chore: bump version to v6.0.0a7

Update the frontend to incorporate the previous changes to how image
selection and general image identification is handled in the frontend.

.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 20
+    - name: setup node 18
       uses: actions/setup-node@v4
       with:
-        node-version: '20'
+        node-version: '18'
 
     - name: setup pnpm
       uses: pnpm/action-setup@v4
       with:
-        version: 10
+        version: 8.15.6
         run_install: false
 
     - name: get pnpm store directory

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/v4'
+[zod]: https://github.com/colinhacks/zod 'zod'
 [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 recent launcher for your operating system:
+Download the most 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/images.py

@@ -14,7 +14,6 @@ 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,
 )
@@ -72,7 +71,7 @@ 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}",
-        examples=['"[1024,1024]"'],
+        example='"[1024,1024]"',
     ),
     metadata: Optional[str] = Body(
         default=None,
@@ -577,11 +576,11 @@ async def get_image_names(
     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"""
+) -> list[str]:
+    """Gets ordered list of all image names (starred first, then unstarred)"""
 
     try:
-        result = ApiDependencies.invoker.services.images.get_image_names(
+        image_names = ApiDependencies.invoker.services.images.get_image_names(
             starred_first=starred_first,
             order_dir=order_dir,
             image_origin=image_origin,
@@ -590,34 +589,6 @@ async def get_image_names(
             board_id=board_id,
             search_term=search_term,
         )
-        return result
+        return image_names
     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

@@ -41,7 +41,6 @@ from invokeai.backend.model_manager.starter_models import (
     STARTER_BUNDLES,
     STARTER_MODELS,
     StarterModel,
-    StarterModelBundle,
     StarterModelWithoutDependencies,
 )
 
@@ -292,7 +291,7 @@ 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", examples=[example_model_input])],
+    changes: Annotated[ModelRecordChanges, Body(description="Model config", example=example_model_input)],
 ) -> AnyModelConfig:
     """Update a model's config."""
     logger = ApiDependencies.invoker.services.logger
@@ -450,7 +449,7 @@ 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 ",
-        examples=[{"name": "string", "description": "string"}],
+        example={"name": "string", "description": "string"},
     ),
 ) -> ModelInstallJob:
     """Install a model using a string identifier.
@@ -800,7 +799,7 @@ async def convert_model(
 
 class StarterModelResponse(BaseModel):
     starter_models: list[StarterModel]
-    starter_bundles: dict[str, StarterModelBundle]
+    starter_bundles: dict[str, list[StarterModel]]
 
 
 def get_is_installed(
@@ -834,7 +833,7 @@ async def get_starter_models() -> StarterModelResponse:
         model.dependencies = missing_deps
 
     for bundle in starter_bundles.values():
-        for model in bundle.models:
+        for model in bundle:
             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, HTTPException, Path, Query
+from fastapi import Body, Path, Query
 from fastapi.routing import APIRouter
 from pydantic import BaseModel, Field
 
@@ -22,7 +22,6 @@ from invokeai.app.services.session_queue.session_queue_common import (
     RetryItemsResult,
     SessionQueueCountsByDestination,
     SessionQueueItem,
-    SessionQueueItemNotFoundError,
     SessionQueueStatus,
 )
 from invokeai.app.services.shared.pagination import CursorPaginatedResults
@@ -60,12 +59,10 @@ async def enqueue_batch(
     ),
 ) -> EnqueueBatchResult:
     """Processes a batch and enqueues the output graphs for execution."""
-    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}")
+
+    return await ApiDependencies.invoker.services.session_queue.enqueue_batch(
+        queue_id=queue_id, batch=batch, prepend=prepend
+    )
 
 
 @session_queue_router.get(
@@ -85,17 +82,14 @@ async def list_queue_items(
 ) -> CursorPaginatedResults[SessionQueueItem]:
     """Gets cursor-paginated queue items"""
 
-    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}")
+    return ApiDependencies.invoker.services.session_queue.list_queue_items(
+        queue_id=queue_id,
+        limit=limit,
+        status=status,
+        cursor=cursor,
+        priority=priority,
+        destination=destination,
+    )
 
 
 @session_queue_router.get(
@@ -110,13 +104,11 @@ async def list_all_queue_items(
     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}")
+
+    return ApiDependencies.invoker.services.session_queue.list_all_queue_items(
+        queue_id=queue_id,
+        destination=destination,
+    )
 
 
 @session_queue_router.put(
@@ -128,10 +120,7 @@ async def resume(
     queue_id: str = Path(description="The queue id to perform this operation on"),
 ) -> SessionProcessorStatus:
     """Resumes session processor"""
-    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}")
+    return ApiDependencies.invoker.services.session_processor.resume()
 
 
 @session_queue_router.put(
@@ -143,10 +132,7 @@ async def Pause(
     queue_id: str = Path(description="The queue id to perform this operation on"),
 ) -> SessionProcessorStatus:
     """Pauses session processor"""
-    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}")
+    return ApiDependencies.invoker.services.session_processor.pause()
 
 
 @session_queue_router.put(
@@ -158,10 +144,7 @@ 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"""
-    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}")
+    return ApiDependencies.invoker.services.session_queue.cancel_all_except_current(queue_id=queue_id)
 
 
 @session_queue_router.put(
@@ -173,10 +156,7 @@ 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}")
+    return ApiDependencies.invoker.services.session_queue.delete_all_except_current(queue_id=queue_id)
 
 
 @session_queue_router.put(
@@ -189,12 +169,7 @@ 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"""
-    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}")
+    return ApiDependencies.invoker.services.session_queue.cancel_by_batch_ids(queue_id=queue_id, batch_ids=batch_ids)
 
 
 @session_queue_router.put(
@@ -207,12 +182,9 @@ 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"""
-    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}")
+    return ApiDependencies.invoker.services.session_queue.cancel_by_destination(
+        queue_id=queue_id, destination=destination
+    )
 
 
 @session_queue_router.put(
@@ -225,10 +197,7 @@ 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"""
-    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}")
+    return ApiDependencies.invoker.services.session_queue.retry_items_by_id(queue_id=queue_id, item_ids=item_ids)
 
 
 @session_queue_router.put(
@@ -242,14 +211,11 @@ 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"""
-    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}")
+    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
 
 
 @session_queue_router.put(
@@ -263,10 +229,7 @@ async def prune(
     queue_id: str = Path(description="The queue id to perform this operation on"),
 ) -> PruneResult:
     """Prunes all completed or errored queue items"""
-    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}")
+    return ApiDependencies.invoker.services.session_queue.prune(queue_id)
 
 
 @session_queue_router.get(
@@ -280,10 +243,7 @@ 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"""
-    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}")
+    return ApiDependencies.invoker.services.session_queue.get_current(queue_id)
 
 
 @session_queue_router.get(
@@ -297,10 +257,7 @@ 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"""
-    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}")
+    return ApiDependencies.invoker.services.session_queue.get_next(queue_id)
 
 
 @session_queue_router.get(
@@ -314,12 +271,9 @@ 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"""
-    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}")
+    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)
 
 
 @session_queue_router.get(
@@ -334,10 +288,7 @@ 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"""
-    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}")
+    return ApiDependencies.invoker.services.session_queue.get_batch_status(queue_id=queue_id, batch_id=batch_id)
 
 
 @session_queue_router.get(
@@ -353,12 +304,7 @@ async def get_queue_item(
     item_id: int = Path(description="The queue item to get"),
 ) -> SessionQueueItem:
     """Gets a queue item"""
-    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}")
+    return ApiDependencies.invoker.services.session_queue.get_queue_item(item_id)
 
 
 @session_queue_router.delete(
@@ -370,10 +316,7 @@ async def delete_queue_item(
     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}")
+    ApiDependencies.invoker.services.session_queue.delete_queue_item(item_id)
 
 
 @session_queue_router.put(
@@ -388,12 +331,8 @@ async def cancel_queue_item(
     item_id: int = Path(description="The queue item to cancel"),
 ) -> SessionQueueItem:
     """Deletes a queue item"""
-    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}")
+
+    return ApiDependencies.invoker.services.session_queue.cancel_queue_item(item_id)
 
 
 @session_queue_router.get(
@@ -406,12 +345,9 @@ async def counts_by_destination(
     destination: str = Query(description="The destination to query"),
 ) -> SessionQueueCountsByDestination:
     """Gets the counts of queue items by 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}")
+    return ApiDependencies.invoker.services.session_queue.get_counts_by_destination(
+        queue_id=queue_id, destination=destination
+    )
 
 
 @session_queue_router.delete(
@@ -424,9 +360,6 @@ async def delete_by_destination(
     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}")
+    return ApiDependencies.invoker.services.session_queue.delete_by_destination(
+        queue_id=queue_id, destination=destination
+    )

invokeai/app/invocations/fields.py

@@ -64,7 +64,6 @@ class UIType(str, Enum, metaclass=MetaEnum):
     Imagen3Model = "Imagen3ModelField"
     Imagen4Model = "Imagen4ModelField"
     ChatGPT4oModel = "ChatGPT4oModelField"
-    FluxKontextModel = "FluxKontextModelField"
     # endregion
 
     # region Misc Field Types
@@ -215,7 +214,6 @@ 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):
@@ -292,12 +290,6 @@ 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

@@ -16,12 +16,13 @@ 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
@@ -33,7 +34,6 @@ 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="4.0.0",
+    version="3.3.0",
 )
-class FluxDenoiseInvocation(BaseInvocation):
+class FluxDenoiseInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Run denoising process with a FLUX transformer model."""
 
     # If latents is provided, this means we are doing image-to-image.
@@ -145,20 +145,11 @@ class FluxDenoiseInvocation(BaseInvocation):
         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)
@@ -385,27 +376,6 @@ class FluxDenoiseInvocation(BaseInvocation):
                 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,
@@ -421,8 +391,6 @@ class FluxDenoiseInvocation(BaseInvocation):
                 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)
@@ -897,10 +865,7 @@ class FluxDenoiseInvocation(BaseInvocation):
 
     def _build_step_callback(self, context: InvocationContext) -> Callable[[PipelineIntermediateState], None]:
         def step_callback(state: PipelineIntermediateState) -> None:
-            # 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()
+            state.latents = unpack(state.latents.float(), self.height, self.width).squeeze()
             context.util.flux_step_callback(state)
 
         return step_callback

invokeai/app/invocations/flux_kontext.py

@@ -1,40 +0,0 @@
-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, Union
+from typing import Iterator, Literal, Optional, Tuple
 
 import torch
 from transformers import CLIPTextModel, CLIPTokenizer, T5EncoderModel, T5Tokenizer, T5TokenizerFast
@@ -111,9 +111,6 @@ 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)
 
@@ -154,9 +151,6 @@ 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)
 
@@ -176,88 +170,3 @@ 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

@@ -5,7 +5,6 @@ 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,
@@ -109,6 +108,6 @@ class ImageRecordStorageBase(ABC):
         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."""
+    ) -> list[str]:
+        """Gets ordered list of all image names (starred first, then unstarred)."""
         pass

invokeai/app/services/image_records/image_records_common.py

@@ -212,11 +212,3 @@ def deserialize_image_record(image_dict: dict) -> ImageRecord:
 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

@@ -7,7 +7,6 @@ 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,
@@ -397,10 +396,17 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
         is_intermediate: Optional[bool] = None,
         board_id: Optional[str] = None,
         search_term: Optional[str] = None,
-    ) -> ImageNamesResult:
+    ) -> list[str]:
         cursor = self._conn.cursor()
 
-        # Build query conditions (reused for both starred count and image names queries)
+        # Base query to get image names in order (starred first, then unstarred)
+        query = """--sql
+        SELECT images.image_name
+        FROM images
+        LEFT JOIN board_images ON board_images.image_name = images.image_name
+        WHERE 1=1
+        """
+
         query_conditions = ""
         query_params: list[Union[int, str, bool]] = []
 
@@ -445,38 +451,22 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
             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}
+            query += (
+                query_conditions
+                + f"""--sql
             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}
+            query += (
+                query_conditions
+                + f"""--sql
             ORDER BY images.created_at {order_dir.value}
             """
+            )
 
-        cursor.execute(names_query, query_params)
+        cursor.execute(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))
+        return [row[0] for row in result]

invokeai/app/services/images/images_base.py

@@ -6,7 +6,6 @@ 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,
@@ -159,6 +158,6 @@ class ImageServiceABC(ABC):
         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."""
+    ) -> list[str]:
+        """Gets ordered list of all image names."""
         pass

invokeai/app/services/images/images_default.py

@@ -10,7 +10,6 @@ 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,
@@ -320,7 +319,7 @@ class ImageService(ImageServiceABC):
         is_intermediate: Optional[bool] = None,
         board_id: Optional[str] = None,
         search_term: Optional[str] = None,
-    ) -> ImageNamesResult:
+    ) -> list[str]:
         try:
             return self.__invoker.services.image_records.get_image_names(
                 starred_first=starred_first,

invokeai/app/services/session_queue/session_queue_common.py

@@ -205,7 +205,6 @@ 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 SessionQueueItem(BaseModel):
@@ -332,7 +331,6 @@ 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):

invokeai/app/services/session_queue/session_queue_sqlite.py

@@ -133,18 +133,6 @@ 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(
@@ -153,7 +141,6 @@ 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
@@ -404,8 +391,6 @@ 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(
@@ -444,8 +429,6 @@ 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(
@@ -548,8 +531,6 @@ 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(
@@ -570,9 +551,12 @@ class SqliteSessionQueue(SessionQueueBase):
                 tuple(params),
             )
             self._conn.commit()
-
             if current_queue_item is not None and current_queue_item.queue_id == queue_id:
-                self._set_queue_item_status(current_queue_item.item_id, "canceled")
+                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
+                )
         except Exception:
             self._conn.rollback()
             raise
@@ -743,7 +727,7 @@ class SqliteSessionQueue(SessionQueueBase):
         counts_result = cast(list[sqlite3.Row], cursor.fetchall())
 
         current_item = self.get_current(queue_id=queue_id)
-        total = sum(row[1] or 0 for row in counts_result)
+        total = sum(row[1] for row in counts_result)
         counts: dict[str, int] = {row[0]: row[1] for row in counts_result}
         return SessionQueueStatus(
             queue_id=queue_id,
@@ -772,7 +756,7 @@ class SqliteSessionQueue(SessionQueueBase):
             (queue_id, batch_id),
         )
         result = cast(list[sqlite3.Row], cursor.fetchall())
-        total = sum(row[1] or 0 for row in result)
+        total = sum(row[1] 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
@@ -804,7 +788,7 @@ class SqliteSessionQueue(SessionQueueBase):
         )
         counts_result = cast(list[sqlite3.Row], cursor.fetchall())
 
-        total = sum(row[1] or 0 for row in counts_result)
+        total = sum(row[1] 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

@@ -2,7 +2,7 @@
 
 import copy
 import itertools
-from typing import Any, Optional, TypeVar, Union, get_args, get_origin
+from typing import Any, Optional, TypeVar, Union, get_args, get_origin, get_type_hints
 
 import networkx as nx
 from pydantic import (
@@ -58,32 +58,17 @@ class Edge(BaseModel):
 
 
 def get_output_field_type(node: BaseInvocation, field: str) -> Any:
-    # 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
+    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
 
 
 def get_input_field_type(node: BaseInvocation, field: str) -> Any:
-    # 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
+    node_type = type(node)
+    node_inputs = get_type_hints(node_type)
+    node_input_field = node_inputs.get(field) or None
+    return node_input_field
 
 
 def is_union_subtype(t1, t2):
@@ -1007,11 +992,10 @@ 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 = []
-            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])
-
+            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)))
             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

@@ -123,11 +123,7 @@ def calc_percentage(intermediate_state: PipelineIntermediateState) -> float:
     if total_steps == 0:
         return 0.0
     if order == 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
+        return floor(step / 2) / floor(total_steps / 2)
     # order == 1
     return step / total_steps
 

invokeai/backend/flux/denoise.py

@@ -30,11 +30,8 @@ def denoise(
     controlnet_extensions: list[XLabsControlNetExtension | InstantXControlNetExtension],
     pos_ip_adapter_extensions: list[XLabsIPAdapterExtension],
     neg_ip_adapter_extensions: list[XLabsIPAdapterExtension],
-    # extra img tokens (channel-wise)
+    # extra img tokens
     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
@@ -49,10 +46,6 @@ 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)
 
@@ -78,26 +71,10 @@ 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)
-
-        # 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_img = torch.cat((img, img_cond), dim=-1) if img_cond is not None else img
         pred = model(
-            img=img_input,
-            img_ids=img_input_ids,
+            img=pred_img,
+            img_ids=img_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,
@@ -111,10 +88,6 @@ 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

@@ -1,149 +0,0 @@
-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

@@ -174,13 +174,11 @@ 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 = img_ids.to(orig_dtype)
+        img_ids.to(orig_dtype)
 
     return img_ids

invokeai/backend/flux/util.py

@@ -18,29 +18,6 @@ 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

@@ -37,7 +37,6 @@ 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,
@@ -353,14 +352,15 @@ class LoRAOmiConfig(LoRAConfigBase, ModelConfigBase):
     @classmethod
     def parse(cls, mod: ModelOnDisk) -> dict[str, Any]:
         metadata = mod.metadata()
-        architecture = metadata["modelspec.architecture"]
+        base_str, _ = metadata["modelspec.architecture"].split("/")
+        base_str = base_str.lower()
 
-        if architecture == stable_diffusion_xl_1_lora:
+        if "stable-diffusion-xl-v1-base" in base_str:
             base = BaseModelType.StableDiffusionXL
-        elif architecture == flux_dev_1_lora:
+        elif "flux" in base_str:
             base = BaseModelType.Flux
         else:
-            raise InvalidModelConfigException(f"Unrecognised/unsupported architecture for OMI LoRA: {architecture}")
+            raise InvalidModelConfigException(f"Unrecognised/unsupported base architecture for OMI LoRA: {base_str}")
 
         return {"base": base}
 

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

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

@@ -13,7 +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.omi import convert_from_omi
 from invokeai.backend.model_manager.taxonomy import (
     AnyModel,
     BaseModelType,

invokeai/backend/model_manager/omi.py

@@ -0,0 +1,16 @@
+import omi_model_standards.convert.lora.convert_lora_util as lora_util
+from omi_model_standards.convert.lora.convert_flux_lora import convert_flux_lora_key_sets
+from omi_model_standards.convert.lora.convert_sdxl_lora import convert_sdxl_lora_key_sets
+
+from invokeai.backend.model_manager.model_on_disk import StateDict
+from invokeai.backend.model_manager.taxonomy import BaseModelType
+
+
+def convert_from_omi(weights_sd: StateDict, base: BaseModelType):
+    keyset = {
+        BaseModelType.Flux: convert_flux_lora_key_sets(),
+        BaseModelType.StableDiffusionXL: 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/__init__.py

@@ -1,7 +0,0 @@
-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

@@ -1,21 +0,0 @@
-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

@@ -1,20 +0,0 @@
-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

@@ -1,84 +0,0 @@
-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

@@ -1,217 +0,0 @@
-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

@@ -1,125 +0,0 @@
-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

@@ -1,19 +0,0 @@
-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

@@ -1,31 +0,0 @@
-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 StarterModelBundle(BaseModel):
+class StarterModelBundles(BaseModel):
     name: str
     models: list[StarterModel]
 
@@ -109,7 +109,7 @@ flux_vae = StarterModel(
 
 # region: Main
 flux_schnell_quantized = StarterModel(
-    name="FLUX.1 schnell (quantized)",
+    name="FLUX 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.1 dev (quantized)",
+    name="FLUX 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.1 schnell",
+    name="FLUX Schnell",
     base=BaseModelType.Flux,
     source="InvokeAI/flux_schnell::transformer/base/flux1-schnell.safetensors",
     description="FLUX schnell transformer in bfloat16. Total size with dependencies: ~33GB",
@@ -133,29 +133,13 @@ flux_schnell = StarterModel(
     dependencies=[t5_base_encoder, flux_vae, clip_l_encoder],
 )
 flux_dev = StarterModel(
-    name="FLUX.1 dev",
+    name="FLUX 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,
@@ -672,7 +656,6 @@ 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,
@@ -793,13 +776,12 @@ flux_bundle: list[StarterModel] = [
     flux_depth_control_lora,
     flux_redux,
     flux_fill,
-    flux_kontext_quantized,
 ]
 
-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),
+STARTER_BUNDLES: dict[str, list[StarterModel]] = {
+    BaseModelType.StableDiffusion1: sd1_bundle,
+    BaseModelType.StableDiffusionXL: sdxl_bundle,
+    BaseModelType.Flux: flux_bundle,
 }
 
 assert len(STARTER_MODELS) == len({m.source for m in STARTER_MODELS}), "Duplicate starter models"

invokeai/backend/model_manager/taxonomy.py

@@ -29,7 +29,6 @@ class BaseModelType(str, Enum):
     Imagen3 = "imagen3"
     Imagen4 = "imagen4"
     ChatGPT4o = "chatgpt-4o"
-    FluxKontext = "flux-kontext"
 
 
 class ModelType(str, Enum):

invokeai/frontend/web/.eslintrc.js

@@ -17,15 +17,6 @@ module.exports = {
     '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': [
@@ -42,38 +33,8 @@ 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

@@ -3,6 +3,8 @@ import type { KnipConfig } from 'knip';
 const config: KnipConfig = {
   project: ['src/**/*.{ts,tsx}!'],
   ignore: [
+    // TODO(psyche): temporarily ignored all files for test build purposes
+    'src/**',
     // This file is only used during debugging
     'src/app/store/middleware/debugLoggerMiddleware.ts',
     // Autogenerated types - shouldn't ever touch these
@@ -12,8 +14,10 @@ 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',
-    // Will be using this
-    'src/common/hooks/useAsyncState.ts',
+    // TODO(psyche): restore HRF functionality?
+    'src/features/hrf/**',
+    // This feature is (temprarily?) disabled
+    'src/features/controlLayers/components/InpaintMask/InpaintMaskAddButtons.tsx',
   ],
   ignoreBinaries: ['only-allow'],
   paths: {

invokeai/frontend/web/package.json

@@ -38,60 +38,71 @@
     "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": "^1.7.4",
-    "@atlaskit/pragmatic-drag-and-drop-auto-scroll": "^2.1.1",
-    "@atlaskit/pragmatic-drag-and-drop-hitbox": "^1.1.0",
-    "@dagrejs/dagre": "^1.1.5",
+    "@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",
     "@dagrejs/graphlib": "^2.2.4",
-    "@fontsource-variable/inter": "^5.2.6",
+    "@fontsource-variable/inter": "^5.2.5",
     "@invoke-ai/ui-library": "^0.0.46",
     "@nanostores/react": "^1.0.0",
-    "@observ33r/object-equals": "^1.1.4",
     "@reduxjs/toolkit": "2.8.2",
     "@roarr/browser-log-writer": "^1.3.0",
-    "@xyflow/react": "^12.7.1",
-    "ag-psd": "^28.2.1",
+    "@xyflow/react": "^12.6.0",
     "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",
+    "dockview": "^4.3.1",
     "filesize": "^10.1.6",
     "fracturedjsonjs": "^4.1.0",
     "framer-motion": "^11.10.0",
-    "i18next": "^25.2.1",
+    "i18next": "^25.0.1",
     "i18next-http-backend": "^3.0.2",
-    "idb-keyval": "^6.2.2",
+    "idb-keyval": "^6.2.1",
     "jsondiffpatch": "^0.7.3",
     "konva": "^9.3.20",
-    "linkify-react": "^4.3.1",
-    "linkifyjs": "^4.3.1",
+    "linkify-react": "^4.2.0",
+    "linkifyjs": "^4.2.0",
+    "lodash-es": "^4.17.21",
     "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": "^2.11.4",
+    "overlayscrollbars": "^2.11.1",
     "overlayscrollbars-react": "^0.5.6",
     "perfect-freehand": "^1.2.2",
-    "query-string": "^9.2.1",
+    "query-string": "^9.1.1",
     "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": "^7.58.1",
+    "react-hook-form": "^7.56.1",
     "react-hotkeys-hook": "4.5.0",
-    "react-i18next": "^15.5.3",
+    "react-i18next": "^15.5.1",
     "react-icons": "^5.5.0",
     "react-redux": "9.2.0",
-    "react-resizable-panels": "^3.0.3",
+    "react-resizable-panels": "^2.1.8",
     "react-textarea-autosize": "^8.5.9",
     "react-use": "^17.6.0",
-    "react-virtuoso": "^4.13.0",
+    "react-virtuoso": "^4.12.6",
     "redux-dynamic-middlewares": "^2.2.0",
     "redux-remember": "^5.2.0",
     "redux-undo": "^1.1.0",
@@ -99,12 +110,12 @@
     "roarr": "^7.21.1",
     "serialize-error": "^12.0.0",
     "socket.io-client": "^4.8.1",
-    "stable-hash": "^0.0.6",
-    "use-debounce": "^10.0.5",
+    "stable-hash": "^0.0.5",
+    "use-debounce": "^10.0.4",
     "use-device-pixel-ratio": "^1.1.2",
     "uuid": "^11.1.0",
-    "zod": "^3.25.67",
-    "zod-validation-error": "^3.5.2"
+    "zod": "^3.24.3",
+    "zod-validation-error": "^3.4.0"
   },
   "peerDependencies": {
     "react": "^18.2.0",
@@ -121,6 +132,7 @@
     "@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",
@@ -134,7 +146,7 @@
     "eslint": "^8.57.1",
     "eslint-plugin-i18next": "^6.1.1",
     "eslint-plugin-path": "^1.3.0",
-    "knip": "^5.61.3",
+    "knip": "^5.50.5",
     "openapi-types": "^12.1.3",
     "openapi-typescript": "^7.6.1",
     "prettier": "^3.5.3",
@@ -143,7 +155,7 @@
     "tsafe": "^1.8.5",
     "type-fest": "^4.40.0",
     "typescript": "^5.8.3",
-    "vite": "^7.0.2",
+    "vite": "^6.3.3",
     "vite-plugin-css-injected-by-js": "^3.5.2",
     "vite-plugin-dts": "^4.5.3",
     "vite-plugin-eslint": "^1.8.1",
@@ -151,7 +163,7 @@
     "vitest": "^3.1.2"
   },
   "engines": {
-    "pnpm": "10"
+    "pnpm": "8"
   },
-  "packageManager": "pnpm@10.12.4"
+  "packageManager": "pnpm@8.15.9+sha512.499434c9d8fdd1a2794ebf4552b3b25c0a633abcee5bb15e7b5de90f32f47b513aca98cd5cfd001c31f0db454bc3804edccd578501e4ca293a6816166bbd9f81"
 }

invokeai/frontend/web/pnpm-workspace.yaml

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

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

@@ -225,16 +225,7 @@
     "prompt": {
         "addPromptTrigger": "Add Prompt Trigger",
         "compatibleEmbeddings": "Compatible Embeddings",
-        "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"
+        "noMatchingTriggers": "No matching triggers"
     },
     "queue": {
         "queue": "Queue",
@@ -344,14 +335,14 @@
         "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": "Drop or Upload",
+        "dropOrUpload": "$t(gallery.drop) or Upload",
         "dropToUpload": "$t(gallery.drop) to Upload",
         "deleteImage_one": "Delete Image",
         "deleteImage_other": "Delete {{count}} Images",
@@ -366,7 +357,7 @@
         "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",
@@ -405,8 +396,7 @@
         "compareHelp4": "Press <Kbd>Z</Kbd> or <Kbd>Esc</Kbd> to exit.",
         "openViewer": "Open Viewer",
         "closeViewer": "Close Viewer",
-        "move": "Move",
-        "useForPromptGeneration": "Use for Prompt Generation"
+        "move": "Move"
     },
     "hotkeys": {
         "hotkeys": "Hotkeys",
@@ -589,16 +579,6 @@
             "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": {
@@ -762,7 +742,7 @@
         "vae": "VAE",
         "width": "Width",
         "workflow": "Workflow",
-        "canvasV2Metadata": "Canvas Layers"
+        "canvasV2Metadata": "Canvas"
     },
     "modelManager": {
         "active": "active",
@@ -783,7 +763,7 @@
         "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 the 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 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?",
@@ -826,11 +806,7 @@
         "urlUnauthorizedErrorMessage": "You may need to configure an API token to access this model.",
         "urlUnauthorizedErrorMessage2": "Learn how here.",
         "imageEncoderModelId": "Image Encoder Model ID",
-        "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",
+        "includesNModels": "Includes {{n}} models and their dependencies",
         "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.",
@@ -893,25 +869,6 @@
         "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",
@@ -948,8 +905,7 @@
         "selectModel": "Select a Model",
         "noLoRAsInstalled": "No LoRAs installed",
         "noRefinerModelsInstalled": "No SDXL Refiner models installed",
-        "defaultVAE": "Default VAE",
-        "noCompatibleLoRAs": "No Compatible LoRAs"
+        "defaultVAE": "Default VAE"
     },
     "nodes": {
         "arithmeticSequence": "Arithmetic Sequence",
@@ -1191,7 +1147,6 @@
             "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)",
@@ -1199,9 +1154,7 @@
             "canvasIsSelectingObject": "Canvas is busy (selecting object)",
             "noPrompts": "No prompts generated",
             "noNodesInGraph": "No nodes in graph",
-            "systemDisconnected": "System disconnected",
-            "promptExpansionPending": "Prompt expansion in progress",
-            "promptExpansionResultPending": "Please accept or discard your prompt expansion result"
+            "systemDisconnected": "System disconnected"
         },
         "maskBlur": "Mask Blur",
         "negativePromptPlaceholder": "Negative Prompt",
@@ -1359,21 +1312,6 @@
         "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",
@@ -1399,15 +1337,9 @@
         "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",
-        "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."
+        "workflowUnpublished": "Workflow Unpublished"
     },
     "popovers": {
         "clipSkip": {
@@ -1930,7 +1862,6 @@
         "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",
@@ -1956,13 +1887,11 @@
         "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",
@@ -2063,8 +1992,6 @@
         "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",
@@ -2331,9 +2258,6 @@
                 "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",
@@ -2362,7 +2286,6 @@
             "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",
@@ -2380,11 +2303,6 @@
             "saveToGallery": "Save To Gallery",
             "showResultsOn": "Showing Results",
             "showResultsOff": "Hiding Results"
-        },
-        "autoSwitch": {
-            "off": "Off",
-            "switchOnStart": "On Start",
-            "switchOnFinish": "On Finish"
         }
     },
     "upscaling": {
@@ -2451,8 +2369,7 @@
         "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.",
-        "togglePromptPreviews": "Toggle Prompt Previews"
+        "viewModeTooltip": "This is how your prompt will look with your currently selected template. To edit your prompt, click anywhere in the text box."
     },
     "upsell": {
         "inviteTeammates": "Invite Teammates",
@@ -2472,55 +2389,6 @@
             "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": {
@@ -2560,9 +2428,8 @@
     "whatsNew": {
         "whatsNewInInvoke": "What's New in Invoke",
         "items": [
-            "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."
+            "Inpainting: Per-mask noise levels and denoise limits.",
+            "Canvas: Smarter aspect ratios for SDXL and improved scroll-to-zoom."
         ],
         "readReleaseNotes": "Read Release Notes",
         "watchRecentReleaseVideos": "Watch Recent Release Videos",
@@ -2571,16 +2438,62 @@
     "supportVideos": {
         "supportVideos": "Support Videos",
         "gettingStarted": "Getting Started",
+        "controlCanvas": "Control Canvas",
         "watch": "Watch",
-        "studioSessionsDesc": "Join our <DiscordLink /> to participate in the live sessions and ask questions. Sessions are uploaded to the playlist the following week.",
+        "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.",
         "videos": {
-            "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."
+            "creatingYourFirstImage": {
+                "title": "Creating Your First Image",
+                "description": "Introduction to creating an image from scratch using Invoke's tools."
             },
-            "studioSessions": {
-                "title": "Studio Sessions",
-                "description": "Deep dive sessions exploring advanced Invoke features, creative workflows, and community discussions."
+            "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."
             }
         }
     }

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

@@ -2,7 +2,8 @@ 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 { $didStudioInit, type StudioInitAction } from 'app/hooks/useStudioInitAction';
+import type { StudioInitAction } from 'app/hooks/useStudioInitAction';
+import { $globalIsLoading } from 'app/store/nanostores/globalIsLoading';
 import type { PartialAppConfig } from 'app/types/invokeai';
 import Loading from 'common/components/Loading/Loading';
 import { useClearStorage } from 'common/hooks/useClearStorage';
@@ -11,7 +12,6 @@ import { memo, useCallback } from 'react';
 import { ErrorBoundary } from 'react-error-boundary';
 
 import AppErrorBoundaryFallback from './AppErrorBoundaryFallback';
-import ThemeLocaleProvider from './ThemeLocaleProvider';
 const DEFAULT_CONFIG = {};
 
 interface Props {
@@ -20,7 +20,7 @@ interface Props {
 }
 
 const App = ({ config = DEFAULT_CONFIG, studioInitAction }: Props) => {
-  const didStudioInit = useStore($didStudioInit);
+  const globalIsLoading = useStore($globalIsLoading);
   const clearStorage = useClearStorage();
 
   const handleReset = useCallback(() => {
@@ -31,14 +31,12 @@ const App = ({ config = DEFAULT_CONFIG, studioInitAction }: Props) => {
 
   return (
     <ErrorBoundary onReset={handleReset} FallbackComponent={AppErrorBoundaryFallback}>
-      <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>
+      <Box id="invoke-app-wrapper" w="100dvw" h="100dvh" position="relative" overflow="hidden">
+        <AppContent />
+        {globalIsLoading && <Loading />}
+      </Box>
+      <GlobalHookIsolator config={config} studioInitAction={studioInitAction} />
+      <GlobalModalIsolator />
     </ErrorBoundary>
   );
 };

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

@@ -1,5 +1,4 @@
 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';
@@ -11,15 +10,14 @@ 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';
@@ -45,8 +43,6 @@ export const GlobalHookIsolator = memo(
     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.
@@ -57,18 +53,16 @@ export const GlobalHookIsolator = memo(
     }, [language]);
 
     useEffect(() => {
-      logger.info({ config }, 'Received config');
-      dispatch(configChanged(config));
+      if (size(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

@@ -1,14 +1,11 @@
 import { useAppSelector } from 'app/store/storeHooks';
 import { useIsRegionFocused } from 'common/hooks/focus';
 import { useAssertSingleton } from 'common/hooks/useAssertSingleton';
-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 { selectIsStaging } from 'features/controlLayers/store/canvasStagingAreaSlice';
+import { useImageActions } from 'features/gallery/hooks/useImageActions';
 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';
@@ -30,64 +27,59 @@ GlobalImageHotkeys.displayName = 'GlobalImageHotkeys';
 const GlobalImageHotkeysInternal = memo(({ imageDTO }: { imageDTO: ImageDTO }) => {
   const isGalleryFocused = useIsRegionFocused('gallery');
   const isViewerFocused = useIsRegionFocused('viewer');
-
-  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);
+  const imageActions = useImageActions(imageDTO);
+  const isStaging = useAppSelector(selectIsStaging);
+  const isUpscalingEnabled = useFeatureStatus('upscaling');
 
   useRegisteredHotkeys({
     id: 'loadWorkflow',
     category: 'viewer',
-    callback: loadWorkflow.load,
-    options: { enabled: loadWorkflow.isEnabled && isFocusOK },
-    dependencies: [loadWorkflow, isFocusOK],
+    callback: imageActions.loadWorkflow,
+    options: { enabled: isGalleryFocused || isViewerFocused },
+    dependencies: [imageActions.loadWorkflow, isGalleryFocused, isViewerFocused],
   });
-
   useRegisteredHotkeys({
     id: 'recallAll',
     category: 'viewer',
-    callback: recallAll.recall,
-    options: { enabled: recallAll.isEnabled && isFocusOK },
-    dependencies: [recallAll, isFocusOK],
+    callback: imageActions.recallAll,
+    options: { enabled: !isStaging && (isGalleryFocused || isViewerFocused) },
+    dependencies: [imageActions.recallAll, isStaging, isGalleryFocused, isViewerFocused],
   });
-
   useRegisteredHotkeys({
     id: 'recallSeed',
     category: 'viewer',
-    callback: recallSeed.recall,
-    options: { enabled: recallSeed.isEnabled && isFocusOK },
-    dependencies: [recallSeed, isFocusOK],
+    callback: imageActions.recallSeed,
+    options: { enabled: isGalleryFocused || isViewerFocused },
+    dependencies: [imageActions.recallSeed, isGalleryFocused, isViewerFocused],
   });
-
   useRegisteredHotkeys({
     id: 'recallPrompts',
     category: 'viewer',
-    callback: recallPrompts.recall,
-    options: { enabled: recallPrompts.isEnabled && isFocusOK },
-    dependencies: [recallPrompts, isFocusOK],
+    callback: imageActions.recallPrompts,
+    options: { enabled: isGalleryFocused || isViewerFocused },
+    dependencies: [imageActions.recallPrompts, isGalleryFocused, isViewerFocused],
   });
-
   useRegisteredHotkeys({
     id: 'remix',
     category: 'viewer',
-    callback: recallRemix.recall,
-    options: { enabled: recallRemix.isEnabled && isFocusOK },
-    dependencies: [recallRemix, isFocusOK],
+    callback: imageActions.remix,
+    options: { enabled: isGalleryFocused || isViewerFocused },
+    dependencies: [imageActions.remix, isGalleryFocused, isViewerFocused],
   });
-
   useRegisteredHotkeys({
     id: 'useSize',
     category: 'viewer',
-    callback: recallDimensions.recall,
-    options: { enabled: recallDimensions.isEnabled && isFocusOK },
-    dependencies: [recallDimensions, isFocusOK],
+    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],
   });
-
   return null;
 });
 

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

@@ -42,6 +42,7 @@ 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;
@@ -329,7 +330,9 @@ const InvokeAIUI = ({
     <React.StrictMode>
       <Provider store={store}>
         <React.Suspense fallback={<Loading />}>
-          <App config={config} studioInitAction={studioInitAction} />
+          <ThemeLocaleProvider>
+            <App config={config} studioInitAction={studioInitAction} />
+          </ThemeLocaleProvider>
         </React.Suspense>
       </Provider>
     </React.StrictMode>

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

@@ -8,7 +8,7 @@ import { paramsReset } from 'features/controlLayers/store/paramsSlice';
 import type { CanvasRasterLayerState } from 'features/controlLayers/store/types';
 import { imageDTOToImageObject } from 'features/controlLayers/store/util';
 import { sentImageToCanvas } from 'features/gallery/store/actions';
-import { MetadataUtils } from 'features/metadata/parsing';
+import { parseAndRecallAllMetadata } from 'features/metadata/util/handlers';
 import { $hasTemplates } from 'features/nodes/store/nodesSlice';
 import { $isWorkflowLibraryModalOpen } from 'features/nodes/store/workflowLibraryModal';
 import {
@@ -19,9 +19,7 @@ import {
 } from 'features/nodes/store/workflowLibrarySlice';
 import { $isStylePresetsMenuOpen, activeStylePresetIdChanged } from 'features/stylePresets/store/stylePresetSlice';
 import { toast } from 'features/toast/toast';
-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 { activeTabCanvasRightPanelChanged, setActiveTab } from 'features/ui/store/uiSlice';
 import { useLoadWorkflowWithDialog } from 'features/workflowLibrary/components/LoadWorkflowConfirmationAlertDialog';
 import { atom } from 'nanostores';
 import { useCallback, useEffect } from 'react';
@@ -92,7 +90,6 @@ 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(sentImageToCanvas());
@@ -119,23 +116,23 @@ export const useStudioInitAction = (action?: StudioInitAction) => {
       const metadata = getImageMetadataResult.value;
       store.dispatch(canvasReset());
       // This shows a toast
-      await MetadataUtils.recallAll(metadata, store);
+      await parseAndRecallAllMetadata(metadata, true);
     },
     [store, t]
   );
 
   const handleLoadWorkflow = useCallback(
-    (workflowId: string) => {
+    async (workflowId: string) => {
       // This shows a toast
-      loadWorkflowWithDialog({
+      await loadWorkflowWithDialog({
         type: 'library',
         data: workflowId,
         onSuccess: () => {
-          navigationApi.switchToTab('workflows');
+          store.dispatch(setActiveTab('workflows'));
         },
       });
     },
-    [loadWorkflowWithDialog]
+    [loadWorkflowWithDialog, store]
   );
 
   const handleSelectStylePreset = useCallback(
@@ -149,7 +146,7 @@ export const useStudioInitAction = (action?: StudioInitAction) => {
         return;
       }
       store.dispatch(activeStylePresetIdChanged(stylePresetId));
-      navigationApi.switchToTab('canvas');
+      store.dispatch(setActiveTab('canvas'));
       toast({
         title: t('toast.stylePresetLoaded'),
         status: 'info',
@@ -159,34 +156,33 @@ export const useStudioInitAction = (action?: StudioInitAction) => {
   );
 
   const handleGoToDestination = useCallback(
-    async (destination: StudioDestinationAction['data']['destination']) => {
+    (destination: StudioDestinationAction['data']['destination']) => {
       switch (destination) {
         case 'generation':
-          // Go to the generate tab, open the launchpad
-          await navigationApi.focusPanel('generate', LAUNCHPAD_PANEL_ID);
+          // Go to the canvas tab, open the image viewer, and enable send-to-gallery mode
           store.dispatch(paramsReset());
           store.dispatch(activeTabCanvasRightPanelChanged('gallery'));
           break;
         case 'canvas':
-          // Go to the canvas tab, open the launchpad
-          await navigationApi.focusPanel('canvas', WORKSPACE_PANEL_ID);
+          // Go to the canvas tab, close the image viewer, and disable send-to-gallery mode
+          store.dispatch(canvasReset());
           break;
         case 'workflows':
           // Go to the workflows tab
-          navigationApi.switchToTab('workflows');
+          store.dispatch(setActiveTab('workflows'));
           break;
         case 'upscaling':
           // Go to the upscaling tab
-          navigationApi.switchToTab('upscaling');
+          store.dispatch(setActiveTab('upscaling'));
           break;
         case 'viewAllWorkflows':
           // Go to the workflows tab and open the workflow library modal
-          navigationApi.switchToTab('workflows');
+          store.dispatch(setActiveTab('workflows'));
           $isWorkflowLibraryModalOpen.set(true);
           break;
         case 'viewAllWorkflowsRecommended':
           // Go to the workflows tab and open the workflow library modal with the recommended workflows view
-          navigationApi.switchToTab('workflows');
+          store.dispatch(setActiveTab('workflows'));
           $isWorkflowLibraryModalOpen.set(true);
           store.dispatch(workflowLibraryViewChanged('defaults'));
           store.dispatch(workflowLibraryTagsReset());
@@ -198,7 +194,7 @@ export const useStudioInitAction = (action?: StudioInitAction) => {
           break;
         case 'viewAllStylePresets':
           // Go to the canvas tab and open the style presets menu
-          navigationApi.switchToTab('canvas');
+          store.dispatch(setActiveTab('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/v4';
+import { z } from 'zod';
 
 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 @observ33r/object-equals's objectEquals for equality check.
+ * A memoized selector creator that uses LRU cache and lodash's isEqual for equality check.
  */
 export const createMemoizedSelector = createSelectorCreator({
   memoize: lruMemoize,
   memoizeOptions: {
-    resultEqualityCheck: objectEquals,
+    resultEqualityCheck: isEqual,
   },
   argsMemoize: lruMemoize,
 });

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

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

@@ -8,6 +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 { addEnsureImageIsSelectedListener } from 'app/store/middleware/listenerMiddleware/listeners/ensureImageIsSelectedListener';
+import { addGalleryImageClickedListener } from 'app/store/middleware/listenerMiddleware/listeners/galleryImageClicked';
 import { addGetOpenAPISchemaListener } from 'app/store/middleware/listenerMiddleware/listeners/getOpenAPISchema';
 import { addImageAddedToBoardFulfilledListener } from 'app/store/middleware/listenerMiddleware/listeners/imageAddedToBoard';
 import { addImageRemovedFromBoardFulfilledListener } from 'app/store/middleware/listenerMiddleware/listeners/imageRemovedFromBoard';
@@ -19,6 +22,7 @@ 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();
 
@@ -40,7 +44,12 @@ addImageUploadedFulfilledListener(startAppListening);
 // Image deleted
 addDeleteBoardAndImagesFulfilledListener(startAppListening);
 
+// Gallery
+addGalleryImageClickedListener(startAppListening);
+
 // User Invoked
+addEnqueueRequestedLinear(startAppListening);
+addEnqueueRequestedUpscale(startAppListening);
 addAnyEnqueuedListener(startAppListening);
 addBatchEnqueuedListener(startAppListening);
 
@@ -71,3 +80,5 @@ addAppConfigReceivedListener(startAppListening);
 addAdHocPostProcessingRequestedListener(startAppListening);
 
 addSetDefaultSettingsListener(startAppListening);
+
+addEnsureImageIsSelectedListener(startAppListening);

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

@@ -1,29 +1,15 @@
 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: async (action, { unsubscribe, cancelActiveListeners, take, getState, dispatch }) => {
+    effect: (action, { unsubscribe, cancelActiveListeners }) => {
       // 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/boardIdSelected.ts

@@ -1,6 +1,6 @@
 import { isAnyOf } from '@reduxjs/toolkit';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
-import { selectGetImageNamesQueryArgs, selectSelectedBoardId } from 'features/gallery/store/gallerySelectors';
+import { selectListImagesBaseQueryArgs } from 'features/gallery/store/gallerySelectors';
 import { boardIdSelected, galleryViewChanged, imageSelected } from 'features/gallery/store/gallerySlice';
 import { imagesApi } from 'services/api/endpoints/images';
 
@@ -11,35 +11,36 @@ 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 board_id = selectSelectedBoardId(state);
-
-      const queryArgs = { ...selectGetImageNamesQueryArgs(state), board_id };
+      const queryArgs = { ...selectListImagesBaseQueryArgs(state), offset: 0 };
 
       // 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.getImageNames.select(queryArgs)(getState()).isSuccess,
+        () => imagesApi.endpoints.listImages.select(queryArgs)(getState()).isSuccess,
         5000
       );
 
-      if (!isSuccess) {
+      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?.image_name ?? null));
+        } else if (boardImagesData) {
+          dispatch(imageSelected(boardImagesData.items[0]?.image_name ?? null));
+        } else {
+          // board has no images - deselect
+          dispatch(imageSelected(null));
+        }
+      } else {
+        // fallback - deselect
         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

@@ -0,0 +1,151 @@
+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 {
+  canvasSessionIdCreated,
+  generateSessionIdCreated,
+  selectCanvasSessionId,
+  selectGenerateSessionId,
+} from 'features/controlLayers/store/canvasStagingAreaSlice';
+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 { selectActiveTab } from 'features/ui/store/uiSelectors';
+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 tab = selectActiveTab(getState());
+      let sessionId = null;
+      if (tab === 'generate') {
+        sessionId = selectGenerateSessionId(getState());
+        if (!sessionId) {
+          dispatch(generateSessionIdCreated());
+          sessionId = selectGenerateSessionId(getState());
+        }
+      } else if (tab === 'canvas') {
+        sessionId = selectCanvasSessionId(getState());
+        if (!sessionId) {
+          dispatch(canvasSessionIdCreated());
+          sessionId = selectCanvasSessionId(getState());
+        }
+      } else {
+        log.warn(`Enqueue requested in unsupported tab ${tab}`);
+        return;
+      }
+
+      const state = getState();
+      const destination = sessionId;
+      assert(destination !== null);
+
+      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 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

@@ -0,0 +1,44 @@
+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/ensureImageIsSelectedListener.ts

@@ -0,0 +1,16 @@
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
+import { imageSelected } from 'features/gallery/store/gallerySlice';
+import { imagesApi } from 'services/api/endpoints/images';
+
+export const addEnsureImageIsSelectedListener = (startAppListening: AppStartListening) => {
+  // 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]?.image_name ?? null));
+      }
+    },
+  });
+};

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

@@ -0,0 +1,77 @@
+import { createAction } from '@reduxjs/toolkit';
+import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
+import { selectListImageNamesQueryArgs } from 'features/gallery/store/gallerySelectors';
+import { imageToCompareChanged, selectionChanged } from 'features/gallery/store/gallerySlice';
+import { uniq } from 'lodash-es';
+import { imagesApi } from 'services/api/endpoints/images';
+
+export const galleryImageClicked = createAction<{
+  imageName: string;
+  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 { imageName, shiftKey, ctrlKey, metaKey, altKey } = action.payload;
+      const state = getState();
+      const queryArgs = selectListImageNamesQueryArgs(state);
+      const imageNames = imagesApi.endpoints.getImageNames.select(queryArgs)(state).data ?? [];
+
+      // If we don't have the image names cached, we can't perform selection operations
+      // This can happen if the user clicks on an image before the names are loaded
+      if (imageNames.length === 0) {
+        // For basic click without modifiers, we can still set selection
+        if (!shiftKey && !ctrlKey && !metaKey && !altKey) {
+          dispatch(selectionChanged([imageName]));
+        }
+        return;
+      }
+
+      const selection = state.gallery.selection;
+
+      if (altKey) {
+        if (state.gallery.imageToCompare === imageName) {
+          dispatch(imageToCompareChanged(null));
+        } else {
+          dispatch(imageToCompareChanged(imageName));
+        }
+      } else if (shiftKey) {
+        const rangeEndImageName = imageName;
+        const lastSelectedImage = selection.at(-1);
+        const lastClickedIndex = imageNames.findIndex((name) => name === lastSelectedImage);
+        const currentClickedIndex = imageNames.findIndex((name) => 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 = imageNames.slice(start, end + 1);
+          dispatch(selectionChanged(uniq(selection.concat(imagesToSelect))));
+        }
+      } else if (ctrlKey || metaKey) {
+        if (selection.some((n) => n === imageName) && selection.length > 1) {
+          dispatch(selectionChanged(uniq(selection.filter((n) => n !== imageName))));
+        } else {
+          dispatch(selectionChanged(uniq(selection.concat(imageName))));
+        }
+      } else {
+        dispatch(selectionChanged([imageName]));
+      }
+    },
+  });
+};

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/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/modelSelected.ts

@@ -1,28 +1,14 @@
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
-import { bboxSyncedToOptimalDimension, rgRefImageModelChanged } from 'features/controlLayers/store/canvasSlice';
+import { bboxSyncedToOptimalDimension } from 'features/controlLayers/store/canvasSlice';
 import { selectIsStaging } from 'features/controlLayers/store/canvasStagingAreaSlice';
 import { loraDeleted } from 'features/controlLayers/store/lorasSlice';
-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 { modelChanged, vaeSelected } from 'features/controlLayers/store/paramsSlice';
+import { selectBboxModelBase } from 'features/controlLayers/store/selectors';
 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');
 
@@ -39,8 +25,9 @@ export const addModelSelectedListener = (startAppListening: AppStartListening) =
       }
 
       const newModel = result.data;
-      const newBase = newModel.base;
-      const didBaseModelChange = state.params.model?.base !== newBase;
+
+      const newBaseModel = newModel.base;
+      const didBaseModelChange = state.params.model?.base !== newBaseModel;
 
       if (didBaseModelChange) {
         // we may need to reset some incompatible submodels
@@ -48,7 +35,7 @@ export const addModelSelectedListener = (startAppListening: AppStartListening) =
 
         // handle incompatible loras
         state.loras.loras.forEach((lora) => {
-          if (lora.model.base !== newBase) {
+          if (lora.model.base !== newBaseModel) {
             dispatch(loraDeleted({ id: lora.id }));
             modelsCleared += 1;
           }
@@ -56,82 +43,20 @@ export const addModelSelectedListener = (startAppListening: AppStartListening) =
 
         // handle incompatible vae
         const { vae } = state.params;
-        if (vae && vae.base !== newBase) {
+        if (vae && vae.base !== newBaseModel) {
           dispatch(vaeSelected(null));
           modelsCleared += 1;
         }
 
-        // 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;
-            }
-          }
-        }
+        // 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' } }));
+        //     }
+        //   }
+        // });
 
         if (modelsCleared > 0) {
           toast({
@@ -146,16 +71,9 @@ export const addModelSelectedListener = (startAppListening: AppStartListening) =
       }
 
       dispatch(modelChanged({ model: newModel, previousModel: state.params.model }));
-
       const modelBase = selectBboxModelBase(state);
-
-      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());
-        }
+      if (!selectIsStaging(state) && modelBase !== state.params.model?.base) {
+        dispatch(bboxSyncedToOptimalDimension());
       }
     },
   });

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

@@ -1,9 +1,7 @@
 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,
@@ -11,7 +9,6 @@ import {
   setSteps,
   vaePrecisionChanged,
   vaeSelected,
-  widthChanged,
 } from 'features/controlLayers/store/paramsSlice';
 import { setDefaultSettings } from 'features/parameters/store/actions';
 import {
@@ -26,7 +23,6 @@ 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';
@@ -90,16 +86,10 @@ export const addSetDefaultSettingsListener = (startAppListening: AppStartListeni
           }
         }
 
-        if (!isNil(cfg_rescale_multiplier)) {
+        if (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) {
@@ -116,24 +106,15 @@ export const addSetDefaultSettingsListener = (startAppListening: AppStartListeni
         const setSizeOptions = { updateAspectRatio: true, clamp: true };
 
         const isStaging = selectIsStaging(getState());
-        const activeTab = selectActiveTab(getState());
-        if (activeTab === 'generate') {
+        if (!isStaging && width) {
           if (isParameterWidth(width)) {
-            dispatch(widthChanged({ width, ...setSizeOptions }));
-          }
-          if (isParameterHeight(height)) {
-            dispatch(heightChanged({ height, ...setSizeOptions }));
+            dispatch(bboxWidthChanged({ width, ...setSizeOptions }));
           }
         }
 
-        if (activeTab === 'canvas') {
-          if (!isStaging) {
-            if (isParameterWidth(width)) {
-              dispatch(bboxWidthChanged({ width, ...setSizeOptions }));
-            }
-            if (isParameterHeight(height)) {
-              dispatch(bboxHeightChanged({ height, ...setSizeOptions }));
-            }
+        if (!isStaging && height) {
+          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 (objectEquals(prevQueueStatusData?.queue, nextQueueStatusData.queue)) {
+        if (isEqual(prevQueueStatusData?.queue, nextQueueStatusData.queue)) {
           return;
         }
 

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

@@ -0,0 +1,13 @@
+import { $didStudioInit } from 'app/hooks/useStudioInitAction';
+import { atom, computed } from 'nanostores';
+import { flushSync } from 'react-dom';
+
+export const $isLayoutLoading = atom(false);
+export const setIsLayoutLoading = (isLoading: boolean) => {
+  flushSync(() => {
+    $isLayoutLoading.set(isLoading);
+  });
+};
+export const $globalIsLoading = computed([$didStudioInit, $isLayoutLoading], (didStudioInit, isLayoutLoading) => {
+  return !didStudioInit || isLayoutLoading;
+});

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

@@ -1,3 +1,4 @@
+import { useStore } from '@nanostores/react';
 import type { AppStore } from 'app/store/store';
 import { atom } from 'nanostores';
 
@@ -31,3 +32,11 @@ 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

@@ -11,7 +11,5 @@ 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

@@ -4,7 +4,6 @@ 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';
@@ -17,6 +16,7 @@ import { paramsPersistConfig, paramsSlice } from 'features/controlLayers/store/p
 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';
@@ -28,6 +28,7 @@ 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';
@@ -56,6 +57,7 @@ const allReducers = {
   [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,
@@ -101,6 +103,7 @@ 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,

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

@@ -1,8 +1,8 @@
-import type { AppStore, AppThunkDispatch, RootState } from 'app/store/store';
+import type { 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.withTypes<AppStore>()();
+export const useAppStore = () => useStore<RootState>();

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

@@ -14,7 +14,6 @@ export type AppFeature =
   | 'githubLink'
   | 'discordLink'
   | 'bugLink'
-  | 'aboutModal'
   | 'localization'
   | 'consoleLogging'
   | 'dynamicPrompting'
@@ -30,8 +29,7 @@ export type AppFeature =
   | 'hfToken'
   | 'retryQueueItem'
   | 'cancelAndClearAll'
-  | 'chatGPT4oHigh'
-  | 'modelRelationships';
+  | 'chatGPT4oHigh';
 /**
  * A disable-able Stable Diffusion feature
  */
@@ -78,7 +76,6 @@ 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

@@ -0,0 +1,56 @@
+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

@@ -8,16 +8,21 @@ const Loading = () => {
   return (
     <Flex
       position="absolute"
+      width="100dvw"
+      height="100dvh"
       alignItems="center"
       justifyContent="center"
-      bg="hsl(220 12% 10% / 1)" // base.900
-      inset={0}
+      bg="#151519"
+      top={0}
+      right={0}
+      bottom={0}
+      left={0}
       zIndex={99999}
     >
       <Image src={InvokeLogoWhite} w="8rem" h="8rem" />
       <Spinner
         label="Loading"
-        color="hsl(220 12% 68% / 1)" // base.300
+        color="grey"
         position="absolute"
         size="sm"
         width="24px !important"

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

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

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,
 });
 
-export const isGroup = <T extends object>(optionOrGroup: OptionOrGroup<T>): optionOrGroup is Group<T> => {
+const isGroup = <T extends object>(optionOrGroup: OptionOrGroup<T>): optionOrGroup is Group<T> => {
   return uniqueGroupKey in optionOrGroup && optionOrGroup[uniqueGroupKey] === true;
 };
 
@@ -198,10 +198,6 @@ 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> = {
@@ -314,9 +310,9 @@ const flattenOptions = <T extends object>(options: OptionOrGroup<T>[]): T[] => {
   return flattened;
 };
 
-export type GroupStatusMap = Record<string, boolean>;
+type GroupStatusMap = Record<string, boolean>;
 
-const useTogglableGroups = <T extends object>(options: OptionOrGroup<T>[], initialGroupStates?: GroupStatusMap) => {
+const useTogglableGroups = <T extends object>(options: OptionOrGroup<T>[]) => {
   const groupsWithOptions = useMemo(() => {
     const ids: string[] = [];
     for (const optionOrGroup of options) {
@@ -336,16 +332,14 @@ const useTogglableGroups = <T extends object>(options: OptionOrGroup<T>[], initi
     const groupStatusMap = $groupStatusMap.get();
     const newMap: GroupStatusMap = {};
     for (const id of groupsWithOptions) {
-      if (initialGroupStates && initialGroupStates[id] !== undefined) {
-        newMap[id] = initialGroupStates[id];
+      if (newMap[id] === undefined) {
+        newMap[id] = false;
       } else if (groupStatusMap[id] !== undefined) {
         newMap[id] = groupStatusMap[id];
-      } else {
-        newMap[id] = false;
       }
     }
     $groupStatusMap.set(newMap);
-  }, [groupsWithOptions, $groupStatusMap, initialGroupStates]);
+  }, [groupsWithOptions, $groupStatusMap]);
 
   const toggleGroup = useCallback(
     (idToToggle: string) => {
@@ -517,14 +511,10 @@ 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,
-    initialGroupStates
-  );
+  const { $groupStatusMap, $areAllGroupsDisabled, toggleGroup } = useTogglableGroups(optionsOrGroups);
   const $activeOptionId = useAtom(getFirstOptionId(optionsOrGroups, getOptionId));
   const $compactView = useAtom(true);
   const $optionsOrGroups = useAtom(optionsOrGroups);

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

@@ -1,15 +1,20 @@
 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 } from 'react-icons/pi';
+import { PiArrowsCounterClockwiseBold, PiFilePlusBold } 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]);
@@ -18,6 +23,12 @@ 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

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

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

@@ -1,115 +0,0 @@
-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/useBoolean.ts

@@ -73,7 +73,7 @@ export const useBoolean = (initialValue: boolean): UseBoolean => {
   };
 };
 
-type UseDisclosure = {
+export type UseDisclosure = {
   isOpen: boolean;
   open: () => void;
   close: () => void;

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

@@ -0,0 +1,165 @@
+/* eslint-disable @typescript-eslint/no-explicit-any */
+
+/**
+ * Adapted from https://github.com/chakra-ui/chakra-ui/blob/v2/packages/hooks/src/use-outside-click.ts
+ *
+ * The main change here is to support filtering of outside clicks via a `filter` function.
+ *
+ * This lets us work around issues with portals and components like popovers, which typically close on an outside click.
+ *
+ * For example, consider a popover that has a custom drop-down component inside it, which uses a portal to render
+ * the drop-down options. The original outside click handler would close the popover when clicking on the drop-down options,
+ * because the click is outside the popover - but we expect the popover to stay open in this case.
+ *
+ * A filter function like this can fix that:
+ *
+ * ```ts
+ * const filter = (el: HTMLElement) => el.className.includes('chakra-portal') || el.id.includes('react-select')
+ * ```
+ *
+ * This ignores clicks on react-select-based drop-downs and Chakra UI portals and is used as the default filter.
+ */
+
+import { useCallback, useEffect, useRef } from 'react';
+
+type FilterFunction = (el: HTMLElement | SVGElement) => boolean;
+
+export function useCallbackRef<T extends (...args: any[]) => any>(
+  callback: T | undefined,
+  deps: React.DependencyList = []
+) {
+  const callbackRef = useRef(callback);
+
+  useEffect(() => {
+    callbackRef.current = callback;
+  });
+
+  // eslint-disable-next-line react-hooks/exhaustive-deps
+  return useCallback(((...args) => callbackRef.current?.(...args)) as T, deps);
+}
+
+export interface UseOutsideClickProps {
+  /**
+   * Whether the hook is enabled
+   */
+  enabled?: boolean;
+  /**
+   * The reference to a DOM element.
+   */
+  ref: React.RefObject<HTMLElement | null>;
+  /**
+   * Function invoked when a click is triggered outside the referenced element.
+   */
+  handler?: (e: Event) => void;
+  /**
+   * A function that filters the elements that should be considered as outside clicks.
+   *
+   * If omitted, a default filter function that ignores clicks in Chakra UI portals and react-select components is used.
+   */
+  filter?: FilterFunction;
+}
+
+export const DEFAULT_FILTER: FilterFunction = (el) => {
+  if (el instanceof SVGElement) {
+    // SVGElement's type appears to be incorrect. Its className is not a string, which causes `includes` to fail.
+    // Let's assume that SVG elements with a class name are not part of the portal and should not be filtered.
+    return false;
+  }
+  return el.className.includes('chakra-portal') || el.id.includes('react-select');
+};
+
+/**
+ * Example, used in components like Dialogs and Popovers, so they can close
+ * when a user clicks outside them.
+ */
+export function useFilterableOutsideClick(props: UseOutsideClickProps) {
+  const { ref, handler, enabled = true, filter = DEFAULT_FILTER } = props;
+  const savedHandler = useCallbackRef(handler);
+
+  const stateRef = useRef({
+    isPointerDown: false,
+    ignoreEmulatedMouseEvents: false,
+  });
+
+  const state = stateRef.current;
+
+  useEffect(() => {
+    if (!enabled) {
+      return;
+    }
+    const onPointerDown: any = (e: PointerEvent) => {
+      if (isValidEvent(e, ref, filter)) {
+        state.isPointerDown = true;
+      }
+    };
+
+    const onMouseUp: any = (event: MouseEvent) => {
+      if (state.ignoreEmulatedMouseEvents) {
+        state.ignoreEmulatedMouseEvents = false;
+        return;
+      }
+
+      if (state.isPointerDown && handler && isValidEvent(event, ref)) {
+        state.isPointerDown = false;
+        savedHandler(event);
+      }
+    };
+
+    const onTouchEnd = (event: TouchEvent) => {
+      state.ignoreEmulatedMouseEvents = true;
+      if (handler && state.isPointerDown && isValidEvent(event, ref)) {
+        state.isPointerDown = false;
+        savedHandler(event);
+      }
+    };
+
+    const doc = getOwnerDocument(ref.current);
+    doc.addEventListener('mousedown', onPointerDown, true);
+    doc.addEventListener('mouseup', onMouseUp, true);
+    doc.addEventListener('touchstart', onPointerDown, true);
+    doc.addEventListener('touchend', onTouchEnd, true);
+
+    return () => {
+      doc.removeEventListener('mousedown', onPointerDown, true);
+      doc.removeEventListener('mouseup', onMouseUp, true);
+      doc.removeEventListener('touchstart', onPointerDown, true);
+      doc.removeEventListener('touchend', onTouchEnd, true);
+    };
+  }, [handler, ref, savedHandler, state, enabled, filter]);
+}
+
+function isValidEvent(event: Event, ref: React.RefObject<HTMLElement | null>, filter?: FilterFunction): boolean {
+  const target = (event.composedPath?.()[0] ?? event.target) as HTMLElement;
+
+  if (target) {
+    const doc = getOwnerDocument(target);
+    if (!doc.contains(target)) {
+      return false;
+    }
+  }
+
+  if (ref.current?.contains(target)) {
+    return false;
+  }
+
+  // This is the main logic change from the original hook.
+  if (filter) {
+    // Check if the click is inside an element matching the filter.
+    // This is used for portal-awareness or other general exclusion cases.
+    let currentElement: HTMLElement | null = target;
+    // Traverse up the DOM tree from the target element.
+    while (currentElement && currentElement !== document.body) {
+      if (filter(currentElement)) {
+        return false;
+      }
+      currentElement = currentElement.parentElement;
+    }
+  }
+
+  // If the click is not inside the ref and not inside a portal, it's a valid outside click.
+  return true;
+}
+
+function getOwnerDocument(node?: Element | null): Document {
+  return node?.ownerDocument ?? document;
+}

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

@@ -1,17 +1,13 @@
-import { useAppStore } from 'app/store/storeHooks';
-import { useDeleteImageModalApi } from 'features/deleteImageModal/store/state';
-import { selectSelection } from 'features/gallery/store/gallerySelectors';
+import { useAppDispatch } from 'app/store/storeHooks';
 import { useClearQueue } from 'features/queue/hooks/useClearQueue';
 import { useDeleteCurrentQueueItem } from 'features/queue/hooks/useDeleteCurrentQueueItem';
 import { useInvoke } from 'features/queue/hooks/useInvoke';
 import { useRegisteredHotkeys } from 'features/system/components/HotkeysModal/useHotkeyData';
 import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';
-import { navigationApi } from 'features/ui/layouts/navigation-api';
-
-import { getFocusedRegion } from './focus';
+import { setActiveTab } from 'features/ui/store/uiSlice';
 
 export const useGlobalHotkeys = () => {
-  const { dispatch, getState } = useAppStore();
+  const dispatch = useAppDispatch();
   const isModelManagerEnabled = useFeatureStatus('modelManager');
   const queue = useInvoke();
 
@@ -69,7 +65,7 @@ export const useGlobalHotkeys = () => {
     id: 'selectGenerateTab',
     category: 'app',
     callback: () => {
-      navigationApi.switchToTab('generate');
+      dispatch(setActiveTab('generate'));
     },
     dependencies: [dispatch],
   });
@@ -78,7 +74,7 @@ export const useGlobalHotkeys = () => {
     id: 'selectCanvasTab',
     category: 'app',
     callback: () => {
-      navigationApi.switchToTab('canvas');
+      dispatch(setActiveTab('canvas'));
     },
     dependencies: [dispatch],
   });
@@ -87,7 +83,7 @@ export const useGlobalHotkeys = () => {
     id: 'selectUpscalingTab',
     category: 'app',
     callback: () => {
-      navigationApi.switchToTab('upscaling');
+      dispatch(setActiveTab('upscaling'));
     },
     dependencies: [dispatch],
   });
@@ -96,7 +92,7 @@ export const useGlobalHotkeys = () => {
     id: 'selectWorkflowsTab',
     category: 'app',
     callback: () => {
-      navigationApi.switchToTab('workflows');
+      dispatch(setActiveTab('workflows'));
     },
     dependencies: [dispatch],
   });
@@ -105,7 +101,7 @@ export const useGlobalHotkeys = () => {
     id: 'selectModelsTab',
     category: 'app',
     callback: () => {
-      navigationApi.switchToTab('models');
+      dispatch(setActiveTab('models'));
     },
     options: {
       enabled: isModelManagerEnabled,
@@ -117,26 +113,24 @@ export const useGlobalHotkeys = () => {
     id: 'selectQueueTab',
     category: 'app',
     callback: () => {
-      navigationApi.switchToTab('queue');
+      dispatch(setActiveTab('queue'));
     },
     dependencies: [dispatch, isModelManagerEnabled],
   });
 
-  const deleteImageModalApi = useDeleteImageModalApi();
-  useRegisteredHotkeys({
-    id: 'deleteSelection',
-    category: 'gallery',
-    callback: () => {
-      const focusedRegion = getFocusedRegion();
-      if (focusedRegion !== 'gallery' && focusedRegion !== 'viewer') {
-        return;
-      }
-      const selection = selectSelection(getState());
-      if (!selection.length) {
-        return;
-      }
-      deleteImageModalApi.delete(selection);
-    },
-    dependencies: [getState, deleteImageModalApi],
-  });
+  // TODO: implement delete - needs to handle gallery focus, which has changed w/ dockview
+  // useRegisteredHotkeys({
+  //   id: 'deleteSelection',
+  //   category: 'gallery',
+  //   callback: () => {
+  //     if (!selection.length) {
+  //       return;
+  //     }
+  //     deleteImageModal.delete(selection);
+  //   },
+  //   options: {
+  //     enabled: (isGalleryFocused || isImageViewerFocused) && isDeleteEnabledByTab && !isWorkflowsFocused,
+  //   },
+  //   dependencies: [isWorkflowsFocused, isDeleteEnabledByTab, selection, isWorkflowsFocused],
+  // });
 };

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

@@ -2,10 +2,10 @@ import type { ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
 import { createSelector } from '@reduxjs/toolkit';
 import { useAppSelector } from 'app/store/storeHooks';
 import type { GroupBase } from 'chakra-react-select';
-import { groupBy, reduce } from 'es-toolkit/compat';
 import { selectParamsSlice } from 'features/controlLayers/store/paramsSlice';
 import type { ModelIdentifierField } from 'features/nodes/types/common';
 import { selectSystemShouldEnableModelDescriptions } from 'features/system/store/systemSlice';
+import { groupBy, reduce } from 'lodash-es';
 import { useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
 import type { AnyModelConfig } from 'services/api/types';

invokeai/frontend/web/src/common/hooks/useImageUploadButton.tsx

@@ -21,15 +21,11 @@ type UseImageUploadButtonArgs =
       isDisabled?: boolean;
       allowMultiple: false;
       onUpload?: (imageDTO: ImageDTO) => void;
-      onUploadStarted?: (files: File) => void;
-      onError?: (error: unknown) => void;
     }
   | {
       isDisabled?: boolean;
       allowMultiple: true;
       onUpload?: (imageDTOs: ImageDTO[]) => void;
-      onUploadStarted?: (files: File[]) => void;
-      onError?: (error: unknown) => void;
     };
 
 const log = logger('gallery');
@@ -53,13 +49,7 @@ const log = logger('gallery');
  * <Button {...getUploadButtonProps()} /> // will open the file dialog on click
  * <input {...getUploadInputProps()} /> // hidden, handles native upload functionality
  */
-export const useImageUploadButton = ({
-  onUpload,
-  isDisabled,
-  allowMultiple,
-  onUploadStarted,
-  onError,
-}: UseImageUploadButtonArgs) => {
+export const useImageUploadButton = ({ onUpload, isDisabled, allowMultiple }: UseImageUploadButtonArgs) => {
   const autoAddBoardId = useAppSelector(selectAutoAddBoardId);
   const isClientSideUploadEnabled = useAppSelector(selectIsClientSideUploadEnabled);
   const [uploadImage, request] = useUploadImageMutation();
@@ -81,7 +71,6 @@ export const useImageUploadButton = ({
           }
           const file = files[0];
           assert(file !== undefined); // should never happen
-          onUploadStarted?.(file);
           const imageDTO = await uploadImage({
             file,
             image_category: 'user',
@@ -93,8 +82,6 @@ export const useImageUploadButton = ({
             onUpload(imageDTO);
           }
         } else {
-          onUploadStarted?.(files);
-
           let imageDTOs: ImageDTO[] = [];
           if (isClientSideUploadEnabled && files.length > 1) {
             imageDTOs = await Promise.all(files.map((file, i) => clientSideUpload(file, i)));
@@ -115,7 +102,6 @@ export const useImageUploadButton = ({
           }
         }
       } catch (error) {
-        onError?.(error);
         toast({
           id: 'UPLOAD_FAILED',
           title: t('toast.imageUploadFailed'),
@@ -123,17 +109,7 @@ export const useImageUploadButton = ({
         });
       }
     },
-    [
-      allowMultiple,
-      onUploadStarted,
-      uploadImage,
-      autoAddBoardId,
-      onUpload,
-      isClientSideUploadEnabled,
-      clientSideUpload,
-      onError,
-      t,
-    ]
+    [allowMultiple, autoAddBoardId, onUpload, uploadImage, isClientSideUploadEnabled, clientSideUpload, t]
   );
 
   const onDropRejected = useCallback(

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

@@ -1,7 +1,7 @@
-import { useAppStore } from 'app/store/storeHooks';
-import { debounce } from 'es-toolkit/compat';
+import { useAppStore } from 'app/store/nanostores/store';
 import type { Dimensions } from 'features/controlLayers/store/types';
 import { selectUiSlice, textAreaSizesStateChanged } from 'features/ui/store/uiSlice';
+import { debounce } from 'lodash-es';
 import { type RefObject, useCallback, useEffect, useMemo } from 'react';
 
 type Options = {

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

@@ -0,0 +1,132 @@
+import type { ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
+import { EMPTY_ARRAY } from 'app/store/constants';
+import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
+import { useAppSelector } from 'app/store/storeHooks';
+import type { GroupBase } from 'chakra-react-select';
+import { selectLoRAsSlice } from 'features/controlLayers/store/lorasSlice';
+import { selectParamsSlice } from 'features/controlLayers/store/paramsSlice';
+import type { ModelIdentifierField } from 'features/nodes/types/common';
+import { uniq } from 'lodash-es';
+import { useMemo } from 'react';
+import { useTranslation } from 'react-i18next';
+import { useGetRelatedModelIdsBatchQuery } from 'services/api/endpoints/modelRelationships';
+import type { AnyModelConfig } from 'services/api/types';
+
+import { useGroupedModelCombobox } from './useGroupedModelCombobox';
+
+type UseRelatedGroupedModelComboboxArg<T extends AnyModelConfig> = {
+  modelConfigs: T[];
+  selectedModel?: ModelIdentifierField | null;
+  onChange: (value: T | null) => void;
+  getIsDisabled?: (model: T) => boolean;
+  isLoading?: boolean;
+  groupByType?: boolean;
+};
+
+// Custom hook to overlay the grouped model combobox with related models on top!
+// Cleaner than hooking into useGroupedModelCombobox with a flag to enable/disable the related models
+// Also allows for related models to be shown conditionally with some pretty simple logic if it ends up as a config flag.
+
+type UseRelatedGroupedModelComboboxReturn = {
+  value: ComboboxOption | undefined | null;
+  options: GroupBase<ComboboxOption>[];
+  onChange: ComboboxOnChange;
+  placeholder: string;
+  noOptionsMessage: () => string;
+};
+
+const selectSelectedModelKeys = createMemoizedSelector(selectParamsSlice, selectLoRAsSlice, (params, loras) => {
+  const keys: string[] = [];
+  const main = params.model;
+  const vae = params.vae;
+  const refiner = params.refinerModel;
+  const controlnet = params.controlLora;
+
+  if (main) {
+    keys.push(main.key);
+  }
+  if (vae) {
+    keys.push(vae.key);
+  }
+  if (refiner) {
+    keys.push(refiner.key);
+  }
+  if (controlnet) {
+    keys.push(controlnet.key);
+  }
+  for (const { model } of loras.loras) {
+    keys.push(model.key);
+  }
+
+  return uniq(keys);
+});
+
+export function useRelatedGroupedModelCombobox<T extends AnyModelConfig>({
+  modelConfigs,
+  selectedModel,
+  onChange,
+  isLoading = false,
+  getIsDisabled,
+  groupByType,
+}: UseRelatedGroupedModelComboboxArg<T>): UseRelatedGroupedModelComboboxReturn {
+  const { t } = useTranslation();
+
+  const selectedKeys = useAppSelector(selectSelectedModelKeys);
+  const { relatedKeys } = useGetRelatedModelIdsBatchQuery(selectedKeys, {
+    selectFromResult: ({ data }) => {
+      if (!data) {
+        return { relatedKeys: EMPTY_ARRAY };
+      }
+      return { relatedKeys: data };
+    },
+  });
+
+  // Base grouped options
+  const base = useGroupedModelCombobox({
+    modelConfigs,
+    selectedModel,
+    onChange,
+    getIsDisabled,
+    isLoading,
+    groupByType,
+  });
+
+  const options = useMemo(() => {
+    if (relatedKeys.length === 0) {
+      return base.options;
+    }
+
+    const relatedOptions: ComboboxOption[] = [];
+    const updatedGroups: GroupBase<ComboboxOption>[] = [];
+
+    for (const group of base.options) {
+      const remainingOptions: ComboboxOption[] = [];
+
+      for (const option of group.options) {
+        if (relatedKeys.includes(option.value)) {
+          relatedOptions.push({ ...option, label: `* ${option.label}` });
+        } else {
+          remainingOptions.push(option);
+        }
+      }
+
+      if (remainingOptions.length > 0) {
+        updatedGroups.push({
+          label: group.label,
+          options: remainingOptions,
+        });
+      }
+    }
+
+    if (relatedOptions.length > 0) {
+      return [{ label: t('modelManager.relatedModels'), options: relatedOptions }, ...updatedGroups];
+    } else {
+      return updatedGroups;
+    }
+  }, [base.options, relatedKeys, t]);
+
+  return {
+    ...base,
+    options,
+  };
+}

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

@@ -0,0 +1,28 @@
+import type { Selector } from '@reduxjs/toolkit';
+import type { RootState } from 'app/store/store';
+import { useAppStore } from 'app/store/storeHooks';
+import type { Atom, WritableAtom } from 'nanostores';
+import { atom } from 'nanostores';
+import { useEffect, useState } from 'react';
+
+/* eslint-disable-next-line @typescript-eslint/no-explicit-any */
+export const useSelectorAsAtom = <T extends Selector<RootState, any>>(selector: T): Atom<ReturnType<T>> => {
+  const store = useAppStore();
+  const $atom = useState<WritableAtom<ReturnType<T>>>(() => atom<ReturnType<T>>(selector(store.getState())))[0];
+
+  useEffect(() => {
+    const unsubscribe = store.subscribe(() => {
+      const prev = $atom.get();
+      const next = selector(store.getState());
+      if (prev !== next) {
+        $atom.set(next);
+      }
+    });
+
+    return () => {
+      unsubscribe();
+    };
+  }, [$atom, selector, store]);
+
+  return $atom;
+};

invokeai/frontend/web/src/common/util/createDeferredPromise.ts

@@ -1,20 +0,0 @@
-export type Deferred<T> = {
-  promise: Promise<T>;
-  resolve: (value: T) => void;
-  reject: (error: Error) => void;
-};
-
-/**
- * Create a promise and expose its resolve and reject callbacks.
- */
-export const createDeferredPromise = <T>(): Deferred<T> => {
-  let resolve!: (value: T) => void;
-  let reject!: (error: Error) => void;
-
-  const promise = new Promise<T>((res, rej) => {
-    resolve = res;
-    reject = rej;
-  });
-
-  return { promise, resolve, reject };
-};

invokeai/frontend/web/src/common/util/generateSeeds.ts

@@ -1,5 +1,5 @@
 import { NUMPY_RAND_MAX, NUMPY_RAND_MIN } from 'app/constants';
-import { random } from 'es-toolkit/compat';
+import { random } from 'lodash-es';
 
 type GenerateSeedsArg = {
   count: number;

invokeai/frontend/web/src/common/util/objectKeys.ts

@@ -0,0 +1,6 @@
+/**
+ * Get the keys of an object. This is a wrapper around `Object.keys` that types the result as an array of the keys of the object.
+ * @param obj The object to get the keys of.
+ * @returns The keys of the object.
+ */
+export const objectKeys = <T extends Record<string, unknown>>(obj: T) => Object.keys(obj) as Array<keyof T>;

invokeai/frontend/web/src/common/util/result.ts

@@ -89,7 +89,7 @@ export function withResult<T>(fn: () => T): Result<T> {
   try {
     return new Ok(fn());
   } catch (error) {
-    return new Err(error instanceof Error ? error : new WrappedError(error));
+    return new Err(error instanceof Error ? error : new Error(String(error)));
   }
 }
 
@@ -104,23 +104,6 @@ export async function withResultAsync<T>(fn: () => Promise<T>): Promise<Result<T
     const result = await fn();
     return new Ok(result);
   } catch (error) {
-    return new Err(error instanceof Error ? error : new WrappedError(error));
-  }
-}
-
-export class WrappedError extends Error {
-  error: unknown;
-
-  constructor(error: unknown) {
-    super('Wrapped Error');
-    this.name = this.constructor.name;
-    this.error = error;
-  }
-
-  static wrap(error: unknown): Error | WrappedError {
-    if (error instanceof Error) {
-      return error;
-    }
-    return new WrappedError(error);
+    return new Err(error instanceof Error ? error : new Error(String(error)));
   }
 }

invokeai/frontend/web/src/common/util/zodUtils.ts

@@ -1,4 +1,4 @@
-import type { z } from 'zod/v4';
+import type { z } from 'zod';
 
 /**
  * Helper to create a type guard from a zod schema. The type guard will infer the schema's TS type.

invokeai/frontend/web/src/features/controlLayers/components/AdvancedSession/AdvancedSession.tsx

@@ -0,0 +1,182 @@
+import type { SystemStyleObject } from '@invoke-ai/ui-library';
+import {
+  ContextMenu,
+  Divider,
+  Flex,
+  IconButton,
+  Menu,
+  MenuButton,
+  MenuList,
+  Tab,
+  TabList,
+  TabPanel,
+  TabPanels,
+  Tabs,
+} from '@invoke-ai/ui-library';
+import { useAppSelector } from 'app/store/storeHooks';
+import { FocusRegionWrapper } from 'common/components/FocusRegionWrapper';
+import { CanvasAlertsInvocationProgress } from 'features/controlLayers/components/CanvasAlerts/CanvasAlertsInvocationProgress';
+import { CanvasAlertsPreserveMask } from 'features/controlLayers/components/CanvasAlerts/CanvasAlertsPreserveMask';
+import { CanvasAlertsSelectedEntityStatus } from 'features/controlLayers/components/CanvasAlerts/CanvasAlertsSelectedEntityStatus';
+import { CanvasContextMenuGlobalMenuItems } from 'features/controlLayers/components/CanvasContextMenu/CanvasContextMenuGlobalMenuItems';
+import { CanvasContextMenuSelectedEntityMenuItems } from 'features/controlLayers/components/CanvasContextMenu/CanvasContextMenuSelectedEntityMenuItems';
+import { CanvasDropArea } from 'features/controlLayers/components/CanvasDropArea';
+import { Filter } from 'features/controlLayers/components/Filters/Filter';
+import { CanvasHUD } from 'features/controlLayers/components/HUD/CanvasHUD';
+import { InvokeCanvasComponent } from 'features/controlLayers/components/InvokeCanvasComponent';
+import { SelectObject } from 'features/controlLayers/components/SelectObject/SelectObject';
+import { CanvasSessionContextProvider } from 'features/controlLayers/components/SimpleSession/context';
+import { GenerateLaunchpadPanel } from 'features/controlLayers/components/SimpleSession/GenerateLaunchpadPanel';
+import { StagingAreaItemsList } from 'features/controlLayers/components/SimpleSession/StagingAreaItemsList';
+import { StagingAreaToolbar } from 'features/controlLayers/components/StagingArea/StagingAreaToolbar';
+import { CanvasToolbar } from 'features/controlLayers/components/Toolbar/CanvasToolbar';
+import { Transform } from 'features/controlLayers/components/Transform/Transform';
+import { CanvasManagerProviderGate } from 'features/controlLayers/contexts/CanvasManagerProviderGate';
+import { selectDynamicGrid, selectShowHUD } from 'features/controlLayers/store/canvasSettingsSlice';
+import { ImageViewer } from 'features/gallery/components/ImageViewer/ImageViewer';
+import { ViewerToolbar } from 'features/gallery/components/ImageViewer/ViewerToolbar';
+import { memo, useCallback } from 'react';
+import { PiDotsThreeOutlineVerticalFill } from 'react-icons/pi';
+
+const FOCUS_REGION_STYLES: SystemStyleObject = {
+  width: 'full',
+  height: 'full',
+};
+
+const MenuContent = memo(() => {
+  return (
+    <CanvasManagerProviderGate>
+      <MenuList>
+        <CanvasContextMenuSelectedEntityMenuItems />
+        <CanvasContextMenuGlobalMenuItems />
+      </MenuList>
+    </CanvasManagerProviderGate>
+  );
+});
+MenuContent.displayName = 'MenuContent';
+
+const canvasBgSx = {
+  position: 'relative',
+  w: 'full',
+  h: 'full',
+  borderRadius: 'base',
+  overflow: 'hidden',
+  bg: 'base.900',
+  '&[data-dynamic-grid="true"]': {
+    bg: 'base.850',
+  },
+};
+
+export const AdvancedSession = memo(({ id }: { id: string | null }) => {
+  const dynamicGrid = useAppSelector(selectDynamicGrid);
+  const showHUD = useAppSelector(selectShowHUD);
+
+  const renderMenu = useCallback(() => {
+    return <MenuContent />;
+  }, []);
+
+  return (
+    <Tabs w="full" h="full">
+      <TabList>
+        <Tab>Welcome</Tab>
+        <Tab>Workspace</Tab>
+        <Tab>Viewer</Tab>
+      </TabList>
+      <TabPanels w="full" h="full">
+        <TabPanel w="full" h="full" justifyContent="center">
+          <GenerateLaunchpadPanel />
+        </TabPanel>
+        <TabPanel w="full" h="full">
+          <FocusRegionWrapper region="canvas" sx={FOCUS_REGION_STYLES}>
+            <Flex
+              tabIndex={-1}
+              borderRadius="base"
+              position="relative"
+              flexDirection="column"
+              height="full"
+              width="full"
+              gap={2}
+              alignItems="center"
+              justifyContent="center"
+              overflow="hidden"
+            >
+              <CanvasManagerProviderGate>
+                <CanvasToolbar />
+              </CanvasManagerProviderGate>
+              <Divider />
+              <ContextMenu<HTMLDivElement> renderMenu={renderMenu} withLongPress={false}>
+                {(ref) => (
+                  <Flex ref={ref} sx={canvasBgSx} data-dynamic-grid={dynamicGrid}>
+                    <InvokeCanvasComponent />
+                    <CanvasManagerProviderGate>
+                      <Flex
+                        position="absolute"
+                        flexDir="column"
+                        top={1}
+                        insetInlineStart={1}
+                        pointerEvents="none"
+                        gap={2}
+                        alignItems="flex-start"
+                      >
+                        {showHUD && <CanvasHUD />}
+                        <CanvasAlertsSelectedEntityStatus />
+                        <CanvasAlertsPreserveMask />
+                        <CanvasAlertsInvocationProgress />
+                      </Flex>
+                      <Flex position="absolute" top={1} insetInlineEnd={1}>
+                        <Menu>
+                          <MenuButton as={IconButton} icon={<PiDotsThreeOutlineVerticalFill />} colorScheme="base" />
+                          <MenuContent />
+                        </Menu>
+                      </Flex>
+                    </CanvasManagerProviderGate>
+                  </Flex>
+                )}
+              </ContextMenu>
+              {id !== null && (
+                <CanvasManagerProviderGate>
+                  <CanvasSessionContextProvider type="advanced" id={id}>
+                    <Flex
+                      position="absolute"
+                      flexDir="column"
+                      bottom={4}
+                      gap={2}
+                      align="center"
+                      justify="center"
+                      left={4}
+                      right={4}
+                    >
+                      <Flex position="relative" maxW="full" w="full" h={108}>
+                        <StagingAreaItemsList />
+                      </Flex>
+                      <Flex gap={2}>
+                        <StagingAreaToolbar />
+                      </Flex>
+                    </Flex>
+                  </CanvasSessionContextProvider>
+                </CanvasManagerProviderGate>
+              )}
+              <Flex position="absolute" bottom={4}>
+                <CanvasManagerProviderGate>
+                  <Filter />
+                  <Transform />
+                  <SelectObject />
+                </CanvasManagerProviderGate>
+              </Flex>
+              <CanvasManagerProviderGate>
+                <CanvasDropArea />
+              </CanvasManagerProviderGate>
+            </Flex>
+          </FocusRegionWrapper>
+        </TabPanel>
+        <TabPanel w="full" h="full">
+          <Flex flexDir="column" w="full" h="full">
+            <ViewerToolbar />
+            <ImageViewer />
+          </Flex>
+        </TabPanel>
+      </TabPanels>
+    </Tabs>
+  );
+});
+AdvancedSession.displayName = 'AdvancedSession';

invokeai/frontend/web/src/features/controlLayers/components/CanvasAlerts/CanvasAlertsSaveAllImagesToGallery.tsx

@@ -1,23 +0,0 @@
-import { Alert, AlertIcon, AlertTitle } from '@invoke-ai/ui-library';
-import { useAppSelector } from 'app/store/storeHooks';
-import { selectSaveAllImagesToGallery } from 'features/controlLayers/store/canvasSettingsSlice';
-import { memo } from 'react';
-import { useTranslation } from 'react-i18next';
-
-export const CanvasAlertsSaveAllImagesToGallery = memo(() => {
-  const { t } = useTranslation();
-  const saveAllImagesToGallery = useAppSelector(selectSaveAllImagesToGallery);
-
-  if (!saveAllImagesToGallery) {
-    return null;
-  }
-
-  return (
-    <Alert status="info" borderRadius="base" fontSize="sm" shadow="md" w="fit-content">
-      <AlertIcon />
-      <AlertTitle>{t('controlLayers.settings.saveAllImagesToGallery.alert')}</AlertTitle>
-    </Alert>
-  );
-});
-
-CanvasAlertsSaveAllImagesToGallery.displayName = 'CanvasAlertsSaveAllImagesToGallery';

invokeai/frontend/web/src/features/controlLayers/components/CanvasBusySpinner.tsx

@@ -1,4 +1,3 @@
-import type { SpinnerProps } from '@invoke-ai/ui-library';
 import { Spinner } from '@invoke-ai/ui-library';
 import { useStore } from '@nanostores/react';
 import { useCanvasManager } from 'features/controlLayers/contexts/CanvasManagerProviderGate';
@@ -6,7 +5,7 @@ import { useAllEntityAdapters } from 'features/controlLayers/contexts/EntityAdap
 import { computed } from 'nanostores';
 import { memo, useMemo } from 'react';
 
-export const CanvasBusySpinner = memo((props: SpinnerProps) => {
+export const CanvasBusySpinner = memo(() => {
   const canvasManager = useCanvasManager();
   const allEntityAdapters = useAllEntityAdapters();
   const $isPendingRectCalculation = useMemo(
@@ -22,7 +21,7 @@ export const CanvasBusySpinner = memo((props: SpinnerProps) => {
   const isCompositing = useStore(canvasManager.compositor.$isBusy);
 
   if (isRasterizing || isCompositing || isPendingRectCalculation) {
-    return <Spinner opacity={0.3} {...props} />;
+    return <Spinner opacity={0.3} />;
   }
   return null;
 });

invokeai/frontend/web/src/features/controlLayers/components/CanvasDropArea.tsx

@@ -12,10 +12,6 @@ const addControlLayerFromImageDndTargetData = newCanvasEntityFromImageDndTarget.
 const addRegionalGuidanceReferenceImageFromImageDndTargetData = newCanvasEntityFromImageDndTarget.getData({
   type: 'regional_guidance_with_reference_image',
 });
-const addResizedControlLayerFromImageDndTargetData = newCanvasEntityFromImageDndTarget.getData({
-  type: 'control_layer',
-  withResize: true,
-});
 
 export const CanvasDropArea = memo(() => {
   const { t } = useTranslation();
@@ -49,6 +45,7 @@ export const CanvasDropArea = memo(() => {
             isDisabled={isBusy}
           />
         </GridItem>
+
         <GridItem position="relative">
           <DndDropTarget
             dndTarget={newCanvasEntityFromImageDndTarget}
@@ -57,14 +54,6 @@ export const CanvasDropArea = memo(() => {
             isDisabled={isBusy}
           />
         </GridItem>
-        <GridItem position="relative">
-          <DndDropTarget
-            dndTarget={newCanvasEntityFromImageDndTarget}
-            dndTargetData={addResizedControlLayerFromImageDndTargetData}
-            label={t('controlLayers.canvasContextMenu.newResizedControlLayer')}
-            isDisabled={isBusy}
-          />
-        </GridItem>
       </Grid>
     </>
   );