fix(ui): correctly fallback to error message when traceback is empty string

There's a race condition where a canceled session may emit a progress event or two after it's been canceled, and the progress image isn't cleared out.

To resolve this, the system slice tracks canceled session ids. When a progress event comes in, we check the cancellations and skip setting the progress if canceled.

docs/contributing/frontend/WORKFLOWS.md

@@ -117,13 +117,13 @@ Stateless fields do not store their value in the node, so their field instances
 
 "Custom" fields will always be treated as stateless fields.
 
-##### Collection and Scalar Fields
+##### Single and Collection Fields
 
-Field types have a name and two flags which may identify it as a **collection** or **collection or scalar** field.
+Field types have a name and cardinality property which may identify it as a **SINGLE**, **COLLECTION** or **SINGLE_OR_COLLECTION** field.
 
-If a field is annotated in python as a list, its field type is parsed and flagged as a **collection** type (e.g. `list[int]`).
-
-If it is annotated as a union of a type and list, the type will be flagged as a **collection or scalar** type (e.g. `Union[int, list[int]]`). Fields may not be unions of different types (e.g. `Union[int, list[str]]` and `Union[int, str]` are not allowed).
+- If a field is annotated in python as a singular value or class, its field type is parsed as a **SINGLE** type (e.g. `int`, `ImageField`, `str`).
+- If a field is annotated in python as a list, its field type is parsed as a **COLLECTION** type (e.g. `list[int]`).
+- If it is annotated as a union of a type and list, the type will be parsed as a **SINGLE_OR_COLLECTION** type (e.g. `Union[int, list[int]]`). Fields may not be unions of different types (e.g. `Union[int, list[str]]` and `Union[int, str]` are not allowed).
 
 ## Implementation
 
@@ -173,8 +173,7 @@ Field types are represented as structured objects:
 ```ts
 type FieldType = {
   name: string;
-  isCollection: boolean;
-  isCollectionOrScalar: boolean;
+  cardinality: 'SINGLE' | 'COLLECTION' | 'SINGLE_OR_COLLECTION';
 };
 ```
 
@@ -186,7 +185,7 @@ There are 4 general cases for field type parsing.
 
 When a field is annotated as a primitive values (e.g. `int`, `str`, `float`), the field type parsing is fairly straightforward. The field is represented by a simple OpenAPI **schema object**, which has a `type` property.
 
-We create a field type name from this `type` string (e.g. `string` -> `StringField`).
+We create a field type name from this `type` string (e.g. `string` -> `StringField`). The cardinality is `"SINGLE"`.
 
 ##### Complex Types
 
@@ -200,13 +199,13 @@ We need to **dereference** the schema to pull these out. Dereferencing may requi
 
 When a field is annotated as a list of a single type, the schema object has an `items` property. They may be a schema object or reference object and must be parsed to determine the item type.
 
-We use the item type for field type name, adding `isCollection: true` to the field type.
+We use the item type for field type name. The cardinality is `"COLLECTION"`.
 
-##### Collection or Scalar Types
+##### Single or Collection Types
 
 When a field is annotated as a union of a type and list of that type, the schema object has an `anyOf` property, which holds a list of valid types for the union.
 
-After verifying that the union has two members (a type and list of the same type), we use the type for field type name, adding `isCollectionOrScalar: true` to the field type.
+After verifying that the union has two members (a type and list of the same type), we use the type for field type name, with cardinality `"SINGLE_OR_COLLECTION"`.
 
 ##### Optional Fields
 

docs/features/CONTROLNET.md

@@ -165,7 +165,7 @@ Additionally, each  section can be expanded with the "Show Advanced" button in o
 There are several ways to install IP-Adapter models with an existing InvokeAI installation:
 
 1. Through the command line interface launched from the invoke.sh / invoke.bat scripts, option [4] to download models.
-2. Through the Model Manager UI with models from the *Tools* section of [www.models.invoke.ai](https://www.models.invoke.ai). To do this, copy the repo ID from the desired model page, and paste it in the Add Model field of the model manager. **Note** Both the IP-Adapter and the Image Encoder must be installed for IP-Adapter to work. For example, the [SD 1.5 IP-Adapter](https://models.invoke.ai/InvokeAI/ip_adapter_plus_sd15) and [SD1.5 Image Encoder](https://models.invoke.ai/InvokeAI/ip_adapter_sd_image_encoder) must be installed to use IP-Adapter with SD1.5 based models.  
+2. Through the Model Manager UI with models from the *Tools* section of [models.invoke.ai](https://models.invoke.ai). To do this, copy the repo ID from the desired model page, and paste it in the Add Model field of the model manager. **Note** Both the IP-Adapter and the Image Encoder must be installed for IP-Adapter to work. For example, the [SD 1.5 IP-Adapter](https://models.invoke.ai/InvokeAI/ip_adapter_plus_sd15) and [SD1.5 Image Encoder](https://models.invoke.ai/InvokeAI/ip_adapter_sd_image_encoder) must be installed to use IP-Adapter with SD1.5 based models.  
 3. **Advanced -- Not recommended ** Manually downloading the IP-Adapter and Image Encoder files - Image Encoder folders shouid be placed in the `models\any\clip_vision` folders. IP Adapter Model folders should be placed in the relevant `ip-adapter` folder of relevant base model folder of Invoke root directory. For example, for the SDXL IP-Adapter, files should be added to the `model/sdxl/ip_adapter/` folder. 
 
 #### Using IP-Adapter

docs/installation/010_INSTALL_AUTOMATED.md

@@ -98,7 +98,7 @@ Updating is exactly the same as installing - download the latest installer, choo
 
 If you have installation issues, please review the [FAQ]. You can also [create an issue] or ask for help on [discord].
 
-[installation requirements]: INSTALLATION.md#installation-requirements
+[installation requirements]: INSTALL_REQUIREMENTS.md
 [FAQ]: ../help/FAQ.md
 [install some models]: 050_INSTALLING_MODELS.md
 [configuration docs]: ../features/CONFIGURATION.md

docs/installation/020_INSTALL_MANUAL.md

@@ -10,7 +10,7 @@ InvokeAI is distributed as a python package on PyPI, installable with `pip`. The
 
 ### Requirements
 
-Before you start, go through the [installation requirements].
+Before you start, go through the [installation requirements](./INSTALL_REQUIREMENTS.md).
 
 ### Installation Walkthrough
 
@@ -79,7 +79,7 @@ Before you start, go through the [installation requirements].
 
 1. Install the InvokeAI Package. The base command is `pip install InvokeAI --use-pep517`, but you may need to change this depending on your system and the desired features.
 
-    - You may need to provide an [extra index URL]. Select your platform configuration using [this tool on the PyTorch website]. Copy the `--extra-index-url` string from this and append it to your install command.
+    - You may need to provide an [extra index URL](https://pip.pypa.io/en/stable/cli/pip_install/#cmdoption-extra-index-url). Select your platform configuration using [this tool on the PyTorch website](https://pytorch.org/get-started/locally/). Copy the `--extra-index-url` string from this and append it to your install command.
 
         !!! example "Install with an extra index URL"
 
@@ -116,4 +116,4 @@ Before you start, go through the [installation requirements].
 
     !!! warning
 
-        If the virtual environment is _not_ inside the root directory, then you _must_ specify the path to the root directory with `--root_dir \path\to\invokeai` or the `INVOKEAI_ROOT` environment variable.
+        If the virtual environment is _not_ inside the root directory, then you _must_ specify the path to the root directory with `--root \path\to\invokeai` or the `INVOKEAI_ROOT` environment variable.

installer/templates/invoke.bat.in

@@ -10,8 +10,7 @@ set INVOKEAI_ROOT=.
 echo Desired action:
 echo 1. Generate images with the browser-based interface
 echo 2. Open the developer console
-echo 3. Run the InvokeAI image database maintenance script
-echo 4. Command-line help
+echo 3. Command-line help
 echo Q - Quit
 echo.
 echo To update, download and run the installer from https://github.com/invoke-ai/InvokeAI/releases/latest.
@@ -34,9 +33,6 @@ IF /I "%choice%" == "1" (
     echo *** Type `exit` to quit this shell and deactivate the Python virtual environment ***
     call cmd /k
 ) ELSE IF /I "%choice%" == "3" (
-   echo Running the db maintenance script...
-   python .venv\Scripts\invokeai-db-maintenance.exe
-) ELSE IF /I "%choice%" == "4" (
     echo Displaying command line help...
     python .venv\Scripts\invokeai-web.exe --help %*
     pause

installer/templates/invoke.sh.in

@@ -47,11 +47,6 @@ do_choice() {
         bash --init-file "$file_name"
         ;;
     3)
-        clear
-        printf "Running the db maintenance script\n"
-        invokeai-db-maintenance --root ${INVOKEAI_ROOT}
-        ;;
-    4)
         clear
         printf "Command-line help\n"
         invokeai-web --help
@@ -71,8 +66,7 @@ do_line_input() {
     printf "What would you like to do?\n"
     printf "1: Generate images using the browser-based interface\n"
     printf "2: Open the developer console\n"
-    printf "3: Run the InvokeAI image database maintenance script\n"
-    printf "4: Command-line help\n"
+    printf "3: Command-line help\n"
     printf "Q: Quit\n\n"
     printf "To update, download and run the installer from https://github.com/invoke-ai/InvokeAI/releases/latest.\n\n"
     read -p "Please enter 1-4, Q: [1] " yn

invokeai/app/api/dependencies.py

@@ -29,7 +29,7 @@ from ..services.model_images.model_images_default import ModelImageFileStorageDi
 from ..services.model_manager.model_manager_default import ModelManagerService
 from ..services.model_records import ModelRecordServiceSQL
 from ..services.names.names_default import SimpleNameService
-from ..services.session_processor.session_processor_default import DefaultSessionProcessor
+from ..services.session_processor.session_processor_default import DefaultSessionProcessor, DefaultSessionRunner
 from ..services.session_queue.session_queue_sqlite import SqliteSessionQueue
 from ..services.urls.urls_default import LocalUrlService
 from ..services.workflow_records.workflow_records_sqlite import SqliteWorkflowRecordsStorage
@@ -103,7 +103,8 @@ class ApiDependencies:
         )
         names = SimpleNameService()
         performance_statistics = InvocationStatsService()
-        session_processor = DefaultSessionProcessor()
+
+        session_processor = DefaultSessionProcessor(session_runner=DefaultSessionRunner())
         session_queue = SqliteSessionQueue(db=db)
         urls = LocalUrlService()
         workflow_records = SqliteWorkflowRecordsStorage(db=db)

invokeai/app/api/routers/images.py

@@ -6,13 +6,12 @@ from fastapi import BackgroundTasks, Body, HTTPException, Path, Query, Request,
 from fastapi.responses import FileResponse
 from fastapi.routing import APIRouter
 from PIL import Image
-from pydantic import BaseModel, Field, ValidationError
+from pydantic import BaseModel, Field, JsonValue
 
-from invokeai.app.invocations.fields import MetadataField, MetadataFieldValidator
+from invokeai.app.invocations.fields import MetadataField
 from invokeai.app.services.image_records.image_records_common import ImageCategory, ImageRecordChanges, ResourceOrigin
 from invokeai.app.services.images.images_common import ImageDTO, ImageUrlsDTO
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
-from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID, WorkflowWithoutIDValidator
 
 from ..dependencies import ApiDependencies
 
@@ -42,13 +41,17 @@ async def upload_image(
     board_id: Optional[str] = Query(default=None, description="The board to add this image to, if any"),
     session_id: Optional[str] = Query(default=None, description="The session ID associated with this upload, if any"),
     crop_visible: Optional[bool] = Query(default=False, description="Whether to crop the image"),
+    metadata: Optional[JsonValue] = Body(
+        default=None, description="The metadata to associate with the image", embed=True
+    ),
 ) -> ImageDTO:
     """Uploads an image"""
     if not file.content_type or not file.content_type.startswith("image"):
         raise HTTPException(status_code=415, detail="Not an image")
 
-    metadata = None
-    workflow = None
+    _metadata = None
+    _workflow = None
+    _graph = None
 
     contents = await file.read()
     try:
@@ -62,22 +65,28 @@ async def upload_image(
 
     # TODO: retain non-invokeai metadata on upload?
     # attempt to parse metadata from image
-    metadata_raw = pil_image.info.get("invokeai_metadata", None)
-    if metadata_raw:
-        try:
-            metadata = MetadataFieldValidator.validate_json(metadata_raw)
-        except ValidationError:
-            ApiDependencies.invoker.services.logger.warn("Failed to parse metadata for uploaded image")
-            pass
+    metadata_raw = metadata if isinstance(metadata, str) else pil_image.info.get("invokeai_metadata", None)
+    if isinstance(metadata_raw, str):
+        _metadata = metadata_raw
+    else:
+        ApiDependencies.invoker.services.logger.debug("Failed to parse metadata for uploaded image")
+        pass
 
     # attempt to parse workflow from image
     workflow_raw = pil_image.info.get("invokeai_workflow", None)
-    if workflow_raw is not None:
-        try:
-            workflow = WorkflowWithoutIDValidator.validate_json(workflow_raw)
-        except ValidationError:
-            ApiDependencies.invoker.services.logger.warn("Failed to parse metadata for uploaded image")
-            pass
+    if isinstance(workflow_raw, str):
+        _workflow = workflow_raw
+    else:
+        ApiDependencies.invoker.services.logger.debug("Failed to parse workflow for uploaded image")
+        pass
+
+    # attempt to extract graph from image
+    graph_raw = pil_image.info.get("invokeai_graph", None)
+    if isinstance(graph_raw, str):
+        _graph = graph_raw
+    else:
+        ApiDependencies.invoker.services.logger.debug("Failed to parse graph for uploaded image")
+        pass
 
     try:
         image_dto = ApiDependencies.invoker.services.images.create(
@@ -86,8 +95,9 @@ async def upload_image(
             image_category=image_category,
             session_id=session_id,
             board_id=board_id,
-            metadata=metadata,
-            workflow=workflow,
+            metadata=_metadata,
+            workflow=_workflow,
+            graph=_graph,
             is_intermediate=is_intermediate,
         )
 
@@ -185,14 +195,21 @@ async def get_image_metadata(
         raise HTTPException(status_code=404)
 
 
+class WorkflowAndGraphResponse(BaseModel):
+    workflow: Optional[str] = Field(description="The workflow used to generate the image, as stringified JSON")
+    graph: Optional[str] = Field(description="The graph used to generate the image, as stringified JSON")
+
+
 @images_router.get(
-    "/i/{image_name}/workflow", operation_id="get_image_workflow", response_model=Optional[WorkflowWithoutID]
+    "/i/{image_name}/workflow", operation_id="get_image_workflow", response_model=WorkflowAndGraphResponse
 )
 async def get_image_workflow(
     image_name: str = Path(description="The name of image whose workflow to get"),
-) -> Optional[WorkflowWithoutID]:
+) -> WorkflowAndGraphResponse:
     try:
-        return ApiDependencies.invoker.services.images.get_workflow(image_name)
+        workflow = ApiDependencies.invoker.services.images.get_workflow(image_name)
+        graph = ApiDependencies.invoker.services.images.get_graph(image_name)
+        return WorkflowAndGraphResponse(workflow=workflow, graph=graph)
     except Exception:
         raise HTTPException(status_code=404)
 

invokeai/app/api/routers/session_queue.py

@@ -203,6 +203,7 @@ async def get_batch_status(
     responses={
         200: {"model": SessionQueueItem},
     },
+    response_model_exclude_none=True,
 )
 async def get_queue_item(
     queue_id: str = Path(description="The queue id to perform this operation on"),

invokeai/app/api_app.py

@@ -164,6 +164,12 @@ def custom_openapi() -> dict[str, Any]:
     for schema_key, schema_json in additional_schemas[1]["$defs"].items():
         openapi_schema["components"]["schemas"][schema_key] = schema_json
 
+    openapi_schema["components"]["schemas"]["InvocationOutputMap"] = {
+        "type": "object",
+        "properties": {},
+        "required": [],
+    }
+
     # Add a reference to the output type to additionalProperties of the invoker schema
     for invoker in all_invocations:
         invoker_name = invoker.__name__  # type: ignore [attr-defined] # this is a valid attribute
@@ -172,6 +178,8 @@ def custom_openapi() -> dict[str, Any]:
         invoker_schema = openapi_schema["components"]["schemas"][f"{invoker_name}"]
         outputs_ref = {"$ref": f"#/components/schemas/{output_type_title}"}
         invoker_schema["output"] = outputs_ref
+        openapi_schema["components"]["schemas"]["InvocationOutputMap"]["properties"][invoker.get_type()] = outputs_ref
+        openapi_schema["components"]["schemas"]["InvocationOutputMap"]["required"].append(invoker.get_type())
         invoker_schema["class"] = "invocation"
 
     # This code no longer seems to be necessary?

invokeai/app/invocations/controlnet_image_processors.py

@@ -24,7 +24,6 @@ from pydantic import BaseModel, Field, field_validator, model_validator
 from invokeai.app.invocations.fields import (
     FieldDescriptions,
     ImageField,
-    Input,
     InputField,
     OutputField,
     UIType,
@@ -80,13 +79,13 @@ class ControlOutput(BaseInvocationOutput):
     control: ControlField = OutputField(description=FieldDescriptions.control)
 
 
-@invocation("controlnet", title="ControlNet", tags=["controlnet"], category="controlnet", version="1.1.1")
+@invocation("controlnet", title="ControlNet", tags=["controlnet"], category="controlnet", version="1.1.2")
 class ControlNetInvocation(BaseInvocation):
     """Collects ControlNet info to pass to other nodes"""
 
     image: ImageField = InputField(description="The control image")
     control_model: ModelIdentifierField = InputField(
-        description=FieldDescriptions.controlnet_model, input=Input.Direct, ui_type=UIType.ControlNetModel
+        description=FieldDescriptions.controlnet_model, ui_type=UIType.ControlNetModel
     )
     control_weight: Union[float, List[float]] = InputField(
         default=1.0, ge=-1, le=2, description="The weight given to the ControlNet"

invokeai/app/invocations/ip_adapter.py

@@ -5,7 +5,7 @@ from pydantic import BaseModel, Field, field_validator, model_validator
 from typing_extensions import Self
 
 from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, invocation, invocation_output
-from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField, TensorField, UIType
+from invokeai.app.invocations.fields import FieldDescriptions, InputField, OutputField, TensorField, UIType
 from invokeai.app.invocations.model import ModelIdentifierField
 from invokeai.app.invocations.primitives import ImageField
 from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
@@ -58,7 +58,7 @@ class IPAdapterOutput(BaseInvocationOutput):
 CLIP_VISION_MODEL_MAP = {"ViT-H": "ip_adapter_sd_image_encoder", "ViT-G": "ip_adapter_sdxl_image_encoder"}
 
 
-@invocation("ip_adapter", title="IP-Adapter", tags=["ip_adapter", "control"], category="ip_adapter", version="1.4.0")
+@invocation("ip_adapter", title="IP-Adapter", tags=["ip_adapter", "control"], category="ip_adapter", version="1.4.1")
 class IPAdapterInvocation(BaseInvocation):
     """Collects IP-Adapter info to pass to other nodes."""
 
@@ -67,7 +67,6 @@ class IPAdapterInvocation(BaseInvocation):
     ip_adapter_model: ModelIdentifierField = InputField(
         description="The IP-Adapter model.",
         title="IP-Adapter Model",
-        input=Input.Direct,
         ui_order=-1,
         ui_type=UIType.IPAdapterModel,
     )

invokeai/app/invocations/model.py

@@ -11,6 +11,7 @@ from invokeai.backend.model_manager.config import AnyModelConfig, BaseModelType,
 from .baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
+    Classification,
     invocation,
     invocation_output,
 )
@@ -93,19 +94,46 @@ class ModelLoaderOutput(UNetOutput, CLIPOutput, VAEOutput):
     pass
 
 
+@invocation_output("model_identifier_output")
+class ModelIdentifierOutput(BaseInvocationOutput):
+    """Model identifier output"""
+
+    model: ModelIdentifierField = OutputField(description="Model identifier", title="Model")
+
+
+@invocation(
+    "model_identifier",
+    title="Model identifier",
+    tags=["model"],
+    category="model",
+    version="1.0.0",
+    classification=Classification.Prototype,
+)
+class ModelIdentifierInvocation(BaseInvocation):
+    """Selects any model, outputting it its identifier. Be careful with this one! The identifier will be accepted as
+    input for any model, even if the model types don't match. If you connect this to a mismatched input, you'll get an
+    error."""
+
+    model: ModelIdentifierField = InputField(description="The model to select", title="Model")
+
+    def invoke(self, context: InvocationContext) -> ModelIdentifierOutput:
+        if not context.models.exists(self.model.key):
+            raise Exception(f"Unknown model {self.model.key}")
+
+        return ModelIdentifierOutput(model=self.model)
+
+
 @invocation(
     "main_model_loader",
     title="Main Model",
     tags=["model"],
     category="model",
-    version="1.0.2",
+    version="1.0.3",
 )
 class MainModelLoaderInvocation(BaseInvocation):
     """Loads a main model, outputting its submodels."""
 
-    model: ModelIdentifierField = InputField(
-        description=FieldDescriptions.main_model, input=Input.Direct, ui_type=UIType.MainModel
-    )
+    model: ModelIdentifierField = InputField(description=FieldDescriptions.main_model, ui_type=UIType.MainModel)
     # TODO: precision?
 
     def invoke(self, context: InvocationContext) -> ModelLoaderOutput:
@@ -134,12 +162,12 @@ class LoRALoaderOutput(BaseInvocationOutput):
     clip: Optional[CLIPField] = OutputField(default=None, description=FieldDescriptions.clip, title="CLIP")
 
 
-@invocation("lora_loader", title="LoRA", tags=["model"], category="model", version="1.0.2")
+@invocation("lora_loader", title="LoRA", tags=["model"], category="model", version="1.0.3")
 class LoRALoaderInvocation(BaseInvocation):
     """Apply selected lora to unet and text_encoder."""
 
     lora: ModelIdentifierField = InputField(
-        description=FieldDescriptions.lora_model, input=Input.Direct, title="LoRA", ui_type=UIType.LoRAModel
+        description=FieldDescriptions.lora_model, title="LoRA", ui_type=UIType.LoRAModel
     )
     weight: float = InputField(default=0.75, description=FieldDescriptions.lora_weight)
     unet: Optional[UNetField] = InputField(
@@ -190,6 +218,75 @@ class LoRALoaderInvocation(BaseInvocation):
         return output
 
 
+@invocation_output("lora_selector_output")
+class LoRASelectorOutput(BaseInvocationOutput):
+    """Model loader output"""
+
+    lora: LoRAField = OutputField(description="LoRA model and weight", title="LoRA")
+
+
+@invocation("lora_selector", title="LoRA Selector", tags=["model"], category="model", version="1.0.1")
+class LoRASelectorInvocation(BaseInvocation):
+    """Selects a LoRA model and weight."""
+
+    lora: ModelIdentifierField = InputField(
+        description=FieldDescriptions.lora_model, title="LoRA", ui_type=UIType.LoRAModel
+    )
+    weight: float = InputField(default=0.75, description=FieldDescriptions.lora_weight)
+
+    def invoke(self, context: InvocationContext) -> LoRASelectorOutput:
+        return LoRASelectorOutput(lora=LoRAField(lora=self.lora, weight=self.weight))
+
+
+@invocation("lora_collection_loader", title="LoRA Collection Loader", tags=["model"], category="model", version="1.0.0")
+class LoRACollectionLoader(BaseInvocation):
+    """Applies a collection of LoRAs to the provided UNet and CLIP models."""
+
+    loras: LoRAField | list[LoRAField] = InputField(
+        description="LoRA models and weights. May be a single LoRA or collection.", title="LoRAs"
+    )
+    unet: Optional[UNetField] = InputField(
+        default=None,
+        description=FieldDescriptions.unet,
+        input=Input.Connection,
+        title="UNet",
+    )
+    clip: Optional[CLIPField] = InputField(
+        default=None,
+        description=FieldDescriptions.clip,
+        input=Input.Connection,
+        title="CLIP",
+    )
+
+    def invoke(self, context: InvocationContext) -> LoRALoaderOutput:
+        output = LoRALoaderOutput()
+        loras = self.loras if isinstance(self.loras, list) else [self.loras]
+        added_loras: list[str] = []
+
+        for lora in loras:
+            if lora.lora.key in added_loras:
+                continue
+
+            if not context.models.exists(lora.lora.key):
+                raise Exception(f"Unknown lora: {lora.lora.key}!")
+
+            assert lora.lora.base in (BaseModelType.StableDiffusion1, BaseModelType.StableDiffusion2)
+
+            added_loras.append(lora.lora.key)
+
+            if self.unet is not None:
+                if output.unet is None:
+                    output.unet = self.unet.model_copy(deep=True)
+                output.unet.loras.append(lora)
+
+            if self.clip is not None:
+                if output.clip is None:
+                    output.clip = self.clip.model_copy(deep=True)
+                output.clip.loras.append(lora)
+
+        return output
+
+
 @invocation_output("sdxl_lora_loader_output")
 class SDXLLoRALoaderOutput(BaseInvocationOutput):
     """SDXL LoRA Loader Output"""
@@ -204,13 +301,13 @@ class SDXLLoRALoaderOutput(BaseInvocationOutput):
     title="SDXL LoRA",
     tags=["lora", "model"],
     category="model",
-    version="1.0.2",
+    version="1.0.3",
 )
 class SDXLLoRALoaderInvocation(BaseInvocation):
     """Apply selected lora to unet and text_encoder."""
 
     lora: ModelIdentifierField = InputField(
-        description=FieldDescriptions.lora_model, input=Input.Direct, title="LoRA", ui_type=UIType.LoRAModel
+        description=FieldDescriptions.lora_model, title="LoRA", ui_type=UIType.LoRAModel
     )
     weight: float = InputField(default=0.75, description=FieldDescriptions.lora_weight)
     unet: Optional[UNetField] = InputField(
@@ -279,12 +376,78 @@ class SDXLLoRALoaderInvocation(BaseInvocation):
         return output
 
 
-@invocation("vae_loader", title="VAE", tags=["vae", "model"], category="model", version="1.0.2")
+@invocation(
+    "sdxl_lora_collection_loader",
+    title="SDXL LoRA Collection Loader",
+    tags=["model"],
+    category="model",
+    version="1.0.0",
+)
+class SDXLLoRACollectionLoader(BaseInvocation):
+    """Applies a collection of SDXL LoRAs to the provided UNet and CLIP models."""
+
+    loras: LoRAField | list[LoRAField] = InputField(
+        description="LoRA models and weights. May be a single LoRA or collection.", title="LoRAs"
+    )
+    unet: Optional[UNetField] = InputField(
+        default=None,
+        description=FieldDescriptions.unet,
+        input=Input.Connection,
+        title="UNet",
+    )
+    clip: Optional[CLIPField] = InputField(
+        default=None,
+        description=FieldDescriptions.clip,
+        input=Input.Connection,
+        title="CLIP",
+    )
+    clip2: Optional[CLIPField] = InputField(
+        default=None,
+        description=FieldDescriptions.clip,
+        input=Input.Connection,
+        title="CLIP 2",
+    )
+
+    def invoke(self, context: InvocationContext) -> SDXLLoRALoaderOutput:
+        output = SDXLLoRALoaderOutput()
+        loras = self.loras if isinstance(self.loras, list) else [self.loras]
+        added_loras: list[str] = []
+
+        for lora in loras:
+            if lora.lora.key in added_loras:
+                continue
+
+            if not context.models.exists(lora.lora.key):
+                raise Exception(f"Unknown lora: {lora.lora.key}!")
+
+            assert lora.lora.base is BaseModelType.StableDiffusionXL
+
+            added_loras.append(lora.lora.key)
+
+            if self.unet is not None:
+                if output.unet is None:
+                    output.unet = self.unet.model_copy(deep=True)
+                output.unet.loras.append(lora)
+
+            if self.clip is not None:
+                if output.clip is None:
+                    output.clip = self.clip.model_copy(deep=True)
+                output.clip.loras.append(lora)
+
+            if self.clip2 is not None:
+                if output.clip2 is None:
+                    output.clip2 = self.clip2.model_copy(deep=True)
+                output.clip2.loras.append(lora)
+
+        return output
+
+
+@invocation("vae_loader", title="VAE", tags=["vae", "model"], category="model", version="1.0.3")
 class VAELoaderInvocation(BaseInvocation):
     """Loads a VAE model, outputting a VaeLoaderOutput"""
 
     vae_model: ModelIdentifierField = InputField(
-        description=FieldDescriptions.vae_model, input=Input.Direct, title="VAE", ui_type=UIType.VAEModel
+        description=FieldDescriptions.vae_model, title="VAE", ui_type=UIType.VAEModel
     )
 
     def invoke(self, context: InvocationContext) -> VAEOutput:

invokeai/app/invocations/sdxl.py

@@ -1,4 +1,4 @@
-from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField, UIType
+from invokeai.app.invocations.fields import FieldDescriptions, InputField, OutputField, UIType
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.backend.model_manager import SubModelType
 
@@ -30,12 +30,12 @@ class SDXLRefinerModelLoaderOutput(BaseInvocationOutput):
     vae: VAEField = OutputField(description=FieldDescriptions.vae, title="VAE")
 
 
-@invocation("sdxl_model_loader", title="SDXL Main Model", tags=["model", "sdxl"], category="model", version="1.0.2")
+@invocation("sdxl_model_loader", title="SDXL Main Model", tags=["model", "sdxl"], category="model", version="1.0.3")
 class SDXLModelLoaderInvocation(BaseInvocation):
     """Loads an sdxl base model, outputting its submodels."""
 
     model: ModelIdentifierField = InputField(
-        description=FieldDescriptions.sdxl_main_model, input=Input.Direct, ui_type=UIType.SDXLMainModel
+        description=FieldDescriptions.sdxl_main_model, ui_type=UIType.SDXLMainModel
     )
     # TODO: precision?
 
@@ -67,13 +67,13 @@ class SDXLModelLoaderInvocation(BaseInvocation):
     title="SDXL Refiner Model",
     tags=["model", "sdxl", "refiner"],
     category="model",
-    version="1.0.2",
+    version="1.0.3",
 )
 class SDXLRefinerModelLoaderInvocation(BaseInvocation):
     """Loads an sdxl refiner model, outputting its submodels."""
 
     model: ModelIdentifierField = InputField(
-        description=FieldDescriptions.sdxl_refiner_model, input=Input.Direct, ui_type=UIType.SDXLRefinerModel
+        description=FieldDescriptions.sdxl_refiner_model, ui_type=UIType.SDXLRefinerModel
     )
     # TODO: precision?
 

invokeai/app/invocations/t2i_adapter.py

@@ -8,7 +8,7 @@ from invokeai.app.invocations.baseinvocation import (
     invocation,
     invocation_output,
 )
-from invokeai.app.invocations.fields import FieldDescriptions, ImageField, Input, InputField, OutputField, UIType
+from invokeai.app.invocations.fields import FieldDescriptions, ImageField, InputField, OutputField, UIType
 from invokeai.app.invocations.model import ModelIdentifierField
 from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
 from invokeai.app.services.shared.invocation_context import InvocationContext
@@ -45,7 +45,7 @@ class T2IAdapterOutput(BaseInvocationOutput):
 
 
 @invocation(
-    "t2i_adapter", title="T2I-Adapter", tags=["t2i_adapter", "control"], category="t2i_adapter", version="1.0.2"
+    "t2i_adapter", title="T2I-Adapter", tags=["t2i_adapter", "control"], category="t2i_adapter", version="1.0.3"
 )
 class T2IAdapterInvocation(BaseInvocation):
     """Collects T2I-Adapter info to pass to other nodes."""
@@ -55,7 +55,6 @@ class T2IAdapterInvocation(BaseInvocation):
     t2i_adapter_model: ModelIdentifierField = InputField(
         description="The T2I-Adapter model.",
         title="T2I-Adapter Model",
-        input=Input.Direct,
         ui_order=-1,
         ui_type=UIType.T2IAdapterModel,
     )

invokeai/app/services/events/events_base.py

@@ -121,7 +121,10 @@ class EventServiceBase:
         node: dict,
         source_node_id: str,
         error_type: str,
-        error: str,
+        error_message: str,
+        error_traceback: str,
+        user_id: str | None,
+        project_id: str | None,
     ) -> None:
         """Emitted when an invocation has completed"""
         self.__emit_queue_event(
@@ -134,7 +137,10 @@ class EventServiceBase:
                 "node": node,
                 "source_node_id": source_node_id,
                 "error_type": error_type,
-                "error": error,
+                "error_message": error_message,
+                "error_traceback": error_traceback,
+                "user_id": user_id,
+                "project_id": project_id,
             },
         )
 
@@ -253,7 +259,9 @@ class EventServiceBase:
                     "status": session_queue_item.status,
                     "batch_id": session_queue_item.batch_id,
                     "session_id": session_queue_item.session_id,
-                    "error": session_queue_item.error,
+                    "error_type": session_queue_item.error_type,
+                    "error_message": session_queue_item.error_message,
+                    "error_traceback": session_queue_item.error_traceback,
                     "created_at": str(session_queue_item.created_at) if session_queue_item.created_at else None,
                     "updated_at": str(session_queue_item.updated_at) if session_queue_item.updated_at else None,
                     "started_at": str(session_queue_item.started_at) if session_queue_item.started_at else None,

invokeai/app/services/image_files/image_files_base.py

@@ -4,9 +4,6 @@ from typing import Optional
 
 from PIL.Image import Image as PILImageType
 
-from invokeai.app.invocations.fields import MetadataField
-from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID
-
 
 class ImageFileStorageBase(ABC):
     """Low-level service responsible for storing and retrieving image files."""
@@ -33,8 +30,9 @@ class ImageFileStorageBase(ABC):
         self,
         image: PILImageType,
         image_name: str,
-        metadata: Optional[MetadataField] = None,
-        workflow: Optional[WorkflowWithoutID] = None,
+        metadata: Optional[str] = None,
+        workflow: Optional[str] = None,
+        graph: Optional[str] = None,
         thumbnail_size: int = 256,
     ) -> None:
         """Saves an image and a 256x256 WEBP thumbnail. Returns a tuple of the image name, thumbnail name, and created timestamp."""
@@ -46,6 +44,11 @@ class ImageFileStorageBase(ABC):
         pass
 
     @abstractmethod
-    def get_workflow(self, image_name: str) -> Optional[WorkflowWithoutID]:
+    def get_workflow(self, image_name: str) -> Optional[str]:
         """Gets the workflow of an image."""
         pass
+
+    @abstractmethod
+    def get_graph(self, image_name: str) -> Optional[str]:
+        """Gets the graph of an image."""
+        pass

invokeai/app/services/image_files/image_files_disk.py

@@ -7,9 +7,7 @@ from PIL import Image, PngImagePlugin
 from PIL.Image import Image as PILImageType
 from send2trash import send2trash
 
-from invokeai.app.invocations.fields import MetadataField
 from invokeai.app.services.invoker import Invoker
-from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID
 from invokeai.app.util.thumbnails import get_thumbnail_name, make_thumbnail
 
 from .image_files_base import ImageFileStorageBase
@@ -56,8 +54,9 @@ class DiskImageFileStorage(ImageFileStorageBase):
         self,
         image: PILImageType,
         image_name: str,
-        metadata: Optional[MetadataField] = None,
-        workflow: Optional[WorkflowWithoutID] = None,
+        metadata: Optional[str] = None,
+        workflow: Optional[str] = None,
+        graph: Optional[str] = None,
         thumbnail_size: int = 256,
     ) -> None:
         try:
@@ -68,13 +67,14 @@ class DiskImageFileStorage(ImageFileStorageBase):
             info_dict = {}
 
             if metadata is not None:
-                metadata_json = metadata.model_dump_json()
-                info_dict["invokeai_metadata"] = metadata_json
-                pnginfo.add_text("invokeai_metadata", metadata_json)
+                info_dict["invokeai_metadata"] = metadata
+                pnginfo.add_text("invokeai_metadata", metadata)
             if workflow is not None:
-                workflow_json = workflow.model_dump_json()
-                info_dict["invokeai_workflow"] = workflow_json
-                pnginfo.add_text("invokeai_workflow", workflow_json)
+                info_dict["invokeai_workflow"] = workflow
+                pnginfo.add_text("invokeai_workflow", workflow)
+            if graph is not None:
+                info_dict["invokeai_graph"] = graph
+                pnginfo.add_text("invokeai_graph", graph)
 
             # When saving the image, the image object's info field is not populated. We need to set it
             image.info = info_dict
@@ -129,11 +129,18 @@ class DiskImageFileStorage(ImageFileStorageBase):
         path = path if isinstance(path, Path) else Path(path)
         return path.exists()
 
-    def get_workflow(self, image_name: str) -> WorkflowWithoutID | None:
+    def get_workflow(self, image_name: str) -> str | None:
         image = self.get(image_name)
         workflow = image.info.get("invokeai_workflow", None)
-        if workflow is not None:
-            return WorkflowWithoutID.model_validate_json(workflow)
+        if isinstance(workflow, str):
+            return workflow
+        return None
+
+    def get_graph(self, image_name: str) -> str | None:
+        image = self.get(image_name)
+        graph = image.info.get("invokeai_graph", None)
+        if isinstance(graph, str):
+            return graph
         return None
 
     def __validate_storage_folders(self) -> None:

invokeai/app/services/image_records/image_records_base.py

@@ -80,7 +80,7 @@ class ImageRecordStorageBase(ABC):
         starred: Optional[bool] = False,
         session_id: Optional[str] = None,
         node_id: Optional[str] = None,
-        metadata: Optional[MetadataField] = None,
+        metadata: Optional[str] = None,
     ) -> datetime:
         """Saves an image record."""
         pass

invokeai/app/services/image_records/image_records_sqlite.py

@@ -328,10 +328,9 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
         starred: Optional[bool] = False,
         session_id: Optional[str] = None,
         node_id: Optional[str] = None,
-        metadata: Optional[MetadataField] = None,
+        metadata: Optional[str] = None,
     ) -> datetime:
         try:
-            metadata_json = metadata.model_dump_json() if metadata is not None else None
             self._lock.acquire()
             self._cursor.execute(
                 """--sql
@@ -358,7 +357,7 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
                     height,
                     node_id,
                     session_id,
-                    metadata_json,
+                    metadata,
                     is_intermediate,
                     starred,
                     has_workflow,

invokeai/app/services/images/images_base.py

@@ -12,7 +12,6 @@ from invokeai.app.services.image_records.image_records_common import (
 )
 from invokeai.app.services.images.images_common import ImageDTO
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
-from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID
 
 
 class ImageServiceABC(ABC):
@@ -51,8 +50,9 @@ class ImageServiceABC(ABC):
         session_id: Optional[str] = None,
         board_id: Optional[str] = None,
         is_intermediate: Optional[bool] = False,
-        metadata: Optional[MetadataField] = None,
-        workflow: Optional[WorkflowWithoutID] = None,
+        metadata: Optional[str] = None,
+        workflow: Optional[str] = None,
+        graph: Optional[str] = None,
     ) -> ImageDTO:
         """Creates an image, storing the file and its metadata."""
         pass
@@ -87,7 +87,12 @@ class ImageServiceABC(ABC):
         pass
 
     @abstractmethod
-    def get_workflow(self, image_name: str) -> Optional[WorkflowWithoutID]:
+    def get_workflow(self, image_name: str) -> Optional[str]:
+        """Gets an image's workflow."""
+        pass
+
+    @abstractmethod
+    def get_graph(self, image_name: str) -> Optional[str]:
         """Gets an image's workflow."""
         pass
 

invokeai/app/services/images/images_default.py

@@ -5,7 +5,6 @@ from PIL.Image import Image as PILImageType
 from invokeai.app.invocations.fields import MetadataField
 from invokeai.app.services.invoker import Invoker
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
-from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID
 
 from ..image_files.image_files_common import (
     ImageFileDeleteException,
@@ -42,8 +41,9 @@ class ImageService(ImageServiceABC):
         session_id: Optional[str] = None,
         board_id: Optional[str] = None,
         is_intermediate: Optional[bool] = False,
-        metadata: Optional[MetadataField] = None,
-        workflow: Optional[WorkflowWithoutID] = None,
+        metadata: Optional[str] = None,
+        workflow: Optional[str] = None,
+        graph: Optional[str] = None,
     ) -> ImageDTO:
         if image_origin not in ResourceOrigin:
             raise InvalidOriginException
@@ -64,7 +64,7 @@ class ImageService(ImageServiceABC):
                 image_category=image_category,
                 width=width,
                 height=height,
-                has_workflow=workflow is not None,
+                has_workflow=workflow is not None or graph is not None,
                 # Meta fields
                 is_intermediate=is_intermediate,
                 # Nullable fields
@@ -75,7 +75,7 @@ class ImageService(ImageServiceABC):
             if board_id is not None:
                 self.__invoker.services.board_image_records.add_image_to_board(board_id=board_id, image_name=image_name)
             self.__invoker.services.image_files.save(
-                image_name=image_name, image=image, metadata=metadata, workflow=workflow
+                image_name=image_name, image=image, metadata=metadata, workflow=workflow, graph=graph
             )
             image_dto = self.get_dto(image_name)
 
@@ -157,7 +157,7 @@ class ImageService(ImageServiceABC):
             self.__invoker.services.logger.error("Problem getting image metadata")
             raise e
 
-    def get_workflow(self, image_name: str) -> Optional[WorkflowWithoutID]:
+    def get_workflow(self, image_name: str) -> Optional[str]:
         try:
             return self.__invoker.services.image_files.get_workflow(image_name)
         except ImageFileNotFoundException:
@@ -167,6 +167,16 @@ class ImageService(ImageServiceABC):
             self.__invoker.services.logger.error("Problem getting image workflow")
             raise
 
+    def get_graph(self, image_name: str) -> Optional[str]:
+        try:
+            return self.__invoker.services.image_files.get_graph(image_name)
+        except ImageFileNotFoundException:
+            self.__invoker.services.logger.error("Image file not found")
+            raise
+        except Exception:
+            self.__invoker.services.logger.error("Problem getting image graph")
+            raise
+
     def get_path(self, image_name: str, thumbnail: bool = False) -> str:
         try:
             return str(self.__invoker.services.image_files.get_path(image_name, thumbnail))

invokeai/app/services/session_processor/session_processor_base.py

@@ -1,6 +1,49 @@
 from abc import ABC, abstractmethod
+from threading import Event
+from typing import Optional, Protocol
 
+from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput
+from invokeai.app.services.invocation_services import InvocationServices
 from invokeai.app.services.session_processor.session_processor_common import SessionProcessorStatus
+from invokeai.app.services.session_queue.session_queue_common import SessionQueueItem
+from invokeai.app.util.profiler import Profiler
+
+
+class SessionRunnerBase(ABC):
+    """
+    Base class for session runner.
+    """
+
+    @abstractmethod
+    def start(self, services: InvocationServices, cancel_event: Event, profiler: Optional[Profiler] = None) -> None:
+        """Starts the session runner.
+
+        Args:
+            services: The invocation services.
+            cancel_event: The cancel event.
+            profiler: The profiler to use for session profiling via cProfile. Omit to disable profiling. Basic session
+                stats will be still be recorded and logged when profiling is disabled.
+        """
+        pass
+
+    @abstractmethod
+    def run(self, queue_item: SessionQueueItem) -> None:
+        """Runs a session.
+
+        Args:
+            queue_item: The session to run.
+        """
+        pass
+
+    @abstractmethod
+    def run_node(self, invocation: BaseInvocation, queue_item: SessionQueueItem) -> None:
+        """Run a single node in the graph.
+
+        Args:
+            invocation: The invocation to run.
+            queue_item: The session queue item.
+        """
+        pass
 
 
 class SessionProcessorBase(ABC):
@@ -26,3 +69,85 @@ class SessionProcessorBase(ABC):
     def get_status(self) -> SessionProcessorStatus:
         """Gets the status of the session processor"""
         pass
+
+
+class OnBeforeRunNode(Protocol):
+    def __call__(self, invocation: BaseInvocation, queue_item: SessionQueueItem) -> None:
+        """Callback to run before executing a node.
+
+        Args:
+            invocation: The invocation that will be executed.
+            queue_item: The session queue item.
+        """
+        ...
+
+
+class OnAfterRunNode(Protocol):
+    def __call__(self, invocation: BaseInvocation, queue_item: SessionQueueItem, output: BaseInvocationOutput) -> None:
+        """Callback to run before executing a node.
+
+        Args:
+            invocation: The invocation that was executed.
+            queue_item: The session queue item.
+        """
+        ...
+
+
+class OnNodeError(Protocol):
+    def __call__(
+        self,
+        invocation: BaseInvocation,
+        queue_item: SessionQueueItem,
+        error_type: str,
+        error_message: str,
+        error_traceback: str,
+    ) -> None:
+        """Callback to run when a node has an error.
+
+        Args:
+            invocation: The invocation that errored.
+            queue_item: The session queue item.
+            error_type: The type of error, e.g. "ValueError".
+            error_message: The error message, e.g. "Invalid value".
+            error_traceback: The stringified error traceback.
+        """
+        ...
+
+
+class OnBeforeRunSession(Protocol):
+    def __call__(self, queue_item: SessionQueueItem) -> None:
+        """Callback to run before executing a session.
+
+        Args:
+            queue_item: The session queue item.
+        """
+        ...
+
+
+class OnAfterRunSession(Protocol):
+    def __call__(self, queue_item: SessionQueueItem) -> None:
+        """Callback to run after executing a session.
+
+        Args:
+            queue_item: The session queue item.
+        """
+        ...
+
+
+class OnNonFatalProcessorError(Protocol):
+    def __call__(
+        self,
+        queue_item: Optional[SessionQueueItem],
+        error_type: str,
+        error_message: str,
+        error_traceback: str,
+    ) -> None:
+        """Callback to run when a non-fatal error occurs in the processor.
+
+        Args:
+            queue_item: The session queue item, if one was being executed when the error occurred.
+            error_type: The type of error, e.g. "ValueError".
+            error_message: The error message, e.g. "Invalid value".
+            error_traceback: The stringified error traceback.
+        """
+        ...

invokeai/app/services/session_processor/session_processor_default.py

@@ -7,21 +7,305 @@ from typing import Optional
 from fastapi_events.handlers.local import local_handler
 from fastapi_events.typing import Event as FastAPIEvent
 
-from invokeai.app.invocations.baseinvocation import BaseInvocation
+from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput
 from invokeai.app.services.events.events_base import EventServiceBase
 from invokeai.app.services.invocation_stats.invocation_stats_common import GESStatsNotFoundError
+from invokeai.app.services.session_processor.session_processor_base import (
+    OnAfterRunNode,
+    OnAfterRunSession,
+    OnBeforeRunNode,
+    OnBeforeRunSession,
+    OnNodeError,
+    OnNonFatalProcessorError,
+)
 from invokeai.app.services.session_processor.session_processor_common import CanceledException
-from invokeai.app.services.session_queue.session_queue_common import SessionQueueItem
+from invokeai.app.services.session_queue.session_queue_common import SessionQueueItem, SessionQueueItemNotFoundError
+from invokeai.app.services.shared.graph import NodeInputError
 from invokeai.app.services.shared.invocation_context import InvocationContextData, build_invocation_context
 from invokeai.app.util.profiler import Profiler
 
 from ..invoker import Invoker
-from .session_processor_base import SessionProcessorBase
+from .session_processor_base import InvocationServices, SessionProcessorBase, SessionRunnerBase
 from .session_processor_common import SessionProcessorStatus
 
 
+class DefaultSessionRunner(SessionRunnerBase):
+    """Processes a single session's invocations."""
+
+    def __init__(
+        self,
+        on_before_run_session_callbacks: Optional[list[OnBeforeRunSession]] = None,
+        on_before_run_node_callbacks: Optional[list[OnBeforeRunNode]] = None,
+        on_after_run_node_callbacks: Optional[list[OnAfterRunNode]] = None,
+        on_node_error_callbacks: Optional[list[OnNodeError]] = None,
+        on_after_run_session_callbacks: Optional[list[OnAfterRunSession]] = None,
+    ):
+        """
+        Args:
+            on_before_run_session_callbacks: Callbacks to run before the session starts.
+            on_before_run_node_callbacks: Callbacks to run before each node starts.
+            on_after_run_node_callbacks: Callbacks to run after each node completes.
+            on_node_error_callbacks: Callbacks to run when a node errors.
+            on_after_run_session_callbacks: Callbacks to run after the session completes.
+        """
+
+        self._on_before_run_session_callbacks = on_before_run_session_callbacks or []
+        self._on_before_run_node_callbacks = on_before_run_node_callbacks or []
+        self._on_after_run_node_callbacks = on_after_run_node_callbacks or []
+        self._on_node_error_callbacks = on_node_error_callbacks or []
+        self._on_after_run_session_callbacks = on_after_run_session_callbacks or []
+
+    def start(self, services: InvocationServices, cancel_event: ThreadEvent, profiler: Optional[Profiler] = None):
+        self._services = services
+        self._cancel_event = cancel_event
+        self._profiler = profiler
+
+    def run(self, queue_item: SessionQueueItem):
+        # Exceptions raised outside `run_node` are handled by the processor. There is no need to catch them here.
+
+        self._on_before_run_session(queue_item=queue_item)
+
+        # Loop over invocations until the session is complete or canceled
+        while True:
+            try:
+                invocation = queue_item.session.next()
+            # Anything other than a `NodeInputError` is handled as a processor error
+            except NodeInputError as e:
+                error_type = e.__class__.__name__
+                error_message = str(e)
+                error_traceback = traceback.format_exc()
+                self._on_node_error(
+                    invocation=e.node,
+                    queue_item=queue_item,
+                    error_type=error_type,
+                    error_message=error_message,
+                    error_traceback=error_traceback,
+                )
+                break
+
+            if invocation is None or self._cancel_event.is_set():
+                break
+
+            self.run_node(invocation, queue_item)
+
+            # The session is complete if all invocations have been run or there is an error on the session.
+            if queue_item.session.is_complete() or self._cancel_event.is_set():
+                break
+
+        self._on_after_run_session(queue_item=queue_item)
+
+    def run_node(self, invocation: BaseInvocation, queue_item: SessionQueueItem):
+        try:
+            # Any unhandled exception in this scope is an invocation error & will fail the graph
+            with self._services.performance_statistics.collect_stats(invocation, queue_item.session_id):
+                self._on_before_run_node(invocation, queue_item)
+
+                data = InvocationContextData(
+                    invocation=invocation,
+                    source_invocation_id=queue_item.session.prepared_source_mapping[invocation.id],
+                    queue_item=queue_item,
+                )
+                context = build_invocation_context(
+                    data=data,
+                    services=self._services,
+                    cancel_event=self._cancel_event,
+                )
+
+                # Invoke the node
+                output = invocation.invoke_internal(context=context, services=self._services)
+                # Save output and history
+                queue_item.session.complete(invocation.id, output)
+
+                self._on_after_run_node(invocation, queue_item, output)
+
+        except KeyboardInterrupt:
+            # TODO(psyche): This is expected to be caught in the main thread. Do we need to catch this here?
+            pass
+        except CanceledException:
+            # When the user cancels the graph, we first set the cancel event. The event is checked
+            # between invocations, in this loop. Some invocations are long-running, and we need to
+            # be able to cancel them mid-execution.
+            #
+            # For example, denoising is a long-running invocation with many steps. A step callback
+            # is executed after each step. This step callback checks if the canceled event is set,
+            # then raises a CanceledException to stop execution immediately.
+            #
+            # When we get a CanceledException, we don't need to do anything - just pass and let the
+            # loop go to its next iteration, and the cancel event will be handled correctly.
+            pass
+        except Exception as e:
+            error_type = e.__class__.__name__
+            error_message = str(e)
+            error_traceback = traceback.format_exc()
+            self._on_node_error(
+                invocation=invocation,
+                queue_item=queue_item,
+                error_type=error_type,
+                error_message=error_message,
+                error_traceback=error_traceback,
+            )
+
+    def _on_before_run_session(self, queue_item: SessionQueueItem) -> None:
+        """Run before a session is executed"""
+
+        self._services.logger.debug(
+            f"On before run session: queue item {queue_item.item_id}, session {queue_item.session_id}"
+        )
+
+        # If profiling is enabled, start the profiler
+        if self._profiler is not None:
+            self._profiler.start(profile_id=queue_item.session_id)
+
+        for callback in self._on_before_run_session_callbacks:
+            callback(queue_item=queue_item)
+
+    def _on_after_run_session(self, queue_item: SessionQueueItem) -> None:
+        """Run after a session is executed"""
+
+        self._services.logger.debug(
+            f"On after run session: queue item {queue_item.item_id}, session {queue_item.session_id}"
+        )
+
+        # If we are profiling, stop the profiler and dump the profile & stats
+        if self._profiler is not None:
+            profile_path = self._profiler.stop()
+            stats_path = profile_path.with_suffix(".json")
+            self._services.performance_statistics.dump_stats(
+                graph_execution_state_id=queue_item.session.id, output_path=stats_path
+            )
+
+        try:
+            # Update the queue item with the completed session. If the queue item has been removed from the queue,
+            # we'll get a SessionQueueItemNotFoundError and we can ignore it. This can happen if the queue is cleared
+            # while the session is running.
+            queue_item = self._services.session_queue.set_queue_item_session(queue_item.item_id, queue_item.session)
+
+            # TODO(psyche): This feels jumbled - we should review separation of concerns here.
+            # Send complete event. The events service will receive this and update the queue item's status.
+            self._services.events.emit_graph_execution_complete(
+                queue_batch_id=queue_item.batch_id,
+                queue_item_id=queue_item.item_id,
+                queue_id=queue_item.queue_id,
+                graph_execution_state_id=queue_item.session.id,
+            )
+
+            # We'll get a GESStatsNotFoundError if we try to log stats for an untracked graph, but in the processor
+            # we don't care about that - suppress the error.
+            with suppress(GESStatsNotFoundError):
+                self._services.performance_statistics.log_stats(queue_item.session.id)
+                self._services.performance_statistics.reset_stats()
+
+            for callback in self._on_after_run_session_callbacks:
+                callback(queue_item=queue_item)
+        except SessionQueueItemNotFoundError:
+            pass
+
+    def _on_before_run_node(self, invocation: BaseInvocation, queue_item: SessionQueueItem):
+        """Run before a node is executed"""
+
+        self._services.logger.debug(
+            f"On before run node: queue item {queue_item.item_id}, session {queue_item.session_id}, node {invocation.id} ({invocation.get_type()})"
+        )
+
+        # Send starting event
+        self._services.events.emit_invocation_started(
+            queue_batch_id=queue_item.batch_id,
+            queue_item_id=queue_item.item_id,
+            queue_id=queue_item.queue_id,
+            graph_execution_state_id=queue_item.session_id,
+            node=invocation.model_dump(),
+            source_node_id=queue_item.session.prepared_source_mapping[invocation.id],
+        )
+
+        for callback in self._on_before_run_node_callbacks:
+            callback(invocation=invocation, queue_item=queue_item)
+
+    def _on_after_run_node(
+        self, invocation: BaseInvocation, queue_item: SessionQueueItem, output: BaseInvocationOutput
+    ):
+        """Run after a node is executed"""
+
+        self._services.logger.debug(
+            f"On after run node: queue item {queue_item.item_id}, session {queue_item.session_id}, node {invocation.id} ({invocation.get_type()})"
+        )
+
+        # Send complete event on successful runs
+        self._services.events.emit_invocation_complete(
+            queue_batch_id=queue_item.batch_id,
+            queue_item_id=queue_item.item_id,
+            queue_id=queue_item.queue_id,
+            graph_execution_state_id=queue_item.session.id,
+            node=invocation.model_dump(),
+            source_node_id=queue_item.session.prepared_source_mapping[invocation.id],
+            result=output.model_dump(),
+        )
+
+        for callback in self._on_after_run_node_callbacks:
+            callback(invocation=invocation, queue_item=queue_item, output=output)
+
+    def _on_node_error(
+        self,
+        invocation: BaseInvocation,
+        queue_item: SessionQueueItem,
+        error_type: str,
+        error_message: str,
+        error_traceback: str,
+    ):
+        """Run when a node errors"""
+
+        self._services.logger.debug(
+            f"On node error: queue item {queue_item.item_id}, session {queue_item.session_id}, node {invocation.id} ({invocation.get_type()})"
+        )
+
+        # Node errors do not get the full traceback. Only the queue item gets the full traceback.
+        node_error = f"{error_type}: {error_message}"
+        queue_item.session.set_node_error(invocation.id, node_error)
+        self._services.logger.error(
+            f"Error while invoking session {queue_item.session_id}, invocation {invocation.id} ({invocation.get_type()}): {error_message}"
+        )
+        self._services.logger.error(error_traceback)
+
+        # Send error event
+        self._services.events.emit_invocation_error(
+            queue_batch_id=queue_item.session_id,
+            queue_item_id=queue_item.item_id,
+            queue_id=queue_item.queue_id,
+            graph_execution_state_id=queue_item.session.id,
+            node=invocation.model_dump(),
+            source_node_id=queue_item.session.prepared_source_mapping[invocation.id],
+            error_type=error_type,
+            error_message=error_message,
+            error_traceback=error_traceback,
+            user_id=getattr(queue_item, "user_id", None),
+            project_id=getattr(queue_item, "project_id", None),
+        )
+
+        for callback in self._on_node_error_callbacks:
+            callback(
+                invocation=invocation,
+                queue_item=queue_item,
+                error_type=error_type,
+                error_message=error_message,
+                error_traceback=error_traceback,
+            )
+
+
 class DefaultSessionProcessor(SessionProcessorBase):
-    def start(self, invoker: Invoker, thread_limit: int = 1, polling_interval: int = 1) -> None:
+    def __init__(
+        self,
+        session_runner: Optional[SessionRunnerBase] = None,
+        on_non_fatal_processor_error_callbacks: Optional[list[OnNonFatalProcessorError]] = None,
+        thread_limit: int = 1,
+        polling_interval: int = 1,
+    ) -> None:
+        super().__init__()
+
+        self.session_runner = session_runner if session_runner else DefaultSessionRunner()
+        self._on_non_fatal_processor_error_callbacks = on_non_fatal_processor_error_callbacks or []
+        self._thread_limit = thread_limit
+        self._polling_interval = polling_interval
+
+    def start(self, invoker: Invoker) -> None:
         self._invoker: Invoker = invoker
         self._queue_item: Optional[SessionQueueItem] = None
         self._invocation: Optional[BaseInvocation] = None
@@ -33,9 +317,7 @@ class DefaultSessionProcessor(SessionProcessorBase):
 
         local_handler.register(event_name=EventServiceBase.queue_event, _func=self._on_queue_event)
 
-        self._thread_limit = thread_limit
-        self._thread_semaphore = BoundedSemaphore(thread_limit)
-        self._polling_interval = polling_interval
+        self._thread_semaphore = BoundedSemaphore(self._thread_limit)
 
         # If profiling is enabled, create a profiler. The same profiler will be used for all sessions. Internally,
         # the profiler will create a new profile for each session.
@@ -49,6 +331,7 @@ class DefaultSessionProcessor(SessionProcessorBase):
             else None
         )
 
+        self.session_runner.start(services=invoker.services, cancel_event=self._cancel_event, profiler=self._profiler)
         self._thread = Thread(
             name="session_processor",
             target=self._process,
@@ -91,6 +374,7 @@ class DefaultSessionProcessor(SessionProcessorBase):
             "failed",
             "canceled",
         ]:
+            self._cancel_event.set()
             self._poll_now()
 
     def resume(self) -> SessionProcessorStatus:
@@ -116,8 +400,8 @@ class DefaultSessionProcessor(SessionProcessorBase):
         resume_event: ThreadEvent,
         cancel_event: ThreadEvent,
     ):
-        # Outermost processor try block; any unhandled exception is a fatal processor error
         try:
+            # Any unhandled exception in this block is a fatal processor error and will stop the processor.
             self._thread_semaphore.acquire()
             stop_event.clear()
             resume_event.set()
@@ -125,8 +409,8 @@ class DefaultSessionProcessor(SessionProcessorBase):
 
             while not stop_event.is_set():
                 poll_now_event.clear()
-                # Middle processor try block; any unhandled exception is a non-fatal processor error
                 try:
+                    # Any unhandled exception in this block is a nonfatal processor error and will be handled.
                     # If we are paused, wait for resume event
                     resume_event.wait()
 
@@ -142,157 +426,62 @@ class DefaultSessionProcessor(SessionProcessorBase):
                     self._invoker.services.logger.debug(f"Executing queue item {self._queue_item.item_id}")
                     cancel_event.clear()
 
-                    # If profiling is enabled, start the profiler
-                    if self._profiler is not None:
-                        self._profiler.start(profile_id=self._queue_item.session_id)
+                    # Run the graph
+                    self.session_runner.run(queue_item=self._queue_item)
 
-                    # Prepare invocations and take the first
-                    self._invocation = self._queue_item.session.next()
-
-                    # Loop over invocations until the session is complete or canceled
-                    while self._invocation is not None and not cancel_event.is_set():
-                        # get the source node id to provide to clients (the prepared node id is not as useful)
-                        source_invocation_id = self._queue_item.session.prepared_source_mapping[self._invocation.id]
-
-                        # Send starting event
-                        self._invoker.services.events.emit_invocation_started(
-                            queue_batch_id=self._queue_item.batch_id,
-                            queue_item_id=self._queue_item.item_id,
-                            queue_id=self._queue_item.queue_id,
-                            graph_execution_state_id=self._queue_item.session_id,
-                            node=self._invocation.model_dump(),
-                            source_node_id=source_invocation_id,
-                        )
-
-                        # Innermost processor try block; any unhandled exception is an invocation error & will fail the graph
-                        try:
-                            with self._invoker.services.performance_statistics.collect_stats(
-                                self._invocation, self._queue_item.session.id
-                            ):
-                                # Build invocation context (the node-facing API)
-                                data = InvocationContextData(
-                                    invocation=self._invocation,
-                                    source_invocation_id=source_invocation_id,
-                                    queue_item=self._queue_item,
-                                )
-                                context = build_invocation_context(
-                                    data=data,
-                                    services=self._invoker.services,
-                                    cancel_event=self._cancel_event,
-                                )
-
-                                # Invoke the node
-                                outputs = self._invocation.invoke_internal(
-                                    context=context, services=self._invoker.services
-                                )
-
-                                # Save outputs and history
-                                self._queue_item.session.complete(self._invocation.id, outputs)
-
-                                # Send complete event
-                                self._invoker.services.events.emit_invocation_complete(
-                                    queue_batch_id=self._queue_item.batch_id,
-                                    queue_item_id=self._queue_item.item_id,
-                                    queue_id=self._queue_item.queue_id,
-                                    graph_execution_state_id=self._queue_item.session.id,
-                                    node=self._invocation.model_dump(),
-                                    source_node_id=source_invocation_id,
-                                    result=outputs.model_dump(),
-                                )
-
-                        except KeyboardInterrupt:
-                            # TODO(MM2): Create an event for this
-                            pass
-
-                        except CanceledException:
-                            # When the user cancels the graph, we first set the cancel event. The event is checked
-                            # between invocations, in this loop. Some invocations are long-running, and we need to
-                            # be able to cancel them mid-execution.
-                            #
-                            # For example, denoising is a long-running invocation with many steps. A step callback
-                            # is executed after each step. This step callback checks if the canceled event is set,
-                            # then raises a CanceledException to stop execution immediately.
-                            #
-                            # When we get a CanceledException, we don't need to do anything - just pass and let the
-                            # loop go to its next iteration, and the cancel event will be handled correctly.
-                            pass
-
-                        except Exception as e:
-                            error = traceback.format_exc()
-
-                            # Save error
-                            self._queue_item.session.set_node_error(self._invocation.id, error)
-                            self._invoker.services.logger.error(
-                                f"Error while invoking session {self._queue_item.session_id}, invocation {self._invocation.id} ({self._invocation.get_type()}):\n{e}"
-                            )
-                            self._invoker.services.logger.error(error)
-
-                            # Send error event
-                            self._invoker.services.events.emit_invocation_error(
-                                queue_batch_id=self._queue_item.session_id,
-                                queue_item_id=self._queue_item.item_id,
-                                queue_id=self._queue_item.queue_id,
-                                graph_execution_state_id=self._queue_item.session.id,
-                                node=self._invocation.model_dump(),
-                                source_node_id=source_invocation_id,
-                                error_type=e.__class__.__name__,
-                                error=error,
-                            )
-                            pass
-
-                        # The session is complete if the all invocations are complete or there was an error
-                        if self._queue_item.session.is_complete() or cancel_event.is_set():
-                            # Send complete event
-                            self._invoker.services.events.emit_graph_execution_complete(
-                                queue_batch_id=self._queue_item.batch_id,
-                                queue_item_id=self._queue_item.item_id,
-                                queue_id=self._queue_item.queue_id,
-                                graph_execution_state_id=self._queue_item.session.id,
-                            )
-                            # If we are profiling, stop the profiler and dump the profile & stats
-                            if self._profiler:
-                                profile_path = self._profiler.stop()
-                                stats_path = profile_path.with_suffix(".json")
-                                self._invoker.services.performance_statistics.dump_stats(
-                                    graph_execution_state_id=self._queue_item.session.id, output_path=stats_path
-                                )
-                            # We'll get a GESStatsNotFoundError if we try to log stats for an untracked graph, but in the processor
-                            # we don't care about that - suppress the error.
-                            with suppress(GESStatsNotFoundError):
-                                self._invoker.services.performance_statistics.log_stats(self._queue_item.session.id)
-                                self._invoker.services.performance_statistics.reset_stats()
-
-                            # Set the invocation to None to prepare for the next session
-                            self._invocation = None
-                        else:
-                            # Prepare the next invocation
-                            self._invocation = self._queue_item.session.next()
-                    else:
-                        # The queue was empty, wait for next polling interval or event to try again
-                        self._invoker.services.logger.debug("Waiting for next polling interval or event")
-                        poll_now_event.wait(self._polling_interval)
-                        continue
-                except Exception:
-                    # Non-fatal error in processor
-                    self._invoker.services.logger.error(
-                        f"Non-fatal error in session processor:\n{traceback.format_exc()}"
+                except Exception as e:
+                    error_type = e.__class__.__name__
+                    error_message = str(e)
+                    error_traceback = traceback.format_exc()
+                    self._on_non_fatal_processor_error(
+                        queue_item=self._queue_item,
+                        error_type=error_type,
+                        error_message=error_message,
+                        error_traceback=error_traceback,
                     )
-                    # Cancel the queue item
-                    if self._queue_item is not None:
-                        self._invoker.services.session_queue.cancel_queue_item(
-                            self._queue_item.item_id, error=traceback.format_exc()
-                        )
-                    # Reset the invocation to None to prepare for the next session
-                    self._invocation = None
-                    # Immediately poll for next queue item
+                    # Wait for next polling interval or event to try again
                     poll_now_event.wait(self._polling_interval)
                     continue
-        except Exception:
+        except Exception as e:
             # Fatal error in processor, log and pass - we're done here
-            self._invoker.services.logger.error(f"Fatal Error in session processor:\n{traceback.format_exc()}")
+            error_type = e.__class__.__name__
+            error_message = str(e)
+            error_traceback = traceback.format_exc()
+            self._invoker.services.logger.error(f"Fatal Error in session processor {error_type}: {error_message}")
+            self._invoker.services.logger.error(error_traceback)
             pass
         finally:
             stop_event.clear()
             poll_now_event.clear()
             self._queue_item = None
             self._thread_semaphore.release()
+
+    def _on_non_fatal_processor_error(
+        self,
+        queue_item: Optional[SessionQueueItem],
+        error_type: str,
+        error_message: str,
+        error_traceback: str,
+    ) -> None:
+        # Non-fatal error in processor
+        self._invoker.services.logger.error(f"Non-fatal error in session processor {error_type}: {error_message}")
+        self._invoker.services.logger.error(error_traceback)
+
+        if queue_item is not None:
+            # Update the queue item with the completed session
+            self._invoker.services.session_queue.set_queue_item_session(queue_item.item_id, queue_item.session)
+            # Fail the queue item
+            self._invoker.services.session_queue.fail_queue_item(
+                item_id=queue_item.item_id,
+                error_type=error_type,
+                error_message=error_message,
+                error_traceback=error_traceback,
+            )
+
+        for callback in self._on_non_fatal_processor_error_callbacks:
+            callback(
+                queue_item=queue_item,
+                error_type=error_type,
+                error_message=error_message,
+                error_traceback=error_traceback,
+            )

invokeai/app/services/session_queue/session_queue_base.py

@@ -16,6 +16,7 @@ from invokeai.app.services.session_queue.session_queue_common import (
     SessionQueueItemDTO,
     SessionQueueStatus,
 )
+from invokeai.app.services.shared.graph import GraphExecutionState
 from invokeai.app.services.shared.pagination import CursorPaginatedResults
 
 
@@ -73,10 +74,17 @@ class SessionQueueBase(ABC):
         pass
 
     @abstractmethod
-    def cancel_queue_item(self, item_id: int, error: Optional[str] = None) -> SessionQueueItem:
+    def cancel_queue_item(self, item_id: int) -> SessionQueueItem:
         """Cancels a session queue item"""
         pass
 
+    @abstractmethod
+    def fail_queue_item(
+        self, item_id: int, error_type: str, error_message: str, error_traceback: str
+    ) -> SessionQueueItem:
+        """Fails a session queue item"""
+        pass
+
     @abstractmethod
     def cancel_by_batch_ids(self, queue_id: str, batch_ids: list[str]) -> CancelByBatchIDsResult:
         """Cancels all queue items with matching batch IDs"""
@@ -103,3 +111,8 @@ class SessionQueueBase(ABC):
     def get_queue_item(self, item_id: int) -> SessionQueueItem:
         """Gets a session queue item by ID"""
         pass
+
+    @abstractmethod
+    def set_queue_item_session(self, item_id: int, session: GraphExecutionState) -> SessionQueueItem:
+        """Sets the session for a session queue item. Use this to update the session state."""
+        pass

invokeai/app/services/session_queue/session_queue_common.py

@@ -3,7 +3,16 @@ import json
 from itertools import chain, product
 from typing import Generator, Iterable, Literal, NamedTuple, Optional, TypeAlias, Union, cast
 
-from pydantic import BaseModel, ConfigDict, Field, StrictStr, TypeAdapter, field_validator, model_validator
+from pydantic import (
+    AliasChoices,
+    BaseModel,
+    ConfigDict,
+    Field,
+    StrictStr,
+    TypeAdapter,
+    field_validator,
+    model_validator,
+)
 from pydantic_core import to_jsonable_python
 
 from invokeai.app.invocations.baseinvocation import BaseInvocation
@@ -189,7 +198,13 @@ class SessionQueueItemWithoutGraph(BaseModel):
     session_id: str = Field(
         description="The ID of the session associated with this queue item. The session doesn't exist in graph_executions until the queue item is executed."
     )
-    error: Optional[str] = Field(default=None, description="The error message if this queue item errored")
+    error_type: Optional[str] = Field(default=None, description="The error type if this queue item errored")
+    error_message: Optional[str] = Field(default=None, description="The error message if this queue item errored")
+    error_traceback: Optional[str] = Field(
+        default=None,
+        description="The error traceback if this queue item errored",
+        validation_alias=AliasChoices("error_traceback", "error"),
+    )
     created_at: Union[datetime.datetime, str] = Field(description="When this queue item was created")
     updated_at: Union[datetime.datetime, str] = Field(description="When this queue item was updated")
     started_at: Optional[Union[datetime.datetime, str]] = Field(description="When this queue item was started")

invokeai/app/services/session_queue/session_queue_sqlite.py

@@ -27,6 +27,7 @@ from invokeai.app.services.session_queue.session_queue_common import (
     calc_session_count,
     prepare_values_to_insert,
 )
+from invokeai.app.services.shared.graph import GraphExecutionState
 from invokeai.app.services.shared.pagination import CursorPaginatedResults
 from invokeai.app.services.shared.sqlite.sqlite_database import SqliteDatabase
 
@@ -81,10 +82,18 @@ class SqliteSessionQueue(SessionQueueBase):
     async def _handle_error_event(self, event: FastAPIEvent) -> None:
         try:
             item_id = event[1]["data"]["queue_item_id"]
-            error = event[1]["data"]["error"]
+            error_type = event[1]["data"]["error_type"]
+            error_message = event[1]["data"]["error_message"]
+            error_traceback = event[1]["data"]["error_traceback"]
             queue_item = self.get_queue_item(item_id)
             # always set to failed if have an error, even if previously the item was marked completed or canceled
-            queue_item = self._set_queue_item_status(item_id=queue_item.item_id, status="failed", error=error)
+            queue_item = self._set_queue_item_status(
+                item_id=queue_item.item_id,
+                status="failed",
+                error_type=error_type,
+                error_message=error_message,
+                error_traceback=error_traceback,
+            )
         except SessionQueueItemNotFoundError:
             return
 
@@ -271,17 +280,22 @@ class SqliteSessionQueue(SessionQueueBase):
         return SessionQueueItem.queue_item_from_dict(dict(result))
 
     def _set_queue_item_status(
-        self, item_id: int, status: QUEUE_ITEM_STATUS, error: Optional[str] = None
+        self,
+        item_id: int,
+        status: QUEUE_ITEM_STATUS,
+        error_type: Optional[str] = None,
+        error_message: Optional[str] = None,
+        error_traceback: Optional[str] = None,
     ) -> SessionQueueItem:
         try:
             self.__lock.acquire()
             self.__cursor.execute(
                 """--sql
                 UPDATE session_queue
-                SET status = ?, error = ?
+                SET status = ?, error_type = ?, error_message = ?, error_traceback = ?
                 WHERE item_id = ?
                 """,
-                (status, error, item_id),
+                (status, error_type, error_message, error_traceback, item_id),
             )
             self.__conn.commit()
         except Exception:
@@ -338,26 +352,6 @@ class SqliteSessionQueue(SessionQueueBase):
             self.__lock.release()
         return IsFullResult(is_full=is_full)
 
-    def delete_queue_item(self, item_id: int) -> SessionQueueItem:
-        queue_item = self.get_queue_item(item_id=item_id)
-        try:
-            self.__lock.acquire()
-            self.__cursor.execute(
-                """--sql
-                DELETE FROM session_queue
-                WHERE
-                  item_id = ?
-                """,
-                (item_id,),
-            )
-            self.__conn.commit()
-        except Exception:
-            self.__conn.rollback()
-            raise
-        finally:
-            self.__lock.release()
-        return queue_item
-
     def clear(self, queue_id: str) -> ClearResult:
         try:
             self.__lock.acquire()
@@ -424,11 +418,34 @@ class SqliteSessionQueue(SessionQueueBase):
             self.__lock.release()
         return PruneResult(deleted=count)
 
-    def cancel_queue_item(self, item_id: int, error: Optional[str] = None) -> SessionQueueItem:
+    def cancel_queue_item(self, item_id: int) -> SessionQueueItem:
         queue_item = self.get_queue_item(item_id)
         if queue_item.status not in ["canceled", "failed", "completed"]:
-            status = "failed" if error is not None else "canceled"
-            queue_item = self._set_queue_item_status(item_id=item_id, status=status, error=error)  # type: ignore [arg-type] # mypy seems to not narrow the Literals here
+            queue_item = self._set_queue_item_status(item_id=item_id, status="canceled")
+            self.__invoker.services.events.emit_session_canceled(
+                queue_item_id=queue_item.item_id,
+                queue_id=queue_item.queue_id,
+                queue_batch_id=queue_item.batch_id,
+                graph_execution_state_id=queue_item.session_id,
+            )
+        return queue_item
+
+    def fail_queue_item(
+        self,
+        item_id: int,
+        error_type: str,
+        error_message: str,
+        error_traceback: str,
+    ) -> SessionQueueItem:
+        queue_item = self.get_queue_item(item_id)
+        if queue_item.status not in ["canceled", "failed", "completed"]:
+            queue_item = self._set_queue_item_status(
+                item_id=item_id,
+                status="failed",
+                error_type=error_type,
+                error_message=error_message,
+                error_traceback=error_traceback,
+            )
             self.__invoker.services.events.emit_session_canceled(
                 queue_item_id=queue_item.item_id,
                 queue_id=queue_item.queue_id,
@@ -562,6 +579,29 @@ class SqliteSessionQueue(SessionQueueBase):
             raise SessionQueueItemNotFoundError(f"No queue item with id {item_id}")
         return SessionQueueItem.queue_item_from_dict(dict(result))
 
+    def set_queue_item_session(self, item_id: int, session: GraphExecutionState) -> SessionQueueItem:
+        try:
+            # Use exclude_none so we don't end up with a bunch of nulls in the graph - this can cause validation errors
+            # when the graph is loaded. Graph execution occurs purely in memory - the session saved here is not referenced
+            # during execution.
+            session_json = session.model_dump_json(warnings=False, exclude_none=True)
+            self.__lock.acquire()
+            self.__cursor.execute(
+                """--sql
+                UPDATE session_queue
+                SET session = ?
+                WHERE item_id = ?
+                """,
+                (session_json, item_id),
+            )
+            self.__conn.commit()
+        except Exception:
+            self.__conn.rollback()
+            raise
+        finally:
+            self.__lock.release()
+        return self.get_queue_item(item_id)
+
     def list_queue_items(
         self,
         queue_id: str,
@@ -578,7 +618,9 @@ class SqliteSessionQueue(SessionQueueBase):
                     status,
                     priority,
                     field_values,
-                    error,
+                    error_type,
+                    error_message,
+                    error_traceback,
                     created_at,
                     updated_at,
                     completed_at,

invokeai/app/services/shared/graph.py

@@ -8,6 +8,7 @@ import networkx as nx
 from pydantic import (
     BaseModel,
     GetJsonSchemaHandler,
+    ValidationError,
     field_validator,
 )
 from pydantic.fields import Field
@@ -190,6 +191,39 @@ class UnknownGraphValidationError(ValueError):
     pass
 
 
+class NodeInputError(ValueError):
+    """Raised when a node fails preparation. This occurs when a node's inputs are being set from its incomers, but an
+    input fails validation.
+
+    Attributes:
+        node: The node that failed preparation. Note: only successfully set fields will be accurate. Review the error to
+            determine which field caused the failure.
+    """
+
+    def __init__(self, node: BaseInvocation, e: ValidationError):
+        self.original_error = e
+        self.node = node
+        # When preparing a node, we set each input one-at-a-time. We may thus safely assume that the first error
+        # represents the first input that failed.
+        self.failed_input = loc_to_dot_sep(e.errors()[0]["loc"])
+        super().__init__(f"Node {node.id} has invalid incoming input for {self.failed_input}")
+
+
+def loc_to_dot_sep(loc: tuple[Union[str, int], ...]) -> str:
+    """Helper to pretty-print pydantic error locations as dot-separated strings.
+    Taken from https://docs.pydantic.dev/latest/errors/errors/#customize-error-messages
+    """
+    path = ""
+    for i, x in enumerate(loc):
+        if isinstance(x, str):
+            if i > 0:
+                path += "."
+            path += x
+        else:
+            path += f"[{x}]"
+    return path
+
+
 @invocation_output("iterate_output")
 class IterateInvocationOutput(BaseInvocationOutput):
     """Used to connect iteration outputs. Will be expanded to a specific output."""
@@ -821,7 +855,10 @@ class GraphExecutionState(BaseModel):
 
         # Get values from edges
         if next_node is not None:
-            self._prepare_inputs(next_node)
+            try:
+                self._prepare_inputs(next_node)
+            except ValidationError as e:
+                raise NodeInputError(next_node, e)
 
         # If next is still none, there's no next node, return None
         return next_node

invokeai/app/services/shared/invocation_context.py

@@ -180,9 +180,9 @@ class ImagesInterface(InvocationContextInterface):
         # If `metadata` is provided directly, use that. Else, use the metadata provided by `WithMetadata`, falling back to None.
         metadata_ = None
         if metadata:
-            metadata_ = metadata
-        elif isinstance(self._data.invocation, WithMetadata):
-            metadata_ = self._data.invocation.metadata
+            metadata_ = metadata.model_dump_json()
+        elif isinstance(self._data.invocation, WithMetadata) and self._data.invocation.metadata:
+            metadata_ = self._data.invocation.metadata.model_dump_json()
 
         # If `board_id` is provided directly, use that. Else, use the board provided by `WithBoard`, falling back to None.
         board_id_ = None
@@ -191,6 +191,14 @@ class ImagesInterface(InvocationContextInterface):
         elif isinstance(self._data.invocation, WithBoard) and self._data.invocation.board:
             board_id_ = self._data.invocation.board.board_id
 
+        workflow_ = None
+        if self._data.queue_item.workflow:
+            workflow_ = self._data.queue_item.workflow.model_dump_json()
+
+        graph_ = None
+        if self._data.queue_item.session.graph:
+            graph_ = self._data.queue_item.session.graph.model_dump_json()
+
         return self._services.images.create(
             image=image,
             is_intermediate=self._data.invocation.is_intermediate,
@@ -198,7 +206,8 @@ class ImagesInterface(InvocationContextInterface):
             board_id=board_id_,
             metadata=metadata_,
             image_origin=ResourceOrigin.INTERNAL,
-            workflow=self._data.queue_item.workflow,
+            workflow=workflow_,
+            graph=graph_,
             session_id=self._data.queue_item.session_id,
             node_id=self._data.invocation.id,
         )

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

@@ -12,6 +12,7 @@ from invokeai.app.services.shared.sqlite_migrator.migrations.migration_6 import
 from invokeai.app.services.shared.sqlite_migrator.migrations.migration_7 import build_migration_7
 from invokeai.app.services.shared.sqlite_migrator.migrations.migration_8 import build_migration_8
 from invokeai.app.services.shared.sqlite_migrator.migrations.migration_9 import build_migration_9
+from invokeai.app.services.shared.sqlite_migrator.migrations.migration_10 import build_migration_10
 from invokeai.app.services.shared.sqlite_migrator.sqlite_migrator_impl import SqliteMigrator
 
 
@@ -41,6 +42,7 @@ def init_db(config: InvokeAIAppConfig, logger: Logger, image_files: ImageFileSto
     migrator.register_migration(build_migration_7())
     migrator.register_migration(build_migration_8(app_config=config))
     migrator.register_migration(build_migration_9())
+    migrator.register_migration(build_migration_10())
     migrator.run_migrations()
 
     return db

invokeai/app/services/shared/sqlite_migrator/migrations/migration_10.py

@@ -0,0 +1,35 @@
+import sqlite3
+
+from invokeai.app.services.shared.sqlite_migrator.sqlite_migrator_common import Migration
+
+
+class Migration10Callback:
+    def __call__(self, cursor: sqlite3.Cursor) -> None:
+        self._update_error_cols(cursor)
+
+    def _update_error_cols(self, cursor: sqlite3.Cursor) -> None:
+        """
+        - Adds `error_type` and `error_message` columns to the session queue table.
+        - Renames the `error` column to `error_traceback`.
+        """
+
+        cursor.execute("ALTER TABLE session_queue ADD COLUMN error_type TEXT;")
+        cursor.execute("ALTER TABLE session_queue ADD COLUMN error_message TEXT;")
+        cursor.execute("ALTER TABLE session_queue RENAME COLUMN error TO error_traceback;")
+
+
+def build_migration_10() -> Migration:
+    """
+    Build the migration from database version 9 to 10.
+
+    This migration does the following:
+    - Adds `error_type` and `error_message` columns to the session queue table.
+    - Renames the `error` column to `error_traceback`.
+    """
+    migration_10 = Migration(
+        from_version=9,
+        to_version=10,
+        callback=Migration10Callback(),
+    )
+
+    return migration_10

invokeai/frontend/web/.eslintrc.js

@@ -10,6 +10,8 @@ module.exports = {
     'path/no-relative-imports': ['error', { maxDepth: 0 }],
     // https://github.com/edvardchen/eslint-plugin-i18next/blob/HEAD/docs/rules/no-literal-string.md
     'i18next/no-literal-string': 'error',
+    // https://eslint.org/docs/latest/rules/no-console
+    'no-console': 'error',
   },
   overrides: [
     /**

invokeai/frontend/web/.gitignore

@@ -43,4 +43,5 @@ stats.html
 yalc.lock
 
 # vitest
-tsconfig.vitest-temp.json
+tsconfig.vitest-temp.json
+coverage/

invokeai/frontend/web/package.json

@@ -35,6 +35,7 @@
     "storybook": "storybook dev -p 6006",
     "build-storybook": "storybook build",
     "test": "vitest",
+    "test:ui": "vitest --coverage --ui",
     "test:no-watch": "vitest --no-watch"
   },
   "madge": {
@@ -132,6 +133,8 @@
     "@types/react-dom": "^18.3.0",
     "@types/uuid": "^9.0.8",
     "@vitejs/plugin-react-swc": "^3.6.0",
+    "@vitest/coverage-v8": "^1.5.0",
+    "@vitest/ui": "^1.5.0",
     "concurrently": "^8.2.2",
     "dpdm": "^3.14.0",
     "eslint": "^8.57.0",

invokeai/frontend/web/pnpm-lock.yaml

@@ -229,6 +229,12 @@ devDependencies:
   '@vitejs/plugin-react-swc':
     specifier: ^3.6.0
     version: 3.6.0(vite@5.2.11)
+  '@vitest/coverage-v8':
+    specifier: ^1.5.0
+    version: 1.6.0(vitest@1.6.0)
+  '@vitest/ui':
+    specifier: ^1.5.0
+    version: 1.6.0(vitest@1.6.0)
   concurrently:
     specifier: ^8.2.2
     version: 8.2.2
@@ -288,7 +294,7 @@ devDependencies:
     version: 4.3.2(typescript@5.4.5)(vite@5.2.11)
   vitest:
     specifier: ^1.6.0
-    version: 1.6.0(@types/node@20.12.10)
+    version: 1.6.0(@types/node@20.12.10)(@vitest/ui@1.6.0)
 
 packages:
 
@@ -1679,6 +1685,10 @@ packages:
     resolution: {integrity: sha512-4iri8i1AqYHJE2DstZYkyEprg6Pq6sKx3xn5FpySk9sNhH7qN2LLlHJCfDTZRILNwQNPD7mATWM0TBui7uC1pA==}
     dev: true
 
+  /@bcoe/v8-coverage@0.2.3:
+    resolution: {integrity: sha512-0hYQ8SB4Db5zvZB4axdMHGwEaQjkZzFjQiN9LVYvIFB2nSUHW9tYpxWriPrWDASIxiaXax83REcLxuSdnGPZtw==}
+    dev: true
+
   /@chakra-ui/accordion@2.3.1(@chakra-ui/system@2.6.2)(framer-motion@10.18.0)(react@18.3.1):
     resolution: {integrity: sha512-FSXRm8iClFyU+gVaXisOSEw0/4Q+qZbFRiuhIAkVU6Boj0FxAMrlo9a8AV5TuF77rgaHytCdHk0Ng+cyUijrag==}
     peerDependencies:
@@ -3635,6 +3645,11 @@ packages:
       wrap-ansi-cjs: /wrap-ansi@7.0.0
     dev: true
 
+  /@istanbuljs/schema@0.1.3:
+    resolution: {integrity: sha512-ZXRY4jNvVgSVQ8DL3LTcakaAtXwTVUxE81hslsyD2AtoXW/wVob10HkOJ1X/pAlcI7D+2YoZKg5do8G/w6RYgA==}
+    engines: {node: '>=8'}
+    dev: true
+
   /@jest/schemas@29.6.3:
     resolution: {integrity: sha512-mo5j5X+jIZmJQveBKeS/clAueipV7KgiX1vMgCxam1RNYiqE1w62n0/tJJnHtjW8ZHcQco5gY85jA3mi0L+nSA==}
     engines: {node: ^14.15.0 || ^16.10.0 || >=18.0.0}
@@ -3822,6 +3837,10 @@ packages:
     dev: true
     optional: true
 
+  /@polka/url@1.0.0-next.25:
+    resolution: {integrity: sha512-j7P6Rgr3mmtdkeDGTe0E/aYyWEWVtc5yFXtHCRHs28/jptDEWfaVOc5T7cblqy1XKPPfCxJc/8DwQ5YgLOZOVQ==}
+    dev: true
+
   /@popperjs/core@2.11.8:
     resolution: {integrity: sha512-P1st0aksCrn9sGZhp8GMYwBnQsbvAWsZAX44oXNNvLHGqAOcoVxmjZiohstwQ7SqKnbR47akdNi+uleWD8+g6A==}
     dev: false
@@ -5146,7 +5165,7 @@ packages:
       dom-accessibility-api: 0.6.3
       lodash: 4.17.21
       redent: 3.0.0
-      vitest: 1.6.0(@types/node@20.12.10)
+      vitest: 1.6.0(@types/node@20.12.10)(@vitest/ui@1.6.0)
     dev: true
 
   /@testing-library/user-event@14.5.2(@testing-library/dom@9.3.4):
@@ -5825,6 +5844,29 @@ packages:
       - '@swc/helpers'
     dev: true
 
+  /@vitest/coverage-v8@1.6.0(vitest@1.6.0):
+    resolution: {integrity: sha512-KvapcbMY/8GYIG0rlwwOKCVNRc0OL20rrhFkg/CHNzncV03TE2XWvO5w9uZYoxNiMEBacAJt3unSOiZ7svePew==}
+    peerDependencies:
+      vitest: 1.6.0
+    dependencies:
+      '@ampproject/remapping': 2.3.0
+      '@bcoe/v8-coverage': 0.2.3
+      debug: 4.3.4
+      istanbul-lib-coverage: 3.2.2
+      istanbul-lib-report: 3.0.1
+      istanbul-lib-source-maps: 5.0.4
+      istanbul-reports: 3.1.7
+      magic-string: 0.30.10
+      magicast: 0.3.4
+      picocolors: 1.0.0
+      std-env: 3.7.0
+      strip-literal: 2.1.0
+      test-exclude: 6.0.0
+      vitest: 1.6.0(@types/node@20.12.10)(@vitest/ui@1.6.0)
+    transitivePeerDependencies:
+      - supports-color
+    dev: true
+
   /@vitest/expect@1.3.1:
     resolution: {integrity: sha512-xofQFwIzfdmLLlHa6ag0dPV8YsnKOCP1KdAeVVh34vSjN2dcUiXYCD9htu/9eM7t8Xln4v03U9HLxLpPlsXdZw==}
     dependencies:
@@ -5869,6 +5911,21 @@ packages:
       tinyspy: 2.2.1
     dev: true
 
+  /@vitest/ui@1.6.0(vitest@1.6.0):
+    resolution: {integrity: sha512-k3Lyo+ONLOgylctiGovRKy7V4+dIN2yxstX3eY5cWFXH6WP+ooVX79YSyi0GagdTQzLmT43BF27T0s6dOIPBXA==}
+    peerDependencies:
+      vitest: 1.6.0
+    dependencies:
+      '@vitest/utils': 1.6.0
+      fast-glob: 3.3.2
+      fflate: 0.8.2
+      flatted: 3.3.1
+      pathe: 1.1.2
+      picocolors: 1.0.0
+      sirv: 2.0.4
+      vitest: 1.6.0(@types/node@20.12.10)(@vitest/ui@1.6.0)
+    dev: true
+
   /@vitest/utils@1.3.1:
     resolution: {integrity: sha512-d3Waie/299qqRyHTm2DjADeTaNdNSVsnwHPWrs20JMpjh6eiVq7ggggweO8rc4arhf6rRkWuHKwvxGvejUXZZQ==}
     dependencies:
@@ -8521,6 +8578,10 @@ packages:
     resolution: {integrity: sha512-3yurQZ2hD9VISAhJJP9bpYFNQrHHBXE2JxxjY5aLEcDi46RmAzJE2OC9FAde0yis5ElW0jTTzs0zfg/Cca4XqQ==}
     dev: true
 
+  /fflate@0.8.2:
+    resolution: {integrity: sha512-cPJU47OaAoCbg0pBvzsgpTPhmhqI5eJjh/JIu8tPj5q+T7iLvW/JAYUqmE7KOB4R1ZyEhzBaIQpQpardBF5z8A==}
+    dev: true
+
   /file-entry-cache@6.0.1:
     resolution: {integrity: sha512-7Gps/XWymbLk2QLYK4NzpMOrYjMhdIxXuIvy2QBsLE6ljuodKvdkWs/cpyJJ3CVIVpH0Oi1Hvg1ovbMzLdFBBg==}
     engines: {node: ^10.12.0 || >=12.0.0}
@@ -9084,6 +9145,10 @@ packages:
     resolution: {integrity: sha512-mxIDAb9Lsm6DoOJ7xH+5+X4y1LU/4Hi50L9C5sIswK3JzULS4bwk1FvjdBgvYR4bzT4tuUQiC15FE2f5HbLvYw==}
     dev: true
 
+  /html-escaper@2.0.2:
+    resolution: {integrity: sha512-H2iMtd0I4Mt5eYiapRdIDjp+XzelXQ0tFE4JS7YFwFevXXMmOp9myNrUvCg0D6ws8iqkRPBfKHgbwig1SmlLfg==}
+    dev: true
+
   /html-parse-stringify@3.0.1:
     resolution: {integrity: sha512-KknJ50kTInJ7qIScF3jeaFRpMpE8/lfiTdzf/twXyPBLAGrLRTmkz3AdTnKeh40X8k9L2fdYwEp/42WGXIRGcg==}
     dependencies:
@@ -9513,6 +9578,39 @@ packages:
     engines: {node: '>=0.10.0'}
     dev: true
 
+  /istanbul-lib-coverage@3.2.2:
+    resolution: {integrity: sha512-O8dpsF+r0WV/8MNRKfnmrtCWhuKjxrq2w+jpzBL5UZKTi2LeVWnWOmWRxFlesJONmc+wLAGvKQZEOanko0LFTg==}
+    engines: {node: '>=8'}
+    dev: true
+
+  /istanbul-lib-report@3.0.1:
+    resolution: {integrity: sha512-GCfE1mtsHGOELCU8e/Z7YWzpmybrx/+dSTfLrvY8qRmaY6zXTKWn6WQIjaAFw069icm6GVMNkgu0NzI4iPZUNw==}
+    engines: {node: '>=10'}
+    dependencies:
+      istanbul-lib-coverage: 3.2.2
+      make-dir: 4.0.0
+      supports-color: 7.2.0
+    dev: true
+
+  /istanbul-lib-source-maps@5.0.4:
+    resolution: {integrity: sha512-wHOoEsNJTVltaJp8eVkm8w+GVkVNHT2YDYo53YdzQEL2gWm1hBX5cGFR9hQJtuGLebidVX7et3+dmDZrmclduw==}
+    engines: {node: '>=10'}
+    dependencies:
+      '@jridgewell/trace-mapping': 0.3.25
+      debug: 4.3.4
+      istanbul-lib-coverage: 3.2.2
+    transitivePeerDependencies:
+      - supports-color
+    dev: true
+
+  /istanbul-reports@3.1.7:
+    resolution: {integrity: sha512-BewmUXImeuRk2YY0PVbxgKAysvhRPUQE0h5QRM++nVWyubKGV0l8qQ5op8+B2DOmwSe63Jivj0BjkPQVf8fP5g==}
+    engines: {node: '>=8'}
+    dependencies:
+      html-escaper: 2.0.2
+      istanbul-lib-report: 3.0.1
+    dev: true
+
   /iterable-lookahead@1.0.0:
     resolution: {integrity: sha512-hJnEP2Xk4+44DDwJqUQGdXal5VbyeWLaPyDl2AQc242Zr7iqz4DgpQOrEzglWVMGHMDCkguLHEKxd1+rOsmgSQ==}
     engines: {node: '>=4'}
@@ -9912,6 +10010,14 @@ packages:
       '@jridgewell/sourcemap-codec': 1.4.15
     dev: true
 
+  /magicast@0.3.4:
+    resolution: {integrity: sha512-TyDF/Pn36bBji9rWKHlZe+PZb6Mx5V8IHCSxk7X4aljM4e/vyDvZZYwHewdVaqiA0nb3ghfHU/6AUpDxWoER2Q==}
+    dependencies:
+      '@babel/parser': 7.24.5
+      '@babel/types': 7.24.5
+      source-map-js: 1.2.0
+    dev: true
+
   /make-dir@2.1.0:
     resolution: {integrity: sha512-LS9X+dc8KLxXCb8dni79fLIIUA5VyZoyjSMCwTluaXA0o27cCK0bhXkpgw+sTXVpPy/lSO57ilRixqk0vDmtRA==}
     engines: {node: '>=6'}
@@ -9927,6 +10033,13 @@ packages:
       semver: 6.3.1
     dev: true
 
+  /make-dir@4.0.0:
+    resolution: {integrity: sha512-hXdUTZYIVOt1Ex//jAQi+wTZZpUpwBj/0QsOzqegb3rGMMeJiSEu5xLHnYfBrRV4RH2+OCSOO95Is/7x1WJ4bw==}
+    engines: {node: '>=10'}
+    dependencies:
+      semver: 7.6.0
+    dev: true
+
   /map-obj@2.0.0:
     resolution: {integrity: sha512-TzQSV2DiMYgoF5RycneKVUzIa9bQsj/B3tTgsE3dOGqlzHnGIDaC7XBE7grnA+8kZPnfqSGFe95VHc2oc0VFUQ==}
     engines: {node: '>=4'}
@@ -10101,6 +10214,11 @@ packages:
     resolution: {integrity: sha512-iSAJLHYKnX41mKcJKjqvnAN9sf0LMDTXDEvFv+ffuRR9a1MIuXLjMNL6EsnDHSkKLTWNqQQ5uo61P4EbU4NU+Q==}
     dev: false
 
+  /mrmime@2.0.0:
+    resolution: {integrity: sha512-eu38+hdgojoyq63s+yTpN4XMBdt5l8HhMhc4VKLO9KM5caLIBvUm4thi7fFaxyTmCKeNnXZ5pAlBwCUnhA09uw==}
+    engines: {node: '>=10'}
+    dev: true
+
   /ms@2.0.0:
     resolution: {integrity: sha512-Tpp60P6IUJDTuOq/5Z8cdskzJujfwqfOTkrwIwj7IRISpnkJnT6SyJ4PCPnGMoFjC9ddhal5KVIYtAt97ix05A==}
     dev: true
@@ -11766,6 +11884,15 @@ packages:
     engines: {node: '>=14'}
     dev: true
 
+  /sirv@2.0.4:
+    resolution: {integrity: sha512-94Bdh3cC2PKrbgSOUqTiGPWVZeSiXfKOVZNJniWoqrWrRkB1CJzBU3NEbiTsPcYy1lDsANA/THzS+9WBiy5nfQ==}
+    engines: {node: '>= 10'}
+    dependencies:
+      '@polka/url': 1.0.0-next.25
+      mrmime: 2.0.0
+      totalist: 3.0.1
+    dev: true
+
   /sisteransi@1.0.5:
     resolution: {integrity: sha512-bLGGlR1QxBcynn2d5YmDX4MGjlZvy2MRBDRNHLJ8VI6l6+9FUiyTFNJ0IveOSP0bcXgVDPRcfGqA0pjaqUpfVg==}
     dev: true
@@ -12191,6 +12318,15 @@ packages:
       unique-string: 2.0.0
     dev: true
 
+  /test-exclude@6.0.0:
+    resolution: {integrity: sha512-cAGWPIyOHU6zlmg88jwm7VRyXnMN7iV68OGAbYDk/Mh/xC/pzVPlQtY6ngoIH/5/tciuhGfvESU8GrHrcxD56w==}
+    engines: {node: '>=8'}
+    dependencies:
+      '@istanbuljs/schema': 0.1.3
+      glob: 7.2.3
+      minimatch: 3.1.2
+    dev: true
+
   /text-table@0.2.0:
     resolution: {integrity: sha512-N+8UisAXDGk8PFXP4HAzVR9nbfmVJ3zYLAWiTIoqC5v5isinhr+r5uaO8+7r3BMfuNIufIsA7RdpVgacC2cSpw==}
     dev: true
@@ -12264,6 +12400,11 @@ packages:
     engines: {node: '>=0.6'}
     dev: true
 
+  /totalist@3.0.1:
+    resolution: {integrity: sha512-sf4i37nQ2LBx4m3wB74y+ubopq6W/dIzXg0FDGjsYnZHVa1Da8FH853wlL2gtUhg+xJXjfk3kUZS3BRoQeoQBQ==}
+    engines: {node: '>=6'}
+    dev: true
+
   /tr46@0.0.3:
     resolution: {integrity: sha512-N3WMsuqV66lT30CrXNbEjx4GEwlow3v6rr4mCcv6prnfwhS01rkgyFdjPNBYd9br7LpXV1+Emh01fHnq2Gdgrw==}
 
@@ -12837,7 +12978,7 @@ packages:
       fsevents: 2.3.3
     dev: true
 
-  /vitest@1.6.0(@types/node@20.12.10):
+  /vitest@1.6.0(@types/node@20.12.10)(@vitest/ui@1.6.0):
     resolution: {integrity: sha512-H5r/dN06swuFnzNFhq/dnz37bPXnq8xB2xB5JOVk8K09rUtoeNN+LHWkoQ0A/i3hvbUKKcCei9KpbxqHMLhLLA==}
     engines: {node: ^18.0.0 || >=20.0.0}
     hasBin: true
@@ -12867,6 +13008,7 @@ packages:
       '@vitest/runner': 1.6.0
       '@vitest/snapshot': 1.6.0
       '@vitest/spy': 1.6.0
+      '@vitest/ui': 1.6.0(vitest@1.6.0)
       '@vitest/utils': 1.6.0
       acorn-walk: 8.3.2
       chai: 4.4.1

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

@@ -2,6 +2,7 @@
     "accessibility": {
         "about": "About",
         "createIssue": "Create Issue",
+        "submitSupportTicket": "Submit Support Ticket",
         "invokeProgressBar": "Invoke progress bar",
         "menu": "Menu",
         "mode": "Mode",
@@ -146,7 +147,9 @@
         "viewing": "Viewing",
         "viewingDesc": "Review images in a large gallery view",
         "editing": "Editing",
-        "editingDesc": "Edit on the Control Layers canvas"
+        "editingDesc": "Edit on the Control Layers canvas",
+        "enabled": "Enabled",
+        "disabled": "Disabled"
     },
     "controlnet": {
         "controlAdapter_one": "Control Adapter",
@@ -774,10 +777,15 @@
         "cannotConnectOutputToOutput": "Cannot connect output to output",
         "cannotConnectToSelf": "Cannot connect to self",
         "cannotDuplicateConnection": "Cannot create duplicate connections",
+        "cannotMixAndMatchCollectionItemTypes": "Cannot mix and match collection item types",
+        "missingNode": "Missing invocation node",
+        "missingInvocationTemplate": "Missing invocation template",
+        "missingFieldTemplate": "Missing field template",
         "nodePack": "Node pack",
         "collection": "Collection",
-        "collectionFieldType": "{{name}} Collection",
-        "collectionOrScalarFieldType": "{{name}} Collection|Scalar",
+        "singleFieldType": "{{name}} (Single)",
+        "collectionFieldType": "{{name}} (Collection)",
+        "collectionOrScalarFieldType": "{{name}} (Single or Collection)",
         "colorCodeEdges": "Color-Code Edges",
         "colorCodeEdgesHelp": "Color-code edges according to their connected fields",
         "connectionWouldCreateCycle": "Connection would create a cycle",
@@ -879,6 +887,7 @@
         "versionUnknown": " Version Unknown",
         "workflow": "Workflow",
         "graph": "Graph",
+        "noGraph": "No Graph",
         "workflowAuthor": "Author",
         "workflowContact": "Contact",
         "workflowDescription": "Short Description",
@@ -891,7 +900,10 @@
         "zoomInNodes": "Zoom In",
         "zoomOutNodes": "Zoom Out",
         "betaDesc": "This invocation is in beta. Until it is stable, it may have breaking changes during app updates. We plan to support this invocation long-term.",
-        "prototypeDesc": "This invocation is a prototype. It may have breaking changes during app updates and may be removed at any time."
+        "prototypeDesc": "This invocation is a prototype. It may have breaking changes during app updates and may be removed at any time.",
+        "imageAccessError": "Unable to find image {{image_name}}, resetting to default",
+        "boardAccessError": "Unable to find board {{board_id}}, resetting to default",
+        "modelAccessError": "Unable to find model {{key}}, resetting to default"
     },
     "parameters": {
         "aspect": "Aspect",
@@ -946,7 +958,7 @@
                 "controlAdapterIncompatibleBaseModel": "incompatible Control Adapter base model",
                 "controlAdapterNoImageSelected": "no Control Adapter image selected",
                 "controlAdapterImageNotProcessed": "Control Adapter image not processed",
-                "t2iAdapterIncompatibleDimensions": "T2I Adapter requires image dimension to be multiples of 64",
+                "t2iAdapterIncompatibleDimensions": "T2I Adapter requires image dimension to be multiples of {{multiple}}",
                 "ipAdapterNoModelSelected": "no IP adapter selected",
                 "ipAdapterIncompatibleBaseModel": "incompatible IP Adapter base model",
                 "ipAdapterNoImageSelected": "no IP Adapter image selected",
@@ -1064,8 +1076,9 @@
     },
     "toast": {
         "addedToBoard": "Added to board",
-        "baseModelChangedCleared_one": "Base model changed, cleared or disabled {{count}} incompatible submodel",
-        "baseModelChangedCleared_other": "Base model changed, cleared or disabled {{count}} incompatible submodels",
+        "baseModelChanged": "Base Model Changed",
+        "baseModelChangedCleared_one": "Cleared or disabled {{count}} incompatible submodel",
+        "baseModelChangedCleared_other": "Cleared or disabled {{count}} incompatible submodels",
         "canceled": "Processing Canceled",
         "canvasCopiedClipboard": "Canvas Copied to Clipboard",
         "canvasDownloaded": "Canvas Downloaded",
@@ -1086,10 +1099,17 @@
         "metadataLoadFailed": "Failed to load metadata",
         "modelAddedSimple": "Model Added to Queue",
         "modelImportCanceled": "Model Import Canceled",
+        "outOfMemoryError": "Out of Memory Error",
+        "outOfMemoryErrorDesc": "Your current generation settings exceed system capacity. Please adjust your settings and try again.",
         "parameters": "Parameters",
-        "parameterNotSet": "{{parameter}} not set",
-        "parameterSet": "{{parameter}} set",
-        "parametersNotSet": "Parameters Not Set",
+        "parameterSet": "Parameter Recalled",
+        "parameterSetDesc": "Recalled {{parameter}}",
+        "parameterNotSet": "Parameter Recalled",
+        "parameterNotSetDesc": "Unable to recall {{parameter}}",
+        "parameterNotSetDescWithMessage": "Unable to recall {{parameter}}: {{message}}",
+        "parametersSet": "Parameters Recalled",
+        "parametersNotSet": "Parameters Not Recalled",
+        "errorCopied": "Error Copied",
         "problemCopyingCanvas": "Problem Copying Canvas",
         "problemCopyingCanvasDesc": "Unable to export base layer",
         "problemCopyingImage": "Unable to Copy Image",
@@ -1109,11 +1129,13 @@
         "sentToImageToImage": "Sent To Image To Image",
         "sentToUnifiedCanvas": "Sent to Unified Canvas",
         "serverError": "Server Error",
+        "sessionRef": "Session: {{sessionId}}",
         "setAsCanvasInitialImage": "Set as canvas initial image",
         "setCanvasInitialImage": "Set canvas initial image",
         "setControlImage": "Set as control image",
         "setInitialImage": "Set as initial image",
         "setNodeField": "Set as node field",
+        "somethingWentWrong": "Something Went Wrong",
         "uploadFailed": "Upload failed",
         "uploadFailedInvalidUploadDesc": "Must be single PNG or JPEG image",
         "uploadInitialImage": "Upload Initial Image",
@@ -1553,7 +1575,6 @@
         "controlLayers": "Control Layers",
         "globalMaskOpacity": "Global Mask Opacity",
         "autoNegative": "Auto Negative",
-        "toggleVisibility": "Toggle Layer Visibility",
         "deletePrompt": "Delete Prompt",
         "resetRegion": "Reset Region",
         "debugLayers": "Debug Layers",

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

@@ -382,7 +382,7 @@
         "canvasMerged": "Lienzo consolidado",
         "sentToImageToImage": "Enviar hacia Imagen a Imagen",
         "sentToUnifiedCanvas": "Enviar hacia Lienzo Consolidado",
-        "parametersNotSet": "Parámetros no establecidos",
+        "parametersNotSet": "Parámetros no recuperados",
         "metadataLoadFailed": "Error al cargar metadatos",
         "serverError": "Error en el servidor",
         "canceled": "Procesando la cancelación",
@@ -390,7 +390,8 @@
         "uploadFailedInvalidUploadDesc": "Debe ser una sola imagen PNG o JPEG",
         "parameterSet": "Conjunto de parámetros",
         "parameterNotSet": "Parámetro no configurado",
-        "problemCopyingImage": "No se puede copiar la imagen"
+        "problemCopyingImage": "No se puede copiar la imagen",
+        "errorCopied": "Error al copiar"
     },
     "tooltip": {
         "feature": {

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

@@ -524,7 +524,20 @@
             "missingNodeTemplate": "Modello di nodo mancante",
             "missingInputForField": "{{nodeLabel}} -> {{fieldLabel}} ingresso mancante",
             "missingFieldTemplate": "Modello di campo mancante",
-            "imageNotProcessedForControlAdapter": "L'immagine dell'adattatore di controllo #{{number}} non è stata elaborata"
+            "imageNotProcessedForControlAdapter": "L'immagine dell'adattatore di controllo #{{number}} non è stata elaborata",
+            "layer": {
+                "initialImageNoImageSelected": "Nessuna immagine iniziale selezionata",
+                "t2iAdapterIncompatibleDimensions": "L'adattatore T2I richiede che la dimensione dell'immagine sia un multiplo di {{multiple}}",
+                "controlAdapterNoModelSelected": "Nessun modello di Adattatore di Controllo selezionato",
+                "controlAdapterIncompatibleBaseModel": "Il modello base dell'adattatore di controllo non è compatibile",
+                "controlAdapterNoImageSelected": "Nessuna immagine dell'adattatore di controllo selezionata",
+                "controlAdapterImageNotProcessed": "Immagine dell'adattatore di controllo non elaborata",
+                "ipAdapterNoModelSelected": "Nessun adattatore IP selezionato",
+                "ipAdapterIncompatibleBaseModel": "Il modello base dell'adattatore IP non è compatibile",
+                "ipAdapterNoImageSelected": "Nessuna immagine dell'adattatore IP selezionata",
+                "rgNoPromptsOrIPAdapters": "Nessun prompt o adattatore IP",
+                "rgNoRegion": "Nessuna regione selezionata"
+            }
         },
         "useCpuNoise": "Usa la CPU per generare rumore",
         "iterations": "Iterazioni",
@@ -824,8 +837,8 @@
         "unableToUpdateNodes_other": "Impossibile aggiornare {{count}} nodi",
         "addLinearView": "Aggiungi alla vista Lineare",
         "unknownErrorValidatingWorkflow": "Errore sconosciuto durante la convalida del flusso di lavoro",
-        "collectionFieldType": "{{name}} Raccolta",
-        "collectionOrScalarFieldType": "{{name}} Raccolta|Scalare",
+        "collectionFieldType": "{{name}} (Raccolta)",
+        "collectionOrScalarFieldType": "{{name}} (Singola o Raccolta)",
         "nodeVersion": "Versione Nodo",
         "inputFieldTypeParseError": "Impossibile analizzare il tipo di campo di input {{node}}.{{field}} ({{message}})",
         "unsupportedArrayItemType": "Tipo di elemento dell'array non supportato \"{{type}}\"",
@@ -863,7 +876,13 @@
         "edit": "Modifica",
         "graph": "Grafico",
         "showEdgeLabelsHelp": "Mostra etichette sui collegamenti, che indicano i nodi collegati",
-        "showEdgeLabels": "Mostra le etichette del collegamento"
+        "showEdgeLabels": "Mostra le etichette del collegamento",
+        "cannotMixAndMatchCollectionItemTypes": "Impossibile combinare e abbinare i tipi di elementi della raccolta",
+        "noGraph": "Nessun grafico",
+        "missingNode": "Nodo di invocazione mancante",
+        "missingInvocationTemplate": "Modello di invocazione mancante",
+        "missingFieldTemplate": "Modello di campo mancante",
+        "singleFieldType": "{{name}} (Singola)"
     },
     "boards": {
         "autoAddBoard": "Aggiungi automaticamente bacheca",
@@ -1034,7 +1053,16 @@
         "graphFailedToQueue": "Impossibile mettere in coda il grafico",
         "batchFieldValues": "Valori Campi Lotto",
         "time": "Tempo",
-        "openQueue": "Apri coda"
+        "openQueue": "Apri coda",
+        "iterations_one": "Iterazione",
+        "iterations_many": "Iterazioni",
+        "iterations_other": "Iterazioni",
+        "prompts_one": "Prompt",
+        "prompts_many": "Prompt",
+        "prompts_other": "Prompt",
+        "generations_one": "Generazione",
+        "generations_many": "Generazioni",
+        "generations_other": "Generazioni"
     },
     "models": {
         "noMatchingModels": "Nessun modello corrispondente",
@@ -1563,7 +1591,6 @@
         "brushSize": "Dimensioni del pennello",
         "globalMaskOpacity": "Opacità globale della maschera",
         "autoNegative": "Auto Negativo",
-        "toggleVisibility": "Attiva/disattiva la visibilità dei livelli",
         "deletePrompt": "Cancella il prompt",
         "debugLayers": "Debug dei Livelli",
         "rectangle": "Rettangolo",

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

@@ -6,7 +6,7 @@
         "settingsLabel": "Instellingen",
         "img2img": "Afbeelding naar afbeelding",
         "unifiedCanvas": "Centraal canvas",
-        "nodes": "Werkstroom-editor",
+        "nodes": "Werkstromen",
         "upload": "Upload",
         "load": "Laad",
         "statusDisconnected": "Niet verbonden",
@@ -34,7 +34,60 @@
         "controlNet": "ControlNet",
         "imageFailedToLoad": "Kan afbeelding niet laden",
         "learnMore": "Meer informatie",
-        "advanced": "Uitgebreid"
+        "advanced": "Uitgebreid",
+        "file": "Bestand",
+        "installed": "Geïnstalleerd",
+        "notInstalled": "Niet $t(common.installed)",
+        "simple": "Eenvoudig",
+        "somethingWentWrong": "Er ging iets mis",
+        "add": "Voeg toe",
+        "checkpoint": "Checkpoint",
+        "details": "Details",
+        "outputs": "Uitvoeren",
+        "save": "Bewaar",
+        "nextPage": "Volgende pagina",
+        "blue": "Blauw",
+        "alpha": "Alfa",
+        "red": "Rood",
+        "editor": "Editor",
+        "folder": "Map",
+        "format": "structuur",
+        "goTo": "Ga naar",
+        "template": "Sjabloon",
+        "input": "Invoer",
+        "loglevel": "Logboekniveau",
+        "safetensors": "Safetensors",
+        "saveAs": "Bewaar als",
+        "created": "Gemaakt",
+        "green": "Groen",
+        "tab": "Tab",
+        "positivePrompt": "Positieve prompt",
+        "negativePrompt": "Negatieve prompt",
+        "selected": "Geselecteerd",
+        "orderBy": "Sorteer op",
+        "prevPage": "Vorige pagina",
+        "beta": "Bèta",
+        "copyError": "$t(gallery.copy) Fout",
+        "toResolve": "Op te lossen",
+        "aboutDesc": "Gebruik je Invoke voor het werk? Kijk dan naar:",
+        "aboutHeading": "Creatieve macht voor jou",
+        "copy": "Kopieer",
+        "data": "Gegevens",
+        "or": "of",
+        "updated": "Bijgewerkt",
+        "outpaint": "outpainten",
+        "viewing": "Bekijken",
+        "viewingDesc": "Beoordeel afbeelding in een grote galerijweergave",
+        "editing": "Bewerken",
+        "editingDesc": "Bewerk op het canvas Stuurlagen",
+        "ai": "ai",
+        "inpaint": "inpainten",
+        "unknown": "Onbekend",
+        "delete": "Verwijder",
+        "direction": "Richting",
+        "error": "Fout",
+        "localSystem": "Lokaal systeem",
+        "unknownError": "Onbekende fout"
     },
     "gallery": {
         "galleryImageSize": "Afbeeldingsgrootte",
@@ -310,10 +363,41 @@
         "modelSyncFailed": "Synchronisatie modellen mislukt",
         "modelDeleteFailed": "Model kon niet verwijderd worden",
         "convertingModelBegin": "Model aan het converteren. Even geduld.",
-        "predictionType": "Soort voorspelling (voor Stable Diffusion 2.x-modellen en incidentele Stable Diffusion 1.x-modellen)",
+        "predictionType": "Soort voorspelling",
         "advanced": "Uitgebreid",
         "modelType": "Soort model",
-        "vaePrecision": "Nauwkeurigheid VAE"
+        "vaePrecision": "Nauwkeurigheid VAE",
+        "loraTriggerPhrases": "LoRA-triggerzinnen",
+        "urlOrLocalPathHelper": "URL's zouden moeten wijzen naar een los bestand. Lokale paden kunnen wijzen naar een los bestand of map voor een individueel Diffusers-model.",
+        "modelName": "Modelnaam",
+        "path": "Pad",
+        "triggerPhrases": "Triggerzinnen",
+        "typePhraseHere": "Typ zin hier in",
+        "useDefaultSettings": "Gebruik standaardinstellingen",
+        "modelImageDeleteFailed": "Fout bij verwijderen modelafbeelding",
+        "modelImageUpdated": "Modelafbeelding bijgewerkt",
+        "modelImageUpdateFailed": "Fout bij bijwerken modelafbeelding",
+        "noMatchingModels": "Geen overeenkomende modellen",
+        "scanPlaceholder": "Pad naar een lokale map",
+        "noModelsInstalled": "Geen modellen geïnstalleerd",
+        "noModelsInstalledDesc1": "Installeer modellen met de",
+        "noModelSelected": "Geen model geselecteerd",
+        "starterModels": "Beginnermodellen",
+        "textualInversions": "Tekstuele omkeringen",
+        "upcastAttention": "Upcast-aandacht",
+        "uploadImage": "Upload afbeelding",
+        "mainModelTriggerPhrases": "Triggerzinnen hoofdmodel",
+        "urlOrLocalPath": "URL of lokaal pad",
+        "scanFolderHelper": "De map zal recursief worden ingelezen voor modellen. Dit kan enige tijd in beslag nemen voor erg grote mappen.",
+        "simpleModelPlaceholder": "URL of pad naar een lokaal pad of Diffusers-map",
+        "modelSettings": "Modelinstellingen",
+        "pathToConfig": "Pad naar configuratie",
+        "prune": "Snoei",
+        "pruneTooltip": "Snoei voltooide importeringen uit wachtrij",
+        "repoVariant": "Repovariant",
+        "scanFolder": "Lees map in",
+        "scanResults": "Resultaten inlezen",
+        "source": "Bron"
     },
     "parameters": {
         "images": "Afbeeldingen",
@@ -353,13 +437,13 @@
         "copyImage": "Kopieer afbeelding",
         "denoisingStrength": "Sterkte ontruisen",
         "scheduler": "Planner",
-        "seamlessXAxis": "X-as",
-        "seamlessYAxis": "Y-as",
+        "seamlessXAxis": "Naadloze tegels in x-as",
+        "seamlessYAxis": "Naadloze tegels in y-as",
         "clipSkip": "Overslaan CLIP",
         "negativePromptPlaceholder": "Negatieve prompt",
         "controlNetControlMode": "Aansturingsmodus",
         "positivePromptPlaceholder": "Positieve prompt",
-        "maskBlur": "Vervaag",
+        "maskBlur": "Vervaging van masker",
         "invoke": {
             "noNodesInGraph": "Geen knooppunten in graaf",
             "noModelSelected": "Geen model ingesteld",
@@ -369,11 +453,25 @@
             "missingInputForField": "{{nodeLabel}} -> {{fieldLabel}} invoer ontbreekt",
             "noControlImageForControlAdapter": "Controle-adapter #{{number}} heeft geen controle-afbeelding",
             "noModelForControlAdapter": "Control-adapter #{{number}} heeft geen model ingesteld staan.",
-            "incompatibleBaseModelForControlAdapter": "Model van controle-adapter #{{number}} is ongeldig in combinatie met het hoofdmodel.",
+            "incompatibleBaseModelForControlAdapter": "Model van controle-adapter #{{number}} is niet compatibel met het hoofdmodel.",
             "systemDisconnected": "Systeem is niet verbonden",
             "missingNodeTemplate": "Knooppuntsjabloon ontbreekt",
             "missingFieldTemplate": "Veldsjabloon ontbreekt",
-            "addingImagesTo": "Bezig met toevoegen van afbeeldingen aan"
+            "addingImagesTo": "Bezig met toevoegen van afbeeldingen aan",
+            "layer": {
+                "initialImageNoImageSelected": "geen initiële afbeelding geselecteerd",
+                "controlAdapterNoModelSelected": "geen controle-adaptermodel geselecteerd",
+                "controlAdapterIncompatibleBaseModel": "niet-compatibele basismodel voor controle-adapter",
+                "controlAdapterNoImageSelected": "geen afbeelding voor controle-adapter geselecteerd",
+                "controlAdapterImageNotProcessed": "Afbeelding voor controle-adapter niet verwerkt",
+                "ipAdapterIncompatibleBaseModel": "niet-compatibele basismodel voor IP-adapter",
+                "ipAdapterNoImageSelected": "geen afbeelding voor IP-adapter geselecteerd",
+                "rgNoRegion": "geen gebied geselecteerd",
+                "rgNoPromptsOrIPAdapters": "geen tekstprompts of IP-adapters",
+                "t2iAdapterIncompatibleDimensions": "T2I-adapter vereist een afbeelding met afmetingen met een veelvoud van 64",
+                "ipAdapterNoModelSelected": "geen IP-adapter geselecteerd"
+            },
+            "imageNotProcessedForControlAdapter": "De afbeelding van controle-adapter #{{number}} is niet verwerkt"
         },
         "isAllowedToUpscale": {
             "useX2Model": "Afbeelding is te groot om te vergroten met het x4-model. Gebruik hiervoor het x2-model",
@@ -383,7 +481,26 @@
         "useCpuNoise": "Gebruik CPU-ruis",
         "imageActions": "Afbeeldingshandeling",
         "iterations": "Iteraties",
-        "coherenceMode": "Modus"
+        "coherenceMode": "Modus",
+        "infillColorValue": "Vulkleur",
+        "remixImage": "Meng afbeelding opnieuw",
+        "setToOptimalSize": "Optimaliseer grootte voor het model",
+        "setToOptimalSizeTooSmall": "$t(parameters.setToOptimalSize) (is mogelijk te klein)",
+        "aspect": "Beeldverhouding",
+        "infillMosaicTileWidth": "Breedte tegel",
+        "setToOptimalSizeTooLarge": "$t(parameters.setToOptimalSize) (is mogelijk te groot)",
+        "lockAspectRatio": "Zet beeldverhouding vast",
+        "infillMosaicTileHeight": "Hoogte tegel",
+        "globalNegativePromptPlaceholder": "Globale negatieve prompt",
+        "globalPositivePromptPlaceholder": "Globale positieve prompt",
+        "useSize": "Gebruik grootte",
+        "swapDimensions": "Wissel afmetingen om",
+        "globalSettings": "Globale instellingen",
+        "coherenceEdgeSize": "Randgrootte",
+        "coherenceMinDenoise": "Min. ontruising",
+        "infillMosaicMinColor": "Min. kleur",
+        "infillMosaicMaxColor": "Max. kleur",
+        "cfgRescaleMultiplier": "Vermenigvuldiger voor CFG-herschaling"
     },
     "settings": {
         "models": "Modellen",
@@ -410,7 +527,12 @@
         "intermediatesCleared_one": "{{count}} tussentijdse afbeelding gewist",
         "intermediatesCleared_other": "{{count}} tussentijdse afbeeldingen gewist",
         "clearIntermediatesDesc1": "Als je tussentijdse afbeeldingen wist, dan wordt de staat hersteld van je canvas en van ControlNet.",
-        "intermediatesClearedFailed": "Fout bij wissen van tussentijdse afbeeldingen"
+        "intermediatesClearedFailed": "Fout bij wissen van tussentijdse afbeeldingen",
+        "clearIntermediatesDisabled": "Wachtrij moet leeg zijn om tussentijdse afbeeldingen te kunnen leegmaken",
+        "enableInformationalPopovers": "Schakel informatieve hulpballonnen in",
+        "enableInvisibleWatermark": "Schakel onzichtbaar watermerk in",
+        "enableNSFWChecker": "Schakel NSFW-controle in",
+        "reloadingIn": "Opnieuw laden na"
     },
     "toast": {
         "uploadFailed": "Upload mislukt",
@@ -425,8 +547,8 @@
         "connected": "Verbonden met server",
         "canceled": "Verwerking geannuleerd",
         "uploadFailedInvalidUploadDesc": "Moet een enkele PNG- of JPEG-afbeelding zijn",
-        "parameterNotSet": "Parameter niet ingesteld",
-        "parameterSet": "Instellen parameters",
+        "parameterNotSet": "{{parameter}} niet ingesteld",
+        "parameterSet": "{{parameter}} ingesteld",
         "problemCopyingImage": "Kan Afbeelding Niet Kopiëren",
         "baseModelChangedCleared_one": "Basismodel is gewijzigd: {{count}} niet-compatibel submodel weggehaald of uitgeschakeld",
         "baseModelChangedCleared_other": "Basismodel is gewijzigd: {{count}} niet-compatibele submodellen weggehaald of uitgeschakeld",
@@ -443,11 +565,11 @@
         "maskSavedAssets": "Masker bewaard in Assets",
         "problemDownloadingCanvas": "Fout bij downloaden van canvas",
         "problemMergingCanvas": "Fout bij samenvoegen canvas",
-        "setCanvasInitialImage": "Ingesteld als initiële canvasafbeelding",
+        "setCanvasInitialImage": "Initiële canvasafbeelding ingesteld",
         "imageUploaded": "Afbeelding geüpload",
         "addedToBoard": "Toegevoegd aan bord",
         "workflowLoaded": "Werkstroom geladen",
-        "modelAddedSimple": "Model toegevoegd",
+        "modelAddedSimple": "Model toegevoegd aan wachtrij",
         "problemImportingMaskDesc": "Kan masker niet exporteren",
         "problemCopyingCanvas": "Fout bij kopiëren canvas",
         "problemSavingCanvas": "Fout bij bewaren canvas",
@@ -459,7 +581,18 @@
         "maskSentControlnetAssets": "Masker gestuurd naar ControlNet en Assets",
         "canvasSavedGallery": "Canvas bewaard in galerij",
         "imageUploadFailed": "Fout bij uploaden afbeelding",
-        "problemImportingMask": "Fout bij importeren masker"
+        "problemImportingMask": "Fout bij importeren masker",
+        "workflowDeleted": "Werkstroom verwijderd",
+        "invalidUpload": "Ongeldige upload",
+        "uploadInitialImage": "Initiële afbeelding uploaden",
+        "setAsCanvasInitialImage": "Ingesteld als initiële afbeelding voor canvas",
+        "problemRetrievingWorkflow": "Fout bij ophalen van werkstroom",
+        "parameters": "Parameters",
+        "modelImportCanceled": "Importeren model geannuleerd",
+        "problemDeletingWorkflow": "Fout bij verwijderen van werkstroom",
+        "prunedQueue": "Wachtrij gesnoeid",
+        "problemDownloadingImage": "Fout bij downloaden afbeelding",
+        "resetInitialImage": "Initiële afbeelding hersteld"
     },
     "tooltip": {
         "feature": {
@@ -533,7 +666,11 @@
         "showOptionsPanel": "Toon zijscherm",
         "menu": "Menu",
         "showGalleryPanel": "Toon deelscherm Galerij",
-        "loadMore": "Laad meer"
+        "loadMore": "Laad meer",
+        "about": "Over",
+        "mode": "Modus",
+        "resetUI": "$t(accessibility.reset) UI",
+        "createIssue": "Maak probleem aan"
     },
     "nodes": {
         "zoomOutNodes": "Uitzoomen",
@@ -547,7 +684,7 @@
         "loadWorkflow": "Laad werkstroom",
         "downloadWorkflow": "Download JSON van werkstroom",
         "scheduler": "Planner",
-        "missingTemplate": "Ontbrekende sjabloon",
+        "missingTemplate": "Ongeldig knooppunt: knooppunt {{node}} van het soort {{type}} heeft een ontbrekend sjabloon (niet geïnstalleerd?)",
         "workflowDescription": "Korte beschrijving",
         "versionUnknown": " Versie onbekend",
         "noNodeSelected": "Geen knooppunt gekozen",
@@ -563,7 +700,7 @@
         "integer": "Geheel getal",
         "nodeTemplate": "Sjabloon knooppunt",
         "nodeOpacity": "Dekking knooppunt",
-        "unableToLoadWorkflow": "Kan werkstroom niet valideren",
+        "unableToLoadWorkflow": "Fout bij laden werkstroom",
         "snapToGrid": "Lijn uit op raster",
         "noFieldsLinearview": "Geen velden toegevoegd aan lineaire weergave",
         "nodeSearch": "Zoek naar knooppunten",
@@ -614,11 +751,56 @@
         "unknownField": "Onbekend veld",
         "colorCodeEdges": "Kleurgecodeerde randen",
         "unknownNode": "Onbekend knooppunt",
-        "mismatchedVersion": "Heeft niet-overeenkomende versie",
+        "mismatchedVersion": "Ongeldig knooppunt: knooppunt {{node}} van het soort {{type}} heeft een niet-overeenkomende versie (probeer het bij te werken?)",
         "addNodeToolTip": "Voeg knooppunt toe (Shift+A, spatie)",
         "loadingNodes": "Bezig met laden van knooppunten...",
         "snapToGridHelp": "Lijn knooppunten uit op raster bij verplaatsing",
-        "workflowSettings": "Instellingen werkstroomeditor"
+        "workflowSettings": "Instellingen werkstroomeditor",
+        "addLinearView": "Voeg toe aan lineaire weergave",
+        "nodePack": "Knooppuntpakket",
+        "unknownInput": "Onbekende invoer: {{name}}",
+        "sourceNodeFieldDoesNotExist": "Ongeldige rand: bron-/uitvoerveld {{node}}.{{field}} bestaat niet",
+        "collectionFieldType": "Verzameling {{name}}",
+        "deletedInvalidEdge": "Ongeldige hoek {{source}} -> {{target}} verwijderd",
+        "graph": "Grafiek",
+        "targetNodeDoesNotExist": "Ongeldige rand: doel-/invoerknooppunt {{node}} bestaat niet",
+        "resetToDefaultValue": "Herstel naar standaardwaarden",
+        "editMode": "Bewerk in Werkstroom-editor",
+        "showEdgeLabels": "Toon randlabels",
+        "showEdgeLabelsHelp": "Toon labels aan randen, waarmee de verbonden knooppunten mee worden aangegeven",
+        "clearWorkflowDesc2": "Je huidige werkstroom heeft niet-bewaarde wijzigingen.",
+        "unableToParseFieldType": "fout bij bepalen soort veld",
+        "sourceNodeDoesNotExist": "Ongeldige rand: bron-/uitvoerknooppunt {{node}} bestaat niet",
+        "unsupportedArrayItemType": "niet-ondersteunde soort van het array-onderdeel \"{{type}}\"",
+        "targetNodeFieldDoesNotExist": "Ongeldige rand: doel-/invoerveld {{node}}.{{field}} bestaat niet",
+        "reorderLinearView": "Herorden lineaire weergave",
+        "newWorkflowDesc": "Een nieuwe werkstroom aanmaken?",
+        "collectionOrScalarFieldType": "Verzameling|scalair {{name}}",
+        "newWorkflow": "Nieuwe werkstroom",
+        "unknownErrorValidatingWorkflow": "Onbekende fout bij valideren werkstroom",
+        "unsupportedAnyOfLength": "te veel union-leden ({{count}})",
+        "unknownOutput": "Onbekende uitvoer: {{name}}",
+        "viewMode": "Gebruik in lineaire weergave",
+        "unableToExtractSchemaNameFromRef": "fout bij het extraheren van de schemanaam via de ref",
+        "unsupportedMismatchedUnion": "niet-overeenkomende soort CollectionOrScalar met basissoorten {{firstType}} en {{secondType}}",
+        "unknownNodeType": "Onbekend soort knooppunt",
+        "edit": "Bewerk",
+        "updateAllNodes": "Werk knooppunten bij",
+        "allNodesUpdated": "Alle knooppunten bijgewerkt",
+        "nodeVersion": "Knooppuntversie",
+        "newWorkflowDesc2": "Je huidige werkstroom heeft niet-bewaarde wijzigingen.",
+        "clearWorkflow": "Maak werkstroom leeg",
+        "clearWorkflowDesc": "Deze werkstroom leegmaken en met een nieuwe beginnen?",
+        "inputFieldTypeParseError": "Fout bij bepalen van het soort invoerveld {{node}}.{{field}} ({{message}})",
+        "outputFieldTypeParseError": "Fout bij het bepalen van het soort uitvoerveld {{node}}.{{field}} ({{message}})",
+        "unableToExtractEnumOptions": "fout bij extraheren enumeratie-opties",
+        "unknownFieldType": "Soort $t(nodes.unknownField): {{type}}",
+        "unableToGetWorkflowVersion": "Fout bij ophalen schemaversie van werkstroom",
+        "betaDesc": "Deze uitvoering is in bèta. Totdat deze stabiel is kunnen er wijzigingen voorkomen gedurende app-updates die zaken kapotmaken. We zijn van plan om deze uitvoering op lange termijn te gaan ondersteunen.",
+        "prototypeDesc": "Deze uitvoering is een prototype. Er kunnen wijzigingen voorkomen gedurende app-updates die zaken kapotmaken. Deze kunnen op een willekeurig moment verwijderd worden.",
+        "noFieldsViewMode": "Deze werkstroom heeft geen geselecteerde velden om te tonen. Bekijk de volledige werkstroom om de waarden te configureren.",
+        "unableToUpdateNodes_one": "Fout bij bijwerken van {{count}} knooppunt",
+        "unableToUpdateNodes_other": "Fout bij bijwerken van {{count}} knooppunten"
     },
     "controlnet": {
         "amult": "a_mult",
@@ -691,9 +873,28 @@
         "canny": "Canny",
         "depthZoeDescription": "Genereer diepteblad via Zoe",
         "hedDescription": "Herkenning van holistisch-geneste randen",
-        "setControlImageDimensions": "Stel afmetingen controle-afbeelding in op B/H",
+        "setControlImageDimensions": "Kopieer grootte naar B/H (optimaliseer voor model)",
         "scribble": "Krabbel",
-        "maxFaces": "Max. gezichten"
+        "maxFaces": "Max. gezichten",
+        "dwOpenpose": "DW Openpose",
+        "depthAnything": "Depth Anything",
+        "base": "Basis",
+        "hands": "Handen",
+        "selectCLIPVisionModel": "Selecteer een CLIP Vision-model",
+        "modelSize": "Modelgrootte",
+        "small": "Klein",
+        "large": "Groot",
+        "resizeSimple": "Wijzig grootte (eenvoudig)",
+        "beginEndStepPercentShort": "Begin-/eind-%",
+        "depthAnythingDescription": "Genereren dieptekaart d.m.v. de techniek Depth Anything",
+        "face": "Gezicht",
+        "body": "Lichaam",
+        "dwOpenposeDescription": "Schatting menselijke pose d.m.v. DW Openpose",
+        "ipAdapterMethod": "Methode",
+        "full": "Volledig",
+        "style": "Alleen stijl",
+        "composition": "Alleen samenstelling",
+        "setControlImageDimensionsForce": "Kopieer grootte naar B/H (negeer model)"
     },
     "dynamicPrompts": {
         "seedBehaviour": {
@@ -706,7 +907,10 @@
         "maxPrompts": "Max. prompts",
         "promptsWithCount_one": "{{count}} prompt",
         "promptsWithCount_other": "{{count}} prompts",
-        "dynamicPrompts": "Dynamische prompts"
+        "dynamicPrompts": "Dynamische prompts",
+        "showDynamicPrompts": "Toon dynamische prompts",
+        "loading": "Genereren van dynamische prompts...",
+        "promptsPreview": "Voorvertoning prompts"
     },
     "popovers": {
         "noiseUseCPU": {
@@ -719,7 +923,7 @@
         },
         "paramScheduler": {
             "paragraphs": [
-                "De planner bepaalt hoe ruis per iteratie wordt toegevoegd aan een afbeelding of hoe een monster wordt bijgewerkt op basis van de uitvoer van een model."
+                "De planner gebruikt gedurende het genereringsproces."
             ],
             "heading": "Planner"
         },
@@ -806,8 +1010,8 @@
         },
         "clipSkip": {
             "paragraphs": [
-                "Kies hoeveel CLIP-modellagen je wilt overslaan.",
-                "Bepaalde modellen werken beter met bepaalde Overslaan CLIP-instellingen."
+                "Aantal over te slaan CLIP-modellagen.",
+                "Bepaalde modellen zijn beter geschikt met bepaalde Overslaan CLIP-instellingen."
             ],
             "heading": "Overslaan CLIP"
         },
@@ -991,17 +1195,26 @@
         "denoisingStrength": "Sterkte ontruising",
         "refinermodel": "Verfijningsmodel",
         "posAestheticScore": "Positieve esthetische score",
-        "concatPromptStyle": "Plak prompt- en stijltekst aan elkaar",
+        "concatPromptStyle": "Koppelen van prompt en stijl",
         "loading": "Bezig met laden...",
         "steps": "Stappen",
-        "posStylePrompt": "Positieve-stijlprompt"
+        "posStylePrompt": "Positieve-stijlprompt",
+        "freePromptStyle": "Handmatige stijlprompt",
+        "refinerSteps": "Aantal stappen verfijner"
     },
     "models": {
         "noMatchingModels": "Geen overeenkomend modellen",
         "loading": "bezig met laden",
         "noMatchingLoRAs": "Geen overeenkomende LoRA's",
         "noModelsAvailable": "Geen modellen beschikbaar",
-        "selectModel": "Kies een model"
+        "selectModel": "Kies een model",
+        "noLoRAsInstalled": "Geen LoRA's geïnstalleerd",
+        "noRefinerModelsInstalled": "Geen SDXL-verfijningsmodellen geïnstalleerd",
+        "defaultVAE": "Standaard-VAE",
+        "lora": "LoRA",
+        "esrganModel": "ESRGAN-model",
+        "addLora": "Voeg LoRA toe",
+        "concepts": "Concepten"
     },
     "boards": {
         "autoAddBoard": "Voeg automatisch bord toe",
@@ -1019,7 +1232,13 @@
         "downloadBoard": "Download bord",
         "changeBoard": "Wijzig bord",
         "loading": "Bezig met laden...",
-        "clearSearch": "Maak zoekopdracht leeg"
+        "clearSearch": "Maak zoekopdracht leeg",
+        "deleteBoard": "Verwijder bord",
+        "deleteBoardAndImages": "Verwijder bord en afbeeldingen",
+        "deleteBoardOnly": "Verwijder alleen bord",
+        "deletedBoardsCannotbeRestored": "Verwijderde borden kunnen niet worden hersteld",
+        "movingImagesToBoard_one": "Verplaatsen van {{count}} afbeelding naar bord:",
+        "movingImagesToBoard_other": "Verplaatsen van {{count}} afbeeldingen naar bord:"
     },
     "invocationCache": {
         "disable": "Schakel uit",
@@ -1036,5 +1255,39 @@
         "clear": "Wis",
         "maxCacheSize": "Max. grootte cache",
         "cacheSize": "Grootte cache"
+    },
+    "accordions": {
+        "generation": {
+            "title": "Genereren"
+        },
+        "image": {
+            "title": "Afbeelding"
+        },
+        "advanced": {
+            "title": "Geavanceerd",
+            "options": "$t(accordions.advanced.title) Opties"
+        },
+        "control": {
+            "title": "Besturing"
+        },
+        "compositing": {
+            "title": "Samenstellen",
+            "coherenceTab": "Coherentiefase",
+            "infillTab": "Invullen"
+        }
+    },
+    "hrf": {
+        "upscaleMethod": "Opschaalmethode",
+        "metadata": {
+            "strength": "Sterkte oplossing voor hoge resolutie",
+            "method": "Methode oplossing voor hoge resolutie",
+            "enabled": "Oplossing voor hoge resolutie ingeschakeld"
+        },
+        "hrf": "Oplossing voor hoge resolutie",
+        "enableHrf": "Schakel oplossing in voor hoge resolutie"
+    },
+    "prompt": {
+        "addPromptTrigger": "Voeg prompttrigger toe",
+        "compatibleEmbeddings": "Compatibele embeddings"
     }
 }

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

@@ -1594,7 +1594,6 @@
         "deleteAll": "Удалить всё",
         "addLayer": "Добавить слой",
         "moveToFront": "На передний план",
-        "toggleVisibility": "Переключить видимость слоя",
         "addPositivePrompt": "Добавить $t(common.positivePrompt)",
         "addIPAdapter": "Добавить $t(common.ipAdapter)",
         "regionalGuidanceLayer": "$t(controlLayers.regionalGuidance) $t(unifiedCanvas.layer)",

invokeai/frontend/web/scripts/typegen.js

@@ -1,3 +1,4 @@
+/* eslint-disable no-console */
 import fs from 'node:fs';
 
 import openapiTS from 'openapi-typescript';

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

@@ -21,10 +21,10 @@ import i18n from 'i18n';
 import { size } from 'lodash-es';
 import { memo, useCallback, useEffect } from 'react';
 import { ErrorBoundary } from 'react-error-boundary';
+import { useGetOpenAPISchemaQuery } from 'services/api/endpoints/appInfo';
 
 import AppErrorBoundaryFallback from './AppErrorBoundaryFallback';
 import PreselectedImage from './PreselectedImage';
-import Toaster from './Toaster';
 
 const DEFAULT_CONFIG = {};
 
@@ -46,6 +46,7 @@ const App = ({ config = DEFAULT_CONFIG, selectedImage }: Props) => {
   useSocketIO();
   useGlobalModifiersInit();
   useGlobalHotkeys();
+  useGetOpenAPISchemaQuery();
 
   const { dropzone, isHandlingUpload, setIsHandlingUpload } = useFullscreenDropzone();
 
@@ -94,7 +95,6 @@ const App = ({ config = DEFAULT_CONFIG, selectedImage }: Props) => {
       <DeleteImageModal />
       <ChangeBoardModal />
       <DynamicPromptsModal />
-      <Toaster />
       <PreselectedImage selectedImage={selectedImage} />
     </ErrorBoundary>
   );

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

@@ -1,5 +1,8 @@
-import { Button, Flex, Heading, Link, Text, useToast } from '@invoke-ai/ui-library';
+import { Button, Flex, Heading, Image, Link, Text } from '@invoke-ai/ui-library';
+import { useAppSelector } from 'app/store/storeHooks';
+import { toast } from 'features/toast/toast';
 import newGithubIssueUrl from 'new-github-issue-url';
+import InvokeLogoYellow from 'public/assets/images/invoke-symbol-ylw-lrg.svg';
 import { memo, useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
 import { PiArrowCounterClockwiseBold, PiArrowSquareOutBold, PiCopyBold } from 'react-icons/pi';
@@ -11,31 +14,39 @@ type Props = {
 };
 
 const AppErrorBoundaryFallback = ({ error, resetErrorBoundary }: Props) => {
-  const toast = useToast();
   const { t } = useTranslation();
+  const isLocal = useAppSelector((s) => s.config.isLocal);
 
   const handleCopy = useCallback(() => {
     const text = JSON.stringify(serializeError(error), null, 2);
     navigator.clipboard.writeText(`\`\`\`\n${text}\n\`\`\``);
     toast({
-      title: 'Error Copied',
+      id: 'ERROR_COPIED',
+      title: t('toast.errorCopied'),
     });
-  }, [error, toast]);
+  }, [error, t]);
 
-  const url = useMemo(
-    () =>
-      newGithubIssueUrl({
+  const url = useMemo(() => {
+    if (isLocal) {
+      return newGithubIssueUrl({
         user: 'invoke-ai',
         repo: 'InvokeAI',
         template: 'BUG_REPORT.yml',
         title: `[bug]: ${error.name}: ${error.message}`,
-      }),
-    [error.message, error.name]
-  );
+      });
+    } else {
+      return 'https://support.invoke.ai/support/tickets/new';
+    }
+  }, [error.message, error.name, isLocal]);
+
   return (
     <Flex layerStyle="body" w="100vw" h="100vh" alignItems="center" justifyContent="center" p={4}>
       <Flex layerStyle="first" flexDir="column" borderRadius="base" justifyContent="center" gap={8} p={16}>
-        <Heading>{t('common.somethingWentWrong')}</Heading>
+        <Flex alignItems="center" gap="2">
+          <Image src={InvokeLogoYellow} alt="invoke-logo" w="24px" h="24px" minW="24px" minH="24px" userSelect="none" />
+          <Heading fontSize="2xl">{t('common.somethingWentWrong')}</Heading>
+        </Flex>
+
         <Flex
           layerStyle="second"
           px={8}
@@ -57,7 +68,9 @@ const AppErrorBoundaryFallback = ({ error, resetErrorBoundary }: Props) => {
             {t('common.copyError')}
           </Button>
           <Link href={url} isExternal>
-            <Button leftIcon={<PiArrowSquareOutBold />}>{t('accessibility.createIssue')}</Button>
+            <Button leftIcon={<PiArrowSquareOutBold />}>
+              {isLocal ? t('accessibility.createIssue') : t('accessibility.submitSupportTicket')}
+            </Button>
           </Link>
         </Flex>
       </Flex>

invokeai/frontend/web/src/app/components/Toaster.ts

@@ -1,44 +0,0 @@
-import { useToast } from '@invoke-ai/ui-library';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import { addToast, clearToastQueue } from 'features/system/store/systemSlice';
-import type { MakeToastArg } from 'features/system/util/makeToast';
-import { makeToast } from 'features/system/util/makeToast';
-import { memo, useCallback, useEffect } from 'react';
-
-/**
- * Logical component. Watches the toast queue and makes toasts when the queue is not empty.
- * @returns null
- */
-const Toaster = () => {
-  const dispatch = useAppDispatch();
-  const toastQueue = useAppSelector((s) => s.system.toastQueue);
-  const toast = useToast();
-  useEffect(() => {
-    toastQueue.forEach((t) => {
-      toast(t);
-    });
-    toastQueue.length > 0 && dispatch(clearToastQueue());
-  }, [dispatch, toast, toastQueue]);
-
-  return null;
-};
-
-/**
- * Returns a function that can be used to make a toast.
- * @example
- * const toaster = useAppToaster();
- * toaster('Hello world!');
- * toaster({ title: 'Hello world!', status: 'success' });
- * @returns A function that can be used to make a toast.
- * @see makeToast
- * @see MakeToastArg
- * @see UseToastOptions
- */
-export const useAppToaster = () => {
-  const dispatch = useAppDispatch();
-  const toaster = useCallback((arg: MakeToastArg) => dispatch(addToast(makeToast(arg))), [dispatch]);
-
-  return toaster;
-};
-
-export default memo(Toaster);

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

@@ -67,6 +67,8 @@ export const useSocketIO = () => {
 
     if ($isDebugging.get() || import.meta.env.MODE === 'development') {
       window.$socketOptions = $socketOptions;
+      // This is only enabled manually for debugging, console is allowed.
+      /* eslint-disable-next-line no-console */
       console.log('Socket initialized', socket);
     }
 
@@ -75,6 +77,8 @@ export const useSocketIO = () => {
     return () => {
       if ($isDebugging.get() || import.meta.env.MODE === 'development') {
         window.$socketOptions = undefined;
+        // This is only enabled manually for debugging, console is allowed.
+        /* eslint-disable-next-line no-console */
         console.log('Socket teardown', socket);
       }
       socket.disconnect();

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

@@ -1,3 +1,6 @@
+/* eslint-disable no-console */
+// This is only enabled manually for debugging, console is allowed.
+
 import type { Middleware, MiddlewareAPI } from '@reduxjs/toolkit';
 import { diff } from 'jsondiffpatch';
 

invokeai/frontend/web/src/app/store/middleware/devtools/actionSanitizer.ts

@@ -1,7 +1,6 @@
 import type { UnknownAction } from '@reduxjs/toolkit';
 import { deepClone } from 'common/util/deepClone';
 import { isAnyGraphBuilt } from 'features/nodes/store/actions';
-import { nodeTemplatesBuilt } from 'features/nodes/store/nodesSlice';
 import { appInfoApi } from 'services/api/endpoints/appInfo';
 import type { Graph } from 'services/api/types';
 import { socketGeneratorProgress } from 'services/events/actions';
@@ -25,13 +24,6 @@ export const actionSanitizer = <A extends UnknownAction>(action: A): A => {
     };
   }
 
-  if (nodeTemplatesBuilt.match(action)) {
-    return {
-      ...action,
-      payload: '<Node templates omitted>',
-    };
-  }
-
   if (socketGeneratorProgress.match(action)) {
     const sanitized = deepClone(action);
     if (sanitized.payload.data.progress_image) {

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

@@ -41,12 +41,10 @@ import { addGeneratorProgressEventListener } from 'app/store/middleware/listener
 import { addGraphExecutionStateCompleteEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketGraphExecutionStateComplete';
 import { addInvocationCompleteEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationComplete';
 import { addInvocationErrorEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationError';
-import { addInvocationRetrievalErrorEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationRetrievalError';
 import { addInvocationStartedEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationStarted';
 import { addModelInstallEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall';
 import { addModelLoadEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketModelLoad';
 import { addSocketQueueItemStatusChangedEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketQueueItemStatusChanged';
-import { addSessionRetrievalErrorEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketSessionRetrievalError';
 import { addSocketSubscribedEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketSubscribed';
 import { addSocketUnsubscribedEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketUnsubscribed';
 import { addStagingAreaImageSavedListener } from 'app/store/middleware/listenerMiddleware/listeners/stagingAreaImageSaved';
@@ -114,8 +112,6 @@ addSocketSubscribedEventListener(startAppListening);
 addSocketUnsubscribedEventListener(startAppListening);
 addModelLoadEventListener(startAppListening);
 addModelInstallEventListener(startAppListening);
-addSessionRetrievalErrorEventListener(startAppListening);
-addInvocationRetrievalErrorEventListener(startAppListening);
 addSocketQueueItemStatusChangedEventListener(startAppListening);
 addBulkDownloadListeners(startAppListening);
 

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

@@ -8,7 +8,7 @@ import {
   resetCanvas,
   setInitialCanvasImage,
 } from 'features/canvas/store/canvasSlice';
-import { addToast } from 'features/system/store/systemSlice';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { queueApi } from 'services/api/endpoints/queue';
 
@@ -30,22 +30,20 @@ export const addCommitStagingAreaImageListener = (startAppListening: AppStartLis
         req.reset();
         if (canceled > 0) {
           log.debug(`Canceled ${canceled} canvas batches`);
-          dispatch(
-            addToast({
-              title: t('queue.cancelBatchSucceeded'),
-              status: 'success',
-            })
-          );
+          toast({
+            id: 'CANCEL_BATCH_SUCCEEDED',
+            title: t('queue.cancelBatchSucceeded'),
+            status: 'success',
+          });
         }
         dispatch(canvasBatchIdsReset());
       } catch {
         log.error('Failed to cancel canvas batches');
-        dispatch(
-          addToast({
-            title: t('queue.cancelBatchFailed'),
-            status: 'error',
-          })
-        );
+        toast({
+          id: 'CANCEL_BATCH_FAILED',
+          title: t('queue.cancelBatchFailed'),
+          status: 'error',
+        });
       }
     },
   });

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

@@ -1,8 +1,8 @@
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { parseify } from 'common/util/serialize';
-import { toast } from 'common/util/toast';
 import { zPydanticValidationError } from 'features/system/store/zodSchemas';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { truncate, upperFirst } from 'lodash-es';
 import { queueApi } from 'services/api/endpoints/queue';
@@ -16,18 +16,15 @@ export const addBatchEnqueuedListener = (startAppListening: AppStartListening) =
       const arg = action.meta.arg.originalArgs;
       logger('queue').debug({ enqueueResult: parseify(response) }, 'Batch enqueued');
 
-      if (!toast.isActive('batch-queued')) {
-        toast({
-          id: 'batch-queued',
-          title: t('queue.batchQueued'),
-          description: t('queue.batchQueuedDesc', {
-            count: response.enqueued,
-            direction: arg.prepend ? t('queue.front') : t('queue.back'),
-          }),
-          duration: 1000,
-          status: 'success',
-        });
-      }
+      toast({
+        id: 'QUEUE_BATCH_SUCCEEDED',
+        title: t('queue.batchQueued'),
+        status: 'success',
+        description: t('queue.batchQueuedDesc', {
+          count: response.enqueued,
+          direction: arg.prepend ? t('queue.front') : t('queue.back'),
+        }),
+      });
     },
   });
 
@@ -40,9 +37,10 @@ export const addBatchEnqueuedListener = (startAppListening: AppStartListening) =
 
       if (!response) {
         toast({
+          id: 'QUEUE_BATCH_FAILED',
           title: t('queue.batchFailedToQueue'),
           status: 'error',
-          description: 'Unknown Error',
+          description: t('common.unknownError'),
         });
         logger('queue').error({ batchConfig: parseify(arg), error: parseify(response) }, t('queue.batchFailedToQueue'));
         return;
@@ -52,7 +50,7 @@ export const addBatchEnqueuedListener = (startAppListening: AppStartListening) =
       if (result.success) {
         result.data.data.detail.map((e) => {
           toast({
-            id: 'batch-failed-to-queue',
+            id: 'QUEUE_BATCH_FAILED',
             title: truncate(upperFirst(e.msg), { length: 128 }),
             status: 'error',
             description: truncate(
@@ -64,9 +62,10 @@ export const addBatchEnqueuedListener = (startAppListening: AppStartListening) =
         });
       } else if (response.status !== 403) {
         toast({
+          id: 'QUEUE_BATCH_FAILED',
           title: t('queue.batchFailedToQueue'),
-          description: t('common.unknownError'),
           status: 'error',
+          description: t('common.unknownError'),
         });
       }
       logger('queue').error({ batchConfig: parseify(arg), error: parseify(response) }, t('queue.batchFailedToQueue'));

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

@@ -21,7 +21,7 @@ export const addDeleteBoardAndImagesFulfilledListener = (startAppListening: AppS
 
       const { canvas, nodes, controlAdapters, controlLayers } = getState();
       deleted_images.forEach((image_name) => {
-        const imageUsage = getImageUsage(canvas, nodes, controlAdapters, controlLayers.present, image_name);
+        const imageUsage = getImageUsage(canvas, nodes.present, controlAdapters, controlLayers.present, image_name);
 
         if (imageUsage.isCanvasImage && !wasCanvasReset) {
           dispatch(resetCanvas());

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/bulkDownload.tsx

@@ -1,8 +1,7 @@
-import type { UseToastOptions } from '@invoke-ai/ui-library';
 import { ExternalLink } from '@invoke-ai/ui-library';
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
-import { toast } from 'common/util/toast';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
 import {
@@ -28,7 +27,6 @@ export const addBulkDownloadListeners = (startAppListening: AppStartListening) =
         // Show the response message if it exists, otherwise show the default message
         description: action.payload.response || t('gallery.bulkDownloadRequestedDesc'),
         duration: null,
-        isClosable: true,
       });
     },
   });
@@ -40,9 +38,9 @@ export const addBulkDownloadListeners = (startAppListening: AppStartListening) =
 
       // There isn't any toast to update if we get this event.
       toast({
+        id: 'BULK_DOWNLOAD_REQUEST_FAILED',
         title: t('gallery.bulkDownloadRequestFailed'),
-        status: 'success',
-        isClosable: true,
+        status: 'error',
       });
     },
   });
@@ -65,7 +63,7 @@ export const addBulkDownloadListeners = (startAppListening: AppStartListening) =
       // TODO(psyche): This URL may break in in some environments (e.g. Nvidia workbench) but we need to test it first
       const url = `/api/v1/images/download/${bulk_download_item_name}`;
 
-      const toastOptions: UseToastOptions = {
+      toast({
         id: bulk_download_item_name,
         title: t('gallery.bulkDownloadReady', 'Download ready'),
         status: 'success',
@@ -77,14 +75,7 @@ export const addBulkDownloadListeners = (startAppListening: AppStartListening) =
           />
         ),
         duration: null,
-        isClosable: true,
-      };
-
-      if (toast.isActive(bulk_download_item_name)) {
-        toast.update(bulk_download_item_name, toastOptions);
-      } else {
-        toast(toastOptions);
-      }
+      });
     },
   });
 
@@ -95,20 +86,13 @@ export const addBulkDownloadListeners = (startAppListening: AppStartListening) =
 
       const { bulk_download_item_name } = action.payload.data;
 
-      const toastOptions: UseToastOptions = {
+      toast({
         id: bulk_download_item_name,
         title: t('gallery.bulkDownloadFailed'),
         status: 'error',
         description: action.payload.data.error,
         duration: null,
-        isClosable: true,
-      };
-
-      if (toast.isActive(bulk_download_item_name)) {
-        toast.update(bulk_download_item_name, toastOptions);
-      } else {
-        toast(toastOptions);
-      }
+      });
     },
   });
 };

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

@@ -2,14 +2,14 @@ import { $logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { canvasCopiedToClipboard } from 'features/canvas/store/actions';
 import { getBaseLayerBlob } from 'features/canvas/util/getBaseLayerBlob';
-import { addToast } from 'features/system/store/systemSlice';
 import { copyBlobToClipboard } from 'features/system/util/copyBlobToClipboard';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 
 export const addCanvasCopiedToClipboardListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: canvasCopiedToClipboard,
-    effect: async (action, { dispatch, getState }) => {
+    effect: async (action, { getState }) => {
       const moduleLog = $logger.get().child({ namespace: 'canvasCopiedToClipboardListener' });
       const state = getState();
 
@@ -19,22 +19,20 @@ export const addCanvasCopiedToClipboardListener = (startAppListening: AppStartLi
         copyBlobToClipboard(blob);
       } catch (err) {
         moduleLog.error(String(err));
-        dispatch(
-          addToast({
-            title: t('toast.problemCopyingCanvas'),
-            description: t('toast.problemCopyingCanvasDesc'),
-            status: 'error',
-          })
-        );
+        toast({
+          id: 'CANVAS_COPY_FAILED',
+          title: t('toast.problemCopyingCanvas'),
+          description: t('toast.problemCopyingCanvasDesc'),
+          status: 'error',
+        });
         return;
       }
 
-      dispatch(
-        addToast({
-          title: t('toast.canvasCopiedClipboard'),
-          status: 'success',
-        })
-      );
+      toast({
+        id: 'CANVAS_COPY_SUCCEEDED',
+        title: t('toast.canvasCopiedClipboard'),
+        status: 'success',
+      });
     },
   });
 };

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

@@ -3,13 +3,13 @@ import type { AppStartListening } from 'app/store/middleware/listenerMiddleware'
 import { canvasDownloadedAsImage } from 'features/canvas/store/actions';
 import { downloadBlob } from 'features/canvas/util/downloadBlob';
 import { getBaseLayerBlob } from 'features/canvas/util/getBaseLayerBlob';
-import { addToast } from 'features/system/store/systemSlice';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 
 export const addCanvasDownloadedAsImageListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: canvasDownloadedAsImage,
-    effect: async (action, { dispatch, getState }) => {
+    effect: async (action, { getState }) => {
       const moduleLog = $logger.get().child({ namespace: 'canvasSavedToGalleryListener' });
       const state = getState();
 
@@ -18,18 +18,17 @@ export const addCanvasDownloadedAsImageListener = (startAppListening: AppStartLi
         blob = await getBaseLayerBlob(state);
       } catch (err) {
         moduleLog.error(String(err));
-        dispatch(
-          addToast({
-            title: t('toast.problemDownloadingCanvas'),
-            description: t('toast.problemDownloadingCanvasDesc'),
-            status: 'error',
-          })
-        );
+        toast({
+          id: 'CANVAS_DOWNLOAD_FAILED',
+          title: t('toast.problemDownloadingCanvas'),
+          description: t('toast.problemDownloadingCanvasDesc'),
+          status: 'error',
+        });
         return;
       }
 
       downloadBlob(blob, 'canvas.png');
-      dispatch(addToast({ title: t('toast.canvasDownloaded'), status: 'success' }));
+      toast({ id: 'CANVAS_DOWNLOAD_SUCCEEDED', title: t('toast.canvasDownloaded'), status: 'success' });
     },
   });
 };

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

@@ -3,7 +3,7 @@ import type { AppStartListening } from 'app/store/middleware/listenerMiddleware'
 import { canvasImageToControlAdapter } from 'features/canvas/store/actions';
 import { getBaseLayerBlob } from 'features/canvas/util/getBaseLayerBlob';
 import { controlAdapterImageChanged } from 'features/controlAdapters/store/controlAdaptersSlice';
-import { addToast } from 'features/system/store/systemSlice';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
 
@@ -20,13 +20,12 @@ export const addCanvasImageToControlNetListener = (startAppListening: AppStartLi
         blob = await getBaseLayerBlob(state, true);
       } catch (err) {
         log.error(String(err));
-        dispatch(
-          addToast({
-            title: t('toast.problemSavingCanvas'),
-            description: t('toast.problemSavingCanvasDesc'),
-            status: 'error',
-          })
-        );
+        toast({
+          id: 'PROBLEM_SAVING_CANVAS',
+          title: t('toast.problemSavingCanvas'),
+          description: t('toast.problemSavingCanvasDesc'),
+          status: 'error',
+        });
         return;
       }
 
@@ -43,7 +42,7 @@ export const addCanvasImageToControlNetListener = (startAppListening: AppStartLi
           crop_visible: false,
           postUploadAction: {
             type: 'TOAST',
-            toastOptions: { title: t('toast.canvasSentControlnetAssets') },
+            title: t('toast.canvasSentControlnetAssets'),
           },
         })
       ).unwrap();

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

@@ -2,7 +2,7 @@ import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { canvasMaskSavedToGallery } from 'features/canvas/store/actions';
 import { getCanvasData } from 'features/canvas/util/getCanvasData';
-import { addToast } from 'features/system/store/systemSlice';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
 
@@ -29,13 +29,12 @@ export const addCanvasMaskSavedToGalleryListener = (startAppListening: AppStartL
 
       if (!maskBlob) {
         log.error('Problem getting mask layer blob');
-        dispatch(
-          addToast({
-            title: t('toast.problemSavingMask'),
-            description: t('toast.problemSavingMaskDesc'),
-            status: 'error',
-          })
-        );
+        toast({
+          id: 'PROBLEM_SAVING_MASK',
+          title: t('toast.problemSavingMask'),
+          description: t('toast.problemSavingMaskDesc'),
+          status: 'error',
+        });
         return;
       }
 
@@ -52,7 +51,7 @@ export const addCanvasMaskSavedToGalleryListener = (startAppListening: AppStartL
           crop_visible: true,
           postUploadAction: {
             type: 'TOAST',
-            toastOptions: { title: t('toast.maskSavedAssets') },
+            title: t('toast.maskSavedAssets'),
           },
         })
       );

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

@@ -3,7 +3,7 @@ import type { AppStartListening } from 'app/store/middleware/listenerMiddleware'
 import { canvasMaskToControlAdapter } from 'features/canvas/store/actions';
 import { getCanvasData } from 'features/canvas/util/getCanvasData';
 import { controlAdapterImageChanged } from 'features/controlAdapters/store/controlAdaptersSlice';
-import { addToast } from 'features/system/store/systemSlice';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
 
@@ -30,13 +30,12 @@ export const addCanvasMaskToControlNetListener = (startAppListening: AppStartLis
 
       if (!maskBlob) {
         log.error('Problem getting mask layer blob');
-        dispatch(
-          addToast({
-            title: t('toast.problemImportingMask'),
-            description: t('toast.problemImportingMaskDesc'),
-            status: 'error',
-          })
-        );
+        toast({
+          id: 'PROBLEM_IMPORTING_MASK',
+          title: t('toast.problemImportingMask'),
+          description: t('toast.problemImportingMaskDesc'),
+          status: 'error',
+        });
         return;
       }
 
@@ -53,7 +52,7 @@ export const addCanvasMaskToControlNetListener = (startAppListening: AppStartLis
           crop_visible: false,
           postUploadAction: {
             type: 'TOAST',
-            toastOptions: { title: t('toast.maskSentControlnetAssets') },
+            title: t('toast.maskSentControlnetAssets'),
           },
         })
       ).unwrap();

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

@@ -4,7 +4,7 @@ import { canvasMerged } from 'features/canvas/store/actions';
 import { $canvasBaseLayer } from 'features/canvas/store/canvasNanostore';
 import { setMergedCanvas } from 'features/canvas/store/canvasSlice';
 import { getFullBaseLayerBlob } from 'features/canvas/util/getFullBaseLayerBlob';
-import { addToast } from 'features/system/store/systemSlice';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
 
@@ -17,13 +17,12 @@ export const addCanvasMergedListener = (startAppListening: AppStartListening) =>
 
       if (!blob) {
         moduleLog.error('Problem getting base layer blob');
-        dispatch(
-          addToast({
-            title: t('toast.problemMergingCanvas'),
-            description: t('toast.problemMergingCanvasDesc'),
-            status: 'error',
-          })
-        );
+        toast({
+          id: 'PROBLEM_MERGING_CANVAS',
+          title: t('toast.problemMergingCanvas'),
+          description: t('toast.problemMergingCanvasDesc'),
+          status: 'error',
+        });
         return;
       }
 
@@ -31,13 +30,12 @@ export const addCanvasMergedListener = (startAppListening: AppStartListening) =>
 
       if (!canvasBaseLayer) {
         moduleLog.error('Problem getting canvas base layer');
-        dispatch(
-          addToast({
-            title: t('toast.problemMergingCanvas'),
-            description: t('toast.problemMergingCanvasDesc'),
-            status: 'error',
-          })
-        );
+        toast({
+          id: 'PROBLEM_MERGING_CANVAS',
+          title: t('toast.problemMergingCanvas'),
+          description: t('toast.problemMergingCanvasDesc'),
+          status: 'error',
+        });
         return;
       }
 
@@ -54,7 +52,7 @@ export const addCanvasMergedListener = (startAppListening: AppStartListening) =>
           is_intermediate: true,
           postUploadAction: {
             type: 'TOAST',
-            toastOptions: { title: t('toast.canvasMerged') },
+            title: t('toast.canvasMerged'),
           },
         })
       ).unwrap();

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

@@ -1,8 +1,9 @@
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
+import { parseify } from 'common/util/serialize';
 import { canvasSavedToGallery } from 'features/canvas/store/actions';
 import { getBaseLayerBlob } from 'features/canvas/util/getBaseLayerBlob';
-import { addToast } from 'features/system/store/systemSlice';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
 
@@ -18,13 +19,12 @@ export const addCanvasSavedToGalleryListener = (startAppListening: AppStartListe
         blob = await getBaseLayerBlob(state);
       } catch (err) {
         log.error(String(err));
-        dispatch(
-          addToast({
-            title: t('toast.problemSavingCanvas'),
-            description: t('toast.problemSavingCanvasDesc'),
-            status: 'error',
-          })
-        );
+        toast({
+          id: 'CANVAS_SAVE_FAILED',
+          title: t('toast.problemSavingCanvas'),
+          description: t('toast.problemSavingCanvasDesc'),
+          status: 'error',
+        });
         return;
       }
 
@@ -41,7 +41,10 @@ export const addCanvasSavedToGalleryListener = (startAppListening: AppStartListe
           crop_visible: true,
           postUploadAction: {
             type: 'TOAST',
-            toastOptions: { title: t('toast.canvasSavedGallery') },
+            title: t('toast.canvasSavedGallery'),
+          },
+          metadata: {
+            _canvas_objects: parseify(state.canvas.layerState.objects),
           },
         })
       );

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

@@ -14,8 +14,9 @@ import {
 } from 'features/controlLayers/store/controlLayersSlice';
 import { CA_PROCESSOR_DATA } from 'features/controlLayers/util/controlAdapters';
 import { isImageOutput } from 'features/nodes/types/common';
-import { addToast } from 'features/system/store/systemSlice';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
+import { isEqual } from 'lodash-es';
 import { getImageDTO } from 'services/api/endpoints/images';
 import { queueApi } from 'services/api/endpoints/queue';
 import type { BatchConfig } from 'services/api/types';
@@ -47,8 +48,10 @@ const cancelProcessorBatch = async (dispatch: AppDispatch, layerId: string, batc
 export const addControlAdapterPreprocessor = (startAppListening: AppStartListening) => {
   startAppListening({
     matcher,
-    effect: async (action, { dispatch, getState, cancelActiveListeners, delay, take, signal }) => {
+    effect: async (action, { dispatch, getState, getOriginalState, cancelActiveListeners, delay, take, signal }) => {
       const layerId = caLayerRecalled.match(action) ? action.payload.id : action.payload.layerId;
+      const state = getState();
+      const originalState = getOriginalState();
 
       // Cancel any in-progress instances of this listener
       cancelActiveListeners();
@@ -57,21 +60,33 @@ export const addControlAdapterPreprocessor = (startAppListening: AppStartListeni
       // Delay before starting actual work
       await delay(DEBOUNCE_MS);
 
-      // Double-check that we are still eligible for processing
-      const state = getState();
       const layer = state.controlLayers.present.layers.filter(isControlAdapterLayer).find((l) => l.id === layerId);
 
-      // If we have no image or there is no processor config, bail
       if (!layer) {
         return;
       }
 
+      // We should only process if the processor settings or image have changed
+      const originalLayer = originalState.controlLayers.present.layers
+        .filter(isControlAdapterLayer)
+        .find((l) => l.id === layerId);
+      const originalImage = originalLayer?.controlAdapter.image;
+      const originalConfig = originalLayer?.controlAdapter.processorConfig;
+
       const image = layer.controlAdapter.image;
       const config = layer.controlAdapter.processorConfig;
 
+      if (isEqual(config, originalConfig) && isEqual(image, originalImage)) {
+        // Neither config nor image have changed, we can bail
+        return;
+      }
+
       if (!image || !config) {
-        // The user has reset the image or config, so we should clear the processed image
+        // - If we have no image, we have nothing to process
+        // - If we have no processor config, we have nothing to process
+        // Clear the processed image and bail
         dispatch(caLayerProcessedImageChanged({ layerId, imageDTO: null }));
+        return;
       }
 
       // At this point, the user has stopped fiddling with the processor settings and there is a processor selected.
@@ -81,8 +96,8 @@ export const addControlAdapterPreprocessor = (startAppListening: AppStartListeni
         cancelProcessorBatch(dispatch, layerId, layer.controlAdapter.processorPendingBatchId);
       }
 
-      // @ts-expect-error: TS isn't able to narrow the typing of buildNode and `config` will error...
-      const processorNode = CA_PROCESSOR_DATA[config.type].buildNode(image, config);
+      // TODO(psyche): I can't get TS to be happy, it thinkgs `config` is `never` but it should be inferred from the generic... I'll just cast it for now
+      const processorNode = CA_PROCESSOR_DATA[config.type].buildNode(image, config as never);
       const enqueueBatchArg: BatchConfig = {
         prepend: true,
         batch: {
@@ -148,7 +163,6 @@ export const addControlAdapterPreprocessor = (startAppListening: AppStartListeni
           log.trace('Control Adapter preprocessor cancelled');
         } else {
           // Some other error condition...
-          console.log(error);
           log.error({ enqueueBatchArg: parseify(enqueueBatchArg) }, t('queue.graphFailedToQueue'));
 
           if (error instanceof Object) {
@@ -160,12 +174,11 @@ export const addControlAdapterPreprocessor = (startAppListening: AppStartListeni
             }
           }
 
-          dispatch(
-            addToast({
-              title: t('queue.graphFailedToQueue'),
-              status: 'error',
-            })
-          );
+          toast({
+            id: 'GRAPH_QUEUE_FAILED',
+            title: t('queue.graphFailedToQueue'),
+            status: 'error',
+          });
         }
       } finally {
         req.reset();

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

@@ -10,7 +10,7 @@ import {
 } from 'features/controlAdapters/store/controlAdaptersSlice';
 import { isControlNetOrT2IAdapter } from 'features/controlAdapters/store/types';
 import { isImageOutput } from 'features/nodes/types/common';
-import { addToast } from 'features/system/store/systemSlice';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
 import { queueApi } from 'services/api/endpoints/queue';
@@ -108,12 +108,11 @@ export const addControlNetImageProcessedListener = (startAppListening: AppStartL
           }
         }
 
-        dispatch(
-          addToast({
-            title: t('queue.graphFailedToQueue'),
-            status: 'error',
-          })
-        );
+        toast({
+          id: 'GRAPH_QUEUE_FAILED',
+          title: t('queue.graphFailedToQueue'),
+          status: 'error',
+        });
       }
     },
   });

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

@@ -8,8 +8,8 @@ import { blobToDataURL } from 'features/canvas/util/blobToDataURL';
 import { getCanvasData } from 'features/canvas/util/getCanvasData';
 import { getCanvasGenerationMode } from 'features/canvas/util/getCanvasGenerationMode';
 import { canvasGraphBuilt } from 'features/nodes/store/actions';
-import { buildCanvasGraph } from 'features/nodes/util/graph/buildCanvasGraph';
 import { prepareLinearUIBatch } from 'features/nodes/util/graph/buildLinearBatchConfig';
+import { buildCanvasGraph } from 'features/nodes/util/graph/canvas/buildCanvasGraph';
 import { imagesApi } from 'services/api/endpoints/images';
 import { queueApi } from 'services/api/endpoints/queue';
 import type { ImageDTO } from 'services/api/types';

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

@@ -1,9 +1,9 @@
 import { enqueueRequested } from 'app/store/actions';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { isImageViewerOpenChanged } from 'features/gallery/store/gallerySlice';
-import { buildGenerationTabGraph } from 'features/nodes/util/graph/buildGenerationTabGraph';
-import { buildGenerationTabSDXLGraph } from 'features/nodes/util/graph/buildGenerationTabSDXLGraph';
 import { prepareLinearUIBatch } from 'features/nodes/util/graph/buildLinearBatchConfig';
+import { buildGenerationTabGraph } from 'features/nodes/util/graph/generation/buildGenerationTabGraph';
+import { buildGenerationTabSDXLGraph } from 'features/nodes/util/graph/generation/buildGenerationTabSDXLGraph';
 import { queueApi } from 'services/api/endpoints/queue';
 
 export const addEnqueueRequestedLinear = (startAppListening: AppStartListening) => {
@@ -18,7 +18,7 @@ export const addEnqueueRequestedLinear = (startAppListening: AppStartListening)
 
       let graph;
 
-      if (model && model.base === 'sdxl') {
+      if (model?.base === 'sdxl') {
         graph = await buildGenerationTabSDXLGraph(state);
       } else {
         graph = await buildGenerationTabGraph(state);

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

@@ -11,9 +11,9 @@ export const addEnqueueRequestedNodes = (startAppListening: AppStartListening) =
       enqueueRequested.match(action) && action.payload.tabName === 'workflows',
     effect: async (action, { getState, dispatch }) => {
       const state = getState();
-      const { nodes, edges } = state.nodes;
+      const { nodes, edges } = state.nodes.present;
       const workflow = state.workflow;
-      const graph = buildNodesGraph(state.nodes);
+      const graph = buildNodesGraph(state.nodes.present);
       const builtWorkflow = buildWorkflowWithValidation({
         nodes,
         edges,

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

@@ -1,7 +1,7 @@
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { parseify } from 'common/util/serialize';
-import { nodeTemplatesBuilt } from 'features/nodes/store/nodesSlice';
+import { $templates } from 'features/nodes/store/nodesSlice';
 import { parseSchema } from 'features/nodes/util/schema/parseSchema';
 import { size } from 'lodash-es';
 import { appInfoApi } from 'services/api/endpoints/appInfo';
@@ -9,7 +9,7 @@ import { appInfoApi } from 'services/api/endpoints/appInfo';
 export const addGetOpenAPISchemaListener = (startAppListening: AppStartListening) => {
   startAppListening({
     matcher: appInfoApi.endpoints.getOpenAPISchema.matchFulfilled,
-    effect: (action, { dispatch, getState }) => {
+    effect: (action, { getState }) => {
       const log = logger('system');
       const schemaJSON = action.payload;
 
@@ -20,7 +20,7 @@ export const addGetOpenAPISchemaListener = (startAppListening: AppStartListening
 
       log.debug({ nodeTemplates: parseify(nodeTemplates) }, `Built ${size(nodeTemplates)} node templates`);
 
-      dispatch(nodeTemplatesBuilt(nodeTemplates));
+      $templates.set(nodeTemplates);
     },
   });
 

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

@@ -29,7 +29,7 @@ import type { ImageDTO } from 'services/api/types';
 import { imagesSelectors } from 'services/api/util';
 
 const deleteNodesImages = (state: RootState, dispatch: AppDispatch, imageDTO: ImageDTO) => {
-  state.nodes.nodes.forEach((node) => {
+  state.nodes.present.nodes.forEach((node) => {
     if (!isInvocationNode(node)) {
       return;
     }

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

@@ -1,4 +1,3 @@
-import type { UseToastOptions } from '@invoke-ai/ui-library';
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { setInitialCanvasImage } from 'features/canvas/store/canvasSlice';
@@ -14,7 +13,7 @@ import {
 } from 'features/controlLayers/store/controlLayersSlice';
 import { fieldImageValueChanged } from 'features/nodes/store/nodesSlice';
 import { selectOptimalDimension } from 'features/parameters/store/generationSlice';
-import { addToast } from 'features/system/store/systemSlice';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { omit } from 'lodash-es';
 import { boardsApi } from 'services/api/endpoints/boards';
@@ -42,16 +41,17 @@ export const addImageUploadedFulfilledListener = (startAppListening: AppStartLis
         return;
       }
 
-      const DEFAULT_UPLOADED_TOAST: UseToastOptions = {
+      const DEFAULT_UPLOADED_TOAST = {
+        id: 'IMAGE_UPLOADED',
         title: t('toast.imageUploaded'),
         status: 'success',
-      };
+      } as const;
 
       // default action - just upload and alert user
       if (postUploadAction?.type === 'TOAST') {
-        const { toastOptions } = postUploadAction;
         if (!autoAddBoardId || autoAddBoardId === 'none') {
-          dispatch(addToast({ ...DEFAULT_UPLOADED_TOAST, ...toastOptions }));
+          const title = postUploadAction.title || DEFAULT_UPLOADED_TOAST.title;
+          toast({ ...DEFAULT_UPLOADED_TOAST, title });
         } else {
           // Add this image to the board
           dispatch(
@@ -70,24 +70,20 @@ export const addImageUploadedFulfilledListener = (startAppListening: AppStartLis
             ? `${t('toast.addedToBoard')} ${board.board_name}`
             : `${t('toast.addedToBoard')} ${autoAddBoardId}`;
 
-          dispatch(
-            addToast({
-              ...DEFAULT_UPLOADED_TOAST,
-              description,
-            })
-          );
+          toast({
+            ...DEFAULT_UPLOADED_TOAST,
+            description,
+          });
         }
         return;
       }
 
       if (postUploadAction?.type === 'SET_CANVAS_INITIAL_IMAGE') {
         dispatch(setInitialCanvasImage(imageDTO, selectOptimalDimension(state)));
-        dispatch(
-          addToast({
-            ...DEFAULT_UPLOADED_TOAST,
-            description: t('toast.setAsCanvasInitialImage'),
-          })
-        );
+        toast({
+          ...DEFAULT_UPLOADED_TOAST,
+          description: t('toast.setAsCanvasInitialImage'),
+        });
         return;
       }
 
@@ -105,68 +101,56 @@ export const addImageUploadedFulfilledListener = (startAppListening: AppStartLis
             controlImage: imageDTO.image_name,
           })
         );
-        dispatch(
-          addToast({
-            ...DEFAULT_UPLOADED_TOAST,
-            description: t('toast.setControlImage'),
-          })
-        );
+        toast({
+          ...DEFAULT_UPLOADED_TOAST,
+          description: t('toast.setControlImage'),
+        });
         return;
       }
 
       if (postUploadAction?.type === 'SET_CA_LAYER_IMAGE') {
         const { layerId } = postUploadAction;
         dispatch(caLayerImageChanged({ layerId, imageDTO }));
-        dispatch(
-          addToast({
-            ...DEFAULT_UPLOADED_TOAST,
-            description: t('toast.setControlImage'),
-          })
-        );
+        toast({
+          ...DEFAULT_UPLOADED_TOAST,
+          description: t('toast.setControlImage'),
+        });
       }
 
       if (postUploadAction?.type === 'SET_IPA_LAYER_IMAGE') {
         const { layerId } = postUploadAction;
         dispatch(ipaLayerImageChanged({ layerId, imageDTO }));
-        dispatch(
-          addToast({
-            ...DEFAULT_UPLOADED_TOAST,
-            description: t('toast.setControlImage'),
-          })
-        );
+        toast({
+          ...DEFAULT_UPLOADED_TOAST,
+          description: t('toast.setControlImage'),
+        });
       }
 
       if (postUploadAction?.type === 'SET_RG_LAYER_IP_ADAPTER_IMAGE') {
         const { layerId, ipAdapterId } = postUploadAction;
         dispatch(rgLayerIPAdapterImageChanged({ layerId, ipAdapterId, imageDTO }));
-        dispatch(
-          addToast({
-            ...DEFAULT_UPLOADED_TOAST,
-            description: t('toast.setControlImage'),
-          })
-        );
+        toast({
+          ...DEFAULT_UPLOADED_TOAST,
+          description: t('toast.setControlImage'),
+        });
       }
 
       if (postUploadAction?.type === 'SET_II_LAYER_IMAGE') {
         const { layerId } = postUploadAction;
         dispatch(iiLayerImageChanged({ layerId, imageDTO }));
-        dispatch(
-          addToast({
-            ...DEFAULT_UPLOADED_TOAST,
-            description: t('toast.setControlImage'),
-          })
-        );
+        toast({
+          ...DEFAULT_UPLOADED_TOAST,
+          description: t('toast.setControlImage'),
+        });
       }
 
       if (postUploadAction?.type === 'SET_NODES_IMAGE') {
         const { nodeId, fieldName } = postUploadAction;
         dispatch(fieldImageValueChanged({ nodeId, fieldName, value: imageDTO }));
-        dispatch(
-          addToast({
-            ...DEFAULT_UPLOADED_TOAST,
-            description: `${t('toast.setNodeField')} ${fieldName}`,
-          })
-        );
+        toast({
+          ...DEFAULT_UPLOADED_TOAST,
+          description: `${t('toast.setNodeField')} ${fieldName}`,
+        });
         return;
       }
     },
@@ -174,7 +158,7 @@ export const addImageUploadedFulfilledListener = (startAppListening: AppStartLis
 
   startAppListening({
     matcher: imagesApi.endpoints.uploadImage.matchRejected,
-    effect: (action, { dispatch }) => {
+    effect: (action) => {
       const log = logger('images');
       const sanitizedData = {
         arg: {
@@ -183,13 +167,11 @@ export const addImageUploadedFulfilledListener = (startAppListening: AppStartLis
         },
       };
       log.error({ ...sanitizedData }, 'Image upload failed');
-      dispatch(
-        addToast({
-          title: t('toast.imageUploadFailed'),
-          description: action.error.message,
-          status: 'error',
-        })
-      );
+      toast({
+        title: t('toast.imageUploadFailed'),
+        description: action.error.message,
+        status: 'error',
+      });
     },
   });
 };

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

@@ -8,8 +8,7 @@ import { loraRemoved } from 'features/lora/store/loraSlice';
 import { modelSelected } from 'features/parameters/store/actions';
 import { modelChanged, vaeSelected } from 'features/parameters/store/generationSlice';
 import { zParameterModel } from 'features/parameters/types/parameterSchemas';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { forEach } from 'lodash-es';
 
@@ -60,16 +59,14 @@ export const addModelSelectedListener = (startAppListening: AppStartListening) =
         });
 
         if (modelsCleared > 0) {
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('toast.baseModelChangedCleared', {
-                  count: modelsCleared,
-                }),
-                status: 'warning',
-              })
-            )
-          );
+          toast({
+            id: 'BASE_MODEL_CHANGED',
+            title: t('toast.baseModelChanged'),
+            description: t('toast.baseModelChangedCleared', {
+              count: modelsCleared,
+            }),
+            status: 'warning',
+          });
         }
       }
 

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

@@ -19,8 +19,7 @@ import {
   isParameterWidth,
   zParameterVAEModel,
 } from 'features/parameters/types/parameterSchemas';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { modelConfigsAdapterSelectors, modelsApi } from 'services/api/endpoints/models';
 import { isNonRefinerMainModelConfig } from 'services/api/types';
@@ -109,7 +108,7 @@ export const addSetDefaultSettingsListener = (startAppListening: AppStartListeni
           }
         }
 
-        dispatch(addToast(makeToast({ title: t('toast.parameterSet', { parameter: 'Default settings' }) })));
+        toast({ id: 'PARAMETER_SET', title: t('toast.parameterSet', { parameter: 'Default settings' }) });
       }
     },
   });

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

@@ -1,5 +1,8 @@
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
+import { deepClone } from 'common/util/deepClone';
+import { $nodeExecutionStates, upsertExecutionState } from 'features/nodes/hooks/useExecutionState';
+import { zNodeStatus } from 'features/nodes/types/invocation';
 import { socketGeneratorProgress } from 'services/events/actions';
 
 const log = logger('socketio');
@@ -9,6 +12,14 @@ export const addGeneratorProgressEventListener = (startAppListening: AppStartLis
     actionCreator: socketGeneratorProgress,
     effect: (action) => {
       log.trace(action.payload, `Generator progress`);
+      const { source_node_id, step, total_steps, progress_image } = action.payload.data;
+      const nes = deepClone($nodeExecutionStates.get()[source_node_id]);
+      if (nes) {
+        nes.status = zNodeStatus.enum.IN_PROGRESS;
+        nes.progress = (step + 1) / total_steps;
+        nes.progressImage = progress_image ?? null;
+        upsertExecutionState(nes.nodeId, nes);
+      }
     },
   });
 };

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

@@ -1,5 +1,6 @@
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
+import { deepClone } from 'common/util/deepClone';
 import { parseify } from 'common/util/serialize';
 import { addImageToStagingArea } from 'features/canvas/store/canvasSlice';
 import {
@@ -9,7 +10,9 @@ import {
   isImageViewerOpenChanged,
 } from 'features/gallery/store/gallerySlice';
 import { IMAGE_CATEGORIES } from 'features/gallery/store/types';
+import { $nodeExecutionStates, upsertExecutionState } from 'features/nodes/hooks/useExecutionState';
 import { isImageOutput } from 'features/nodes/types/common';
+import { zNodeStatus } from 'features/nodes/types/invocation';
 import { CANVAS_OUTPUT } from 'features/nodes/util/graph/constants';
 import { boardsApi } from 'services/api/endpoints/boards';
 import { imagesApi } from 'services/api/endpoints/images';
@@ -28,7 +31,7 @@ export const addInvocationCompleteEventListener = (startAppListening: AppStartLi
       const { data } = action.payload;
       log.debug({ data: parseify(data) }, `Invocation complete (${action.payload.data.node.type})`);
 
-      const { result, node, queue_batch_id } = data;
+      const { result, node, queue_batch_id, source_node_id } = data;
       // This complete event has an associated image output
       if (isImageOutput(result) && !nodeTypeDenylist.includes(node.type)) {
         const { image_name } = result.image;
@@ -110,6 +113,16 @@ export const addInvocationCompleteEventListener = (startAppListening: AppStartLi
           }
         }
       }
+
+      const nes = deepClone($nodeExecutionStates.get()[source_node_id]);
+      if (nes) {
+        nes.status = zNodeStatus.enum.COMPLETED;
+        if (nes.progress !== null) {
+          nes.progress = 1;
+        }
+        nes.outputs.push(result);
+        upsertExecutionState(nes.nodeId, nes);
+      }
     },
   });
 };

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

@@ -1,14 +1,72 @@
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
+import { deepClone } from 'common/util/deepClone';
+import { $nodeExecutionStates, upsertExecutionState } from 'features/nodes/hooks/useExecutionState';
+import { zNodeStatus } from 'features/nodes/types/invocation';
+import { toast } from 'features/toast/toast';
+import ToastWithSessionRefDescription from 'features/toast/ToastWithSessionRefDescription';
+import { t } from 'i18next';
+import { startCase } from 'lodash-es';
 import { socketInvocationError } from 'services/events/actions';
 
 const log = logger('socketio');
 
+const getTitle = (errorType: string) => {
+  if (errorType === 'OutOfMemoryError') {
+    return t('toast.outOfMemoryError');
+  }
+  return t('toast.serverError');
+};
+
+const getDescription = (errorType: string, sessionId: string, isLocal?: boolean) => {
+  if (!isLocal) {
+    if (errorType === 'OutOfMemoryError') {
+      return ToastWithSessionRefDescription({
+        message: t('toast.outOfMemoryDescription'),
+        sessionId,
+      });
+    }
+    return ToastWithSessionRefDescription({
+      message: errorType,
+      sessionId,
+    });
+  }
+  return errorType;
+};
+
 export const addInvocationErrorEventListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: socketInvocationError,
-    effect: (action) => {
+    effect: (action, { getState }) => {
       log.error(action.payload, `Invocation error (${action.payload.data.node.type})`);
+      const { source_node_id, error_type, error_message, error_traceback, graph_execution_state_id } =
+        action.payload.data;
+      const nes = deepClone($nodeExecutionStates.get()[source_node_id]);
+      if (nes) {
+        nes.status = zNodeStatus.enum.FAILED;
+        nes.progress = null;
+        nes.progressImage = null;
+
+        nes.error = {
+          error_type,
+          error_message,
+          error_traceback,
+        };
+        upsertExecutionState(nes.nodeId, nes);
+      }
+
+      const errorType = startCase(error_type);
+      const sessionId = graph_execution_state_id;
+      const { isLocal } = getState().config;
+
+      toast({
+        id: `INVOCATION_ERROR_${errorType}`,
+        title: getTitle(errorType),
+        status: 'error',
+        duration: null,
+        description: getDescription(errorType, sessionId, isLocal),
+        updateDescription: isLocal ? true : false,
+      });
     },
   });
 };

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

@@ -1,14 +0,0 @@
-import { logger } from 'app/logging/logger';
-import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
-import { socketInvocationRetrievalError } from 'services/events/actions';
-
-const log = logger('socketio');
-
-export const addInvocationRetrievalErrorEventListener = (startAppListening: AppStartListening) => {
-  startAppListening({
-    actionCreator: socketInvocationRetrievalError,
-    effect: (action) => {
-      log.error(action.payload, `Invocation retrieval error (${action.payload.data.graph_execution_state_id})`);
-    },
-  });
-};

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

@@ -1,5 +1,8 @@
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
+import { deepClone } from 'common/util/deepClone';
+import { $nodeExecutionStates, upsertExecutionState } from 'features/nodes/hooks/useExecutionState';
+import { zNodeStatus } from 'features/nodes/types/invocation';
 import { socketInvocationStarted } from 'services/events/actions';
 
 const log = logger('socketio');
@@ -9,6 +12,12 @@ export const addInvocationStartedEventListener = (startAppListening: AppStartLis
     actionCreator: socketInvocationStarted,
     effect: (action) => {
       log.debug(action.payload, `Invocation started (${action.payload.data.node.type})`);
+      const { source_node_id } = action.payload.data;
+      const nes = deepClone($nodeExecutionStates.get()[source_node_id]);
+      if (nes) {
+        nes.status = zNodeStatus.enum.IN_PROGRESS;
+        upsertExecutionState(nes.nodeId, nes);
+      }
     },
   });
 };

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

@@ -1,5 +1,9 @@
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
+import { deepClone } from 'common/util/deepClone';
+import { $nodeExecutionStates } from 'features/nodes/hooks/useExecutionState';
+import { zNodeStatus } from 'features/nodes/types/invocation';
+import { forEach } from 'lodash-es';
 import { queueApi, queueItemsAdapter } from 'services/api/endpoints/queue';
 import { socketQueueItemStatusChanged } from 'services/events/actions';
 
@@ -39,21 +43,31 @@ export const addSocketQueueItemStatusChangedEventListener = (startAppListening:
         queueApi.util.updateQueryData('getBatchStatus', { batch_id: batch_status.batch_id }, () => batch_status)
       );
 
-      // Update the queue item status (this is the full queue item, including the session)
-      dispatch(
-        queueApi.util.updateQueryData('getQueueItem', queue_item.item_id, (draft) => {
-          if (!draft) {
-            return;
-          }
-          Object.assign(draft, queue_item);
-        })
-      );
-
       // Invalidate caches for things we cannot update
       // TODO: technically, we could possibly update the current session queue item, but feels safer to just request it again
       dispatch(
-        queueApi.util.invalidateTags(['CurrentSessionQueueItem', 'NextSessionQueueItem', 'InvocationCacheStatus'])
+        queueApi.util.invalidateTags([
+          'CurrentSessionQueueItem',
+          'NextSessionQueueItem',
+          'InvocationCacheStatus',
+          { type: 'SessionQueueItem', id: queue_item.item_id },
+        ])
       );
+
+      if (['in_progress'].includes(action.payload.data.queue_item.status)) {
+        forEach($nodeExecutionStates.get(), (nes) => {
+          if (!nes) {
+            return;
+          }
+          const clone = deepClone(nes);
+          clone.status = zNodeStatus.enum.PENDING;
+          clone.error = null;
+          clone.progress = null;
+          clone.progressImage = null;
+          clone.outputs = [];
+          $nodeExecutionStates.setKey(clone.nodeId, clone);
+        });
+      }
     },
   });
 };

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

@@ -1,14 +0,0 @@
-import { logger } from 'app/logging/logger';
-import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
-import { socketSessionRetrievalError } from 'services/events/actions';
-
-const log = logger('socketio');
-
-export const addSessionRetrievalErrorEventListener = (startAppListening: AppStartListening) => {
-  startAppListening({
-    actionCreator: socketSessionRetrievalError,
-    effect: (action) => {
-      log.error(action.payload, `Session retrieval error (${action.payload.data.graph_execution_state_id})`);
-    },
-  });
-};

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

@@ -1,6 +1,6 @@
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { stagingAreaImageSaved } from 'features/canvas/store/actions';
-import { addToast } from 'features/system/store/systemSlice';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
 
@@ -29,15 +29,14 @@ export const addStagingAreaImageSavedListener = (startAppListening: AppStartList
             })
           );
         }
-        dispatch(addToast({ title: t('toast.imageSaved'), status: 'success' }));
+        toast({ id: 'IMAGE_SAVED', title: t('toast.imageSaved'), status: 'success' });
       } catch (error) {
-        dispatch(
-          addToast({
-            title: t('toast.imageSavingFailed'),
-            description: (error as Error)?.message,
-            status: 'error',
-          })
-        );
+        toast({
+          id: 'IMAGE_SAVE_FAILED',
+          title: t('toast.imageSavingFailed'),
+          description: (error as Error)?.message,
+          status: 'error',
+        });
       }
     },
   });

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

@@ -1,12 +1,11 @@
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { updateAllNodesRequested } from 'features/nodes/store/actions';
-import { nodeReplaced } from 'features/nodes/store/nodesSlice';
+import { $templates, nodesChanged } from 'features/nodes/store/nodesSlice';
 import { NodeUpdateError } from 'features/nodes/types/error';
 import { isInvocationNode } from 'features/nodes/types/invocation';
 import { getNeedsUpdate, updateNode } from 'features/nodes/util/node/nodeUpdate';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 
 export const addUpdateAllNodesRequestedListener = (startAppListening: AppStartListening) => {
@@ -14,7 +13,8 @@ export const addUpdateAllNodesRequestedListener = (startAppListening: AppStartLi
     actionCreator: updateAllNodesRequested,
     effect: (action, { dispatch, getState }) => {
       const log = logger('nodes');
-      const { nodes, templates } = getState().nodes;
+      const { nodes } = getState().nodes.present;
+      const templates = $templates.get();
 
       let unableToUpdateCount = 0;
 
@@ -24,13 +24,18 @@ export const addUpdateAllNodesRequestedListener = (startAppListening: AppStartLi
           unableToUpdateCount++;
           return;
         }
-        if (!getNeedsUpdate(node, template)) {
+        if (!getNeedsUpdate(node.data, template)) {
           // No need to increment the count here, since we're not actually updating
           return;
         }
         try {
           const updatedNode = updateNode(node, template);
-          dispatch(nodeReplaced({ nodeId: updatedNode.id, node: updatedNode }));
+          dispatch(
+            nodesChanged([
+              { type: 'remove', id: updatedNode.id },
+              { type: 'add', item: updatedNode },
+            ])
+          );
         } catch (e) {
           if (e instanceof NodeUpdateError) {
             unableToUpdateCount++;
@@ -44,24 +49,18 @@ export const addUpdateAllNodesRequestedListener = (startAppListening: AppStartLi
             count: unableToUpdateCount,
           })
         );
-        dispatch(
-          addToast(
-            makeToast({
-              title: t('nodes.unableToUpdateNodes', {
-                count: unableToUpdateCount,
-              }),
-            })
-          )
-        );
+        toast({
+          id: 'UNABLE_TO_UPDATE_NODES',
+          title: t('nodes.unableToUpdateNodes', {
+            count: unableToUpdateCount,
+          }),
+        });
       } else {
-        dispatch(
-          addToast(
-            makeToast({
-              title: t('nodes.allNodesUpdated'),
-              status: 'success',
-            })
-          )
-        );
+        toast({
+          id: 'ALL_NODES_UPDATED',
+          title: t('nodes.allNodesUpdated'),
+          status: 'success',
+        });
       }
     },
   });

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

@@ -4,7 +4,7 @@ import type { AppStartListening } from 'app/store/middleware/listenerMiddleware'
 import { parseify } from 'common/util/serialize';
 import { buildAdHocUpscaleGraph } from 'features/nodes/util/graph/buildAdHocUpscaleGraph';
 import { createIsAllowedToUpscaleSelector } from 'features/parameters/hooks/useIsAllowedToUpscale';
-import { addToast } from 'features/system/store/systemSlice';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { queueApi } from 'services/api/endpoints/queue';
 import type { BatchConfig, ImageDTO } from 'services/api/types';
@@ -29,12 +29,11 @@ export const addUpscaleRequestedListener = (startAppListening: AppStartListening
           { imageDTO },
           t(detailTKey ?? 'parameters.isAllowedToUpscale.tooLarge') // should never coalesce
         );
-        dispatch(
-          addToast({
-            title: t(detailTKey ?? 'parameters.isAllowedToUpscale.tooLarge'), // should never coalesce
-            status: 'error',
-          })
-        );
+        toast({
+          id: 'NOT_ALLOWED_TO_UPSCALE',
+          title: t(detailTKey ?? 'parameters.isAllowedToUpscale.tooLarge'), // should never coalesce
+          status: 'error',
+        });
         return;
       }
 
@@ -65,12 +64,11 @@ export const addUpscaleRequestedListener = (startAppListening: AppStartListening
         if (error instanceof Object && 'status' in error && error.status === 403) {
           return;
         } else {
-          dispatch(
-            addToast({
-              title: t('queue.graphFailedToQueue'),
-              status: 'error',
-            })
-          );
+          toast({
+            id: 'GRAPH_QUEUE_FAILED',
+            title: t('queue.graphFailedToQueue'),
+            status: 'error',
+          });
         }
       }
     },

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

@@ -2,50 +2,64 @@ import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { parseify } from 'common/util/serialize';
 import { workflowLoaded, workflowLoadRequested } from 'features/nodes/store/actions';
+import { $templates } from 'features/nodes/store/nodesSlice';
 import { $flow } from 'features/nodes/store/reactFlowInstance';
+import type { Templates } from 'features/nodes/store/types';
 import { WorkflowMigrationError, WorkflowVersionError } from 'features/nodes/types/error';
+import { graphToWorkflow } from 'features/nodes/util/workflow/graphToWorkflow';
 import { validateWorkflow } from 'features/nodes/util/workflow/validateWorkflow';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
+import { checkBoardAccess, checkImageAccess, checkModelAccess } from 'services/api/hooks/accessChecks';
+import type { GraphAndWorkflowResponse, NonNullableGraph } from 'services/api/types';
 import { z } from 'zod';
 import { fromZodError } from 'zod-validation-error';
 
+const getWorkflow = async (data: GraphAndWorkflowResponse, templates: Templates) => {
+  if (data.workflow) {
+    // Prefer to load the workflow if it's available - it has more information
+    const parsed = JSON.parse(data.workflow);
+    return await validateWorkflow(parsed, templates, checkImageAccess, checkBoardAccess, checkModelAccess);
+  } else if (data.graph) {
+    // Else we fall back on the graph, using the graphToWorkflow function to convert and do layout
+    const parsed = JSON.parse(data.graph);
+    const workflow = graphToWorkflow(parsed as NonNullableGraph, true);
+    return await validateWorkflow(workflow, templates, checkImageAccess, checkBoardAccess, checkModelAccess);
+  } else {
+    throw new Error('No workflow or graph provided');
+  }
+};
+
 export const addWorkflowLoadRequestedListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: workflowLoadRequested,
-    effect: (action, { dispatch, getState }) => {
+    effect: async (action, { dispatch }) => {
       const log = logger('nodes');
-      const { workflow, asCopy } = action.payload;
-      const nodeTemplates = getState().nodes.templates;
+      const { data, asCopy } = action.payload;
+      const nodeTemplates = $templates.get();
 
       try {
-        const { workflow: validatedWorkflow, warnings } = validateWorkflow(workflow, nodeTemplates);
+        const { workflow, warnings } = await getWorkflow(data, nodeTemplates);
 
         if (asCopy) {
           // If we're loading a copy, we need to remove the ID so that the backend will create a new workflow
-          delete validatedWorkflow.id;
+          delete workflow.id;
         }
 
-        dispatch(workflowLoaded(validatedWorkflow));
+        dispatch(workflowLoaded(workflow));
         if (!warnings.length) {
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('toast.workflowLoaded'),
-                status: 'success',
-              })
-            )
-          );
+          toast({
+            id: 'WORKFLOW_LOADED',
+            title: t('toast.workflowLoaded'),
+            status: 'success',
+          });
         } else {
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('toast.loadedWithWarnings'),
-                status: 'warning',
-              })
-            )
-          );
+          toast({
+            id: 'WORKFLOW_LOADED',
+            title: t('toast.loadedWithWarnings'),
+            status: 'warning',
+          });
+
           warnings.forEach(({ message, ...rest }) => {
             log.warn(rest, message);
           });
@@ -58,54 +72,42 @@ export const addWorkflowLoadRequestedListener = (startAppListening: AppStartList
         if (e instanceof WorkflowVersionError) {
           // The workflow version was not recognized in the valid list of versions
           log.error({ error: parseify(e) }, e.message);
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('nodes.unableToValidateWorkflow'),
-                status: 'error',
-                description: e.message,
-              })
-            )
-          );
+          toast({
+            id: 'UNABLE_TO_VALIDATE_WORKFLOW',
+            title: t('nodes.unableToValidateWorkflow'),
+            status: 'error',
+            description: e.message,
+          });
         } else if (e instanceof WorkflowMigrationError) {
           // There was a problem migrating the workflow to the latest version
           log.error({ error: parseify(e) }, e.message);
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('nodes.unableToValidateWorkflow'),
-                status: 'error',
-                description: e.message,
-              })
-            )
-          );
+          toast({
+            id: 'UNABLE_TO_VALIDATE_WORKFLOW',
+            title: t('nodes.unableToValidateWorkflow'),
+            status: 'error',
+            description: e.message,
+          });
         } else if (e instanceof z.ZodError) {
           // There was a problem validating the workflow itself
           const { message } = fromZodError(e, {
             prefix: t('nodes.workflowValidation'),
           });
           log.error({ error: parseify(e) }, message);
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('nodes.unableToValidateWorkflow'),
-                status: 'error',
-                description: message,
-              })
-            )
-          );
+          toast({
+            id: 'UNABLE_TO_VALIDATE_WORKFLOW',
+            title: t('nodes.unableToValidateWorkflow'),
+            status: 'error',
+            description: message,
+          });
         } else {
           // Some other error occurred
           log.error({ error: parseify(e) }, t('nodes.unknownErrorValidatingWorkflow'));
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('nodes.unableToValidateWorkflow'),
-                status: 'error',
-                description: t('nodes.unknownErrorValidatingWorkflow'),
-              })
-            )
-          );
+          toast({
+            id: 'UNABLE_TO_VALIDATE_WORKFLOW',
+            title: t('nodes.unableToValidateWorkflow'),
+            status: 'error',
+            description: t('nodes.unknownErrorValidatingWorkflow'),
+          });
         }
       }
     },

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

@@ -21,7 +21,8 @@ import { galleryPersistConfig, gallerySlice } from 'features/gallery/store/galle
 import { hrfPersistConfig, hrfSlice } from 'features/hrf/store/hrfSlice';
 import { loraPersistConfig, loraSlice } from 'features/lora/store/loraSlice';
 import { modelManagerV2PersistConfig, modelManagerV2Slice } from 'features/modelManagerV2/store/modelManagerV2Slice';
-import { nodesPersistConfig, nodesSlice } from 'features/nodes/store/nodesSlice';
+import { nodesPersistConfig, nodesSlice, nodesUndoableConfig } from 'features/nodes/store/nodesSlice';
+import { workflowSettingsPersistConfig, workflowSettingsSlice } from 'features/nodes/store/workflowSettingsSlice';
 import { workflowPersistConfig, workflowSlice } from 'features/nodes/store/workflowSlice';
 import { generationPersistConfig, generationSlice } from 'features/parameters/store/generationSlice';
 import { postprocessingPersistConfig, postprocessingSlice } from 'features/parameters/store/postprocessingSlice';
@@ -50,7 +51,7 @@ const allReducers = {
   [canvasSlice.name]: canvasSlice.reducer,
   [gallerySlice.name]: gallerySlice.reducer,
   [generationSlice.name]: generationSlice.reducer,
-  [nodesSlice.name]: nodesSlice.reducer,
+  [nodesSlice.name]: undoable(nodesSlice.reducer, nodesUndoableConfig),
   [postprocessingSlice.name]: postprocessingSlice.reducer,
   [systemSlice.name]: systemSlice.reducer,
   [configSlice.name]: configSlice.reducer,
@@ -66,6 +67,7 @@ const allReducers = {
   [workflowSlice.name]: workflowSlice.reducer,
   [hrfSlice.name]: hrfSlice.reducer,
   [controlLayersSlice.name]: undoable(controlLayersSlice.reducer, controlLayersUndoableConfig),
+  [workflowSettingsSlice.name]: workflowSettingsSlice.reducer,
   [api.reducerPath]: api.reducer,
 };
 
@@ -111,6 +113,7 @@ const persistConfigs: { [key in keyof typeof allReducers]?: PersistConfig } = {
   [modelManagerV2PersistConfig.name]: modelManagerV2PersistConfig,
   [hrfPersistConfig.name]: hrfPersistConfig,
   [controlLayersPersistConfig.name]: controlLayersPersistConfig,
+  [workflowSettingsPersistConfig.name]: workflowSettingsPersistConfig,
 };
 
 const unserialize: UnserializeFunction = (data, key) => {

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

@@ -74,6 +74,7 @@ export type AppConfig = {
   maxUpscalePixels?: number;
   metadataFetchDebounce?: number;
   workflowFetchDebounce?: number;
+  isLocal?: boolean;
   sd: {
     defaultModel?: string;
     disabledControlNetModels: string[];

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

@@ -1,11 +1,10 @@
-import { useAppToaster } from 'app/components/Toaster';
 import { useImageUrlToBlob } from 'common/hooks/useImageUrlToBlob';
 import { copyBlobToClipboard } from 'features/system/util/copyBlobToClipboard';
+import { toast } from 'features/toast/toast';
 import { useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
 
 export const useCopyImageToClipboard = () => {
-  const toaster = useAppToaster();
   const { t } = useTranslation();
   const imageUrlToBlob = useImageUrlToBlob();
 
@@ -16,12 +15,11 @@ export const useCopyImageToClipboard = () => {
   const copyImageToClipboard = useCallback(
     async (image_url: string) => {
       if (!isClipboardAPIAvailable) {
-        toaster({
+        toast({
+          id: 'PROBLEM_COPYING_IMAGE',
           title: t('toast.problemCopyingImage'),
           description: "Your browser doesn't support the Clipboard API.",
           status: 'error',
-          duration: 2500,
-          isClosable: true,
         });
       }
       try {
@@ -33,23 +31,21 @@ export const useCopyImageToClipboard = () => {
 
         copyBlobToClipboard(blob);
 
-        toaster({
+        toast({
+          id: 'IMAGE_COPIED',
           title: t('toast.imageCopied'),
           status: 'success',
-          duration: 2500,
-          isClosable: true,
         });
       } catch (err) {
-        toaster({
+        toast({
+          id: 'PROBLEM_COPYING_IMAGE',
           title: t('toast.problemCopyingImage'),
           description: String(err),
           status: 'error',
-          duration: 2500,
-          isClosable: true,
         });
       }
     },
-    [imageUrlToBlob, isClipboardAPIAvailable, t, toaster]
+    [imageUrlToBlob, isClipboardAPIAvailable, t]
   );
 
   return { isClipboardAPIAvailable, copyImageToClipboard };

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

@@ -1,13 +1,12 @@
 import { useStore } from '@nanostores/react';
-import { useAppToaster } from 'app/components/Toaster';
 import { $authToken } from 'app/store/nanostores/authToken';
 import { useAppDispatch } from 'app/store/storeHooks';
 import { imageDownloaded } from 'features/gallery/store/actions';
+import { toast } from 'features/toast/toast';
 import { useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 
 export const useDownloadImage = () => {
-  const toaster = useAppToaster();
   const { t } = useTranslation();
   const dispatch = useAppDispatch();
   const authToken = useStore($authToken);
@@ -37,16 +36,15 @@ export const useDownloadImage = () => {
         window.URL.revokeObjectURL(url);
         dispatch(imageDownloaded());
       } catch (err) {
-        toaster({
+        toast({
+          id: 'PROBLEM_DOWNLOADING_IMAGE',
           title: t('toast.problemDownloadingImage'),
           description: String(err),
           status: 'error',
-          duration: 2500,
-          isClosable: true,
         });
       }
     },
-    [t, toaster, dispatch, authToken]
+    [t, dispatch, authToken]
   );
 
   return { downloadImage };

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

@@ -1,6 +1,6 @@
-import { useAppToaster } from 'app/components/Toaster';
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppSelector } from 'app/store/storeHooks';
+import { toast } from 'features/toast/toast';
 import { activeTabNameSelector } from 'features/ui/store/uiSelectors';
 import { useCallback, useEffect, useState } from 'react';
 import type { Accept, FileRejection } from 'react-dropzone';
@@ -26,7 +26,6 @@ const selectPostUploadAction = createMemoizedSelector(activeTabNameSelector, (ac
 
 export const useFullscreenDropzone = () => {
   const { t } = useTranslation();
-  const toaster = useAppToaster();
   const postUploadAction = useAppSelector(selectPostUploadAction);
   const autoAddBoardId = useAppSelector((s) => s.gallery.autoAddBoardId);
   const [isHandlingUpload, setIsHandlingUpload] = useState<boolean>(false);
@@ -37,13 +36,14 @@ export const useFullscreenDropzone = () => {
     (rejection: FileRejection) => {
       setIsHandlingUpload(true);
 
-      toaster({
+      toast({
+        id: 'UPLOAD_FAILED',
         title: t('toast.uploadFailed'),
         description: rejection.errors.map((error) => error.message).join('\n'),
         status: 'error',
       });
     },
-    [t, toaster]
+    [t]
   );
 
   const fileAcceptedCallback = useCallback(
@@ -62,7 +62,8 @@ export const useFullscreenDropzone = () => {
   const onDrop = useCallback(
     (acceptedFiles: Array<File>, fileRejections: Array<FileRejection>) => {
       if (fileRejections.length > 1) {
-        toaster({
+        toast({
+          id: 'UPLOAD_FAILED',
           title: t('toast.uploadFailed'),
           description: t('toast.uploadFailedInvalidUploadDesc'),
           status: 'error',
@@ -78,7 +79,7 @@ export const useFullscreenDropzone = () => {
         fileAcceptedCallback(file);
       });
     },
-    [t, toaster, fileAcceptedCallback, fileRejectionCallback]
+    [t, fileAcceptedCallback, fileRejectionCallback]
   );
 
   const onDragOver = useCallback(() => {

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

@@ -1,3 +1,4 @@
+import { useStore } from '@nanostores/react';
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppSelector } from 'app/store/storeHooks';
 import {
@@ -9,13 +10,16 @@ import { selectControlLayersSlice } from 'features/controlLayers/store/controlLa
 import type { Layer } from 'features/controlLayers/store/types';
 import { selectDynamicPromptsSlice } from 'features/dynamicPrompts/store/dynamicPromptsSlice';
 import { getShouldProcessPrompt } from 'features/dynamicPrompts/util/getShouldProcessPrompt';
-import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
+import { $templates, selectNodesSlice } from 'features/nodes/store/nodesSlice';
+import type { Templates } from 'features/nodes/store/types';
+import { selectWorkflowSettingsSlice } from 'features/nodes/store/workflowSettingsSlice';
 import { isInvocationNode } from 'features/nodes/types/invocation';
 import { selectGenerationSlice } from 'features/parameters/store/generationSlice';
 import { selectSystemSlice } from 'features/system/store/systemSlice';
 import { activeTabNameSelector } from 'features/ui/store/uiSelectors';
 import i18n from 'i18next';
 import { forEach, upperFirst } from 'lodash-es';
+import { useMemo } from 'react';
 import { getConnectedEdges } from 'reactflow';
 
 const LAYER_TYPE_TO_TKEY: Record<Layer['type'], string> = {
@@ -25,199 +29,208 @@ const LAYER_TYPE_TO_TKEY: Record<Layer['type'], string> = {
   regional_guidance_layer: 'controlLayers.regionalGuidance',
 };
 
-const selector = createMemoizedSelector(
-  [
-    selectControlAdaptersSlice,
-    selectGenerationSlice,
-    selectSystemSlice,
-    selectNodesSlice,
-    selectDynamicPromptsSlice,
-    selectControlLayersSlice,
-    activeTabNameSelector,
-  ],
-  (controlAdapters, generation, system, nodes, dynamicPrompts, controlLayers, activeTabName) => {
-    const { model } = generation;
-    const { size } = controlLayers.present;
-    const { positivePrompt } = controlLayers.present;
+const createSelector = (templates: Templates) =>
+  createMemoizedSelector(
+    [
+      selectControlAdaptersSlice,
+      selectGenerationSlice,
+      selectSystemSlice,
+      selectNodesSlice,
+      selectWorkflowSettingsSlice,
+      selectDynamicPromptsSlice,
+      selectControlLayersSlice,
+      activeTabNameSelector,
+    ],
+    (controlAdapters, generation, system, nodes, workflowSettings, dynamicPrompts, controlLayers, activeTabName) => {
+      const { model } = generation;
+      const { size } = controlLayers.present;
+      const { positivePrompt } = controlLayers.present;
 
-    const { isConnected } = system;
+      const { isConnected } = system;
 
-    const reasons: { prefix?: string; content: string }[] = [];
+      const reasons: { prefix?: string; content: string }[] = [];
 
-    // Cannot generate if not connected
-    if (!isConnected) {
-      reasons.push({ content: i18n.t('parameters.invoke.systemDisconnected') });
-    }
+      // Cannot generate if not connected
+      if (!isConnected) {
+        reasons.push({ content: i18n.t('parameters.invoke.systemDisconnected') });
+      }
 
-    if (activeTabName === 'workflows') {
-      if (nodes.shouldValidateGraph) {
-        if (!nodes.nodes.length) {
-          reasons.push({ content: i18n.t('parameters.invoke.noNodesInGraph') });
+      if (activeTabName === 'workflows') {
+        if (workflowSettings.shouldValidateGraph) {
+          if (!nodes.nodes.length) {
+            reasons.push({ content: i18n.t('parameters.invoke.noNodesInGraph') });
+          }
+
+          nodes.nodes.forEach((node) => {
+            if (!isInvocationNode(node)) {
+              return;
+            }
+
+            const nodeTemplate = templates[node.data.type];
+
+            if (!nodeTemplate) {
+              // Node type not found
+              reasons.push({ content: i18n.t('parameters.invoke.missingNodeTemplate') });
+              return;
+            }
+
+            const connectedEdges = getConnectedEdges([node], nodes.edges);
+
+            forEach(node.data.inputs, (field) => {
+              const fieldTemplate = nodeTemplate.inputs[field.name];
+              const hasConnection = connectedEdges.some(
+                (edge) => edge.target === node.id && edge.targetHandle === field.name
+              );
+
+              if (!fieldTemplate) {
+                reasons.push({ content: i18n.t('parameters.invoke.missingFieldTemplate') });
+                return;
+              }
+
+              if (fieldTemplate.required && field.value === undefined && !hasConnection) {
+                reasons.push({
+                  content: i18n.t('parameters.invoke.missingInputForField', {
+                    nodeLabel: node.data.label || nodeTemplate.title,
+                    fieldLabel: field.label || fieldTemplate.title,
+                  }),
+                });
+                return;
+              }
+            });
+          });
+        }
+      } else {
+        if (dynamicPrompts.prompts.length === 0 && getShouldProcessPrompt(positivePrompt)) {
+          reasons.push({ content: i18n.t('parameters.invoke.noPrompts') });
         }
 
-        nodes.nodes.forEach((node) => {
-          if (!isInvocationNode(node)) {
-            return;
-          }
+        if (!model) {
+          reasons.push({ content: i18n.t('parameters.invoke.noModelSelected') });
+        }
 
-          const nodeTemplate = nodes.templates[node.data.type];
-
-          if (!nodeTemplate) {
-            // Node type not found
-            reasons.push({ content: i18n.t('parameters.invoke.missingNodeTemplate') });
-            return;
-          }
-
-          const connectedEdges = getConnectedEdges([node], nodes.edges);
-
-          forEach(node.data.inputs, (field) => {
-            const fieldTemplate = nodeTemplate.inputs[field.name];
-            const hasConnection = connectedEdges.some(
-              (edge) => edge.target === node.id && edge.targetHandle === field.name
-            );
-
-            if (!fieldTemplate) {
-              reasons.push({ content: i18n.t('parameters.invoke.missingFieldTemplate') });
-              return;
-            }
-
-            if (fieldTemplate.required && field.value === undefined && !hasConnection) {
-              reasons.push({
-                content: i18n.t('parameters.invoke.missingInputForField', {
-                  nodeLabel: node.data.label || nodeTemplate.title,
-                  fieldLabel: field.label || fieldTemplate.title,
-                }),
-              });
-              return;
-            }
-          });
-        });
-      }
-    } else {
-      if (dynamicPrompts.prompts.length === 0 && getShouldProcessPrompt(positivePrompt)) {
-        reasons.push({ content: i18n.t('parameters.invoke.noPrompts') });
-      }
-
-      if (!model) {
-        reasons.push({ content: i18n.t('parameters.invoke.noModelSelected') });
-      }
-
-      if (activeTabName === 'generation') {
-        // Handling for generation tab
-        controlLayers.present.layers
-          .filter((l) => l.isEnabled)
-          .forEach((l, i) => {
-            const layerLiteral = i18n.t('controlLayers.layers_one');
-            const layerNumber = i + 1;
-            const layerType = i18n.t(LAYER_TYPE_TO_TKEY[l.type]);
-            const prefix = `${layerLiteral} #${layerNumber} (${layerType})`;
-            const problems: string[] = [];
-            if (l.type === 'control_adapter_layer') {
-              // Must have model
-              if (!l.controlAdapter.model) {
-                problems.push(i18n.t('parameters.invoke.layer.controlAdapterNoModelSelected'));
-              }
-              // Model base must match
-              if (l.controlAdapter.model?.base !== model?.base) {
-                problems.push(i18n.t('parameters.invoke.layer.controlAdapterIncompatibleBaseModel'));
-              }
-              // Must have a control image OR, if it has a processor, it must have a processed image
-              if (!l.controlAdapter.image) {
-                problems.push(i18n.t('parameters.invoke.layer.controlAdapterNoImageSelected'));
-              } else if (l.controlAdapter.processorConfig && !l.controlAdapter.processedImage) {
-                problems.push(i18n.t('parameters.invoke.layer.controlAdapterImageNotProcessed'));
-              }
-              // T2I Adapters require images have dimensions that are multiples of 64
-              if (l.controlAdapter.type === 't2i_adapter' && (size.width % 64 !== 0 || size.height % 64 !== 0)) {
-                problems.push(i18n.t('parameters.invoke.layer.t2iAdapterIncompatibleDimensions'));
-              }
-            }
-
-            if (l.type === 'ip_adapter_layer') {
-              // Must have model
-              if (!l.ipAdapter.model) {
-                problems.push(i18n.t('parameters.invoke.layer.ipAdapterNoModelSelected'));
-              }
-              // Model base must match
-              if (l.ipAdapter.model?.base !== model?.base) {
-                problems.push(i18n.t('parameters.invoke.layer.ipAdapterIncompatibleBaseModel'));
-              }
-              // Must have an image
-              if (!l.ipAdapter.image) {
-                problems.push(i18n.t('parameters.invoke.layer.ipAdapterNoImageSelected'));
-              }
-            }
-
-            if (l.type === 'initial_image_layer') {
-              // Must have an image
-              if (!l.image) {
-                problems.push(i18n.t('parameters.invoke.layer.initialImageNoImageSelected'));
-              }
-            }
-
-            if (l.type === 'regional_guidance_layer') {
-              // Must have a region
-              if (l.maskObjects.length === 0) {
-                problems.push(i18n.t('parameters.invoke.layer.rgNoRegion'));
-              }
-              // Must have at least 1 prompt or IP Adapter
-              if (l.positivePrompt === null && l.negativePrompt === null && l.ipAdapters.length === 0) {
-                problems.push(i18n.t('parameters.invoke.layer.rgNoPromptsOrIPAdapters'));
-              }
-              l.ipAdapters.forEach((ipAdapter) => {
+        if (activeTabName === 'generation') {
+          // Handling for generation tab
+          controlLayers.present.layers
+            .filter((l) => l.isEnabled)
+            .forEach((l, i) => {
+              const layerLiteral = i18n.t('controlLayers.layers_one');
+              const layerNumber = i + 1;
+              const layerType = i18n.t(LAYER_TYPE_TO_TKEY[l.type]);
+              const prefix = `${layerLiteral} #${layerNumber} (${layerType})`;
+              const problems: string[] = [];
+              if (l.type === 'control_adapter_layer') {
                 // Must have model
-                if (!ipAdapter.model) {
+                if (!l.controlAdapter.model) {
+                  problems.push(i18n.t('parameters.invoke.layer.controlAdapterNoModelSelected'));
+                }
+                // Model base must match
+                if (l.controlAdapter.model?.base !== model?.base) {
+                  problems.push(i18n.t('parameters.invoke.layer.controlAdapterIncompatibleBaseModel'));
+                }
+                // Must have a control image OR, if it has a processor, it must have a processed image
+                if (!l.controlAdapter.image) {
+                  problems.push(i18n.t('parameters.invoke.layer.controlAdapterNoImageSelected'));
+                } else if (l.controlAdapter.processorConfig && !l.controlAdapter.processedImage) {
+                  problems.push(i18n.t('parameters.invoke.layer.controlAdapterImageNotProcessed'));
+                }
+                // T2I Adapters require images have dimensions that are multiples of 64 (SD1.5) or 32 (SDXL)
+                if (l.controlAdapter.type === 't2i_adapter') {
+                  const multiple = model?.base === 'sdxl' ? 32 : 64;
+                  if (size.width % multiple !== 0 || size.height % multiple !== 0) {
+                    problems.push(i18n.t('parameters.invoke.layer.t2iAdapterIncompatibleDimensions', { multiple }));
+                  }
+                }
+              }
+
+              if (l.type === 'ip_adapter_layer') {
+                // Must have model
+                if (!l.ipAdapter.model) {
                   problems.push(i18n.t('parameters.invoke.layer.ipAdapterNoModelSelected'));
                 }
                 // Model base must match
-                if (ipAdapter.model?.base !== model?.base) {
+                if (l.ipAdapter.model?.base !== model?.base) {
                   problems.push(i18n.t('parameters.invoke.layer.ipAdapterIncompatibleBaseModel'));
                 }
                 // Must have an image
-                if (!ipAdapter.image) {
+                if (!l.ipAdapter.image) {
                   problems.push(i18n.t('parameters.invoke.layer.ipAdapterNoImageSelected'));
                 }
-              });
-            }
+              }
 
-            if (problems.length) {
-              const content = upperFirst(problems.join(', '));
-              reasons.push({ prefix, content });
-            }
-          });
-      } else {
-        // Handling for all other tabs
-        selectControlAdapterAll(controlAdapters)
-          .filter((ca) => ca.isEnabled)
-          .forEach((ca, i) => {
-            if (!ca.isEnabled) {
-              return;
-            }
+              if (l.type === 'initial_image_layer') {
+                // Must have an image
+                if (!l.image) {
+                  problems.push(i18n.t('parameters.invoke.layer.initialImageNoImageSelected'));
+                }
+              }
 
-            if (!ca.model) {
-              reasons.push({ content: i18n.t('parameters.invoke.noModelForControlAdapter', { number: i + 1 }) });
-            } else if (ca.model.base !== model?.base) {
-              // This should never happen, just a sanity check
-              reasons.push({
-                content: i18n.t('parameters.invoke.incompatibleBaseModelForControlAdapter', { number: i + 1 }),
-              });
-            }
+              if (l.type === 'regional_guidance_layer') {
+                // Must have a region
+                if (l.maskObjects.length === 0) {
+                  problems.push(i18n.t('parameters.invoke.layer.rgNoRegion'));
+                }
+                // Must have at least 1 prompt or IP Adapter
+                if (l.positivePrompt === null && l.negativePrompt === null && l.ipAdapters.length === 0) {
+                  problems.push(i18n.t('parameters.invoke.layer.rgNoPromptsOrIPAdapters'));
+                }
+                l.ipAdapters.forEach((ipAdapter) => {
+                  // Must have model
+                  if (!ipAdapter.model) {
+                    problems.push(i18n.t('parameters.invoke.layer.ipAdapterNoModelSelected'));
+                  }
+                  // Model base must match
+                  if (ipAdapter.model?.base !== model?.base) {
+                    problems.push(i18n.t('parameters.invoke.layer.ipAdapterIncompatibleBaseModel'));
+                  }
+                  // Must have an image
+                  if (!ipAdapter.image) {
+                    problems.push(i18n.t('parameters.invoke.layer.ipAdapterNoImageSelected'));
+                  }
+                });
+              }
 
-            if (
-              !ca.controlImage ||
-              (isControlNetOrT2IAdapter(ca) && !ca.processedControlImage && ca.processorType !== 'none')
-            ) {
-              reasons.push({ content: i18n.t('parameters.invoke.noControlImageForControlAdapter', { number: i + 1 }) });
-            }
-          });
+              if (problems.length) {
+                const content = upperFirst(problems.join(', '));
+                reasons.push({ prefix, content });
+              }
+            });
+        } else {
+          // Handling for all other tabs
+          selectControlAdapterAll(controlAdapters)
+            .filter((ca) => ca.isEnabled)
+            .forEach((ca, i) => {
+              if (!ca.isEnabled) {
+                return;
+              }
+
+              if (!ca.model) {
+                reasons.push({ content: i18n.t('parameters.invoke.noModelForControlAdapter', { number: i + 1 }) });
+              } else if (ca.model.base !== model?.base) {
+                // This should never happen, just a sanity check
+                reasons.push({
+                  content: i18n.t('parameters.invoke.incompatibleBaseModelForControlAdapter', { number: i + 1 }),
+                });
+              }
+
+              if (
+                !ca.controlImage ||
+                (isControlNetOrT2IAdapter(ca) && !ca.processedControlImage && ca.processorType !== 'none')
+              ) {
+                reasons.push({
+                  content: i18n.t('parameters.invoke.noControlImageForControlAdapter', { number: i + 1 }),
+                });
+              }
+            });
+        }
       }
-    }
 
-    return { isReady: !reasons.length, reasons };
-  }
-);
+      return { isReady: !reasons.length, reasons };
+    }
+  );
 
 export const useIsReadyToEnqueue = () => {
+  const templates = useStore($templates);
+  const selector = useMemo(() => createSelector(templates), [templates]);
   const value = useAppSelector(selector);
   return value;
 };

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

@@ -1,6 +0,0 @@
-import { createStandaloneToast, theme, TOAST_OPTIONS } from '@invoke-ai/ui-library';
-
-export const { toast } = createStandaloneToast({
-  theme: theme,
-  defaultOptions: TOAST_OPTIONS.defaultOptions,
-});

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

@@ -5,22 +5,7 @@ import type {
   ParameterT2IAdapterModel,
 } from 'features/parameters/types/parameterSchemas';
 import type { components } from 'services/api/schema';
-import type {
-  CannyImageProcessorInvocation,
-  ColorMapImageProcessorInvocation,
-  ContentShuffleImageProcessorInvocation,
-  DepthAnythingImageProcessorInvocation,
-  DWOpenposeImageProcessorInvocation,
-  HedImageProcessorInvocation,
-  LineartAnimeImageProcessorInvocation,
-  LineartImageProcessorInvocation,
-  MediapipeFaceProcessorInvocation,
-  MidasDepthImageProcessorInvocation,
-  MlsdImageProcessorInvocation,
-  NormalbaeImageProcessorInvocation,
-  PidiImageProcessorInvocation,
-  ZoeDepthImageProcessorInvocation,
-} from 'services/api/types';
+import type { Invocation } from 'services/api/types';
 import type { O } from 'ts-toolbelt';
 import { z } from 'zod';
 
@@ -28,20 +13,20 @@ import { z } from 'zod';
  * Any ControlNet processor node
  */
 export type ControlAdapterProcessorNode =
-  | CannyImageProcessorInvocation
-  | ColorMapImageProcessorInvocation
-  | ContentShuffleImageProcessorInvocation
-  | DepthAnythingImageProcessorInvocation
-  | HedImageProcessorInvocation
-  | LineartAnimeImageProcessorInvocation
-  | LineartImageProcessorInvocation
-  | MediapipeFaceProcessorInvocation
-  | MidasDepthImageProcessorInvocation
-  | MlsdImageProcessorInvocation
-  | NormalbaeImageProcessorInvocation
-  | DWOpenposeImageProcessorInvocation
-  | PidiImageProcessorInvocation
-  | ZoeDepthImageProcessorInvocation;
+  | Invocation<'canny_image_processor'>
+  | Invocation<'color_map_image_processor'>
+  | Invocation<'content_shuffle_image_processor'>
+  | Invocation<'depth_anything_image_processor'>
+  | Invocation<'hed_image_processor'>
+  | Invocation<'lineart_anime_image_processor'>
+  | Invocation<'lineart_image_processor'>
+  | Invocation<'mediapipe_face_processor'>
+  | Invocation<'midas_depth_image_processor'>
+  | Invocation<'mlsd_image_processor'>
+  | Invocation<'normalbae_image_processor'>
+  | Invocation<'dw_openpose_image_processor'>
+  | Invocation<'pidi_image_processor'>
+  | Invocation<'zoe_depth_image_processor'>;
 
 /**
  * Any ControlNet processor type
@@ -71,7 +56,7 @@ export const isControlAdapterProcessorType = (v: unknown): v is ControlAdapterPr
  * The Canny processor node, with parameters flagged as required
  */
 export type RequiredCannyImageProcessorInvocation = O.Required<
-  CannyImageProcessorInvocation,
+  Invocation<'canny_image_processor'>,
   'type' | 'low_threshold' | 'high_threshold' | 'image_resolution' | 'detect_resolution'
 >;
 
@@ -79,7 +64,7 @@ export type RequiredCannyImageProcessorInvocation = O.Required<
  * The Color Map processor node, with parameters flagged as required
  */
 export type RequiredColorMapImageProcessorInvocation = O.Required<
-  ColorMapImageProcessorInvocation,
+  Invocation<'color_map_image_processor'>,
   'type' | 'color_map_tile_size'
 >;
 
@@ -87,7 +72,7 @@ export type RequiredColorMapImageProcessorInvocation = O.Required<
  * The ContentShuffle processor node, with parameters flagged as required
  */
 export type RequiredContentShuffleImageProcessorInvocation = O.Required<
-  ContentShuffleImageProcessorInvocation,
+  Invocation<'content_shuffle_image_processor'>,
   'type' | 'detect_resolution' | 'image_resolution' | 'w' | 'h' | 'f'
 >;
 
@@ -95,7 +80,7 @@ export type RequiredContentShuffleImageProcessorInvocation = O.Required<
  * The DepthAnything processor node, with parameters flagged as required
  */
 export type RequiredDepthAnythingImageProcessorInvocation = O.Required<
-  DepthAnythingImageProcessorInvocation,
+  Invocation<'depth_anything_image_processor'>,
   'type' | 'model_size' | 'resolution' | 'offload'
 >;
 
@@ -108,7 +93,7 @@ export const isDepthAnythingModelSize = (v: unknown): v is DepthAnythingModelSiz
  * The HED processor node, with parameters flagged as required
  */
 export type RequiredHedImageProcessorInvocation = O.Required<
-  HedImageProcessorInvocation,
+  Invocation<'hed_image_processor'>,
   'type' | 'detect_resolution' | 'image_resolution' | 'scribble'
 >;
 
@@ -116,7 +101,7 @@ export type RequiredHedImageProcessorInvocation = O.Required<
  * The Lineart Anime processor node, with parameters flagged as required
  */
 export type RequiredLineartAnimeImageProcessorInvocation = O.Required<
-  LineartAnimeImageProcessorInvocation,
+  Invocation<'lineart_anime_image_processor'>,
   'type' | 'detect_resolution' | 'image_resolution'
 >;
 
@@ -124,7 +109,7 @@ export type RequiredLineartAnimeImageProcessorInvocation = O.Required<
  * The Lineart processor node, with parameters flagged as required
  */
 export type RequiredLineartImageProcessorInvocation = O.Required<
-  LineartImageProcessorInvocation,
+  Invocation<'lineart_image_processor'>,
   'type' | 'detect_resolution' | 'image_resolution' | 'coarse'
 >;
 
@@ -132,7 +117,7 @@ export type RequiredLineartImageProcessorInvocation = O.Required<
  * The MediapipeFace processor node, with parameters flagged as required
  */
 export type RequiredMediapipeFaceProcessorInvocation = O.Required<
-  MediapipeFaceProcessorInvocation,
+  Invocation<'mediapipe_face_processor'>,
   'type' | 'max_faces' | 'min_confidence' | 'image_resolution' | 'detect_resolution'
 >;
 
@@ -140,7 +125,7 @@ export type RequiredMediapipeFaceProcessorInvocation = O.Required<
  * The MidasDepth processor node, with parameters flagged as required
  */
 export type RequiredMidasDepthImageProcessorInvocation = O.Required<
-  MidasDepthImageProcessorInvocation,
+  Invocation<'midas_depth_image_processor'>,
   'type' | 'a_mult' | 'bg_th' | 'image_resolution' | 'detect_resolution'
 >;
 
@@ -148,7 +133,7 @@ export type RequiredMidasDepthImageProcessorInvocation = O.Required<
  * The MLSD processor node, with parameters flagged as required
  */
 export type RequiredMlsdImageProcessorInvocation = O.Required<
-  MlsdImageProcessorInvocation,
+  Invocation<'mlsd_image_processor'>,
   'type' | 'detect_resolution' | 'image_resolution' | 'thr_v' | 'thr_d'
 >;
 
@@ -156,7 +141,7 @@ export type RequiredMlsdImageProcessorInvocation = O.Required<
  * The NormalBae processor node, with parameters flagged as required
  */
 export type RequiredNormalbaeImageProcessorInvocation = O.Required<
-  NormalbaeImageProcessorInvocation,
+  Invocation<'normalbae_image_processor'>,
   'type' | 'detect_resolution' | 'image_resolution'
 >;
 
@@ -164,7 +149,7 @@ export type RequiredNormalbaeImageProcessorInvocation = O.Required<
  * The DW Openpose processor node, with parameters flagged as required
  */
 export type RequiredDWOpenposeImageProcessorInvocation = O.Required<
-  DWOpenposeImageProcessorInvocation,
+  Invocation<'dw_openpose_image_processor'>,
   'type' | 'image_resolution' | 'draw_body' | 'draw_face' | 'draw_hands'
 >;
 
@@ -172,14 +157,14 @@ export type RequiredDWOpenposeImageProcessorInvocation = O.Required<
  * The Pidi processor node, with parameters flagged as required
  */
 export type RequiredPidiImageProcessorInvocation = O.Required<
-  PidiImageProcessorInvocation,
+  Invocation<'pidi_image_processor'>,
   'type' | 'detect_resolution' | 'image_resolution' | 'safe' | 'scribble'
 >;
 
 /**
  * The ZoeDepth processor node, with parameters flagged as required
  */
-export type RequiredZoeDepthImageProcessorInvocation = O.Required<ZoeDepthImageProcessorInvocation, 'type'>;
+export type RequiredZoeDepthImageProcessorInvocation = O.Required<Invocation<'zoe_depth_image_processor'>, 'type'>;
 
 /**
  * Any ControlNet Processor node, with its parameters flagged as required

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

@@ -4,7 +4,7 @@ import { CALayerControlAdapterWrapper } from 'features/controlLayers/components/
 import { LayerDeleteButton } from 'features/controlLayers/components/LayerCommon/LayerDeleteButton';
 import { LayerMenu } from 'features/controlLayers/components/LayerCommon/LayerMenu';
 import { LayerTitle } from 'features/controlLayers/components/LayerCommon/LayerTitle';
-import { LayerVisibilityToggle } from 'features/controlLayers/components/LayerCommon/LayerVisibilityToggle';
+import { LayerIsEnabledToggle } from 'features/controlLayers/components/LayerCommon/LayerVisibilityToggle';
 import { LayerWrapper } from 'features/controlLayers/components/LayerCommon/LayerWrapper';
 import { layerSelected, selectCALayerOrThrow } from 'features/controlLayers/store/controlLayersSlice';
 import { memo, useCallback } from 'react';
@@ -26,7 +26,7 @@ export const CALayer = memo(({ layerId }: Props) => {
   return (
     <LayerWrapper onClick={onClick} borderColor={isSelected ? 'base.400' : 'base.800'}>
       <Flex gap={3} alignItems="center" p={3} cursor="pointer" onDoubleClick={onToggle}>
-        <LayerVisibilityToggle layerId={layerId} />
+        <LayerIsEnabledToggle layerId={layerId} />
         <LayerTitle type="control_adapter_layer" />
         <Spacer />
         <CALayerOpacity layerId={layerId} />

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

@@ -5,7 +5,7 @@ import { InitialImagePreview } from 'features/controlLayers/components/IILayer/I
 import { LayerDeleteButton } from 'features/controlLayers/components/LayerCommon/LayerDeleteButton';
 import { LayerMenu } from 'features/controlLayers/components/LayerCommon/LayerMenu';
 import { LayerTitle } from 'features/controlLayers/components/LayerCommon/LayerTitle';
-import { LayerVisibilityToggle } from 'features/controlLayers/components/LayerCommon/LayerVisibilityToggle';
+import { LayerIsEnabledToggle } from 'features/controlLayers/components/LayerCommon/LayerVisibilityToggle';
 import { LayerWrapper } from 'features/controlLayers/components/LayerCommon/LayerWrapper';
 import {
   iiLayerDenoisingStrengthChanged,
@@ -66,7 +66,7 @@ export const IILayer = memo(({ layerId }: Props) => {
   return (
     <LayerWrapper onClick={onClick} borderColor={layer.isSelected ? 'base.400' : 'base.800'}>
       <Flex gap={3} alignItems="center" p={3} cursor="pointer" onDoubleClick={onToggle}>
-        <LayerVisibilityToggle layerId={layerId} />
+        <LayerIsEnabledToggle layerId={layerId} />
         <LayerTitle type="initial_image_layer" />
         <Spacer />
         <IILayerOpacity layerId={layerId} />

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

@@ -3,7 +3,7 @@ import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { IPALayerIPAdapterWrapper } from 'features/controlLayers/components/IPALayer/IPALayerIPAdapterWrapper';
 import { LayerDeleteButton } from 'features/controlLayers/components/LayerCommon/LayerDeleteButton';
 import { LayerTitle } from 'features/controlLayers/components/LayerCommon/LayerTitle';
-import { LayerVisibilityToggle } from 'features/controlLayers/components/LayerCommon/LayerVisibilityToggle';
+import { LayerIsEnabledToggle } from 'features/controlLayers/components/LayerCommon/LayerVisibilityToggle';
 import { LayerWrapper } from 'features/controlLayers/components/LayerCommon/LayerWrapper';
 import { layerSelected, selectIPALayerOrThrow } from 'features/controlLayers/store/controlLayersSlice';
 import { memo, useCallback } from 'react';
@@ -22,7 +22,7 @@ export const IPALayer = memo(({ layerId }: Props) => {
   return (
     <LayerWrapper onClick={onClick} borderColor={isSelected ? 'base.400' : 'base.800'}>
       <Flex gap={3} alignItems="center" p={3} cursor="pointer" onDoubleClick={onToggle}>
-        <LayerVisibilityToggle layerId={layerId} />
+        <LayerIsEnabledToggle layerId={layerId} />
         <LayerTitle type="ip_adapter_layer" />
         <Spacer />
         <LayerDeleteButton layerId={layerId} />

invokeai/frontend/web/src/features/controlLayers/components/LayerCommon/LayerVisibilityToggle.tsx

@@ -1,8 +1,8 @@
 import { IconButton } from '@invoke-ai/ui-library';
 import { useAppDispatch } from 'app/store/storeHooks';
 import { stopPropagation } from 'common/util/stopPropagation';
-import { useLayerIsVisible } from 'features/controlLayers/hooks/layerStateHooks';
-import { layerVisibilityToggled } from 'features/controlLayers/store/controlLayersSlice';
+import { useLayerIsEnabled } from 'features/controlLayers/hooks/layerStateHooks';
+import { layerIsEnabledToggled } from 'features/controlLayers/store/controlLayersSlice';
 import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 import { PiCheckBold } from 'react-icons/pi';
@@ -11,21 +11,21 @@ type Props = {
   layerId: string;
 };
 
-export const LayerVisibilityToggle = memo(({ layerId }: Props) => {
+export const LayerIsEnabledToggle = memo(({ layerId }: Props) => {
   const { t } = useTranslation();
   const dispatch = useAppDispatch();
-  const isVisible = useLayerIsVisible(layerId);
+  const isEnabled = useLayerIsEnabled(layerId);
   const onClick = useCallback(() => {
-    dispatch(layerVisibilityToggled(layerId));
+    dispatch(layerIsEnabledToggled(layerId));
   }, [dispatch, layerId]);
 
   return (
     <IconButton
       size="sm"
-      aria-label={t('controlLayers.toggleVisibility')}
-      tooltip={t('controlLayers.toggleVisibility')}
+      aria-label={t(isEnabled ? 'common.enabled' : 'common.disabled')}
+      tooltip={t(isEnabled ? 'common.enabled' : 'common.disabled')}
       variant="outline"
-      icon={isVisible ? <PiCheckBold /> : undefined}
+      icon={isEnabled ? <PiCheckBold /> : undefined}
       onClick={onClick}
       colorScheme="base"
       onDoubleClick={stopPropagation} // double click expands the layer
@@ -33,4 +33,4 @@ export const LayerVisibilityToggle = memo(({ layerId }: Props) => {
   );
 });
 
-LayerVisibilityToggle.displayName = 'LayerVisibilityToggle';
+LayerIsEnabledToggle.displayName = 'LayerVisibilityToggle';

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

@@ -6,7 +6,7 @@ import { AddPromptButtons } from 'features/controlLayers/components/AddPromptBut
 import { LayerDeleteButton } from 'features/controlLayers/components/LayerCommon/LayerDeleteButton';
 import { LayerMenu } from 'features/controlLayers/components/LayerCommon/LayerMenu';
 import { LayerTitle } from 'features/controlLayers/components/LayerCommon/LayerTitle';
-import { LayerVisibilityToggle } from 'features/controlLayers/components/LayerCommon/LayerVisibilityToggle';
+import { LayerIsEnabledToggle } from 'features/controlLayers/components/LayerCommon/LayerVisibilityToggle';
 import { LayerWrapper } from 'features/controlLayers/components/LayerCommon/LayerWrapper';
 import {
   isRegionalGuidanceLayer,
@@ -55,7 +55,7 @@ export const RGLayer = memo(({ layerId }: Props) => {
   return (
     <LayerWrapper onClick={onClick} borderColor={isSelected ? color : 'base.800'}>
       <Flex gap={3} alignItems="center" p={3} cursor="pointer" onDoubleClick={onToggle}>
-        <LayerVisibilityToggle layerId={layerId} />
+        <LayerIsEnabledToggle layerId={layerId} />
         <LayerTitle type="regional_guidance_layer" />
         <Spacer />
         {autoNegative === 'invert' && (

invokeai/frontend/web/src/features/controlLayers/components/RGLayer/RGLayerNegativePrompt.tsx

@@ -45,7 +45,6 @@ export const RGLayerNegativePrompt = memo(({ layerId }: Props) => {
           variant="darkFilled"
           paddingRight={30}
           fontSize="sm"
-          spellCheck={false}
         />
         <PromptOverlayButtonWrapper>
           <RGLayerPromptDeleteButton layerId={layerId} polarity="negative" />

invokeai/frontend/web/src/features/controlLayers/components/RGLayer/RGLayerPositivePrompt.tsx

@@ -45,7 +45,6 @@ export const RGLayerPositivePrompt = memo(({ layerId }: Props) => {
           variant="darkFilled"
           paddingRight={30}
           minH={28}
-          spellCheck={false}
         />
         <PromptOverlayButtonWrapper>
           <RGLayerPromptDeleteButton layerId={layerId} polarity="positive" />

invokeai/frontend/web/src/features/controlLayers/hooks/layerStateHooks.ts

@@ -39,7 +39,7 @@ export const useLayerNegativePrompt = (layerId: string) => {
   return prompt;
 };
 
-export const useLayerIsVisible = (layerId: string) => {
+export const useLayerIsEnabled = (layerId: string) => {
   const selectLayer = useMemo(
     () =>
       createSelector(selectControlLayersSlice, (controlLayers) => {

invokeai/frontend/web/src/features/controlLayers/store/controlLayersSlice.ts

@@ -139,7 +139,7 @@ export const controlLayersSlice = createSlice({
     layerSelected: (state, action: PayloadAction<string>) => {
       exclusivelySelectLayer(state, action.payload);
     },
-    layerVisibilityToggled: (state, action: PayloadAction<string>) => {
+    layerIsEnabledToggled: (state, action: PayloadAction<string>) => {
       const layer = state.layers.find((l) => l.id === action.payload);
       if (layer) {
         layer.isEnabled = !layer.isEnabled;
@@ -616,12 +616,24 @@ export const controlLayersSlice = createSlice({
     iiLayerAdded: {
       reducer: (state, action: PayloadAction<{ layerId: string; imageDTO: ImageDTO | null }>) => {
         const { layerId, imageDTO } = action.payload;
+
+        // Retain opacity and denoising strength of existing initial image layer if exists
+        let opacity = 1;
+        let denoisingStrength = 0.75;
+        const iiLayer = state.layers.find((l) => l.id === layerId);
+        if (iiLayer) {
+          assert(isInitialImageLayer(iiLayer));
+          opacity = iiLayer.opacity;
+          denoisingStrength = iiLayer.denoisingStrength;
+        }
+
         // Highlander! There can be only one!
         state.layers = state.layers.filter((l) => (isInitialImageLayer(l) ? false : true));
+
         const layer: InitialImageLayer = {
           id: layerId,
           type: 'initial_image_layer',
-          opacity: 1,
+          opacity,
           x: 0,
           y: 0,
           bbox: null,
@@ -629,7 +641,7 @@ export const controlLayersSlice = createSlice({
           isEnabled: true,
           image: imageDTO ? imageDTOToImageWithDims(imageDTO) : null,
           isSelected: true,
-          denoisingStrength: 0.75,
+          denoisingStrength,
         };
         state.layers.push(layer);
         exclusivelySelectLayer(state, layer.id);
@@ -779,7 +791,7 @@ class LayerColors {
 export const {
   // Any Layer Type
   layerSelected,
-  layerVisibilityToggled,
+  layerIsEnabledToggled,
   layerTranslated,
   layerBboxChanged,
   layerReset,

invokeai/frontend/web/src/features/controlLayers/util/controlAdapters.test.ts

@@ -1,23 +1,9 @@
-import type { S } from 'services/api/types';
+import type { Invocation } from 'services/api/types';
 import type { Equals } from 'tsafe';
 import { assert } from 'tsafe';
 import { describe, test } from 'vitest';
 
 import type {
-  _CannyProcessorConfig,
-  _ColorMapProcessorConfig,
-  _ContentShuffleProcessorConfig,
-  _DepthAnythingProcessorConfig,
-  _DWOpenposeProcessorConfig,
-  _HedProcessorConfig,
-  _LineartAnimeProcessorConfig,
-  _LineartProcessorConfig,
-  _MediapipeFaceProcessorConfig,
-  _MidasDepthProcessorConfig,
-  _MlsdProcessorConfig,
-  _NormalbaeProcessorConfig,
-  _PidiProcessorConfig,
-  _ZoeDepthProcessorConfig,
   CannyProcessorConfig,
   CLIPVisionModelV2,
   ColorMapProcessorConfig,
@@ -45,16 +31,16 @@ describe('Control Adapter Types', () => {
     assert<Equals<ProcessorConfig['type'], ProcessorTypeV2>>();
   });
   test('IP Adapter Method', () => {
-    assert<Equals<NonNullable<S['IPAdapterInvocation']['method']>, IPMethodV2>>();
+    assert<Equals<NonNullable<Invocation<'ip_adapter'>['method']>, IPMethodV2>>();
   });
   test('CLIP Vision Model', () => {
-    assert<Equals<NonNullable<S['IPAdapterInvocation']['clip_vision_model']>, CLIPVisionModelV2>>();
+    assert<Equals<NonNullable<Invocation<'ip_adapter'>['clip_vision_model']>, CLIPVisionModelV2>>();
   });
   test('Control Mode', () => {
-    assert<Equals<NonNullable<S['ControlNetInvocation']['control_mode']>, ControlModeV2>>();
+    assert<Equals<NonNullable<Invocation<'controlnet'>['control_mode']>, ControlModeV2>>();
   });
   test('DepthAnything Model Size', () => {
-    assert<Equals<NonNullable<S['DepthAnythingImageProcessorInvocation']['model_size']>, DepthAnythingModelSize>>();
+    assert<Equals<NonNullable<Invocation<'depth_anything_image_processor'>['model_size']>, DepthAnythingModelSize>>();
   });
   test('Processor Configs', () => {
     // The processor configs are manually modeled zod schemas. This test ensures that the inferred types are correct.
@@ -75,3 +61,33 @@ describe('Control Adapter Types', () => {
     assert<Equals<_ZoeDepthProcessorConfig, ZoeDepthProcessorConfig>>();
   });
 });
+
+// Types derived from OpenAPI
+type _CannyProcessorConfig = Required<
+  Pick<Invocation<'canny_image_processor'>, 'id' | 'type' | 'low_threshold' | 'high_threshold'>
+>;
+type _ColorMapProcessorConfig = Required<
+  Pick<Invocation<'color_map_image_processor'>, 'id' | 'type' | 'color_map_tile_size'>
+>;
+type _ContentShuffleProcessorConfig = Required<
+  Pick<Invocation<'content_shuffle_image_processor'>, 'id' | 'type' | 'w' | 'h' | 'f'>
+>;
+type _DepthAnythingProcessorConfig = Required<
+  Pick<Invocation<'depth_anything_image_processor'>, 'id' | 'type' | 'model_size'>
+>;
+type _HedProcessorConfig = Required<Pick<Invocation<'hed_image_processor'>, 'id' | 'type' | 'scribble'>>;
+type _LineartAnimeProcessorConfig = Required<Pick<Invocation<'lineart_anime_image_processor'>, 'id' | 'type'>>;
+type _LineartProcessorConfig = Required<Pick<Invocation<'lineart_image_processor'>, 'id' | 'type' | 'coarse'>>;
+type _MediapipeFaceProcessorConfig = Required<
+  Pick<Invocation<'mediapipe_face_processor'>, 'id' | 'type' | 'max_faces' | 'min_confidence'>
+>;
+type _MidasDepthProcessorConfig = Required<
+  Pick<Invocation<'midas_depth_image_processor'>, 'id' | 'type' | 'a_mult' | 'bg_th'>
+>;
+type _MlsdProcessorConfig = Required<Pick<Invocation<'mlsd_image_processor'>, 'id' | 'type' | 'thr_v' | 'thr_d'>>;
+type _NormalbaeProcessorConfig = Required<Pick<Invocation<'normalbae_image_processor'>, 'id' | 'type'>>;
+type _DWOpenposeProcessorConfig = Required<
+  Pick<Invocation<'dw_openpose_image_processor'>, 'id' | 'type' | 'draw_body' | 'draw_face' | 'draw_hands'>
+>;
+type _PidiProcessorConfig = Required<Pick<Invocation<'pidi_image_processor'>, 'id' | 'type' | 'safe' | 'scribble'>>;
+type _ZoeDepthProcessorConfig = Required<Pick<Invocation<'zoe_depth_image_processor'>, 'id' | 'type'>>;

invokeai/frontend/web/src/features/controlLayers/util/controlAdapters.ts

@@ -1,27 +1,7 @@
 import { deepClone } from 'common/util/deepClone';
 import { zModelIdentifierField } from 'features/nodes/types/common';
 import { merge, omit } from 'lodash-es';
-import type {
-  BaseModelType,
-  CannyImageProcessorInvocation,
-  ColorMapImageProcessorInvocation,
-  ContentShuffleImageProcessorInvocation,
-  ControlNetModelConfig,
-  DepthAnythingImageProcessorInvocation,
-  DWOpenposeImageProcessorInvocation,
-  Graph,
-  HedImageProcessorInvocation,
-  ImageDTO,
-  LineartAnimeImageProcessorInvocation,
-  LineartImageProcessorInvocation,
-  MediapipeFaceProcessorInvocation,
-  MidasDepthImageProcessorInvocation,
-  MlsdImageProcessorInvocation,
-  NormalbaeImageProcessorInvocation,
-  PidiImageProcessorInvocation,
-  T2IAdapterModelConfig,
-  ZoeDepthImageProcessorInvocation,
-} from 'services/api/types';
+import type { BaseModelType, ControlNetModelConfig, Graph, ImageDTO, T2IAdapterModelConfig } from 'services/api/types';
 import { z } from 'zod';
 
 const zId = z.string().min(1);
@@ -32,9 +12,6 @@ const zCannyProcessorConfig = z.object({
   low_threshold: z.number().int().gte(0).lte(255),
   high_threshold: z.number().int().gte(0).lte(255),
 });
-export type _CannyProcessorConfig = Required<
-  Pick<CannyImageProcessorInvocation, 'id' | 'type' | 'low_threshold' | 'high_threshold'>
->;
 export type CannyProcessorConfig = z.infer<typeof zCannyProcessorConfig>;
 
 const zColorMapProcessorConfig = z.object({
@@ -42,9 +19,6 @@ const zColorMapProcessorConfig = z.object({
   type: z.literal('color_map_image_processor'),
   color_map_tile_size: z.number().int().gte(1),
 });
-export type _ColorMapProcessorConfig = Required<
-  Pick<ColorMapImageProcessorInvocation, 'id' | 'type' | 'color_map_tile_size'>
->;
 export type ColorMapProcessorConfig = z.infer<typeof zColorMapProcessorConfig>;
 
 const zContentShuffleProcessorConfig = z.object({
@@ -54,9 +28,6 @@ const zContentShuffleProcessorConfig = z.object({
   h: z.number().int().gte(0),
   f: z.number().int().gte(0),
 });
-export type _ContentShuffleProcessorConfig = Required<
-  Pick<ContentShuffleImageProcessorInvocation, 'id' | 'type' | 'w' | 'h' | 'f'>
->;
 export type ContentShuffleProcessorConfig = z.infer<typeof zContentShuffleProcessorConfig>;
 
 const zDepthAnythingModelSize = z.enum(['large', 'base', 'small']);
@@ -68,9 +39,6 @@ const zDepthAnythingProcessorConfig = z.object({
   type: z.literal('depth_anything_image_processor'),
   model_size: zDepthAnythingModelSize,
 });
-export type _DepthAnythingProcessorConfig = Required<
-  Pick<DepthAnythingImageProcessorInvocation, 'id' | 'type' | 'model_size'>
->;
 export type DepthAnythingProcessorConfig = z.infer<typeof zDepthAnythingProcessorConfig>;
 
 const zHedProcessorConfig = z.object({
@@ -78,14 +46,12 @@ const zHedProcessorConfig = z.object({
   type: z.literal('hed_image_processor'),
   scribble: z.boolean(),
 });
-export type _HedProcessorConfig = Required<Pick<HedImageProcessorInvocation, 'id' | 'type' | 'scribble'>>;
 export type HedProcessorConfig = z.infer<typeof zHedProcessorConfig>;
 
 const zLineartAnimeProcessorConfig = z.object({
   id: zId,
   type: z.literal('lineart_anime_image_processor'),
 });
-export type _LineartAnimeProcessorConfig = Required<Pick<LineartAnimeImageProcessorInvocation, 'id' | 'type'>>;
 export type LineartAnimeProcessorConfig = z.infer<typeof zLineartAnimeProcessorConfig>;
 
 const zLineartProcessorConfig = z.object({
@@ -93,7 +59,6 @@ const zLineartProcessorConfig = z.object({
   type: z.literal('lineart_image_processor'),
   coarse: z.boolean(),
 });
-export type _LineartProcessorConfig = Required<Pick<LineartImageProcessorInvocation, 'id' | 'type' | 'coarse'>>;
 export type LineartProcessorConfig = z.infer<typeof zLineartProcessorConfig>;
 
 const zMediapipeFaceProcessorConfig = z.object({
@@ -102,9 +67,6 @@ const zMediapipeFaceProcessorConfig = z.object({
   max_faces: z.number().int().gte(1),
   min_confidence: z.number().gte(0).lte(1),
 });
-export type _MediapipeFaceProcessorConfig = Required<
-  Pick<MediapipeFaceProcessorInvocation, 'id' | 'type' | 'max_faces' | 'min_confidence'>
->;
 export type MediapipeFaceProcessorConfig = z.infer<typeof zMediapipeFaceProcessorConfig>;
 
 const zMidasDepthProcessorConfig = z.object({
@@ -113,9 +75,6 @@ const zMidasDepthProcessorConfig = z.object({
   a_mult: z.number().gte(0),
   bg_th: z.number().gte(0),
 });
-export type _MidasDepthProcessorConfig = Required<
-  Pick<MidasDepthImageProcessorInvocation, 'id' | 'type' | 'a_mult' | 'bg_th'>
->;
 export type MidasDepthProcessorConfig = z.infer<typeof zMidasDepthProcessorConfig>;
 
 const zMlsdProcessorConfig = z.object({
@@ -124,14 +83,12 @@ const zMlsdProcessorConfig = z.object({
   thr_v: z.number().gte(0),
   thr_d: z.number().gte(0),
 });
-export type _MlsdProcessorConfig = Required<Pick<MlsdImageProcessorInvocation, 'id' | 'type' | 'thr_v' | 'thr_d'>>;
 export type MlsdProcessorConfig = z.infer<typeof zMlsdProcessorConfig>;
 
 const zNormalbaeProcessorConfig = z.object({
   id: zId,
   type: z.literal('normalbae_image_processor'),
 });
-export type _NormalbaeProcessorConfig = Required<Pick<NormalbaeImageProcessorInvocation, 'id' | 'type'>>;
 export type NormalbaeProcessorConfig = z.infer<typeof zNormalbaeProcessorConfig>;
 
 const zDWOpenposeProcessorConfig = z.object({
@@ -141,9 +98,6 @@ const zDWOpenposeProcessorConfig = z.object({
   draw_face: z.boolean(),
   draw_hands: z.boolean(),
 });
-export type _DWOpenposeProcessorConfig = Required<
-  Pick<DWOpenposeImageProcessorInvocation, 'id' | 'type' | 'draw_body' | 'draw_face' | 'draw_hands'>
->;
 export type DWOpenposeProcessorConfig = z.infer<typeof zDWOpenposeProcessorConfig>;
 
 const zPidiProcessorConfig = z.object({
@@ -152,14 +106,12 @@ const zPidiProcessorConfig = z.object({
   safe: z.boolean(),
   scribble: z.boolean(),
 });
-export type _PidiProcessorConfig = Required<Pick<PidiImageProcessorInvocation, 'id' | 'type' | 'safe' | 'scribble'>>;
 export type PidiProcessorConfig = z.infer<typeof zPidiProcessorConfig>;
 
 const zZoeDepthProcessorConfig = z.object({
   id: zId,
   type: z.literal('zoe_depth_image_processor'),
 });
-export type _ZoeDepthProcessorConfig = Required<Pick<ZoeDepthImageProcessorInvocation, 'id' | 'type'>>;
 export type ZoeDepthProcessorConfig = z.infer<typeof zZoeDepthProcessorConfig>;
 
 const zProcessorConfig = z.discriminatedUnion('type', [

invokeai/frontend/web/src/features/dnd/hooks/useScaledCenteredModifer.ts

@@ -1,23 +1,21 @@
 import type { Modifier } from '@dnd-kit/core';
 import { getEventCoordinates } from '@dnd-kit/utilities';
-import { createSelector } from '@reduxjs/toolkit';
+import { useStore } from '@nanostores/react';
 import { useAppSelector } from 'app/store/storeHooks';
-import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
+import { $viewport } from 'features/nodes/store/nodesSlice';
 import { activeTabNameSelector } from 'features/ui/store/uiSelectors';
 import { useCallback } from 'react';
 
-const selectZoom = createSelector([selectNodesSlice, activeTabNameSelector], (nodes, activeTabName) =>
-  activeTabName === 'workflows' ? nodes.viewport.zoom : 1
-);
-
 /**
  * Applies scaling to the drag transform (if on node editor tab) and centers it on cursor.
  */
 export const useScaledModifer = () => {
-  const zoom = useAppSelector(selectZoom);
+  const activeTabName = useAppSelector(activeTabNameSelector);
+  const workflowsViewport = useStore($viewport);
   const modifier: Modifier = useCallback(
     ({ activatorEvent, draggingNodeRect, transform }) => {
       if (draggingNodeRect && activatorEvent) {
+        const zoom = activeTabName === 'workflows' ? workflowsViewport.zoom : 1;
         const activatorCoordinates = getEventCoordinates(activatorEvent);
 
         if (!activatorCoordinates) {
@@ -42,7 +40,7 @@ export const useScaledModifer = () => {
 
       return transform;
     },
-    [zoom]
+    [activeTabName, workflowsViewport.zoom]
   );
 
   return modifier;