chore: bump version to v6.1.0rc1

Make the staging area a virtualized list so it doesn't choke when there
are a large number (i.e. more than a few hundred) of queue items.

.github/actions/install-frontend-deps/action.yml

@@ -3,15 +3,15 @@ description: Installs frontend dependencies with pnpm, with caching
 runs:
   using: 'composite'
   steps:
-    - name: setup node 18
+    - name: setup node 20
       uses: actions/setup-node@v4
       with:
-        node-version: '18'
+        node-version: '20'
 
     - name: setup pnpm
       uses: pnpm/action-setup@v4
       with:
-        version: 8.15.6
+        version: 10
         run_install: false
 
     - name: get pnpm store directory

.gitignore

@@ -180,6 +180,7 @@ cython_debug/
 # Scratch folder
 .scratch/
 .vscode/
+.zed/
 
 # source installer files
 installer/*zip

docs/contributing/frontend/workflows.md

@@ -297,7 +297,7 @@ Migration logic is in [migrations.ts].
 <!-- links -->
 
 [pydantic]: https://github.com/pydantic/pydantic 'pydantic'
-[zod]: https://github.com/colinhacks/zod 'zod'
+[zod]: https://github.com/colinhacks/zod 'zod/v4'
 [openapi-types]: https://github.com/kogosoftwarellc/open-api/tree/main/packages/openapi-types 'openapi-types'
 [reactflow]: https://github.com/xyflow/xyflow 'reactflow'
 [reactflow-concepts]: https://reactflow.dev/learn/concepts/terms-and-definitions

docs/installation/quick_start.md

@@ -35,7 +35,7 @@ More detail on system requirements can be found [here](./requirements.md).
 
 ## Step 2: Download
 
-Download the most launcher for your operating system:
+Download the most recent launcher for your operating system:
 
 - [Download for Windows](https://download.invoke.ai/Invoke%20Community%20Edition.exe)
 - [Download for macOS](https://download.invoke.ai/Invoke%20Community%20Edition.dmg)

invokeai/app/api/routers/board_images.py

@@ -1,21 +1,12 @@
 from fastapi import Body, HTTPException
 from fastapi.routing import APIRouter
-from pydantic import BaseModel, Field
 
 from invokeai.app.api.dependencies import ApiDependencies
+from invokeai.app.services.images.images_common import AddImagesToBoardResult, RemoveImagesFromBoardResult
 
 board_images_router = APIRouter(prefix="/v1/board_images", tags=["boards"])
 
 
-class AddImagesToBoardResult(BaseModel):
-    board_id: str = Field(description="The id of the board the images were added to")
-    added_image_names: list[str] = Field(description="The image names that were added to the board")
-
-
-class RemoveImagesFromBoardResult(BaseModel):
-    removed_image_names: list[str] = Field(description="The image names that were removed from their board")
-
-
 @board_images_router.post(
     "/",
     operation_id="add_image_to_board",
@@ -23,17 +14,26 @@ class RemoveImagesFromBoardResult(BaseModel):
         201: {"description": "The image was added to a board successfully"},
     },
     status_code=201,
+    response_model=AddImagesToBoardResult,
 )
 async def add_image_to_board(
     board_id: str = Body(description="The id of the board to add to"),
     image_name: str = Body(description="The name of the image to add"),
-):
+) -> AddImagesToBoardResult:
     """Creates a board_image"""
     try:
-        result = ApiDependencies.invoker.services.board_images.add_image_to_board(
-            board_id=board_id, image_name=image_name
+        added_images: set[str] = set()
+        affected_boards: set[str] = set()
+        old_board_id = ApiDependencies.invoker.services.images.get_dto(image_name).board_id or "none"
+        ApiDependencies.invoker.services.board_images.add_image_to_board(board_id=board_id, image_name=image_name)
+        added_images.add(image_name)
+        affected_boards.add(board_id)
+        affected_boards.add(old_board_id)
+
+        return AddImagesToBoardResult(
+            added_images=list(added_images),
+            affected_boards=list(affected_boards),
         )
-        return result
     except Exception:
         raise HTTPException(status_code=500, detail="Failed to add image to board")
 
@@ -45,14 +45,25 @@ async def add_image_to_board(
         201: {"description": "The image was removed from the board successfully"},
     },
     status_code=201,
+    response_model=RemoveImagesFromBoardResult,
 )
 async def remove_image_from_board(
     image_name: str = Body(description="The name of the image to remove", embed=True),
-):
+) -> RemoveImagesFromBoardResult:
     """Removes an image from its board, if it had one"""
     try:
-        result = ApiDependencies.invoker.services.board_images.remove_image_from_board(image_name=image_name)
-        return result
+        removed_images: set[str] = set()
+        affected_boards: set[str] = set()
+        old_board_id = ApiDependencies.invoker.services.images.get_dto(image_name).board_id or "none"
+        ApiDependencies.invoker.services.board_images.remove_image_from_board(image_name=image_name)
+        removed_images.add(image_name)
+        affected_boards.add("none")
+        affected_boards.add(old_board_id)
+        return RemoveImagesFromBoardResult(
+            removed_images=list(removed_images),
+            affected_boards=list(affected_boards),
+        )
+
     except Exception:
         raise HTTPException(status_code=500, detail="Failed to remove image from board")
 
@@ -72,16 +83,25 @@ async def add_images_to_board(
 ) -> AddImagesToBoardResult:
     """Adds a list of images to a board"""
     try:
-        added_image_names: list[str] = []
+        added_images: set[str] = set()
+        affected_boards: set[str] = set()
         for image_name in image_names:
             try:
+                old_board_id = ApiDependencies.invoker.services.images.get_dto(image_name).board_id or "none"
                 ApiDependencies.invoker.services.board_images.add_image_to_board(
-                    board_id=board_id, image_name=image_name
+                    board_id=board_id,
+                    image_name=image_name,
                 )
-                added_image_names.append(image_name)
+                added_images.add(image_name)
+                affected_boards.add(board_id)
+                affected_boards.add(old_board_id)
+
             except Exception:
                 pass
-        return AddImagesToBoardResult(board_id=board_id, added_image_names=added_image_names)
+        return AddImagesToBoardResult(
+            added_images=list(added_images),
+            affected_boards=list(affected_boards),
+        )
     except Exception:
         raise HTTPException(status_code=500, detail="Failed to add images to board")
 
@@ -100,13 +120,20 @@ async def remove_images_from_board(
 ) -> RemoveImagesFromBoardResult:
     """Removes a list of images from their board, if they had one"""
     try:
-        removed_image_names: list[str] = []
+        removed_images: set[str] = set()
+        affected_boards: set[str] = set()
         for image_name in image_names:
             try:
+                old_board_id = ApiDependencies.invoker.services.images.get_dto(image_name).board_id or "none"
                 ApiDependencies.invoker.services.board_images.remove_image_from_board(image_name=image_name)
-                removed_image_names.append(image_name)
+                removed_images.add(image_name)
+                affected_boards.add("none")
+                affected_boards.add(old_board_id)
             except Exception:
                 pass
-        return RemoveImagesFromBoardResult(removed_image_names=removed_image_names)
+        return RemoveImagesFromBoardResult(
+            removed_images=list(removed_images),
+            affected_boards=list(affected_boards),
+        )
     except Exception:
         raise HTTPException(status_code=500, detail="Failed to remove images from board")

invokeai/app/api/routers/images.py

@@ -14,10 +14,17 @@ from invokeai.app.api.extract_metadata_from_image import extract_metadata_from_i
 from invokeai.app.invocations.fields import MetadataField
 from invokeai.app.services.image_records.image_records_common import (
     ImageCategory,
+    ImageNamesResult,
     ImageRecordChanges,
     ResourceOrigin,
 )
-from invokeai.app.services.images.images_common import ImageDTO, ImageUrlsDTO
+from invokeai.app.services.images.images_common import (
+    DeleteImagesResult,
+    ImageDTO,
+    ImageUrlsDTO,
+    StarredImagesResult,
+    UnstarredImagesResult,
+)
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
 from invokeai.app.services.shared.sqlite.sqlite_common import SQLiteDirection
 from invokeai.app.util.controlnet_utils import heuristic_resize_fast
@@ -65,7 +72,7 @@ async def upload_image(
     resize_to: Optional[str] = Body(
         default=None,
         description=f"Dimensions to resize the image to, must be stringified tuple of 2 integers. Max total pixel count: {ResizeToDimensions.MAX_SIZE}",
-        example='"[1024,1024]"',
+        examples=['"[1024,1024]"'],
     ),
     metadata: Optional[str] = Body(
         default=None,
@@ -153,18 +160,30 @@ async def create_image_upload_entry(
     raise HTTPException(status_code=501, detail="Not implemented")
 
 
-@images_router.delete("/i/{image_name}", operation_id="delete_image")
+@images_router.delete("/i/{image_name}", operation_id="delete_image", response_model=DeleteImagesResult)
 async def delete_image(
     image_name: str = Path(description="The name of the image to delete"),
-) -> None:
+) -> DeleteImagesResult:
     """Deletes an image"""
 
+    deleted_images: set[str] = set()
+    affected_boards: set[str] = set()
+
     try:
+        image_dto = ApiDependencies.invoker.services.images.get_dto(image_name)
+        board_id = image_dto.board_id or "none"
         ApiDependencies.invoker.services.images.delete(image_name)
+        deleted_images.add(image_name)
+        affected_boards.add(board_id)
     except Exception:
         # TODO: Does this need any exception handling at all?
         pass
 
+    return DeleteImagesResult(
+        deleted_images=list(deleted_images),
+        affected_boards=list(affected_boards),
+    )
+
 
 @images_router.delete("/intermediates", operation_id="clear_intermediates")
 async def clear_intermediates() -> int:
@@ -376,31 +395,32 @@ async def list_image_dtos(
     return image_dtos
 
 
-class DeleteImagesFromListResult(BaseModel):
-    deleted_images: list[str]
-
-
-@images_router.post("/delete", operation_id="delete_images_from_list", response_model=DeleteImagesFromListResult)
+@images_router.post("/delete", operation_id="delete_images_from_list", response_model=DeleteImagesResult)
 async def delete_images_from_list(
     image_names: list[str] = Body(description="The list of names of images to delete", embed=True),
-) -> DeleteImagesFromListResult:
+) -> DeleteImagesResult:
     try:
-        deleted_images: list[str] = []
+        deleted_images: set[str] = set()
+        affected_boards: set[str] = set()
         for image_name in image_names:
             try:
+                image_dto = ApiDependencies.invoker.services.images.get_dto(image_name)
+                board_id = image_dto.board_id or "none"
                 ApiDependencies.invoker.services.images.delete(image_name)
-                deleted_images.append(image_name)
+                deleted_images.add(image_name)
+                affected_boards.add(board_id)
             except Exception:
                 pass
-        return DeleteImagesFromListResult(deleted_images=deleted_images)
+        return DeleteImagesResult(
+            deleted_images=list(deleted_images),
+            affected_boards=list(affected_boards),
+        )
     except Exception:
         raise HTTPException(status_code=500, detail="Failed to delete images")
 
 
-@images_router.delete(
-    "/uncategorized", operation_id="delete_uncategorized_images", response_model=DeleteImagesFromListResult
-)
-async def delete_uncategorized_images() -> DeleteImagesFromListResult:
+@images_router.delete("/uncategorized", operation_id="delete_uncategorized_images", response_model=DeleteImagesResult)
+async def delete_uncategorized_images() -> DeleteImagesResult:
     """Deletes all images that are uncategorized"""
 
     image_names = ApiDependencies.invoker.services.board_images.get_all_board_image_names_for_board(
@@ -408,14 +428,19 @@ async def delete_uncategorized_images() -> DeleteImagesFromListResult:
     )
 
     try:
-        deleted_images: list[str] = []
+        deleted_images: set[str] = set()
+        affected_boards: set[str] = set()
         for image_name in image_names:
             try:
                 ApiDependencies.invoker.services.images.delete(image_name)
-                deleted_images.append(image_name)
+                deleted_images.add(image_name)
+                affected_boards.add("none")
             except Exception:
                 pass
-        return DeleteImagesFromListResult(deleted_images=deleted_images)
+        return DeleteImagesResult(
+            deleted_images=list(deleted_images),
+            affected_boards=list(affected_boards),
+        )
     except Exception:
         raise HTTPException(status_code=500, detail="Failed to delete images")
 
@@ -424,36 +449,50 @@ class ImagesUpdatedFromListResult(BaseModel):
     updated_image_names: list[str] = Field(description="The image names that were updated")
 
 
-@images_router.post("/star", operation_id="star_images_in_list", response_model=ImagesUpdatedFromListResult)
+@images_router.post("/star", operation_id="star_images_in_list", response_model=StarredImagesResult)
 async def star_images_in_list(
     image_names: list[str] = Body(description="The list of names of images to star", embed=True),
-) -> ImagesUpdatedFromListResult:
+) -> StarredImagesResult:
     try:
-        updated_image_names: list[str] = []
+        starred_images: set[str] = set()
+        affected_boards: set[str] = set()
         for image_name in image_names:
             try:
-                ApiDependencies.invoker.services.images.update(image_name, changes=ImageRecordChanges(starred=True))
-                updated_image_names.append(image_name)
+                updated_image_dto = ApiDependencies.invoker.services.images.update(
+                    image_name, changes=ImageRecordChanges(starred=True)
+                )
+                starred_images.add(image_name)
+                affected_boards.add(updated_image_dto.board_id or "none")
             except Exception:
                 pass
-        return ImagesUpdatedFromListResult(updated_image_names=updated_image_names)
+        return StarredImagesResult(
+            starred_images=list(starred_images),
+            affected_boards=list(affected_boards),
+        )
     except Exception:
         raise HTTPException(status_code=500, detail="Failed to star images")
 
 
-@images_router.post("/unstar", operation_id="unstar_images_in_list", response_model=ImagesUpdatedFromListResult)
+@images_router.post("/unstar", operation_id="unstar_images_in_list", response_model=UnstarredImagesResult)
 async def unstar_images_in_list(
     image_names: list[str] = Body(description="The list of names of images to unstar", embed=True),
-) -> ImagesUpdatedFromListResult:
+) -> UnstarredImagesResult:
     try:
-        updated_image_names: list[str] = []
+        unstarred_images: set[str] = set()
+        affected_boards: set[str] = set()
         for image_name in image_names:
             try:
-                ApiDependencies.invoker.services.images.update(image_name, changes=ImageRecordChanges(starred=False))
-                updated_image_names.append(image_name)
+                updated_image_dto = ApiDependencies.invoker.services.images.update(
+                    image_name, changes=ImageRecordChanges(starred=False)
+                )
+                unstarred_images.add(image_name)
+                affected_boards.add(updated_image_dto.board_id or "none")
             except Exception:
                 pass
-        return ImagesUpdatedFromListResult(updated_image_names=updated_image_names)
+        return UnstarredImagesResult(
+            unstarred_images=list(unstarred_images),
+            affected_boards=list(affected_boards),
+        )
     except Exception:
         raise HTTPException(status_code=500, detail="Failed to unstar images")
 
@@ -524,3 +563,61 @@ async def get_bulk_download_item(
         return response
     except Exception:
         raise HTTPException(status_code=404)
+
+
+@images_router.get("/names", operation_id="get_image_names")
+async def get_image_names(
+    image_origin: Optional[ResourceOrigin] = Query(default=None, description="The origin of images to list."),
+    categories: Optional[list[ImageCategory]] = Query(default=None, description="The categories of image to include."),
+    is_intermediate: Optional[bool] = Query(default=None, description="Whether to list intermediate images."),
+    board_id: Optional[str] = Query(
+        default=None,
+        description="The board id to filter by. Use 'none' to find images without a board.",
+    ),
+    order_dir: SQLiteDirection = Query(default=SQLiteDirection.Descending, description="The order of sort"),
+    starred_first: bool = Query(default=True, description="Whether to sort by starred images first"),
+    search_term: Optional[str] = Query(default=None, description="The term to search for"),
+) -> ImageNamesResult:
+    """Gets ordered list of image names with metadata for optimistic updates"""
+
+    try:
+        result = ApiDependencies.invoker.services.images.get_image_names(
+            starred_first=starred_first,
+            order_dir=order_dir,
+            image_origin=image_origin,
+            categories=categories,
+            is_intermediate=is_intermediate,
+            board_id=board_id,
+            search_term=search_term,
+        )
+        return result
+    except Exception:
+        raise HTTPException(status_code=500, detail="Failed to get image names")
+
+
+@images_router.post(
+    "/images_by_names",
+    operation_id="get_images_by_names",
+    responses={200: {"model": list[ImageDTO]}},
+)
+async def get_images_by_names(
+    image_names: list[str] = Body(embed=True, description="Object containing list of image names to fetch DTOs for"),
+) -> list[ImageDTO]:
+    """Gets image DTOs for the specified image names. Maintains order of input names."""
+
+    try:
+        image_service = ApiDependencies.invoker.services.images
+
+        # Fetch DTOs preserving the order of requested names
+        image_dtos: list[ImageDTO] = []
+        for name in image_names:
+            try:
+                dto = image_service.get_dto(name)
+                image_dtos.append(dto)
+            except Exception:
+                # Skip missing images - they may have been deleted between name fetch and DTO fetch
+                continue
+
+        return image_dtos
+    except Exception:
+        raise HTTPException(status_code=500, detail="Failed to get image DTOs")

invokeai/app/api/routers/model_manager.py

@@ -41,6 +41,7 @@ from invokeai.backend.model_manager.starter_models import (
     STARTER_BUNDLES,
     STARTER_MODELS,
     StarterModel,
+    StarterModelBundle,
     StarterModelWithoutDependencies,
 )
 
@@ -291,7 +292,7 @@ async def get_hugging_face_models(
 )
 async def update_model_record(
     key: Annotated[str, Path(description="Unique key of model")],
-    changes: Annotated[ModelRecordChanges, Body(description="Model config", example=example_model_input)],
+    changes: Annotated[ModelRecordChanges, Body(description="Model config", examples=[example_model_input])],
 ) -> AnyModelConfig:
     """Update a model's config."""
     logger = ApiDependencies.invoker.services.logger
@@ -449,7 +450,7 @@ async def install_model(
     access_token: Optional[str] = Query(description="access token for the remote resource", default=None),
     config: ModelRecordChanges = Body(
         description="Object containing fields that override auto-probed values in the model config record, such as name, description and prediction_type ",
-        example={"name": "string", "description": "string"},
+        examples=[{"name": "string", "description": "string"}],
     ),
 ) -> ModelInstallJob:
     """Install a model using a string identifier.
@@ -799,7 +800,7 @@ async def convert_model(
 
 class StarterModelResponse(BaseModel):
     starter_models: list[StarterModel]
-    starter_bundles: dict[str, list[StarterModel]]
+    starter_bundles: dict[str, StarterModelBundle]
 
 
 def get_is_installed(
@@ -833,7 +834,7 @@ async def get_starter_models() -> StarterModelResponse:
         model.dependencies = missing_deps
 
     for bundle in starter_bundles.values():
-        for model in bundle:
+        for model in bundle.models:
             model.is_installed = get_is_installed(model, installed_models)
             # Remove already-installed dependencies
             missing_deps: list[StarterModelWithoutDependencies] = []

invokeai/app/api/routers/session_queue.py

@@ -1,6 +1,6 @@
 from typing import Optional
 
-from fastapi import Body, Path, Query
+from fastapi import Body, HTTPException, Path, Query
 from fastapi.routing import APIRouter
 from pydantic import BaseModel, Field
 
@@ -14,13 +14,15 @@ from invokeai.app.services.session_queue.session_queue_common import (
     CancelByBatchIDsResult,
     CancelByDestinationResult,
     ClearResult,
+    DeleteAllExceptCurrentResult,
+    DeleteByDestinationResult,
     EnqueueBatchResult,
     FieldIdentifier,
     PruneResult,
     RetryItemsResult,
     SessionQueueCountsByDestination,
     SessionQueueItem,
-    SessionQueueItemDTO,
+    SessionQueueItemNotFoundError,
     SessionQueueStatus,
 )
 from invokeai.app.services.shared.pagination import CursorPaginatedResults
@@ -58,17 +60,19 @@ async def enqueue_batch(
     ),
 ) -> EnqueueBatchResult:
     """Processes a batch and enqueues the output graphs for execution."""
-
-    return await ApiDependencies.invoker.services.session_queue.enqueue_batch(
-        queue_id=queue_id, batch=batch, prepend=prepend
-    )
+    try:
+        return await ApiDependencies.invoker.services.session_queue.enqueue_batch(
+            queue_id=queue_id, batch=batch, prepend=prepend
+        )
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Unexpected error while enqueuing batch: {e}")
 
 
 @session_queue_router.get(
     "/{queue_id}/list",
     operation_id="list_queue_items",
     responses={
-        200: {"model": CursorPaginatedResults[SessionQueueItemDTO]},
+        200: {"model": CursorPaginatedResults[SessionQueueItem]},
     },
 )
 async def list_queue_items(
@@ -77,12 +81,42 @@ async def list_queue_items(
     status: Optional[QUEUE_ITEM_STATUS] = Query(default=None, description="The status of items to fetch"),
     cursor: Optional[int] = Query(default=None, description="The pagination cursor"),
     priority: int = Query(default=0, description="The pagination cursor priority"),
-) -> CursorPaginatedResults[SessionQueueItemDTO]:
-    """Gets all queue items (without graphs)"""
+    destination: Optional[str] = Query(default=None, description="The destination of queue items to fetch"),
+) -> CursorPaginatedResults[SessionQueueItem]:
+    """Gets cursor-paginated queue items"""
 
-    return ApiDependencies.invoker.services.session_queue.list_queue_items(
-        queue_id=queue_id, limit=limit, status=status, cursor=cursor, priority=priority
-    )
+    try:
+        return ApiDependencies.invoker.services.session_queue.list_queue_items(
+            queue_id=queue_id,
+            limit=limit,
+            status=status,
+            cursor=cursor,
+            priority=priority,
+            destination=destination,
+        )
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Unexpected error while listing all items: {e}")
+
+
+@session_queue_router.get(
+    "/{queue_id}/list_all",
+    operation_id="list_all_queue_items",
+    responses={
+        200: {"model": list[SessionQueueItem]},
+    },
+)
+async def list_all_queue_items(
+    queue_id: str = Path(description="The queue id to perform this operation on"),
+    destination: Optional[str] = Query(default=None, description="The destination of queue items to fetch"),
+) -> list[SessionQueueItem]:
+    """Gets all queue items"""
+    try:
+        return ApiDependencies.invoker.services.session_queue.list_all_queue_items(
+            queue_id=queue_id,
+            destination=destination,
+        )
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Unexpected error while listing all queue items: {e}")
 
 
 @session_queue_router.put(
@@ -94,7 +128,10 @@ async def resume(
     queue_id: str = Path(description="The queue id to perform this operation on"),
 ) -> SessionProcessorStatus:
     """Resumes session processor"""
-    return ApiDependencies.invoker.services.session_processor.resume()
+    try:
+        return ApiDependencies.invoker.services.session_processor.resume()
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Unexpected error while resuming queue: {e}")
 
 
 @session_queue_router.put(
@@ -106,7 +143,10 @@ async def Pause(
     queue_id: str = Path(description="The queue id to perform this operation on"),
 ) -> SessionProcessorStatus:
     """Pauses session processor"""
-    return ApiDependencies.invoker.services.session_processor.pause()
+    try:
+        return ApiDependencies.invoker.services.session_processor.pause()
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Unexpected error while pausing queue: {e}")
 
 
 @session_queue_router.put(
@@ -118,7 +158,25 @@ async def cancel_all_except_current(
     queue_id: str = Path(description="The queue id to perform this operation on"),
 ) -> CancelAllExceptCurrentResult:
     """Immediately cancels all queue items except in-processing items"""
-    return ApiDependencies.invoker.services.session_queue.cancel_all_except_current(queue_id=queue_id)
+    try:
+        return ApiDependencies.invoker.services.session_queue.cancel_all_except_current(queue_id=queue_id)
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Unexpected error while canceling all except current: {e}")
+
+
+@session_queue_router.put(
+    "/{queue_id}/delete_all_except_current",
+    operation_id="delete_all_except_current",
+    responses={200: {"model": DeleteAllExceptCurrentResult}},
+)
+async def delete_all_except_current(
+    queue_id: str = Path(description="The queue id to perform this operation on"),
+) -> DeleteAllExceptCurrentResult:
+    """Immediately deletes all queue items except in-processing items"""
+    try:
+        return ApiDependencies.invoker.services.session_queue.delete_all_except_current(queue_id=queue_id)
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Unexpected error while deleting all except current: {e}")
 
 
 @session_queue_router.put(
@@ -131,7 +189,12 @@ async def cancel_by_batch_ids(
     batch_ids: list[str] = Body(description="The list of batch_ids to cancel all queue items for", embed=True),
 ) -> CancelByBatchIDsResult:
     """Immediately cancels all queue items from the given batch ids"""
-    return ApiDependencies.invoker.services.session_queue.cancel_by_batch_ids(queue_id=queue_id, batch_ids=batch_ids)
+    try:
+        return ApiDependencies.invoker.services.session_queue.cancel_by_batch_ids(
+            queue_id=queue_id, batch_ids=batch_ids
+        )
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Unexpected error while canceling by batch id: {e}")
 
 
 @session_queue_router.put(
@@ -144,9 +207,12 @@ async def cancel_by_destination(
     destination: str = Query(description="The destination to cancel all queue items for"),
 ) -> CancelByDestinationResult:
     """Immediately cancels all queue items with the given origin"""
-    return ApiDependencies.invoker.services.session_queue.cancel_by_destination(
-        queue_id=queue_id, destination=destination
-    )
+    try:
+        return ApiDependencies.invoker.services.session_queue.cancel_by_destination(
+            queue_id=queue_id, destination=destination
+        )
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Unexpected error while canceling by destination: {e}")
 
 
 @session_queue_router.put(
@@ -159,7 +225,10 @@ async def retry_items_by_id(
     item_ids: list[int] = Body(description="The queue item ids to retry"),
 ) -> RetryItemsResult:
     """Immediately cancels all queue items with the given origin"""
-    return ApiDependencies.invoker.services.session_queue.retry_items_by_id(queue_id=queue_id, item_ids=item_ids)
+    try:
+        return ApiDependencies.invoker.services.session_queue.retry_items_by_id(queue_id=queue_id, item_ids=item_ids)
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Unexpected error while retrying queue items: {e}")
 
 
 @session_queue_router.put(
@@ -173,11 +242,14 @@ async def clear(
     queue_id: str = Path(description="The queue id to perform this operation on"),
 ) -> ClearResult:
     """Clears the queue entirely, immediately canceling the currently-executing session"""
-    queue_item = ApiDependencies.invoker.services.session_queue.get_current(queue_id)
-    if queue_item is not None:
-        ApiDependencies.invoker.services.session_queue.cancel_queue_item(queue_item.item_id)
-    clear_result = ApiDependencies.invoker.services.session_queue.clear(queue_id)
-    return clear_result
+    try:
+        queue_item = ApiDependencies.invoker.services.session_queue.get_current(queue_id)
+        if queue_item is not None:
+            ApiDependencies.invoker.services.session_queue.cancel_queue_item(queue_item.item_id)
+        clear_result = ApiDependencies.invoker.services.session_queue.clear(queue_id)
+        return clear_result
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Unexpected error while clearing queue: {e}")
 
 
 @session_queue_router.put(
@@ -191,7 +263,10 @@ async def prune(
     queue_id: str = Path(description="The queue id to perform this operation on"),
 ) -> PruneResult:
     """Prunes all completed or errored queue items"""
-    return ApiDependencies.invoker.services.session_queue.prune(queue_id)
+    try:
+        return ApiDependencies.invoker.services.session_queue.prune(queue_id)
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Unexpected error while pruning queue: {e}")
 
 
 @session_queue_router.get(
@@ -205,7 +280,10 @@ async def get_current_queue_item(
     queue_id: str = Path(description="The queue id to perform this operation on"),
 ) -> Optional[SessionQueueItem]:
     """Gets the currently execution queue item"""
-    return ApiDependencies.invoker.services.session_queue.get_current(queue_id)
+    try:
+        return ApiDependencies.invoker.services.session_queue.get_current(queue_id)
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Unexpected error while getting current queue item: {e}")
 
 
 @session_queue_router.get(
@@ -219,7 +297,10 @@ async def get_next_queue_item(
     queue_id: str = Path(description="The queue id to perform this operation on"),
 ) -> Optional[SessionQueueItem]:
     """Gets the next queue item, without executing it"""
-    return ApiDependencies.invoker.services.session_queue.get_next(queue_id)
+    try:
+        return ApiDependencies.invoker.services.session_queue.get_next(queue_id)
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Unexpected error while getting next queue item: {e}")
 
 
 @session_queue_router.get(
@@ -233,9 +314,12 @@ async def get_queue_status(
     queue_id: str = Path(description="The queue id to perform this operation on"),
 ) -> SessionQueueAndProcessorStatus:
     """Gets the status of the session queue"""
-    queue = ApiDependencies.invoker.services.session_queue.get_queue_status(queue_id)
-    processor = ApiDependencies.invoker.services.session_processor.get_status()
-    return SessionQueueAndProcessorStatus(queue=queue, processor=processor)
+    try:
+        queue = ApiDependencies.invoker.services.session_queue.get_queue_status(queue_id)
+        processor = ApiDependencies.invoker.services.session_processor.get_status()
+        return SessionQueueAndProcessorStatus(queue=queue, processor=processor)
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Unexpected error while getting queue status: {e}")
 
 
 @session_queue_router.get(
@@ -250,7 +334,10 @@ async def get_batch_status(
     batch_id: str = Path(description="The batch to get the status of"),
 ) -> BatchStatus:
     """Gets the status of the session queue"""
-    return ApiDependencies.invoker.services.session_queue.get_batch_status(queue_id=queue_id, batch_id=batch_id)
+    try:
+        return ApiDependencies.invoker.services.session_queue.get_batch_status(queue_id=queue_id, batch_id=batch_id)
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Unexpected error while getting batch status: {e}")
 
 
 @session_queue_router.get(
@@ -266,7 +353,27 @@ async def get_queue_item(
     item_id: int = Path(description="The queue item to get"),
 ) -> SessionQueueItem:
     """Gets a queue item"""
-    return ApiDependencies.invoker.services.session_queue.get_queue_item(item_id)
+    try:
+        return ApiDependencies.invoker.services.session_queue.get_queue_item(item_id)
+    except SessionQueueItemNotFoundError:
+        raise HTTPException(status_code=404, detail=f"Queue item with id {item_id} not found in queue {queue_id}")
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Unexpected error while fetching queue item: {e}")
+
+
+@session_queue_router.delete(
+    "/{queue_id}/i/{item_id}",
+    operation_id="delete_queue_item",
+)
+async def delete_queue_item(
+    queue_id: str = Path(description="The queue id to perform this operation on"),
+    item_id: int = Path(description="The queue item to delete"),
+) -> None:
+    """Deletes a queue item"""
+    try:
+        ApiDependencies.invoker.services.session_queue.delete_queue_item(item_id)
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Unexpected error while deleting queue item: {e}")
 
 
 @session_queue_router.put(
@@ -281,8 +388,12 @@ async def cancel_queue_item(
     item_id: int = Path(description="The queue item to cancel"),
 ) -> SessionQueueItem:
     """Deletes a queue item"""
-
-    return ApiDependencies.invoker.services.session_queue.cancel_queue_item(item_id)
+    try:
+        return ApiDependencies.invoker.services.session_queue.cancel_queue_item(item_id)
+    except SessionQueueItemNotFoundError:
+        raise HTTPException(status_code=404, detail=f"Queue item with id {item_id} not found in queue {queue_id}")
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Unexpected error while canceling queue item: {e}")
 
 
 @session_queue_router.get(
@@ -295,6 +406,27 @@ async def counts_by_destination(
     destination: str = Query(description="The destination to query"),
 ) -> SessionQueueCountsByDestination:
     """Gets the counts of queue items by destination"""
-    return ApiDependencies.invoker.services.session_queue.get_counts_by_destination(
-        queue_id=queue_id, destination=destination
-    )
+    try:
+        return ApiDependencies.invoker.services.session_queue.get_counts_by_destination(
+            queue_id=queue_id, destination=destination
+        )
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Unexpected error while fetching counts by destination: {e}")
+
+
+@session_queue_router.delete(
+    "/{queue_id}/d/{destination}",
+    operation_id="delete_by_destination",
+    responses={200: {"model": DeleteByDestinationResult}},
+)
+async def delete_by_destination(
+    queue_id: str = Path(description="The queue id to query"),
+    destination: str = Path(description="The destination to query"),
+) -> DeleteByDestinationResult:
+    """Deletes all items with the given destination"""
+    try:
+        return ApiDependencies.invoker.services.session_queue.delete_by_destination(
+            queue_id=queue_id, destination=destination
+        )
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Unexpected error while deleting by destination: {e}")

invokeai/app/invocations/baseinvocation.py

@@ -582,6 +582,8 @@ def invocation(
 
         fields: dict[str, tuple[Any, FieldInfo]] = {}
 
+        original_model_fields: dict[str, OriginalModelField] = {}
+
         for field_name, field_info in cls.model_fields.items():
             annotation = field_info.annotation
             assert annotation is not None, f"{field_name} on invocation {invocation_type} has no type annotation."
@@ -589,7 +591,7 @@ def invocation(
                 f"{field_name} on invocation {invocation_type} has a non-dict json_schema_extra, did you forget to use InputField?"
             )
 
-            cls._original_model_fields[field_name] = OriginalModelField(annotation=annotation, field_info=field_info)
+            original_model_fields[field_name] = OriginalModelField(annotation=annotation, field_info=field_info)
 
             validate_field_default(cls.__name__, field_name, invocation_type, annotation, field_info)
 
@@ -676,6 +678,7 @@ def invocation(
         docstring = cls.__doc__
         new_class = create_model(cls.__qualname__, __base__=cls, __module__=cls.__module__, **fields)  # type: ignore
         new_class.__doc__ = docstring
+        new_class._original_model_fields = original_model_fields
 
         InvocationRegistry.register_invocation(new_class)
 

invokeai/app/invocations/fields.py

@@ -64,6 +64,7 @@ class UIType(str, Enum, metaclass=MetaEnum):
     Imagen3Model = "Imagen3ModelField"
     Imagen4Model = "Imagen4ModelField"
     ChatGPT4oModel = "ChatGPT4oModelField"
+    FluxKontextModel = "FluxKontextModelField"
     # endregion
 
     # region Misc Field Types
@@ -214,6 +215,7 @@ class FieldDescriptions:
     flux_redux_conditioning = "FLUX Redux conditioning tensor"
     vllm_model = "The VLLM model to use"
     flux_fill_conditioning = "FLUX Fill conditioning tensor"
+    flux_kontext_conditioning = "FLUX Kontext conditioning (reference image)"
 
 
 class ImageField(BaseModel):
@@ -290,6 +292,12 @@ class FluxFillConditioningField(BaseModel):
     mask: TensorField = Field(description="The FLUX Fill inpaint mask.")
 
 
+class FluxKontextConditioningField(BaseModel):
+    """A conditioning field for FLUX Kontext (reference image)."""
+
+    image: ImageField = Field(description="The Kontext reference image.")
+
+
 class SD3ConditioningField(BaseModel):
     """A conditioning tensor primitive value"""
 

invokeai/app/invocations/flux_denoise.py

@@ -16,13 +16,12 @@ from invokeai.app.invocations.fields import (
     FieldDescriptions,
     FluxConditioningField,
     FluxFillConditioningField,
+    FluxKontextConditioningField,
     FluxReduxConditioningField,
     ImageField,
     Input,
     InputField,
     LatentsField,
-    WithBoard,
-    WithMetadata,
 )
 from invokeai.app.invocations.flux_controlnet import FluxControlNetField
 from invokeai.app.invocations.flux_vae_encode import FluxVaeEncodeInvocation
@@ -34,6 +33,7 @@ from invokeai.backend.flux.controlnet.instantx_controlnet_flux import InstantXCo
 from invokeai.backend.flux.controlnet.xlabs_controlnet_flux import XLabsControlNetFlux
 from invokeai.backend.flux.denoise import denoise
 from invokeai.backend.flux.extensions.instantx_controlnet_extension import InstantXControlNetExtension
+from invokeai.backend.flux.extensions.kontext_extension import KontextExtension
 from invokeai.backend.flux.extensions.regional_prompting_extension import RegionalPromptingExtension
 from invokeai.backend.flux.extensions.xlabs_controlnet_extension import XLabsControlNetExtension
 from invokeai.backend.flux.extensions.xlabs_ip_adapter_extension import XLabsIPAdapterExtension
@@ -63,9 +63,9 @@ from invokeai.backend.util.devices import TorchDevice
     title="FLUX Denoise",
     tags=["image", "flux"],
     category="image",
-    version="3.3.0",
+    version="4.0.0",
 )
-class FluxDenoiseInvocation(BaseInvocation, WithMetadata, WithBoard):
+class FluxDenoiseInvocation(BaseInvocation):
     """Run denoising process with a FLUX transformer model."""
 
     # If latents is provided, this means we are doing image-to-image.
@@ -145,11 +145,20 @@ class FluxDenoiseInvocation(BaseInvocation, WithMetadata, WithBoard):
         description=FieldDescriptions.vae,
         input=Input.Connection,
     )
+    # This node accepts a images for features like FLUX Fill, ControlNet, and Kontext, but needs to operate on them in
+    # latent space. We'll run the VAE to encode them in this node instead of requiring the user to run the VAE in
+    # upstream nodes.
 
     ip_adapter: IPAdapterField | list[IPAdapterField] | None = InputField(
         description=FieldDescriptions.ip_adapter, title="IP-Adapter", default=None, input=Input.Connection
     )
 
+    kontext_conditioning: Optional[FluxKontextConditioningField] = InputField(
+        default=None,
+        description="FLUX Kontext conditioning (reference image).",
+        input=Input.Connection,
+    )
+
     @torch.no_grad()
     def invoke(self, context: InvocationContext) -> LatentsOutput:
         latents = self._run_diffusion(context)
@@ -376,6 +385,27 @@ class FluxDenoiseInvocation(BaseInvocation, WithMetadata, WithBoard):
                 dtype=inference_dtype,
             )
 
+            kontext_extension = None
+            if self.kontext_conditioning is not None:
+                if not self.controlnet_vae:
+                    raise ValueError("A VAE (e.g., controlnet_vae) must be provided to use Kontext conditioning.")
+
+                kontext_extension = KontextExtension(
+                    context=context,
+                    kontext_conditioning=self.kontext_conditioning,
+                    vae_field=self.controlnet_vae,
+                    device=TorchDevice.choose_torch_device(),
+                    dtype=inference_dtype,
+                )
+
+            # Prepare Kontext conditioning if provided
+            img_cond_seq = None
+            img_cond_seq_ids = None
+            if kontext_extension is not None:
+                # Ensure batch sizes match
+                kontext_extension.ensure_batch_size(x.shape[0])
+                img_cond_seq, img_cond_seq_ids = kontext_extension.kontext_latents, kontext_extension.kontext_ids
+
             x = denoise(
                 model=transformer,
                 img=x,
@@ -391,6 +421,8 @@ class FluxDenoiseInvocation(BaseInvocation, WithMetadata, WithBoard):
                 pos_ip_adapter_extensions=pos_ip_adapter_extensions,
                 neg_ip_adapter_extensions=neg_ip_adapter_extensions,
                 img_cond=img_cond,
+                img_cond_seq=img_cond_seq,
+                img_cond_seq_ids=img_cond_seq_ids,
             )
 
         x = unpack(x.float(), self.height, self.width)
@@ -865,7 +897,10 @@ class FluxDenoiseInvocation(BaseInvocation, WithMetadata, WithBoard):
 
     def _build_step_callback(self, context: InvocationContext) -> Callable[[PipelineIntermediateState], None]:
         def step_callback(state: PipelineIntermediateState) -> None:
-            state.latents = unpack(state.latents.float(), self.height, self.width).squeeze()
+            # The denoise function now handles Kontext conditioning correctly,
+            # so we don't need to slice the latents here
+            latents = state.latents.float()
+            state.latents = unpack(latents, self.height, self.width).squeeze()
             context.util.flux_step_callback(state)
 
         return step_callback

invokeai/app/invocations/flux_kontext.py

@@ -0,0 +1,40 @@
+from invokeai.app.invocations.baseinvocation import (
+    BaseInvocation,
+    BaseInvocationOutput,
+    invocation,
+    invocation_output,
+)
+from invokeai.app.invocations.fields import (
+    FieldDescriptions,
+    FluxKontextConditioningField,
+    InputField,
+    OutputField,
+)
+from invokeai.app.invocations.primitives import ImageField
+from invokeai.app.services.shared.invocation_context import InvocationContext
+
+
+@invocation_output("flux_kontext_output")
+class FluxKontextOutput(BaseInvocationOutput):
+    """The conditioning output of a FLUX Kontext invocation."""
+
+    kontext_cond: FluxKontextConditioningField = OutputField(
+        description=FieldDescriptions.flux_kontext_conditioning, title="Kontext Conditioning"
+    )
+
+
+@invocation(
+    "flux_kontext",
+    title="Kontext Conditioning - FLUX",
+    tags=["conditioning", "kontext", "flux"],
+    category="conditioning",
+    version="1.0.0",
+)
+class FluxKontextInvocation(BaseInvocation):
+    """Prepares a reference image for FLUX Kontext conditioning."""
+
+    image: ImageField = InputField(description="The Kontext reference image.")
+
+    def invoke(self, context: InvocationContext) -> FluxKontextOutput:
+        """Packages the provided image into a Kontext conditioning field."""
+        return FluxKontextOutput(kontext_cond=FluxKontextConditioningField(image=self.image))

invokeai/app/invocations/flux_text_encoder.py

@@ -1,5 +1,5 @@
 from contextlib import ExitStack
-from typing import Iterator, Literal, Optional, Tuple
+from typing import Iterator, Literal, Optional, Tuple, Union
 
 import torch
 from transformers import CLIPTextModel, CLIPTokenizer, T5EncoderModel, T5Tokenizer, T5TokenizerFast
@@ -111,6 +111,9 @@ class FluxTextEncoderInvocation(BaseInvocation):
 
             t5_encoder = HFEncoder(t5_text_encoder, t5_tokenizer, False, self.t5_max_seq_len)
 
+            if context.config.get().log_tokenization:
+                self._log_t5_tokenization(context, t5_tokenizer)
+
             context.util.signal_progress("Running T5 encoder")
             prompt_embeds = t5_encoder(prompt)
 
@@ -151,6 +154,9 @@ class FluxTextEncoderInvocation(BaseInvocation):
 
             clip_encoder = HFEncoder(clip_text_encoder, clip_tokenizer, True, 77)
 
+            if context.config.get().log_tokenization:
+                self._log_clip_tokenization(context, clip_tokenizer)
+
             context.util.signal_progress("Running CLIP encoder")
             pooled_prompt_embeds = clip_encoder(prompt)
 
@@ -170,3 +176,88 @@ class FluxTextEncoderInvocation(BaseInvocation):
             assert isinstance(lora_info.model, ModelPatchRaw)
             yield (lora_info.model, lora.weight)
             del lora_info
+
+    def _log_t5_tokenization(
+        self,
+        context: InvocationContext,
+        tokenizer: Union[T5Tokenizer, T5TokenizerFast],
+    ) -> None:
+        """Logs the tokenization of a prompt for a T5-based model like FLUX."""
+
+        # Tokenize the prompt using the same parameters as the model's text encoder.
+        # T5 tokenizers add an EOS token (</s>) and then pad to max_length.
+        tokenized_output = tokenizer(
+            self.prompt,
+            padding="max_length",
+            max_length=self.t5_max_seq_len,
+            truncation=True,
+            add_special_tokens=True,  # This is important for T5 to add the EOS token.
+            return_tensors="pt",
+        )
+
+        input_ids = tokenized_output.input_ids[0]
+        tokens = tokenizer.convert_ids_to_tokens(input_ids)
+
+        # The T5 tokenizer uses a space-like character ' ' (U+2581) to denote spaces.
+        # We'll replace it with a regular space for readability.
+        tokens = [t.replace("\u2581", " ") for t in tokens]
+
+        tokenized_str = ""
+        used_tokens = 0
+        for token in tokens:
+            if token == tokenizer.eos_token:
+                tokenized_str += f"\x1b[0;31m{token}\x1b[0m"  # Red for EOS
+                used_tokens += 1
+            elif token == tokenizer.pad_token:
+                # tokenized_str += f"\x1b[0;34m{token}\x1b[0m"  # Blue for PAD
+                continue
+            else:
+                color = (used_tokens % 6) + 1  # Cycle through 6 colors
+                tokenized_str += f"\x1b[0;3{color}m{token}\x1b[0m"
+                used_tokens += 1
+
+        context.logger.info(f">> [T5 TOKENLOG] Tokens ({used_tokens}/{self.t5_max_seq_len}):")
+        context.logger.info(f"{tokenized_str}\x1b[0m")
+
+    def _log_clip_tokenization(
+        self,
+        context: InvocationContext,
+        tokenizer: CLIPTokenizer,
+    ) -> None:
+        """Logs the tokenization of a prompt for a CLIP-based model."""
+        max_length = tokenizer.model_max_length
+
+        tokenized_output = tokenizer(
+            self.prompt,
+            padding="max_length",
+            max_length=max_length,
+            truncation=True,
+            return_tensors="pt",
+        )
+
+        input_ids = tokenized_output.input_ids[0]
+        attention_mask = tokenized_output.attention_mask[0]
+        tokens = tokenizer.convert_ids_to_tokens(input_ids)
+
+        # The CLIP tokenizer uses '</w>' to denote spaces.
+        # We'll replace it with a regular space for readability.
+        tokens = [t.replace("</w>", " ") for t in tokens]
+
+        tokenized_str = ""
+        used_tokens = 0
+        for i, token in enumerate(tokens):
+            if attention_mask[i] == 0:
+                # Do not log padding tokens.
+                continue
+
+            if token == tokenizer.bos_token:
+                tokenized_str += f"\x1b[0;32m{token}\x1b[0m"  # Green for BOS
+            elif token == tokenizer.eos_token:
+                tokenized_str += f"\x1b[0;31m{token}\x1b[0m"  # Red for EOS
+            else:
+                color = (used_tokens % 6) + 1  # Cycle through 6 colors
+                tokenized_str += f"\x1b[0;3{color}m{token}\x1b[0m"
+            used_tokens += 1
+
+        context.logger.info(f">> [CLIP TOKENLOG] Tokens ({used_tokens}/{max_length}):")
+        context.logger.info(f"{tokenized_str}\x1b[0m")

invokeai/app/services/image_records/image_records_base.py

@@ -5,6 +5,7 @@ from typing import Optional
 from invokeai.app.invocations.fields import MetadataField
 from invokeai.app.services.image_records.image_records_common import (
     ImageCategory,
+    ImageNamesResult,
     ImageRecord,
     ImageRecordChanges,
     ResourceOrigin,
@@ -97,3 +98,17 @@ class ImageRecordStorageBase(ABC):
     def get_most_recent_image_for_board(self, board_id: str) -> Optional[ImageRecord]:
         """Gets the most recent image for a board."""
         pass
+
+    @abstractmethod
+    def get_image_names(
+        self,
+        starred_first: bool = True,
+        order_dir: SQLiteDirection = SQLiteDirection.Descending,
+        image_origin: Optional[ResourceOrigin] = None,
+        categories: Optional[list[ImageCategory]] = None,
+        is_intermediate: Optional[bool] = None,
+        board_id: Optional[str] = None,
+        search_term: Optional[str] = None,
+    ) -> ImageNamesResult:
+        """Gets ordered list of image names with metadata for optimistic updates."""
+        pass

invokeai/app/services/image_records/image_records_common.py

@@ -3,7 +3,7 @@ import datetime
 from enum import Enum
 from typing import Optional, Union
 
-from pydantic import Field, StrictBool, StrictStr
+from pydantic import BaseModel, Field, StrictBool, StrictStr
 
 from invokeai.app.util.metaenum import MetaEnum
 from invokeai.app.util.misc import get_iso_timestamp
@@ -207,3 +207,16 @@ def deserialize_image_record(image_dict: dict) -> ImageRecord:
         starred=starred,
         has_workflow=has_workflow,
     )
+
+
+class ImageCollectionCounts(BaseModel):
+    starred_count: int = Field(description="The number of starred images in the collection.")
+    unstarred_count: int = Field(description="The number of unstarred images in the collection.")
+
+
+class ImageNamesResult(BaseModel):
+    """Response containing ordered image names with metadata for optimistic updates."""
+
+    image_names: list[str] = Field(description="Ordered list of image names")
+    starred_count: int = Field(description="Number of starred images (when starred_first=True)")
+    total_count: int = Field(description="Total number of images matching the query")

invokeai/app/services/image_records/image_records_sqlite.py

@@ -7,6 +7,7 @@ from invokeai.app.services.image_records.image_records_base import ImageRecordSt
 from invokeai.app.services.image_records.image_records_common import (
     IMAGE_DTO_COLS,
     ImageCategory,
+    ImageNamesResult,
     ImageRecord,
     ImageRecordChanges,
     ImageRecordDeleteException,
@@ -386,3 +387,96 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
             return None
 
         return deserialize_image_record(dict(result))
+
+    def get_image_names(
+        self,
+        starred_first: bool = True,
+        order_dir: SQLiteDirection = SQLiteDirection.Descending,
+        image_origin: Optional[ResourceOrigin] = None,
+        categories: Optional[list[ImageCategory]] = None,
+        is_intermediate: Optional[bool] = None,
+        board_id: Optional[str] = None,
+        search_term: Optional[str] = None,
+    ) -> ImageNamesResult:
+        cursor = self._conn.cursor()
+
+        # Build query conditions (reused for both starred count and image names queries)
+        query_conditions = ""
+        query_params: list[Union[int, str, bool]] = []
+
+        if image_origin is not None:
+            query_conditions += """--sql
+            AND images.image_origin = ?
+            """
+            query_params.append(image_origin.value)
+
+        if categories is not None:
+            category_strings = [c.value for c in set(categories)]
+            placeholders = ",".join("?" * len(category_strings))
+            query_conditions += f"""--sql
+            AND images.image_category IN ( {placeholders} )
+            """
+            for c in category_strings:
+                query_params.append(c)
+
+        if is_intermediate is not None:
+            query_conditions += """--sql
+            AND images.is_intermediate = ?
+            """
+            query_params.append(is_intermediate)
+
+        if board_id == "none":
+            query_conditions += """--sql
+            AND board_images.board_id IS NULL
+            """
+        elif board_id is not None:
+            query_conditions += """--sql
+            AND board_images.board_id = ?
+            """
+            query_params.append(board_id)
+
+        if search_term:
+            query_conditions += """--sql
+            AND (
+                images.metadata LIKE ?
+                OR images.created_at LIKE ?
+            )
+            """
+            query_params.append(f"%{search_term.lower()}%")
+            query_params.append(f"%{search_term.lower()}%")
+
+        # Get starred count if starred_first is enabled
+        starred_count = 0
+        if starred_first:
+            starred_count_query = f"""--sql
+            SELECT COUNT(*)
+            FROM images
+            LEFT JOIN board_images ON board_images.image_name = images.image_name
+            WHERE images.starred = TRUE AND (1=1{query_conditions})
+            """
+            cursor.execute(starred_count_query, query_params)
+            starred_count = cast(int, cursor.fetchone()[0])
+
+        # Get all image names with proper ordering
+        if starred_first:
+            names_query = f"""--sql
+            SELECT images.image_name
+            FROM images
+            LEFT JOIN board_images ON board_images.image_name = images.image_name
+            WHERE 1=1{query_conditions}
+            ORDER BY images.starred DESC, images.created_at {order_dir.value}
+            """
+        else:
+            names_query = f"""--sql
+            SELECT images.image_name
+            FROM images
+            LEFT JOIN board_images ON board_images.image_name = images.image_name
+            WHERE 1=1{query_conditions}
+            ORDER BY images.created_at {order_dir.value}
+            """
+
+        cursor.execute(names_query, query_params)
+        result = cast(list[sqlite3.Row], cursor.fetchall())
+        image_names = [row[0] for row in result]
+
+        return ImageNamesResult(image_names=image_names, starred_count=starred_count, total_count=len(image_names))

invokeai/app/services/images/images_base.py

@@ -6,6 +6,7 @@ from PIL.Image import Image as PILImageType
 from invokeai.app.invocations.fields import MetadataField
 from invokeai.app.services.image_records.image_records_common import (
     ImageCategory,
+    ImageNamesResult,
     ImageRecord,
     ImageRecordChanges,
     ResourceOrigin,
@@ -125,7 +126,7 @@ class ImageServiceABC(ABC):
         board_id: Optional[str] = None,
         search_term: Optional[str] = None,
     ) -> OffsetPaginatedResults[ImageDTO]:
-        """Gets a paginated list of image DTOs."""
+        """Gets a paginated list of image DTOs with starred images first when starred_first=True."""
         pass
 
     @abstractmethod
@@ -147,3 +148,17 @@ class ImageServiceABC(ABC):
     def delete_images_on_board(self, board_id: str):
         """Deletes all images on a board."""
         pass
+
+    @abstractmethod
+    def get_image_names(
+        self,
+        starred_first: bool = True,
+        order_dir: SQLiteDirection = SQLiteDirection.Descending,
+        image_origin: Optional[ResourceOrigin] = None,
+        categories: Optional[list[ImageCategory]] = None,
+        is_intermediate: Optional[bool] = None,
+        board_id: Optional[str] = None,
+        search_term: Optional[str] = None,
+    ) -> ImageNamesResult:
+        """Gets ordered list of image names with metadata for optimistic updates."""
+        pass

invokeai/app/services/images/images_common.py

@@ -1,6 +1,6 @@
 from typing import Optional
 
-from pydantic import Field
+from pydantic import BaseModel, Field
 
 from invokeai.app.services.image_records.image_records_common import ImageRecord
 from invokeai.app.util.model_exclude_null import BaseModelExcludeNull
@@ -39,3 +39,27 @@ def image_record_to_dto(
         thumbnail_url=thumbnail_url,
         board_id=board_id,
     )
+
+
+class ResultWithAffectedBoards(BaseModel):
+    affected_boards: list[str] = Field(description="The ids of boards affected by the delete operation")
+
+
+class DeleteImagesResult(ResultWithAffectedBoards):
+    deleted_images: list[str] = Field(description="The names of the images that were deleted")
+
+
+class StarredImagesResult(ResultWithAffectedBoards):
+    starred_images: list[str] = Field(description="The names of the images that were starred")
+
+
+class UnstarredImagesResult(ResultWithAffectedBoards):
+    unstarred_images: list[str] = Field(description="The names of the images that were unstarred")
+
+
+class AddImagesToBoardResult(ResultWithAffectedBoards):
+    added_images: list[str] = Field(description="The image names that were added to the board")
+
+
+class RemoveImagesFromBoardResult(ResultWithAffectedBoards):
+    removed_images: list[str] = Field(description="The image names that were removed from their board")

invokeai/app/services/images/images_default.py

@@ -10,6 +10,7 @@ from invokeai.app.services.image_files.image_files_common import (
 )
 from invokeai.app.services.image_records.image_records_common import (
     ImageCategory,
+    ImageNamesResult,
     ImageRecord,
     ImageRecordChanges,
     ImageRecordDeleteException,
@@ -309,3 +310,27 @@ class ImageService(ImageServiceABC):
         except Exception as e:
             self.__invoker.services.logger.error("Problem getting intermediates count")
             raise e
+
+    def get_image_names(
+        self,
+        starred_first: bool = True,
+        order_dir: SQLiteDirection = SQLiteDirection.Descending,
+        image_origin: Optional[ResourceOrigin] = None,
+        categories: Optional[list[ImageCategory]] = None,
+        is_intermediate: Optional[bool] = None,
+        board_id: Optional[str] = None,
+        search_term: Optional[str] = None,
+    ) -> ImageNamesResult:
+        try:
+            return self.__invoker.services.image_records.get_image_names(
+                starred_first=starred_first,
+                order_dir=order_dir,
+                image_origin=image_origin,
+                categories=categories,
+                is_intermediate=is_intermediate,
+                board_id=board_id,
+                search_term=search_term,
+            )
+        except Exception as e:
+            self.__invoker.services.logger.error("Problem getting image names")
+            raise e

invokeai/app/services/session_queue/session_queue_base.py

@@ -10,6 +10,8 @@ from invokeai.app.services.session_queue.session_queue_common import (
     CancelByDestinationResult,
     CancelByQueueIDResult,
     ClearResult,
+    DeleteAllExceptCurrentResult,
+    DeleteByDestinationResult,
     EnqueueBatchResult,
     IsEmptyResult,
     IsFullResult,
@@ -17,7 +19,6 @@ from invokeai.app.services.session_queue.session_queue_common import (
     RetryItemsResult,
     SessionQueueCountsByDestination,
     SessionQueueItem,
-    SessionQueueItemDTO,
     SessionQueueStatus,
 )
 from invokeai.app.services.shared.graph import GraphExecutionState
@@ -92,6 +93,11 @@ class SessionQueueBase(ABC):
         """Cancels a session queue item"""
         pass
 
+    @abstractmethod
+    def delete_queue_item(self, item_id: int) -> None:
+        """Deletes a session queue item"""
+        pass
+
     @abstractmethod
     def fail_queue_item(
         self, item_id: int, error_type: str, error_message: str, error_traceback: str
@@ -109,6 +115,11 @@ class SessionQueueBase(ABC):
         """Cancels all queue items with the given batch destination"""
         pass
 
+    @abstractmethod
+    def delete_by_destination(self, queue_id: str, destination: str) -> DeleteByDestinationResult:
+        """Deletes all queue items with the given batch destination"""
+        pass
+
     @abstractmethod
     def cancel_by_queue_id(self, queue_id: str) -> CancelByQueueIDResult:
         """Cancels all queue items with matching queue ID"""
@@ -119,6 +130,11 @@ class SessionQueueBase(ABC):
         """Cancels all queue items except in-progress items"""
         pass
 
+    @abstractmethod
+    def delete_all_except_current(self, queue_id: str) -> DeleteAllExceptCurrentResult:
+        """Deletes all queue items except in-progress items"""
+        pass
+
     @abstractmethod
     def list_queue_items(
         self,
@@ -127,10 +143,20 @@ class SessionQueueBase(ABC):
         priority: int,
         cursor: Optional[int] = None,
         status: Optional[QUEUE_ITEM_STATUS] = None,
-    ) -> CursorPaginatedResults[SessionQueueItemDTO]:
+        destination: Optional[str] = None,
+    ) -> CursorPaginatedResults[SessionQueueItem]:
         """Gets a page of session queue items"""
         pass
 
+    @abstractmethod
+    def list_all_queue_items(
+        self,
+        queue_id: str,
+        destination: Optional[str] = None,
+    ) -> list[SessionQueueItem]:
+        """Gets all queue items that match the given parameters"""
+        pass
+
     @abstractmethod
     def get_queue_item(self, item_id: int) -> SessionQueueItem:
         """Gets a session queue item by ID"""

invokeai/app/services/session_queue/session_queue_common.py

@@ -205,9 +205,10 @@ class FieldIdentifier(BaseModel):
     kind: Literal["input", "output"] = Field(description="The kind of field")
     node_id: str = Field(description="The ID of the node")
     field_name: str = Field(description="The name of the field")
+    user_label: str | None = Field(description="The user label of the field, if any")
 
 
-class SessionQueueItemWithoutGraph(BaseModel):
+class SessionQueueItem(BaseModel):
     """Session queue item without the full graph. Used for serialization."""
 
     item_id: int = Field(description="The identifier of the session queue item")
@@ -251,42 +252,7 @@ class SessionQueueItemWithoutGraph(BaseModel):
         default=None,
         description="The ID of the published workflow associated with this queue item",
     )
-    api_input_fields: Optional[list[FieldIdentifier]] = Field(
-        default=None, description="The fields that were used as input to the API"
-    )
-    api_output_fields: Optional[list[FieldIdentifier]] = Field(
-        default=None, description="The nodes that were used as output from the API"
-    )
     credits: Optional[float] = Field(default=None, description="The total credits used for this queue item")
-
-    @classmethod
-    def queue_item_dto_from_dict(cls, queue_item_dict: dict) -> "SessionQueueItemDTO":
-        # must parse these manually
-        queue_item_dict["field_values"] = get_field_values(queue_item_dict)
-        return SessionQueueItemDTO(**queue_item_dict)
-
-    model_config = ConfigDict(
-        json_schema_extra={
-            "required": [
-                "item_id",
-                "status",
-                "batch_id",
-                "queue_id",
-                "session_id",
-                "priority",
-                "session_id",
-                "created_at",
-                "updated_at",
-            ]
-        }
-    )
-
-
-class SessionQueueItemDTO(SessionQueueItemWithoutGraph):
-    pass
-
-
-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"
@@ -366,6 +332,7 @@ class EnqueueBatchResult(BaseModel):
     requested: int = Field(description="The total number of queue items requested to be enqueued")
     batch: Batch = Field(description="The batch that was enqueued")
     priority: int = Field(description="The priority of the enqueued batch")
+    item_ids: list[int] = Field(description="The IDs of the queue items that were enqueued")
 
 
 class RetryItemsResult(BaseModel):
@@ -397,6 +364,18 @@ class CancelByDestinationResult(CancelByBatchIDsResult):
     pass
 
 
+class DeleteByDestinationResult(BaseModel):
+    """Result of deleting by a destination"""
+
+    deleted: int = Field(..., description="Number of queue items deleted")
+
+
+class DeleteAllExceptCurrentResult(DeleteByDestinationResult):
+    """Result of deleting all except current"""
+
+    pass
+
+
 class CancelByQueueIDResult(CancelByBatchIDsResult):
     """Result of canceling by queue id"""
 

invokeai/app/services/session_queue/session_queue_sqlite.py

@@ -17,6 +17,8 @@ from invokeai.app.services.session_queue.session_queue_common import (
     CancelByDestinationResult,
     CancelByQueueIDResult,
     ClearResult,
+    DeleteAllExceptCurrentResult,
+    DeleteByDestinationResult,
     EnqueueBatchResult,
     IsEmptyResult,
     IsFullResult,
@@ -24,7 +26,6 @@ from invokeai.app.services.session_queue.session_queue_common import (
     RetryItemsResult,
     SessionQueueCountsByDestination,
     SessionQueueItem,
-    SessionQueueItemDTO,
     SessionQueueItemNotFoundError,
     SessionQueueStatus,
     ValueToInsertTuple,
@@ -46,10 +47,6 @@ class SqliteSessionQueue(SessionQueueBase):
             clear_result = self.clear(DEFAULT_QUEUE_ID)
             if clear_result.deleted > 0:
                 self.__invoker.services.logger.info(f"Cleared all {clear_result.deleted} queue items")
-        else:
-            prune_result = self.prune(DEFAULT_QUEUE_ID)
-            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__()
@@ -136,6 +133,18 @@ class SqliteSessionQueue(SessionQueueBase):
                     """,
                     values_to_insert,
                 )
+            with self._conn:
+                cursor = self._conn.cursor()
+                cursor.execute(
+                    """--sql
+                    SELECT item_id
+                    FROM session_queue
+                    WHERE batch_id = ?
+                    ORDER BY item_id DESC;
+                    """,
+                    (batch.batch_id,),
+                )
+                item_ids = [row[0] for row in cursor.fetchall()]
         except Exception:
             raise
         enqueue_result = EnqueueBatchResult(
@@ -144,6 +153,7 @@ class SqliteSessionQueue(SessionQueueBase):
             enqueued=enqueued_count,
             batch=batch,
             priority=priority,
+            item_ids=item_ids,
         )
         self.__invoker.services.events.emit_batch_enqueued(enqueue_result)
         return enqueue_result
@@ -217,6 +227,19 @@ class SqliteSessionQueue(SessionQueueBase):
     ) -> SessionQueueItem:
         try:
             cursor = self._conn.cursor()
+            cursor.execute(
+                """--sql
+                SELECT status FROM session_queue WHERE item_id = ?
+                """,
+                (item_id,),
+            )
+            row = cursor.fetchone()
+            if row is None:
+                raise SessionQueueItemNotFoundError(f"No queue item with id {item_id}")
+            current_status = row[0]
+            # Only update if not already finished (completed, failed or canceled)
+            if current_status in ("completed", "failed", "canceled"):
+                return self.get_queue_item(item_id)
             cursor.execute(
                 """--sql
                 UPDATE session_queue
@@ -328,6 +351,27 @@ class SqliteSessionQueue(SessionQueueBase):
         queue_item = self._set_queue_item_status(item_id=item_id, status="canceled")
         return queue_item
 
+    def delete_queue_item(self, item_id: int) -> None:
+        """Deletes a session queue item"""
+        try:
+            self.cancel_queue_item(item_id)
+        except SessionQueueItemNotFoundError:
+            pass
+        try:
+            cursor = self._conn.cursor()
+            cursor.execute(
+                """--sql
+                DELETE
+                FROM session_queue
+                WHERE item_id = ?
+                """,
+                (item_id,),
+            )
+            self._conn.commit()
+        except Exception:
+            self._conn.rollback()
+            raise
+
     def complete_queue_item(self, item_id: int) -> SessionQueueItem:
         queue_item = self._set_queue_item_status(item_id=item_id, status="completed")
         return queue_item
@@ -360,6 +404,8 @@ class SqliteSessionQueue(SessionQueueBase):
                   AND status != 'canceled'
                   AND status != 'completed'
                   AND status != 'failed'
+                  -- We will cancel the current item separately below - skip it here
+                  AND status != 'in_progress'
                 """
             params = [queue_id] + batch_ids
             cursor.execute(
@@ -398,6 +444,8 @@ class SqliteSessionQueue(SessionQueueBase):
                   AND status != 'canceled'
                   AND status != 'completed'
                   AND status != 'failed'
+                  -- We will cancel the current item separately below - skip it here
+                  AND status != 'in_progress'
                 """
             params = (queue_id, destination)
             cursor.execute(
@@ -425,6 +473,71 @@ class SqliteSessionQueue(SessionQueueBase):
             raise
         return CancelByDestinationResult(canceled=count)
 
+    def delete_by_destination(self, queue_id: str, destination: str) -> DeleteByDestinationResult:
+        try:
+            cursor = self._conn.cursor()
+            current_queue_item = self.get_current(queue_id)
+            if current_queue_item is not None and current_queue_item.destination == destination:
+                self.cancel_queue_item(current_queue_item.item_id)
+            params = (queue_id, destination)
+            cursor.execute(
+                """--sql
+                SELECT COUNT(*)
+                FROM session_queue
+                WHERE
+                  queue_id = ?
+                  AND destination = ?;
+                """,
+                params,
+            )
+            count = cursor.fetchone()[0]
+            cursor.execute(
+                """--sql
+                DELETE
+                FROM session_queue
+                WHERE
+                  queue_id = ?
+                  AND destination = ?;
+                """,
+                params,
+            )
+            self._conn.commit()
+        except Exception:
+            self._conn.rollback()
+            raise
+        return DeleteByDestinationResult(deleted=count)
+
+    def delete_all_except_current(self, queue_id: str) -> DeleteAllExceptCurrentResult:
+        try:
+            cursor = self._conn.cursor()
+            where = """--sql
+                WHERE
+                  queue_id == ?
+                  AND status == 'pending'
+                """
+            cursor.execute(
+                f"""--sql
+                SELECT COUNT(*)
+                FROM session_queue
+                {where};
+                """,
+                (queue_id,),
+            )
+            count = cursor.fetchone()[0]
+            cursor.execute(
+                f"""--sql
+                DELETE
+                FROM session_queue
+                {where};
+                """,
+                (queue_id,),
+            )
+            self._conn.commit()
+        except Exception:
+            self._conn.rollback()
+            raise
+        return DeleteAllExceptCurrentResult(deleted=count)
+
     def cancel_by_queue_id(self, queue_id: str) -> CancelByQueueIDResult:
         try:
             cursor = self._conn.cursor()
@@ -435,6 +548,8 @@ class SqliteSessionQueue(SessionQueueBase):
                   AND status != 'canceled'
                   AND status != 'completed'
                   AND status != 'failed'
+                  -- We will cancel the current item separately below - skip it here
+                  AND status != 'in_progress'
                 """
             params = [queue_id]
             cursor.execute(
@@ -455,12 +570,9 @@ class SqliteSessionQueue(SessionQueueBase):
                 tuple(params),
             )
             self._conn.commit()
+
             if current_queue_item is not None and current_queue_item.queue_id == queue_id:
-                batch_status = self.get_batch_status(queue_id=queue_id, batch_id=current_queue_item.batch_id)
-                queue_status = self.get_queue_status(queue_id=queue_id)
-                self.__invoker.services.events.emit_queue_item_status_changed(
-                    current_queue_item, batch_status, queue_status
-                )
+                self._set_queue_item_status(current_queue_item.item_id, "canceled")
         except Exception:
             self._conn.rollback()
             raise
@@ -540,26 +652,12 @@ class SqliteSessionQueue(SessionQueueBase):
         priority: int,
         cursor: Optional[int] = None,
         status: Optional[QUEUE_ITEM_STATUS] = None,
-    ) -> CursorPaginatedResults[SessionQueueItemDTO]:
+        destination: Optional[str] = None,
+    ) -> CursorPaginatedResults[SessionQueueItem]:
         cursor_ = self._conn.cursor()
         item_id = cursor
         query = """--sql
-            SELECT item_id,
-                status,
-                priority,
-                field_values,
-                error_type,
-                error_message,
-                error_traceback,
-                created_at,
-                updated_at,
-                completed_at,
-                started_at,
-                session_id,
-                batch_id,
-                queue_id,
-                origin,
-                destination
+            SELECT *
             FROM session_queue
             WHERE queue_id = ?
         """
@@ -571,6 +669,12 @@ class SqliteSessionQueue(SessionQueueBase):
                 """
             params.append(status)
 
+        if destination is not None:
+            query += """---sql
+                AND destination = ?
+            """
+            params.append(destination)
+
         if item_id is not None:
             query += """--sql
                 AND (priority < ?) OR (priority = ? AND item_id > ?)
@@ -586,7 +690,7 @@ class SqliteSessionQueue(SessionQueueBase):
         params.append(limit + 1)
         cursor_.execute(query, params)
         results = cast(list[sqlite3.Row], cursor_.fetchall())
-        items = [SessionQueueItemDTO.queue_item_dto_from_dict(dict(result)) for result in results]
+        items = [SessionQueueItem.queue_item_from_dict(dict(result)) for result in results]
         has_more = False
         if len(items) > limit:
             # remove the extra item
@@ -594,6 +698,37 @@ class SqliteSessionQueue(SessionQueueBase):
             has_more = True
         return CursorPaginatedResults(items=items, limit=limit, has_more=has_more)
 
+    def list_all_queue_items(
+        self,
+        queue_id: str,
+        destination: Optional[str] = None,
+    ) -> list[SessionQueueItem]:
+        """Gets all queue items that match the given parameters"""
+        cursor_ = self._conn.cursor()
+        query = """--sql
+            SELECT *
+            FROM session_queue
+            WHERE queue_id = ?
+        """
+        params: list[Union[str, int]] = [queue_id]
+
+        if destination is not None:
+            query += """---sql
+                AND destination = ?
+            """
+            params.append(destination)
+
+        query += """--sql
+            ORDER BY
+                priority DESC,
+                item_id ASC
+            ;
+            """
+        cursor_.execute(query, params)
+        results = cast(list[sqlite3.Row], cursor_.fetchall())
+        items = [SessionQueueItem.queue_item_from_dict(dict(result)) for result in results]
+        return items
+
     def get_queue_status(self, queue_id: str) -> SessionQueueStatus:
         cursor = self._conn.cursor()
         cursor.execute(
@@ -608,7 +743,7 @@ class SqliteSessionQueue(SessionQueueBase):
         counts_result = cast(list[sqlite3.Row], cursor.fetchall())
 
         current_item = self.get_current(queue_id=queue_id)
-        total = sum(row[1] for row in counts_result)
+        total = sum(row[1] or 0 for row in counts_result)
         counts: dict[str, int] = {row[0]: row[1] for row in counts_result}
         return SessionQueueStatus(
             queue_id=queue_id,
@@ -637,7 +772,7 @@ class SqliteSessionQueue(SessionQueueBase):
             (queue_id, batch_id),
         )
         result = cast(list[sqlite3.Row], cursor.fetchall())
-        total = sum(row[1] for row in result)
+        total = sum(row[1] or 0 for row in result)
         counts: dict[str, int] = {row[0]: row[1] for row in result}
         origin = result[0]["origin"] if result else None
         destination = result[0]["destination"] if result else None
@@ -669,7 +804,7 @@ class SqliteSessionQueue(SessionQueueBase):
         )
         counts_result = cast(list[sqlite3.Row], cursor.fetchall())
 
-        total = sum(row[1] for row in counts_result)
+        total = sum(row[1] or 0 for row in counts_result)
         counts: dict[str, int] = {row[0]: row[1] for row in counts_result}
 
         return SessionQueueCountsByDestination(

invokeai/app/services/shared/graph.py

@@ -2,11 +2,12 @@
 
 import copy
 import itertools
-from typing import Any, Optional, TypeVar, Union, get_args, get_origin, get_type_hints
+from typing import Any, Optional, TypeVar, Union, get_args, get_origin
 
 import networkx as nx
 from pydantic import (
     BaseModel,
+    ConfigDict,
     GetCoreSchemaHandler,
     GetJsonSchemaHandler,
     ValidationError,
@@ -57,17 +58,32 @@ class Edge(BaseModel):
 
 
 def get_output_field_type(node: BaseInvocation, field: str) -> Any:
-    node_type = type(node)
-    node_outputs = get_type_hints(node_type.get_output_annotation())
-    node_output_field = node_outputs.get(field) or None
-    return node_output_field
+    # TODO(psyche): This is awkward - if field_info is None, it means the field is not defined in the output, which
+    # really should raise. The consumers of this utility expect it to never raise, and return None instead. Fixing this
+    # would require some fairly significant changes and I don't want risk breaking anything.
+    try:
+        invocation_class = type(node)
+        invocation_output_class = invocation_class.get_output_annotation()
+        field_info = invocation_output_class.model_fields.get(field)
+        assert field_info is not None, f"Output field '{field}' not found in {invocation_output_class.get_type()}"
+        output_field_type = field_info.annotation
+        return output_field_type
+    except Exception:
+        return None
 
 
 def get_input_field_type(node: BaseInvocation, field: str) -> Any:
-    node_type = type(node)
-    node_inputs = get_type_hints(node_type)
-    node_input_field = node_inputs.get(field) or None
-    return node_input_field
+    # TODO(psyche): This is awkward - if field_info is None, it means the field is not defined in the output, which
+    # really should raise. The consumers of this utility expect it to never raise, and return None instead. Fixing this
+    # would require some fairly significant changes and I don't want risk breaking anything.
+    try:
+        invocation_class = type(node)
+        field_info = invocation_class.model_fields.get(field)
+        assert field_info is not None, f"Input field '{field}' not found in {invocation_class.get_type()}"
+        input_field_type = field_info.annotation
+        return input_field_type
+    except Exception:
+        return None
 
 
 def is_union_subtype(t1, t2):
@@ -787,6 +803,22 @@ class GraphExecutionState(BaseModel):
         default_factory=dict,
     )
 
+    model_config = ConfigDict(
+        json_schema_extra={
+            "required": [
+                "id",
+                "graph",
+                "execution_graph",
+                "executed",
+                "executed_history",
+                "results",
+                "errors",
+                "prepared_source_mapping",
+                "source_prepared_mapping",
+            ]
+        }
+    )
+
     @field_validator("graph")
     def graph_is_valid(cls, v: Graph):
         """Validates that the graph is valid"""
@@ -975,10 +1007,11 @@ class GraphExecutionState(BaseModel):
         new_node_ids = []
         if isinstance(next_node, CollectInvocation):
             # Collapse all iterator input mappings and create a single execution node for the collect invocation
-            all_iteration_mappings = list(
-                itertools.chain(*(((s, p) for p in self.source_prepared_mapping[s]) for s in next_node_parents))
-            )
-            # all_iteration_mappings = list(set(itertools.chain(*prepared_parent_mappings)))
+            all_iteration_mappings = []
+            for source_node_id in next_node_parents:
+                prepared_nodes = self.source_prepared_mapping[source_node_id]
+                all_iteration_mappings.extend([(source_node_id, p) for p in prepared_nodes])
+
             create_results = self._create_execution_node(next_node_id, all_iteration_mappings)
             if create_results is not None:
                 new_node_ids.extend(create_results)

invokeai/app/util/step_callback.py

@@ -123,7 +123,11 @@ def calc_percentage(intermediate_state: PipelineIntermediateState) -> float:
     if total_steps == 0:
         return 0.0
     if order == 2:
-        return floor(step / 2) / floor(total_steps / 2)
+        # Prevent division by zero when total_steps is 1 or 2
+        denominator = floor(total_steps / 2)
+        if denominator == 0:
+            return 0.0
+        return floor(step / 2) / denominator
     # order == 1
     return step / total_steps
 

invokeai/backend/flux/denoise.py

@@ -30,8 +30,11 @@ def denoise(
     controlnet_extensions: list[XLabsControlNetExtension | InstantXControlNetExtension],
     pos_ip_adapter_extensions: list[XLabsIPAdapterExtension],
     neg_ip_adapter_extensions: list[XLabsIPAdapterExtension],
-    # extra img tokens
+    # extra img tokens (channel-wise)
     img_cond: torch.Tensor | None,
+    # extra img tokens (sequence-wise) - for Kontext conditioning
+    img_cond_seq: torch.Tensor | None = None,
+    img_cond_seq_ids: torch.Tensor | None = None,
 ):
     # step 0 is the initial state
     total_steps = len(timesteps) - 1
@@ -46,6 +49,10 @@ def denoise(
     )
     # guidance_vec is ignored for schnell.
     guidance_vec = torch.full((img.shape[0],), guidance, device=img.device, dtype=img.dtype)
+
+    # Store original sequence length for slicing predictions
+    original_seq_len = img.shape[1]
+
     for step_index, (t_curr, t_prev) in tqdm(list(enumerate(zip(timesteps[:-1], timesteps[1:], strict=True)))):
         t_vec = torch.full((img.shape[0],), t_curr, dtype=img.dtype, device=img.device)
 
@@ -71,10 +78,26 @@ def denoise(
         # controlnet_residuals datastructure is efficient in that it likely contains multiple references to the same
         # tensors. Calculating the sum materializes each tensor into its own instance.
         merged_controlnet_residuals = sum_controlnet_flux_outputs(controlnet_residuals)
-        pred_img = torch.cat((img, img_cond), dim=-1) if img_cond is not None else img
+
+        # Prepare input for model - concatenate fresh each step
+        img_input = img
+        img_input_ids = img_ids
+
+        # Add channel-wise conditioning (for ControlNet, FLUX Fill, etc.)
+        if img_cond is not None:
+            img_input = torch.cat((img_input, img_cond), dim=-1)
+
+        # Add sequence-wise conditioning (for Kontext)
+        if img_cond_seq is not None:
+            assert img_cond_seq_ids is not None, (
+                "You need to provide either both or neither of the sequence conditioning"
+            )
+            img_input = torch.cat((img_input, img_cond_seq), dim=1)
+            img_input_ids = torch.cat((img_input_ids, img_cond_seq_ids), dim=1)
+
         pred = model(
-            img=pred_img,
-            img_ids=img_ids,
+            img=img_input,
+            img_ids=img_input_ids,
             txt=pos_regional_prompting_extension.regional_text_conditioning.t5_embeddings,
             txt_ids=pos_regional_prompting_extension.regional_text_conditioning.t5_txt_ids,
             y=pos_regional_prompting_extension.regional_text_conditioning.clip_embeddings,
@@ -88,6 +111,10 @@ def denoise(
             regional_prompting_extension=pos_regional_prompting_extension,
         )
 
+        # Slice prediction to only include the main image tokens
+        if img_input_ids is not None:
+            pred = pred[:, :original_seq_len]
+
         step_cfg_scale = cfg_scale[step_index]
 
         # If step_cfg_scale, is 1.0, then we don't need to run the negative prediction.

invokeai/backend/flux/extensions/kontext_extension.py

@@ -0,0 +1,149 @@
+import einops
+import numpy as np
+import torch
+from einops import repeat
+from PIL import Image
+
+from invokeai.app.invocations.fields import FluxKontextConditioningField
+from invokeai.app.invocations.flux_vae_encode import FluxVaeEncodeInvocation
+from invokeai.app.invocations.model import VAEField
+from invokeai.app.services.shared.invocation_context import InvocationContext
+from invokeai.backend.flux.sampling_utils import pack
+from invokeai.backend.flux.util import PREFERED_KONTEXT_RESOLUTIONS
+
+
+def generate_img_ids_with_offset(
+    latent_height: int,
+    latent_width: int,
+    batch_size: int,
+    device: torch.device,
+    dtype: torch.dtype,
+    idx_offset: int = 0,
+) -> torch.Tensor:
+    """Generate tensor of image position ids with an optional offset.
+
+    Args:
+        latent_height (int): Height of image in latent space (after packing, this becomes h//2).
+        latent_width (int): Width of image in latent space (after packing, this becomes w//2).
+        batch_size (int): Number of images in the batch.
+        device (torch.device): Device to create tensors on.
+        dtype (torch.dtype): Data type for the tensors.
+        idx_offset (int): Offset to add to the first dimension of the image ids.
+
+    Returns:
+        torch.Tensor: Image position ids with shape [batch_size, (latent_height//2 * latent_width//2), 3].
+    """
+
+    if device.type == "mps":
+        orig_dtype = dtype
+        dtype = torch.float16
+
+    # After packing, the spatial dimensions are halved due to the 2x2 patch structure
+    packed_height = latent_height // 2
+    packed_width = latent_width // 2
+
+    # Create base tensor for position IDs with shape [packed_height, packed_width, 3]
+    # The 3 channels represent: [batch_offset, y_position, x_position]
+    img_ids = torch.zeros(packed_height, packed_width, 3, device=device, dtype=dtype)
+
+    # Set the batch offset for all positions
+    img_ids[..., 0] = idx_offset
+
+    # Create y-coordinate indices (vertical positions)
+    y_indices = torch.arange(packed_height, device=device, dtype=dtype)
+    # Broadcast y_indices to match the spatial dimensions [packed_height, 1]
+    img_ids[..., 1] = y_indices[:, None]
+
+    # Create x-coordinate indices (horizontal positions)
+    x_indices = torch.arange(packed_width, device=device, dtype=dtype)
+    # Broadcast x_indices to match the spatial dimensions [1, packed_width]
+    img_ids[..., 2] = x_indices[None, :]
+
+    # Expand to include batch dimension: [batch_size, (packed_height * packed_width), 3]
+    img_ids = repeat(img_ids, "h w c -> b (h w) c", b=batch_size)
+
+    if device.type == "mps":
+        img_ids = img_ids.to(orig_dtype)
+
+    return img_ids
+
+
+class KontextExtension:
+    """Applies FLUX Kontext (reference image) conditioning."""
+
+    def __init__(
+        self,
+        kontext_conditioning: FluxKontextConditioningField,
+        context: InvocationContext,
+        vae_field: VAEField,
+        device: torch.device,
+        dtype: torch.dtype,
+    ):
+        """
+        Initializes the KontextExtension, pre-processing the reference image
+        into latents and positional IDs.
+        """
+        self._context = context
+        self._device = device
+        self._dtype = dtype
+        self._vae_field = vae_field
+        self.kontext_conditioning = kontext_conditioning
+
+        # Pre-process and cache the kontext latents and ids upon initialization.
+        self.kontext_latents, self.kontext_ids = self._prepare_kontext()
+
+    def _prepare_kontext(self) -> tuple[torch.Tensor, torch.Tensor]:
+        """Encodes the reference image and prepares its latents and IDs."""
+        image = self._context.images.get_pil(self.kontext_conditioning.image.image_name)
+
+        # Calculate aspect ratio of input image
+        width, height = image.size
+        aspect_ratio = width / height
+
+        # Find the closest preferred resolution by aspect ratio
+        _, target_width, target_height = min(
+            ((abs(aspect_ratio - w / h), w, h) for w, h in PREFERED_KONTEXT_RESOLUTIONS), key=lambda x: x[0]
+        )
+
+        # Apply BFL's scaling formula
+        # This ensures compatibility with the model's training
+        scaled_width = 2 * int(target_width / 16)
+        scaled_height = 2 * int(target_height / 16)
+
+        # Resize to the exact resolution used during training
+        image = image.convert("RGB")
+        final_width = 8 * scaled_width
+        final_height = 8 * scaled_height
+        image = image.resize((final_width, final_height), Image.Resampling.LANCZOS)
+
+        # Convert to tensor with same normalization as BFL
+        image_np = np.array(image)
+        image_tensor = torch.from_numpy(image_np).float() / 127.5 - 1.0
+        image_tensor = einops.rearrange(image_tensor, "h w c -> 1 c h w")
+        image_tensor = image_tensor.to(self._device)
+
+        # Continue with VAE encoding
+        vae_info = self._context.models.load(self._vae_field.vae)
+        kontext_latents_unpacked = FluxVaeEncodeInvocation.vae_encode(vae_info=vae_info, image_tensor=image_tensor)
+
+        # Extract tensor dimensions
+        batch_size, _, latent_height, latent_width = kontext_latents_unpacked.shape
+
+        # Pack the latents and generate IDs
+        kontext_latents_packed = pack(kontext_latents_unpacked).to(self._device, self._dtype)
+        kontext_ids = generate_img_ids_with_offset(
+            latent_height=latent_height,
+            latent_width=latent_width,
+            batch_size=batch_size,
+            device=self._device,
+            dtype=self._dtype,
+            idx_offset=1,
+        )
+
+        return kontext_latents_packed, kontext_ids
+
+    def ensure_batch_size(self, target_batch_size: int) -> None:
+        """Ensures the kontext latents and IDs match the target batch size by repeating if necessary."""
+        if self.kontext_latents.shape[0] != target_batch_size:
+            self.kontext_latents = self.kontext_latents.repeat(target_batch_size, 1, 1)
+            self.kontext_ids = self.kontext_ids.repeat(target_batch_size, 1, 1)

invokeai/backend/flux/sampling_utils.py

@@ -174,11 +174,13 @@ def generate_img_ids(h: int, w: int, batch_size: int, device: torch.device, dtyp
         dtype = torch.float16
 
     img_ids = torch.zeros(h // 2, w // 2, 3, device=device, dtype=dtype)
+    # Set batch offset to 0 for main image tokens
+    img_ids[..., 0] = 0
     img_ids[..., 1] = img_ids[..., 1] + torch.arange(h // 2, device=device, dtype=dtype)[:, None]
     img_ids[..., 2] = img_ids[..., 2] + torch.arange(w // 2, device=device, dtype=dtype)[None, :]
     img_ids = repeat(img_ids, "h w c -> b (h w) c", b=batch_size)
 
     if device.type == "mps":
-        img_ids.to(orig_dtype)
+        img_ids = img_ids.to(orig_dtype)
 
     return img_ids

invokeai/backend/flux/util.py

@@ -18,6 +18,29 @@ class ModelSpec:
     repo_ae: str | None
 
 
+# Preferred resolutions for Kontext models to avoid tiling artifacts
+# These are the specific resolutions the model was trained on
+PREFERED_KONTEXT_RESOLUTIONS = [
+    (672, 1568),
+    (688, 1504),
+    (720, 1456),
+    (752, 1392),
+    (800, 1328),
+    (832, 1248),
+    (880, 1184),
+    (944, 1104),
+    (1024, 1024),
+    (1104, 944),
+    (1184, 880),
+    (1248, 832),
+    (1328, 800),
+    (1392, 752),
+    (1456, 720),
+    (1504, 688),
+    (1568, 672),
+]
+
+
 max_seq_lengths: Dict[str, Literal[256, 512]] = {
     "flux-dev": 512,
     "flux-dev-fill": 512,

invokeai/backend/model_manager/config.py

@@ -37,6 +37,7 @@ from invokeai.app.util.misc import uuid_string
 from invokeai.backend.model_hash.hash_validator import validate_hash
 from invokeai.backend.model_hash.model_hash import HASHING_ALGORITHMS
 from invokeai.backend.model_manager.model_on_disk import ModelOnDisk
+from invokeai.backend.model_manager.omi import flux_dev_1_lora, stable_diffusion_xl_1_lora
 from invokeai.backend.model_manager.taxonomy import (
     AnyVariant,
     BaseModelType,
@@ -334,6 +335,36 @@ class T5EncoderBnbQuantizedLlmInt8bConfig(T5EncoderConfigBase, LegacyProbeMixin,
     format: Literal[ModelFormat.BnbQuantizedLlmInt8b] = ModelFormat.BnbQuantizedLlmInt8b
 
 
+class LoRAOmiConfig(LoRAConfigBase, ModelConfigBase):
+    format: Literal[ModelFormat.OMI] = ModelFormat.OMI
+
+    @classmethod
+    def matches(cls, mod: ModelOnDisk) -> bool:
+        if mod.path.is_dir():
+            return False
+
+        metadata = mod.metadata()
+        return (
+            metadata.get("modelspec.sai_model_spec")
+            and metadata.get("ot_branch") == "omi_format"
+            and metadata["modelspec.architecture"].split("/")[1].lower() == "lora"
+        )
+
+    @classmethod
+    def parse(cls, mod: ModelOnDisk) -> dict[str, Any]:
+        metadata = mod.metadata()
+        architecture = metadata["modelspec.architecture"]
+
+        if architecture == stable_diffusion_xl_1_lora:
+            base = BaseModelType.StableDiffusionXL
+        elif architecture == flux_dev_1_lora:
+            base = BaseModelType.Flux
+        else:
+            raise InvalidModelConfigException(f"Unrecognised/unsupported architecture for OMI LoRA: {architecture}")
+
+        return {"base": base}
+
+
 class LoRALyCORISConfig(LoRAConfigBase, ModelConfigBase):
     """Model config for LoRA/Lycoris models."""
 
@@ -350,7 +381,7 @@ class LoRALyCORISConfig(LoRAConfigBase, ModelConfigBase):
 
         state_dict = mod.load_state_dict()
         for key in state_dict.keys():
-            if type(key) is int:
+            if isinstance(key, int):
                 continue
 
             if key.startswith(("lora_te_", "lora_unet_", "lora_te1_", "lora_te2_", "lora_transformer_")):
@@ -668,6 +699,7 @@ AnyModelConfig = Annotated[
         Annotated[ControlNetDiffusersConfig, ControlNetDiffusersConfig.get_tag()],
         Annotated[ControlNetCheckpointConfig, ControlNetCheckpointConfig.get_tag()],
         Annotated[LoRALyCORISConfig, LoRALyCORISConfig.get_tag()],
+        Annotated[LoRAOmiConfig, LoRAOmiConfig.get_tag()],
         Annotated[ControlLoRALyCORISConfig, ControlLoRALyCORISConfig.get_tag()],
         Annotated[ControlLoRADiffusersConfig, ControlLoRADiffusersConfig.get_tag()],
         Annotated[LoRADiffusersConfig, LoRADiffusersConfig.get_tag()],

invokeai/backend/model_manager/load/model_loaders/flux.py

@@ -7,7 +7,14 @@ from typing import Optional
 import accelerate
 import torch
 from safetensors.torch import load_file
-from transformers import AutoConfig, AutoModelForTextEncoding, CLIPTextModel, CLIPTokenizer, T5EncoderModel, T5Tokenizer
+from transformers import (
+    AutoConfig,
+    AutoModelForTextEncoding,
+    CLIPTextModel,
+    CLIPTokenizer,
+    T5EncoderModel,
+    T5TokenizerFast,
+)
 
 from invokeai.app.services.config.config_default import get_config
 from invokeai.backend.flux.controlnet.instantx_controlnet_flux import InstantXControlNetFlux
@@ -139,7 +146,7 @@ class BnbQuantizedLlmInt8bCheckpointModel(ModelLoader):
             )
         match submodel_type:
             case SubModelType.Tokenizer2 | SubModelType.Tokenizer3:
-                return T5Tokenizer.from_pretrained(Path(config.path) / "tokenizer_2", max_length=512)
+                return T5TokenizerFast.from_pretrained(Path(config.path) / "tokenizer_2", max_length=512)
             case SubModelType.TextEncoder2 | SubModelType.TextEncoder3:
                 te2_model_path = Path(config.path) / "text_encoder_2"
                 model_config = AutoConfig.from_pretrained(te2_model_path)
@@ -183,7 +190,7 @@ class T5EncoderCheckpointModel(ModelLoader):
 
         match submodel_type:
             case SubModelType.Tokenizer2 | SubModelType.Tokenizer3:
-                return T5Tokenizer.from_pretrained(Path(config.path) / "tokenizer_2", max_length=512)
+                return T5TokenizerFast.from_pretrained(Path(config.path) / "tokenizer_2", max_length=512)
             case SubModelType.TextEncoder2 | SubModelType.TextEncoder3:
                 return T5EncoderModel.from_pretrained(
                     Path(config.path) / "text_encoder_2", torch_dtype="auto", low_cpu_mem_usage=True

invokeai/backend/model_manager/load/model_loaders/lora.py

@@ -13,6 +13,7 @@ from invokeai.backend.model_manager.config import AnyModelConfig
 from invokeai.backend.model_manager.load.load_default import ModelLoader
 from invokeai.backend.model_manager.load.model_cache.model_cache import ModelCache
 from invokeai.backend.model_manager.load.model_loader_registry import ModelLoaderRegistry
+from invokeai.backend.model_manager.omi.omi import convert_from_omi
 from invokeai.backend.model_manager.taxonomy import (
     AnyModel,
     BaseModelType,
@@ -43,6 +44,8 @@ from invokeai.backend.patches.lora_conversions.sd_lora_conversion_utils import l
 from invokeai.backend.patches.lora_conversions.sdxl_lora_conversion_utils import convert_sdxl_keys_to_diffusers_format
 
 
+@ModelLoaderRegistry.register(base=BaseModelType.Flux, type=ModelType.LoRA, format=ModelFormat.OMI)
+@ModelLoaderRegistry.register(base=BaseModelType.StableDiffusionXL, type=ModelType.LoRA, format=ModelFormat.OMI)
 @ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.LoRA, format=ModelFormat.Diffusers)
 @ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.LoRA, format=ModelFormat.LyCORIS)
 @ModelLoaderRegistry.register(base=BaseModelType.Flux, type=ModelType.ControlLoRa, format=ModelFormat.LyCORIS)
@@ -77,12 +80,23 @@ class LoRALoader(ModelLoader):
         else:
             state_dict = torch.load(model_path, map_location="cpu")
 
+        # Strip 'bundle_emb' keys - these are unused and currently cause downstream errors.
+        # To revisit later to determine if they're needed/useful.
+        state_dict = {k: v for k, v in state_dict.items() if not k.startswith("bundle_emb")}
+
+        # At the time of writing, we support the OMI standard for base models Flux and SDXL
+        if config.format == ModelFormat.OMI and self._model_base in [
+            BaseModelType.StableDiffusionXL,
+            BaseModelType.Flux,
+        ]:
+            state_dict = convert_from_omi(state_dict, config.base)  # type: ignore
+
         # Apply state_dict key conversions, if necessary.
         if self._model_base == BaseModelType.StableDiffusionXL:
             state_dict = convert_sdxl_keys_to_diffusers_format(state_dict)
             model = lora_model_from_sd_state_dict(state_dict=state_dict)
         elif self._model_base == BaseModelType.Flux:
-            if config.format == ModelFormat.Diffusers:
+            if config.format in [ModelFormat.Diffusers, ModelFormat.OMI]:
                 # HACK(ryand): We set alpha=None for diffusers PEFT format models. These models are typically
                 # distributed as a single file without the associated metadata containing the alpha value. We chose
                 # alpha=None, because this is treated as alpha=rank internally in `LoRALayerBase.scale()`. alpha=rank
@@ -99,7 +113,7 @@ class LoRALoader(ModelLoader):
                 elif is_state_dict_likely_in_flux_aitoolkit_format(state_dict=state_dict):
                     model = lora_model_from_flux_aitoolkit_state_dict(state_dict=state_dict)
                 else:
-                    raise ValueError(f"LoRA model is in unsupported FLUX format: {config.format}")
+                    raise ValueError("LoRA model is in unsupported FLUX format")
             else:
                 raise ValueError(f"LoRA model is in unsupported FLUX format: {config.format}")
         elif self._model_base in [BaseModelType.StableDiffusion1, BaseModelType.StableDiffusion2]:

invokeai/backend/model_manager/omi/__init__.py

@@ -0,0 +1,7 @@
+from invokeai.backend.model_manager.omi.omi import convert_from_omi
+from invokeai.backend.model_manager.omi.vendor.model_spec.architecture import (
+    flux_dev_1_lora,
+    stable_diffusion_xl_1_lora,
+)
+
+__all__ = ["flux_dev_1_lora", "stable_diffusion_xl_1_lora", "convert_from_omi"]

invokeai/backend/model_manager/omi/omi.py

@@ -0,0 +1,21 @@
+from invokeai.backend.model_manager.model_on_disk import StateDict
+from invokeai.backend.model_manager.omi.vendor.convert.lora import (
+    convert_flux_lora as omi_flux,
+)
+from invokeai.backend.model_manager.omi.vendor.convert.lora import (
+    convert_lora_util as lora_util,
+)
+from invokeai.backend.model_manager.omi.vendor.convert.lora import (
+    convert_sdxl_lora as omi_sdxl,
+)
+from invokeai.backend.model_manager.taxonomy import BaseModelType
+
+
+def convert_from_omi(weights_sd: StateDict, base: BaseModelType):
+    keyset = {
+        BaseModelType.Flux: omi_flux.convert_flux_lora_key_sets(),
+        BaseModelType.StableDiffusionXL: omi_sdxl.convert_sdxl_lora_key_sets(),
+    }[base]
+    source = "omi"
+    target = "legacy_diffusers"
+    return lora_util.__convert(weights_sd, keyset, source, target)  # type: ignore

invokeai/backend/model_manager/omi/vendor/convert/lora/convert_clip.py

@@ -0,0 +1,20 @@
+from invokeai.backend.model_manager.omi.vendor.convert.lora.convert_lora_util import (
+    LoraConversionKeySet,
+    map_prefix_range,
+)
+
+
+def map_clip(key_prefix: LoraConversionKeySet) -> list[LoraConversionKeySet]:
+    keys = []
+
+    keys += [LoraConversionKeySet("text_projection", "text_projection", parent=key_prefix)]
+
+    for k in map_prefix_range("text_model.encoder.layers", "text_model.encoder.layers", parent=key_prefix):
+        keys += [LoraConversionKeySet("mlp.fc1", "mlp.fc1", parent=k)]
+        keys += [LoraConversionKeySet("mlp.fc2", "mlp.fc2", parent=k)]
+        keys += [LoraConversionKeySet("self_attn.k_proj", "self_attn.k_proj", parent=k)]
+        keys += [LoraConversionKeySet("self_attn.out_proj", "self_attn.out_proj", parent=k)]
+        keys += [LoraConversionKeySet("self_attn.q_proj", "self_attn.q_proj", parent=k)]
+        keys += [LoraConversionKeySet("self_attn.v_proj", "self_attn.v_proj", parent=k)]
+
+    return keys

invokeai/backend/model_manager/omi/vendor/convert/lora/convert_flux_lora.py

@@ -0,0 +1,84 @@
+from invokeai.backend.model_manager.omi.vendor.convert.lora.convert_clip import map_clip
+from invokeai.backend.model_manager.omi.vendor.convert.lora.convert_lora_util import (
+    LoraConversionKeySet,
+    map_prefix_range,
+)
+from invokeai.backend.model_manager.omi.vendor.convert.lora.convert_t5 import map_t5
+
+
+def __map_double_transformer_block(key_prefix: LoraConversionKeySet) -> list[LoraConversionKeySet]:
+    keys = []
+
+    keys += [LoraConversionKeySet("img_attn.qkv.0", "attn.to_q", parent=key_prefix)]
+    keys += [LoraConversionKeySet("img_attn.qkv.1", "attn.to_k", parent=key_prefix)]
+    keys += [LoraConversionKeySet("img_attn.qkv.2", "attn.to_v", parent=key_prefix)]
+
+    keys += [LoraConversionKeySet("txt_attn.qkv.0", "attn.add_q_proj", parent=key_prefix)]
+    keys += [LoraConversionKeySet("txt_attn.qkv.1", "attn.add_k_proj", parent=key_prefix)]
+    keys += [LoraConversionKeySet("txt_attn.qkv.2", "attn.add_v_proj", parent=key_prefix)]
+
+    keys += [LoraConversionKeySet("img_attn.proj", "attn.to_out.0", parent=key_prefix)]
+    keys += [LoraConversionKeySet("img_mlp.0", "ff.net.0.proj", parent=key_prefix)]
+    keys += [LoraConversionKeySet("img_mlp.2", "ff.net.2", parent=key_prefix)]
+    keys += [LoraConversionKeySet("img_mod.lin", "norm1.linear", parent=key_prefix)]
+
+    keys += [LoraConversionKeySet("txt_attn.proj", "attn.to_add_out", parent=key_prefix)]
+    keys += [LoraConversionKeySet("txt_mlp.0", "ff_context.net.0.proj", parent=key_prefix)]
+    keys += [LoraConversionKeySet("txt_mlp.2", "ff_context.net.2", parent=key_prefix)]
+    keys += [LoraConversionKeySet("txt_mod.lin", "norm1_context.linear", parent=key_prefix)]
+
+    return keys
+
+
+def __map_single_transformer_block(key_prefix: LoraConversionKeySet) -> list[LoraConversionKeySet]:
+    keys = []
+
+    keys += [LoraConversionKeySet("linear1.0", "attn.to_q", parent=key_prefix)]
+    keys += [LoraConversionKeySet("linear1.1", "attn.to_k", parent=key_prefix)]
+    keys += [LoraConversionKeySet("linear1.2", "attn.to_v", parent=key_prefix)]
+    keys += [LoraConversionKeySet("linear1.3", "proj_mlp", parent=key_prefix)]
+
+    keys += [LoraConversionKeySet("linear2", "proj_out", parent=key_prefix)]
+    keys += [LoraConversionKeySet("modulation.lin", "norm.linear", parent=key_prefix)]
+
+    return keys
+
+
+def __map_transformer(key_prefix: LoraConversionKeySet) -> list[LoraConversionKeySet]:
+    keys = []
+
+    keys += [LoraConversionKeySet("txt_in", "context_embedder", parent=key_prefix)]
+    keys += [
+        LoraConversionKeySet("final_layer.adaLN_modulation.1", "norm_out.linear", parent=key_prefix, swap_chunks=True)
+    ]
+    keys += [LoraConversionKeySet("final_layer.linear", "proj_out", parent=key_prefix)]
+    keys += [
+        LoraConversionKeySet("guidance_in.in_layer", "time_text_embed.guidance_embedder.linear_1", parent=key_prefix)
+    ]
+    keys += [
+        LoraConversionKeySet("guidance_in.out_layer", "time_text_embed.guidance_embedder.linear_2", parent=key_prefix)
+    ]
+    keys += [LoraConversionKeySet("vector_in.in_layer", "time_text_embed.text_embedder.linear_1", parent=key_prefix)]
+    keys += [LoraConversionKeySet("vector_in.out_layer", "time_text_embed.text_embedder.linear_2", parent=key_prefix)]
+    keys += [LoraConversionKeySet("time_in.in_layer", "time_text_embed.timestep_embedder.linear_1", parent=key_prefix)]
+    keys += [LoraConversionKeySet("time_in.out_layer", "time_text_embed.timestep_embedder.linear_2", parent=key_prefix)]
+    keys += [LoraConversionKeySet("img_in.proj", "x_embedder", parent=key_prefix)]
+
+    for k in map_prefix_range("double_blocks", "transformer_blocks", parent=key_prefix):
+        keys += __map_double_transformer_block(k)
+
+    for k in map_prefix_range("single_blocks", "single_transformer_blocks", parent=key_prefix):
+        keys += __map_single_transformer_block(k)
+
+    return keys
+
+
+def convert_flux_lora_key_sets() -> list[LoraConversionKeySet]:
+    keys = []
+
+    keys += [LoraConversionKeySet("bundle_emb", "bundle_emb")]
+    keys += __map_transformer(LoraConversionKeySet("transformer", "lora_transformer"))
+    keys += map_clip(LoraConversionKeySet("clip_l", "lora_te1"))
+    keys += map_t5(LoraConversionKeySet("t5", "lora_te2"))
+
+    return keys

invokeai/backend/model_manager/omi/vendor/convert/lora/convert_lora_util.py

@@ -0,0 +1,217 @@
+import torch
+from torch import Tensor
+from typing_extensions import Self
+
+
+class LoraConversionKeySet:
+    def __init__(
+        self,
+        omi_prefix: str,
+        diffusers_prefix: str,
+        legacy_diffusers_prefix: str | None = None,
+        parent: Self | None = None,
+        swap_chunks: bool = False,
+        filter_is_last: bool | None = None,
+        next_omi_prefix: str | None = None,
+        next_diffusers_prefix: str | None = None,
+    ):
+        if parent is not None:
+            self.omi_prefix = combine(parent.omi_prefix, omi_prefix)
+            self.diffusers_prefix = combine(parent.diffusers_prefix, diffusers_prefix)
+        else:
+            self.omi_prefix = omi_prefix
+            self.diffusers_prefix = diffusers_prefix
+
+        if legacy_diffusers_prefix is None:
+            self.legacy_diffusers_prefix = self.diffusers_prefix.replace(".", "_")
+        elif parent is not None:
+            self.legacy_diffusers_prefix = combine(parent.legacy_diffusers_prefix, legacy_diffusers_prefix).replace(
+                ".", "_"
+            )
+        else:
+            self.legacy_diffusers_prefix = legacy_diffusers_prefix
+
+        self.parent = parent
+        self.swap_chunks = swap_chunks
+        self.filter_is_last = filter_is_last
+        self.prefix = parent
+
+        if next_omi_prefix is None and parent is not None:
+            self.next_omi_prefix = parent.next_omi_prefix
+            self.next_diffusers_prefix = parent.next_diffusers_prefix
+            self.next_legacy_diffusers_prefix = parent.next_legacy_diffusers_prefix
+        elif next_omi_prefix is not None and parent is not None:
+            self.next_omi_prefix = combine(parent.omi_prefix, next_omi_prefix)
+            self.next_diffusers_prefix = combine(parent.diffusers_prefix, next_diffusers_prefix)
+            self.next_legacy_diffusers_prefix = combine(parent.legacy_diffusers_prefix, next_diffusers_prefix).replace(
+                ".", "_"
+            )
+        elif next_omi_prefix is not None and parent is None:
+            self.next_omi_prefix = next_omi_prefix
+            self.next_diffusers_prefix = next_diffusers_prefix
+            self.next_legacy_diffusers_prefix = next_diffusers_prefix.replace(".", "_")
+        else:
+            self.next_omi_prefix = None
+            self.next_diffusers_prefix = None
+            self.next_legacy_diffusers_prefix = None
+
+    def __get_omi(self, in_prefix: str, key: str) -> str:
+        return self.omi_prefix + key.removeprefix(in_prefix)
+
+    def __get_diffusers(self, in_prefix: str, key: str) -> str:
+        return self.diffusers_prefix + key.removeprefix(in_prefix)
+
+    def __get_legacy_diffusers(self, in_prefix: str, key: str) -> str:
+        key = self.legacy_diffusers_prefix + key.removeprefix(in_prefix)
+
+        suffix = key[key.rfind(".") :]
+        if suffix not in [".alpha", ".dora_scale"]:  # some keys only have a single . in the suffix
+            suffix = key[key.removesuffix(suffix).rfind(".") :]
+        key = key.removesuffix(suffix)
+
+        return key.replace(".", "_") + suffix
+
+    def get_key(self, in_prefix: str, key: str, target: str) -> str:
+        if target == "omi":
+            return self.__get_omi(in_prefix, key)
+        elif target == "diffusers":
+            return self.__get_diffusers(in_prefix, key)
+        elif target == "legacy_diffusers":
+            return self.__get_legacy_diffusers(in_prefix, key)
+        return key
+
+    def __str__(self) -> str:
+        return f"omi: {self.omi_prefix}, diffusers: {self.diffusers_prefix}, legacy: {self.legacy_diffusers_prefix}"
+
+
+def combine(left: str, right: str) -> str:
+    left = left.rstrip(".")
+    right = right.lstrip(".")
+    if left == "" or left is None:
+        return right
+    elif right == "" or right is None:
+        return left
+    else:
+        return left + "." + right
+
+
+def map_prefix_range(
+    omi_prefix: str,
+    diffusers_prefix: str,
+    parent: LoraConversionKeySet,
+) -> list[LoraConversionKeySet]:
+    # 100 should be a safe upper bound. increase if it's not enough in the future
+    return [
+        LoraConversionKeySet(
+            omi_prefix=f"{omi_prefix}.{i}",
+            diffusers_prefix=f"{diffusers_prefix}.{i}",
+            parent=parent,
+            next_omi_prefix=f"{omi_prefix}.{i + 1}",
+            next_diffusers_prefix=f"{diffusers_prefix}.{i + 1}",
+        )
+        for i in range(100)
+    ]
+
+
+def __convert(
+    state_dict: dict[str, Tensor],
+    key_sets: list[LoraConversionKeySet],
+    source: str,
+    target: str,
+) -> dict[str, Tensor]:
+    out_states = {}
+
+    if source == target:
+        return dict(state_dict)
+
+    # TODO: maybe replace with a non O(n^2) algorithm
+    for key, tensor in state_dict.items():
+        for key_set in key_sets:
+            in_prefix = ""
+
+            if source == "omi":
+                in_prefix = key_set.omi_prefix
+            elif source == "diffusers":
+                in_prefix = key_set.diffusers_prefix
+            elif source == "legacy_diffusers":
+                in_prefix = key_set.legacy_diffusers_prefix
+
+            if not key.startswith(in_prefix):
+                continue
+
+            if key_set.filter_is_last is not None:
+                next_prefix = None
+                if source == "omi":
+                    next_prefix = key_set.next_omi_prefix
+                elif source == "diffusers":
+                    next_prefix = key_set.next_diffusers_prefix
+                elif source == "legacy_diffusers":
+                    next_prefix = key_set.next_legacy_diffusers_prefix
+
+                is_last = not any(k.startswith(next_prefix) for k in state_dict)
+                if key_set.filter_is_last != is_last:
+                    continue
+
+            name = key_set.get_key(in_prefix, key, target)
+
+            can_swap_chunks = target == "omi" or source == "omi"
+            if key_set.swap_chunks and name.endswith(".lora_up.weight") and can_swap_chunks:
+                chunk_0, chunk_1 = tensor.chunk(2, dim=0)
+                tensor = torch.cat([chunk_1, chunk_0], dim=0)
+
+            out_states[name] = tensor
+
+            break  # only map the first matching key set
+
+    return out_states
+
+
+def __detect_source(
+    state_dict: dict[str, Tensor],
+    key_sets: list[LoraConversionKeySet],
+) -> str:
+    omi_count = 0
+    diffusers_count = 0
+    legacy_diffusers_count = 0
+
+    for key in state_dict:
+        for key_set in key_sets:
+            if key.startswith(key_set.omi_prefix):
+                omi_count += 1
+            if key.startswith(key_set.diffusers_prefix):
+                diffusers_count += 1
+            if key.startswith(key_set.legacy_diffusers_prefix):
+                legacy_diffusers_count += 1
+
+    if omi_count > diffusers_count and omi_count > legacy_diffusers_count:
+        return "omi"
+    if diffusers_count > omi_count and diffusers_count > legacy_diffusers_count:
+        return "diffusers"
+    if legacy_diffusers_count > omi_count and legacy_diffusers_count > diffusers_count:
+        return "legacy_diffusers"
+
+    return ""
+
+
+def convert_to_omi(
+    state_dict: dict[str, Tensor],
+    key_sets: list[LoraConversionKeySet],
+) -> dict[str, Tensor]:
+    source = __detect_source(state_dict, key_sets)
+    return __convert(state_dict, key_sets, source, "omi")
+
+
+def convert_to_diffusers(
+    state_dict: dict[str, Tensor],
+    key_sets: list[LoraConversionKeySet],
+) -> dict[str, Tensor]:
+    source = __detect_source(state_dict, key_sets)
+    return __convert(state_dict, key_sets, source, "diffusers")
+
+
+def convert_to_legacy_diffusers(
+    state_dict: dict[str, Tensor],
+    key_sets: list[LoraConversionKeySet],
+) -> dict[str, Tensor]:
+    source = __detect_source(state_dict, key_sets)
+    return __convert(state_dict, key_sets, source, "legacy_diffusers")

invokeai/backend/model_manager/omi/vendor/convert/lora/convert_sdxl_lora.py

@@ -0,0 +1,125 @@
+from invokeai.backend.model_manager.omi.vendor.convert.lora.convert_clip import map_clip
+from invokeai.backend.model_manager.omi.vendor.convert.lora.convert_lora_util import (
+    LoraConversionKeySet,
+    map_prefix_range,
+)
+
+
+def __map_unet_resnet_block(key_prefix: LoraConversionKeySet) -> list[LoraConversionKeySet]:
+    keys = []
+
+    keys += [LoraConversionKeySet("emb_layers.1", "time_emb_proj", parent=key_prefix)]
+    keys += [LoraConversionKeySet("in_layers.2", "conv1", parent=key_prefix)]
+    keys += [LoraConversionKeySet("out_layers.3", "conv2", parent=key_prefix)]
+    keys += [LoraConversionKeySet("skip_connection", "conv_shortcut", parent=key_prefix)]
+
+    return keys
+
+
+def __map_unet_attention_block(key_prefix: LoraConversionKeySet) -> list[LoraConversionKeySet]:
+    keys = []
+
+    keys += [LoraConversionKeySet("proj_in", "proj_in", parent=key_prefix)]
+    keys += [LoraConversionKeySet("proj_out", "proj_out", parent=key_prefix)]
+    for k in map_prefix_range("transformer_blocks", "transformer_blocks", parent=key_prefix):
+        keys += [LoraConversionKeySet("attn1.to_q", "attn1.to_q", parent=k)]
+        keys += [LoraConversionKeySet("attn1.to_k", "attn1.to_k", parent=k)]
+        keys += [LoraConversionKeySet("attn1.to_v", "attn1.to_v", parent=k)]
+        keys += [LoraConversionKeySet("attn1.to_out.0", "attn1.to_out.0", parent=k)]
+        keys += [LoraConversionKeySet("attn2.to_q", "attn2.to_q", parent=k)]
+        keys += [LoraConversionKeySet("attn2.to_k", "attn2.to_k", parent=k)]
+        keys += [LoraConversionKeySet("attn2.to_v", "attn2.to_v", parent=k)]
+        keys += [LoraConversionKeySet("attn2.to_out.0", "attn2.to_out.0", parent=k)]
+        keys += [LoraConversionKeySet("ff.net.0.proj", "ff.net.0.proj", parent=k)]
+        keys += [LoraConversionKeySet("ff.net.2", "ff.net.2", parent=k)]
+
+    return keys
+
+
+def __map_unet_down_blocks(key_prefix: LoraConversionKeySet) -> list[LoraConversionKeySet]:
+    keys = []
+
+    keys += __map_unet_resnet_block(LoraConversionKeySet("1.0", "0.resnets.0", parent=key_prefix))
+    keys += __map_unet_resnet_block(LoraConversionKeySet("2.0", "0.resnets.1", parent=key_prefix))
+    keys += [LoraConversionKeySet("3.0.op", "0.downsamplers.0.conv", parent=key_prefix)]
+
+    keys += __map_unet_resnet_block(LoraConversionKeySet("4.0", "1.resnets.0", parent=key_prefix))
+    keys += __map_unet_attention_block(LoraConversionKeySet("4.1", "1.attentions.0", parent=key_prefix))
+    keys += __map_unet_resnet_block(LoraConversionKeySet("5.0", "1.resnets.1", parent=key_prefix))
+    keys += __map_unet_attention_block(LoraConversionKeySet("5.1", "1.attentions.1", parent=key_prefix))
+    keys += [LoraConversionKeySet("6.0.op", "1.downsamplers.0.conv", parent=key_prefix)]
+
+    keys += __map_unet_resnet_block(LoraConversionKeySet("7.0", "2.resnets.0", parent=key_prefix))
+    keys += __map_unet_attention_block(LoraConversionKeySet("7.1", "2.attentions.0", parent=key_prefix))
+    keys += __map_unet_resnet_block(LoraConversionKeySet("8.0", "2.resnets.1", parent=key_prefix))
+    keys += __map_unet_attention_block(LoraConversionKeySet("8.1", "2.attentions.1", parent=key_prefix))
+
+    return keys
+
+
+def __map_unet_mid_block(key_prefix: LoraConversionKeySet) -> list[LoraConversionKeySet]:
+    keys = []
+
+    keys += __map_unet_resnet_block(LoraConversionKeySet("0", "resnets.0", parent=key_prefix))
+    keys += __map_unet_attention_block(LoraConversionKeySet("1", "attentions.0", parent=key_prefix))
+    keys += __map_unet_resnet_block(LoraConversionKeySet("2", "resnets.1", parent=key_prefix))
+
+    return keys
+
+
+def __map_unet_up_block(key_prefix: LoraConversionKeySet) -> list[LoraConversionKeySet]:
+    keys = []
+
+    keys += __map_unet_resnet_block(LoraConversionKeySet("0.0", "0.resnets.0", parent=key_prefix))
+    keys += __map_unet_attention_block(LoraConversionKeySet("0.1", "0.attentions.0", parent=key_prefix))
+    keys += __map_unet_resnet_block(LoraConversionKeySet("1.0", "0.resnets.1", parent=key_prefix))
+    keys += __map_unet_attention_block(LoraConversionKeySet("1.1", "0.attentions.1", parent=key_prefix))
+    keys += __map_unet_resnet_block(LoraConversionKeySet("2.0", "0.resnets.2", parent=key_prefix))
+    keys += __map_unet_attention_block(LoraConversionKeySet("2.1", "0.attentions.2", parent=key_prefix))
+    keys += [LoraConversionKeySet("2.2.conv", "0.upsamplers.0.conv", parent=key_prefix)]
+
+    keys += __map_unet_resnet_block(LoraConversionKeySet("3.0", "1.resnets.0", parent=key_prefix))
+    keys += __map_unet_attention_block(LoraConversionKeySet("3.1", "1.attentions.0", parent=key_prefix))
+    keys += __map_unet_resnet_block(LoraConversionKeySet("4.0", "1.resnets.1", parent=key_prefix))
+    keys += __map_unet_attention_block(LoraConversionKeySet("4.1", "1.attentions.1", parent=key_prefix))
+    keys += __map_unet_resnet_block(LoraConversionKeySet("5.0", "1.resnets.2", parent=key_prefix))
+    keys += __map_unet_attention_block(LoraConversionKeySet("5.1", "1.attentions.2", parent=key_prefix))
+    keys += [LoraConversionKeySet("5.2.conv", "1.upsamplers.0.conv", parent=key_prefix)]
+
+    keys += __map_unet_resnet_block(LoraConversionKeySet("6.0", "2.resnets.0", parent=key_prefix))
+    keys += __map_unet_resnet_block(LoraConversionKeySet("7.0", "2.resnets.1", parent=key_prefix))
+    keys += __map_unet_resnet_block(LoraConversionKeySet("8.0", "2.resnets.2", parent=key_prefix))
+
+    return keys
+
+
+def __map_unet(key_prefix: LoraConversionKeySet) -> list[LoraConversionKeySet]:
+    keys = []
+
+    keys += [LoraConversionKeySet("input_blocks.0.0", "conv_in", parent=key_prefix)]
+
+    keys += [LoraConversionKeySet("time_embed.0", "time_embedding.linear_1", parent=key_prefix)]
+    keys += [LoraConversionKeySet("time_embed.2", "time_embedding.linear_2", parent=key_prefix)]
+
+    keys += [LoraConversionKeySet("label_emb.0.0", "add_embedding.linear_1", parent=key_prefix)]
+    keys += [LoraConversionKeySet("label_emb.0.2", "add_embedding.linear_2", parent=key_prefix)]
+
+    keys += __map_unet_down_blocks(LoraConversionKeySet("input_blocks", "down_blocks", parent=key_prefix))
+    keys += __map_unet_mid_block(LoraConversionKeySet("middle_block", "mid_block", parent=key_prefix))
+    keys += __map_unet_up_block(LoraConversionKeySet("output_blocks", "up_blocks", parent=key_prefix))
+
+    keys += [LoraConversionKeySet("out.0", "conv_norm_out", parent=key_prefix)]
+    keys += [LoraConversionKeySet("out.2", "conv_out", parent=key_prefix)]
+
+    return keys
+
+
+def convert_sdxl_lora_key_sets() -> list[LoraConversionKeySet]:
+    keys = []
+
+    keys += [LoraConversionKeySet("bundle_emb", "bundle_emb")]
+    keys += __map_unet(LoraConversionKeySet("unet", "lora_unet"))
+    keys += map_clip(LoraConversionKeySet("clip_l", "lora_te1"))
+    keys += map_clip(LoraConversionKeySet("clip_g", "lora_te2"))
+
+    return keys

invokeai/backend/model_manager/omi/vendor/convert/lora/convert_t5.py

@@ -0,0 +1,19 @@
+from invokeai.backend.model_manager.omi.vendor.convert.lora.convert_lora_util import (
+    LoraConversionKeySet,
+    map_prefix_range,
+)
+
+
+def map_t5(key_prefix: LoraConversionKeySet) -> list[LoraConversionKeySet]:
+    keys = []
+
+    for k in map_prefix_range("encoder.block", "encoder.block", parent=key_prefix):
+        keys += [LoraConversionKeySet("layer.0.SelfAttention.k", "layer.0.SelfAttention.k", parent=k)]
+        keys += [LoraConversionKeySet("layer.0.SelfAttention.o", "layer.0.SelfAttention.o", parent=k)]
+        keys += [LoraConversionKeySet("layer.0.SelfAttention.q", "layer.0.SelfAttention.q", parent=k)]
+        keys += [LoraConversionKeySet("layer.0.SelfAttention.v", "layer.0.SelfAttention.v", parent=k)]
+        keys += [LoraConversionKeySet("layer.1.DenseReluDense.wi_0", "layer.1.DenseReluDense.wi_0", parent=k)]
+        keys += [LoraConversionKeySet("layer.1.DenseReluDense.wi_1", "layer.1.DenseReluDense.wi_1", parent=k)]
+        keys += [LoraConversionKeySet("layer.1.DenseReluDense.wo", "layer.1.DenseReluDense.wo", parent=k)]
+
+    return keys

invokeai/backend/model_manager/omi/vendor/model_spec/architecture.py

@@ -0,0 +1,31 @@
+stable_diffusion_1_lora = "stable-diffusion-v1/lora"
+stable_diffusion_1_inpainting_lora = "stable-diffusion-v1-inpainting/lora"
+
+stable_diffusion_2_512_lora = "stable-diffusion-v2-512/lora"
+stable_diffusion_2_768_v_lora = "stable-diffusion-v2-768-v/lora"
+stable_diffusion_2_depth_lora = "stable-diffusion-v2-depth/lora"
+stable_diffusion_2_inpainting_lora = "stable-diffusion-v2-inpainting/lora"
+
+stable_diffusion_3_medium_lora = "stable-diffusion-v3-medium/lora"
+stable_diffusion_35_medium_lora = "stable-diffusion-v3.5-medium/lora"
+stable_diffusion_35_large_lora = "stable-diffusion-v3.5-large/lora"
+
+stable_diffusion_xl_1_lora = "stable-diffusion-xl-v1-base/lora"
+stable_diffusion_xl_1_inpainting_lora = "stable-diffusion-xl-v1-base-inpainting/lora"
+
+wuerstchen_2_lora = "wuerstchen-v2-prior/lora"
+stable_cascade_1_stage_a_lora = "stable-cascade-v1-stage-a/lora"
+stable_cascade_1_stage_b_lora = "stable-cascade-v1-stage-b/lora"
+stable_cascade_1_stage_c_lora = "stable-cascade-v1-stage-c/lora"
+
+pixart_alpha_lora = "pixart-alpha/lora"
+pixart_sigma_lora = "pixart-sigma/lora"
+
+flux_dev_1_lora = "Flux.1-dev/lora"
+flux_fill_dev_1_lora = "Flux.1-fill-dev/lora"
+
+sana_lora = "sana/lora"
+
+hunyuan_video_lora = "hunyuan-video/lora"
+
+hi_dream_i1_lora = "hidream-i1/lora"

invokeai/backend/model_manager/starter_models.py

@@ -23,7 +23,7 @@ class StarterModel(StarterModelWithoutDependencies):
     dependencies: Optional[list[StarterModelWithoutDependencies]] = None
 
 
-class StarterModelBundles(BaseModel):
+class StarterModelBundle(BaseModel):
     name: str
     models: list[StarterModel]
 
@@ -109,7 +109,7 @@ flux_vae = StarterModel(
 
 # region: Main
 flux_schnell_quantized = StarterModel(
-    name="FLUX Schnell (Quantized)",
+    name="FLUX.1 schnell (quantized)",
     base=BaseModelType.Flux,
     source="InvokeAI/flux_schnell::transformer/bnb_nf4/flux1-schnell-bnb_nf4.safetensors",
     description="FLUX schnell transformer quantized to bitsandbytes NF4 format. Total size with dependencies: ~12GB",
@@ -117,7 +117,7 @@ flux_schnell_quantized = StarterModel(
     dependencies=[t5_8b_quantized_encoder, flux_vae, clip_l_encoder],
 )
 flux_dev_quantized = StarterModel(
-    name="FLUX Dev (Quantized)",
+    name="FLUX.1 dev (quantized)",
     base=BaseModelType.Flux,
     source="InvokeAI/flux_dev::transformer/bnb_nf4/flux1-dev-bnb_nf4.safetensors",
     description="FLUX dev transformer quantized to bitsandbytes NF4 format. Total size with dependencies: ~12GB",
@@ -125,7 +125,7 @@ flux_dev_quantized = StarterModel(
     dependencies=[t5_8b_quantized_encoder, flux_vae, clip_l_encoder],
 )
 flux_schnell = StarterModel(
-    name="FLUX Schnell",
+    name="FLUX.1 schnell",
     base=BaseModelType.Flux,
     source="InvokeAI/flux_schnell::transformer/base/flux1-schnell.safetensors",
     description="FLUX schnell transformer in bfloat16. Total size with dependencies: ~33GB",
@@ -133,13 +133,29 @@ flux_schnell = StarterModel(
     dependencies=[t5_base_encoder, flux_vae, clip_l_encoder],
 )
 flux_dev = StarterModel(
-    name="FLUX Dev",
+    name="FLUX.1 dev",
     base=BaseModelType.Flux,
     source="InvokeAI/flux_dev::transformer/base/flux1-dev.safetensors",
     description="FLUX dev transformer in bfloat16. Total size with dependencies: ~33GB",
     type=ModelType.Main,
     dependencies=[t5_base_encoder, flux_vae, clip_l_encoder],
 )
+flux_kontext = StarterModel(
+    name="FLUX.1 Kontext dev",
+    base=BaseModelType.Flux,
+    source="https://huggingface.co/black-forest-labs/FLUX.1-Kontext-dev/resolve/main/flux1-kontext-dev.safetensors",
+    description="FLUX.1 Kontext dev transformer in bfloat16. Total size with dependencies: ~33GB",
+    type=ModelType.Main,
+    dependencies=[t5_base_encoder, flux_vae, clip_l_encoder],
+)
+flux_kontext_quantized = StarterModel(
+    name="FLUX.1 Kontext dev (Quantized)",
+    base=BaseModelType.Flux,
+    source="https://huggingface.co/unsloth/FLUX.1-Kontext-dev-GGUF/resolve/main/flux1-kontext-dev-Q4_K_M.gguf",
+    description="FLUX.1 Kontext dev quantized (q4_k_m). Total size with dependencies: ~14GB",
+    type=ModelType.Main,
+    dependencies=[t5_8b_quantized_encoder, flux_vae, clip_l_encoder],
+)
 sd35_medium = StarterModel(
     name="SD3.5 Medium",
     base=BaseModelType.StableDiffusion3,
@@ -656,6 +672,7 @@ flux_fill = StarterModel(
 # List of starter models, displayed on the frontend.
 # The order/sort of this list is not changed by the frontend - set it how you want it here.
 STARTER_MODELS: list[StarterModel] = [
+    flux_kontext_quantized,
     flux_schnell_quantized,
     flux_dev_quantized,
     flux_schnell,
@@ -776,12 +793,13 @@ flux_bundle: list[StarterModel] = [
     flux_depth_control_lora,
     flux_redux,
     flux_fill,
+    flux_kontext_quantized,
 ]
 
-STARTER_BUNDLES: dict[str, list[StarterModel]] = {
-    BaseModelType.StableDiffusion1: sd1_bundle,
-    BaseModelType.StableDiffusionXL: sdxl_bundle,
-    BaseModelType.Flux: flux_bundle,
+STARTER_BUNDLES: dict[str, StarterModelBundle] = {
+    BaseModelType.StableDiffusion1: StarterModelBundle(name="Stable Diffusion 1.5", models=sd1_bundle),
+    BaseModelType.StableDiffusionXL: StarterModelBundle(name="SDXL", models=sdxl_bundle),
+    BaseModelType.Flux: StarterModelBundle(name="FLUX.1 dev", models=flux_bundle),
 }
 
 assert len(STARTER_MODELS) == len({m.source for m in STARTER_MODELS}), "Duplicate starter models"

invokeai/backend/model_manager/taxonomy.py

@@ -29,6 +29,7 @@ class BaseModelType(str, Enum):
     Imagen3 = "imagen3"
     Imagen4 = "imagen4"
     ChatGPT4o = "chatgpt-4o"
+    FluxKontext = "flux-kontext"
 
 
 class ModelType(str, Enum):
@@ -88,6 +89,7 @@ class ModelVariantType(str, Enum):
 class ModelFormat(str, Enum):
     """Storage format of model."""
 
+    OMI = "omi"
     Diffusers = "diffusers"
     Checkpoint = "checkpoint"
     LyCORIS = "lycoris"

invokeai/frontend/web/.eslintrc.js

@@ -9,13 +9,25 @@ module.exports = {
     // https://github.com/qdanik/eslint-plugin-path
     'path/no-relative-imports': ['error', { maxDepth: 0 }],
     // https://github.com/edvardchen/eslint-plugin-i18next/blob/HEAD/docs/rules/no-literal-string.md
-    'i18next/no-literal-string': 'error',
+    // TODO: ENABLE THIS RULE BEFORE v6.0.0
+    // 'i18next/no-literal-string': 'error',
     // https://eslint.org/docs/latest/rules/no-console
-    'no-console': 'error',
+    'no-console': 'warn',
     // https://eslint.org/docs/latest/rules/no-promise-executor-return
     'no-promise-executor-return': 'error',
     // https://eslint.org/docs/latest/rules/require-await
     'require-await': 'error',
+    // Restrict setActiveTab calls to only use-navigation-api.tsx
+    'no-restricted-syntax': [
+      'error',
+      {
+        selector: 'CallExpression[callee.name="setActiveTab"]',
+        message:
+          'setActiveTab() can only be called from use-navigation-api.tsx. Use navigationApi.switchToTab() instead.',
+      },
+    ],
+    // TODO: ENABLE THIS RULE BEFORE v6.0.0
+    'react/display-name': 'off',
     'no-restricted-properties': [
       'error',
       {
@@ -30,8 +42,38 @@ module.exports = {
           'The Clipboard API is not available by default in Firefox. Use the `useClipboard` hook instead, which wraps clipboard access to prevent errors.',
       },
     ],
+    'no-restricted-imports': [
+      'error',
+      {
+        paths: [
+          {
+            name: 'lodash-es',
+            importNames: ['isEqual'],
+            message: 'Please use objectEquals from @observ33r/object-equals instead.',
+          },
+          {
+            name: 'lodash-es',
+            message: 'Please use es-toolkit instead.',
+          },
+          {
+            name: 'es-toolkit',
+            importNames: ['isEqual'],
+            message: 'Please use objectEquals from @observ33r/object-equals instead.',
+          },
+        ],
+      },
+    ],
   },
   overrides: [
+    /**
+     * Allow setActiveTab calls only in use-navigation-api.tsx
+     */
+    {
+      files: ['**/use-navigation-api.tsx'],
+      rules: {
+        'no-restricted-syntax': 'off',
+      },
+    },
     /**
      * Overrides for stories
      */

invokeai/frontend/web/knip.ts

@@ -12,10 +12,8 @@ const config: KnipConfig = {
     'src/features/parameters/types/parameterSchemas.ts',
     // TODO(psyche): maybe we can clean up these utils after canvas v2 release
     'src/features/controlLayers/konva/util.ts',
-    // TODO(psyche): restore HRF functionality?
-    'src/features/hrf/**',
-    // This feature is (temprarily?) disabled
-    'src/features/controlLayers/components/InpaintMask/InpaintMaskAddButtons.tsx',
+    // Will be using this
+    'src/common/hooks/useAsyncState.ts',
   ],
   ignoreBinaries: ['only-allow'],
   paths: {

invokeai/frontend/web/package.json

@@ -38,70 +38,60 @@
     "test:ui": "vitest --coverage --ui",
     "test:no-watch": "vitest --no-watch"
   },
-  "madge": {
-    "excludeRegExp": [
-      "^index.ts$"
-    ],
-    "detectiveOptions": {
-      "ts": {
-        "skipTypeImports": true
-      },
-      "tsx": {
-        "skipTypeImports": true
-      }
-    }
-  },
   "dependencies": {
-    "@atlaskit/pragmatic-drag-and-drop": "^1.5.3",
-    "@atlaskit/pragmatic-drag-and-drop-auto-scroll": "^2.1.0",
-    "@atlaskit/pragmatic-drag-and-drop-hitbox": "^1.0.3",
-    "@dagrejs/dagre": "^1.1.4",
+    "@atlaskit/pragmatic-drag-and-drop": "^1.7.4",
+    "@atlaskit/pragmatic-drag-and-drop-auto-scroll": "^2.1.1",
+    "@atlaskit/pragmatic-drag-and-drop-hitbox": "^1.1.0",
+    "@dagrejs/dagre": "^1.1.5",
     "@dagrejs/graphlib": "^2.2.4",
-    "@fontsource-variable/inter": "^5.2.5",
+    "@fontsource-variable/inter": "^5.2.6",
     "@invoke-ai/ui-library": "^0.0.46",
     "@nanostores/react": "^1.0.0",
-    "@reduxjs/toolkit": "2.7.0",
+    "@observ33r/object-equals": "^1.1.4",
+    "@reduxjs/toolkit": "2.8.2",
     "@roarr/browser-log-writer": "^1.3.0",
-    "@xyflow/react": "^12.6.0",
+    "@xyflow/react": "^12.7.1",
+    "ag-psd": "^28.2.1",
     "async-mutex": "^0.5.0",
     "chakra-react-select": "^4.9.2",
     "cmdk": "^1.1.1",
     "compare-versions": "^6.1.1",
+    "dockview": "^4.4.0",
+    "es-toolkit": "^1.39.5",
     "filesize": "^10.1.6",
     "fracturedjsonjs": "^4.1.0",
     "framer-motion": "^11.10.0",
-    "i18next": "^25.0.1",
+    "i18next": "^25.2.1",
     "i18next-http-backend": "^3.0.2",
-    "idb-keyval": "^6.2.1",
+    "idb-keyval": "^6.2.2",
     "jsondiffpatch": "^0.7.3",
     "konva": "^9.3.20",
-    "linkify-react": "^4.2.0",
-    "linkifyjs": "^4.2.0",
-    "lodash-es": "^4.17.21",
+    "linkify-react": "^4.3.1",
+    "linkifyjs": "^4.3.1",
     "lru-cache": "^11.1.0",
     "mtwist": "^1.0.2",
     "nanoid": "^5.1.5",
     "nanostores": "^1.0.1",
     "new-github-issue-url": "^1.1.0",
-    "overlayscrollbars": "^2.11.1",
+    "overlayscrollbars": "^2.11.4",
     "overlayscrollbars-react": "^0.5.6",
     "perfect-freehand": "^1.2.2",
-    "query-string": "^9.1.1",
+    "query-string": "^9.2.1",
     "raf-throttle": "^2.0.6",
     "react": "^18.3.1",
     "react-colorful": "^5.6.1",
     "react-dom": "^18.3.1",
     "react-dropzone": "^14.3.8",
     "react-error-boundary": "^5.0.0",
-    "react-hook-form": "^7.56.1",
+    "react-hook-form": "^7.58.1",
     "react-hotkeys-hook": "4.5.0",
-    "react-i18next": "^15.5.1",
+    "react-i18next": "^15.5.3",
     "react-icons": "^5.5.0",
     "react-redux": "9.2.0",
-    "react-resizable-panels": "^2.1.8",
+    "react-resizable-panels": "^3.0.3",
     "react-textarea-autosize": "^8.5.9",
     "react-use": "^17.6.0",
-    "react-virtuoso": "^4.12.6",
+    "react-virtuoso": "^4.13.0",
     "redux-dynamic-middlewares": "^2.2.0",
     "redux-remember": "^5.2.0",
     "redux-undo": "^1.1.0",
@@ -109,12 +99,12 @@
     "roarr": "^7.21.1",
     "serialize-error": "^12.0.0",
     "socket.io-client": "^4.8.1",
-    "stable-hash": "^0.0.5",
-    "use-debounce": "^10.0.4",
+    "stable-hash": "^0.0.6",
+    "use-debounce": "^10.0.5",
     "use-device-pixel-ratio": "^1.1.2",
     "uuid": "^11.1.0",
-    "zod": "^3.24.3",
-    "zod-validation-error": "^3.4.0"
+    "zod": "^3.25.67",
+    "zod-validation-error": "^3.5.2"
   },
   "peerDependencies": {
     "react": "^18.2.0",
@@ -131,7 +121,6 @@
     "@storybook/react": "^8.6.12",
     "@storybook/react-vite": "^8.6.12",
     "@storybook/theming": "^8.6.12",
-    "@types/lodash-es": "^4.17.12",
     "@types/node": "^22.15.1",
     "@types/react": "^18.3.11",
     "@types/react-dom": "^18.3.0",
@@ -145,7 +134,7 @@
     "eslint": "^8.57.1",
     "eslint-plugin-i18next": "^6.1.1",
     "eslint-plugin-path": "^1.3.0",
-    "knip": "^5.50.5",
+    "knip": "^5.61.3",
     "openapi-types": "^12.1.3",
     "openapi-typescript": "^7.6.1",
     "prettier": "^3.5.3",
@@ -154,7 +143,7 @@
     "tsafe": "^1.8.5",
     "type-fest": "^4.40.0",
     "typescript": "^5.8.3",
-    "vite": "^6.3.3",
+    "vite": "^7.0.2",
     "vite-plugin-css-injected-by-js": "^3.5.2",
     "vite-plugin-dts": "^4.5.3",
     "vite-plugin-eslint": "^1.8.1",
@@ -162,7 +151,7 @@
     "vitest": "^3.1.2"
   },
   "engines": {
-    "pnpm": "8"
+    "pnpm": "10"
   },
-  "packageManager": "pnpm@8.15.9+sha512.499434c9d8fdd1a2794ebf4552b3b25c0a633abcee5bb15e7b5de90f32f47b513aca98cd5cfd001c31f0db454bc3804edccd578501e4ca293a6816166bbd9f81"
+  "packageManager": "pnpm@10.12.4"
 }

invokeai/frontend/web/pnpm-workspace.yaml

@@ -0,0 +1,3 @@
+onlyBuiltDependencies:
+  - '@swc/core'
+  - esbuild

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

@@ -225,7 +225,16 @@
     "prompt": {
         "addPromptTrigger": "Add Prompt Trigger",
         "compatibleEmbeddings": "Compatible Embeddings",
-        "noMatchingTriggers": "No matching triggers"
+        "noMatchingTriggers": "No matching triggers",
+        "generateFromImage": "Generate prompt from image",
+        "expandCurrentPrompt": "Expand Current Prompt",
+        "uploadImageForPromptGeneration": "Upload Image for Prompt Generation",
+        "expandingPrompt": "Expanding prompt...",
+        "resultTitle": "Prompt Expansion Complete",
+        "resultSubtitle": "Choose how to handle the expanded prompt:",
+        "replace": "Replace",
+        "insert": "Insert",
+        "discard": "Discard"
     },
     "queue": {
         "queue": "Queue",
@@ -335,14 +344,14 @@
         "images": "Images",
         "assets": "Assets",
         "alwaysShowImageSizeBadge": "Always Show Image Size Badge",
-        "assetsTab": "Files you’ve uploaded for use in your projects.",
+        "assetsTab": "Files you've uploaded for use in your projects.",
         "autoAssignBoardOnClick": "Auto-Assign Board on Click",
         "autoSwitchNewImages": "Auto-Switch to New Images",
         "boardsSettings": "Boards Settings",
         "copy": "Copy",
         "currentlyInUse": "This image is currently in use in the following features:",
         "drop": "Drop",
-        "dropOrUpload": "$t(gallery.drop) or Upload",
+        "dropOrUpload": "Drop or Upload",
         "dropToUpload": "$t(gallery.drop) to Upload",
         "deleteImage_one": "Delete Image",
         "deleteImage_other": "Delete {{count}} Images",
@@ -357,7 +366,7 @@
         "gallerySettings": "Gallery Settings",
         "go": "Go",
         "image": "image",
-        "imagesTab": "Images you’ve created and saved within Invoke.",
+        "imagesTab": "Images you've created and saved within Invoke.",
         "imagesSettings": "Gallery Images Settings",
         "jump": "Jump",
         "loading": "Loading",
@@ -396,7 +405,8 @@
         "compareHelp4": "Press <Kbd>Z</Kbd> or <Kbd>Esc</Kbd> to exit.",
         "openViewer": "Open Viewer",
         "closeViewer": "Close Viewer",
-        "move": "Move"
+        "move": "Move",
+        "useForPromptGeneration": "Use for Prompt Generation"
     },
     "hotkeys": {
         "hotkeys": "Hotkeys",
@@ -579,6 +589,16 @@
             "cancelTransform": {
                 "title": "Cancel Transform",
                 "desc": "Cancel the pending transform."
+            },
+            "settings": {
+                "behavior": "Behavior",
+                "display": "Display",
+                "grid": "Grid",
+                "debug": "Debug"
+            },
+            "toggleNonRasterLayers": {
+                "title": "Toggle Non-Raster Layers",
+                "desc": "Show or hide all non-raster layer categories (Control Layers, Inpaint Masks, Regional Guidance)."
             }
         },
         "workflows": {
@@ -742,7 +762,7 @@
         "vae": "VAE",
         "width": "Width",
         "workflow": "Workflow",
-        "canvasV2Metadata": "Canvas"
+        "canvasV2Metadata": "Canvas Layers"
     },
     "modelManager": {
         "active": "active",
@@ -763,7 +783,7 @@
         "convertToDiffusers": "Convert To Diffusers",
         "convertToDiffusersHelpText1": "This model will be converted to the 🧨 Diffusers format.",
         "convertToDiffusersHelpText2": "This process will replace your Model Manager entry with the Diffusers version of the same model.",
-        "convertToDiffusersHelpText3": "Your checkpoint file on disk WILL be deleted if it is in InvokeAI root folder. If it is in a custom location, then it WILL NOT be deleted.",
+        "convertToDiffusersHelpText3": "Your checkpoint file on disk WILL be deleted if it is in the InvokeAI root folder. If it is in a custom location, then it WILL NOT be deleted.",
         "convertToDiffusersHelpText4": "This is a one time process only. It might take around 30s-60s depending on the specifications of your computer.",
         "convertToDiffusersHelpText5": "Please make sure you have enough disk space. Models generally vary between 2GB-7GB in size.",
         "convertToDiffusersHelpText6": "Do you wish to convert this model?",
@@ -806,7 +826,11 @@
         "urlUnauthorizedErrorMessage": "You may need to configure an API token to access this model.",
         "urlUnauthorizedErrorMessage2": "Learn how here.",
         "imageEncoderModelId": "Image Encoder Model ID",
-        "includesNModels": "Includes {{n}} models and their dependencies",
+        "installedModelsCount": "{{installed}} of {{total}} models installed.",
+        "includesNModels": "Includes {{n}} models and their dependencies.",
+        "allNModelsInstalled": "All {{count}} models installed",
+        "nToInstall": "{{count}} to install",
+        "nAlreadyInstalled": "{{count}} already installed",
         "installQueue": "Install Queue",
         "inplaceInstall": "In-place install",
         "inplaceInstallDesc": "Install models without copying the files. When using the model, it will be loaded from its this location. If disabled, the model file(s) will be copied into the Invoke-managed models directory during installation.",
@@ -869,6 +893,25 @@
         "starterBundleHelpText": "Easily install all models needed to get started with a base model, including a main model, controlnets, IP adapters, and more. Selecting a bundle will skip any models that you already have installed.",
         "starterModels": "Starter Models",
         "starterModelsInModelManager": "Starter Models can be found in Model Manager",
+        "bundleAlreadyInstalled": "Bundle already installed",
+        "bundleAlreadyInstalledDesc": "All models in the {{bundleName}} bundle are already installed.",
+        "launchpadTab": "Launchpad",
+        "launchpad": {
+            "welcome": "Welcome to Model Management",
+            "description": "Invoke requires models to be installed to utilize most features of the platform. Choose from manual installation options or explore curated starter models.",
+            "manualInstall": "Manual Installation",
+            "urlDescription": "Install models from a URL or local file path. Perfect for specific models you want to add.",
+            "huggingFaceDescription": "Browse and install models directly from HuggingFace repositories.",
+            "scanFolderDescription": "Scan a local folder to automatically detect and install models.",
+            "recommendedModels": "Recommended Models",
+            "exploreStarter": "Or browse all available starter models",
+            "quickStart": "Quick Start Bundles",
+            "bundleDescription": "Each bundle includes essential models for each model family and curated base models to get started.",
+            "browseAll": "Or browse all available models:",
+            "stableDiffusion15": "Stable Diffusion 1.5",
+            "sdxl": "SDXL",
+            "fluxDev": "FLUX.1 dev"
+        },
         "controlLora": "Control LoRA",
         "llavaOnevision": "LLaVA OneVision",
         "syncModels": "Sync Models",
@@ -905,7 +948,8 @@
         "selectModel": "Select a Model",
         "noLoRAsInstalled": "No LoRAs installed",
         "noRefinerModelsInstalled": "No SDXL Refiner models installed",
-        "defaultVAE": "Default VAE"
+        "defaultVAE": "Default VAE",
+        "noCompatibleLoRAs": "No Compatible LoRAs"
     },
     "nodes": {
         "arithmeticSequence": "Arithmetic Sequence",
@@ -1147,6 +1191,7 @@
             "modelIncompatibleScaledBboxWidth": "Scaled bbox width is {{width}} but {{model}} requires multiple of {{multiple}}",
             "modelIncompatibleScaledBboxHeight": "Scaled bbox height is {{height}} but {{model}} requires multiple of {{multiple}}",
             "fluxModelMultipleControlLoRAs": "Can only use 1 Control LoRA at a time",
+            "fluxKontextMultipleReferenceImages": "Can only use 1 Reference Image at a time with Flux Kontext",
             "canvasIsFiltering": "Canvas is busy (filtering)",
             "canvasIsTransforming": "Canvas is busy (transforming)",
             "canvasIsRasterizing": "Canvas is busy (rasterizing)",
@@ -1154,7 +1199,9 @@
             "canvasIsSelectingObject": "Canvas is busy (selecting object)",
             "noPrompts": "No prompts generated",
             "noNodesInGraph": "No nodes in graph",
-            "systemDisconnected": "System disconnected"
+            "systemDisconnected": "System disconnected",
+            "promptExpansionPending": "Prompt expansion in progress",
+            "promptExpansionResultPending": "Please accept or discard your prompt expansion result"
         },
         "maskBlur": "Mask Blur",
         "negativePromptPlaceholder": "Negative Prompt",
@@ -1312,6 +1359,21 @@
         "problemCopyingLayer": "Unable to Copy Layer",
         "problemSavingLayer": "Unable to Save Layer",
         "problemDownloadingImage": "Unable to Download Image",
+        "noRasterLayers": "No Raster Layers Found",
+        "noRasterLayersDesc": "Create at least one raster layer to export to PSD",
+        "noActiveRasterLayers": "No Active Raster Layers",
+        "noActiveRasterLayersDesc": "Enable at least one raster layer to export to PSD",
+        "noVisibleRasterLayers": "No Visible Raster Layers",
+        "noVisibleRasterLayersDesc": "Enable at least one raster layer to export to PSD",
+        "invalidCanvasDimensions": "Invalid Canvas Dimensions",
+        "canvasTooLarge": "Canvas Too Large",
+        "canvasTooLargeDesc": "Canvas dimensions exceed the maximum allowed size for PSD export. Reduce the total width and height of the canvas of the canvas and try again.",
+        "failedToProcessLayers": "Failed to Process Layers",
+        "psdExportSuccess": "PSD Export Complete",
+        "psdExportSuccessDesc": "Successfully exported {{count}} layers to PSD file",
+        "problemExportingPSD": "Problem Exporting PSD",
+        "canvasManagerNotAvailable": "Canvas Manager Not Available",
+        "noValidLayerAdapters": "No Valid Layer Adapters Found",
         "pasteSuccess": "Pasted to {{destination}}",
         "pasteFailed": "Paste Failed",
         "prunedQueue": "Pruned Queue",
@@ -1337,9 +1399,15 @@
         "fluxFillIncompatibleWithT2IAndI2I": "FLUX Fill is not compatible with Text to Image or Image to Image. Use other FLUX models for these tasks.",
         "imagenIncompatibleGenerationMode": "Google {{model}} supports Text to Image only. Use other models for Image to Image, Inpainting and Outpainting tasks.",
         "chatGPT4oIncompatibleGenerationMode": "ChatGPT 4o supports Text to Image and Image to Image only. Use other models Inpainting and Outpainting tasks.",
+        "fluxKontextIncompatibleGenerationMode": "FLUX Kontext does not support generation from images placed on the canvas. Re-try using the Reference Image section and disable any Raster Layers.",
         "problemUnpublishingWorkflow": "Problem Unpublishing Workflow",
         "problemUnpublishingWorkflowDescription": "There was a problem unpublishing the workflow. Please try again.",
-        "workflowUnpublished": "Workflow Unpublished"
+        "workflowUnpublished": "Workflow Unpublished",
+        "sentToCanvas": "Sent to Canvas",
+        "sentToUpscale": "Sent to Upscale",
+        "promptGenerationStarted": "Prompt generation started",
+        "uploadAndPromptGenerationFailed": "Failed to upload image and generate prompt",
+        "promptExpansionFailed": "We ran into an issue. Please try prompt expansion again."
     },
     "popovers": {
         "clipSkip": {
@@ -1862,6 +1930,7 @@
         "saveCanvasToGallery": "Save Canvas to Gallery",
         "saveBboxToGallery": "Save Bbox to Gallery",
         "saveLayerToAssets": "Save Layer to Assets",
+        "exportCanvasToPSD": "Export Canvas to PSD",
         "cropLayerToBbox": "Crop Layer to Bbox",
         "savedToGalleryOk": "Saved to Gallery",
         "savedToGalleryError": "Error saving to gallery",
@@ -1887,11 +1956,13 @@
         "mergingLayers": "Merging layers",
         "clearHistory": "Clear History",
         "bboxOverlay": "Show Bbox Overlay",
+        "ruleOfThirds": "Show Rule of Thirds",
         "newSession": "New Session",
         "clearCaches": "Clear Caches",
         "recalculateRects": "Recalculate Rects",
         "clipToBbox": "Clip Strokes to Bbox",
         "outputOnlyMaskedRegions": "Output Only Generated Regions",
+        "saveAllImagesToGallery": "Save All Images to Gallery",
         "addLayer": "Add Layer",
         "duplicate": "Duplicate",
         "moveToFront": "Move to Front",
@@ -1992,6 +2063,8 @@
         "disableTransparencyEffect": "Disable Transparency Effect",
         "hidingType": "Hiding {{type}}",
         "showingType": "Showing {{type}}",
+        "showNonRasterLayers": "Show Non-Raster Layers (Shift+H)",
+        "hideNonRasterLayers": "Hide Non-Raster Layers (Shift+H)",
         "dynamicGrid": "Dynamic Grid",
         "logDebugInfo": "Log Debug Info",
         "locked": "Locked",
@@ -2015,7 +2088,9 @@
         "resetGenerationSettings": "Reset Generation Settings",
         "replaceCurrent": "Replace Current",
         "controlLayerEmptyState": "<UploadButton>Upload an image</UploadButton>, drag an image from the <GalleryButton>gallery</GalleryButton> onto this layer, <PullBboxButton>pull the bounding box into this layer</PullBboxButton>, or draw on the canvas to get started.",
-        "referenceImageEmptyState": "<UploadButton>Upload an image</UploadButton>, drag an image from the <GalleryButton>gallery</GalleryButton> onto this layer, or <PullBboxButton>pull the bounding box into this layer</PullBboxButton> to get started.",
+        "referenceImageEmptyStateWithCanvasOptions": "<UploadButton>Upload an image</UploadButton>, drag an image from the <GalleryButton>gallery</GalleryButton> onto this Reference Image or <PullBboxButton>pull the bounding box into this Reference Image</PullBboxButton> to get started.",
+        "referenceImageEmptyState": "<UploadButton>Upload an image</UploadButton> or drag an image from the <GalleryButton>gallery</GalleryButton> onto this Reference Image to get started.",
+        "uploadOrDragAnImage": "Drag an image from the gallery or <UploadButton>upload an image</UploadButton>.",
         "imageNoise": "Image Noise",
         "denoiseLimit": "Denoise Limit",
         "warnings": {
@@ -2256,6 +2331,9 @@
                 "label": "Preserve Masked Region",
                 "alert": "Preserving Masked Region"
             },
+            "saveAllImagesToGallery": {
+                "alert": "Saving All Images to Gallery"
+            },
             "isolatedStagingPreview": "Isolated Staging Preview",
             "isolatedPreview": "Isolated Preview",
             "isolatedLayerPreview": "Isolated Layer Preview",
@@ -2284,6 +2362,7 @@
             "newGlobalReferenceImage": "New Global Reference Image",
             "newRegionalReferenceImage": "New Regional Reference Image",
             "newControlLayer": "New Control Layer",
+            "newResizedControlLayer": "New Resized Control Layer",
             "newRasterLayer": "New Raster Layer",
             "newInpaintMask": "New Inpaint Mask",
             "newRegionalGuidance": "New Regional Guidance",
@@ -2301,6 +2380,11 @@
             "saveToGallery": "Save To Gallery",
             "showResultsOn": "Showing Results",
             "showResultsOff": "Hiding Results"
+        },
+        "autoSwitch": {
+            "off": "Off",
+            "switchOnStart": "On Start",
+            "switchOnFinish": "On Finish"
         }
     },
     "upscaling": {
@@ -2367,7 +2451,8 @@
         "uploadImage": "Upload Image",
         "useForTemplate": "Use For Prompt Template",
         "viewList": "View Template List",
-        "viewModeTooltip": "This is how your prompt will look with your currently selected template. To edit your prompt, click anywhere in the text box."
+        "viewModeTooltip": "This is how your prompt will look with your currently selected template. To edit your prompt, click anywhere in the text box.",
+        "togglePromptPreviews": "Toggle Prompt Previews"
     },
     "upsell": {
         "inviteTeammates": "Invite Teammates",
@@ -2387,6 +2472,55 @@
             "upscaling": "Upscaling",
             "upscalingTab": "$t(ui.tabs.upscaling) $t(common.tab)",
             "gallery": "Gallery"
+        },
+        "launchpad": {
+            "workflowsTitle": "Go deep with Workflows.",
+            "upscalingTitle": "Upscale and add detail.",
+            "canvasTitle": "Edit and refine on Canvas.",
+            "generateTitle": "Generate images from text prompts.",
+            "modelGuideText": "Want to learn what prompts work best for each model?",
+            "modelGuideLink": "Check out our Model Guide.",
+            "workflows": {
+                "description": "Workflows are reusable templates that automate image generation tasks, allowing you to quickly perform complex operations and get consistent results.",
+                "learnMoreLink": "Learn more about creating workflows",
+                "browseTemplates": {
+                    "title": "Browse Workflow Templates",
+                    "description": "Choose from pre-built workflows for common tasks"
+                },
+                "createNew": {
+                    "title": "Create a new Workflow",
+                    "description": "Start a new workflow from scratch"
+                },
+                "loadFromFile": {
+                    "title": "Load workflow from file",
+                    "description": "Upload a workflow to start with an existing setup"
+                }
+            },
+            "upscaling": {
+                "uploadImage": {
+                    "title": "Upload Image to Upscale",
+                    "description": "Click or drag an image to upscale (JPG, PNG, WebP up to 100MB)"
+                },
+                "replaceImage": {
+                    "title": "Replace Current Image",
+                    "description": "Click or drag a new image to replace the current one"
+                },
+                "imageReady": {
+                    "title": "Image Ready",
+                    "description": "Press Invoke to begin upscaling"
+                },
+                "readyToUpscale": {
+                    "title": "Ready to upscale!",
+                    "description": "Configure your settings below, then click the Invoke button to begin upscaling your image."
+                },
+                "upscaleModel": "Upscale Model",
+                "model": "Model",
+                "scale": "Scale",
+                "helpText": {
+                    "promptAdvice": "When upscaling, use a prompt that describes the medium and style. Avoid describing specific content details in the image.",
+                    "styleAdvice": "Upscaling works best with the general style of your image."
+                }
+            }
         }
     },
     "system": {
@@ -2426,8 +2560,9 @@
     "whatsNew": {
         "whatsNewInInvoke": "What's New in Invoke",
         "items": [
-            "Inpainting: Per-mask noise levels and denoise limits.",
-            "Canvas: Smarter aspect ratios for SDXL and improved scroll-to-zoom."
+            "Generate images faster with new Launchpads and a simplified Generate tab.",
+            "Edit with prompts using Flux Kontext Dev.",
+            "Export to PSD, bulk-hide overlays, organize models & images — all in a reimagined interface built for control."
         ],
         "readReleaseNotes": "Read Release Notes",
         "watchRecentReleaseVideos": "Watch Recent Release Videos",
@@ -2436,62 +2571,16 @@
     "supportVideos": {
         "supportVideos": "Support Videos",
         "gettingStarted": "Getting Started",
-        "controlCanvas": "Control Canvas",
         "watch": "Watch",
-        "studioSessionsDesc1": "Check out the <StudioSessionsPlaylistLink /> for Invoke deep dives.",
-        "studioSessionsDesc2": "Join our <DiscordLink /> to participate in the live sessions and ask questions. Sessions are uploaded to the playlist the following week.",
+        "studioSessionsDesc": "Join our <DiscordLink /> to participate in the live sessions and ask questions. Sessions are uploaded to the playlist the following week.",
         "videos": {
-            "creatingYourFirstImage": {
-                "title": "Creating Your First Image",
-                "description": "Introduction to creating an image from scratch using Invoke's tools."
+            "gettingStarted": {
+                "title": "Getting Started with Invoke",
+                "description": "Complete video series covering everything you need to know to get started with Invoke, from creating your first image to advanced techniques."
             },
-            "usingControlLayersAndReferenceGuides": {
-                "title": "Using Control Layers and Reference Guides",
-                "description": "Learn how to guide your image creation with control layers and reference images."
-            },
-            "understandingImageToImageAndDenoising": {
-                "title": "Understanding Image-to-Image and Denoising",
-                "description": "Overview of image-to-image transformations and denoising in Invoke."
-            },
-            "exploringAIModelsAndConceptAdapters": {
-                "title": "Exploring AI Models and Concept Adapters",
-                "description": "Dive into AI models and how to use concept adapters for creative control."
-            },
-            "creatingAndComposingOnInvokesControlCanvas": {
-                "title": "Creating and Composing on Invoke's Control Canvas",
-                "description": "Learn to compose images using Invoke's control canvas."
-            },
-            "upscaling": {
-                "title": "Upscaling",
-                "description": "How to upscale images with Invoke's tools to enhance resolution."
-            },
-            "howDoIGenerateAndSaveToTheGallery": {
-                "title": "How Do I Generate and Save to the Gallery?",
-                "description": "Steps to generate and save images to the gallery."
-            },
-            "howDoIEditOnTheCanvas": {
-                "title": "How Do I Edit on the Canvas?",
-                "description": "Guide to editing images directly on the canvas."
-            },
-            "howDoIDoImageToImageTransformation": {
-                "title": "How Do I Do Image-to-Image Transformation?",
-                "description": "Tutorial on performing image-to-image transformations in Invoke."
-            },
-            "howDoIUseControlNetsAndControlLayers": {
-                "title": "How Do I Use Control Nets and Control Layers?",
-                "description": "Learn to apply control layers and controlnets to your images."
-            },
-            "howDoIUseGlobalIPAdaptersAndReferenceImages": {
-                "title": "How Do I Use Global IP Adapters and Reference Images?",
-                "description": "Introduction to adding reference images and global IP adapters."
-            },
-            "howDoIUseInpaintMasks": {
-                "title": "How Do I Use Inpaint Masks?",
-                "description": "How to apply inpaint masks for image correction and variation."
-            },
-            "howDoIOutpaint": {
-                "title": "How Do I Outpaint?",
-                "description": "Guide to outpainting beyond the original image borders."
+            "studioSessions": {
+                "title": "Studio Sessions",
+                "description": "Deep dive sessions exploring advanced Invoke features, creative workflows, and community discussions."
             }
         }
     }

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

@@ -2,8 +2,7 @@ import { Box } from '@invoke-ai/ui-library';
 import { useStore } from '@nanostores/react';
 import { GlobalHookIsolator } from 'app/components/GlobalHookIsolator';
 import { GlobalModalIsolator } from 'app/components/GlobalModalIsolator';
-import type { StudioInitAction } from 'app/hooks/useStudioInitAction';
-import { $didStudioInit } from 'app/hooks/useStudioInitAction';
+import { $didStudioInit, type StudioInitAction } from 'app/hooks/useStudioInitAction';
 import type { PartialAppConfig } from 'app/types/invokeai';
 import Loading from 'common/components/Loading/Loading';
 import { useClearStorage } from 'common/hooks/useClearStorage';
@@ -12,6 +11,7 @@ import { memo, useCallback } from 'react';
 import { ErrorBoundary } from 'react-error-boundary';
 
 import AppErrorBoundaryFallback from './AppErrorBoundaryFallback';
+import ThemeLocaleProvider from './ThemeLocaleProvider';
 const DEFAULT_CONFIG = {};
 
 interface Props {
@@ -31,12 +31,14 @@ const App = ({ config = DEFAULT_CONFIG, studioInitAction }: Props) => {
 
   return (
     <ErrorBoundary onReset={handleReset} FallbackComponent={AppErrorBoundaryFallback}>
-      <Box id="invoke-app-wrapper" w="100dvw" h="100dvh" position="relative" overflow="hidden">
-        <AppContent />
-        {!didStudioInit && <Loading />}
-      </Box>
-      <GlobalHookIsolator config={config} studioInitAction={studioInitAction} />
-      <GlobalModalIsolator />
+      <ThemeLocaleProvider>
+        <Box id="invoke-app-wrapper" w="100dvw" h="100dvh" position="relative" overflow="hidden">
+          <AppContent />
+          {!didStudioInit && <Loading />}
+        </Box>
+        <GlobalHookIsolator config={config} studioInitAction={studioInitAction} />
+        <GlobalModalIsolator />
+      </ThemeLocaleProvider>
     </ErrorBoundary>
   );
 };

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

@@ -1,4 +1,5 @@
 import { useGlobalModifiersInit } from '@invoke-ai/ui-library';
+import { setupListeners } from '@reduxjs/toolkit/query';
 import type { StudioInitAction } from 'app/hooks/useStudioInitAction';
 import { useStudioInitAction } from 'app/hooks/useStudioInitAction';
 import { useSyncQueueStatus } from 'app/hooks/useSyncQueueStatus';
@@ -8,19 +9,24 @@ import { appStarted } from 'app/store/middleware/listenerMiddleware/listeners/ap
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import type { PartialAppConfig } from 'app/types/invokeai';
 import { useFocusRegionWatcher } from 'common/hooks/focus';
+import { useCloseChakraTooltipsOnDragFix } from 'common/hooks/useCloseChakraTooltipsOnDragFix';
 import { useGlobalHotkeys } from 'common/hooks/useGlobalHotkeys';
+import { useDndMonitor } from 'features/dnd/useDndMonitor';
 import { useDynamicPromptsWatcher } from 'features/dynamicPrompts/hooks/useDynamicPromptsWatcher';
 import { useStarterModelsToast } from 'features/modelManagerV2/hooks/useStarterModelsToast';
 import { useWorkflowBuilderWatcher } from 'features/nodes/components/sidePanel/workflow/IsolatedWorkflowBuilderWatcher';
 import { useReadinessWatcher } from 'features/queue/store/readiness';
 import { configChanged } from 'features/system/store/configSlice';
 import { selectLanguage } from 'features/system/store/systemSelectors';
+import { useNavigationApi } from 'features/ui/layouts/use-navigation-api';
 import i18n from 'i18n';
-import { size } from 'lodash-es';
 import { memo, useEffect } from 'react';
 import { useGetOpenAPISchemaQuery } from 'services/api/endpoints/appInfo';
+import { useGetQueueCountsByDestinationQuery } from 'services/api/endpoints/queue';
 import { useSocketIO } from 'services/events/useSocketIO';
 
+const queueCountArg = { destination: 'canvas' };
+
 /**
  * GlobalHookIsolator is a logical component that runs global hooks in an isolated component, so that they do not
  * cause needless re-renders of any other components.
@@ -38,22 +44,31 @@ export const GlobalHookIsolator = memo(
     useGlobalHotkeys();
     useGetOpenAPISchemaQuery();
     useSyncLoggingConfig();
+    useCloseChakraTooltipsOnDragFix();
+    useNavigationApi();
+    useDndMonitor();
+
+    // Persistent subscription to the queue counts query - canvas relies on this to know if there are pending
+    // and/or in progress canvas sessions.
+    useGetQueueCountsByDestinationQuery(queueCountArg);
 
     useEffect(() => {
       i18n.changeLanguage(language);
     }, [language]);
 
     useEffect(() => {
-      if (size(config)) {
-        logger.info({ config }, 'Received config');
-        dispatch(configChanged(config));
-      }
+      logger.info({ config }, 'Received config');
+      dispatch(configChanged(config));
     }, [dispatch, config, logger]);
 
     useEffect(() => {
       dispatch(appStarted());
     }, [dispatch]);
 
+    useEffect(() => {
+      return setupListeners(dispatch);
+    }, [dispatch]);
+
     useStudioInitAction(studioInitAction);
     useStarterModelsToast();
     useSyncQueueStatus();

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

@@ -1,17 +1,22 @@
 import { useAppSelector } from 'app/store/storeHooks';
 import { useIsRegionFocused } from 'common/hooks/focus';
 import { useAssertSingleton } from 'common/hooks/useAssertSingleton';
-import { selectIsStaging } from 'features/controlLayers/store/canvasStagingAreaSlice';
-import { useImageActions } from 'features/gallery/hooks/useImageActions';
+import { useLoadWorkflow } from 'features/gallery/hooks/useLoadWorkflow';
+import { useRecallAll } from 'features/gallery/hooks/useRecallAll';
+import { useRecallDimensions } from 'features/gallery/hooks/useRecallDimensions';
+import { useRecallPrompts } from 'features/gallery/hooks/useRecallPrompts';
+import { useRecallRemix } from 'features/gallery/hooks/useRecallRemix';
+import { useRecallSeed } from 'features/gallery/hooks/useRecallSeed';
 import { selectLastSelectedImage } from 'features/gallery/store/gallerySelectors';
 import { useRegisteredHotkeys } from 'features/system/components/HotkeysModal/useHotkeyData';
-import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';
 import { memo } from 'react';
+import { useImageDTO } from 'services/api/endpoints/images';
 import type { ImageDTO } from 'services/api/types';
 
 export const GlobalImageHotkeys = memo(() => {
   useAssertSingleton('GlobalImageHotkeys');
-  const imageDTO = useAppSelector(selectLastSelectedImage);
+  const imageName = useAppSelector(selectLastSelectedImage);
+  const imageDTO = useImageDTO(imageName);
 
   if (!imageDTO) {
     return null;
@@ -25,59 +30,64 @@ GlobalImageHotkeys.displayName = 'GlobalImageHotkeys';
 const GlobalImageHotkeysInternal = memo(({ imageDTO }: { imageDTO: ImageDTO }) => {
   const isGalleryFocused = useIsRegionFocused('gallery');
   const isViewerFocused = useIsRegionFocused('viewer');
-  const imageActions = useImageActions(imageDTO);
-  const isStaging = useAppSelector(selectIsStaging);
-  const isUpscalingEnabled = useFeatureStatus('upscaling');
+
+  const isFocusOK = isGalleryFocused || isViewerFocused;
+
+  const recallAll = useRecallAll(imageDTO);
+  const recallRemix = useRecallRemix(imageDTO);
+  const recallPrompts = useRecallPrompts(imageDTO);
+  const recallSeed = useRecallSeed(imageDTO);
+  const recallDimensions = useRecallDimensions(imageDTO);
+  const loadWorkflow = useLoadWorkflow(imageDTO);
 
   useRegisteredHotkeys({
     id: 'loadWorkflow',
     category: 'viewer',
-    callback: imageActions.loadWorkflow,
-    options: { enabled: isGalleryFocused || isViewerFocused },
-    dependencies: [imageActions.loadWorkflow, isGalleryFocused, isViewerFocused],
+    callback: loadWorkflow.load,
+    options: { enabled: loadWorkflow.isEnabled && isFocusOK },
+    dependencies: [loadWorkflow, isFocusOK],
   });
+
   useRegisteredHotkeys({
     id: 'recallAll',
     category: 'viewer',
-    callback: imageActions.recallAll,
-    options: { enabled: !isStaging && (isGalleryFocused || isViewerFocused) },
-    dependencies: [imageActions.recallAll, isStaging, isGalleryFocused, isViewerFocused],
+    callback: recallAll.recall,
+    options: { enabled: recallAll.isEnabled && isFocusOK },
+    dependencies: [recallAll, isFocusOK],
   });
+
   useRegisteredHotkeys({
     id: 'recallSeed',
     category: 'viewer',
-    callback: imageActions.recallSeed,
-    options: { enabled: isGalleryFocused || isViewerFocused },
-    dependencies: [imageActions.recallSeed, isGalleryFocused, isViewerFocused],
+    callback: recallSeed.recall,
+    options: { enabled: recallSeed.isEnabled && isFocusOK },
+    dependencies: [recallSeed, isFocusOK],
   });
+
   useRegisteredHotkeys({
     id: 'recallPrompts',
     category: 'viewer',
-    callback: imageActions.recallPrompts,
-    options: { enabled: isGalleryFocused || isViewerFocused },
-    dependencies: [imageActions.recallPrompts, isGalleryFocused, isViewerFocused],
+    callback: recallPrompts.recall,
+    options: { enabled: recallPrompts.isEnabled && isFocusOK },
+    dependencies: [recallPrompts, isFocusOK],
   });
+
   useRegisteredHotkeys({
     id: 'remix',
     category: 'viewer',
-    callback: imageActions.remix,
-    options: { enabled: isGalleryFocused || isViewerFocused },
-    dependencies: [imageActions.remix, isGalleryFocused, isViewerFocused],
+    callback: recallRemix.recall,
+    options: { enabled: recallRemix.isEnabled && isFocusOK },
+    dependencies: [recallRemix, isFocusOK],
   });
+
   useRegisteredHotkeys({
     id: 'useSize',
     category: 'viewer',
-    callback: imageActions.recallSize,
-    options: { enabled: !isStaging && (isGalleryFocused || isViewerFocused) },
-    dependencies: [imageActions.recallSize, isStaging, isGalleryFocused, isViewerFocused],
-  });
-  useRegisteredHotkeys({
-    id: 'runPostprocessing',
-    category: 'viewer',
-    callback: imageActions.upscale,
-    options: { enabled: isUpscalingEnabled && isViewerFocused },
-    dependencies: [isUpscalingEnabled, imageDTO, isViewerFocused],
+    callback: recallDimensions.recall,
+    options: { enabled: recallDimensions.isEnabled && isFocusOK },
+    dependencies: [recallDimensions, isFocusOK],
   });
+
   return null;
 });
 

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

@@ -6,7 +6,7 @@ import {
   NewGallerySessionDialog,
 } from 'features/controlLayers/components/NewSessionConfirmationAlertDialog';
 import { CanvasManagerProviderGate } from 'features/controlLayers/contexts/CanvasManagerProviderGate';
-import DeleteImageModal from 'features/deleteImageModal/components/DeleteImageModal';
+import { DeleteImageModal } from 'features/deleteImageModal/components/DeleteImageModal';
 import { FullscreenDropzone } from 'features/dnd/FullscreenDropzone';
 import { DynamicPromptsModal } from 'features/dynamicPrompts/components/DynamicPromptsPreviewModal';
 import DeleteBoardModal from 'features/gallery/components/Boards/DeleteBoardModal';
@@ -15,6 +15,7 @@ import { ShareWorkflowModal } from 'features/nodes/components/sidePanel/workflow
 import { WorkflowLibraryModal } from 'features/nodes/components/sidePanel/workflow/WorkflowLibrary/WorkflowLibraryModal';
 import { CancelAllExceptCurrentQueueItemConfirmationAlertDialog } from 'features/queue/components/CancelAllExceptCurrentQueueItemConfirmationAlertDialog';
 import { ClearQueueConfirmationsAlertDialog } from 'features/queue/components/ClearQueueConfirmationAlertDialog';
+import { DeleteAllExceptCurrentQueueItemConfirmationAlertDialog } from 'features/queue/components/DeleteAllExceptCurrentQueueItemConfirmationAlertDialog';
 import { DeleteStylePresetDialog } from 'features/stylePresets/components/DeleteStylePresetDialog';
 import { StylePresetModal } from 'features/stylePresets/components/StylePresetForm/StylePresetModal';
 import RefreshAfterResetModal from 'features/system/components/SettingsModal/RefreshAfterResetModal';
@@ -39,6 +40,7 @@ export const GlobalModalIsolator = memo(() => {
       <StylePresetModal />
       <WorkflowLibraryModal />
       <CancelAllExceptCurrentQueueItemConfirmationAlertDialog />
+      <DeleteAllExceptCurrentQueueItemConfirmationAlertDialog />
       <ClearQueueConfirmationsAlertDialog />
       <NewWorkflowConfirmationAlertDialog />
       <LoadWorkflowConfirmationAlertDialog />

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

@@ -42,7 +42,6 @@ import { $socketOptions } from 'services/events/stores';
 import type { ManagerOptions, SocketOptions } from 'socket.io-client';
 
 const App = lazy(() => import('./App'));
-const ThemeLocaleProvider = lazy(() => import('./ThemeLocaleProvider'));
 
 interface Props extends PropsWithChildren {
   apiUrl?: string;
@@ -330,9 +329,7 @@ const InvokeAIUI = ({
     <React.StrictMode>
       <Provider store={store}>
         <React.Suspense fallback={<Loading />}>
-          <ThemeLocaleProvider>
-            <App config={config} studioInitAction={studioInitAction} />
-          </ThemeLocaleProvider>
+          <App config={config} studioInitAction={studioInitAction} />
         </React.Suspense>
       </Provider>
     </React.StrictMode>

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

@@ -1,6 +1,7 @@
 import '@fontsource-variable/inter';
 import 'overlayscrollbars/overlayscrollbars.css';
 import '@xyflow/react/dist/base.css';
+import 'common/components/OverlayScrollbars/overlayscrollbars.css';
 
 import { ChakraProvider, DarkMode, extendTheme, theme as _theme, TOAST_OPTIONS } from '@invoke-ai/ui-library';
 import type { ReactNode } from 'react';

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

@@ -3,13 +3,12 @@ import { useAppStore } from 'app/store/storeHooks';
 import { useAssertSingleton } from 'common/hooks/useAssertSingleton';
 import { withResultAsync } from 'common/util/result';
 import { canvasReset } from 'features/controlLayers/store/actions';
-import { settingsSendToCanvasChanged } from 'features/controlLayers/store/canvasSettingsSlice';
 import { rasterLayerAdded } from 'features/controlLayers/store/canvasSlice';
+import { paramsReset } from 'features/controlLayers/store/paramsSlice';
 import type { CanvasRasterLayerState } from 'features/controlLayers/store/types';
 import { imageDTOToImageObject } from 'features/controlLayers/store/util';
-import { $imageViewer } from 'features/gallery/components/ImageViewer/useImageViewer';
 import { sentImageToCanvas } from 'features/gallery/store/actions';
-import { parseAndRecallAllMetadata } from 'features/metadata/util/handlers';
+import { MetadataUtils } from 'features/metadata/parsing';
 import { $hasTemplates } from 'features/nodes/store/nodesSlice';
 import { $isWorkflowLibraryModalOpen } from 'features/nodes/store/workflowLibraryModal';
 import {
@@ -20,7 +19,9 @@ import {
 } from 'features/nodes/store/workflowLibrarySlice';
 import { $isStylePresetsMenuOpen, activeStylePresetIdChanged } from 'features/stylePresets/store/stylePresetSlice';
 import { toast } from 'features/toast/toast';
-import { activeTabCanvasRightPanelChanged, setActiveTab } from 'features/ui/store/uiSlice';
+import { navigationApi } from 'features/ui/layouts/navigation-api';
+import { LAUNCHPAD_PANEL_ID, WORKSPACE_PANEL_ID } from 'features/ui/layouts/shared';
+import { activeTabCanvasRightPanelChanged } from 'features/ui/store/uiSlice';
 import { useLoadWorkflowWithDialog } from 'features/workflowLibrary/components/LoadWorkflowConfirmationAlertDialog';
 import { atom } from 'nanostores';
 import { useCallback, useEffect } from 'react';
@@ -91,12 +92,10 @@ export const useStudioInitAction = (action?: StudioInitAction) => {
       const overrides: Partial<CanvasRasterLayerState> = {
         objects: [imageObject],
       };
+      await navigationApi.focusPanel('canvas', WORKSPACE_PANEL_ID);
       store.dispatch(canvasReset());
       store.dispatch(rasterLayerAdded({ overrides, isSelected: true }));
-      store.dispatch(settingsSendToCanvasChanged(true));
-      store.dispatch(setActiveTab('canvas'));
       store.dispatch(sentImageToCanvas());
-      $imageViewer.set(false);
       toast({
         title: t('toast.sentToCanvas'),
         status: 'info',
@@ -118,25 +117,25 @@ export const useStudioInitAction = (action?: StudioInitAction) => {
         return;
       }
       const metadata = getImageMetadataResult.value;
+      store.dispatch(canvasReset());
       // This shows a toast
-      await parseAndRecallAllMetadata(metadata, true);
-      store.dispatch(setActiveTab('canvas'));
+      await MetadataUtils.recallAll(metadata, store);
     },
     [store, t]
   );
 
   const handleLoadWorkflow = useCallback(
-    async (workflowId: string) => {
+    (workflowId: string) => {
       // This shows a toast
-      await loadWorkflowWithDialog({
+      loadWorkflowWithDialog({
         type: 'library',
         data: workflowId,
         onSuccess: () => {
-          store.dispatch(setActiveTab('workflows'));
+          navigationApi.switchToTab('workflows');
         },
       });
     },
-    [loadWorkflowWithDialog, store]
+    [loadWorkflowWithDialog]
   );
 
   const handleSelectStylePreset = useCallback(
@@ -150,7 +149,7 @@ export const useStudioInitAction = (action?: StudioInitAction) => {
         return;
       }
       store.dispatch(activeStylePresetIdChanged(stylePresetId));
-      store.dispatch(setActiveTab('canvas'));
+      navigationApi.switchToTab('canvas');
       toast({
         title: t('toast.stylePresetLoaded'),
         status: 'info',
@@ -160,37 +159,34 @@ export const useStudioInitAction = (action?: StudioInitAction) => {
   );
 
   const handleGoToDestination = useCallback(
-    (destination: StudioDestinationAction['data']['destination']) => {
+    async (destination: StudioDestinationAction['data']['destination']) => {
       switch (destination) {
         case 'generation':
-          // Go to the canvas tab, open the image viewer, and enable send-to-gallery mode
-          store.dispatch(setActiveTab('canvas'));
+          // Go to the generate tab, open the launchpad
+          await navigationApi.focusPanel('generate', LAUNCHPAD_PANEL_ID);
+          store.dispatch(paramsReset());
           store.dispatch(activeTabCanvasRightPanelChanged('gallery'));
-          store.dispatch(settingsSendToCanvasChanged(false));
-          $imageViewer.set(true);
           break;
         case 'canvas':
-          // Go to the canvas tab, close the image viewer, and disable send-to-gallery mode
-          store.dispatch(setActiveTab('canvas'));
-          store.dispatch(settingsSendToCanvasChanged(true));
-          $imageViewer.set(false);
+          // Go to the canvas tab, open the launchpad
+          await navigationApi.focusPanel('canvas', WORKSPACE_PANEL_ID);
           break;
         case 'workflows':
           // Go to the workflows tab
-          store.dispatch(setActiveTab('workflows'));
+          navigationApi.switchToTab('workflows');
           break;
         case 'upscaling':
           // Go to the upscaling tab
-          store.dispatch(setActiveTab('upscaling'));
+          navigationApi.switchToTab('upscaling');
           break;
         case 'viewAllWorkflows':
           // Go to the workflows tab and open the workflow library modal
-          store.dispatch(setActiveTab('workflows'));
+          navigationApi.switchToTab('workflows');
           $isWorkflowLibraryModalOpen.set(true);
           break;
         case 'viewAllWorkflowsRecommended':
           // Go to the workflows tab and open the workflow library modal with the recommended workflows view
-          store.dispatch(setActiveTab('workflows'));
+          navigationApi.switchToTab('workflows');
           $isWorkflowLibraryModalOpen.set(true);
           store.dispatch(workflowLibraryViewChanged('defaults'));
           store.dispatch(workflowLibraryTagsReset());
@@ -202,7 +198,7 @@ export const useStudioInitAction = (action?: StudioInitAction) => {
           break;
         case 'viewAllStylePresets':
           // Go to the canvas tab and open the style presets menu
-          store.dispatch(setActiveTab('canvas'));
+          navigationApi.switchToTab('canvas');
           $isStylePresetsMenuOpen.set(true);
           break;
       }

invokeai/frontend/web/src/app/logging/logger.ts

@@ -2,7 +2,7 @@ import { createLogWriter } from '@roarr/browser-log-writer';
 import { atom } from 'nanostores';
 import type { Logger, MessageSerializer } from 'roarr';
 import { ROARR, Roarr } from 'roarr';
-import { z } from 'zod';
+import { z } from 'zod/v4';
 
 const serializeMessage: MessageSerializer = (message) => {
   return JSON.stringify(message);

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

@@ -1,13 +1,13 @@
+import { objectEquals } from '@observ33r/object-equals';
 import { createDraftSafeSelectorCreator, createSelectorCreator, lruMemoize } from '@reduxjs/toolkit';
-import { isEqual } from 'lodash-es';
 
 /**
- * A memoized selector creator that uses LRU cache and lodash's isEqual for equality check.
+ * A memoized selector creator that uses LRU cache and @observ33r/object-equals's objectEquals for equality check.
  */
 export const createMemoizedSelector = createSelectorCreator({
   memoize: lruMemoize,
   memoizeOptions: {
-    resultEqualityCheck: isEqual,
+    resultEqualityCheck: objectEquals,
   },
   argsMemoize: lruMemoize,
 });

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

@@ -8,10 +8,13 @@ import { diff } from 'jsondiffpatch';
  * Super simple logger middleware. Useful for debugging when the redux devtools are awkward.
  */
 export const getDebugLoggerMiddleware =
-  (options?: { withDiff?: boolean; withNextState?: boolean }): Middleware =>
+  (options?: { filter?: (action: unknown) => boolean; withDiff?: boolean; withNextState?: boolean }): Middleware =>
   (api: MiddlewareAPI) =>
   (next) =>
   (action) => {
+    if (options?.filter?.(action)) {
+      return next(action);
+    }
     const originalState = api.getState();
     console.log('REDUX: dispatching', action);
     const result = next(action);

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts

@@ -1,7 +1,6 @@
 import type { TypedStartListening } from '@reduxjs/toolkit';
 import { addListener, createListenerMiddleware } from '@reduxjs/toolkit';
 import { addAdHocPostProcessingRequestedListener } from 'app/store/middleware/listenerMiddleware/listeners/addAdHocPostProcessingRequestedListener';
-import { addStagingListeners } from 'app/store/middleware/listenerMiddleware/listeners/addCommitStagingAreaImageListener';
 import { addAnyEnqueuedListener } from 'app/store/middleware/listenerMiddleware/listeners/anyEnqueued';
 import { addAppConfigReceivedListener } from 'app/store/middleware/listenerMiddleware/listeners/appConfigReceived';
 import { addAppStartedListener } from 'app/store/middleware/listenerMiddleware/listeners/appStarted';
@@ -9,16 +8,9 @@ import { addBatchEnqueuedListener } from 'app/store/middleware/listenerMiddlewar
 import { addDeleteBoardAndImagesFulfilledListener } from 'app/store/middleware/listenerMiddleware/listeners/boardAndImagesDeleted';
 import { addBoardIdSelectedListener } from 'app/store/middleware/listenerMiddleware/listeners/boardIdSelected';
 import { addBulkDownloadListeners } from 'app/store/middleware/listenerMiddleware/listeners/bulkDownload';
-import { addEnqueueRequestedLinear } from 'app/store/middleware/listenerMiddleware/listeners/enqueueRequestedLinear';
-import { addGalleryImageClickedListener } from 'app/store/middleware/listenerMiddleware/listeners/galleryImageClicked';
-import { addGalleryOffsetChangedListener } from 'app/store/middleware/listenerMiddleware/listeners/galleryOffsetChanged';
 import { addGetOpenAPISchemaListener } from 'app/store/middleware/listenerMiddleware/listeners/getOpenAPISchema';
 import { addImageAddedToBoardFulfilledListener } from 'app/store/middleware/listenerMiddleware/listeners/imageAddedToBoard';
-import { addImageDeletionListeners } from 'app/store/middleware/listenerMiddleware/listeners/imageDeletionListeners';
 import { addImageRemovedFromBoardFulfilledListener } from 'app/store/middleware/listenerMiddleware/listeners/imageRemovedFromBoard';
-import { addImagesStarredListener } from 'app/store/middleware/listenerMiddleware/listeners/imagesStarred';
-import { addImagesUnstarredListener } from 'app/store/middleware/listenerMiddleware/listeners/imagesUnstarred';
-import { addImageToDeleteSelectedListener } from 'app/store/middleware/listenerMiddleware/listeners/imageToDeleteSelected';
 import { addImageUploadedFulfilledListener } from 'app/store/middleware/listenerMiddleware/listeners/imageUploaded';
 import { addModelSelectedListener } from 'app/store/middleware/listenerMiddleware/listeners/modelSelected';
 import { addModelsLoadedListener } from 'app/store/middleware/listenerMiddleware/listeners/modelsLoaded';
@@ -27,7 +19,6 @@ import { addSocketConnectedEventListener } from 'app/store/middleware/listenerMi
 import type { AppDispatch, RootState } from 'app/store/store';
 
 import { addArchivedOrDeletedBoardListener } from './listeners/addArchivedOrDeletedBoardListener';
-import { addEnqueueRequestedUpscale } from './listeners/enqueueRequestedUpscale';
 
 export const listenerMiddleware = createListenerMiddleware();
 
@@ -47,27 +38,12 @@ export const addAppListener = addListener.withTypes<RootState, AppDispatch>();
 addImageUploadedFulfilledListener(startAppListening);
 
 // Image deleted
-addImageDeletionListeners(startAppListening);
 addDeleteBoardAndImagesFulfilledListener(startAppListening);
-addImageToDeleteSelectedListener(startAppListening);
-
-// Image starred
-addImagesStarredListener(startAppListening);
-addImagesUnstarredListener(startAppListening);
-
-// Gallery
-addGalleryImageClickedListener(startAppListening);
-addGalleryOffsetChangedListener(startAppListening);
 
 // User Invoked
-addEnqueueRequestedLinear(startAppListening);
-addEnqueueRequestedUpscale(startAppListening);
 addAnyEnqueuedListener(startAppListening);
 addBatchEnqueuedListener(startAppListening);
 
-// Canvas actions
-addStagingListeners(startAppListening);
-
 // Socket.IO
 addSocketConnectedEventListener(startAppListening);
 

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

@@ -25,7 +25,7 @@ export const addArchivedOrDeletedBoardListener = (startAppListening: AppStartLis
     matcher: matchAnyBoardDeleted,
     effect: (action, { dispatch, getState }) => {
       const state = getState();
-      const deletedBoardId = action.meta.arg.originalArgs;
+      const deletedBoardId = action.meta.arg.originalArgs.board_id;
       const { autoAddBoardId, selectedBoardId } = state.gallery;
 
       // If the deleted board was currently selected, we should reset the selected board to uncategorized

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

@@ -1,46 +0,0 @@
-import { isAnyOf } from '@reduxjs/toolkit';
-import { logger } from 'app/logging/logger';
-import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
-import { canvasReset, newSessionRequested } from 'features/controlLayers/store/actions';
-import { stagingAreaReset } from 'features/controlLayers/store/canvasStagingAreaSlice';
-import { toast } from 'features/toast/toast';
-import { t } from 'i18next';
-import { queueApi } from 'services/api/endpoints/queue';
-
-const log = logger('canvas');
-
-const matchCanvasOrStagingAreaReset = isAnyOf(stagingAreaReset, canvasReset, newSessionRequested);
-
-export const addStagingListeners = (startAppListening: AppStartListening) => {
-  startAppListening({
-    matcher: matchCanvasOrStagingAreaReset,
-    effect: async (_, { dispatch }) => {
-      try {
-        const req = dispatch(
-          queueApi.endpoints.cancelByBatchDestination.initiate(
-            { destination: 'canvas' },
-            { fixedCacheKey: 'cancelByBatchOrigin' }
-          )
-        );
-        const { canceled } = await req.unwrap();
-        req.reset();
-
-        if (canceled > 0) {
-          log.debug(`Canceled ${canceled} canvas batches`);
-          toast({
-            id: 'CANCEL_BATCH_SUCCEEDED',
-            title: t('queue.cancelBatchSucceeded'),
-            status: 'success',
-          });
-        }
-      } catch {
-        log.error('Failed to cancel canvas batches');
-        toast({
-          id: 'CANCEL_BATCH_FAILED',
-          title: t('queue.cancelBatchFailed'),
-          status: 'error',
-        });
-      }
-    },
-  });
-};

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

@@ -1,15 +1,29 @@
 import { createAction } from '@reduxjs/toolkit';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
+import { selectLastSelectedImage } from 'features/gallery/store/gallerySelectors';
+import { imageSelected } from 'features/gallery/store/gallerySlice';
+import { imagesApi } from 'services/api/endpoints/images';
 
 export const appStarted = createAction('app/appStarted');
 
 export const addAppStartedListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: appStarted,
-    effect: (action, { unsubscribe, cancelActiveListeners }) => {
+    effect: async (action, { unsubscribe, cancelActiveListeners, take, getState, dispatch }) => {
       // this should only run once
       cancelActiveListeners();
       unsubscribe();
+
+      // ensure an image is selected when we load the first board
+      const firstImageLoad = await take(imagesApi.endpoints.getImageNames.matchFulfilled);
+      if (firstImageLoad !== null) {
+        const [{ payload }] = firstImageLoad;
+        const selectedImage = selectLastSelectedImage(getState());
+        if (selectedImage) {
+          return;
+        }
+        dispatch(imageSelected(payload.image_names.at(0) ?? null));
+      }
     },
   });
 };

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

@@ -1,9 +1,9 @@
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
+import { truncate } from 'es-toolkit/compat';
 import { zPydanticValidationError } from 'features/system/store/zodSchemas';
 import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
-import { truncate } from 'lodash-es';
 import { serializeError } from 'serialize-error';
 import { queueApi } from 'services/api/endpoints/queue';
 import type { JsonObject } from 'type-fest';

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

@@ -1,6 +1,7 @@
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
+import { selectRefImagesSlice } from 'features/controlLayers/store/refImagesSlice';
 import { selectCanvasSlice } from 'features/controlLayers/store/selectors';
-import { getImageUsage } from 'features/deleteImageModal/store/selectors';
+import { getImageUsage } from 'features/deleteImageModal/store/state';
 import { nodeEditorReset } from 'features/nodes/store/nodesSlice';
 import { selectNodesSlice } from 'features/nodes/store/selectors';
 import { selectUpscaleSlice } from 'features/parameters/store/upscaleSlice';
@@ -20,9 +21,10 @@ export const addDeleteBoardAndImagesFulfilledListener = (startAppListening: AppS
       const nodes = selectNodesSlice(state);
       const canvas = selectCanvasSlice(state);
       const upscale = selectUpscaleSlice(state);
+      const refImages = selectRefImagesSlice(state);
 
       deleted_images.forEach((image_name) => {
-        const imageUsage = getImageUsage(nodes, canvas, upscale, image_name);
+        const imageUsage = getImageUsage(nodes, canvas, upscale, refImages, image_name);
 
         if (imageUsage.isNodesImage && !wasNodeEditorReset) {
           dispatch(nodeEditorReset());

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

@@ -1,6 +1,6 @@
 import { isAnyOf } from '@reduxjs/toolkit';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
-import { selectListImagesQueryArgs } from 'features/gallery/store/gallerySelectors';
+import { selectGetImageNamesQueryArgs, selectSelectedBoardId } from 'features/gallery/store/gallerySelectors';
 import { boardIdSelected, galleryViewChanged, imageSelected } from 'features/gallery/store/gallerySlice';
 import { imagesApi } from 'services/api/endpoints/images';
 
@@ -11,36 +11,35 @@ export const addBoardIdSelectedListener = (startAppListening: AppStartListening)
       // Cancel any in-progress instances of this listener, we don't want to select an image from a previous board
       cancelActiveListeners();
 
+      if (boardIdSelected.match(action) && action.payload.selectedImageName) {
+        // This action already has a selected image name, we trust it is valid
+        return;
+      }
+
       const state = getState();
 
-      const queryArgs = selectListImagesQueryArgs(state);
+      const board_id = selectSelectedBoardId(state);
+
+      const queryArgs = { ...selectGetImageNamesQueryArgs(state), board_id };
 
       // wait until the board has some images - maybe it already has some from a previous fetch
       // must use getState() to ensure we do not have stale state
       const isSuccess = await condition(
-        () => imagesApi.endpoints.listImages.select(queryArgs)(getState()).isSuccess,
+        () => imagesApi.endpoints.getImageNames.select(queryArgs)(getState()).isSuccess,
         5000
       );
 
-      if (isSuccess) {
-        // the board was just changed - we can select the first image
-        const { data: boardImagesData } = imagesApi.endpoints.listImages.select(queryArgs)(getState());
-
-        if (boardImagesData && boardIdSelected.match(action) && action.payload.selectedImageName) {
-          const selectedImage = boardImagesData.items.find(
-            (item) => item.image_name === action.payload.selectedImageName
-          );
-          dispatch(imageSelected(selectedImage || null));
-        } else if (boardImagesData) {
-          dispatch(imageSelected(boardImagesData.items[0] || null));
-        } else {
-          // board has no images - deselect
-          dispatch(imageSelected(null));
-        }
-      } else {
-        // fallback - deselect
+      if (!isSuccess) {
         dispatch(imageSelected(null));
+        return;
       }
+
+      // the board was just changed - we can select the first image
+      const imageNames = imagesApi.endpoints.getImageNames.select(queryArgs)(getState()).data?.image_names;
+
+      const imageToSelect = imageNames?.at(0) ?? null;
+
+      dispatch(imageSelected(imageToSelect));
     },
   });
 };

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

@@ -1,123 +0,0 @@
-import type { AlertStatus } from '@invoke-ai/ui-library';
-import { createAction } from '@reduxjs/toolkit';
-import { logger } from 'app/logging/logger';
-import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
-import { extractMessageFromAssertionError } from 'common/util/extractMessageFromAssertionError';
-import { withResult, withResultAsync } from 'common/util/result';
-import { parseify } from 'common/util/serialize';
-import { $canvasManager } from 'features/controlLayers/store/ephemeral';
-import { prepareLinearUIBatch } from 'features/nodes/util/graph/buildLinearBatchConfig';
-import { buildChatGPT4oGraph } from 'features/nodes/util/graph/generation/buildChatGPT4oGraph';
-import { buildCogView4Graph } from 'features/nodes/util/graph/generation/buildCogView4Graph';
-import { buildFLUXGraph } from 'features/nodes/util/graph/generation/buildFLUXGraph';
-import { buildImagen3Graph } from 'features/nodes/util/graph/generation/buildImagen3Graph';
-import { buildImagen4Graph } from 'features/nodes/util/graph/generation/buildImagen4Graph';
-import { buildSD1Graph } from 'features/nodes/util/graph/generation/buildSD1Graph';
-import { buildSD3Graph } from 'features/nodes/util/graph/generation/buildSD3Graph';
-import { buildSDXLGraph } from 'features/nodes/util/graph/generation/buildSDXLGraph';
-import { UnsupportedGenerationModeError } from 'features/nodes/util/graph/types';
-import { toast } from 'features/toast/toast';
-import { serializeError } from 'serialize-error';
-import { enqueueMutationFixedCacheKeyOptions, queueApi } from 'services/api/endpoints/queue';
-import { assert, AssertionError } from 'tsafe';
-
-const log = logger('generation');
-
-export const enqueueRequestedCanvas = createAction<{ prepend: boolean }>('app/enqueueRequestedCanvas');
-
-export const addEnqueueRequestedLinear = (startAppListening: AppStartListening) => {
-  startAppListening({
-    actionCreator: enqueueRequestedCanvas,
-    effect: async (action, { getState, dispatch }) => {
-      log.debug('Enqueue requested');
-      const state = getState();
-      const { prepend } = action.payload;
-
-      const manager = $canvasManager.get();
-      assert(manager, 'No canvas manager');
-
-      const model = state.params.model;
-      assert(model, 'No model found in state');
-      const base = model.base;
-
-      const buildGraphResult = await withResultAsync(async () => {
-        switch (base) {
-          case 'sdxl':
-            return await buildSDXLGraph(state, manager);
-          case 'sd-1':
-          case `sd-2`:
-            return await buildSD1Graph(state, manager);
-          case `sd-3`:
-            return await buildSD3Graph(state, manager);
-          case `flux`:
-            return await buildFLUXGraph(state, manager);
-          case 'cogview4':
-            return await buildCogView4Graph(state, manager);
-          case 'imagen3':
-            return await buildImagen3Graph(state, manager);
-          case 'imagen4':
-            return await buildImagen4Graph(state, manager);
-          case 'chatgpt-4o':
-            return await buildChatGPT4oGraph(state, manager);
-          default:
-            assert(false, `No graph builders for base ${base}`);
-        }
-      });
-
-      if (buildGraphResult.isErr()) {
-        let title = 'Failed to build graph';
-        let status: AlertStatus = 'error';
-        let description: string | null = null;
-        if (buildGraphResult.error instanceof AssertionError) {
-          description = extractMessageFromAssertionError(buildGraphResult.error);
-        } else if (buildGraphResult.error instanceof UnsupportedGenerationModeError) {
-          title = 'Unsupported generation mode';
-          description = buildGraphResult.error.message;
-          status = 'warning';
-        }
-        const error = serializeError(buildGraphResult.error);
-        log.error({ error }, 'Failed to build graph');
-        toast({
-          status,
-          title,
-          description,
-        });
-        return;
-      }
-
-      const { g, seedFieldIdentifier, positivePromptFieldIdentifier } = buildGraphResult.value;
-
-      const destination = state.canvasSettings.sendToCanvas ? 'canvas' : 'gallery';
-
-      const prepareBatchResult = withResult(() =>
-        prepareLinearUIBatch({
-          state,
-          g,
-          prepend,
-          seedFieldIdentifier,
-          positivePromptFieldIdentifier,
-          origin: 'canvas',
-          destination,
-        })
-      );
-
-      if (prepareBatchResult.isErr()) {
-        log.error({ error: serializeError(prepareBatchResult.error) }, 'Failed to prepare batch');
-        return;
-      }
-
-      const req = dispatch(
-        queueApi.endpoints.enqueueBatch.initiate(prepareBatchResult.value, enqueueMutationFixedCacheKeyOptions)
-      );
-
-      try {
-        await req.unwrap();
-        log.debug(parseify({ batchConfig: prepareBatchResult.value }), 'Enqueued batch');
-      } catch (error) {
-        log.error({ error: serializeError(error as Error) }, 'Failed to enqueue batch');
-      } finally {
-        req.reset();
-      }
-    },
-  });
-};

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

@@ -1,44 +0,0 @@
-import { createAction } from '@reduxjs/toolkit';
-import { logger } from 'app/logging/logger';
-import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
-import { parseify } from 'common/util/serialize';
-import { prepareLinearUIBatch } from 'features/nodes/util/graph/buildLinearBatchConfig';
-import { buildMultidiffusionUpscaleGraph } from 'features/nodes/util/graph/buildMultidiffusionUpscaleGraph';
-import { serializeError } from 'serialize-error';
-import { enqueueMutationFixedCacheKeyOptions, queueApi } from 'services/api/endpoints/queue';
-
-const log = logger('generation');
-
-export const enqueueRequestedUpscaling = createAction<{ prepend: boolean }>('app/enqueueRequestedUpscaling');
-
-export const addEnqueueRequestedUpscale = (startAppListening: AppStartListening) => {
-  startAppListening({
-    actionCreator: enqueueRequestedUpscaling,
-    effect: async (action, { getState, dispatch }) => {
-      const state = getState();
-      const { prepend } = action.payload;
-
-      const { g, seedFieldIdentifier, positivePromptFieldIdentifier } = await buildMultidiffusionUpscaleGraph(state);
-
-      const batchConfig = prepareLinearUIBatch({
-        state,
-        g,
-        prepend,
-        seedFieldIdentifier,
-        positivePromptFieldIdentifier,
-        origin: 'upscaling',
-        destination: 'gallery',
-      });
-
-      const req = dispatch(queueApi.endpoints.enqueueBatch.initiate(batchConfig, enqueueMutationFixedCacheKeyOptions));
-      try {
-        await req.unwrap();
-        log.debug(parseify({ batchConfig }), 'Enqueued batch');
-      } catch (error) {
-        log.error({ error: serializeError(error as Error) }, 'Failed to enqueue batch');
-      } finally {
-        req.reset();
-      }
-    },
-  });
-};

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

@@ -1,73 +0,0 @@
-import { createAction } from '@reduxjs/toolkit';
-import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
-import { selectListImagesQueryArgs } from 'features/gallery/store/gallerySelectors';
-import { imageToCompareChanged, selectionChanged } from 'features/gallery/store/gallerySlice';
-import { imagesApi } from 'services/api/endpoints/images';
-import type { ImageDTO } from 'services/api/types';
-
-export const galleryImageClicked = createAction<{
-  imageDTO: ImageDTO;
-  shiftKey: boolean;
-  ctrlKey: boolean;
-  metaKey: boolean;
-  altKey: boolean;
-}>('gallery/imageClicked');
-
-/**
- * This listener handles the logic for selecting images in the gallery.
- *
- * Previously, this logic was in a `useCallback` with the whole gallery selection as a dependency. Every time
- * the selection changed, the callback got recreated and all images rerendered. This could easily block for
- * hundreds of ms, more for lower end devices.
- *
- * Moving this logic into a listener means we don't need to recalculate anything dynamically and the gallery
- * is much more responsive.
- */
-
-export const addGalleryImageClickedListener = (startAppListening: AppStartListening) => {
-  startAppListening({
-    actionCreator: galleryImageClicked,
-    effect: (action, { dispatch, getState }) => {
-      const { imageDTO, shiftKey, ctrlKey, metaKey, altKey } = action.payload;
-      const state = getState();
-      const queryArgs = selectListImagesQueryArgs(state);
-      const queryResult = imagesApi.endpoints.listImages.select(queryArgs)(state);
-
-      if (!queryResult.data) {
-        // Should never happen if we have clicked a gallery image
-        return;
-      }
-
-      const imageDTOs = queryResult.data.items;
-      const selection = state.gallery.selection;
-
-      if (altKey) {
-        if (state.gallery.imageToCompare?.image_name === imageDTO.image_name) {
-          dispatch(imageToCompareChanged(null));
-        } else {
-          dispatch(imageToCompareChanged(imageDTO));
-        }
-      } else if (shiftKey) {
-        const rangeEndImageName = imageDTO.image_name;
-        const lastSelectedImage = selection[selection.length - 1]?.image_name;
-        const lastClickedIndex = imageDTOs.findIndex((n) => n.image_name === lastSelectedImage);
-        const currentClickedIndex = imageDTOs.findIndex((n) => n.image_name === rangeEndImageName);
-        if (lastClickedIndex > -1 && currentClickedIndex > -1) {
-          // We have a valid range!
-          const start = Math.min(lastClickedIndex, currentClickedIndex);
-          const end = Math.max(lastClickedIndex, currentClickedIndex);
-          const imagesToSelect = imageDTOs.slice(start, end + 1);
-          dispatch(selectionChanged(selection.concat(imagesToSelect)));
-        }
-      } else if (ctrlKey || metaKey) {
-        if (selection.some((i) => i.image_name === imageDTO.image_name) && selection.length > 1) {
-          dispatch(selectionChanged(selection.filter((n) => n.image_name !== imageDTO.image_name)));
-        } else {
-          dispatch(selectionChanged(selection.concat(imageDTO)));
-        }
-      } else {
-        dispatch(selectionChanged([imageDTO]));
-      }
-    },
-  });
-};

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

@@ -1,119 +0,0 @@
-import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
-import { selectListImagesQueryArgs } from 'features/gallery/store/gallerySelectors';
-import { imageToCompareChanged, offsetChanged, selectionChanged } from 'features/gallery/store/gallerySlice';
-import { imagesApi } from 'services/api/endpoints/images';
-
-export const addGalleryOffsetChangedListener = (startAppListening: AppStartListening) => {
-  /**
-   * When the user changes pages in the gallery, we need to wait until the next page of images is loaded, then maybe
-   * update the selection.
-   *
-   * There are a three scenarios:
-   *
-   * 1. The page is changed by clicking the pagination buttons. No changes to selection are needed.
-   *
-   * 2. The page is changed by using the arrow keys (without alt).
-   * - When going backwards, select the last image.
-   * - When going forwards, select the first image.
-   *
-   * 3. The page is changed by using the arrows keys with alt. This means the user is changing the comparison image.
-   * - When going backwards, select the last image _as the comparison image_.
-   * - When going forwards, select the first image _as the comparison image_.
-   */
-  startAppListening({
-    actionCreator: offsetChanged,
-    effect: async (action, { dispatch, getState, getOriginalState, take, cancelActiveListeners }) => {
-      // Cancel any active listeners to prevent the selection from changing without user input
-      cancelActiveListeners();
-
-      const { withHotkey } = action.payload;
-
-      if (!withHotkey) {
-        // User changed pages by clicking the pagination buttons - no changes to selection
-        return;
-      }
-
-      const originalState = getOriginalState();
-      const prevOffset = originalState.gallery.offset;
-      const offset = getState().gallery.offset;
-
-      if (offset === prevOffset) {
-        // The page didn't change - bail
-        return;
-      }
-
-      /**
-       * We need to wait until the next page of images is loaded before updating the selection, so we use the correct
-       * page of images.
-       *
-       * The simplest way to do it would be to use `take` to wait for the next fulfilled action, but RTK-Q doesn't
-       * dispatch an action on cache hits. This means the `take` will only return if the cache is empty. If the user
-       * changes to a cached page - a common situation - the `take` will never resolve.
-       *
-       * So we need to take a two-step approach. First, check if we have data in the cache for the page of images. If
-       * we have data cached, use it to update the selection. If we don't have data cached, wait for the next fulfilled
-       * action, which updates the cache, then use the cache to update the selection.
-       */
-
-      // Check if we have data in the cache for the page of images
-      const queryArgs = selectListImagesQueryArgs(getState());
-      let { data } = imagesApi.endpoints.listImages.select(queryArgs)(getState());
-
-      // No data yet - wait for the network request to complete
-      if (!data) {
-        const takeResult = await take(imagesApi.endpoints.listImages.matchFulfilled, 5000);
-        if (!takeResult) {
-          // The request didn't complete in time - bail
-          return;
-        }
-        data = takeResult[0].payload;
-      }
-
-      // We awaited a network request - state could have changed, get fresh state
-      const state = getState();
-      const { selection, imageToCompare } = state.gallery;
-      const imageDTOs = data?.items;
-
-      if (!imageDTOs) {
-        // The page didn't load - bail
-        return;
-      }
-
-      if (withHotkey === 'arrow') {
-        // User changed pages by using the arrow keys - selection changes to first or last image depending
-        if (offset < prevOffset) {
-          // We've gone backwards
-          const lastImage = imageDTOs[imageDTOs.length - 1];
-          if (!selection.some((selectedImage) => selectedImage.image_name === lastImage?.image_name)) {
-            dispatch(selectionChanged(lastImage ? [lastImage] : []));
-          }
-        } else {
-          // We've gone forwards
-          const firstImage = imageDTOs[0];
-          if (!selection.some((selectedImage) => selectedImage.image_name === firstImage?.image_name)) {
-            dispatch(selectionChanged(firstImage ? [firstImage] : []));
-          }
-        }
-        return;
-      }
-
-      if (withHotkey === 'alt+arrow') {
-        // User changed pages by using the arrow keys with alt - comparison image changes to first or last depending
-        if (offset < prevOffset) {
-          // We've gone backwards
-          const lastImage = imageDTOs[imageDTOs.length - 1];
-          if (lastImage && imageToCompare?.image_name !== lastImage.image_name) {
-            dispatch(imageToCompareChanged(lastImage));
-          }
-        } else {
-          // We've gone forwards
-          const firstImage = imageDTOs[0];
-          if (firstImage && imageToCompare?.image_name !== firstImage.image_name) {
-            dispatch(imageToCompareChanged(firstImage));
-          }
-        }
-        return;
-      }
-    },
-  });
-};

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

@@ -1,9 +1,9 @@
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { parseify } from 'common/util/serialize';
+import { size } from 'es-toolkit/compat';
 import { $templates } from 'features/nodes/store/nodesSlice';
 import { parseSchema } from 'features/nodes/util/schema/parseSchema';
-import { size } from 'lodash-es';
 import { serializeError } from 'serialize-error';
 import { appInfoApi } from 'services/api/endpoints/appInfo';
 import type { JsonObject } from 'type-fest';

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

@@ -8,16 +8,16 @@ export const addImageAddedToBoardFulfilledListener = (startAppListening: AppStar
   startAppListening({
     matcher: imagesApi.endpoints.addImageToBoard.matchFulfilled,
     effect: (action) => {
-      const { board_id, imageDTO } = action.meta.arg.originalArgs;
-      log.debug({ board_id, imageDTO }, 'Image added to board');
+      const { board_id, image_name } = action.meta.arg.originalArgs;
+      log.debug({ board_id, image_name }, 'Image added to board');
     },
   });
 
   startAppListening({
     matcher: imagesApi.endpoints.addImageToBoard.matchRejected,
     effect: (action) => {
-      const { board_id, imageDTO } = action.meta.arg.originalArgs;
-      log.debug({ board_id, imageDTO }, 'Problem adding image to board');
+      const { board_id, image_name } = action.meta.arg.originalArgs;
+      log.debug({ board_id, image_name }, 'Problem adding image to board');
     },
   });
 };

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

@@ -1,221 +0,0 @@
-import { logger } from 'app/logging/logger';
-import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
-import type { AppDispatch, RootState } from 'app/store/store';
-import { entityDeleted, referenceImageIPAdapterImageChanged } from 'features/controlLayers/store/canvasSlice';
-import { selectCanvasSlice } from 'features/controlLayers/store/selectors';
-import { getEntityIdentifier } from 'features/controlLayers/store/types';
-import { imageDeletionConfirmed } from 'features/deleteImageModal/store/actions';
-import { isModalOpenChanged } from 'features/deleteImageModal/store/slice';
-import { selectListImagesQueryArgs } from 'features/gallery/store/gallerySelectors';
-import { imageSelected } from 'features/gallery/store/gallerySlice';
-import { fieldImageCollectionValueChanged, fieldImageValueChanged } from 'features/nodes/store/nodesSlice';
-import { isImageFieldCollectionInputInstance, isImageFieldInputInstance } from 'features/nodes/types/field';
-import { isInvocationNode } from 'features/nodes/types/invocation';
-import { forEach, intersectionBy } from 'lodash-es';
-import { imagesApi } from 'services/api/endpoints/images';
-import type { ImageDTO } from 'services/api/types';
-import type { Param0 } from 'tsafe';
-
-const log = logger('gallery');
-
-//TODO(psyche): handle image deletion (canvas staging area?)
-
-// Some utils to delete images from different parts of the app
-const deleteNodesImages = (state: RootState, dispatch: AppDispatch, imageDTO: ImageDTO) => {
-  const actions: Param0<typeof dispatch>[] = [];
-  state.nodes.present.nodes.forEach((node) => {
-    if (!isInvocationNode(node)) {
-      return;
-    }
-
-    forEach(node.data.inputs, (input) => {
-      if (isImageFieldInputInstance(input) && input.value?.image_name === imageDTO.image_name) {
-        actions.push(
-          fieldImageValueChanged({
-            nodeId: node.data.id,
-            fieldName: input.name,
-            value: undefined,
-          })
-        );
-        return;
-      }
-      if (isImageFieldCollectionInputInstance(input)) {
-        actions.push(
-          fieldImageCollectionValueChanged({
-            nodeId: node.data.id,
-            fieldName: input.name,
-            value: input.value?.filter((value) => value?.image_name !== imageDTO.image_name),
-          })
-        );
-      }
-    });
-  });
-
-  actions.forEach(dispatch);
-};
-
-const deleteControlLayerImages = (state: RootState, dispatch: AppDispatch, imageDTO: ImageDTO) => {
-  selectCanvasSlice(state).controlLayers.entities.forEach(({ id, objects }) => {
-    let shouldDelete = false;
-    for (const obj of objects) {
-      if (obj.type === 'image' && obj.image.image_name === imageDTO.image_name) {
-        shouldDelete = true;
-        break;
-      }
-    }
-    if (shouldDelete) {
-      dispatch(entityDeleted({ entityIdentifier: { id, type: 'control_layer' } }));
-    }
-  });
-};
-
-const deleteReferenceImages = (state: RootState, dispatch: AppDispatch, imageDTO: ImageDTO) => {
-  selectCanvasSlice(state).referenceImages.entities.forEach((entity) => {
-    if (entity.ipAdapter.image?.image_name === imageDTO.image_name) {
-      dispatch(referenceImageIPAdapterImageChanged({ entityIdentifier: getEntityIdentifier(entity), imageDTO: null }));
-    }
-  });
-};
-
-const deleteRasterLayerImages = (state: RootState, dispatch: AppDispatch, imageDTO: ImageDTO) => {
-  selectCanvasSlice(state).rasterLayers.entities.forEach(({ id, objects }) => {
-    let shouldDelete = false;
-    for (const obj of objects) {
-      if (obj.type === 'image' && obj.image.image_name === imageDTO.image_name) {
-        shouldDelete = true;
-        break;
-      }
-    }
-    if (shouldDelete) {
-      dispatch(entityDeleted({ entityIdentifier: { id, type: 'raster_layer' } }));
-    }
-  });
-};
-
-export const addImageDeletionListeners = (startAppListening: AppStartListening) => {
-  // Handle single image deletion
-  startAppListening({
-    actionCreator: imageDeletionConfirmed,
-    effect: async (action, { dispatch, getState }) => {
-      const { imageDTOs, imagesUsage } = action.payload;
-
-      if (imageDTOs.length !== 1 || imagesUsage.length !== 1) {
-        // handle multiples in separate listener
-        return;
-      }
-
-      const imageDTO = imageDTOs[0];
-      const imageUsage = imagesUsage[0];
-
-      if (!imageDTO || !imageUsage) {
-        // satisfy noUncheckedIndexedAccess
-        return;
-      }
-
-      try {
-        const state = getState();
-        await dispatch(imagesApi.endpoints.deleteImage.initiate(imageDTO)).unwrap();
-
-        if (state.gallery.selection.some((i) => i.image_name === imageDTO.image_name)) {
-          // The deleted image was a selected image, we need to select the next image
-          const newSelection = state.gallery.selection.filter((i) => i.image_name !== imageDTO.image_name);
-
-          if (newSelection.length > 0) {
-            return;
-          }
-
-          // Get the current list of images and select the same index
-          const baseQueryArgs = selectListImagesQueryArgs(state);
-          const data = imagesApi.endpoints.listImages.select(baseQueryArgs)(state).data;
-
-          if (data) {
-            const deletedImageIndex = data.items.findIndex((i) => i.image_name === imageDTO.image_name);
-            const nextImage = data.items[deletedImageIndex + 1] ?? data.items[0] ?? null;
-            if (nextImage?.image_name === imageDTO.image_name) {
-              // If the next image is the same as the deleted one, it means it was the last image, reset selection
-              dispatch(imageSelected(null));
-            } else {
-              dispatch(imageSelected(nextImage));
-            }
-          }
-        }
-
-        deleteNodesImages(state, dispatch, imageDTO);
-        deleteReferenceImages(state, dispatch, imageDTO);
-        deleteRasterLayerImages(state, dispatch, imageDTO);
-        deleteControlLayerImages(state, dispatch, imageDTO);
-      } catch {
-        // no-op
-      } finally {
-        dispatch(isModalOpenChanged(false));
-      }
-    },
-  });
-
-  // Handle multiple image deletion
-  startAppListening({
-    actionCreator: imageDeletionConfirmed,
-    effect: async (action, { dispatch, getState }) => {
-      const { imageDTOs, imagesUsage } = action.payload;
-
-      if (imageDTOs.length <= 1 || imagesUsage.length <= 1) {
-        // handle singles in separate listener
-        return;
-      }
-
-      try {
-        const state = getState();
-        await dispatch(imagesApi.endpoints.deleteImages.initiate({ imageDTOs })).unwrap();
-
-        if (intersectionBy(state.gallery.selection, imageDTOs, 'image_name').length > 0) {
-          // Some selected images were deleted, need to select the next image
-          const queryArgs = selectListImagesQueryArgs(state);
-          const { data } = imagesApi.endpoints.listImages.select(queryArgs)(state);
-          if (data) {
-            // When we delete multiple images, we clear the selection. Then, the the next time we load images, we will
-            // select the first one. This is handled below in the listener for `imagesApi.endpoints.listImages.matchFulfilled`.
-            dispatch(imageSelected(null));
-          }
-        }
-
-        // We need to reset the features where the image is in use - none of these work if their image(s) don't exist
-
-        imageDTOs.forEach((imageDTO) => {
-          deleteNodesImages(state, dispatch, imageDTO);
-          deleteControlLayerImages(state, dispatch, imageDTO);
-          deleteReferenceImages(state, dispatch, imageDTO);
-          deleteRasterLayerImages(state, dispatch, imageDTO);
-        });
-      } catch {
-        // no-op
-      } finally {
-        dispatch(isModalOpenChanged(false));
-      }
-    },
-  });
-
-  // When we list images, if no images is selected, select the first one.
-  startAppListening({
-    matcher: imagesApi.endpoints.listImages.matchFulfilled,
-    effect: (action, { dispatch, getState }) => {
-      const selection = getState().gallery.selection;
-      if (selection.length === 0) {
-        dispatch(imageSelected(action.payload.items[0] ?? null));
-      }
-    },
-  });
-
-  startAppListening({
-    matcher: imagesApi.endpoints.deleteImage.matchFulfilled,
-    effect: (action) => {
-      log.debug({ imageDTO: action.meta.arg.originalArgs }, 'Image deleted');
-    },
-  });
-
-  startAppListening({
-    matcher: imagesApi.endpoints.deleteImage.matchRejected,
-    effect: (action) => {
-      log.debug({ imageDTO: action.meta.arg.originalArgs }, 'Unable to delete image');
-    },
-  });
-};

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

@@ -1,32 +0,0 @@
-import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
-import { imageDeletionConfirmed } from 'features/deleteImageModal/store/actions';
-import { selectImageUsage } from 'features/deleteImageModal/store/selectors';
-import { imagesToDeleteSelected, isModalOpenChanged } from 'features/deleteImageModal/store/slice';
-
-export const addImageToDeleteSelectedListener = (startAppListening: AppStartListening) => {
-  startAppListening({
-    actionCreator: imagesToDeleteSelected,
-    effect: (action, { dispatch, getState }) => {
-      const imageDTOs = action.payload;
-      const state = getState();
-      const { shouldConfirmOnDelete } = state.system;
-      const imagesUsage = selectImageUsage(getState());
-
-      const isImageInUse =
-        imagesUsage.some((i) => i.isRasterLayerImage) ||
-        imagesUsage.some((i) => i.isControlLayerImage) ||
-        imagesUsage.some((i) => i.isReferenceImage) ||
-        imagesUsage.some((i) => i.isInpaintMaskImage) ||
-        imagesUsage.some((i) => i.isUpscaleImage) ||
-        imagesUsage.some((i) => i.isNodesImage) ||
-        imagesUsage.some((i) => i.isRegionalGuidanceImage);
-
-      if (shouldConfirmOnDelete || isImageInUse) {
-        dispatch(isModalOpenChanged(true));
-        return;
-      }
-
-      dispatch(imageDeletionConfirmed({ imageDTOs, imagesUsage }));
-    },
-  });
-};

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

@@ -2,12 +2,12 @@ import { isAnyOf } from '@reduxjs/toolkit';
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import type { RootState } from 'app/store/store';
+import { omit } from 'es-toolkit/compat';
 import { imageUploadedClientSide } from 'features/gallery/store/actions';
 import { selectListBoardsQueryArgs } from 'features/gallery/store/gallerySelectors';
 import { boardIdSelected, galleryViewChanged } from 'features/gallery/store/gallerySlice';
 import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
-import { omit } from 'lodash-es';
 import { boardsApi } from 'services/api/endpoints/boards';
 import { imagesApi } from 'services/api/endpoints/images';
 import type { ImageDTO } from 'services/api/types';

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

@@ -1,30 +0,0 @@
-import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
-import { selectionChanged } from 'features/gallery/store/gallerySlice';
-import { imagesApi } from 'services/api/endpoints/images';
-import type { ImageDTO } from 'services/api/types';
-
-export const addImagesStarredListener = (startAppListening: AppStartListening) => {
-  startAppListening({
-    matcher: imagesApi.endpoints.starImages.matchFulfilled,
-    effect: (action, { dispatch, getState }) => {
-      const { updated_image_names: starredImages } = action.payload;
-
-      const state = getState();
-
-      const { selection } = state.gallery;
-      const updatedSelection: ImageDTO[] = [];
-
-      selection.forEach((selectedImageDTO) => {
-        if (starredImages.includes(selectedImageDTO.image_name)) {
-          updatedSelection.push({
-            ...selectedImageDTO,
-            starred: true,
-          });
-        } else {
-          updatedSelection.push(selectedImageDTO);
-        }
-      });
-      dispatch(selectionChanged(updatedSelection));
-    },
-  });
-};

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

@@ -1,30 +0,0 @@
-import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
-import { selectionChanged } from 'features/gallery/store/gallerySlice';
-import { imagesApi } from 'services/api/endpoints/images';
-import type { ImageDTO } from 'services/api/types';
-
-export const addImagesUnstarredListener = (startAppListening: AppStartListening) => {
-  startAppListening({
-    matcher: imagesApi.endpoints.unstarImages.matchFulfilled,
-    effect: (action, { dispatch, getState }) => {
-      const { updated_image_names: unstarredImages } = action.payload;
-
-      const state = getState();
-
-      const { selection } = state.gallery;
-      const updatedSelection: ImageDTO[] = [];
-
-      selection.forEach((selectedImageDTO) => {
-        if (unstarredImages.includes(selectedImageDTO.image_name)) {
-          updatedSelection.push({
-            ...selectedImageDTO,
-            starred: false,
-          });
-        } else {
-          updatedSelection.push(selectedImageDTO);
-        }
-      });
-      dispatch(selectionChanged(updatedSelection));
-    },
-  });
-};

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

@@ -1,14 +1,28 @@
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
-import { bboxSyncedToOptimalDimension } from 'features/controlLayers/store/canvasSlice';
+import { bboxSyncedToOptimalDimension, rgRefImageModelChanged } from 'features/controlLayers/store/canvasSlice';
 import { selectIsStaging } from 'features/controlLayers/store/canvasStagingAreaSlice';
 import { loraDeleted } from 'features/controlLayers/store/lorasSlice';
-import { modelChanged, vaeSelected } from 'features/controlLayers/store/paramsSlice';
-import { selectBboxModelBase } from 'features/controlLayers/store/selectors';
+import { modelChanged, syncedToOptimalDimension, vaeSelected } from 'features/controlLayers/store/paramsSlice';
+import { refImageModelChanged, selectReferenceImageEntities } from 'features/controlLayers/store/refImagesSlice';
+import {
+  selectAllEntitiesOfType,
+  selectBboxModelBase,
+  selectCanvasSlice,
+} from 'features/controlLayers/store/selectors';
+import { getEntityIdentifier } from 'features/controlLayers/store/types';
 import { modelSelected } from 'features/parameters/store/actions';
 import { zParameterModel } from 'features/parameters/types/parameterSchemas';
 import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
+import { selectGlobalRefImageModels, selectRegionalRefImageModels } from 'services/api/hooks/modelsByType';
+import type { AnyModelConfig } from 'services/api/types';
+import {
+  isChatGPT4oModelConfig,
+  isFluxKontextApiModelConfig,
+  isFluxKontextModelConfig,
+  isFluxReduxModelConfig,
+} from 'services/api/types';
 
 const log = logger('models');
 
@@ -25,9 +39,8 @@ export const addModelSelectedListener = (startAppListening: AppStartListening) =
       }
 
       const newModel = result.data;
-
-      const newBaseModel = newModel.base;
-      const didBaseModelChange = state.params.model?.base !== newBaseModel;
+      const newBase = newModel.base;
+      const didBaseModelChange = state.params.model?.base !== newBase;
 
       if (didBaseModelChange) {
         // we may need to reset some incompatible submodels
@@ -35,7 +48,7 @@ export const addModelSelectedListener = (startAppListening: AppStartListening) =
 
         // handle incompatible loras
         state.loras.loras.forEach((lora) => {
-          if (lora.model.base !== newBaseModel) {
+          if (lora.model.base !== newBase) {
             dispatch(loraDeleted({ id: lora.id }));
             modelsCleared += 1;
           }
@@ -43,20 +56,82 @@ export const addModelSelectedListener = (startAppListening: AppStartListening) =
 
         // handle incompatible vae
         const { vae } = state.params;
-        if (vae && vae.base !== newBaseModel) {
+        if (vae && vae.base !== newBase) {
           dispatch(vaeSelected(null));
           modelsCleared += 1;
         }
 
-        // handle incompatible controlnets
-        // state.canvas.present.controlAdapters.entities.forEach((ca) => {
-        //   if (ca.model?.base !== newBaseModel) {
-        //     modelsCleared += 1;
-        //     if (ca.isEnabled) {
-        //       dispatch(entityIsEnabledToggled({ entityIdentifier: { id: ca.id, type: 'control_adapter' } }));
-        //     }
-        //   }
-        // });
+        // Handle incompatible reference image models - switch to first compatible model, with some smart logic
+        // to choose the best available model based on the new main model.
+        const allRefImageModels = selectGlobalRefImageModels(state).filter(({ base }) => base === newBase);
+
+        let newGlobalRefImageModel = null;
+
+        // Certain models require the ref image model to be the same as the main model - others just need a matching
+        // base. Helper to grab the first exact match or the first available model if no exact match is found.
+        const exactMatchOrFirst = <T extends AnyModelConfig>(candidates: T[]): T | null =>
+          candidates.find(({ key }) => key === newModel.key) ?? candidates[0] ?? null;
+
+        // The only way we can differentiate between FLUX and FLUX Kontext is to check for "kontext" in the name
+        if (newModel.base === 'flux' && newModel.name.toLowerCase().includes('kontext')) {
+          const fluxKontextDevModels = allRefImageModels.filter(isFluxKontextModelConfig);
+          newGlobalRefImageModel = exactMatchOrFirst(fluxKontextDevModels);
+        } else if (newModel.base === 'chatgpt-4o') {
+          const chatGPT4oModels = allRefImageModels.filter(isChatGPT4oModelConfig);
+          newGlobalRefImageModel = exactMatchOrFirst(chatGPT4oModels);
+        } else if (newModel.base === 'flux-kontext') {
+          const fluxKontextApiModels = allRefImageModels.filter(isFluxKontextApiModelConfig);
+          newGlobalRefImageModel = exactMatchOrFirst(fluxKontextApiModels);
+        } else if (newModel.base === 'flux') {
+          const fluxReduxModels = allRefImageModels.filter(isFluxReduxModelConfig);
+          newGlobalRefImageModel = fluxReduxModels[0] ?? null;
+        } else {
+          newGlobalRefImageModel = allRefImageModels[0] ?? null;
+        }
+
+        // All ref image entities are updated to use the same new model
+        const refImageEntities = selectReferenceImageEntities(state);
+        for (const entity of refImageEntities) {
+          const shouldUpdateModel =
+            (entity.config.model && entity.config.model.base !== newBase) ||
+            (!entity.config.model && newGlobalRefImageModel);
+
+          if (shouldUpdateModel) {
+            dispatch(
+              refImageModelChanged({
+                id: entity.id,
+                modelConfig: newGlobalRefImageModel,
+              })
+            );
+            modelsCleared += 1;
+          }
+        }
+
+        // For regional guidance, there is no smart logic - we just pick the first available model.
+        const newRegionalRefImageModel = selectRegionalRefImageModels(state)[0] ?? null;
+
+        // All regional guidance entities are updated to use the same new model.
+        const canvasState = selectCanvasSlice(state);
+        const canvasRegionalGuidanceEntities = selectAllEntitiesOfType(canvasState, 'regional_guidance');
+        for (const entity of canvasRegionalGuidanceEntities) {
+          for (const refImage of entity.referenceImages) {
+            // Only change the model if the current one is not compatible with the new base model.
+            const shouldUpdateModel =
+              (refImage.config.model && refImage.config.model.base !== newBase) ||
+              (!refImage.config.model && newRegionalRefImageModel);
+
+            if (shouldUpdateModel) {
+              dispatch(
+                rgRefImageModelChanged({
+                  entityIdentifier: getEntityIdentifier(entity),
+                  referenceImageId: refImage.id,
+                  modelConfig: newRegionalRefImageModel,
+                })
+              );
+              modelsCleared += 1;
+            }
+          }
+        }
 
         if (modelsCleared > 0) {
           toast({
@@ -71,9 +146,16 @@ export const addModelSelectedListener = (startAppListening: AppStartListening) =
       }
 
       dispatch(modelChanged({ model: newModel, previousModel: state.params.model }));
+
       const modelBase = selectBboxModelBase(state);
-      if (!selectIsStaging(state) && modelBase !== state.params.model?.base) {
-        dispatch(bboxSyncedToOptimalDimension());
+
+      if (modelBase !== state.params.model?.base) {
+        // Sync generate tab settings whenever the model base changes
+        dispatch(syncedToOptimalDimension());
+        if (!selectIsStaging(state)) {
+          // Canvas tab only syncs if not staging
+          dispatch(bboxSyncedToOptimalDimension());
+        }
       }
     },
   });

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

@@ -1,11 +1,7 @@
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import type { AppDispatch, RootState } from 'app/store/store';
-import {
-  controlLayerModelChanged,
-  referenceImageIPAdapterModelChanged,
-  rgIPAdapterModelChanged,
-} from 'features/controlLayers/store/canvasSlice';
+import { controlLayerModelChanged, rgRefImageModelChanged } from 'features/controlLayers/store/canvasSlice';
 import { loraDeleted } from 'features/controlLayers/store/lorasSlice';
 import {
   clipEmbedModelSelected,
@@ -15,8 +11,9 @@ import {
   t5EncoderModelSelected,
   vaeSelected,
 } from 'features/controlLayers/store/paramsSlice';
+import { refImageModelChanged, selectRefImagesSlice } from 'features/controlLayers/store/refImagesSlice';
 import { selectCanvasSlice } from 'features/controlLayers/store/selectors';
-import { getEntityIdentifier } from 'features/controlLayers/store/types';
+import { getEntityIdentifier, isFLUXReduxConfig, isIPAdapterConfig } from 'features/controlLayers/store/types';
 import { modelSelected } from 'features/parameters/store/actions';
 import { postProcessingModelChanged, upscaleModelChanged } from 'features/parameters/store/upscaleSlice';
 import {
@@ -210,12 +207,12 @@ const handleControlAdapterModels: ModelHandler = (models, state, dispatch, log)
 
 const handleIPAdapterModels: ModelHandler = (models, state, dispatch, log) => {
   const ipaModels = models.filter(isIPAdapterModelConfig);
-  selectCanvasSlice(state).referenceImages.entities.forEach((entity) => {
-    if (entity.ipAdapter.type !== 'ip_adapter') {
+  selectRefImagesSlice(state).entities.forEach((entity) => {
+    if (!isIPAdapterConfig(entity.config)) {
       return;
     }
 
-    const selectedIPAdapterModel = entity.ipAdapter.model;
+    const selectedIPAdapterModel = entity.config.model;
     // `null` is a valid IP adapter model - no need to do anything.
     if (!selectedIPAdapterModel) {
       return;
@@ -225,16 +222,16 @@ const handleIPAdapterModels: ModelHandler = (models, state, dispatch, log) => {
       return;
     }
     log.debug({ selectedIPAdapterModel }, 'Selected IP adapter model is not available, clearing');
-    dispatch(referenceImageIPAdapterModelChanged({ entityIdentifier: getEntityIdentifier(entity), modelConfig: null }));
+    dispatch(refImageModelChanged({ id: entity.id, modelConfig: null }));
   });
 
   selectCanvasSlice(state).regionalGuidance.entities.forEach((entity) => {
-    entity.referenceImages.forEach(({ id: referenceImageId, ipAdapter }) => {
-      if (ipAdapter.type !== 'ip_adapter') {
+    entity.referenceImages.forEach(({ id: referenceImageId, config }) => {
+      if (!isIPAdapterConfig(config)) {
         return;
       }
 
-      const selectedIPAdapterModel = ipAdapter.model;
+      const selectedIPAdapterModel = config.model;
       // `null` is a valid IP adapter model - no need to do anything.
       if (!selectedIPAdapterModel) {
         return;
@@ -245,7 +242,7 @@ const handleIPAdapterModels: ModelHandler = (models, state, dispatch, log) => {
       }
       log.debug({ selectedIPAdapterModel }, 'Selected IP adapter model is not available, clearing');
       dispatch(
-        rgIPAdapterModelChanged({ entityIdentifier: getEntityIdentifier(entity), referenceImageId, modelConfig: null })
+        rgRefImageModelChanged({ entityIdentifier: getEntityIdentifier(entity), referenceImageId, modelConfig: null })
       );
     });
   });
@@ -254,11 +251,11 @@ const handleIPAdapterModels: ModelHandler = (models, state, dispatch, log) => {
 const handleFLUXReduxModels: ModelHandler = (models, state, dispatch, log) => {
   const fluxReduxModels = models.filter(isFluxReduxModelConfig);
 
-  selectCanvasSlice(state).referenceImages.entities.forEach((entity) => {
-    if (entity.ipAdapter.type !== 'flux_redux') {
+  selectRefImagesSlice(state).entities.forEach((entity) => {
+    if (!isFLUXReduxConfig(entity.config)) {
       return;
     }
-    const selectedFLUXReduxModel = entity.ipAdapter.model;
+    const selectedFLUXReduxModel = entity.config.model;
     // `null` is a valid FLUX Redux model - no need to do anything.
     if (!selectedFLUXReduxModel) {
       return;
@@ -268,16 +265,16 @@ const handleFLUXReduxModels: ModelHandler = (models, state, dispatch, log) => {
       return;
     }
     log.debug({ selectedFLUXReduxModel }, 'Selected FLUX Redux model is not available, clearing');
-    dispatch(referenceImageIPAdapterModelChanged({ entityIdentifier: getEntityIdentifier(entity), modelConfig: null }));
+    dispatch(refImageModelChanged({ id: entity.id, modelConfig: null }));
   });
 
   selectCanvasSlice(state).regionalGuidance.entities.forEach((entity) => {
-    entity.referenceImages.forEach(({ id: referenceImageId, ipAdapter }) => {
-      if (ipAdapter.type !== 'flux_redux') {
+    entity.referenceImages.forEach(({ id: referenceImageId, config }) => {
+      if (!isFLUXReduxConfig(config)) {
         return;
       }
 
-      const selectedFLUXReduxModel = ipAdapter.model;
+      const selectedFLUXReduxModel = config.model;
       // `null` is a valid FLUX Redux model - no need to do anything.
       if (!selectedFLUXReduxModel) {
         return;
@@ -288,7 +285,7 @@ const handleFLUXReduxModels: ModelHandler = (models, state, dispatch, log) => {
       }
       log.debug({ selectedFLUXReduxModel }, 'Selected FLUX Redux model is not available, clearing');
       dispatch(
-        rgIPAdapterModelChanged({ entityIdentifier: getEntityIdentifier(entity), referenceImageId, modelConfig: null })
+        rgRefImageModelChanged({ entityIdentifier: getEntityIdentifier(entity), referenceImageId, modelConfig: null })
       );
     });
   });

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

@@ -1,7 +1,9 @@
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
+import { isNil } from 'es-toolkit';
 import { bboxHeightChanged, bboxWidthChanged } from 'features/controlLayers/store/canvasSlice';
 import { selectIsStaging } from 'features/controlLayers/store/canvasStagingAreaSlice';
 import {
+  heightChanged,
   setCfgRescaleMultiplier,
   setCfgScale,
   setGuidance,
@@ -9,6 +11,7 @@ import {
   setSteps,
   vaePrecisionChanged,
   vaeSelected,
+  widthChanged,
 } from 'features/controlLayers/store/paramsSlice';
 import { setDefaultSettings } from 'features/parameters/store/actions';
 import {
@@ -23,6 +26,7 @@ import {
   zParameterVAEModel,
 } from 'features/parameters/types/parameterSchemas';
 import { toast } from 'features/toast/toast';
+import { selectActiveTab } from 'features/ui/store/uiSelectors';
 import { t } from 'i18next';
 import { modelConfigsAdapterSelectors, modelsApi } from 'services/api/endpoints/models';
 import { isNonRefinerMainModelConfig } from 'services/api/types';
@@ -86,10 +90,16 @@ export const addSetDefaultSettingsListener = (startAppListening: AppStartListeni
           }
         }
 
-        if (cfg_rescale_multiplier) {
+        if (!isNil(cfg_rescale_multiplier)) {
           if (isParameterCFGRescaleMultiplier(cfg_rescale_multiplier)) {
             dispatch(setCfgRescaleMultiplier(cfg_rescale_multiplier));
           }
+        } else {
+          // Set this to 0 if it doesn't have a default. This value is
+          // easy to miss in the UI when users are resetting defaults
+          // and leaving it non-zero could lead to detrimental
+          // effects.
+          dispatch(setCfgRescaleMultiplier(0));
         }
 
         if (steps) {
@@ -106,15 +116,24 @@ export const addSetDefaultSettingsListener = (startAppListening: AppStartListeni
         const setSizeOptions = { updateAspectRatio: true, clamp: true };
 
         const isStaging = selectIsStaging(getState());
-        if (!isStaging && width) {
+        const activeTab = selectActiveTab(getState());
+        if (activeTab === 'generate') {
           if (isParameterWidth(width)) {
-            dispatch(bboxWidthChanged({ width, ...setSizeOptions }));
+            dispatch(widthChanged({ width, ...setSizeOptions }));
+          }
+          if (isParameterHeight(height)) {
+            dispatch(heightChanged({ height, ...setSizeOptions }));
           }
         }
 
-        if (!isStaging && height) {
-          if (isParameterHeight(height)) {
-            dispatch(bboxHeightChanged({ height, ...setSizeOptions }));
+        if (activeTab === 'canvas') {
+          if (!isStaging) {
+            if (isParameterWidth(width)) {
+              dispatch(bboxWidthChanged({ width, ...setSizeOptions }));
+            }
+            if (isParameterHeight(height)) {
+              dispatch(bboxHeightChanged({ height, ...setSizeOptions }));
+            }
           }
         }
 

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

@@ -1,8 +1,8 @@
+import { objectEquals } from '@observ33r/object-equals';
 import { createAction } from '@reduxjs/toolkit';
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { $baseUrl } from 'app/store/nanostores/baseUrl';
-import { isEqual } from 'lodash-es';
 import { atom } from 'nanostores';
 import { api } from 'services/api';
 import { modelsApi } from 'services/api/endpoints/models';
@@ -64,7 +64,7 @@ export const addSocketConnectedEventListener = (startAppListening: AppStartListe
         const nextQueueStatusData = await queueStatusRequest.unwrap();
 
         // If the queue hasn't changed, we don't need to do anything.
-        if (isEqual(prevQueueStatusData?.queue, nextQueueStatusData.queue)) {
+        if (objectEquals(prevQueueStatusData?.queue, nextQueueStatusData.queue)) {
           return;
         }
 

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

@@ -1,4 +1,3 @@
-import { useStore } from '@nanostores/react';
 import type { AppStore } from 'app/store/store';
 import { atom } from 'nanostores';
 
@@ -32,11 +31,3 @@ export const getStore = () => {
   }
   return store;
 };
-
-export const useAppStore = () => {
-  const store = useStore($store);
-  if (!store) {
-    throw new ReduxStoreNotInitialized();
-  }
-  return store;
-};

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

@@ -11,5 +11,7 @@ export const $false: ReadableAtom<boolean> = atom(false);
 /**
  * A fallback non-writable atom that always returns `true`, used when a nanostores atom is only conditionally available
  * in a hook or component.
+ *
+ * @knipignore
  */
 export const $true: ReadableAtom<boolean> = atom(true);

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

@@ -4,19 +4,19 @@ import { logger } from 'app/logging/logger';
 import { idbKeyValDriver } from 'app/store/enhancers/reduxRemember/driver';
 import { errorHandler } from 'app/store/enhancers/reduxRemember/errors';
 import { deepClone } from 'common/util/deepClone';
+import { keys, mergeWith, omit, pick } from 'es-toolkit/compat';
 import { changeBoardModalSlice } from 'features/changeBoardModal/store/slice';
 import { canvasSettingsPersistConfig, canvasSettingsSlice } from 'features/controlLayers/store/canvasSettingsSlice';
 import { canvasPersistConfig, canvasSlice, canvasUndoableConfig } from 'features/controlLayers/store/canvasSlice';
 import {
+  canvasSessionSlice,
   canvasStagingAreaPersistConfig,
-  canvasStagingAreaSlice,
 } from 'features/controlLayers/store/canvasStagingAreaSlice';
 import { lorasPersistConfig, lorasSlice } from 'features/controlLayers/store/lorasSlice';
 import { paramsPersistConfig, paramsSlice } from 'features/controlLayers/store/paramsSlice';
-import { deleteImageModalSlice } from 'features/deleteImageModal/store/slice';
+import { refImagesPersistConfig, refImagesSlice } from 'features/controlLayers/store/refImagesSlice';
 import { dynamicPromptsPersistConfig, dynamicPromptsSlice } from 'features/dynamicPrompts/store/dynamicPromptsSlice';
 import { galleryPersistConfig, gallerySlice } from 'features/gallery/store/gallerySlice';
-import { hrfPersistConfig, hrfSlice } from 'features/hrf/store/hrfSlice';
 import { modelManagerV2PersistConfig, modelManagerV2Slice } from 'features/modelManagerV2/store/modelManagerV2Slice';
 import { nodesPersistConfig, nodesSlice, nodesUndoableConfig } from 'features/nodes/store/nodesSlice';
 import { workflowLibraryPersistConfig, workflowLibrarySlice } from 'features/nodes/store/workflowLibrarySlice';
@@ -28,7 +28,6 @@ import { configSlice } from 'features/system/store/configSlice';
 import { systemPersistConfig, systemSlice } from 'features/system/store/systemSlice';
 import { uiPersistConfig, uiSlice } from 'features/ui/store/uiSlice';
 import { diff } from 'jsondiffpatch';
-import { keys, mergeWith, omit, pick } from 'lodash-es';
 import dynamicMiddlewares from 'redux-dynamic-middlewares';
 import type { SerializeFunction, UnserializeFunction } from 'redux-remember';
 import { rememberEnhancer, rememberReducer } from 'redux-remember';
@@ -54,20 +53,19 @@ const allReducers = {
   [configSlice.name]: configSlice.reducer,
   [uiSlice.name]: uiSlice.reducer,
   [dynamicPromptsSlice.name]: dynamicPromptsSlice.reducer,
-  [deleteImageModalSlice.name]: deleteImageModalSlice.reducer,
   [changeBoardModalSlice.name]: changeBoardModalSlice.reducer,
   [modelManagerV2Slice.name]: modelManagerV2Slice.reducer,
   [queueSlice.name]: queueSlice.reducer,
-  [hrfSlice.name]: hrfSlice.reducer,
   [canvasSlice.name]: undoable(canvasSlice.reducer, canvasUndoableConfig),
   [workflowSettingsSlice.name]: workflowSettingsSlice.reducer,
   [upscaleSlice.name]: upscaleSlice.reducer,
   [stylePresetSlice.name]: stylePresetSlice.reducer,
   [paramsSlice.name]: paramsSlice.reducer,
   [canvasSettingsSlice.name]: canvasSettingsSlice.reducer,
-  [canvasStagingAreaSlice.name]: canvasStagingAreaSlice.reducer,
+  [canvasSessionSlice.name]: canvasSessionSlice.reducer,
   [lorasSlice.name]: lorasSlice.reducer,
   [workflowLibrarySlice.name]: workflowLibrarySlice.reducer,
+  [refImagesSlice.name]: refImagesSlice.reducer,
 };
 
 const rootReducer = combineReducers(allReducers);
@@ -103,7 +101,6 @@ const persistConfigs: { [key in keyof typeof allReducers]?: PersistConfig } = {
   [uiPersistConfig.name]: uiPersistConfig,
   [dynamicPromptsPersistConfig.name]: dynamicPromptsPersistConfig,
   [modelManagerV2PersistConfig.name]: modelManagerV2PersistConfig,
-  [hrfPersistConfig.name]: hrfPersistConfig,
   [canvasPersistConfig.name]: canvasPersistConfig,
   [workflowSettingsPersistConfig.name]: workflowSettingsPersistConfig,
   [upscalePersistConfig.name]: upscalePersistConfig,
@@ -113,6 +110,7 @@ const persistConfigs: { [key in keyof typeof allReducers]?: PersistConfig } = {
   [canvasStagingAreaPersistConfig.name]: canvasStagingAreaPersistConfig,
   [lorasPersistConfig.name]: lorasPersistConfig,
   [workflowLibraryPersistConfig.name]: workflowLibraryPersistConfig,
+  [refImagesSlice.name]: refImagesPersistConfig,
 };
 
 const unserialize: UnserializeFunction = (data, key) => {
@@ -175,6 +173,7 @@ export const createStore = (uniqueStoreKey?: string, persist = true) =>
         .concat(api.middleware)
         .concat(dynamicMiddlewares)
         .concat(authToastMiddleware)
+        // .concat(getDebugLoggerMiddleware())
         .prepend(listenerMiddleware.middleware),
     enhancers: (getDefaultEnhancers) => {
       const _enhancers = getDefaultEnhancers().concat(autoBatchEnhancer());
@@ -209,3 +208,4 @@ export type RootState = ReturnType<AppStore['getState']>;
 // eslint-disable-next-line @typescript-eslint/no-explicit-any
 export type AppThunkDispatch = ThunkDispatch<RootState, any, UnknownAction>;
 export type AppDispatch = ReturnType<typeof createStore>['dispatch'];
+export type AppGetState = ReturnType<typeof createStore>['getState'];

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

@@ -1,8 +1,8 @@
-import type { AppThunkDispatch, RootState } from 'app/store/store';
+import type { AppStore, AppThunkDispatch, RootState } from 'app/store/store';
 import type { TypedUseSelectorHook } from 'react-redux';
 import { useDispatch, useSelector, useStore } from 'react-redux';
 
 // Use throughout your app instead of plain `useDispatch` and `useSelector`
 export const useAppDispatch = () => useDispatch<AppThunkDispatch>();
 export const useAppSelector: TypedUseSelectorHook<RootState> = useSelector;
-export const useAppStore = () => useStore<RootState>();
+export const useAppStore = () => useStore.withTypes<AppStore>()();

invokeai/frontend/web/src/app/store/use-debounced-app-selector.ts

@@ -1,6 +1,6 @@
 import type { Selector } from '@reduxjs/toolkit';
-import { useAppStore } from 'app/store/nanostores/store';
 import type { RootState } from 'app/store/store';
+import { useAppStore } from 'app/store/storeHooks';
 import { useEffect, useState } from 'react';
 
 /**

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

@@ -14,6 +14,7 @@ export type AppFeature =
   | 'githubLink'
   | 'discordLink'
   | 'bugLink'
+  | 'aboutModal'
   | 'localization'
   | 'consoleLogging'
   | 'dynamicPrompting'
@@ -29,7 +30,8 @@ export type AppFeature =
   | 'hfToken'
   | 'retryQueueItem'
   | 'cancelAndClearAll'
-  | 'chatGPT4oHigh';
+  | 'chatGPT4oHigh'
+  | 'modelRelationships';
 /**
  * A disable-able Stable Diffusion feature
  */
@@ -76,6 +78,7 @@ export type AppConfig = {
   allowPrivateStylePresets: boolean;
   allowClientSideUpload: boolean;
   allowPublishWorkflows: boolean;
+  allowPromptExpansion: boolean;
   disabledTabs: TabName[];
   disabledFeatures: AppFeature[];
   disabledSDFeatures: SDFeature[];

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

@@ -1,56 +0,0 @@
-import { Box, type BoxProps, type SystemStyleObject } from '@invoke-ai/ui-library';
-import { useAppSelector } from 'app/store/storeHooks';
-import { type FocusRegionName, useFocusRegion, useIsRegionFocused } from 'common/hooks/focus';
-import { selectSystemShouldEnableHighlightFocusedRegions } from 'features/system/store/systemSlice';
-import { memo, useMemo, useRef } from 'react';
-
-interface FocusRegionWrapperProps extends BoxProps {
-  region: FocusRegionName;
-  focusOnMount?: boolean;
-}
-
-const FOCUS_REGION_STYLES: SystemStyleObject = {
-  position: 'relative',
-  '&[data-highlighted="true"]::after': {
-    borderColor: 'blue.700',
-  },
-  '&::after': {
-    content: '""',
-    position: 'absolute',
-    inset: 0,
-    zIndex: 1,
-    borderRadius: 'base',
-    border: '2px solid',
-    borderColor: 'transparent',
-    pointerEvents: 'none',
-    transition: 'border-color 0.1s ease-in-out',
-  },
-};
-
-export const FocusRegionWrapper = memo(
-  ({ region, focusOnMount = false, sx, children, ...boxProps }: FocusRegionWrapperProps) => {
-    const shouldHighlightFocusedRegions = useAppSelector(selectSystemShouldEnableHighlightFocusedRegions);
-
-    const ref = useRef<HTMLDivElement>(null);
-
-    const options = useMemo(() => ({ focusOnMount }), [focusOnMount]);
-
-    useFocusRegion(region, ref, options);
-    const isFocused = useIsRegionFocused(region);
-    const isHighlighted = isFocused && shouldHighlightFocusedRegions;
-
-    return (
-      <Box
-        ref={ref}
-        tabIndex={-1}
-        sx={useMemo(() => ({ ...FOCUS_REGION_STYLES, ...sx }), [sx])}
-        data-highlighted={isHighlighted}
-        {...boxProps}
-      >
-        {children}
-      </Box>
-    );
-  }
-);
-
-FocusRegionWrapper.displayName = 'FocusRegionWrapper';

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

@@ -15,9 +15,9 @@ import {
 } from '@invoke-ai/ui-library';
 import { createSelector } from '@reduxjs/toolkit';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { merge, omit } from 'es-toolkit/compat';
 import { selectSystemSlice, setShouldEnableInformationalPopovers } from 'features/system/store/systemSlice';
 import { toast } from 'features/toast/toast';
-import { merge, omit } from 'lodash-es';
 import type { ReactElement } from 'react';
 import { memo, useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';

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

@@ -8,20 +8,16 @@ const Loading = () => {
   return (
     <Flex
       position="absolute"
-      width="100dvw"
-      height="100dvh"
       alignItems="center"
       justifyContent="center"
-      bg="#151519"
-      top={0}
-      right={0}
-      bottom={0}
-      left={0}
+      bg="hsl(220 12% 10% / 1)" // base.900
+      inset={0}
+      zIndex={99999}
     >
       <Image src={InvokeLogoWhite} w="8rem" h="8rem" />
       <Spinner
         label="Loading"
-        color="grey"
+        color="hsl(220 12% 68% / 1)" // base.300
         position="absolute"
         size="sm"
         width="24px !important"

invokeai/frontend/web/src/common/components/OverlayScrollbars/ScrollableContent.tsx

@@ -11,13 +11,14 @@ import { memo, useEffect, useMemo, useState } from 'react';
 
 type Props = PropsWithChildren & {
   maxHeight?: ChakraProps['maxHeight'];
+  maxWidth?: ChakraProps['maxWidth'];
   overflowX?: 'hidden' | 'scroll';
   overflowY?: 'hidden' | 'scroll';
 };
 
 const styles: CSSProperties = { position: 'absolute', top: 0, left: 0, right: 0, bottom: 0 };
 
-const ScrollableContent = ({ children, maxHeight, overflowX = 'hidden', overflowY = 'scroll' }: Props) => {
+const ScrollableContent = ({ children, maxHeight, maxWidth, overflowX = 'hidden', overflowY = 'scroll' }: Props) => {
   const overlayscrollbarsOptions = useMemo(
     () => getOverlayScrollbarsParams({ overflowX, overflowY }).options,
     [overflowX, overflowY]
@@ -44,7 +45,7 @@ const ScrollableContent = ({ children, maxHeight, overflowX = 'hidden', overflow
   }, [os]);
 
   return (
-    <Flex w="full" h="full" maxHeight={maxHeight} position="relative">
+    <Flex w="full" h="full" maxHeight={maxHeight} maxWidth={maxWidth} position="relative">
       <Box position="absolute" top={0} left={0} right={0} bottom={0}>
         <OverlayScrollbarsComponent ref={osRef} style={styles} options={overlayscrollbarsOptions}>
           {children}

invokeai/frontend/web/src/common/components/OverlayScrollbars/constants.ts

@@ -1,5 +1,5 @@
 import { deepClone } from 'common/util/deepClone';
-import { merge } from 'lodash-es';
+import { merge } from 'es-toolkit/compat';
 import { ClickScrollPlugin, OverlayScrollbars } from 'overlayscrollbars';
 import type { UseOverlayScrollbarsParams } from 'overlayscrollbars-react';
 import type { CSSProperties } from 'react';

invokeai/frontend/web/src/common/components/OverlayScrollbars/overlayscrollbars.css

@@ -1,6 +1,6 @@
 .os-scrollbar {
   /*      The size of the scrollbar */
-  --os-size: 9px;
+  --os-size: 8px;
   /*      The axis-perpedicular padding of the scrollbar (horizontal: padding-y, vertical: padding-x) */
   /* --os-padding-perpendicular: 0; */
   /*      The axis padding of the scrollbar (horizontal: padding-x, vertical: padding-y) */
@@ -8,11 +8,11 @@
   /*      The border radius of the scrollbar track */
   /* --os-track-border-radius: 0; */
   /*      The background of the scrollbar track */
-  /* --os-track-bg: rgba(0, 0, 0, 0.3); */
+  --os-track-bg: rgba(0, 0, 0, 0.5);
   /*      The :hover background of the scrollbar track */
-  /* --os-track-bg-hover: rgba(0, 0, 0, 0.3); */
+  --os-track-bg-hover: rgba(0, 0, 0, 0.5);
   /*      The :active background of the scrollbar track */
-  /* --os-track-bg-active: rgba(0, 0, 0, 0.3); */
+  --os-track-bg-active: rgba(0, 0, 0, 0.6);
   /*      The border of the scrollbar track */
   /* --os-track-border: none; */
   /*      The :hover background of the scrollbar track */
@@ -22,11 +22,11 @@
   /*      The border radius of the scrollbar handle */
   /* --os-handle-border-radius: 2px; */
   /*      The background of the scrollbar handle */
-  /* --os-handle-bg: var(--invokeai-colors-accentAlpha-500); */
+  --os-handle-bg: var(--invoke-colors-base-400);
   /*      The :hover background of the scrollbar handle */
-  /* --os-handle-bg-hover: var(--invokeai-colors-accentAlpha-700); */
+  --os-handle-bg-hover: var(--invoke-colors-base-300);
   /*      The :active background of the scrollbar handle */
-  /* --os-handle-bg-active: var(--invokeai-colors-accentAlpha-800); */
+  --os-handle-bg-active: var(--invoke-colors-base-250);
   /*      The border of the scrollbar handle */
   /* --os-handle-border: none; */
   /*      The :hover border of the scrollbar handle */
@@ -34,23 +34,23 @@
   /*      The :active border of the scrollbar handle */
   /* --os-handle-border-active: none; */
   /*      The min size of the scrollbar handle */
-  --os-handle-min-size: 50px;
+  --os-handle-min-size: 32px;
   /*      The max size of the scrollbar handle */
   /* --os-handle-max-size: none; */
   /*      The axis-perpedicular size of the scrollbar handle (horizontal: height, vertical: width) */
   /* --os-handle-perpendicular-size: 100%; */
   /*      The :hover axis-perpedicular size of the scrollbar handle (horizontal: height, vertical: width) */
-  /* --os-handle-perpendicular-size-hover: 100%; */
+  --os-handle-perpendicular-size-hover: 100%;
   /*      The :active axis-perpedicular size of the scrollbar handle (horizontal: height, vertical: width) */
   /* --os-handle-perpendicular-size-active: 100%; */
   /*      Increases the interactive area of the scrollbar handle. */
-  /* --os-handle-interactive-area-offset: 0; */
+  --os-handle-interactive-area-offset: -1px;
 }
 
 .os-scrollbar-handle {
-  cursor: grab;
+  /* cursor: grab; */
 }
 
 .os-scrollbar-handle:active {
-  cursor: grabbing;
+  /* cursor: grabbing; */
 }

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

@@ -87,7 +87,7 @@ export const buildGroup = <T extends object>(group: Omit<Group<T>, typeof unique
   [uniqueGroupKey]: true,
 });
 
-const isGroup = <T extends object>(optionOrGroup: OptionOrGroup<T>): optionOrGroup is Group<T> => {
+export const isGroup = <T extends object>(optionOrGroup: OptionOrGroup<T>): optionOrGroup is Group<T> => {
   return uniqueGroupKey in optionOrGroup && optionOrGroup[uniqueGroupKey] === true;
 };
 
@@ -198,6 +198,10 @@ type PickerProps<T extends object> = {
    * Whether the picker should be searchable. If true, renders a search input.
    */
   searchable?: boolean;
+  /**
+   * Initial state for group toggles. If provided, groups will start with these states instead of all being disabled.
+   */
+  initialGroupStates?: GroupStatusMap;
 };
 
 export type PickerContextState<T extends object> = {
@@ -310,9 +314,9 @@ const flattenOptions = <T extends object>(options: OptionOrGroup<T>[]): T[] => {
   return flattened;
 };
 
-type GroupStatusMap = Record<string, boolean>;
+export type GroupStatusMap = Record<string, boolean>;
 
-const useTogglableGroups = <T extends object>(options: OptionOrGroup<T>[]) => {
+const useTogglableGroups = <T extends object>(options: OptionOrGroup<T>[], initialGroupStates?: GroupStatusMap) => {
   const groupsWithOptions = useMemo(() => {
     const ids: string[] = [];
     for (const optionOrGroup of options) {
@@ -332,14 +336,16 @@ const useTogglableGroups = <T extends object>(options: OptionOrGroup<T>[]) => {
     const groupStatusMap = $groupStatusMap.get();
     const newMap: GroupStatusMap = {};
     for (const id of groupsWithOptions) {
-      if (newMap[id] === undefined) {
-        newMap[id] = false;
+      if (initialGroupStates && initialGroupStates[id] !== undefined) {
+        newMap[id] = initialGroupStates[id];
       } else if (groupStatusMap[id] !== undefined) {
         newMap[id] = groupStatusMap[id];
+      } else {
+        newMap[id] = false;
       }
     }
     $groupStatusMap.set(newMap);
-  }, [groupsWithOptions, $groupStatusMap]);
+  }, [groupsWithOptions, $groupStatusMap, initialGroupStates]);
 
   const toggleGroup = useCallback(
     (idToToggle: string) => {
@@ -511,10 +517,14 @@ export const Picker = typedMemo(<T extends object>(props: PickerProps<T>) => {
     OptionComponent = DefaultOptionComponent,
     NextToSearchBar,
     searchable,
+    initialGroupStates,
   } = props;
   const rootRef = useRef<HTMLDivElement>(null);
   const inputRef = useRef<HTMLInputElement>(null);
-  const { $groupStatusMap, $areAllGroupsDisabled, toggleGroup } = useTogglableGroups(optionsOrGroups);
+  const { $groupStatusMap, $areAllGroupsDisabled, toggleGroup } = useTogglableGroups(
+    optionsOrGroups,
+    initialGroupStates
+  );
   const $activeOptionId = useAtom(getFirstOptionId(optionsOrGroups, getOptionId));
   const $compactView = useAtom(true);
   const $optionsOrGroups = useAtom(optionsOrGroups);

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

@@ -1,20 +1,15 @@
 import { MenuItem } from '@invoke-ai/ui-library';
 import { useAppDispatch } from 'app/store/storeHooks';
-import {
-  useNewCanvasSession,
-  useNewGallerySession,
-} from 'features/controlLayers/components/NewSessionConfirmationAlertDialog';
 import { allEntitiesDeleted } from 'features/controlLayers/store/canvasSlice';
 import { paramsReset } from 'features/controlLayers/store/paramsSlice';
 import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
-import { PiArrowsCounterClockwiseBold, PiFilePlusBold } from 'react-icons/pi';
+import { PiArrowsCounterClockwiseBold } from 'react-icons/pi';
 
 export const SessionMenuItems = memo(() => {
   const { t } = useTranslation();
   const dispatch = useAppDispatch();
-  const { newGallerySessionWithDialog } = useNewGallerySession();
-  const { newCanvasSessionWithDialog } = useNewCanvasSession();
+
   const resetCanvasLayers = useCallback(() => {
     dispatch(allEntitiesDeleted());
   }, [dispatch]);
@@ -23,12 +18,6 @@ export const SessionMenuItems = memo(() => {
   }, [dispatch]);
   return (
     <>
-      <MenuItem icon={<PiFilePlusBold />} onClick={newGallerySessionWithDialog}>
-        {t('controlLayers.newGallerySession')}
-      </MenuItem>
-      <MenuItem icon={<PiFilePlusBold />} onClick={newCanvasSessionWithDialog}>
-        {t('controlLayers.newCanvasSession')}
-      </MenuItem>
       <MenuItem icon={<PiArrowsCounterClockwiseBold />} onClick={resetCanvasLayers}>
         {t('controlLayers.resetCanvasLayers')}
       </MenuItem>

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

@@ -6,6 +6,7 @@ import { atom, computed } from 'nanostores';
 import type { RefObject } from 'react';
 import { useEffect } from 'react';
 import { objectKeys } from 'tsafe';
+import z from 'zod/v4';
 
 /**
  * We need to manage focus regions to conditionally enable hotkeys:
@@ -30,23 +31,34 @@ const log = logger('system');
 /**
  * The names of the focus regions.
  */
-export type FocusRegionName = 'gallery' | 'layers' | 'canvas' | 'workflows' | 'viewer';
+const zFocusRegionName = z.enum([
+  'launchpad',
+  'viewer',
+  'gallery',
+  'boards',
+  'layers',
+  'canvas',
+  'workflows',
+  'progress',
+  'settings',
+]);
+export type FocusRegionName = z.infer<typeof zFocusRegionName>;
 
 /**
  * A map of focus regions to the elements that are part of that region.
  */
-const REGION_TARGETS: Record<FocusRegionName, Set<HTMLElement>> = {
-  gallery: new Set<HTMLElement>(),
-  layers: new Set<HTMLElement>(),
-  canvas: new Set<HTMLElement>(),
-  workflows: new Set<HTMLElement>(),
-  viewer: new Set<HTMLElement>(),
-} as const;
+const REGION_TARGETS: Record<FocusRegionName, Set<HTMLElement>> = zFocusRegionName.options.values().reduce(
+  (acc, region) => {
+    acc[region] = new Set<HTMLElement>();
+    return acc;
+  },
+  {} as Record<FocusRegionName, Set<HTMLElement>>
+);
 
 /**
  * The currently-focused region or `null` if no region is focused.
  */
-export const $focusedRegion = atom<FocusRegionName | null>(null);
+const $focusedRegion = atom<FocusRegionName | null>(null);
 
 /**
  * A map of focus regions to atoms that indicate if that region is focused.
@@ -62,11 +74,13 @@ const FOCUS_REGIONS = objectKeys(REGION_TARGETS).reduce(
 /**
  * Sets the focused region, logging a trace level message.
  */
-const setFocus = (region: FocusRegionName | null) => {
+export const setFocusedRegion = (region: FocusRegionName | null) => {
   $focusedRegion.set(region);
   log.trace(`Focus changed: ${region}`);
 };
 
+export const getFocusedRegion = () => $focusedRegion.get();
+
 type UseFocusRegionOptions = {
   focusOnMount?: boolean;
 };
@@ -99,14 +113,14 @@ export const useFocusRegion = (
     REGION_TARGETS[region].add(element);
 
     if (focusOnMount) {
-      setFocus(region);
+      setFocusedRegion(region);
     }
 
     return () => {
       REGION_TARGETS[region].delete(element);
 
       if (REGION_TARGETS[region].size === 0 && $focusedRegion.get() === region) {
-        setFocus(null);
+        setFocusedRegion(null);
       }
     };
   }, [options, ref, region]);
@@ -163,7 +177,7 @@ const onFocus = (_: FocusEvent) => {
     return;
   }
 
-  setFocus(focusedRegion);
+  setFocusedRegion(focusedRegion);
 };
 
 /**

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

@@ -0,0 +1,115 @@
+import { useStore } from '@nanostores/react';
+import { WrappedError } from 'common/util/result';
+import type { Atom } from 'nanostores';
+import { atom } from 'nanostores';
+import { useCallback, useEffect, useMemo, useState } from 'react';
+
+type SuccessState<T> = {
+  status: 'success';
+  value: T;
+  error: null;
+};
+
+type ErrorState = {
+  status: 'error';
+  value: null;
+  error: Error;
+};
+
+type PendingState = {
+  status: 'pending';
+  value: null;
+  error: null;
+};
+
+type IdleState = {
+  status: 'idle';
+  value: null;
+  error: null;
+};
+
+export type State<T> = IdleState | PendingState | SuccessState<T> | ErrorState;
+
+type UseAsyncStateOptions = {
+  immediate?: boolean;
+};
+
+type UseAsyncReturn<T> = {
+  $state: Atom<State<T>>;
+  trigger: () => Promise<void>;
+  reset: () => void;
+};
+
+export const useAsyncState = <T>(execute: () => Promise<T>, options?: UseAsyncStateOptions): UseAsyncReturn<T> => {
+  const $state = useState(() =>
+    atom<State<T>>({
+      status: 'idle',
+      value: null,
+      error: null,
+    })
+  )[0];
+
+  const trigger = useCallback(async () => {
+    $state.set({
+      status: 'pending',
+      value: null,
+      error: null,
+    });
+    try {
+      const value = await execute();
+      $state.set({
+        status: 'success',
+        value,
+        error: null,
+      });
+    } catch (error) {
+      $state.set({
+        status: 'error',
+        value: null,
+        error: WrappedError.wrap(error),
+      });
+    }
+  }, [$state, execute]);
+
+  const reset = useCallback(() => {
+    $state.set({
+      status: 'idle',
+      value: null,
+      error: null,
+    });
+  }, [$state]);
+
+  useEffect(() => {
+    if (options?.immediate) {
+      trigger();
+    }
+  }, [options?.immediate, trigger]);
+
+  const api = useMemo(
+    () =>
+      ({
+        $state,
+        trigger,
+        reset,
+      }) satisfies UseAsyncReturn<T>,
+    [$state, trigger, reset]
+  );
+
+  return api;
+};
+
+type UseAsyncReturnReactive<T> = {
+  state: State<T>;
+  trigger: () => Promise<void>;
+  reset: () => void;
+};
+
+export const useAsyncStateReactive = <T>(
+  execute: () => Promise<T>,
+  options?: UseAsyncStateOptions
+): UseAsyncReturnReactive<T> => {
+  const { $state, trigger, reset } = useAsyncState(execute, options);
+  const state = useStore($state);
+
+  return { state, trigger, reset };
+};

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

@@ -0,0 +1,29 @@
+import { combine } from '@atlaskit/pragmatic-drag-and-drop/combine';
+import { dropTargetForElements } from '@atlaskit/pragmatic-drag-and-drop/element/adapter';
+import { dropTargetForExternal } from '@atlaskit/pragmatic-drag-and-drop/external/adapter';
+import { useTimeoutCallback } from 'common/hooks/useTimeoutCallback';
+import type { RefObject } from 'react';
+import { useEffect } from 'react';
+
+export const useCallbackOnDragEnter = (cb: () => void, ref: RefObject<HTMLElement>, delay = 300) => {
+  const [run, cancel] = useTimeoutCallback(cb, delay);
+
+  useEffect(() => {
+    const element = ref.current;
+    if (!element) {
+      return;
+    }
+    return combine(
+      dropTargetForElements({
+        element,
+        onDragEnter: run,
+        onDragLeave: cancel,
+      }),
+      dropTargetForExternal({
+        element,
+        onDragEnter: run,
+        onDragLeave: cancel,
+      })
+    );
+  }, [cancel, ref, run]);
+};