequested = createAction(
   'nodes/updateAllNodesRequested'
 );
+
+export const workflowLoaded = createAction<WorkflowV2>(
+  'workflow/workflowLoaded'
+);

invokeai/frontend/web/src/features/nodes/store/nodesSlice.ts

@@ -1,33 +1,5 @@
 import { createSlice, PayloadAction } from '@reduxjs/toolkit';
-import { cloneDeep, forEach, isEqual, uniqBy } from 'lodash-es';
-import {
-  addEdge,
-  applyEdgeChanges,
-  applyNodeChanges,
-  Connection,
-  Edge,
-  EdgeChange,
-  EdgeRemoveChange,
-  getConnectedEdges,
-  getIncomers,
-  getOutgoers,
-  Node,
-  NodeChange,
-  OnConnectStartParams,
-  SelectionMode,
-  updateEdge,
-  Viewport,
-  XYPosition,
-} from 'reactflow';
-import { receivedOpenAPISchema } from 'services/api/thunks/schema';
-import {
-  appSocketGeneratorProgress,
-  appSocketInvocationComplete,
-  appSocketInvocationError,
-  appSocketInvocationStarted,
-  appSocketQueueItemStatusChanged,
-} from 'services/events/actions';
-import { v4 as uuidv4 } from 'uuid';
+import { workflowLoaded } from 'features/nodes/store/actions';
 import { SHARED_NODE_PROPERTIES } from 'features/nodes/types/constants';
 import {
   BoardFieldValue,
@@ -57,7 +29,35 @@ import {
   NodeExecutionState,
   zNodeStatus,
 } from 'features/nodes/types/invocation';
-import { WorkflowV2 } from 'features/nodes/types/workflow';
+import { cloneDeep, forEach } from 'lodash-es';
+import {
+  addEdge,
+  applyEdgeChanges,
+  applyNodeChanges,
+  Connection,
+  Edge,
+  EdgeChange,
+  EdgeRemoveChange,
+  getConnectedEdges,
+  getIncomers,
+  getOutgoers,
+  Node,
+  NodeChange,
+  OnConnectStartParams,
+  SelectionMode,
+  updateEdge,
+  Viewport,
+  XYPosition,
+} from 'reactflow';
+import { receivedOpenAPISchema } from 'services/api/thunks/schema';
+import {
+  appSocketGeneratorProgress,
+  appSocketInvocationComplete,
+  appSocketInvocationError,
+  appSocketInvocationStarted,
+  appSocketQueueItemStatusChanged,
+} from 'services/events/actions';
+import { v4 as uuidv4 } from 'uuid';
 import { NodesState } from './types';
 import { findConnectionToValidHandle } from './util/findConnectionToValidHandle';
 import { findUnoccupiedPosition } from './util/findUnoccupiedPosition';
@@ -70,20 +70,6 @@ const initialNodeExecutionState: Omit<NodeExecutionState, 'nodeId'> = {
   outputs: [],
 };
 
-const INITIAL_WORKFLOW: WorkflowV2 = {
-  name: '',
-  author: '',
-  description: '',
-  version: '',
-  contact: '',
-  tags: '',
-  notes: '',
-  nodes: [],
-  edges: [],
-  exposedFields: [],
-  meta: { version: '2.0.0' },
-};
-
 export const initialNodesState: NodesState = {
   nodes: [],
   edges: [],
@@ -103,7 +89,6 @@ export const initialNodesState: NodesState = {
   nodeOpacity: 1,
   selectedNodes: [],
   selectedEdges: [],
-  workflow: INITIAL_WORKFLOW,
   nodeExecutionStates: {},
   viewport: { x: 0, y: 0, zoom: 1 },
   mouseOverField: null,
@@ -308,23 +293,6 @@ const nodesSlice = createSlice({
       }
       state.modifyingEdge = false;
     },
-    workflowExposedFieldAdded: (
-      state,
-      action: PayloadAction<FieldIdentifier>
-    ) => {
-      state.workflow.exposedFields = uniqBy(
-        state.workflow.exposedFields.concat(action.payload),
-        (field) => `${field.nodeId}-${field.fieldName}`
-      );
-    },
-    workflowExposedFieldRemoved: (
-      state,
-      action: PayloadAction<FieldIdentifier>
-    ) => {
-      state.workflow.exposedFields = state.workflow.exposedFields.filter(
-        (field) => !isEqual(field, action.payload)
-      );
-    },
     fieldLabelChanged: (
       state,
       action: PayloadAction<{
@@ -344,20 +312,6 @@ const nodesSlice = createSlice({
       }
       field.label = label;
     },
-    nodeEmbedWorkflowChanged: (
-      state,
-      action: PayloadAction<{ nodeId: string; embedWorkflow: boolean }>
-    ) => {
-      const { nodeId, embedWorkflow } = action.payload;
-      const nodeIndex = state.nodes.findIndex((n) => n.id === nodeId);
-
-      const node = state.nodes?.[nodeIndex];
-
-      if (!isInvocationNode(node)) {
-        return;
-      }
-      node.data.embedWorkflow = embedWorkflow;
-    },
     nodeUseCacheChanged: (
       state,
       action: PayloadAction<{ nodeId: string; useCache: boolean }>
@@ -522,9 +476,6 @@ const nodesSlice = createSlice({
     },
     nodesDeleted: (state, action: PayloadAction<AnyNode[]>) => {
       action.payload.forEach((node) => {
-        state.workflow.exposedFields = state.workflow.exposedFields.filter(
-          (f) => f.nodeId !== node.id
-        );
         if (!isInvocationNode(node)) {
           return;
         }
@@ -687,7 +638,6 @@ const nodesSlice = createSlice({
     nodeEditorReset: (state) => {
       state.nodes = [];
       state.edges = [];
-      state.workflow = cloneDeep(INITIAL_WORKFLOW);
     },
     shouldValidateGraphChanged: (state, action: PayloadAction<boolean>) => {
       state.shouldValidateGraph = action.payload;
@@ -704,56 +654,6 @@ const nodesSlice = createSlice({
     nodeOpacityChanged: (state, action: PayloadAction<number>) => {
       state.nodeOpacity = action.payload;
     },
-    workflowNameChanged: (state, action: PayloadAction<string>) => {
-      state.workflow.name = action.payload;
-    },
-    workflowDescriptionChanged: (state, action: PayloadAction<string>) => {
-      state.workflow.description = action.payload;
-    },
-    workflowTagsChanged: (state, action: PayloadAction<string>) => {
-      state.workflow.tags = action.payload;
-    },
-    workflowAuthorChanged: (state, action: PayloadAction<string>) => {
-      state.workflow.author = action.payload;
-    },
-    workflowNotesChanged: (state, action: PayloadAction<string>) => {
-      state.workflow.notes = action.payload;
-    },
-    workflowVersionChanged: (state, action: PayloadAction<string>) => {
-      state.workflow.version = action.payload;
-    },
-    workflowContactChanged: (state, action: PayloadAction<string>) => {
-      state.workflow.contact = action.payload;
-    },
-    workflowLoaded: (state, action: PayloadAction<WorkflowV2>) => {
-      const { nodes, edges, ...workflow } = action.payload;
-      state.workflow = workflow;
-
-      state.nodes = applyNodeChanges(
-        nodes.map((node) => ({
-          item: { ...node, ...SHARED_NODE_PROPERTIES },
-          type: 'add',
-        })),
-        []
-      );
-      state.edges = applyEdgeChanges(
-        edges.map((edge) => ({ item: edge, type: 'add' })),
-        []
-      );
-
-      state.nodeExecutionStates = nodes.reduce<
-        Record<string, NodeExecutionState>
-      >((acc, node) => {
-        acc[node.id] = {
-          nodeId: node.id,
-          ...initialNodeExecutionState,
-        };
-        return acc;
-      }, {});
-    },
-    workflowReset: (state) => {
-      state.workflow = cloneDeep(INITIAL_WORKFLOW);
-    },
     viewportChanged: (state, action: PayloadAction<Viewport>) => {
       state.viewport = action.payload;
     },
@@ -899,6 +799,32 @@ const nodesSlice = createSlice({
     builder.addCase(receivedOpenAPISchema.pending, (state) => {
       state.isReady = false;
     });
+
+    builder.addCase(workflowLoaded, (state, action) => {
+      const { nodes, edges } = action.payload;
+      state.nodes = applyNodeChanges(
+        nodes.map((node) => ({
+          item: { ...node, ...SHARED_NODE_PROPERTIES },
+          type: 'add',
+        })),
+        []
+      );
+      state.edges = applyEdgeChanges(
+        edges.map((edge) => ({ item: edge, type: 'add' })),
+        []
+      );
+
+      state.nodeExecutionStates = nodes.reduce<
+        Record<string, NodeExecutionState>
+      >((acc, node) => {
+        acc[node.id] = {
+          nodeId: node.id,
+          ...initialNodeExecutionState,
+        };
+        return acc;
+      }, {});
+    });
+
     builder.addCase(appSocketInvocationStarted, (state, action) => {
       const { source_node_id } = action.payload.data;
       const node = state.nodeExecutionStates[source_node_id];
@@ -984,7 +910,6 @@ export const {
   nodeAdded,
   nodeReplaced,
   nodeEditorReset,
-  nodeEmbedWorkflowChanged,
   nodeExclusivelySelected,
   nodeIsIntermediateChanged,
   nodeIsOpenChanged,
@@ -1008,16 +933,6 @@ export const {
   shouldSnapToGridChanged,
   shouldValidateGraphChanged,
   viewportChanged,
-  workflowAuthorChanged,
-  workflowContactChanged,
-  workflowDescriptionChanged,
-  workflowExposedFieldAdded,
-  workflowExposedFieldRemoved,
-  workflowLoaded,
-  workflowNameChanged,
-  workflowNotesChanged,
-  workflowTagsChanged,
-  workflowVersionChanged,
   edgeAdded,
 } = nodesSlice.actions;
 

invokeai/frontend/web/src/features/nodes/store/types.ts

@@ -29,7 +29,6 @@ export type NodesState = {
   shouldColorEdges: boolean;
   selectedNodes: string[];
   selectedEdges: string[];
-  workflow: Omit<WorkflowV2, 'nodes' | 'edges'>;
   nodeExecutionStates: Record<string, NodeExecutionState>;
   viewport: Viewport;
   isReady: boolean;
@@ -41,3 +40,5 @@ export type NodesState = {
   addNewNodePosition: XYPosition | null;
   selectionMode: SelectionMode;
 };
+
+export type WorkflowsState = Omit<WorkflowV2, 'nodes' | 'edges'>;