Create new data structures for captioned images, and a list of captioned images. Create auto_caption_image node which can take a single image or list of images to caption

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.
 
-##### Single and Collection Fields
+##### Collection and Scalar Fields
 
-Field types have a name and cardinality property which may identify it as a **SINGLE**, **COLLECTION** or **SINGLE_OR_COLLECTION** field.
+Field types have a name and two flags which may identify it as a **collection** or **collection or scalar** field.
 
-- 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).
+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).
 
 ## Implementation
 
@@ -173,7 +173,8 @@ Field types are represented as structured objects:
 ```ts
 type FieldType = {
   name: string;
-  cardinality: 'SINGLE' | 'COLLECTION' | 'SINGLE_OR_COLLECTION';
+  isCollection: boolean;
+  isCollectionOrScalar: boolean;
 };
 ```
 
@@ -185,7 +186,7 @@ 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`). The cardinality is `"SINGLE"`.
+We create a field type name from this `type` string (e.g. `string` -> `StringField`).
 
 ##### Complex Types
 
@@ -199,13 +200,13 @@ 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. The cardinality is `"COLLECTION"`.
+We use the item type for field type name, adding `isCollection: true` to the field type.
 
-##### Single or Collection Types
+##### Collection or Scalar 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, with cardinality `"SINGLE_OR_COLLECTION"`.
+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.
 
 ##### 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 [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.  
+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.  
 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/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](./INSTALL_REQUIREMENTS.md).
+Before you start, go through the [installation requirements].
 
 ### Installation Walkthrough
 
@@ -79,7 +79,7 @@ Before you start, go through the [installation requirements](./INSTALL_REQUIREME
 
 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](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.
+    - 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.
 
         !!! example "Install with an extra index URL"
 
@@ -116,4 +116,4 @@ Before you start, go through the [installation requirements](./INSTALL_REQUIREME
 
     !!! warning
 
-        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.
+        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.

installer/templates/invoke.bat.in

@@ -10,7 +10,8 @@ set INVOKEAI_ROOT=.
 echo Desired action:
 echo 1. Generate images with the browser-based interface
 echo 2. Open the developer console
-echo 3. Command-line help
+echo 3. Run the InvokeAI image database maintenance script
+echo 4. Command-line help
 echo Q - Quit
 echo.
 echo To update, download and run the installer from https://github.com/invoke-ai/InvokeAI/releases/latest.
@@ -33,6 +34,9 @@ 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

@@ -47,6 +47,11 @@ 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
@@ -66,7 +71,8 @@ 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: Command-line help\n"
+    printf "3: Run the InvokeAI image database maintenance script\n"
+    printf "4: 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, DefaultSessionRunner
+from ..services.session_processor.session_processor_default import DefaultSessionProcessor
 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
@@ -103,8 +103,7 @@ class ApiDependencies:
         )
         names = SimpleNameService()
         performance_statistics = InvocationStatsService()
-
-        session_processor = DefaultSessionProcessor(session_runner=DefaultSessionRunner())
+        session_processor = DefaultSessionProcessor()
         session_queue = SqliteSessionQueue(db=db)
         urls = LocalUrlService()
         workflow_records = SqliteWorkflowRecordsStorage(db=db)

invokeai/app/api/routers/images.py

@@ -6,12 +6,13 @@ 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, JsonValue
+from pydantic import BaseModel, Field, ValidationError
 
-from invokeai.app.invocations.fields import MetadataField
+from invokeai.app.invocations.fields import MetadataField, MetadataFieldValidator
 from invokeai.app.services.image_records.image_records_common import ImageCategory, ImageRecordChanges, ResourceOrigin
 from invokeai.app.services.images.images_common import ImageDTO, ImageUrlsDTO
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
+from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID, WorkflowWithoutIDValidator
 
 from ..dependencies import ApiDependencies
 
@@ -41,17 +42,13 @@ 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
-    _graph = None
+    metadata = None
+    workflow = None
 
     contents = await file.read()
     try:
@@ -65,28 +62,22 @@ async def upload_image(
 
     # TODO: retain non-invokeai metadata on upload?
     # attempt to parse metadata from image
-    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
+    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
 
     # attempt to parse workflow from image
     workflow_raw = pil_image.info.get("invokeai_workflow", None)
-    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
+    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
 
     try:
         image_dto = ApiDependencies.invoker.services.images.create(
@@ -95,9 +86,8 @@ async def upload_image(
             image_category=image_category,
             session_id=session_id,
             board_id=board_id,
-            metadata=_metadata,
-            workflow=_workflow,
-            graph=_graph,
+            metadata=metadata,
+            workflow=workflow,
             is_intermediate=is_intermediate,
         )
 
@@ -195,21 +185,14 @@ 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=WorkflowAndGraphResponse
+    "/i/{image_name}/workflow", operation_id="get_image_workflow", response_model=Optional[WorkflowWithoutID]
 )
 async def get_image_workflow(
     image_name: str = Path(description="The name of image whose workflow to get"),
-) -> WorkflowAndGraphResponse:
+) -> Optional[WorkflowWithoutID]:
     try:
-        workflow = ApiDependencies.invoker.services.images.get_workflow(image_name)
-        graph = ApiDependencies.invoker.services.images.get_graph(image_name)
-        return WorkflowAndGraphResponse(workflow=workflow, graph=graph)
+        return ApiDependencies.invoker.services.images.get_workflow(image_name)
     except Exception:
         raise HTTPException(status_code=404)
 

invokeai/app/api/routers/session_queue.py

@@ -203,7 +203,6 @@ 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/invocations/controlnet_image_processors.py

@@ -24,6 +24,7 @@ from pydantic import BaseModel, Field, field_validator, model_validator
 from invokeai.app.invocations.fields import (
     FieldDescriptions,
     ImageField,
+    Input,
     InputField,
     OutputField,
     UIType,
@@ -79,13 +80,13 @@ class ControlOutput(BaseInvocationOutput):
     control: ControlField = OutputField(description=FieldDescriptions.control)
 
 
-@invocation("controlnet", title="ControlNet", tags=["controlnet"], category="controlnet", version="1.1.2")
+@invocation("controlnet", title="ControlNet", tags=["controlnet"], category="controlnet", version="1.1.1")
 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, ui_type=UIType.ControlNetModel
+        description=FieldDescriptions.controlnet_model, input=Input.Direct, 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/image.py

@@ -1,10 +1,11 @@
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
 
-from typing import Literal, Optional
+from typing import Literal, Optional, List, Union
 
 import cv2
 import numpy
 from PIL import Image, ImageChops, ImageFilter, ImageOps
+from transformers import AutoModelForCausalLM, AutoTokenizer
 
 from invokeai.app.invocations.constants import IMAGE_MODES
 from invokeai.app.invocations.fields import (
@@ -15,7 +16,7 @@ from invokeai.app.invocations.fields import (
     WithBoard,
     WithMetadata,
 )
-from invokeai.app.invocations.primitives import ImageOutput
+from invokeai.app.invocations.primitives import ImageOutput, CaptionImageOutputs, CaptionImageOutput
 from invokeai.app.services.image_records.image_records_common import ImageCategory
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.backend.image_util.invisible_watermark import InvisibleWatermark
@@ -66,6 +67,56 @@ class BlankImageInvocation(BaseInvocation, WithMetadata, WithBoard):
         return ImageOutput.build(image_dto)
 
 
+@invocation(
+    "auto_caption_image",
+    title="Automatically Caption Image",
+    tags=["image", "caption"],
+    category="image",
+    version="1.2.2",
+)
+class CaptionImageInvocation(BaseInvocation, WithMetadata, WithBoard):
+    """Adds a caption to an image"""
+
+    images: Union[ImageField,List[ImageField]] = InputField(description="The image to caption")
+    prompt: str = InputField(default="Describe this list of images in 20 words or less", description="Describe how you would like the image to be captioned.")
+
+    def invoke(self, context: InvocationContext) -> CaptionImageOutputs:
+
+        model_id = "vikhyatk/moondream2"
+        model_revision = "2024-04-02"
+        tokenizer = AutoTokenizer.from_pretrained(model_id, revision=model_revision)
+        moondream_model = AutoModelForCausalLM.from_pretrained(
+            model_id, trust_remote_code=True, revision=model_revision
+        )
+        output: CaptionImageOutputs = CaptionImageOutputs()
+        try:
+            from PIL.Image import Image
+            images: List[Image] = []
+            image_fields = self.images if isinstance(self.images, list) else [self.images]
+            for image in image_fields:
+                images.append(context.images.get_pil(image.image_name))
+            answers: List[str] = moondream_model.batch_answer(
+                images=images,
+                prompts=[self.prompt] * len(images),
+                tokenizer=tokenizer,
+            )
+            assert isinstance(answers, list)
+            for i, answer in enumerate(answers):
+                output.images.append(CaptionImageOutput(
+                    image=image_fields[i],
+                    width=images[i].width,
+                    height=images[i].height,
+                    caption=answer
+                ))
+        except:
+            raise
+        finally:
+            del moondream_model
+            del tokenizer
+
+        return output
+
+
 @invocation(
     "img_crop",
     title="Crop Image",
@@ -194,7 +245,7 @@ class ImagePasteInvocation(BaseInvocation, WithMetadata, WithBoard):
 class MaskFromAlphaInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Extracts the alpha channel of an image as a mask."""
 
-    image: ImageField = InputField(description="The image to create the mask from")
+    image: List[ImageField] = InputField(description="The image to create the mask from")
     invert: bool = InputField(default=False, description="Whether or not to invert the mask")
 
     def invoke(self, context: InvocationContext) -> ImageOutput:

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, InputField, OutputField, TensorField, UIType
+from invokeai.app.invocations.fields import FieldDescriptions, Input, 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="1.4.1")
+@invocation("ip_adapter", title="IP-Adapter", tags=["ip_adapter", "control"], category="ip_adapter", version="1.4.0")
 class IPAdapterInvocation(BaseInvocation):
     """Collects IP-Adapter info to pass to other nodes."""
 
@@ -67,6 +67,7 @@ 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

@@ -11,7 +11,6 @@ from invokeai.backend.model_manager.config import AnyModelConfig, BaseModelType,
 from .baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
-    Classification,
     invocation,
     invocation_output,
 )
@@ -94,46 +93,19 @@ 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="1.0.3",
+    version="1.0.2",
 )
 class MainModelLoaderInvocation(BaseInvocation):
     """Loads a main model, outputting its submodels."""
 
-    model: ModelIdentifierField = InputField(description=FieldDescriptions.main_model, ui_type=UIType.MainModel)
+    model: ModelIdentifierField = InputField(
+        description=FieldDescriptions.main_model, input=Input.Direct, ui_type=UIType.MainModel
+    )
     # TODO: precision?
 
     def invoke(self, context: InvocationContext) -> ModelLoaderOutput:
@@ -162,12 +134,12 @@ class LoRALoaderOutput(BaseInvocationOutput):
     clip: Optional[CLIPField] = OutputField(default=None, description=FieldDescriptions.clip, title="CLIP")
 
 
-@invocation("lora_loader", title="LoRA", tags=["model"], category="model", version="1.0.3")
+@invocation("lora_loader", title="LoRA", tags=["model"], category="model", version="1.0.2")
 class LoRALoaderInvocation(BaseInvocation):
     """Apply selected lora to unet and text_encoder."""
 
     lora: ModelIdentifierField = InputField(
-        description=FieldDescriptions.lora_model, title="LoRA", ui_type=UIType.LoRAModel
+        description=FieldDescriptions.lora_model, input=Input.Direct, title="LoRA", ui_type=UIType.LoRAModel
     )
     weight: float = InputField(default=0.75, description=FieldDescriptions.lora_weight)
     unet: Optional[UNetField] = InputField(
@@ -225,12 +197,12 @@ class LoRASelectorOutput(BaseInvocationOutput):
     lora: LoRAField = OutputField(description="LoRA model and weight", title="LoRA")
 
 
-@invocation("lora_selector", title="LoRA Selector", tags=["model"], category="model", version="1.0.1")
+@invocation("lora_selector", title="LoRA Selector", tags=["model"], category="model", version="1.0.0")
 class LoRASelectorInvocation(BaseInvocation):
     """Selects a LoRA model and weight."""
 
     lora: ModelIdentifierField = InputField(
-        description=FieldDescriptions.lora_model, title="LoRA", ui_type=UIType.LoRAModel
+        description=FieldDescriptions.lora_model, input=Input.Direct, title="LoRA", ui_type=UIType.LoRAModel
     )
     weight: float = InputField(default=0.75, description=FieldDescriptions.lora_weight)
 
@@ -301,13 +273,13 @@ class SDXLLoRALoaderOutput(BaseInvocationOutput):
     title="SDXL LoRA",
     tags=["lora", "model"],
     category="model",
-    version="1.0.3",
+    version="1.0.2",
 )
 class SDXLLoRALoaderInvocation(BaseInvocation):
     """Apply selected lora to unet and text_encoder."""
 
     lora: ModelIdentifierField = InputField(
-        description=FieldDescriptions.lora_model, title="LoRA", ui_type=UIType.LoRAModel
+        description=FieldDescriptions.lora_model, input=Input.Direct, title="LoRA", ui_type=UIType.LoRAModel
     )
     weight: float = InputField(default=0.75, description=FieldDescriptions.lora_weight)
     unet: Optional[UNetField] = InputField(
@@ -442,12 +414,12 @@ class SDXLLoRACollectionLoader(BaseInvocation):
         return output
 
 
-@invocation("vae_loader", title="VAE", tags=["vae", "model"], category="model", version="1.0.3")
+@invocation("vae_loader", title="VAE", tags=["vae", "model"], category="model", version="1.0.2")
 class VAELoaderInvocation(BaseInvocation):
     """Loads a VAE model, outputting a VaeLoaderOutput"""
 
     vae_model: ModelIdentifierField = InputField(
-        description=FieldDescriptions.vae_model, title="VAE", ui_type=UIType.VAEModel
+        description=FieldDescriptions.vae_model, input=Input.Direct, title="VAE", ui_type=UIType.VAEModel
     )
 
     def invoke(self, context: InvocationContext) -> VAEOutput:

invokeai/app/invocations/primitives.py

@@ -1,6 +1,6 @@
 # Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
 
-from typing import Optional
+from typing import Optional, List
 
 import torch
 
@@ -247,6 +247,17 @@ class ImageOutput(BaseInvocationOutput):
         )
 
 
+@invocation_output("captioned_image_output")
+class CaptionImageOutput(ImageOutput):
+    caption: str = OutputField(description="Caption for given image")
+
+
+
+@invocation_output("captioned_image_outputs")
+class CaptionImageOutputs(BaseInvocationOutput):
+    images: List[CaptionImageOutput] = OutputField(description="List of captioned images", default=[])
+
+
 @invocation_output("image_collection_output")
 class ImageCollectionOutput(BaseInvocationOutput):
     """Base class for nodes that output a collection of images"""

invokeai/app/invocations/sdxl.py

@@ -1,4 +1,4 @@
-from invokeai.app.invocations.fields import FieldDescriptions, InputField, OutputField, UIType
+from invokeai.app.invocations.fields import FieldDescriptions, Input, 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="1.0.3")
+@invocation("sdxl_model_loader", title="SDXL Main Model", tags=["model", "sdxl"], category="model", version="1.0.2")
 class SDXLModelLoaderInvocation(BaseInvocation):
     """Loads an sdxl base model, outputting its submodels."""
 
     model: ModelIdentifierField = InputField(
-        description=FieldDescriptions.sdxl_main_model, ui_type=UIType.SDXLMainModel
+        description=FieldDescriptions.sdxl_main_model, input=Input.Direct, ui_type=UIType.SDXLMainModel
     )
     # TODO: precision?
 
@@ -67,13 +67,13 @@ class SDXLModelLoaderInvocation(BaseInvocation):
     title="SDXL Refiner Model",
     tags=["model", "sdxl", "refiner"],
     category="model",
-    version="1.0.3",
+    version="1.0.2",
 )
 class SDXLRefinerModelLoaderInvocation(BaseInvocation):
     """Loads an sdxl refiner model, outputting its submodels."""
 
     model: ModelIdentifierField = InputField(
-        description=FieldDescriptions.sdxl_refiner_model, ui_type=UIType.SDXLRefinerModel
+        description=FieldDescriptions.sdxl_refiner_model, input=Input.Direct, 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, InputField, OutputField, UIType
+from invokeai.app.invocations.fields import FieldDescriptions, ImageField, Input, 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="1.0.3"
+    "t2i_adapter", title="T2I-Adapter", tags=["t2i_adapter", "control"], category="t2i_adapter", version="1.0.2"
 )
 class T2IAdapterInvocation(BaseInvocation):
     """Collects T2I-Adapter info to pass to other nodes."""
@@ -55,6 +55,7 @@ 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

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

@@ -4,6 +4,9 @@ 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."""
@@ -30,9 +33,8 @@ class ImageFileStorageBase(ABC):
         self,
         image: PILImageType,
         image_name: str,
-        metadata: Optional[str] = None,
-        workflow: Optional[str] = None,
-        graph: Optional[str] = None,
+        metadata: Optional[MetadataField] = None,
+        workflow: Optional[WorkflowWithoutID] = None,
         thumbnail_size: int = 256,
     ) -> None:
         """Saves an image and a 256x256 WEBP thumbnail. Returns a tuple of the image name, thumbnail name, and created timestamp."""
@@ -44,11 +46,6 @@ class ImageFileStorageBase(ABC):
         pass
 
     @abstractmethod
-    def get_workflow(self, image_name: str) -> Optional[str]:
+    def get_workflow(self, image_name: str) -> Optional[WorkflowWithoutID]:
         """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

@@ -7,7 +7,9 @@ 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
@@ -54,9 +56,8 @@ class DiskImageFileStorage(ImageFileStorageBase):
         self,
         image: PILImageType,
         image_name: str,
-        metadata: Optional[str] = None,
-        workflow: Optional[str] = None,
-        graph: Optional[str] = None,
+        metadata: Optional[MetadataField] = None,
+        workflow: Optional[WorkflowWithoutID] = None,
         thumbnail_size: int = 256,
     ) -> None:
         try:
@@ -67,14 +68,13 @@ class DiskImageFileStorage(ImageFileStorageBase):
             info_dict = {}
 
             if metadata is not None:
-                info_dict["invokeai_metadata"] = metadata
-                pnginfo.add_text("invokeai_metadata", metadata)
+                metadata_json = metadata.model_dump_json()
+                info_dict["invokeai_metadata"] = metadata_json
+                pnginfo.add_text("invokeai_metadata", metadata_json)
             if workflow is not None:
-                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)
+                workflow_json = workflow.model_dump_json()
+                info_dict["invokeai_workflow"] = workflow_json
+                pnginfo.add_text("invokeai_workflow", workflow_json)
 
             # When saving the image, the image object's info field is not populated. We need to set it
             image.info = info_dict
@@ -129,18 +129,11 @@ class DiskImageFileStorage(ImageFileStorageBase):
         path = path if isinstance(path, Path) else Path(path)
         return path.exists()
 
-    def get_workflow(self, image_name: str) -> str | None:
+    def get_workflow(self, image_name: str) -> WorkflowWithoutID | None:
         image = self.get(image_name)
         workflow = image.info.get("invokeai_workflow", None)
-        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
+        if workflow is not None:
+            return WorkflowWithoutID.model_validate_json(workflow)
         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[str] = None,
+        metadata: Optional[MetadataField] = None,
     ) -> datetime:
         """Saves an image record."""
         pass

invokeai/app/services/image_records/image_records_sqlite.py

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

invokeai/app/services/images/images_base.py

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

invokeai/app/services/images/images_default.py

@@ -5,6 +5,7 @@ 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,
@@ -41,9 +42,8 @@ class ImageService(ImageServiceABC):
         session_id: Optional[str] = None,
         board_id: Optional[str] = None,
         is_intermediate: Optional[bool] = False,
-        metadata: Optional[str] = None,
-        workflow: Optional[str] = None,
-        graph: Optional[str] = None,
+        metadata: Optional[MetadataField] = None,
+        workflow: Optional[WorkflowWithoutID] = 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 or graph is not None,
+                has_workflow=workflow 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, graph=graph
+                image_name=image_name, image=image, metadata=metadata, workflow=workflow
             )
             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[str]:
+    def get_workflow(self, image_name: str) -> Optional[WorkflowWithoutID]:
         try:
             return self.__invoker.services.image_files.get_workflow(image_name)
         except ImageFileNotFoundException:
@@ -167,16 +167,6 @@ 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

@@ -1,49 +1,6 @@
 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):
@@ -69,85 +26,3 @@ 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

@@ -7,305 +7,21 @@ 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, BaseInvocationOutput
+from invokeai.app.invocations.baseinvocation import BaseInvocation
 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, SessionQueueItemNotFoundError
-from invokeai.app.services.shared.graph import NodeInputError
+from invokeai.app.services.session_queue.session_queue_common import SessionQueueItem
 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 InvocationServices, SessionProcessorBase, SessionRunnerBase
+from .session_processor_base import SessionProcessorBase
 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 __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:
+    def start(self, invoker: Invoker, thread_limit: int = 1, polling_interval: int = 1) -> None:
         self._invoker: Invoker = invoker
         self._queue_item: Optional[SessionQueueItem] = None
         self._invocation: Optional[BaseInvocation] = None
@@ -317,7 +33,9 @@ class DefaultSessionProcessor(SessionProcessorBase):
 
         local_handler.register(event_name=EventServiceBase.queue_event, _func=self._on_queue_event)
 
-        self._thread_semaphore = BoundedSemaphore(self._thread_limit)
+        self._thread_limit = thread_limit
+        self._thread_semaphore = BoundedSemaphore(thread_limit)
+        self._polling_interval = polling_interval
 
         # 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.
@@ -331,7 +49,6 @@ 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,
@@ -374,7 +91,6 @@ class DefaultSessionProcessor(SessionProcessorBase):
             "failed",
             "canceled",
         ]:
-            self._cancel_event.set()
             self._poll_now()
 
     def resume(self) -> SessionProcessorStatus:
@@ -400,8 +116,8 @@ 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()
@@ -409,8 +125,8 @@ 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()
 
@@ -426,62 +142,157 @@ class DefaultSessionProcessor(SessionProcessorBase):
                     self._invoker.services.logger.debug(f"Executing queue item {self._queue_item.item_id}")
                     cancel_event.clear()
 
-                    # Run the graph
-                    self.session_runner.run(queue_item=self._queue_item)
+                    # If profiling is enabled, start the profiler
+                    if self._profiler is not None:
+                        self._profiler.start(profile_id=self._queue_item.session_id)
 
-                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,
+                    # 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()}"
                     )
-                    # Wait for next polling interval or event to try again
+                    # 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
                     poll_now_event.wait(self._polling_interval)
                     continue
-        except Exception as e:
+        except Exception:
             # Fatal error in processor, log and pass - we're done here
-            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)
+            self._invoker.services.logger.error(f"Fatal Error in session processor:\n{traceback.format_exc()}")
             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

@@ -16,7 +16,6 @@ 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
 
 
@@ -74,17 +73,10 @@ class SessionQueueBase(ABC):
         pass
 
     @abstractmethod
-    def cancel_queue_item(self, item_id: int) -> SessionQueueItem:
+    def cancel_queue_item(self, item_id: int, error: Optional[str] = None) -> 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"""
@@ -111,8 +103,3 @@ 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

@@ -3,16 +3,7 @@ import json
 from itertools import chain, product
 from typing import Generator, Iterable, Literal, NamedTuple, Optional, TypeAlias, Union, cast
 
-from pydantic import (
-    AliasChoices,
-    BaseModel,
-    ConfigDict,
-    Field,
-    StrictStr,
-    TypeAdapter,
-    field_validator,
-    model_validator,
-)
+from pydantic import BaseModel, ConfigDict, Field, StrictStr, TypeAdapter, field_validator, model_validator
 from pydantic_core import to_jsonable_python
 
 from invokeai.app.invocations.baseinvocation import BaseInvocation
@@ -198,13 +189,7 @@ 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_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"),
-    )
+    error: Optional[str] = Field(default=None, description="The error message if this queue item errored")
     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

@@ -27,7 +27,6 @@ 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
 
@@ -82,18 +81,10 @@ class SqliteSessionQueue(SessionQueueBase):
     async def _handle_error_event(self, event: FastAPIEvent) -> None:
         try:
             item_id = event[1]["data"]["queue_item_id"]
-            error_type = event[1]["data"]["error_type"]
-            error_message = event[1]["data"]["error_message"]
-            error_traceback = event[1]["data"]["error_traceback"]
+            error = event[1]["data"]["error"]
             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_type=error_type,
-                error_message=error_message,
-                error_traceback=error_traceback,
-            )
+            queue_item = self._set_queue_item_status(item_id=queue_item.item_id, status="failed", error=error)
         except SessionQueueItemNotFoundError:
             return
 
@@ -280,22 +271,17 @@ 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_type: Optional[str] = None,
-        error_message: Optional[str] = None,
-        error_traceback: Optional[str] = None,
+        self, item_id: int, status: QUEUE_ITEM_STATUS, error: Optional[str] = None
     ) -> SessionQueueItem:
         try:
             self.__lock.acquire()
             self.__cursor.execute(
                 """--sql
                 UPDATE session_queue
-                SET status = ?, error_type = ?, error_message = ?, error_traceback = ?
+                SET status = ?, error = ?
                 WHERE item_id = ?
                 """,
-                (status, error_type, error_message, error_traceback, item_id),
+                (status, error, item_id),
             )
             self.__conn.commit()
         except Exception:
@@ -352,6 +338,26 @@ 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()
@@ -418,34 +424,11 @@ class SqliteSessionQueue(SessionQueueBase):
             self.__lock.release()
         return PruneResult(deleted=count)
 
-    def cancel_queue_item(self, item_id: int) -> SessionQueueItem:
+    def cancel_queue_item(self, item_id: int, error: Optional[str] = None) -> 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="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,
-            )
+            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
             self.__invoker.services.events.emit_session_canceled(
                 queue_item_id=queue_item.item_id,
                 queue_id=queue_item.queue_id,
@@ -579,29 +562,6 @@ 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,
@@ -618,9 +578,7 @@ class SqliteSessionQueue(SessionQueueBase):
                     status,
                     priority,
                     field_values,
-                    error_type,
-                    error_message,
-                    error_traceback,
+                    error,
                     created_at,
                     updated_at,
                     completed_at,

invokeai/app/services/shared/graph.py

@@ -8,7 +8,6 @@ import networkx as nx
 from pydantic import (
     BaseModel,
     GetJsonSchemaHandler,
-    ValidationError,
     field_validator,
 )
 from pydantic.fields import Field
@@ -191,39 +190,6 @@ 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."""
@@ -855,10 +821,7 @@ class GraphExecutionState(BaseModel):
 
         # Get values from edges
         if next_node is not None:
-            try:
-                self._prepare_inputs(next_node)
-            except ValidationError as e:
-                raise NodeInputError(next_node, e)
+            self._prepare_inputs(next_node)
 
         # 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.model_dump_json()
-        elif isinstance(self._data.invocation, WithMetadata) and self._data.invocation.metadata:
-            metadata_ = self._data.invocation.metadata.model_dump_json()
+            metadata_ = metadata
+        elif isinstance(self._data.invocation, WithMetadata):
+            metadata_ = self._data.invocation.metadata
 
         # If `board_id` is provided directly, use that. Else, use the board provided by `WithBoard`, falling back to None.
         board_id_ = None
@@ -191,14 +191,6 @@ 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,
@@ -206,8 +198,7 @@ class ImagesInterface(InvocationContextInterface):
             board_id=board_id_,
             metadata=metadata_,
             image_origin=ResourceOrigin.INTERNAL,
-            workflow=workflow_,
-            graph=graph_,
+            workflow=self._data.queue_item.workflow,
             session_id=self._data.queue_item.session_id,
             node_id=self._data.invocation.id,
         )

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

@@ -12,7 +12,6 @@ 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
 
 
@@ -42,7 +41,6 @@ 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

@@ -1,35 +0,0 @@
-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/public/locales/en.json

@@ -2,7 +2,6 @@
     "accessibility": {
         "about": "About",
         "createIssue": "Create Issue",
-        "submitSupportTicket": "Submit Support Ticket",
         "invokeProgressBar": "Invoke progress bar",
         "menu": "Menu",
         "mode": "Mode",
@@ -147,9 +146,7 @@
         "viewing": "Viewing",
         "viewingDesc": "Review images in a large gallery view",
         "editing": "Editing",
-        "editingDesc": "Edit on the Control Layers canvas",
-        "enabled": "Enabled",
-        "disabled": "Disabled"
+        "editingDesc": "Edit on the Control Layers canvas"
     },
     "controlnet": {
         "controlAdapter_one": "Control Adapter",
@@ -778,14 +775,10 @@
         "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",
-        "singleFieldType": "{{name}} (Single)",
-        "collectionFieldType": "{{name}} (Collection)",
-        "collectionOrScalarFieldType": "{{name}} (Single or Collection)",
+        "collectionFieldType": "{{name}} Collection",
+        "collectionOrScalarFieldType": "{{name}} Collection|Scalar",
         "colorCodeEdges": "Color-Code Edges",
         "colorCodeEdgesHelp": "Color-code edges according to their connected fields",
         "connectionWouldCreateCycle": "Connection would create a cycle",
@@ -887,7 +880,6 @@
         "versionUnknown": " Version Unknown",
         "workflow": "Workflow",
         "graph": "Graph",
-        "noGraph": "No Graph",
         "workflowAuthor": "Author",
         "workflowContact": "Contact",
         "workflowDescription": "Short Description",
@@ -900,10 +892,7 @@
         "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.",
-        "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"
+        "prototypeDesc": "This invocation is a prototype. It may have breaking changes during app updates and may be removed at any time."
     },
     "parameters": {
         "aspect": "Aspect",
@@ -958,7 +947,7 @@
                 "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 {{multiple}}",
+                "t2iAdapterIncompatibleDimensions": "T2I Adapter requires image dimension to be multiples of 64",
                 "ipAdapterNoModelSelected": "no IP adapter selected",
                 "ipAdapterIncompatibleBaseModel": "incompatible IP Adapter base model",
                 "ipAdapterNoImageSelected": "no IP Adapter image selected",
@@ -1076,9 +1065,8 @@
     },
     "toast": {
         "addedToBoard": "Added to board",
-        "baseModelChanged": "Base Model Changed",
-        "baseModelChangedCleared_one": "Cleared or disabled {{count}} incompatible submodel",
-        "baseModelChangedCleared_other": "Cleared or disabled {{count}} incompatible submodels",
+        "baseModelChangedCleared_one": "Base model changed, cleared or disabled {{count}} incompatible submodel",
+        "baseModelChangedCleared_other": "Base model changed, cleared or disabled {{count}} incompatible submodels",
         "canceled": "Processing Canceled",
         "canvasCopiedClipboard": "Canvas Copied to Clipboard",
         "canvasDownloaded": "Canvas Downloaded",
@@ -1099,17 +1087,10 @@
         "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",
-        "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",
+        "parameterNotSet": "{{parameter}} not set",
+        "parameterSet": "{{parameter}} set",
+        "parametersNotSet": "Parameters Not Set",
         "problemCopyingCanvas": "Problem Copying Canvas",
         "problemCopyingCanvasDesc": "Unable to export base layer",
         "problemCopyingImage": "Unable to Copy Image",
@@ -1129,13 +1110,11 @@
         "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",
@@ -1575,6 +1554,7 @@
         "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 recuperados",
+        "parametersNotSet": "Parámetros no establecidos",
         "metadataLoadFailed": "Error al cargar metadatos",
         "serverError": "Error en el servidor",
         "canceled": "Procesando la cancelación",
@@ -390,8 +390,7 @@
         "uploadFailedInvalidUploadDesc": "Debe ser una sola imagen PNG o JPEG",
         "parameterSet": "Conjunto de parámetros",
         "parameterNotSet": "Parámetro no configurado",
-        "problemCopyingImage": "No se puede copiar la imagen",
-        "errorCopied": "Error al copiar"
+        "problemCopyingImage": "No se puede copiar la imagen"
     },
     "tooltip": {
         "feature": {

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

@@ -524,20 +524,7 @@
             "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",
-            "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"
-            }
+            "imageNotProcessedForControlAdapter": "L'immagine dell'adattatore di controllo #{{number}} non è stata elaborata"
         },
         "useCpuNoise": "Usa la CPU per generare rumore",
         "iterations": "Iterazioni",
@@ -837,8 +824,8 @@
         "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}} (Singola o Raccolta)",
+        "collectionFieldType": "{{name}} Raccolta",
+        "collectionOrScalarFieldType": "{{name}} Raccolta|Scalare",
         "nodeVersion": "Versione Nodo",
         "inputFieldTypeParseError": "Impossibile analizzare il tipo di campo di input {{node}}.{{field}} ({{message}})",
         "unsupportedArrayItemType": "Tipo di elemento dell'array non supportato \"{{type}}\"",
@@ -876,13 +863,7 @@
         "edit": "Modifica",
         "graph": "Grafico",
         "showEdgeLabelsHelp": "Mostra etichette sui collegamenti, che indicano i nodi collegati",
-        "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)"
+        "showEdgeLabels": "Mostra le etichette del collegamento"
     },
     "boards": {
         "autoAddBoard": "Aggiungi automaticamente bacheca",
@@ -1053,16 +1034,7 @@
         "graphFailedToQueue": "Impossibile mettere in coda il grafico",
         "batchFieldValues": "Valori Campi Lotto",
         "time": "Tempo",
-        "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"
+        "openQueue": "Apri coda"
     },
     "models": {
         "noMatchingModels": "Nessun modello corrispondente",
@@ -1591,6 +1563,7 @@
         "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": "Werkstromen",
+        "nodes": "Werkstroom-editor",
         "upload": "Upload",
         "load": "Laad",
         "statusDisconnected": "Niet verbonden",
@@ -34,60 +34,7 @@
         "controlNet": "ControlNet",
         "imageFailedToLoad": "Kan afbeelding niet laden",
         "learnMore": "Meer informatie",
-        "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"
+        "advanced": "Uitgebreid"
     },
     "gallery": {
         "galleryImageSize": "Afbeeldingsgrootte",
@@ -363,41 +310,10 @@
         "modelSyncFailed": "Synchronisatie modellen mislukt",
         "modelDeleteFailed": "Model kon niet verwijderd worden",
         "convertingModelBegin": "Model aan het converteren. Even geduld.",
-        "predictionType": "Soort voorspelling",
+        "predictionType": "Soort voorspelling (voor Stable Diffusion 2.x-modellen en incidentele Stable Diffusion 1.x-modellen)",
         "advanced": "Uitgebreid",
         "modelType": "Soort model",
-        "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"
+        "vaePrecision": "Nauwkeurigheid VAE"
     },
     "parameters": {
         "images": "Afbeeldingen",
@@ -437,13 +353,13 @@
         "copyImage": "Kopieer afbeelding",
         "denoisingStrength": "Sterkte ontruisen",
         "scheduler": "Planner",
-        "seamlessXAxis": "Naadloze tegels in x-as",
-        "seamlessYAxis": "Naadloze tegels in y-as",
+        "seamlessXAxis": "X-as",
+        "seamlessYAxis": "Y-as",
         "clipSkip": "Overslaan CLIP",
         "negativePromptPlaceholder": "Negatieve prompt",
         "controlNetControlMode": "Aansturingsmodus",
         "positivePromptPlaceholder": "Positieve prompt",
-        "maskBlur": "Vervaging van masker",
+        "maskBlur": "Vervaag",
         "invoke": {
             "noNodesInGraph": "Geen knooppunten in graaf",
             "noModelSelected": "Geen model ingesteld",
@@ -453,25 +369,11 @@
             "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 niet compatibel met het hoofdmodel.",
+            "incompatibleBaseModelForControlAdapter": "Model van controle-adapter #{{number}} is ongeldig in combinatie met het hoofdmodel.",
             "systemDisconnected": "Systeem is niet verbonden",
             "missingNodeTemplate": "Knooppuntsjabloon ontbreekt",
             "missingFieldTemplate": "Veldsjabloon ontbreekt",
-            "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"
+            "addingImagesTo": "Bezig met toevoegen van afbeeldingen aan"
         },
         "isAllowedToUpscale": {
             "useX2Model": "Afbeelding is te groot om te vergroten met het x4-model. Gebruik hiervoor het x2-model",
@@ -481,26 +383,7 @@
         "useCpuNoise": "Gebruik CPU-ruis",
         "imageActions": "Afbeeldingshandeling",
         "iterations": "Iteraties",
-        "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"
+        "coherenceMode": "Modus"
     },
     "settings": {
         "models": "Modellen",
@@ -527,12 +410,7 @@
         "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",
-        "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"
+        "intermediatesClearedFailed": "Fout bij wissen van tussentijdse afbeeldingen"
     },
     "toast": {
         "uploadFailed": "Upload mislukt",
@@ -547,8 +425,8 @@
         "connected": "Verbonden met server",
         "canceled": "Verwerking geannuleerd",
         "uploadFailedInvalidUploadDesc": "Moet een enkele PNG- of JPEG-afbeelding zijn",
-        "parameterNotSet": "{{parameter}} niet ingesteld",
-        "parameterSet": "{{parameter}} ingesteld",
+        "parameterNotSet": "Parameter niet ingesteld",
+        "parameterSet": "Instellen parameters",
         "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",
@@ -565,11 +443,11 @@
         "maskSavedAssets": "Masker bewaard in Assets",
         "problemDownloadingCanvas": "Fout bij downloaden van canvas",
         "problemMergingCanvas": "Fout bij samenvoegen canvas",
-        "setCanvasInitialImage": "Initiële canvasafbeelding ingesteld",
+        "setCanvasInitialImage": "Ingesteld als initiële canvasafbeelding",
         "imageUploaded": "Afbeelding geüpload",
         "addedToBoard": "Toegevoegd aan bord",
         "workflowLoaded": "Werkstroom geladen",
-        "modelAddedSimple": "Model toegevoegd aan wachtrij",
+        "modelAddedSimple": "Model toegevoegd",
         "problemImportingMaskDesc": "Kan masker niet exporteren",
         "problemCopyingCanvas": "Fout bij kopiëren canvas",
         "problemSavingCanvas": "Fout bij bewaren canvas",
@@ -581,18 +459,7 @@
         "maskSentControlnetAssets": "Masker gestuurd naar ControlNet en Assets",
         "canvasSavedGallery": "Canvas bewaard in galerij",
         "imageUploadFailed": "Fout bij uploaden afbeelding",
-        "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"
+        "problemImportingMask": "Fout bij importeren masker"
     },
     "tooltip": {
         "feature": {
@@ -666,11 +533,7 @@
         "showOptionsPanel": "Toon zijscherm",
         "menu": "Menu",
         "showGalleryPanel": "Toon deelscherm Galerij",
-        "loadMore": "Laad meer",
-        "about": "Over",
-        "mode": "Modus",
-        "resetUI": "$t(accessibility.reset) UI",
-        "createIssue": "Maak probleem aan"
+        "loadMore": "Laad meer"
     },
     "nodes": {
         "zoomOutNodes": "Uitzoomen",
@@ -684,7 +547,7 @@
         "loadWorkflow": "Laad werkstroom",
         "downloadWorkflow": "Download JSON van werkstroom",
         "scheduler": "Planner",
-        "missingTemplate": "Ongeldig knooppunt: knooppunt {{node}} van het soort {{type}} heeft een ontbrekend sjabloon (niet geïnstalleerd?)",
+        "missingTemplate": "Ontbrekende sjabloon",
         "workflowDescription": "Korte beschrijving",
         "versionUnknown": " Versie onbekend",
         "noNodeSelected": "Geen knooppunt gekozen",
@@ -700,7 +563,7 @@
         "integer": "Geheel getal",
         "nodeTemplate": "Sjabloon knooppunt",
         "nodeOpacity": "Dekking knooppunt",
-        "unableToLoadWorkflow": "Fout bij laden werkstroom",
+        "unableToLoadWorkflow": "Kan werkstroom niet valideren",
         "snapToGrid": "Lijn uit op raster",
         "noFieldsLinearview": "Geen velden toegevoegd aan lineaire weergave",
         "nodeSearch": "Zoek naar knooppunten",
@@ -751,56 +614,11 @@
         "unknownField": "Onbekend veld",
         "colorCodeEdges": "Kleurgecodeerde randen",
         "unknownNode": "Onbekend knooppunt",
-        "mismatchedVersion": "Ongeldig knooppunt: knooppunt {{node}} van het soort {{type}} heeft een niet-overeenkomende versie (probeer het bij te werken?)",
+        "mismatchedVersion": "Heeft niet-overeenkomende versie",
         "addNodeToolTip": "Voeg knooppunt toe (Shift+A, spatie)",
         "loadingNodes": "Bezig met laden van knooppunten...",
         "snapToGridHelp": "Lijn knooppunten uit op raster bij verplaatsing",
-        "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"
+        "workflowSettings": "Instellingen werkstroomeditor"
     },
     "controlnet": {
         "amult": "a_mult",
@@ -873,28 +691,9 @@
         "canny": "Canny",
         "depthZoeDescription": "Genereer diepteblad via Zoe",
         "hedDescription": "Herkenning van holistisch-geneste randen",
-        "setControlImageDimensions": "Kopieer grootte naar B/H (optimaliseer voor model)",
+        "setControlImageDimensions": "Stel afmetingen controle-afbeelding in op B/H",
         "scribble": "Krabbel",
-        "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)"
+        "maxFaces": "Max. gezichten"
     },
     "dynamicPrompts": {
         "seedBehaviour": {
@@ -907,10 +706,7 @@
         "maxPrompts": "Max. prompts",
         "promptsWithCount_one": "{{count}} prompt",
         "promptsWithCount_other": "{{count}} prompts",
-        "dynamicPrompts": "Dynamische prompts",
-        "showDynamicPrompts": "Toon dynamische prompts",
-        "loading": "Genereren van dynamische prompts...",
-        "promptsPreview": "Voorvertoning prompts"
+        "dynamicPrompts": "Dynamische prompts"
     },
     "popovers": {
         "noiseUseCPU": {
@@ -923,7 +719,7 @@
         },
         "paramScheduler": {
             "paragraphs": [
-                "De planner gebruikt gedurende het genereringsproces."
+                "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."
             ],
             "heading": "Planner"
         },
@@ -1010,8 +806,8 @@
         },
         "clipSkip": {
             "paragraphs": [
-                "Aantal over te slaan CLIP-modellagen.",
-                "Bepaalde modellen zijn beter geschikt met bepaalde Overslaan CLIP-instellingen."
+                "Kies hoeveel CLIP-modellagen je wilt overslaan.",
+                "Bepaalde modellen werken beter met bepaalde Overslaan CLIP-instellingen."
             ],
             "heading": "Overslaan CLIP"
         },
@@ -1195,26 +991,17 @@
         "denoisingStrength": "Sterkte ontruising",
         "refinermodel": "Verfijningsmodel",
         "posAestheticScore": "Positieve esthetische score",
-        "concatPromptStyle": "Koppelen van prompt en stijl",
+        "concatPromptStyle": "Plak prompt- en stijltekst aan elkaar",
         "loading": "Bezig met laden...",
         "steps": "Stappen",
-        "posStylePrompt": "Positieve-stijlprompt",
-        "freePromptStyle": "Handmatige stijlprompt",
-        "refinerSteps": "Aantal stappen verfijner"
+        "posStylePrompt": "Positieve-stijlprompt"
     },
     "models": {
         "noMatchingModels": "Geen overeenkomend modellen",
         "loading": "bezig met laden",
         "noMatchingLoRAs": "Geen overeenkomende LoRA's",
         "noModelsAvailable": "Geen modellen beschikbaar",
-        "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"
+        "selectModel": "Kies een model"
     },
     "boards": {
         "autoAddBoard": "Voeg automatisch bord toe",
@@ -1232,13 +1019,7 @@
         "downloadBoard": "Download bord",
         "changeBoard": "Wijzig bord",
         "loading": "Bezig met laden...",
-        "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:"
+        "clearSearch": "Maak zoekopdracht leeg"
     },
     "invocationCache": {
         "disable": "Schakel uit",
@@ -1255,39 +1036,5 @@
         "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

@@ -1594,6 +1594,7 @@
         "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/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 = {};
 
@@ -46,7 +46,6 @@ const App = ({ config = DEFAULT_CONFIG, selectedImage }: Props) => {
   useSocketIO();
   useGlobalModifiersInit();
   useGlobalHotkeys();
-  useGetOpenAPISchemaQuery();
 
   const { dropzone, isHandlingUpload, setIsHandlingUpload } = useFullscreenDropzone();
 
@@ -95,6 +94,7 @@ const App = ({ config = DEFAULT_CONFIG, selectedImage }: Props) => {
       <DeleteImageModal />
       <ChangeBoardModal />
       <DynamicPromptsModal />
+      <Toaster />
       <PreselectedImage selectedImage={selectedImage} />
     </ErrorBoundary>
   );

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

@@ -1,8 +1,5 @@
-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 { Button, Flex, Heading, Link, Text, useToast } from '@invoke-ai/ui-library';
 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';
@@ -14,39 +11,31 @@ 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({
-      id: 'ERROR_COPIED',
-      title: t('toast.errorCopied'),
+      title: 'Error Copied',
     });
-  }, [error, t]);
+  }, [error, toast]);
 
-  const url = useMemo(() => {
-    if (isLocal) {
-      return newGithubIssueUrl({
+  const url = useMemo(
+    () =>
+      newGithubIssueUrl({
         user: 'invoke-ai',
         repo: 'InvokeAI',
         template: 'BUG_REPORT.yml',
         title: `[bug]: ${error.name}: ${error.message}`,
-      });
-    } else {
-      return 'https://support.invoke.ai/support/tickets/new';
-    }
-  }, [error.message, error.name, isLocal]);
-
+      }),
+    [error.message, error.name]
+  );
   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}>
-        <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>
-
+        <Heading>{t('common.somethingWentWrong')}</Heading>
         <Flex
           layerStyle="second"
           px={8}
@@ -68,9 +57,7 @@ const AppErrorBoundaryFallback = ({ error, resetErrorBoundary }: Props) => {
             {t('common.copyError')}
           </Button>
           <Link href={url} isExternal>
-            <Button leftIcon={<PiArrowSquareOutBold />}>
-              {isLocal ? t('accessibility.createIssue') : t('accessibility.submitSupportTicket')}
-            </Button>
+            <Button leftIcon={<PiArrowSquareOutBold />}>{t('accessibility.createIssue')}</Button>
           </Link>
         </Flex>
       </Flex>

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

@@ -0,0 +1,44 @@
+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/store/middleware/listenerMiddleware/index.ts

@@ -41,10 +41,12 @@ 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';
@@ -112,6 +114,8 @@ 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 { toast } from 'features/toast/toast';
+import { addToast } from 'features/system/store/systemSlice';
 import { t } from 'i18next';
 import { queueApi } from 'services/api/endpoints/queue';
 
@@ -30,20 +30,22 @@ export const addCommitStagingAreaImageListener = (startAppListening: AppStartLis
         req.reset();
         if (canceled > 0) {
           log.debug(`Canceled ${canceled} canvas batches`);
-          toast({
-            id: 'CANCEL_BATCH_SUCCEEDED',
-            title: t('queue.cancelBatchSucceeded'),
-            status: 'success',
-          });
+          dispatch(
+            addToast({
+              title: t('queue.cancelBatchSucceeded'),
+              status: 'success',
+            })
+          );
         }
         dispatch(canvasBatchIdsReset());
       } catch {
         log.error('Failed to cancel canvas batches');
-        toast({
-          id: 'CANCEL_BATCH_FAILED',
-          title: t('queue.cancelBatchFailed'),
-          status: 'error',
-        });
+        dispatch(
+          addToast({
+            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';
@@ -16,15 +16,18 @@ export const addBatchEnqueuedListener = (startAppListening: AppStartListening) =
       const arg = action.meta.arg.originalArgs;
       logger('queue').debug({ enqueueResult: parseify(response) }, 'Batch enqueued');
 
-      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'),
-        }),
-      });
+      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',
+        });
+      }
     },
   });
 
@@ -37,10 +40,9 @@ export const addBatchEnqueuedListener = (startAppListening: AppStartListening) =
 
       if (!response) {
         toast({
-          id: 'QUEUE_BATCH_FAILED',
           title: t('queue.batchFailedToQueue'),
           status: 'error',
-          description: t('common.unknownError'),
+          description: 'Unknown Error',
         });
         logger('queue').error({ batchConfig: parseify(arg), error: parseify(response) }, t('queue.batchFailedToQueue'));
         return;
@@ -50,7 +52,7 @@ export const addBatchEnqueuedListener = (startAppListening: AppStartListening) =
       if (result.success) {
         result.data.data.detail.map((e) => {
           toast({
-            id: 'QUEUE_BATCH_FAILED',
+            id: 'batch-failed-to-queue',
             title: truncate(upperFirst(e.msg), { length: 128 }),
             status: 'error',
             description: truncate(
@@ -62,10 +64,9 @@ export const addBatchEnqueuedListener = (startAppListening: AppStartListening) =
         });
       } else if (response.status !== 403) {
         toast({
-          id: 'QUEUE_BATCH_FAILED',
           title: t('queue.batchFailedToQueue'),
-          status: 'error',
           description: t('common.unknownError'),
+          status: 'error',
         });
       }
       logger('queue').error({ batchConfig: parseify(arg), error: parseify(response) }, t('queue.batchFailedToQueue'));

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

@@ -1,7 +1,8 @@
+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 'features/toast/toast';
+import { toast } from 'common/util/toast';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
 import {
@@ -27,6 +28,7 @@ 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,
       });
     },
   });
@@ -38,9 +40,9 @@ 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: 'error',
+        status: 'success',
+        isClosable: true,
       });
     },
   });
@@ -63,7 +65,7 @@ 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}`;
 
-      toast({
+      const toastOptions: UseToastOptions = {
         id: bulk_download_item_name,
         title: t('gallery.bulkDownloadReady', 'Download ready'),
         status: 'success',
@@ -75,7 +77,14 @@ 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);
+      }
     },
   });
 
@@ -86,13 +95,20 @@ export const addBulkDownloadListeners = (startAppListening: AppStartListening) =
 
       const { bulk_download_item_name } = action.payload.data;
 
-      toast({
+      const toastOptions: UseToastOptions = {
         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, { getState }) => {
+    effect: async (action, { dispatch, getState }) => {
       const moduleLog = $logger.get().child({ namespace: 'canvasCopiedToClipboardListener' });
       const state = getState();
 
@@ -19,20 +19,22 @@ export const addCanvasCopiedToClipboardListener = (startAppListening: AppStartLi
         copyBlobToClipboard(blob);
       } catch (err) {
         moduleLog.error(String(err));
-        toast({
-          id: 'CANVAS_COPY_FAILED',
-          title: t('toast.problemCopyingCanvas'),
-          description: t('toast.problemCopyingCanvasDesc'),
-          status: 'error',
-        });
+        dispatch(
+          addToast({
+            title: t('toast.problemCopyingCanvas'),
+            description: t('toast.problemCopyingCanvasDesc'),
+            status: 'error',
+          })
+        );
         return;
       }
 
-      toast({
-        id: 'CANVAS_COPY_SUCCEEDED',
-        title: t('toast.canvasCopiedClipboard'),
-        status: 'success',
-      });
+      dispatch(
+        addToast({
+          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 { toast } from 'features/toast/toast';
+import { addToast } from 'features/system/store/systemSlice';
 import { t } from 'i18next';
 
 export const addCanvasDownloadedAsImageListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: canvasDownloadedAsImage,
-    effect: async (action, { getState }) => {
+    effect: async (action, { dispatch, getState }) => {
       const moduleLog = $logger.get().child({ namespace: 'canvasSavedToGalleryListener' });
       const state = getState();
 
@@ -18,17 +18,18 @@ export const addCanvasDownloadedAsImageListener = (startAppListening: AppStartLi
         blob = await getBaseLayerBlob(state);
       } catch (err) {
         moduleLog.error(String(err));
-        toast({
-          id: 'CANVAS_DOWNLOAD_FAILED',
-          title: t('toast.problemDownloadingCanvas'),
-          description: t('toast.problemDownloadingCanvasDesc'),
-          status: 'error',
-        });
+        dispatch(
+          addToast({
+            title: t('toast.problemDownloadingCanvas'),
+            description: t('toast.problemDownloadingCanvasDesc'),
+            status: 'error',
+          })
+        );
         return;
       }
 
       downloadBlob(blob, 'canvas.png');
-      toast({ id: 'CANVAS_DOWNLOAD_SUCCEEDED', title: t('toast.canvasDownloaded'), status: 'success' });
+      dispatch(addToast({ 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 { toast } from 'features/toast/toast';
+import { addToast } from 'features/system/store/systemSlice';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
 
@@ -20,12 +20,13 @@ export const addCanvasImageToControlNetListener = (startAppListening: AppStartLi
         blob = await getBaseLayerBlob(state, true);
       } catch (err) {
         log.error(String(err));
-        toast({
-          id: 'PROBLEM_SAVING_CANVAS',
-          title: t('toast.problemSavingCanvas'),
-          description: t('toast.problemSavingCanvasDesc'),
-          status: 'error',
-        });
+        dispatch(
+          addToast({
+            title: t('toast.problemSavingCanvas'),
+            description: t('toast.problemSavingCanvasDesc'),
+            status: 'error',
+          })
+        );
         return;
       }
 
@@ -42,7 +43,7 @@ export const addCanvasImageToControlNetListener = (startAppListening: AppStartLi
           crop_visible: false,
           postUploadAction: {
             type: 'TOAST',
-            title: t('toast.canvasSentControlnetAssets'),
+            toastOptions: { 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 { toast } from 'features/toast/toast';
+import { addToast } from 'features/system/store/systemSlice';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
 
@@ -29,12 +29,13 @@ export const addCanvasMaskSavedToGalleryListener = (startAppListening: AppStartL
 
       if (!maskBlob) {
         log.error('Problem getting mask layer blob');
-        toast({
-          id: 'PROBLEM_SAVING_MASK',
-          title: t('toast.problemSavingMask'),
-          description: t('toast.problemSavingMaskDesc'),
-          status: 'error',
-        });
+        dispatch(
+          addToast({
+            title: t('toast.problemSavingMask'),
+            description: t('toast.problemSavingMaskDesc'),
+            status: 'error',
+          })
+        );
         return;
       }
 
@@ -51,7 +52,7 @@ export const addCanvasMaskSavedToGalleryListener = (startAppListening: AppStartL
           crop_visible: true,
           postUploadAction: {
             type: 'TOAST',
-            title: t('toast.maskSavedAssets'),
+            toastOptions: { 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 { toast } from 'features/toast/toast';
+import { addToast } from 'features/system/store/systemSlice';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
 
@@ -30,12 +30,13 @@ export const addCanvasMaskToControlNetListener = (startAppListening: AppStartLis
 
       if (!maskBlob) {
         log.error('Problem getting mask layer blob');
-        toast({
-          id: 'PROBLEM_IMPORTING_MASK',
-          title: t('toast.problemImportingMask'),
-          description: t('toast.problemImportingMaskDesc'),
-          status: 'error',
-        });
+        dispatch(
+          addToast({
+            title: t('toast.problemImportingMask'),
+            description: t('toast.problemImportingMaskDesc'),
+            status: 'error',
+          })
+        );
         return;
       }
 
@@ -52,7 +53,7 @@ export const addCanvasMaskToControlNetListener = (startAppListening: AppStartLis
           crop_visible: false,
           postUploadAction: {
             type: 'TOAST',
-            title: t('toast.maskSentControlnetAssets'),
+            toastOptions: { 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 { toast } from 'features/toast/toast';
+import { addToast } from 'features/system/store/systemSlice';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
 
@@ -17,12 +17,13 @@ export const addCanvasMergedListener = (startAppListening: AppStartListening) =>
 
       if (!blob) {
         moduleLog.error('Problem getting base layer blob');
-        toast({
-          id: 'PROBLEM_MERGING_CANVAS',
-          title: t('toast.problemMergingCanvas'),
-          description: t('toast.problemMergingCanvasDesc'),
-          status: 'error',
-        });
+        dispatch(
+          addToast({
+            title: t('toast.problemMergingCanvas'),
+            description: t('toast.problemMergingCanvasDesc'),
+            status: 'error',
+          })
+        );
         return;
       }
 
@@ -30,12 +31,13 @@ export const addCanvasMergedListener = (startAppListening: AppStartListening) =>
 
       if (!canvasBaseLayer) {
         moduleLog.error('Problem getting canvas base layer');
-        toast({
-          id: 'PROBLEM_MERGING_CANVAS',
-          title: t('toast.problemMergingCanvas'),
-          description: t('toast.problemMergingCanvasDesc'),
-          status: 'error',
-        });
+        dispatch(
+          addToast({
+            title: t('toast.problemMergingCanvas'),
+            description: t('toast.problemMergingCanvasDesc'),
+            status: 'error',
+          })
+        );
         return;
       }
 
@@ -52,7 +54,7 @@ export const addCanvasMergedListener = (startAppListening: AppStartListening) =>
           is_intermediate: true,
           postUploadAction: {
             type: 'TOAST',
-            title: t('toast.canvasMerged'),
+            toastOptions: { title: t('toast.canvasMerged') },
           },
         })
       ).unwrap();

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

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

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

@@ -14,9 +14,8 @@ import {
 } from 'features/controlLayers/store/controlLayersSlice';
 import { CA_PROCESSOR_DATA } from 'features/controlLayers/util/controlAdapters';
 import { isImageOutput } from 'features/nodes/types/common';
-import { toast } from 'features/toast/toast';
+import { addToast } from 'features/system/store/systemSlice';
 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';
@@ -48,10 +47,8 @@ const cancelProcessorBatch = async (dispatch: AppDispatch, layerId: string, batc
 export const addControlAdapterPreprocessor = (startAppListening: AppStartListening) => {
   startAppListening({
     matcher,
-    effect: async (action, { dispatch, getState, getOriginalState, cancelActiveListeners, delay, take, signal }) => {
+    effect: async (action, { dispatch, getState, 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();
@@ -60,33 +57,21 @@ 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) {
-        // - 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
+        // The user has reset the image or config, so we should clear the processed image
         dispatch(caLayerProcessedImageChanged({ layerId, imageDTO: null }));
-        return;
       }
 
       // At this point, the user has stopped fiddling with the processor settings and there is a processor selected.
@@ -96,8 +81,8 @@ export const addControlAdapterPreprocessor = (startAppListening: AppStartListeni
         cancelProcessorBatch(dispatch, layerId, layer.controlAdapter.processorPendingBatchId);
       }
 
-      // 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);
+      // @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);
       const enqueueBatchArg: BatchConfig = {
         prepend: true,
         batch: {
@@ -174,11 +159,12 @@ export const addControlAdapterPreprocessor = (startAppListening: AppStartListeni
             }
           }
 
-          toast({
-            id: 'GRAPH_QUEUE_FAILED',
-            title: t('queue.graphFailedToQueue'),
-            status: 'error',
-          });
+          dispatch(
+            addToast({
+              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 { toast } from 'features/toast/toast';
+import { addToast } from 'features/system/store/systemSlice';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
 import { queueApi } from 'services/api/endpoints/queue';
@@ -108,11 +108,12 @@ export const addControlNetImageProcessedListener = (startAppListening: AppStartL
           }
         }
 
-        toast({
-          id: 'GRAPH_QUEUE_FAILED',
-          title: t('queue.graphFailedToQueue'),
-          status: 'error',
-        });
+        dispatch(
+          addToast({
+            title: t('queue.graphFailedToQueue'),
+            status: 'error',
+          })
+        );
       }
     },
   });

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

@@ -1,3 +1,4 @@
+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';
@@ -13,7 +14,7 @@ import {
 } from 'features/controlLayers/store/controlLayersSlice';
 import { fieldImageValueChanged } from 'features/nodes/store/nodesSlice';
 import { selectOptimalDimension } from 'features/parameters/store/generationSlice';
-import { toast } from 'features/toast/toast';
+import { addToast } from 'features/system/store/systemSlice';
 import { t } from 'i18next';
 import { omit } from 'lodash-es';
 import { boardsApi } from 'services/api/endpoints/boards';
@@ -41,17 +42,16 @@ export const addImageUploadedFulfilledListener = (startAppListening: AppStartLis
         return;
       }
 
-      const DEFAULT_UPLOADED_TOAST = {
-        id: 'IMAGE_UPLOADED',
+      const DEFAULT_UPLOADED_TOAST: UseToastOptions = {
         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') {
-          const title = postUploadAction.title || DEFAULT_UPLOADED_TOAST.title;
-          toast({ ...DEFAULT_UPLOADED_TOAST, title });
+          dispatch(addToast({ ...DEFAULT_UPLOADED_TOAST, ...toastOptions }));
         } else {
           // Add this image to the board
           dispatch(
@@ -70,20 +70,24 @@ export const addImageUploadedFulfilledListener = (startAppListening: AppStartLis
             ? `${t('toast.addedToBoard')} ${board.board_name}`
             : `${t('toast.addedToBoard')} ${autoAddBoardId}`;
 
-          toast({
-            ...DEFAULT_UPLOADED_TOAST,
-            description,
-          });
+          dispatch(
+            addToast({
+              ...DEFAULT_UPLOADED_TOAST,
+              description,
+            })
+          );
         }
         return;
       }
 
       if (postUploadAction?.type === 'SET_CANVAS_INITIAL_IMAGE') {
         dispatch(setInitialCanvasImage(imageDTO, selectOptimalDimension(state)));
-        toast({
-          ...DEFAULT_UPLOADED_TOAST,
-          description: t('toast.setAsCanvasInitialImage'),
-        });
+        dispatch(
+          addToast({
+            ...DEFAULT_UPLOADED_TOAST,
+            description: t('toast.setAsCanvasInitialImage'),
+          })
+        );
         return;
       }
 
@@ -101,56 +105,68 @@ export const addImageUploadedFulfilledListener = (startAppListening: AppStartLis
             controlImage: imageDTO.image_name,
           })
         );
-        toast({
-          ...DEFAULT_UPLOADED_TOAST,
-          description: t('toast.setControlImage'),
-        });
+        dispatch(
+          addToast({
+            ...DEFAULT_UPLOADED_TOAST,
+            description: t('toast.setControlImage'),
+          })
+        );
         return;
       }
 
       if (postUploadAction?.type === 'SET_CA_LAYER_IMAGE') {
         const { layerId } = postUploadAction;
         dispatch(caLayerImageChanged({ layerId, imageDTO }));
-        toast({
-          ...DEFAULT_UPLOADED_TOAST,
-          description: t('toast.setControlImage'),
-        });
+        dispatch(
+          addToast({
+            ...DEFAULT_UPLOADED_TOAST,
+            description: t('toast.setControlImage'),
+          })
+        );
       }
 
       if (postUploadAction?.type === 'SET_IPA_LAYER_IMAGE') {
         const { layerId } = postUploadAction;
         dispatch(ipaLayerImageChanged({ layerId, imageDTO }));
-        toast({
-          ...DEFAULT_UPLOADED_TOAST,
-          description: t('toast.setControlImage'),
-        });
+        dispatch(
+          addToast({
+            ...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 }));
-        toast({
-          ...DEFAULT_UPLOADED_TOAST,
-          description: t('toast.setControlImage'),
-        });
+        dispatch(
+          addToast({
+            ...DEFAULT_UPLOADED_TOAST,
+            description: t('toast.setControlImage'),
+          })
+        );
       }
 
       if (postUploadAction?.type === 'SET_II_LAYER_IMAGE') {
         const { layerId } = postUploadAction;
         dispatch(iiLayerImageChanged({ layerId, imageDTO }));
-        toast({
-          ...DEFAULT_UPLOADED_TOAST,
-          description: t('toast.setControlImage'),
-        });
+        dispatch(
+          addToast({
+            ...DEFAULT_UPLOADED_TOAST,
+            description: t('toast.setControlImage'),
+          })
+        );
       }
 
       if (postUploadAction?.type === 'SET_NODES_IMAGE') {
         const { nodeId, fieldName } = postUploadAction;
         dispatch(fieldImageValueChanged({ nodeId, fieldName, value: imageDTO }));
-        toast({
-          ...DEFAULT_UPLOADED_TOAST,
-          description: `${t('toast.setNodeField')} ${fieldName}`,
-        });
+        dispatch(
+          addToast({
+            ...DEFAULT_UPLOADED_TOAST,
+            description: `${t('toast.setNodeField')} ${fieldName}`,
+          })
+        );
         return;
       }
     },
@@ -158,7 +174,7 @@ export const addImageUploadedFulfilledListener = (startAppListening: AppStartLis
 
   startAppListening({
     matcher: imagesApi.endpoints.uploadImage.matchRejected,
-    effect: (action) => {
+    effect: (action, { dispatch }) => {
       const log = logger('images');
       const sanitizedData = {
         arg: {
@@ -167,11 +183,13 @@ export const addImageUploadedFulfilledListener = (startAppListening: AppStartLis
         },
       };
       log.error({ ...sanitizedData }, 'Image upload failed');
-      toast({
-        title: t('toast.imageUploadFailed'),
-        description: action.error.message,
-        status: 'error',
-      });
+      dispatch(
+        addToast({
+          title: t('toast.imageUploadFailed'),
+          description: action.error.message,
+          status: 'error',
+        })
+      );
     },
   });
 };

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

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

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

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

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

@@ -1,7 +1,7 @@
 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 { $nodeExecutionStates } from 'features/nodes/hooks/useExecutionState';
 import { zNodeStatus } from 'features/nodes/types/invocation';
 import { socketGeneratorProgress } from 'services/events/actions';
 
@@ -18,7 +18,6 @@ export const addGeneratorProgressEventListener = (startAppListening: AppStartLis
         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/socketInvocationError.ts

@@ -3,70 +3,24 @@ 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, { getState }) => {
+    effect: (action) => {
       log.error(action.payload, `Invocation error (${action.payload.data.node.type})`);
-      const { source_node_id, error_type, error_message, error_traceback, graph_execution_state_id } =
-        action.payload.data;
+      const { source_node_id } = action.payload.data;
       const nes = deepClone($nodeExecutionStates.get()[source_node_id]);
       if (nes) {
         nes.status = zNodeStatus.enum.FAILED;
+        nes.error = action.payload.data.error;
         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

@@ -0,0 +1,14 @@
+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/socketQueueItemStatusChanged.ts

@@ -43,15 +43,20 @@ 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',
-          { type: 'SessionQueueItem', id: queue_item.item_id },
-        ])
+        queueApi.util.invalidateTags(['CurrentSessionQueueItem', 'NextSessionQueueItem', 'InvocationCacheStatus'])
       );
 
       if (['in_progress'].includes(action.payload.data.queue_item.status)) {

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

@@ -0,0 +1,14 @@
+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 { toast } from 'features/toast/toast';
+import { addToast } from 'features/system/store/systemSlice';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
 
@@ -29,14 +29,15 @@ export const addStagingAreaImageSavedListener = (startAppListening: AppStartList
             })
           );
         }
-        toast({ id: 'IMAGE_SAVED', title: t('toast.imageSaved'), status: 'success' });
+        dispatch(addToast({ title: t('toast.imageSaved'), status: 'success' }));
       } catch (error) {
-        toast({
-          id: 'IMAGE_SAVE_FAILED',
-          title: t('toast.imageSavingFailed'),
-          description: (error as Error)?.message,
-          status: 'error',
-        });
+        dispatch(
+          addToast({
+            title: t('toast.imageSavingFailed'),
+            description: (error as Error)?.message,
+            status: 'error',
+          })
+        );
       }
     },
   });

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

@@ -1,11 +1,12 @@
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { updateAllNodesRequested } from 'features/nodes/store/actions';
-import { $templates, nodesChanged } from 'features/nodes/store/nodesSlice';
+import { $templates, nodeReplaced } 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 { toast } from 'features/toast/toast';
+import { addToast } from 'features/system/store/systemSlice';
+import { makeToast } from 'features/system/util/makeToast';
 import { t } from 'i18next';
 
 export const addUpdateAllNodesRequestedListener = (startAppListening: AppStartListening) => {
@@ -30,12 +31,7 @@ export const addUpdateAllNodesRequestedListener = (startAppListening: AppStartLi
         }
         try {
           const updatedNode = updateNode(node, template);
-          dispatch(
-            nodesChanged([
-              { type: 'remove', id: updatedNode.id },
-              { type: 'add', item: updatedNode },
-            ])
-          );
+          dispatch(nodeReplaced({ nodeId: updatedNode.id, node: updatedNode }));
         } catch (e) {
           if (e instanceof NodeUpdateError) {
             unableToUpdateCount++;
@@ -49,18 +45,24 @@ export const addUpdateAllNodesRequestedListener = (startAppListening: AppStartLi
             count: unableToUpdateCount,
           })
         );
-        toast({
-          id: 'UNABLE_TO_UPDATE_NODES',
-          title: t('nodes.unableToUpdateNodes', {
-            count: unableToUpdateCount,
-          }),
-        });
+        dispatch(
+          addToast(
+            makeToast({
+              title: t('nodes.unableToUpdateNodes', {
+                count: unableToUpdateCount,
+              }),
+            })
+          )
+        );
       } else {
-        toast({
-          id: 'ALL_NODES_UPDATED',
-          title: t('nodes.allNodesUpdated'),
-          status: 'success',
-        });
+        dispatch(
+          addToast(
+            makeToast({
+              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 { toast } from 'features/toast/toast';
+import { addToast } from 'features/system/store/systemSlice';
 import { t } from 'i18next';
 import { queueApi } from 'services/api/endpoints/queue';
 import type { BatchConfig, ImageDTO } from 'services/api/types';
@@ -29,11 +29,12 @@ export const addUpscaleRequestedListener = (startAppListening: AppStartListening
           { imageDTO },
           t(detailTKey ?? 'parameters.isAllowedToUpscale.tooLarge') // should never coalesce
         );
-        toast({
-          id: 'NOT_ALLOWED_TO_UPSCALE',
-          title: t(detailTKey ?? 'parameters.isAllowedToUpscale.tooLarge'), // should never coalesce
-          status: 'error',
-        });
+        dispatch(
+          addToast({
+            title: t(detailTKey ?? 'parameters.isAllowedToUpscale.tooLarge'), // should never coalesce
+            status: 'error',
+          })
+        );
         return;
       }
 
@@ -64,11 +65,12 @@ export const addUpscaleRequestedListener = (startAppListening: AppStartListening
         if (error instanceof Object && 'status' in error && error.status === 403) {
           return;
         } else {
-          toast({
-            id: 'GRAPH_QUEUE_FAILED',
-            title: t('queue.graphFailedToQueue'),
-            status: 'error',
-          });
+          dispatch(
+            addToast({
+              title: t('queue.graphFailedToQueue'),
+              status: 'error',
+            })
+          );
         }
       }
     },

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

@@ -4,62 +4,49 @@ 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 { toast } from 'features/toast/toast';
+import { addToast } from 'features/system/store/systemSlice';
+import { makeToast } from 'features/system/util/makeToast';
 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: async (action, { dispatch }) => {
+    effect: (action, { dispatch }) => {
       const log = logger('nodes');
-      const { data, asCopy } = action.payload;
+      const { workflow, asCopy } = action.payload;
       const nodeTemplates = $templates.get();
 
       try {
-        const { workflow, warnings } = await getWorkflow(data, nodeTemplates);
+        const { workflow: validatedWorkflow, warnings } = validateWorkflow(workflow, nodeTemplates);
 
         if (asCopy) {
           // If we're loading a copy, we need to remove the ID so that the backend will create a new workflow
-          delete workflow.id;
+          delete validatedWorkflow.id;
         }
 
-        dispatch(workflowLoaded(workflow));
+        dispatch(workflowLoaded(validatedWorkflow));
         if (!warnings.length) {
-          toast({
-            id: 'WORKFLOW_LOADED',
-            title: t('toast.workflowLoaded'),
-            status: 'success',
-          });
+          dispatch(
+            addToast(
+              makeToast({
+                title: t('toast.workflowLoaded'),
+                status: 'success',
+              })
+            )
+          );
         } else {
-          toast({
-            id: 'WORKFLOW_LOADED',
-            title: t('toast.loadedWithWarnings'),
-            status: 'warning',
-          });
-
+          dispatch(
+            addToast(
+              makeToast({
+                title: t('toast.loadedWithWarnings'),
+                status: 'warning',
+              })
+            )
+          );
           warnings.forEach(({ message, ...rest }) => {
             log.warn(rest, message);
           });
@@ -72,42 +59,54 @@ 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);
-          toast({
-            id: 'UNABLE_TO_VALIDATE_WORKFLOW',
-            title: t('nodes.unableToValidateWorkflow'),
-            status: 'error',
-            description: e.message,
-          });
+          dispatch(
+            addToast(
+              makeToast({
+                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);
-          toast({
-            id: 'UNABLE_TO_VALIDATE_WORKFLOW',
-            title: t('nodes.unableToValidateWorkflow'),
-            status: 'error',
-            description: e.message,
-          });
+          dispatch(
+            addToast(
+              makeToast({
+                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);
-          toast({
-            id: 'UNABLE_TO_VALIDATE_WORKFLOW',
-            title: t('nodes.unableToValidateWorkflow'),
-            status: 'error',
-            description: message,
-          });
+          dispatch(
+            addToast(
+              makeToast({
+                title: t('nodes.unableToValidateWorkflow'),
+                status: 'error',
+                description: message,
+              })
+            )
+          );
         } else {
           // Some other error occurred
           log.error({ error: parseify(e) }, t('nodes.unknownErrorValidatingWorkflow'));
-          toast({
-            id: 'UNABLE_TO_VALIDATE_WORKFLOW',
-            title: t('nodes.unableToValidateWorkflow'),
-            status: 'error',
-            description: t('nodes.unknownErrorValidatingWorkflow'),
-          });
+          dispatch(
+            addToast(
+              makeToast({
+                title: t('nodes.unableToValidateWorkflow'),
+                status: 'error',
+                description: t('nodes.unknownErrorValidatingWorkflow'),
+              })
+            )
+          );
         }
       }
     },

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

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

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

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

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

@@ -1,12 +1,13 @@
 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);
@@ -36,15 +37,16 @@ export const useDownloadImage = () => {
         window.URL.revokeObjectURL(url);
         dispatch(imageDownloaded());
       } catch (err) {
-        toast({
-          id: 'PROBLEM_DOWNLOADING_IMAGE',
+        toaster({
           title: t('toast.problemDownloadingImage'),
           description: String(err),
           status: 'error',
+          duration: 2500,
+          isClosable: true,
         });
       }
     },
-    [t, dispatch, authToken]
+    [t, toaster, 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';
@@ -26,6 +26,7 @@ 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);
@@ -36,14 +37,13 @@ export const useFullscreenDropzone = () => {
     (rejection: FileRejection) => {
       setIsHandlingUpload(true);
 
-      toast({
-        id: 'UPLOAD_FAILED',
+      toaster({
         title: t('toast.uploadFailed'),
         description: rejection.errors.map((error) => error.message).join('\n'),
         status: 'error',
       });
     },
-    [t]
+    [t, toaster]
   );
 
   const fileAcceptedCallback = useCallback(
@@ -62,8 +62,7 @@ export const useFullscreenDropzone = () => {
   const onDrop = useCallback(
     (acceptedFiles: Array<File>, fileRejections: Array<FileRejection>) => {
       if (fileRejections.length > 1) {
-        toast({
-          id: 'UPLOAD_FAILED',
+        toaster({
           title: t('toast.uploadFailed'),
           description: t('toast.uploadFailedInvalidUploadDesc'),
           status: 'error',
@@ -79,7 +78,7 @@ export const useFullscreenDropzone = () => {
         fileAcceptedCallback(file);
       });
     },
-    [t, fileAcceptedCallback, fileRejectionCallback]
+    [t, toaster, fileAcceptedCallback, fileRejectionCallback]
   );
 
   const onDragOver = useCallback(() => {

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

@@ -137,7 +137,7 @@ const createSelector = (templates: Templates) =>
                 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 }));
+                    problems.push(i18n.t('parameters.invoke.layer.t2iAdapterIncompatibleDimensions'));
                   }
                 }
               }

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

@@ -0,0 +1,6 @@
+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/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 { LayerIsEnabledToggle } from 'features/controlLayers/components/LayerCommon/LayerVisibilityToggle';
+import { LayerVisibilityToggle } 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}>
-        <LayerIsEnabledToggle layerId={layerId} />
+        <LayerVisibilityToggle 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 { LayerIsEnabledToggle } from 'features/controlLayers/components/LayerCommon/LayerVisibilityToggle';
+import { LayerVisibilityToggle } 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}>
-        <LayerIsEnabledToggle layerId={layerId} />
+        <LayerVisibilityToggle 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 { LayerIsEnabledToggle } from 'features/controlLayers/components/LayerCommon/LayerVisibilityToggle';
+import { LayerVisibilityToggle } 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}>
-        <LayerIsEnabledToggle layerId={layerId} />
+        <LayerVisibilityToggle 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 { useLayerIsEnabled } from 'features/controlLayers/hooks/layerStateHooks';
-import { layerIsEnabledToggled } from 'features/controlLayers/store/controlLayersSlice';
+import { useLayerIsVisible } from 'features/controlLayers/hooks/layerStateHooks';
+import { layerVisibilityToggled } 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 LayerIsEnabledToggle = memo(({ layerId }: Props) => {
+export const LayerVisibilityToggle = memo(({ layerId }: Props) => {
   const { t } = useTranslation();
   const dispatch = useAppDispatch();
-  const isEnabled = useLayerIsEnabled(layerId);
+  const isVisible = useLayerIsVisible(layerId);
   const onClick = useCallback(() => {
-    dispatch(layerIsEnabledToggled(layerId));
+    dispatch(layerVisibilityToggled(layerId));
   }, [dispatch, layerId]);
 
   return (
     <IconButton
       size="sm"
-      aria-label={t(isEnabled ? 'common.enabled' : 'common.disabled')}
-      tooltip={t(isEnabled ? 'common.enabled' : 'common.disabled')}
+      aria-label={t('controlLayers.toggleVisibility')}
+      tooltip={t('controlLayers.toggleVisibility')}
       variant="outline"
-      icon={isEnabled ? <PiCheckBold /> : undefined}
+      icon={isVisible ? <PiCheckBold /> : undefined}
       onClick={onClick}
       colorScheme="base"
       onDoubleClick={stopPropagation} // double click expands the layer
@@ -33,4 +33,4 @@ export const LayerIsEnabledToggle = memo(({ layerId }: Props) => {
   );
 });
 
-LayerIsEnabledToggle.displayName = 'LayerVisibilityToggle';
+LayerVisibilityToggle.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 { LayerIsEnabledToggle } from 'features/controlLayers/components/LayerCommon/LayerVisibilityToggle';
+import { LayerVisibilityToggle } 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}>
-        <LayerIsEnabledToggle layerId={layerId} />
+        <LayerVisibilityToggle layerId={layerId} />
         <LayerTitle type="regional_guidance_layer" />
         <Spacer />
         {autoNegative === 'invert' && (

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

@@ -45,6 +45,7 @@ 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

@@ -45,6 +45,7 @@ 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 useLayerIsEnabled = (layerId: string) => {
+export const useLayerIsVisible = (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);
     },
-    layerIsEnabledToggled: (state, action: PayloadAction<string>) => {
+    layerVisibilityToggled: (state, action: PayloadAction<string>) => {
       const layer = state.layers.find((l) => l.id === action.payload);
       if (layer) {
         layer.isEnabled = !layer.isEnabled;
@@ -616,24 +616,12 @@ 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,
+          opacity: 1,
           x: 0,
           y: 0,
           bbox: null,
@@ -641,7 +629,7 @@ export const controlLayersSlice = createSlice({
           isEnabled: true,
           image: imageDTO ? imageDTOToImageWithDims(imageDTO) : null,
           isSelected: true,
-          denoisingStrength,
+          denoisingStrength: 0.75,
         };
         state.layers.push(layer);
         exclusivelySelectLayer(state, layer.id);
@@ -791,7 +779,7 @@ class LayerColors {
 export const {
   // Any Layer Type
   layerSelected,
-  layerIsEnabledToggled,
+  layerVisibilityToggled,
   layerTranslated,
   layerBboxChanged,
   layerReset,

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

@@ -1,5 +1,6 @@
 import { Flex, MenuDivider, MenuItem, Spinner } from '@invoke-ai/ui-library';
 import { useStore } from '@nanostores/react';
+import { useAppToaster } from 'app/components/Toaster';
 import { $customStarUI } from 'app/store/nanostores/customStarUI';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { useCopyImageToClipboard } from 'common/hooks/useCopyImageToClipboard';
@@ -10,13 +11,10 @@ import { iiLayerAdded } from 'features/controlLayers/store/controlLayersSlice';
 import { imagesToDeleteSelected } from 'features/deleteImageModal/store/slice';
 import { useImageActions } from 'features/gallery/hooks/useImageActions';
 import { sentImageToCanvas, sentImageToImg2Img } from 'features/gallery/store/actions';
-import { $templates } from 'features/nodes/store/nodesSlice';
 import { selectOptimalDimension } from 'features/parameters/store/generationSlice';
 import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';
-import { toast } from 'features/toast/toast';
 import { setActiveTab } from 'features/ui/store/uiSlice';
 import { useGetAndLoadEmbeddedWorkflow } from 'features/workflowLibrary/hooks/useGetAndLoadEmbeddedWorkflow';
-import { size } from 'lodash-es';
 import { memo, useCallback } from 'react';
 import { flushSync } from 'react-dom';
 import { useTranslation } from 'react-i18next';
@@ -46,10 +44,10 @@ const SingleSelectionMenuItems = (props: SingleSelectionMenuItemsProps) => {
   const optimalDimension = useAppSelector(selectOptimalDimension);
   const dispatch = useAppDispatch();
   const { t } = useTranslation();
+  const toaster = useAppToaster();
   const isCanvasEnabled = useFeatureStatus('canvas');
   const customStarUi = useStore($customStarUI);
   const { downloadImage } = useDownloadImage();
-  const templates = useStore($templates);
 
   const { recallAll, remix, recallSeed, recallPrompts, hasMetadata, hasSeed, hasPrompts, isLoadingMetadata } =
     useImageActions(imageDTO?.image_name);
@@ -85,12 +83,13 @@ const SingleSelectionMenuItems = (props: SingleSelectionMenuItemsProps) => {
     });
     dispatch(setInitialCanvasImage(imageDTO, optimalDimension));
 
-    toast({
-      id: 'SENT_TO_CANVAS',
+    toaster({
       title: t('toast.sentToUnifiedCanvas'),
       status: 'success',
+      duration: 2500,
+      isClosable: true,
     });
-  }, [dispatch, imageDTO, t, optimalDimension]);
+  }, [dispatch, imageDTO, t, toaster, optimalDimension]);
 
   const handleChangeBoard = useCallback(() => {
     dispatch(imagesToChangeSelected([imageDTO]));
@@ -134,7 +133,7 @@ const SingleSelectionMenuItems = (props: SingleSelectionMenuItemsProps) => {
       <MenuItem
         icon={getAndLoadEmbeddedWorkflowResult.isLoading ? <SpinnerIcon /> : <PiFlowArrowBold />}
         onClickCapture={handleLoadWorkflow}
-        isDisabled={!imageDTO.has_workflow || !size(templates)}
+        isDisabled={!imageDTO.has_workflow}
       >
         {t('nodes.loadWorkflow')}
       </MenuItem>

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

@@ -1,34 +0,0 @@
-import { IAINoContentFallback } from 'common/components/IAIImageFallback';
-import { memo, useMemo } from 'react';
-import { useTranslation } from 'react-i18next';
-import { useDebouncedImageWorkflow } from 'services/api/hooks/useDebouncedImageWorkflow';
-import type { ImageDTO } from 'services/api/types';
-
-import DataViewer from './DataViewer';
-
-type Props = {
-  image: ImageDTO;
-};
-
-const ImageMetadataGraphTabContent = ({ image }: Props) => {
-  const { t } = useTranslation();
-  const { currentData } = useDebouncedImageWorkflow(image);
-  const graph = useMemo(() => {
-    if (currentData?.graph) {
-      try {
-        return JSON.parse(currentData.graph);
-      } catch {
-        return null;
-      }
-    }
-    return null;
-  }, [currentData]);
-
-  if (!graph) {
-    return <IAINoContentFallback label={t('nodes.noGraph')} />;
-  }
-
-  return <DataViewer data={graph} label={t('nodes.graph')} />;
-};
-
-export default memo(ImageMetadataGraphTabContent);

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

@@ -1,7 +1,6 @@
 import { ExternalLink, Flex, Tab, TabList, TabPanel, TabPanels, Tabs, Text } from '@invoke-ai/ui-library';
 import { IAINoContentFallback } from 'common/components/IAIImageFallback';
 import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
-import ImageMetadataGraphTabContent from 'features/gallery/components/ImageMetadataViewer/ImageMetadataGraphTabContent';
 import { useMetadataItem } from 'features/metadata/hooks/useMetadataItem';
 import { handlers } from 'features/metadata/util/handlers';
 import { memo } from 'react';
@@ -53,7 +52,6 @@ const ImageMetadataViewer = ({ image }: ImageMetadataViewerProps) => {
           <Tab>{t('metadata.metadata')}</Tab>
           <Tab>{t('metadata.imageDetails')}</Tab>
           <Tab>{t('metadata.workflow')}</Tab>
-          <Tab>{t('nodes.graph')}</Tab>
         </TabList>
 
         <TabPanels>
@@ -83,9 +81,6 @@ const ImageMetadataViewer = ({ image }: ImageMetadataViewerProps) => {
           <TabPanel>
             <ImageMetadataWorkflowTabContent image={image} />
           </TabPanel>
-          <TabPanel>
-            <ImageMetadataGraphTabContent image={image} />
-          </TabPanel>
         </TabPanels>
       </Tabs>
     </Flex>

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

@@ -1,5 +1,5 @@
 import { IAINoContentFallback } from 'common/components/IAIImageFallback';
-import { memo, useMemo } from 'react';
+import { memo } from 'react';
 import { useTranslation } from 'react-i18next';
 import { useDebouncedImageWorkflow } from 'services/api/hooks/useDebouncedImageWorkflow';
 import type { ImageDTO } from 'services/api/types';
@@ -12,17 +12,7 @@ type Props = {
 
 const ImageMetadataWorkflowTabContent = ({ image }: Props) => {
   const { t } = useTranslation();
-  const { currentData } = useDebouncedImageWorkflow(image);
-  const workflow = useMemo(() => {
-    if (currentData?.workflow) {
-      try {
-        return JSON.parse(currentData.workflow);
-      } catch {
-        return null;
-      }
-    }
-    return null;
-  }, [currentData]);
+  const { workflow } = useDebouncedImageWorkflow(image);
 
   if (!workflow) {
     return <IAINoContentFallback label={t('nodes.noWorkflow')} />;

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

@@ -1,5 +1,4 @@
 import { ButtonGroup, IconButton, Menu, MenuButton, MenuList } from '@invoke-ai/ui-library';
-import { useStore } from '@nanostores/react';
 import { createSelector } from '@reduxjs/toolkit';
 import { skipToken } from '@reduxjs/toolkit/query';
 import { upscaleRequested } from 'app/store/middleware/listenerMiddleware/listeners/upscaleRequested';
@@ -13,14 +12,12 @@ import { sentImageToImg2Img } from 'features/gallery/store/actions';
 import { selectLastSelectedImage } from 'features/gallery/store/gallerySelectors';
 import { selectGallerySlice } from 'features/gallery/store/gallerySlice';
 import { parseAndRecallImageDimensions } from 'features/metadata/util/handlers';
-import { $templates } from 'features/nodes/store/nodesSlice';
 import ParamUpscalePopover from 'features/parameters/components/Upscale/ParamUpscaleSettings';
 import { useIsQueueMutationInProgress } from 'features/queue/hooks/useIsQueueMutationInProgress';
 import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';
 import { selectSystemSlice } from 'features/system/store/systemSlice';
 import { setActiveTab } from 'features/ui/store/uiSlice';
 import { useGetAndLoadEmbeddedWorkflow } from 'features/workflowLibrary/hooks/useGetAndLoadEmbeddedWorkflow';
-import { size } from 'lodash-es';
 import { memo, useCallback } from 'react';
 import { useHotkeys } from 'react-hotkeys-hook';
 import { useTranslation } from 'react-i18next';
@@ -51,7 +48,7 @@ const CurrentImageButtons = () => {
   const lastSelectedImage = useAppSelector(selectLastSelectedImage);
   const selection = useAppSelector((s) => s.gallery.selection);
   const shouldDisableToolbarButtons = useAppSelector(selectShouldDisableToolbarButtons);
-  const templates = useStore($templates);
+
   const isUpscalingEnabled = useFeatureStatus('upscaling');
   const isQueueMutationInProgress = useIsQueueMutationInProgress();
   const { t } = useTranslation();
@@ -146,7 +143,7 @@ const CurrentImageButtons = () => {
           icon={<PiFlowArrowBold />}
           tooltip={`${t('nodes.loadWorkflow')} (W)`}
           aria-label={`${t('nodes.loadWorkflow')} (W)`}
-          isDisabled={!imageDTO?.has_workflow || !size(templates)}
+          isDisabled={!imageDTO?.has_workflow}
           onClick={handleLoadWorkflow}
           isLoading={getAndLoadEmbeddedWorkflowResult.isLoading}
         />

invokeai/frontend/web/src/features/gallery/components/ImageViewer/ToggleMetadataViewerButton.tsx

@@ -1,5 +1,6 @@
 import { IconButton } from '@invoke-ai/ui-library';
 import { skipToken } from '@reduxjs/toolkit/query';
+import { useAppToaster } from 'app/components/Toaster';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { selectLastSelectedImage } from 'features/gallery/store/gallerySelectors';
 import { setShouldShowImageDetails } from 'features/ui/store/uiSlice';
@@ -13,6 +14,7 @@ export const ToggleMetadataViewerButton = memo(() => {
   const dispatch = useAppDispatch();
   const shouldShowImageDetails = useAppSelector((s) => s.ui.shouldShowImageDetails);
   const lastSelectedImage = useAppSelector(selectLastSelectedImage);
+  const toaster = useAppToaster();
   const { t } = useTranslation();
 
   const { currentData: imageDTO } = useGetImageDTOQuery(lastSelectedImage?.image_name ?? skipToken);
@@ -22,7 +24,7 @@ export const ToggleMetadataViewerButton = memo(() => {
     [dispatch, shouldShowImageDetails]
   );
 
-  useHotkeys('i', toggleMetadataViewer, { enabled: Boolean(imageDTO) }, [imageDTO, shouldShowImageDetails]);
+  useHotkeys('i', toggleMetadataViewer, { enabled: Boolean(imageDTO) }, [imageDTO, shouldShowImageDetails, toaster]);
 
   return (
     <IconButton

invokeai/frontend/web/src/features/gallery/hooks/useImageActions.ts

@@ -53,7 +53,7 @@ export const useImageActions = (image_name?: string) => {
 
   const recallSeed = useCallback(() => {
     handlers.seed.parse(metadata).then((seed) => {
-      handlers.seed.recall && handlers.seed.recall(seed, true);
+      handlers.seed.recall && handlers.seed.recall(seed);
     });
   }, [metadata]);
 

invokeai/frontend/web/src/features/metadata/util/handlers.ts

@@ -1,4 +1,5 @@
 import { objectKeys } from 'common/util/objectKeys';
+import { toast } from 'common/util/toast';
 import type { Layer } from 'features/controlLayers/store/types';
 import type { LoRA } from 'features/lora/store/loraSlice';
 import type {
@@ -14,7 +15,6 @@ import type {
 import { fetchModelConfig } from 'features/metadata/util/modelFetchingHelpers';
 import { validators } from 'features/metadata/util/validators';
 import type { ModelIdentifierField } from 'features/nodes/types/common';
-import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { assert } from 'tsafe';
 
@@ -89,23 +89,23 @@ const renderLayersValue: MetadataRenderValueFunc<Layer[]> = async (layers) => {
   return `${layers.length} ${t('controlLayers.layers', { count: layers.length })}`;
 };
 
-const parameterSetToast = (parameter: string) => {
+const parameterSetToast = (parameter: string, description?: string) => {
   toast({
-    id: 'PARAMETER_SET',
-    title: t('toast.parameterSet'),
-    description: t('toast.parameterSetDesc', { parameter }),
+    title: t('toast.parameterSet', { parameter }),
+    description,
     status: 'info',
+    duration: 2500,
+    isClosable: true,
   });
 };
 
-const parameterNotSetToast = (parameter: string, message?: string) => {
+const parameterNotSetToast = (parameter: string, description?: string) => {
   toast({
-    id: 'PARAMETER_NOT_SET',
-    title: t('toast.parameterNotSet'),
-    description: message
-      ? t('toast.parameterNotSetDescWithMessage', { parameter, message })
-      : t('toast.parameterNotSetDesc', { parameter }),
+    title: t('toast.parameterNotSet', { parameter }),
+    description,
     status: 'warning',
+    duration: 2500,
+    isClosable: true,
   });
 };
 
@@ -458,18 +458,7 @@ export const parseAndRecallAllMetadata = async (
         });
       })
   );
-
   if (results.some((result) => result.status === 'fulfilled')) {
-    toast({
-      id: 'PARAMETER_SET',
-      title: t('toast.parametersSet'),
-      status: 'info',
-    });
-  } else {
-    toast({
-      id: 'PARAMETER_SET',
-      title: t('toast.parametersNotSet'),
-      status: 'warning',
-    });
+    parameterSetToast(t('toast.parameters'));
   }
 };

invokeai/frontend/web/src/features/modelManagerV2/hooks/useInstallModel.ts

@@ -1,48 +0,0 @@
-import { toast } from 'features/toast/toast';
-import { useCallback } from 'react';
-import { useTranslation } from 'react-i18next';
-import { useInstallModelMutation } from 'services/api/endpoints/models';
-
-type InstallModelArg = {
-  source: string;
-  inplace?: boolean;
-  onSuccess?: () => void;
-  onError?: (error: unknown) => void;
-};
-
-export const useInstallModel = () => {
-  const { t } = useTranslation();
-  const [_installModel, request] = useInstallModelMutation();
-
-  const installModel = useCallback(
-    ({ source, inplace, onSuccess, onError }: InstallModelArg) => {
-      _installModel({ source, inplace })
-        .unwrap()
-        .then((_) => {
-          if (onSuccess) {
-            onSuccess();
-          }
-          toast({
-            id: 'MODEL_INSTALL_QUEUED',
-            title: t('toast.modelAddedSimple'),
-            status: 'success',
-          });
-        })
-        .catch((error) => {
-          if (onError) {
-            onError(error);
-          }
-          if (error) {
-            toast({
-              id: 'MODEL_INSTALL_QUEUE_FAILED',
-              title: `${error.data.detail} `,
-              status: 'error',
-            });
-          }
-        });
-    },
-    [_installModel, t]
-  );
-
-  return [installModel, request] as const;
-};

invokeai/frontend/web/src/features/modelManagerV2/hooks/useStarterModelsToast.tsx

@@ -17,11 +17,7 @@ export const useStarterModelsToast = () => {
 
   useEffect(() => {
     if (toast.isActive(TOAST_ID)) {
-      if (mainModels.length === 0) {
-        return;
-      } else {
-        toast.close(TOAST_ID);
-      }
+      return;
     }
     if (data && mainModels.length === 0 && !didToast && isEnabled) {
       toast({

invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/HuggingFaceFolder/HuggingFaceForm.tsx

@@ -1,9 +1,11 @@
 import { Button, Flex, FormControl, FormErrorMessage, FormHelperText, FormLabel, Input } from '@invoke-ai/ui-library';
-import { useInstallModel } from 'features/modelManagerV2/hooks/useInstallModel';
+import { useAppDispatch } from 'app/store/storeHooks';
+import { addToast } from 'features/system/store/systemSlice';
+import { makeToast } from 'features/system/util/makeToast';
 import type { ChangeEventHandler } from 'react';
 import { useCallback, useState } from 'react';
 import { useTranslation } from 'react-i18next';
-import { useLazyGetHuggingFaceModelsQuery } from 'services/api/endpoints/models';
+import { useInstallModelMutation, useLazyGetHuggingFaceModelsQuery } from 'services/api/endpoints/models';
 
 import { HuggingFaceResults } from './HuggingFaceResults';
 
@@ -12,19 +14,50 @@ export const HuggingFaceForm = () => {
   const [displayResults, setDisplayResults] = useState(false);
   const [errorMessage, setErrorMessage] = useState('');
   const { t } = useTranslation();
+  const dispatch = useAppDispatch();
 
   const [_getHuggingFaceModels, { isLoading, data }] = useLazyGetHuggingFaceModelsQuery();
-  const [installModel] = useInstallModel();
+  const [installModel] = useInstallModelMutation();
+
+  const handleInstallModel = useCallback(
+    (source: string) => {
+      installModel({ source })
+        .unwrap()
+        .then((_) => {
+          dispatch(
+            addToast(
+              makeToast({
+                title: t('toast.modelAddedSimple'),
+                status: 'success',
+              })
+            )
+          );
+        })
+        .catch((error) => {
+          if (error) {
+            dispatch(
+              addToast(
+                makeToast({
+                  title: `${error.data.detail} `,
+                  status: 'error',
+                })
+              )
+            );
+          }
+        });
+    },
+    [installModel, dispatch, t]
+  );
 
   const getModels = useCallback(async () => {
     _getHuggingFaceModels(huggingFaceRepo)
       .unwrap()
       .then((response) => {
         if (response.is_diffusers) {
-          installModel({ source: huggingFaceRepo });
+          handleInstallModel(huggingFaceRepo);
           setDisplayResults(false);
         } else if (response.urls?.length === 1 && response.urls[0]) {
-          installModel({ source: response.urls[0] });
+          handleInstallModel(response.urls[0]);
           setDisplayResults(false);
         } else {
           setDisplayResults(true);
@@ -33,7 +66,7 @@ export const HuggingFaceForm = () => {
       .catch((error) => {
         setErrorMessage(error.data.detail || '');
       });
-  }, [_getHuggingFaceModels, installModel, huggingFaceRepo]);
+  }, [_getHuggingFaceModels, handleInstallModel, huggingFaceRepo]);
 
   const handleSetHuggingFaceRepo: ChangeEventHandler<HTMLInputElement> = useCallback((e) => {
     setHuggingFaceRepo(e.target.value);

invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/HuggingFaceFolder/HuggingFaceResultItem.tsx

@@ -1,20 +1,47 @@
 import { Flex, IconButton, Text } from '@invoke-ai/ui-library';
-import { useInstallModel } from 'features/modelManagerV2/hooks/useInstallModel';
+import { useAppDispatch } from 'app/store/storeHooks';
+import { addToast } from 'features/system/store/systemSlice';
+import { makeToast } from 'features/system/util/makeToast';
 import { useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 import { PiPlusBold } from 'react-icons/pi';
+import { useInstallModelMutation } from 'services/api/endpoints/models';
 
 type Props = {
   result: string;
 };
 export const HuggingFaceResultItem = ({ result }: Props) => {
   const { t } = useTranslation();
+  const dispatch = useAppDispatch();
 
-  const [installModel] = useInstallModel();
+  const [installModel] = useInstallModelMutation();
 
-  const onClick = useCallback(() => {
-    installModel({ source: result });
-  }, [installModel, result]);
+  const handleInstall = useCallback(() => {
+    installModel({ source: result })
+      .unwrap()
+      .then((_) => {
+        dispatch(
+          addToast(
+            makeToast({
+              title: t('toast.modelAddedSimple'),
+              status: 'success',
+            })
+          )
+        );
+      })
+      .catch((error) => {
+        if (error) {
+          dispatch(
+            addToast(
+              makeToast({
+                title: `${error.data.detail} `,
+                status: 'error',
+              })
+            )
+          );
+        }
+      });
+  }, [installModel, result, dispatch, t]);
 
   return (
     <Flex alignItems="center" justifyContent="space-between" w="100%" gap={3}>
@@ -24,7 +51,7 @@ export const HuggingFaceResultItem = ({ result }: Props) => {
           {result}
         </Text>
       </Flex>
-      <IconButton aria-label={t('modelManager.install')} icon={<PiPlusBold />} onClick={onClick} size="sm" />
+      <IconButton aria-label={t('modelManager.install')} icon={<PiPlusBold />} onClick={handleInstall} size="sm" />
     </Flex>
   );
 };

invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/HuggingFaceFolder/HuggingFaceResults.tsx

@@ -8,12 +8,15 @@ import {
   InputGroup,
   InputRightElement,
 } from '@invoke-ai/ui-library';
+import { useAppDispatch } from 'app/store/storeHooks';
 import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
-import { useInstallModel } from 'features/modelManagerV2/hooks/useInstallModel';
+import { addToast } from 'features/system/store/systemSlice';
+import { makeToast } from 'features/system/util/makeToast';
 import type { ChangeEventHandler } from 'react';
 import { useCallback, useMemo, useState } from 'react';
 import { useTranslation } from 'react-i18next';
 import { PiXBold } from 'react-icons/pi';
+import { useInstallModelMutation } from 'services/api/endpoints/models';
 
 import { HuggingFaceResultItem } from './HuggingFaceResultItem';
 
@@ -24,8 +27,9 @@ type HuggingFaceResultsProps = {
 export const HuggingFaceResults = ({ results }: HuggingFaceResultsProps) => {
   const { t } = useTranslation();
   const [searchTerm, setSearchTerm] = useState('');
+  const dispatch = useAppDispatch();
 
-  const [installModel] = useInstallModel();
+  const [installModel] = useInstallModelMutation();
 
   const filteredResults = useMemo(() => {
     return results.filter((result) => {
@@ -42,11 +46,34 @@ export const HuggingFaceResults = ({ results }: HuggingFaceResultsProps) => {
     setSearchTerm('');
   }, []);
 
-  const onClickAddAll = useCallback(() => {
+  const handleAddAll = useCallback(() => {
     for (const result of filteredResults) {
-      installModel({ source: result });
+      installModel({ source: result })
+        .unwrap()
+        .then((_) => {
+          dispatch(
+            addToast(
+              makeToast({
+                title: t('toast.modelAddedSimple'),
+                status: 'success',
+              })
+            )
+          );
+        })
+        .catch((error) => {
+          if (error) {
+            dispatch(
+              addToast(
+                makeToast({
+                  title: `${error.data.detail} `,
+                  status: 'error',
+                })
+              )
+            );
+          }
+        });
     }
-  }, [filteredResults, installModel]);
+  }, [filteredResults, installModel, dispatch, t]);
 
   return (
     <>
@@ -55,7 +82,7 @@ export const HuggingFaceResults = ({ results }: HuggingFaceResultsProps) => {
         <Flex justifyContent="space-between" alignItems="center">
           <Heading size="sm">{t('modelManager.availableModels')}</Heading>
           <Flex alignItems="center" gap={3}>
-            <Button size="sm" onClick={onClickAddAll} isDisabled={results.length === 0} flexShrink={0}>
+            <Button size="sm" onClick={handleAddAll} isDisabled={results.length === 0} flexShrink={0}>
               {t('modelManager.installAll')}
             </Button>
             <InputGroup w={64} size="xs">

invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/InstallModelForm.tsx

@@ -1,9 +1,12 @@
 import { Button, Checkbox, Flex, FormControl, FormHelperText, FormLabel, Input } from '@invoke-ai/ui-library';
-import { useInstallModel } from 'features/modelManagerV2/hooks/useInstallModel';
+import { useAppDispatch } from 'app/store/storeHooks';
+import { addToast } from 'features/system/store/systemSlice';
+import { makeToast } from 'features/system/util/makeToast';
 import { t } from 'i18next';
 import { useCallback } from 'react';
 import type { SubmitHandler } from 'react-hook-form';
 import { useForm } from 'react-hook-form';
+import { useInstallModelMutation } from 'services/api/endpoints/models';
 
 type SimpleImportModelConfig = {
   location: string;
@@ -11,7 +14,9 @@ type SimpleImportModelConfig = {
 };
 
 export const InstallModelForm = () => {
-  const [installModel, { isLoading }] = useInstallModel();
+  const dispatch = useAppDispatch();
+
+  const [installModel, { isLoading }] = useInstallModelMutation();
 
   const { register, handleSubmit, formState, reset } = useForm<SimpleImportModelConfig>({
     defaultValues: {
@@ -21,22 +26,40 @@ export const InstallModelForm = () => {
     mode: 'onChange',
   });
 
-  const resetForm = useCallback(() => reset(undefined, { keepValues: true }), [reset]);
-
   const onSubmit = useCallback<SubmitHandler<SimpleImportModelConfig>>(
     (values) => {
       if (!values?.location) {
         return;
       }
 
-      installModel({
-        source: values.location,
-        inplace: values.inplace,
-        onSuccess: resetForm,
-        onError: resetForm,
-      });
+      installModel({ source: values.location, inplace: values.inplace })
+        .unwrap()
+        .then((_) => {
+          dispatch(
+            addToast(
+              makeToast({
+                title: t('toast.modelAddedSimple'),
+                status: 'success',
+              })
+            )
+          );
+          reset(undefined, { keepValues: true });
+        })
+        .catch((error) => {
+          reset(undefined, { keepValues: true });
+          if (error) {
+            dispatch(
+              addToast(
+                makeToast({
+                  title: `${error.data.detail} `,
+                  status: 'error',
+                })
+              )
+            );
+          }
+        });
     },
-    [installModel, resetForm]
+    [dispatch, reset, installModel]
   );
 
   return (

invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ModelInstallQueue/ModelInstallQueue.tsx

@@ -1,6 +1,8 @@
 import { Box, Button, Flex, Heading } from '@invoke-ai/ui-library';
+import { useAppDispatch } from 'app/store/storeHooks';
 import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
-import { toast } from 'features/toast/toast';
+import { addToast } from 'features/system/store/systemSlice';
+import { makeToast } from 'features/system/util/makeToast';
 import { t } from 'i18next';
 import { useCallback, useMemo } from 'react';
 import { useListModelInstallsQuery, usePruneCompletedModelInstallsMutation } from 'services/api/endpoints/models';
@@ -8,6 +10,8 @@ import { useListModelInstallsQuery, usePruneCompletedModelInstallsMutation } fro
 import { ModelInstallQueueItem } from './ModelInstallQueueItem';
 
 export const ModelInstallQueue = () => {
+  const dispatch = useAppDispatch();
+
   const { data } = useListModelInstallsQuery();
 
   const [_pruneCompletedModelInstalls] = usePruneCompletedModelInstallsMutation();
@@ -16,22 +20,28 @@ export const ModelInstallQueue = () => {
     _pruneCompletedModelInstalls()
       .unwrap()
       .then((_) => {
-        toast({
-          id: 'MODEL_INSTALL_QUEUE_PRUNED',
-          title: t('toast.prunedQueue'),
-          status: 'success',
-        });
+        dispatch(
+          addToast(
+            makeToast({
+              title: t('toast.prunedQueue'),
+              status: 'success',
+            })
+          )
+        );
       })
       .catch((error) => {
         if (error) {
-          toast({
-            id: 'MODEL_INSTALL_QUEUE_PRUNE_FAILED',
-            title: `${error.data.detail} `,
-            status: 'error',
-          });
+          dispatch(
+            addToast(
+              makeToast({
+                title: `${error.data.detail} `,
+                status: 'error',
+              })
+            )
+          );
         }
       });
-  }, [_pruneCompletedModelInstalls]);
+  }, [_pruneCompletedModelInstalls, dispatch]);
 
   const pruneAvailable = useMemo(() => {
     return data?.some(

invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ModelInstallQueue/ModelInstallQueueItem.tsx

@@ -1,5 +1,7 @@
 import { Flex, IconButton, Progress, Text, Tooltip } from '@invoke-ai/ui-library';
-import { toast } from 'features/toast/toast';
+import { useAppDispatch } from 'app/store/storeHooks';
+import { addToast } from 'features/system/store/systemSlice';
+import { makeToast } from 'features/system/util/makeToast';
 import { t } from 'i18next';
 import { isNil } from 'lodash-es';
 import { useCallback, useMemo } from 'react';
@@ -27,6 +29,7 @@ const formatBytes = (bytes: number) => {
 
 export const ModelInstallQueueItem = (props: ModelListItemProps) => {
   const { installJob } = props;
+  const dispatch = useAppDispatch();
 
   const [deleteImportModel] = useCancelModelInstallMutation();
 
@@ -34,22 +37,28 @@ export const ModelInstallQueueItem = (props: ModelListItemProps) => {
     deleteImportModel(installJob.id)
       .unwrap()
       .then((_) => {
-        toast({
-          id: 'MODEL_INSTALL_CANCELED',
-          title: t('toast.modelImportCanceled'),
-          status: 'success',
-        });
+        dispatch(
+          addToast(
+            makeToast({
+              title: t('toast.modelImportCanceled'),
+              status: 'success',
+            })
+          )
+        );
       })
       .catch((error) => {
         if (error) {
-          toast({
-            id: 'MODEL_INSTALL_CANCEL_FAILED',
-            title: `${error.data.detail} `,
-            status: 'error',
-          });
+          dispatch(
+            addToast(
+              makeToast({
+                title: `${error.data.detail} `,
+                status: 'error',
+              })
+            )
+          );
         }
       });
-  }, [deleteImportModel, installJob]);
+  }, [deleteImportModel, installJob, dispatch]);
 
   const sourceLocation = useMemo(() => {
     switch (installJob.source.type) {

invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanFolder/ScanFolderResults.tsx

@@ -11,13 +11,15 @@ import {
   InputGroup,
   InputRightElement,
 } from '@invoke-ai/ui-library';
+import { useAppDispatch } from 'app/store/storeHooks';
 import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
-import { useInstallModel } from 'features/modelManagerV2/hooks/useInstallModel';
+import { addToast } from 'features/system/store/systemSlice';
+import { makeToast } from 'features/system/util/makeToast';
 import type { ChangeEvent, ChangeEventHandler } from 'react';
 import { useCallback, useMemo, useState } from 'react';
 import { useTranslation } from 'react-i18next';
 import { PiXBold } from 'react-icons/pi';
-import type { ScanFolderResponse } from 'services/api/endpoints/models';
+import { type ScanFolderResponse, useInstallModelMutation } from 'services/api/endpoints/models';
 
 import { ScanModelResultItem } from './ScanFolderResultItem';
 
@@ -28,8 +30,9 @@ type ScanModelResultsProps = {
 export const ScanModelsResults = ({ results }: ScanModelResultsProps) => {
   const { t } = useTranslation();
   const [searchTerm, setSearchTerm] = useState('');
+  const dispatch = useAppDispatch();
   const [inplace, setInplace] = useState(true);
-  const [installModel] = useInstallModel();
+  const [installModel] = useInstallModelMutation();
 
   const filteredResults = useMemo(() => {
     return results.filter((result) => {
@@ -55,15 +58,61 @@ export const ScanModelsResults = ({ results }: ScanModelResultsProps) => {
       if (result.is_installed) {
         continue;
       }
-      installModel({ source: result.path, inplace });
+      installModel({ source: result.path, inplace })
+        .unwrap()
+        .then((_) => {
+          dispatch(
+            addToast(
+              makeToast({
+                title: t('toast.modelAddedSimple'),
+                status: 'success',
+              })
+            )
+          );
+        })
+        .catch((error) => {
+          if (error) {
+            dispatch(
+              addToast(
+                makeToast({
+                  title: `${error.data.detail} `,
+                  status: 'error',
+                })
+              )
+            );
+          }
+        });
     }
-  }, [filteredResults, installModel, inplace]);
+  }, [filteredResults, installModel, inplace, dispatch, t]);
 
   const handleInstallOne = useCallback(
     (source: string) => {
-      installModel({ source, inplace });
+      installModel({ source, inplace })
+        .unwrap()
+        .then((_) => {
+          dispatch(
+            addToast(
+              makeToast({
+                title: t('toast.modelAddedSimple'),
+                status: 'success',
+              })
+            )
+          );
+        })
+        .catch((error) => {
+          if (error) {
+            dispatch(
+              addToast(
+                makeToast({
+                  title: `${error.data.detail} `,
+                  status: 'error',
+                })
+              )
+            );
+          }
+        });
     },
-    [installModel, inplace]
+    [installModel, inplace, dispatch, t]
   );
 
   return (

invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/StarterModels/StartModelsResultItem.tsx

@@ -1,16 +1,20 @@
 import { Badge, Box, Flex, IconButton, Text } from '@invoke-ai/ui-library';
-import { useInstallModel } from 'features/modelManagerV2/hooks/useInstallModel';
+import { useAppDispatch } from 'app/store/storeHooks';
 import ModelBaseBadge from 'features/modelManagerV2/subpanels/ModelManagerPanel/ModelBaseBadge';
+import { addToast } from 'features/system/store/systemSlice';
+import { makeToast } from 'features/system/util/makeToast';
 import { useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
 import { PiPlusBold } from 'react-icons/pi';
 import type { GetStarterModelsResponse } from 'services/api/endpoints/models';
+import { useInstallModelMutation } from 'services/api/endpoints/models';
 
 type Props = {
   result: GetStarterModelsResponse[number];
 };
 export const StarterModelsResultItem = ({ result }: Props) => {
   const { t } = useTranslation();
+  const dispatch = useAppDispatch();
   const allSources = useMemo(() => {
     const _allSources = [result.source];
     if (result.dependencies) {
@@ -18,13 +22,36 @@ export const StarterModelsResultItem = ({ result }: Props) => {
     }
     return _allSources;
   }, [result]);
-  const [installModel] = useInstallModel();
+  const [installModel] = useInstallModelMutation();
 
-  const onClick = useCallback(() => {
+  const handleQuickAdd = useCallback(() => {
     for (const source of allSources) {
-      installModel({ source });
+      installModel({ source })
+        .unwrap()
+        .then((_) => {
+          dispatch(
+            addToast(
+              makeToast({
+                title: t('toast.modelAddedSimple'),
+                status: 'success',
+              })
+            )
+          );
+        })
+        .catch((error) => {
+          if (error) {
+            dispatch(
+              addToast(
+                makeToast({
+                  title: `${error.data.detail} `,
+                  status: 'error',
+                })
+              )
+            );
+          }
+        });
     }
-  }, [allSources, installModel]);
+  }, [allSources, installModel, dispatch, t]);
 
   return (
     <Flex alignItems="center" justifyContent="space-between" w="100%" gap={3}>
@@ -40,7 +67,7 @@ export const StarterModelsResultItem = ({ result }: Props) => {
         {result.is_installed ? (
           <Badge>{t('common.installed')}</Badge>
         ) : (
-          <IconButton aria-label={t('modelManager.install')} icon={<PiPlusBold />} onClick={onClick} size="sm" />
+          <IconButton aria-label={t('modelManager.install')} icon={<PiPlusBold />} onClick={handleQuickAdd} size="sm" />
         )}
       </Box>
     </Flex>

invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelListItem.tsx

@@ -4,7 +4,8 @@ import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { setSelectedModelKey } from 'features/modelManagerV2/store/modelManagerV2Slice';
 import ModelBaseBadge from 'features/modelManagerV2/subpanels/ModelManagerPanel/ModelBaseBadge';
 import ModelFormatBadge from 'features/modelManagerV2/subpanels/ModelManagerPanel/ModelFormatBadge';
-import { toast } from 'features/toast/toast';
+import { addToast } from 'features/system/store/systemSlice';
+import { makeToast } from 'features/system/util/makeToast';
 import type { MouseEvent } from 'react';
 import { memo, useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
@@ -52,19 +53,25 @@ const ModelListItem = (props: ModelListItemProps) => {
     deleteModel({ key: model.key })
       .unwrap()
       .then((_) => {
-        toast({
-          id: 'MODEL_DELETED',
-          title: `${t('modelManager.modelDeleted')}: ${model.name}`,
-          status: 'success',
-        });
+        dispatch(
+          addToast(
+            makeToast({
+              title: `${t('modelManager.modelDeleted')}: ${model.name}`,
+              status: 'success',
+            })
+          )
+        );
       })
       .catch((error) => {
         if (error) {
-          toast({
-            id: 'MODEL_DELETE_FAILED',
-            title: `${t('modelManager.modelDeleteFailed')}: ${model.name}`,
-            status: 'error',
-          });
+          dispatch(
+            addToast(
+              makeToast({
+                title: `${t('modelManager.modelDeleteFailed')}: ${model.name}`,
+                status: 'error',
+              })
+            )
+          );
         }
       });
     dispatch(setSelectedModelKey(null));

invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ControlNetOrT2IAdapterDefaultSettings/ControlNetOrT2IAdapterDefaultSettings.tsx

@@ -1,9 +1,10 @@
 import { Button, Flex, Heading, SimpleGrid, Text } from '@invoke-ai/ui-library';
-import { useAppSelector } from 'app/store/storeHooks';
+import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { useControlNetOrT2IAdapterDefaultSettings } from 'features/modelManagerV2/hooks/useControlNetOrT2IAdapterDefaultSettings';
 import { DefaultPreprocessor } from 'features/modelManagerV2/subpanels/ModelPanel/ControlNetOrT2IAdapterDefaultSettings/DefaultPreprocessor';
 import type { FormField } from 'features/modelManagerV2/subpanels/ModelPanel/MainModelDefaultSettings/MainModelDefaultSettings';
-import { toast } from 'features/toast/toast';
+import { addToast } from 'features/system/store/systemSlice';
+import { makeToast } from 'features/system/util/makeToast';
 import { useCallback } from 'react';
 import type { SubmitHandler } from 'react-hook-form';
 import { useForm } from 'react-hook-form';
@@ -18,6 +19,7 @@ export type ControlNetOrT2IAdapterDefaultSettingsFormData = {
 export const ControlNetOrT2IAdapterDefaultSettings = () => {
   const selectedModelKey = useAppSelector((s) => s.modelmanagerV2.selectedModelKey);
   const { t } = useTranslation();
+  const dispatch = useAppDispatch();
 
   const { defaultSettingsDefaults, isLoading: isLoadingDefaultSettings } =
     useControlNetOrT2IAdapterDefaultSettings(selectedModelKey);
@@ -44,24 +46,30 @@ export const ControlNetOrT2IAdapterDefaultSettings = () => {
       })
         .unwrap()
         .then((_) => {
-          toast({
-            id: 'DEFAULT_SETTINGS_SAVED',
-            title: t('modelManager.defaultSettingsSaved'),
-            status: 'success',
-          });
+          dispatch(
+            addToast(
+              makeToast({
+                title: t('modelManager.defaultSettingsSaved'),
+                status: 'success',
+              })
+            )
+          );
           reset(data);
         })
         .catch((error) => {
           if (error) {
-            toast({
-              id: 'DEFAULT_SETTINGS_SAVE_FAILED',
-              title: `${error.data.detail} `,
-              status: 'error',
-            });
+            dispatch(
+              addToast(
+                makeToast({
+                  title: `${error.data.detail} `,
+                  status: 'error',
+                })
+              )
+            );
           }
         });
     },
-    [selectedModelKey, reset, updateModel, t]
+    [selectedModelKey, dispatch, reset, updateModel, t]
   );
 
   if (isLoadingDefaultSettings) {

invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Fields/ModelImageUpload.tsx

@@ -1,6 +1,8 @@
 import { Box, Button, Flex, Icon, IconButton, Image, Tooltip } from '@invoke-ai/ui-library';
+import { useAppDispatch } from 'app/store/storeHooks';
 import { typedMemo } from 'common/util/typedMemo';
-import { toast } from 'features/toast/toast';
+import { addToast } from 'features/system/store/systemSlice';
+import { makeToast } from 'features/system/util/makeToast';
 import { useCallback, useState } from 'react';
 import { useDropzone } from 'react-dropzone';
 import { useTranslation } from 'react-i18next';
@@ -13,6 +15,7 @@ type Props = {
 };
 
 const ModelImageUpload = ({ model_key, model_image }: Props) => {
+  const dispatch = useAppDispatch();
   const [image, setImage] = useState<string | null>(model_image || null);
   const { t } = useTranslation();
 
@@ -31,21 +34,27 @@ const ModelImageUpload = ({ model_key, model_image }: Props) => {
         .unwrap()
         .then(() => {
           setImage(URL.createObjectURL(file));
-          toast({
-            id: 'MODEL_IMAGE_UPDATED',
-            title: t('modelManager.modelImageUpdated'),
-            status: 'success',
-          });
+          dispatch(
+            addToast(
+              makeToast({
+                title: t('modelManager.modelImageUpdated'),
+                status: 'success',
+              })
+            )
+          );
         })
-        .catch(() => {
-          toast({
-            id: 'MODEL_IMAGE_UPDATE_FAILED',
-            title: t('modelManager.modelImageUpdateFailed'),
-            status: 'error',
-          });
+        .catch((_) => {
+          dispatch(
+            addToast(
+              makeToast({
+                title: t('modelManager.modelImageUpdateFailed'),
+                status: 'error',
+              })
+            )
+          );
         });
     },
-    [model_key, t, updateModelImage]
+    [dispatch, model_key, t, updateModelImage]
   );
 
   const handleResetImage = useCallback(() => {
@@ -56,20 +65,26 @@ const ModelImageUpload = ({ model_key, model_image }: Props) => {
     deleteModelImage(model_key)
       .unwrap()
       .then(() => {
-        toast({
-          id: 'MODEL_IMAGE_DELETED',
-          title: t('modelManager.modelImageDeleted'),
-          status: 'success',
-        });
+        dispatch(
+          addToast(
+            makeToast({
+              title: t('modelManager.modelImageDeleted'),
+              status: 'success',
+            })
+          )
+        );
       })
-      .catch(() => {
-        toast({
-          id: 'MODEL_IMAGE_DELETE_FAILED',
-          title: t('modelManager.modelImageDeleteFailed'),
-          status: 'error',
-        });
+      .catch((_) => {
+        dispatch(
+          addToast(
+            makeToast({
+              title: t('modelManager.modelImageDeleteFailed'),
+              status: 'error',
+            })
+          )
+        );
       });
-  }, [model_key, t, deleteModelImage]);
+  }, [dispatch, model_key, t, deleteModelImage]);
 
   const { getInputProps, getRootProps } = useDropzone({
     accept: { 'image/png': ['.png'], 'image/jpeg': ['.jpg', '.jpeg', '.png'] },